lawrence technological universitys), the 12-item soar profile, and the nine-item team collaboration...
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Lawrence Technological University
College of Management
An Evaluation of the Relationship among Emotional Intelligence,
SOAR, and Collaboration: Implications for Teams
Presented in partial fulfillment of the requirements
for the degree of
Doctor of Business Administration
John D. Cox
2014
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© COPYRIGHT BY
John D. Cox
2014
All Rights Reserved
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LAWRENCE TECHNOLOGICAL UNIVERSITY
AN EVALUATION OF THE RELATIONSHIP AMONG EMOTIONAL
INTELLIGENCE, SOAR, AND COLLABORATION: IMPLICATIONS
FOR TEAMS
by
John D. Cox
Master of Business Administration, Lawrence Technological University, 1993
Bachelor of Science Electrical Engineering, Lawrence Technological University, 1986
Dissertation Submitted to the
Graduate Faculty of the College of Management
in Partial Fulfillment of the Requirements for the Degree of
DOCTOR OF BUSINESS ADMINISTRATION
DISSERTATION COMMITTEE CHAIR: Matthew Cole, Ph.D.
COMMITTEE MEMBERS: Jacqueline Stavros, D.M., and Patricia Castelli, Ph.D.
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Abstract
There is a need to develop a climate of collaboration in today’s business culture
due to the rapid expansion of a global environment of open communication, cooperative
work, and an expanded consideration of consumer markets. In order to improve
collaboration at all levels of the organization, it is essential that professionals acquire
emotional intelligence (EI)—the ability to develop awareness and management of
emotions in themselves and others. Research suggests that EI has the ability to impact
performance outcomes in organizations, in particular those in which successful
negotiation, cohesion, and collaboration is desired. Furthermore, it is important that
teams collaborate from a strengths, opportunities, aspirations, and results (SOAR)-based
perspective that maximizes collaborative strategies that are inclusive.
The purpose of this dissertation was to evaluate the relationships between EI,
SOAR, and collaboration among a sample of professionals either actively working in
teams or who have had recent experience working in teams. A sample of 308 participants
completed the 16-item Work Group Emotional Intelligence Profile-Short Form (WEIP-
S), the 12-item SOAR Profile, and the nine-item Team Collaboration Questionnaire.
This study used a quantitative cross-sectional design with moderating and mediating
variables to test the prediction of collaboration by EI, the moderation of the EI-
collaboration relationship by team role, team type, and time in teams, and the mediation
of the EI-collaboration relationship by SOAR. Data analysis using multiple linear
regression and structural equation modeling (SEM) with bootstrapped confidence
intervals found EI was a significant predictor of collaboration, the impact of EI on
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collaboration was moderated by team role, team type, and time in teams, and SOAR
mediates the effect that EI has on collaboration.
This study has implications for teams and team members working collaboratively.
First, creation of the Team Collaboration Questionnaire, an original rapid assessment tool
developed in this study, has implications for the reliable and valid measurement of
collaboration. Second, by showing that EI growth improves elements of collaboration
related to integrating, compromising, and communication, this study recommends
methods to improve EI abilities in team members that may ultimately improve team
effectiveness, such as improving ability to be more effective at integrating ideas, seeking
compromise, and encouraging open and effective communication. Third, by testing
moderating variables, this study found that the impact of EI on collaboration is
maximized when teams are comprised of leaders, when teams are virtual, and when
experience with teams is greater than one year. Lastly, this study found SOAR
functioned as a partial mediating variable, suggesting that a framework for strategy based
on the strengths and aspirations of team members may explain how EI impacts team-
based collaboration.
Recommendations for future research include studying the relationship between
trait and ability-based measures of EI via a longitudinal study that focuses on EI growth
and its effect on collaboration. Future research should also study the impact of EI on
team-based collaboration using objective rather than self-report measures of
collaboration, such as observation of collaboration by independent observers. Finally,
future research should seek to clarify the distinction between partial and full mediation
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that were found in this study in order to determine other variables that may explain how
EI impacts team-based collaboration.
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Dedication
This dissertation is dedicated to Grant and Elaine.
May you continue to cultivate a passion for accomplishment, life-long learning, and
personal growth in yourselves and others.
With pride in you, Dad.
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Acknowledgements
Don and Sandy Cox
In gratitude for your unwavering support and inspiration throughout my academic career.
For facilitating the means to reach these academic achievements, the encouragement
when the future wasn’t so bright, and never losing faith in what I could become.
Thank you.
Deborah Cox
For all the days when we would have preferred doing something else. For the late dinners
after class, the early breakfast before class, and your patience with the other frequent and
unanticipated dissertation priorities. For sharing your pride in me, and the motivation to
live life after the dissertation.
Thank you.
Dissertation Committee
Thank you also to my dissertation chair, Dr. Matthew Cole and my committee members,
Dr. Jacqueline Stavros and Dr. Patricia Castelli for your support and guidance throughout
the dissertation journey.
Lawrence Technological University
An institution founded and dedicated to the practical success of its students, LTU has
consistently provided exemplary faculty in the Colleges of Management and Engineering.
I am proud to say I received a BSEE, MBA, and DBA from LTU.
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Table of Contents
ABSTRACT ........................................................................................................................ V
DEDICATION ................................................................................................................ VIII
ACKNOWLEDGEMENTS .............................................................................................. IX
TABLE OF CONTENTS .................................................................................................... X
LIST OF TABLES ......................................................................................................... XIV
LIST OF FIGURES ...................................................................................................... XVII
CHAPTER 1 INTRODUCTION ......................................................................................1
Background to the Study .................................................................................................3
Problem Statement ..........................................................................................................4
Purpose of the Study .......................................................................................................5
Research Variables ..........................................................................................................6
Research Questions and Hypotheses ...............................................................................8
Significance of the Study ................................................................................................9
Overview of the Research Methodology.......................................................................10
Limitations of the Research ..........................................................................................11
Definitions of Key Terms..............................................................................................13
Organization of Discussion ...........................................................................................15
CHAPTER 2 LITERATURE REVIEW .........................................................................18
Introduction ...................................................................................................................18
Emotional Intelligence ..................................................................................................18
Theory. .....................................................................................................................19
Relevance to hypothetical model. ............................................................................21
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Framework. ..............................................................................................................24
The emotionally intelligent individual. ....................................................................33
The emotionally intelligent leader. ...........................................................................35
Emotional intelligence and teamwork. .....................................................................41
Emotional intelligence and collaboration. ................................................................41
Measures of emotional intelligence. .........................................................................42
Collaboration .................................................................................................................48
Theory. .....................................................................................................................48
Relevance to hypothetical model. ............................................................................49
Collaboration and leaders. ........................................................................................51
Collaboration and integration. ..................................................................................53
Collaboration and compromise. ...............................................................................57
Collaboration and communication. ..........................................................................58
Improving collaboration through the development of emotional intelligence. ........59
Measures of collaboration. .......................................................................................62
SOAR ............................................................................................................................67
Theory. .....................................................................................................................67
Relevance to hypothetical model. ............................................................................70
Measures of SOAR ...................................................................................................71
Summary .......................................................................................................................73
CHAPTER 3 RESEARCH METHODOLOGY ..............................................................77
Introduction ...................................................................................................................77
Research Design ............................................................................................................77
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Research Questions and Hypotheses .............................................................................78
Research Variables ........................................................................................................79
Population and Sample ..................................................................................................81
Measures .......................................................................................................................82
Pilot Study .....................................................................................................................83
Data Collection Procedure ............................................................................................85
Data Analysis ................................................................................................................86
Descriptive statistics. ................................................................................................87
Psychometric properties ...........................................................................................87
Inferential statistics. .................................................................................................88
CHAPTER 4 RESULTS .................................................................................................89
Introduction ...................................................................................................................89
Demographic Characteristics of the Sample .................................................................90
Reliability and Validity .................................................................................................96
Intercorrelations Between Study Variables .................................................................105
Descriptive Statistics ...................................................................................................107
Emotional Intelligence (EI). ...................................................................................107
Collaboration. .........................................................................................................113
SOAR. ....................................................................................................................118
Hypotheses Testing Results for H1 .............................................................................125
Hypotheses Testing Results for H2 .............................................................................136
Hypotheses Testing Results for H3 .............................................................................139
CHAPTER 5 DISCUSSION .........................................................................................144
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Introduction .................................................................................................................144
Summary of Results and Discussion ...........................................................................144
Implications for Practice and Recommendations ........................................................154
Recommendations for Future Research ......................................................................166
Study Limitations ........................................................................................................169
Summary .....................................................................................................................170
REFERENCES ................................................................................................................172
APPENDIX A ..................................................................................................................187
Certificate of Training .................................................................................................187
APPENDIX B ..................................................................................................................188
IRB Letter of Approval ...............................................................................................188
APPENDIX C ..................................................................................................................189
Informed Consent ........................................................................................................189
APPENDIX D ..................................................................................................................190
Survey Instrument .......................................................................................................190
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List of Tables
Table 2.1 Summary of Common Measures of Emotional Intelligence (EI) ..................... 44
Table 2.2 Summary of Common Measures of Collaboration in Business Journals ......... 63
Table 2.3 Strategic Inquiry—Appreciative Intent: Inspiration to SOAR ......................... 70
Table 4.1 Characteristics of Sample by Gender, Age, Ethnicity, and Education ............. 93
Table 4.2 Characteristics of Sample by Industry, and Position ........................................ 94
Table 4.3 Characteristics of Sample by Team Size, Team Membership, Team Type, Team
Role, and Time Working in This Particular Team ............................................................ 95
Table 4.4 Characteristics of Sample by Team Role, and Time Involved in Teams (When
Working in Team-Based Activities in General) ............................................................... 96
Table 4.5 Reliability and Validity of the WEIP-S (Workgroup Emotional Intelligence
Profile – Short Version, 16-items) .................................................................................... 98
Table 4.6 Reliability and Validity of the Team Collaboration Questionnaire (15-items,
and 14-items) .................................................................................................................... 99
Table 4.7 Reliability and Validity of the Team Collaboration Questionairre (9-items) . 102
Table 4.8 Reliability and Validity of the SOAR Profile (20-items) ............................... 104
Table 4.9 Reliability and Validity of the SOAR Profile (12-items) ............................... 105
Table 4.10 Intercorrelations Between Study Variables .................................................. 106
Table 4.11 Mean and SD of Emotional Intelligence and its Four Constitutive Factors
across Gender, Age, Ethnicity, and Education ............................................................... 108
Table 4.12 Mean and SD of Emotional Intelligence and its Four Constitutive Factors
across Industry, and Position .......................................................................................... 109
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Table 4.13 Mean and SD of Emotional Intelligence and its Four Constitutive Factors
across Team Size, Team Membership, Team Type, Team Role, and Time Working in
This Particular Team ....................................................................................................... 111
Table 4.14 Mean and SD of Emotional Intelligence and its Four Constitutive Factors
across Team Role, and Time Involved in Teams (When Working in Team-Based Activities
in General) ...................................................................................................................... 113
Table 4.15 Mean and SD of Collaboration and its Three Constitutive Factors across
Gender, Age, Ethnicity, and Education .......................................................................... 114
Table 4.16 Mean and SD of Collaboration and its Three Constitutive Factors across
Industry, and Position ..................................................................................................... 115
Table 4.17 Mean and SD of Collaboration and its Three Constitutive Factors across Team
Size, Team Membership, Team Type, Team Role, and Time Working in This Particular
Team ............................................................................................................................... 117
Table 4.18 Mean and SD of Collaboration and its Three Constitutive Factors across Team
Role, and Time Involved in Teams (When Working in Team-Based Activities in General)
......................................................................................................................................... 118
Table 4.19 Mean and SD of SOAR and its Four Constitutive Factors across Gender, Age,
Ethnicity, and Education ................................................................................................. 120
Table 4.20 Mean and SD of SOAR and its Four Constitutive Factors across Industry, and
Position ........................................................................................................................... 121
Table 4.21 Mean and SD of SOAR and its Four Constitutive Factors across Team Size,
Team Membership, Team Type, Team Role, and Time Working in This Particular Team
......................................................................................................................................... 123
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Table 4.22 Mean and SD of SOAR and its Four Constitutive Factors across Team Role,
Time Involved in Teams (When Working in Team-Based Activities in General) ......... 124
Table 4.23 Collaboration Regressed on EI Alone (EI Predicting Collaboration) ........... 125
Table 4.24 Collaboration Regressed on EI (EI predicting collaboration controlling for
age, ethnicity, and education) ......................................................................................... 127
Table 4.25 Collaboration Regressed on SA (SA predicting collaboration) .................... 128
Table 4.26 Collaboration Regressed on SM (SM predicting collaboration) .................. 129
Table 4.27 Collaboration Regressed on AO (AO predicting collaboration) .................. 130
Table 4.28 Collaboration Regressed on MO (MO predicting collaboration) ................. 131
Table 4.29 Collaboration Regressed on SA, SM, AO and MO ...................................... 132
Table 4.30 Integrating Regressed on EI (EI predicting integrating) ............................... 133
Table 4.31 Compromising Regressed on EI (EI predicting compromising) .................. 134
Table 4.32 Communication Regressed on EI (EI predicting communication) ............... 135
Table 4.33 Hieararchical Regression of Collaboration on EI and Team Role ................ 137
Table 4.34 Hieararchical Regression of Collaboration on EI and Team Type ............... 138
Table 4.35 Hieararchical Regression of Collaboration on EI and Time in Teams ......... 138
Table 4.36 Mediation of the Effect of Emotional Intelligence on Collaboration through
Strengths, Opportunities, Aspirations, and Results (Full Construct) Background Factors
......................................................................................................................................... 141
Table 4.37 Mediation of the Effect of Emotional Intelligence on Collaboration through
Strengths, Opportunities, Aspirations, and Results Background Factors ....................... 142
Table 5.1 Summary of Practical Recommendations ....................................................... 162
Table 5.2 Personalized Summary Assessment Example: EI, Collaboration and SOAR 166
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List of Figures
Figure 1.1 Hypothetical Model of the Study: SOAR Mediating the Impact of Emotional
Intelligence on Collaboration .............................................................................................. 7
Figure 2.1 The SOAR Framework .................................................................................... 68
Figure 3.1 Hypothetical Model of the Study: SOAR Mediating the Impact of Emotional
Intelligence on Collaboration ............................................................................................ 81
Figure 4.1 SOAR Mediating the Effect of EI on Collaboration ..................................... 141
Figure 4.2 SOAR and its Constitutive Factors Mediating Collaboration ....................... 143
Figure 5.1 Model of the Study: SOAR Mediating the Impact of Emotional Intelligence on
Collaboration with Demographic Moderating Variables ................................................ 147
Figure 5.2 Team Role as a Moderator of the Relationship between EI and Collaboration
......................................................................................................................................... 151
Figure 5.3 Team Type as a Moderator of the Relationship between EI and Collaboration
......................................................................................................................................... 152
Figure 5.4 Time in Teams as a Moderator of the Relationship between EI and
Collaboration................................................................................................................... 153
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 1
Chapter 1 Introduction
Successful teamwork requires more than the intelligence of team leaders and team
members—it requires consideration of all participants engaged in the team process. The
proposition is that leaders of the future with emotional intelligence (EI) will be more
adept in promoting collaboration among teams and team members. EI provides active
support of the collaborative process, and as EI is developed throughout the collaborative
team, support of a common goal grows and team effectiveness increases (Xavier, 2005).
Emotional intelligence is defined as the capacity to perceive, reason about and
recognize the meaning of emotions, to effectively regulate and manage emotions, and to
problem-solve and act on them so as to promote emotional and intellectual growth
(Mayer, Salovey, & Caruso, 2004). EI is also defined as a set of emotion processing
abilities that lead to improving social interactions. These emotion processing abilities are
awareness of own and others’ emotions, emotional facilitation, emotional understanding,
and management of own and others’ emotions (Mayer & Salovey, 1997). While other
models of emotional intelligence vary from this (e.g., Goleman, 1995), the common point
they share is a focus on emotional awareness and emotional management as core abilities.
In understanding how emotional intelligence works in teams, the focus is on abilities
related to one’s own emotions and dealing with other people’s emotions (Jordan &
Lawrence, 2009).
Emotional intelligence is composed of several factors, or abilities such as self-
awareness (awareness of own emotions), self-management (management of own
emotions), social-awareness (awareness of others’ emotions), and relationship-
management (management of others’ emotions) (Mayer & Salovey, 1997). However, it
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 2
is not clear which of the EI abilities are viewed as most important for collaboration in
teams. An individual’s strengths-based strategic thinking capacity from the SOAR
framework (Strengths, Opportunities, Aspirations, and Results) may also be one of the
mechanisms by which EI has a significantly positive impact on collaboration. If EI
involves awareness of one’s own and others’ emotions, SOAR may help to characterize
the mechanism of how this awareness of emotions impacts collaboration. Awareness and
management of own and others’ emotions has closeness to Appreciative Inquiry and
inclusion which are the central philosophical tenets of SOAR.
Wolff and Koman (2008) emphasize the impact that emotionally competent
leaders have on organization development and positive performance outcomes: “Leaders
who are emotionally intelligent are essential to developing a climate where employees are
encouraged to perform to the best of their ability” (p. 59). In addressing the potential
impact that EI has on leadership, this dissertation evaluated the relationship between
emotional intelligence (EI) and collaboration, and determined which components of EI
promote collaboration in teams. It also considered SOAR as a mediating variable to help
characterize the mechanism of how EI (awareness and management of own and others’
emotions) impacts collaboration in teams.
Methodologically, this dissertation conducted an empirical investigation of EI and
its contribution to collaborative outcomes utilizing a cross-sectional design. A sample of
professionals who were either actively engaging in teamwork or who have engaged in
teamwork in the past within their organization completed a self-report survey comprised
of an existing measure of EI, and a measure of collaboration uniquely developed for this
study. Additionally, the survey measured an individual’s strengths-based strategic
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 3
thinking capacity from the SOAR framework (Strengths, Opportunities, Aspirations, and
Results) in order to determine the role that SOAR plays in mediating the relationship
between EI and collaboration. This dissertation is intended to provide scholars and
practitioners recommendations for improving collaboration among individuals working in
teams.
Background to the Study
The framework of emotional intelligence (EI) has been defined and refined over the
last ten years, and a majority of interest in the literature centers on the assessment and
development of EI abilities and their application to positive outcomes in leadership and
teamwork (Goleman, 2006). There is a growing body of literature seeking to advance the
measurement of EI via rapid self-report assessment instruments for individuals and teams
in order to investigate the link between EI and outcome variables that have implications for
collaboration. For example, studies by Moore and Mamiseishvili (2012), and Troth,
Jordan, and Lawrence (2012), have investigated the relationship between EI and group
cohesion, and EI and social cohesion, respectively. In both of these studies, team
cohesiveness is positively related to collaboration and team effectiveness (Dailey, 1978).
Therefore, there has been interest among researchers in business and management to
investigate the potential relationship between EI and collaboration.
One aspect of collaboration that is important for increasing team effectiveness is
supporting collaborative strategies that are inclusive and draw upon the potentials and
expertise of team members and their commitment to sharing and exchanging knowledge
(Shaw & Lindsay, 2008). In light of the need for collaborative strategies that are inclusive,
the SOAR framework was included in this study due to its ability to promote an inclusive
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 4
approach that builds the capacity for strategic thinking and planning (Cole & Stavros,
2013). At the heart of the SOAR framework is an inclusive approach that promotes team
members to frame strategy from a strengths-based perspective utilizing the team’s unique
strengths, assets, networks, resources, and capabilities (Cooperrider, Whitney, & Stavros,
2008).
This study reviewed the current state of research on EI, some of the widely used
self-report assessment measures of EI and collaboration, and conducted empirical research
to characterize the relationship between EI and collaboration within teams. SOAR was
evaluated as a mediating variable to characterize what may be one of the mechanisms by
which EI has a significantly positive effect on collaboration. An essential component of
the dissertation was to explain the theory and development of EI for the purposes of
extending its measurement, assessment, and analysis within the context of collaborative
teams.
Problem Statement
In multi-national organizations, the rapid, and essentially real-time
communication afforded by the world-wide-web has increased consumers’ access to
international markets and manufacturers of all kinds who are capable of engaging in an
endless array of expansive thought and ideas (Gereffi, 2001). Through virtual
communication and virtual collaboration, the Internet has played a prominent role in
location becoming largely irrelevant in business, and the for-profit, non-profit, and
academia circles of today must address the consequences of communication occurring
without boundaries. As globalization increases, the business landscape is shifting to a
culture in which efficient communication and collaboration are key factors in
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 5
organizational success. In fact, “collaboration is widely recognized as a mechanism for
leveraging competitiveness and thus increasing survivability in turbulent market
conditions” (Romero, Galeano, & Molina, 2009, p. 4691). Thus, modern business
cultures are finding that there is a need to develop a climate of collaboration due to the
rapid expansion of a global environment of open communication, cooperative work, and
an expanded consideration of consumer markets (Jassawalla & Sashittal, 1998). In order
to maintain a competitive pace in this environment, it is essential that professionals
acquire EI in order to develop awareness and management of emotions in themselves and
others to improve collaboration at all levels of the organization (Gohm, 2004).
Furthermore, it is important that teams collaborate from a perspective that maximizes
their strengths-based approach to strategic thinking and planning to facilitate team
effectiveness (Bright, Cooperrider, & Galloway, 2006).
Purpose of the Study
Individuals have an opportunity to recognize that interactive, codependent, and
collaborative relationships are manifested in communication intended to produce a
positive result. With an influential and cooperative intent in collaboration, leaders with
EI skills and abilities have the capacity to establish an emotional connection with
followers who may overcome resistance to produce meaningful change (Groves, 2006).
Emotional intelligence (EI) and the application of EI abilities to recognize, understand,
and use emotional information about oneself and others has led to positive outcomes in
leadership (Anand & Udayasuriyan, 2010; Blattner & Bacigalupo, 2007; Boyatzis, 2007),
and are seen to be increasingly important to an individual's ability to be socially effective
and engaging in team collaboration (Kerr, Garvin, Heaton, & Boyle, 2006). Within this
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 6
context, the purpose of this dissertation was to evaluate the link between EI and
collaboration outcomes in teams, to characterize the EI abilities that contribute to
collaboration, and to investigate the mediating role that SOAR (i.e., strengths-based
strategic thinking and planning capacity) has on the relationship between EI and
collaboration among team members.
Research Variables
Emotional intelligence (EI) exists within a framework of multiple abilities and
competencies (cf. Goleman, 2006), and knowledge and practice of these competencies
can be a life-long journey. Similar to Intelligence Quotient (IQ), emotional
intelligence—often referred to as Emotional Quotient (EQ)—involves personal growth
and a commitment to practice. For example, EI involves self-awareness and self-
management of one’s own feelings, and social awareness and management of what others
are feeling (Dulewicz & Higgs, 2000). Leaders and team members learning the EI
competencies typically practice self-awareness and self-management; self-awareness,
social awareness, and relationship management are common threads explored by
researchers and individuals intending to expand their understanding of the EI
competencies.
Collaboration in the scholarly literature is most commonly discussed in terms of
team building and team integration, cooperative work relationships that foster negotiation
and comprise, group cohesiveness, and effective communication (Aram & Morgan, 1976;
Quoidbach, & Hansenne, 2009; Rahim, 1983a, 1983b; Thomson, Perry, & Miller, 2009;
Whitaker, 2009). Collaboration is also discussed in the context of strategy and strategic
thinking (Gray, 1985), and strengths-based strategic thinking may have an impact on
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 7
collaboration in teams due to the relationship between group cohesiveness and positive
attitudes (Lott & Lott, 1965). The relationship between EI and collaboration, and SOAR
as a mediating variable was evaluated in this study with a cross-sectional research design
and quantitative data for the purpose of helping leaders and team members understand the
EI factors that promote positive collaboration outcomes.
Figure 1.1 presents the hypothetical model for this study. According to the model,
EI, which has been derived from the Mayer and Salovey (1997) model of EI in a research
study by Jordan and Lawrence (2009), EI in teams is comprised of four factors—
awareness and management of own emotions, and awareness and management of others’
emotions. EI is an independent variable (IV) that impacts the dependent variable (DV),
collaboration, which is comprised of three factors—integrating, compromsing, and
communication.
Figure 1.1 Hypothetical Model of the Study: SOAR Mediating the Impact of Emotional
Intelligence on Collaboration
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 8
To explore the impact of variables that could moderate the impact of EI on
collaboration, demographic characteristics (such as gender, age, position, and previous or
current participation in teams) were included in the model as moderators (MOD). In
consideration of variables that could mediate the indirect effects of EI on collaboration, a
construct used for framing a strengths-based approach to strategic thinking, SOAR, was
included in the model as a mediator (MED). According to Baron and Kenny (1986),
“Moderator variables specify when certain effects will hold, mediators speak to how or
why such effects occur” (p. 1176). Therefore, this study proposed that various
demographic characteristics will serve as moderators, and SOAR will serve as a mediator
of the impact that EI has on collaboration.
Research Questions and Hypotheses
People engaged in cooperative work seek to advance their mutual interests
(Whitaker, 2009); however, would individuals working in teams be in a better position to
advance their cooperative work if they adopted EI in both theory and practice? Are EI
competencies differentially related to collaboration? For example, are there differences
in the impact that emotional self-awareness and self-management, and awareness and
management of other’ emotions may have on collaboration? Are there any variables that
influence EI and its impact on collaboration and may help to explain the mechanism by
which EI affects collaboration? For example, are there certain demographic
characteristics that moderate the potential impact of EI on collaboration, and are there
certain mediators, such as (i.e., SOAR), that help to explain the impact that EI has on
collaboration?
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 9
The following four research questions were posed in this empirical study of
emotional intelligence and its relationship to collaboration:
Q1. Is there a relationship between emotional intelligence and collaboration?
Q2. Are there differences in the contribution of the emotional intelligence
abilities awareness of own emotions, management of own emotions, awareness of others’
emotions, and management of others’ emotions to collaboration?
Q3. Are there any demographic characteristics that moderate the impact
emotional intelligence may have on improved collaboration outcomes?
Q4. To help understand a potential mechanism for why EI may have an impact
on collaboration, does the SOAR framework for strengths-based strategic thinking,
planning, and leading mediate the impact that EI may have on collaboration?
The following three hypotheses were tested to answer the research questions:
H1. Emotional intelligence is related to collaboration such that EI has a positive
impact on collaboration.
H2. The impact of emotional intelligence on collaboration is moderated by
participants’ demographic characteristics.
H3. The SOAR framework mediates the relationship between emotional
intelligence and collaboration.
Significance of the Study
In traditional EI research, theoretical development of the construct and its
assessment have been primarily organized around individual EI abilities and/or the
individual’s personal level of EI competency within distinct EI domains. Currently, there
is a growing focus on the application of EI to such real-world issues as team-based
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 10
collaboration and collaborative outcomes (e.g., Blattner & Bacigalupo, 2007; Farh, Seo,
& Tesluk, 2012; Troth et al., 2012). This dissertation intends to contribute to that
interest, and advance the scholarly literature to understand EI and its impact on
collaboration.
The significance of this study is in four areas. First is the contribution to the
theoretical development of EI by utilizing an existing and widely acceptable individual EI
assessment tool to incorporate the benefits of EI to team-based applications. Second is
conducting new scholarly research on the link between EI and collaboration. Third is
investigating the moderating and mediating effects in EI research (i.e. SOAR and
demographic variables). Fourth is offering practical recommendations suitable for
practitioner adoption.
Overview of the Research Methodology
The research methodology for this study was a quantitative cross-sectional design
with moderating and mediating variables. The independent variable, EI, was tested as a
predictor of the dependent variable, collaboration, using linear regression inferential
statistics. Demographic characteristics, such as industry type, leadership experience, and
team experience were tested as moderators via significant interactions between EI and the
demographic characteristics in predicting collaboration in a linear regression. Finally, the
variable SOAR was tested as a mediator by looking for an indirect effect between EI and
collaboration in a mediation path model using structural equation modeling (SEM).
The population for this study were professionals actively working in teams or
those who have had recent experience working in teams. A sample of these individuals
were invited to participate in an electronic survey designed to assess their demographic
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 11
characteristics, EI, collaboration, and SOAR. EI was measured by the 16-item WEIP-S
(Work Group Emotional Intelligence Profile-Short Form; Jordan & Lawrence, 2009) to
establish areas of respondent competency in four EI abilities helpful for understanding
how EI works in teams (Mayer & Salovey, 1997): awareness of own emotions,
management of own emotions, awareness of others’ emotions, and management of
others’ emotions. The measure for assessing collaboration was the nine-item Team
Collaboration Questionnaire, an original measure of collaboration adapted from Aram
and Morgan (1976), and Rahim (1983a, 1983b), which measures three factors of self-
reported collaborative activity among members of a team: integrating, compromising, and
communication. Finally, strengths-based strategic thinking was measured by the 12-item
SOAR Profile (Cole & Stavros, 2013), a self-report measure of strategic capacity from
the SOAR framework. The measures were selected for their ability to rapidly identify EI
competency in teams, collaboration, and SOAR most critical to achieving positive
outcomes in collaboration.
Limitations of the Research
The limitations of this research concern the main construct of the study, emotional
intelligence (EI), and its relationship to the outcome and mediator variables in the study,
collaboration and SOAR, respectively. Specifically, while EI is an appealing, yet
occasionally controversial construct, the idea that an individual’s intelligence and
capability, normally quantified via the IQ, may have an equivalent emotional component
quantified by the EQ, is controversial. Being a fairly recent theory in the relevant
literature, the idea of EI does face some scrutiny and potential limitations. Although
studies have shown that EI can be a useful predictor and enabler of improved
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 12
performance (e.g., Sy, Tram, S., & O’hara, 2006), it has been argued that there is little if
any incremental validity to justify its relative importance over cognitive abilities which
are routinely measured via the IQ (Van Rooy, Viswesvaran, & Pluta, 2005).
There are also disjointed conclusions over what actually constitutes the EI
construct. One viewpoint claims that EI is nothing more than a renaming of existing
constructs of intelligence and emotional stability, while others dismiss its importance
because of inconsistency in its definition and lack of reliable and agreed upon assessment
models (Van Rooy et al., 2005). The basis for this argument rests in the definition of
intelligence narrowly scoped to cognitive intelligence—or inherently personal traits and
characteristics. Accordingly, one of the limitations of this study acknowledge that while
EI may be investigated from a variety of perspectives and possibilities, the construct was
studied from a framework of effective teamwork and positive outcomes in collaboration
mediated by SOAR.
Collaboration is also not without its challenges—it requires more than merely the
establishment of a group of individuals who are directed to engage in achievement of a
common goal. Factors that may have a negative impact on collaboration and team
success include size of the group, ability to meet and work together in person (as opposed
to working in a virtual team), whether any of the team members know each other, and the
disparity in expertise. These challenges may be overcome through EI and the application
of EI abilities that have been found to be important for collaboration in teams (e.g.,
Borges, Kirkham, Deardroff, & Moore, 2012; Troth et al., 2012). Additionally, these
challenges may be overcome through the SOAR framework and its application to
strengths-based strategic thinking and planning. This dissertation acknowledges that
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 13
while collaboration is investigated from a variety of perspectives, this study focused on
factors that represent characteristics of collaboration (i,e., integrating, compromising, and
communication).
This study has limitations related to the use of self-report data in general, as self-
report methodology has inherent limitations of validity of the data. Another limitation
may include the potential for common-method bias. Common-method bias may occur
when data for the independent variable comes from the same source as the dependent
variable. Ideally, team based collaboration would be measured by independent observers.
Finally, since research participants estimated the collaborative outcomes of their
teamwork, as well as their capacity for strengths-based strategic thinking and planning
(i.e., SOAR) through the use of two novel assessment tools—the Team Collaboration
Questionnaire and the SOAR Profile—the psychometric properties of these assessment
instruments were evaluated using tests of reliability and validity prior to data analysis.
Definitions of Key Terms
The following key terms are used throughout this dissertation.
Appreciative Inquiry (AI). The search for the best in people, their
organizations, and the relevant world around them (Cooperrider, Whitney, & Stavros,
2008).
Collaboration. The degree to which study participants rate integrating,
compromising, and communication among co-workers in a team (Aram & Morgan, 1976;
Rahim, 1983a, 1983b).
Emotional Intelligence (EI). “The capacity to reason about emotions, and of
emotions to enhance thinking. It includes the abilities to accurately perceive emotions, to
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 14
access and generate emotions so as to assist thought, to understand emotions and
emotional knowledge, and to reflectively regulate emotions so as to promote emotional
and intellectual growth. Emotional intelligence from this theoretical perspective refers
specifically to the cooperative combination of intelligence and emotion” (Mayer,
Salovey, & Caruso, 2004, p. 197).
Emotional Intelligence Abilities. EI abilities are interchangeably referred to in
the literature as domains, clusters, dimensions, skills, and competencies (Bar-On, 1997;
Dulewicz & Higgs, 2000, 2004; Goleman, 1998, 2006; Mayer et al., 2004; Salovey &
Mayer, 1990). An individual’s awareness, management, and application of EI abilities
can enhance his or her effectiveness with tasks that involve interpersonal relationships.
