Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/79749
Title: Evolutionary game analysis and regulatory strategies for online group-buying based on system dynamics
Authors: Jiang, ZZ
He, N
Qin, XW
Ip, WH 
Wu, CH 
Yung, KL 
Keywords: Online group-buying
Bounded rationality
Three-parties evolutionary game
System dynamics
Regulatory strategies
Issue Date: 2018
Publisher: Taylor & Francis
Source: Enterprise information systems, 2018, v. 12, no. 6, p. 695-713 How to cite?
Journal: Enterprise information systems 
Abstract: The emergence of online group-buying provides a new consumption pattern for consumers in e-commerce era. However, many consumers realize that their own interests sometimes can't be guaranteed in the group-buying market due to the lack of being regulated. This paper aims to develop effective regulation strategies for online group-buying market. To the best of our knowledge, most existing studies assume that three parties in online group-buying market, i.e. the retailer, the group-buying platform and the consumer, are perfectly rational. To better understand the decision process, in this paper, we incorporate the concept of bounded rationality into consideration. Firstly, a three-parties evolutionary game model is established to study each player's game strategy based on bounded rationality. Secondly, the game model is simulated as a whole by adopting system dynamics to analyze its stability. Finally, theoretical analysis and extensive computational experiments are conducted to obtain the managerial insights and regulation strategies for online group-buying market. Our results clearly demonstrate that a suitable bonus-penalty measure can promote the healthy development of online group-buying market.
URI: http://hdl.handle.net/10397/79749
ISSN: 1751-7575
EISSN: 1751-7583
DOI: 10.1080/17517575.2017.1412503
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