Research

The NRF Business of Retail Initiative at Georgetown University’s McDonough School of Business supports faculty-driven research that addresses critical challenges in the retail industry. Through close collaboration with retail partners, the initiative generates actionable insights, informs business practice, and contributes to the ongoing transformation of the retail sector.

Retail Traffic, Technology, and the Future of Promotion Measurement

Professor Ronald Goodstein

Key Finding: Tracking shopper arrival traffic gives retailers a more accurate measure of promotional success and helps optimize staffing, inventory, and operations.
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Brand Visibility and Marketing in the Age of AI

Professor Luc Wathieu

Key Finding: Brands with clear and consistent, digital information are more likely to be recommended by generative AI, making AI visibility a critical part of modern marketing strategy.
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Consumer Behavior using Product Customization

Professor Suh Yoeh Kim and Rebecca Hamilton

Key Finding: Product customization experiences encourage repeat customization and builds long-term customer value through increased spending and engagement.
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Published Papers

Consumer Behavior

Consumer Psychology (March 10, 2022) Zhongbin Wang, Luyi Yang, Shiliang Cui, Sezer Ülkü And Yong-pin Zhou. “Pooling Agents For Customer-intensive Services.” Operations Research (March 9, 2022). 

  • Key Finding: Pooling service agents improves response efficiency and customer satisfaction in high-demand services.

Shawn Mankad, Masha Shunko And Qiuping Yu. “Too Close For Comfort? Understanding Peer Effects In Large Franchised Networks.” SSRN Electronic Journal (August 26, 2021). 

  • Key Finding: Customers’ comfort and behavior are strongly shaped by those around them in large retail networks.

Retail Technology & AI

Yin, Mingzhang, Ziwei Cong, and Jia Liu. “Unraveling Multifaceted User Preferences on Digital Platforms: A Bayesian Deep-Learning Approach.” Forthcoming at Marketing Science (2026).

  • Key Finding: Retail and digital platforms can improve personalization and customer experience by using Bayesian deep learning to identify consumers evolving preferences.

Cinthia B. Satornino, Dhruv Grewal, Abhijit Guha, Elisa B. Schweiger And Ronald C. Goodstein. “The Perks And Perils Of Artificial Intelligence Use In Lateral Exchange Markets.” Journal Of Business Research, 158 (March 1, 2023): 113580. DOI: https://doi.org/10.1016/j.jbusres.2022.113580.

  • Key Finding: Artificial Intelligence can enhance retail-like marketplaces by improving search recommendations.

Pricing & Promotions

Chun, SoYeon and Rebecca W. Hamilton. “Should I Pay with Money or Redeem Points for This Purchase? Effects of Exchange Rate Stability on Loyalty Point Redemption.” Journal of Marketing Research, 61, 5 (October 2024): 858-871.

  • Key Finding: Consumers are more likely to redeem loyalty points when point-to-currency exchange rates are stable and predictable.

Chris Hydock and Luc Wathieu. “Not Just About Price: How Benefit Focus Determines Consumers’ Retailer Pricing Strategy Preference.” Journal of Consumer Research (August 1, 2023)

  • Key Finding: Consumers’ preferred pricing strategies depend on whether they focus more on monetary savings or other benefits, not just the price itself.

Service and Customer Experience 

Consumer Psychology (March 10, 2022) Zhongbin Wang, Luyi Yang, Shiliang Cui, Sezer Ülkü And Yong-pin Zhou. “Pooling Agents For Customer-intensive Services.” Operations Research (March 9, 2022). 

  • Key Finding: Pooling service agents improves response efficiency and customer satisfaction in high-demand services.

Shawn Mankad, Masha Shunko And Qiuping Yu. “Too Close For Comfort? Understanding Peer Effects In Large Franchised Networks.” SSRN Electronic Journal (August 26, 2021). 

  • Key Finding: Performance and operational decisions within franchise networks are influenced by nearby peer locations, creating measurable spillover effects.

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