Abstract
PurposeSelf-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/approachBased 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.FindingsAccording to the NCA analysis results, 12 latent variables were relevant for predicting SSTs adoption, but only seven were necessary conditions for user adoption.Originality/valueThe 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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