Customer’s satisfaction, delivery time inefficiency, expensive delivery fee, and limited delivery distance are all challenges faced when using an online food delivery service platform. The main objective of this study is to examine the relationship between customers’ satisfaction who have used and experienced online food delivery services and the independent variables which are; ease of use, availability, and privacy. The other objective is to identify which factors (ease of use, availability and privacy) significantly affect Klang Valley residents’ satisfaction on online food delivery service. The data were collected through online questionnaires from a snowball sample of 400 Klang Valley residents. In order to reach the respondents, the questionnaires were delivered online using Google Form. The data are analyzed by using the Pearson’s Correlation Coefficient and Multiple Linear Regression. The Pearson’s correlation coefficient found that there is a significant relationship between customers’ satisfaction towards online food delivery services. Additionally, the findings of the Multiple Linear Regression analysis indicate that all the factors have a significant impact on customers’ satisfaction towards online food delivery services. The researcher’s recommendation is to look at the relationships between riders’ views toward consumers and what they think of online food delivery services. The other recommendation is to broaden the target group and apply this type of study to different environments.
Ahmad, M., & Lasi, M. (2020). The attitudes on consumer perception towards viral marketing: A study on foodpanda food delivery in malaysia. International Journal of Research and Scientific Innovation, 7(9), 251–255.
Belanger, F., Hiller, J. S., & Smith, W. J. (2002). Trustworthiness in electronic commerce: the role of privacy, security, and site attributes. The journal of strategic Information Systems, 11(3-4), 245–270.
Hair, J. F., Ortinau, D. J., & Harrison, D. E. (2010). Essentials of marketing research (Vol. 2). McGraw-Hill/Irwin New York, NY.
Kassambara, A. (2018). Linear regression assumptions and diagnostics in r: Essentials. Statistical Tools for High-Throughput Data Analysis.
Koonce, G. L., & Kelly, M. D. (2014). Analysis of the reliability and validity of a mentor’s assessment for principal internships. Education Leadership Review, 15(2), 33–48.
Lestari, V. T., & Ellyawati, J. (2019). Effect of e-service quality on repurchase intention: 38 Testing the role of e-satisfaction as mediator variable. International Journal of Innovative Technology and Exploring Engineering (IJITEE), 8(7), 158–162.
Midi, H., Sarkar, S. K., & Rana, S. (2010). Collinearity diagnostics of binary logistic regression model. Journal of interdisciplinary mathematics, 13(3), 253–267.
Nayan, N. M., & Hassan, M. (2020). Customer satisfaction evaluation for online food service delivery system in malaysia. J. Inf. Syst. Technol. Manag, 5(9), 123–136.
Nicolaides, A. (2008). Service quality, empowerment and ethics in the south african hospitality and tourism industry and the road ahead using iso9000/1 (Unpublished doctoral dissertation).
Susanti, A., Soemitro, R. A. A., Suprayitno, H., & Ratnasari, V. (2019). Searching the appropriate minimum sample size calculation method for commuter train passenger travel behavior survey. Journal of Infrastructure & Facility Asset Management, 1(1)
Tranmer, M., & Elliot, M. (2008). Multiple linear regression. The Cathie Marsh Centre for Census and Survey Research (CCSR), 5(5), 1–5.
In-Text Citation: (Zahidi et al., 2022)
To Cite this Article: Zahidi, E. Z. M., Hanapiah, N. W. M., Nazmi, N., & Othman, J. (2022). The Satisfaction Factors on Online Food Delivery Service: A Case Study: Residents of Klang Valley, Malaysia. International Journal of Academic Research in Business and Social Sciences, 12(11), 2925– 2938.
Copyright: © 2022 The Author(s)
Published by Knowledge Words Publications (www.kwpublications.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 non-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
