Wireless network capacity management: A real options approach

Abstract

This paper applies financial option valuation methods to new wireless network capacity investment decision timing. In particular, we consider the case of network capacity for cellular telephone service. Given a cluster of base stations (with a certain traffic capacity per base station), we determine when it is optimal to increase capacity for each of the base stations contained in the cluster. We express this in terms of the fraction of total cluster capacity in use, i.e. we calculate the optimal time to upgrade in terms of the ratio of observed usage to existing capacity. We study the optimal decision problem of adding new capacity in the presence of stochastic wireless demand for services. A four factor algorithm is developed, based on a real options formulation. Numerical examples are provided to illustrate various aspects of the model.

Circular Economy and Value Creation: Sustainable Finance with a Real Options Approach

“…Additionally, a typology of real options was initially available in the work by [60]: defer option, abandon option, expansion option, and contract option, among others. Far from being exhaustive, theoretical and practical applications are numerous in fields such as mining investment (see [61] for a review), water utilities ( [62,63]), power transmission investment ( [64]), wireless network management ( [65]), pharmaceutical R&D valuation ( [66]), oil investments ( [67]), carbon capture and storage investment ( [68]), solar photovoltaic power generation ( [69]), among many others. To our knowledge, however, papers combining real options and the circular economy are still to come.…”

Operations Research (OR) in Service Industries: A Comprehensive Review

“…Chamberland () studied the expansion decision of the network when updating the base station subsystem to minimize the expansion cost; he applied the heuristic based on the tabu search to obtain an optimized solution. d'Halluin et al () discussed adding new capacity in the presence of stochastic wireless demand for services and developed a four‐factor algorithm based on a real‐options formulation. Paik and Soni () presented a mathematical model and simulated an annealing‐based approach to find optimal location updates and paging area configuration.…”

Compound real option valuation with phase-specific volatility: A multi-phase mobile payments case study

“…They do differ in the choice of option-type models to handle the business case and use a wide range of models such as the Black-Scholes model (Benaroch and Kauffman, 1999;Elnegaard and Stordahl, 2002;Basili and Fontini, 2003;Iatropoulos et al, 2004), binomial trees (Favaro et al, 1998;Benaroch et al, 2006;Kenyon and Cheliotis, 2002), the Margrabe model (Dos Santos, 1991;Kumar, 2002;Bardhan et al, 2004) and numerical and analytic approximations (Taudes et al, 2000;Dai et al, 2007;D'Halluin et al, 2007). However, all of the proposed approaches in the above literature have one thing in common: they all assume a constant volatility of the project return over the life time of the real option.…”