A.W. Neumann References 1. Adomavicius, G, Tuzhilin, A Toward the next generation of recommender sys- tems: a survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering 17(6), 734-749(2005) 2. Avery, C, Resnick, P, Zeckhauser, R. The market for evaluations. American Eco- nomic review89(3),564-584(1999) 3. Emons, W: Credence goods and fraudulent experts. RAND Journal of Eco- nomiC28(1),107-120(1997) 4. Fudenberg, D, Tirole, J. Game Theory. MIT Press, Cambridge(1995 5. Geyer-Schulz, A, Hahsler, M, Jahn, M. Educational and scientific recommender systems. International Journal of Engineering Education 17(2), 153-163(2001) 6. Geyer-Schulz, A, Hahsler, M, Neumann, A, Thede, A: Behavior-based recom- mender systems as value-added services for scientific libraries. In: Bozdogan, H d)Statistical Data Mining Knowledge Discovery. Chapman Hall/CR (2003) 7. Geyer-Schulz, A, Neumann, A, Heitmann, A, Stroborn, K: Strategic positioning options for scientific libraries in markets of scientific and technical information the economic impact of digitization. Journal of Digital Information 4(2)(2003) 8. Geyer-Schulz, A, Neumann, A, Thede, A An architecture for behavior-based ibrary recommender systems. Information Technology and Libraries 22(4)(2003) 9. Herlocker, J L, Konstan, J.A., Terveen, L G, Riedl, J.T. Evaluating collaborative filtering recommender systems. ACM Transactions on Informations Systems 22(1) 53(2004) 10. Klatt, R, Gavriilidis, K, Kleinsimlinghaus, K, Feldmann, M.: Nutzung und Poten- ziale der innovativen Mediennutzung in Lernalltag der Hochschulen. BMBF-Studie (2001),http://www.stefi.de/ 11. Kotler, P. Marketing management: analysis, planning, and control, 4th edn Prentice-Hall, Englewood Cliffs(1980) 12. Kunz, A.H., Pfaff, D: Agency theory, performance evaluation, and the hypothetical onstruct of intrinsic motivation. Accounting, Organizations and Society 27(3) 275-295(2002) 13. Milgrom, P, Roberts, J. Economics, Organization and Management, Ist edn Prentice-Hall, Englewood Cliffs(1992) 14. Narayana, C L, Markin, R.J. Consumer behavior and product performance: An alternative conceptualization. Journal of Marketing 39 (4), 1-6 (1975) 15. Prendergast, C. The provision of incentives in firms. Journal of Economic Litera ture37(1),7-64(1999 16. Resnick, P, Varian, H R. Recommender systems. Communications of the ACM40(3),56-58(1997) othschild, M, Stiglitz, J. Equilibrium in competitive insurance markets: An essay on the economics of imperfect information. Quarterly Journal of Economics 80 629649(1976) 18. Schafer, J.B., Konstan, J.A., Riedl, J: Recommender system in e-commerce. Ir Proceedings of the ACM Conference on Electronic Commerce, pp. 115-152. ACM New York(1999) 19. Schafer, J B, Konstan, J.A., Riedl, J. E-commerce recommendation applications Data Mining and Knowledge Discovery 5, 115-152(2001) 20. Shapiro, C, Varian, H.R. Information rules. Harvard Business School, Boston438 A.W. Neumann References 1. Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender sys￾tems: a survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering 17(6), 734–749 (2005) 2. Avery, C., Resnick, P., Zeckhauser, R.: The market for evaluations. American Eco￾nomic Review 89(3), 564–584 (1999) 3. Emons, W.: Credence goods and fraudulent experts. RAND Journal of Eco￾nomic 28(1), 107–120 (1997) 4. Fudenberg, D., Tirole, J.: Game Theory. MIT Press, Cambridge (1995) 5. Geyer-Schulz, A., Hahsler, M., Jahn, M.: Educational and scientific recommender systems. International Journal of Engineering Education 17(2), 153–163 (2001) 6. Geyer-Schulz, A., Hahsler, M., Neumann, A., Thede, A.: Behavior-based recom￾mender systems as value-added services for scientific libraries. In: Bozdogan, H. (ed.) Statistical Data Mining & Knowledge Discovery. Chapman & Hall / CRC (2003) 7. Geyer-Schulz, A., Neumann, A., Heitmann, A., Stroborn, K.: Strategic positioning options for scientific libraries in markets of scientific and technical information – the economic impact of digitization. Journal of Digital Information 4(2) (2003) 8. Geyer-Schulz, A., Neumann, A., Thede, A.: An architecture for behavior-based library recommender systems. Information Technology and Libraries 22(4) (2003) 9. Herlocker, J.L., Konstan, J.A., Terveen, L.G., Riedl, J.T.: Evaluating collaborative filtering recommender systems. ACM Transactions on Informations Systems 22(1), 5–53 (2004) 10. Klatt, R., Gavriilidis, K., Kleinsimlinghaus, K., Feldmann, M.: Nutzung und Poten￾ziale der innovativen Mediennutzung im Lernalltag der Hochschulen, BMBF-Studie (2001), http://www.stefi.de/ 11. Kotler, P.: Marketing management: analysis, planning, and control, 4th edn. Prentice-Hall, Englewood Cliffs (1980) 12. Kunz, A.H., Pfaff, D.: Agency theory, performance evaluation, and the hypothetical construct of intrinsic motivation. Accounting, Organizations and Society 27(3), 275–295 (2002) 13. Milgrom, P., Roberts, J.: Economics, Organization and Management, 1st edn. Prentice-Hall, Englewood Cliffs (1992) 14. Narayana, C.L., Markin, R.J.: Consumer behavior and product performance: An alternative conceptualization. Journal of Marketing 39(4), 1–6 (1975) 15. Prendergast, C.: The provision of incentives in firms. Journal of Economic Litera￾ture 37(1), 7–64 (1999) 16. Resnick, P., Varian, H.R.: Recommender systems. Communications of the ACM 40(3), 56–58 (1997) 17. Rothschild, M., Stiglitz, J.: Equilibrium in competitive insurance markets: An essay on the economics of imperfect information. Quarterly Journal of Economics 80, 629–649 (1976) 18. Schafer, J.B., Konstan, J.A., Riedl, J.: Recommender system in e-commerce. In: Proceedings of the ACM Conference on Electronic Commerce, pp. 115–152. ACM, New York (1999) 19. Schafer, J.B., Konstan, J.A., Riedl, J.: E-commerce recommendation applications. Data Mining and Knowledge Discovery 5, 115–152 (2001) 20. Shapiro, C., Varian, H.R.: Information rules. Harvard Business School, Boston (1999)