A systems-based approach to assessing leadership styles in engineers

A Systems–based Approach to Assessing Leadership Styles in Engineers
BY
Olatoyosi Olud
´
e–Afolabi
B.S., University of Nebraska, Lincoln, 1998
M.S., State University of New York, Binghamton, 2003
DISSERTATION
Submitted in partial fulfillment of the requirements for
the degree of Doctor of Philosophy in Systems Science
in the Graduate School of
Binghamton University
State University of New York
2010




UMI Number: 3408995






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c
 Copyright by Olatoyosi Olud´e–Afolabi 2010
All rights reserved
Accepted in partial fulfillment of the requirements for
the degree of Doctor of Philosophy in Systems Science

in the Graduate School of
Binghamton University
State University of New York
2010
April 08, 2010
Prof. Eileen. C. Way, Chair
Department of Systems Science and Industrial Engineering,
Binghamton University
Prof. Harold. W. Lewis III, Graduate Chair
Department of Systems Science and Industrial Engineering,
Binghamton University
Prof. Shelley Dionne, Member
School Of Management, Binghamton University
Prof. William D. Spangler, Member
School Of Management, Binghamton University
Prof. Bahgat Sammakia, External Examiner
Department of Mechanical Engineering, Binghamton University
iii
Abstract
There is a widely recognized gap in the skill set of newly graduated engineers and
the needs and expectations of industry. The Accreditation Board of Engineering and
Technology (ABET) has taken steps to address this gap by adjusting its criteria for
accrediting engineering programs.
In particular, ABET has specified program outcomes that address technical skills
in relation to the ability to function on teams, the ability to communicate effectively
and an understanding of professional and ethical responsibility. However, there are
still gaps not directly addressed by ABET, gaps involving leadership skills, which are
defined as a combination of leadership terms. These leadership terms are communica-
tion, motivation, team–building, visionary, coaching & mentoring, time management,
listening and innovation. This research explores the key components of leadership to

engineering academia and industry using system techniques that classifies the differ-
ent definitions of leadership.
Through the use of text mining, data was collected from industry trade journals
then fuzzy similarity was used to classify different terms employed in the definition
of leadership. Finally, the results suggest that the more terms used by journals
were classified by engineering academia as having more leadership terms in defining
leadership when compared to industry.
iv
To Mark, JoAnne, JoElle and Jolla Afolabi.
v
Acknowledgments
I am expressing my profound gratitude to Professor Eileen Way, my advisor, for her
suggestions and constant support during my research. She has been a mentor and a
coach throughout my graduate career. Without her, I would be languishing on my
adventure to knowledge. Advisors like her are extremely few to find.
In addition, I will like to thank Professor Hal Lewis for his support, teaching and
encouragement in all of his classes. I appreciate his persistence in my learning, he
imparted confidence about being a doctoral student.
I am also thankful to Professors Shelley Dionne and Don Spangler for their guidance
through the early years of chaos and confusion. They taught me the importance of
leadership and the appropriate use of leadership skills to solve problems. Definitely,
the adventure to knowledge is worth the effort.
The Clifford D. Clark Fellowship, awarded to me for the period 2002–2007, was crucial
to the successful completion of this research. Without this financial support research
like this would have been impossible.
I am grateful to my parents and siblings for everything. I will use this opportunity
to express gratitude to my friends, mentors and in–laws who supported me through
my difficult years to complete this dissertation. I will like to remember my sisters
and mother-in-law, who taught me love, courage, and confidence and without them I
wouldn’t be this successful. Last but not the least, I will like to thank my daughters

and my better half for their great sense of humor. The adventure is an excitement.
vi
Table of Contents





List of Figures

List of Tables

1 Introduction

1.1 Problem Definition—Assessing the Key





x

xi

1
Components of Leadership in Engineers . . . . . . . . . . . . . . . .
. . . . . . . . 2
1.2 Theoretical Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.3 Research Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.3.1 Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

