Consumer behavior in response to the effects of the covid-19 pandemic: a study on the relationship between self-isolation intention and unusual purchases
DOI:
https://doi.org/10.24023/FutureJournal/2175-5825/2023.v15i1.744Keywords:
Consumer Behavior, Unusual Purchase, Self-isolation, Covid-19Abstract
Purpose: The aim of this study is to investigate consumer behavior in the context of the COVID-19 pandemic in Brazil to assess the relationship between the intention of self-isolation and to make unusual purchases.
Methodology /Approach: Through an online survey with a sample of 181 individuals in Brazil, the proposed model and hypotheses were tested using Structural Equation Modeling (PLS-SEM.)
Findings: The results demonstrate a link between perceived severity in the two behavioral responses measured, the intention to make unusual purchases and, more strongly, the intention to voluntary self-isolation.
Originality/Value: The study discusses consumer behavior for unusual purchases (cyberchondria) in risky situations such as the COVID-19 pandemic in Brazil.
Contributions and implications: We demonstrate how information overload leads to cyberchondria. In addition, the perceived severity leads the individual to make unusual purchases and self-isolation. In turn, exposure to online information sources leads to cyberchondria, which leads to behavior that increases the intention to make unusual purchases, and to self-isolation, which further increases exposure to online information. Furthermore, this study extends existing research (Laato et al., 2020) that suggests that research be carried out in different contexts.
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References
Abd-Alrazaq, A., Alhuwail, D., Househ, M., Hamdi, M., & Shah, Z. (2020). Top concerns of tweeters during the COVID-19 pandemic; Infoveillance study. Journal of Medical Internet Research, 22(4). https://doi.org/10.2196/19016
Ahmed, F., Zviedrite, N. & Uzicanin, A. (2018). Effectiveness of workplace social distancing measures in reducing influenza transmission: A systematic review. BMC Public Health 18(1). https://doi.org/10.1186/s12889-018-5446-1
Al-Homssi, M.A., & Ali, A.A. (2022). Factors influencing panic buying behavior among consumers in Lebanon during the COVID-19 pandemic. Trade and Finances, 42(2), 31-70. https://doi.org/10.21608/CAF.2022.251768
Anderson, R. M., Heesterbeek, H., Klinkenberg, D., & Hollingsworth, T. D. (2020). How will country-based mitigation measures influence the course of the COVID-19 epidemic. The Lancet, 395(10228), 931–934. https://doi.org/10.1016/S0140-6736(20)30567-5
Baker, S. R., R. A., Farrokhnia, S., Meyer, M., Pagel, & Yannelis, C. (2020). How does household spending respond to an epidemic? Consumption during the 2020 COVID-19 pandemic.. Review of Asset Pricing Studies, 10(4), 834-862. https://doi.org/10.1093/rapstu/raaa009
Baumgartner, S. E. & Hartmann, T. (2011). The role of health anxiety in online health information search. Cyberpsychology, Behavior and Social Networking, 14 (10), 613618. https://doi.org/10.1089/cyber.2010.0425
Eppler, M. & Mengis, J. (2004). The concept of information overload: A review of literature from organization science, accounting, marketing, MIS, and related disciplines. Information Society, 20(5), 325-344. https://doi.org/10.1080/01972240490507974
Farooq, A., Laato, S., & Islam, A. K. M. N. (2020). Impact of online Information on selfIsolation intention during the COVID-19 pandemic: Cross-sectional study. Journal of Medical Internet Research, 22(5), e19128. https://doi.org/10.2196/19128
Federici, R.A., & Skaalvik, E.M. Principal self-efficacy: relations with burnout, job satisfaction and motivation to quit. Social Psychology of Education, 15, 295–320 (2012). https://doi.org/10.1007/s11218-012-9183-5
Fineberg, H. V. (2014). Pandemic preparedness and response - Lessons from the H1N1 influenza of 2009. New England Journal of Medicine, 370(14), 1335–1342. https://doi.org/10.1056/NEJMra1208802
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
Goodwin, R., Haque, S., Neto, F., & Myers, L.B., 2009. Initial psychological responses to Influenza A, H1N1 ("Swine flu"). BMC Infectious Disease, 9(1), 166. https://doi.org/10.1186/1471-2334-9-166
Greenhalgh, T., Schmid, M. B., Czypionka, T. , Bassler, D. & Gruer, L. (2020). Face masks for the public during the covid-19 crisis. British Medical Journal, 369. https://doi.org/10.1136/bmj.m1435
Guerreiro, A. C., & Vilela, G. (2021). Os impactos do coronavírus nos pequenos negócios de turismo no Brasil: uma análise a partir dos dados do Sebrae. Revista Turismo em Análise, 32(1), 79-99. https://doi.org/10.11606/issn.1984-4867.v32i1p79-99
Hacioglu, S., D. Kanzig, & P. Surico (2020). Consumption in the time of COVID-19: Evidence from UK transaction data. CEPR Discussion Paper DP14733.
