ProSeBiCA: development of new library services by means of conjoint analysis

Author:

Hermelbracht Antonia,Koeper Bettina

Abstract

PurposeThe purpose of this article is to provide a description of the project ProSeBiCA, carried out in order to adapt the marketing research tool conjoint analysis for the development of future library services. The paper describes the methodical approach, and provides an overview of the results gained by several user surveys.Design/methodology/approachThe methodical approach includes the use of adaptive conjoint analysis (ACA) and choice‐based conjoint analysis (CBC).FindingsConjoint analysis is an appropriate tool for the strategic development of library services. It provides detailed results by identifying users' preferences towards concrete services, and allows to deduce general statements about future trends for library services.Research limitations/implicationsFuture plans include cooperation with the Sheridan Libraries at Johns Hopkins University (Baltimore, Maryland), the Association of Research Libraries (ARL), and other interested partners in order to adapt the ProSeBiCA framework for US libraries and to integrate techniques used by the partners (CAPM, LibQUAL+TM). The extension of conjoint analysis to the evaluation of services for a fee will be an additional area of research.Practical implicationsService orientation in libraries can be based on a systematic approach. Depending on local circumstances, interested libraries can improve their service orientation in different ways, either by discussing the results of the analysis made in this project or by using the Conjoint Analysis questionnaire for a survey in their institutions.Originality/valueThe paper describes the current status and provides the latest results of ProSeBiCA. It is of interest to library managers and marketing researchers.

Publisher

Emerald

Subject

Library and Information Sciences,Information Systems

Reference7 articles.

1. Choudhury, S., Hobbs, B. and Lorie, M. (2002), “A framework for evaluating digital library services”, D‐Lib Magazine, Vol. 8 Nos 7/8, available at: www.dlib.org/dlib/july02/choudhury/07choudhury.html (accessed March 9, 2006).

2. Decker, R. and Hermelbracht, A. (2005), “Pattern detection with growing neural networks: an application to marketing and library data”, in Fleuren, H., den Hertog, D. and Kort, P. (Eds), Operations Research Proceedings 2004, Springer, Berlin, pp. 230‐7.

3. Decker, R. and Hermelbracht, A. (2006), “Planning and evaluation of new academic library services by means of web‐based conjoint analysis”, The Journal of Academic Librarianship, in press.

4. Heath, F., Kyrillidou, M., Webster, D., Choudhury, S., Hobbs, B., Lorie, M. and Flores, N. (2003), “Emerging tools for evaluating digital library services: conceptual adaptations of LibQUAL+ and CAPM”, Journal of Digital Information, Vol. 4 No. 2, available at: http://jodi.tamu.edu/Articles/v04/i02/Heath/ (accessed March 9, 2006).

5. Hermelbracht, A. and Koeper, B. (2006), “Der Einsatz der Conjoint‐Analyse in wissenschaftlichen Bibliotheken – Imagegewinn durch Dienstleistungsentwicklung ‘nahe am Kunden’”, in Lülfing, D. and Siebert, I. (Eds), Deutscher Bibliothekartag in Düsseldorf 2005, Klostermann, Frankfurt am Main, pp. 78‐92.

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