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行政院國家科學委員會專題研究計畫 成果報告

資訊專業人員的生涯承諾-從投資模型的觀點

研究成果報告(精簡版)

計 畫 類 別 : 個別型 計 畫 編 號 : NSC 98-2410-H-151-005- 執 行 期 間 : 98 年 08 月 01 日至 99 年 07 月 31 日 執 行 單 位 : 國立高雄應用科技大學資訊管理系 計 畫 主 持 人 : 傅振瑞 計畫參與人員: 碩士級-專任助理人員:黃姿寧 報 告 附 件 : 出席國際會議研究心得報告及發表論文 公 開 資 訊 : 本計畫涉及專利或其他智慧財產權,1 年後可公開查詢

中 華 民 國 99 年 10 月 31 日

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行政院國家科學委員會補助專題研究計畫

行政院國家科學委員會補助專題研究計畫

行政院國家科學委員會補助專題研究計畫

行政院國家科學委員會補助專題研究計畫

■ 成 果 報 告

成 果 報 告

成 果 報 告

成 果 報 告

□期中進度報告

期中進度報告

期中進度報告

期中進度報告

資訊專業人員的生涯承諾-從投資模型的觀點

計畫類別:■個別型計畫 □整合型計畫

計畫編號:NSC 98-2410-H-151-005-

執行期間: 2009 年 8 月 1 日至 2010 年 7 月 31 日

執行機構及系所:

計畫主持人:傅振瑞

計畫參與人員: 黃姿寧

成果報告類型(依經費核定清單規定繳交):■精簡報告 □完整報告

本計畫除繳交成果報告外,另須繳交以下出國心得報告:

■赴國外出差或研習心得報告

□赴大陸地區出差或研習心得報告

□出席國際學術會議心得報告

□國際合作研究計畫國外研究報告

處理方式:

除列管計畫及下列情形者外,得立即公開查詢

□涉及專利或其他智慧財產權,□一年■二年後可公開查詢

中 華 民 國 2010 年 10 月 1 日

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Career Commitment of Information Technology Professionals–

The Investment Model Perspective

Jen-Ruei Fu

Department of Information Management, National Kaohsiung University of Applied Sciences, Taiwan fred@cc.kuas.edu.tw

Abstract

Using investment model as a theoretical lens, this study provides a compelling theoretical model that helps understand the differences between IT professionals and non-IT employees on their career commitment. Data to test the hypotheses were drawn from a cross-sectional field study of top-1000 large-scale companies in Taiwan. The results generally supported the research model. Career satisfaction was the most important determinant of career commitment. Additionally, career investment and professional self-efficacy were significant in predicting individuals’ career commitment. The moderating analysis revealed distinct patterns that IT professionals and non-IT employees seemed to hold different attitudes about career. Interestingly, the threat of professional obsolescence and professional self-efficacy is more salient to ITPs, compared with non-IT employees. Insight and implications on management strategy for IT/HR managers are discussed.

Keywords: Career commitment, Investment model, Professional obsolescence, Professional self-efficacy, IT professionals

1. INTRODUCTION

*

The global economy is undergoing a fundamental change. Increasingly, the organizations can no longer ensure the stability and security of personal career development. This process affects the lives of most people in the age of knowledge economy, but it has a special significance for information technology (IT) professionals1. Carson and Bedeian (1994) have suggested that coping with the uncertainty associated with changes such as mergers, acquisitions, downsize and layoffs has caused many employees to intensify their focus on, and commitment to, the aspect of their work life and professional career, instead of their working organizations.

Blau (1985) defined career commitment as “one’s attitude towards one’s profession or vocation”. It is conceptualized as the extent to which someone identifies with and values his or her profession or vocation and the amount of time and effort spent acquiring relevant knowledge. Career commitment is important because of its potential links to work performance. Past research indicates that individuals who are highly committed to their careers have been shown to spend more time in developing skills, and show less intention to withdraw from their careers and jobs, and have better job performance (Majd & Ibrahim, 2008).

1

In this study, IT professionals refer to people who are directly engaged in the mainstream of information systems work, i.e., those who design, develop, implement, and support computer-based information systems.

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However, it is becoming increasingly difficult for IT professionals (hereafter ITPs) to commit to their careers. ITPs today perceive significantly more occupational stress than their counterpart. Long working hours, unexpected user demands, unmet deadlines, and skills’ obsolescence are not uncommon for ITPs (Thong & Yap, 2000). Thus, there are many compelling social and economic reasons why ITPs decide or be obliged to consider changing careers.

Past research noted that ITPs have lower social needs than non-IT individuals. And ITPs have a higher need for achievement than those in some other occupations (Ferratt & Short, 1986). Couger et al. (1994) showed that users and IT staffs have different beliefs and views of company policies. Therefore, these findings challenge the assumption that all employees are homogenous in their work value and thus the “one size fits all” arrangements seem not feasible. Focusing on the career concerns of employees, this study explores differences in career commitment and its determinants among ITPs and non-IT employees. Investigating career commitment contributes to our understanding of how people develop, make sense of, and integrate their multiple work-related commitments. To our knowledge, career commitment has been examined to a limited extent in the literature. However, the career at hand and its future potential may be much more important and consciously contemplated by an employee. We propose that relationship factors (e.g., investment, availability of alternatives, and satisfaction) and individual variables (e.g., professional self-efficacy) play an integral part in whether an individual stays in or leaves a career. Important situational variables (the threat of professional obsolescence) were also employed. Moreover, we examined the differences in career concerns between ITPs and non-IT employees.

2. THEORETICAL

BACKGROUND

2.1 Interdependence Theory and Investment Model

One model seems ideal to the investigation the relationship factors involved in the relationship between a professional and his/her career is the investment model. The investment model is based on Kelley and Thiabaut’s (1978) interdependence theory, which holds that interdependence in a relationship is characterized by satisfaction and dependence. Rusbult (1983) extends these notions by introducing the concept of investment which is defined as the resources (e.g., time, energy, effort, or money) that a person has put into a relationship. Rusbult postulates that such investments would be lost if the relationship ends. Using investment model as a theoretical lens, it can be reasonably inferred that the present situation and the anticipated future situation (alternative career, and loss of previous investments) may determine ITPs’ behavior and attitudes toward career changes.

