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

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!

I

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

II

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

III

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

IV

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

V

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

1

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

2

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

3

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.

4

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,

5

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.

6

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.

7

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).

8

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

9

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.

10

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

11

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.

12

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

13

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

14

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.

15

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

16

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

17

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.

18

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

19

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

20

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

21

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

22

(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.

23

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.

24

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.

25

Figure 3.2. Research procedure.

Conclude Research Results

Analyze Data

Conduct Data Collection

Conduct Expert Review and Pilot Test

Develop Research Instrument

Design Research Procedure

Construct Research Framework

Develop Research Purpose and Questions

Conduct Literature Review

Determine Research Topic

26

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%).

27

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)

Demographics Category Frequency Percentage

(%) Gender Male 188 45.6

Female 224 54.4

Age Below 30 years old 95 23.1

31-40 years old 105 25.4

41-50 years old 130 31.6

51-60 years old 73 17.7

above 61 years old 9 2.2

Education Level High School, Vocational School 123 29.9

Bachelor Degree 182 44.2

Master Degree 104 25.2

PhD Degree 3 0.7

(Continued)

28

Table 3.1. (Continued)

Demographics Category Frequency Percentage

(%) Marital Status Married 244 59.2

Single 145 35.2

Divorced 15 3.6

Widowed 1 0.2

Cohabitate 7 1.7

Position Employee 190 46.1

First Level Manager 74 18.0

Mid-Level Manager 72 17.5

Top Level Manager 37 9.0

Others 39 9.5

Tenure 1~5 years 206 50

6~10 years 77 18.7

11~15 years 46 11.2 16~20 years 30 7.3

Above 21 years 53 12.9

Career Year 1~5 years 90 21.8

6~10 years 58 14.1

11~15 years 55 13.3 16~20 years 61 14.8 Above 21 years 148 35.9 Number of Dependents

No dependent 128 31.1

1~2 dependents 193 46.8

More than 2 dependents 91 22.1 (Continued)

29

Table 3.1. (Continued)

Demographics Category Frequency Percentage

(%) Industry Real estate 76 18.4

Other services 58 14.1

Manufacturing 52 12.6

Financial and insurance service 48 11.7

Education 30 7.3

Professional, scientific and technical service 24 5.8

Wholesale and retail trade 21 5.1

Information and communication 21 5.1

Construction 19 4.6

Human health and social work 19 4.6

Accommodation and food service 12 2.9

Agriculture, forestry and fishing 9 2.2

Arts, entertainment and recreation 9 2.2

Transportation and storage 8 1.9

Administrative and support service 3 0.7

Electricity, gas, steam and air conditioning supply

2 0.5

Mining and quarrying 1 0.2

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.

30

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

31

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

32

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.

33

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,

34

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).

35

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.

36

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

Item Factors

1 Final Dimension Items Deleted

TI3 .911 TI

TI4 .831 TI

TI1 .812 TI

TI2 .798 TI

TI5 .533

Deleted

Note. Extraction Method: Principal Component Analysis. Rotation Method:

Varimax. TI: Turnover Intention.

37

Table 3.3.

Exploratory Factor Analysis (EFA): Career Plateau

Item Factors

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

38

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

Item

Factors

1 2 3 4 5 6 7 8 9 Final

Dimension

Items

Deleted

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)

39

Table 3.4. (Continued)

Item

Factors

1 2 3 4 5 6 7 8 9 Final

Dimension

Items

Deleted

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)

40

Table 3.4. (Continued)

Item

Factors

1 2 3 4 5 6 7 8 9 Final

Dimension

Items

Deleted

GEN4

.889

GEN

GEN3

.848

GEN

GEN5

.675

GEN

GEN2

.518

Deleted

TEC4

.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

41

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.

42

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.

43

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.

44

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

45

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

46

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.

47

Table 4.1.

