An Extended Diffusion Model for the Marketing Dynamics of Generations of Mobile Phone Display Panels

10.6186/IJIMS.2011.22.3.5

Su-Yun Chiang；Terry Wu-Tung Chen

Mobile phone ； simulated approach ； Bass model ； optimization

International Journal of Information and Management Sciences

22：3（2011 / 09 / 01）

265 - 276

英文

In this paper, we investigate the marketing dynamics of generations of mobile phones by using an advanced diffusion model. The adopted model considers the effects of non-uniform influence, and the heterogeneity of the population of potential adaptors on marketing dynamics. This study not only provides a basis for assessment, but also enables us to forecast the influence of recent technologies on earlier stage. Furthermore, we use the Fisher-Pry model to test the substitution on the sales of mobile phone display panels among different generations. The simulated results, compared to the real data, validate the theoretical findings, and therefore point to the ability to forecast the overwhelming growth of marketing dynamics among mobile phone display panel generations.

1. Bass, F. M.(1969).A new product growth for model consumer durables.Management Science,15,215-227.
2. Bass, F. M.(2004).Comments on a new product growth model for consumer durables.Management Science,50,1833-1840.
3. Chiang, S. Y.,Li, Y.,Yu, H. C.(2010).Modeling and simulation of market dynamics for successive generation of flash memory.International Journal of Computational Engineering Science,5,50-57.
4. Core, A. P.,Lavaraj, U. A.(1987).Innovation Diffusion in a Heterogeneous Population.Technological Forecasting and Social Change,32,163-168.
5. Easingwood, C.,Mahajan, V.,Muller, E.(1983).A nonuniform influence innovation diffusion model for new product acceptance.Marketing Science,2,273-296.
6. Fisher, J. C.,Pry, R. H.(1971).A simple substitution model of technological change.Technological Forecasting and Social Change,3,75-88.
7. Fourt, L. A.,Woodlock, J. W.(1960).Early prediction of market success for grocery products.Journal of Marketing,25,31-38.
8. Iansiti, M.(2000).How the incumbent can win: Managing technological transitions in the semiconductor industry.Management Science,46,169-185.
9. Kalish, S.,Lilien, G. L.(1986).A market entry timing model for new technologies.Management Science,32,194-205.
10. Kim, W. J.,Lee, J. D.,Kim, T. Y.(2005).Demand forecasting for multigenerational products combining discrete choice and dynamics of diffusion under technological trajectories.Technological Forecasting and Social Change,72,825-849.
11. Li, Y.,Chiang, S. Y.,Liou, K. Y.(2007).Evolutionary estimation of diffusion models in multigeneration NAND flash memory using genetic algorithm.Proceedings of the International Conference of Computational Methods in Sciences and Engineering,Greece:
12. Mahajan, V.,Muller, E.,Bass, F. M.(1990).New product diffusion models in marketing: A review and directions for research.Journal of Marketing,54,1-26.
13. Mahajan, V.,Peterson, R. A.(1979).Integrating time and space in technological substitution models.Technological Forecasting and Social Change,14,231-241.
14. Mansfield, E.(1961).Technical change and the rate of imitation.Econometrica,29,741-766.
15. Masini, A.,Frankl, P.(2003).Forecasting the diffusion of photovoltaic systems in southern europe: A learning curve approach.Technological Forecasting and Social Change,70,39-65.
16. Meade, N.,Islam, T.(2006).Modeling and forecasting the diffusion of innovation-A 25-year review.International Journal of Forecasting,22,519-545.
17. Meyer, P. S.,Yung, J. W.,Ausubel, J. H.(1999).A primer on logistic growth and substitution: The mathematics of the Loglet Lab software.Technological Forecasting and Social Change,61,247-271.
18. Midgley, D.(1979).A simple mathematical theory of innovative behavior.Journal of Consumer Research,3,31-41.
19. Norton, J. A.,Bass, F. M.(1987).A diffusion theory model of adoption and substitution for successive generations of high-technology products.Management Science,33,1069-1086.
20. Parker, P.(1993).Choosing among diffusion models: some empirical evidence.Marketing Letters,4,81-94.
21. Parker, P. M.(1994).Aggregate diffusion forecasting models in marketing: A critical review.International Journal of Forecasting,10,353-380.
22. Rogers, E. M.(1983).Diffusions of Innovations.New York:The Free Press.
23. Ruiz-Conde, E.(2004).Modeling Innovation Diffusion Patterns.Labyrint Publications.
24. Ruiz-Conde, E.,Leeflang, P. S. H.(2006).Diffusion of franchising as an innovation of managerial organization.Marketing JRM,65-75.
25. Ruiz-Conde, E.,Leeflang, P. S. H.,Wieringa, J. E.(2006).Marketing variables in macro-level diffusion models.Journal für Betriebswirtschaft,56,155-183.
26. Sharif, M.,Ramanathan, K.(1982).Polynomial innovation diffusion models.Technological Forecasting and Social Change,21,301-323.
27. Srinivasan, V.,Mason, C. H.(1986).Nonlinear least squares estimation of new product diffusion models.Marketing Science,5,169-178.
28. Steffens, P. R.(1998).Applying diffusion models with regional heterogeneity.Marketing Letters,70,361-369.
29. Versluis, C.(2002).DRAMs, fiber and energy compared with three models od market penetration.Technological Forecasting and Social Change,69,263-286.
30. Victor, N. M.,Ausubel, J. H.(2002).DRAMs as model organisms for study of technological evolution.Technological Forecasting and Social Change,69,243-262.
31. Weerahandi, S.,Dalal, S. R.(1992).A choice-based approach to the diffusion of a service: Forecasting fax penetration by market segments.Marketing Science,11,39-53.