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Customer Relationship Management as an Imperative for Academic Libraries: A Conceptual Model-121 E-Agent Framework

Customer Relationship Management as an Imperative for Academic Libraries: A Conceptual Model-121 E-Agent Framework

Amanda Xu, Sharon Q. Yang
Copyright: © 2016 |Pages: 34
ISBN13: 9781466694668|ISBN10: 1466694661|EISBN13: 9781466694675
DOI: 10.4018/978-1-4666-9466-8.ch072
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MLA

Xu, Amanda, and Sharon Q. Yang. "Customer Relationship Management as an Imperative for Academic Libraries: A Conceptual Model-121 E-Agent Framework." Web-Based Services: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2016, pp. 1641-1674. https://doi.org/10.4018/978-1-4666-9466-8.ch072

APA

Xu, A. & Yang, S. Q. (2016). Customer Relationship Management as an Imperative for Academic Libraries: A Conceptual Model-121 E-Agent Framework. In I. Management Association (Ed.), Web-Based Services: Concepts, Methodologies, Tools, and Applications (pp. 1641-1674). IGI Global. https://doi.org/10.4018/978-1-4666-9466-8.ch072

Chicago

Xu, Amanda, and Sharon Q. Yang. "Customer Relationship Management as an Imperative for Academic Libraries: A Conceptual Model-121 E-Agent Framework." In Web-Based Services: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 1641-1674. Hershey, PA: IGI Global, 2016. https://doi.org/10.4018/978-1-4666-9466-8.ch072

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Abstract

This chapter proposes a conceptual model, the 121 e-Agent Framework, for Customer Relationship Management (CRM) in academic libraries. Linked data and Semantic Web are the core components of this model. The implementation of the Framework will enable the participating U.S. academic libraries to reach out to their user communities through systematic customer group identification, differentiation, and interaction. The main contributions of the chapter are 1) applying Semantic Web technologies for CRM in academic libraries using the 121 e-Agent Framework, 2) defining the relevance challenges of CRM for academic libraries, 3) adding trust management to the linked data layer with a touch of tagging, categorizing, query log analysis, and social ranking as part of the underlying structure for distributed customer data filtering on the Web in CRM applications, and 4) making the approach extensible to address the challenges of CRM in other fields.

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