Share:


The EU e-commerce market in a pandemic context – linking demographic factors and territorial convergence

    Ancuța Stângaciu Affiliation
    ; Laura Țimiraș Affiliation
    ; Luminița Zaiț Affiliation
    ; Bogdan Nichifor Affiliation
    ; Marcela Danu Affiliation
    ; Eugenia Harja Affiliation

Abstract

This article presents a comprehensive analysis of the European Union’s e-commerce market within the context of the COVID-19 pandemic. It examines the correlation between demographic factors and the territorial convergence of e-commerce activities across EU member states. By leveraging empirical data and employing the General Linear Model – Repeated Measures (GLM-RM) to analyze temporal changes in the phenomena of interest across EU countries, the study provides a nuanced understanding of the market’s evolution during and after the pandemic. The research reveals a notable expansion in the EU’s e-commerce market value, leading to a reduction in economic disparities among member states. It highlights the role of consumer demographics in shaping online shopping behavior, with age being a pivotal factor that demonstrates significant variations. Additionally, the study delves into the differential performance of various product categories, reflecting a pattern of selective sectoral convergence. A key finding is the pandemic’s dual role as a disruptor and an accelerator for digital integration, particularly in enhancing digital inclusivity in less economically developed EU regions. This study contributes to the broader discourse on e-commerce market dynamics in times of global crises, offering valuable insights for policymakers and business strategists.

Keyword : e-commerce, demographic factors, online purchases, EU, share of e- commerce in GDP, convergence, pandemic period

How to Cite
Stângaciu, A., Țimiraș, L., Zaiț, L., Nichifor, B., Danu, M., & Harja, E. (2024). The EU e-commerce market in a pandemic context – linking demographic factors and territorial convergence. Journal of Business Economics and Management, 25(1), 21–46. https://doi.org/10.3846/jbem.2024.20705
Published in Issue
Jan 26, 2024
Abstract Views
699
PDF Downloads
604
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Al Fagih, K. (2016). An empirical analysis of factors predicting the behavioral intention to adopt Internet shopping technology among non-shoppers in a developing country context: Does gender matter? Journal of Retailing and Consumer Services, 30, 140–164. https://doi.org/10.1016/j.jretconser.2016.01.016

Alaimo, L. S., Fiore, M., & Galati, A. (2020). How the COVID-19 pandemic is changing online food shopping human behaviour in Italy. Sustainability, 12(22), Article 9594. https://doi.org/10.3390/su12229594

Alkan, Ö., Küçükoglu, H., & Tutar, G. (2021). Modeling of the factors affecting e-commerce use in Turkey by categorical data analysis. International Journal of Advanced Computer Science and Applications, 12(1), 95–105. https://doi.org/10.14569/IJACSA.2021.0120113

Al-Tit, A. A. (2020). E-commerce drivers and barriers and their impact on e-customer loyalty in Small and Medium-Sized Enterprises (SMEs). Business: Theory and Practice, 21(1), 146–157. https://doi.org/10.3846/btp.2020.11612

Assaker, G. (2020). Age and gender differences in online travel reviews and user-generated-content (UGC) adoption: Extending the technology acceptance model (TAM) with credibility theory. Journal of Hospitality Marketing & Management, 29(4), 428–449. https://doi.org/10.1080/19368623.2019.1653807

Barro, R. J., & Sala-i-Martin, X. (1992). Convergence. Journal of Political Economy, 100(2), 223–251. https://doi.org/10.1086/261816

Cárdenas, I., Beckers, J., & Vanelslander, T. (2017). E-commerce last-mile in Belgium: Developing an external cost delivery index. Research in Transportation Business & Management, 24, 123–129. https://doi.org/10.1016/j.rtbm.2017.07.006

Ceocea, C., Nichifor, B., & Timiras, L. (2020). Brief analisys on the impact of COVID-19 on the European economy. Studies And Scientific Researches. Economics Edition, 32, 129–138. https://doi.org/10.29358/sceco.v0i0.473

Chang, V., Liu, O., Barbole, K. V., Xu, Q. A., Gao, X. J., & Tabrizi, W. (2023). Customer behavioral trends in online grocery shopping during COVID-19. Journal of Global Information Management, 31(1), 1–27. https://doi.org/10.4018/JGIM.317081

Clarke, G., Thompson, C., & Birkin, M. (2015). The emerging geography of e-commerce in British retailing. Regional Studies, Regional Science, 2(1), 371–391. https://doi.org/10.1080/21681376.2015.1054420

Cristobal-Fransi, E., Martin-Fuentes, E., & Daries-Ramon, N. (2015). Behavioural analysis of subjects interacting with information technology: Categorising the behaviour of e-consumers. International Journal of Services Technology and Management, 21, 163–182. https://doi.org/10.1504/IJSTM.2015.071121

Davidavičienė, V., & Davidavičius, S. (2022). Consumer perception of innovative solutions in e-commerce. International Journal of Learning and Change, 14(5–6), 588–599. https://doi.org/10.1504/IJLC.2022.126485

