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Modeling Risk Factors on Expected Bids in Certified Sustainable Construction

Permanent Link: http://ufdc.ufl.edu/UFE0042142/00001

Material Information

Title: Modeling Risk Factors on Expected Bids in Certified Sustainable Construction
Physical Description: 1 online resource (99 p.)
Language: english
Creator: Piela, Jeremy
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2010

Subjects

Subjects / Keywords: bidding, building, certified, certifiication, construction, cost, high, leed, location, model, modeling, performance, risk, sustainability, sustainable
Building Construction -- Dissertations, Academic -- UF
Genre: Building Construction thesis, M.S.B.C.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science in Building Construction MODELING RISK FACTORS ON EXPECTED BIDS IN CERTIFIED SUSTAINABLE CONSTRUCTION By Jeremy Piela August, 2010 Chair: James G. Sullivan Cochair: R. Raymond Issa Major: Building Construction Current research shows that a high-performance building (HPB) that is certified as such under a rating system such as the Leadership in Energy and Environmental Design (LEEDregistered trademark) building rating system developed by the United States Green Building Council (USGBC) demonstrate an increase in construction costs over the cost of traditional projects that do not pursue LEED certification (Steven Winter Associates 2004). This increase is often evident in projects that are produced by designers, builders and other involved parties that have extensive experience and education in the construction of buildings that incorporate many of the design features and construction techniques that are included in HPBs. The purpose of this study is to propose a model that examines potential cost increases over traditional buildings of similar construction. This study reviews bid strategy and risk aversion models to explain the impacts of certification level, experience, location, perceived risk, and the risk behaviors of bidding contractors on the pricing of high-performance buildings. This study proposes that this increase in costs is related to the perceived risk involved in the construction of a project that pursues green certification, the level of certification pursued, and the individual risk behaviors of the contractors that are operating in a particular bidding climate.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Jeremy Piela.
Thesis: Thesis (M.S.B.C.)--University of Florida, 2010.
Local: Adviser: Sullivan, James.
Local: Co-adviser: Issa, R. Raymond.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2011-08-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2010
System ID: UFE0042142:00001

Permanent Link: http://ufdc.ufl.edu/UFE0042142/00001

Material Information

Title: Modeling Risk Factors on Expected Bids in Certified Sustainable Construction
Physical Description: 1 online resource (99 p.)
Language: english
Creator: Piela, Jeremy
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2010

Subjects

Subjects / Keywords: bidding, building, certified, certifiication, construction, cost, high, leed, location, model, modeling, performance, risk, sustainability, sustainable
Building Construction -- Dissertations, Academic -- UF
Genre: Building Construction thesis, M.S.B.C.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science in Building Construction MODELING RISK FACTORS ON EXPECTED BIDS IN CERTIFIED SUSTAINABLE CONSTRUCTION By Jeremy Piela August, 2010 Chair: James G. Sullivan Cochair: R. Raymond Issa Major: Building Construction Current research shows that a high-performance building (HPB) that is certified as such under a rating system such as the Leadership in Energy and Environmental Design (LEEDregistered trademark) building rating system developed by the United States Green Building Council (USGBC) demonstrate an increase in construction costs over the cost of traditional projects that do not pursue LEED certification (Steven Winter Associates 2004). This increase is often evident in projects that are produced by designers, builders and other involved parties that have extensive experience and education in the construction of buildings that incorporate many of the design features and construction techniques that are included in HPBs. The purpose of this study is to propose a model that examines potential cost increases over traditional buildings of similar construction. This study reviews bid strategy and risk aversion models to explain the impacts of certification level, experience, location, perceived risk, and the risk behaviors of bidding contractors on the pricing of high-performance buildings. This study proposes that this increase in costs is related to the perceived risk involved in the construction of a project that pursues green certification, the level of certification pursued, and the individual risk behaviors of the contractors that are operating in a particular bidding climate.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Jeremy Piela.
Thesis: Thesis (M.S.B.C.)--University of Florida, 2010.
Local: Adviser: Sullivan, James.
Local: Co-adviser: Issa, R. Raymond.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2011-08-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2010
System ID: UFE0042142:00001


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MODELING RISK FACTORS ON EXPECTED BIDS IN CERTIFIED SUSTAINABLE
CONSTRUCTION


















By

JEREMY PIELA


A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE IN BUILDING CONSTRUCTION

UNIVERSITY OF FLORIDA

2010
































2010 Jeremy Piela
































To my Mom and my brother Jonathan









ACKNOWLEDGMENTS

I thank my parents, my brother Jonathan, and the rest of my family for their

continuing support of my academic ventures. Leaving a career in Connecticut and

returning to school was a very difficult decision for me, and would have been impossible

without their support. I also thank the wonderful friends that I have made at the

University of Florida who were extremely important in the success that I enjoyed in my

pursuit of the advanced degree associated with this project. I not only made lifelong

friends, but learned lessons from those friendships that are beyond value and will surely

be the key to my success in the future. I finally thank the faculty and staff of the Rinker

School of Building Construction at the University of Florida for their efforts that have

made my experience there so enjoyable.









TABLE OF CONTENTS

page

A C KNO W LEDG M ENTS ............................... .......................................... ...............

L IS T O F T A B L E S ........................ .................................................................................. 8

LIST O F FIG URES........................................... ............... 10

LIST OF ABBREVIATIONS......................................... ............... 11

A BSTRACT ........................ ............................................. 12

CHAPTER

1 INTRODUCTION ................. ................................. ............. .......... 13

B ackgro und .............................. .............. ...... 13
Problem Statem ent ... ................................ .... .. .............................. 14
R is k S tu d y ......................... .......14.......... .................

2 LITERATURE REVIEW ................................. ............... 17

G re e n B u ild in g .......... .............. ....... .......... .................. ...................................... 1 7
LEED ................ ........................................... 17
Davis Langdon 2004 ................... ............................... 19
Increased Risk ..................... ............................... 21
Cost of LEED ................................................................... 21
P roxim ity to S services ........................ ........ .......... .. ........................... 22
Bidding Clim ate and Culture................................................ .................... 23
Number of Bidders .................................................. 24
Other potential projects ................. ........................ ......... 24
Experience of bidders .................. ........................ ........... 25
Intent and V alues of the Project ........................ ................. ........ ..... 25
Climate ............................................................ 26
Tim ing of Im plem entation ........................ ................. ........... ..... ... 27
S ize of B u ild ing ............................... ............... 2 7
Point Synergies .. .................................. ............................................... 28
LE E D A associated R isk ........................................................................ ......... 28
S usta ina b le S ite s .......................................................................... ......... 2 8
Water Efficiency ..................... .............................. 29
Energy and Atmosphere............................ ............... 30
M materials and Resources............................................... .................... 31
Indoor Environmental Quality .................... ............ .......... 32
Innovation in Design............................................. ............... 33
LE E D C redits A affected ........................ ........ ......... .. ........................... 33
Risk to the Contractor .................. ................................ 34









C contracts ........................................................................................... ........ 38
Risk Analysis ....................................................................... ......... 38
External R isk ............................................................................................ ........ 39
Internal Risk .................................... ......... ................. 40
Risk Balance ..................................................................... ......... 40
L e v e ls o f R is k ................................................................. ................................. 4 1
Z ero R isk .................................................................................................. 4 1
Approval-Com pensation .................................. ...................... ... ........... 41
Utility Based Criteria ........................................................ ......... .. ...... 42
Risk Criterion ....................................................................... ......... 42
R is k F a c to rs ............................................................................................ 4 4
R is k in B id d in g ................................................................ ................................. 4 6
Risk Compensation................... .. ............................. 47
W winners C urse ................................................................... .......... 48
Risks Associated with the Winner's Curse .................................................... 50
Identifying the W inner's Curse.............................................. .................... 51
Experienced Bidders............................... ............... 52
R isk and H PB .................. ........................................... 53
Bidding M odel (Tang et al. 2006) ........................................................ ...... .... 53
M odel Factors .......................................................................................... ......... 54

3 METHODOLOGY ............................................. .......... ........ 57

Standard Building C characteristics .................................................................... 57
Level of Certification .................................................................... ....... 60
S o ft C o s ts ....................................................................................................... 6 1
R is k A v e rs io n ........................................................................................ ......... 6 1
Perceived Value; c .................................................... 62
High Bid; ch................................................................. 63
N u m b e r of B id d e rs ; n ........................................................................ 6 3
R is k B e h a v io r; 6 ............................................................................. ...... ........ 6 4
Experience ................................. ................................. ........ .. 65
Location n ........................... ............ ............... 66
Assumptions.................... ... ......... 68
Calculations................... ... ................................ 69
C a lcu latio n T a b le ...... .................................................................... ............... 6 9

4 A N A L Y S IS ..................................................................................................... 7 3

E xa m p le P roject................................................ 73
P ro je c t ..................................................................................................... 7 3
Bidder.................................... ...... ............... 73
A n a ly s is ....................................................................................................... 7 3
B ase P rice .................................................................................. .. .... ... 73
Level of Certification ........................................................ ......... .. ...... 73
Baseline Case ..................................................................... ....... 74
B id C lim a te ....................................................................... ..... ............... 7 6


6









Risk Aversion .................................... ......... ............. ..... 77
Location n ........................... ............ ............... 78
S o ft C o sts ...................................................... 7 9
Expected Costs ..................................................................... ....... 80
R e s u lts .......................................................................................... 8 0
Sensitivity Analysis .......................................... ................... ... ........ 82
Certified Level Building................................................ .................... 82
S ilv e r L e v e l B u ild in g ........................................................................ 8 2
G old Level B building ................................................................... 83
P latinum Level B building ................................................................... 83
Risk Aversion .................................... ......... ............. ..... 84
N u m be r of B id d e rs ............................................................................ ..... ........ 84
Experience .......................................... .................. ................... 85

5 SUMMARY AND CONCLUSIONS...................................... 89

S u m m a ry ...................................................................................................... 8 9
C o n c lu s io n s .................................................................. ................................... 8 9

6 RECOMMENDATIONS FOR FURTHER STUDY.................. ........... ... 92

APPENDIX: SUPPORTING DATA....................... ....... .................... 94

LIST OF REFERENCES .................................................................... ....... 97

BIOGRAPHICAL SKETCH ........................................................ .......... .. ...... 99









LIST OF TABLES


Table page

2-1 Rating categories and points available under LEED-NC v2.2. ......................... 19

2-2 Rating levels and associated point totals under LEED-NC v2.2 .................... 19

2-3 Effects of demographic density on feasibility of LEED-NC v2.2 credits.............. 23

2-4 Costs associated with bidding climate ................................. ....................... 24

2-5 Effects of climate on cost of LEED construction.............. .... ................ 26

2-6 Contractor's risk responsibilities related to Sustainable Sites, LEED-NC v2.2 ... 29

2-7 Contractor's risk responsibilities related to Water Efficiency, LEED-NC v2.2..... 30

2-8 Contractor's risk responsibilities related to Energy and Atmosphere.................. 30

2-9 Contractor's risk responsibilities related to Materials and Resources................. 31

2-10 Contractor's risk responsibilities related to Indoor Environmental Quality. ......... 32

2-11 Contractor's risk responsibilities related to Innovation in Design ................... 33

2-12 Total number of LEED-NC v2.2 credits that affect risk to the contractor ........... 34

2-13 Methods of dealing with risk and risk acceptance compensation policies. ......... 43

2-14 Additional costs based on experience .......... .......................... .................. 44

2-15 Percentages of bid based on the difference range of bids tendered................. 51

3-1 Percentage increases in cost of LEED certification from GSA 2004 study......... 60

3-2 Estimates of LEED related soft costs ........................ ........... 61

3-3 Economic factor multipliers for the base case of the risk model...................... 64

3-4 Table for determination of the risk factor for a particular contractor................ 64

3-5 Determination of experience factor for a specific bidder................................. 65

3-6 Factors for determining costs related to the proximity to urban centers ............. 66

3-7 Percentage increase in LEED costs as related to climate............................. 67

3-8 Calculations for Location Factor. ................... ............ ........ ............... 67









3-9 LEED Premium and Bid Amount calculation table........................................ 72

4-1 Expected LEED costs for example 55,000 square foot classroom .............. .. 74

4-2 Calculation of costs in the baseline scenario ............... ........ ....................... 75

4-3 Determ nation of baseline analysis ............ ................................ ...... ............. 76

4.4 Determ nation of baseline analysis ............ ................................ ...... ............. 76

4-5 Economic factor determination ...... .................. ............... 77

4-6 The determination of the Experience Factor................ ..................................... 77

4-7 Determination of the number of bidders. ................................................. 77

4-8 Determination of bidder's Risk Aversion Factor ............................................ 78

4-9 Risk Aversion calculation........................................................ 78

4-10 Adjustment factors for location of the example project. ..................................... 79

4-11 Estim ated Soft Costs ............. .... ....... ..... ............................. ........ 80

4-12 Comparison of baseline case to example scenario. ........... ........................... 80

4-13 Results of m odel calculations ...... .................................................... .. ............... 81

A-1 Supporting data for sensitivity analysis ......... ..... ........ ......... ........... ....... 94









LIST OF FIGURES


Figure page

2-1 Effects of risk on the cost of a LEED certified building. ................................. 22

2-2 Display of the flow of risk associated with a LEED certified project ................ 35

2-3 LEED related risks to contractors............................................... 37

2-4 Elements of project related risk from Alquien 1999. .......................... ........ 40

3-1 Cost per square foot of college classroom facilities.................. ........... 58

3-2 Cost per square foot of college dormitory facilities....... .......................... 58

3-3 Cost per square foot of college student union facilities................. .......... 59

3-4 Cost per square foot of college student union facilities................. .......... 59

3-5 Interactions of the factors and costs associated with the LEED premium. ......... 69

4-1 Graphical representation of the effects on a Certified level building ............... 85

4-2 Graphical representation of the effects on a Silver level building. ................. 86

4-3 Graphical representation of the effects on a Gold level building...................... 86

4-4 Graphical representation of the effects on c a Platinum level building.............. 87

4-5 The effects of various risk aversion behaviors................................................... 87

4-6 The effect of the num ber of bidders............................................. .... .. ............... 88

4-7 The effects of the level of experience......... ........................... .. ............... ...... 88

5-1 Effects of the number of bidders on a LEED Gold project. .............. ............... 90











HPB

LEED

LEED-NC v2.2


USGBC


LIST OF ABBREVIATIONS

High-Performance Building

Leadership in Energy and Environmental Design

Leadership in Energy and Environmental Design rating system for
New Construction and Major Renovation, version 2.2

United States Green Building Council









Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science in Building Construction

MODELING RISK FACTORS ON EXPECTED BIDS IN CERTIFIED SUSTAINABLE
CONSTRUCTION
By

Jeremy Piela

August 2010

Chair: James G. Sullivan
Cochair: R. Raymond Issa
Major: Building Construction

Current research shows that a high-performance building (HPB) that is certified as

such under a rating system such as the Leadership in Energy and Environmental

Design (LEED) building rating system developed by the United States Green Building

Council (USGBC) demonstrate an increase in construction costs over the cost of

traditional projects that do not pursue LEED certification (Steven Winter Associates

2004). This increase is often evident in projects that are produced by designers,

builders and other involved parties that have extensive experience and education in the

construction of buildings that incorporate many of the design features and construction

techniques that are included in HPBs. The purpose of this study is to propose a model

that examines potential cost increases over traditional buildings of similar construction.

This study reviews bid strategy and risk aversion models to explain the impacts of

certification level, experience, location, perceived risk, and the risk behaviors of bidding

contractors on the pricing of high-performance buildings. This study proposes that this

increase in costs is related to the perceived risk involved in the construction of a project

that pursues green certification, the level of certification pursued, and the individual risk

behaviors of the contractors that are operating in a particular bidding climate.









CHAPTER 1
INTRODUCTION

Background

Sustainable construction is becoming a more popular form of construction in the

industry today. As society becomes more aware of the problems that have been

created by the practices that have been utilized in the past, the construction industry is

becoming more aware of the repercussions of the materials and techniques that are

used to develop modern buildings. The built environment consumes an enormous

amount of the resources that are used today, as well as producing a large amount of

waste. Recently, there has been a shift in thinking towards being more responsible with

the resources that are consumed and the wastes that are generated. In the

construction industry, this has resulted in the construction of buildings that are more

responsible in terms of material use, energy use, and the health of the building

occupants.

In response to these concerns, there has been the development of building rating

systems that help to gauge the level of sustainability that is built into a structure. Today,

there are many different systems throughout the world, each with varying popularity.

One of the most popular in the United States is the Leadership in Energy and

Environmental Design (LEED) building rating system. This system has been proven to

reduce the amount of energy that is consumed in buildings, and is also concerned with

the reduction in waste materials, the responsible use of materials, and the health of

building occupants.

While there is some debate over the effectiveness of the rating system, there is

generally agreement that these types of systems are helping the construction industry to









produce buildings that are more environmentally responsible. As these systems gain

popularity, this type of construction is becoming more of the norm in the built

environment.

Problem Statement

Sustainable construction is generally accepted to be more expensive than

standard construction projects. This increase in costs pervades even in the presence of

contractors that are experienced in this type of construction. As this type of construction

becomes the norm, this increase of costs should begin to disappear, as there is no

substantial difference between the rated structures and ones that are not certified.

Certified buildings cost more than similar, non-certified buildings and this study will

propose a framework to account for those costs.

Risk Study

This study will aim to define and rationalize the reasons for the increases that are

evident in the construction of certified buildings. The LEED building rating system will

be studied, as there exists a large amount of data that is accessible due to the

popularity of the system. This study will equate the additional costs to additional risk

that is assumed by the contractor. These risks will be shown to arise from the

perception that these projects are innovative and unique, and therefore pose a latent

risk of loss to the contractor that is in excess of the risk that is assumed in a standard

construction project.

Chapter 2 is a review of the literature that exists in this area of study. The history

of the LEED system will be addressed, and the rating system will be further examined to

help identify possible explanations for this cost increase. The origins of this cost and

the underlying risk will be examined. This will include an analysis of the contract









language that can affect the amount of risk that is assumed by a contractor. A thorough

analysis of the points that are available under the LEED rating system and the risks

associated with pursuing these points will be included.

Included in the Chapter 2 literature review will be an analysis of the types of risk

that a contractor must deal with, and the techniques that are used to deal with risk.

These risk analyses will be carried into a discussion of the effects of risk in the

environment of an auction where contractors submit bids for the construction of a

project. Methods and models that help to determine expected bids will be examined.

Chapter 3 will introduce the model that was developed as part of this study that will

be used to evaluate and predict the bids that are submitted by a particular contractor for

a specific project, using the factors that are laid out in various cost studies that relate to

certified sustainable construction. The model consists of several factors, all of which

are laid out in detail in this chapter. This model is developed using a computerized

spreadsheet and the set up of the model is explained in detail. The methodology of the

model will be laid out in this section, including the relationships of the variables that are

proposed.

Chapter 4 will propose a sample scenario that will be used to show the

relationships that exist in the model. This example will consist of the construction of a

fictional structure on a college campus in the southeast United States that is seeking

certification under the LEED rating system. The associated costs with different levels of

certification will be examined for this particular scenario. The proposed model will be

used to examine this sample scenario, and a thorough analysis of the results will be

included. This sample scenario is produced using a fictional company and project, and









some of the variables will be assumed. This model is meant to produce real world

results, but in this study will only be used to examine and evaluate the relationships

between the risk variables that are involved.

Chapter 5 will include a summary of the study, as well as conclusions that the

author has reached. Chapter 6 will consist of a discussion of the limitations of this study

and recommendations for further research.









CHAPTER 2
LITERATURE REVIEW

Green Building

High-performance buildings (HPB) are buildings that fulfill needs in the built

environment utilizing many of the best methods of conventional construction coupled

with the latest high-performance approaches to construction in areas such as energy

reduction, water reduction, indoor environmental quality, and occupant health. HPBs

are becoming increasingly prevalent in the United States due to several primary

reasons including (Kibert 2008):

* HPB construction provides an ethical and practical response to issues of
environmental impact and resource consumption. This includes a greater reliance
on renewable resources for energy, recycling and reuse of water and other
materials, native landscaping, passive design considerations and other accepted
practices that reduce environmental impacts and resource consumption of the built
environment.

* From a life-cycle cost (LCC) perspective, which examines first costs, performance,
and maintenance, HPBs are almost always a more attractive investment. While
many of the strategies employed are more expensive on a first-cost basis, this
initial cost is usually recouped quickly. This effect is exacerbated by increases in
energy and other resource costs due to increasing demand and diminishing
supply.

* Design and construction of HPBs take into account the effect of the building and its
operation on the health and well-being of the building's future occupants. Building
related illness is a relevant concern, as lost productivity has been estimated to
exceed $150 billion per year (Kibert 2008). Strategies include protection of
ductwork during construction to prevent contamination; specifying finishes with little
or no volatile organic compounds (VOCs) to prevent potential off-gassing; and
utilizing techniques to limit mold and bacteria growth inside of the structure.

LEED

Modern buildings that seek to be considered as high-performance have several

different building rating systems that may be utilized to certify that a building attains a

certain level of performance. One rating system in the United States is the Leadership









in Energy and Environmental Design (LEED) building assessment tool produced by the

United States Green Building Council (USGBC). This system is useful for gauging the

level of sustainability, or greenness in a building (Mathiessen and Morris 2004). The

LEED system "provides third party verification that a building or community was

designed and built using strategies aimed at improving performance across all the

metrics that matter most: energy savings, water efficiency, C02 emissions reduction,

improved indoor environmental quality, and stewardship of resources and sensitivity to

their impacts (USGBC 2010)."

LEED is a standard that is used to measure the level of sustainable measures that

are incorporated into the design and construction of a building. For the purposes of this

study, the LEED-NC rating system will be used. LEED-NC is for new construction and

major renovation (greater than 50% of the occupied space is affected). The system

provides a framework that awards points under several categories that results in a total

score for the building, and a corresponding rating level of Certified, Silver, Gold, and

Platinum. The LEED rating system has gone through many changes since its inception

in 1998 as a pilot program. More recent versions according to the USGBC (2010)

website have been LEED-NC v1.0 (1999), LEED-NC v2.0 (March 2000), LEED-NC v2.1

(November 2002), LEED-NC v2.2 (October 2005), and LEED-NC v3 (April 2009).

The LEED version that this study addresses is the LEED-NC 2.2 rating system.

While this study was performed during the tenure of the LEED-NC v3 system, there was

very little information published about projects under this format. As projects are

registered with the USGBC, they are registered under a rating system and follow that

system through completion. Due to this, there is a useful amount of information that









was available at the time of this study related to the LEED-NC v2.2 rating system, and

projects using this system were examined. While much of the information introduced in

this study can be used under different systems, it should be noted that the information

used and studies cited in this study related to the LEED-NC v2.2 rating system.

Table 2-1 displays the points available in each category and Table 1-2 shows the

points related to each level of certification under the LEED-NC v2.2 rating system.

Table 2-1. Rating categories and points available under LEED-NC v2.2.
Point Category Available Points
Sustainable Sites 14
Water Efficiency 5
Energy and Atmosphere 17
Materials and Resources 13
Indoor Environmental Quality 15
Innovation and Design 5
Total Points Available: 69

Table 2-2. Rating levels and associated point totals under LEED-NC v2.2.
Rating Level Project Point Total
Certified 26 32
Silver 33 38
Gold 39 51
Platinum 52 -69

The higher the levels of certification require a significant concerted effort from the

owner, designer, contractor and the rest of the project team to achieve. This can often

be at a high additional cost.

Davis Langdon 2004

The Davis Langdon study of 2004 compared a database of completed buildings in

order to compare the construction HPBs where LEED certification was a primary goal to

similar buildings where LEED certification was not considered. The 2004 study

reviewed 138 buildings; 93 that were non-LEED and 45 that were LEED-seeking









projects. The prices were normalized for location and time to ensure consistency of the

measurements. It should be noted that many of these projects that were not designed

with the LEED rating in mind would have achieved several LEED credits, though this

was not the intention of the project from the design stage. This study covered several

types of buildings including academic buildings, laboratory buildings, and library

buildings. The Davis Langdon study drew four key conclusions from the analysis

regarding the construction costs of LEED versus non-LEED seeking projects:

* There is a very large variation in costs of buildings, even within the same building
program category

* Cost differences between buildings are due primarily to program type

* There are low cost and high cost green buildings

* There are low cost and high cost non-green buildings

The Davis Langdon study in fact found that there are no statistically significant

differences between the cost per square foot between LEED seeking and non-LEED

seeking buildings. The 2004 study concludes that the variation in the cost of all

buildings makes the price difference in LEED construction not discernable from the

normal variation. The 2007 follow-up to this study again confirmed these conclusions,

using the latest data available at the time of the study.

While the Davis Langdon study shows evidence that there is no significant

difference in the cost of LEED certified buildings and buildings that do not pursue

certification, other studies have shown that there is a difference in the costs of green

buildings that are submitted for bid, such as the GSA study of 2004 (Steven Winter

Associates 2004).









Increased Risk

The difference in price that exists in the construction bidding environment stems

from the risk that is associated with construction with the goal of certification under a

system such as LEED. This risk arises from the additional burden placed on the

contractor to deliver a building that meets a certain criteria. With the added innovation

and planning comes risk, and risk management is the main consideration when

managing creative projects (Alquier 1999). There is often included in the contract

language a requirement for the contractor to ensure that the building performs up to a

certain level of sustainable certification, and failure to achieve this goal and the

associated economic costs are certainly a risk. Many of these buildings, particularly at

higher levels of certification, can be quite innovative and unique, which can present

substantial additional risk. "Green building embodies a greater latent potential for

unrealized expectations, misunderstandings, physical or economic failure, and litigation

(Anderson 2010)."

Cost of LEED

This study proposes that this increase in costs is related to the perceived risk

involved in the construction of a project that pursues green certification, the level of

certification pursued, and the individual risk behaviors of the contractors that are

operating in a particular bidding climate. Since these additional risks pose a latent

potential cost to the contractor, there is a cost increase that is associated with the

additional risk that is passed on to the building owner. These costs are mapped out in

Figure 2-1. The Davis Langdon study of 2004 identified seven particular factors that

affect the cost and feasibility of a LEED certified project. The factors and the effects

that they have on the cost of LEED construction are laid out in seven sections.










How Perceived Risk Affects LEED Premium


re -. Eet o r o te t a LEE erted ld.

SProximity to Serviceser
aa a aalae Pr L' Leel [y of
M o. e on a aer afer-- fed d y lat f ae genery aailEDPral aille i

ot ma m at an i ae t o t t a iat it ra tti






















community connectivity and development density requirements, as well as the public
6 E-Lperteane






Figure 2-1. Effects of risk on the cost of a LEED certified building.

Proximity to Services

Location can have a considerable impact on the cost and feasibility of certain

LEED points. Of the points that are affected by location, five are generally available in a

rural location, while six to eight are available in an urban location, though two of these

points may come at an increased cost over the cost associated with rural construction.

The LEED system is weighted toward the development of urban environments. The

community connectivity and development density requirements, as well as the public

transportation access credit are direct results of this. The credits that are affected by

the demographic location are listed in Table 2-3. As well as an increase in available

credits, urban environments are more likely to have a well established construction

waste recycling or reclamation program. In addition to the availability of services,

contractors are also more likely to be familiar with these practices in an urban setting,

presenting a more sophisticated pool of potential bidders. Infrastructure that is









conducive to the construction of a LEED structure may also exist to a greater extent in

an urban environment.

Table 2-3. Effects of demographic density on feasibility of LEED-NC v2.2 credits. $$$
indicates that the credit may be available, though at an increased cost.
Figure generated from data found in Steven Winter Associates 2004.
Location
Point Category Rural Urban
Site Selection X
Urban Redevelopment X
Alternative Transportation, Public Transportation Access X
Reduced Site Disturbance, Public Transportation Access X
Reduced Site Disturbance, Development Footprint X
Stormwater Management, Rate and Quantity X $$$
Stormwater Management, Treatment X $$$
Water Efficient Landscaping, Reduce by 50% X
Water Efficient Landscaping, No Potable Use or No Irrigation X
Construction Waste Management, Divert 50% X
Construction Waste Management, Divert 75% X
Total Points Available 5 6 to 8

Bidding Climate and Culture

The bidding climate is potentially the most significant factor in the cost of a high

performance building. The bidding climate is the response of the contractors to the

specific requirements of building performance laid out in the contract. The culture of the

entities and relationships between them will also have an effect on the resulting

behavior of the participating contractors. These costs consist of two components;

actual costs borne by the contractor, and the perceived risk associated with the building

performance requirements. Some of these costs are further defined in Table 2-4. The

actual (physical) costs are relatively small, while the cost associated with risk can be

much larger. This will be examined more thoroughly in this study, since this factor is the

one that most extensively drives the cost of LEED construction.









Table 2-4. Costs associated with bidding climate.
Direct Costs Risk Associated
Documentation Costs Liability
IAQ Costs Smaller Bidder Pool
Schedule Impacts Local Familiarity with Sustainable Building

There are many factors related to the amount of the cost of risk, but there are two

major reasons for the increase of cost for wary bidders:

* Bidders are inclined to add contingencies or risk premiums to cover the perceived
risk

* As bid pool diminishes, competition lessens and bid prices increase

As the number of bidders increases, a bidder realizes that to win the auction, they must

bid more aggressively, but the presence of more bidders also increases the chance that

if the contract is won, the winner will suffer a loss (Thaler 1988). This phenomenon is

called the "winner's curse" and is described in detail in this report in the section titled

"Winner's Curse."

Number of Bidders

The number of bidders is also affected by other factors. The strength of the

economy plays a part in the determination of the number of bidders. During a period of

strong economic growth, there are more projects on the market that the contractor could

potentially bid on. Bidders are more likely to bid on projects that are perceived as less

risky if the jobs are available.

