Analyzing competitive effects between fixed and mobile broadband
[Introduction] The diffusion of mobile broadband, which use cellular mobile communication technology, is at an advanced state in many countries. It is, however, unclear how mobile broadband diffusion affects other broadband services, and fixed broadband access in particular. Following the definition of ITU (2012) we define broadband as a high speed access to the Internet with download speeds of greater or equal to 256 kbit/s. Fixed broadband includes wired technologies such as cable, DSL and FTTH.1 Mobile broadband enables a non-stationary Internet access based on cellular mobile communication technologies (such as LTE, UMTS or WIMAX). Competitive effects between different broadband access technologies are of high importance for regulation as well as for competitive strategy: With regard to regulations, technology platform competition can have an effect on the competitive behavior in the individual markets. With regard to competitive strategy, competitive or complementarity effects between different access technologies significantly determine the success of service bundeling strategies. The goal of our research is twofold. Firstly, want to gain a deeper understanding of how mobile and fixed broadband diffusion affect each other based on the latest country level panel data (ITU 2012, World Bank 2013). A second objective of our research is to deepen the understanding of factors moderating the competitive relationship between fixed and mobile broadband. We therefore present a methodology for moderation analysis and exemplarily demonstrate its application. The paper is structured as follows. The related research is presented in the following section. The third section addresses the models, data and methodology of analysis. Thereafter, the results of the competition and the moderation analyses are presented and discussed. The conclusions section discusses limitations and next research steps.
|Date of creation:||2013|
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- Yogesh V. Joshi & David J. Reibstein & Z. John Zhang, 2009. "Optimal Entry Timing in Markets with Social Influence," Management Science, INFORMS, vol. 55(6), pages 926-939, June.
- World Bank, 2013. "World Development Indicators 2013," World Bank Publications, The World Bank, number 13191.
- Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
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