Pet-owner synchrony: Operationalization, application, and implications

Abstract Despite the pet industry’s significant economic and social importance, academic attention to this sector of the economy has been limited. Rather than focusing solely on the household demographics of pet ownership or the attitudinal components of the pet-owner relationship, we explore actual purchase decisions of pet owners. In this study, we examine pet-owner synchrony, a behavioral operationalization of pet-owner relationships that is grounded in attachment theory, anthropomorphism, and the extended self. Utilizing scanner data from 875,853 market baskets including 23 million transactions collected from a regional supermarket chain, we analyze cross-category co-occurrence patterns within shopping baskets. Our analysis reveals affinities, or parallels, in pet owners’ purchases of health and wellness products and hedonic products for both themselves and their pets, which we attribute to pet-owner synchrony. We identify two moderators that influence the strength of pet-owner synchrony: pet type (cat versus dog) and the presence of young children in the household. In addition, we evaluate how basket size, holidays, and price elasticities impact pet-owner synchrony. Our findings deliver useful insights into pet-owner relationships, have direct implications for retail and manufacturing managers, and yield recommendations for public policy.

Authors

Institutions

Publication Details

Journal
Journal of the Academy of Marketing Science
Published
2026-10-15
DOI
https://doi.org/10.1007/s11747-026-01214-9
Primary Topic
Consumer Market Behavior and Pricing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Pet-owner synchrony: Operationalization, application, and implications

Mayukh Dass, Sunhee Choi, Wesley Friske
Journal of the Academy of Marketing Science
Consumer Market Behavior and Pricing
article

Pet-owner synchrony: Operationalization, application, and implications

Mayukh Dass, Sunhee Choi, Wesley Friske
article en

Abstract

Abstract Despite the pet industry’s significant economic and social importance, academic attention to this sector of the economy has been limited. Rather than focusing solely on the household demographics of pet ownership or the attitudinal components of the pet-owner relationship, we explore actual purchase decisions of pet owners. In this study, we examine pet-owner synchrony, a behavioral operationalization of pet-owner relationships that is grounded in attachment theory, anthropomorphism, and the extended self. Utilizing scanner data from 875,853 market baskets including 23 million transactions collected from a regional supermarket chain, we analyze cross-category co-occurrence patterns within shopping baskets. Our analysis reveals affinities, or parallels, in pet owners’ purchases of health and wellness products and hedonic products for both themselves and their pets, which we attribute to pet-owner synchrony. We identify two moderators that influence the strength of pet-owner synchrony: pet type (cat versus dog) and the presence of young children in the household. In addition, we evaluate how basket size, holidays, and price elasticities impact pet-owner synchrony. Our findings deliver useful insights into pet-owner relationships, have direct implications for retail and manufacturing managers, and yield recommendations for public policy.

Journal of the Academy of Marketing Science
Missouri State University (US), Texas Tech University (US), Shippensburg University (US)
Openalex Percentile: Top 7%
Consumer Market Behavior and Pricing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.