Davidavičienė, V., Markus, O., & Davidavičius, S. (2020). Identification of the opportunities to improve customer’s experience in e-commerce. Journal of Logistics, Informatics and Service Science, 7(1), 42–57. https://doi.org/10.33168/LISS.2020.0104

Davidavičienė, V., Raudeliūnienė, J., Jonytė-Zemlickienė, A., & Tvaronavičienė, M. (2021). Factors affecting customer buying behavior in online shopping. Marketing and Management of Innovations, 4, 11–19. https://doi.org/10.21272/mmi.2021.4-01

Devi, M., Das, L., & Baruah, M. (2019). Inclination towards online shopping – A changing trend among the consumers. Journal of Economics, Management and Trade, 25(2), 1–11. https://doi.org/10.9734/jemt/2019/v25i230190

Dewalska-Opitek, A., Bilińska, K., & Cierpiał-Wolan, M. (2022). The application of the soft modeling method to evaluate changes in customer behavior towards e-commerce in the time of the global COVID-19 pandemic. Risks, 10(3), Article 62. https://doi.org/10.3390/risks10030062

Dewi, C., Mohaidin, Z., & Murshid, M. (2019). Determinants of online purchase intention: A PLS-SEM approach: Evidence from Indonesia. Journal of Asia Business Studies. https://doi.org/10.1108/JABS-03-2019-0086

Doolin, B., Dillon, S., Thompson, F., & Corner, J. L. (2005). Perceived risk, the internet shopping experience and online purchasing behavior: A New Zealand perspective. Journal of Global Information Management, 13(2), 66–88. https://doi.org/10.4018/jgim.2005040104

Eurostat. (2023). Database. Retrieved April 13, 2023, from https://ec.europa.eu/eurostat/data/database

Gao, Y., Zang, L., & Sun, J. (2018). Does computer penetration increase farmers’ income? An empirical study from China. Telecommunications Policy, 42(5), 345–360. https://doi.org/10.1016/j.telpol.2018.03.002

Ghita, S. I., Saseanu, A. S., Gogonea, R.-M., & Grosu, R. M. (2022). Online shopping profiles within European countries during the COVID-19 pandemic. Transformations in Business & Economics, 21(2(56)), 21–40.

Gomes, S., & Lopes, J. M. (2022). Evolution of the online grocery shopping experience during the COVID-19 pandemic: Empiric study from Portugal. Journal of Theoretical and Applied Electronic Commerce Research, 17(3), 909–923. https://doi.org/10.3390/jtaer17030047

Handa, M., & Gupta, N. (2014). A study of the relationship between shopping orientation and online shopping behavior among Indian youth. Journal of Internet Commerce, 13(1), 22–44. https://doi.org/10.1080/15332861.2014.918437

Herrando, C., Jimenez-Martinez, J., & Martin-De Hoyos, M. J. (2019). Tell me your age and I tell you what you trust: The moderating effect of generations. Internet Research, 29(4), 799–817. https://doi.org/10.1108/IntR-03-2017-0135

Higueras-Castillo, E., Liébana-Cabanillas, F. J., & Villarejo-Ramos, Á. F. (2023). Intention to use e-commerce vs physical shopping. Difference between consumers in the post-COVID era. Journal of Business Research, 157, Article 113622. https://doi.org/10.1016/j.jbusres.2022.113622

Iancu, A. (2006). Problema convergentei economice. Theoretical and Applied Economics, 4(S499), 43–64.

Jain, N. K., Gajjar, H., & Shah, B. J. (2021). Electronic logistics service quality and repurchase intention in e-tailing: Catalytic role of shopping satisfaction, payment options, gender and returning experience. Journal of Retailing and Consumer Services, 59(C). https://ideas.repec.org//a/eee/joreco/v59y2021ics0969698920313680.html

Jasek, P., Vrana, L., Sperkova, L., Smutny, Z., & Kobulsky, M. (2019). Comparative analysis of selected probabilistic customer lifetime value models in online shopping. Journal of Business Economics and Management, 20(3), 398–423. https://doi.org/10.3846/jbem.2019.9597

Jasińska-Biliczak, A. (2022). E-commerce from the customer panel: The phenomenon of the pandemic increase and future challenge. Business, Management and Economics Engineering, 20(1), 139–151. https://doi.org/10.3846/bmee.2022.16752

Jílková, P., & Králová, P. (2021). Digital consumer behaviour and eCommerce trends during the COVID-19 crisis. International Advances in Economic Research, 27(1), 83–85. https://doi.org/10.1007/s11294-021-09817-4

Kannan, P. K. (2020). Introduction to the special section: Research for the new normal. International Journal of Research in Marketing, 37(3), 441–442.

