Post on 30-Apr-2020
Governing the Mobile Broadband Ecosystem
Johannes M. BauerKorea Association for Telecommunications Policy
20th Anniversary Global WorkshopHonolulu, Hawaii, June 27, 2014
Background and motivation
• Policy makers worldwide are experimenting with measures intended to boost the benefits of mobile broadband
• Regulatory theory and practice use simplifying assumptions that deviate in many ways from the workings of advanced communication systems
• Requires understanding of the conditions under which the existing approaches are acceptable and when alternative approaches are needed
Overview
• An international comparison of selected mobile broadband performance metrics
• Re‐conceptualizing governance in highly interrelated systems
• Implications for policy research and practice• Recap of main points
Comparative performance
Mobile broadband players
Mobile networks
Network equipment
DevicesDevelopment platforms,operating systems
Voice, data, messaging services
Componentmanufacturers
Towers,spectrum
Applications, content, mobile commerce
Devices U
sersAd
vertise
rs
Governance (voluntary, mandated, spontaneous)
Governance (voluntary, mandated, spontaneous)
External enviro
nment External environm
ent
Performance (mobile broadband adoption, infrastructure quality, innovation rate, prices, overall economic and societal impact
Fixed networks
Global mobile traffic
Source: Akamai, 2014
Peak mobile Internet traffic(1H 2014)
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
North America Europe Asia Pacific Latin America Africa
Outside top 5
Webbrowsing
Communications
Social networking
Tunneling
Marketplaces
Real‐time entertainment
Source: Sandvine, 2014
Wireless broadband subscriptions(in 106, as of June 2013)
Source: OECD Broadband Portal, 2014
Wireless broadband adoption(per 100 inhabitants, as of June 2013)
0
20
40
60
80
100
120OECD wireless broadband subscriptions per 100 inhabitants, by technology
Dedicated mobile data subscriptions
Standard mobile broadbandsubscriptionsTerrestrial fixed wireless
Source: OECD Broadband Portal, 2014
Network quality(average and peak download speeds, mbps)
8.5 7 5.9 8.9 7.9 7.8 5.4 4.7 4.1 3.9 1.8 1.7
16.1 15.2
27.7
55.5
37.528.9
135.6
28.6
111.2
19.7 19.513.1
Average Peak
Source: Akamai, 2014
North America
Europe, Middle East, Africa Asia Pacific
Caribbean, Latin America
Source: Akamai, 2014
Mobile penalty(average page download time in milliseconds)
0
2000
4000
6000
8000
10000
12000
14000
millisecon
ds
Broadband
Mobile
Source: Akamai, 2014
Heterogeneity and divergence
0
1
2
3
4
5
6
7
8
9
0.0 20.0 40.0 60.0 80.0 100.0 120.0
Average mob
ile dow
nloa
d speed
Mobile broadband adoption per 100 inhabitants
Own calculation, based on OECD (2014), Akamai (2014)
r=0.38
Re‐conceptualizing governance in highly interrelated systems
An interrelated (eco)system
Network equipment
Componentmanufacturers
Towers,spectrum
Governance (voluntary, mandated, spontaneous)
Governance (voluntary, mandated, spontaneous)
External environment
Performance (mobile broadband adoption, infrastructure quality, innovation rate, prices, overall economic and societal impact
Development platforms,operating systems
Voice, data, messaging services
Applications, content, mobile commerce
Users
Advertise
rs
External enviro
nment
Devices
Fixed networks
Devices
Mobile networks
Rationales for governance• Market power and dominance
– Bottlenecks in the system (e.g., local access)– Horizontal market concentration– Vertical integration across layers of some players
• Coordination requirements– Numbering (e.g., Domain Names)– Interoperability (e.g., standards, roaming)
• Externalities and public good effects– Overall innovation dynamics of the system– Economic effects on communities– Instability and volatility of the sector (e.g., security, reliability of equipment supply)
– Quality of infrastructure platforms
Governance instruments
Networks
Network equipment
DevicesDevelopment platforms,operating systems
Voice, data, messaging services
Componentmanufacturers
Towers,spectrum
Applications, content, mobile commerce
Devices U
sersAd
vertise
rs
Governance (voluntary, mandated, spontaneous)
Governance (voluntary, mandated, spontaneous)
External enviro
nment External environm
ent
Performance (mobile broadband adoption, infrastructure quality, innovation rate, prices, overall economic and societal impact
Spectrum policy
Standards
R&D policy
Open data Net neutrality
Universal service
Access to content
Roaming, MVNOs
E‐government
Public procurement
ROW policy
Governance challenges (Bauer, 2014)#1: Pervasive interdependencies
– Policy and regulation lead to adjustments of directly and indirectly affected players
