Distributed decision-making in the shadow of hierarchy: How hierarchical similarity biases idea evaluation

• 成果类型: Article
• 署名作者: Schweisfurth, Tim G.; Schoettl, Claus P.; Raasch, Christina; Zaggl, Michael A.
• 署名单位: Hamburg University of Technology; University of Twente; Technical University of Munich; Kuhne Logistics University; Leibniz Association; Institut fur Weltwirtschaft an der Universitat Kiel (IFW); Aarhus University
• 刊物名称: STRATEGIC MANAGEMENT JOURNAL
• ISSN/ISSBN: 0143-2095
• DOI: 10.1002/smj.3497
• 发表日期: 2023
• 页码: 2255-2282
• 关键词: Bias; distributed decision-making; hierarchy; idea selection; internal crowdfunding

摘要

Research SummaryCompanies are increasingly opening up decision-making, involving employees on all levels in distributed-and purportedly hierarchy-free-decision processes. We examine how hierarchy reaches into such democratized systems, arguing that it is a source of homophily that biases idea evaluation decisions. Using a data set from internal crowdfunding at one of the world's largest industrial manufacturers, we show that idea evaluators overvalue hierarchically similar others' ideas. Competition in the form of lateral closeness dampens this bias, whereas uncertainty in the form of novelty amplifies this bias. We contribute to the literatures on decision biases in centralized versus distributed innovation and on structural similarity as a driver of employee behaviors.Managerial SummaryMany companies are starting to involve employees on all levels in strategic decisions, so as to curb hierarchical rigidities and integrate multiple perspectives. However, such distributed decision-making opens the door to new biases and, ultimately, suboptimal strategic decisions. In the context of internal crowdfunding at a large industrial manufacturer, we show that employees evaluate hierarchically similar others' ideas overly favorably. Thus, hierarchy is not just a source of rivalry, but also of identification, leading to favoritism among hierarchical peers. Further, employees are particularly likely to assess ideas based on hierarchical similarity rather than content if the ideas are novel and therefore hard to evaluate. We provide suggestions for the design of distributed decision-making systems.