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Key Factors Affecting Labor Productivity in the Construction Industry

Permanent Link: http://ufdc.ufl.edu/UFE0021576/00001

Material Information

Title: Key Factors Affecting Labor Productivity in the Construction Industry
Physical Description: 1 online resource (54 p.)
Language: english
Creator: Kuykendall, Casey Jo D
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: 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: Labor productivity is one of the least studied areas within the construction industry. Productivity improvements achieve high cost savings with minimal investment. Due to the fact that profit margins are small on construction projects, cost savings associated with productivity are crucial to becoming a successful contractor. The chief setback to improving labor productivity is measuring labor productivity. The main objective of this study is to assign a weight of importance to each of the top twelve factors affecting productivity. Experts at the University of Florida Rinker School of Construction compiled a list of the top twelve factors affecting productivity. A survey consisting of the twelve factors and a brief explanation of each was mailed to contractors listed on the ENR Top 400 (2006) in which they were asked to apply a weight to each of the twelve factors, totaling 100%. Results of this survey were then analyzed using the Delphi Method. These weights will be used in a future study to create a tool to help contractor?s grade productivity on their projects in the preplanning stage and plan improvements in the most beneficial areas. This productivity tool will be created by breaking each factor down into a list of activities. The project manager will assign a value to each activity representing how well their current project is achieving this activity. The total for each factor is then multiplied by its respective weight (generated in this study). The outcome of the tool will give a breakdown of areas for improvement along with values that allow for project managers to focus on the most beneficial areas.
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 Casey Jo D Kuykendall.
Thesis: Thesis (M.S.B.C.)--University of Florida, 2007.
Local: Adviser: Issa, R. Raymond.
Local: Co-adviser: Flood, Ian.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021576:00001

Permanent Link: http://ufdc.ufl.edu/UFE0021576/00001

Material Information

Title: Key Factors Affecting Labor Productivity in the Construction Industry
Physical Description: 1 online resource (54 p.)
Language: english
Creator: Kuykendall, Casey Jo D
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: 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: Labor productivity is one of the least studied areas within the construction industry. Productivity improvements achieve high cost savings with minimal investment. Due to the fact that profit margins are small on construction projects, cost savings associated with productivity are crucial to becoming a successful contractor. The chief setback to improving labor productivity is measuring labor productivity. The main objective of this study is to assign a weight of importance to each of the top twelve factors affecting productivity. Experts at the University of Florida Rinker School of Construction compiled a list of the top twelve factors affecting productivity. A survey consisting of the twelve factors and a brief explanation of each was mailed to contractors listed on the ENR Top 400 (2006) in which they were asked to apply a weight to each of the twelve factors, totaling 100%. Results of this survey were then analyzed using the Delphi Method. These weights will be used in a future study to create a tool to help contractor?s grade productivity on their projects in the preplanning stage and plan improvements in the most beneficial areas. This productivity tool will be created by breaking each factor down into a list of activities. The project manager will assign a value to each activity representing how well their current project is achieving this activity. The total for each factor is then multiplied by its respective weight (generated in this study). The outcome of the tool will give a breakdown of areas for improvement along with values that allow for project managers to focus on the most beneficial areas.
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 Casey Jo D Kuykendall.
Thesis: Thesis (M.S.B.C.)--University of Florida, 2007.
Local: Adviser: Issa, R. Raymond.
Local: Co-adviser: Flood, Ian.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021576:00001


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KEY FACTORS AFFECTING LABOR PRODUCTIVITY IN THE CONSTRUCTION
INDUSTRY




















By

CASEY JO KUYKENDALL


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 INT BUILDING CONSTRUCTION



UNIVERSITY OF FLORIDA

2007

































O 2007 Casey Jo Kuykendall


































To my family and friends









ACKNOWLEDGMENTS

I would like to thank my family and friends especially my parents, Billy and Selina

Kuykendall; and my fiance, Ryan Kennedy for their continued support. I also thank my

professors and peers for their support. I would not be where I am today if I stood alone in my

day-to-day endeavors. For that, I am grateful.












TABLE OF CONTENTS


page

ACKNOWLEDGMENTS .............. ...............4.....


LIST OF TABLES ............_...... ...............7...


LIST OF FIGURES .............. ...............8.....


AB S TRAC T ............._. .......... ..............._ 10...


1 INTRODUCTION ................. ...............12.......... ......


Main Goals of This Study ................. ...............12........... ...
Study Objectives............... ...............1

2 LITERATURE REVIEW ................. ...............14................


Background .................. ...............14.......... ......
Does a Problem Exist? ................ ...............15................
Defining Productivity ........... ... .. ... ................. ...............1
How Does Productivity Relate to the Construction Industry? ................ .......................19
Top 12 Factors Affecting Construction Labor Productivity ................. ................. ......20
Management of Construction Tools .............. ...............20....
Managing Construction Equipment............... ...............2
Access Issues ............. ...... ._ ...............21....

M management Skills .............. ...............21....
Safety Issues .............. ...............22....
Quality Control ............ _...... ._ ...............23....
Scheduling ............... ...... ...............24....
Employee Training/Skills............... ............2
Employee Age .............. ...............25....
Temperature/ Humidity .............. ...............26....
Employee Motivation ........._.._.. ........_. ...............27.....
Degree of Bilateral Communication............... .............2
Sum m ary ................. ...............28........ ......


3 METHODOLOGY .............. ...............29....


4 RE SULT S .............. ...............32....


Feedback ................. ...............32........ ......

Responses .............. ...............32....
Delphi M ethod ................. ...............33........ ......
Mean Weights ....__. ................. ......._.._..........3
Further Statistical Analysis............... ...............34
Summary ...._.. ................. ........_.._.........42












5 CONCLUSIONS AND RECO1V1VENDATIONS .............. ...............44....


Recap of Obj ectives ................. ...............44................
Recommendations..................... .............4
What Should be Done Differently? ............. ...............45.....
Future W orks ................. ...............45.................


APPENDIX


A THE SURVEY ................. ...............46........... ....


B THE QUESTIONAIRRE............... .............4


C EXA1VPLE WORKSHEET APPLICATION OF WEIGHTS .............. ....................4


D EXA1VPLE EVALUATION SHEET ................. ......... ...............50. ...


E IRB APPROVAL................ ...............5


LIST OF REFERENCES ............ ..... ._ ...............52...


BIOGRAPHICAL SKETCH .............. ...............54....










LIST OF TABLES


Table page

2-1 A multi-industry comparison of injury cases per 100 full-time employees during
1996, 1997 and 1999 adapted from a book by Chris Hendrickson. ............. ................23

4-1 Mean, median, mode, standard deviation, and variance of the weighted percentages
for the top 12 factors affecting labor productivity ................. ...............35........... .










LIST OF FIGURES


Figure page

2-1 Labor productivity index for US construction industry and all non-farm industries
from 1964 through 2003. ............. ...............14.....

2-2 Time utilization of worker productivity in the United States. ................ .........___...... 15

2-3 Problems contributing to unproductive time adapted from a study conducted in the
United Kingdom. ........... ........... ...............17....

2-4 Basic ingredients to successful proj ect management adapted from a book by Chris
Hendrickson. ............. ...............22.....

4-1 Current j ob positions held by survey respondents. ....._____ .... ...___ ............__...32

4-2 Gender of survey participants represented as a percentage .............. .....................3

4-3 Average years of industry experience compared to average years in current position
respondents was 21.1 years in the industry and 18.1 years in their current position.........33

4-4 Mean weighted percentages for top 12 factors affecting construction labor
productivity in ascending order correlation between the data responses...........................35

4-5 Histogram for results from tool management factor comparing responses (as a range
of percentages) to the number of responses (falling within each range). ........._.._.............36

4-6 Histogram for results from equipment management factor comparing responses (as a
range of percentages) to the number of responses (falling within each range). ........._......36

4-7 Histogram for results from access issues factor comparing responses (as a range
ofpercentages) to the number of responses (falling within each range). .................. .........37

4-8 Histogram for results management skills factor comparing responses (as a range of
percentages) to the number of responses (falling within each range) ............... .... .........._.37

4-9 Histogram for results from safety management factor comparing responses (as a
range of percentages) to the number of responses (falling within each range). ................38

4-10 Histogram for results from quality control factor comparing responses (as a range of
percentages) to the number of responses (falling within each range) ........._...... ..............38

4-11 Histogram for results from schedule management factor comparing responses (as a
range of percentages) to the number of responses (falling within each range). ................39

4-12 Histogram for results from employee training/skills factor comparing responses (as a
range of percentages) to the number of responses (falling within each range). ................39











4-13 Histogram for results from employee age factor comparing responses (as a range of
percentages) to the number of responses (falling within each range). .............. ..............40

4-14 Histogram for results from temperature/ humidity factor comparing responses (as a
range of percentages) to the number of responses (falling within each range). ...............40

4-15 Histogram for results from employee motivation factor comparing responses (as a
range of percentages) to the number of responses (falling within each range). ........._.....41

4-16 Histogram for results from the degree of bilateral communication factor comparing
responses (as a range of percentages) to the number of responses (falling within each
range). ............. ...............42.....

A-1 The survey............... ...............47.

B-1 The questionnaire ....._.. ................. ........_._ .........4

C-1 Example worksheet for the application of weights ....._.. ................. ................ ..49

D-1 Final Evaluation Sheet ....._.__................. ...........__........5

E-1 IRB approval form. ............. ...............51.....









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

KEY FACTORS AFFECTING LABOR PRODUCTIVITY INT THE CONSTRUCTION
INDUSTRY
By

Casey Jo Kuykendall

December 2007

Chair: R. Raymond Issa
Cochair: lan Flood
Major: Building Construction

Labor productivity is one of the least studied areas within the construction industry.

Productivity improvements achieve high cost savings with minimal investment. Due to the fact

that profit margins are small on construction proj ects, cost savings associated with productivity

are crucial to becoming a successful contractor. The chief setback to improving labor

productivity is measuring labor productivity. The main obj ective of this study is to assign a

weight of importance to each of the top twelve factors affecting productivity. Experts at the

University of Florida Rinker School of Construction compiled a list of the top twelve factors

affecting productivity. A survey consisting of the twelve factors and a brief explanation of each

was mailed to contractors listed on the ENR Top 400 (2006) in which they were asked to apply a

weight to each of the twelve factors, totaling 100%. Results of this survey were then analyzed

using the Delphi Method. These weights will be used in a future study to create a tool to help

contractor' s grade productivity on their proj ects in the preplanning stage and plan improvements

in the most beneficial areas. This productivity tool will be created by breaking each factor down

into a list of activities. The proj ect manager will assign a value to each activity representing how

well their current proj ect is achieving this activity. The total for each factor is then multiplied by

its respective weight (generated in this study). The outcome of the tool will give a breakdown of










areas for improvement along with values that allow for proj ect managers to focus on the most

beneficial areas.









CHAPTER 1
INTTRODUCTION

Construction is one of the nation's largest industries. Construction accounted for 7 % of

the nation's GDP in 1997 (Tucker 1999). In 2004, the construction industry provided 7 million

wage and salary jobs including 1.9 million self-employed and unpaid family workers (Bureau of

Labor Statistics 2006). In 1999, the construction industry provided 6.4 million jobs and the total

value of new construction for the same year was $764 billion (Langsford 2006).

A successful construction proj ect is one that is completed on time, within budget, meets

specified standards of quality, and strictly conforms to safety policies and precautions. All of

this is feasible only if the premeditated levels of productivity can be achieved. All the same,

productivity, or lack there of, is one of the construction industry's most prevalent problems. Due

to the nature of construction proj ects, its importance to society and the existing economic

resources, more emphasis should be given to improving productivity.

Main Goals of This Study

In the end, this study will provide a weight of importance for each of the most common

factors affecting productivity. These weights will then be used by a group of experts to compose

a questionnaire that will provide construction managers and decision makers with a productivity

tool that will enhance proj ect productivity. Unlike other currently existing productivity tools,

this tool can be used in the planning stage and serve as a checklist to guarantee a more

productive completion of proj ects. Keep in mind this is not intended to serve as a remedy for all

problems that occur on construction proj ects, but as one of the necessary tools for success. The

maj or intentions of this study are as follows:

*To assemble a list of the most notable factors affecting productivity within the
construction industry today.










To develop a weight for each individual factor based on the Delphi Method, with a total
weight of 100 %.

To create an example tool in which the weights derived will be used to help proj ect
managers and top decision makers assess the current productivity issues on their proj ects
from the pre-planning stage through the proj ect' s completion.

Study Objectives

The initial objective of this study is to identify the main factors associated with lost

productivity on construction proj ects. In order to be aware of the problems associated with each

factor, the problems must be completely understood. The top factors were identified by experts

within the construction and human factors Hield of study from the University of Florida. Each of

these factors will be thoroughly defined within the literature review section of this study. The

next obj ective is to acquire a weight of importance for each of these factors. In order to ensure

that the weights are not discussed between respondents, a survey is distributed to 200 contractors

listed on the ENR top 400 (2006), in which they are asked to assign a weight to each of the

factors. Once these weights are established, a future study will further break down each factor

into its components. These components will enable the project managers to give themselves a

score from 1 to 10 for each of the components within each factor. The Einal score can then be

evaluated to serve as a checklist to ensure increased productivity all the way up to the completion

of the project. The main objectives of this study are as follows:

1. To expand upon the main factors affecting labor productivity

a) Definition of the factor, and
b) common problems associated with each factor.

2. To allocate a weight to each factor based on its importance

c) Each weight will be derived by surveys distributed to experts, and
d) the Delphi Method will then be used to compile the survey
responses.
3. To compose a sample productivity checklist to serve as an example of how
the weights will be used in the future.









CHAPTER 2
LITERATURE REVIEW

Background

Construction requires extensive manual labor. Human performance and

productivity are reliant on one another. Therefore, the most commonly used measure of

productivity is the constant contract dollars of new construction work per work hour

(Hendrickson 1998). A study by Teicholtz (2004) revealed that over 40 years (1964-2003) the

construction industry lags compared to all other non-farm industries in developing and applying

labor saving techniques and substituting equipment for labor. Figure 2-1 depicts construction

labor productivity changes as opposed to all non-farm industries from 1964-2003. A study by

250.00%rc













1SO, 84~ 196 197 197 19Rfl 19P, 19A1 1964 7flf~lfel)








Figure 2-1 Labor productivity index for US construction industry and all non-farm industries
from 1964 through 2003 (U. S. Bureau of Labor Statistics 2004).









Hendrickson (1998) addressed the time utilization of the average construction worker. Only 40

% of a workers time is considered to be productive, with 55 % unproductive time, and 5 %

personal time. Figure 2-2 shows a breakdown of the average workers time utilization.

