An Interpretive Structural Modelling Approach for Modelling the Factors Affecting Consumer Online Buying Behavior - Chauhan, Trishala; Nayyar, Ruchi (Indian Journal of Computer Science, 2020)
E-commerce industry is one the fastest growing sectors worldwide. It is not confined to any specific category or demography. Online shopping done at the click of a button is so convenient that consumers can easily navigate through large number of brands competing in the market and make the best possible choice. The present paper aims to explore the factors that endeavor consumers to purchase online. Subsequently, an interpretive structural modelling approach is employed to detect the interrelationship among these factors. Finally, an ISM model is formed that depicts the interrelationship among the factors that impact online buying behavior of consumers. Further MICMAC analysis is performed to categorize the factors on the basis of their driving and dependence power. Factors identified include price, product details, perceived risk, perceived benefits, attitude, trust, e-loyalty, and subjective norms. An ISM model depicting four levels of hierarchy is developed. MICMAC analysis reveals that price and perceived risk are dependent factors, whereas, perceived benefit, attitude, and trust are linking factors. Last, product details, e-loyalty, and subjective norms are categorized as independent factors.