#2: Policies work as constellations– Policy instruments rarely act as single, additive factors;
rather they work as constellations that need to be aligned with national and sector conditions
#3: Direct and indirect costs of regulation– More differentiated types of intervention are typically
associated with higher direct and indirect costs#4: Technology, economics and policy co‐evolve
– Dynamic adjustments by players seek to increase “fitness” relative to legal and regulatory framework (but not necessarily toward higher welfare)
Challenge 1: interdependencies• Highly interrelated system even though not all segments are connected equally – Convergence and platform mobility– Prevalence of two‐ and multi‐sided markets– New forms of competition (e.g., WhatsApp, KakaoTalk)
• Implications for regulatory theory and practice– Interventions percolate through system– Policy has direct and multiple indirect effects – Limited theoretical and empirical foundations
• Unanticipated positive and negative effects will regularly occur, require continuous adaptation
The case of wireless net neutrality• Spectrum of governance options from “strict” to “weak” to “no” neutrality rules
• Effects of various policy options on innovation performance highly contested among stakeholders
• Research findings contingent on modeling assumptions– Gans (2014), Choi (2010) find positive effects of strict neutrality on network investment and app innovation
– Majority of researchers find negative effects of strict neutrality on network investment and positive effects on app innovation (e.g., Krämer et al. 2013)
– Bauer (2014) clarifies that effects differ depending on type of innovation and argues for an intermediate approach
–
Modeling systemic relations
Strict net neutrality
Innovation incentives for app developers
Innovation incentives for
network operators
+
Overall innovation performance
+
+
+
Overall effect contingent on relative strength of relations, can be (+) or (–)
20
+
Innovation scenarios• Differences between innovation types recognized in
industrial organization research (e.g., Malerba and Orsenigo, 1996; Aghion et al., 2005)
• Modular innovation– Coordination between relevant players can be achieved via
interfaces (e.g., app economy)– Standardized access to network and logical platforms expands
set of profitable innovations– Stricter net neutrality facilitates modular innovation
• Coupled innovation– Coordination between relevant players requires knowledge
sharing, large‐scale coordination– Facilitated by temporary exclusivity and barriers to entry– Stricter net neutrality stifles coupled innovation
–
Scenario 1: stronger positive feedbacks
Strict net neutrality
Innovation incentives for app developers
Innovation incentives for
network operators
+
Overall innovation performance
+
+
+
Overall effect (+)
22
+
–
Scenario 2: stronger negative feedbacks
Strict net neutrality
Innovation incentives for app developers
Innovation incentives for
network operators
+
Overall innovation performance
+
+
+
Overall effect (–)
23
+
24
Tuning the system to optimal performance
Investment-, Innovation-incentives
Strict neutrality
No neutrality
NL N* NU
Challenge 2: policy constellations• Institutional economics suggests that policy does not effect performance in an additive fashion (as often tacitly assumed)
• Rather, policy variables affect outcomes as “constellations”, that is in combination with other policy and contextual factors
• Therefore, policy makers need to get the set of relevant factors right rather than just specific instruments
• Consistency seems to be more important than the specific course of action (Finger et al., 2005)
Complex patterns of causation
26
O
F4
I2
I1
F1
O
F4
F … explanatory factors, I … policy instruments, O … outcome
Sufficientconditions
Necessary condition
F5
Jointly sufficientcondition
Jointly necessary condition
I2
F1
I1
The case of platform access• Dependence on contextual factors
– Belloc et al. (2012) show that no best practice model applies across all OECD countries
– Rather, best policy contingent on national (and probably local) conditions
• Importance of appropriate policy constellation– Bauer et al. (2013) examine determinants of infrastructure
quality– Effects of unbundling policy can be positive or negative,
depending on context• Tsai and Bauer (2014)
– Use Qualitative Comparative Analysis (QCA) to systematically examine interactions among policy variables
– Detect varying interaction patterns among universal service, LLU, competition policy
Restating the policy problem• Existence of an effective policy
– Does a stable relation exist between a single instrument (a constellation of instruments) and performance given the working of the mobile broadband system?
