The Differential Effect of Career Anchor Profiles on the Relationship between Career Plateau and Turnover Intention

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(1)The Differential Effect of Career Anchor Profiles on the Relationship between Career Plateau and Turnover Intention. by Lin, Bing-Han. A Thesis Submitted to the Graduate Faculty in Partial Fulfillment of the Requirements for the Degree of MASTER OF BUSINESS ADMINISTRATION Major: International Human Resource Development. Advisor: Dr. C. Rosa Yeh, Ph. D.. National Taiwan Normal University Taipei, Taiwan August 2017.

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(3) ACKNOWLEDGEMENT This thesis is dedicated to each and every one who has been there every step of the way throughout my two years being a graduate student. Without all the supports I received from all of you, I couldn’t have made it to where I am today. First, I would like to thank my advisor, Dr. Yeh. Thank you for guiding me through the completion of my thesis. Without the guidance and advice, I would not be able to accomplish this tough task. In addition, the attitude that you taught me when dealing with work is the priceless treasure in this journey. Second, I would like to thank my family. Although, there is little you can do to help with my schoolwork and thesis (Actually, data collection is a huge part.), the continuous encouragement and confidence in me are the energy that help me cross the finish line. Finally, I would like to thank Rick for all the help I received from you; Owen, Karina, Derrick, Shanglin, Fan, Lynn and all other dear fellows in IHRD for accompanying me from the beginning till the end. Things that I have learned from all of you have become a part of me and made me who I am today. Hope that I did the same to you all too. At last, I want to say that “We did it!.

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(5) ABSTRACT Career plateau is a situation that individuals will face sooner or later in their career life. It generally leads to negative outcomes such as dissatisfaction toward the job, low organizational commitment, and even worse high turnover intention and turnover rate. In this study, the researcher intended to discover the relationship between career plateau, turnover intention and career anchors to help resolve the talent management problem. Therefore, two hypotheses were proposed. First, career plateau had a relationship with turnover intention. Second, career anchor profiles had a moderating effect on the relationship between career plateau and turnover intention. A quantitative research was conducted and the data was collected through online questionnaires. The participants in this study were the current employees in Taiwan who have been working for at least one year in private sectors. The final number of valid responses was 412. After the statistical analysis, three clusters: low career pursuers, mid-career pursuers and high career pursuers, were generated. The result demonstrated an individual’s career development stages. In the beginning, individuals focus more on the stability/security and lifestyle anchors. After accumulation of experiences and explored their career, individuals developed into mid-career pursuers who paid great attention to technical/functional competence and service/ dedication to a cause anchors. Finally, when they were well developed in their career and became the high career pursuers, the general managerial competence and entrepreneurial creativity seem to be the most important anchors at the stage. The effects of the three cluster profiles on the relationship between career plateau and turnover intention also support the aforementioned findings.. Keywords: career plateau, turnover intention, career anchors. I.

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(7) TABLE OF CONTENTS ABSTRACT ................................................................................................ I TABLE OF CONTENTS........................................................................... II LIST OF TABLES ................................................................................... IV LIST OF FIGURES ................................................................................... V CHAPTER I INTRODUCTION .................................................................1 Background of the Study ........................................................................................... 1 Statement of the Problem ........................................................................................... 4 Purpose of the Study .................................................................................................. 5 Research Questions .................................................................................................... 6 Scope of the Study ..................................................................................................... 6 Definition of the Terms .............................................................................................. 7. CHAPTER II LITERATURE REVIEW ....................................................8 Turnover ..................................................................................................................... 8 Career Plateau .......................................................................................................... 15 The Moderating Effects of Career Anchor Profiles ................................................. 18. CHAPTER III RESEARCH METHOD ...................................................23 Research Framework ............................................................................................... 23 Research Procedure .................................................................................................. 24 Research Design....................................................................................................... 26 Measurement ............................................................................................................ 30 Validity and Reliability Tests .................................................................................. 35. CHAPTER IV DATA ANALYSIS AND FINDINGS.............................45 II.

(8) Correlation Analysis ................................................................................................ 45 Cluster Analysis ....................................................................................................... 48 Hierarchical Regression Analysis ............................................................................ 51. CHAPTER V CONCLUSIONS AND DISCUSSION .............................56 Conclusion ............................................................................................................... 56 Discussion ................................................................................................................ 56 Theoretical Implications .......................................................................................... 58 Practical Implications............................................................................................... 59 Limitations ............................................................................................................... 59 Suggestions for Future Research ............................................................................. 60. REFERENCE ............................................................................................61 APPENDIX ...............................................................................................67. III.

(9) LIST OF TABLES Table 3.1. Demographics of the Sample………………………………….......…...27 Table 3.2.. Exploratory Factor Analysis (EFA): Turnover Intention......................36. Table 3.3.. Exploratory Factor Analysis (EFA): Career Plateau………………….37. Table 3.4. Exploratory Factor Analysis (EFA): Career Anchors…………………38 Table 3.5.. Indices of Model Fits………………………....…...…………………..41. Table 3.6.. Career plateau and turnover intention model fit summary……………43. Table 3.7.. Cronbach’s Alpha……………………………………………………..44. Table 4.1.. Mean, Standard Deviation, Correlation and Reliability among Research Variables ……………………………………………………………...47. Table 4.2.. Final Cluster Centers………………………………………………….48. Table 4.3.. Cluster Profile…………………………………………………………50. Table 4.4.. Hierarchical Regression Result……………………………...…..….…51. Table 4.5.. Hierarchical Regression Result among Clusters……………..………..53. Table 4.6. Hierarchical Regression Result among Clusters: Turnover Intention Regressed on Job Content Plateau……………………….….…….…..53 Table 4.7. Hierarchical Regression Result among Clusters : Turnover Intention Regressed on Hierarchical Plateau…………………………..…….......54 Table 4.8. Hypotheses Testing Result Summary…………………………….……55. IV.

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(11) LIST OF FIGURES Figure 2.1.. The employee turnover decision process……………………….…..10. Figure 2.2.. A schematic representation of the primary variables and process of employee turnover……………………………………..…..……..…11. Figure 3.1.. Research framework……………………….……...………………..23. Figure 3.2.. Research procedure………………….……………………………...25. Figure 3.3.. Career plateau and turnover intention model…………………….…42. Figure 4.1.. K-mean cluster analysis………………………..……........................48. V.

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(13) CHAPTER I. INTRODUCTION. Background of the Study Nowadays, thanks to the advancement of transportation and technology, the world has become more and more globalized and competitive. In order to survive the fierce competition, the companies today modify their organizational structures into flatter types with fewer hierarchical levels. In this case, the companies can reduce the time needed to communicate among hierarchical levels to respond to the rapid changing market quickly. This phenomenon happened quite commonly in recent Taiwan society. Because of some natural constrains such as the population and industry types, most companies in Taiwan are small and medium enterprises (SMEs). According to the statistics from Ministry of Economic Affair in Taiwan, around 97.6% of the companies are SMEs and approximately 78.2% of the entire population in Taiwan works in SMEs (Small and Medium Enterprise Administration, Ministry of Economic Affairs, 2016). SMEs are defined as companies with less than 100 employees (200 employees for manufacture and mining industry). With these few employees in the company, the organization structures tend to have fewer ranks and often look flatter. As a result, employees’ mobility toward the upper level will be more difficult and more competitive with the few ranks existing in the companies. This brings out the issue of career plateau, which originally refers to an individual staying at the same position without moving to a higher rank in an organization. When it was first discussed, career plateau talks only about the vertical and horizontal mobility within the organization. However, Veiga (1981) suggested that there is possibility that employees received upward movement without actually earning more salary, facing extra or different job contents as well as challenges. The study indicated that simply judging whether an employee is plateaued or not through 1.

