Advances in Marketing Management Support Systems

  • Berend Wierenga
  • Gerrit H. van Bruggen
  • Niek A. P. Althuizen
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 121)


Decision Support System Customer Relationship Management Technology Acceptance Model Analogical Reasoning Individual Customer 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. Aamodt, A., E. Plaza. 1994. Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. AI Communications 7(1) 39–59.Google Scholar
  2. Abraham, M.M., L.M. Lodish. 1987. PROMOTER: An Automated Promotion Evaluation System. Marketing Science 6(2) 101–23.CrossRefGoogle Scholar
  3. Ackoff, R.L. 1967. Management Misinformation Systems. Management Science 14(December) 147–156.CrossRefGoogle Scholar
  4. Adams, B., E.S. Berner, J. R. Wyatt. 2004. Applying Strategies to Overcome User Resistance in a Group of Clinical Managers to a Business Software Application: A Case Study. Journal of Organizational and End User Computing 16(4) 55–64.Google Scholar
  5. Alavi, M., E.A. Joachimsthaler. 1992. Revisiting DSS Implementation Research: A Meta-Analysis of the Literature and Suggestions for Researchers. MIS Quarterly 16(1) 95–116.CrossRefGoogle Scholar
  6. Althuizen, N.A.P., B. Wierenga. 2007. The Value of Analogical Reasoning for the Design of Sales Promotion Campaigns: A Case-Based Reasoning Approach. ERIM Working Paper. Erasmus University, 2008.Google Scholar
  7. Ambler, T., J. Roberts. 2006. Beware the Silver Metric: Marketing Performance Measurement Has to Be Multidimensional. MSI Reports. Marketing Science Institute.Google Scholar
  8. Barki, H., S.L. Huff. 1990. Implementing Decision Support Systems: Correlates of User Satisfaction and System Usage. INFOR 28(2) 89–101.Google Scholar
  9. Bass, F.M., R.D. Buzzel, M.R. Greene, Eds. 1961. Mathematical Models and Methods in Marketing. Homewood, Irwin, IL.Google Scholar
  10. Blattberg, R.C., R. Glazer, J.D.C. Little, Eds. 1994. The Marketing Information Revolution. Harvard Business School Press, Boston.Google Scholar
  11. Brien, R.H., J.E. Stafford. 1968. Marketing Information Systems: A New Dimension for Marketing Research. Journal of Marketing 32(3) 19–23.CrossRefGoogle Scholar
  12. Bucklin, R.E., D.R. Lehmann, J.D.C. Little. 1998. From Decision Support to Decision Automation: A 2020 Vision. Marketing Letters 9(3) 235–246.CrossRefGoogle Scholar
  13. Burke, R.R. 1991. Reasoning with Empirical Marketing Knowledge. International Journal of Research in Marketing 8(1) 75–90.CrossRefGoogle Scholar
  14. Burke, R.R., A. Rangaswamy, J. Wind, J. Eliashberg. 1990. A Knowledge-Based System for Advertising Design. Marketing Science 9(3) 212–29.CrossRefGoogle Scholar
  15. Buzzel, R.D. 1964. Mathematical Models and Marketing Management. Harvard University, Division of Research, Boston.Google Scholar
  16. Carlsson, C., E. Turban. 2002. DSS: Directions for the Next Decade. Decision Support Systems 33(2) 105–110.CrossRefGoogle Scholar
  17. Chakravarti, D., A. Mitchell, R. Staelin. 1979. Judgment Based Marketing Decision Models: An Experimental Investigation of the Decision Calculus Approach. Management Science 25(3) 251–263.CrossRefGoogle Scholar
  18. Davis, F.D. 1989. Perceived Usefulness, Perceived Ease Of Use, And User Acceptance of Information Technology. MIS Quarterly 13(3) 319–340.CrossRefGoogle Scholar
  19. Day, G.S. 2003. Creating a Superior Customer-Relating Capability. Sloan Management Review 44(3) 77–82.Google Scholar
  20. DeLone, W.H., E.R. McLean. 1992. Information Systems Success: The Quest for the Dependent Variable. Information Systems Research 3(1) 60–95.CrossRefGoogle Scholar
  21. Eliashberg, J., G.L. Lilien. 1993. Handbooks in Operations Research and Management Science. Volume 5: Marketing. Elsevier Science Publishers, Amsterdam.Google Scholar
  22. Engel, J.F., M.R. Warshaw. 1964. Allocating Advertising Dollars by Linear-Programming. Journal of Advertising Research 4(1) 42–48.Google Scholar
