Academy of Marketing Studies Journal (Print ISSN: 1095-6298; Online ISSN: 1528-2678)

Abstract

Text Mining for Decision Making of Refurbished Smartphone based on Amazon Reviews

Author(s): Abhishek Tripathi, Tripti Singh and Yatish Joshi

With the focus on the circular economy, the online purchase of remanufactured products, especially refurbished smart phones, has surged drastically over the years. With varying benefits and challenges of refurbished products, it is important to understand the consumer concerns and refurbished product preference criteria. The present paper attempts to review customer opinions to identify the salient traits of their purchasing patterns of refurbished smart phones through online E-Commerce sites. The methods employ extracting customer reviews from the Amazon website and then processing them using the computer aided programming method such as cluster analysis. It attempts to identify the factors influencing consumer purchase behavior, identify various product flaws, and split the consumer groups based on their sentiments. The findings reveal six consumer groups based on their preference for features, quality, and overall value, less cost, camera, and good battery life. Among them, budget-friendly and quality seekers account for the most significant proportion who intends to buy refurbished electronic products. The finding can assist in resolving customer issues and serve as a basis for making suitable decisions for marketing refurbished products.

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