This chapter introduces the research framework, research hypotheses, sample, data collection, measurement, basic translation, pilot study, and data analysis.
Research Framework
The research framework illustrates the relationships between variables. Figure 3.1 shows the research framework in this study. The job content plateau serves as independent variable.
Career commitment, career identity, career planning, and career resilience serves as dependent variable. Also, self-efficacy serves as a moderator to exam the relationship between job content plateau and career commitment.
Figure 3.1 Research Framework
Research Hypotheses
The research hypotheses of this study were shown in the Table 3.1:
Job Content Plateau
Self-Efficacy
Career commitment
Career identity
Career planning
Career resilience H2
H1
Control variables
Age
Working experience
Year salary
Table 3.1.
Research Hypotheses Hypothesis
Hypothesis 1 There is a significantly negative relationship between job content plateau and career commitment.
Hypothesis 1a There is a significantly negative relationship between job content plateau and career identity.
Hypothesis 1b There is a significantly negative relationship between job content plateau and career planning.
Hypothesis 1c There is a significantly negative relationship between job content plateau and career resilience. educational advance. This study did not specify any category of business student.
In this study, 497 copies of questionnaires were distributed for the target respondents.
455 copies of questionnaires were collected. However, 255 copies of questionnaires were eliminated since missing data. So there were 200 copies of questionnaires and the return rate was 40.2 %.
Data Collection
This study utilizes purposive sampling to collect data. Phone calls and E-mails were applied to contact professors of business courses for the purpose of getting their permission to distribute self-reported questionnaires during classes. After finishing questionnaires, the respondents received McDonald's sweet cards.
Measurement
Job content plateau. The 6 item job content plateau scale was adapted by Allen, Russell, Poteet and Dobbins in1999.This scale was initially developed by Milliman (1992).
The typical items was “My job responsibilities have increase significantly”. The response categories ranged from 1 (Strongly disagree) to 5 (Strongly agree). The Cronbach’s coefficient Alpha reliabilities of career plateau ranged from 0.83 to 0.85 (Allen et al., 1999).
Career commitment. This study will use Carson and Bedeian’s (1994) Career Commitment Measure (CCM) to assess three components of career commitment. There are 12 items divided into three dimensions: career identity with four items, career planning with four items and career resilience with four items. Career identity refers to establishing a close emotional association with one’s career, and a typical item is “My line of work/career field is an important part of who I am”. Career planning indicates the concept of determining developmental needs and setting career goals, and a typical item is” I have created a plan for my development in this line of work/career field”. Career resilience represents a person who resists career disruption in the face of adversity and in sub dimension of career identity, and a typical item is “The discomforts associated with my line of work/career field sometimes seem
too great”. This scale employs five point Likert scale (1= strongly disagree, 2= disagree, 3=
neutral 4= agree, 5= strongly agree). The Cronbach’s coefficient Alpha reliabilities of Career Commitment Measure ranged from 0.79 to 0.85( Carson and Bedeian,1994).
Self-efficacy. General Self-Efficacy (GSE) scale is utilized to assess general self-efficacy.
General Self-Efficacy (GSE) scale was initially developed by Schwarzer and Jerusalem in 1995. This scale is totally 10 items, and typical items are “It is easy for me to stick to my aims and accomplish my goals.” and” Thanks to my resourcefulness, I know how to handle unforeseen situations.” The scale used seven-point Likert scale (1= Strongly not true to 7 = Strongly true). The Cronbach’s alphas reliabilities ranged from .76 to .90 (Schwarzer &
Jerusalem, 1995).
Control variables
In this study, control variables are age, working experience, and year salary. On the concern of age, it was one of important factors to affect career commitment (Adio & Popoola, 2010; Blau, 1995; Carson & Bedeian, 1994; Colarelli & Bishop, 1990; Mathieu & Zajac, 1990; Popoola & Oluwole, 2007). Colarelli and Bishop (1990) mentioned that age was positively correlated to career commitment. However, Popoola and Oluwole (2007) found that there is significant negative relationship between age and career commitment. Working experience was chosen as control variable. The previous studies showed that work experience had impact on career commitment (Adio & Popoola , 2010; Blau, 1995; Carson & Bedeian;
1994; Chang, 1999 ). Carson and Bedeian (1994) indicated that people have more work experience are inclined to have higher career commitment. Besides, research showed that year salary influenced career commitment. (Ballout, 2009 ; Colarelli & Bishop, 1990; Day &
Allen, 2004; Poon, 2004 ). Ballout (2009) observed that salary was positively related to career commitment. People have higher salary will leads to higher career commitment.
