A multi-method approach to examining consumer intentions to use smart retail technology

Journal article


Fazal-e-Hasan, Syed Muhammad, Amrollahi, Alireza, Mortimer, Gary, Adapa, Sujana and Balaji, M. S.. (2021). A multi-method approach to examining consumer intentions to use smart retail technology. Computers in Human Behavior. 117, p. 106622. https://doi.org/10.1016/j.chb.2020.106622
AuthorsFazal-e-Hasan, Syed Muhammad, Amrollahi, Alireza, Mortimer, Gary, Adapa, Sujana and Balaji, M. S.
Abstract

This study examines the antecedents and consequences of customers' intentions to use smart retail technology (SRT), specifically Smart Retail Carts. We propose that perceived novelty, perceived efficacy, perceived compatibility, and perceived risk of SRT determine consumers' intentions to use SRT, which, in turn, influences their shopping value through and interaction with this SRT. Survey responses from 338 actual shoppers with prior experience of SRT were used to test the research model. In addition to structural equation modeling (SEM), the Fuzzy-Set Qualitative Comparative Analysis (fsQCA) technique was used to analyze the data. SEM analysis enabled us to investigate and hypothesize relationships among the above factors, while fsQCA helped develop configurations of factors and find the appropriate target consumers of SRT. The findings posit perceived novelty, perceived efficacy, perceived compatibility, and perceived risk of SRT as antecedents to, and shopping value through SRT and interaction with SRT as consequences of, customers' intentions to use SRT. Moreover, the study found configurations of factors, such as perceived novelty and perceived compatibility, resulted in improved intention to use this form of SRT. The present study offers a better understanding of consumers' intentions to adopt SRT that may help managers to develop adoption strategies for successful implementation of SRT in-store.

Keywordsinnovativeness; value; loyalty; intentions to adopt; fsQCA
Year2021
JournalComputers in Human Behavior
Journal citation117, p. 106622
PublisherElsevier Ltd
ISSN0747-5632
Digital Object Identifier (DOI)https://doi.org/10.1016/j.chb.2020.106622
Scopus EID2-s2.0-85097089769
Research or scholarlyResearch
Page range1-11
Publisher's version
License
All rights reserved
File Access Level
Controlled
Output statusPublished
Publication dates
Print12 Nov 2020
Publication process dates
Accepted04 Nov 2020
Deposited26 Aug 2021
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