Global information technology report 2016 wef

Insight Report
The Global Information
Technology Report 2016
Innovating in the Digital Economy
Silja Baller, Soumitra Dutta, and Bruno Lanvin, editors

Insight Report
The Global Information
Technology Report 2016
Innovating in the Digital Economy
Silja Baller, World Economic Forum
Soumitra Dutta, Cornell University
Bruno Lanvin, INSEAD
Editors

The Global Information Technology Report 2016 is
a special project within the framework of the World
Economic Forum’s Global Competitiveness and Risks
Team and the Industry Partnership Programme for
Information and Communication Technologies. It is the
result of collaboration between the World Economic
Forum and INSEAD.
Visit The Global Information Technology Report page
at www.weforum.org/gitr.
World Economic Forum
Geneva
Copyright © 2016
by the World Economic Forum and INSEAD
All rights reserved.
All rights reserved. No part of this publication may be
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of the World Economic Forum.
ISBN: 978-1-944835-03-3
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The Global Information Technology Report 2016 | iii
Contents
Preface v
Richard Samans and Margareta Drzeniek Hanouz (World Economic Forum)
Acknowledgments vii
Alan Marcus (World Economic Forum)
Foreword ix
Chuck Robbins (Cisco Systems)
Executive Summary xi
Silja Baller (World Economic Forum), Soumitra Dutta (Cornell University),
and Bruno Lanvin (INSEAD)
Part 1: Innovating in the Digital Economy 1
1.1 The Networked Readiness Index 2016 3
Silja Baller and Attilio Di Battista (World Economic Forum),
Soumitra Dutta (Cornell University), and Bruno Lanvin (INSEAD)
Appendix: The Networked Readiness Index framework: 33
A methodological note
1.2 Cross-Border Data Flows, Digital Innovation, 39
and Economic Growth
Robert Pepper, John Garrity, and Connie LaSalle (Cisco Systems)
Part 2: Data Presentation 49
2.1 Country/Economy Profiles 51
How to Read the Country/Economy Profiles.........................................................................53
Index of Countries/Economies..............................................................................................55
Country/Economy Profiles.....................................................................................................56
2.2 Data Tables 195
How to Read the Data Tables.............................................................................................197
Index of Data Tables...........................................................................................................199
Data Tables.........................................................................................................................201
2.3 Technical Notes and Sources 269
About the Authors 279
Partner Institutes 281
Strategic Partner Acknowledgment 289

The Global Information Technology Report 2016 | v
As the 2016 edition of The Global Information
Technology Report is released, the world is entering the
Fourth Industrial Revolution. Processing and storage
capacities are rising exponentially, and knowledge is
becoming accessible to more people than ever before
in human history. The future holds an even higher
potential for human development as the full effects of
new technologies such as the Internet of Things, artificial
intelligence, 3-D Printing, energy storage, and quantum
computing unfold.
The exponential speed of developments; disruption
across all major industries; and the impact on entire
systems of production, management, and governance
are what differentiates these developments from
previous “industrial revolutions.” However, while all
these developments will bring many benefits, they also
carry risks. If managed well, they have the potential to
give rise to innovation that will drive growth and social
impact. If not handled appropriately, challenges such
as the rising threat of cyberattacks that expand into the
physical world, privacy issues, and the polarizing effects
of technologies on labor markets could derail these
benefits. Countries and businesses that embrace these
developments, anticipate challenges, and deal with them
in a strategic way are more likely to prosper, while those
that do not will more likely fall behind.
Information and communication technologies
(ICTs) are the backbone of this revolution. The future of
countries, businesses, and individuals will depend more
than ever on whether they embrace digital technologies.
And many of those who stand to gain the most are not
yet connected.
Since 2001, The Global Information Technology
Report series published by the World Economic Forum
in partnership with INSEAD and Cornell University has
measured the drivers of the ICT revolution globally,
using the Networked Readiness Index (NRI). The Index
has evolved over time and currently assesses the state
of networked readiness using 53 individual indicators.
For each of the 139 economies covered, it allows the
identification of areas of priority to more fully leverage
ICTs for socioeconomic development.
Four important messages emerge from the Report
this year. First, innovation is increasingly based on digital
technologies and business models, which can drive
economic and social gains from ICTs if channelled in a
smart way. Second, the way businesses adopt ICTs is
key for leveraging them for development, so encouraging
businesses to fully embrace the powers of digital
technologies should be a priority of governments. Third,
both the private sector and governments need to step
up efforts to invest in innovative digital solutions to drive
social impact. Last but not least, a sustainable digital
economy will depend on quickly evolving governance
frameworks that allow societies to anticipate and shape
the impact of emerging technologies and react quickly to
changing circumstances.
Against this background, the Report is meant to
be a call for action. Policymakers must work with other
stakeholders to swiftly adopt holistic long-term strategies
for ICT development and lead in adapting governance
and leadership behaviors to ensure that ICTs deliver
maximum benefits. Under the theme “Innovating in the
Digital Economy,” The Global Information Technology
Report 2016 highlights striking innovation patterns in
the NRI data that can help point the way for policy and
investment priorities.
As the digital economy is developing exponentially,
its measurement must evolve as well. Chapter 1.1
therefore includes an outlook for potential next steps for
the NRI that can serve as a starting point for discussing
the evolving concepts and measurements of networked
readiness. In the course of the coming year, we plan
to identify key questions concerning the drivers and
implications of the emerging Fourth Industrial Revolution
and develop relevant concepts and measures with
experts, policymakers, and businesses to be included in
the updated next edition of the NRI.
The Report is part of the World Economic Forum’s
wider efforts to address digital technology questions
through its System Initiative on the Digital Economy and
Society. The aim of this initiative is to help shape the
Internet as a true and open platform and as a driver of
economic development and social progress. We hope
that through this Report and its system initiatives the
World Economic Forum can contribute to making the ICT
revolution truly global, growth-supportive, and inclusive.
Preface
RICHARD SAMANS, Member of the Managing Board, World Economic Forum
MARGARETA DRZENIEK HANOUZ, World Economic Forum

The Global Information Technology Report 2016 | vii
Over the past 16 years, the World Economic Forum,
INSEAD, and, more recently, Cornell University have
partnered on publishing The Global Information
Technology Report (GITR), which examines the
increasing proliferation of technology and its effects
on advancing global prosperity. Today we have come
to a critical tipping point, where the ICT-fueled digital
economy is taking off in an exponential way. We have
also come to recognize the beginning of a Fourth
Industrial Revolution, which will fundamentally change
the way we live, work, and relate to one another.
This transformation is not defined by any particular
set of technologies, but rather by a transition to new
ecosystems built on the infrastructure of the digital
revolution. The World Economic Forum is seeking to
shape and design these new systems by emphasizing
and scaling cross-sector and cross-geographic
collaborations. The key findings of this Report over the
years led to and informed a broad range of discussions
around the Forum’s Future of Digital Economy and
Society system, such as digital inclusion and access,
cybercrime and cybersecurity, data privacy and usage,
digital transformation of business, digital governance,
and trade across borders.
Under the theme “Innovating in the Digital Economy,”
this year’s Report looks into how digital technologies are
changing the nature of innovation in various ways. The
Report examines the exponential shift brought about by
digital technologies, the way we measure the impact of
innovation, the continuous pressure for both tech and
non-tech sectors to boost innovation through digital
means, and the need for agile governance and regulation
systems to adapt to the speed and scale of changes
while mitigating ethical, legal, and regulatory risks.
Each year, the ICT Industries and the Global
Competitiveness and Risks Teams at the World
Economic Forum collaborate on the annual production
of the GITR; the Report has evolved to become one
of the most respected publications of its kind. As we
shift toward a systems approach to solve the most
challenging issues stemming from the Fourth Industrial
Revolution, this Report will continue its evolution to
capture milestones in unleashing the full potential of the
digital economy led by ICTs, and to inform decision-
making processes for policymakers and organizations
across sectors and regions.
We would like to acknowledge the editors of the
Report, Silja Baller at the World Economic Forum;
Professor Soumitra Dutta, Dean of the College of
Business at Cornell University; and Bruno Lanvin at
INSEAD. The World Economic Forum and INSEAD and,
more recently, Cornell University have been publishing
the GITR since 2001; through this longstanding
partnership, the three institutions have developed and
evolved the Networked Readiness Index (NRI) to reflect
the growing importance of technology and innovation
across the world.
A special thanks also goes out to our Report
partner, Cisco, for its continuous support and
engagement in this year’s edition. We also wish to
convey our gratitude to Robert Pepper, John Garrity,
and Connie LaSalle at Cisco Systems for their unique
contributions, built upon the insights generated by the
NRI; their enhancement of its thematic elements; and
their contributions to the overall distinctiveness of the
Report.
We would like to extend our sincere thanks to
Professor Klaus Schwab, Chairman of the World
Economic Forum for his leadership. Appreciation
goes to the core project team: Silja Baller, Oliver
Cann, Attilio Di Battista, Danil Kerimi, and Roger Yong
Zhang. We also wish to acknowledge the leadership
of Richard Samans, Member of the Managing Board,
as well as Jennifer Blanke, Chief Economist, and the
contributions of members of the Global Competitiveness
and Risks Team: Ciara Browne, Roberto Crotti, Gaëlle
Marti, Margareta Drzeniek Hanouz, Caroline Galvan,
Daniel Gomez Gaviria, Thierry Geiger, and Stéphanie
Verin. Appreciation also goes to the members of the
Information and Communication Technology Industries
Team, under the leadership of Cheryl Martin, Head of
Centre for Global Industries, and Murat Sönmez, Chief
Business Officer: David Connolly, Aurelie Corre, Daniel
Dobrygowski, Mara Kelly, Peter Lyons, Isabelle Mauro,
Derek O’Halloran, and Adam Sherman.
Last but not least, we would like to express our
gratitude to our 160 Partner Institutes around the world
and to all the business executives who completed our
Executive Opinion Survey.
Acknowledgments
ALAN MARCUS
World Economic Forum

The Global Information Technology Report 2016 | ix
Foreword
CHUCK ROBBINS
Chief Executive Officer, Cisco Systems
In my 18 years at Cisco, I have seen first-hand how
technology can transform industries and lives. As the
role of hardware, software, and services becomes
even more important for governments, businesses, and
individuals, the high-speed broadband Internet Protocol
(IP) networks that enable them have become integral
to daily life. In fact, by 2020, there will be over 26 billion
Internet-connected devices and over 4 billion global
Internet users. Broadband Internet has been categorized
as one of the world’s most important general-purpose
technologies, with the capability to dramatically impact
social structures and entire economies.
Underpinning this development is data’s role as
the new currency. Every day, exabytes of new data are
created and transported over IP networks. In 2016 the
world has entered the “zettabyte era”: global IP traffic
will reach 1.1 zettabytes, or over 1 trillion gigabytes.
By 2020 global IP traffic will reach 2.3 zettabytes. This
data growth is fueling economies, sparking innovation,
and unleashing waves of creativity. This year’s Global
Information Technology Report highlights the role of
technology, and broadband in particular, in driving global
innovation.
But no innovation can occur without the network.
IP networks have the capacity to connect every person,
every country, and every IP-enabled device. Global
networks allow data to flow unimpeded, driving growth
and enabling collaborative innovation in many areas,
from production to processes. Those countries that are
adept at fostering digital activity will continue to see new
industries emerge, as well as experience the accelerated
development of traditional sectors.
The global Internet must therefore be allowed to
further develop without obstacles—this is essential in
order for everyone to benefit. Increasingly, barriers to
digital flows threaten to diminish the Internet’s potential
to drive positive social and economic impact. The open
exchange of information is a hallmark of the growing
knowledge economy. All stakeholders—including
governments, businesses, the technical community,
citizens, and consumers—play a role in building trust
and confidence in global networks. Privacy and security
should be integrated into technological design from the
outset; strategies to protect and maintain the integrity of
data must account for an array of diverse and emerging
risks; and policy should enable innovation and global
data flows while safeguarding against those who seek to
cause damage.
Getting the balance right requires active,
collaborative participation from everyone. At Cisco, we
are committed to helping drive the next wave of global
growth, productivity, and innovation.

The Global Information Technology Report 2016 | xi
Executive Summary
SILJA BALLER, World Economic Forum
SOUMITRA DUTTA, Cornell University
BRUNO LANVIN, INSEAD
Part 1 of the 2016 edition of The Global Information
Technology Report assesses the state of networked
readiness of 139 economies using the Networked
Readiness Index (NRI) (Chapter 1.1) and, under the
theme “Innovating in the Digital Economy,” examines
the role of information and communication technologies
(ICTs) in driving innovation (Chapters 1.1 and 1.2). Part
2 consists of an extensive data compendium with the
detailed performance of each economy in the NRI
(Section 2.1) and rankings for each of the 53 individual
indicators included in the NRI (Section 2.2).
PART 1: INNOVATING IN THE DIGITAL ECONOMY
We are at the dawn of the Fourth Industrial Revolution,
which represents a transition to a new set of systems,
bringing together digital, biological, and physical
technologies in new and powerful combinations. These
new systems are being built on the infrastructure of the
digital revolution. The Global Information Technology
Report 2016 features the latest iteration of the NRI,
which assesses countries’ preparedness to reap the
benefits of emerging technologies and to capitalize
on the opportunities presented by the digital revolution
and beyond.
The Networked Readiness Index 2016
Chapter 1.1 presents the results of the NRI 2016, which
measures the capacity of countries to leverage ICTs
for increased competitiveness and well-being. It also
considers innovation trends of recent years through the
lens of the NRI.
The networked readiness framework
The networked readiness framework rests on six
principles: (1) a high-quality regulatory and business
environment is critical in order to fully leverage ICTs and
generate impact; (2) ICT readiness—as measured by ICT
affordability, skills, and infrastructure—is a pre-condition
to generating impact; (3) fully leveraging ICTs requires
a society-wide effort: the government, the business
sector, and the population at large each have a critical
role to play; (4) ICT use should not be an end in itself.
The impact that ICTs actually have on the economy and
society is what ultimately matters; (5) the set of drivers—
the environment, readiness, and usage—interact, co-
evolve, and reinforce each other to form a virtuous cycle;
and (6) the networked readiness framework should
provide clear policy guidance.
The framework translates into the NRI, a composite
indicator made up of four main categories (subindexes),
10 subcategories (pillars), and 53 individual indicators
distributed across the different pillars:
A. Environment subindex
1. Political and regulatory environment (9 indicators)
2. Business and innovation environment (9 indicators)
B. Readiness subindex
3. Infrastructure (4 indicators)
4. Affordability (3 indicators)
5. Skills (4 indicators)
C. Usage subindex
6. Individual usage (7 indicators)
7. Business usage (6 indicators)
8. Government usage (3 indicators)
D. Impact subindex
9. Economic impacts (4 indicators)
10. Social impacts (4 indicators)
The computation of the overall NRI score is based
on successive aggregations of scores: individual
indicators are aggregated to obtain pillar scores, which
are then combined to obtain subindex scores. Subindex
scores are in turn combined to produce a country’s
overall NRI score. The appendix of Chapter 1.1 presents
the detailed methodology and composition of the NRI.
About half of the individual indicators used in the
NRI are sourced from international organizations. The
main providers are the International Telecommunication
Union, UNESCO and other UN agencies, and the World
Bank. The other half of the NRI indicators are derived
from the World Economic Forum’s Executive Opinion
Survey (the Survey). The Survey is used to measure
concepts that are qualitative in nature or for which
internationally comparable statistics are not available for
enough countries. The 2015 edition of the Survey was
completed by over 14,000 business executives in more
than 140 countries.

xii | The Global Information Technology Report 2016
Executive Summary
Key Findings
Under the theme “Innovating in the Digital Economy,” The
Global Information Technology Report 2016 highlights
the ways in which the digital revolution is changing both
the nature of innovation and the rising pressure for firms
to innovate continuously. The analysis yields four key
findings:
Key Finding 1: The digital revolution changes the
nature of innovation. One of the key characteristics of
the digital revolution is that it is nurtured by a different
type of innovation, increasingly based on digital
technologies and on the new business models it allows.
In addition to making traditional research tools more
powerful, it allows for new and near-costless types of
innovation that require little or no R&D effort. Examples
include the digitization of existing products and
processes, distributed manufacturing, blockchains, and
advertising-based “free services” as well as the prospect
of more “uberized” activities in multiple sectors, including
transport, banking, entertainment, and education.
The NRI data show that the minds of business
executives around the world are increasingly focused
on innovation, as reflected by the steady upward trend
in firms’ perceived capacity to innovate. Traditional
measures for innovation, such as the number of patents
registered, are picking up only part of the story. Instead,
new types of innovation, such as business-model
innovation, look set to become an important part of the
innovation story: executives in almost 100 countries
report increases in the perceived impact of ICTs on
business-model innovation compared with last year.
Key Finding 2: Firms will face increasing pressure
to innovate continuously. Seven countries stand out in
terms of economic and digital innovation impact: Finland,
Switzerland, Sweden, Israel, Singapore, the Netherlands,
and the United States. Considering the different
elements of networked readiness for these seven
countries, it is noticeable that all seven are characterized
by very high levels of business ICT adoption. This
technology-enabled innovation in turn unleashes new
competitive pressures that call for yet more innovation by
tech and non-tech firms alike.
Because digital technologies are driving winner-
take-all dynamics for an increasing number of industries,
getting there first matters. However, although firms
feel that overall capacity to innovate has increased, a
stagnating rate of ICT adoption and usage by existing
firms across all regions suggests that a large number of
firms are not getting into the game fast enough.
Key Finding 3: Businesses and governments are
missing out on a rapidly growing digital population.
In recent years, digital innovation has been primarily
driven by consumer demand. Yet this increasing
demand for digital products and services by a global
consumer base is largely being met by a relatively small
number of companies. Businesses need to act now
and adopt digital technologies to capture their part of
this growing market. A widening and worrying gap is
also emerging between growth in individual ICT usage
and public-sector engagement in the digital economy,
as government usage is increasingly falling short of
expectations. Governments can do more to invest in
innovative digital solutions to drive social impact.
Key Finding 4: A new economy is shaping, requiring
urgent innovations in governance and regulation.
As the new digital economy is taking shape, offering
it the right framework conditions will be crucial to
ensuring its sustainability. Digital technologies are
unleashing new economic and social dynamics that
will need to be managed if the digital transformation of
industries and societies are to deliver long-term and
broad-based gains. A resilient digital economy also
calls for new types of leadership, governance, and
behaviors. A critical ingredient for the success and
sustainability of the emerging system will be agile
governance frameworks that allow societies to anticipate
and shape the impact of emerging technologies and
react quickly to changing circumstances.
Networked Readiness Index 2016: Results overview
Chapter 1.1 then reports the rankings of the overall NRI
2016, its four subindexes, and their respective pillars.
The composition of the group of top 10 performers
is unchanged from last year. The group consists of a mix
of high-income Southeast Asian (Singapore and Japan)
and European countries (Finland, Sweden, Norway, the
Netherlands, Switzerland, the United Kingdom, and
Luxembourg) as well as the United States. Networked
readiness therefore remains highly correlated with per
capita income.
Europe remains at the technology frontier with
seven out of the top 10 NRI countries being European.
Yet the performance range is wide, with Greece
dropping four places to 70th position and Bosnia and
Herzegovina closing the group at 97. Several Eastern
European countries—notably the Slovak Republic,
Poland, and the Czech Republic—are making big strides,
landing spots in the top 50 of the NRI; better affordability
and large improvements in economic and social impacts
are contributing to this success in these three countries
in a major way. Italy is another notable mover this year,
improving 10 places to reach 45th position as economic
and social impacts of ICTs are starting to be realized (up
18 in the global impact rankings).
The Eurasia region continues its upward trajectory,
with the average NRI score for the region increasing
significantly since 2012. In particular, it is notable that
the improvement is observed across all four elements
that make up the Index: Environment, Readiness, Usage,
and Impact. The region is led by Kazakhstan, which