Does a Problem Exist?

From 1966 to 2003 Haskell (2004) conducted research analyzing and reporting long-term

trends in construction labor productivity within the US building construction industry. This

research uses two distinct methodologies. The first approach is aggregate productivity, which is

measured using constant dollars as the input (for both labor and non-labor expenditures) and

square feet of building area adjusted for quality changes as the measure of aggregate output. The


Time Ltilization

Sr-odluctive Tirmn

16% m Lwkpoductive tirne-
Achiliistrative
o ULwkpoductive tirne-
Inefficiert V\brk IMe~tods
o ULwkpoductive tirne-Lao
~OD1~LMJ risdcotions
20%/
mPersonal tine



Figure 2-2 Time utilization of worker productivity in the United States.

second approach is task productivity, which is calculated using labor man-hours as input and

production units as output (Haskell 2004).

The first approach, the output based approach shows a comparison of the unit costs of

buildings constructed in 1966 in dollars per square foot, compared to buildings built in 2003.

Using a factor of 5.68, the 2003 costs are then deflated back to 1966 costs. The outcome of this

data shows a 12.34 % decrease in costs per square foot. The outcome is further adjusted for









qualitative changes in order to be able to make a qualitative comparison. Finally after applying a

formula involving the qualitative productivity increase and the quantitative productivity increase,

total productivity is found to have increased by 33.2 %. The second approach, the input based

approach studies two effects. The first one is the effect of observable increases in labor

productivity, offset by increases in capital costs (Haskell 2004).

The second effect is the documented decrease in materials costs (Haskell, 2004). The

result of this research, 32.4 % falls very close to the result of the output based result of 33.2 %.

The conclusions of this research is that the similarity of the outcomes based on two different

approaches, input and output, prove that productivity within the construction industry have in

fact increased over the last 37 years by about 33 % (Haskell 2004).

Another recent study by Teicholtz (2004), mentioned earlier measured productivity

within the construction industry over a 40-year period ranging from 1964 to 2003. This study

measured productivity as constant contract dollars of new construction work per work hour

(Teicholtz 2004). The results are the opposite of that cited by Haskell. Teicholtz finds that

productivity has been decreasing over the last forty years at a rate of about 0.59 % per year.

Teicholtz summarizes this stating:

The construction industry suffers from structural productivity problems that will not be
rapidly cured. The slow erosion of labor productivity, the aging of the construction work
force, the slow rate of change in field practice and the current lack of student preference
for civil engineering education are serious indications that new approaches are needed to
revitalize and bring fresh ideas into this industry (Teicholtz 2004).

By comparing these two studies, it is apparent that measuring productivity and deriving a

pattern is dependent on the method of data collection and measurement. Different researchers

will inevitably come up with different outcomes until a standard measure of productivity is

derived or if a preplanning tool is created to guarantee significant increases in productivity early

on in the proj ect.










A study very similar to our study was conducted in Canada known as the "Productivity

Improvements on Alberta Maj or Construction Proj ects." Within this, a study conducted in the

United Kingdom was cited. The workers were asked to rank a general list of common problems

on their construction site and in addition they were asked to estimate the respective lost time per

problem area (McTague 2002). The four tables included in Figure 2-3 illustrate the problems

and their respective time loss.

Order of Factors Influencing Productivity

Factor Overall Order
1 Lack of Materials
2 Crew Interference
3 Repeat Work
4 Supervision
5 Lack of Equipment, Tools
6 Absenteeism

Estimated Time loss per Problem in a 40-Hour Week
Factor Estimated Time Loss
3 Lack of Materials
2 Crew Interference
2.5 Repeat Work
2 Supervision
2 Lack of Equipment, Tools
0.5 Absenteeism

Order of Causes of Lack of Mlaterials
Factor Overall Order
1 Lack of Planning
2 Transport within Site
3 Improper Materials
4 Interference
5 Unnecessary Paperwork

Order of Causes of Rework
Factor Estimated Time Loss
1 Change of Instructions
2 Unclear Instructions
3 Complex Specification
4 Poor Workmanship


Figure 2-3 Problems contributing to unproductive time adapted from a study conducted in the
United Kingdom (McTague 2002).









The construction industry is continuously becoming more complicated, with clients with higher

expectations and requirements. More commonly, clients are expecting more complex projects to

be completed in a shorter period of time. Moreover, the increased competition is causing

contractors to complete day-to-day business with very low profit margins, while taking on more

risks (McTague 2002).

In order to survive in such an industry, decision makers and proj ect managers need to be

able to ensure that their proj ects are being completed as productively as possible. In order for

this to take place a new tool needs to be developed to ensure maximum productivity from the

beginning to the end of each proj ect. The development of such a tool is the main focus of this

study .

Defining Productivity

Many definitions of the word "productivity" exist. For the basis of this study the

Merriam-Webster definition will be used. Merriam-Webster defines productivity as the quality

or state of being productive. Labor productivity is typically measured as output per worker or

output per labor-hour. Although there are endless definitions for productivity, they all refer to

productivity as a comparison of input versus output. Productivity = Output/ Input. Increased

productivity occurs when either

1. Output is constant, while input is reduced, and/or
2. Input is constant, while either the quantity or quality of output has been increased or
enhanced.

Productivity serves as a source of competitive advantage. Increasing productivity will

increase output or the quality of output and if at a faster rate then competition, benefits will be

achieved through the value-added through the products (McTague 2002).









How Does Productivity Relate to the Construction Industry?

Increased productivity in the construction industry can be viewed from two perspectives,

the consumer and the contractor. From the consumer's perspective, increased productivity

lowers costs, shortens construction schedules, offers more value for the money, and achieves

better returns on investments. From the contractor's perspective, increased productivity leads to

a more satisfied customer, while also providing a competitive advantage, and in return leading to

faster turnover and increased profits (Horner 2001).

The definition for productivity with regards to construction is the measurement of the

output of construction goods and services per unit of labor (McTague 2002). McTague (2002) of

"Productivity Improvements on Alberta Maj or Construction Proj ects" compiled the following list

of commonly used definitions to measure productivity in the construction industry:

Labor Productivity = Output/ Labor Cost or

Labor Productivity = Output/Work Hours

In case the input is a combination of various factors, productivity is termed as

Total Factor Productivity and is measured as

Total Factor Productivity = Total Output/ Labor + Material + Equipment + Energy +
Capital

Various agencies may modify the definition of productivity as per their requirements by
deleting some factors and or adding other factors.

For example, the American Federal Highway Administration may define productivity as:

Productivity = Output/ Design + Inspection + Construction + Right of Way

Or

Productivity = Lane Mile/ Dollars (McTague 2002).










Top 12 Factors Affecting Construction Labor Productivity

Management of Construction Tools

Materials and tool management are a large part of any construction proj ect. In more

recent years, construction firms have allocated more focus on retaining small tools, which in the

past were perceived as "disposable". Numerous technological advances have been made that

enable tool tracking to be more efficient. Barcodes and scanners are one of the most common

techniques used to track tools today. The problem with implementing this system is the

complexity of the process. In the past the tools were just replaced, one simple step. The barcode

system requires labeling, tracking, cataloguing, filing, and coordinating a multitude of tools. The

process is much more demanding. In an article from the Engineering News Record, it is cited

that Kafka, a former electrical contractor, achieved an average savings of $0.40 per employee per

hour by implementing the barcode system. This compares to an average loss of $0.80 per hour

per employee from lack and loss of tools before the barcode system was in place. Other tool

tracking systems being researched include radio-frequency identification and forensic chemical

marking (Hampton 2003).

Managing Construction Equipment

The Construction Industry Institute states that material and equipment currently comprise

50-60 % of construction proj ect costs (Materials Management Task Force 2007). In addition,

lack of proper materials and equipment is the number one cause of construction delays. Over the

last 20 years significant gains have been made in the construction industry through the

implementation of computers. Along with the continued emergence of computers, equipment

and materials management will assume a more important role in the industry. Good equipment

management begins at the time the equipment is purchased. Purchasing the proper equipment

that matches the need of the j ob, while achieving the lowest costs is necessary to attain suitable










equipment management. Proper record keeping provides information for planning maintenance

and replacement activities, ensuring that they occur at the proper time. Managing construction

equipment includes preventative maintenance, planning maintenance, and replacement activities

(O'Brien and Zilly 2007).

Access Issues

Very little information is available on access issues on construction sites. Reiterating

what was said in the access issues portion of the survey, site drawings should be available

indicating where dense areas of labor are working and indicating their route to and from the site.

Alternate plans to cut roads should only be made when other acceptable routes are ready. A

common problem on construction sites is poor or disrupted access caused by holes and

barricades and time spent finding alternate routes.

Management Skills

Construction management is schedule and plan work and materials to make certain that

no one is waiting for materials, labor, or the completion of another task. Proper management of

construction projects requires knowledge of modern management techniques. Figure 2-4 shows

the main ingredients of successful proj ect management. A familiarity with general management

knowledge and special knowledge domains are indispensable, while supporting disciplines such

as computer based information systems is a plus (Hendrickson 1998). A study at the Center for

Construction Industry Studies at the University of Texas at Austin has revealed that poor

management was responsible for over half of the time wasted on a j obsite. A construction

proj ect is unable to achieve profitability and success




























Figure 2-4 Basic ingredients to successful project management adapted from a book by Chris
Hendrickson (Hendrickson, 1998).

without the presence of good management (Tucker 1999). Good management skills include

adopting a performance based management viewpoint. This involves setting priorities for

improvements, provide cost efficient and easy to use methods, promote a supportive labor-

management relationship, and cut costs while increasing profits (Alfred 1988).

Safety Issues

Many benefits as well as losses exist through construction safety management. The

construction industry is the leader in injuries and lost workdays due to injuries. Thus these

injuries are very costly. Table 2-1 shows a comparison of the number of injury cases between

the construction industry and other prevalent industries. In 1996, 1997 and 1998 the construction

industry has the highest occurrence of injury cases when compared to agriculture, mining,

manufacturing, transportation, wholesale and retail, Einance, and services. The more visible

benefits of construction safety include cheaper workers' compensation coverage that' s comes

with a lower experience modification rating, also increased quality, and owner satisfaction. The

Business Roundtable Booklet even goes as far as stating that a contractor' s safety performance is


Ingredients to Successful Project ILhnagena~nt










an indication of the contractor' s commitment to quality; basically stating that the two go hand in

hand. The most prevalent hidden costs include worker replacement time, crew efficiency loss,

Table 2-1 a multi-industry comparison of injury cases per 100 full-time employees during 1996,
1997 and 1999 adapted from a book by Chris Hendrickson (Hendrickson 1998).

Industry 1996 1997 1998
Agriculture, foretr,fishin 8.7 8.4 7.3
Mining 5.4 5.9 4.4
Construction 9.9 9.5 8.6
Manufacturing 10.6 10.3 9.2
Transportation/ public utilities 8.7 8.2 7.3
Wholesale and retail trade 6.8 6.7 6.1
Finance, insurance, real
estate 2.4 2.2 1.8
Services 6 5.6 4.9

costs incurred due to delays, costs due to rescheduled work, and safety personnel costs (Levitt

and Samelson 2007). A study done in the early 1980's by the Business Roundtable called the

"Construction Industry Cost Effectiveness Project" reported that 6.5 % of total construction costs

could be attributed to accidents. Recommendations to lower this percentage include placing

safety requirements in contracts, using safety records as part of the subcontractor prequalification

process, and finally requiring management to take a more active role in onsite safety

management (Schneider 2007).

Quality Control

Alfred (1988) states that there are two measures for construction quality, they are

accuracy and workmanship. Accuracy is defined as the measurement of "how closely the j ob

conforms to plans, specifications, code requirements, and accepted industry standards for

workmanship" (Alfred 1988). Workmanship is defined as the measurement of"significant

differences in the worth of the finished j ob created by master craftsman-ship skills (assuming, of

course, that all of the work meets standards of accuracy" (Alfred 1988).









Some benefits associated with quality control are avoided rework, generation of new

work methods, and circumventing long term problems. Following is a list of key quality control

checkpoints and quality problem areas that should be addressed within a jobsite quality

inspection checklist. The list includes:

* Design requirements
* Completed preceding work segments
* Work done by qualified employees
* Accepted materials used
* Appropriate amount of materials
* Scope of work requirements achieved
* Installation specifications met
* Entire work phase complete
* All quality problems have been fixed

Quality control pays for itself by increasing productivity while reducing costs (Hendrickson

1998).

Scheduling

The purpose of scheduling is to organize and allocate the resources of, equipment and

labor with the construction proj ect' s tasks over a set period of time. Benefits of good scheduling

include, avoiding proj ect bottlenecks, allowing for suitable procurement or necessary materials,

and overall ensuring that the project is completed as quickly as possible. Poor scheduling can

result in unnecessary waste of time caused by delays as laborers wait for materials of equipment

to become available or proceeding tasks to be completed (Hendrickson 1998). In order to

successfully schedule a project, there must be some methodology to the process. Many

scheduling methods exist. For the basis of this study it will be assumed that computer based

scheduling is applied. One of the most common scheduling techniques is the Critical Path

Method (CPM) (Hendrickson 1998). CPM is a deterministic technique that uses preset time

estimates for each activity. CPM is very easy to understand; yet it lacks consideration for









variations that can have a large impact on the final completion time for more complex proj ects.

Another scheduling method that allows for randomness in completion times for each activity is

known as Program Evaluation and Review Technique (PERT). PERT involves six basic steps:

* Identify activities
* Place all activities in the proper order
* Construct a network diagram
* Make time estimates for each activity
* Determine critical path
* Continually update chart as proj ect progresses

Proper applications of scheduling techniques will help avoid unnecessary delays and in turn

reduce cost overruns.

Employee Training/Skills

Employee training benefits are much underestimated. Jordan (2006) noted that according

to the US Department of Labor, apprenticeship training provides a $54 return for every dollar

invested. Despite this large return on investment contractors are hesitant to pull their workers off

the job to allocate time for proper training. In addition, contractors are averse to spending money

on training. In the same article he states that contractors spend only 1.83 % of their payroll on

training, compared to the 2 % spent by the industrial sector overall. Jordan cites a specific study

completed by the University of Florida' s Rinker School of Building Construction, in which one

company's training efforts resulted in a 42 % increase in productivity (Cox, Issa and Collins

1998). Overall, investing in employee training programs will increase productivity and reduce

costs caused by rework and lost time.

