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Problem Solving Styles and Methods of Florida Agricultural Industry Leaders

Permanent Link: http://ufdc.ufl.edu/UFE0016140/00001

Material Information

Title: Problem Solving Styles and Methods of Florida Agricultural Industry Leaders
Physical Description: 1 online resource (70 p.)
Language: english
Creator: Durham, Dyanna R
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: creative, critical, decision, problem, solving, thinking
Agricultural Education and Communication -- Dissertations, Academic -- UF
Genre: Agricultural Education and Communication thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: The purpose of this study was to identify and describe the problem solving styles and practices of leaders in the Florida agricultural industry. Sixteen leaders representing nine major commodity groups participated in qualitative interviews and completed a problem solving style assessment in order to identify and compare leaders' problem solving styles and methods. This study found that the participating leaders most often face personnel, staff and management problems. These leaders often sought to work with others when solving the problems faced in their positions, and the problem solving practices utilized by the leaders was determined by the nature of the problem and situation. This study found both adaptive and innovative leaders in Florida's agricultural industry, with 56% of the participants being innovators and 44% being adaptors. These leaders, both adaptors and innovators, were found to utilize problem solving practices predicted for their problem solving style as well as practices not predicted for their style. The majority of participants who utilized unpredicted problem solving practices utilized practices that were more adaptive than expected.
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 Dyanna R Durham.
Thesis: Thesis (M.S.)--University of Florida, 2007.
Local: Adviser: Rudd, Rick.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0016140:00001

Permanent Link: http://ufdc.ufl.edu/UFE0016140/00001

Material Information

Title: Problem Solving Styles and Methods of Florida Agricultural Industry Leaders
Physical Description: 1 online resource (70 p.)
Language: english
Creator: Durham, Dyanna R
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: creative, critical, decision, problem, solving, thinking
Agricultural Education and Communication -- Dissertations, Academic -- UF
Genre: Agricultural Education and Communication thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: The purpose of this study was to identify and describe the problem solving styles and practices of leaders in the Florida agricultural industry. Sixteen leaders representing nine major commodity groups participated in qualitative interviews and completed a problem solving style assessment in order to identify and compare leaders' problem solving styles and methods. This study found that the participating leaders most often face personnel, staff and management problems. These leaders often sought to work with others when solving the problems faced in their positions, and the problem solving practices utilized by the leaders was determined by the nature of the problem and situation. This study found both adaptive and innovative leaders in Florida's agricultural industry, with 56% of the participants being innovators and 44% being adaptors. These leaders, both adaptors and innovators, were found to utilize problem solving practices predicted for their problem solving style as well as practices not predicted for their style. The majority of participants who utilized unpredicted problem solving practices utilized practices that were more adaptive than expected.
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 Dyanna R Durham.
Thesis: Thesis (M.S.)--University of Florida, 2007.
Local: Adviser: Rudd, Rick.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0016140:00001


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PROBLEM SOLVING STYLES AND METHODS OF FLORIDA AGRICULTURAL
INDUSTRY LEADERS














By

DYANNA RENEE DURHAM


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

UNIVERSITY OF FLORIDA


2007



































2007 Dyanna Renee Durham

































To my parents, Tommy and Janice Durham, and my sister, Amanda, for their incredible
love and support.















ACKNOWLEDGMENTS

This document would not have been a reality had it not been for several individuals

who provided support and guidance.

I express my humble gratitude to Dr. Rick Rudd for his kind and patient guidance

during my education at the University of Florida. His dedication to me as a student,

commitment to excellence and demands for success helped me achieve this and many

other goals. I feel blessed to have been given the opportunity to work with and learn from

such an accomplished and well respected individual. I enjoyed the research process, as

well as the other aspects of my graduate education because of his persistent belief in me.

I also express my sincere thanks to Dr. Glenn Israel for sharing his knowledge in

research and providing guidance as a member of my graduate committee. I thank the

faculty and staff in Agricultural Education and Communication at the University of

Florida for continually challenging me, providing support when needed, and making me

part of an unforgettable academic family.

The graduate students in the Agricultural Education and Communication

Department at the University of Florida are an incredible group of individuals who

combine to create a treasured and dynamic group of friends who I am proud to have

called colleagues. I thank each of them for the special role they played in helping make

graduate school meaningful in many ways.

Special thanks are also due to my wonderful friends Emily Hand, Chris Vitelli,

Marshall and Robyn Baker, Melissa Muegge, Christy Windham, Elio Chiarelli, Paul and









Shari Willis, Doug and Linda Felton, and Barrett Keene. Each of them played an

instrumental role in making Gainesville not a place I attended school, but a place I call

my second home. I love each of them very much.

Thanks go to my dear friends Tracy Nash and Casey Hammond, for loving me

from miles away and never missing a beat when we pick up the phone after it has been

way too long. Also, thanks go to my friend Marty Tatman for much needed

encouragement and understanding as we conquered this process together.

Lastly, I thank God for blessing me with my incredible family, especially my

parents, Janice and Tommy Durham. I thank them for supporting me through every

challenge and every accomplishment. Their willingness to step back and allow me to

explore and grow in this journey has been extremely valuable and much appreciated. I

will always be grateful for their many sacrifices. Thanks go to my sister Amanda for the

love, laughter and growth we've shared. Finally, thanks go to my grandparents, Dr. Pat

Durham and Dr. Marilyn Durham, for their belief in me, their support in many forms, and

for stimulating an interest in the unknown at a very early age.
















TABLE OF CONTENTS



A C K N O W L E D G M E N T S ................................................................................................. iv

LIST OF TABLES .................................................... ix

LIST O F FIG U RE S .............. ......................... ........................... ....................... .. .. .... .x

L IST O F K E Y TER M S ..................................................................................... xi

A B S T R A C T ...................................................................................................................... x ii

CHAPTER

1 IN TR O D U C T IO N ........ .. ......................................... ..........................................1.

A agriculture in the U united States ....................... ...............................................1......
A agriculture in F lorida .......................................... ................................................2...
L leaders in O organizations .............. ...... ............ .................................................. 3
N eed for th e Stu dy ................................................................................................. .. 3
L im stations of the Study ................ .............. ............................................4... .
Su m m ary .................................................................................................... ......... 5

2 REV IEW OF TH E LITER A TU RE ............................................................ ............... 6

Cognitive Function ........ ..................... .. ............. ................ 6
Decision Making, Problem Solving and Creativity ................................................ 8
Decision Making ...................... ............ .............................9
P rob lem S olv in g ............................................................................................ 9
Problem Solving Style ........................................................... 10
K irton adaption-innovation inventory..................................... .................. 11
Problem solving style and dem ographics................................ ................ 12
Problem solving style and gender ........................................... ................ 12
C hoping behavior ............... ................ ............................................. 13
C critical and C relative Thinking ....................................................... ............... 13
O organizational L leadership ......................................... ......................... ............... 14









3 M E T H O D O L O G Y .................................................. ............................................. 19

R research D design ......................................................................................... 19
P opu nation ........................................................................ .... ............. .................. 2 0
Instrum entation ...................................................................................................... 21
D em graphic Instrum ent ..................................................................................22
Interview Questionnaire .........................................22
Kirton Adaption-Innovation Inventory.............................................................22
D ata Collection and A analysis ..................................................................................23
M ethods U sed for Question One......................................................................23
M ethods Used for Question Two .....................................................................24
M ethods Used for Question Three ...................................................................24
Methods Used for Question Four ..................... ...................................25
S u m m a ry .....................................................................................................................2 5

4 R E S U L T S .......................................................................................... ..................... 2 7

Question 1: What Are the Characteristics of Leaders in the Florida Agricultural
Indu stry ? ....... .... ........ .... .. ............ .. ........ ..... ...... ............ 27
Question 2: How Do Florida Agricultural Industry Leaders Solve Problems? ..........27
Solution G enerating Strategies.........................................................................29
N um ber of Solutions G generated ....................... ................................................29
Types of Solutions G generated ..........................................................................29
V iew of the Problem .........................................................................................30
C onform ing to R ules ........................................................................................ 31
Consensus Building ..........................................................................................32
Question 3: What are the Problem Solving Styles of Florida Agricultural Industry
Leaders? ........................ ...... ............ ..... .. ........................33
Question 4: How Do the Problem Solving Styles of Leaders Compare With Their
P problem Solving Practices? ..................... ......................................... ...............33
Sum m ary ......................................................................................... ............. ....... 34

5 SUM M ARY AND DISCUSSION ..........................................................................43

Su m m ary of th e Stu dy ......................................................................................... ....... 4 3
R research Q questions ..........................................................................................43
M methodology ................................................................................................... 43
C onclu sions ....................................................................................... ..................... 44
D discussion and Im plications .............................................................. .. ..... ...............45
Question 1: What Are the Characteristics of Leaders in the Florida
Agricultural Industry? .......................................... .................................... 45
Most of the participating leaders were Caucasian males. ............................45
Most of the participating leaders were over the age of 40. ..........................46
Question 2: How Do Leaders in the Florida Agricultural Industry Solve
P rob lem s? ................................. ............. ...... ................ 4 6
Types of problems most often faced by Florida agricultural industry
leaders include personnel/staff problems and management problems .... 46









Participants most often sought to work with others when generating
solutions for a problem ...................................................... ................ 47
The nature of the problem and situation determined which problem
solving practices leaders utilized .................................... .................. 47
Question 3: What Are the Problem Solving Styles of Florida Agricultural
Indu stry L leaders? .... ................. .. .................................. .. ........... ....... .....48
Leaders in the Florida agriculture industry include both adaptors and
innovators...... ..... ......................... ................. ................... 48
Question 4: How Do Problem Solving Styles of Leaders Compare With Their
Problem Solving Practices? .............. .................. ........ ............... 48
Adaptors and innovators utilized problem solving practices that are both
in their problem solving style and outside their problem solving style..48
The majority of participants who utilized unpredicted problem solving
practices utilized practices that were more adaptive than expected .......49
Participants most often preferred to operate within the rules when
solving problem s .......................................... .... ...... ... ................. 50
Challenging the views of others is an important practice in group
problem solving, but building consensus among the group is an
im portant goal for m any leaders ....................................... ................ 50
Suggestions for A additional R esearch..................................................... ................ 51

APPENDIX

A DEM OGRAPHIC IN STRUM ENT ....................................................... ................ 52

B IN TERV IEW QU E STION A IRE .............................................................. ............... 54

L IST O F R E FE R E N C E S ................................................. ............................................ 55

BIO GR APH ICAL SK ETCH .................................................................... ................ 58















LIST OF TABLES


Table page

2-1 Descriptors for Adaptors and Innovators. .................................................. 17

3-1 Agricultural Commodity Groups Represented....................................................26

4-1 Demographic Profile of Agricultural Industry Leader Participants (N=16) ............35

4-2 Types of Problems Faced by Florida Agricultural Industry Leader Participants.....36

4-3 KAI Sub-Scores and Accompanying Problem Solving Practices.........................36

4-4 Solution G enerating Strategies............................................................ ................ 37

4-5 N um ber of Solutions G enerated.......................................................... ................ 36

4-6 Types of Solutions G generated ............................................................. ................ 36

4-7 V iew of the Problem ........................................................... ................ 36

4-8 C onform ing to R ules .. ...................................................................... ................ 36

4-9 Consensus Building .. .................................................................................... 40

4-10 KAI Scores and Sub-Scores of Agricultural Industry Leaders Participants ............36

4-16 Actual problem solving practices discussed by KAI score (N=16)......................36

4-17 Unpredicted responses by KAI category............................................. ................ 36
















LIST OF FIGURES


Figure


2-1 Kirton's (2003) Cognitive Function Schem a ...................................... ................ 18


page

















Leadership


Agricultural Leader


Decision Making


Problem Solving



Preferred Problem
Solving Style

Problem Solving
Method

Adaptor



Innovator


LIST OF KEY TERMS

The process by which influence is exerted over individuals and
groups in order to achieve goals (Yukl, 2002, Northouse, 2004).

An individual in a managerial leadership position with decision
making capacity.

A process that involves problem identification, solution generation,
evaluation, and implementation (Delbecq & Mills, 1985).

A process of recognizing and representing a problem, devising
and/or choosing a solution plan, followed by execution and
evaluation of the plan (Beyer, 1987).

Where an individual falls on the adaptive-innovative scale of the
Kirton Adaption-Innovation Inventory (KAI) (Kirton, 2003).

The steps and strategies actually used by an individual when
solving problems.

Individuals scoring 96-160 (any score above the theoretical mean
of 96) on the Kirton Adaption-Innovation Inventory (Kirton,
2003).

Individuals scoring 32-95 (any score below the theoretical mean of
96) on the Kirton Adaption-Innovation Inventory (Kirton, 2003).














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

PROBLEM SOLVING STYLES AND METHODS OF FLORIDA AGRICULTURAL
INDUSTRY LEADERS

By

Dyanna Renee Durham

August 2007

Chair: Rick Rudd
Major: Agricultural Education and Communication

The purpose of this study was to identify and describe the problem solving styles

and practices of leaders in the Florida agricultural industry. Sixteen leaders representing

nine major commodity groups participated in qualitative interviews and completed a

problem solving style assessment in order to identify and compare leaders' problem

solving styles and methods.

This study found that the participating leaders most often face personnel, staff and

management problems. These leaders often sought to work with others when solving

problems, and the problem solving practices utilized by the leaders was determined by

the nature of the problem and situation.

Adaptive and innovative leaders were found in Florida's agricultural industry, with

56% of the participants being innovators and 44% being adaptors. All leaders were

found to utilize both problem solving practices and not predicted for their style.














CHAPTER 1
INTRODUCTION

Agriculture in the United States

Agriculture is a vital sector of the United States economy. Agriculturists in the

United States produce food, fiber, ethanol, and bio-diesel. These commodities help feed

and support not only the population and economy of the United States, but of other

countries as well (American Farm Bureau Federation [AFBF], 2004).

Employment in the U.S. agricultural industry has greatly decreased since the early

20th century. In 1935, the number of farms in the United States peaked at 6.8 million and

agricultural careers accounted for nearly 20% of total jobs in the United States. In 2005

the employment percentage stood at less than 2% with only 2.13 million farms (AFBF,

2004; Lachman & Zorska, 1999). Despite the number and percentage of jobs

decreasing, farm output has increased significantly (Lachman & Zorska, 1999). Clearly,

agriculture still significantly impacts the United States.

Farmers in the United States are the most productive in the world; each American

farmer produces enough food and fiber to support 144 people. The efficiency of

agricultural production in the United States greatly contributes to the successful U.S.

economy and elevated standard of living for Americans. Consumers in the United States

spend only 10% of their disposable annual income on food the lowest percentage of

income spent on food world-wide (AFBF, 2004).

The agricultural sector has a large impact on the value of U.S. exports.

Agricultural commodities contribute $10 billion annually to the U.S. trade balance.









These export sales support 900,000 jobs in the United States (United States Department

of Agriculture, 2002).

The agriculture industry faces many complex issues. Water rights, chemical use,

biotechnology, trade, and conservation are examples of challenges farmers and leaders in

the industry must address. These issues have the potential to greatly affect the success of

the agricultural industry.

Agriculture in Florida

The agricultural industry has a large economic impact in the state of Florida it is

Florida's second largest industry after tourism (Park, 2005). Agricultural output sales in

Florida were $35.2 billion in the year 2000, with agricultural sales to markets outside of

Florida at $19.4 billion, employing 338,253 persons with a personal and business net

income of $14.8 billion (Hodges & Mulkey, 2003).

Florida ranks ninth nationally in the value of farm products and is a leader in the

production of many commodities. Specifically, Florida leads the country in citrus

production and ranks second in the production of fresh vegetables. In addition, Florida

farmers rank third nationally in net farm income (Florida Department of Agriculture and

Consumer Sciences, 2002).

The agriculture industry in Florida shares many similar issues with agriculture

throughout the United States. For example, in an effort to preserve Florida's diverse

ecosystems (including the Everglades), water rights and usage is an important issue.

These issues continue to be under scrutiny and debate by the public, stakeholders,

activists, and leaders of the industry.









Leaders in Organizations

Leaders play vital roles in organizations. According to Kouzes and Posner (2002),

successful organizations need good leaders because leaders transform organizations into

valued institutions that survive over time. Northouse (2004) suggests that leaders have

influence over their followers and their organizations. Leaders have the power and

ability to influence organizational culture, processes, performance, and effectiveness

(Yukl, 2002). One way for leaders to exert influence in organizations is through the

power of decision making. Both Mintzberg (1973) and Yukl (2002) found that the role of

making decisions in organizations falls on leaders in managerial roles. The decisions

made by managerial leaders have an effect on the success of their organization (Yukl,

2002).

Need for the Study

Decisions made by leaders in the agricultural industry have bearing on the success

of not only their companies, but on the agricultural industry as a whole. The success of

the agricultural industry has a significant impact on the economy both in Florida and the

United States. Because of the significance of this impact, it is necessary for individuals

who are leading the agricultural industry to be skilled and well trained in decision

making. In order for the United States to thrive, the U.S. economy must prosper, and the

agriculture industry is a large contributor to the national economy. Decisions about the

many issues facing the agricultural industry and business decisions made by leaders in

the industry have great bearing on the success of agriculture. High quality decisions

leading to the sustainability, success and advancement of the agricultural industry and its

contributing enterprises are vital. Therefore, the leaders who influence agriculture in the

United States and Florida should have high quality decision making skills. The decisions









leaders in the agricultural industry make can have a large impact so there is a great need

for excellent decision makers in agricultural leadership positions.

The decisions made by leaders in the Florida agricultural industry have far-reaching

effects. Daily decisions made by these leaders affect the success of their individual

organizations, which affect the success of the state-wide industry. The success of the

state-wide industry affects the economy of Florida and therefore, residents, employees,

and consumers of the state. There is a need to investigate the quality of decision making

skills of leaders in the Florida agricultural industry. Therefore, the research questions for

this study were

1. What are characteristics of leaders in the Florida agricultural industry?

2. How do these leaders solve problems?

3. What is the problem solving style of Florida agricultural industry leaders?

4. How does the problem solving styles of leaders compare with their problem solving
practices?

Limitations of the Study

As with any academic research, limitations exist that limit the generalizability of

this study. Qualitative interviews of agricultural industry leaders in the state of Florida

were conducted. Due to the nature of qualitative interviews and the specificity of the

interviews and interviewees, the findings of the study cannot be generalized beyond this

group of leaders, though they are likely to offer insight to the decision making process of

similar leaders.









