Marketing Models
IPHD Program
Guanghua School of Management, Beijing University
Fall, 2005
Dr. Jianan Wu
Associate Professor of Marketing A. B. Freeman School of Business Tulane University
New Orleans, LA 70118, USA Email: jianan.wu@tulane.edu Dr. Guoqun Fu
Professor of Marketing Guanghua School of Management Beijing University
Beijing, PRC
Email: fugq@gsm.
Cour Description and Objective
The scientific inquiry on marketing has made significant progress in the past three decades. Following the scientific inquiry tradition in other disciplines, marketing scientists build quantitative marketing models, which conceive and transfer marketing concepts into mathematical logic framework. This treatment not only eks to develop and test a unified framework for theory and methodology in academic marketing, but also shapes the new standards for marketing practitioner in industry.
This cour consists of two intrinsically related parts of Marketing Models. In Part I, we study the basics of this scientific inquiry, including the marketing science philosophy, the quantitative tools frequently ud, the relevance to marketing practices and some basics models in consumer choices and promotions. In Part II, we examine veral lected topics in frontier rearch of the inquiry. The topics are active and timely in academic rearch in marketing and reprented by lected publications from leading marketing journals.
Texts Required and Recommended
Required
Cour Package.
Recommended
⎽ Lilien (1992), Marketing Models.
⎽ Leeflang, Witink, Wedel, and Naert (2000), Building Models for Marketing
Decision.
⎽ Lilien and Rangaswamy (2003), Marketing Engineering: Computer Assisted
Marketing Analysis and Planning. 2nd Edition.
⎽ Simon and Blume (1994), Mathematics for Economists.
⎽ Greene (2000), Econometric Analysis.
⎽ Gibbons (1994), Game Theory for Applied Economists.
Grading System
⎽ Participation (20%)
⎽ Prentation40%)
Paper (40%)
Each of the students is required to write a paper which falls in the domain of quantitative marketing models. The idea in this paper must be original and have the potential to grow to a publishable paper.
Daily Schedule
Part I: Basics of Marketing Models (By Prof. Guoqun Fu)
Class 1 . Marketing Science Thoughts
Bass (1993), .The Future of Rearch in Marketing: Marketing Science,. Journal of Marketing Rearch, Vol. XXX (February), pp. 1-6.
Moorthy (1993), Theoretical Modeling in Marketing, Journal of 血肌酐高是什么原因
Marketing vol. 57 (April), pp.92-106.
Simon (1994) .Marketing Science.s Pilgrimage to the Ivory Tower,. commentary by John D. C. Little
et al., and Leonard J. Parsons et al. Rearch Traditions in Marketing, eds. Gills Laurent, Gary L. Lilien, Bernard Pras, Boston: Kluwer Academic Publishers, pp. 27- 78.
Little (1993), .Models for Marketing Managers: Then and Now., 1992 Paul D. Conver Award Symposium, University of Il打铁还需自身硬
linois at Urbana-Champaign, May 5. Class 2 .Choice Modeling and Purcha
Choice and Purcha Timing Models, Blattberg and Neslin, Sales Promotions, Englewood-Cliffs, N.J.: Prentice-Hall, 1990, Chapter 8
Guandagni P. and J. D. C. Little, A Logit Model of Brand Choice calibrated on Scanner Data, Marketing Science, Summer 1983, pp. 203-238
Lattin J. M. and Bucklin, R. E., Reference effect of Price and Promotion on Brand Choice Behavior, Journal of Marketing Rearch, volume 26, August 1989, pp. 299-310
Jain, D. C. Vilcassim, N. J., “Investing Houhold Purcha Timing Decisions:
A Conditional Hazard Function Approach,” Marketing Science, Winter 1991, pp. 1-23. Bucklin, R. E. and Lattin, J. M. “A Two State model of Purcha Incidence and Brand Choice,” Marketing Science,
Vol. 10, No.2 Winter 1991, pp. 24-39.
Gupta, Sunil, “Impact of Sales Promotions on梦见自己是杀人犯
When, What, and How Much to Buy,” Journal of Marketing Rearch, Vol. XXV (November 1988), p蒹葭教学设计
p. 342-355.
Class 3 Consumer Behavior Models of Promotions
“Retail Promotions”, Blattberg and Neslin, Sales Promotions, Englewood-Cliffs, N. J.: Prentice-Hall, 1990, Chapter 2.
Kalyanaram, G. and Winer, R. S., “Empirical Generalizations from Reference Price Rearch,” Management Science, Vol 14, No. 3, 1995, pp.161-169.
Winer, R.S., “A Reference Price Model of Brand Choice for Frequently Purchad Products, Journal of Consumer Rearch, Vol 13 (September 1986), pp. 250-256.
Kalwani, M. U. and Yim, C. K., “Consumer Price and Promotion expectations: an Experimental Study,” Journal of Marketing Rearch, Vol. XXIX (February 1992), 90-100.
Krishna, A. “Effect of Dealing Patterns on Consumer Perceptions of Deal Frequency and Willingness to Pay,” Journal of Marketing Rearch, Vol. XXVIII (November1991), pp. 441-451.
Class 4 .Retail Promotions
KLM Chapter 7, 324-360.
Blattberg, R. C. and K. J. Wisniewski, “Price-Induced Patterns of Competition,” Marketing Science, Vol8, No.4, Falll 1989, pp. 291-309.
