ON PERFORMANCE FEASIBILITY AND SERVICE QUALITY OF E-COMMERCE MARKETING BASED ON FUZZY LOGIC

Abstract

In the evolving era of digitization, the success of the modern e-commerce industry is measured by several key performance metrics. These performance indicators determine its efficiency and overall service quality in online business marketing. In this paper, we investigate the feasibility performance of e-commerce based on assessment of multiple qualitative parameters influencing the behaviour of online consumers. The attributes considered for evaluating the proficiency of e-commerce platforms and improving their service quality in the highly competitive global market include setup and operational cost, scalability, execution time, and resources accessibility. These multiple independent parameters with different units and range of values exhibit implicit imprecision and uncertainties, which can be effectively handled by multivariate fuzzy logic modeling. For a given dataset application of the presented fuzzy multi-criteria decision making framework, simulation results are used to compute the absolute error, root mean square error and normalized error in the estimation of fuzzy output variable of feasibility, thereby validating the proposed model. Furthermore, numerical results and analyses depict that our model offers substantial performance enhancement in terms of achieving higher accuracy than other estimation methodologies existing in literature with equivalent dataset size