Psychological Reports: Employment Psychology & Marketing 2014, 114, 2, 625-634. © Psychological Reports 2014
ROLE OF CAREER DECISION-MAKING SELF-EFFICACY AND RISK OF CAREER OPTIONS ON CAREER DECISION-MAKING OF CHINESE GRADUATES1, 2 YINGHUA YE Zhejiang University Summary.—This study investigated the influence of Chinese graduates' career decision-making self-efficacy (CDMSE) and the moderating effect of career options on career decisions. Graduates (92 men, 119 women, 5 unreported gender; M age = 22.3 yr., SD = 1.2) from four different types of universities in Zhejiang Province participated in the study. CDMSE was measured with the CDMSE Scale for University Students, and participants rated their choices on 3 career options with different levels of risk. The results showed that participants were more likely to choose a high-risk option, and that career options moderated the relation between graduates' CDMSE and career decision. Graduate career counseling programs should encourage students to develop more reasonable career goals that match their skills.
The concept of self-efficacy, introduced by Bandura, is defined as “the conviction that one can successfully execute the behavior required to produce certain outcomes” (Kirsch, 1986). Many studies have demonstrated that self-efficacy influences behavior through internal representations and in a variety of settings, such as attributions and work performance (Stajkovic & Luthans, 1998; Ajzen, 2002). Taylor and Betz (1983) assessed the utility of Bandura's self-efficacy theory to the treatment of career indecision, and defined the concept of career decision-making self-efficacy (CDMSE) as the individual's belief that one can successfully complete the tasks necessary to make career decisions (Taylor & Betz, 1983; Luzzo, 1993; Paulsen & Betz, 2004). Taylor and Betz (1983) also developed the CDMSE Scale (later the CDSE) to measure this concept (Luzzo, 1993). The scale was constructed using the five career choice competencies proposed in Crites's model of career maturity: “accurate self-appraisal,” “gathering occupational information,” “goal selection,” “making plans for the future,” and “problem-solving.” Each factor was represented by 10 items on the CDMSE Scale (Betz & Luzzo, 1996). The original scale and subscales had good internal consistency reliability, with Cronbach's α = .97 for the total score and αs ranging from 0.86 to 0.89 for the subscales (Taylor & Betz, 1983; Betz, Klein, & Taylor, 1996). To create a more practical scale for individual assessment, a 25-item short form Address correspondence to Yinghua Ye, College of Education, Zhejiang University, Hangzhou, Zhejiang 310028, People's Republic of China or e-mail ([email protected]). 2 This study was supported by the “ZiJing Plan” of Zheiiang University, and the Philosophy and Social Sciences Foundation of Zhejiang Province (Grant No. 10CGJY05YBQ). 1
DOI 10.2466/01.17.PR0.114k20w9
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(CDMSE–SF, later termed the CDSE–SF) was constructed by eliminating 5 of the 10 items from each of the five factors. A total scale α of 0.94 has been reported for this short form (Betz, Klein, & Taylor, 1996). Several cross-cultural studies have used confirmatory factor analysis to test the underlying factor structure of the CDMSE–SF and CDMSE scales with diverse samples outside of the United States. Gardron (2011) examined the reliability and the factor structure of the CDMSE–SF with 650 French university students; the results revealed a four-factor model that had a better fit than the original five-factor model. Peng and Long (2001) reported that the CDMSE Scale had good reliability, internal consistency, and high discriminant validity in a sample of 1,000 Chinese university students. Jin, Ye, and Watkins (2012) constructed and tested three competing factorial structure models of the CDMSE–SF with a sample of 796 Chinese graduate students, and found that a single-factor model fit the data as well as the five-factor model. These studies suggest that the CDMSE Scale and CDMSE–SF might be sensitive to cultural differences. The theory and measures for career decision-making self-efficacy have been widely applied in studies on career choice behaviors, and researchers have found a positive relationship between scores on the CDMSE and a variety of career variables, such as vocational identity (r = .30; Gushue, Scanlan-Kolone, Pantzer, & Clarke, 2006), career commitment (r = .45; Chung, 2002), and self-esteem (r = .58; Robbins, 1985; Betz & Luzzo, 1996). Other examples include higher scores on CDMSE being related to greater engagement with career exploration activities (r = .31; Gushue, et al., 2006); Luzzo (1993) found that CDMSE was moderately and positively related to career decision-making attitudes (r = .41) but not related skills (r = .05), and in a regression vocational attitude could be predicted by career decision-making capability (β = 0.32), CDMSE (β = 0.31), and age (β = 0.19). Betz (2004) also applied the CDMSE theory to vocational counseling. In addition to the above career variables, CDMSE has been reported to be associated with career choice (Betz & Hackett, 1986). As proposed in social-cognitive career theory, self-efficacy is a direct causal antecedent of career choice goals and actions, such as career decision making (Lent, Brown, & Hackett, 1994). Career decisions are often highly complex and difficult decisions, and indecision can lead to problems during the career selection process (Fabio, Palazzeschi, Asulin-Peretz, & Gati, 2013). The predictive association of CDMSE and career indecision has been found in numerous studies (Osipow & Gati, 1998; Guay, Senécal, Gauthier, & Fernet, 2003; Creed, Patton, & Prideaux, 2006); however, this is an inverse association. For example, one study showed that CDMSE was moderately and negatively related to vocational indecision (r = −.51) and locus of control (r = −.30), whereas moderate positive relationships were found between CDMSE, vocational
