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| Grounded Research on the Impacting Mechanism of Satisfaction with Intelligent Information Recommendation Services by Digital Libraries |
| Zha Xianjin1,2, Zhang Kun2,3, Yan Yalan4 |
1.Center for Studies of Information Resources, Wuhan University, Wuhan 430072
2.School of Information Management, Wuhan University, Wuhan 430072
3.National Demonstration Center for Experimental Library and Information Science Education, Wuhan University, Wuhan 430072
4.Evergrande School of Management, Wuhan University of Science and Technology, Wuhan 430065 |
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Abstract At present, the information environment of digital libraries has changed from lack of information to information overload. Thus, the corresponding service mode should accordingly be changed from “people looking for information” to “information looking for people.” The application of intelligent information recommendation services can be helpful in coping with the new challenges presented by the transformation of digital libraries. However, there is a lack of in-depth research on the impacting mechanism of satisfaction with intelligent information recommendation services by digital libraries at home and abroad. This study employs the grounded theory method to conduct coding analysis on original data obtained through interviews, eliciting 78 initial concepts, 24 basic categories. and 6 main categories. Based on these data, the relationship paths and mechanisms among categories are combed, and a theoretical model of the impacting mechanism of satisfaction with intelligent information recommendation services by digital libraries is developed. It is found that recommendation system quality, recommendation information quality, recommendation service quality, and recommendation form jointly affect satisfaction, with a moderating effect of user preference. The results of this research provide useful references for service optimization and the healthy development of digital libraries and also offer theoretical and practical implications.
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Received: 28 September 2020
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