Extended Acceptance Models for Recommender System Adaption, Case of Retail and Banking Service in Iran

Rise of ecommerce, which followed by Internet, has created some complexities in most industries. To overcome the information overload for Internet users, several Recommender Systems (RS) have been developed. RS is a kind of automated and sophisticated decision support system by monitoring the past actions of a group of customers to make a recommendation to individual members of the group to mitigate the problem of vast product and service information. The main issue is adoption and implementation of RS to make it suitable for society and avoid wasting time, energy and cost. Therefore, we compare several models of acceptance and introduce the critical and main parameters of a proper acceptance model for the product and service, which guarantee the result of RS employment. Two independent acceptance models with questionnaire will be derived for the retail and banking service industry, localized for Iran’s product and service context as a tool to measure customer’s intention to adopt an RS. To verify the validity of the parameters and selected models, two questioners are run. The statistical information and numerical result from LISREL presents the validity of the proposed extended TPB and TAM model for the retail and banking service context, respectively.

Extended Acceptance Models for Recommender System Adaption, Case of Retail and Banking Service in Iran Keywords:

Ecommerce , Recommender System , Adoption , Retail , Service , TPB , TAM