JMR Updates – Dec 2024
Introduction
How I Wrote This and more from the Journal of Marketing Research
INTEREST CATEGORY: MARKETING RESEARCH
POSTING TYPE: Journal News
Posted by: Rebecca Hamilton
JMR Updates – December 2024
Special Issue: New Methods for the Future of Marketing
Technological advances have opened up new opportunities for marketers to create and capture value; for consumers to engage with products, services, organizations and each other; for marketing researchers to combine data across modalities and touchpoints. In this , we will publish papers testing new and improved methods for the future of marketing. These methods may collect insights from new sources, analyze new or existing data in new ways, combine data from multiple sources or multiple media, improve on existing methods by analyzing data more accurately or efficiently. See our for more ideas.
Do Switching Costs Make Markets Less Competitive? Find out in “How I Wrote This” Episode 14
In , JMR Co-Editor sits down with and from the University of Chicago Booth School of Business and from the UCLA Anderson School of Management. They discuss their influential paper, ? Since the 1960s, marketing and economics scholars have studied switching costs, with theoretical literature largely suggesting that these costs lead to higher prices among competing firms. However, when these three researchers conducted an empirical analysis, they found surprising results that challenged the prevailing wisdom. Join them as they share how their project evolved over time, including their measured response to critical feedback and how they expanded their initial scope of inquiry.
Listen on , , or wherever you get your podcasts.
Strategies for Causal Inference with Quasi-Experimental Data
In this of , , and provide guidance to researchers for choosing appropriate methods for understanding causal relationships from observational data. First, they provide an overview of design choices in quasi-experimental settings based on characteristics of the data, such as the number of pre-treatment periods and availability of covariates. Next, they discuss the fit of various methods, including difference-in-differences, synthetic control, and matching, to data with different characteristics. Learn more in their !