2019 Marketing Seminars

This year the Wisconsin School of Business' Marketing Department is inviting doctoral candidates to come and present their research to our school. 

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Optimizing User Engagement through Adaptive Ad Sequencing 

Synopsis

Mobile in-app advertising has grown exponentially in the last few years. In-app ads are often shown in a sequence of short-lived exposures for the duration of a user’s stay in an app. The current state of both research and practice ignores the dynamics of ad sequencing and instead adopts a myopic framework to serve ads. In this paper, we propose a unified dynamic framework for adaptive ad sequencing that optimizes user engagement in the session, e.g., the number of clicks or length of stay. Our framework comprises of two components – (1) a Markov Decision Process
that captures the domain structure and incorporates inter-temporal trade-offs in ad interventions, and (2) an empirical framework that combines machine learning methods such as Extreme Gradient Boosting (XGBoost) with ideas from the causal inference literature to obtain counterfactual estimates of user behavior. We apply our framework to large-scale data from the leading in-app ad-network of an Asian country. We document significant gains in user engagement from adopting a dynamic framework. We show that our forward-looking ad sequencing policy outperforms all the existing methods by comparing it to a series of benchmark policies often used in research and practice. Further, we demonstrate that these gains are heterogeneous across sessions: adaptive forward-looking ad sequencing is most effective when users are new to the platform. Finally, we use a descriptive approach to explain the gains from adopting the dynamic framework.

Revenue-Optimal Dynamic Auctions for Adaptive Ad Sequencing 

Synopsis

Digital publishers often use real-time auctions to allocate their advertising inventory. These auctions are designed with the assumption that advertising exposures within a user’s browsing or app-usage session are independent. Rafieian (2019) empirically documents the interdependence in the sequence of ads in mobile in-app advertising, and shows that dynamic sequencing of ads can improve the match between users and ads. In this paper, we examine the revenue gains from adopting a revenue-optimal dynamic auction to sequence ads. We propose a unified framework with two components – (1) a theoretical framework to derive the revenue-optimal dynamic auction that captures both advertisers’ strategic bidding and users’ ad response and app usage, and (2) an empirical framework that involves the structural estimation of advertisers’ click valuations as well as personalized estimation of users’ behavior using machine learning techniques. We apply our framework to large-scale data from the leading in-app ad-network of an Asian country. We document significant revenue gains from using the revenue-optimal dynamic auction compared to the revenue-optimal static auction. These gains stem from the improvement in the match between users and ads in the dynamic auction. The revenue-optimal dynamic auction also improves all key market outcomes, such as the total surplus, average advertisers’ surplus, and market concentration.

Tesary Lin, Doctoral Student, University of Chicago

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Valuing Intrinsic and Instrumental Preferences for Privacy

Synopsis

In this paper, I propose a framework for understanding why and to what extent people value their privacy. In particular, I distinguish between two motives for protecting privacy: the intrinsic motive, that is, a “taste” for privacy; and the instrumental motive, which reflects the expected economic loss from revealing one’s “type” specific to the transactional environment. Distinguishing between the two preference components not only improves the measurement of privacy preferences across contexts, but also plays a crucial role in developing inferences based on data voluntarily shared by consumers. Combining a two-stage experiment and a structural model, I measure the dollar value of revealed preference corresponding to each motive, and examine how these two motives codetermine the composition of consumers choosing to protect their personal data. The compositional differences between consumers who withhold and who share their data strongly influence the quality of firms’ inference on consumers and their subsequent managerial decisions. Counterfactual analysis investigates strategies firms can adopt to improve their inference: Ex ante, firms can allocate resources to collect personal data where their marginal value is the highest. Ex post, a consumer’s data-sharing decision per se contains information that reflects how consumers self-select into data sharing, and improves aggregate-level managerial decisions. Firms can leverage this information instead of imposing arbitrary assumptions on consumers not in their dataset.

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2019 Marketing Camp

The Wisconsin School of Business’ Marketing Department hosts an annual Marketing Camp that invites guest speakers from all around the globe to present their research. The objective of the Camp is to network, share research, studies, and findings regarding the ever-changing marketing landscape. The marketing landscape is continuously evolving due to technological advancements and the multifaceted human population. We believe that in this day and age marketing research has never been more imperative. The focus of our marketing research is to help us gain key insights on marketing analytics and big data, consumer culture theory, and consumer behavior. A big part of this research involves bringing in new ideas from our fellow peers in the world of academia. As such, we have invited these four guest speakers below to share with us some of the research that they have been working on.

