The relationship between emotional intelligence and turnover intention the case of ho chi minh city employees

In an effort to help sales executive have an overview about the behavior and performance of employees, the present study explores the relationship between emotional intelligence and turn

UNIERSITY OF ECONOMICS HO CHI MINH CITY

International School of Business

-

NGUYEN THI THIEN HUONG

THE RELATIONSHIP BETWEEN

EMOTIONAL INTELLIGENCE AND TURNOVER INTENTION: THE CASE OF

HO CHI MINH CITY EMPLOYEES

MASTER OF BUSINESS (Honors)

Ho Chi Minh City-Year 2016

UNIERSITY OF ECONOMICS HO CHI MINH CITY

International School of Business

-

NGUYEN THI THIEN HUONG

THE RELATIONSHIP BETWEEN

EMOTIONAL INTELLIGENCE AND TURNOVER INTENTION: THE CASE OF

HO CHI MINH CITY EMPLOYEES

ID: 22130029

MASTER OF BUSINESS (Honors)

SUPERVISOR: DINH THAI HOANG

ACKNOWLEDGEMENT

First all, I would like to express my sincere gratitude to my supervisor, Dr Dinh Thai Hoang, for his professional guidance, positive encouragements and helpful guidance during the time of doing my research

I would like to express my appreciation to Dr Nguyen Dong Phong, Dr Nguyen Dinh Tho, Dr Tran Ha Minh Quan and Dr Nguyen Thi Nguyet Que for their valuable time and advice

as the members of the proposal examination committee Their comments and meaningful suggestions are significantly contributed to this research completion

My sincere thanks are given to all of my teachers at International Business School for their teaching and guidance during my master course

Finally, my deepest gratitude also goes to my family for their financial support and gentle encouragement so that I have an opportunity to be here - University of Economics of Ho Chi Minh City

ABSTRACT

The concept of employee turnover intention is becoming a popular topic for managerial effectiveness both in the public organization and private companies In 21st century, employee retention is considered as a key factor for business survival for all level of management in service industry However, very few of the scholars have discussed about this matter particularly

in the field of sales In term of sales management, staff turnover is also incredibly important due

to the nature of sales positions, their historically high turnover levels, and the difficulty involved

in filling them In an effort to help sales executive have an overview about the behavior and performance of employees, the present study explores the relationship between emotional intelligence and turnover intention through the impact of emotional intelligence on work-family conflict and emotional exhaustion A survey had sample size of 201 valid questionnaires that were used for data analysis with CFA and SEM The findings broaden knowledge on how these variables affect the turnover intention and how to reduce turnover rate more successfully in the world of intense competition

Keywords: Emotional intelligence, work-family conflict, emotional exhaustion, turnover intention, turnover

CONTENTS

ACKNOWLEDGEMENT

ABSTRACT

ABBREVIATION

Chapter 1: INTRODUCTION 1

1.1 Background to the research and research problem 1

1.2 Research objectives 4

1.3 Methodology 5

1.4 Research significance 5

1.5 Research structure 6

CHAPTER 2 LIETERATURE REVIEW AND HYPOTHESES 7

2.1 Turnover intention 7

2.2 Emotional intelligence 8

2.3 Work-family conflict 9

2.4 Emotional exhaustion 11

2.5 Relationship among variables 11

2.6 Conceptual model 15

Chapter 3: METHODOLOGY 17

3.1 Research design 17

3.1.1 Research process 17

3.1.2 Measurement scales 19

3.2 The quantitative study 23

3.2.1 Sampling and data collection 23

3.2.2 Data analysis procedure 24

Chapter 4: DATA ANALYSIS 26

4.1 Respondents’ demographics 26

4.2.1 CFA for the first-order constructs 28

4.2.2 CFA for second-order constructs 32

4.2.3 CFA for the final measurement model 34

4.3 Structural equation modeling (SEM) 39

4.4 Discussion 42

Chapter 5: CONCLUSIONS, IMPLICATIONS AND LIMITATION 46

5.1 Conclusions and implications 46

5.2 Limitations and recommendations for Future Research 49

REFERENCES 51

APPENDIX 60

LIST OF FIGURES

Figure 2.1 Conceptual model 15

Figure 3.1 Research process 18

Figure 4.1 CFA model of Work-Family Conflict 28

Figure 4.2 CFA model of emotional exhaustion 30

Figure 4.3 CFA model of turnover intention 30

Figure 4.4 CFA model of Emotional Intelligence 33

Figure 4.5 Final measurement model 38

Figure 4.6 Structural results (standardized estimates) 40

LIST OF TABLES Table 3.1 Source of data collection 23

Table 4.1 Respondents’ characteristics 27

Table 4.2 The first run of CFA (of work-family conflict, emotional exhaustion and turnover intention) 29

Table 4.3 Summarized of CR, AVE and Cronbach’α (first order constructs) 31

Table 4.4 Summarized of CR, AVE andCronbach’α (emotional intelligence) 32

Table 4.5 Correlation (of Emotional Intelligence) 34

Table 4.6 Summarized of CR, AVE and Cronbach’α (final model) 35

Table 4.7 CFA Summary of eliminated item 36

Table 4.8 Correlations (final measurement model) 36

Table 4.9 Chi-square difference test for the constrained and unconstrained models (other-emotions appraisal and use of emotions) 37

Table 4.10 Unstandardized structural paths 39

Table 4.11 Measurement validation 41

LIST OF APPENDIX Appendix A List of in-depth interviews’ participants 60

Appendix B Qualitative in-depth interview 60

Appendix C Qualitative in-depth interview findings 63

Appendix D Questionnaire (English Version) 67

Appendix E Questionnaire (Vietnamese Version) 70

Appendix F Correlations among components of emotional intelligence, work-family conflict, emotional exhaustion and turnover intention 73

