DEVELOPMENT OF AN ONLINE STORE MANAGEMENT SYSTEM: FROM ORDER AUTOMATION TO INTELLIGENT RECOMMENDATIONS
Abstract
The article presents the results of research and development of a modular online store management system aimed at automating business processes and implementing recommendation systems. The main emphasis is placed on integrating modern information technologies, particularly artificial intelligence algorithms, to improve the efficiency of managing orders, products and transactions. The study analyzes existing approaches to online retail automation, identifying their key advantages and disadvantages. The main methods of building recommendation systems were investigated, including content-based filtering, collaborative filtering, and transaction analysis-based approaches. The choice of the Apriori algorithm for implementing the recommendation system, which allows effective identification of associative rules without the need to store personal purchase history, is justified. The proposed system architecture is based on a modular approach that provides flexibility, scalability, and the ability to adapt functionality to specific business needs. Integration with the recommendation system allows generating personalized offers based on transaction data, significantly improving the speed and accuracy of recommendations. The article also details the mechanism for updating the database to ensure transaction relevance and optimize the volume of stored data. The conducted SWOT analysis of the system confirmed its potential for implementation in online stores of various scales, especially for niche markets. The research results demonstrate the effectiveness of the proposed approach to business process automation, which allows increasing productivity, reducing costs, and improving customer experience. The conclusions point to the possibility of further system improvement through API integration for external platforms, expanding analytics functionality, and using machine learning algorithms to increase recommendation accuracy. The proposed system is a promising solution for modern e-commerce, providing a balance between functionality, ease of use, and implementation costs.
References
Singh, Nehul; Chouhan, Satyendra (2021): Role of Artificial Intelligence for Development of IntelligentBusiness Systems. 2021 IEEE International Symposium on Smart Electronic Systems (iSES), 2021, 373-377. DOI: https://doi.ieeecomputersociety.org/10.1109/iSES52644.2021.00092 .
Zhang, M., Chen, Y. (2018) Link Prediction Based on Graph Neural Networks. 32nd Conference on Neural Information Processing Systems (NeurIPS 2018), Montréal, 3-8 December 2018, 5171-5181.
Lari H., Vaishnava K., Manu K. (2022). Artifical Intelligence in E-Commerce: Applications, Implications and Challenges. Asian Journal of Management, (July). DOI:10.52711/2321-5763.2022.00041.
Сичова, О., Осипенко, Н., Петрішина, Т. (2023). Цифровий маркетинг як інструмент сталого розвитку бізнесу. Економіка та суспільство, (50). DOI: https://doi.org/10.32782/2524-0072/2023-50-32.
Жуковська, В., Климанський, В. (2024). Трансформація бізнес-процесів на підприємстві електронної торгівлі: вплив цифрових технологій. Економіка та суспільство, (66). DOI: https://doi.org/10.32782/2524-0072/2024-66-69.
Орєхов, Д. (2024). Застосування штучного інтелекту в управлінні сучасним підприємством. Економіка та суспільство, (64). DOI: https://doi.org/10.32782/2524-0072/2024-64-143.
Струнгар, А. (2024). Вплив штучного інтелекту на стратегії цифрового маркетингу: поточні можливості та перспективи розвитку. Економіка та суспільство, (62). DOI: https://doi.org/10.32782/2524-0072/2024-62-160.
Hryshko, V., Zinchenko, I. (2023). Synergy of ai and business as a factor of management efficiency in the context of technology development. Science Journal «Economics and Region», 4(91), 223-229. DOI: https://doi.org/10.26906/EiR.2023.4(91).3216.
Жосан, Г. В., Кириченко, Н. В. (2022). Управління цифровізацією бізнес-процесів діяльності підприємства. Economic Synergy, (4), 82–91. DOI: https://doi.org/10.53920/ES-2022-4-6.
Каліна, І., Шуляр, Н., Ліщенко, А. (2024). Операційні процеси управління циклом замовлення в логістичній діяльності. Економіка та суспільство, (64). DOI: https://doi.org/10.32782/2524-0072/2024-64-75.
Чернишова, О.О., Домашенко, С.В., Домашенко Д.Г. (2024). Вплив штучного інтелекту на бізнес-процеси з метою оптимізації та покращення ефективності роботи організації. Вчені записки Таврійського національного університету імені В.І. Вернадського. Серія: Технічні науки, 35(74), №2, 196-204. DOI: https://doi.org/10.32782/2663-5941/2024.2/27.
