Sitemap
A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
Pages
Posts
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Blog Post number 1
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publications
Measuring Long-Run Marketing Effects and Their Implications for Long-Run Marketing Decisions
This paper is about measuring the long-run effects of marketing actions and their strategic implications.
Citation: Bronnenberg, B., Dubé, J. P., Mela, C., Albuquerque, P., Erdem, T., Gordon, B. R., Hanssens, D., Hitsch, G., Hong, H., & Sun, B. (2008). "Measuring Long-Run Marketing Effects and Their Implications for Long-Run Marketing Decisions." Marketing Letters. 19, 367-382.
A Dynamic Model of Consumer Replacement Cycles in the PC Processor Industry
This paper develops and estimates a dynamic model of consumer purchase timing decisions in the market for personal computer (PC) microprocessors.
Citation: Gordon, B. R. (2009). "A Dynamic Model of Consumer Replacement Cycles in the PC Processor Industry." Marketing Science. 28(5), 846-867.
Drs. Muth and Mills Meet Dr. Tiebout: Integrating Location-Specific Amenities into Multi-Community Equilibrium Models
This article analyzes and compares two alternative approaches of incorporating location-specific amenities in equilibrium models of local jurisdictions.
Citation: Epple, D., Gordon, B. R., & Sieg, H. (2010). "Drs. Muth and Mills meet Dr. Tiebout: Integrating Location-Specific Amenities into Multi-Community Equilibrium Models." Journal of Regional Science. 50(1), 381-400.
A New Approach to Estimating the Production Function for Housing
This paper develops a new approach to estimating the production function for housing.
Citation: Epple, D., Gordon, B. R., & Sieg, H. (2010). "A New Approach to Estimating the Production Function for Housing." American Economic Review. 100(3), 905-924.
Revisiting the Workshop on Quantitative Marketing and Structural Econometrics
This article reflects on the history and contributions of the Workshop on Quantitative Marketing and Structural Econometrics (QMSE).
Citation: Gordon, B. R., Thomadsen, R., Bradlow, E. T., Dubé, J. P., & Staelin, R. (2011). "Revisiting the Workshop on Quantitative Marketing and Structural Econometrics." Marketing Science. 30(6), 945-949.
Competitive Strategy for Open Source Software
This paper develops a game-theoretic model to study the competitive interaction between a commercial software vendor and an open source software (OSS) community.
Citation: Kumar, V., Gordon, B. R., & Srinivasan, K. (2011). "Competitive Strategy for Open Source Software." Marketing Science. 30(6), 1066-1078.
Does AMD Spur Intel to Innovate More?
We develop a dynamic equilibrium model of competition in the market for computer processors that allows for endogenous product innovation and quality-contingent consumer adoption.
Citation: Goettler, R. L. & Gordon, B. R. (2011). "Does AMD spur Intel to innovate more?." Journal of Political Economy. 119(6), 1141-1200.
Download Paper | Preprint (PDF)
Marketing and Politics: Models, Behavior, and Policy Implications
This essay discusses the intersection of marketing and political science, highlighting how marketing models and frameworks can be applied to understand political phenomena.
Citation: Gordon, B. R., Lovett, M., Shachar, R., Arceneaux, K., Moorthy, S., Peress, M., Rao, A., Sen, S., Soberman, D., & Urminsky, O. (2012). "Marketing and Politics: Models, Behavior, and Policy Implications." Marketing Letters. 23(2), 391-403.
Advertising Effects in Presidential Elections
This paper investigates the effects of television advertising in presidential elections.
Citation: Gordon, B. R. & Hartmann, W. (2013). "Advertising Effects in Presidential Elections." Marketing Science. 32(1), 19-35.
Does Price Elasticity Vary with Economic Growth? A Cross-Category Analysis
This study investigates how consumer price sensitivity for consumer packaged goods changes over the business cycle.
Citation: Gordon, B. R., Goldfarb, A., & Li, Y. (2013). "Does Price Elasticity Vary with Economic Growth? A Cross-Category Analysis." Journal of Marketing Research. 50(1), 4-23.
Competition and Product Innovation in Dynamic Oligopoly
We develop and estimate a dynamic oligopoly model of competition in the market for computer processors.
Citation: Goettler, R. L. & Gordon, B. R. (2014). "Competition and Product Innovation in Dynamic Oligopoly." Quantitative Marketing and Economics. 12(1), 1-42.
A Dynamic Model of Rational Addiction: Evaluating Cigarette Taxes
This paper develops and estimates a dynamic model of cigarette consumption based on the theory of rational addiction.
Citation: Gordon, B. R. & Sun, B. (2015). "A Dynamic Model of Rational Addiction: Evaluating Cigarette Taxes." Marketing Science. 34(3), 452-470.
Multiplicity of Equilibria and Information Structures in Empirical Games: Challenges and Prospects
This article discusses the challenge of equilibrium multiplicity in the estimation of empirical games, particularly in marketing.
Citation: Borkovsky, R., Ellickson, P., Gordon, B. R., Aguirregabiria, V., Gardete, P., Grieco, P., Gureckis, T., Ho, T. H., Mathevet, L. & Sweeting, A. (2015). "Multiplicity of Equilibria and Information Structures in Empirical Games: Challenges and Prospects." Marketing Letters. 26(2), 115-125.
