Nowadays, word of mouth and the Voice-of-Customers have largely left their physical and relational dimension to be replaced by online digital platforms where users can describe their experiences and share them openly. However, the increasing availability of user-generated content, related to the usage of products and services, poses several challenges for research. A key priority is to understand how to use these large amounts of accessible and low-cost data to improve the quality of products and/or services and, consequently, customer satisfaction. The purpose of this paper is to show the potential of digital Voice-of-Customers (digital VoCs) as a source of information to monitor quality over time. The obtained insights may represent a first step towards developing quality tracking tools based on digital VoCs, thereby allowing the evolution of changes in perceived quality to be understood. Some examples accompany the description.

Product quality tracking based on digital Voice-of Customers / Barravecchia, Federico; Mastrogiacomo, Luca; Franceschini, Fiorenzo. - In: TOTAL QUALITY MANAGEMENT & BUSINESS EXCELLENCE. - ISSN 1478-3363. - STAMPA. - 34:11-12(2023), pp. 1386-1409. [10.1080/14783363.2023.2177147]

Product quality tracking based on digital Voice-of Customers

Federico Barravecchia;Luca Mastrogiacomo;Fiorenzo Franceschini
2023

Abstract

Nowadays, word of mouth and the Voice-of-Customers have largely left their physical and relational dimension to be replaced by online digital platforms where users can describe their experiences and share them openly. However, the increasing availability of user-generated content, related to the usage of products and services, poses several challenges for research. A key priority is to understand how to use these large amounts of accessible and low-cost data to improve the quality of products and/or services and, consequently, customer satisfaction. The purpose of this paper is to show the potential of digital Voice-of-Customers (digital VoCs) as a source of information to monitor quality over time. The obtained insights may represent a first step towards developing quality tracking tools based on digital VoCs, thereby allowing the evolution of changes in perceived quality to be understood. Some examples accompany the description.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2979557
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