科技不斷創新，資訊流通快速，各類新產品也不斷上市。新產品對公司營業額的貢獻可高達70% - 90%，然而創新產品具有較高的風險，失敗率也可達35% - 40%。因此，企業要如何有效的預測和正確的掌握市場未來之需求，配合適當的行銷策略，提升新產品上市的成功率，成為企業以來在追求的目標。
行動電話為創新通訊方式之一。相較於固定電話，行動電話屬於無線通訊技術，並提供給消費者更有彈性之個人通訊模式。行動電話市場因通訊技術不停的創新而擴散速率也不斷的加快。在現今國際化的產業經濟環境中，行動電話的擴散趨向已不侷限於國境內單一市場的擴散，而呈現出具有跨國市場的擴散特性，並成為創新擴散研究領域之重要議題。
本研究修正Bass (1969)基本創新擴散模型與Kumar & Krishnan (2002)模型進行探討行動電話在跨國間之影響情形。本研究藉由修正Bass模型建立多國擴散模型，探討各國行動電話普及程度之起飛現象，再以修正Kumar & Krishnan模型建立跨國影響擴散模型，將動態市場潛量和跨國影響因素加入模型，探討行動電話在不同跨國影響狀況下的成長趨勢，以及模型的適配與預測能力。
透過實證分析，各國行動電話成長趨勢套用在兩種擴散模型上呈現出極佳的適配能力與高準確性的預測效果。研究發現各國行動電話普及程度估計出的創新係數皆小於模仿係數，表示行動電話在各國市場擴散情況受到大眾媒體影響小於口碑傳播影響，意味著企業在行銷策略上應將資源多數集中在滿足消費者需求、著重產品品質，而不是過量投入廣告。在分析各國行動電話起飛現象，可發現高度發展國家之行動電話普及程度在很早的時間點就出現起飛現象，但須經過較長的時間才能達到百分之百的普及率，而接受創新較晚的新興國家，達到起飛現象的時間點較晚，然而只需經過較短的時間就能進入飽和期。另一方面，探討跨國影響擴散過程中，可以了解行動電話在各國之間的影響關係，從動態市場潛量也可發現各國行動電話市場受到人口分佈的影響大於經濟環境因素，證明了各國行動電話市場的大小，普及程度的高低主要受到人口成長和分佈情形，而經濟因素決定擴散過程的速率。因此，企業可透過模型中參數估計的結果，在不同國家擬定不同的行銷策略與商業模式的參考依據。

Technological innovation has been changing incessantly, the information flow has been transferred rapidly day by day in the different ways, many kinds of new products have been launched constantly to fulfill the customer's demands. The contribution of new products plays an important role to the 70%-90% of company's revenue. However, these innovative products also contain many risks which can lead to the 35%-40% of failure rate. Thus, knowing how to forecast future demand accurately and building the marketing strategy effectively for specific market are the precious keys for company's success to achieve their goals.
An evolution of mobile phone is the greatest innovation of telephone communication. Mobile phone with wireless communication technology brought more flexibility to customer compared to fixed-lined phones. Besides that, due to the technological development, the diffusion rate of mobile phone subscriptions is accelerating. In the context of globalization, this diffusion not only happens inside any single country but also presents in the cross-nation and cross-nation issues seem to be the new inspiration for innovation diffusion research.
The innovation diffusion model of Bass (1969) and Kumar & Krishnan (2002) model helped to explore the mobile phone transnational situation. Therefore, basing on the origin Bass model and Kumar-Krishnan model, I modified them and turned Bass model into the multi-national diffusion model to examine the take-off phenomenon of cell phones penetration and then turned Kumar & Krishnan model into cross -national effects diffusion model to investigate the growth trend of phones in different conditions under the dynamic market potential cross- national effects as well as the model fit and forecasting ability.
Through the empirical analysis about the growth trend of mobile phone using rate by using both diffusion models above, they brought the positive results of excellent adaptation capability with high forecast accuracy. The study found that the innovative coefficients are less than imitation coefficients. This results presented that the effect of mass media is less than word of mouth. Therefore, enterprises should invest more resources on building the relationship with customers by face-to-face selling, product quality improvement rather than just focusing on advertising. Take-off phenomenon in the analysis, the result showed that the mobile phone penetration in developed countries which started earlier than developing ones could achieve take-off phenomenon quickly but it was time-consuming for reaching at 100% of penetration rate compared to developing ones though they absorbed innovation later. In addition, basing on the cross-border effects, we can see the cross-national effects on mobile phone. The dynamic market potential of mobile phones is affected by the population distribution rather than economic factors. It stated that the growth and distribution of population will determine the size of mobile phone market and the level of penetration, while the economic factors will impact the rate of diffusion processes. Through these results above, enterprises could consider them as their own reference to building and improving their marketing strategies and business model to apply perfectly for specific market in each country.

英文文獻：
Arndt, J. 1967. Role of product-related conversations in the diffusion of a new product. Journal of marketing Research: 291-295.
Baraldi, A. L. 2008. Network Externalities and Critical Mass in the Mobile Telephone Network: a Panel Data Estimation.
Bass, & Krishnan, T. 1992. A Generalization of the Bass Model: Decision Variable Considerations. Working Paper Series.
Bass, F. M. 1969. A New Product Growth for Model Consumer Durables. Management Science, 15(5): 215-227.
Bass, F. M., Krishnan, T. V., & Jain, D. C. 1994. Why the Bass model fits without decision variables. Marketing Science, 13(3): 203-223.
Bass, P., & Bass, F. M. 2004. IT waves: Two completed generational diffusion models. University of Texas, Dallas.
Bayus, B. L. 1987. Forecasting sales of new contingent products: An application to the compact disc market. Journal of Product Innovation Management, 4(4): 243-255.
Bonnet, D. C. L. 1986. Nature of the R&D/Marketing co-operation in the design of technologically advanced new industrial products. R&D Management, 16(2): 117-126.
Chu, W. L., Wu, F. S., Kao, K. S., & Yen, D. C. 2009. Diffusion of mobile telephony: An empirical study in Taiwan. Telecommunications policy, 33(9): 506-520.
Cooper, R. G., & Kleinschmidt, E. J. 1987. New Products: What Separates Winners from Losers? Journal of Product Innovation Management, 4(3): 169-184.
Danaher, P. J., Hardie, B. G. S., & Putsis Jr, W. P. 2001. Marketing-mix variables and the diffusion of successive generations of a technological innovation. Journal of marketing Research: 501-514.
Dekimpe, M. G., Parker, P. M., & Sarvary, M. 1998. Staged estimation of international diffusion models: An application to global cellular telephone adoption. Technological Forecasting and Social Change, 57(1): 105-132.
Elberse, A., & Eliashberg, J. 2003. Demand and supply dynamics for sequentially released products in international markets: The case of motion pictures. Marketing Science, 22(3): 329-354.
Fischer, C. S. 1994. America calling: A social history of the telephone to 1940: University of California Press.
Fourt, L. A., & Woodlock, J. W. 1960. Early prediction of market success for new grocery products. The Journal of Marketing: 31-38.
Gatignon, H., Eliashberg, J., & Robertson, T. S. 1989. Modeling multinational diffusion patterns: An efficient methodology. Marketing Science, 8(3): 231-247.
Goldenberg, J., Libai, B., & Muller, E. 2010. The chilling effects of network externalities. International Journal of Research in Marketing, 27(1): 4-15.
Golder, P. N., & Tellis, G. J. 1997. Will it ever fly? Modeling the takeoff of really new consumer durables. Marketing Science, 16(3): 256-270.
Golder, P. N., & Tellis, G. J. 2004. Growing, growing, gone: Cascades, diffusion, and turning points in the product life cycle. Marketing Science, 23(2): 207-218.
Granovetter, M. 1978. Threshold models of collective behavior. American journal of sociology: 1420-1443.
Horsky, D., & Simon, L. S. 1983. Advertising and the diffusion of new products. Marketing Science, 2(1): 1-17.
Jain, D., Mahajan, V., & Muller, E. 1991. Innovation diffusion in the presence of supply restrictions. Marketing Science, 10(1): 83-90.
Jain, D. C., & Rao, R. C. 1990. Effect of price on the demand for durables: Modeling, estimation, and findings. Journal of Business & Economic Statistics, 8(2): 163-170.
Jones, J. M., & Ritz, C. J. 1991. Incorporating distribution into new product diffusion models. International Journal of Research in Marketing, 8(2): 91-112.
Jun, D. B., & Park, Y. S. 1999. A choice-based diffusion model for multiple generations of products. Technological Forecasting and Social Change, 61(1): 45-58.
Kalish, S. 1985. A new product adoption model with price, advertising, and uncertainty. Management Science, 31(12): 1569-1585.
Kalish, S., & Lilien, G. L. 1986. A market entry timing model for new technologies. Management Science, 32(2): 194-205.
Kamakura, W. A., & Ealasubramanian, S. K. 1987. Long‐term forecasting with innovation diffusion models: The impact of replacement purchases. Journal of forecasting, 6(1): 1-19.
Kreng, V. B., & Wang, H. T. 2009. A technology replacement model with variable market potential—An empirical study of CRT and LCD TV. Technological Forecasting and Social Change, 76(7): 942-951.
Kumar, V., Ganesh, J., & Echambadi, R. 1998. Cross‐National Diffusion Research: What Do We Know and How Certain Are We? Journal of Product Innovation Management, 15(3): 255-268.
Kumar, V., & Krishnan, T. V. 2002. Research note: Multinational diffusion models: An alternative framework. Marketing Science, 21(3): 318-330.
Lehmann, D. R., & Esteban-Bravo, M. 2006. When giving some away makes sense to jump-start the diffusion process. Marketing Letters, 17(4): 243-254.
Leuthold, R. M. 1975. On the use of Theil's inequality coefficients. American Journal of Agricultural Economics: 344-346.