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decidedness (r = .46), and occupational self-efficacy (r = .44) in 407 college students (Taylor & Popma, 1990). It can be concluded from the results of the above studies that CDMSE may affect career decision making. Despite the wealth of literature demonstrating that CDMSE is a significant predictor of variables related to the career decision-making process, there has been little research on the effect of CDMSE on the content of career choice, and no studies have examined the moderating effect of environmental variables. According to social-cognitive career theory, proximal environmental variables (e.g., socioeconomic status, job opportunities, or labor laws) can moderate how self-efficacy affects career decisions (Lent, et al., 1994). Chen and Zhang (2009) examined the effect of different levels of risk in a career on career decision making, and found that college students' career decision making was negatively related to the magnitude of risk; i.e., more students chose jobs with low risk. In the present study, constructed career options with three levels of risk were the objective variables, and the operational definition of the career risk was “the acceptability of the job to the individual and the conformity of the individual's qualifications to the job requirements” (Chen & Zhang, 2009). For example, a job seeker faces high career risk when the individual has to accept a job offer that he/she may not be actually interested in and/or when the individual does not possess sufficient qualifications to meet the job requirements. Thus, to clarify this under-researched topic, the present study focused on the influence of CDMSE on Chinese graduates' career choices and on the moderating effect of career risk. Recently, with the increased enrollment in higher education institutions in China, graduates have been faced with increased difficulty in finding a job after graduation. Mismatch between the enrollment expansion and job market demand has led to heated employment competition. China created 12.66 million new urban job opportunities in 2012 (although not specifically requiring university degrees), while the number of new graduates was approximately 6.8 million (Ministry of Human Resources and Social Security of the People's Republic of China, 2013). The fact that many Chinese graduates are still unemployed suggests that the new jobs created do not meet the expectations of university graduates or do not require their university training. Graduates' career decision making and the falling graduate employment rate are the topics worthy of study. Despite the availability of many jobs, apparently the characteristics of these jobs do not seem attractive to the new graduates. Previous studies on the employment problems of university graduates in China have focused on psychological characteristics, mental blocks, and pressures to find a job (Qiu & Zhang, 2009; Zhang & Yao, 2009). However, because the properties of the jobs were not investigated,
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these studies did not describe certain basic aspects of graduates' intrinsic career decision making related to skills and job attractiveness. Based on the aforementioned studies, it was hypothesized that graduates' CDMSE would affect their career decision making, and this effect will be moderated by the different risk levels of the career options available. Hypothesis 1. Chinese graduates' career decisions will be related to the risk level of career options. Hypothesis 2. Career options' risk levels will moderate the relation between CDMSE and career decisions. METHOD Participants The participants (N = 216) were selected from nine classes from four schools in Zhejiang Province. The students were told that the survey was anonymous and that they could withdraw anytime. The measures were distributed to the participants by teachers during class time in the classrooms. No compensation was offered to the students. The interested students completed this survey as volunteers during their class breaks. Participants were all college seniors (92 men, 119 women, 5 did not report gender) from different types of colleges and universities; 72 from normal schools, 63 from business schools, 32 from vocational colleges, and 49 from comprehensive universities. The majors represented were the arts (n = 153), sciences (n = 35), and engineering (n = 28). The mean age of the participants was 22.3 yr. (SD = 1.2). Measures The CDMSE Scale for University Students.—Peng and Long's (2001) Chinese adaptation of the CDMSE Scale was used. This Chinese version replaced five items from the original English version that did not apply to Chinese students with other five items that were more applicable. They used all five factors of the CDMSE Scale, including accurate self-appraisal (e.g., “List some jobs you are interested in”), gathering occupational information (e.g., “Investigate the prospect of one job or career”), goal selection (e.g., “Select one job that will fit your interests”), making plans for the future (e.g., “Determine the steps you need to successfully complete your chosen job”), and problem solving (e.g., “Protect your rights by using the employment policies and regulations”). Eleven items were deleted in the item and exploratory factor analysis process, and this resulted in a total of 39 items. Responses are made on a 5-point Likert scale, with anchors 1: No confidence at all and 5: Complete confidence. The scale scores are the sums of means for all the items, so scores can range from 1 to 5, with higher scores indicating higher career decision-making self-efficacy. The inter-
