Customers perception on logistics service quality using Kansei engineering: empirical evidence from indonesian logistics providers
This article designed a service model in logistics services for document and package delivery through the exploration of service element relationships and customer perceived (i.e. Kansei). Kansei engineering is used in this article to design 24 questionnaire instruments and 41 services attribute que...
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Autores principales: | , , |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Taylor & Francis Group
2020
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Materias: | |
Acceso en línea: | https://doaj.org/article/88e23b249bf841f9a3378cfcdab590f9 |
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Sumario: | This article designed a service model in logistics services for document and package delivery through the exploration of service element relationships and customer perceived (i.e. Kansei). Kansei engineering is used in this article to design 24 questionnaire instruments and 41 services attribute questionnaire instruments. The questionnaire was distributed by purposive sampling with a total of 100 respondents in logistics services: package delivery services, package tracking services, and package delivery services. In this study, Partial Least Square for Structural Equation Modelling (PLS-SEM) is used to analyze the relationship between Kansei and the logistics service elements. The results indicate that Kansei’s words affect significantly on the three logistics services. The results of this study indicate that the variables obtained from Kansei words have a significant effect on 16 elements of logistics services. The innovative Kansei word has the most influence in the delivery service, the reliable Kansei word has the most influence in the tracking service, the reliable and adjustable Kansei word has the most impact in the delivery service. This study also produces the best service attributes at each service stage to improve the quality of logistics services. This finding has important implications for logistics managers in designing services that take into account elements of customer-based voice services. |
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