Transformations  in
Business & Economics

A MULTI-CRITERIA DECISION-MAKING MODEL BASED ON ONLINE CONSUMER REVIEWS UNDER INTERVAL-VALUED PROBABILISTIC LINGUISTIC ENVIRONMENT¹
Huchang Liao, Jiayi Wang, Xingli Wu, Ruey-Huei Yeh, Samer Khouri

ABSTRACT: As an outcome of the development of e-commerce, online consumer reviews (OCRs) contain lots of information about products, which can help consumers evaluate products and make purchase decisions, and help merchants grasp the competitiveness of products in a timely manner. This study aims to propose a multi-criteria decision-making model based on OCRs to select products for consumers and provide a basis to merchants for product improvement. The model consists of three aspects of innovative work: (1) interval-valued probabilistic linguistic term sets (IVPLTSs) are used to describe consumers’ sentiment opinions in text reviews, taking into account the vagueness in information representation; (2) data envelopment analysis and grey related analysis are combined as a ranking method to maximize consumers’ sentiment opinions within the context of IVPLTSs; (3) based on the sentiment analysis and ranking results, product criteria are classified to provide the basis for criteria prioritization. An empirical study regarding the OCRs of six types of cars on www.autohome.com.cn is carried out to valid the proposed model. The effectiveness of the model is illustrated by comparative analysis.

KEYWORDS:  online consumer reviews, interval-valued probabilistic linguistic term sets, data envelopment analysis, grey related analysis, Kano model.

JEL classification:  C02, C44, D71, D81, R41.

¹Acknowledgments:  The work was supported by the National Natural Science Foundation of China (Nos. 71771156, 71971145, 72171158), the 2022 Sichuan Planning Project of Social Science (SC22A021), the 2022 Key Project of the Key Research Institute of Humanities and Social Sciences in Sichuan Province (CJZ22-04), and the Chengdu Philosophy and Social Sciences Planning Project under Grant 2022C16.