Hair, J. F., & Celsi, M. W. (2014). Fundamentos de Pesquisa de Marketing-3. AMGH Editora.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (1998). Multivariate data analysis (Vol. 5, No. 3, pp. 207-219).
Hair, J.F., Risher, J.J., Sarstedt, M. and Ringle, C.M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31 (1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203
Hair, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2017). Advanced issues in partial least squares structural equation modeling. Sage Publications.
Hall, M., Scott, D. & Gössling, S. (2020). Pandemics, Transformations and Tourism: Be Careful What You Wish For. Tourism Geographies, 22, 3, 577-598. https://doi.org/10.1080/14616688.2020.1759131
Hamilton, R., Thompson, D., Bone, S., Chaplin, L. N., Griskevicius, V., Goldsmith, K., et al. (2019). The effects of scarcity on consumer decision journeys. Journal of the Academy of Marketing Science, 47(3), 532–550. https://doi.org/10.1007/s11747-018-0604-7
Hobbs, J. E. (2020). Food Supply Chains during the COVID-19 Pandemic. Canadian Journal of Agricultural Economics/Revue Canadienne d’agroeconomie 68, 171–176 https://doi.org/10.1111/cjag.12237
IBGE – Instituto Brasileiro de Geografia e Pesquisa (2022). PNAD Contínua - Pesquisa Nacional por Amostra de Domicílios Contínua. Disponível em: https://www.ibge.gov.br/estatisticas/sociais/rendimento-despesa-e-consumo/9171-pesquisa-nacional-por-amostra-de-domicilios-continua-mensal.html?=&t=destaques Acesso em: 11 Jan. 2022.
Islam, M. S., Sarkar, T., Khan, S. H., Kamal, A. H. M., Hasan, S. M., Kabir, A., . . . Seale, H. (2020). COVID-19-related infodemic and its impact on public health: A global social media analysis. The American Journal of Tropical Medicine and Hygiene, 103(4), 1621‒1629. doi:10.4269/ajtmh.20-0812
Jokić-Begić, N., Mikac, U., Čuržik, D. et al. (2019). The Development and Validation of the Short Cyberchondria Scale (SCS). Journal of Psychopathology and Behavioral Assessment, 41, 662–676. https://doi.org/10.1007/s10862-019-09744-z
Keane, M., & Neal, T. (2020). Consumer panic in the COVID-19 pandemic. Journal of Econometrics. http://doi.org/10.1016/j.jeconom.2020.07.045
Kouzy, R., Abi Jaoude, J., Kraitem, A., El Alam, M. B., Karam, B., Adib, E., . . . Baddour, K. (2020). Coronavirus goes viral: Quantifying the COVID-19 misinformation epidemic on Twitter. Cureus, 12(3), e7255. doi:10.7759/cureus.7255
Kuruppu, G. N., & Zoysa, A. (2020). COVID-19 and Panic Buying: Na Examination of the Impact of Behavioural Biases. Working paper SS-HO-D-20- 00393. http://dx.doi.org/10.2139/ssrn.3596101
Laato, S., Islam, A. N., Farooq, A., & Dhir, A. (2020). Unusual purchasing behavior during the early stages of the COVID-19 pandemic: The stimulus-organism-response approach. Journal of Retailing and Consumer Services, 57, Article 102224. https://doi.org/10.1016/j.jretconser.2020.102224
Maftei, A. & Holman, A. (2020). Cyberchondria During the Coronavirus Pandemic: The Effects of Neuroticism and Optimism. Frontiers in Psychology, 11. https://doi.org/10.3389/fpsyg.2020.567345
Marcelino, J. S., Rezende, A. & Miyaji, M. (2020). Impactos Iniciais da COVID-19 nas Micro e Pequenas Empresas do Estado do Paraná – Brasil. Boletim de Conjuntura, ano II, v. 2, n. 5.: http://dx.doi.org/10.5281/zenodo.3779308