The Global Information Technology Report 2016 | xiii
Executive Summary
continues on its positive trajectory of recent years to land
in 39th position this year.
Leading the Emerging and Developing Asian
economies in 2016 is Malaysia, which continues to
perform strongly and moves up one spot to 31st position
overall; this performance is supported by a government
that is fully committed to the digital agenda. The top five
in the region in terms of overall ICT readiness remain
China, Malaysia, Mongolia, Sri Lanka, and Thailand, as
in 2015. The group of Emerging and Developing Asian
countries has been both moving up and converging
since 2012. Individual usage in the region is still one of
the lowest in the world, but has been growing strongly in
recent years.
The performance range of countries in the Latin
America and Caribbean region remains widely
dispersed with almost 100 places between Chile (38th)
and Haiti (137th). There was no clear trend from 2015
to 2016 in terms of relative performance, with Chile and
Haiti staying put; of the remaining group, half of the
countries improve their ranking and the other half drop.
Considering the absolute NRI score, however, the region
has been moving up and converging since 2012. In order
to foster the innovation forces that are key for thriving in
the digitized world and the emerging Fourth Industrial
Revolution, many governments in the region will urgently
need to reinforce efforts to improve the regulatory and
innovation environment in their countries.
The UAE (26th) and Qatar (27th) continue to lead the
Arab world when it comes to networked readiness. The
MENAP region (Middle East, North Africa, and Pakistan)
is home to two of the biggest movers in this year’s
rankings: Kuwait (61st, up 11) and Lebanon (88th, also
up 11). In both cases, individuals are leading the charge
with the business sector catching up and strongly
contributing to the successful performance. Although
governments are lagging behind in terms of digital
adoption (81st in Kuwait, 124th in Lebanon), the business
community in both countries is registering an increased
weight on ICTs in government vision and efforts to
improve the regulatory environment.
This year’s NRI also sees several sub-Saharan
African countries among the top upward movers,
including South Africa (65th, up 10), Ethiopia (120th,
up 10), and Côte d’Ivoire (106th, up 9). Leadership
in terms of digital adoption is coming from different
groups of stakeholders. Although efforts are very much
government-driven in Ethiopia and Côte d’Ivoire, the
business sector is providing the most momentum in
South Africa. Going forward, the largest barriers to tackle
for Côte d’Ivoire will be infrastructure and affordability;
reversing the trend of a deteriorating business and
innovation environment for South Africa; and individual
usage and skills for Ethiopia.
Chapter 1.1 provides an overview of the
performance of the 10 best-performing countries in the
NRI 2016, a selection of economies that were among
the top movers as well as other selected economies,
including members of the G20 outside the top 10.
The Index maps a quickly evolving space and has
been adapted since its inception in 2001. Since the digital
economy is developing exponentially, its measurement
must be adapted to reflect the new realities on the
ground. A multi-stakeholder process will be put in place
to identify key questions concerning the drivers and
implications of the emerging Fourth Industrial Revolution
and to develop relevant concepts and measures with a
view to incorporating these findings into the next edition
of the NRI.
Cross-border data flows, digital innovation, and
economic growth
In Chapter 1.2, Robert Pepper, John Garrity, and Connie
LaSalle explore the impact of the free flow of data
across national borders on innovation and growth. The
authors highlight the development of cross-border data
traffic over Internet protocol, starting with the first email
messages in the early days of the Internet to today,
where over 3.2 billion people across the world have
access to and use the Internet.
The flow of digital communication between
countries, companies, and citizens has been recognized
for years as a critical driver of economic growth and
productivity. Countries adept at fostering digital activity
have witnessed the emergence of new industries as well
as the accelerated development of traditional sectors.
However, despite the intensive and extensive growth of
the global Internet, concerns over growing barriers to
digital flows are mounting.
The authors first review the literature on the impact
of cross-border data flows on countries, companies,
and individuals. The chapter then presents an original
analysis of the growth of new services built on the free
flow of trade through global digitization, and concludes
by discussing policy guidelines that mitigate concerns
over national data transmission while simultaneously
maximizing the benefits of cross-border data flows.
PART 2: DATA PRESENTATION
Part 2 of the Report contains individual scorecards
detailing the performance in the Networked Readiness
Index of each of the 139 economies (Section 2.1) and
tables reporting the global rankings for each of the 53
individual indicators composing the NRI (Section 2.2).

Part 1
Innovating in the
Digital Economy

The Global Information Technology Report 2016 | 3
CHAPTER 1.1
The Networked
Readiness Index 2016
SILJA BALLER, World Economic Forum
ATTILIO DI BATTISTA, World Economic Forum
SOUMITRA DUTTA, Cornell University
BRUNO LANVIN, INSEAD
We are at the dawn of the Fourth Industrial Revolution.
The Fourth Industrial Revolution represents a transition
to a new set of systems that bring together digital,
biological, and physical technologies in new and
powerful combinations (Box 1). Just as the digital
revolution was built on the heart of the second industrial
revolution—electricity, mass communication systems,
and modern manufacturing—the new systems that
mark the Fourth Industrial Revolution are being built
on the infrastructure of the third, digital revolution—the
availability of global, digital communications; low-cost
processing and high-density data storage; and an
increasingly connected population of active users of
digital technologies.
The Global Information Technology Report 2016
features the latest iteration of the Networked Readiness
Index (NRI), which represents a key tool in assessing
countries’ preparedness to reap the benefits of emerging
technologies and capitalize on the opportunities
presented by the digital transformation and beyond.
More particularly, the Report assesses the factors,
policies, and institutions that enable a country to fully
leverage information and communication technologies
(ICTs) for increased prosperity and crystallizes them into
a global ranking of networked readiness at the country
level in the form of the NRI.
Countries are assessed over four categories
of indicators: (1) the overall environment for technology
use and creation (political, regulatory, business, and
innovation); (2) networked readiness in terms of ICT
infrastructure, affordability, and skills; (3) technology
adoption/usage by the three groups of stakeholders
(government, the private sector, and private individuals);
and (4) the economic and social impact of the
new technologies. Whenever relevant, the Index
looks at what the different actors in society, both
private and public, can do to contribute to the country’s
networked readiness.
An important channel by which digital technologies
can contribute to increased prosperity is via their
impact on innovation. As the digital transformation
is gathering speed and looks ready to substantially
change the global industrial landscape, staying ahead
of the curve is becoming more and more important
for business survival. Under the theme “Innovating in
the Digital Economy” this chapter shines a spotlight
on recent innovation trends. It develops a taxonomy
of mechanisms for the innovation impact of digital
Acknowledgments: The authors are grateful to David Aikman, Marisol
Argueta, Jennifer Blanke, Oliver Cann, Sangeet Choudary, Nicholas
Davis, Miroslav Dusek, Mehran Gul, Sriram Gutta, Anastasia Kalinina,
Elsie Kanza, Danil Kerimi, Martina Larkin, Alan Marcus, Patrick McGee,
Viraj Mehta, Fulvia Montresor, Vanessa Moungar, Bernhard Petermeier,
Mel Rogers, Mark Spelman, Christoph Sprung, Lisa Ventura, Bruce
Weinelt, Eric White, Justin Wood, and Alex Wong as well as to the
Global Competitiveness and Risks Team—Ciara Browne, Roberto Crotti,
Margareta Drzeniek Hanouz, Caroline Galvan, Thierry Geiger, Daniel
Gomez Gaviria, Gaëlle Marti, and Stéphanie Verin—for valuable feedback
and discussions.

1.1: The Networked Readiness Index 2016
4 | The Global Information Technology Report 2016
technologies and draws on NRI data to characterize
current innovation dynamics.
One of the key characteristics of the digital era is
that it is nurtured by a new type of innovation. In addition
to making traditional research tools more powerful,
digital technology allows for near-costless types
of digital innovation by recombination that requires
little or no research and development (R&D) effort.1
Examples of this type of innovation include the
digitization of existing products and processes; new
business models, including platform businesses,
distributed manufacturing, blockchains, and
advertising-based “free services”; and innovation
processes such as crowd-sourcing. A key challenge
associated with analyzing this new characteristic of
innovation is the insufficiency of traditional measures
for innovation outcomes, such as patenting activity.
Indeed, the NRI data show diverging trends between
patenting activity and firms’ perceived capacity
to innovate, with the latter rising rapidly across
all regions.
A second observation regarding innovation in the
digital era is that technology unleashes new competitive
pressures—for example, by integrating markets—that
call for yet more innovation by tech and non-tech firms
alike. In addition, because new technologies are driving
winner-take-all dynamics for an increasing number of
industries, getting there first matters. Firms thus face
growing pressure to innovate continuously and scale
fast so as not to be displaced. Out of the 10 pillars that
constitute the NRI, a high rate of ICT adoption among
firms is the most common characteristic of countries
that obtain the greatest economic and innovation impact
from ICTs. The NRI data suggest that these conditions
are in place for only a handful of countries: a perceived
stagnating rate of ICT usage by existing firms across all
regions indicates that a large number of firms are not
getting in the game fast enough.
The forces and systems of the emerging Fourth
Industrial Revolution will need to be channeled and
designed in order to achieve broad-based gains. Finding
the right framework conditions in the form of competition
and employment policies will be vital. Because the
importance of network dynamics has grown significantly
with the platform economy, the emergence of lock-in
effects needs to be addressed in order to ensure a level
playing field. When it comes to the job market, digital
technologies are already disrupting existing career paths,
ousting entire sets of skills, and creating the need for
new ones. At the same time, platform technologies are
increasingly used to match workers with jobs, leading
to more and more freelance activity. Policy will need to
ensure that these developments are not accompanied
by a loss of social protection for workers. Education and
life-long learning will have key roles to play in the years
to come as even more fundamental changes are to be
expected in the Fourth Industrial Revolution.
The innovation spotlight concludes by pointing
out that the digital economy raises new challenges
in multiple arenas, not only in terms of economic
imperatives. It also calls for new types of leadership
and behaviors, as well as more flexible approaches to
governance. New innovation governance approaches,
such as the framework for Responsible Research and
Innovation (RRI),2
are highly relevant in this context and
are used to anticipate the long-term impacts of emerging
technologies.
The second section of this chapter turns to overall
global trends in networked readiness as well as regional
assessments. The chapter then presents this year’s
rankings and country-level highlights, including profiles of
the top 10 performers and the top countries moving up
in the Index.
The Index maps a quickly evolving space and
has been adapted since its inception in 2001. Since
the digital economy is developing exponentially, its
measurement must be modified to reflect the new
realities on the ground. This chapter therefore also
includes an outlook for potential next steps for the NRI
as a starting point for discussing the evolving concepts
and measurements of networked readiness. A multi-
stakeholder process will be put in place over the course
of next year to identify key questions concerning the
drivers and implications of the emerging Fourth Industrial
Revolution and to develop relevant concepts and
measures with a view to incorporating these findings into
the next edition of the NRI (see Box 2).
We are at the beginning of a global transformation that is
characterized by the convergence of digital, physical, and
biological technologies in ways that are changing both
the world around us and our very idea of what it means
to be human. The changes are historic in terms of their
size, speed, and scope. This transformation—the Fourth
Industrial Revolution—is not defined by any particular
set of emerging technologies themselves, but rather by
the transition to new systems that are being built on the
infrastructure of the digital revolution. As these individual
technologies become ubiquitous, they will fundamentally
alter the way we produce, consume, communicate, move,
generate energy, and interact with one another. And
given the new powers in genetic engineering and neuro-
technologies, they may directly impact who we are and
how we think and behave. The fundamental and global
nature of this revolution also poses new threats related
to the disruptions it may cause—affecting labor markets
and the future of work, income inequality, and geopolitical
security as well as social value systems and ethical
frameworks.
Adapted from Klaus Schwab, The Fourth Industrial Revolution, 2016.
Box 1: The Fourth Industrial Revolution

INNOVATION IN THE DIGITAL ECONOMY THROUGH
THE LENS OF THE NRI
This section begins with an overview of the networked
readiness framework and then considers two key
mechanisms by which digital technologies are affecting
innovation: the first mechanism is changing the nature
of innovation, whereas the second is driving a new
urgency to innovate. Next, four key findings that emerge
from the analysis of historical and this year’s NRI data
are presented.
The networked readiness framework
Launched by the World Economic Forum in 2001
and significantly extended in 2012, the NRI can help
to assess countries’ ability to capitalize on the digital
revolution and their preparedness to benefit from the
emerging Fourth Industrial Revolution. This chapter
uses the NRI to point out some striking patterns in
countries’ innovation performance. The Index aggregates
data from 53 indicators, organized on the basis of the
networked readiness framework (Figure 1). Networked
readiness rests on whether a country possesses the
drivers necessary for digital technologies to unleash their
potential, and on whether these technologies are actually
impacting the economy and society.
The drivers are grouped within four subindexes as
follows:
A. Environment subindex
1. Political and regulatory environment (9 indicators)
2. Business and innovation environment (9 indicators)
B. Readiness subindex
3. Infrastructure (4 indicators)
4. Affordability (3 indicators)
5. Skills (4 indicators)
C. Usage subindex
6. Individual usage (7 indicators)
7. Business usage (6 indicators)
8. Government usage (3 indicators)
Impact is measured as a separate subindex:
D. Impact subindex
9. Economic impacts (4 indicators)
10. Social impacts (4 indicators)
About half of the 53 individual indicators used in
the NRI are sourced from international organizations.
The main providers are the International
Telecommunication Union (ITU); the World Bank;
the United Nations Educational, Scientific and
Cultural Organization (UNESCO); and other UN
agencies. Carefully chosen alternative data sources,
including national sources, are used to fill data gaps
in certain cases. The other half of the NRI indicators
are derived from the World Economic Forum’s annual
Executive Opinion Survey (the Survey). The Survey
is used to measure concepts that are qualitative in
nature or for which internationally comparable
statistics are not available for enough countries.3
The 2016 iteration of the Index covers 139
economies, accounting for 98.1 percent of world GDP.
Angola, Barbados, Burkina Faso, Libya, Suriname,
Timor-Leste, and Yemen—all covered in the 2015
edition—have been excluded, in line with the country
coverage of The Global Competitiveness Report
2015–2016. Sierra Leone was also excluded, even
though Survey data do exist for that country, because
too many data points were missing for other indicators.
Benin, Bosnia and Herzegovina, Ecuador, and Liberia
have been reinstated this year. The appendix provides
a detailed description of the networked readiness
framework and its rationale, together with a complete
methodological note on the computation of the NRI.
Infrastructure
Affordability Skills
Individual
Environment
DRIVERS
Business Government
IMPACT
Economic
Social
Readiness Usage
Figure 1: Networked readiness framework

Digital technologies are changing innovation itself in
a qualitative way as well as amplifying the urgency to
innovate. Identified below are a direct mechanism, which
is changing the nature of innovation, and an indirect
effect, which drives a new urgency to innovate; the latter
applies to tech and non-tech firms alike.
The direct way in which digital technology
affects innovation is via an augmentation of existing
tools, products, processes, and business models by
embedding new technologies. This mechanism applies
along the entire value chain from design to marketing. In
addition to allowing firms to achieve marginal productivity
improvements (e.g., by digitizing existing products
How digital technology affects the nature and
urgency of innovation: Two mechanisms
This section shines a spotlight on the innovation
mechanisms brought into play by digital technologies
and subsequently shows consistent emerging patterns in
the NRI data.
The joint EU/OECD Oslo Manual defines innovation
as follows: 4
An innovation is the implementation of a new or
significantly improved product (good or service),
a new process, a new marketing method, or a
new organizational method in business practices,
workplace organization, or external relations.
The NRI, a critical tool for tracking access and impact
Since its inception in 2001, the NRI has proven critical as a
tool to identify gaps, to catalyze action, to structure policy
dialogue, and to track progress in ICT readiness over time.
The indicators that make up the NRI shine a light on two
major questions: (1) What level of ICT access and use is
reached within a country? (2) What is the impact of digital
technologies once there is access?
In order to ensure that the NRI remains relevant in
the fast-changing field of ICTs, adjustments to the Index in
the next edition are envisaged. To this end, the Forum will
convene relevant experts and put in place a rigorous multi-
stakeholder consultation to ensure that the Index continues
to build on the latest developments in terms of both data
and methodology.
Key questions going forward
In a next step, two sets of questions will require attention if
the digital revolution is to be shaped in a way that can bring
broad-based improvements in living standards, making our
societies more prosperous and inclusive.
First, there is a need to measure the impact of
technologies beyond productivity and innovation, ensuring
that the digital revolution is also socially beneficial and
sustainable. In assessing the impact of the unfolding digital
revolution, parts of the picture are currently missing. Ideally
more mechanisms would be captured by which new
technologies enable and empower people and to more
systematically keep track of distributional impact. What is
measured matters for the way trust in new technologies is
built and the way the emerging Fourth Industrial Revolution
can be shaped.
Second, new indicators could usefully be introduced
to better map various micro-factors of ICT readiness. For
example, although the supply side regarding the access
question can be measured (see infrastructure and coverage
data in the NRI), there are gaps in understanding of the
demand side. In particular, a good understanding of the
offline population in environments where digital infrastructure
is available is absent. Lack of relevant content, missing
platforms, and affordability or privacy concerns are potential
explanations for why individuals and businesses do not join
the online world even though the infrastructure is in place.
When it comes to measuring the availability of local content,
the World Economic Forum’s Global Agenda Council on
Media, Entertainment and Information (June 2016) has
recently provided suggestions for new indicators in this
respect. In a next step, systematic data sources for these
indicators will need to be identified. It may be possible to
capture some of these demand-side factors using either
survey data or possibly commercially collected data. In
order get a more accurate picture of the offline population,
household surveys will be a critical complement.
Ideally, and conditional on the availability of systematic
data, new indicators would also be introduced to anticipate
key aspects of the Fourth Industrial Revolution infrastructure
and systems.
Country-level measures of ICT readiness will need to be
complemented with contextualizing data at the local level.
The World Economic Forum is catalyzing data collection at
this level in regional partnerships under the umbrella of the
Internet for All initiative. Public-private partnerships are vital in
this context because data that are critical for public policy are
currently collected by private entities.
Unlocking new data sources
Digital technologies have opened the way to new types of
data. Given the high frequency, larger coverage, and greater
accuracy of such data, it will be important to integrate these
into the NRI to the largest extent possible. In order to do so,
progress will be essential on several fronts with regard to data
access and sharing: much of the new, critical data are being
collected by private entities and the location of these data is
not necessarily known. Once located, several questions will
still need to be solved with regard to data management and
sharing. Although data gathering is becoming ever cheaper,
data management and storage are not. Considerable legal
uncertainties still exist, in particular with regard to privacy
considerations and data ownership. Furthermore, the
business rationale for data sharing is not necessarily clear in
all cases. Finally, big data by itself is missing the local context;
thus localized data-gathering efforts continue to remain
important. It is worth noting that well-designed surveys are
currently still considered best practice for data gathering. Yet
as these bottlenecks are being resolved, it will be important
to include new data sources that are updated at higher than
annual frequency into the NRI data effort.
Box 2: Possible next steps for the Networked Readiness Index

