Person-job cognitive style fit for software developers: The effect on strain and performance

• 成果类型: Review
• 署名作者: Chilton, MA; Hardgrave, BC; Armstrong, DJ
• 署名单位: Kansas State University; University of Arkansas System; University of Arkansas Fayetteville
• 刊物名称: JOURNAL OF MANAGEMENT INFORMATION SYSTEMS
• ISSN/ISSBN: 0742-1222
• DOI: 10.1080/07421222.2005.11045849
• 发表日期: 2005
• 页码: 193-226
• 关键词: mis project teams; adaption-innovation; ENVIRONMENT FIT; information-systems; individual-differences; OCCUPATIONAL STRESS; construct-validity; ROLE-CONFLICT; management; attitudes

摘要

Software developers face a constant barrage of innovations designed to improve the development environment. Yet stress/strain among software developers has been steadily increasing and is at an all-time high, while their productivity is often questioned. Why, if these innovations are meant to improve the environment, are developers more stressed and less productive than they should be? Using a combination of cognitive style and person-environment fit theories as the theoretical lens, this study examines one potential source of stress/strain and productivity impediment among software developers. Specifically, this paper examines the fit between the preferred cognitive style of a software developer and his or her perception of the cognitive style required by the job environment, and the effect of that fit on stress/strain and performance. Data collected from a field study of 123 (object-oriented) software developers suggest that performance decreases and stress increases as this gap between cognitive styles becomes wider. Using surface response methodology, the precise fit relationship is modeled. The interaction of the developer and the environment provides explanatory power above and beyond either of the factors separately, suggesting that studies examining strain and performance of developers should explicitly consider and measure the cognitive style fit between the software developer and the software development environment. In practice, managers can use the results to help recognize misfit, its consequences, and the appropriate interventions (such as training or person/task matching).