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

Paulo Duarte; Susana C. Silva; Marcelo Augusto Linardi; Beatriz Novais

doi:10.1108/IJRDM-05-2022-0164

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

Paulo Duarte^*
, Susana C. Silva^*
, Marcelo Augusto Linardi^*
, Beatriz Novais^*

^*Autor correspondente para este trabalho

Resultado de pesquisa › revisão de pares

37 Citações (Scopus)

16 Transferências (Pure)

Resumo

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.

Idioma original	English
Páginas (de-até)	140-163
Número de páginas	24
Revista	International Journal of Retail and Distribution Management
Volume	50
Número de emissão	13
DOIs	https://doi.org/10.1108/IJRDM-05-2022-0164
Estado da publicação	Publicado - 14 set. 2022

Acesso ao documento

10.1108/IJRDM-05-2022-0164Licença:

51936240Final published version, 1,63 MBLicença:

http://hdl.handle.net/10400.14/38971Licença:

Outros arquivos e links

Link to publication in Scopus

CEGE: Research Center in Management and Economics
Silva, M. (Professor Catedrático), Sousa, R. (Professor Catedrático), Alves, P. (Professor Auxiliar), Madsen, A. (Professor Auxiliar Convidado), Lourenço, A. (Professor Associado), Carvalho, A. S. (Professor Associado), Andrade, A. (Professor Auxiliar), Silva, P. D. (Professor Associado), Vlačić, B. (Professor Auxiliar Convidado), Martins, C. (Professor Auxiliar Convidado), Gomes, C. (Investigador Auxiliar), Gevrek, Z. E. (Professor Auxiliar Convidado), Oliveira, F. G. D. (Professor Associado), Faria, G. (Professor Associado Convidado), Marreiros, H. (Bolseiro), Pinho, J. (Professor Auxiliar Convidado), Machado, J. (Professor Associado), Araújo, J. (Investigador Auxiliar), Pinto, J. (Professor Auxiliar), Rego, A. (Professor Catedrático), Gaspar, J. M. (Investigador Auxiliar), Corbo, L. (Professor Auxiliar Convidado), Costa, L. (Professor Associado), Fernandes, L. (Professor Auxiliar), Sottomayor, M. (Professor Auxiliar), Martins, N. (Professor Catedrático), Hernández-Marrero, P. (Investigador Auxiliar), Gonçalves, R. (Professor Associado), Ribeiro, R. (PI), Coelho, S. L. (Docente Assistente), Pereira, S. M. (Investigador Auxiliar), Silva, S. (Professor Associado), Rodrigues, V. (Professor Associado), Sotiros, D. G. (Investigador Auxiliar), Valverde, C. (Professor Auxiliar), Leitão, A. (Professor Auxiliar), Julião, J. (Professor Auxiliar), Tavares, M. (Professor Auxiliar), Lages, C. R. (Investigador Auxiliar), Elmashhara, M. G. (Investigador Auxiliar) & Teymourifar, A. (Investigador Auxiliar)
1/01/20 → 31/12/25
Projeto

Citação

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title = "Understanding the implementation of retail self-service check-out technologies using necessary condition analysis",

abstract = "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.",

keywords = "Self-service technology, Adoption, Retail, NCA, Omnichannel strategy",

author = "Paulo Duarte and Silva, \{Susana C.\} and Linardi, \{Marcelo Augusto\} and Beatriz Novais",

note = "Funding Information: The authors would like to thank NECE – Research Unit in Business Sciences funded by the Multiannual Funding Programme of R\&D Centres of FCT – Funda{\c c}{\~a}o para a Ci{\^e}ncia e a Tecnologia, under the project UIDB/04630/2020 and to CEGE – Research Centre in Management and Economics, funded by the Multiannual Funding Programme of R\&D Centres of FCT – Funda{\c c}{\~a}o para a Ci{\^e}ncia e a Tecnologia, under the project UIDB/00731/2020. Publisher Copyright: {\textcopyright} 2022, Paulo Duarte, Susana C. Silva, Marcelo Augusto Linardi and Beatriz Novais.",

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T1 - Understanding the implementation of retail self-service check-out technologies using necessary condition analysis

AU - Duarte, Paulo

AU - Silva, Susana C.

AU - Linardi, Marcelo Augusto

AU - Novais, Beatriz

N1 - Funding Information: The authors would like to thank NECE – Research Unit in Business Sciences funded by the Multiannual Funding Programme of R&D Centres of FCT – Fundação para a Ciência e a Tecnologia, under the project UIDB/04630/2020 and to CEGE – Research Centre in Management and Economics, funded by the Multiannual Funding Programme of R&D Centres of FCT – Fundação para a Ciência e a Tecnologia, under the project UIDB/00731/2020. Publisher Copyright: © 2022, Paulo Duarte, Susana C. Silva, Marcelo Augusto Linardi and Beatriz Novais.

PY - 2022/9/14

Y1 - 2022/9/14

N2 - 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.

AB - 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.

KW - Self-service technology

KW - Adoption

KW - Retail

KW - NCA

KW - Omnichannel strategy

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JO - International Journal of Retail and Distribution Management

JF - International Journal of Retail and Distribution Management

IS - 13

ER -

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

Resumo

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CEGE: Research Center in Management and Economics

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