or providing new ways of organizing the production
system), digital technologies are importantly changing
the nature of innovation itself. The large wave of rapid
and accelerating web-driven innovation can be explained
by a type of almost costless combinatorial innovation.
It relies on the fact that parts that are being combined
into new products are bits (protocols and languages)
rather than physical parts and components and thus
have no time-to-manufacture, no inventory issues, no
delivery problems, and can be shipped around the world
instantaneously.5
In particular, digital technologies are affecting
innovation directly in the following ways:
• R&D and basic research: New technologies
augment tools used in research and decrease costs
of previously unaffordable research activities. They
allow more accurate inference based on larger
amounts of data and enable more extensive long-
distance research collaboration, including crowd-
sourcing.
• Product and process innovation: Digital
technology makes possible new products and
services, and re-engineering production systems
give cost and quality advantages. Chapter 1.2 in this
Report provides extensive case study evidence for a
wide range of industries to illustrate this point.6
• Business model innovation: Digital technologies
are allowing firms to entirely reimagine current
business models within the emerging network of
people and machines, giving price and quality-
of-service advantages over incumbents. Key for
businesses are the new opportunities this brings for
ways of matching people to needs and of leveraging
the network for decentralized information gathering
to create systems that are constantly re-optimizing
themselves. Thus, in addition to allowing for more
efficient directed/explicit learning systems in the
form of crowd-sourcing models for innovation,
the new level of connectivity that characterizes
the emerging industrial landscape is also creating
increasingly self-learning systems. Some of the
biggest success stories of the digital era have been
companies that have moved into the business
of market-making. The gains to be had from this
approach to leveraging technology are currently
looking bigger than the gains to be had from
incremental product and process improvements for
existing products.
In an indirect way, digital technology is leading
to more innovation by changing the incentives of
incumbents to innovate. This is competition-driven
innovation, where innovation itself does not necessarily
involve new technologies. In particular, this includes
technology having the effect of:
• Increasing market size: Technology acts to
integrate markets by reducing communication costs
and increasing matching efficiency, which in turn
increases competitive pressures. For example,
online platforms through which firms can connect
almost without cost to a global consumer base are
creating a tougher competitive environment.
• Reducing barriers to entry: New online services,
such as globally accessible cloud computing and
online marketing platforms, are saving start-ups
and small- and medium-sized enterprises (SMEs)
a significant share of the fixed costs of running a
business. This facilitates entry and scaling, and
thereby contributes to a leveling of the playing field
vis-à-vis large incumbents. Mettler and Williams
(2011) identify six such types of business platforms:
crowd-financing, digital utilities, professional services
marketplaces, micro-manufacturing, innovation
marketplaces, and e-commerce platforms.7
• Acquiring and leveraging knowledge of
consumer preferences: Big data is giving firms
the opportunity to target products so they more
closely align with consumer preferences based on
more accurate information about the latter. This can
act like a quality upgrade from the point of view of
the consumer, and therefore increases pressure on
other firms to innovate themselves.
In addition to increasing competitive pressures from
new forms of innovation, the central position of networks
in this emerging industrial landscape is dramatically
changing the rules of the game for companies across
sectors: a key implication for businesses is that the
ability to scale fast is starting to become a precondition
for innovation success.
Why is innovation alone no longer enough? Across
industries, achieving scale quickly (in terms of customer
base) is crucial because of the self-reinforcing nature of
network effects and the implied winner-take-all outcome
for the player that achieves a large enough network the
fastest.8
Scale is also important for self-optimization of
systems: the more participants, the faster the system
updates priors about the behavior of market participants,
allowing for ever closer matches of preferences and
creating yet more value. Quick scaling is also allowing
companies to set industry standards, which can act as a
competitive advantage because the company that scales
quickly sets the precedent and thus can define that
precedent. Businesses therefore need to substantially
accelerate all processes across the firm in order to win
the race for the market.
The ability to scale cannot be taken for granted
in the digital economy. An ecosystem that systematically
allows top innovations to be scaled globally remains a
key feature of only a handful of places, including
Silicon Valley.9

Technology-enabled innovation is thus creating
significant competitive pressures for tech and non-tech
firms alike. In competitive economies, the only way to
escape is yet more innovation. These mechanisms look
set to be reinforced as the Fourth Industrial Revolution is
starting to gain a foothold.
Key findings
This section presents the four key findings that emerge
from an analysis of the last five years of NRI data.
1. The changing nature of innovation: The minds of
business executives around the world are increasingly
focused on innovation as reflected by the steady upward
trend in firms’ perceived capacity to innovate. Traditional
measures for innovation, such as the number of patents
registered, are telling only part of the story. This is related
to the fact that the current transformation is nurtured
by a different type of innovation, increasingly based on
digital technologies and on the new business models
it allows: executives in almost 100 countries report
increases in the perceived impact of ICTs on business-
model innovation compared with last year.
The World Economic Forum’s Executive Opinion
Survey annually asks more than 14,000 business
executives in more than 140 economies about their
perception of the capacity to innovate by firms in their
country. The data of the last five years show some
striking global patterns. Business executives across all
regions of the world state that the capacity to innovate of
firms in their countries has increased steadily (Figure 2).
With this clear global shift in focus toward innovation
by the business sector, three questions arise: Is the
increased innovation capacity being realized and
reflected in terms of innovation output? If it is, what kinds
of innovation are firms engaging in? What is driving this
favorable shift in innovation capacity?
Consider the most traditional of innovation output
measures: the number of patents normalized by
population size. Patenting activity continues on an
upward trend in advanced economies and is starting to
pick up across most regions of the world. It has been
growing in particular in Emerging Europe as well as in the
Middle East and North Africa. Figure 2 illustrates these
positive trends (with a change in patenting compared to
the 2012 base on the right-hand scale). Nevertheless,
much of the increased innovation capacity remains
unaccounted for once innovation output in the form of
patents is taken into account. Several explanations are
possible for this observation.
For technologically advanced countries, patent
trends are more closely matched to perceived innovation
trends, yet in some sectors there is a divergence
between the two. Patenting is slowing, particularly in
industries with high digital content, at the same time that
innovation is accelerating (see Box 3). Several reasons for
this slowdown are put forward in Box 3: one driver is the
shortening of product cycles, which is especially evident
in industries, such as audio-visual technologies and
telecommunications, that are most affected by digital
disruption. In addition, patent pendency times have been
rising. These two developments combined often make
it unprofitable for firms to patent their innovations. In
addition, the pressure to innovate has increased to such
an extent that many firms are focusing their resources
entirely on cost-saving/efficiency innovation rather than
attempting moonshots, or what Clayton Christensen
calls “empowering innovation.”10
Thus, although digital
innovation is accelerating, the expectation is that these
Advanced
Economies
1
2
3
4
5
6
7
–1
20162015201420132012
Score(1–7)
20162015201420132012
Percent
Sources: NRI, 2012–2016 editions. Based on Executive Opinion Survey data and World Intellectual Property Organization (WIPO) PCT data, sourced from the Organisation for Economic
Co-operation and Development (OECD) Patent Database.
Eurasia
Figure 2: Trends for perceived capacity to innovate and PCT patents per million population, 2012–16
–1
0
1
2
3
4
5
6
7
20162015201420132012
20162015201420132012
–1
0
1
2
3
4
5
6
7
Emerging and
Developing Asia
Emerging and
Developing Europe

trends will be captured less and less well by traditional
innovation measures in the future.
A broader measure of innovation outcomes—the
Economic impacts pillar of the NRI, which comprises
both patents and survey-based measures of the impact
of ICTs on business model and on organizational model
innovation—can give some additional insights: the 2016
iteration of the NRI sees a positive change compared
to 2015 in the perceived impact of ICTs on business
model innovation in almost 100 countries. Importantly,
as Figure 3 demonstrates, the increased power of ICTs
to enable new business models is being felt across
the entire networked readiness spectrum.11
ICT-driven
business model innovation thus is a candidate to be
watched as an important source of digital innovation
impact.
2. The increasing urgency to adopt and innovate
continuously: Although innovation is clearly on
executives’ minds, seven countries truly stand out in
terms of their digital innovation performance. A closer
look at their characteristics reveals very high rates of
business ICT adoption and a top innovation environment.
Although perceived capacity to innovate is going
up across the world, certain countries are far ahead of
the rest in terms of innovation impact as captured by the
NRI (Figure 4): when looking at the score distribution for
the Economic impacts pillar of the NRI, seven countries
stand out in terms of their performance: Finland,
Switzerland, Sweden, Israel, Singapore, the Netherlands,
and the United States. A closer examination of these top
seven innovative countries gives important clues about
potential drivers for innovation success in the digital era.
In order to establish how the top seven are different
from other countries, Figure 5 shows the distribution
of ranks for these countries across all other individual
pillars of the NRI. The data reveal some striking patterns:
top innovation impact performers are all characterized
by top ranks in business usage of digital technologies.
More particularly, this means these countries perform
especially well on the combination of firm technology
absorption, innovation capacity, patenting, and business-
to-business (B2B) and business-to-consumer (B2C)
Internet use as well as ICT staff training. In addition
to having very high levels of business ICT use, the
top seven all rank highly in terms of their business
and innovation environment as well as in individual
technology usage.
At the country level, high levels of business
adoption of digital technologies and a strong business
and innovation environment thus stand out as a key
Percent
–1
0
1
2
3
4
5
6
7
20162015201420132012
Score(1–7)
Sub-Saharan Africa
20162015201420132012
1
2
3
4
5
6
7
–1
20162015201420132012
Latin America
and the Caribbean
Middle East,
North Africa, and Pakistan
— PCT patents per million pop.
— Capacity for innovation
(indicator 7.02)
n PCT patents per million pop.
change relative to 2012, right axis
Figure 2: Trends for perceived capacity to innovate and PCT patents per million population, 2012–16 (cont’d.)
Notes: The number of PCT patents per million population is shown on a normalized scale of 1 to 7. Based on a constant sample of 127 economies. Groupings follow the IMF classification; IMF
“CIS” = “Eurasia.”
2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0
2.5
3.0
3.5
4.0
4.5
5.0
5.5
6.0
Figure 3: Perceived impact of technology on business
model innovation: 2015 vs 2016
Source: NRI, 2015 and 2016 editions.
Note: Numbers are based on a constant sample of a 135 economies.
2016score
2015 score
l Positive change
l Negative change

characteristic of highly innovative countries. To the
extent that digitization allows for faster processes, this
finding resonates with both survey-based and anecdotal
evidence at the firm level, which shows that speed in
bringing new inventions to market is the most crucial
factor in becoming and staying a top innovative firm in
the Digital Age.12
Because digital technologies are driving
winner-take-all dynamics for an increasing number of
industries, getting there first matters.
Note that a crucial ingredient for innovation success
will continue to be talent competitiveness. Although the
NRI contains a broad measure of skills, it currently does
not map the availability of the very specialized talent
needed to drive digital innovation.13
Yet this type of talent
will be at the core of any success story in the unfolding
Fourth Industrial Revolution: it will limit or enhance the
ability of individual countries to fuel their development,
growth, and employment strategies through digital
The World Intellectual Property Organization (WIPO) (2015)
shows a global rise of patent applications to a total of 2.7
million, an increase of 4.5 percent over 2014.1
Yet two patent
fields—audio-visual technologies and telecommunications—
show a constant decline in their number of patent
applications over the last 10 years, of 13 percent and 20
percent, respectively. Moreover, since peaking in 2005, the
total number of patent filings of the top 100 global patent
applicants has followed a downward trend of more than 20
percent in the last decade. This has resulted in part from
a sharp decline in filings by three large companies, which
have reduced their patent activities by more than two-
thirds. Those three and the remaining companies in the top
100 are predominantly in the computer, semiconductor,
telecommunications, and consumer electronic business.
Three potential drivers of this trend are shortening product
life cycles, longer patent pendency times, and a shift in
innovation types:
Product life cycles are getting shorter
Various studies have shown that the duration of product life
cycles is steadily decreasing across all industries. Between
1997 and 2012 the average life cycle length across industries
fell by 24 percent.2
The digitalization of almost every business
aspect and the resulting efficiency boosts have contributed a
big part of this development.
Besides a general shortening of product life cycles, the
existence of differences across various industry sectors are
especially important with respect to their development cycle
times and useful product life spans.3
For fast, risky industries
even small delays in time-to-market can have extensive
effects on the expected return. Being late to market yields a
significant loss of revenue; this can quickly exceed the costs
incurred during the development and manufacturing phase.
Imagine a semiconductor company that produces a
chip with two years of product life on the market. Releasing
a new chip only one quarter (three months) too late means
the company loses more than one-third of the expected
return of releasing on time. This could potentially exceed the
development costs of the product and be a very sensitive
profit killer. Compare this to the world’s largest passenger
airplane, the Airbus A380, which has a useful product life
of around 20 years. Delays in the delivery of commercial
airplanes are rather the rule than the exception, and the
incurred cost of mistakes are easier to amortize.
Patent pendency time is getting longer
The average patent pendency time has increased in many
patent offices around the world to four years and more. This
trend, together with the simultaneous shortening of product
life cycles across all industries, could have led to a situation
where filing patents increasingly become an unpractical and
tardy means for technological innovations with short-term
applicability. If this was true, we would see the affected
industries rather shifting to more time-strategic, broad
patenting of features for the sole purpose of delaying the
development cycle for competitors.
A shift in the type of innovation toward efficiency
Clayton Christensen (2012) distinguishes three major forms
of innovation: “empowering,” “sustaining,” and “efficiency”
innovations. While the first and the second type create and
sustain jobs, the third is describing innovations that streamline
processes and tend to reduce the number of available jobs.4
Fast-paced industries in the sustaining category will
feel a continuous pressure to increase productivity, and will
incentivize to invest and operate in the efficiency innovation
scheme. The 2015 industry employment and output
projections to 2024 by the US Bureau of Labor Statistics, for
example, find that the US computer and peripheral equipment
manufacturing industry is among those with the highest
projected changes both in terms of increases in output
and declines in employment.5
This is an indication that the
industry is running in full efficiency innovation mode.
How can such an industry then be open to taking
more risks by working on completely new approaches and
potential moonshots if most resources are spent to increase
efficiency to stay in business? One way could be through
new partnership models with, and investment in, start-ups.
If a business is running like clockwork and trimmed toward
optimized outcomes, it might not be the right environment
to follow out-of-the-box ideas. A positive development is
that an increasing number of agile entrepreneurs with
bold ideas are starting to shake up industries that are fully
engaged with themselves. In addition, corporate investment
arms that strategically back young companies are on the rise.
A diversification of corporate culture might be essential for
survival in the long run.
Notes
1 WIPO 2015.
2 Roland Berger Strategy Consultants 2012.
3 Prasad 1997.
4 Christensen 2012.
5 United States Department of Labor, Bureau of Labor Statistics
2015.
Contributed by Bernhard Petermeier, Technology Pioneers, World
Economic Forum.
Box 3: The decline of patents in ICT-driven industries

innovation. When it comes to succeeding at innovation,
countries critically need to think not only about educating
future innovators but also about how to retain talent once
educated, as the pull of Silicon Valley remains strong.14
3. Missed opportunities: In recent years, digital
innovation has been primarily driven by consumer
demand. Yet this increasing demand for digital products
and services by a global consumer base is being met
by a relatively small number of companies. Businesses
need to act now and adopt digital technologies to
capture their part of this growing market. A widening
and worrying gap is also emerging between growth in
individual ICT usage and public-sector engagement in
the digital economy, as government usage is increasingly
falling short of expectations. Governments can do more
to invest in innovative digital solutions to drive social
impact.
The NRI data suggest that business usage and
adoption is stagnating or moving only slowly across
regions (Figure 6). This suggests that a large number of
existing firms are not getting in the game fast enough.
The data also imply that it is not a lack of technology
take-up by individuals that is holding back business
adoption: companies that do adopt digital technologies
will find themselves with a fast-growing connected
consumer base. As Figure 6 shows, this trend of rising
individual adoption is remarkably uniform across all
regions of the world. The number of Internet users grew
in all but nine countries since the 2015 iteration of the
Index. Household ownership of personal computers and
the number of households with an Internet connection
is also increasing in all but a handful of countries. In
particular, the quality of Internet service is improving, with
fixed and mobile broadband subscriptions increasing
across the board.
Furthermore, an expectations gap has opened
up with respect to public-sector performance in using
Figure 4: Economic impact of ICTs in the Top 7 economies
vs other country groups and regions, 2012–16
Score
Source: NRI, 2012–2016 editions.
Notes: Top 7 identifies the seven best performers in terms of economic impact: Finland,
Switzerland, Sweden, Israel, Singapore, the Netherlands, and the United States.
Numbers are based on a constant sample of a 127 economies. Groupings follow the IMF
classification; IMF “CIS” = “Eurasia.”
1
2
3
4
5
6
7
2014 2016201520132012
Emerging and Developing Asia
Other advanced economies
Middle East, North Africa, and Pakistan
Top 7
Sub-Saharan Africa
Eurasia
Latin America and the Caribbean
Emerging and Developing Europe
139
120
100
80
60
40
20
1
Social
impacts
Government
usage
Business
usage
Individual
usage
SkillsAffordabilityInfrastructureBusiness and
innovation
environment
Political and
regulatory
environment
Figure 5: Distribution of ranks for Top 7 performers on the economic impacts pillar across the remaining 9 pillars
Rank (1 to 139)
Source: NRI, 2016 edition.
Note: The light blue boxes identify the interquartile range—from the 75th to the 25th percentile—for each distribution.
| Max/min range
n Q1/Q3 range
— Median
l Outliers

and promoting digital technologies. The upward trend
in government usage (NRI pillar 8) observed up to
2013 is slowly being reversed in all regions of the world
(Figure 6). Governments are also seen to be falling
behind in terms of using digital technologies efficiently
for social impact (NRI indicator 10.03, Figure 7). Using
ICTs to more efficiently provide services to citizens is an
important area where digital technologies can make a
difference in generating broad-based gains.
Yet it does not have to be the government alone that
is driving social outcomes. Indeed, overall social impact
scores (NRI pillar 10) are up in a group of countries,
in particular the advanced economies (Figure 8). ICTs
can be used in many innovative ways to achieve social
impact—for example, in facilitating access to basic
services such as healthcare, finance, and insurance
(Figure 9). Even in cases where the government remains
firmly in charge of the system, access to the system
can be facilitated by digital technologies and private
initiative. A pioneering example of such a public-private
digital collaboration for social impact is a Dutch service
provider that has partnered with the government to
facilitate access to the justice system (Box 4).
4. Building a resilient digital economy: As the new
digital economy is taking shape, offering it the right
framework conditions will be crucial to ensuring its
sustainability. Digital technologies are unleashing new
economic and social dynamics that will need to be
managed if the digital transformation of industries and
societies are to deliver long-term and broad-based
gains. A resilient digital economy also calls for new types
of leadership, governance, and behaviors. A critical
ingredient for the success and sustainability of the
Figure 6: Time trends for individual, business, and government usage, 2012–16
1
2
3
4
5
6
7
20162015201420132012 20162015201420132012
Advanced Economies Eurasia
20162015201420132012 20162015201420132012
Emerging and
Developing Asia
Emerging and
Developing Europe
Score(1–7)
Figure 7: Impacts of ICTs on government efficiency, 2012–16
Score (1–7)
Note: Regional groupings follow the IMF classification; IMF “CIS” = “Eurasia.”
3
4
5
6
2015 2016201520132012
Advanced economies
Sub-Saharan Africa
Eurasia
2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
5.5
6.0
6.5
Figure 8: Social impacts score (pillar 10): 2015 vs 2016
2016score
2015 score
l Positive change
l Negative change

