logo
calendar20 январ 2025
view2
Asosiy til:Ingliz

Review of supply chain innovation through artificial intelligence: Possible applications in Uzbekistan

Fan yo'nalishi:
pdf

678e31c8620fd.pdf

PDF

MAQOLA ANNOTATSIYASI

quote
The presented article represents a systematic literature review of empirical studies on the adoption of AI for applications in the field of supply chain management. In the last decade, AI has advanced remarkably, bringing transformative changes to business operations and society. This review explores current technological approaches and their wide-ranging applications, offering valuable insights with potential to revolutionize supply chain processes in regions like Uzbekistan, where AI integration could drive significant economic growth and operational advancements. This study sets the stage for future academic research in Uzbekistan while also offering insights to help managers make better decisions about using AI in supply chain management.

MUALIFLAR

Teglar

# logistics# transportation# artificial intelligence# Internet technologies# supply chain innovations# SCM# disruption management# intelligent solutions

Maqolani baholang

0

0 ta

Maqola idintifikatorlari

Foydalanilgan adabiyotlar

Harvard University. (2017). The history of Artificial Intelligence. Retrieved from https://sitn.hms.harvard.edu/flash/2017/history-artificialintelligence/

Cabinet of Ministers of Uzbekistan. (2023). On measures to implement the state program for the development of artificial intelligence for 2023–2030. Retrieved from https://lex.uz/ru/pdfs/7158606

Durach, C.F., Kembro, J., & Wieland, A. (2017). A new paradigm for systematic literature reviews in supply chain management. Journal of Supply Chain Management, 53(4), 67–85.

Gartner. (2024, February 20). Gartner says top supply chain organizations are using AI to optimize processes at more than twice the rate of low-performing peers. Gartner Newsroom. Retrieved from https://www.gartner.com/en/newsroom/pressreleases/2024-02-20-gartner-says-top-supply-chainorganizations-are-using-ai-to-optimize-processes-at-morethan-twice-the-rate-of-low-performing-peers

Chen, Y. T., Sun, E. W., Chang, M. F., & Lin, Y. B. (2021). Pragmatic real-time logistics management with traffic IoT infrastructure: Big data predictive analytics of freight travel time for Logistics 4.0. International Journal of Production Economics, 238, 108157. https://doi.org/10.1016/j.ijpe.2021.108157

Brock, J. K.-U., & von Wangenheim, F. (2019). Demystifying AI: What Digital Transformation Leaders Can Teach You about Realistic Artificial Intelligence. Business Horizons, 61(4). https://doi.org/10.1177/1536504219865226.

Cannas, V. G., Ciano, M. P., Saltalamacchia, M., & Secchi, R. (2023). Artificial intelligence in supply chain and operations management: A multiple case study research. International Journal of Production Research, 61(14), 3333- 3360. https://doi.org/10.1080/00207543.2023.2232050.

Brintrup, A., Kosasih, E., Schaffer, P., Zheng, G., Demirel, G., & MacCarthy, B. L. (2023). Digital supply chain surveillance using artificial intelligence: Definitions, opportunities and risks. International Journal of Production Research, 61(20), 4674-4695. https://doi.org/10.1080/00207543.2023.2270719.

Chuang, H. H., Chou, Y., & Oliva, R. (2021). Crossitem learning for volatile demand forecasting: An intervention with predictive analytics. Journal of Operations Management, 67(7), 828–852

Wang, G., Gunasekaran, A., Ngai, E. W., & Papadopoulos, T. (2016). Big data analytics in logistics and supply chain management: Certain investigations for research and applications. International Journal of Production Economics, 176, 98–110. https://doi.org/10.1016/j.ijpe.2016.03.014

Kinkel, S., Capestro, M., Di Maria, E., & Bettiol, M. (2023). Artificial intelligence and relocation of production activities: An empirical cross-national study. International Journal of Production Economics, 261, 108890. https://doi.org/10.1016/j.ijpe.2023.108890

Bodendorf, F., Dentler, S., & Franke, J. (2023). Digitally enabled supply chain integration through business and process analytics. Industrial Marketing Management, 114, 14–31.

Rodríguez-Espíndola, O., Chowdhury, S., Dey, P. K., Albores, P., & Emrouznejad, A. (2022). Analysis of the adoption of emergent technologies for risk management in the era of digital manufacturing. Technological Forecasting and Social Change, 178, 121562

Kanitz, R., Gonzalez, K., Briker, R., & Straatmann, T. (2023). Augmenting organizational change and strategy activities: Leveraging generative artificial intelligence. Journal of Applied Behavioral Science, 59(3), 345–363.

Pillai, R., Sivathanu, B., Mariani, M., Rana, N. P., Yang, B., & Dwivedi, Y. K. (2021). Adoption of AIempowered industrial robots in auto component manufacturing companies. Production Planning & Control, 32(12), 1517–1533. https://doi.org/10.1080/09537287.2021.1882689

S. Wong, J.K.-W. Yeung, Y.-Y. Lau, T. Kawasaki, A case study of how maersk adopts cloud-based blockchain integrated with machine learning for sustainable practices, Sustainability 15 (9) (2023) 7305.

Huang, D., Wang, S., & Liu, Z. (2021). A systematic review of prediction methods for emergency management. International Journal of Disaster Risk Reduction, 62, 102412. https://doi.org/10.1016/j.ijdrr.2021.102412

Abou-Foul, M., Ruiz-Alba, J. L., & LópezTenorio, P. J. (2023). The influence of artificial intelligence capabilities on servitization: Examining the moderating role of absorptive capacity from a dynamic capabilities perspective. Journal of Business Research, 157, 113609. https://doi.org/10.1016/j.jbusres.2022.113609

Burger, M., Nitsche, A.-M., & Arlinghaus, J. (2023). Hybrid intelligence in procurement: Disillusionment with AI’s superiority? Computers in Industry, 150, 103946.

public

SLIB.uz — O'zbekiston ilmiy jurnallari va maqolalar yagona tizimda ilmiy nashirlarni bir joyda ko'rish, izlash va ulardan foydalanish imkonini beruvchi zamonaviy platforma.

Ijtimoiy tarmoqlarda
instagramtelegramyoutubefacebook

Bog'lanish uchun

Manzil:Chilonzor tumani Qatortol ko'chasi 60B

Tel:+998(55)511-44-00

Savol-javob va takliflar uchun

© 2026 Barcha huquqlar himoyalangan.