Comportamiento del consumidor durante la pandemia por COVID-19: análisis de clases latentes sobre actitudes de afrontamiento y hábitos de compra

Autores/as

  • Sérgio Luiz do Amaral Moretti Professor, Faculdade de Gestão e Negócios, Universidade Federal de Uberlândia, Uberlândia, Brasil. https://orcid.org/0000-0002-9457-6064
  • Marcelo Luiz Dias da Silva Gabriel Professor, Programa de Mestrado Profissional em Administração de Empresas, Universidade Ibirapuera, São Paulo, Brasil. https://orcid.org/0000-0001-8861-0783
  • Rejane Alexandrina Domingues Pereira do Prado Professora, Faculdade de Ciências Integradas do Pontal, Universidade Federal de Uberlândia, Ituiutaba, Brasil. https://orcid.org/0000-0002-5094-1613
  • André Francisco Alcântara Fagundes Professor, Faculdade de Gestão e Negócios, Universidade Federal de Uberlândia, Uberlândia, Brasil. https://orcid.org/0000-0003-1177-4514

DOI:

https://doi.org/10.18046/j.estger.2021.159.4433

Palabras clave:

COVID-19, actitudes de afrontamiento, cambio de hábitos de compra, análisis de clases latentes, comportamiento del consumidor

Resumen

La COVID-19 transformó la realidad mundial al imponer restricciones a las formas de vivir, trabajar y consumir. Pocos estudios anteriores a junio de 2020 han abordado sus impactos en el comportamiento del consumidor. Esta investigación tuvo como objetivo verificar la existencia de grupos heterogéneos en las actitudes hacia la pandemia y su efecto en el comportamiento de compra. El enfoque fue cuantitativo, con escalas probadas en los contextos de SARS y H1N1, adaptadas y validadas para el contexto brasileño. Se aplicó el modelado de ecuaciones estructurales y se identificaron tres segmentos: “Escéptico” (36,7%), “Preocupado” (50,1%) e “Indiferente” (13,22%). Los resultados apuntan a una diferenciación de los consumidores por actitudes ante situaciones de riesgo percibido, rol de creencias y el consecuente cambio en el comportamiento de compra, con implicaciones para la gestión de la salud pública y empresarial.

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Referencias

Agência Brasil (2020). Segunda onda da COVID-19 pode levar PIB do Brasil a cair 9,1%. Recuperado de: https://n9.cl/fkar1

Ajzen, I., & Madden, T. (1986). Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control. Journal of Experimental Social Psychology, 22(5), 453-474. https://doi.org/10.1016/0022-1031(86)90045-4

Aven, T., & Bouder, F. (2020). The COVID-19 pandemic: How can risk science help? Journal of Risk Research, 23(7-8), 849-854. https://doi.org/10.1080/13669877.2020.175638

Bagozzi, R. P., Belanche, D., Casaló, L. V., & Flavián, C. (2016). The role of anticipated emotions in purchase intentions. Psychology & Marketing, 33(8), 629-645. https://doi.org/10.1002/mar.20905

Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Freeman

Bido, D. S., & Silva, D. (2019). SmartPLS 3: Specification, estimation, evaluation and reporting. Administração: Ensino e Pesquisa. 20(2), 465-513. https://doi.org/10.13058/raep.2019.v20n2.1545

Blackwell, R. D., Miniard, P. W., & Engel, J. F. (2005). Comportamento do consumidor (9a. ed). São Paulo: Thomson Learning.

Blunch, N. J. (2013). Introduction to structural equation modeling using IBM SPSS Statistics and AMOS. (2nd ed.). Thousand Oaks, CA: SAGE Publications, Inc.

Boletim Focus (2020). Relatório de mercado de 22 de junho. Recuperado de: https://n9.cl/tu39hv

Bontempo, R. N., Bottom, W. P., & Weber, E. U. (1997). Cross-cultural differences in risk perception: A model-based approach. Risk Analysis, 17(4), 479-488. https://doi.org/10.1111/j.1539-6924.1997.tb00888.x

Boslaugh, S. (Ed.). (2007). Encyclopedia of epidemiology. San Luis: Sage Publications.