Reliability and Validity
Back Translation
This original instrument was developed in English. We had master students majoring in English and psychology help translate from English version into Chinese version. After translation process, Chinese version of this questionnaire was confirmed by experts such as professors and human resource practitioners for the purpose of making the measuring cording consistently with original version.
Pilot Study
In pilot study, Cronbach’s alpha was tested by 50 business students. The results showed that Cronbach’s alpha of job content plateau was 0.82. Cronbach’s alpha of career commitment was 0.87, and its sub dimensions ranged from 0.81 to 0.89. Cronbach’s alpha of self-efficacy was 0.85. The 50 business students were excluded in final sample.
Cronbach’s Alpha of Instruments
For the reliability, it was tested by internal consistency. According to Guieford (1965), the qualified Cronbach’s alpha should be higher than 0.7. The Cronbach’s alpha of job content plateau was 0.83. The Cronbach’s alpha of career commitment and sub dimensions was ranged from 0.77 to 0.85. The Cronbach’s alpha of self-efficacy was 0.80.
Confirmatory Factor Analysis (CFA)
Before the process of testing the hypotheses, confirmatory factor analysis (CFA) was employed to evaluate the distinctiveness of the measures used in this study. The result of CFA was shown in Table 3.2. The value of chi square divide degree of freedom was below 3.
Besides, the overall model fit was examined by various fit indices, including root mean square error of approximation (RMSEA), comparative fit index (CFI), normed fit index (NFI), incremental fit index (IFI), Tucker–Lewis index (TLI), and goodness of fit index (GFI). The standard of good model fit was that RMSEA was below or equal to 0.08 (Browne
& Cudeck, 1993). Also, the score of GFI was above 0.90 (Joreskog & Sorbon, 1981). The scores of CFI, NFI, IFI, and TLI were above 0.90 (Bentler & Bonett, 1980).
In this study, there were six items in job content plateau. The chi square divide degree of freedom of job content plateau was 1.965. The RMSEA of job content plateau was 0.070, and the other fit indexes were: CFI= 0.985, NFI= 0.970, IFI= 0.985, TLI= 0.972, GFI = 0.976. There were 12 items and three sub dimensions in career commitment. The chi square divide degree of freedom of career commitment was 2.075. The RMSEA of career commitment was 0.074, and the other fit indexes were: CFI= 0.949, NFI= 0.908, IFI= 0.950, TLI= 0.930, GFI = 0.926. In addition, there were ten items in self-efficacy. The chi square divide degree of freedom of self-efficacy was 2.015. The RMSEA of self-efficacy was 0.071, and the other fit indexes were: CFI= 0.935, NFI= 0.883, IFI= 0.937, TLI = 0.906, GFI = 0.940.
Table 3.2.
Results of Confirmatory Factor Analysis (N=200) Model fit indices
χ² df χ²/df RMSEA CFI NFI IFI TLI GFI 1. Job content plateau 15.179 8 1.965 .070 .985 .970 .985 .972 .976 2. Career Commitment 99.609 48 2.075 .074 .949 .908 .950 .930 .926 3. Self-efficacy 62.467 31 2.015 .071 .935 .883 .937 .906 .940
Data Analysis
The data of this research analyzed by using the SPSS 18.0 and AMOS 18.0.
Confirmatory factor analysis, Sample descriptive statistics, correlation analysis, and hierarchical regression analysis were employed in this study. Each process of data analysis was clearly listed below:
Sample Descriptive Statistics
Sample descriptive statistics were applied to analyze the valid sample and demographic information. Sample characteristics were divided into individual level and organization level.
In individual level, there were age, work experience, gender, education level, major, and year salary in questionnaires. In organization level, there were job category, company category, industry, and job position in questionnaires. These sample characteristics were described by frequency and percentage.
Correlation Analysis
Pearson coefficient correlation were adopted to investigate the correlation among those variables in order to understand the correlation among control variables, job content plateau, career commitment, and self-efficacy,
Hierarchical Regression Analysis
Hierarchical regression analysis would be to test the relationships and significant level among control variables, job content plateau, career commitment, and self-efficacy. In addition, according to Baron and Kenny (1986), moderating effect was tested by hierarchical regression analysis.
CHAPTER IV FINGDING AND DISCUSSIONS
In this chapter, the result of data analysis would be respectively introduced including sample descriptive statistics, correlation analysis, and hierarchical regression analysis.
