Compra por comercio electrónico de alimentos en Costa Rica durante el COVID-19

Alexis Villalobos Monge

doi:10.15517/am.v34i1.50438

Autores/as

Alexis Villalobos Monge Universidad de Costa Rica, San José, Costa Rica

DOI:

https://doi.org/10.15517/am.v34i1.50438

Palabras clave:

pandemias, comportamiento del consumidor, comportamiento económico

Resumen

Introducción. La influencia del comercio electrónico (CE) sobre las decisiones de las personas en la compra de alimentos, ha sido relevante durante la pandemia por COVID-19. En Costa Rica no se dispone de información sobre la forma en que este medio ha modificado las conductas de compra y consumo de alimentos en las familias costarricenses durante esta emergencia sanitaria. Objetivo. Analizar cambios en los patrones de compra y consumo de alimentos de los costarricenses que fueron influenciados durante la pandemia por el CE. Materiales y métodos. En junio de 2021 se ejecutó una encuesta en línea con la metodología de bola de nieve en diferentes grupos de redes sociales de Costa Rica. Se utilizó modelación por ecuaciones estructurales para establecer las causas asociadas con variables endógenas (confianza, conveniencia, impulsos hedónicos) y exógenas (nivel socioeconómico, decisiones de compra por COVID-19) que delinearon los cambios en los hábitos de compra. Se revisaron los estímulos generados desde CE que influyeron sobre estas decisiones de compra según el grupo específico de alimentos. Resultados. Se encontró una fuerte causalidad desde la variable latente conveniencia (β=0,89; p<0,01), para la compra de alimentos por CE, además de poco impacto (β=-0,35; p<0,01) en los hábitos de consumo de alimentos, generado por las medidas definidas para atender la pandemia. Las medidas sanitarias decretadas por las autoridades evidenciaron causalidad en la respuesta general del consumidor de alimentos por CE (NORM_1<0,8; p<0,01), la cual fue baja si se compara su valor estimado con otros motivadores en las decisiones de compra como la conveniencia por las mejoras en la calidad de vida (CO1≅0,8; p<0,01), o incluso la confianza por el compromiso de calidad ofrecido por el sitio web (CF3≅0,6; p<0,01). Conclusiones. La pandemia promovió una mejor percepción del consumidor respecto a situaciones ventajosas de emplear CE para realizar la compra de alimentos.

Descargas

Los datos de descargas todavía no están disponibles.

Citas

AlTarrah, D., AlShami, E., AlHamad, N., AlBesher, F., & Devarajan, S. (2021). The impact of Coronavirus COVID-19 pandemic on food purchasing, eating behavior, and perception of food safety in Kuwait. Sustainability, 13(16), Article 8987. https://doi.org/10.3390/su13168987

Baltar, F., & Brunet, I. (2012). Social research 2.0: Virtual snowball sampling method using Facebook. Internet Research, 22(1), 57–74. https://doi.org/10.1108/10662241211199960

Bolek, S. (2021). Food purchasing, preservation, and eating behavior during COVID-19 pandemic: A consumer analysis. Italian Journal of Food Science, 33(3), 14–24. https://doi.org/10.15586/ijfs.v33i3.2048

Bonett, D. G., & Wright, T. A. (2015). Cronbach’s alpha reliability: Interval estimation, hypothesis testing, and sample size planning. Journal of Organizational Behavior, 36(1), 3–15. https://doi.org/10.1002/job.1960

Browne, D. T., Wade, M., May, S. S., Jenkins, J. M., & Prime, H. (2021). COVID-19 Disruption gets inside the family: A two-month multilevel study of family stress during the pandemic. Developmental Psychology, 57(10), 1681–1692. https://doi.org/10.1037/dev0001237

Bujang, M. A., Omar, E. D., & Baharum, N. A. (2018). A review on sample size determination for Cronbach’s Alpha test: A simple guide for researchers. Malaysian Journal of Medical Sciences, 25(6), 85–99. https://doi.org/10.21315/mjms2018.25.6.9

Clay, L. A., & Rogus, S. (2021). Food access worries, food assistance use, purchasing behavior, and food insecurity among New Yorkers during COVID-19. Frontiers in Nutrition, 8, Article 647365. https://doi.org/10.3389/fnut.2021.647365