The primary goal of investment model is to predict the degree of commitment to ongoing relationships. The investment model is considered a rich interdisciplinary model predicted on psychological and sociological constructs. It has been applied to wide range of relationships: employee’s commitment, job satisfaction, and turnover (Rusbult & Farrell, 1983), satisfaction and commitment in friendship (Rusbult, Martz, & Agnew, 1998). Findings in past research suggest that investment model is robust and explains the maintenance and termination of a variety of different types of relationships across a variety of contexts.

2.2 Professional Obsolescence and Self-Efficacy of IT Professionals

One major factor contributing to the turnover of ITPs is the work exhaustion triggered by constant changes and

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obsolescence in technology (Moore, 2000; Rong & Grover, 2009). Many ITPs realize that they either must constantly engage in retraining or seek out another field of employment (Joseph, Ang, & Slaughter, 2005). Additionally, in an environment of constant change, Trimmer, Blanton, & Schambach (1998) suggested that ITPs’ self-efficacy would stimulate their motivation to participate in updating activities. Cherniss (1991) suggested that professional self-efficacy plays a central role in the maintenance of individual career commitment. However, little work has been done to understand how the threat of professional obsolescence and professional self-efficacy influence their career changing decisions.

3. RESEARCH MODEL AND

HYPOTHESES

Career Investment (INV) Availability of Career Alternatives (ALT) Career Satisfaction (SAT) Career Commitment (COM) Threat of Professional Obsolescence (TPO) Professional Self-Efficacy (PSE) Investment Model

Figure 1: The Research Model

3.1 Investment Model

Satisfaction refers to the positive versus negative affect experienced in a relationship. Career satisfaction is defined as the level of overall happiness experienced through one’s choice of career. All things considered, it is easier for a relationship to continue when it feels good than when it feels bad. A satisfied employee is expected to like his or her career and will most likely to have a favorable disposition and be committed to his or her career. Thus, it is reasonable to expect that the more satisfied professionals are with their careers, the higher their career commitment.

H1: Career satisfaction positively influences individuals’ career commitment. Rusbult, Martz and Agnew (1998) suggests the commitment to a relationship depends on how much we have already invested in the relationship. Career investment reflects accumulated investments in one’s career that would be lost or deemed worthless if one were to pursue a new career. ITPs invested a lot of time to learn programming languages, operating systems, methodologies and tools, etc. However, these specialized techniques and knowledge are specific and non-portable and are valuable only in designing and implementing information systems. The loss of investment (e.g., time, training, profession ties) can exact an emotional toll on a person changing their career.

The concept of investment is akin to the specific human asset in transaction cost theory since the investments made to support a particular career have a higher value to that career than they would have if they were redeployed for any other purpose. Thus, the individual is “tied in” in a hold-up situation. The investment generate value in one hand, it also create sunk cost in another to hinder the professional from switching to another career. Thus, having a high level of investment in its continuity, the individual would tend to persist in their careers.

H2: Career investment positively influences individuals’ career commitment. The final component of the investment model, availability of alternative options, gauges the perceived lack/abundant of available options for pursuing a new career. If the unmet need is strong and could be satisfied by changing careers, the employee may quit and switch with a better career alternative. Expectancy research suggests that attitudes are influenced by individuals’ comparisons of their current situation with external opportunities (Thatcher, Stepina, & Boyle, 2002). A lack of attractive alternative options increases individuals’ commitment

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to their current ones. When individuals perceive many career alternatives, they will express lower levels of career commitment. Thus, we predict:

H3: Availability of Career alternatives negatively influences individuals’ career commitment.

3.2 The Threat of Professional Obsolescence

Professional obsolescence is defined as the erosion of professional competencies required for successful performance (Dubin, 1990). According to Fossum, Arvey, Paradise, and Robbins(1986), obsolescence occurs when the job incumbent previously possessed talents commensurate with requirements of the profession; however, change in the knowledge domain or change in the individual has resulted in a mismatch. Consequently, individuals must put many efforts to remain technologically current and continuously acquire new knowledge and skills because it affects their employability, career development, and compensation. Professionals need to be able to face situations in which their knowledge no longer applies. As a result, individuals who feel the threat of professional obsolescence may express less committed to their career. Hence, we predict that individuals are opting to switch careers as a result of the threat of professional obsolescence.

H4: The threat of professional obsolescence negatively influences individuals’ career commitment.

3.3 Professional Self-Efficacy

Professional self-efficacy is the degree that one believes that he or she is capable of successfully managing one’s professions (Kossek, Roberts, Fisher, & Demarr, 1998). Bandura (1986) suggests that a key to the willingness to commitment a specific vocational choice, is belief in the capacity to mobilize the physical, intellectual, and emotional resources needed to succeed in the

occupation of choice, that is, professional self-efficacy. Following the logics, we postulate that high self-efficacy supports career commitment. Thus,

H5: Professional Self-Efficacy positively influences individuals’ career commitment.

ITPs need the up-to-date knowledge and necessary ski1ls to maintain effective performance. Unlike other professionals where basic knowledge remains enduring, the half-life of knowledge and skills in the IT profession is estimated at less than two years (Dubin, 1990). Therefore, an ITP’s stock of competencies erodes and comes under the continuous threat of professional obsolescence (Dubin, 1990; Pazy, 1996). Therefore, the erosion of competencies is imminent in the careers and constitutes a potential threat to ITPs, which will undermine their commitment to IT career. On the contrary, non-IT employee may be less aware of the threat of professional obsolescence. Thus, compared with non-IT employees, the threat of professional obsolescence would be considered a more serious inhibitor to ITPs’ career commitment. Thus, we predict:

H6: The relationship between the threat of professional obsolescence and career commitment will be stronger for ITPs than for non-IT employees.

While knowledge is the key resource and investment for ITPs, it is difficult for ITPs to accumulate knowledge overtime. Advancement in IT fields can make some professional knowledge irrelevant or useless. Job requirements in terms of skills, competencies, qualifications and trainings for ITPs are changing rapidly. It thus made most of the past investment worthless. The unending effort to keep up-to-date requires an enormous investment of energy. These new competencies, however, may bear little relation to past competencies. Therefore, an ITP’s stock of competencies erodes and quickly turns into sunk cost. Thus, for ITPs, their investment in IT professions did not actually create a “hold-up” situation, and the causal link

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between career investment and career commitment were attenuated gradually, as compared with non-IT employees.

H7: The relationship between career investment and career commitment will be stronger for non-IT employees than for ITPs.