Mean, Standard Deviation, Correlation and Reliability among Research Variables (n=412) Mean Std. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

1. Turnover Intention 2.77 1.01 (.87)

2. Career Plateau 3.67 0.89 .37** (.76)

3. Job Content Plateau 3.33 1.27 .16** .73** (.92)

4. Hierarchical Plateau 4.10 1.37 .35** .61** -.09 (.88)

5. Autonomy / Independence 4.65 1.05 .01 -.18** -.23** .01 (.83)

6. Stability / Security 4.68 1.07 -.0 7 .13** .06 .12* .25** (.85)

7. Technical / Functional 4.80 1.02 -.08 -.21** -.24** -.03 .52** .37** (.82)

8. General Management

Competence

3.48 1.26 .07 -.07 -.03 -.07 .24** .21** .21** (.86)

9. Entrepreneurial Creativity 3.98 1.38 .16** -.00 .00 -.01 .34** .19** .26** .51** (.93)

10. Service / Dedication 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** .58**

Note: **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).

Gender: 0= Male; 1= Female 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.

48

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

Low-Career Pursuer High-Career Pursuer Mid-Career Pursuer

Autonomy / Independence 2.47 5.09 4.45 Stability / Security 3.23 4.99 4.53 Technical / Functional Competence 2.46 5.27 4.59 General Management Competence 2.19 4.18 2.94 Entrepreneurial Creativity 1.71 5.03 3.23 Service / Dedication 2.11 5.21 4.29 Pure Challenge 2.05 4.93 3.98 Lifestyle 3.09 5.30 4.65

Figure 4.1. K-mean cluster analysis.

0.00

1.00

2.00

3.00

4.00

5.00

6.00

Fina

l Clu

ster

Cen

ters

K-mean Cluster Analysis

Low Career Pursuer

High Career Pursuer

Mid Career Pursuer

49

(1) The Low-Career Pursuer: Participants in this cluster scored relatively lower

than the other two clusters on all eight anchors. Their average age was 33.53 years old

and their career year was 8.42, which were both the lowest among the clusters.

Among them, 57.9% were entry-level employees and 26.3% were at the first-level

managerial positions, meaning that these participants were either not interested in

pursuing a higher career or they were still at the very start of their career. The latter

case suggested that they were still exploring in their career path and do not know what

were the essentials they want to pursue. From the pattern, it can be noted that

employees in this cluster valued more on the stability and job security, as well as the

work-life balance in their career.

(2) The Mid-Career Pursuer: In this cluster, the participants have their scores of

8 anchors between the Low-Career and High-Career cluster. The pattern looked

similar to those in High-Career cluster; however, they scored relatively low in the

general management competence and entrepreneurial creativity. Their average age

was 39.51 and the career year was 15.26. A 52.9% of these employees were in the

non-managerial positions; 18.6% were first level managers; 15.2% were mid-level

managers and 6.4% are in high managerial positions. These participants had a better

understanding about what they wanted for their career and knew quite well that they

did not want to or were not ready to be general managers or create their own business.

(3) The High-Career Pursuer: As to people classified as High-Career Pursuers,

they tended to pursue as many anchors as they can. However, the result still shows

that people would rather be technical or functional professionals in specific domain

than being at general managerial positions. Their average age was 42.55 and the

average career year was 18.16. Among all participants in this cluster, only 37.6% were

not in managerial positions; 16.4% were first level managers; 21.7% were in

mid-level managerial positions and 12.7% were high level managers. The result

suggested that most of these people had a relatively mature career and they wanted to

attend to each and every aspect of their career.

The cluster profiles are shown in Table 4.3.

50

Table 4.3.

