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市場調查報告書

行動通訊業者的經營模式:課題,市場機會及策略

Mobile Operator Business Models: Challenges, Opportunities & Strategies 2014-2019

出版商 Juniper Research 商品編碼 200278
出版日期 內容資訊 英文
商品交期: 最快1-2個工作天內
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行動通訊業者的經營模式:課題,市場機會及策略 Mobile Operator Business Models: Challenges, Opportunities & Strategies 2014-2019
出版日期: 2014年10月22日 內容資訊: 英文
簡介

手機業者因為面臨業務收益的減少與網路成本上升這二個課題,而必須拓展新收益源和降低處理成本。M2M,行動金融,直接營運商計費及「巨量資料」分析等領域上在今後5年的商機有達到660億美元以上的可能性。

本報告提供MNO所面臨的嚴重課題調查分析,彙整面對未來要維持充分利益所需的各種策略,為您概述為以下內容。

摘要整理

第1章 課題:飽和的全球

  • 簡介
  • 飽和的全球
  • MNO的ARPU的減少
  • OTT的崛起
  • MNO收益的減少

第2章 課題:資料中心的全球

  • 簡介
  • CAPEX的上升:網路的建立
  • 摘要:收益的持平,Capex的增加,Opex的增加

第3章 課題:法規因素

  • 簡介
  • 綠色imperative(環保相關義務)
  • 價格控制
  • 追加課稅
  • 網路中立性的課題

第4章 從電路替換方式轉換為ALL-IP網路

  • 新的策略,新的經營模式
  • 4G環境的策略性方法
  • 4G環境核心服務的收益化
  • 售後服務
  • 結論:課題的差異化

第5章 新的收益源:計費關係

  • 簡介
  • 直接營運商計費的促進要素
  • 直接營運商計費的課題

第6章 新的收益源:雲端·巨量資料

  • 對雲端的轉換
  • 巨量資料的機會
  • 巨量資料的收益化

第7章 新的收益源:行動金融

  • MNO為何應該開始行動金融服務
  • 行動金融匯款服務的收益化
  • 身為金融服務啟用/供應商的業者
  • NFC:MNO的時期過去了
  • 行動金融機會的評估

第8章 新的收益源:M2M & 連接

  • 行動M2M定義
  • M2M的收益模式
  • 聯網汽車領域的MNO的機會
  • 智慧家庭領域的MNO的機會
  • MNO M2M機會的規模

第9章 適應策略:減輕網路的負擔

  • 課題的規模評估:卸載解決方案
  • 網路的最佳化
  • 基地台配合OPEX
  • 網路的綠色化:降低OPEX與永續性的措施

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目錄

Juniper's market leading research provides mobile operators, faced by the twin problems of decreasing service revenues and rising network costs, with an essential strategic guide to maximising new revenue streams and cost reduction.

Providing an authoritative, objective assessment of operator challenges and opportunities, this research is a must-have strategic guide for industry professionals.

Key Features

  • Strategic guide to maximising new revenue streams and cost reduction.
  • Assesses and quantifies the nature and scale of the threats facing network operators.
  • Highlights a host of alternative pricing and bundling options through which players can better monetise their core voice and data offerings.
  • Features a heat map analysis enabling Tier 1 and Tier 2 operators in both developed and developing markets to prioritise their strategic decisions and maximise their revenue potential.
  • Invaluable insights from interviews with the leading players across the mobile industry, including Three UK, Amdocs, Bango, Gemalto and Ruckus Wireless.

Key Questions

  • 1.How can MNOs leverage their existing assets to create new revenue opportunities?
  • 2.How will operator ARPUs and service revenues develop over the next 5 years?
  • 3.What strategies should MNOs adopt to optimise their existing revenue streams?
  • 4.How can MNOs address the opex and capacity issues associated with high levels of data traffic?
  • 5.Which operators have successfully remodelled their business to adapt to the evolving mobile ecosystem?

Companies Referenced

Interviewed: Amdocs, Bango, Gemalto, Ruckus Wireless, Three UK.

Case Studied: AT&T, China Mobile.

