New ProductDiffusion Acceleration: Measurementand Analysis

is a popular contention that products launched today dif- fuse faster than products launched in the past. However, the evidence of diffusion acceleration is rather scant, and the methodology used in previous studies has several weak- nesses. Also, little is known about why such acceleration would have occurred. This study investigates changes in dif- fusion speed in the United States over a period of 74 years (1923-1996) using data on 31 electrical household durables. This study defines diffusion speed as the time it takes to go from one penetration level to a higher level, and it measures speed using the slope coefficient of the logistic diffusion model. This metric relates unambiguously both to speed as just defined and to the empirical growth rate, a measure of instantaneous penetration growth. The data are analyzed us- ing a single-stage hierarchical modeling approach for all products simultaneously in which parameters capturing the adoption ceilings are estimated jointly with diffusion speed parameters. The variance in diffusion speed across and within products is represented separately but analyzed simultaneously. The focus of this study is on description and explanation

[1]  C. Shapiro,et al.  Systems Competition and Network Effects , 1994 .

[2]  Jaishankar Ganesh,et al.  Cross‐National Diffusion Research: What Do We Know and How Certain Are We? , 1998 .

[3]  S. Greenstein,et al.  The Product Life Cycle in the Commercial Mainframe Computer Market, 1968-1982 , 1998 .

[4]  G. Tellis,et al.  Will It Ever Fly? Modeling the Takeoff of Really New Consumer Durables , 1997 .

[5]  J. C. Fisher,et al.  A simple substitution model of technological change , 1971 .

[6]  Richard W. Olshavsky,et al.  Time and the Rate of Adoption of Innovations , 1980 .

[7]  P. Diggle,et al.  Analysis of Longitudinal Data. , 1997 .

[8]  M. Sarvary,et al.  Staged estimation of international diffusion models - An application to global cellular telephone adoption , 1998 .

[9]  R. Porter,et al.  Consumption and the World of Goods , 1994 .

[10]  P. Diggle,et al.  Analysis of Longitudinal Data , 2003 .

[11]  E. Mansfield.  TECHNICAL CHANGE AND THE RATE OF IMITATION , 1961 .

[12]  T. S. Robertson,et al.  Modeling Multinational Diffusion Patterns: An Efficient Methodology , 1989 .

[13]  S. Besen,et al.  Compatibility Standards, Competition, and Innovation in the Broadcasting Industry , 1986 .

[14]  W. Clark,et al.  Opportunities for revitalizing stagnant markets: An analysis of household appliances , 1984 .

[15]  F. Bass.  A new product growth model for consumer durables , 1976 .

[16]  D. Lehmann,et al.  Extent and Impact of Incubation Time in New Product Diffusion , 1999 .

[17]  J. Ware,et al.  Random-effects models for longitudinal data. , 1982, Biometrics.

[18]  Barry L. Bayus,et al.  Have diffusion rates been accelerating over time? , 1992 .

[19]  Jr William P. Putsis.  Parameter variation and new product diffusion , 1998 .

[20]  H. Bonus.  Quasi-Engel Curves, Diffusion, and the Ownership of Major Consumer Durables , 1973, Journal of Political Economy.

[21]  Shlomo Yitzhaki,et al.  The Diffusion of Innovations: A Methodological Reappraisal , 1982 .

[22]  R. Dixon,et al.  Hybrid Corn Revisited , 1980 .

[23]  V. Rao,et al.  A micro-analytic threshold model for the timing of first purchases of durable goods , 1998 .

[24]  Philip M. Parker,et al.  Price Elasticity Dynamics over the Adoption Life Cycle , 1992 .

[25]  G. Lilien,et al.  Bias and Systematic Change in the Parameter Estimates of Macro-Level Diffusion Models , 1997 .

[26]  Arnulf Grubler,et al.  The Rise and Fall of Infrastructures: Dynamics of Evolution and Technological Change in Transport , 1990 .