1.4 Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.5 Dissertation Overview . . . . . . . . …… . . . . . . . . . . . . . . . . 7

2 Literature Review 9
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . 9
2.1.1 The Leadership Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.1.2 Required Leadership Skill Set for New Engineers . . . . . . . . . . . . . . . 11
2.1.3 Leadership and Management Roles . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.1.4 Important Elements for Engineering Definition of
Leadership & Why . . . . . . . . . . . . . . . . . . . . . . . . 18
2.1.5 What does leadership mean in an engineering context? . . . . 19
2.1.6 Ideal Concepts of Leadership based on Research Experts . . . 20
2.1.7 Actual Data Concepts vs. Ideal Concepts of Leadership . . . . 25
2.2 Overview of Classification Methods for
Leadership . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.2.1 Overview of Text Mining . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . 29
2.2.2 Overview of Artificial Neural Network (ANN) . . . . . . . . . . . .
. . . 31
2.2.3 Overview of Fuzzy Set Theory . . . . . . . . . . . . . . . . . . . . . . . . .
. . . 37
2.2.4 The Value of Fuzzy Set Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38
2.2.5 Overview of Fuzzy Similarity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42
2.2.6 The Value of Fuzzy Similarity . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . 44
2.2.7 Applications of Fuzzy Similarity Measures . . . . . . . . . . . . . . . . . . . . . 46

vii
2.3 Overview of Data Collection Methods for
LeadershipAnalysis 50
2.3.1 Types of Data Collection Techniques 50
2.3.2 DirectObservationversusSurveys 51
2.3.3 ContentAnalysis 53
2.3.4 EspousedTheoryofAction 53
2.4 Chapter Summary 55
3 Methodology 56
3.1 Introduction 56
3.2 Research Design 58
3.2.1 Level1:DataCollectionProcess 58
3.2.2 Level2:CollectedData 64
3.2.3 Level3:FuzzySystem 65
3.2.4 Level4:AnalysisofResult 68
3.2.5 Level5:Conclusions 69
3.3 Software Design—Engineering Leadership Fuzzy System (ELFS) . . . 69
3.4 Procedural steps of Classifying the definitions of leadership 70
3.5 PrototypeofEngineeringLeadershipFuzzySystem(ELFS) 71
3.6 Text–Mining Tool—YALE 73
3.6.1 YALE: Mapping Ideal Concepts of Leadership 73
3.7 Chapter Summary 76
4 Results 77
4.1 Introduction 77
4.2 Five–StageAnalysisSystem 78
4.2.1 Stage I: Ideal Concepts of Leadership based on Research Experts 78
4.2.2 Stage II: Mapping Ideal Concepts of Leadership 79
4.2.3 Stage III: Frequency of each Ideal Concept per Document . . . 79
4.2.4 StageIV:MeasureofImportanceofeachIdealConcept 82

4.2.5 Stage V: Actual Data Concepts vs. Ideal Concepts of Leadership 83
4.2.6 Summary of the Five–Stage System 83
4.3 AnalysisofResults 84
4.3.1 Reliability of Collected Data 84
4.3.2 Reliability of Classified Data 86
4.4 Results Summary 87
4.4.1 How does the definition of leadership and management in En-
gineering Academia differ from Industry? . . 87
4.4.2 Do the leadership skill sets relate to management skills? . . . 90
4.5 Chapter Summary 92
5 Conclusion 94
5.1 Introduction 94
5.2 Research 95
5.3 Contributions & Recommendations 98
viii
5.4 BenefitsofResearch 99
5.5 Limitations of Research 100
5.6 FutureResearch 101
5.7 Chapter Summary 102
6 Appendix 104
A ABET’s Criteria for Accrediting Engineering Programs 104
B ABET’s Surveys 127
C Maple Code 149
7 Bibliography 158
ix
List of Figures
2.1 Leadership & Management Skill Ratings [Adapted from AMA Research
(2003)] 25
2.2 IdealConceptsofManagement 27
2.3 IdealConceptsofLeadership 27

