ARTIFICIAL INTELLIGENCE IN THE RETAIL SECTOR: MARKET AND BUSINESS MODEL TRANSFORMATION
Keywords:
Artificial Intelligence, Retail, Market Transformation, Business Model.Abstract
In the dynamic landscape of the retail industry, Artificial Intelligence (AI) has become an important catalyst for transformation. The study in this research used a literature review. The research findings show that AI contributes to the personalization of the customer experience, with machine learning algorithms offering personalized product recommendations, increasing engagement, and stimulating sales. In terms of inventory and supply chain management, AI helps optimize stock through accurate forecasting, reduce wastage, and adapt procurement to changing market demands. Automated cashier operations and the use of chatbots effectively reduce waiting times and improve customer service quality. Analysis of the rapid development of consumer behavior through AI allows for more responsive and aspiring marketing strategies.
References
Agrawal, A., & Khosla, V. (2021). How artificial intelligence and the digital transformation change business and society. Managing Digital Transformation, Query date: 2024-05-30 11:17:17, 127–132. https://doi.org/10.4324/9781003008637-12
Annunziata, F. (2023). Artificial intelligence and market manipulation. Artificial Intelligence and Market Abuse Legislation, Query date: 2024-05-30 11:17:17, 109–167. https://doi.org/10.4337/9781035310722.00008
Baber, W. W., Ojala, A., Sarata, M., & Tsukamoto, M. (2021). Business Model Transformation during Firm Internationalisation: Stretching from Japan to the US Market. Business Models and Firm Internationalisation, Query date: 2024-05-30 11:17:17, 97–110. https://doi.org/10.4324/9781003204268-6
Bonsón, E., & Bednárová, M. (2022). Artificial Intelligence Disclosures in Sustainability Reports: Towards an Artificial Intelligence Reporting Framework. Lecture Notes in Information Systems and Organisation, Query date: 2024-05-30 11:17:17, 391–407. https://doi.org/10.1007/978-3-030-94617-3_27
Chen, Z., Zhao, J., & Jin, C. (2023). Business intelligence for Industry 4.0: Predictive models for retail and distribution. International Journal of Retail & Distribution Management, Query date: 2024-05-30 11:17:17. https://doi.org/10.1108/ijrdm-02-2023-0101
Chudayeva, I., & Dmitruk, B. (2022). INTRODUCTION OF ARTIFICIAL INTELLIGENCE ACHIEVEMENTS – A PREREQUISITE FOR LABOR MARKET TRANSFORMATION. 64, 64, 23–34. https://doi.org/10.26565/2524-2547-2022-64-03
Connock, A. (2022a). Media business models. Media Management and Artificial Intelligence, Query date: 2024-05-30 11:17:17, 26–42. https://doi.org/10.4324/9781003213611-4
Connock, A. (2022b). Media Management and Artificial Intelligence. Query date: 2024-05-30 11:17:17. https://doi.org/10.4324/9781003213611
Daase, C., Haertel, C., & Turowski, K. (2024). Explainable Business Intelligence for Video Analytics in Retail. Proceedings of the 26th International Conference on Enterprise Information Systems, Query date: 2024-05-30 11:17:17. https://doi.org/10.5220/0012694600003690
Dahlberg, M. (2023). Digital Business and Tax Law: New and Global Tax Rules for Tech-Giants Using Artificial Intelligence in their Business Models. De Lege, Query date: 2024-05-30 11:17:17. https://doi.org/10.33063/dl.vi.427
Echeberria, A. L. (2022). AI Integration in the Digital Transformation Strategy. Artificial Intelligence for Business, Query date: 2024-05-30 11:17:17, 115–140. https://doi.org/10.1007/978-3-030-88241-9_5
Elorza, M., & Castellano, E. (2022). Customer Data-driven Business Models: A Case Study in the Retail Industry. Proceedings of the 19th International Conference on Smart Business Technologies, Query date: 2024-05-30 11:17:17. https://doi.org/10.5220/0011138800003280