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nal consistency of the Chinese version in a sample of 1,000 Chinese university students was .93, and the re-test reliability was .66 (Peng & Long, 2001). Zhao, Li, and Zhang (2009) used Peng and Long's (2001) scale to test the relationship between CDMSE and career maturity (r = .57), so the scale has external validity. Career options.—Descriptions of career options were constructed with different levels of “risk.” The risk of a career option was considered to comprise (1) the acceptability of the job to the respondent (satisfaction) and (2) the conformity of the respondent's qualifications to the job requirements. The described career options were: high-risk (high satisfaction/low conformity), mid-risk (moderate satisfaction/moderate conformity), and lowrisk (low satisfaction/high conformity). These three types of career options were presented to participants in a questionnaire. A within-subjects design was used in this study, so every participant responded to all 3 types of the career options. To avoid an order effect, half of the participants started with the low-risk option, and the another half started with the high-risk option. For example, the high-risk career scenario was described as “Here is a job opportunity that you are satisfied with, but you do not fully meet the requirements for this job, so the probability of getting the job is lower. Would you apply for this job?” (Chen & Zhang, 2009). Participants rated the likelihood of applying for each job on a 7-point Likert-type scale, with anchors 1: “I would never apply for it” and 7: “I will definitely apply for it.” Procedure In the first step, the CDMSE scale was administered. Then, the participants read the descriptions of the three different career options and rated the likelihood of making each choice for the three career descriptions. Analysis A confirmatory factor analysis (CFA) was conducted to explore the factor structure of the “CDMSE Scale for University Students.” SPSS 11.5 was used to analyze the data. In this study, the independent variable was the score on the CDMSE, the moderator variable was the career options with different level of risk, and the dependent variable was the career decision ratings. Student t tests and F tests were used to examine the differences between each factor score and the total scores across gender, schools, and majors. Pairwise comparisons were made with the Least Significance Difference (LSD) method. A repeated-measures analysis was used to analyze participants' choices on the three career options with different levels of risk. Grouping regressions were used to analyze the moderating effect of career option. This study used the model suggested by Wen, Hau, and Chang (2005) for independent variables that are continuous and moderator variables that are categorical. The first step was to sort the file by grouping on
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the variable of career option, and then run the regression analysis by the moderator variable M. If the difference between the regression coefficients is significant, then the moderation role of M is significant (Wen, et al., 2005). RESULTS Construct Validity of the CDMSE Scale for University Students The CFA supported the five-factor model of this scale. The fit indices of the model were all acceptable (CMIN/df = 2.16, RMSEA = 0.074, CFI = 0.814, IFI = 0.816). According to Schermelleh-Engel and Moosbrugger (2003), RMSEA values between 0.05 and 0.08 can be considered as an adequate fit, which indicated that the theoretical model was reflected in the CDMSE Scale for University Students. The internal consistency of the CDMSE was Cronbach's α = .96. Scores on the CDMSE Scale Participants' scores were close to the medium rating on the CDMSE. The highest score of the five factors was self-appraisal (M = 3.60, SD = 0.73), followed by gathering occupational information (M = 3.58, SD = 0.70), goal selection (M = 3.55, SD = 0.68), problem solving (M = 3.52, SD = 0.67), and making plans for the future (M = 3.48, SD = 0.71). There were no significant differences in the scores across gender, school, or major. Moderating Effect of Career Options The repeated-measures analysis showed that the scores for the careers with different levels of risks were significantly differently preferred (F2, 216 = 20.34, p < .001, effect size = 0.44). The LSD results indicated that participants' mean rating of the low-risk option was significantly lower than that of the mid-risk and high-risk options, as showed in Table 1. Hypothesis 1 was supported. Using correlation analysis, a preliminary exploration of the relationship between CDMSE total scores and career decision-making scores was carried out. The total CDMSE score had significant correlations with the high-risk option (r = .30, p < .01) and mid-risk option (r = .21, p < .01) ratings, but not with the low-risk option (r = .10, ns). TABLE 1 DIFFERING RISK LEVELS IN CAREER OPTIONS Model
N
M
SD
Low-risk option
216
4.13
2.01
F
Mid-risk option
216
4.97
1.91 20.34‡
High-risk option
216
5.15
1.85
‡p < .001.
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A simple regression method was adopted to examine the influence of graduates' CDMSE total scores on their career decision-making. The results showed that the total score had a significant effect on career decision making (β = 0.59, F = 25.02, R2 = .04, p < .001). The results of the grouping regressions are shown in Table 2. The effect of graduates' CDMSE on their career option ratings was different for the three different career options. In the high-risk option the effect was largest (F = 20.20, p < .001, R2 = .09), while in the low-risk option it was the smallest (F = 2.04, p < .05, R2 = .01); R2 change was significant. It can be inferred that the differences in career options had a moderating effect on the relationship between CDMSE and career decision making. Thus, Hypothesis 2 was supported. TABLE 2 RESULTS OF THE GROUPING REGRESSIONS OF CDMSE ON CAREER DECISION-MAKING BY CAREER OPTIONS Model Low-risk option
R2
F
ΔR2
β
0.01
2.04
0.01
0.31
Mid-risk option
0.05
10.12†
0.05†
0.65†
High-risk option
0.09
20.20‡
0.09‡
0.87‡
Note.—Dependent variable: career decision-making, predictors: CDMSE. †p < .01. ‡p < .001.
