Online Food Shopping: Determinants and Profile of Portuguese Buyers in the Pandemic Context
Compra de alimentos en línea: determinantes y perfil de los compradores en Portugal durante la pandemia
Compras de alimentos on-line: determinantes e perfil dos compradores portugueses no contexto pandêmico
DOI:
https://doi.org/10.15446/innovar.v33n87.105507Palabras clave:
E-commerce, behavior, COVID-19, online, food, buying intention (en)Descargas
The covid-19 pandemic brought the opportunity to accelerate the acceptance and usage of existing behaviors and innovations by society and the market. Amongst these innovations, e-commerce food stands out, allowing food companies to redesign their models to face the demand during the pandemic. This research aims to recognize the profile of online food buyers within Portugal and understand the determinants of online food purchase intention in the context of the pandemic. The methodology applied is quantitative, using the Partial Least Squares method to test the hypotheses formulated by the proposed structural model. The data used resulted from applying an online questionnaire to 358 food consumers in Portugal. The results show that situational factors directly related to eating behavior positively impact the online food shopping experience, increasing the intention to purchase food online during covid-19. Concerning the profile of the e-consumer, it seems that owning a vehicle negatively influences the intention to purchase food in e-commerce, as opposed to the level of income, which is a positive factor. On the theoretical side, this research contributes to the literature by contributing on the theme of food e-commerce in a pandemic time, which is currently very scarce. As for practical contributions, through the identification of the trends in consumer behavior during and after the pandemic, companies can better anticipate and prepare for new consumer needs and profiles, consequently developing new strategies and increasing their e-commerce sales. Since Portugal has a small digital population and less than 35% of digital natives, the prominence of studies in this area is minor. The current research is original and innovative, as studies that analyze consumer behavior in food e-commerce in this country, specifically during a pandemic, are scarcer.
La pandemia de covid-19 permitió acelerar la aceptación y el uso de comportamientos e innovaciones existentes por parte de la sociedad y el mercado, entre los que destaca la compra de alimentos en línea, mecanismo que hizo posible que las empresas de alimentos rediseñaran sus modelos de negocio para hacer frente a la demanda durante la pandemia. Esta investigación tiene como objetivo reconocer el perfil de los compradores de alimentos en línea en Portugal y comprender los determinantes de la intención de compra de alimentos mediante este canal en el contexto de la pandemia. La metodología aplicada es de tipo cuantitativo, con el uso de mínimos cuadrados parciales para contrastar las hipótesis formuladas en el modelo estructural propuesto. Los datos utilizados resultaron de la aplicación de un cuestionario en línea a 358 consumidores de alimentos en Portugal. Los resultados muestran que los factores situacionales directamente relacionados con los hábitos alimenticios impactan positivamente la experiencia de compra de alimentos en línea, favoreciendo la intención de compra bajo esta modalidad durante la pandemia de covid-19. En cuanto al perfil del e-consumidor, parece que tener un vehículo influye negativamente en la intención de compra de alimentos de manera electrónica, mientras que el nivel de ingresos se constituye como un factor positivo. Desde una perspectiva teórica, esta investigación aporta a la literatura sobre el comercio electrónico de alimentos en tiempos de pandemia, que actualmente es un tema poco abordado. En cuanto a las implicaciones prácticas, la identificación de tendencias en el comportamiento de los consumidores durante y después de la pandemia permiten que las empresas puedan anticiparse y prepararse mejor para satisfacer las nuevas necesidades y perfiles de consumidores, desarrollando nuevas estrategias e incrementando sus niveles de ventas en el canal electrónico. Dado que Portugal cuenta con una población digital pequeña y menos de 35 % de sus habitantes son nativos digitales, el protagonismo de los estudios en esta área del conocimiento es modesto. Por ello, la presente investigación resulta ser original e innovadora, ya que son escasos los estudios que analizan el comportamiento del consumidor en el comercio electrónico de alimentos de dicho país, y específicamente durante una pandemia.
