The pricing strategies of online grocery retailers

Diego Aparicio (), Zachary Metzman () and Roberto Rigobon ()
Additional contact information
Diego Aparicio: IESE Business School
Zachary Metzman: MIT
Roberto Rigobon: MIT & NBER

Quantitative Marketing and Economics (QME), 2024, vol. 22, issue 1, No 1, 21 pages

Abstract: Abstract This paper documents the differences in pricing strategies between online and offline (brick-and-mortar) channels. We collect price data for identical products from leading online grocery retailers in the United States and complement it with offline data for the same products from scanner data. Our findings reveal a consistent pattern: online retailers exhibit higher price dispersion than their offline counterparts. More specifically, online grocers employ price algorithms that amplify price discrimination in three key dimensions: (1) over time (through frequent price changes), (2) across locations (by charging varying prices based on delivery zipcodes), and (3) across sellers (by setting dispersed prices for identical products across rival retailers).

Keywords: Algorithmic pricing; Price dispersion; Price discrimination; Online groceries; Scanner data; Amazon; Walmart (search for similar items in EconPapers)
JEL-codes: L1 L2 M3 O3 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11129-023-09273-w

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