Fundamentally, the framework of EI followed in this dissertation is the four abilities
helpful for understanding how EI works in teams (Mayer & Salovey, 1997): awareness of
own emotions, management of own emotions, awareness of others’ emotions and
management of others’ emotions.
Emotional Quotient (EQ). Considered the level of one’s emotional intelligence,
EQ is often used interchangeably with EI.
Intelligence Quotient (IQ). A quantitative index of one’s verbal and nonverbal
intelligence.
Mediating Variable (MED). “A mediator is defined as a variable that explains
the relationship between a predictor and an outcome. In other words, a mediator is the
mechanism through which a predictor influences an outcome variable” (Frazier, Tix, &
Barron, 2004, p. 116). The MED in this study was SOAR.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 15
Moderating Variable (MOD). “A moderator is a variable that alters the
direction or strength of the relation between a predictor and an outcome” (Frazier et al.,
2004, p. 116). The MODs in this study were three demographic characteristics, team
role, team type, and time in teams.
SOAR (Strengths, Opportunities, Aspirations and Results). “SOAR enables
individuals, organizations, business units and teams to create strategic plans in new ways
by addressing the following key concern of most organizations: ‘How do we sustain the
value, momentum, energy and commitment to see the plan implemented and achieve the
desired results of the planning effort?’” (Stavros, 2013, p. 12).
Organization of Discussion
This dissertation is organized into five chapters. The first chapter provided an
introduction and background to the research study investigating the relationship between
emotional intelligence and collaboration. Chapter One defined the problem statement,
purpose, and significance of the study. An introduction to the research methodology was
presented, and the chapter concluded with the study research questions and the
hypotheses tested to answer them.
Chapter Two provides a comprehensive investigation into the existing literature
on emotional intelligence, EI’s relationship to collaboration and team-based activities,
and some of the more widely used measures of EI. Similarly, the theoretical foundations
of SOAR and relevance to the hypothetical model are discussed. The SOAR Profile
(Cole & Stavros, 2013), a unique measure of SOAR, is introduced as the measurement
instrument used for investigating the mediating effects of SOAR on the relationship
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 16
between EI and collaboration. Finally, the extant literature on collaboration is presented,
followed by relevance to the hypothetical model, and existing measures.
In this literature review, applications of the study constructs are considered in the
presence of team-based activities. Beyond the theoretical framework of each construct
and relevance to the hypothetical model, their relationships with team-based activities are
investigated. These include the emotionally intelligent individual, the emotionally
intelligent leader, EI and teamwork and EI and collaboration. For each study construct,
measurement instruments are reviewed. SOAR, being a relatively new construct, is
specific in its theoretical framework, and measures of SOAR are limited to the SOAR
Profile (Cole and Stavros, 2013). To consider if SOAR is one mechanism of action by
which positive collaboration outcomes can be achieved in the presence of EI, SOAR is
specifically investigated as a potential mediator of the relationship between EI and
collaboration. Finally, collaboration is similarly described in theory, relevance and
measurement. Extensions to leadership and teamwork are studied, with a specific
emphasis on the collaboration factors of integration, compromise, and communication.
Chapter Three provides the research methodology used in this study. The study
sample, organization of the survey instruments, procedures used, and analysis methods
are definitively described. The research variables are identified and the subsequent
analysis methods planned for Chapter Four are introduced. These include the descriptive
statistics of the study variables, the psychometric properties of the survey instruments,
and the inferential statistics used for hypothesis testing.
Chapter Four presents the research study results, and begins with a review of the
research questions and the hypotheses tested to answer them. Descriptive statistics are
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 17
used to summarize the detailed participant responses to various demographic
characteristics and each of the study variables EI, SOAR, and collaboration. Each of the
study constructs also included survey questions related to their constitutive factors. For
EI, this included self-awareness, self-management, awareness of others’ emotions, and
management of others’ emotions. SOAR included Strengths, Opportunities, Aspirations
and Results. Finally, collaboration included the factors integrating, compromising, and
communication.
Chapter Five focuses on the interpretation of results, followed by a discussion of
study implications and recommendations. Results of hypothesis testing, moderation and
mediation analyses are interpreted, and discussed in terms of implications for
practitioners. The chapter closes with a brief summary, study limitations, and suggestions
for future research.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 18
Chapter 2 Literature Review
Introduction
The literature review is strategically organized around the practical definitions
and research of the study variables, emotional intelligence (EI), collaboration, and
SOAR. For each variable, the underlying theory and relevance to the study model are
presented, including a review of EI and its potential relationship to collaboration.
Concepts describing collaboration and relevant extensions are explored to review the
scope of research on collaboration. In consideration of a strengths-based strategic
thinking and planning style that may mediate the relationship between EI and
collaboration, the SOAR framework is evaluated to the extent it may help to explain the
mechanism by which EI impacts collaboration. The chapter also includes a review of
conflicts and controversies in recent literature related to the theoretical development of
EI.
In this study, the measurement of the study variables required careful
consideration in accurately selecting measures well correlated with the study variables.
The prominent measurement tools in the literature for EI, SOAR, and collaboration were
reviewed and evaluated for their applicability to the hypothetical model. Each following
section on EI, SOAR, and collaboration concludes with the measurement tool selected,
and the reasons why it was chosen.
Emotional Intelligence
Emotional intelligence (EI), the first of three study constructs used in this study,
functions as the independent variable (IV) in the hypothetical model (see Figure 1.1).
The following sections present the theoretical foundations of EI, relevance to the
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 19
hypothetical model, and the framework used in this study (i.e., an ability-based model
consisting of four factors, self-awareness (SA), self-management (SM), awareness of
others’ emotions (AO), and management of others’ emotions (MO). The literature on EI
is subsequently explored in areas applicable to EI’s relationship with team based
collaboration: EI in individuals and leaders, teams, and collaborative teamwork. The
section concludes with a review of the mainstream measures used in assessing levels of
EI in individuals.
Theory. Emotional Intelligence (EI) as a fairly recent theory first labeled and
explained in the mid-1990s by the pioneering research of two main teams of theorists,
Daniel Goleman and Richard Boyatzis, and Peter Salovey and John Mayer (Boyatzis,
Goleman, & Rhee, 2000; Goleman, 1995; Goleman, Boyatzis, & McKee, 2002; Salovey
& Mayer, 1990), EI is broadly defined as a construct representing a set of competencies
for identifying, processing, and managing emotions (Zeidner, Roberts, & Matthews,
2008). EI is an evolving extension of the quantitative measures of intelligence, e.g.,
intelligence quotient (IQ). Research on EI began at the end of the 20th
century and gained
popularity with the public through Goleman’s (1995) book, Emotional Intelligence: Why
It Can Matter More than IQ. A widely accepted definition of EI is rooted in the
pioneering efforts of Goleman, Mayer, Salovey and Caruso:
[Emotional intelligence is] the capacity to reason about emotions, and of emotions
to enhance thinking. It includes the abilities to accurately perceive emotions, to
access and generate emotions so as to assist thought, to understand emotions and
emotional knowledge, and to reflectively regulate emotions so as to promote
emotional and intellectual growth. Emotional intelligence from this theoretical
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 20
perspective refers specifically to the cooperative combination of intelligence and
emotion. (Mayer et al., 2004, p. 197)
The primary theory of EI utilized in this dissertation is based on the four EI
abilities of Mayer and Salovey (1997): awareness of emotions (own and others),
management of emotions (own and others), emotional understanding, and emotional
facilitation (generation of emotions). These abilities are further refined for understanding
how EI works in teams by focusing on self- and other-awareness and management of
emotions; in the context of teams, EI is generally considered to be a value added
competency to various aspects of individual and group performance, namely
collaboration (Jordan & Troth, 2004).
Research in the field of intelligence proposes that intelligence extends beyond the
traditional quantitative index of IQ to incorporate knowledge of one’s emotions, and
knowledge of the emotions of self and others contributes to higher levels of individual
intelligence and subsequent performance outcomes in leadership, organization
development, negotiation, collaboration, and positive communication (Caruso, Mayer, &
Salovey, 2004). The essence of EI for teams and leadership is self-knowledge of
emotions, e.g., EI involves self-awareness and self-management of one’s own feelings,
and social awareness and management of what others are feeling (Dulewicz & Higgs,
2000; Mayer & Salovey, 1997). Keys to a leader’s success are improved self- and social-
awareness, relationship management, and team building. Thus, leadership requires more
than cognitive intelligence, it requires consideration and awareness of both self and
others. The importance that emotional awareness of self and others has on positive
relationship outcomes is one of the benefits of EI for understanding emotions in
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 21
organizations (Gabriel & Griffiths, 2002) and for building team process effectiveness and
collaboration (Jordan, Ashkanasy, Härtel, & Hooper, 2002).
Unlike IQ which focuses on verbal and nonverbal cognitive abilities, EI focuses
on awareness, management, and understanding of self-emotions, and the emotions of
others. EI also involves the ability of an individual to self-regulate emotions and to use
emotions to make good decisions, and to act and interact effectively and empathetically.
EI is the basis for personal self-confidence, integrity, knowledge of strengths and
weaknesses, resilience in times of adversity, self-motivation, perseverance, and the ability
to get along well with others. EI is the primary source of personal energy, authenticity,
and aspiration, and activates innermost values in life, transforming them from thoughts to
actions. EI helps people to recognize, readily acknowledge, respond appropriately, and
value core feelings in themselves and others. EI spurs creative genius and intuition,
shapes trusting relationships, clarifies important decision making, and guides people to
consider creative possibilities and breakthrough solutions (Nwokah & Ahiauzu, 2010).
Relevance to hypothetical model. Today’s business climate is characterized by
limited face-to-face interactions. Each personal interaction that occurs must be as
successful as possible. Increasing the value of personal interactions requires more than
intelligence, it requires understanding of emotions in leaders and teams, i.e.,
understanding of EI. Research suggests that EI has the ability to impact performance
outcomes in organizations, in particular those in which successful negotiation, cohesion,
and collaboration is desired (Kerr et al., 2006). Collaboration is a process of social
interaction, where one’s ability to influence the emotional climate and behavior of others
can strongly influence performance outcomes. As an emerging leadership attribute, EI
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 22
competency is seen to be increasingly important to an individual's ability to be socially
effective and therefore more adept at enabling successful collaborative outcomes.
Within a collaborative team, individuals who are emotionally self-aware may
have a positive attitude that contributes to effective conflict management and resolution
of disagreements, i.e., emotional self-awareness improves one’s ability to negotiate,
compromise, and seek the best alternatives that yield positive results (Xavier, 2005). Just
as the personal development of EI improves an individual’s ability to manage change, the
development of EI among team members improves the team’s ability to manage
change—as EI competencies are developed throughout the collaborative team, the more
effective the team can become. This is especially important because it allows teams to
dispel norms and develop new and more prosperous cultures supporting a common goal
(Xavier, 2005). Furthermore, in helping a team to attain desired goals, effective leaders
have substantial levels of EI as well as cognitive intelligence. As Nwokah and Ahiauzu
(2010) note:
Under the guidance of an emotionally intelligent leader, people feel a mutual
comfort level. They share ideas, learn from one another, make decisions
collaboratively, and get things done as they form an emotional bond that helps
them stay focused even amid profound change and uncertainty. (p. 159)
Researchers have been studying aspects of EI for some time; however, there is
still much that is unclear about the nature, assessment, and application of EI. Numerous
case studies on the application of EI and its impact on individuals and organizations have
been reviewed (Dulewicz, & Higgs, 2000). Case studies that describe EI competency as
a benefit to the scenario under study have critics who debate over whether EI is a valid
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 23
construct “because it is not a form of intelligence and because it is defined so broadly and
inconclusively that it has no intelligible meaning” (Locke, 2005, p. 425).
Criticism is also presented on the measurement and predictive power of EI in
influencing leadership and group effectiveness (Singh, 2008).
By asserting that leadership is an emotional process, Goleman [as one of the
primary EI proponents] denigrates the very critical role played by rational
thinking and actual intelligence in the leadership process. Given all the add-ons
to the concept proposed by Goleman, any associations between leadership
effectiveness and an emotional intelligence scale that included these add-ons
would be meaningless. (Locke, 2005, p. 430)
The basis for these critical views begins with an assertion that it is arbitrary to attach the
word ‘intelligence’ to what are simply habits or skills. For example, the ability to
monitor one’s emotions refers to the EI competency of self-awareness rather than an
intelligence per-say. One of the conclusions reached by these critics is that “there is no
such thing as actual emotional intelligence, although intelligence can be applied to
emotions” (Locke, 2005, p. 430).
Some researchers say that EI is not viable as a scientific construct, is inadequately
defined, defined inconsistently between researchers, and represents a continuation of a
long line of discredited research into social intelligence that lacks consistency in
application with no appropriate measure (Ashkanasy & Daus, 2005). In response to this
harsh criticism, proponents see EI neither as some new form of social intelligence, nor a
substitute for intellectual intelligence, but rather as a valid and viable construct for
organizational behavior researchers and practitioners to use in their efforts to understand
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 24
and predict behavior in order to improve individual and organizational performance
outcomes. Indeed, there is growing evidence that research on EI comprises an exciting
and developing area of research in organizational behavior and leadership competency
(e.g., Anand & Udayasuriyan, 2010; Blattner & Bacigalupo, 2007; Rosete & Ciarrochi,
2005).
Framework. The framework of EI used in this dissertation follows the four
abilities of EI useful for understanding how EI works in teams (Mayer & Salovey, 1997):
self-awareness (awareness of own emotions), self-management (management of own
emotions), social-awareness (awareness of others’ emotions), and relationship-
management (management of others’ emotions). While this framework is centered on the
theoretical work of Mayer and Salovey (1997), it overlaps with the theoretical
perspectives put forth by the primary researchers in the field of EI (Bar-On, 1997;
Dulewicz & Higgs, 2000, 2004; Goleman, 1998, 2006; Mayer et al., 2004; Salovey &
Mayer, 1990). Collectively, these EI researchers conceptualized EI from a framework of
four, five, or seven abilities that share a common focus on the core abilities of emotional
awareness and emotional management. An individual’s awareness and management of
these core EI abilities can enhance his or her effectiveness with tasks that involve
interpersonal relationships. Since motivation is required in managing emotions, the
domain of self-motivation has been addressed in the EI literature, and it will also be
reviewed in this overview of the framework of EI.
Self-Awareness. Leaders competent in self-awareness are aware of their
weaknesses and are comfortable in admitting them, view constructive criticism
positively, and recognize their emotions and the effect they have in the collaborative
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 25
environment (Xavier, 2005). As the keystone of EI, self-awareness refers to recognizing
one’s emotions and feelings as they occur. Self-awareness involves monitoring feelings
from moment to moment, and offers crucial insight to self-understanding. People with
greater certainty about their feelings are better pilots of their lives and have a definite
sense of how they feel about personal decisions (Goleman, 2006). Self-awareness is
comprised of three components: emotional self-awareness, accurate self-assessment, and
self-confidence.
Emotional self-awareness refers to recognizing one’s own emotions and their
effects on us and others. Emotions drive behaviors, and a leader’s ability to consider the
potential overwhelming importance his or her own emotions may have on decision
making is important. This awareness does not mean that the emotionally aware leader
has to detach emotions from leadership, but rather that they be understood, and in control
(Xavier, 2005). People with this competence know which emotions they are feeling and
why, realize the link between their feelings and what they think, do and say, recognize
how their feelings affect their performance, and have a guiding awareness of their values
and goals (“Emotional competence framework,” 1998).
Accurate self-assessment refers to knowing one’s strengths, limits, and
weaknesses. A leader can be slightly aware of the emotions of others if he does not have
an accurate view of his own (Xavier, 2005). People with an accurate self-assessment are
aware of their strengths and weaknesses, learn from experience through reflection, are
open to feedback, new perspectives, continuous learning, and are able to show a sense of
humor and perspective about themselves (“Emotional competence framework,” 1998).
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 26
Self-confidence refers to having a strong sense of one’s self-worth and abilities.
Leaders lacking in self-worth can appear weak and lacking in inspiration. The ability to
inspire and motivate followers is a desirable leadership attribute; self-confidence, if
genuine, can lead to improved leadership effectiveness (Xavier, 2005). People with this
competence present themselves with self-assurance, can voice unpopular views, and are
decisive in the presence of uncertainty and pressure (“Emotional competence
framework,” 1998).
Self-Management. Emotionally intelligent leaders recognize the importance of
creating a collaborative environment regulated with trust and equality, and are careful to
self-manage their emotions and resultant behavior accordingly. Followers quickly adopt
the optimism, enthusiasm, and inspiration of a leader demonstrating a genuine interest in
the shared success of the team. Self-management is comprised of seven components:
adaptability, emotional self-control, initiative, achievement orientation,
conscientiousness, innovativeness, and trustworthiness.
Adaptability refers to flexibility in handling change and dealing with changing
situations, emotional self-control refers to inhibiting emotions that are in contrast to
organizational norms and managing disruptive emotions and impulses (“Emotional
competence framework,” 1998; Xavier, 2005). People with adaptability can smoothly
handle multiple demands, can rapidly change and shift priorities, can adapt their
responses and tactics to fit changing circumstances, and can behave with flexibility in
how they see events ("Emotional competence framework," 1998). People with emotional
self-control manage their impulsive feelings well, stay composed, positive and
unflappable even in distressing times, and think clearly and stay focused under pressure.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 27
Having initiative in self-management refers to being proactive and operating with
a bias toward action that can be contagious. With achievement orientation, one’s ability
to self-manage their emotions involves striving to do better and coaching others to reach
their highest potentials (Xavier, 2005). Self-management also involves
conscientiousness, i.e., taking responsibility for personal performance. A person with
this competence keeps promises, meets commitments, holds themselves accountable for
meeting objectives, and is organized and careful in their work (“Emotional competence
framework,” 1998).
Innovativeness is a component of self-management that involves individuals
being comfortable with, and open to, new ideas and new information. People with this
competence seek out fresh ideas from a variety of sources, entertain original solutions to
problems, generate new ideas, and take fresh perspectives and risks in their thinking
(“Emotional competence framework," 1998). With trustworthiness, the ability to
demonstrate integrity and consistency with emotions and behavior is an important
component of self-managing emotions (Xavier, 2005). People with this competence act
ethically, build trust through their reliability, admit their own mistakes and confront
unethical situations in others, and take principled stands even if they are unpopular
("Emotional competence framework," 1998).
Awareness of others’ emotions. Effective leaders and individuals are not only
aware of their own emotions but those of their team. Empathy, trust, and integrity are
critical competencies in collaborative effectiveness, particularly in consideration of the
diverse backgrounds and cultures that may be present in collaborative teams. People with
high social awareness can assess situations from other points of view which contribute to
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 28
improved comradery, trust, and confidence in the capabilities of the collaborative team.
This also leads to improved employee satisfaction, decreased turnover, and confidence in
leadership (Xavier, 2005). Individuals who exhibit empathy are more attuned to the
subtle social signals that indicate what others need (Goleman, 2006). This makes them
better at meeting those needs, and exhibiting support for others’ abilities and reaching of
their highest potentials. Social awareness is comprised of five components: empathy,
service orientation, organizational and political awareness, developing others, and
leveraging diversity.
Empathy refers to understanding others and taking an active interest in their
concerns. Effective leaders value the ideas and futures of their followers (Xavier, 2005).
People with this competence are attentive to emotional queues and listen well, show
sensitivity, understand others’ perspectives, and are willing to help others based on an
understanding of their needs and feelings ("Emotional competence framework,” 1998).
Service orientation refers to anticipating, recognizing, and meeting customers’
needs. Leaders who consider themselves as a resource to their followers, and offering of
themselves to help meet objectives gain the respect and camaraderie of their followers
(Xavier, 2005). People with this competence understand customers’ needs and match
them to services, seek ways to increase customer satisfaction and loyalty, gladly offer
assistance, and grasp a customer’s perspective (“Emotional competence framework,”
1998).
Organizational and political awareness refers to establishing meaningful
relationships with customers, within work teams, and the organization (Xavier, 2005).
People with this competence read a group’s emotional currents and power relationships,
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 29
detect crucial social networks, understand the forces that shape views and actions of
others, and accurately read situations and organizational and external realities
(“Emotional competence framework,” 1998).
Developing others involves sensing what others need in order to develop and
improve their abilities. People with this competence acknowledge and reward others’
strengths, accomplishments, development needs, offer useful feedback, mentor, give
timely coaching, and offer assignments that challenge and grow a person’s skill
(“Emotional competence framework,” 1998).
Leveraging diversity refers to the cultivation of opportunities through diverse
workgroups. People with this competence respect and relate well to others from different
backgrounds, are sensitive to group differences, see diversity as an opportunity, and
challenge bias and intolerance ("Emotional competence framework,” 1998).
Management of others’ emotions. Effective leaders work constructively with
others and understand the importance of moving their collaborative teams toward desired
outcomes (Xavier, 2005). Handling relationships is in large part the skill of managing
emotions in others, and the EI competency of relationship management encompasses
abilities that mediate popularity, leadership, and interpersonal effectiveness. Leaders and
individuals who are effective at relationship management do well at tasks that rely on
interacting smoothly with others—they are social stars (Goleman, 2006). Relationship
management is comprised of eight components: inspirational leadership, being a change
catalyst, conflict management, influence, communication, teamwork and collaboration,
building bonds, and collaboration and cooperation.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 30
Inspirational leadership is the component of relationship management that refers
to inspiring and guiding behavior of others intellectually and emotionally (Xavier, 2005).
People with the competence of managing others’ emotions articulate and arouse
enthusiasm for a shared vision and mission, step forward to lead where needed regardless
of position, guide the performance of others, and lead by example ("Emotional
competence framework,” 1998).
The relationship management component refers to the ability to initiate and
manage change, and of having a positive attitude inclusive of the impact change has on
others (Xavier, 2005). People with this competence recognize the need for change and
remove barriers, challenge the status quo acknowledging the need for change, champion
positive change and involve others in its pursuit, and model the change expected of others
(“Emotional competence framework,” 1998).
Conflict management refers to the resolving of disagreements, and being able to
negotiate compromise and seek the best alternatives for the team (Xavier, 2005). The
competence of managing others’ emotions has application to essential leadership
characteristics that support successful teams, such as conflict management, influence,
open communication, and collaboration. The ability to manage conflict with diplomacy
and tact brings disagreements into the open, encourages debate and open discussion, and
orchestrates win-win solutions ("Emotional competence framework," 1998).
Influence refers to the ability of gaining the agreement of others. Leaders avoid
autocratic dictation, yet remain influential in decision making that yields positive results
(Xavier, 2005). People with the EI competence of managing others’ emotions are skilled
at influence and persuasion, arrange presentations that appeal to the listener, use indirect
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 31
influence to build consensus and support, and orchestrate dramatic events to effectively
make a point ("Emotional competence framework,” 1998).
Communication is another component of managing others’ emotions, and
effective leaders use communication to send clear and convincing messages. Leaders
with strong communication skills are effective in compromise, deal with difficult issues
straightforwardly, listen well, seek mutual understanding and welcome information
exchange whether the news is good or bad ("Emotional competence framework," 1998).
Teamwork and collaboration are components of managing others’ emotions based
on building relationships with a shared vision and synergy in pursuing collective goals
(Xavier, 2005). When teams and team members engage in teamwork and collaboration
they work with others toward shared goals. By managing the emotions of others, leaders
have the ability to promote teamwork and collaboration by modeling team attributes such
as respect, helpfulness, and cooperation, drawing all team members into active and
enthusiastic participation, building team identity and cooperation, protecting the
reputation of the team and team members, and sharing credits and success. They also
balance task focus with attention to relationships, and share plans, information and
resources while promoting a friendly and cooperative climate ("Emotional competence
framework,” 1998).
Another important component involved in effectively managing the emotions of
others is building bonds. Building bonds refers to the nurturing of instrumental
relationships, i.e., relationships that are instrumental in collaboration. Leaders and
individuals who build bonds are essentially cultivating and maintaining informal
networks, seeking out relationships that are mutually beneficial, building rapport, and
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 32
maintaining open communication to keep others in the loop ("Emotional competence
framework,” 1998).
Finally, collaboration and cooperation are components of relationship
management that refers to working with others toward shared goals. Leaders who are
effective at promoting collaboration and cooperation among teams and team members
maximize the EI competence of managing others’ emotions. Additionally, they balance
task focus with attention to relationships, collaboration, sharing of plans, information and
resources while promoting a friendly cooperative climate within the team or organization
("Emotional competence framework,” 1998).
The foregoing framework of EI, based on an ability-based model useful for
understanding how EI works in teams, is the theoretical foundation for which this
dissertation is based. As put forth by Mayer and Salovey, (1997), self-awareness, self-
management, awareness of others’ emotions, and management of others’ emotions are
competencies necessary for team effectiveness. These four competencies are what Jordan
and Lawrence, (2009) set out to measure with their Workgroup Emotional Intelligence
Profile. Together, this dissertation seeks to determine if aptitude and betterment of these
abilities may lead to improved collaboration and ultimately team effectiveness.
Self-Motivation. Managing emotions in support of a goal is essential for self-
motivation, attentiveness, and creativity. Delaying gratification and stifling
impulsiveness underlies accomplishment of every sort. People with this skill tend to be
more productive and effective in whatever they undertake (Goleman, 2006). Self-
motivation is comprised of four components: achievement drive, commitment, initiative,
and optimism.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 33
Achievement drive refers to the motivation to improve or meet a standard of
excellence. People with this competence are results-oriented, exhibit a high personal
drive to meet their objectives and standards, set challenging goals and take careful risks,
pursue information to reduce uncertainty, and find ways to do better and improve their
performance. While achievement drive motivates leaders toward goal attainment,
commitment seeks to align the goals of the group, team or organization. People with this
competence readily make personal or group sacrifices to meet organizational goals, find a
sense of purpose in their larger objectives, use the group’s core values in guiding decision
making, and actively seek out opportunities to fulfill the group’s mission ("Emotional
competence framework,” 1998).
Initiative refers to a readiness to act on opportunities. People with this
competence are ready to seize opportunities, pursue goals beyond expectations, cut
through red tape when necessary to get jobs done, and mobilize others through unusual,
enterprising efforts. While motivation, achievement drive, and initiative seek the ideals
of accomplishment, optimism guides individuals toward a positive view of life and the
future. Optimistic leaders also demonstrate persistence in pursuing goals despite
obstacles and setbacks, operate from hope of success rather than fear of failure, and see
setbacks as due to manageable circumstance rather than a personal flaw (“Emotional
competence framework”, 1998). Without the element of optimism in a leader’s self-
motivation, followers are unlikely to embrace the pessimistic views therein (Xavier,
2005).
The emotionally intelligent individual. EI improves one’s ability to initiate and
manage change. Within a collaborative team, having a positive attitude inclusive of the
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 34
impact change has on others contributes to effective conflict management and resolving
of disagreements. Thus, EI affords an individual the ability to negotiate compromise and
seek the best alternatives that yield positive results (Xavier, 2005).
“Emotional intelligence refers to an ability to recognize the meaning of emotion
and their relationships, and to reason and problem solve on the basis of them” (Marques,
2007, p. 645). Without EI, an individual might lack the crucial quality of reading
between the lines and listening to the unspoken. Awareness and application of EI
competencies have the potential to facilitate problem solving, ease conflict resolution,
and bring collaborative teams to a higher state of being. EI involves the capacity to
perceive emotions, interpret the information expressed in emotions, and manage emotions
effectively (Marques, 2007). When emotions are positive, individuals experience a
broadening of their momentary thought-action reflex. This theory suggests that an
individual expressing positive emotion will have a wider array of response considerations
for a particular scenario. In terms of enabling improved collaboration outcomes,
“positive emotions broaden habitual modes of thinking or acting” (Cameron, Dutton, &
Quinn, 2003, p. 166).
EI, particularly positive EI, has the potential to equip an individual with cognitive
abilities to effectively process difficult decision making and conflict. A growing body of
research suggests that conflict can be beneficial, and experiencing conflict helps an
individual to be emotionally activated (Bodtker, Jameson, 2001). Maintaining self-
awareness and self-control of these activated emotions relies on the cognitive abilities of
EI. Experiencing positive emotions has several benefits, such as helping to down-play
negative emotional arousal, improving one’s ability to cope with adversity, and
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 35
transforming individuals into more resilient, socially integrated, and capable versions of
themselves. Positive emotions also help to curb organizational conflict by promoting
constructive interpersonal engagement. “Positive emotions can transform organizations
because they broaden people’s habitual modes of thinking, and in doing so make
organization members more flexible, empathic, creative, and so on” (Cameron et al.,
2003, p. 174). “The bottom-line message is that people should cultivate positive
emotions in themselves and those around them, not just as an end-state in themselves, but
also as a means to achieving psychological growth and improved psychological and
physical well-being over time” (Fredrickson, 2004, p. 1367).
Individuals who embrace an environment that cultivates and exploits their
positive emotions will grow to levels not ordinarily achieved. This optimal level of
functioning will provide them with a means for sustaining optimal performance in
themselves and their organization. When an environment taps an individual’s ideas and
promotes empowerment and teamwork, sustainable change action is possible throughout
the collaborative organization (Bramson & Buss, 2002). As individuals develop their
capacity, or ability to evaluate and manage emotions in themselves and others, team
effectiveness will improve. This dissertation identified those particular emotion
processing abilities most important to achieving improved collaboration and team
effectiveness.
The emotionally intelligent leader. Leadership is a process of social interaction
where the leader's ability to influence the emotional climate and behavior of followers
can strongly influence performance outcomes. Leadership consists of such dimensions as
supervision, delegation, discipline, and power utilization, and refers to the ability to
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 36
influence, motivate and enable others to contribute to the effectiveness and success of
their organization (Kilburg, 2000). As an emerging leadership attribute, EI competency
is seen to be increasingly important to an individual's ability to be socially effective (Kerr
et al., 2006). The application of the EI competencies to recognize, understand, manage,
and use emotional information about oneself and others contributes to and impacts
effective performance by leaders and managers (Boyatzis, 2007). In order to maximize
leadership effectiveness and the ability to influence others, leaders and managers should
possess the knowledge and skills of EI (Palmer, Walls, Burgess, & Stough, 2001).
Furthermore, “leaders who are emotionally intelligent are essential to developing a
climate where employees are encouraged to perform to the best of their ability” (Wolff &
Koman, 2008, p. 59).
Regardless of the leadership model, leadership effectiveness is enhanced by
leaders possessing EI (Higgs, 2003). EI competency at the individual, team, and
organization levels are key to leaders of the future possessing leadership effectiveness.
Executives who are motivated to understand and adapt to change, and who are motivated
to assess themselves and their employees, EI fosters an emotional and intellectually
healthy environment necessary for successful leadership (Xavier, 2005).
Leaders without EI may be missing a valuable skill that effective leaders of the
future will possess. Emotionally intelligent leaders are likely to have followers who are
motivated to do their best because they feel enthusiastic, passionate, and believe in the
values of both the leader and themselves. EI can be a subtle, yet powerful competitive
advantage in the collaborative team’s ability to succeed as leaders with EI seek to
increase team competency in the EI abilities of self-awareness, self-management, social
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 37
awareness, and relationship management. “People high in emotional intelligence will
build real social fabric within an organization, and between an organization and those it
serves, whereas those low in emotional intelligence may tend to create problems for the
organization through their individual behaviors” (Mayer, Salovey, & Caruso, 2002, p. 4).
Since EI and leadership is seen to be increasingly important to team effectiveness,
determining the specific EI abilities uniquely important for leaders was an objective of
this dissertation.
A fundamental component of leadership is the development of sound decision
making, and emotions are essential for rational thought and reasoning leading to sound
decision making. EI competency plays a key role in determining leadership success, and
while often subtle, the influence of emotional competency on effective decision making
and positive interaction with others remains important in determining leadership
effectiveness. Macaleer and Shannon (2002) describe the important relationship between
leadership development and emotional awareness:
Anyone who has any role in working with organizations and their long-term
effectiveness should begin to understand how emotional intelligence can affect
leadership development. The idea is not to suppress emotions (because every
feeling has its value and significance), but to strike a balance between rational
thought and emotions. One of the keys to sound decision making is a greater
awareness of our emotions and those of others. (p. 10)
Application of EI can also be seen as a leader’s ability to effectively deal with
their interpersonal relationships. This connection is based on the idea that one explores
their emotions looking at such attributes as empathy, self-image, social skills, feelings,
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 38
flexibility, happiness, stress tolerance, optimism, assertiveness, and impulse control.
Followers need a sense of security, and the behaviors of the leader play a role in their
ability to feel secure. If the leader is not in control of his or her emotions, followers may
lose confidence and support for the leader. Conversely, if leaders have no understanding
or consideration of the feelings of followers, they will be less effective in maintaining
cohesion and team effectiveness. The objective is to strengthen and exploit the emotions
of the situation in order to accomplish a desired goal in a collaborative environment. In
essence one needs to know oneself along with specific tendencies as well as come to
know as quickly as possible the emotions of followers in order to have a quality
exchange. The ability to size up a given situation and act positively on it leads to a
desired advantage (Chrusciel, 2006). Ideally, EI is used such that emotional issues do not
detract from the leader’s effectiveness, or team's progress. In terms of performance
management, it is important for a leader to be able not only to deliver outputs, but also to
deal effectively with themselves and staff. Leaders higher on EI are more likely to
achieve business outcomes, and be considered as effective leaders by their subordinates
and direct manager (Rosete & Ciarrochi, 2005).
