Speaker:Guangwen Kong, University of Minnesota, Twin Cities(UMN), US
Date:June 18, 2019
Location:B1032 Lecture Hall, Zhixin Building, Central Campus
Sponsor:School of Mathematics
We examine the impact of social learning in a referral program when customers' preferences are correlated in a social network. We characterize customers' purchasing strategies based on their information and their types, and derive the demand distributions when customers are involved in social learning in a referral program. While customers in lack of knowledge on their own preferences will introduce bias to the demand expectation, social learning reduces the bias at the expense of increasing demand variance. We investigate a firm's inventory decision when customers involved in social learning in a referral program. We find that the stock-out of one product would suppress the demand of the other product when customers are involved in social learning. Allowing customers to make multiple referrals reduces the negative effect of stock-out but meanwhile dramatically increases the demand variance.
Guangwen Kong is an Assistant Professor at Temple University Fox School of Business. She is also an affiliated faculty at University of Minnesota. She holds a Ph.D. degree in Operations Management from the Marshall School of Business, University of Southern California. Her interests are strategic interactions and behavioral decision making in the area of Supply Chain Management, Service Operations, and Business Model Innovation such as Sharing Economy and On-demand Platforms. She has been working on projects in peer to peer product sharing, online promotion, on-demand service platform, service contracts design and supply chain contracts. She has published papers in Management Science and Production and Operations Management, served as Editorial Review Board member of Production and Operations Management, and reviewer of Operations Research, European Journal of Operational Research, Manufacturing & Service Operations Management, Journal of Management Studies, Production and Operations Management and Naval Research Logistics.
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Edited by: Qu Xilin