CFA Confirmatory Factor Analysis

EFA Exploratory Factor Analysis

Chapter 1: INTRODUCTION 1.1 Background to the research and research problem

In the recent decades, the concept of employee turnover intention has been further becoming a popular term in various studies on different managerial disciplines; thus, prompting more executives/managers in many different business fields (e.g sales in service industry) to apply this concept for their employee management (Tett & Meyer, 1993; Lee & Chon, 2000) Lee and Chon (2000) identify job turnover intention as key considered management term for successful careers and business survival at all level in service industry for 21st century Therefore, organizations in the service industry should give a try to improve their people work-life and take advantages of these emotional balance to create beneficial outcomes

The special feature of a service industry is “the contact and interaction between service providers (employees) and service acceptors (customers)” (Tsaur, Chang, & Wu, 2003, p 435) The main products provided by service organizations are services and the employees who play role as service providers will provide those services to customers Thus, employee in service industry becomes a part of service products and the work-life balance will enhance their suitable emotions in responding customers’ expectations help to form image of organizations (Kusluvan, 2003) The issue, then, is how service employees manage their emotions effectively and lessen job turnover intention Most successful service organizations understand their people’s feelings and always have the special cares about any issues that may hurt the employees Thus, the traditional management provided by hierarchical structure might not be a truthful way to understand subordinates while the tones of workloads and stresses are killing human emotions even with the workaholic (Cropanzano, Rupp & Byrne, 2003) It is critical for an organizations

to build a working environment of trust, understanding and encouraging (Taylor, 2001)

In the trend of transitioning and developing Vietnam’s economy, service sector is identified as one of the largest sectors in the economy and one of the biggest contributors to the overall growth rate According to the general statistics office of Vietnam, the growth rate of the service industry is 6.56%/year and the economic structure has been adjusted to the better direction that the services sector continued to contribute the largest portion to the GDP increasing from 41.7% of 2012 to 43.31% in 2013 Furthermore, it is said that Service sector plays a significant role in the economic development of Ho Chi Minh City with the fastest rate of growth among industry and agriculture sectors during 2011-2013 (GSO, as cited in Tap Chi Cong San, 2013) As a result, service domain should provide excellent customer service that comes from a quality workforce However, International Labor Organization (2015) stated that Viet Nam’s labor productivity level is the lowest among ASEAN countries due to low-skill labor forces and high job turn-over intention This organization also assumes that recent productivity growth rates are maintained, “Viet Nam will reach the Philippines only by 2038, Thailand by

2069 and take far more time to catch up with many other countries” (ILO, 2015, p 1) It is also said that Viet Nam's service workforce lacks experience, skills and professionalism for providing good quality services (Tran, as cited in Xuan Huong, 2013) Aslam, Shumaila, Azhar and Sadaqat (2011) realized that these service fields are experiencing labor shortage problems caused

by high job turnover and poor employee performance Therefore, the service industry are strongly required to improve its human resource management in providing services

Currently, Vietnamese government efforts are trying to renovate service industry in Vietnam The workforce in this industry has been training to gain more experience, skills and professionalism for providing good quality services (Nguyen Van Tuan, as cited in Thanh Tam, 2014) However, the challenge is that Vietnam service organizations are characterized by

hierarchical and autocratic styles which create a barrier preventing high management level to understand the reason of high employee’s turnover intention Numerous researchers have emphasized the significant role of avoiding job turnover in organizations to remain competitive

in the rapidly expanding market and business survival (Knudsen, Ducharme & Roman, 2008; Saeed, Waseem, Sikander, & Rizwan, 2014) Additionally, turnover intention is a painful issue

in human resources management which cause negative influence to the organizations including cost of selection, recruitment, training, etc (Lee & Chon, 2000; Saeed et al., 2014)

With the increasing interest in employee turnover intention, numerous studies have been conducted in predictors of job turnover intention and they discovered several factors including employee stress, job satisfaction and work-life balance Among those, emotional intelligence is also one of the key factor which affecting turnover intention (Avey, Luthans & Jensen, 2009) Prior studies have confirmed that emotional intelligence strongly affects people intention to leave their jobs in different managerial level by causing lack of trust, work–family conflict, and work stress (O'Boyle, Humphrey, Pollack, Hawver & Story, 2011) Additionally, things change and people change People’s emotion changes quickly basing on the challenges in the workplaces Therefore, the management of employee emotional change is an issue for both employees and organization in service industry

Gabčanová (2011) stated that human resource is the most important asset of every organization It is neither that technology nor structure made the organization development but people The organization is evaluated as highest performance companies if they have high human development index (Khan, Nazir, Kazmi, Khalid, Kiyani & Shahzad, 2014) Therefore, retaining talented and knowledgeable employees become a major concern for many organizations And reducing employee turnover is one of real solutions for this issue (Aslam et al., 2011) As

employee turnover not only causes considerable financial costs to organizations but loses their talents Because of its powerful impact on both organization aspect and employee positive emotion, many researches encourage to enhance managers’ acknowledgement about the connection between emotional intelligence and turnover intention in order to retain its critical workforce

