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Reviews and product recommendations at online stores enable customers to readily evaluate alternative products prior to purchase. In this context, firms generate recommendations referring customers to a wider variety of products. They also display customer-generated online reviews in order to facilitate evaluation of those recommended products. This study integrates these two IT artifacts to investigate consumer choice vis-à-vis competing products. We use a dataset we collected from Amazon.com consisting of books, sales ranks, recommendations, reviews, and reviewers. We derive the granular impact of reviews, product referrals, and reviewer opinions on product sale dynamics within a competitive market using comprehensive econometric analyses.
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Stored only when both papers are in the corpus — 155 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.