Person:

Chung, Doug

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. A major challenge is that privacy laws prevent us from observing information about the applicant pool. I overcome this challenge by using order statistic distribution to infer applicant quality from information on enrolled students. Using a flexible random coefficients aggregate discrete choice model—which accommodates heterogeneity in preferences for school quality and athletic success—and an extensive set of school fixed effects to control for unobserved quality in athletics and academics, I estimate the impact of athletic success on applicant quality and quantity. 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. Furthermore, the decay rate of athletics goodwill is significant only for students with lower SAT scores, suggesting that the goodwill created by intercollegiate athletics resides more extensively with low-ability students than with their high-ability counterparts. But, surprisingly, athletic success impacts applications even among academically stronger students.

The platform—a business model that creates value by connecting groups of users—is increasingly popular in many industries. Extant papers largely assume that platforms dominate the pricing decision, whereas in practice, prices in business-to-business transactions are often determined by a bargaining process. We study how the relative bargaining power of business partners affects pricing and competition in a two-sided market. We compile a unique and comprehensive dataset using sales data from the US daily deal market and specify a structural model based on Nash bargaining solutions. We find that Groupon, the larger deal platform, has more price-bargaining power than LivingSocial and that larger and chain merchants have more bargaining power than smaller and independent merchants. The difference in bargaining power between different types of merchant, interestingly, is more substantial on LivingSocial than on Groupon. Therefore, the size of a platform has two faces: while a larger customer base helps attract merchants, the platform’s bargaining power may motivate some merchants to work with its smaller competitors, over which they have more influence on price setting. Our counterfactual results show that the allocation of price-bargaining power plays an important role in the daily deal markets and that merchants are significantly worse off if platforms have higher price-bargaining power during the negotiation. Furthermore, as it increases the bargaining power, LivingSocial would be able to boost its profits but lose its attraction in acquiring merchants.

Firms increasingly use both mass-media advertising and targeted personal selling to successfully promote products and brands in the marketplace. In this study, we jointly examine the effect of mass-media advertising and personal selling in the context of U.S. presidential elections, where the former is referred to as the “air war” and the latter the “ground game.” Specifically, we look at how different types of advertising―candidate own ads vs. outside ads―and personal selling―in the form of utilizing field offices―affect voter preferences. Further, we ask how these various campaign activities affect the outcome of elections through their diverse effects on various types of people. We find that personal selling has a stronger effect among partisan voters, while candidate's own advertising is better received by non-partisans. We also find that personal selling accounted for the Democratic victories in the 2008 and 2012 elections, and that advertising was critical only in a close election, such as the one in 2004. Interestingly, had the Democrats received more outside advertising in 2004, the election would have ended up in a 269-269 tie. Our findings generate insights on how to allocate resources across and within channels.

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.

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. A major challenge is that privacy laws prevent us from observing information about the applicant pool. I overcome this challenge by using order statistic distribution to infer applicant quality from information on enrolled students. Using a flexible random coefficients aggregate discrete choice model that accommodates heterogeneity in preferences for school quality and athletic success, and an extensive set of school fixed effects to control for unobserved quality in athletics and academics, I estimate the impact of athletic success on applicant quality and quantity. 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. Furthermore, the decay rate of athletics goodwill is significant only for students with lower SAT scores, suggesting that the goodwill created by intercollegiate athletics resides more extensively with low-ability students than with their high-ability counterparts. But, surprisingly, athletic success impacts applications even among academically stronger students.

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.

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 salesforce 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. We find no evidence that effectiveness differs between a quota-bonus plan and 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; when immediate, sales force performance decreases. We also find heterogeneity in the impact of compensation on performance across salespeople; unconditional compensation is more effective for salespeople with high intrinsic ability, whereas conditional compensation is equally effective across all types of salespeople. Lastly, we find seasonality to significantly influence sales volumes for low ability, but not so much for high ability, salespeople.

We examine the effects of various political campaign activities on voter preferences in the domain of US Presidential elections. We construct a comprehensive data set that covers the three most recent elections, with detailed records of voter preferences at the state-week level over an election period. We include various types of the most frequently utilized marketing instruments: two forms of advertising—candidate’s own and outside advertising, and two forms of personal selling—retail campaigning and field operations. Although effectiveness varies by instrument and party, among the significant effects we find that a candidate’s own advertising is more effective than outside advertising, and that advertising and retail campaigning work more favorably towards Republican candidates. In contrast, we find field operations to be more effective for Democratic candidates, primarily through get-out-the-vote efforts. We do not find any between-party differences in the effectiveness of outside advertising. Lastly, we also find a moderate but statistically significant carryover effect of campaign activities, indicating the presence of dynamics of marketing efforts over time.

We collaborate with a Swedish retail chain to conduct a field experiment in which we change the sales force compensation scheme from a monthly to a daily quota plan. This intervention, along with a control group that did not encounter a change in compensation structure, allows us to analyze the effect of quota frequency on sales force performance. Over a given time frame (i.e., a month), we find that shifting to a temporally more frequent quota plan—the daily quota plan as compared to the monthly quota plan—leads to an increase in sales performance, mainly for low-performing salespeople, by preventing them from giving up in the latter days of a month. However, we find high-performing salespeople to give up more frequently in earlier days of a month under the daily quota plan. With more frequent quotas, salespeople sell more quantities of low-ticket items, which benefit the firm through a decrease in returned merchandise. However, with quotas set over shorter time horizons, even the highest-performing salespeople focus mainly on incremental sales, resulting in a decrease in sales of higher-value-added and higher-margin products, thereby hurting firm profits.

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.