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Technical Note: Optimal Salesforce Compensation with Supply–Demand Mismatch Costs

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  • Binqing Xiao
  • Wenqiang Xiao

Abstract

In this study, we characterize the optimal compensation scheme for a firm that sells a single product with a limited stocking quantity through a sales agent. Our focus is on understanding how the supply–demand mismatch costs affect the firm’s optimal compensation scheme. There are two main findings. First, under the deterministic demand response, the classical optimality result of the convex increasing compensation scheme breaks with the consideration of supply–demand mismatch costs. Instead, the optimal compensation is S‐shaped under certain conditions. Second, under the stochastic demand response, the classical optimality result of the menu of linear compensation schemes fails to hold with the consideration of supply–demand mismatch costs. Instead, the optimal compensation schemes consist of a menu of linear compensation coupled with a penalty of the agent’s forecast error.

Suggested Citation

  • Binqing Xiao & Wenqiang Xiao, 2020. "Technical Note: Optimal Salesforce Compensation with Supply–Demand Mismatch Costs," Production and Operations Management, Production and Operations Management Society, vol. 29(1), pages 62-71, January.
  • Handle: RePEc:bla:popmgt:v:29:y:2020:i:1:p:62-71
    DOI: 10.1111/poms.13096
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    References listed on IDEAS

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    Cited by:

    1. Yang, Xiaolin & Gou, Qinglong & Wang, Xin & Zhang, Juzhi, 2022. "Does bonus motivate streamers to perform better? An analysis of compensation mechanisms for live streaming platforms," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    2. Zhaolin Li & Samuel N. Kirshner, 2021. "Salesforce Compensation and Two‐Sided Ambiguity: Robust Moral Hazard with Moment Information," Production and Operations Management, Production and Operations Management Society, vol. 30(9), pages 2944-2961, September.

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