Cluster Profiles

Clusters

Low-Career

Pursuer Mid-Career

Pursuer High-Career

Pursuer n 19 204 189

Gender Male 52.6% 43.1% 47.6% Female 47.4% 56.9% 52.4% Mean Age 33.53 39.51 42.55 Average Career Year 8.42 15.26 18.16 Average Number of Dependent 1.37 1.31 1.72 Marital Status Married 63.2% 54.9% 66.1% Not Married 36.8% 45.1% 33.9% Education Level High School or under 5.3% 9.8% 15.3% Vocational School 26.3% 13.7% 21.2% Bachelor Degree 31.6% 51.5% 37.6% Master Degree or above 36.8% 25% 25.9% Position

Non-Managerial 57.9% 52.9% 37.6%

First Level Manager 26.3% 18.6% 16.4%

Mid-Level Manager 0% 15.2% 21.7%

Top-Level Manager 0% 6.4% 12.7%

51

Hierarchical Regression Analysis In this section, hierarchical regression was performed to test the research

hypotheses. For career plateau, the entire variable and its both dimensions were

analyzed separately. The results are shown in Table 4.2.

In Table 4.4., Model 1 showed that control variables were analyzed and only age

had a significant negative effect on turnover intention (β=-.235, p<.001). Model 2

tested the first research hypothesis: Career plateau is positively related to employees’

turnover intention. This hypothesis was supported by the result that career plateau is

significantly positively influencing turnover intention (β=.374, p<.001). In Model 3

and 4, the researcher moved on to the dimensional level of the independent variable

and found that both job content plateau and hierarchical plateau had a significant

positive effect on turnover intention (β=.183, p<.001; β=.335, p<.001). The results

supported the Hypothesis 1 that career plateau had a significantly positive effect on

turnover intention.

Table 4.4. Hierarchical Regression Result (n=412)

Variable Turnover Intention

Model 1 Model 2 Model 3 Model 4

β β β β Gender -.027 -.019 -.019 -.034 Age -.235*** -.279*** -.249*** -.264*** Education Level .075 .057 .087 .025 Managerial Position -.034 .034 .000 -.017 Married -.059 -.029 -.056 -.026 Number of Dependents -.079 -.095 -.090 -.077

Career Plateau .374*** Job Content Plateau .183*** Hierarchical Plateau .335*** Adj. R2 .113 .249 .144 .222 ΔR2 .126 .136 .031 .109 F for ΔR2 9.753*** 20.513*** 10.872*** 17.754*** *p<.05. **p<.01. ***p<.001.

52

In Table 4.5., the sample was divided in to three groups according to the three

clusters generated in the previous section. The researcher intended to investigate the

differential effects of participants from the three clusters regarding how their career

plateau affected their intention to turnover. For Low Career Pursuers, there was no

significant effect of career plateau on turnover intention (β=.083, p>.05). However,

for Mid-Career Pursuers and High Career Pursuers, the results showed that their

career plateau did significantly positively influenced their turnover intention (β=.358,

p<.001; β=.400, p<.001) and that the effect for High Career Pursuers was stronger

than that of Mid-Career Pursuers (.400>.358).

Table 4.5.

Hierarchical Regression Result among Clusters (n=412)

Variable Turnover Intention

Low Career Pursuers Mid-Career Pursuers High Career Pursuers

β β β

Model 1 Model 2 Model 1 Model 2 Model 1 Model 2

Gender .226 .210 .027 .027 -.072 -.059

Age .017 .023 -.232* -.304** -.253** -.292***

Education Level .492 .434 .084 .082 .055 .039

Managerial Position .505 .511 -.051 -.003 -.115 -.018

Married -.141 -.181 -.061 -.018 -.128 -.090

Number of

Dependents -.415 -.397 .017 -.020 -.087 -.095

Career Plateau

.083

.358***

.400***

Adj. R2 .515 .477 .073 .196 .169 .321

ΔR2

.004

.124

.151

F for ΔR2 4.181* 3.348* 3.655** 8.069*** 7.351*** 13.695***

n 19 19 204 204 189 189

*p<.05. **p<.01. ***p<.001.

53

Later on, the researcher went on analyzing the dimensional level for the reason

that the two dimensions: job content plateau and hierarchical plateau have distinct

differences. The participants might experience them quite differently. Therefore, the

dimensions were tested to see whether there are indeed variations when it comes to

the effects of turnover intention. In Table 4.6., turnover intention was first regressed

on job content plateau. It demonstrated that for Low Career Pursuers, job content

plateau did not affect their turnover intention (β=.029, p>.05). For Mid-Career

Pursuers, job content plateau did have a significant positive influence on turnover

intention (β=.250, p<.001). As to High Career Pursuers, job content plateau also had a

significant positive effect on turnover intention (β=.166, p<.05); however, the effect

was weaker and less significant compare with that of Mid-Career Pursuers.