Self-efficacy represents judgments or beliefs about one’s performance capabilities in a particular domain (Wood & Bandura, 1989). Given the rapid advancement of information technology, individuals’ judgments about their capabilities and confidence for continuous update are likely to influence their decision to commit to IT careers. Compared with non-IT employees, ITPs with low level of professional self-efficacy may find it hard to continue their career thus make their future commitment less likely. Thus, we hypothesize:

H8: The relationship between professional self-efficacy and career commitment will be stronger for ITPs than for non-IT employees.

4. METHOD

Field research employing quantitative analysis of self-report questionnaire data is the primary method of this study. Furthermore, qualitative interviews and data gathered from senior managers were used to supplement the primary quantitative analysis and evaluate potential common-method bias.

Data to test the model and hypotheses were drawn from a cross-sectional field study from Top-1000 large-scale companies in Taiwan. Invitation emails were sent to CIOs to invite their subordinates and employees from other functional departments (for example, accounting, law, marketing, manufacturing) to participate. Eight-two organizations agreed to distribute questionnaires (in paper form). Individuals with less than one-year working experience were excluded to ensure that respondents had sufficient working history to form career

attitudes. Respondents’ participations in this study were strictly voluntary.

Constructs were measured using multiple-item scales, drawn from pre-validated measures in related studies whenever possible. The survey instrument was created after conducting literature reviews and in depth interviews with several ITPs. Preliminary versions of this questionnaire were reviewed and discussed by peers and practitioners.

The origin version of questionnaire was written in English and then we translated them to traditional Chinese. To ensure consistency between the English and Chinese versions, the Chinese survey was checked by a professor with MIS discipline and three MIS domain expert proficient in both English and traditional Chinese in a panel discussion. Items which appeared inconsistent were discussed and then revised.

Table 1. Constructs and Measures

Construct Items Source

Career Commitment 9 Carson and Bedeian (1994)

Career satisfaction 5 Greenhaus et al. (1990)

Professional Self-Efficacy 4 Developed for this study

Attractiveness of Career Alternative 3 Dam (2005) Investment 5 Dam (2005). Threat of Professional Obsolescence 10 Pazy (1994)

5. DATA ANALYSIS AND

RESULTS

5.1 Samples

A total of 501 respondents participated in the study. This represented 41.8% of those who had received mailed questionnaires (N=1200). The sample was divided into groups of 255 ITPs, and 246 non-IT employees.

5.2 Scale Validation

PLS was used to assess the psychometric properties of all scales used in this study and the structural model. PLS offers an alternative for incorporating formative as well as reflective indicators in one model. Since career commitment and threat of professional obsolescence are formative constructs, PLS appeared the

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most appropriate technique based on the properties of the scale at hand.

Table 1:Correlation of Latent Variables (Full Sample)

Composite Reliability

SAT ALT INV PSE CAP CAI CAR TPO_S TPO_T TPO_C

SAT 0.90 0.82 ALT 0.89 -0.04 0.82 INV 0.92 0.14 -0.15 0.75 PSE 0.92 0.12 0.25 0.20 0.81 CAP 0.93 0.22 0.07 0.42 0.37 0.88 CAI 0.95 0.16 0.22 0.30 0.48 0.53 0.91 CAR 0.93 -0.22 0.13 -0.02 -0.03 -0.30 -0.15 0.88 TPO_S 0.87 -0.07 0.27 0.24 0.15 0.17 0.15 0.16 0.76 TPO_T 0.82 -0.10 0.20 0.17 0.04 -0.04 0.06 0.19 0.55 0.83 TPO_C 0.88 -0.02 0.03 0.06 0.04 -0.01 0.02 0.06 0.08 0.26 0.71

The shaded numbers on the leading diagonal are the square root of the variance shared between the constructs and their measures. Off diagonal elements are the correlations among constructs.

Legend: SAT: Career Satisfaction, Alt: Availability of Career Alternatives, INV: Career Investment, SEE: Professional Self-Efficacy, CAP: Career Planning, CAI: Career Identity, CAR: Career Resilience, TPO: Threat of Professional Obsolescence (S: Scope, T: Time, C: Social Comparison)

A CFA was conducted in PLS to assess item loadings, disrciminant validity, and internal consistency of all scales. Item loadings and internal consistencies greater than 0.70 are considered acceptable (Fornell & Larcker, 1981). Factor analysis suggested that all items exhibit high loadings on their respective constructs. All indicators load more highly on their own construct than on other constructs. To assess discriminant validity, we found that all constructs shared more variance with their indicators than with other constructs. Thus these results point to the discriminant validity of our scales. Likewise, the values for internal consistency were all above the suggested minimum of 0.70. Overall, all reflective constructs and sub-constructs displayed adequate internal consistency and discriminant validity.

5.3 Hypothesis Testing

With the exception of professional obsolescence and career commitment, all other constructs in the model are modeled as reflective. The formative constructs were modeled as such since their underlying dimensions do not necessarily covary (Jarvis, MacKenzie, & Podsakoff, 2003). Since PLS does not directly support second order factors, for the formative constructs, factor scores were calculated for each dimension and used in the structural model. Following the suggestion of Chin (2003), we modeled the path weights from the first- to the second-order constructs (the weights of formative constructs are treated as PLS coefficients, and the variance explained in the second-order construct is unity).

Furthermore, multi-group or between-group analyses were common in the information systems literature (Qureshi & Compeau, 2009). Some

researchers have suggested that the moderated multiple regression or other techniques such as LISREL or PLS have greater capacity to detect moderation effects (i.e., more statistical power than does the subgroup analysis strategy (Cohen, 2003)). However, Stone-Romero, Alliger, & Aguinis (1994) suggested moderated multiple regression is subject to type II error if the moderator is a dichotomous variable. Researchers have concluded that subgroup analysis is an appropriate method for testing strength moderation in the case of nominal moderating variables. In the current research, we tested the difference between ITPs and non-IT employees. As suggested by Qureshi & Compeau (2009), we estimated model parameters for each group separately and then performed between-group test of significance across the groups, using a t–test with pooled standard errors.

