A Hidden Markov Model of Customer Relationship Dynamics

References

• Aaker J., Fournier S., Brasel A. S. When good brands do bad. J. Consumer Res. (2004) 31(June):1–18Crossref, Google Scholar
• Allenby G. M., Ginter J. L. Using extremes to design products and segment markets. J. Marketing Res. (1995) 32(November):392–403Crossref, Google Scholar
• Allenby G. M., Leone R. P., Jen L. A dynamic model of purchase timing with application to direct marketing. J. Amer. Statist. Assoc. (1999) 93(446):365–374Crossref, Google Scholar
• Andrews R. L., Currim I. S. A comparison of segment retention criteria for finite mixture models. J. Marketing Res. (2003) 39(May):235–243Crossref, Google Scholar
• Arnett D. B., German S., Hunt S. D. The identity salience model of relationship marketing success: The case of nonprofit marketing. J. Marketing (2003) 67(2):89–105Crossref, Google Scholar
• Atchadé Y. F. An adaptive version for the metropolis adjusted Langevin algorithm with a truncated drift. Methodology and Comput. Appl. Probab. (2006) 8(2):235–254Crossref, Google Scholar
• Baade R. A., Sundberg J. O. What determines alumni generosity? Econom. Ed. Rev. (1996) 15(1):75–81Crossref, Google Scholar
• Böckenholt U., Dillon W. R. Inferring latent brand dependencies. J. Marketing Res. (2000) 37(February):72–87Crossref, Google Scholar
• Böckenholt U., Langeheine R. Latent change in recurrent choice data. Psychometrika (1996) 61(2):285–302Crossref, Google Scholar
• Bolton R. N. A dynamic model of the duration of the customer's relationship with a continuous service provider: The role of satisfaction. Marketing Sci. (1998) 17(1):45–65Link, Google Scholar
• Bucklin R. E., Lattin J. M. A two-state model of purchase incidence and brand choice. Marketing Sci. (1991) 10(1):24–39Link, Google Scholar
• Bult J. R., Wansbeek T. Optmal selection for direct mail. Marketing Sci. (1995) 14 (4):378–394Link, Google Scholar
• Dekimpe M. G., Hanssens D. M. Time-series models in marketing: Past, present and future. Internat. J. Res. Marketing (2000) 17(2–3):183–193Crossref, Google Scholar
• Dillon W. R., Böckenholt U., de Borrero M. S., Bozdogan H., DeSarbo W., Gupta S., Kamakura W., Kumar A., Ramaswamy V., Zenor M. Issues in the estimation and application of latent structure models of choice. Marketing Lett. (1994) 5(4):323–334Crossref, Google Scholar
• Djurić P. M., Chun J.-H. An MCMC sampling approach to estimation of nonstationary hidden Markov models. IEEE Trans. Signal Processing (2002) 50(5):1113–1123Crossref, Google Scholar
• Du R., Kamakura W. A. Household lifecycles and lifestyles in america. J. Marketing Res. (2006) 43(February):121–132Crossref, Google Scholar
• Dwyer R. F., Schurr P. H., Oh S. Developing buyer-seller relationships. J. Marketing (1987) 51(April):11–27Crossref, Google Scholar
• Erdem T., Sun B. Testing for choice dynamics in panel data. J. Bus. Econom. Statist. (2001) 19(2):142–152Crossref, Google Scholar
• Fader P. S., Lattin J. M. Accounting for heterogeneity and nonstationarity in a cross-sectional model of consumer purchase behavior. Marketing Sci. (1993) 12(3):304–317Link, Google Scholar
• Fader P. S., Hardie B. G. S., Huang C.-Y. A dynamic changepoint model for new product sales forecasting. Marketing Sci. (2004) 23(1):50–65Link, Google Scholar
• Flanagan J. C. The critical incident technique. Psych. Bull. (1954) 51(4):327–359Crossref, Google Scholar
• Fournier S. Consumers and their brands: Developing relationship theory in consumer research. J. Consumer Res. (1998) 24(March):343–373Crossref, Google Scholar
• Frank R. E. Brand choice as a probability process. J. Bus. (1962) 35(January):43–56Crossref, Google Scholar
• Gelman A., Rubin D. B. Inference from iterative simulation using multiple sequences. Statist. Sci. (1992) 7:457–511Crossref, Google Scholar
• Greene W. H.Econometric Analysis (1997) 3rd ed.(Prentice Hall, Englewood Cliffs, NJ) Google Scholar
• Guadagni P. M., Little J. D. C. A logit model of brand choice Calibrated on scanner data. Marketing Sci. (1983) 2(3):203–238Link, Google Scholar