Summary

This study identified and described the problem solving styles and practices of

leaders in the Florida agricultural industry. Four research questions were presented and

the significance of the study was discussed. The research questions are

1. What are the characteristics of leaders in the Florida agricultural industry?

2. How do these leaders solve problems?

3. What is the problem solving style of Florida agricultural industry leaders?

4. How does the problem solving styles of leaders compare with their problem solving
practices?














CHAPTER 2
REVIEW OF THE LITERATURE

The primary purpose of this study was to identify and describe the problem solving

styles and practices of leaders in the Florida agricultural industry. Specifically, this study

sought to describe current agricultural industry leaders in terms of their demographics,

determine how agricultural industry leaders solve problems, determine and describe the

problem solving style of agricultural industry leaders, and compare agricultural industry

leaders' problem solving styles with their problem solving practices.

This chapter presents a review of the literature concerned with problem solving and

practices. This review of the literature includes three major sections. Part one is an

examination of the research in the area of cognitive function. Part two discusses the

relationship between decision making, problem solving and critical and creative thinking.

Part three describes organizational leadership and the roles leaders play in organizations.

Cognitive Function

Much research has been conducted regarding thinking and cognition. Dewey

(1910) defined thinking as, "that operation in which present facts suggest other facts (or

truths) in such a way as to induce belief in the latter upon the ground or warrant of the

former." Cognitive psychology refers to all processes by which the sensory input is

transformed, reduced, elaborated, stored, recovered, and used (Neisser, 1967). Reed

(1982) simply defines cognition as the acquisition and use of knowledge. Beyer (1987)

wrote that the goal of cognition is meaning-making, which could include finding a

solution to a problem, understanding a situation, or making a judgment.









Each of the above definitions of cognition focuses on mental operations. However,

thinking includes "thinking tasks" such as problem solving and decision making. The

execution of these tasks requires not only mental operations, but also knowledge, skill,

persistence, time, the disposition to take time, and the willingness and desire to examine

alternatives (Beyer, 1987).

Three elements directly affect cognition: cognitive effect, cognitive affect, and

cognitive resource. Cognitive effect involves the cognitive problem solving process. It is

in this element that the brain determines the behavior that is needed in order to achieve

the goal. Kirton (2003) describes two components of cognitive effect: preferred style and

potential level. Preferred style refers to how the individual goes about solving problems.

Potential level refers to the potential cognitive capacity, which can be measured in IQ

(Kirton, 2003).

Cognitive affect refers to how the brain selects the problem to be solved and

determines the type of solution needed. Through this process, the brain determines

where to begin when solving a problem. Cognitive affect is influenced by motive, which

is determined by the needs, values, attitudes, and beliefs of the thinker (Kirton, 2003).

Cognitive resource is the accumulation and availability of the knowledge, skills,

and experience needed to solve problems. Knowledge, skills, and experience combine to

create cognitive techniques, which refers to how we best us what we have learned.

Techniques are saved by and accessed through memory (Kirton, 2003).

According to Kirton (2003), the external environment also has an impact on the

cognitive process. The environment includes the culture, climate, and opportunities









presented to an individual, and any other aspects of the outside world. The environment

interacts with cognitive process to play a role in behavior (Kirton, 2003).

The schema in Figure 2-1 represents the complex operation of cognitive function as

described by Kirton (2003). It is displayed in a chart-like manner to depict the main units

of operation and illustrate, in a simple manner, how the brain solves problems. Problem

solving style as measured by the Kirton Adaption Inventory is an aspect of cognitive

effect. Coping behavior as evidenced in problem solving practices are a cognitive

resource utilized in cognitive function. Both problem solving style and coping behavior

are further discussed below.

The consequence of cognitive functioning is behavior. Kirton (2003) defines

behavior as the sum of all cognitive operations. However, Kirton argues that behavior is

not the result of cognitive functioning alone; it is the result of many internal and external

variables involved in cognitive effect, cognitive affect, and the environment (Kirton,

2003).

Decision Making, Problem Solving and Creativity

All people engage in problem solving, and all people are creative through the

problem solving process. Problem solving, decision making and creativity are often

considered synonymous. Brain function appears to make no distinction between problem

solving, decision making, and creativity as they involve many of the same steps and

cognitive processes, such as novelty (Kirton, 2003). For the purpose of research, these

processes can be examined as the same, or as separate entities and thinking strategies.

Decision making and problem solving are strategies that involve a sequence of operations

and procedures that the thinker follows in an orderly fashion (Beyer, 1987).









Decision Making

Delbecq and Mills' (1985) definition of decision making includes an individual

proceeding through the following process: problem identification, solution generation,

evaluation, and implementation. According to Beyer (1987), decision making is a

strategy that is made up of a sequence of operations and procedures that the thinker

follows in an orderly fashion. Beyer's (1987) decision making strategy proposes the

following steps

1. Define the goal
2. Identify alternatives
3. Analyze alternatives
4. Rank alternatives
5. Judge highest-ranked alternatives
6. Choose "best" alternatives

The result of decision making is a decided behavior. Many variables contribute to

the arrival of a decision for a particular behavior. These variables include those directly

related to problem solving and creativity, and variables imposing on them such as

environmental factors (Kirton, 2003).

Problem Solving

According to Beyer (1987), problem solving relates to cognition in that problem

solving is a result of thinking. Newell and Simon's (1972) theory of problem solving

suggests that problem solving is influenced by information-processing capabilities of

people as determined by short term memory and long term memory, the structure of the

problem and it's effect on finding a solution, and effectiveness of strategies and sources

of information. Greeno (1978) identified three types of problems: arrangement, inducing

structure, and transformation. Each type is categorized by the skills needed to solve the

problem.









Many problem solving models and processes exist. According to Paul and Elder

(2003), problem solving begins with determining the goal and/or purpose. Next, the

problem solver must seek information, analyze and interpret that information, draw

reasonable inferences, determine options for action, evaluate those options, adopt a

strategy, and monitor the implications of the decided action. This process closely aligns

with the steps of Delbecq and Mills' (1985) definition of decision making, demonstrating

the similarity of problem solving and decision making noted by many researchers.

Other models of decision making include those of Sternberg and Beyer.

Sternberg's (1977) model includes four processes: encoding, inference, mapping, and

application. Like his decision making strategy, Beyer's (1987) problem solving strategy

is made up of a sequence of operations and procedures that the thinker follows in an

orderly fashion

* Recognize a problem
* Represent the problem
* Devise/choose solution plan
* Execute the plan
* Evaluate the solution


Problem Solving Style

Kirton's (2003) Adaption-Innovation (A-I) theory is a model of problem solving

and creativity. According to A-I theory, individuals are limited by pre-set restrictions

when they solve problems. Examples of these restrictions include an individual's

capacity for intelligence (IQ), intelligence flexibility, and preferred problem solving

style. Adaption-Innovation theory assumes that while each of these factors interacts to

impose limitations on a problem solver, they are unrelated in level (Kirton, 2003).









The A-I continuum places people according to their preference to solve problems

with more or less structure. Individuals on the adaptive end of the continuum need more

structure when solving problems. Individuals on the innovative end of the continuum

still need structure to solve problems; however, they need less structure than others. A-I

theory assumes that this style is stable and should not change over the course of an

individual's life (Kirton, 2003).

Kirton adaption-innovation inventory

Problem solving style as related to A-I Theory is measured by The Kirton

Adaption-Innovation Inventory (KAI) was developed and tested by M. J. Kirton (2003).

The inventory measured respondents' style of problem solving and creativity through a

series of 26 statements, asking respondents to answer each item on a scale ranging from 1

(strongly disagree) to 5 (strongly agree). The KAI may only be administered by a KAI

certified practitioner.

KAI has a possible score range of 32 to 160, with the score indicating a place on a

scale. High adaptors have low scores and high innovators have high scores (Kirton,

2003). The total score is derived from the sum of 3 sub-scores which are inter-related but

do not contribute equally to the total score. The three sub-scores are as follows:

Sufficiency of Originality, Efficiency, and Rule/Group Conformity.

Sufficiency of Originality measures how people prefer to generate and handle

original ideas and solutions. The more adaptive usually produce a smaller number of

original ideas that tend to be seen as very relevant, safe and useful. The more innovate

tend to produce a higher number of ideas which may be seen by others as irrelevant,

risky, and unacceptable (Kirton, 2003).









Efficiency measures the difference between styles in problem solving methods and

strategies. The more adaptive tend to tightly define the problem, work within the set

structure, minimize risk, and seek immediate efficiency. The more innovate tend to pay

less attention to detail and structure, taking a wider overview approach and looking

outside the current system (Kirton, 2003).

Rule/Group Conformity measures differences in the preference for and

management of existing structures for problem solving. The more adaptive tend to more

closely conform to the rules and seek consensus and cohesion in group problem solving.

The more innovative tend to have less regard for existing rules and often challenge group

members rather than strive to build consensus (Kirton, 2003). Common descriptors for

adaptors and innovators can be seen in Table 2-1.

Problem solving style and demographics

According to Kirton (2003), most demographic background factors do not have an

impact on problem solving style. Because the style characteristic is deeply rooted in

cognitive function it is not found to be influenced by other factors. A-I theory assumes

that no differences exist in age, class, occupational status, country, or culture (Kirton,

2003). The single demographic characteristic Kirton found to have an impact on problem

solving style was gender.

Problem solving style and gender

The differences in problem solving found between males and females is minimal

with a standard deviation between one quarter and one third. While this difference has

been found to be very consistent among large groups, it is not consistent among smaller

sample groups (Kirton, 2003).









Coping behavior

Although every individual has a preferred problem solving behavior that is a result

of their preferred style, sometimes altered behavior is necessary. Coping behavior refers

to behavior carried out that is not in accordance with an individual's preferred style

(Kirton, 2003). Coping behavior is utilized when insight or foresight indicates that

different behavior is needed for desired results. This behavior is learned and is a

deliberate response to an environment or situation. Operating in coping behavior requires

greater cognitive effort than working within the preferred style (Kirton, 2003).

Critical and Creative Thinking

Critical and creative thinking are both achievements of cognition. The two are

inseparable elements of thought and are considered to be the result of high quality

thinking (Paul & Elder, 2004). Rudd (2002) defines critical thinking as reasoned,

purposeful, and reflective that helps one make decisions, solve problems, and master

concepts. Paul and Elder (2002) present another definition of critical thinking: "the

disciplined art of ensuring that you use the best thinking you are capable of in any set of

circumstances" (7). Criticality implies a process of assessing or judging (Paul & Elder,

2004). A good critical thinker asks the right questions, assesses the right information,

produces good conclusions and solutions, is able to think with an open mind, and can

communicate effectively (Paul & Elder, 2003). Facione (1998) determined six core

critical thinking skills: interpretation, analysis, synthesis, explanation, evaluation, and

self-regulation.

According to Beyer (1987) critical thinking is evaluative in nature, and requires the

thinker analyze persistently while being objective. Critical thinking differs from problem

solving and decision making because critical thinking is not a strategy; it is a collection









of operations that can be used alone or combined. Beyer's (1987) critical thinking skills

include

* Distinguishing between verifiable facts and value claims
* Distinguishing relevant from irrelevant information, claims, and reasons
* Determining factual accuracy of a statement
* Determining the credibility of a source
* Identifying ambiguous claims or arguments
* Identifying unstated assumptions
* Detecting bias
* Identifying logical fallacies
* Recognizing logical inconsistencies in a line of reasoning
* Determining the strength of an argument or claim

According to Paul and Elder (2004), creativity is the mastering of a process of

making or producing. Paul and Elder (2002) write that the very definition of creative

implies a critical component. While creative thinking is related to critical thinking, they

are not the same thing. Creative thinking is divergent, seeks to create something new,

and can violate accepted principles. Critical thinking is convergent, assesses worth or

validity of something already existing, and focuses on applying accepted principles

(Beyer, 1987). Scriven (1976) describes creativity as ideas that are not only original and

novel, but also valid and superior.

According to Kirton (2003), creativity is a subset of problem solving and involves

both adaption and innovation. Therefore, A-I theory states that all individuals solve

problems and are creative. Problem solving style does not determine if an individual is

creative but how an individual is creative. Adaptors and Innovators both have creative

and novel ideas, they simply generate them in different ways (Kirton, 2003).

Organizational Leadership

Early research in organizational leadership focused on managers and supervisors in

organizations. In recent decades, the focus has shifted toward the strategic leadership of









executives and top managers (Cannella & Monroe, 1997). Mintzberg (1973) proposed

ten roles that account for most activities of a manager. The roles are grouped into three

categories: interpersonal, information processing, and decision making.

* Interpersonal Roles
o leader
o liaison
o figurehead
* Information Processing Roles
o monitor
o disseminator
o spokesperson
* Decision Making Roles
o entrepreneur
o disturbance handler
o resource allocator
o negotiator

The work of managers and leaders in organizations is rapidly changing.

Technology (especially computers and telecommunication), the changing structure of

organizations, cultural changes, and outsourcing contribute to this change. These

changes influence the skills leaders need and alter the demands of leaders' jobs (Yukl,

2002).

Leaders have the power and ability to influence organizational culture, processes,

performance, and effectiveness. Leaders accomplish this through filling various roles in

their organizations. One such role is as a problem solver and decision maker (Yukl,

2002). Both Mintzberg (1973) and Yukl (2002) found that the role of making decisions

in organizations falls on leaders in managerial roles.

Barnard (1938) listed several stimuli that brought about decision making at work

* Authoritative communication from superiors
* Cases referred upwards for decision by subordinates
* Originated as the initiative of the executive concerned









This suggests that Barnard viewed decision making as an activity undertaken

mainly by management. He was among those who drew the attention of managers to the

need to analyze decision making as a key element in management.

According to Yukl (2002) managers make different kinds of decisions some large

in magnitude, some more short term and operational. Important decisions usually involve

many other people, as leaders must attain support and authorization. Less important

decisions involving day-to-day operations or short term goals are usually made alone or

after consulting just a few people. Yukl (2002) proposed guidelines for managerial

problem solving

* Identify important problems that can be solved
* Look for connections among problems
* Experiment with innovative solutions
* Take decisive action to deal with crisis

The literature showed that problem solving is an outcome of cognitive function and

creativity is a sub-set of problem solving. There is literature to suggest that problem

solving occurs in a structured and orderly fashion using specific skills and practices.

Problem solving style is deeply rooted in cognitive function and affects the way

individuals approach and solve problems. Literature also suggests that an important role

of leaders in organizations is to make decisions and solve problems.










Table 2-1. Descriptors for Adaptors and Innovators.


Adaptors
Seen by Innovators as:
sound
conforming
safe
predictable
inflexible
wedded to the system
intolerant of ambiguity


Tend to accept problems as defined by
consensus, accepting generally agreed
constraints.

Important considerations:
early resolution of problem
limiting disruption
immediate increased efficiency

Prefer to generate a few novel, creative,
relevant and acceptable solutions aimed at
'doing things better'.

Have confidence in implementing solutions
effectively, despite size and complexity.

Prefer more well-established, structured
situations.

Best at incorporating new data or events in
existing structures or policies, making them
more efficient.

Essential to managing current systems.



Encounter difficulty regrouping established
roles in times of unexpected changes from
unexpected directions.


Innovators
Seen by Adaptors as:
glamorous
exciting
unsound
impractical
risky
abrasive
threatening the established system
causing dissonance

Tend to reject the generally accepted
perception of problems and redefine them.


Their view of the problem may be hard to
get across.



Seem less concerned with immediate
efficiency, look to possible long-term
goals.

Generally produce numerous ideas, some
of which may not appear relevant or be
acceptable to others.
Ideas often contain solutions which result
in 'doing things differently'.

Prefer less lightly structured situations.



Use new data as opportunities to set new
structures or policies, accepting greater risk
to current paradigm.

Essential in times of radical change or
crisis.

May have trouble applying themselves to
managing change within ongoing
organizational structures.












COGNITIVE FUNCTION


Cognitive Effect
Preferred Style (E.G. A-I)
Potential Level (E.G. IQ)


Via Cognitive Process


All the ele
solving &
elements


Cognitive Resource
Knowledge, Know-how
Skills Experience
(E.G. Conitive Technique)

Via Learning & Memory


'A- Cognitive Affect
NTeAl eXdal ac


BEHAVIOR

(Preferred & Coping
Behavior)



PRODUCT

(Idea, Artifact)

ments interrelate in problem
creativity. (The operational
ire not in capitals.)


Attitude, Beliefs


Via Motive


Figure 2-1. Kirton's (2003) Cognitive Function Schema


_


--ENVIRONMENT

Social Effect
(Especially Social
Evaluation)

Scope, Climate, Culture,
Opportunity

Via Group Dynamics














CHAPTER 3
METHODOLOGY

This chapter describes the methods used to answer the research questions presented

in the study. Four specific questions were established to guide the study

1. What are characteristics of leaders in the Florida agricultural industry?

2. How do these leaders solve problems?

3. What is the problem solving style of Florida agricultural industry leaders?

4. How does the problem solving styles of leaders compare with their problem solving
practices?

This chapter specifically explains the research design, target population and

sample, instrumentation, data collection procedures, and procedures that were used to

analyze the data.

Research Design

This study employed basic descriptive research to answer the research questions

and was conducted with the intent to provide base line research that will be of use in

future studies regarding problem solving style. Because of the basic and foundational

nature of this research, a qualitative in-depth interview design was used. Content

analysis of the interview data provided information concerning research question one and

was also be used in answering research question four. An existing instrument, the Kirton

Adaption-Innovation Inventory (KAI), was utilized to answer research questions three

and four. The independent variables for this study were participants' age, gender, highest

degree, leadership/management position, employer, and length of employment in current

position. The KAI score of participants was the dependent variable in the study.









Population

The population of this study consisted of leaders in the Florida agricultural

industry. For the purpose of this study, leaders were defined as individuals in a

managerial leadership position with decision making capacity. A purposive sample of

managerial leaders was utilized for this study.

Leaders targeted for this study were those in managerial leadership positions with

decision making capacity who were responsible for the daily operation of their

organization. A cross section of leaders representing the major commodity groups in

Florida agriculture was utilized. Two organizations were utilized in identifying potential

participants: The Agricultural Institute of Florida and the Wedgeworth Leadership

Institute for Agriculture and Natural Resources.

Twenty companies and organizations are represented by a member on the board of

directors for the Agricultural Institute of Florida, which seeks to offer networking and

support for organizations within the agricultural industry of Florida. Each member

serving on the board of directors was contacted via e-mail and informed of the nature and

purposes of the study. These individuals were asked to refer individuals in their

respective organization or industry who were managerial leaders with decision making

capacity. The leaders referred from each organization or industry were then contacted via

e-mail and informed about the nature and purposes of this study, were asked to confirm

that they were in a managerial leadership position with decision making capacity

responsible for the day-to-day operation of their organization, and asked to participate in

the study if the fit the leadership description.

