Factors that influence the behavioral intention of customers toward online food delivery service

Ram Paudel; Sanaz Tehrani; Muhammad Zohaib Waris

doi:10.62910/transame24008

Authors

Ram Paudel International American University (IAU), Los Angeles, California, USA Author https://orcid.org/0009-0002-8801-5452
Sanaz Tehrani International American University (IAU), Los Angeles, California, USA Author https://orcid.org/0000-0001-5202-0351
Muhammad Zohaib Waris Estonian Entrepreneurship University of Applied Sciences Author

DOI:

https://doi.org/10.62910/transame24008

Keywords:

Online food delivery services, consumer behavioral intent, brand trust, time-saving benefits, food safety risk perception.

Abstract

Many studies focus on components that influence consumers' behavioral intent to acquire an online food delivery service rather than those responsible for determining consumers' online behavioral intent to purchase service providers. Therefore, this study aims to identify such factors and assess the impact on the behavioral intention toward OFDs according to the consumer's point of view. Findings are supported by the explanatory approach and the quantitative research technique and were collected via a questionnaire accessible through a Google Form. Costumers living in Tallinn, Estonia, were polled using a non-probability sample approach, and 137 responses were received. Trust demonstrates the highest impact of 30.8% on the intention of using OFD service by customers, followed by time-saving benefits (21.0%), perceived ease of use (15.2%), and perceived usefulness (14.5%). Price-saving benefits and food safety risk perception are insignificant statistically, and the study assumptions are rejected. The study suggested that customers' intentions to use Online food delivery services must be tailored to their preferences and perceptions of the product's intrinsic and extrinsic worth and quality. Service providers must become more alert and efficient to keep everything safe and confidential. A secure system for sharing information should be implemented if at all practicable.

Author Biographies

Ram Paudel, International American University (IAU), Los Angeles, California, USA

Ram is currently pursuing a Doctorate in Business Administration (DBA) at American University (IAU) in the USA, building on his Master’s in Business Administration from the Estonian Entrepreneurship University and a Bachelor’s in Education and Psychology from Tribhuvan University in Nepal. His research focuses on global business strategy, AI-driven advancements in HR, and the behavioral aspects of real estate investment, bringing a multifaceted perspective to international business and workforce management. During his time in Estonia, he gained extensive international exposure by traveling to countries including Portugal, France, Finland, Sweden, Italy, Germany, Norway, Belgium, Latvia, Lithuania, and Denmark.
Sanaz Tehrani, International American University (IAU), Los Angeles, California, USA

Ph.D. in Engineering Management from a Multimedia University, concentrating on Operation Research with Strategic Decision Making. She has 25 years of teaching and research in higher education, graduate and undergraduate, and research in Methodologist. She has been a national research science and project/ program manager since 2000. She is involved in many National/ international projects in the USA, ASIA, and the Middle East. Twenty-five years of experience in manufacturing, automotive, semiconductor, and service industries. She is also involved with many aerospace projects from NASA, X-SPACE, Lockheed Martin, and other Aviation and Aerospace projects. Also, she is a trainer for self-development and self-actualization. She has also passed advanced teaching and communication training courses, management information systems, system development, financial planning, customer service, health and medical management, leadership and marketing, Lean Six Sigma, Different BI and AI development, Data analysis and analytics, Industry 4.0 and 5.0. Currently, she is a Professor at International American University, Los Angeles, California, USA.
Muhammad Zohaib Waris, Estonian Entrepreneurship University of Applied Sciences

Graduate Researcher at Estonian Entrepreneurship University of Applied Sciences, Estonia.

