The heterogeneity of shoppers’ supermarket behaviors based on the use of carrying equipment

Nils Magne Larsen · Valdimar Sigurðsson · Jørgen Breivik · Jacob Lund Orquin

38 citations0/0 files storedJournal of Business Research

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Consumer Retail Behavior Studies Consumer Market Behavior and Pricing Evacuation and Crowd Dynamics

Abstract

Research on in-store behavior has largely focused on shoppers with carts. In a study involving 15 stores and a total of 3540 shoppers, we document that only 20 percent of shoppers actually use shopping carts, while 28 percent use baskets and 51 percent use no carrying equipment. To better understand the role of carrying equipment, we collected data in a second study from 635 complete shopping trips using behavioral tracking technology and systematic sampling. We show that there is important heterogeneity in in-store behavior related to equipment and that carrying equipment is a suitable variable for segmenting shoppers. It is an objective and observable measure that consistently explains the variance in travel distance, shopping duration, store area coverage, walking speed, basket size, and shopper efficiency. We also find non-equipment trips to be least efficient, despite their popularity. The findings have implications for both research and retail practices.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 38 citations exist upstream.

References

1987External Search Effort: An Investigation Across Several Product Categories 2001Why we buy: the science of shopping 2017Shopper-Facing Retail Technology: A Retailer Adoption Decision Framework Incorporating Shopper Attitudes and Privacy Concerns 1967Customer Impulse Purchasing Behavior 2009The Interplay among Category Characteristics, Customer Characteristics, and Customer Activities on in-Store Decision Making 2007Review of Marketing Research 2005An exploratory look at supermarket shopping paths 2013The Effect of In-Store Travel Distance on Unplanned Spending: Applications to Mobile Promotion Strategies

Cited by

2022When AI meets store layout design: a review 2023How in-store sensor technologies can help retailers to understand their customers: overview on two decades of research 2021Combining sell-out data with shopper behaviour data for category performance measurement: The role of category conversion power 2019The marketing firm: Retailer and consumer contingencies 2023The dark side of multiunit discounts: Multiunit discounts reduce rest of basket revenue

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.