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THE RELATIONSHIP BETWEEN PERSON-ORGANIZATION FIT AND EMOTIONAL INTELLIGENCE

by Cheryl Reneé Bates

A Dissertation Presented in Partial Fulfillment of the Requirements for the Degree

Doctor of Management in Organizational Leadership

UNIVERSITY OF PHOENIX

February 2009

UMI Number: 3353756 Copyright 2009 by Bates, Cheryl Renee All rights reserved

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ABSTRACT The relationship between person-organization fit (P-O fit) and emotional intelligence (EI) was investigated using a quantitative research method and correlational design. Eightynine human resource professionals from a myriad of disciplines, employment levels, and industries participated. Quantitative measurements occurred using the Mayer-SaloveyCaruso Emotional Intelligence Test (MSCEITTM) for EI and Cable and DeRue's ThreeItem Person-Organization Fit Scale. Pearson's correlation coefficients were performed to determine and analyze the relationship between P-O fit and EI. Even though a positive correlation was found between participant P-O fit and EI scores (r = .18, p = .10), the relationship was not statistically significant (p>.05). The study's findings led to the conclusion that because a statistically significant relationship does not exist between P-O fit and EI, leaders should exercise caution when using EI skill level as a determinant of PO fit.

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DEDICATION I dedicate this dissertation to those who carried me on their shoulders when my feet grew weary on this journey. To my savior, Jesus Christ, without whom I could not have found the courage or fortitude to embark upon this journey. I looked to my mother, Sandra Dixon, for strength throughout this journey. Her courage and tenacity reminded me that I was made from her stock. My sister and best friend, Cynthia Bates, inspired me to keep one foot in front of the other and constantly reminded me that a life without sacrifice and dedication to your dreams is not worth living. One look in Cynthia's eyes and I knew I had to make it across the finish line. To Dr. Jasmine Harris, who inspired me to begin this journey and live up to our family's dreams for the education of their children. To my father, Leonard Bates, who set the example for learning and excellence. To Alphonso Fulton, who was and continues to be the light for which I reach to keep my footing. Alphonso, I am indebted to you for your thoughtful insights and considerations during the course of this journey. I also dedicate this dissertation to human resource professionals who have dedicated their lives to the service of humanity. I am truly inspired and humbled by each of you.

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ACKNOWLEDGEMENTS I would like to acknowledge the following groups for their contributions and support during this journey. I am eternally grateful to the professors at the University of Phoenix who facilitated an exuberant and intellectual doctoral education. Dr. Ann Deaton, my mentor, who provided gentle support and guidance and who constantly reminded me that humility is a core competence of leadership. I acknowledge committee members Dr. Janice Terrell and Dr. Matthew Reis for their commitment to this project and their thoughtful review and criticism. You pushed me to higher heights and I will forever be grateful. I am extremely thankful for the participation of the Society for Human Resource Management and the human resource professionals who were so eager to contribute to the project. I owe my gratitude to Dr. Jasmine Harris for her help with the study group and her support throughout this project. I am grateful to Dr. Martin Barugel for his assistance with statistical processes for the study. I owe my sanity to Mary Wise, my sister and peer coach. We traveled this journey together, with me kicking and screaming the entire way. You provided me with peace, support, and realism. Your "We're in this together attitude" kept me moving toward our goal. Finally, I acknowledge the unconditional love and support from my family, Sandra, Roy, Cynthia, Alphonso, LaTrece, Jonathan, Nickolas, Leonard, Martha, Mervyn, Frances, Jasmine, Brenda, and Mary. I stand on your shoulders and I thank you for the support.

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TABLE OF CONTENTS LIST OF TABLES.....................................................................................................xiii LIST OF FIGURES ...................................................................................................xiv CHAPTER 1: INTRODUCTION ..............................................................................1 Background ................................................................................................................2 Problem Statement .....................................................................................................7 Purpose.......................................................................................................................8 Significance of the Study ...........................................................................................9 Significance to the Field of Leadership ............................................................10 Nature of the Study ....................................................................................................11 Research Method ..............................................................................................11 Research Design................................................................................................13 Research Question and Hypotheses ...........................................................................14 Research Question ............................................................................................14 Null and Alternative Hypotheses ......................................................................15 Theoretical Frameworks ............................................................................................15 Person-Organization Fit (P-O Fit) Framework ..................................................16 Emotional Intelligence (EI) Framework ............................................................17 Definitions..................................................................................................................19 Assumptions...............................................................................................................21 Scope, Limitations, and Delimitations.......................................................................22 Scope.................................................................................................................22 Limitations ........................................................................................................22

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Delimitations.....................................................................................................23 Summary ....................................................................................................................24 CHAPTER 2: REVIEW OF THE LITERATURE ....................................................26 Documentation...........................................................................................................27 Germinal Foundations, Historical Overviews, and Current Findings........................28 Germinal Foundation of P-O Fit ................................................................................29 Historical Overview of P-O Fit..................................................................................31 P-O Fit Models and Frameworks......................................................................32 Measuring P-O Fit.............................................................................................36 Current Findings ........................................................................................................38 Distinguishing P-O Fit ......................................................................................41 Germinal Foundation of EI ........................................................................................42 Historical Overview of EI..........................................................................................43 EI Models and Frameworks ..............................................................................46 Measuring EI.....................................................................................................52 Current Findings ........................................................................................................60 EI in the Workplace ..........................................................................................62 Leadership.........................................................................................................63 Training, Productivity, and Retention...............................................................66 Controversy in the EI Field...............................................................................67 Conclusion .................................................................................................................68 Summary ....................................................................................................................69 CHAPTER 3: METHODS.........................................................................................71

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Research Method and Design Appropriateness .........................................................72 Research Question and Hypotheses ...........................................................................74 Research Question..............................................................................................75 Null and Alternative Hypotheses .......................................................................75 Instrumentation ..........................................................................................................75 Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEITTM)..................76 Three-Item Person-Organization Fit Scale .......................................................78 Validity and Reliability..............................................................................................79 Three-Item P-O Fit Scale ..................................................................................80 MSCEITTM ........................................................................................................80 Population and Sampling ...........................................................................................81 Population ........................................................................................................81 Sampling Frame ...............................................................................................82 Informed Consent.......................................................................................................84 Confidentiality ...........................................................................................................85 Procedures for Data Collection..................................................................................87 Procedures for Data Analysis.....................................................................................89 Summary ....................................................................................................................90 CHAPTER 4: PRESENTATION AND DATA ANALYSIS ...................................92 Research Instrument Results......................................................................................92 MSCEITTM .......................................................................................................93 Three-Item P-O Fit Scale .................................................................................94 Descriptive Statistics..................................................................................................95

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Results and Findings ..................................................................................................99 Research Question and Hypotheses ..................................................................99 Pearson's Correlation Coefficient ....................................................................99 MSCEITTM and P-O Fit Sore Results by Characteristic ...................................101 Summary ....................................................................................................................104 Conclusion .................................................................................................................104 CHAPTER 5: CONCLUSIONS, IMPLICATIONS, AND RECOMMENDATIONS..........................................................................................105 Conclusions................................................................................................................106 Pearson's Correlation Coefficient ....................................................................106 Non-Significant Positive Correlation between P-O Fit and EI.........................106 Relationship of the Current Study to Previous Research...........................................107 Significance of the Current Study..............................................................................111 Study Limitations and Delimitations .........................................................................112 Possible Research Design Errors ...............................................................................116 Analysis of P-O Fit and EI Branches................................................................116 Study Population ..............................................................................................117 Quantitative Instrumentation ...........................................................................117 Implications and Recommendations for Leaders.......................................................117 Suggestions for Future Research ...............................................................................120 EI Model ...........................................................................................................120 Research Methodology ....................................................................................121 Study Population and Geographic Region .......................................................121

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Alternative Measurements and Instrumentation ..............................................121 Choice and Motivation Theories.......................................................................122 Conclusion .................................................................................................................122 References..................................................................................................................124 APPENDIX A: COMPONENTS OF POPULAR EI THEORIES ............................ 143 APPENDIX B: APPROVAL TO USE THE MSCEITTM .........................................145 APPENDIX C: THE MSCEITTM ..............................................................................147 APPENDIX D: APPROVAL TO USE THREE-ITEM P-O FIT SCALE.................150 APPENDIX E: THREE-ITEM PERSON-ORGANIZATON FIT SCALE...............153 APPENDIX F: PERMISSION TO USE THE SOCIETY OF HUMAN RESOURCES MANAGEMENT AS STUDY PARTICIPANTS.............................155 APPENDIX G: LETTER OF INTRODUCTION AND INVITATION TO STUDY................................................................................................................159 APPENDIX H: INFORMED CONSENT: PARTICIPANTS 18 YEARS OF AGE AND OLDER (WEB-BASED AND U.S.MAIL) ......................................162 APPENDIX I: ACCESS TO WEB-BASED AND U.S. MAIL SURVEYS) ............167 APPENDIX J: DEMOGRAPHIC QUESTIONNAIRE ............................................170 APPENDIX K: MSCEITTM TASK SCORES............................................................173 APPENDIX L: DESCRIPTIVE STATISTICS FOR ORGANIZATIONAL CHARACTERISTICS ...............................................................................................175 APPENDIX M: ORGANIZATION BY CONTINUOUS VARIABLES..................178 APPENDIX N: JOB POSITION BY CONTINUOUS VARIABLES ......................180 APPENDIX O: TIME IN HR POSITION BY CONTINUOUS VARIABLES ........182

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APPENDIX P: LENGTH OF TIME IN CURRENT POSITION .............................184 APPENDIX Q: AGE BY CONTINUOUS VARIABLES.........................................186 APPENDIX R: EDUCATION BY CONTINUOUS VARIABLES..........................188 APPENDIX S: ORGANIZATIONAL POSITION BY CONTINUOUS VARIABLES .............................................................................................................190

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LIST OF TABLES Table 1 Dimensions of Person-Environment Fit .......................................................31 Table 2 Kristof's P-O Fit Concepts ...........................................................................34 Table 3 Mental Abilities and Mixed Models of EI .....................................................46 Table 4 Bar-On's Five EI Competencies ...................................................................47 Table 5 Four Branches of Mayer and Salovey's 1997 EI Model ..............................49 Table 6 Five Categories of Goleman's 1998 EI Model .............................................50 Table 7 Goleman's 2001 Updated EI Model .............................................................51 Table 8 EQ-i Scores ...................................................................................................54 Table 9 EI Competencies Measured by the ECI ........................................................55 Table 10 MSCEITTM Measurement Components.......................................................58 Table 11 MSCEITTM Branch Reliability Scores ........................................................59 Table 12 MSCEITTM Scoring .....................................................................................77 Table 13 EI Branch Reliability Scores.......................................................................81 Table 14 Measures of Central Tendency for MSCEITTM...........................................93 Table 15 Measures of Central Tendency for P-O Fit Items.......................................95 Table 16 Descriptive Statistics for Gender and Ethnicity .........................................97 Table 17 Descriptive Statistics for Education and Position Level ............................98 Table 18 Correlation Results for MSCEITTM and P-O Fit Variables .......................100 Table 19 Ethnicity by Continuous Variables .............................................................102 Table 20 Gender by Continuous Variables................................................................103

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LIST OF FIGURES Figure 1. The Research Process.................................................................................71 Figure 2. Participant Ages ........................................................................................96 Figure 3. Scatterplot Matrix of Relationships ...........................................................100

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CHAPTER 1: INTRODUCTION The U.S. work environment has become increasingly turbulent, dynamic, diverse, global, and competitive. These factors have contributed to the growing need for emotional intelligence (EI) in the workplace (Cherniss & Goleman, 2001; Fiedeldey-Van Dijk & Freedman, 2007; Iordanoglou, 2007). EI is "the competence to identify and express emotions, understand emotions, assimilate emotions in thought, and regulate both positive and negative emotions in oneself and others" (Matthews, Zeidner, & Roberts, 2004a, p. xv). Today's leaders are seeking to hire and retain leaders and employees with high EI skills in hopes of attaining person-organization fit (P-O fit) (Erdogan, & Bauer, 2005; Frase, 2007; Landen, 2002; D. Smith, 2006). P-O fit refers to the compatibility between an individual and the organization (Autrey & Wheeler, 2005; Kristof, 1996). The P-O fit construct is fast becoming one of the most popular ways used to assess if a person will fit within an organization (Kwantes, Arbour, & Boglarsky, 2007). The construct has become important in the study of organizational effectiveness because it improves upon the traditional paradigm of matching skills, knowledge, and abilities in predicting if an individual will be successful in a particular organization (Chuang & Sackett, 2005; Erdogan & Bauer, 2005; Spors, 2007; Westerman & Cyr, 2004). Billsberry, Ambrosini, Moss-Jones, and Marsh (2005) and Resick, Baltes, and Shantz (2007) posit that leaders, employees, and job candidates may need to build and use their EI skills in order to help assess their ability to fit within an organization's culture and work environment. While a vast number of studies exist on EI and P-O fit as individual constructs, no research was reviewed that focused on determining if a relationship exists between them. Exploration into this gap is necessary to provide a foundation for the

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assumptions made by authors and organizational leaders about a close, even dependent relationship between EI and P-O fit. Chapter 1 introduces the EI and P-O fit constructs, presents the background of the problem, and discusses why the research problem is of social and theoretical interest. The purpose of the study and the general and specific problem are presented. A discussion of the study's nature is provided along with the research method, research design, independent and dependent variables, research question, hypotheses, study population, and geographical location. The research variables and the theoretical framework under which the study falls are delineated in chapter 1. Chapter 1 also introduces the significance of the study and explains the uniqueness of the research, the study's value to the field of leadership, and beneficiaries of the study's results. Prior to the summary, chapter 1 provides operational definitions, assumptions, scope, limitations, and delimitations. Background The study is of social concern because the level of EI skills of leaders and employees are being used to determine and assume P-O fit within an organization. A social concern arises because leaders and employees may lack awareness that their EI skills are being assessed to determine their ability to fit within an organization. Leaders and employees with awareness of EI assessment may be better equipped to determine ways in which to improve their skills to obtain entrance into organizations and, in many cases, retain employment. The study is of theoretical interest because there were no studies reviewed that examined the existence of a relationship between EI and P-O fit. The current research

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may add to existing theory and add depth to the literature for both constructs. To add to the existing body of theoretical knowledge, the current study sought to examine the existence of a significant relationship between the two constructs. The focus on hiring and retaining employees and leaders based solely on skills and experience is changing. Today's organizations are putting more focus on hiring people who fit their organizational culture (Arthur, 2006; Bielski, 2007; D. Smith, 2006; Siegel, 2003; Spors, 2007; Williams, 2007). Many organizations are measuring prospective and employee's ability to fit within an organization by the level of his or her EI (Goleman, 2001; Hunt, 2007; Landen, 2002; Spors). P-O fit is becoming one of the most popular ways used by organizations to assess if a person will fit within an organization (Kwantes, Arbour, & Boglarsky, 2007). Williams (2007) proposed that employers as well as job candidates should assess their ability to fit within an organization using fit assessment tools such as the Fit Assessment Form and Hogan, Hogan, and Warrenfeltz"s (2007) Motives, Values, Preferences Inventory. Proponents of P-O fit believe that the construct has become important in the study of organizational effectiveness because it improves upon the traditional paradigm of matching skills, knowledge, and abilities in predicting if an individual will be successful in a particular organization (Chuang, & Sackett, 2005; Erdogan & Bauer, 2005; Spors, 2007; Westerman & Cyr, 2004). P-O fit adds another dimension to the hiring equation. Some authors posit that individuals whose values fit with an organization's values will result in positive contributions to organizational effectiveness and lower turnover rates (Ambrose, Arnaud, & Schminke, 2008; Erdogan & Bauer; McCulloch & Turban, 2007; Westerman & Cyr).

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Assessing for P-O fit can determine if a person's values will conflict with organizational values (Ambrose et al., 2008; Chatman, 1989; Kristof, 2000; Spors, 2007; Westerman & Cyr; 2004), a conflict that could have a negative impact in terms of organizational effectiveness and turnover (DelCampo, 2006). The importance of P-O fit and its impact on organizational culture and workplace effectiveness is well documented. According to Hogan et al. (2007), individuals with values that are not congruent with the organization's values will not be successful in the organization. In a study by Cooper-Thomas, van Vianen, and Anderson (2004), the authors found that employees and leaders who perceived P-O fit experienced an increase in job satisfaction. Davis (2006) found that job satisfaction, citizenship behavior, and commitment to the organization increased as employee perception of P-O fit increased. DelCampo (2006) and Westerman and Cyr (2004) proposed that retention and turnover is directly influenced by P-O fit. Organizations are also focusing on increasing the level of EI in employees and leaders in an effort to increase retention and improve employee interactions (Macrae, 2004; Scott-Ladd & Chan, 2004). In the literature, EI's important role in the workplace is well documented in various areas. Organizations such as the U.S. Air Force, American Express, and Tandem Computers all claim to have successfully used EI skills to improve organizational effectiveness (Seal, Boyatzis, & Bailey, 2006). Goleman (2001) suggested that EI skills are critical to successful leadership outcomes. In a study conducted by Dulewicz and Higgs (2003), EI was shown to be important in selecting leaders as components such as integrity, resilience, and influence were found to be important attributes for leadership effectiveness and organizational

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change. Palethorpe (2006) proposed that EI skills are a critical component of transformational leadership. Laff (2008) wrote that organizations are including EI as a required competence for enhancing performance. Iordanoglou (2007) found that EI has a positive impact on organizational commitment, leadership behavior, and leadership effectiveness. Landen (2002) wrote that as the workforce is required to change to a more knowledge-based arena, tacit knowledge becomes more important. Hiring and retaining employees and leaders with high EI skills could have a positive effect on those employees' congruence with organizational strategies. Organizations with EI training programs may experience improvements in employee behavior and workplace socialization, which could improve organizational congruence (Carmeli & Josman, 2006; Kunnanat, 2004). Jordan and Troth (2004) found that team performance and conflict resolution, which can enhance workplace socialization, might improve if those within the teams exhibited high EI skills. The ability to use emotions intelligently to guide behavior and thinking can enhance business results (Bradberry & Greaves, 2005). The three most desired traits for potential leaders are communication skills, interpersonal skills, and initiative, which are components of EI (Goleman, 1998). While academic intellect may help a prospective employee gain entrance into an organization, emotional intelligence is critical to becoming a successful leader once an individual has been hired (Fiedeldey-Van Dijk, & Freedman, 2007). Scott and Davis (2007) wrote that organizations are social systems that affect the ways in which people communicate, perform, make decisions, solve problems, set goals,

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and attain and exercise power. Organizational success depends on consistency and uniformity and enables society to operate and provide infrastructure to further its growth and maintenance. Social systems that have benefited from organizational success include the military, police departments, banks, universities, retail organizations, and hospitals (Scott & Davis). The EI and P-O fit constructs include components of an organization's social system that could further enhance organizational success (Iordanoglou, 2007; Spors, 2007). The literature contains numerous studies showing the positive effects that EI and P-O fit have on organizational success individually. Studies suggest that those with high EI skills are more likely to be successful and that employers who can retain such employees have a greater chance at success. The literature also shows that many employers believe that if one's values and goals are congruent with those of the organization, the likelihood of success improves for the employee and the organization. The ability to fit within an organization's culture may enhance job satisfaction (Autry & Daugherty, 2003; Ravlin & Rithie, 2006; Resick et al., 2007). EI skills have been shown to improve one's ability to interact with others positively in the workplace (Carmeli & Josman, 2006; Goleman, 2001; Iordanoglou, 2007; Kunnanatt, 2004). Some researchers have suggested a dependent relationship between EI and P-O fit: If one has high EI, the likelihood of being able to discern fit increases (Billsberry et al., 2005; Book, 2008; Kouzes, 2008; Landen, 2002; Resick et al.; Williams, 2007). Schoo (2008) wrote that those with developed EI skills are aware of their needs and the needs of others, which enables them to make better choices about organizational relationships and their congruence with the organization.