Employee Age

Many studies suggest that the "working class" is aging, which is leading to a shortage of

young skilled workers. One article in the Sacramento Business Journal states that there has been

a decline from 37.5 % to 28.5 % of skilled construction workers between the ages of 25 to 34









between 1988 and 1997. The average age determined by The Associated General Contractors of

America of the construction worker in 2004 was 47 (LeClaire 2004). Zeiss (2007) predicted that

by the year 2010 the number of workers between the ages of 3 5 to 44 will decrease by 19 %,

while the number of workers between the ages of 45 to 54 will increase by 21 %. The shortage

is caused by the retirement of the baby boom generation and popularity within the younger

working class to opt for office oriented j obs. Current solutions to this growing problem include a

strengthening and modernization of the nation's vocational school system. One particular

proposition by the Bush Administration is a program known as "Skills to Build America' s

Future", a plan aimed to attract young people into careers in trade fields. The industry is also

filling the void by reaching out to minority groups to fill the positions (LeClaire 2004).

Temperature/ Humidity

Weather is to some extent unpredictable. When not scheduled adequately, weather can

cause delays due to forced changes in the schedule as well as damages causing rework.

Productivity decreases in poor weather conditions for many reasons. Some construction

processes are affected poorly by suboptimal weather conditions. For example, mortar and

concrete become less efficient. Labor is also affected poorly by unfavorable weather conditions.

For instance, when weather apparel such as raincoats or heavy jackets is necessary, labor is

hindered (Mincks and Johnston 2003). Hot weather, in particular, has both a physiological and

psychological effect on workers. Psychologically workers tend to become restless and irritable.

Physiologically they can acquire heat cramps, heat stroke, heat exhaustion, etc. The four factors

in a hot environment that cause the increased stress include:

* Humidity
* Air Movement
* Air Temperature
* Heat Radiation (Schwarzkopf 1995).










The most effective solution to curb the effect of inclement weather is planning with a

consideration for seasonal conditions. Forecast bad weather and plan weather sensitive activities

accordingly. In addition, build some amount of flexibility into the work schedule to allow for

weather delays. Strive to keep laborers as comfortable as possible considering the weather

conditions. For instance, during periods high temperatures ensure that cold water is always

available to the workers at the installation station (Mincks and Johnston 2003). The key to

suppress the effects of foul weather on productivity is planning.

Employee Motivation

Motivation is defined by Cooper (2004) as "the process that directs your people's work

energy. It is the drive behind your own and your people's wish to satisfy 'workplace' wants and

needs." Most successful leaders consider motivational factors such as praise, recognition, and

self-esteem. People's behavior is affected by motivation, which in turn results in a committed

energy throughout the workplace. Some guidelines for increasing motivation within the

workplace include:

* Provide a safe work environment.
* Recognize good behavior.
* Show appreciation.
* Set attainable goals.
* Develop a fair pay system.
* Provide adequate training programs (Cooper 2004).

Many motivational theories are used in the construction industry in an effort to increase

productivity. Some of these theories include Herzberg's Two Factor Theory (1959), Maslow' s

Hierarchy of Needs (1954), and McGregor' s Theory X and Theory Y (1960) (Lam and Tang

2003). In order to maximize productivity, it is necessary to enlist motivational schemes to

maximize each worker' s potential.










Degree of Bilateral Communication

Good communication is necessary to efficiently complete a project. Lack of sufficient

communication can lead to lack of worker motivation. With today's technology many

communication tools are available. Some of the more commonly used forms of communication

include two-way radios, cellular phones, GPS and mobile wireless internet. Lack of

communication can cause delays due to mistakes causing rework, lack of information causing

downtime, and misinterpretation. Although endless options for communication are available,

technical problems do exist. Many people do not familiarize themselves with the user manuals,

and when problems occur, they are left with very little options. To avoid situations such as this,

employees should be encouraged to become familiar with their communication tools. Other

common problems associated with communication on construction projects include

understanding the chain of command and continuously communicating about the proj ect and

foreseeing potential problems in the future. This can be avoided by holding regular proj ect

management team meetings (Cingoranelli 2007).

Summary

Many methods for measuring productivity exist. Regardless of what measurement of

output or input is used on a construction proj ect, increasing productivity will increase a proj ect' s

efficiency and therefore increase success. The purpose of this literature review is to expand on

the top 12 factors affecting construction productivity.









CHAPTER 3
METHODOLOGY


A survey was administered to the ENR Top 400 Construction Companies (2006). The

goal was to identify and assign a weight to the top 12 factors affecting labor productivity in the

construction industry. Each factor is defined and the potential problems within each factor are

identified and explained within the literature review section of this study. The study was based

upon the following 12 maj or productivity factors:

1. Tool Management
2. Equipment Management
3. Access Planning
4. Management Skills
5. Safety
6. Quality Control
7. Scheduling
8. Employee Training/ Skills
9. Employee Age
10. Temperature/ Humidity
11. Employee Motivation
12. Degree of Bilateral Communication

The survey was distributed to 200 contractors from the ENR Top 400. The survey gives a

brief description of each factor and the contractor is asked assign a weight to each of the

factors based on his or her knowledge and past experience in the construction industry. A

complete copy of the survey can be found in Appendix A. The following are the descriptions

as they appear in the survey:


1. Management of Construction Tools: In order to maintain large amounts of tools, tool
rooms should be used to store non-permanently used tools. Periodic reports should be
performed by tool room supervisors. Tool kits should be issued on the basis of trade and
each person should be held accountable. A record should be kept of all tool kit
assignments, as well as tools not included in the kits. Periodic site inventories are
necessary to control loss, theft, and breakage. Some common problems associated with
tool management include lack of tool availability, lack of the proper tools, poor tool
maintenance, etc.









2. Managing Construction Equipment: Productivity of construction equipment is directly
linked to how the equipment is used and how the crews and operators are assigned.
Advanced planning is necessary to establish the length of time the equipment will be
utilized. Strong efforts should be made to keep the same crew and operator on the same
piece of equipment as much as possible. Some common equipment management
problems include lack of equipment usage reports, lack of equipment safety checklists,
and lack of proper scheduling of equipment.

3. Access: Site drawings should be available indicating where dense areas of labor are
working and indicating their route to and from the site. Alternate plans to cut roads
should only be made when other acceptable routes are ready. A common problem on
construction sites is poor or disrupted access caused by holes and barricades and time
spent finding alternate routes.

4. Management Skills: Management often times obscures progress on a project. Good
management is required for profitability and success.

5. Safety Management: Everyone involved with a project should be concerned with the
level of safety that is maintained. At a minimum, the level of safety on a proj ect must
comply with legislated criteria. Some common safety problems include lack of safety in
the design, lack of safety training, lack of management support, lack of preventative
maintenance on tools and equipment, etc.


6. Quality: Traditionally, generic quality tolerances are used on most projects. Therefore,
experienced operators should be periodically reviewing quality on the proj ect and
interpreting the quality expectations on the proj ect. Lack of quality control leads to
increased costs associated with rework.

7. Schedule Management: Project schedules should establish guidelines as to when and
how the proj ect should be executed. Schedule requirements need to be communicated
and properly managed throughout the entire proj ect. Some common scheduling problems
include outdated schedules, lack of schedule communication, lack of detail, trade
stacking, etc.

8. Employee Training/Skills: Overall, there is a lack of formal training in the construction
industry. High employee turnover rates deter investments in employee training. Lack of
training causes delays due to rework and overall capability levels among workers.

9. Employee Age: Some studies have claimed that the working age is beginning to decline
and impacts are becoming evident within the labor market. As the working age
diminishes, new young laborers could become harder to come by.

10. Temperature/Humidity: High temperatures and humidity tend to slow down worker
productivity. Jobsites should have appropriate rain gear and inclement weather planning.










1 1. Employee Motivation: Lack of employee motivation can be caused by many factors.
Empowering employees is one way to encourage employee motivation. Unmotivated
workers can cause loss of productivity associated with excessive down time and lack of
concentration.

12. Degree of Bilateral Communication: Effective communication between all members of a
construction project is necessary in order to maximize a proj ect and a team's potential.
Lack of communication can affect worker motivation.

Following this portion of the survey the contractor is asked to fill out a questionnaire.

This section of the survey includes questions pertaining to age, gender and industry experience.

It also includes question regarding to job title, years in the industry, size of company, and

average project size. These questions are multiple choice and fill in the blank. The objective of

these questions is to find out the perspective of the surveyed individual with regards to their

position within the industry. A copy of this portion of the survey can be found in Appendix A.


The total of all of the weights assigned to each of the factors on each survey should total

100 %. Any survey that does not meet this requirement will not be used. In addition any survey

that is not completely filled out will also be discarded from the study.










CHAPTER 4
RESULTS

Feedback

Responses

A total of 200 surveys were mailed to construction companies listed on the ENR Top 400

Contractors (2006). The surveys resulted in feedback from 24 companies, approximately a 12

% feedback. The survey was limited to the United States. The participants were asked to fill out

a questionnaire about their job title, years in the industry, years at current job, and gender. The

results of the demographic portions of the questionnaire are shown in Figures 4-1, 4-2, and 4-3.

Figure 4-1 is comparison of the positions currently held by the survey respondents. 50% of the

respondents were project managers. The remaining 50% consisted of human resource officers,

owners, and company presidents. Figure 4-2 is a gender comparison chart. Of the surveyors, 4

% were female and 96 % were male. Figure 4-3 is a histogram that represents the average

number of years the respondents have worked in the construction industry compared to the

average number of years they have been at their current j ob. The average construction

experience of the


Position






Pmiject Mayn~-
5(P/o 50P/







Figure 4-1 Current j ob positions held by survey respondents.











Gexxler


Fenrale









Ma~le
9%O/




Figure 4-2 Gender of survey participants represented as a percentage


Experience




25.00
20.00
15.00
10.00
5.00
0.oo
In~dasry ChrrentJob



Figure 4-3 Average years of industry experience compared to average years in current position
respondents was 21.1 years in the industry and 18.1 years in their current position.


Delphi Method

The Delphi Method is a method used to gather the opinions of a group of experts without

any conversation between the experts, which might sway their initial responses. This is

accomplished through the use of a mail survey. The results of the survey are then averaged to

find the mean for each question or section of the survey. In this study, the experts (holding










positions within the construction industry) were asked to apply a weight to each of the top 12

factors affecting construction labor productivity, with a final total equal to 100 %.

Mean Weights

By taking the average of the 24 responses for each factor, the mean weight for each of the

factors is calculated as follows:

* Tool Management 6.48%
* Equipment Management 9.30%
* Access Planning 4.83%
* Management Skills 3.61%
* Safety 10.00%
* Quality Control 13.22%
* Scheduling 7.78%
* Employee Training/ Skills 10.35%
* Employee Age 17.39%
* Temperature/ Humidity 5.65%
* Employee Motivation 7.87%
* Degree of Bilateral Communication 4.43%

Figure 4-4 shows a comparison of the mean weights. Management Skills is the highest weighted

factor (17.39 %), followed by Schedule Management (13.2 %). The lowest weighted factor is

Employee Age (3.6%).

Further Statistical Analysis

The data is further analyzed in Table 4-1. The responses for each factor are examined to

determine the median, mode, standard deviation, and variance. Notably, six of the twelve factors

have a standard deviation higher than 5. Management Skills had the highest standard deviation

and variance (11.52 and 32.79). In order to visualize the correlation between the 24 responses

for each of the twelve factors, histograms were created as shown in Figures 4.5- 4. 16. By

looking at each of the histograms it is visible that there is very little, if any correlation between

the data responses. The histograms show how many responses fell within similar percentages.








































Figure 4-4 Mean weighted percentages for top 12 factors affecting construction labor
productivity in ascending order correlation between the data responses.




Tool management (Figure 4-5), employee age (Figure 4-13), quality control (Figure 4-10), and


access issues (Figure 4-7) all have a common recurrence of "5 %".


Table 4-1 Mean, median, mode, standard deviation, and variance of the weighted percentages for
the top 12 factors affecting labor productivity


Tool Equipment Access Management Safety
Factor Maaeent Maaement Issues Skills Maagmnt Quality Control
Mean 4.43 7.87 5.65 17.39 10.35 7.78
Median 5 5 5 15 10 7
Mode 5 5 5 10 10 5
Std. Dev 2.66 6.49 3.38 11.52 9.17 4.40
Variance 7.08 42.12 11.42 132.79 84.15 19.36


Schedule Employee Employee Temperature Employee Degree of
Factor Management Training/Skills Age /Humidity Motivation Communication
Mean 13.22 10.00 3.61 4.83 9.30 6.48
Median 10 10 5 5 7 5
Mode 10 5 5 5 5 5
Std. Dev 8.41 6.16 2.55 4.42 9.88 4.05
Variance 70.72 37.91 6.52 19.51 97.68 16.44


IRbn~ Factor Iercen~tages


Employee Age
Tool ivianageanet

Temper~ature/Huniclity
Access Issues

Igee of Ckxm unicatial

Equtipumet 19nageanet

Quality CkxtroH

Employee I/btivation

Employee Tr-ahingSkills
Safety V/anageanet

Schedule IRhnageanet

IV/anagean~et Skills


O 2 4 6 8 10 12
Ivan~ Penteage


14 16 18 20


.61

4 42r













Tool IV~anagement


18
16
14
12
10
# of esponses 8




0 to 5 6 to 10 11 to 15 16 to 20 21 to 25 25+

Weiight Range percentage )



Figure 4-5 Histogram for results from tool management factor comparing responses (as a range
of percentages) to the number of responses (falling within each range).


Equipment IV~angement


12
10


# of Responses 6




0 to 5 6 to 10 11 to 15 16 to 20 21 to 25 25+

Weight Range percentage )



Figure 4-6 Histogram for results from equipment management factor comparing responses (as a
range of percentages) to the number of responses (falling within each range).









Access Issues


14

12

# of Faspo~nses




0 to 5 6 to 10 11 to 15 16 to 20 21 to 25 25-
Weight Fange percentage )


Figure 4-7 Histogram for results from access issues factor comparing responses (as a range of
percentages) to the number of responses (falling within each range).


I~hnagervent Skills







# of Faesponses


0 to 5 6 to 10 11 to 15 16 to 20 21 to 25 25-


Weight Fange percentage )


Figure 4-8 Histogram for results from management skills factor comparing responses (as a range
of percentages) to the number of responses (falling within each range).





Figure 4-9 Histogram for results from safety management factor comparing responses (as a range
of percentages) to the number of responses (falling within each range).


Figure 4-10 Histogram for results from quality control factor comparing responses (as a range of
percentages) to the number of responses (falling within each range).


