Modelling customers' satisfaction towards online shopping using multiple linear regression / Shamsunarnie Mohamed Zukri ...[et al.] - Mohamed Zukri, Shamsunarnie; Mohd Fauzi, Noor Zafarina; Ibrahim, Nur Safwati; Azizan, Nurul Hafizah; Ibrahim, Nurul Bariyah; Hamzah, Nor Hazreeni (Universiti Teknologi MARA, Kelantan, 2023)
Online shopping can be defined as the process a customer takes to purchase a service or product over the internet. Online shopping is the easy solution for busy life in today's world. With the advancement of technology and the huge role of the internet, online shopping has been fulfilling customers' and businesses' needs. In Malaysia, online shopping has begun to grow, thus, it is essential to embrace issues that influence customers' satisfaction. The purpose of this study is to determine factors affecting customers' satisfaction towards online shopping. A cross-sectional design was used in this study conducted among Universiti Teknologi MARA Cawangan Kelantan, Kampus Kota Bharu (UiTMKB) students. A sample size of 336 students from Part 2 to Part 6 studying in semester October 2020 to February 2021 was obtained using Proportionate Stratified Random Sampling technique. A self-administered questionnaire was used to collect the data through Google Forms questionnaire. Pearson Correlation and Multiple Linear Regression was used as data analyses. There was a significant positive moderate linear association between independent variables (product and service quality, system security and delivery service) and customer satisfaction. Results indicate that the factors that affect customers' satisfaction towards online shopping were product and service quality and delivery service. It is recommended, in order to obtain a more precise result, that this sn1dy be carried out with larger respondents and different demographics. It is also recommended to include other variables. Improvement actions need to be planned, especially by online sellers, on the quality of products and services as well as delivery services for online purchases to satisfy customer satisfaction.