• Title/Summary/Keyword: 다차원 교육과정

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The Impact of Self-efficacy on Job Engagement and Job Performance of SMEs' Members: SEM-ANN Analysis (중소기업 조직구성원의 자기효능감이 직무열의와 직무성과에 미치는 영향: 구조모형분석-인공신경망 분석의 적용)

  • Kang, Tae-Won;Lee, Yong-Ki;Lee, Yong-Suk
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.13 no.6
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    • pp.155-166
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    • 2018
  • The purpose of this study is to analyze the impact of self-efficacy of SMEs' organization members on job engagement and job performance, and to analyze the difference between gender and marital status by applying SEM-ANN analysis. To accomplish the study purpose, 285 valid samples were collected from 400 SMEs' organization members and analyzed. In this study, self - efficacy consisted of three sub-dimensions: self-confidence, self-regulation efficacy, and task difficulty preference. As a result of the analysis, self - efficacy such as self-confidence, self-regulation efficacy, and task difficulty preference had a positive direct effect on job engagement. In addition, self-efficacy and self-control efficacy have a positive effect on job performance, but the preference of task difficulty has no significant effect. In addition, job engagement has a positive(+) effect on job performance, and has a mediating role in the relationship between self-efficacy and job performance. Also, married males preferred self-regulation efficacy, while females preferred self-regulation and self-control efficacy regardless of marital status. The purpose of this study is to present the framework of self-efficacy-job engagement-job performance of SMEs by measuring the self-efficacy related researches mainly in education and service industries, and is meaningful that companies can help to find the basis of management of organization members by gender and marital status of organization members. In addition, the SEM-ANN analysis process of this study is different in that it explains the nonlinear (nonobservative) relationship that can analyze the influence or the combination of the reference variables in the linear (compensatory) relation using the SEM.