Gantzias, G. (2021). Dynamics of Cultural Management, Artificial Intelligence and Global Regulation: The Values of the “Business Intelligence Culture” Model. Strategic Management in the Age of Digital Transformation, Query date: 2024-05-30 11:17:17. https://doi.org/10.51432/978-1-8381524-3-7_6
Heggernes, T. A. (2021). AI in Business and Education. Artificial Intelligence: Models, Algorithms and Applications, Query date: 2024-05-30 11:17:17, 66–82. https://doi.org/10.2174/9781681088266121010007
Hu, H., Tan, D., Thaichon, P., Wang, B., & Zhu, Z. (2024). Forecasting Grid-Based Market Sales for Retail Business: A Novel Framework by Synthesizing Automatic Machine Learning and Geospatial Intelligence. Query date: 2024-05-30 11:17:17. https://doi.org/10.2139/ssrn.4801735
Hussain, T., Santamaria, L., & Kuzmina, K. (2021). Circular market-places: Exploring retail fashion circular business models, customer value and participation. Query date: 2024-05-30 11:17:17. https://doi.org/10.31880/10344/10216
Karamotchev, P. (2022). BUSINESS MODELS AND PROCUREMENT. Artificial Intelligence, Query date: 2024-05-30 11:17:17, 515–526. https://doi.org/10.4337/9781800371729.00042
Kim, K., Lee, K., & Kwon, O. (2024). A systematic literature review of the empirical studies on STEAM education in Korea: 2011–2019. Disciplinary and Interdisciplinary Education in …, Query date: 2024-05-10 07:14:07. https://doi.org/10.1007/978-3-031-52924-5_6
Kő, A., & Kovács, T. (2023). Artificial/enhanced intelligence. Smart Business and Digital Transformation, Query date: 2024-05-30 11:17:17, 82–89. https://doi.org/10.4324/9781003390312-8
Kundu, N., Mustafa, F., K, H., & Chola, C. (2023). Artificial Intelligence in Retail Marketing. Artificial Intelligence for Business, Query date: 2024-05-30 11:17:17, 86–107. https://doi.org/10.4324/9781003358411-6
Masenya, T. M. (2023). Digital Transformation in SMEs: Developing Digital Business Model Innovations Based on Artificial Intelligence. Business Models and Innovative Technologies for SMEs, Query date: 2024-05-30 11:17:17, 62–84. https://doi.org/10.2174/9789815196719123010006
Mboli, J., Thakker, D., & Mishra, J. (2023). Artificial Intelligence-Powered Decisions Support System for Circular Economy Business Models. Proceedings of the 25th International Conference on Enterprise Information Systems, Query date: 2024-05-30 11:17:17. https://doi.org/10.5220/0011997100003467
Miller, R., & Fang, A. (2023). Business Intelligence Leveraging Regression Models, Artificial Intelligence, Business Intelligence and Strategy. SSRN Electronic Journal, Query date: 2024-05-30 11:17:17. https://doi.org/10.2139/ssrn.4453875
Mohan, S. (2021). Artificial Intelligence in Retail. Demystifying AI for the Enterprise, Query date: 2024-05-30 11:17:17, 193–222. https://doi.org/10.4324/9781351032940-7
Nguyen, D., Boeren, E., Maitra, S., & ... (2024). A review of the empirical research literature on PLCs for teachers in the Global South: Evidence, implications, and directions. … Development in Education, Query date: 2024-05-10 07:14:07. https://doi.org/10.1080/19415257.2023.2238728
Oyekunle, D., & Boohene, D. (2024). DIGITAL TRANSFORMATION POTENTIAL: THE ROLE OF ARTIFICIAL INTELLIGENCE IN BUSINESS. International Journal of Professional Business Review, 9(3). https://doi.org/10.26668/businessreview/2024.v9i3.4499
Panzaru, C., & Negoiță, G. (2022). Artificial Intelligence: Challenges and Opportunities for the Labour Market. The Relevance of Artificial Intelligence in the Digital and Green Transformation of Regional and Local Labour Markets Across Europe, Query date: 2024-05-30 11:17:17, 27–44. https://doi.org/10.5771/9783957104113-27
R., M., & Devi, A. J. (2022). Amazon’s Artificial Intelligence in Retail Novelty—Case Study. International Journal of Case Studies in Business, IT, and Education, Query date: 2024-05-30 11:17:17, 787–804. https://doi.org/10.47992/ijcsbe.2581.6942.0233
