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

Abstract

I n 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.

Suspecting service overprovisions: how market signals help restore personal control and reduce decision deferrals

“…A large literature on salesforce compensation supports the idea that salary and commissions address different seller motives. While salaries put less focus on the quantity and more focus on the quality of the services provided to the customers, commissions do the reverse (Basu et al, 1985;Dai and Jerath, 2019;John and Weitz, 1989;Lal and Staelin, 1986;Xiao and Xiao, 2020). Notice, also, that paying a fixed salary imposes a high fixed cost on the sellers that is unconnected to sales, and the fixed nature of such investments makes this signal harder to mimic for other sellers who lack the deep pockets for doing so (Kalra et al, 2003).…”

“…the mechanics doing the diagnostics and repairs) with fixed salaries instead of commissions. The assumption is that fixed salaries, unlike commissions, will take away the agents' motivation to overprovide services to consumers (Lal and Staelin, 1986;Xiao and Xiao, 2020).…”

Salesforce Compensation and Two‐Sided Ambiguity: Robust Moral Hazard with Moment Information

“…These models show that classical inventory results could be combined with linear contracts if there were no lost sales. More recently, Xiao and Xiao (2020) study an inventory allocation model where sales agents influence market demand, and the firm pays a penalty cost for a mismatch between supply and demand (of which backorders is the most natural special case). Considering a broad class of contracts, Xiao and Xiao (2020) advocate the use of S‐shaped compensation schemes and forecast‐based incentive schemes for firms with high operational mismatch costs.…”

“…More recently, Xiao and Xiao (2020) study an inventory allocation model where sales agents influence market demand, and the firm pays a penalty cost for a mismatch between supply and demand (of which backorders is the most natural special case). Considering a broad class of contracts, Xiao and Xiao (2020) advocate the use of S-shaped compensation schemes and forecastbased incentive schemes for firms with high operational mismatch costs. Chu and Lai (2013) and Dai and Jerath (2013) consider the impact of demand censoring on inventory allocation and salesforce compensation contracts in the context of full information on the demand distribution.…”

“…Specifically, we can obtain an improved a TQ contract with a similar form to the contract illustrated in Figure 1b (see Appendix C for details). The TQ contract has similar properties to the S-contract proposed by Xiao and Xiao (2020), since both contracts have upper and lower bounds on the payment to the agent. Thus, the DF contract dominates any standard QB contract and protects the firm against the main drawback of pure quadratic contracts (i.e., a negative textitex post profit due to high demand).…”