emerging system will be agile governance frameworks
that allow societies to anticipate and shape the impact
of emerging technologies and react quickly to changing
circumstances.
From an economic standpoint, two developments
that come in the wake of the unfolding digital revolution
carry direct implications for future competitiveness
and inclusive growth and will require a careful policy
response: the impact of digital technologies and new
networks on (1) competition dynamics in product
markets and (2) labor market dynamics.
As network dynamics are becoming a key feature
of competition in the emerging platform economy, being
able to bring products to market fast and scale rapidly is
increasingly important for companies. At the same time,
the risk of lock-in needs to be managed. Governments
can play a supportive role in creating a level playing field
by ensuring a business environment that allows firms to
quickly react to new developments; this includes speedy
procedures for opening a new business and bringing
products to market, providing a supportive innovation
ecosystem, ensuring that barriers to entry stay low by
enforcing a competition regime that counteracts potential
network lock-in, and promoting and facilitating ICT
adoption by building out infrastructure and having a clear
ICT strategy.
Similar to trade liberalization, the spread of digital
technologies is creating winners and losers within the
labor force. Two key ways in which digital technologies
are affecting outcomes can be identified.
First, as digital technologies are increasingly allowing
for the automation of routine jobs, they are currently
accelerating the polarization of the income distribution
because middle-skilled workers are most affected up to
this point. In the United States, total employment grew
significantly in the lower end of the skill spectrum, where
— Individual usage
— Business usage
— Government usage
Figure 6: Time trends for individual, business, and government usage, 2012–16 (cont’d.)
20162015201420132012
Notes: Based on a constant sample of 127 economies. Groupings follow the IMF classification; IMF “CIS” = “Eurasia.”
Sub-Saharan Africa
20162015201420132012
7
1
2
3
4
5
6
20162015201420132012
Latin America
and the Caribbean
Middle East, North Africa,
and Pakistan
Score(1–7)
Score(1–7)
Figure 9: Impact of ICTs on access to basic services
(indicator 10.01), 2012–16
Note: Groupings follow the IMF classification; IMF “CIS” = “Eurasia.”
3.5
4.5
5.5
6.5
2015 2016201520132012
3.5
4.5
5.5
6.5
2015 2016201520132012
Advanced economies
Sub-Saharan Africa
Eurasia
wages were generally stagnating or grew slightly, and
at the higher end of the spectrum, where wages grew
significantly. Many middle-skilled workers have been
seeing their earnings decline or their jobs evaporate.15
Economies need to face the double challenge of
further upgrading the skills of workers at the upper end
of the spectrum while ensuring that the rest, the majority,
of the population also receive the necessary training
to prosper in the digital world. The World Economic
Forum Future of Jobs report examines future skills
needs via a survey of Chief Human Resource Officers
from 366 companies worldwide. The responses indicate
that complex problem-solving skills comprise the set
of skills that will be considered a core requirement by
the largest share of jobs across industries (36 percent).
Skills that are not considered crucial today will account
for about a third of the most-needed skills by 2020.

Demand for narrow technical skills such as programming
or equipment operation and control will be rather
stable, while demand will grow for cognitive abilities,
content, process, and social skills.16
Policy must play an
important role in terms of supporting the transition of
workers into new jobs and ensuring that workers’ skills
match market demand.
In addition to automation, a second mechanism
by which digital technologies are affecting the labor
market is through the effects of the platform economy.17
Digital platforms are used not only to match consumers
with goods but also increasingly to match workers with
jobs. This is leading to more freelance activity and fewer
workers being employed by firms in full-time jobs with
correspondingly more uncertainty over income flows and
less social protection (e.g., insurance, pension). Despite
these developments, continued social protection for
workers needs to be ensured.
Anticipatory governance of innovation
Given the likelihood that extremely powerful and
multi-use technologies will be developed, tested, and
commercialized in coming years, it will be important
to guide innovation and commercialization processes
with the wider social, economic, and environmental
context in mind. Importantly, new technologies should
not be thought of as panaceas or simple tools but
rather as entities that exert power over users and that
will have different impacts in different social contexts.
It is therefore critical to keep in mind the social reality
in which emerging technologies will be used and to
appreciate the economic and social dynamics they may
exacerbate, such as inequality.
Ideally the governance of innovation processes
would start before economic policies become a relevant
instrument, anticipating some of the important societal
challenges as applications are developed. Recognizing
these challenges, the European Union has recently
adopted guidelines on Responsible Research and
Innovation (RRI) that reflect these considerations.18
RRI
is currently applied mainly with regard to emerging
technologies—notably nanotechnologies, genomics,
synthetic biology, and geo-engineering. It has been
defined as “a transparent, interactive process by
which societal actors and innovators become mutually
responsive to each other with a view to the (ethical)
acceptability, sustainability and societal desirability of
the innovation process and its marketable products
in order to allow a proper embedding of scientific and
technological advances in our society.”19
In terms of evaluating the social desirability of
research undertakings, several sets of principles have
been suggested: (1) orienting research so as to address
major existing or emerging global risks—tightening
supplies of energy, water, and food; pandemics; aging
societies; global warming; public health and security;20
(2) constitutional values21
—for example, in the case of
the European Union, “respect for human dignity, liberty,
democracy, equality, the rule of law and respect for
human rights, including the rights of persons belonging
to minorities. […] Moreover […] pluralism, non-
discrimination, tolerance, justice, solidarity and equality
between women and men”;22
and (3) general principles
of human and labor rights as enshrined in the UN Global
Compact’s 10 principles.23
One key challenge to more appropriate forms of
innovation governance is the fact that technologies
change far faster than regulatory regimes do. As the
World Economic Forum’s Global Agenda Council on
the Future of Software and Society has pointed out,
Rechtwijzer 2.0 is a collaborative effort between HiiL
Innovating Justice, the Dutch Legal Aid Board, Modria, and
the Dutch Ministry of Justice and Security. The online-based
dispute resolution (ODR) platform aims to inform people about
their legal options as well as to support legal professionals
so they can intervene more effectively. The initiative allows
citizens to find sustainable solutions to their legal issues,
such as divorce, separation, landlord-tenant disputes,
and employment disputes. The ODR platform empowers
citizens to access justice by providing simple models that
have worked for others as well as tailored support by legal
professionals. The platform is a major innovation that helps
citizens get access to justice and could offer a sustainable
solution to many judicial systems.
Rechtwijzer 2.0 is a great example of a wider movement
and need: justice innovation. Justice innovation is a form of
social innovation that is key to reforming judicial systems. It
uses market-based approaches that benefit society. It will
help close the gap on the estimated 4 billion people who
do not have adequate access to justice. Social innovation is
described by the Global Agenda Council on Social Innovation
as “the application of innovative, practical, sustainable,
market-based approaches to benefit society in general, and
low-income or underserved populations in particular.”1
This
approach is more collaborative and will empower low-income
people to participate in the global economy with dignity.
Note
1 World Economic Forum 2016e.
Contributed by Lisa Ventura, Society and Innovation, World Economic
Forum.
Box 4: Public-private collaboration in digital social innovation: Rechtwijzer, the Dutch digital platform for
dispute resolution

technology has so fundamentally changed many
behaviors and processes being governed that current
regulations are not fully relevant (see A Call for Agile
Governance Principles). In an attempt to close this
“agility gap,” the Council took inspiration from agile
approaches used in software development to create four
“agile governance” principles. The work proposes that
policymakers could create governance systems that are
more robust, adaptable, and responsive to changing
technologies if their decision-making frameworks valued
outcomes over rules; if they valued responding to
change over following a plan; participation over control;
and self-organization over centralization. In addition to
suggesting these new heuristics, the Council looks at
specific areas where new policy options need to be
generated in order to ensure that emerging technologies
deliver inclusive benefits to society, including the “gig
economy,” the use of decentralized payment systems,
peer-to-peer transactions, and autonomous devices.
Building on this work, as well as work by the Global
Agenda Council on Justice and others, in July 2016 the
World Economic Forum launched a new set of Global
Future Councils that includes a number of councils
specifically focused on the governance of emerging
technologies and the potential for new forms of agile
governance to guide innovation and the Fourth Industrial
Revolution toward positive outcomes for society.
COUNTRY AND REGIONAL TRENDS FROM THE NRI
This section of the chapter turns to the general global
and regional trends emerging from this year’s results of
the NRI (see Tables 1 through 5), as well as to a detailed
analysis of the performance of selected economies.
Networked readiness continues to improve almost
everywhere in the world, with a clear upward trend in
mean country performance across all regions; however,
convergence within regions is far from being the norm
(Figure 10). Clearly divergent regional performances
are observed for the group of countries within Eurasia;
Emerging and Developing Europe; the Middle East,
North Africa, and Pakistan (MENAP); and sub-Saharan
Africa. In the case of MENAP and sub-Saharan Africa,
this is driven by the fact that top countries improve their
performance at the same time that the performance
of the worst-scoring countries is deteriorating. There is
a clear upward trend for the entire range of countries
for the group of Advanced Economies, Emerging
and Developing Asia, Eurasia, and Latin America and
the Caribbean. Notably, the group of Emerging and
Developing Asian countries is both moving up and
converging in terms of overall NRI scores. Average
performance on the NRI in 2016 is highest for the
group of Advanced Economies, followed by Emerging
and Developing Europe, the Eurasian countries and
MENAP (the two are approximately even), Emerging and
Developing Asia, Latin America and the Caribbean, and
Sub-Saharan Africa.
1
2
3
4
5
6
7
20162012201620122016201220162012201620122016201220162012
Sub-Saharan
Africa
Middle East,
North Africa,
and Pakistan
Latin America
and the Caribbean
Emerging and
Developing Europe
Emerging and
Developing Asia
EurasiaAdvanced
economies
Max
Mean
Min
Max/min range
Sweden
Singapore
Kazakhstan
Kazakhstan
Malaysia Malaysia
Hungary
Chile
Chile
Bahrain
United
Arab
Emirates
Mauritius
Mauritius
Poland
Figure 10: The Networked Readiness Index by regional group, 2012 vs 2016
Score (1–7)
Note: Numbers are based on a constant sample of 132 economies. Groupings follow the IMF classification; IMF “CIS” = “Eurasia.”

2015 rank
Rank Country/Economy Value (out of 143) Income level* Group†
1 Singapore 6.0 1 HI ADV
2 Finland 6.0 2 HI-OECD ADV
3 Sweden 5.8 3 HI-OECD ADV
4 Norway 5.8 5 HI-OECD ADV
5 United States 5.8 7 HI-OECD ADV
6 Netherlands 5.8 4 HI-OECD ADV
7 Switzerland 5.8 6 HI-OECD ADV
8 United Kingdom 5.7 8 HI-OECD ADV
9 Luxembourg 5.7 9 HI-OECD ADV
10 Japan 5.6 10 HI-OECD ADV
11 Denmark 5.6 15 HI-OECD ADV
12 Hong Kong SAR 5.6 14 HI ADV
13 Korea, Rep. 5.6 12 HI-OECD ADV
14 Canada 5.6 11 HI-OECD ADV
15 Germany 5.6 13 HI-OECD ADV
16 Iceland 5.5 19 HI-OECD ADV
17 New Zealand 5.5 17 HI-OECD ADV
18 Australia 5.5 16 HI-OECD ADV
19 Chinese Taipei 5.5 18 HI ADV
20 Austria 5.4 20 HI-OECD ADV
21 Israel 5.4 21 HI-OECD ADV
22 Estonia 5.4 22 HI-OECD ADV
23 Belgium 5.4 24 HI-OECD ADV
24 France 5.3 26 HI-OECD ADV
25 Ireland 5.3 25 HI-OECD ADV
26 United Arab Emirates 5.3 23 HI MENAP
27 Qatar 5.2 27 HI MENAP
28 Bahrain 5.1 30 HI MENAP
29 Lithuania 4.9 31 HI ADV
30 Portugal 4.9 28 HI-OECD ADV
31 Malaysia 4.9 32 UM EDA
32 Latvia 4.8 33 HI ADV
33 Saudi Arabia 4.8 35 HI MENAP
34 Malta 4.8 29 HI ADV
35 Spain 4.8 34 HI-OECD ADV
36 Czech Republic 4.7 43 HI-OECD ADV
37 Slovenia 4.7 37 HI-OECD ADV
38 Chile 4.6 38 HI-OECD LATAM
39 Kazakhstan 4.6 40 UM EURAS
40 Cyprus 4.6 36 HI ADV
41 Russian Federation 4.5 41 HI EURAS
42 Poland 4.5 50 HI-OECD EDE
43 Uruguay 4.5 46 HI LATAM
44 Costa Rica 4.5 49 UM LATAM
45 Italy 4.4 55 HI-OECD ADV
46 Macedonia, FYR 4.4 47 UM EDE
47 Slovak Republic 4.4 59 HI-OECD ADV
48 Turkey 4.4 48 UM EDE
49 Mauritius 4.4 45 UM SSA
50 Hungary 4.4 53 HI-OECD EDE
51 Montenegro 4.3 56 UM EDE
52 Oman 4.3 42 HI MENAP
53 Azerbaijan 4.3 57 UM EURAS
54 Croatia 4.3 54 HI EDE
55 Panama 4.3 51 UM LATAM
56 Armenia 4.3 58 LM EURAS
57 Mongolia 4.3 61 UM EDA
58 Georgia 4.3 60 LM EURAS
59 China 4.2 62 UM EDA
60 Jordan 4.2 52 UM MENAP
61 Kuwait 4.2 72 HI MENAP
62 Thailand 4.2 67 UM EDA
63 Sri Lanka 4.2 65 LM EDA
64 Ukraine 4.2 71 LM EURAS
65 South Africa 4.2 75 UM SSA
66 Romania 4.1 63 UM EDE
67 Trinidad and Tobago 4.1 70 HI LATAM
68 Colombia 4.1 64 UM LATAM
69 Bulgaria 4.1 73 UM EDE
70 Greece 4.1 66 HI-OECD ADV
2015 rank
Rank Country/Economy Value (out of 143) Income level* Group†
71 Moldova 4.0 68 LM EURAS
72 Brazil 4.0 84 UM LATAM
73 Indonesia 4.0 79 LM EDA
74 Seychelles 4.0 74 HI SSA
75 Serbia 4.0 77 UM EDE
76 Mexico 4.0 69 UM LATAM
77 Philippines 4.0 76 LM EDA
78 Morocco 3.9 78 LM MENAP
79 Vietnam 3.9 85 LM EDA
80 Rwanda 3.9 83 LI SSA
81 Tunisia 3.9 81 UM MENAP
82 Ecuador 3.9 n/a UM LATAM
83 Jamaica 3.9 82 UM LATAM
84 Albania 3.9 92 UM EDE
85 Cape Verde 3.8 87 LM SSA
86 Kenya 3.8 86 LM SSA
87 Bhutan 3.8 88 LM EDA
88 Lebanon 3.8 99 UM MENAP
89 Argentina 3.8 91 HI LATAM
90 Peru 3.8 90 UM LATAM
91 India 3.8 89 LM EDA
92 Iran, Islamic Rep. 3.7 96 UM MENAP
93 El Salvador 3.7 80 LM LATAM
94 Honduras 3.7 100 LM LATAM
95 Kyrgyz Republic 3.7 98 LM EURAS
96 Egypt 3.7 94 LM MENAP
97 Bosnia and Herzegovina 3.6 n/a UM EDE
98 Dominican Republic 3.6 95 UM LATAM
99 Namibia 3.6 102 UM SSA
100 Guyana 3.6 93 LM LATAM
101 Botswana 3.5 104 UM SSA
102 Ghana 3.5 101 LM SSA
103 Guatemala 3.5 107 LM LATAM
104 Lao PDR 3.4 97 LM EDA
105 Paraguay 3.4 105 UM LATAM
106 Côte d’Ivoire 3.4 115 LM SSA
107 Senegal 3.4 106 LM SSA
108 Venezuela 3.4 103 HI LATAM
109 Cambodia 3.4 110 LI EDA
110 Pakistan 3.4 112 LM MENAP
111 Bolivia 3.3 111 LM LATAM
112 Bangladesh 3.3 109 LM EDA
113 Gambia, The 3.3 108 LI SSA
114 Tajikistan 3.3 117 LM EURAS
115 Lesotho 3.3 124 LM SSA
116 Zambia 3.2 114 LM SSA
117 Algeria 3.2 120 UM MENAP
118 Nepal 3.2 118 LI EDA
119 Nigeria 3.2 119 LM SSA
120 Ethiopia 3.1 130 LI SSA
121 Uganda 3.1 116 LI SSA
122 Zimbabwe 3.0 121 LI SSA
123 Mozambique 3.0 129 LI SSA
124 Cameroon 3.0 126 LM SSA
125 Gabon 2.9 122 UM SSA
126 Tanzania 2.9 123 LI SSA
127 Mali 2.9 127 LI SSA
128 Benin 2.9 n/a LI SSA
129 Swaziland 2.9 125 LM SSA
130 Liberia 2.8 n/a LI SSA
131 Nicaragua 2.8 128 LM LATAM
132 Malawi 2.7 133 LI SSA
133 Myanmar 2.7 139 LM EDA
134 Guinea 2.6 142 LI SSA
135 Madagascar 2.6 135 LI SSA
136 Mauritania 2.5 138 LM MENAP
137 Haiti 2.5 137 LI LATAM
138 Burundi 2.4 141 LI SSA
139 Chad 2.2 143 LI SSA
Note: Income level classification follows the World Bank classification by income (situation as of July 2015). Group classification follows the International Monetary Fund’s classification (situation
as of April 2016). IMF “CIS” = “Eurasia.”
* Income groups: HI = high-income economies that are not members of the OECD; HI-OECD = high-income OECD members; UM = upper-middle-income economies; LM = lower-middle-income
economies; LI = low-income economies.
† Groups: ADV = Advanced economies; EDA = Emerging and Developing Asia; EDE = Emerging and Developing Europe; EURAS = Eurasia; LATAM = Latin America and the Caribbean; MENAP =
Middle East, North Africa, and Pakistan; SSA = Sub-Saharan Africa.
Table 1: The Networked Readiness Index 2016