Other potential projects

Contractors will be less likely to bid on a project perceived as risky if there is a

large amount of other work available. A contractor, as any other entity, is generally

considered to be risk averse and therefore does not pursue unnecessary risks. If there

is a large amount of work that is available to the contractor that is perceived as less









risky, there are likely to be a smaller number of bidders that are willing to offer a bid on

a project that contains any added risk. The opposite is also true. In a period when the

economy is struggling, there is likely to be a larger pool of contractors that are willing to

take on a larger amount of risk than at other times simply because there is less work

available. An increase in the number of bidders has the general result of reducing the

bid price offered, though this is a general rule and can be affected by other factors.

Experience of bidders

The second is the experience of the bidders that are participating in the auction.

More experience with LEED associated projects will cause the perceived risk to the

experienced contractor to be less than that of the inexperienced contractor. This has

the effect of lowering the amount of the bid. This phenomenon is more completely

discussed in the "Experienced Bidders" section of this report.

The two factors that have the greatest effect are the familiarity of the bidding

community with green building, and the availability of alternative work in the

construction market in the local area of the project. Attempting a project where high

performance building is an unfamiliar concept and/or where contractors are unwilling to

offer bids can significantly affect the cost of the project. Local and regional design

standards, as well as building codes and initiatives will have an effect.

Intent and Values of the Project

This category describes the effect of the intents and values of the owner and

project team as related to the project. The best and most economical sustainable

designs are ones in which the features are incorporated at an early stage into the

project, and where the features are integrated, effectively supporting each other

(Mathiessen and Morris 2004). If members of the project team, particularly the owner,









are not fully invested in incorporating high performance aspects into the project, it will

be more difficult to include these changes into the project. This largely hinges on fully

understanding the intents and desires of the owner and design team. These are

difficulties that the contractor has little or no control over and therefore represents a risk

to the contractor.

Climate

The climate that a building is constructed in has an effect on the feasibility of

certain LEED points, and the cost associated with certain levels of LEED certification.

This factor refers to the natural environmental climate of the location of the project.

Mathiessen and Morris described values associated with location in the Davis Langdon

study of 2004. This is shown in Table 2-5.

Table 2-5. Effects of climate on cost of LEED construction (Mathiessen and Morris
2004).
% Increase Based on Certification Level
Location Certified Silver Gold Platinum
Mild Coastal 1.00% 2.70% 7.80%
California Central Valley 3.70% 5.30% 10.30%
Gulf Coast 1.70% 6.30% 9.10%
Northeast Coast 2.60% 4.20% 8.80%
Rocky Mountain 1.20% 2.80% 7.60%
Average Increase: 2.04% 4.26% 8.72%

The Davis Langdon study took into effect the cost of energy and the amount of

energy consumed, altering the effectiveness of the energy efficiency measures. This

difference in calculation is included in the associated costs. These increases were

derived from a study that took an actually constructed building in Santa Barbara,

California and placed it in five hypothetical environmental locations. These locations

were defined as:









* Mild Coastal Santa Barbara and San Francisco
* California Central Valley Merced
* Gulf Coast Houston
* Northeast Coast Boston
* Rocky Mountains Denver

Yearly temperature fluctuations and humidity levels can play a significant role in

determining cost for mechanical systems, and the feasibility of passive heating and

cooling.

Timing of Implementation

The timing of implementation of a building rating system can also have an effect

on the cost and feasibility of achieving a level of building certification. This factor was

not covered in the Mathiessen and Morris (2004) study since this is extremely difficult to

quantify and measure. This would be a situation specific factor that would have to be

closely analyzed before a project was undertaken.

Size of Building

The size of the building also has an effect on the cost of LEED certification. This

is most notable in the direct cost of the building, but the cost of perceived risk also

increases as a factor of this cost. As the value of the project increases, the costs

associated with risk also increase. Many of these risks are proportional to the total cost

of the project, and will rise as the overall cost of the project increases. If a contractor

were to run late on a project, the damages that the contractor could be held responsible

for could be increased for a larger project. Litigation costs will generally also be tied to

the overall value of the project that is in question, and penalties associated may be tied

to the overall project value, or the potential value to the owner or other financially

interested party.









Point Synergies

The points under the LEED system that are pursued also have an effect on the

cost of certification. Some points are synergistic and can assist in obtaining other

points, lowering the overall cost of a certain level of certification.

LEED Associated Risk

The 2006 Davis Langdon study addressed each category and related costs to

each of the LEED credits. Some credits had little or no associated costs, while others

were very expensive. As with costs, there are risks that fall squarely into the field of

work for certain project members. There are relatively few credits that are the direct

responsibility of the contractor, as the LEED system is weighted heavily towards the

design of the project. Table 2-6, Table 2-7, Table 2-8, Table 2-9, Table 2-10, and Table

2-11 outline the specific credits that fall to some extent under the responsibility of the

contractor, and therefore represent risk to the contractor.

Sustainable Sites

The Sustainable Sites category of the LEED-NC v2.2 rating system is in place to

help reduce the impact of the built environment on the natural environment. The credits

include stormwater and pollution prevention, site selection that encourages use of

previously developed land, and increased use of alternative transportation.

The contractor has little responsibility for most of the Sustainable Sites credits. Note

that there is a perceived risk for Prerequisite 1. This credit usually does not require any

additional activities above and beyond a standard construction project, but under the

LEED rating system this takes on a greater significance. If the contractor fails to follow

local pollution prevention plans, or fails to document compliance, the LEED certification









could be forfeit since this is a prerequisite. This represents a significant additional risk

to the contractor. The risks are outlined in Table 2-6.

Table 2-6. Contractor's risk responsibilities related to Sustainable Sites, LEED-NC v2.2.
Risk to Contractor?
(LEED 2.2 Rating System) Yes No
Sustainable Sites
SS Prerequisite 1: Construction Activity Pollution Prevention X
SS 1: Site Selection X
SS 2: Development Density and Community Connectivity X
SS 3: Brownfield Redevelopment X
SS 4.1: Alternative Transportation Public Transportation Access X
SS 4.2: Alternative Transportation Bicycle Storage and Changing
Rooms X
SS 4.3: Alternative Transportation Low-Emitting and Fuel-
Efficient Vehicles X
SS 4.4: Alternative Transportation Parking Capacity X
SS 5.1: Reduced Site Disturbance Protect or Restore Habitat X
SS 5.2: Reduced Site Disturbance Maximize Open Space X
SS 6.1: Stormwater Management Quantity Control X
SS 6.2: Stormwater Management Quality Control X
SS 7.1: Heat Island Effect Non-Roof X
SS 7.2: Heat Island Effect Roof X
SS 8: Light Pollution Reduction X

Water Efficiency

The Water Efficiency category of the LEED-NC v2.2 rating system is in place to

encourage more efficient use of water resources. This includes reduction of water use,

reduction or elimination of potable water use for landscaping, and innovations in the

treatment of wastewater. The Water Efficiency credits are all related to the design of

the project and pose little if any direct risk to the contractor. The risk responsibilities

concerning the contractor are outlined in Table 2-7. The contractor should be aware of

these credits so that any additional planning that may be required is incorporated into

the schedule.









Table 2-7. Contractor's risk responsibilities related to Water Efficiency, LEED-NC v2.2.
Risk to Contractor?
(LEED 2.2 Rating System) Yes No
Water Efficiency
WE 1.1 and 1.2: Water Efficient Landscaping Reduce by 50% and
No Potable Use or No Irrigation X
WE 2: Innovative Wastewater Technologies X
WE 3.1 and 3.2: Water Use Reduction 20% and 30% Reduction X

Energy and Atmosphere

The Energy and Atmosphere category of the LEED-NC v2.2 rating system is in

place to encourage the reduction in the use of energy and the reduction of the use of

harmful refrigerants in building systems. This includes the reduction of overall building

energy use, commissioning of building systems, and the production or purchase of

renewable energy. The analysis of these risks are outlined in Table 2-8.

Table 2-8. Contractor's risk responsibilities related to Energy and Atmosphere, LEED-
NC v2.2.
Risk to Contractor?


(LEED 2.2 Rating System) Yes No
Energy and Atmosphere
EA Prereq. 1: Fundamental Commissioning of Building Systems X
EA Prereq. 2: Minimum Energy Performance X
EA Prereq. 3: Fundamental Refrigerant Management X
EA 1: Optimize Energy Performance (1-10 points) X
EA 2: On-Site Renewable Energy (1-3 points) X
EA 3: Enhanced Commissioning X
EA 4: Enhanced Refrigerant Management X
EA 5: Measurement and Verification X
EA 6: Green Power X

The Energy and Atmosphere category has little effect on the performance of the

contractor. This is generally a design category and is a cooperative effort between the

designers and installers of the building systems. Again the contractor should be aware

of these credits so that the schedule may be adjusted accordingly.









Materials and Resources

The risks that are presented to the contractor are outlined in Table 2-9. The

Materials and Resources category of the LEED 2.2 rating system is in place to promote

the reuse and recycling of building materials, as well as materials that are considered

sustainably harvested or produced locally.

Table 2-9. Contractor's risk responsibilities related to Materials and Resources, LEED-
NC v2.2.
Risk to Contractor?
(LEED 2.2 Rating System) Yes No
Materials and Resources
MR Prerequisite 1: Storage and Collection of Recyclables X
MR 1.1 to 1.3: Building Reuse X
MR 2.1 and 2.2: Construction Waste Management Divert From
Landfill X
MR 3.1 and 3.2: Materials Reuse X
MR 4.1 and 4.2: Recycled Content X
MR 5.1 and 5.2: Local/Regional Materials X
MR 6: Rapidly Renewable Materials X
MR 7: Certified Wood X

The risk associated with the Materials and Resources category falls squarely in

the realm of the project responsibilities of the contractor. The Building Reuse credit

requires the contractor to develop a construction plan that must be followed through to

preserve the required proportion of the building. The Construction Waste Management

credit is perhaps the only credit that is the direct responsibility of the contractor. An

experienced contractor should be familiar with this type of requirement, but the related

risk is the direct responsibility of the contractor. The risk for credits MR 3 MR 7 stems

mainly from the procurement of the proper materials and the maintenance of the

documentation that is necessary to show compliance with the credit requirements.









Indoor Environmental Quality

The Indoor Environmental Quality portion of the LEED 2.2 rating system is in place

to help protect the health and well-being of the inhabitants of the building. The risk to

the contractor is outlined in Table 2-10. While much of this category is the responsibility

of the design team, the contractor holds some responsibility for following through with

the designed plans.

Table 2-10. Contractor's risk responsibilities related to Indoor Environmental Quality.
Risk to Contractor?
(LEED 2.2 Rating System) Yes No
Indoor Environmental Quality
EQ Prerequisite 1: Minimum IAQ Performance X
EQ Prerequisite 2: Environmental Tobacco Smoke (ETS) Control X
EQ 1: Outdoor Air Delivery Monitoring X
EQ 2: Increase Ventilation X
EQ 3.1: Construction IAQ Management Plan During Construction X
EQ 3.2: Construction IAQ Management Plan Before Occupancy X
EQ 4.1 to 4.4: Low Emitting Materials X
EQ 5: Indoor Chemical and Pollutant Source Control X
EQ 6.1: Controllability of Systems Lighting X
EQ 6.2: Controllability of Systems Thermal Comfort X
EQ 7.1: Thermal Comfort Design X
EQ 7.2: Thermal Comfort Verification X
EQ 8.1: Daylight and Views 75% of Spaces X
EQ 8.2: Daylight and Views 90% of Spaces X

There are a few credits in the Indoor Environmental Quality category that pose

potential risk to the contractor. EQ 3.1 relates to the protection of materials and the

HVAC system during the construction process. EQ 3.2 does not directly involve the

contractor, but must be incorporated into the contractor's construction schedule. If the

contractor failed to plan for an appropriate amount of time for these activities, the

schedule may be extended beyond the required date of substantial completion. The

risk is that the contractor may be responsible for not delivering the project on time if this









credit is not appropriately planned for. EQ 4.1 to 4.4 would likely fall into the

contractor's risk area, unless the materials to be used were expressly specified in the

contract documents.

Innovation in Design

The Innovation in Design category of the LEED-NC v2.2 rating system is used to

award exemplary performance in one of the listed categories or the utilization of

innovative technologies or other methods that improve building performance. Risks to

the contractor are outlined in Table 2-11.

Table 2-11. Contractor's risk responsibilities related to Innovation in Design.
(LEED 2.2 Rating System) Risk to Contractor?
Innovation in Design Yes No
ID 1-4: Innovative Design (projects average two of these credits) X
ID 5: LEED Accredited Professional X

Most of the projects in the Davis Langdon study received two points in the Innovation in

Design category for credits other than the LEED Accredited Professional credit. These

credits were almost always for exemplary performance in the categories where this is

an option. It is assumed that the contractor could have some risk responsibility in these

credits as the study did not address which credits were involved.

LEED Credits Affected

The total number of points may vary depending on the contract language, the type

of project being considered, and the associated credits that are being pursued by the

project team. The credits presented here show potentially affected credits that would be

seen in a standard construction project, though this may vary. The risk that the

contractor is exposed to should be limited to the performance of these credits. The

credits that affect the risk level of the contractor are outlined in Table 2-12.









Table 2-12. Total number of LEED-NC v2.2 credits that affect risk to the contractor.
The prerequisite is included in the Sustainable Sites category.
Point Category Point Total
Sustainable Sites 1 + 3
Water Efficiency 0
Energy and Atmosphere 0
Materials and Resources 13
Indoor Environmental Quality 6
Innovation and Design 2
Total Points Affected: 25


Risk to the Contractor

The risk related to compliance with these credits is generally passed on to the

contractor from the owner in order to cover the potential costs to the owner that may

stem from failure to achieve green certification. These potential damages can include

the loss of a tenant or sale, loss of government incentives and tax credits, increased

design and construction costs, rescinded donations on endowed projects, penalties on

public projects with green mandates, increased energy and water costs over the life of

the building, and diminished asset value (Anderson 2010).

Contract language. A major factor that must be considered is the amount of risk

that is put upon the contractor by the owner or other parties. This is largely affected by

the language that is included in the contract documents. While standard AIA

documents are often used for construction projects, the green building movement is

relatively new and some of these documents are insufficient. To avoid any confusion,

there should be language or additional documents included in the documents that

clearly defines the responsibilities for each party in relation to the area of green

certification.











The association of risk with potential activities in the construction of a building is


shown in Figure 2-2. Anderson et al. 2010 identified four areas that specifically affect


the contractor on a construction project when green certification is desired. These are:


Performance specifications versus design specifications. The Spearin


doctrine states that "[I]f the contractor is bound to build according to plans and


specifications prepared by the owner, the contractor will not be responsible for the


consequences of defects in the plans and specifications (248 U.S. 132, 1918)." This


doctrine applies to design specifications and not performance specifications. In an



PJk Rei1pon ibility forLEED Ceri ed Pojecrs BasedonCSI Division



LEED
CeDrifmation

LEED
Admim i tao r






Subcontracto rs



D~Eumentation Documentatnioand Performmnme
-Diision 3 Concrete Diiion 2 Site Construction
*Division4-Masonry *Division 7- Thermal and Meisture Protectio
*Division 5 Metals *Division 8 Doors and Winadws
*Division 6 aod ad Plksties Division9- Finish s
-Division 10 Specialties -Division 11 Equipment
*Division 12 Fmurishmi~ *Division 13 Special Costruction
*Division 14 Conveying *Division 15 Mechnical
Systems *Division 6 Electrical


Supliers


Figure 2-2. Display of the flow of risk associated with the construction of a LEED
certified project.

area such as product selection for adhesives and sealants, under performance


specifications the contractor would be responsible for selecting materials that were









appropriate under SS credit 4, Low Emitting Materials. By accepting a contract with

performance based specifications, the contractor would be accepting the responsibility

for the design of this area of the project, and the resultant effects on the green

certification. The risk associated would be bore entirely by the contractor.

Guaranteeing LEED certification. Generally, the contractor should at least be

aware and probably cautious of guaranteeing LEED certification. The contractor in fact

has little control over the certification in that very few of the LEED credits are under the

control of the contractor. It is recommended that the contractor take appropriate

responsibility for their portion of the project in a way that protects the owner's interests,

but it is often unreasonable and unlikely for the contractor to assume all risk for the

certification of the project (Anderson 2010).

Potential delays. There are components of a green building project that directly

affect the schedule of the project, which falls squarely in the domain of the contractor.

One issue stems from the popularity of green projects, and the availability of materials

that are associated with these projects. Some of these products may be in high

demand and low supply, which can present extended procurement times. Some of the

LEED credits actually require more time to be included in the project schedule. Low-

emitting paints associated with IEQ credit 4.2 generally take more time to cure, and may

extend the time required for other activities. The building flush-out procedure that is

associated with EQ credit 3.2 also has an associated time period that takes place

following final construction activities, but prior to occupancy. This directly affects the

critical path of the project as no other construction related activities may take place

during this operation. This extra time may not be immediately quantifiable for a









contractor, particularly one with limited experience in this arena, and presents a risk to

the contractor of negatively affecting the schedule and any monetary penalties that are

incurred related to these delays.

Green performance bonds. In certain locales, including Washington D.C.,

performance bonds are being utilized to ensure compliance with green mandates. If a

building does not achieve LEED certification within two years after the issuance of the

certificate of occupancy, the bond is forfeit. While the contractor may or may not be

directly responsible for the performance mandated by this bond, they should be aware

of the existence and consequences of this and the risk that is associated with non-

compliance. The popularity of this type of performance bond should be monitored, as it

will affect the latent risk that is posed to contractors undertaking projects where these

are present.

The risks that are posed to a contractor due to the LEED certification system are

outlined in Figure 2-3.


Risks to Contractors


Total Risk to Contractor



Performance Versus Construction Delays Related to
Design Specifications Earning LEED Points



Guarantee of LEED Forfeiture of Bonds,
Certification or Points Litigation, or Other Penalties


Figure 2-3. LEED related risks to contractors.









Contracts

Green building is becoming more common in the construction arena today, but

there are still areas where the usual way of doing things is insufficient for the green

building environment. Particularly the wording that is common in many standardized

construction contract documents is insufficient. One particular example is the AIA A201

- 2007 General Conditions definition of "work." This does not account for the

requirement that contractors, subcontractors, and suppliers provide documentation that

is essential to the LEED certification process. This documentation must be created and

maintained throughout the project, and credits could be lost if this requirement is not

performed (Anderson 2010). The AIA is providing documents that help to fill these gaps

(such as AIA B101, B211, and B214), but holes still exist that may pose an increased

risk to the contractor that they may or may not realize that they are subjecting

themselves to.

Risk Analysis

The risk and potential costs appropriated by the contractor bidding on a

construction project is a parameter that can be modeled and analyzed to gain insight

into the decision of a contractor to increase price due to a perceived risk. The analysis

of risk can also affect the decision of a contractor to bid on a certain project at all,

affecting the number of bidders that may participate in the auction for a construction

contract.

Analysis of risk and risk models are useful in that they allow us to obtain better

insight and understanding about the problem at hand. This does not always equate to

determining an exact scientific conclusion, but often creating a model that allows us

some insight into the factors that we would like to control to achieve a more desirable









outcome. This can be important in innovative construction projects since the "creative

projects have to focus on risk management and risk management is the main

consideration when managing creative projects (Alquien 1999)." Possible alternatives

are often not clearly defined and analysis is used to help the decision maker to identify

and explore possible alternatives and scenarios as well as to choose among them

(Granger et al. 1990). James G March has defined this model in the following summary:

Human beings make choices. If done properly choices are made by
evaluating alternatives in terms of goals on the basis of information
currently available. The alternative that is most attractive in terms of the
goals is chosen. The process of making choices can be improved by using
the technology of choice. Through the paraphernalia of modern techniques,
we can improve the quality of the search for alternatives, the quality of
information, and the quality of the analysis used to evaluate alternatives.
Although actual choice may fall short of the ideal in various ways, it is an
attractive model of how choices should be made by individuals,
organizations and social systems. (March 1976)

Under this framework, we can use these models to provide an aid in the evaluation

of different scenarios. According to Granger et al. (1990), a model can be used to

assist in the "systematic exploration of alternative possible goals" by using a framework

to identify existing and invent new alternatives to aid in reaching a that goal. The aim of

this study is to understand how bidders in a construction auction develop a bid, based

on risk and other factors, and to provide a tool for analyzing what goes into these bids.

The first step is to understand the source of the risk in the broadest sense. In this

approach, there exists two types of risk; internal and external. These are described in

Alquien (1999) and are described in detail in this report.

External Risk

External risk is a portion of total risk that the company does not control. External

risk relates to factors in the environment that the company operates in such as; market








shifts, government action, environmental (nature) interactions, market competition, and

external regulation. External risk is also called market or environment risk.

Internal Risk

Internal risk represents the portion of total risk that is supposed to be under

company control. Internal risk is associated with the technical solutions regarding

products, processes, and resources. These can include new technology, required

resources, innovative processes, and cost estimations.

Risk Balance

The risk balance of a company in regards to a specific project contains elements

of both internal and external risk. The goal of a risk analysis is to evaluate the internal

and external risks that have the potential to affect the company or project. These risks

are outlined in Figure 2-4. The company must then decide whether these risks are

acceptable, and if so at what level.


Project Related Risk


Internal Risk External Risk



1 4

Technical Solutions Customer Requirements
Costs Price
Resource Availability Market Risk
Process Innovation Environmental Risk
Legal Risks

Figure 2-4. Elements of project related risk from Alquien 1999.









Levels of Risk

There are different levels of risk, and organizations and people are willing to

accept varying levels of risk in the activities that they pursue. Every undertaking is

associated with a certain level of risk and our decision to pursue this activity or not is

based on our own risk acceptance policies.

Zero Risk

A zero-risk criterion is described as; independent of the benefits and costs, and of

how big the risks are, eliminate, or do not allow the introduction of the risk (Granger et

al. 1990). This describes the rationale that there is no reason for every policy to be

accepted or every activity to be undertaken. Some activities will not be accepted

because there is a risk involved, and the entity that is in the decision making position is

unwilling to take on any associated risk. In the area of high-performance buildings and

LEED certification, this is the equivalent of a contractor that is unwilling to even place a

bid on a project because they are unwilling to accept any of the potential risk that is

involved, no matter what the price. This may be due to the contractor having very

limited experience in this type of construction, or a bidder that is very risk averse.

Approval-Compensation

Another criterion that is useful in describing levels of risk acceptance or aversion is

the approval-compensation criterion. Under this model, one accepts risk or other costs

to be imposed upon them in exchange for some sort of compensation in repayment for

their inconvenience or potential losses. In the realm of sustainable construction, this

refers to the cost increase that is included to recognize the risk in performing the project

goals. This is one of the types of risk acceptance that will be useful in this study, since

this is a quantifiable criterion that can be analyzed using a model that will be developed.









Examples of some alternative decision criteria that may be applied in risk

management analysis (Granger et al. 1990) that are included in decision making, and

will be useful in this study include several utility based criteria.

Utility Based Criteria

Utility criteria depend on the amount of risk that an entity is willing to accept and

the amount of compensation that is required.

* Deterministic benefit-cost: Estimate the benefits and costs of the alternatives in
economic terms and choose the one with the highest net benefit.

* Probabilistic benefit-cost: Same as deterministic benefit-cost but incorporate
uncertainties and use expected value of resulting uncertain net benefit.

* Bounded cost: Do the best you can within the constraints of a budget that is the
maximum budget the entity is prepared to devote to the activity.

* Maximize multi-attribute utility (MAU): This is the most general form of utility based
criterion. Rather than use monetary value as the evaluation measure, MAU
involves specifying a utility function that evaluates outcomes in terms of all their
important attributes (including uncertainties and risk). The alternative with
maximum utility is selected. Some of the Life-Cycle costing and other factors that
are involved with sustainable construction would be included in this section, and
could help to make a decision for an owner to spend more money to create a
green building.

* Minimize chance of worst possible outcome: Political and behavioral
considerations frequently dictate the use of such criteria.

These criteria are summarized in Figure 2-4.

Risk Criterion

In the environment of an auction, which a bidding environment is, contractors will

utilize one or more of these decision criteria to make decisions regarding bids on

projects perceived as risky. These decisions will be based on a hybrid type of risk

criterion, since the process of construction bidding is very complex and involves many

discrete factors and entities. Bidders will generally have either a risk seeking, risk









neutral, or risk averse mentality, and based on this characteristic will place a value on

the risk based on the size of the risk and the attitude of the bidder with respect to risk

practices.

Table 2-13. Methods of dealing with risk and risk acceptance compensation policies.
Risk Practice Choice Methodology
Deterministic Benefit-Cost Choose option with highest net economic
benefit
Probabilistic Benefit-Cost Choose option with highest net economic
benefit incorporating uncertainties and expected
values
Bounded Cost/Risk Choose best options while remaining within
certain levels of cost/risk
Maximize multi-attribute utility Choose option with highest total benefit

Minimize worst case Choose least risky option


Different bidders will have different utility based decision making processes that

they may make use of. This may depend on the characteristics of that particular bidder

and the situation that the bidder is in at the time of the auction. A bidder is left to

determine the benefits and costs of a decision, and when applied to LEED construction,

the costs can be high to a bidder. Contractors may be required to deliver a building that

is certified to a certain level, and this is likely to be stated in the contract documents.

The contractor is then left with this obligation to fulfill. Assuming that the contractor is

familiar with the LEED process, they may understand the costs that may be incurred.

The contract language that is in place will generally describe the responsibilities of the

contractor, and assign the risks that are involved to the interested parties. Some risks

are specific to the contractor and the physical construction of the project. These may

include (but are not limited to):









* Training costs: training to perform for certain LEED credits may be required
including materials treatment under EQ credit 3.1 Construction IAQ Management
Plan, or training for processing and documentation of LEED.

* Equipment costs: new equipment may need to be purchased such as storage
areas, cleaning machines, or pieces of machinery that are required for the
installation of materials that are unfamiliar to the contractor.

On top of the costs that are expected to be incurred during the completion of a

LEED project, there are also the costs that may be in addition to expected costs if the

contractor is unfamiliar with the LEED process, or makes a mistake along the way.

These include:

* Costs for appealing credits: There can be a significant cost associated with the
failure to achieve credits that were targeted, particularly if these credits are
required for the level of certification that is required

* Litigation: If a contractor fails to achieve the project standards that are outlined in
the contract documents, then the owner may choose to recover money from the
contractor to finish the project in a manner that meets the project requirements

* Documentation: If a contractor does not have the personnel or systems in place to
provide the documentation that is required to successfully complete the
certification of a building

These criteria are summarized in Table 2-14.

Table 2-14. Additional costs based on experience.
Inexperienced (in addition to costs to
Experienced experienced contractors)
Training Costs Credit Appeal Costs
Equipment Costs Litigation Costs
Documentation Costs

Risk Factors

The first factor that will go into the model of a particular entities risk based decision

is the level of risk (6) that a bidder is willing to undertake. Entities exist on a scale that

ranges from risk-averse (6 => 1) to risk seeking (6 => -1). Risk aversion refers to the

proclivity to avoid risk as much as possible. These contractors may be willing to only









undertake projects that they perceive as having very little or no risk. When LEED

buildings are considered, this risk is assumed to be additional risk, on top of the normal

amount of risk that is commonly associated with construction projects. The risk that will

be considered in this study refers to the amount of additional risk that is perceived by

the owner that is taken on above and beyond the risk associated with the normal

business model of that entity.

A risk averse bidder may be reluctant to bid at all on a LEED project that they feel

they is too risky for them. There are many reasons that a contractor may feel this way

about a project. These include:

* The general risk aversion of the company The company may feel that a LEED
certified project presents more risk than they are willing to take on. This may vary
from lower to higher levels of certification.

* The level of risk associated The size of the project or the level of certification that
is being pursued can have an effect. The amount of responsibility placed on the
contractor in the construction documents can determine this level.

* The perceived risk based on internal factors Company may not be familiar with
LEED construction, or not have the necessary elements in place to properly deal
with a given project.

* The perceived risk based on external factors This could include other bidders,
the state of the economy, location, or other risks apportioned to the contractor in
the construction documents. Collectively referred to as the "bidding environment".

This risk is compensated for is the amount of money that a contractor charges in

addition to the profit that they are expected to make. This is a type of probabilistic

benefit-cost. While contractors likely do not realize that they are performing this type of

action, they probably are. This condition is described by adding a premium onto the

project that is the result of the amount of risk perceived and the value of the project.

This study is concerned with construction costs and the risk preferences and

values that drive those costs in a construction bid environment. The risk analysis is









important in the early stages of the project (the bidding phase), because this is when

uncertainty is the greatest. "Risk knowledge is fuzzy, distributed, unstructured, tacit,

ancient history forgotten or transformed, insufficiently organized, not or completely

cataloged, underestimated, registered in heterogeneous information systems, secretive,

possessed by experts who are rare in the company (Alquien 1999)." There are certainly

other costs and benefits associated with sustainable design and construction that

should be considered, including operations and maintenance implications, user

productivity and health, design and documentation fees, among other financial

measurements (Mathiessen and Morris 2004), but the initial costs are the subject that

will be more closely studied here. While each project must be studied individually,

particularly if a higher level of certification is desired, there exists sufficient evidence to

make generalizations about the costs associated with these projects which are

becoming more and more commonplace. These projects are moving more from an

innovative construction project to being the norm in the built environment today. Even

buildings that do not seek any type of certification often use many of the same

strategies as they make their way into building codes. Many owners also see the

benefits financially from many of these strategies and wish to incorporate them into

more of their projects.

