讲座:Can Employees’ Past Helping Behavior be Used to Improve Shift Scheduling? Evidence from ICU Nurses 发布时间:2022-12-14

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题 目:Can Employees’ Past Helping Behavior be Used to Improve Shift Scheduling? Evidence from ICU Nurses.

嘉 宾:王亦昕,助理教授,伊利诺伊大学厄巴纳-香槟分校

主持人:曹宇峰 助理教授 上海交通大学安泰经济与管理学院

时 间:2022年12月21日(周三)8:30-10:00am

地 点:腾讯会议(校内师生如需获取会议号和密码,请于12月20日下午18点前发送电邮至yuxin.su@sjtu.edu.cn)

内容简介:

Employees routinely make valuable contributions at work that are not part of their formal job description, such as helping a struggling coworker. These contributions, termed organizational citizenship behavior (OCB), have been studied from many angles in the organizational behavior literature. However, whether an employee's past helping behaviors can be used to improve shift scheduling decisions remains an under-explored operations question. We define two measures of past helping behavior for members of a shift - the total past helping of each employee and the past helping between each pair of employees - and hypothesize that they are associated with shift performance. We empirically confirm our hypotheses with detailed scheduling and patient outcome data from six ICUs at a large academic medical center, using the hospital's electronic medical records to identify cases of one nurse helping another. Our empirical results indicate that both measures of past helping are predictive of patient length of stay (LOS), more so than the broadly studied notion of team familiarity. Counterfactual analysis shows that relatively small changes in shift composition can yield significant reduction in total LOS, indicating the managerial significance of the results. Overall, our study suggests the potential value of shift scheduling using data on past helping behaviors, which may have promise far beyond the selected application to ICU nursing.

演讲人简介:

Yixin “Iris” Wang is an Assistant Professor of Operations Management at the Gies College of Business, University of Illinois at Urbana-Champaign. Her main research interests are empirical supply chain management and human-interactions in operations management. She has worked extensively with large-scale data and investigated how supply network, strategic policy reactions, and behavioral business decisions affect company performance. She has worked in collaboration with big automakers in U.S. and conducted experiments with pharmacy retail chains in China. Her research has been recognized by several awards and received honorable mention at paper competitions.

 

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