Personalized content recommendation and user satisfaction: Theoretical synthesis and empirical findings

Journal of Management Information Systems

Volumn 23, Issue 3, 2006, Pages 45-70

  Liang, Ting Peng ^a,b,c   Lai, Hung Jen ^d   Ku, Y I Cheng ^e  

^a Department of Information Systems ^*

^b NATIONAL SUN YAT SEN UNIVERSITY   (Taiwan)

^c IEEE

^d Department of Information Management   (Taiwan)

^e PROVIDENCE UNIVERSITY   (Taiwan)

Author keywords

Content recommendation; Personalization; Recommendation systems; User satisfaction

Indexed keywords

INFORMATION RETRIEVAL; INFORMATION USE; INTERNET; WEBSITES;

CONTENT RECOMMENDATION; PERSONALIZED SERVICES; RECOMMENDATION SYSTEMS; USER SATISFACTION;

USER INTERFACES;

EID: 34249092657     PISSN: 07421222     EISSN: None     Source Type: Journal    
DOI: 10.2753/MIS0742-1222230303     Document Type: Article

References (51)

1. Adomavicius, G., and Tuzhilin, A. Personalization technologies: A process-oriented perspective. Communications of the ACM, 48, 10 (2005), 83-90.
2. Allen, T.J. Managing the Flow of Information. Cambridge, MA: MIT Press, 1977.
3. Ansari, A.; Essegaier, S.; and Kohli, R. Internet recommendation systems. Journal of Marketing Research, 37, 3 (August 2000), 363-375.
4. Atwater, T.; Heeler, C.; and Brown, N. Foreshadosving the electronic publishing age: First exposure to Viesvtron. Journalism Quarterly, 62, 4 (1985), 807-815.
5. Barki, H., and Hartwick, J. Rethinking the concept of user involvement. MIS Quarterly, 13, 1 (1989), 53-63.
6. Bauer, T., and Leake, D. Using document access sequences to recommend customized information. IEEE Intelligent Systems, 17, 6 (2002), 27-33.
7. Berghel, H. Cyberspace 2000: Dealing with information overload. Communications of the ACM, 40, 2 (1997), 19-24.
8. Blumler, J.G. The role of theory in uses and gratifications studies. Communication Research, 6, 1 (January 1979), 9-36.
9. Bosman, J., and Renckstorf, K. Information needs: Problems, interests, and consumption. In K. Renckstorf (ed.), Media Use as Social Action: European Approach to Audience Studies. London: John Libbey, 1996, pp. 43-52.
10. Case, D.O. Looking for Information: A Survey of Research on Information Seeking, Needs, and Behavior. San Diego, CA: Academic Press, 2002.
11. Chung, W.; Chen, H.; and Nunamaker, J.A. Visual framework for knowledge discovery on the Web: An empirical study of business intelligence exploration. Journal of Management Information Systems, 21, 4 (Spring 2005), 57-84.
12. Dervin, B. From the mind's eye of the user: The sense-making qualitative-quantitative methodology. In J.D. Glazier and R.R. Powell (eds.), Qualitative Research in Information Management. Englewood, CO: Libraries Unlimited, 1992, pp. 61-84.
13. Dewan, R.; Jing, B.; and Seidmann, A. Adoption of Internet-based product customization and pricing strategies. Journal of Management Information Systems, 17, 2 (Fall 2000), 9-28.
14. Doll, W.J., and Torkzadeh, G. The measurement of end-user computing satisfaction. MIS Quarterly, 12, 2 (June 1988), 259-274.
15. Farhoomand, A.F., and Drury, D.H. Managing information overload. Communications of the ACM, 45, 10 (October 2002), 127-131.
16. Ferguson, D., and Perse, E. The World Wide Web as a functional alternative to television. Journal of Broadcasting and Electronic Media, 44, 2 (2000), 155-174.
17. Garramone, G.M.; Harris, A.C.; and Anderson, R. Uses of political computer bulletin boards. Journal of Broadcasting and Electronic Media, 30, 3 (1986), 325-339.
18. Grise, M., and Gallupe, B. Information overload: Addressing the productivity paradox in face-to-face electronic meeting. Journal of Management Information Systems, 16, 3 (Winter 1999-2000), 157-185.
19. Heeter, C., and Greenberg, B. Cable and program choice. In D. Zillmann and J. Bryant (eds.), Selective Exposure to Communication. Hillsdale, NJ: Lawrence Erlbaum, 1985, pp. 203-224.
20. Herbig, P., and Kramer, H. The effect of information overload on the innovation choice process: Innovation overload. Journal of Consumer Market, 11, 2 (June 1994), 45-54.
21. Ho, J., and Tang, K. Towards an optimal resolution to information overload: An infomediary approach. In S. Ellis, T. Rodden, and I. Zigurs (eds.), Proceedings of the 2001 International ACM SIGGROUP Conference on Supporting Group Work. Boulder, CO: ACM Press, 2001, pp. 91-96.
22. Ives, B., and Olson, M. User involvement and MIS success: A review of the literature. Management Science, 30, 5 (1984), 586-603.
23. Katz, E.; Blumler, J.G.; and Gurevitch, M. Utilization of mass communication by individual. In J.G. Blumler and E. Katz (eds.), The Use of Communications. Beverly Hills, CA: Sage, 1974, pp. 19-32.