2.4 PartialManagementConcepts 28
2.5 PartialLeadershipConcepts 28
2.6 BackpropagationNetwork 36
2.7 Knowledge–based classification [Adapted from Zimmerman(2001)] . . 48
3.1 ProjectDataFlowchart 57
3.2 EngineeringLeadershipCorpus 64
3.3 DatafromYALEsoftware 66
3.4 FuzzyLinguisticVariables 68
3.5 ScreenShotofEngineeringLeadershipFuzzySystem(ELFS) 70
4.1 Document File Distribution (In Files) 80
4.2 Document File Distribution (In Pages) 81
4.3 Leadership and Management in Academia vs. Industry 88
4.4 Engineering Academia, Industry and Total Classification in Compari-
son 90
4.5 Engineering Academia, Industry and Overall Level of Importance in
Comparison 91
x
List of Tables
2.1 Leadership Skills—[Adapted from AMA Research (2003)] 19
2.2 Survey Data for Leadership [Adapted from Harper Jr. (2003)] 23
2.3 Survey Data for People Management & Development [Adapted from
HarperJr.(2003)] 23
2.4 Survey Data for Teamwork [Adapted from Harper Jr. (2003)] 24
2.5 Survey Data for Creativity & Innovation [Adapted from Harper Jr.
(2003)] 24
3.1 Database Abbreviations 62
3.2 DocumentsFoundusingGrokker 62
3.3 DocumentsFoundusingFactiva 62
3.4 DataConceptClassification 71
3.5 Sample Results Data 72

3.6 Sample Data for Analysis 72
3.7 Concept Mapping of Leadership & Management 74
4.1 Leadership Ideal Concepts–Summary Statistics 81
4.2 Management Ideal Concepts–Summary Statistics 82
4.3 Descriptive Statistics–Leadership Concepts 85
4.4 Descriptive Statistics–Fuzzy Concepts 86
4.5 Document Classification regarding Key Concepts of Leadership . . . 89
4.6 Level of Importance regarding Key Concepts of Leadership 89
xi
Chapter 1
Introduction
The American industry needs leadership to remain competitive in today’s global
economy; furthermore, the industry needs risk takers, change masters, big thinkers,
good communicators and other important qualities to stay competitive (Farr, Walesh
and Forsythe, 1997; Farr and Brazil, 2009). The skills to show these qualities are
regarded as leadership skills, which Engineers frequently downplay as soft people
skills in comparison to the hard math and technical skills that are needed in the
engineering curriculum.
However, in this competitive environment, business and industry demand exception-
ally trained engineers that have leadership skills. Engineers study for years to mas-
ter the technical skills required in their respective fields to design and develop new
products and improve processes, but often do not master leadership skills because
“ leadership is rarely addressed in formal engineering/engineering technology edu-
cation programs” (Summers, Davis and Tomovic, 2004).
There is a widely recognized gap in the skill set of new engineers, according to the
1
American Society for Engineering Management (ASEM, 1995), which reported seven
areas including leadership as a “perceived gap in the value of the organization versus
preparedness for new BS engineers” (Summers et al., 2004). However, “the area
where the perceived gap was the greatest was leadership” (Farr et al., 1997; Summers

