Using cost based price calculations in a converged network
Purpose ‐ The purpose of this paper is to show how in a converged network, all services are provided over the same network infrastructure. This obfuscates the costs of the different services in an overall sunk cost. When deploying a new service over the network it is important to know the price that will cover the costs incurred by this service. This paper aims to investigate different approaches to calculate this price, to propose an optimal calculation approach and to estimate the sensitivity of this approach to changes in the inputs or when the inputs will recursively depend on the price set for the service. Design/methodology/approach ‐ The paper uses existing cost allocation schemes to this particular problem and within simulations, it investigates their outcome on the bottom price margin. Additionally dedicated Monte-Carlo simulations give information on general sensitivity and iterative simulations are used for detecting the impact of this recursive influence of price on its inputs. Findings ‐ The optimal calculation approach uses a combination of incremental allocation and full allocation which places a bottom margin on the price which is both sustainable and competitive in the long run. Simulations show large differences of up to 50 percent with other approaches. Additionally the simulations indicate the importance of the length of the calculation horizon as a too small calculation horizon could also lead to differences of up to 50 percent. Sensitivity results indicated a low impact of changes on the bottom margin obtained using this optimal calculation approach and a much higher impact on the non-optimal margins. Finally iterative calculations showed the importance of highly detailed market research as a 10 percent mismatch between market-research implicit price and calculated price margin will lead to at least 10 percent difference and might lead to up to 25 percent difference. Originality/value ‐ The paper links the research field of cost allocation and bottom up cost calculation to the pricing margins calculated in a typical business case evaluation phase. It also links the pricing recursively to adoption and completes the calculations in an iterative manner. Finally the research is completed with sensitivity analysis of the results to changes in the input adoption.
Keywords: Bottom up decision making; Cost allocation; Pricing
Document Type: Research Article
Publication date: 08 May 2009
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