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AI Algorithms and Rising Concerns of Racial Biases: An Analysis of Airbnb’s Smart Pricing Algorithm

Nitin Mehta, Professor, Rotman School of Business, University of Toronto

Synopsis 

AI algorithms have sparked concerns that they might produce outcomes that perpetuate or exacerbate existing racial biases. We examine the implementation of Airbnb’s smart-pricing algorithm and derive market implications across different ethnic groups of Airbnb hosts who adopted it. After its introduction, the revenue gap between white and black hosts further increased by 16.4% suggesting that the algorithm exacerbated existing racial biases. However, this result is unconditional on its adoption. Conditional on its adoption, the revenue gap decreased by 57.2%, which shows that it can substantially mitigate racial biases, but the challenge is to enhance its adoption among black hosts. The reason why the algorithm helped black hosts more than white hosts is because while the magnitude of the price correction by the algorithm was the same across black and white hosts, the rental-demand for black hosts is more responsive to price changes. 

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Combating Fake News: A Consumer Psychology Perspective 

Gita Johar, Professor, Columbia Business School

Synopsis 

An increasing proliferation of misinformation and “fake news” has been widely reported and documented. Reality is now under attack from advertising-optimized information architectures mediating our contemporary reality and disinformation campaigns proliferate on online forums and social media. My research program aims to answer questions regarding why we believe and share fake news and how to prevent or correct inaccurate beliefs. In a recent paper titled “Perceived Social Presence Reduces Fact-Checking” (Proceedings of the National Academy of Science 2017), we find that consumers are less likely to fact check ambiguous news headlines when they feel they are in the presence of others compared to when they are alone. We find that this reluctance to fact check is caused by reduced vigilance in group settings such as social media. In a series of follow-up research projects, I am designing interventions such as direct debunking as well as subtle flagging of news headlines and testing their impact on message scrutiny. We find mixed evidence for the efficacy of these interventions. We also find that increasing message skepticism and scrutiny can have unintended spillover consequences in terms of reduced trust in brands advertised on these social platforms. In another research project, I address the issue of fake news from a different perspective and examine sharers of fake news. Who are they, and what motivates them to share fake news? We contrast fake news sharers, fact-check sharers, sharers of news articles from general media outlets and a random sample of social media users across five dimensions--demographics, political ideology, social media usage, emotions and personality. We access these characteristics by collecting their personal information as posted on Twitter as well as the content of their tweets. Fake news sharers differ from the other groups on multiple characteristics, but they also show similarities to fact check users on their emotional profile. Our findings can help social platforms to screen, prioritize and scrutinize messages posted by potential fake news sharers before false messages are widely disseminated. Taken together, this research program aims to guide policy discussions on how to combat the spread of fake news.

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A Model of Smart Technologies

Monica Sun, Associate Professor, Questrom School of Business, Boston University

Pending Synopsis

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Reconciling Cocreation Logics through Institutional Work

Albert Muniz, Professor, Driehaus College of Business, DePaul University

Synopsis

Corporations recognize the strategic advantages of harnessing user ingenuity; however, beyond cases of successful, narrowly scoped and/or temporally limited collaborations, little is known about what undergirds enduring cocreation. We assert that the extant literature on cocreation reveals two operating institutional logics: market and community. We evidence a profound cleavage between these logics in the marketplace which feeds into a similar institutional chasm in academic literature. Utilizing the construct of ideal types, we distinguish market and community cocreation logics and discover that within both, participants quest for mastery and affiliation. Toward a more comprehensive understanding of prolonged multi-stakeholder cocreation, we study reconciliation of divergent stakeholder perspectives on cocreation within the LEGO Ideas cocreation platform. We find that users thwarted in mastery and affiliation, utilize exit, voice and loyalty to assert their agency within cocreation initiatives. Likewise, firms looking for sustainable cocreation cannot take consumer mastery and affiliation for granted and must recognize the gap in logics from the outset, and be willing to engage in institutional work towards a unified logic.