References

Ahuja, K.,Chandra, V., Lord, V., & Peens, C. (2021). Ordering in: The rapid evolution of food delivery. https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/ordering-in-the-rapid-evolution-of-food-delivery#/

Al Amin, M., Arefin, M. S., Alam, M. R., Ahammad, T., & Hoque, M. R. (2021). Using mobile food delivery applications during COVID-19 pandemic: An extended model of planned behavior. Journal of Food Products Marketing, 27(2), 105–126. https://doi.org/10.1080/10454446.2021.1906817

Alalwan, A. A. (2020). Mobile food ordering apps: An empirical study of the factors affecting customer e-satisfaction and continued intention to reuse. International Journal of Information Management, 50(1), 28–44. https://doi.org/10.1016/j.ijinfomgt.2019.04.008

Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99–110. https://doi.org/10.1016/j.ijinfomgt.2017.01.002

Alarcón D., Sánchez J. A., De Olavide U. (2015). Assessing convergent and discriminant validity in the ADHD-R IV rating scale: User-written commands for Average Variance Extracted (AVE), Composite Reliability (CR), and Heterotrait-Monotrait ratio of correlations (HTMT). In Spanish STATA meeting Universidad Pablo de Olavide. (Vol. 39, 1–39).

Ali, H., Zainal, V. R., & Ilhamalimy, R. (2020). Determination of purchase decisions and customer satisfaction: Analysis of brand image and service quality(review literature of marketing management). Dinasti International Journal of Digital Business Management, 2(1), 141–152. https://doi.org/10.31933/dijdbm.v2i1

Amir, H., & Rizvi, W. (2017). Influence of perceived risk and familiarity on willingness to transact in online food shopping in developing economies: An (extended) abstract. Creating Marketing Magic and Innovative Future Marketing Trends, 891–895. https://doi.org/10.1007/978-3-319-45596-9_162

Anderson, R. E., & Srinivasan, S. S. (2003). E-satisfaction and e-loyalty: A contingency framework. Psychology and Marketing, 20(2), 123–138. https://doi.org/10.1002/mar.10063

Bansal A (2019). On-demand food delivery apps are making life easier. Jungleworks. https://jungleworks.com/on-demand-food-delivery-apps-are-making-the-life-easier/

Bhattacherjee, A., Perols, J., & Sanford, C. (2008). Information technology continuance: A theoretic extension and empirical test. Journal of Computer Information Systems, 49(1), 17–26. https://doi.org/10.1080/08874417.2008.11645302

Carlos Martins Rodrigues Pinho, J., & Soares, A. M. (2011). Examining the technology acceptance model in the adoption of social networks. Journal of Research in Interactive Marketing, 5(2/3), 116–129. https://doi.org/10.1108/17505931111187767

Chai, L. T., & Yat, D. N. C. (2019). Online food delivery services: Making food delivery the new normal. Journal of Marketing advances and Practices, 1(1), 62-77.

Chen, H.-S., Liang, C.-H., Liao, S.-Y., & Kuo, H.-Y. (2020). Consumer attitudes and purchase intentions toward food delivery platform services. Sustainability, 12(23), Article 10177. https://doi.org/10.3390/su122310177

Cho, M., Bonn, M. A., & Li, J. (Justin). (2019). Differences in perceptions about food delivery apps between single-person and multi-person households. International Journal of Hospitality Management, 77, 108–116. https://doi.org/10.1016/j.ijhm.2018.06.019

Correa, J. C., Garzón, W., Brooker, P., Sakarkar, G., Carranza, S. A., Yunado, L., & Rincón, A. (2019). Evaluation of collaborative consumption of food delivery services through web mining techniques. Journal of Retailing and Consumer Services, 46, 45–50. https://doi.org/10.1016/j.jretconser.2018.05.002

Curtis, T., Abratt, R., Dion, P., & Rhoades, D. L. (2011). Customer satisfaction, loyalty, and repurchase: Some evidence from apparel consumers. Review of Business, 32(1), 47. https://commons.erau.edu/db-management/20

ERR, N (2022). Restaurants teaming up against food delivery services' price policies. ERR. https://news.err.ee/1098962/restaurants-teaming-up-against-food-delivery-services-price-policies

ERR, N. (2020, April 24). Food couriers expand delivery areas during pandemic crisis. ERR. https://news.err.ee/1081880/food-couriers-expand-delivery-areas-during-pandemic-crisis

Esko, T., Vieraankivi, M. L., Aho, H., Ernsteins, R., Kursinska, S., Sulga, D., ... & Munne, P. (2012). FOODWEB consumer awareness study report II: Estonia, Finland, Latvia.