Referenced: Accenture, Acision, Air Kenya, Alcatel-Lucent, Amazon, Antel, Apple, Bakinder, Banco Sabadell, Banglalink, BBVA, BEREC (Body of European Regulators for Electronic Communication), Bharti Airtel, BlackBerry, Boku, Bouygues Telecom, BT, Capital One, CCK, Cellmania, China Mobile, China Unicom, Chunghwa Telecom, Cinterion, Cisco, Citrix, CMT Concirrus, Danal, Deezer Mobile, Deloitte, Demos, Deutsche Telekom, Dialogue, DIMOCO, Disney, EA, EE, Equity Bank, Etisalat, ETNO, ETSI (European Telecommunications Standards Institute), Facebook, FATF (Financial Action Task Force), Flash Networks, Fonix, France Telecom, Giesecke & Devrient, Generali Seguros, Globe, Google, GSA, GSMA, Hughes Telematics, Hulu, Hyundai, ICASA, Idea Cellular, IMI, Impulse, Interdnestrcom, ITU, Jasper Wireless, KakaoTalk, KDDI, Kenya Airways, Kik Messenger, Kore Telematics, KPN, La Caixa, LightSquared, LINE, LOVEFiLM, MasterCard, Masternaut, MetroPCS, Microsoft, Mixi, Mozilla, MTN, Naivas, NatWest Bank, Netflix, Net-M, Neul, Nimbuzz, Nokia, Novarra, NTT DoCoMo, Numerex, O2, Oberthur, Ofcom, Onstar, OpenMarket, Openwave Mobility, Oracle, Orange, Orca, Oxygen8, Pandora, Payforit, PayPal, Proxama, Rabobank, Redtail Telematics, Reliance, Rogers, Roku, Safaricom, Samsung, Sandvine, SAP, SFR, Siemens, Sierra Wireless, SimplyTapp, SK Telecom, Sky, SoftBank, SoftCard, Sparkassen, Spectranet, Spotify, Sprint, STC, Syniverse, Syntonic Wireless, Tango, Tata, Tele2, Telecom Italia, Telefonica, Telenet, Telenor, TeliaSonera, Telit, Telma, Telstra, Tencent, textPlus, TiVo, Towers Watson, Transatel, Trilliant, Twitter, txtNation, Uchumi, UNE EPM Telecomunicaciones, Uninor, Velti, Veoo, Verizon Wireless, Viber, Vimpelcom, Virgin Media, Visa, Vodafone, WeChat, Western Union, Weve, WhatsApp, WIND, XL Axiata, YouTube, Zain, Zalo.

Data & Interactive Forecast

Juniper Research's highly granular interactive excels enable clients to compare select markets side by side in customised charts and tables.

This user friendly document allows the purchaser to gain an in-depth understanding of operator revenue streams, both in terms of core (voice and data) revenues and new opportunities from areas such as M2M (machine to machine), direct carrier billing and analytics.

Forecast suite also includes:

  • Regional & Sector Analysis tools allowing clients to compare select markets side by side in customised charts and tables.
  • Access to the full set of forecast data of more than 500 datapoints.

