Doug J. Chung is the MBA Class of 1962 Associate Professor of Business Administration at Harvard Business School. He teaches Sales Management & Strategy in the second year MBA Elective Curriculum. He also chairs the Executive Education program, Managing Sales Teams and Distribution Channels. He has previously taught B2B Marketing in the MBA Elective Curriculum, the core Marketing course in the first year MBA Required Curriculum, Marketing Models in the PhD Curriculum, and in various Executive Education programs at the Harvard Business School and Harvard Law School.
Professor Chung focuses his research primarily on sales strategy, sales force management and incentive compensation. He has worked with firms worldwide to develop effective employee incentive compensation systems and his work has been published in Marketing Science, Management Science, Journal of Marketing Research, and the Harvard Business Review. His current work examines how specific elements of an incentive compensation system affect the performance and selection of varying types of sales employees.
Professor Chung earned his Ph.D. in management at Yale University, where he also earned an M.A. and M.Phil. in management. He was the finalist for the 2014 John D. C. Little Award, the 2015 Frank M. Bass Award, and the 2020 Gary L. Lilien Practice Prize. He was selected as a 2017 MSI Young Scholar by the Marketing Science Institute. Professor Chung serves on the editorial board at major academic journals, including Marketing Science, Journal of Marketing Research, and the International Journal of Research in Marketing. He currently serves as a Senior Advisor for McKinsey & Company’s sales and marketing practices. He completed his undergraduate studies at Korea University. Prior to pursuing a career in academics, Professor Chung served as a platoon commander in the South Korean Special Warfare Command.
This study provides a comprehensive model of an agent’s behavior in response to multiple sales management instruments, including compensation, recruiting/termination, and training. The model takes into account many of the key elements that constitute a realistic sales force setting—allocation of effort; forward-looking behavior; present bias; training effectiveness; and employee selection and attrition. By understanding how these elements jointly influence agents’ behavior, the study provides guidance on the optimal design of sales management policies. A field validation, by comparing counterfactual and actual outcomes under a new policy, attests the accuracy of the model. The results demonstrate a trade-off between adjusting fixed and variable pay; how sales training serve as an alternative to compensation; a potential drawback of hiring high-performing experienced salespeople; and how utilizing a leave package leads to sales force restructuring. In addition, the study offers a key methodological contribution by providing formal identification conditions for hyperbolic time preferences. The key to identification is that, under a multi-period nonlinear incentive system, an agent’s proximity to a goal affects only future payoffs in non-pecuniary benefit periods, providing exclusion restrictions on the current payoff.
This study jointly examines the effects of television advertising and field operations in U.S. presidential elections, with the former referred to as the “air war” and the latter as the “ground game.” Specifically, the study focuses on how different campaign activities—personal selling in the form of field operations and mass media advertising by the candidate and outside sources—vary in their effectiveness with voters who have different political predispositions. The voting choice model takes into consideration voter heterogeneity and analyzes comprehensive data that include voting outcomes, detailed campaign activities, and voters’ party affiliation for three presidential elections (2004-2012). The results reveal that different campaign activities have heterogeneous effects depending on voters’ party affiliation. Field operations and political advertising from outside groups are more effective with partisans, while a candidate’s advertising is more effective with non-partisans. These findings can help strategists better allocate resources across and within channels to design an effective political marketing campaign.
Personal selling represents one of the most important elements in the marketing mix, and appropriate management of the sales force is vital to achieving the organization’s objectives. Among the various instruments of sales management, compensation plays a pivotal role in motivating and incentivizing sales agents. This monograph reviews the evolution of research in sales compensation and discusses future trends and opportunities. Specifically, it examines the managerial relevance of the theoretical foundations, discussing the underlying reasons for their applicability (or lack thereof) in practice. Furthermore, the monograph surveys recent empirical methods—including field experiments and structural econometrics—that are practical for analyzing sales agents’ behavior under various compensation systems. It also discusses prominent areas of future research in the midst of a changing sales environment. In particular, this monograph sheds light on how the use of big data, machine learning, and artificial intelligence can affect sales strategy formulation and, thus, sales compensation systems to better motivate and incentivize an organization’s sales force.
This study investigates the comprehensive and multidimensional effects of quota (goal) frequency on sales force performance. The study provides a theory of salespeople’s behavior—aggregate effort and the product type focus—in response to the temporal length of a sales-quota cycle. The theory includes many realistic elements, such as salespeople’s multi-dimensional effort, heterogeneity in ability, product focus, and forward-looking behavior. We test the theory through a field experiment, varying the sales compensation structure of a major retail chain in Sweden. Consistent with the developed theory, shifting to a temporally frequent quota structure leads to an increase in sales performance for low-performing salespeople by preventing them from giving up in later periods within a quota-evaluation cycle, but to a decrease in sales performance for high-performing salespeople. With quotas set over short time horizons, the high-performing salespeople focus mainly on low-ticket products, resulting in a decrease in both sales volume and the sale of high-ticket products, thus reducing the firm’s profits.