Brauer, F. (2011). A simple model for behaviour change in epidemics. BMC Public Health, 11(Suppl 1), S3. https://doi.org/10.1186/1471-2458-11-S1-S3

Bryman, A. & Cramer, D. (2011) Quantitative data analysis with SPSS 17, 18 and 19: A guide for social scientists. New York: Routledge. https://doi.org/10.4324/9780203180990

Byrne, B. M. (2010). Structural equation modeling with AMOS: basic concepts, applications, and programming. (2nd ed). New York: Routledge .

Campo, S., Brossard, D., Frazer, M. S., Marchell, T., Lewis, D., & Talbot, J. (2003). Are social norms campaigns really magic bullets? Assessing the effects of students' misperceptions on drinking behavior. Health Communication, 15(4), 48-497. https://doi.org/10.1207/S15327027HC1504_06

Chang, E. C., & Asakawa, K. (2003). Cultural variations on optimistic and pessimistic bias for self versus a sibling: Is there evidence for self-enhancement in the West and for self-criticism in the East when the referent group is specified? Journal of Personality and Social Psychology, 84(3), 569-581. https://doi.org/10.1037/0022-3514.84.3.569

Chauhan, V., & Shah, M. H. (2020). An empirical analysis into sentiments, media consumption habits, and consumer behaviour during the Coronavirus (COVID-19) Outbreak. Purakala UGC Care Journal, 31(20), 353-375.

Cho, H., & Lee, J. S. (2015). The influence of self-efficacy, subjective norms, and risk perception on behavioral intentions related to the H1N1 flu pandemic: A comparison between Korea and the US. Asian Journal of Social Psychology, 18(4), 311-324. https://doi.org/10.1111/ajsp.12104

Chronopoulos, D. K., Lukas, M., & Wilson, J. O. (2020). Consumer Spending Responses to the COVID-19 Pandemic: An Assessment of Great Britain. Available at SSRN 3586723.

Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155-159. https://doi.org/10.1037/0033-2909.112.1.155

Cortez, R. M., & Johnston, W. J. (2020). The Coronavirus crisis in B2B settings: Crisis uniqueness and managerial implications based on social exchange theory. Industrial Marketing Management, 88, 125- 135. https://doi.org/10.1016/j.indmarman.2020.05.004

Cranfield, J. A. (2020). Framing consumer food demand responses in a viral pandemic. Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, 68(2), 151-156. https://doi.org/10.1111/cjag.12246

Deloitte. (2020). COVID-19 e os impactos nos setores: Um olhar atento às projeções futuras e à evolução dos negócios durante a pandemia. Recuperado de: https://n9.cl/ev0ra

Fishbein, M. & Ajzen, I. (1975), Belief, Attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.

Fiocruz (2020). Observatório COVID-19. Recuperado de: https://n9.cl/70gt

Floyd, D. L., Prentice-Dunn, S. & Rogers, R. W. (2000). A meta-analysis of research on protection motivation theory. Journal of Applied Social Psychology, 30(2), 407-429. https://doi.org/10.1111/j.1559-1816.2000.tb02323.x

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/10.2307/3151312

Gibbons, F. X., Helweg-Larsen, M., & Gerrard, M. (1995). Prevalence estimates and adolescent risk behavior: cross-cultural differences in social influence. Journal of Applied Psychology, 80(1), 107-121. https://doi.org/10.1037/0021-9010.80.1.107

Gilbride, T. J., Inman, J. J., & Stilley, K. M. (2015). The role of within-trip dynamics in unplanned versus planned purchase behavior. Journal of Marketing, 79(3), 57-73. https://doi.org/10.1509/jm.13.0286

Hagenaars, J. A., & McCutcheon, A. L. (Eds.). (2002). Applied latent class analysis. Cambridge: University Press.

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017a). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). Thousand Oaks, CA: SAGE Publications, Inc .

Hair, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2017b). Advanced issues in partial least squares structural equation modeling. Thousand Oaks, CA: SAGE Publications, Inc .

Hair, J. F., Gabriel,M. L. D. S., Silva, D., Braga Júnior, S. S. (2019a). Development and validation of attitudes measurement scales: fundamental and practical aspects. RAUSP Management Journal, 54(4), 490-507. https://doi.org/10.1108/RAUSP-05-2019-0098

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019b). 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

Hays, J. N. (2005). Epidemics and pandemics: their impacts on human history. Santa Barbara, CA: Abc-clio.

