Exploring the Impact of Artificial Intelligence on the Development of Demand Forecasting Systems for Retail Businesses

Authors

    Zahra Shamloo Master's degree in Educational Management, Roudhen Branch, Islamic Azad University, Roudhen, Iran
    Fattah Nazem * Associate Professor, Department of Educational Sciences, Roudehen Branch, Islamic Azad University, Roudehen, Iran nazem@riau.ac.ir
https://doi.org/10.61838/kman.jtesm.2.1.2

Keywords:

Artificial Intelligence, Demand Forecasting, Retail Businesses, Implementation Challenges, Organizational Strategy

Abstract

This study aims to investigate how artificial intelligence (AI) influences the development of demand forecasting systems in retail businesses, identifying the benefits, challenges, and opportunities presented by AI technologies. A qualitative research design was employed, using semi-structured interviews as the primary method for data collection. Participants included 20 managers and experts in the fields of retail and information technology, selected through purposive sampling. Five main themes were identified: the use of AI in demand forecasting, challenges in implementing AI, opportunities created by AI, effects on organization and strategy, and social and ethical impacts. AI was found to enhance demand forecasting accuracy, operational efficiency, and customer satisfaction. However, technical, organizational, and financial challenges were also noted. Despite the challenges associated with AI implementation, the study concludes that AI has a significant positive impact on improving demand forecasting and overall retail business performance. Retailers are encouraged to embrace AI technologies to stay competitive in the rapidly evolving market.

Downloads

Download data is not yet available.

References

Brau, R. I., Sanders, N. R., Aloysius, J., & Williams, D. (2023). Utilizing People, Analytics, and AI for Decision Making in

the Digitalized Retail Supply Chain. Journal of Business Logistics. https://doi.org/10.1111/jbl.12355

Giri, C., & Chen, Y. (2022). Deep Learning for Demand Forecasting in the Fashion and Apparel Retail Industry. Forecasting.

https://doi.org/10.3390/forecast4020031

Jain, A., & Ormsbee, L. (2001). A Decision Support System for Drought Characterization and Management. Civil Engineering

and Environmental Systems. https://doi.org/10.1080/02630250108970296

Jiang, K., Qin, M., & Li, S. (2022). Chatbots in Retail: How Do They Affect the Continued Use and Purchase Intentions of

Chinese Consumers? Journal of Consumer Behaviour. https://doi.org/10.1002/cb.2034

Kilimci, Z. H., Akyuz, A. O., Akyokuş, S., Uysal, M., Bülbül, B. A., & Ekmis, M. A. (2019). An Improved Demand Forecasting

Model Using Deep Learning Approach and Proposed Decision Integration Strategy for Supply Chain. Complexity.

https://doi.org/10.1155/2019/9067367

Kolková, A., & Ključnikov, A. (2022). Demand Forecasting: AI-based, Statistical and Hybrid Models vs Practice-Based

Models - The Case of SMEs and Large Enterprises. Economics & Sociology. https://doi.org/10.14254/2071-789x.2022/15-

/2

Lin, L., & Zhang, W. (2019). Precision Marketing Driven by the Internet Supply Chain in the New Retail Era.

https://doi.org/10.2991/febm-19.2019.52

Oosthuizen, K., Botha, E., Robertson, J., & Montecchi, M. (2020). Artificial Intelligence in Retail: The AI-enabled Value

Chain. Australasian Marketing Journal (Amj). https://doi.org/10.1016/j.ausmj.2020.07.007

Souhe, F. G. Y., Mbey, C. F., Boum, A. T., & Ele, P. (2021). Forecasting of Electrical Energy Consumption of Households in

a Smart Grid. International Journal of Energy Economics and Policy. https://doi.org/10.32479/ijeep.11761

Yang, G., Ji, G., & Tan, K. H. (2020). Impact of Artificial Intelligence Adoption on Online Returns Policies. Annals of

Operations Research. https://doi.org/10.1007/s10479-020-03602-y

Downloads

Published

2023-05-29

Submitted

2023-04-14

Revised

2023-05-18

Accepted

2023-05-26

Issue

Section

مقاله کیفی

How to Cite

Shamloo, Z., & Nazem, F. (2023). Exploring the Impact of Artificial Intelligence on the Development of Demand Forecasting Systems for Retail Businesses. Journal of Technology in Entrepreneurship and Strategic Management (JTESM), 2(1), 5-16. https://doi.org/10.61838/kman.jtesm.2.1.2

Similar Articles

1-10 of 143

You may also start an advanced similarity search for this article.