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The Pricing Strategies of Online Grocery Retailers

Author

Listed:
  • Diego Aparicio
  • Zachary Metzman
  • Roberto Rigobon

Abstract

Matched product data is collected from the leading online grocers in the U.S. The same exact products are identified in scanner data. The paper documents pricing strategies within and across online (and offline) retailers. First, online retailers exhibit substantially less uniform pricing than offline retailers. Second, online price differentiation across competing chains in narrow geographies is higher than offline retailers. Third, variation in offline elasticities, shipping distance, pricing frequency, and local demo- graphics are utilized to explain price differentiation. Surprisingly, pricing technology (across time) magnifies price differentiation (across locations). This evidence motivates a high-frequency study to unpack the patterns of algorithmic pricing. The data shows that algorithms: personalize prices at the delivery zipcode level, update prices very frequently and in tiny magnitudes, reduce price synchronization, exhibit lower menu costs, constantly explore the price grid, and often match competitors’ prices.

Suggested Citation

  • Diego Aparicio & Zachary Metzman & Roberto Rigobon, 2021. "The Pricing Strategies of Online Grocery Retailers," NBER Working Papers 28639, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:28639
    Note: IFM IO ITI ME
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    Citations

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    Cited by:

    1. Vladimir Fedoseev & Svetlana Fedoseeva, 2022. "Same DNA, same location, same price? Price differences across distribution e‐channels of a single online retailer," Agribusiness, John Wiley & Sons, Ltd., vol. 38(4), pages 874-884, October.
    2. Jung, Jinho & Kim, Yong J. & Kim, Sanghyo, 2022. "Sales-Weighted Online Agricultural Commodity Price Index: Using Sales and Price Data web-scraped from Online Grocery Stores in South Korea," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322525, Agricultural and Applied Economics Association.
    3. Strasser, Georg & Wieland, Elisabeth & Macias, Paweł & Błażejowska, Aneta & Szafranek, Karol & Wittekopf, David & Franke, Jörn & Henkel, Lukas & Osbat, Chiara, 2023. "E-commerce and price setting: evidence from Europe," Occasional Paper Series 320, European Central Bank.
    4. Sullivan, Tom, 2022. "Price dispersion in the rideshare industry : a study of the Mexico City market," Warwick-Monash Economics Student Papers 40, Warwick Monash Economics Student Papers.
    5. John Asker & Chaim Fershtman & Ariel Pakes, 2024. "The impact of artificial intelligence design on pricing," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 33(2), pages 276-304, March.
    6. Kooli, Maher & Zhang, Aoran & Zhao, Yunfei, 2022. "How IPO firms' product innovation strategy affects the likelihood of post-IPO acquisitions?," Journal of Corporate Finance, Elsevier, vol. 72(C).
    7. Rhodes, Andrew & Zhou, Jidong, 2022. "Personalized Pricing and Competition," TSE Working Papers 22-1333, Toulouse School of Economics (TSE), revised Mar 2024.
    8. Macias, Paweł & Stelmasiak, Damian & Szafranek, Karol, 2023. "Nowcasting food inflation with a massive amount of online prices," International Journal of Forecasting, Elsevier, vol. 39(2), pages 809-826.
    9. repec:ecb:ecbdps:202323 is not listed on IDEAS
    10. Aparicio, Diego & Rigobon, Roberto, 2023. "Quantum prices," Journal of International Economics, Elsevier, vol. 143(C).
    11. Huelden, Tobias & Jascisens, Vitalijs & Roemheld, Lars & Werner, Tobias, 2024. "Human-machine interactions in pricing: Evidence from two large-scale field experiments," DICE Discussion Papers 412, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
    12. Benjamin R. Shiller, 2022. "Discreet Personalized Pricing," CESifo Working Paper Series 10025, CESifo.
    13. Fiskara Indawan & Aryo Sasongko & Dian Rahmawati, 2023. "Price Setting Behavior In An Online Market," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 26(2), pages 192-220, May.
    14. Dedola, Luca & Ehrmann, Michael & Hoffmann, Peter & Lamo, Ana & Paz-Pardo, Gonzalo & Slacalek, Jiri & Strasser, Georg, 2023. "Digitalisation and the economy," Working Paper Series 2809, European Central Bank.
    15. Chen, I-Ju & Hsu, Po-Hsuan & Wang, Yanzhi, 2022. "Staggered boards and product innovations: Evidence from Massachusetts State Bill HB 5640," Research Policy, Elsevier, vol. 51(4).
    16. Diego Aparicio & Duncan Simester, 2022. "Price Frictions and the Success of New Products," Marketing Science, INFORMS, vol. 41(6), pages 1057-1073, November.

    More about this item

    JEL classification:

    • D9 - Microeconomics - - Micro-Based Behavioral Economics
    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
    • L2 - Industrial Organization - - Firm Objectives, Organization, and Behavior
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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