9
8
7
6
5
# of aesponses
4
3
2
1


0 to 5 6 to 10 11 to 15 16 to 20 21 to 25


Weight Range percentage )


# of Uesponses


0 to 5 6 to 10 11 to 15 16 to 20 21 to 25 25+


Weight Range percentage )


Safetyc IVanagenant


Qlality Conb'o





Schedule IVhaagemrent






# of Fasponses




0 to 5 6 to 10 11 to 15 16 to 20 21 to 25 25+
Weight Fange percentage )


Figure 4-11 Histogram for results from schedule management factor comparing responses (as a
range of percentages) to the number of responses (falling within each range).


to 25 25-


Figure 4-12 Histogram for results from employee training/skills factor comparing responses (as a
range of percentages) to the number of responses (falling within each range).


Employee Trainingr Skills


12

10


# of Fasponses 6





0 to 5 6 to 10 11 to 15 16 to 20 21

Weigt Ranye (pecentag)





# of Fasponses 10





0 to 5 6 to 10 11 to 15 16 to 20 21 to 25 25+

Weiight Fhnge percentage )



Figure 4-13 Histogram for results from employee age factor comparing responses (as a range of
percentages) to the number of responses (falling within each range).


TeniperatumfJ Humridity


16
14
12
10
# of Responses 8




O to 5 6 to 10 11 to 15 16 to 20 21 to 25 25+
Weight Range percentage )


Figure 4-14 Histogram for results from temperature/ humidity factor comparing responses (as a
range of percentages) to the number of responses (falling within each range).

Further analysis was done to determine if there was any correlation between the responses and

the gender of the respondents, as well as the number of years in the industry, and years in the


En~ployee Alge








current position held by the respondents. The correlation coefficient is a number between 1 and -

1, which measures the degree to which two variables are linearly related. A correlation of .3 or

lower was derived for each of the variables considered. There was no significant correlation

between the responses of males compared to females. When comparing years in the industry, the

correlation test considered respondents with greater than 15 years of experience compared to

those with less than 15 years of experience. The correlation was also determined to be less than

.3, an insignificant correlation. The final correlation test considered respondents with greater

than 10 years in their current position compared to those with less than 10 years in their current


Figure 4-15 Histogram for results from employee motivation factor comparing responses (as a
range of percentages) to the number of responses (falling within each range).


Employee IMblivation


# of hqsonses


0 to 5 6 to 10 11 to 15 16 to 20 21 to 25

Weight Anlge percentage )











Degree of Bilateral Connunication

14
12
10

# of Re~sponses




O to 5 6 to 10 11 to 15 16 to 20 21 to 25 25+-
V\b~ight Range percentage )


Figure 4-16 Histogram for results from the degree of bilateral communication factor comparing
responses (as a range of percentages) to the number of responses (falling within each
range) .

The result from this correlation test was that there is no significant correlation between the

number of years the respondents have been in their current position and their respective

responses.

Summary

In order for the average weights that have resulted from this study to be meaningful,

some sort of correlation should exist between the responses. It has become evident that this

study's limitations may be too broad. Covering the entire United States with only 24 responses

can in no way be considered an accurate average to represent all construction contractors within

such a large region. For example, if the survey had been limited to the county of Alachua, 24

respondents, out of 200 would have resulted in more accurate conclusions. As 24 is a larger

percentage of the contractors representing Alachua County compared to the percentage

representing the United States. Another deficiency in this study, using one factor as a more

specific example, "Temperature and Humidity" has various effects across the United States. A










company in Maine would deal with snow and cold weather issues as opposed to Florida, which

would deal with more rain and extreme heat issues. The two regions in this example may need

to be studied separately. Overall, the study did not result in enough responses to make a truly

accurate list of the average weights for the top 12 factors affecting labor productivity within the

United States.









CHAPTER 5
CONCLUSIONS AND RECOMMENDATIONS



Recap of Objectives

The main factors were identified and defined. Each factor was then expanded upon

within the literature review. The second objective of the study called for a list of weights for

each of the 12 factors. The list and the factors are as follows:

1. Tool Management 4.43%
2. Equipment Management 7.87%
3. Access Planning 5.65%
4. Management Skills 17.39%
5. Safety 10.35%
6. Quality Control 7.78%
7. Scheduling 13.22%
8. Employee Training/ Skills 10%
9. Employee Age 3.61%
10. Temperature/ Humidity 4.83%
11. Employee Motivation 9.30%
12. Degree of Bilateral Communication 6.48%

The third and final objective relates to the future applications of these percentages. In appendix

B, a worksheet and summary sheet have been created to serve as an example of how these

weights can be applied in the future. In a completed set of worksheets, each of the 12 factors

would consist of one work sheet. Each worksheet would contain a list of activities that are

involved in obtaining 100% satisfaction within this factor. The contractor is asked to assign a

value from 1 to 10 indicating how well they are achieving each particular activity on their current

project. The values for all of the activities for each individual factor are summed and then

transferred to the evaluation sheet at the end of the workbook. The total value for each factor is

then multiplied by the factor' s respective weight. The results can then be used to make very

specific plan for improving productivity early on in the project.









Recommendations


What Should be Done Differently?

In the event that this study is to be recreated, some parts of the study would yield more

accurate results if done differently. The answers from the different respondents yielded very

little correlation for most of the factors. One adjustment to this study that may change the results

is to conduct multiple surveys with the same respondents, allowing them to see where their

answers differed from other respondents, giving them the opportunity to explain. Another

beneficial change would be to increase the number of surveys distributed. These changes would

require a large increase in the amount of time allotted for the study.

Future Works

In the future, a similar, but more focused study could be done. Instead of only limiting

the survey to upper level construction managers and owners, focus on different levels throughout

the construction industry and compare the results between the levels. In addition, this study

could also be done focusing on multiple smaller regions across the United States and then

checking the correlation between them. In regards to this current study, in order to make the

weights useful to the construction industry, checklists must be created that will enable

construction managers to apply the weights to the scores they have given themselves and target

their productivity weaknesses early on in the proj ect.









APPENDIX A


THE SURVEY

Weighting Key Components Affecting Labor Productivity


The following survey lists the 12 most common factors in the construction industry that affect
labor productivity and a short description. Please read the description for each of the 12 factors
and allocate a percentage for each factor, with a combined total percentage of 100%. The
weights should be based on past industry knowledge and experience. Following the weighting
portion of the survey is a short questionnaire.

Instructions: Please allocate a weight to each of the following factors affecting productivity.
This weight should be allocated based upon how much this factor affects construction
productivity .

3. Management of Construction Tools: In order to maintain large amounts of tools, tool
rooms should be used to store non-permanently used tools. Periodic reports should be performed
by tool room supervisors. Tool kits should be issued on the basis of trade and each person
should be held accountable. A record should be kept of all tool kit assignments, as well as tools
not included in the kits. Periodic site inventories are necessary to control loss, theft, and
breakage. Some common problems associated with tool management include lack of tool
availability, lack of the proper tools, poor tool maintenance, etc.
Weight %

4. Managing Construction Equipment: Productivity of construction equipment is directly
linked to how the equipment is used and how the crews and operators are assigned. Advanced
planning is necessary to establish the length of time the equipment will be utilized. Strong
efforts should be made to keep the same crew and operator on the same piece of equipment as
much as possible. Some common equipment management problems include lack of equipment
usage reports, lack of equipment safety checklists, and lack of proper scheduling of equipment.
Weight %

5. Access: Site drawings should be available indicating where dense areas of labor are
working and indicating their route to and from the site. Alternate plans to cut roads should only
be made when other acceptable routes are ready. A common problem on construction sites poor
or disrupted access caused by holes and barricades and time spent finding alternate routes.
Weight %

6. Management Skills: Management often times obscures progress on a project. Good
management is required for profitability and success.
Weight %

7. Safety Management: Everyone involved with a project should be concerned with the
level of safety that is maintained. At a minimum, the level of safety on a project must comply
with legislated criteria. Some common safety problems include lack if safety in the design, lack









of safety training, lack of management support, lack of preventative maintenance on tools and
equipment, etc.
Weight %

8. Quality: Traditionally, generic quality tolerances are used on most projects. Therefore,
experienced operators should be periodically reviewing quality on the project and interpreting
the quality expectations on the project. Lack of quality control leads to increased costs
associated with rework.
Weight %

9. Schedule Management: Project schedules should establish guidelines as to when and
how the project should be executed. Schedule requirements need to be communicated and
properly managed throughout the entire project. Some common scheduling problems include
outdated schedules, lack of schedule communication, lack of detail, trade stacking, etc.
Weight_ %

10. Employee Training/Skills: Overall, there is a lack of formal training in the construction
industry. High employee turnover rates deter investments in employee training. Lack of training
causes delays due to rework and overall capability levels among workers.
Weight _%

11. Employee Age: Some studies have claimed that the working age is beginning to decline
and impacts are becoming evident within the labor market. As the working age diminishes, new
young laborers could become harder to come by.
Weight %

12. T emp erature/Humi dity: High temperatures and humidity tend to slow down worker
productivity. Jobsites should have appropriate rain gear and inclement weather planning.
Weight %

13. Employee Motivation: Lack of employee motivation can be caused by many factors.
Empowering employees is one way to encourage employee motivation. Unmotivated workers
can cause loss of productivity associated with excessive down time and lack of concentration.
Weight %

14. Degree of Bilateral Communication: Effective communication between all members of a
construction project is necessary in order to maximize a project and a team's potential. Lack of
communication can affect worker motivation.
Weight %

(Should be 100%) TOTAL WEIGHT %


Figure A-1 The survey









APPENDIX B


THE QUESTIONNAIRE


Questionnaire: Please circle the best answer for each of the following questions.
1. What is your current position within the company?
e) Project Manager b)Foreman c) Laborer d) Other:

2. How long have you worked in the construction industry? Years

3. How long have you been employed at your current job? Years

4. What is your gender? Female Male
Upon completion, please return this survey via email, fax or standard mail.
Email: caseyjo@ufl.edu
Fax: (352) 846-2772 Attn: Casey Kuykendall
Address: Casey Kuykendall
Attn: Dottie
Box 115703
Gainesville, FL 32611
Thank you for your time! Your efforts will help us complete our productivity program
enabling better opportunities for management to achieve proj ect costs savings from relatively
small investments early on in the proj ect.


Figure B-1 The questionnaire.











APPENDIX C

EXAMPLE WORKSHEET APPLICATION OF WEIGHTS

Worksheet #1 SCHEDULE MANAGEMENT (Weig~ht Value 13.22%)

Activities Weig~ht Grade (1 10) Value (Grade x Weig~ht)

1. Construction milestone schedule 40%

2. Continuous Monitoring of Proj ect 20%

3. Activities and milestones in proper sequence 5%

4. Critical path is determined. 10%

5. Trend and Change Order Procedure. 10%

6. Accurate activity duration estimates 20%

TOTAL VALUE FOR COST 100%



Figure C-1 Example worksheet for the application of weights.











APPENDIX D

EXAMPLE EVALUATION SHEET


Final Evaluation Sheet

Project: Owner:

Location: Contractor:

Contract Type: Duration:



Factor Weight Value Score

(Worksheet 1-12) (Weight Value)

1) Tool Management 4%

2) Equipment Management 8%

3) Access Plamling 6%

4) Management Skills 17%

5) Safety 10%

6) Quality Control 8%

7) Scheduling 13%

8) Employee Training/ Skills 9%

9) Employee Age 4%

10) Temperature/ Humidity 5%

11) Employee Motivation 9%

12) Degree of Bilateral Conununication 6%



TOTAL PROJECT 100%









Figure D-1 Final Evaluation Sheet





SUBJECT: Approval of Protocol #2007-U-0591
TITLE: Weighting Key Components Affecting Labor Productivity
SPONSOR: None

Iam pleased to advise you that the University of Florida Institutional Review Board has
recommended approval of this protocol. Based on its review, the UFIRB determined that this
research presents no more than minimal risk to participants. Given your protocol, it is
essential that you obtain signed documentation of informed consent from each participant.
Enclosed is the dated, IRB-approved informed consent to be used when recruiting participants
for the research.

It is essential that each of your participants sign a copy of your approved informed
consent that bears the IRB approval stamp and expiration date.


If you wish to make any changes to this protocol, including the need to increase the number
of participants authorized, you must disclose your plans before you implement them so that
the Board can assess their impact on your protocol. In addition, you must report to the Board
any unexpected complications that affect your participants.

If you have not completed this protocol by July 1. 2008, please telephone our office (392-
0433), and we will discuss the renewal process with you. It is important that you keep your
Department Chair informed about the status of this research protocoL.
ISF:dl


APPENDIX E


IRB APPROVAL


ro Box 1122so
Gainesville, FL 32611-2250
352-392-0433 (Phonle)
352-392-9234 (Fax)
irb2@uufl.edu


DATE:

TO:


FROM:


July 9, 2007

Casey Kuykendall
10288 SW 105t" Drive
Gainesville, FL 32608
Ira S. Fischler, PhD; Chair
University of Florida
Institutional Review Board


An Equal Opportunity Institution


UFI UNIVE~~~RSITY f FLRIDA


Figure E-1 IRB approval form.










LIST OF REFERENCES


Alfred, Louis E. Construction Productivity: Onsite Measurement and Management. New York:
McGraw-Hill, Inc., 1988. 1-61.

Bureau of Labor Statistics. "Career Guide to Industries." U.S. Department of Labor. 2006. 21
July 2007 .

Cingoranelli, Dom. "Use Partnering to Improve Construction Productivity." 14 Jan. 2007.
Newsreleasewire.Com. Fall 2007..

Cooper, David. Improving People Performance in Construction. Aldershot, NH: Gower, Ltd.,
2004. Fall 2007.

Cox, R.F., Issa, R.R.A., and Collins, H., Determining the Quantitative Return on Investment
(ROI) of Craft Training, National Center for Construction Education and Research,
Gainesville, FL, July, 1998 (12 pages).

Hampton, Tudor. "Firms are Using Tool Tracking for Smarter Asset Management." Engineering
News Record. 07 July 2003. Fall 2007
.

Hendrickson, Chris, and Tung Au. Project Management for Construction. 1st ed. Prentice Hall,
1998.

Horner, R. M., and A. R. Duff. More for Less: a Contractor's Guide for Improving Productivity
in Construction. Westminster, London: CIRIA, 2001. More for Less. Fall 2007
.

Jordan, Jim. "Training for Field Workers More Important Than Ever." Finance (2006). McGraw
Hill Construction. Fall 2007

Lam, Steve Y., and Conrad H. Tang, comps. Motivation of Survey Employees in Construction
Projects. 24 July 2003. Hong Kong Polytechnic University. Fall 2007
.

