| Business-to-Customer electronic commerce presents substantial opportunities to businesses even after the recent downturn in the dot-com business. However, the usage rate of online shopping in Hong Kong and worldwide is still very low. Risk perceptions and lack of trust have been identified as two major obstacles to the adoption of online shopping. However, there is paucity of research that investigates the complex relationships among these variables. There are even fewer studies examining the effectiveness of various trust building mechanisms and their interactions. In this thesis, this issue is addressed by developing an integrative research model based upon insights from a number of theoretical perspectives, including the Triandis Model, social exchange theory, Sitkin and Pablo's model of risk behavior, and the risk-return framework, to understand the factors affecting the intention to use online shopping. Some of the previously overlooked variables and relationships, such as risk propensity of customers, facilitating conditions, trust in the transaction medium, and the mediating role of perceived risks, were included in the model. This model elucidates the adoption process of electronic commerce.; Three trust building mechanisms (i.e., third-party certification, reputation, and return policy) and a new construct, perceived process risk, were proposed and examined in this study.; The scenario survey method was used for data collection. 463 usable questionnaires were collected from respondents with diverse backgrounds. The validity and reliability of the newly developed scales for perceived process risks were demonstrated using factor analysis.; Regression results show that all three trust building mechanisms have significant positive effects on trust in the online vendor. Their effects are not simple ones; the different trust building mechanisms interact with one another to produce an overall effect on the level of trust. Path analyses, via structural equation modeling, provide support for the validity and usefulness of the research model in explaining the intention to use online shopping. Seventy-five percent of the variance of the intention is explained by its antecedents. Most of the relationships posited in the model gain support from the data. |