Risk in Bidding

Much construction that is performed today is valued through a competitive sealed-

bid auction. This is a type of auction that requires qualified bidders to submit sealed

bids by a fixed deadline. The bid is then opened and the lowest price or second lowest

price bidder is awarded the contract. The type of auction utilized in construction bidding

generally involves both private and common value elements (Tang et al. 2006), though









the auction is generally treated as a common value auction (Dyer 1996). This means

that the bidders all have different estimates of the value of the project at the time that

they bid, though the contract is generally believed to have the same value to each of the

bidders. This valuation is based on the degree of uncertainty that is involved in the

project, causing risk averse bidders to submit higher bids and risk seeking bidders to

submit lower bids, with risk neutral bidders submitting bids in the middle. This arises

from the manner in which bidders with different risk preferences consider the

uncertainty.

Risk Compensation

Uncertainty always exists, but different bidders will view it under different lights.

When a contractor faces a risk, the marginal utility of their income increases, leading to

what is termed as precautionary bidding (Eso 2003). This has the effect of causing

bidders to bid less aggressively since the value of each dollar of income is increased as

compared to the value of winning the auction. A risk-averse (6 => 1) bidder would

presume the uncertain factors to consist of a proportionately larger latent cost than

latent profit. This indicates that a risk-averse bidder would perceive the uncertainties to

contain a probabilistic negative profit.

The risk-seeking (6 => -1) bidders would view this scenario another way. The risk

seeker would perceive the uncertainties involved in the project to be latent profit that

can be realized, versus being a risk with the potential to result in a loss. This means

that the risk-seeker believes that there is more profit in the project, and therefore is

willing to submit a lower bid.









This indicates that the risk-seeking bidders are most likely to win the bid. This can

have adverse consequences in several ways. The first is that the risk seeking bidder

may also be increasing the latent risk of the bid seller. By selecting the riskiest bidder,

the entity offering the bid is taking on increased risk. If the risk seeking bidder is then

unable to perform the contract and cannot compensate for the loss, the seller/owner

may be forced to accept the cost for the failure of the contract. The owner may be

unknowingly accepting this risk and may be unwilling to do so.

If a very low bid is submitted, this could be an indication that this particular bidder

is a risk-seeking bidder. There could be many reasons for this, including:

* Bidder may be struggling for work and is therefore willing to take on more risk or
less return for a unit of work

* Economic conditions can have a significant effect, with many normally risk-averse
bidders more willing to take on risk in a market that has less work

* Bidder may not understand the risks involved

* Bidder may have unseen barriers in place in case of failure that could affect the
owner in the event that the bidder fails to perform.

Winners Curse

Another unintended consequence of accepting the lowest bid is that the low bidder

faces an adverse selection problem as they only win when he/she has one of the lowest

estimates of the cost of construction (Dyer 1996). If bidders are not careful to account

for this adverse selection problem, then the low bidder may suffer from a "winner's

curse", when the bidder wins the auction but the bid is so low that it results in a bid that

delivers below normal or even negative profits. In a potentially risky scenario, such as

the additional risk burden that is assumed in the construction of a LEED certified









building, this is a type of risk that can be compensated for through the increase in the

bid price that is tendered for the project.

The winner's curse is a phenomenon that has been well studied in the past. This

phenomenon was first identified in an article often cited entitled "Competitive Bidding in

High-Risk Situations" by Capen, Clapp and Campbell (1971). There were extreme

discrepancies in the realized value of the early outer continental shelf (OCS) oil lease

auctions that began in 1954 (Dyer 1996). Values of the fields were exaggerated by very

aggressive bidders that were bidding on items that had a value that was very difficult to

define. Bidding spiraled out of control and some winning bidders found themselves in

possession of oil field leases that provided very small if any returns for their initial

investment. Similar claims have been made regarding auctions for book publication

rights, in professional baseball's free agency market, and in corporate takeover battles

(Dyer 1996). This outcome has proven to be pervasive even in a laboratory

environment.

In a study conducted by Dyer et al. in 1989, it was shown that even sophisticated

bidders, drawn from a pool of executives in the construction industry, suffered

extensively from the winner's curse. The 1989 study results showed that over 50% of

the bids that were submitted (in the laboratory) were below the expected value

conditional on winning the auction, so that half of the bids resulted in negative expected

profit. This is a concern, because the owner that is asking for these bids may be

unknowingly hiring a bidder that has put themselves in a position where the project is

not going to be profitable for them.









Risks Associated with the Winner's Curse

The winning bidder is likely to not be pleased with the negative profit scenario that

is associated with the winner's curse in winning the auction. This is a dangerous

position for both the winning bidder and the bid seller. The bidder may choose to not

perform on the contract or may choose to try to make up for the lost profit through

change orders or other means. Both of these scenarios will result in a higher than

expected cost to an owner. This final cost may even be larger than some of the higher

bids that were rejected, but were likely more responsible bids.

Another potential out for a bidder that has fallen victim to the winner's curse is the

withdrawal of the bid due to arithmetical errors. In most states there exist laws that

allow bidders to withdraw their bids without penalty (without loss of bid bond) if they

believe that they have errors included in the bid. The interpretation of these errors can

be quite broad (Dyer 1996). While intended to include clear arithmetical errors that can

occur, this can also be an out for a bidder that has made a mistake in generating a bid

that is too low. There are some reasons that are given by owners that explain why they

would allow a broad interpretation of these errors. The owner does not want a

contractor working for them that has submitted a bid that is so low that they will certainly

lose money on the job. A survey by Dyer and Kagel in 1996 developed some of the

reasons that were given that owners would allow a bid to be withdrawn:

* To preserve the relationship between the contractor and the owner

* To prevent damage to the contractor by forcing completion of the contract that
could result in disruption to the job schedule

* Forcing forfeiture of bid bonds can result in the reduction of the number of bids on
subsequent bids, causing an increase in the bid prices submitted based on bid
models









The resulting problems that occur from accepting performance on a bid that is too

low can result in effects on the owner and project that are similar to the effects of the

winner's curse on the bidders. Risk seeking bidders can therefore have a widespread

effect on the auction, the project, and even subsequent auctions.

Identifying the Winner's Curse

One possible way to identify the winner's curse in the auction environment is the

quantification of the difference between the lowest and the second lowest bid. This is

commonly referred to as "money left on the table". This is money that the lowest bidder

could still have collected and still have been the lowest bid. As the number of bidders

(n) increases, bid amounts decrease, and the money left on the table should decrease

also. The relationships are outlined in Table 2-15.

Table 2-15. Percentages of bid based on the difference range of bids tendered. Values
derived from Dyer et al. 1996, page 1466.
n: 4 7 12
Mark-up needed to prevent winner's curse 60.0% 75.0% 84.6%
Expected Profit 40.0% 25.0% 15.4%
Money left on table 10.0% 3.6% 1.3%

Contractors are generally aware of at least the effect of these factors, and make

up for these deficiencies through increases in the bid price. The key findings of Fu et

al.'s 2002 study was that inexperienced contractors, largely without expertise and being

wary of the winner's curse, would submit higher bids in bidding. This is included in the

bidding model that is proposed in Tang et al. 2006, and is presumed to be included in

the contractors bid. This price increase is a result of the risk aversion policies of the

contractor, and the contractor's perceived risk associated with that particular project.

Through examination of the winner's curse and money left on the table, we can then

determine:









* How the number of bidders affects the bid price and competition among bidders

* How the lowest bidder brings increased risk not only to themselves, but also to the
bid seller.

Experienced Bidders

The experience of the bidder that is submitting the bid also has an effect on the bid

price that is offered. The Fu et al. study of 2002 found that contractors who bid more

frequently are more competitive than contractors that bid occasionally. While this

serves to reflect in the overall bid strategy of the contractor, the effect was much

stronger in construction work that was more standardized. While much of the work that

is related to LEED construction is not considered standard yet, much of the work is

repeatable from project to project. This would infer that the more LEED contracts that a

contractor bids on, the more competitively priced that these bids will become.

Construction experience can be considered as the synthesis of five components that

apply to bidding as well, since bidding is seen as an integral part of the construction

process (Fu et al. 2002):

1. Managerial experience
2. Technological experience (construction methods)
3. Costing experience
4. Local experience (trade practice, legal environment, etc.)
5. Institutional experience (knowledge of client's preferences, etc.)

These components are roughly equivalent to the types of the internal and external

risks that the contractor faces that are outlined in Figure 2-4. The experience of the

contractor in fact is a mechanism that allows the contractor to better deal with the risks

that are presented to them. As is discussed in this report, risk can be seen as either an

opportunity for profit or loss. Experienced contractors have learned to limit their









exposure to the downside of this risk, and the bids that they tender reflect the reduction

of this uncertainty.

The Fu et al. study of 2002 concluded that the bidding performance of less

experienced contractors is likely to be more erratic in terms of competitiveness.

Following this logic, the more experienced that a contractor is, the more likely they are

to bid not only competitively but also consistently.

Risk and HPB

There is an increased risk that is associated with constructing HPBs. This is

particularly true with a building certification requirement under a system such as LEED,

where a building can be considered a failure if it does not achieve the level of

certification that is required by the owner. This risk is associated with a cost that is

passed on to the owner by inclusion of a mark-up on the bid price which can be called a

"LEED premium." The actual cost of this is often the first concern of an owner or other

parties involved. Inexperienced bidders will likely have a less accurate estimation of the

risk involved and the profits available, and are therefore more likely to overcompensate

for a potential winner's curse, raising the bid price in response to this risk.

Bidding Model (Tang et al. 2006)

Tang et al. 2006 developed a model that takes into account many of these the

factors that are commonly referred to as the bid climate, including the risk tendencies of

a particular bidder. The basic models of bidding when related to construction projects

assume that a buyer (bidder) purchases a single item from sellers in a one-shot auction.

The number of bidders (n) and the probability distribution of bidders' private information

are assumed to be common knowledge. In the traditional model all bidders are also









considered to be risk neutral (problems with this assumption are addressed in the Tang

et al. 2006 bid model).

The Tang et al. 2006 formula differs from the standard bidding model in one

important way. The standard bidding model assumes that all bidders are risk averse,

while this is untrue in the low-price bids that are applied in the construction setting. In an

auction bidding environment, the bidders may all have different risk preference

tendencies and will all compete for the same contract. This differs from the first

assumption of the standard bidding model that states:

* All bidders are risk neutral

The Tang et al. 2006 study sets up a model that allows for the variance in the

bidders risk preferences of the various bidders. Other assumptions that will be made

and are taken from the standard bidding model are:

* Every bidder has the independent information of estimating the bid
* Payment is just the function of the price quoted
* The distribution of bidders' price quoted is symmetric

Model Factors

In the modified model, the number of bidders is denoted as n. These bidders are

all assumed to be qualified to bid for the project in question. All of the bidders in the

auction may have a different value of the project denoted by c;. These different

valuations are all assumed to be independent and drawn from the same distribution of

private values denoted by distribute function F on interval [ c/, ch ], c/ = min{ci, h =

max{c;} (i = 1,2,3, ...,n), c; is a private value that is known only to bidder i. The cost c; is

assumed to be estimated by bidders that are risk neutral, and therefore is not influenced

by uncertain factors.









The estimation of risk is defined as bidder i's estimation for uncertain factors and is

denoted as c The value of c and the degree that it influences the valuation c1 depend

on the risk preferences of the bidder i. Thus the valuation of ci is made up of three

parts: first is c1 affected by positive c ,, second is ci affected by negative c and third is c1

not affected by c ,, representing the differing risk preferences of the bidders. So the

payment to the bidder from the owner would be noted as:

Pi = c + 6C i (2-1)

Where pidenotes the payment to bidder i, 6 E [-1,1], represents the bidder i's risk

taking preference with three cases;

* 6 E [-1,0), 6 presents risk seeking bidders degree of seeking risk
* 6 E (0,1], 6 presents risk averse bidders degree of avoiding risk
* 6 = 0 indicates that the bidder is risk neutral

Therefore, if the assumptions of the model are true, then the bid price valuation bi

submitted by bidder i can be represented by:


bi = +(c-+ n- 6c (2-2)

This model is an extended bidding model that considers the bidders' risk

preferences. The number of bidders lowers the price that is submitted, as the auction

becomes more competitive. Bidders may also be aware of the rise in the number of

bidders and their bid may reflect this. The model in equation (1) takes this into account

but at the same time makes the value of the perceived risk and the risk preferences of

the bidder distinct. In this model, the bidder iwho submits the lowest price bi will win the

bid in the lowest price sealed bid construction auction. If the bidder is risk neutral then

6 = 0 and the quote price is equal to:









bi= c +(c-ci (2-3)
n

This model (3) is nearly identical to the standard bidding model.

If the bidder i is risk seeking, then 6 E [-1,0). When 6 approaches -1, the

suggestion is that the bidder will lower their price so as to win the construction contract

by increasing their degree of risk seeking 6.

If the bidder is risk averse, then 6 E (0,1]. As 6 approaches 1, the bidders will tend

to increase their bid price. The bidders hope to win the bid, but increase the risk based

on the amount of risk perceived.

The number of bidders (n) brings into effect two competing forces that change as

the number of bidders increases (Dyer 1996). Since n is assumed to be known to all of

the bidders involved, the bids are directly affected by this. As n increases, strategic

factors promote lower bids, since any chance of perceived profit is contingent on

winning the auction. The heightened awareness of adverse selection that occurs with

the decrease in bid price competes with the strategic factors to form the function of the

assumed equilibrium distribution that exists in the auction. Though there is evidence

that the bid price initially decreases with respect to n, the expected winning bid is

expected to decrease as n increases throughout (Dyer 1996). This phenomenon is

exemplified in Figure 5-1.

The conclusions of this model are that in a lowest price, sealed bid auction for a

construction project, risk averse bidders will tend to quote a higher price, risk seeking

bidders will submit a lower price, and risk neutral bidders will quote a price in the middle

of the two. The risk seeking bidders are therefore more likely to win the bid for the

construction project.









CHAPTER 3
METHODOLOGY

The aim of this study is to create a model that identifies and quantifies the

perceived risks that are associated with LEED construction. This will be done by

creating a spreadsheet that utilizes the Tang et al. model, location factors, information

from the GSA 2004 and Davis Langdon 2004 and 2007 studies and knowledge of risk

practices and the LEED process.

Standard Building Characteristics

This is the cost of construction that is related to a project that is not seeking LEED

certification. This is used to establish a base price for the project bid. This information

is generated from a database of costs generated by EVstudio and RSMeans and found

on-line (EVstudio 2010). These costs reflect the cost of educational facilities and was

generated using April 2010 RSMeans information providing a cost for college

classrooms, college dormitories, college student unions, and college laboratories. The

cost was provided for each of the building types in many locations throughout the United

States. The data that was generated by EVstudio is provided in Figure 3-1, Figure 3-2,

Figure 3-3, and Figure 3-4.

The square foot costs of the buildings are extremely varied, and the particular type

of building and location of the structure must be considered before the analysis. These

calculations are for use as an example only and costs that are associated with a

particular project should be used if the model is to be applied to a particular situation. It

should be noted that these costs are used to generate a cost for a specific area of the

country and will be later adjusted to reflect the type of demographic location that the

actual structure is located in.












Classroom
$250600 --






$f0000 6 -
4c 3 L-
























2010 from RSMeans data April 2010.



Dormitory


$150i -







2s
a









$5000oo





S $' -^ q q-gp

Location


Figure 3-2. Cost per square foot of college dormitory facilities generated by EVStudio
2010 from RSMeans data April 2010.
$ 3;0 0 -0 0 -,- g-------------------------------------------


$250-00 B H ^ S ^ ^-----------
























2010 from RSMeans data April 2010.













Student Union


$250.00



$200.00



$15000oo



$10000oo


so. o 1111 1 111111111111111








Location



Figure 3-3. Cost per square foot of college student union facilities generated by
EVStudio 2010 from RSMeans data April 2010.


Laboratory


$300-00


$250.00


$200.00
Szoo.oo


$150.00


$100.00


$50.00


$-


*1

.Hn -4 intmfl
rri C .H
"O lfl mm~ m
t~e LO~, LD
uceIf jo
rl Jvrnm


-a-ea-se-ss-ss mm mm mm sa-aa-aa-aa-a


Location



Figure 3-4. Cost per square foot of college student union facilities generated by
EVStudio 2010 from RSMeans data April 2010.









Level of Certification

The level of LEED certification that is desired will have an impact on the level of

risk to the contractor and therefore the value of the bids submitted for the construction

of the project. The values that will be used are based on the average cost premiums of

LEED certified projects as a percentage increase of the contract price. These

premiums were collected from the 2004 GSA cost study and are displayed in Table 3-1

Table 3-1. Percentage increases in cost of LEED certification from GSA 2004 study.
Maximum% Markup
Level of LEED Certification (Based on GSA Study) GSA Data Range
Certified: 1.00% -0.4% to 1.0%
Silver: 4.40% -0.03% to 4.4%
Gold: 8.10% 1.4% to 8.1%

Platinum level certification was not included in the 2004 GSA study or the table

above because the platinum level of certification requires an extraordinary level of

performance to attain the required point level. A percentage increase is included in the

model but is only applicable if the appropriate factors are known to an extent for the

model to be useful. These factors can be very project specific and without specific

information fall outside of the scope of the framework for the purposes of this model.

The information in the GSA study is used to produce the model, and is not

required for proper analysis. The GSA study was used because of the extent of data

that was available in the study, which was useful for developing the model. The results

of this study are certainly not appropriate for all scenarios. The percentages shown in

Table 3-1 can be changed to fit any particular scenario without adjusting the model.

The percentages in Table 3-1 are used to establish a baseline for the perceived

uncertainty and may be adjusted to fit a particular project but should be accompanied

with other data inputs that are consistent with that particular scenario.









Soft Costs

There are two types of costs that are represented in the increase in costs that are

seen in the construction of a LEED certified building (Northbridge 2003). These costs

are construction costs and soft costs. Soft costs are costs that are not directly related to

the construction of the building, but are necessary and in addition to original building

estimates. These costs are outlined as percentages in Table 3-2.

Table 3-2. Estimates of LEED related soft costs derived from the Northbridge
Environmental report 2003, p. 6.
Cost Category Estimated % Range
Design Costs 0.5% 0.4% 0.6%
Commissioning 1.0% 0.5%-1.5%
Documentation and Fees 0.7% 0.5% 0.9%
Energy Modeling 0.1% 0.1%
Total 2.3% 1.5%-3.1%
*For GSA data, use : 0.25%

The soft costs are considered part of the cost in achieving LEED certification, but

do not represent an increase in the cost to the contractor, except for a portion of the

documentation costs, and will therefore be subtracted from the total estimated LEED

mark-up for the project. The information that is supplied by the GSA study, when used

in the model, will reflect a lower percentage of soft costs since much of this additional

work is already included in the cost estimates. Subtracting the soft costs will allow the

analysis of only the costs associated with the direct construction costs of the building.

Risk Aversion

The risk aversion segment of this model will be based on the auction model

developed by Tang et al. 2006. This model is defined as:

(ch-ci) n--1 -
b,= c, + ( + n 6c, (2-2)

where:









* bi = expected bid from contractor i.

* c; = bidder i's perceived value of a project the common value of the auction, or
the base line construction estimate as provided by RSMeans.

* Ch = expected value of the high bid described as twice the bidder's perceived risk
to represent a worst case bidder.

* n = number of bidders determined by a base case number further refined by the
appropriate adjustments.

* 6 = risk behavior of contractor i determined by the risk aversion behavior of the
particular contractor.

* c/= perceived risk to contractor i product of the base price of the project, an
expected cost of LEED certification as determined in the GSA 2004 study to
represent LEED related risk in excess of the standard building risk, and the
Experience Factor.


Perceived Value; ci

The perceived value of the project is assumed to be the cost of the construction

that is related to the project based on the RSMeans estimate that was described in

"Standard Building Characteristics". Based on the Davis Langdon studies of 2004 and

2007, there is no measureable difference in the average value of a standard building

and the value of a LEED certified building. Following this, the value of the project to the

contractor should not be more than the estimated construction costs of the project.

LEED related costs are expected to be "extra" costs that are a factor of the LEED

Premium that is placed on general construction tasks due to the increased risk.

Assuming that this value is the same for all bidding parties defines the designation of a

"common value" auction, meaning that all bidders will receive the same benefit from

winning the contract. There is some debate as to whether this definition fits a

construction auction exactly, but for the purposes of modeling, this assumption must be

made.









High Bid; ch

Research on bid ranges showed that bid results can vary wildly dependent on a

variety of factors, and there is little data on predicting what a high bid will be. To set a

baseline for the model, the high bid is set to the perceived value, representing a

scenario in which all of the bids submitted at the same price, therefore not affecting

other bids. For the example project scenario the high bid is assumed to be the base

cost of the building, c;, plus twice the expected mark-up as related to certification level

defined in Table 3-1. This provides an ample range for bid prices, without disabling the

model. In a specific situation, the owner that is putting this contract out would generally

have an accurate representation of this number. For the purposes of the model, this

number only needs to be predicted to demonstrate the behavior of the other variables.

Number of Bidders; n

The number of bidders (n) is entered as an expected value that is then adjusted

for several environmental factors collectively referred to as the "bidding environment".

The initial number of expected bidders would have to be determined from historical

precedence that would be specific to the type of project that is being constructed. For

the purposes of normalizing this model, a base case of 10 expected bidders was used.

This number decreased as the level of certification increased as shown in Figure 3-6.

This number would then be adjusted for economic conditions as described by the

bidding climate and economic factor.

Bidding climate/economic factor. The strength of the economy at the time of

the auction will affect the number of bids that are submitted. This phenomenon is

described in the "LEED Associated Risk" section and is determined using the data in

Table 3-3. The economic factor is multiplied by the number of bidders expected under









normal conditions to simulate a reduction in n during stronger economic times or an

adverse bid climate. If the number of bidders is known previous to the construction of

the model, this factor can be ignored, but determination of the number of bidders is

important to the accuracy of the model, and should be adjusted accordingly to match

the expected bidding environment.

Table 3-3. Economic factor multipliers for the base case of the risk model.
Bid Climate Factor
Very Restricted Climate 0.50
Restricted Climate 0.75
Stable Climate 1.00
Open Climate 1.25
Very Open Climate 1.50

Risk Behavior; 6

The risk behavior of a particular contractor must be identified and entered into the

model. This factor will be different for each particular contractor, and may vary with

time. This factor is more clearly defined in the section titled "Risk". This factor is

defined directly from the chart in Table 3-4 and entered into the model. This factor

represents the risk-aversion behaviors of the contractor that is bidding on the project.

"Very risk averse" would mean that the contractor has a strong aversion to taking on

any additional risk, while a "Very risk seeking" bidder would be willing to take on more

risk in a project. This factor is applicable to the current project only, and may differ for

the same contractor when considering other projects.

Table 3-4. Table for determination of the risk factor for a particular contractor.
Risk Policy Factor
Very risk averse 1.0
Somewhat risk averse 0.5
Risk Neutral 0.0
Somewhat risk seeking -0.5
Very risk seeking -1.0










Experience

The experience in bidding and construction for a particular contractor will have an

effect on the bid that is submitted. The factors that are used to define the Experience

Factor for a specific contractor are shown in Figure 2-9. This factor is used to represent

the amount of experience that a certain contractor has in a specific type of construction.

In this case the contractor's experience would be experience with LEED certified

projects, though experience with general construction relative to the project would play

a part in determining this factor. This factor may also vary among the levels of LEED

certification. If a contractor had extensive experience in LEED certified buildings but

had never constructed any building higher than LEED Silver, the experience factor may

be less if the certification level desired is Gold or Silver. An experience level of 1

represents an average level of experience in the type of project being considered. The

potential values shown in Table 3-5 reflect potential values, but does not represent the

limits of these values.

Table 3-5. Determination of experience factor for a specific bidder, relative to a specific
project.
Experience Level Factor
Very Experienced Bidder 0.90
Experienced Bidder 0.95
Average Experience 1.00
Very Little Experience 1.15
Inexperienced Bidder 1.30

Experience will be related to the particular project with a specific contractor. LEED

related projects often pursue varying strategies for achieving points, and experience

with a strategy in the past could have an effect on the experience of the contractor.

Experience with a certain level of certification could also affect this value. Location









could also play a part, if the contractor has performed multiple projects in the location

and is familiar with the local requirements and conditions.

Location

The results from the model and the inputs must be subjected to a further

adjustment for the location of the project. From the Tang et al. (2006) model there is

determined what will be called a "LEED Uncertainty Cost". This is the amount of extra

cost that would be added onto the original building price for the total in the contractor's

bid. The final adjustments that must be made for this price are:

Proximity to services. The Davis Langdon study of 2004 determined that there

are benefits from having a project in an urban setting. This phenomenon is examined in

depth in the "Cost of LEED" section of this study. The factors in Figure 2-10 are used to

reflect the effect of demographic location on the expected bid price. These factors are

specific to this example, as extraordinary conditions may exist for a specific project.

This could occur if the project is located in an area that is particularly capable of

providing services or infrastructure that is beneficial to the LEED rating system. It

should be noted that locations exist where LEED is impossible to attain or is

prohibitively expensive. This model assumes that neither of these conditions exist and

that there are no extremely adverse conditions that occur that limit the feasibility of the

project.

Table 3-6. Factors for determining costs related to the proximity to urban centers. Data
derived from Mathiessen and Morris 2004
Proximity to Services Factor
Very urban location 0.50
Somewhat urban location 0.75
Suburban location 1.00
Somewhat rural location 1.25
Very rural location 1.50









Climate factor. The climate that a project is located in also has an effect on the

amount that LEED certification will cost. The additional cost associated with the climate

that a project is located in is defined in the Davis Langdon study of 2004. The results of

that study are shown in Table 3-7.

Table 3-7. Percentage increase in LEED costs as related to climate. Data derived from
Mathiessen and Morris 2004.
Location Certified Silver Gold Platinum
Mild Coastal 1.00% 2.70% 7.80%
California Central Valley 3.70% 5.30% 10.30%
Gulf Coast 1.70% 6.30% 9.10%
Northeast Coast 2.60% 4.20% 8.80%
Rocky Mountain 1.20% 2.80% 7.60%
Average Increase: 2.04% 4.26% 8.72%

The percentages shown in Table 3-7 are increases in LEED costs over standard

construction costs and are related to energy use, cost of energy, temperature

fluctuations and relative humidity.

Location factor. The two factors related to the location of the project have been

combined into what will be called the Location Factor. The factor is the product of the

proximity multiplier and the percentage increase defined in Table 3-7 as the Climate

Factor. The table shown in Table 3-8 shows the result of this calculation. The column

for Location Factor is the result of subtracting the Location Percentage Increase from

the Average Location Increase and multiplying the result by the Proximity Factor.

Table 3-8. Calculations for Location Factor.
Certification Location % Proximity Average Location Location
Level Increase* Factor Increase Factor
Certified 0.00 0.00% 0.00%
Silver 2.04% 0.00 2.04% 0.00%
Gold 4.26% 0.00 4.26% 0.00%
Platinum 8.72% 0.00 8.72% 0.00%









Assumptions

The Davis Langdon (2004) study outlined seven factors that affect the cost of

LEED certification. Of the seven the first three will be used to calculate expected bids

using the model described. These three factors are:

1. Demographic Location
2. Bidding Climate and Culture
3. Climate

Assumptions are made involving the remainder of the factors listed in the Davis

Langdon (2004) study. These remaining factors are assumed to be true and constant.

4. Project owners and team members are fully invested in the certification of the
building

5. The goals of certification are outlined sufficiently earlier in the project to avoid any
negative effects, and the design is as fully developed at time of bidding as is
normally expected

6. The size of the building only affects the overall cost of the building and systems,
and the relative cost is unchanged over a reasonable range of costs and building
size

7. Point synergies will be used to all possible effect for each given project. This will
be different for each building, and would be impossible to predict for a general
sampling.

For the purposes of this model, factors 4 -7 are assumed to be normal and

average. This does not indicate that this is the case in all construction projects. These

factors are likely to be variable in a real world scenario, but to make this model effective

and valid these must be assumed so that heterogeneity of the data may be preserved.

For this reason the factors will be divided into five categories. The first three categories

will represent 3/5 of the LEED/Risk Premium, with the final four categories representing

2/5 of the LEED/Risk Premium as ghost categories that are assumed to not affect the

amount of perceived risk for the purposes of this model.









Calculations

The factors and costs that were addressed in "Modeling Factors" will be used to

calculate the risk based LEED costs and bid amounts. The flow of the calculations is

outlined in Figure3-5, and the spreadsheet form is shown in Figure 3-6.

Calculation Inputs for Expected Risk-Adjusted LEED Construction Bid


(A)
Standard Building Cost
(RSMeans)


(B.C)
Level of Certification





I
(E)
Expected LEED Premium


(F.G)
Risk Aversion Premium


(H.1)
Location Premium

(D)
Experience Factor

Assumed Factors



I
(JK)
Calculated LEED Premiumn


(K)
LEED/Risk Based
Premium

(M)
Total Expected Bid
Amount






Expected Risk-Adjusted
Bid Amount


Figure 3-5. Interactions of the factors and costs associated with the calculation of LEED
premium.

Calculation Table

The calculations are listed by column as follows from Table 3-9:

A. Base Cost This is the cost of the building without any LEED certification. This is
generated from RSMeans and is adjusted for the project location.

B. Certification Level This is the level of LEED certification that is desired. This is
defined as Certified, Silver, Gold, and Platinum.

C. Average LEED Risk % This is the average LEED percentage markup that was
found in the GSA (2004) study. This value is applied to the Base Cost as a
baseline value and to provide inputs for other equations including high bid and
perceived risk.




