The Causal Impact of Incentive Structure and Message Design on Product Diffusion: Evidence from Two Randomized Field Experiments

University of Minnesota Ph.D. dissertation.May 2017. Major: Business Administration. Advisor: Ravi Bapna. 1 computer file (PDF); iv, 98 pages.59% of people consult friends for advice in making purchase decisions. Not surprisingly, concomitant with the exploding growth of digital social networks, firms recognize the importance of using referral programs towards driving new business. Such schemes encourage existing customers with an incentive-laden call-to-action to engage their social networks by informing them about products and ultimately influencing and stimulating friends’ purchase decisions. While referral marketing is a widely adopted practice, the underlying science behind understanding and optimizing its various dimensions is nascent. The optimal design of referral program can be determined by three key design choices: incentive design (for both sender and recipients), call-to-action for information sharing (to the sender) and message design (to the recipient). While previous research has examined the design of message sent to the recipients, no study has investigated how firms can optimally design the incentive to the sender and receiver and message to the sender in the form of a call-to-action to engage customers. In this dissertation, I examine whether and how a firm can enhance social contagion by varying incentives (first essay) as well as the framing of the call-to-action messages (second essay) shared by customers with their friends. In collaboration with two US-based companies, I conduct two randomized field experiments to identify the causal effect of three types of difference incentive schemes, as well as three different types of call for sharing, respectively. The first experiment involves manipulations of how the monetary reward is shared between the sender and the receiver of the referral: selfish reward (sender gets all), equal reward (50-50 split), and generous reward (receiver gets all). In the second experiment, I test the effect of three different calls for referral: a) the egoistic call for sharing action, where I highlight the reward to the sender, b) the equitable based call for sharing action, where I highlight that both sender and the receiver get the reward, and c) the altruistic call for sharing action, where I highlight the reward to the receiver. The results show that the generous pro-social referral reward schemes and altruistic framing dominate selfish schemes and egoistic framing in creating word-of-mouth. Theoretically, the results together provide concrete and causal support to the hitherto under-studied role of altruism in creating social contagion. The findings of the study provide insights to companies planning to run referral programs to promote WOM based adoption of the products

Blessing or Curse: Impact of Algorithmic Trading Bots Invasion of the Cryptocurrency Market

In this paper, we investigate the impact of the absence of trading bots on human traders’ investment returns. Using comprehensive data set obtained from a large cryptocurrency exchange platform, we find that trading bots play a market-making role, and they boost human traders’ investment returns. We use the natural experiment setting that transforms a heterogenous market co-created with trading bots and human traders into a human-only financial market for empirical design. This paper extends the traditional investment decision under uncertainty by considering human attitudes toward algorithms while providing significant contributions to policymakers and regulators by providing empirical evidence on trading bots

Does Care Lead to Share? Evidence from a Randomized Field Experiment on Call for Sharing

Information sharing through online WOM has become increasingly important for businesses. Despite the popularity of online referral programs, little is known about how firms can optimally design call for sharing to encourage referrals, as well as the motives underlying those referrals. In collaboration with a large US based online platform, we conduct a randomized field experiment involving 100,000 customers to identify the causal effect of three types of call for sharing (egoistic, equitable and altruistic). Our experiment shows that ‘altruistic’ call for sharing leads to the highest likelihood of sharing and best sharing outcomes. In addition, the analysis results provide direct managerial implications to firms on the optimal design of call for sharing campaigns (how, to whom and when to initial call for sharing). Finally, we discuss the key differences and complementarity between call for sharing and call for purchase, and offer guidance on firm\u27s integrated marketing communication strategy

Are More Choices Better? Examining the Impact of Choice Capacity in Online Dating Platform

Online matching platforms require new approaches to market design since firms can now control many aspects of search and interaction process through various IT-enabled features. While choice capacity—the size of choice set and the number of choices a platform offers to its customers—is one of the key design features of online matching platforms, there has been lack of understanding of its impact on engagement and matching outcomes. In this study, we examine the effect of different choice capacities on the number of choices and matches on the platform by conducting a randomized field experiment in collaboration with an online dating platform. We find that providing higher choice capacities to male and female users have different effect on choice behaviors and matching outcomes. We find that while increasing the choice capacity of male users yields the highest number of choices, increasing the choice capacity of female users turns out to be the most effective way to increase matching outcomes

Mobile as a Channel: Evidence from Online Dating

While it has been widely documented that mobile users tend to differ from PC users in their observed behavior, such differences cannot necessarily be attributed to adoption of the mobile app because of endogeneity issues in drawing inferences from observing users who decide to adopt the mobile app. In this paper, we causally explore the changes in user behavior as well as matching outcomes due to adopting a mobile app in the online dating context. We demonstrate that once users have adopted the mobile app, they become more ubiquitous in their use and also become more socially engaged. We also find that female adopters are able to achieve more matches and become more efficient in achieving matches per each message sent. As mobile app adoption becomes widespread, understanding the causal impact on social engagement and outcomes has implications for both end users as well as businesses investing in app development

Love Unshackled: Identifying the Effect of Mobile App Adoption in Online Dating

The proliferation of smartphones and other mobile devices has led to numerous companies investing significant resources in developing mobile applications, in every imaginable domain. As apps proliferate, understanding the impact of app adoption on key outcomes of interest and linking this understanding to the underlying mechanisms that drive these results is imperative. In this paper, we explore the changes in user behavior induced by adoption of a mobile application, in terms of engagement and matching outcomes in the online dating context. We also identify three mechanisms that are somewhat unique to the mobile environment, but are hitherto unestablished in the literature, that drive this shift in behavior: ubiquity, impulsivity, and disinhibition. Our main identification strategy uses propensity score matching combined with difference-in-differences, coupled with a rigorous falsification test to confirm the validity of our identification strategy. Our results demonstrate that mobile app adoption induces users to become more socially engaged as measured by key engagement metrics such as visiting significantly more profiles, sending significantly more messages, and importantly, achieving more matches. We also discover various mechanisms facilitating this increased engagement: ubiquity of mobile use—users log in more, and login across a wider range of hours in the day. We find that men act more impulsively, in that they are less likely to check the profile of a user who messaged them before replying to them. This effect is not visible for women who continue to be deliberate in their checking before replying even after adoption of the mobile app. Finally, we find that both men and women exhibit disinhibition, in that users initiate actions to a more diverse set of potential partners than they did before on dimensions of race, education, and height