A System Dynamics Model for Pricing Converged Telco Services CPRSouth 2016Zanzibar, TZ Presenter: J. Walubengo, Sept 2016 Co-Authors Prof. T. Waema, Prof. D. Williams Jwalubengo@mmu.ac.ke, jwalu@yahoo.com

Background(a) Pricing of Telco (Internet Access) services remains high despite the landing of the submarine cables, liberalization.(Waema et. al .2010) Internet Price “NOT Affordable” based on the fact that monthly internet rates i.e. cost of 1Mbs of Internet Access per month is 35% of Average incomes (ITU, 2015); It is 15%, 32%, 41% for Ghana, Ethiopia & Senegal respectively

Background(b) Fixed Broadband Prices, %GNI ITU, 2014 Price as a proportion of GNI. – measuring affordability

Problem Definition How can you tell if an operator is overcharging their Internet based services? How do you establish the appropriate or optimal price for a given economy? It was easier for older voice-based communication where cost of providing services was easy to establish (cost+ approaches)

Problem Definition From a regulatory policy perspective, the pricing of Telco services has tended to focus on the wholesale pricing that incumbent operators would charge prospective retailers to connect to their networks. The aim of the regulator has been to find a mechanism for estimating the cost of services for purposes of setting interconnection prices.

Problem Definition Telecommunication market has in recent years shifted away from incumbent market structures Regulators have to find new and appropriate ways for estimating optimal pricing for contemporary Telco(internet) services Furthermore, these Internet Service have new properties with commercial implications: -Multi-Sided Market and Multi-platform aspects.

Problem Defn (Bauer 2014) Complex and dynamic relationships within and between operators make it difficult for regulatory (tarrif intevention). Some, if not most of the actors lie outsider the traditional Telco regulatory domain Traditional tariff regulatory approaches fail or do not adequately address the challenge of establishing optimal price levels.

Symbiotic & Dynamic Relationships (Fransman 2009) Complex relationships make it difficult to establish optimal price levels for services thus discouraging regulatory(tariff) interventions.

Problem Definition Old regulatory tools have been revised to match the new converged environment such as Long Run Incremental Cost by (Casier et al., 2009), Profitability Methodology by (Frederiksen 2011) However, revised regulatory tools still inadequate to address new internet based telco services because they are centered on cost-based approaches (Bauer, 2014)

Proposed Solution Given the multi-sided, multi-platform nature of Internet based services a new regulatory framework is proposed. It considers a macro level approach by targeting & maximizing selected regulatory indicators over the long term Market Penetration Quality of Service (QoS) ROI, Sustainable Profit(Revenue) Based on the modified works of Dutta 2001, Rouskas 2009

Price Charged by operators for a given Service (x) lies between cost of inputs and willingness to pay (Utility) Price can be equal to Cost (maximum competition=Perfect Competition) or Price can be equal to Utility (minimum competition=monopoly) Price can be ‘in-between’ in moderately competitive environments. Operator Surplus=Operator Benefit, Profit (Price-Cost) User Surplus=User Benefit (Willingnes to Pay – Price) Social Surplus=Combined Benefit, Regulator’s objective

Telco Operations – System Dynamic View (Dutta 2001)

Conceptual Framework

Proposed Solution Acknowledges that the regulatory objective is to maximize both the consumer surplus and the telecomm provider surplus by ensuring fair competition and universal access (ITU,2010), The pricing problem is therefore redefined into one of optimization.

Proposed Solution We seek the optimal price possible, subject to meeting regulatory objectives and parameters as given below: Maximize Market Penetration:- regulatory universal access obligation that aims to reach widest possible number of users. Maximize Operational Income:-regulatory obligation that ensures operators can sustain operations while making reasonable returns to attract investments. Maximize Quality of Service:-regulatory obligation to ensure an acceptable network quality(performance) in order to protect users rights to reliable services.

Proposed Solution Assumes that the best or optimal price is one that delivers the best outcome on selected regulatory targets. E.g. For given price X, what would be the regulatory outcome within 10 years? Regulatory outcome based on the following: % Market Penetration % QoS Operational Income (+ve/-ve)

Proposed Solution Solution models and simulates a typical Telco operation. Allows Regulator to simulate various parameter instances, such as : Given Price X at given, time, T, what would be its impact in the market in terms of Market Penetration, QoS and ROI after 10years? Regulator Re-execute model with target optimization values (i.e max User/Operator Surplus). Optimization module searches for best price within the given search space of Service Levels & Competition Level The derived (optimized) price is one that delivers on the above regulatory outcome

Generic-Moderate Competition & Service Levels

Findings Regulatory Authorities must explore new tools for price interventions. A System Dynamics Pricing model is presented and simulated to show how the optimal price for converged telco services can be determined. The Optimal Price is determined to be the one that maximizes the regulatory output –rather than one that only maximizes operator surplus (cost-based). The pricing model proposes a Price search-space constrained within regulatory indicators of Market Penetration, QoS and Operator Profit. The model demonstrates the dynamic tensions between conflicting objectives of market penetration, QoS & Profit with Price as the moderating variable. Tool can be fine-tuned for specific economies and operations.

References Bauer, J.M. (2014), “Platforms, systems competition, and innovation: Reassessing the foundations of communications policy”, Telecommunications Policy, Vol. 38 No. 8-9, pp. 662–673.   Casier, K., Verbrugge, S., Ooteghem, J.V., Colle, D., Pickavet, M. and Demeester, P. (2009), “Using cost based price calculations in a converged network”, info,Vol. 11 No. 3, pp. 6–18. Dutta, A. (2001), “Business planning for network services: A systems thinking approach”, Information Systems Research, Vol. 12 No. 3, pp. 260–283. Frederiksen, J. (2011), “Broadband access, regulatory issues and profitability analyses”, info, Vol. 13 No. 5, pp. 19–28. Sterman, (2000) Business Dynamics: Systems Thinking and Modeling for a Complex World, McGraw-Hill/Irwin,

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