Organizing Customer Knowledge in Academic Libraries


  • Farhad Daneshgar
  • Lyn Bosanquet


Knowledge taxonomy customer knowledge management knowledge management in library evaluation of customer knowledge innovative services academic libraries


Availability of sophisticated ICT infrastructure combined with emerging business processes such as various service orientation configurations, constitute major characteristics of many of today's libraries in western universities. This has created a vast amount of customer‑related information in libraries. This article provides a methodology for organising customer knowledge in academic libraries. A two‑dimensional Customer Knowledge Taxonomy (CKT) has been presented for organizing the customer knowledge, thus providing a formal and explicit specification to deliver a shared conceptualization of customer knowledge. Based on the proposed CKT, customer knowledge in academic libraries can be classified into (i) knowledge about customers, (ii) knowledge from customers and (iii) knowledge for customers. The knowledge in each of these three categories can be 'explicit' and 'tacit', thus providing six categories of customer knowledge. The second major contribution of this paper is to introduce a method for integrating the above first and second categories of customer knowledge in order to derive the third category. This integration methodology is based on an integrated cyclical knowledge flow model that consists of four phases including: (i) communication, (ii) knowledge sharing & dissemination, (iii) knowledge acquisition and application, and 'iv' knowledge utilization and evaluation. Through a qualitative research, the proposed framework, consisting of the CKT and the corresponding integrated cyclical knowledge flow model, was then applied to a large university library for coding and classifying the vast amounts of existing customer data residing in 2,500 interview scripts within the case study organization. In doing so, a uniform coding scheme had to be developed using a focus group methodology. Data were then stored into a customer knowledge base using the Laximancer software. The proposed framework was evaluated for consistency of conceptualisation to ensure reusability in similar environments. It is expected that similar organisations will benefit from the proposed methodology for classifying the customer knowledge in academic libraries and the associated evaluation methodology for design and development of integrated knowledge based systems which in turn will support emerging processes within the organization.



1 Jan 2010