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The Diffusion of Innovations: A Methodological Reappraisal

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  • Trajtenberg, Manuel
  • Yitzhaki, Shlomo

Abstract

Studies of diffusion have traditionally relied on specific distributions-primarily the logistic- to characterize and estimate those processes.We argue here that such approach gives rise to serious problems of comparability and interpretation, and may result in large biases inthe estimates of the parameters of interest. We propose instead the Gini's expected mean differenceas ameasure of diffusion speed, discuss its advantages over the traditional approach, and tackle with it the problems of truncated processes, inter-group comparisons, and related issues. We also elaborateon the use of the hazardrate, and suggest some possible extensions. The diffusion of CT scanners is presented as an illustration.
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Suggested Citation

  • Trajtenberg, Manuel & Yitzhaki, Shlomo, 1989. "The Diffusion of Innovations: A Methodological Reappraisal," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(1), pages 35-47, January.
    • Handle: RePEc:bes:jnlbes:v:7:y:1989:i:1:p:35-47
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    References listed on IDEAS

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    1. Shalit, Haim & Yitzhaki, Shlomo, 1984. "Mean-Gini, Portfolio Theory, and the Pricing of Risky Assets," Journal of Finance, American Finance Association, vol. 39(5), pages 1449-1468, December.
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    12. Romeo, Anthony A, 1975. "Interindustry and Interfirm Differences in the Rate of Diffusion of an Innovation," The Review of Economics and Statistics, MIT Press, vol. 57(3), pages 311-319, August.
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    Cited by:

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    2. Chen, Xiaoping & Lu, Yi & Zhu, Lianming, 2017. "Product cycle, contractibility, and global sourcing," Journal of Development Economics, Elsevier, vol. 127(C), pages 283-296.
    3. Grajek, Michal & Kretschmer, Tobias, 2009. "Usage and diffusion of cellular telephony, 1998-2004," International Journal of Industrial Organization, Elsevier, vol. 27(2), pages 238-249, March.
    4. Jonathan Beck, 2007. "The sales effect of word of mouth: a model for creative goods and estimates for novels," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 31(1), pages 5-23, March.
    5. Manuel Trajtenberg, 1985. "The Welfare Analysis of Product Innovations with an Application to CT Scanners," NBER Working Papers 1724, National Bureau of Economic Research, Inc.
    6. Kathryn Rudie Harrigan & Yunzhe Fang, 2020. "The financial benefits of persistently high forward citations," The Journal of Technology Transfer, Springer, vol. 45(2), pages 619-647, April.
    7. Jonathan Beck & Michal Grajek & Christian Wey, 2011. "Estimating level effects in diffusion of a new technology: barcode scanning at the checkout counter," Applied Economics, Taylor & Francis Journals, vol. 43(14), pages 1737-1748.
    8. Shun-Chen Niu, 2006. "A Piecewise-Diffusion Model of New-Product Demands," Operations Research, INFORMS, vol. 54(4), pages 678-695, August.
    9. repec:bla:jecsur:v:12:y:1998:i:2:p:131-76 is not listed on IDEAS
    10. Christophe Van den Bulte, 2000. "New Product Diffusion Acceleration: Measurement and Analysis," Marketing Science, INFORMS, vol. 19(4), pages 366-380, June.
    11. Bemmaor, Albert C. & Zheng, Li, 2018. "The diffusion of mobile social networking: Further study," International Journal of Forecasting, Elsevier, vol. 34(4), pages 612-621.
    12. Nin Pratt, Alejandro & Hertel, Thomas W. & Foster, Kenneth A. & Rae, Allan N., 2001. "Productivity Growth And Catching-Up: Implications For China'S Trade In Livestock Products," 2001 Annual meeting, August 5-8, Chicago, IL 20590, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

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