ISSN: 2222-6990
Open access
The market size of food industry across Southeast Asia has recorded a tremendous and robust surge especially in the food delivery sector during 2020 due the global pandemic. As far back as previous years reports show that the dynamic use of the current innovative mobile technologies in the Food and Service industries has orchestrated a vast array of innovative entrepreneurial opportunities and start-up business ventures for app developers and accrued tremendous growth for the restaurant and food businesses such as Zomato, Uber Eats and Food Panda Statista (2018)
Food delivery applications (FDAs are mobile application that account for food delivery platform that account for daily used by an estimated 15 million deliveries solely in China and over a million in India. (Jindal, 2018). Online Food Delivery (OFD) platforms and Online-to-Offline (O2O) in collaboration are the two means by which mobile food apps curate the ecommerce of food business especially those in the restaurant-to-consumer markets through their platforms through online orderings which transcend into offline deliveries (Statista, 2019).
However, regardless of how online mobile applications have curated a compelling yet significant paradigm shift in online shopping and ecommerce as well as the food and hospitality, it leaves much to understand how consumers attribute, relate and perceive these innovative services. Scholarly research and existing literature aimed at ensuring the apprehension across the various aspects of these mobile applications and platform is imperative. So as to give insight on how consumer behavior is appreciated with regards to the use of these Food Delivery Application (FDAs) and Online Food Deliveries (OFDs).
Nevertheless, there is a crucial need to apprehend the ever evolving nature of these technologies and the dynamic nature of consumer behavior related to FDAs and OFDs that elicit a continuous scholarly overview into ascertaining an enriched accumulation of research jeered at facilitating a better and enriched understanding of the ever-changing area of food commerce. Since extensive similar research predominantly in the global markets spanning across Americas, Middle East, and Europe have been propounded to highlight the remarkably impetus the said food market through FDAs and OFDs have for significant investment (Hirschberg et al., 2016).
In the wake of the global manner of how business is now conducted through online-to-offline all contained around deliveries, notably the food commerce of offering food and services (Roh and Park, 2019). This study seeks to stray from the convention of merely studying the consumer’s attribute and behavior towards these food delivery applications and the impact e-service, customer loyalty and food quality thereof (Suhartanto et al., 2019), but rather culminate a better insight of the acceptance of these food ordering and delivery platforms with the inherent awareness of the current global Corona Virus pandemic raging across the world and south-east Asia with emphasis to the country Malaysia.
Inherent to the above research study one theory led is the consumer attitude and the end result aimed at leveling the intricacies of understanding the behavioral intention to use OFD services so as to investigate the notion of information system theory of the Technology Acceptance Model (TAM), serving as a framework to highlight the average consumers apprehension and acceptance and continuous use of these FDAs and OFDs. (Yeo et al., 2017). Alagoz and Hekimoglu (2012) also significantly explored the technology acceptance model ascertain the decision making processes entailed prior and during the online ordering of food through OFDS & FDAs while highlighting the consumers insight in this process as well as the role the theoretical model plays (Kang and Namkung, 2019a). Also , notable proposed study which hallmarks the unified theory of acceptance and use of technology (UTAUT) has been implored to comprehend the psychological factors that be and their impact to the use of mobile diet apps for ordering food online (Okumus et al., 2018). Consequentially, this study seeks to merged the prior knowledge of consumer attitudes and behavior with insight of the cited Technology Acceptance Model so as to delve into an in-depth comprehension of how these two propound a better understanding of why consumers ought to use or will use FDAs or OFDs during this health safety and conscious era of the global Corona Pandemic.
Azjen I., & Fishbien, M. (l980). Understanding attitudes and redirecting social behavior.Englewood—Cliffs, NJ: Prentice-Hall.
Azjen, I. (1991). "The theory of planned behavior". Organizational Behavior and Human Decision Process, 50 (2), 179-211
Ansa. (2020). Panedemia,Pagamenti DigitaliE Comodit_a_Cos_Il Food Delivery Ha Fatto Il Boom, available at :
https:www.ansa.it/canale_lifestle/notizie/food/2020/05/27/pandemia-pagamentidigitali-e-comodita-cosi-il-food-delivery-ha-fatto-il-boom_efb9561f-3bcbe-45da Dagamentidigitali-e-comodila-cosi-il-food-deliverv-ha-fatto-il-boom etb9561f-3cbe-45da- b3 e7026b0e042ca5 .html.
Barkhi, R., and Wallace, L. (2007). "The impact of personality type on purchasing decision in virtual stores", Information Technology Management, 8 (4), pp. 313-30.
Blosch, M. (2000). Customer knowledge, knowledge and Process Management Cuneyt,K.
Brown, S., and Venkateshh, V. (2005). Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS Quarterly, 29(3), 399-426.
Bums, N., and Grove, S. (1999). Understanding Nursing Research. (2nd ed). WB Saunders. Philadelphia
Burns, N., and Grove, S. (2001). The Practice of Nursing Research: Conduct, Critique and WB Saunders. Philadelphia
Charles H. W. (1998). E-commerce strategies. USA: Microsoft.
Creswell, J. W. (1995). Research design: Qualitative and quantitative approaches. Thousand Oaks. CA: Sage Publications.
Creswell, J. W. (1998). Qualitative inquiry and research design: Choosing among ?ve traditions.
Thousand Oaks. CA: Sage Publications.