Table 4.6.

Hierarchical Regression Result among Clusters (n=412): Turnover Intention

Regressed on Job Content Plateau

Variable Turnover Intention

Low Career Pursuers Mid-Career Pursuers High Career Pursuers

β β β

Model 1 Model 2 Model 1 Model 2 Model 1 Model 2

Gender .226 .218 .027 .039 -.072 -.063

Age .017 .022 -.232* -.248* -.253** -.277**

Education Level .492 .475 .084 .120 .055 .067

Managerial Position .505 .504 -.051 -.032 -.115 -.072

Married -.141 -.140 -.061 -.070 -.128 -.123

Number of

Dependents -.415 -.435 .017 .027 -.087 -.093

Job Content Plateau .029 .250*** .166*

Adj. R2 .515 .471 .073 .130 .169 .191

ΔR2 .000 .060 .026

F for ΔR2 3.098* 3.291* 3.655** 5.350*** 7.351*** 7.321***

n 19 19 204 204 189 189

*p<.05. **p<.01. ***p<.001.

54

Finally, the researcher analyzed the effects of hierarchical plateau on turnover

intention from the three clusters. Same as the previous results, for Low Career

Pursuers, hierarchical plateau did not have any significant effect of turnover intention.

While the analysis on Mid-Career Pursuers and High Career Pursuers found that

hierarchical plateau did have significant positive effect on turnover intention (β=.250,

p<.001; β=.399, p<.001) and the effect seemed to have stronger influence for High

Career Pursuers than Mid-Career Pursuers. The results are presented in Table 4.7.

Table 4.7.

Hierarchical Regression Result among Clusters (n=412): Turnover Intention

Regressed on Hierarchical Plateau

Dependent Variable Turnover Intention

Low Career Pursuers Mid-Career Pursuers High Career Pursuers

β β β

Model 1 Model 2 Model 1 Model 2 Model 1 Model 2

Gender .226 .243 .027 .012 -.072 -.076

Age .017 .003 -.232* -.288** -.253** -.245**

Education Level .492 .485 .084 .042 .055 -.001

Managerial Position .505 .520 -.051 -.022 -.115 -.090

Married -.141 -.212 -.061 -.007 -.128 -.085

Number of

Dependents -.415 -.277 .017 -.032 -.087 -.084

Hierarchical Plateau .133 .250*** .399***

Adj. R2 .515 .478 .073 .129 .169 .322

ΔR2 .005 .059 .152

F for ΔR2 3.098* 3.358* 3.655** 5.283*** 7.351*** 13.733***

n 19 19 204 204 189 189

*p<.05. **p<.01. ***p<.001.

55

To sum up, based on the results of hierarchical regression analysis used to test

the research hypotheses, Hypothesis 1 and 2 were both supported. That is, career

plateau did have significant positive effect on turnover intention and career anchor

profiles did moderate this relationship. The integrated result is shown in Table 4.8.

Table 4.8.

Hypotheses Testing Result Summary

Hypotheses Result

Hypothesis 1 Career plateau will be positively significantly related

employees’ turnover intention. Supported

Hypothesis 2 Career anchor profiles will moderate the relationship

between career plateau and turnover intention. Supported

56

CHAPTER V CONCLUSIONS AND DISCUSSION This chapter presented the conclusions, discussion and implication based on the

findings in this research. Future suggestions and limitation of this research were also

provided.

Conclusion Career plateau is a situation that employees encounter sooner or later in their

career life, especially in a rapid changing era and a society full of SMEs like Taiwan.