Sample Descriptive Statistics
10 items had been chosen as the demographic information items in questionnaires. The demographic information included age, work experience, gender, education level, major, job category, company category, industry, year salary, and job position. The demographic information which divided into personal-related level and job-related level were shown in Table 4.1 and Table 4.2. In personal-related level, most of respondents aged from 31 to 40 (47%). Regarding work experience, most of respondents had between 11 to 20 work experiences (44.5%). In addition, 60.5% of respondents were male. For the education level, the respondents mainly had bachelor degree (72.5%). Besides, most of respondents’ major were related to management and economics (48.5%). For the year salary, interval of 500,001 to 750,000 NT dollars (25%) occupied most percentage of sample. In job-related level, concerning job category, 77.5% of respondents’ job categorized as business service. Also, respondents mainly from local company (82%). For the industry, respondents mainly work in financial and insurance (19.5 %). Besides, 34.5% of respondents were middle level manager.
Table 4.1.
Table 4.1. (continued)
Professionals (e.g. doctor, lawyer, and accouter) 12 6
Free lancer 3 1.5
Semi-conductors / Software / Electronic products related 30 15
Manufacturing 36 18
(continued)
Table 4.2. (continued)
Items Frequency Percentage
Agriculture/ Forestry/ Fishing /Animal husbandry / Natural
resource 3 1.5
Human health and cleaning activities 11 5.5
Accommodation and food service 2 1 variables, job content plateau, career commitment, career identity, career planning, career resilience, and self-efficacy. The mean, standard deviation, reliabilities, and correlation values were shown in Table 4.3. The mean of job content plateau was 2.22, and the standard deviation was 0.57. The mean of career commitment and sub dimensions was ranged from 4.04 to 5.37, and standard deviation was ranged from 0.84 to 1.20. The mean of self-efficacy was 3.76, and the standard deviation was 0.38.
The job content plateau was significantly negative related to career commitment (r = - 0.27, p < 0.01). Regarding four dimensions of career commitment, career identity (r = - 0.40, p < 0.01) and career planning (r = - 0.20, p < 0.01) were significantly negative related to job content plateau. Job content plateau was significantly negative related to self-efficacy(r = -
0.19, p < 0.01). Career commitment was significantly positive relate to career identity(r = 0.75, p < 0.01), career planning(r = 0.79, p < 0.01), and career resilience (r = 0.77, p < 0.01).
33
Table 4.3.
Descriptive Statistics and Correlations (n=200)
Variable Mean S.D. 1 2 3 4 5 6 7 8 9
1 Age 39.75 8.09
2 Work experience 15.65 7.77 .92**
3 Year salary 4.06 1.66 .49** .51**
4 Job content plateau 2.22 0.57 -.03 -.03 -.14* (.83)
5 Career commitment 4.75 0.84 .16* .21** .17* -.27** (.85)
6 Career identity 5.37 0.90 .15* .16* .12 -.40** .75** (.77)
7 Career planning 4.85 1.17 .10 .14 .21** -.20** .79** .45** (.82)
8 Career resilience 4.04 1.20 .14 .17* .07 -.08 .77** .38** .34** (.82)
9 Self-efficacy 3.76 0.38 .04 .05 .06 -.19** .14 .12 .16* .04 (.80)
Note:* p < .05. ** p < .01. Cronbach's alpha are in parentheses.
Year salary (1 = Under 250,000; 2 = 250,001-500,000; 3 = 500,001-750,000; 4 = 750,001-1,000,000; 5 = 1,000,001-1,250,000;
6 = 1,250,001-1,500,000; 7 = Over 1,500,000 NT dollars).
Hierarchical Regression Analysis
Hypotheses were tested by using the hierarchical regression analysis. Age, work experience, and year salary were chosen as control variables.
Job Content Plateau and Career Commitment
Hypothesis 1 predicted that job content plateau was negatively related to career
commitment. The effects of job content plateau on career commitment variables are presented in Table 4.3. In the Model 1, we added the control variables into the first step. Then, we added the job content plateau into Model 2. As predicted, there is a significant and negative relationship between job content plateau and career commitment (β = -.26, t =-3.81***, p<
0.001). After adding job content plateau into second step, the job content plateau increased seven percentage of the explained variance in career commitment (adjusted R2= .10, ∆R2= .07, F = 6.55, ∆F = 14.52, p< 0.001). The Model 2 was significant. Therefore, business students with higher job content plateau are inclined to have lower career commitment. This result supported for the Hypothesis 1. Regarding sub dimensions of career commitment, hypothesis 1a stated that there is a significantly negative relationship between job content plateau and career identity. As shown in Table 4.4, we added the control variables into the first step in the model 1. Then, we added the job content plateau into model 2. As predicted, there is a significantly negative relationship between job content plateau and career identity (β = -.39, t
=-5.95***, p< 0.001). After adding job content plateau into second step, the job content plateau increased 15 percentage of the explained variance in career commitment (adjusted R2= .16, ∆R2= .15, F = 10.43, ∆F = 35.40, p< 0.001). The Model 2 was significant. Therefore, business students with higher job content plateau are inclined to have lower career identity.
