Pricing Strategies for Competing Adaptive Retailers Facing Complex Consumer Behavior: Agent-based Model
Heng Du and
Tiaojun Xiao
Additional contact information
Heng Du: Center for Behavioral Decision and Control, School of Management and Engineering, Nanjing University, Nanjing 210093, China
Tiaojun Xiao: Center for Behavioral Decision and Control, School of Management and Engineering, Nanjing University, Nanjing 210093, China
International Journal of Information Technology & Decision Making (IJITDM), 2019, vol. 18, issue 06, 1909-1939
Abstract:
This paper examines pricing strategies for two adaptive retailers competing on two products in the presence of complex consumer behavior, where consumers own heterogeneous product and store valuations and the number of potential consumers is random. Each retailer can choose one from two pricing strategies: the uniform pricing format (offering the same price for two products) or the differentiated pricing format (offering different prices). Utilizing agent-based model (each retailer is modeled as an autonomous agent with the reinforcement learning behavior), we find that: (i) the differentiated pricing format is not always the optimal choice; (ii) when the uncertainty of one product/store valuation is a little larger than that of the rival, both retailers should adopt uniform pricing. Besides, when wholesale price contract is endogenous, we find that supplier’s pricing behavior can change the impact of the fixed cost on the pricing strategy.
Keywords: Pricing strategy; complex consumer behavior; supply chain management; agent-based model; game theory (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S021962201950038X
Access to full text is restricted to subscribers
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:wsi:ijitdm:v:18:y:2019:i:06:n:s021962201950038x
Ordering information: This journal article can be ordered from
DOI: 10.1142/S021962201950038X
Access Statistics for this article
International Journal of Information Technology & Decision Making (IJITDM) is currently edited by Yong Shi
More articles in International Journal of Information Technology & Decision Making (IJITDM) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().