Typically emotions are viewed as too personal to be discussed at the workplace,
yet leaders who appreciate the impact emotions have on the workplace environment have
an advantage over those who ignore them (Xavier, 2005). Gardner and Stough (2002)
address the emotionally intelligent leader:
The ability to successfully manage emotions allows the leader to handle the stress
of the job, the frustrations, disappointments, and joys. Leaders who are able to
understand and manage their emotions and display self-control act as role models
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 39
for followers, enhancing the followers trust and respect for the leader. This
contagion is carried over to the collaborative team. The ability to manage
emotions and relationships permits the emotionally intelligent leader to
understand followers’ needs and to react accordingly. (p. 70)
Becoming an emotionally intelligent leader or team member who also has the
ability to be collaborative involves learning and trusting one’s own emotions, and
improving the personal qualities and skills in the awareness of others’ emotions. As
leaders of the future look to improve their competitive advantage, speed to market,
quality, and team effectiveness, application of EI competencies will enhance one’s ability
to recognize and control feelings, and to recognize those of other people and respond to
them constructively and skillfully (Mackenzie & Welch, 2005).
“Emotional expressivity skills allow visionary leaders to establish an emotional
connection with followers that may overcome resistance to produce meaningful
organizational change” (Groves, 2006, p. 578). Maintaining a competitive advantage
remains a torturous struggle of change and adaptation to shifting market, economic, and
regulatory conditions. Leaders want honesty, commitment, and trust from their
followers, but they also must exemplify these ideals. Leadership does not flourish in a
climate of targets, testing and suspicion - it requires trust. Trust that people will seek to
achieve within themselves a passion for their work (Mackenzie & Welch, 2005).
Emotionally intelligent leaders are thought to be happier and more committed to
their organization, achieve greater success, perform better in the workplace, take
advantage of and use positive emotions to envision major improvements in organizational
functioning, and use emotions to improve their decision-making. This instills a sense of
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 40
enthusiasm, trust, and cooperation in their employees through interpersonal relationships.
This is addressed by Gardner and Stough (2002):
Emotional intelligence enhances a leader’s ability to solve problems and to
address issues and opportunities facing them and the organization. A leader high
in emotional intelligence is able to accurately appraise how their followers feel
and use this information to influence their subordinate’s emotions, so that they are
receptive and supportive of the goals and objectives of the organization. Leaders
who are able to use emotions to guide decision-making are able to motivate
subordinates by engaging in activities facilitated by emotions, and are able to
encourage open-minded idea generation, decision-making and planning, because
they can consider multiple points of view. (p. 70)
Successful leaders who are able to manage positive and negative emotions within
themselves and within others are able to articulate a vision for the future, talk
optimistically, provide encouragement, stimulate thinking, encourage the expression of
new ideas, and intervene in problems before they become serious. Emotional
management may underlie the ability of the leader to be inspirationally motivating and
intellectually stimulating. The ability to identify and understand the emotions of others in
the workplace is important for leaders so that they can influence the feeling of
subordinates to maintain enthusiasm, productivity, and organizational effectiveness.
Given the extensively positive relationship between EI and leadership, and the
importance of leadership to team effectiveness, this study aimed to identify the specific
EI competencies and abilities critical for leaders to develop within themselves and their
collaborative teams.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 41
Emotional intelligence and teamwork. A team is a cohesive group of people
who collaborate in support of a common vision and aspirations (Katzenbach, 1998). EI
has gained popularity as an essential personal factor for effective teamwork since leaders
with high EI are successful in negotiating and resolving conflict (Anand & Udayasuriyan,
2010; Blattner & Bacigalupo, 2007). Modern business cultures reflect accelerated
changes in work force, impact of technology, industrialization, and globalization. People
currently need to function in a world vastly different from that of previous generations.
To function effectively in what are now inherently natural collaborative environments,
individuals and leaders working collaboratively require EI aptitude.
Research suggests that managers with high EI obtain results from employees that
are beyond expectations, while developing and using talents crucial for organizational
effectiveness (Chen, Jacobs, & Spencer, 1998). Effective managers steer their own
feelings, acknowledge the feelings of subordinates concerning their work situation, and
intervene effectively to enhance morale. Moreover, close to 90 percent of success in
leadership positions can be attributed to EI (Anand & Udayasuriyan, 2010). Therefore,
an environment for collaborative success is created when emotionally intelligent
leadership is combined with an emotionally intelligent team. Optimizing this relationship
for team effectiveness and collaboration necessitates the development of EI skills within
the collaborative team.
Emotional intelligence and collaboration. Collaboration involves sharing risks,
resources, and responsibilities in order to achieve a common goal that would not be
possible if attempted individually. Collaborative team members integrate themselves into
a collaborative culture which comprises an awareness of self and others, seeks a
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 42
willingness to adapt for the benefit of all, and demonstrates supportive and positive
behaviors to enhance the capabilities of others (Romero, et al., 2009). The importance of
teams developing EI and operating from an awareness of the EI competencies is
demonstrated by the team’s ability to dispel norms, and allows their respective
organizations to develop common collaborative goals that may contribute to an
organizational culture that is prosperous and successful (Xavier, 2005).
The link between EI and effective collaboration is demonstrated when the same
EI competencies that are displayed in strong leadership are displayed by teams, i.e., to
recognize, understand, manage, and use emotional information about oneself and others
(Boyatzis, 2007). Teams that develop and practice EI are likely to be effective with
collaboration because positive emotions reverberate through individuals as they
interact—positive emotions are contagious. When team members are aware of self and
others’ positive emotions, performance increases, when emotions are negative,
performance decreases and there is dissonance within the collaborative team (Xavier,
2005).
Measures of emotional intelligence. Several measures of EI are available to
researchers, and in general, the EI measures that are reviewed in the literature vary
widely in both content and method of assessment (Conte, 2005; McEnrue & Groves,
2006; Zeidner et al., 2008). Measures of EI provide information about an individual’s
level of EI using two approaches: measures based on abilities (i.e., EI competencies), and
measures based on traits. While EI abilities refer to those abilities related to emotions
(Salovey and Mayer, 1990), trait EI refers to emotion-related behavioral dispositions and
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 43
attributes (Petrides, 2011). Table 2.1 presents a comparison of some of the most common
measures of EI abilities and EI traits used in the literature.
The Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT; Mayer,
Salovey, & Caruso, 2002) is the prototypical ability-based self-report measure of EI in
which emotional awareness and emotional management are core abilities referenced
against expert and consensus opinion. The Emotional Competence Inventory (ECI;
Boyatzis et al., 2000) and the Bar-On Emotional Quotient Inventory (EQ-i; Bar-On,
1997) are self-report trait-based measures. The MSCEIT and EQ-i have a large number
of items, with 141 and 133-items respectively; the ECI has 72-items.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 44
Table 2.1 Summary of Common Measures of Emotional Intelligence (EI)
EI Measure Type Theoretical
Model
EI Dimensions and
Scales
Length
Mayer-Salovey-
Caruso Emotional
Intelligence Test
(MSCEIT)
Self-report
questionnaire
referenced
against
expert and
consensus
opinion
(Ability-based)
Salovey &
Mayer
(1990,
1997)
Perception, appraisal,
and expression of
emotion
Emotional facilitation
of thinking
Understanding and
analyzing emotional
information
Regulation and
management of
emotion
141
Items
Emotional
Competence
Inventory,
Version 2
(ECI-2)
Self-report
questionnaire
(Trait based)
Goleman
(1995,1998)
Boyatzis,
Goleman, &
Rhee
(1999)
Self-awareness
Self-management
Social awareness
Social skills
72
Items
Emotional
Quotient
Inventory
(EQ-i)
Self-report
questionnaire
(Trait based)
Bar-On
(1997)
Intrapersonal
Interpersonal
Adaptation
Stress management
General mood
133
Items
Trait Emotional
Intelligence
Questionnaire—
Short Form
(TEIQue-SF)
Self-report
questionnaire
(Trait based)
Petrides
(2009)
Well-being
Emotionality
Sociability
Self-control
30
Items
Work Group
Emotional
Intelligence
Profile-Short
Version (WEIP-S)
Self-report
questionnaire
(Ability-based)
Jordan &
Lawrence
(2009)
Awareness of own
emotions
Management of own
emotions
Awareness of others’
emotions
Management of
others’ emotions
16
Items
Note. Adapted from McEnrue and Groves (2006).
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 45
EI measures with considerably fewer numbers of items have been developed for
rapid assessment of EI within larger assessment batteries. For example, the Trait
Emotional Intelligence Questionnaire—Short Form (TEIQue—SF; Cooper & Petrides,
2010) is a 30-item self-report trait-based measure of EI, and the Workgroup Emotional
Intelligence Profile-Short Version (WEIP-S) scale (Jordan & Lawrence, 2009) is a 16-
item self-report questionnaire of EI abilities. Of the EI measures used in empirical
research, ability-based measures of EI, such as the MSCEIT and the WEIP-S have been
researched in team settings. The WEIP-S was selected for this dissertation in order to
measure team-based EI abilities.
MSCEIT (Mayer-Salovey-Caruso emotional intelligence test). The MSCEIT
(Mayer et al., 2002) is an ability-based self-report instrument designed to assess the four
EI abilities of Mayer and Salovey (1997) useful for understanding how EI works in
teams: self-awareness (awareness of own emotions), self-management (management of
own emotions), social-awareness (awareness of others’ emotions), and relationship-
management (management of others’ emotions). The MSCEIT has been used in team-
based studies; however, its considerable length of 141-items did not support practical use
in this study.
ECI (emotional competency inventory). The ECI (Boyatzis et al., 2000) is a self-
report trait-based measure of EI based on Goleman’s (1995, 1998) model of four EI
clusters: self-awareness, self-management, social awareness, and social skills (Cherniss,
2000). While useful in certain research settings as a peer-review instrument, the ECI is
not well suited for this study which seeks a self-assessment of EI abilities best suited for
teams.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 46
Bar-On’s EQ-i (emotional quotient inventory). The Bar-On EQ-i is often
referred to as one of the most widely used instruments in assessing EI, perhaps only for
the reason that it was one of the first attempts at creating an EI assessment tool and has
familiarity in the field due to its age (Macaleer & Shannon, 2002; Anand &
Udayasuriyan, 2010). The EQ-i self-report trait-based measure of EI is long (133-items),
takes about 45 minutes to complete, and doesn’t lend itself well to comparison - one
person’s EI assessment doesn’t necessarily imply higher EI compared to another.
Discriminating among the most intelligent people seems to be desirable by many, and
self-report measures like the Bar-On EQ-i are not generally accepted as an accurate way
of doing so. In particular with EI, how one feels on a particular day could influence how
questions are answered versus another day (Van Rooy et al., 2005). This remains a clear
limitation in demonstration, acceptance, and quantitative validity of the EI construct,
particularly in discussion relative to the Bar-On EQ-i. Bar-On however, defends the
ability to accurately provide an EI assessment and indicates that the term intelligence was
used to describe the collection of skills, competencies and abilities of an individual, and
emotional was added as a prefix to discriminate this intelligence from cognitive ability
(Van Rooy et al., 2005).
The EQ-i provides an assessment of five general categories of EI: interpersonal
EQ, intrapersonal EQ, stress management, adaptability, and general mood. These five
categories of EI consist of fifteen subscales which measure areas such as empathy,
independence and optimism which are considered to be certain facets of personality (Van
Rooy et al., 2005). This is the basis for the most common argument raised by critics of
EI, that it simply draws from different aspects of personality. The EQ-i was primarily
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 47
designed to assess those personal traits that enable improved emotional well-being for an
individual, not necessarily how the traits may affect or contribute to improved work-place
situations, or collaborative activities. Hence, the EQ-i was not selected for this research.
TEIQue—SF (trait emotional intelligence questionnaire—short form). Trait EI
refers to a set of emotional self-perceptions related to personality and emotional
experience, and the TEIQue—SF is a self-report questionnaire developed to
comprehensively evaluate trait EI domains rather than EI abilities (Cooper & Petrides,
2010). The TEIQue—SF, which was developed from the 144-item TEIQue (Petrides &
Furnham, 2006; Petrides, Pérez, & Furnham, 2003), covers 15 EI traits grouped in four
factors: well-being, emotionality, sociability, and self-control. Two items from each of
the 15 EI traits comprise the 30-item self-report questionnaire. Since the tool measures
EI traits rather EI abilities, it was not selected for use in the current study.
WEIP-S (workgroup emotional intelligence profile-short version). The
Workgroup Emotional Intelligence Profile-Short Version (WEIP-S) is based on abilities
vital during the interaction of team members (Jordan & Lawrence, 2009). The WEIP-S is
a 16-item self-report questionnaire aligned with the Mayer and Salovey (1997)
framework for EI which measures four EI abilities helpful for understanding how EI
works in teams: awareness of own emotions, management of own emotions, awareness of
others’ emotions, and management of others’ emotions. Each ability is measured by its
own subscale, and each subscale demonstrates high reliability (Cronbach’s alpha = 0.805
– 0.903). The WEIP-S is a short version of the Workgroup Emotional Intelligence
Profile (WEIP), a 27-item self-report measure of EI within a team context consisting of
items that were selected from an original item pool of 52-items (Jordan et al., 2002). The
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 48
WEIP was revised over six versions, and the WEIP-S is comprised of a selection of the
ability-based items listed in the WEIP-S (Jordan & Troth, 2004). The WEIP-S was
selected for this study based on its high reliability statistics for each of the four subscales
that measure EI abilities of individuals to work effectively with others in a team (Borges
et al., 2012; Moore & Mamiseishvili, 2012; Troth et al., 2012).
Collaboration
Collaboration, the second of three study constructs used in this study, functions as
the dependent variable (DV) in the hypothetical model (see Figure 1.1). The following
sections present the theoretical foundations of collaboration, relevance to the hypothetical
model, and the framework used in this study (i.e., a team-based model consisting of three
factors, integrating, compromise, and communication). The literature on collaboration is
explored relative to leadership, and introduces the objective of increasing collaboration
through EI growth. The section concludes with a review of the mainstream measures
used in assessing levels of collaboration in teams.
Theory. Collaborative relationships offer a unique opportunity to innovate in
uncertain conditions, and collaboration may prove most beneficial to organizations
undergoing change (Shaw & Lindsay, 2008). Precursors to successful collaboration
include trust, shared goals, and open communication (Hattori & Lapidus, 2004).
Fundamental in collaborative efforts is trust, and in business relationships trust indicates
the highest dynamic of relationships. While trust is essential for collaborative innovation
and collaborative success, the absence of trust creates significant barriers to
collaboration. As trust wanes, so do relationships, and consequently, any potential for
successful collaboration is diminished. Because collaboration involves taking
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 49
responsibility for the organization or team as a whole, the concerns of the team must
support the collective interests of the organization and must be aligned with the
individual (i.e., the individual refers to individual members of a team or organization
versus the team or organization as a whole). Trust is an extension of normal team
dynamics, and as the foundation of collaboration, trust facilitates group success and
achievement of a common goal.
In collaboration, the concept of leadership is unilaterally applied. Although the
collaborative team may identify a chairperson or leader by title, each and every team
member brings a particular set of skills and expertise. Through the interaction,
development and un-biased sharing of these unique skills, collaborative efforts can
produce positive outcomes in ways not ordinarily achievable. “Collaboration between
different organization and organizational parts is often critical for the accomplishment of
the common goal and is therefore an important factor that explains organizational
outcomes and performance” (Dietrich, Eskerod, Dalcher, & Sandhawalia, 2010, p. 63).
High quality characteristics of collaboration include fluency and openness of the
participants, adaptability, and a willingness to align efforts toward a common goal.
Alignment and activation of these characteristics contribute to knowledge integration
leading to otherwise unattainable learning and innovation, project success, and future
collaboration.
Relevance to hypothetical model. Primary elements linking collaboration to EI
are inclusion (Shaw & Lindsay, 2008), integration and compromise (Rahim, 1983a,
1983b), and communication (Aram & Morgan, 1976; Romero et al., 2009). Inclusion
draws upon the potential and expertise of individuals, the need for attention in managing
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 50
the complexity of collaboration, and the need for an ongoing commitment to knowledge
sharing in the development of collaborative strategies within a team (Shaw & Lindsay,
2008). Integration and compromise involve an active intent to support collaborative
strategies through the establishment of a common ground, unified strategies, and
integration of ideas (Rahim, 1983a, 1983b). Teams seeking compromise develop
supportive and positive behaviors to enhance the capabilities of others and to adapt for
the benefit of all (Romero et al., 2009). Communication involves information exchange
for mutual benefit among individuals and teams, aligning of efforts so that more efficient
results can be achieved, and sharing of resources to reach compatible goals (Aram &
Morgan, 1976).
The EI factors of self-awareness and self-management of emotions correlate with
compromise and integration in collaboration. Awareness and management of others’
emotions is a necessary influence in resolving conflict for the purpose of achieving
compromise in a collaborative environment (Mita & Debasis, 2008). Concern for self
and others promotes integration of ideas, sharing of resources, cooperation and inclusion
of all team members focused on shared goals (Romero et al., 2009). Further, additional
elements revealed in the literature essential to having a direct effect on the quality of
collaboration are communication, coordination, mutual support, aligned efforts, and
cohesion (Dietrich et al, 2010). While communication refers to open and efficient
information exchange and coordination refers to shared and mutual goals, mutual support
refers to willingness to help others and exhibiting the flexibility to do so. Aligned efforts
refer to alignment of contributions with expectations and priorities. Finally, cohesion,
which is the most important source of success for groups (Carron & Brawley, 2000), is
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 51
the extent to which members of a group like and trust one another, are committed to
accomplishing goals, and share group pride (Beal, Cohen, Burke, & McLendon, 2003).
The essence of this study is that the more cohesive a group, team, or organization is, the
greater the likelihood that the group, team, or organization will experience positive
collaboration.
A discussion on collaboration in the Harvard Business Review identifies eight
factors that contribute to the creation of collaborative teams that are productive and
innovative (Gratton & Erickson, 2007). Among these factors are leadership behaviors
among top executives indicative of EI and EI competencies, including building successful
relationships, modeling collaborative behavior, and enabling a strong sense of community
within the team of collaborative participants. The practices of the team leader support a
model where the elements of EI have an impact on collaboration. Specifically, success in
collaboration is strongly influenced by the extent that top leaders endorse EI, practice EI
competencies, invest in supportive social relationships, and demonstrate collaborative
behavior themselves.
Collaboration and leaders. Where leaders were once seen to control, plan, and
inspect the overall running of an organization, leadership roles are now seen to also
motivate and inspire others, to foster positive attitudes at work, and to create a sense of
contribution, importance, and collaboration with team members. During the last decade,
interpersonal skills have become integral to effective leadership and positive
collaboration outcomes (Palmer et al., 2001). The importance of EI lies in the obvious
but often ignored fact that the mood of the leader and how it impacts others on the team
are interrelated. EI is more than being happy or sad, it's the ability to effectively express
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 52
and manage one's emotions and relationships with others leading to a positive result
(Xavier, 2005).
The connection between leadership and collaboration suggests that improved
leadership outcomes are possible through a combination of facilitative, democratic, and
collaborative skills. This style of leadership runs contrary to the experience of many
administrators, particularly where hierarchical organizational structures are deeply
engrained in a company’s cultural base. A non-hierarchical leadership style where the
central theme is a network of individuals working together collaboratively requires, or at
least is recommended to exhibit behaviors of caring, building trust, and open sharing of
ideas in collaboration (Slater, 2005).
Recognizing the relationship between leadership and collaboration, Gratton and
Erickson (2007) have identified eight leadership behaviors that can guide teams to
collaborative success. First is by investing in signature relationship practices. This
behavior refers to executive support and investment in a commitment to collaboration,
e.g., open floor plans, shared and sufficient meeting locations, and other mechanisms to
enable open communication. Second is in modeling collaborative behavior. This refers
to senior executives who model collaborative behavior themselves while also
encouraging followers to do so. Third is creating a gift culture. This behavior involves
mentoring and coaching to help employees build the networks they need to work across
corporate boundaries. Fourth is by ensuring the requisite skills, which refers to having
the training or support of human resources and organizational development leaders that
teach employees how to build relationships, improve communication and resolve
conflicts. Fifth is by supporting a strong sense of community. This behavior involves
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 53
knowledge and management of team member emotions in order to help team members
experience a sense of community. Sixth is by assigning team leaders that are both task
and relationship oriented. This behavior is critical to building productive teams and is
important for ensuring that relationship orientation is fostered once team-based tasks are
underway. Seventh is building on heritage relationships, which involves creating teams
that contain some team members who already know and have experience with each other.
Eighth is understanding role clarity and task ambiguity, which refers to the knowledge
and management of clear role definitions within a collaborative environment that
supports individuality.
Collaboration and integration. Collaboration implies sharing risks and rewards
among team members acting as a joint entity in order to achieve common goals that
would not be possible if attempted individually. Collaboration is also recognized as a
mechanism for leveraging competitiveness in turbulent market conditions (Romero et al.,
2009). Successful collaboration also requires team member competence, a nurturing
climate, commitment, and relationships calling for an extraordinary degree of trust
among the participants (Hattori & Lapidus, 2004, p. 97). This level of trust and
relationship building can be enabled by a team of emotionally competent members. EI
involves thinking intelligently about emotions in group settings and using emotions to
think intelligently about groups and group performance (Druskatt & Wolff, 1999). EI is
thus personal as well as social, leading to certain behaviors concerning group
performance. These behaviors, whether positive or negative, depend in large part on how
emotions are interpreted. Understanding the personal and social impact these behaviors
have on collaboration is where the EI framework enters, and the more leaders understand
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 54
themselves and their employees, the more likely they are to lead their teams to successful
outcomes (Xavier, 2005). In this study, collaboration is comprised of three factors,
integration, compromise and communication. Integrating ideas involves the sharing of
opinions, listening, keeping an open mind, and being respectful of each other in the
interest of idea gathering.
EI has a strong impact on improving the leadership success of individuals and
increases the likelihood of a collaborative organization achieving its strategic and
collaborative goals. That way a win-win scenario can be achieved for both the individual
and the organization (Chrusciel, 2006). “As with emotionally intelligent leaders,
members who are emotionally intelligent form strong relationships and a solid team
support system” (Prati et al., 2003, p. 30). Further, team cohesion is closely aligned to
collaboration in terms of referring to the existence of the collaborative spirit between
team members (Hoegl & Gemuenden, 2001), and cohesiveness and collaboration are
each positively related to team success and group productivity (Carron & Brawley, 2000;
Dailey, 1977).
The ability to work collaboratively is becoming a core requisite in the global
economy, and therefore a further understanding of collaborative behaviors in terms of
their emotional content is warranted. Successful collaboration drives a style of leadership
that is more supportive and participative than directive, and demands behaviors that are
concerned with healthy interpersonal relationships as collaboration is essentially
emotional work. Action that supports collaboration is behavior that encourages
empowerment and valuing the capacity of individuals. This includes leading by example,
listening, sharing in leadership responsibility, openness in relationships, and the honest
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 55
sharing and disclosure of information. Valuing the capacity of individuals means more
than just listening, but to take their input and use it for improving the collaboration
process and related decision making. Team members need to embrace and exhibit an
advocacy for collaboration that promotes the beliefs, goals, and value of the collaborative
process (Slater, 2005).
Since collaboration has emerged as an integral component of working together in
new ways, workplace skills related to collaboration should also be developed. This
doesn’t mean necessarily that some new innovative working style is required, but rather
proper application of skills already available within the domains of EI. Of primary
importance to studying collaboration and the factors that impact collaboration is in
understanding the emotions of others, and allowing each member of a team or group to be
heard—this is supported by a firm foundation of emotional competency based on
empathy and taking an active interest in others for mutual understanding (Slater, 2005).
Emotional self-awareness is another crucial skill in collaboration. Self-awareness
relies on the ability of an individual to have a strong sense of self-worth, so as to be
confident in presenting new ideas. “Having the courage to speak out is an emotional
competency based on self-confidence; a dimension of self-awareness” (Slater, 2005, p.
329). Emotional self-awareness also means being aware of strengths and weaknesses,
where in a collaborative situation individuals recognize the strengths they bring to the
group, but also acknowledge when weaknesses exist.
“Relationships are the building blocks of collaboration” (Slater, 2005, p. 330).
Individuals and leaders that are adept at building relationships are more likely to succeed
as they share time and experiences together through open communication, trust, and
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 56
rising above an initial common ground. Relationships enable the development of key
competencies required for facilitation, reaching consensus, conflict resolution, team
building and problem solving in a shared context. Non-verbal behavior has also been
acknowledged as an effective measure for reducing conflict and promoting positive
relationships. The emotional nature of collaborative work appears to be important and
essential for successful collaboration, and as Macaleer and Shannon (2002) note,
effective work teams are cohesive, innovative, and supportive of its members:
When managers understand the competencies, and especially the emotional
intelligence capabilities of their team, they will have a better understanding of the
team’s strengths and developmental areas and will be in a better position to
maximize the effectiveness of the team. Understanding an employee’s emotional
intelligence skills will enable better decisions on career development programs,
saving countless dollars that are typically spent on training that does not advance
the capabilities of the individual. Any restructuring of an organization, whether to
acquire additional capabilities or reduce staff, should start with an understanding
of the existing makeup and talents of the employees. Otherwise you might
eliminate or waste important assets. (p. 17)
Emotionally intelligent individuals lend themselves more easily to the team
qualities of collaboration, innovation, and support, hence the inference that EI is essential
for effective team interaction and productivity. Additionally, team members high in EI
are likely to contribute to the overall EI of the group, recognize their roles in the team
structure, are more prone to empathetic behavior, form strong relationships, and enable a
cohesive support system in and among themselves. This cohesiveness facilitates trust
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 57
and innovation, as well as efficient decision making and promotes the effective
functioning of the team (Prati et al., 2003).
Collaboration and compromise. Emotional intelligence provides a unique
insight in trying to enhance the chances of conflict resolution and compromise. It is
important to not only recognize the value of EI but to encourage and promote the
improvement of EI in situations of conflict (Chrusciel, 2006). If an individual does not
regulate their emotions, negotiations can sometimes degenerate so that both parties leave
the negotiation dissatisfied with the outcomes. Given the reciprocal social influence
inherent in a negotiation, the EI of both negotiators can strongly influence objective and
subjective outcomes. Each negotiator aims to create value, and claim value. Having an
understanding, and control of emotions in this interaction can improve outcomes for each
party (Foo, Elfenbein, Tan, & Aik, 2005).
EI can be seen as an influential means to enhance the chances of conflict
resolution and compromise (Chrusciel, 2006), and EI can strengthen one’s
communication skills (Xavier, 2005). Meaningful and effective negotiation is a
necessary skill for productive business professionals to produce relationships that are
manifested in communication, and negotiation improves one’s ability to initiate and
manage change. Having a positive attitude inclusive of the impact change has on others
contributes to both effective conflict management and resolution of disagreements
through negotiation, compromise, and seeking of the best alternatives that yield positive
results for both parties (Xavier, 2005). Thus, the second factor of collaboration in this
study, compromise, seeks to extend the basis of idea integration leading to a balanced
solution for all team members.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 58
Collaboration and communication. Successful communication requires an
emphasis on self and social awareness, and awareness of the emotions of others.
Maintaining relationships with clients, customers, and colleagues requires the delivery of
messages that are accurate in meaning, importance, and emotion. For example, senders
and receivers often interpret e-mail communication differently; words have different
meanings, emotions are difficult to express (and interpret) correctly, and clarifying
feedback is not immediately available. In considering these factors and their inevitable
risks, one may not hear the emotional intensity a sender desires to achieve, and one may
not adequately reply with appropriate emotional appreciation for their intended result.
Goleman, Boyatzis, and McKee (2009) discuss the impact of communication on
successful collaboration:
The difference between ineffective and effective leaders lay in the mood and tone
with which they deliver their messages: One may drive the group toward
antagonism and hostility, the other toward optimism, even inspiration, in the face
of difficulty. While most people recognize that a leader’s mood – and how he or
she impacts the mood of others – is important, emotions are often seen as too
personal or unquantifiable to talk about. The best leaders find effective ways to
understand and improve the way they handle their own and other people’s
emotions. Understanding the powerful role of emotions sets the best leaders apart
from the rest – not just in tangibles, such as better business results and the
retention of talent, but also in intangibles, such as higher morale, motivation, and
commitment. (p. 9)
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 59
Communication therefore, the third factor of collaboration in this study, is
involved in all aspects of the collaborative process. Team members seek the exchange of
ideas that are meaningful and relevant, consider compromise in the solution, and that are
mindful of the environment, i.e., face-to-face, virtual, or both. Finally, communication is
closely related to relationship management and recognition of self and others, which are
ability-based EI competencies important in this study.
Improving collaboration through the development of emotional intelligence.
“Emotional intelligence is generally accepted to be a combination of emotional and
interpersonal competencies that influence our behavior, thinking, and interaction with
others” (Macaleer & Shannon, 2002, p. 9). Since EI is believed to influence interaction
with others, collaboration should be improved through the development of EI abilities
and competencies. Emotional competencies within the domains of EI can be acquired
over time through education, practice and emotional maturity (Macaleer & Shannon,
2002). According to Seal, Boyatzis and Bailey (2006), EI competencies should be taught
in management schools in order to improve the eventual collaborative abilities of future
leaders and managers:
In terms of management education, although schools are largely lauded for their
ability to prepare students for the technical knowledge necessary for future jobs,
they are routinely criticized for not adequately preparing the types of managers
and leaders that organizations need. Few graduate professional program
curriculums adequately address the intrapersonal and interpersonal skills that
prospective employers want most in their employees and that employees find
most useful in their work. To better prepare future managers for the changing,
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 60
team-oriented workplace of the future, management education must be willing to
accept the challenge by incorporating these various ‘people skills’ into their
curriculums. In order for future managers to deal with the rapid pace of change
and the increasing use of teams, management education must respond to the
challenge by addressing emotional and social intelligence in their curriculums. (p.
202)
Individual EI has a group analog; collaborative groups boost their performance by
developing their team’s EI. Absent of EI, a collaborative group can still continue through
the motions of participation and cooperation, but the team may not be as effective as it
could be if members do not fully engage emotionally. To be most effective, the team
needs to develop and nurture emotionally intelligent norms that support the building of
trust, group cooperation and efficacy. However,
…a team with emotionally intelligent members does not necessarily make for an
emotionally intelligent group…creating an upward, self-reinforcing spiral of trust,
group identity, and group efficacy requires more than a few members who exhibit
emotionally intelligent behavior. It requires a team atmosphere in which the
norms build emotional capacity and influence emotions in constructive ways.
(Druskatt & Wolff, 1999, p. 2)
EI is favored by aspiring individuals, teams, and leaders desiring of improvement
in self and social awareness, negotiation, and upward spirals in themselves and their
collaborative activities. “Given that the key components of the collaborative process are
inherently emotional in nature, leaders who are successful in developing collaborative
work cultures may be those who are able to manage, rather than deny, their emotional
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 61
selves” (Slater, 2005, p. 330). Since collaboration has the potential to yield positive
outcomes not otherwise attainable, leaders and managers who learn to manage the
emotional aspects of their work and add EI competency to rationale, technical, and
organizational decision making may be successful collaborators at all levels of the
organization (Slater, 2005).
Teams that are emotionally intelligent and collaborative build social capital
(Brooks & Nafukho, 2006). Specifically, EI impacts effective task processes and
individual engagement in those processes, and impacts effective information sharing,
knowledge and idea integration leading to positive collaboration outcomes. Emotion
drives behavior, and behavior affects relationships between individuals, groups and
within the collaborative environment. Emotions and subsequent behaviors can be
positive or negative, but EI allows for the positive application of these emotions
contributing to positive collaborative outcomes. Individuals and teams lacking in trust
are less likely to respond to emotional stressors in ways that build the social capital of the
group (Druskatt & Wolff, 1999). Being cognizant of trust which is founded in the EI
domain of self-management can enable pathways to success thereby avoiding pitfalls of
negative social capital, and ultimately demise of the collaborative process.
Emotions are connected to rationality and reasoning, not only behaviors. Positive
emotions act as catalysts for creativity, and contribute to motivation. Since emotions can
be intense but short-lived, the resultant behaviors can have lasting effects on the
productivity of a collaborative team. It is important to remember that since EI reflects the
ability to accurately appraise and understand emotions, the positive application of these
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 62
emotions to facilitate thinking and creativity, flexibility and trust must remain the
primary goals of the collaborative individual (Chattopadhyay & Finn, 2000).
Measures of collaboration. Successful collaboration implies that a team has
maximized the benefits of cooperative work. A review by Thomson et al. (2009) found
few instruments exist to measure collaboration. Nevertheless, researchers have used
measures which include a variety of factors that represent characteristics of collaboration,
such as integration of ideas, negotiating compromise, communication, problem solving,
sharing risk, and team cohesiveness. Table 2.2 presents a summary of the most common
measures of collaboration found in the scholarly literature on business and management.
