Economic instability and its effect on brand preferences: big data examination of self-image and online shopping conduct
DOI: https://doi.org/10.3846/bmee.2026.23594Abstract
Purpose – This study will examine how consumer brand preference is impacted by economic instability in the market of e-commerce in Indonesia, the relationship between self-image and purchasing patterns under three different periods; pre-crisis (2017–2019), crisis (2020–2022), and post-crisis recovery (2022–2023).
Research methodology – Transactional variables (Total payment volume, average order value, and purchase frequency) were analyzed using the mixed-methods approach in three brand categories (global, local, unbranded) and two product subcategories (care, decorated). ANO- VA and T-tests were used as a quantitative analysis of one of the largest Indonesian e-commerce platforms. The methods of qualitative analysis included semi-structured interviews with 20 industry experts who were chosen while engaging in purposive sampling and analyzed based on thematic analysis, in order to understand the emergent themes and patterns.
Findings – The findings indicate that the preference of global brands declined throughout the period of crisis (Z-sales declined 1.84 to –0.002) whereas local brands rejuvenated through community-oriented messages. The balanced status and sense of practicality seen in the post-crisis consumption saw global brands partially recovering (Z-sales: 1.43) and status-related self-image shifted into the health-conscious and community-supportive groups.
Research limitations – The study has a limitation of studying the e-commerce market and beauty product of Indonesia and the generalization to other regions or products. Besides, the qualitative element is based on only 14 internal experts working in the e-commerce and beauty sectors, which is insufficient to reflect direct consumer experiences and motivation to behaviour. Although the managerial interpretations bring about strategic data, the findings on self-image and consumer psychology should be confirmed by conducting empirical research with customers.
Practical implications – The results illustrate the significance of matching message of the brand with changing consumer values and using big data to create personalized marketing plans.
Originality/Value – This study is the first one to synthesize big data analysis with the use of expertise to indicate how consumer self-perception and purchase behavior are redefined due to economic shocks in online markets.
Keywords:
e-commerce, consumer behavior, self-image, economic crisis, big data analyticsHow to Cite
Share
License
Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University.
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Afanasyev, M., & Shash, N. (2024). The strategy of “green“ reindustrialization: Managerial and financial aspects. Public Administration Issues, (2), 41–63.
Ahmed, S., Islam, T., & Ghaffar, A. (2024). Shaping brand loyalty through social media influencers: The mediating role of follower engagement and social attractiveness. SAGE Open, 14(2). https://doi.org/10.1177/21582440241242928
Anguelov, K., & Stoyanova, T. (2025). Assessment of factors influencing market leadership and innovation of fintech companies in the digital economy. Economics Ecology Socium, 9(3), 93–109. https://doi.org/10.61954/2616-7107/2025.9.3-7
Appolloni, A., Basile, V., Caboni, F., & Pizzichini, L. (2023). An innovative approach to online consumer behaviour segmentation: The self-determination theory in an uncertain scenario. European Journal of Innovation Management, 26(7), 308–327. https://doi.org/10.1108/EJIM-11-2022-0609
Bartoli, C. (2022). Consumer self-concept and digitalization: what does this mean for brands?. Italian Journal of Marketing, 2022, 419–437. https://doi.org/10.1007/s43039-022-00059-8
Bharadwaj, N., Ballings, M., Naik, P. A., Moore, M., & Arat, M. M. (2022). A new livestream retail analytics framework to assess the sales impact of emotional displays. Journal of Marketing, 86(1), 27–47. https://doi.org/10.1177/00222429211013042
Berkman, E. T. (2016). Self-regulation training. In K. D. Vohs & R. F. Baumeister (Eds.), Handbook of self-regulation: Research, theory and applications (3rd ed.) (pp. 2–36). Guilford.
