Please use this identifier to cite or link to this item: https://ir.iimcal.ac.in:8443/jspui/handle/123456789/342
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dc.contributor.authorSaha, Debashis
dc.contributor.authorBanerjee, Ashok
dc.date.accessioned2017-05-03T10:38:17Z
dc.date.accessioned2021-08-26T03:54:33Z-
dc.date.available2017-05-03T10:38:17Z
dc.date.available2021-08-26T03:54:33Z-
dc.date.issued2008-02-01
dc.identifier.urihttps://ir.iimcal.ac.in:8443/jspui/handle/123456789/342-
dc.description.abstractTelecom Infrastructure (TI) services have recently become popular due to the unbundling of legacy telecom business into smaller service segments across the value chain. TI service providers (TISPs) develop their proprietary basic infrastructure (such as ducts for laying fibre optic cables and/or dark fibres) and deliver that infrastructure on demand in such a way that customers neither incur the high fixed costs of building the required infrastructure on their own, nor commit to long-term fixed-price outsourcing contracts. However, given the high opportunity cost involved in this kind of projects, TISPs often find it difficult to mark the correct price for their offerings. We argue that the century-old cost-plus pricing method is especially inadequate for TI services, because these services have uncertain demand, high development costs, and a long life cycle. This is truer for a TISP operating in a monopolistic environment where it has to provide regulated services- say in an upcoming special economic zone or a satellite township with no such infrastructure in place. In this type of green-field projects, the initial growth pattern ought to be sporadic- there will be a few hubs (or concentrations) against some moderate-to-low demands distributed randomly. Further, the hubs will not be all equally spaced. So it is very difficult to predict and estimate the overall demand pattern in such a scenario. Thus, only an appropriate pricing methodology, which explicitly takes into account the inherent uncertainty in the pricing decision by modeling contingent factors, such as uncertain rate of adoption or demand elasticity, can account for opportunity as well as risk. The proposed methodology optimizes the expected “net present value (NPV),” subject to financial performance constraints,en_US
dc.description.sponsorshipINDIAN INSTITUTE OF MANAGEMENT CALCUTTAen_US
dc.language.isoen_USen_US
dc.publisherINDIAN INSTITUTE OF MANAGEMENT CALCUTTAen_US
dc.relation.ispartofseriesWORKING PAPER SERIES;WPS No. 625/ February 2008
dc.titlePricing Telecom Infrastructure in a Monopolistic Market: A Novel NPV-based Approachen_US
dc.typeWorking Paperen_US
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