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EMAC 2024 Annual


Unpacking Gender Disparities: Insights from Quantitative Marketing Research
(A2024-119032)

Published: May 28, 2024

AUTHORS

Andreas Bayerl, Erasmus School of Economics, Erasmus University; Ali Goli, University of Washington; Alisa Wu, Columbia University; Martina Pocchiari, Rotterdam School of Management, Erasmus University

ABSTRACT

The recent Nobel Prize in Economics recognized the study of gender differences in labor market outcomes. Yet, gender differences also affect consumer markets, offering insights for marketing, from gender-based segmentation success over evolving gender-specific needs to gender-specific behaviors. Our special session combines quantitative marketing research examining gender diversity and stereotypes in cable news and TV ads and investigates how men and women share experiences through text or online reviews. Using innovative methods and new data, we aim to advance our understanding of gender's role in marketing. The paper by Ali Goli and Simha Mummalaneni, “Gender Diversity on Cable News: An Analysis of On-Screen Talent and Viewership”, investigates the representation and impact of women (on viewership) in cable news in the United States. Focusing on three major networks (CNN, Fox News, and MSNBC) from 2010 to 2021, the research examines disparities in screen time and topical assignments between male and female talent, alongside the influence of gender representation on viewership. The paper by Alisa Wu and Vicki Morwitz, “Are Female Consumers Emotional? Understanding Gender Stereotypes in Online Reviews”, examines in a user-generated-content context, how gender stereotypes in general, and the belief that females are more emotional than males in particular, influences readers’ reactions to reviews as well as the manner in which review writers construct their reviews. This research calls for more inclusive online review system designs where all genders can express themselves without concern. The paper by Clément Bellet and Martina Pocchiari, “Gender Stereotypes and Advertising Effectiveness”, documents the evolution of gender-stereotyping in TV advertising in the United States using an exhaustive dataset of TV ads aired between 2010 and 2020, covering hundreds of brands across many product categories. Linking stereotypical ad content to brand-level sales, the paper discusses the extent from which stereotyping can benefit or hurt ad effectiveness. The paper by Andreas Bayerl, Yaniv Dover, Hila Riemer and Danny Shapira, “Gender rating gap in online reviews”, shows in 1.2 billion online reviews across several datasets covering a broad scope of contexts that women’s ratings are more favorable. This phenomenon of the gender rating gap is novel, and only recently, thanks to name-based demographic inference tools and Computer Vision, are we equipped with methods that allow us to extract users’ most likely gender and thus assess gender differences in online review ratings.