Marketing and Management of Innovations

ISSN (print) – 2218-4511 

ISSN (online) – 2227-6718

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The language of publication is English. 

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Oleksii Lyulyov

Sumy State University | Ukraine

The Development of The E-Commerce Market in Poland in the Conditions of Intensification of Migration Processes

Tetiana Zatonatska 1,*,   , Yana Fareniuk 1, , Vytautas Juscius 2, , Jurgita Martinkiene 3, , Olena Maksymchuk 1,  
  1. Department of Economic Cybernetics, Faculty of Economics, Taras Shevchenko National University of Kyiv, Ukraine
  2. Department of Economics, Klaipeda University, Lithuania
  3. Lithuania Business College, Lithuania

* Corresponding author

DOI: https://doi.org/10.21272/mmi.2024.1-13

Pages: 160-177

Received: 20 September 2023

Revised: 15 January 2024

Accepted: 15 March 2024

Abstract

The impact of the war in Ukraine and migration has affected the e-commerce markets of the recipient countries, presenting both opportunities, in the form of an increased consumer base, and challenges, such as the lack of a clear development vision. This paper aims to investigate the influence of migration processes on the development of e-commerce in Poland and examine the feasibility of using forecasting methods by e-commerce companies under these conditions for future activity planning. To fulfill the research objective, the following tasks were addressed: investigating the current state of e-commerce development influenced by migration processes; exploring modern migration processes and their impact on global economies; assessing the impact of migration from Ukraine on the Polish market; and analyzing a Polish online store to develop a model for forecasting data and planning activities under the influence of migration processes. To achieve this goal, three models were constructed: a multiple regression model to assess the level of migration processes’ influence on e-commerce; a neural network to forecast sales for a Polish e-commerce store; and cluster analysis to identify clusters of goods most affected by migration processes. The study analyzed the nuances of modern migration processes and assessed the reverse effect of migration as a driver of e-commerce development. Migration stimulates e-commerce by altering consumer behavior and logistics routes, increasing exports and imports, and fostering the spread of digital entrepreneurship. Using data from a Polish online store, the study modeled the impact of market changes on the company’s operations and identified the most significant factors. Thus, the analysis explored the impact of migration on e-business in Poland through constructed models. Regression analysis revealed that migration processes have contributed to the development of the Polish online store’s sales, thanks to the increase in migrant consumers and rising price levels. A neural network was developed with machine learning, incorporating macroeconomic and demographic factors into its forecasting typology. Cluster analysis was employed to examine the online store’s assortment, identifying clusters by sales volume and migrants’ influence. The analysis determined that, following the onset of the migration movement, categories experiencing a surge in demand from refugees, such as baby food products, appliances, telephones, furniture, and communication devices, saw the most significant growth.

Keywords: e-commerce; migration; forecasting; modeling; machine learning; big data; Data Science: regression analysis: clustering; neural network.

How to Cite: Zatonatska, T., Fareniuk, Y., Juscius, V., Martinkiene, Ju. & Maksymchuk, O. (2024). The Development of the E-Commerce Market in Poland in the Conditions of Intensification of Migration Processes. Marketing and Management of Innovations, 15(1), 160–177. https://doi.org/10.21272/mmi.2024.1-13