The Wedgeworth Leadership Institute for Agriculture and Natural Resources is a

leadership program designed to develop leadership qualities in people who are involved









in policy decision making processes within agriculture and natural resources. Selected

past participants of the Wedgeworth Leadership Institute were identified and

recommended to participate in the study by the director of the Institute.

Recommendations were based on past performance and current involvement with the

Institute and University of Florida. Theses recommended prospective participants were

contacted via e-mail and informed about the nature and purposes of this study, were

asked to confirm that they were in a managerial leadership position with decision making

capacity responsible for the day-to-day operation of their organization, and asked to

participate in the study if the fit the leadership description. Based on the responses to

these e-mails, a list of leaders was compiled to serve as the sample for this study.

Of the 45 leaders initially contacted from the population frame of identified

agricultural industry leaders, 22 responded to the request to participate in the study. 16 of

the 22 respondents agreed to participate in the study and four declined to participate. The

16 leaders participating represented nine major agricultural commodity groups in the

state of Florida. The maj or commodity groups and the commodities within them

represented in the study are shown in Table 3-1.

Instrumentation

Three instruments were used in this study. The first, a demographic instrument,

was developed by the researcher. The second instrument was a researcher-designed

interview questionnaire, which was used to collect information from leaders regarding

their specific problem solving practices. The third instrument for this study, the Kirton

Adaption-Innovation Inventory, was used to identify the problem solving style of leaders.

Researcher developed instruments were evaluated by a panel of experts for content and

face validity and were pilot tested prior to data collection.









Demographic Instrument

The instrument used to collect data on the demographic characteristics of

participants was developed by the researcher. The data collected included participants'

age, gender, highest degree, leadership/management position, employer, and length of

employment in current position. This instrument provided a description of demographic

characteristics of leaders in the Florida agricultural industry. The instrument was

evaluated for content and face validity and was pilot tested prior to collecting data.

Interview Questionnaire

When conducting in-depth interviews, the use of a questionnaire is essential (Rubin

& Rubin, 2005). The use of a questionnaire provided structure for the interviews and

ensured the objectives of the interview are met. According to McCracken (1988), the

questionnaire also helped ensure consistency among all participants, provided a direction

and scope for the conversations, and allowed the interview to focus attention on

participant responses.

Questions for the interview were developed based on the review of the literature,

specifically Kirton's Adaption-Innovation Inventory (Kirton, 2003). Questions identified

specific problem solving practices related to each sub-score of the KAI. The

questionnaire was evaluated for content and face validity and was pilot tested prior to

conducting interviews.

Kirton Adaption-Innovation Inventory

The Kirton Adaption-Innovation Inventory (KAI) was developed and tested by M.

J. Kirton (2003). The inventory measured respondents' style of problem solving and

creativity through a series of 26 statements, asking respondents to answer each item on a









scale ranging from 1 (strongly disagree) to 5 (strongly agree). The KAI may only be

administered by a KAI certified practitioner.

KAI has a possible score range of 32 to 160, with the score indicating a place on a

scale. High adaptors have low scores and high innovators have high scores (Kirton,

2003). The total score breaks down into 3 sub-scores which are inter-related but do not

contribute equally to the total score. The three sub-scores are: Sufficiency of Originality,

Efficiency, and Rule/Group Conformity.

Data Collection and Analysis

Prior to the collection of data, a proposal to conduct the study was submitted to the

University of Florida Institutional Review Board for non-medical projects (IRB-02). The

proposal was approved (Protocol #2006-U-0484). A copy of the informed consent form

that was mailed to participants in the study was submitted to the IRB along with the

proposal. The informed consent form described the study, the voluntary nature of

participation, and informed participants of any potential risks and/or benefits associated

with participating in the study.

Once approval to conduct this study was granted by the IRB, data was collected

and analyzed by the researcher. Data was collected during June of 2006. Specific data

collection and analysis procedures that were used are discussed for each research

question.

Methods Used for Question One

In order to answer research question one describing the characteristics of leaders

in the Florida agricultural industry the purposive sample of these leaders provided

demographic information via the researcher-developed instrument. The demographic

instrument was mailed to each participant prior to their interview date, and participants









were asked to complete the instrument prior to the interview. Data collected from the

demographic instrument was analyzed using SPSS statistical package for WindowsTM.

Descriptive statistics such as frequencies and measures of central tendency was used to

describe leaders in terms of their gender, age, highest degree earned,

leadership/management position, and length of employment in current position.

Methods Used for Question Two

To answer research question number two how leaders solve problems this

purposive sample of leaders participated in interviews using the interview questionnaire

developed by the researcher. Interviews were conducted in person, or over the telephone

and lasted 15 to 30 minutes. The interviews were tape-recorded and transcribed in their

entirety following the interview. The transcripts and audio tapes were analyzed using

content analysis to identify problem solving style themes reviewed in the literature.

The themes and practices measured in KAI sub-scores served as a guide for the

coding process, however themes were revised, eliminated or added as necessary. Themes

were analyzed according to specific problem solving practices. Sub strategies, practices

or themes were identified for each group of problem solving practices. Key words and

actions for each strategy, practice and theme were identified. As key words and actions

or closely related words and actions were cited by the subject, content was coded

accordingly.

Methods Used for Question Three

In order to answer research question number three to determine the problem

solving style of Florida agriculture industry leaders the Kirton Adaption-Innovation

Inventory (KAI) was administered to the purposive sample of leaders. The KAI was

mailed along with the demographic instrument prior to the interview date and participants









were asked to complete the inventory prior to the interview. Using SPSS statistical

package for WindowsTM, descriptive statistics such as frequencies and measures of

central tendency were used to describe the leaders in terms of their preferred problem

solving style, as identified by KAI. In addition, a correlation between independent and

dependent variables were analyzed to examine the effect of the independent variables on

the dependent variables on an individual basis.

Methods Used for Question Four

In order to answer research question four comparing the problem solving styles

of leaders with their problem solving practices results of the content analysis of

interviews and KAI scores were compared. Adaption and innovation themes that

emerged form problem solving practices in the content analysis were compared with KAI

score on an individual basis in order to determine if leaders' actual problem solving

practices matched the practices predicted by their KAI score according to A-I theory.

Summary

This study involved descriptive research with a correlation design to describe

Florida agricultural industry leaders and explain the influence of demographics on their

preferred problem solving style, as well as a qualitative in-depth interview design to

determine problem solving practices of these leaders. The population for this study

consisted of individuals in managerial leadership positions with decision making

capacity.

Three instruments were used in this study: a demographic instrument developed by

the researcher, an interview questionnaire developed by the researcher, and the Kirton

Adaption-Innovation Inventory (Kirton, 2003). Data was collected though face-to-face

meetings and telephone interviews.









Data analysis procedures were also discussed in this chapter. In the quantitative

portion of the study, descriptive statistics and correlations were used. Content analysis of

interview tapes and transcripts was used in the qualitative portion.



Table 3-1. Agricultural Commodity Groups Represented
Commodity Group Specific Commodity Represented
Dairy Edible dairy products

Environmental Horticulture Landscape trees and products
Nursery grown products
Fertilizers Agricultural fertilizers- chemical and
organic
Fruit and Nuts Citrus
Oranges
Grapefruit
Fruit Trees
Strawberries
Tomatoes
Fruit Juice
Forestry Timber
Live Animals Beef Cattle
Dairy Cattle
Meat- Edible Beef
Sugars Raw and refined sugar
Vegetables Sweet corn














CHAPTER 4
RESULTS

This chapter presents the findings of the study. Findings are organized by the

research questions of the study identified in Chapter 1.

Question 1: What Are the Characteristics of Leaders in the Florida Agricultural
Industry?

Of the 16 agricultural industry leaders who participated in this study, 68.8% (n=l 1)

were male and 31.2% (n=5) were female. In terms of ethnicity, 100% (n=16) were

Caucasian. The gender of participant by ethnicity is shown in Table 4-1. Age of the

participants ranged form 25 to 65. The mean age of participants was 47.

Tenure within their organizations ranged from .75 years to 34 years and had a mean

of 18.5 years. One participant did not report their tenure within their organization.

Tenure in organizational leadership positions ranged from .66 years to 34 years and had a

mean of 9.2 years.

In terms of the highest degree held by study participants, 6.2% (n=l) had a high

school diploma, 75% (n=12) had a bachelors degree, and 18.8% (n=3) had a masters

degree. The full demographic profile of respondents is shown in Table 4-1.

Question 2: How Do Florida Agricultural Industry Leaders Solve Problems?

Twenty four major problem solving practices emerged from the analysis of the

interview transcripts and audio tapes. During each interview, participants were asked a

series of questions (Appendix B) developed by the researcher based on the review of the

literature. Participants were first asked to describe the types of problems they faced as









leaders in their organization. Four categories of problems most commonly faced by

respondents emerged from the interviews- two being identified as major themes and two

as minor themes. The most frequently discussed problem area was personnel and staff

problems. When asked to identify the types of problems most commonly encountered in

their role one study participant replied, "Basically, my role has primarily evolved into a

people managing business." Another said, "Labor is the number one problem to be

solved today, as in how are we going to source enough labor initially in the season and

manage that labor."

The other major theme identified was management problems. One participant

described making "basic managerial decisions with respect to procurement, contracts, and

also dealing with the best use of the organization's funds and assets." Another

described the management problem of having "too much to do and too little time to do

it." The specific types of problems most common among respondents are identified in

Table 4-2.

The remaining questions asked participants to identify specific practices they used

when solving the problems they discussed. Consistent with the literature, the questions

were divided into three major categories, each reflecting a sub-score of the total KAI

score. The categories were: Sufficiency of Originality, Efficiency, and Rule/Group

Conformity. Each question recognized a specific practice of problem solving based on

one of the three major categories. The specific problem solving practices for each

category are listed in Table 4-3.









Solution Generating Strategies

When asked to describe personal strategies for generating solutions, participants

most often discussed strategies for analyzing available options and working with others to

solve the problem. Discussing analyzing strategies, one participant said, "I try to look at

all possible outcomes ... what are the possible outcomes and how will it affect me?"

Another participant preferred to "determine the course of action you're going to take on

the basis of information."

One participant described that when working with others "a certain synergy that

will occur if a problem is discussed." Another participant discussed the value of working

with others, noting, "I very seldom would work in a vacuum in terms of me coming up

with a solution." From the four strategies identified in the solution generating practices,

28 sub-strategies emerged (Table 4-4).

Number of Solutions Generated

Then number of solutions generated when solving a problem was the most specific

problem solving practice area, with only three general practices identified (Table 4-5).

Most participants referred to a specific number, while some gave more general

responses. One participant preferred said this of generating solutions "I try and develop

as many potential ideas as possible and then narrow the scope down to those that are

actually practical and doable." Participants explained their number preferences, with one

participant explaining, "Too many and it just muddies the water, and not enough and you

get stuck."

Types of Solutions Generated

In terms of types of solutions, participants were asked if they preferred to generated

solutions that focus on refining what exists or creating something new. Many









participants preferred to focus on generating solutions that refine and existing practice or

policy. As one explained, "I don't see it as the best use of time to reinvent the wheel so

to speak." Another participant said, "I think I can build it better than it's already been

built. You show me something, and I think I can improve on it."

Some participants preferred to generate solutions that focused on a new approach.

One participant pointed out the importance of generating new and different solutions. "I

think you want to try to look at ways where you can get beyond the proverbial box, you

want to really expand your thoughts and look at things from a different angle." Another

participant said, "As technology changes, I like to produce ideas that will help us do

something completely different than the way we've been doing it."

Some participants did not identify a preference, but responded that it depended on

the situation. One participant said this about the type of solution needed being dependent

on the situation

I think it depends on the situation. We have to be efficient. We have to be
profitable. If a given situation can be addressed as the way it's always been done
that's one thing but if it has to be changed, it has to be changed. It all depends on
the circumstances. There's no set rules.

The sub-themes that emerged from the types of solutions are shown in Table 4-6.

View of the Problem

In terms of view of the problem, participants were asked if they preferred

approaching problems with a "big picture" view or by attending to the details. While

many participants chose one or the other, others took a different strategy. Some preferred

to examine the big picture and then approach the details, while others said it depended on

the situation or they did both at the same time.









Many participants who chose the "big picture" view explained that details were

unimportant or uninteresting. One participant said, "If you get bogged down in the

details sometimes you lose sight of what the true goal and vision you want to achieve is."

Another participant explained that details were "not as interesting to me as the big picture

... I don't want to get bogged down in the details." Another participant has this to say

about viewing a problem: "I paint walls. I'm inclined to be a large picture person, and

have always needed and appreciated people who attend to the details."

Regarding looking at the big picture first and then details, one participant said, "I

look at the big picture, and how it's going to affect me, and then I go back and look at all

of the little details for what would need to happen." Another said, "start out with the big

picture and then try to break it up into components ... once you see how everything fits

together then you can look at each ... role." Participant preferences and the sub-themes

identified for each of them are listed in Table 4-7.

Conforming to Rules

When asked if they preferred to operate within established rules or break those rules

most participants said they were more comfortable operating within the rules.

Participants who preferred rules often referred to structure and consistency and

consequences. One participant noted the value of rules when saying, "Structure is

important and we need to have consistency and people need to know what the

expectations are." Another participant said, "my thinking is that there's a reason why

that rule or process existed in the first place."

Some participants preferred to break the rules when problem solving. These

participants spoke about "getting out of the box" and feeling restricted by rules. As one

participant put it, "If we keep doing it the same way we'll never advance. The rules hold









you back." Another said, "you can become stifled by the bureaucratic processes, and lose

sight of what you're trying to actually do, and let the process fun the business rather than

the business run the process." The complete list of sub-themes related to conforming to

rules is found in Table 4-8.

Consensus Building

Participants were asked to discuss their preferences for group problem solving in

regard to building consensus and challenging views in the group. This category

contained many overlapping answers. Nearly all participants said they regularly

challenge the views of group members when engaged in group problem solving.

However, most participants said they regularly seek to build consensus during group

problem solving. Many of the participants who discussed building consensus also said

they challenged views.

Of preferring to challenge the views of the group one participant said, "Consensus

certainly doesn't always work and the best ideas don't always come from consensus, so

sometimes you have to break out and confront." Another said, "I like to challenge the

views of the group and I also like to be challenged myself." Another participant noted,

"If you let yourself be convinced that there's only one way to do this ... it can be a

problem ... don't ever accept status quo."

Many participants asserted that the end goal of group problem solving is consensus.

These participants each said that while they both challenge and build consensus

throughout the process, consensus is vital after the decision has been made. As one

participant stated

I like challenging the views, because what that does is causes people to think about
the rationale they've used for it ... But at the end of the day, when we've finally









said ok, this is where we're going, I want consensus. I want everybody to agree
that we can get there doing this. It's about buying in with the program.


Another participant stated, "What you always try and achieve is a consensus and

agreement at the end of the day so you can proceed in an organized way." Practices

related to group problem solving and consensus building and the sub-themes that

emerged from these practices are listed in Table 4-9.

Question 3: What are the Problem Solving Styles of Florida Agricultural Industry
Leaders?

Problem solving styles of participants were determined as outlined in the KAI

scoring key. KAI scores have a possible range of 32 to 160. KAI scores of participants

ranged from 76 to 134. KAI scores are comprised of three sub scores: Sufficiency of

Originality, with a possible range of 13 to 65; Efficiency, with a possible range of seven

to 35; and Rule/Group Conformity, with a possible range of 12 to 60. KAI scores and

sub-scores of participants are reported in Table 4-10.

Nine of the 16 participants (56%) scored above 96 on the KAI, and therefore are

"more innovative". These participants will be referred to as innovators. Seven of the 16

participants (43%) scored 95 or less on the KAI, and therefore are "more adaptive".

These participants will be referred to as adaptors.

Question 4: How Do the Problem Solving Styles of Leaders Compare With Their
Problem Solving Practices?

Participant KAI scores determined a list of predicted practices for problem solving

based on the literature. These predicted practices were compared participants actual

practices as discussed in the interviews. All 16 participants discussed utilizing a mix of

adaptive and innovative practice to some degree. Individual KAI scores and the number









of actual utilized adaptive and innovative problem solving practices discussed by the

respective participant are shown in Table 4-11.

Individuals with scores of 95 and below are considered "more adaptive", and

therefore would be predicted to discuss using more adaptive practices than innovative

practices. Likewise, individuals with scores of 96 and above are considered "more

innovative" and therefore would be predicted to discuss using more innovative practices

than adaptive practices.

Five participants' (31%) responses to interview questions did not match their

predicted responses based on KAI score. Four of the five participants with unpredicted

responses were innovators who utilized more adaptive practices than innovative

practices. One of the five participants with unpredicted responses was an adaptor who

reported utilizing more innovative practices than adaptive practices. Unpredicted

responses by KAI category are shown in Table 4-12.

Summary

This chapter presented the findings of this study. Findings were organized by the

following research questions: (1) what are the characteristics of leaders in the Florida

agricultural industry, (2) How do these leaders solve problems, (3) What is the problem

solving style of Florida agricultural industry leaders, (4) How does the problem solving

style of leaders compare with their problem solving practices?