Garaus, M. (2018). Confusion in internet retailing: Causes and consequences. Internet Research, 28(2), 477–499. https://doi.org/10.1108/intr-11-2016-0356

Garaus, M., & Wagner, U. (2016). Retail shopper confusion: Conceptualization, scale development, and consequences. Journal of Business Research, 69(9), 3459–3467. https://doi.org/10.1016/j.jbusres.2016.01.040

Groupon Grubhub promo codes. 2021. https://www.groupon.com/coupons/grubhub

Gunden, N., Morosan, C., & DeFranco, A. (2020). Consumers’ intentions to use online food delivery systems in the USA. International Journal of Contemporary Hospitality Management, 32(3), 1325–1345. https://doi.org/10.1108/ijchm-06-2019-0595

He, Z., Han, G., Cheng, T. C. E., Fan, B., & Dong, J. (2019). Evolutionary food quality and location strategies for restaurants in competitive online-to-offline food ordering and delivery markets: An agent-based approach. International Journal of Production Economics, 215, 61–72. https://doi.org/10.1016/j.ijpe.2018.05.008

Hoffmann, T., & Prause, G. (2018). On the regulatory framework for last-mile delivery robots. Machines, 6(3), Article 33. https://doi.org/10.3390/machines6030033

Hooper, D., Coughlan, J. and Mullen, M. R.(2008). Structural equation modelling: Guidelines for determining Model Fit. The Electronic Journal of Business Research Methods Volume 6 (1), 53 - 60. https://academic-publishing.org/index.php/ejbrm/article/view/1224/1187

Inman, J. J., Winer, R. S., & Ferraro, R. (2009). The interplay among category characteristics, customer characteristics, and customer activities on in-Store decision making. Journal of Marketing, 73(5), 19–29. https://doi.org/10.1509/jmkg.73.5.19

Islam, A., & Sultana, S. (2020). Role of e-commerce for the survival of food service industry during covid-19 (Dissertation). 1-64. https://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-35223

Jun, K., Yoon, B., Lee, S., & Lee, D.-S. (2021). Factors influencing customer decisions to use online food delivery service during the COVID-19 pandemic. Foods, 11(1), Article 64. https://doi.org/10.3390/foods11010064

Just Eat. (2016, December 12). The Takeaway Sector- Delivering Jobs & Economic Benefits to Ireland [Press release]. https://www.just-eat.ie/blog/press-releases/the-takeaway-sector-delivering-jobs-economic-benefits-to-ireland

Kandasivam, A. (2017). Competition, demand, changing behaviour: Making food delivery the new normal. Digital News Asia.

Kapoor, A. P., & Vij, M. (2018). Technology at the dinner table: Ordering food online through mobile apps. Journal of Retailing and Consumer Services, 43, 342–351. https://doi.org/10.1016/j.jretconser.2018.04.001

Kasmani, N., & Shafie, F. A. (202). Consumer perception on food safety of online food delivery services. In IFEH World Academic Conference on Environmental Health

Kassim, N., & Abdullah, N. A. (2010). The effect of perceived service quality dimensions on customer satisfaction, trust, and loyalty in e‐commerce settings. Asia Pacific Journal of Marketing and Logistics, 22(3), 351–371.