Aram and Morgan’s (1976) Work Collaboration Questionnaire measures problem
solving, communication, and knowledge- based risk taking using an 18-item self-report,
and Mattisich and Monsey’s (1992) Collaboration Experience Questionnaire measures
factors that influence successful collaboration using a checklist of 19-items. In contrast
to these two measures of collaboration, Rahim’s (1983a, 1983b) Organizational Conflict
Inventory-II measures variables that are highly correlated with collaboration, such as
communication, mutual support (compromising), and aligned efforts (integration and
inclusion).
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 63
Table 2.2 Summary of Common Measures of Collaboration in Business Journals
Measure of
Collaboration
Type Theoretical
Model
Collaboration Factors Length
Work Collaboration
Questionnaire
Self-report
questionnaire
Aram & Morgan
(1976) Problem solving
Communication
Knowledge based risk
taking
18
Items
Collaboration
Experience
Questionnaire
Self-report
checklist of
factors that
influence
successful
collaboration
Mattisich &
Monsey (1992) Environment
Measurement
Process/Structure
Communication
Purpose
Resources
19
Items
Rahim organizational
conflict inventory-II
(ROCI-II)
Self-report
questionnaire
Rahim (1983a,
1983b) Integrating
Obliging
Compromising
Dominating
Avoiding
28
Items
Team Collaboration
Questionnaire
Self-report
questionnaire
Adapted from
Aram and
Morgan (1976)
and Rahim
(1983a, 1983b)
Integrating
Compromising
Communication
15
Items
Collaboration is an essential part of teamwork, and effective collaboration leads to
effective team outcomes (Aram & Morgan, 1976). In this study, the measurement of
collaboration required careful consideration in accurately selecting factors measured by
items correlated with the study variables applicable to the hypothetical model—
integrating, compromising, and communication. For this reason, an original
measurement instrument was uniquely developed for this study, a 15-item team
collaboration questionnaire, adapted from the measures developed by Aram and Morgan
(1976), and Rahim (1983a, 1983b).
Emotional intelligence, while rooted in self-awareness and self-management, is
inherently social in its manifestation to bring about cooperative exchange between
individuals, i.e., to invest in relationships with concern for others. In collaboration, a
similar cooperative exchange is desired to bring about positive outcomes. Collaboration
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 64
encompasses the collective effort of a group or team of diverse members or organizations
who are working together for a common purpose. Collaboration moves beyond a
working group and implies that stakeholders are working together to accomplish an
outcome that is more significant as a team than that which could be accomplished by the
individual members alone (Gray, 1985; Romero, 2009). Determining the effectiveness of
that collaboration, and having a quantitative method for collaboration assessment is the
purpose of this section of the study.
Collaboration involves mutual influence, open communication, and conflict
resolution (Aram & Morgan, 1976). An assessment of collaboration can be accomplished
by evaluating such team attributes as integration of ideas (integrating), seeking
compromise that optimizes team effectiveness (compromising), and team interaction that
fosters open and authentic dialogue (communication). The Team Collaboration
Questionnaire, a unique measure of team-based collaboration developed for this study,
includes these three factors. The integrating and compromising collaboration factors
were adapted from Rahim (1983a, 1983b), and the communication factor was adapted
from Aram and Morgan (1976). Each factor of collaboration includes five- items each
specific to collaboration and team effectiveness. The complete 15-item questionnaire is
shown in Appendix B. Note after adjusting for improved reliability and validity of the
measurement instrument, the final form of the Team Collaboration Questionnaire
included three factors with three-items each, for a nine-item questionnaire.
Work collaboration questionnaire. The work collaboration questionnaire (Aram
& Morgan, 1976) is a self-report questionnaire focused on three factors of collaboration
(problem solving, communication, and knowledge-based risk taking) with 18-items of
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 65
behavior relevant to collaboration. The questionnaire seeks to relate items of
interpersonal influence, conflict resolution, and support for innovation. The study of
Aram and Morgan encourages risk taking in an environment of collaboration and focuses
on individual performance as well as successful team outcomes. The strength of the
communication factor was adapted to this study based on its relevance to team
cohesiveness and recognition of self and other awareness, which are ability-based EI
competencies important to this study.
Collaboration experience questionnaire. The collaboration experience
questionnaire (Mattisich & Monsey, 1992) is a self-report measure focused on six-factors
of collaboration (environment, measurement, process/structure, communication, purpose
and resources). These factors and related 19-items are intended to measure individual
experiences which influence success in collaboration. The purpose of this questionnaire
is to provide a resource for people who wish to enhance their experience in collaboration,
and to understand the elements one should consider in starting or improving their
experience in a collaborative activity. While very suitable for that purpose, the
collaboration experience questionnaire is not specifically geared to team performance in a
measurable way. The questionnaire is very comprehensive in describing items to
consider in collaboration, and functions as a collaboration handbook with case examples,
but does not provide a specific measure of collaboration items closely linked to team
cohesiveness, or the EI factors of self and other awareness. For these reasons, the
collaboration experience questionnaire was not chosen for this study.
ROCI-II. The Rahim Organizational Conflict Inventory-II (ROCI-II) (Rahim,
1983a, 1983b) was originally developed as a measure of interpersonal conflict, but also
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 66
has strong ties to the EI factors of self-awareness, and awareness of others. The ROCI-II
is a five-factor self-report questionnaire with 28-items. The factors are integrating,
obliging, compromising, dominating, and avoiding. The ROCI-II factors relevant to
collaboration and team effectiveness are integrating and compromise. These factors seek
to measure the extent to which team members integrate themselves in the collaborative
process. Compromise and negotiation further build on the ability-based EI competencies
of concern for self and others, and the relationship between these factors and EI fit the
hypothetical model this study is based on.
Collaboration is a process in which team members seek compromise, jointly
create rules and structures involving their relationships, and invest in activities for the
purpose of mutually beneficial interactions (Thomson et al., 2009). With integration, the
team can envision and create possibilities that go beyond their own limited vision of what
is possible (Gray, 1989). For this reason, the ROCI-II factors of compromise and
integration were adapted for this study and included in the original measure of
collaboration for research on collaborative activity.
Team collaboration questionnaire. This study uses an original measure of
collaboration adapted from Aram and Morgan (1976), and Rahim (1983a, 1983b), and
includes three factors with 15-items. Note after adjusting for reliability and validity of
the measurement instrument, the Team Collaboration Questionnaire included three
factors with three-items each in its final form. The factors that represent characteristics
of collaboration (integrating, compromising, and communication) are common themes in
the literature on collaboration. These measurable items of collaboration were selected
because of their applicability to team cohesiveness and positive outcomes in
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 67
collaboration. The items correlate well with the ability-based EI factors of self and other
awareness, and management of self and others’ emotions. The collaboration factors
shown in the hypothetical model of the study (see Figure 1.1), will be the measures used
to investigate the hypothesized relationship between EI and collaboration.
SOAR
SOAR, the third of three constructs used in this study, functions as the mediating
variable (MED) in the hypothetical model (see Figure 1.1). The following sections
present the theoretical foundations of SOAR, relevance to the hypothetical model, and the
framework used in this study (i.e., strengths (S), opportunities (O), aspirations (A) and
results (R)). The section concludes with a review of the SOAR Profile (Stavros & Cole,
2013) used in assessing levels of SOAR in individuals, and subsequently used in this
study.
Theory. SOAR (Strengths, Opportunities, Aspirations, and Results) is an
innovative, strengths-based approach to strategic thinking and planning involving all
individuals with a stake in the strategic thinking process (Stavros & Hinrichs, 2009).
SOAR is a “strengths-based framework with a participatory approach to strategic
analysis, strategy development, and organizational change” (Stavros & Saint, 2010, p.
380). As such, SOAR integrates Appreciative Inquiry (AI) with a strategic planning
framework to create a transformational process that inspires organizations and
stakeholders of the organization to engage in results-oriented strategic planning efforts
(Stavros, Cooperrider, & Kelley, 2003).
As shown in Figure 2.1, the SOAR framework transforms alternative approaches
to strategic thinking that do not emphasize strengths, opportunities, aspirations, and
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 68
results, such as SWOT-based traditional strategic planning of strengths, weaknesses,
opportunities and threats. In contrast to SWOT-based strategic thinking that reinforces
historical focus on weaknesses and threats, SOAR-based strategic thinking engages
organizational members to frame organizational issues from a solution-oriented
perspective that is generative and focused on organizational strengths, opportunities,
aspirations, and desired results to build a positive future (Stavros & Wooten, 2012). As a
framework for strategic thinking and planning, SOAR describes the elements and
activities that team members, teams and organizations should follow in their collaborative
strategic thinking and planning if they are following a strengths-based approach (Stavros,
Cooperrider, & Kelley, 2007).
Figure 2.1 The SOAR Framework
Available from www.soar-strategy.com. Used with permission.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 69
The SOAR approach is inherently a team-oriented collaborative process that
focuses on the strengths, values, and shared vision and mission of those having a critical
interest in the team and organization’s success or failure. SOAR seeks to involve all
individuals having a perspective and stake in the organization’s strategic planning
initiatives and begins with an inquiry into what works well, followed by the identification
of possible opportunities for growth. The SOAR approach enables stakeholders to
identify and build on strengths, define specific goals and strategic initiatives, and identify
enabling objectives. With the SOAR foundation, the organization is able to design
strategies and methods to meet objectives, define performance metrics aligned with goals
and objectives, and discover new and profitable opportunities. Such an approach
promotes individual and organizational freedom to imagine an innovative and creative
future in which a strengths-based strategic plan is implemented that is dynamic and
enabling of positive outcomes (Stavros & Hinrichs, 2009).
Since SOAR depends on the interaction of key stakeholders in the strategic
planning process, it may be appropriate to suggest that participants be emotionally
intelligent in their exchange of ideas. Participants are invited to share their perceptions,
ideas, goals and vision for the future, and the key abilities of EI addressed in this
dissertation necessarily include those personal skills that will benefit from SOAR-based
thinking. It is important to recognize the distinction of the SOAR approach as its focus
remains to identify and build on strengths and opportunities, rather than weaknesses and
threats. The collaborative process of dialogue and strengths-based information exchange
may lead an organization to understand what happens when they are at their best, and to
identify what and where they wish to be for the future (Stavros & Hinrichs, 2009). Table
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 70
2.3 depicts the specific activities within the SOAR framework that act as enablers for the
successful interaction of team members (Stavros et al., 2003).
Table 2.3 Strategic Inquiry—Appreciative Intent: Inspiration to SOAR
Planning
Processes
SOAR
Elements
SOAR Activities
Strategic
Inquiry
Strengths
What are we doing well?
What are our greatest assets?
Opportunities
What are the best possible market opportunities?
How do we best partner with others?
Appreciative
Intent
Aspirations
To what do we aspire?
What is our preferred future?
Results
What are the measurable results?
What do we want to be known for?
Note. Adapted from Stavros et al. (2003).
Relevance to hypothetical model. For teams and organizations, a shared vision,
purpose and respect for each other’s roles is necessary to achieve breakthrough results.
While SOAR is essentially a strategic thinking and planning framework for
organizations, it depends on the successful interactions of people. The EI domains are
closely related to the skills necessary to achieve these successful interactions. The
contribution SOAR competency has in successful collaboration outcomes has been
considered and supported, but there is no evidence to suggest that SOAR has any
influence on the link between EI and collaboration. Since this process invites all
stakeholders to participate and focus on the elements of SOAR, dynamic relationships
within the collaborative group are important. The elements of EI are likely to support
these relationships. Elements of trust, respect, empathy, and understanding must be
present in order for the collaborative team to succeed. This study organizes the EI
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 71
domains and their influence on positive collaboration outcomes, and considers the
interaction of SOAR dynamics in this relationship.
Strengths-based strategic thinking and planning within the SOAR framework is an
example of organizational collaboration uniquely suitable for EI. The SOAR framework
has the potential to build strong and dynamic relationships, and may help teams and team
members to understand the importance of working collaboratively to develop strategy,
measurable objectives, and methods to achieve a visionary future based on strengths and
opportunities, rather than weaknesses and threats. The manifestation of SOAR
relationships are exemplified in self-reflection, mutual understanding, and a consideration
for the collaborative group as a whole. As participants exchange ideas, aspirations, and
desired results, they share a vision for the future with energy, vitality, and commitment
(Stavros & Hinrichs, 2009). EI abilities are closely linked to a SOAR-based pattern of
idea exchange and are supportive of the competencies necessary to achieve desired
results from a SOAR-based perspective. The results, implications, and recommendations
of this study contribute to clarifying and enhancing the relationships necessary for
positive collaboration outcomes in the presence of the SOAR framework.
Measures of SOAR. Traditional measures of SOAR involve qualitative case
study methodology, such as interviews and grounded theory analysis, and quantitative
self-report rating scales. To date, SOAR has been explored qualitatively by one doctoral
dissertation (Malone, 2010), and quantitatively by one peer-review publication (Sprangel,
Stavros, & Cole, 2011) and two doctoral dissertations (Glovis, 2012; Sprangel, 2009).
This study is best-suited for a quantitative index of SOAR in which SOAR is rapidly
assessed among a survey-based assessment battery of EI and collaboration measures.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 72
Malone’s (2010) qualitative study of SOAR involved 39 in-depth interviews
analyzed using grounded theory in which SOAR was examined as a method to build
strategic capacity among individuals who used or supported the use of the SOAR
framework in organizations and in books and articles in the strategy field. The study
results support SOAR as a framework for building strategic capacity. The study also
demonstrated that the SOAR framework can be utilized in a small group setting to build
strategic capacity that is expressed as the capabilities to engage in strengths-based
strategic thinking and planning.
Among quantitative measures, published measures of strategy and strategic
thinking include measures of strategic learning, such as the Motivated Strategies for
Learning Questionnaire (Pintrich, Smith, Garcia, & McKeachie, 1993), and the Learning
and Study Strategy Inventory (Weinstein, Schulte, & Palmer, 1987). Quantitative
measures of thinking style, such as the Thinking Styles Inventory (Sternberg & Wagner,
1992), and measures of decision making, such as the General Decision-Making Style
Inventory (Scott & Bruce, 1995), account for the most widely recognized measurement
instruments most closely related to the SOAR construct and its factors, S, O, A, and R.
In the three quantitative studies of SOAR, SOAR was measured using a 16-item
self-report questionnaire developed by Sprangel (2009) that assessed eight elements
involved in the SOAR framework approach to strategic thinking that are descriptive of
SOAR-based capabilities: (1) an internal capability is analyzed; (2) an external capability
assessment is conducted; (3) values, vision and mission are created; (4) innovations and
potential outcomes are developed; (5) strategies and strategic initiatives are outlined; (6)
tactical/functional plans and integrated programs are planned; (7) goals and objectives are
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 73
established; and (8) the implementation and continuous improvement initiatives are
implemented. Sprangel’s questionnaire was used to study the relationship between
SOAR, trust, environmental management systems (EMS), and supplier performance was
investigated in a sample of 71 chemical management services (CMS) program managers
and customers (Sprangel, 2009; Sprangel et al., 2011). In the Glovis (2012) study, the
Sprangel questionnaire was used to investigate SOAR as a mediator of the relationship
between flow and project success in a sample of 122 SAP professionals. Both studies
demonstrate the utility of measuring SOAR quantitatively in order to investigate the role
of strengths-based strategic thinking and SOAR-based capabilities in managerial
performance and project management contexts.
Recently, a new quantitative measure of SOAR was created, the SOAR Profile, in
which the four elements of the SOAR framework of strategic thinking are assessed using
a 16-item self-report questionnaire (Cole & Stavros, 2013). The SOAR Profile asks
respondents to rate their current level of strategic thinking along a 10-point Likert rating
scale (Never-Always) using 3-items for each of the SOAR elements and 4-items for
engaging in strategic thinking from an appreciative inquiry perspective. In pilot studies,
the SOAR Profile demonstrates good reliability and construct validity (M. Cole, personal
communication, July 10, 2013).
Summary
This chapter has presented a literature review of the study variables: emotional
intelligence, collaboration, and SOAR. A central theme in the EI literature is that EI
improves one’s ability to be socially effective and can lead to improved leadership,
performance, and collaborative outcomes. The strength of the research in emotional
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 74
intelligence has been to advance its application with the competencies that contribute to
emotional awareness and regulation at all levels of interaction, so that teams can build the
solid foundation of trust, group identity, and group efficacy they need for true
cooperation and collaboration (Druskatt & Wolff, 2001).
The literature on emotional intelligence also reveals that consistency in the
measurement and assessment of the EI competencies is an area frequently investigated by
researchers. The challenges in EI measures are almost unilaterally focused on the use of
the word “intelligence”, and the inconsistent methods of emotional intelligence
assessment. These are not necessarily problems indicative of an invalid and
inappropriate construct, but rather suggesting of one that is in development and open to
new ideas and refinement, in particular, how to measure it. The early research of EI by
Goleman (1995, 1998) and later by Mayer, Salovey, and Caruso (2002, 2004) establish
the most well-recognized and accepted models of EI today. These models are often
targeted for refinement and measurement by other researchers seeking to advance the
positive outcomes of EI and its application. For example, researchers postulate differing
numbers of competencies, whether EI should be a self-report or peer review, or in what
ways elements of EI competency should be organized (Barling et al., 2000).
Notwithstanding the conceptual origins of EI by the seminal researchers
Goleman, Salovey, Mayer and Caruso, EI measures vary in content and method of
assessment (Conte, 2005; McEnrue & Groves, 2006; Zeidner et al., 2008). Although
there is no standard metric, instrument, or assessment method for determining the
aptitude of an emotionally intelligent individual, the research of Bar-On (1997), Jordan
and Lawrence (2009), Salovey and Mayer (1990) and Goleman (1995, 1998) has
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 75
provided scholars and practitioners with EI measures that have acceptable psychometric
properties and applied significance. Although these measures of EI vary in style, their
use in a variety of research studies suggests EI is a value-added construct for leadership
and teamwork applications. The continuing investigation into EI measures represents an
energetic and logical process of new construct development, and is an inherent part of the
process of theory development and scientific discovery in any field (Emmerling &
Goleman, 2003).
This literature review provided a theoretical foundation of research on EI,
collaboration, and SOAR. The literature reviewed suggests that knowledge and
application of EI abilities have the potential to positively impact collaboration in team
settings. The potential of EI as a viable construct remains evident in the research
initiatives of those seeking to further the EI framework and assessment models that are
currently under development today. Investigators also remain in support of EI as a means
to equip individuals and leaders with skills to better inform, perform, and interact with
colleagues within and throughout their organizations to further their collaborative
performance and competitive advantage.
This dissertation seeks to advance the development of an ability-based model of
EI aimed at having a distinct relationship with positive collaboration outcomes. Further,
this study aims to evaluate the link between EI and collaboration, to characterize the EI
abilities that contribute to collaboration, and to investigate the moderating role that
demographic characteristics and the mediating role that strengths-based strategic thinking
and planning (i.e., SOAR) has on the relationship between EI and collaboration among
team members. The methodology for this empirical study was a cross-sectional design,
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 76
drawing from the experiences of a sample of individuals with team experience. EI
abilities were assessed using the Workgroup Emotional Intelligence Profile-Short Form
(WEIP-S; Jordan & Lawrence, 2009). Collaboration was assessed using an original
measure of collaboration developed for this study, the Team Collaboration Questionnaire,
adapted from Aram and Morgan (1976) and Rahim (1983a, 1983b), and SOAR was
measured by the SOAR Profile (Cole & Stavros, 2013).
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 77
Chapter 3 Research Methodology
Introduction
The purpose of this dissertation was to evaluate the relationship between
emotional intelligence (EI) and collaboration. The dissertation aimed to identify the EI
competencies that are most critical for achieving collaboration among teams and team
members. The relationship between EI and collaboration was considered in the presence
of potential moderating demographic factors and the mediating effects of SOAR, a
framework for strengths-based strategic thinking and planning.
EI was evaluated for its impact on collaboration among a sample of professionals
either actively working in teams or who have had recent experience working in teams.
Existing measures were used to measure EI and SOAR, and an original measure of team-
based collaboration developed for this study was used for collaboration. This chapter
presents the research questions, hypotheses, and methods that were used in the study,
including description of the research design, sample, variables, data collection, and data
analysis methods.
Research Design
In this study, the research methodology was a quantitative cross-sectional design
with moderating and mediating variables. The analysis was linear regression in which
the dependent variable, collaboration, was regressed on the independent variable,
emotional intelligence (EI). An interaction term of EI x demographic characteristics was
included in the regression analysis to test if any of the sample demographic
characteristics moderate the impact of EI on collaboration. To determine if SOAR
mediates the relationship between EI and collaboration, a mediation path model was
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 78
analyzed using structural equation modeling (SEM) to test if there was an indirect effect
of SOAR on the relationship between EI and collaboration (Preacher & Hayes, 2008).
For this cross-sectional design, a sample of individuals were sought from a population of
professionals with some degree of team experience to participate in an electronic survey
that measured demographic characteristics, EI, collaboration, and SOAR.
Research Questions and Hypotheses
People engaged in cooperative work seek to advance their mutual interests
(Whitaker, 2009); however, would individuals working in teams be in a better position to
advance their cooperative work if they adopted emotional intelligence (EI) in both theory
and practice? Are EI abilities differentially related to collaboration? For example, are
there differences in the impact that emotional self-awareness and self-management, and
awareness and management of other’ emotions may have on collaboration? Are there
any variables that influence EI and its impact on collaboration and may help to explain
the mechanism by which EI affects collaboration? For example, are there certain
demographic characteristics that moderate the potential impact of EI on collaboration,
and are there certain mediators, such as strengths-based strategic thinking (i.e., SOAR),
that help to explain the impact that EI has on collaboration?
The four research questions posed in this study are:
Q1. Is there a relationship between emotional intelligence and collaboration?
Q2. Are there differences in the contribution of the emotional intelligence
abilities awareness of own emotions, management of own emotions, awareness of others’
emotions, and management of others’ emotions to collaboration?
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 79
Q3. Are there any demographic characteristics that moderate the impact
emotional intelligence may have on improved collaboration outcomes?
Q4. To help understand a potential mechanism for why EI may have an impact
on collaboration, does the SOAR framework for strengths-based strategic thinking,
planning, and leading mediate the impact that EI may have on collaboration?
The following three hypotheses were tested to answer the research questions:
H1. Emotional intelligence is related to collaboration such that EI has a positive
impact on collaboration.
H2. The impact of emotional intelligence on collaboration is moderated by
participant demographic characteristics.
H3. The SOAR framework mediates the relationship between emotional
intelligence and collaboration.
Research Variables
Three research variables were studied in this dissertation: emotional intelligence
(EI), collaboration, and SOAR (i.e., strengths-based strategic thinking). EI involves self-
awareness and self-management of one’s own feelings, and social awareness and
management of what others are feeling (Dulewicz & Higgs, 2000); collaboration involves
integration, compromise and communication (Aram & Morgan, 1976; Rahim, 1983a,
1983b). Collaboration is also discussed in the context of strategy and strategic thinking
(Gray, 1985), and SOAR and its measurement by the SOAR Profile served as the index
of a strengths-based approach to strategic thinking for consideration as a mediating
variable between EI and collaboration (Stavros & Hinrichs, 2009; Stavros et al., 2003,
2007; Cole & Stavros, 2013).
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 80
Figure 3.1 presents the hypothetical model for this study. According to the model,
EI, which has been derived from the Mayer and Salovey (1997) model of EI in a research
study by Jordan and Lawrence (2009) on EI in teams and workgroups, is comprised of
four factors—awareness and management of own emotions, and awareness and
management of others’ emotions. EI is an independent variable (IV) that impacts the
dependent variable (DV), collaboration, which is comprised of three factors—integrating,
compromsing, and communication.
To explore the impact of variables that could moderate the impact of EI on
collaboration, team-based demographic characteristics (such as team role, team type, and
time in teams) were included in the model as moderators (MOD). In consideration of
variables that could mediate the indirect effects of EI on collaboration, a construct used
for framing a strengths-based approach to strategic thinking, SOAR, was included in the
model as a mediator (MED). According to Baron and Kenny (1986), “Moderator
variables specify when certain effects will hold, mediators speak to how or why such
effects occur” (p. 1176). Therefore, this study also proposed that SOAR serves as a
mediator of the impact that EI has on collaboration. All together, the ultimate goal of the
research was to characterize the relationship between EI and collaboration.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 81
Figure 3.1 Hypothetical Model of the Study: SOAR Mediating the Impact of Emotional
Intelligence on Collaboration
Population and Sample
The population for this study was comprised of professionals actively working in
teams, or professionals who have had recent experience working in teams. In order to
expose participation in this study to as many individuals as possible, a concerted effort
was made to connect with individuals who routinely work in teams in general.
Invitations to participate were distributed across a wide range of professionals from
industry, academia, and the U.S. Government. Country data was not collected as no
respondents were to be excluded based on their location. However, it is known from
personal respondent feedback that approximately 2% were from outside the U.S. Those
respondents providing voluntary consent to participate in the electronic survey became
the study sample. The study survey was designed to assess their demographic
characteristics, EI, collaboration, and SOAR. The target sample size was N > 200.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 82
Protection of participants’ rights. Research participants in this study were
protected according to the federal requirements specified by the Department of Health
and Human Services’ Code of Federal Regulations, 45 CFR 46. The author received the
National Institute of Health (NIH) Office of Extramural Research Certificate of
Completion of the NIH web-based training course “Protecting Human Research
Participants” (Appendix A). In accordance with the federal requirements, approval to
conduct research with human participants was obtained from The Lawrence
Technological University Institutional Review Board (IRB). IRB approval (Appendix B)
was obtained before any research was conducted, and stipulated that participants
voluntarily complete an informed consent prior to participating in the study. The
informed consent (Appendix C) was included as the first page of the on-line survey, and
required acceptance by the survey respondent in order to proceed.
Measures
Study variables were measured via an online survey instrument (see Appendix D).
The survey instrument consisted of 68 questions divided into five sections: (1) team
characteristics (5 questions), (2) emotional intelligence (16 questions), (3) team
collaboration (15 questions), (4) SOAR Profile (24 questions), and (5) demographics (8
questions). The questions on team characteristics asked respondents about the size of
their most current team (from 2 team members up to more than 20 team members), the
characteristics of team members in their most current team (internal vs. external), the
type of team (face-to-face vs. virtual), team role (leader vs. member), and time
involvement with their most current team (less than 1 month through greater than 20
years).
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 83
EI was measured by the 16-item “WEIP-S” (Work Group Emotional Intelligence
Profile-Short Form; Jordan & Lawrence, 2009) to establish areas of respondent
competency in four EI abilities helpful for understanding how EI works in teams (Mayer
& Salovey, 1997): awareness of own emotions, management of own emotions, awareness
of others’ emotions, and management of others’ emotions. The measure for assessing
collaboration was the 15-item Team Collaboration Questionnaire, an original measure of
collaborative activity among teams, adapted from Aram and Morgan (1976), and Rahim
(1983a, 1983b). Note after adjusting for improved reliability and validity of the
measurement instrument, the Team Collaboration Questionnaire was reduced to nine-
items, three per factor. Participants rated both the EI and the Collaboration items using a
7-point Likert scale where 1 = strongly disagree, and 7 = strongly agree.
SOAR was measured by the 24-item SOAR Profile (Cole & Stavros, 2013), a
self-report measure of strategic capacity from a SOAR framework. Note after adjusting
or improved reliability and validity of the measurement instrument, the SOAR Profile
was reduced to 12-items, three per factor. These measures were selected for their ability
to rapidly identify EI competencies, collaboration, and SOAR characteristics most critical
to achieving positive outcomes in collaboration. Finally, demographic questions asked
respondents about their age, gender, ethnicity, education, general role in teams (leader vs.
member), general involvement in teams (from less than 1 year through greater than 20
years), industry, and position in current company.
Pilot Study
A two-part pilot study was conducted on the survey instrument in order to assess
question clarity, proper function of the on-line administration method, and to evaluate
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 84
psychometric properties of the survey instrument on a sample of N = 75 participants. In
part one, prior to administration of the survey instrument, the researcher’s dissertation
committee members reviewed the questions for clarity, provided feedback on
organization of the questions, and tested the on-line function in SurveyMonkey. This
evaluation resulted in the modification of five questions for readability, and added one
response item to the team-type question (a choice of ‘both’ was added to the original two
choices of face-to-face or virtual). The factors of EI, SOAR and collaboration were
consolidated into a single list for each such that the distinct factors were not clearly
identifiable. For example, instead of having four groups of four questions each for EI
(each group representing the EI factors SA, SM, AO and MO respectively), the questions
were randomized to a final list of 16-items. This was done similarly for SOAR and
collaboration. The fidelity of the age demographic question was improved to provide a
more accurate representation of the age groups participating in the study. Finally, the
survey instrument offered participants the opportunity of providing their contact
information. When testing this function in SurveyMonkey, an issue was identified that
caused the survey to halt prior to completion. This issue was resolved and did not
reoccur in the administration of the final survey.
Part two of the pilot study required administering the survey to a large enough
population to evaluate the psychometric properties of the survey instrument. This was
accomplished by administering the final survey (see Appendix D) to the target population
with the intent of halting the survey after a sufficient sample was reached (N = 75).
Seven days into data collection, seventy-five surveys were evaluated for reliability of the
survey instrument. The psychometric properties of the WEIP-S, Team Collaboration
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 85
Questionnaire, and the SOAR Profile were evaluated via Cronbach’s coefficient alpha
test of internal consistency reliability (Cronbach, 1951), and via CFA test of construct
validity (Lu, 2006). With no negative or otherwise constructive feedback from the
sample of N = 75, and having demonstrated acceptable reliability and validity of the
survey instrument, the on-line survey was allowed to continue.
Data Collection Procedure
Data collection was comprised of the following 8-step process:
(1) IRB approval was obtained.
(2) Colleagues from academia, industry and government were invited to participate in
the study.
(3) Relevant LinkedIn groups in the dissertation areas of interest were identified, and
approval to join the LinkedIn groups was requested from group managers.
(4) After joining relevant LinkedIn groups, permission was requested from the
selected LinkedIn group managers to post an invitation to group members for
participation in the dissertation research study.
(5) LinkedIn group postings were monitored for activity, questions, and comments.
(6) After 1-2 weeks, depending on LinkedIn group activity, a second invitation to
participate in the study was posted.
(7) Surveys were administered and data were collected via SurveyMonkey from
11/9/13 through 12/10/13; the dissertation chair monitored and reported progress
only by survey respondent count (target sample size was N > 200).
Invitations to participate included a brief description of the study and a
SurveyMonkey link. Invitations to participate were also sent via email to colleagues in
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 86
industry, government, and academia. In addition, invitations to participate were posted
on relevant LinkedIn groups. Relevant LinkedIn groups were identified as suitable
forums in which to solicit potential study participants. Once appropriate permissions
were granted by each LinkedIn group manager, the survey invitations were posted. The
selected relevant LinkedIn groups were organized around the study areas of interest.
These areas included emotional intelligence, leadership, Appreciative Inquiry, team-work
and team-effectiveness, strategic planning, change management, project management,
academia, financial management, general business management, and several industrial
organizations. The LinkedIn group postings were monitored daily for participant
interactions, modification of the invitation, or were removed from the group site if there
was no activity or interest.
The survey was administered over a four week period from 11/9/13 through
12/10/13. If a sufficient quantity of respondents were not obtained in this timeframe (N <
200), the data collection period would have been extended with an action to reinvigorate
and follow-up on the invitation postings on LinkedIn. This extension was not needed as
N = 405 surveys were collected during the four week period, at which time the on-line
survey was closed. Collected data from SurveyMonkey were stored in a secure database
at Lawrence Technological University (LTU) with access only to the researcher and the
dissertation chair.
Data Analysis
Survey data were entered into Excel via SurveyMonkey. Data were transferred
from Excel to Minitab version 16.2.1 for descriptive and inferential quantitative statistical
analysis. Data were also transferred to Mplus version 7 for confirmatory factory analysis
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 87
(CFA) and mediation path models via structural equation modeling (SEM). For each
statistical procedure, all available data were used. For all inferential statistics,
significance was evaluated at the 95% confidence level.
Descriptive statistics. Descriptive statistics of categorical demographic
characteristics were comprised of frequency analysis. Descriptive statistics of continuous
variables were comprised of means and standard deviations.
Psychometric properties. The psychometric properties of the WEIP-S, the Team
Collaboration Questionnaire and The SOAR Profile were evaluated via Cronbach’s
coefficient alpha test of internal consistency reliability (Cronbach, 1951), and via CFA
test of construct validity (Lu, 2006). The essence of Cronbach’s alpha test is the
calculation of the intercorrelations among items in a scale, which can range from an alpha
of 0.0, to an alpha of 1.0. Alpha measures of 0.7 or higher serve as a reference for
acceptable reliability (Hinkin, 1998). In evaluating construct validity using CFA, the
Comparative Fit Index (CFI), Root Mean Square Error of Approximation (RMSEA), and
the ratio of chi-square to the degrees of freedom (df) was examined. CFI values of at
least 0.90, RMSEA less than 0.08, and χ2/df ratio less than 2 to 1 were indicative of
acceptable construct validity (Bentler, 1990; Bentler, 2007; Loehlin, 1998).
