Marketing - HKU Business School

19 May

Brand Name Disfluency Effects

SPEAKER

Professor Shi Zhang
Associate Professor of Marketing
Anderson School of Management
University of California, Los Angeles

ABSTRACT

We study the established dual impact of brand name fluency, the positive effect of fluency and negative effect of disfluency, by challenging the findings and demonstrating positive effects of disfluency and their underlying mechanisms. We introduce an innovative method using the event-related potential (ERP) experimental paradigm to assess the brand name fluency/disfluency on product evaluations, capturing both behavioral responses and neural data. Further, we support the above lab findings with an online field study correlating brand name fluency/disfluency with actual product sales.

19 May

Caregiving And Consumption Sacrifice: How Caregiving Affects Choices For The Self

SPEAKER

Professor Peggy Liu
Ben L. Fryrear Professor of Marketing
Joseph M. Katz Graduate School of Business and College of Business Administration
University of Pittsburgh

ABSTRACT

Billions of consumers worldwide have caregiving responsibilities. In this talk, I will discuss my latest research on how caregiving affects choices for the self in key ways with well-being implications for caregivers. A central theme in my talk is the concept of “consumption sacrifice”—wherein caregiving prompts consumers to give up consumption choices that may best serve their own well-being. I will first briefly highlight our published research on whether, why, and when making healthy choices for one’s child leads parents to make different choices for themselves. Then, I will mainly present our latest in-progress research that examines whether, why, and when caregiving responsibilities, relative to other responsibilities, uniquely discourage leisure activities due to their perceived “time unboundedness.” Altogether, this work aims to develop a deeper theoretical understanding of how the prevalent act of caregiving shapes consumers’ choices for the self, with the aim of facilitating our understanding of theory-consistent interventions to support caregiver well-being.

19 May

Starbuck’s America vs. McDonald’s America: Political Polarization and Brand Iconicity

SPEAKER

Professor Carlos Torelli
Professor of Marketing
Department Head and Anthony J Petullo Professor of Business
Gies College of Business
The University of Illinois Urbana-Champaign

ABSTRACT

Which brands best symbolize America – brands like Walmart and McDonald’s or brands like Target and Starbucks? In this article, the authors demonstrate that what kinds of brands become icons depends on political ideology and that this association intensifies during highly polarized times. Results from six datasets reveal that conservatives uphold a more stratified/hierarchical society than liberals, and see brands as more iconic when they are aligned with these societal values. We focus on brands embodying horizontal values (e.g., equality, openness to change) and vertical values (e.g., social status, hierarchy, tradition) and show that conservatives (liberals) evaluate vertical (horizontal) brands as more iconic of America. These differences in brand iconicity result in stronger psychological connection with and commitment to ideologically aligned vertical vs. horizontal brands. Critically, these associations are amplified during highly polarized times in society, as evidenced by both individuals’ perceptions of polarization and objective societal political polarization measures. The findings suggest that political ideology provides a powerful lens through which people perceive society and brand iconicity. Our research contributes to understanding how brands become iconic, the effect of political polarization on divergent brand meanings, and the role of horizontal and vertical values in these perceptions.

08 May

Beyond Monetization: Heterogeneous Effects of Open Access as a Freemium Strategy for Public Good

SPEAKER

Professor Xian Gu
Assistant Professor of Marketing
Kelley School of Business
Indiana University

