This article analyzes the algorithmic recommendation system of the Uzum Market e-commerce platform and its impact on consumer purchasing decisions. The platform's algorithmic recommendations generate personalized product offers based on users' previous activity, search history, and purchasing behavior. At the same time, Uzbek consumers can also rely on social confirmation sources such as traditional word-of-mouth (WOM) and electronic word-of-mouth (eWOM) during the purchase process. The study examined the impact of algorithmic recommendations, WOM, and eWOM on consumer decisions based on existing international scientific literature. A small-scale pilot survey was also conducted as part of the preparation of the article. The survey results provide initial empirical evidence to assess the impact of algorithmic recommendations on consumer purchasing decisions in the Uzbek e-commerce market, in particular on the Uzum Market platform. The results will provide a scientific basis for further, more comprehensive and in-depth research in this area.
| Mualliflar | Davronova , Sabrina, Давронова, Сабрина, Davronova , Sabrina |
|---|---|
| Jurnal | Иқтисодий тараққиёт ва таҳлил |
| Nashr sanasi | 2026-07-31 |
| Jild | 4 |
| Son | 7 |
| Betlar | 66-73 |
| Til | O‘zbek |
| DOI | 10.60078/2992-877x-2026-vol4-iss7-pp66-73 |
DOI: 10.60078/2992-877x-2026-vol4-iss7-pp66-73 · Maqolaning asl sahifasi
algorithmic recommendations, artificial intelligence, e-commerce, Uzum Market, consumer decision-making, Word-of-Mouth (WOM), Electronic Word-of-Mouth (eWOM), алгоритмические рекомендации, искусственный интеллект, электронная коммерция, рынок Узум, принятие решений потребителями, сарафанное радио (WOM), электронное сарафанное радио (eWOM), algoritmik tavsiyalar, sun’iy intellekt, elektron tijorat, Uzum Market, iste’molchi qarorlarini qabul qilish, Word-of-Mouth (WOM), Electronic Word-of-Mouth (eWOM)
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