Table 4-1. Demographic Profile of Agricultural Industry Leader Participants (N=16)
Characteristic Frequency Percent
Gender
Male 11 68.8
Female 5 31.2

Ethnicity
Caucasian 16 100

Age
25-34 3 18.8
35-44 3 18.8
45-54 5 31.2
55-65 5 31.2

Highest Degree Earned
High School Diploma 1 6.2
Bachelors Degree 12 75
Masters Degree 3 18.8
Tenure with Organization
Less than one year 1 6.2
2-5 years 2 12.5
6-10 years 2 12.5
11-15 years 1 6.2
More than 15 years 9 37.5

Tenure in Current Position
Less than one year 2 12.5
2-5 years 5 31.3
6-10 years 4 25
11-15 years 2 12.5
More than 15 years 3 18.7









Table 4-2. Types of Problems Faced by Florida Agricultural Industry Leader Participants
Problem Category Sub-Category
Major Theme: Hiring
Personnel/Staff Problems Turnover
Scheduling
Communication
Personal Issues
Personalities


Major Theme:
Management Problems









Minor Theme:
Organizational Problems










Minor Theme:
Relationship Problems


Logistics
Scheduling/Planning
Budget
Operation/Production
Programmatic development/
instrumentation
Crisis management
Daily issues
Short term strategies

Structure
Vision
Goals
Efficiency
High quality for
Low production cost
Planning
Long term strategy
Growth
Marketing

Among personnel
With outside supporters
With superiors
With industry peers
With political figures


Table 4-3. KAI Sub-Scores and Accompanying Problem Solving Practices.
KAI Sub-Score Accompanying Problem Solving Practice
Sufficiency of Originality Solution generating strategies
Number of solutions generated

Efficiency Types of solutions generated
View of the problem

Rule/Group Conformity Conforming to rules
Consensus Building










Table 4-4. Solution Generating Strategies


Strategy
Major Strategy:
Analyze Options/Solutions


Major Strategy
Teamwork/Communication


Minor Theme:
Assess the Problem


Sub-Strategy
Predict all possible outcomes
Ask "what if?"
Evaluate existing solutions
Research possibilities
Research past efforts
Reflect on personal experiences
Predict long term outcomes
Base action on information
Communicate directly with
those involved
Solicit guidance from outsiders
Seek consensus with those
involved
Request input from leaders
(superiors)
Create a team/collaborate
Consult experts
Seek feedback
Asses situation
Define problem
Examine the facts
Asses support from key figures
Research the problem
Evaluate every facet of the
problem
Evaluate resources
Examine big picture and details


Minor Theme: Formal brainstorming -
Brainstorm on paper
Informal brainstorming -
"in head"
Create lists
List many scenarios
Think "outside the box" of
Known options

Table 4-5. Number of Solutions Generated
Reported Themes
Specific number
3 or less
Five or less
As many as possible
Many at first, then evaluate and narrow down to a few





Table 4-6. Types of Solutions Generated
Type of Solution
Solutions that do things better
(refining)








Solutions that do things differently









Situation dependent


Sub-Themes
Do not reinvent the wheel
Always seek to refine first
Efficiency- solves problems
quickly
Best for short term solutions
Seek to hone the system
Easier than changing
Structure, rules and procedures

Get outside the box
Be open to new things
More challenging and enjoyable
Needed for major issues/long
term problems
Look at situations from
different angels
Seek change

Depends on type of problem
Comfortable with both
First evaluate problem
Depends on desired outcome
Dependent on resources









Table 4-7. View of the Problem.
View
Big Picture











Big Picture, Then Details









Depends on Situation/Both




Details


Sub-Themes
Focusing on details may prevent
reaching a solution
Big picture is equivalent to the goal
Focusing on details can cause losing
sight of vision and goal
Others attend to details
Necessary for management or
executives
Details are not interesting
Set direction and overview

Start with big picture and break it
into components
Allows view of how everything fits
together
Details may or may not be important
depending on the big picture
After examining big picture, must
ensure details work

Must look at both to ensure success
Details ensure accuracy while big
picture shows direction
Depends on the nature of the problem

Details set the stage for assessing the
situation
If the details do not work the problem
has not been solved
Personally detail oriented
Having all the details portrays the bigger
picture









Table 4-8. Conforming to Rules
Practice
Operate within the rules


Break the rules


Table 4-9. Consensus Building
Practice
Challenge Views


Build Consensus


Consensus is End Goal


Sub-Themes
Work within established protocol,
parameters, and policy
Structure and consistency
Adhere to expectations and guidelines
Ethics and honesty
Rules exist for a reason
Consequences
Shouldn't change for the sake of
Changing
Rules are restrictive/ prevent
advancement
Getting "outside the box" is key for
survival
Breaking the rules yields better
solutions
Rules can be re-written


Sub-Themes
Challenge/change the status quo
Get "out of the box"
Play Devil's Advocate
Prevent groupthinkk"
Do not assume
Make others think/be creative
Broaden thinking
Creating buy-in is necessary
Division undercuts the goal
Organizes process
Creates comfort
Builds confidence
Provides clear direction
Leaders must be able to follow group
Challenging is vital during solution
generating process
Consensus is the ultimate goal
After challenges have been made
decision making is collective















Table 4-10. KAI Scores and Sub-Scores of Agricultural Industry Leaders Participants
KAI Total Score Sufficiency of Efficiency Rule/Group
Originality Conformity
76 36 17 23
77 32 15 30
83 47 11 25
86 48 12 26
93 51 12 30
94 40 18 36
95 43 16 36
98 40 14 44
99 49 17 33
101 49 17 35
101 43 19 39
108 55 20 33
115 49 25 41
119 45 29 45
131 62 23 46
134 54 30 50

Table 4-11. Actual problem solving practices discussed by KAI score (N=16)
KAI Score Number of Adaptive Number of Innovative
Practices Discussed Practices Discussed
76 5 2
77 5 2
83 6 4
86 3 4
93 6 1
94 6 1
95 5 2
98 5 3
99 2 5
101 7 1
101 3 4
108 2 5
115 6 1
119 5 3
131 2 5
134 2 7






42



Table 4-12. Unpredicted responses by KAI category
Reported KAI Category Number Deviating from Expected Practices

Adaptor 1

Innovator 4














CHAPTER 5
SUMMARY AND DISCUSSION

This chapter presents a summary of the study as well as a discussion of the

conclusions drawn from the findings, implications of the findings, and recommendations

for future research. The chapter begins with an overview of the study, including the

research questions presented, the methodology utilized, and the findings of the study.

The remainder of the chapter discusses conclusions, implications and recommendations.

Summary of the Study

Research Questions

The primary purpose of this study was to identify and describe the problem solving

styles and practices of leaders in the Florida agricultural industry. Specifically, this study

sought to answer the following questions

1. What are the characteristics of leaders in the Florida agricultural industry?

2. How do these leaders solve problems?

3. What is the problem solving style of Florida agricultural industry leaders?

4. How does the problem solving styles of leaders compare with heir problem solving
practices?

Methodology

This basic descriptive research utilized mixed methods to answer the research

questions. Qualitative in-depth interviews were conducted with leaders in Florida

agricultural organizations who had decision making capacity and were responsible for the

day-today operation of their organization. Sixteen individuals representing nine major

agricultural commodity groups in Florida participated in the study.









Data for this study was collected using two methods. The first utilized two survey

instruments were delivered to participants via mail. Demographics and problem solving

style were measured with these instruments. Data analysis consisted of descriptive and

frequencies.

Data was also collected through face-to-face and telephone interviews which were

audio-taped. The audio tapes were transcribed in their entirety following the interviews

and the transcripts and audio-tapes were analyzed using content analysis. Themes that

emerged from the analysis were used to identify specific problem solving practices

among the participating leaders. These actual problem solving practices were then

compared with measured problem solving style on an individual basis in order to

determine if leaders' actual problem solving practices matched the practices predicted by

their preferred problem solving style.

Conclusions

Because of the qualitative and descriptive nature of this study and the specificity of

the interviews and interviewees, findings, conclusions, implications and

recommendations of this study can be used only to understand this population.

Therefore, the application of this understanding beyond the group of leaders described is

minimal, though they may offer insight to the decision making process of similar leaders.

With awareness of this limitation, the following conclusions were drawn from the

findings of the research questions.

* Most of the participating leaders were Caucasian males.

* Most of the participating leaders were over the age of 40.

* Types of problems most often faced by Florida agricultural industry leaders include
personnel/staff problems and management problems.









* Participants most often analyzed options and solutions and sought to work with
others when generating solutions for a problem.

* The nature of the problem and situation determined which problem solving
practices leaders utilized.

* Leaders in the Florida agriculture industry include both adaptors and innovators.

* Adaptors and innovators utilized problem solving practices that are both in their
problem solving style and outside their problem solving style.

* Most of the participants who used unpredicted problem solving practices used
practices that were more adaptive than expected.

* Participants most often preferred to operate within the rules when solving
problems.

* Challenging the views of others is an important practice in group problem solving,
but building consensus among the group is an important goal for many leaders.

Discussion and Implications

Question 1: What Are the Characteristics of Leaders in the Florida Agricultural
Industry?

Most of the participating leaders were Caucasian males.

In this study, 69% (n=l 1) of participants were male and 31% (n=5) were female.

100% of the participants were Caucasian. Because the participants in this study were a

purposive sample of leaders in Florida agriculture rather than a representative sample the

demographic characteristics of this sample cannot be generalized to the entire population

of agricultural leaders in Florida. Therefore, the conclusion that the majority of

participating leaders were Caucasian males does not necessarily imply that the same

distribution of gender and ethnicity exists in the entire targeted population. It is possible

that women and minorities were underrepresented in the particular groups utilized to

select the sample.









Most of the participating leaders were over the age of 40.

In this study, age of the participants ranged from 25 to 65. The mean age of

participants was 47. Of the 16 participants, 69% were over the age of 40. It must again

be pointed out that because the participants in this study were a purposive sample of

leaders in Florida agriculture rather than a representative sample the demographic

characteristics of this sample cannot be generalized to the entire population of

agricultural leaders in Florida. Therefore, the conclusion that the majority of

participating leaders were over the age of 40 does not necessarily imply that the same

distribution of age exists in the entire targeted population. It is possible that leaders

under the age of 40 were underrepresented in the particular groups utilized to select the

sample.

Question 2: How Do Leaders in the Florida Agricultural Industry Solve Problems?

Types of problems most often faced by Florida agricultural industry leaders include
personnel/staff problems and management problems.

The participants reported two major themes and two minor themes regarding the

types of problems they solve in their positions. Most participants reported regularly

solving problems focused around personnel and staff, such as hiring, turnover and

communication. Many of participants reported solving problems of a management nature

such as logistics, budget, operating and programmatic concerns on a regular basis. These

problems are somewhat consistent with Mintzberg's managerial roles (1973), which

include interpersonal roles, serving as a monitor, disturbance handler and resource

allocator, among others.

These reported problems were expected to emerge, because they are concerned

with the day-to-day issues facing organizations. The population for this study was









leaders who had decision making capacity and were responsible for the day-to-day

operation of their respective organizations. Therefore it is not unusual that the most

common problems faced related to day-to-day issues.

Participants most often sought to work with others when generating solutions for a
problem.

Although the interview questions were designed to focus on personal and

individual problem solving strategies, the majority of participants insisted that problem

solving was rarely a solitary event, and therefore could not be discussed only in terms of

solitary and introspective strategies. These leaders discussed creating a team, seeking

advice, and communicating with others throughout the problem solving process in order

to generate the best solutions possible.

The common use of this practice could simply be a matter of personal preference.

It could perhaps indicate that these particular leaders work in organizations that promote

communication and teamwork when solving problems. Or perhaps it could be a

reflection of the "close-knit" nature of the agricultural industry.

The nature of the problem and situation determined which problem solving
practices leaders utilized.

While some leaders chose one specific problem solving practice for each area of

their problem solving preferences, the majority of leaders said "it depends" or "I do both"

several times. While A-I theory suggests that individuals have a style they prefer to

operate in (Kirton, 2003), many participants insisted they did not prefer one practice or

another on a regular basis, but instead evaluated the situation and chose the most useful

strategy based on the nature of the problem.

Because this was reported by individuals all across the KAI score scale, this is not

readily explained by leaders who's scores are near the theoretical KAI mean. This could









be an indication of learned coping behavior (Kirton, 2003), in which individuals choose

to operate outside of their preferred style because insight or foresight tells them it will be

more advantageous.

Question 3: What Are the Problem Solving Styles of Florida Agricultural Industry
Leaders?

Leaders in the Florida agriculture industry include both adaptors and innovators.

The distribution of adaptors and innovators among the participants was fairly

normal. 56% of the 16 participants were innovators, and 43% were adaptors. This is an

accurate reflection of the distribution for large general populations of adaptors and

innovators, which forms a normal curve (Kirton, 2003). Although the distribution of

adaptors and innovators in this sample cannot be directly generalized to the entire

population of leaders in Florida agriculture, because of it's consistency with the

distribution in large populations it can be assumed that there is a normal distribution of

adaptors and innovators among Florida agricultural industry leaders.

Question 4: How Do Problem Solving Styles of Leaders Compare With Their
Problem Solving Practices?

Adaptors and innovators utilized problem solving practices that are both in their
problem solving style and outside their problem solving style.

All 16 participants reported utilizing problem solving practices that were both

adaptive and innovative. This is consistent with the literature. A-I theory states that

every individual is both adaptive and innovative, but according to where they fall on the

A-I scale they prefer one over the other to some degree. Therefore, it was expected that

participants would engage in both adaptive and innovative practices, regardless of their

KAI score. This conclusion therefore supports the literature.









The majority of participants who utilized unpredicted problem solving practices
utilized practices that were more adaptive than expected.

Five of the 16 participants (31%) reported utilizing an amount of problem solving

practices that were inconsistent with their KAI score. Four of these five were innovators

who reported utilizing practices that were more adaptive than expected.

The literature contains a few possible explanations for all five inconsistencies. It is

possible that these individuals are displaying coping behavior in the way they solve

problems related to their leadership roles. This coping behavior could be a result of

conforming to the nature of the industry (actual or perceived), conforming the culture of

their organization (actual or perceived), or conforming to the constraints of the problems

most often faced (Kirton, 2003). Another possibility is that participants did not respond

to the KAI in a way that reflected their true preferences consistently across time.

The above explanations could also apply specifically to the majority of the

inconsistencies being innovators who utilized an unexpected amount of adaptive

behavior. These individuals may be innovators who work in a very adaptive environment

and used coping behavior to adjust to the demands of their position. This possibility can

be seen in a statement of one participant, who stated, "My preference and my reality are

two different things". In considering the possibility that the participants did not respond

accurately to the KAI it should be considered that the A-I literature states that adaptors

often see innovators as glamorous and exciting (Kirton, 2003). Responses could possibly

be skewed as a result of this, which could explain adaptors receiving a higher score

because they wanted to see themselves as more innovative.









Participants most often preferred to operate within the rules when solving
problems.

Preferring to operate within the rules is a practice preferred by more adaptive

individuals. Only 7 participants were labeled adaptors based on their KAI score,

however 10 participants said they preferred the adaptive practice of operating within the

rules. Participants who preferred to operate within the rules spoke of the need for rules,

structure and ethics, as well as concern for consequences.

This could be explained by the earlier conclusion that adaptors and innovators

utilized problem solving practices that are both in their problem solving style and outside

their problem solving style. A-I theory states that every individual is both adaptive and

innovative, but according to where they fall on the A-I scale they prefer one over the

other to some degree (Kirton, 2003). Therefore, it was expected that participants would

engage in both adaptive and innovative practices, regardless of their KAI score.

Perhaps this was an occurrence of coping behavior. It is possible that this

occurrence was a reflection of the culture of the organizations leaders represented (very

rule or consequence driven, perhaps), or again a reflection of the nature of the agricultural

industry.

Challenging the views of others is an important practice in group problem solving,
but building consensus among the group is an important goal for many leaders.

This problem solving practice is where the most overlap occurred. 14 of the 16

participants said they regularly challenge the views of group members when engaged in

group problem solving. However, nine participants said they regularly seek to build

consensus during group problem solving, with seven of the nine participants who

discussed building consensus also said they challenged views. In addition, eight

participants asserted that the end goal of group problem solving is consensus.









Again, utilizing both strategies could be a learned behavior or a coping behavior.

Participants repeatedly and separately said that each of these practices is what good

leaders do. In this case participants may have been utilizing coping behavior in order to

operate in a way they believe will make them a better leader. It could also again be

explained by the earlier conclusion that adaptors and innovators utilized problem solving

practices that are both in their problem solving style and outside their problem solving

style.

Suggestions for Additional Research

Based on the findings and conclusions of this study, the following suggestions for

additional research were made

* Because this was a qualitative and descriptive study with very specific interviews
and interviewees and only a small purposive sample was included in the study,
additional research needs to be conducted with a larger population that is more
representative of leaders in the Florida agricultural industry.

* Due to the descriptive nature of the study and purposive sample, relationships and
correlations among variables could not be determined. Additional research should
be conducted with a larger population in order to identify relationships among
demographic variable and problem solving style among Florida agricultural
industry leaders.

* This study identified specific problem solving practices utilized by leaders in
Florida agriculture. Future research should be conducted to study the use of these
practices and their relation to problem solving style more in-depth.

* Several of the conclusions drawn from the findings of this study related to the use
of more adaptive problem solving practices than innovative practices despite the
presence of more innovators in the population. One possible explanation is that
this was a reflection of the nature of the agricultural industry. Future research
should be conducted to examine the nature and culture of the agricultural industry
and the constraints it places on problem solvers.














APPENDIX A
DEMOGRAPHIC INSTRUMENT

Please complete the following demographic questions.


* What is your gender? (please check)
o I Male
o I Female

* What is your ethnicity? (please check)
o I American Indian or Alaska Native
o I Asian
o I Black or African American
o 0 Hawaiian or Pacific Islander
o I Hispanic or Latino
o 0 Caucasian
o I Other (please indicate)

* What is your age (in years)?

* Please list the degree, year awarded, major, and granting institution for each of your
degrees

Degree Year Awarded Major Institution






* Please list the name of your organization:

* Please describe your organization- who you serve, your mission, focus, etc.






53


* Please indicate your current position within your organization:



* How long (in years) have you been employed with your organization?


* How long (in years) have you been in your current position within your
organization?














APPENDIX B
INTERVIEW QUESTIONNAIRE

Questions
5. What types of decisions do you make in your leadership role? Give examples.

6. Think about the last time you solved a problem- how did you generate ideas?-

7. How many ideas do you like to generate when solving a problem?

8. Do you like to produce ideas that help you do the same thing better or help you do
something different? Give examples.

9. When solving a problem do you pay more attention to details or do you take a
wider overview approach? How so?

10. When solving problems do you like to stick to the agreed rules or break the rules?
Give examples.

11. In group problem solving, are you more comfortable ensuring group consensus or
challenging the views of the group? Why?














LIST OF REFERENCES

American Farm Bureau Federation. (2004). Farm facts. Washington, DC: American
Farm Bureau Federation.

Barnard, C. (1938). The functions of the executive. Cambridge, MA: Harvard University
Press.

Beyer, B.K. (1987). Practical strategies for the teaching of thinking. Boston: Allyn and
Bacon, Inc.

Cannella, A. A., & Monroe, M. J. (1997). Contrasting perspectives on strategic leaders:
Toward a more realistic view of top managers. Journal of Management, 23 (3),
213-237.

Delbecq, A.L., & Mills, P.K. (1985). Managerial practices that enhance innovation.
Organisational Dynamics, 14, 24-34.

Dewey, J. (1910). How we think. Boston: D.C. Health.

Facione, P. A. (1998). Critical thinking: What it is and why it counts. Millbrae, CA:
California Academic Press.

Florida Department of Agriculture and Consumer Services. (2002). Retrieved October 5,
2005, from http://www.florida-agriculture.com/agfacts.htm

Greeno, J.G. (1978). Natures of problem solving abilities. In W.K. Estes (Ed.).
Handbook of learning and cognitive processes (5th Ed.). Hillsdale: Erlbaum.