Miri, S.M., Roozbeh, F., Omranirad, A & Alavian, S.M. (2020). Panic of buying toilet papers: a historical memory or a horrible truth? Systematic review of gastrointestinal manifestations of COVID-19. Hepatitis Monthly, 20 (3). https://doi.10.5812/hepatmon.102729
O'Connell, M., Paula, Á. & Smith, K (2020). Preparing for a Pandemic: Spending Dynamics and Panic Buying During the COVID-19 First Wave. CEPR Discussion Paper No. DP15371, Available at SSRN: https://doi.org/10.1111/1475-5890.12271
Pajares, F. (1997). Current directions in self-efficacy research. Advances in Motivation and Achievement, 10(149), 1-49.
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
Parmet, W. E., & Sinha, M. S. (2020). Covid-19—the law and limits of quarantine. New England Journal of Medicine, 382(15), e28. https://doi.org/10.1056/NEJMp2004211
Perinotto, A. R. C., Sobrinho, L. L., Soares, J. R. R. & Fernandéz, M. D. S. (2021). O uso das estratégias de co-marketing, coopetição e marketing do destino, por meio da mídia social Instagram no período da pandemia. PODIUM Sport, Leisure and Tourism Review, 10(2), 81-105. https://doi.org/10.5585/podium.v10i2.19018
Poonaklom, P., Rungram, V., Abthaisong, P. & Piralam, B. (2020). Factors Associated with Preventive Behaviors towards Coronavirus Disease (COVID-19) among Adults in Kalasin Province, Thailand 2020. OSIR Journal, 13(3), 78-89. https://doi.org/10.1177/21501327211036251
Powell, J., Inglis, N., Ronnie, J. & Large, S. (2011). The characteristics and motivations of online health information seekers: cross-sectional survey and qualitative interview study. Journal of Medical Internet Research, 13 (1), e20, doi:10.2196/jmir.1.suppl1.e119
Richards, T. J., & Bradley R. (2020). COVID-19 Impact on Fruit and Veg- etable Markets. Canadian Journal of Agricultural Economics/Revue Canadienne d’Agroe- conomie 68, 189-194. https://doi.org/10.1111/cjag.12231
Ringle, C. M., Da Silva, D., & Bido, D. de S. (2014). Modelagem de equações estruturais com utilização do SmartPLS. Revista Brasileira de Marketing, 13(2), 56–73. https://doi.org/10.5585/remark.v13i2.2717
Ringle, C. M., Sarstedt, M., Mitchell, R., & Gudergan, S. P. (2020). Partial least squares structural equation modeling in HRM research. The International Journal of Human Resource Management, 31(12), 1617–1643. https://doi.org/10.1080/09585192.2017.1416655
Shah, A. K., Shafir, E., & Mullainathan, S. (2015). Scarcity frames value. Psychological Science, 26(4), 402–412. https://doi.org/10.1177/0956797614563958
Sharifirad, G., Yarmohammadi, P., Sharifabad, M. A. M. & Zohreh, R. (2014). Determination of preventive behaviors for pandemic influenza A/H1N1 based on protection motivation theory among female high school students in Isfahan, Iran. Journal of Education and Health Promotion, 3(7), 36-41. https://doi.org/10.4103/2277-9531.127556
Sharma, M., Yadav, K., Yadav, N & Ferdinand, K. C. (2017). Zika virus pandemic-analysis of Facebook as a social media health information platform. American Journal of Infection Control, 45(3), 301302. https://doi.org/10.1016/j.ajic.2016.08.022