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Problem Statement An observation of the general problem identified the need to explore the existence of a relationship between P-O fit and EI. The general problem is that leaders are assuming, without a foundation of extensive empirical research and knowledge on which to base their assumption, that high EI skills lead to a high level of P-O fit (Billsberry et al., 2005; Book, 2008; Bradberry & Greaves, 2005; Frase, 2007; Hunt, 2007; Kouzes, 2008; Roberson, Collins, & Oreg, 2005; D. Smith, 2006; Spors, 2007; Williams, 2007). The assumption by leaders of a significant relationship between P-O fit and EI and the resulting changes in organizational paradigms to accommodate this assumption clearly demonstrate that a general problem exists. The specific problem is that leaders are using the assumption of a significant relationship between EI and P-O fit as a basis for making critical organizational decisions that affect hiring, retention, and organizational effectiveness (Billsberry et al., 2005; Book, 2008; Bradberry & Greaves, 2005; Frase, 2007; Hunt, 2007; Kouzes, 2008; Roberson et al., 2005; D. Smith, 2006; Williams, 2007). The assumption of a relationship between EI and P-O fit contains the further assumption that leaders and employees who do not exhibit high EI skills could bring poor performance, organizational incompatibility, and job turnover to a workplace, which in turn could reduce organizational effectiveness (Carmeli & Josman, 2006; Cherniss & Goleman, 2001). The specific problem confirms the need for exploration into the existence of a significant relationship between EI and P-O fit. Using a quantitative correlational research method and design, the current study examined the existence of a significant relationship between P-O fit and EI. The general

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population (N = 475) was accessed through the Southwest region of the Society for Human Resource Management (SHRM). The sample (n = 89) was obtained from the general population. Purpose The purpose of the quantitative correlational study was to examine if a significant relationship exists between EI and P-O fit. A quantitative method was used to evaluate the relationship between the variables. A correlational research design was used to measure the degree of association between these variables using the statistical procedure of correlational analysis. The degree of association indicates how the two variables are related and if a change in one variable reflects a change in the other variable (Creswell, 2005). In the study, EI was the predictor variable and P-O fit was the outcome variable. To fulfill this purpose, the study assessed human resource professionals over the age of 18 with full-time employment at various employment levels and in various human resource disciplines and industries. The disciplines included employee relations, benefits, compensation, recruiting, onboarding, training, document management, quality, human resource information systems, and operations. The sample for the research study was n = 89 participants. The geographic location was the Southwest region of SHRM in the United States. The group was surveyed using two web-based survey instruments. EI was measured by the Mayer­Salovey­Caruso Emotional Intelligence Test (MSCEITTM) (Mayer, Salovey, & Caruso, 2002). The MSCEITTM is an abilities-based measure that assesses EI. P-O fit was measured using Cable and DeRue's (2002) Three-Item P-O Fit

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Scale. The Three-Item Fit Scale is a self-report instrument that measures the degree of compatibility between an individual and his or her organization. Significance of Study Today's business leaders are searching for ways to exert a positive impact on their increasingly diverse and competitive working environments. Leaders with the goal of increasing organizational effectiveness are using EI and P-O fit concepts. EI (Bradberry & Greaves, 2005; Cherniss & Goleman, 2001; Daus & Ashkanasy, 2005; Iordanoglou, 2007) and P-O fit (Autrey & Wheeler, 2005; Kristof-Brown, Zimmerman, & Johnson, 2005; Ravlin & Ritchie, 2006) have been shown to be positive indicators with direct applicability to organizational effectiveness. The ability to use emotions intelligently to guide behavior and thinking can enhance business results (Goleman, 2001). P-O fit has a "unique and interactive effect on employee commitment, intention to stay with the organization, satisfaction, beliefs about agency effectiveness, and perceptions of conflict" (Ravlin & Ritchie, p. 179). Authors and researchers suggest that leaders and employees with high EI skills could help organizations gain and maintain an edge in today's competitive work environment (Fiedeldey-van Dijk & Freedman, 2007; Iordanoglou, 2007); and P-O fit, researchers believe, could do the same (Arthur, 2006; Siegel, 2003). Researchers and authors suggest that leaders and employees with high EI skills are better able to make job decisions regarding their ability to fit within an organization's culture (Billsberry et al., 2005; Kouzes, 2008; Resick et al., 2007). Leaders and employees who can make better decisions, using their EI skills to discern their fit within an organization, may be able to make greater contributions to the organization's strategies, goals, and overall success

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(Bradberry & Greaves, 2005; Carmeli, 2003; Landen, 2002; Ravlin & Ritchie, 2006). While EI and P-O fit have been studied as individual constructs, no research was found in the course of the current study that included a focus on the question of if a relationship exists between the constructs. Authors and researchers have suggested that a relationship exists between EI and P-O fit (Book, 2008; Frase, 2007; Hunt, 2008; Kouzes, 2008; D. Smith, 2006; Spors, 2007; Williams, 2007). The study's goal was to determine if a significant relationship exists between the constructs. The study's results will determine the degree and significance of the relationship between the constructs in the case that the null hypothesis is rejected. Significance to the Field of Leadership The field of leadership is concerned with providing a clear vision, shared purpose, and continuous organizational improvement. Many of today's leaders are embracing the EI and P-O fit concepts as a part of their leadership strategy to increase organizational effectiveness. The research study may provide benefit to leadership knowledge and literature by adding empirical research and data for the usage of EI and P-O fit to improve organizational effectiveness. The study's results could provide data that will help leaders deliver a clear vision and effective strategies when using P-O fit and EI to increase organizational effectiveness. The research study has the potential to add knowledge to the field of leadership by providing statistical evidence for assumptions currently being made regarding the existence of a relationship between EI and P-O fit. The goal of the study was to provide valuable empirical knowledge and evidence that could possibly result in a framework and

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methodology for recruiting, training, and retaining leaders and employees in an effort to improve organizational effectiveness. The study's findings could add valuable information to the existing body of knowledge and be applicable to leaders who are searching for ways to explain, predict, and improve organizational performance using EI and P-O fit models. Nature of the Study One reason to conduct scientific research is to "learn how the world works so that people can control or predict events" (Neuman, 2003, p. 71). To determine an appropriate research method, a researcher must determine the best approach for his or her study. The study's problem, nature, and theoretical perspective guided the research method and design choice. The study's goal was to determine if a significant relationship exists between EI and P-O fit. A quantitative research method and a correlational research design were the appropriate methods to use. Two quantitative survey instruments were used to collect data: Mayer­Salovey­Caruso Emotional Intelligence Test (MSCEITTM) (Mayer et al., 2002) and Cable and DeRue's (2002) Three-Item P-O Fit Scale. Research Method The study examined the relationship between EI and P-O fit. EI was the predictor variable; P-O fit was the outcome variable. A quantitative research method rather than a qualitative or mixed method was chosen for the current study because (a) quantitative designs are used to identify trends and explain relationships between variables, and (b) quantitative designs measure variables and produce results can be generalized to a large

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number of people (Creswell, 2005). The study sought to determine if a relationship exists between the variables of EI and P-O fit. Quantitative, rather than qualitative, designs measure variables and the results can be generalized to a large number of people (Creswell). Qualitative research focuses on concepts, themes, words, images, and generalizations while quantitative research uses variables, hypotheses, and data in the form of numbers (Neuman, 2003). Qualitative research methods are used in studies where the research problem seeks to learn about individual views, processes over time, trends, and participant perspectives (Creswell, 2005). The study's goal was to determine if significant relationships existed between variables, not to measure individual perspectives or processes over time. A quantitative rather than qualitative research was appropriate to determine relationships between the variables because quantitative methods allow the measurement of relationships between variables. Mixed methods combine quantitative and qualitative research. Mixed methods allow researchers to collect, analyze, and mix quantitative and qualitative data to gain a better understanding of the research problem (Creswell, 2005). Researches seeking to build upon quantitative data by incorporating individual perspectives, reporting trends or explanations of social phenomena may benefit from mixed methods. The study does not seek to explore social phenomena, but rather sought to determine if a significant relationship exists between two variables. The choice of a quantitative research method is the most appropriate choice for the study because the method will allow the researcher to examine relationships between variables.

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Research Design According to Creswell (2005), correlational designs are quantitative studies in which the researcher's focus is on measuring using the correlational statistical test, the relationship between two or more variables. The study's goal was to measure and correlate the data resulting from the two survey instruments. The study's purpose was to determine if a significant relationship exists between the two variables of EI and P-O fit. Correlational designs are used to measure the degree of association between the variables using the statistical procedure of correlational analysis. The statistical analysis of Pearson's correlation coefficients was used to measure and relate the research variables. This degree of association indicated if the two variables were related or if changes in one variable were reflected in the other variable (Creswell, 2005). The correlational analysis also showed if a significant relationship or association exists between P-O fit and distinct branches of EI such as perceiving emotion, facilitating thought, understanding emotion, and managing emotion. A correlational design was the most appropriate because the study's goal was to measure the degree of association between variables. To fulfill the purpose of the study, the Three-Item Person-Organization Fit Scale and the MSCEITTM were chosen as the survey tools. To determine the results from each research tool, a quantitative correlational research method and design was necessary. To perform analyses from both tools that will relate the variables, a quantitative research method with a correlational design was appropriate.

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The study's results are statistically presented in chapter 4. Statistical results for each variable are presented the chapter. Chapter 4 also includes the statistical results for the relationships between each research variable. Research Question and Hypotheses P-O fit (Kwantes, Arbour, & Boglarsky, 2007) and EI (Ravlin & Ritchie, 2006) are fast becoming important constructs in the hiring, training, and retaining of leaders and employees. Many leaders are assuming, without a foundation of extensive empirical research and knowledge on which to base their assumption, that high EI skills lead to a high level of P-O fit (Billsberry et al., 2005; Book, 2008; Bradberry & Greaves, 2005; Frase, 2007; Hunt, 2007; Kouzes, 2008; Roberson, Collins, & Oreg, 2005; D. Smith, 2006; Spors, 2007; Williams, 2007). The purpose of the quantitative correlational study was to determine the degree and significance of the relationship between EI and P-O fit. The study's results could provide organizations with a framework for recruiting and retaining leaders and employees, which could improve organizational effectiveness. A successful research study begins with the identification of research questions (Neuman, 2003). Research questions help to narrow the focus of a study to the specific issues the researcher seeks to address (Creswell, 2005). The following research question and hypotheses were guided by the study's problem and the nature of the study. Research Question What is the relationship between person-organization fit and emotional intelligence?

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Null and Alternative Hypotheses Hypotheses are statements about the relationship between variables that will be tested by the researcher (Neuman, 2003). Researchers use null and alternative hypotheses to make predictions about a study's outcome (Creswell, 2005). The null hypothesis predicts that there will be no relationship between the predictor and outcome variables. The alternative hypothesis predicts that there will be a relationship between the variables (Creswell). The Three-Item Fit Scale and the MSCEITTM was used to assess participants' levels of P-O fit and EI. The study employed the Mayer and Salovey's (2004) model of EI. The model is comprised of four abilities or branches including (a) perceiving emotion, (b) facilitating thought, (c) understanding emotion, and (d) managing emotion. Each of these components may affect P-O fit, a fact that is reflected in the hypotheses. Hypotheses must be framed to answer the research question. The study's research question guided the hypotheses and they are as follows: Null and Alternative Hypotheses H10: A significant relationship does not exist between P-O fit and EI. H1A: A significant relationship exists between P-O fit and EI. Theoretical Frameworks Theoretical frameworks are "orientations or sweeping ways of looking at the social world. They provide collections of assumptions, concepts, and forms of explanations" (Neuman, 2003, p. 62). Theoretical frameworks supports studies that seek to examine relationships between research variables (Neuman). The goal of the quantitative correlational study was to assess participants' levels of EI and P-O fit and to

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determine if a significant relationship exists between the constructs. The next section explores the theoretical frameworks under which the research falls for EI and P-O fit. Person-Organization Fit Framework The P-O fit construct under review in the current research study can be categorized under the theoretical work began by Murray (1938). P-O fit has been studied for many years and has its roots in Murray's need-press theory. In 1938, Murray described the interaction between an individual's needs and the demands of an environment in determining individual attitudes and outcomes (Westerman & Vanka, 2005). Since Murray's theory was published, the concept of P-O fit has been further conceptualized (Autrey & Daugherty, 2003; Autrey & Wheeler, 2005; Chatman, 1989; Cooper-Thomas et al., 2004; Kristof, 1996; O'Reilly, Chatman, & Caldwell, 1991). P-O fit research posits that attitudes, behaviors, and other person-level outcomes result from the relationship between the person and the work environment. P-O fit takes an interactionist view of the organization, focusing on the relationship among values, attitudes, and behaviors (Chatman, 1989). The P-O fit construct assumes that through contact with the organization, an individual acquires knowledge of that organization's culture and of what is expected of his or her behavior. An individual then possesses feelings about that organization that affect his or her behavioral choices (Autrey & Wheeler, 2005; Ng & Burke, 2005). Controversies surrounding the construct of P-O fit include those concerning the construct's (a) multiple conceptualizations and operationalizations, (b) limited distinction from other forms of P-O fit, and (c) means of measurement (Billsberry et al., 2005; Carless, 2005; Kristof, 1996; van Vianen, 2001).

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Today, many employers are hiring applicants who fit the organization's culture first and the position's job skills second (Spors, 2007; Williams, 2007). The importance of P-O fit for organizations has been indicated in significant relationships between P-O fit and turnover (DelCampo, 2006; O'Reilly et al., 1991), work attitudes (Ambrose et al., 2008; Dawis & Lafquist, 1984), organizational citizenship (Chatman, 1989), retention, teamwork (Westerman & Cyr, 2004), diversity (Ng & Burke, 2005), and work performance (Coppola & Carini, 2006; Prati, Douglas, Ferris, Ammeter, & Buckley, 2003). Cable and DeRue's (2002) P-O fit concepts provided the framework used to guide the research. Cable and DeRue suggests that positive P-O fit perceptions should result in increased identification with the organization. When employees perceive their values to match the organization's values, they are more likely to attribute positive motives to the organization's behaviors and actions toward employees. Specific components of this framework include (a) identification with an organization, (b) citizenship behaviors, and (c) decisions to stay in or leave an organization. A person is said to have P-O fit when his or her values are congruent with the organization's values. Emotional Intelligence (EI) Frameworks The current study's theoretical foundation for EI can be found in the early works started by Thorndike (1920). The roots of EI can be traced to Thorndike's (1920) social intelligence theory. While the concept as currently understood is relatively new (Cherniss & Goleman, 2001), aspects of EI have been studied for decades.

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Three models garner attention today. Bar-On pioneered a model of EI in 1988. Salovey and Mayer proposed a comprehensive theory of EI in 1990. In 1995, Goleman introduced his concept of EI. Bar-On's model represents a set of social and emotional abilities that help people cope with daily life (Cherniss & Goleman, 2001). Details of the Bar-On model can be found in Appendix A. The Salovey and Mayer model of EI focuses on the way in which a person processes information about emotion and emotional responses (Mayer & Salovey, 2004). Goleman's EI model represents different ways in which competencies such as empathy, learned optimism, and self-control contribute to important outcomes in one's life (Cherniss & Goleman, 2001). Controversies surrounding EI focus on (a) if the construct can be operationalized, (b) if reliable EI tests can be constructed, (c) if EI is a new construct that differ from existing personality constructs, (d) what EI predicts and at what levels, and (e) how to determine correct answers to tests measuring EI (Caruso, Salovey, & Mayer, 2004; Matthews, Zeidner & Roberts, 2004b; Murphy, 2006). Mayer, Salovey, and Caruso (2008) attribute confusion in the field to the "eclectic mix of traits" (p. 503) used in today's literature. The current quantitative correlational study was based on the concepts and assumptions first proposed by Mayer and Salovey (2004) and expanded by Caruso et al. (2004) in their abilities model. In this framework, EI involves the "abilities to perceive emotions, to access and generate emotions to assist thought, to understand emotion and emotional knowledge, and to regulate emotions reflectively to promote emotional and intellectual growth" (Caruso et al., p. 306). The construct focuses on a person's skill in

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recognizing emotional information and on carrying out abstract reasoning using this emotional information (Caruso et al.). The theoretical framework that guided the current study was the Mayer and Salovey (2004) model, expanded by Caruso et al. (2004). The Mayer and Caruso model was chosen because of the model's localization to the specific interaction between emotion and cognition. In addition, this model is the only EI model to be classified as a true intelligence (Mayer, Caruso, & Salovey, 2004). Of the three EI models, the Mayer and Salovey model has received the most rigorous testing and support. The model is the only framework that features an accompanying abilities measure of the construct (Caruso et al.). Four abilities or skills, referred to as branches, make up the model: (a) perceive emotion, (b) use emotion to facilitate thought, (c) understand emotion, and (d) manage emotion (Caruso et al.). Definitions The following operational definitions are provided to ensure that certain terms used in the study are understood and employed consistently (Cooper & Schindler, 2003). Intelligence. Intelligence is "the aggregate or global capacity of the individual to act purposefully, to think rationally and to deal effectively with his environment" (Wechsler, 1944, p. 3). To be considered an intelligence, a construct must meet three criteria: It should be capable of being operationalized as a set of abilities. Second, it must meet certain correlational criteria: the abilities defined by the intelligence should form a related set (i.e., be intercorrelated), and be related to pre-existing intelligences, while also showing some unique variance. Third, the abilities of the

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intelligence should develop with age and experience (Mayer et al., 2004, pp. 123124). Emotional intelligence is a class of intelligence that combines intelligence and emotion (Caruso et al., 2004). Mayer and Salovey (2004) define EI as follows: Emotional intelligence involves the ability to perceive accurately, appraise, and express emotion; the ability to access and/or generate feelings when they facilitate thought; the ability to understand emotion and emotional knowledge; and the ability to regulate emotions to promote emotional and intellectual growth (p. 35). EI is "a member of a class of intelligences including social, practical, and personal intelligences" (p. 197). EI is composed of four abilities or branches: 1. The ability to perceive emotion. 2. The ability to use emotion to facilitate thoughts. 3. The ability to understand emotions. 4. The ability to manage emotion. Person-organization fit is obtained when a person perceives that his or her values and goals are congruent with the organization's values and goals (Cable & DeRue, 2002). Employees and leaders who perceive P-O fit usually identify with and define themselves in terms of their organizations and feel a link with the organizational mission, vision, and goals.. These employees tend to form a social "category" (p. 876) within the organization and see themselves as a part of the organization's social network.

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Assumptions Assumptions are statements about a study regarding issues that are not "observable or testable" (Neuman, 2003, p. 49). Pointing out assumptions creates an awareness of issues within the study that may or may not be under the researcher's control. Noting and understanding assumptions at the beginning of a study can help the researcher avoid as much of the unknown as possible. The first assumption was that the population and sample size would be adequate to assume generalizability of the study results. A power analysis was conducted to determine the appropriate sample size for the current study. The analysis suggested that 67 participants would be an adequate sample size for the study. To enhance generalizability and control for this assumption, the study's sample was increased from 67 to a minimum of 75. A second assumption was that 30 or more participants would respond to the webbased surveys. The rationale for this assumption was based on Creswell's (2005) suggestion that at least 30 responses are needed for an adequate quantitative correlational study. The study population was human resource professionals from a variety of disciplines, levels of employment, and industries. The assumption was that there would be diversity in the current study population's knowledge and abilities pertaining to EI and P-O fit, which may enhance the study's ability to be generalized to other professions. The MSCEITTM and Three-Item P-O Fit Scale were used to determine the participants' level of EI and P-O fit. A third assumption was that the web-based survey tools used to assess the study participants will yield answers to the study's research question that would support or refute the hypothesis. The rationale for this assumption

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was based on the availability of other tools that could be used to test the participants. Both tools were chosen based on their high levels of reliability, validity, and rigorous testing results. A further assumption was that participants will respond to survey tools in a timely manner, with honesty and self-awareness, and that response rates will be adequate, with low error rates. The rationale for this assumption was based on the history of low response rates of surveys. The Dillman survey method was used to communicate with study participants and to remind them to complete the surveys. The Dillman method outlined a contact and communication process to increase response rates (Ray & Tabor, 2003). Scope, Limitations, and Delimitations Scope The scope of the current research study was to examine the relationship between P-O fit and EI. The Three-Item Person-Organization Fit Scale and the MSCEITTM were used to examine the existence of a relationship between the constructs. The study's participants were human resource professionals in the Southwest region of SHRM. Pearson's correlation coefficient was used to examine the relationship between P-O fit and EI. Limitations The study was limited by the use of the human resource profession and one professional organization. The study was further limited by the voluntary participation of SHRM members and participants yielding from the snowball sampling technique used to

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obtain study participants. Another limitation was the assumed honesty and self-awareness of participants answering survey questions. A further limitation of the study was the use of individual and self-report tools to measure EI and P-O fit. The use of individual-level tools will not address EI and P-O fit at the organizational level, which was beyond the scope of the current study. The study focused on individual perceptions and abilities so the use of individual self-report tools was appropriate. Delimitations Delimitations define a study's boundaries and could exert an impact on generalizability (Bryant, 2004). The study's sample included only human resource professionals, which could affect its generalizability to other professions. Ensuring diversity in the study sample by including a variety of disciplines within human resources could increase the study's generalizability to professions outside human resources. For example, information systems professionals manage the information and computer systems within a human resources department. Information systems professionals can also be found in a myriad of organizational units and departments outside human resources. To increase generalizability, a diverse mix of human resource professionals was solicited. The sample included individuals working in benefits, compensation, training, employee relations, onboarding, document management, organizational development, information systems, quality and risk management, and operations. Williams (2007) posited that as employees move up the corporate ladder, their EI skills tend to increase. If this assumption is true, the study's results may reflect participant's length of employment, which, in turn, could affect the study's ability to

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capture the P-O fit levels for the studied population accurately. Even a limited result could prove beneficial to organizations using EI as a tool to assess P-O fit. The results could also provide valuable training and development information. Summary The competition for talent has intensified and many organizations are seeking to recruit and retain employees who fit within their organizational culture (Spors, 2007; Williams, 2007). Many organizations assume that those with high EI skills are better able to assess their P-O fit within an organization, which enables better decision making and organizational success (Bradberry & Greaves, 2005; Erdogan & Bauer, 2005; Landen, 2002; Roberson et al., 2005; D. Smith, 2006; Spors). Proponents of P-O fit suggest that those with values and goal congruence with an organization are likely to identify with and remain employed with that organization (Ambrose et al., 2008; Autrey & Wheeler, 2005; Erdogan & Bauer, 2005; 2005; Kristof-Brown et al., 2005; Westerman & Cyr, 2004). While leaders tend to assume that those with high EI skills could be better equipped to perceive their P-O fit with an organization than those with low EI skills, no literature was found in this course of study that supported such a linkage. EI is a popular construct that gained popularity with Goleman's (1995) work. Goleman was not the first to conceptualize and study EI. The concepts and assumptions of EI were first proposed by Mayer and Salovey (1990) and later expanded by Caruso et al. (2004) in their abilities model. Mayer and Salovey's model is the only EI model to be categorized as a true intelligence (Caruso et al., 2004). Organizational leaders are searching for ways to recruit and retain employees who can contribute to the organization's success. Some research suggests that those who have

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not improved their EI skills could find themselves unemployed and not moving up the corporate ladder (Daus & Ashkanasy, 2005; Dulewicz & Higgs, 2003; Frase, 2007; Goleman, 1998; Macrae, 2004; Ravlin & Ritchie, 2006; Williams, 2007). Previous research has been conducted studying EI and P-O fit as individual constructs, but no studies were found that linked the two constructs or studied if a relationship exists between them. The research study examined the constructs together to determine if a significant relationship exists between them. Chapter 2 presents a literature review that includes germinal, historical, and current reviews for the P-O fit and EI constructs. A discussion of the articles, journals, books, and research documents reviewed for the research study is presented. A discussion of literature relevant to each research variable and existing gaps in the literature is presented.

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CHAPTER 2: REVIEW OF THE LITERATURE Chapter 1 introduced the research study and discussed the significance of the research and the study's social and theoretical value to society. The study's background, problem statement, methodology, research question, and hypotheses were provided. Chapter 2 presents a literature review of germinal, historical, and current literature pertaining to the research study and provides an analysis of the literature by comparing and contrasting the various viewpoints for the P-O fit and EI constructs. The purpose of the quantitative correlational study was to determine if a significant relationship exists between emotional intelligence (EI) and personorganization fit (P-O fit). The traditional paradigm of hiring and retaining employees specifically for job skills and experience is changing (Bielski, 2007; Goleman 2001; Kinsman, 2006; Kristof, 1996; D. Smith, 2006; Spors, 2007). Today's organizational leaders are seeking to hire and retain leaders and employees with high EI skills (Cherniss & Goleman, 2001; Goleman, 1998; Wakeman, 2006), assuming that high EI skills lead to P-O fit (Erdogan & Bauer, 2005; Frase, 2007; Landen, 2002; D. Smith). The importance of P-O fit and its impact on organizational culture (Autrey & Daugherty, 2003), citizenship behaviors (Cooper-Thomas et al., 2004), work attitudes (Ambrose et al., 2008; Chatman, 1991; Kristof-Brown et al., 2005), workplace socialization (Autrey & Wheeler, 2005; Chatman), work performance (Coppola & Carini, 2006), and job satisfaction (O'Reilly et al., 1991) have been well documented. Individuals with high EI skills are able to recognize emotions in themselves and others and use emotions effectively to manage their behavior and relationships with

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others (Mayer, Salovey, & Caruso, 2004). In the literature, a great deal of documentation can be found that supports EI's role in leadership (Daus & Ashkanasy, 2005; Dulewicz & Higgs, 2003; Goleman, 2001), workplace outcomes (Carmeli & Josman, 2006), selfawareness, behavior (Carmeli, 2003; Macrae, 2004), workforce retention, behavior, job satisfaction, workplace socialization, interpersonal communication, employee commitment, acclimation, and professional success (Bradberry & Greaves, 2005; Carmeli; Goleman, 1998, 2001). The literature review (a) introduces, defines, and explains the EI and P-O fit constructs with a focus on germinal research for each variable; (b) reviews literature linking the constructs; and (c) reviews literature citing measurement strategies for each. Results of the study may be applicable to leaders who are searching for ways to increase organizational effectiveness using EI and P-O fit models and frameworks. Documentation A well-researched and thorough literature review introduces the study topics, discusses past and current methodologies and research techniques, reviews the significance of the research, and examines the current state of the field (Boote & Beile, 2005). The first step in delivering a quality literature review is to perform an in-depth literature search. A literature search of the ProQuest, EBSCOHost, and Gale Power Search databases for documents published after 2003 using the key words personorganization fit and emotional intelligence produced five matches. All five matches were conference papers, whose authors covered each construct individually but did not seek to determine if a relationship existed between EI and P-O fit.