Henseler, J., Hubona, G., & Ray, P. A. (2016) Using PLS path modeling in new technology research: updated guidelines. Industrial Management & Data Systems, 116(1), 2-20. https://doi.org/10.1108/IMDS-09-2015-0382

Kaynak, R., & Ekşi, S. (2014). Effects of personality, environmental and health consciousness on understanding the anti-consumptional atitudes. Procedia-Social and Behavioral Sciences, 114, 771-776. https://doi.org/10.1016/j.sbspro.2013.12.783

Kim, J. O., & Mueller, C. W. (1978). Factor analysis: Statistical methods and practical issues (No. 14). Beverly Hills, CA: Sage.

Klein, C. T. F & Helweg-Larsen, M. (2002). Perceived control and the optimistic bias: A meta-analytic review. Psychology and Health, 17(4), 437-446. https://doi.org/10.1080/0887044022000004920

Kline, R. B. (2005). Principles and practice of structural equation modeling. (2nd ed.). New York: The Guilford Press.

Koschate-Fischer, N., Hoyer, W. D., Stokburger-Sauer, N. E., & Engling, J. (2018). Do life events always lead to change in purchase? The mediating role of change in consumer innovativeness, the variety seeking tendency, and price consciousness. Journal of the Academy of Marketing Science, 46(3), 516-536. https://doi.org/10.1007/s11747-017-0548-3

Kramer, T., & Block, L. (2011). Nonconscious effects of peculiar beliefs on consumer psychology and choice. Journal of Consumer Psychology, 21(1), 101-111. https://doi.org/10.1016/j.jcps.2010.09.009

Massara, F., Melara, R. D., & Liu, S. S. (2014). Impulse versus opportunistic purchasing during a grocery shopping experience. Marketing Letters, 25(4), 361-372. https://doi.org/10.1007/s11002-013-9255-0

Maxwell, K. A. (2002). Friends: The role of peer influence across adolescent risk behaviors. Journal of Youth and Adolescence, 31, 267- 27. https://doi.org/10.1080/09540120050042918

McKinsey (2020). COVID-19: Implications for business. McKinsey & Co. Recuperado de: https://www.mckinsey.com/#

Ng, B. Y., Kankanhalli, A., & Xu, Y. C. (2009). Studying users' computer security behavior: A health belief perspective. Decision Support Systems, 46(4), 815-825. https://doi.org/10.1016/j.dss.2008.11.010

Nielsen (2020). Life Beyond COVID-19. What manufacturers and retailers must now prepare for. Recuperado de: https://www.nielsen.com/ch/en/insights/article/2020/life-beyond-COVID

Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory. New York: McGraw-Hill.

Nylund-Gibson, K., & Choi, A. Y. (2018). Ten frequently asked questions about latent class analysis. Translational Issues in Psychological Science, 4(4), 440. https://doi.org/10.1037/tps0000176

Parboteeah, D. V., Valachch, J. S., & Wells, J. D. (2009). The influence of website characteristics on a consumer’s Urge to buy impulsively. Information Systems Research, 20(1), 60-78. https://doi.org/10.1287/isre.1070.0157

Reid, A. E. & Aiken, L. S. (2011). Integration of five health behaviour models: Common strengths and unique contributions to understanding condom use. Psychology & Health, 26, 1499-1520. https://doi.org/10.1080/08870446.2011.572259

Relihan, L., Ward, M., Wheat, C. W. & Farrell, D. (2020). The early impact of COVID-19 on local commerce: changes in spend across neighborhoods and online. COVID Economics, 28, 1-28.

Rhead, R., Elliot, M., & Upham, P. (2018) Using latent class analysis to produce a typology of environmental concern in the UK. Social Science Research, 74, 210-222. https://doi.org/10.1016/j.ssresearch.2018.06.001

Ringle, C., Silva, D., & Bido, D. (2014). Structural equation modeling with the SmartPLS. Brazilian Journal of Marketing, 13(2), 56-73. https://doi.org/10.5585/remark.v13i2.2717

Rogers, R. W. (1983). Cognitive and physiological processes in fears appeals and attitude change: a revised theory of protection motivation. In Cacioppo, J. & Petty, R., Social psychology: a source book (pp. 153-176). New York: Guilford Press.