Chen, J. F., Chang, I. F., Kao, C. W., & Huang, Y. M. (2016). Integrating ISSM into TAM to enhance digital library services: A case study of the Taiwan digital meta-library. Electronic Library, 34(1). 58773. https://doi.org110. 1l OS/EL701720147
Chen, I., Gillenson, M. I., & Sherrel, D. L. (2002). Enticing online consumers: an expended
technology acceptance perspective. Information & Management. 39(8). 705-719
Davis, F. D., Bagozzi, R. P., and Warshaw, P. R. (1989). User Acceptance of Computer
Technology: A Comparison of Two Theoretical Models. Management Science. 35. 982-1003.
Davis, F. D. (1989). “Perceived usefulness, perceived ease of use and user Acceptance of Information Technology", MIS Quarterly, 13 (3), pp. 319-340.
Dwivedi, Y. K. (2005). Investigating adoption, usage and impact of broadband: UK households,
Unpublished PhD Thesis. DISC. & Brunel University.
Holbrook, M. B. (2006). “Consumption experience, customer value, and subjective personal
Introspection: An illustrative photographic essay", Journal of Business Research, 59 (6),
pp. 714-725.
Holbrook, M. B. (1982) “Some Further Dimensions of Psycholinguistics, Imagery and Consumer
Response, Advances in Consumer Research, 9 (1), pp. ll2-l l7.
Hobbs, J. E. (2020). “Food supply chains during the COVID-19 pandemic", Canadian Journal of
Agricultural Economics, 68 (2), pp. 171-176
Horton, R. P., Buck, T., Waterson, R. E., & Clegg, C. W. (2001). Explaining Intranet Use the
Technology Acceptance Model, Journal of Information Technology, (14), 23749.
Howe, K. R. (1988). Against the quantitative-qualitative thesis or dogmas die hard. Educational Researcher, 17. 10-16
Huang, K. R., Chen, C. H., Chang, C. Y., & Lin, C. Y. (2020). Technology Acceptance, Growth
Needs, and Pedagogical Usability as Factors In?uencing Teachers’ Perception and Use of the
Geometer‘s Sketchpad Software. (2). pp.95-133.
Koufaris, M. (2002). Applying the Technology Acceptance Model and Flow Theory to Online
Consumer Behavior.Information Systems Research, 13(2), 205-223.369-381.
Lee, N. R., & Kotler, P. (2011). Social marketing: In?uencing behaviors for good. USA:
Sage
Li, R., & Suh, A. (2015). Factors in?uencing information credibility on social media platforms: Evidence from Facebook Pages. Procedia Computer Science 72 (2015) 314-328
Lau,T. C., & David, N. (2019). Online Food Delivery Services: Making Food Delivery the New
Normal, Journal of Marketing and Advances Practices. 1 (1), 2019 e-ISSN 2682«8170
Ling, K. C., Duad, D. Bin,Piev T. H., Keoy, H., & Hassan, P. (2011). Perceived Risk,
Perceived Technology, Online Trust for the Online Purchase Intention in Malaysia. International Journal of Business and Management. 6(6).
https//doi.org/IO.5539/ijbm.v6n69167
Steinfield, C. (1998). Electronic commerce and computer-mediated communication, New
Direction for research. Trends in Communication. 5, 19-36‘
Kardoyo, K., Nurkhin, A., & Arief, S. (2015). The determination of student intention to use mobile learning. PEOPLE: International Journal of Social Sciences Special Issue, 102-117
Kotler, P., Armstrong, G., Tolba, A., & Habib, A. (2011). “Principles of Marketing”, Pearson Education UK
Kotler, P., & Amstrong, G. (1997). Principles of Marketing (9th ed) Cliffs, NJ: Prentice Hall.
Mathwick C. (2001). The Effect of Dynamic Retail Experience on experiential perception of value: An internet and catalogue comparison, Journal on Retailing: 78 (1). pp. 51—647.
McKchnie, S., Winklhofer H., & Ennew, C. (2006). "Apply The Technology Acceptance Model to the retailing and financial services.” Edited by Doherty, NF International Journal of Retail and Distribution Management, 34.
Monsuwe, T. P., Dellaert, B. G., & Ruyter, K. D. (2004). What Drives Consumers to Shop Online?” A Literature Review, International Journal of Service Industry Management 15(1) 102-121
Onwuegbazie, A. J., & Leech, N. L. (2005). “On becoming a pragmatic researcher; Importance of Combining Qualitative and Quantitative Research Methodologies”. International Journal of Social Research Methodology. 8(5) 375.351
Polit, D., & Hungler B. (2004). Research Design & Methodology (6th ed) William and Wolkins.
Politecnico Di Milano. (2019) ”Osservatorio ecommerce B2C“. Available at: https//www.osseervatori.net/it_it/osservatoi/comunicati-stampa/food-grocery-online-crescitavalore-2019
Van der, H., Verhagen, T., & Creemers, M. (2003). Understanding online purchase intentions:
Contributions from technology and trust perspectives. European Journal of Information Systems. 12. 41-48
Venkatesh, V., & Brown, S. (2001). A longitudinal investigation of personal computers in homes: adoption determinants and emerging challenges, MIS Quarterly, 25(1), 71-102.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the Technology Acceptance
Model: four longitudinal ?eld studies, Management Science. 46(2), 186-204.
In-Text Citation: (Chung et al., 2022)
To Cite this Article: Chung, J. F., Al-Khaled, A. A. S., & Dickens, J-J. M. (2022). A Study on Consumer Attitude, Perceived Usefulness and Perceived Ease of Use to the Intention to Use Mobile Food Apps during COVID-19 Pandemic in Klang Valley, Malaysia. International Journal of Academic Research in Business and Social Sciences. 12(6), 987– 1000.
Copyright: © 2022 The Author(s)
Published by Human Resource Management Academic Research Society (www.hrmars.com)
This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non0-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode