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Firm level innovation diffusion of 3G mobile connections in international context

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  • Islam, Towhidul
  • Meade, Nigel

Abstract

Our objective is to explain the differences in the technology diffusion of 3G mobile phones at the firm level. Using a firm level diffusion model, we investigate: the effect of social globalization on within- and across-brand word-of-mouth communications; the impact of competitive fractionalization on the probability of adoption; and the effect of the population density on market potential. We use non-linear mixed modeling on pooled multi-country data from 123 firms in 40 countries to estimate a generalised firm level model. Our substantive findings are: social globalization has a positive impact on within-brand communications, and a negative impact on across-brand communications; competitive fractionalization has a negative impact on the probability of firm level adoption; and population density has a positive impact on the market potential. Finally, we demonstrate the model’s validity using the model fit and predictive accuracy. Our findings will aid international managers in the evaluation of diverse international market forecasts for entries and regulators in their formulation of strategy and policy.

Suggested Citation

  • Islam, Towhidul & Meade, Nigel, 2015. "Firm level innovation diffusion of 3G mobile connections in international context," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1138-1152.
    • Handle: RePEc:eee:intfor:v:31:y:2015:i:4:p:1138-1152
    DOI: 10.1016/j.ijforecast.2013.05.002
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    1. Alesina, Alberto & Devleeschauwer, Arnaud & Easterly, William & Kurlat, Sergio & Wacziarg, Romain, 2003. "Fractionalization," Journal of Economic Growth, Springer, vol. 8(2), pages 155-194, June.
    2. John A. Norton & Frank M. Bass, 1987. "A Diffusion Theory Model of Adoption and Substitution for Successive Generations of High-Technology Products," Management Science, INFORMS, vol. 33(9), pages 1069-1086, September.
    3. Bing Jing, 2011. "Social Learning and Dynamic Pricing of Durable Goods," Marketing Science, INFORMS, vol. 30(5), pages 851-865, September.
    4. Aghion, Philippe & Howitt, Peter, 1992. "A Model of Growth through Creative Destruction," Econometrica, Econometric Society, vol. 60(2), pages 323-351, March.
    5. Frank M. Bass & Trichy V. Krishnan & Dipak C. Jain, 1994. "Why the Bass Model Fits without Decision Variables," Marketing Science, INFORMS, vol. 13(3), pages 203-223.
    6. Islam, Towhidul & Meade, Nigel, 2012. "The impact of competition, and economic globalization on the multinational diffusion of 3G mobile phones," Technological Forecasting and Social Change, Elsevier, vol. 79(5), pages 843-850.
    7. Maria Akers & Jason Henderson, 2009. "Coming home to rural America: demographic shifts in the Tenth District," Economic Review, Federal Reserve Bank of Kansas City, vol. 94(Q III), pages 65-90.
    8. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    9. Stephan Klasen & Thorsten Nestmann, 2006. "Population, population density and technological change," Journal of Population Economics, Springer;European Society for Population Economics, vol. 19(3), pages 611-626, July.
    10. Cindy Chung & Peter Darke, 2006. "The consumer as advocate: Self-relevance, culture, and word-of-mouth," Marketing Letters, Springer, vol. 17(4), pages 269-279, December.
    11. Wolfgang Keller, 2004. "International Technology Diffusion," Journal of Economic Literature, American Economic Association, vol. 42(3), pages 752-782, September.
    12. Frederiksen, Peter C, 1981. "Further Evidence on the Relationship between Population Density and Infrastructure: The Philippines and Electrification," Economic Development and Cultural Change, University of Chicago Press, vol. 29(4), pages 749-758, July.
    13. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    14. Hubert Gatignon & Jehoshua Eliashberg & Thomas S. Robertson, 1989. "Modeling Multinational Diffusion Patterns: An Efficient Methodology," Marketing Science, INFORMS, vol. 8(3), pages 231-247.
    15. Axel Dreher, 2006. "Does globalization affect growth? Evidence from a new index of globalization," Applied Economics, Taylor & Francis Journals, vol. 38(10), pages 1091-1110.
    16. Christophe Van den Bulte & Stefan Stremersch, 2004. "Social Contagion and Income Heterogeneity in New Product Diffusion: A Meta-Analytic Test," Marketing Science, INFORMS, vol. 23(4), pages 530-544, July.
    17. Islam, Towhidul & Fiebig, Denzil G. & Meade, Nigel, 2002. "Modelling multinational telecommunications demand with limited data," International Journal of Forecasting, Elsevier, vol. 18(4), pages 605-624.
    18. Islam, Towhidul & Fiebig, Denzil G, 2001. "Modelling the Development of Supply-Restricted Telecommunications Markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 20(4), pages 249-264, July.
    19. Sergei Savin & Christian Terwiesch, 2005. "Optimal Product Launch Times in a Duopoly: Balancing Life-Cycle Revenues with Product Cost," Operations Research, INFORMS, vol. 53(1), pages 26-47, February.
    20. Islam, Towhidul & Meade, Nigel, 2013. "The impact of attribute preferences on adoption timing: The case of photo-voltaic (PV) solar cells for household electricity generation," Energy Policy, Elsevier, vol. 55(C), pages 521-530.
    21. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
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    Cited by:

    1. Edward Oughton, 2018. "Towards 5G: scenario-based assessment of the future supply and demand for mobile telecommunications infrastructure," Working Papers 2017/04 (revised), Cambridge Judge Business School, University of Cambridge.
    2. Edward Oughton, 2017. "Towards 5G: scenario-based assessment of the future supply and demand for mobile telecommunications infrastructure," Working Papers 2017/04, Cambridge Judge Business School, University of Cambridge.
    3. Meade, Nigel & Islam, Towhidul, 2021. "Modelling and forecasting national introduction times for successive generations of mobile telephony," Telecommunications Policy, Elsevier, vol. 45(3).
    4. Lim, Hyungsoo & Jun, Duk Bin & Hamoudia, Mohsen, 2019. "A choice-based diffusion model for multi-generation and multi-country data," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 163-173.

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