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There were 278 matches for a search using the key words person-organization fit. Of those, 146 were scholarly articles. There were 4,833 matches for a search using only the key words emotional intelligence, and of those, 1,597 were scholarly articles. A search of the ProQuest database for dissertations published after 2003 resulted in no matches for documents containing both of the following key words: personorganization fit and emotional intelligence. There were 39 matches using only the key words person-organization fit and 357 using only emotional intelligence. None of these researchers sought to determine the existence of a relationship between EI and P-O fit. The works on P-O fit focused on examining the viability of the construct, especially with respect to recruiting, hiring, retention, and turnover rates. Works on EI were numerous; authors of these works focused on the construct's viability as well as on the leadership implications of EI, employee work life, citizenship behavior, and a plethora of other work issues. As the literature search did not reveal any studies or articles whose authors sought to determine if a relationship exists between P-O fit and EI, a gap in the literature is evident. While the seminal research literature relating to EI was vast, seminal literature for P-O fit was minimal and published primarily during the period of 1989 to 1998, which resulted in only 74% of references within the period of 20032008, as opposed to the required 85% of recent references. Germinal Foundations, Historical Overviews, and Current Findings The next section in the literature review provided the germinal foundation for each research variable. The section also provides a historical overview of each variable including (a) models and frameworks, (b) theoretical concepts, (c) ways in which each

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construct has been operationalized, and (d) methods of measurement. The outcome variable was P-O fit and EI was the predictor variable. Germinal Foundation of P-O Fit The P-O fit construct has its roots in several theories: Murray's (1938) need-press theory (e.g., tendency); Byrne's (1971) similarity-attraction theory; Dawis and Lofquist's (1984) work adjustment theory; Tajfel and Turner's (1985) social identity theory; and Schneider's (1987) attrition-selection-attraction framework (ASA). Murray proposed that a person's attitude and success depend on the interaction between the needs and demands of the job in relation to the needs of the person. The author proposed that a person's reactions are in direct response to the environment (e.g., job), and his theory suggests that a person may more readily adjust to a job if the needs of the job are congruent with his or her own personal needs. In Murray's theory, the word press describes environmental elements that could harm or benefit the person; resulting behavior is based on the perceived harm or benefit. In the similarity-attraction theory, Byrne (1971) proposed that individuals would seek situations and organizations that have characteristics similar to their own. Byrnes suggested that individuals will search for social, physical, and status characteristics within organizations that are similar to their own. Byrne's theory focused on the interaction between people within organizations. In the work adjustment theory, Dawis and Lofquist (1984) posit a direct relationship affecting work outcomes between an individual and the environment. Dawis and Lofquist describe the theory as follows:

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The work adjustment theory is based on the concept of correspondence between individual and environment, which implies conditions that can be described as a harmonious relationship between individual and environment, suitability of the individual to the environment and of the environment for the individual, consonance or agreement between individual and environment, and a reciprocal and complementary relationship between the individual and the environment (p. 54). In 1985, Tajfel and Turner (1985) introduced the social identity theory. The authors proposed that organizations shape the people within them. Tajfel and Turner proposed that people who viewed the organization's values as significant and of value to them would identify with the organization in positive ways. Individuals who viewed the organization positively were more likely to remain with the organization. The ASA framework is in contrast to Tajfel and Turner's (1985) social identity theory. In the ASA framework, Schneider (1987) focused on "the people that make the place" (p. 439). Schneider asserted that organizations do not shape people; rather, people shape organizations. Schneider claimed that the collective characters, personalities, values, and attitudes of the people in the workplace shape an organization's culture. As newcomers enter the organization, they can change it. In an update to Schneider's 1987 ASA theory, Schneider, Goldstein, and Smith (1995) warned organizations that rely on the ASA model for hiring and retaining employees that they could be in danger of becoming homogenous. Homogeneity, Schneider et al. contended, could negatively affect the long-term success of the organization by leading to resistance and even inability to adapt and change in response

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to environmental influences. If Schneider et al. are correct, the concept of fit could be challenged as inappropriate or inadequate as the sole model for selecting and retaining employees. Historical Overview of P-O Fit P-O fit is one of several dimensions of person-environment fit (P-E fit), which encompasses person-organization, person-job, person-vocation, person-group, and person-person (see Table 1). Person-environment fit (P-E fit) is the congruence between an individual and the environment (Jansen & Kristof-Brown, 2006). P-O fit is defined in the literature as the value congruence between an individual and an organization (Chatman, 1989; Kristof, 1996; Kristof-Brown et al., 2005; Yaniv & Farkas, 2005). Table 1 Dimensions of Person-Environment Fit Dimensions of Person-Environment Fit (P-E fit) Person-organization fit (P-O fit) Person-job fit (P-J fit) Person-vocation fit (P-V fit) Person-group fit (P-G fit) Person-person fit (P-P fit)

Literature on the P-O school of thought focuses on various aspects of the P-O fit construct. One of the first models was offered by Chatman (1989). Chatman expressed the interactionist view of P-O fit. Later models took a multidimensional approach to the construct (Kristof, 1996; Westerman & Cyr, 2004).

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P-O Fit Models and Frameworks The P-O fit construct has been labeled as broad and elusive (Billsberry et al., 2005) because of the various ways in which the construct has been operationalized (Kristof, 1996), and because of the way in which an individual views his or her own ideals and sense of fit (Billsberry et al.; Cable & DeRue, 2002). The P-O fit construct has been studied for only about two decades but there have been many attempts in the literature to define the construct. Researchers have also sought to conceptualize and operationalize P-O fit. This literature review examines two notable efforts by Chatman (1989) and Kristof (1996) on the subject of P-O fit. Chatman was one of the first to explain the P-O fit construct. Chatman's (1989) interactional model has its roots in Lewin's (1951) supposition that behavior is a function of the person and the environment. Both researchers focused on the effect individuals have on situations; they understood people as active rather than "passive" (p. 337) players in their choice of situations and their resulting performance. In the interactional model, Chatman defined P-O fit as "the congruence between the norms and values of organizations and the values of persons" (Chatman, p. 339) and considers the person within the organization as well as the situations the individual may encounter within the organization. This view is in contrast to some views of P-O fit such as contingency models (e.g., Fiedler, 1976). Supporters of the interactional view maintain that the person may influence the situation (Roberts & Foti, 1998), whereas contingencytype models focus on matching a task to a person's personality and characteristics. Interactionists propose that the contingency model is weak because it takes only immediate task situations into account rather than considering the possibility that the task

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and situation change over time. For example, a person whom is initially good at a certain task might or might not have the personality or characteristics required to adapt to situation and task changes. Support for the interactionist view can be seen in the study conducted by Dvir, Sadeh, and Malach-Pines (2006) in which the P-O fit concept was tested using a group of project managers. The researchers found practical support for the theory writing that a better fit could be created if a person's personality was matched to the assigned project. Kristof (1996) offered one of the most in-depth analyses of the P-O fit model found in the literature. Kristof attempted to define, conceptualize, operationalize, and offer methods of measurement for the P-O fit construct. Some researchers have called the P-O fit construct "elusive" (Billsberry et al., 2005). Kristof challenged this elusive characterization with an integrative model of P-O fit. Even Kristof's attempt to offer an in-depth model of P-O fit has not convinced some researchers who contend that the construct is inadequate in predicting fit because the construct does not consider cultural differences in global values (Nyambegera Daniels, & Sparrow, 2001). Kristof (1996) proposed various concepts of fit including complementary, supplementary, needs-supplies, demands-abilities, and demands-abilities fit (see Table 2). Complementary fit is attained when a person brings characteristics to the work environment that were previously missing (Kristof, 1996; Piasentin & Chapman, 2007), "making the environment whole" (Kristof, p. 3). Individual characteristics include a person's "values, goals, personality, and attitudes (p. 4). Supplementary fit is achieved when an individual enters an environment with characteristics that are similar to or match those of others within the environment (Kristof; Piasentin & Chapman).

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Table 2 Kristof's P-O Fit Concepts Type of Fit Complementary fit Definition of Fit Concepts Individual's values, goals, and attitude meets organization's needs. Supplementary fit Individual's characteristics match those of others in the organization. Needs-supplies Individual's needs, desires, and preferences are met by organization. Demands-abilities Individual's characteristics meet the organization's demands.

Prior to Kristof's (1996) review, the needs-supplies and demands-abilities concepts had been examined separately in the literature, but not in an integrative manner (Kristof). Needs-supplies fit is achieved when a person's "needs, desires, or preferences" (p. 3) are met by an organization. This form of fit results in increased levels of satisfaction and commitment (Westerman & Cyr, 2004). Demands-abilities fit occurs when an individual's characteristics and skills meet the demands of the organization (Kristof). Kristof also offered ways in which to measure the construct based on its various concepts and modes of operation. Kristof's work is often cited in the literature (Carless, 2005; Erdogan, & Bauer, 2005; Westerman & Cyr, 2004) and seems to be the basis on which today's concept of P-O fit is used in the workplace.

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In the integrative model, Kristof (1996) offers a variety of ways in which the P-O fit construct can be operationalized: (a) values congruence, (b) goal congruence, (c) individual preferences or needs and organizational systems and structure, and (d) organizational personality congruence. Value congruence is critical to P-O fit (Kristof). Individuals who have values similar to those of their organization have been found to assimilate faster into the organization and intend to remain with that organization (Abbott, White, & Charles, 2005). Goal congruence is based on Schneider's (1987) ASA framework where the author proposes that individuals are attracted to organizations that have goals similar to their own (Kristof). While organizational leaders may view this congruence as positive, Schneider et al. (1995) caution against using the ASA framework exclusively, as homogeneity may become an issue. The congruence between individual preferences or needs and an organization's systems and structure has its roots in Murray's (1938) needs-press theory, in which an individual's needs versus the current situation play a role in P-O fit. This operationalization can also be traced to Dawis and Lofquist's (1984) work adjustment theory whereby an individual obtains satisfaction if the environment or organization meets his or her work needs. Organizational personality congruence is attained when an individual's personality or attitude results in the individual valuing the organization's systems, such as compensation, rewards, and supplies (Kristof, 1996). While personality congruence is said to be important to P-O fit, Westerman and Cyr (2004) found that personality congruence was not significant in predicting satisfaction or intent to stay with an organization.

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Measuring P-O Fit P-O fit can be measured in a variety of ways; disagreement exists as to which method is most appropriate. The literature presents several ways in which P-O fit has been assessed over the years including commensurate, perceived, and actual fit measurements. Commensurate measurements are described as those that examine the same characteristics for the organization and the individual (Kristof, 1996; Westerman & Cyr, 2004). Kristof suggested using commensurate methods to measure supplementary fit, as commensurate methods can measure specific characteristics such as "honesty values or social welfare goals" (p. 10). Kristof provided a caveat to using commensurate measurements with complementary fit suggesting that the breadth of the construct should be determined in order to ensure the matching of characteristics under study. Perceived and actual fit should be measured using methods appropriate for each. Perceived fit, being subjective, is best assessed using measurements that ask a person direct questions about the existence of fit. The premise is that if a person perceives a fit to exist, then it does for that person (Kristof, 1996). Kelly (2003) found that perceived fit measures could predict job satisfaction. In a study conducted by Piasentin and Chapman (2007), employees with higher levels of perceived fit experienced greater job satisfaction and commitment to their organizations. Criticisms of perceived measurements include the concern that if direct characteristics are not listed, no way exists to correlate fit (Kristof). In contrast to perceived fit measures, actual fit measures assess specific characteristics of the individual and organization (Carless, 2005; Cooper-Thomas et al, 2004; Kristof, 1996). Actual fit can be measured using two approaches, indirect crosslevel measurements and indirect individual-level measurements. Indirect cross-level

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measurements are used to measure complementary and supplementary P-O fit. Indirect cross-level methods measure congruence of the individual and the organization, in contrast to perceived measurements, which address only one level of analysis (e.g., individual). Indirect individual-level methods measure the individual's level of actual fit (Kristof, 1996). The organization level is not directly measured using this method; rather the person's perception of the organization's characteristics is measured. While the individual level of measurement may seem inadequate, researchers point to the fact that perceptions are reality, writing that perceptions tend to drive a person's appraisal of his or her environment. Measures of perceived fit may be stronger than actual fit measures (Kristof, 1996, 2000; Ostrof et al., 2005; Piasentin & Chapman, 2007; Ravlin & Ritchie, 2006). Van Vianen (2001) disagreed with these measurement methods questioning the way in which rating scales are interpreted and bringing up the argument that no overall taxonomy of individual and organizational characteristics exists. The Organizational Culture Profile (OCP) and Cable and DeRue's (2002) Three-Item P-O Fit Scale are used pervasively in the literature to measure P-O fit. The Organizational Culture Profile. The OCP was developed in 1991 by O'Reilly. The instrument measures actual fit using an indirect cross-level method. The OCP consists of 54 statements to capture individual and organizational values as well as the "crystallization" (p. 341) of those values by people within the organization (Chatman, 1989). The results can determine an individual's preference for those specific values (Chatman; O'Reilly et al, 1991). In the O'Reilly study, the OCP showed strong reliability

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with a reliability coefficient of 0.88 for the organization-level profiles and a reliability of 0.86 for the individual-level profiles. Cable and DeRue's Three-Item P-O Fit Scale. Cable and DeRue (2002) conducted a study to determine employee perceptions about P-O fit, needs-supplies fit, and demands-abilities fit. To determine fit perceptions, the authors developed a threeitem assessment tool to measure these three types of fit. P-O fit was assessed using the following Three-Item P-O Fit Scale: 1. The things that I value in my life are very similar to the things that my organization values. 2. My personal values match my organization's values and culture. 3. My organizational values and culture provide a good fit with the things that I value in life (p. 879). Cable and DeRue's Three-Item P-O Fit Scale measures supplementary and perceived fit using an indirect individual-level measurement method. The reliability of the Three-Item P-O Fit Scale was r =.91 and .92, respectively, in the single-firm and multiple-firm samples. Cable and DeRue found that P-O fit perceptions could predict citizenship behavior. Current Findings P-O fit has been found to be a strong predictor of whom will have influence in organizations (Anderson, Spataro, & Flynn, 2008). Anderson et al., found that those with P-O fit, regardless of position within the organization, work performance, or demographics, were more likely to have influence in their organizations. Proponents of PO fit believe that the construct has become important in the study of organizational

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effectiveness because it improves upon the traditional paradigm of matching skills, knowledge, and abilities in predicting if an individual will be successful in a particular organization (Chatman, 1991; Erdogan & Bauer, 2005; McCulloch & Turban, 2007; Westerman & Cyr, 2004). Assessing for P-O fit can determine if a person's values will conflict with organizational values (Chatman; Kristof, 2000; D. Smith, 2006; Westerman & Cyr, 2004), a conflict that could have a negative impact on organizational effectiveness and turnover (Ambrose et al., 2008; DelCampo, 2006). Today, the P-O fit construct has become one of the most popular ways used to assess if a person will fit within an organization (Kwantes, Arbour, & Boglarsky, 2007). Hogan et al. (2007) proposed that congruence between an individual's values and the organization's values could lead to success. The P-O fit construct explores the phenomenon of hiring and retaining individuals based on characteristics of the organization, in contrast to the traditional paradigm of hiring people solely based in the job's characteristics (Chatman, 1989; Westerman & Cyr, 2004). The traditional paradigm for hiring focuses on determining if a person's skills, knowledge and abilities fit a particular job (Cox, 2006), whereas the P-O fit paradigm centers on if a person's values fit with the organization's values (Ambrose et al., 2008; Bielski, 2007; Carless, 2005; Chatman; Kinsman, 2006; Kristof, 1996). While proponents of P-O fit argue that the construct is key to organizational success, some disagree saying that fit does not always matter (Nyambegera et al., 2001). Nyambegera et al. argued that the notion of fit does not transcend cultures and that the construct could be different in economies outside of the United States. They further

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contended that a person's socialization and enculturation towards work have more impact on P-O fit than personal values do. Arthur, Bell, Villado, and Doverspike (2006) questioned the use of P-O fit in employment decisions writing that while the relationship of P-O fit to work attitudes is clear, the construct's relationship to performance and turnover is not. In addition, there may be legal implications of using the P-O paradigm in the selection of employees. Segal (2006) stated that eliminating a potential candidate from an interview pool based on the recruiter's assessment of perceived fit could violate the law under Title VIII and other antidiscrimination laws. Supporters of P-O fit believe that individuals whose values fit with an organization's values will contribute to organizational effectiveness and will be less likely to leave the organization (Ambrose et al., 2008; Coldwell, Billsberry, Meurs, & Marsh, 2007; Spors, 2007; Westerman & Cyr, 2004). In a study conducted by Swyny and Albrecht (2003), the authors found a significant relationship between P-O fit and employee satisfaction and intent to stay with the organization. In a study of Asian leaders, Li (2006) found that employees showed motivation, commitment to the organization, and trust when they believed his or her leaders' values were congruent with organizational values. Opponents express concern about the likelihood that organizations that hire and retain individuals based solely on P-O fit could risk "conformity, homogeneity, and lowered innovation as people and organizations become unable to adapt to new environmental contingencies" (Chatman, 1989, p. 343). To avoid a homogenous organization, organizational leaders should seek a level of P-O

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fit that is beneficial to long-term organizational effectiveness (Giberson, Resick, & Dickson, 2005). Distinguishing P-O Fit Today's researchers are studying ways in which to identify distinctions and similarities for fit concepts. Researchers have proposed that other P-E fit constructs complement the congruence of P-O fit (see Table 1; Carless, 2005; Davis, 2006; Kristof, 1996; Kristof-Brown et al., 2005; Ostroff Shin, & Kinicki, 2005). In a study of fit perceptions, Scroggins found that multiple aspects of fit affect job satisfaction and turnover. Person-vocation (P-V) fit, person-job (P-J) fit, person-goal (P-G) fit, and person-person (P-P) fit have all been highlighted as important to an individual's success in an organization (Davis; Kristof-Brown et al.; Westerman & Vanka, 2005). P-J fit is the broadest category of fit in the workplace (Kristof, 1996) and is defined as the matching of a person's personality with a career type (Jansen & KristofBrown, 2006; Kristof). P-J fit, one of the most studied types of fit, is said to exist when a person's knowledge, skills, and abilities meet the job's demands (Carless, 2005; Kristof). P-G fit is the compatibility of a person with his or her team or work group (Kristof; Kristof-Brown, Jansen, & Colbert, 2002). P-P fit involves the impact that one person may have on the work environment of another person, such as his or her supervisor (Jansen & Kristof-Brown). While researchers agree that these fit concepts play a key role in organizational effectiveness (Chuang & Sackett, 2005), P-O fit is argued to be more important, if not the most important, to individual success within an organization (Billsberry et al., 2006; Cable & DeRue, 2002; Carless).

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In the next section of the literature review, (a) the predictor variable is introduced, (b) the construct's evolution is reviewed, (c) the construct's application to the workplace is discussed, (d) popular EI models and frameworks are reviewed, and (e) popular EI measurement tools are presented. Germinal Foundation of EI EI has its origins in Thorndike's social intelligence theory (Dulewicz & Higgs, 2000; Landy, 2005; Mayer et al., 2004; Thorndike, 1920). Thorndike suggested that variances in the outcomes of his study on the predictive ability of IQ could be affected by personal qualities such as "dependability, loyalty, readiness to shoulder responsibility for his own acts, freedom from conceit and selfishness, readiness and ability to co-operate" (Thorndike, p. 27). Thorndike attempted to distinguish traditional forms of intelligence from social intelligence theory but was unable to accomplish this goal (Seal et al., 2006). Thorndike, and later, Wechsler (1944) were pioneers in theories of social intelligence. Weschler (1944) offered a definition of intelligence that suggested multiple components of intelligence. Weschler defined intelligence as "the global capacity to act purposefully, to think rationally, and to deal effectively with his environment" (p. 3). Weschler was the first to offer an intelligence test, the Wechsler's Adult Intelligence Scale. The scale differed from today's traditional intelligence scales in that it included components of social intelligence. In 1948, Leeper published an article that sought to establish a connection between emotion and thought (Leeper, 1948). In his article, Leeper discusses the concept of "disorganization emotion" (p. 11). Disorganization emotion is described as a person's

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negative response to a situation in which he or she has no ready response. Leeper argued that emotions could produce negative and positive behavioral responses. Many writers cite Salovey and Mayer (1990) as the first to coin the phrase emotional intelligence. The phrase was used by Leuner in 1966 in the German journal Praxis der Kinderpsychologie und Kinderpsychiatrie (Matthews et al., 2004a). In Leuner's article, a group of adult women was described as having low EI due to their inability to adjust to their social roles. The second mention of the EI construct was in Payne's (1985) doctoral dissertation. Payne used the construct in an educational context advocating the use of EI by suggesting that schools take student's feelings into consideration (Matthews et al., 2004a). While Salovey and Mayer were the first to use the term EI, Goleman (1995) popularized the construct. Historical Overview of EI Emotional intelligence (EI) has been defined in many ways, a fact that has contributed to its characterization as a nebulous and elusive construct (Dulewicz & Higgs, 2000; Locke, 2005; Matthews et al., 2004a, 2004b; Murphy & Siderman, 2006). Matthews et al. (2004a) define EI as "the competence to identify and express emotions, understand emotions, assimilate emotions in thought, and regulate both positive and negative emotions in oneself and others" (p. xv.) Landen (2002) described an emotionally intelligent person as one who can regulate his or her emotions and respond positively to the needs of the organization and of fellow employees. Socialization, defined as acclimating individuals to the organization, is touted as the key to workforce retention.

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The emergence of the integrated study of emotion and intelligence evolved during 1970-1989 (Mayer et al., 2002). The study of EI in the early seventies was mainly in the academic arena (Sharma, 2008). Sharma (1983; 1985) conducted studies during this period on the cognitive issues affecting academic success. During this period, Gardner (2004), with his multiple intelligence theory, challenged educators to look for several types of intelligences for those with diverse learning abilities. Gardner is credited with reintroducing the discussion around research aimed at discovering alternatives to traditional intelligence (Seal et al., 2006). In his multiple intelligence theory, Gardner (2004) introduced the concept of "personal intelligences" (p. 239). Gardner sought to examine internal and external ways in which an individual processed and reacted to information. Internal processes included ways in which the individual was aware of his or her own feelings, moods, and temperament. External personal intelligence included "one's ability to notice and make distinctions among other individuals and, in particular, among their moods, temperaments, motivations, and intentions" (p. 239.) Wagner and Sternberg (1985) introduced their concept of "practical intelligence" (p. 437). The authors proposed that practical intelligence, that is, the use of one's "emotions and feelings" (p. 437), was also an important factor in assessing intelligence. It was during this period that the phrase emotional intelligence was used for the first time in a dissertation by Payne (1985). The period 1990-1993 saw a definitive theory of EI developed by Salovey and Mayer (1990), which marked a milestone for focused study and research in the field. The authors addressed the usage of the phrase emotional intelligence and offered the first

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definition of the construct. Salovey and Mayer also attributed skills to the EI construct. The authors also offered a way in which to measure EI as a mental ability. The result was an abilities-based method that used color and design elements to determine on one's ability to identify emotional states. EI study during the nineties focused on the study of emotions and the meanings behind emotions and thought (Salovey, Brackett, & Mayer, 2004). Researchers focused on how emotions and mood influenced personal thought processes and one's judgment (Palfai & Salovey, 1993-1994; Salovey & Birnbaum, 1989; Salovey et al.). Early studies were conducted with depressed and bipolar individuals. The field of EI was popularized between 1990-1994 by Goleman, a psychologist and journalist, in his book Emotional Intelligence (Mayer et al., 2002). Goleman's book was based on the research and writings of previous authors in the EI field. Goleman suggested that EI might be the most important predictor of success (Mayer et al.). It was during this period that psychologists, educators, and human resource professionals began to use the EI construct as one way to achieve organizational success (Salovey et al., 2004). Salovey and Mayer wrote that Goleman changed the meaning of EI, making it more of a social behavior than a cognitive construct. The authors proposed that the change in meaning categorized Goleman's theory of EI as representative of personality rather than intelligence. The next section traces the historical evolution of EI models, frameworks, and measurement.

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EI Models and Frameworks While there have been many attempts to conceptualize the EI construct, three models are pervasive in the literature: (a) Bar-On's model of EI and social intelligence, (b) Mayer and Salovey's abilities-based model and (c) Goleman's EI- based theory of performance. EI models are categorized as either mental-ability or mixed models. In mental-ability models, researchers examine the interaction between emotions and thought. In mixed models, though based on ability models of EI, researchers examine cognitive mental abilities as well as noncognitive personality traits such as motivation (Caruso et al., 2004). While mental-abilities models may be better able to predict outcomes, mixed models are also valuable (Daus & Ashkanasy, 2005; Mayer et al., 2004). Table 3 shows EI models for each category. Table 3 Mental Abilities and Mixed Models of EI Mental Abilities Model Mayer and Salovey (2004) Mixed Models Goleman's EI framework (1995, 2001) Bar-On (1997)

Bar-On's model of emotional and social intelligence (mixed model). Bar-On is credited with coining the phrase emotional quotient (Matthews et al., 2004a). Bar-On referred to his theory as "a model of emotional and social intelligence" (p. 206) and defined EI as "an array of non-cognitive capabilities, competencies, and skills that influence one's ability to succeed in coping with environmental demands and pressures"

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(p. 15). Bar-On's conceptualization of the construct appears to include personality traits and consists of five competencies, each with multiple components (see Table 4). Table 4 Bar-On's Five EI Competencies and Components Bar-On's Five EI Competencies and Components Competency Intrapersonal skills Component Emotional self-awareness, assertiveness, self-regard, self-actualization, independence Interpersonal skills Adaptability Stress management General mood Interpersonal relationships, social responsibility, empathy Problem solving, reality testing, flexibility Stress tolerance, impulse, control Happiness, optimism

Bar-On's definition and conceptualization seem broad, a fact that has been criticized by other EI researchers (Matthews et al., 2004b; Murphy, 2006). Critics of BarOn's model write that the theory is not distinct from other theories, such as Goleman's, and criticize the author for not providing a clear and thorough explanation of his model (Matthews et al.). Mayer and Salovey's mental abilities model. Mayer and Salovey (2004) define EI as follows: Emotional intelligence involves the ability to perceive accurately,

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appraise, and express emotion; the ability to access and/or generate feelings when they facilitate thought; the ability to understand emotion and emotional knowledge; and the ability to regulate emotions to promote emotional and intellectual growth (p. 35). Mayer and Salovey identified four branches of EI, which are shown in Table 5. The order of the branches is important, as each branch builds upon the next to determine EI (Mayer et al., 2002). Branch 1 relates to individuals' ability to identify emotions in themselves and in others and the ability to express those emotions in a positive and accurate manner. Branch 2 describes individuals' ability to use their emotions to consider different points of view, resulting in a synthesis of information for problem solving. Branch 3 involves the ability to recognize emotional states and those states' resulting feelings. The final branch involves the ability to recognize and regulate one's emotions in an effort to control negative behavior. To be classified as emotionally intelligent, individuals must have abilities in all four areas. Mayer and Salovey's model is unique in that it focuses on mental abilities alone rather than including personality traits (Caruso et al., 2004). In the 1997 introduction of the model, Mayer and Salovey confessed that because EI had not been extensively studied, little was known about its predictive power.

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Table 5 Four Branches of Mayer and Salovey's 1997 EI Model Four Branches of EI Perceptions, appraisal, and expression of emotion Emotional facilitation of thinking Understanding and analyzing emotions; Employing emotional knowledge Reflective regulation of emotions to promote emotional and intellectual growth

Mayer et al. (2004) proposed that their mental abilities model should be classified as an intelligence. The authors view EI as one of the hot intelligences, that is, "social, practical, and personal intelligences" (p. 197). To qualify as an intelligence, a construct must be seen as a set of abilities, be correlational with other intelligences while showing some distinction, and improve as one grows older (Mayer et al.). In two separate studies, the authors found that their four-branch model met these criteria (Mayer et al.). Daus and Ashkanasy (2005) supported Mayer et al.'s work writing that the ability-based model is the most promising model of EI and adds value to psychology. Clarke (2007) wrote that abilities-based models offer greater validity and show "a clear link between this set of emotional abilities, transformational leadership and the quality of individuals' social relationships" (p. 48). Goleman's EI-based theories of performance (mixed model). Goleman (1998) proposed that EI could predict success in school, work, and social situations defining EI as "the capacity for recognizing our own feelings and those of others, for motivating

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ourselves, and for managing emotions well in ourselves and in our relationships" (Goleman, p. 317). Goleman posited that his framework is based on competencies that are different from IQ competencies (i.e., intelligence competencies). Goleman introduced an EI framework based on what he termed emotional competence defining the term as "a learned capability based on EI that result in outstanding performance at work" (p. 24). The framework consists of five categories (see Table 6). Table 6 Five Categories of Goleman's 1998 EI Model Five EI Categories of Emotional Intelligence Self-awareness Motivation Self-regulation Empathy Adeptness

The self-awareness category of Goleman's 1998 model involves being aware of one's emotions and how they affect behavior and job performance. Individuals who demonstrate motivation exhibit a desire and drive to meet their goals, take risks, and seek ways to improve. An individual who has attained self-regulation can recognize and control emotions when faced with pressure. Individuals who demonstrate empathy are able to identify with the needs of others and can understand the others' perspectives. Adeptness in relationships can be achieved by using one's influence and skills to gain

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agreement and support. In 2001, Goleman introduced an updated version of his theory, in which he provided more physiological evidence to support EI and reduced the number of emotional categories from five to four (Cherniss, 2001; see Table 7). Table 7 Goleman's 2001 Updated EI Model Four EI Categories of Emotional Intelligence Self-awareness Social awareness Self-management Relationship management

In the 2001 updated model, Goleman proposed the existence of "distinct neurological mechanisms that distinguish each domain from the others and all four from purely cognitive domains of ability" (Cherniss, 2001, p. 29). The newer version also includes more workplace dimensions such as organizational awareness. The selfawareness competence remains the same as in the previous model. The social awareness competence encompasses the previous model's empathy competence. Goleman's updates to the model included information regarding how lesions in the brain could negatively affect that competency. As with social awareness, Goleman updated the previous self-management competence by adding information about how damage to the left medial prefrontal cortex could affect an individual's ability to regulate their behavior. Relationship management, as in Goleman's early EI model, describes an

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individual's ability to recognize emotions in others and the ability to control one's negative emotional behavior. Critics of Goleman's framework have argued that his definition is too broad and appears to be based on personality traits and "Judeo-Christian ethical values" (Matthews et al., 2004a, p. 11). The EI framework has also been accused of being a "psychological fad" (Matthews et al., 2004b, p. 179). Locke (2005) discounted Goleman's use of neurophysiology reasoning that "ideas do not have the same attributes as neurons" (p. 429). Mayer et al. (2004) and Matthews et al. (2004a) refute Goleman's claim that EI has predictive abilities citing the lack of substantiated empirical studies in that area. McEnrue and Groves (2006) agree with Matthews et al. citing the "limited evidence of ability to predict job performance" (p. 29). Matthews et al. characterized Goleman as a journalist who had taken scientific information and marketed the construct as pure science. Measuring EI The development of a sound measurement tool begins with the clear conceptualization of a construct (Matthews et al, 2004a). Creswell (2005) explained that tools used to measure constructs must be reliable and have content, criterion-related, and construct validity. Reliability can be assessed based on the stability of test scores over multiple samples; content validity can be gauged based on the extent to which the tool covers the construct's components.

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Criterion-related validity is the extent to which the tool's scores can predict outcomes. Construct validity measures the significance of the results after using the tool. Three common approaches exist for measuring EI: (a) self-report tests, (b) 360-degree tests, and (c) abilities-based tests (Grewal & Salovey, 2005). Below is a review of each approach along with the most commonly used measurement tool for each. Self-report measurements: Bar-On's emotional equivalent inventory (EQ-i). Selfreport measurements are popular because of their ease of use (Grewal & Salovey, 2005). Participants taking self-report tests answer questions in which they rate themselves. Selfreport EI tests measure the respondent's perceptions of his or her own EI. Critics of selfreport tests contend that they tend to measure characteristics outside EI, such as personality. Respondents may also lack self-awareness and answer questions in ways that reflect how they want to view themselves, rather than answering realistically (Salovey & Grewal, 2005). The EQ-i was the first commercial EI test published (Bar-On & Parker, 2000) and has been translated into 22 languages. EQ-i was originally designed as an experimental tool to test emotional and social functioning (Bar-On & Parker). The EQ-i is a 40-minute, 133-item EI self-report tool that measures five components of EQ: (a) intrapersonal, (b) interpersonal, (c) adaptability, (d) general mood, and (e) stress management (Conte, 2005). The tool is appropriate for environments such as clinics, schools, medical settings, human resource departments, and research institutions (Wakeman, 2006). Table 8 shows the scores for inter-scale correlations, internal consistency, and stability reliability (BarOn & Parker).

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Table 8 EQ-i Scores EQ-i Scores Inter-scale correlations Internal consistency Stability reliability .50 (overall average) .76 (overall average) .73

Critics who question the use of Bar-On's self-report measurement have charged that it measures too many items outside pure EI factors such as "effective decision making" (Daus, 2006, p. 304). In addition, the tool does not appear to measure any construct that is not already measured in other personality tests (Matthews et al., 2004b). The instrument's content and construct validity are also in question (McEnrue & Groves, 2006). McEnrue and Groves proposed (2006) that the EQ-i's content validity "lacks affect" and "omits emotional expression" (p. 29). The authors cite the tool's lack of construct validity writing that the tool has "very high intercorrelations with other EI measures" (p. 29). Matthews et al. recommended that organizations that use the EQ-i test for employee selection exercise caution, as the tool appears to assess personality rather than cognitive ability. 360-degree measurements: Goleman's emotional competence inventory (ECI). Measurements characterized as 360-degree tests differ from self-report tests in that other people are involved in assessing an individual. Researchers solicit answers regarding the

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individual's EI skills from peers, friends, supervisors, and so forth in order to assess EI. Thus, 360-degree tests offer more objective views of individuals (Grewal & Salovey, 2005). As leaders move higher up in the organizational chart, fewer opportunities exist for feedback regarding their EI (Sala, 2001). Initially developed in 1998 and updated in 2000, the ECI is a 35-minute, 110-item EI measurement tool that provides 360-degree feedback on strengths and weaknesses and on the possible gap between one's self-perception of his or her own EI and others' perceptions (Sala, 2001). The ECI was designed to measure emotional competencies and social behaviors (Conte, 2005) and measures four competencies as shown in Table 9. Table 9 EI Competencies Measured by the ECI Emotional Intelligence Competencies Self-awareness Self-management Social awareness Social skills Emotional self-awareness, accurate self-assessment, selfconfidence Self-control, trustworthiness, conscientiousness, adaptability, achievement, orientation Empathy, developing others, service orientation, organizational awareness Influence, communication, conflict management, leadership, change catalyst, building bonds, teamwork and collaboration

In a study conducted by Sala (2001), the ECI was administered to 1,214 employees from a variety of organizations. Eighty-one percent of those responding held the position of first-level managers or higher. Results indicated that the leaders tended to have higher assessments of their own EI abilities than did lower-level employees. The

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leaders' self-imposed ratings also tended to be higher than the ratings they received in the 360-degree feedback responses from those with whom they worked. As with the Bar-On measurement, critics have questioned the notion that the ECI is a pure EI tool, as it measures multiple factors (Daus, 2006). Reliability scores for the ECI range from .629 for the Emotional Self-Awareness cluster to .866 for the Change Catalyst cluster (Gowing, 2001). Gowing wrote that the ECI's validity and reliability scores are supported by its predecessor, the Self-Assessment Questionnaire, a test that measures performance competencies. McEnrue and Groves (2006) questioned the tool's construct and content validity. Conte (2005) stated that the ECI should not be taken seriously due to its lack of evidence of discriminant and predictive validity. McEnrue and Groves charged that the ECI measures factors other than emotion including change and flexibility. The authors also suggested that the ECI does not appear to measure items that differ from those on other personality tests, which is a concern of many researchers (Conte; Matthews et al., 2004b; Murphy, 2006). Gowing wrote that the ECI is a tool designed for developing people, not for making human resource decisions such as hiring, promoting, and assessing compensation. Mental ability-based measurements. Caruso et al. (2004) argued that an abilitybased measurement could be used to improve organizational effectiveness. They contended that the use of performance measurements assess EI more effectively than selfreport measures do as performance measurements include emotional skills. When measured as ability, reliability and validity can be proven (Caruso et al).

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The first abilities-based test, the Multifactor Emotional Intelligence Scale (MEIS), was introduced in 1998 by Mayer and Salovey. According to Caruso et al., abilities-based measures are appropriate to use in workplace settings because they measure performance as it relates to emotional skills. The abilities-based measurement gauges the ability of the respondent to use problem-solving skills in assessing his or her EI. In contrast to perception-based or self-report tests, ability-based measurements result in right and wrong answers, the lack of which has been a criticism of EI tests (Ashkanasy & Daus, 2005; Mayer Salovey, Caruso, & Sitarenios, 2003; McClelland, 1973). The MEIS is a 402-item tool consisting of four subscales that correspond to the abilities identified in the Mayer and Salovey model. The measurement tool provides ability-based questions and rating responses for each of the four branches. For example, for the perceiving and expressing emotions branch, the respondent is asked to identify the emotion on images of faces. The respondent's answer is then scored as right or wrong (Gowing, 2001). While the test has some excellent reliability and validity scores in some branches, other branches need improvement (Gowing). The overall reliability score for the MEIS is r = 0.95. Critics of the MEIS have challenged the measurement's ability to determine correct answers, test reliability, and test factor structure (Mayer et al., 2004). In 2003, Mayer et al. introduced an improved model of EI, the Mayer­Salovey­Caruso Emotional Intelligence Test (MSCEITTM). The MSCEITTM measures a person's ability to identify emotions in others, use emotions to facilitate thought, understand emotional meanings, and ability to manage emotions (Mayer et al., 2004). The 141-item scale provides an overall score for the four

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branches of EI: (a) perceiving emotion accurately, (b) using emotion to facilitate cognitive abilities, (c) understanding emotion, and (d) managing emotion. Each branch is measured using specific components as shown in Table 10. Table 10 MSCEITTM Measurement Components

Components of Each EI Branch as Measured by the MSCEITTM EI Branch Branch 1: Perceiving emotion How Measured? Identification of emotions as portrayed in faces and pictures of landscapes and designs. Branch 2: Using emotion to facilitate thought Comparison of emotions using sensations and other stimuli and identification of emotions that would facilitate a type of thinking. Branch 3: Understanding emotion Measures a person's ability to change emotional states as situations change. Branch 4: Managing emotion Uses hypothetical situations to gauge how one would change or maintain his or her feelings.

The MSCEITTM reports overall reliability scores of r = .91 and .93 for general and expert scoring, respectively (Mayer et al., 2004), and has been shown to have high reliability for each of the branches as reported in Table 11.The MSCEITTM is reported to

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have factorial validity in that the tool measures all four branches distinctly (Mayer et al.). McEnrue and Groves (2006) reported that the MSCEITTM has better content and construct reliability when compared with its competitors (i.e., ECI and EQ-i). The MSCEITTM has reasonable discriminant validity in that the EI construct is a distinct form of intelligence and does not duplicate other EI measurement tools (Mayer et al.). McEnrue and Groves confirmed that the MSCEITTM shows discriminant and convergent validity. Questions have been raised regarding the lack of scientific standards for consensus and expert scoring; for example, the manner in which experts are chosen has been challenged (Conte, 2005). Table 11 MSCEITTM Branch Reliability Scores MSCEITTM Branch Reliability Scores Branch Branch 1: Perceiving emotion Branch 2: Using emotion to facilitate thought Branch 3: Understanding emotion Branch 4: Managing emotion Reliability Score r = .91 and .90 r = .79 and .76 r = .80 and .77 r = .83 and .81

The MSCEITTM is scored two ways: (a) using a consensus method taken from a worldwide sample of respondents, and (b) through expert scoring by a group of 21 emotion researchers (Salovey & Grewal, 2005). Both methods have proven reliable (Mayer et al., 2003). Two 40-minute versions of the tool are available: a hard copy pen-

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and-paper version and an online version. McEnrue and Groves (2006) argued that among the competing EI measurement tools, the MSCEITTM shows the most promise. The EI construct has been criticized for its multiple conceptualizations and lack of clarity (Dulewicz & Higgs, 2000; Locke, 2005; Matthews et al., 2004a; Matthews, Emo, Roberts, & Zeidner, 2006). Critics of EI have suggested that current measurement tools do not adequately measure the construct (Conte & Dean, 2006; Matthews et al., 2004b). The multiple and differing conceptualizations of EI may present a problem for content validity, and the predictive value of the construct is in question (Matthews, et al., 2004a, 2006). The construct validity of self-report and performance-based EI tools is also in question. Researchers have noted the inability of these tests to measure a common construct as well as the differences in scoring rationales (Conte & Dean; Hunt, 2007; Matthews et al., 2004a). Researchers have cited the abilities-based models (i.e., MEIS and MSCEITTM) as promising (Grewal & Salovey, 2005; Matthews et al., 2004a). Current Findings Today, organizational leaders are seeking to hire and retain people with good socialization skills. In a study regarding the skills that corporations viewed as critical for future leaders, the three most desired traits were communication skills, interpersonal skills, and initiative, which are components of EI (Goleman, 1998). While academic intellect can help a prospective employee obtain entrance into an organization, EI is critical to his or her ongoing success (Bradberry & Greaves, 2005; Carmeli, 2003; Cross & Travaglione, 2003).

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Even though aspects of EI have been studied for many years, the concept as a whole is barely two decades old (Cherniss & Goleman, 2001; Matthews et al., 2004a). Interest in the construct is said to have developed out of the failure of tests such as IQ measures, SATs, and school grades in predicting who will be successful (Dulewicz & Higgs, 2000). McClelland (1973) vehemently argued that the use of aptitude tests alone to predict job performance is not reliable. In a study conducted by Dulewicz and Higgs (2003), it was shown not only that EI is important in selecting leaders, but also that components of EI such as integrity, resilience, and influence are important attributes for leadership effectiveness and organizational change. Some researchers have proposed that EI may even be a better predictor of success than IQ (Dulewicz, Young, & Dulewicz, 2005a; Frase, 2007; Goleman, 1998). Frase noted that IQ has shown itself to be a successful predictor of success in school but has been less helpful in other situations. McClelland (1973) cited the lack of criterion sampling as a barrier to the use of IQ tests to predict performance. Gardner (2004) wrote that while IQ tests may have some value in assessing educational aptitude, multiple forms of intelligence such as personal intelligence should be considered as indicators for success later in life. In a study of leaders in the Royal Navy conducted by Dulewicz et al., EI was shown to be a better predictor of success than IQ. Matthews et al. (2004a) argued that EI provides hope for those who previously believed that IQ was the only measurement of intelligence, in contrast to the belief by some that IQ could be genetic (Hernstein & Murray, 1994).

