Paper Title
Analysing Website Usability Satisfaction Data: A Comparison of Structural Equation Modelling and Artificial Neural Network Approaches

Abstract
It is widely known that E-commerce marketplace is hypercompetitive, therefore, all it takes for a customer to shift loyalty is a click of a button thereby making website’s usability one of the most critical success factors. Thus, measuring usability of an E-commerce website is of utmost importance. For this purpose, questionnaire survey method was used, and 430 usable surveys provide data for the study. The data thus collected is analyzed by applying confirmatory technique i.e., Structural Equation Modeling and exploratory technique i.e., Artificial Neural Networks. Five (four independent and one dependent) constructs are modelled using the two techniques Both techniques suggest that Trust is most important in determining User Satisfaction followed by Service Quality. System quality and Content Quality do not have significant bearing on User Satisfaction in the present context. Keywords - Artificial Neural Networks, Back Propagation Algorithm, Content Quality, E-Commerce, Learning Algorithms, Trust, Transfer Function, Service Quality, System Quality, User Satisfaction. Document type - Article