  23. Fader, P.S., B.G.S. Hardie, K.K. Lee. 2005. Counting Your Customers the Easy Way: an Alternative to the Pareto/NBD Model. Marketing Science 24(2) 275–284.CrossRefGoogle Scholar
  24. Ferrat, T.W., G.E. Vlahos. 1998. An Investigation of Task-Technology Fit for Managers in Greece and the US. European Journal of Information Systems 7(2) 123–136.CrossRefGoogle Scholar
  25. Finke, R.A., T.B. Ward, S.M. Smith. 1992. Creative Cognition: Theory, Research, and Applications. MIT Press, Cambridge, MAGoogle Scholar
  26. Frank, R.E., A.A. Kuehn, W.F. Massy, Eds.1962. Quantitative Techniques in Marketing Analyses. Irwin, Homewood, IL.Google Scholar
  27. Fudge, W.K., L.M. Lodish. 1977. Evaluation of the Effectiveness of a Model Based Salesman's Planning by Field Experimentation. Interfaces 8(1, Part 2) 97–106.CrossRefGoogle Scholar
  28. Gensch, D., N. Arersa, S.P. Moore. 1990. A Choice Modeling Market Information system that Enabled ABB Electric to Expand Its Market Share. Interfaces 20(1) 6–25.CrossRefGoogle Scholar
  29. Gentner, D. 1983. Structure-Mapping: A Theoretical Framework for Analogy. Cognitive Science 7(2) 155–70.CrossRefGoogle Scholar
  30. George, M., C. Ma, T. Mark, J.A. Petersen. 2007. Marketing Metrics and Financial Performance. Marketing Science Conference on Marketing Metrics and Financial Performance Vol. 07-300. MSI., Boston, Massachusetts.Google Scholar
  31. Gick, M.L., K.J. Holyoak.1980. Analogical Problem Solving. Cognitive Psychology 12(3) 306–55.CrossRefGoogle Scholar
  32. Glazer, R. 1999. Winning in Smart Markets. Sloan Management Review 40(4) 59–69.Google Scholar
  33. Goel,V., P. Pirolli. 1989. Motivating the Notion of Generic Design Within Information-Processing Theory: The Design Problem Space. AI Magazine 10(1) 19–36.Google Scholar
  34. Goldstein, D.K. 2001. Product Managers' Use of Scanner Data: A Story of Organizational Learning. Deshpande, R. Ed. Using Market Knowledge. Sage Publications, Thousand Oaks, CA.Google Scholar
  35. Gorry, G.A., M.S. Scott-Morton. 1971. A Framework for Management Information Systems. Sloan Management Review 13(Fall) 55–70.Google Scholar
  36. Gregan-Paxton, J., D.R. John. 1997. Consumer Learning by Analogy: A Model of Internal Knowledge Transfer. Journal of Consumer Research 24(December) 266–84.CrossRefGoogle Scholar
  37. Hoch, S.J., D.A. Schkade. 1996. A Psychological Approach to Decision Support Systems. Management Science 42(1) 51–64.CrossRefGoogle Scholar
  38. Holyoak, K.J., P. Thagard. 1995. Mental Leaps: Analogy in Creative Thought. MIT Press, Cambridge, MA.Google Scholar
  39. Jonassen, D.H. 2000. Toward a Design Theory of Problem Solving. Educational Technology Research and Development 48(4) 63–85.CrossRefGoogle Scholar
  40. Kayande, U., A. De Bruyn, G. Lilien, A. Rangaswamy, G.H. van Bruggen. 2006. How Feedback Can Improve Managerial Evaluations of Model-based Marketing Decision Support Systems. Institute for the Study of Business Markets, Penn State University.Google Scholar
  41. Kolodner, J.L. 1993. Case-based Reasoning. Morgan Kaufmann Publishers, Inc., San Mateo, CA.Google Scholar
  42. Kotler, PH. 1966. A Design for the Firm's Marketing Nerve Center. Business Horizons 9(3) 63–74.CrossRefGoogle Scholar
  43. Kotler, PH. 1971. Marketing Decision Making: A Model Building Approach. Holt, Rinehart and Winston, New York.Google Scholar
  44. Leake, D.B. 1996. CBR in Context: The Present and Future. Leake, D.B. Ed. Case-Based Reasoning: Experiences, Lessons, and Future Directions. AAAI Press/MIT Press, Menlo Park.Google Scholar
  45. Leonard-Barton, D., I. Deschamps. 1988. Managerial Influence In The Implementation Of New Technology. Management Science 34(10) 1252–1265.CrossRefGoogle Scholar
  46. Li, E.Y, R. McLeod, Jr., J.C. Rogers. 2001. Marketing information systems in Fortune 500 companies: a longitudinal analysis of 1980, 1990, and 2000. Information & Management 38(5) 307–322.CrossRefGoogle Scholar
  47. Lilien, G.L., PH. Kotler.1983. Marketing Decision Making: A Model-Building Approach. Harper & Row, New York.Google Scholar