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Even more hopeful is the suggestion that EI can be developed by individuals (Goleman, 2001; Palethorpe, 2006). Matthews et al. and Landy (2005) advised caution when suggesting that EI might be learnable, citing the lack of empirical research and the probable overstatement of results due to minimal evidence in the EI field. In a review of the construct, Ashkanasy and Daus (2005) proposed that EI is not a new form of social intelligence or a substitute for it, but a tool that can be used to study organizational behavior. EI in the Workplace An abundance of literature is available supporting EI's role in leadership (Daus & Ashkanasy, 2005; Dulewicz & Higgs, 2003; Goleman, 2001), workplace outcomes (Carmeli & Josman, 2006), self-awareness (Carmeli & Josman; Macrae, 2004), workforce retention, job satisfaction, workplace socialization, interpersonal communication, employee commitment, acclimation, and professional success (Bradberry & Greaves, 2005; Carmeli & Josman; Goleman, 1998, 2001). Landen (2002) wrote that as the workforce changes to a more knowledge-based arena, tacit knowledge becomes more important. Hiring and retaining employees and leaders with high EI skills could have a positive effect on their willingness to cooperate with organizational strategies, including retention strategies. Landen (2002) viewed emotions as the key to behavior and suggested that organizations will use EI to ensure success. Cross and Travaglione (2003) wrote that emotions are an important component to consider in workplace success because the ability to use emotions in a positive manner can result in better decision making as well

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as enhance innovation. Laff (2008) wrote that EI has become a required competence for high performance in organizations. Goleman (2001) suggested, and other studies have shown, that as leaders climb the organizational ladder, EI becomes more important (Bradberry & Greaves; Dulewicz et al., 2005a; Fiedeldey-van Dijk & Freedman, 2007; Palethorpe, 2006). While EI is reported to be important to organizational learning (ScottLadd & Chan, 2004), Goleman noted that EI does not guarantee automatic success, stating that an individual with high EI skills simply has the potential to be successful. Leadership Emotionally intelligent leaders are seen as transformational ones, those who "engage with others and create a connection that raises the level of motivation and morality in both the leader and the follower" (Northouse, 2004, p.170). In a study by Bono, Foldes, Vinson, and Muros (2007), employees who had leaders characterized as transformational experienced increased positive emotions. Northouse wrote that transformational leadership deals with the full individual ­ emotions, ethics, values, and long-term goals ­ and includes assessing follower motives in an effort to satisfy follower needs. EI skills play a key role in the ability of transformational leaders to manage and lead people toward organizational success (Palethorpe, 2006). Schoo (2008) contributed leaders' ability to make the best choices for their organizations to EI. Leaders must then be able to communicate these choices to the organization's members. Mayer et al. (2002) posited that EI skills increase one's ability to deliver motivational messages and organizational visions effectively. Goleman (2001) proposed

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that emotionally intelligent leaders are necessary for creating and sustaining a work environment that motivates employees toward success. In a Gallup study involving 700 companies with more than 2 million employees, the authors found that the relationship between a supervisor and an employee determines productivity and retention (Cherniss & Goleman, 2001). In times of change, effective leadership is critical. Leaders must be intellectually and emotionally equipped to adapt to environmental changes while leading and motivating their people toward organizational success (Connell & Travaglione, 2004; Iordanoglou, 2007). In a survey conducted by Ferres and Connell (2004), employees reported that they were less cynical during times of change if they believed that their leaders were emotionally intelligent. Ferres and Connell explained that employees who exhibit positive and proactive attitudes during times of change are more likely to support organizational change. The positive contribution of EI to the field of leadership is well documented. Dulewicz, Young, and Dulewicz (2005b) wrote that there "is a shift towards the importance of emotional intelligence rather than cognitive intelligence for effective leadership" (p. 72). In their study of leaders in the Royal Navy, Dulewicz et al. found that EI contributed more significantly to overall performance and leadership than IQ did. The authors thus suggested that EI has become more important than IQ in predicting leadership success. Mayer et al. (2002) confirmed that employees value leaders with high EI skills. Carmeli (2003) conducted a study seeking to determine if there was a relationship

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between EI and organizational commitment and found that leaders with high EI skills had better work outcomes were committed to their organizations and were less likely to leave. In a study of teachers, Iordanoglou (2007) found that EI had a positive effect on leadership behavior, organizational success, and commitment. Salisbury (2007) found that EI might determine individual potential for learning and leadership. In a study of innovation and management, Yuvaraj and Srivastava (2007) reported a positive correlation between EI, management innovation, and effectiveness. In a study of leadership and creativity, Rego, Sousa, Cunha, Correia, and Saur-Amaral found that leader EI could have an impact on employee and team creativity. Leaders with high EI may create and maintain work environments that stimulate creativity (Rego et al.). While many studies have attested to the importance of EI in the workplace, skepticism exists regarding the construct's significance to the field of leadership (Antonakis, 2003). Contrary to popular literature, dissertations by Weinberger (2003) and R. Smith (2006) refuted the idea that a significant relationship exists between EI and leadership effectiveness. Locke (2005) called EI's foray into leadership theory as "unfortunate" (p. 430) positing that leadership is less about emotions than it is about critical thinking and "actual intelligence" (p. 430). Frase (2007) wrote that more companies are using tests to gauge EI when recruiting and selecting leaders and cautioned against using such tools as the only measure of potential effectiveness.

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Training, Productivity, and Retention As organizations grow and adapt to change, employees and leaders can benefit from having an educated workforce that stays abreast of changing trends (Murtagh, 2006). Scott-Ladd and Chan (2004) asserted that EI plays a critical role in organizational learning, arguing that if a person is aware of his or her emotions he or she can adapt and change when necessary. Macrae (2004) showed that those who increased their awareness of their EI skills were able to improve their leadership skills. Salisbury (2007) found that EI might be a determinant of learning and leadership. Scott-Ladd and Chan stated that those with high EI are reported to have higher productivity and better peer relationships, while those with low EI tend to react negatively and show signs of insecurity and low coping skills, attributes that could have a negative impact on organizational learning. EI is a critical component in an employee's productivity and in his or her intent to stay with or leave an organization (Carmeli, 2003; Cherniss & Goleman, 2001; Scott-Ladd & Chan). EI can be developed but doing so takes willingness, dedication, and organizational support (Bradberry & Greaves, 2005; Dasborough & Ashakansy, 2003; Fiedeldey-van Dijk & Freedman, 2007). In a study of middle managers from major Fortune 1,000 organizations, Wofford (2007) found that higher-level managers had high EI skills, whereas the EI skills of middle managers were lower. More important, Wofford reported that even when middle managers are aware of their low EI skills, they are not willing to engage in organizational learning that could improve them. Such unwillingness to improve EI skills could hamper the ability of middle managers to motivate and lead

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their employees effectively and could have a negative impact on organizational effectiveness. Yuvaraj and Srivastava (2007) suggested that the development of EI should be included in leadership development programs. Clarke (2007) suggested that the programs that organizations develop to address EI could be the culprit behind employee disinterest. Goleman (1998) suggests that organizations gauge the readiness level of their employees and leaders for EI training and development. The author posited that if employees and leaders are not ready to change and develop, EI training and development programs could be a waste of time and money. The EI assessment process can determine (a) organization, employee, and leadership readiness for training; (b) provide clear communications about the program; and (c) provide continuous coaching, feedback, and support (Wofford). An increasing amount of literature is emerging on the inclusion of EI in business school curriculum. Krishnamurthia and Ganesan (2008) and Dhiman (2008) suggested that EI should be included in business school training. In a study of MBA students who completed EI courses, Krishnamurthia and Ganesan found a significant increase in EI scores following the study. Dhiman suggested that leaders could enhance their success if they develop and improve their EI skills. Dhiman proposed that EI training prior to entering the business arena could provide organizations with employees and leaders who enter the business world emotionally competent. Controversy in the EI Field Research regarding the benefits of EI has been well documented as well as the controversy that continues to surround the construct. Mayer et al. (2006) attributes the

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controversy to the "eclectic mixes of traits" (p. 503) being conceptualized in today's literature. Cleveland and Fleisman (2006) proposed three overarching concerns in the field of EI. The first concern is the lack of agreement regarding the definition of EI. The second concerns the possible overlapping of the construct with existing constructs such as personality. The claims being made about the importance and relevance of EI form the third concern, especially the claim that EI may be more important in gauging success than IQ. Conclusion EI and P-O fit have been linked to organizational effectiveness, with P-O fit focusing on values congruence (Carless, 2005; Chatman, 1989; DelCampo, 2006; Westerman & Cyr, 2004) and EI focusing on the use of emotions in the workplace (Caruso & Salovey, 2004; Goleman, 2001; Matthews et al., 2004a). During the history of EI and P-O fit, both constructs have been criticized for their multiple conceptualizations and many researchers have suggested ways in which to operationalize the constructs (Billsberry et al., 2005; Dulewicz & Higgs, 2000; Kristof, 1996; Locke, 2005; Matthews et al., 2004b). The literature offers several models and frameworks for both constructs, some more integrative (Kristof, 1996; Mayer & Salovey, 2004) than others (Bar-On & Parker, 2000; Chatman, 1989). As with the multiple operations of the constructs, researchers have offered several ways in which to measure both constructs. P-O fit measurement tools include O'Reilly's (1991) Organizational Culture Profile (OCP) and Cable and DeRue's (2002) Three-Item P-O Fit Scale. EI measurement instruments fall into three categories: (a) self-report, (b) 360degree, and (c) mental abilities-based instruments. Bar-On's EQ-i is an example of a self-

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report tool (Bar-On & Parker, 2000). Goleman's Emotional Competence Inventory (ECI) is a 360-degree measurement tool and Mayer and Salovey's MSCEITTM is a mental abilities-based instrument. Today, controversy surrounds the measurement of EI and P-O fit because of the many ways in which researchers have conceptualized the constructs; these multiple conceptualizations have resulted in several measurement tools. Summary Chapter 2 offered an in-depth review of germinal, historical, and current literature on EI and P-O fit, including ways in which the constructs have been conceptualized, operationalized, and measured. A large amount of literature exists for each construct. Germinal research on P-O fit can be traced back to 1938 with Murray's need-press theory. Foundational research for the EI construct can be found in Thorndike's (1920) social intelligence theory. The most cited P-O fit theorist is Kristof (1996, 2000) who has written several reviews and offered in-depth analyses of the P-O fit concept. While the EI construct had been studied for many years by Mayer et al. (2004), who posited that their mental abilities-based model of EI could be categorized as a true intelligence, Goleman (1995) popularized the construct. Organizational effectiveness is linked to P-O fit (Autrey & Daugherty, 2003; Autrey & Wheeler, 2005; Cooper-Thomas et al., 2004; O'Reilly et al., 1991) and EI (Daus & Ashkanasy, 2005; Dulewiez & Higgs, 2003; Goleman, 1998; Macrae, 2004; Ravlin & Ritchie, 2006). P-O fit and EI have been studied in many different environments. During the course of this review, no publications were found in which researchers explored the existence of a relationship between the constructs. Consequently, a gap in the literature exists. Given the lack of empirical research in this area, the quantitative correlational

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study's goal was to add to the body of knowledge by determining if a significant relationship exists between EI and P-O fit. Chapter 3 established the framework for the study's research methodology and design used to determine the existence of a significant relationship between P-O fit and EI. The chapter presents the study's research method and design and discusses the appropriateness of the chosen method. The study's research question and null and alternative hypotheses are presented. A discussion of the survey tools employed in the research study, including the validity and reliability of the instruments, is presented in chapter 3. Prior to the chapter's summary, a discussion of the population and study sample, procedures for data collection, informed consent process, confidentiality procedures, and methods for data analysis is presented.

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CHAPTER 3: METHODS Chapter 2 provided a review of the literature relevant to the research study. The purpose of the quantitative correlational study was to investigate the relationship between P-O fit EI. Chapter 3 presents the study's research method and design and discusses the appropriateness of the method and design. The study's population, sampling methodology, geographic location, informed consent, confidentiality, instrumentation, and procedures for data collection and analysis are presented in chapter 3. Figure 1 presents a diagram of the study's research process.

Figure 1. The research process.

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Research Method and Design Appropriateness One reason to conduct scientific research is to "learn how the world works so that people can control or predict events" (Neuman, 2003, p. 71). To determine an appropriate research method, a researcher must determine the best approach for his or her study. Qualitative research methods focus on concepts, themes, words, images, and generalizations while quantitative research uses variables, hypotheses, and data in the form of numbers (Neuman). Qualitative methods are phenomenological and rely on perceptions of study participants (Glatthorn & Joyner, 2005). Quantitative research methods have a positivist approach grounded in objectivity that can be expressed in numbers (Glatthorn, & Joyner, 2005). Quantitative methods are (a) used to identify trends and explain relationships between variables, and (b) measure variables and produce results can be generalized to a large number of people (Creswell, 2005). A quantitative research method was chosen for the study because of the desire to examine relationships between the P-O Fit and EI variables. The implementation of a quantitative research design was appropriate for the study since the variables that are of interest can be directly measured from the subjects in study. Variables and resulting data for the study can have numerical values assigned to each of the variables, which in turn can be assessed by different statistical procedures. The quantitative method was appropriate since the survey instruments (Mayer­Salovey­ Caruso Emotional Intelligence Test and the Three-Item Person-Organization Fit Scale) have been shown to be a valid and reliable instruments when it comes to measuring the

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EI and P-O fit of the study participants. The use of the EI test and P-O fit scale enabled the researcher to obtain quantitative data for the variables in the study. Qualitative designs such as grounded theory, ethnographic, and narrative were considered and could have been implemented for the current study but the researcher would not be able to determine the direct relationship between the EI and P-O fit variables. Grounded theory designs seek to explain processes and actions (Creswell, 2005). The study does not seek to explain, but rather seeks to determine if significant relationships exists between variables. The purpose of the ethnographic study design is to examine the variables rather than draw conclusions or make inferences to the target population (Glatthorn & Joyner, 2005), which makes the non-experimental correlational research design more appropriate. Narrative designs tell the lived stories of study participants, which is contrary to the current study's focus (Creswell, 2005). A qualitative design would not determine if there was a relationship between the EI and P-O fit of the subjects based on just describing the characteristics and making observations with respect to the participants in the study. For these reasons, the most appropriate method for the research study was a quantitative method with a correlational research design. The quantitative research design is more appropriate for the study than a qualitative design because with a qualitative design one would not be able to assess a direct relationship between two variables as result of the open-ended questions (Cozby, 2001). The responses received during qualitative research are based on open-ended questions that have to be interpreted and coded to identify trends or relationships in the responses by the researcher. Since the information has to be coded by the researcher

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conducting the analysis, the findings may be subjective depending on how the variables were coded. The quantitative non-experimental correlational design was appropriate for the current study since the objective was to determine if relationships exist between the EI and P-O fit of the study participants. Correlational research designs are quantitative studies in which the researcher's focus is on measuring using the correlational statistical test, the relationship between two or more variables (Creswell, 2005). To determine if a significant relationship exists between the two variables of EI and P-O fit, the current study employed a correlational design. The purpose of the study was to examine relationships, not to predict outcomes. Explanatory correlational designs measure the degree of association between the variables using the statistical procedure of correlational analysis. This degree of association will indicate if the two variables are related or if changes in one variable are reflected in the other variable (Creswell). The explanatory correlational analysis may also show whether a significant relationship or association exists between P-O fit and distinct branches of EI such as perceiving emotion, facilitating thought, understanding emotion, and managing emotion. Research Question and Hypotheses Research questions are used in quantitative research to narrow the focus of the research to specific issues (Creswell, 2005). "A hypothesis is a proposition to be tested or a tentative statement of a relationship between two variables" (Neuman, 2003, p. 151). The purpose of the quantitative correlational study was to determine if a significant

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relationship exists between EI and P-O fit. The following research question and hypotheses guided the study. Research Question What is the relationship between person-organization fit and emotional intelligence? Null and Alternative Hypotheses Researchers use null and alternative hypotheses to make predictions about a study's outcome (Creswell, 2005). The null hypothesis predicts that there will be no relationship between the independent and dependent variables. The alternative hypothesis predicts that there will be a relationship between the variables (Creswell). The study used the Mayer and Salovey's (2004) model of EI. The model is composed of four abilities or branches including (a) perceiving emotion, (b) facilitating thought, (c) understanding emotion, and (d) managing emotion. Each of these components may affect P-O fit, a fact that is reflected in the hypotheses. The study's hypotheses were as follows: Null and Alternative Hypotheses H10: A significant relationship does not exist between P-O fit and EI. H1A: A significant relationship exists between P-O fit and EI. Instrumentation The development of a sound measurement tool begins with the clear conceptualization of a construct (Matthews et al., 2004a). Creswell (2005) wrote that tools used to measure constructs must be reliable and have content, criterion-related, and construct validity. Quantitative data can be collected using questionnaires, surveys, notes, recording sheets, and so on (Neuman, 2003). To measure the participants' levels of

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perceived EI and P-O fit, the study employed surveys. Surveys have proven popular because they are easy to conduct and people tend to enjoy the process (Ray & Tabor, 2003). The objective of the study was to determine if a correlation exists between the constructs of EI and P-O fit. P-O fit was the outcome variable and EI was the predictor variable. Two instruments were used to collect data regarding the study participants' P-O fit and EI. The Three-Item P-O Fit Scale, designed by Cable and DeRue (2002) was used to measure P-O fit. The Three-Item P-O Fit Scale was chosen for its proven reliability and validity (Cable & DeRue, 2002). The scale also meets the needs of the study because fit can be assessed at the individual level. Mayer­Salovey­Caruso Emotional Intelligence Test (MSCEITTM) The MSCEITTM, the first abilities-based measure of EI, is a 141-item measurement tool designed to assess EI using an abilities-based scale. The scale measures how well people solve emotional problems and perform tasks rather than asking for their subjective assessment of their emotional skills and abilities (Mayer et al., 2003). The MSCEITTM is a performance-based measurement for people 17 years of age or older. The MSCEITTM can be administered by paper and pencil or online. All responses are computer-scored by Multi-Health Systems, Inc. The current study was conducted using the online version of the MSCEITTM. The MSCEITTM scale yields an overall EI score, two area scores (i.e., Emotional Experience and Emotional Reasoning), and scores for each of the four EI branches (see Table 12). The MSCEITTM is the first measurement to report valid scores in all four areas of EI (Mayer et al.). The MSCEITTM, developed by Mayer et al. (2002), is intended to

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measure for the following skill groups (a) perceiving emotion accurately, (b) using emotion to facilitate thought, (c) understanding emotion, and (d) managing emotion. Table 12 MSCEITTM Scoring MSCEITTM Scoring Overall score Two area scores Overall emotional intelligence score Experiential emotional intelligence; strategic emotional intelligence Four branch scores Perceiving emotion, facilitating thought, Understanding emotion, managing emotion

The Mayer and Salovey model is the only EI model to be classified as a true intelligence (Mayer et al., 2004). It has also received the most rigorous testing and support of the three models (i.e., it has undergone more testing and has received more support than the EQ-i and ECI) and is the only model that has an accompanying ability measure of the construct (Mayer et al.). The MSCEITTM measures the capacity to reason using feelings and the capacity of feelings to enhance thought (Mayer et al., 2002). The MSCEITTM can be scored two ways: (a) using a consensus method taken from a worldwide sample of respondents, and (b) through expert scoring by a group of 21 emotion researchers (Salovey & Grewal, 2005). Each method has proven to be reliable (Mayer et al., 2003). For the current study, the MSCEITTM used the consensus method of scoring since the alternative method of scoring is for EI experts.

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The MSCEITTM has been shown to be a valid and very reliable instrument when it comes to measuring the emotional intelligence of subjects (Mayer et al., 2002). The MSCEITTM has reasonable discriminant validity in that the EI construct is a distinct form of intelligence and does not duplicate other EI measurement tools (Mayer et al., 2004). The MSCEITTM was chosen because the tool is an abilities-based instrument that has "higher correlations with general mental ability" (Conte, 2005, p. 437) than self-report measures. Ability-based measurements are more likely to be used in the future because selfreport tools tend to measure personality characteristics (Conte). For these reasons, the MSCEITTM instrument provides one with more information regarding the EI of the subjects. Permission to use the MSCEITTM can be found in Appendix B. MSCEITTM descriptive and contact information can be found in Appendix C. Three-Item Person-Organization Fit Scale The study measured perceived fit using Cable and DeRue's (2002) Three-Item PO Fit Scale. Perceived fit, being subjective, is best measured using measurements that ask direct questions about the existence of fit. The premise is that if a person perceives a fit to exist, then it does for that person (Kristof, 1996; Piasentin & Chapman, 2007). While the self-assessment level of measurement may seem inadequate, researchers point to the fact that perceptions are reality; perceptions tend to drive a person's appraisal of his or her environment and measures of perceived fit may be stronger than actual fit measures (Kristof, 2000; Kristof-Brown et al., 2005; Ostrof et al., 2005; Piasentin & Chapman; Ravlin & Ritchie, 2006). Cable and DeRue's Three-Item P-O Fit Scale measures perceived fit using an indirect individual-level measurement method.

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The Three-Item P-O Fit Scale is based on the participants' responses to three items, which must be rated using a seven-point Likert scale (from strongly agree to strongly disagree). The three items to which participants must respond are the following: 1. The things that I value in life are very similar to the things that my organization values. 2. My personal values match my organization's values and culture. 3. My organization's values and culture provide a good fit with the things that I value in life (Cable & DeRue, 2002, p. 879). To obtain the P-O fit score for each participant, responses to the three items were coded from 1 through 7 and averaged. Permission to use the Three-Item P-O Fit scale can be found in Appendix D. The scale in its entirety can be found in Appendix E. Validity and Reliability Validity is the degree to which an instrument measures the construct or behavior being assessed (Creswell, 2005). Creswell identified three types of validity: content, criterion-related, and construct. Content validity is established when the questions on the instrument are representative of all questions that could be asked; criterion-related validity is established when the scores relate to the study's outcome; and construct validity is established when the resulting scores from the instrument are useful and significant (Creswell). Reliability is the level of consistency obtained when using the instrument (Creswell, 2005). Creswell suggested two types of procedures to assess reliability: testretest and internal consistency. The test-retest procedure determines if an instrument's

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scores are constant over time, while the internal consistency procedure determines if an individual's scores are consistent throughout the instrument (Creswell). Three-Item P-O Fit Scale The validity and reliability of the Three-Item P-O Fit Scale were established in a study by Cable and DeRue (2002). In the study, Cable and DeRue examined the factor structure of P-O fit and found that employees of two different samples differentiated between P-O fit and needs-supplies fit and demands-abilities fit. Moreover, the proposed factor structure showed an excellent fit to the data, with a goodness of fit index of 0.92 and 0.96 in each of the two samples. Using a sample of 187 managers, Cable and DeRue concluded that P-O fit was significantly related to organization-focused outcomes (such as organizational identification and turnover decisions). The instrument also had exhibited excellent internal consistency reliability, with Cronbach's alpha of 0.91 and 0.92 in each of the two samples. MSCEITTM The MSCEITTM reports overall reliability scores of r = .91 or .93, for general and expert scoring, respectively (Caruso et al., 2004; Mayer et al., 2003). In addition to having high reliability scores, the MSCEITTM is reported to have factorial validity in that the tool measures all four branches of the EI model distinctly (see Table 13; Mayer et al., 2004). The four branches are (a) perceiving emotion, (b) facilitating thought, (c) understanding emotion, and (d) managing emotion. The one-factor solution (i.e., assuming

all items are loaded on a single EI construct) and a four-factor solution (based on the four aforementioned skill groups) exhibited excellent fits, with normed fit indices ranging from 0.97 through 0.99. McEnrue and Groves (2006) reported that the MSCEITTM has better content

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and construct reliability when compared with its competitors, the Emotional Competencies Inventory (ECI) and the Emotional Equivalent Inventory (EQ-i). The MSCEITTM has reasonable discriminant validity in that the EI construct is a distinct form of intelligence (Mayer et al., 2003). Table 13 Branch Reliability Scores Branch Reliability Scores Perceiving emotion Using emotion to facilitate thought Understanding emotion Managing emotion r = .91 and .90 r = .79 and .76 r = .80 and .77 r = .83 and .81

Population and Sampling Population To answer the research question under study, a researcher must determine the population and locations to be studied (Creswell, 2005). A population is a group of people who share characteristics. Quantitative researchers usually choose their study participants from lists of people who are available to participate in the study (Creswell, 2005). The population and sample were accessed through the Southwest region of the Society of Human Resource Management (SHRM) in the United States. SHRM is the world's largest human resource professional association devoted to human resource management with more than 225,000 members from over 125 countries.

