Do Bonuses Enhance Sales Productivity? A Dynamic Structural Analysis of Bonus-Based Compensation Plans

Abstract

We estimate a dynamic structural model of sales force response to a bonus based compensation plan. Substantively, the paper sheds insights on how different elements of the compensation plan enhance productivity. We find evidence that: (1) bonuses enhance productivity across all segments; (2) overachievement commissions help sustain the high productivity of the best performers even after attaining quotas; and (3) quarterly bonuses help improve performance of the weak performers by serving as pacers to keep the sales force on track to achieve their annual sales quotas. The paper also introduces two main methodological innovations to the marketing literature: First, we implement empirically the method proposed by Arcidiacono and Miller (2011) to accommodate unobserved latent class heterogeneity using a computationally light two-step estimator. Second, we illustrate how discount factors can be estimated in a dynamic structural model using field data through a combination of (1) an exclusions restriction separating current and future payoff and (2) a finite horizon model in which there is no forward looking behavior in the last period.

Consumer learning and evolution of consumer brand preferences

“…We estimated the model with few different weekly discount factors but the results were not very sensitive to the exact value of the discount factor. Please note that the best way to identify the discount factor is either to find contexts where proper exclusion restrictions and practical identification exist (e.g., Chung et al (2014)) or use (experimental or field) data that has information on behavior both in static and dynamic contexts/regimes to pin down the discount factor (e.g., Yao et al (2012)) but we do not have such data. There are indeed very few cases where such data are available.…”

Salesforce Compensation with Inventory Considerations

“…In 2006, firms in the United States spent $800 billion on salesforce compensation, which was three times the amount spent on advertising (Zoltners et al 2008). There is an extensive literature that has significantly enhanced our understanding of the issues involved in designing salesforce compensation contracts (Basu et al 1985, Bhardwaj 2001, Chung et al 2013, Felli and Villas-Boas 2000, Godes 2004, Hauser et al 1994, Jain 2012, Jerath et al 2010, Joseph and Kalwani 1998, Kishore et al 2013, Misra and Nair 2011, Prendergast 1999, Raju and Srinivasan 1996, Simester and Zhang 2010, Steenburgh 2008. This literature has typically assumed that there are no availability constraints, i.e., whereas demand is uncertain, realized demand is always fulfilled.…”

Short-Run Needs and Long-Term Goals: A Dynamic Model of Thirst Management

“…See, e.g., Khwaja et al (2007), Chevalier andGoolsbee (2009), andChung et al (2014) for alternative approaches to estimate discount factors when analyzing intertemporal decision making and forward-looking behavior. 8 We do not observe product availability for each individual at the time of consumption; therefore, we assume that the choice set is the same across individuals and across time.…”