Understanding the implementation of retail self-service check-out technologies using necessary condition analysis

Bibliographic Details
Main Author: Duarte, Paulo
Publication Date: 2022
Other Authors: Silva, Susana C., Linardi, Marcelo Augusto, Novais, Beatriz
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10400.14/38971
Summary: Purpose Self-service check-out technologies (SSTs) are becoming a trend across different retail settings, allowing companies to gain efficiency and reduce costs. Nevertheless, the success of SSTs implementation is still subject to challenges and uncertainties. This study aims to provide insights for theory and managers on the necessary conditions for the successful implementation of retail SSTs. Design/methodology/approach Based on an online survey, data from 251 participants were collected to understand the factors predicting SSTs adoption and realise what conditions are mandatory for the adoption. partial Least Squares Structural Equation Modelling (PLS-SEM) and necessary condition analysis (NCA) were used to analyse the data. Findings According to the NCA analysis results, 12 latent variables were relevant for predicting SSTs adoption, but only seven were necessary conditions for user adoption. Originality/value The complementarity of perspectives for understanding the adoption of SSTs based on the two data analysis techniques provides novel insights into theory and support for retailers' decision-making on self-service technologies (STTs) implementation.
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spelling Understanding the implementation of retail self-service check-out technologies using necessary condition analysisSelf-service technologyAdoptionRetailNCAOmnichannel strategyPurpose Self-service check-out technologies (SSTs) are becoming a trend across different retail settings, allowing companies to gain efficiency and reduce costs. Nevertheless, the success of SSTs implementation is still subject to challenges and uncertainties. This study aims to provide insights for theory and managers on the necessary conditions for the successful implementation of retail SSTs. Design/methodology/approach Based on an online survey, data from 251 participants were collected to understand the factors predicting SSTs adoption and realise what conditions are mandatory for the adoption. partial Least Squares Structural Equation Modelling (PLS-SEM) and necessary condition analysis (NCA) were used to analyse the data. Findings According to the NCA analysis results, 12 latent variables were relevant for predicting SSTs adoption, but only seven were necessary conditions for user adoption. Originality/value The complementarity of perspectives for understanding the adoption of SSTs based on the two data analysis techniques provides novel insights into theory and support for retailers' decision-making on self-service technologies (STTs) implementation.VeritatiDuarte, PauloSilva, Susana C.Linardi, Marcelo AugustoNovais, Beatriz2022-09-22T11:44:12Z2022-09-142022-09-14T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.14/38971eng0959-055210.1108/IJRDM-05-2022-0164info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-13T13:13:26Zoai:repositorio.ucp.pt:10400.14/38971Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T01:54:41.820477Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Understanding the implementation of retail self-service check-out technologies using necessary condition analysis
title Understanding the implementation of retail self-service check-out technologies using necessary condition analysis
spellingShingle Understanding the implementation of retail self-service check-out technologies using necessary condition analysis
Duarte, Paulo
Self-service technology
Adoption
Retail
NCA
Omnichannel strategy
title_short Understanding the implementation of retail self-service check-out technologies using necessary condition analysis
title_full Understanding the implementation of retail self-service check-out technologies using necessary condition analysis
title_fullStr Understanding the implementation of retail self-service check-out technologies using necessary condition analysis
title_full_unstemmed Understanding the implementation of retail self-service check-out technologies using necessary condition analysis
title_sort Understanding the implementation of retail self-service check-out technologies using necessary condition analysis
author Duarte, Paulo
author_facet Duarte, Paulo
Silva, Susana C.
Linardi, Marcelo Augusto
Novais, Beatriz
author_role author
author2 Silva, Susana C.
Linardi, Marcelo Augusto
Novais, Beatriz
author2_role author
author
author
dc.contributor.none.fl_str_mv Veritati
dc.contributor.author.fl_str_mv Duarte, Paulo
Silva, Susana C.
Linardi, Marcelo Augusto
Novais, Beatriz
dc.subject.por.fl_str_mv Self-service technology
Adoption
Retail
NCA
Omnichannel strategy
topic Self-service technology
Adoption
Retail
NCA
Omnichannel strategy
description Purpose Self-service check-out technologies (SSTs) are becoming a trend across different retail settings, allowing companies to gain efficiency and reduce costs. Nevertheless, the success of SSTs implementation is still subject to challenges and uncertainties. This study aims to provide insights for theory and managers on the necessary conditions for the successful implementation of retail SSTs. Design/methodology/approach Based on an online survey, data from 251 participants were collected to understand the factors predicting SSTs adoption and realise what conditions are mandatory for the adoption. partial Least Squares Structural Equation Modelling (PLS-SEM) and necessary condition analysis (NCA) were used to analyse the data. Findings According to the NCA analysis results, 12 latent variables were relevant for predicting SSTs adoption, but only seven were necessary conditions for user adoption. Originality/value The complementarity of perspectives for understanding the adoption of SSTs based on the two data analysis techniques provides novel insights into theory and support for retailers' decision-making on self-service technologies (STTs) implementation.
publishDate 2022
dc.date.none.fl_str_mv 2022-09-22T11:44:12Z
2022-09-14
2022-09-14T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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format article
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url http://hdl.handle.net/10400.14/38971
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0959-0552
10.1108/IJRDM-05-2022-0164
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