A System Dynamics Model for Pricing Converged Telecommunication Services

A System Dynamics Model for Pricing Converged Telecommunication Services.

Paper Submitted to

CPRSouth 2016

May 2016

10

Table of Contents

10

Abstract 4

SECTION 1:-Introduction 5

Background 5

Problem Statement/Policy Relevance: 5

Principal Research Questions: 6

SECTION 2: Literature Review 7

Cost Based Pricing Methods 7

Price & Cost Allocation type 7

Limitation of cost-based pricing approaches. 7

Investment oriented pricing alternatives 7

Symbiotic & Dynamic Pricing relationships 8

SECTION 3: Theoretical /Conceptual Framework 10

Generic Telecomms Models 10

System Dynamic Telecommunication Models 11

Proposed Conceptual Framework 12

Description of Proposed Model 13

SECTION 4:METHODS & DATA SOURCES 15

System Dynamics Approach 15

Data Sources 17

Dynamic Hypothesis (Casual Loop Diagram) 18

MODEL DEVELOPMENT 19

Balancing Loops 19

Reinforcing Loops 21

Model Testing 22

SECTION 5: Results, Analysis & Discussions. 24

Maximizing Social & Operator Surplus (Social Surplus) 24

Resulting Price Level 26

Resulting Competition Level 26

Resulting Market Indicators (Outcomes) 27

Discussions 29

SECTION 6: -Conclusion & Recommendations 30

References 31

APPENDIX- SD Model & Equations 33

Figures

Figure 1 Relationships in the new ICT Ecosystem 8

Figure 2 Techno-Economic Model (Walrand 2008) 10

Figure 5 Conceptual View -Regulatory Pricing Model (Author 2016) 12

Figure 6 Proposed System Dynamics Price Model:-Regulatory View (Author 2016) 14

Figure 7 System Dynamics Steps (Sterman 2000) 15

Figure 8 Key Relationships between Price & Regulatory Variables (Author 2016) 18

Figure 9 Estimated Price-Competition Relationship 19

Figure 10 Estimated Price-Market Penetration Relationship 20

Figure 11 Estimated Traffic Load-QoS Relationship 21

Figure 13 Internet Market Trends, Kenya (Economic Survey 2016) 23

Figure 14 User Surplus - None & Optimized Comparison 24

Figure 15 Operator Surplus - None & Optimized Comparison 25

Figure 16 Social Surplus- None Optimized & Optimized Comparison 25

Figure 17 Price – None Optimized & Optimized Comparison 26

Figure 18 Competition – None Optimized & Optimized Comparison 26

Figure 19 Market Penetration - None & Optimized Comparison 27

Figure 20 Network Performance - None & Optimized Comparison 27

Figure 21 Operational Income – None Optimized & Optimized Comparison 28

Figure 22 Market Penetration, QoS & OpIncome - Combined View 28

Tables

Table 1 Key Relationships & Theories 18

Table 2 Summary Results - Initialized vs Optimized Values 29

Abstract

Purpose:

The purpose of this paper is to propose a new model for determining the optimal prices for converged (internet) services. A new framework is considered necessary because existing telecommunication pricing models fail to capture the multiplatform and multisided nature of contemporary Telco services (Bauer, 2014)

Design/Methodology

Noting that the converged communications sector is complex and dynamic, this study uses the System Dynamics approach (Sterman, 2000) to map out key regulatory indicators (variables) and how they relate and interact with (feedback into) the Price variable. The optimal price will be one that delivers the best regulatory output - that is the price that delivers the best revenues (profit margins) subject to the constraints of market penetration and quality of services.

Results/Findings

After optimizing and executing the model, the maximized regulatory objective was achieved with 25% drop in the price value and a 50% increase in the competition level. The corresponding market outcome reported a 23% increase in market penetration, an 18% drop in the Operational Income and a 53% drop in the quality of service.

Originality/Value

A System Dynamics analytical model for pricing services for the converged telecommunication (ICT) sector is presented. Through optimization, it addresses the challenges of establishing prices for converged telco services that have multi-sided and multiplatform properties.

Key Words: ICT Policy, Regulation, Networks, Broadband, Telecommunications, Indicators, System Dynamics

SECTION 1:-Introduction

Background

Broadband internet prices remain relatively high and unaffordable, particularly in the developing countries of Africa. ITU 2015 specifically reports that the monthly broadband rates in Kenya for 1Mbs of internet access per month is at 35% of average incomes. Comparatively, it is 15%, 32% & 41% of average incomes in Ghana, Ethiopia and Senegal respectively.

