Assessing customers perception of online shopping risks: A structural equation modeling–based multigroup analysis

Increasing evidence shows the role of perceived risk in customers' attitude and intention to use online shopping services. However, the literature shows disagreement regarding the types of risks that influence purchase intention. Therefore, this study aims to empirically identify the most relevant sources of risks and uncertainties associated with online shopping services and to investigate the influence of sociodemographic characteristics (e.g., gender, age, and online shopping experience) on the levels of perceived risk using data collected through a survey questionnaire. A total of 558 participants were selected across three countries (Jordan, Saudi Arabia, and Kuwait). The responses were evaluated using structural equation modeling and multigroup analysis. The analysis showed that of the tested types of risks and uncertainty, only three had a significant influence on customers' purchase decisions: financial risk, information risk, and privacy risk. Regarding the moderating role of sociodemographic variables, the analysis showed that previous experience has a significant moderating effect. At the same time, gender and age were found not to affect the relationship between perceived risks and customers' purchase intention. These findings may help online stores understand customers’ concerns when considering online shopping. The limitations and theoretical and managerial implications of the present study are discussed.