69









D. LEED Uncertainty This is the cost increase that is expected to be seen based on
the cost of a standard building, the level of certification that is desired, and the
experience level of the contractor submitting the bid.

E. Risk Aversion Factor This is the factor that is described by the Tang et al. (2006)
risk model. This model takes into account the perceived value of the project, the
expected number of bidders, the expected high bid, the perceived risk to the
contractor, and the risk tendencies of the contractor. The factor is defined as the
difference ratio of the expected bid price to the perceived value of the contract.

F. Risk Aversion Premium The premium, in dollars, that is a result of the increase
of the bid price using the Risk Aversion Factor. This is a portion of the total
increase in the cost found in Column K. This factor is assumed to make up 80% of
the value of the total increase found in Column K.

G. Project Location Factor This factor is related to the difference of the cost of
LEED certification in different geographical locations.

H. Location Premium The premium, in dollars, that is added to the base price of the
building to achieve LEED certification. This is a factor of the total LEED risk price
and is assumed to make up 20% of the total increase found in Column K.

1. Experience Factor This factor is determined from the table shown in Figure 25
and is entered directly into the spreadsheet. This value may differ for different
levels of certification.

J. Calculated LEED Premium % This is the increase, in percentage, that is
observed from the calculated LEED/Risk based premium and the Base Cost of the
building.

K. Calculated LEED Premium This is the total result of the calculations including
the Risk Aversion Premium, the Location Premium, and the Experience Factor.
Represents the total cost increase over the Base Cost that is expected.

L. LEED Premium Baseline Value of LEED costs when no other factors are
included. Represents the average current cost of LEED construction and is used
as a baseline to compare other calculations.

M. Total Expected Project Cost The base cost of the project plus the anticipated
LEED/Risk Based Premium.

N. LEED Related Soft Costs Calculated at 1.6% of the construction costs. This
cost represents the soft costs that are not directly bore by the contractor.

O. LEED Based Increase in Construction Costs Represents the increase in costs
that can be expected over the standard costs of a building.









P. Total Risk Adjusted Bid Price Value of the bid that can be expected to be
submitted by contractor i for the given LEED certified project.









Table 3-9. LEED Premium and Bid Amount calculation table.
From
From Table 3 Ax C x I (or Table 9 From Table
Table 2 Column B Entry x I) Column H 0.8 x Dx E 12 0.2 x D x G From Table 7
A B C D E F G H

Risk Risk
Average Perceived Aversion Aversion Project Project
Base Certification LEED LEED Factor [- Premium Location Location Experience
Cost Level Risk % Uncertainty 1,1] ($) Factor [-1,1] Premium ($) Factor
$ Certified 1.00% $ 0.00% $ 0.00% $ 0
$ Silver 4.40% $ 0.00% $ 0.00% $ 0
$ Gold 8.10% $ 0.00% $ 0.00% $ 0
$ Platinum 12.00% $ 0.00% $ 0.00% $ 0


Table 13
K/A (F + H)xl A + D A + K Value xA K- N A + O
J K L M N O P
Value
Using Total Additional
LEED LEED/Risk Average Expected LEED Related Total Bid for
Premium Based Bid Risk Project Construction Construction
% Premium Scenario Cost Soft Costs Costs Costs
0.00% $ $ $ $ $ $
0.00% $ $ $ $ $ $
0.00% $ $ $ $ $ $
0.00% $ $ $ $ $ $









CHAPTER 4
ANALYSIS

To represent the method of using the model developed in this study, an example

will be used for demonstration. A baseline scenario will be conducted to verify the

accuracy of the model, and then an analysis of the input factors will be performed.

Example Project

Project

This project will be a college classroom in Atlanta, Georgia. This building will

encompass 55,000 square feet and will be evaluated for potential costs related to LEED

certification. The project is located in a dense urban area. The project is expected to

occur during a time of strong economic growth, with an open bidding environment.

Bidder

The model proposed is sensitive to the specific properties of the bidder. The

bidder is a large company that is rated very risk averse. The bidder has relatively little

experience in LEED related projects.

Analysis

Base Price

The base price of the structure, in Atlanta, Georgia, is calculated using the

RSMeans tables. Calculated value is $8,283,000.00

Level of Certification

Table 3-1 shows the expected (average) costs for the corresponding level of LEED

certification. These factors are based on the 2004 GSA study and are appropriate for

this type of building. All of the factors will be applied to demonstrate the use of the









model. It should be noted that for this example, the highest cost estimations will be

used from the GSA 2004 study.

Table 4-1. Expected LEED costs for example 55,000 square foot classroom in Atlanta,
GA with a base value of $8,283,000. Maximum mark-up amounts will be
used for the example. Values based on GSA 2004 data.
From GSA or Enter Value Table 2 value x B Table 2 value + C
A B C D
Level of Additional
LEED % Markup (Based on GSA Perceived Risk Total Expected
Certification Study) Premium Building Cost
Certified: Max 1.00% $82,830 $8,365,830
Min -0.4% $(33,132) $8,249,868
Silver: Max 4.40% $364,452 $8,647,452
Min -0.03% $(2,484) $8,280,515
Gold: Max 8.10% $670,923 $8,953,923
Min 1.4% $115,962 $8,398,962
Platinum*: Max 12.00% $993,960 $9,276,960
*No data exists in the GSA 2004 study for Platinum level certification.

Baseline Case

First, an analysis showing the average or expected value of the project with the

associated LEED certification scenarios. In this case, all variables will be set to the

assumed average default value to validate the accuracy of the model. The results of

this analysis are shown in Table 4-2. In the baseline case, the expected bids and costs

are equal to the increases that are expected to be observed. This reflects an average

scenario that does not take into account the specific factors associated with a particular

project and contractor. From this analysis it can be shown that the expected total costs

are as follow in Table 4-3 and 4-4. The relationships between the expected and

standard costs are outlined and reflect the calculations in the model.

Note that the expected cost of the structure is equal to the calculated cost as

shown in Table 4-2, and the expected values in Table 4-3. This shows that the model is









Table 4-2. Calculation of costs in the baseline scenario.
From
Table 3
From Table Column A x C x I (or Table 9 From Table
2 B Entry x 1) Column H 0.8 x Dx E 12 0.2 x D x G From Table 7
A B C D E F G H I
Risk
Average Perceived Risk Aversion Project Project
Certification LEED LEED Aversion Premium Location Location Experience
Base Cost Level Risk % Uncertainty Factor [-1,1] ($) Factor [-1,1] Premium ($) Factor

$8,283,000 Certified 1.00% $95,254 1.13% $77,067 0.00% $19,050 1.15

$8,283,000 Silver 4.40% $419,119 5.13% $352,507 -0.51% $83,396 1.15

$8,283,000 Gold 8.10% $771,561 9.90% $678,356 1.02% $155,886 1.15

$8,283,000 Platinum 12.00% $1,143,054 15.20% $1,053,438 0.19% $229,045 1.15


A+D
L

Value Using
Average Risk


A+K
M
Total
Expected
Project


Table 13
Value x A
N


K-N
0
Additional
LEED Related
Construction


A+O
P

Total Bid for
Construction


% Premium Scenario Cost Soft Costs Costs Costs

1.16% $96,118 $8,378,254 $8,379,118 $20,550 $75,567 $8,358,567

5.26% $435,904 $8,702,119 $8,718,904 $21,344 $414,559 $8,697,559

10.07% $834,243 $9,054,561 $9,117,243 $22,209 $812,033 $9,095,033

15.48% $1,282,483 $9,426,054 $9,565,483 $23,120 $1,259,363 $9,542,363


K/A
J

LEED
Premium


(F + H) x I
K

LEED/Risk
Based Bid










Table 4-3. Determination of baseline analysis.


Certification LEED
Level Base Cost Average Cal
Certified $8,283,000 8,378,254 $8,,
Silver $8,283,000 8,702,119 $8,;
Gold $8,283,000 $9,054,561 $9,1
Platinum $8,283,000 9,426,054 $9,,

Table 4.4. Determination of baseline analysis.


culated
379,118
718,904
117,243
565,483


LEED Increase Compared to
Average
%
$ Difference Difference
$ 863.64 0.01%
S 16,784.35 0.19%
S 62,681.65 0.69%
$ 139,429.73 1.48%


Total Project Increase
Compared to Non-LEED
Certification Base LEED %
Level Cost Average $ Difference Difference
Certified 1.00% 1.16% $ 96,118.14 1.16%
Silver 4.40% 5.26% $ 435,904.15 5.26%
Gold 8.10% 10.07% $ 834,243.10 10.07%
Platinum 12.00% 15.48% $ 1,282,483.73 15.48%

capable of predicting the baseline scenario when all of the variables are set to assumed

normal conditions. There is no difference in the calculated values versus the expected

values. The effects of the changes to these variables are all based on this scenario, to

more easily determine the effects of the changes of certain conditions. Following the

establishment of this baseline, the variables associated with the specific case will now

be input.

Bid Climate

The climate of the bidding pool and environment must be determined. These

factors are described using the Economic Factor (Table 4-5) to determine the number of

bidders and the Experience Factor (Table 4-6) to determine perceived risk in the final

analysis. The economic factor affects the number of bidders, and the experience factor

affects the perceived risk to the contractor. Heightened experience levels result in a

lower perceived risk.









Table 4-5. Economic factor determination will result in the selection of 0.75 reflecting a
strong external economic condition and restricted bid environment.
Climate Description Factor
Very Restricted Climate 0.50
Restricted Climate 0.75
Stable Climate 1.00
Open Climate 1.25
Very Open Climate 1.50

Table 4-6. The determination of the Experience Factor will result in the selection of a
factor of 1.15.
Experience Level Factor
Very Experienced Bidder 0.70
Experienced Bidder 0.85
Average Experience 1.00
Very Little Experience 1.15
Inexperienced Bidder 1.30

The number of bidders is assumed to be 10 in an ideal environment. The

Economic Factor and the Level of Certification are used to adjust this number based on

the bidding environment as shown in Table 4-7.

Table 4-7. Determination of the number of bidders.
Expected # of
Level of Certification Bidders Bid Climate Factor # of Bidders
Certified 10 0.75 8
Silver 8 0.75 6
Gold 6 0.75 5
Platinum 5 0.75 4

Risk Aversion

The example bidder is described as very risk averse, which will result in an

elevated Risk Aversion Factor. A Risk aversion factor of 1.0 has been selected to

correlate with the determination that the bidder is very risk averse. This will serve to

elevate the effect of the amount of perceived risk involved in the project. The

determination of this factor is shown in Table 4-8.









Table 4-8. Determination of bidder's Risk Aversion Factor. A factor of 1.0 has been
selected to represent the example scenario.
Description of Bidding Entity 6
Very risk averse 1.0
Somewhat risk averse 0.5
Risk Neutral 0.0
Somewhat risk seeking -0.5
Very risk seeking -1.0
Using the Tang et al. 2006 model and the inputs that have been derived thus far

the amount of the bid based on uncertainty can be determined as shown in Table 4-9.

The Tang et al. 2006 risk model is defined as:

(Ch-ci) n-1 -
b, = c, +( + n 6c, (2-2)

where:

* bi = expected bid from contractor i
* ci = bidder i's perceived value of a project
* Ch = expected value of the high bid
* n = number of bidders
* 6 = risk behavior of contractor i
* c i= perceived risk to contractor i

Table 4-9. Risk Aversion calculation using the model described in Tang et al. 2006.
Level of
Certification Perceived Value Expected Bid Value Risk Aversion Factor
Certified $8,283,000 $8,376,874 1.13%
Silver $8,283,000 $8,708,194 5.13%
Gold $8,283,000 $9,103,017 9.90%
Platinum $8,283,000 $9,542,016 15.20%

Location

The location of the project is in Atlanta, Georgia, which will be considered a gulf

coast location for the purpose of using the Davis Langdon 2004 location adjustments.

The appropriate Proximity Factor has also been selected to represent the fact that the

project is located in a downtown urban location. The combination of these factors is

defined in Table 4-10.









Table 4-10. Adjustment factors for location of the example project.
Certification Location % Proximity Average Location Location
Level Increase* Factor Increase Adjustment
Certified 0.50 0.00% 0.00%
Silver 1.70% 0.50 2.04% -0.51%
Gold 6.30% 0.50 4.26% 1.02%
Platinum 9.10% 0.50 8.72% 0.19%

The Location Adjustment represents the aggregate effects of the Location

Increase and the Proximity to Services. The observed negative value under the

Certified level scenario shows that due to the location of the project, the cost is less

than the average increase that is expected.

Soft Costs

Soft Costs represent the value of the costs that are not directly related to the

construction of the project. Since this example is using the GSA costs for analysis,

most of these costs are included in the price increase, and can be left out. The increase

in soft costs for the GSA analysis result in an increase of 50 cents per square foot, or

0.25% of the per square foot cost. The result will be a soft cost value of 0.25% that will

represent the cost of Documentation and Fees. This cost will be used since it is also

applicable in an institutional environment such as a college campus. Many institutional

entities use the same type of standards that the GSA uses, and these calculations are

more appropriate. Since this project related to a school campus the data from the GSA

study is appropriate. This will vary for each scenario, but for this example it will be

assumed that the institution in question is using standards similar to the GSA including

requiring commissioning, and minimum energy performance. This cost is quantified in

Table 4-11, and is expressed as a percentage of the overall costs of the construction

project. Note that in the GSA study this is calculated as a per square foot cost.









Table 4-11. Estimated Soft Costs. 0.25% will reflect GSA data.
A B C
Cost Category Estimated % Range
Design Costs 0.5% 0.4% 0.6%
Commissioning 1.0% 0.5%-1.5%
Documentation and Fees 0.7% 0.5% 0.9%
Energy Modeling 0.1% 0.1%
Total 2.3% 1.5%-3.1%
Enter Soft Costs: 0.25%

Expected Costs

The results of the analysis are shown in Table 4-13.

Results

This example highlights the effects of the decision to pursue LEED certification on

the expected overall and construction costs of the project. The increase that is shown

in the example is greater than the baseline case due to the following factors:

* High risk aversion factor
* Decreased number of bids due to the effects of the bidding climate
* Increased costs due to the lack of experience of the contractor

The results of the calculations in the example case are highlighted in Figure 4-12.

Table 4-12. Comparison of baseline case to example scenario.
LEED Increase Compared to Average
$ Difference % Difference
$ 863.64 0.01%
$ 16,784.35 0.19%
$ 62,681.65 0.69%
$ 139,429.73 1.48%
Total Project Increase Compared to Non-LEED
$ Difference % Difference
$ 96,118.14 1.16%
$ 435,904.15 5.26%
$ 834,243.10 10.07%
$ 1,282,483.73 15.48%









Table 4-13. Results of model calculations using the example scenario showing the costs of LEED certification.
From Table From A x C x I (or Table 9 From
2 Table 3 Entry x I) Column H 0.8 x Dx E Table 12 0.2 x D x G From Table 7
A B C D E F G H
Project
Average Perceived Risk Location
Certificati LEED LEED Aversion Risk Aversion Factor [- Project Location Experience
Base Cost on Level Risk % Uncertainty Factor [-1,1] Premium ($) 1,1] Premium ($) Factor
$8,283,000 Certified 1.00% $95,254 1.13% $77,067 0.00% $19,050 1.15
$8,283,000 Silver 4.40% $419,119 5.13% $352,507 -0.51% $83,396 1.15
$8,283,000 Gold 8.10% $771,561 9.90% $678,356 1.02% $155,886 1.15
$8,283,000 Platinum 12.00% $1,143,054 15.20% $1,053,438 0.19% $229,045 1.15

K/A (F+ H)xl A+ D A+ K K- N A+O
J K L M N O P
Additional LEED
LEED LEED/Risk Value Using Total Related Total Bid for
Premium Based Bid Average Expected Construction Construction
% Premium Risk Project Cost Soft Costs Costs Costs
1.16% $96,118 $8,378,254 $8,379,118 $20,550 $75,567.71 $8,358,567
5.26% $435,904 $8,702,119 $8,718,904 $21,344 $414,559 $8,697,559
10.07% $834,243 $9,054,561 $9,117,243 $22,209 $812,033.80 $9,095,033
15.48% $1,282,483 $9,426,054 $9,565,483 $23,120 $1,259,363 $9,542,363









Sensitivity Analysis

A sensitivity analysis has been performed to demonstrate how the LEED related

costs change as the inputs are altered. The purpose of the model is to be able to see

the relationships between the variables that affect the costs of LEED construction, and a

sensitivity analysis will help to highlight these effects.

A sensitivity analysis was conducted and the results are shown in Figures 4-1 to 4-

7. This analysis will help to evaluate the effects and relationships that are involved in

the model. The supporting data is found in Appendix A.

Certified Level Building

The analysis of this building is shown in Figure 4-1. The most sensitive factor of

the ones that are depicted here is the risk aversion factor. Proximity to services has no

effect as this was the result of the Davis Langdon (2004) study. The strength of the

economy had the predicted effect of increasing costs as the economy became stronger.

This is due to the increased risk aversion of the bidders and the resultant decrease in

the number of bidders that are willing to submit a bid on the project. This effect is small,

as predicted for a Certified level project, since the perceived risk of this level of

certification is relatively small.

Silver Level Building

The analysis under the Silver level of certification is shown in Figure 4-2. The

most sensitive factor of the ones that are depicted here is the risk aversion factor.

Proximity to services has a small effect as this was the result of the Davis Langdon

(2004) study. The strength of the economy had the predicted effect of increasing costs

as the economy became stronger. This is due to the increased risk aversion of the

bidders and the resultant decrease in the number of bidders that are willing to submit a









bid on the project. This effect is small, as predicted for a Silver level project, since the

perceived risk of this level of certification is relatively small, but is noticeably larger than

the effect of the economy that was seen in the Certified level project. This is due to the

higher level of risk that is associated with the higher level of certification.

Gold Level Building

The analysis of the Gold level certified building is shown in Figure 4-3. The most

sensitive factor of the ones that are depicted here is the risk aversion factor. Proximity

to services has a small effect as was the result of the Davis Langdon (2004) study. The

strength of the economy had the predicted effect of increasing costs as the economy

became stronger. This is due to the increased risk aversion of the bidders and the

resultant decrease in the number of bidders that are willing to submit a bid on the

project. This effect is larger, as predicted for a Gold level project, since the perceived

risk of this level of certification is relatively large, and is noticeably larger than the effect

of the economy that was seen in the Certified and Silver level projects. This is due to

the higher level of risk that is associated with the higher level of certification. The

additional risk results in a lower number of bidders that are willing to compete for the

project, and this is increased as the economic condition strengthens.

Platinum Level Building

The analysis of the Platinum level building is shown in Figure 4-4. The most

sensitive factor of the ones that are depicted here is the economic factor, surpassing the

effects of the Risk Aversion Factor. Proximity to services has a small effect as was the

result of the Davis Langdon (2004) study. The strength of the economy had the

predicted effect of increasing costs as the economy became stronger. This is due to the

increased risk aversion of the bidders and the resultant decrease in the number of









bidders that are willing to submit a bid on the project. This effect is very large, as

predicted for a Platinum level project, since the perceived risk of this level of certification

is large, and is noticeably larger than the effect of the economy that was seen in the

other levels of certification. This is due to the higher level of risk that is associated with

the highest level of certification. The additional risk results in a much lower number of

bidders that are willing to compete for the project, and this is amplified as the economic

condition strengthens.

Risk Aversion

The analysis of the effect of risk aversion is shown in Figure 4-5. Increases are

relatively small for the lower levels of certification since the perceived risk to the

contractors is small. Since the risk is small, even the most risk averse contractors do

not place a large additional premium on the construction costs. This condition changes

as the level of certification rises. As higher levels of certification are pursued, the

amount of risk to the contractor is increased. For risk-seeking contractors, this has less

of an effect than that seen with the risk-averse contractors. As the perceived risk, and

the risk-aversion of the contractor increases, the total effect on the cost of the project

begins to amplify more quickly. This effect would be more pronounced if the perceived

risk is increased, or the contractor has a higher level of risk aversion.

Number of Bidders

The analysis of the effect of the number of bidders is shown in Figure 4-6. This

effect increases as the level of certification that is being pursued is increased, due to the

level of risk that is associated with the level of certification. Larger numbers of bidders

has the effect of heightened competition which drives down the cost of the project.

When put into the model, the effect of having a very small number of bidders increases










steeply as the certification level rises. If a project has a small number of expected

bidders, the owner should take actions to increase the number of bidders. This could

be accomplished by lowering the level of certification as shown in this figure.

Experience

The analysis of the amount of experience that the contractor has is shown in

Figure 4-7. This demonstrates the amount of the increase in LEED related costs are a

function of the perceived risk of the contractor and the amount of experience that the

contractor has in that particular type of building. As experience increases, perceived

risk diminishes and becomes part of the standard cost. This has the effect of removing

the volatility of the price increase since the additional costs are no longer affected by the

risk policies of the bidder. This accurately reflects the limited experience that

contractors have with higher levels of LEED certification and the large cost increases

that are associated with these projects.


LEED Certified


$84,00000
$83,800o0
$83,60000
$83,400.00
t $83,200 00
S$83,000 00
A $82,80000

S$82,60000
$82,400.00
$82,200.00
$82,00000


--4Economic Factor
--Proximity to Services


1.0 0.5 0.0 -0.5 -1.0
Factor Value

Figure 4-1. Graphical representation of the effects on certain variables on the LEED
associated increase of construction costs on a Certified level building.











LEED Silver Certification


assoooo.oo


$370,000.00
$3so,ooo.oo

$365,000.00

$360,000.00

$355,000.00

$350,000.00

$345,000.00

$340,000.00


1.0 0.5 0.0 -0.5 -1.0

Factor Value

Figure 4-2. Graphical representation of the effects on certain variables on the LEED
associated increase of construction costs on a Silver level building.


LE ED Gold Certification


- ,-Economic Factor
I- Proximity to Services


1,0 05 0.0 -0. -1.0

Factor Value

Figure 4-3. Graphical representation of the effects on certain variables on the LEED
associated increase of construction costs on a Gold level building.


--3

--Economic Factor

Proximity to Services


5720 000 00


$700,000.00


$680 000 00


5660 000 cc00


5640 000 00


$520 000 00


SPo0 000 00


4L^












LEED Platinum Certification


$1 150 000 00


$1,100,000.00

$1,050,000.00

$100000000

$950.000 00


$900 000 00

$850 000 00


i--0-

---Economic Factor

-U-Proximity to Services


1.0 0.5 0.0 -0.5 -1.0


Factor Vaue

Figure 4-4. Graphical representation of the effects on certain variables on the LEED
associated increase of construction costs on a Platinum level building.


Risk Aversion


1.200.0o00o 0


51.000 C00.00




$500.000.00




$400.000 00


S200 000.00


- E-- -


--Platinumr
*-Gold
Silver
--Ce rtified


1.0 0.5 0-0 -05 -1.0
Risk Aversion Factor

Figure 4-5. The effects of various risk aversion behaviors on the additional cost of
LEED construction.


L









Number of Bidders


Ia


2500000

2000000

1500000

1000000

500000


IIhhhI


10
Numberof Bidders


mCertified mSilver Gold mPlatinum
Figure 4-6. The effect of the number of bidders has a definite effect on the increase in
construction costs of a LEED project.

Experience Factor


1600000
1400000
1200000
1000000
800000
600000
400000
200000


0.7 0.5 1 1.15 13
Experience Factor


1Certified ESilver Gold EPlatinum
Figure 4-7. The effects of the level of experience of the contractor and the level of
certification.


-I


=11 I""









CHAPTER 5
SUMMARY AND CONCLUSIONS

Summary

Green building, while becoming the standard in modern construction, still has risks

involved from the view of the contractor. This is evidenced by the increase in the bid

price that is seen in projects that pursue a level of green certification under a building

rating system such as the LEED system that has become enormously popular in the

United States. The level of risk that is included in a project varies, and the behaviors

that the contractor follows to deal with this risk vary also. While each project is unique,

the goal of this study is to help to define some of the interactions that occur between the

variables that define the included risk and the ways that this can affect a construction

project. This was accomplished through the use of a model that allows the calculation

of an expected bid price based on a number of variables and assumptions that take into

account; standard building price, perceived risk, risk aversion policies, bidding

environment, experience, and location factors. This model can be used to examine the

interactions between these factors, and the resultant effects on the price of a project.

Conclusions

This study produced a number of meaningful conclusions. Through the sensitivity

analysis it can be shown how the variables included in the model interact with each

other. From this analysis of an example project, it was seen that the factor that had the

most impact on the project price was the bidding environment. When the bid

environment becomes too hostile, the bid prices that are seen tend to spike, particularly

in the higher levels of certification as shown in Figure 5-1. This is due to the severe

decrease in the number of bidders that are willing to bid on the project. As the number










of bidders approaches zero, the cost of the project goes to infinity. As the number of

bidders increases, the price comes down, but at a slower rate as the number of bidders

gets larger. This creates an optimal range of the number of bidders that is project

specific and should be analyzed.


Number of Bidders
Gold Level Project

$780,000-00
$740,000.00

S $740,000.00

S$720o,o.oo

I $7\oooo

.= Number of Bidders
S$so,6Qoo 00


$620,000.00
$640,000.00 .

$620,000.00 i i i i i i i i i i i i i i 1 1 1 1i -i
1 3 5 7 9 11 13 15 17 19 25 35 45 60 80 100
Numberof Bidders

Figure 5-1. Effects of the number of bidders on a LEED Gold project.

The perceived risk that the bidder recognizes is pushed through to the owner as

an increase in the cost of a project. This perceived risk is then amplified or partially

negated by the risk behavior of the contractor. If high performance buildings are to

become the standard buildings in the future and be priced similarly, this perceived risk

must be eliminated. What remains to be seen is whether this additional price will be

absorbed into the standard building price, or will be removed entirely. If it were

absorbed into the standard building price, the cost of these buildings would not be

reduced, but the variations in the bids would become smaller as experience increased









and the extra cost would cease to be an extra risk premium and would become part of

the standard building cost. The other option is that the cost currently associated with

risk could disappear. If this cost is solely based on risk and has no grounding in actual

costs, then the cost may vanish as the contractor pool becomes more sophisticated.

The true solution is probably somewhere in the middle. There is evidence that

LEED projects do cost more, such as direct costs that are required for enhanced

documentation, and extended schedules. These costs though, are relatively minimal.

Most of the extra cost that is witnessed in certified projects stems from the perceived

risk of the contractor, and the negative effect on the bidding environment that this risk

entails. As contractors become more experienced perceived risk should be reduced.

Contract language will be refined that will appropriate risk in a more standardized

manner, allowing for the construction industry to become accustomed to this type of

environment. This will promote a more open bidding environment that will allow for a

more beneficial, competitive auction environment.









CHAPTER 6
RECOMMENDATIONS FOR FURTHER STUDY

Some interesting opportunities for future research are presented in this study. The

model should be used to evaluate real world data and applied to a specific situation. A

particular owner could learn how their decisions could affect expected bids, of a

contractor could use this tool to become more aware of the bidding environment that

they are entering into. This may make the participant more educated on the factors that

affect decisions in this arena.

One area is in the effects that contract language has on the perceived risk to the

bidder in a green building scenario. Some contracts have wording in them that makes

certification such as LEED the responsibility of the contractor. This is questionable

since most of the LEED credits are geared toward design. Examining how contractors

are dealing with this could provide further insight into the decision process when

submitting a bid. Examining the appropriate risk allocation in the contract documents

and the effects that these have could go a long way in eliminating some of the

perceived risk that results in increased costs.

Another potential area of study would be the bidding environment that exists for

this type of project. This study showed that the bidding environment can have a very

significant effect on the bid prices that are offered. A closer look at factors that are

producing an unnecessarily hostile bid environment should be looked at, as this could

increase costs sharply. An environment that is too open could also increase costs due

to an overabundance of inexperienced bidders.

A closer study of the make-up of the risks perceived by contractors could also be

performed. This extra cost is generally considered by the contractor, but many of them









probably don't even realize it. If a contractor is adjusting a bid up 8% to account for the

additional risks involved, where is this number coming from, and is the contractor aware

of what is going into this cost? A good question to a pool of contractors could be to ask

them to list the risks that they feel they are subject to on a certified green project and

quantify the level of each. Different answers would probably be telling of the bid

environment and the contractors risk aversion principles.









APPENDIX
SUPPORTING DATA


Table A-1. Supporting data for sensitivity analysis.
Certified
6 Number of Bidders
% $ Increase in $ Increase in LEED
6 Increase LEED Cost n % Increase Cost
1.0 1.01% $83,558.90 1 1.02% $84,155.28
0.5 1.01% $83,260.72 5 1.00% $83,095.06
0.0 1.00% $82,962.53 10 1.00% $82,962.53
-0.5 1.00% $82,664.34 50 1.00% $82,856.51
-1.0 0.99% $82,366.15 100 1.00% $82,843.25
Silver
6 Number of Bidders
% $ Increase in $ Increase in LEED
6 Increase LEED Cost n % Increase Cost
1.0 4.57% $378,563.58 1 4.71% $390,109.42
0.5 4.50% $372,790.66 5 4.46% $369,583.48
0.0 4.43% $367,017.74 10 4.43% $367,017.74
-0.5 4.36% $361,244.82 50 4.41% $364,965.15
-1.0 4.29% $355,471.90 100 4.40% $364,708.57
Gold
6 Number of Bidders
% $ Increase in $ Increase in LEED
6 Increase LEED Cost n % Increase Cost
1.0 8.68% $718,746.39 1 9.15% $757,874.62
0.5 8.44% $699,182.28 5 8.31% $688,313.32
0.0 8.20% $679,618.16 10 8.20% $679,618.16
-0.5 7.97% $660,054.05 50 8.12% $672,662.03
-1.0 7.73% $640,489.93 100 8.11% $671,792.52
Platinum
6 Number of Bidders
% $ Increase in $ Increase in LEED
d Increase LEED Cost n % Increase Cost
1.0 13.27% $1,054,078.68 1 14.30% $1,184,800.32
0.5 12.75% $1,036,286.79 5 12.46% $1,032,128.06
0.0 12.23% $1,018,494.91 10 12.23% $1,013,044.03
-0.5 11.71% $970,104.96 50 12.05% $997,776.81
-1.0 11.19% $927,165.89 100 12.02% $995,868.40









Table A-1 continued.