24. Kaye, B.K., and Johnson, T.J. Online and in the know: Uses and gratifications of the Web for political information. Journal of Broadcasting and Electronic Media, 46, 1 (2002), 54-72.
25. Konstan, J.A.; Miller, B.N.; Maltz, D.; Hcrlockcr, J.L; Gordon, L.R.; and Riedl, J. GroupLens: Applying collaborative filtering to Usenet news. Communications of the ACM, 40, 3 (March 1997), 77-87.
26. Lai, H.J.; Liang, T.P.; and Ku, Y.C. Customized Internet news services based on customer profiles. In N. Sadeh (ed.), Proceedings of the Fifth International Conference on Electronic Commerce. New York: ACM Press, 2003, pp. 225-229.
27. Levy, M.R. Home video recorders: A user survey. Journal of Communication, 30, 4 (Fall 1980), 23-27.
28. Lin, C.A., and Jeffres, L. Predicting adoption of multimedia cable services. Journalism Quarterly, 75 (1998), 251-275.
29. Linden, G.; Smith, B.; and York, J. Amazon.com recommendations: Item-to-item collaborative filtering. IEEE Intelligent Systems, 7, 1 (2003), 76-80.
30. McKeen, J.D.; Guimaraes, T.; and Wetherbe, J.C. The relationship between user participation and user satisfaction: An investigation of four contingency factors. MIS Quarterly, 18, 4 (1994), 427-451.
31. McQuail, D., and Windahl, S. Communication Models for the Study of Mass Communication, 2d ed. New York: Longman, 1993.
32. Mock, K., and Vemuri, V. Information filtering via hill climbing, Wordnet, and index patterns. Information Processing and Management, 33, 5 (1997), 633-644.
33. Orad, D., and Kim, J. Implicit feedback for recommender systems. AAAI Technical Report WS-98-08: Workshop on Recommender Systems. American Association for Artificial Intelligence, Menlo Park, CA, 1998.
34. Parasuraman, A.; Zeithaml, V. A.; and Berry, L.L. SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64, 1 (1988), 12-40.
35. Perse, E.M., and Ferguson, D.A. The impact of the newer television technologies on television satisfaction. Journalism Quarterly, 70, 4 (1993), 843-853.
36. Renckstorf, K., and McQuail, D. Social action perspectives in mass communication research: An introduction. In K. Renckstorf (ed.), Media Use as Social Action: European Approach to Audience Studies. London: John Libbey, 1996, pp. 1-17.
37. Rosenberg, V. Factors affecting the preferences of industrial personnel for information gathering methods. Information Storage and Retrieval, 3, 3 (1967), 119-127.
38. Rubin, A.M. Television uses and gratifications: The interaction of viewing patterns and motivations. Journal of Broadcasting, 27, 1 (1983), 37-51.
39. Rubin, A.M., and Bantz, C.R. Uses and gratifications of videocassette recorders. In J.L. Salvaggio and J. Bryant (eds.), Media Use in the Information Age, Emerging Patterns of Adoption and Consumer Use. Hillsdale, NJ: Lawrence Erlbaum, 1989, pp. 181-195.
40. Sakagami, H., and Kamba, T. Learning personal preferences on online newspaper articles from user behaviors. Computer Networks and ISDN Systems, 29, 8 (1997), 1447-1455.
41. Salton, G. Automatic Text Processing: The Transformation, Analysis, and Retrieval of Information by Computer. Reading, MA: Addison-Wesley, 1989.
42. Saracevic, T., and Kantor, P. A study in information seeking and retrieving, II: Users, questions and effectiveness. Journal of the American Society for Information Science, 39, 3 (1998), 177-196.
43. Schafer, J.B.; Konstan, J.; and Riedl, J. Recommender systems in e-commerce. In M.P. Wellman (ed.), Proceedings of the First ACM Conference on Electronic Commerce. New York: ACM Press, 1999, pp. 158-166.
44. Sharma, S.; Durand, R.M.; and Gurarie, O. Identification and analysis of moderator variables. Journal of Marketing Research, 18, 3 (August 1981), 231-300.
45. Stephenson, W. The Play Theory of Mass Communication. Chicago: University of Chicago Press, 1967.
46. Toms, E.G. What motivates the browser? In T.D. Watson and D.K. Allen (eds.), Information Behavior: Proceedings of the Second International Conference on Research in Information Needs, Seeking, and Use in Different Contexts. London: Taylor Graham, 1999, pp. 191-208.
47. Tuzhilin, A. Report on the KDD2000 panel personalization and data mining: Exploring the synergies. SIGKDD Explorations, 2, 2 (December 2001), 115-116.
48. Vandenbosch, B., and Huff, S.L. Searching and scanning: How executives obtain information from executive information systems. MIS Quarterly, 21, 1 (1997), 81-107.
49. Wilson, P. Unused relevant information in research and development. Journal of American Society of Information Science, 46, 1 (1995), 45-51.
50. Zedeck, S. Problems with the use of "moderator" variables. Psychological Bulletin, 76, 4 (October 1971), 295-310.
51. Zhang, B., and Seo, Y. Personalized Web-document filtering using reinforcement learning. Applied Artificial Intelligence, 15, 1 (2001), 665-685.