官员
程序正义
培训(气象学)
心理学
经济正义
政治学
社会心理学
公共关系
应用心理学
业务
法学
感知
物理
气象学
神经科学
作者
Rodrigo Canales,Juan Santini,Marina González Magaña,Alexis Cherem
出处
期刊:Management Science
[Institute for Operations Research and the Management Sciences]
日期:2025-03-03
卷期号:71 (11): 8995-9013
被引量:2
标识
DOI:10.1287/mnsc.2022.03243
摘要
Research on organizational justice shows that perceptions of justice by internal and external agents are reliable predictors of key organizational outcomes. But how can we promote the enactment of fair behavior by those with decision-making authority within organizations? This is particularly important for organizations that depend on frequent client interactions, in which individual discretion is required to make consequential decisions, and where necessary evils are unavoidable. Few organizations face this challenge as intensely as police forces, in which misconduct and bad decisions by their street-level bureaucrats can have large negative consequences. This paper analyzes whether police officers can be trained to effectively incorporate the principles of procedural justice in their interactions with citizens. In collaboration with the Mexico City police, we implemented a randomized controlled trial with 1,854 officers to measure whether procedural justice training changed their perceptions of policing and actual behavior on the field. We find significant and positive effects of the training across all measures of the procedural justice model. Our research yields insights into critical elements to consider in organizational training programs, including managerial alignment with the objectives of the training and a consideration of employees’ perceptions of the extent to which their work is understood by others. This paper was accepted by Isabel Fernandez-Mateo, organizations. Funding: This research was funded by the U.S. State Department’s Bureau of International Narcotics and Law Enforcement Affairs (INL) [Grant SINLEC17CA2007]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.03243 .
科研通智能强力驱动
Strongly Powered by AbleSci AI