Table of Contents

1. The Challenge: A Saturated World

  • 1.1 Introduction
  • 1.2 A Saturated World
    • Figure & Table 1.1: Global Mobile Subscriber Base (m) Split by 8 Key Regions 2003-2013
    • Table 1.2: Historical Mobile Penetration Rates Split by 8 Key Regions 2006-2013
    • Table 1.3: Forecast Mobile Penetration Rates Split by 8 Key Regions 2014-2019
    • Figure & Table 1.4: Global Mobile Active SIM Cards (m) Split by 8 Key Regions 2014-2019
  • 1.3 MNO ARPUs are Declining
    • 1.3.1 Attributing Factors
    • Figure & Table 1.5: Operator-billed Monthly ARPU ($) Split by 8 Key Regions 2005-2013
    • 1.3.2 ARPU Baseline Analysis: Developed Markets
    • Figure 1.6: Baseline Analysis of Historic ARPU, Developed Markets 2005-2013
    • 1.3.3 ARPU Baseline Analysis: Developing/Emerging Markets
    • Figure 1.7: Baseline Analysis of Historic ARPU, Developing/Emerging Markets 2005-2013
    • 1.3.4 Regional ARPU Forecasts
    • Figure & Table 1.8: Mobile ARPU ($) Split by 8 Key Regions 2014-2019
  • 1.4 The Rise of the OTTs
    • 1.4.1 Mobile Communications in Transition
    • Figure 1.9: Evolution of Mobile Personal Communications
    • 1.4.2 OTT Messaging Substitution
    • Table 1.10: Leading Mobile IM Service Users Bases (Active/Registered) and Traffic Levels, 2013-2014
    • i. Regional Variations
    • Figure 1.11: Most Popular IM Apps in a Selection of Countries, December 2013
    • ii. Quantifiable Impact
    • Table 1.12: Average SMS Sent Per User Per Month, Selected Operators, 2011- 2013
    • 1.4.3 Social Media Substitution
    • Figure 1.13: Facebook Mobile Users (m), 2008-H1 2014
    • 1.4.4 OTT VoIP Substitution
    • 1.4.5 The Impact on MNO Voice Revenues
    • Figure 1.14: Baseline Analysis of Operator-billed Voice Revenues, Selected Markets, 2008-2013
    • 1.4.6 Quantifying the OTT Effect
    • Figure & Table 1.15: The Lost Opportunity: MNO Revenue Loss to OTT mVoIP/IM Services ($m) Split by 8 Key Regions 2012-2014
  • 1.5 MNO Revenues are Now in Decline
    • Figure & Table 1.16: Operator-billed Service Revenues ($bn) Split by 8 Key Regions 2005-2013
    • Figure & Table 1.17: Operator-billed Service Revenues ($bn) Split by 8 Key Regions 2014-2019

2. The Challenge: A Data-centric World

  • 2.1 Introduction
  • 2.2 Rising Opex: Data Delivery Costs
    • 2.2.1 The Rise of the Mobile Internet
    • Figure & Table 2.1: Mobile Internet User Base (m) Split by 8 Key Regions 2009- 2013
    • 2.2.2 The Rise in Data Traffic
    • Figure & Table 2.2: Total Data Traffic per Annum from Mobile Handsets (PB) Split by 7 Data Categories 2013-2017
    • Figure & Table 2.3: Total Data Traffic Per Annum (PB) Carried Via Cellular Networks Split by 8 Key Regions 2013-2017
    • 2.2.3 Cost Implications of the Data Surge
    • Figure 2.4: Global Operator-Billed Service Revenues versus Delivery Costs of Unoptimised Data ($bn) 2013 & 2018
  • 2.3 Rising Capex: Network Buildout
    • 2.3.1 Spectrum Costs
    • Figure 2.5: Number of Commercial LTE Network Launches 2009-2014
      • i. Indian Spectrum Auction
      • Figure 2.6: Bharti Airtel: Cumulative 3G Data Revenues ($m) vs Percentage of 3G Licence Fee Recouped (%), 2011-2014
      • Figure 2.7: Bharti Airtel: Cumulative 3G Data Revenues ($m) Historic and Forecast, 2011-2017
      • ii. Refarming Spectrum
    • 2.3.2 Infrastructure Costs
  • 2.4 Summary: Flatlining Revenues, Rising Capex, Rising Opex
    • Figure & Table 2.8: Base Line Analysis of Global Mobile Subscriber Growth, ARPU & Operator-Billed Revenues 2013-2019
    • Figure & Table 2.9: Global MNO Service Revenues vs Capex/Opex ($bn) 2013- 2018

