An Analysis of the Determinants of Trust in Virtual Buying: An Interpretive Structural Modeling Approach

Abstract

The aim of the study is to determine what determinants influence trust in online purchases as well as how those determinants relate to one another in different contexts. The general design of this qualitative study includes a literature review, primary data gathering strategies, and qualitative analytic approaches. Relying on the purposive sample method, data are gathered through one-on-one interviews with a panel of experts utilizing a matrix-style questionnaire. Interpretive Structural Modeling (ISM) and Cross impact matrix multiplication applied to classification (MICMAC) have been the two main methods employed. As a result of its position at the bottom of the ISM model and in the independent quadrant of the MICMAC model, the determinant “return policies” is shown to be crucial, whereas the determinants “natural propensity to trust,” “attitude toward online shopping,” and “online impulse buying” are the least significant because they are at the top of the ISM. This study offers new important information about the determinants of trust in virtual buying. It offers a useful structural model and categorization of significant determinants. The study has certain unique data, methodological, and resource-related constraints. It is the qualitative methodology reveals relationships between determinants but does not quantify connections. The study is a conventional academic researcher effort with constrained physical/financial resources; as a result, the findings of the study outcomes is constrained.