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The Past, the Present and the Future of Marketing Decision Models

Introduction to the Handbook

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Book cover Handbook of Marketing Decision Models

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 121))

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Notes

  1. 1.

    Pierson (1959)

  2. 2.

    Gordon and Howell (1959)

  3. 3.

    See also Chapter 16 of this Handbook

References

  • Aaker, D.A. 1975. ADMOD: An Advertising Decision Model. Journal of Marketing 12(1) 37–45.

    Article  Google Scholar 

  • Abraham, M.M., L.M. Lodish. 1987. PROMOTER: An Automated Promotion Evaluation System. Marketing Science 6(2) 101–123.

    Article  Google Scholar 

  • Abraham, M.M., L.M. Lodish. 1993. An Implemented System for Improving Promotion Productivity Using Store Scanner Data. Marketing Science 12(3) 248–269.

    Article  Google Scholar 

  • Alderson, W. 1962. Introduction in Frank., R.E., A.A. Kuehn, and W.F. Massy, eds. Quantitative Techniques in Marketing Analysis. Irwin, Homewood, IL, (xi–xvii).

    Google Scholar 

  • Ansari, A., C.F. Mela. 2003. E-Customization. Journal of Marketing Research 40(2) 131–45.

    Article  Google Scholar 

  • Asmus, G., J.U. Farley, D.R. Lehmann. 1984. How Advertising Affects Sales: Meta-Analysis of Econometric Results. Journal of Marketing Research 21(1) 65–74.

    Article  Google Scholar 

  • Bass, F.M., R.D. Buzzel, M.R. Greene et al., Eds. 1961. Mathematical Models and Methods in Marketing. Homewood, Irwin, IL.

    Google Scholar 

  • Bass, F.M., J. Wind. 1995. Special Issue: Empirical Generalizations in Marketing. Marketing Science 14(3, Part 2 of 2).

    Google Scholar 

  • Blattberg, R.C., R. Glazer, J.D.C. Little, Eds.1994. The Marketing Information Revolution. Harvard Business School Press, Boston, MA.

    Google Scholar 

  • 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.

    Article  Google Scholar 

  • Bucklin, R.E., C. Sismeiro. 2003. A Model of Web Site Browsing Behavior Estimated on Clickstream Data. Journal of Marketing Research 40(3) 249–67.

    Article  Google Scholar 

  • Burke, R.R., A. Rangaswamy, Y.Wind, J. Eliashberg. 1990. A Knowledge-Based System for Advertising Design. Marketing Science 9(3) 212–229.

    Article  Google Scholar 

  • Buzzel, R.D. 1964. Mathematical Models and Marketing Management. Harvard University, Division of Research, Boston, MA.

    Google Scholar 

  • Chatterjee, P.D., L. Hoffman, T.P. Novak. 2003. Modeling the Clickstream: Implications for Web-Based Advertising Efforts. Marketing Science 22(4) 520–41.

    Article  Google Scholar 

  • Chintagunta, P.K., D.C. Jain, N.J. Vilcassim. 1991. Investigating Heterogeneity in Brand Preferences in Logit Models for Panel Data. Journal of Marketing Research 28(4) 417–428.

    Article  Google Scholar 

  • Choi, S.C. 1991. Price Competition in a Channel Structure with a Common Retailer. Marketing Science 10(4) 271–296.

    Article  Google Scholar 

  • Clarke D.G. 1976. Economic Measurement of the Duration of Advertising Effects on Sales. Journal of Marketing Research 18(4) 345–357.

    Article  Google Scholar 

  • Dorfman, R., P.O. Steiner. 1954. Optimal Advertising and Optimal Quality. American Economic Review 44 826–836.

    Google Scholar 

  • Eliashberg, J., G.L. Lilien. 1993. Handbooks in Operations Research and Management Science. Volume 5: Marketing. Elsevier Science Publishers, Amsterdam.

    Google Scholar 

  • Engel, J.F., M.R. Warshaw. 1964. Allocating Advertising Dollars by Linear Programming. Journal of Advertising Research 4 42–48.

    Google Scholar 

  • Frank, R.E., A.A. Kuehn, W.F. Massy, Eds. 1962. Quantitative Techniques in Marketing Analyses. Irwin, Homewood, IL.

    Google Scholar 

  • Gordon, R.A., J.E. Howell. 1959.Higher Education for Business. Columbia University Press, New York, NY.