(14) evaluating his/her chances of getting a promotion is not sufficient. Therefore, the previous studies developed the construct of career plateau with two dimensions: job content plateau and hierarchical plateau (Bardwick, 1986; Feldman & Weitz, 1988). Career plateau is a situation that every employee will naturally encounter sooner or later in their career life. It does not necessarily lead to bad consequences. Research showed that plateaued employees constantly provide positive support to the companies (Bardwick, 1986). However, generally, negative results were found in studies. Job dissatisfaction, low engagement and commitment and even worse the high turnover rate of employees might harm the companies badly (Feldman & Weitz, 1988). Often when employees are stocked at the same position too long, they are not able to receive more payment or new job tasks. Doing routine works makes employees feel bored, which results in the dissatisfaction toward the jobs and maybe even the companies. Later on they may be reluctant to dedicate themselves to the company and the performance start to deteriorate. If the situation becomes worse, misbehaviors like absenteeism will start happening. Eventually, employees may consider or actually leave the company, which is called employee turnover (Chao, 1990; Milliman, 1992). For a human resource practitioner, the employee turnover rate of a company needs to be monitored constantly. Turnover does not always come with bad consequences. Positively, it prevents companies from aging and improves the overall performance of companies as well (Staw, 1980). However, a turnover rate too high will definitely do harm to the company. The company might end up wasting lots of time and great deal of money to recruit and train new employees (Allen, Weeks, & Moffitt, 2005). In order to prevent these from happening, maintaining the turnover rate at a certain level (it is impossible to totally eliminate turnover in an organization) is indeed crucial. In addition, the best turnover will be keeping the good performers 2.

(15) and replace the poor performers. For the purpose of keeping the talents in the companies, the employers have to understand their employees. Knowing what the employees want and what they valued most toward jobs is indeed crucial, especially today in a world where companies have to take proactive measures to find and retain talents. Hence, this research intends to utilize career anchors to discover how differently employees prioritize their personal needs regarding their career choices (Schein & Maanen, 2016). Career anchors developed by Schein (1978) are the tools used to facilitate talent management. It helps identify an individual’s internal factor that he/she will never give up even when making difficult career decisions. It is an individual’s self-image which is developed through their personality, skills, abilities, talents and past experiences. However, individuals may not know what their career anchors are without actually doing the job. It takes some time to accumulate experiences and learn in the early years of their career life. Once an individual’s anchor is formed, he/she will use it as guidance to their career path. However, from other studies, researchers proposed that individuals do not only have one career anchor that influences career decision making process (Suutari & Taka, 2004; Chapman & Brown, 2014); rather, multiple anchors working at the same time as the dominant anchors is the more common phenomenon in individuals’ career. Therefore, this research intended to discover how employees in Taiwan react when they encountered career plateau, especially their intention to leave the organization. Meanwhile, using career anchors to identify how individuals’ personal preferences affect the career decisions they have to make.. 3.

(16) Statement of the Problem From past studies, the relationship between career plateau and turnover intention have been widely studied (Chao, 1990; Milliman, 1992) and the investigation of factors in between has been focused on the variables such as organizational/supervisor supports (Wickramasinghe & Jayaweera, 2010) and mentoring (Foster, Shastri, & Withane, 2011). These research mostly focus on contextual factors that affect individuals’ career decisions or behaviors; however, few studies focus on individuals’ inner factors such as personality and individual career-career oriented variables that greatly influence how they make choices regarding their career (Ettington, 1998; Wen & Liu, 2015). In addition, nowadays in the private sector in Taiwan, many companies conduct all sort of personality tests when recruiting employees to make sure that the candidates have either person-job fit or person-organization fit. However, companies only apply the tests to the new employees when entering the company. Not many companies utilize the tools and examine their workers regularly to see whether their personal traits, preferences, priorities, and state of mind have changed over time, especially in SMEs where talent management are usually not well-structured or even ignored. When employees are plateaued, they might face some career decisions. Career anchors then play an important role in the decision-making process. With the career anchors, employees will have a better guidance toward their future career, while the employers will be able to know what the employees valued most, how the employees feel about being plateaued. In this case, the employers might be able to predict employees’ possible reactions (stay, turnover or else) so as to take appropriate measures to minimize the effect of career plateau on turnover. Nevertheless, different from the original definition of career anchors (Schein, 4.

(17) 1978) that every individual have only one dominant anchor that plays as the most important personal factor when dealing with career decisions, many researchers found that individuals may have multiple dominant anchors at the same time (Erwee, 1990; Coetzee & Schreuder, 2014). Therefore, in this research, the researcher proposed that the eight career anchors to an individual is more an idea of different profile patterns and each anchor has different level of influence rather than a choice of the most important one.. Purpose of the Study There are two purposes in this study. First, this study aims to discover the relationship between career plateau and turnover intention in Taiwan. The researcher wants to discover what relationship it is in such an extreme industry structure (over 97% of companies are SMEs). Second, the researcher intends to explore the existence of career anchor profiles and their differential level of the effects on the relationship between career plateau and turnover intention. Thus, the researcher hoped to investigate the general profile patterns of employees in Taiwan and understood the general reactions to turnover intention of plateaued employees with different career anchor profiles. It was expected to facilitate human resource management and talent development within companies.. 5.

(18) Research Questions From the problem statement and the purpose of this study, the research questions derived are as follow: 1. In Taiwan, how does career plateau affect an individual’s turnover intention? 2. How will different career anchor profiles influence the relationship between career plateau and turnover intention?. Scope of the Study This study focuses on the relationship between career plateau and turnover intention in Taiwan. Career anchor profiles are used as the moderators to see the effects on such relationship. Some other important variables that might affect employees’ turnover intention are not discussed in this research. In addition, other consequences of career plateau are not included in the study as well. Due to time and budget constraint, the participants of this research are Taiwan employees who have been working for more than one year. The research questionnaires are distributed online and the size of the sample is around 400; therefore, the results of this study might not be able to generalize to the entire country or all industries.. 6.

(19) Definition of the Terms Career Plateau In this study, the researcher adopted the definition from Bardwick (1986) that there are two different forms of career plateau: hierarchical plateau and job content plateau. Hierarchical plateauing happens when employees have little mobility among the organization ranks. As to job content plateau, it occurs when individuals are not able to receive new tasks or challenges in an organization.. Turnover Intention Turnover intention was defined by Mobley (1977) as an employee’s intention to permanently leave the organization voluntarily. Career Anchors Career anchors include an individual’s past experiences, talents, values and attitudes which provide stability and guidance to a person’s career. It can either be the ‘motivator’ or ‘driver’ of the individual. A career anchor is the self-image element that people will not give up, even when facing difficult career decisions (Schein, 1978).. 7.

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(21) CHAPTER II. LITERATURE REVIEW Turnover. Definition of Turnover In the organizational behavior field, turnover has been widely and frequently studied in the past 50 years. A lot of scholars have made significant contributions to the concept and construct of turnover. For example, Wanous, Strumpf, and Bedrosian (1979) identified two kinds of turnover: voluntary and involuntary turnover. Dalton, Todor and Krackhardt (1982) divided turnover into functional and dysfunctional turnover. According to Mobley (1977), turnover is defined as an employee works in an organization, through deep consideration after working for a period of time, the employee decided to leave the organization permanently. Williams and Hazer (1986) viewed turnover as the act of an employee actually leaving the organization. Ferguson and Ferguson (1986) said turnover is the termination of the relationship between employers and employees, no matter the decision is made from which side. Hendrix, Robbins, Miller and Summers (1998) defined turnover as both employees’ voluntary and involuntary leaving the organizations permanently. In this research, turnover will be defined as the employees’ voluntary decision of leaving a company permanently.. Types of Turnover Wanous, et al. (1979) classified turnover into two types. One is voluntary turnover and the other one is involuntary turnover. The former one referred to employees’ behavior of leaving the position or organization voluntarily due to organizational or personal factors, such as salary, promotion, health and so on. The latter one indicated that employees are forced by the organization to quit. 8.

(22) permanently (e.g. dismissal or layoff). Most studies focused on the voluntary turnover for the reasons that this is the most commonly seen type of employees’ turnovers and that the factors influencing voluntary turnover can often be controlled by the organization (Morrell, Loan-Clarke, & Wilkinson, 2001). In addition, Abelson (1987) categorized employee turnover into avoidable and unavoidable. This categorization is more for an organization point of view. For avoidable turnover, organizations can always take measures to prevent or control it from happening, regardless of whether it is employee’s voluntary or involuntary turnover. As to unavoidable turnover, it refers to situations and conditions that cannot be easily controlled or avoid by the organization. The following figure showed some examples of the abovementioned categorization.. Turnover Process Model The turnover process model in Figure 2.1. is the most commonly seen model developed by Mobley (1977). It demonstrated an individual’s mind process all the way till the actual turnover happened, from feeling dissatisfied with the current job, evaluating the pros and cons of quitting, searching for the alternatives, comparing options with the present job, having the intention to leave or stay, and finally made up his/her mind to quit or stay.. 9.

(23) Figure 2.1. The employee turnover decision process. Adapted from “Intermediate linkages in the relationship between job satisfaction and employee turnover,” by Mobley, W.H., 1977, Journal of Applied Psychology, 62(2), p.238.. Later on, Mobley, Griffeth, Hand and Meglino (1979) revised and enriched the model by adding other related factors and control variables (refer to Figure 2.2.). There are five features of this turnover process model: (a) Beside the differences among personal perception, expectation and values, the model included personal and occupational variables. (b) The perception and evaluation toward job opportunities are demonstrated. (c) The centrality of work values and interests relative to other values and interests, beliefs regarding non-work-related consequences of leaving or 10.

(24) staying, and contractual constraints are presented in the model. (d) The contribution to turnover of current job satisfaction, expected job attraction, and the attraction of attainable job alternatives are proposed. (e) Turnover intention is viewed as the immediate precursor of actual turnover, while impulsive behavior will weaken the relationship between them. This model is developed from the actual turnover behavior and traced all the way back to its antecedents.. Figure 2.2. A schematic representation of the primary variables and process of employee turnover. Adapted from “Review and conceptual analysis of the employee turnover process,” by Mobley, W. H., Griffeth, R. W., Hand, H. H., & Meglino, B. M., 1979, Psychological bulletin, 86(3), p.493.. 11.

(25) Turnover Intention Over the past five decades, the turnover process model has been discussed in the field of organizational research. Other than the turnover process model developed by Mobley in 1977, there are a lot of research regarding the idea of turnover, the turnover process models and their antecedents. However, among all antecedents of turnover, turnover intention has been shown to be the best predictor among all other antecedents (Miller, Katerberg, & Hulin, 1979; Hom, Caranikas-Walker & Prussia, 1992). In the field of psychology, Fishbein and Ajzen (1977) once said that the best way to predict an individual’s behavior is to observe and measure his/her intention to perform that certain behavior. Because of these reasons, this study intends to measure turnover intention as the outcome variable. Turnover intention and intention to leave (quit) are used as interchangeable terms for each other. Porter and Steers (1973) defined intention to leave as the withdrawal behavior of an individual when his/her expectations toward their work or organization are not met. Mobley (1977) defined intention to quit as an employee’s last stage of turnover decision process right before the actual turnover. Throughout the process, job satisfaction, searching for alternative jobs and the evaluation among alternatives and the current job are involved. In the research of Miller et al. (1979), intention to leave is defined as a comprehensive idea that includes an individual’s thought of leaving the current job, and seeking possible alternatives out of the organization. Williams and Hazer (1986) defined intention to quit as an individual’s intention, desire and plans to leave their job. To sum up the above definitions from previous studies, turnover intention is merely an individual’s intention to search for other job opportunities outside the current organization. The actual turnover has not happened yet at this stage. The individual will process through some related problems and questions (e.g., the idea of quitting, finding new jobs and evaluate all 12.

(26) alternative) then make a feasible and satisfying overall assessment. After all these been done, the actual turnover happened, which means leaving the position or organization permanently.. Antecedents of Turnover Intention Demographic Factors. Generally speaking, personal factors, such as gender, age, marital status, education background, tenure, and job position, are variables that are related to turnover intention. According to previous research results, Marsh and Mannari (1977) and Weisberg and Kirschenbaum (1993) found that females had higher turnover rates than males. Hayes (2015) found that age was negatively related to turnover intention. In other words, the older an individual is, the lower their turnover intention will be. Studies also found that family responsibility, which is measured by an individual’s marital status and the number of his/her dependents, was related to turnover intention (Koh & Goh, 1995). For people who are single, their turnover intention tends to be higher, whereas those married employees and those with dependents have a lower intention to quit. In addition, education background influences employees’ turnover intention. However, the direction of the effect on turnover intention is inconclusive. Mobley (1982) found that education background was negatively related to turnover intention while Cotton and Tuttle (1986) indicated that the higher an individual is educated, the stronger turnover intention he/she has. Work-Related Factors. Job satisfaction is the most commonly studied variable related to turnover intention. Research showed that it is one of the most immediate variables to predict an individual’s intention to leave an organization (Sousa-Poza & Hennebeger, 2004). The results are intuitive. They showed that job satisfaction is 13.

(27) significantly negatively related to turnover intention. In other words, if an employee is satisfied with his/her job, their turnover intention will be low (Porter & Steers, 1973; Price, 1977; Fogarty, Singh, Rhoads, & Moore, 2000; Sousa-Poza & Hennebeger, 2004). Organizational commitment is another important variable often used to predict turnover intention. Abundant research presented the result that organizational commitment is significantly and negatively related to turnover intention. That is, the less committed an employee is to their organization, the stronger their intention to quit the job permanently. Still other minor factors affecting an employee’s intention to leave the organization. For example, if the work is less repetitive, the turnover intention will be lower; if the work provides an employee a larger room for autonomy, the employee will less likely leave the organization as well (Hackman & Lawler, 1971). Also, regarding work performance, high performers in an organization have lower desire to quit their job (Dreher, 1982). Finally, an individual’s perception of job opportunities and alternatives is related to their turnover intention. If an employee perceived that there are lots of opportunities outside the company, he/she will have a higher intention to leave the job for the alternatives.. 14.

(28) Career Plateau Definition of Career Plateau Ference, Stoner and Warren (1977) considered career plateau to be a natural consequence of the organization structure development. When an individual reaches a point that the possibility of further promotion in the organization is low, he/she is defined as experiencing a plateau in his/her career. Later on Veiga (1981) extended the concept of career plateau to not only focusing on the vertical movement (promotion), but also the horizontal transfer within the organization. However, at this stage, career plateau is still focusing on an individual’s mobility in the organization. Feldman and Weitz (1988) proposed that employees might experience the increase of work responsibilities without actual promotion in the organization. In this case, those employees might still have the chance to grow and develop themselves; therefore, their self-perception of career plateau might be low. Likewise, employees might also be promoted in the organization with given new tasks or responsibilities. Hence, simply judging whether employees are plateaued through hierarchical movement in the organization is not sufficient. Based on these previous studies (Bardwick, 1986; Feldman & Weitz, 1988), Milliman (1992) developed a measurement with two dimensions (job content plateau and hierarchical plateau) to test an individual’s perception of his/her career status.. Antecedents of Career Plateau Individual Factors. Individual factors are often the constraints or limitation of an individual’s mobility and development in the organization. Studies often showed that demographic variables often affect both subject and object career success. For example, Gattiker and Larwood (1990) discovered that people who are plateaued tend to be older than others who continued to make progress in their career. It is 15.

(29) logical that older people are more likely to have longer working years as well as the tenure in the organization. The longer they work the higher chance they have to be plateaued. Education level is also a factor that can influence an employee’s mobility and development. Lorence and Mortimer (1985) pointed out that the higher education background an individual has the greater chance he/she will receive promotion. Other than that, people who have higher education level are viewed as more capable of taking up additional responsibilities; therefore, result in the increase of their job content then lead to their growth. However, the level of education affects more significantly at the entry stage of one’s career. Throughout the time, the effect will become weaker as other factors such as experience will be more a determinant of an individual’s mobility in the organization. Other personal factors such as motivation to learn, career exploration, career planning and job involvement, are also related to career plateau (Allen, Russell, Poteet, & Dobbins, 1999). Some scholars viewed them as the results that are affected by individuals’ personalities. The effects will influence an individual’s attitudes toward receiving new tasks, facing challenges or pursuing a higher rank in the organization and eventually causing he/she to be plateaued or not. Organizational Factors. People facing career plateau is a commonly happened phenomenon caused by the traditional hierarchical structure of the organization. The funnel effect in an organization will naturally occur because of the fewer positions when employees are trying to pursue upper movement, (Near, 1980) not to mention that nowadays, there are more and more horizontal-organizational structures. With fewer hierarchical levels in an organization, employees might seriously confront hierarchical plateau. Moreover, as the upward movement is blocked, employees got stock at the same position and kept on doing the same jobs and task. This will also 16.

(30) cause the employees to be plateaued on the job content aspect.. Consequences of Career Plateau The outcomes of career plateau can be both positive and negative. Some studies showed that employees who faced the career plateau are often the solid citizen with the organization. They are the one who make positive contribution to the company (Bardwick, 1986; Feldman & Weitz, 1988; Ference et al., 1977; Near, 1980; Heilmann, Holt, & Rilovick, 2008). Most findings, however, indicate that career plateau generally has negative impacts on the organization (Allen et al., 1999; Tremblay & Roger, 1993). For instance, the absenteeism of employees happened more often on plateaued ones compared with those still making progress in the organization. Plateaued employees are also less satisfied with their supervisors (Near, 1980, 1985). Other research results proposed that career plateau can also lead to low job satisfaction and organizational commitment; then result in dissatisfying work performance and eventually, lead to an increase of an individual’s turnover intention and actual turnover (Chao, 1990; Milliman, 1992; Tremblay, Roger, & Toulouse, 1995; Allen et al., 1999). Therefore, this study predicts the following: Hypothesis 1: Career plateau will be positively significantly related to employees’ turnover intention.. 17.

(31) The Moderating Effects of Career Anchor Profiles From the previous research analyzed above, the effects of personal factors indeed seemed to happen on both career plateau and turnover intention (Feldman & Weitz, 1988; Guan, Wen, Chen, Liu, Si, Liu, Wang, Fu, Zhang, & Dong, 2014). However, few studies focus on the moderating effect of an individual’s personality or personal factors on the relationship between career plateau and turnover intention (Ettington, 1998; Lee, Huang, & Zhao, 2012; Wen & Liu; 2015). Some evidence was found that inventories used to test an individual’s vocational interest and biographical information blank could be fairly used to predict turnover intention (Porter & Steers, 1973). Individual factors such as personality were also included into the turnover process model (Mobley et al., 1979). Still other studies indicated that personal traits or work orientation do impact on turnover behavior (Steers & Mowday, 1981; Williams & Hazer, 1986; Steel, 2004). Therefore, this study aims to use career anchors developed by Edgar H. Schein (1978) to investigate the influence of career-oriented factors on the relationship between career plateau and turnover intention.. Schein’s Career Anchors Schein (1978) first had the idea of career anchors. He proposed that there is a factor within each individual’s career. The factor not only affects people’s career decision, but also forms the goals that they strive to achieve in their lives. This internal factor is called the career anchor. It is a self-image developed from people’s intelligence, knowledge, value and experiences. This concept will influence people’s expectation and preference when choosing their jobs. It is also the element that people will not give up even when facing a difficult choice. Schein said that at the beginning of people’s career, their self-concepts are still 18.

(32) vague. This is the stage when they learn and develop themselves through their job and the organization they are in. They continuously experience and cultivate themselves so as to recognize what they are interested in, what are their motivation, what they valued the most in life and what advantages and KSAOs they possess. After accumulating work experiences, they will have a higher decision-making power toward choosing their jobs. Then they keep on the learning and self-discovering process. When they are facing new tasks and challenges, they will have the opportunity to find out their potentials. Finally, the self-concept and understanding built up through the process will form a career anchor in their mind. This anchor serves as the guide when people make critical decisions regarding their career. In this study, Schein presented five categories of career anchors, which are technical/functional competence, managerial competence, creativity, autonomy and security. Later, Schein in 1990 increase the career anchors into eight categories. Meanwhile, managerial insights, such as types of jobs, compensation and benefits, and promotion, are also embedded into the descriptions. The eight categories are as follow: Technical / Functional Competence. People with this type of anchor will not give up the opportunity to apply the skills they choose in that certain area. They like the feeling of being the experts in the field and will gain satisfaction from the technical or functional work they are doing. They can also enjoy managing others in that certain field. However, they will avoid general management position for that managing others is not the purpose of their career. General Managerial Competence. People with this anchor tend to pursue higher level in the organization because position at a certain level enable them to put their efforts into managing cross functional departments and coordinate them for a greater performance. They are willing to take up larger responsibility, dedicate 19.

(33) themselves to the organization and identify their work with the success of the organization. Autonomy / Independence. People with this career never give up the chance to control over their own work. They want to feel free on what to do, how they do it and the pace of doing the job. They often choose self-employment or freelance for job because of the high autonomous. Security / Stability. People with this anchor value the employment security above all other factors. Their top priority is to make sure the stability of their job in the organization. It can be either on financial or geographical aspects. This type of people is less concerned with the job content not the rank in the organization. They are willing to do whatever the employers ask to accept any arrangement as long as they secure and stabilize their job. Entrepreneurial Creativity. People with this anchor desired to create an organization on their own. They want to overcome the obstacles with their ability and are willing to take up all the risk of establishing their enterprise. They might start with working in other people’s organizations to learn the skills needed and to assess future opportunities. However, they will leave the organization as soon as they feel that they are ready to handle the mission to set up their company. Service / Dedication to a Cause. People with this anchor tend to pursue work opportunities that they think are of value and will make the world a better place. They will search for jobs that solve the environmental problems, cure diseases with new products, create harmony in the world, and so on. Pure Challenge. People who fall into this category like to find solutions to unsolved problems, to win over tough competitions and to conquer all difficulties and barriers. For them the crucial reason for them to pursue a job is to face challenges one after another, and successfully win out all of them. Once the 20.