The seven hypotheses presented earlier are tested collectively using the partial least squares (PLS), and the significance levels were assessed with 200 bootstrap runs. We then ran the structural model on the two sub-samples respectively. Results demonstrated a difference between ITPs and non-IT employees. Variance explained for career commitment is 53.8% and 42.0%, respectively. In general, the findings supported most of the hypotheses, except for H3 and H4 were partially supported. Career satisfaction appeared a strong predictor of career commitment (β=0.48, p-value < 0.01 for ITPs, and β=0.57, p-value < 0.01 for non-IT employees) and accounted for a substantial amount of variance, thus H1 was supported. Career investment (β=0.17, p-value < 0.01 for ITPs, β=0.14, p-value < 0.01 for non-IT employees) and professional self-efficacy (β=0.27, p-value < 0.01, and =0.12, p-value < 0.01) were positively related to

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career commitment, which supported H2 and H5. The negative effects of threat of professional obsolescence on career commitment (β=-0.18, p-value < 0.01) was found for IT professionals but not for non-IT employees, thus H4 was partially supported. Finally, the effect of availability of career alternatives on career commitment was significant for non-IT employees but not for ITPs, thus H3 was partially supported.

:first order construct :second order construct (formative)

INV ALT SAT COM R2=0.54 PSE TPO Investment Model 0.48 (6.62) .09 (1.68) 0.17 (2.70) -0.18 (2.88) 0.27 (4.39)

1. Structural path estimates are the standardized parameter estimates, and the associated t-values are in parentheses. Solid-lines stand for significant paths and dotted-lines for non-significant ones. Measurement model is not shown above for purposes of clarity. 2. The strength of the relationships among the constructs is represented by

standardized path coefficients.

Figure 2: Result of PLS analysis (Full-Sampled Model, n=501)

To more rigorously compare the results across groups, we calculated t-statistics to evaluate the differences in path coefficients across groups. Before doing this, it was necessary to assess whether the latent constructs were perceived in a similar fashion between the two groups (Carte & Russell, 2003). We found loading patterns and factor loadings were very similar, thus permitting between-group path comparison. We calculated t-statistics to evaluate the differences in path coefficients across the two groups, using procedures described by Chin et al. (2004), as follows:

where pi, path coefficient in structural model

of involvement i or trust i; nj, sample size of dataset

for involvement i or trust i; SEi, standard error of

path in structural model for involvement i or trust i; tij, t-statistic with n1 + n2–2 degrees of freedom.

The approach we used and the procedure we employed is consistent with recent research evaluating the influence of nominal group membership on the nomological network of relationships between IT-related constructs. For instance, Keil et al. (2000) utilized this approach to test the moderating effects of national culture on risk taking and the willingness to continue a project. In order to test the moderating effects, we closely patterned our analysis after that of Keil et al. (2000).

We estimated three separate models in PLS: the IT employee subgroup, and the non-IT employee subgroup. We then tested for differences across the two models using the test for differences as suggested by Chin et al. (2003) and implemented by Keil et al. (2000).

Table 3. Results of Multi-Group Comparison

ITP Group (n=255) Non-IT Group(n=246) Path

Path Stdev t Path Stdev t Difference df t SAT  CA 0.48 0.059 6.52 0.57 0.477 6.09 -0.09 499 -0.19 ALT CA 0.09 0.051 1.47 0.19 0.141 1.99 -0.1 499 -0.68 INV  CA 0.17 0.069 2.38 0.14 0.124 1.67 0.03 499 0.21 TPO  CA -0.18 0.044 -2.31 -0.04 -0.038 -0.40 -0.14 499 -2.41 PSE  CA 0.27 0.06 4.54 0.11 0.063 1.67 0.16 499 1.92

A comparison of results in Table 3 suggests that significant differences exist across the two groups. For ITPs, the path coefficients from career investment to career commitment are not significantly different (t=0.21, p>0.1). Thus, H7 was not supported. Finally, the results provide support on the relationship of the threat of professional obsolescence (t= -2.41, p<0.01) and professional self-efficacy (t= 1.92, p<0.01) with career commitment, which support H6 and H8.

6. DISCUSSION

The study aims to understand the differences in career concerns between ITPs and non-IT employees. A basic understanding obtained from this study is the magnitude and significance of relationships between career commitment and its existing antecedents. Overall, investment model was partially supported. Findings indicated that career satisfaction is the strongest drivers of career commitment. Individuals who perceived greater satisfaction reported greater career commitment. Additionally, career investment and professional self-efficacy were significant in predicting individuals’ career commitment.

Table 4. Uni-variate Analysis of Constructs

ITP Group Non-IT Employee

Group Construct

Mean Stdev Mean Stdev

F Sig. SAT 4.28 1.19 4.17 1.13 1.10 0.295 ALT 4.31 1.31 4.18 1.25 1.25 0.265 INV 4.38 1.23 4.07 1.23 8.02 0.005 SEE 4.40 1.15 4.34 1.05 0.38 0.539 CAP 4.26 1.21 4.22 1.20 0.02 0.662 CAI 4.60 1.29 4.59 1.16 0.19 0.885 CAR 4.30 1.40 4.29 1.38 0.02 0.889 TPO_S 5.12 0.85 4.17 1.10 116.40 0.000 TPO_T 4.48 1.14 3.63 1.30 61.07 0.000 TPO_C 4.51 1.09 3.72 1.21 60.41 0.000

Across the two groups, we found that ITPs and non-IT employees seemed to hold different attitudes careers. First, the negative impacts of the threat of professional obsolescence on career commitment for ITPs implied that an increase in the threat of

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professional obsolescence significantly lowers the possibility that ITPs will commit their career in IT profession. In contrast, analysis of the non-IT employees group revealed a distinct pattern that the professional obsolescence did not seem to be an important antecedent to their career commitment. The uni-variate analysis shown in Table 4 indicated that ITPs did feel more threaten by professional obsolescence than non-IT employees did. In sum, we conclude that professional obsolescence is an important factor and constitutes a substantial threat to ITPs’ intention to continue their current career, but not for non-IT employees.

Second, the professional self-efficacy is more salient to ITPs’ career commitment compared with non-IT employees. In comparison with non-IT employees, ITPs reported higher career commitment when they perceived higher professional self-efficacy. This suggests that ITPs’ judgments about their capabilities for successful performance significantly influence their attitudes of committing to IT careers.

7. IMPLICATIONS FOR PRACTITIONERS An understanding of the relative importance allows IT/HR managers to design more effective programs to retain valuable IT human resources. Furthermore, ITPs and non-IT employees seemed to hold different attitude about career. Thus, managers should scheme proactively proper career development programs for different occupational groups. Our results also provide additional insights on management strategy for IT/HR managers.

