Assessing the influence of e-commerce item recommender systems on user continuance intention for future use of recommender system

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2013
Shahmanzari, Masoud
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In recent years, there are several research studies on initial adaptation of information systems using recommender agents. This study, however, investigates the post-adaption behavior of users of such systems. As online e-commerce service websites are attracting users, existence of a recommender technology plays a substantial role in encouraging users to continue using system by helping them to discover and find items which they may interested and subsequently prefer to purchase. Researchers found that acquiring a new customer for a specific service or product costs five times more than retaining existing customer. Recommender systems are sophisticated, intelligent and automated software which help customers to make an ideal decision by providing high quality recommendations for them. Using online costumer behavior tracking or gain information from them, recommender v systems provide the most interesting service or products to customers. Implementing recommender systems increases online retailer‟s sales as well as their customer‟s loyalty. The main objective of this study is to assess the influence of e-commerce product recommender systems on consumer‟s continuance intention to use of information system in future. The proposed model in this study consists of four constructs including quality of decision, decision effort, overall satisfaction and continuance intention to use information system.
Recommender systems (Information filtering)., Information filtering systems., Electronic commerce., Information technology.
http://etd.lib.metu.edu.tr/upload/12616220/index.pdf
https://hdl.handle.net/11511/23082
Graduate School of Informatics, Thesis

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Citation Formats
M. Shahmanzari, “Assessing the influence of e-commerce item recommender systems on user continuance intention for future use of recommender system,” M.S. - Master of Science, Middle East Technical University, 2013.
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