Certified
Bid Climate Factor Experience Factor
% $ Increase in $ Increase in LEED
Increase LEED Cost % Increase Cost
0.50 1.00% $83,095.06 0.90 0.90% $74,666.28
0.75 1.00% $83,006.70 0.95 0.95% $78,814.40
1.00 1.00% $82,962.53 1.00 1.00% $82,962.53
1.25 1.00% $82,936.02 1.15 1.15% $95,406.91
1.50 1.00% $82,918.35 1.30 1.30% $107,851.29

Silver
Bid Climate Factor Experience Factor
% $ Increase in $ Increase in LEED
Increase LEED Cost % Increase Cost
0.50 4.46% $369,583.48 0.90 3.99% $330,315.97
0.75 4.44% $367,872.99 0.95 4.21% $348,666.85
1.00 4.43% $367,017.74 1.00 4.43% $367,017.74
1.25 4.42% $366,504.59 1.15 5.10% $422,070.40
1.50 4.42% $366,162.49 1.30 5.76% $477,123.06

Gold
Bid Climate Factor Experience Factor
% $ Increase in $ Increase in LEED
Increase LEED Cost % Increase Cost
0.50 8.31% $688,313.32 0.90 7.38% $611,656.35
0.75 8.24% $682,516.55 0.95 7.79% $645,637.25
1.00 8.20% $679,618.16 1.00 8.20% $679,618.16
1.25 8.18% $677,879.13 1.15 9.44% $781,560.89
1.50 8.17% $676,719.77 1.30 10.67% $883,503.61

Platinum
Bid Climate Factor Experience Factor
% $ Increase in $ Increase in LEED
Increase LEED Cost % Increase Cost
0.50 12.46% $1,032,128.06 0.90 11.01% $911,739.63
0.75 12.31% $1,019,405.38 0.95 11.62% $962,391.83
1.00 12.23% $1,013,044.03 1.00 12.23% $1,013,044.03
1.25 12.18% $1,009,227.23 1.15 14.06% $1,165,000.64
1.50 12.15% $1,006,682.69 1.30 15.90% $1,316,957.24









Table A-1 continued.


Certified
Proximity to Services
% Increase $ Increase in LEED Cost
0.50 1.00% $ 82,962.53
0.75 1.00% $ 82,962.53
1.00 1.00% $ 82,962.53
1.25 1.00% $ 82,962.53
1.50 1.00% $ 82,962.53

Silver
Proximity to Services
% Increase $ Increase in LEED Cost
0.50 4.44% $ 367,622.73
0.75 4.44% $ 367,925.23
1.00 4.45% $ 368,227.72
1.25 4.45% $ 368,530.22
1.50 4.45% $ 368,832.71

Gold
Proximity to Services
% Increase $ Increase in LEED Cost
0.50 8.21% $ 680,315.92
0.75 8.22% $ 680,664.80
1.00 8.22% $ 681,013.68
1.25 8.23% $ 681,362.56
1.50 8.23% $ 681,711.44

Platinum
Proximity to Services
% Increase $ Increase in LEED Cost
0.50 12.25% $ 1,014,614.49
0.75 12.26% $ 1,015,399.72
1.00 12.27% $ 1,016,184.95
1.25 12.28% $ 1,016,970.17
1.50 12.29% $ 1,017,755.40









LIST OF REFERENCES


Alquier, A.M., and Tignol, M.H. (1999). Project management technique to estimate and
manage risk of innovative projects, Universite Toulouse 1, Anatole, France.

Anderson, M. K., Bidgood, J.K., and Heady, E. J. (2010). "Hidden legal risks of green
building." The Florida Bar Journal, 84(3), 35-41.

Capen, E.C., Clapp, R.V., and Campbell, W.M. (1971). "Competitive bidding in high-risk
situations." Journal of Petroleum Technology, 23(6), 641-653.

Dyer, D., and Kagel, J.H. (1996). "Bidding in common value auctions: How the
commercial construction industry corrects for the winner's curse." Management
Science, 42(10), 1463-1475.

Eso, P., and White, L. (2003). Precautionary bidding in auctions, Centre for Economic
Policy Research, London.

EVStudio. (2010). "Cost per square foot of college building types by region."
region/>. (May 30, 2010).

Fu, W.K., Drew, D.S., and Lo, H.P. (2002). "The effect of experience on contractors'
competitiveness in recurrent bidding." Construction Management and Economics,
20(7), 655-656.

Kibert, C.J. (2008). Sustainable construction: Green building design and delivery, 2nd
Ed., Wiley, Hoboken, N.J.

March, J.G., and Olsen, J.P. (1976). Ambiguity and choice in organizations,
Universitetsforlaget, Bergen, Norway.

Mathiessen, L.F., and Morris, P. (2004). Costing green: A comprehensive cost database
and budgeting methodology, Davis Langdon, London.

Morgan, M., Granger, M.H., and Small, M. (1990). Uncertainty: A guide to dealing with
uncertainty in quantitative risk and policy analysis, Cambridge University Press,
New York.

Morris, P., and Mathiessen, L.F. (2007). Cost of green revisited: Reexamining the
feasibility and cost impact of sustainable design in the light of increased market
adoption, Davis Langdon, London.

Northbridge Environmental Consultants. (2003). Analyzing the cost of obtaining LEED
certification, Washington, D.C.

Steven Winter Associates Inc. (2004). GSA LEED cost study: Final report, Norwalk,
Conn.









Tang, F., Zong, W., and Song, S. (2006). Tenders with different risk preferences in
construction industry, Department of Economics, University of Nevada, Reno, Nev.

Thaler, R.H. (1998). "Anomalies: The winner's curse." Journal of Economic
Perspectives, 2(1), 191-202.

USGBC (2010). "USGBC: Intro- What LEED is."
(May 29, 2010).









BIOGRAPHICAL SKETCH

The author was born in Connecticut and attended the University of Connecticut,

receiving a Bachelor of Science degree in Finance from the School of Business

Administration. After working for several years for a contractor in Hartford, Connecticut

the author relocated to Florida to attend the University of Florida in pursuit of a degree

of Masters of Science in Building Construction. The author plans to return to

Connecticut to continue his career.





PAGE 1

1 MODELING RISK FACTORS ON EXPECTED BIDS I N CERTIFIED SUSTAINABLE CONSTRUCTION By JEREMY PIELA A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN BUILDING CONSTRUCTION UNIVERSITY OF FLORIDA 2010

PAGE 2

2 2010 Jeremy Piela

PAGE 3

3 To my Mom and my brother Jonathan

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4 ACKNOWLEDGMENTS I thank my parents, my brother Jonathan, and the rest of my family for their continuing support of my academic ventures. Leaving a career in Connecticut and returning to school was a very difficult decision for me, and would have been impossible without their support. I also thank the wonderful friends that I have made at the University of Florida who were extremely important in the success that I enjoyed in my pursuit of the advanced degree associated with this project. I not only made lifelong friends, but learned lessons from those friendships that are beyond value and will surely be the key to my success in the future. I finally thank the faculty and staff of the Rinker School of Building Construction at the University of Florida for their efforts that have made my experience there so enjoyable.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................. 4 LIST OF TABLES ............................................................................................................ 8 LIST OF FIGURES ........................................................................................................ 10 LIST OF ABBREVIATIONS ........................................................................................... 11 ABSTRACT ................................................................................................................... 12 CHAPTER 1 INTRODUCTION .................................................................................................... 13 Background ............................................................................................................. 13 Problem Statement ................................................................................................. 14 Risk Study ............................................................................................................... 14 2 LITERATURE REVIEW .......................................................................................... 17 Green Buildi ng ........................................................................................................ 17 LEED ...................................................................................................................... 17 Davis Langdon 2004 ........................................................................................ 19 Increased Risk .................................................................................................. 21 Cost of LEED .......................................................................................................... 21 Proximity to Service s ........................................................................................ 22 Bidding Climate and Culture ............................................................................. 23 Number of Bidders ........................................................................................... 24 Other potential projects .............................................................................. 24 Experience of bidders ................................................................................ 25 Intent and Values of the Project ....................................................................... 25 Climate ............................................................................................................. 26 Timing of Implementation ................................................................................. 27 Size of Building ................................................................................................. 27 Point Synergies ................................................................................................ 28 LEED Associated Risk ............................................................................................ 28 Sustainable Sites .............................................................................................. 28 Water Efficiency ............................................................................................... 29 Energy and Atmosphere ................................................................................... 30 Materials and Resources .................................................................................. 31 Indoor Environmental Quality ........................................................................... 32 Innovation in Design ......................................................................................... 33 LEED Credits Affected ..................................................................................... 33 Risk to th e Contractor ....................................................................................... 34

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6 Contracts .......................................................................................................... 38 Risk Analysis .......................................................................................................... 38 External Risk .................................................................................................... 39 Internal Risk ..................................................................................................... 40 Risk Balance .................................................................................................... 40 Levels of Risk ......................................................................................................... 41 Zero Risk .......................................................................................................... 41 Approval Compensation ................................................................................... 41 Utility Based Criteria ......................................................................................... 42 Risk Crite rion .......................................................................................................... 42 Risk Factors ............................................................................................................ 44 Risk in Bidding ........................................................................................................ 46 Risk Compensation ................................................................................................. 47 Winners Curse ........................................................................................................ 48 Risks Associated with the Winners Curse ....................................................... 50 Identifying the Winners Curse .......................................................................... 51 Experienced Bidders ............................................................................................... 52 Risk and HPB ......................................................................................................... 53 Bidding Model (Tang et al. 2006) ............................................................................ 53 Model Factors ......................................................................................................... 54 3 METHODOLOGY ................................................................................................... 57 Standard Building Characteristics ........................................................................... 57 Level of Certification ............................................................................................... 60 Soft Costs ............................................................................................................... 61 Risk Aversion .......................................................................................................... 61 Perceived Value; ci ........................................................................................... 62 High Bid; ch ....................................................................................................... 63 Number of Bidders; n ....................................................................................... 63 Risk Behavior; ............................................................................................... 64 Experience ....................................................................................................... 65 Location ............................................................................................................ 66 Assumptions ..................................................................................................... 68 Calculations ...................................................................................................... 69 Calculation Table .............................................................................................. 69 4 ANALYSIS .............................................................................................................. 73 Example Project ...................................................................................................... 73 Project .............................................................................................................. 73 Bidder ............................................................................................................... 73 Analysis .................................................................................................................. 73 Base Price ........................................................................................................ 73 Level of Certification ......................................................................................... 73 Baseline Case .................................................................................................. 74 Bid Climate ....................................................................................................... 76

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7 Risk Aversion ................................................................................................... 77 Location ............................................................................................................ 78 Soft Costs ......................................................................................................... 79 Expected Costs ................................................................................................ 80 Results .................................................................................................................... 80 Sensitivity Analysis ................................................................................................. 82 Certified Level Building ..................................................................................... 82 Silver Level Building ......................................................................................... 82 Gold Level Building .......................................................................................... 83 Platinum Lev el Building .................................................................................... 83 Risk Aversion ................................................................................................... 84 Number of Bidders ........................................................................................... 84 Experience ....................................................................................................... 85 5 SUMMARY AND CONCLUSIONS .......................................................................... 89 Summar y ................................................................................................................ 89 Conclusions ............................................................................................................ 89 6 RECOMMENDATIONS FOR FURTHER STUDY ................................................... 92 APPENDIX: SUPPORTING DATA ................................................................................ 94 LIST OF REFERENCES ............................................................................................... 97 BIOGRAPHICAL S KETCH ............................................................................................ 99

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8 LIST OF TABLES Table page 2 1 Rating categories and points available under LEED NC v2.2. ........................... 19 2 2 Rating levels and associated point totals under LEED NC v2.2. ........................ 19 2 3 Effects of demographic density on feasibility of LEED NC v2.2 credits .............. 23 2 4 Costs associated with bidding climate. ............................................................... 24 2 5 Effects of climate on cost of LEED construction ................................................. 26 2 6 Contractor's risk responsibilities related to Sustainable Sites, LEED NC v2.2 ... 29 2 7 Contractor's risk responsibilities related to Water Efficiency, LEED NC v2.2 ..... 30 2 8 Contractor's risk responsibilities related to Energy and Atmosphere .................. 30 2 9 Contractor's risk responsibilities related to Materials and Resources ................. 31 2 10 Contractor's risk responsibilities related to Indoor Environmental Quality. ......... 32 2 11 C ontractor's risk responsibilities related to Innovation in Design. ....................... 33 2 12 Total number of LEED NC v2.2 credits that affect risk to the contractor ............ 34 2 13 Methods of dealing with risk and risk acceptance compensation policies. ......... 43 2 14 Additional costs based on experience. ............................................................... 44 2 15 Percentages of bid based on the difference range of bids tendered ................... 51 3 1 Percentage increases in cost of LEED certification from GSA 2004 study. ........ 60 3 2 Estimates of LEED related soft costs ................................................................. 61 3 3 Economic factor multipliers for the base case of the risk model. ........................ 64 3 4 Table for determination of the risk factor for a particular contractor. ................... 64 3 5 Determination of experience factor for a specific bidder ..................................... 65 3 6 Factors for determining costs related to the proximity to urban centers ............. 66 3 7 Percentage increase in LEED costs as related to climate .................................. 67 3 8 Calculations for Location Factor. ........................................................................ 67

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9 3 9 LEED Premium and Bid Amount calculation table. ............................................. 72 4 1 Expected LEED costs for example 55,000 square foot classroom ..................... 74 4 2 Calculation of costs in the baseline scenario. ..................................................... 75 4 3 Determination of baseline analysis. .................................................................... 76 4.4 Determination of baseline analysis. .................................................................... 76 4 5 Economic factor determination ........................................................................... 77 4 6 The determinat ion of the Experience Factor ....................................................... 77 4 7 Determination of the number of bidders. ............................................................ 77 4 8 Determination of bidder's Risk Aversion Factor .................................................. 78 4 9 Risk Aversion calculation .................................................................................... 78 4 10 Adjustment factors for location of the example project. ...................................... 79 4 11 Estimated Soft Costs .......................................................................................... 80 4 12 Comparison of baseline case to example scenario. ........................................... 80 4 13 Results of model calculations ............................................................................ 81 A 1 Supporting data for sensitivity analysis. .............................................................. 94

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10 LIST OF FIGURES Figure page 2 1 Effects of risk on the cost of a LEED certified building. ...................................... 22 2 2 Display of the flow of risk associated with a LEED certified project. ................... 35 2 3 LEED related risks to contractors. ...................................................................... 37 2 4 Elements of project related risk from Alquien 1999. ........................................... 40 3 1 Cost per square foot of college classroom facilities ............................................ 58 3 2 Cost per square foot of college dormitory facilities ............................................. 58 3 3 Cost per square foot of college student union facilities ....................................... 59 3 4 Cost per square foot of college student union facilities ....................................... 59 3 5 Interactions of the factors and costs associated with the LEED premium. ......... 69 4 1 Graphical representation of the effects on a Certified level building. .................. 85 4 2 Graphical representation of the effects on a Silver level building. ...................... 86 4 3 Graphical representation of the effects on a Gold level building. ........................ 86 4 4 Graphical repr esentation of the effects on c a Platinum level building. ............... 87 4 5 The effects of various risk aversion behaviors .................................................... 87 4 6 The effect of the number of bidders .................................................................... 88 4 7 The effects of the level of experience ................................................................. 88 5 1 Effects of the number of bidders on a LEED Gold project. ................................. 90

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11 LIST OF ABBREVIATION S HPB High Performance Building LEED Leadership in Energy and Environmental Design LEED NC v2.2 Leadership in Energy and Environmental Design rating system for New Construction and Major Renovation, version 2.2 USGBC United States Green Building Council

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12 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requir ements for the Degree of Master of Science in Building Construction MODELING RISK FACTORS ON EXPECTED BIDS IN CERTIFIED SUSTAINABLE CONSTRUCTION By Jeremy Piela August 2010 Chair: James G. Sullivan Cochair: R. Raymond Issa Major: Building Construction Current research shows that a highperformance building (HPB) that is certified as such under a rating system such as the Leadership in Energy and Environmental Design (LEED) building rating system developed by the United States Green Building Council (US GBC) demonstrate an increase in construction costs over the cost of traditional projects that do not pursue LEED certification ( Steven Winter Associates 2004) This increase is often evident in projects that are produced by designers, builders and other involved parties that have extensive experience and education in the construction of buildings that incorporate many of the design features and construction tec hniques that are included in HPBs The purpose of this study is to propose a model that examines potential cost increases over traditional buildings of similar construction. This study reviews bid strategy and risk aversion models to explain the impacts of certification level, experience, location, perceived risk, and the risk behaviors of bidding contractors on the pricing of highperformance buildings. This study proposes that this increase in costs is related to the perceived risk involved in the construction of a project that pursues green certification, the level of certification pursued, and the individual risk behaviors of the contractors that are operating in a particular bidding climate.

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13 CHAPTER 1 INTRODUCTION Background Sustainable construction is becoming a more popular form of construction in the industry today. As society becomes more aware of the problems that have been created by the practices that have been utilized in the past, the construction industry is becoming more aware of the repercussions of the materials and techniques that are used to develop modern buildings The built environment consumes an enormous amount of the resources that are used today, as well as producing a large amount of waste. Recently, there has been a shift in thinking towards being more responsible with the resources that are consumed and the wastes that are generated. In the construction industry, this has resulted in the construction of buildings that are more responsible in terms of material use, energy use, and the health of the building occupants. In response to these concerns, there has been the development of building rating systems that help to gauge the level of sustainability that is built into a structure. Today, there are m any different systems throughout the world, each with varying popularity. One of the most popular in the United States is the Leadership in Energy and Environmental Design ( LEED ) building rating system. This system has been proven to reduce the amount of energy that is consumed in buildings, and is also concerned with the reduction in waste materials, the responsible use of materials, and the health of building occupants. While there is some debate over the effectiveness of the rating system, there is gen erally agreement that these types of systems are helping the construction industry to

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14 produce buildings that are more environmentally responsible. As these systems gain popularity, this type of construction is becoming more of the norm in the built environment. Problem Statement Sustainable construction is generally accepted to be more expensive than standard construction projects. This increase in costs pervades even in the presence of contractors that are experienced in this type of construction. As this type of construction becomes the norm, this increase of costs should begin to disappear, as there is no substantial difference between the rated structures and ones that are not certified. Certified buildings cost more than similar, non certified bui ldings and this study will propose a framework to account for those costs. Risk Study This study will aim to define and rationalize the reasons for the increases that are evident in the construction of certified buildings. The LEED building rating system will be studied, as there exists a large amount of data that is accessible due to the popularity of the system. This study will equate the additional costs to additional risk that is assumed by the contractor. These risks will be shown to arise from the perception that these projects are innovative and unique, and therefore pose a latent risk of loss to the contractor that is in excess of the risk that is assumed in a standard construction project. Chapter 2 is a review of the literature that exists in this area of study. The history of the LEED system will be addressed, and the rating system will be further examined to help identify possible explanations for this cost increase. The origins of this cost and the underlying risk will be examined. This wil l include an analysis of the contract

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15 language that can affect the amount of risk that is assumed by a contractor. A thorough analysis of the points that are available under the LEED rating system and the risks associated with pursuing these points will be included. Included in the Chapter 2 literature review will be an analysis of the types of risk that a contractor must deal with, and the techniques that are used to deal with risk. These risk analyses will be carried into a discussion of the effects of risk in the environment of an auction where contractors submit bids for the construction of a project. Methods and models that help to determine expected bids will be examined. Chapter 3 will introduce the model that was developed as part of this study that will be used to evaluate and predict the bids that are submitted by a particular contractor for a specific project, using the factors that are laid out in various cost studies that relate to certified sustainable construction. The model consists of sev eral factors, all of which are laid out in detail in this chapter. This model is developed using a computerized spreadsheet and the set up of the model is explained in detail. The methodology of the model w ill be laid out in this section, including the r elationships of the variables that are proposed. Chapter 4 will propose a sample scenario that will be used to show the relationships that exist in the model. This example will consist of the construction of a fictional structure on a college campus in th e southeast United States that is seeking certification under the LEED rating system. The associated costs with different levels of certification will be examined for this particular scenario. The proposed model will be used to examine this sample scenar io and a thorough analysis of the results will be included. This sample scenario is produced using a fictional company and project, and

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16 some of the variables will be assumed. This model is meant to produce real world results, but in this study will only be used to examine and evaluate the relationships between the risk variables that are involved. Chapter 5 will include a summary of the study, as well as conclusions that the author has reached. Chapter 6 will consist of a discussion of the limitations o f this study and recommendations for further research.

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17 CHAPTER 2 LITERATURE REVIEW Green Building High performance buildings (HPB) are buildings that fulfill needs in the built environment utilizing many of the best methods of conventional construction coupled with the latest highperformance approaches to construction in areas such as energy reduction, water reduction, indoor environmental quality, and occupant health. HPBs are becoming increasingly prevalent in the United States due to several primary reasons including (Kibert 2008): HPB construction provides an ethical and practical response to issues of environmental impact and resource consumption. This includes a greater reliance on renewable resources for energy, recycling and reuse of water and other materials, native landscaping, passive design considerations and other accepted practices that reduce environmental impacts and resource consumption of the built environment. From a lifecycle cost (LCC) perspective, which examines first costs, performance, and maintenance, HPBs are almost always a more attractive investment. While many of the strategies employed are more expensive on a first cost basis, this initial cost is usually recouped quickly. This effect is exacerbated by increases in energy and other resource costs due to increasing demand and diminishing supply. Design and construction of HPB s take into account the effect of the building and its operation on the health and well being of the buildings future occupants. Building related illness is a relevant concern, as lost productivity has been estimated to exceed $150 billion per year (Kibert 2008). Strategies include protection of ductwork during construction to prevent contamination; specifying finishes with little or no volatile organic compounds (VOCs) to prevent potential off gassing; and utilizing techniques to limit mold and bacteria growth inside of the structure. LEED Modern buildings that seek to be considered as highperformance have several di fferent building rating systems that may be utilized to certify that a building attains a certain level of performance. One rating system in the United States is the Leadership

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18 in Energy and Environmental Design (LEED ) building assessment tool produced by the United States Green Building Council (USGBC). This system is useful for gauging the level of sustainability, or greenness in a building (Mathiessen and Morris 2004). The LEED system provides third party verification that a building or community was designed and built using strategies aimed at improving performance across all the metrics that matter most: energy savings, water efficiency, CO2 emissions reduction, improved indoor environmental quality, and stewardship of resources and sensitivity to t heir impacts ( USGBC 2010 ). LEED is a standard that is used to measure the level of sustainable measures that are incorporated into the design and construction of a building. For the purposes of this study, the LEED NC rating system will be used. LEED NC is for new construction and major renovation (greater than 50% of the occupied space is affected). The system provides a framework that awards points under several categories that results in a total score for the building, and a corresponding rating level of Certified, Silver, Gold, and Platinum. The LEED rating system has gone through many changes since its inception in 1998 as a pilot program. More recent versions according to the USGBC (2010) website have been LEED NC v 1 .0 (1999), LEED NC v 2 .0 ( March 2000), LEED NC v2.1 (November 2002), LEED NC v2.2 (October 2005), and LEED NC v3 (April 2009). The LEED version that this study addresses is the LEED NC 2.2 rating system. While this study was performed during the tenure of the LEED NC v3 system, there w as very little information published about projects under this format. As projects are registered with the USGBC, they are registered under a rating system and follow that system through completion. Due to this, there is a useful amount of information th at

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19 was available at the time of this study related to the LEED NC v2.2 rating system, and projects using this system were examined. While much of the information introduced in this study can be used under different systems, it should be noted that the inf ormation used and studies cited in this study related to the LEED NC v2.2 rating system. Table 2 1 displays the points available in each category and Table 1 2 shows the points related to each level of certification under the LEED NC v2.2 rating system Table 21. Rating categories and points available under LEED NC v2.2. Point Category Available Points Sustainable Sites 14 Water Efficiency 5 Energy and Atmosphere 17 Materials and Resources 13 Indoor Environmental Quality 15 Innovation and Design 5 Total Points Available: 69 Table 22 Rating levels and associated point totals under LEED NC v2.2 Rating Level Project Point Total Certified 26 32 Silver 33 38 Gold 39 51 Platinum 52 69 The higher the levels of certification require a significant concerted effort from the owner, designer, contractor and the rest of the project team to achieve. This can often be at a high additional cost. Davis Langdon 2004 The Davis Langdon study of 2004 compared a database of completed buildings in o rder to compare the construction HPBs where LEED certification was a primary goal to similar buildings where LEED certification was not considered. The 2004 study reviewed 138 buildings; 93 that were nonLEED and 45 that were LEED seeking

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20 projects. The prices were normalized for location and time to ensure consistency of the measurements. It should be noted that many of these projects that were not designed with the LEED rating in mind would have achieved several LEED credits, though this was not the int ention of the project from the design stage. This study covered several types of buildings including academic buildings, laboratory buildings, and library buildings. The Davis Langdon study drew four key conclusions from the analysis regarding the constr uction costs of LEED versus nonLEED seeking projects: There is a very large variation in costs of buildings, even within the same building program category Cost differences between buildings are due primarily to program type There are low cost and high cost green buildings There are low cost and high cost nongreen buildings The Davis Langdon study in fact found that there are no statistically significant differences between the cost per square foot between LEED seeking and nonLEED seeking buildings. The 2004 study concludes that the variation in the cost of all buildings makes the price difference in LEED construction not discernable from the normal variation. The 2007 follow up to this study again confirmed these conclus ions, using the latest data avai lable at the time of the study. While the Davis Langdon study shows evidence that there is no significant difference in the cost of LEED certified buildings and buildings that do not pursue certification, other studies have shown that there is a difference in the costs of green buildings that are submitted for bid, such as the GSA study of 2004 ( Steven Winter Associates 2004).

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21 Increased Risk The difference in price that exists in the construction bidding environment stems from the risk that is associated with construction with the goal of certification under a system such as LEED. This risk arises from the additional burden placed on the cont ractor to deliver a building that meets a certain criteria. With the added innovation and planning comes risk, and risk management is the main consideration when managing creative projects (Alquier 1999). There is often included in the contract language a requirement for the contractor to ensure that the building performs up to a certain level of sustainable certification, and failure to achieve this goal and the associated economic costs are certainly a risk. Many of these buildings, particularly at hig her levels of certification, can be quite innovative and unique, which can present substantial additional risk. Green building embodies a greater latent potential for unrealized expectations, misunderstandings, physical or economic failure, and litigatio n (Anderson 2010). Cost of LEED This study proposes that this increase in costs is related to the perceived risk involved in the construction of a project that pursues green certification, the level of certification pursued, and the individual risk behavi ors of the contractors that are operating in a particular bidding climate. Since these additional risks pose a latent potential cost to the contractor, there is a cost increase that is associated with the additional risk that is passed on to the building owner. These co sts are mapped out in Figure 21 The Davis Langdon study of 2004 identified seven particular factors that affect the cost and feasibilit y of a LEED certified project. The factors and the effects that they have on the cost of LEED construction are laid out in seven sections.

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22 Figure 21 Effects of risk on the cost of a LEED certified building. Proximity to Services Location can have a considerable impact on the cost and feasibility of certain LEED points. Of the points that are affected by location, five are generally available in a rural location, while six to eight are available in an urban location, though two of these points may come at an increased cost over the cost associated with rural construction. The LEED system is weighted toward the development of urban environments. The community connectivity and development density requirements, as well as the public transportation access credit are direct results of this. The credits that are affected by the demographic location are listed in Table 2 3 As well as an increase in available credits, urban environments are more likely to have a well established construc tion waste recycling or reclamation program. In addition to the availability of services, contractors are also more likely to be familiar with these practices in an urban setting, presenting a more sophisticated pool of potential bidders. Infrastructure that is

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23 conducive to the construction of a LEED structure may also exist to a greater extent in an urban environment. Table 2 3 Effects of demographic density on feasibility of LEEDNC v2.2 credits. $$$ indicates that the credit may be available, though at an increased cost Figure generated from data found in Steven Winter Associates 2004. Point Category Location Rural Urban Site Selection X Urban Redevelopment X Alternative Transportation, Public Transportation Access X Reduced Site Disturbance, Public Transportation Access X Reduced Site Disturbance, Development Footprint X Stormwater Management, Rate and Quantity X $$$ Stormwater Management, Treatment X $$$ Water Efficient Landscaping, Reduce by 50% X Water Efficient Landscaping, No Potable Use or No Irrigation X Construction Waste Management, Divert 50% X Construction Waste Management, Divert 75% X Total Points Available 5 6 to 8 Bidding Climate and Culture The bidding climate is potentially the most significant factor in the cost of a high performance building. The bidding climate is the response of the contractors to the specific requirements of building performance laid out in the contract. The culture o f the entities and relationships between them will also have an effect on the resulting behavior of the participating contractors. These costs consist of two components; actual costs borne by the contractor, and the perceived risk associated with the buil ding performance requirements. Some of these costs are further defined in Table 2 4 The actual (physical) costs are relatively small, while the cost associated with risk can be much larger. This will be examined more thoroughly in this study, since this factor is the one that most extensively drives the cost of LEED construction.

