Optimal service quality and pricing for App service supply chain with network externality based on four different scenarios

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Abstract

Purpose: The paper aims to investigate the optimal service quality and pricing for a mobile application (App) service supply chain (SSC) and analyze the impact of network externality on App SSC members' utilities. After that, the corresponding management inspirations and suggestions are put forward. Design/methodology/approach: The paper developed a SSC consisted of an App service supplier and an App service operator. Our models aim to maximize the SSC members' utilities. By utilizing the game theory, equilibrium solutions are obtained. Numerical examples are used to manifest the impact of parameters on decisions by Matlab. Some management enlightenment could be obtained by comparison analysis. Findings: Cooperating with an App service operator that asks for a lower revenue sharing ratio will enable the App service supplier to have sufficient funds to provide high-quality update service. With the increase of network externality, adopting a high-quality service strategy can bring higher utility to the App service operator and users. Pouring attention into consumer welfare moderately will improve the App service supplier's utility. Scenario CRS can achieve a win–win goal for App SSC members and consumers. Originality/value: The innovations of this paper are as follows: Firstly, the authors investigate the optimal service quality and pricing for the App SSC, which has been discussed little in previous literature. Secondly, the authors discuss how network externality and enterprises' attention to consumer welfare affect the optimal decisions and utilities of App service supply chain members. Thirdly, this paper considers four different circumstances and determines the optimal operation scenario for App SSC through comparative analysis.

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APA

Xing, P., Wang, M., & Yao, J. (2023). Optimal service quality and pricing for App service supply chain with network externality based on four different scenarios. Kybernetes, 52(9), 3425–3450. https://doi.org/10.1108/K-06-2021-0470

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