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Determining factors affecting intention to adopt banking recommender system: case of Iran
2008 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

By the rapid growth of information technology, banks in many parts of the world are trying to change their traditional methods and try to adapt in to new technologies. One of the most fundamental changes of banking industry is the movement from traditional banking to more electronic banking. But, beside the new facilities, this brings the problem of information overload. So preparing a proper information filtering and recommender system that could help customers to find appropriate services and facilities based on their needs, has become a crucial issue for banks. The purpose of this master thesis is to explain and analyze the issues that influence Iranian bank customer’s intentions, toward banking recommender system adoption. Based on a detailed literature review, a research model on the basis of an extended Technology Acceptance Model (TAM) with original variables perceived usefulness, perceived ease of use, attitude, intention to use, and external variables personality, personal innovativeness and perceived playfulness was employed. A quantitative research approach was conducted to get a better understanding of the issues. The empirical data was collected from sixteen Tejarat bank (A famous governmental bank in Iran) branches in seven different cities (classified in to four zones) of Iran by the means of questionnaires. Data analyses were done in accordance with the research questions and research model by SPSS 15 and Lisrel 8.53 softwares, and the hypotheses were analyzed by Structural Equation Modeling (SEM) technique. The results show that only personal innovativeness has no significant effect on personal usefulness of the system. The implications of the findings for theory and practice are discussed further. Finally the overall findings from respondent’s data show that they have great level of intention toward using a banking recommender system that could guide them through better choices among several available financial services.

Place, publisher, year, edition, pages
Keyword [en]
Technology, recommender system, technology acceptance model (TAM), Tejarat Bank, customers, structural equation modeling (SEM), intention to adopt
Keyword [sv]
URN: urn:nbn:se:ltu:diva-48893ISRN: LTU-PB-EX--08/036--SELocal ID: 6502d472-1a2f-4879-811e-45ac76af93c3OAI: diva2:1022238
Subject / course
Student thesis, at least 30 credits
Educational program
Business Administration, master's level
Validerat; 20101217 (root)Available from: 2016-10-04 Created: 2016-10-04Bibliographically approved

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