In this study, the two proposed hypotheses were both tested. The significant

relationship between career plateau and turnover intention is proven to be true and the

hypothesis of the moderating effect of career anchor profiles is supported as well. The

results indicated that certain individual factors do play an important role in

employee’s turnover decision making process. In addition, three clusters were

generated to have a better understanding of the sample that this research intended to

investigate. The results did indicate several interesting findings that allowed the

researcher to provide some academic insights and practical suggestions to the

employers and human resource practitioners.

Discussion In this research, there were two focuses, the first one was to investigate the

relationship between career plateau and turnover intention in Taiwan. With a labor

market so small and a high percentage of population working in SMEs, people face

the plateau situation in their career quite often and soon. The consequence of career

plateau that when employees are facing a plateau in their career, they are more likely

to leave the organization and search for better development for their career in the

labor market was found. This proved what was stated in the literature to be also true

in Taiwan (Chao, 1990; Tremblay et al., 1995). The other focus of this study was to

find out the moderating role of personal interests in the relationship between career

plateau and turnover intention by using the career anchors profiles. Base on the model

proposed by Mobley et al. (1979), individual’s personal interests do take part in the

turnover decision making process. The findings of this research also supported the

model. The effects of career anchor profiles from the three generated clusters did

affect the relationship between career plateau and turnover intention differently.

57

The three clusters generated in this research were named as Low Career

Pursuers, Mid-Career Pursuers and High Career Pursuers. The patterns of the eight

career anchors from these three clusters generally represented three stages of an

individual’s career development process. In the beginning, which is the Low Career

Pursuers, it is the group with the lowest mean age among the three clusters. Therefore,

the researcher reasonably presumed that these people were at the beginning of their

career. They were still exploring what they want to pursue in their career and

meanwhile accumulating experiences in their jobs. At this stage, they mainly focused

on the stability and security of their job as well as the lifestyle to balance needs from

personal, family and work. As to other anchors, since they were still discovering

themselves or somehow disoriented on the career path, they scored low on these

indicators. However, when times go by with their experiences all piled up, they

developed into Mid-Career Pursuers.

When individuals got into the Mid-Career Pursuers group, they tended to have

better understandings toward themselves. At this stage, all career anchors were rated a

lot higher than Low Career Pursuers. The scores for Technical / Functional

Competence, Pure Challenge and Service / Dedication to a Cause had significantly

increased compared to the previous stage probably because individuals had chosen

their professions and were cultivating them to maturity already. They wanted to

sharpen their professional skills and make a different in their organization or to the

society. However, they were yet well-prepared for taking over general managerial

positions or create their own business outside the companies. This might be the reason

why individuals scored relatively lower on General Managerial Competence and

Entrepreneurial Creativity than other six anchors.

Finally, individuals entered the High Career Pursuers stage after being

experienced and well-developed on all aspects. Their professional skills were mature

and they were ready for general management positions in the company or perhaps

leaving the company and running their own business with all the competences and

skills they acquired after years of training. This might be the reason why the High

Career Pursuers scored higher in General Managerial Competence and

Entrepreneurial Creativity in comparison with the scores from Mid-Career Pursuers.

The hierarchical regression results also supported the abovementioned scenarios.

Generally, for both Mid-Career Pursuers and High Career Pursuers, career plateau did

58

have significant positive effect on turnover intention. In addition, the effect of High

Career Pursuers was stronger than that of Mid-Career Pursuers because with all skills

and competence matured, High Career Pursuers were more likely to have stronger

reactions when they faced a plateau situation in their career. Looking from the

dimensional level of career plateau, Mid-Career Pursuers’ job content plateau did

have stronger influence on turnover intention compare to High Career Pursuers. This

fit the point that the most focused career anchors for Mid-Career Pursuers were

Technical / Functional Competence, Service / Dedication to a Cause and Pure

Challenge, which were all related to their job contents. If job content plateau

happened on them, they would not be able to develop their professional skills and

might decide to leave for other opportunities. As to hierarchical plateau, the effect on

turnover intention from High Career Pursuers was the strongest for the reason that

they would like to climb up the ladder for higher rankings, which usually means

general managerial positions. When High Career Pursuers faced a hierarchical plateau

that stop them from moving upward in the organizations, they would consider leaving

the companies and create their own business.