Doong, H., & Wang, H. (2011). Do males and females differ in how they perceive and elaborate on agent-based recommendations in Internet-based selling? Electronic Commerce Research and Applications, 10(5), 595–604. https://doi.org/10.1016/j.elerap.2010.12.005

Economic Commission for Latin America and the Caribbean. (2020). América Latina y el Caribe ante la pandemia del COVID-19: Efectos económicos y sociales (Informe especial COVID-19 No. 1). United Nations. https://doi.org/10.18356/9789210054720

Faour-Klingbeil, D., Osaili, T. M., Al-Nabulsi, A. A., Jemni, M., & Todd, E. C. D. (2021). An on-line survey of the behavioral changes in Lebanon, Jordan and Tunisia during the COVID-19 pandemic related to food shopping, food handling, and hygienic practices. Food Control, 125, Article 107934. https://doi.org/10.1016/j.foodcont.2021.107934

Floh, A., & Madlberger, M. (2013). The role of atmospheric cues in online impulse-buying behavior. Electronic Commerce Research and Applications, 12(6), 425–439. https://doi.org/10.1016/j.elerap.2013.06.001

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), Article e0237900. https://doi.org/10.1371/journal.pone.0237900

Güney, O. I., & Sangün, L. (2021). How COVID-19 affects individuals’ food consumption behaviour: A consumer survey on attitudes and habits in Turkey. British Food Journal, 123(7), 2307–2320. https://doi.org/10.1108/BFJ-10-2020-0949

Instituto Nacional de Estadísticas y Censos. (2019). Encuesta Nacional de Ingresos y Gastos de los Hogares. http://www.inec.go.cr/ingresos-y-gastos-de-hogares/ingresos-de-los-hogares

Jílková, P., & Králová, P. (2021). Digital consumer behaviour and eCommercetrends during the COVID-19 crisis. International Advances in Economic Research, 27, 83–85. https://doi.org/10.1007/s11294-021-09817-4

Jordan, I., Keding, G. B., Stosius, L.,Hawrysz, I.,Janiszewska, K., & Heil, E. A. (2021). Changes in vegetable consumption in times of COVID-19—First findings from an international civil science project. Frontiers in Nutrition, 8, Article 686786. https://doi.org/10.3389/fnut.2021.686786

Kim, C., Galliers, R. D., Shin, N., Ryoo, J. -H., & Kim, J. (2012). Factors influencing Internet shopping value and customer repurchase intention. Electronic Commerce Research and Applications, 11(4), 374–387. https://doi.org/10.1016/j.elerap.2012.04.002

Kim, H. -W., Xu, Y., & Gupta, S. (2012). Which is more important in Internet shopping, perceived price or trust? Electronic Commerce Research and Applications, 11(3), 241–252. https://doi.org/10.1016/j.elerap.2011.06.003

Laborde, D.,Martin, W.,& Vos, R. (2021). Impacts of COVID-19 on global poverty, food security, and diets: Insights from global model scenario analysis. Agricultural Economics, 52(3), 375–390. https://doi.org/10.1111/agec.12624

Li, S., Kallas, Z., & Rahmani, D. (2022). Did the COVID-19 lockdown affect consumers’ sustainable behaviour in food purchasing and consumption in China? Food Control, 132, Article 108352. https://doi.org/10.1016/j.foodcont.2021.108352

Li, S., Kallas, Z., Rahmani, D., & Maria Gil, J. (2021). Trends in food preferences and sustainable behavior during the COVID-19 lockdown: Evidence from Spanish consumers. Foods, 10(8), Article 1898. https://doi.org/10.3390/foods10081898

Liang, T. -P., & Huang, J. -S. (1998). An empirical study on consumer acceptance of products in electronic markets: A transaction cost model. Decision Support Systems, 24(1), 29–43. https://doi.org/10.1016/S0167-9236(98)00061-X

Liao, C., Liu, C. -C., & Chen, K. (2011). Examining the impact of privacy, trust and risk perceptions beyond monetary transactions: An integrated model. Electronic Commerce Research and Applications, 10(6), 702–715. https://doi.org/10.1016/j.elerap.2011.07.003