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Membership in the Southwest region totals more than 39,492. All study participants were over the age of 18 with full-time employment at various employment levels and in various disciplines and industries within human resources. Permission to use SHRM members as study participants can be found in Appendix F. A variety of disciplines exist within the human resources profession, including employee relations, benefits, compensation, information systems, quality assurance, organizational development, risk management, recruiting, training, onboarding, operations, and document management. The diversity in functions within the human resource profession may improve the study's potential to be generalized to other professions. Even though the study population was limited to human resource professionals, the study's results could have implications and immediate applicability to leaders throughout organizations as leaders generally participate in EI and P-O fit assessment and training at some point in their management of people. Four hundred and seventy-five SHRM members received an email request to participate in the research study or had access to SHRM's online newsletter, which published the request. One hundred and seventeen individuals responded to the invitation and agreed to participate in the study. Of the 117 affirmative responses, n = 89 completed the demographic questionnaire, the Three-Item Person-Organization Fit Scale, and the MSCEITTM. The response rate was 76.1%. Sampling Frame Snowball sampling was used to select participants from among SHRM members in the Southwest region of the United States. Snowball sampling is the intentional selection of individuals based on certain criteria or characteristics; snowball sampling is

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used in order to understand the relationship of the variables to individuals within a group (Creswell, 2005). This type of sampling does not suggest that study participants will know each other personally, though they may be connected through linkages with SHRM, organizational work relationships, or friendships (Neuman, 2003). A request for participation was sent to SHRM members who in turn sent the request to other SHRM members, organizational peers, and other human resource professionals. Participants were linked through their professions in human resources as well as through membership in SHRM. The criteria for selection were that an individual is (a) a human resource professional and (b) affiliated with the Southwest region of SHRM or its members. The power of a test refers to its ability to reject the null hypothesis when the null hypothesis is false (e.g., to conclude that the means of two groups are unequal, given that they are indeed unequal). The power of a test depends mainly on two factors: 1. Effect size: This is a measure of the magnitude of the treatment effect. The larger the effect size, the more powerful the test is (because it becomes easier to detect deviations from the null hypothesis). 2. Sample size. Again, the larger the sample size, the more powerful the test. Assuming a moderate (r = 0.3) correlation between EI and P-O fit and a standard significance level of 0.05, the required sample size in order to achieve the rigorous statistical power of 0.8 would be 67 participants. The standard significance level of 0.05 means that the probability for inaccurately rejecting the null hypothesis when valid is 5%.

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Based on the level of significance, the study and the study's results have a 95% confidence level. Results from the power analysis for the study indicated that 67 participants would be an adequate sample size. Creswell (2005) explained that the larger the sample, the lower the potential for sampling error. In the current study, the number of participants was increased to a minimum of 75 to control for potential sampling error. The ending sample was 89. When testing the hypotheses, it was important to understand problems that may arise due to Type I or Type II errors (Creswell, 2005). Researchers should take measures to minimize errors that could result from inappropriate sample size, which could affect the study's testing of the hypotheses. If the null hypothesis is rejected when valid, a Type I error has occurred. If an error occurs due to the acceptance of significance, when in fact significance does not exist, a Type II error has occurred (Bryant, 2004). Establishing an acceptable level of significance can control for Type I and Type II errors. The standard significance level of 0.05 and the increased sample size should control for Type I and Type II errors. Informed Consent The letter of introduction and invitation to participate in the research study was emailed to prospective study participants (see Appendix G). Respondents to the email invitation received the Informed Consent form, which outlined the guarantees of the participant's rights while he or she is participating in the study. The Informed Consent form included (a) an acknowledgement of voluntary participation, (b) a statement of the right to withdraw from the study at any time, (c) an explanation of the study's purpose,

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(d) a description of data collection procedures, (e) acknowledgement of the right to ask questions and receive a copy of the study results, (f) a statement indicating the lack of known risks associated with the study, (g) a statement indicating the benefits of participating in the study, and (h) the researcher's contact information (see Appendix H) (Creswell, 2005). The web-based Informed Consent form asked respondents to acknowledge participation by selecting the appropriate radio button. The form also contained an optout radio button. Respondents were required to select either the consent to participate button or the opt-out button before being allowed to move on to the survey instruments (see Appendix I) and the demographic questionnaire (see Appendix J). Respondents who consented to participate were directed to the survey; respondents selecting to opt-out did not receive the survey. There were no paper invitations and forms distributed because all study participants had access to a computer and the Internet. Only participants over the age of 18 who actively acknowledged consent were permitted to participate in the research study. Confidentiality Researchers should take every measure possible to protect the confidentiality of study participants (Neuman, 2003). Neuman described confidentiality as the researcher's obligation not to reveal to the public personally identifiable information, such as names, that he or she may obtain through the course of the study. Survey instruments did not contain participants' names, so there was no link of individuals to specific responses and data. A statement of confidentiality is contained within the informed consent form in Appendix H.

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Each study participant received a randomly assigned identification number for use on each survey instrument. Only participants over the age of 18 that actively acknowledged consent were permitted to participate in the research study. Participant identification numbers were used to track and organize each participant's response for data analysis. Data results are presented in chapter 4 in an aggregate form, such as means and percentages, as suggested by Neuman (2003). Web-based surveys were administered and collected at a central point with access only available to the researcher. SurveyMonkey (2008), an online survey tool, was used to collect data for the demographic survey and the Three-Item Person-Organization Fit Scale. The MSCEITTM was administered online via Multi-Health System's (MHS) website. To ensure confidentiality and privacy, SurveyMonkey and MHS use multiple layers of security. All data are contained behind a firewall and uses intrusion prevention technology to ensure security. SurveyMonkey and MHS use Secure Sockets Layer (SSL) encryption to ensure data confidentiality security. SSL ensures confidentiality by encrypting test user information, including test data, responses, and reports returned to the administrator, protecting against disclosure to third parties. Informed consent forms and all survey data will be stored in secure files for three years at the researcher's home upon completion of the research study. Access to informed consent forms and survey data will be restricted to only the researcher. At the end of the three-year data retention period, all informed consent forms and data will be shredded and destroyed, including all electronic data held on portable media devices.

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Procedures for Data Collection Participation in the study was purely voluntary. Participants were informed that they could opt out of the study at any time. The data collection process included a method for distributing and collecting surveys from study participants who did not have access to a computer or the Internet. Using the web-based and the U.S. mail methods afforded several advantages, including the ability to use participants who do not have access to the Internet. All study participants had access to a computer and the Internet, so there were no surveys distributed via the U.S. mail. The study population received an email from the Society for Human Resource Management (SHRM) requesting program participation. One SHRM chapter posted the request on an online newsletter. One hundred and seventeen people responded yes to the request for participation in the research study. Participation in the study was based solely on the participants volunteering for the study. Individuals responding to the request for study participants received an Informed Consent form. Participants were informed that they could opt out of the study at any time. Those who agreed to the Informed Consent received the remainder of the research instruments and the code to access the survey instruments, which were facilitated online via a link directly to SurveyMonkey's secure website. Informed Consent forms will be electronically stored in the researcher's home safe according to the University of Phoenix policy for three years from the date of receipt. The demographic questionnaire and the Three-Item P-O Fit Scale were completed online at SurveyMonkey's secure website. The MSCEITTM was accessed and completed using a link on the last page in SurveyMonkey that automatically directed the participant

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to the Multi-Health Systems secure website. There were no paper and pen versions of the instruments distributed. Study participants completed the 10-question demographic questionnaire in approximately 2-3 minutes. The Three-Item P-O Fit Scale was completed in approximately 1-2 minutes. Study participants completed the 141-item MSCEITTM in approximately 30-45 minutes. The web-based surveys provided an efficient and economic central repository for data collection, organization, and analyzation. One hundred and seventeen respondents agreed to participate in the research study. Twenty-seven did not complete the Informed Consent, demographic questionnaire, or the Three-Item P-O Fit Scale. One person opted out of the study. Raw data was downloaded and stored on Microsoft Excel spreadsheets, which will be stored in a safe in the researcher's home for three years as required by the University of Phoenix. Dillman's survey process was used to distribute invitations and survey information and to follow up with those invited in an effort to increase the survey response rate (Ray & Tabor, 2003). Dillman's process involved six instances of contact with participants: (a) study introduction and announcement; (b) request for participation including information on the importance of the study to the researcher and participants; (c) reminder to non-responders, (d) final notice to nonresponders; (e) thank you to respondents; and (f) mailing of study results to those who requested them.Prior to coding and analysis, the data was reviewed for missing and incomplete data. As suggested by Neuman (2003), all resulting raw data was then coded in preparation for analyzation using statistical software. Each participant record was reviewed to ensure completion of

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each research instrument. Records for participants who did not complete all study instruments were omitted. Eighty-nine participants completed all study instruments. Two participant records had missing data on the MSCEITTM. The two records were omitted from the analysis. The final sample for which data was reported was 87. Procedures for Data Analysis Descriptive and inferential statistics were used to compute and analyze the study data. Descriptive, bivariate correlation analysis were analyzed and computed using the Statistical Package for the Social Sciences (SPSS) Version 16.0®. Results from the demographic survey were used to develop descriptive statistics, which were used to determine central tendencies (i.e., mean, median, and mode) (Creswell, 2005). Histograms were used to develop frequency tables to show the data points around each value. The raw data from the Three-Item P-O Fit Scale and the MSCEITTM was translated into scores measuring participants' levels of P-O fit and EI. Scatterplots were used to depict relationships between variables. The statistical analysis of Pearson's correlation coefficient was used to measure and relate the research variables. This degree of association indicated if the two variables were related or if changes in one variable were reflected in the other variable (Creswell, 2005). The correlational analysis also showed if a significant relationship or association exists between P-O fit and distinct branches of EI such as perceiving emotion, facilitating thought, understanding emotion, and managing emotion. Pearson's correlation coefficient between scores from the MSCEITTM instrument and the Three-Item P-O Fit Scale were computed. Four subscale scores are associated

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with the MSCEITTM instrument. Four correlation coefficients were computed. The correlation between P-O fit and each of the four subscales of the MSCEITTM were computed. A correlation coefficient of 0.1 indicated a weak relationship between these two variables; a correlation coefficient of 0.3 indicated a moderate relationship; and a coefficient of 0.5 indicated a strong relationship. Even if a weak relationship exists between the variables, the relationship could still be significant. For this reason, the significance of the relationship was determined by the p-values of the relationships. For this reason, a p-value of less than .05 indicates a significant relationship between the two variables in the study (i.e., P-O fit and EI). Summary The purpose of the quantitative correlational study was to investigate the existence of a significant relationship between P-O fit and EI. These constructs were operationalized into testable hypotheses. The study population and sampling method was discussed. The study population (N = 475) and sample (n = 89) consisted of human resource professionals from various disciplines, employment levels, and industries. Web-based surveys were distributed, collected, and analyzed. All study participants received communication regarding the study parameters including informed consent and confidentiality information. Survey tools employed to answer the study's research question were discussed in chapter 3. P-O fit was measured using the Three-Item P-O Fit Scale. EI was measured with the MSCEITTM. A justification for choosing the survey tools was provided,

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including an argument supporting the use of the intelligence-based MSCEITTM over other EI tools (Mayer et al., 2003) and the use of Cable and DeRue's (2002) Three-Item P-O Fit Scale. The rationale for using Pearson's correlation coefficient to determine the relationship between EI and P-O fit was furnished. Chapter 4 provides the research study's findings and details of the data analysis. Application of the research methods applied to the study is discussed in chapter 4. Chapter 4 presents a summary of the statistical characteristics of the study participants and addresses the research question and hypotheses as they relate to the research study's findings.

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CHAPTER 4: PRESENTATION AND DATA ANALYSIS Chapter 3 outlined the research methodology that was applied to the study. The study's population, sample, data collection, and analysis procedures were delineated. The survey instruments and their validity and reliability were discussed. The methods for ensuring participant confidentiality and informed consent were outlined. The purpose of the quantitative correlational study was to examine if a significant relationship exists between P-O fit and EI. A quantitative method was used to evaluate the relationship between variables. A correlational design was used to measure the degree of association between the variables using the statistical procedure of correlational analysis. Chapter 4 presents the research study's findings and results. Findings and results include (a) instrument scoring results for the MSCEITTM and Three-Item P-O Fit Scale, (b) descriptive statistics based on the demographic characteristics of study participants, (c) reliability analysis and the measures of central tendency for each research variable, and (d) correlational analysis. Research Instrument Results The results in this section are for the constructed variables included in the current study. The MSCEITTM variables included the overall MSCEITTM scores and the four EI branches (a) perceiving emotion, (b) facilitating thought, (c) understanding emotion, and (d) managing emotion. The P-O fit variable scores are also presented. The results include presenting the reliability analysis for each of the variables as well as the measures of central tendency for each constructed variable. Prior to the reliability analysis, the measures of central tendency for each of the individual scores are provided.

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MSCEITTM The MSCEITTM is comprised of eight tasks (A, B, C, D, E, F, G, and H). To capture the overall MSCEITTM score, the eight tasks were averaged together. A description of each task by branch can be found in Appendix K. The overall EI score had a range from .26 up to .52 and had an average value of .43 (SD = 0.5). For the MSCEITTM instrument, the raw score with the lowest average value was task D (M = .43, SD = .05), managing emotion. The raw score with the highest average value was task C (M = .56, SD = .07), understanding emotion. The reason for using the raw scores in the analysis is based on the instructions provided by the tool's authors, Mayer et al. (2002), suggesting that the raw scores be used to construct variables. There were two observations that had missing values for these scores. The two with missing data were omitted from the results of the current study. The results were based on a sample of 87 individuals. Table 14 presents the summary statistics for the MSCEITTM . Table 14 Measures of Central Tendency for MSCEITTM N Raw score A Raw score B Raw score C Raw score D Raw score E Raw score F Raw score G Raw score H 88 87 88 88 88 88 88 88 Min .09 .15 .35 .29 .03 .14 .22 .17 Max .67 .58 .67 .52 .64 .62 .61 .54 M 0.48 0.45 0.56 0.43 0.53 0.49 0.50 0.44 SD 0.17 0.10 0.07 0.05 0.12 0.11 0.08 0.07

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Three-Item P-O Fit Scale The Three-Item P-O Fit Scale is based on participants' responses to three items, which must be rated using a seven-point Likert scale (from strongly agree to strongly disagree). The three items to which participants responded were: 1. The things that I value in life are very similar to the things that my organization values. 2. My personal values match my organization's values and culture. 3. My organization's values and culture provide a good fit with the things that I value in life (Cable & DeRue, 2002, p. 879). The P-O fit score was then comprised of averaging the scores received from the three P-O fit items. Prior to constructing the scores for the overall P-O fit, a reliability analysis was conducted to determine how reliable each of the items was with one another. There was good reliability between the P-O fit items as indicated by the Cronbach's alpha score, = .90. The P-O fit scale's first item had the highest average value (M = 5.55, SD = 1.30). The second item had the lowest average value (M = 5.47, SD = 1.40). The P-O fit variable, which was calculated by using the average of the three items, was equal to 5.52 (SD = 1.20). Table 15 depicts summary statistics for P-O fit items.

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Table 15 Measures of Central Tendency for P-O Fit Items N P-O fit P-O fit 1 P-O fit 2 P-O fit 3 Min Max M SD

89 89 89

1.00 1.00 2.00

7.00 7.00 7.00

5.55 5.47 5.54

1.30 1.40 1.23

Descriptive Statistics Results from the demographic survey were used to conduct descriptive analyses, which were used to determine central tendencies (i.e., mean, standard deviation, minimum, and maximum values). Histograms were used to develop frequency tables to show the data points around each value. Statistics were computed using SPSS Version 16.0®. Sample demographics were examined by presenting frequency distributions and measures of central tendency for the gender, age, and ethnicity of each participant in the study. The frequency distribution provides the number and percentage of occurrence for each categorical variable. The measures of central tendency present the mean, standard deviation, and range of values for the continuous variables in the study. The majority of the participants in the study were female (79.8%) with male participants comprising 20.2% of the sample. As for the ethnicity of the participants, 57.3% were White, 23.6% Black/African American, 11.2% Hispanic, 3.4% Asian, and 4.5% Other. The majority of participants were aged 31-35 (26.97%) with those aged 3640 representing 17.98%.

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Participants aged 41-45 and 51-55 represented 12.36% each. Participants aged 2530 and 46-50 comprised 10.11% each. Participants aged 61 and older comprised 4.49%. Participants aged 56-60 represented 3.37% and 18-24 year-olds comprised 2.25%. The average individual in the study was a White female between the ages of 3135 years of age. Figure 2 presents a histogram of participants' age ranges. Table 16 displays the participants' gender and ethnicity.

Figure 2. Participant ages.

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Table 16 Descriptive Statistics for Gender and Ethnicity Variable Gender Female Male Ethnicity Asian Black/African American Hispanic White Other 3 21 10 51 4 3.4 23.6 11.2 57.3 4.5 71 18 79.8 20.2 Frequency (N = 89) Percent

Note. Other: White/Asian (2); White/Pacific Islander; White/Cherokee.

The most frequent education level held by the participants was a bachelor's degree (43.82%), followed by a master's degree (29.21%), and high school/GED (15.73%). For the occupational position of the participant, the most frequent response was for a non-managerial position (41.57%), followed by manager (25.84%), and director (13.48%). Table 17 depicts participant education and position level. As for the current job of the participant, HR Generalist was the most frequent response (20.22%), followed by Recruiter (11.24%). New Hire Onboarding participants represented 10.11% of the study sample. Participants in their current position between 1

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and 3 years totaled 44.45% of the study's participants. Participants with 10 to 12 years experience in HR comprised 31.46% of the study's participants. Table 17 Descriptive Statistics for Education and Position Level Variable Education High School/GED Associate's Bachelor's Master's Doctorate Other Occupational position Non-managerial Front-Line supervisor Manager Associate/Assistant director Director Senior director Vice president Executive director

Note. Other = Business trade school.

Frequency (N = 89)

Percent (%)

14 5 39 26 4 1

15.7 5.6 43.8 29.2 4.5 1.1

37 4 23 6 12 2 4 1

41.6 4.5 25.8 6.7 13.5 2.2 4.5 1.1

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Participants in non-managerial positions represented 41.57% of the study's participants. Financial services (41.6%) were the most frequent types of organizations in which participants worked followed by healthcare (30.34%). Organizational characteristics are displayed in Appendix L. Results and Findings The purpose of the quantitative correlational study was to examine the existence of a statistically significant relationship between P-O fit and EI. The study's results and findings are presented by statistical procedure and by hypothesis. The following research question guided the study. Research Question and Hypotheses What is the relationship between person-organization fit and emotional intelligence? Hypotheses H10 and H1A H10: A significant relationship does not exist between P-O fit and EI. H1A: A significant relationship exists between P-O fit and EI. Pearson's Correlation Coefficient The data collected from each participant were analyzed using Pearson's correlation coefficient. All statistics were computed and analyzed using SPSS Version 16.0®. Pearson's correlation coefficients between scores from the MSCEITTM instrument and the Three-Item P-O Fit Scale were computed. The statistical procedure of Pearson's correlation coefficient detected a positive correlation between the P-O fit scores and the overall MSCEITTM scores of the participants, r = .18, p = .10. The correlation was not significant at the .05 level of

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significance since the p-value was greater than .05. The null hypothesis was not rejected. The variation of less than 4% is of note. Table 18 presents a summary of the correlation. The final sample size was n = 87. The scatterplot matrix in Figure 3 depicts the relationship between the variables. Table 18 Correlation Results for MSCEITTM and P-O Fit Variables Overall EIa Overall EI P-O fit

a

P-O Fita

1 .176 1

n = 87.

Note. ** p < .01 and * p < .05.

Figure 3. Scatterplot matrix of relationship between P-O fit and EI.

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MSCEIT TM and P-O Fit Score Results for Continuous Variables by Characteristic The study sample's demographics were analyzed by characteristic. The sample's results by variable, as they relate to P-O fit and EI scores, could be important when comparing the current study's results to previous research. A discussion regarding the current study's results and previous research is presented in chapter 5. Organizational characteristics. Participants working in technology organizations had the highest average value for the overall MSCEITTM (EI) score (M = .62, SD < .01). Participants working in educational organizations had the highest average value for the PO Fit variable (M = 6.22, SD = .66). Results for organizational characteristics by continuous variable are shown in Appendix M. Job position. The job position that had the highest average value for the overall MSCEITTM score (EI) was Employee Relations (M = .46, SD = .02) and HRIS (M = .46, SD = .04). The job position that had the highest average value for the PO-Fit variable was the compliance position (M = 6.50, SD = .71). The results by job description are presented in Appendix N. Time in HR position. The length of time in the HR position that had the highest average values for the overall MSCEITTM score (EI) was less than 1 year (M = .45, SD = .05); 13 to 15 years (M = .45, SD = .05); and 16 to 18 years (M = .45, SD = .06). The length of time in HR position that had the highest average value for the P-O fit variable was 13 to 15 years (M = 6.22, SD = .66). The length of time in HR position results are depicted in Appendix O. Time in current position. The length of time in the current position that had the highest average value for the overall MSCEITTM score (EI) was 7 to 9 years (M = .45, SD

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= .06). For 13 to 15 years, 16 to 18 years, and 19 or more years, there was one observation so they will not be included in those with the highest average values. The length of time in current position that had the highest average value for the P-O fit variable was 10 to 12 years (M = 5.85, SD = .83). The results for time in current position are presented in Appendix P. Ethnicity. The ethnicities with the highest average value for the overall MSCEITTM score (EI) was Asians (M = .44, SD = .02) and Whites (M = .44, SD = .04). Asians had the highest average value for the P-O fit variable (M = 6.33, SD = .58). Table 19 presents the results by ethnicity. Table 19 Ethnicity by Continuous Variables

Ethnicity

Asian (N = 3) M SD 0.02 0.58

AA/Black (N = 21) M 0.40 5.17 SD 0.08 1.43

Hispanic (N = 10) M 0.42 4.80 SD 0.04 1.38

White (N = 51) M 0.44 5.71 SD 0.04 1.04

MSCEITTM P-O fit

0.44 6.33

Gender. Females and males had the same average value for the overall MSCEITTM score (EI) with females (M = .43, SD = .06) and males (M = .43, SD = .04). Males had the highest average value for the P-O fit variable (M = 5.73, SD = .89). Table 20 presents the results for gender.

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Table 20 Gender by Continuous Variables

Gender

Female (N = 71) M SD 0.06 1.27

Male (N = 18) M 0.43 5.73 SD 0.04 0.89

MSCEITTM P-O fit

0.43 5.47

Age. The age group with the highest average value for the overall MSCEITTM score (EI) was 18 to 24 years (M = .48, SD = .05). The age group that had the highest average value for the P-O fit variable was 41 to 45 years (M = 6.03, SD = .67). Results for age groups are shown in Appendix Q. Education. The education level that had the highest average value for the overall MSCEITTM score (EI) was those with a doctorate (M = .46, SD = .04) and high school/GED education (M = .46, SD = .01). High school/GED had the highest average value for the P-O fit variable (M = 6.50, SD = .71). Results for education are presented in Appendix R. Organizational position. Positions with the highest average value for the overall MSCEITTM score (EI) was director (M = .45, SD = .03) and senior directors, vice presidents, and the executive director (M = .45, SD = .05). Directors had the highest average value for the P-O fit variable (M = 5.94, SD = .96). Results for organizational position by continuous variable are presented in Appendix S.

