Analysis of students’ online shopping behaviour using a partial least squares approach: Case study of Indonesian students

Abstract

The emergence of the Internet has influenced business methods in the world, which made online shopping has become popular due to its practical strengths. Students are one of the potential markets of online shopping in Indonesia. This research investigates the factors influencing university students’ online shopping behaviour in Surabaya as one of the fastest-growing cities in Indonesia, an important issue that has never been explored. The survey dataset is analyzed by using Structural Equation Modeling-Partial Least Squares (SEM-PLS) as well as PLS Predictive-Oriented Segmentation (PLS-OLS) to group the students based on their online behaviour. Both methods are applied due to the fact that the sample size is relatively small. The analysis shows that the students’ online shopping behaviour is significantly influenced by enjoyment, perceived risk, and social influence. Clustering with PLS-POS leads to three segments of students based on behaviour: those mostly influenced by social influence and perceived risk, those influenced by enjoyment and website quality, and those influenced by website quality and trust and security. These results can be a meaningful knowledge and input for the online business owners in Indonesia in designing their marketing strategy.

Keywords

• sem-pls
• online
• trust
• risk
• latent
• marketing