透明度(行为)
采购
互惠(文化人类学)
激励
业务
自由裁量权
微观经济学
采购
营销
经济
心理学
社会心理学
计算机科学
政治学
计算机安全
法学
作者
Ruth Beer,Ignacio Ríos,Daniela Sabán
出处
期刊:Management Science
[Institute for Operations Research and the Management Sciences]
日期:2021-04-09
卷期号:67 (12): 7511-7534
被引量:22
标识
DOI:10.1287/mnsc.2020.3894
摘要
Motivated by recent initiatives to increase transparency in procurement, we study the effects of disclosing information about previous purchases in a setting where an organization delegates its purchasing decisions to its employees. When employees can use their own discretion, which may be influenced by personal preferences, to select a supplier, the incentives of the employees and the organization may be misaligned. Disclosing information about previous purchasing decisions made by other employees can reduce or exacerbate this misalignment, as peer effects may come into play. To understand the effects of transparency, we introduce a theoretical model that compares employees’ actions in two settings: one where employees cannot observe each other’s choices and one where they can observe the decision previously made by a peer before making their own. Two behavioral assumptions are central to our model: that employees are heterogeneous in their reciprocity toward their employer, and that they experience peer effects in the form of income inequality aversion toward their peer. As a result, our model predicts the existence of negative spillovers as a reciprocal employee is more likely to choose the expensive supplier (which gives the employee a personal reward) when the employee observes that a peer did so. A laboratory experiment confirms the existence of negative spillovers and the main behavioral mechanisms described in our model. A surprising result not predicted by our theory is that employees whose decisions are observed by their peers are less likely to choose the expensive supplier than the employees in the no-transparency case. We show that observed employees’ preferences for compliance with the social norm of appropriate purchasing behavior explain our data well. This paper was accepted by Yuval Victor Martinez de Albeniz, operations management.
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