et al., 2004). Similarly, in order to meet industry needs, the American Society for
Engineering Education has found that leadership education in engineering programs
need to be improved to stay competitive in today’s global economy (ASEE, 1994),
hence the need of leadership skills in engineers. Russell and Yao concluded that
“ that anengineerishired for heror histechnical skills, fired for poor people skills
and promoted for leadership and management skills” (Russell and Yao, 1997).
Organizations such as the U. S. Accreditation Board for Engineering and Technology
(ABET) has held engineering schools accountable for producing functioning engineers
who possess leadership skills through the introduction of the Engineering Criteria
2000 (EC2000) i.e. Accreditation by assessment (ABET, 2000a,b). In addition, the
National Academy of Engineers (NAE) has established funding for sparking innovative
spirit in both faculty and engineering students (National Academy of Engineering of
Academies, 2003).
1.1 Problem Definition—Assessing the Key
Components of Leadership in Engineers
In an attempt to improve engineering programs, Pennsylvania State University (PSU)
Prados et al. (2005); Volkwein et al. (2004) has designed surveys (see Appendix B
2
on page 127) to assess the skills of entry-level engineers due to the fact that ABET
requires leadership skills (see Appendix A on page 104). However, assessing the key
components of leadership involves defining, measuring and designing both the teach-
ing and assessment programs to analyze the critical dimensions of leadership in en-
gineers. As Kotterman (2006), pointed out, leadership cannot be assessed, measured
or tested if it cannot be defined.
A major problem in improving leadership education in engineering programs is defin-
ing the term leadership since there are “approximately three hundred and fifty def-
initions of leadership [that] have been generated over the last thirty years” (Bennis
and Nanus, 1985). Thus, “developing a concise definition of leadership for engineering
managers appears to be a difficult task” (Davis, 2004; Summers et al., 2004).
Another problem with improving leadership education in an engineering program is

assessing the defined leadership terms. Leadership assessment reflected in test scores
or in a student’s performance is based on subjective human values and people have
different values and judgements, which often leads to different evaluation criteria,
ultimately resulting in different final assessments (Loadman and Thomas, 2000).
However, before assessing the definition of leadership, the critical dimensions of lead-
ership, which are subjective, needs to be measured. Based on this measurement,
programs for teaching leadership skills can be designed and finally, an assessment
program can be created to measure the accomplishment of leadership skills in stu-
dents.
3
Measuring the definition of leadership that has roughly three hundred and fifty def-
initions is obviously challenging. Also, assessing an education program based on
this measurement is a daunting task; nonetheless, in order to improve engineering
programs this challenging problem was divided into four phases, as follows:
Phase I: Identifying the definition of leadership in engineering
Phase II: Measuring the definition of leadership in engineering
Phase III: Designing the teaching programs for the leadership dimensions and
Phase IV: Designing an assessment program to measure the achievement of the
critical dimensions of leadership in students
Among the four phases identified earlier, this research will be focused on Phase I.
As Kotterman (2006) pointed out, leadership cannot be assessed, measured or tested
if it cannot be defined. Identifying the definition of leadership in engineering is the
foundation to solving this challenging task.
In addition, identifying the definition of leadership will recognize and classify the key
components of leadership in engineers. In order to classify the definition of leadership,
exploring different classification methods such as neural network, fuzzy logic, and
fuzzy similarity can be utilized. One of these classification methods will be used to
analyze the critical aspects of the definition of leadership.
Furthermore, identifying the critical dimensions of leadership involves finding answers
to questions such as “What does leadership mean in an Engineering Context?, How

4
are the leadership skill sets of an engineer defined?, What specific skills are needed by
industry?, Are the critical aspects of the definition of leadership actually management
skills or leadership skills?, and Do the critical aspects of the definition of leadership
include management skills?.”
1.2 Theoretical Framework
The theoretical framework of this dissertation is based on determining the critical
dimensions from all the definitions of leadership that are important to engineers based
on research data from surveys of leadership and management (AMA Research, 2000a;
AMA Research , 2000b; AMA Research, 2003; American Management Association,
2005; Harper Jr., 2003). The critical dimensions from research data are compared
to the leadership skills needed that industry communicates in trade journals. This
comparison is determined using a subjective and approximate reasoning approach
called fuzzy similarity (Biswas, 1995; Tversky, 1977; Vosniadou and Ortony, 1989;
Zimmermann, 2001).
1.3 Research Objective
The main objective of this dissertation is to determine the key components of leader-
ship for engineering academia and industry and also to explore different classification
methods that can be used such as neural network, fuzzy logic and fuzzy similarity to
analyze the critical aspects of the definition of leadership.
In order to explore the key components of leadership needed for engineering academia
5
and industry, the following questions will guide the research
1. What does leadership mean in an engineering context?
2. How does the definition of leadership in engineering academia differ from in-
dustry?
3. How are the leadership skill sets of an entry-level engineer defined?
4. Do the above leadership skill sets relate to management skills?
Implementation of the techniques used to attain the main objectives of this research
is discussed below.

