Constructing a hybird model for the evaluation of the service quality of O2O platforms

Abstract

The spread of COVID-19 has led many people to turn to O2O platforms to buy daily supplies leading to a boom in the O2Oe-commerce industry. How to improve the service quality of O2O platforms to attract more customers has become an important concern for service providers. This study differs from previous statistical analysis studies in that it applies the data mining methodology to extract the key factors that affect the service quality of O2O e-commerce platforms. A hybrid multi-criteria decision-making method is then utilized to obtain the influence relationships and weights of the dimensions and criteria. The results suggest that privacy security, and reliability have a positive impact on social interaction, recommendation quality, efficiency and empathy. Empathy, social interaction and recommendation quality are the three most important factors for evaluating the service quality of O2Oe-commerce platforms. Finally, the theoretical implications and management implications based on the findings are discussed.