In evaluating construct validity using CFA, the Comparative Fit Index (CFI),
Root Mean Square Error of Approximation (RMSEA), and the ratio of chi-square to the
degrees of freedom (df) were examined. CFI values of at least 0.90, RMSEA less than
.08, and χ2/df ratio less than 2 to 1 were indicative of acceptable construct validity
(Bentler, 1990; Bentler, 2007; Loehlin, 1998).
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 88
Inferential statistics. The significance of the frequency distribution of
categorical demographic variables was tested using chi-square statistics. The relationship
between demographic characteristics and study variables was tested using univariate
analysis of variance (ANOVA) models. Post-hoc comparisons were conducted for
significant ANOVA findings using Tukey’s honestly significant difference analysis to
minimize the inflation of type I error (Shavelson, 1996). Hypothesis testing of H1 was
carried out using linear regression; testing of H2 was carried out using linear regression
with a demographic x EI interaction term included using the Baron and Kenny (1986)
causal-steps approach; in addition, a bootstrapped confidence interval for the ab indirect
effect was obtained using procedures described by Preacher and Hayes (2008).
Specifically, the dependent variable, collaboration, was regressed on the independent
variable, emotional intelligence (EI). An interaction term of EI x demographic
characteristics was included in the regression analysis to test if any of the sample
demographic characteristics moderate the impact of EI on collaboration. Finally, a
mediation path model was analyzed using SEM to test if there was an indirect effect of
SOAR on the relationship between EI and collaboration, i.e., to determine if SOAR
mediates the relationship between EI and collaboration.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 89
Chapter 4 Results
Introduction
This study investigated the relationship between emotional intelligence (EI) and
collaboration, and determined the EI competencies that are most important for achieving
collaboration among teams and team members. An interaction term of EI x demographic
characteristics was included in the regression analysis to test if any of the sample
demographic characteristics moderate the impact of EI on collaboration. The study also
investigated the mediating effects of SOAR, a framework for strengths-based strategic
thinking, on the relationship between EI and collaboration. Data were collected via an
electronically administered survey using SurveyMonkey. The survey respondents were
those actively engaged in teams, or who have had recent experience working in teams.
The survey instrument was attempted by four hundred five participants (N = 405),
serving as the full sample size for initial frequency distribution. Three hundred ninety
nine (N = 399) provided their voluntary consent to participate in the study, while six did
not. Forty eight of the consenting participants did not complete the survey, and an
additional 40 provided a partially complete survey in which not all of the construct data
was provided. Two survey respondents did not work in teams, and although they
provided responses they were dropped from the analysis. The final sample size was N =
308. Data analysis involved analysis of all available data. Data were analyzed using
regression-based inferential statistics and SEM (Structural Equation Modeling) to test the
following three research hypotheses:
H1. Emotional intelligence is related to collaboration such that EI has a positive
impact on collaboration.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 90
H2. The impact of emotional intelligence on collaboration is moderated by
participants’ demographic characteristics.
H3. The SOAR framework mediates the relationship between emotional
intelligence and collaboration.
First, descriptive statistics were used to describe the demographic and team
characteristics of the sample, measured by frequency analysis and chi-square tests for
distribution (Tables 4.1 through 4.4). Next, the psychometric properties (internal
consistency reliability measured by Cronbach’s alpha, and construct validity measured by
CFA) of the WEIP-S, Team Collaboration Questionnaire, and SOAR Profile are
presented (Tables 4.5 through 4.9), followed by the intercorrelations between the study
variables (Table 4.10). Tables 4.11 through 4.22 describe the results of an analysis of the
study constructs across demographic characteristics. Specifically, mean and SD of
Emotional Intelligence (Tables 4.11 through 4.14), Collaboration (Tables 4.15 through
4.18), and SOAR (Tables 4.19 through 4.22). Tables 4.23 through 4.37 present the
results of inferential statistics and testing of the three study hypotheses: H1, a series of
linear regressions in Tables 4.23 through 4.32; H2, tests of moderation in Tables 4.33
through 4.35; and H3, mediation path analysis using structural equation modeling in
Tables 4.36 and 4.37. For all inferential statistics, significance was evaluated at the 95%
confidence level.
Demographic Characteristics of the Sample
Tables 4.1 to 4.4 report the descriptive statistics, comprised of frequency analysis
and chi-square tests for distribution, used to describe the categorical demographic and
team characteristics of the sample. Tables 4.1 and 4.2 present the results of the
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 91
demographic characteristics. As shown in Table 4.1, the sample (N = 308) was
essentially equally distributed among males and females. In contrast, age, ethnicity, and
education were significantly distributed according to chi-square test for equality of
distribution. This is shown in the age variable by the large percentage of participants in
the 45-64 years of age class (52%) compared to the 25-44 years of age class (29% of the
participants). Similarly, 77% of the participants were white, and 70% earned a Master’s
degree or higher. As shown in Table 4.2, significant distributions by industry type were
reported with more than 25% working in education, followed by consulting (13%),
healthcare (10%) and automotive (7%). However, positions held within these industries
were essentially equally distributed according to chi-square test for equality of
distribution.
Tables 4.3 and 4.4 present the results of the team characteristic variables. Table
4.3, which refers to the team the study participant is currently active with, or has most
recent experience with, shows that there were significant distributions among the team
characteristic variables: team size, team membership, team type, team role, and time with
team. For example, as shown in Table 4.3, 12% of the participants reported working in
teams with two or three members, whereas 70% reported working in teams of 4-15
members (36% in teams of 4-6 members, and 34% in teams of 7-15 members), and 17%
in teams of 16 or more. For the team membership variable, 71% of the sample reported
team membership was internal to their organizations, 8% was external, and 21% were
comprised of internal and external team members. For team type, the majority of
participants (62%) reported working in face-to-face as opposed to virtual teams (4%), and
34% reported teams comprised of face-to-face and virtual interactions. Regarding team
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 92
role, 52% reported serving as the team leader, while 47% were team members. Finally,
48% reported working with their team for less than 1 year, 33% for 1-3 years, and 18%
for more than 3 years.
In addition to asking study participants to report characteristics of the team they
are currently involved with, the study survey also asked participants to report information
concerning their team experiences in general (see Table 4.4). Results found that 57% of
participants reported functioning typically as the team leader, and most (66%) of the
participants have been involved in team-based activities for more than 15 years.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 93
Table 4.1 Characteristics of Sample by Gender, Age, Ethnicity, and Education
Characteristic n %
Total Sample 308 100.0
Gender
Female 152 49.4
Male 131 42.5
No Response 25 8.1
Age
18-24 13***
4.2
25-34 35 11.4
35-44 54 17.5
45-54 80 26.0
55-64 80 26.0
65-74 22 7.1
75+ 0 0.0
No Response 24 7.8
Ethnicity
Asian 19***
6.2
Black/African American 15 4.9
Hispanic/Latino 6 1.9
White 236 76.6
2 or More Races 2 0.7
Decline 1 0.3
Other 5 1.6
No Response 24 7.8
Education
High school 9***
2.9
Associate 8 2.6
Bachelor 51 16.6
Master 147 47.7
Doctoral 70 22.7
No Response 23 7.5 Note. Sample frequency is expressed as % of all participants, N = 308.
*** p < .001 Chi-square test for equality of distribution.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 94
Table 4.2 Characteristics of Sample by Industry, and Position
Characteristic n %
Total Sample 308 100.0
Industry
Automotive 22***
7.1
Consulting 41 13.3
Education 79 25.6
Engineering 24 7.8
Finance 19 6.2
Government 14 4.5
Healthcare 32 10.4
IT 17 5.5
Marketing 14 4.6
Non-profit 16 5.2
Other 2 0.7
No response 28 9.1
Position
Administrative 38 12.3
CEO 16 5.2
Consultant 8 2.6
Director 37 12.0
Educator 42 13.6
Engineer 14 4.5
Manager 87 28.2
Student 5 1.6
Supervisor 18 5.8
VP 16 5.2
No Response 27 8.8 Note. Sample frequency is expressed as % of all participants, N = 308.
*** p < .001 Chi-square test for equality of distribution.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 95
Table 4.3 Characteristics of Sample by Team Size, Team Membership, Team Type, Team
Role, and Time Working in This Particular Team
Characteristic n % Characteristic n %
Total Sample 308 100.0
Team Role
Team Size Leader 159***
51.6
2 Members 13***
4.2 Member 146 47.4
3 Members 25 8.1 No Response 3 1.0
4 Members 35 11.4 Time With Team
5 Members 44 14.3 Less Than 1 Month 10***
3.2
6 Members 32 10.4 1-3 Months 37 12.0
7-10 Members 69 22.4 3-6 Months 40 13.0
11-15 Members 37 12.0 6-9 Months 28 9.1
16-20 Members 24 7.8 9-12 Months 33 10.7
21 or More Members 29 9.4 1-2 Years 57 18.5
Team Membership 2-3 Years 46 15.0
Internal 218***
70.8 3-5 Years 26 8.4
External 25 8.1 5-10 Years 22 7.1
Both 63 20.5 10-20 Years 8 2.6
No Response 2 0.6 No Response 1 0.3
Team Type
Face-to-Face 191***
62.0
Virtual 12 3.9
Both 104 33.8
No Response 1 0.3 Note. Sample frequency is expressed as % of all participants, N = 308.
*** p < .001 Chi-square test for equality of distribution.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 96
Table 4.4 Characteristics of Sample by Team Role, and Time Involved in Teams (When
Working in Team-Based Activities in General)
Characteristic n %
Total Sample 308 100.0
Team Role
Leader 175***
56.8
Member 108 35.1
No Response 25 8.1
Time Involved in Teams
Less Than 1 Year 7***
2.3
1-2 Years 6 1.9
2-3 Years 9 2.9
3-4 Years 3 1.0
4-5 Years 16 5.2
5-10 Years 38 12.3
11-15 Years 36 11.7
16-20 Years 52 16.9
More Than 20 Years 116 37.7
No Response 25 8.1 Note. Sample frequency is expressed as % of all participants, N = 308.
*** p < .001 Chi-square test for equality of distribution.
Reliability and Validity
The psychometric properties of the WEIP-S, Team Collaboration Questionnaire
and the SOAR Profile were evaluated via Cronbach’s coefficient alpha test of internal
consistency reliability (Cronbach, 1951), and via CFA test of construct validity (Lu,
2006). Reliability of the survey instrument was determined by Cronbach’s alpha, and
construct validity was evaluated with CFA. The essence of Cronbach’s alpha test is the
calculation of the intercorrelations among items in a scale, which can range from an alpha
of 0.0, to an alpha of 1.0. Alpha measures of 0.7 or higher serve as a reference for
acceptable reliability (Hinkin, 1998). In evaluating construct validity using CFA, the
Comparative Fit Index (CFI), Root Mean Square Error of Approximation (RMSEA), and
the ratio of chi-square to the degrees of freedom (df) were examined. CFI values of at
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 97
least .90, RMSEA less than .08, and χ2/df ratio less than 2 to 1 are indicative of
acceptable construct validity (Bentler, 1990; Bentler, 2007; Loehlin, 1998). Construct
validity tests the fit of the items within a scale to the construct that the items are intending
to measure. Tables 4.5 through 4.9 present the results of reliability and validity testing
using Cronbach’s alpha and CFA for each construct full-scale and subscales.
The psychometric properties of the WEIP-S, Team Collaboration Questionnaire,
and SOAR Profile are presented in sequence. Initial results and subsequent item analysis
revealed that dropping certain items from the Team Collaboration Questionnaire and
SOAR Profile would yield improved reliability and validity of the survey instruments. In
their final form, all scales had acceptable reliability, with alpha values ranging from .853-
.893 for the three study variables, EI, Collaboration and SOAR. Cronbach’s alpha values
for the EI subscales (self-awareness, self-management, awareness of others and
management of others) were also acceptable and ranged from .805-.903. The Team
Collaboration Questionnaire sub-scales (integrating, compromising, and communication)
showed alpha values ranging from .721-.909. Alpha values for the SOAR subscales
(Strengths, Opportunities, Aspirations, and Results) ranged from .649-.850. Results of
higher-order CFA support the construct validity of the study constructs, with all three sets
of measures satisfying the goodness of fit indices used to evaluate CFA—chi-square/df
ratio less than 2, RMSEA < .08, and CFI > .900. Additionally, the factor loadings of all
indicators were significant, as was the factor loadings of all first-order latent constructs
onto the higher-order constructs.
The reliability and validity testing results of the WEIP-S are presented in Table
4.5. The mean and SD for the WEIP-S full-scale, subscales (self-awareness, self-
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 98
management, other awareness and other management) and each of the 16-items is shown.
Cronbach’s alpha for the WEIP-S full-scale (.893) and each of the four subscales is also
shown, and all are within acceptable limits for internal consistency reliability. Tests of
model fit for confirmatory factor analysis (CFA) are supportive of construct validity (CFI
= .984, χ2/df ratio = 1.44, and RMSEA = .039). With all three sets of measures satisfying
the goodness of fit indices used to evaluate CFA—chi-square/df ratio less than 2,
RMSEA < .08, and CFI > .900, acceptable validity of the survey instrumented was
demonstrated. Finally, the factor loadings were also shown to be supportive of construct
validity.
Table 4.5 Reliability and Validity of the WEIP-S (Workgroup Emotional Intelligence
Profile – Short Version, 16-items)
Emotional Intelligence (EI) Items Mean1
SD2
Alpha3
Factor4
EI Full Scale (16-items)
5.32 .79 .893
Self-Awareness (Awareness of Own Emotions) 4-items 4.76 1.36 .888 .524
I can explain the emotions I feel to team members 5.14 1.49 .840
I can discuss the emotions I feel with other team members 4.85 1.56 .920
If I feel down, I can tell team members what will make me feel better. 4.27 1.62 .642
I can talk to other members of the team about the emotions I experience. 4.76 1.58 .812
Self-Management (Management of Own Emotions) 4-items 5.96 .84 .805 .655
I respect the opinion of team members, even if I think they are wrong. 6.00 1.06 .636
I can overcome my frustration with other team members. 5.60 1.11 .624
I try to see all sides of a disagreement before I come to a conclusion. 6.07 1.01 .818
I give a fair hearing to fellow team members’ ideas. 6.18 1.00 .791
Other Awareness (Awareness of Others’ Emotions) 4-items 5.10 1.11 .886 .646
I can read fellow team members ‘true’ feelings, even if they try to hide them. 5.10 1.30 .862
I am able to describe accurately the way others in the team are feeling. 5.03 1.26 .890
I can gauge true feelings of team members from their body language. 5.20 1.22 .785
I can tell when team members don’t mean what they say. 5.12 1.22 .685
Other Management (Management of Others’ Emotions) 4-items 5.47 .99 .903 .856
My enthusiasm can be contagious for members of a team. 5.54 1.16 .847
I am able to cheer team members up when they are feeling down. 5.47 1.10 .818
I can get fellow team members to share my keenness for a project. 5.46 1.08 .754
I can provide the ‘spark’ to get fellow team members enthusiastic. 5.41 1.13 .855
Note. Psychometric properties conducted on EI data from N = 308 study participants. Tests of model fit for
confirmatory factor analysis (CFA): χ2 = 141.532, df = 98, p = .003; RMSEA (90% CI) = .039 (.023-.052);
CFI = .984. 1Mean of items within scale where each item is measured on a 7-point Likert scale; 1 =
strongly disagree, 7 = strongly agree. 2Standard deviation.
3Cronbach’s alpha reliability measure of internal
consistency. 4Factor loading scores from CFA significant at p < .05 unless otherwise noted as non-
significant (ns).
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 99
The reliability and validity testing results of the Team Collaboration Questionairre
are presented in Tables 4.6 and 4.7. First, results of the original 15-item survey
instrument (as administered in this study), and a 14-item analysis are shown in Table 4.6.
Results of the final nine-item survey instrument that satisfied the study criteria for
reliability and validity (and was therefore used in study analyses) are shown in Table 4.7.
Table 4.6 Reliability and Validity of the Team Collaboration Questionnaire (15-items,
and 14-items)
Collaboration Items
Mean2
SD Alpha
Factor4
Collaboration Full Scale (15-items) 5.72 .67 .872
Collaboration Full Scale (14-items) 5.91 .72 .904
Integrating (5-items) 6.23 .83 .925 .852
I work with my team for a proper understanding of a problem. 6.29 .96 .817
I investigate an issue with my team to find acceptable solution. 6.24 .92 .854
I integrate my ideas with my team to come up with a joint decision. 6.10 .96 .821
I work with my team to find solutions to problems that satisfy our needs. 6.23 .92 .942
I exchange accurate information with team to solve a problem together. 6.28 .93 .774
Compromising (5-items) 5.42 .99 .844 .528
I usually propose a middle ground for breaking deadlocks. 5.18 1.35 .661
I bring concerns in the open so issues are resolved the best possible way. 5.83 1.17 .440
I try to find a middle course to resolve an impasse. 5.16 1.39 .737
I negotiate with my team so that a compromise can be reached. 5.52 1.19 .878
I use ‘give and take’ so that a compromise can be made. 5.42 1.25 .802
Communication (5-items) 5.52 .64 .492 1.079
I value the opinions of team members. 6.35 .87 .687
My opinion matters most. 3.16 1.61 .692
I consider suggestions of team members to maximize team effectiveness. 6.16 .83 .676
I share my expertise to satisfy the needs of my team. 6.14 .93 .531
I share my ideas with the team concisely. 5.80 1.09
Communication (4-items; “My opinion matters most” dropped) 6.11 .72 .779
Note. Psychometric properties conducted on Collaboration data from N = 308 study participants.
Tests of model fit for confirmatory factor analysis (CFA): χ2 = 223.326, df = 70, p = .000; RMSEA (90%
CI) = .087 (.075-.100); CFI = .943. 1Mean of items within scale where each item is measured on a 7-point
Likert scale; 1 = strongly disagree, 7 = strongly agree. 2Standard deviation.
3Cronbach’s alpha reliability
measure of internal consistency. 4Factor loading scores from CFA significant at p < .05 unless otherwise
noted as non-significant (ns).
The 15-item Team Collaboration Questionnaire is an original measure of
collaborative activity among teams, adapted from Aram and Morgan (1976), and Rahim
(1983a, 1983b). The 15-item questionnaire consisted of three sub-scales (integrating,
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 100
compromising, and communication) with five-items in each factor. Reliability analysis
showed acceptable reliability as measured by Cronbach’s alpha for the 15-item full-scale
(.872), the integrating sub-scale (.925), and the compromising sub-scale (.844).
However, the communication sub-scale showed unacceptable reliability with Cronbach’s
alpha equal to .492. The communication item “my opinion matters most” had significant
respondent variation as indicated by the high SD = 1.61. This may have been a good
item if trying to solely determine if “my opinion matters most”, but not if measuring a
construct called communication. This item doesn’t fit well as shown by its influence on
Cronbach’s alpha; it brings down the reliability of the whole sub-scale. In dropping this
item, Cronbach’s alpha for the communication factor improved to .779, which is within
acceptable limits for construct reliability. Additionally, Cronbach’s alpha for the 15-item
full-scale (.872) improved to .904 in the 14-item scale.
Within the communication sub-scale, there were two items related to opinions in a
team setting. The first being “I value the opinions of team members”, and the latter, “my
opinion matters most”. Similarity in meaning of these items may have caused
respondents to think differently about the two items causing variability in the responses.
Eliminating one of the items doesn’t relax the attention given to considering the opinions
of self and others in a team setting. Dropping the item “my opinion matters most” from
the construct provided items that fit well together, and Cronbach’s alpha rises to .779.
Further analysis revealed that while dropping the item “my opinion matters most”
from the communication sub-scale would provide for strong reliability with Chronbach’s
alpha equal to .779, CFA showed that the model fit was not acceptable with the set of 14-
items. The CFI for the 14-item scale was .943, with the ratio of chi-square to the degrees
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 101
of freedom (df) = 3.19, and RMSEA = .087. Validity of the study constructs depends on
all three sets of measures satisfying the goodness of fit indices used to evaluate CFA—
chi-square/df ratio less than 2, RMSEA < .08, and CFI > .900. With the 14-item scale,
both the χ2/df ratio and the RMSEA were above the desired threshold for construct
validity.
Continuing the analysis described above, the contribution of each sub-scale
(integrating, compromising, and communication) to the CFA was evaluated, while
maintaining or improving scale reliability. In this case, two-items from the integrating
and compromising subscales, and one additional item from the communication subscale
were dropped (see Table 4.7). The result was a nine-item full-scale Team Collaboration
Questionairre with three-items in each factor (integrating, compromising, and
communication). The CFI for the nine-item scale = .990, χ2/df ratio = 1.62, and RMSEA
= .046. With all three sets of measures satisfying the goodness of fit indices used to
evaluate CFA—chi-square/df ratio less than 2, RMSEA < .08, and CFI > .900, this
extended analisys resulted in an optimized nine-item survey instrument with strong
reliability and validity for measuring collaboration in a team setting. All analyses were
conducted on the nine-item collaboration full-scale and the three-item collaboration
subscales.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 102
Table 4.7 Reliability and Validity of the Team Collaboration Questionairre (9-items)
Collaboration Items Mean1
SD2
Alpha3
Factor4
Collaboration Full Scale (9-items) 5.86 .73 .853
Integrating (3-items) 6.19 .86 .909 .888
I investigate an issue with my team to find acceptable solution. 6.24 .92 .852
I integrate my ideas with my team to come up with a joint decision. 6.10 .96 .853
I work with my team to find solutions to problems that satisfy our needs. 6.24 .91 .951
Compromising (3-items) 5.36 1.12 .849 .467
I try to find a middle course to resolve an impasse. 5.18 1.39 .674
I negotiate with my team so that a compromise can be reached. 5.53 1.19 .968
I use ‘give and take’ so that a compromise can be made. 5.43 1.25 .732
Communication (3-items) 6.03 .77 .721 .903
I consider suggestions of team members to maximize team effectiveness. 6.17 .82 .723
I share my expertise to satisfy the needs of my team. 6.14 .93 .746
I share my ideas with the team concisely. 5.79 1.09 .668
Note. Psychometric properties conducted on Collaboration data from N = 308 study participants. Tests of
model fit for confirmatory factor analysis (CFA): χ2 = 35.695, df = 22, p = .033; RMSEA (90% CI) = .046
(.013-.073); CFI = .990. 1Mean of items within scale where each item is measured on a 7-point Likert scale;
1 = strongly disagree, 7 = strongly agree. 2Standard deviation.
3Cronbach’s alpha reliability measure of
internal consistency. 4Factor loading scores from CFA significant at p < .05 unless otherwise noted as non-
significant (ns).
The 24-item SOAR Profile (Cole & Stavros, 2013) administered in this study
included five sub-scales, five-items each for Strengths (S), Opportunities (O), Aspirations
(A), and Results (R), and 4-items related to Appreciative Inquiry (AI). The four-items
for AI were included in the survey instrument (inherent to the SOAR Profile), but were
not used in this study or the analyses. First, results of the original 24-item survey
instrument as administered in this study are shown in Table 4.8 (the four-items related to
AI are not included, providing a 20-item scale for initial analysis). Results of the final
12-item survey instrument that satisfied the study criteria for reliability and validity (and
was therefore used in study analyses) are shown in Table 4.9. The four-items related to
AI (inherent to the SOAR Profile) were discarded in both cases as they were not relevant
to this study.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 103
Performing analysis similar to that described with the Team Collaboration
Questionnaire, the initial 20-item scale showed acceptable reliability (Cronbach’s alpha
measures of 0.7 or higher for SOAR full-scale and sub-scales), but not construct validity
as determined by CFA. The CFI for the 20 item scale was .780, with the ratio of chi-
square to the degrees of freedom (df) = 4.34, and RMSEA = .114. Validity of the study
construct depends on all three sets of measures satisfying the goodness of fit indices used
to evaluate CFA—chi-square/df ratio less than 2, RMSEA < .08, and CFI > .900. With
the 20-item scale, both the χ2/df ratio and the RMSEA were above the desired threshold
for construct validity, and the CFI was below the threshold.
Continuing the analyis to improve CFA using items with highest factor loadings,
the contribution of each sub-scale (S, O, A and R) to the CFA was evaluated while
maintaining or improving scale reliability. Subsequently, it was revealed that the SOAR
Profile would yield improved validity of the survey instrument if certain items were
dropped. In this case, 2-items from each SOAR subscale (see Table 4.9). The result was a
12 item full-scale SOAR Profile with 3-items in each factor. Cronbach’s alpha for the
SOAR Profile 12 item full-scale = .855, which is above the minimum threshold of 0.7 for
construct reliability. Alpha for the four sub-scales, Strengths (.649), Opportunities (.795),
Aspirations (.850), and Results (.790) also show acceptable reliability of the survey
instrument. The CFI for the 12-item scale = .970, χ2/df ratio = 1.8, and RMSEA = .055.
With all three sets of measures satisfying the goodness of fit indices used to evaluate
CFA—chi-square/df ratio less than 2, RMSEA < .08, and CFI > .900, this extended
analysis resulted in an optimized 12-item survey instrument with strong reliability and
validity for measuring SOAR, a strengths-based strategic thinking style in a team setting.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 104
All analyses were conducted on the 12-item SOAR Profile, and the three-item sub-scales
of S, O, A, and R.
Table 4.8 Reliability and Validity of the SOAR Profile (20-items)
SOAR Items Mean1
SD2
Alpha3
Factor4
SOAR Full Scale (20-items)
7.82 1.03 .908
Strengths (5-items) 7.96 1.17 .791 .845
Strengths 8.53 1.42 .707
Abilities 7.95 1.46 .668
Assets 7.13 1.85 .605
Capabilities 8.26 1.42 .819
Resources 7.99 1.64 .597
Opportunities (5-items) 8.10 1.23 .788 .882
Opportunities 8.26 1.53 .733
Connections 7.15 2.11 .510
Ideas 8.62 1.37 .765
Innovations 8.19 1.64 .651
Possibilities 8.31 1.57 .731
Aspirations (5-items) 7.45 1.42 .813 .646
Aspirations 7.24 1.83 .875
Ambitions 6.72 1.90 .745
Desires 7.01 1.95 .773
Inspiration 7.98 1.82 .577
Values 8.30 1.90 .514
Results (5-items) 7.77 1.32 .823 .677
Results 8.41 1.49 .790
Achievement 6.94 1.84 .478
Completed tasks 7.57 1.88 .678
Goals obtained 7.53 1.84 .718
Outcomes 8.41 1.49 .804
Note. Psychometric properties conducted on SOAR data from N = 308 study participants. Tests of model fit
for confirmatory factor analysis (CFA): χ2 = 720.750, df = 166, p = .000; RMSEA (90% CI) = .114 (.105-
.112); CFI = .780. 1Mean of items within scale where each item is measured on a 10-point Likert scale; 1 =
never, 4 = rarely, 7 = often, 10 = always. 2Standard deviation.
3Cronbach’s alpha reliability measure of
internal consistency. 4Factor loading scores from CFA significant at p < .05 unless otherwise noted as non-
significant (ns).
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 105
Table 4.9 Reliability and Validity of the SOAR Profile (12-items)
SOAR Items Mean1
SD2
Alpha3
Factor4
SOAR Full Scale (12-items)
8.00 1.05 .861
Strengths (3-items) 7.96 1.27 .722 .893
Strengths 8.53 1.42 .759
Assets 7.13 1.85 .573
Capabilities 8.26 1.42 .588
Opportunities (3-items) 8.40 1.26 .795 .887
Opportunities 8.26 1.53 .793
Ideas 8.62 1.37 .706
Possibilities 8.31 1.57 .754
Aspirations (3-items) 7.52 1.54 .739 .949
Aspirations 7.24 1.83 .821
Desires 7.01 1.95 .822
Values 8.30 1.90 .679
Results (3-items) 8.13 1.37 .790 .539
Results 8.41 1.49 .844
Completed Tasks 7.57 1.88 .584
Outcomes 8.41 1.49 .854
Note. Psychometric properties conducted on SOAR data from N = 308 study participants. Tests of model fit
for confirmatory factor analysis (CFA): χ2 = 88.345, df = 49, p = .001; RMSEA (90% CI) = .055 (.036-
.073); CFI = .970 1Mean of items within scale where each item is measured on a 10-point Likert scale; 1 =
never, 4 = rarely, 7 = often, 10 = always. 2Standard deviation.
3Cronbach’s alpha reliability measure of
internal consistency. 4Factor loading scores from CFA significant at p < .05 unless otherwise noted as non-
significant (ns).
Intercorrelations Between Study Variables
As presented in the psychometric properties analysis section above, the three
study variables (EI, collaboration and SOAR) were determined by a 16-item measure of
EI, a nine-item measure of collaboration, and a 12-item measure of SOAR. The
intercorrelations of these variables (and their constitutive factors) are presented in Table
4.10, and show strong and significant correlations among the study variables. For
example, correlations between EI and its factors range from .66 to .79. Collaboration and
its factors show correlations between .78 and .82, and SOAR is correlated with its factors
from .69 to .80. In the analysis of intercorrelations, significant correlation (p < .05)
means all variables are well correlated, and that there are strong linear relationships
between them.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 106
The intercorrelations are important in seeing how changes in one variable and its
factors affect other factors. Correlations range from +1 to –1, and can be positive or
negative. If p < .05, correlation is considered significant, and stronger with p < .01.
Correlations of zero indicate no correlation, .3 is low, .5 is medium and .7 is high. In this
study, essentially all of the study variables are correlated at the p < .01 level of
significance which indicates strong and relevant interactions between the variables and
their factors. All variables are positively correlated with each other, 98% are correlated
at p < .05, and 97% are correlated at p < .01. This provides statistical support of the
preceding CFA which measures construct validity, and taken together support the next
step in determining inferential statistics.
Table 4.10 Intercorrelations Between Study Variables
Var Mean (SD) EI SA SM AO MO SO ST OP AS RE CL IN CP
EI 5.32 (0.79) --
SA 4.76 (1.36) 0.75+ --
SM 5.96 (0.84) 0.66+ 0.31+ --
AO 5.10 (1.11) 0.74+ 0.33+ 0.33+ --
MO 5.47 (0.99) 0.79+ 0.40+ 0.46+ 0.52+ --
SO 8.00 (1.05) 0.45+ 0.28+ 0.19+ 0.41+ 0.43+ --
ST 7.96 (1.27) 0.35+ 0.21+ 0.17* 0.31+ 0.34+ 0.82+ --
OP 8.40 (1.26) 0.43+ 0.23+ 0.24+ 0.36+ 0.41+ 0.81+ 0.57+ --
AS 7.52 (1.54) 0.41+ 0.31+ 0.09 0.37+ 0.37+ 0.78+ 0.53+ 0.57+ --
RE 8.13 (1.37) 0.21+ 0.10 0.09 0.23+ 0.20+ 0.69+ 0.48+ 0.40+ 0.26+ --
CL 5.86 (0.73) 0.49+ 0.24+ 0.56+ 0.31+ 0.40+ 0.43+ 0.37+ 0.39+ 0.23+ 0.38+ --
IN 6.19 (0.86) 0.45+ 0.22+ 0.58+ 0.23+ 0.37+ 0.35+ 0.33+ 0.31+ 0.17+ 0.30+ 0.82+ --
CP 5.36 (1.12) 0.30+ 0.13* 0.30+ 0.26+ 0.23+ 0.31+ 0.24+ 0.25+ 0.18+ 0.29+ 0.78+ 0.37+ -- CO 6.03 (0.77) 0.46+ 0.26+ 0.50+ 0.24+ 0.39+ 0.40+ 0.35+ 0.39+ 0.21+ 0.32+ 0.79+ 0.68+ 0.35+
Note. EI = Emotional Intelligence; SA = Self-Awareness; SM = Self-Management; AO = Awareness of
Others; MO = Management of Others; SO = SOAR; ST = Strengths; OP = Opportunities; AS =
Aspirations; RE = Results; CL = Collaboration; IN = Integrating; CP = Compromising; CO =
Communication. *p < .05. Correlation is significant at the 0.05 level (2-tailed).
+p < .01. Correlation is significant at the 0.01 level (2-tailed).
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 107
Descriptive Statistics
This section presents the results of descriptive statistical analysis of the following
study constructs: EI, Collaboration, and SOAR. For each study construct variable, the
mean and SD are given. Additionally, the mean and SD for each study variable is given
across each demographic characteristic. For the descriptive statistics tables, if the
distribution was not evenly distributed, i.e, there was a significant distribution, and if the
mean scores within each demographic characteristic were significantly different, then the
mean score for the relevant demographic characterstic was annotated depending on the
level of significance ( *p < .05,
+p < .01). This implies the mean scores were different
from each other at either the .05 or .01 level. The analysis was done with ANOVA which
looks at mean construct scores across each demographic characteristic. Regression,
which looks at each unit change of the IV (emotional intelligence, and other covariates)
on the DV (collaboration), are presented in the next section.