A pandemia ocasionada pela covid-19 trouxe a oportunidade de acelerar a aceitação e o uso de comportamentos e inovações existentes pela sociedade e pelo mercado. Entre essas inovações, destaca-se o e-commerce de alimentos, que permitiu que as empresas de alimentos redesenhassem seus modelos para enfrentar a demanda durante a pandemia. Esta pesquisa tem como objetivo reconhecer o perfil dos compradores de alimentos on-line dentro de Portugal e entender os determinantes da intenção de compra de alimentos on-line no contexto da pandemia. A metodologia aplicada é quantitativa, a partir do método Parcial Least Squares para testar as hipóteses formuladas pelo modelo estrutural proposto. Os dados utilizados resultaram da aplicação de um questionário on-line a 358 consumidores de alimentos em Portugal. Os resultados mostram que fatores situacionais diretamente relacionados ao comportamento alimentar impactam positivamente a experiência de compra de alimentos on-line, aumentando a intenção de comprar alimentos on-line durante a pandemia. Com respeito ao perfil do consumidor eletrônico, parece que possuir um veículo influencia negativamente a intenção de comprar alimentos no e-commerce, ao contrário do nível de renda, que se revelou um fator positivo. Quanto ao aspecto teórico, esta pesquisa colabora para a literatura ao contribuir com o tema do e-commerce alimentar no período pandêmico, que atualmente é muito escasso. Quanto às contribuições práticas, por meio da identificação das tendências de comportamento do consumidor durante e após a pandemia, as empresas podem antecipar e se preparar melhor para novas necessidades e perfis de consumidores e, consequentemente, desenvolver novas estratégias e aumentar suas vendas no e-commerce. Como Portugal tem uma pequena população digital e menos de 35% de nativos digitais, o destaque dos estudos nessa área é menor. A pesquisa atual é original e inovadora, pois estudos que analisam o comportamento do consumidor no comércio eletrônico de alimentos neste país, especificamente durante uma pandemia, são mais escassos.
Referencias
Abdul-Muhmin, A. G. (2010). Repeat purchase intentions in online shopping: The role of satisfaction, attitude, and online retailers' performance. Journal of International Consumer Marketing, 23, 5-20, https://doi.org/10.1080/08961530.2011.524571
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-T
Alaimo, L. S., Fiore, M., & Galati, A. (2020). How the Covid-19 Pandemic is changing online food shopping human behaviour in Italy. Sustainability, 12(22), 9594. https://doi.org/10.3390/su12229594
Ali, S., Khalid, N., Javed, H. M., & Islam, D. M. Z. (2021). Consumer adoption of online food delivery ordering (OFDO) services in Pakistan: The impact of the COVID-19 pandemic situation. Journal of Open Innovation: Technology, Market, and Complexity, 7(1), 10. https://doi.org/10.3390/joitmc7010010
Beer, S., Edwards, J., Fernandes, C., & Sampaio, F. (2002). 12 regional food cultures: Integral to the rural tourism product? In A. M. Hjalager & G. Richards (Eds.), Tourism and gastronomy (pp. 207-223). Routledge.
Berg, J., & Henriksson, M. (2020). In search of the ‘good life’: Understanding online grocery shopping and everyday mobility as social practices. Journal of Transport Geography, 83, 102633. https://doi.org/10.1016/j.jtrangeo.2020.102633
Bin, Q., Chen, S. J., & Sun, S. Q. (2003). Cultural differences in e-commerce: A comparison between the US and China. Journal of Global Information Management (JGIM), 11(2), 48-55. https://doi.org/10.4018/jgim.2003040103
Bryła, P. (2018). Organic food online shopping in Poland. British Food Journal, 120(5), 1015-1027. https://doi.org/10.1108/BFJ-09-2017-0517
Cavallo, C., Sacchi, G., & Carfora, V. (2020). Resilience effects in food consumption behaviour at the time of Covid-19: Perspectives from Italy. Heliyon, 6(12), e05676. https://doi.org/10.1016/j.heliyon.2020.e05676
Chenarides, L., Grebitus, C., Lusk, J. L., & Printezis, I. (2021). Food consumption behavior during the COVID-19 pandemic. Agribusiness, 37(1), 44-81. https://doi.org/10.1002/agr.21679
Chiu, C. M.; Hsu, M. H.; Lai, H.; Chang, C. M. (2012). Re-examining the influence of trust on online repeat purchase intention: The moderating role of habit and its antecedents. Decision Support Systems, 53, 835-845. https://doi.org/10.1016/j.dss.2012.05.021
Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences, 2nd ed. London: Routledge.