Table 2: Environment subindex and pillars
ENVIRONMENT SUBINDEX
Rank Country/Economy Value Rank Value Rank Value
1 Singapore 6.0 2 5.9 1 6.0
2 New Zealand 5.6 3 5.9 6 5.4
3 United Kingdom 5.6 5 5.7 5 5.5
4 Hong Kong SAR 5.6 14 5.4 2 5.8
5 Finland 5.6 4 5.8 9 5.4
6 Norway 5.5 6 5.7 7 5.4
7 Switzerland 5.5 7 5.6 8 5.4
8 Netherlands 5.5 8 5.6 10 5.4
9 Luxembourg 5.5 1 5.9 27 5.0
10 Canada 5.4 15 5.4 4 5.5
11 Ireland 5.4 11 5.5 11 5.4
12 Sweden 5.3 10 5.5 20 5.2
13 United States 5.3 21 5.2 3 5.5
14 Denmark 5.3 17 5.3 16 5.3
15 Qatar 5.3 18 5.3 15 5.3
16 Australia 5.2 13 5.4 23 5.1
17 Japan 5.2 9 5.5 33 4.9
18 Iceland 5.2 22 5.1 17 5.3
19 United Arab Emirates 5.2 25 5.1 13 5.4
20 Germany 5.2 16 5.4 28 5.0
21 Malaysia 5.1 24 5.1 18 5.2
22 Belgium 5.1 20 5.2 22 5.1
23 Estonia 5.0 27 5.0 26 5.1
24 Israel 5.0 28 4.7 12 5.4
25 Austria 5.0 19 5.2 40 4.7
26 France 5.0 23 5.1 35 4.8
27 Rwanda 4.9 12 5.4 63 4.4
28 Saudi Arabia 4.9 29 4.6 25 5.1
29 Chinese Taipei 4.8 40 4.2 14 5.3
30 Portugal 4.7 33 4.4 24 5.1
31 Korea, Rep. 4.7 34 4.3 21 5.1
32 Chile 4.7 38 4.3 19 5.2
33 South Africa 4.7 26 5.0 65 4.3
34 Mauritius 4.7 30 4.6 41 4.7
35 Bahrain 4.6 36 4.3 29 5.0
36 Lithuania 4.6 41 4.2 31 5.0
37 Latvia 4.6 45 4.2 30 5.0
38 Jordan 4.5 39 4.2 38 4.8
39 Malta 4.5 32 4.5 56 4.5
40 Czech Republic 4.5 35 4.3 47 4.6
41 Spain 4.4 47 4.0 37 4.8
42 Macedonia, FYR 4.4 62 3.9 32 5.0
43 Cyprus 4.4 56 3.9 36 4.8
44 Uruguay 4.4 44 4.2 51 4.6
45 Slovenia 4.4 67 3.8 34 4.9
46 Zambia 4.3 61 3.9 39 4.8
47 Kazakhstan 4.3 48 4.0 54 4.5
48 Poland 4.2 57 3.9 53 4.6
49 Turkey 4.2 69 3.8 43 4.7
50 Jamaica 4.2 49 4.0 62 4.4
51 Hungary 4.2 50 4.0 59 4.4
52 Oman 4.2 53 4.0 58 4.4
53 Namibia 4.2 31 4.5 103 3.9
54 Thailand 4.2 80 3.7 48 4.6
55 Panama 4.1 85 3.6 45 4.7
56 Georgia 4.1 73 3.7 55 4.5
57 Croatia 4.1 92 3.5 44 4.7
58 Mongolia 4.1 81 3.6 52 4.6
59 Botswana 4.1 46 4.1 84 4.1
60 Montenegro 4.1 94 3.5 46 4.7
61 Slovak Republic 4.1 74 3.7 60 4.4
62 Indonesia 4.1 65 3.8 64 4.4
63 Bhutan 4.1 37 4.3 102 3.9
64 Cape Verde 4.0 55 4.0 80 4.1
65 Romania 4.0 66 3.8 71 4.2
66 Bulgaria 4.0 101 3.3 42 4.7
67 Russian Federation 4.0 88 3.6 57 4.5
68 Kuwait 4.0 63 3.8 72 4.2
69 Costa Rica 4.0 60 3.9 78 4.1
70 Tajikistan 4.0 42 4.2 105 3.8
71 Ghana 4.0 54 4.0 92 4.0
72 Côte d’Ivoire 4.0 51 4.0 96 3.9
73 Sri Lanka 3.9 64 3.8 81 4.1
74 Azerbaijan 3.9 79 3.7 74 4.2
75 Lesotho 3.9 52 4.0 100 3.9
76 Seychelles 3.9 59 3.9 97 3.9
77 Morocco 3.9 70 3.8 87 4.1
78 Armenia 3.9 116 3.2 50 4.6
79 Mexico 3.9 77 3.7 83 4.1
80 Senegal 3.9 76 3.7 88 4.0
81 Kenya 3.9 75 3.7 93 4.0
82 Iran, Islamic Rep. 3.9 91 3.5 76 4.2
83 China 3.9 58 3.9 104 3.8
84 Guyana 3.9 86 3.6 79 4.1
85 Italy 3.8 96 3.4 68 4.3
86 Vietnam 3.8 82 3.6 91 4.0
87 Dominican Republic 3.8 100 3.4 69 4.3
88 Albania 3.8 109 3.2 61 4.4
89 Philippines 3.8 87 3.6 85 4.1
90 Gambia, The 3.8 43 4.2 123 3.4
91 Lebanon 3.8 126 3.0 49 4.6
92 Greece 3.8 108 3.3 66 4.3
93 Lao PDR 3.8 68 3.8 106 3.8
94 Ukraine 3.8 113 3.2 67 4.3
95 Kyrgyz Republic 3.7 103 3.3 75 4.2
96 Trinidad and Tobago 3.7 104 3.3 77 4.1
97 Peru 3.7 118 3.1 70 4.3
98 Honduras 3.7 95 3.4 95 3.9
99 India 3.7 78 3.7 110 3.7
100 Mali 3.7 71 3.7 116 3.6
101 Uganda 3.7 72 3.7 118 3.6
102 Colombia 3.7 97 3.4 94 4.0
103 Serbia 3.7 110 3.2 82 4.1
104 El Salvador 3.6 106 3.3 90 4.0
105 Ecuador 3.6 111 3.2 86 4.1
106 Ethiopia 3.6 89 3.6 109 3.7
107 Guatemala 3.6 122 3.0 73 4.2
108 Liberia 3.6 84 3.6 117 3.6
109 Tunisia 3.6 90 3.5 112 3.7
110 Nepal 3.5 114 3.2 99 3.9
111 Moldova 3.5 125 3.0 89 4.0
112 Tanzania 3.5 83 3.6 125 3.4
113 Egypt 3.5 102 3.3 113 3.7
114 Cameroon 3.5 105 3.3 114 3.7
115 Pakistan 3.4 128 3.0 98 3.9
116 Nigeria 3.4 117 3.2 111 3.7
117 Malawi 3.4 93 3.5 126 3.4
118 Brazil 3.4 98 3.4 124 3.4
119 Cambodia 3.4 124 3.0 108 3.7
120 Mozambique 3.3 112 3.2 121 3.5
121 Bosnia and Herzegovina 3.3 120 3.1 120 3.6
122 Swaziland 3.3 115 3.2 122 3.4
123 Benin 3.3 99 3.4 130 3.3
124 Argentina 3.3 127 3.0 115 3.6
125 Paraguay 3.3 133 2.7 101 3.9
126 Gabon 3.3 107 3.3 131 3.3
127 Madagascar 3.2 129 2.8 119 3.6
128 Zimbabwe 3.1 121 3.0 132 3.2
129 Bolivia 3.1 119 3.1 134 3.2
130 Bangladesh 3.1 137 2.5 107 3.7
131 Algeria 3.1 123 3.0 133 3.2
132 Nicaragua 3.0 130 2.7 128 3.3
133 Myanmar 3.0 134 2.7 127 3.3
134 Burundi 2.9 136 2.5 129 3.3
135 Mauritania 2.8 135 2.6 135 3.0
136 Haiti 2.8 131 2.7 138 2.8
137 Guinea 2.7 138 2.5 137 2.9
138 Chad 2.7 132 2.7 139 2.6
139 Venezuela 2.6 139 2.2 136 3.0
Political and Business and
regulatory innovation
environment environment
Political and Business and
regulatory innovation
environment environment

Table 3: Readiness subindex and pillars
READINESS SUBINDEX
Rank Country/Economy Value Rank Value Rank Value Rank Value
1 Finland 6.6 3 7.0 13 6.4 2 6.5
2 Chinese Taipei 6.4 1 7.0 12 6.5 23 5.8
3 Iceland 6.4 7 7.0 19 6.3 15 6.0
4 Norway 6.4 1 7.0 28 6.1 12 6.0
5 United States 6.4 5 7.0 17 6.4 27 5.8
6 Austria 6.3 13 6.6 5 6.7 28 5.7
7 Sweden 6.3 3 7.0 25 6.2 25 5.8
8 Canada 6.2 7 7.0 61 5.6 11 6.1
9 Switzerland 6.2 11 6.8 70 5.4 3 6.4
10 Australia 6.2 7 7.0 57 5.6 13 6.0
11 Hong Kong SAR 6.2 25 6.0 16 6.4 10 6.1
12 Denmark 6.1 17 6.4 31 6.1 17 5.9
13 Germany 6.1 12 6.6 55 5.6 8 6.1
14 Korea, Rep. 6.1 5 7.0 48 5.8 35 5.6
15 Japan 6.1 14 6.6 49 5.8 14 6.0
16 Singapore 6.1 15 6.6 72 5.3 1 6.5
17 Belgium 6.1 19 6.4 62 5.5 4 6.4
18 Estonia 6.0 16 6.5 59 5.6 19 5.9
19 Luxembourg 5.9 26 6.0 36 6.0 20 5.9
20 United Kingdom 5.9 20 6.3 53 5.7 24 5.8
21 Cyprus 5.9 33 5.5 22 6.3 16 6.0
22 Czech Republic 5.9 23 6.3 46 5.8 39 5.5
23 Netherlands 5.9 18 6.4 83 5.0 6 6.2
24 New Zealand 5.9 10 6.8 97 4.6 7 6.2
25 Slovenia 5.8 24 6.1 60 5.6 21 5.8
26 Bahrain 5.8 31 5.8 40 5.9 31 5.7
27 France 5.8 22 6.3 76 5.2 18 5.9
28 Poland 5.8 35 5.3 11 6.6 40 5.5
29 Ireland 5.7 27 6.0 77 5.2 9 6.1
30 Ukraine 5.7 51 4.7 6 6.6 33 5.6
31 Latvia 5.6 43 5.0 23 6.3 36 5.6
32 Russian Federation 5.5 52 4.7 10 6.6 48 5.4
33 Portugal 5.5 40 5.1 41 5.9 34 5.6
34 Spain 5.5 34 5.4 42 5.9 57 5.3
35 Trinidad and Tobago 5.5 37 5.2 44 5.9 43 5.5
36 Malta 5.5 21 6.3 88 4.8 44 5.5
37 Israel 5.5 32 5.5 68 5.5 38 5.5
38 Costa Rica 5.5 60 4.5 21 6.3 30 5.7
39 Kazakhstan 5.5 64 4.4 7 6.6 45 5.4
40 Turkey 5.5 59 4.5 2 6.9 69 5.0
41 Italy 5.5 39 5.1 52 5.7 37 5.6
42 Lithuania 5.4 57 4.5 34 6.0 26 5.8
43 Armenia 5.4 61 4.4 18 6.3 51 5.4
44 Mongolia 5.3 79 4.0 4 6.7 62 5.2
45 Montenegro 5.3 41 5.0 67 5.5 50 5.4
46 Georgia 5.3 65 4.4 15 6.4 64 5.1
47 Croatia 5.3 47 4.8 66 5.5 42 5.5
48 Serbia 5.2 45 4.9 56 5.6 61 5.2
49 Macedonia, FYR 5.2 56 4.6 39 5.9 66 5.1
50 Bosnia and Herzegovina 5.2 50 4.7 32 6.1 84 4.7
51 Kuwait 5.2 30 5.8 89 4.8 77 4.9
52 Moldova 5.1 69 4.2 29 6.1 70 5.0
53 Romania 5.1 55 4.6 73 5.2 41 5.5
54 Qatar 5.1 29 5.8 120 3.1 5 6.4
55 Brazil 5.1 58 4.5 26 6.2 91 4.5
56 United Arab Emirates 5.0 28 5.9 116 3.4 22 5.8
57 Mauritius 5.0 68 4.3 65 5.5 53 5.3
58 Hungary 5.0 48 4.8 80 5.0 56 5.3
59 Slovak Republic 5.0 70 4.2 51 5.8 72 5.0
60 Saudi Arabia 5.0 36 5.2 101 4.3 49 5.4
61 Panama 5.0 63 4.4 33 6.1 93 4.5
62 Thailand 4.9 67 4.3 64 5.5 73 5.0
63 Sri Lanka 4.9 103 3.0 35 6.0 32 5.7
64 Tunisia 4.9 82 3.7 24 6.3 85 4.7
65 Chile 4.9 54 4.6 84 4.9 67 5.1
66 Colombia 4.9 76 4.1 58 5.6 79 4.9
67 Azerbaijan 4.8 74 4.1 71 5.3 68 5.1
68 Albania 4.8 75 4.1 92 4.7 29 5.7
69 South Africa 4.8 44 4.9 74 5.2 95 4.4
70 Oman 4.8 46 4.9 96 4.6 76 5.0
READINESS SUBINDEX
71 Ecuador 4.8 78 4.0 78 5.1 63 5.2
72 Bulgaria 4.8 38 5.2 111 3.8 52 5.4
73 Malaysia 4.8 71 4.2 91 4.7 46 5.4
74 Seychelles 4.8 49 4.7 98 4.5 74 5.0
75 China 4.7 90 3.3 63 5.5 47 5.4
76 Uruguay 4.7 53 4.7 87 4.8 83 4.8
77 Greece 4.7 42 5.0 110 3.9 58 5.3
78 Argentina 4.7 66 4.3 n/a n/a 71 5.0
79 Kyrgyz Republic 4.7 97 3.1 27 6.1 81 4.8
80 Bhutan 4.7 73 4.1 45 5.9 103 4.1
81 Indonesia 4.6 105 2.9 38 5.9 65 5.1
82 Vietnam 4.6 121 2.4 3 6.8 82 4.8
83 Iran, Islamic Rep. 4.6 101 3.0 37 6.0 80 4.8
84 Mexico 4.6 84 3.7 54 5.7 92 4.5
85 Venezuela 4.6 89 3.3 50 5.8 88 4.6
86 Paraguay 4.5 62 4.4 79 5.1 105 3.9
87 Lebanon 4.5 77 4.0 109 4.0 55 5.3
88 India 4.4 114 2.6 8 6.6 101 4.1
89 Peru 4.4 72 4.1 95 4.6 94 4.5
90 Jamaica 4.4 93 3.2 69 5.4 86 4.6
91 El Salvador 4.4 83 3.7 75 5.2 98 4.2
92 Philippines 4.4 87 3.6 107 4.1 54 5.3
93 Jordan 4.3 92 3.2 94 4.6 59 5.3
94 Morocco 4.3 102 3.0 20 6.3 110 3.7
95 Algeria 4.3 80 3.9 99 4.4 89 4.6
96 Cape Verde 4.3 100 3.1 86 4.8 75 5.0
97 Egypt 4.2 94 3.1 47 5.8 111 3.7
98 Bangladesh 4.1 107 2.8 14 6.4 122 3.1
99 Honduras 4.1 96 3.1 85 4.9 97 4.2
100 Cambodia 4.1 98 3.1 43 5.9 120 3.3
101 Guyana 4.0 104 2.9 104 4.2 78 4.9
102 Bolivia 4.0 91 3.2 103 4.3 90 4.6
103 Dominican Republic 4.0 85 3.7 106 4.2 104 4.0
104 Pakistan 4.0 126 2.1 1 6.9 127 2.8
105 Kenya 3.9 99 3.1 102 4.3 96 4.2
106 Nepal 3.9 130 1.9 30 6.1 115 3.6
107 Lao PDR 3.9 108 2.7 82 5.0 106 3.9
108 Lesotho 3.7 120 2.4 81 5.0 108 3.8
109 Guatemala 3.7 86 3.6 108 4.0 118 3.4
110 Namibia 3.6 81 3.9 119 3.2 109 3.8
111 Botswana 3.5 95 3.1 125 2.9 87 4.6
112 Guinea 3.5 132 1.8 9 6.6 137 2.1
113 Ghana 3.5 125 2.2 105 4.2 102 4.1
114 Zimbabwe 3.4 123 2.3 112 3.8 100 4.1
115 Rwanda 3.3 106 2.8 114 3.6 117 3.5
116 Ethiopia 3.1 122 2.3 93 4.6 131 2.5
117 Nigeria 3.1 113 2.6 100 4.3 134 2.4
118 Myanmar 3.1 115 2.6 122 3.0 113 3.6
119 Gabon 3.0 128 2.0 113 3.6 116 3.5
120 Nicaragua 3.0 88 3.5 136 1.9 112 3.6
121 Tajikistan 3.0 133 1.6 134 2.2 60 5.2
122 Gambia, The 3.0 109 2.7 123 3.0 121 3.2
123 Swaziland 3.0 119 2.5 133 2.2 99 4.2
124 Uganda 3.0 112 2.7 117 3.3 126 2.9
125 Mozambique 2.9 131 1.9 90 4.8 136 2.1
126 Côte d’Ivoire 2.9 110 2.7 127 2.9 123 3.1
127 Zambia 2.7 129 2.0 129 2.5 114 3.6
128 Benin 2.6 116 2.6 126 2.9 133 2.4
129 Senegal 2.6 118 2.5 130 2.5 128 2.8
130 Tanzania 2.6 117 2.6 131 2.3 125 2.9
131 Cameroon 2.6 138 1.1 128 2.8 107 3.8
132 Haiti 2.5 137 1.1 115 3.5 124 3.0
133 Burundi 2.5 134 1.3 124 2.9 119 3.3
134 Malawi 2.4 111 2.7 135 2.0 130 2.7
135 Liberia 2.2 135 1.2 121 3.1 132 2.4
136 Mauritania 2.1 136 1.2 118 3.3 138 1.9
137 Madagascar 2.0 124 2.2 138 1.0 129 2.8
138 Chad 1.9 127 2.0 137 1.9 139 1.9
139 Mali 1.9 139 1.1 132 2.3 135 2.4
Infrastructure Affordability Skills Infrastructure Affordability Skills