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24 Table 2 4 Costs associated with bidding climate. Direct Costs Risk Associated Documentation Costs Liability IAQ Costs Smaller Bidder Pool Schedule Impacts Local Familiarity with Sustainable Building There are many factors related to the amount of the cost of risk, but there are two major reasons for the increase of cost for wary bidders: Bidders are inclined to add contingencies or risk premiums to cover the perceived risk As bid pool diminishes, competition lessens and bid prices increase As the number of bidders increases, a bidder realizes that to win the auction, they must bid more aggressively, but the presence of more bidders also increases the chance that if the contract is won, the winner will suffer a loss (Thaler 1988). This phenomenon is called the winners curse and is described in detail in this report in the section titled Winners Curse. Number of Bidders The number of bidders is also affect ed by other factors. The strength of the economy plays a part in the determination of the number of bidders. During a period of strong economic growth, there are more projects on the market that the contractor could potentiall y bid on. Bidders are more likely to bid on projects that are perceived as less risky if the jobs are available. Other potential projects Contractors will be less likely to bid on a project perceived as risky if there is a large amount of other work available. A contractor, as any other entity is general ly considered to be risk averse and therefore does not pursue unnecessary risks. If there is a large amount of work that is available to the contractor that is perceived as less

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25 risky, there are likely to be a smaller number of bidders that are willing to offer a bid on a project that contains any added risk. The opposite is also true. In a period when the economy is struggling, there is likely to be a larger pool of contractors that are willing to take on a larger amount of risk than at other times simply because there is less work available. An increase in the number of bidders has the general result of reducing the bid price offered, though this is a general rule and can be affected by other factors. Experience of bidders The s econd is the experience of the bidders that are participating in the auction. More experience with LEED associated projects will cause the perceived risk to the experienced contractor to be less than that of the inexperienced contractor. This has the eff ect of lowering the amount of the bid. This phenomenon is more completely discussed in the Experienced Bidders section of this report. The two factors that have the greatest effect are the familiarity of the bidding community with green building, and the availability of alternative work in the construction market in the local area of the project. Attempting a project where high performance building is an unfamiliar concept and/or where contractors are unwilling to offer bids can significantly affect the cost of the project. Local and regional design standards, as well as building codes and initiatives will have an effect. Intent and Values of the Project This category describes the effect of the intents and values of the owner and project team as relate d to the project. The best and most economical sustainable designs are ones in which the features are incorporated at an early stage into the project, and where the features are integrated effectively supporting each other (Mathiessen and Morris 2004). If members of the project team, particularly the owner,

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26 are not fully invested in incorporating high performance aspects into the project, it will be more difficult to include these changes into the project. This largely hinges on fully understanding the intents and desires of the owner and design team. These are difficulties that the contractor has little or no control over and therefore represents a risk to the contractor. Climate The climate that a building is constructed in has an effect on the feasibility of certain LEED points, and the cost associated with certain levels o f LEED certification. T his factor refers to the natural environmental climate of the location of the project. Mathiesse n and Morris described values associated with location in the Davis Langdon study of 2004. This is shown in Table 2 5 Table 25 Effects of climate on cost of LEED construction ( Mathiessen and Morris 2004) Location % Increase Based on Certification Level Certified Silver Gold Platinum Mild Coastal 1.00% 2.70% 7.80% California Central Valley 3.70% 5.30% 10.30% Gulf Coast 1.70% 6.30% 9.10% Northeast Coast 2.60% 4.20% 8.80% Rocky Mountain 1.20% 2.80% 7.60% Average Increase: 2.04% 4.26% 8.72% The Davis Langdon study took into effect the cost of energy and the amount of energy consumed, altering the effectiveness of the energy efficiency measures. This difference in calculation is included in the associated costs. These increases were derived from a study that took an actually constructed building in Santa Barbara, California and placed it in five hypothetical environmental locations These locations were defined as:

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27 Mild Coastal Santa Barbara and San Francisco California Central Valley Merced Gulf Coast Houston Northeast Coast Boston Rocky Mountains Denver Yearly temperature fluctuations and humidity levels can play a significant role in determining cost for mechanical systems, and the feasibility of passive heating and cooling. Timing of I mplementation The timing of implementation of a building rating system can also have an effect on the cost and feasibility of achieving a level of building certification. This factor was not covered in the Mathiessen and Morris (2004) study since this is extremely difficult to quantify and measure. This would be a situation specific factor that would have to be closely analyzed before a project was undertaken. Size of B uilding The size of the building also has an effect on the cost of LEED certification. This is most notable in the direct cost of the building, but the cost of perceived risk also increases as a factor of this cost. As the value of the project increases, the costs associated with risk also increase. Many of these risks are proportional to the total cost of the project, and will rise as the overall cost of the project increases. If a contractor were to run late on a project, the damages that the contractor could be held responsible for could be increased for a larger project. Litigation costs will generally also be tied to the overall value of the project that is in question, and penalties associated may be tied to the overall project value, or the potential value to the owner or other financially interested party.

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28 Point S ynergies The points under the LEED system that are p ursued also have an effect on the cost of certification. Some points are synergistic and can assist in obtaining other points, lowering the overall cost of a certain level of certification. LEED Associated Risk The 2006 Davis Langdon study addressed each category and related costs to each of the LEED credits. Some credits had little or no associated costs, while others were very expensive. As with costs, there are risks that fall squarely into the field of work for certain project members. There are rel atively few credits that are the direct responsibility of the contractor, as the LEED system is weighted heavily towards the design of the project. Table 2 6, Table 2 7, Table 2 8, Table 2 9, Table 2 10, and Table 2 1 1 outline the specific credits that fall to some extent under the responsibility of the contractor, and therefore represent risk to the contractor. Sustainable Sites The Sustainable Sites category of the LEED NC v 2.2 rating system is in place to help reduce the impact of the built environment on the natural environment. The credits include stormwater and pollution prevention, site selection that encourages use of previously developed land, and increased use of alternative transportation. The contractor has little responsibility for most of the Sustainable Sites credits. Note that there is a perceived risk for Prerequisite 1. This credit usually does not require any additional activities above and beyond a standard construction project, but under the LEED rating system this takes on a greater significance. If the contractor fails to follow local pollution prevention plans, or fails to document compliance, the LEED certification

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29 could be forfeit since this is a prerequisite. This represents a significant additional risk to the contractor. The risks are outlined in Table 26. Table 26 Contractor's risk responsibilities related to Sustainable Sites LEED NC v2.2. (LEED 2.2 Rating System) Risk to Contractor? Yes No Sustainable Sites SS Prerequisite 1: Construction Activity Pollution Prevention X SS 1: Site Selection X SS 2: Development Density and Community Connectivity X SS 3: Brownfield Redevelopment X SS 4.1: Alternative Transportation Public Transportation Access X SS 4.2: Alternative Transportation Bicycle Storage and Changing Rooms X SS 4.3: Alternative Transportation Low Emitting and Fuel Efficient Vehicles X SS 4.4: Alternative Transportation Parking Capacity X SS 5.1: Reduced Site Disturbance Protect or Restore Habitat X SS 5.2: Reduced Site Disturbance Maximize Open Space X SS 6.1: Stormwater Management Quantity Control X SS 6.2: Stormwater Management Quality Control X SS 7.1: Heat Island Effect Non Roof X SS 7.2: Heat Island Effect Roof X SS 8: Light Pollution Reduction X Water Efficiency The Water Efficiency category of the LEED NC v 2.2 rating system is in place to encourage more efficient use of water resources. This includes reduction of water use, reduction or elimination of potable water use for landscaping, and innovations in the treatment of wastewater. The Water Efficiency credits are all related to the design of the project and pose little if any direct risk to the contractor. The risk responsibilities concerning the contractor are outlined in Table 27. Th e contractor should be aware of these credits so that any additional planning that may be required is incorporated into the schedule.

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30 T able 27 Contractor's risk responsibilities related to Water Efficiency LEED NC v2.2. (LEED 2.2 Rating System) Risk to Contractor? Yes No Water Efficiency WE 1.1 and 1.2: Water Efficient Landscaping Reduce by 50% and No Potable Use or No Irrigation X WE 2: Innovative Wastewater Technologies X W E 3.1 and 3.2: Water Use Reducti on 20% and 30% Reduction X Energy and Atmosphere The Energy and Atmosphere category of the LEED NC v 2.2 rating system is in place to encourage the reduction in the use of energy and the reduction of the use of harmful refrigerants in building systems. This includes the reduction of overall building energy use, commissioning of building systems, and the production or purchase of r enewable energy. The analysis of these risks are outlined in Table 28. T able 28 Contractor's risk responsibilities related to Energy and At mosphere, LEED NC v2.2. (LEED 2.2 Rating System) Risk to Contractor? Yes No Energy and Atmosphere EA Prereq. 1: Fundamental Commissioning of Building Systems X EA Prereq. 2: Minimum Energy Performance X EA Prereq. 3: Fundamental Refrigerant Management X EA 1: Optimize Energy Performance (1 10 points) X EA 2: On Site Renewable Energy (1 3 points) X EA 3: Enhanced Commissioning X EA 4: Enhanced Refrigerant Management X EA 5: Measurement and Verification X EA 6: Green Power X The Energy and Atmosphere category has little effect on the performance of the contractor. This is generally a design category and is a cooperative effort between the designers and installers of the building systems. Again the contractor should be aware of t hese credits so that the schedule may be adjusted accordingly.

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31 Materials and Resources The risks that are presented to the contractor are outlined in Table 2 9. The Materials and Resources category of the LEED 2.2 rating system is in place to promote the reuse and recycling of building materials, as well as materials that are considered sustainably harvested or produced locally. Table 29 Contractor's risk responsibilities related to Materials and Resources LEED NC v2.2. (LEED 2.2 Rating System) Risk to Contractor? Yes No Materials and Resources MR Prerequisite 1: Storage and Collection of Recyclables X MR 1.1 to 1.3: Building Reuse X MR 2.1 and 2.2: Construction Waste Management Divert From Landfill X MR 3.1 and 3.2: Materials Reuse X MR 4.1 and 4.2: Recycled Content X MR 5.1 and 5.2: Local/Regional Materials X MR 6: Rapidly Renewable Materials X MR 7: Certified Wood X The risk associated with the Materials and Resources category falls squarely in the realm of the project responsibilities of the contractor. The Building Reuse credit requires the contractor to develop a construction plan that must be followed through to preserve the required proportion of the building. The Construction Waste Management credit is perhaps the only credit that is the direct responsibility of the contractor. An experienced contractor should be familiar with this type of requirement, but the related risk is the direct responsibility of the contractor. The risk for credits MR 3 MR 7 stems mainly from the procurement of the proper materials and the maintenance of the documentation that is necessary to show compliance with the credit requirements.

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32 Indoor Environmental Quality The Indoor Environmental Quality portion of the LEED 2.2 rating system is in place to help protect the health and well being of the inhabitants of the building. The risk to the contractor is outlined in Table 21 0. While much of this category is the responsibility of the design team, the contractor holds some responsibility for following through with the designed plans. Table 210. Contractor's risk responsibilities related to Indoor Environmental Quality. (LEED 2.2 Rating System) Risk to Contractor? Yes No Indoor Environmental Quality EQ Prerequisite 1: Minimum IAQ Performance X EQ Prerequisite 2: Environmental Tobacco Smoke (ETS) Control X EQ 1: Outdoor Air Delivery Monitoring X EQ 2: Increase Ventilation X EQ 3.1: Construction IAQ Management Plan During Construction X EQ 3.2: Construction IAQ Management Plan Before Occupancy X EQ 4.1 to 4.4: Low Emitting Materials X EQ 5: Indoor Chemical and Pollutant Source Control X EQ 6.1: Controllability of Systems Lighting X EQ 6.2: Controllability of Systems Thermal Comfort X EQ 7.1: Thermal Comfort Design X EQ 7.2: Thermal Comfort Verification X EQ 8.1: Daylight and Views 75% of Spaces X EQ 8.2: Daylight and Views 90% of Spaces X There are a few credits in the Indoor Environmental Quality category that pose potential risk to the contractor. EQ 3.1 relates to the protection of materials and the HVAC system during the construction process. EQ 3.2 does not directly involve the contr actor, but must be incorporated into the contractors construction schedule. If the contractor failed to plan for an appropriate amount of time for these activities, the schedule may be extended beyond the required date of substantial completion. The ris k is that the contractor may be responsible for not delivering the project on time if this

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33 credit is not appropriately planned for. EQ 4.1 to 4.4 would likely fall into the contractors risk area, unless the materials to be used were expressly specified i n the contract documents. Innovation in Design The Innovation in Design category of the LEED NC v 2.2 rating system is used to award exemplary performance in one of the listed categories or the utilization of innovative technologies or other methods that im prove building performance. Risks to the contractor are outlined in Table 211. Table 211. Contractor's risk responsibilities related to Innovation in Design. (LEED 2.2 Rating System) Risk to Contractor? Innovation in Design Yes No ID 1 4: Innovative Design (projects average two of these credits) X ID 5: LEED Accredited Professional X Most of the projects in the Davis Langdon study received two points in the Innovation in Design category for credits other than the LEED Accredited Professional credit. These credits were almost always for exemplary performance in the categories where this is an option. It is assumed that the contractor could have some risk responsibility in these credits as the study did not addres s which credits were involved. LEED Credits Affected The total number of points may vary depending on the contract language, the type of project being considered, and the associated credits that are being pursued by the project team. The credits presented here show potentially affected credits that would be seen in a standard construction project, though this may vary. The risk that the contractor is exposed to should be limited to the performance of these credits. The credits that affect the risk level of the cont ra ctor are outlined in Table 2 12.

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34 Table 212. Total number of LEED NC v2.2 credits that affect risk to the contractor. The prerequisite is included in the Sustainable Sites category. Point Category Point Total Sustainable Sites 1 + 3 Water Efficiency 0 Energy and Atmosphere 0 Materials and Resources 13 Indoor Environmental Quality 6 Innovation and Design 2 Total Points Affected: 25 Risk to the Contractor The risk related to compliance with these credits is generally passed on to the contractor from the owner in order to cover the potential costs to the owner that may stem from failure to achieve green certification. These potential damages can include the loss of a tenant or sale, loss of government incentives and tax credits, increased design and construction costs, rescinded donations on endowed projects, penalties on public projects with green mandates, increased energy and water costs over the life of the building, and diminished asset value (Anderson 2010). Contract l anguage A major factor that must be considered is the amount of risk that is put upon the contractor by the owner or other parties. This is largely affected by the language that is included in the contract documents. While standard AIA documents are often used for constructi on projects, the green building movement is relatively new and some of these documents are insufficient. To avoid any confusion, there should be language or additional documents included in the documents that clearly defines the responsibilities for each party in relation to the area of green certification.

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35 The association of risk with potential activities in the construction of a building is shown in Figure 22 Anderson et al. 2010 identified four areas that specifically affect the contractor on a const ruction project when green certification is desired. These are: Performance specifications versus design specifications. The Spearin doctrine states that [I]f the contractor is bound to build according to plans and specifications prepared by the owner, the contractor will not be responsible for the consequences of defects in the plans and specifications (248 U.S. 132, 1918). This doctrine applies to design specifications and not performance specifications. In an Figure 2 2 Display of the flow of risk associated with the construction of a LEED certified project. area such as product selection for adhesives and sealant s, under performance specifications the contractor would be responsible for selecting materials that were

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36 appropriate under SS credit 4, Low Emitting Materials. By accepting a contract with performance based specifications, the contractor would be accepti ng the responsibility for the design of this area of the project, and the resultant effects on the green certification. The risk associated would be bore entirely by the contractor. Guaranteeing LEED certification. Generally, the contractor should at least be aware and probably cautious of guaranteeing LEED certification. The contractor in fact has little control over the certification in that very few of the LEED credits are under the control of the contractor. It is recommended that the contractor tak e appropriate responsibility for their portion of the project in a way that protects the owners interests, but it is often unreasonable and unlikely for the contractor to assume all risk for the certification of the project (Anderson 2010) Potential dela ys. There are components of a green building project that directly affect the schedule of the project, which falls squarely in the domain of the contractor. One issue stems from the popularity of green projects, and the availability of materials that are associated with these projects. Some of these products may be in high demand and low supply, which can present extended procurement times. Some of the LEED credits actually require more time to be included in the project schedule. Low emitting paints associated with IEQ credit 4.2 generally take more time to cure, and may extend the time required for other activities. The building flushout procedure that is associated with EQ credit 3.2 also has an associated time period that takes place following fin al construction activities, but prior to occupancy. This directly affects the critical path of the project as no other construction related activities may take place during this operation. This extra time may not be immediately quantifiable for a

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37 contrac tor, particularly one with limited experience in this arena, and presents a risk to the contractor of negatively affecting the schedule and any monetary penalties that are incurred related to these delays. G reen performance bonds. In certain locales, incl uding Washington D.C., performance bonds are being utilized to ensure compliance with green mandates. If a building does not achieve LEED certification within two years after the issuance of the certificate of occupancy, the bond is forfeit. While the contractor may or may not be directly responsible for the performance mandated by this bond, they should be aware of the existence and consequences of this and the risk that is associated with noncompliance. The popularity of this type of performance bond should be monitored, as it will affect the latent risk that is posed to contractors undertaking projects where these are present. The risks that are posed to a contractor due to the LEED certification system are outlined in Fi gure 23 Figure 23 LEED related risks to contractors.

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38 Contracts Green building is becoming more common in the construction arena today, but there are still areas where the usual way of doing things is insufficient for the green building environment. Particularly the wording that is common in many standardized construction contract documents is insufficient. One particular example is the AIA A201 2007 General Conditions definition of work. This does not account for the requirement that contractors, subcontractors, and suppliers provide documentation that is essential to the LEED certification process. This documentation must be created and maintained throughout the project, and credits could be lost if this requirement is not performed (Anderson 2010). The AIA is providing documents that help to fill these gaps (such as AIA B101, B211, and B214), but holes still exist that may pose an increased risk to the contractor that they may or may not realize that they are subjecting themselves to. Risk Analysis The risk and potential costs appropriated by the contractor bidding on a construction project is a parameter that can be modeled and analyzed to gain insight into the decision of a contractor to increase price due to a perceived risk. The analysis of risk can also affect the decision of a contractor to bid on a certain project at all, affecting the number of bidders that may participate in the auction for a construction contract. Analysis of risk and risk models are useful in that they allow us to obtain better insight and understanding about the problem at hand. This does not always equate to determining an exact scientific conclusion, but often creating a model that allows us some insight into the factors that we would like to control to achieve a more desirable

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39 outcome. This can be important in innovative construction projects since the creative projects have to focus on risk management and risk management is the main consideration when managing creative projects (Alquien 1999). Possible alternatives are often not clearly defined and analysis is used to help the decision maker to identify and explore possible alternatives and scenarios as well as to choose among them (Granger et al. 1990). James G March has defined this model in the following summary: Human beings make choices. If done properly choices are made by evaluating alternatives in terms of goals on the basis of information currently available. The alternative that is most att ractive in terms of the goals is chosen. The process of making choices can be improved by using the technology of choice. Through the paraphernalia of modern techniques, we can improve the quality of the search for alternatives, the quality of information, and the quality of the analysis used to evaluate alternatives. Although actual choice may fall short of the ideal in various ways, it is an attractive model of how choices should be made by individuals, organizations and social syst ems. (March 1976) Un der this framework, we can use these models to provide an aid in the evaluation of different scenarios. A ccording to Granger et al. (1990), a model can be used to assist in the systematic exploration of alternative possible goals by using a framework t o identify existing and invent new alternatives to aid in reaching a that goal. The aim of this study is to understand how bidders in a construction auction develop a bid, based on risk and other factors, and to provide a tool for analyzing what goes into these bids. The first step is to understand the source of the risk in the broadest sense. In this approach, there exists two types of risk; internal and ex ternal. These are described in Alquien (1999) and are described in detail in this report. External Risk External risk is a portion of total r isk that the company does not control. External risk r elates to factors in the environment that the company operates in such as; market

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40 shifts, government action, environmental (nature) interactions, market competition, and external regulation. External risk is a lso called market or environment risk. Internal Risk Internal risk represents the portion of total r isk that is supposed to be under company control. Internal risk is associated with the technical solutions regarding products, processes, and resources. These can include new technology, required resources, innovative processes, and cost estimations. Risk Balance The risk balance of a company in regards to a specific project contains elements of both internal and external risk. The goal of a risk analysis is to evaluate the internal and external risks that have the potential to affect the company or project. These risks are outli ned in Figure 2 4 The company must then decide whether these risks are acceptable, and if so at what level. Figure 2 4 Elements of project related risk from Alquien 1999.

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41 Levels of Risk There are different levels of risk, and organizations and people are willing to accept varying levels of risk in the activities that they pursue. Every undertaking is associated with a certain level of risk and our decision to pursue this activity or not is based on our own risk acceptance policies. Zero Risk A zero risk criterion is described as; independent of the benefits and costs, and of how big the risks are, eliminate, or do not allow the introduction of the risk (Granger et al. 1990). This describes the rationale that there is no reason for every policy to be accepted or every activity to be undertaken. Some activities will not be accepted because there is a risk involved, and the entity that is in the decision making position is unwilling to take on any associated risk. In the area of highperformance buil dings and LEED certification, this is the equivalent of a contractor that is unwilling to even place a bid on a project because they are unwilling to accept any of the potential risk that is involved, no matter what the price. This may be due to the contr actor having very limited experience in this type of construction, or a bidder that is very risk averse. Approval Compensation Another criterion that is useful in describing levels of risk acceptance or aversion is the approval compensation criterion. Under this model, one accepts risk or other costs to be imposed upon them in exchange for some sort of compensation in repayment for their inconvenience or potential losses. In the realm of sustainable construction, this refers to the cost increase that is i ncluded to recognize the risk in performing the project goals. This is one of the types of risk acceptance that will be useful in this study, since this is a quantifiable criterion that can be analyzed using a model that will be developed.

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42 Examples of som e alternative decision criteria that may be applied in risk management analysis (Granger et al. 1990) that are included in decision making, and will be useful in this study include several utility based criteria. Utility Based Criteria Utility criteria dep end on the amount of risk that an entity is willing to accept and the amount of compensation that is required. Deterministic benefit cost: Estimate the benefits and costs of the alternatives in economic terms and choose the one with the highest net benefi t. Probabilistic benefit cost: Same as deterministic benefit cost but incorporate uncertainties and use expected value of resulting uncertain net benefit. Bounded cost: Do the best you can within the constraints of a budget that is the maximum budget the entity is prepared to devote to the activity. Maximize multi attribute utility (MAU): This is the most general form of utility based criterion. Rather than use monetary value as the evaluation measure, MAU involves specifying a utility function that evaluates outcomes in terms of all their important attributes (including uncertainties and risk). The alternative with maximum utility is selected. Some of the Life Cycle costing and other factors that are involved with sustainable construction would be inc luded in this section, and could help to make a decision for an owner to spend more money to create a green building. Minimize chance of worst possible outcome: Political and behavioral considerations frequently dictate the use of such criteria. These cri teria are summarized in Figure 2 4 Risk Criterion In the environment of an auction, which a bidding environment is, contractors will utilize one or more of these decision criteria to make decisions regarding bids on projects perceived as risky. These decisions will be based on a hybrid type of risk criterion, since the process of construction bidding is very complex and involves many discrete factors and entities. Bidders will generally have either a risk seeking, risk

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43 neutral, or risk averse mentalit y, and based on this characteristic will place a value on the risk based on the size of the risk and the attitude of the bidder with respect to risk practices. Table 213. Methods of dealing with risk and risk acceptance compensation policies Risk Practice Choice Methodology Deterministic Benefit Cost Choose option with highest net economic benefit Probabilistic Benefit Cost Choose option with highest net economic benefit incorporating uncertainties and expected values Bounded Cost/Risk Choose best options while remaining within certain levels of cost/risk Maximize multi attribute utility Choose option with highest total benefit Minimize worst case Choose least risky option Different bidders will have different utility based decision making processes that they may make use of. This may depend on the characteristics of that particular bidder and the situation that the bidder is in at the time of the auction. A bidder is left to determine the benefits and costs of a decision, and when applied to LEED construction, the costs can be high to a bidder. Contractors may be required to deliver a building that is certified to a certain level, and this is likely to be stated in the co ntract documents. The contractor is then left with this obligation to fulfill. Assuming that the contractor is familiar with the LEED process, they may understand the costs that may be incurred. The contract language that is in place will generally desc ribe the responsibilities of the contractor, and assign the risks that are involved to the interested parties. Some risks are specific to the contractor and the physical construction of the project. These may include (but are not limited to):

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44 Training costs: training to perform for certain LEED credits may be required including materials treatment under EQ credit 3.1 Construction IAQ Management Plan, or training for processing and documentation of LEED. Equipment costs: new equipment may need to be purchased such as storage areas, cleaning machines, or pieces of machinery that are required for the installation of materials that are unfamiliar to the contractor. On top of the costs that are expected to be incurred during the completion of a LEED project, there are also the costs that may be in addition to expected costs if the contractor is unfamiliar with the LEED process, or makes a mistake along the way. These include: Costs for appealing credits: There can be a significant cost associated with th e failure to achieve credits that were targeted, particularly if these credits are required for the level of certification that is required Litigation: If a contractor fails to achieve the project standards that are outlined in the contract documents, the n the owner may choose to recover money from the contractor to finish the project in a manner that meets the project requirements Documentation: If a contractor does not have the personnel or systems in place to provide the documentation that is required to successfully complete the certification of a building These criteria are summarized in Table 214. Table 214. Additional costs based on experience. Experienced Inexperienced (in addition to costs to experienced contractors) Training Costs Credit Appeal Costs Equipment Costs Litigation Costs Documentation Costs Risk Factors The first factor that will go into the model of a particular entities risk based decision is the level of risk ( ) that a bidder is willing to undertake. Entities exist on a scale that ranges from risk averse ( => 1) to risk seeking ( => 1) Risk aversion refers to the proclivity to avoid risk as much as possible. These contractors may be willing to only

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45 undertake projects that they perceive as having very little or no risk. When LEED buildings are considered, this risk is assumed to be additional risk, on top of the normal amount of risk that is commonly associated with construction projects. The risk that will be considered in this study refers to the amount of ad ditional risk that is perceived by the owner that is taken on above and beyond the risk associated with the normal business model of that entity. A risk averse bidder may be reluctant to bid at all on a LEED project that they feel they is too risky for t hem. There are many reasons that a contractor may feel this way about a project. These include: The general risk aversion of the company The company may feel that a LEED certified project presents more risk than they are willing to take on. This may v ary from lower to higher levels of certification. The level of risk associated The size of the project or the level of certification that is being pursued can have an effect. The amount of responsibility placed on the contractor in the construction docu ments can determine this level. The perceived risk based on internal factors Company may not be familiar with LEED construction, or not have the necessary elements in place to properly deal with a given project. The perceived risk based on external factors This could include other bidders, the state of the economy, location, or other risks apportioned to the contractor in the construction documents. Collectively referred to as the bidding environment This risk is compensated for is the amount of mon ey that a contractor charges in addition to the profit that they are expected to make. This is a type of probabilistic benefit cost. While contractors likely do not realize that they are performing this type of a ction, they probably are. This condition is described by adding a premium onto the project that is the result of the amount of risk perceived and the value of the project. This study is concerned with construction costs and the risk preferences and values that drive those costs in a construction bid environment. The risk analysis is

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46 important in the early stages of the project (the bidding phase), because this is when uncertainty is the greatest. Risk knowledge is fuzzy, distributed, unstructured, tacit, ancient history forgotten or transformed insufficiently organized, not or completely cataloged, underestimated, registered in heterogeneous information systems, secretive, possessed by experts who are rare in the company (Alquien 1999). There are certainly other costs and benefits associated with sustainable design and construction that should be considered, including operations and maintenance implications, user productivity and health, design and documentation fees, among other financial measurements (Mathiessen and Morris 2004), but the ini tial costs are the subject that will be more closely studied here. While each project must be studied individually, particularly if a higher level of certification is desired, there exists sufficient evidence to make generalizations about the costs associ ated with these projects which are becoming more and more commonplace. These projects are moving more from an innovative construction project to being the norm in the built environment today. Even buildings that do not seek any type of certification often use many of the same strategies as they make their way into building codes. Many owners also see the benefits financially from many of these strategies and wish to incorporate them into more of their projects. Risk in Bidding Much construction that is performed today is valued through a competitive sealedbid auction. This is a type of auction that requires qualified bidders to submit sealed bids by a fixed deadline. The bid is then opened and the lowest price or second lowest price bidder is awarded t he contract. The type of auction utilized in construction bidding generally involves both private and common value elements (Tang et al. 2006), though

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47 the auction is generally treated as a common value auction (Dyer 1996). This means that the bidders all have different estimates of the value of the project at the time that they bid, though the contract is generally believed to have the same value to each of the bidders. This valuati on is based on the degree of uncertainty that is involved in the project, causing risk averse bidders to submit higher bids and risk seeking bidders to submit lower bids, with risk neutral bidders submitting bids in the middle. This arises from the manner in which bidders with different risk preferences consider the uncertaint y. Risk Compensation Uncertainty always exists, but different bidders will view it under different lights. When a contractor faces a risk, the marginal utility of their income increases, leading to what is termed as precautionary bidding (Es 2003). This has the effect of causing bidders to bid less aggressively since the value of each dollar of income is increased as compared to the value of winning the auction. A risk averse ( => 1) bidder would presume the uncertain factors to consist of a proportionately larger latent cost than latent profit. This indicates that a risk averse bidder would perceive the uncertainties to contain a probabilistic negative profit. The risk seeking ( => 1) bidders would view this scenario another way. The risk seeker would perceive the uncertainties involved in the project to be latent profit that can be realized, versus being a risk with the potential to result in a loss. This means that the risk seeker believes that there is more profit in the project, and therefore is willing to submit a lower bid.

