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A study on online platforms' price discrimination behavior and the same-side network effects.

Authors :
Yao, Can-Zhong
Mo, Yi-Na
Source :
Kybernetes. 2021, Vol. 50 Issue 11, p3037-3057. 21p.
Publication Year :
2021

Abstract

Purpose: The purpose of this paper is to whether competition between platforms can be effective, thus leading to efficient allocations. Design/methodology/approach: Based on the classic linear Hoteling model, this paper builds a two-period competition model for two competing platforms using two variants, namely, a discrimination pricing model and a unified pricing model. Findings: In the case of the discrimination pricing model, the competition is moderate, and the two platforms split the market evenly in the first stage, while both platforms tended to offer preferential treatment to new users and set higher prices for regular customers in the second stage. Compared to the unified pricing model, in the first stage, the platform can provide a higher price that depends on the cross-network effect when it implements discrimination, and thus, obtains higher profits. However, in the second stage, fierce competition leads to the release of benefits, new and regular customers obtain lower prices and the platforms lose higher profits. In the long-run, discriminatory pricing is not the best option due to lower total profits. The two platforms will implement cooperative pricing or one platform becomes dominant. Originality/value: Instead of focusing on the cross-network effects, this paper emphasizes the role of the same-side network effect on price discrimination regarding the platforms' competition. The same-side network effects are investigated in relation to a discrimination pricing strategy and compared to a unified pricing strategy. Another innovative aspect is the study of these network effects in a dynamic setting based on a two-period competition model for two platforms. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0368492X
Volume :
50
Issue :
11
Database :
Academic Search Index
Journal :
Kybernetes
Publication Type :
Periodical
Accession number :
153551845
Full Text :
https://doi.org/10.1108/K-06-2020-0353