(34) challenges stop existing, they felt bored about the work immediately. Lifestyle. People who possess this anchor will never give up the situations that enable them to balance the personal needs, family demands and the requirement of their career. To them, a successful career is not simply about being promoted to a high level or earning a fortune, it’s more of an integration of every part of their life. Therefore, the job they are searching for should be flexible enough to make arrangement whenever needed.. Career Anchor Profiles Despite the fact that the original design of career anchors is to find out one dominant anchor out of eight for each individual, the researcher believed the secondary anchors are also of great import when studying individuals’ career-oriented factors that influence their decision-making process. Past studies also support the idea of individuals possessing multiple career anchors which may even form several different profiles. Igbaria, Greenhaus and Parasuraman (1991) applied the career anchor measurement on employees working in the management information systems and found that instead of finding merely one dominant anchor, three anchors were identified: technical / functional competence, general managerial competence and entrepreneurial creativity. Suutari and Taka (2004) studied on managers and leaders with global careers who engaged in international tasks and business. They specifically focused on the career anchor(s) that these participants based on when they had to make decisions. The result indicated that most managers and leaders consider themselves using two or three career anchors instead of one dominant anchor when dealing with their daily work. The major anchors identified were managerial competence and pure challenge. Singh, Bhattacharjee and Kodwani 21.

(35) (2009) utilized the career anchors on executives in engineering sectors for the purpose of facilitating career management and planning. The result in their study also showed multiple anchors possessed by the participants, which were pure challenge, service / dedication to a cause and lifestyle. Still other studies all demonstrated results of individuals having more than one dominant career anchors at the same time. These research proved what Feldman and Bolino (1996) proposed: individual could have multiple career anchors at the same time under different conditions, to be true. Therefore, in this research, the researcher proposed the possibility of career anchor profiles existing that rather than either belonging or not belonging to a certain career anchor category, individuals vary along a continuum of career anchors. In addition, the difference profile patterns that represented individuals’ varied career preferences would affect their reaction on turnover intention when they faced a plateau situation in their career. Therefore, Hypothesis 2 is proposed as followed. Hypothesis 2: Career anchor profiles will moderate the positive relationship between career plateau and turnover intention.. 22.

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(37) CHAPTER III. RESEARCH METHOD. In this chapter, the research framework, hypotheses and the methodology were presented. It outlined the research procedure, sample of the study, instrument used, data collection procedure and statistical methods for data analysis.. Research Framework The research framework was developed on the basis of the purpose of this study, and the literature reviewed in the previous chapter. The figure presented in Figure 3.1. shows the variables of this study. According to the hypotheses aforementioned, this study aimed to explore the relationship between career plateau and turnover intention, and demonstrate how people with diverse career anchors react differently when facing a plateaued situation in their career.. Figure 3.1. Research framework.. 23.

(38) Two hypotheses were derived from the research framework of this study. H1: Career plateau will be positively significantly related to employees’ turnover intention. H2: Career anchor profiles will moderate the positive relationship between career plateau and turnover intention.. Research Procedure The research procedure included the eight steps shown in Figure 3.2. below. At the beginning of this research, the researcher was interested in one specific phenomenon. The researcher then reviewed the previous studies and came up with a topic for this study. After the research topic was determined, the researcher thought about the purpose and significance of this research, trying to find out the questions and answers the study aimed to discover. Next, the researcher developed the research framework. Based on the framework, the researcher then searched for appropriate instruments developed from previous researchers and adopted them in the present study. The research procedure was then designed. The selected instruments were compiled and organized into a questionnaire, which went through the expert review and pilot test to insure the validity and reliability. After the instruments were tested, the questionnaires were distributed to the research targets for data collection. Finally, the hypotheses were tested and the results were presented at the end of the study.. 24.

(39) Determine Research Topic Conduct Literature Review Develop Research Purpose and Questions Construct Research Framework. Design Research Procedure Develop Research Instrument Conduct Expert Review and Pilot Test Conduct Data Collection Analyze Data Conclude Research Results Figure 3.2. Research procedure.. 25.

(40) Research Design This study adopted the quantitative research method to examine the relationship among career plateau, turnover intention and the moderating effect of career anchors. A questionnaire was used in this research to obtain data from employees in different industries in Taiwan. Before the data collection process, the questionnaire was examined by experts to insure content validity of the scales used in this study. Finally, statistical analysis methods were adopted to insure construct validity and reliability of the measurement and to test the abovementioned hypotheses.. Research Sample and Data Collection The targets of this study were the current employees in Taiwan. They worked in all kinds of industries were full-time employees who had been working in private sectors for at least one year in the same position in the organizations. During the data collection, the researcher constantly monitored the distribution of the collected data through the demographics to make sure that the numbers of responses received from all industries were similar so as to present more general results that apply to all industries. The data collection process started from April 17th to April 30th and was conducted through online questionnaires. The link of the questionnaire was sent through email to people that the researcher has personal contact with. These people were either current employees in the company or the managers who assisted in the distribution of the online questionnaires. In addition, the link was posted on several social media websites to reach a wider range of targets. The total number of questionnaires collected was 533 and the final number of the valid responses was 412 (valid rate: 77%).. 26.

(41) Sample Profile After reviewing the final valid responses, the following are the demographics of the sample in this study. A total of 224 (54.4%) responses were from females and 188 (45.6%) from male participants. Moving on to the industries the participants come from: 76 (18.4%) of them were from the real estate industry, 58 (14.1%) service, 52 (12.6%) manufacturing, 48 (11.7%) financial and 178 (43.2%) other different industries. Regarding participants’ education level, 182 (44.2%) had a bachelor degree as their highest education level, 107 (25.9%) a master degree or above and the rest (123, 29.8%) a degree of vocational school, high school or under. As to respondents’ position within their company, 190 (46.1%) were at the entry level, 74 (18%) low-level managers, 72 (17.5%) middle-level managers and 37 (9%) top-level managerial positions. Finally, 244 (59.2%) of the respondents were married and 145 (35.2%) were single. Detail information is shown in Table 3.1. Table 3.1. Demographics of the Sample (n=412) Frequency. Percentage (%). Male Female. 188 224. 45.6 54.4. Below 30 years old 31-40 years old 41-50 years old 51-60 years old. 95 105 130 73. 23.1 25.4 31.6 17.7. above 61 years old. 9. 2.2. 123 182 104 3. 29.9 44.2 25.2 0.7. Demographics. Category. Gender Age. Education Level High School, Vocational School Bachelor Degree Master Degree PhD Degree. (Continued). 27.

(42) Table 3.1. (Continued) Frequency. Percentage (%). Married Single Divorced Widowed Cohabitate. 244 145 15 1 7. 59.2 35.2 3.6 0.2 1.7. Employee First Level Manager. 190 74. 46.1 18.0. Mid-Level Manager Top Level Manager Others. 72 37 39. 17.5 9.0 9.5. 1~5 years. 206. 50. 6~10 years 11~15 years 16~20 years Above 21 years. 77 46 30 53. 18.7 11.2 7.3 12.9. 1~5 years 6~10 years. 90 58. 21.8 14.1. 11~15 years 16~20 years Above 21 years. 55 61 148. 13.3 14.8 35.9. No dependent. 128. 31.1. 1~2 dependents More than 2 dependents. 193 91. 46.8 22.1. Demographics. Category. Marital Status. Position. Tenure. Career Year. Number of Dependents. (Continued). 28.