Up to now, numerous studies have been conducted about the perceptions of subordinates

in term of emotional intelligence, work-family conflict, emotional exhaustion, and employee turnover intention and their significant mutual relationships in developed countries (O'Boyle et al., 2011; Bande, Fernández-Ferrín, Varela & Jaramillo, 2015) Very few scholars do the research about this issue in Vietnam where the term of emotional intelligence and turnover intention are not truly considered in management These studies, however, focus on other contexts of turnover intention and these studies do not measure the relationships of these concepts in one model (Tuan, 2013; Ninh, 2014) As indicated, however this issue has not yet resolved Thus, basing on this gap, this study aims for examining the mutual impact of emotional intelligence on work-family conflict and emotional exhaustion, and subsequently exploring its effect on turnover intention of sales employees in the service industry in Vietnam

1.2 Research objectives

The overall objective of this study is to examine the role of emotional intelligence in work-family conflict and emotional exhaustion, and subsequently in turnover intention of salespeople who are working in the service industry in Ho Chi Minh City, Vietnam Specifically,

it investigates:

 The relationship between emotional intelligence and emotional exhaustion;

 The relationship between emotional intelligence and work-family conflict;

 The relationship between work-family conflict and emotional exhaustion;

 The relationship between emotional exhaustion and turnover intention;

 The relationship between work-family conflict and turnover intention

1.3 Methodology

In this research, two phases of study were undertaken: a qualitative study and a quantitative study The questionnaire was translated from English into Vietnamese Through qualitative study, in-depth interviews with six people were conducted in order to adjust the items closing to features of Vietnamese cultures and to make the improvement for the official questionnaire In the quantitative study, the author collected data by using a convenience sampling approach and employed self-administered survey For analyzing the collected data, SPSS 16 and Amos 22 were used to test the model For the reliability and validity, the researcher used CFA Then, SEM was used to test the hypothesized model

Due to the limitation of time, this research is therefore limited to Vietnamese sales employees who are working in service industry in Ho Chi Minh City; since it is one of the biggest cities in Vietnam and most of service companies centralize here Respondents of this research include employees in sales departments

1.4 Research significance

According to the managerial implications, this finding provides board of directors a deep understanding about employee turnover intention that it significantly impact on organization’s survival and development Therefore, results of this study can be used to develop management

strategies to reduce the turnover rate and maximum performance and job satisfaction to retain their valuable and experienced employees

This study also contribute theory to the academic field This is a unique study that discover a relationship between emotional intelligence and turnover intention in the case of Vietnamese employees As a result, the sale and educational field is expected to expand the literature

1.5 Research structure

This thesis is organized into five chapters The introduction chapter reflects the current situation of service industry in Vietnam as well as discusses about the existing relationship of emotional intelligence, work-family conflict, emotional exhaustion and employee turnover intention in this field It leads to propose the research problem, and research objectives Besides the significance of this thesis contributes to management practice, the scope of the research and methodology of data analysis are also mentioned in the first chapter The second chapter reviews and synthesizes the theories in the literature of research’s concepts, including emotional intelligence, work-family conflict, emotional exhaustion and turnover intention Based on the literature review, this chapter also presents the conceptual model and hypotheses The third chapter mentions about research methodology used to empirically test the research model Chapter four describes the results of data analysis and analyzes them for their relevance to the research questions or hypotheses The last chapter is organized to conclude about research hypotheses, research problems It also suggests implications for theories, implications for policies and practices based on the findings; and points out some limitations for further research

CHAPTER 2 LIETERATURE REVIEW AND HYPOTHESES

This chapter presents relevant literature about the research, which are conducted by many scholar academic and are related to all research concepts and research model Firstly, researcher describes the concepts of emotional intelligence, work-family conflict, emotional exhaustion, and turnover intention Then, it reviews the previous research of these concepts and the related discussion of the chosen subject Finally, based on the foregoing review and previous research, this section declares the hypotheses of this study

2.1 Turnover intention

It has been established that employee turnover intention is one of strongest factor projecting actual turnover (Knudsen et al., 2008) Turnover intention is defined when an individual intents to leave their organization (Tett & Meyer, 1993; Khan et al., 2014) It is inevitable that turnover occurs in every organization in which some of employees are voluntary

to leave the organization while others are discharged by organization Either voluntary or involuntary turnover creates serious consequences to organization in today’s business world including a number of difficulties on replacement, recruitment, selection, socialization cost etc

(Khan et al., 2014; Saeed et al., 2014) To be more detailed, there’s an unavoidable disruption in

productivity when an experienced employee leave the organization Other employees have to pull off their job to replace this position while the company finds quality candidates When the company does recruit a new employees, that person need to be trained weeks or months before producing at the level of the former employee (Huselid, 1995)

According to Dess and Shaw (2001), turnover is divided into two types consisting of voluntary turnover and involuntary turnover It is called voluntary turnover when employees are not satisfied with their job and willing to look for another job in another place And turnover

intention is the volunteer intention of employees to have desire to leave their organization On the contract, it is called involuntary turnover when employees are fired by their organization High turnover rate is definitely not good for organization as it creases heavy cost in recruitment for instance However, the organization cannot reduce it to 0% as employee, who has poor performance, need to be replaced with a qualified one which leads to the labor productivity growth (Saeed et al., 2014) Thus, employee turnover not only has negative effects but also positive effects to the organization (Staw, 1980)

Measuring actual employee turnover is one of the principal objectives that turnover research is expected to reach, however, it is unable to be reached employee data This data is not correctly or consistently collected, so it is unavailable Consequently, employee turnover intention is used as a proxy for actual employee As a result, one of the next best method to measure actual turnover is turnover intention (Lambert, Hogan & Barton, 2001; Knudsen et al., 2008) Employee turnover and turnover intention will be used interchangeably through this

study

2.2 Emotional intelligence

Emotional intelligence is first identified as the concept of “social intelligence” to refer the ability to use emotions in both oneself and others to produce beneficial outcomes (Thorndike,