Hypothesis 1b stated that there is a significantly negative relationship between job content plateau and career planning. In Model 1, control variables were added into the first step. Then, we added the job content plateau into Model 2. As predicted, there is a significantly negative
relationship between job content plateau and career planning (β = -.18, t =-2.56*, p< 0.05).
After adding job content plateau into second step, the job content plateau increased three percentage of the explained variance in career commitment (adjusted R2= .07, ∆R2= .03, F = 4.44, ∆F = 6.58, p< 0.05). The Model 2 was significant. Therefore, business students with higher job content plateau are inclined to have lower career planning. However, Hypothesis 1c stated that there is a significantly negative relationship between job content plateau and career resilience. However, the results were not supported (β = -.08, t =-1.09, p >
0.1). There is no significantly negative relationship between job content plateau and career resilience.
Table 4.4
Hierarchical Regression Results for Job Content Plateau and Career Commitment. (n=200)
Variables
Model 1 Model 2
β β
Step 1: Control variables
Age -.20 -.20
Work Experience .34+ .36*
Year Salary .09 .05
Step 2: Main Effect
Job Content Plateau -.26***
R2 .05 .12
Adj. R2 .04 .10
∆R2 .07
F 3.64* 6.55***
∆F 14.52***
Notes: + p < .10. * p < .05. ** p < .01. *** p < .001.
Table 4.5.
Hierarchical Regression Results for Job Content Plateau, Career Identity, Career Planning, and Career Resilience. (n=200)
Variables
Career identity Career planning Career resilience Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 relationship between job content plateau and career commitment. Further, we also predicted that sub dimensions of career commitment had the interaction effect. The results of hierarchical regression were shown in Table 4.5. In the Model 1, the control variables were added into the first step. Then, in second main effect step, job content plateau and self-efficacy were added into Model 2. In third step, the interaction effect of job content plateau and self-efficacy was added into the Model 3. As predicated, self-efficacy negatively moderated the influence of job content plateau on career commitment (β = -.22, t =-3.19**, p< 0.01) (Kleinbanum, Kupper, & Muller, 1998). Their interaction term account for seven percent of the explained variance in career commitment (adjusted R2= .14, ∆R2= .04, F = 6.48,
∆F = 10.16, p< 0.01). A clear picture of the form of the interaction for Hypothesis 2 can be
obtained by examining the plotted interaction in Figure 4.1, the plot of the interaction term showed that job content plateau was related to career commitment for high self-efficacy (Aiken & West, 1991). On the contrary, the flat slope showed that job content plateau affected career commitment slightly for the group with low self-efficacy. Therefore, business students have more self-efficacy will strength the relationship between job content plateau and career commitment. Equally, when business students have less self-efficacy will weaken the relationship between job content plateau and career commitment. Hypothesis 2 was supported.
Table 4.6.
Hierarchical Regression for the Moderating Effect of Self-efficacy on the Relationship between Job Content Plateau and Career Commitment. (n=200)
Figure 4.1.
The Interaction Effect of Self-efficacy and Job Content Plateau on Career Commitment In our hypotheses, we also predicted that the interaction of job content plateau and self-efficacy had moderating effect on three sub dimensions of career commitment. As shown in Table 4.6, the hieratical regression result of each dimensions. The interaction of job content plateau and self-efficacy had moderating effect on career identity (β = -.14, t =-2.03*, p <
0.05). The increasing amount of explained variance and the Model 3 were significant (adjusted R2= .17, ∆R2= .01, F =7.78, ∆F = 4.12, p< 0.01). Higher self-efficacy strengths the relationship between job content plateau and career identity. Therefore, business students have more self-efficacy will strength the relationship between job content plateau and career identity. Equally, when business students have less self-efficacy will weaken the relationship between job content plateau and career identity. Hypothesis 2a was supported. Hypothesis 2b predicted that self-efficacy moderates relationship between job content plateau and career planning. In Table 4.6, the interaction of job content plateau and self-efficacy had moderating effect on career planning (β = -.19, t = -2.80**, p< 0.01). The increasing amount of explained variance and the Model 3 were significant (adjusted R2= .11, ∆R2= .04, F =4.89, ∆F = 7.84, p< 0.01). Higher self-efficacy strengths the relationship between job content plateau and
career planning. Therefore, business students have more self-efficacy will strength the relationship between job content plateau and career planning. Equally, when business students have less self-efficacy will weaken the relationship between job content plateau and career planning. Hypothesis 2b was supported. Hypothesis 2c predicted that self-efficacy moderates relationship between job content plateau and career resilience. In Table 4.6, the interaction of job content plateau and self-efficacy had moderating effect on career resilience (β = -.16, t =-2.26*, p< 0.05). The increasing amount of explained variance and the Model 3 were significant (adjusted R2= .04, ∆R2= .03, F =2.27, ∆F = 5.10, p< 0.5). Higher self-efficacy strengths the relationship between job content plateau and career resilience.
