How Do Sales Efforts Pay Off? Dynamic Panel Data Analysis in the Nerlove-Arrow Framework

• 成果类型: Article
• 署名作者: Chung, Doug J.; Kim, Byungyeon; Park, Byoung G.
• 署名单位: Harvard University; State University of New York (SUNY) System; University at Albany, SUNY
• 刊物名称: MANAGEMENT SCIENCE
• ISSN/ISSBN: 0025-1909
• DOI: 10.1287/mnsc.2018.3189
• 发表日期: 2019
• 页码: 5197-5218
• 关键词: Nerlove-Arrow framework; stock-of-goodwill; dynamic panel data; serial correlation; instrumental variables; sales effectiveness; detailing; Pharmaceutical industry

摘要

This paper evaluates the short- and long-term value of sales representatives' detailing visits to different types of physicians. By understanding the dynamic effect of sales calls across heterogeneous physicians, we provide guidance on the design of optimal call patterns for route sales. The findings reveal that the long-term persistence effect of detailing is more pronounced for specialist physicians, whereas the contemporaneous marginal effect is higher for generalists. The paper also provides a key methodological insight to the marketing and economics literature. In the Nerlove-Arrow framework, moment conditions that are typically used in conventional dynamic panel data methods become vulnerable to serial correlation in the error structure. We discuss the associated biases and present a robust set of moment conditions for both lagged dependent and predetermined explanatory variables. Furthermore, we show that conventional tests to detect serial correlation have weak power, resulting in the misuse of moment conditions that leads to incorrect inference. Theoretical illustrations and Monte Carlo simulations are provided for validation.