These figures are far off the global targets of 5% average incomes that was set by the UN, Broadband Commission for affordable internet.

(Waema et. al. 2010) had earlier noted that despite the liberalization of the communication sector, improved regulatory policies and the landing of multiple of submarine cables to enhance connectivity to the rest of the world, the price of retail internet access remains prohibitive.

This suggests that new insights and approaches are required to tackle the question of pricing internet service in developing countries.

Problem Statement/Policy Relevance:

From a regulatory point of view, the pricing of telco services has tended to focus on the whole-sale pricing that incumbent operators would charge prospective retailers to connect to their networks. The aim of the regulator has been to find formulea to estimate the cost of services for purposes of setting interconnection prices.

However, the telecommunication market has over the last years moved away from incumbent market structures and now regulators have to find new ways to establish optimal pricing formulae for telco services that exist today, particularly those that are internet based.

Several methodologies have been proposed such as the modified Long Run Incremental Cost (Casier et al., 2009), Profitability Methodology, (Frederiksen, 2011a) to try and address this emerging challenge. Whereas these new pricing methodologies can be used to inform regulators of the cost and appropriate price elements of the new generation telecommunication services, they still suffer from the fact that they do not capture the multiplatform and multisided nature of contemporary Telco services (Bauer, 2014a)

Multisided platform refers to the property of a communication service to generate revenues from third parties rather than from the specific user of the service. Examples include free online videos where content providers or advertisers meet the cost of provision while users access the free service. This means that the price charged is decoupled from the underlying costs of service provision. It is simply a negotiated price contract between operators and the advertiser that is then partly taken up by the user.

This study used the system dynamics approach to develop a model that allows regulators to view the impact that various price values have on the overall telco-market performance. Regulators can then set targets and retrospectively derive the optimal price values expected to deliver on the same. In this manner, one can resolve the challenge of pricing services that are agnostic to underlying cost factors.

Principal Research Questions:

The key research objective is to develop a regulatory pricing model that is appropriate for the contemporary, multisided and converged (internet based) telecoms sector. In so doing, the non-linear relationships that inform the model behavior (output) was examined.

Specifically, the relationship that pricing has with selected regulatory indicators of Market Penetration, Operational Incomes (Profit) and Quality of Service (QoS) was explored and estimated under the following questions:

1. How does Internet Price relate to Market Penetration? As an example, how would a 10% price increase or price drop influence market penetration?

2. How does Internet Price relate to Revenues, Incomes (Profit)”? As an example, would does a 10% price increase or price drop influence revenues or incomes?

3. How does Internet Price relate to Quality of Service? As an example, how would a 10% price increase or price drop influence network performance (QoS)

4. What are the Tipping Points in the above relationships? Given a scale of 0-1, where 0=Lowest,1=Highest Price, which Price point gives: (i) Highest and Lowest acceptable Market Share (ii) Minimum and Max Revenues (iii) Lowest and Highest QoS.

The rest of the paper is organized as follows: Section 2:- reviews literature covering prevailing pricing mechanisms and their limitations; Section 3:- gives underpinning theoretical foundations and proposes a new regulatory pricing model; Section 4:- describes the methodology and data sources used; Section 5:- presents and discusses the results and Section 6:- provides conclusions and future work.

SECTION 2: Literature Review

Cost Based Pricing Methods

The prevailing methods for pricing communication services are cost based. This essentially means that in determining what price to charge consumers, the operator’s objective is to ensure that the cost of providing the services is covered while making acceptable returns on the investment for the shareholders.

Price & Cost Allocation type

The final price charged is therefore the cost of provisioning the service plus ‘x’, where ‘x’ is the expected profit margin. The value of possible tariffs or prices charged would range between the Break-Even Point, through the Incremental Cost (IC), Fully Allocated Costs (FAC) and the Stand Alone Cost (SAC) as described by (Casier et al., 2009)).

This is supported by (Harno, 2010) (de Aguiar, Pinheiro, Neto, Cunha, & Pinheiro, 2009) who used these cost based pricing approaches to estimate the price operators may charge to offer 3G services while (Bjorkdahl, Bohlin, & Lindmark, 2004) & (Bohline 2005) did the same to estimate prices for 4G mobile networks. (He & Walrand, 2006) did a similar analysis for the case of an Internet Service Provider.

