Value-Partitioning of Sales Contribution in Business Markets

• 成果类型: Article; Early Access
• 署名作者: Shi, Huanhuan; Sridhar, Shrihari; Grewal, Rajdeep
• 署名单位: Texas A&M University System; Texas A&M University College Station; Mays Business School; University of North Carolina; University of North Carolina Chapel Hill; University of North Carolina School of Medicine
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1177/10591478251340433
• 发表日期: 2025
• 关键词: Business Markets; EMPIRICAL BAYES; fixed effects; Marketing and Operations Interface; Sales Operations; Sales Reps; Unobserved Effects

摘要

In business markets, sales from customers are often jointly determined by multiple roles, yet firms struggle to quantify individual contribution of each role and the synergies among them. This study applies a value-partitioning approach to separate the sales contributions of customer-focused outside (OS) representatives (reps) and operations-focused inside (IS) reps, and their synergistic effects. It leverages variations in OS-IS combinations to generate individual-level value-added metrics, as well as metrics for dyadic synergies. To address empirical challenges such as limited variations in OS-IS combinations, the study employs empirical Bayes estimation, which provides best linear unbiased prediction (BLUP) estimates. An application using data from a Fortune 500 firm operating in business markets, reveals that the value added by OS reps, IS reps, and their interface have substantial and differential impacts on customer sales. Specifically, an increase of one standard deviation in the effect of OS, IS, or interface synergy improves customer sales by 17.8%, 11.6%, or 14.3%, respectively. Simulations demonstrate the superiority of empirical Bayes over fixed effects estimation in reducing bias, and that the value-added metrics are predictive of future customer sales. This research also illustrates how value-added metrics can be applied to evaluate the impact of sales programs on different sales roles.