A voice of the customer real-time strategy: An integrated quality function deployment approach. (July 2022) - Shen, Yixuan; Zhou, Jian; Pantelous, Athanasios A.; Liu, Yanbao; Zhang, Ziying
Highlights: A full-process product improvement solution driven by online reviews is raised. An online review screening model is constructed based on twenty-eight indicators. CRs are identified by text mining, and the weights are assigned via fuzzy inference. CRs' weights are mapped to ECs' priorities by machine-learning techniques. Abstract: In the era of Industry 4.0, the rapid development of information technology in the last decade has provided new challenges for product improvement by enabling users to give their feedback and sentiments in real time. In this paper, combining with genetic algorithm back propagation neutral network, fuzzy inference method, and entropy-based synthesis evaluation method, we raise a full-process product improvement solution driven by online reviews, from the initial online review collection to the final engineering characteristic prioritization. The proposed novel integrated quality function deployment-based approach adheres to the customer-oriented design principle, allowing manufacturers to strengthen the launched product based on the spontaneously-articulated voice of customer, rather than the traditional expertise. In this way, an off-the-shelf product improvement strategy is available for enterprises, and its special advantages like fast adaptation and real-time responsiveness, would significantly reduce management costs, shorten response time to market dynamics, and enhance customer satisfaction. In addition, a case study in smartphone industry is conducted for illustration, and the results clearly demonstrate the effectiveness and practicability of the treatment.