Kaur, P., Dhir, A., Talwar, S., & Ghuman, K. (2021). The value proposition of food delivery apps from the perspective of theory of consumption value. International Journal of Contemporary Hospitality Management, 33(4), 1129–1159. https://doi.org/10.1108/ijchm-05-2020-0477

Kietzmann, J., Paschen, J., & Treen, E. (2018). Artificial intelligence in advertising: How marketers can leverage artificial intelligence along the consumer journey. Journal of Advertising Research, 58(3), 263–267. https://doi.org/10.2501/jar-2018-035

Kim, J. J., & Hwang, J. (2020). Merging the norm activation model and the theory of planned behavior in the context of drone food delivery services: Does the level of product knowledge really matter? Journal of Hospitality and Tourism Management, 42, 1–11. https://doi.org/10.1016/j.jhtm.2019.11.002

Kim, M., & Qu, H. (2014). Travelers’ behavioral intention toward hotel self-service kiosks usage. International Journal of Contemporary Hospitality Management, 26(2), 225–245. https://doi.org/10.1108/ijchm-09-2012-0165

Li, C., Mirosa, M., & Bremer, P. (2020). Review of online food delivery platforms and their impacts on sustainability. Sustainability, 12(14), 1–17. https://doi.org/10.3390/su12145528

Lichtenstein N. (2020) The hidden cost of food delivery. Tech Crunch. 16. https://techcrunch.com/2020/03/16/the-hidden-cost-of-food-delivery

Mehrolia, S., Alagarsamy, S., & Solaikutty, V. M. (2020). Customers response to online food delivery services during COVID‐19 outbreak using binary logistic regression. International Journal of Consumer Studies, 45(3), 396–408. https://doi.org/10.1111/ijcs.12630

Mendoza-Tello, J. C., Mora, H., Pujol-Lopez, F. A., & Lytras, M. D. (2018). Social commerce as a driver to enhance trust and intention to use cryptocurrencies for electronic payments. IEEE Access, 6, 50737–50751. https://doi.org/10.1109/access.2018.2869359

Momani, A. M. (2020). The unified theory of acceptance and use of technology. International Journal of Sociotechnology and Knowledge Development, 12(3), 79–98. https://doi.org/10.4018/ijskd.2020070105

Momani, A. M., Jamous, M. M., & Hilles, S. M. S. (2017). Technology acceptance theories. International Journal of Cyber Behavior, Psychology and Learning, 7(2), 1–14. https://doi.org/10.4018/ijcbpl.2017040101

Moondra, C., Mangwani, H. K., Deshpande, K., Bundela, A. S., & Namdev, K. (2020). Impact of online food delivery on customers. International Research Journal of Engineering and Technology (IRJET), 7(4), 2362-2364.

Novita, D., Husna, N., Azwari, A., Gunawan, A., Trianti, D., & Bella, C. (2020). Behavioral intention toward online food delivery (OFD) services (the study of consumer behavior during pandemic covid-19). Jurnal Manajemen Dan Bisnis (Performa), 17(1), 52–59. https://doi.org/10.29313/performa.v17i1.7233

Ogunsemi, O. I. (2020). Consumer behavior towards online food delivery services in Ireland-a segmental analysis(Doctoral dissertation, Dublin Business School).

Old, M. (2021). Improving Regulatory Delivery in Food Safety. https://doi.org/10.1787/bf34907e-en

Prabowo, G. T., & Nugroho, A. (2019). Factors that influence the attitude and behavioral intention of Indonesian users toward online food delivery service by the go-food application. Proceedings of the 12th International Conference on Business and Management Research (ICBMR 2018), 72, 204–210. https://doi.org/10.2991/icbmr-18.2019.34

Ramayah, T., & Ignatius, J. (2005). Impact of perceived usefulness perceived ease of use, and perceived enjoyment on intention to shop online. ICFAI Journal of Systems Management (IJSM), 3(3), 36-51.