First, ITPs don’t respond to the same stimuli that non-IT employees do. In contrast to non-IT employees, results of this study suggested that ITPs who feel threaten by professional obsolescence tend to consider career change. the uni-variate analysis in table 4 shows that ITPs invested more on their careers than non-IT employees did. In addition, ITPs perceived more threat of professional obsolescence than their counterparts. It suggested that ITPs have invested a great deal of time and effort in developing their professional skills. However, they suffer seriously from the threat of professional obsolescence, which would make their prior investment in vain. Thus, managers and human resource practitioners need to understand how the threat of obsolescence is perceived by ITPs, and what professionals actually do to alleviate this threat.

Second, self-efficacy has stronger effect on career commitment for ITPs than for non-IT

employees. Thus, high self-efficacy may help an ITP commit his/her professional career. Since the advancement in IT fields makes some skills irrelevant very quickly or over-emphasizes others, it is difficult for an ITP’s without high professional self-efficacy to persist long enough in constant renewing, learning and updating his/her knowledge. Thus, organizations should select job candidates possessing high self-confidence because high professional self-efficacy employees are likely to be motivated to continue their career and remain proficient, especially for ITPs.

Third, satisfaction with present professional career was among all the variables the most important determinant of career commitment, especially for senior ITPs. Thus, management should constantly keep track on their satisfaction level of their career.

Fourth, the greater perceived accumulated costs may lead to a greater sense of obligation to one’s career. This suggests that increasing one’s accumulated investment over time, through for example increased participation in continuing education activities or professional associations, would further increase one’s career commitment.

8. CONCLUSION

As various technologies expand their reach, many issues facing the IT worker of today are likely to filter down and become the reality for increasing numbers of non-IT employees. While the threat of professional obsolescence may be greater or more immediate for ITPs, it represents a potential problem for all evolving, highly skilled professions. Therefore, studying IT workers today may yield important lessons for managing the general workforce of tomorrow. Findings in this study should be relevant to all such professionals. A deeper understanding of career commitment can assist employers in devising appropriate management strategies to increase favorable outcomes.

While the search for related literature was grossly limited, this would affect the robustness of the discussion on the findings. The study has a number of limitations. First, the use of self-report scale to measure the variables suggests the possibility that common method variance may account for some of the results obtained. It would be appropriate to develop more direct objective measures for career commitment. Second, the use of single-source data may have inflated correlation coefficients. Third, the proportions of unexplained

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variance indicate that variables not included in the model might be important to consider. Additional variables might further improve the model’s ability to predict ITPs’ career commitment.

REFERENCES

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2. Blau, G. J. 1985. The Measurement and Prediction of Career Commitment. Journal of Occupational psychology, 58(4): 277-288. 3. Carson, K. D., & Bedeian, A. G. 1994. Career

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Investment Model: The Development (and Deterioration) of Satisfaction and Commitment in Heterosexual Involvements. Journal of Personality and Social Psychology, 45(1): 101-117.

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Is Information Technology Career Unique?

Exploring Differences in Career Commitment and its Determinants among

IT and non-IT Employees

Jen-Ruei Fu

Department of Information Management,

National Kaohsiung University of Applied Sciences, Taiwan fred@cc.kuas.edu.tw

Abstract

Using investment model as a theoretical lens, this study provides a compelling theoretical model that helps understand the differences between IT professionals and non-IT employees on their career commitment. Data to test the hypotheses were drawn from a cross-sectional field study of top-1000 large-scale companies in Taiwan. The results generally supported the research model. Career satisfaction was the most important determinant of career commitment. Additionally, career investment and professional self-efficacy were significant in predicting individuals’ career commitment. The moderating analysis revealed distinct patterns that IT professionals and non-IT employees seemed to hold different attitudes about career. Interestingly, the threat of professional obsolescence and professional self-efficacy is more salient to ITPs, compared with non-IT employees. Insight and implications on management strategy for IT/HR managers are discussed.

Keywords: Career commitment, Investment model, Professional obsolescence, Professional

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1. Introduction

The global economy is undergoing a fundamental change. Increasingly, the organizations can no longer ensure the stability and security of personal career development. This process affects the lives of most people in the age of knowledge economy, but it has a special significance for information technology (IT) professionals1. Carson and Bedeian (1994) have suggested that coping with the uncertainty associated with changes such as mergers, acquisitions, downsize and layoffs has caused many employees to intensify their focus on, and commitment to, the aspect of their work life and professional career, instead of their working organizations.

Blau (1985) defined career commitment as “one’s attitude towards one’s profession or vocation”. It is conceptualized as the extent to which someone identifies with and values his or her profession or vocation and the amount of time and effort spent acquiring relevant knowledge. Career commitment is important because of its potential links to work performance. Past research indicates that individuals who are highly committed to their careers have been shown to spend more time in developing skills, and show less intention to withdraw from their careers and jobs, and have better job performance (Majd & Ibrahim, 2008). However, it is becoming increasingly difficult for IT professionals (hereafter ITPs) to commit to their careers. ITPs today perceive significantly more occupational stress than their counterpart. Long working hours, unexpected user demands, unmet deadlines, and skills’ obsolescence are not uncommon for ITPs (Thong & Yap, 2000). Thus, there are many compelling social and economic reasons why ITPs decide or be obliged to consider changing careers.

Past research noted that ITPs have lower social needs than non-IT individuals. And ITPs have a higher need for achievement than those in some other occupations (Ferratt & Short, 1986). Couger et al. (1994) showed that users and IT staffs have different beliefs and views of company policies. Therefore, these findings challenge the assumption that all employees are homogenous in their work value and thus the “one size fits all” arrangements seem not feasible. Focusing on the career concerns of employees, this study explores differences in career commitment and its determinants among ITPs and non-IT employees. Investigating career commitment contributes to our understanding of how people develop, make sense of, and integrate their multiple work-related commitments. To our knowledge, career commitment has been examined to a limited extent in the literature. However, the career at hand and its future potential may be much more important and consciously contemplated by an employee. We propose that relationship factors (e.g., investment, availability of alternatives, and satisfaction) and individual variables (e.g., professional self-efficacy) play        

1 In this study, IT professionals refer to people who are directly engaged in the mainstream of information

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an integral part in whether an individual stays in or leaves a career. Important situational variables (the threat of professional obsolescence) were also employed. Moreover, we examined the differences in career concerns between ITPs and non-IT employees.

