Acceptance of recommendations to buy in online retailing

Nowadays, many online shops try to improve their customer service by personalization. Personal welcomings, individual assistance as well as recommendations to inform and buy are getting an integral part of the customer communication. These new elements are assumed to increase the retailer's share of wallet and - ideally at the same time - the customer's satisfaction with the online shop. However, till date only few studies have analyzed which external factors influence the customer's acceptance of such assistance. This paper closes this gap by an experiment, where a modified Technology Acceptance Model is used for measuring the customer's acceptance. Volunteers are offered an online shopping experience with individually generated recommendations to buy. The results show a high acceptance of the generated recommendations 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.