Langsford, Tom. "United States of America: Country Overview." Encyclopedia of the Nations.
Advameg Inc., 2006. Encyclopedia of the Nations. Gainesville. Sept.-Oct. 2007
.

Leclaire, Jennifer. "Construction Industry Braces for Long-Term Labor Shortage." Sacramento
Business Journal (2004). BizJournal. Fall 2007
.

Levitt, Raymond E., and Nancy M. Samelson. Construction Safety Management. New York:
John Wiley and Sons. Fall 2007 .










Materials Management Task Force. "Proj ect Materials Management Handbook." Construction
Industry Institute. 2007. Fall 2007 institute. org/scriptcontent/more/sp4_more. cfm>.

McTague, Bob, comp. Productivity Improvements on Alberta Major Construction Projects. Vers.
1. May 2002. Fall 2007 canada. com/statpub/albertaConstructionProj ects/pdf/ConProdStudy03 .pdf>.

Mincks, William R., and Hal Johnston. Construction Jobsite Management. 2nd ed. Thompson
Delmar Learning, 2003.

O'Brien, James J., and Robert Zilly. "From Procurement to Maintenance and Service." Builder
Space. 2007. Fall 2007 management.html>.

Schneider, Scott P. Economics of Health and Safety in Construction. Laborers' Health and Safety
Fund of North America. 1-12. 27 Sept. 2007

Schwartzkopf, William. Calculating Lost Labor Productivity in Construction Claims. 2nd ed.
Aspen, 1995. Fall 2007

Teicholtz, Paul. "Labor Productivity Declines in the Construction Industry: Causes and
Remedies." AECbytes. 14 Apr. 2004. 11 July 2007

Tucker, Richard L. "U. S. Construction Labor Productivity Trends, 1970-1998." ECLOSH 7
(1999). Electronic Library of Occupational Safety and Health. Gainesville. 3 Oct. 2007
.

United States. Bureau of Labor Statistics. Construction and Non-Farm Labor Productivity Index.
2004. Fall 2007 .

Zeiss, Geoff. "Worldwide Challenges Facing the Construction Industry." New Technology. 05
Sept. 2007. Fall 2007
.









BIOGRAPHICAL SKETCH

Casey Kuykendall was born and raised in Punta Gorda, Florida. Her parents are William

and Selina Kuykendall. She was the third of three children. She has two brothers: Jeremy and

Travis Kuykendall. In 2001, she moved to Gainesville to attend the University of Florida' s

Warrington College of Business. Upon graduating with a Bachelor of Science degree, she

continued her education in the master' s program at the Rinker School of Building Construction

also at the University of Florida. In December 2007 she will graduate with a Master of Science

in Building Construction. Upon graduation, Casey, newly married, plans to start a new career

and a family with her husband, Ryan Kennedy.





PAGE 1

KEY FACTORS AFFECTING LABOR PRODUCTIVITY IN THE CONSTRUCTION INDUSTRY By CASEY JO KUYKENDALL A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN BUILDING CONSTRUCTION UNIVERSITY OF FLORIDA 2007 1

PAGE 2

2007 Casey Jo Kuykendall 2

PAGE 3

To my family and friends 3

PAGE 4

ACKNOWLEDGMENTS I would like to thank my family and friends especially my parents, Billy and Selina Kuykendall; and my fianc, Ryan Kennedy for th eir continued support. I also thank my professors and peers for their s upport. I would not be where I am today if I stood alone in my day-to-day endeavors. For that, I am grateful. 4

PAGE 5

TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................4 LIST OF TABLES................................................................................................................. ..........7 LIST OF FIGURES.........................................................................................................................8 ABSTRACT...................................................................................................................................10 1 INTRODUCTION................................................................................................................. .12 Main Goals of This Study....................................................................................................... 12 Study Objectives.....................................................................................................................13 2 LITERATURE REVIEW.......................................................................................................14 Background.............................................................................................................................14 Does a Problem Exist?.......................................................................................................... ..15 Defining Productivity.......................................................................................................... ...18 How Does Productivity Relate to the Construction Industry?................................................19 Top 12 Factors Affecting C onstruction Labor Productivity...................................................20 Management of Construction Tools................................................................................20 Managing Construction Equipment.................................................................................20 Access Issues...................................................................................................................21 Management Skills..........................................................................................................21 Safety Issues....................................................................................................................22 Quality Control................................................................................................................23 Scheduling.......................................................................................................................24 Employee Training/Skills................................................................................................25 Employee Age.................................................................................................................25 Temperature/ Humidity...................................................................................................26 Employee Mo tivation......................................................................................................27 Degree of Bilateral Communication................................................................................28 Summary.................................................................................................................................28 3 METHODOLOGY.................................................................................................................2 9 4 RESULTS...................................................................................................................... .........32 Feedback.................................................................................................................................32 Responses...............................................................................................................................32 Delphi Method........................................................................................................................33 Mean Weights..................................................................................................................3 4 Further Statistical Analysis..............................................................................................34 Summary..........................................................................................................................42 5

PAGE 6

5 CONCLUSIONS AND RECOMMENDATIONS.................................................................44 Recap of Objectives............................................................................................................ ....44 Recommendations................................................................................................................ ...45 What Should be Done Differently?.................................................................................45 Future Works...................................................................................................................45 APPENDIX A THE SURVEY................................................................................................................... .....46 B THE QUESTIONAIRRE........................................................................................................48 C EXAMPLE WORKSHEET APPLICATION OF WEIGHTS...............................................49 D EXAMPLE EVALUATION SHEET.....................................................................................50 E IRB APPROVAL................................................................................................................. ...51 LIST OF REFERENCES...............................................................................................................52 BIOGRAPHICAL SKETCH.........................................................................................................54 6

PAGE 7

LIST OF TABLES Table page 2-1 A multi-industry comparison of injury cases per 100 full-time employees during 1996, 1997 and 1999 adapted from a book by Chris Hendrickson....................................23 4-1 Mean, median, mode, standard deviati on, and variance of the weighted percentages for the top 12 factors a ffecting labor productivity.............................................................35 7

PAGE 8

LIST OF FIGURES Figure page 2-1 Labor productivity index for US construction industry and all non-farm industries from 1964 through 2003 ...................................................................................................14 2-2 Time utilization of worker productivity in the United States............................................15 2-3 Problems contributing to unproductive time adapted from a study conducted in the United Kingdom.................................................................................................................17 2-4 Basic ingredients to successful proj ect management adapted from a book by Chris Hendrickson.......................................................................................................................22 4-1 Current job positions held by survey respondents.............................................................32 4-2 Gender of survey participan ts represented as a percentage...............................................33 4-3 Average years of industry experience co mpared to average year s in current position respondents was 21.1 years in the industry a nd 18.1 years in their current position.........33 4-4 Mean weighted percentages for top 12 factors affecting construction labor productivity in ascending order correl ation between the data responses...........................35 4-5 Histogram for results from tool manage ment factor comparing responses (as a range of percentages) to the number of re sponses (falling within each range)...........................36 4-6 Histogram for results from equipment ma nagement factor comparing responses (as a range of percentages) to the number of responses (falling within each range).................36 4-7 Histogram for results from access issues factor comparing responses (as a range ofpercentages) to the number of res ponses (falling within each range)............................37 4-8 Histogram for results management skills factor comparing responses (as a range of percentages) to the number of res ponses (falling within each range)................................37 4-9 Histogram for results from safety ma nagement factor comparing responses (as a range of percentages) to the number of responses (falling within each range).................38 4-10 Histogram for results from quality control factor comparing responses (as a range of percentages) to the number of res ponses (falling within each range)................................38 4-11 Histogram for results from schedule ma nagement factor comparing responses (as a range of percentages) to the number of responses (falling within each range).................39 4-12 Histogram for results from employee trai ning/skills factor comp aring responses (as a range of percentages) to the number of responses (falling within each range).................39 8

PAGE 9

4-13 Histogram for results from employee age factor comparing responses (as a range of percentages) to the number of res ponses (falling within each range)................................40 4-14 Histogram for results from temperature/ humidity factor comparing responses (as a range of percentages) to the number of responses (falling within each range).................40 4-15 Histogram for results from employee mo tivation factor comparing responses (as a range of percentages) to the number of responses (falling within each range).................41 4-16 Histogram for results from the degree of bilateral communication factor comparing responses (as a range of per centages) to the number of re sponses (falling within each range)......................................................................................................................... ........42 A-1 The survey................................................................................................................ ..........47 B-1 The questionnaire......................................................................................................... ......48 C-1 Example worksheet for th e application of weights............................................................49 D-1 Final Evaluation Sheet.......................................................................................................50 E-1 IRB approval form......................................................................................................... ....51 9

PAGE 10

Abstract of Thesis Presen ted 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 KEY FACTORS AFFECTING LABOR PRODUCTIVITY IN THE CONSTRUCTION INDUSTRY By Casey Jo Kuykendall December 2007 Chair: R. Raymond Issa Cochair: Ian Flood Major: Building Construction Labor productivity is one of the least studied areas with in the construction industry. Productivity improvements achieve hi gh cost savings with minimal investment. Due to the fact that profit margins are small on construction proj ects, cost savings associated with productivity are crucial to becoming a successful contract or. The chief setback to improving labor productivity is measuring labor productivity. The main objective of this study is to assign a weight of importance to each of the top twelve factors affecti ng productivity. Experts at the University of Florida Rinker School of Construc tion compiled a list of the top twelve factors affecting productivity. A survey consisting of the twelve factors and a brief explanation of each was mailed to contractors listed on the ENR Top 400 (2006) in which they were asked to apply a weight to each of the twelve fact ors, totaling 100%. Results of this survey were then analyzed using the Delphi Method. These we ights will be used in a future study to create a tool to help contractors grade produ ctivity on their projects in the pr eplanning stage and plan improvements in the most beneficial areas. This productivity tool will be created by breaking each factor down into a list of activities. The project manager will assign a value to each activity representing how well their current project is achieving this activity The total for each factor is then multiplied by its respective weight (generated in this study). The outcome of the tool will give a breakdown of 10

PAGE 11

areas for improvement along with values that allow fo r project managers to focus on the most beneficial areas. 11

PAGE 12

CHAPTER 1 INTRODUCTION Construction is one of the nations largest industries. Construction accounted for 7 % of the nations GDP in 1997 (Tucker 1999). In 2004, the construction industry provided 7 million wage and salary jobs including 1.9 million self-employed and unpaid family workers (Bureau of Labor Statistics 2006). In 1999, the construction industry provided 6.4 million jobs and the total value of new construction for the same year was $764 billion (Langsford 2006). A successful construction projec t is one that is completed on time, within budget, meets specified standards of quality, and strictly conf orms to safety policies and precautions. All of this is feasible only if the pr emeditated levels of productivity can be achieved. All the same, productivity, or lack there of, is one of the construction industry s most prevalent problems. Due to the nature of construction projects, its importance to so ciety and the existing economic resources, more emphasis should be given to improving productivity. Main Goals of This Study In the end, this study will provide a weight of importance for each of the most common factors affecting productivity. Th ese weights will then be used by a group of experts to compose a questionnaire that will provide construction managers and deci sion makers with a productivity tool that will enhance project productivity. Unlike other currently existing productivity tools, this tool can be used in the planning stage and serve as a checklist to guarantee a more productive completion of projects. Keep in mind this is not inte nded to serve as a remedy for all problems that occur on construction projects, but as one of the necessary tools for success. The major intentions of this study are as follows: To assemble a list of the most notable factors affecting productivity within the construction industry today. 12

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To develop a weight for each individual fact or based on the Delphi Method, with a total weight of 100 %. To create an example tool in which the wei ghts derived will be used to help project managers and top decision makers assess the current productivity issues on their projects from the pre-planning stage through the projects completion. Study Objectives The initial objective of this study is to iden tify the main factors associated with lost productivity on construction projects. In order to be aware of the problems associated with each factor, the problems must be completely underst ood. The top factors were identified by experts within the construction a nd human factors field of study from the University of Florida. Each of these factors will be thoroughly defi ned within the literature review section of this study. The next objective is to acquire a we ight of importance for each of thes e factors. In order to ensure that the weights are not discussed between respondents, a survey is distributed to 200 contractors listed on the ENR top 400 (2006), in which they are asked to assi gn a weight to each of the factors. Once these weights ar e established, a future study will further break down each factor into its components. These components will enable the project managers to give themselves a score from 1 to 10 for each of the components with in each factor. The final score can then be evaluated to serve as a checklist to ensure increased productivity all the way up to the completion of the project. The main objectiv es of this study are as follows: 1. To expand upon the main factors affecting labor productivity a) Definition of the factor, and b) common problems associated with each factor. 2. To allocate a weight to each factor based on its importance c) Each weight will be derived by surveys distributed to experts, and d) the Delphi Method will then be used to compile the survey responses. 3. To compose a sample productivity checklist to serve as an example of how the weights will be used in the future. 13

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CHAPTER 2 LITERATURE REVIEW Background Construction requires extensive ma nual labor. Human performance and productivity are reliant on one another. Th erefore, the most commonly used measure of productivity is the constant contract dolla rs of new construction work per work hour (Hendrickson 1998). A study by Teicholtz (2004) revealed that over 40 years (1964-2003) the construction industry lags compared to all other non-farm industries in developing and applying labor saving techniques and s ubstituting equipment for labor. Figure 2-1 depicts construction labor productivity changes as opposed to all non-farm industries from 1964-2003. A study by Figure 2-1 Labor productivity index for US cons truction industry and all non-farm industries from 1964 through 2003 (U.S. Bureau of Labor Statistics 2004). 14

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Hendrickson (1998) addressed the time utilization of the average construction worker. Only 40 % of a workers time is considered to be productive, with 55 % unproductive time, and 5 % personal time. Figure 2-2 shows a breakdown of the average workers time utilization. Does a Problem Exist? From 1966 to 2003 Haskell (2004) conducted rese arch analyzing and reporting long-term trends in construction labor pr oductivity within the US building construction industry. This research uses two distinct methodologies. The fi rst approach is aggregate productivity, which is measured using constant dollars as the input (for both labor and non-labor expenditures) and square feet of building area adjusted for quality changes as the measure of aggregate output. The Time Utilization40% 20% 20% 15% 5% Productive Time Unproductive timeAdministrative Unproductive timeInefficient W ork Mehtods Unproductive timeLabor Jurisdictions Personal time Figure 2-2 Time utilization of worker productivity in the United States. second approach is task productivity, which is calculated using labor man-hours as input and production units as output (Haskell 2004). The first approach, the output based appro ach shows a comparison of the unit costs of buildings constructed in 1966 in dollars per squa re foot, compared to buildings built in 2003. Using a factor of 5.68, the 2003 costs are then deflated back to 1966 costs. The outcome of this data shows a 12.34 % decrease in costs per square foot. The outcome is further adjusted for 15