1.3.1 Techniques
The following are techniques that will be used in this research.
• Definition of Leadership—Different definitions of leadership are explored in both
engineering and industry literature. In addition, the key concepts of leader-
ship are explored utilizing research surveys (American Management Associa-
tion, 1999; Carr et al., 2005; Davis, 2004; Kerzner, 2001; Summers et al., 2004;
Thompson, 2004).
• Text Mining—Used to extract meaningful concepts from raw documents, con-
cepts and higher–level entities are used to support a range of knowledge dis-
covery in database operations on documents and finally, the frequency of co–
occurrence of concepts is used to provide concept linking (Feldman, 2003; Ye,
2003).
6
• Fuzzy Similarity—models the theories of similarities including the analysis of
connotative meanings. Fuzzy similarity also models the human cognitive pro-
cess using approximate reasoning and linguistic representation (Biswas, 1995;
Tversky, 1977; Turksen and Zhong, 1988; Vosniadou and Ortony, 1989; Zim-
mermann, 2001).
1.4 Assumptions
• The frequency of each word in a document is related to the level of importance
of each word in a document. Analysis of results was based on the level of
importance.
• The unit of measurement is the number of documents i.e. number of files
• Selection of documents were random, i.e. representation of documents was
random.
1.5 Dissertation Overview
Chapter 2 reviews the literature concerning key concepts of defining leadership. It
discusses the applications and value of fuzzy logic and fuzzy similarities.
Chapter 3 introduces the methods used in classifying the definition of the key concepts
of leadership and finding the fuzzy similarity of these key concepts.

Chapter 4 presents the result summaries and the findings from researched data to
determine the key concepts of leadership.
7
Chapter 5 completes the research by pointing out significant contributions, benefits
and limitations of the research, and finally concludes with future research.
8
Chapter 2
Literature Review
2.1 Introduction
The need for leadership skill in the skill set of newly graduated engineers has not been
directly addressed by ABET. The need to explore the missing skills in engineering
education is important. This chapter will review the rationale for requiring leader-
ship skills and the difference between leadership and management roles. In order to
explore the meaning of leadership in an engineering context, the important elements
for engineering definition of leadership will also be examined.
Critical aspects of the definition of leadership in engineers involves vagueness and
subjectivity, which leads to analyzing the theoretical concepts of systems methodol-
ogy. This chapter discusses the value of fuzzy set theory and fuzzy similarity. In order
to clarify implicit theories of leadership that academia and industry have, data col-
lection techniques needs to be investigated. This chapter concludes with an overview
of text–mining including its approaches and drawbacks.
9
2.1.1 The Leadership Theory
The definition of leadership has been evolving because according to Bennis and Nanus
in 1985, they reported that “approximately three hundred and fifty definitions of
leadership have been generated over the last thirty years” (Bennis and Nanus, 1985).
It has been defined in terms of traits, behaviors, role relationships and occupation of
an administrative position (Yukl, 2002; Daft, 2002). Examples of such definitions are
(Yukl, 2002):
• Leadership is “the process of influencing the activities of an organized group

