Increasing interactions and uncertainty in the current economic environment has an impact on the investment decisions companies need to make. However, the tools these companies have at their disposal fail at incorporating and valuing the impact of both aspects. The migration towards FTTC and FTTH was introduced as case study to indicate how traditional techno-economic analysis is conducted. The results of such an analysis give an indication on the economic viability of the project, but this conclusion is depending on initial assumptions made. A change in an input factor will be reflected in the final result.
In addition, the analysis only captures the financial objective of the decision maker. In reality, as was also indicated in the case study, this decision maker has additional drivers, which cannot be captured through an economic assessment. This dissertation aims at providing insight in the available extensions to techno-
economic analysis, incorporating the value of uncertainty, flexibility and competition.
References
[2.1] H. L. (Hans) van Kranenburg and J. Hagedoorn, “Strategic focus of incumbents in the European telecommunications industry: The cases of BT, Deutsche Telekom and KPN,” Telecommunications Policy, vol. 32, no. 2, pp. 116–130, Mar. 2008.
[2.2] W. Lemstra, V. Hayes, and J. P. M. Groenewegen, Eds. (2010). “The innovation journey of Wi-Fi – The road to global success”. Cambridge, UK: Cambridge University Press
[2.3] S. A. Ross, R. W. Westerfield, and J. F. Jaffe, Corporate Finance. McGraw-Hill, 2006.
[2.4] S. Verbrugge, K. Casier, J. Van Ooteghem, and B. Lannoo, “Practical steps in techno-economic evaluation of network deployment planning,”
IEEE Globecom, Tutorial, vol. 11, 2008.
[2.5] C. Lange, T. Monath, E. Weis, M. Kind, M. Adamy, and N. Gieschen, “Techno-Economic Comparison of Passive Optical Network Scenarios,” in BroadBand Europe, pp. 3–5.
[2.6] J. Harno, D. Katsianis, T. Smura, T. G. Eskedal, R. Venturin, O. P. Pohjola, K. R. R. Kumar, and D. Varoutas, “Alternatives for mobile operators in the competitive 3G and beyond business,”
Telecommunication Systems, vol. 41, no. 2, pp. 77–95, Apr. 2009.
[2.7] A. Saltelli, M. Ratto, T. Andres, F. Campolongo, J. Cariboni, D. Gatelli, M. Saisana, and S. Tarantola, Global Sensitivity Analysis: The Primer. John Wiley & Sons, 2008.
[2.8] T. Rokkas, D. Katsianis, T. Kamalakis, and D. Varoutas, “Economics of Time and Wavelength Domain Multiplexed Passive Optical Networks,”
Optical Communications and Networking, IEEE/OSA Journal of, vol. 2,
no. 12, pp. 1042–1051, Nov. 2010.
[2.9] K. Casier, S. Verbrugge, J. Van Ooteghem, D. Colle, R. Meersman, M. Pickavet, and P. Demeester, “Impact of sensitivity and iterative calculations on cost-based pricing,” in 6th Conference on
[2.10] T. E. Copeland and P. T. Keenan, “How much is flexibility worth?,”
McKinsey Quarterly, no. 2, pp. 38–50, 1998.
[2.11] T. E. Copeland and V. Antikarov, Real Options - a practitioner’s guide. Texere, 2003.
[2.12] M. Tahon, S. Verbrugge, P. J. Willis, P. Botham, D. Colle, and M. Pickavet, “Migration to Next Generation Access Networks : a Real Option Approach,” in Proceedings of ROC 2012, 2012, p. 11.
[2.13] K. Casier, “Techno-economic Evaluation of a next generation access network deployment in a competitive setting,” PhD Dissertation, 2009, p. 283.
[2.14] Analysys Mason, “The costs of deploying fibre-based next-generation broadband infrastructure,” Report for the Broadband Stakeholder Group, 2008.
[2.15] A. Cárdenas, M. García-Molina, S. Sales, and J. Capmany, “A New Model of Bandwidth Growth Estimation Based on the Gompertz Curve : Application to Optical Access Networks,” Lightwave Technology, vol. 22, no. 11, pp. 2460–2468, 2004.
[2.16] The information society EURIM, “Making broadband investment markets work - summary,” Working paper, 2011.
[2.17] B. Gompertz, “On the nature of the function expressive the law of human mortality, and on a new method of determining the value of life contingencies,” Philosophical Transactions of the Royal Society, vol. 36, pp. 513–585, 1825.
[2.18] M. J. O’Sullivan, C. G. Walker, M. L. O’Sullivan, T. D. Thompson, and A. B. Philpott, “Protecting local access telecommunications networks: Toward a minimum-cost solution,” Telecommunication Systems, vol. 33, no. 4, pp. 353–376, Dec. 2006.
[2.19] K. Casier, J. Van Ooteghem, M. Sikkema, S. Verbrugge, D. Colle, M. Pickavet, and P. Demeester, “Influence of geomarketing on the rollout of new telecom network infrastructure,” in Telecommunication, Media and
Internet Techno-Economics (CTTE), 10th Conference of, 2011, pp. 1–7.
[2.20] S. Verbrugge, D. Colle, M. Pickavet, P. Demeester, S. Pasqualini, A. Iselt, A. Kirstädter, R. Hülsermann, F.-J. Westphal, and M. Jäger, “Methodology and input availability parameters for calculating OpEx
and CapEx costs for realistic network scenarios,” Journal of Optical
Networking, vol. 5, no. 6, pp. 509–520, 2006.
[2.21] K. Casier, S. Verbrugge, R. Meersman, D. Colle, and P. Demeester, “On the costs of operating a next-generation access network,” in Proceedings
of CTTE2008, the 7th Conference Telecom, internet and media Techno- Economics (CTTE), 2008.
[2.22] Federale Overheid, “Bevolking,” Cijfers Bevolking 1990-2010, 2010.
[Online]. Available:
http://statbel.fgov.be/nl/modules/publications/statistiques/bevolking/cijfe rs_bevolking_1_1_2009.jsp. [Accessed: 04-Jul-2013].
3
Actors and their Objectives
“Management by objective works – if you know the objective. Ninety percent of the time you don’t”, Peter Drucker
The need for advanced evaluation techniques in techno-economics was introduced in the previous chapter. It was indicated how competitive and cooperative interaction must be taken into account when making decisions, as these interactions influence the viability of the investment decision. Not only does customer uptake impact the revenue potential, it is also the main driver for the network dimensioning and equipment modelling. However, before these competitive influences can be identified and captured, it is required to know the impacting actors. In this chapter, the basics of multi-actor analysis will be introduced.
A multi-actor analysis serves a double purpose. First, it helps at defining the different roles that must be taken up to produce a good or offer a service. From these role definitions, a detailed cost-benefit model can be built, starting from the underlying technological requirements. Secondly, by sketching the broader picture of the environment in which the company is active, other actors can be identified. Cooperation possibilities and competitive interactions can be indicated in this value network. Following this introduction, some of the important actors in the telecom environment will be discussed.
Building upon the qualitative description of the value network, the detailed quantitative modelling is performed. For this modelling, it is important to have a clear view on both the financial and non-financial objectives of the different actors. For financial objectives, there exists a plethora of metrics. The translation of non-financial goals is more challenging. Specifically for the fixed broadband market, a composite index was developed to measure the regulatory and policy goals.