To sum up, although the cluster analysis is a data driven result, the researcher

believed the reasoning provided above was logical it also fits with Super’s

Developmental Theory (1957) that individuals’ careers go through changes as they

mature. The development patterns are determined by the experiences, opportunities

and other socioeconomic factors they exposed to. People also develop their

self-concepts through the work roles they experience on their career path. Even

though the results might be different from the developmental stages and the

corresponding age ranges Super proposed, the general idea of the theory matched well

with the findings in this research.

Theoretical Implications The research result demonstrates the importance of personal career-oriented

interests/ factors that influence the relationship between career plateau and turnover

intention. In other words, the significance of individuals’ career interests can very

much affect their career decision. In addition, the result of cluster analysis proved the

plurality of career anchors proposed be Feldman and Bolino (1996) to be true. Also,

this research found that in accordance with previous studies, individuals’ career

59

anchors changed when people aged and went through life and career stages (Wey

Smola, & Sutton, 2002; Rodrigues & Guest, 2010). The results also suggested that

certain career-oriented variables can be utilized to study the career development

stages nowadays. Future research can focus on different individual interests between

the career plateau and turnover intention relationship with other career oriented

variables.

Practical Implications For practical implications, the important implication of the research is to

understand the employees in the company. Knowing the needs and what they place a

high value on is essential to keep talent within the companies as well as make the

companies grow. Therefore, career orientation assessments and the design of

individuals’ career path are crucial. Based on the findings in this research, for

employees in different career stages: Low, Mid and High Career Pursuers, the most

urgent needs for them to fulfill are Security / Stability, Technical / Functional

Competence and General Managerial Competence respectively. Human resource

practitioners can then identify and focus on fulfilling individuals’ needs to lower

employees’ intention to leave and the actual turnover behavior.

Other than the focus on individuals’ needs, age is also an important indicator

according to the cluster analysis. Employees in different age might result in different

stages of their career development as well. Take corresponding measures for

employees in different age range might be helpful for decreasing the turnover rate in

the companies.

Limitations A limitation of this study is that the researcher used convenient sampling by

asking friends and connections to fill out the online questionnaires. In doing so, the

result could be biased and might not be able to generalize to a larger society. Another

limitation is that the design of questionnaire was only able to find out the important

anchors; however, the most important anchor might not be able to identify. According

to Schein (2016), the identification of one dominant anchor can be done by interviews

with the research participants. Nevertheless, due to the limited time and budget, the

researcher was not able to conduct a comprehensive study to identify each

60

respondent’s dominant career anchor through an interview, but rather relied on the

respondent’s self-report which might be biased. Finally, because of the sample was

confined in Taiwan, due to cultural context, the results might not be generalizable.

Suggestions for Future Research There are three suggestions for the future research. (1) As mentioned by Schein

(2016), the future study regarding the career anchors can be done through the

combination of both qualitative and quantitative research approaches. In this case, the

researchers might be able to retrieve more accurate result of individuals’

career-oriented factors. (2) Individual factors between career plateau and turnover

intention can be further studied with different individual career orientation variables,

such as Holland Occupational Themes. In this case, researchers can understand

employees’ needs from different angles. (3) Future researcher can focus on different

cultural context or specific group of participants to investigate variation of career

anchor profiles and career development stages.