Emotional Intelligence (EI). Tables 4.11 through 4.14 present the results of the
descriptive statistics of EI and its four constitutive factors, SA, SM, AO and MO across
each demographic characteristic. Results are presented as the mean and SD.
Additionally, each table presents results of ANOVA test for any difference in mean EI,
SA, SM, AO or MO score across each of the demographic characteristics.
As shown in Table 4.11, the mean scores for EI and three of its factors (SA, SM
and AO) were not significantly different across gender, age, ethnicity, and education
according to ANOVA. However, for the EI factor MO, ANOVA found differences in the
mean score for age, ethnicity, and education. Results of Tukey’s post-hoc analysis found
that the impact of age, ethnicity, and education on MO occurred in the 25-34 vs. the 55-
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 108
65 age range (mean = 5.18 vs. 5.72), Hispanics vs. White (mean = 4.38 vs. 5.57), and
High School education vs. College education (mean = 4.53 vs. 5.62), respectively.
Table 4.11 Mean and SD of Emotional Intelligence and its Four Constitutive Factors across
Gender, Age, Ethnicity, and Education
Demographic EI Full-Scale
Self-
Awareness
Self-
Management
Awareness of
Others
Management
of Others
Characteristic M SD M SD M SD M SD M SD
Total Sample 5.32 0.79 4.76 1.36 5.96 0.84 5.10 1.11 5.47 0.99
Gender
Female 5.40 0.78 4.87 1.32 5.98 0.80 5.22 1.16 5.52 1.03
Male 5.28 0.75 4.67 1.33 5.98 0.81 5.02 1.02 5.47 0.90
Age
18-24 5.18 0.75 4.77 0.84 6.08 0.58 4.92 1.45
5.00* 1.35
25-34 5.18 0.91 4.47 1.39 5.89 1.10 5.18 1.20 5.18 1.12
35-44 5.24 0.76 4.59 1.40 5.86 0.85 5.12 0.97 5.42 1.01
45-54 5.37 0.77 4.89 1.21 5.92 0.76 5.21 1.15 5.48 0.97
55-64 5.47 0.73 4.92 1.45 6.17 0.65 5.09 1.12 5.72 0.80
65-74 5.32 0.61 4.73 1.20 5.86 0.82 4.97 0.80 5.70 0.73
Ethnicity
Asian 5.18 0.93 4.33 1.62 5.80 1.00 5.37 1.27 5.24* 1.11
Black 5.21 1.11 4.45 1.78 5.90 0.99 5.20 1.15 5.30 1.11
Hispanic 4.75 1.18 4.42 1.44 5.46 1.42 4.75 1.42 4.38 1.39
White 5.39 0.70 4.84 1.26 6.03 0.72 5.12 1.07 5.57 0.91
2 or More 4.59 0.93 2.75 0.35 6.13 0.53 4.13 1.59 5.38 1.24
Other 5.25 0.64 4.80 1.98 5.35 1.23 5.35 1.35 5.60 1.13
Education
High school 5.11 0.44 4.83 0.56 5.94 0.66 5.14 1.54 4.53* 1.03
Associate 5.63 0.43 5.28 1.17 6.28 0.60 4.97 1.61 5.97 0.69
Bachelors 5.29 0.74 4.75 1.28 5.91 0.88 5.07 0.99 5.46 0.98
Masters 5.35 0.82 4.70 1.38 5.98 0.84 5.18 1.08 5.55 1.00
Doctoral 5.34 0.72 4.82 1.38 5.99 0.70 5.07 1.10 5.48 0.84
Note. *p < .05,
**p < .01 significant difference between scores within demographic characteristic according
to ANOVA. Total sample N = 308.
Table 4.12 shows that industry did not have a significant effect on EI or its four
factors. However, among self-reported position, the mean scores for EI and SA were
significantly different. Tukey’s post-hoc analysis found that for EI, CEO’s and managers
had significantly higher scores than engineers (5.64/5.51 vs. 4.83). For SA, similarly
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 109
higher scores were found for CEO’s and managers (5.53/4.99) vs. engineers (4.11). For
other self-reported positions, which may have been interpreted as titles, there was no
significant difference between positions.
Table 4.12 Mean and SD of Emotional Intelligence and its Four Constitutive Factors
across Industry, and Position
Demographic EI Full-Scale
Self-
Awareness
Self-
Management
Awareness of
Others
Management
of Others
Characteristic M SD M SD M SD M SD M SD
Total Sample 5.32 0.79 4.76 1.36 5.96 0.84 5.10 1.11 5.47 0.99
Industry
Automotive 5.07 0.75 4.50 1.25 5.84 0.89 4.77 1.10 5.16 1.10
Consulting 5.46 0.45 4.99 1.05 6.06 0.56 5.19 0.87 5.59 0.65
Education 5.34 0.79 4.83 1.37 5.97 0.83 5.09 1.13 5.47 1.00
Engineering 5.04 0.97 4.21 1.37 5.80 1.04 4.94 1.40 5.19 1.06
Finance 5.53 1.03 4.71 1.76 6.03 0.84 5.57 1.03 5.82 1.21
Government 5.35 0.67 4.63 1.39 5.95 0.46 5.20 0.98 5.60 0.98
Healthcare 5.34 0.61 4.94 1.45 6.03 0.67 4.94 1.12 5.49 0.77
IT 5.32 0.64 4.51 1.14 6.03 0.78 5.15 1.13 5.59 0.57
Marketing 5.67 1.01 5.07 1.27 6.00 1.33 5.84 0.91 5.79 1.15
Non-profit 5.38 0.74 4.86 1.43 6.15 0.53 5.00 1.07 5.48 1.16
Other 4.97 0.93 4.13 0.18 5.38 0.53 4.88 1.59 5.50 1.41
Position
Administrative 5.17*
0.87 4.55*
1.59 5.97 0.88 4.90 1.43 5.24 1.17
CEO 5.64 0.42 5.53 0.59 5.98 0.62 5.25 0.71 5.78 0.66
Consultant 5.51 0.89 4.72 1.46 6.16 0.60 5.41 1.41 5.75 1.17
Director 5.39 0.56 4.93 1.06 6.05 0.56 4.96 0.88 5.59 0.84
Educator 5.28 0.85 4.61 1.53 5.93 0.91 5.06 1.22 5.52 0.97
Engineer 4.83 0.88 4.11 1.18 5.64 1.11 4.44 1.10 5.14 0.78
Manager 5.51 0.58 4.99 1.13 6.12 0.57 5.31 0.94 5.63 0.77
Student 4.98 0.51 4.75 0.64 6.15 0.58 4.70 1.87 4.30 0.89
Supervisor 5.16 0.96 4.28 1.73 5.60 1.21 5.29 0.89 5.46 1.03
VP 5.22 1.13 4.34 1.66 5.76 1.08 5.40 1.03 5.40 1.47
Note. *p < .05,
**p < .01 significant difference between scores within demographic characteristic according
to ANOVA. Total sample N = 308.
Table 4.13 presents descriptive statistics for the team study participant was
currently active in when they completed the survey. As shown in Table 4.13 the mean
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 110
scores for EI and its four factors (SA, SM, AO, and MO) were not significantly different
across team size according to ANOVA. However, for EI, ANOVA found differences in
the mean score for team membership, team type, team role and time with team. Results
of Tukey’s post-hoc analysis found that the impact of team membership on EI was
significant between teams composed of strictly internal members, vs. both. The mean EI
score for teams composed of internal members was 5.24 vs. teams composed of internal
and external members (5.48). Mean EI scores for team type were higher in those who
interacted face-to-face (5.28) as opposed to virtually (4.87), and were highest in those
who interacted in both ways (5.45). Team role showed a very significant difference (p <
.0001) in mean EI scores between team leaders and team members, with leaders at 5.48
and members at 5.17. Time with team was also significant with a mean EI score of 5.06
for those active in a team for one to three months, vs. those active in a team for five to ten
years (5.78). Consistently, mean EI scores rose with increasing time with team.
The mean score for self-awareness (SA) was significantly different (p < .0001)
across team role, with leaders having higher SA (4.95) than members (4.57). As was
seen with mean EI scores, mean AO scores were similarly distributed across team type
with higher scores in those who interacted face-to-face (5.06) as opposed to virtually
(4.44), and were highest in those who interacted in both ways (5.27). For team role,
mean AO scores were significantly higher in team leaders (5.33) vs. 4.86 for members.
Similar to mean EI scores, mean MO scores were higher (5.96) in those who have been
with a team for five to ten years vs. one to three months (5.05), and MO consistently rose
with time in team.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 111
Table 4.13 Mean and SD of Emotional Intelligence and its Four Constitutive Factors
across Team Size, Team Membership, Team Type, Team Role, and Time Working in
This Particular Team
Demographic EI Full-Scale
Self-
Awareness
Self-
Management
Awareness of
Others
Management
of Others
Characteristic M SD M SD M SD M SD M SD
Total Sample 5.32 0.79 4.76 1.36 5.96 0.84 5.10 1.11 5.47 0.99
Team Size
2 Members 5.53 0.88 5.14 1.26 6.08 0.86 5.13 1.14 5.77 1.03
3 Members 5.35 0.74 5.12 1.42 5.86 0.74 4.99 0.89 5.42 0.88
4 Members 5.04 0.82 4.44 1.45 5.69 0.97 4.81 1.14 5.24 1.07
5 Members 5.35 0.69 4.72 1.28 6.16 0.66 5.16 1.13 5.36 1.00
6 Members 5.50 0.65 4.68 1.19 6.22 0.61 5.53 0.70 5.63 0.96
7-10 Members 5.17 0.83 4.58 1.30 5.83 0.88 4.95 1.29 5.31 0.99
11-15 Members 5.37 0.76 4.80 1.43 6.05 0.85 5.04 1.20 5.62 0.94
16-20 Members 5.26 1.02 4.76 1.68 5.90 0.98 5.03 1.11 5.36 1.12
21+ Members 5.61 0.68 5.16 1.20 5.94 0.90 5.46 0.85 5.91 0.88
Team Membership
Internal 5.24*
0.75 4.65 1.32 5.92 0.84 5.01 1.11 5.38 0.96
External 5.52 0.88 4.83 1.54 6.14 0.69 5.37 1.08 5.72 1.23
Both 5.48 0.87 5.05 1.38 5.97 0.90 5.27 1.11 5.66 0.99
Team Type
Virtual 4.87* 0.91 4.08 1.18 5.71 0.81 4.44 1.50 5.21 1.19
Face-to-face 5.28
0.81 4.76 1.38 5.92 0.91 5.06*
1.13 5.42 1.01
Both 5.45 0.69 4.85 1.32 6.06 0.68 5.27 0.98 5.61 0.93
Team Role
Leader 5.48**
0.77 4.95*
1.26 5.98 0.80 5.33**
1.05 5.66**
0.98
Member 5.17 0.77 4.57 1.44 5.95 0.86 4.86 1.12 5.29 0.96
Time With Team
Less than 1 Month 5.08*
0.84 4.18 1.39 5.90 0.67 4.95 1.36 5.39*
1.00
1-3 Months 5.06 0.89 4.75 1.33 5.70 1.13 4.72 1.20 5.05 1.17
3-6 Months 5.27 0.73 4.66 1.22 5.84 0.65 5.00 1.03 5.57 0.84
6-9 Months 5.26 0.58 4.45 1.37 6.11 0.56 5.29 0.89 5.18 0.97
9-12 Months 5.20 0.83 4.56 1.48 5.89 0.95 4.98 1.17 5.39 0.93
1-2 Years 5.31 0.89 4.75 1.16 5.92 0.99 5.12 1.17 5.43 1.10
2-3 Years 5.37 0.78 4.90 1.52 6.17 0.68 4.99 1.15 5.44 0.95
3-5 Years 5.45 0.65 4.74 1.58 5.92 0.82 5.39 0.99 5.78 0.69
5-10 Years 5.78 0.72 5.48 1.14 6.05 0.67 5.64 0.93 5.96 1.00
10-20 Years 5.78 0.44 4.94 1.34 6.41 0.48 5.63 0.33 6.16 0.27
Note. *p < .05,
**p < .01 significant difference between scores within demographic characteristic according
to ANOVA. Total sample N = 308.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 112
For team-based activities in general, Table 4.14 shows that the mean scores for EI
across team role and time in teams are significantly different according to ANOVA.
Team leaders are shown to have higher EI (5.43) compared to members (5.19). For time
in teams, mean EI scores are higher (5.50) for those in teams 16-20 years, vs. two to three
years (4.65). For SA, there is a significant difference in mean scores for time in teams,
with Tukey’s post-hoc analysis showing that mean SA scores are highest in those with
experience in teams 16-20 years (5.01), compared to those with two to three years of
experience (3.50). The impact of SM across team role and time in teams shows no
significant difference, but mean scores for AO are significantly different across team role
with leaders again having the higher AO score (5.28) vs. members (4.87). Time in teams
however had no impact on AO. Mean scores for MO were found to be significantly
different across team role with team leaders having the higher score (5.66) vs. members
(5.23). Additionally, mean MO scores were highest in those with extensive experience
working in teams (16+ years), compared to those with less (two to three years).
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 113
Table 4.14 Mean and SD of Emotional Intelligence and its Four Constitutive Factors across
Team Role, and Time Involved in Teams (When Working in Team-Based Activities in General)
Demographic EI Full-Scale
Self-
Awareness
Self-
Management
Awareness of
Others
Management
of Others
Characteristic M SD M SD M SD M SD M SD
Total Sample 5.32 0.79 4.76 1.36 5.96 0.84 5.10 1.11 5.47 0.99
Team Role
Leader 5.43* 0.71 4.78 1.29 6.00 0.73 5.28
+ 1.06 5.66
+ 0.89
Member 5.19 0.83 4.72 1.43 5.94 0.90 4.87 1.13 5.23 1.03
Time Involved in Teams
Less Than 1 Yr 5.31* 0.99 4.89
* 1.27 6.00 0.95 5.60 1.09 4.71
** 1.43
1-2 Years 5.71 0.47 5.00 0.63 6.25 0.63 5.75 0.69 5.83 0.82
2-3 Years 4.65 0.84 3.50 1.55 5.78 1.20 4.81 1.52 4.53 1.27
3-4 Years 5.46 0.85 5.50 1.09 5.92 1.01 4.92 0.76 5.50 0.66
4-5 Years 5.27 0.82 4.66 1.62 6.09 0.63 4.80 1.32 5.53 1.09
5-10 Years 5.03 1.01 4.28 1.54 5.75 1.15 4.98 1.24 5.14 1.18
11-15 Years 5.32 0.72 4.58 1.33 6.06 0.60 5.15 1.20 5.49 0.89
16-20 Years 5.50 0.71 5.01 1.09 6.04 0.74 5.37 0.93 5.58 0.92
20+ Years 5.41 0.65 4.91 1.28 5.99 0.72 5.07 1.03 5.67 0.80
Note. *p < .05,
**p < .01 significant difference between scores within demographic characteristic according
to ANOVA. Total sample N = 308.
Collaboration. Tables 4.15 through 4.18 present the results of the descriptive
statistics of collaboration and its three constitutive factors, integrating, compromising,
and communication across each demographic characteristic. Results are presented as the
mean and SD. Additionally, each table presents results of ANOVA test for any
difference in mean collaboration, integrating, compromising, or communication score
across each of the demographic characteristics.
As shown in Table 4.15, the mean scores for collaboration and two of its factors
(integrating and compromising) were not significantly different across gender, age,
ethnicity, and education according to ANOVA. However, for the collaboration factor
communication, ANOVA found differences in the mean score for age. Results of
Tukey’s post-hoc analysis found that the impact of age on communication occurred in the
25-34 years of age range (5.64) vs. the 55-64 years of age range (6.22).
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 114
Table 4.15 Mean and SD of Collaboration and its Three Constitutive Factors across
Gender, Age, Ethnicity, and Education
Demographic
Collaboration
Full-Scale Integrating Compromising Communication
Characteristic M SD M SD M SD M SD
Total Sample 5.86 0.73 6.19 0.86 5.36 1.12 6.03 0.77
Gender
Female 5.91 0.74 6.27 0.88 5.46 1.08 6.02 0.78
Male 5.80 0.74 6.10 0.84 5.25 1.17 6.05 0.77
Age
18-24 5.81 0.56 6.18 0.70 5.41 0.61 5.85**
0.82
25-34 5.66 1.01 6.04 1.24 5.30 1.23 5.64 1.13
35-44 5.78 0.76 6.07 0.95 5.31 1.00 5.94 0.80
45-54 5.86 0.73 6.17 0.84 5.36 1.19 6.06 0.75
55-64 6.00 0.63 6.31 0.71 5.47 1.17 6.22 0.57
65-74 5.91 0.62 6.33 0.56 5.20 1.18 6.19 0.48
Ethnicity
Asian 5.96 0.80 6.21 0.85 5.54 1.37 6.12 0.88
Black 5.75 1.13 5.91 1.09 5.40 1.50 5.93 1.08
Hispanic 5.54 1.18 5.33 1.66 5.61 1.06 5.67 1.25
White 5.87 0.69 6.33 0.80 5.34 1.09 6.04 0.74
2 or more 5.72 0.24 6.67 0.47 4.33 0.94 6.17 0.71
Other 6.07 0.58 5.93 1.23 6.13 0.51 6.13 0.69
Education
High school 5.80 0.69 6.26 0.62 5.33 1.25 5.81 0.53
Associate 5.90 0.97 6.29 0.70 5.29 1.72 6.13 0.91
Bachelors 5.71 0.69 6.07 0.86 5.16 1.01 5.90 0.76
Masters 5.87 0.79 6.21 0.92 5.38 1.16 6.02 0.84
Doctoral 5.94 0.64 6.19 0.80 5.50 1.05 6.14 0.65
Note. *p < .05,
**p < .01 significant difference between scores within demographic characteristic according
to ANOVA. Total sample N = 308.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 115
Table 4.16 shows that the mean scores for industry and self-reported position did
not have a significant effect on collaboration or its three factors, integrating,
compromising, and communication.
Table 4.16 Mean and SD of Collaboration and its Three Constitutive Factors across
Industry, and Position
Demographic
Collaboration
Full-Scale Integrating Compromising Communication
Characteristic M SD M SD M SD M SD
Total Sample 5.86 0.73 6.19 0.86 5.36 1.12 6.03 0.77
Industry
Automotive 5.81 0.67 6.21 0.77 4.91 1.29 6.32 0.43
Consulting 5.85 0.59 6.19 0.65 5.18 1.11 6.17 0.68
Education 5.95 0.72 6.19 0.95 5.66 0.94 6.00 0.72
Engineering 5.66 1.07 5.96 1.22 5.39 1.17 5.64 1.18
Finance 5.90 0.89 6.26 0.88 5.47 1.04 5.96 0.99
Government 5.86 0.54 6.19 0.57 5.29 1.29 6.10 0.58
Healthcare 5.78 0.62 6.24 0.74 5.13 1.21 5.98 0.62
IT 5.94 0.67 6.20 0.66 5.37 1.36 6.25 0.43
Marketing 5.76 1.12 6.05 1.41 5.40 1.11 5.83 1.23
Non-profit 5.90 0.62 6.33 0.60 5.23 1.20 6.15 0.69
Other 5.78 0.16 6.00 0.00 5.50 0.71 5.83 0.24
Position
Administrative 5.78 0.82 6.18 0.85 5.39 1.18 5.78 0.87
CEO 5.96 0.66 6.38 0.70 5.19 1.37 6.31 0.65
Consultant 5.90 0.70 6.38 0.81 5.25 1.38 6.08 0.83
Director 5.79 0.52 6.16 0.75 5.11 0.91 6.09 0.52
Educator 5.90 0.73 6.12 1.00 5.60 0.95 6.00 0.72
Engineer 5.55 1.05 5.93 1.37 5.10 1.08 5.62 1.26
Manager 5.96 0.69 6.23 0.70 5.48 1.20 6.17 0.67
Student 5.93 0.36 6.40 0.55 5.40 0.72 6.00 0.47
Supervisor 5.65 1.03 6.02 1.33 5.11 1.25 5.83 1.09
VP 5.95 0.77 6.23 0.83 5.40 1.18 6.23 0.70
Note. *p < .05, +p < .01 significant difference between scores within demographic characteristic according
to ANOVA. Total sample N = 308.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 116
As shown in Table 4.17, the mean scores for collaboration and its three
constitutive factors were not significantly different across team size and team
membership according to ANOVA. However, there was a significant difference in the
mean collaboration score across time in team. Results of Tukey’s post-hoc analysis
found that the impact of time in team on collaboration occurred in the 9-12 month range
(5.52) vs. 10-15 years (6.37). ANOVA found differences in the mean integrating score
across team type, with both face-to-face and virtual team settings being significantly
higher than either of the two alone (6.37 vs. 6.12 and 6.10 respectively). There was no
impact on the mean compromising score across team type, team role or time with team.
However, the communication factor showed significant differences in team type and team
role. Here also, mean communication scores are highest in settings where teams engage
face-to-face as well as virtually (6.22), compared with either of the two alone (6.02 and
5.93 respectively). Finally, mean scores for communication were higher for team leaders
(6.17) vs. team members (5.90).
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 117
Table 4.17 Mean and SD of Collaboration and its Three Constitutive Factors across Team
Size, Team Membership, Team Type, Team Role, and Time Working in This Particular
Team
Demographic
Collaboration
Full-Scale Integrating Compromising Communication
Characteristic M SD M SD M SD M SD
Total Sample 5.86 0.73 6.19 0.86 5.36 1.12 6.03 0.77
Team Size
2 Members 5.85 0.81 6.31 0.85 5.31 1.24 5.95 0.77
3 Members 5.81 0.78 6.17 0.83 5.35 1.13 5.93 0.91
4 Members 5.69 0.70 5.97 1.07 5.27 1.04 5.82 0.67
5 Members 5.95 0.58 6.12 0.62 5.53 1.05 6.21 0.57
6 Members 5.91 0.60 6.29 0.76 5.37 0.87 6.08 0.83
7-10 Members 5.84 0.88 6.20 1.05 5.34 1.15 5.97 0.94
11-15 Members 5.87 0.65 6.28 0.69 5.33 1.16 5.99 0.65
16-20 Members 5.87 0.73 6.12 0.79 5.45 1.30 6.03 0.68
21+ Members 5.94 0.76 6.29 0.85 5.27 1.37 6.27 0.60
Team Membership
Internal 5.81 0.76 6.12 0.92 5.33 1.10 5.96 0.80
External 5.95 0.66 6.38 0.58 5.40 1.21 6.08 0.72
Both 5.98 0.64 6.30 0.72 5.43 1.18 6.21 0.64
Team Type
Face-to-face 5.80 0.79 6.10*
0.95 5.36 1.14 5.93+
0.84
Virtual 5.86 0.71 6.12 0.65 5.45 0.95 6.02 0.68
Both 5.99 0.56 6.37 0.62 5.37 1.12 6.22 0.56
Team Role
Leader 5.93 0.65 6.26 0.76 5.36 1.11 6.17+
0.66
Member 5.80 0.79 6.12 0.94 5.39 1.14 5.90 0.83
Time With Team
Less than 1 Mth 5.80*
0.60 5.96 0.82 5.52 0.75 5.93 0.57
1-3 Months 5.74 0.93 6.02 1.12 5.37 1.24 5.83 0.99
3-6 Months 5.62 0.56 6.07 0.66 4.91 0.75 5.88 0.76
6-9 Months 6.04 0.56 6.47 0.55 5.46 1.26 6.19 0.60
9-12 Months 5.52 0.86 5.84 1.24 4.94 1.20 5.80 1.00
1-2 Years 5.99 0.69 6.33 0.79 5.47 1.15 6.15 0.70
2-3 Years 5.97 0.68 6.29 0.70 5.46 1.19 6.15 0.60
3-5 Years 5.92 0.68 6.14 0.83 5.63 1.02 6.00 0.60
5-10 Years 5.99 0.73 6.17 0.77 5.74 0.93 6.06 0.85
10-20 Years 6.36 0.53 6.75 0.58 5.75 1.34 6.58 0.24 Note. *p < .05,
+p < .01 significant difference between scores within demographic characteristic according
to ANOVA. Total sample N = 308.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 118
For team-based activities in general, Table 4.18 shows the mean scores for
collaboration and two of its three factors (integrating and compromising) were not
significantly different across team role and time in teams. However, for the
communication factor, ANOVA found differences in the mean score for both team role
and time in teams. Team role showed team leaders with significantly higher scores (6.11)
compared to team members (5.89). Results of Tukey’s post-hoc analysis found that the
impact of time involved in teams on communication occurred in the two to three year
range (5.52) vs. 16-20 years (6.20).
Table 4.18 Mean and SD of Collaboration and its Three Constitutive Factors across
Team Role, and Time Involved in Teams (When Working in Team-Based Activities in
General)
Demographic
Collaboration
Full-Scale Integrating Compromising Communication
Characteristic M SD M SD M SD M SD
Total Sample 5.86 0.73 6.19 0.86 5.36 1.12 6.03 0.77
Team Role
Leader 5.92 0.67 6.26 0.76 5.41 1.11 6.11*
0.67
Member 5.76 0.83 6.06 1.01 5.33 1.13 5.89 0.91
Time Involved in Teams
Less Than 1 Yr 6.03 0.77 6.29 0.76 5.81 1.03 6.00*
0.61
1-2 Years 6.19 0.57 6.28 0.80 6.28 0.65 6.00 0.60
2-3 Years 5.51 0.63 5.96 0.81 5.04 0.73 5.52 0.93
3-4 Years 6.11 0.51 6.00 1.00 5.78 0.84 6.56 0.38
4-5 Years 5.86 0.63 6.46 0.69 5.31 1.13 5.81 0.88
5-10 Years 5.61 1.09 5.94 1.35 5.19 1.23 5.69 1.19
11-15 Years 5.84 0.73 6.16 0.95 5.39 1.08 5.98 0.83
16-20 Years 5.93 0.73 6.17 0.81 5.42 1.12 6.20 0.74
20+ Years 5.92 0.61 6.27 0.66 5.36 1.16 6.14 0.53
Note. *p < .05, +p < .01 significant difference between scores within demographic characteristic according
to ANOVA. Total sample N = 308.
SOAR. Tables 4.19 through 4.22 present the results of the descriptive statistics of
SOAR and its four constitutive factors, S, O, A, and R across each demographic
characteristic. Results are presented as the mean and SD. Additionally, each table
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 119
presents results of ANOVA test for any significant difference in mean SOAR, S, O, A, or
R score across each of the demographic characteristics. As shown in Table 4.19, S and A
did show a significant difference across gender, with females having a higher mean score
of 8.03 vs. 7.68, and 7.19 vs. 6.77 respectively.
For age, mean scores for SOAR, S, and O showed a significant difference
according to ANOVA. Tukey’s post-hoc analysis showed difference between the age
range 18-24 (7.03) compared to the age range 65-74 (8.17), but also a general increase in
SOAR with age. Mean scores for S across age showed a difference in the age range 18-
24 (6.85) vs. age range 45-54 (7.94) and 65-74 (8.27). Mean scores for O across age
showed difference in the age range 18-24 (6.82) vs. all other age ranges which were
significantly higher between 8.24 and 8.81.
For education, mean scores for SOAR, S and O showed a very significant
difference between those who achieved at least an associate degree, compared to those
who’s highest level of education was high school. In all cases, recognizing some level of
university education grows mean scores for SOAR, S, O, A and R by at least 1 full point.
While mean scores for SOAR and all its constitutive factors generally increase with
education, the largest incremental increase comes with education beyond high school.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 120
Table 4.19 Mean and SD of SOAR and its Four Constitutive Factors across Gender, Age,
Ethnicity, and Education
Demographic
SOAR Full-
Scale Strengths Opportunities Aspirations
Results
Characteristic M SD M SD M SD M SD M SD
Total Sample 8.00 1.05 7.96 1.27 8.40 1.25 7.52 1.54 8.13 1.37
Gender
Female 8.10 1.07 8.12* 1.29 8.46 1.26 7.68 1.49 8.16 1.32
Male 7.89 1.03 7.79 1.25 8.32 1.26 7.35 1.56 8.10 1.44
Age
18-24 7.06* 0.91 6.92* 0.82 6.82+ 1.26 7.08 1.40 7.44 1.07
25-34 8.08 0.90 8.06 1.21 8.34 1.26 7.46 1.40 8.47 1.00
35-44 7.89 1.30 7.87 1.55 8.24 1.52 7.63 1.76 7.83 1.58
45-54 7.98 1.03 7.98 1.11 8.30 1.25 7.53 1.56 8.11 1.32
55-64 8.13 0.96 8.03 1.33 8.75 0.93 7.54 1.52 8.18 1.44
65-74 8.34 0.78 8.36 0.94 8.81 0.75 7.56 1.20 8.61 1.24
Ethnicity
Asian 8.30 0.94 7.91 1.31 8.76 1.12 7.84 1.66 8.70 0.98
Black 8.12 1.14 8.02 1.29 8.29 1.25 7.71 1.68 8.44 1.03
Hispanic 7.75 2.07 7.67 2.39 7.94 2.28 7.22 2.03 8.17 1.81
White 7.99 1.01 7.97 1.23 8.41 1.21 7.51 1.48 8.06 1.40
2 or more 6.71 1.36 6.67 0.00 6.50 2.59 5.50 1.65 8.17 1.18
Other 8.54 1.44 9.08 1.42 8.33 1.47 7.75 2.87 9.00 1.41
Education
High school 6.57+ 0.83 6.67* 0.96 6.63+ 1.43 5.96 1.62 7.04 1.12
Associate 8.17 1.67 8.29 1.58 8.33 1.57 7.46 2.66 8.58 1.64
Bachelors 7.92 0.88 7.79 1.06 8.27 1.00 7.58 1.29 8.04 1.08
Masters 8.04 1.10 8.08 1.36 8.41 1.34 7.55 1.59 8.11 1.47
Doctoral 8.13 0.89 7.96 1.16 8.66 1.00 7.58 1.36 8.32 1.29
Note. *p < .05, +p < .01 significant difference between scores within demographic characteristic according
to ANOVA. Total sample N = 308.
Table 4.20 shows that the mean scores for SOAR, S and R did not have a
significant difference across industry and self-reported position according to ANOVA.
Tukey’s post-hoc analysis revealed that the mean score for A showed a significant
difference across industry, with marketing at 8.29 and engineering at 6.08. Mean scores
for O across self-reported position also were significantly different between students (6.6)
and managers (8.58), directors (8.64) and VP’s (8.67). It can also be observed that mean
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 121
EI scores for engineering and engineers are consistently lowest in SOAR and each of its
constitutive factors.
Table 4.20 Mean and SD of SOAR and its Four Constitutive Factors across Industry, and
Position
Demographic
SOAR Full-
Scale Strengths Opportunities Aspirations
Results
Characteristic M SD M SD M SD M SD M SD
Total Sample 8.00 1.05 7.96 1.27 8.40 1.25 7.52 1.54 8.13 1.37
Industry
Automotive 8.02 0.89 8.11 1.11 8.64 0.97 7.24* 1.62 8.08 1.55
Consulting 7.99 0.86 7.62 1.20 8.54 0.97 7.74 1.21 8.08 1.26
Education 8.07 1.13 8.10 1.31 8.40 1.37 7.52 1.52 8.25 1.38
Engineering 7.54 0.97 7.56 1.23 7.99 1.36 6.67 1.41 7.96 1.24
Finance 8.31 1.53 8.35 1.55 8.65 1.65 7.89 1.84 8.37 1.63
Government 7.92 1.07 7.92 1.51 8.02 1.19 7.36 1.58 8.38 1.55
Healthcare 7.82 0.96 7.93 1.09 8.07 1.36 7.59 1.41 7.69 1.56
IT 8.00 1.19 7.98 1.33 8.37 1.25 7.06 2.10 8.61 1.09
Marketing 8.52 0.78 8.33 1.10 8.83 0.98 8.60 0.94 8.31 0.78
Non-profit 8.02 0.93 7.84 1.38 8.64 0.88 7.40 1.43 8.18 1.37
Other 7.33 0.82 8.00 0.94 7.67 1.41 6.83 1.65 6.83 0.71
Position
Administrative 7.76 1.39 7.83 1.53 7.90+ 1.48 7.28 1.75 8.01 1.61
CEO 8.05 1.05 7.73 1.35 8.58 0.94 7.77 1.46 8.10 1.36
Consultant 8.13 1.17 8.21 1.48 8.67 1.37 7.25 1.54 8.38 1.01
Director 8.01 0.87 8.05 1.16 8.64 0.99 7.51 1.28 7.83 1.20
Educator 8.02 1.14 7.91 1.36 8.41 1.35 7.37 1.48 8.40 1.44
Engineer 7.54 0.86 7.57 0.77 7.93 1.43 6.52 1.79 8.12 0.94
Manager 8.19 0.89 8.10 1.18 8.58 1.15 7.87 1.41 8.21 1.41
Student 6.85 0.97 7.07 0.83 6.60 1.59 6.47 1.83 7.27 0.92
Supervisor 7.91 1.13 7.86 1.50 8.28 1.10 7.24 1.59 8.26 1.12
VP 8.22 1.00 8.31 1.08 8.67 1.06 7.60 1.65 8.29 1.65
Note. *p < .05, +p < .01 significant difference between scores within demographic characteristic according
to ANOVA. Total sample N = 308.