Chrysochou, P. (2017). Consumer behavior research methods. In G. Emilien, R. Weitkunat, & F. Lüdicke (Eds.), Consumer Perception of product risks and benefits (pp. 409-428). Springer International Publishing. https://doi.org/10.1007/978-3-319-50530-5_22
Eger, L., Komárková, L., Egerová, D., & Mičík, M. (2021). The effect of COVID-19 on consumer shopping behaviour: Generational cohort perspective. Journal of Retailing and Consumer Services, 61, 102542. https://doi.org/10.1016/j.jretconser.2021.102542
Feinberg, A., Mullapudi, M., Benore, M., & Page, O. (2016). The restaurant of the future – Creating the next generation customer experience. Deloitte https://www2.deloitte.com/content/dam/Deloitte/mx/Documents/consumer-business/El-restaurante-del%20futuro.pdf
Frank, D. A., & Peschel, A. O. (2020). Sweetening the deal: The ingredients that drive consumer adoption of online grocery shopping. Journal of Food Products Marketing, 26, 535-544. https://doi.org/10.1080/10454446.2020.1829523
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), e0237900. https://doi.org/10.1371/journal.pone.0237900
Gasmi, A., Noor, S., Tippairote, T., Dadar, M., Menzel, A., & Bjorklund, G. (2020). Individual risk management strategy and potential therapeutic options for the COVID-19 pandemic. Clinical Immunology, 215, 108409. https://doi.org/10.1016/j.clim.2020.108409
Goldfarb, A., & Tucker, C. (2019). Digital economics. Journal of Economic Literature, 57(1), 3-43. https://doi.org/10.1257/jel.20171452
Grashuis, J., Skevas, T., & Segovia, M. S. (2020). Grocery shopping preferences during the COVID-19 pandemic. Sustainability, 12(13), 5369. https://doi.org/10.3390/su12135369
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, 102570. https://doi.org/10.1016/j.jretconser.2021.102570
Hair, J. F., Risher, J. J., Sarstedt, M., & 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
Hand, C., Dall'Olmo Riley, F., Harris, P., Singh, J., & Rettie, R. (2009). Online grocery shopping: The influence of situational factors. European Journal of Marketing, 43(9/10), 1205-1219. https://doi.org/10.1108/03090560910976447
Hansen, T. (2005). Consumer adoption of online grocery buying: A discriminant analysis. International Journal of Retail & Distribution Management, 33(2), 101-121. https://doi.org/10.1108/09590550510581449
Hansen, T. (2008). Consumer values, the theory of planned behaviour and online grocery shopping. International Journal of Consumer Studies, 32(2), 128-137. https://doi.org/10.1111/j.1470-6431.2007.00655.x
Hao, N., Wang, H. H., & Zhou, Q. J. (2020). The impact of online grocery shopping on stockpile behavior in Covid-19. China Agricultural Economic Review, 12(3), 459-470. https://doi.org/10.1108/caer-04-2020-0064
Heidarian, E. (2019). The impact of trust propensity on consumers' cause-related marketing purchase intentions and the moderating role of culture and gender. Journal of International Consumer Marketing, 31(4), 345-362. https://doi.org/10.1080/08961530.2019.1575316
Hernández, B., Jiménez, J., & José Martín, M. (2011). Age, gender and income: Do they really moderate online shopping behaviour? Online Information Review, 35(1), 113-133. https://doi.org/10.1108/14684521111113614
Kirk, C. P., & Rifkin, L. S. (2020). I'll trade you diamonds for toilet paper: Consumer reacting, coping and adapting behaviors in the COVID-19 pandemic. Journal of Business Research, 117, 124-131. https://doi.org/10.1016/j.jbusres.2020.05.028
Koch, J., Frommeyer, B., Schewe, G. (2020). Online shopping motives during the COVID-19 pandemic—Lessons from the crisis. Sustainability, 12, 10247. https://doi.org/10.3390/su122410247
Kuijpers, D., Wintels, S., & Yamakawa, N. (2020). Reimagining food retail in Asia after COVID-19. McKinsey & Company. https://www.mckinsey.com/~/media/mckinsey/industries/retail/our%20insights/reimagining%20food%20retail%20in%20asia%20after%20covid%2019/reimagining-food-retail-in-asia-after-covid-19.pdf
