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Optimal Salesforce Compensation with General Demand and Operational Considerations

Author

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  • Haotian Song

    (School of Management, Zhejiang University, Hangzhou 310058, China)

  • Guoming Lai

    (McCombs School of Business, The University of Texas, Austin, Texas 78712)

  • Wenqiang Xiao

    (Stern School of Business, New York University, New York, New York 10012)

Abstract

Problem definition : We investigate the optimal salesforce compensation scheme in the context of private information and unobservable actions, considering common operational factors encountered in practice, including inventory costs, contractible versus censored demand information, and controlled versus delegated ordering. Methodology/results : Based on an agency model with general demand and cost functions, we derive optimality conditions for implementable contracts that can achieve the second-best outcome in all scenarios. The contracts are in the forms of a menu with linear compensation for demand or sales, incorporating inventory costs. Moreover, the contracts feature adjustments in compensation corresponding to the ordering level if it is delegated. Managerial implications : Our study reveals that, under reasonably mild conditions, optimal salesforce contracts can still maintain relatively simple forms, even when confronted with common operational factors and generalized demand and cost functions. However, the contracts must be tailored to suit the operational settings. Intriguingly, neither the loss of demand information nor the delegation of inventory decisions would compromise system efficiency at optimum.

Suggested Citation

  • Haotian Song & Guoming Lai & Wenqiang Xiao, 2024. "Optimal Salesforce Compensation with General Demand and Operational Considerations," Manufacturing & Service Operations Management, INFORMS, vol. 26(6), pages 2274-2283, November.
    • Handle: RePEc:inm:ormsom:v:26:y:2024:i:6:p:2274-2283
    DOI: 10.1287/msom.2022.0400
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    References listed on IDEAS

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    1. Mingliu Chen & Feng Tian & Ruiting Zuo, 2025. "Optimal Capacity and Price Designs Under Ex Ante and Ex Post Theft," Manufacturing & Service Operations Management, INFORMS, vol. 27(6), pages 2016-2035, November.

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