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Summary The purpose of the research study was to examine the existence of a statistically significant relationship between P-O fit and EI. Chapter 4 presented the data collected from the demographic questionnaire and the research instruments. The methodology discussed in chapter 3 was applied to the data. A quantitative research method with a correlational design was used to conduct the study. Quantitative instruments used to collect participant data included the MSCEITTM (Mayer et al., 2002) and the Three-Item P-O Fit scale (Cable & DeRue, 2002). The research instruments were administered using secure websites. Study participants received the links to the websites after agreeing to the Informed Consent form. Eightynine individuals participated in the study. Pearson's correlation coefficient was employed to conduct the statistical analysis. The statistical procedure of Pearson's correlation coefficient detected a correlation between P-O fit and EI; the relationship was not statistically significant. The null hypothesis was not rejected. Conclusion Chapter 4 presented the findings and results of the quantitative correlational research study. The application of the study's research methodology and design were applied to the data collected from the study participants and presented in chapter 4. Chapter 5 provides a discussion of the study's findings. Presented in chapter 5 is a discussion of the study's results, relationship of the study's findings to previous research, implications for leaders, possible research design errors, and suggestions for future research.

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CHAPTER 5: CONCLUSIONS, IMPLICATIONS, AND RECOMMENDATIONS The purpose of the study was to examine the existence of a statistically significant relationship between P-O fit and EI. The observation of a general problem related to the assumption of a significant relationship between P-O fit and EI provided the impetus for the research study. The assumption of a relationship between EI and P-O fit contains the further assumption that leaders and employees who do not exhibit high EI skills could bring poor performance, organizational incompatibility, and job turnover to a workplace, which in turn could reduce organizational effectiveness (Carmeli & Josman, 2006; Cherniss & Goleman, 2001). The specific problem is that leaders are using the assumption of a significant relationship between EI and P-O fit as a basis for making critical organizational decisions that affect hiring, retention, and organizational effectiveness (Billsberry et al., 2005; Book, 2008; Bradberry & Greaves, 2005; Frase, 2007; Hunt, 2007; Kouzes, 2008; Roberson et al., 2005; D. Smith, 2006; Williams, 2007). A quantitative study method with a correlational research design was used to determine the existence of a significant relationship between EI and P-O fit. Pearson's correlation coefficient was used to determine the significance of a relationship presented in the hypotheses. The population was accessed through the Southwest region of SHRM in the United States. The sample included a diverse group of human resource professionals from a myriad of disciplines. Eighty-nine respondents participated in the research study. The study presents research that resulted in empirical data and knowledge regarding the correlation between P-O fit and EI. The results provided empirical data regarding the existence of a relationship between P-O fit and EI.

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Chapter 4 provided a detailed review of the study's findings, including the application of the research method and study design. Chapter 5 provides conclusions, implications, and recommendations. Chapter 5 is organized into four sections (a) conclusions, (b) relationship of current study to previous research, (c) implications, and (d) future recommendations. The intent of chapter 5 is to discuss and interpret the study's results as presented in chapter 4 and provide implications for leaders seeking information about frameworks and methodology to affect organizational change. Conclusions Pearson's Correlation Coefficient Pearson's correlation coefficient was used to determine the existence of a statistically significant relationship between the overall scores of the MSCEITTM (EI) and the Three-Item P-O Fit score. Null hypothesis H10 was not rejected. While a positive correlation was detected between the P-O fit scores and the overall MSCEITTM scores of the participants, the correlation was not significant. The variation of less than 4% is of note. The finding suggests that while not statistically significant, value exists in the positive correlation. Non-Significant Positive Correlation between P-O Fit and EI The study found that while a positive correlation exists between P-O fit and EI, the relationship is not statistically significant. This finding is in direct contrast to the assumption by researchers and leaders that individuals with high EI skills may be better able to discern and attain P-O fit (Billsberry et al., 2005; Book, 2008; Kouzes, 2008; Landen, 2002; Resick et al., 2007; Williams, 2007). Schoo (2008) wrote that those with developed EI skills are aware of their needs and the needs of others, which enables them

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to make better choices about organizational relationships and their congruence with the organization. The study's result of a statistically nonsignificant relationship between P-O fit and EI are in direct opposition with these researchers and leaders. Carmeli and Josman (2006) and Kunnant (2004) proposed that EI might improve workplace congruence. The author's proposal could be in line with the positive correlation found between EI and P-O fit in that no attempt was made to suggest that a model of EI and P-O fit is the answer to workplace congruence. The authors are cautious in that they suggest the use of the constructs as tools to enhance organizational effectiveness. While a positive correlation exists between P-O fit and EI, the relationship is not statistically significant. The study does not seek to negate the benefits of the constructs as individual contributors to organizational effectiveness. The study's goal was to create awareness that while both constructs are important to organizational success as individual constructs, caution should be exercised when combining the constructs into one model to assess and determine organizational fit. Relationship of the Current Study to Previous Research During the course of the current study, no research was found that examined a relationship between P-O fit and EI. The focus of this section will be on the positive correlation found between P-O fit and EI even though the relationship was not statistically significant. The assumption by researchers and leaders of a significant relationship between P-O fit and EI is not totally without merit. The study's results suggest that leaders should exercise caution if combining the constructs in a model and

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using the model as methodology for such critical decision-making as hiring, succession planning, promotion, and retention. While the relationship between P-O fit and EI is not statistically significant, the positive correlation is worth noting. The positive correlation confirms previous research regarding the benefit of increasing one's EI skills to affect organizational effectiveness (Fiedeldey-van Dijk & Freeman, 2007; Goleman, 2001; Iordanoglou, 2007; Laff, 2008; Seal, Boyatzis, & Bailey, 2006). Of note is the total explained variance of less than 4%, which suggests that EI skills of employees and leaders explain only a small amount of the variance in the P-O fit construct. The total explained variance also suggests that other

variables may be better predictors of P-O fit than EI.

As with EI, the literature was abundant in studies reporting the benefits of attaining P-O fit including job satisfaction (Autry & Daugherty, 2003; Ravlin & Ritchie, 2006). Individuals seeking job satisfaction and intent to stay with an organization could benefit from seeking organizations with values congruence (DelCampo, 2006; Westerman & Cyr, 2004). While the results of the current study did not find a statistically significant relationship between the constructs, the correlation may provide justification to conduct further research, especially since the total explained variance was less than 4%. The section of this document on suggestions for further research provides ideas for refinements. In chapter 2, literature was reviewed where authors suggested that leaders and employees with high EI skills are better able to make decisions regarding their ability to fit within an organization's culture (Billsberry et al., 2005; Kouzes, 2008; Resick et al., 2007). Researchers posit that leaders and employees with high EI skills are better able to

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contribute to the organization's strategies, goals, and overall success (Bradberry & Greaves, 2005; Carmeli, 2003; Landen, 2002; Ravlin & Ritchie, 2006). Goleman (2001), Hunt (2007) Landen (2002), and Spors (2007) proposed that many organizations are measuring prospective and employee's ability to fit within an organization by the level of his or her EI. While both constructs individually have been found to increase organizational effectiveness, the positive correlation found in the current study is not statistically significant. When making decisions about constructs to be used to affect organizational effectiveness, the study's results suggest that EI and P-O fit should be analyzed as distinct concepts that could be used in concert with other organizational effectiveness concepts and strategies. Landen (2002) suggested that EI could have a positive effect on an individual's values congruence. Landen's assumption of a relationship between EI and P-O fit could possibly align with the study's finding of a correlation between EI and P-O fit. Landen suggests that there could be a positive effect, which is in alignment with the positive correlation found in the current study between EI and P-O fit. Iordanoglou's (2007) position on the EI and P-O fit concepts are in line with the study's findings of a positive correlation between the constructs but not at a statistically significant level. Iordanoglou suggested that both constructs were components of organizational social systems necessary for success. The author did not make cause and effect assumptions about the constructs but wrote that the presence of both constructs could improve organizational effectiveness.

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The current study's results provide critical information to leaders who are using EI skills to assess P-O fit, especially if job or income loss is a byproduct of the process. The current study's finding regarding the lack of a statistically significant relationship between EI and P-O fit suggests that further research should be conducted to substantiate the findings. Further research could also provide further evidence regarding suggestions offered by other researchers. Carmeli and Josman (2006) and Cherniss and Goleman (2001) suggested that the lack of EI skills could lead to poor P-O fit resulting in poor performance, organizational incompatibility, and job turnover. The current study's results suggest that while EI and PO fit are positively correlated, the relationship is statistically insignificant. Findings in the current study showed several groups with high P-O fit scores but low EI scores (see Appendixes M-S). A limitation of the current study was that the scope did not include performance information. Further research that expands upon the current study's methodology could provide additional value to the body of knowledge and to leaders. During the course of this study, no literature was reviewed that confirmed assumptions of a significant relationship between EI and P-O ft. While the current research study's results do not support the theory of a statistically significant relationship between P-O fit and EI, a small positive correlation was detected. Based on the current study's results, leaders who are suggesting that high EI skills equal P-O fit (Billsberry et al., 2005; Book, 2008; Frase, 2007; Goleman, 2001; Kouzes, 2008) should exercise caution when suggesting that EI is a determinant of P-O fit. The study supports suggestions made by authors of a positive correlation between the variables (Iordanoglou, 2007; Landen, 2002).

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Significance of the Current Study Leaders are searching for methods and frameworks with which to improve organizational effectiveness. An example of the search lies in the assumptions leaders make about the significant relationship between P-O fit and EI (Billsberry et al., 2005; Book, 2008; Frase, 2007; Goleman, 2001; Kouzes, 2008). The study's results did not detect a significant relationship between the constructs. The study's findings provide empirical evidence that a framework built upon EI skills as a determinant of P-O fit may not be the best strategy to attain organizational effectiveness. The positive correlation found between the constructs in the current study suggests that the use of the constructs individually may provide organizational value. The current study was of social concern due to the increasing practice by leaders of using EI skills to determine and assume P-O fit. The study's results provide empirical data regarding the limitations of this assumption that should cause leaders to examine their assumption regarding EI skill as a determinant of P-O fit. The role of leaders is to provide a clear vision to improve organizational success. Because the current study was conducted at the individual level versus the organization level, leaders are provided with insight into the perceptions of fit from the employee perspective. While the individual level of assessment may seem inadequate, researchers point to the fact that perceptions are reality; perceptions tend to drive a person's appraisal of his or her environment and measures of perceived fit may be stronger than actual fit measures conducted at the organizational level (Kristof, 2000; Kristof-Brown et al., 2005; Ostrof et al., 2005; Piasentin & Chapman; Ravlin & Ritchie, 2006). The ability to understand the thoughts of employees adds value in that leaders can design and

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implement strategy and visions that directly affects employee perceptions of the organization. The current study provides such clarity in that leaders now have empirical data that can be used to affect organizational strategies in hiring, training, and development of employees and leaders. During the literature search and review, no studies were found that examined the relationship between P-O fit and EI. The goal of the current study was to provide valuable empirical knowledge and evidence that could possibly result in a framework and methodology for recruiting, training, and retaining leaders and employees in an effort to improve organizational effectiveness. The current study is of theoretical significance because the results provide valuable empirical data to the existing body of knowledge concerning P-O fit and EI. While the results did not result in a model of P-O fit and EI, the findings were important because of the assumptions being made by today's leaders of a significant relationship between P-O fit and EI (Billsberry et al., 2005; Book, 2008; Frase, 2007; Goleman, 2001; Kouzes, 2008). Even though there was a positive correlation found between the constructs, the relationship was not statistically significant. The current study provides substantial evidence to the leadership body of knowledge. The study's findings provide valuable information to the existing body of knowledge and are applicable to leaders searching for ways to explain, predict, and improve organizational performance using P-O fit and EI models. Study Limitations and Delimitations The study was limited due to the use of one industry and one professional organization, which could affect the potential constriction of range on study variables.

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The study was further limited by the voluntary participation of SHRM members and participants yielding from the snowball sampling technique used to obtain study participants. The population provided an adequate sample according to the power analysis suggestion of a minimum of 67 participants. To decrease the likelihood of Type I error, the sample was increased to a minimum of 75. Eighty-nine individuals participated in the study. Another limitation was the assumed honesty and self-awareness of participants answering survey questions. The study did not pre-assess individual awareness levels for a before and after comparison regarding self-awareness. The study also did not attempt to gather and compare honesty perceptions of the individuals. The ability to determine honesty and self-awareness were beyond the scope of the current study. A further limitation of the study was the use of individual level and self-report tools to measure EI and P-O fit, which will not address EI and P-O fit at the organizational level. The study focused on individual perceptions and abilities so the use of individual self-report tools was appropriate for the current study. The scope of the study was to assess participants at the individual level, so the use of self-report tools was necessary. Future studies at the organizational level could build upon the current study. Tools that measure EI and P-O fit using 360° measurement tools could provide valuable information to leaders. Gap analyses resulting from the measurements could be used to develop education and training that could improve organizational effectiveness. Delimitations define a study's boundaries and could exert an impact on generalizability (Bryant, 2004). The study's sample included only human resource

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professionals, which could affect its generalizability to other professions and may have negatively affected the total explained variance between the study variables. To enhance generalizability, the study sample included a variety of disciplines within human resources. For example, information systems professionals manage the information and computer systems within a human resources department. Information systems professionals can also be found in a myriad of organizational units and departments other than human resources. The sample included individuals working in benefits, compensation, training, employee relations, onboarding, document management, organizational development, information systems, quality and risk management, and operations. A myriad of organizational types were represented in the sample including healthcare, financial services, education, technology, legal, telecommunications, social services, hospitality and tourism, aerospace, and space and shuttle. The majority of the participants in the study were female (79.8%) with male participants comprising 20.2% of the sample. The higher proportion of women versus men was expected. In a report issued by the U.S. Census Bureau, Fronczek and Johnson (2003) reported that a higher number of women work in office occupations. This fact provides justification for the current study's ability to generalize the study's results to males and females in the United States. As for the ethnicity of the participants, over half were White (57.3%), followed by Black/African Americans (23.6%). The frequency distribution of the top two ethnicities participating in the study is in line with the distribution of ethnicity in the U.S. workforce,

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with the majority of workers reporting White, followed by Black/African Americans (Fronczek & Johnson, 2003). Hispanic participants were the next highest with 11.2%. Participant ages ranged between 23 to 71 years of age with ages 31-40 representing the majority of the study's participants. Based on data published in the U.S. Census Bureau's American Community Survey (2006), the majority of workers in the U.S. are between the ages of 25-44 years. Based on this information, the study's results should be generalizable to the majority of the U.S. working population. In a U.S. Census report (2006), the data showed that 87% of employed Americans have attained at least a high school/GED or higher education. The most frequent education level attained by participants was a bachelor's degree (43.82%), followed by a master's degree (29.21%). Those with high school/GED represented 15.73% of study participants. This fact supports generalizability of the current study to employed individuals in the U.S. population whom have attained at least a high school/GED. Overall, the diversity in industries in the study represented 76.2% of U.S. industries (Fronczek & Johnson, 2003). The diversity and number of industries represented should increase the study's generalizability. The intent of the study was to include a diverse study population and sample. The study sample's diversity in ethnicity, gender, age, industries, occupations, and education enhanced the study's generalizability. When determining the population and sample, there was some trepidation that the population would be acutely familiar with the study constructs and results would be flawed by study participants with high P-O fit and EI correlations. Study results proved the contrary.

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The choice to diversify the population with participants from a myriad of work roles and levels of employment within human resources enhanced the study's generalizability. Modest differences in MSCEITTM scores exist between the ethnic groups (Mayer et al., 2002). Normative data for the MSCEITTM were collected from more than 50 geographically and ethically diverse locations from the United and several countries. The results reflected modest differences between ethnic groups. The difference between the current study and the normative study was that in the normative study Whites scored highest in overall EI scores followed by Hispanics, Blacks/African American, and Asians, respectively. In the current study, Asians and Whites scored highest followed by Hispanics and Blacks/African Americans, respectively. According to Mayer et al. (2002), variations in overall EI scores between ethnicities may vary, including branch scores. Caruso and Salovey (2004) suggest that differences in scores across ethnicities could be due to the acclimation of societal norms in the geographical location. Possible Research Design Errors The design and implementation of a research study can be improved. Choices in methodology, frameworks, population, and instrumentation are areas in which one can examine for future improvement. The next section presents possible design errors. Analysis of P-O Fit and EI Branches The study included analysis of the four subscales of EI. While there was some value in the resulting information, significant value was not added to the overall study's results. The overall study focused on the relationship between P-O fit and EI, not the subscales. The omission of the subscale may provide clearer, more focused results.

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Study Population The study's population was accessed through SHRM, the world's largest human resource management organization. A diverse sample provided the ability to generalize the study's results to the general population. An improvement to the study would be to seek a diverse group of individuals from a variety of professions. Quantitative Instrumentation The MSCEITTM was chosen for the current study based on the study's theoretical framework (Mayer & Salovey, 2004) and the tool's reliability and validity. The MSCEITTM is an abilities-based, self-report tool. A 360° measurement tool may increase objectivity (Grewal & Salovey, 2005). EI measurements characterized as 360° tests differ from self-report tests in that other people are involved in assessing an individual. Researchers solicit answers regarding the individual's EI skills from peers, friends, supervisors, and so forth in order to assess EI. Implications and Recommendations for Leaders Many leaders are operating under the assumption of a significant relationship between P-O fit and EI (Billsberry et al., 2005; Book, 2008; Kouzes, 2008; Landen, 2002; Resick et al., 2007; Schoo, 2008; Williams, 2007). While the study found a positive correlation between the constructs, the study's results did not detect a statistically significant relationship between the constructs. The study's results do not negate the importance of the constructs as individual contributors to organizational effectiveness. Rather, the positive correlation confirms the choice by leaders to use the constructs in strategies that could improve organizational effectiveness.

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Even though a significant relationship was not found to exist between P-O fit and EI, overall MSCEITTM results of particular study participants were of interest. Study participants with the highest overall MSCEITTM scores included (a) individuals working in Employee Relations and HRIS; (b) participants with less than one year of experience in human resources; (c) participants with doctorate degrees and high school/GED; (d) participants 18-24 years of age; and (e) directors, senior directors, vice-presidents, and executive directors. The high overall MSCEITTM for participants working in Employee Relations was expected. The high overall MSCEITTM scores for HRIS workers were unexpected. An expectation prior to the data analyses was that Recruiters would be among the highest MSCEITTM scorers, especially since this group uses EI skills to assess candidates. Williams (2007) posited that as employees move up the corporate ladder, their EI skills tend to increase. Results from the current study provided evidence regarding Williams' assumption in regard to organizational position. Directors, senior directors, vice presidents, and executive directors were found to have the highest average value for the overall MSCEITTM score. While the current study's focus was to determine if a statistically significant relationship exists between P-O fit and EI, future researchers could expand upon the study by focusing on if statistically significant differences exist within the study sample that relate to age, work experience, and other factors. The assumption made by Williams (2007) warrants further discussion because study participants with doctoral degrees, high school/GED education, participants aged 18-24, and participants with less than one year in HR were among the highest overall MSCEITTM scores. These results suggest that high EI skills are not contingent upon

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movement up the corporate ladder, but can be found within all levels of employment, education, and employment tenure, especially since emotional competencies are now taught in many grade schools (Goleman, 1995). The study's results are congruent with the results of previous researchers in that EI is a nebulous and elusive construct (Dulewicz & Higgs, 2000; Locke, 2005; Matthews et al., 2004a, 2004b; Murphy & Siderman, 2006) and leaders should ensure that assumptions about EI skills are not being made based on individual characteristics such as age, education, employment level, occupation, and tenure. Future studies focusing on the study population's characteristics could build upon the current study and add value to the body of knowledge. Today, leaders are basing critical organizational decisions such as hiring, development, retention, and succession on assumptions of a statistically significant relationship between EI and P-O fit. The study's results provide empirical data that should caution leaders against combining the constructs into one model to assess performance potential. This finding provides further evidence and strengthens the recommendation that leaders should exercise caution when using EI as a determinant of P-O fit. Another recommendation based on the study's findings is that leaders should examine intervening variables that may affect the positive correlation between P-O fit and EI. For example, leaders may consider the impact that intervening factors such as choice and motivation theories may have on EI. In choice theory, "frustration is the discrepancy between what is wanted and that what is perceived to be received. The perceived imbalance motivates people to get what they want or to leave" (Schoo, 2008, p. 40). Choice theory includes the consideration of values congruence and

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EI (Schoo). A relationship between choice theory and EI may have a role in assessing PO fit. Motivation theories such as need-satisfaction models of motivation may also affect EI and P-O fit. The needs that employees and leaders bring to the workplace could affect their choices and desires to engage, perform, and stay with an organization (Kersten, 2008). Intervening factors that could affect P-O fit include the need for (a) perspective, (b) self-control, (c) self-determination, (d) strategies to deal with difficult people (Kersten). Suggestions for Future Research The current study did not find a statistically significant relationship between P-O fit and EI. A positive correlation was detected between the constructs. Improvements to the current study could yield different results. Suggestions for future research include (a) the use of alternative EI frameworks; (b) expanding the study's research methodology, study population, and geographic region; and (c) exploring the use of alternative measurement methods. EI Model The theoretical framework that guided the current study was the Mayer and Salovey (2004) mental abilities model, expanded by Caruso et al. (2004). EI models are categorized as either mental-ability or mixed models. A suggestion for future research is to conduct a study using a mixed model. Mental-ability models examine the interaction between emotions and thought. Mixed models, though based on ability models of EI, examine cognitive mental abilities as well as noncognitive personality traits such as motivation (Caruso et al., 2004).