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qualitative changes in order to be able to make a qualitative comparison. Finally after applying a formula involving the qualitative productivity increase and the quant itative productivity increase, total productivity is found to ha ve increased by 33.2 %. The s econd approach, the input based approach studies two effects. The first one is the effect of observa ble increases in labor productivity, offset by increases in capital costs (Haskell 2004). The second effect is the documented decrea se in materials cost s (Haskell, 2004). The result of this research, 32.4 % fa lls very close to the result of the output based result of 33.2 %. The conclusions of this research is that the similarity of the outcomes based on two different approaches, input and output, pr ove that productivity within th e construction industry have in fact increased over the la st 37 years by about 33 % (Haskell 2004). Another recent study by Teicholtz (2004) mentioned earlier measured productivity within the constructi on industry over a 40-year period ranging from 1964 to 2003. This study measured productivity as constant contract dol lars of new construction work per work hour (Teicholtz 2004). The results ar e the opposite of that cited by Ha skell. Teicholtz finds that productivity has been decreasing over the last forty years at a rate of about 0.59 % per year. Teicholtz summarizes this stating: The construction industry suffers from structural productivity problems that will not be rapidly cured. The slow erosion of labor productivity, the aging of the construction work force, the slow rate of change in field pract ice and the current lack of student preference for civil engineering education are serious indi cations that new approaches are needed to revitalize and bring fresh ideas into this industry (Teicholtz 2004). By comparing these two studies, it is apparent that measuring productivity and deriving a pattern is dependent on the method of data collection and measurement. Different researchers will inevitably come up with different outcome s until a standard measure of productivity is derived or if a preplanning tool is created to guarantee signifi cant increases in productivity early on in the project. 16

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A study very similar to our study was conduc ted in Canada known as the Productivity Improvements on Alberta Major Construction Proj ects. Within this, a study conducted in the United Kingdom was cited. The workers were as ked to rank a general list of common problems on their construction site and in addition they we re asked to estimate the respective lost time per problem area (McTague 2002). The four tables included in Figure 2-3 illustrate the problems and their respective time loss. Order of Factors Influencing Productivity Factor Overall Order 1 Lack of Materials 2 Crew Interference 3 Repeat Work 4 Supervision 5 Lack of Equipment, Tools 6 Absenteeism Estimated Time loss per Pr oblem in a 40-Hour Week Factor Estimated Time Loss 3 Lack of Materials 2 Crew Interference 2.5 Repeat Work 2 Supervision 2 Lack of Equipment, Tools 0.5 Absenteeism Order of Causes of Lack of Materials Factor Overall Order 1 Lack of Planning 2 Transport within Site 3 Improper Materials 4 Interference 5 Unnecessary Paperwork Order of Causes of Rework Factor Estimated Time Loss 1 Change of Instructions 2 Unclear Instructions 3 Complex Specification 4 Poor Workmanship Figure 2-3 Problems contributi ng to unproductive time adapted from a study conducted in the United Kingdom (McTague 2002). 17

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The construction industry is continuously becomi ng more complicated, with clients with higher expectations and requirements. More commonly, c lients are expecting more complex projects to be completed in a shorter period of time. Moreover, the increased competition is causing contractors to complete day-to-day business with very low profit margins, while taking on more risks (McTague 2002). In order to survive in such an industry, decision makers and project managers need to be able to ensure that their projects are being comp leted as productively as possible. In order for this to take place a new tool needs to be deve loped to ensure maximum productivity from the beginning to the end of each project The development of such a t ool is the main focus of this study. Defining Productivity Many definitions of the word productivity exis t. For the basis of this study the Merriam-Webster definition will be used. Merriam-Webster defi nes productivity as the quality or state of being productive. La bor productivity is typically meas ured as output per worker or output per labor-hour. Although there are endless de finitions for productivity, they all refer to productivity as a comparison of input versus out put. Productivity = Output/ Input. Increased productivity occurs when either 1. Output is constant, while input is reduced, and/or 2. Input is constant, while either the quantity or quality of output has been increased or enhanced. Productivity serves as a source of competitive advantage. Increasing productivity will increase output or the quality of output and if at a faster rate then competition, benefits will be achieved through the valueadded through the products (McTague 2002). 18

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How Does Productivity Relate to the Construction Industry? Increased productivity in the construction industry can be vi ewed from two perspectives, the consumer and the contractor. From the c onsumers perspective, increased productivity lowers costs, shortens constr uction schedules, offers more value for the money, and achieves better returns on investments. From the contracto rs perspective, increased productivity leads to a more satisfied customer, while also providing a competitive advantage, and in return leading to faster turnover and increased profits (Horner 2001). The definition for productivity with regards to construction is the measurement of the output of construction goods and services per unit of labor (McTague 2002). McTague (2002) of Productivity Improvements on Alberta Major Cons truction Projects comp iled the following list of commonly used definitions to measure productivity in the c onstruction industry: Labor Productivity = Ou tput/ Labor Cost or Labor Productivity = Output/Work Hours In case the input is a combin ation of various factors, productivity is termed as Total Factor Productivity and is measured as Total Factor Productivity = Total Output/ Labor + Material + Equipment + Energy + Capital Various agencies may modify the definition of productivity as per their requirements by deleting some factors and or adding other factors. For example, the American Federal Highway Administration may de fine productivity as: Productivity = Output/ Desi gn + Inspection + Constr uction + Right of Way Or Productivity = Lane Mile/ Dollars (McTague 2002). 19

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Top 12 Factors Affecting Construction Labor Productivity Management of Construction Tools Materials and tool management are a large part of any construction project. In more recent years, construction firms have allocated mo re focus on retaining small tools, which in the past were perceived as disposable. Numerous technological advances have been made that enable tool tracking to be more efficient. Ba rcodes and scanners are one of the most common techniques used to track tool s today. The problem with implementing this system is the complexity of the process. In the past the tools were just replaced, one si mple step. The barcode system requires labeling, tracking, cataloguing, f iling, and coordinating a multitude of tools. The process is much more demanding. In an article from the Engineering News Record, it is cited that Kafka, a former electrical contractor, achieved an averag e savings of $0.40 per employee per hour by implementing the barcode system. This compares to an average loss of $0.80 per hour per employee from lack and loss of tools before the barcode system was in place. Other tool tracking systems being researched include radiofrequency identification and forensic chemical marking (Hampton 2003). Managing Construction Equipment The Construction Industry Instit ute states that material and equipment currently comprise 50-60 % of construction project costs (Materials Management Task Force 2007). In addition, lack of proper materials and equipment is the number one cause of construction delays. Over the last 20 years significant gains have been made in the c onstruction industry through the implementation of computers. Along with the continued emergence of computers, equipment and materials management will assume a more im portant role in the industry. Good equipment management begins at the time the equipment is purchased. Purchasing the proper equipment that matches the need of the job, while achieving th e lowest costs is necessary to attain suitable 20

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equipment management. Proper record keeping provides information for planning maintenance and replacement activities, ensuring that they oc cur at the proper time. Managing construction equipment includes preventative maintenance, pl anning maintenance, and replacement activities (OBrien and Zilly 2007). Access Issues Very little information is available on access issues on construction sites. Reiterating what was said in the access issues portion of th e survey, site drawings should be available indicating where dense areas of labor are working a nd indicating their route to and from the site. Alternate plans to cut roads should only be ma de when other acceptable routes are ready. A common problem on construction sites is poor or disrupted access caused by holes and barricades and time spent finding alternate routes. Management Skills Construction management is schedule and plan work and materials to make certain that no one is waiting for materials, labor, or the comp letion of another task. Proper management of construction projects requires knowledge of mode rn management techniques. Figure 2-4 shows the main ingredients of successful project manage ment. A familiarity with general management knowledge and special knowledge do mains are indispensable, while supporting disciplines such as computer based information systems is a plus (Hendrickson 1998). A study at the Center for Construction Industry Studies at the University of Texas at Au stin has revealed that poor management was responsible for over half of th e time wasted on a jobsite. A construction project is unable to achieve profitability and success 21

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Ingredients to Successful Project ManagementGeneral Management Special Knowledge Domains Supporting Disciplines Figure 2-4 Basic ingredients to successful project manageme nt adapted from a book by Chris Hendrickson (Hendrickson, 1998). without the presence of good management (Tucker 1999). Good management skills include adopting a performance based management view point. This involves setting priorities for improvements, provide cost efficient and eas y to use methods, promote a supportive labormanagement relationship, and cu t costs while increasing profits (Alfred 1988). Safety Issues Many benefits as well as losses exist th rough construction safety management. The construction industry is the leader in injuries and lost workdays due to injuries. Thus these injuries are very costly. Table 2-1 shows a co mparison of the number of injury cases between the construction industry and ot her prevalent industries. In 1996, 1997 and 1998 the construction industry has the highest occurr ence of injury cases when co mpared to agriculture, mining, manufacturing, transportation, wholesale and retail, finance, and services. The more visible benefits of construction safety include cheaper workers compensation coverage thats comes with a lower experience modification rating, also increased quality, and owner satisfaction. The Business Roundtable Booklet even goes as far as st ating that a contractors safety performance is 22

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an indication of the contractors commitment to quality; basically stating that the two go hand in hand. The most prevalent hidden costs include worker replacement time, crew efficiency loss, Table 2-1 a multi-industry comparison of injury cases per 100 full-time employees during 1996, 1997 and 1999 adapted from a book by Chris Hendrickson (Hendrickson 1998). Industry 1996 1997 1998 Agriculture, forestry, fishing 8.7 8.4 7.3 Mining 5.4 5.9 4.4 Construction 9.9 9.5 8.6 Manufacturing 10.6 10.3 9.2 Transportation/ public utilities 8.7 8.2 7.3 Wholesale and retail trade 6.8 6.7 6.1 Finance, insurance, real estate 2.4 2.2 1.8 Services 6 5.6 4.9 costs incurred due to delays, costs due to rescheduled work, and safety personnel costs (Levitt and Samelson 2007). A study done in the ea rly 1980s by the Business Roundtable called the Construction Industry Cost Effectiveness Project reported that 6.5 % of total construction costs could be attributed to acciden ts. Recommendations to lower this percentage include placing safety requirements in contracts, using safety records as part of the subc ontractor prequalification process, and finally requiring management to take a more active role in onsite safety management (Schneider 2007). Quality Control Alfred (1988) states that th ere are two measures for c onstruction quality, they are accuracy and workmanship. Accuracy is defined as the measurement of how closely the job conforms to plans, specifications, code requi rements, and accepted industry standards for workmanship (Alfred 1988). Workmanship is defined as the measurement of significant differences in the worth of the finished job creat ed by master craftsman-sh ip skills (assuming, of course, that all of the work meets standards of accu racy (Alfred 1988). 23

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Some benefits associated with quality c ontrol are avoided rework, generation of new work methods, and circumventing long term problem s. Following is a list of key quality control checkpoints and quality problem areas that s hould be addressed within a jobsite quality inspection checklist. The list includes: Design requirements Completed preceding work segments Work done by qualified employees Accepted materials used Appropriate amount of materials Scope of work requirements achieved Installation specifications met Entire work phase complete All quality problems have been fixed Quality control pays for itself by increasing productivity while reducing costs (Hendrickson 1998). Scheduling The purpose of scheduling is to organize a nd allocate the resources of, equipment and labor with the construction projec ts tasks over a set period of tim e. Benefits of good scheduling include, avoiding project bottleneck s, allowing for suitable procur ement or necessary materials, and overall ensuring that the project is completed as quickly as possible. Poor scheduling can result in unnecessary waste of time caused by delays as laborers wait for materials of equipment to become available or proceeding tasks to be completed (Hendrickson 1998). In order to successfully schedule a project, there must be some methodology to the process. Many scheduling methods exist. For the basis of this study it will be assumed that computer based scheduling is applied. One of the most comm on scheduling techniques is the Critical Path Method (CPM) (Hendrickson 1998). CPM is a determinis tic technique that uses preset time estimates for each activity. CPM is very easy to understand; yet it lacks consideration for 24

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variations that can have a larg e impact on the final completion time for more complex projects. Another scheduling method that allows for randomness in completion times for each activity is known as Program Evaluation and Review Technique (PERT). PERT involves six basic steps: Identify activities Place all activities in the proper order Construct a network diagram Make time estimates for each activity Determine critical path Continually update chart as project progresses Proper applications of scheduling techniques will help avoid unnecessary delays and in turn reduce cost overruns. Employee Training/Skills Employee training benefits are much underestim ated. Jordan (2006) noted that according to the US Department of Labor, apprenticeshi p training provides a $54 re turn for every dollar invested. Despite this large return on investment contractors are hesitant to pull their workers off the job to allocate time for proper training. In addition, contractor s are averse to spending money on training. In the same article he states that contractors sp end only 1.83 % of their payroll on training, compared to the 2 % spen t by the industrial sector overall. Jordan cites a specific study completed by the University of Floridas Rinke r School of Building Construction, in which one companys training efforts resulted in a 42 % increase in productivity (Cox, Issa and Collins 1998). Overall, investing in em ployee training programs will in crease productivity and reduce costs caused by rework and lost time. Employee Age Many studies suggest that the w orking class is aging, which is leading to a shortage of young skilled workers. One article in the Sacramento Business Journal states that there has been a decline from 37.5 % to 28.5 % of skilled constr uction workers between the ages of 25 to 34 25

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between 1988 and 1997. The average age determined by The Associated Ge neral Contractors of America of the construction worker in 2004 was 47 (LeClaire 2004). Zeiss (2007) predicted that by the year 2010 the number of workers between the ages of 35 to 44 will decrease by 19 %, while the number of workers between the ages of 45 to 54 will increase by 21 %. The shortage is caused by the retirement of the baby boom generation and popularity within the younger working class to opt for office oriented jobs. Cu rrent solutions to this growing problem include a strengthening and modernization of the nation s vocational school system. One particular proposition by the Bush Administration is a program known as Skills to Build Americas Future, a plan aimed to attract young people into careers in trade fields. The industry is also filling the void by reaching out to minority groups to fill the positions (LeClaire 2004). Temperature/ Humidity Weather is to some extent unpredictable. When not scheduled ad equately, weather can cause delays due to forced changes in the schedule as well as damages causing rework. Productivity decreases in poor weather conditions for many reasons. Some construction processes are affected poorly by suboptimal weather conditions. For example, mortar and concrete become less efficient. Labor is also affected poorly by unfavorable weather conditions. For instance, when weather apparel such as rain coats or heavy jackets is necessary, labor is hindered (Mincks and Johnston 2003). Hot weather, in particular, has both a physiological and psychological effect on workers. Psychologically workers tend to b ecome restless and irritable. Physiologically they can acquire heat cramps, heat stroke, heat exhaustion, etc. The four factors in a hot environment that cause the increased stress include: Humidity Air Movement Air Temperature Heat Radiation (Schwarzkopf 1995). 26