These cost-driven price models are the same ones regulators (ITU 2009) rely on when determining appropriate wholesale interconnection prices they would enforce on incumbent operators in order to open up competition.

Limitation of cost-based pricing approaches.

However, the new (Internet-based) communication networks have disrupted the classical economic theory as the de-facto framework for setting prices and brings in other perspectives for cost recovery. Newer approaches such as investment oriented and symbiotic pricing approaches have been proposed.

Investment oriented pricing alternatives

(Frederiksen, 2011a) looked at costing broadband services in the new regulatory environment. He adopted the view that pricing of services should be based on encouraging investments rather than just establishing the interconnection charges designed to determine how much incumbent or dominant operators should charge retailers.

(Frederiksen, 2014) further noted that regulatory policy in the original regime was very much about deciding prices for wholesale products for the incumbent, based on either retail minus or cost plus with Long Run Incremental Cost (LRIC) as the most used cost concept. He says that this approach no longer applies since the main problem now is based on how to give the right incentives to all the players. This means incentivizing the incumbent, the dominant, the new entrants amongst others, so that they can make the huge investments in the next generation networks.

Symbiotic & Dynamic Pricing relationships

(Jonason, 2002) earlier observed that the traditional micro-economics methods (Supply-Demand) for establishing price levels may not entirely apply in the new digital economy. Internet Services could be priced based on spill over effects rather than cost-recovery basis.The traditional pricing approach considers the Product, Owner and Pricing as well known and distinct entities but in the digital economy, the distinction is blurred and dynamic.

He noted that pricing mechanisms indigital services are part of the product and the owners of the digital product maybe different from the owners of the Pricing mechanism.The total price of the product therefore is not based on the cost of the product alone, but includes the cost of the charging mechanism. Furthermore, the dichotomy between Seller and Buyer keeps changing, such that at one point the buyers are the sellers and vice versa.

These complex relationships that complicate the pricing of services is also observed by (Fransman, 2009)) who described them as symbiotic and documented them as shown below:

Figure 1 Relationships in the new ICT Ecosystem

Essentially, he outlines how innovation and value is created through interactions between various autonomous stakeholders. He identifies six symbiotic and dynamic relationships that connect together diverse stakeholders that include: (1) Hardware providers (2) Network Operators (3) Content & Application providers (4) Consumers. Each of these players may have a role to play in deciding the price of the communication service.

This is supported by (Bauer, 2014a) who observed the rise of Multi-Sided Platform (MSP) markets, whereby Content providers, Application providers and Network operators can be in fluid relationships. In such circumstances, the issue of pricing of services has to move beyond the traditional cost-based approaches. This is particularly the case when the service can actually be offered at no charge through Zero Rating, given the understanding that revenues will be recouped from other sources such as advertisements.

The implication is that the final price set for a service is not within the functional control of one individual player within the ICT ecosystem. It also therefore means that any regulatory intervention that focuses solely on one or two of stakeholders without thoroughly working through the impact this may have on rest of the relationships is likely to be more harmful than beneficial. This calls for dynamic regulation as described by (Bauer & Bohlin, 2008).

This research work aims to contribute to this body of knowledge by designing a regulatory pricing tool that explores the use of other parameters, over and above the traditional cost-based ones, in dealing with the question of pricing contemporary communication services. In addition, given the observed dynamic nature of the new communication services, the System Dynamics paradigm presents a suitable methodology for exploring issue.

It is expected that the tool would provide the regulator and operator a better understanding of the telecommunications market dynamics and subsequently trigger more effective pricing policies for the sector.

SECTION 3: Theoretical /Conceptual Framework

Generic Telecomms Models

(Walrand, 2008) captured quite clearly the closed looped interactions and relationships between Users, Operators and the Network (Capacity). Additionally, she demonstrated how Prices, Revenues, Investments, Demand and Quality of Service were interrelated as outlined below:

Figure 2 Techno-Economic Model (Walrand 2008)

She went further to categorize these relationships under the Economic, Regulatory and Technological layers and argued that the performance of communication networks (QoS) has often been studied extensively but always in isolation. This meant that there was little attention as to how QoS links into the Economic and the Regulatory layers. She subsequently proposed the Techno-Economic model above as a framework for holistically studying the telecommunication network.