Correlation of customer experience with the acceptance of product-service systems and circular economy
Tipo
Artigo
Data de publicação
2021
Periódico
Journal of Cleaner Production
Citações (Scopus)
31
Autores
Pecorari P.M.
Lima C.R.C.
Lima C.R.C.
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Resumo
© 2020 Elsevier LtdProduct-service systems have been used as a tool for the practical application of the concepts of sustainability and circular economy. The customer experience through such systems has become an ally for its broad implementation, while customer acceptance is a barrier. However, it is unclear what contributes to customer experience and acceptance. This paper sought to find in the literature the main variables that contribute to the factors of customer experience and acceptance of product-service systems, then making it possible to analyze and understand the correlation between these factors to increase the strength of the experience and decrease the resistance for acceptance. This work was conducted in a B2B truck-maintenance environment, carrying out a survey analysis with 154 road freight transport companies in Brazil. A structural equation model was developed to use the research responses and perform the confirmatory factor analysis of the correlation between the variables of customer experience and acceptance, found in the literature, and adapted in the form of statements in a web questionnaire. The results of the work suggest that the customer experience with customer service, relationship, knowledge, proactivity, information Integration, and performance indicators, influences the acceptance of solutions based on trust, technology, and innovation, access to knowledge, and operation control. The Fitted Conceptual Model presents the scientific value added by this work and path found to help product-service solutions, related to truck-maintenance, to have a greater chance of success in their business, and consequently implement more frequent concepts of sustainability and circular economy for cleaner production.
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Assuntos Scopus
Confirmatory factor analysis , Customer acceptance , Customer experience , Information integration , Performance indicators , Product-service systems , Road freight transport , Structural equation modeling