| The topological design of telecommunications network, categorized as a class of optimization problems known as the Optimum Network Problems (Minoux 1976, 1981; Yaged 1971, 1973), has long been of great interest to the operations research community. Optimum Network Problems (ONP), in short, focuses on the optimal design of network infrastructure in order to meet a certain set of requirements (multicommodity flow specifications, traffic bandwidth requirements, technical constraints, transmission quality, etc.) while minimize total costs. Although this type of approach provides a benchmark in terms of cost minimization in assisting the long term planing of network infrastructure, it does not explicitly consider the value of flexibilities involved during the decision making process in relation to its overall network value. When the investment is firm-specific, and thus irreversible, the decision to invest, once executed, incurs an opportunity cost. This forgone opportunity cost is equivalent to the value of the firm’s option to wait. The incremental value of a marginal unit of capacity must equal the sum the total costs for an investment to take place.
Early models of irreversible investment decisions over uncertain future price were developed by McDonald & Siegel (1985), and Brennan & Schwartz (1985), Pindyck (1988). These areas of work are the ones most closely associated with the model we develop in this paper. Here in particular, we extend the real options framework of Pindyck (1988) to characterize the investment strategies available for the quantity and timing of capacity expansion investments for a telecommunications network operator. Such investment decisions are determined under the assumption of a stochastic aggregate customer demand for telecommunication services following a geometric Brownian motion. We consider how the market value of the firm is maximized when a precise number of future network growth options are held and a precise number are exercised. A rule for determining the value of future network growth options and the optimal timing of exercising them is derived for an optimal level network capacity to be attainable. Limitations of this model are discussed in the end and we propose further directions to further extend the research undertaken.
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