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Intrinsic motivation and extrinsic incentives jointly predict performance: A 40-year meta-analysis.

激励 内在动机 心理学 荟萃分析 社会心理学 认知评价理论 意外事故 自决论 目标理论 质量(理念) 认知心理学 微观经济学 经济 医学 政治学 哲学 内科学 法学 认识论 自治 语言学
作者
Christopher P. Cerasoli,Jessica M. Nicklin,Michael T. Ford
出处
期刊:Psychological Bulletin [American Psychological Association]
卷期号:140 (4): 980-1008 被引量:1696
标识
DOI:10.1037/a0035661
摘要

More than 4 decades of research and 9 meta-analyses have focused on the undermining effect: namely, the debate over whether the provision of extrinsic incentives erodes intrinsic motivation. This review and meta-analysis builds on such previous reviews by focusing on the interrelationship among intrinsic motivation, extrinsic incentives, and performance, with reference to 2 moderators: performance type (quality vs. quantity) and incentive contingency (directly performance-salient vs. indirectly performance-salient), which have not been systematically reviewed to date. Based on random-effects meta-analytic methods, findings from school, work, and physical domains (k = 183, N = 212,468) indicate that intrinsic motivation is a medium to strong predictor of performance (ρ = .21-45). The importance of intrinsic motivation to performance remained in place whether incentives were presented. In addition, incentive salience influenced the predictive validity of intrinsic motivation for performance: In a "crowding out" fashion, intrinsic motivation was less important to performance when incentives were directly tied to performance and was more important when incentives were indirectly tied to performance. Considered simultaneously through meta-analytic regression, intrinsic motivation predicted more unique variance in quality of performance, whereas incentives were a better predictor of quantity of performance. With respect to performance, incentives and intrinsic motivation are not necessarily antagonistic and are best considered simultaneously. Future research should consider using nonperformance criteria (e.g., well-being, job satisfaction) as well as applying the percent-of-maximum-possible (POMP) method in meta-analyses.
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