Hodges, A.W., & Mulkey, W.D. (2003). Regional economic impacts of Florida's
agricultural and natural resource industries. Economic impact analysis program.
Gainesville: University of Florida Institute of Food & Agricultural Sciences.

Kirton, M.J. (2003). Adaption-Innovation in the context of diversity and change. New
York: Routledge.

Kouzes, J., & Posner, B. (2002). The leadership challenge. San Francisco: Jossey-Bass.

Lachman, M., & Zorska, D. (1999). Economic trends. Cleveland: Federal Reserve Bank
of Cleveland.






56


McCarthy, R. (1993). The relationship of individual characteristics of women managers
to the pressures experienced at work and choice of coping strategy. PhD Thesis,
Unviersity of Hertfordshire.

McCracken, G. (1988). The long interview. Newbury Park, CA: Sage Publications, Inc.

Mintzberg, H. (1973). The nature of managerial work. New York: Harper & Row.

Neisser, U. (1967). Cognitive psychology. New York: Appleton-Century-Crofts.

Newcomb, L.H., & Trefz, M.K. (1987). Levels of cognition of student tests and
assignments in the College of Agriculture at The Ohio State University.
Proceedings of the Central Region 41st Annual Research Conference in
Agricultural Education. Chicago.

Newell, A., & Simon, H.A. (1972). Human problem solving. Englewood Cliffs: Prentice
Hall.

Northouse P.G. (2004). Leadership theory and practice. Thousand Oaks: Sage
Publications, Inc.

Park, K. (2005). World Almanac & Book of Facts. New York: World Almanac
Education Group Inc.

Paul, R. & Elder, L. (2002). Critical thinking: Tools for taking charge of your
professional and personal life. Upper Saddle River: Prentice Hall.

Paul, R., & Elder, L. (2003). The miniature guide to critical thinking concepts and tools.
Dillon Beach, CA: Foundation for Critical Thinking.

Paul, R., & Elder, L. (2004). The thinker's guide to the nature and functions of critical
and creative thinking. Dillon Beach, CA: Foundation for Critical Thinking.

Reed, S.K. (1982). Cognition theory and applications. Monterey: Brooks/Cole Publishing
Company.

Ricketts, J. C., & Rudd, R. D. (2002). A comprehensive leadership education model to
train, teach and develop leadership in youth. Journal of Career and Technical
Education, 19 (1), 7-17.

Rubin, H.J., & Rubin, I.S. (2005). Qualitative interviewing: The art of hearing data.
Thousand Oaks: Sage Publications.

Scriven, M. (1976). Reasoning. New York: McGraw Hill.

Sternberg, R.J. (1977). Component processes in analogical reasoning. Psychological
Review, (84), 353-378.






57


United States Department of Agriculture. (2002). Census of agriculture. Retrieved
October 5, 2005, from http://www.nass.usda.gov/census/

Yukl, G. (2002). Leadership in organizations. Upper Saddle River, NJ: Prentice Hall.















BIOGRAPHICAL SKETCH

Dyanna Renee Durham was born and raised in the small town of Prairie Grove,

Arkansas. After graduating from Prairie Grove High School in 2000, she began her

undergraduate career at the University of Arkansas. She graduated from there with a

Bachelor of Science degree in agricultural & extension education with a concentration in

agricultural education.

In the summer of 2004, Renee moved to Gainesville, Florida to begin the pursuit

her Master of Science degree in the Department of Agricultural Education and

Communication at the University of Florida. In July of 2006 Renee accepted a position

with the National FFA Organization as an education specialist for chapter leadership

programs. She will complete the requirements of her degree in August 2007 and

continue her work with youth leadership programs at FFA.





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PROBLEM SOLVING STYLES AND METH ODS OF FLORIDA AGRICULTURAL INDUSTRY LEADERS By DYANNA RENEE DURHAM 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 UNIVERSITY OF FLORIDA 2007

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2007 Dyanna Renee Durham

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To my parents, Tommy and Janice Durham, a nd my sister, Amanda, for their incredible love and support.

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ACKNOWLEDGMENTS This document would not have been a reality had it not been for several individuals who provided support and guidance. I express my humble gratitude to Dr. Rick Rudd for his kind and patient guidance during my education at the University of Florida. His dedication to me as a student, commitment to excellence and demands for success helped me achieve this and many other goals. I feel blessed to have been given the opportunity to work with and learn from such an accomplished and well respected individual. I enjoyed the research process, as well as the other aspects of my graduate education because of his persistent belief in me. I also express my sincere thanks to Dr. Glenn Israel for sharing his knowledge in research and providing guidance as a member of my graduate committee. I thank the faculty and staff in Agricultural Education and Communication at the University of Florida for continually challenging me, providing support when needed, and making me part of an unforgettable academic family. The graduate students in the Agricultural Education and Communication Department at the University of Florida are an incredible group of individuals who combine to create a treasured and dynamic group of friends who I am proud to have called colleagues. I thank each of them for the special role they played in helping make graduate school meaningful in many ways. Special thanks are also due to my wonderful friends Emily Hand, Chris Vitelli, Marshall and Robyn Baker, Melissa Muegge, Christy Windham, Elio Chiarelli, Paul and iv

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Shari Willis, Doug and Linda Felton, and Barrett Keene. Each of them played an instrumental role in making Gainesville not a place I attended school, but a place I call my second home. I love each of them very much. Thanks go to my dear friends Tracy Nash and Casey Hammond, for loving me from miles away and never missing a beat when we pick up the phone after it has been way too long. Also, thanks go to my friend Marty Tatman for much needed encouragement and understanding as we conquered this process together. Lastly, I thank God for blessing me with my incredible family, especially my parents, Janice and Tommy Durham. I thank them for supporting me through every challenge and every accomplishment. Their willingness to step back and allow me to explore and grow in this journey has been extremely valuable and much appreciated. I will always be grateful for their many sacrifices. Thanks go to my sister Amanda for the love, laughter and growth weve shared. Finally, thanks go to my grandparents, Dr. Pat Durham and Dr. Marilyn Durham, for their belief in me, their support in many forms, and for stimulating an interest in the unknown at a very early age. v

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TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................iv LIST OF TABLES .............................................................................................................ix LIST OF FIGURES .............................................................................................................x LIST OF KEY TERMS .....................................................................................................xi ABSTRACT ......................................................................................................................xii CHAPTER 1 INTRODUCTION........................................................................................................1 Agriculture in the United States...................................................................................1 Agriculture in Florida...................................................................................................2 Leaders in Organizations..............................................................................................3 Need for the Study........................................................................................................3 Limitations of the Study...............................................................................................4 Summary.......................................................................................................................5 2 REVIEW OF THE LITERATURE..............................................................................6 Cognitive Function.......................................................................................................6 Decision Making, Problem Solving and Creativity......................................................8 Decision Making...................................................................................................9 Problem Solving....................................................................................................9 Problem Solving Style.........................................................................................10 Kirton adaption-innovation inventory..........................................................11 Problem solving style and demographics.....................................................12 Problem solving style and gender................................................................12 Coping behavior...........................................................................................13 Critical and Creative Thinking............................................................................13 Organizational Leadership..........................................................................................14 vi

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3 METHODOLOGY.....................................................................................................19 Research Design.........................................................................................................19 Population...................................................................................................................20 Instrumentation...........................................................................................................21 Demographic Instrument.....................................................................................22 Interview Questionnaire......................................................................................22 Kirton Adaption-Innovation Inventory................................................................22 Data Collection and Analysis.....................................................................................23 Methods Used for Question One.........................................................................23 Methods Used for Question Two........................................................................24 Methods Used for Question Three......................................................................24 Methods Used for Question Four........................................................................25 Summary.....................................................................................................................25 4 RESULTS...................................................................................................................27 Question 1: What Are the Characteristics of Leaders in the Florida Agricultural Industry?................................................................................................................27 Question 2: How Do Florida Agricultural Industry Leaders Solve Problems?..........27 Solution Generating Strategies............................................................................29 Number of Solutions Generated..........................................................................29 Types of Solutions Generated.............................................................................29 View of the Problem............................................................................................30 Conforming to Rules...........................................................................................31 Consensus Building.............................................................................................32 Question 3: What are the Problem Solving Styles of Florida Agricultural Industry Leaders?.................................................................................................................33 Question 4: How Do the Problem Solving Styles of Leaders Compare With Their Problem Solving Practices?...................................................................................33 Summary.....................................................................................................................34 5 SUMMARY AND DISCUSSION.............................................................................43 Summary of the Study................................................................................................43 Research Questions.............................................................................................43 Methodology........................................................................................................43 Conclusions.................................................................................................................44 Discussion and Implications.......................................................................................45 Question 1: What Are the Characteristics of Leaders in the Florida Agricultural Industry?......................................................................................45 Most of the participating leaders were Caucasian males.............................45 Most of the participating leaders were over the age of 40...........................46 Question 2: How Do Leaders in the Florida Agricultural Industry Solve Problems?.........................................................................................................46 Types of problems most often faced by Florida agricultural industry leaders include personnel/staff problems and management problems....46 vii

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Participants most often sought to work with others when generating solutions for a problem...........................................................................47 The nature of the problem and situation determined which problem solving practices leaders utilized............................................................47 Question 3: What Are the Problem Solving Styles of Florida Agricultural Industry Leaders?.............................................................................................48 Leaders in the Florida agriculture industry include both adaptors and innovators................................................................................................48 Question 4: How Do Problem Solving Styles of Leaders Compare With Their Problem Solving Practices?.............................................................................48 Adaptors and innovators utilized problem solving practices that are both in their problem solving style and outside their problem solving style..48 The majority of participants who utilized unpredicted problem solving practices utilized practices that were more adaptive than expected.......49 Participants most often preferred to operate within the rules when solving problems.....................................................................................50 Challenging the views of others is an important practice in group problem solving, but building consensus among the group is an important goal for many leaders.............................................................50 Suggestions for Additional Research..........................................................................51 APPENDIX A DEMOGRAPHIC INSTRUMENT............................................................................52 B INTERVIEW QUESTIONAIRE................................................................................54 LIST OF REFERENCES...................................................................................................55 BIOGRAPHICAL SKETCH.............................................................................................58 viii

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LIST OF TABLES Table page 2-1 Descriptors for Adaptors and Innovators.................................................................17 3-1 Agricultural Commodity Groups Represented.........................................................26 4-1 Demographic Profile of Agricultural Industry Leader Participants (N=16)............35 4-2 Types of Problems Faced by Florida Agricultural Industry Leader Participants.....36 4-3 KAI Sub-Scores and Accompanying Problem Solving Practices............................36 4-4 Solution Generating Strategies.................................................................................37 4-5 Number of Solutions Generated...............................................................................36 4-6 Types of Solutions Generated..................................................................................36 4-7 View of the Problem................................................................................................36 4-8 Conforming to Rules................................................................................................36 4-9 Consensus Building..................................................................................................40 4-10 KAI Scores and Sub-Scores of Agricultural Industry Leaders Participants............36 4-16 Actual problem solving practices discussed by KAI score (N=16).........................36 4-17 Unpredicted responses by KAI category..................................................................36 ix

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LIST OF FIGURES Figure page 2-1 Kirtons (2003) Cognitive Function Schema...........................................................18 x

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LIST OF KEY TERMS Leadership The process by which influence is exerted over individuals and groups in order to achieve goals (Yukl, 2002, Northouse, 2004). Agricultural Leader An individual in a managerial leadership position with decision making capacity. Decision Making A process that involves problem identification, solution generation, evaluation, and implementation (Delbecq & Mills, 1985). Problem Solving A process of recognizing and representing a problem, devising and/or choosing a solution plan, followed by execution and evaluation of the plan (Beyer, 1987). Preferred Problem Where an individual falls on the adaptive-innovative scale of the Solving Style Kirton Adaption-Innovation Inventory (KAI) (Kirton, 2003). Problem Solving The steps and strategies actually used by an individual when Method solving problems. Adaptor Individuals scoring 96-160 (any score above the theoretical mean of 96) on the Kirton Adaption-Innovation Inventory (Kirton, 2003). Innovator Individuals scoring 32-95 (any score below the theoretical mean of 96) on the Kirton Adaption-Innovation Inventory (Kirton, 2003). xi

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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 PROBLEM SOLVING STYLES AND METHODS OF FLORIDA AGRICULTURAL INDUSTRY LEADERS By Dyanna Renee Durham August 2007 Chair: Rick Rudd Major: Agricultural Education and Communication The purpose of this study was to identify and describe the problem solving styles and practices of leaders in the Florida agricultural industry. Sixteen leaders representing nine major commodity groups participated in qualitative interviews and completed a problem solving style assessment in order to identify and compare leaders problem solving styles and methods. This study found that the participating leaders most often face personnel, staff and management problems. These leaders often sought to work with others when solving problems, and the problem solving practices utilized by the leaders was determined by the nature of the problem and situation. Adaptive and innovative leaders were found in Floridas agricultural industry, with 56% of the participants being innovators and 44% being adaptors. All leaders were found to utilize both problem solving practices and not predicted for their style. xii

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CHAPTER 1 INTRODUCTION Agriculture in the United States Agriculture is a vital sector of the United States economy. Agriculturists in the United States produce food, fiber, ethanol, and bio-diesel. These commodities help feed and support not only the population and economy of the United States, but of other countries as well (American Farm Bureau Federation [AFBF], 2004). Employment in the U.S. agricultural industry has greatly decreased since the early 20 th century. In 1935, the number of farms in the United States peaked at 6.8 million and agricultural careers accounted for nearly 20% of total jobs in the United States. In 2005 the employment percentage stood at less than 2% with only 2.13 million farms (AFBF, 2004; Lachman & Zorska, 1999). Despite the number and percentage of jobs decreasing, farm output has increased significantly (Lachman & Zorska, 1999). Clearly, agriculture still significantly impacts the United States. Farmers in the United States are the most productive in the world; each American farmer produces enough food and fiber to support 144 people. The efficiency of agricultural production in the United States greatly contributes to the successful U.S. economy and elevated standard of living for Americans. Consumers in the United States spend only 10% of their disposable annual income on food the lowest percentage of income spent on food world-wide (AFBF, 2004). The agricultural sector has a large impact on the value of U.S. exports. Agricultural commodities contribute $10 billion annually to the U.S. trade balance. 1

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2 These export sales support 900,000 jobs in the United States (United States Department of Agriculture, 2002). The agriculture industry faces many complex issues. Water rights, chemical use, biotechnology, trade, and conservation are examples of challenges farmers and leaders in the industry must address. These issues have the potential to greatly affect the success of the agricultural industry. Agriculture in Florida The agricultural industry has a large economic impact in the state of Florida it is Floridas second largest industry after tourism (Park, 2005). Agricultural output sales in Florida were $35.2 billion in the year 2000, with agricultural sales to markets outside of Florida at $19.4 billion, employing 338,253 persons with a personal and business net income of $14.8 billion (Hodges & Mulkey, 2003). Florida ranks ninth nationally in the value of farm products and is a leader in the production of many commodities. Specifically, Florida leads the country in citrus production and ranks second in the production of fresh vegetables. In addition, Florida farmers rank third nationally in net farm income (Florida Department of Agriculture and Consumer Sciences, 2002). The agriculture industry in Florida shares many similar issues with agriculture throughout the United States. For example, in an effort to preserve Floridas diverse ecosystems (including the Everglades), water rights and usage is an important issue. These issues continue to be under scrutiny and debate by the public, stakeholders, activists, and leaders of the industry.

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3 Leaders in Organizations Leaders play vital roles in organizations. According to Kouzes and Posner (2002), successful organizations need good leaders because leaders transform organizations into valued institutions that survive over time. Northouse (2004) suggests that leaders have influence over their followers and their organizations. Leaders have the power and ability to influence organizational culture, processes, performance, and effectiveness (Yukl, 2002). One way for leaders to exert influence in organizations is through the power of decision making. Both Mintzberg (1973) and Yukl (2002) found that the role of making decisions in organizations falls on leaders in managerial roles. The decisions made by managerial leaders have an effect on the success of their organization (Yukl, 2002). Need for the Study Decisions made by leaders in the agricultural industry have bearing on the success of not only their companies, but on the agricultural industry as a whole. The success of the agricultural industry has a significant impact on the economy both in Florida and the United States. Because of the significance of this impact, it is necessary for individuals who are leading the agricultural industry to be skilled and well trained in decision making. In order for the United States to thrive, the U.S. economy must prosper, and the agriculture industry is a large contributor to the national economy. Decisions about the many issues facing the agricultural industry and business decisions made by leaders in the industry have great bearing on the success of agriculture. High quality decisions leading to the sustainability, success and advancement of the agricultural industry and its contributing enterprises are vital. Therefore, the leaders who influence agriculture in the United States and Florida should have high quality decision making skills. The decisions

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4 leaders in the agricultural industry make can have a large impact so there is a great need for excellent decision makers in agricultural leadership positions. The decisions made by leaders in the Florida agricultural industry have far-reaching effects. Daily decisions made by these leaders affect the success of their individual organizations, which affect the success of the state-wide industry. The success of the state-wide industry affects the economy of Florida and therefore, residents, employees, and consumers of the state. There is a need to investigate the quality of decision making skills of leaders in the Florida agricultural industry. Therefore, the research questions for this study were 1. What are characteristics of leaders in the Florida agricultural industry? 2. How do these leaders solve problems? 3. What is the problem solving style of Florida agricultural industry leaders? 4. How does the problem solving styles of leaders compare with their problem solving practices? Limitations of the Study As with any academic research, limitations exist that limit the generalizability of this study. Qualitative interviews of agricultural industry leaders in the state of Florida were conducted. Due to the nature of qualitative interviews and the specificity of the interviews and interviewees, the findings of the study cannot be generalized beyond this group of leaders, though they are likely to offer insight to the decision making process of similar leaders.

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5 Summary This study identified and described the problem solving styles and practices of leaders in the Florida agricultural industry. Four research questions were presented and the significance of the study was discussed. The research questions are 1. What are the characteristics of leaders in the Florida agricultural industry? 2. How do these leaders solve problems? 3. What is the problem solving style of Florida agricultural industry leaders? 4. How does the problem solving styles of leaders compare with their problem solving practices?

