Mobile shopping before COVID-19 and intention to continue mobile shopping after the pandemic. Methodological aspects of gender-based empirical study

This paper aims to determine whether there is an association between gender and mobile shopping buying behavior both during and post-COVID-19 period. Three types of categorical variables were defined: the installation of mobile shopping apps before the pandemic, the use of mobile shopping apps before the pandemic, and the decision to stop using mobile shopping apps after the pandemic. In a pilot study, the population only included Polish respondents. The field survey method was applied to collect the primary data. In April 2021, the survey was launched via social media. Primary data were collected from 102 respondents. The nonparametric statistical method was selected as a suitable analytical technique and the chi-square test of independence was used to test the hypotheses. According to the pilot study, gender does not influence installation of mobile shopping apps before the pandemic, the use of mobile shopping apps before the pandemic, or the intention to stop using mobile shopping apps after the COVID-19 period. The findings are significant for mobile shopping application developers, modern trades, and business decision-makers in the Polish market. Meanwhile, the applied research methodology is most relevant for future similar kinds of research studies.

Celem artykułu jest ustalenie, czy istnieje związek między płcią a zachowaniami związanymi z zakupami mobilnymi podczas COVID-19 i okresie postcovidowym. Zdefiniowano trzy rodzaje zmiennych zależnych: instalacja aplikacji do zakupów mobilnych przed pandemią, korzystanie z aplikacji do zakupów mobilnych przed pandemią oraz pomysł zaprzestania korzystania z aplikacji do zakupów mobilnych po pandemii. Populację w badaniu pilotażowym stanowili polscy respondenci. Badanie ankietowe zostało uruchomione za pośrednictwem mediów społecznościowych w kwietniu 2021 r. Dane pierwotne zostały zebrane od 102 respondentów. Jako technikę analityczną zastosowano nieparametryczną metodę statystyczną, wykorzystując test niezależności chi-kwadrat do sprawdzenia hipotez badawczych. Badanie pilotażowe wykazało, że nie było istotnego związku między płcią a instalowaniem mobilnych aplikacji zakupowych przed pandemią, między płcią a korzystaniem z aplikacji do zakupów mobilnych przed pandemią, oraz między płcią a decyzją o zaprzestaniu korzystania z aplikacji do zakupów mobilnych po pandemii. Wyniki są istotne dla twórców aplikacji do zakupów mobilnych, nowoczesnych branż i decydentów biznesowych na polskim rynku, a zastosowana metodologia badań jest odpowiednia dla prowadzenia analogicznych badań naukowych w przyszłości. 

References/Bibliografia

AHDB. (2023). Changing consumer trends. https://ahdb.org.uk/news/consumer-insight-changing-consumer-trends (retrieved 20.01.2023).

CIHR Institute of Gender and Health (2012). What a difference sex and gender make: A gender, sex and health research casebook. SSRN Scholarly Paper No. 2199670. https://papers.ssrn.com/abstract=2199670

Dholakia, R. R., & Dholakia, N. (2004). Mobility and markets: Emerging outlines of m-commerce. Journal of Business Research, 57(12), 1391–1396. https://doi.org/10.1016/S0148-2963(02)00427-7

EPW. (2022). Is COVID-19 an Exogenous Shock? https://www.epw.in/engage/article/COVID-19-exogenous-shockn (retrieved 30.12.2022).

Eriksson, N., & Stenius, M. (2020). Changing behavioral patterns in grocery shopping in the initial phase of the COVID-19 crisis: A qualitative study of news articles. Open Journal of Business and Management, 8(5). https://doi.org/10.4236/ojbm.2020.85119

Gara, K. (2021, November 16). Shopping in Poland: How many of us do the shopping online? https://oexfulfilio.com/en/shopping-in-poland-how-many-ofus-do-the-shopping-online/

Heidari, S., Babor, T. F., De Castro, P., Tort, S., & Curno, M. (2016). Sex and gender equity in research: Rationale for the SAGER guidelines and recommended use. Research Integrity and Peer Review, 1(1), 2. https://doi.org/10.1186/s41073-016-0007-6

Investopedia. (2023). Demand: How it works plus economic determinants and the demand curve. https://www.investopedia.com/terms/d/demand.asp (retrieved 20.01.2023).

Kao, W.-K., & L'Huillier, E. A. (2022). The moderating role of social distancing in mobile commerce adoption. Electronic Commerce Research and Applications, 52, 101116. https://doi.org/10.1016/j.elerap.2021.101116

KeyDifferences.com. (2015, June 16). Difference between customer and consumer (with comparison chart). https://keydifferences.com/difference-betweencustomer-and-consumer.html

Martin, C. (2013, June 11). The mobile shopping life cycle. Harvard Business Review. https://hbr.org/2013/06/the-mobile-shopping-life-cycle

NetSuite.com. (2023). The trick to meeting customer demand. Oracle NetSuite. https://www.netsuite.com/portal/resource/articles/erp/demandplanning.shtml (retrieved 20.01.2023).

Oxford English Dictionary. (2023). https://www.oed.com/viewdictionaryentry/Entry/77468 (retrieved 19.01.2023).

Pantano, E., Pizzi, G., Scarpi, D., & Dennis, C. (2020). Competing during a pandemic? Retailers' ups and downs during the COVID-19 outbreak. Journal of Business Research, 116, 209–213. https://doi.org/10.1016/j.jbusres.2020.05.036

Poland.afs.org. (2018, April 13). How is it to live in Polish family? https://poland.afs.org/2018/04/13/how-is-it-to-live-in-polish-family/

Principato, L., Mattia, G., Di Leo, A., & Pratesi, C. A. (2021). The household wasteful behavior framework: A systematic review of consumer food waste. Industrial Marketing Management, 93, 641–649. https://doi.org/10.1016/j.indmarman.2020.07.010

Shang, D., & Wu, W. (2017). Understanding mobile shopping consumers' continuance intention. Industrial Management and Data Systems, 117(1), 213–227. Scopus. https://doi.org/10.1108/IMDS-02-2016-0052

Shmerling, R. H. (2022, October 26). Is the COVID-19 pandemic over, or not? Harvard Health Publishing. https://www.health.harvard.edu/blog/is-the-COVID-19-pandemic-over-or-not-202210262839

Wiścicka-Fernando, M. (2021). The use of mobile technologies in online shopping during the COVID-19 pandemic. An empirical study. Procedia Computer Science, 192, 3413–3422. https://doi.org/10.1016/j.procs.2021.09.114

Zach. (2020, April 27). Chi-square test of independence: Definition, formula, and example. Statology. https://www.statology.org/chi-square-test-ofindependence/