1920, p.227) The definition given by Salovey and Mayer (1990) for emotional intelligence was

“the subset of social intelligence that involves the ability to monitor one’s own and others’ feelings and emotions, to discriminate among them and to use this information to one’s thinking and actions” (p.189) With the increasing of interest on emotions, emotional intelligence has received a substantial amount of attention among social and organizational psychologists Mayer and Salovey (1993) have established the scope of emotional intelligence consists of four

dimensions including (1) the self- emotions appraisal relating to the ability of a person to understand own emotions and be able to express properly, then apply knowledge of those emotions to create beneficial outcomes Particularly, salesperson who have good emotions is more likely good negotiation with customers and suppliers (Elfenbein, Der Foo, White, Tan & Aik, 2007) and customers are the key area of most companies that can greater meet customer satisfaction by increasing sales domain’s professionals (Martin, O'neill, Hubbard & Palmer, 2008); (2) the other emotions appraisal relating to the ability of an individual to observe and understand other’s emotion A person who have high capability in this dimension will have good observe on other people’s emotions and predict other’s emotional reaction (Davies, Stankov & Roberts, 1998); (3) the use of emotion relating to the ability of an individual to access, generate and use his or her emotion to facilitate personal performance People who rate highly in this ability will able to return rapidly to normal psychological states after suffering depressed or upset; (4) the regulation of emotion relating to the ability of a person to regulate his or her emotion to achieve an expected outcome and able to remain balance from psychological distress

to solve problem (Mayer & Salovey, 1993; Wong & Law, 2002) Specific to sales section, a salesperson with high ability in this area would performance effectively at enhancing customer enthusiasm and reducing customer frustration (Kidwell, Hardesty, Murtha & Sheng, 2011) Therefore, the need of understanding employee emotional intelligence is strongly considered in this study

2.3 Work-family conflict

The intersection of family care and paid work was the subject of innovative research during the first decade of the 21st century and also continued to be a painful public policy issue (Gao, Shi, Niu & Wang, 2013) Work-family conflict is defined as “a form of inter-role conflict

in which the role pressures from the work and family domains are mutually incompatible in some respect” (Greenhaus & Beutell, 1985, p.76) Researchers have developed a variety of conceptual frameworks to model the work-family conflict, Kelloway, Gottlieb and Barham (1999) have divided work-family conflict into three types: time-based, strain-based and behavior-based conflicts Time-based conflict is experienced when the time demands for doing one role restrict the amount of time that can be consumed to other role, interfering the performance of the latter role Strain based conflict takes place when pressure or strain from one role affects performance of another role, and behavior-based conflict occurs when behavioral patterns required and exhibited in one role are inconsistent with those expected for another role While others researchers define two types of conflict: work interfere with family and family interfere with work (Boyar, Maertz Jr, Pearson, & Keough, 2003) This study considers one of dimension of work-family conflict (work interfering to family), because researchers have argued that work interfere with family is more common and closer associated with job satisfaction, exhaustion and job turnover (Bande et al., 2015)

With this increasing interest in work-family conflict, numerous studies have been conducted in the impact of work-family conflict on job and life satisfaction, increased job and life stress, lowered organizational commitment, and increased intention to turnover (Boyar et al., 2003; Allen & Armstrong, 2006) Work-family conflict arises in all kinds of job, however sales positions have been proven that salesperson experience more negative effect from this conflict than other position due to the nature of sales job To be more detailed, work-family conflict reduces level of job satisfaction in sales context more than other context (Boles, Dudley, Onyemah & Rouzies, 2012) Although organization can be guilty for work-family conflict, employees have an obligation for their work-life balance (Bande et al., 2015) Both organization

and its employee are responsible for eliminating work-family conflict (Hammonds, 1996; Carmeli, 2003)

2.4 Emotional exhaustion

According to Moon and Hur (2011), emotional exhaustion is defined as the awareness that emotional resource has been fully consumed It is considered as the main dimension of three dimensions in Maslach and Jackson’s (1981) classic model of employee burnout – (the three dimensions are emotional exhaustion, depersonalization and diminished personal accomplishment) and emotional exhaustion is the core factor of job burnout (Jackson, Schwab & Schuler, 1986) In this study, the author uses the words emotional exhaustion and burnout interchangeably The feelings of tiredness and fatigue, a lack of energy and the reduction of an individual’s emotional resources are types of character of emotional exhaustion (Moore, 2000) Emotional exhaustion is assumed to be the very first step of the burnout process (Gaines & Jermier, 1983) Researchers have found that burnout leads to serious consequences for example low quality of service and reductions of customer satisfaction, high level of job turnover and absenteeism, poor job performance (Cropanzano et al., 2003) and poor morale (Grandey, 2003)

2.5 Relationship among variables

Emotional intelligence and work-family conflict are one of fundamental importance to manufacture organizations (Lenaghan, Buda & Eisner, 2007) Both organization and its employees are responsible for eliminating work-family conflict Companies have their own policies and procedures to help their staff manage stress, but their employees still burnt out Certainly, individuals hold some responsibility for regulating their own family balance, but they need organizational support Organizations need to recognize and adapt employees’ work and lives to win employee loyalty (Keith, as cited in Carmeli, 2003)

According to the conservation of resource (COR) theory, Hobfoll, (1989) has identified individual differences as resources causing the negative effects of stressful events on individuals Individuals who have more personal resources can deal with the loss of other kinds of resources, including resource loss caused by work-family conflict “Emotional intelligence represents individual differences in the ability and capacity to monitor and recognize one’s own and other’s

emotions and to use this information to regulate one’s emotions and actions” (Gao et al., 2013,

p.223)