Ray, A., & Bala, P. K. (2021). User generated content for exploring factors affecting intention to use travel and food delivery services. International Journal of Hospitality Management, 92, Article 102730. https://doi.org/10.1016/j.ijhm.2020.102730

Ray, A., Dhir, A., Bala, P. K., & Kaur, P. (2019). Why do people use food delivery apps (FDA)? A uses and gratification theory perspective. Journal of Retailing and Consumer Services, 51(1), 221–230. https://doi.org/10.1016/j.jretconser.2019.05.025

Sands, S., Ferraro, C., Campbell, C., & Pallant, J. (2016). Segmenting multichannel consumers across search, purchase and after-sales. Journal of Retailing and Consumer Services, 33, 62–71. https://doi.org/10.1016/j.jretconser.2016.08.001

Sjahroeddin, F. (2018). The role of E-S-Qual and food quality on customer satisfaction in online food delivery service. Prosiding Industrial Research Workshop and National Seminar, 9, 551–558. https://doi.org/10.35313/irwns.v9i0.1097

Soosalo, T, (2022). The volume of e-commerce transactions has leaped up during the pandemic. https://www.eestipank.ee/en/press/volume-e-commerce-transactions-has-leapt-during-pandemic-26012022

Statista. (2020). eServices: Market data & analysis. https://www.statista.com/study/42306/eservices-report

Statista. (2021). Online food delivery. https://www.sstatista.com/outlook/dmo/eservices/online-food-delivery/estonia

Strielkowski, W., Gryshova, I., & Kalyugina, S. (2017). Modern technologies in public administration management: A Comparison of Estonia, India and United Kingdom. Administration & Public Management Review, 28, 174-185. https://www.ceeol.com/search/viewpdf?id=743057

Suhartanto, D., Helmi Ali, M., Tan, K. H., Sjahroeddin, F., & Kusdibyo, L. (2019). Loyalty toward online food delivery service: the role of e-service quality and food quality. Journal of Foodservice Business Research, 22(1), 81–97. https://doi.org/10.1080/15378020.2018.1546076

Tata, S. V., Prashar, S., & Parsad, C. (2020). Examining the influence of satisfaction and regret on online shoppers’ post-purchase behaviour. Benchmarking: An International Journal, 28(6). 1987-2007. https://doi.org/10.1108/bij-06-2020-0332

TNS Emor (2008) Ostu- ja tarbimiskäitumise uuring. Eesti elanike väärtushinnangud

Tran, V.-D. (2021). Improved expectation-maximization algorithm for unknown reverberant audio-source separation. Journal of Applied Data Sciences, 2(4), 174–182. https://doi.org/10.47738/jads.v2i4.45

Tsap, V., Lips, S., & Draheim, D. (2020). Analyzing eID Public Acceptance and User Preferences for Current Authentication Options in Estonia. Springer Link, 12394, 159–173. https://doi.org/10.1007/978-3-030-58957-8_12

Vazquez, D., & Xu, X. (2009). Investigating linkages between online purchase behaviour variables. International Journal of Retail & Distribution Management, 37(5), 408–419. https://doi.org/10.1108/09590550910954900

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478. https://doi.org/10.2307/30036540

Wang, J., Shen, X., Huang, X., & Liu, Y. (2021). Influencing factors of the continuous usage intention of consumers of online food delivery platform based on an information system success model. Frontiers in Psychology, 12, Article 716796. https://doi.org/10.3389/fpsyg.2021.716796

Wang, Y.-S., Tseng, T. H., Wang, W.-T., Shih, Y.-W., & Chan, P.-Y. (2019). Developing and validating a mobile catering app success model. International Journal of Hospitality Management, 77, 19–30. https://doi.org/10.1016/j.ijhm.2018.06.002

Yarış, A., & Aykol, Ş. (2021). The impact of social media use on restaurant choice. Anatolia, 33(3), 1–13. https://doi.org/10.1080/13032917.2021.1931379

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. https://doi.org/10.1016/j.jretconser.2016.12.013

Yuan, S., Ma, W., Kanthawala, S., & Peng, W. (2015). Keep using my health apps: Discover users’ perception of health and fitness apps with the UTAUT2 model. Telemedicine and E-Health, 21(9), 735–741. https://doi.org/10.1089/tmj.2014.0148

Zhou, T., Lu, Y., & Wang, B. (2010). Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior, 26(4), 760–767. https://doi.org/10.1016/j.chb.2010.01.013

Factors that influence the behavioral intention of customers toward online food delivery service

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