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48 This indicates that the risk seeking bidders are most likely to win the bid. This can have adverse consequences in several ways. The first is that th e risk seeking bidder may also be increasing the latent risk of the bid seller. By selecting the riskiest bidder, the entity offering the bid is taking on increased risk. If the risk seeking bidder is then unable to perform the contract and cannot compensate for the loss, the seller/owner may be forced to accept the cost for the failure of the contract. The owner may be unknowingly accepting this risk and may be unwilling to do so. If a very low bid is submitted, this could be an indication that this part icular bidder is a risk seeking bidder. There could be many reasons for this, including: Bidder may be struggling for work and is therefore willing to take on more risk or less return for a unit of work Economic conditions can have a significant effect, w ith many normally risk averse bidders more willing to take on risk in a market that has less work Bidder may not understand the risks involved Bidder may have unseen barriers in place in case of failure that could affect the owner in the event that the bidder fails to perform. Winners C urse Another unintended consequence of accepting the lowest bid is that the low bidder faces an adverse selection problem as they only win when he/she has one of the lowest estimates of the cost of construction (Dyer 1996). If bidders are not careful to account for this adverse selection problem, then th e low bidder may suffer from a winners curse when the bidder wins the auction but the bid is so low that it results in a bid that delivers below nor mal or even negative profits. In a potentially risky scenario, such as the additional risk burden that is assumed in the construction of a LEED certified

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49 building, this is a type of risk that can be compensated for through the increase in the bid price that is tendered for the project. The winners curse is a phenomenon that has been well studied in the past. This phenomenon was first identified in an article often cited entitled Competitive Bidding in High Risk Situations by Capen, Clapp and Campbell (1971). There were extr eme discrepancies in the realized value of the early outer continental shelf (OCS) oil lease auctions that began in 1954 (Dyer 1996). Values of the fields were exaggerated by very aggressive bidders that were bidding on items that had a value that was ver y difficult to define. Bidding spiraled out of control and some winning bidders found themselves in possession of oil field leases that provided very small if any returns for their initial investment. Similar claims have been made regarding auctions for book publication rights, in professional baseballs free agency market, and in corporate takeover battles (Dyer 1996). This outcome has proven to be pervasive even in a laboratory environment In a study conducted by Dyer et al. in 1989, it was shown that even sophisticated bidders, drawn from a pool of executives in the construction industry, suffered extensively from the winners curse. The 1989 study results showed that over 50% of the bids that were submitted (in the laboratory) were below the expected value conditional on winning the auction, so that half of the bids resulted in negative expected profit. This is a concern, because the owner that is asking for these bids may be unknowingly hiring a bidder that has put themselves in a position where th e project is not going to be profitable for them.

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50 Risks Associated with the Winners Curse The winning bidder is likely to not be pleased with the negative profit scenario that is associated with the winners curse in winning the auction. This is a danger ous position for both the winning bidder and the bid seller. The bidder may choose to not perform on the contract or may choose to try to make up for the lost profit through change orders or other means. Both of these scenarios will result in a higher than expected cost to an owner. This final cost may even be larger than some of the higher bids that were rejected, but were likely more responsible bids. Another potential out for a bidder that has fallen victim to the winners curse is the withdrawal of t he bid due to arithmetical errors In most states there exist laws that allow bidders to withdraw their bids without penalty (without loss of bid bond) if they believe that they have errors included in the bid. The interpretation of these errors can be q uite broad (Dyer 1996). While intended to include clear arithmetical errors that can occur, this can also be an out for a bidder that has made a mistake in generating a bid that is too low. There are some reasons that are given by owners that explain why they would allow a broad interpretation of these errors. The owner does not want a contractor working for them that has submitted a bid that is so low that they will certainly lose money on the job. A survey by Dyer and Kagel in 1996 developed some of t he reasons that were given that owners would allow a bid to be withdrawn: To preserve the relationship between the contractor and the owner To prevent damage to the contractor by forcing completion of the contract that could result in disruption to the job schedule Forcing forfeiture of bid bonds can result in the reduction of the number of bids on subsequent bids, causing an increase in the bid prices submitted based on bid models

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51 The resulting problems that occur from accepting performance on a bid that i s too low can result in effects on the owner and project that are similar to the effects of the winners curse on the bidders. Risk seeking bidders can therefore have a widespread effect on the auction, the project, and even subsequent auctions. Identifyi ng the Winners Curse One possible way to identify the winners curse in the auction environment is the quantification of the difference between the lowest and the second lowest bid. T his is commonly referred to as money left on the table This is money that the lowest bidder could still have collected and still have been the lowest bid. As the number of bidders ( n ) increases, bid amounts decrease, and the money left on the table should decrease also. The relationships are outlined in Table 215. Tabl e 215. Percentages of bid based on the difference range of bids tendered. Values derived from Dyer et al. 1996, page 1466. n: 4 7 12 Mark up needed to prevent winner's curse 60.0% 75.0% 84.6% Expected Profit 40.0% 25.0% 15.4% Money left on table 10.0% 3.6% 1.3% Contractors are generally aware of at least the effect of these factors, and make up for these deficiencies through increases in the bid price. The key findings of Fu et al.s 2002 study was that inexperienced contractors, largely without expertise and being wary of the winners curse, would submit higher bids in bidding. This is included in the bidding model that is proposed in Tang et al. 2006, and is presumed to be included in the contractors bid. This price increase is a result of the risk aversion policies of the contractor, and the contractors perceived risk associated with that particular project. Through examination of the winners curse and money left on the table, we can then determine :

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52 How the number of bidders affects the bid price and competition among bidders How the lowest bidder brings increased risk not only to themselves, but also to the bid seller. Experienced Bidders The experience of the bidder that is submitting the bid also has an effect on the bid price that is offered. The Fu et al. study of 2002 found that contractors who bid more frequently are more competitive than contractors that bid occasionally. While this serves to reflect in the overall bid strategy of the contractor, the effect was much stronger in construction work t hat was more standardized. While much of the work that is related to LEED construction is not considered standard yet, much of the work is repeatable from project to project. This would infer that the more LEED contracts that a contractor bids on, the more competitively priced that these bids will become. Construction experience can be considered as the synthesis of five components that apply to bidding as well, since bidding is seen as an integral part of the construction process (Fu et al. 2002): 1. Manag erial experience 2. Technological experience (construction methods) 3. Costing experience 4. Local experience (trade practice, legal environment, etc.) 5. I nstitutional experience (knowledge of clients preferences, etc.) These components are roughly equivalent to the types of the internal and external risks that the contractor faces that are outlined in Figure 2 4 The experience of the contractor in fact is a mechanism that allows the contractor to better deal with the r isks that are presented to them. As is discussed in this report, risk can be seen as either an opportunity for profit or loss. Experienced contractors have learned to limit their

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53 exposure to the downside of this risk, and the bids that they tender reflec t the reduction of this uncertainty. The Fu et al. study of 2002 concluded that the bidding performance of less experienced contractors is likely to be more erratic in terms of competitiveness. Following this logic, the more experienced that a contractor is, the more likely they are to bid not only competitively but also consistently. Risk and HPB There is an increased risk that is associated with constructing HPBs. This is particularly true with a building certification requirement under a system such as LEED, where a building can be considered a failure if it does not achieve the level of certification that is required by the owner. This risk is associated with a cost that is passed on to the owner by inclusion of a mark up on the bid price which can be called a LEED premium. The actual cost of this is often the first concern of an owner or other parties involved. Inexperienced bidders will likely have a less accurate estimation of the risk involved and the profits available, and are therefore more l ikely to overcompensate for a potential winners curse, raising the bid price in response to this risk. Bidding Model (Tang et al. 2006) Tang et al. 2006 developed a model that takes into account many of these the factors that are commonly referred to as t he bid climate, including the risk tendencies of a particular bidder. The basic models of bidding when related to construction projects assume that a buyer (bidder) purchases a single item from sellers in a oneshot auction. The number of bidders (n) and the probability distribution of bidders private information are assumed to be common knowledge. In the traditional model all bidders are also

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54 considered to be risk neutral (problems with this assumption are addressed in th e Tang et al. 2006 bid model). The Tang et al. 2006 formula differs from the standard bidding model in one important way. The standard bidding model assumes that all bidders are risk averse, while this is untrue in the low price bids that are applied in the construction setting. In an auction bidding environment, the bidders may all have different risk preference tendencies and will all compete for the same contract. This differs from the first assumption of the standard bidding model that states: All bidders are risk neutral The Tang et al. 2006 study sets up a model that allows for the variance in the bidders risk preferences of the various bidders. Other assumptions that will be made and are taken from the standard bidding model are: Every bidder has the independent in formation of estimating the bid Payment is just t he function of the price quoted The distribution of bidders price quoted is symmetric Model Factors In the modified model, the number of bidders is denoted as n These bidders are all assumed to be qualified to bid for the project in question. All of the bidders in the auction may have a different value of the project denoted by ci. These different valuations are all assumed to be independent and drawn from the same distribution of private values denoted by distribute function F on interval [ cl ch ], cl = min{ci}, ch = max{ ci} ( i = 1,2,3, n ), ci is a private value that is know n only to bidder i The cost ci is assumed to be estimated by bidders that are risk neutral, and therefore is not influenced by uncertain factors.

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55 The estimation of risk is defined as bidder i s estimation for uncertain factors and is denoted as c i. The value of c i and the degree that it influences the valuation ci depend on the risk preferences of the bidder i. Thus the valuation of ci is made up of three parts: first is ci affected by positive c i, second is ci aff ected by negative c i, and third is ci not affected by c i, representing the differing risk preferences of the bidders. So the payment to the bidder from the owner would be noted as: pi = ci + c i (2 1) Where pi denotes the payment to bidder i [ 1,1], represents the bidder i s risk taking preference with three cases; [ 1,0), presents risk seeking bidders degree of seeking risk (0,1], presents risk averse bidders degree of avoiding risk = 0 indicates that the bidder is risk neutral Therefore, if the assumptions of the model are true, then the bid price valuation bi submitted by bidder i can be represented by: bi = ci + ( ) + c I (2 2) T his model is an extended bidding model that considers the bidders risk preferences. The number of bidders lowers the price that is submitted, as the auction becomes more competitive. Bidders may also be aware of the rise in the number of bidders and their bid may reflect this. The model in equation (1) takes this into account but at the same time makes the value of the perceived risk and the risk preferences of the bidder distinct. In this model, the bidder i who submits the lowest price bi will win the bid in the lowest price sealed bid construction auction. If the bidder is risk neutral then = 0 and the quote price is equal to:

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56 bi = ci + ( ) (2 3) This model (3) is nearly identical to the standard bidding model. If the bidder i is risk seeking, then [ 1,0). When approaches 1, the suggestion is that the bidder will lower their price so as to win the construction contract by increasing their degree of risk seeking If the bidder is risk averse, then (0,1]. As approaches 1, the bidders will tend to i ncrease their bid price. The bidders hope to win the bid, but increase the risk based on the amount of risk perceived. The number of bidders ( n ) brings into effect two competing forces that change as the number of bidders increases (Dyer 1996). Since n is assumed to be known to all of the bidders involved, the bids are directly affected by this. As n increases, strategic factors promote lower bids, since any chance of perceived profit is contingent on winning the auction. The heightened awareness of adverse selection that occurs with the decrease in bid price competes with the strategic factors to form the function of the assumed equilibrium distribution that exists in the auction. Though there is evidence that the bid price initially decreases with r espect to n the expected winning bid is expected to decrease as n increases throughout (Dyer 1996). This phenomenon is exemplified in Figure 5 1 The conclusions of this model are that in a lowest price, sealed bid auction for a construction project, ri sk averse bidders will tend to quote a higher price, risk seeking bidders will submit a lower price, and risk neutral bidders will quote a price in the middle of the two. The risk seeking bidders are therefore more likely to win the bid for the constructi on project.

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57 CHAPTER 3 METHODOLOGY The aim of this study is to create a model that identifies and quantifies the perceived risks that are associated with LEED construction. This will be done by creating a spreadsheet that utilizes the Tang et al. model, l ocation factors, information from the GSA 2004 and Davis Langdon 2004 and 2007 studies and knowledge of risk practices and the LEED process. Standard Building Characteristics This is the cost of construction that is related to a project that is not seeking LEED certification. This is used to establish a base price for the project bid. This information is generated from a database of costs generated by EVstudio and RSMeans and found online (EVstudio 2010). These costs reflect the cost of educational facilities and was generated using April 2010 RSMeans information providing a cost for college classrooms, college dormitories, college student unions, and college laboratories. The cost was provided for each of the building types in many locations thr oughout the United States. The data that was generated by EVstudio i s provided in Figure 31 Figure 32 Figure 33 and Figure 34 The square foot costs of the buildings are extremely varied, and the particular type of building and location of the structure must be considered before the analysis. These calculations are for use as an example only and costs that are associated with a particular project should be used if the model is to be applied to a particular situation. It should be noted that these costs are used to generate a cost for a specific area of the country and will be later adjusted to reflect the type of demographic location that the actual structure is located in.

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58 Figure 3 1 Cost per square foot of college c lassroom facilities generat ed by EVStudio 2010 from RSMeans data April 2010. Figure 32 Cost per square foot of college dormitory facilities generated by EVStudio 2010 from RSMeans data April 2010.

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59 Figure 33 Cost per square foot of college student union facilities generated by EVStudio 2010 from RSMeans data April 2010. Figure 34 Cost per square foot of college student union facilities generated by EVStudio 2010 from RSMeans data April 2010.

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60 Level of Certification The level of LEED certification that is desired will have an impact on the level of risk to the contractor and therefore the value of the bids submitted for the construction of the project. The values that will be used are based on the average cost premiums of LEED certified projects as a percentage increase of the contract price. These premiums were collected from the 2004 GSA cost stu dy and are displayed in Table 31 Table 31 Percentage increases in cost of LEED certification from GSA 2004 study. Level of LEED Certification Maximum % Markup (Based on GSA Study) GSA Data Range Certified: 1.00% 0.4 % to 1.0% Silver: 4.40% 0.03% to 4.4% Gold: 8.10% 1.4% to 8.1% Platinum level certification was not included in the 2004 GSA study or the table above because the platinum level of certification requires an extraordinary level of performance to attain the required point level. A percentage increase is included in the model but is only applicable if the appropriate factors are known to an extent for the model to be useful. These factors can be very project specific and without specific information fall outside of the scope of the framework for the purposes of this model. The information in the GSA study is used to produce the model, and is not required for proper analysis. The GSA study was used because of the extent of data that was available in the study, which was useful for developing the model. The results of this study are certainly not appropriate for all scenarios. The percentages shown in Table 3 1 can be changed to fit any particular scenario without adjusting the model. The percentages in Table 31 are used to establish a baseline for the perceived uncertainty and may be adjusted to fit a particular project but should be accompanied with other data inputs that are consi stent with that particular scenario.

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61 Soft Costs There are two types of costs that are represented in the increase in costs that are seen in the construction of a LEED certified building (Northbridge 2003). These costs are construction costs and soft costs Soft costs are costs that are not directly related to the construction of the building, but are necessary and in addition to original building estimates. These costs are outlined as percentages in Table 32 Table 32 Estimates of LEED related soft c osts derived from the Northbridge Environmental report 2003, p. 6. Cost Category Estimated % Range Design Costs 0.5% 0.4% 0.6% Commissioning 1.0% 0.5% 1.5% Documentation and Fees 0.7% 0.5% 0.9% Energy Modeling 0.1% 0.1% Total 2.3% 1.5% 3.1% *For GSA data, use : 0.25% The soft costs are considered part of the cost in achieving LEED certification, but do not represent an increase in the cost to the contractor, except for a portion of the documentation costs, and will therefore be subtracted from the total estimated LEED mark up for the project. The information that is supplied by the GSA study, when used in the model, will reflect a lower percentage of soft costs since much of this additional work is already included in the cost estimates. Subtracting the soft costs will allow the analysis of only the costs associated with the direct construction costs of the building. Risk Aversion The risk aversion segment of this model will be based on the auction model developed by Tang et al 2006. This model is defined as: bi = ci + ( ) + c i ( 2 2 ) where:

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62 bi = expected bid from contractor i ci = bidder i s perceived value of a project the common value of the auction, or the base line construction estimate as provided by RSMeans ch = expected value of the high bid described as twice the bidders perceived risk to represent a worst case bidder n = number of bidders determined by a base case number further refined by the appropriate adjustments = risk behavior of contractor i determined by the risk aversion behavior of the particular contractor c I = perceived risk to contractor i product of the base price of the project, an expected cost of LEED certification as determined in t he GSA 2004 study to represent LEED related risk in excess of the standard bui lding risk, and the Experience Factor. Perceived Value; ci The perceived value of the project is assumed to be the cost of the construction that is related to the project based on the RSMeans estimate that was described in Standard Building Characteristics. Based on the Davis Langdon studies of 2004 and 2007, there is no measureable difference in the average value of a standard building and the value of a LEED certified building. Following t his, the value of the project to the contractor should not be more than the estimated construction costs of the project. LEED re lated costs are expected to be extra costs that are a factor of the LEED Premium that is placed on general construction tasks due to the increased risk. Assuming that this value is the same for all bidding parties defines the designation of a common value auction, meaning that all bidders will receive the same benefit from winning the contract. There is some debate as to whether this definition fits a construction auction exactly, but for the purposes of modeling, this assumption must be made.

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63 High Bid; ch Research on bid ranges showed that bid results can vary wildly dependent on a variety of factors, and there is little dat a on predicting what a high bid will be. To set a baseline for the model, the high bid is set to the perceived value, representing a scenario in which all of the bids submitted at the same price, therefore not affecting other bids. For the example projec t scenario the high bid is assumed to be the base cost of the building, ci, plus twice the expected mark up as related to certific ation level defined in Table 31 This provides an ample range for bid prices, without disabling the model. In a specific situation, the owner that is putting this contract out would generally have an accurate representation of this number. For the purposes of the model, this number only needs to be predicted to demonstrate the behavior of the other variables. Number of B idders; n The number of bidders ( n ) is entered as an expected value that is then adjusted for several environmental factors c ollectively referred to as the bidding env ironment The initial number of expected bidders would have to be determined from historical precedence that would be specific to the type of project that is being constructed. For the purposes of normalizing this model, a base case of 10 expected bidders was used. This number decreased as the level of certification increased as shown in Figure 36 This number would then be adjusted for economic conditions as described by the bidding climate and economic factor. Bidding climate/economic factor The s trength of the economy at the time of the auction will affect the number of bids that are submitted. This phenomenon is described in the LEED Associated Risk section and is determ ined using the data in Table 33 The economic factor is multiplied by the number of bidders expected under

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64 normal conditions to simulate a reduction in n during stronger economic times or an adverse bid climate. If the number of bidders is known previous to the construction of the model, this factor can be ignored, but determ ination of the number of bidders is important to the accuracy of the model, and should be adjusted accordingly to match the expected bidding environment. Table 33 Economic factor multipliers for the base case of the risk model. Bid Climate Factor Very Restricted Climate 0.50 Restricted Climate 0.75 Stable Climate 1.00 Open Climate 1.25 Very Open Climate 1.50 Risk B ehavior; The risk behavior of a particular contractor must be identified and entered into the model. This factor will be different for each particular contractor, and may vary with time. This factor is more clearly defined in the section titled Risk This fact or is defined directly from the chart in Table 34 and entered into the model. This factor represents the risk aversion behaviors of the contractor that is bidding on the project. Very risk averse would mean that the contractor has a strong aversion to taking on any additional risk, while a Very risk seeking bidder would be willing to take on more risk in a project. This factor is applicable to the current project only, and may differ for the same contractor when considering other projects. Table 34 Table for determination of the risk factor for a particular contractor. Risk Policy Factor Very risk averse 1.0 Somewhat risk averse 0.5 Risk Neutral 0.0 Somewhat risk seeking 0.5 Very risk seeking 1.0

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65 Experience The experience in bidding and construction for a particular contractor will have an effect on the bid that is submitted. The factors that are used to define the Experience Factor for a specific contractor are shown in Figure 29 This factor is used to represent the amount of experience that a certain contractor has in a specific type of construction. In this case the contractors experience would be experience with LEED certified projects, though experience with general construction relative to the project would play a part in deter mining this factor. This factor may also vary among the levels of LEED certification. If a contractor had extensive experience in LEED certified buildings but had never constructed any building higher than LEED Silver, the experience factor may be less i f the certification level desired is Gold or Silver. An experience level of 1 represents an average level of experience in the type of project being considered. The potential values shown in Table 35 reflect potential values, but does not represent the limits of these values. Table 35 Determination of experience factor for a specific bidder, relative to a specific project. Experience Level Factor Very Experienced Bidder 0.90 Experienced Bidder 0.95 Average Experience 1.00 Very Little Experience 1.15 Inexperienced Bidder 1.30 Experience will be related to the particular project with a specific contractor. LEED related projects often pursue varying strategies for achieving points, and experience with a strategy in the past could have an effect on the experience of the contractor. Experience with a certain level of certification could also affect this value. Location

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66 could also play a part, if the contractor has performed multiple projects in the location and is familiar with the local requirements and conditions. Location The results from the model and the inputs must be subjected to a further adjustment for the location of the project. From the Tang et al. (2006) model there is determined what will be called a LEED Uncertainty Cost. This is the amount of extra cost that wo uld be added onto the original building price for the total in the contractors bid. The final adjustments that must be made for this price are: Proximity to s ervices. The Davis Langdon study of 2004 determined that there are benefits from having a proj ect in an urban setting. This phenomenon is examined in depth in the Cost of LEED section of this study. The factors in Figure 210 are used to reflect the effect of demographic location on the expected bid price. These factors are specific to this example, as extraordinary conditions may exist for a specific project. This could occur if the project is located in an area that is par ticularly capable of providing services or infrastructure that is beneficial to the LEED rating system. It should be noted that locations exist where LEED is impossible to attain or is prohibitively expensive. This model assumes that neither of these conditions exist and that there are no extremely adverse conditions that occur that limit the feasibility of the project Table 36 Factors for determining costs related to the proximity to urban centers. Data derived from Mathiessen and Morris 2004 Proxim ity to Services Factor Very urban location 0.50 Somewhat urban location 0.75 Suburban location 1.00 Somewhat rural location 1.25 Very rural location 1.50

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67 Climate f actor. The climate that a project is located in also has an effect on the amount that LEED certification will cost. The additional cost associated with the climate that a project is located in is defined in the Davis Langdon study of 2004. The results of that study are shown in Table 37 Table 37 Percentage increase in LEED costs as related to climate. Data derived from Mathiessen and Morris 2004. Location Certified Silver Gold Platinum Mild Coastal 1.00% 2.70% 7.80% California Central Valley 3.70% 5.30% 10.30% Gulf Coast 1.70% 6.30% 9.10% Northeast Coast 2.60% 4.20% 8.80% Rocky Mountain 1.20% 2.80% 7.60% Average Increase: 2.04% 4.26% 8.72% The percentages shown in Table 37 are increases in LEED costs over standard construction costs and are related to energy use, cost of energy, temperature fluctuations and relative humidity. Location f actor The two factors related to the location of the project have been combined into what will be called the Location Factor. The factor is t he product of the proximity multiplier and the percentag e increase defined in Table 37 as the Climate Facto r. The table shown in Table 38 shows the result of this calculation. The column for Location Factor is the result of subtracting the Location Per centage Increase from the Average Location Increase and multiplying the result by the Proximity Factor. Table 38. Calculations for Location Factor. Certification Level Location % Increase* Proximity Factor Average Location Increase Location Factor Certified 0.00 0.00% 0.00% Silver 2.04% 0.00 2.04% 0.00% Gold 4.26% 0.00 4.26% 0.00% Platinum 8.72% 0.00 8.72% 0.00%

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68 Assumptions The Davis Langdon (2004) study outlined seven factors that affect the cost of LEED certification. Of the seven the first three will be used to calculate expected bids using the model described. These three factors are: 1. Demographic Location 2. Bidding Climate and Culture 3. Climate Assumptions are made involving the remainder of the factors listed in the Davis Langdon (2004) study. These remaining factors are assumed to be true and constant. 4. Project owners and team members are fully invested in the certification of the building 5. The goals of certification are outlined sufficiently earlier in the project to avoi d any negative effects, and the design is as fully developed at time of bidding as is normally expected 6. The size of the building only affects the overall cost of the building and systems, and the relative cost is unchanged over a reasonable range of cos ts and building size 7. Point synergies will be used to all possible effect for each given project. This will be different for each building, and would be impossible to predict for a general sampling. For the purposes of this model, factors 4 7 are assumed to be normal and average. This does not indicate that this is the case in all construction projects. These factors are likely to be variable in a real world scenario, but to make this model effective and valid these must be assumed so that heterogeneity of the data may be preserved. For this reason the factors will be divided into five categories. The first three categories will represent 3/5 of the LEED/Risk Premium, with the final four categories representing 2/5 of the LEED/Risk Premium as gh ost categories that are assumed to not affect the amount of perceived risk for the purposes of this model.

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69 Calculations The factors and costs that were addressed in Modeling Factors will be used to calculate the risk based LEED costs and bid amounts. Th e flow of the calculations is outlined in Figure3 5 and the spreadsheet form is shown in Figure 3 6 Figure 3 5. Interactions of the factors and costs associated with the calculation of LEED premium. Calculation Table The calculations are listed by col umn as follows from Table 39 : A. Base Cost This is the cost of the building without any LEED certification. This is generated from RSMeans and is adjusted for the project location. B. Certification Level This is the level of LEED certification that i s desired. This is defined as Certified, Silver, Gold, and Platinum. C. Average LEED Risk % This is the average LEED percentage markup that was found in the GSA (2004) study. This value is applied to the Base Cost as a baseline value and to provide inputs for other equations including high bid and perceived risk.

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70 D. LEED Uncertainty This is the cost increase that is expected to be seen based on the cost of a standard building, the level of certification that is desired, and the experience level of the contractor submitting the bid. E. Risk Aversion Factor This is the factor that is described by the Tang et al. (2006) risk model. This model takes into account the perceived value of the project, the expected number of bidders, the expected high bid, the perceived risk to the contractor, and the risk tendencies of the contractor. The factor is defined as the difference ratio of the expected bid price to the perceived value of the contract. F. Risk Aversion Premium The premium, in dollars, that is a result of the increase of the bid price using the Risk Aversion Factor. This is a portion of the total increase in the cost found in Column K. This factor is assumed to make up 80% of the value of the total increase found in Column K. G. Project Locati on Factor This factor is related to the difference of the cost of LEED certification in different geographical locations. H. Location Premium The premium, in dollars, that is added to the base price of the building to achieve LEED certification. This is a factor of the total LEED risk price and is assumed to make up 20% of the total increase found in Column K. I. Experience Factor This factor is determined from the table shown in Figure 25 and is entered directly into the spreadsheet. This value may differ for different levels of certification. J. Calculated LEED Premium % This is the increase, in percentage, that is observed from the calculated LEED/Risk based premium and the Base Cost of the building. K. Calculated LEED Premium This is the tota l result of the calculations including the Risk Aversion Premium, the Location Premium, and the Experience Factor. Represents the total cost increase over the Base Cost that is expected. L. LEED Premium Baseline Value of LEED costs when no other factors are included. Represents the average current cost of LEED construction and is used as a baseline to compare other calculations. M. Total Expected Project Cost The base cost of the project plus the anticipated LEED/Risk Based Premium. N. LEED Related So ft Costs Calculated at 1.6% of the construction costs. This cost represents the soft costs that are not directly bore by the contractor. O. LEED Based Increase in Construction Costs Represents the increase in costs that can be expected over the standard costs of a building.

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71 P Total Risk Adjusted Bid Price Value of the bid that can be expected to be submitted by contractor i for the given LEED certified project.

