Smart allocation of a developer's spending on product quality and non-salary employee benefits in a supply chain of apps

IF 3.7 4区 管理学 Q2 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Operations Research Perspectives Pub Date : 2024-12-05 DOI:10.1016/j.orp.2024.100320
Leonard Omer Maly, Tal Avinadav
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Abstract

Qualified and capable employees are crucial for the success of high-tech companies. With an ever-shrinking pool of talent, employers are forced to devise creative recruitment and retention methods, which increasingly take the form of heavy spending on non-salary benefits. The present study contributes to the existing supply-chain literature through examining the role played by such benefits in a two-agent system consisting of a platform and an app developer. In particular, we examine the effect of non-salary benefits on the outgoing quality created by the employees of the app developer. The parties follow a Stackelberg sequential game led by the platform to accurately reflect the interaction in the market, allowing us to reach equilibrium using backward induction. Our results indicate that when app developers are more risk averse or face greater uncertainty, they spend a greater amount on non-salary benefits and comparatively less on app quality. This finding highlights the importance of investing in workers, particularly in uncertain times. We further extend the applicability and robustness of our findings by introducing multiple developers to our two-agent system. The extension proves that the platform charges a universal commission rate, irrespective of the number of developers – a finding that is consistent with current practice. Given the non-linear effect of key model parameters on the profits of the supply-chain members in both the single and the multiple-developer setups, we also utilize numerical analyses and arrive at telling managerial implications for all parties.
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来源期刊
Operations Research Perspectives
Operations Research Perspectives Mathematics-Statistics and Probability
CiteScore
6.40
自引率
0.00%
发文量
36
审稿时长
27 days
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