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Research Methodology In the current study, a quantitative research method with a correlational design was used to examine the relationship between P-O fit and EI. A suggestion for future research is to explore the use of a mixed method to add qualitative data to the design. The current study provided quantitative data that resulted in answering the research question. A mixed method could improve the study by adding depth to the quantitative data (Creswell, 2005). For example, the current study did not detect a statistically significant relationship between P-O fit an EI. Qualitative data could add depth to the study by providing contributing factors that could affect the study's results. Study Population and Geographic Region The current study's population included human resource professionals from a variety of disciplines, employment levels, and industries. The study's generalization was increased by the variety of organizations represented by professionals participating in the study. Suggestions for future research include expanding the population beyond human resource professionals and increasing the sample size to improve generalizability. The explained variance between the correlations of EI and P-O fit was less than 4%. The study was conducted using human resource professionals from the Southwest region of SHRM in the United States. Suggestions for future research include expanding the geographical regions throughout the U.S. Expanding the geographical boundaries globally could also add value to future studies by increasing the study's generalizability. Alternative Measurements and Instrumentation Self-report tools versus organizational level tools. A limitation of the study was the use of individual and self-report tools to measure EI and P-O fit, which did not

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address EI and P-O fit at the organizational level. The study focused on individual perceptions and abilities, so the use of individual self-report tools was appropriate for the current study. The scope of the study was to assess participants at the individual level, so the use of self-report tools was appropriate. A suggestion for future research is to expand the scope of the study to the organizational level and use organizational level instruments such as 360° assessments. P-O fit measurement. The current study used Cable and DeRue's (2002) ThreeItem P-O Fit Scale that measured perceived fit at the individual level. A recommendation is to conduct a study using commensurate measurements, which measures actual fit at the organizational level. In contrast to perceived fit measures, actual fit measures assess specific characteristics of the individual and organization (Carless, 2005; Cooper-Thomas et al, 2004; Kristof, 1996). Choice and Motivation Theories The results from the current study suggest that other variables may be better predictors of P-O fit than is EI. Leaders should consider the impact that choice and motivation theories may have on EI and P-O fit. Employees and leaders could be emotionally intelligent but make choices that fulfill primary needs affecting their lives at that time. Conclusion Today's work environment has become increasingly complex and turbulent. To affect organizational success, leaders are searching for frameworks and methodologies that can enhance critical decision-making. The assumption of a significant relationship between P-O fit and EI is being used today as a basis for critical decision making in

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organizations (Billsberry et al., 2005; Book, 2008; Bradberry & Greaves, 2005; Frase, 2007; Kouzes, 2008). The current study examined the existence of a relationship between P-O fit and EI. The current study added to the existing body of leadership knowledge regarding the existence of a relationship between P-O fit and EI. While a positive correlation was found to exist between P-O fit and EI, the relationship was not statistically significant. The study fills a gap in the knowledge since no literature was found or reviewed during the study that examined the existence of a significant relationship between the constructs. The study provides new literature to the body of knowledge regarding the relationship. Leaders seeking to enhance organizational effectiveness could benefit from the study's new knowledge. Based on the current study's results, leaders should exercise caution when using EI skill level as a determinant of P-O fit. While both constructs are beneficial as individual constructs, no significant relationship was found to exist between P-O fit and EI.

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APPENDIX A: COMPONENTS OF POPULAR EI THEORIES

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COMPONENTS OF POPULAR EI THEORIES

Theory Bar-On's Mixed Model

Description EQ represents a set of social and emotional abilities that help people cope with daily life (Cherniss & Goleman, 2001).

Salovey & Mayer's Ability-Based

EQ represents the way in which a person processes information about emotion and emotional responses. Ability models place emotional intelligence within the sphere of an intelligence; emotion and thought are understood to interact in meaningful and adaptive ways (Mayer & Salovey, 2004; Mayer, Salovey, & Caruso, 2002; Salovey & Mayer, 1990).

Goleman's Mixed Model: PerformanceBased

EQ represents different ways in which competencies such as empathy, learned optimism, and self-control contribute to important outcomes in one's life (Cherniss & Goleman, 2001; Mayer & Salovey, 2004).

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APPENDIX B: APPROVAL TO USE THE MSCEITTM

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APPENDIX C: THE MSCEITTM

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THE MSCEITTM The MSCEITTM is the first abilities-based measure of emotional intelligence. The MSCEITTM is a 141-item measurement tool designed to assess emotional intelligence using an abilities-based scale. The scale measures how well people solve emotional problems and perform tasks rather than asking for their subjective assessment of their emotional skills and abilities (Mayer et al., 2003). The scale yields an overall emotional intelligence score, two area scores (i.e., Emotional Experience and Emotional Reasoning), and scores for each of the four emotional intelligence branches: Perceiving Emotions, Facilitating Thought, Understanding Emotions, and Managing Emotions. The MSCEITTM is the first measurement to report valid scores in all four areas of emotional intelligence (Mayer et al.) The MSCEITTM is a performance-based measurement for people 17 years of age or older. The measurement can be administered by paper and pencil and/or online. All responses are computer-scored by Multi-Health Systems, Inc. (MHS). Data sets are available for researchers interested in analyzing the data for research studies. MHS provides two types of reports for participant results (a) Personal Summary Reports and (b) Resource Reports. Personal Summary Reports are used to evaluate a person's emotional intelligence. These reports are used by the researcher when evaluating the client. Personal Summary Reports are not to be shared with study participants. Resource Reports are detailed reports summarizing the participant's emotional intelligence. Resource Reports are written at an easy-to understand reading level and can be shared with the respondent. Both tools used together provide valuable information to

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researchers (Mayer et al., 2002). The publisher does not permit reproduction of the MSCEITTM. Copies of the tool can be obtained by contacting MHS.

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APPENDIX D: APPROVAL TO USE THE THREE-ITEM P-O FIT SCALE

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APPROVAL TO USE THE THREE-ITEM P-O FIT SCALE >>> "Cable, Daniel M > 12/18/2007 1:22 AM >>> Yes, please do use the scale.

Daniel M. Cable, Ph.D. Townsend Distinguished Professor of Management Kenan-Flagler Business School University of North Carolina at Chapel Hill Campus Box 3490, McColl Building Chapel Hill, NC 27599-3490 xxx-xxx-xxxx xxx-xxx-xxxx (fax)

From: Cheryl Bates Sent: Monday, December 17, 2007 5:13 PM To: Cable, Daniel M. Subject: Permission to Use the 3-Item Fit Scale Dear Dr. Cable, I am a Doctoral Student in Management (Organizational Leadership) at the University of Phoenix. I am writing to ask permission to use in my dissertation the 3-Item Fit Scale used in your 2002 publication The Convergent and Discriminant Validity of Subjective Fit Perceptions. I plan to present the scale to 100 participants in my study. I would greatly appreciate your permission to use the tool in my research. If you have any questions, please feel free to contact me at any time. If approved, could you please include your contact information at the bottom of the email? Thanks so much!

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APPENDIX E: THREE-ITEM PERSON-ORGANIZATION FIT SCALE

154 THREE-ITEM PERSON-ORGANIZATION FIT SCALE

Dear Study Participant: Thank you for your participation in this dissertation research study. Please complete the following survey by marking the box that corresponds to your level of agreement with each statement.

Participant ID # ___________

Three-Item Person-Organization Fit Scale 1. The things that I value in life are very similar to the things that my organization values.

Strongly Disagree Disagree Slightly Disagree Neither Agree nor Disagree Slightly Agree Strongly Agree

2. My personal values match my organization's values and culture.

Strongly Disagree Disagree Slightly Disagree Neither Agree nor Disagree Slightly Agree Strongly Agree

3. My organization's values and culture provide a good fit with the things that I value in life.

Strongly Disagree Disagree Slightly Disagree Neither Agree nor Disagree Slightly Agree Strongly Agree

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APPENDIX F: PERMISSION TO USE THE SOCIETY OF HUMAN RESOURCE MANAGEMENT MEMBERS AS STUDY PARTICIPANTS

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APPENDIX G: LETTER OF INTRODUCTION AND INVITATION TO STUDY

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LETTER OF INTRODUCTION AND INVITATION TO STUDY Dear Potential Study Participant, I am a doctoral student at the University of Phoenix working on a dissertation research project as part of my degree requirements. You are being asked to participate in an anonymous study that will explore the relationship between emotional intelligence and person-organization fit. I am hopeful that the results of the current study will provide today's leaders with a framework for recruiting, training, and retaining leaders and employees in an effort to improve organizational effectiveness. To be eligible to participate in the study, you must be at least 18 years of age and employed full-time as a human resources professional. If you would like to participate in the research study, you will be asked to complete a demographic questionnaire and two survey instruments, the Mayer-SaloveyCaruso Emotional Intelligence Test (MSCEITTM), and the Three-Item P-O Fit Scale. You will also be asked to sign an Informed Consent form. All components should take no more than one hour of your time. Your responses will be kept confidential and all results will be reported cumulatively with no individual results. If you would like to participate, please click on this link (link to be inserted here). You will be directed to the Informed Consent form. If you do not wish to participate, please click on this opt-out link (opt-out link to be inserted here). If you have any questions, please send an email or call me at (xxx) xxx-xxxx. Thank you in advance for your participation.

Sincerely,

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Cheryl R. Bates Doctoral Student/Researcher University of Phoenix

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APPENDIX H: INFORMED CONSENT: PARTICIPANTS 18 YEARS OF AGE AND OLDER

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UNIVERSITY OF PHOENIX INFORMED CONSENT: PARTICIPANTS 18 YEARS OF AGE AND OLDER (WEB-BASED) Dear Study Participant, Thank you for agreeing to participate in this research study. The purpose of the research study is to determine whether a relationship exists between person-organization fit and emotional intelligence. Your participation in the study will involve completing a demographic questionnaire, a three-question scale on person-organization fit, and an emotional intelligence test. It should take approximately thirty to forty-five minutes to complete all components. Your participation in the study is purely voluntary. If you choose not to participate, or if at any time during the study you want to withdraw, you can do so without any penalty or loss of benefit to yourself. The results of the research study may be published, but to assure anonymity, your name nor your organization's name will be used and your results will be maintained in confidence. Any published information will not be traceable to you nor your organization. There are no foreseeable risks to you for participating in this study. In addition, there is no compensation or specific benefits from your participation. Although there may be no direct benefit to you, the benefit of your participation could have potential benefit to the field of leadership. If you have any questions about the research study, please feel free to contact me at any time. Please review the Informed Consent below and respond by selecting one of the participation choices. If you agree to the Informed Consent, the survey will be emailed to you.

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Informed Consent (Web-Based) I acknowledge that I understand the nature of the study, and any potential risks to me as a participant, and the means by which my identity will be kept confidential. Clicking on the first box below indicates that I am over the age of 18 and that I give my permission to voluntarily serve as a participant in the study. Please check one of the boxes below. I understand the above statements and give consent for my information to be used in the study. I understand the above statements and do NOT give consent for my information to be used in the study. Insert Your Name Here: ____________________________________

Cheryl R. Bates Doctoral Student/Researcher University of Phoenix

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UNIVERSITY OF PHOENIX INFORMED CONSENT: PARTICIPANTS 18 YEARS OF AGE AND OLDER (U.S. MAIL) Dear Study Participant, Thank you for agreeing to participate in this research study. The purpose of the research study is to determine whether a relationship exists between person-organization fit and emotional intelligence. Your participation in the study will involve completing a demographic questionnaire, a three-question scale on person-organization fit, and an emotional intelligence test. It should take approximately thirty to forty-five minutes to complete all components. Your participation in the study is purely voluntary. If you choose not to participate, or if at any time during the study you want to withdraw, you can do so without any penalty or loss of benefit to yourself. The results of the research study may be published, but to assure anonymity, your name nor your organization's name will be used and your results will be maintained in confidence. Any published information will not be traceable to you nor your organization. There are no foreseeable risks to you for participating in this study. In addition, there is no compensation or specific benefits from your participation. Although there may be no direct benefit to you, the benefit of your participation could have potential benefit to the field of leadership. If you have any questions about the research study, please feel free to contact me at any time. Please review the Informed Consent below and respond by selecting one of the participation choices. If you agree to the Informed Consent, the survey will be mailed to you.

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Informed Consent (U.S. Mail) By signing this form, I acknowledge that I understand the nature of the study, the potential risks to me as a participant, and the means by which my identity will be kept confidential. My signature on this form also indicates that I am 18 years old or older and that I give my permission to voluntarily serve as a participant in the study described.

Signature ______________________________

Date _____________________

Cheryl R. Bates Doctoral Student/Researcher University of Phoenix

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APPENDIX I: ACCESS TO WEB-BASED AND US MAIL SURVEYS

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WEB-BASED SURVEY LETTER Dear Study Participant, Thank you for agreeing to participate in this dissertation research study. Please begin the study by clicking on this link (SurveyMonkey link will be inserted). The demographic survey and the Three-Item Person-Organization Fit Scale will be accessible. To ensure confidentiality, please use your Participant ID# instead of your name. Your Participant ID# is (xxxx). When you open the MSCEITTM, please use the following code and password to complete the survey. When asked for your name, please use your Participant ID# instead of your name. Code: xxxx-xxx-xxx Password: xxxxx If you have any questions, please send an email or call me. Thank you in advance for your participation.

Sincerely, Cheryl R. Bates Doctoral Student/Researcher University of Phoenix

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U.S. MAIL SURVEY LETTER

Dear Study Participant, Thank you for agreeing to participate in this dissertation research study. Enclosed in this package please find these documents: Demographic survey, the Three-Item Person-Organization Fit Scale, and the MSCEITTM. Please complete all surveys and return them in the postage paid envelope contained in this package. Please use your Participant ID# when asked for your name on the survey instruments. Your Participant ID# is (xxxx). If you have any questions, please send an email or call me. Thank you in advance for your participation.

Sincerely,

Cheryl R. Bates Doctoral Student/Researcher University of Phoenix

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APPENDIX J: DEMOGRAPHIC QUESTIONNAIRE

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DEMOGRAPHIC QUESTIONNAIRE

Participant ID#: ________________ Dear Study Participant, please mark your response to each of the following questions.

1. Gender:

Male

Female

2. Which category best describes your age group: 18-24 46-50 3. Race/Ethnicity: 25-30 51-55 White 31-35 56-60 36-40 61 or older Hispanic Asian 41-45

African-American

Other: Please specify __________ 4. Highest level of education completed High School/GED Bachelor's Degree Doctorate Degree Associate's Degree Master's Degree Post-Doctorate

Other: Please specify ________________ 5. Current Position Level Non-managerial Employee Associate/Assistant Director Supervisor Director Manager

Other: Please specify _____________________ 6. Years in current position < 1 year 1-3 years 4-6 years 7-9 years

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10-12 years

13-15 years

16-18 years

19 or more years

7. Total years in management position N/A < 1 year 7-9 years 19 or more 10-12 years

1-3 years 13-15 years

4-6 years 16-18 years

8. Total years in human resources profession < 1 year 10-12 years 1-3 years 13-15 years 4-6 years 16-18 years 7-9 years 19 or more years

9. Which category describes your current job in human resources? HR Generalist Benefits Employee Relations Quality/Risk Management Human Resource Information Systems (HRIS) Other: Please specify ______________________ 10. Which category best describes your organization? Education Healthcare Technology Financial Services Hospitality/Tourism Government Legal Recruiting Compensation HR Operations

Other: Please specify _______________

Thank you for completing the demographic survey.

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APPENDIX K: MSCEITTM TASK SCORES

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MSCEITTM TASK SCORES

Branch Perceiving emotion

Task description (A) Faces: Identification of facial expressions (E) Picture: Expression of emotions through images and landscapes.

Facilitating thought

(B) Sensations: Comparison of emotions and Sensations. (F) Facilitation: Interaction of moods to support thinking and reasoning.

Understanding emotion

(C) Blends: Analyzation of blends of emotions into parts and complex feelings (G) Changes: Transition of emotions from one to another.

Managing emotion

(D) Emotion Management: Incorporating emotions for one's own decision making and regulation of emotions. (H) Emotional Relations: Incorporating emotions into decision making that involves others.

175

APPENDIX L: DESCRIPTIVE STATISTICS FOR ORGANIZATIONAL CHARACTERISTICS

176

DESCRIPTIVE STATISTICS FOR ORGANIZATIONAL CHARACTERISTICS Variable Organization Aeronautical, Space, Satellite Construction Education Financial Services Food and Beverage Healthcare Hospitality/Tourism HR Outsourcing Legal Manufacturing Oil and Gas Social Services Technology Telecommunications Current position Administrative Benefits Compensation Compliance Concierge and Travel Services Document Management Employee Relations HR Generalist Human Resource Information Systems Immigration Services Offer Letter Administration Onboarding (New Hires) Operations Organizational Development Quality/Risk Management Recruiter Training Length in current position <1 year 1 to 3 years 4 to 6 years 7 to 9 years Frequency (N = 89) 2 1 6 37 1 27 1 1 4 1 1 4 2 1 2 7 4 2 3 2 5 17 6 1 1 10 5 3 2 11 8 18 36 11 10 Percent 2.2% 1.1% 6.7% 41.6% 1.1% 30.3% 1.1% 1.1% 4.5% 1.1% 1.1% 4.5% 2.2% 1.1% 2.2% 7.9% 4.5% 2.2% 3.4% 2.2% 5.6% 19.1% 6.7% 1.1% 1.1% 11.2% 5.6% 3.4% 2.2% 12.4% 9.0% 20.2% 40.4% 12.4% 11.2%

177

10 to 12 years Variable Length in current position 13 to 15 years 16 to 18 years 19 or more years Length in management position N/A <1 year 1 to 3 years 4 to 6 years 7 to 9 years 10 to 12 years 13 to 15 years 16 to 18 years 19 or more years Length in HR position <1 years 1 to 3 years 4 to 6 years 7 to 9 years 10 to 12 years 13 to 15 years 16 to 18 years 19 or more years

11 Frequency (N = 89) 1 1 1 32 5 10 11 8 5 5 3 10 6 11 10 19 28 5 2 8

12.4% Percent 1.1% 1.1% 1.1% 36.0% 5.6% 11.2% 12.4% 9.0% 5.6% 5.6% 3.4% 11.2% 6.7% 12.4% 11.2% 21.3% 31.5% 5.6% 2.2% 9.0%

178

APPENDIX M: ORGANIZATION BY CONTINUOUS VARIABLES

179

ORGANIZATION BY CONTINUOUS VARIABLES

MSCEITTM Organization Education (N = 6) Healthcare (N = 27) Technology (N = 2) Financial services (N = 36) Hospitality/Tourism (N = 1) Legal (N = 4) Non-profit (N = 3) Other (N = 9) M 0.42 0.44 0.50 0.43 0.44 0.41 0.47 0.39 SD 0.08 0.04 0.01 0.05 0.03 0.01 0.08 M 6.22 5.67 4.00 5.56 6.00 4.83 6.44 4.74

P-O fit SD 0.66 0.99 2.83 1.06 1.77 0.69 1.71

Note. Other = Aerospace, Consulting, Telecommunications, Energy, Banking, Food/Beverage, Media/Cable, Utilities, and Childcare.

180

APPENDIX N: JOB POSITION BY CONTINUOUS VARIABLES

181

JOB POSITION BY CONTINUOUS VARIABLES

MSCEITTM Job position HR Generalist (N = 17) Benefits (N = 8) Employee relations (N = 5) Quality/Risk management (N = 2) HRIS (N = 6) Recruiting (N = 11) Compensation (N = 4) HR Operations (N = 5) Training (N = 6) Onboarding (N = 8) HR Concierge (N = 3) Document management (N = 2) Compliance (N = 2) Other (N = 9) M 0.43 0.43 0.46 0.31 0.46 0.43 0.42 0.43 0.43 0.42 0.42 0.39 0.43 0.45 SD 0.07 0.02 0.02 0.07 0.04 0.06 0.04 0.07 0.05 0.05 0.03 0.02 0.03 0.04 M

P-O fit SD 1.41 0.50 1.52 0.24 1.06 0.65 0.67 2.02 1.36 0.62 0.51 1.41 0.71 1.72

5.31 5.42 5.60 4.83 5.39 6.24 5.67 4.40 5.17 5.83 5.56 6.00 6.50 5.48

Note. Other = Organizational Development, Immigration, Administrative, Wellness, Workplace Solutions, Offer Letter Administration, Ethics, and Compliance.

182

APPENDIX O: TIME IN HR POSITION BY CONTINUOUS VARIABLE

183

TIME IN HR POSITION BY CONTINUOUS VARIABLE

MSCEITTM Time in HR position < 1 year (N = 6) 1 to 3 years (N = 11) 4 to 6 years (N = 10) 7 to 9 years (N = 18) 10 to 12 years (N = 27) 13 to 15 years (N = 6) 16 to 18 years (N = 2) 19 years or more (N = 8) M 0.45 0.42 0.40 0.44 0.43 0.45 0.45 0.41 SD 0.05 0.06 0.06 0.06 0.04 0.05 0.06 0.07 M

P-O fit SD 1.66 1.00 1.43 1.52 1.02 0.66 0.00 1.00

5.17 5.94 5.40 5.15 5.60 6.22 6.00 5.25

184

APPENDIX P: LENGTH OF TIME IN CURRENT POSITION

185

LENGTH OF TIME IN CURRENT POSITION

MSCEITTM Time in current position < 1 year (N = 17) 1 to 3 years (N = 37) 4 to 6 years (N = 10) 7 to 9 years (N = 10) 10 to 12 years (N = 11) 13 to 15 years (N = 1) 16 to 18 years (N = 1) 19 years or more (N = 1) M 0.43 0.43 0.41 0.45 0.41 0.44 0.49 0.49 SD 0.05 0.04 0.07 0.06 0.06 M

P-O fit SD 1.46 1.29 1.17 1.00 0.83 -

5.51 5.41 5.33 5.53 5.85 6.00 6.00 7.00

186

APPENDIX Q: AGE BY CONTINUOUS VARIABLES

187

AGE BY CONTINUOUS VARIABLES

MSCEITTM Age in years 18 to 24 (N = 2) 25 to 30 (N = 8) 31 to 35 (N = 24) 36 to 40 (N = 15) 41 to 45 (N = 11) 46 to 50 (N = 9) 51 to 55 (N = 9) 56 to 60 (N = 4) 61 and over (N = 3) M 0.48 0.42 0.43 0.44 0.42 0.43 0.43 0.42 0.46 SD 0.05 0.04 0.04 0.06 0.06 0.08 0.08 0.02 0.04 M

P-O fit SD 0.47 1.22 1.13 0.70 0.67 1.27 2.16 0.88 2.04

5.67 5.13 5.40 6.00 6.03 5.11 5.30 5.83 5.22

188

APPENDIX R: EDUCATION BY CONTINUOUS VARIABLES

189

EDUCATION BY CONTINUOUS VARIABLES

MSCEITTM Education High school/GED (N = 15) Associate's (N = 5) Bachelor's (N = 40) Master's (N = 25) Doctorate (N = 4) M 0.42 0.43 0.43 0.43 0.46 SD 0.04 0.05 0.06 0.06 0.04 M

P-O fit SD 1.43 1.04 1.20 1.17 0.74

5.26 4.83 5.48 5.64 6.25

190

APPENDIX S: ORGANIZATIONAL POSITION BY CONTINUOUS VARIABLES

191

ORGANIZATIONAL POSITION BY CONTINUOUS VARIABLES

MSCEITTM Position Non-managerial (N = 37) Supervisor (N = 4) Manager (N = 23) Associate/Assistant director (N = 7) Director (N = 11) Senior director/Vice president/Executive director (N = 7) M 0.43 0.43 0.42 0.39 0.45 0.45 SD 0.05 0.02 0.06 0.07 0.03 0.05 M

P-O fit SD 1.26 1.41 1.14 1.21 0.96 1.53

5.36 5.00 5.62 5.50 5.94 5.67

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