With respect to the role of individuals, researchers have emphasized emotional intelligence is an important factor in protecting employees from the beginning of work-family conflict and stress to identify, acknowledge and manage the emotions Particularly, Suliman and Al-Shaikh (2007) stated that in term of conflict management, employees with inflated level of emotional intelligence seem to have effective control with conflict) Indeed, people with high ability of emotional intelligence seem to suffer less work-family conflict (Lenaghan et al., 2007) Accordingly, it is hypothesized that:

H1: Emotional intelligence has a negative impact on work-family conflict

It has suggested that emotional intelligence enable individuals to control pressure and adapt easily with the challenge to avoid the burnout (Bar-On, 1997; Taylor, 2001) In relation to emotional exhaustion, people who have elevated levels of emotional intelligence dealing better with life’s challenges and job stresses, which leads to good psychological and physical health (Taylor, 2001) and makes them less likely to experience emotional exhaustion (Van Rooy & Viswesvaran, 2004; Moon & Hur, 2011) The fourth dimension of emotional intelligence enables

a person to regulate their emotion quickly and work on emotive information effectively (Mayer

& Salovey, 1993; Wong & Law, 2002) Regarding to this matter, emotionally intelligent

individual helps salespeople choose appropriate approaches to cope with frustration and make a response more effectively relating to the emotion aspect Employees with high levels of emotional intelligence can keep away from dysfunctional and angry emotions that would be consequence on burnout (Carmeli, 2003) Individuals with high ability of managing their emotions would be less likely to experience burnout Therefore, it could be hypothesized that:

H2: Emotional intelligence has a negative impact on emotional exhaustion

Impact of work-family conflict was studied and the findings showed that work-family conflict was strongly influence to lower job and family satisfaction, greater stress and higher turnover intention (Aslam et al., 2011) Experiencing work-family conflict, individuals are subject to exhaustion that lead to the consequence of conflict between work and family domains, which seems to result in draining on their emotional and physical energy (Golden, 2012; Bande

et al., 2015) According to Hobfoll (1988, 1989) in his COR theory, energy and time are resources that people attempt to maintain, protect and create In addition, “during recovery periods when not confronted with an immediate need for resources, individuals attempt to recover and stockpile resources to counter future losses” (Golden, 2012, p.256) Hobfoll (1989) perceived that work-family conflict expends an individual’s energy and other sources and keep them from “resource stockpiling” which is likely necessary to fend off other current and future resource demands For this reason, individuals tend to suffer higher levels of exhaustion People with high level of work-family conflict are susceptible to exhaustion because conflicts unable individual to accomplish their work and family obligation (Bande et al., 2015; Golden, 2012; Hobfoll, 1989) Consequently, a positive relationship is expected between work-family conflict and emotional exhaustion

H3: Work-family conflict has a positive impact on emotional exhaustion

Over the past twenty years, many researchers have believed that when experiencing work-family conflict, employees have a tendency to quit their job to eliminate the conflict There are various result between work-family conflict and turnover intentions Some researchers believe that work-family conflict has an indirect impact on turnover intentions where work-family conflict first lead to emotional exhaustion which subsequently leads to intention to leave (Cropanzano et al., 2003) On the other hand, other researchers find that work-family conflict has a direct impact on turnover intentions (Boyar et al., 2003) Greenhaus, Parasuraman and Collins (2001) proved that being disappointed with work, family and life entail to the thought that withdraw from work These studies demonstrate that when job-related retention grows too strong in the organization, one of solution that employee could choose is to leave their firm Allen and Armstrong (2006) suggested that work-family conflict could cause employees to quit their job because the demand of work lead to frustration in the workplace and the strain from work make it difficult to fulfill family duties Employees left the emotions felt in the work place

at home as a result they find it hard to concentrate on work task Similarly, Khan et al (2014) examined and found that work-family-conflict has significant impact on employee retention Therefore higher levels of work-family conflict are likely to be associated with higher levels of turnover intentions (Netemeyer, Boles & McMurrian, 1996) Based on the foregoing review and previous research, the hypothesis is proposed:

H4: Work-family conflict has a positive impact on turnover intention

Many researchers have explored that emotional exhaustion have been shown to be strongly associated with turnover intention (Cropanzano et al., 2003; Knudsen et al., 2008) Similarly, according to Layne, Hohenshil, and Singh (2004), turnover intention is corresponded with stress Employees with high level of stress are more likely to leave their organization and

seek for another opportunity In addition, emotional exhaustion will result in lower rates of organizational commitment and higher rates of turnover and turnover intention (Jackson et al., 1986; DeVries & Wilkerson, as cited in Khan et al., 2014; Layne et al., 2004) Employee experiencing higher level of emotional exhaustion result in higher level of turnover intentions (Cropanzano et al., 2003) The amount of burnout has a significant positive effect on turnover intentions (Moore, 2000) Therefore, the following relationship is hypothesized:

H5: Emotional exhaustion has a positive impact on turnover intention

Figure 2.1 Conceptual model

Emotional

intelligence

Emotional exhaustion

Turnover intention Work-family

conflict

These are given hypotheses:

 H1: Emotional intelligence has a negative impact on work-family conflict

 H2: Emotional intelligence has a negative impact on emotional exhaustion

 H3: Work-family conflict has a positive impact on emotional exhaustion

 H4: Work-family conflict has a positive impact on turnover intention

 H5: Emotional exhaustion has a positive impact on turnover intention

In summary, this chapter presents theoretical background of each concept in the model Based on discussion of literature review, emotional intelligence are affected by four dimensions including: the self- emotions appraisal, the other emotions appraisal, the use of emotion, and the regulation of emotion Then, the influence of emotional intelligence on work-family conflict and emotional exhaustion and subsequently on turnover intention is also considered The relationships of these factors already tested by many previous scholars are reviewed for the conceptual model Finally, five hypotheses are proposed to figure out the research objectives

in chapter which is stated in the previous research in Vietnamese context The next chapter will discuss about methodology that used to analyze the data and test hypotheses of the research model