• Gupta S., Zeithaml V. A. Customer metrics and their impact on financial performance. Marketing Sci. (2006) 25(6):718–739Link, Google Scholar
• Hamilton J. D. A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica (1989) 57(2):357–384Crossref, Google Scholar
• Harrison W. B., Mitchell S. K., Peterson S. P. Alumni donations and colleges' development expenditures: Does spending matter? (1995) 54(October):397–413Google Scholar
• Heckman J. J., Rosen S. Heterogeneity and state dependence. Studies in Labor Markets (1981) (University of Chicago Press, Chicago) 91–139Google Scholar
• Hinde R. A.Towards Understanding Relationships (1979) (Academic, London) Google Scholar
• Hughes J. P., Guttorp P. A class of stochastic models for relating synoptic atmospheric patterns to regional hydrologic phenomena. Water Resources Res. (1994) 30(5):1535–1546Crossref, Google Scholar
• Jain D., Singh S. S. Customer lifetime value research in marketing: A review and future direction. J. Interactive Marketing (2002) 16(2):34–46Crossref, Google Scholar
• Jeuland A. P., Bass F. M., Wright G. P. A multibrand stochastic model compounding heterogeneous Erlang timing and multinomial choice processes. Oper. Res. (1980) 28(2):255–277Link, Google Scholar
• Kahneman D., Miller D. T. Norm theory: Comparing reality to its alternatives. Psych. Rev. (1986) 93(2):136–153Crossref, Google Scholar
• Kamakura W. A., Russell G. J. A probabilistic choice model for market segmentation and elasticity structure. J. Marketing Res. (1989) 26(November):379–390Crossref, Google Scholar
• Keane M. P. Modeling heterogeneity and state dependence in consumer choice behavior. J. Bus. Econom. Statist. (1997) 15(July):310–327Google Scholar
• Kim C.-J., Nelson C. R.State-Space Models with Regime Switching: Classical and Gibbs Sampling Approaches with Applications (1999) (M.I.T. Press, Cambridge, MA) Google Scholar
• Lewis M. The influence of loyalty programs and short-term promotions on customer retention. J. Marketing Res. (2004) 41(August):281–292Crossref, Google Scholar
• Libai B., Narayandas D., Humby C. Toward an individual customer profitability model: A segment-based approach. J. Service Res. (2002) 5(1):69–76Crossref, Google Scholar
• Liechty J. C., Wedel M., Pieters R. The representation of local and global scanpaths in eye movements through Bayesian hidden Markov models. Psychometrika (2003) 68(4):519–541Crossref, Google Scholar
• MacDonald I. L., Zucchini W.Hidden Markov and Other Models for Discrete-Valued Time Series (1997) (Chapman and Hall, London) Google Scholar
• McAlister L., Srivastava R., Horowitz J., Jones M., Kamakura W., Kulchitsky J., Ratchford B., Russell G., Sultan F., Yai T., Weiss D., Winer R. Incorporating choice dynamics in models of consumer behavior. Marketing Lett. (1991) 2(3):241–252Crossref, Google Scholar
• Montgomery A. L., Li S., Srinivasan K., Liechty J. C. Predicting online purchase conversion using web path analysis. Marketing Sci. (2004) 23(4):579–595Link, Google Scholar
• Moon S., Kamakura W. A., Ledolter J. Estimating promotion response when competitive promotions are unobservable. J. Marketing Res. (2007) . ForthcomingCrossref, Google Scholar
• Morgan R. M., Hunt S. D. The commitment-trust theory of relationship marketing. J. Marketing (1994) 58(3):20–38Crossref, Google Scholar
• Morrison D. G., Chen R. D. H., Karpis S. L., Britney K. E. A. Modeling retail customer behavior at merrill lynch. Marketing Sci. (1982) 1(2):123–141Link, Google Scholar
• Naik P. A., Mantrala M. K., Sawyer A. G. Planning media schedules in the presence of dynamic advertising quality. Marketing Sci. (1998) 17(3):214–235Link, Google Scholar
• Netzer O. A hidden Markov model of customer relationship dynamics. (2004) . Ph.D. dissertation, Stanford University, Stanford, CAGoogle Scholar
• Newton M. A., Raftery A. E. Approximate Bayesian inference by the weighted likelihood bootstrap. J. Roy. Statist. Soc. B (1994) 56(1):3–48Google Scholar
