Hành vi sử dụng dịch vụ giao đồ ăn trực tuyến của khách hàng Việt Nam trong thời kỳ dịch bệnh COVID-19

Addo, P. C., Jiaming, F., Kulbo, N. B., & Liangqiang, L. (2020). COVID‐19: Fear appeal favoring purchase behavior towards personal protective equipment. Service Industries Journal, 40(7–8), 471–490. doi:10.1080/02642069.2020.1751823

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211. doi:10.1016/0749-5978(91)90020-t

Bearden, W. O., & Netemeyer, R. G. (1999). Handbook of Marketing Scales: MultiItem Measures for Marketing and Consumer Behavior Research (2nd ed.). Thousand Oaks: Sage Publication, Inc.

Bentler, P., & Bonett, D. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–606. doi:10.1037/0033-2909.88.3.588

Berg, M. B., & Lin, L. (2020). Prevalence and predictors of early COVID-19 behavioral intentions in the United States. Translational Behavioral Medicine, 10(4), 843–849. doi:10.1093/tbm/ibaa085

Bish, A., & Michie, S. (2010). Demographic and attitudinal determinants of protective behaviours during a pandemic: A review. British Journal of Health Psychology, 15(4), 797–824. doi:10.1348/13591 0710X485826

Byrne, B. M. (2010). Structural Equation Modeling with AMOS: Basic Concepts, Applications, and Programming (2nd ed.). UK: Routledge/Taylor & Francis Group. doi: 10.12691/education-4-2-10

Cai, S., & Jun, M. (2003). Internet users’ perceptions of online service quality: A comparison of online buyers and information searchers. Managing Service Quality, 13(6), 504–519. doi: 10.1108/09604520310506568

Chan, E. Y. Y., Huang, Z., Lo, E. S. K., Hung, K. K. C., Wong, E. L. Y., & Wong, S. Y. S. (2020). Sociodemographic predictors of health risk perception, attitude and behavior practices associated with health-emergency disaster risk management for biological hazards: The case of COVID-19 pandemic in Hong Kong, SAR China. International Journal of Environmental Research and Public Health, 17(11), 3869. doi: 10.3390/ijerph17113869

Chang, H.-H., & Meyerhoefer, C. (2020). COVID-19 and the demand for online food shopping services: Empirical evidence from Taiwan. American Journal of Agricultural Economics, 103(2), 448–465. doi:10.1111/ajae.12170

Chuo, H. Y. (2007). Theme park visitors’ responses to the SARS outbreak in Taiwan. Advances in Hospitality and Leisure, 3, 87–104. doi:10.1016/S1745-3542(06)03006-2

Dang, H. L., Li, E., Bruwer, J., & Nuberg, I. (2014). Farmers’ perceptions of climate variability and barriers to adaptation: lessons learned from an exploratory study in Vietnam. Mitigation and Adaptation Strategies for Global Change, 19, 531–548. doi: 10.1007/s11027-012-9447-6

Davis, F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. doi: 10.2307/249008

Deloitte. (2021). The Vietnam Consumer Survey: Staying resilient amidst headwinds. Retrieved from https://www2.deloitte.com/mm/en/pages/consumer-business/articles/vietnam-consumer-survey-2021.html

Gebrehiwot, T., & van der Veen, A. (2015). Farmers prone to drought risk: Why some farmers undertake farm-level risk-reduction measures while others not?. Environmental Management, 55, 588–602. doi: 10.1007/s00267-014-0415-7

Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51–90. doi:10.2307/30036519

Green, S. B., & Salkind, N. J. (2003). Using SPSS for Windows and Macintosh: Analyzing and Understanding Data (3rd ed.). New Jersey: Prentice Hall.

Grothmann, T., & Reusswig, F. (2006). People at risk of flooding: Why some residents take precautionary action while others do not. Natural Hazards, 38(1–2), 101–120.

doi:10.1007/s11069-005-8604-6

Hair, J. F., Anderson, R. E., Babin, B. J., & Black, W. C. (2010). Multivariate Data Analysis: A Global Perspective. Upper Saddle River. N.J., USA: Pearson.

Hill, J., & Lee, H.-H. (2012). Young generation Y consumers’ perceptions of sustainability in the apparel industry. Journal of Fashion Marketing and Management, 16, 477–491. doi: 10.1108/13612021211265863

Hirschberg, C., Rajko, A., Schumacher, T., & Wrulich, M. (2016). The changing market for food delivery. Retreived from https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/the-changing-market-for-food-delivery

Hobbs, J. E. (2020). Food supply chains during the COVID‐19 pandemic. Canadian Journal of Agricultural Economics/ Revue Canadienne D'agroeconomie, 68(2), 171–176. doi: 10.1111/cjag.12237

Hsieh, H. L., Kuo, Y. M., Wang, S. R., Chuang, B. K., & Tsai, C. H. (2017). A study of personal health record user's behavioral model based on the PMT and UTAUT integrative perspective. International Journal of Environmental Research and Public Health, 14(1), 8. doi: 10.3390/ijerph14010008

Huang, H. T., Kuo, Y. M., Wang, S. R., Wang, C. F., & Tsai, C. H. (2016). Structural factors affecting health examination behavioral intention. International Journal of Environmental Research and Public Health, 13(4), 395. doi: 10.3390/ijerph13040395

IMARC. (2020). Vietnam online food delivery market: Industry trends, share, size, growth, opportunity and forecast 2021–2026. Survey report. Retrieved from https://www.imarcgroup.com/vietnam-online-food-delivery-market