(43) Table 3.1. (Continued) Frequency. Percentage (%). Real estate Other services Manufacturing Financial and insurance service Education Professional, scientific and technical service Wholesale and retail trade. 76 58 52 48 30 24 21. 18.4 14.1 12.6 11.7 7.3 5.8 5.1. Information and communication Construction Human health and social work Accommodation and food service. 21 19 19 12. 5.1 4.6 4.6 2.9. Agriculture, forestry and fishing Arts, entertainment and recreation Transportation and storage Administrative and support service Electricity, gas, steam and air conditioning supply. 9 9 8 3. 2.2 2.2 1.9 0.7. 2. 0.5. Mining and quarrying. 1. 0.2. Demographics. Category. Industry. Questionnaire Design The questionnaire included the measurement that measured the variables in the research framework. It consisted of four sections, three research variables parts and one demographic section. These measurements were found through the previous studies and were originally developed in English. However, the targets of this study were Taiwanese employees who speak Chinese, so the questionnaire was translated into Chinese. After the translation, the Chinese version was examined by experts who had expertise in Chinese and English to back translate and make sure the meanings of the items remained the same. After finalizing the questionnaire, the pilot test was conducted to make sure the initial validity and reliability.. 29.

(44) According to Podsakoff and Organ (1986) the common method variance (CMV) might affect the result of this study because the instruments used to measure all variables were self-reports from the same source. In order to minimize the effect of CMV, 7-point and 5-point Likert-type scale and a 6-point frequency scale were utilized on career plateau, turnover intention and career anchors respectively. Meanwhile, the order of instruments was re-arranged so that the respondents answered the outcome variable first than the independent variable. The moderating variable and personal information were answered at last.. Measurement The measurements used in this study are described below. The complete questionnaire can be seen in the Appendix: Questionnaire.. Career Plateau Milliman (1992) first developed a two-dimensional instrument (Job content plateau and Hierarchical Plateau) to measure an individual’s perceived career plateau. The version this study utilized was the adapted version of Milliman (1992) which was presented in Allen et al. (1999). The scale consists of two dimensions: job content plateau and hierarchical plateau. In each dimension, six items were rated on a 7-point Likert scale ranging from “1” “Totally Disagree” to “7” “Totally Agree” in order to measure an individual’s self-perception of career plateau. A sample item for Job Content Plateau is: “My job tasks and activities have become routine for me.” A sample item for Hierarchical Plateau is: “I am unlikely to obtain a much higher job title in the Organization.” Some items were reverse coded to insure the reliability of the responses. A sample reverse coded item is: I expect to be constantly challenged in my job. The Cronbach Alpha for job content plateau and hierarchical 30.

(45) plateau were 0.83 and 0.85 respectively in Allen et al.’s (1999) research.. Turnover Intention To measure the respondents’ intention to leave their current job, the scale from Wayne, Shore and Liden (1997) was adopted. There were five items in total and each item was rated on a 5-point Likert scale ranging from “1” “Strongly Disagree” to “5” “Strongly Agree”. A sample item is: “I am actively looking for a job outside [company name]”. The Cronbach Alpha reported in Wayne et al. (1997) was 0.89.. Career Anchors The instrument used to test the moderating effect in this framework was the career orientation inventory developed by Schein (2006). There were eight dimensions and each contained 5 items. The following shows the eight categories and a sample item for each. Technical /Functional Competence: “I want to be so good at what I do that others will always seek my expert advice.” General Managerial Competence: “I will feel successful only if I become a high-level general manager in some organization.” Autonomy/Independence: “I will feel successful in my career only if I achieve complete autonomy and freedom to define my work.” Security/Stability: I would not stay in an organization that would give me assignments that would jeopardize my job security. Entrepreneur Creativity: “I dream of starting up and building my own business.” Service/Dedication to a Cause: “I dream of being in a career that makes a real contribution to humanity and society.” Pure Challenge: “I prefer work opportunities that strongly challenge my 31.

(46) problem-solving and competitive skills.” Lifestyle: “I have always sought out work opportunities that minimize interference with my personal and family concerns.” The 40 items from eight dimensions were rated based on a 6-point self-reported frequency ranging from “1” “Never True for me” to “6” “Always True for me”. The use of an even number scale was to avoid the neutralization of responses so as to have a more distinguished categorization. The Cronbach Alpha of this instrument was reported from 0.77 to 0.81 by Coetzee and Schreuder (2011). Control Variables The following demographic variables are selected from the previous studies. They serve as the control variables in the current study. Gender. From the past studies, Valcour and Tolbert (2003) found that females tend to have higher turnover rate over males. Therefore, in this study, the respondents were asked to answer their gender. Age. According to the previous literatures, employees’ age seems to influence their turnover intention (Hayes, 2015). Therefore, in this study, the respondents were asked to fill in their birth year (e.g.,1992) so as to calculate their age for the analysis. Education Level. An individual’s education level affects their career plateau and turnover intention as well even though the effect on turnover intention was inconclusive (Mobley, 1982; Cotton & Tuttle, 1986). Hence, the researcher intended to collect the information of the participants’ education level so as to do further analysis. The respondents were asked to choose among “Under High School or vocational school”, “Bachelor’s degree”, “Master’s degree” and “Doctorate degree” to indicate their education level.. 32.

(47) Marital Status. Koh and Goh (1995) indicated that the marital status and the number of dependents have great impact on individuals’ intention to leave. They proposed that people who were married were less likely to quit their jobs. Therefore, in this study, the researcher asked the respondents to answer whether they were “married”, “Divorced”, “Single”, “Widowed” and “Cohabitate”. Number of Dependents. According to Steel and Lounsbury (2009), family responsibility was one of the main factors that influence employees’ intention to leave the organization. Participants were asked to answer how many dependents they had.. Demographic Variables Tenure of Current Job. An individual’s tenure of current job might influence their perception toward career plateau. Therefore, the respondents were asked to fill out an open-ended question of the years they have been working at the present job and throughout their lives. Total Working Years. The total working years of an employee may affect their intention to leave the organizations. The longer time people work, their perception of career plateau and their intention to leave might be changed. Industry type. In order to examine the relationship among career plateau, turnover intention and career anchors in different industries, the respondents were asked to report the industries they were currently working in. The 19 industry categories: Agriculture, forestry and fishing, Mining and quarrying, Manufacturing, Electricity, gas, steam and air conditioning supply, Water supply; sewerage, waste management and remediation activities, Construction, Wholesale and retail trade; repair. of. motor. vehicles. and. motorcycles,. Transportation. and. storage,. Accommodation and food service activities, Information and communication, 33.

(48) Financial and insurance activities, Real estate activities, Professional, scientific and technical activities, Administrative and support service activities, Public administration and defense; compulsory social security, Education, Human health and social work activities, Arts, entertainment and recreation and Other service activities are from the Directorate-General of Budget, Accounting and Statistics, Executive Yuan in Taiwan (2016).. 34.