As shown in Table 4.21 the mean scores for SOAR were not significantly
different across team size, team membership, team type, team role and time with team
according to ANOVA. For S, ANOVA found a significant difference in mean S scores
across team size, and following Tukey’s post-hoc analysis, this significant difference
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 122
occurs with teams of two members having a mean S score of 8.23 vs. teams with 21 or
more members (8.46). It can also be observed that in general, as team size grows so does
S. For O, there was no significant difference in mean O scores across team size and time
with team according to ANOVA. However, there was a significant difference in mean O
scores across team membership, team type and team role. Across team membership,
mean O scores were lowest (8.27) for internal teams, then 8.62 for teams that engaged
both internal and external team members, and highest for external teams (8.82). Mean
scores for O across team type were significantly different with the mean O score for face-
to-face interactions (8.28) vs. teams engaging members from both internal and external
sources (8.62). Mean O scores across team role are also significantly different according
to ANOVA, with team leaders showing higher mean O scores (8.65) than team members
at 8.24. And finally, significant by ANOVA, are mean A scores across team type.
Tukey’s post-hoc analysis found that teams engaging in a strictly virtual space have the
lowest mean A scores (5.65) compared to the differentially higher mean A scores for
face-to-face teams (7.03).
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 123
Table 4.21 Mean and SD of SOAR and its Four Constitutive Factors across Team Size,
Team Membership, Team Type, Team Role, and Time Working in This Particular Team
Demographic
SOAR Full-
Scale Strengths Opportunities Aspirations
Results
Characteristic M SD M SD M SD M SD M SD
Total Sample 8.00 1.05 7.96 1.27 8.40 1.25 7.52 1.54 8.13 1.37
Team Size
2 Members 8.07 0.78 8.46* 1.17 8.15 1.01 7.40 1.60 8.26 1.45
3 Members 7.63 0.88 7.43 1.26 8.28 1.23 6.96 1.48 7.85 1.23
4 Members 7.73 1.21 7.69 1.44 8.01 1.49 7.21 1.59 8.00 1.32
5 Members 7.92 0.98 7.88 1.16 8.39 1.30 7.30 1.54 8.11 1.33
6 Members 7.98 1.35 7.69 1.68 8.32 1.44 7.47 1.38 8.45 1.53
7-10 Members 8.06 1.01 8.06 1.13 8.40 1.16 7.61 1.44 8.17 1.36
11-15 Members 8.07 0.99 7.91 1.22 8.49 1.29 7.75 1.37 8.14 1.47
16-20 Members 8.06 1.02 8.16 1.17 8.51 1.29 7.76 1.49 7.83 1.43
21+ Members 8.53 0.96 8.62 1.09 8.96 0.85 8.17 1.93 8.36 1.35
Team Membership
Internal 7.91 1.09 7.93 1.31 8.27* 1.34 7.39 1.54 8.04 1.40
External 8.28 0.75 8.05 1.20 8.82 0.92 7.83 1.77 8.42 1.28
Both 8.18 0.95 7.98 1.19 8.62 1.00 7.83 1.39 8.31 1.28
Team Type
Face-to-face 7.95 1.11 7.96 1.30 8.28* 1.31 7.53 1.45 8.03 1.37
Virtual 7.71 1.04 7.95 1.49 8.03 1.44 6.83 1.60 8.03 1.24
Both 8.16 0.90 7.98 1.20 8.67 1.06 7.61 1.66 8.37 1.35
Team Role
Leader 8.09 0.95 8.01 1.23 8.56*
1.06 7.67 1.37 8.14 1.34
Member 7.93 1.14 7.95 1.32 8.24 1.41 7.40 1.69 8.16 1.40
Time With Team
Less than 1 Mth 7.58 0.97 7.39 1.30 7.59 1.19 7.31 1.82 8.04 1.32
1-3 Months 8.03 1.17 7.98 1.37 8.41 1.45 7.44 1.53 8.27 1.36
3-6 Months 7.90 0.80 7.88 1.08 8.18 1.16 7.44 1.24 8.11 1.00
6-9 Months 8.07 0.80 7.78 1.03 8.68 0.95 7.39 1.19 8.42 1.24
9-12 Months 7.70 1.23 7.50 1.41 8.05 1.47 7.37 1.70 7.88 1.52
1-2 Years 8.14 0.94 8.27 1.14 8.38 1.09 7.74 1.43 8.20 1.31
2-3 Years 8.01 1.05 7.95 1.25 8.53 1.30 7.45 1.77 8.10 1.51
3-5 Years 8.10 1.05 8.11 1.49 8.57 0.83 7.38 1.66 8.35 1.25
5-10 Years 7.89 1.46 8.08 1.54 8.48 1.70 7.70 1.79 7.30 1.70
10-20 Years 8.97 0.54 8.63 0.95 9.24 0.71 8.75 0.64 9.29 0.85
Note. *p < .05, +p < .01 significant difference between scores within demographic characteristic according
to ANOVA. Total sample N = 308.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 124
As shown in Table 4.22, the mean scores for SOAR, S, A, and R were not
significantly different across team role and time involved with teams according to
ANOVA. However for O, ANOVA found a significant difference in mean O scores
across team role, and time involved with teams. When working in team-based activities
in general, team leaders reported significantly higher O scores (8.51) compared to
members (8.20). Tukey’s post-hoc analysis found the significant difference with time in
teams to be from two to three years (7.44) vs. time in teams greater than five years (8.06).
From five to greater than 20 years, mean O scores rose consistently peaking at 8.72 for
those involved in teams for more than 20 years.
Table 4.22 Mean and SD of SOAR and its Four Constitutive Factors across Team Role,
Time Involved in Teams (When Working in Team-Based Activities in General)
Demographic
SOAR Full-
Scale Strengths Opportunities Aspirations
Results
Characteristic M SD M SD M SD M SD M SD
Total Sample 8.00 1.05 7.96 1.27 8.40 1.25 7.52 1.54 8.13 1.37
Team Role
Leader 8.08 0.96 7.99 1.22 8.51* 1.06 7.61 1.43 8.20 1.30
Member 7.87 1.18 7.90 1.36 8.20 1.51 7.35 1.68 8.02 1.48
Time Involved in Teams
Less Than 1 Yr 7.97 1.10 7.58 2.00 8.61+ 1.18 7.33 0.94 8.33 1.23
1-2 Years 8.44 1.15 8.39 1.39 8.22 0.98 8.08 1.54 9.06 1.06
2-3 Years 7.36 1.04 7.41 1.14 7.44 1.64 6.48 1.41 8.11 1.29
3-4 Years 8.00 0.93 8.67 0.88 8.33 0.67 7.11 2.22 7.89 1.02
4-5 Years 7.67 0.88 7.56 1.25 7.77 1.36 7.19 1.39 8.15 1.20
5-10 Years 7.86 1.29 7.78 1.39 8.06 1.55 7.49 1.66 8.11 1.47
11-15 Years 7.86 1.20 7.84 1.31 8.18 1.40 7.52 1.47 7.90 1.28
16-20 Years 8.15 0.98 8.14 1.35 8.44 1.09 7.67 1.60 8.34 1.36
20+ Years 8.11 0.96 8.05 1.17 8.72 1.06 7.57 1.54 8.09 1.43
Note. *p < .05, +p < .01 significant difference between scores within demographic characteristic according
to ANOVA. Total sample N = 308.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 125
Hypotheses Testing Results for H1
H1. Emotional intelligence is related to collaboration such that EI has a positive
impact on collaboration.
This section presents the results of linear regression analyses used to test H1:
there is a significant relationship between emotional intelligence (EI) and collaboration.
Results are first presented of the regression of collaboration on the EI full scale score.
Next, results are presented of regression of collaboration on the EI factors in order to
determine the EI competencies that are most important for achieving collaboration among
teams and team members. In all regressions, demographic characteristics were included
as covariates where appropriate.
Table 4.23 shows the result of collaboration regressed on EI to determine if EI
predicts collaboration. Expressed as unstandardized regression coefficients (to assist
with real-world practical interpretation), the regression of collaboration on EI alone was β
= .470**
, and Z = 9.67, which supports H1 and confirms that EI is a significant predictor
of collaboration. β was found to be significant at p < .01 which implies that for every
unit increase in EI, there is a linear relationship with collaboration such that there is a
positive change of 0.47 units of collaboration.
Table 4.23 Collaboration Regressed on EI Alone (EI Predicting Collaboration)
Collaboration
Variable Beta SE Z
Constant 3.353**
.262 12.81
EI 0.470**
.049 9.67
R-square
24.1% Note. See text for coding of variables. *p < .05,
**p < .01 Regression coefficient
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 126
In testing hypotheses, it is important it investigate the potential impact of sample
characteristics in order to determine their effect on the outcome variable. In the analysis
of EI as a predictor of collaboration, it was necessary to include those demographic
characteristics that were not evenly distributed across the sample (non-equal proportions
in each category of the variable) in order to determine their effect on collaboration. In
this case age, ethnicity, and education were included as covariates since the sample was
significantly distributed across these three fundamental demographic characteristics (see
Table 4.1), i.e., the regression analyses controlled for age, ethnicity, and education. As
covariates, age and education were included using their initial coding scheme, whereas
ethnicity was recoded as a dichotomous variable with whites coded as a two, and all other
ethnicities coded as a one. All betas for H1 and H2 reflect this recoding.
As a first step in the investigation of age, ethnicity, and education as covariates in
the analysis of collaboration regressed on EI, Tables 4.11 and 4.15 were revisited to
further understand the potential impact of these demographic characteristics on EI and
collaboration according to ANOVA. As shown in Table 4.11, ANOVA found no
difference in mean scores of EI and three of its factors, SA, SM, and AO across age,
ethnicity, and education. However, for MO, there was a significant difference across age,
ethnicity, and education, thereby increasing the need to include these demographic
variables as covariates. As shown in Table 4.15, ANOVA found no significant difference
in mean scores for collaboration and two of its factors, integrating and compromising
across age, ethnicity, and education. However, there was a significant different in mean
scores for the collaboration factor communication across age.
Tables 4.24-4.32 present regression analyses as the following two-step process:
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 127
1) In the first step, collaboration was regressed on age, ethnicity, and education to
test the regression of demographic characteristics on collaboration.
2) In the second step, EI and its factors SA, SM, AO and MO were added to the
regression model to test the full impact of the study predictor EI on collaboration
while controlling for age, ethnicity, and education.
Table 4.24 presents the regression of collaboration on age, ethnicity, and
education alone (see Step 1). As shown, there was no significant effect for age, ethnicity,
and education, i.e., the β’s were minimal (.059 or less), p > .05, R-square was low
(1.7%), and the variation on β was negligible. Also shown in Table 4.24 is the regression
of collaboration on EI controlling for age, ethnicity, and education (see Step 2). As
shown, the β for EI was significant at .475 (p < .01), and R-square increased to 25.4%,
with EI contributing 23.7% of the positive variance in collaboration. Steps one and two
show that when including age, ethnicity, and education in the regression of collaboration
on EI, EI remains a significant predictor of positive collaboration. There is essentially no
variation in collaboration that can be attributed to the demographic characteristics.
Table 4.24 Collaboration Regressed on EI (EI predicting collaboration controlling for
age, ethnicity, and education)
Collaboration
Variable Step 1 Step 2
Beta SE Z Beta SE Z
Age .059 .035 1.67 .032 .031 1.04
Ethnicity .003
.119 .028 -.111 .104 -1.06
Education .046 .050 .918 .043 .044 .991
EI .475**
.051 9.38
R-square
1.7% 25.4%
Change in R-square 23.7%**
Note. See text for coding of variables. *p < .05,
**p < .01 Regression coefficient, Change in R-square
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 128
Table 4.25 presents the regression of collaboration on age, ethnicity, and
education alone (see Step 1). As shown, there was no significant effect for age, ethnicity,
and education, i.e., the β’s were minimal (.059 or less), p > .05, R-square was low
(1.7%), and the variation on β was negligible. Also shown in Table 4.25 is the regression
of collaboration on SA controlling for age, ethnicity, and education (see Step 2). As
shown, the β for SA was significant at .133 (p < .01), and R-square increased to 7.4%,
with SA contributing 5.7% of the positive variance in collaboration. Steps one and two
show that when including age, ethnicity, and education in the regression of collaboration
on SA, SA remains a significant predictor of positive collaboration. There is essentially
no variation in collaboration that can be attributed to the demographic characteristics.
Table 4.25 Collaboration Regressed on SA (SA predicting collaboration)
Collaboration
Variable Step 1 Step 2
Beta SE Z Beta SE Z
Age .059 .035 1.67 .049 .034 1.409
Ethnicity .003
.119 .023 -.050 .116 -.431
Education .046 .050 .915 .051 .049 1.040
SA .133**
.032 4.112
R-square
1.7% 7.4%
Change in R-square 5.7%**
Note. See text for coding of variables. *p < .05,
**p < .01 Regression coefficient, Change in R-square
Table 4.26 presents the regression of collaboration on age, ethnicity, and
education alone (see Step 1). As shown, there was no significant effect for age, ethnicity,
and education, i.e., the β’s were minimal (.059 or less), p > .05, R-square was low
(1.7%), and the variation on β was negligible. Also shown in Table 4.26 is the regression
of collaboration on SM controlling for age, ethnicity, and education (see Step 2). As
shown, the β for SM was significant at .522 (p < .01), and R-square increased to 32.6%,
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 129
with SM contributing 30.9% of the positive variance in collaboration. Steps one and two
show that when including age, ethnicity, and education in the regression of collaboration
on SM, SM remains a significant predictor of positive collaboration. There is essentially
no variation in collaboration that can be attributed to the demographic characteristics.
Table 4.26 Collaboration Regressed on SM (SM predicting collaboration)
Collaboration
Variable Step 1 Step 2
Beta SE Z Beta SE Z
Age .059 .035 1.672 .046 .029 1.577
Ethnicity .003 .119 .028 -.135 .099 -1.356
Education .046 .050 .918 .043 .042 1.038
SM .522**
.046 11.272
R-square
1.7% 32.6%
Change in R-square 30.9%**
Note. See text for coding of variables. *p < .05,
**p < .01 Regression coefficient, Change in R-square
Table 4.27 presents the regression of collaboration on age, ethnicity, and
education alone (see Step 1). As shown, there was no significant effect for age, ethnicity,
and education, i.e., the β’s were minimal (.059 or less), p > .05, R-square was low
(1.7%), and the variation on β was negligible. Also shown in Table 4.27 is the regression
of collaboration on AO controlling for age, ethnicity, and education (see Step 2). As
shown, the β for AO was significant at .215 (p < .01), and R-square increased to 12.2%,
with EI contributing 10.5% of the positive variance in collaboration. Steps one and two
show that when including age, ethnicity, and education in the regression of collaboration
on AO, AO remains a significant predictor of positive collaboration. There is essentially
no variation in collaboration that can be attributed to the demographic characteristics.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 130
Table 4.27 Collaboration Regressed on AO (AO predicting collaboration)
Collaboration
Variable Step 1 Step 2
Beta SE Z Beta SE Z
Age .059 .035 1.672 .061 .033 1.836
Ethnicity .003 .119 .028 .013 .113 .119
Education .046 .050 .918 .044 .047 .933
AO .215**
.038 5.742
R-square
1.7% 12.2%
Change in R-square 10.5%**
Note. See text for coding of variables. *p < .05,
**p < .01 Regression coefficient, Change in R-square
Table 4.28 presents the regression of collaboration on age, ethnicity, and
education alone (see Step 1). As shown, there was no significant effect for age, ethnicity,
and education, i.e., the β’s were minimal (.054 or less), p > .05, R-square was low
(1.6%), and the variation on β was negligible. Also shown in Table 4.28 is the regression
of collaboration on MO controlling for age, ethnicity, and education (see Step 2). As
shown, the β for MO was significant at .300 (p < .01), and R-square increased to 16.3%,
with MO contributing 14.7% of the positive variance in collaboration. Steps one and two
show that when including age, ethnicity, and education in the regression of collaboration
on MO, MO remains a significant predictor of positive collaboration. There is essentially
no variation in collaboration that can be attributed to the demographic characteristics.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 131
Table 4.28 Collaboration Regressed on MO (MO predicting collaboration)
Collaboration
Variable Step 1 Step 2
Beta SE Z Beta SE Z
Age .054 .036 1.515 .016 .033 .484
Ethnicity .008 .119 .070 -.092 .111 -.826
Education .048 .050 .961 .036 .046 .780
MO .300**
.043 6.957
R-square
1.6% 16.3%
Change in R-square 14.7%**
Note. See text for coding of variables. *p < .05,
**p < .01 Regression coefficient, Change in R-square
Analyzing the impact of EI and its constitutive factors as predictors of
collaboration, Tables 4.24 through 4.28 have shown by the regression coefficients that EI
(β = .475), SA (β = .133), SM (β = .522), AO (β = .215) and MO (β = .300) all contribute
positively to collaboration at p < .01, with SM (β = .522) and MO (β = .300) being the
primary predictors.
Table 4.29 presents the regression of collaboration on age, ethnicity, and
education alone (see Step 1). As shown, there was no significant effect for age, ethnicity,
and education, i.e., the β’s were minimal (.054 or less), p > .05, R-square was low
(1.6%), and the variation on β was negligible. Also shown in Table 4.29 is the regression
of collaboration on the four EI factors (SA, SM, AO, and MO) controlling for age,
ethnicity, and education (see Step 2). As shown, the β for SM was significant at .434 (p
< .01), as was MO at .104 (p < .05). R-square increased to 36.4%, with the four EI
factors (SA, SM, AO, and MO) contributing 34.8% of the positive variance in
collaboration. Steps one and two show that when including age, ethnicity, and education
in the regression of collaboration on SA, SM, AO, and MO, the four EI factors remain a
significant predictor of positive collaboration. There is essentially no variation in
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 132
collaboration that can be attributed to the demographic characteristics, and SM (β = .434)
and MO (β = .104) are the most influential in predicting collaboration.
Table 4.29 Collaboration Regressed on SA, SM, AO and MO
Collaboration
Variable Step 1 Step 2
Beta SE Z Beta SE Z
Age .054 .036 1.512 .032 .030 1.093
Ethnicity .008 .119 .066 -.147 .098 -1.496
Education .048 .050 .958 .040 .041 .990
SA .014 .030 .468
SM .434**
.051 8.586
AO .070 .039 1.787
MO .104* .049 2.149
R-square
1.6% 36.4%
Change in R-square 34.8%**
Note. See text for coding of variables. *p < .05,
**p < .01 Regression coefficient, Change in R-square
In the preceding analyses, the determination of EI and its factors as predictors of
collaboration was confirmed. To further understand the relationship between EI and
collaboration, regression of the individual collaboration factors (integrating,
compromising, and communication) on EI are shown in Tables 4.30 through 4.32. These
regressions will show how EI predicts the constitutive elements of collaboration similar
to how EI and its factors predict collaboration.
In this regression two steps were conducted:
1) Integrating was regressed on age, ethnicity, and education (to show their
impact alone on integrating).
2) Integrating was regressed on EI to show its impact on integrating
(controlling for age, ethnicity, and education).
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 133
Table 4.30 presents the regression of integrating on age, ethnicity, and education
alone (see Step 1). As shown, there was no significant effect for age, ethnicity, and
education, i.e., the β’s were minimal (.190 or less), p > .05, R-square was low (1.7%),
and the variation on β was negligible. Also shown in Table 4.30 is the regression of
integrating on EI controlling for age, ethnicity, and education (see Step 2). As shown, the
β for EI was significant at .487 (p < .01), and R-square increased to 20.1%, with EI
contributing 18.4% of the positive variance in integrating. Steps one and two show that
when including age, ethnicity, and education in the regression of integrating on EI, EI
remains a significant predictor of integrating. There is essentially no variation in
integrating that can be attributed to the demographic characteristics.
Table 4.30 Integrating Regressed on EI (EI predicting integrating)
Integrating
Variable Step 1 Step 2
Beta SE Z Beta SE Z
Age .059 .041 1.439 .031 .037 .843
Ethnicity .190 .138 1.375 .073 .126 .583
Education .006 .058 .094 .003 .053 .053
EI .487**
.061 7.982
R-square
1.7% 20.1%
Change in R-square 18.4%**
Note. See text for coding of variables. *p < .05,
**p < .01 Regression coefficient, Change in R-square
In this regression two steps were conducted:
1) Compromising was regressed on age, ethnicity, and education (to show
their impact alone on compromising).
2) Compromising was regressed on EI (to show its impact on compromising
(controlling for age, ethnicity, and education).
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 134
Table 4.31 presents the regression of compromising on age, ethnicity, and
education alone (see Step 1). As shown, there was no significant effect for age, ethnicity,
and education, i.e., the β’s were minimal (.090 or less), p > .05, R-square was low
(0.7%), and the variation on β was negligible. Also shown in Table 4.31 is the regression
of compromising on EI controlling for age, ethnicity, and education (see Step 2). As
shown, the β for EI was significant at .496 (p < .01), and R-square increased to 11.7%,
with EI contributing 10.9% of the positive variance in compromising. Steps one and two
show that when including age, ethnicity, and education in the regression of compromising
on EI, EI remains a significant predictor of compromising. There is essentially no
variation in compromising that can be attributed to the demographic characteristics.
Table 4.31 Compromising Regressed on EI (EI predicting compromising)
Compromising
Variable Step 1 Step 2
Beta SE Z Beta SE Z
Age -.004 .054 -.070 -.032 .052 -.618
Ethnicity -.144 .183 -.784 -.262 .174 -1.505
Education .090 .077 1.167 .088 .073 1.197
EI .496**
.085 5.850
R-square
0.7% 11.7%
Change in R-square 10.9%**
Note. See text for coding of variables. *p < .05,
**p < .01 Regression coefficient, Change in R-square
In this regression two steps were conducted:
1) Communication was regressed on age, ethnicity, and education (to show
their impact alone on communication).
2) Communication was regressed on EI (to show its impact on
communication (controlling for age, ethnicity, and education).
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 135
Table 4.32 presents the regression of communication on age, ethnicity, and
education alone (see Step 1). As shown, there was no significant effect for age, ethnicity,
and education, i.e., the β’s were minimal (.090 or less), p > .05, R-square was low
(0.7%), and the variation on β was negligible. Also shown in Table 4.32 is the regression
of communication on EI controlling for age, ethnicity, and education (see Step 2). As
shown, the β for EI was significant at .441 (p < .01), and R-square increased to 23.2%,
with EI contributing 18.3% of the positive variance in communication. Steps one and
two show that when including age, ethnicity, and education in the regression of
communication on EI, EI remains a significant predictor of communication. There is
essentially no variation in communication that can be attributed to the demographic
characteristics.
Table 4.32 Communication Regressed on EI (EI predicting communication)
Communication
Variable Step 1 Step 2
Beta SE Z Beta SE Z
Age .121**
.037 3.319 .096**
.033 2.914
Ethnicity -.037 .123 -.297 -.142 .112 -1.275
Education .044 .052 .847 .042 .047 .888
EI .441**
.054 8.135
R-square
4.9% 23.2%
Change in R-square 18.3%**
Note. See text for coding of variables. *p < .05,
**p < .01 Regression coefficient, Change in R-square
In the analysis of EI as a predictor of the collaboration factors, Tables 4.30
through 4.32 have shown by the regression coefficients that EI contributes positively to
each factor, integrating (β = .487), compromising (β = .496) and communication (β =
.441) at p < .01. EI has the largest impact on compromising (β = .496), followed by
integrating (β = .487) and communication (β = .441) respectively. Each regression was
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 136
controlled for age, ethnicity, and education, and here also, the contribution of the
demographic characteristics is negligible.
Overall, the regression analyses presented in Tables 4.24-4.32 show that when
controlling for age, ethnicity, and education, EI is a significant predictor of collaboration,
and when breaking EI down into its constitutive elements (SA, SM, AO, and MO), SM
and MO are the components of EI that appear to function as the most significant
predictors of collaboration. SA and AO are also significant predictors of collaboration
according to the regression coefficients, but to a lesser extent than SM and MO. EI was
also shown to be a significant predictor of the collaboration factors.
Hypotheses Testing Results for H2
H2. The impact of emotional intelligence on collaboration is moderated by
participants’ demographic characteristics.
As shown in Tables 4.33 through 4.35, an interaction term of either EI x Team
Role, EI x Team Type, or EI x Time in Teams was included in the regression analysis to
test if team role, team type, and time in teams moderate the impact of EI on collaboration.
Team role, team type, and time in teams were selected as moderators due to their
significant relationship with EI according to ANOVA (see Table 4.13). Moderation was
tested using hierarchical regression such that the effect of EI acting alone as a predictor
of collaboration was compared against a model in which EI, the moderator, and the EI x
moderator interaction term were tested.
In Table 4.33, team role was tested as a potential moderator of EI predicting
collaboration. Results of the hierarchical regression show the interaction of EI x team
role is significant (β = .255, p < .05). Furthermore, the change in R-square from 24.3%
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 137
to 26.0% is significant (1.6%, p < .05) implying that there is improvement to the model.
These results suggest that there is moderation of the EI-collaboration relationship
occurring by team role.
Table 4.33 Hieararchical Regression of Collaboration on EI and Team Role
Collaboration
Variable Step 1 Step 2 Step 3 Step 4
Age .062 .035 .036 .031
Ethnicity -.043 -.137 -.141 -.152
Education .059 .053 .052 .052
EI .458**
.464**
.334**
Team Role .037 -1.332*
EI x Team Role .255*
R-square
2.1% 24.3% 24.3% 26.0%
Change in R-square 22.1%**
0.1%
1.6%*
Note. See text for coding of variables. *p < .05,
**p < .01 Regression coefficient, Change in R-square
As shown Table 4.34, team type was tested as a potential moderator of EI
predicting collaboration. Results of the hierarchical regression show that in contrast to the
interaction of EI x team role, the interaction of EI x team type is not significant (β = -
.150, p > .05). Furthermore, the change in R-square from 24.4% to 25.3% is not
significant (0.7%, p > .05) implying that there is not improvement to the model.
However, a simples slopes test of the difference in the slopes of the lines that plot EI’s
prediction of collaboration at the three different values of team type (corresponding to
virtual, face-to-face, and both) found the slopes were significantly different at p = .01
(Aiken & West, 1991; Dawson, 2014). These results suggest that team type may be
functioning as moderator of the EI-collaboration relationship.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 138
Table 4.34 Hieararchical Regression of Collaboration on EI and Team Type
Collaboration
Variable Step 1 Step 2 Step 3 Step 4
Age .059 .033 .032 .031
Ethnicity .012 -.102 -.109 -.101
Education .047 .044 .043 .041
EI .463**
.460**
.797**
Team Type .040 .843
EI x Team Type -.150
R-square
1.8% 24.4% 24.5% 25.3%
Change in R-square 22.6%**
0.1% 0.7% Note. See text for coding of variables. *p < .05,
**p < .01 Regression coefficient, Change in R-square
In Table 4.35, time in teams was tested as a potential moderator of EI predicting
collaboration. Results of the hierarchical regression show the interaction of EI x time in
teams is significant (β = -.123, p < .05). Furthermore, the change in R-square from
26.7% to 27.9% is significant (1.1%, p < .05) implying that there is improvement to the
model. These results suggest that there is moderation of the EI-collaboration relationship
occurring by time in teams.
Table 4.35 Hieararchical Regression of Collaboration on EI and Time in Teams
Collaboration
Variable Step 1 Step 2 Step 3 Step 4
Age .059 .031 .039 .030
Ethnicity .011 -.104 -.098 -.129
Education .049 .045 .044 .045
EI .486**
.487**
.719**
Time in Teams -.020 .641
EI x Time in Teams -.123*
R-square
1.8% 26.7% 26.8% 27.9%
Change in R-square 24.9%**
0.0% 1.1%*
Note. See text for coding of variables. *p < .05,
**p < .01 Regression coefficient, Change in R-square
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 139
Hypotheses Testing Results for H3
H3. The SOAR framework mediates the relationship between emotional
intelligence and collaboration.
Table 4.36 and Figure 4.1 present the results of the full SOAR construct as a
single mediator of the relationship between EI and collaboration. In support of H3, when
the mediator, SOAR, was added to the regression as a covariate, EI remained a
significant predictor of collaboration (β = .376, Z = 3.803), and SOAR was also a
significant predictor of collaboration (β = .179, Z = 3.280). Also in support of H3, Table
4.37 and Figure 4.2 present the results of the constitutive elements of SOAR included in
the mediation analysis as multiple mediators. Results of collaboration regressed on EI
and the four mediators found EI was a significant predictor of collaboration (β = .402, Z
= 4.160), and strengths (β = .089, Z = 2.169), aspirations (β = -.061, Z = 2.064) and
results (β = .112, Z = 3.742) were also significant predictors of collaboration (the slope of
opportunities was not significantly different from zero).
As shown in Table 4.36 and Figure 4.1, the unit-free index of strength of the
mediated effect of EI on collaboration through the mediating variable SOAR is given by
the total indirect effect of X on Y = βa1b1 = .110. The Sobel test (Sobel, 1982; Z =
2.449), and the use of bootstrapping (bias corrected) 95% CI (.034, .209) found the
indirect effect to differ significantly from zero. The finding of a significant mediated
path and a significant direct c' path suggests the influence of EI on collaboration is
partially mediated by SOAR. Therefore, EI may have some additional effect on
collaboration that is not mediated by SOAR.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 140
Results shown in Table 4.37 and Figure 4.2 break down SOAR into its
constitutive elements, and test Strengths, Opportunities, Aspirations, and Results as
multiple mediators of the effect of EI on collaboration. The total indirect effect of X on Y
= .085. Although the Sobel test was not significant at the .05 level (Z = 1.874), the use of
bootstrapping (bias corrected) 95% CI (.007, .186) found the indirect effect to differ
significantly from zero. Similar to each of the c' paths, the indirect effects of EI on
collaboration through the multiple mediators strengths, aspirations and results were
significant. These results suggest that strengths, aspirations, and results were partial
mediators of the effect of EI on collaboration.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 141
Table 4.36 Mediation of the Effect of Emotional Intelligence on Collaboration through
Strengths, Opportunities, Aspirations, and Results (Full Construct) Background Factors
Product of Coefficients Bootstrapping (Bias
Corrected) 95% CI
Background factors β SE Z p Lower Upper
Path c
Emotional Intelligence .470 .071 6.646 .000 .331 .606
Path a
SOAR .624 .100 6.219 .000 .431 .830
Paths b and c'
SOAR .183 .054 3.402 .001 .069 .286
Emotional Intelligence .373 .099 3.766 .000 .202 .578
Indirect effects
SOAR .114 .046 2.495 .013 .041 .224
Total .114 .046 2.495 .013 .041 .224 *significant p < .05,
**significant p < .01,
***significant p < .001; 5,000 bootstrapping
samples; CI = confidence interval
Figure 4.1 SOAR Mediating the Effect of EI on Collaboration
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 142
Table 4.37 Mediation of the Effect of Emotional Intelligence on Collaboration through
Strengths, Opportunities, Aspirations, and Results Background Factors
Product of Coefficients Bootstrapping (Bias
Corrected) 95% CI
Background factors β SE Z p Lower Upper
Path c
Emotional Intelligence .470 .071 6.646 .000 .331 .606
Path a
Strengths .591 .113 4.861 .000 .377 .812
Opportunities .699 .110 6.356 .000 .492 .931
Aspirations .819 .144 5.202 .000 .542 1.105
Results .385 .120 3.241 .001 .162 .635
Paths b and c'
Strengths .071 .038 1.966 .049 .008 .144
Opportunities .078 .042 1.842 .065 -.004 .158
Aspirations -.064 .037 1.739 .082 -.139 .004
Results .113 .028 4.033 .000 .056 .167
Emotional Intelligence .400 .094 4.247 .000 .224 .587
Indirect effects
Strengths .042 .025 1.966 .049 .000 .098
Opportunities .054 .031 1.968 .049 .000 .123
Aspirations -.053 .029 1.787 .074 -.117 .000
Results .044 .017 2.614 .009 .018 .087
Total .087 .044 1.985 .047 .013 .184 *significant p < .05,
**significant p < .01,
***significant p < .001; 5,000 bootstrapping
samples; CI = confidence interval
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 143
Figure 4.2 SOAR and its Constitutive Factors Mediating Collaboration
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 144
Chapter 5 Discussion
Introduction
This study investigated the relationship between emotional intelligence (EI) and
collaboration, and determined the EI abilities that are most critical for achieving
collaboration among teams and team members. The study also investigated the
moderating effects of demographic factors, and the mediating effects of SOAR (a
framework for strengths-based strategic thinking), on the relationship between EI and
collaboration. Data for the study were collected via an electronically administered survey
using SurveyMonkey. Analysis of the data was completed via regression-based
inferential statistics and Structural Equation Modeling. This chapter presents the
hypothesis testing results, implications for practice and recommendations,
recommendations for future research, and concludes with potential study limitations.