Ceylan, E., & Kirgiz, A. C. (2020). The effect of the 2018 economic crisis on purchasing behavior. European Journal of Business and Management Research, 5(3). https://doi.org/10.24018/ejbmr.2020.5.3.344
Creswell, J. (2014). Steps in conducting a scholarly mixed methods study (DEBR Speaker Series). https://digitalcommons.unl.edu/cgi/viewcontent.cgi?params=/context/dberspeakers/article/1047/&path_info=2013_11_14_ALL_Steps_in_Conducting_Mixed_Methods_Research_Creswell.pdf
Creswell, J. W., & Plano Clark, V. L. (2023). Revisiting mixed methods research designs twenty years later. In C. N. Poth (Ed.), Handbook of mixed methods research designs (pp. 21–36). Sage.
Das, D., Sarkar, A., & Debroy, A. (2022). Impact of COVID‐19 on changing consumer behaviour: Lessons from an emerging economy. International Journal of Consumer Studies, 46(3), 692–715. https://doi.org/10.1111/ijcs.12786
Ding, W., & Han, S. (2024). Consumer psychology of mysterious consumption: Embracing uncertainty through a perception of control. Behavioral Sciences, 14(5), Article 411. https://doi.org/10.3390/bs14050411
Esmaeilpour, M., Hoseini, S. Y., & Jafarpour, Y. (2016). An empirical analysis of the adoption barriers of e-commerce in small and medium sized enterprises (SMEs) with implementation of technology acceptance model. Journal of Internet Banking and Commerce, 21(2), 1–24.
Fodouop Kouam, A. W. (2025). Toward digital transformation: Insights into Chinese cross-border e-commerce SMEs during the COVID-19 pandemic and the post-pandemic era. SAGE Open, 15(1). https://doi.org/10.1177/21582440251318792
Gupta, C. P., Ravi Kumar, V. V., & Khurana, A. (2024 February 28–March 01). Artificial intelligence application in e-commerce: Transforming customer service, personalization and marketing. In Proceedings of the 2024 11th International Conference on Computing for Sustainable Global Development (INDIACom) (pp. 10–16). New Delhi, India. IEEE. https://doi.org/10.23919/INDIACom61295.2024.10498474
Gürhan-Canli, Z., Sarial-Abi, G., & Hayran, C. (2018). Consumers and brands across the globe: Research synthesis and new directions. Journal of International Marketing, 26(1). https://doi.org/10.1509/jim.17.0063
Guthrie, C., Fosso-Wamba, S., & Arnaud, J. B. (2021). Online consumer resilience during a pandemic: An exploratory study of e-commerce behavior before, during and after a COVID-19 lockdown. Journal of Retailing and Consumer Services, 61, Article 102570. https://doi.org/10.1016/j.jretconser.2021.102570
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2022). Multivariate data analysis. Cengage Learning.
Hirose, M., & Creswell, J. W. (2023). Applying core quality criteria of mixed methods research to an empirical study. Journal of Mixed Methods Research, 17(1), 12–28. https://doi.org/10.1177/15586898221086346
Holland, D. V., & Shepherd, D. A. (2013). Deciding to persist: Adversity, values, and entrepreneurs’ decision policies. Entrepreneurship Theory and Practice, 37(2), 331–358. https://doi.org/10.1111/j.1540-6520.2011.00468.x
Holland, D., Barrell, R., Fic, T., Hurst, I., Liadze, I., Orazgani, A., & Whitworth, R. (2009). The world economy: Consumer spending and the financial crisis. National Institute Economic Review, 210, 9–15. https://doi.org/10.1177/0027950109354531
Jain, A., Dash, S., & Malhotra, N. K. (2023). Consumption coping to deal with pandemic stress: Impact on subjective well-being and shifts in consumer behavior. European Journal of Marketing, 57(5), 1467–1501. https://doi.org/10.1108/EJM-11-2021-0864
Jia, X., Alvi, A. K., Nadeem, M. A., Akhtar, N., & Zaman, H. M. F. (2022). Impact of perceived influence, virtual interactivity on consumer purchase intentions through the path of brand image and brand expected value. Frontiers in Psychology, 13, Article 947916. https://doi.org/10.3389/fpsyg.2022.947916
Kaur, J., Mogaji, E., Paliwal, M., Jha, S., Agarwal, S., & Mogaji, S. A. (2024). Consumer behavior in the metaverse. Journal of Consumer Behaviour, 23(4), 1720–1738. https://doi.org/10.1002/cb.2298
Keller, K. L., & Swaminathan, V. (2013). Strategic brand management: Building, measuring, and managing brand equity (5th ed.). Pearson.