(49) Validity and Reliability Tests Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were both used to test the construct validity of the research. EFA was first utilized during pilot testing. According to the EFA result, the item translation and the sequence of measures in the questionnaire were slightly modified before data was collected for the main study. After the final valid responses were determined, CFA was conducted. However, since the CFA resulted in less-than-satisfactory fit, minor modification to the measurement was performed. The researcher relied on EFA to modify the measurement, but cross validated the modification using CFA with data from a different sample. To complete this procedure, the sample was randomly split into half. The first half of the data was analyzed through EFA in SPSS. According to Costello and Osborne (2005), a factor loading above .4 is acceptable. However, in order to retain only those items that better represent the construct, the criterion of the factor loading for an item was set at the minimum of .65 and no cross loading to ensure the quality of the scales was good. After the modification, the new measurement model went through a cross-validation test by entering the second data set from the split sample in a CFA. Both career plateau and turnover intention measurement successfully went through cross validation process mentioned above. However, since the career anchors scale was designed as a formative measurement instead of a latent one, and that the AMOS CFA technique does not handle well on formative measures, the validity of the career anchors scale was tested using only EFA. The results are as followed.. 35.

(50) Exploratory Factor Analysis (EFA) Result Table 3.2. Table 3.3. and Table 3.4. show the EFA result of turnover intention, career plateau and career anchors. The finalized dimensions and the item deleted are indicated in the tables. Table 3.2. Exploratory Factor Analysis (EFA): Turnover Intention Factors Item 1. Final Dimension. TI3. .911. TI. TI4. .831. TI. TI1. .812. TI. TI2. .798. TI. TI5. .533. Items Deleted. Deleted. Note. Extraction Method: Principal Component Analysis. Rotation Method: Varimax. TI: Turnover Intention.. 36.

(51) Table 3.3. Exploratory Factor Analysis (EFA): Career Plateau Factors Item 1. 2. Final Dimension. Items Deleted. JCP6. .904. JCP. JCP2. .881. JCP. JCP5. .873. JCP. JCP1. .855. JCP. JCP4. .738. JCP. HP2. .631. .439. Deleted. HP6. .500. .499. Deleted. HP5. .899. HP. HP4. .845. HP. HP1. .805. HP. HP3. .781. HP. JCP3. .503. Deleted. Note. Extraction Method: Principal Component Analysis. Rotation Method: Varimax. JCP: Job Content Plateau; HP: Hierarchical Plateau; TI: Turnover Intention.. The Kaiser-Meyer-Olkin Measure of Sampling Adequacy for EFA of turnover intention and career plateau were .799 and .835. The Bartlett’s tests of sphericity were both significant. These indicate that the data was suitable for the EFA analysis. One factor in turnover intention and two factors in career plateau were extracted with the eigenvalue larger than 1, which fit the original designs of the scales: one. 37.

(52) dimension for turnover intention and two for career plateau. Those items with a factor loading lower than .65 or with cross loading problems were deleted; therefore, the remaining numbers of items were four for turnover intention; five for job content plateau and four for hierarchical plateau. Table 3.4. Exploratory Factor Analysis (EFA): Career Anchors Factors Item 1. 2. 3. 4. 5. 6. 7. 8. Final. Items. Dimension. Deleted. 9. CHA2 .815. CHA. CHA4 .812. CHA. CHA3 .789. CHA. CHA1 .764. CHA. CHA5 .763. CHA. ENT5. .865. ENT. ENT1. .841. ENT. ENT2. .826. ENT. ENT4. .795. ENT. ENT3. .510. Deleted. TEC1. .729. TEC. TEC2. .712. TEC. TEC3. .693. TEC. TEC5. .629. Deleted. GEN1. .550. Deleted (Continued). 38.

(53) Table 3.4. (Continued) Factors Item 1. 2. 3. 4. 5. 6. 7. 8. Final. Items. Dimension. Deleted. 9. LIF3. .805. LIF. LIF2. .788. LIF. LIF1. .730. LIF. LIF4. .708. LIF. LIF5. .637. Deleted. STA3. .897. STA. STA4. .829. STA. STA1. .750. STA. STA2. .649. Deleted. STA5. .534. Deleted. SER4. .805. SER. SER3. .788. SER. SER1. .712. SER. SER2. .651. SER. SER5. .568. Deleted. AU3. .779. AU. AU2. .765. AU. AU4. .692. AU. AU1. .691. AU. AU5. .456. Deleted (Continued). 39.

(54) Table 3.4. (Continued) Factors Item 1. 2. 3. 4. 5. 6. 7. 8. Final. Items. Dimension. Deleted. 9. GEN4. .889. GEN. GEN3. .848. GEN. GEN5. .675. GEN. GEN2. .518. TEC4. Deleted .723. Deleted. Note. Extraction Method: Principal Component Analysis. Rotation Method: Varimax. CHA: Pure Challenge; ENT: Entrepreneurial Creativity; SER: Service/Dedication to a Cause. STA: Stability/Security; TEC: Technical/Functional Competence; LIF: Lifestyle; AU: Autonomy/Independence; GEN: General Management Competence.. As to career anchors, the Kaiser-Meyer-Olkin Measure of Sampling Adequacy for EFA was .929. The Bartlett’s test of sphericity was also significant. Nine factors were extracted according to the result. However, TEC4 itself stands alone in the ninth factor and was deleted. In addition, items with factor loading lower than .65 or cross loaded were deleted as well. The final eight-factor structure was the same as the initial development of the scale and the number of the remaining items was 30.. Confirmatory Factor Analysis (CFA) Base on the EFA result of career plateau and turnover intention, the remaining items were used to conduct CFA with data from the other half of the randomly split. 40.

(55) sample. The purpose was to see whether the modified measurement model did have a satisfactory model fit. The modification indices in AMOS output that this study selected include x2/df, SRMR, CFI, RMSEA. Base on Hooper, Coughlan and Mullen (2008), these indices were appropriate indicators that should be able to point out the goodness of model fit in this study. The criteria of good model fit indices are presented in Table 3.5. Table 3.5. Indices of Model Fits Fit Indices. Good Fit. Acceptable Fit. x2/df. 2~5. <5. SRMR. <0.05. ≤0.08. CFI. ≥0.95. GFI. ≥.90. ≥.80. AGFI. ≥.90. ≥.80. RMSEA. <0.08. <0.1. CR. >.7. AVE. >.5. Note: Adapted from “Structural Equation Modelling: Guidelines for Determining Model Fit,” by D. Hooper, J. Coughlan and M. Mullen, 2008, Electronic Journal of Business Research Method, 6(1), p. 53-60. Copyright 2008 by the Academic Conferences Ltd. and “Multivariate Data Analysis” by Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L., 1998., fifth ed. Prentice Hall, New Jersey.. 41.

(56) Figure 3.3. Career plateau and turnover intention model.. CFA for career plateau and turnover intention Base on the EFA result, nine items measuring the career plateau and four for turnover intention were used as the measurement model. The model and the standardized regression weights are shown in Figure 3.3. The goodness of fit indices of career plateau and turnover intention model is presented in Table 3.5.. 42.