• Okunade A. A. Logistic regression and probability of business school alumni donations: Micro-data evidence. Ed. Econom. (1993) 1:243–258Google Scholar
• Okunade A. A., Berl R. L. Determinants of charitable giving of business school alumni. Res. Higher Ed. (1997) 38(April):201–214Crossref, Google Scholar
• Oliver R. L.Satisfaction: A Behavioral Perspective on the Consumer (1997) (McGraw-Hill, New York) Google Scholar
• Pauwels K., Currim I., Dekimpe M. G., Ghysels E., Hanssens D. M., Mizik N., Naik P. Modeling marketing dynamics by time series econometrics. Marketing Lett. (2004) 15(4):167–183Crossref, Google Scholar
• Pfeifer P. E., Carraway R. L. Modeling customer relationships using Markov chains. J. Interactive Marketing (2000) 14(2):43–55Crossref, Google Scholar
• Poulsen C. S. Mixed Markov and latent Markov modeling applied to brand choice behavior. Internat. J. Res. Marketing (1990) 7(1):5–19Crossref, Google Scholar
• Rabiner L. R. A tutorial on hidden Markov models and selected applications in speech recognition. Proc. IEEE (1989) 77(2):257–286Crossref, Google Scholar
• Rabiner L. R., Juang B.-H.Fundamentals of Speech Recognition (1993) (Prentice Hall, Englewood Cliffs, NJ) Google Scholar
• Ramaswamy V. Evolutionary preference segmentation with panel survey data: An application to new products. Internat. J. Res. Marketing (1997) 14(1):57–80Crossref, Google Scholar
• Reinartz W., Kumar V. The impact of customer relationship characteristics on profitable lifetime duration. J. Marketing (2003) 67(1):77–99Crossref, Google Scholar
• Rossi P. E., Allenby G. M. Bayesian statistics and marketing. Marketing Sci. (2003) 22(3):304–328Link, Google Scholar
• Rust R. T., Chung T. S. Marketing models of service and relationships. Marketing Sci. (2006) 25(6):560–580Link, Google Scholar
• Rust R. T., Lemon K. N., Zeithaml V. A. Return on marketing: Using customer equity to focus marketing strategy. J. Marketing (2004) 68(1):109–127Crossref, Google Scholar
• Schmittlein D. C., Peterson R. A. Customer base analysis: An industrial purchase process application. Marketing Sci. (1994) 13(1):41–67Link, Google Scholar
• Schwarz G. Estimating the dimension of a model. Ann. Statist. (1978) 6(2):461–464Crossref, Google Scholar
• Scott L. S. Bayesian methods for hidden Markov models, recursive computing in the 21st century. J. Amer. Statist. Assoc. (2002) 97(475):337–351Crossref, Google Scholar
• Smith A., Naik P. A., Tsai C.-L. Markov-switching model selection using Kullback-Leibler divergence. J. Econometrics (2006) 134(2):553–577Crossref, Google Scholar
• Soukup J. D. A Markov analysis of fund-raising alternatives. J. Marketing Res. (1983) 20(August):314–319Crossref, Google Scholar
• Spiegelhalter D. J., Best N. G., Carlin B. P., van der Linde A. Bayesian measures of model complexity and fit. J. Roy. Statist. Soc. Ser. B (2002) 64(3):583–639Crossref, Google Scholar
• Srinivasan V., Kesavan R. An alternative interpretation of the linear learning model of brand choice. J. Consumer Res. (1976) 3(September):76–83Crossref, Google Scholar
• Storm S. After years of cash flow, universities hit an ebb. New York Times (2003) 13(March):25Google Scholar
• Taylor A. L., Martin J. C. Characteristics of alumni donors at a research I public university. Res. Higher Ed. (1995) 36(3):283–302Crossref, Google Scholar
• Thomas J. S. The importance of linking customer acquisition to customer retention. J. Marketing Res. (2001) 39(May):262–268Crossref, Google Scholar
• Wedel M., Kamakura W. A.Market Segmentation: Conceptual and Methodological Foundations (2000) (Kluwer, Dordrecht, The Netherlands) Crossref, Google Scholar
• Willemain T. R., Goyal A., Van Deven M., Thukral I. S. Alumni giving: The influences of reunion, class and year. Res. Higher Ed. (1994) 35(2):201–214Google Scholar
• Winer R. S. A framework for customer relationship management. California Management Rev. (2001) 43(Summer):89–105Crossref, Google Scholar
• Xie J. X., Song M., Sirbu M., Wang Q. Kalman filter estimation of new product diffusion models. J. Marketing Res. (1997) 34(August):378–393Crossref, Google Scholar