Chapter 3: METHODOLOGY

Chapter three shows the research methodology and research design used in the current study to explore the relationships among emotional intelligence, work-family conflict, emotional exhaustion and turnover intention toward sales employees in service industry in Vietnam The research process is implemented through a combination between qualitative research and quantitative research Through the qualitative analysis, in-depth interviews are involved to modify and revise the measurement In the quantitative analysis, data is collected to test the measurement and structural models This chapter mentions about research design, research process, measurement scales, sampling, data collection and data analysis methodology

3.1 Research design

3.1.1 Research process

The empirical setting in this research is the organization in the context of Ho Chi Minh City, particularly in the service industry The research divided into two phases: a qualitative study and a quantitative study (see figure 3.1) Based on the literature review and the Vietnamese context, the draft questionnaire consisted of four measurement scales, which measured emotional intelligence, work-family conflict, emotional exhaustion and turnover intention The survey questionnaire was originally designed in English and then translated into Vietnamese by the researcher with the support of some English experts The qualitative study was undertaken by in-depth interviews during a week with six employees who working in service industry The researcher arranged a meeting with each of interviewees in the suitable places For each interviewee, the researcher alternately read each item of the measurement scale and asked for his

or her understanding If the interviewee didn’t understand the question, the researcher would

Translation Draft Questionnaire

Revision Final Questionnaire

Research

Problem

Research Model & Hypotheses Literature Review

Confirmatory Factor Analysis

have asked the reasons of misunderstanding and asked for the suggestions from the interviewee The in-depth interviews followed by one by one until the researcher got no more suggestions

Based on the feedback of respondents, the survey questionnaire was slightly modified to make it clearer and more understandable (see Appendix A, B, & C) After the questionnaire was modified, the self-administrated quantitative survey with convenience sampling was conducted

to collect data for testing the research’s hypotheses

Figure 3.1 Research process

Participants self-completed a survey with all items were measured by five-point Likert scale, anchor points from “strongly disagree” (= 1) to “strongly agree” (=5) The questionnaire was mainly delivered to respondents via electronic mail and hard copies (see Table 3.1) SPSS and AMOS were used to test the measurement and structural models.

by three items, reflecting the ability of a person to understand his or her deep emotions and to be able to express emotions naturally Appraisal and recognition of emotion in others was measured

by three items, addressing the ability of a person to perceive and understand the emotions of the people around them Other three items were used to measure regulation of emotion in the self in regulating one’s emotions, enabling a faster recovery from psychological distress Use of emotion to facilitate performance was measured by three items, reflecting the degree to which an individual can use of his or her emotions by directing them toward constructive activities and personal performance

Emotional intelligence (adapted from Wong & Law, 2002) Coding

Self-Emotions Appraisal (SelfEmoA)

1 I have a good sense of why I have certain feelings most of the time

2 I have good understanding of my own emotions

3 I always know whether or not I am happy

Others-Emotions Appraisal (OtherEmoA)

4 I always know my friends’ emotions from their behavior

5 I am a good observer of others’ emotions

6 I am sensitive to the feelings and emotions of others

Use of Emotion (UseEmo)

7 I always set goals for myself and then try my best to achieve them

8 I always tell myself I am a competent person

9 In general, I am a self-motivating person

Regulation of Emotion (RegulaE)

10 I am able to control my temper so that I can handle difficulties rationally

11 I am quite capable of controlling my own emotions

12 I can always calm down quickly when I am very angry

SelfEmoA1 SelfEmoA2 SelfEmoA3

OtherEmoA1 OtherEmoA2 OtherEmoA3

UseEmo1 UseEmo2 UseEmo3

RegulaE1 RegulaE2 RegulaE3

Work-family conflict

The scale items, which were adapted from the five scales of Netemeyer et al (1996), were used to measure work-family conflict to realize the form of inter-role conflict in which the role pressures from the work and family domains are mutually incompatible in some respect The items were adapted to help respondents to understand by eliminating unsuitable items in the qualitative research

Work-family conflict (adapted from Netemeyer et al., 1996) Coding

1 The demands of my work interfere with my home and family life

2 Things I want to do at home do not get done because of the demands my

job puts on me

3 My job produces strain that makes it difficult to fulfill family duties

4 Due to work-related duties, I have to make changes to my plans for family

activities

WorkfaC1 WorkfaC2

Emotional exhaustion (adapted from Maslach and Jackson, 1986) Coding

1 I feel emotionally drained from my work

2 I feel fatigued when I get up in the morning and have to face another day on

the job

3 Working with people all day is really a strain for me

4 I feel frustrated by my job

5 I feel used up at the end of the workday

6 I feel I'm working too hard on my job

EmoExhaus1 EmoExhaus2

EmoExhaus3 EmoExhaus4 EmoExhaus5 EmoExhaus6

Turnover intentions

Turnover intention was measured using four-item from a scale developed by Walsh, Ashford and Hill (1985) These items were used to measure the intention to leave the organizations of employees

