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A Multi-Stage Model for Perceived Quality Evaluation of Clothing Brands

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Listed:
  • Minhui Ren

    (School of Economics and Management, Beijing Information Science and Technology University, Beijing 100192, China)

  • Yu Fan

    (School of Economics and Management, Beijing Information Science and Technology University, Beijing 100192, China
    Beijing Key Laboratory of Big Data Decision Making for Green Development, Beijing Information Science and Technology University, Beijing 100192, China)

  • Jindong Chen

    (School of Economics and Management, Beijing Information Science and Technology University, Beijing 100192, China
    Beijing International Science and Technology Cooperation Base for Intelligent Decision and Big Data Application, Beijing 100192, China)

  • Jian Zhang

    (School of Economics and Management, Beijing Information Science and Technology University, Beijing 100192, China
    Beijing Key Laboratory of Big Data Decision Making for Green Development, Beijing Information Science and Technology University, Beijing 100192, China
    Beijing International Science and Technology Cooperation Base for Intelligent Decision and Big Data Application, Beijing 100192, China)

Abstract

Perceived quality is crucial for the functioning of clothing brands. However, accurate evaluation of the perceived quality of clothing brands remains a common challenge. To achieve a multidimensional evaluation of the perceived quality of clothing brands, an index system is derived based on perceived quality theory. Then, by combining a fine-grained sentiment analysis approach with stochastic dominance criteria, a multi-stage model ECRM is proposed for the perceived quality evaluation of clothing brands based on online user reviews. ECRM comprises three stages: Extraction, Classification, and Ranking. To begin with, Contrastive Attention and dependency parsing are used to extract attribute–viewpoint phrases from online reviews. Subsequently, the pre-trained models are employed to classify the indexes and sentiment levels of these phrases. Furthermore, the perceived quality indexes are ranked using stochastic dominance criteria and the PROMETHEE-II method. Empirical analysis is conducted for the clothing brands of ALDB, AND, BNL, and QPL; the results show that, based on online user reviews, ECRM enables accurate evaluation of the perceived quality of clothing brands. Based on the evaluation results, it is found that Comfort, External, Protection, and Fineness are highly valued by consumers; moreover, the four brands focus on different indexes. Specific strategies for perceived quality improvements are proposed depending on the current status of the brands.

Suggested Citation

  • Minhui Ren & Yu Fan & Jindong Chen & Jian Zhang, 2023. "A Multi-Stage Model for Perceived Quality Evaluation of Clothing Brands," Mathematics, MDPI, vol. 11(18), pages 1-16, September.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:18:p:3928-:d:1240655
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    References listed on IDEAS

    as
    1. Su-min Yu & Zhi-jiao Du & Xu-dong Lin & Han-yang Luo & Jian-qiang Wang, 2020. "A Stochastic Dominance-Based Approach for Hotel Selection under Probabilistic Linguistic Environment," Mathematics, MDPI, vol. 8(9), pages 1-25, September.
    2. Behzadian, Majid & Kazemzadeh, R.B. & Albadvi, A. & Aghdasi, M., 2010. "PROMETHEE: A comprehensive literature review on methodologies and applications," European Journal of Operational Research, Elsevier, vol. 200(1), pages 198-215, January.
    3. Wenzhi Cao & Xingen Yang & Yi Yang, 2023. "A Large-Scale Reviews-Driven Multi-Criteria Product Ranking Approach Based on User Credibility and Division Mechanism," Mathematics, MDPI, vol. 11(13), pages 1-19, July.
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