3. The Challenge: Regulatory Factors

  • 3.1 Introduction
  • 3.2 The Green Imperative
    • 3.2.1 Developing Markets
    • Figure 3.1: Global WTI Crude Oil Price Per Barrel ($), 2007-2014
    • 3.2.2 Developed Markets
  • 3.3 Pricing Controls
    • Figure & Table 3.2: EU Average SMS Prices (€) Split by Retail & Wholesale Q3 2008-Q2 2013
    • Figure & Table 3.3: EU Average Prices per MB of Roaming Data (€) Split Retail & Wholesale Q3 2008-Q3 2013
    • Table 3.4: EU Retail and Wholesale Roaming Price Caps (€) 2012-2014
    • 3.3.1 Mobile Termination Rate Cuts
    • Figure 3.5: Vodafone, Retail Price Per Minute, Selected Markets, 2008-2013 (YE March)
  • 3.4 Additional Taxation
    • 3.4.1 Service Taxation
    • 3.4.2 Licence Fee Increases
    • Table 3.6: Current and Proposed Total Annual Licence Fees for UK 900MHz & 1800MHz Spectrum, August 2014 (£/$m)
  • 3.5 The Net Neutrality Issue

4. From Circuit Switched to All IP Networks

  • 4.1 New Strategies, New Business Models
  • 4.2 Strategic Approaches in a 4G Environment
    • 4.2.1 LTE Options for Voice Explored by Operators but VoLTE Slow to Take Off
      • i. MNOs Embrace OTT, Creating Carrier OTT Plays
      • ii. New Service Propositions to Emerge from OTT/ MNO Partnerships
      • iii. Regulatory Regimes Level the Playing field for OTT Providers
      • iv. OTT Opens the Door to New Business Models and Fixed Line Players
      • v. Revenue Summary
      • Figure & Table 4.1: Redressing the Balance: MNO OTT mVoIP Opportunity ($m), Split by 8 Key Regions 2014-2018
  • 4.3 Monetising Core Services in a 4G Environment
    • 4.3.1 The Shared Data Plan
    • Table 4.2: Verizon Wireless, More Everything Monthly Line Charges, August 2014
    • Table 4.3: Verizon Wireless, More Everything Monthly Data Allowance Charges, August 2014
      • i. Prognosis
      • Figure 4.4: AT&T Mobile Share Accounts * Connections (m), 2013-2014
      • ii. Juniper's View:
    • 4.3.2 The Unlimited Data Option
      • i. What is unlimited data?
      • ii. Prognosis
    • 4.3.3 The Content Bundle
      • i. Prognosis
    • 4.3.4 The Social Media Bundle
    • Table 4.5: Approximate Data Usage, Selected Mobile Applications
      • i. Prognosis
    • 4.3.5 Third Party Pays
      • i. Prognosis
  • 4.4 After Sales Service
    • 4.4.1 Enhancing Customer Relationship Management
  • 4.5 Conclusion: The Differentiation Challenge
    • Figure 4.6: Possible Core Service Differentiation Strategies, Developed Markets

5. New Revenue Streams: the Billing Relationship

  • 5.1 Introduction
  • 5.2 The Drivers of Direct Carrier Billing
    • 5.2.1 Monetising the Unbanked and Underbanked
    • 5.2.2 Monetising Younger Demographics
    • 5.2.3 Direct Carrier Billing is Optimal for Impulse Purchases
    • Figure 5.1: Percentage of BlackBerry Users that Prefer Carrier Billing if the Option is Available
    • 5.2.4 High Conversion Rates
    • Figure 5.2: Billing Mechanism Conversion Rate Comparison, Low Value Purchases: Credit Card vs Direct Carrier Billing
    • 5.2.5 Uplift in Transaction Volumes and Values
    • 5.2.6 Direct Carrier Billing Enables MNOs to Retain Foothold in Content Value Chain
  • 5.3 The Challenges of Direct Carrier Billing
    • 5.3.1 Revenue Share
    • 5.3.2 Integration Issues
    • Table 5.3: Selected OTT Storefronts, Operator Billing Availability 2012-2014
    • 5.3.3 Direct Carrier Billing is Less Suited to Higher Value Transactions in Prepaid-centric Markets
    • Table 5.4: Selected Markets, Prepaid Users as % of Mobile User Base, 2013
    • 5.3.4 Bill Shock
    • 5.3.5 Wi-Fi Payments
    • 5.3.6 Local Regulation