Turnover intention (adapted from Walsh et al., 1985) Coding

1 As soon as I can find a better job, I will leave this center

2 I am actively looking for a job at another center

3 I am seriously thinking of quitting my job

4 I think I will be working for this center 5 years from now (reverse coded)

TurnoverI1 TurnoverI2 TurnoverI3 TurnoverI4

3.2 The quantitative study

3.2.1 Sampling and data collection

The empirical setting in this research was the organization in the context of Ho Chi Minh City Respondents were salespeople in private organizations This paper used the method of self-administered survey, which consisted of 04 constructs and 26 variables A minimum subject requirement to item ratio is at least 5:1 (Hair, Black, Babin, Anderson, & Tatham, 2006) It means that one variable needs at least 5 observations The present research has 26 items Hence, the minimum sample size required is n=26*5=130 observations To obtain the size of 130, it is supposed to conduct 350 questionnaires using non-probability sampling method Particularly, in the present research, convenience sampling is chosen to gather relevant data After collecting, total 223 responses were collected; the response rate was approximately 64 percent (see Table 3.1) Then, total 22 questionnaires were eliminated because they were invalid (respondents just chose one option for all questions or their answers were implausible or they were not working in service industry as a salesperson) Finally, 201 questionnaires were used as valid data for this research In comparison with minimum sample size, this number of data was satisfactory

Table 3.1 Source of data collection Source Delivered Collected Response rate Eliminated Valid

3.2.2 Data analysis procedure

Test of reliability, CFA and SEM test were conducted to analyze the collected data The author used SPSS 16 for calculating Cronbach’s alpha and Amos 22 for running CFA to test the reliability for each measurement component separately and the validity for all scales And the measurement scale’s reliability among constructs was evaluated based on composite reliability (CR) in the research model According to CFA results, average variance extracted (AVE) was used to conclude the convergent validity and correlation between items (r) was used to identify the discriminate validity Additionally, in orther to implie that the measurement is good, Cronbach’s alpha for each construct should be at least 0.6 (Nunnally & Burnstein, as cited in Prajogo, 2007); the factor loading should be 0.5 (Prajogo, 2007); the minimum value of AVE is 0.5 (Chong, Ooi, Lin & Tan, 2010); and the composite reliability should be over 0.7 as

recommended by Nunnally (as cited in Chong et al., 2010) Considering the convergent and

discriminated validity, the inappropriate items would be removed if necessity Moreover, the CFA would indicate the model fit if CMIN/DF was less than 2 with p-value larger than 5%, and the comparative fit index (CFI) analyzed the model fit by examining the discrepancy between the data and the hypothesized model, while adjusting the issues of sample size inherence in the chi-squared test of model fit, and the normed fit index A CFI value of 0.90 or larger was generally considered to indicate acceptable model fit The non-normed fit index (NNFI; also known as the Tucker-Lewis index-TLI) resolved some of the issues of negative bias, though NNFI values may sometimes fall beyond the 0 to 1 range Values for both the NFI and NNFI should range of 95 or greater, indicating a good model fit The root mean square error of approximation (RMSEA) avoided issues of sample size by analyzing the discrepancy between the hypothesized model, with optimally chosen parameter estimates, and the population covariance matrix RMSEA was

smaller than 8% indicated an acceptable model fit (Tho & Trang, 2008) Then, structural equation modeling (SEM) tested the hypothesized model and estimated path coefficients for each proposed relationship in the structural model

As mentioned above, four measurement scales were sufficient for convergent and discriminant validity, were analyzed by the Confirmatory factor analysis before the hypothesized model was tested by SEM The first-order constructs were work-family conflict, emotional exhaustion and turnover intention The second-order construct were emotional intelligence, which consisted of four sub-components: self-emotions appraisal, other-emotions appraisal, use

of emotions and self- regulations of emotion

In summary, this chapter described the research process, measurement scale construction, calculation of sample size, and research method conducted to analyze the collected data This study was designed into two stages: qualitative study (in-depth interview), quantitative study (main survey) The in-depth interview was conducted to modify the measurement scale and the questionnaire was adjusted slightly for the quantitative survey Main survey had sample size of

201 valid questionnaires that were used for data analysis with CFA and SEM The next chapter will present data analysis of main survey

Chapter 4: DATA ANALYSIS

Chapter 4 presents the analysis results of the sample size n=201 This process used SPSS

to review the sample’s characters and the descriptive statistic tested the normal distribution of variables basing on respondents’ demographics Then, AMOS was used for confirmatory factor analysis to examine the reliability and validity of the first order constructs, the second order construct and the final measurement model In addition, structural equation modeling was used

to test the conceptual Based on the analysis’s results, the explanation for finding research was finally discussed

4.1 Respondents’ demographics

The collected data were analyzed using the SPSS – Statistical Software Package This part aimed to provide the general information of respondents from private organizations in HCM City The results of the demographics analysis were summarized in table 4.1 Initial analysis of data indicated that gender of respondents was not quite equally between female and male Female was higher with 54.7% of respondents and male seized 45.3% of respondents More than half of the respondents who took part in this study were young people from 25 to 35 years old with 54.7% of total sample This number indicates that the current labor force in marketing and sales is very young Age ranged from 18 to over 45 years old, with 39.3% of respondents were between 18 and 25 years old, 3.5% of people were from 35 to 45 years old, and only 2.5% of people was older than 45 years old In addition, the frequency of education level also indicates a fair equal ratio with 54.2% for college/university and 43.3% for post-graduation There was a very small part of education level with 2.5 percent of respondents who just finished high school Income per month was divided in four groups Income per month of most of respondents was not very high, fluctuated between 5 million VND and less than 10 million VND Specifically, 52.8%

of respondents revealed that their income ranged from 5 to 10 million VND, 12.4% of people earned less than 5 million VND There were about 19.4% of respondents’ income from 10 to 15 million VND, and the last portion was the respondents with the income more than 15 million VND per month with 15.4% of sample size Basing on the results of frequency, almost people in these groups graduated college, university and post-graduation, and reflected their understanding about emotional intelligence However, this demographic profile might not reflect the picture Due to research topic as mentioned above, these information only help researcher have a better understanding about respondents