DISCUSSION According to Social Cognitive Career Theory, this study explored Chinese graduates' career decision-making self-efficacy, the differences in career decisions across three different career options with varying risk, and the moderating effect of career options on the relationship between CDMSE and the career decision ratings. Results supported the first hypothesis that the career decisions of Chinese graduates would vary by career options with different levels of risk. The career decision of participants was highest in the high-risk career option, while the scores were lowest in the low-risk career option. This contradicts the results of Chen and Zhang (2009) who showed that career decision scores increased as the career options decreased in risk. This contradiction may be due to two aspects of the design. First, the studies had different numbers and types of participants; Chen and Zhang's (2009) study consisted of 46 university students, whereas this study consisted of 216 participants who were already graduates. Second, the mechanism governing the career decision-making process of graduates is complex. In addition to the career options, there are many other moderating factors such as that tested in the second hypothesis of this study.
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The results also supported the second hypothesis. Career option had a moderating effect on the relationship between CDMSE and career decision ratings. As proposed by Social Cognitive Career Theory, self-efficacy was an antecedent variable to career choice actions (Lent, et al., 1994). Creed, et al. (2006) found that a change in CDMSE was not associated with a change in career indecision over time. They believed it was possible that there are other variables that mediate or moderate the relationship between CDMSE and career indecision longitudinally. Career options with different levels of risk may be one such variable. The influence of CDMSE on career decision is moderated by career options. With a low-risk career option, CDMSE did not influence career decision ratings. The graduates with relatively low CDMSE chose low-risk career options more than the high-risk options, whereas the graduates with relatively high CDMSE chose the high-risk options more than the low-risk career options. Although it is common to choose a job that matches one's abilities, the graduates with high CDMSE tended to prefer a more challenging job. This deviation in career cognition may be one reason for their difficulty in securing a job. Choosing to pursue a more challenging job lessens the chances of being hired. Thus, contrary to the notion of insufficient career opportunities, it appears that the career decision-making of the graduates who preferred a job that was less in accord with their skills may partly contribute to the current lack of employment among graduates. Graduate career counseling programs would help students develop well-reasoned career goals. All participants came from the same province of China, which may have led to a lack of generalizability. In addition, this study focused on CDMSE and career options, but there are other factors that also may affect graduates' career decisions. The present study is based on a laboratory simulation, so the participants' preferences for a particular career choice may not reflect actual career decisions; in the real world, the participants may make other choices due to a tough job market. Future studies should continue to explore the complex psychological mechanisms behind Chinese graduates’ career decisions. REFERENCES
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CHEN, S. P., & ZHANG, Y. (2009) Effects of risk preference and framing effect on college students' career decision-making. Studies of Psychology and Behavior, 3, 183-187. CHUNG, Y. B. (2002) Career decision-making self-efficacy and career commitment: gender and ethnic differences among college students. Journal of Career Assessment, 4, 277-284. CREED, P., PATTON, W., & PRIDEAUX, L. A. (2006) Causal relationship between career indecision and career decision-making self-efficacy: a longitudinal cross-lagged analysis. Journal of Career Development, 1, 47-65. FABIO, A. D., PALAZZESCHI, L., ASULIN-PERETZ, L., & GATI, I. (2013) Career indecision versus indecisiveness: associations with personality traits and emotional intelligence. Journal of Career Assessment, 21, 42-56. GARDRON, J. P. (2011) A psychometric evaluation of the Career Decision Self-efficacy Scale–Short Form among French university students. Journal of Career Assessment, 19, 420-430. GUAY, F., SENÉCAL, C., GAUTHIER, L., & FERNET, C. (2003) Predicting career indecision: a self-determination theory perspective. Journal of Counseling Psychology, 50, 165177. GUSHUE, G. V., SCANLAN-KOLONE, R. L., PANTZER, K. M., & CLARKE, C. P. (2006) The relationship of career decision-making self-efficacy, vocational identity, and career exploration behavior in African American high school students. Journal of Career Development, 1, 19-28. JIN, L. L., YE, S. Q., & WATKINS, D. (2012) The dimensionality of the Career Decision Self-Efficacy Scale–Short Form among Chinese graduate students. Journal of Career Assessment, 20, 520-529. KIRSCH, I. (1986) Early research on self-efficacy: what we already know without knowing we knew. Journal of Social and Clinical Psychology, 4, 339-358. LENT, R. W., BROWN, S. D., & HACKETT, G. (1994) Toward a unifying social cognitive theory of career and academic interest, choice, and performance. Journal of Vocational Behavior, 45(1), 79-122. LUZZO, D. A. (1993) Value of career-decision-making self-efficacy in predicting careerdecision-making attitudes and skills. Journal of Counseling Psychology, 2, 194-199. MINISTRY OF HUMAN RESOURCES AND SOCIAL SECURITY OF THE PEOPLE'S REPUBLIC OF CHINA. (2013) The news conference of the fourth quarter of 2012. Retrieved from http://www. china.com.cn/zhibo/2013-01/25/content_27762443.htm. OSIPOW, S. H., & GATI, I. (1998) Construct and concurrent validity of the Career Decisionmaking Difficulties Questionnaire. Journal of Career Assessment, 6, 347-364. PAULSEN, A. M., & BETZ, N. E. (2004) Basic confidence predictors of career decision-making self-efficacy. The Career Development Quarterly, 52, 354-362. PENG, Y. X., & LONG, L. R. (2001) Research on Career Decision-Making Self-Efficacy Scale in Chinese college students. Applied Psychology, 7, 38-43. QIU, G. P., & ZHANG, L. J. (2009) Research on employment pressure of university graduates. Education Theory and Practice, 5, 6-8. ROBBINS, S. B. (1985) Validity estimates for the Career Decision-Making Self-Efficacy Scale. Measurement and Evaluation in Counseling and Development, 18, 64-71. SCHERMELLEH-ENGEL, K., & MOOSBRUGGER, H. (2003) Evaluating the fit of structural equation models: tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research, 8(2), 23-74.
