Abstract
The majority of studies concerning diffusion or product growth of consumer durables have treated the U.S. market as a whole and have applied the diffusion model on the assumption that the market exhibits a homogeneous response in its diffusion process. If the market is heterogeneous, however, an aggregate model entails a misspecification problem which could adversely affect the applicability and efficiency of the model. A modeling framework is developed for analyzing the diffusion process in a possibly heterogeneous market. Empirical analysis using data on the videocassette recorder (VCR) market reveals that the modeling framework captures to a fair extent heterogeneous diffusion processes across different regions in the U.S. market. Managerial implications are derived and discussed.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Bass FM (1969) A new product growth model for consumer durables. Management Science 15:215–27
Brown LA (1981) Innovation diffusion: A new perspective. New York: Methuen and Co. Ltd.
Brown LA, Malecki EJ, Spector AN (1976) Adopter categories in a spatial context: Alternative explanations for an empirical regularity. Rural Sociology 41:99–118
Gore AP, Lavaraj VA (1987) Innovation diffusion in a heterogeneous population. Technological Forecasting and Social Change 32:163–7
Hagerstrand T (1965) A Monte Carlo approach to diffusion. Archives Europeennes de Sociologie 6:43–67
Hagerstrand T (1967) Innovation diffusion as a spatial process. Chicago: University of Chicago Press
Jain D, Rao RC (1990) Effects of price on the demand for durables: Modeling, estimation, and findings. Journal of Business and Economic Statistics 8:163–70
Kotler P (1988) Marketing management: Analysis, planning, implementations, and control. New Jersey: Prentice-Hall
Mahajan V, Mason CH, Srinivasan V (1986) An evaluation of estimation procedures for new product diffusion models. In: Innovation diffusion models of new product acceptance, Mahajan V, Wind Y (ed) Massachusetts: Ballinger Publishing Co 203–32
Mahajan V, Muller E, Bass FM (1990) New product diffusion models in marketing: A review and directions for research. Journal of Marketing 54:1–26
Mahajan V, Peterson RA (1978) Innovation diffusion in a dynamic potential adopter population. Management Science 24:1589–97
Mahajan V, Wind Y (1986) Innovation diffusion models of new product acceptance. Massachusetts: Ballinger Publishing Co
Maddala GS (1977) Econometrics. New York: McGraw-Hill
Moriarty M (1975) Cross-sectional, time-series issues in the analysis of marketing decision variables. Journal of Marketing Research 12:142–50
Raj B, Ullah A (1981) Econometrics: A varying coefficients approach. London: Croom Helm
Rao CR (1973) Linear statistical inference and its applications, New York: John Wiley and Sons
Rogers EM (1983) Diffusion of innovations, 3rd ed. New York: The Free Press
Scheffé H (1959) The analysis of variance. New York: John Wiley & Sons
Srinivasan V, Mason C (1986) Nonlinear least squares estimation of new product diffusion models. Marketing Science 5:169–178
Swamy PAVB (1971) Statistical inference in random coefficient regression models. Berlin: Springer-Verlag
Takada H (1989) Does the Bass model perform well internationally? In New-product development and testing, Henry WA, Menasco M, Takada H (ed) Massachusetts: Lexington Books 243–58
Ullah A, Racine J (1992) Smooth improved estimators of econometric parameters. In Readings in econometric theory and practice, Griffith WE et al (ed) in honor of G. Judge, North Holland
Wittink D (1977) Exploring territorial differences in the relationship between marketing variables. Journal of Marketing Research 14:145–55
Zellner A (1962) An efficient method of estimating seemingly unrelated regressions and tests for aggregation bias. Journal of the American Statistical Association 57:348–68
Author information
Authors and Affiliations
Additional information
We greatly benefited from Professor Baldev Raj, Editor, and two anonymous reviewers. We thank Professor Aman Ullah, University of California, Riverside, for his valuable suggestions for the manuscript, and Mary M. Long, Ph.D. candidate, Baruch College, for her editorial assistance. Authors are listed in alphabetical order; each contributed equally to this research.