Table 4: Usage subindex and pillars
USAGE SUBINDEX
1 Singapore 6.0 12 6.4 14 5.4 1 6.3
2 Japan 5.9 11 6.4 3 5.9 7 5.4
3 Netherlands 5.9 8 6.6 7 5.8 14 5.4
4 Sweden 5.9 4 6.7 2 6.0 23 5.0
5 Luxembourg 5.9 2 6.8 15 5.4 9 5.4
6 Korea, Rep. 5.8 10 6.5 13 5.4 4 5.6
7 Finland 5.8 6 6.6 5 5.8 21 5.0
8 United States 5.8 17 6.2 4 5.9 12 5.4
9 Norway 5.8 3 6.7 11 5.5 18 5.2
10 Denmark 5.8 1 6.9 9 5.7 38 4.7
11 United Kingdom 5.7 5 6.6 16 5.2 10 5.4
12 Switzerland 5.7 9 6.6 1 6.1 43 4.5
13 United Arab Emirates 5.6 19 6.2 27 4.6 2 6.2
14 Germany 5.6 18 6.2 6 5.8 30 4.8
15 Israel 5.5 31 5.6 8 5.8 17 5.3
16 Chinese Taipei 5.5 24 6.0 12 5.5 24 5.0
17 New Zealand 5.5 20 6.1 20 5.0 13 5.4
18 Iceland 5.5 7 6.6 18 5.1 36 4.7
19 Qatar 5.4 23 6.0 25 4.8 5 5.5
20 France 5.4 25 6.0 19 5.0 15 5.3
21 Austria 5.4 27 5.9 10 5.6 28 4.8
22 Australia 5.4 13 6.3 24 4.8 22 5.0
23 Estonia 5.4 15 6.3 28 4.4 8 5.4
24 Bahrain 5.3 14 6.3 37 4.0 3 5.7
25 Hong Kong SAR 5.3 16 6.3 21 4.9 37 4.7
26 Canada 5.2 30 5.7 22 4.9 19 5.1
27 Belgium 5.2 22 6.0 17 5.2 42 4.6
28 Ireland 5.2 28 5.9 23 4.9 25 4.9
29 Saudi Arabia 5.1 21 6.0 42 3.9 11 5.4
30 Malaysia 5.1 47 5.1 26 4.7 6 5.5
31 Lithuania 4.9 35 5.5 29 4.3 33 4.7
32 Spain 4.8 33 5.6 43 3.9 32 4.7
33 Malta 4.7 26 5.9 40 4.0 49 4.3
34 Portugal 4.7 45 5.1 33 4.2 29 4.8
35 Latvia 4.6 36 5.5 35 4.1 50 4.3
36 Oman 4.5 39 5.3 94 3.4 34 4.7
37 Czech Republic 4.5 29 5.8 31 4.3 101 3.4
38 Uruguay 4.5 44 5.2 90 3.4 27 4.8
39 Chile 4.5 52 4.9 47 3.9 39 4.6
40 Russian Federation 4.5 40 5.3 67 3.6 44 4.4
41 Azerbaijan 4.4 56 4.8 58 3.7 35 4.7
42 Slovenia 4.4 38 5.4 30 4.3 86 3.6
43 Italy 4.4 37 5.5 52 3.8 62 4.0
44 Kazakhstan 4.4 58 4.8 69 3.6 26 4.8
45 Slovak Republic 4.4 34 5.6 48 3.9 73 3.7
46 Costa Rica 4.3 55 4.8 38 4.0 56 4.1
47 Kuwait 4.3 32 5.6 72 3.6 81 3.7
48 Hungary 4.2 41 5.3 73 3.6 70 3.8
49 Poland 4.2 42 5.3 64 3.6 82 3.6
50 Macedonia, FYR 4.2 49 5.0 92 3.4 58 4.1
51 China 4.1 75 3.9 44 3.9 40 4.6
52 Cyprus 4.1 51 4.9 54 3.8 75 3.7
53 Jordan 4.1 70 4.1 41 3.9 47 4.4
54 Colombia 4.1 71 4.1 82 3.5 31 4.8
55 Mauritius 4.1 66 4.3 55 3.8 48 4.3
56 Montenegro 4.1 61 4.6 99 3.4 53 4.2
57 Brazil 4.0 57 4.8 59 3.7 84 3.6
58 Croatia 4.0 43 5.2 98 3.4 90 3.5
59 Turkey 4.0 65 4.3 56 3.8 57 4.1
60 Morocco 4.0 67 4.2 105 3.3 41 4.6
61 Panama 4.0 72 4.0 39 4.0 60 4.1
62 Greece 4.0 50 4.9 87 3.5 91 3.5
63 Thailand 4.0 64 4.3 51 3.9 69 3.8
64 Bulgaria 4.0 48 5.0 77 3.5 102 3.3
65 Armenia 4.0 69 4.1 101 3.4 46 4.4
66 Philippines 3.9 79 3.8 36 4.0 63 4.0
67 Sri Lanka 3.9 102 2.8 49 3.9 20 5.0
68 Romania 3.9 60 4.7 68 3.6 96 3.5
69 Trinidad and Tobago 3.9 59 4.7 79 3.5 94 3.5
70 Seychelles 3.9 62 4.3 70 3.6 79 3.7
USAGE SUBINDEX
71 Mongolia 3.9 82 3.7 61 3.7 51 4.2
72 Georgia 3.8 68 4.1 108 3.2 54 4.1
73 Argentina 3.8 53 4.9 103 3.4 111 3.3
74 Mexico 3.8 84 3.6 66 3.6 52 4.2
75 South Africa 3.8 77 3.9 32 4.2 105 3.3
76 Moldova 3.8 63 4.3 112 3.2 66 3.9
77 Lebanon 3.8 46 5.1 97 3.4 124 2.9
78 Indonesia 3.8 92 3.3 34 4.1 65 3.9
79 Serbia 3.7 54 4.9 125 3.1 106 3.3
80 Tunisia 3.7 78 3.9 107 3.3 55 4.1
81 Vietnam 3.7 85 3.6 81 3.5 61 4.0
82 Ecuador 3.7 87 3.5 83 3.5 64 3.9
83 Rwanda 3.6 127 1.9 60 3.7 16 5.3
84 Kenya 3.6 107 2.6 50 3.9 45 4.4
85 Jamaica 3.6 86 3.5 62 3.7 87 3.6
86 Albania 3.6 83 3.6 93 3.4 76 3.7
87 Cape Verde 3.6 81 3.7 95 3.4 88 3.6
88 Ukraine 3.6 76 3.9 63 3.6 114 3.1
89 Egypt 3.5 80 3.8 129 3.0 67 3.8
90 El Salvador 3.5 91 3.3 78 3.5 85 3.6
91 Ghana 3.5 89 3.5 80 3.5 98 3.4
92 Peru 3.5 93 3.2 91 3.4 74 3.7
93 Honduras 3.4 104 2.8 46 3.9 78 3.7
94 Namibia 3.4 98 3.0 57 3.7 92 3.5
95 Senegal 3.4 106 2.6 53 3.8 68 3.8
96 Botswana 3.4 94 3.2 96 3.4 89 3.6
97 Dominican Republic 3.4 95 3.2 88 3.5 95 3.5
98 Venezuela 3.3 74 3.9 131 3.0 118 3.0
99 Iran, Islamic Rep. 3.3 90 3.3 126 3.1 93 3.5
100 Côte d’Ivoire 3.3 109 2.6 65 3.6 80 3.7
101 Bhutan 3.3 99 2.9 111 3.2 83 3.6
102 Gambia, The 3.3 108 2.6 85 3.5 77 3.7
103 India 3.3 120 2.1 75 3.6 59 4.1
104 Kyrgyz Republic 3.2 88 3.5 109 3.2 117 3.0
105 Guyana 3.2 105 2.7 76 3.5 99 3.4
106 Guatemala 3.2 100 2.8 45 3.9 122 2.9
107 Bosnia and Herzegovina 3.2 73 4.0 123 3.1 133 2.6
108 Bolivia 3.1 97 3.0 132 3.0 108 3.3
109 Nigeria 3.1 112 2.5 86 3.5 112 3.3
110 Cambodia 3.1 101 2.8 104 3.3 116 3.0
111 Bangladesh 3.0 121 2.1 119 3.1 72 3.8
112 Paraguay 3.0 96 3.1 121 3.1 128 2.7
113 Zambia 3.0 126 2.0 71 3.6 104 3.3
114 Cameroon 2.9 125 2.0 74 3.6 107 3.3
115 Mali 2.9 113 2.5 124 3.1 113 3.2
116 Tajikistan 2.9 116 2.3 102 3.4 115 3.1
117 Lao PDR 2.9 124 2.0 89 3.4 110 3.3
118 Pakistan 2.9 123 2.1 110 3.2 103 3.3
119 Gabon 2.9 110 2.5 115 3.2 119 2.9
120 Uganda 2.9 129 1.9 106 3.3 97 3.4
121 Zimbabwe 2.8 114 2.5 117 3.1 120 2.9
122 Benin 2.8 119 2.2 84 3.5 127 2.8
123 Ethiopia 2.8 136 1.6 127 3.0 71 3.8
124 Mozambique 2.8 128 1.9 114 3.2 109 3.3
125 Algeria 2.8 103 2.8 133 2.9 130 2.7
126 Tanzania 2.7 134 1.7 122 3.1 100 3.4
127 Swaziland 2.7 115 2.4 116 3.2 131 2.7
128 Lesotho 2.7 122 2.1 120 3.1 121 2.9
129 Nepal 2.6 117 2.2 128 3.0 129 2.7
130 Liberia 2.6 130 1.8 113 3.2 123 2.9
131 Nicaragua 2.6 111 2.5 130 3.0 138 2.3
132 Madagascar 2.6 135 1.6 100 3.4 125 2.8
133 Mauritania 2.5 118 2.2 135 2.8 134 2.5
134 Malawi 2.5 137 1.5 118 3.1 126 2.8
135 Guinea 2.3 133 1.8 136 2.8 135 2.5
136 Haiti 2.3 132 1.8 134 2.8 139 2.2
137 Myanmar 2.3 131 1.8 138 2.6 137 2.3
138 Chad 2.2 139 1.3 137 2.6 132 2.6
139 Burundi 2.1 138 1.3 139 2.5 136 2.4

Individual Business Governent
usage usage usage

Individual Business Governent
usage usage usage

Table 5: Impact subindex and pillars
IMPACT SUBINDEX
1 Singapore 6.1 5 5.9 1 6.2
2 Netherlands 6.0 6 5.8 3 6.1
3 Sweden 5.8 3 6.1 12 5.6
4 Finland 5.8 1 6.1 18 5.5
5 United States 5.8 7 5.8 7 5.7
6 Israel 5.7 4 5.9 15 5.5
7 United Kingdom 5.6 11 5.3 5 5.9
8 Switzerland 5.6 2 6.1 33 5.0
9 Norway 5.6 8 5.4 8 5.7
10 Korea, Rep. 5.6 14 5.1 4 6.0
11 Canada 5.4 12 5.2 11 5.6
12 Luxembourg 5.4 9 5.4 23 5.3
13 Hong Kong SAR 5.3 13 5.2 14 5.5
14 Japan 5.3 15 5.1 16 5.5
15 Germany 5.3 10 5.4 30 5.2
16 Estonia 5.2 24 4.6 6 5.9
17 Denmark 5.2 16 5.1 26 5.3
18 United Arab Emirates 5.2 26 4.3 2 6.1
19 France 5.2 20 4.9 17 5.5
20 Chinese Taipei 5.2 18 5.0 20 5.4
21 Australia 5.2 23 4.7 9 5.7
22 Iceland 5.1 22 4.8 21 5.4
23 Belgium 5.0 19 4.9 31 5.1
24 Austria 5.0 21 4.9 29 5.2
25 New Zealand 5.0 25 4.6 19 5.4
26 Ireland 5.0 17 5.0 34 5.0
27 Qatar 4.9 28 4.2 10 5.6
28 Lithuania 4.8 27 4.3 25 5.3
29 Portugal 4.7 31 4.1 24 5.3
30 Malaysia 4.6 30 4.1 28 5.2
31 Latvia 4.5 34 4.0 32 5.1
32 Bahrain 4.5 48 3.5 13 5.5
33 Malta 4.5 33 4.0 37 4.9
34 Spain 4.4 35 4.0 39 4.8
35 Chile 4.4 47 3.5 27 5.2
36 Uruguay 4.4 62 3.4 22 5.4
37 Slovenia 4.3 29 4.1 50 4.5
38 Saudi Arabia 4.3 40 3.7 36 4.9
39 China 4.2 37 3.8 41 4.7
40 Kazakhstan 4.2 51 3.5 35 4.9
41 Russian Federation 4.1 38 3.7 45 4.6
42 Costa Rica 4.1 49 3.5 40 4.8
43 Czech Republic 4.1 32 4.1 67 4.2
44 Slovak Republic 4.1 41 3.6 47 4.6
45 Panama 4.0 45 3.6 51 4.5
46 Azerbaijan 4.0 50 3.5 48 4.5
47 Hungary 4.0 36 3.8 64 4.2
48 Italy 4.0 39 3.7 62 4.2
49 Sri Lanka 4.0 70 3.2 42 4.7
50 Kenya 3.9 54 3.4 52 4.5
51 Jordan 3.9 61 3.4 53 4.4
52 Colombia 3.9 84 3.1 43 4.7
53 Macedonia, FYR 3.9 55 3.4 55 4.3
54 Armenia 3.9 56 3.4 56 4.3
55 Rwanda 3.9 99 2.9 38 4.8
56 Cyprus 3.9 43 3.6 70 4.1
57 Montenegro 3.8 52 3.5 63 4.2
58 Turkey 3.8 67 3.2 54 4.4
59 Poland 3.8 44 3.6 74 4.0
60 Mongolia 3.8 82 3.1 49 4.5
61 Greece 3.8 65 3.3 58 4.3
62 Philippines 3.8 60 3.4 66 4.2
63 Georgia 3.8 91 2.9 44 4.6
64 Croatia 3.8 42 3.6 82 3.9
65 Thailand 3.7 74 3.2 57 4.3
66 Oman 3.7 95 2.9 46 4.6
67 Mauritius 3.7 69 3.2 61 4.2
68 Bulgaria 3.7 46 3.5 83 3.9
69 Ukraine 3.7 59 3.4 75 4.0
70 Mexico 3.7 64 3.3 71 4.1
IMPACT SUBINDEX
71 Moldova 3.7 81 3.1 60 4.2
72 Senegal 3.6 63 3.3 81 3.9
73 India 3.6 80 3.1 69 4.1
74 Honduras 3.6 53 3.5 87 3.8
75 Ecuador 3.6 86 3.0 68 4.1
76 Vietnam 3.6 92 2.9 65 4.2
77 Romania 3.6 72 3.2 79 3.9
78 Indonesia 3.5 85 3.1 73 4.0
79 Brazil 3.5 75 3.1 77 3.9
80 Morocco 3.5 110 2.8 59 4.3
81 Peru 3.5 88 3.0 72 4.1
82 Seychelles 3.5 73 3.2 86 3.8
83 Côte d’Ivoire 3.4 66 3.3 92 3.6
84 Tunisia 3.4 93 2.9 78 3.9
85 Egypt 3.4 58 3.4 103 3.5
86 Dominican Republic 3.4 68 3.2 94 3.6
87 Cape Verde 3.4 77 3.1 89 3.7
88 Trinidad and Tobago 3.4 78 3.1 90 3.7
89 Serbia 3.4 79 3.1 93 3.6
90 Kuwait 3.4 102 2.9 84 3.9
91 El Salvador 3.4 106 2.8 80 3.9
92 Argentina 3.4 87 3.0 88 3.7
93 South Africa 3.4 57 3.4 112 3.3
94 Jamaica 3.3 76 3.1 97 3.5
95 Guyana 3.3 94 2.9 91 3.7
96 Guatemala 3.3 71 3.2 107 3.4
97 Albania 3.3 121 2.6 76 4.0
98 Bhutan 3.2 119 2.6 85 3.8
99 Tajikistan 3.2 101 2.9 96 3.5
100 Gambia, The 3.2 103 2.9 95 3.5
101 Namibia 3.2 98 2.9 100 3.5
102 Iran, Islamic Rep. 3.2 100 2.9 101 3.5
103 Lebanon 3.2 83 3.1 114 3.3
104 Lao PDR 3.1 97 2.9 110 3.4
105 Pakistan 3.1 105 2.8 106 3.4
106 Bolivia 3.1 113 2.7 98 3.5
107 Bangladesh 3.1 104 2.8 108 3.4
108 Botswana 3.1 107 2.8 105 3.4
109 Mali 3.1 96 2.9 113 3.3
110 Kyrgyz Republic 3.1 114 2.7 104 3.4
111 Ghana 3.1 117 2.7 99 3.5
112 Venezuela 3.0 118 2.6 102 3.5
113 Zambia 3.0 115 2.7 111 3.3
114 Nigeria 3.0 90 2.9 123 3.0
115 Cameroon 3.0 89 2.9 124 3.0
116 Mozambique 2.9 112 2.7 117 3.1
117 Cambodia 2.9 111 2.7 122 3.0
118 Paraguay 2.9 109 2.8 125 3.0
119 Ethiopia 2.9 131 2.4 109 3.4
120 Uganda 2.9 120 2.6 118 3.1
121 Bosnia and Herzegovina 2.8 123 2.6 119 3.1
122 Tanzania 2.8 132 2.4 115 3.3
123 Benin 2.8 108 2.8 128 2.8
124 Zimbabwe 2.8 133 2.3 116 3.2
125 Lesotho 2.7 130 2.4 121 3.1
126 Liberia 2.7 125 2.5 127 2.9
127 Madagascar 2.7 126 2.5 126 2.9
128 Nepal 2.7 136 2.3 120 3.1
129 Algeria 2.6 124 2.6 132 2.7
130 Gabon 2.6 127 2.5 129 2.7
131 Malawi 2.6 128 2.5 130 2.7
132 Nicaragua 2.6 122 2.6 133 2.6
133 Mauritania 2.5 116 2.7 134 2.4
134 Swaziland 2.5 134 2.3 131 2.7
135 Myanmar 2.4 129 2.4 135 2.4
136 Haiti 2.3 135 2.3 136 2.4
137 Burundi 2.1 137 2.1 138 2.2
138 Guinea 2.1 139 2.0 137 2.2
139 Chad 2.1 138 2.0 139 2.1
Economic Social
impacts impacts
Economic Social
impacts impacts

The overall improvement in the NRI score masks a
diversity of trends across subindexes (Figure 12 on page
22). Most importantly, there is a clear positive trend
both in terms of Usage and Impact across regions. The
regulatory and innovation environment is perceived to
be improving as well, but although this improvement
has been large in Eurasia, it is almost negligible in Latin
America and the Caribbean, where regulatory reforms
seem to have come to a standstill in many countries.
Performance in terms of Readiness is mostly stagnant,
with large intertemporal fluctuations driven by changes
in affordability and sluggish improvements in skills
and infrastructure, where investments have not been
enough to keep up with the pace of increase in Usage.
Affordability remains a barrier to ICT adoption and use in
sub-Saharan Africa, and indeed this barrier seems to be
growing.
The distribution of scores across the 10 pillars
shows interesting patterns (Figure 11) and provides
further support for the findings outlined above.
Infrastructure and individual usage are the two areas
with the largest dispersion of performance across
countries, with advanced economies leading the way
and sub-Saharan Africa still behind other regions—
although certain countries in the region are pushing
ahead (see the Country/Economy Profiles). Countries’
scores in business usage and economic impact is
most skewed toward the lower end of the distribution,
with the average performance of advanced economies
placed well ahead that of the rest of the world and
that of the best performers (Switzerland and Finland,
respectively) having the largest gap from the upper end
of the interquartile range. This confirms that businesses
in only a few economies are leveraging ICTs at their full
potential and reaping the resulting strong economic
impact. As in previous years, affordability is the only
area where advanced economies as a whole are not
the best-performing group (note that while “affordability”
indicators capture prices without quality adjustments,
it is ultimately the price that poses the entry barrier for
the poorest and not the quality-adjusted price). The
advanced economies are preceded in this regard by
the group of Eurasian countries, and Pakistan is the
market with the lowest price points. Sub-Saharan
Africa is at this moment still the lowest-scoring region,
with the notable exception of the perceived political
and regulatory environment, where the region follows
advanced economies and MENAP countries and
precedes Emerging and Developing Asia, Emerging and
Developing Europe, Eurasia, and Latin America and the
Caribbean. In terms of best performers, Luxembourg
replaces New Zealand this year as having the best
political and regulatory environment, and Finland has
been toppled by Singapore as the country with the best
skillset.
Overall, and as was explored in detail in the 2015
edition of this Report, the digital divide is still wide, yet
progress is being made. In particular, several initiatives
have been formed to tackle this gap, including the World
Economic Forum’s Internet for All initiative, which aims to
help connect the 4 billion people who are not yet online
(see Box 5).
1
2
3
4
5
6
7
Best
Worst
Advanced economies
Sub-Saharan Africa
Eurasia
Finland
Singapore
Switzerland
Denmark
Singapore
Pakistan
Chinese Taipei
Norway
SingaporeLuxembourg
Singapore
Social
impacts
Economic
impacts
Government
usage
Business
usage
Individual
usage
SkillsAffordabilityInfrastructureBusiness
and
innovation
environment
Political
and
regulatory
environment
Figure 11: Best and worst performers and regional performance by NRI pillar
Score (1–7)
Notes: The light blue boxes identify the interquartile range—from the 75th to the 25th percentile—for each distribution. Regional groupings follow the IMF classification; IMF “CIS” = “Eurasia.”