Lewis, C. D. 1982. Industrial and business forecasting methods: A practical guide to exponential smoothing and curve fitting: Butterworth Scientific London,, UK.
Lilien, G. L., Rao, A. G., & Kalish, S. 1981. Bayesian estimation and control of detailing effort in a repeat purchase diffusion environment. Management Science, 27(5): 493-506.
Lim, B.-L., Choi, M., & Park, M.-C. 2003. The late take-off phenomenon in the diffusion of telecommunication services: network effect and the critical mass. Information Economics and Policy, 15(4): 537-557.
Lukas, B. A., & Ferrell, O. 2000. The effect of market orientation on product innovation. Journal of the academy of marketing science, 28(2): 239-247.
Mahajan, & Peterson, R. A. 1978. Innovation diffusion in a dynamic potential adopter population. Management Science, 24(15): 1589-1597.
Mahajan, V., & Muller, E. 1994. Innovation diffusion in a borderless global market: will the 1992 unification of the European Community accelerate diffusion of new ideas, products, and technologies? Technological Forecasting and Social Change, 45(3): 221-235.
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): 1-26.
Mahajan, V., Muller, E., & Kerin, R. A. 1984. Introduction strategy for new products with positive and negative word-of-mouth. Management Science, 30(12): 1389-1404.
Mahajan, V., & Peterson, R. A. 1979. Integrating time and space in technological substitution models. Technological Forecasting and Social Change, 14(3): 231-241.
Mansfield, E. 1961. Technical change and the rate of imitation. Econometrica: Journal of the Econometric Society: 741-766.
Mascarenhas, J. P. 1993. Molecular mechanisms of pollen tube growth and differentiation. The Plant Cell, 5(10): 1303.
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(9): 1069-1086.
Peres, R., Muller, E., & Mahajan, V. 2010. Innovation diffusion and new product growth models: A critical review and research directions. International Journal of Research in Marketing, 27(2): 91-106.
Röller, L. H., & Waverman, L. 2001. Telecommunications infrastructure and economic development: A simultaneous approach. American Economic Review: 909-923.
Robertson, T. S. 1967. The process of innovation and the diffusion of innovation. The Journal of Marketing: 14-19.
Robinson, B., & Lakhani, C. 1975. Dynamic price models for new-product planning. Management Science, 21(10): 1113-1122.
Rogers, E. M. 1983. Diffusion of Innovations (1983).
Rogers, E. M. 1995. Diffusion of innovations: Simon and Schuster.
Rogers, E. M. 2003. Diffusion of innovations. Social Science.
Sarvary, M., Parker, P. M., & Dekimpe, M. G. 2000. Global diffusion of technological innovations: A coupled-hazard approach. Journal of marketing Research: 47-59.
Schelling, T. C. 1978. Egonomics, or the Art of Self-Management. The American Economic Review, 68(2): 290-294.
Schmittlein, D. C., & Mahajan, V. 1982. Maximum likelihood estimation for an innovation diffusion model of new product acceptance. Marketing Science, 1(1): 57-78.
Sharif, M. N., & Ramanathan, K. 1981. Binomial innovation diffusion models with dynamic potential adopter population. Technological Forecasting and Social Change, 20(1): 63-87.
Speece, M. W., & Maclachlan, D. L. 1995. Application of a multi-generation diffusion model to milk container technology. Technological Forecasting and Social Change, 49(3): 281-295.
Srinivasan, V., & Mason, C. H. 1986. Technical Note—Nonlinear Least Squares Estimation of New Product Diffusion Models. Marketing Science, 5(2): 169-178.
Srivastava, R. K., Mahajan, V., Ramaswami, S. N., & Cherian, J. 1985. A multi-attribute diffusion model for forecasting the adoption of investment alternatives for consumers. Technological Forecasting and Social Change, 28(4): 325-333.
Steenkamp, J. B. E. M., & Burgess, S. M. 2002. Optimum stimulation level and exploratory consumer behavior in an emerging consumer market. International Journal of Research in Marketing, 19(2): 131-150.
Stremersch, S. 2008. Takeoff and Growth across Technology Generations.
Stremersch, S., & Lemmens, A. 2009. Sales growth of new pharmaceuticals across the globe: The role of regulatory regimes. Marketing Science, 28(4): 690-708.
Stremersch, S., & Tellis, G. J. 2004. Understanding and managing international growth of new products. International Journal of Research in Marketing, 21(4): 421-438.
Sundqvist, S., Frank, L., & Puumalainen, K. 2005. The effects of country characteristics, cultural similarity and adoption timing on the diffusion of wireless communications. Journal of Business Research, 58(1): 107-110.
Takada, H., & Jain, D. 1991. Cross-national analysis of diffusion of consumer durable goods in Pacific Rim countries. The Journal of Marketing: 48-54.
Tellis, G. J., Stremersch, S., & Yin, E. 2003. The international takeoff of new products: The role of economics, culture, and country innovativeness. Marketing Science, 22(2): 188-208.
Van Everdingen, Y., Fok, D., & Stremersch, S. 2008. Modeling global spill-over of new product takeoff.

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