Research Interests
Job Market Paper
The Social Motivation of Leaderboards: Theory and Evidence from Sales Contests, with Madhu Viswanathan and George John
Sales contests have long been recognized as an effective tool to improve sales performance by motivating salespeople. However, existing research mainly focuses on how sales contests motivate participants through monetary motivation. This research aims to identify and explain the social effects that motivate participants in large-scale sales contests with leaderboards. We build a theoretical model to illustrate that leaderboards can heavily motivate agents who are leading (first-place loving effect) and who are lagging behind (last-place loathing effect) compared to agents in the middle. In addition, in the presence of social effects, leaderboards can play a significant role in improving the overall effort levels of agents when these social effects are salient. Using a set of real-world contests with leaderboards with each contest involving hundreds of participants and employing an identical leaderboard design with multiple pages viewable to participants, we show the existence of first-place loving effect and last-place loathing effect, and find that page standings influence next-day sales in a ``U"-shaped way, with participants on the first and last pages making more sales on a subsequent day compared to those on the middle pages, which is consistent with our model prediction. We then investigate the social motivation at different salience levels and find that agents who are closer to a page boundary when the social motivation is more salient make greater sales than their neighbors far away. Our research sheds light on the social incentives that motivate salespeople in real-world sales contests and provides practical implications for sales managers and firms looking to motivate their sales teams.
Working Papers (Manuscripts Available)
Referral, Learning, and Inventory Decisions in Social Networks, with Guangwen Kong and Ankur Mani (Equal Authorship)
With the proliferation of digital social networks, businesses increasingly use referral programs to increase market exposure and sales. When customers refer a product to others they naturally disclose their purchase decisions. Thus the referral process introduces a social learning effect. We study the interaction between social learning and referral program structure and examine their impact on a firm's inventory decisions. We find that the presence of customers who lack knowledge of their own preferences introduces demand bias but social learning reduces this bias at the expense of increased demand variance. We characterize the optimal inventory levels for different numbers of referrals allowed by the firm and find that it is governed by the combination of market exposure effect and demand substitution effect. In a single referral program, the stock-out of one product can diminish the demand of the other product. In contrast, a multiple referral program allows a firm to achieve full market exposure but meanwhile increases the demand variance. Hence, the optimal referral program has to balance the trade-off between market exposure and demand variance, and thus allows either one or two referrals per customer.
Social Listening with Competition: The Roles of Social Closeness and Extremity Bias, with Yi Zhu and Anthony Dukes
Social listening is the practice of companies using social media data to understand consumers’ perceptions of brands in the market. By engaging in social listening, the marketer wants to better assess demand and improve pricing strategy. However, when competitors have accesses to the same data, the profitability of social listening is not obvious. We build a stylized model to conceptualize social listening and derive conditions on market conditions for which firms profitably engage in this practice in equilibrium. The conditions we derive pertain to key constructs of social media information. Our framework indicates that firms’ equilibrium price and profitability are moderated by the social closeness between influencers and followers, as well as the extremity bias associated with social media posting. We show that social listening can be a profitable equilibrium strategy, but only in the presence of extremity bias and only when social sharing generates a sufficient degree of market segmentation that aligns with brand preferences.
Search, Prominence, and Product Design, with Ruitong Wang
Internet search traffic is heavily concentrated on a few selected prominent firms. The public worries that this phenomenon of search prominence can undermine competition, leading to a decline in product quality and thus harming consumers. However, little is known about the impact of search order on the firm’s strategic choice of product quality and pricing. This research provides a game-theoretical framework to unpack the ramification of search prominence on the firm’s choice of product quality and price, market competition, and consumer welfare. Surprisingly, we find that the prominent firm may deliberately downgrade its product quality even when the cost of production is the same for any quality level. In addition, prominence can be a liability rather than an asset such that more search traffic can sometimes reduce a firm’s profit. Finally, we find that search prominence can be welfare-improving to consumers even though it lowers the average quality level in the market.
Working in Progress
Presentations
"The Social Motivation of Leaderboards: Theory and Evidence from Sales Contests"
"Referral, Learning and Inventory Decisions"
"Social Listening with Competition: The Roles of Social Closeness and Extremity Bias"
- Salesforce, Incentive Design, Gamification, Behavioral Economics, Consumer Search, Social Interactions
Job Market Paper
The Social Motivation of Leaderboards: Theory and Evidence from Sales Contests, with Madhu Viswanathan and George John
- Dissertation essay 1
- IOEA Accessit Best Project Award, 2022
- 2022 ISBM Doctoral Dissertation Award, Finalist
- AMS 2023 Mary Kay Dissertation Proposal Award, Runner-up
Sales contests have long been recognized as an effective tool to improve sales performance by motivating salespeople. However, existing research mainly focuses on how sales contests motivate participants through monetary motivation. This research aims to identify and explain the social effects that motivate participants in large-scale sales contests with leaderboards. We build a theoretical model to illustrate that leaderboards can heavily motivate agents who are leading (first-place loving effect) and who are lagging behind (last-place loathing effect) compared to agents in the middle. In addition, in the presence of social effects, leaderboards can play a significant role in improving the overall effort levels of agents when these social effects are salient. Using a set of real-world contests with leaderboards with each contest involving hundreds of participants and employing an identical leaderboard design with multiple pages viewable to participants, we show the existence of first-place loving effect and last-place loathing effect, and find that page standings influence next-day sales in a ``U"-shaped way, with participants on the first and last pages making more sales on a subsequent day compared to those on the middle pages, which is consistent with our model prediction. We then investigate the social motivation at different salience levels and find that agents who are closer to a page boundary when the social motivation is more salient make greater sales than their neighbors far away. Our research sheds light on the social incentives that motivate salespeople in real-world sales contests and provides practical implications for sales managers and firms looking to motivate their sales teams.