Romeo-Arroyo, E., Mora, M., & Vázquez-Araújo, L. (2020). Consumer behavior in confinement times: food choice and cooking attitudes in Spain. International Journal of Gastronomy and Food Science, 21, 100226. https://doi.org/10.1016/j.ijgfs.2020.100226

Shavitt, S., Cho, Y. I., Johnson, T. P., Jiang, D., Holbrook, A., & Stavrakantonaki, M. (2016). Culture moderates the relation between perceived stress, social support, and mental and physical health. Journal of Cross-Cultural Psychology, 47(7), 956-980. https://doi.org/10.1177/0022022116656132

Schwenk, G. & Möser, G. (2009), Intention and behavior: a Bayesian meta-analysis with focus on the Ajzen-Fishbein Model in the field of environmental behavior. Quality & Quantity, 43(5), 743-755. https://doi.org/10.1007/s11135-007-9162-7

Sheth, J., Mittal, B. & Newman, B. (2001). Comportamento do cliente: indo além do comportamento do consumidor. São Paulo: Atlas.

Sheth, J. N. (2020). Impact of COVID-19 on Consumer Behavior: Will the Old Habits Return or Die? Journal of Business Research, 117, 280- 283. https://doi.org/10.1016/j.jbusres.2020.05.059

Social Miner-Opinion Box (2020). O futuro do consumo num cenário pós- COVID-19. Recuperado de: https://n9.cl/ek07p

Stilley, K. M., Inman, J. J., & Wakefield, K. L. (2010). Planning to make unplanned purchases? The role of in-store slack in budget deviation. Journal of Consumer Research, 37(2), 264-278. https://doi.org/10.1086/651567

Van Steenburg, E., & Naderi, I. (2020). Unplanned purchase decision making under simultaneous financial and time pressure. Journal of Marketing Theory and Practice, 28(1), 98-116. https://doi.org/10.1080/10696679.2019.1684206

Vermunt, J. K. (2010). Latent class modeling with covariates: Two improved three-step approaches. Political Analysis, 18(04), 450-469. https://doi.org/10.1093/pan/mpq025

Wang, Y., Hong, A., Li, X., & Gao, J. (2020). Marketing innovations during a global crisis: A study of China firms’ response to COVID-19. Journal of Business Research, 116, 214-220. https://doi.org/10.1016/j.jbusres.2020.05.029

Weinstein, N. D. (1989). Optimistic biases about personal risks. Science, 246(4935), 1232-1234. https://doi.org/10.1126/science.2686031

Weller, B. E., Bowen, N. K., & Faubert, S. J. (2020). Latent Class Analysis: A Guide to Best Practice. Journal of Black Psychology, 46(4), 287-311. https://doi.org/10.1177/0095798420930932

Wen, Z., Huimin, G., & Kavanaugh, R. R. (2005). The impacts of SARS on the consumer behaviour of Chinese domestic tourists. Current Issues in Tourism, 8(1), 22-38. https://doi.org/10.1080/13683500508668203

Wen, J., Kozak, M., Yang, S., & Liu, F. (2020). COVID-19: potential effects on Chinese citizens’ lifestyle and travel. Tourism Review, 76(1), 74-87. https://doi.org/10.1108/TR-03-2020-0110

WHO (2020). World Health Organization. Coronavirus Disease (COVID-19) Dashboard 2020. Recuperado de: https://COVID19.who.int/

Woodside, A. G., Hsu, S. Y., & Marshall, R. (2011). General theory of cultures' consequences on international tourism behavior. Journal of Business Research, 64(8), 785-799. https://doi.org/10.1016/j.jbusres.2010.10.008

Yen-Tsang, C., Csillag, J. M., & Siegler, J. (2012). Theory of reasoned action for continuous improvement capabilities: a behavioral approach. Revista de Administração de Empresas, 52(5), 546-564. https://doi.org/10.1590/S0034-75902012000500006

Publicado

2021-04-13

Cómo citar

Comportamiento del consumidor durante la pandemia por COVID-19: análisis de clases latentes sobre actitudes de afrontamiento y hábitos de compra . (2021). Estudios Gerenciales, 37(159), 303-317. https://doi.org/10.18046/j.estger.2021.159.4433