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STAJKOVIC, A. D., & LUTHANS, F. (1998) Self-efficacy and work-related performance: a metaanalysis. Psychological Bulletin, 2, 240-261. TAYLOR, K. M., & BETZ, N. E. (1983) Applications of self-efficacy theory to the understanding and treatment of career indecision. Journal of Vocational Behavior, 22, 6381. TAYLOR, K. M., & POPMA, J. (1990) An examination of the relationships among career decision-making self-efficacy, career salience, locus of control, and vocational indecision. Journal of Vocational Behavior, 37(1), 17-31. WEN, Z. L., HAU, K. T., & CHANG, L. (2005) A comparison of moderator and mediator and their applications. Acta Psychologica Sinica, 2, 268-274. ZHANG, H., & YAO, J. (2009) The analysis of the graduates' employment psychological disorder and adjustment in vocational school. Journal of Lianyungang Technical College, 1, 71-74. ZHAO, X., LI, N., & ZHANG, D. J. (2009) The relationship between undergraduates' career decision-making self-efficacy and career maturity. Vocational Education Research, 4, 73-75. Accepted February 12, 2014.
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ROLE OF CAREER DECISION-MAKING SELF-EFFICACY AND RISK OF CAREER OPTIONS ON CAREER DECISION-MAKING OF CHINESE GRADUATES1, 2 YINGHUA YE Zhejiang University Summary.—This study investigated the influence of Chinese graduates' career decision-making self-efficacy (CDMSE) and the moderating effect of career options on career decisions. Graduates (92 men, 119 women, 5 unreported gender; M age = 22.3 yr., SD = 1.2) from four different types of universities in Zhejiang Province participated in the study. CDMSE was measured with the CDMSE Scale for University Students, and participants rated their choices on 3 career options with different levels of risk. The results showed that participants were more likely to choose a high-risk option, and that career options moderated the relation between graduates' CDMSE and career decision. Graduate career counseling programs should encourage students to develop more reasonable career goals that match their skills.
The concept of self-efficacy, introduced by Bandura, is defined as “the conviction that one can successfully execute the behavior required to produce certain outcomes” (Kirsch, 1986). Many studies have demonstrated that self-efficacy influences behavior through internal representations and in a variety of settings, such as attributions and work performance (Stajkovic & Luthans, 1998; Ajzen, 2002). Taylor and Betz (1983) assessed the utility of Bandura's self-efficacy theory to the treatment of career indecision, and defined the concept of career decision-making self-efficacy (CDMSE) as the individual's belief that one can successfully complete the tasks necessary to make career decisions (Taylor & Betz, 1983; Luzzo, 1993; Paulsen & Betz, 2004). Taylor and Betz (1983) also developed the CDMSE Scale (later the CDSE) to measure this concept (Luzzo, 1993). The scale was constructed using the five career choice competencies proposed in Crites's model of career maturity: “accurate self-appraisal,” “gathering occupational information,” “goal selection,” “making plans for the future,” and “problem-solving.” Each factor was represented by 10 items on the CDMSE Scale (Betz & Luzzo, 1996). The original scale and subscales had good internal consistency reliability, with Cronbach's α = .97 for the total score and αs ranging from 0.86 to 0.89 for the subscales (Taylor & Betz, 1983; Betz, Klein, & Taylor, 1996). To create a more practical scale for individual assessment, a 25-item short form Address correspondence to Yinghua Ye, College of Education, Zhejiang University, Hangzhou, Zhejiang 310028, People's Republic of China or e-mail ([email protected]). 2 This study was supported by the “ZiJing Plan” of Zheiiang University, and the Philosophy and Social Sciences Foundation of Zhejiang Province (Grant No. 10CGJY05YBQ). 1
DOI 10.2466/01.17.PR0.114k20w9
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ISSN 0033-2941
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Y. YE
(CDMSE–SF, later termed the CDSE–SF) was constructed by eliminating 5 of the 10 items from each of the five factors. A total scale α of 0.94 has been reported for this short form (Betz, Klein, & Taylor, 1996). Several cross-cultural studies have used confirmatory factor analysis to test the underlying factor structure of the CDMSE–SF and CDMSE scales with diverse samples outside of the United States. Gardron (2011) examined the reliability and the factor structure of the CDMSE–SF with 650 French university students; the results revealed a four-factor model that had a better fit than the original five-factor model. Peng and Long (2001) reported that the CDMSE Scale had good reliability, internal consistency, and high discriminant validity in a sample of 1,000 Chinese university students. Jin, Ye, and Watkins (2012) constructed and tested three competing factorial structure models of the CDMSE–SF with a sample of 796 Chinese graduate students, and found that a single-factor model fit the data as well as the five-factor model. These studies suggest that the CDMSE Scale and CDMSE–SF might be sensitive to cultural differences. The theory and measures for career decision-making self-efficacy have been widely applied in studies on career choice behaviors, and researchers have found a positive relationship between scores on the CDMSE and a variety of career variables, such as vocational identity (r = .30; Gushue, Scanlan-Kolone, Pantzer, & Clarke, 2006), career commitment (r = .45; Chung, 2002), and self-esteem (r = .58; Robbins, 1985; Betz & Luzzo, 1996). Other examples include higher scores on CDMSE being related to greater engagement with career exploration activities (r = .31; Gushue, et al., 2006); Luzzo (1993) found that CDMSE was moderately and positively related to career decision-making attitudes (r = .41) but not related skills (r = .05), and in