A Cointegration Model with Structure Breaks for Customer Migration Analysis

References

• Allenet B, Barry H. Opinion and behaviour of pharmacists towards the substitution of branded drugs by generic drugs: Survey of 1,000 French community pharmacists. Pharm. World Sci. (2003) 25(5):197–202Crossref, Google Scholar
• Au TS, Duan R, Jiang W. A data mining framework for product and service migration analysis. Ann. Oper. Res. (2012) 192(1):105–121Crossref, Google Scholar
• Bai J, Perron P. Computation and analysis of multiple structural change models. J. Appl. Econometrics (2003) 18(1):1–22Crossref, Google Scholar
• Bass FM. A new product growth model for consumer durables. Management Sci. (1969) 15(1):215–227Link, Google Scholar
• Bass P, Bass FM. IT waves: Two completed generational diffusion models. (2004) . Working paper, University of Texas at Dallas, RichardsonGoogle Scholar
• Boswijk HP, Franses PH, Van Dijk D. Cointegration in a historical perspective. J. Econometrics (2010) 158(1):156–159Crossref, Google Scholar
• Broman KW, Speed TP. A model selection approach for the identification of quantitative trait loci in experimental crosses. J. Roy. Statist. Soc. Ser. B (2002) 64(Part 4):641–656Crossref, Google Scholar
• Chen J, Chen Z. Extended Bayesian information criterion for model selection with large model spaces. Biometrika (2008) 95(3):759–771Crossref, Google Scholar
• Constantiou ID, Kautz K. Economic factors and diffusion of IP telephony: Empirical evidence from an advanced market. Telecommun. Policy (2008) 32(3/4):197–211Crossref, Google Scholar
• Efron B, Hastie T, Johnstone I, Tibshirani R. Least angle regression. Ann. Statist. (2004) 32(2):407–489Crossref, Google Scholar
• Elliott G, Rothenberg TJ, Stock JH. Efficient tests for an autoregressive unit root. Econometrica (1996) 64(4):813–836Crossref, Google Scholar
• Engle RF, Granger CWJ. Co-integration and error correction: Representation, estimation, and testing. Econometrica (1987) 55(2):251–276Crossref, Google Scholar
• Executive Office of the President, Office of Management and BudgetNorth American Industry Classification System (NAICS) (1999) (Jist Works, Indianapolis) Google Scholar
• Goldenberg J, Oreg S. Laggards in disguise: Resistance to adopt and the leapfrogging effect. Tech. Forecasting Soc. Change (2007) 74(8):1272–1281Crossref, Google Scholar
• Granger CWJ. Some properties of time series data and their use in econometric model specification. J. Econometrics (1981) 16(1):121–130Crossref, Google Scholar
• IBM IBM study finds consumers prefer a mobile device over the PC. (2008) . Press release (October 22), IBM, Armonk, NY. http://www-03.ibm.com/press/us/en/pressrelease/25737.wssGoogle Scholar
• Johansen S, Juselius K. Maximum likelihood estimation and inference on cointegration: With applications to the demand for money. Oxford Bull. Econom. Statist. (1990) 52(2):169–210Crossref, Google Scholar
• Johansen S, Mosconi R, Nielsen B. Cointegration analysis in the presence of structural breaks in the deterministic trend. J. Econometrics (2000) 3(2):216–249Crossref, Google Scholar
• Johnson WC, Bhatia K. Technological substitution in mobile communication. J. Bus. Indust. Marketing (1997) 12(6):383–386Crossref, Google Scholar
• Kurita T, Nielsen HB, Rahbek A. An I(2) cointegration model with piecewise linear trends. J. Econometrics (2011) 14(2):131–155Crossref, Google Scholar
• Maddala GS, Kim IM. Structural change and unit roots. J. Statist. Planning Inference (1996) 49(1):73–103Crossref, Google Scholar
• Norton JA, Bass FM. Evolution of technological generations: The law of capture. Sloan Management Rev. (1992) 33(2):66–77Google Scholar
• Peres R, Muller E, Mahajan V. Innovation diffusion and new product growth models: A critical review and research directions. J. Res. Marketing (2010) 27(2):91–106Crossref, Google Scholar
• Perron P. The great crash, the oil price shock, and the unit root hypothesis. Econometrica (1989) 57(6):1361–1401Crossref, Google Scholar
• Perron P. Testing for a unit root in a time series with a changing mean. J. Bus. Econom. Statist. (1990) 8(2):153–162Google Scholar
• Porter ME. How competitive forces shape strategy. Harvard Bus. Rev. (1979) March/April):137–145Google Scholar
• Qian ZG, Jiang W, Tsui K-L. Churn detection via customer profile modeling. Internat. J. Production Res. (2006) 44(14):2913–2933Crossref, Google Scholar
• Qiu RG. Computational thinking of service systems: Dynamics and adaptiveness modeling. Service Sci. (2009) 1(1):42–55Link, Google Scholar
• Reisinger D. Opinion: Can Blockbuster be saved? Ars Technica (2008) . Retrieved January 27, 2012, http://arstechnica.com/author/don-reisinger/Google Scholar
• Rogers EM. New product adoption and diffusion. J. Consumer Res. (1976) 2(4):290–301Crossref, Google Scholar
• Steffens PR, Kaya M, Gillin L. Drivers of technology substitution: Successive generations of high tech products. Proc. 6th AGSE Internat. Entrepreneurship Res. Exchange (2009) Adelaide, SA, Australia:137–145Google Scholar
• Stremersch S, Muller E, Peres R. Does new product growth accelerate across technology generations? J. Marketing (2010) 2):103–120Google Scholar
• Tibshirani RJ. Regression shrinkage and selection via the LASSO. J. Roy. Statist. Soc. Ser. B (1996) 58(1):267–288Crossref, Google Scholar
• Wang H, Leng C. A note on adaptive group lasso. Comput. Statist. Data Analysis (2008) 52(12):5277–5286Crossref, Google Scholar
• Wang J, Zivot E. A Bayesian time series model of multiple structural changes in level, trend, and variance. J. Bus. Econom. Statist. (2000) 18(3):374–386Google Scholar
• Wang H, Li B, Leng C. Shrinkage tuning parameter selection with a diverging number of parameters. J. Roy. Statist. Soc. Ser. B (2009) 71(3):671–683Crossref, Google Scholar
• Yankee Group Growing pains persist in an adolescent market: Yankee Group's 2007 U.S. consumer VoIP subscriber forecast. (2007) . Report (July 30), Yankee Group, Boston. http://www.yankeegroup.com/ResearchDocument.do?id=15951Google Scholar
• Yao YC. Estimating the number of changepoints via Schwarz criterion. Statist. Probab. Lett. (1988) 6(3):181–189Crossref, Google Scholar
• Yuan M, Lin Y. Model selection and estimation in regression with grouped variables. J. Roy. Statist. Soc. Ser. B (2006) 68(1):49–67Crossref, Google Scholar