Sunʼiy intellekt asosidagi talabni prognozlashning chakana marketing innovatsiyasini takomillashtirishdagi roli

Ostonaqulova Gulsaraxon Muhammadyoqub qizi

Marketing · 2026-yil

Annotatsiya

В статье исследовано влияние прогнозирования спроса на основе искусственного интеллекта (ИИ) на маркетинговые инновации в розничной торговле в условиях цифровой трансформации. Применен подход, объединяющий анализ временных рядов и метод анализа иерархий (AHP). На основе опроса менеджеров розничной торговли три варианта прогнозирования были оценены методом AHP, а динамика индекса точности прогноза и индекса эффективности маркетинговых инноваций за 2000-2024 годы проанализирована с помощью теста ADF, моделей VAR и ARIMA. Согласно результатам AHP, наивысший приоритет получило прогнозирование на основе временных рядов (0,603), второе место заняло ИИ-прогнозирование (0,335). Оба индекса показали устойчивый рост, а влияние точности прогноза на маркетинговые результаты имело положительную направленность. Обосновано, что точность прогноза и эффективность маркетинговых инноваций тесно связаны с уровнем цифровой готовности предприятия. Ключевые слова: прогнозирование спроса на основе ИИ, розничная торговля, маркетинговые инновации, анализ временных рядов, метод анализа иерархий (AHP), цифровая готовность, персонализация, сегментация, точность прогноза. The article examined the impact of artificial intelligence (AI) based demand forecasting on marketing innovation in retail under digital transformation. An approach combining time-series analysis with the Analytic Hierarchy Process (AHP) was applied. Using a survey of retail managers, three forecasting options were evaluated with AHP, and the 2000-2024 dynamics of a forecast accuracy index and a marketing innovation effectiveness index were analysed with the ADF test, VAR and ARIMA models. According to the AHP results, time-series forecasting received the highest priority (0.603) and AI forecasting ranked second (0.335). Both indices showed a stable upward trend, and the effect of forecast accuracy on marketing outcomes was positive in direction. The study substantiated that forecast accuracy and the effectiveness of marketing innovation were closely linked to the firmʼs level of digital readiness.

Maqola ma’lumotlari
MualliflarOstonaqulova Gulsaraxon Muhammadyoqub qizi
JurnalMarketing
NashriyotТошкент давлат иқтисодиёт университети
ISSN3060-4621
Nashr sanasi2026-10-15
Son10
Betlar408-418
TilO‘zbek
Ilmiy sohaIqtisodiyot
DOI10.67668/mj/2026iss10/2233
Indeksga qo‘shilgan2026-10-31

DOI: 10.67668/mj/2026iss10/2233 · Maqolaning asl sahifasi

Kalit so‘zlar

AI asosidagi talab prognozi, chakana savdo marketingi, marketing innovatsiyalari, vaqt qatorlari tahlili, analitik iyerarxiya jarayoni (AHP), raqamli tayyorgarlik, personalizatsiya, segmentatsiya, prognoz aniqligi, прогнозирование спроса на основе ИИ, розничная торговля, маркетинговые инновации, анализ временных рядов, метод анализа иерархий (AHP), цифровая готовность, персонализация, сегментация, точность прогноза. The article examined the impact of artificial intelligence (AI) based demand forecasting on marketing innovation in retail under digital transformation. An approach combining time-series analysis with the Analytic Hierarchy Process (AHP) was applied. Using a survey of retail managers, three forecasting options were evaluated with AHP, and the 2000-2024 dynamics of a forecast accuracy index and a marketing innovation effectiveness index were analysed with the ADF test, VAR and ARIMA models. According to the AHP results, time-series forecasting received the highest priority (0.603) and AI forecasting ranked second (0.335). Both indices showed a stable upward trend, and the effect of forecast accuracy on marketing outcomes was positive in direction. The study substantiated that forecast accuracy and the effectiveness of marketing innovation were closely linked to the firmʼs level of digital readiness. Keywords: AI-based demand forecasting, retail marketing innovation, time-series ana, AI-based demand forecasting, retail marketing innovation, time-series analysis, Analytic Hierarchy Process (AHP), digital readiness, personalization, segmentation, forecast accuracy

Ilmiy soha

Iqtisodiyot

Iqtibos keltirish

APAOstonaqulova Gulsaraxon Muhammadyoqub qizi (2026). SUNʼIY INTELLEKT ASOSIDAGI TALABNI PROGNOZLASHNING CHAKANA MARKETING INNOVATSIYASINI TAKOMILLASHTIRISHDAGI ROLI. Marketing, (10), 408-418. https://doi.org/10.67668/mj/2026iss10/2233
GOST (OAK)Ostonaqulova Gulsaraxon Muhammadyoqub qizi SUNʼIY INTELLEKT ASOSIDAGI TALABNI PROGNOZLASHNING CHAKANA MARKETING INNOVATSIYASINI TAKOMILLASHTIRISHDAGI ROLI // Marketing. – 2026. – № 10. – B. 408-418. – DOI: 10.67668/mj/2026iss10/2233.
MLAOstonaqulova Gulsaraxon Muhammadyoqub qizi. “SUNʼIY INTELLEKT ASOSIDAGI TALABNI PROGNOZLASHNING CHAKANA MARKETING INNOVATSIYASINI TAKOMILLASHTIRISHDAGI ROLI.” Marketing, (10), 408-418, 2026. https://doi.org/10.67668/mj/2026iss10/2233
ChicagoOstonaqulova Gulsaraxon Muhammadyoqub qizi. “SUNʼIY INTELLEKT ASOSIDAGI TALABNI PROGNOZLASHNING CHAKANA MARKETING INNOVATSIYASINI TAKOMILLASHTIRISHDAGI ROLI.” Marketing, (10), 408-418 (2026). https://doi.org/10.67668/mj/2026iss10/2233
HarvardOstonaqulova Gulsaraxon Muhammadyoqub qizi (2026) ‘SUNʼIY INTELLEKT ASOSIDAGI TALABNI PROGNOZLASHNING CHAKANA MARKETING INNOVATSIYASINI TAKOMILLASHTIRISHDAGI ROLI’, Marketing, (10), 408-418. https://doi.org/10.67668/mj/2026iss10/2233
BibTeX
@article{ostonaqulovagulsaraxonmuhammadyoqubqizi2026,
  title = {SUNʼIY INTELLEKT ASOSIDAGI TALABNI PROGNOZLASHNING CHAKANA MARKETING INNOVATSIYASINI TAKOMILLASHTIRISHDAGI ROLI},
  author = {Ostonaqulova Gulsaraxon Muhammadyoqub qizi},
  journal = {Marketing},
  year = {2026},
  number = {10},
  pages = {408-418},
  doi = {10.67668/mj/2026iss10/2233},
  url = {https://doi.org/10.67668/mj/2026iss10/2233}
}

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