Janz, N. K., & Becker, M. H. (1984). The health belief model: A decade later. Health Education & Behavior, 11(1), 1–47. doi: 10.1177/10901981840110010

Jeong, J.-Y., & Ham, S. (2018). Application of the Health Belief Model to customers’ use of menu labels in restaurants. Appetite, 123, 208–215. doi:10.1016/j.appet.2017.12.012

Koufaris, M., & Hampton-Sosa, W. (2004). The development of initial trust in an online company by new customers. Information and Management, 41(3), 377–397. doi: 10.1016/j.im.2003.08.004

Lee, S.-H., & Hoang, T. B. N. (2010). Investigating the on-line shopping intentions of Vietnamese students : An extension of the theory of planned behaviour. World Transations on Engineering and Technology Education, 8(4), 471–476.

Malhotra, N. K., Kim, S. S., & Patil, A. (2006). Common method variance in IS research: A comparison of alternative approaches and a reanalysis of past research. Management Science, 52(12), 1865–1883. doi: 10.1287/mnsc.1060.0597

McIver, J. P., & Carmines, E. G. (1981). Unidimensional Scaling: Series. Quantitative Applications in the Social Sciences. United States: Sage Publications, Inc.

Milne, S., Sheeran, P., & Orbell, S. (2000). Prediction and intervention in health‐related behavior: A meta‐analytic review of protection motivation theory. Journal of Applied Social Psychology, 30(1), 106–143. doi: 10.1111/j.1559-1816.2000.tb02308.x

Nguyen, M. N. (2021). Online shopping behavior shifts during COVID-19 in Vietnam 2020. Survey Report in Rakuten Insight. Retrieved from https://www.statista.com/statistics/1128314/vietnam-change-of-online-purchase-behavior-during-coronavirus/

Nguyen, T. H. D., & Vu, D. C. (2020). Food delivery service during social distancing: Proactively preventing or potentially spreading COVID-19?. Disaster Medicine and Public Health Preparedness, 1–4. doi: 10.1017/dmp.2020.135

Nunnally, J. C. (1978). Psychometric Theory (2nd ed.). New York: McGraw-Hill.

Pavlou, P. A. (2003). Integrating trust and risk with the consumer acceptance of

electronic commerce: Technology acceptance model. International Journal of

Electronic Commerce, 7(3), 69–103. doi: 10.2307/27751067

Peterson, R. A. (1994). Meta-analysis of Alpha Cronbach’s coefficient. Journal of Consumer Research, 21(2), 381–391. doi: 10.1086/209405

Pigatto, G., Machado, J. G., Negreti, A., & Machado, L. (2017). Have you chosen your request? Analysis of online food delivery companies in Brazil. British Food Journal, 119(3), 639–657. doi: 10.1108/BFJ-05-2016-0207

Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63, 539–569. doi: 10.1146/annurev-psych-120710-100452

Youn, S.-Y., Lee, J. E., & Ha-Brookshire, J. (2021). Fashion consumers’ channel switching behavior during the COVID-19: Protection motivation theory in the extended planned behavior framework. Clothing and Textiles Research Journal, 39(2), 139–156. doi: 10.1177/0887302X20986521

Steiger, J. H. (1998). A note on multiple sample extensions of the RMSEA fit index structural equation modeling. A Multidisciplinary Journal, 5(4), 411–419. doi: 10.1080/10705519809540115

Sun, Y., Wang, N., Guo, X., & Peng, Z. (2013). Understanding the acceptance of mobile health services: A comparison and integration of alternative models. Journal of Electronic Commerce Research, 14(2), 183–200.

Tanner, J. F. Jr, Hunt, J. B., & Eppright, D. R. (1991). The protection motivation model: A normative model of fear appeals”. Journal of Marketing, 55(3), 36–45.

doi: 10.2307/1252146

Tarhini, A., Hone, K., & Liu, X. (2014). Measuring the moderating effect of gender and age on e-learning acceptance in England: A structural equation modeling approach for an extended technology acceptance model. Journal of Educational Computing Research, 51(2), 163–184. doi: 10.2190/EC.51.2.b

Teasdale, E., Yardley, L., Schlotz, W., & Michie, S. (2012). The importance of coping appraisal in behavioural responses to pandemic flu. British Journal of Health Psychology, 17(1), 44–59. doi: 10.1111/j.2044-8287.2011.02017.x

Tiwari, P., & Joshi, H. (2020). Factors influencing online purchase intention towards

online shopping of Gen Z. International Journal of Business Competition and Growth,

7(2), 175–187. doi: 10.1504/IJBCG.2020.111944

Venkatesh, V., & Davis, F. D. (2000). Theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 46(2), 186–204. doi: 10.1287/mnsc.46.2.186.11926

Yeo, V. C. S., Goh, S.-K., & Rezaei, S. (2017). Consumer experiences, attitude and behavioral intention toward online food delivery (OFD) services. Journal of Retailing and Consumer Services, 35, 150–162. doi: 10.1016/j.jretconser.2016.12.013

Wang, L., Law, R., Guillet, B. D., Hung, K., & Fong, D. K. C. (2015). Impact of hotel website quality on online booking intentions: eTrust as a mediator. International Journal of Hospitality Management, 47, 108–115. doi: 10.1016/j.ijhm.2015.03.012

Wood, S. (2013). Generation Z as consumers: Trends and innovation. Raleigh: Institute for Emerging Issues, NC State University.