为搭建我校博士后之间的学术交流平台，促进学术水平提升，学校博士后管理办公室组织开展博士后学术沙龙活动。本次沙龙由我校博士后魏强、王浩旻、HOSSIN MD ALTAB、Evans Asante Boadi分享其研究成果，诚挚邀请感兴趣的师生参加。
（1）主题：Urban Sharing Logistics Strategies against Epidemic (e.g. COVID-19) Outbreaks: Its Feasibility and Sustainability
COVID-19 has caused a serious disruption of logistics, and the coordination of intercity logistics and urban distribution has played an important role in goods distribution. In this paper, we first develop a two-echelon logistics benchmark model (BM) with two intercity logistics companies, and two urban distribution companies, which considers the load ratio and the disruption factor. Then, we develop three urban sharing logistics models with two intercity logistics companies and one urban sharing logistics distribution company with the sharing mechanism SM1 (only sharing logistics), SM2 (sharing logistics with revenue-sharing) and SM3 (sharing logistics with equity investment). We compare the pros and cons of the sharing mechanism SMi, and find their optimal and suboptimal Pareto improvements for the BM. Therefore, we identify different sharing decisions with respect to different load ratio and the disruption ratio. Finally, we analyze the sustainability of three sharing mechanism from the load ratio, low-carbon and low-disruption dimensions. The managerial implications drawn from the model and case study provide a practice framework for the sharing logistics operations: vertical integration, standardization of logistics technology and equipment, the coordination and sharing.
Wei Qiang is now a post-doc in School of Management and Economics, UESTC. He obtained PhD in Management Science and Engineering from the SWUFE. His research interests are Supply Chain Finance, Sharing Economy, Plantform Economy, etc.
（1）主题：Pairwise comparisons: trends, methods and applications
Pairwise comparison matrix (PCM) is an important tool in intelligent decision making systems. Traditionally, PCMs come from decision makers’ subjective judgments and are normally smaller than 100 dimensions. Recently, a new research direction, which expands the application of PCMs to objective data, has emerged. Though large-scale sparse PCMs appear frequently in today’s big data environment, it’s hard for existing prioritization methods to handle large-scale sparse PCMs efficiently due to the curse of dimensionality.
We propose a new algorithm, Bipartite Graph Iterative Method (BGIM), to derive priorities from large-scale sparse PCMs. We first extended graph representations of PCMs to bipartite graphs. A transition matrix was induced by resource allocation on the bipartite graph. Finally, an iterative algorithm was designed to calculate priorities. The theoretical properties of the BGIM were analyzed to show its ability to derive priorities from large-scale sparse PCMs. Two experiments were conducted to validate the proposed approach. The numerical examples indicated that the BGIM can deal with traditional decision problems and derive reliable priorities with minimum Euclidean Distance and Minimum Violation among the tested methods. The simulation examples suggested that the BGIM can not only derive reliable priorities from large-scale sparse PCMs, but also require the least computation time compared with eight prioritization approaches. To demonstrate its applicability to real-world large-scale problems, we applied the BGIM to rank movies using MovieLens dataset with more than 100,000 ratings for 9125 movies. The results showed that the BGIM was the fastest approach and obtained the best ranking among the average ratings and the five prioritization methods.
Wang Haomin received the B.S. degree in mathematics and applied mathematics from University of Electronic Science and Technology of China, in 2014, and the Ph.D. degree in management science and engineering from University of Electronic Science and Technology of China, in 2020. He is currently a Postdoctoral Fellow of School of Management and Economics, University of Electronic Science and Technology of China. His research interests include machine learning, intelligent decision support and risk management.
（1）主题：Understanding firms performance through big data analytics and economic theories in the context of online marketplaces
（2）主讲人： HOSSIN MD ALTAB 经济与管理学院博士后
In this talk, we briefly discuss firms’ competitive advantages through exploiting seminal economic theories such as resource-based view, signalling theory and organizational theory. There are three issues: (1) How firms can gain the competitive advantages, (2) what are the issues in contemporary online markets rather than traditional offline business. (3) What are the challenging factors and their effects which can attenuate the firm’s performance.
First, we briefly discuss the introduction and importance of the topics. Discuss the past, present, and future point of view for the topics with theoretical literature review. Second, discuss the characteristics of online marketplaces which are potentially influence the firm’s performance. Besides the characteristics, also elicit the environmental effects which strengths/attenuate the firm performances. Third, display the sources of data, big data analytics, empirical methodology to investigate the characteristics of online marketplaces and their interaction with market environment. Finally, share the empirical findings, theoretical and managerial implications, connotations, contributions, challenges, and future directions of the research in the context of online marketplace and firm’s performance. We also delineate that, how firms can favourably benefitted through understanding the characteristics to increase the sustainable advantages.
HOSSIN MD ALTAB received PhD and Master Degree from University of Electronic Science and Technology of China. Currently he is working as a Post-doctoral Research Fellow at the School of Management and Economics, University of Electronic Science and Technology of China (UESTC). His research interests include Enterprise Management, Online marketplaces, Information Systems & Management, Data Mining techniques, NLP, and Consumer behavior. His paper available on several SSCI and SCI journal including International Journal of Electronic Commerce (IJEC).
（1）主题：Customer Value Co-creation and Employee Behaviour; Personal and Organizational Resources as Explanatory Mechanisms.
（2）主讲人：Evans Asante Boadi 经济与管理学院博士后
A growing number of empirical studies and the concept of service-dominant logic has shown that employees are always expected to influence customers’ experience. The customer experience is mostly determined through physical consumption, thinking and dreaming about something, as well as feeling good about something. In this vein, it is doubtful the extent to which employees can always meet customer expectations in value cocreation. Therefore, in this talk;
1.We will explore the extent to which customer value co-creation influence employees’ negative coping behaviours from the perspective of the service-dominant logic. Our interest in employees’ negative coping behaviours is based on their association with negative consequences such as burnout and low productivity. 2. We will examine how employee personal resource can explain the relationship between customer value cocreation and employees’ negative coping behaviours. 3. We will find out how organizational resources based on social information processing theory can improve the link between customer value cocreation and employees’ negative coping behaviours.
C. Asante Boadi received master’s degree from University of Applied Management, Erding, Germany and Ph. D from the School of Management and Economics, University of Electronic Science and Technology of China (UESTC). He serves as article editor and referee for peer review journals including International Journal of Contemporary Hospitality Management, Journal of Sustainable Tourism, Journal of Hospitality and Tourism Management. His current research focuses on customer and employee behaviour using cross-disciplinary approach to resolve research questions with theories from psychology, sociology and marketing in the context of hospitality and tourism industry.
编辑：林坤 / 审核：林坤 / 发布者：陈伟