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72 Table 3 9 LEED Premium and Bid Amount calculation table. From Table 2 From Table 3 Column B A x C x I (or Entry x I) Table 9 Column H 0.8 x D x E From Table 12 0.2 x D x G From Table 7 A B C D E F G H I Base Cost Certification Level Average LEED Risk % Perceived LEED Uncertainty Risk Aversion Factor [ 1,1] Risk Aversion Premium ($) Project Location Factor [ 1,1] Project Location Premium ($) Experience Factor $ Certified 1.00% $ 0.00% $ 0.00% $ 0 $ Silver 4.40% $ 0.00% $ 0.00% $ 0 $ Gold 8.10% $ 0.00% $ 0.00% $ 0 $ Platinum 12.00% $ 0.00% $ 0.00% $ 0 K/A (F + H) x I A + D A + K Table 13 Value x A K N A + O J K L M N O P LEED Premium % LEED/Risk Based Bid Premium Value Using Average Risk Scenario Total Expected Project Cost Soft Costs Additional LEED Related Construction Costs Total Bid for Constructi on Costs 0.00% $ $ $ $ $ $ 0.00% $ $ $ $ $ $ 0.00% $ $ $ $ $ $ 0.00% $ $ $ $ $ $

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73 CHAPTER 4 ANALYSIS To represent the method of using the model developed in this study, an example will be used for demonstration. A baseline scenario will be conducted to verify the accuracy of the model, and then an analysis of the input factors will be performed. Example Project Proje ct This project will be a c ollege classroom in Atlanta, Georgia. This building will encompass 55,000 square feet and will be evaluated for potential costs related to LEED certification. The project is located in a dense urban area. The project is expect ed to occur during a time of strong economic growth, with an open bidding environment. Bidder The model proposed is sensitive to the specific properties of the bidder. The bidder is a large company that is rated very risk averse. The bidder has relatively little experience in LEED related projects. Analysis Base Price The base price of the structure, in Atlanta, Georgia, is calculated using the RSMeans tables. Calculated value is $8,283,000.00 Level of Certification Table 3 1 shows the expected (average) costs for the corresponding level of LEED certific ation. These factors are based on the 2004 GSA study and are appropriate for this type of building. All of the factors will be applied to demonstrate the use of the

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74 model. It should be noted that for this example, the highest cost estimations will be used from the GSA 2004 study. Table 41 Expected LEED costs for example 55,000 squar e foot classroom in Atlanta, GA with a base value of $8,283,000. Maximum mark up amounts will be used for the example. Values based on GSA 2004 data. From GSA or Enter Value Table 2 value x B Table 2 value + C A B C D Level of LEED Certification % Markup (Based on GSA Study ) Additional Perceived Risk Premium Total Expected Building Cost Certified: Max 1.00% $82,830 $8,365,830 Min 0.4% $(33,132) $8,249,868 Silver: Max 4.40% $364,452 $8,647,452 Min 0.03% $(2,484) $8,280,515 Gold: Max 8.10% $670,923 $8,953,923 Min 1.4% $115,962 $8,398,962 Platinum*: Max 12.00% $993,960 $9,276,960 *No data exists in the GSA 2004 study for Platinum level certification. Baseline Case First, an analysis showing the average or expected value of the project with the associated LEED certification scenarios. In this case, all variables will be set to the assumed average default value to validate the accuracy of the model. The results of this analysis are shown in Table 42 In the baseline case, the expected bids and costs are equal to the increases that are expected to be observed. This reflects an average scenario that does not take into account the specific factors associated with a particular project and contractor. From this analysis it can be shown that the expected total costs are as follow in Table 43 and 44 The relationships between the expected and standard costs are outlined and reflect the calculations in the model. Note that the expected cost of the structure is equal to the calculated cost as shown in Table 42 and the expected values in Table 43 This shows that the model is

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75 Table 4 2. Calculation of costs in the baseline scenario. From Table 2 From Table 3 Column B A x C x I (or Entry x I) Table 9 Column H 0.8 x D x E From Table 12 0.2 x D x G From Table 7 A B C D E F G H I Base Cost Certification Level Average LEED Risk % Perceived LEED Uncertainty Risk Aversion Factor [ 1,1] Risk Aversion Premium ($) Project Location Factor [ 1,1] Project Location Premium ($) Experience Factor $8,283,000 Certified 1.00% $95 ,254 1.13% $ 77,067 0.00% $19,050 1.15 $8,283,000 Silver 4.40% $ 419,119 5.13% $ 352,507 0.51% $83,396 1.15 $8,283,000 Gold 8.10% $ 771,561 9.90% $ 678,356 1.02% $155,886 1.15 $8,283,000 Platinum 12.00% $ 1,143,054 15.20% $ 1,053,438 0.19% $229,045 1.15 K/A (F + H) x I A + D A + K Table 13 Value x A K N A + O J K L M N O P LEED Premium % LEED/Risk Based Bid Premium Value Using Average Risk Scenario Total Expected Project Cost Soft Costs Additional LEED Related Construction Costs Total Bid for Constructi on Costs 1.16% $96,118 $ 8,378,254 $ 8,379,118 $20,550 $75,567 $8,358,567 5.26% $435,904 $8,702,119 $ 8,718,904 $21,344 $ 414,5 59 $8,697,559 10.07% $834,243 $9,054,561 $ 9,117,243 $22,209 $ 812,033 $9,095,033 15.48% $1,282,483 $ 9 ,426,054 $ 9,565,483 $23,120 $1,259,363 $9,542,363

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76 Table 43 Determination of baseline analysis. LEED Increase Compared to Average Certification Level Base Cost LEED Average Calculated $ Difference % Difference Certified $ 8,283,000 8,378,254 $ 8,379,118 $ 863.64 0.01% Silver $ 8,283,000 8,702,119 $ 8,718,904 $ 16,784.35 0.19% Gold $ 8,283,000 $ 9,054,561 $ 9,117,243 $ 62,681.65 0.69% Platinum $ 8,283,000 9,426,054 $ 9,565,483 $ 139,429.73 1.48% Table 4.4. Determination of baseline analysis. Certification Level Base Cost LEED Average Total Project Increase Compared to Non LEED $ Difference % Difference Certified 1.00% 1.16% $ 96,118.14 1.16% Silver 4.40% 5.26% $ 435,904.15 5.26% Gold 8.10% 10.07% $ 834,243.10 10.07% Platinum 12.00% 15.48% $ 1,282,483.73 15.48% capable of predicting the baseline scenario when all of the variables are set to assumed normal conditions. There is no difference in the calculated values versus the expected values. The effects of the changes to these variables are all based on this scenario, to more easily determine the effects of the changes of certain conditions. Following the establishment of this baseline, the variables associated with the specific case will now be input. Bid Climate The climate of the bidding pool and environment must be determined. These factors are described using the Economic Factor ( Table 45 ) to determine the number of bidders and the Experience Factor ( Table 46 ) to determine perceived risk in the final analysis. The economic factor affects the number of bidders, and the experience factor affects the perceived risk to the contractor. Heightened experience levels result in a lower perceived risk.

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77 Table 4 5 Economic factor determination will result in the selection of 0.75 reflecting a strong external economic condition and restricted bid environment. Climate Description Factor Very Restricted Climate 0.50 Restricted Climate 0.75 Stable Climate 1.00 Open Climate 1.25 Very Open Climate 1.50 Table 46 The determination of the Experience Factor will result in the selection of a factor of 1.15. Experience Level Factor Very Experienced Bidder 0.70 Experienced Bidder 0.85 Average Experience 1.00 Very Little Experience 1.15 Inexperienced Bidder 1.30 The number of bidders is assumed to be 10 in an ideal environment. The Economic Factor and the Level of Certification are used to adjust this number based on the bidding environment as shown in Table 4 7 Table 47 Determination of the number of bidders Level of Certification Expected # of Bidders Bid Climate Factor # of Bidders Certified 10 0.75 8 Silver 8 0.75 6 Gold 6 0.75 5 Platinum 5 0.75 4 Risk Aversion The example bidder is described as very risk averse, which will result in an elevated Risk Aversion Factor A Risk aversion factor of 1.0 has been selected to correlate with the determination that the bidder is very risk averse. This will serve to elevate the effect of the amount of perceived risk involved in the project The determination of this factor is shown in Table 48

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78 Table 48 Determination of bidder's Risk Aversion Factor. A factor of 1.0 has been selected to represent the example scenario. Description of Bidding Entity Very risk averse 1.0 Somewhat risk averse 0.5 Risk Neutral 0.0 Somewhat risk seeking 0.5 Very risk seeking 1.0 Using the Tang et al. 2006 model and the inputs t hat have been derived thus far the amount of the bid based on uncertainty can be determined as shown in Table 49 The Tang et al. 2006 risk model is defined as: bi = ci + ( ) + c i (2 2) where: bi = expected bid from contractor i ci = bidder i s perceived value of a project ch = expected value of the high bid n = number of bidders = risk behavior of contractor i c i = perceived risk to contractor i Table 49 Risk Aversion calculation using the model described in Tang et al. 2006. Level of Certification Perceived Value Expected Bid Value Risk Aversion Factor Certified $ 8,283,000 $ 8,376,874 1.13% Silver $ 8,283,000 $ 8,708,194 5.13% Gold $ 8,283,000 $ 9,103,017 9.90% Platinum $ 8,283,000 $ 9,542,016 15.20% Location The location of the project is in Atlanta, Georgia, which will be considered a gulf coast location for the purpose of using the Davis Langdon 2004 location adjustments. The appropriate Proximity Factor has also been selected to represent the fact that the project is located in a downtown urban location. The combination of these factors is defined in Table 410

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79 Table 410. Adjustment factors for location of the example project. Certification Level Location % Increase* Proximity Factor Average Location In crease Location Adjustment Certified 0.50 0.00% 0.00% Silver 1.70% 0.50 2.04% 0.51% Gold 6.30% 0.50 4.26% 1.02% Platinum 9.10% 0.50 8.72% 0.19% The Location Adjustment represents the aggregate effects of the Location Increase and the Proximity to Services. The observed negative value under the Certified level scenario shows that due to the location of the project, the cost is less than the average increase that is expected. Soft Costs Soft Costs represent the value of the costs that are not directly related to the construction of the project. Since this example is using the GSA costs for analysis, most of these costs are included in the pri ce increase, and can be left out. The increase in soft costs for the GSA analysis result in an increase of 50 cents per square foot, or 0.25% of the per square foot cost. The result will be a soft cost value of 0.25% that will represent the cost of Docum entation and Fees. This cost will be used since it is also applicable in an institutional environment such as a college campus. Many institutional entities use the same type of standards that the GSA uses, and these calculations are more appropriate. Si nce this project related to a school campus the data from the GSA study is appropriate. This will vary for each scenario, but for this example it will be assumed that the institution in question is using standards similar to the GSA including requiring commissioning, and minimum energy performance. This cost is quantified in Table 411, and is expressed as a percentage of the overall costs of the construction project. Note that in the GSA study this is calculated as a per square foot cost.

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80 Table 411. E stimated Soft Costs. 0.25% will reflect GSA data. A B C Cost Category Estimated % Range Design Costs 0.5% 0.4% 0.6% Commissioning 1.0% 0.5% 1.5% Documentation and Fees 0.7% 0.5% 0.9% Energy Modeling 0.1% 0.1% Total 2.3% 1.5% 3.1% Enter Soft Costs: 0.25% Expected Costs The results of the analysis are shown in Table 413 Results This example highlights the effects of the decision to pursue LEED certification on the expected overall and construction costs of the project. The increase that is shown in the example is greater than the baseline case due to the following factors: High risk aversion factor Decreased number of bids due to the effects of the bidding climate Increased costs due to the lack of experience of the contractor The results of the calculations in the example case are highlighted in Figure 41 2 Table 412. Comparison of baseline case to example scenario. LEED Increase Compared to Average $ Difference % Difference $ 863.64 0.01% $ 16,784.35 0.19% $ 62,681.65 0.69% $ 139,429.73 1.48% Total Project Increase Compared to Non LEED $ Difference % Difference $ 96,118.14 1.16% $ 435,904.15 5.26% $ 834,243.10 10.07% $ 1,282,483.73 15.48%

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81 Table 413. Results of model calculations using the example scenario showing the costs of LEED certification. From Table 2 From Table 3 A x C x I (or Entry x I) Table 9 Column H 0.8 x D x E From Table 12 0.2 x D x G From Table 7 A B C D E F G H I Base Cost Certificati on Level Average LEED Risk % Perceived LEED Uncertainty Risk Aversion Factor [ 1,1] Risk Aversion Premium ($) Project Location Factor [ 1,1] Project Location Premium ($) Experience Factor $8,283,000 Certified 1.00% $95,254 1.13% $77,067 0.00% $19,050 1.15 $8,283,000 Silver 4.40% $419,119 5.13% $352,507 0.51% $83,396 1.15 $8,283,000 Gold 8.10% $771,561 9.90% $678,356 1.02% $155,886 1.15 $8,283,000 Platinum 12.00% $1,143,054 15.20% $1,053,438 0.19% $229,045 1.15 K/A (F + H) x I A + D A + K K N A + O J K L M N O P LEED Premium % LEED/Risk Based Bid Premium Value Using Average Risk Total Expected Project Cost Soft Costs Additional LEED Related Construction Costs Total Bid for Construc ti on Costs 1.16% $96,118 $ 8,378,254 $8,379,118 $ 20,550 $ 75,567.71 $ 8,358,567 5.26% $435,904 $ 8,702,119 $8,718,904 $ 21,344 $ 414,559 $ 8,697,559 10.07% $ 834,243 $ 9,054,561 $9,117,243 $22,209 $812,033.80 $9,095,033 15.48% $ 1,282,483 $ 9,426,054 $9,565,483 $23,120 $1,259,363 $9,542,363

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82 Sensitivity Analysis A sensitivity analysis has been performed to demonstrate how the LEED related costs change as the inputs are altered. The purpose of the model is to be able to see the relationships between the variables that affect the costs of LEED construction, and a sensitivity analysis will help to highlight th ese effects. A sensitivity analysis was conducted and the results are shown in Figures 4 1 to 4 7 This analysis will help to evaluate the effects and relationships that are involved in the model. The supporting data is found in Appendix A. Certified Lev el Building The analysis of this building is shown in Figure 4 1 The most sensitive factor of the ones that are depicted here is the risk aversion factor. Proximity to services has no effect as this was the result of the Davis Langdon (2004) study. The strength of the economy had the predicted effect of increasing costs as the economy became stronger. This is due to the increased risk aversion of the bidders and the resultant decrease in the number of bidders that are willing to submit a bid on the project. This effect is small, as predicted for a Certified level project, since the perceived risk of this level of certification is relatively small. Silver Level Building The analysis under the Silver level of certification is shown in Figure 4 2 The mo st sensitive factor of the ones that are depicted here is the risk aversion factor. Proximity to services has a small effect as this was the result of the Davis Langdon (2004) study. The strength of the economy had the predicted effect of increasing cost s as the economy became stronger. This is due to the increased risk aversion of the bidders and the resultant decrease in the number of bidders that are willing to submit a

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83 bid on the project. This effect is small, as predicted for a Silver level project since the perceived risk of this level of certification is relatively small, but is noticeably larger than the effect of the economy that was seen in the Certified level project. This is due to the higher level of risk that is associated with the higher level of certification. Gold Level Building The analysis of the Gold level certified building is shown in Figure 4 3 The most sensitive factor of the ones that are depicted here is the risk aversion factor. Proximity to services has a small effect as w as the result of the Davis Langdon (2004) study. The strength of the economy had the predicted effect of increasing costs as the economy became stronger. This is due to the increased risk aversion of the bidders and the resultant decrease in the number o f bidders that are willing to submit a bid on the project. This effect is larger, as predicted for a Gold level project, since the perceived risk of this level of certification is relatively large, and is noticeably larger than the effect of the economy t hat was seen in the Certified and Silver level projects. This is due to the higher level of risk that is associated with the higher level of certification. The additional risk results in a lower number of bidders that are willing to compete for the project, and this is increased as the economic condition strengthens. Platinum Level Building The analysis of the Platinum level building is shown in Figure 4 4 The most sensitive factor of the ones that are depicted here is the economic factor, surpassing th e effects of the Risk Aversion Factor. Proximity to services has a small effect as was the result of the Davis Langdon (2004) study. The strength of the economy had the predicted effect of increasing costs as the economy became stronger. This is due to the increased risk aversion of the bidders and the resultant decrease in the number of

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84 bidders that are willing to submit a bid on the project. This effect is very large, as predicted for a Platinum level project, since the perceived risk of this level of certification is large, and is noticeably larger than the effect of the economy that was seen in the other levels of certification. This is due to the higher level of risk that is associated with the highest level of certification. The additional risk r esults in a much lower number of bidders that are willing to compete for the project, and this is amplified as the economic condition strengthens. Risk Aversion The analysis of the effect of risk aversion is shown in Figure 4 5 Increases are relatively s mall for the lower levels of certification since the perceived risk to the contractors is small. Since the risk is small, even the most risk averse contractors do not place a large additional premium on the construction costs. This condition changes as t he level of certification rises. As higher levels of certification are pursued, the amount of risk to the contractor is increased. For risk seeking contractors, this has less of an effect than that seen with the risk averse contractors. As the perceived risk, and the risk aversion of the contractor increases, the total effect on the cost of the project begins to amplify more quickly. This effect would be more pronounced if the perceived risk is increased, or the contractor has a higher level of risk aversion. Number of Bidders The analysis of the effect of the number of bidders is shown in Figure 4 6 This effect increases as the level of certification that is being pursued is increased, due to the level of risk that is associated with the level of cert ification. Larger numbers of bidders has the effect of heightened competition which drives down the cost of the project. When put into the model, the effect of having a very small number of bidders increases

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85 steeply as the certification level rises If a project has a small number of expected bidders, the owner should take actions to increase the number of bidders. This could be accomplished by lowering the level of certification as shown in this figure. Experience The analysis of the amount of experience that the contractor has is shown in Figure 4 7 This demonstrates the amount of the increase in LEED related costs are a function of the perceived risk of the contractor and the amount of experience that the contractor has in that particular type of building. As experience increases, perceived risk dim inishes and becomes part of the standard cost. This has the effect of removing the volatility of the price increase since the additional costs are no longer affected by the risk policies of the bidder This accurately reflects the limited experience that contractors have with higher levels of LEED certification and the large cost increases that are associated with these projects. Figure 4 1 Graphical representation of the effects on certain variables on the LEED associated increase of construction cos ts on a Certified level building.

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86 Figure 4 2 Graphical representation of the effects on certain variables on the LEED associated increase of construction cos ts on a Silver level building. Figure 4 3 Graphical representation of the effects on cer tain variables on the LEED associated increase of construction costs on a Gold level building.

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87 Figure 4 4 Graphical representation of the effects on certain variables on the LEED associated increase of construction costs on a Platinum level building. Figure 4 5 The effects of various risk aversion behaviors on the additional cost of LEED construction.

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88 Figure 4 6 The effect of the number of bidders has a definite effect on the increase in constru ction costs of a LEED project. Figure 4 7 The effects of the level of experience of the contractor and the level of certification

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89 CHAPTER 5 SUMMARY AND CONCLUSIONS Summary Green building, while becoming the standard in modern construction, still has risks involved from the view of the contractor. This is evidenced by the increase in the bid price that is seen in projects that pursue a level of green certification under a building rating system such as the LEED system that has become enormously popular in the United States. The level of risk that i s included in a project varies, and the behaviors that the contractor follows to deal with this risk vary also. While each project is unique, the goal of this study is to help to define some of the interactions that occur between the variables that define the included risk and the ways that this can affect a construction project. This was accomplished through the use of a model that allows the calculation of an expected bid price based on a number of variables and assumptions that take into account; standard building price, perceived risk, risk aversion policies, bidding environment, experience, and location factors. This model can be used to examine the interactions between these factors, and the resultant effects on the price of a project. Conclusions T his study produced a number of meaningful conclusions. Through the sensitivity analysis it can be shown how the variables included in the model interact with each other. From this analysis of an example project, it was seen that the factor that had the m ost impact on the project price was the bidding environment. When the bid environment becomes too hostile, the bid prices that are seen tend to spike, particularly in the higher levels of certification as shown in Figure 51 This is due to the severe decrease in the number of bidders that are willing to bid on the project. As the number

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90 of bidders approaches zero, the cost of the project goes to infinity. As the number of bidders increases, the price comes down, but at a slower rate as the number of bi dders gets larger. This creates an optimal range of the number of bidders that is project specific and should be analyzed. Figure 5 1 Effects of the number of bidders on a LEED Gold project The perceived risk that the bidder recognizes is pushed thr ough to the owner as an increase in the cost of a project. This perceived risk is then amplified or partially negated by the risk behavior of the contractor. If high performance buildings are to become the standard buildings in the future and be priced s imilarly, this perceived risk must be eliminated. What remains to be seen is whether this additional price will be absorbed into the standard building price, or will be removed entirely. If it were absorbed into the standard building price, the cost of t hese buildings would not be reduced, but the variations in the bids would become smaller as experience increased

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91 and the extra cost would cease to be an extra risk premium and would become part of the standard building cost. The other option is that the c ost currently associated with risk could disappear. If this cost is solely based on risk and has no grounding in actual costs, then the cost may vanish as the contractor pool becomes more sophisticated. The true solution is probably somewhere in the middl e. There is evidence that LEED projects do cost more, such as direct costs that are required for enhanced documentation, and extended schedules. These costs though, are relatively minimal. Most of the extra cost that is witnessed in certified projects s tems from the perceived risk of the contractor, and the negative effect on the bidding environment that this risk entails. As contractors become more experienced perceived risk should be reduced. Contract language will be refined that will appropriate ri sk in a more standardized manner, allowing for the construction industry to become accustomed to this type of environment. This will promote a more open bidding environment that will allow for a more beneficial, competitive auction environment.

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92 CHAPTER 6 RECOMMENDATIONS FOR FURTHER STUDY Some interesting opportunities for future research are presented in this study. The model should be used to evaluate real world data and applied to a specific situation. A particular owner could learn how their decisions could affect expected bids, of a contractor could use this tool to become more aware of the bidding environment that they are entering into. This may make the participant more educated on the factors that affect decisions in this arena. One area is in t he effects that contract language has on the perceived risk to the bidder in a green building scenario. Some contracts have wording in them that makes certification such as LEED the responsibility of the contractor. This is questionable since most of the LEED credits are geared toward design. Examining how contractors are dealing with this could provide further insight into the decision process when submitting a bid. Examining the appropriate risk allocation in the contract documents and the effects that these have could go a long way in eliminating some of the perceived risk that results in increased costs. Another potential area of study would be the bidding environment that exists for this type of project. This study showed that the bidding environme nt can have a very significant effect on the bid prices that are offered. A closer look at factors that are producing an unnecessarily hostile bid environment should be looked at, as this could increase costs sharply. An environment that is too open coul d also increase costs due to an overabundance of inexperienced bidders. A closer study of the makeup of the risks perceived by contractors could also be performed. This extra cost is generally considered by the contractor, but many of them

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93 probably dont even realize it. If a contractor is adjusting a bid up 8% to account for the additional risks involved, where is this number coming from, and is the contractor aware of what is going into this cost? A good question to a pool of contractors could be to ask them to list the risks that they feel they are subject to on a certified green project and quantify the level of each. Different answers would probably be telling of the bid environment and the contractors risk aversion principles.

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94 APPENDIX SUPPORTING DATA Table A 1. Supporting data for sensitivity analysis. Certified Number of Bidders % Increase $ Increase in LEED Cost n % Increase $ Increase in LEED Cost 1.0 1.01% $83,558.90 1 1.02% $ 84,155.28 0.5 1.01% $83,260.72 5 1.00% $ 83,095.06 0.0 1.00% $82,962.53 10 1.00% $ 82,962.53 0.5 1.00% $82,664.34 50 1.00% $ 82,856.51 1.0 0.99% $82,366.15 100 1.00% $ 82,843.25 Silver Number of Bidders % Increase $ Increase in LEED Cost n % Increase $ Increase in LEED Cost 1.0 4.57% $ 378,563.58 1 4.71% $ 390,109.42 0.5 4.50% $ 372,790.66 5 4.46% $ 369,583.48 0.0 4.43% $ 367,017.74 10 4.43% $ 367,017.74 0.5 4.36% $ 361,244.82 50 4.41% $ 364,965.15 1.0 4.29% $ 355,471.90 100 4.40% $ 364,708.57 Gold Number of Bidders % Increase $ Increase in LEED Cost n % Increase $ Increase in LEED Cost 1.0 8.68% $ 718,746.39 1 9.15% $ 757,874.62 0.5 8.44% $ 699,182.28 5 8.31% $ 688,313.32 0.0 8.20% $ 679,618.16 10 8.20% $ 679,618.16 0.5 7.97% $ 660,054.05 50 8.12% $ 672,662.03 1.0 7.73% $ 640,489.93 100 8.11% $ 671,792.52 Platinum Number of Bidders d % Increase $ Increase in LEED Cost n % Increase $ Increase in LEED Cost 1.0 13.27% $ 1,054,078.68 1 14.30% $ 1,184,800.32 0.5 12.75% $ 1,036,286.79 5 12.46% $ 1,032,128.06 0.0 12.23% $ 1,018,494.91 10 12.23% $ 1,013,044.03 0.5 11.71% $ 970,104.96 50 12.05% $ 997,776.81 1.0 11.19% $ 927,165.89 100 12.02% $ 995,868.40

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95 Table A 1 continued. Certified Bid Climate Factor Experience Factor % Increase $ Increase in LEED Cost % Increase $ Increase in LEED Cost 0.50 1.00% $83,095.06 0.90 0.90% $74,666.28 0.75 1.00% $83,006.70 0.95 0.95% $78,814.40 1.00 1.00% $82,962.53 1.00 1.00% $82,962.53 1.25 1.00% $82,936.02 1.15 1.15% $95,406.91 1.50 1.00% $82,918.35 1.30 1.30% $107,851.29 Silver Bid Climate Factor Experience Factor % Increase $ Increase in LEED Cost % Increase $ Increase in LEED Cost 0.50 4.46% $ 369,583.48 0.90 3.99% $ 330,315.97 0.75 4.44% $ 367,872.99 0.95 4.21% $ 348,666.85 1.00 4.43% $ 367,017.74 1.00 4.43% $ 367,017.74 1.25 4.42% $ 366,504.59 1.15 5.10% $ 422,070.40 1.50 4.42% $ 366,162.49 1.30 5.76% $ 477,123.06 Gold Bid Climate Factor Experience Factor % Increase $ Increase in LEED Cost % Increase $ Increase in LEED Cost 0.50 8.31% $ 688,313.32 0.90 7.38% $ 611,656.35 0.75 8.24% $ 682,516.55 0.95 7.79% $ 645,637.25 1.00 8.20% $ 679,618.16 1.00 8.20% $ 679,618.16 1.25 8.18% $ 677,879.13 1.15 9.44% $ 781,560.89 1.50 8.17% $ 676,719.77 1.30 10.67% $ 883,503.61 Platinum Bid Climate Factor Experience Factor % Increase $ Increase in LEED Cost % Increase $ Increase in LEED Cost 0.50 12.46% $ 1,032,128.06 0.90 11.01% $ 911,739.63 0.75 12.31% $ 1,019,405.38 0.95 11.62% $ 962,391.83 1.00 12.23% $ 1,013,044.03 1.00 12.23% $ 1,013,044.03 1.25 12.18% $ 1,009,227.23 1.15 14.06% $ 1,165,000.64 1.50 12.15% $ 1,006,682.69 1.30 15.90% $ 1,316,957.24

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96 Table A 1 continued. Certified Proximity to Services % Increase $ Increase in LEED Cost 0.50 1.00% $ 82,962.53 0.75 1.00% $ 82,962.53 1.00 1.00% $ 82,962.53 1.25 1.00% $ 82,962.53 1.50 1.00% $ 82,962.53 Silver Proximity to Services % Increase $ Increase in LEED Cost 0.50 4.44% $ 367,622.73 0.75 4.44% $ 367,925.23 1.00 4.45% $ 368,227.72 1.25 4.45% $ 368,530.22 1.50 4.45% $ 368,832.71 Gold Proximity to Services % Increase $ Increase in LEED Cost 0.50 8.21% $ 680,315.92 0.75 8.22% $ 680,664.80 1.00 8.22% $ 681,013.68 1.25 8.23% $ 681,362.56 1.50 8.23% $ 681,711.44 Platinum Proximity to Services % Increase $ Increase in LEED Cost 0.50 12.25% $ 1,014,614.49 0.75 12.26% $ 1,015,399.72 1.00 12.27% $ 1,016,184.95 1.25 12.28% $ 1,016,970.17 1.50 12.29% $ 1,017,755.40

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97 LIST OF REFERENCES Alquier, A.M., and Tignol, M.H. (1999). Project management technique to estimate and man age risk of innovative projects Universite Toulouse 1, Anatole, France. Anderson, M K. Bidgood, J.K ., and Heady, E J. (2010). Hidden legal risks of green building. The Florida Bar Journal 84(3), 35 41. Capen, E.C., Clapp, R.V., and Campbell, W.M. (1971). Competitive bidding in highrisk situations. Journal of Petroleum Technology 23(6), 641653. Dyer, D., and Kagel, J.H. (1996). Bidding in common value auctions: How the commercial construction indust ry corrects for the winners curse. Management Science 42(10), 14631475. Es, P., and White, L. (2003). Precautionary bidding in a uctions Centre for Economic Policy Research, London. EVStudio (2010). Cost per square foot of college building types by region. . (May 30, 2010). Fu, W.K., Drew, D.S., and Lo, H.P. (2002). The effect of experience on contractors competitiveness in recurrent bidding. Construction M anagement and Economics 20(7), 655656. Kibert, C.J. (2008). Sustainable construction: Green building design and delivery 2nd Ed., Wiley, Hoboken, N.J. March, J.G., and Olsen, J.P. (1976). Ambiguity and choice in organizations Universitetsforlaget Berg en, Norway. Mathiessen, L.F., and Morris, P. (2004). Costing green: A comprehensive cost da tabase and budgeting methodology Davis Langdon, London. Morgan, M., Granger, M.H., and Small, M. (1990). Uncertainty: A guide to dealing with uncertainty in quantit ative risk and policy analysis Cambridge University Press, New York. Morris, P., and Mathiessen, L.F. (2007). Cost of green revisited: Reexamining the feasibility and cost impact of sustainable design in the light of increased market adoption, Davis Langdon, London. Northbridge Environmental Consultants. (2003). Analyzing the cost of obtaining LEED certification Washington, D.C. Steven Winter Associates Inc. (2004). GSA LEED cost study: Final report Norwalk, Conn.

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98 Tang, F., Zong, W., and Song, S. (2006). Tenders with different risk preferences in construction industry Department of Economics, University of Nevada, Reno, Nev. Thaler, R.H. (1998). Anomalies: The winners curse. Journal of Economic Perspectives 2(1), 191202. USGBC (2010). USGBC: I ntro What LEED is. < http://www.usgbc.org/DisplayPage.aspx?CMSPageID=1988> (May 29, 2010).

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99 BIOGRAPHICAL SKETCH The author was born in Connecticut and attended the University of Connecticut, receiving a Bachelor of Science degree in Finance from the School of Business Administration. After working for several years for a contractor in Hartford, Connecticut the author relocated to Florida to attend the University of Florida in pursuit of a degree of Masters of Scienc e in Building Construction. The author plans to return to Connecticut to continue his career.