6. New Revenue Streams: Cloud & Big Data

  • 6.1 The Transition to Cloud
    • 6.1.1 Monetising Cloud Traffic
    • 6.1.2 Leveraging the pipe
    • 6.1.3 Rethinking IT strategy
  • 6.2 The Big Data Opportunity
    • 6.2.1 The Challenge for MNOs
    • 6.2.2 The Challenge of Customer Analytics
    • 6.2.3 The Monetisation of Customer Information
      • i. Monetisation with Third-parties
      • ii. Case Study: Verizon Precision Market Insight - Analytics for Third-Party Research
    • 6.2.4 The Privacy Challenge
  • 6.3 Monetising Big Data
    • Figure & Table 6.1: The MNO Incremental Revenue Opportunity ($m) from Analytics, Split by 8 Key Regions 2013-2018

7. New Revenue Streams: Mobile Money

  • 7.1 Why Should MNOs Launch Mobile Money Services?
    • 7.1.1 Barriers to Co-operation: The Banks' Perception
  • 7.2 Monetising Mobile Money Transfer Services
    • 7.2.1 Setting the Trend: M-PESA
    • Figure & Table 7.1: Safaricom Data Revenues (KES bn) Split by Broadband, MPESA & SMS 2009-2014
      • i. Service Developments
    • 7.2.2 Service Regulation
      • i. Key Criteria for Success
  • 7.3 The Operator as Financial Service Enabler/Provider
  • 7.4 NFC: The MNO Window Has Passed
    • 7.4.1 SIM-based SE Loses Out to HCE-based Solutions
    • 7.4.2 Apple Pay Further Erodes MNO Opportunity
  • 7.5 Assessing the Mobile Money Opportunity
    • Figure & Table 7.2: MNO Mobile Money Revenue Opportunity ($m) Split by Banking, Transfers & Remittances, NFC & Carrier Billing 2014-2018

8. New Revenue Streams: M2M & Connectivity

  • 8.1 Defining Mobile M2M
    • Figure 8.1: The Player Value Chain
  • 8.2 M2M Revenue Models
    • Figure 8.2: M2M Revenue Models
    • 8.2.1 MNO M2M Drivers
    • i. Applications Beginning to Require Higher Bandwidth
    • 8.2.2 White Space Spectrum to offer new Possibilities
  • 8.3 MNO Opportunities in the Connected Car Space
    • Figure 8.3: Selected MNO Connected Car Initiatives
  • 8.4 MNO Opportunities in the Smart Home Space
    • 8.4.1 Strategic Opportunities for MNOs
      • i. The Road-Runner Problem: Collaboration is the Solution
      • ii. Case Study: AT&T - Dumb Pipe to Smart Pipe
      • iii. Subscription: the Optimal Smart Home Business Model for MNOs?
  • 8.5 Sizing the MNO M2M Opportunity
    • Figure & Table 8.4: Operator M2M Opportunity: Annual Connectivity & Enablement Revenues 2013-2018

9. Adaptive Strategies: Taking the Network Strain

  • 9.1 Introduction
  • 9.2 Assessing the Scale of the Challenge: Offload Solutions
    • 9.2.1 Established Offload Solutions: Wi-Fi & Small Cells
    • Figure & Table 9.1: Data Traffic (PB/Annum) Generated by Smartphones, Featurephones & Tablets, 2013-2017
      • i. Wi-Fi
      • ii. Small Cells and Femtocells
  • 9.3 Network Optimisation
    • 9.3.1 New Opportunies: NFV
    • Figure 9.2: ETSI Vision for NFV
  • 9.4 Addressing Base Station Opex
    • 9.4.1 Addressing Site Lease Costs - Network Sharing
      • i. Active and Passive RAN sharing
    • Figure 9.3: Active vs Passive RAN Sharing Infrastructure Models
    • 9.4.2 Improving the Efficiencies in the Base Station
  • 9.5 Greening the Network: Reducing Opex & Meeting Sustainability Commitments
    • 9.5.1 China Mobile: Analysis.
    • Figure & Table 9.4: China Mobile, Base Stations Powered by Sustainable Energy 2008-2013
    • Figure & Table 9.5: Base Line Analysis of China Mobile Subscriber Growth vs CO2 Emissions and Energy Usage, 2007-2013
    • 9.5.2 Transitioning to Green Networks: the Environmental & Financial Imperative
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