ABSTRACT

Open access (OA) provides free digital access to scholarly content without copyright restrictions, aiming to enhance knowledge visibility and accessibility. While increasingly adopted by OA platforms and publishers to broaden consumer reach, open access raises concerns about potential revenue loss and fairness, as its impacts on book downloads and sales may differ across authors and consumer groups in ways that are not yet fully understood. This research addresses these issues through a randomized field experiment with a leading digital platform for academic content. Approximately 1,400 book titles were randomly assigned to a control group (no OA) or a treatment group (OA). Despite concerns, we show that open access significantly increases book downloads without reducing book sales on average. However, open access disproportionately reduces sales for books by female authors and has divergent effects across consumers — decreasing sales in lower GDP areas while increasing them in wealthier, more educated regions. Analysis of individual treatment effects reveals substantial heterogeneity: about half of the books experience increased sales, while the other half see declines. Further investigation reveals that open access tends to increase sales for older or less popular books, suggesting that its impact varies based on a book’s existing market presence. Our findings suggest that open access can expand readership without reducing average revenue, offering platforms and publishers a sustainable model to broaden impact. To maximize benefits, platforms and publishers should adopt differentiated release strategies based on a book’s age and popularity and address equity concerns arising from heterogeneous effects across author and consumer socioeconomic backgrounds.

08 May

Racial Diversity Representation Improves Preference for Stigmatized Products

SPEAKER

Professor Julio Sevilla
L. Edmund Rast Chair of Business
Professor of Marketing
Terry College of Business
University of Georgia

ABSTRACT

Evidence for consumer preference toward racially diverse representation in marketing is mixed. One under-researched theme in this domain is how consumers respond to racially diverse representation in advertisements for stigmatized offerings (e.g., STD treatment, Alcoholics Anonymous). Empirical evidence across six laboratory-controlled studies (four preregistered, one in the web appendix, N = 4,420) and real in-market consumer response data indicates that the representation of mixed-race groups (versus White or minority only groups) delivers the best ad outcomes in the context of stigmatized (versus non-stigmatized) products. This effect is driven by enhanced perceptions of inclusion and brand expertise. In contrast to recent research on non-stigmatized products featuring romantic couples or employees, the present findings reveal that ads for stigmatized products benefit from mixed-race representation compared to monoracial representation (e.g., Black or White). This research holds important theoretical and managerial implications for how stigmatized products should be effectively marketed.

14 April

When Is Heterogeneity Actionable for Personalization?

SPEAKER

Professor Ron Berman
Associate Professor of Marketing
Graduate Group Chair, Marketing
The Wharton School
University of Pennsylvania

ABSTRACT

Targeting and personalization policies can be used to improve outcomes beyond the uniform policy that assigns the best performing treatment in an A/B test to everyone. Personalization relies on the presence of heterogeneity of treatment effects, yet, as we show in this paper, heterogeneity alone is not sufficient for personalization to be successful. We develop a statistical model to quantify “actionable heterogeneity,” or the conditions when personalization is likely to outperform the best uniform policy. We show that actionable heterogeneity can be visualized as crossover interactions in outcomes across treatments and depends on three population-level parameters: within-treatment heterogeneity, cross-treatment correlation, and the variation in average responses. Our model can be used to predict the expected gain from personalization prior to running an experiment and also allows for sensitivity analysis, providing guidance on how changing treatments can affect the personalization gain. To validate our model, we apply five common personalization approaches to two large-scale field experiments with many interventions that encouraged flu vaccination. We find an 18% gain from personalization in one and a more modest 4% gain in the other, which is consistent with our model. Counterfactual analysis shows that this difference in the gains from personalization is driven by a drastic difference in within-treatment heterogeneity. However, reducing cross-treatment correlation holds a larger potential to further increase personalization gains. Our findings provide a framework for assessing the potential from personalization and offer practical recommendations for improving gains from targeting in multi-intervention settings.

31 March

Ambiguity in digital advertising

SPEAKER

Professor Shunyuan Zhang
Assistant Professor of Business Administration
Marketing Unit
Harvard Business School
Harvard University

ABSTRACT

We explore the effect of digital ambiguous ads on consumers’ behavior throughout the purchase funnel, considering a multi-modal perspective of the display ad’s visual banner and its textual caption. Collaborating with a display ad platform, we first examine the consumers’ click-through rates (CTRs) for tens of thousands of cross-category digital ads. To operationalize ambiguity, we develop two custom deep learning-based ambiguity prediction models, each for one data modal. We find that beyond a rich set of ad characteristics (e.g., photographic attributes, language features, and image-text coherence), ambiguous ads receive higher click-through rates but lower conversion rates and efficiency. Next, to verify the causal links suggested in the field data, we conduct a pre-registered randomized field experiment, where we manipulate the amount of ambiguity of in a campaign. In particular, we create four versions of ads for a hearing-aid product with very similar images and texts, but different levels of ambiguity. Our analysis further reveals a negative impact of ad ambiguity on consumer conversion rate. Overall, our findings suggest that advertisers and scholars are well-advised to assess images and texts together rather than individually, and use ambiguity with care.