a regression vocational attitude could be predicted by career decision-making capability (β = 0.32), CDMSE (β = 0.31), and age (β = 0.19). Betz (2004) also applied the CDMSE theory to vocational counseling. In addition to the above career variables, CDMSE has been reported to be associated with career choice (Betz & Hackett, 1986). As proposed in social-cognitive career theory, self-efficacy is a direct causal antecedent of career choice goals and actions, such as career decision making (Lent, Brown, & Hackett, 1994). Career decisions are often highly complex and difficult decisions, and indecision can lead to problems during the career selection process (Fabio, Palazzeschi, Asulin-Peretz, & Gati, 2013). The predictive association of CDMSE and career indecision has been found in numerous studies (Osipow & Gati, 1998; Guay, Senécal, Gauthier, & Fernet, 2003; Creed, Patton, & Prideaux, 2006); however, this is an inverse association. For example, one study showed that CDMSE was moderately and negatively related to vocational indecision (r = −.51) and locus of control (r = −.30), whereas moderate positive relationships were found between CDMSE, vocational
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decidedness (r = .46), and occupational self-efficacy (r = .44) in 407 college students (Taylor & Popma, 1990). It can be concluded from the results of the above studies that CDMSE may affect career decision making. Despite the wealth of literature demonstrating that CDMSE is a significant predictor of variables related to the career decision-making process, there has been little research on the effect of CDMSE on the content of career choice, and no studies have examined the moderating effect of environmental variables. According to social-cognitive career theory, proximal environmental variables (e.g., socioeconomic status, job opportunities, or labor laws) can moderate how self-efficacy affects career decisions (Lent, et al., 1994). Chen and Zhang (2009) examined the effect of different levels of risk in a career on career decision making, and found that college students' career decision making was negatively related to the magnitude of risk; i.e., more students chose jobs with low risk. In the present study, constructed career options with three levels of risk were the objective variables, and the operational definition of the career risk was “the acceptability of the job to the individual and the conformity of the individual's qualifications to the job requirements” (Chen & Zhang, 2009). For example, a job seeker faces high career risk when the individual has to accept a job offer that he/she may not be actually interested in and/or when the individual does not possess sufficient qualifications to meet the job requirements. Thus, to clarify this under-researched topic, the present study focused on the influence of CDMSE on Chinese graduates' career choices and on the moderating effect of career risk. Recently, with the increased enrollment in higher education institutions in China, graduates have been faced with increased difficulty in finding a job after graduation. Mismatch between the enrollment expansion and job market demand has led to heated employment competition. China created 12.66 million new urban job opportunities in 2012 (although not specifically requiring university degrees), while the number of new graduates was approximately 6.8 million (Ministry of Human Resources and Social Security of the People's Republic of China, 2013). The fact that many Chinese graduates are still unemployed suggests that the new jobs created do not meet the expectations of university graduates or do not require their university training. Graduates' career decision making and the falling graduate employment rate are the topics worthy of study. Despite the availability of many jobs, apparently the characteristics of these jobs do not seem attractive to the new graduates. Previous studies on the employment problems of university graduates in China have focused on psychological characteristics, mental blocks, and pressures to find a job (Qiu & Zhang, 2009; Zhang & Yao, 2009). However, because the properties of the jobs were not investigated,
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these studies did not describe certain basic aspects of graduates' intrinsic career decision making related to skills and job attractiveness. Based on the aforementioned studies, it was hypothesized that graduates' CDMSE would affect their career decision making, and this effect will be moderated by the different risk levels of the career options available. Hypothesis 1. Chinese graduates' career decisions will be related to the risk level of career options. Hypothesis 2. Career options' risk levels will moderate the relation between CDMSE and career decisions. METHOD Participants The participants (N = 216) were selected from nine classes from four schools in Zhejiang Province. The students were told that the survey was anonymous and that they could withdraw anytime. The measures were distributed to the participants by teachers during class time in the classrooms. No compensation was offered to the students. The interested students completed this survey as volunteers during their class breaks. Participants were all college seniors (92 men, 119 women, 5 did not report gender) from different types of colleges and universities; 72 from normal schools, 63 from business schools, 32 from vocational colleges, and 49 from comprehensive universities. The majors represented were the arts (n = 153), sciences (n = 35), and engineering (n = 28). The mean age of the participants was 22.3 yr. (SD = 1.2). Measures The CDMSE Scale for University Students.—Peng and Long's (2001) Chinese adaptation of the CDMSE Scale was used. This Chinese version replaced five items from the original English version that did not apply to Chinese students with other five items that were more applicable. They used all five factors of the CDMSE Scale, including accurate self-appraisal (e.g., “List some jobs you are interested in”), gathering occupational information (e.g., “Investigate the prospect of one job or career”), goal selection (e.g., “Select one job that will fit your interests”), making plans for the future (e.g., “Determine the steps you need to successfully complete your chosen job”), and problem solving (e.g., “Protect your rights by using the employment policies and regulations”). Eleven items were deleted in the item and exploratory factor analysis process, and this resulted in a total of 39 items. Responses are made on a 5-point Likert scale, with anchors 1: No confidence at all and 5: Complete confidence. The scale scores are the sums of means for all the items, so scores can range from 1 to 5, with higher scores indicating higher career decision-making self-efficacy. The inter-