Summary of Results and Discussion
The sample for this study consisted of 308 participants, essentially equally
divided between males and females. Participants were predominantly white, age 45-64,
and educated with a Master’s degree or higher. Half reported functioning as the team
leader and working with their current team for more than one year. Participants
described the majority of their teams as including 4-15 members, were internal to the
organization, and met face-to-face (as opposed to virtually). Most of the participants
reported being involved in teams for more than 10 years, and that they typically
functioned as the team leader.
The survey instrument used in this study was administered on-line to individuals
currently working in teams or those with recent experience in doing so. The five-section
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 145
survey included questions on participant demographics and team characteristics,
emotional intelligence, collaboration and SOAR. Emotional intelligence was measured
by the WEIP-S (Jordan & Lawrence, 2009), to establish respondent competency in the
four EI abilities helpful for understanding how EI works in teams. The EI construct
factors, or abilities, were awareness of own emotions, management of own emotions,
awareness of others’ emotions, and management of others’ emotions (Mayer & Salovey,
1997). Collaboration was measured by the Team Collaboration Questionnaire, an
original measure of collaborative activity uniquely developed for this study. Adapted
from Aram and Morgan (1976), and Rahim (1983a, 1983b), the Team Collaboration
Questionnaire measured three factors of collaboration: integrating, compromising, and
communication. Finally, SOAR was measured by the SOAR Profile (Cole & Stavros,
2013), a self-report measure of strengths-based strategic thinking capacity from a SOAR
framework. The measures were selected for their ability to rapidly identify EI abilities,
collaboration, and SOAR elements most critical to achieving positive outcomes in team-
based collaboration.
The psychometric properties of the WEIP-S, Team Collaboration Questionnaire,
and the SOAR Profile were evaluated via Cronbach’s coefficient alpha test of internal
consistency reliability (Cronbach, 1951), and via CFA test of construct validity (Lu, 2006)
prior to testing the hypotheses. The WEIP-S demonstrated acceptable psychometric
properties in its original form, but the Team Collaboration Questionnaire and SOAR
Profile required the following adjustments: for collaboration, six-items of the original set
of 15-items were removed leading to a final set of nine-items; and for SOAR, eight-items
from the original set of 20-items were removed leading to a final set of 12-items. In their
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 146
final form, all scales had acceptable reliability, with alpha values ranging from .853-.893
for the three study variables, EI, Collaboration, and SOAR. Cronbach’s alpha values for
the EI subscales (self-awareness, self-management, awareness of others’ emotions, and
management of others’ emotions) were also acceptable and ranged from .805-.903. The
Team Collaboration Questionnaire sub-scales (integrating, compromising, and
communication) showed alpha values ranging from .721-.909. Alpha values for the
SOAR subscales (Strengths, Opportunities, Aspirations and Results) ranged from .722-
.795. Results of higher-order CFA supported the construct validity of the study
constructs, with all three sets of measures satisfying the goodness of fit indices used to
evaluate CFA—chi-square/df ratio less than 2, RMSEA < .08, and CFI > .900.
Additionally, the factor loadings of all indicators were significant, as was the factor
loadings of all first-order latent constructs onto the higher-order constructs.
Four research questions were posed in this study:
Q1. Is there a relationship between emotional intelligence and collaboration?
Q2. Are there differences in the contribution of the emotional intelligence
abilities awareness of own emotions, management of own emotions, awareness of others’
emotions, and management of others’ emotions to collaboration?
Q3. Are there any demographic characteristics that moderate the impact
emotional intelligence may have on improved collaboration outcomes?
Q4. To help understand a potential mechanism for why EI may have an impact
on collaboration, does the SOAR framework for strengths-based strategic thinking,
planning, and leading mediate the impact that EI may have on collaboration?
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 147
Three hypotheses were tested to answer the research questions and to evaluate the
relationships between the study variables (see study model shown in Figure 5.1).
H1. Emotional intelligence is related to collaboration such that EI has a positive
impact on collaboration.
H2. The impact of emotional intelligence on collaboration is moderated by
participants’ demographic characteristics.
H3. The SOAR framework mediates the relationship between emotional
intelligence and collaboration.
Figure 5.1 Model of the Study: SOAR Mediating the Impact of Emotional Intelligence on
Collaboration with Demographic Moderating Variables
H1: Supported. Emotional intelligence is related to collaboration such that EI
has a positive impact on collaboration. H1 was tested to answer the first two research
questions: Is there a relationship between EI and collaboration? Are there differences in
the contribution of the EI factors to collaboration?
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 148
According to the results of multiple regression analyses that were used to test H1,
the answer to the first research question is that there is a robust relationship between EI
and collaboration, such that as EI grows there is a significant positive impact on
collaboration. Further regression analyses answered the second research question, that
there are differences in the contribution of each EI factor to collaboration. Self-
management (SM) and management of others (MO) were determined to be the
components of EI that function as the most significant predictors of collaboration,
followed by awareness of others (AO) and self-awareness (SA). With H1 supported,
practitioners concerned with increasing team-based collaboration are recommended to
increase EI abilities in themselves and their collaborative teams, particularly in the EI
factors of SM and MO. EI provides active support of the collaborative process, and as EI
is developed throughout the collaborative team, support of a common goal grows and
team effectiveness increases (Xavier, 2005).
EI is an important factor in predicting team performance (Jordan & Lawrence,
2009), and this study evaluated and determined the specific EI abilities that contribute to
positive collaboration in teams. The study confirmed that EI is a significant predictor of
collaboration, and that certain factors of EI contribute more than others to collaboration.
Tested by way of regression-based inferential statistics, EI was found to be a significant
predictor of collaboration, with a Beta coefficient of 0.475 when controlling for age,
ethnicity, and education (significant at the p < .01 level). This implies that for every unit
increase in EI, collaboration increases by approximately 0.48 units. When breaking
down EI into its’ constitutive factors, self-management (SM) and management of others
(MO) were determined to be the components of EI that function as the most significant
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 149
predictors of collaboration, followed by awareness of others (AO) and self-awareness
(SA). When the collective impact of the four EI abilities on collaboration were analyzed,
all had positive correlation with collaboration. SM and MO were statistically significant,
whereas SA and AO were not.
The finding that demographic characteristics of age, ethnicity, and education did
not have a significant impact on the relationship between EI and collaboration implies
that EI transcends certain participant demographic characteristics. The mean scores for
EI were not significantly different across gender, age, ethnicity, and education according
to ANOVA. Further, the regression of collaboration on age, ethnicity, and education
alone showed there was no significant effect for age, ethnicity, and education, i.e., the β’s
were minimal (.059 or less), p > .05, R-square was low (1.7%), and the variation on β
was negligible.
H2: Supported. The impact of emotional intelligence on collaboration is
moderated by participants’ demographic characteristics. H2 was tested to answer the
third research question: Are there any demographic characteristics that moderate the
impact emotional intelligence may have on improved collaboration outcomes?
According to the results of hierarchical regression analyses with demographic
interaction terms, the answer to the third research question is that team role, team type,
and time in teams moderate the impact EI has on collaboration. Furthermore, the results
of the hierarchical regression analyses suggest that EI’s impact on collaboration is
increased when team role is leader, when team type is virtual, and when time-in-teams is
greater than one year. Hierarchical regression also showed that age, gender, ethnicity and
education do not appear to have an effect on the relationship between EI and
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 150
collaboration. With H2 supported, practitioners concerned with building effective
collaborative teams are recommended to seek participants with leadership experience,
and team-based experience for greater than one year. Wolff and Koman (2008)
emphasize the impact that emotionally intelligent leaders have on organization
development and positive performance outcomes. The team should also emphasize the
impact virtual teams have on levels of EI, thereby also contributing to increased
opportunities for successful collaboration.
To facilitate the interpretation of moderating effects, three graphs were created
that plot the slope of collaboration at different levels of EI when moderated by team role
(Figure 5.2), team type (Figure 5.3), and time in teams (Figure 5.4). As shown in Figure
5.2, when individual EI is low, team role moderates the impact of EI on collaboration in
that team leaders achieve higher levels of collaboration than team members. Exhibiting
EI with a concern for self and others promotes integration of ideas, cooperation and
inclusion of all team members (Romero et al., 2009). As individual EI grows, the
distinction between leaders and members lessen, with no impact at all as EI grows from
medium to high. To have a positive impact on collaboration beyond medium levels of
EI, what matters is EI growth, not team role.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 151
Figure 5.2 Team Role as a Moderator of the Relationship between EI and Collaboration
Figure 5.3 illustrates the moderation effect of team type on EI’s prediction of
collaboration. When individual EI is low to medium, there is minimal distinction as to
team type (face-to-face or virtual). However, as individual EI grows, the ability to be
collaborative in a virtual environment significantly grows. The difference in the slopes of
the lines that plot EI’s prediction of collaboration when team type was virtual compared
to face-to-face or both was significant at p < .01 according to simple slopes analysis
(Aiken & West, 1991; Dawson, 2014).
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 152
Figure 5.3 Team Type as a Moderator of the Relationship between EI and Collaboration
Figure 5.4 illustrates the moderation effect of time in teams on EI as a predictor of
collaboration. Similar to team role, when individual EI grows beyond the low level to the
medium and high levels, there is little moderation of time in teams on the effect that EI
has on collaboration. Further, when individual EI is low, time in teams moderates the
effect EI has on collaboration such that individuals who have team experience beyond 10
years show significantly more of an EI effect on collaboration compared to those who
have less experience.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 153
Figure 5.4 Time in Teams as a Moderator of the Relationship between EI and
Collaboration
H3: Supported. The SOAR framework mediates the relationship between
emotional intelligence and collaboration. H3 was tested to answer the fourth research
question: Does the SOAR framework for strengths-based strategic thinking mediate the
impact that EI may have on collaboration? According to the results of structural equation
modeling (SEM) that was used to test H3, the answer to the fourth research question is
that SOAR mediates the effect EI has on collaboration.
The study supports the hypothesis that SOAR mediates the effect that EI has on
collaboration. Specifically, results of structural equation modeling (SEM) found a
significant indirect effect between EI and collaboration through the mediator, SOAR.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 154
SEM also found that the EI-collaboration direct path remained significant along with the
EI-collaboration indirect path, suggesting that there was partial mediation (as opposed to
full mediation). Characterizing the constitutive elements of SOAR as multiple mediators
found that Strengths (S), Opportunities (O), and Results (R) were significant mediators of
the relationship between EI and collaboration. This implies that SOAR is one of the
mechanisms that may explain how the relationship between EI and collaboration occurs.
At the heart of the SOAR framework is an inclusive approach that promotes team
members to frame strategy from a strengths-based perspective utilizing the team’s unique
strengths, assets, and capabilities (Cooperrider, Whitney, & Stavros, 2008). For
practitioners, SOAR should be considered by teams and team members seeking
increasingly positive collaboration outcomes, with a particular emphasis on developing
their strategic strengths, opportunities, and results.
Implications for Practice and Recommendations
This study has implications for teams and team members such that focusing on
methods to improve EI abilities in themselves and others may be critical for increasing
collaboration in teams, and ultimately team effectiveness. EI, as measured by the WEIP-
S in this study, was concerned with the measurement of EI abilities (self-awareness, self-
management, and awareness and management of others’ emotions). The strong
psychometric properties of the WEIP-S support the implication that the WEIP-S
functions as a valid and reliable tool for determining baseline EI competency. The
implication of H1 being supported is that levels of EI have a direct effect on collaboration
outcomes in teams, i.e., the study shows that an increase in EI abilities contributes
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 155
directly to improved collaboration outcomes, particularly in the SM and MO factors of
EI.
There is more to effective teamwork than the accomplishment of tasks within
some metric of performance. Collaboration implies that team members are working
together to accomplish an outcome that is more significant as a team than that which
could be accomplished by the individual members acting alone (Gray, 1985; Romero,
2009). Achieving collaborative goals can actually be influenced by an individual’s
emotional self-awareness and awareness of others’ emotions. The significance of this
implication is important to collaborative teams seeking to gain a competitive advantage
within some framework of time, cost, and performance. Teams lacking the influence of
EI abilities in its members are immediately at a disadvantage to those that acquire EI in
order to develop awareness and management of emotions in themselves and others
(Gohm, 2004).
The finding that SM and MO were significant predictors of collaboration has
implications for organizational leadership to support teams and team members by
prioritizing emotional self-management and management of others’ emotions when
promoting the EI abilities. The finding that the collaboration factors (integrating,
compromising, and communication) have individual variation relative to changes in EI
also has implications for teams. As EI improves, so do the elements of collaboration.
This suggests that improving one’s capability for collaboration can also be achieved with
EI growth as it contributes to one’s ability to be more effective at integrating ideas,
seeking of compromise, and encouraging open and effective communication.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 156
EI transcends diversity in age, ethnicity, and education, i.e., EI growth and
positive collaboration outcomes appear to be possible with male and female team
members of various ages, ethnicities, and education. Regarding education in particular,
the finding that there was no relationship between EI and education has important
implications to the potential makeup of a diverse work team. Unlike IQ, which has
moderate to high correlation with amount of education, such that the more time in school
generally leads to greater intelligence (Deary & Johnson, 2010), EI appears to have
minimal correlation with amount of education (Wong & Law, 2002). Results of the
current study also suggest that there is no relationship between EI and level of education.
For example, ANOVA did not find a significant relationship between the levels of
education and mean EI score. In fact, this finding overcame the significant distribution of
the sample in which there were significantly more Master’s and Doctoral level
participants in the study (greater than 70%). The implication of this finding, that EI has
no correlation with education, is that teams with diverse educational level can benefit
from targeted EI improvements. As teams organize members with certain requisite skills
and abilities, no particular distinction should be made with regard to level of education.
With H2 being supported, the implication is that certain participant demographic
characteristics affect the relationship between EI and collaboration. Specifically, higher
levels of EI increase collaboration among team members, teams that meet in a virtual
environment, and among individuals who have limited experience working in teams.
These characteristics, team role, team type, and time in teams, were found to have a
significant effect on EI’s prediction of collaboration. The further implication is that these
characteristics should be considered when building teams, and in teams seeking to
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 157
improve their potential for positive collaboration. Effective collaboration is
demonstrated when the same EI competencies that are displayed in strong leadership are
displayed by teams, i.e., to recognize, manage, and use emotional information about
oneself and others (Boyatzis, 2007).
With team role, leadership emerges as an important characteristic when EI is low.
As EI increases within the collaborative team, the distinction between leaders and
members lessens; what is important is that they have EI, or EI growth, not team role.
With team type, teams that engage virtually can actually exhibit higher potential for
collaboration when EI levels are high. When EI is high, virtual teams exhibit some
accentuation of, or emphasize their need to collaborate in recognition of the potential
difficulties with lack of face-to-face interactions. As individuals gain experience in team
settings, time-in-teams becomes less a factor in EI predicting collaboration. When EI is
low, individuals with extensive experience in teams (10+ years) have significantly higher
potential for collaboration compared to those with less experience. Finally, EI is not
affected by industry, which implies EI can be learned and applied in any setting.
Team role, team type, and time in teams are all important factors to consider when
planning, building, and participating in teams. These factors are important to teams in
meeting organizational objectives, and when supporting collaboration among team
members to maximize team effectiveness. Team leaders and team members can seek to
improve their collaborative effectiveness by focusing on the EI abilities most critical to
achieving collaborative success – emotional self-management (SM) and management of
others’ emotions (MO). By focusing on these critical EI abilities first, team members
will be in the best position to achieve positive collaboration. Becoming proficient in all
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 158
the EI abilities (SA, SM, AO, and MO) will maximize the potential impact EI may have
on collaboration.
In teams where members are low in EI, team leaders can play a strong role in
bringing the benefits of EI competency to the collaborative team, e.g., SM and MO.
Teams should consider, at least in the short-term, to identify a leader highly competent in
the EI abilities. If the technical merits necessary for team leadership preclude the
selection of a leader high in the EI competencies, a co-leader may be suggested as a team
member responsible for elevating the EI competency of the team. As EI increases in the
members of the collaborative team, team role becomes less important. Team leaders and
team members contribute essentially equally to positive collaboration as EI builds in all
team members.
In teams where interaction occurs virtually, the potential for positive collaboration
significantly improves as EI grows. Raising the level of EI competency in virtual team
members will maximize the impact EI can have on collaboration, and should therefore be
the areas targeted first for EI development. Team members with high levels of team
experience (10+ years) provide the best opportunity to bring strong EI skills to the team.
These individuals should be tasked with the guidance and development of EI in less
experienced team members.
The implication of H3 being supported is that SOAR definitively functions as a
mechanism of action between EI and collaboration, and should be considered when
seeking to improve collaboration in teams. A framework for strategy based on the
strengths and aspirations of team members helps to explain how EI leads to positive
collaboration. This implies further that EI abilities and their effect on collaboration can
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 159
be accentuated in individuals and teams competent in SOAR. Since strengths (S),
opportunities (O), and results (R) function as the main mediators of EI and collaboration,
these should be targeted first. Study results imply that when individuals are working in a
team context, especially when collaboration is the desired outcome, team members are
aware of their natural strategic capacity for strengths-based strategic thinking, are aware
of bringing their visions and aspirations into the collaboration, and are focused on
completing tasks and obtaining results to bring the team collaboration to a successful
outcome.
A framework for strategy based on the strengths and aspirations of team members
helps to explain how EI leads to positive collaboration. Enabling strategic thinking
capacity from a SOAR-based framework in team members will provide the best
opportunity to influence collaboration. Leaders can assemble teams that build on
strengths and aspirations of members to identify opportunities and achieve positive
results. Education and training in the SOAR competencies may be the best approach for
team members unfamiliar with SOAR and strengths-based strategic thinking. When
individuals are working in a team context, especially when collaboration is the desired
outcome, team members competent in SOAR will be able to maximize the impact EI has
on collaboration.
Study results found SOAR partially mediated the relationship between EI and
collaboration among participants working in teams. SOAR was measured by the SOAR
Profile, which emerged from the fields of strategy, organization development and change,
and Appreciative Inquiry (AI). AI is vital to the emergence of SOAR due to its
engagement of people at all levels of an organization in an inquiry into the organization’s
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 160
positive core, similar to strengths-based approaches to strategic thinking. The SOAR
Profile is also positioned through the lens of positive organizational scholarship (POS),
with its focus on generative dynamics of how leaders can build teams as social systems
that build on strengths and aspirations of members to achieve positive results. This
positive approach leads to changes in the organization based on images of the best
possible future as articulated and visualized by the people who make up the human
system of the organization (Cooperrider et al, 2008).
As team members seek to raise their levels of EI, they can begin by first
completing an EI self-assessment baseline such as the WEIP-S to identify areas of
strength and weakness in each EI factor, and then looking at the four-items (questions)
that make up each factor. Areas of relative strength and weakness in these items,
particularly when compared to a reference population, can provide additional
understanding as to the abilities of particular interest for EI growth. Initiating appropriate
change action to improve the EI abilities of team members should be focused on the areas
of most importance depending on their background, team role, team type, and time in
teams.
Because there is the potential for variability in the effect that EI has on the
different factors of collaboration, practitioners are also recommended to complete the
Team Collaboration Questionnaire, an original measure of collaborative activity uniquely
developed for this study. This metric of collaboration will provide an assessment of
strengths and weaknesses in the collaboration factors (integrating, compromising, and
communication) important to team effectiveness. Areas of relative strength and
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 161
weakness in these items, particularly when compared to a reference population, will
provide an indication of the factors most appropriate for improvement.
Finally, team members should complete the SOAR Profile to help understand
their natural capacity for strategic thinking, and its relevance to positive collaboration
outcomes. In this study, the SOAR Profile was used as a rapid assessment instrument
specifically designed to understand an individual’s natural tendency to reinterpret
problems as solutions, and to ultimately maximize the impact that SOAR competent team
members may have on collaboration (Cole & Stavros, 2014).
The implications of this study and resultant recommendations (summarized in
Table 5.1), offer significant opportunities for practitioners seeking improved outcomes in
their collaborative teams. Learning and practicing the EI abilities can significantly
impact team collaboration in a positive way. Self-awareness, self-management,
awareness of others’ emotions and management of others’ emotion can be acquired over
time through education, practice and emotional maturity (Macaleer & Shannon, 2002).
Other research on EI considers EI from a trait based perspective inherent to personality,
which in practice is not easily changed. EI abilities, in contrast are dynamic, and
therefore have the potential to be improved through behavior change interventions.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 162
Table 5.1 Summary of Practical Recommendations
Emotional Intelligence
Recommendations for Practice Literature Support
Focus on ability-based models of EI and their assessment methods, e.g.,
Jordan and Lawrence (2009), and the corresponding WEIP-S. Establish
self-report baseline for mean EI and mean EI scores for each factor (SA,
SM, AO, and MO) to identify areas of strength and weakness. Compare
with a relevant reference population to further refine areas of strength
and weakness.
(Gray, 1985;
Romero, 2009;
Gohm, 2004;
Jordan and
Lawrence, 2009)
SM and MO are the primary EI factors most critical to achieving
positive outcomes in collaboration; seek to raise individual levels of SM
and MO first by studying results of the WEIP-S at the SM and MO
factor levels, with a particular emphasis on the individual questions that
make up each factor (4 questions for each factor). Seek to compare
results with a relevant reference population to determine priority for
development and training.
(“Emotional
competence
framework,” 1998;
Xavier, 2005)
Similar to SM and MO, the SA and AO factors also contribute to
positive collaboration. Seek to evaluate and improve these EI factors
with secondary priority to SM and MO. Follow the same procedure
described for SM and MO, paying particular attention to the four
questions that make up each factor. Compare to relevant reference
population.
(“Emotional
competence
framework,” 1998;
Goleman,
2006; Xavier,
2005)
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 163
Collaboration
Recommendations for Practice Literature Support
Establish self-report baseline for collaboration and its factors,
integrating, compromise, and communication, using the Team
Collaboration Questionnaire. Compare results with other team members
or relevant reference population to identify areas of strength and
weakness. Target appropriate areas for improvement by focusing on the
individual questions that make up each factor. Repeat the collaboration
self-assessment at a later date to evaluate progress.
(Dietrich et al.,
2010; Hattori &
Lapidus, 2004;
Prati et al., 2003;;
Shaw & Lindsay,
2008)
Leaders high in EI raise collaboration in teams to a greater extent than
team members having lower EI. Improving EI in all team members
optimizes potential for positive collaboration. Identify highly EI
competent leaders or co-leaders responsible for raising levels of EI in
team members.
(Wolff & Koman,
2008; Boyatzis,
2007)
When EI is high, virtual teams exhibit significantly higher levels of
collaboration. Consider adding a virtual element to team interactions,
and/or seek to improve levels of EI in face-to-face teams.
(Romero et al.,
2009)
Team members with 10+ years of team experience exhibit highest levels
of EI. Seek to have a team member who can bring this characteristic to
the rest of the team.
(Macaleer &
Shannon, 2002).
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 164
SOAR
Recommendations for Practice Literature Support
Complete the SOAR Profile to help understand and learn about one’s
natural capacity for strategic thinking and planning. Evaluate each
factor score by referring to the individual questions that make up each
factor. See which questions are comparatively low to determine areas of
strength and weakness. Compare with team members or relevant
reference population to refine areas of strength and weakness.
(Cole & Stavros,
2013; Stavros &
Hinrichs, 2009;
Cole & Stavros,
2014)
The elements of SOAR having the largest impact on collaboration are S,
O and R. Seek to improve these SOAR competencies first.
(Cooperrider,
Whitney &
Stavros, 2008)
Individuals working in teams should seek to advance their natural
capacity for strategic thinking and planning from a strengths-based
perspective. This and other positive approaches to problem solving can
be learned from participation in Appreciative Inquiry exercises and
SOAR-based workshops. Positive Organizational Scholarship
approaches to problem solving and team effectiveness should also be
investigated as natural strength-based competencies essential for
collaboration.
(Cooperrider,
2008; Dutton &
Quinn, 2003;
Stavros & Wooten,
2012; Dutton &
Quinn, 2003)
In this dissertation, the survey questions were derived from three independent
measurement instruments: the 16-item workgroup emotional intelligence profile (WEIP-
S), the nine-item Team Collaboration Questionnaire uniquely developed for this study,
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 165
and the 12-item SOAR Profile. The results of descriptive and inferential statistics were
reported categorically, segmented by the various demographic characteristics of the total
study population. No single respondent was used as an example to maintain
confidentiality of the participants. However, in practice, individual data would be
available for use a means to evaluate baseline competency in EI, collaboration, and
SOAR, and to provide a personalized assessment of the study categories relative to a
larger sample.
For example, if the total population (e.g., team) has a mean EI score of 5.5, and a
particular individual has a mean EI score of 5.2, this would provide the individual a
comparative assessment of EI strength or weakness relative to other team members. The
individualized data would also allow for the evaluation of the constitutive factors of EI,
namely mean scores for SA, SM, AO and MO. Results could also be compared within
various demographic segments such as gender, age, ethnicity, education, team size and
team type. Going further, the response for each individual question would be available to
pinpoint specific items which bring down, or raise the factor score being evaluated. In a
further example, if an SA score is higher or lower within a demographic group of interest,
this would be meaningful to an individual seeking to assess strength or weakness in a
particular competency, compared with a population of similar demographics, e.g., team
type, team role or time in teams.
Similarly, the data reported for both collaboration and SOAR could be analyzed
in the same way. In the end, according to the study model, the distinct relationships
between EI, collaboration, and SOAR could be understood at the individual, team, and
reference population levels. Targeted improvements through education and training can
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 166
be subsequently deployed in a strategic fashion with high confidence the effort will yield
maximum returns in achieving positive collaboration. Table 5.2 shows an example of
how individual self-report data could be summarized and used for comparison with a
reference population.
Table 5.2 Personalized Summary Assessment Example: EI, Collaboration and SOAR
Categorical Descriptive Statistic Individual self-report data Categorical Reference (Mean)
Current Team
Characteristic EI SA SM AO MO
Team size Table 4.13 6 members 5.50 4.68 6.22 5.53 5.63
Team membership Table 4.13 Internal, external 5.48 5.05 5.97 5.27 5.66
Team type Table 4.13 Face-to-face 5.28 4.76 5.92 5.06 5.42
Team role Table 4.13 Leader 5.48 4.95 5.98 5.33 5.66
Time in team Table 4.13 3-6 months 5.27 4.66 5.84 5.00 5.57
Teams in general
Team role Table 4.14 Leader 5.43 4.78 6.00 5.28 5.66
Time in teams Table 4.14 11-15 years 5.32 4.58 6.06 5.15 5.49
Demographics
Age Table 4.11 35-44 5.24 4.59 5.86 5.12 5.42
Gender Table 4.11 Female 5.40 4.87 5.98 5.22 5.52
Ethnicity Table 4.11 White 5.39 4.84 6.03 5.12 5.57
Education Table 4.11 Masters 5.35 4.70 5.98 5.18 5.55
Industry Table 4.12 Skip - - - - -
Profession/position Table 4.12 Skip - - - - -
Summary of self-report data Self-report Population
Mean EI Table 4.11 5.69 5.32
Mean SA Table 4.11 5.50 4.76
Mean SM Table 4.11 5.75 5.96
Mean AO Table 4.11 5.75 5.10
Mean MO Table 4.11 5.75 5.47
Mean Collaboration Table 4.15 5.53 5.86
Mean SOAR Table 4.19 8.25 8.00
Recommendations for Future Research
An avenue of interest for future research may include a study of both trait- and
ability-based EI competency in team members. Evaluating and comparing individual
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 167
traits and abilities relative to their impact on collaboration may yield additional
implications as to areas of EI competency that may also prove beneficial to team
effectiveness. This future research may also yield clues as to the relationship between
collaboration among team members and the team output, depending on levels of EI
within the collaborative team. This approach could also be used to evaluate EI growth
over time, as would be done with a longitudinal research methodology.
Future research should also seek to clarify the distinction between partial and full
mediation of SOAR in order to determine what other variables may explain the effect that
EI has on collaboration. The implication will be that strengths-based strategic thinking
and planning is only one mechanism by which EI impacts collaboration, and that there
may be other potential mechanisms. For practitioners, identifying additional mediating
variables may provide even greater opportunity to maximize the positive impact EI has
on collaboration.
Extending the demographic characteristics of respondents to include an
assessment of their pre-existing knowledge of EI may yield additional results in
determining the elements of EI most critical to team effectiveness. EI competency, as a
construct and its factors, could be tested as a moderator of the impact EI has on
collaboration. Introducing a demographic question such as “are you aware of, or practice
the EI abilities of self-awareness, self-management, awareness of others’ emotions and
management of others’ emotions?” This demographic variable may shed insight on
whether EI has an impact on collaboration, moderated by pre-awareness of the EI factors,
or abilities as defined by Jordan & Lawrence, 2009.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 168
Another interesting avenue of research could be to explore whether some team
members use EI to manipulate others. Inappropriate use and application of the EI
abilities would likely come at the expense of the team, potentially failing the keys to
positive collaboration, i.e., integration, compromise, and communication. As an EI
ability, management of others’ emotions (MO) may be used ineffectively, or
inappropriately for extending one’s agenda over others. Assessing respondent views on
manipulation and its potential impact on collaboration may prove an important area to
mitigate against.
Future research may also investigate other methods of EI assessment which are
not self-report, e.g., 360 degree assessment instruments, interviews and other qualitative
approaches. Results of this future research could be compared with the results of this
study for correlation, or to exhibit unique and valuable differences in the relationship
between EI and collaboration. This could also address the potential for common-method
bias which may occur when the same source is used for the independent and dependent
variables.
As discovered in this study, survey respondents from the engineering and
technical disciplines consistently reported lower mean EI scores in almost every
demographic category. Future research could investigate and seek to understand the
apparently limited baseline EI abilities of the technical community. Implications for
modeling behavior change interventions could be developed and deployed for improving
EI and ultimately collaboration in the technical community.
In recognition of additional respondent feedback, it may be important to clarify
what “self-awareness” means in a team setting. Respondents indicated that while they
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 169
considered certain aspects of self-awareness evident in themselves, they felt constrained
by the team’s norms to effectively apply it. Further, they suggested their responses to the
WEIP-S self-awareness items would vary depending on the team being considered when
completing the survey. Since this study instructed participants to provide their self-
assessment within the context of the team they are currently involved with, or had recent
experience with, self-awareness assessments may not be representative of an individual’s
overall competency in this particular factor. In a future study, it may be interesting to
perform the WEIP-S self-assessment considering an individual’s team experiences in
general, or in comparing mean EI scores between two teams in which the respondent is
currently active.
Study Limitations
In order to satisfy construct reliability and validity of the study’s measurement
instruments, the Team Collaboration Questionnaire and the SOAR Profile were modified
in their item count. While this satisfied the psychometric properties desired in the final
study survey, it was not deployed to a new sample in order to evaluate correlation with
the initial study results.
The study survey employed a single demographic question regarding “position”.
Given the data is self-report and there is a sense of self-fulfilling prophecy, individuals
may have identified themselves with position titles that cannot be equivalently compared
across industries. With the possibility of study participants over-representing their
position relative to their level of responsibility, and apparent inconsistencies in title
definitions across industries, it was decided to draw no conclusions based on this
demographic question.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 170
This study has limitations related to the use of self-report data in general, as self-
report methodology has inherent limitations of validity of the data. Another limitation
associated with self-report measurement instruments includes the potential for common-
method bias. Common-method bias may occur when data for the independent variable
comes from the same source as the dependent variable. Ideally, team based collaboration
would be measured by independent observers. Finally, since research participants
estimated the collaborative outcomes of their teamwork, as well as their capacity for
strengths-based strategic thinking and planning (i.e., SOAR) through the use of two novel
assessment tools—the Team Collaboration Questionnaire, and the SOAR Profile—the
psychometric properties of these assessment devices were evaluated using tests of
reliability and validity prior to data analysis.
Summary
This study considered emotional intelligence and its constitutive factors (self-
awareness, self-management, awareness of others’ emotions, and management of others’
emotions) as predictors of collaboration (integrating, compromising, and communication)
among teams and team members. Demographic characteristics (team role, team type, and
time in teams) were tested as moderators of the impact EI has on collaboration, and
capacity for strategic thinking (SOAR) was investigated as a mediator. Within this
context, the purpose of the dissertation was to evaluate the link between EI and
collaboration outcomes in teams, to characterize the EI abilities that contribute to
collaboration, and to investigate the mediating role that SOAR (i.e., strengths-based
strategic thinking and planning capacity) has on the relationship between EI and
collaboration among team members.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 171
Results conclude as EI improves, so does the potential for improved
collaboration, most notably in the SM and MO factors of EI. EI was also found to impact
(positively) the collaboration factors, integrating, compromising, and communication.
Team role, team type, and time in teams were found to moderate the impact of EI and
collaboration. SOAR was found to be a significant mediator of EI and collaboration, with
S, A, and R functioning as partial mediators.
EMOTIONAL INTELLIGENCE, SOAR, AND COLLABORATION 172
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Appendix A
Certificate of Training
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Appendix B
IRB Letter of Approval
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Appendix C
Informed Consent
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Appendix D
Survey Instrument
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