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CHAPTER 2 REVIEW OF THE LITERATURE The primary purpose of this study was to identify and describe the problem solving styles and practices of leaders in the Florida agricultural industry. Specifically, this study sought to describe current agricultural industry leaders in terms of their demographics, determine how agricultural industry leaders solve problems, determine and describe the problem solving style of agricultural industry leaders, and compare agricultural industry leaders problem solving styles with their problem solving practices. This chapter presents a review of the literature concerned with problem solving and practices. This review of the literature includes three major sections. Part one is an examination of the research in the area of cognitive function. Part two discusses the relationship between decision making, problem solving and critical and creative thinking. Part three describes organizational leadership and the roles leaders play in organizations. Cognitive Function Much research has been conducted regarding thinking and cognition. Dewey (1910) defined thinking as, that operation in which present facts suggest other facts (or truths) in such a way as to induce belief in the latter upon the ground or warrant of the former. Cognitive psychology refers to all processes by which the sensory input is transformed, reduced, elaborated, stored, recovered, and used (Neisser, 1967). Reed (1982) simply defines cognition as the acquisition and use of knowledge. Beyer (1987) wrote that the goal of cognition is meaning-making, which could include finding a solution to a problem, understanding a situation, or making a judgment. 6

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7 Each of the above definitions of cognition focuses on mental operations. However, thinking includes thinking tasks such as problem solving and decision making. The execution of these tasks requires not only mental operations, but also knowledge, skill, persistence, time, the disposition to take time, and the willingness and desire to examine alternatives (Beyer, 1987). Three elements directly affect cognition: cognitive effect, cognitive affect, and cognitive resource. Cognitive effect involves the cognitive problem solving process. It is in this element that the brain determines the behavior that is needed in order to achieve the goal. Kirton (2003) describes two components of cognitive effect: preferred style and potential level. Preferred style refers to how the individual goes about solving problems. Potential level refers to the potential cognitive capacity, which can be measured in IQ (Kirton, 2003). Cognitive affect refers to how the brain selects the problem to be solved and determines the type of solution needed. Through this process, the brain determines where to begin when solving a problem. Cognitive affect is influenced by motive, which is determined by the needs, values, attitudes, and beliefs of the thinker (Kirton, 2003). Cognitive resource is the accumulation and availability of the knowledge, skills, and experience needed to solve problems. Knowledge, skills, and experience combine to create cognitive techniques, which refers to how we best us what we have learned. Techniques are saved by and accessed through memory (Kirton, 2003). According to Kirton (2003), the external environment also has an impact on the cognitive process. The environment includes the culture, climate, and opportunities

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8 presented to an individual, and any other aspects of the outside world. The environment interacts with cognitive process to play a role in behavior (Kirton, 2003). The schema in Figure 2-1 represents the complex operation of cognitive function as described by Kirton (2003). It is displayed in a chart-like manner to depict the main units of operation and illustrate, in a simple manner, how the brain solves problems. Problem solving style as measured by the Kirton Adaption Inventory is an aspect of cognitive effect. Coping behavior as evidenced in problem solving practices are a cognitive resource utilized in cognitive function. Both problem solving style and coping behavior are further discussed below. The consequence of cognitive functioning is behavior. Kirton (2003) defines behavior as the sum of all cognitive operations. However, Kirton argues that behavior is not the result of cognitive functioning alone; it is the result of many internal and external variables involved in cognitive effect, cognitive affect, and the environment (Kirton, 2003). Decision Making, Problem Solving and Creativity All people engage in problem solving, and all people are creative through the problem solving process. Problem solving, decision making and creativity are often considered synonymous. Brain function appears to make no distinction between problem solving, decision making, and creativity as they involve many of the same steps and cognitive processes, such as novelty (Kirton, 2003). For the purpose of research, these processes can be examined as the same, or as separate entities and thinking strategies. Decision making and problem solving are strategies that involve a sequence of operations and procedures that the thinker follows in an orderly fashion (Beyer, 1987).

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9 Decision Making Delbecq and Mills (1985) definition of decision making includes an individual proceeding through the following process: problem identification, solution generation, evaluation, and implementation. According to Beyer (1987), decision making is a strategy that is made up of a sequence of operations and procedures that the thinker follows in an orderly fashion. Beyers (1987) decision making strategy proposes the following steps 1. Define the goal 2. Identify alternatives 3. Analyze alternatives 4. Rank alternatives 5. Judge highest-ranked alternatives 6. Choose best alternatives The result of decision making is a decided behavior. Many variables contribute to the arrival of a decision for a particular behavior. These variables include those directly related to problem solving and creativity, and variables imposing on them such as environmental factors (Kirton, 2003). Problem Solving According to Beyer (1987), problem solving relates to cognition in that problem solving is a result of thinking. Newell and Simons (1972) theory of problem solving suggests that problem solving is influenced by information-processing capabilities of people as determined by short term memory and long term memory, the structure of the problem and its effect on finding a solution, and effectiveness of strategies and sources of information. Greeno (1978) identified three types of problems: arrangement, inducing structure, and transformation. Each type is categorized by the skills needed to solve the problem.

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10 Many problem solving models and processes exist. According to Paul and Elder (2003), problem solving begins with determining the goal and/or purpose. Next, the problem solver must seek information, analyze and interpret that information, draw reasonable inferences, determine options for action, evaluate those options, adopt a strategy, and monitor the implications of the decided action. This process closely aligns with the steps of Delbecq and Mills (1985) definition of decision making, demonstrating the similarity of problem solving and decision making noted by many researchers. Other models of decision making include those of Sternberg and Beyer. Sternbergs (1977) model includes four processes: encoding, inference, mapping, and application. Like his decision making strategy, Beyers (1987) problem solving strategy is made up of a sequence of operations and procedures that the thinker follows in an orderly fashion Recognize a problem Represent the problem Devise/choose solution plan Execute the plan Evaluate the solution Problem Solving Style Kirtons (2003) Adaption-Innovation (A-I) theory is a model of problem solving and creativity. According to A-I theory, individuals are limited by pre-set restrictions when they solve problems. Examples of these restrictions include an individuals capacity for intelligence (IQ), intelligence flexibility, and preferred problem solving style. Adaption-Innovation theory assumes that while each of these factors interacts to impose limitations on a problem solver, they are unrelated in level (Kirton, 2003).

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11 The A-I continuum places people according to their preference to solve problems with more or less structure. Individuals on the adaptive end of the continuum need more structure when solving problems. Individuals on the innovative end of the continuum still need structure to solve problems; however, they need less structure than others. A-I theory assumes that this style is stable and should not change over the course of an individuals life (Kirton, 2003). Kirton adaption-innovation inventory Problem solving style as related to A-I Theory is measured by The Kirton Adaption-Innovation Inventory (KAI) was developed and tested by M. J. Kirton (2003). The inventory measured respondents style of problem solving and creativity through a series of 26 statements, asking respondents to answer each item on a scale ranging from 1 (strongly disagree) to 5 (strongly agree). The KAI may only be administered by a KAI certified practitioner. KAI has a possible score range of 32 to 160, with the score indicating a place on a scale. High adaptors have low scores and high innovators have high scores (Kirton, 2003). The total score is derived from the sum of 3 sub-scores which are inter-related but do not contribute equally to the total score. The three sub-scores are as follows: Sufficiency of Originality, Efficiency, and Rule/Group Conformity. Sufficiency of Originality measures how people prefer to generate and handle original ideas and solutions. The more adaptive usually produce a smaller number of original ideas that tend to be seen as very relevant, safe and useful. The more innovate tend to produce a higher number of ideas which may be seen by others as irrelevant, risky, and unacceptable (Kirton, 2003).

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12 Efficiency measures the difference between styles in problem solving methods and strategies. The more adaptive tend to tightly define the problem, work within the set structure, minimize risk, and seek immediate efficiency. The more innovate tend to pay less attention to detail and structure, taking a wider overview approach and looking outside the current system (Kirton, 2003). Rule/Group Conformity measures differences in the preference for and management of existing structures for problem solving. The more adaptive tend to more closely conform to the rules and seek consensus and cohesion in group problem solving. The more innovative tend to have less regard for existing rules and often challenge group members rather than strive to build consensus (Kirton, 2003). Common descriptors for adaptors and innovators can be seen in Table 2-1. Problem solving style and demographics According to Kirton (2003), most demographic background factors do not have an impact on problem solving style. Because the style characteristic is deeply rooted in cognitive function it is not found to be influenced by other factors. A-I theory assumes that no differences exist in age, class, occupational status, country, or culture (Kirton, 2003). The single demographic characteristic Kirton found to have an impact on problem solving style was gender. Problem solving style and gender The differences in problem solving found between males and females is minimal with a standard deviation between one quarter and one third. While this difference has been found to be very consistent among large groups, it is not consistent among smaller sample groups (Kirton, 2003).

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13 Coping behavior Although every individual has a preferred problem solving behavior that is a result of their preferred style, sometimes altered behavior is necessary. Coping behavior refers to behavior carried out that is not in accordance with an individuals preferred style (Kirton, 2003). Coping behavior is utilized when insight or foresight indicates that different behavior is needed for desired results. This behavior is learned and is a deliberate response to an environment or situation. Operating in coping behavior requires greater cognitive effort than working within the preferred style (Kirton, 2003). Critical and Creative Thinking Critical and creative thinking are both achievements of cognition. The two are inseparable elements of thought and are considered to be the result of high quality thinking (Paul & Elder, 2004). Rudd (2002) defines critical thinking as reasoned, purposeful, and reflective that helps one make decisions, solve problems, and master concepts. Paul and Elder (2002) present another definition of critical thinking: the disciplined art of ensuring that you use the best thinking you are capable of in any set of circumstances (7). Criticality implies a process of assessing or judging (Paul & Elder, 2004). A good critical thinker asks the right questions, assesses the right information, produces good conclusions and solutions, is able to think with an open mind, and can communicate effectively (Paul & Elder, 2003). Facione (1998) determined six core critical thinking skills: interpretation, analysis, synthesis, explanation, evaluation, and self-regulation. According to Beyer (1987) critical thinking is evaluative in nature, and requires the thinker analyze persistently while being objective. Critical thinking differs from problem solving and decision making because critical thinking is not a strategy; it is a collection

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14 of operations that can be used alone or combined. Beyers (1987 ) critical thinking skills include Distinguishing between verifiable facts and value claims Distinguishing relevant from irrelevant information, claims, and reasons Determining factual accuracy of a statement Determining the credibility of a source Identifying ambiguous claims or arguments Identifying unstated assumptions Detecting bias Identifying logical fallacies Recognizing logical inconsistencies in a line of reasoning Determining the strength of an argument or claim According to Paul and Elder (2004), creativity is the mastering of a process of making or producing. Paul and Elder (2002) write that the very definition of creative implies a critical component. While creative thinking is related to critical thinking, they are not the same thing. Creative thinking is divergent, seeks to create something new, and can violate accepted principles. Critical thinking is convergent, assesses worth or validity of something already existing, and focuses on applying accepted principles (Beyer, 1987). Scriven (1976) describes creativity as ideas that are not only original and novel, but also valid and superior. According to Kirton (2003), creativity is a subset of problem solving and involves both adaption and innovation. Therefore, A-I theory states that all individuals solve problems and are creative. Problem solving style does not determine if an individual is creative but how an individual is creative. Adaptors and Innovators both have creative and novel ideas, they simply generate them in different ways (Kirton, 2003). Organizational Leadership Early research in organizational leadership focused on managers and supervisors in organizations. In recent decades, the focus has shifted toward the strategic leadership of

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15 executives and top managers (Cannella & Monroe, 1997). Mintzberg (1973) proposed ten roles that account for most activities of a manager. The roles are grouped into three categories: interpersonal, information processing, and decision making. Interpersonal Roles o leader o liaison o figurehead Information Processing Roles o monitor o disseminator o spokesperson Decision Making Roles o entrepreneur o disturbance handler o resource allocator o negotiator The work of managers and leaders in organizations is rapidly changing. Technology (especially computers and telecommunication), the changing structure of organizations, cultural changes, and outsourcing contribute to this change. These changes influence the skills leaders need and alter the demands of leaders jobs (Yukl, 2002). Leaders have the power and ability to influence organizational culture, processes, performance, and effectiveness. Leaders accomplish this through filling various roles in their organizations. One such role is as a problem solver and decision maker (Yukl, 2002). Both Mintzberg (1973) and Yukl (2002) found that the role of making decisions in organizations falls on leaders in managerial roles. Barnard (1938) listed several stimuli that brought about decision making at work Authoritative communication from superiors Cases referred upwards for decision by subordinates Originated as the initiative of the executive concerned

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16 This suggests that Barnard viewed decision making as an activity undertaken mainly by management. He was among those who drew the attention of managers to the need to analyze decision making as a key element in management. According to Yukl (2002) managers make different kinds of decisions some large in magnitude, some more short term and operational. Important decisions usually involve many other people, as leaders must attain support and authorization. Less important decisions involving day-to-day operations or short term goals are usually made alone or after consulting just a few people. Yukl (2002) proposed guidelines for managerial problem solving Identify important problems that can be solved Look for connections among problems Experiment with innovative solutions Take decisive action to deal with crisis The literature showed that problem solving is an outcome of cognitive function and creativity is a sub-set of problem solving. There is literature to suggest that problem solving occurs in a structured and orderly fashion using specific skills and practices. Problem solving style is deeply rooted in cognitive function and affects the way individuals approach and solve problems. Literature also suggests that an important role of leaders in organizations is to make decisions and solve problems.

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17 Table 2-1. Descriptors for Adaptors and Innovators. Adaptors Innovators Seen by Innovators as: sound conforming safe predictable inflexible wedded to the system intolerant of ambiguity Seen by Adaptors as: glamorous exciting unsound impractical risky abrasive threatening the established system causing dissonance Tend to accept problems as defined by consensus, accepting generally agreed constraints. Tend to reject the generally accepted perception of problems and redefine them. Important considerations: early resolution of problem limiting disruption immediate increased efficiency Their view of the problem may be hard to get across. Prefer to generate a few novel, creative, relevant and acceptable solutions aimed at doing things better. Seem less concerned with immediate efficiency, look to possible long-term goals. Have confidence in implementing solutions effectively, despite size and complexity. Generally produce numerous ideas, some of which may not appear relevant or be acceptable to others. Prefer more well-established, structured situations. Ideas often contain solutions which result in doing things differently. Best at incorporating new data or events in existing structures or policies, making them more efficient. Prefer less lightly structured situations. Essential to managing current systems. Use new data as opportunities to set new structures or policies, accepting greater risk to current paradigm. Encounter difficulty regrouping established roles in times of unexpected changes from unexpected directions. Essential in times of radical change or crisis. May have trouble applying themselves to managing change within ongoing organizational structures.

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18 ENVIRONMENT Social Effect (Especially Social Evaluation) Scope, Climate, Culture, Opportunity Via Group Dynamics COGNITIVE FUNCTION Cognitive Effect Cognitive Resource Preferred Style (E.G. A-I) Knowledge, Know-how Potential Level (E.G. IQ) Skills Experience (E.G. Conitive Technique) Via Cognitive Process Via Learning & Memory Cognitive Affect Need, Values Attitude, Beliefs Via Motive BEHAVIOR (Preferred & Coping Behavior) PRODUCT (Idea, Artifact) All the elements interrelate in problem solving & creativity. (The operational elements are not in capitals.) Figure 2-1. Kirtons (2003) Cognitive Function Schema

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CHAPTER 3 METHODOLOGY This chapter describes the methods used to answer the research questions presented in the study. Four specific questions were established to guide the study 1. What are characteristics of leaders in the Florida agricultural industry? 2. How do these leaders solve problems? 3. What is the problem solving style of Florida agricultural industry leaders? 4. How does the problem solving styles of leaders compare with their problem solving practices? This chapter specifically explains the research design, target population and sample, instrumentation, data collection procedures, and procedures that were used to analyze the data. Research Design This study employed basic descriptive research to answer the research questions and was conducted with the intent to provide base line research that will be of use in future studies regarding problem solving style. Because of the basic and foundational nature of this research, a qualitative in-depth interview design was used. Content analysis of the interview data provided information concerning research question one and was also be used in answering research question four. An existing instrument, the Kirton Adaption-Innovation Inventory (KAI), was utilized to answer research questions three and four. The independent variables for this study were participants age, gender, highest degree, leadership/management position, employer, and length of employment in current position. The KAI score of participants was the dependent variable in the study. 19

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20 Population The population of this study consisted of leaders in the Florida agricultural industry. For the purpose of this study, leaders were defined as individuals in a managerial leadership position with decision making capacity. A purposive sample of managerial leaders was utilized for this study. Leaders targeted for this study were those in managerial leadership positions with decision making capacity who were responsible for the daily operation of their organization. A cross section of leaders representing the major commodity groups in Florida agriculture was utilized. Two organizations were utilized in identifying potential participants: The Agricultural Institute of Florida and the Wedgeworth Leadership Institute for Agriculture and Natural Resources. Twenty companies and organizations are represented by a member on the board of directors for the Agricultural Institute of Florida, which seeks to offer networking and support for organizations within the agricultural industry of Florida. Each member serving on the board of directors was contacted via e-mail and informed of the nature and purposes of the study. These individuals were asked to refer individuals in their respective organization or industry who were managerial leaders with decision making capacity. The leaders referred from each organization or industry were then contacted via e-mail and informed about the nature and purposes of this study, were asked to confirm that they were in a managerial leadership position with decision making capacity responsible for the day-to-day operation of their organization, and asked to participate in the study if the fit the leadership description. The Wedgeworth Leadership Institute for Agriculture and Natural Resources is a leadership program designed to develop leadership qualities in people who are involved

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21 in policy decision making processes within agriculture and natural resources. Selected past participants of the Wedgeworth Leadership Institute were identified and recommended to participate in the study by the director of the Institute. Recommendations were based on past performance and current involvement with the Institute and University of Florida. Theses recommended prospective participants were contacted via e-mail and informed about the nature and purposes of this study, were asked to confirm that they were in a managerial leadership position with decision making capacity responsible for the day-to-day operation of their organization, and asked to participate in the study if the fit the leadership description. Based on the responses to these e-mails, a list of leaders was compiled to serve as the sample for this study. Of the 45 leaders initially contacted from the population frame of identified agricultural industry leaders, 22 responded to the request to participate in the study. 16 of the 22 respondents agreed to participate in the study and four declined to participate. The 16 leaders participating represented nine major agricultural commodity groups in the state of Florida. The major commodity groups and the commodities within them represented in the study are shown in Table 3-1. Instrumentation Three instruments were used in this study. The first, a demographic instrument, was developed by the researcher. The second instrument was a researcher-designed interview questionnaire, which was used to collect information from leaders regarding their specific problem solving practices. The third instrument for this study, the Kirton Adaption-Innovation Inventory, was used to identify the problem solving style of leaders. Researcher developed instruments were evaluated by a panel of experts for content and face validity and were pilot tested prior to data collection.