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References

  1. Bosma, N., Hill, S., Ionescu-Somers, A., Kelley, D., Levie, J., & Tarnawa, A. (2020). GEM Global Report 2019/2020. The Global Entrepreneurship Monitor. [Link]
  2. Comeau, N. (2019). Predictive analytics in migration. Progress Solved. [Link]
  3. Committee on Payments and Market Infrastructures (2022). Interlinking payment systems and the role of application programming interfaces: a framework for cross-border payments. [Link]
  4. Cottier, T., & Shingal, A. (2021). Migration, International Trade and Foreign Direct Investment in the Twenty-first Century: Towards a New Common Concern of Humankind. International Organization for Migration (IOM). [Link]
  5. Czaika, M., & Reinprecht, C. (2020). Drivers of migration: A synthesis of knowledge 2020. International Migration Institute. [Link]
  6. Deng, F., Lin, Y., & Jiang, X. (2023). Influence mechanism of consumers’ characteristics on impulsive purchase in E-commerce livestream marketing. Computers in Human Behavior, 148, article 107894. [Google Scholar] [CrossRef]
  7. Duan, C., Kotey, B., & Sandhu, K. (2020). Digital Entrepreneurship for Immigrants: Motivations, Strategies, Ecosystems, and Performance. In K. Sandhu (Ed.), Leadership, Management, and Adoption Techniques for Digital Service Innovation (pp. 162-181). IGI Global. [Google Scholar] [CrossRef]
  8. EcommerceDB (2022). eCommerce market in Poland. [Link]
  9. Elia, G., Margherita, A., & Passiante, G. (2019). Digital entrepreneurship ecosystem: How digital technologies and collective intelligence are reshaping the entrepreneurial process. Technological Forecasting and Social Change, 150(1). [Google Scholar] [CrossRef]
  10. Englery, P., Honjo, K., MacDonald, M, Piazza, R., & Sher, G. (2020). The macroeconomic effects of global migration. International monetary fund. IMF. [Link]
  11. Esipova, N., Pugliese, A., & Ray, J. (2018). More Than 750 Million Worldwide Would Migrate If They Could. Gallup. [Link]
  12. Global Migration Group (2017). Handbook for Improving the production and use of Migration Data for Development. [Link]
  13. Government of the United States of America (2021). Report on the Impact of Climate Change on Migration 2021. [Link]
  14. Gumzej, R. (2021). E-Commerce. In Intelligent Logistics Systems for Smart Cities and Communities. Springer. pp. 53–58. [Link]
  15. Huang, L., Huang, Y., Huang, R., Xie, G., & Cai, W. (2022). Factors influencing returning migrants’ entrepreneurship intentions for rural E-commerce: an empirical investigation in China. Sustainability, 14(6), 3682. [Google Scholar] [CrossRe]
  16. Internal Displacement Monitoring Centre (IDMC) (2021). Global Report on Internal Displacement 2021. [Link]
  17. IOM (2022). World Migration Report 2022. International Organization for Migration. [Link]
  18. Kaczmarska, R., & Ono M. (2022). Migration Trends and Families. Division for inclusive social development. united nations. [Link]
  19. Kemp, S. (2023). Digital 2023: global overview report. [Link]
  20. Koczan, Z., Peri, G., Pinat, M., & Rozhkov, D. (2021). The Impact of International Migration on Inclusive Growth: A Review. International Organization for Migration. [Link]
  21. Lin, Y. (2019). E-urbanism: E-commerce, migration, and the transformation of Taobao villages in urban China. Cities, 91, 202-212. [Google Scholar] [CrossRef].
  22. Molodan, V. (2023). Landmark on your own. How Nova Post entered the Polish market. [Link]
  23. O’Trakoun, J. (2022). Business forecasting during the pandemic. Business Economics, 57(3), 95-110. [Google Scholar] [CrossRef]
  24. Operational data portal (2023). Ukraine Refugee Situation. [Link]
  25. Pan, C. L., Yu, Y., Zhou, W., Zheng, W., Ou, C., & Xu, H. (2021, March). Research on Digitizing and E-commerce in the Era of the Digital Economy. In 2021 2nd International Conference on E-Commerce and Internet Technology (ECIT)(pp. 189-192). [Google Scholar][CrossRef]
  26. Petropoulos, F., Apiletti, D., Assimakopoulos, V., Babai, M. Z., Barrow, D. K., Taieb, S. B., … & Ziel, F. (2022). Forecasting: theory and practice. International Journal of Forecasting, 38(3), 705-871. [Google Scholar] [CrossRef]
  27. Polat, C. (2007). The Role of Forecasting and Its Potential for Functional Management: A Review from the Value-Chain Perspective. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 9, 373. 2007. [Link]
  28. Portes, A., Haller, W. J., & Guarnizo, L. E. (2002). Transnational entrepreneurs: An alternative form of immigrant economic adaptation. American sociological review, 67(2), 278-298. [Google Scholar] [CrossRef]
  29. PWC (2023). Development prospects for the e-commerce market in Poland in 2018–2027. [Link]
  30. Ramzi, F. (2022). How customs and immigration officials can benefit from data analytics. IO World Asia. [Link]
  31. Serwis Rzeczypospolitej Polskiej (2022). Ochrona międzynarodowa w 2021. [Link]
  32. Shekhar, A., Barkbu, B., Batini, N., Berger, H., Detragiache, E., Dizioli, A., & Ebeke, C. (2016). The Refugee Surge in Europe: Economic Challenges. National Institute Economic Review IMF, 235 (1), F16–F31. [Link]
  33. Singh, G., Kaur, H., & Singh, A. (2018, August). Dropshipping in e-commerce: A perspective. In Proceedings of the 2018 9th International Conference on E-business, Management and Economics(pp. 7-14). [Google Scholar] [CrossRef]
  34. Statista (2023a). Number of Ukrainian refugees in Poland 2022-2023. [Link]
  35. Statista (2023b). Retail e-commerce sales worldwide from 2014 to 2026. [Link]
  36. Statistics Poland (2023). Gross Domestic Product of Poland. [Link]
  37. Tang, L., Li, J., Du, H., Li, L., Wu, J., & Wang, S. (2022). Big data in forecasting research: a literature review. Big Data Research, 27, 100289.[Google Scholar] [CrossRef]
  38. Tucha, O., Spivak, I., Bondarenko, O., & Pogarska, O. (2022). Staff Discussion Note: Impact of Ukrainian Migrants on Economies of Recipient Countries. NBU. [Link]
  39. UNHCR (2022). Refugee Statistics. [Link]
  40. Vegesana, S. (2018). Predictive analytics for classification of immigration visa applications: A discriminative machine learning approach. Kansas State University. [Link]
  41. Yevmishkina, O.L. (2016). The concept of forecasting and the relationship between forecasting and state strategic planning. State and regions, 3(55), 28-32. [Link]
  42. Zatonatska, T., Fareniuk, Y., Zatonatskiy, , Dluhopolska, T., Poltoratska, A. (2023). The Influence of Migration Processes Caused by the Russian- Ukrainian War on the Development of E-Commerce in Ukraine. Conference: IT&I-WS 2022: Workshops at Information Technology and Implementation 2022. [Link]
  43. Zatonatska, T., Liashenko, O., Fareniuk, Y., Dluhopolskyi, O., Dmowski, A., & Cichorzewska, M. (2022). The migration influence on the forecasting of health care budget expenditures in the direction of sustainability: Case of Ukraine. Sustainability, 14(21), 14501. [Google Scholar] [CrossRef]

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