    Google Scholar 

  • Green, P.E., J.D. Caroll, S.M. Goldberg. 1981. A General Approach to Product Design Optimization via Conjoint Analysis. Journal of Marketing 45(3), 17–37.

    Article  Google Scholar 

  • Green, P.E., V. Srinivasan. 1978. Conjoint Analysis in Consumer Research: Issues and Outlook. Journal of Consumer Research 5(2) 103–123.

    Article  Google Scholar 

  • Guadagni, P.M., J.D.C. Little. 1983. A Logit Model of Brand Choice Calibrated on Scanner Data. Marketing Science 2(3) 203–238.

    Article  Google Scholar 

  • Gupta, S. 1988. Impact of Sales Promotions on When, What, and How Much to Buy. Journal of Marketing Research 259(4) 342–355.

    Article  Google Scholar 

  • Gupta, S., D.R. Lehmann, J.A. Stuart. 2004. Valuing Customers. Journal of Marketing Research 51(1) 71–8.

    Google Scholar 

  • Hanssens, D.M., L.J. Parsons, R.L. Schultz. 2001. Market Response Models: Econometric and Time Series Analysis(2 nd ed.). Kluwer Academic Publishers, Boston.

    Google Scholar 

  • Hardie, G.S., K.L. Lee, P.S. Fader. 2005. Counting Your Customers the Easy Way: An Alternative to the Pareto/NBD Model. Marketing Science 24(2) 275–284.

    Article  Google Scholar 

  • Hruschka, H. 1993. Determining Market Response Functions by Neural Network Modeling: A Comparison to Econometric Techniques. European Journal of Operations Research 66 27–35.

    Article  Google Scholar 

  • Kim, S.Y., R. Staelin. 1999. Manufacturer Allowances and Retailer Pass-Through Rates in a Competitive Environment. Marketing Science 18(1) 59–76.

    Article  Google Scholar 

  • Kotler, P.H. 1971.Marketing Decision Making: A Model Building Approach. Holt, Rinehart, and Winston, New York, NY.

    Google Scholar 

  • Leeflang, P.S.H., D.R. Wittink, M. Wedel, P.A. Naert. 2000.Building Models for Marketing Decisions. Kluwer Academic Publishers, Boston, MA.

    Google Scholar 

  • Lilien, G.L., P.H. Kotler.1983. Marketing Decision Making: A Model-Building Approach. Harper & Row, New York, NY.

    Google Scholar 

  • Lilien, G.L., P.H. Kotler, K.S. Moorthy.1992. Marketing Models. Prentice Hall, Englewood Cliffs, NJ.

    Google Scholar 

  • Lilien, G.L., A. Rangaswamy. 2000. Modeled to Bits: Decision Models for the Digital Networked Economy. International Journal of Research in Marketing 17(2–3) 227–235.

    Article  Google Scholar 

  • Lilien, G.L., A. Rangaswamy. 2004.Marketing Engineering: Computer Assisted Marketing Analysis and Planning. (2 nd ed.). Prentice Hall, Upper Saddle River, NJ.

    Google Scholar 

  • Little, J.D.C. 1970. Models and Managers: The Concept of A Decision Calculus. Management Science 16 B466–B485.

    Article  Google Scholar 

  • Little, J.D.C. 1979a. Aggregate Advertising Models: The State of the Art. Operations Research, 27(4) 629–667.

    Article  Google Scholar 

  • Little, J.D.C. 1979b. Decision Support Systems for Marketing Managers. Journal of Marketing 43(3) 9–26.

    Article  Google Scholar 

  • Lodish, L.M. 1971. CALLPLAN: An Interactive Salesman’s Call Planning System. Management Science 18(4 Part II) 25–40.

    Google Scholar 

  • Massy, W.F., D.B. Montgomery, D.G. Morrison. 1970. Stochastic Models of Buying Behavior. M.I.T. Press, Boston, MA.

    Google Scholar 

  • McCann, J.M., J.P. Gallagher.1990.Expert Systems for Scanner Data Environments. Kluwer Academic Publishers, Boston MA.

    Google Scholar 

  • Moe, W.W., P.S. Fader. 2004. Dynamic Conversion Behavior at e-Commerce Sites.Management Science 50(3) 326–35.

    Article  Google Scholar 

  • Moorthy, K.S. 1993. Theoretical Modeling in Marketing.Journal of Marketing  57(2) 92–106.