2. Theoretical Background

2.1 Interdependence Theory and Investment Model

One model seems ideal to the investigation the relationship factors involved in the relationship between a professional and his/her career is the investment model. The investment model is based on Kelley and Thiabaut’s (1978) interdependence theory, which holds that interdependence in a relationship is characterized by satisfaction and dependence. Rusbult (1983) extends these notions by introducing the concept of investment which is defined as the resources (e.g., time, energy, effort, or money) that a person has put into a relationship. Rusbult postulates that such investments would be lost if the relationship ends. Using investment model as a theoretical lens, it can be reasonably inferred that the present situation and the anticipated future situation (alternative career, and loss of previous investments) may determine ITPs’ behavior and attitudes toward career changes.

The primary goal of investment model is to predict the degree of commitment to ongoing relationships. The investment model is considered a rich interdisciplinary model predicted on psychological and sociological constructs. It has been applied to wide range of relationships: employee’s commitment, job satisfaction, and turnover (Rusbult & Farrell, 1983), satisfaction and commitment in friendship (Rusbult, Martz, & Agnew, 1998). Findings in past research suggest that investment model is robust and explains the maintenance and termination of a variety of different types of relationships across a variety of contexts.

2.2 Professional Obsolescence and Self-Efficacy of IT Professionals

One major factor contributing to the turnover of ITPs is the work exhaustion triggered by constant changes and obsolescence in technology (Moore, 2000; Rong & Grover, 2009). Many ITPs realize that they either must constantly engage in retraining or seek out another field of employment (Joseph, Ang, & Slaughter, 2005). Additionally, in an environment of constant change, Trimmer, Blanton, & Schambach (1998) suggested that ITPs’ self-efficacy would stimulate their motivation to participate in updating activities. Cherniss (1991) suggested that professional self-efficacy plays a central role in the maintenance of individual career commitment. However, little work has been done to understand how the threat of professional obsolescence and professional self-efficacy influence their career changing decisions.

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3. Research Model and Hypotheses

3.1 Investment Model

Satisfaction refers to the positive versus negative affect experienced in a relationship. Career satisfaction is defined as the level of overall happiness experienced through one’s choice of career. All things considered, it is easier for a relationship to continue when it feels good than when it feels bad. A satisfied employee is expected to like his or her career and will most likely to have a favorable disposition and be committed to his or her career. Thus, it is reasonable to expect that the more satisfied professionals are with their careers, the higher their career commitment.

H1: Career satisfaction positively influences individuals’ career commitment.

Rusbult, Martz and Agnew (1998) suggests the commitment to a relationship depends on how much we have already invested in the relationship. Career investment reflects accumulated investments in one’s career that would be lost or deemed worthless if one were to pursue a new career. ITPs invested a lot of time to learn programming languages, operating systems, methodologies and tools, etc. However, these specialized techniques and knowledge are specific and non-portable and are valuable only in designing and implementing information systems. The loss of investment (e.g., time, training, profession ties) can exact an emotional toll on a person changing their career.

The concept of investment is akin to the specific human asset in transaction cost theory since the investments made to support a particular career have a higher value to that career than they would have if they were redeployed for any other purpose. Thus, the individual is “tied in” in a hold-up situation. The investment generate value in one hand, it also create sunk cost in another to hinder the professional from switching to another career. Thus, having a

Figure 1. The Research Model

Career Investment  (INV)  Availability of  Career Alternatives  (ALT)  Career Satisfaction  (SAT) Career  Commitment  (COM) Threat of Professional  Obsolescence  (TPO) Professional  Self‐Efficacy  (PSE) Investment Model 

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high level of investment in its continuity, the individual would tend to persist in their careers.

H2: Career investment positively influences individuals’ career commitment.

The final component of the investment model, availability of alternative options, gauges the perceived lack/abundant of available options for pursuing a new career. If the unmet need is strong and could be satisfied by changing careers, the employee may quit and switch with a better career alternative. Expectancy research suggests that attitudes are influenced by individuals’ comparisons of their current situation with external opportunities (Thatcher, Stepina, & Boyle, 2002). A lack of attractive alternative options increases individuals’ commitment to their current ones. When individuals perceive many career alternatives, they will express lower levels of career commitment. Thus, we predict:

H3: Availability of Career alternatives negatively influences individuals’ career

commitment.

3.2 The Threat of Professional Obsolescence

Professional obsolescence is defined as the erosion of professional competencies required for successful performance (Dubin, 1990). According to Fossum, Arvey, Paradise, and Robbins(1986), obsolescence occurs when the job incumbent previously possessed talents commensurate with requirements of the profession; however, change in the knowledge domain or change in the individual has resulted in a mismatch. Consequently, individuals must put many efforts to remain technologically current and continuously acquire new knowledge and skills because it affects their employability, career development, and compensation. Professionals need to be able to face situations in which their knowledge no longer applies. As a result, individuals who feel the threat of professional obsolescence may express less committed to their career. Hence, we predict that individuals are opting to switch careers as a result of the threat of professional obsolescence.

H4: The threat of professional obsolescence negatively influences individuals’ career

commitment.

3.3 Professional Self-Efficacy

Professional self-efficacy is the degree that one believes that he or she is capable of successfully managing one’s professions (Kossek, Roberts, Fisher, & Demarr, 1998). Bandura (1986) suggests that a key to the willingness to commitment a specific vocational choice, is belief in the capacity to mobilize the physical, intellectual, and emotional resources needed to succeed in the occupation of choice, that is, professional self-efficacy. Following the logics, we postulate that high self-efficacy supports career commitment. Thus,

H5: Professional Self-Efficacy positively influences individuals’ career commitment.

ITPs need the up-to-date knowledge and necessary ski1ls to maintain effective performance. Unlike other professionals where basic knowledge remains enduring, the half-life of knowledge and skills in the IT profession is estimated at less than two years (Dubin, 1990). Therefore, an ITP’s stock of competencies erodes and comes under the

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continuous threat of professional obsolescence (Dubin, 1990; Pazy, 1996). Therefore, the erosion of competencies is imminent in the careers and constitutes a potential threat to ITPs, which will undermine their commitment to IT career. Thus, compared with non-IT employees, the threat of professional obsolescence would be considered a more serious inhibitor to ITPs’ career commitment. Thus, we predict:

H6: The relationship between the threat of professional obsolescence and career

commitment will be stronger for ITPs than for non-IT employees.