Advertising Competition in Presidential Elections
We study television advertising in recent U.S. presidential elections.
Citation: Gordon, B. R. & Hartmann, W. R. (2016). "Advertising Competition in Presidential Elections." Quantitative Marketing and Economics. 14(1), 1-40.
LETTER: Field studies of psychologically targeted ads face threats to internal validity
In their study, Matz et al. report the results of three field experiments that test the effectiveness of psychological targeting in digital advertising.
Citation: Eckles, D., Gordon, B. R., & Johnson, G. A. (2018). "LETTER: Field studies of psychologically targeted ads face threats to internal validity." Proceedings of the National Academy of Sciences. 115(23), E5254-E5255.
An Empirical Study of National vs. Local Pricing by Chain Stores under Competition
This paper empirically investigates the pricing strategies of national chain stores, focusing on the choice between uniform national pricing and flexible local pricing.
Citation: Li, Y., Gordon, B. R., & Netzer, O. (2018). "An Empirical Study of National vs. Local Pricing by Chain Stores under Competition." Marketing Science. 37(5), 812-837.
A Comparison of Approaches to Advertising Measurement: Evidence from Big Field Experiments at Facebook
Firms need to measure the return on their advertising investments.
Citation: Gordon, B. R., Zettelmeyer, F., Bhargava, N., & Chapsky, D. (2019). "A Comparison of Approaches to Advertising Measurement: Evidence from Big Field Experiments at Facebook." Marketing Science. 38(2), 193-225.
Inefficiencies in Digital Advertising Markets
Digital advertising is a large and rapidly growing industry, but there is growing concern about its efficiency.
Citation: Gordon, B. R., Jerath, K., Katona, Z., Narayanan, S., Shin, J., & Wilbur, K. C. (2021). "Inefficiencies in Digital Advertising Markets." Journal of Marketing. 85(1), 7-25.
Digitization and Flexibility: Evidence from the South Korean Movie Market
This paper studies how digitization affects the flexibility of firms’ product assortment and pricing decisions.
Citation: Yang, J., Anderson, E. T., & Gordon, B. R. (2021). "Digitization and Flexibility: Evidence from the South Korean Movie Market." Marketing Science. 40(5), 821-843.
Disentangling Ad Tone Effects on Voter Turnout and Candidate Choice in Presidential Elections
A long-standing debate in political science concerns the effects of negative advertising.
Citation: Gordon, B. R., Lovett, M. J., Luo, B., & Reeder, J. C. (2023). "Disentangling Ad Tone Effects on Voter Turnout and Candidate Choice in Presidential Elections." Management Science. 69(1), 220-243.
Close Enough? A Large-Scale Exploration of Non-experimental Approaches to Advertising Measurement
Randomized controlled trials (RCTs) are the gold standard for measuring advertising effectiveness, but they can be costly and difficult to implement.
Citation: Gordon, B. R., Moakler, R., & Zettelmeyer, F. (2023). "Close Enough? A Large-Scale Exploration of Non-experimental Approaches to Advertising Measurement." Marketing Science. 42(4), 768-793.
Predictive Incrementality by Experimentation (PIE) for Ad Measurement
The measurement of advertising effectiveness is a central problem in marketing.
Citation: Gordon, B. R., Moakler, R., & Zettelmeyer, F. (2023). "Predictive Incrementality by Experimentation (PIE) for Ad Measurement." arXiv preprint arXiv:2304.06828.
Multicell experiments for marginal treatment effect estimation of digital ads
The average treatment effect (ATE) from an A/B test is the standard for measuring the causal impact of an intervention such as an ad campaign.
Citation: Waisman, C. & Gordon, B. R. (2024). "Multicell experiments for marginal treatment effect estimation of digital ads." Management Science. (forthcoming).
Download Paper | Preprint (PDF)
Personalization and Targeting: How to Experiment, Learn & Optimize
Personalization and targeting are key strategies in modern marketing, aiming to enhance customer engagement and firm performance by tailoring marketing actions to individual customer needs and characteristics.
Citation: Lemmens, A., Roos, J., Gabel, S., Ascarza, E., Bruno, H., Gordon, B. R., Israeli, A., Feit, E. M., Mela, C., & Netzer, O. (2025). "Personalization and Targeting: How to Experiment, Learn & Optimize." International Journal of Research in Marketing, forthcoming.
teaching
Retail Analytics and Pricing (MKTG-462-0)
MBA course, Kellogg School of Management, 1900
This course will teach you how to use analytics and data to address decisions faced by retailers and manufacturers. Pricing and promotion decisions are emphasized, with additional coverage on topics such as private labels, product assortment, trade funding, shopper marketing, and more. The course is organized around a hierarchy of topics. We spend roughly one week understanding pricing and promoting to an individual customer. This analysis provides the foundation as we move to more aggregate decisions, such as setting regular and promoted prices at the product level, managing category pricing, and understanding the drivers of store traffic. As we progress through this hierarchy of decisions, we illustrate how different types of data can—or can’t—be used to answer managerial questions. A key part of the class is understanding the limitations of different types of data and how better planning can both simplify the analytics and increase your confidence in the findings. This class is very practical and hands-on. Most of the data we analyze is from real-world managerial problems, through collaborations with leading retailers and consulting firms who have brought problem-driven challenges to the classroom. Weekly homework assignments, both individual and group, are paired with in-class cases. There is no final exam.