时间：2022年5月19日 14:30

地点：腾讯会议线上

主讲人一：李若辰

题目：Consumer Stockpiling as a Form of Behavioural-Based Price Discrimination。摘要: In this paper, I set up a two-period monopoly model that incorporates consumer stockpiling behaviour to investigate the effect of behavioural-based price discrimination (BBPD). In equilibrium, I show that when the product differentiation is high, consumer stockpiling behaviour can be used as a device for the firm to perform `stockpiling-based price discrimination'. The following welfare analysis suggests that consumer stockpiling improves consumer surplus and profit despite the associated `stockpiling-based price discrimination'.

主讲人二：李爱军

题目：A New Network Data Envelopment Analysis Prospect Window-Based Cross-Efficiency Model and an Application to Chinese Universities

摘要：The existing Data Envelopment Analysis (DEA) studies on the cross-efficiency method faces one drawback, since it may produce unrealistic weights and is not good at tracking their dynamic changes. To solve this drawback, this study proposes the concepts of window-based cross-efficiency and window-based relative weights. Furthermore, relative weights analysis assists us in better understanding the prior strategies of DMUs. Furthermore, this study proposes a new type of network DEA prospect window-based cross-efficiency model. To the best of our knowledge, such work cannot be found in the previous studies. As an empirical application, this study considers the case of China and evaluates the performance of universities at a provincial level from 2007 to 2019. The main conclusions are summarized as follows. First, Chinese universities have experienced an overall regress in efficiency measures during the observed periods. Second, most attention has been given to the research and development (R&D) stage, while the scientific and technological (S&T) transformation stage has received minor attention. Finally, Chinese universities has succeeded in realizing a general decline in overall efficiency Gini coefficient. Looking ahead, China should attach more importance to the S&T transformation stage.