Capturing the Benefits of Worker Specialization: Effects of Managerial and Organizational Task Experience

• 成果类型: Article
• 署名作者: Madiedo, Juan Pablo; Chandrasekaran, Aravind; Salvador, Fabrizio
• 署名单位: Erasmus University Rotterdam; Erasmus University Rotterdam - Excl Erasmus MC; University System of Ohio; Ohio State University; IE University
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1111/poms.13145
• 发表日期: 2020
• 页码: 973-994
• 关键词: influence tactics; LEARNING-CURVE; software maintenance; performance; KNOWLEDGE; boredom; MODEL; management; CONSEQUENCES; QUALITY

摘要

Learning by doing is a fundamental driver of productivity among knowledge workers. As workers accumulate experience working on certain types of tasks (i.e., they become specialized), they also develop proficiency in executing these tasks. However, previous research suggests that organizations may struggle to leverage the knowledge workers accrue through specialization because specialized workers tend to lose interest and reduce effort during task execution. This study investigates how organizations can improve specialized workers' performance by mitigating the dysfunctional effects of specialization. In particular, we study how other sources of task experiences from the worker's immediate manager as well as the organization itself help manage the relationship between worker specialization and performance. We do so by analyzing a proprietary dataset that comprises of 39,162 software service tasks that 310 employees in a Fortune 100 organization executed under the supervision of 92 managers. Results suggest that the manager role experience (i.e., the manager's experience supervising workers) is instrumental in mitigating the potential negative effect of worker specialization on performance, measured as task execution time. Such influence, however, is contingent on cases in which organizational task experience (i.e., the organization's experience in executing tasks of the same substantive content as the focal task) is limited. Taken together, our research contributes to multiple streams of research and unearths important insights on how multiple sources of experience beyond the workers themselves can help capture the elusive benefits of worker specialization.