  48. Lilien, G.L., PH. Kotler, K.S. Moorthy.1992. Marketing Models. Prentice-Hall, Englewood Cliffs NJ.Google Scholar
  49. Lilien, G.L., A. Rangaswamy. 2004. Marketing Engineering: Computer Assisted Marketing Analysis and Planning. (2nd ed.). PrenticeHall, Upper Saddle River NJ.Google Scholar
  50. Lilien, G.L, A. Rangaswamy, K. Starke, G.H. van Bruggen. 2001. How and Why Decision Models Influence Marketing Resource Allocations. University Park, PA. ISBM.Google Scholar
  51. Lilien, G.L., A. Rangaswamy, G.H. Van Bruggen, K. Starke. 2004. DSS Effectiveness in Marketing Resource Allocation Decisions: Reality vs. Perception. Information Systems Research 15(3) 216–35.CrossRefGoogle Scholar
  52. Little, J.D.C. 1970. Models and Managers: The Concept of A Decision Calculus. Management Science 16 B466–B485.CrossRefGoogle Scholar
  53. Little, J.D.C. 1979. Decision Support Systems for Marketing Managers. Journal of Marketing 43(3) 9–26.CrossRefGoogle Scholar
  54. Lodish, L.M., E. Curtis, M. Ness, M.K. Simpson. 1988. Sales Force Sizing and Deployment Using a Decision Calculus Model at Syntex Laboratories. Interfaces 18(1) 5–20.CrossRefGoogle Scholar
  55. Markman, A.B., C.P. Moreau. 2001. Analogy and Analogical Comparison. Gentner D., K.J. Holyoak, B.N. Kokinov, Eds.The Analogical Mind: Perspectives from Cognitive Science. The MIT Press, Cambridge, MA.Google Scholar
  56. Marsh, R.L., J.D. Landau, J.L. Hicks. 1996. How Examples May (and May Not) Constrain Creativity. Memory & Cognition 24(5) 669–80.CrossRefGoogle Scholar
  57. McCann, J.M., Gallagher, J.P. 1990. Expert Systems for Scanner Data Environments. Kluwer, Boston, MA.Google Scholar
  58. McIntyre, S.H. 1982. An Experimental Study of the Impact of Judgment-Based Marketing Models. Management Science 28(1) 17–33.CrossRefGoogle Scholar
  59. Montgomery, D.B., G.L. Urban.1969. Management Science in Marketing. Prentice Hall, Englewood Cliffs.Google Scholar
  60. Neslin, S.A, S. Gupta, W. Kamakura, J. Lu, Ch.H. Mason. 2006. Defection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models. Journal of Marketing Research 43(May) 204–211.CrossRefGoogle Scholar
  61. Payne, J.W., J. Bettman, E.J. Johnson. 1993. The Adaptive Decision Maker. Cambridge University Press, New York.Google Scholar
  62. Pettigrew, A.M. 1979. On Studying Organizational Cultures. Administrative Science Quarterly 24(4) 570–581.CrossRefGoogle Scholar
  63. Rai, A., S.S. Lang, R.B Welker. 2002. Assessing the Validity of IS Success Models: An Empirical Test and Theoretical Analysis. Information Systems Research 13(1) 50.CrossRefGoogle Scholar
  64. Rangaswamy, A. 1993. Marketing Decision Models: From Linear Programs to Knowledge-based Systems. Eliashberg, J., G.L. Lilien, Eds. Handbooks in Operations Research and Management Science: Marketing. Vol. 5. Elsevier Science Publishers, Amsterdam, 733–771.Google Scholar
  65. Reitman, W.R. 1965. Cognition and Thought. John Wiley and Sons, New York, NY.Google Scholar
  66. Reinartz, W., M. Krafft, W.D. Hoyer. 2004. The Customer Relationship Management Process: Its Measurement and Impact on Performance. Journal of Marketing Research 41(3) 293–305.CrossRefGoogle Scholar
  67. Riesbeck, C.K., R.C. Schank. 1989. Inside Case-Based Reasoning. Lawrence Erlbaum, Hillsdale, NJ.Google Scholar
  68. Rigby, D. 2001. Management Tools and Techniques: A survey. California Management Review 43(2) 139–160.Google Scholar
  69. Roberts, J.H. 2000. The Intersection of Modelling Potential and Practice. International Journal of Research in Marketing 17(2/3) 127–134.CrossRefGoogle Scholar
  70. Sanders, N.R., K.B. Manrodt. 2003. Forecasting Software in Practice: Use, Satisfaction, and Performance. Interfaces 33(5) 90–93.CrossRefGoogle Scholar
  71. Schank, R.C. 1982. Dynamic Memory. Cambridge University Press, Cambridge.Google Scholar
  72. Seddon, P.B. 1997. A Respecification and Extension of the Delone and McLean Model of IS Success. Information Systems Research 8(3) 240–253.CrossRefGoogle Scholar