Blatteberg R. C., R. Briesch and E. Fox, “How Promotions Work,” Management Science, Vol. No. 3, 1995, pp.122-132.
Blattberg and Neslin, Sales Promotions, Englewood Cliffs, N. J.: Prentice Hall, 1990, “Retail Promotions”, Chapter 12
Part II: Frontier Rearch in Marketing Models (by Prof. Jianan Wu)
Class 5 . New Product Diffusion Models
Bass (1969), .A New Product Growth Model for Consumer Durables,. Management Science, 15(5), 215-227.
Srinivasan and Mason (1986), .Nonlinear Least Squares Estimation of New Product Diffusion Models,. Marketing Science, 5(2), 169-178.
Bass, Krishnan, and Jain (1994), .Why the Bass Model Fits without Decision
Variables,. Marketing Science, 13(3), 203-223.
Van den Bulte and Lilien (1998), .Bias and Systematic Change in the Parameter
Estimates of Macro-Level Diffusion Models,. Marketing Science, 16(4), 338-353.
Class 6 . Consumer Choice Models
Gadagni and Little (1983), .A Logit Model of Brand Choice Calibrated on
Scanner Data,. Marketing Science, 2(3), pp.203-238.
Gensch (1987), .Empirical Evidence Supporting the U of Multiple Choice
Models in Analyzing a Population,. Journal of Marketing Rearch, XXIV, 197-
207.
Kamakura and Rusll (1989), .A Probabilistic Choice Model for Market
Segmentation and Elasticity Structure,. Journal of Marketing Rearch, XXVI,
379-390.
Gupta and Chintagunta (1994), .On Using Demographic Variables to Determine
Membership in Logit Mixture Models,. Journal of Marketing Rearch, XXXI,
128-136.
Class7. Consumer Consideration Set Models
Roberts and Lattin (1991), .Development and Testing of a Model of
Consideration Set Composition,. Journal of Marketing Rearch, XXVIII, 429-
440.
Siddarth, Bucklin, and Morrison (1995), .Making the Cut: Modeling and
Analyzing Choice Set Restriction in Scanner Panel Data.. Journal f Marketing
Rearch, XXXII, 255-266.
Andrews and Srinivasan (1995), .Studying Consideration Effects in Empirical
Choice Models Using Scanner Panel Data,. Journal of Marketing Rearch,
XXXII, 30-41.
Brennenberg and Vanhonack (1996), .Limited Choice Sets, Local Price Respon, and Implied Measures of Price Competition,. Journal of Marketing Rearch,
XXXIII, 163-173.
Roberts and Lattin (1997), .Consideration: Review of Rearch and Prospects for Future Insights,. Journal of Marketing Rearch, XXXIV, 406-410.
Chiang, Chib, and Narasimhan (1997), .Markov Chain Monte Carlo and Models
of Consideration Set and Parameter Heterogeneity,. Journal of Econometrics, Class 8 . Customer R
elationship Management (CRM) Models
Homburg, Workman Jr, and Jenn (2002), .A configurational perspective on key account management,. Journal of Marketing. 66 (2), 38 - 61
Lemon, White, and Winer (2002), .Dynamic customer relationship management: Incorporating future considerations into the rvice retention decision,. Journal of Marketing. 66 (1), 1 . 14.
Anderson (2002), .Sharing the Wealth: When Should Firms Treat Customers as
Partners?. Management Science, 18 (8), 955 - 971.
Verhoef (2003), .Understanding the effect of customer relationship management
efforts on customer retention and customer share development,. Journal of
Marketing. 67 (4), 30 - ??
Kamakura, Wedel, Rosa, and Mazzon (2003), .Cross-lling through databa
marketing: a mixed data factor analyzer for data augmentation and prediction,.
International Journal of Rearch in Marketing, 20, 45-65.
Padmanabhan and Tuzhilin (2003), .On the u of optimization for data mining:
Theoretical interactions and eCRM opportunities,. Management Science. 49 (10), 1327 - 1343
Class 9 . Consumer Search Behavior Models (in E-Commerce)
Bakos (1997), .Reducing buyer arch costs: Implications for electronic
marketplaces,. Management Science, 43 (12), 1676-1692.
Brynjolfsson and Smith (2000), .Internet Price Dispersion., Management Science, 46(4).
Degeratu, Rangaswamy, and Wu (2000), .Consumer Choice Behavior in Online
and Traditional Supermarkets: The Effects of Brand Name, Price, and other
Search Attributes,. International Journal of Rearch in Marketing, 17(1), 55-78.
Johnson, Moe, Fader, Bellman, and Loshe (2003), .On the Depth and Dyn图腾是什么意思
amics
of Online Search Behavior,. Management Science, 50 (3), 299 . 308.
Wu and Rangaswamy (2003), .A Fuzzy Set Model of Consideration Set
Formation Calibrated Using Data from An Online Supermarket,. Ma写酒的诗
rketing
Science, 22 (3), 411 . 434
Zwick, Rapoport, Lo, and Muthukrishnan (2003), .Consumer Sequential Search: Not Enough or Too Much?. Marketing Science 22 (4). 503 - 519
Wu, Cook, and Strong (2004), .A Dynamic Two-Stage Model of Advertising and