Singh, Nehul; Chouhan, Satyendra (2021): Role of Artificial Intelligence for Development of IntelligentBusiness Systems, 2021 IEEE International Symposium on Smart Electronic Systems (iSES), 2021, 373-377. DOI: https://doi.ieeecomputersociety.org/10.1109/iSES52644.2021.00092 .
Zhang, M., Chen, Y. (2018) Link Prediction Based on Graph Neural Networks. 32nd Conference on Neural Information Processing Systems (NeurIPS 2018), Montréal, 3-8 December 2018, 5171-5181.
Lari H., Vaishnava K., Manu K. (2022). Artifical Intelligence in E-Commerce: Applications, Implications and Challenges. Asian Journal of Management, (July). DOI:10.52711/2321-5763.2022.00041.
Sychova, O., Osypenko, N., & Petrishyna, T. (2023) Tsyfrovyi marketynh yak instrument staloho rozvytku biznesu [Digital marketing as a tool for sustainable business development]. Ekonomika ta suspilstvo – Economy and Society, (50). DOI: https://doi.org/10.32782/2524-0072/2023-50-32. (in Ukrainian)
Zhukovska, V., & Klymanskyi, V. (2024) Transformatsiia biznes-protsesiv na pidpryiemstvi elektronnoi torhivli: vplyv tsyfrovykh tekhnolohii [Transformation of business processes in e-commerce enterprise: the impact of digital technologies]. Ekonomika ta suspilstvo – Economy and Society, (66). DOI: https://doi.org/10.32782/2524-0072/2024-66-69. (in Ukrainian)
Oriekhov, D. (2024) Zastosuvannia shtuchnoho intelektu v upravlinni suchasnym pidpryiemstvom [Application of artificial intelligence in modern enterprise management]. Ekonomika ta suspilstvo – Economy and Society, (64). DOI: https://doi.org/10.32782/2524-0072/2024-64-143. (in Ukrainian)
Strunhar, A. (2024) Vplyv shtuchnoho intelektu na stratehii tsyfrovoho marketynhu: potochni mozhlyvosti ta perspektyvy rozvytku [The impact of artificial intelligence on digital marketing strategies: current opportunities and development prospects]. Ekonomika ta suspilstvo – Economy and Society, (62). DOI: https://doi.org/10.32782/2524-0072/2024-62-160. (in Ukrainian)
Hryshko, V., Zinchenko, I. (2023). Synergy of ai and business as a factor of management efficiency in the context of technology development. Science Journal «Economics and Region», 4(91), 223-229. DOI: https://doi.org/10.26906/EiR.2023.4(91).3216.
Zhosan, H. V., & Kyrychenko, N. V. (2022) Upravlinnia tsyfrovizatsiieiu biznes-protsesiv diialnosti pidpryiemstva [Management of digitalization of business processes of enterprise activity]. Economic Synergy, (4), 82-91. DOI: https://doi.org/10.53920/ES-2022-4-6. (in Ukrainian)
Kalina, I., Shuliar, N., & Lishchenko, A. (2024) Operatsiini protsesy upravlinnia tsyklom zamovlennia v lohistychnii diialnosti [Operational processes of order cycle management in logistics activities]. Ekonomika ta suspilstvo – Economy and Society, (64). DOI: https://doi.org/10.32782/2524-0072/2024-64-75. (in Ukrainian)
Chernyshova, O.O., Domashenko, S.V., & Domashenko, D.H. (2024) Vplyv shtuchnoho intelektu na biznes-protsesy z metoiu optymizatsii ta pokrashchennia efektyvnosti roboty orhanizatsii [The influence of artificial intelligence on business processes to optimize and improve the efficiency of the organization]. Vcheni zapysky Tavriiskoho natsionalnoho universytetu imeni V.I. Vernadskoho. Seriia: Tekhnichni nauky – Scientific notes of V.I. Vernadsky Taurida National University. Series: Technical Sciences, 35(74)(2), 196-204. DOI: https://doi.org/10.32782/2663-5941/2024.2/27. (in Ukrainian)
This work is licensed under a Creative Commons Attribution 4.0 International License.