28 February

From Disposable to Reusable and Repairable: Interventions to Increase Sustainable Consumer Behavior

SPEAKER

Professor Karen Page Winterich
Gerald I. Susman Professor in Sustainability and Professor of Marketing
Smeal College of Business
The Pennsylvania State University

ABSTRACT

Just a few decades ago, we celebrated the invention of disposables, but today we recognize our disposable lifestyle is not sustainable. Though some consumers may want to consume more sustainably, they need interventions to overcome current unsustainable behavior. This research presents several tactics companies can implement to increase repair and reuse behavior as part of a circular economy. To increase repair, companies offer brand repair services that signal unused utility in broken products. In take-back programs, companies can increase repeat participation in recycling and reuse programs through acknowledgment. Not only can such initiatives increase sustainable behavior to benefit society at large, but they also benefit the brand, decreasing switching behavior and increasing company sustainability perceptions.

28 February

Measurement Invariance Across Conditions: A Case Study of Material and Experiential Happiness

SPEAKER

Professor Dan Schley
Associate Professor of Marketing
Rotterdam School of Management
Erasmus University

ABSTRACT

Experimentation is often called the strongest tool for defining causality in the proverbial scientific toolbelt. But, the claim of “causality” comes with the burden of many explicit and implicit experimental assumptions. In this research, I investigate the role of measurement invariance across experimental conditions – something implicitly assumed to hold, and as a consequence previously ignored in experimental research. When manipulating treatment X (e.g., watching funny versus neutral videos), that manipulation is assumed to cause a change in a relevant latent construct (e.g., happiness). This construct is then measured using some operationalized dependent variable (e.g., a 5-item happiness scale). If happiness in one condition is higher than in the other, we usually assume that to mean that the treatment caused happiness. That is true under the tacit assumption that the dependent variable is measuring the same construct in both conditions. Does, for example, a happiness scale measure the same latent factor of “happiness” after watching a funny video as it does after watching a neutral video? This may be the case in many instances, but need not always be true. In this talk I introduces the potential issues that occur if there is not measurement invariance across conditions and introduce some initial simulations for defining a test for measurement invariance across conditions. I will demonstrate the implications in the context of a recent hot topic in consumer research: the “experiential advantage” whereby consumers derive more “happiness” from consuming experiences compared to consuming material goods.

12 February

Platforms as Innovation Enablers: How Do Platform Support and Innovation Strategy Enhance App Performance?

SPEAKER

Professor Vanitha Swaminathan
Associate Dean for Research and Strategic Initiatives
Thomas Marshall Professor of Marketing
University of Pittsburgh

ABSTRACT

Digital platform businesses, such as mobile application markets, rely heavily on the success of platform complementors, such as app developers, for their growth. Innovation plays a crucial role in enabling complementors to thrive in hypercompetitive marketplaces. Existing research has identified various complementor strategies for achieving innovation success. However, studies focusing on understanding the role of platform support in facilitating innovation and how the interaction of such support with innovation strategies such as timing and benefit influences innovation outcomes are scarce. Drawing from research on platform ecosystems and the assemblage approach of digital platforms, the authors propose a platform support metric comprising complementor-related “technical guidance” and “developer community” factors. Using the adoption of augmented reality in mobile apps as an example context for innovation, they show that innovation timing and benefit have distinct impacts on app performance. They also find that greater platform support affects these innovation strategies differently. These findings offer novel insights into the value of platforms as facilitators of innovation and the underlying mechanisms for maximizing innovation outcomes.