The impact of internalization and familiarity on trust and adoption of recommendation agents

Computer agent technology is a useful technology for a customer to deal with information overload and search complexity in ecommerce. This study focus on how a product-brokering recommendation agent (RA) can be designed better so that a customer will be more likely to trust and then adopt the R A for the customer's purchase decision making. Our research model predicts that internalization and familiarity will increase both cognitive trust and emotional trust in an RA, which will then increase a customer's intention to adopt the R A either as a delegated agent or as a decision aid. Internalization refers to a customer's perception of how well an R A represents the customer's real needs. A customer's familiarity with an R A is expected to increase from the initial interaction through repeated interactions. We conducted a lab experiment to test the model. We also used a processtracing method to track the processes of trust formation. The results of the quantitative analysis (PLS analysis) support our hypotheses. (1) Internalization significantly increases a customer's intention to adopt an R A via increased cognitive trust and emotional trust. This implies that an R A should make sure a customer's specifications of product attributes (i.e. the expressed needs) actually represent the customer's real needs instead just taking a customer's specifications as they are, and that the focus of R A design should shift from product filtering toward customer representation. (2) This study shows that R A adoption is not purely rational or cognitive. R A adoption is affected by both cognitive trust and emotional trust. Emotional trust in an R A directly increases a customer's intention to adopt an RA, and emotional trust fully mediates the impact of cognitive trust on the intention to adopt an RA. The effect of emotional trust on the intention to adopt an R A as a delegated agent is higher than its impact on the intention to adopt an R A as a decision aid, while the effect of cognitive trust on the intention to adopt an R A as a delegated agent is lower than its effect on the intention to adopt an R A as a decision aid. This implies that emotional trust should be investigated in IT adoption and trust research. (3) The intention to adopt an R A as a delegated agent and the intention to adopt an R A as a decision aid are different levels of R A adoption that merit separate research. They are different at the conceptual, measurement, and behavioral levels. (4) The total effects of familiarity on the intention to adopt an R A are low, indicating that a customer decides on R A adoption mainly during her initial interaction with an R A . In addition, we used a process-tracing method to track how customer trust/distrust in an R A is formed. To our best knowledge, this is the first empirical study to trace the processes of trust/distrust formation. We developed two coding schemes in terms of: a) the source and the destination of a process, and b) trust/distrust formation via different ways that customers process their knowledge of an RA. The verbal protocols from 49 subjects, speaking 40 minutes per person on average, were collected. The results of the protocol analysis include: (1) Trust and distrust have different structures in terms of cognitive and emotional components. (2) Trust and distrust in an R A are formed via different ways that customers process their knowledge about an R A (3) An R A needs to be designed in different ways in order to facilitate cognitive and emotional trust while preventing cognitive and emotional distrust. (4) Repeated interactions change neither the structures of trust/distrust nor the proportion of different trust/distrust formation processes. However, the quantities of processes in all categories drop by almost 50% from initial interactions to second interactions, and then reach a stable level. (5) The level of R A internalization change neither trust/distrust structures, nor the way that customers process their knowledge in order to form trust or distrust. (6) Finally, an R A needs to be designed in different ways in order to facilitate cognitive trust vs. emotional trust. Similarly, the R A needs to be designed in different ways in order to prevent cognitive distrust vs. emotional distrust.