ReportTitle:
Dynamic Pricing and Inventory Management under Network Externalities
Reporter(Institution):
Renyu (Philip) Zhang, New York University Shanghai
Time:10:00.am,23th Dec, 2016
Location:B-201, Building of Economics & Management, Jiulonghu Campus
Abstract:
We study the impact of network externalities upon a firm's pricing and inventory policy under demand uncertainty. The firm sells a product associated with an online service or communication network, which is formed by (part of) the customers who have purchased the product. The product exhibits network externalities, i.e., a customer's willingness-to-pay and, thus, the potential demand are increasing in the size of the associated network. We show that a network-size-dependent base-stock/list-price policy is optimal. Interestingly, the inventory dynamics of the firm do not influence the optimal policy as long as the initial inventory is below the initial base-stock level. Hence, we can reduce the dynamic program that characterizes the optimal policy to one with a single-dimensional state-space (the network size). Network externalities give rise to the trade-off between generating current profits and inducing future demands, thus having several important implications upon the firm's operations decisions. First, network externalities drive the firm to deliver a better service and attract more customers into the network. Hence, the safety-stock and base-stock levels are higher with the presence of network externalities. Second, thanks to the aforementioned trade-off between current profits and future demands, the network size evolution follows a mean-reverting pattern: When the current network size is small (resp. big), it will have an increasing (resp. decreasing) trend in expectation. Third, although myopic profit optimization leads to significant losses under network externalities, balancing the current profits and near-future demands will suffice to exploit network externalities. We propose a dynamic look-ahead heuristic policy that well leverages this idea and achieves tiny optimality gaps with exponential decay in the look-ahead time-window length. Finally, we develop a general (costly) network expansion strategy that effectively exploits network externalities and improves the profit. This strategy facilitates the firm to (partially) separate generating current profits and inducing future demands via network externalities.
Reporter:
Renyu (Philip) Zhang has been an Assistant Professor of Operations Management at New York University Shanghai since August 2016. He is broadly interested in providing in-depth theoretical analysis to problems of practical relevance from an operations perspective, and developing effective models and methodologies for such analysis. His research focuses on some fundamental operations issues under the emerging trends in technology, marketplace, and society. Philip is particularly enthusiastic about developing operations and analytics techniques to analyze problems in two streams of research: (a) operations management under social interactions (e.g., social networks, sharing economy, and online markets) and (b) sustainable operations. His research works have been published in Operations Research and Manufacturing & Service Operations Management. Please visit his personal website for more about Philip: https://www.nyu.edu/projects/rzhang/.
Before joining NYU Shanghai, Philip obtained his doctoral degree in business administration (Operations Management) at Olin Business School, Washington University in St. Louis in May 2016 under the supervision of Professor Nan Yang and Professor Fuqiang Zhang. In July 2011, Philip got a B.S. degree in mathematics at School of Mathematical Sciences, Peking University.
