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Wisdom of crowds: SWOT analysis based on hybrid text mining methods using online reviews

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  • Wu, Jie
  • Zhao, Narisa
  • Yang, Tong

Abstract

Consumer online reviews are prolific, authentic, and real-time, providing potential business opportunities. Traditional SWOT analysis is highly subjective, lacks an effective focus on the core competitive advantages and disadvantages, and fails to act on the dynamic business environment. To address these issues, we propose an innovative methodology that utilizes hybrid text mining methods to conduct SWOT analysis using online reviews. After first identifying the service attributes from the literature, we calculate attribute performance via sentiment analysis. Second, guided by salience theory, factor importance is calculated based on the TF-IDF algorithm. Following the essential meaning of SWOT factors, we then construct the factor determination rules. Finally, we model the changing trends of SWOT factors from a dynamic perspective, which can help managers develop preventive strategies. Online reviews of five hotels crawled from Ctrip were applied to validate the proposed method. The comparison with two state-of-the-art methods also demonstrated its effectiveness.

Suggested Citation

  • Wu, Jie & Zhao, Narisa & Yang, Tong, 2024. "Wisdom of crowds: SWOT analysis based on hybrid text mining methods using online reviews," Journal of Business Research, Elsevier, vol. 171(C).
    • Handle: RePEc:eee:jbrese:v:171:y:2024:i:c:s0148296323007373
    DOI: 10.1016/j.jbusres.2023.114378
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