While knowledge is the key resource and investment for ITPs, it is difficult for ITPs to accumulate knowledge overtime. Advancement in IT fields can make some professional knowledge irrelevant or useless. Job requirements in terms of skills, competencies, qualifications and trainings for ITPs are changing rapidly. It thus made most of the past investment worthless. The unending effort to keep up-to-date requires an enormous investment of energy. These new competencies, however, may bear little relation to past competencies. Therefore, an ITP’s stock of competencies erodes and quickly turns into sunk cost. Thus, for ITPs, their investment in IT professions did not actually create a “hold-up” situation, and the causal link between career investment and career commitment were attenuated gradually, as compared with non-IT employees.

H7: The relationship between career investment and career commitment will be stronger

for non-IT employees than for ITPs.

Self-efficacy represents judgments or beliefs about one’s performance capabilities in a particular domain (Wood & Bandura, 1989). Given the rapid advancement of information technology, individuals’ judgments about their capabilities and confidence for continuous update are likely to influence their decision to commit to IT careers. Compared with non-IT employees, ITPs with low level of professional self-efficacy may find it had to continue their thus make their future commitment less likely. Thus, we hypothesize:

H8: The relationship between professional self-efficacy and career commitment will be

stronger for ITPs than for non-IT employees.

4. Method

Field research employing quantitative analysis of self-report questionnaire data is the primary method of this study. Furthermore, qualitative interviews and data gathered from senior managers were used to supplement the primary quantitative analysis and evaluate potential common-method bias.

Data to test the model and hypotheses were drawn from a cross-sectional field study from Top-1000 large-scale companies in Taiwan. Invitation emails were sent to CIOs to invite their subordinates and employees from other functional departments (for example, accounting, law, marketing, manufacturing) to participate. Eight-two organizations agreed to distribute questionnaires (in paper form). Individuals with less than one-year working experience were

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excluded to ensure that respondents had sufficient working history to form career attitudes. Respondents’ participations in this study were strictly voluntary.

Constructs were measured using multiple-item scales, drawn from pre-validated measures in related studies whenever possible. The survey instrument was created after conducting literature reviews and in depth interviews with several ITPs. Preliminary versions of this questionnaire were reviewed and discussed by peers and practitioners.

Construct Items Source

Career Commitment 9 Carson and Bedeian (1994) Career satisfaction 5 Greenhaus et al. (1990) Professional Self-Efficacy 4 Developed for this study Attractiveness of Career Alternative 3 Dam (2005) Investment 5 Dam (2005).

Threat of Professional Obsolescence 10 Pazy (1994)

5. Data Analysis and Results

5.1 Samples

A total of 501 respondents participated in the study. This represented 41.8% of those who had received mailed questionnaires (N=1200). The sample was divided into groups of 255 ITPs, and 246 non-IT employees.

5.2 Scale Validation

PLS was used to assess the psychometric properties of all scales used in this study and the structural model. PLS offers an alternative for incorporating formative as well as reflective indicators in one model. Since career commitment and threat of professional obsolescence are formative constructs, PLS appeared the most appropriate technique based on the properties of the scale at hand.

A CFA was conducted in PLS to assess item loadings, disrciminant validity, and internal consistency of all scales. Item loadings and internal consistencies greater than 0.70 are considered acceptable (Fornell & Larcker, 1981). Factor analysis suggested that all items exhibit high loadings on their respective constructs. All indicators load more highly on their own construct than on other constructs. To assess discriminant validity, we found that all constructs shared more variance with their indicators than with other constructs. Thus these results point to the discriminant validity of our scales. Likewise, the values for internal consistency were all above the suggested minimum of 0.70. Overall, all reflective constructs and sub-constructs displayed adequate internal consistency and discriminant validity.

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Table 1. Correlation of Latent Variables (Full Sample)

  Composite  Reliability 

SAT  ALT  INV  PSE  CAP  CAI  CAR  TPO_S  TPO_T  TPO_C 

SAT  0.90  0.82        ALT  0.89  ‐0.04  0.82        INV  0.92  0.14  ‐0.15  0.75        PSE  0.92  0.12  0.25  0.20  0.81        CAP  0.93  0.22  0.07  0.42  0.37  0.88        CAI  0.95  0.16  0.22  0.30  0.48  0.53  0.91          CAR  0.93  ‐0.22  0.13  ‐0.02  ‐0.03  ‐0.30  ‐0.15  0.88        TPO_S  0.87  ‐0.07  0.27  0.24  0.15  0.17  0.15  0.16  0.76      TPO_T  0.82  ‐0.10  0.20  0.17  0.04  ‐0.04  0.06  0.19  0.55  0.83    TPO_C  0.88  ‐0.02  0.03  0.06  0.04  ‐0.01  0.02  0.06  0.08  0.26  0.71 

The shaded numbers on the leading diagonal are the square root of the variance shared between the constructs and their measures. Off diagonal elements are the correlations among constructs.

5.3 Hypothesis Testing

With the exception of professional obsolescence and career commitment, all other constructs in the model are modeled as reflective. The formative constructs were modeled as such since their underlying dimensions do not necessarily covary (Jarvis, MacKenzie, & Podsakoff, 2003). Since PLS does not directly support second order factors, for the formative constructs, factor scores were calculated for each dimension and used in the structural model. Following the suggestion of Chin et al. (2003), we modeled the path weights from the first- to the second-order constructs (the weights of formative constructs are treated as PLS coefficients, and the variance explained in the second-order construct is unity).

Furthermore, multi-group or between-group analyses were common in the information systems literature (Qureshi & Compeau, 2009). In the current research, we tested the difference between ITPs and non-IT employees. As suggested by Qureshi & Compeau (2009), we estimated model parameters for each group separately and then performed between-group test of significance across the groups, using a t–test with pooled standard errors.