Therefore, business students have more self-efficacy will strength the relationship between job content plateau and career resilience. Equally, when business students have less self-efficacy will weaken the relationship between job content plateau and career resilience.
Hypothesis 2c was supported.
As shown in Figure 4.1, the result shows that for those people with high self-efficacy, job content plateau was strongly related to career identity, career planning, and career resilience. Whereas for those with low self-efficacy, job content plateau was weekly related to career identity, career planning, and career resilience.
The purpose of this study was to examine the relationships among job content plateau, self-efficacy and career commitment. The results supported Hypothesis 1 and Hypothesis 2, there was a significantly negative relationship between job content plateau and career commitment. Also, self-efficacy moderated the relationship between job content plateau and career commitment. However, Hypothesis 1c was not satisfied.
Table 4.7.
Hierarchical Regression for the Moderating Effect of Self-efficacy on the Relationship among Job Content Plateau, Career Identity, Career Planning, and Career Resilience.
Variables
Career identity Career planning Career resilience
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Model 9
β Β β β β β β β β
Step 1: Control variables
Age -.00 .00 -.02 -.25 -.25 -.27 -.17 -.17 -.19
Work Experience .14 .16 .19 .27 .27 .31+ .34+ .35+ .38*
Year Salary .05 -.03 -.02 .19* .16+ .16* -.02 -.04 -.03
Step 2: Main Effects
Job Content Plateau -.39*** -.41*** -.16* -.19** -.08 -.11
Self-efficacy .04 .03 .12+ .10 .02 .00
Step 3: Interaction Self-efficacy x
Job content plateau -.14* -.19** -.16*
R2 .03 .18 .20 .05 .10 .13 .04 .04 .07
Adj. R2 .01 .16 .17 .04 .07 .11 .02 .02 .04
∆R2 .15 .02 .05 .04 .01 .03
F 1.78 8.37*** 7.78*** 3.63* 4.15** 4.89*** 2.37+ 1.66 2.27*
∆F 17.79*** 4.12* 4.74* 7.84** 0.62 5.10*
Notes: + p < .10. * p < .05. ** p < .01. *** p < .001.
Figure. 4.2. The interaction effect of self-efficacy and job content plateau on career identity, career planning, and career resilience.
CHAPTER V CONCLUSIONS AND RECOMMENDATIONS
This chapter consists of conclusions and recommendations. Conclusions present the integration of hypotheses result in this study. Recommendations include the implication for theoretical and practical view, research limitations and suggestion for future research.
Conclusions
Table 5.1.
The Integration Results of Hypotheses Testing
Hypothesis Explanation Test Result
Hypothesis 1 There is a significantly negative relationship between job content plateau and career commitment.
Supported
Hypothesis 1a There is a significantly negative relationship between job content plateau and career identity.
Supported Hypothesis 1b There is a significantly negative relationship between job
content plateau and career planning.
Supported Hypothesis 1c There is a significantly negative relationship between job
content plateau and career resilience.
As the Table 5.1 showed, all the hypotheses in this research were satisfied except Hypothesis 1c.
The purpose of the study was to examine the relationships between job content plateau and career commitment and self-efficacy served as moderator to examine the relationship between job content plateau and career commitment in the sample of business students. The results showed that job content plateau negatively influence career commitment. Besides, self-efficacy negatively moderates the relationship between job content plateau and career commitment. Specifically, the higher self-efficacy, the stronger effect of job content plateau on career commitment. Regarding sub dimensions of career commitment, the results are
The purpose of the study was to examine the relationships between job content plateau and career commitment and self-efficacy served as moderator to examine the relationship between job content plateau and career commitment in the sample of business students. The results showed that job content plateau negatively influence career commitment. Besides, self-efficacy negatively moderates the relationship between job content plateau and career commitment. Specifically, the higher self-efficacy, the stronger effect of job content plateau on career commitment. Regarding sub dimensions of career commitment, the results are