The prevalence of online platforms opens new doors to traditional businesses for customer reach and revenue growth. This research investigates platform competition in a setting where prices are determined by negotiations between platforms and businesses. We compile a unique and comprehensive data set from the U.S. daily deal market, where merchants offer deals to generate revenues and attract new customers. We specify and estimate a two-stage supply-side model in which platforms and merchants bargain on the wholesale price of deals. Based on Nash bargaining solutions, our model generates insights on how bargaining power and bargaining position jointly determine price and firm profits. By working with a bigger platform, merchants enjoy a larger customer base but they are subject to lower margins due to less bargaining power during negotiation. Counterfactual results reveal that, in the absence of platform competition merchants are worse off due to their weaker bargaining position but consumers experience lower prices, leading to an increase in total demand.
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
We conduct a field experiment in which we vary the sales force compensation scheme at an Asian enterprise that sells consumer durable goods. With variation generated by the experimental treatments, we model sales force performance to identify the effectiveness of various forms of conditional and unconditional compensation. We account for salesperson heterogeneity by using a hierarchical Bayesian framework to estimate our model. We find conditional compensation in the form of quota-bonus incentives to improve performance; however, it may lead to lower future performance. We find little evidence that effectiveness differs between a quota-bonus plan and a punitive-bonus plan framed as a penalty for not achieving quota. We find unconditional compensation in the form of reciprocity to be effective at improving sales force performance only when given as a delayed reward of which the effectiveness decreases with repeated exposure. We also find heterogeneity in the impact of compensation on performance across salespeople; unconditional compensation is more effective for salespeople with high base performance, whereas conditional compensation is equally effective across all types of salespeople.
Intercollegiate athletics in the United States have become a multibillion-dollar industry over the past several decades. In this study, we investigate the short- and long-term direct monetary effects of operating a winning athletics program for an academic institution of higher education. We construct a unique panel dataset from multiple sources and utilize the latest dynamic panel data estimation methods to account for heterogeneity while also addressing endogeneity concerns. We find that success in men’s football and basketball has a significant impact on a school’s respective football and basketball revenues; however, the effect is different based on the type of school. We find that regular season wins in football account for most of the increase in revenue for established schools whereas invitations to prestigious postseason bowl games play a big part for less-established schools. Furthermore, we find that student population and education quality dissipate the effect of athletic success on monetary payoffs. We find that success in basketball carries over more from the past than in football with additional contemporaneous marginal effects for established schools. We do find, however, that past athletic success carries over significantly to the present in both football and basketball, suggesting the significance of the long-term monetary effect of athletic success to many academic institutions in the United States.
Much of what we believe about the best ways to compensate and motivate the sales force is based on theory and lab experiments. But in the past decade, researchers have been moving out of the lab and into the field, analyzing companies' sales and pay data, and conducting experiments involving actual salespeople. The findings from this new wave of research support some current compensation practices but call others into question. For example, studies clearly show that caps on commissions hurt sales. If managers must retain a cap, they should set it as high as possible to avoid reducing reps' incentives. Although overly complicated compensation systems have their downsides, research has found that a system needs to include enough elements (such as quarterly performance and overachievement bonuses) to keep high performers, low performers, and average performers engaged throughout the year. Managers should be careful in setting and adjusting quotas. For instance, studies show that ratcheting (raising a salesperson's annual quota if he or she exceeded it the previous year) dampens motivation. The research also suggests that it's important to pay attention to the timing of bonuses: a reward given at the end of a period is more motivating than one given at the beginning.
For practical reasons, many companies offer a common incentive plan to an entire sales force rather than offering customised plans for each individual. Doug J. Chung, Thomas Steenburgh, and K. Sudhir address how companies can design a single plan that motivates everyone to work to the best of their abilities.
I measure the spillover effect of intercollegiate athletics on the quantity and quality of applicants to institutions of higher education in the United States, popularly known as the "Flutie Effect." I treat athletic success as a stock of goodwill that decays over time, similar to that of advertising. Overall, athletic success has a significant long-term goodwill effect on future applications and quality. However, students with lower than average SAT scores tend to have a stronger preference for athletic success, while students with higher SAT scores have a greater preference for academic quality.
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 exclusion restriction separating current and future payoff and (2) a finite horizon model in which there is no forward looking behavior in the last period.