• Feasibility of an intervention– Do policy makers have a sufficient control span over necessary and sufficient conditions to design and implement successful interventions?
• Anticipated net benefits– Taking into account all direct and indirect effects, do the expected benefits exceed the expected costs?
Implications for policy research and practice
Implications for theory• Choice of appropriate modeling approach
– Most of current regulatory theory is based on static equilibrium models
– Not necessarily wrong but only holds if an acceptable approximation
– Dynamic modeling framework needed if not• Attention to interdependencies
– Current models are only appropriate if these interdependencies are weak
– If not, need to adopt theoretical and empirical models that allow taking them into account
– Expand use of Qualitative Comparative Analysis (QCA, e.g., Ragin, 2000) and computational models (e.g., agent‐based, system dynamic, e.g., Sterman, 2000)
Implications for practice• Explicit consideration of actual and potential costs of
regulation– Need to go beyond assumptions of omniscient, omnipotent and
benevolent policy makers– Build on early efforts to develop a generalized political economy
of regulation– Endogenize feasibility conditions into policy research and
practice• Toward more adaptive regulation
– Need to examine the co‐evolutionary dynamic of the system– Ask different questions (e.g., what might the unanticipated
consequences be?)– Continuous monitoring to fine‐tune regulation ex post based on
outcomes, possibly based on ex ante enforcement framework (Yoo 2012)
Recap of main points
Take away• Mobile broadband (like advanced communications in general) is a highly interrelated system of players
• Research and policy often fall short of taking these interrelations explicitly into account
• Stronger reliance on dynamic economic approaches and systemic models can help overcome theory deficits
• Consideration of direct and indirect costs of regulation as well as attention to co‐evolutionary trajectory of system can help improve practice
• Nations can learn from each other but need to calibrate policy to their specific goals and conditions
References• Aghion, P., N. Bloom, R. Blundell, R.Griffith, R. and P. Howitt (2005), ‘Competition
and innovation: An inverted‐U relationship’, Quarterly Journal of Economics, 120, 701‐728.
• Bauer, J.M. (2014), ‘Platforms, systems competition, and innovation: reassessing the foundations of communications policy’, Telecommunications Policy, 38.
• Bauer, J. M., Y. Schneider and P. Zenhäusern (2013). ‘Impact of sector‐specific regulation on ICT infrastructure quality’, paper presented at the 24th European Regional Conference of the International Telecommunication Society (ITS), Florence, Italy, October 23‐25, 2013.
• Belloc, F., A. Nicita and M.A. Rossi (2012), ‘Whither policy design for broadband penetration? Evidence from 30 OECD countries’, Telecommunications Policy, 36(5), 382‐398.
• Choi, J.P. and B.‐C. Kim (2010), ‘Net Neutrality and Investment Incentives’, RAND Journal of Economics, 41(3), 446‐471.
• Finger, M., J. Groenewegen and R. Künneke (2005), ‘The quest for coherence between institutions and technologies in infrastructures’, Journal of Network Industries, 6(4), 227‐259.
• Gans, J.S. (2014), ‘Weak versus strong net neutrality’, NBER Working Paper 20160, May 2014.
References …• Krämer, J., L. Wiewiorra and C. Weinhardt (2013), ‘Net neutrality: A progress
report’, Telecommunications Policy, 37(9), 794‐813. • Malerba, F. and L. Orsenigo (1996), ‘Schumpeterian patterns of innovation are
technology‐specific’, Research Policy, 25(3), 451‐478.• Ragin, C.C. (2000), Fuzzy‐set Social Science. Chicago, IL: University of Chicago Press.• Sterman, J.D. (2000), Business Dynamics: Systems Thinking and Modeling for a
Complex World. Boston, MA: McGraw‐Hill.• Tsai, H.‐Y.S. and J.M. Bauer (2014), Effects of public policy on the quality of
broadband services: A comparative analysis of Internet download speeds, paper presented at the Conference of the International Communications Association, Seattle, WA, May 23‐26, 2014.
• Yoo, C.S. (2012), The Dynamic Internet: How Technology, Users, and Businesses are Transforming the Network. Washington, D.C.: AEI Press.
Contact
Johannes M. BauerProfessor and Chairperson
Department of Media and InformationMichigan State University, USA
Email: bauerj@msu.eduWeb: www.msu.edu/~bauerj
Twitter: @jm_bauer