The seven hypotheses presented earlier are tested collectively using the partial least squares (PLS), and the significance levels were assessed with 200 bootstrap runs. We then ran the structural model on the two sub-samples respectively. Results demonstrated a difference between ITPs and non-IT employees. Variance explained for career commitment is 53.8% and 42.0%, respectively. In general, the findings supported most of the hypotheses, except for H3 and H4 were partially supported. Career satisfaction appeared a strong predictor of career commitment (β=0.48, p-value < 0.01 for ITPs, and β=0.57, p-value < 0.01 for non-IT employees) and accounted for a substantial amount of variance, thus H1 was supported. Career investment (β=0.17, p-value < 0.01 for ITPs, β=0.14, p-value < 0.01 for non-IT employees) and professional self-efficacy (β=0.27, p-value < 0.01, and =0.12, p-value < 0.01) were positively related to career commitment, which supported H2 and H5. The negative effects of threat of professional obsolescence on career commitment (β=-0.18, p-value < 0.01) was found for IT professionals but not for non-IT employees, thus H4 was partially supported. Finally, the effect of availability of career alternatives on career commitment was significant for non-IT employees but not for ITPs, thus H3 was partially supported.

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To more rigorously compare the results across groups, we calculated t-statistics to evaluate the differences in path coefficients across groups. Before doing this, it was necessary to assess whether the latent constructs were perceived in a similar fashion between the two groups (Carte & Russell, 2003). We found loading patterns and factor loadings were very similar, thus permitting between-group path comparison. We calculated t-statistics to evaluate the differences in path coefficients across the two groups, using procedures described by Chin et al. (2004).

Table 2. Results of Multi-Group Comparison

ITP Group (n=255)  Non‐IT Group(n=246)  Path 

Path  Stdev  Path  Stdev  Difference  df 

SAT  CA  0.48  0.059  6.52  0.57  0.477  6.09  ‐0.09  499  ‐0.19 

ALT CA  0.09  0.051  1.70  0.19  0.141  1.99  ‐0.1  499  ‐0.68 

INV  CA  0.17  0.069  2.38  0.14  0.124  1.67  0.03  499  0.21 

PRB  CA  ‐0.18  0.044  ‐2.31  ‐0.04  ‐0.038  ‐0.40  ‐0.14  499  ‐2.41 

PSE  CA  0.27  0.06  4.54  0.11  0.063  1.67  0.16  499  1.92 

A comparison of results in Table 2 suggests that significant differences exist across the two groups. For ITPs, the path coefficients from career investment to career commitment are not significantly different (t=0.21, p>0.1). Thus, H7 was not supported. Finally, the results provide support on the relationship of the threat of professional obsolescence (t= -2.41, p<0.01) and professional self-efficacy (t= 1.92, p<0.01) with career commitment, which support H6 and H8. 1.  Structural path estimates are the standardized parameter estimates, and the associated t‐values are in  parentheses. Solid‐lines stand for significant paths and dotted‐lines for non‐significant ones. Measurement  model is not shown above for purposes of clarity.    2.  The strength of the relationships among the constructs is represented by standardized path coefficients.  :first order construct      :second order construct (formative)  Figure 2. Result of PLS analysis (Full-Sampled Model, n=501)

INV  ALT  SAT  COM  R2=0.54  PSE  TPO  Investment Model  0.48 (6.62)  .09 (1.68) 0.17 (2.70) ‐0.18 (2.88) 0.27 (4.39)

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6. Discussion

The study aims to understand the differences in career concerns between ITPs and non-IT employees. A basic understanding obtained from this study is the magnitude and significance of relationships between career commitment and its existing antecedents. Overall, investment model was partially supported. Findings indicated that career satisfaction is the strongest drivers of career commitment. Individuals who perceived greater satisfaction reported greater career commitment. Additionally, career investment and professional self-efficacy were significant in predicting individuals’ career commitment.

Table 3. Uni-variate Analysis of Constructs

ITP Group  Non‐IT Employee Group 

Construct 

Mean  Stdev  Mean  Stdev  Sig. 

SAT  4.28  1.19  4.17  1.13  1.10  0.295  ALT  4.31  1.31  4.18  1.25  1.25  0.265  INV  4.38  1.23  4.07  1.23  8.02  0.005  SEE  4.40  1.15  4.34  1.05  0.38  0.539  CAP  4.26  1.21  4.22  1.20  0.02  0.662  CAI  4.60  1.29  4.59  1.16  0.19  0.885  CAR  4.30  1.40  4.29  1.38  0.02  0.889  TPO_S  5.12  0.85  4.17  1.10  116.40  0.000  TPO_T  4.48  1.14  3.63  1.30  61.07  0.000  TPO_C  4.51  1.09  3.72  1.21  60.41  0.000 

Across the two groups, we found that ITPs and non-IT employees seemed to hold different attitudes careers. First, the negative impacts of the threat of professional obsolescence on career commitment for ITPs implied that an increase in the threat of professional obsolescence significantly lowers the possibility that ITPs will commit their career in IT profession. In contrast, analysis of the non-IT employees group revealed a distinct pattern that the professional obsolescence did not seem to be an important antecedent to their career commitment. The uni-variate analysis shown in Table 3 indicated that ITPs did feel more threaten by professional obsolescence than non-IT employees did. In sum, we conclude that professional obsolescence is an important factor and constitutes a substantial threat to ITPs’ intention to continue their current career, but not for non-IT employees.

Second, the professional self-efficacy is more salient to ITPs’ career commitment

compared with non-IT employees. In comparison with non-IT employees, ITPs reported higher career commitment when they perceived higher professional self-efficacy. This suggests that ITPs’ judgments about their capabilities for successful performance significantly influence their attitudes of committing to IT careers. Since the advancement in IT fields makes some skills irrelevant very quickly or over-emphasizes others, it is difficult for an ITP’s without high professional self-efficacy to persist long enough in constant renewing, leaning and updating his/her knowledge.

7. Implications for Practitioners

An understanding of the relative importance allows IT/HR managers to design more effective programs to retain valuable IT human resources. Furthermore, ITPs and non-IT

數據

Table 1:Correlation of Latent Variables (Full Sample)
Figure 2: Result of PLS analysis (Full-Sampled Model, n=501)
Figure 1. The Research Model
Table 1.   Correlation of Latent Variables (Full Sample)
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1.5 In addition, EMB organised a total of 58 forums and briefings (45 on COS and 13 on special education) to explain the proposals in detail and to collect feedback from

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1 The five components of OLE are: Aesthetic Development, Physical Development, Moral and Civic Education, Community Services, and Career-related Experiences.. learning

Reflection 反思 經過反思後,可再作選擇 Your Career, we Care..

- Highlights of course content, briefing on further study pathways and career prospects - Brief introduction of the functions and required skills of public relations (PR) -

(2011).Linking learning to the 21st Century:Preparing all students for college, career, and civic participation.Boulder, CO: National Education Policy Center.