Table 4.1 Respondents’ characteristics Demographic profile Category Frequency Percentage (%)

Female Total

91

110

201

45.3 54.7

100

25 – 35

35 – 45 Over 45 Total

4.2.1 CFA for the first-order constructs

Work-family conflict was measured by 4 items For the first run of CFA, the CFA model

of work-family conflict fitted the data well (Chi-square/df=0.023; P=0.977; CFI=1.000; TLI=1.016; NFI=1.000; RMSEA=0.000; PCLOSE=0.986) Additionally, the factor loading of items to measure work-family conflict were significant with 0.75 for WorkfaC1, 0.87 for WorkfaC2, 0.82 for WorkfaC3 and 0.69 for WorkfaC4 (see figure 4.1 and table 4.2)

Figure 4.1 CFA model of Work-Family Conflict

For the first run of CFA for emotional exhaustion construct, standardized regression weights of EmoExhaus2, EmoExhaus3, EmoExhaus5 and EmoExhaus6 were higher than 0.5 (0.64, 0.78, 0.78, and 0.77 in sequence) Although these estimates fitted the data well, the factor loadings of EmoExhaus1 and EmoExhaus4 were not significant (0.015 and 0.006 < 0.5) (see Table 4.2)

Table 4.2 The first run of CFA (of work-family conflict, emotional exhaustion and turnover

intention)

Factor Loadings

WorkFamilyConflict  WorkfaC1 0.75 WorkFamilyConflict  WorkfaC2 0.87 WorkFamilyConflict  WorkfaC3 0.82 WorkFamilyConflict  WorkfaC4 0.69 EmoExhaustion  EmoExhaus1 0.015 EmoExhaustion  EmoExhaus2 0.64 EmoExhaustion  EmoExhaus3 0.78 EmoExhaustion  EmoExhaus4 0.006

EmoExhaustion  EmoExhaus6 0.77 TurnOverIntention  TurnoverI1 0.78 TurnOverIntention  TurnoverI2 0.91 TurnOverIntention  TurnoverI3 0.80 TurnOverIntention  TurnoverI4 0.51

After removing insignificant item EmoExhaus1 and EmoExhaus4, the model of emotional exhaustion was measured by four items: EmoExhaus2, EmoExhaus3, EmoExhaus5 and EmoExhaus6 Figure 4.2 displayed the result of CFA analysis and the CFA model of emotional exhaustion for the second run also fitted the data well (Chi-square/df=1.280; P=0.278; CFI=0.998; TLI=0.994; NFI=0.991; RMSEA=0.038; PCLOSE=0.438)

Figure 4.2 CFA model of emotional exhaustion

For the first run for CFA model of turnover intention, this first order construct was measured by four items TurnoverI1, TurnoverI2, TurnoverI3 and TurnoverI4 The findings show that all factor loadings were higher than 0.5 (0.78, 0.91, 0.80 and 0.51 respectively) and the CFA model also fitted the data well (Chi-square/df = 0.572; P=.565; CFI=1.000; TLI=1.008; NFI=0.997; RMSEA=0.000; PCLOSE=0.699)

Figure 4.3 CFA model of turnover intention

For each construct, the author tested the reliability and convergent validity by calculating Cronbach’α, composite reliability (CR) and averaged variance extracted (AVE) values based on items’ standardized loadings Cronbach’α, composite reliability of work-family conflict, emotional exhaustion and turnover intention were higher than 0.7 (0.86 and 0.86; 0.84 and 0.83; 0.83 and 0.84 respectively) Thus, reliability of first order constructs was acceptable

Table 4.3 Summarized of CR, AVE and Cronbach’α (first order constructs)

Standardized loadings

Reliability (CR; AVE)

CR=0.86 AVE=0.61

TurnOverIntention  TurnoverI2 0.91

TurnOverIntention  TurnoverI3 0.80

TurnOverIntention  TurnoverI4 0.51

Notes: CR: composite reliability; AVE: averaged variance extracted

The averaged variance extracted value of emotional exhaustion was lower than 0.5 in its first run of CFA However, this value was higher than 0.5 in the second run of CFA after the author eliminated EmoExhaus1 and EmoExhaus4 Thus, the AVE value of emotional exhaustion

is acceptable Additionally, AVE values of work-family conflict and turnover intention were higher than 0.5 (0.61 and 0.57 respectively) In summary, the CFA model of the first-order

constructs including work-family conflict, emotional exhaustion and turnover intention fitted the data well All the data analysis of these first-order constructs is presented in Table 4.3

4.2.2 CFA for second-order constructs

The second-order construct was emotional intelligence, which consisted of four components: self-emotions appraisal, other-emotions appraisal, use of emotions and self- regulations of emotion For the first run of CFA model, the data fitted the model (Chi-square=61.660; df=48; Chi-square/df=1.285; P=.089; CFI=.990; TLI=.986; NFI=.956; RMSEA=.038) and all of the items had significant factor loadings (>0.5) (see Table 4.4 and Figure 4.4)

sub-Table 4.4 Summarized of CR, AVE andCronbach’α (emotional intelligence)

Standardized loadings Reliability (CR; AVE)

CR=0.86 AVE=0.67

CR=0.83 AVE=0.62

CR=0.87 AVE=0.68

CR=0.79 AVE=0.56

Notes: CR: composite reliability; AVE: averaged variance extracted