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22 Demographic Instrument The instrument used to collect data on the demographic characteristics of participants was developed by the researcher. The data collected included participants age, gender, highest degree, leadership/management position, employer, and length of employment in current position. This instrument provided a description of demographic characteristics of leaders in the Florida agricultural industry. The instrument was evaluated for content and face validity and was pilot tested prior to collecting data. Interview Questionnaire When conducting in-depth interviews, the use of a questionnaire is essential (Rubin & Rubin, 2005). The use of a questionnaire provided structure for the interviews and ensured the objectives of the interview are met. According to McCracken (1988), the questionnaire also helped ensure consistency among all participants, provided a direction and scope for the conversations, and allowed the interview to focus attention on participant responses. Questions for the interview were developed based on the review of the literature, specifically Kirtons Adaption-Innovation Inventory (Kirton, 2003). Questions identified specific problem solving practices related to each sub-score of the KAI. The questionnaire was evaluated for content and face validity and was pilot tested prior to conducting interviews. Kirton Adaption-Innovation Inventory The Kirton Adaption-Innovation Inventory (KAI) was developed and tested by M. J. Kirton (2003). The inventory measured respondents style of problem solving and creativity through a series of 26 statements, asking respondents to answer each item on a

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23 scale ranging from 1 (strongly disagree) to 5 (strongly agree). The KAI may only be administered by a KAI certified practitioner. KAI has a possible score range of 32 to 160, with the score indicating a place on a scale. High adaptors have low scores and high innovators have high scores (Kirton, 2003). The total score breaks down into 3 sub-scores which are inter-related but do not contribute equally to the total score. The three sub-scores are: Sufficiency of Originality, Efficiency, and Rule/Group Conformity. Data Collection and Analysis Prior to the collection of data, a proposal to conduct the study was submitted to the University of Florida Institutional Review Board for non-medical projects (IRB-02). The proposal was approved (Protocol #2006-U-0484). A copy of the informed consent form that was mailed to participants in the study was submitted to the IRB along with the proposal. The informed consent form described the study, the voluntary nature of participation, and informed participants of any potential risks and/or benefits associated with participating in the study. Once approval to conduct this study was granted by the IRB, data was collected and analyzed by the researcher. Data was collected during June of 2006. Specific data collection and analysis procedures that were used are discussed for each research question. Methods Used for Question One In order to answer research question one describing the characteristics of leaders in the Florida agricultural industry the purposive sample of these leaders provided demographic information via the researcher-developed instrument. The demographic instrument was mailed to each participant prior to their interview date, and participants

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24 were asked to complete the instrument prior to the interview. Data collected from the demographic instrument was analyzed using SPSS statistical package for Windows. Descriptive statistics such as frequencies and measures of central tendency was used to describe leaders in terms of their gender, age, highest degree earned, leadership/management position, and length of employment in current position. Methods Used for Question Two To answer research question number two how leaders solve problems this purposive sample of leaders participated in interviews using the interview questionnaire developed by the researcher. Interviews were conducted in person, or over the telephone and lasted 15 to 30 minutes. The interviews were tape-recorded and transcribed in their entirety following the interview. The transcripts and audio tapes were analyzed using content analysis to identify problem solving style themes reviewed in the literature. The themes and practices measured in KAI sub-scores served as a guide for the coding process, however themes were revised, eliminated or added as necessary. Themes were analyzed according to specific problem solving practices. Sub strategies, practices or themes were identified for each group of problem solving practices. Key words and actions for each strategy, practice and theme were identified. As key words and actions or closely related words and actions were cited by the subject, content was coded accordingly. Methods Used for Question Three In order to answer research question number three to determine the problem solving style of Florida agriculture industry leaders the Kirton Adaption-Innovation Inventory (KAI) was administered to the purposive sample of leaders. The KAI was mailed along with the demographic instrument prior to the interview date and participants

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25 were asked to complete the inventory prior to the interview. Using SPSS statistical package for Windows, descriptive statistics such as frequencies and measures of central tendency were used to describe the leaders in terms of their preferred problem solving style, as identified by KAI. In addition, a correlation between independent and dependent variables were analyzed to examine the effect of the independent variables on the dependent variables on an individual basis. Methods Used for Question Four In order to answer research question four comparing the problem solving styles of leaders with their problem solving practices results of the content analysis of interviews and KAI scores were compared. Adaption and innovation themes that emerged form problem solving practices in the content analysis were compared with KAI score on an individual basis in order to determine if leaders actual problem solving practices matched the practices predicted by their KAI score according to A-I theory. Summary This study involved descriptive research with a correlation design to describe Florida agricultural industry leaders and explain the influence of demographics on their preferred problem solving style, as well as a qualitative in-depth interview design to determine problem solving practices of these leaders. The population for this study consisted of individuals in managerial leadership positions with decision making capacity. Three instruments were used in this study: a demographic instrument developed by the researcher, an interview questionnaire developed by the researcher, and the Kirton Adaption-Innovation Inventory (Kirton, 2003). Data was collected though face-to-face meetings and telephone interviews.

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26 Data analysis procedures were also discussed in this chapter. In the quantitative portion of the study, descriptive statistics and correlations were used. Content analysis of interview tapes and transcripts was used in the qualitative portion. Table 3-1. Agricultural Commodity Groups Represented Commodity Group Specific Commodity Represented Dairy Edible dairy products Environmental Horticulture Landscape trees and products Nursery grown products Fertilizers Agricultural fertilizerschemical and organic Fruit and Nuts Citrus Oranges Grapefruit Fruit Trees Strawberries Tomatoes Fruit Juice Forestry Timber Live Animals Beef Cattle Dairy Cattle MeatEdible Beef Sugars Raw and refined sugar Vegetables Sweet corn

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CHAPTER 4 RESULTS This chapter presents the findings of the study. Findings are organized by the research questions of the study identified in Chapter 1. Question 1: What Are the Characteristics of Leaders in the Florida Agricultural Industry? Of the 16 agricultural industry leaders who participated in this study, 68.8% (n=11) were male and 31.2% (n=5) were female. In terms of ethnicity, 100% (n=16) were Caucasian. The gender of participant by ethnicity is shown in Table 4-1. Age of the participants ranged form 25 to 65. The mean age of participants was 47. Tenure within their organizations ranged from .75 years to 34 years and had a mean of 18.5 years. One participant did not report their tenure within their organization. Tenure in organizational leadership positions ranged from .66 years to 34 years and had a mean of 9.2 years. In terms of the highest degree held by study participants, 6.2% (n=1) had a high school diploma, 75% (n=12) had a bachelors degree, and 18.8% (n=3) had a masters degree. The full demographic profile of respondents is shown in Table 4-1. Question 2: How Do Florida Agricultural Industry Leaders Solve Problems? Twenty four major problem solving practices emerged from the analysis of the interview transcripts and audio tapes. During each interview, participants were asked a series of questions (Appendix B) developed by the researcher based on the review of the literature. Participants were first asked to describe the types of problems they faced as 27

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28 leaders in their organization. Four categories of problems most commonly faced by respondents emerged from the interviewstwo being identified as major themes and two as minor themes. The most frequently discussed problem area was personnel and staff problems. When asked to identify the types of problems most commonly encountered in their role one study participant replied, Basically, my role has primarily evolved into a people managing business. Another said, Labor is the number one problem to be solved today, as in how are we going to source enough labor initially in the season and manage that labor. The other major theme identified was management problems. One participant described making basic managerial decisions with respect to procurement, contracts, and also dealing with the best use of the organizations funds and assets. Another described the management problem of having too much to do and too little time to do it. The specific types of problems most common among respondents are identified in Table 4-2. The remaining questions asked participants to identify specific practices they used when solving the problems they discussed. Consistent with the literature, the questions were divided into three major categories, each reflecting a sub-score of the total KAI score. The categories were: Sufficiency of Originality, Efficiency, and Rule/Group Conformity. Each question recognized a specific practice of problem solving based on one of the three major categories. The specific problem solving practices for each category are listed in Table 4-3.

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29 Solution Generating Strategies When asked to describe personal strategies for generating solutions, participants most often discussed strategies for analyzing available options and working with others to solve the problem. Discussing analyzing strategies, one participant said, I try to look at all possible outcomes what are the possible outcomes and how will it affect me? Another participant preferred to determine the course of action youre going to take on the basis of information. One participant described that when working with others a certain synergy that will occur if a problem is discussed. Another participant discussed the value of working with others, noting, I very seldom would work in a vacuum in terms of me coming up with a solution. From the four strategies identified in the solution generating practices, 28 sub-strategies emerged (Table 4-4). Number of Solutions Generated Then number of solutions generated when solving a problem was the most specific problem solving practice area, with only three general practices identified (Table 4-5). Most participants referred to a specific number, while some gave more general responses. One participant preferred said this of generating solutions I try and develop as many potential ideas as possible and then narrow the scope down to those that are actually practical and doable. Participants explained their number preferences, with one participant explaining, Too many and it just muddies the water, and not enough and you get stuck. Types of Solutions Generated In terms of types of solutions, participants were asked if they preferred to generated solutions that focus on refining what exists or creating something new. Many

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30 participants preferred to focus on generating solutions that refine and existing practice or policy. As one explained, I dont see it as the best use of time to reinvent the wheel so to speak. Another participant said, I think I can build it better than its already been built. You show me something, and I think I can improve on it. Some participants preferred to generate solutions that focused on a new approach. One participant pointed out the importance of generating new and different solutions. I think you want to try to look at ways where you can get beyond the proverbial box, you want to really expand your thoughts and look at things from a different angle. Another participant said, As technology changes, I like to produce ideas that will help us do something completely different than the way weve been doing it. Some participants did not identify a preference, but responded that it depended on the situation. One participant said this about the type of solution needed being dependent on the situation I think it depends on the situation. We have to be efficient. We have to be profitable. If a given situation can be addressed as the way its always been done thats one thing but if it has to be changed, it has to be changed. It all depends on the circumstances. Theres no set rules. The sub-themes that emerged from the types of solutions are shown in Table 4-6. View of the Problem In terms of view of the problem, participants were asked if they preferred approaching problems with a big picture view or by attending to the details. While many participants chose one or the other, others took a different strategy. Some preferred to examine the big picture and then approach the details, while others said it depended on the situation or they did both at the same time.

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31 Many participants who chose the big picture view explained that details were unimportant or uninteresting. One participant said, If you get bogged down in the details sometimes you lose sight of what the true goal and vision you want to achieve is. Another participant explained that details were not as interesting to me as the big picture I dont want to get bogged down in the details. Another participant has this to say about viewing a problem: I paint walls. Im inclined to be a large picture person, and have always needed and appreciated people who attend to the details. Regarding looking at the big picture first and then details, one participant said, I look at the big picture, and how its going to affect me, and then I go back and look at all of the little details for what would need to happen. Another said, start out with the big picture and then try to break it up into components once you see how everything fits together then you can look at each role. Participant preferences and the sub-themes identified for each of them are listed in Table 4-7. Conforming to Rules When asked if they preferred to operate within established rules or break those rules most participants said they were more comfortable operating within the rules. Participants who preferred rules often referred to structure and consistency and consequences. One participant noted the value of rules when saying, Structure is important and we need to have consistency and people need to know what the expectations are. Another participant said, my thinking is that theres a reason why that rule or process existed in the first place. Some participants preferred to break the rules when problem solving. These participants spoke about getting out of the box and feeling restricted by rules. As one participant put it, If we keep doing it the same way well never advance. The rules hold

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32 you back. Another said, you can become stifled by the bureaucratic processes, and lose sight of what youre trying to actually do, and let the process fun the business rather than the business run the process. The complete list of sub-themes related to conforming to rules is found in Table 4-8. Consensus Building Participants were asked to discuss their preferences for group problem solving in regard to building consensus and challenging views in the group. This category contained many overlapping answers. Nearly all participants said they regularly challenge the views of group members when engaged in group problem solving. However, most participants said they regularly seek to build consensus during group problem solving. Many of the participants who discussed building consensus also said they challenged views. Of preferring to challenge the views of the group one participant said, Consensus certainly doesnt always work and the best ideas dont always come from consensus, so sometimes you have to break out and confront. Another said, I like to challenge the views of the group and I also like to be challenged myself. Another participant noted, If you let yourself be convinced that theres only one way to do this it can be a problem dont ever accept status quo. Many participants asserted that the end goal of group problem solving is consensus. These participants each said that while they both challenge and build consensus throughout the process, consensus is vital after the decision has been made. As one participant stated I like challenging the views, because what that does is causes people to think about the rationale theyve used for it But at the end of the day, when weve finally

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33 said ok, this is where were going, I want consensus. I want everybody to agree that we can get there doing this. Its about buying in with the program. Another participant stated, What you always try and achieve is a consensus and agreement at the end of the day so you can proceed in an organized way. Practices related to group problem solving and consensus building and the sub-themes that emerged from these practices are listed in Table 4-9. Question 3: What are the Problem Solving Styles of Florida Agricultural Industry Leaders? Problem solving styles of participants were determined as outlined in the KAI scoring key. KAI scores have a possible range of 32 to 160. KAI scores of participants ranged from 76 to 134. KAI scores are comprised of three sub scores: Sufficiency of Originality, with a possible range of 13 to 65; Efficiency, with a possible range of seven to 35; and Rule/Group Conformity, with a possible range of 12 to 60. KAI scores and sub-scores of participants are reported in Table 4-10. Nine of the 16 participants (56%) scored above 96 on the KAI, and therefore are more innovative. These participants will be referred to as innovators. Seven of the 16 participants (43%) scored 95 or less on the KAI, and therefore are more adaptive. These participants will be referred to as adaptors. Question 4: How Do the Problem Solving Styles of Leaders Compare With Their Problem Solving Practices? Participant KAI scores determined a list of predicted practices for problem solving based on the literature. These predicted practices were compared participants actual practices as discussed in the interviews. All 16 participants discussed utilizing a mix of adaptive and innovative practice to some degree. Individual KAI scores and the number

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34 of actual utilized adaptive and innovative problem solving practices discussed by the respective participant are shown in Table 4-11. Individuals with scores of 95 and below are considered more adaptive, and therefore would be predicted to discuss using more adaptive practices than innovative practices. Likewise, individuals with scores of 96 and above are considered more innovative and therefore would be predicted to discuss using more innovative practices than adaptive practices. Five participants (31%) responses to interview questions did not match their predicted responses based on KAI score. Four of the five participants with unpredicted responses were innovators who utilized more adaptive practices than innovative practices. One of the five participants with unpredicted responses was an adaptor who reported utilizing more innovative practices than adaptive practices. Unpredicted responses by KAI category are shown in Table 4-12. Summary This chapter presented the findings of this study. Findings were organized by the following research questions: (1) what are the characteristics of leaders in the Florida agricultural industry, (2) How do these leaders solve problems, (3) What is the problem solving style of Florida agricultural industry leaders, (4) How does the problem solving style of leaders compare with their problem solving practices?

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35 Table 4-1. Demographic Profile of Agricultural Industry Leader Participants (N=16) Characteristic Frequency Percent Gender Male Female 11 5 68.8 31.2 Ethnicity Caucasian 16 100 Age 25-34 35-44 45-54 55-65 3 3 5 5 18.8 18.8 31.2 31.2 Highest Degree Earned High School Diploma Bachelors Degree Masters Degree 1 12 3 6.2 75 18.8 Tenure with Organization Less than one year 2-5 years 6-10 years 11-15 years More than 15 years 1 2 2 1 9 6.2 12.5 12.5 6.2 37.5 Tenure in Current Position Less than one year 2-5 years 6-10 years 11-15 years More than 15 years 2 5 4 2 3 12.5 31.3 25 12.5 18.7

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36 Table 4-2. Types of Problems Faced by Florida Agricultural Industry Leader Participants Problem Category Sub-Category Major Theme: Personnel/Staff Problems Hiring Turnover Scheduling Communication Personal Issues Personalities Major Theme: Management Problems Logistics Scheduling/Planning Budget Operation/Production Programmatic development/ instrumentation Crisis management Daily issues Short term strategies Minor Theme: Organizational Problems Structure Vision Goals Efficiency High quality for Low production cost Planning Long term strategy Growth Marketing Minor Theme: Relationship Problems Among personnel With outside supporters With superiors With industry peers With political figures Table 4-3. KAI Sub-Scores and Accompanying Problem Solving Practices. KAI Sub-Score Accompanying Problem Solving Practice Sufficiency of Originality Solution generating strategies Number of solutions generated Efficiency Types of solutions generated View of the problem Rule/Group Conformity Conforming to rules Consensus Building

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37 Table 4-4. Solution Generating Strategies Strategy Sub-Strategy Major Strategy: Analyze Options/Solutions Predict all possible outcomes Ask what if? Evaluate existing solutions Research possibilities Research past efforts Reflect on personal experiences Predict long term outcomes Base action on information Major Strategy Teamwork/Communication Communicate directly with those involved Solicit guidance from outsiders Seek consensus with those involved Request input from leaders (superiors) Create a team/collaborate Consult experts Seek feedback Minor Theme: Assess the Problem Asses situation Define problem Examine the facts Asses support from key figures Research the problem Evaluate every facet of the problem Evaluate resources Examine big picture and details Minor Theme: Brainstorm Formal brainstorming on paper Informal brainstorming in head Create lists List many scenarios Think outside the box of Known options Table 4-5. Number of Solutions Generated Reported Themes Specific number 3 or less Five or less As many as possible Many at first, then evaluate and narrow down to a few

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38 Table 4-6. Types of Solutions Generated Type of Solution Sub-Themes Solutions that do things better (refining) Do not reinvent the wheel Always seek to refine first Efficiencysolves problems quickly Best for short term solutions Seek to hone the system Easier than changing Structure, rules and procedures Solutions that do things differently Get outside the box Be open to new things More challenging and enjoyable Needed for major issues/long term problems Look at situations from different angels Seek change Situation dependent Depends on type of problem Comfortable with both First evaluate problem Depends on desired outcome Dependent on resources

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39 Table 4-7. View of the Problem. View Sub-Themes Big Picture Focusing on details may prevent reaching a solution Big picture is equivalent to the goal Focusing on details can cause losing sight of vision and goal Others attend to details Necessary for management or executives Details are not interesting Set direction and overview Big Picture, Then Details Start with big picture and break it into components Allows view of how everything fits together Details may or may not be important depending on the big picture After examining big picture, must ensure details work Depends on Situation/Both Must look at both to ensure success Details ensure accuracy while big picture shows direction Depends on the nature of the problem Details Details set the stage for assessing the situation If the details do not work the problem has not been solved Personally detail oriented Having all the details portrays the bigger picture

