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Aalto University School of Business Master's Theses are now in the Aaltodoc publication archive (Aalto University institutional repository)
School of Business | Department of Accounting | Accounting | 2014
Thesis number: 13610
Pricing of additional features in mobile telecommunication networks
Author: Reijonen, Antti
Title: Pricing of additional features in mobile telecommunication networks
Year: 2014  Language: eng
Department: Department of Accounting
Academic subject: Accounting
Index terms: laskentatoimi; accounting; teleoperaattorit; telecommunications industry; teleliikenne; teletraffic; hinnoittelu; pricing
Pages: 134
Full text:
» hse_ethesis_13610.pdf pdf  size:2 MB (1093171)
Key terms: pricing; additional feature; software; hardware; telecommunication; mobile; cdma; wcdma; lte; operator; network
Abstract:
In this Master's thesis are investigated different pricing strategies for additional features in Mobile Telecommunication Networks (MTN). Pricing is studied from three different perspectives (i) MTN equipment vendor costs (ii) MTN operator value from additional features and (iii) end user benefits from additional features. In the MTN industry value is formed from hundreds of different variables and the MTN operators are varying significantly on size and business concept. In this Master's thesis it was found that it is not possible to select any universal pricing strategy or tool that would fit for all additional features. Generally pricing strategies based on a measurable variable like cost, demand or value, are better than those strategies, where the price or part of it is set without any direct link to any such variable. Even if no single common practical pricing method can be formed; it is possible to build a sequence chart or guidelines for assisting pricing decisions in finding most suitable method for finding an optimal reference price. Also for some individual features it is possible to build a new pricing tool or modifies an existing tool for calculating a proper reference price for an additional feature via analytical methods.
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