PREDICTING GREEK INTERNET USERS’ INTENTIONS TO USE ONLINE SHOPPING: EMPIRICAL EVIDENCE USING AN EXTENDED TECHNOLOGY ACCEPTANCE MODEL

This study develops and validates an extended model to predict internet users’ intentions to buy online using a Business-to-Consumer (B2C) e-commerce platform, based on the Technology Acceptance Model (TAM). TAM has been introduced and applied as a reliable and robust model for predicting users’ adoption determinants of different technologies. However, researchers usually integrate additional constructs to the original model in order to improve its predictive power. Hence, in the proposed model, in addition to ease of use and usefulness, compatibility with the technology, an element of Innovation Diffusion Theory (IDT), and perceived risk are also proposed to be considered as determinants of customers’ attitudes and intentions toward on-line shopping acceptance. The model was validated using data collected from 931 internet users and analyzed using Partial Least Squares Path Modeling technique (PLS-PM). The results provided substantial support for all the proposed hypotheses and showed the significance of the extended constructs. The implications of the results to both researchers and practitioners are discussed at the end of the paper.