Figure 12: Trends at the subindex level, 2012–16
Score (1–7)
1
2
3
4
5
6
7
20162015201420132012
1
2
3
4
5
6
7
20162015201420132012
Advanced Economies Eurasia
1
2
3
4
5
6
7
20162015201420132012
1
2
3
4
5
6
7
20162015201420132012
Emerging and
Developing Asia
Emerging and
Developing Europe
Score(1–7)
country tops the rankings in the Readiness subindex.
This is the result of high scores in particular in the
infrastructure (3rd) and skills pillars (2nd); in addition,
affordability is very good (13th), although Finland is one
of several countries that sees broadband prices increase
significantly this year (51st, down from 39th in 2015).
There is currently room for improvement in particular in
the business and innovation environment, where Finland
ranks 9th. With 14 days to start a business, the country
comes in only at a low 81st place in this particular
indicator; as pressure for firms to bring products to
market quickly is increasing, these types of framework
conditions matter more than ever. That said, Finland
has extremely good access to the latest technologies
(1st) as well as venture capital (6th), and its businesses
are highly connected (5th on business usage). These
factors are all important in helping Finland achieve its
top global rank in economic impacts. The government
is currently perceived as playing a less proactive role in
promoting ICTs than in the past (21st place, down from
10th in 2013): indicators are dropping for government
procurement of advanced technologies, importance of
ICTs to government vision, government success in ICT
promotion, and ICT use to boost government efficiency.
3. Sweden keeps its 3rd position in the NRI as
scores in all four subindexes remain almost unchanged.
Overall, it ranks best in Usage (4th), which derives
from very high scores in individual (4th) and business
usage (2nd), and notably does very well in Impact (3rd).
Businesses are taking advantage of the fact that their
consumer base is highly connected, which is reflected in
one of the highest rates of B2C interaction globally (4th).
Government, on the other hand, is not yet connecting
with citizens online to the same extent as business,
with a 45th rank for the government E-Participation
Top 10 NRI performers
The composition of the group of top 10 performers is
unchanged from last year. The group consists of a mix
of high-income Southeast Asian (Singapore and Japan)
and European countries (Finland, Sweden, Norway, the
Netherlands, Switzerland, the United Kingdom, and
Luxembourg) as well as the United States. Networked
readiness therefore remains highly correlated with per
capita income.
1. Singapore tops the Index this year, defending
its number 1 position. Its outstanding performance is
underlined by the fact that it ranks 1st in the world in
three of the four subindexes (Environment, Usage, and
Impact), driven by top spots on several pillars: political and
regulatory environment (2nd), business and innovation
environment (1st), skills (1st), government usage (1st), and
social impact (1st). Overall, this ranking is to a large extent
the result of strong government commitment to the digital
agenda, including its Smart Nation program. The drop in
the Readiness subindex to 16th place is largely explained
by a drop in the affordability of broadband, although the
price points of broadband packages may hide quality
differences (i.e., a price increase may come with a quality
increase). Singapore currently has an offline population of
18 percent, potentially explained by its demographics, and
the country is still out of the top 10 for individual usage
(12th) and business adoption (14th). Nevertheless, gains
from ICT adoption are widely shared in Singapore, as the
country tops the Social impacts pillar, making excellent
use of digital technologies to provide access to basic
and government services and ensuring that schools are
connected.
2. Finland stays in 2nd place with an unchanged
overall score, but sees some slight rank drops for the
Environment, Usage, and Impact subindexes. The

Internet for All is one of the core projects of the Forum’s
Digital Economy and Society System Initiative. As a critical
enabler of the Fourth Industrial Revolution, Internet for All
focuses on connecting the over 4 billion people not yet
connected to the Internet. The project’s core objective is
to develop scalable, replicable, public-private collaboration
models to accelerate Internet access and adoption at the
national, regional, and global levels.
In 2015, Internet for All convened stakeholders from
various backgrounds to collect successful practice examples
for global Internet access and adoption, and to develop a
framework in which to accelerate achieving “Internet for
all.” The framework emphasizes the need for an ecosystem
approach to simultaneously address the challenges related to
infrastructure, affordability, skills and awareness, and content.
The report also includes a checklist, based on the framework,
to help policymakers and others assess where their countries
currently stand and the kinds of programs to consider. The
white paper “Internet for All: A Framework for Accelerating
Internet Access and Adoption” can be accessed at http://
www3.weforum.org/docs/WEF_Internet_for_All_Framework_
Accelerating_Internet_Access_Adoption_report_2016.pdf.
In 2016, Internet for All has two main objectives:
1. To develop new scalable and replicable on-the-ground
models of public-private collaboration, in partnership with
governments, to accelerate the achievement of the broad-
er social and economic priorities of the country/region in
the context of accelerating Internet for all. Programs will
be launched initially in up to three countries/regions. The
first such program, for Northern Corridor countries in East
Africa (Kenya, Rwanda, South Sudan, and Uganda), was
launched in May 2016, and additional country program
partnership opportunities in Asia and Latin America will
also be explored.
2. To develop a physical and digital platform that results in
increased coordination and collaboration among the mul-
tiple private, bilateral/multilateral, and non-profit organiza-
tions involved in catalyzing Internet access and adoption
at the global, regional, and country levels.
Box 5: The World Economic Forum’s Internet for All initiative
— Environmental subindex
— Readiness subindex
— Usage subindex
— Impact subindex
Figure 12: Trends at the subindex level, 2012–16 (cont’d.)
Score (1–7)
1
2
3
4
5
6
7
20162015201420132012
Sub-Saharan Africa
1
2
3
4
5
6
7
20162015201420132012
1
2
3
4
5
6
7
20162015201420132012
Latin America
and the Caribbean
Middle East, North Africa,
and Pakistan
Score(1–7)
Index. In general, the Swedish government is perceived
as less proactive than other advanced economies in
their use of digital technologies (23rd for government
usage); in particular, business executives feel that it has
somewhat been losing sight of the digital agenda (20th
for government ICT vision, down from 11th in 2014).
Yet the government has been taking steps to improve
the overall framework conditions for business: there
is visible progress in several areas of the political and
regulatory environment and the business and innovation
environment pillars. In particular, Sweden slashes
the number of days it takes to start a business from
16 to 7, moving it up 45 places in the ranking in this
indicator to 42nd place. Driven to an important extent
by the business sector, digital technologies are making
themselves felt in terms of economic impact (3rd) and an
improvement by four places in social impact to 12th.
4. Norway moves up one rank to 4th place, with
small but positive score changes in all four subindexes.
The country seems to have reached a plateau, with little
Notes: Based on a constant sample of 127 economies. Groupings follow the IMF classification; IMF “CIS” = “Eurasia.”

movement in its total NRI score in recent years. Its digital
economy is built on the very solid basis of top regulatory
and innovation environments (6th and 7th, respectively)
as well as the world’s best ICT infrastructure. Although
fixed broadband prices are relatively high (71st) there
has not been a further increase this year, and with 96.3
percent of the population online (2nd for individuals
using the Internet), the high prices do not seem to act
as an access barrier. Similar to the situation in Sweden,
Norwegian firms are capitalizing on the high ICT literacy
among the general population and workforce by using
digital technologies heavily in their interactions with
consumers as well as among each other (8th and 7th,
respectively). There has also been a visible positive
move in government usage (importance in vision,
success in ICT promotion, and government efficiency),
moving the country up six places to the 18th rank in the
government usage pillar. Unsurprisingly, these strong
digital foundations are reflected in two 8th ranks for the
two Impact pillars.
5. The United States moves up two ranks overall,
continuing a positive trend from 2013 (from 9th place
in 2013 to 7th in both 2014 and 2015 to 5th place
this year). This is based on improvements in all four
subindexes.24
The United States stands out in terms
of its extremely favorable business and innovation
environment (3rd), which has given rise to one of the
most agile and digitized business sectors globally. The
public sector is also using digital technologies effectively
to deliver services to citizens (4th the on Government
Online Service index) and to facilitate participation
(9th on the E-Participation Index). All stakeholders
can take advantage of very low broadband prices
(ranked 17th), with the cheapest package at US$16
per month, compared to a global average of US$52
and an average of US$26 in high-income countries;25
however, although international Internet bandwidth per
user has been growing steadily in recent years, the race
has accelerated such that the United States is slipping
from 34rd in 2013 to 42nd this year. The overall impact
of digital technologies in the United States is strong (it
ranks 7th for both economic and social impacts) and
growing, in particular in the social dimension: this year,
the United States moves up 15 places to rank 15th in the
perceived impact of ICTs on access to basic services.
6. The Netherlands drops by two spots in the
overall rankings, but remains one of the countries that
makes the best use of digital technologies to achieve
both economic and, in particular, social impacts (it ranks
6th and 3rd, respectively, in the two pillars and 2nd in
the Impact subindex). This is despite high mobile tariffs
(105th) and high and rising broadband prices (85th,
down from 68th). Other drops at the indicator level can
largely be attributed to the fact that, although conditions
are stable or even improving slightly in absolute terms,
other countries are moving ahead faster. This is true in
particular for the business and innovation environment
as well as ICT infrastructure. The Dutch population is
one of the most technology savvy and connected in the
world (8th for individual usage), an asset that both the
government and the business sector are making good
use of (3rd for B2C Internet use, 8th for the Government
Online Service index, and 1st for the E-Participation
index). Businesses are extensively deploying
digital technologies to reshape their business and
organizational models (4th in both indicators) and basic
service providers, whether they are public or private, are
working hand-in-hand with the population to facilitate
access via their platforms (2nd).
7. Switzerland slips by one spot overall to 7th, placing
in the top 10 for the Environment, Readiness, and Impact
and 12th for Usage subindexes. The country moves up
by two places in the innovation environment assessment,
largely driven by a jump in perceived availability of venture
capital as well as continued high levels of government
procurement of advanced technologies; this is against an
overall global trend of falling government demand for the
latest technologies. However, in general the government
has so far been a less avid adopter and promoter of
digitization, as reflected in a 43rd place for government
usage. Although it is strong in the high-tech procurement
market, it seems to be using digital technologies relatively
less to interact with citizens. On the other hand, the
country remarkably places 1st for business usage, driven
by high business technology absorption and innovation
capacity and high levels of digital B2B interaction
(interestingly, more than with consumers). This in turn has
been generating strong economic impact (2nd rank), as
reflected also in a steady upward trend in the share of
knowledge-intensive jobs (3rd).
8. The United Kingdom remains in 8th position,
improving slightly in absolute scores on all four
subindexes. Improvements at the indicator level are
particularly concentrated in the business and innovation
environment: perceived venture capital availability,
the quality of management schools, and government
procurement of advanced technologies have all
increased compared to last year, while the number of
days and procedures to start a business was reduced.
Although infrastructure and individual usage are moving
in the right direction, they are not moving fast enough to
result in gains in the rankings. Business adoption is high
and UK businesses are top in the world in making use
of the Internet to interact with their consumers as well as
with their production network (1st in B2C, 2nd in B2B).
They are also pushing the boundaries in terms of using
ICTs to reshape their business and organizational models
(ranking 2nd and 1st, respectively). The government
is also moving closer to the global frontier in terms of
technology use, jumping six places into the top 10 of the
government usage pillar.
9. Luxembourg’s NRI rank stays the same as last
year at 9th place, with its overall score continuing its
steady upward trend. Improvements at the pillar level

come in three areas: political and regulatory environment
and individual usage, moving Luxembourg to 1st and
2nd place in these categories, respectively, and in the
area where the country is most behind, affordability:
here in particular, a large drop in mobile cellular tariffs
moves the country up 14 places in the affordability pillar.
Although performance in terms of innovation environment
is mixed, good availability of venture capital (8th) and a
strong government commitment to procuring advanced
technologies (5th) bode well for the commercialization of
new ideas. In general government is perceived to play
an important role in supporting Luxembourg’s digital
economy, with business executives attesting to a high
importance of ICTs in the government’s vision (5th) and
its success in ICT promotion (6th). Furthermore, strong
framework conditions have been put in place, reflected
in the top rank regarding the level of sophistication for
ICT related laws (e.g., for e-commerce, digital signatures,
and consumer protection). The country also boasts a top
infrastructure with top ranks for international bandwidth
(1st) and the number of secure servers per capita (3rd).
10. Japan remains in 10th place overall, as in 2015,
and is able to climb two places to 2nd in the Usage
subindex; with business and government usage already
among the highest globally (3rd and 7th, respectively),
the country moves up two places in individual usage to
11th place. The business and innovation environment
is improving visibly with progress in the perceived
availability of venture capital, the quality of management
schools, and government procurement of advanced
technologies; this is the continuation of a strong positive
trend, moving the country from 40th place in 2014 to
33rd in 2016 in this particular pillar. Japan also keeps
building out its infrastructure, in particular international
Internet bandwidth and the number of secure servers.
In terms of impact, the country is slightly losing ground,
mainly because its peers are moving ahead faster.
Top movers
Italy is among the group of top movers this year,
climbing up by 10 places to an overall NRI rank of 45.
The most significant driver is a large improvement in
terms of both economic and social impacts, putting Italy
18 places ahead in the Impact rankings to 48th. Over
the past years, the Italian government has launched a
number of policies aiming at improving the provision
of online services to its citizens and creating a better
environment for start-ups and innovative companies.
However, key constraints remain, including the lack of
venture capital and the overall political and business
environment. Here the country seems to be moving
in the right direction, gaining in almost every aspect
of the regulatory environment pillar, but it remains
far below the global average. Italy is currently doing
best in individual usage (37th), followed by business
(52nd) and government use (62nd). Yet only a small
portion of Italians are connected to fixed broadband:
the number has been historically low but the gap with
other advanced economies has only increased in recent
years, when subscriptions per 100 people increased by
less than 10 percent from 21.9 (28th highest, in 2010)
to 23.5 (36th, in 2014). With the private sector currently
reorganizing itself and the launch of the 2015 national
Digital Agenda, which will unfold in the coming years,
the country has an opportunity to close this gap. Going
forward, it will be important to capitalize on this positive
momentum.
The Slovak Republic is one of the two biggest
movers in this year’s NRI, climbing 12 ranks to 47th
place, mainly on the back of reinforced effort from the
public sector: although the country ranks fairly low in
the regulatory environment (its lowest ranks overall are
in this category), it is starting to catch up this year in
terms of the effectiveness of law-making bodies, laws
relating to ICTs, and judicial independence. Furthermore,
the government is perceived to have been more active
in procuring advanced technologies as well as putting
digital technologies to use to increase government
efficiency. This is reflected in large moves compared
to last year for these indicators, of 29 and 31 places,
respectively (to 89th and 80th). In addition, the business
and innovation environment is perceived to be improving
markedly in terms of venture capital and tech availability,
as well as procedures to start a business. Together with
fairly high individual usage (34th), a good level of buy-in
from the business sector (48th), and quickly dropping
fixed broadband prices, the efforts to embrace the digital
economy are starting to pay off: the Slovak Republic is
able to improve its ranking in the Impact subindex by 14
places to 44th. This is thanks to better access to basic
services as well as firms taking advantage of digital
technologies to innovate in terms of organizational and
business models.
Kuwait is another top mover in the NRI this year,
moving up 11 spots to 61st place. This gain is supported
by substantial improvements in particular in Readiness,
Usage, and Impact. These improvements are very much
driven by individuals and businesses. Kuwait is doing
very well overall in terms of individual adoption—ranking
overall 32nd and very high in individual indicators:
mobile coverage (1st), mobile phone subscriptions (2nd),
households with personal computers (14th), and mobile
broadband subscriptions (2nd)—and is close to attaining
a rank in the top half for business adoption. In particular,
the country substantially improves its international Internet
bandwidth per user, jumping more than 50 places to rank
51st, according to ITU data. All of this is starting to show
in terms of economic impacts: Kuwait reports a large
perceived improvement in ICT impact on business model
innovation this year (although starting from a low base).
Although social impact is perceived to have improved less
than economic impact, it is worth noting that the social
impact of ICTs in Kuwait is perceived to be substantially
higher than economic impact (84th for social, 102nd for

