SPEAKER

Prof. Alok R. Saboo
Taylor E. Little Jr. Professor of Marketing
J. Mack Robinson College of Business
Georgia State University

ABSTRACT

Climate change is one of the most important sociopolitical issues. Disclosures have emerged as a prominent tool for firms to participate in climate discussions and respond to the increasing pressure from multiple stakeholders to get involved in mitigating climate challenges. However, the impact of climate disclosures on organizational outcomes is unclear, reducing their uptake. Using the context of IPO firms, the authors propose a nonlinear relationship between disclosure volume and firm performance. The authors argue that lower climate disclosures only amplify the overall risk. In contrast, the benefits of information, stewardship, and climate-friendly reputation increase nonlinearly with increased disclosure volume and outweigh the risks associated with such disclosures, resulting in a U-shaped relationship. Further, the authors explore boundary conditions related to the sender (reputation of the firm and its underwriters) and message (optimism and clarity) characteristics. Using multi-sourced data from 1712 IPO firms, a state-of-the-art machine learning algorithm (BERT) to identify climate-related text from prospectuses, and robust econometric methods, the authors find support for their proposed U-shaped relationship. In addition, firm and underwriter reputation, message optimism, and clarity moderate (steepen) the curvilinear relationship between climate disclosures and firm performance.

SPEAKER

Dr. Yang Li
Associate Professor of Marketing
Executive Academic Director for MBA Program and Executive Education Programs
Cheung Kong Graduate School of Business

ABSTRACT

Contextual set-based personalized recommendations are important in many settings. For example, in the music industry playlists (i.e., sets of songs) are now the principal mechanism for music listening on digital streaming platforms. Given the large heterogeneity in musical tastes and the endless number of playlists that can be constructed, the automated design, completion, and recommendation of personalized playlists is critical. We develop a novel deep generative modeling framework to perform these tasks. We use interlocked Variational Hypergraph Auto-Encoders to uncover latent variables that summarize the musical themes and contextual moods associated with songs and playlists and the preferences of users. We fit our model on a data set of Spotify users’ playlists that we augmented with acoustic features and textual tags for the songs. Our application yields interesting insights about the diversity in musical preferences across users and contexts. We then use our model estimates to perform several managerial tasks such as similarity-based recommendations, complete existing playlists with congruent songs, and automatically design new playlists for personalized musical experiences.

SPEAKER

Professor Ayelet Gneezy
Carol Lazier and Family Endowed Chair in Social Innovation and Impact
Professor of Behavioral Sciences & Marketing, Rady School of Management
University of California San Diego

INTRODUCTION

In this talk, I will present findings from several projects investigating PWYW and other types of Consumer Elective Pricing (CEP).

In October 2007, Radiohead released its then-newest album for sale online, using pay-whatyou-want (PWYW) pricing: consumers were invited to download the album and pay as much or as little as they wished. An estimated 40% of downloaders paid something. Intrigued, I embarked on a journey (alongside my coauthors) dedicated to understanding what influences consumers’ decisions regarding whether to buy and how much to pay for a product or service they can receive for free.

In the first paper, we conducted a large-scale field experiment, collaborating with Disney research. In the experiment, we offered a product for sale, varying the price (fixed vs. PWYW) and whether payments benefited a charitable cause. Our data show that when PWYW is paired with a charitable cause, average payments increase dramatically—when half the revenue went to charity, Disney returned its most significant profit in addition to generating a generous charitable surplus (Gneezy et al. 2010).

Probing deeper into the factors affecting behavior under PWYW, we find that purchase likelihood decreases substantially under PWYW pricing compared to when a product is offered for a fixed low price. We argue that choosing whether to purchase a product or service and how much to pay for it has a self-signaling value. People feel bad when violating the norm, and thus, to avoid risking doing so, they choose not to buy (Gneezy et al. 2012). Consistent with the proposed role of signaling, we find that people are insensitive to the percentage of payments allocated to the cause: a 1% charitable contribution meaningfully changes behavior but moving from 1% to 100% has very little effect (Jung et al. 2017). Finally, data obtained in a series of field experiments suggest that replacing the word ‘Want” with “Can” significantly increases payments, arguably by shifting consumers’ focus away from self-interest motives (Saccardo et al. 2021).