    Article  Google Scholar 

  • Montgomery, D.B., G.L. Urban.1969.Management Science in Marketing. Prentice Hall, Englewood Cliffs, NJ.

    Google Scholar 

  • Montgomery, D.B., G.L. Urban, Eds. 1970.Applications of Management Sciences in Marketing. Prentice Hall, Englewood Cliffs, NJ.

    Google Scholar 

  • Montgomery, D.B., C.B. Weinberg. 1973. Modeling Marketing Phenomena: A Managerial Perspective.Journal of Contemporary Business, Autumn, 17–43.

    Google Scholar 

  • Naert, P.A., P.S.H. Leeflang, 1978.Building Implementable Marketing Models. Leiden: Martinus Nijhoff.

    Google Scholar 

  • Nerlove, M., K.J. Arrow. 1962. Optimal Advertising Policy under Dynamic Conditions.Econometrica, 29 (May), 129–142.

    Google Scholar 

  • Neslin, S.A. 1990. A Market Response Model for Sales Promotion.Marketing Science,9(2), 125–145.

    Article  Google Scholar 

  • Pierson, F.C. 1959.The Education of American Businessmen. McGraw Hill, New York, NY.

    Google Scholar 

  • Pratt, J., H. Raiffa, R. Schlaifer. 1965.Introduction to Statistical Decision Theory. Mc-Graw-Hill, New York, NY.

    Google Scholar 

  • Reinartz, W.J., V. Kumar. 2000. On the Profitability of Long-Life Customers in a Noncontractual Setting: An Empirical Investigation and Implications for Marketing.Journal of Marketing,64(4) 17–35.

    Article  Google Scholar 

  • Reinartz, W., J.S. Thomas, V. Kumar. 2005. Balancing Acquisition and Retention Resources to Maximize Customer Profitability.Journal of Marketing,69(1) 63–79.

    Article  Google Scholar 

  • Rossi, P.E., G.M. Allenby, R. McCulloch. 2005.Bayesian Statistics and Marketing. John Wiley, Chichester, UK.

    Book  Google Scholar 

  • Shiv, B., A. Bechara, I. Levin, J.W. Alba, J.R. Bettman, L. Dube, A. Isen, B. Mellers, A. Smidts, S.J. Grant, A.P McCraw. 2005. Decision Neuroscience.Marketing Letters 16(3/4) 375–386.

    Article  Google Scholar 

  • Silk, A.J., G.L. Urban. 1978. Evaluation of New Packaged Goods: A Model and Measurement Methodology.Journal of Marketing Research 15(2) 171–191.

    Article  Google Scholar 

  • Tellis, G.J. 1988. The Price Elasticity of Selective Demand: A Meta-Analysis of Econometric Models of Sales.Journal of Marketing Research 25(4) 331–341.

    Article  Google Scholar 

  • Van der Lans, R., G.H. Van Bruggen, J. Eliashberg, B. Wierenga. 2008. A Viral Branching Model for Predicting the Spread of ElectronicWord-of-Mouth in Viral Marketing Campaigns. Working paper RSM Erasmus University, 2008.

    Google Scholar 

  • Vidale, M.L., H.B. Wolfe. 1957. An Operations-Research Study of Sales Response to Advertising.Operations Research 5(3) 370–81.

    Article  Google Scholar 

  • West, P.M., P.L. Brocket, L. Golden 1997. A Comparative Analysis of Neural Networks and Statistical Methods for Predicting Consumer Choice.Marketing Science 16(4) 370–391.

    Article  Google Scholar 

  • Wierenga, B., G.H. Van Bruggen. 2000.Marketing Management Support Systems: Principles, Tools, and Implementation. Kluwer Academic Publishers, Boston, MA.

    Google Scholar 

  • Wittink, D.R., M. Vriens, W. Burhenne. 1994. Commercial Use of Conjoint Analysis in Europe: Results and Critical Reflections.International Journal of Research in Marketing 11(1) 41–52.

    Article  Google Scholar 

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  1. RSM Erasmus University, Rotterdam, The Netherlands

    Berend Wierenga

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  1. Berend Wierenga
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    Berend Wierenga (Prof) (Prof)

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Wierenga, B. (2008). The Past, the Present and the Future of Marketing Decision Models. In: Wierenga, B. (eds) Handbook of Marketing Decision Models. International Series in Operations Research & Management Science, vol 121. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-78213-3_1

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