Khoo, V., Ahmi, A., & Saad, R. A. J. (2018). E-commerce adoption research: A review of literature. Journal of Social Sciences Research, (6), 90–99.
Koos, S. (2017). Crises and consumption. In M. Keller, B. Halkier, T.-A. Wilska, & M. Truninger (Eds.), Routledge handbook on consumption. Routledge. https://doi.org/10.4324/9781315675015-11
Ngo, T. T. A., Nguyen, H. L. T., Nguyen, H. P., Mai, H. T. A., Mai, T. H. T., & Hoang, P. L. (2024). A comprehensive study on factors influencing online impulse buying behavior: Evidence from Shopee video platform. Heliyon, 10(15), Article e35743. https://doi.org/10.1016/j.heliyon.2024.e35743
Perriman, H. E., Ramsaran-Fowdar, R. R., & Baguant, P. (2010). The impact of the global financial crisis on consumer behaviour. The 2010 Annual London Business, 14.
Ratchford, B., Soysal, G., Zentner, A., & Gauri, D. K. (2022). Online and offline retailing: What we know and directions for future research. Journal of Retailing, 98(1), 152–177. https://doi.org/10.1016/j.jretai.2022.02.007
Rather, R. A., Hollebeek, L. D., Vo-Thanh, T., Ramkissoon, H., Leppiman, A., & Smith, D. (2022). Shaping customer brand loyalty during the pandemic: The role of brand credibility, value congruence, experience, identification, and engagement. Journal of Consumer Behaviour, 21(5), 1175–1189. https://doi.org/10.1002/cb.2070
Rohden, S. F., & Espartel, L. B. (2024). Consumer reactions to technology in retail: Choice uncertainty and reduced perceived control in decisions assisted by recommendation agents. Electronic Commerce Research, 24, 901–923. https://doi.org/10.1007/s10660-024-09808-7
Singh, K., & Basu, R. (2023). Online consumer shopping behaviour: A review and research agenda. International Journal of Consumer Studies, 47(3), 815–851.
Srivastava, D. K., Ganguly, M., & Bagale, G. (2024). The impact of the social media on consumer behaviour amid economic crisis: the case of luxury consumption. International Journal of Intellectual Property Management, 14(1), 57–71.
Tangri, K., Kalra, D., Katuse, P., Masaeid, T. A., & Afifi, M. A. (2023, March 7–8). The nexus between digital innovation and digital entrepreneurship in the strategic transformation. In Proceedings of the 2023 International Conference on Business Analytics for Technology and Security (ICBATS) (pp. 1–5). Dubai, United Arab Emirates. IEEE. https://doi.org/10.1109/ICBATS57792.2023.10111410
Winit, W., Gregory, G., Cleveland, M., & Verlegh, P. (2014). Global vs local brands: How home country bias and price differences impact brand evaluations. International Marketing Review, 31(2), 102–128. https://doi.org/10.1108/IMR-01-2012-0001
Xia, Y. X., Chae, S. W., & Xiang, Y. C. (2024). How social and media cues induce live streaming impulse buying? SOR model perspective. Frontiers in Psychology, 15, Article 1379992. https://doi.org/10.3389/fpsyg.2024.1379992
Xie, Y., Batra, R., & Peng, S. (2015). An extended model of preference formation between global and local brands: The roles of identity expressiveness, trust, and affect. Journal of International Marketing, 23(1), 50–71. https://doi.org/10.1509/jim.14.0009
View article in other formats
CrossMark check
Published
Issue
Section
Copyright
Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University.
License
This work is licensed under a Creative Commons Attribution 4.0 International License.