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nal consistency of the Chinese version in a sample of 1,000 Chinese university students was .93, and the re-test reliability was .66 (Peng & Long, 2001). Zhao, Li, and Zhang (2009) used Peng and Long's (2001) scale to test the relationship between CDMSE and career maturity (r = .57), so the scale has external validity. Career options.—Descriptions of career options were constructed with different levels of “risk.” The risk of a career option was considered to comprise (1) the acceptability of the job to the respondent (satisfaction) and (2) the conformity of the respondent's qualifications to the job requirements. The described career options were: high-risk (high satisfaction/low conformity), mid-risk (moderate satisfaction/moderate conformity), and lowrisk (low satisfaction/high conformity). These three types of career options were presented to participants in a questionnaire. A within-subjects design was used in this study, so every participant responded to all 3 types of the career options. To avoid an order effect, half of the participants started with the low-risk option, and the another half started with the high-risk option. For example, the high-risk career scenario was described as “Here is a job opportunity that you are satisfied with, but you do not fully meet the requirements for this job, so the probability of getting the job is lower. Would you apply for this job?” (Chen & Zhang, 2009). Participants rated the likelihood of applying for each job on a 7-point Likert-type scale, with anchors 1: “I would never apply for it” and 7: “I will definitely apply for it.” Procedure In the first step, the CDMSE scale was administered. Then, the participants read the descriptions of the three different career options and rated the likelihood of making each choice for the three career descriptions. Analysis A confirmatory factor analysis (CFA) was conducted to explore the factor structure of the “CDMSE Scale for University Students.” SPSS 11.5 was used to analyze the data. In this study, the independent variable was the score on the CDMSE, the moderator variable was the career options with different level of risk, and the dependent variable was the career decision ratings. Student t tests and F tests were used to examine the differences between each factor score and the total scores across gender, schools, and majors. Pairwise comparisons were made with the Least Significance Difference (LSD) method. A repeated-measures analysis was used to analyze participants' choices on the three career options with different levels of risk. Grouping regressions were used to analyze the moderating effect of career option. This study used the model suggested by Wen, Hau, and Chang (2005) for independent variables that are continuous and moderator variables that are categorical. The first step was to sort the file by grouping on
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the variable of career option, and then run the regression analysis by the moderator variable M. If the difference between the regression coefficients is significant, then the moderation role of M is significant (Wen, et al., 2005). RESULTS Construct Validity of the CDMSE Scale for University Students The CFA supported the five-factor model of this scale. The fit indices of the model were all acceptable (CMIN/df = 2.16, RMSEA = 0.074, CFI = 0.814, IFI = 0.816). According to Schermelleh-Engel and Moosbrugger (2003), RMSEA values between 0.05 and 0.08 can be considered as an adequate fit, which indicated that the theoretical model was reflected in the CDMSE Scale for University Students. The internal consistency of the CDMSE was Cronbach's α = .96. Scores on the CDMSE Scale Participants' scores were close to the medium rating on the CDMSE. The highest score of the five factors was self-appraisal (M = 3.60, SD = 0.73), followed by gathering occupational information (M = 3.58, SD = 0.70), goal selection (M = 3.55, SD = 0.68), problem solving (M = 3.52, SD = 0.67), and making plans for the future (M = 3.48, SD = 0.71). There were no significant differences in the scores across gender, school, or major. Moderating Effect of Career Options The repeated-measures analysis showed that the scores for the careers with different levels of risks were significantly differently preferred (F2, 216 = 20.34, p < .001, effect size = 0.44). The LSD results indicated that participants' mean rating of the low-risk option was significantly lower than that of the mid-risk and high-risk options, as showed in Table 1. Hypothesis 1 was supported. Using correlation analysis, a preliminary exploration of the relationship between CDMSE total scores and career decision-making scores was carried out. The total CDMSE score had significant correlations with the high-risk option (r = .30, p < .01) and mid-risk option (r = .21, p < .01) ratings, but not with the low-risk option (r = .10, ns). TABLE 1 DIFFERING RISK LEVELS IN CAREER OPTIONS Model
N
M
SD
Low-risk option
216
4.13
2.01
F
Mid-risk option
216
4.97
1.91 20.34‡
High-risk option
216
5.15
1.85
‡p < .001.
