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Mobile buying bahavior during the Covid-19 pandemic –the case of Poland

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EN
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EN
Purpose: This pilot study aimed to understand the mobile buying behavior of Polish respondents in terms of the number of transactions per month during the Covid-19 pandemic time. The respondents' gender and place of residence were taken into consideration as chosen socio-demographic characteristics. Design/methodology/approach: The field survey method was applied to collect the primary data. Descriptive and inferential statistics that include the matched-pair test, the Wilcoxon signed-rank test, and the chi-square test of independence were applied for the primary data analysis. Findings: According to the chi-square test of independence, such socio-demographic characteristics as gender, place of residence, women’s place of residence and men’s place of residence in relation to mobile buying behavior are independent. The results of the matched-pair test and the Wilcoxon signed-rank test in the large and medium cities show that there is a significant difference in the average number of mobile shopping transactions per month before and during pandemic time. Research limitations/implications: The authors suggest conducting the same analysis with a larger sample size to generalize the phenomena. Practical implications: In order to stay competitive on the market, enterprises should constantly develop mobile distribution channels. Moreover, while communicating with a mobile shopper, enterprises can create similar messages, despite the gender and / or place of residence of the receivers. Originality/value: The findings will be helpful to FMCG-related marketing decision-makers and mobile shopping-related app developers.
Rocznik
Tom
Strony
131--143
Opis fizyczny
Bibliogr. 21 poz.
Bibliografia
  • 1. Çelik, S., Köse, G. G. (2021). Mediating effect of intolerance of uncertainty in the relationship between coping styles with stress during pandemic (COVID-19) process and compulsive buying behavior. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 110, 110321, https://doi.org/10.1016/j.pnpbp.2021.110321.
  • 2. Chen, T., Jin, Y., Yang, J., Cong, G. (2022). Identifying emergence process of group panic buying behavior under the COVID-19 pandemic. Journal of Retailing and Consumer Services, 67, 102970, https://doi.org/10.1016/j.jretconser.2022.102970.
  • 3. Chopdar, P. K., Paul, J., Korfiatis, N., Lytras, M. D. (2022). Examining the role of consumer impulsiveness in multiple app usage behavior among mobile shoppers. Journal of Business Research, 140, 657-669, https://doi.Org/10.1016/j.jbusres.2021.11.031.
  • 4. De Canio, F., Fuentes-Blasco, M. (2021). I need to touch it to buy it! How haptic information influences consumer shopping behavior across channels. Journal of Retailing and Consumer Services, 61, 102569, https://doi.org/10.1016/j.jretconser.2021.102569.
  • 5. Eriksson, N., Stenius, M. (2022). Online grocery shoppers due to the Covid-19 pandemic— An analysis of demographic and household characteristics. Procedia Computer Science, 196, 93-100, https://doi.org/10.1016/j.procs.2021.11.077.
  • 6. Euromonitor. The World Beyond the Pandemic. Retrieved from https://www.euromonitor.com/the-world-beyond-the-pandemic/report, 30.10.2022.
  • 7. Frishammar, J., Cenamor, J., Cavalli-Björkman, H., Hernell, E., Carlsson, J. (2018). Digital strategies for two-sided markets: A case study of shopping malls. Decision Support Systems, 108, 34-44, https://doi.org/10.1016/j.dss.2018.02.003.
  • 8. Gao, X., Shi, X., Guo, H., Liu, Y. (2020). To buy or not buy food online: the impact of the COVID-19 epidemic on the adoption of e-commerce in China. PLoS One, 15(8).
  • 9. Guo, H., Liu, Y., Shi, X., Chen, K.Z. (2020). The role of e-commerce in the urban food system under COVID-19: lessons from China. China Agric. Econ. Rev. 2020;13(2), 436455.
  • 10. Hou, J., Elliott, K. (2021). Mobile shopping intensity: Consumer demographics and motivations. Journal of Retailing and Consumer Services, 63, 102741, https://doi.org/10.1016/j.jretconser.2021.102741.
  • 11. influentialpoints.com. Wilcoxon matched pairs signed rank test: Use & misuse—Versus paired t-test, distribution of differences, symmetricality, power. Retrieved from https://influentialpoints.com/Training/Wilcoxon_matched_pairs_signed_rank_test_use_an d_misuse.htm, 26.10.2022.
  • 12. Jiang, Y., Stylos, N. (2021). Triggers of consumers’ enhanced digital engagement and the role of digital technologies in transforming the retail ecosystem during COVID-19 pandemic. Technological Forecasting and Social Change, 172, 121029, https://doi.org/10.1016/j.techfore.2021.121029.
  • 13. Kassas, B., Nayga, R. M. (2021). Understanding the importance and timing of panic buying among U.S. Households during the COVID-19 pandemic. Food Quality and Preference, 93, 104240. https://doi.org/10.1016/j.foodqual.2021.104240.
  • 14. Li, X., Zhao, X., Xu, W. (Ato), Pu, W. (2020). Measuring ease of use of mobile applications in e-commerce retailing from the perspective of consumer online shopping behaviour patterns. Journal of Retailing and Consumer Services, 55, 102093, https://doi.org/10.1016/j.jretconser.2020.102093.
  • 15. Li, J., Hallsworth, A.G., Coca- Stefaniak, J.A. (2020). Changing grocery shopping behaviours among Chinese consumers at the outset of the COVID- 19 outbreak. Tijdschr. Econ. Soc. Geogr.;111(3), 574-583.
  • 16. McKinsey and Company, Emerging consumer trends in a post COVID 19 world. Retrieved from https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/emerging-consumer-trends-in-a-post-covid-19-world, 30.10.2022.
  • 17. Reisch, T., Heiler, G., Hurt, J., Klimek, P., Hanbury, A., Thurner, S. (2021). Behavioral gender differences are reinforced during the COVID-19 crisis. Scientific Reports, 11(1), 112, https://doi.org/10.1038/s41598-021-97394-1.
  • 18. Szasz, L., Balint, C., Csiki, O., Nagy, B. Z., Racz, B-G., Csala, D., Harris, L. C. (2022). The impact of COVID-19 on the evolution of online retail: The pandemic as a window of opportunity. Journal of Retailing and Consumer Services, Nov. 69, doi: 10.1016/j.jretconser.2022.103089
  • 19. Tiejun, Z. (2021). Implementation Status and Development Thinking on “Cloud National Examination” in China under the situation of “Online Anti-COVID-19 Epidemic.” Technological Forecasting and Social Change, 162, 120322, https://doi.org/10.1016/j.techfore.2020.120322
  • 20. Tyrväinen, O., Karjaluoto, H. (2022). Online grocery shopping before and during the COVID-19 pandemic: A meta-analytical review. Telematics and Informatics, 71, 101839, https://doi.org/10.1016/j.tele.2022.101839
  • 21. Wiścicka-Fernando, M. (2021). The use of mobile technologies in online shopping during the Covid-19 pandemic—An empirical study. Procedia Computer Science, 192, 34133422, https://doi.org/10.1016/j.procs.2021.09.114.
Typ dokumentu
Bibliografia
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bwmeta1.element.baztech-2cf73c82-82ac-4f8e-9cde-8677555d94e1
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