Customer's Choice in the Context of Cross-border E-Commerce: An Application of SEM

Kurzfassung

Emerging E-Commerce enables the purchasing and delivering activities during the Pandemic. However, along with the eased situation, i.e. in the Post-Pandemic era, the business models of E-Commerce are facing increasing numbers of competitive service providers and demanding customers. Therefore, I investigate the customers’ choice so to provide commercial insights to the E-Commerce service provider by applying SEM, i.e. Structural Equation Modeling. SEM is a mathematical modeling method which is based on factor analysis, SEM is often applied to investigate empirical research, such as in the field of psychology, economics, sociology, etc. In this thesis, one kind of the SEM: ESEM (Exploratory Structural Equation Modelling)+CFA (Confirmatory Factor Analysis) 1 model is used to explore which factors may significant impact on Customers Repurchase Intention (CRI) of textile products in the context of Cross-Border E-Commerce (CBEC) . Compared with the traditional CFA model, ESEM+CFA focuses on exploration and confirmatory of CRI-related research. This research on customers repurchase intention is conducted based on 187 feedback collected from questionnaire, as well as the factors and indicators are defined from different perspectives to observe the factor extraction, and their impacts on CRI among to 187 respondents within a model. The thesis is divided into 8 chapters: (1) Introduction: an overview of the background, motivation, aims and challenges in this article. (2) Literature Review: description of the literature and sources that provide theoretical support, and analytical concepts applied in this thesis. (3) Terminology: a description of the theoretical concepts, the threshold criteria and their cut-off values. (4) Methodology: introduction of the analytical approach, the applied software and operations, as well as the data processing methods. (5) Analysis: this chapter describes the data implementation in the software and the evaluation of the model fit, as well as also the model extraction. (6) Discussion: the comparison of different structure models and different sample sizes. (7) Results: a description of the analytical results and a discussion of the reasons for the results. (8) Conclusion and Future Research: a summary of the results, and a few steps to be future developed.