Purpose - Digital Voice-of-Customer (digital VoC) primarily consists of textual feedback posted by users of products or services on the web. Digital VoC may represent a valuable source of information for quality management, and its promising potential is also receiving a lot of attention in the new Quality 4.0 framework. However, manufacturers and service providers still lack operative approaches to fully exploit the value of digital VoC. This study tries to answer the following research question: How Statistical Process Control (SPC) techniques can be used to monitor digital VoC over time? Design/methodology/approach - This article explores the applicability of SPC to support digital VoC analysis. Two types of control charts, for variables and attributes, were applied to a real case study concerning a product-service system (car-sharing). Findings - SPC tools may represent an interesting alternative to traditional quality tracking approaches to analyze the evolution of quality determinants over time. Originality/value – This study shows how Artificial intelligence algorithms and SPC tools may support product and service designers in implementing continuous improvement actions by analyzing digital VoC over time.

Statistical Process Control techniques to monitor quality determinants in digital Voice-of-Customer / Barravecchia, Federico; Mastrogiacomo, Luca; Tavani, Lorenzo; Franceschini, Fiorenzo. - ELETTRONICO. - (2022), pp. 120-141. (Intervento presentato al convegno 5th International Conference on Quality Engineering and Management, 2022 tenutosi a Braga, Portogallo nel 14-15 July 2022).

Statistical Process Control techniques to monitor quality determinants in digital Voice-of-Customer

Barravecchia, Federico;Mastrogiacomo, Luca;Franceschini, Fiorenzo
2022

Abstract

Purpose - Digital Voice-of-Customer (digital VoC) primarily consists of textual feedback posted by users of products or services on the web. Digital VoC may represent a valuable source of information for quality management, and its promising potential is also receiving a lot of attention in the new Quality 4.0 framework. However, manufacturers and service providers still lack operative approaches to fully exploit the value of digital VoC. This study tries to answer the following research question: How Statistical Process Control (SPC) techniques can be used to monitor digital VoC over time? Design/methodology/approach - This article explores the applicability of SPC to support digital VoC analysis. Two types of control charts, for variables and attributes, were applied to a real case study concerning a product-service system (car-sharing). Findings - SPC tools may represent an interesting alternative to traditional quality tracking approaches to analyze the evolution of quality determinants over time. Originality/value – This study shows how Artificial intelligence algorithms and SPC tools may support product and service designers in implementing continuous improvement actions by analyzing digital VoC over time.
2022
978-989-54911-1-7
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2970158