수사관의 직무열의에의 영향요인: 직무요구-자원 모델을 중심으로
A Study on the factors to influence Investigators’ Job Engagement: Focused on Job Demands-Resources Model
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초록
직무요구-자원 모델(JD-R Model)은 조직구성원의 웰빙과 성과를 향상시키기 위해서 다양한 직업에 적용될 수 있는 인기 있는 연구 모델이다. 이 연구의 목적은 직무요구-자원 모델에 기초해서 수사관의 직무열의에 미치는 영향을 분석하는 것이다. 이 연구는 주로 외국에서 검증되어 온 직무요구-자원모델(JD-R Model)이 우리나라에서도 적용될 수 있는지 여부를 검증하고, 수사관의 직무열의에 영향을 미치는 선행요인을 통계적으로 검증함으로써 수사관의 직무열의를 향상시키기 위한 방안을 제시하였다. 이 연구의 종속변수는 수사관의 직무열의이고, 독립변수는 직무요구(직무 과부하, 일-가정 갈등), 직무자원(분배적 공정성, 자기개발 기회, 성과 피드백), 사회적 자원(관리자 지원, 동료 지원), 개인적 자원(자기 효능감)이며 통제변수는 인구사회적 변수이다. 다중회귀분석 결과는 자기 효능감(β=.358), 자기개발기회/성과 피드백(β=.265), 분배적 공정성(β=.170), 관리자 지원(β=.139, p=.020)이 수사관의 직무열의에 통계적으로 유의한 영향을 미치는 것을 보여주었다. 따라서, 수사관의 직무열의 수준을 향상시키기 위해서 수사부서는 수사관의 자기 효능감을 높이고, 더 많은 자기개발기회 및 성과 피드백을 제공하고, 분배적 공정성 및 관리자 지원 인식을 향상시키기 위해 노력해야 할 것이다.
Abstract
The purpose of this study is to analyze the factors to influence investigators' job engagement based on the job demand-resource model. This study verifies whether the job demand-resource model, which has been mainly verified in foreign countries, can be applied to investigation department of South Korea, and suggests the measures to improve investigators' job engagement. The dependent variables of this study are the investigator's job engagement, and the independent variables are job demands(job overload, work-family conflict), job resources(distributive fairness, self-development opportunities, performance feedback), social resources(manager support, peer support), and control variables are socio-demographic variables. The results of multiple regression analysis showed that self-efficacy(β=.358), self-development opportunities/performance feedback(β=.265), distributive fairness(β=.170), manager support(β=.139) had a statistically significant effect on the investigator's job engagement. Therefore, in order to improve the level of the investigator's job engagement, investigation department should make much of efforts to increase the investigator's self-efficacy, provide more opportunities for self-development and performance feedback, and enhance perceived distributive fairness and manage support.
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