toward goal achievement” (Rauch and Behling, 1984, p.46)
• “Leadership is the process of making sense of what people are doing together so
that people will understand and be committed” (Drath and Palus, 1994, p.4)
• “Leadership is about articulating visions, embodying values, and creating the
environment within which things can be accomplished” (Richards and Engle,
1986, p.206)
• “Leadership is an influence relationship among leaders and followers who intend
real changes and outcomes that reflect their shared purposes” (Daft, 2002, p.5)
In the words of Yukl (2002), leadership is “the process of influencing others to under-
stand and agree about what needs to be done and how it can be done effectively, and
the process of facilitating individual and collective efforts to accomplish the shared
objectives”.
10
No matter the discipline, a leader must demonstrate skills that create a motivating
environment that reinforces and energizes follower commitment (Blank, 2001).
2.1.2 Required Leadership Skill Set for New Engineers
In 1997, National Science Foundation conducted a study with nearly two million
working engineers with degrees. The results showed that 82% of all trained engi-
neers were employed by business and industry and 58% of the 82% trained engineers
developed their careers in management, sales and administration (Summers et al.,
2004).
Evidently, engineers are working in business and leaderships roles, which they were
not prepared or trained for and a large portion of the 49% interviewed faced leadership
and business challenges (Summers et al., 2004). Based on these challenges, Norman
Augustine,co-chair ofthe National AdvisoryCouncilpointed outthat “ engineers
lack the ability to communicate” (Augustine, 1994). The ability to communicate
and other leadership skills are regarded as soft skills. The reasons for the lack of
communication is discussed later.
Beverly Davis (Davis, 2004), a professor of Organizational Leadership in the School of
Technology at Purdue University, pointed out that possessing soft engineering skills

referred to Augustine as the combination of leadership skills, soft skills and engineer-
ing skills, will help in the transition from student to professional. These soft skills are
often regarded as unimportant in an engineering discipline which is heavily reliant
on math and science. As the Program Chair for the ASEE Manufacturing Division,
11
she found out the need for the following skills in an initial job of the engineering
discipline, which are discussed below (Davis, 2004):
• Communication—An ability to communicate effectively.
• Creativity—An ability to apply creativity in the design of systems, compo-
nents, or processes appropriate to program objectives.
• Respect for diversity—A respect for diversity and a knowledge of
contemporary professional, societal and global issues.
• Ethics—an ability to understand professional, ethical, and social
responsibilities.
• Lifelong Learning—A recognition of the need for, and an ability to engage
in lifelong learning.
• Team Membership—An ability to function effectively on teams i.e a team
with complementary skills committed to a common purpose, performance goals,
and approach for which they hold themselves mutually accountable.
Communication
Is extremely important because of the growing complexity of systems and the new
cross-functional teams in engineering. Many employers have numerous reasons for the
need of great communication skills such as the ability to explain what an individual is
doing throughout a project to people who are not engineers. Employers also require
12
communication skill in order to get people involved in the process, and also possess
the ability to work in the early stages of a project and obtain feedback from various
teams impacted by the potential changes (Davis, 2004).
In summary, since “ successful leaders work hard to make [relationship–building]
look effortless” (Nyman, 2006), communication is a tool used to achieve such a success.

Davis (2004) noted that “a recent study conducted with 301 former engineering grad-
uates from Southern Illinois University–Carbondale, . . . found that listening was the
most important non-technical skill needed to function in team–based work environ-
ments. While decision–making ranked second, verbal communication was ranked
third in perceived importance for graduate skills.” To show the importance of com-
munication skill, Dr. Jerry Bischof, director of nuclear engineering for Dominion
Resources visited an engineering school for an on–campus interview to fill ten posi-
tions. He discovered that 50% of the one–hundred resum´es were rejected for lack of
communication skills (Davis, 2004).
Creativity
Employers expect new graduates to be innovative and creative. The reason is because
engineers will need to lead “. . . creative consensus–building tasks regardless of the dis-
cipline.” Since teamwork is the norm, creativity will be required for any engineering
position in today’s global workforce. For example, if a manufacturing engineer grad-
uate is involved with the production of goods, the generation of knowledge and the
creative skills needed to generate new knowledge allows for manufacturing to compete
13