Lin, J., Lu, Y., Wang, B., & Wei, K. K. (2011). The role of inter-channel trust transfer in establishing mobile commerce trust. Electronic Commerce Research and Applications, 10(6), 615–625. https://doi.org/10.1016/j.elerap.2011.07.008

Martínez-López, F. J., Pla-García, C., Gázquez-Abad, J. C., & Rodríguez-Ardura, I. (2014). Utilitarian motivations in online consumption: Dimensional structure and scales. Electronic Commerce Research and Applications, 13(3), 188–204. https://doi.org/10.1016/j.elerap.2014.02.002

Reardon, T., Heiman, A., Lu, L., Nuthalapati, C. S. R., Vos, R., & Zilberman, D. (2021). “Pivoting” by food industry firms to cope with COVID-19 in developing regions: E-commerce and “copivoting” delivery intermediaries. Agricultural Economics, 52(3), 459–475. https://doi.org/10.1111/agec.12631

Rodríguez-Ramírez, S., Gaona-Pineda, E. B., Martínez-Tapia, B., Romero-Martínez, M., Mundo-Rosas, V., & Shamah-Levy, T. (2021). Inseguridad alimentaria y percepción de cambios en la alimentación en hogares mexicanos durante el confinamiento por la pandemia de Covid-19. Salud Pública de México, 63(6), 763–772. https://doi.org/10.21149/12790

Ronto, R., Nanayakkara, J., Worsley, A., & Rathi, N. (2021). COVID-19 & culinary behaviours of Australian household food gatekeepers: A qualitative study. Appetite, 167, Article 105598. https://doi.org/10.1016/j.appet.2021.105598

Satorra, A., & Bentler, P. M. (2001). A scaled difference chi-square test statistic for moment structure analysis. Psychometrika, 66, 507–514. https://doi.org/10.1007/BF02296192

Schierz, P. G., Schilke, O., & Wirtz, B. W. (2010). Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Research and Applications, 9(3), 209–216. https://doi.org/10.1016/j.elerap.2009.07.005

Schokkenbroek, J. M., Hardyns, W., Anrijs, S., & Ponnet, K. (2021). Partners in lockdown: Relationship stress in men and women during the COVID-19 pandemic. Couple and Family Psychology-Research and Practice, 10(3), 149–157. https://doi.org/10.1037/cfp0000172

Sheth, J. (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

Tabernero, C., Castillo-Mayén, R., Luque, B., & Cuadrado, E. (2020). Social values, self- and collective efficacy explaining behaviours in coping with Covid-19: Self-interested consumption and physical distancing in the first 10 days of confinement in Spain. PLOS ONE, 15(9), Article e0238682. https://doi.org/10.1371/journal.pone.0238682

Teo, T. S. H., & Yu, Y. (2005). Online buying behavior: A transaction cost economics perspective. Omega, 33(5), 451–465. https://doi.org/10.1016/j.omega.2004.06.002

Tonsor, G. T., Lusk, J. L., & Tonsor, S. L. (2021). Meat demand monitor during COVID-19. Animals, 11(4), Article 1040. https://doi.org/10.3390/ani11041040

Villalobos Monge, A. (2021). Buying food online: What explains the consumer purchase behaviour? International Journal of Food and Agricultural Economics, 9(1), 73–88. https://doi.org/10.22004/ag.econ.309387

Villalobos Monge, A., Chacón Cascante, A., Montero Vega, M., & Quirós Madrigal, O. (2020). Costos de transacción económica: Análisis de una experiencia real de venta en línea de alimentos. e-Agronegocios, 6(2), 82–102. https://doi.org/10.18845/ea.v6i2.5214

Wang, E., An, N., Gao, Z., Kiprop, E., & Geng, X. (2020). Consumer food stockpiling behavior and willingness to pay for food reserves in COVID-19. Food Security, 12, 739–747. https://doi.org/10.1007/s12571-020-01092-1

Westland, J. C. (2010). Lower bounds on sample size in structural equation modeling. Electronic Commerce Research and Applications, 9(6), 476–487. https://doi.org/10.1016/j.elerap.2010.07.003

World Bank. (2021). Costa Rica: Panorama general. https://www.bancomundial.org/es/country/costarica/overview