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The most effective solution to curb the effect of inclement weather is planning with a consideration for seasonal conditio ns. Forecast bad weather and pl an weather sensitive activities accordingly. In addition, build some amount of flexibility into the work schedule to allow for weather delays. Strive to keep laborers as comfortable as possible considering the weather conditions. For instance, during periods high temperatures ensure that cold water is always available to the workers at the installation station (Mincks and Johnston 2003). The key to suppress the effects of foul weathe r on productivity is planning. Employee Motivation Motivation is defined by Cooper (2004) as t he process that dire cts your peoples work energy. It is the drive behind your own and your peoples wish to satisf y workplace wants and needs. Most successful leaders consider motivat ional factors such as praise, recognition, and self-esteem. Peoples behavior is affected by motivation, which in turn results in a committed energy throughout the workplace. Some guide lines for increasing motivation within the workplace include: Provide a safe work environment. Recognize good behavior. Show appreciation. Set attainable goals. Develop a fair pay system. Provide adequate training programs (Cooper 2004). Many motivational theories are used in the construction industry in an effort to increase productivity. Some of these theories include Herzbergs Two Factor Theory (1959), Maslows Hierarchy of Needs (1954), and McGregors Th eory X and Theory Y (1960) (Lam and Tang 2003). In order to maximize productivity, it is necessary to enlist motivational schemes to maximize each workers potential. 27

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Degree of Bilateral Communication Good communication is necessary to efficiently complete a project. Lack of sufficient communication can lead to lack of worker motivation. With todays technology many communication tools are available. Some of the more commonl y used forms of communication include two-way radios, cellula r phones, GPS and mobile wi reless internet. Lack of communication can cause delays due to mistakes causing rework, lack of information causing downtime, and misinterpretation. Although endl ess options for communication are available, technical problems do exist. Many people do not familiarize themselves with the user manuals, and when problems occur, they are left with very little options. To avoid s ituations such as this, employees should be encouraged to become fami liar with their communication tools. Other common problems associated with communi cation on construction projects include understanding the chain of command and con tinuously communicating about the project and foreseeing potential problems in the future. This can be avoided by holding regular project management team meetings (Cingoranelli 2007). Summary Many methods for measuring productivity exist. Regardless of what measurement of output or input is used on a construction proj ect, increasing productivity will increase a projects efficiency and therefore increase success. The purpose of this literature review is to expand on the top 12 factors affecti ng construction productivity. 28

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CHAPTER 3 METHODOLOGY A survey was administered to the ENR Top 400 Construction Companies (2006). The goal was to identify and assign a we ight to the top 12 factors aff ecting labor productivity in the construction industry. Each factor is defined and the potential pr oblems within each factor are identified and explained within the literature review section of this study. The study was based upon the following 12 major productivity factors: 1. Tool Management 2. Equipment Management 3. Access Planning 4. Management Skills 5. Safety 6. Quality Control 7. Scheduling 8. Employee Training/ Skills 9. Employee Age 10. Temperature/ Humidity 11. Employee Motivation 12. Degree of Bilateral Communication The survey was distributed to 200 contractor s from the ENR Top 400. The survey gives a brief description of each factor and the contractor is asked assign a weight to each of the factors based on his or her knowledge and past experience in the cons truction industry. A complete copy of the survey can be found in Appendix A. The following are the descriptions as they appear in the survey: 1. Management of Construction Tools: In orde r to maintain large amounts of tools, tool rooms should be used to store non-permanently used tools. Periodic reports should be performed by tool room supervisors. Tool k its should be issued on the basis of trade and each person should be held accountable. A record should be kept of all tool kit assignments, as well as tools not included in the kits. Periodic site inventories are necessary to control loss, theft, and breakage. Some common problems associated with tool management include lack of tool availa bility, lack of the pr oper tools, poor tool maintenance, etc. 29

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2. Managing Construction Equipment: Productivity of construction equipment is directly linked to how the equipment is used and how the crews and operators are assigned. Advanced planning is necessary to establish the length of time the equipment will be utilized. Strong efforts should be made to keep the same crew a nd operator on the same piece of equipment as much as possible. Some common equipment management problems include lack of equipment usage report s, lack of equipments safety checklists, and lack of proper scheduling of equipment. 3. Access: Site drawings should be availabl e indicating where dense areas of labor are working and indicating their ro ute to and from the site. Alternate plans to cut roads should only be made when other acceptable routes are ready. A common problem on construction sites is poor or disrupted acce ss caused by holes and barricades and time spent finding alternate routes. 4. Management Skills: Management often times obscures progress on a project. Good management is required for profitability and success. 5. Safety Management: Everyone involved with a project should be concerned with the level of safety that is maintained. At a minimum, the level of safety on a project must comply with legislated criteria. Some common safety problems include lack of safety in the design, lack of safety training, lack of management support, lack of preventative maintenance on tools and equipment, etc. 6. Quality: Traditionally, generic quality tolerances are used on most projects. Therefore, experienced operators should be periodical ly reviewing quality on the project and interpreting the quality expecta tions on the project. Lack of quality control leads to increased costs associated with rework. 7. Schedule Management: Project schedules shoul d establish guidelines as to when and how the project should be executed. Sche dule requirements need to be communicated and properly managed throughout the entire project. Some common scheduling problems include outdated schedules, lack of sche dule communication, lack of detail, trade stacking, etc. 8. Employee Training/Skills: Overall, there is a lack of formal training in the construction industry. High employee turnover rates deter investments in employee training. Lack of training causes delays due to rework and overall capability le vels among workers. 9. Employee Age: Some studies have claimed that the working age is beginning to decline and impacts are becoming evident within the labor market. As the working age diminishes, new young laborers could become harder to come by. 10. Temperature/Humidity: High temperatures a nd humidity tend to slow down worker productivity. Jobsites should have appropriate rain gear and inclement weather planning. 30

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11. Employee Motivation: Lack of employee mo tivation can be caused by many factors. Empowering employees is one way to encourage employee motivation. Unmotivated workers can cause loss of productivity associ ated with excessive down time and lack of concentration. 12. Degree of Bilateral Communication: Effec tive communication between all members of a construction project is necessary in order to maximize a project and a teams potential. Lack of communication can affect worker motivation. Following this portion of the survey the contractor is asked to fill out a questionnaire. This section of the survey includes questions pe rtaining to age, gender an d industry experience. It also includes question regarding to job ti tle, years in the industr y, size of company, and average project size. These questions are multiple choice and fill in the blank. The objective of these questions is to find out the perspective of the surveyed individual with regards to their position within the industry. A copy of this por tion of the survey can be found in Appendix A. The total of all of the weight s assigned to each of the factors on each survey should total 100 %. Any survey that does not meet this requir ement will not be used. In addition any survey that is not completely filled out w ill also be discarded from the study. 31

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CHAPTER 4 RESULTS Feedback Responses A total of 200 surveys were mailed to c onstruction companies listed on the ENR Top 400 Contractors (2006). The survey s resulted in feedback from 24 companies, approximately a 12 % feedback. The survey was limited to the United States. The participants were asked to fill out a questionnaire about their job title, years in the industry, year s at current job, and gender. The results of the demographic portions of the questi onnaire are shown in Figures 4-1, 4-2, and 4-3. Figure 4-1 is comparison of the positions currently held by the survey respondents. 50% of the respondents were project managers. The remain ing 50% consisted of human resource officers, owners, and company presidents. Figure 4-2 is a gender comparison chart. Of the surveyors, 4 % were female and 96 % were male. Figure 4-3 is a histogram that represents the average number of years the respondents have worked in the construction industry compared to the average number of years they have been at their current job. The average construction experience of the Position Project Manager 50% Other 50% Figure 4-1 Current job positions held by survey respondents. 32

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Gende r Male 96% Female 4% Figure 4-2 Gender of survey particip ants represented as a percentage 21.09 11.80 0.00 5.00 10.00 15.00 20.00 25.00 Industry Current Job Experience Figure 4-3 Average years of industry experience compared to average ye ars in current position respondents was 21.1 years in the industry a nd 18.1 years in their current position. Delphi Method The Delphi Method is a method used to gath er the opinions of a gr oup of experts without any conversation between the experts, which mi ght sway their initial responses. This is accomplished through the use of a mail survey. The results of the survey are then averaged to find the mean for each question or section of th e survey. In this study, the experts (holding 33

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positions within the construction industry) were asked to apply a weight to each of the top 12 factors affecting constructi on labor productivity, with a final total equal to 100 %. Mean Weights By taking the average of the 24 responses for each factor, the mean weight for each of the factors is calculated as follows: Tool Management 6.48% Equipment Management 9.30% Access Planning 4.83% Management Skills 3.61% Safety 10.00% Quality Control 13.22% Scheduling 7.78% Employee Training/ Skills 10.35% Employee Age 17.39% Temperature/ Humidity 5.65% Employee Motivation 7.87% Degree of Bilateral Communication 4.43% Figure 4-4 shows a comparison of the mean weights. Management Skills is the highest weighted factor (17.39 %), followed by Schedule Management (13.2 %). The lowest weighted factor is Employee Age (3.6%). Further Statistical Analysis The data is further analyzed in Table 4-1. The responses for each factor are examined to determine the median, mode, standa rd deviation, and variance. Nota bly, six of the twelve factors have a standard deviation higher than 5. Manage ment Skills had the highest standard deviation and variance (11.52 and 32.79). In order to visu alize the correlation be tween the 24 responses for each of the twelve factors, histograms were created as shown in Figures 4.54.16. By looking at each of the histograms it is visible that there is very little, if any correlation between the data responses. The histograms show how ma ny responses fell within similar percentages. 34

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Mean Factor Percentages 17.39 13.22 10.35 10 9.3 7.87 7.78 6.48 5.65 4.83 4.43 3.61 02468101214161820 Management Skills Schedule Management Safety Management Employee Training/Skills Employee Motivation Quality Controll Equipment Management Degree of Communication Access Issues Temperature/Humidity Tool Management Employee Age Mean Percentage Figure 4-4 Mean weighted percentages for t op 12 factors affecti ng construction labor productivity in ascending order correl ation between the data responses. Tool management (Figure 4-5), employee age (Fi gure 4-13), quality cont rol (Figure 4-10), and access issues (Figure 4-7) all have a common recurrence of %. Table 4-1 Mean, median, mode, standard deviatio n, and variance of the weighted percentages for the top 12 factors affec ting labor productivity Factor Tool Management Equipment Management Access Issues Management Skills Safety Management Quality Control Mean 4.43 7.87 5.65 17.39 10.35 7.78 Median 5 5 5 15 10 7 Mode 5 5 5 10 10 5 Std. Dev 2.66 6.49 3.38 11.52 9.17 4.40 Variance 7.08 42.12 11.42 132.79 84.15 19.36 Factor Schedule Management Employee Training/Skills Employee Age Temperature /Humidity Employee Motivation Degree of Communication Mean 13.22 10.00 3.61 4.83 9.30 6.48 Median 10 10 5 5 7 5 Mode 10 5 5 5 5 5 Std. Dev 8.41 6.16 2.55 4.42 9.88 4.05 Variance 70.72 37.91 6.52 19.51 97.68 16.44 35

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18 5 0 0 0 0 0 2 4 6 8 10 12 14 16 18 # of Response s 0 to 56 to 1011 to 1516 to 2021 to 2525+ Weight Range (pecentage)Tool Management Figure 4-5 Histogram for results from tool management factor comparing responses (as a range of percentages) to the number of re sponses (falling within each range). 12 7 1 2 1 0 0 2 4 6 8 10 12 # of Response s 0 to 56 to 1011 to 1516 to 2021 to 2525+ Weight Range (pecentage)Equipment Mangement Figure 4-6 Histogram for results from equipment management fact or comparing responses (as a range of percentages) to the number of responses (falling within each range). 36

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14 8 1 0 0 0 0 2 4 6 8 10 12 14 # of Response s 0 to 56 to 1011 to 1516 to 2021 to 2525+ Weight Range (pecentage)Access Issues Figure 4-7 Histogram for results from access issues factor comparing responses (as a range of percentages) to the number of res ponses (falling within each range). 4 6 4 3 1 5 0 1 2 3 4 5 6 # of Response s 0 to 56 to 1011 to 1516 to 2021 to 2525+ Weight Range (pecentage)Management Skills Figure 4-8 Histogram for results fr om management skills factor comparing responses (as a range of percentages) to the number of re sponses (falling within each range). 37

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9 9 2 1 0 2 0 1 2 3 4 5 6 7 8 9 # of Response s 0 to 56 to 1011 to 1516 to 2021 to 2525+ Weight Range (pecentage)Safety Management Figure 4-9 Histogram for results from safety mana gement factor comparing responses (as a range of percentages) to the number of re sponses (falling within each range). 11 9 2 1 0 0 0 2 4 6 8 10 12 # of Response s 0 to 56 to 1011 to 1516 to 2021 to 2525+ Weight Range (pecentage)Quality Control Figure 4-10 Histogram for results from quality cont rol factor comparing responses (as a range of percentages) to the number of res ponses (falling within each range). 38

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6 7 5 1 1 3 0 1 2 3 4 5 6 7 # of Response s 0 to 56 to 1011 to 1516 to 2021 to 2525+ Weight Range (pecentage)Schedule Management Figure 4-11 Histogram for results from schedule management factor comparing responses (as a range of percentages) to the number of responses (falling within each range). 11 1 8 3 0 0 0 2 4 6 8 10 12 # of Response s 0 to 56 to 1011 to 1516 to 2021 to 2525+ Weight Range (pecentage)Employee Training/ Skills Figure 4-12 Histogram for results from employee tr aining/skills factor co mparing responses (as a range of percentages) to the number of responses (falling within each range). 39

