Planning and Evaluation of New Academic Library Services by Means of Web-based Conjoint Analysis

Journal of Academic Librarianship

Volumn 32, Issue 6, 2006, Pages 558-572

  Decker, Reinhold ^a   Hermelbracht, Antonia ^a  

^a BIELEFELD UNIVERSITY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 33751426574     PISSN: 00991333     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.acalib.2006.06.016     Document Type: Article

References (32)

1. See, e.g., Shaheen, M.A., "The Library of tfshe Future", SciTech World (September 2004) and Windau, B., "Library 2007", IFLA Conference 2003 - Berlin. Steele, C., "No Easy Rider? The Scholar and the Future of the Research Library, by Fremond Rider: A Review Article", The Journal of Librarianship and Information Science, 37 (2005) emphasizes that this subject is relevant and up-to-date since many years.
2. See, e.g., Green, P.E. & Srinivasan, V., "Conjoint Analysis in Consumer Research: Issues and Outlook", Journal of Consumer Research 5 (September 1978): 103-123, and Green, P.E., Srinivasan, V., "Conjoint Analysis in Marketing: New Developments with Implications for Research and Practice", Journal of Marketing 17 (1990): 3-19, for an introduction into the basic conjoint methodology. See also Halperin, M., "Determining User Preferences for Information Services," Drexel Library Quarterly 17 (No. 2, 1981): 88-98, Ramsing, K., Wish, J.R., "What do Library Users Want? A Conjoint Measurement Technique May Yield the Answer," Information Processing and Management 18 (2) (1982): 237-242, as well as Joseph, V. & Binwal, J.C., "Conjoint Analysis: Technique for Assessing Customer's Preferences on Library Products and Services," Journal of Library Information Science 19 (2) (1994): 75-85 for more specific considerations in the library context.
3. Halperin M., and Strazdon M. Measuring Students' Preferences for Reference Service: a Conjoint Analysis. Library Quarterly 50 2 (1980) 208-224
4. Crawford G.A. "A Conjoint Analysis of Reference Services in Academic Libraries". College and Research Libraries 55 3 (1994) 257-267
5. Karlowitsch M., Mueller U., and Vierschilling N. Introduction of an Electronic Document Delivery Service as a 'Complement' to Conventional Interlibrary Loan. In: Niggemann E., et al. (Ed). Controlling and Marketing in Academic Libraries (1998), Deutsches Bibliotheksinstitut, Berlin 114-163 (in German)
6. Further details about the ProSeBiCA project as whole and the empirical survey in particular are available at http://www.prosebica.de.
7. Wittink D.R., and Cattin P. Commercial Use of Conjoint Analysis: an Update. Journal of Marketing 53 3 (1989) 91-96
8. Wittink D.R., Vriens M., and Burhenne W. Commercial Use of Conjoint Analysis in Europe: Results and Critical Reflections. International Journal of Research in Marketing 11 1 (1994) 41-52
9. Green P.E., Krieger A.M., and Wind Y.J. Thirty Years of Conjoint Analysis: Reflections and Prospects. Interfaces 31 3 (2001) 56-73
10. Hartmann A., and Sattler H. Preference Measurement in Marketing Research Practice. Proceedings of the 31st Annual Conference of the European Marketing Academy (2002), CD-ROM Publication, Braga
11. Krapp A., and Sattler H. Rethinking Preference Measurement. Proceedings of the 30th Annual Conference of the European Marketing Academy (2001), CD-ROM Publication, Bergen
12. Green and Srinivasan, "Conjoint Analysis in Consumer Research".
13. See, e.g., Green, P.E., Krieger, A.M., "What's Right With Conjoint Analysis?", Marketing Research 14 (2002): 25-27.
14. Since the PWU values are computed by means of an iterative optimization technique individual measures of statistical significance are not available. Instead, the quality of the ACA results can be explored through an internal measure of goodness of fit.
15. See, e.g., Gustafsson, A., Herrmann, A. and Huber, F., "Conjoint Analysis as an Instrument of Market Research Practice", in Conjoint Measurement: Methods and Applications, edited by Gustafsson A., et al. (Berlin: Springer, 2000): 5-45.
16. See, e.g., Green, P.E., Krieger, A.M., Agarwal, M.K., "Adaptive Conjoint Analysis: Some Caveats and Suggestions", Journal of Marketing Research 5 (1991): 215-222 and Herrmann, A., Schmidt-Gallas, D., Huber, F., "Adaptive Conjoint Analysis: Understanding the Methodology and Assessing Reliability and Validity", in Conjoint Measurement: Methods and Applications, edited by Gustafsson A.,et al. (Berlin: Springer, 2000): 253-277 for a more detailed description of the relevant methodology.
17. Dahan E., Hauser J.R., Simester D., and Toubia O. Application and Test of Web-based Adaptive Polyhedral Conjoint Analysis. Working Paper (2002), Sloan School of Management, Cambridge
18. For details see Sawtooth Software, "ACA 5.0", Technical Paper Series (Sequim: Sawtooth Software, 2002).
19. Green, P.E., Krieger, A.M., Agarwal, M.K., "Adaptive Conjoint Analysis: Some Caveats and Suggestions".
20. Cohen S. Perfect Union, CBCA Marries the Best of Conjoint and Discrete Choice Models. Marketing Research 9 1 (1997) 12-17
21. McFadden D. The Choice Theory Approach to Market Research. Marketing Science 5 4 (1986) 275-297
22. Orme, B., "The CBC/HB System for Hierarchical Bayes Estimation-Version 3.2" (Sequim: Sawtooth Software, 1999) and Natter, M. and Feurstein, M., "Real World Performance of Choice-based Conjoint Models", European Journal of Operational Research 137 (2) (2002): 448-458.
23. The f(x) values given in the hierarchy have been deduced from the ACA study we are going to describe in the next section.
24. Burns A.C., and Bush R.F. Marketing Research: Online Research Applications (2005), Pearson, New Jersey
25. See Decker, R., Hermelbracht, A., "Pattern Detection with Growing Neural Networks-An Application to Marketing and Library Data", in: Operations Research Proceedings 2004, edited by Fleuren, H., et al. (Berlin: Springer, 2005): 230-237.
26. The adaptive structure of an ACA questionnaire enables a dynamic adjustment to individual service perceptions. Since ACA questionnaires are tailored to the specific requirements of the underlying estimation procedures they significantly differ from ordinary questionnaires, where, for instance, the arrangement of the questions can be the subject of additional analyses.
27. 2.
28. Figure 7 illustrates the possibly emerging differences in the scales of different attributes. To avoiding misinterpretations the individual scales of the attributes have always to be taken into account when the PWU values of different attributes are considered. Once again, we have to stress that direct comparisons are solely possible between the different levels of one attribute, but not between two or more attributes. Comparisons of the spans between the maximum and minimum PWU values of different attributes are valid if the numbers of levels are comparable.
29. See Sawtooth Software, "Choice-based Conjoint (CBC)", Technical Paper Series (Sequim: Sawtooth Software, 1999).
30. Orme, "The CBC/HB System".
31. See Paivio, A., Imagery and Verbal Processes (New York: Holt, Rinehart and Winston, 1971) and Paivio, A., Mental Representations: A Dual Coding Approach (New York: Oxford University Press, 1986).
32. Decker R., Hermelbracht A., and Klocke S. "An Empirical Study on the Future Service Offerings of Public Libraries". Bibliothek - Forschung und Praxis 29 (2005) 295-302 (in German)