Lau, J. T., Griffiths, S., Choi, K. C., Tsui, H. Y. (2010). Avoidance behaviors and negative psychological responses in the general population in the initial stage of the H1N1 pandemic in Hong Kong. BMC Infectious Diseases, 10, 139. https://doi.org/10.1186/1471-2334-10-139
Leguina, A. (2015). A primer on partial least squares structural equation modeling (PLS-SEM). International Journal of Research & Method in Education, 38(2), 220-221. https://doi.org/10.1080/1743727X.2015.1005806
Lian, J. W., & Yen, D. C. (2014). Online shopping drivers and barriers for older adults: Age and gender differences. Computers in Human Behavior, 37, 133-143. https://doi.org/10.1016/j.chb.2014.04.028
Long, N. N., & Khoi, B. H. (2020). An empirical study about the intention to hoard food during COVID-19 pandemic. Eurasia Journal of Mathematics, Science and Technology Education, 16(7), em1857. https://doi.org/10.29333/ejmste/8207
Malhotra, N. K., Nunan, D., & Birks, D. F. (2017). Marketing research: An applied approach (5 ed.). Pearson Education Limited.
Marty, L., de Lauzon-Guillain, B., Labesse, M., & Nicklaus, S. (2021) Food choice motives and the nutritional quality of diet during the COVID-19 lockdown in France. Appetite, 157, 105005. https://doi.org/10.1016/j.appet.2020.105005
Mayakkannan, R. (2018). Impact of buying behaviour of consumers towards instant food products in Chennai District. International Journal of Pure and Applied Mathematics, 119(12), 16279-16286. https://doi.org/10.13140/RG.2.2.25497.57449
Mokhtarian, P. L. (2004). A conceptual analysis of the transportation impacts of B2C e-commerce. Transportation, 31(3), 257-284. https://doi.org/10.1023/B:PORT.0000025428.64128.d3
Moon, J., Choe, Y., & Song, H. (2021). Determinants of consumers’ online/offline shopping behaviours during the COVID-19 pandemic. International Journal of Environmental Research and Public Health, 18(4). https://doi.org/10.3390/ijerph18041593
Morganosky, M. A., & Cude, B. J. (2000). Consumer response to online grocery shopping. International Journal of Retail & Distribution Management, 28(1), 17-26. https://doi.org/10.1108/09590550010306737
Mylan, J., & Southerton, D. (2018). The social ordering of an everyday practice: The case of laundry. Sociology, 52(6), 1134-1151. https://doi.org/10.1177/0038038517722932
Naseri, M. B., & Elliott, G. (2011). Role of demographics, social connectedness and prior internet experience in adoption of online shopping: Applications for direct marketing. Journal of Targeting, Measurement and Analysis for Marketing, 19, 69-84. https://doi.org/10.1057/jt.2011.9
Naushad, V. A., Bierens, J. J., Nishan, K. P., Firjeeth, C. P., Mohammad, O. H., Maliyakkal, A. M. & Schreiber, M. D. (2019). A systematic review of the impact of disaster on the mental health of medical responders. Prehospital and disaster medicine, 34(6), 632-643. https://doi.org/10.1017/S1049023X19004874
Nielsen (2020). Key consumer behavior thresholds identified as the coronavirus outbreak evolves. Nielsen. https://nielseniq.com/global/en/insights/analysis/2020/key-consumer-behavior-thresholds-identified-as-the-coronavirus-outbreak-evolves-2/
Norum, P. S. (2008). Student internet purchases. Family and Consumer Sciences Research Journal, 36(4), 373-388. https://doi.org/10.1177/1077727X08318705
Oliveira, J., Santos, T., Sousa, M., Lopes, J. M., Gomes, S., & Oliveira, M. (2021). Physical health of food consumers during the COVID-19 pandemic. Social Sciences, 10(6), 1-14. https://doi.org/10.3390/socsci10060218
Pei, X. L., Guo, J. N., Wu, T. J., Zhou, W. X., & Yeh, S. P. (2020). Does the effect of customer experience on customer satisfaction create a sustainable competitive advantage? A comparative study of different shopping situations. Sustainability, 12(18), 7436. https://doi.org/10.3390/su12187436