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40 Table 4-8. Conforming to Rules Practice Sub-Themes Operate within the rules Work within established protocol, parameters, and policy Structure and consistency Adhere to expectations and guidelines Ethics and honesty Rules exist for a reason Consequences Shouldnt change for the sake of Changing Break the rules Rules are restrictive/ prevent advancement Getting outside the box is key for survival Breaking the rules yields better solutions Rules can be re-written Table 4-9. Consensus Building Practice Sub-Themes Challenge Views Challenge/change the status quo Get out of the box Play Devils Advocate Prevent groupthink Do not assume Make others think/be creative Broaden thinking Build Consensus Creating buy-in is necessary Division undercuts the goal Organizes process Creates comfort Builds confidence Provides clear direction Leaders must be able to follow group Consensus is End Goal Challenging is vital during solution generating process Consensus is the ultimate goal After challenges have been made decision making is collective

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41 Table 4-10. KAI Scores and Sub-Scores of Agricultural Industry Leaders Participants KAI Total Score Sufficiency of Originality Efficiency Rule/Group Conformity 76 36 17 23 77 32 15 30 83 47 11 25 86 48 12 26 93 51 12 30 94 40 18 36 95 43 16 36 98 40 14 44 99 49 17 33 101 49 17 35 101 43 19 39 108 55 20 33 115 49 25 41 119 45 29 45 131 62 23 46 134 54 30 50 Table 4-11. Actual problem solving practices discussed by KAI score (N=16) KAI Score Number of Adaptive Practices Discussed Number of Innovative Practices Discussed 76 5 2 77 5 2 83 6 4 86 3 4 93 6 1 94 6 1 95 5 2 98 5 3 99 2 5 101 7 1 101 3 4 108 2 5 115 6 1 119 5 3 131 2 5 134 2 7

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42 Table 4-12. Unpredicted responses by KAI category Reported KAI Category Number Deviating from Expected Practices Adaptor 1 Innovator 4

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CHAPTER 5 SUMMARY AND DISCUSSION This chapter presents a summary of the study as well as a discussion of the conclusions drawn from the findings, implications of the findings, and recommendations for future research. The chapter begins with an overview of the study, including the research questions presented, the methodology utilized, and the findings of the study. The remainder of the chapter discusses conclusions, implications and recommendations. Summary of the Study Research Questions The primary purpose of this study was to identify and describe the problem solving styles and practices of leaders in the Florida agricultural industry. Specifically, this study sought to answer the following questions 1. What are the characteristics of leaders in the Florida agricultural industry? 2. How do these leaders solve problems? 3. What is the problem solving style of Florida agricultural industry leaders? 4. How does the problem solving styles of leaders compare with heir problem solving practices? Methodology This basic descriptive research utilized mixed methods to answer the research questions. Qualitative in-depth interviews were conducted with leaders in Florida agricultural organizations who had decision making capacity and were responsible for the day-today operation of their organization. Sixteen individuals representing nine major agricultural commodity groups in Florida participated in the study. 43

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44 Data for this study was collected using two methods. The first utilized two survey instruments were delivered to participants via mail. Demographics and problem solving style were measured with these instruments. Data analysis consisted of descriptive and frequencies. Data was also collected through face-to-face and telephone interviews which were audio-taped. The audio tapes were transcribed in their entirety following the interviews and the transcripts and audio-tapes were analyzed using content analysis. Themes that emerged from the analysis were used to identify specific problem solving practices among the participating leaders. These actual problem solving practices were then compared with measured problem solving style on an individual basis in order to determine if leaders actual problem solving practices matched the practices predicted by their preferred problem solving style. Conclusions Because of the qualitative and descriptive nature of this study and the specificity of the interviews and interviewees, findings, conclusions, implications and recommendations of this study can be used only to understand this population. Therefore, the application of this understanding beyond the group of leaders described is minimal, though they may offer insight to the decision making process of similar leaders. With awareness of this limitation, the following conclusions were drawn from the findings of the research questions. Most of the participating leaders were Caucasian males. Most of the participating leaders were over the age of 40. Types of problems most often faced by Florida agricultural industry leaders include personnel/staff problems and management problems.

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45 Participants most often analyzed options and solutions and sought to work with others when generating solutions for a problem. The nature of the problem and situation determined which problem solving practices leaders utilized. Leaders in the Florida agriculture industry include both adaptors and innovators. Adaptors and innovators utilized problem solving practices that are both in their problem solving style and outside their problem solving style. Most of the participants who used unpredicted problem solving practices used practices that were more adaptive than expected. Participants most often preferred to operate within the rules when solving problems. Challenging the views of others is an important practice in group problem solving, but building consensus among the group is an important goal for many leaders. Discussion and Implications Question 1: What Are the Characteristics of Leaders in the Florida Agricultural Industry? Most of the participating leaders were Caucasian males. In this study, 69% (n=11) of participants were male and 31% (n=5) were female. 100% of the participants were Caucasian. Because the participants in this study were a purposive sample of leaders in Florida agriculture rather than a representative sample the demographic characteristics of this sample cannot be generalized to the entire population of agricultural leaders in Florida. Therefore, the conclusion that the majority of participating leaders were Caucasian males does not necessarily imply that the same distribution of gender and ethnicity exists in the entire targeted population. It is possible that women and minorities were underrepresented in the particular groups utilized to select the sample.

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46 Most of the participating leaders were over the age of 40. In this study, age of the participants ranged from 25 to 65. The mean age of participants was 47. Of the 16 participants, 69% were over the age of 40. It must again be pointed out that because the participants in this study were a purposive sample of leaders in Florida agriculture rather than a representative sample the demographic characteristics of this sample cannot be generalized to the entire population of agricultural leaders in Florida. Therefore, the conclusion that the majority of participating leaders were over the age of 40 does not necessarily imply that the same distribution of age exists in the entire targeted population. It is possible that leaders under the age of 40 were underrepresented in the particular groups utilized to select the sample. Question 2: How Do Leaders in the Florida Agricultural Industry Solve Problems? Types of problems most often faced by Florida agricultural industry leaders include personnel/staff problems and management problems. The participants reported two major themes and two minor themes regarding the types of problems they solve in their positions. Most participants reported regularly solving problems focused around personnel and staff, such as hiring, turnover and communication. Many of participants reported solving problems of a management nature such as logistics, budget, operating and programmatic concerns on a regular basis. These problems are somewhat consistent with Mintzbergs managerial roles (1973), which include interpersonal roles, serving as a monitor, disturbance handler and resource allocator, among others. These reported problems were expected to emerge, because they are concerned with the day-to-day issues facing organizations. The population for this study was

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47 leaders who had decision making capacity and were responsible for the day-to-day operation of their respective organizations. Therefore it is not unusual that the most common problems faced related to day-to-day issues. Participants most often sought to work with others when generating solutions for a problem. Although the interview questions were designed to focus on personal and individual problem solving strategies, the majority of participants insisted that problem solving was rarely a solitary event, and therefore could not be discussed only in terms of solitary and introspective strategies. These leaders discussed creating a team, seeking advice, and communicating with others throughout the problem solving process in order to generate the best solutions possible. The common use of this practice could simply be a matter of personal preference. It could perhaps indicate that these particular leaders work in organizations that promote communication and teamwork when solving problems. Or perhaps it could be a reflection of the close-knit nature of the agricultural industry. The nature of the problem and situation determined which problem solving practices leaders utilized. While some leaders chose one specific problem solving practice for each area of their problem solving preferences, the majority of leaders said it depends or I do both several times. While A-I theory suggests that individuals have a style they prefer to operate in (Kirton, 2003), many participants insisted they did not prefer one practice or another on a regular basis, but instead evaluated the situation and chose the most useful strategy based on the nature of the problem. Because this was reported by individuals all across the KAI score scale, this is not readily explained by leaders whos scores are near the theoretical KAI mean. This could

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48 be an indication of learned coping behavior (Kirton, 2003), in which individuals choose to operate outside of their preferred style because insight or foresight tells them it will be more advantageous. Question 3: What Are the Problem Solving Styles of Florida Agricultural Industry Leaders? Leaders in the Florida agriculture industry include both adaptors and innovators. The distribution of adaptors and innovators among the participants was fairly normal. 56% of the 16 participants were innovators, and 43% were adaptors. This is an accurate reflection of the distribution for large general populations of adaptors and innovators, which forms a normal curve (Kirton, 2003). Although the distribution of adaptors and innovators in this sample cannot be directly generalized to the entire population of leaders in Florida agriculture, because of its consistency with the distribution in large populations it can be assumed that there is a normal distribution of adaptors and innovators among Florida agricultural industry leaders. Question 4: How Do Problem Solving Styles of Leaders Compare With Their Problem Solving Practices? Adaptors and innovators utilized problem solving practices that are both in their problem solving style and outside their problem solving style. All 16 participants reported utilizing problem solving practices that were both adaptive and innovative. This is consistent with the literature. A-I theory states that every individual is both adaptive and innovative, but according to where they fall on the A-I scale they prefer one over the other to some degree. Therefore, it was expected that participants would engage in both adaptive and innovative practices, regardless of their KAI score. This conclusion therefore supports the literature.

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49 The majority of participants who utilized unpredicted problem solving practices utilized practices that were more adaptive than expected. Five of the 16 participants (31%) reported utilizing an amount of problem solving practices that were inconsistent with their KAI score. Four of these five were innovators who reported utilizing practices that were more adaptive than expected. The literature contains a few possible explanations for all five inconsistencies. It is possible that these individuals are displaying coping behavior in the way they solve problems related to their leadership roles. This coping behavior could be a result of conforming to the nature of the industry (actual or perceived), conforming the culture of their organization (actual or perceived), or conforming to the constraints of the problems most often faced (Kirton, 2003). Another possibility is that participants did not respond to the KAI in a way that reflected their true preferences consistently across time. The above explanations could also apply specifically to the majority of the inconsistencies being innovators who utilized an unexpected amount of adaptive behavior. These individuals may be innovators who work in a very adaptive environment and used coping behavior to adjust to the demands of their position. This possibility can be seen in a statement of one participant, who stated, My preference and my reality are two different things. In considering the possibility that the participants did not respond accurately to the KAI it should be considered that the A-I literature states that adaptors often see innovators as glamorous and exciting (Kirton, 2003). Responses could possibly be skewed as a result of this, which could explain adaptors receiving a higher score because they wanted to see themselves as more innovative.

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50 Participants most often preferred to operate within the rules when solving problems. Preferring to operate within the rules is a practice preferred by more adaptive individuals. Only 7 participants were labeled adaptors based on their KAI score, however 10 participants said they preferred the adaptive practice of operating within the rules. Participants who preferred to operate within the rules spoke of the need for rules, structure and ethics, as well as concern for consequences. This could be explained by the earlier conclusion that adaptors and innovators utilized problem solving practices that are both in their problem solving style and outside their problem solving style. A-I theory states that every individual is both adaptive and innovative, but according to where they fall on the A-I scale they prefer one over the other to some degree (Kirton, 2003). Therefore, it was expected that participants would engage in both adaptive and innovative practices, regardless of their KAI score. Perhaps this was an occurrence of coping behavior. It is possible that this occurrence was a reflection of the culture of the organizations leaders represented (very rule or consequence driven, perhaps), or again a reflection of the nature of the agricultural industry. Challenging the views of others is an important practice in group problem solving, but building consensus among the group is an important goal for many leaders. This problem solving practice is where the most overlap occurred. 14 of the 16 participants said they regularly challenge the views of group members when engaged in group problem solving. However, nine participants said they regularly seek to build consensus during group problem solving, with seven of the nine participants who discussed building consensus also said they challenged views. In addition, eight participants asserted that the end goal of group problem solving is consensus.

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51 Again, utilizing both strategies could be a learned behavior or a coping behavior. Participants repeatedly and separately said that each of these practices is what good leaders do. In this case participants may have been utilizing coping behavior in order to operate in a way they believe will make them a better leader. It could also again be explained by the earlier conclusion that adaptors and innovators utilized problem solving practices that are both in their problem solving style and outside their problem solving style. Suggestions for Additional Research Based on the findings and conclusions of this study, the following suggestions for additional research were made Because this was a qualitative and descriptive study with very specific interviews and interviewees and only a small purposive sample was included in the study, additional research needs to be conducted with a larger population that is more representative of leaders in the Florida agricultural industry. Due to the descriptive nature of the study and purposive sample, relationships and correlations among variables could not be determined. Additional research should be conducted with a larger population in order to identify relationships among demographic variable and problem solving style among Florida agricultural industry leaders. This study identified specific problem solving practices utilized by leaders in Florida agriculture. Future research should be conducted to study the use of these practices and their relation to problem solving style more in-depth. Several of the conclusions drawn from the findings of this study related to the use of more adaptive problem solving practices than innovative practices despite the presence of more innovators in the population. One possible explanation is that this was a reflection of the nature of the agricultural industry. Future research should be conducted to examine the nature and culture of the agricultural industry and the constraints it places on problem solvers.

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APPENDIX A DEMOGRAPHIC INSTRUMENT Please complete the following demographic questions. What is your gender? (please check) o Male o Female What is your ethnicity? (please check) o American Indian or Alaska Native o Asian o Black or African American o Hawaiian or Pacific Islander o Hispanic or Latino o Caucasian o Other (please indicate) _________________ What is your age (in years)? _____________________ Please list the degree, year awarded, major, and granting institution for each of your degrees Degree Year Awarded Major Institution Please list the name of your organization: _______________________________ Please describe your organizationwho you serve, your mission, focus, etc. 52

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53 Please indicate your current position within your organization: How long (in years) have you been employed with your organization? _____ How long (in years) have you been in your current position within your organization? _____

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APPENDIX B INTERVIEW QUESTIONAIRE Questions 5. What types of decisions do you make in your leadership role? Give examples. 6. Think about the last time you solved a problemhow did you generate ideas?7. How many ideas do you like to generate when solving a problem? 8. Do you like to produce ideas that help you do the same thing better or help you do something different? Give examples. 9. When solving a problem do you pay more attention to details or do you take a wider overview approach? How so? 10. When solving problems do you like to stick to the agreed rules or break the rules? Give examples. 11. In group problem solving, are you more comfortable ensuring group consensus or challenging the views of the group? Why? 54

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LIST OF REFERENCES American Farm Bureau Federation. (2004). Farm facts. Washington, DC: American Farm Bureau Federation. Barnard, C. (1938). The functions of the executive. Cambridge, MA: Harvard University Press. Beyer, B.K. (1987). Practical strategies for the teaching of thinking. Boston: Allyn and Bacon, Inc. Cannella, A. A., & Monroe, M. J. (1997). Contrasting perspectives on strategic leaders: Toward a more realistic view of top managers. Journal of Management, 23 (3), 213-237. Delbecq, A.L., & Mills, P.K. (1985). Managerial practices that enhance innovation. Organisational Dynamics, 14, 24-34. Dewey, J. (1910). How we think. Boston: D.C. Health. Facione, P. A. (1998). Critical thinking: What it is and why it counts. Millbrae, CA: California Academic Press. Florida Department of Agriculture and Consumer Services. (2002). Retrieved October 5, 2005, from http://www.florida-agriculture.com/agfacts.htm Greeno, J.G. (1978). Natures of problem solving abilities. In W.K. Estes (Ed.). Handbook of learning and cognitive processes (5 th Ed.). Hillsdale: Erlbaum. Hodges, A.W., & Mulkey, W.D. (2003). Regional economic impacts of Floridas agricultural and natural resource industries. Economic impact analysis program. Gainesville: University of Florida Institute of Food & Agricultural Sciences. Kirton, M.J. (2003). Adaption-Innovation in the context of diversity and change. New York: Routledge. Kouzes, J., & Posner, B. (2002). The leadership challenge. San Francisco: Jossey-Bass. Lachman, M., & Zorska, D. (1999). Economic trends. Cleveland: Federal Reserve Bank of Cleveland. 55

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56 McCarthy, R. (1993). The relationship of individual characteristics of women managers to the pressures experienced at work and choice of coping strategy. PhD Thesis, Unviersity of Hertfordshire. McCracken, G. (1988). The long interview. Newbury Park, CA: Sage Publications, Inc. Mintzberg, H. (1973). The nature of managerial work. New York: Harper & Row. Neisser, U. (1967). Cognitive psychology. New York: Appleton-Century-Crofts. Newcomb, L.H., & Trefz, M.K. (1987). Levels of cognition of student tests and assignments in the College of Agriculture at The Ohio State University. Proceedings of the Central Region 41 st Annual Research Conference in Agricultural Education. Chicago. Newell, A., & Simon, H.A. (1972). Human problem solving. Englewood Cliffs: Prentice Hall. Northouse P.G. (2004). Leadership theory and practice. Thousand Oaks: Sage Publications, Inc. Park, K. (2005). World Almanac & Book of Facts New York: World Almanac Education Group Inc. Paul, R. & Elder, L. (2002). Critical thinking: Tools for taking charge of your professional and personal life. Upper Saddle River: Prentice Hall. Paul, R., & Elder, L. (2003). The miniature guide to critical thinking concepts and tools. Dillon Beach, CA: Foundation for Critical Thinking. Paul, R., & Elder, L. (2004). The thinkers guide to the nature and functions of critical and creative thinking. Dillon Beach, CA: Foundation for Critical Thinking. Reed, S.K. (1982). Cognition theory and applications. Monterey: Brooks/Cole Publishing Company. Ricketts, J. C., & Rudd, R. D. (2002). A comprehensive leadership education model to train, teach and develop leadership in youth. Journal of Career and Technical Education, 19 (1), 7-17. Rubin, H.J., & Rubin, I.S. (2005). Qualitative interviewing: The art of hearing data. Thousand Oaks: Sage Publications. Scriven, M. (1976). Reasoning New York: McGraw Hill. Sternberg, R.J. (1977). Component processes in analogical reasoning. Psychological Review, (84), 353-378.

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57 United States Department of Agriculture. (2002). Census of agriculture. Retrieved October 5, 2005, from http://www.nass.usda.gov/census/ Yukl, G. (2002). Leadership in organizations. Upper Saddle River, NJ: Prentice Hall.

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BIOGRAPHICAL SKETCH Dyanna Renee Durham was born and raised in the small town of Prairie Grove, Arkansas. After graduating from Prairie Grove High School in 2000, she began her undergraduate career at the University of Arkansas. She graduated from there with a Bachelor of Science degree in agricultural & extension education with a concentration in agricultural education. In the summer of 2004, Renee moved to Gainesville, Florida to begin the pursuit her Master of Science degree in the Department of Agricultural Education and Communication at the University of Florida. In July of 2006 Renee accepted a position with the National FFA Organization as an education specialist for chapter leadership programs. She will complete the requirements of her degree in August 2007 and continue her work with youth leadership programs at FFA. 58