Radenković, S. D., Hanić, H., & Bugarčić, M. (2023). Applying Artificial Intelligence in the Digital Transformation of Banking Sector. International Scientific Conference on Digital Transformation in Business: Challenges and New Opportunities, Query date: 2024-05-30 11:17:17. https://doi.org/10.3390/proceedings2023085019
Rajagopal. (2021). Crowd-Based Business Models. Springer International Publishing. https://doi.org/10.1007/978-3-030-77083-9
Rodgers, W., Yeung, F., Odindo, C., & Degbey, W. Y. (2021). Artificial intelligence-driven music biometrics influencing customers’ retail buying behavior. Journal of Business Research, 126(Query date: 2024-05-30 11:17:17), 401–414. https://doi.org/10.1016/j.jbusres.2020.12.039
Rodriguez, M., & Peterson, R. (2024). Artificial intelligence in business-to-business (B2B) sales process: A conceptual framework. Journal of Marketing Analytics, Query date: 2024-05-30 11:17:17. https://doi.org/10.1057/s41270-023-00287-7
Ruehle, C. R. (2020). Investigating Market and Regulatory Forces Shaping Artificial Intelligence Adoptions. Muma Business Review, 4(Query date: 2024-05-30 11:17:17), 177–192. https://doi.org/10.28945/4644
Santos, V., & Bacalhau, L. M. (2023). Digital Transformation of the Retail Point of Sale in the Artificial Intelligence Era. Management and Marketing for Improved Retail Competitiveness and Performance, Query date: 2024-05-30 11:17:17, 200–216. https://doi.org/10.4018/978-1-6684-8574-3.ch010
Shastri, V. (2023). Comparing Statistical, Deep Learning, and Additive Models for Forecasting in the Indian Stock Market. Artificial Intelligence for Capital Markets, Query date: 2024-05-30 11:17:17, 141–158. https://doi.org/10.1201/9781003327745-9
Sio, K., Fraser, B., & Fredline, L. (2024). A contemporary systematic literature review of gastronomy tourism and destination image. Tourism Recreation Research, Query date: 2024-05-10 07:14:07. https://doi.org/10.1080/02508281.2021.1997491
Spanke, M. (2020). Artificial Intelligence. Retail Isn’t Dead, Query date: 2024-05-30 11:17:17, 55–62. https://doi.org/10.1007/978-3-030-36650-6_7
Spiess-Knafl, W. (2022). Introduction to artificial intelligence. Artificial Intelligence and Blockchain for Social Impact, Query date: 2024-05-30 11:17:17, 20–39. https://doi.org/10.4324/9781003218913-2
Stanciu, A., Titu, A. M., & Deac-Suteu, D. V. (2021). Driving Digital Transformation Of Knowledge-Based Organizations Through Artificial Intelligence Enabled Data Centric, Consumption Based, As-A-Service Models. 2021 13th International Conference on Electronics, Computers and Artificial Intelligence (ECAI), Query date: 2024-05-30 11:17:17. https://doi.org/10.1109/ecai52376.2021.9515172
Tachicart, R. (2023). Artificial Intelligence and Its Impact on the Moroccan Labor Market: Job Disruption or Transformation? Query date: 2024-05-30 11:17:17. https://doi.org/10.20944/preprints202309.0193.v1
Torres, A. I., & Beirão, G. (2024). Artificial Intelligence Technologies. Artificial Intelligence Approaches to Sustainable Accounting, Query date: 2024-05-30 11:17:17, 229–248. https://doi.org/10.4018/979-8-3693-0847-9.ch013
Yensabai, C., Ngoenthai, W., Leangarun, T., & Koolpiruck, D. (2023). Digital Retail Shop Services in Cyber-Physical Retail System: A Case Study of Food Business. 2023 Third International Symposium on Instrumentation, Control, Artificial Intelligence, and Robotics (ICA-SYMP), Query date: 2024-05-30 11:17:17. https://doi.org/10.1109/ica-symp56348.2023.10044743
Ying, Z. (2022). Analysis on Transformation Path of Entity Retail Enterprises Under New Retail Background. BCP Business & Management, 23(Query date: 2024-05-30 11:17:17), 746–749. https://doi.org/10.54691/bcpbm.v23i.1435
Zeba, F., & Shaheen, M. (2021). Consumer Insights through Retail Analytics. Artificial Intelligence and Machine Learning in Business Management, Query date: 2024-05-30 11:17:17, 15–27. https://doi.org/10.1201/9781003125129-2