Silva, L. E. N., Gomes Neto, M. B., Grangeiro, R. R. & Nadae, J. (2021). Pandemia do COVID-19: Por que é importante para a pesquisa do consumidor? Revista Brasileira de Marketing, 20(2), 258-285. https://doi.org/10.5585/remark.v20i2.18677
Starcevic, V. (2017). Cyberchondria: challenges of problematic online searches for healthrelatedinformation. Psychotherapy and Psychosomatics, 86(3), 129-133. https://doi.org/10.1159/000465525
Starcevic, V. and Berle, D. (2013). Cyberchondria: towards a better understanding of excessive health-related Internet use. Expert Review of Neurotherapeutics, 13(2), 205-213. https://doi.org/10.1586/ern.12.162
Sweller, J., (2011). Cognitive load theory. In: Psychology of Learning and Motivation, 55, 37–76. https://doi.org/10.1016/B978-0-12-387691-1.00002-8
Valentini, F., & Damásio, B. F. (2016). Variância média extraída e confiabilidade composta: indicadores de precisão. Psicologia: teoria e pesquisa, 32(2 ), 1-7. https://doi.org/10.1590/0102-3772e322225
Verhallen, T. M., & Robben, H. S. (1994). Scarcity and preference: An experimente on unavailability and product evaluation. Journal of Economic Psychology, 15(2), 315–331. https://doi.org/10.1016/0167-4870(94)90007-8
Vollmann, T. E. (1991). Cutting the Gordian knot of misguided performance measurement. Industrial Management & Data Systems, 91(1), 24–26. https://doi.org/10.1108/02635579110138126
Wang, Y., McKee, M., Torbica, A., & Stuckler, D. (2019). Revisão sistemática da literatura sobre a disseminação de desinformação relacionada à saúde nas mídias sociais. Ciências Sociais e Medicina, https://doi.org/10.1016/j.socscimed.2019.112552
Wang, C., Pan, R., Wan, X., Tan, Y., Xu, L., & Ho, C. S. (2020). Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in China. International Journal of Environmental Research and Public Health, 17(5), 1729. https://doi.org/10.3390/ijerph17051729
Wilder-Smith, A. & Freedman, D. (2020). Isolation, quarantine, social distancing and community containment: Pivotal role for old-style public health measures in the novel coronavirus (2019-nCoV) outbreak. Journal of Travel Medicine, 27, 1-4. https://doi.org/10.3390/jcm9030623
Yao, X., Zhang, C., Qu, Z., & Tan, B. C. (2020). Global village or virtual balkans? evolution and performance of scientific collaboration in the information age. Journal of the Association for Information Science and Technology, 71(4), 395–408. https://doi.org/10.1002/asi.24251
Yoo, W., Oh, S. H., & Choi, D. H. (2023). COVID-19, Digital Media, and Health| Exposure to COVID-19 Misinformation Across Instant Messaging Apps: Moderating Roles of News Media and Interpersonal Communication. International Journal of Communication, 17 (23). https://ijoc.org/index.php/ijoc/article/view/17594
Zhao, N. & Li, H. (2020). How can social commerce be boosted? The impact of consumer behaviors on the information dissemination mechanism in a social commerce network. Electronic Commerce Research, 20(5), 833–856 https://doi.org/10.1007/s10660-018-09326-3
Zheng, H., Sin, S.-C.J., Kim, H.K. & Theng, Y.-L. (2020). Cyberchondria: a systematic review. Internet Research, 31(2), 677-698. https://doi.org/10.1108/INTR-03-2020-0148
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