Working Papers (Manuscripts Available)
Referral, Learning, and Inventory Decisions in Social Networks, with Guangwen Kong and Ankur Mani (Equal Authorship)
- Reject & Resubmit at Management Science
- NET Institute Summer Grant, 2018
With the proliferation of digital social networks, businesses increasingly use referral programs to increase market exposure and sales. When customers refer a product to others they naturally disclose their purchase decisions. Thus the referral process introduces a social learning effect. We study the interaction between social learning and referral program structure and examine their impact on a firm's inventory decisions. We find that the presence of customers who lack knowledge of their own preferences introduces demand bias but social learning reduces this bias at the expense of increased demand variance. We characterize the optimal inventory levels for different numbers of referrals allowed by the firm and find that it is governed by the combination of market exposure effect and demand substitution effect. In a single referral program, the stock-out of one product can diminish the demand of the other product. In contrast, a multiple referral program allows a firm to achieve full market exposure but meanwhile increases the demand variance. Hence, the optimal referral program has to balance the trade-off between market exposure and demand variance, and thus allows either one or two referrals per customer.
Social Listening with Competition: The Roles of Social Closeness and Extremity Bias, with Yi Zhu and Anthony Dukes
- Prepare for submission
Social listening is the practice of companies using social media data to understand consumers’ perceptions of brands in the market. By engaging in social listening, the marketer wants to better assess demand and improve pricing strategy. However, when competitors have accesses to the same data, the profitability of social listening is not obvious. We build a stylized model to conceptualize social listening and derive conditions on market conditions for which firms profitably engage in this practice in equilibrium. The conditions we derive pertain to key constructs of social media information. Our framework indicates that firms’ equilibrium price and profitability are moderated by the social closeness between influencers and followers, as well as the extremity bias associated with social media posting. We show that social listening can be a profitable equilibrium strategy, but only in the presence of extremity bias and only when social sharing generates a sufficient degree of market segmentation that aligns with brand preferences.
Search, Prominence, and Product Design, with Ruitong Wang
- Prepare for submission
Internet search traffic is heavily concentrated on a few selected prominent firms. The public worries that this phenomenon of search prominence can undermine competition, leading to a decline in product quality and thus harming consumers. However, little is known about the impact of search order on the firm’s strategic choice of product quality and pricing. This research provides a game-theoretical framework to unpack the ramification of search prominence on the firm’s choice of product quality and price, market competition, and consumer welfare. Surprisingly, we find that the prominent firm may deliberately downgrade its product quality even when the cost of production is the same for any quality level. In addition, prominence can be a liability rather than an asset such that more search traffic can sometimes reduce a firm’s profit. Finally, we find that search prominence can be welfare-improving to consumers even though it lowers the average quality level in the market.
Working in Progress
- The Effect of Windfalls on Sales Performance, with Madhu Viswanathan and George John
- Dissertation essay 2
- AI-related Biases in B2B, with Shantanu Dutta, Shankar Ganesan, Navid Mojir, Irene Nahm, Seshadri Tirunillai
- Inaugural B2B Connect Research Symposium
Presentations
"The Social Motivation of Leaderboards: Theory and Evidence from Sales Contests"
- ISMS Marketing Science Conference, Miami, Jun 2023
- CSOM Applied Econ Seminar, UMN, May 2023
- 2023 AMS Annual Conference, New Orleans, May 2023
- 2023 George John Symposium, Austin, May 2023
- 2023 Marketing Analytics Symposium Sydney, Sydney, Feb 2023
- 2023 AMA Winter Conference, Nashville, Feb 2023
- Marketing Dynamics Conference, Atlanta, Nov 2022
- 44th ISMS Marketing Science Conference, Virtual, Jun 2022
- 19th Institutional and Organizational Economics Academy, Corse, May 2022
- Enhancing Sales Force Productivity Conference, Kansas University, Apr 2022
"Referral, Learning and Inventory Decisions"
- 13th POMS-HK International Conference, Virtual, Jan 2023
- MSOM Annual Meeting, Virtual, June 2021
- POMS Annual Meeting, Virtual, May 2021
- INFORMS Annual Meeting, Nashville, November, 2016
"Social Listening with Competition: The Roles of Social Closeness and Extremity Bias"
- Haring Symposium, Indiana University, Apr 2021
- 42th ISMS Marketing Science Conference, Virtual, June 2020
- MSOM Annual Meeting, Singapore, July, 2019
- 41th ISMS Marketing Science Conference, Rome, June 2019