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20 3 0 0 0 0 0 5 10 15 20 # of Response s 0 to 56 to 1011 to 1516 to 2021 to 2525+ Weight Range (pecentage)Employee Age Figure 4-13 Histogram for results from employee ag e factor comparing responses (as a range of percentages) to the number of res ponses (falling within each range). 15 7 0 1 0 0 0 2 4 6 8 10 12 14 16 # of Response s 0 to 56 to 1011 to 1516 to 2021 to 2525+ Weight Range (pecentage)Temperature/ Humidity Figure 4-14 Histogram for results from temperatur e/ humidity factor comparing responses (as a range of percentages) to the number of responses (falling within each range). Further analysis was done to determine if ther e was any correlation between the responses and the gender of the respondents, as well as the number of years in the industry, and years in the 40

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current position held by the respondents. The correl ation coefficient is a number between 1 and 1, which measures the degree to which two variable s are linearly related. A correlation of .3 or lower was derived for each of the variables cons idered. There was no significant correlation between the responses of males compared to fema les. When comparing ye ars in the industry, the correlation test considered respondents with grea ter than 15 years of ex perience compared to those with less than 15 years of experience. The correlation was al so determined to be less than .3, an insignificant correlation. The final correlation test considered respondents with greater than 10 years in their current position compared to those with less than 10 years in their current 11 6 5 0 0 1 0 2 4 6 8 10 12 # of Response s 0 to 56 to 1011 to 1516 to 2021 to 2525+ Weight Range (pecentage)Employee Motivation Figure 4-15 Histogram for results from employee motivation factor comparing responses (as a range of percentages) to the number of responses (falling within each range). 41

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14 5 4 0 0 0 0 2 4 6 8 10 12 14 # of Responses 0 to 56 to 1011 to 1516 to 2021 to 2525+ Weight Range (pecentage)Degree of Bilateral Communication Figure 4-16 Histogram for results from the degree of bilateral communication factor comparing responses (as a range of per centages) to the number of re sponses (falling within each range). The result from this correlation test was that there is no significant correlation between the number of years the respondents have been in their current position and their respective responses. Summary In order for the average weights that have resulted from this study to be meaningful, some sort of correlation should ex ist between the responses. It has become evident that this studys limitations may be too broad. Covering the entire United States with only 24 responses can in no way be considered an accurate average to represent all construc tion contractors within such a large region. For example, if the survey had been limit ed to the county of Alachua, 24 respondents, out of 200 would have resulted in mo re accurate conclusions. As 24 is a larger percentage of the contractors representing Alachua County compared to the percentage representing the United States. Another deficiency in this stu dy, using one factor as a more specific example, Temperature and Humidity ha s various effects across the United States. A 42

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company in Maine would deal with snow and cold weather issues as opposed to Florida, which would deal with more rain and extreme heat issu es. The two regions in this example may need to be studied separately. Over all, the study did not result in enough responses to make a truly accurate list of the average weights for the top 12 factors affecting labor productivity within the United States. 43

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CHAPTER 5 CONCLUSIONS AND RECOMMENDATIONS Recap of Objectives The main factors were identified and defined. Each factor was then expanded upon within the literature review. The second objectiv e of the study called for a list of weights for each of the 12 factors. The list and the factors are as follows: 1. Tool Management 4.43% 2. Equipment Management 7.87% 3. Access Planning 5.65% 4. Management Skills 17.39% 5. Safety 10.35% 6. Quality Control 7.78% 7. Scheduling 13.22% 8. Employee Training/ Skills 10% 9. Employee Age 3.61% 10. Temperature/ Humidity 4.83% 11. Employee Motivation 9.30% 12. Degree of Bilateral Communication 6.48% The third and final objective relates to the future applications of these percentages. In appendix B, a worksheet and summary sheet have been created to serve as an example of how these weights can be applied in the future. In a co mpleted set of worksheets, each of the 12 factors would consist of one work sheet. Each workshee t would contain a list of activities that are involved in obtaining 100% satisfaction within this factor. The contractor is asked to assign a value from 1 to 10 indicating how well they are achieving each part icular activity on their current project. The values for all of the activities for each individual factor are summed and then transferred to the evaluation sheet at the end of the workbook. The total value for each factor is then multiplied by the factors respective weight. The results can then be used to make very specific plan for improving producti vity early on in the project. 44

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Recommendations What Should be Done Differently? In the event that this study is to be recreated, some part s of the study would yield more accurate results if done differently. The answer s from the different respondents yielded very little correlation for most of the factors. One adjustment to this study that may change the results is to conduct multiple surveys with the same respondents, allowing them to see where their answers differed from other respondents, givi ng them the opportunity to explain. Another beneficial change would be to increase the num ber of surveys distribute d. These changes would require a large increase in the amoun t of time allotted for the study. Future Works In the future, a similar, but more focused study could be done. Instead of only limiting the survey to upper level construction managers and owners, focus on di fferent levels throughout the construction industry and compare the result s between the levels. In addition, this study could also be done focusing on multiple smaller regions across the United States and then checking the correlation between them. In regard s to this current study, in order to make the weights useful to the construction industry, ch ecklists must be created that will enable construction managers to apply the weights to the scores they have given themselves and target their productivity weaknesses early on in the project. 45

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APPENDIX A THE SURVEY Weighting Key Components Affecting Labor Productivity The following survey lists the 12 most common f actors in the constructi on industry that affect labor productivity and a short desc ription. Please read the descri ption for each of the 12 factors and allocate a percentage for each factor, with a combined to tal percentage of 100%. The weights should be based on past industry knowle dge and experience. Following the weighting portion of the survey is a short questionnaire. Instructions: Please allocate a weight to each of the following factors affecting productivity. This weight should be allocated based upon how much this factor affects construction productivity. 3. Management of Construction Tools: In orde r to maintain large amounts of tools, tool rooms should be used to store non-permanently used tools. Periodic reports should be performed by tool room supervisors. Tool kits should be issued on the basis of trade and each person should be held accountable. A record should be kept of all tool ki t assignments, as well as tools not included in the kits. Periodic site invent ories are necessary to control loss, theft, and breakage. Some common problems associated w ith tool management include lack of tool availability, lack of the proper tools, poor tool maintenance, etc. Weight____% 4. Managing Construction Equipment: Productivity of construction equipment is directly linked to how the equipment is used and how th e crews and operators are assigned. Advanced planning is necessary to establish the length of time the equipment will be utilized. Strong efforts should be made to keep the same crew and operator on the same piece of equipment as much as possible. Some common equipment ma nagement problems include lack of equipment usage reports, lack of equipments safety checklis ts, and lack of proper scheduling of equipment. Weight____% 5. Access: Site drawings shoul d be available indicating where dense areas of labor are working and indicating their route to and from th e site. Alternate plans to cut roads should only be made when other acceptable routes are ready. A common problem on construction sites poor or disrupted access caused by holes and barricad es and time spent finding alternate routes. Weight____% 6. Management Skills: Management often tim es obscures progress on a project. Good management is required for profitability and success. Weight____% 7. Safety Management: Everyone involved with a project should be concerned with the level of safety that is maintained. At a minimu m, the level of safety on a project must comply with legislated criteria. Some common safety pr oblems include lack if safety in the design, lack 46

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of safety training, lack of management support, lack of preven tative maintenance on tools and equipment, etc. Weight____% 8. Quality: Traditionally, generic quality tolerances are used on most projects. Therefore, experienced operators should be periodically re viewing quality on the project and interpreting the quality expectations on the project. Lack of quality control leads to increased costs associated with rework. Weight____% 9. Schedule Management: Project schedules shou ld establish guidelines as to when and how the project should be execu ted. Schedule requirements need to be communicated and properly managed throughout the entire project. Some common scheduling problems include outdated schedules, lack of schedule communication, lack of detail, trade stacking, etc. Weight___ % 10. Employee Training/Skills: Overall, there is a lack of formal training in the construction industry. High employee turnover rates deter investments in empl oyee training. Lack of training causes delays due to rework and overall capability levels among workers. Weight ___ % 11. Employee Age: Some studies have claimed th at the working age is beginning to decline and impacts are becoming evident within the labor market. As the working age diminishes, new young laborers could become harder to come by. Weight____% 12. Temperature/Humidity: High temperatures and humidity tend to slow down worker productivity. Jobsites should have appropriate rain gear and inclement weather planning. Weight____% 13. Employee Motivation: Lack of employee mo tivation can be caused by many factors. Empowering employees is one way to encourage employee motivation. Unmotivated workers can cause loss of productivity asso ciated with excessive down tim e and lack of concentration. Weight____% 14. Degree of Bilateral Communication: Effec tive communication between all members of a construction project is n ecessary in order to maximize a project and a teams potential. Lack of communication can affect worker motivation. Weight____% (Should be 100%) TOTAL WEIGHT_____% Figure A-1 The survey 47

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APPENDIX B THE QUESTIONNAIRE Questionnaire: Please circle the best answer for each of the following questions. 1. What is your current positi on within the company? e) Project Manager b)Foreman c) Laborer d) Other: __________ 2. How long have you worked in the c onstruction industry? ______ Years 3. How long have you been employed at your current job? ______ Years 4. What is your gender? ________Female ________Male Upon completion, please return this surv ey via email, fax or standard mail. Email: caseyjo@ufl.edu Fax: (352) 846-2772 Attn: Casey Kuykendall Address: Casey Kuykendall Attn: Dottie Box 115703 Gainesville, FL 32611 Thank you for your time! Your efforts will help us complete our productivity program enabling better opportunities for management to achieve project costs savings from relatively small investments early on in the project. Figure B-1 The questionnaire. 48

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APPENDIX C EXAMPLE WORKSHEET APPLICATION OF WEIGHTS Worksheet #1 SC HEDULE MANAGEMENT (Weight Value 13.22%) Activities Weight Grade (1 10) Value (Grade x Weight) 1. Construction milestone schedule 40% 2. Continuous Monitoring of Project 20% 3. Activities and milestones in proper sequence 5% 4. Critical path is determined. 10% 5. Trend and Change Order Procedure. 10% 6. Accurate activity duration estimates 20% TOTAL VALUE FOR COST 100% Figure C-1 Example worksheet for the application of weights. 49

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APPENDIX D EXAMPLE EVALUATION SHEET Final Evaluation Sheet Project: Owner: Location: Contractor: Contract Type: Duration: Factor Weight Value Score (Worksheet 1-12) (Weight Value) 1) Tool Management 4% 2) Equipment Management 8% 3) Access Planning 6% 4) Management Skills 17% 5) Safety 10% 6) Quality Control 8% 7) Scheduling 13% 8) Employee Training/ Skills 9% 9) Employee Age 4% 10) Temperature/ Humidity 5% 11) Employee Motivation 9% 12) Degree of Bilateral Communication 6% ________________________________________________________________________ TOTAL PROJECT 100% Figure D-1 Final Evaluation Sheet 50

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APPENDIX E IRB APPROVAL Figure E-1 IRB approval form. 51

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LIST OF REFERENCES Alfred, Louis E. Construction Productivit y: Onsite Measurement and Management New York: McGraw-Hill, Inc., 1988. 1-61. Bureau of Labor Statistics. "C areer Guide to Industries." U.S. Department of Labor. 2006. 21 July 2007 . Cingoranelli, Dom. "Use Partnering to Im prove Construction Pr oductivity." 14 Jan. 2007. Newsreleasewire.Com Fall 2007.. Cooper, David. Improving People Performance in Construction Aldershot, NH: Gower, Ltd., 2004. Fall 2007. Cox, R.F., Issa, R.R.A., and Collins, H., Determ ining the Quantitative Return on Investment (ROI) of Craft Training, Na tional Center for Constructi on Education and Research, Gainesville, FL, July, 1998 (12 pages). Hampton, Tudor. "Firms are Using Tool Tracking for Smarter Asset Management." Engineering News Record. 07 July 2003. Fall 2007 . Hendrickson, Chris, and Tung Au. Pr oject Management for Construction 1st ed. Prentice Hall, 1998. Horner, R. M., and A. R. Duff. More for Less: a Contractor's Guide for Improving Productivity in Construction Westminster, London: CIRIA, 2001. More for Less Fall 2007 . Jordan, Jim. "Training for Field Workers More Important Than Ever." Finance (2006). McGraw Hill Construction Fall 2007 . Lam, Steve Y., and Conrad H. Tang, comps. Mo tivation of Survey Employees in Construction Projects 24 July 2003. Hong Kong Polytechnic University. Fall 2007 . Langsford, Tom. "United States of America: Country Overview." Encyclopedia of the Nations Advameg Inc., 2006. Encyclopedia of the Nations Gainesville. Sept.-Oct. 2007 . Leclaire, Jennifer. "Construction Industry Braces for Long-Term Labor Shortage." Sacramento Business Journal (2004). BizJournal Fall 2007 . Levitt, Raymond E., and Nancy M. Samelson. Construction Safety Management New York: John Wiley and Sons. Fall 2007 52

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Materials Management Task Force. "Project Materials Management Handbook." Construction Industry Institute. 2007. Fall 2007 . McTague, Bob, comp. Productivity Improvement s on Alberta Major Construction Projects Vers. 1. May 2002. Fall 2007 . Mincks, William R., and Hal Johnston. Construction Jobsite Management 2nd ed. Thompson Delmar Learning, 2003. OBrien, James J., and Robert Zilly. From Proc urement to Maintenance and Service. Builder Space 2007. Fall 2007 . Schneider, Scott P. Economics of Health and Safety in Construction Laborers' Health and Safety Fund of North America. 1-12. 27 Se pt. 2007 . Schwartzkopf, William. Calculating Lost Labor Productivity in Construction Claims 2nd ed. Aspen, 1995. Fall 2007 Teicholtz, Paul. "Labor Productiv ity Declines in the Constr uction Industry: Causes and Remedies." AECbytes. 14 Apr. 2004. 11 July 2007 . Tucker, Richard L. "U.S. Construction Labor Productivity Trends, 1970-1998." ECLOSH 7 (1999). Electronic Library of O ccupational Safety and Health Gainesville. 3 Oct. 2007 . United States. Bureau of Labor Statistics. Construction and Non-Farm Labor Productivity Index. 2004. Fall 2007 . Zeiss, Geoff. "Worldwide Challenges Facing the Construction Indus try." New Technology. 05 Sept. 2007. Fall 2007 . 53

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BIOGRAPHICAL SKETCH Casey Kuykendall was born and raised in Punt a Gorda, Florida. Her parents are William and Selina Kuykendall. She was the third of thr ee children. She has two brothers: Jeremy and Travis Kuykendall. In 2001, she moved to Gain esville to attend the Un iversity of Floridas Warrington College of Business. Upon graduating with a Bach elor of Science degree, she continued her education in the masters progra m at the Rinker School of Building Construction also at the University of Florid a. In December 2007 she will gra duate with a Master of Science in Building Construction. Upon graduation, Case y, newly married, plans to start a new career and a family with her husband, Ryan Kennedy. 54