Pordata (2018). Resident population, annual average: total and by age group. Pordata. https://www.pordata.pt/en/Portugal/Resident+population++annual+average+total+and+by+age+group-10-1126
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
Ringle, C. M., & Sarstedt, M. (2016). Gain more insight from your PLS-SEM results the importance-performance map analysis. Industrial Management and Data Systems, 116(9), 1865-1886. https://doi.org/10.1108/IMDS-10-2015-0449
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
Ruiu, G., & Ruiu, M. L. (2019). The complex relationship between education and happiness: The case of highly educated individuals in Italy. Journal of Happiness Studies, 20(8), 2631-2653. https://doi.org/10.1007/s10902-018-0062-4
Rogers, R. W. (1975). A Protection motivation theory of fear appeals and attitude change. The Journal of Psychology, 91(1), 93-114. https://doi.org/10.1080/00223980.1975.9915803
Shen, H., Namdarpour, F., & Lin, J. (2022). Investigation of online grocery shopping and delivery preference before, during, and after COVID-19. Transportation Research Interdisciplinary Perspectives, 14, 100580, https://doi.org/10.1016/j.trip.2022.100580
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
Sorić, T., Brodić, I., Mertens, E., Sagastume, D., Dolanc, I., Jonjić, A., Delale, E. A., Mavar, M., Missoni, S., Peñalvo, J. L., & Coklo, M. (2021). Evaluation of the Food Choice Motives before and during the COVID-19 Pandemic: A Cross-Sectional Study of 1232 Adults from Croatia. Nutrients, 13, 3165. https://doi.org/10.3390/nu13093165
Stylianou, A. C., Robbins, S. S., & Jackson, P. (2003). Perceptions and attitudes about e-commerce development in China: An exploratory study. Journal of Global Information Management (JGIM), 11(2), 31-47. https://doi.org/10.4018/jgim.2003040102
Taylor, M., Agho, K. E., Stevens, G., & Raphael, B. (2008). Factors influencing psychological distress during a disease epidemic: Data from Australia’s first outbreak of equine influenza. BMC Public Health, 8, 347. https://doi.org/10.1186/1471-2458-8-347
Tran, L. T. T. (2021). Managing the effectiveness of e-commerce platforms in a pandemic. Journal of Retailing and Consumer Services, 58, 102287. https://doi.org/10.1016/j.jretconser.2020.102287
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46, 186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
Wang, O., & Somogyi, S. (2018). Consumer adoption of online food shopping in China. British Food Journal, 120(12), 2868-2884. https://doi.org/10.1108/BFJ-03-2018-0139
Wang, C., Pan, R., Wan, X., Tan, Y., Xu, L., Ho, C. S., & Ho, R. (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, 1729. https://doi.org/10.3390/ijerph17051729
Wang, Y., Xu, R., Schwartz, M., Ghosh, D., & Chen, X. (2020). COVID-19 and retail grocery management: Insights from a Broad-based consumer survey. IEEE Engineering Management Review, 48(3), 202-211, 9146107. https://doi.org/10.1109/EMR.2020.3011054
Yoon, C. (2009). The effects of national culture values on consumer acceptance of e-commerce: Online shoppers in China. Information & Management, 46(5), 294-301. https://doi.org/10.1016/j.im.2009.06.001
Zhong, X. (2019). How delivery has transformed the restaurant industry. Deliverect. https://www.deliverect.com/en/blog/expert-talks/deliverect-ceo-zhong-xu-s-take-on-the-evolution-of-online-restaurant-operations
Zhu, Y., Chen, Y. P., Ayed, C., Li, B., & Liu, Y. (2020). An on-line study about consumers’ perception and purchasing behavior toward umami seasonings in China. Food Control, 110, 107037. https://doi.org/10.1016/j.foodcont.2019.107037
Zwanka, R. J., & Buff, C. (2020). COVID-19 generation: A conceptual framework of the consumer behavioral shifts to be caused by the COVID-19 pandemic. Journal of International Consumer Marketing, 33(1), 58-67. https://doi.org/10.1080/08961530.2020.1771646
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