Finally, because the “right” price is often inherently ambiguous, knowing what others pay could be helpful for the consumer trying to decide how much to pay. However, because this information is often unavailable, people likely make guesses that serve as a descriptive norm. If people assume others are generous, that descriptive norm may induce more generosity. Comparing payments under two financially identical CEP offers using PWYW and Pay-it-Forward. Results show people pay more under pay-it-forward, and this effect is driven by perceptions of others’ kindness (Jung et al. 2014).

SPEAKER

Ms. Lingrui (Ling-Ling) Zhou
Ph.D. Candidate in Marketing
Fuqua School of Business
Duke University

ABSTRACT

Brands often find themselves on the receiving end of negative public feedback from a variety of sources, such as consumers, industry experts, or competitors. Sometimes this feedback can even become insulting or derogatory and has a negative impact on firm success. Typically, brands respond to such degradation by rejecting the insult or ignoring it. This research explores a third strategy: reappropriating the insult. We reveal that reappropriation—an act of intentional self-labeling with an externally-imposed derogatory label—can garner unexpected benefits for brands. Six experiments, including a Facebook advertising field experiment, demonstrate that consumers who witness a brand reappropriate an insult have more positive attitudes towards and more interest in the brand. The advantage of reappropriation is driven by perceptions of mental toughness and specific to situations in which the reappropriated insult is nonmoral in nature and is not perceived to be clearly justified. This work contributes to our understanding of how brands can recover from negative events and provides practical insights for brand managers facing certain types of hostility.

SPEAKER

Ms. Emily Prinsloo
Ph.D. Candidate in Marketing
Harvard Business School
Harvard University

ABSTRACT

Seven preregistered studies (N = 2,890) conducted in the field, lab, and online document opportunity neglect: a tendency to reject opportunities with low probability of success, even when they come with little or no objective cost (e.g., time, money, reputation). In Study 1, participants rejected a low-probability opportunity in an everyday context. Participants also rejected incentive-compatible gambles with positive expected value–for both goods (Study 2), and money (Studies 3-7)–even with no possibility of monetary loss and non-trivial stakes (e.g., a 1% chance at $99). Participants rejected low-probability opportunities more frequently than high-probability opportunities with equal expected value (Study 3). While taking some real-life opportunities comes with costs, we show that people are even willing to incur costs to opt out of low-probability opportunities (Study 4). Opportunity neglect can be mitigated by highlighting that rejecting an opportunity is equivalent to choosing a zero probability of success (Studies 6-7).

SPEAKER

Mr. Yingkang Xie
Ph.D. Candidate in Marketing
Kellogg School of Management
Northwestern University

ABSTRACT

Leakage happens when buyers and sellers coordinate outside the platform to cut out the middleman, usually to avoid paying fees. Although platforms are concerned about losing revenue, leakage—by its very nature—is hard to measure and manage. Using geolocation data from a large on-demand service platform for cargo delivery, we identify offline transactions that are typically hard to track in online marketplaces. We exploit a quasi-experiment that gradually introduced driver commissions, thereby generating variation in participants’ incentives for leakage. The introduction of this commission increased leakage by nearly four percentage points, doubling the percentage of offline transactions we detected. We leverage the variation in commission fees to estimate price sensitivities and transaction costs in a structural model. The likelihood of leakage increases as the quoted price of the delivery increases, as the drivers’ potential savings in the commission exceed the costs of offline coordination. Our model estimates suggest that customers typically receive half of the commission savings from drivers to rationalize their agreement to leakage. Counterfactuals show that a stronger bargaining power of customers would exacerbate platform leakage. To conclude, we discuss how targeting coupons, monitoring technology, and strategic matching policy can mitigate leakage by aligning incentives, which are alternatives to ex-post punishments.