(57) Table 3.6. Career Plateau and Turnover Intention Model Fit Summary Model. X2/df. CFI. GFI. AGFI. SRMR. RMSEA. CP and TI. 2.785. .936. .87. .812. .0929. .095. Composite Reliability (CR). Average Variance Extracted (AVE). Job Content Plateau. 0.929. 0.727. Hierarchical Plateau. 0.923. 0.750. Turnover Intention. 0.904. 0.703. After examining the model fit summary in Table 3.6. and the criteria for good model fit in Table 3.5., the model adopted in this research had an acceptable fit. Therefore, the following statistical analysis utilized the measurement model proposed above.. Common Method Variance (CMV) Because all instruments used in this research were self-reported, the potential problem of common method variance needed to be inspected. Harman’s one factor analysis was examined to make sure there was no serious CMV problem. The total variance explained in the first component of Eigenvalue greater than one was 24.89%, which was far below the 50% criteria. Therefore, the CMV problem was not a potential threat to this study.. 43.

(58) Cronbach’s Alpha After the model was set, Cronbach’s alpha reliability test was performed to make sure that the measurement scales adopted in this research were reliable. According to Nunnally (1978), the Cronbach’s alpha above .70 was considered reliable. The Cronbach’s alpha is demonstrated in Table 3.7. and the results were all above .70, which mean that the scales utilized in this research were reliable. Table 3.7. Cronbach’s Alpha Measurement Scale. Coefficeint Alpha. Career plateau. .76. Job Content Plateau. .92. Hierarchical Plateau. .88. Turnover Intention. .87. Career Anchors. .93. Autonomy / Independence. .83. Security / Stability. .85. Technical / Functional Competence. .82. General Managerial Competence. .86. Entrepreneurial Creativity. .93. Service / Dedication to a Cause. .90. Pure Challenge. .93. Lifestyle. .86. 44.

(59) CHAPTER IV. DATA ANALYSIS AND FINDINGS. In this chapter, the correlation analysis was used to gain a preliminary knowledge of the relationship between variables. In addition, hierarchical regression and K-mean cluster analysis were conducted to test the hypotheses proposed in this study.. Correlation Analysis Mean, Standard deviation, Cronbach’s alpha and the correlation between variables are presented in Table 4.1. Starting from the control variables, as literature stated, Age was significantly and negatively correlated with turnover intention (r=-.33, p<.01), meaning that the older an employee is, the less likely they will think about quitting. Marital status and the number of dependents were both significantly and negatively correlated with turnover intention as well (r=-.26, p<.01; r=-.23, p<.01). It means that when people are married or when they have more dependents relying on them, their intention to leave their job will be lower. When employees are managers in their companies, they tend to stay at the position rather than leaving (r=-.13, p<.05). In addition, employees’ education level was significantly and positively correlated with turnover intention. This indicated that people with higher degrees are more likely to think about leaving their company. Pearson’s Correlation was also used to examine the relationship between independent variables, dependent variables and moderators. In this research, the data did show that career plateau, and its two dimensions: job content plateau and hierarchical plateau were significantly and positively correlated with turnover intention (r=.37, p<.01; r=.16, p<.01; r=.35, p<.01). These suggested that when employees meet a stagnant situation no matter on their job content or their position. 45.

(60) in companies, they tend to have a higher intention to leave the organization that makes them stuck at the current situation. However, the results of Pearson’s correlation were inconclusive and did not test the hypothesized effects of career plateau on turnover intention. Therefore, hierarchical regression was utilized in the following sections to test the proposed research hypotheses.. 46.

(61) Table 4.1. Mean, Standard Deviation, Correlation and Reliability among Research Variables (n=412) Mean. Std.. 1. 1. Turnover Intention. 2.77. 1.01. (.87). 2. Career Plateau. 3.67. 0.89. .37**. (.76). **. .73**. (.92). .61**. -.09. 3. Job Content Plateau. 3.33. 1.27. .16. 4. Hierarchical Plateau. 4.10. 1.37. .35**. 2. **. 5. Autonomy / Independence. 4.65. 1.05. .01. -.18. 6. Stability / Security. 4.68. 1.07. -.0 7. .13**. 7. Technical / Functional. 4.80. 1.02. 8. General Management. 3.48. 1.26. 9. Entrepreneurial Creativity. 3.98. 10. Service / Dedication. **. 3. -.23. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. **. .01. (.83). .12*. .25**. (.85). -.03. .52. **. .37**. (.82). -.08. -.21. .07. -.07. -.03. -.07. .24**. .21**. .21**. (.86). 1.38. .16**. -.00. .00. -.01. .34**. .19**. .26**. .51**. (.93). 4.61. 1.06. -.08. -.14** -.18** .00. .40**. .28**. .55**. .27**. .42**. (.90). 11. Pure Challenge. 4.32. 1.12.. -.09. -.15** -.16** -.03. .39**. .17**. .54**. .28**. .45**. .64**. (.93). 12. Lifestyle. 4.88. 0.97. -.00. -.07. -.17** .10*. .41**. .44**. .46**. .15**. .28**. .48**. .36**. (.86). 13. Gender. 0.54. 0.50. .01. .00. -.00. .00. .08. .13**. .14**. -.15** -.09. .06. .02. .03. 14. Age. 40.63. 10.58. -.33** .02. 0.05. -.03. .00. .24**. .12*. .13**. .14**. .24**. .16**. .08. -.12*. 15. Education Level. 2.85. 0.96. .15**. .01. -.10*. .14**. -.08. -.14** -.14** .02. -.08. -.06. -.07. -.10. -.23** -.20**. 16. Managerial Position. 0.44. 0.50. -.13*. -.14** -.15** -.03. .06. -.01. .18**. .14**. .05. .11*. .17**. .02. -.23** .35**. .12*. 17. Marital Status. 0.59. 0.49. -.26** -.03. .04. -.08. -.04. .12*. .04. .14**. .14**. .14**. .05. .04. -.15** .62**. -.14** .23**. 18. Number of Dependents. 1.50. 1.32. -.23** .01. .07. -.06. .02. .09. .03. .11*. .14**. .12*. .09. .01. -.14** .44**. -.16** .16**. Competence. Note: **. Correlation is significant at the 0.01 level (2-tailed). Gender: 0= Male; 1= Female. 17. (.88) **. .06 -.24. 4. *. Correlation is significant at the 0.05 level (2-tailed).. 0= Non-Managerial Positions; Managerial Position: 1= Managerial Positions. Marital status: 0=Non-Married; 1=Married. Education Level: 1=High school or under; 2=Vocational School; 3=Bachelor degree; 4=Master degree; 5=PhD degree Numbers in the parentheses represent the values of Cronbach’s Alpha.. 47. .58**. 18.

(62) Cluster Analysis In this research, cluster analysis was conducted to investigate the distinct segments of the participants. K-mean cluster algorithm was utilized to obtain three final clusters, which were later on named as High-Career Pursuer, Mid-Career Pursuer and Low-Career Pursuer. The final cluster centers are shown in Table 4.2. and Figure 4.1. demonstrates the line graph of the three clusters. Table 4.2. Final Cluster Centers Cluster Autonomy / Independence Stability / Security Technical / Functional Competence General Management Competence Entrepreneurial Creativity Service / Dedication Pure Challenge Lifestyle. Low-Career Pursuer. High-Career Pursuer. Mid-Career Pursuer. 2.47 3.23 2.46 2.19 1.71 2.11 2.05 3.09. 5.09 4.99 5.27 4.18 5.03 5.21 4.93 5.30. 4.45 4.53 4.59 2.94 3.23 4.29 3.98 4.65. K-mean Cluster Analysis. Final Cluster Centers. 6.00 5.00 4.00 3.00 2.00 Low Career Pursuer. 1.00. High Career Pursuer. 0.00. Mid Career Pursuer. Figure 4.1. K-mean cluster analysis.. 48.