【会议】How can Artificial Intelligence Technologies be a “Useful Servant” for Managers? A Case of Employee Performance Evaluation and Feedback
发布者：沙晓燕 发布时间：2022-11-29 浏览次数：10
Meeting Time：2022/12/5 9:30-10:00
VOOV meeting: 157-564-411
Speaker: Prof. Bo Xu
Prof. Bo Xu is Associate Professor at School of Management, Fudan University, China. He received the Ph.D. degree in Management Information Systems from Texas Tech University, USA. His research interests include artificial intelligence applications, electronic commerce, and open innovation He has published over thirty research papers in IS and marketing journals, including Decision Support Systems, Information systems Journal, Information & Management, European Journal of Information Systems, Journal of the Academy of Marketing Science, Journal of Business Research, Database for Advances in Information Systems, Journal of Database Management, International Journal of Human-Computer Interaction, Electronic Markets, and so on. He was principal investigator of research projects funded by National Natural Science Foundation and National Social Science Foundation of China. Prof. Xu teaches MIS courses at graduate and undergraduate levels and received teaching excellence award from School of Management, Fudan University.
Abstract: Can Artificial Intelligence (AI) technologies assist human managers with managing employees to improve employees’ performance? While AI’s superior data abilities may enable managers to use large amounts of data to produce accurate employee performance evaluations, not all human managers stand to benefit equally from this assistance. We argue that managers who develop stronger interpersonal relationships with employees, as demonstrated by stronger transformational leadership are able to use AI generated information to improve employee performance to a greater extent than the managers who have weaker interpersonal relationships with employees, as captured by a greater extent of transactional leadership. This impact is primarily driven by employees’ greatest trust in and the highest willingness to adopt the feedback that is generated by AI and conveyed by transformational managers. We provide empirical evidence from mixed methods: A randomized field experiment conducted in a large fintech company to demonstrate causal effects on employee performance, and semi-structured interviews conducted with employees to generate in-depth qualitative insights into the underlying mechanisms. The findings offer useful implications for effective adoption of AI technologies in managing organizations to improve employee performance. These insights are particularly relevant for designing AI-manager teams that create greater complementarity between machines and humans to increase the effectiveness of management during the fourth industrial revolution of AI automation.