SPEAKER

Ms. Lingrui (Ling-Ling) Zhou
Ph.D. Candidate in Marketing
Fuqua School of Business
Duke University

ABSTRACT

With the current digital age and the rise of fan culture, consumers are privy to a wide variety of content from media figures (e.g., celebrities, content creators, athletes, influencers). We focus on investigating the effects of observing positive interactions between media figures on consumer perceptions. Using qualitative data, secondary field data, and experimental studies, we demonstrate that consumers enjoy viewing positive interactions between media figures and that viewing these interactions increase interest in and attitudes towards the focal media figure. This effect is driven by the mechanistic humanization of the media figure, such that these positive interactions allow the media figure to seem more human and relatable to the consumer, which then leads to other positive downstream consequences for the media figure.

SPEAKER

Ms. Xinyao Kong
Ph.D. Candidate in Marketing
Booth School of Business
The University of Chicago

ABSTRACT

This paper studies heterogeneity in consumer myopia and its role in creating a gap in financing cost across consumers in consumer credit markets. Using a unique data set of the US automobile and auto loan market, I find that consumers in the lowest income quartile tend to pay more for auto financing. In particular, they are less likely to accelerate car purchases with an interest rate hike in sight, acting as more myopic agents. I build a structural model to test and quantify the extent to which the financing gap arises from myopia, as opposed to differences in price sensitivities and automobile preferences. I find  that consumers are considerably more impatient than would be implied by the real rate of interest, and socio-economically disadvantaged consumers are more myopic and more price sensitive. A decomposition analysis quantifies the amount myopia contributes to the predicted financing gap. Counterfactual analysis further shows that strategic dealers may exacerbate the financing gap by gaining market power from more myopic consumers.

SPEAKER

Ms. Xiuyi (Sherry) He
Ph.D. Candidate in Marketing
UCLA Anderson School of Management
University of California, Los Angeles

ABSTRACT

I study how rating system design affects innovation incentives. In settings in which product quality cannot be observed prior to purchase, online ratings serve as a signal of product quality for consumers and affect demand. Owing to their impact on sales, ratings also motivate firms to innovate. If firms use displayed ratings to guide their investments in improving product quality, then platform rating aggregation policies can play a key role in increasing or decreasing firms’ innovation incentives. I study the impact of online rating systems on innovation incentives and, more importantly, the implications of the design of the rating aggregation policy. After collecting a unique firm-level dataset from a mobile game app platform, I combined reduced-form analysis and a structural model to show how rating systems can be optimized for innovation. I show that innovation has a positive impact on all key rating system metrics and that a lower rating significantly increases innovation incentives. Building on empirical evidence, I develop a dynamic structural model to represent firms’ forward-looking behavior and estimate innovation cost. I then evaluate the impact of alternative rating aggregation policies on innovation incentives. The counterfactual analysis shows that placing greater weight on recent ratings can increase the innovation rate substantially.

SPEAKER

Prof. Haitao (Tony) Cui
Ecolab-Pierson M. Grieve Chair In International Marketing
University of Minnesota

ABSTRACT

We analyzed 254 target documents published in five UTD 24 academic journals between 2000 and 2020, as well as their 8,567 cited and 5,076 quoting references, to examine how scholars collaborated and how behavioral operations management (BOM) study themes evolved. In particular, we examine the coauthor network to determine how author collaboration has evolved over time and what research subjects have been pursued. Our findings indicate that there exists a significant co-authorship networking impact, and that academic relationships play an important role in the co-authorship network. Also investigated is the flow of newly discovered knowledge from fundamental disciplines such as economics and psychology to applied disciplines such as marketing and operations, as well as the flow in the opposite direction, which provides crucial insight into the likely future direction of BOM research. In addition, the results demonstrate that the most investigated study themes in the early years differed significantly from those in recent years.

Besides sharing the above on-going research project, Dr. Cui will also share some ideas about how to generate research ideas, mainly for graduate students and/or young scholars who are in the early stage of pursuing appropriate research topics.