Recommendations to Buy in Online Retailing and Their Acceptance

Abstract

Personal welcomings, individual assistance, as well as recommendations to inform and buy are becoming an integral part in online retailing. These new so-called personalization elements are assumed to increase the retailer’s share of wallet and the customer’s satisfaction. However, up to now only little is known about which external factors influence the customer’s acceptance of such personalization elements. This chapter discusses the forms of recommendations to buy and how their acceptance can be measured using the well-known Technology Acceptance Model (TAM) approach. An experiment is used, where volunteers are offered an online shopping experience with individually generated recommendations to buy. The experiment shows how high the acceptance of the generated recommendations is and how close this acceptance is connected to the quality and shopping relevance of the recommendations. Even though the results are limited to the specific recommendation types used, they give important implications for an adequate design of modern online shops.