61

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APPENDIX

國立臺灣師範大學

學術研究問卷

親愛的先生/女士您好:

本研究旨在暸解台灣員工職涯傾向與其工作行為。研究結果對員工及僱

主雙方皆有所幫助。懇請您撥冗協助填答此問卷。您於本問卷中提供的所

有資訊皆將保密且僅屬學術用途，您的填答不會與您的身份以及所屬公司

有所連結。若您同意以上敘述，即可開始作答。

若您有任何關於此研究的問題，歡迎您直接與我們聯繫。非常感謝您的

時間與合作。

林秉翰/ 研究生

國際人力資源發展研究所

國立臺灣師範大學

指導教授

葉俶禎 博士

國際人力資源發展研究所

國立臺灣師範大學

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第一部分

請您依據目前工作的感受選擇最適合的答案 並圈選數字作答 (1=完全不同意 5=完全同意)

完全不同意

不同意

普通

同意

完全同意

1. 我正積極地尋找公司外的工作機會 1 2 3 4 5 2. 一旦找到更好的工作，我將離開目前就職的公司 1 2 3 4 5 3. 我現在正認真地思考辭去目前的工作 1 2 3 4 5 4. 我經常考慮辭去目前任職公司的工作 1 2 3 4 5 5. 我認為一年後我仍任職於目前的公司 1 2 3 4 5

第二部分 請根據您目前的工作情形選擇最適合的答案 並圈選數字作答 (1=完全不同意, 7=完全同意)

完全不同意

非常不同意

不同意

普通

同意

非常同意

完全同意

1. 我預期目前的工作仍會繼續有各種挑戰 1 2 3 4 5 6 7 2. 目前的工作中，我有機會大量的學習與成長 1 2 3 4 5 6 7 3. 我的工作職掌與活動對我來說已經變成是循環的例行性工作

1 2 3 4 5 6 7

4. 我的工作職責有顯著地增加 1 2 3 4 5 6 7 5. 我的工作需要我不斷的拓展自身能力與知識 1 2 3 4 5 6 7 6. 我的工作具有挑戰性 1 2 3 4 5 6 7 7. 我在這家公司中的升遷機會很有限 1 2 3 4 5 6 7 8. 我預期自己在公司會有很多的升遷 1 2 3 4 5 6 7 9. 我在公司中能出頭的機會很有限 1 2 3 4 5 6 7 10. 在公司中我已經達到一個不太有機會能再升遷的職位 1 2 3 4 5 6 7 11. 我不太可能在這家公司中獲得更高的職稱了 1 2 3 4 5 6 7 12. 我預期自己近期內在公司中將升到更高的職位 1 2 3 4 5 6 7

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第三部分

請回答下列各題項的敘述，符合自己面對【職涯/工作選擇】時的考量的程度有多高，並圈選數字作答。 (1=完全不符合; 6=完全符合)

完全不符合

完全符合

1. 我夢想我的工作能允許我自由地以自己的方式與步調來做事 1 2 3 4 5 6 2. 當我能全然自由地安排自己的工作、行程與工作方式時，最能感到滿足 1 2 3 4 5 6 3. 當能完全自主與自由地定義我的工作時，我才能感受到職涯的成功 1 2 3 4 5 6 4. 對我來說能以自己的方式做事，免於種種規定的限制，是非常重要的 1 2 3 4 5 6 5. 我寧願離開公司也不願意接受會減少自主與自由的工作 1 2 3 4 5 6

6. 比起工作自由與自主性，工作的保障與安全性對我而言更為重要 1 2 3 4 5 6 7. 我不願意留在一個會指派可能危及我工作保障的任務給我的組織 1 2 3 4 5 6 8. 我通常尋求能讓我感受到保障與穩定的工作 1 2 3 4 5 6 9. 我夢想能找到一份讓我感到穩定且有保障的工作 1 2 3 4 5 6 10. 當我在財務與工作上皆有所保障時，我最能感到滿足 1 2 3 4 5 6

11. 我想在工作上得心應手，使得其他人總是來尋求我的專業建議 1 2 3 4 5 6 12. 當我能在工作上不斷精進自己的能力時，我才會感受到職涯上的成功 1 2 3 4 5 6 13. 在我的專業領域上成為資深的功能性或技術性主管比成為總經理更加吸

引我 1 2 3 4 5 6

14. 我寧願離開公司也不願接受會使我離開專業領域的輪調性工作 1 2 3 4 5 6 15. 當我能在工作上運用我特殊的才能，我最能感到滿足 1 2 3 4 5 6