Kshetri, N. (2018). Rural e-commerce in developing countries. IT Professional, 20(2), 91–95. https://doi.org/10.1109/MITP.2018.021921657

Liébana-Cabanillas, F., Singh, N., Kalinic, Z., & Carvajal-Trujillo, E. (2021). Examining the determinants of continuance intention to use and the moderating effect of the gender and age of users of NFC mobile payments: A multi-analytical approach. Information Technology and Management, 22(2), 133–161. https://doi.org/10.1007/s10799-021-00328-6

Lissitsa, S., & Kol, O. (2016). Generation X vs. Generation Y – A decade of online shopping. Journal of Retailing and Consumer Services, 31, 304–312. https://doi.org/10.1016/j.jretconser.2016.04.015

Malik, G., & Guptha, A. (2013). An empirical study on behavioral intent of consumers in online shopping. Business Perspectives and Research, 2(1), 13–28. https://doi.org/10.1177/2278533720130102

Mbah, C. C., Akpan, A. O., & Odike, M. (2019). Effect of education on online shopping behavioir in Nigeria. Advance Journal of Economics and Marketing Research, 4(4), 24–31. https://aspjournals.org/ajemr/index.php/ajemr/article/view/12

National Bank of Romania. (2018). Annual Report 2017. www.bnr.ro

Nemec, A. F. L. (1995). Analysis of repeated measures and time series: An introduction with forestry examples. Biometrics Information Handbook No. 6.

Oghazi, P., Karlsson, S., Hellström, D., Mostaghel, R., & Sattari, S. (2021). From Mars to Venus: Alteration of trust and reputation in online shopping. Journal of Innovation & Knowledge, 6(4), 197–202. https://doi.org/10.1016/j.jik.2020.06.002

Palan, K., Gentry, J., Chun, S., Commuri, S., Fischer, E., Jun, S., Mcginnis, L., & Strahilevitz, M. (2011). Gender identity in consumer behavior research: A literature review and research agenda.

Park, S., & Lee, D. (2017). An empirical study on consumer online shopping channel choice behavior in omni-channel environment. Telematics and Informatics, 34(8), 1398–1407. https://doi.org/10.1016/j.tele.2017.06.003

Raudeliūnienė, J., Davidavičienė, V., Tvaronavičienė, M., & Radeckytė, V. (2018). A study of success factors of women’s leadership in e-commerce. Terra Economicus, 16(3), 131–149. https://doi.org/10.23683/2073-6606-2018-16-3-131-149

Sánchez-Torres, J. A., Arroyo-Cañada, F. J., Montoya-Restrepo, L. A., & Rivera-González, J. A. (2017). Moderating effect of socioeconomic factors and educational level on electronic purchasing in Colombia. Tékhne, 15(1), 26–34. https://doi.org/10.1016/j.tekhne.2017.07.001

Sebastianelli, R., Tamimi, N., & Rajan, M. (2008). Perceived quality of online shopping: Does gender make a difference? Journal of Internet Commerce, 7(4), 445–469. https://doi.org/10.1080/15332860802507164

Seetharaman, P. (2020). Business models shifts: Impact of COVID-19. International Journal of Information Management, 54, Article 102173. https://doi.org/10.1016/j.ijinfomgt.2020.102173

Simon, H. (2009). The crisis and customer behaviour: Eight quick solutions. Journal of Customer Behaviour, 8(2), 177–186. https://doi.org/10.1362/147539209X459796

Statista. (2022). Online shopping in Europe – statistics and facts. Retrieved March 25, 2023, from https://www.statista.com/topics/3881/online-shopping-in-europe/

Svatosova, V. (2022). Changes in online shopping behavior in the Czech Republic during the COVID-19 crisis. Journal of Competitiveness, 14(1), 155–175. https://doi.org/10.7441/joc.2022.01.09

Timiras, L. C., & Nichifor, B. (2015). Landmarks on the evolution of e-commerce in the European Union. Studies And Scientific Researches. Economics Edition, 21, 151–160. https://doi.org/10.29358/sceco.v0i21.316

Trocchia, P. J., & Janda, S. (2000). A phenomenological investigation of Internet usage among older individuals. Journal of Consumer Marketing, 17(7), 605–616. https://doi.org/10.1108/07363760010357804

Tyrväinen, O., & Karjaluoto, H. (2022). Online grocery shopping before and during the COVID-19 pandemic: A meta-analytical review. Telematics and Informatics, 71, Article 101839. https://doi.org/10.1016/j.tele.2022.101839

Ünver, S., & Alkan, Ö. (2021). Determinants of e-commerce use at different educational levels: Empirical evidence from Turkey. International Journal of Advanced Computer Science and Applications (IJACSA), 12(3), 40–49. https://doi.org/10.14569/IJACSA.2021.0120305

Wu, C., Zhou, X., & Song, M. (2016). Sustainable consumer behavior in China: An empirical analysis from the Midwest regions. Journal of Cleaner Production, 134(A), 147–165. https://doi.org/10.1016/j.jclepro.2015.06.057

Yuan, J., Lu, Y., Ferrier, R. C., Liu, Z., Su, H., Meng, J., Song, S., & Jenkins, A. (2018). Urbanization, rural development and environmental health in China. Environmental Development, 28, 101–110. https://doi.org/10.1016/j.envdev.2018.10.002