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A simple regression method was adopted to examine the influence of graduates' CDMSE total scores on their career decision-making. The results showed that the total score had a significant effect on career decision making (β = 0.59, F = 25.02, R2 = .04, p < .001). The results of the grouping regressions are shown in Table 2. The effect of graduates' CDMSE on their career option ratings was different for the three different career options. In the high-risk option the effect was largest (F = 20.20, p < .001, R2 = .09), while in the low-risk option it was the smallest (F = 2.04, p < .05, R2 = .01); R2 change was significant. It can be inferred that the differences in career options had a moderating effect on the relationship between CDMSE and career decision making. Thus, Hypothesis 2 was supported. TABLE 2 RESULTS OF THE GROUPING REGRESSIONS OF CDMSE ON CAREER DECISION-MAKING BY CAREER OPTIONS Model Low-risk option
R2
F
ΔR2
β
0.01
2.04
0.01
0.31
Mid-risk option
0.05
10.12†
0.05†
0.65†
High-risk option
0.09
20.20‡
0.09‡
0.87‡
Note.—Dependent variable: career decision-making, predictors: CDMSE. †p < .01. ‡p < .001.
DISCUSSION According to Social Cognitive Career Theory, this study explored Chinese graduates' career decision-making self-efficacy, the differences in career decisions across three different career options with varying risk, and the moderating effect of career options on the relationship between CDMSE and the career decision ratings. Results supported the first hypothesis that the career decisions of Chinese graduates would vary by career options with different levels of risk. The career decision of participants was highest in the high-risk career option, while the scores were lowest in the low-risk career option. This contradicts the results of Chen and Zhang (2009) who showed that career decision scores increased as the career options decreased in risk. This contradiction may be due to two aspects of the design. First, the studies had different numbers and types of participants; Chen and Zhang's (2009) study consisted of 46 university students, whereas this study consisted of 216 participants who were already graduates. Second, the mechanism governing the career decision-making process of graduates is complex. In addition to the career options, there are many other moderating factors such as that tested in the second hypothesis of this study.
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The results also supported the second hypothesis. Career option had a moderating effect on the relationship between CDMSE and career decision ratings. As proposed by Social Cognitive Career Theory, self-efficacy was an antecedent variable to career choice actions (Lent, et al., 1994). Creed, et al. (2006) found that a change in CDMSE was not associated with a change in career indecision over time. They believed it was possible that there are other variables that mediate or moderate the relationship between CDMSE and career indecision longitudinally. Career options with different levels of risk may be one such variable. The influence of CDMSE on career decision is moderated by career options. With a low-risk career option, CDMSE did not influence career decision ratings. The graduates with relatively low CDMSE chose low-risk career options more than the high-risk options, whereas the graduates with relatively high CDMSE chose the high-risk options more than the low-risk career options. Although it is common to choose a job that matches one's abilities, the graduates with high CDMSE tended to prefer a more challenging job. This deviation in career cognition may be one reason for their difficulty in securing a job. Choosing to pursue a more challenging job lessens the chances of being hired. Thus, contrary to the notion of insufficient career opportunities, it appears that the career decision-making of the graduates who preferred a job that was less in accord with their skills may partly contribute to the current lack of employment among graduates. Graduate career counseling programs would help students develop well-reasoned career goals. All participants came from the same province of China, which may have led to a lack of generalizability. In addition, this study focused on CDMSE and career options, but there are other factors that also may affect graduates' career decisions. The present study is based on a laboratory simulation, so the participants' preferences for a particular career choice may not reflect actual career decisions; in the real world, the participants may make other choices due to a tough job market. Future studies should continue to explore the complex psychological mechanisms behind Chinese graduates’ career decisions. REFERENCES
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