  73. Simon, H.A. 1977. The New Science of Management Decision, revised edition. Prentice-Hall, Englewood Cliffs, NJ.Google Scholar
  74. Simon, H.A., A. Newell. 1958. Heuristic Problem Solving: The Next Advance in Operations Research. Operations Research 6(January–February) 1–10.CrossRefGoogle Scholar
  75. Swift, R.S. 2001. Accelerating Customer Relationships: Using CRM and Relationship Technologies. Prentice Hall, Upper Saddle River NJ.Google Scholar
  76. Todd, P., I. Benbasat. 1999. Evaluating the Impact of DSS, Cognitive Effort, and Incentives on Strategy Selection. Information Systems Research 10(4) 356–374.CrossRefGoogle Scholar
  77. Tversky, A., D. Kahneman. 1974. Judgment Under Uncertainty: Heuristics and Biases. Science 185 1124–30.CrossRefGoogle Scholar
  78. Udo, G.J., J.S. Davis.1992. Factors Affecting Decision Support System Benefits. Information & Management 23(6) 359–371.CrossRefGoogle Scholar
  79. Van Bruggen, G.H., A. Smidts, B. Wierenga. 1996. The Impact of the Quality of a Marketing Decision Support System: An Experimental Study. International Journal of Research in Marketing 13(4) 331–343.CrossRefGoogle Scholar
  80. Van Bruggen, G.H., A. Smidts, B. Wierenga.1998. Improving Decision Making by Means of a Marketing Decision Support System. Management Science 44(5) 645–58.CrossRefGoogle Scholar
  81. Venkatesh, V. 2000. Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model. Information Systems Research 11(4) 342–365.CrossRefGoogle Scholar
  82. Vlahos, G.E., T.W. Ferratt, G. Knoepfle. 2004. The Use of Computer-Based Information Systems by German Managers to Support Decision Making. Information & Management 41(6) 763–779.CrossRefGoogle Scholar
  83. Voss, J.F., T.A. Post. 1988. On the Solving of Ill-Structured Problems. Chi, M.T., R. Glaser, M.J. Farr, Eds. The Nature of Expertise. Lawrence Erlbaum, New Jersey.Google Scholar
  84. Wierenga, B. 1990. The First Generation of Marketing Expert Systems. Working Paper. Marketing Department, The Wharton school, University of Pennsylvania.Google Scholar
  85. Wierenga, B., A. Dalebout, S. Dutta. 2000. BRANDFRAME: A Marketing Management Support System for the Brand Manager. Wierenga, B., G.H. van Bruggen, Eds. Marketing Management Support System: Principles, Tools, and Implementation. Kluwer Academic Publisher, Boston, 231–262.Google Scholar
  86. Wierenga, B., P.A.M. Oude Ophuis. 1997. Marketing Decision Support Systems: Adoption, Use, and Satisfaction. International Journal of Research in Marketing 14(3) 275–290.Google Scholar
  87. Wierenga, B., G.H. van Bruggen. 1997. The Integration of Marketing Problem-Solving Modes and Marketing Management Support Systems. Journal of Marketing 61(3) 21.CrossRefGoogle Scholar
  88. Wierenga, B., and G.H. van Bruggen. 2000. Marketing Management Support Systems: Principles, Tools and Implementation. Kluwer Academic Publishers, Boston.Google Scholar
  89. Wierenga, B., G.H. van Bruggen. 2001. Developing a Customized Decision-Support System for Brand Managers. Interfaces 31(3, Part 2 of 2) S128–S45.CrossRefGoogle Scholar
  90. Wierenga, B., G.H. van Bruggen, R. Staelin. 1999. The Success of Marketing Management Support Systems. Marketing Science 18(3) 196–207.CrossRefGoogle Scholar
  91. Winer, R.S. 2001. A Framework for Customer Relationship Management. California Management Review 43(Summer) 89–105.Google Scholar
  92. Zinkhan, G.M., E.A. Joachimsthaler, T.C. Kinnear. 1987. Individual Differences and Marketing Decision Support System Usage and Satisfaction. Journal of Marketing Research 24(2) 208–214.CrossRefGoogle Scholar
  93. Zmud, R.W. 1979. Individual Differences and MIS Success: A Review of the Empirical Literature. Management Science 25(10) 966–975.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Berend Wierenga
    • 1
  • Gerrit H. van Bruggen
  • Niek A. P. Althuizen
  1. 1.RSM Erasmus University

Personalised recommendations