What attracts vehicle consumers’ buying: A Saaty scale-based VIKOR (SSC-VIKOR) approach from after-sales textual perspective?

Fuli Zhou , Ming Lim, Yandong He , Saurabh Pratap

    Research output: Contribution to journalArticlepeer-review

    46 Citations (Scopus)
    368 Downloads (Pure)


    Purpose: The increasingly booming e-commerce development has stimulated vehicle consumers to express individual reviews through online forum. The purpose of this paper is to probe into the vehicle consumer consumption behavior and make recommendations for potential consumers from textual comments viewpoint. Design/methodology/approach: A big data analytic-based approach is designed to discover vehicle consumer consumption behavior from online perspective. To reduce subjectivity of expert-based approaches, a parallel Naïve Bayes approach is designed to analyze the sentiment analysis, and the Saaty scale-based (SSC) scoring rule is employed to obtain specific sentimental value of attribute class, contributing to the multi-grade sentiment classification. To achieve the intelligent recommendation for potential vehicle customers, a novel SSC-VIKOR approach is developed to prioritize vehicle brand candidates from a big data analytical viewpoint. Findings: The big data analytics argue that “cost-effectiveness” characteristic is the most important factor that vehicle consumers care, and the data mining results enable automakers to better understand consumer consumption behavior. Research limitations/implications: The case study illustrates the effectiveness of the integrated method, contributing to much more precise operations management on marketing strategy, quality improvement and intelligent recommendation. Originality/value: Researches of consumer consumption behavior are usually based on survey-based methods, and mostly previous studies about comments analysis focus on binary analysis. The hybrid SSC-VIKOR approach is developed to fill the gap from the big data perspective.

    Original languageEnglish
    Pages (from-to)57-78
    JournalIndustrial Management and Data Systems
    Issue number1
    Early online date20 Nov 2019
    Publication statusPublished - 2019

    Bibliographical note

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    • Intelligent recommendation
    • Parallel Naïve Bayes method
    • Saaty scale-based VIKOR (SSC-VIKOR)
    • Sentiment classification
    • Sentiment value

    ASJC Scopus subject areas

    • Management Information Systems
    • Industrial relations
    • Computer Science Applications
    • Strategy and Management
    • Industrial and Manufacturing Engineering


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