16. 當我在工作中能夠整合眾人的心血來完成一個共同的任務時，我對於工作最感到滿足。

1 2 3 4 5 6

17. 我夢想能負責管理一整個組織 1 2 3 4 5 6 18. 唯有在公司中成為高階總經理時，我才會感到成功 1 2 3 4 5 6 19. 對我來說成為總經理比在專業領域上成為資深功能性主管更為吸引人 1 2 3 4 5 6 20. 我寧願離開公司也不願意接受會讓我偏離升遷到高階管理的工作 1 2 3 4 5 6

21. 我總是在尋找靈感讓我能夠創立自己的事業 1 2 3 4 5 6 22. 建立自己的事業比在他人公司中擔任高階主管來得重要 1 2 3 4 5 6 23. 當我能以自己的能力及努力來創造出東西時，我最能感到滿足 1 2 3 4 5 6 24. 唯有根據我的想法以及能力來創立自己的企業，才能讓我感到成功 1 2 3 4 5 6 25. 我夢想創建我自己的事業 1 2 3 4 5 6

26. 當我的工作對社會福祉有實質貢獻時，我才會感受到職業生涯上的成功 1 2 3 4 5 6

27. 當我能在工作上以自己的才能服務他人，我最能感到滿足 1 2 3 4 5 6

28. 能夠發揮才能讓世界變得更美好是我職涯選擇的考量因素 1 2 3 4 5 6

29. 我夢想中的工作是能對全人類及社會有實質的貢獻 1 2 3 4 5 6

70

30. 我寧願離開公司也不願意接受會用不上我服務他人能力的工作 1 2 3 4 5 6

31. 我夢想中的職涯是能不斷挑戰解決更困難的問題 1 2 3 4 5 6 32. 唯有能在工作上不斷遇到並解決更困難的挑戰時，我才能感受到職涯上

的成功 1 2 3 4 5 6

33. 當我能解決看似難解甚至不可能完成的任務時，我最能感到滿足 1 2 3 4 5 6 34. 工作上我偏好強烈挑戰我個人解決問題能力與競爭力的機會 1 2 3 4 5 6 35. 比起達到高階管理階層，從事解決難題的工作對我而言更為重要 1 2 3 4 5 6

36. 我寧願選擇離開公司，也不願留在會讓我無法顧全個人與家庭的工作上 1 2 3 4 5 6 37. 我夢想中的職業要能夠同時滿足我個人、家庭以及工作需求 1 2 3 4 5 6 38. 唯有能均衡個人、家庭及工作需求時，我才會感到人生的成功 1 2 3 4 5 6 39. 比起擔任高階管理職位，能維持個人與專業上需求的平衡對我而言更為

重要 1 2 3 4 5 6

40. 我總是尋找對我個人以及家庭影響最小的工作 1 2 3 4 5 6

基本資料

1. 我的性別是 □男 □女 2. 我出生在西元 _______年 3. 我的最高學歷是 □高中職畢業及以下 □專科畢業 □學士畢業 □碩士畢業 □博士畢業 4. 我在目前職位的年資 ________ 5. 我總共工作了幾年 ________ 6. 目前工作職階： □自僱(自己開業) □一般職員 □初階管理層 □中階管理層 □高階管理層 □其他 7. 我的婚姻狀態是 □已婚 □單身 □離婚 □寡居 □同居 8. 我目前撫養的人數 ________ 9. 我目前工作所在的產業

□農、林、漁、牧業 □礦業及土石採取業 □製造業 □電力及燃氣供應業 □用水供應及

污染整治業 □營造業 □批發及零售業 □運輸及倉儲業 □住宿及餐飲業 □資訊及通訊

傳播業 □金融及保險業 □不動產業 □專業、科學及技術服務業 □支援服務業 □公共

行政及國防；強制性社會安全 □教育服務業 □醫療保健及社會工作服務業 □藝術、娛

樂及休閒服務業 □其他服務業

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感謝您的耐心填答