A novel approach for product competitive analysis based on online reviews

Zhen He, Lu Zheng () and Shuguang He
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Zhen He: Tianjin University
Lu Zheng: Tianjin University
Shuguang He: Tianjin University

Electronic Commerce Research, 2023, vol. 23, issue 4, No 11, 2259-2290

Abstract: Abstract Recently, online reviews have become a prevalent information source for competitive analysis because they provide rich information on the voices of customers. Based on online reviews, we propose a novel method named Integrated-Degree based K-shell decomposition (ID-KS) to conduct competitive analysis via product comparison networks. Under the consideration of feature differences among products, we apply text-mining approaches and ID-KS to convert online reviews into competitive insights including competitor identification, product comparison, product ranking, brand comparison and market-structure analysis. To validate the feasibility and the effectiveness of ID-KS, we demonstrate our approach in two cases, SUV cars and laptops, and compare it with state-of-the-art methods. The results show that ID-KS analyzes product comparison networks more effectively and properly, and it derives comprehensive comparative insights that are not fully captured by existing studies.

Keywords: Competitive analysis; Text analysis; Latent dirichlet allocation; Sentiment analysis; K-shell decomposition (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10660-022-09534-y

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