Optimal pricing in social networks considering reference price effect
Yongrui Duan and
Yixuan Feng
Journal of Retailing and Consumer Services, 2021, vol. 61, issue C
Abstract:
We study the optimal monopoly pricing strategies in a social network, in which consumers experience a network effect that is dependent on their neighbors' consumptions and a reference price which is the average price received by their neighbors. We establish a two-stage game model for any social network. Utilizing the backward induction, we derive the equilibrium price by maximizing the monopolist's profit. In addition, we apply this model to the two most commonly used network structures: the star network and the bipartite network. We find that both the network effect and the reference price effect play a critical role in deciding pricing strategies in social networks. Moreover, our numerical results demonstrate that whether to implement discriminatory pricing depends critically on the network structure. This work provides monopoly firms a useful guideline for optimal pricing decisions in social network marketing.
Keywords: Network effects; Pricing; Reference price; Social networks (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S096969892100093X
Full text for ScienceDirect subscribers only
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:eee:joreco:v:61:y:2021:i:c:s096969892100093x
DOI: 10.1016/j.jretconser.2021.102527
Access Statistics for this article
Journal of Retailing and Consumer Services is currently edited by Harry Timmermans
More articles in Journal of Retailing and Consumer Services from Elsevier
Bibliographic data for series maintained by Catherine Liu ().