economic). This is a good basis on which to build for
further improvements, and the government continues on
its course to improve the regulatory environment, as it has
done over the past year.
Despite an overall mixed performance, South Africa
makes large strides in the overall NRI rankings to 65th,
almost entirely driven by improvements in infrastructure
and affordability. South Africa’s digital transformation
is mostly business driven, as the country notably
performs best in business usage (32nd), followed by
individual usage (77th), followed by government usage
(105th). Although the country is perceived by South
African business executives to be performing relatively
well in terms of its regulatory and political environment,
its innovation and business environment is rated
significantly worse and, in addition, shows strong signs
of deterioration—especially regarding technology and
venture capital availability, government procurement
of the latest technologies, and days as well as
procedures to start a business. It would be a pity if these
developments were to offset investments in infrastructure
that have significantly increased international Internet
bandwidth and put the country among the top 20
globally on this particular indicator. Furthermore, mobile
tariffs have more than halved and broadband tariffs
dropped slightly, reducing barriers to adoption also
in terms of affordability. In order for impact to start
materializing, significantly more buy-in from government
will be needed across all areas of vision, promotion, and
efficient use.
Lebanon is the second biggest mover this year,
gaining 11 ranks to land in 88th place in the overall NRI.
Importantly, the country is registering substantial positive
moves in all four subindexes. In terms of adoption,
Lebanon is doing best in individual usage (46th), followed
by business usage (97th) and government usage (124th).
Most indicators of personal usage have been improving
over the past year, with the business sector catching
up in its use and adoption of digital technologies; with
overall perceived progress in business adoption being
slow around the world, this is a positive exception to the
trend. Starting from a low level, government indicators
are also moving in the right direction: in particular, the
regulatory environment is improving in terms of judicial
independence, the efficiency of the legal system, and
the effectiveness of law-making bodies. Substantial
improvements are registered for the impact of ICTs on
business models, organizational models, basic services,
and government efficiency. Building also on a solid basis
in terms of education, skills, and knowledge-intensive
jobs, Lebanon has many of the factors in place to
continue on this positive trajectory.
Côte d’Ivoire stands out as improving in almost
every dimension of networked readiness. All but
eight indicators go up this year, leaving the country
nine places improved in 106th position. The business
community reports large gains in the regulatory and
business environment. In particular, strong government
efforts to lower entry barriers by slashing the number of
days (from 32 to 7 days since 2013) and procedures to
start a business (4 steps, down from 10) are noteworthy.
Business executives also feel that the government has
a strong ICT vision and correspondingly considerable
success in ICT promotion (80th place for government
usage, up from 114th). In addition, they attest to
considerable ICT-driven improvements in government
efficiency. As business and individual usage are also
growing strongly, the existing infrastructure is starting to
be stretched—this is one of the few areas where Côte
d’Ivoire is falling behind. Going forward, progress in
upgrading infrastructure and tackling affordability seem
top priorities for sustaining momentum.
Ethiopia moves up 10 spots to 120th place in the
NRI, led by the government sector (71st for government
usage). Yet the business sector is starting to catch up,
moving up 8 spots to 127th, as executives feel innovation
capacity in the country is increasing and businesses
are starting to explore the use of the Internet to interact
with consumers (123rd this year, up from 138th). It will
be important that this momentum is not broken by a
deteriorating business environment; in particular, setting
up a new business seems to be getting tougher, with
the required number of days and procedures increasing.
The private sector is also still constrained by a very
small base of online consumers: only 31 percent of the
population had a mobile phone subscription in 2014. Yet,
because prices are falling significantly, ICTs will become
accessible to a larger part of the population (93rd rank
on affordability, up from 113th). In addition, the country
has been edging forward on the skills dimension,
although a large gap remains to be closed. Importantly,
the NRI figures suggest that there have been significant
improvements in giving schoolchildren access to the
Internet (ranking 96th, up from 115th), an effort that will
most certainly pay off in the coming years.
Other selected economies
The Republic of Korea further improves its score but
less than its peers, and thus slips one notch to 13th.
The country’s political and regulatory environment,
historically one of its relative weaknesses, has improved
significantly, especially when it comes to the judicial
system. Infrastructure has also improved further,
allowing Korea to climb to 5th position globally on the
back of increased international bandwidth capacity
(approximately 50 percent higher) and a further increase
in the number of secure servers installed in the country.
Digital technologies are fully leveraged in Korea to
provide online services to the population (4th) and
allowing the participation of citizens in public life and
decision-making (1st). With 98.5 percent of households
having access to the Internet, Korea has one of the
most tech-savvy populations in the world. However, a
stronger entrepreneurial spirit will be necessary to bring

innovation out of the large chaebols and into the rest of
the economy. Although it has increased in recent years,
venture capital availability is still low, with most funds
being channeled to existing companies rather than start-
ups in the seed and early-growth stages.
Canada improves its absolute performance but
less than its peers, thus sliding down three positions to
14th. The country can rely on one of the best business
and innovation environments in the world (4th), where
starting a business is easy and quick (ranking 3rd on
both time and procedures to start a business). The
potential of a highly skilled workforce (11th) remains
partially untapped, as individual usage remains relatively
low (30th): for example, there are only 54.3 mobile
broadband subscriptions per 100 people in Canada
(52nd), compared to 102.7 in the United States. Although
the government has been quite successful in using
digital technologies to provide online services (10th) and
allow citizens’ e-participation (14th), it has not shown a
strong vision for ICTs (49th) nor has it been particularly
successful in promoting them (38th). This might change
in the future because the government is stepping up
efforts to promote innovation policies, which will need
to include a strong ICT component. Once an innovation
leader in the mobile industry, Canada still relies heavily
on mining and medium-technology sectors. Improving
businesses’ adoption of ICTs (22nd) can be a powerful
driver of innovation for the country.
Germany drops two spots this year to 15th place,
despite a slight improvement in its absolute score.
Although businesses operate in a very good regulatory
environment (16th), more can be done to support new
firms—for example, by reducing further the number
of days and procedures required to start a business.
Germany’s infrastructure and skills base is one of the best
in the world, while fixed broadband prices are high and
rising. Individual adoption and usage is increasing further,
although it is not moving fast enough to move Germany
up in the rankings on this dimension. Germany is one of
the highest-scoring countries for business usage (6th),
yet the government is not yet using digital technologies to
their full potential (30th); that said, executives feel that the
government is starting to develop a stronger digital vision.
A big positive jump is registered this year for the impact of
ICTs on access to basic services.
With a stable overall score, Australia slips two spots
to 18th position. Improvements in terms of Environment
(16th, up one) are outweighed by a deterioration of the
country’s level of Readiness, especially when it comes to
affordability (57th), where fixed broadband subscriptions
remain particularly expensive (US$46.7 PPP per
month, ranked 100th worldwide). Individual usage has
also increased in the country, with mobile broadband
subscriptions largely widespread (10th highest penetration
in the world) and more common than fixed ones (25th).
The Australian government and public sector are among
the leaders in the world in providing online services (8th)
and allowing citizens’ e-participation (7th), but there is
room for improvement in the level of businesses’ adoption
of ICTs (28th), as the country still relies heavily on mining
industries. The country’s National Innovation and Science
Agenda, launched in December 2015, if fully implemented,
might help to orient Australia’s economy more toward
innovation, bridging some of the gaps, especially in
venture capital availability (40th worldwide) and the
creation of new business models via ICTs (41st).
With an improvement of performance across the
board, France climbs up two positions to 24th place.
Government and businesses are pushing the frontier
of networked readiness in the country. France is the
global leader in delivering public online services to its
citizens and one of the best in terms of allowing their
e-participation to the government’s decision process
(4th). Over the past year, the government has also
increased efforts in promoting ICTs and providing
a long-term vision for the sector, including a Digital
Republic Bill aiming to guide the way in which the ICT
revolution will shape French society in the future. French
businesses have also stepped up their efforts to leverage
ICTs, especially in terms of adopting new organizational
models (26th, up 22 positions) and improving B2B
transactions (33rd, up 11). The country can rely on
a skilled workforce (18th) and on good infrastructure
(22nd), allowing, among other things, one of the highest
penetrations in the world of fixed broadband (4th). Issues
remain especially in the business environment, which
has one of the highest taxation rates in the world—62.7
percent—although on a slowly declining trend.
The United Arab Emirates continues to lead the
Arab world in terms of networked readiness in 26th
position. The government is leading the way to greater
digital connectivity (2nd in terms of government usage),
providing a consistent vision for the sector and achieving
success at promoting it (1st on both indicators).
Individual usage has also further improved (19th, up
one spot) especially in terms of mobile broadband
subscriptions and households with Internet access,
although other important ICT services are not yet widely
available: in 2014, fixed broadband subscriptions were
still 11.6 per 100 people. Businesses’ adoption of and
the economic impacts of ICTs have been improving in
recent years, but a gap still exists with most advanced
economies in this area. Patent activity, both general and
ICT-related, remains relatively low.
Malaysia’s overall position in the NRI has
remained largely stable in recent years, with the
country climbing one spot to 31st position in 2016.
This strong performance continues to be supported
by a government that is fully committed to the digital
agenda and that is seen to be ahead of its peers in
terms of adopting the latest technologies. With
approximately two-thirds of the population online,
individual usage is growing further (47th, up 10 spots);
in particular, the uptake of mobile broadband has taken

off and reached almost 60 percent. An agile business
sector (26th for business usage) is using ICTs to its
advantage, interacting with consumers online and
re-optimizing business models and organizational
structures, thereby contributing to the overall strong
performance. An increase in international Internet
bandwidth (currently ranked 81st) combined with a
drop in broadband prices (110th) would give a further
boost to Malaysia’s digital economy.
Saudi Arabia climbs up two positions to 33rd this
year. The government is leading the way to increased
networked readiness, promoting ICTs in the country;
however, individual usage (21st) and business adoption
(42nd) are still lagging behind. Affordability of ICTs (101st)
and the general level of skills in the workforce (49th)
remain an issue, with only 64 percent of the population
using the Internet on a regular basis. Allowing further
means of e-participation (51st) might contribute to
spurring individual ICT adoption. The business and
innovation environment is hampered by one of the most
complex and lengthy processes in the world to start a
business (125th and 97th, respectively), which reduces
access to the market of potential new and innovative
competitors. Saudi Arabia remains an oil-based
economy, with low patenting activity in both general
technology and ICTs. A transition to a more innovation-
driven economic model will require improvements
in the country’s ICT readiness, with a broad-based
participation of the population and of the business
community in the digital revolution.
The Russian Federation remains in 41st place
this year, as in 2015. The country places in the top third
of the rankings for Readiness, Usage, and Impact, yet
continues to be held back by a weak and deteriorating
regulatory environment. As mobile and fixed Internet
tariffs are very low and dropping further (10th place
overall on affordability), individual usage continues to
rise in almost every dimension, leaving Russia in 40th
place in this category. However, the data suggest that
infrastructure build-out is not keeping up with demand
as Russia sees its availability of Internet bandwidth per
user falling. Although Russia is close to the median in
terms of business use overall, online sales to consumers
(as opposed to other firms) are particularly strong (35th
place). The positive impact of ICTs is felt both in the
economic and the social dimensions, as reflected in
rankings in the top third for both impact pillars.
Turkey’s overall ranking and score remains
unchanged from last year at 48th place, yet this fact
masks strong conflicting movements at the pillar
level. With some of the cheaper mobile and fixed
Internet tariffs around and improving digital skills in the
population, individual usage is broadening further. Yet
these positive movements are offset by a deteriorating
regulatory and business environment as well as the
declining importance of ICTs in the government’s vision
and promotion. Overall, the negative effects seem to
outweigh the positive ones, with economic impacts and
particularly social outcomes suffering. Turkey, however,
remains in the top third of the rankings in terms of its
business and innovation environment, a good basis from
which to push further ahead.
China moves up by three places to 59th based
on improvements in Usage and Impact. Adoption by
individuals has increased, particularly in terms of mobile
broadband subscriptions, which nearly doubled in one
year from 21.4 to 41.8 per 100 population. Chinese
businesses will need to step up their efforts to embrace
digital technologies and spur innovative processes
for the country to become an innovation-driven, high-
income economy. Although patenting activity has
increased significantly in recent years, it is still relatively
low compared with that of advanced economies, and
the full economic and social impacts of ICTs are still in
the process of materializing. The business environment
remains one of the key bottlenecks (104th): according
to World Bank data, China maintains high taxation
on businesses (67.8 percent) and has lengthy and
complex processes to set up a new business (121st
and 120th, respectively), discouraging new and more
competitive firms from entering the market. Recognizing
the challenge, the government is currently implementing
a reform program to streamline business procedures
across the country. The full results of these reforms will
be reflected in future assessments.
Colombia maintains the same score as last year,
but slips four ranks to 68th because other countries
improved their performances. ICT adoption among the
population kept increasing at a fast rate: there were 45.1
mobile broadband subscriptions per 100 people in 2014,
up from 25.0 in 2013 and 3.7 in 2011. This increase in
individual usage has not been matched by a similar
trend among businesses or within the government. The
extent of usage of ICTs for B2B and B2C operations
as well as for the creation of new business models has
been stagnating in past years. The overall political and
business environment in the country remains its main
weakness, with low effectiveness of law-making bodies
(121st) and an inefficient judicial system (1,288 days are
required to enforce a contract, ranking 133rd in the world
in this indicator). Taxation also remains disproportionately
high, at a rate of 69.7 percent (6th highest among the
countries in the sample).
Brazil comes in at 72nd place this year, partially
reversing the strong downward trend of recent years.26
ICT adoption and usage by both individuals and the
business community is good and supported by very
good affordability—in particular, cheap fixed broadband
Internet connections (14th). Brazil makes large strides in
terms of improving individual usage this year, climbing
five places to 57th—this is a considerable achievement,
given that other countries are also moving quickly on
individual adoption. Yet networked readiness in the
country continues to be held back by a weak regulatory

environment. The business and innovation environment
is also ranked as one of the weakest in the world (124th),
with both venture capital availability and government
technology procurement falling further. Government
support of the ICT agenda is perceived to be weak and
the business community sees the government as failing
to deliver in terms of incorporating digital technologies
in their overall strategy (121st) as well as in the direct
promotion of ICT (122nd).
Indonesia moves up six spots to 73rd place this
year, driven in part by improvements in affordability and
an accompanying strong rise in individual usage (92nd,
up five spots). In order to capitalize on this positive trend,
infrastructure will need to keep up; as the number of
users is increasing, the existing infrastructure is starting
to be stretched, which has the country dropping seven
spots to rank 105th in this particular pillar. Business and
government usage are already high at 34th and 65th
rank, with a flat trend line for business and one that has
been slightly on the decline for government. Although
momentum across pillars is somewhat heterogeneous,
a recently reformed regulatory (65th) and business
environment (64th) provide a good basis for building out
the digital economy, as long as recent backward slides
for some important indicators are reversed (legislative,
legal system, availability of latest technologies, and
number of procedures to start a business).
Mexico places 76th in the NRI overall this year.27
Individual usage (84th) is rising further; in particular,
mobile broadband subscriptions are becoming
increasingly popular and individual usage is thus
catching up with business usage (66th) and government
usage (52nd). Although government use of ICTs was
already considered relatively strong in the 2015 NRI,
Mexico moves up 13 places in government ICT vision
this year, to 71st; importantly, the government makes
good use of ICTs to interact with the population, ranking
35th on the government services index. At the same
time, the regulatory environment is perceived to have
deteriorated along several lines, such as the efficiency
of the legal system in settling disputes (104th) and
challenging regulations (102nd). Economic impact is
on an upward trajectory and Mexico is edging back on
the social impacts ranking, having been overtaken by a
significant number of countries between 2014 and 2015.
Rwanda climbs three spots this year to 80th
position, driven by a government that is very focused
on the digital agenda. The government is also making
strong efforts to provide a stable regulatory framework,
resulting in an improvement of five ranks in the
Environment subindex. The private sector is making large
strides in terms of adopting digital technologies, moving
up 10 places to 60th rank for business usage. Individual
adoption is still lagging (127th) as mobile fees and
broadband prices remain high; efforts to provide Internet
access in schools is an important step in the direction of
boosting social gains, providing the next generation with
important digital skills. In general, the social impact of
digital technologies is being felt, in particular with regard
to giving access to basic services.
Argentina continues on its upward trajectory,
ranking 89th this year. Weak (though improving)
regulatory and innovation environments seem to be
the two biggest bottlenecks preventing larger gains
from digital technologies. With mobile phone use one
of the highest in the world (13th) and an overall solid
adoption rate among individuals, businesses are making
use of digital technologies to transact with consumers
(76th), yet B2B ICT use remains low (120th). There is
also much room for greater public-sector adoption
of digital technologies: although the Argentinian
government seems to be making good use of ICTs to
provide services to the population (55th), the business
community in 2015 perceived the government as lacking
in vision and effort when it comes to ICT promotion. Yet
the recent change in government looks ready to bring
renewed momentum to the digital agenda. Consistent
with previous years, Argentina does not have data in
the affordability pillar because of the lack of reliable
PPP estimates.
Despite of improvements in its political and
regulatory environment (78th, up four) and in its business
and innovation environment (110th, up five), India slips
down two positions to an overall rank of 91. Although
India’s absolute score has changed only marginally in
recent years, the drop can be attributed in part to the
fact that other countries are moving ahead at higher
speeds. In addition, lack of infrastructure (114th) and low
levels of skills among the population (101st) remain the
key bottlenecks to widespread ICT adoption, especially
in terms of individual usage (120th). A third of the Indian
population is still illiterate (95th) and a similar share of
youth is not enrolled in secondary education (103rd).
Only 15 out of 100 households have access to the
Internet and mobile broadband remains a privilege of the
few, with only 5.5 subscriptions for every 100 people.
This is in spite of the fact that affordability has long been
one of the strengths of the Indian ICT ecosystem, with
the country ranking 8th this year in this area. A deep
divide persists between well-connected metropolitan
hubs and remote rural areas, where even the most basic
infrastructure is insufficient. In 2015 the government
launched the Digital India program, which aims to close
this gap by fostering investment in digital infrastructure,
improving digital literacy, and increasingly providing
online services to citizens. India’s performance in terms
of providing online services and allowing e-participation
has so far been in line with that of peer countries, but far
from the global best (57th and 40th, respectively).
Although Nigeria did not move overall in the NRI
rankings, staying in 119th position, this fact masks
significant heterogeneity in terms of moves in individual
dimensions of networked readiness—in particular, a
six-spot move up in Readiness (to 117th) and a ten-spot

move down in Impacts (to 114th). The improvement in
Readiness is to a large extent thanks to Nigeria reaching
full mobile coverage this year; broadband prices have
also fallen slightly, although they remain high. The
political and regulatory environment are perceived to
be improving on several fronts, while at the same time
the business and innovation environment are perceived
as deteriorating. Government usage and engagement
is perceived to have dropped significantly over the
course of the last year, yet this may change under the
new government that came to power in 2015. Overall,
conditions for ICT impacts seem to have deteriorated:
both economic and social impacts record a decline. A
policy priority with far-reaching benefits in other areas
should be to address the country’s skills gap (134th).
CONCLUSIONS
The picture that emerges from this year’s analysis gives
reason for optimism but not for complacency. Although
there are still large heterogeneities across countries
in terms of networked readiness, the overall trend is
positive across all regions of the world.
In particular, individual adoption is growing steadily
across the globe as efforts continue to close the digital
divide. Business executives are optimistic about their
countries’ growing innovation capacities, yet the digital
innovation impact is so far coming through much more
strongly in some countries than in others—the gap
between seven digital front runners and the followers
is wide. The analysis identifies a high level of business
adoption and usage of digital technologies as one of the
key characteristics of countries in which ICTs are having
a robust economic and digital innovation impact. In most
countries, businesses are perceived to be moving at
only a moderate pace in truly embracing all dimensions
of digitization—in their relations upstream with suppliers
and downstream with consumers. This process will need
renewed momentum if firms are hoping to thrive in the
Fourth Industrial Revolution.
Although government use and promotion of ICTs
has recently started to fall short of expectations across
regions, a number of countries are making large strides
in the Index thanks to a strong government ICT vision
and engagement in the digital economy. Overall,
governments can do more to drive the social impact
of digital technologies—for example, by using them to
make basic government services more accessible. As
technologies are rapidly evolving and can be expected to
have a profound impact on our economies and societies,
new governance structures will also urgently need to be
put in place in order to channel technological forces in
ways that bring broad-based gains to societies.
NOTES
1 Varian 2010.
2 Owen et al. 2012.
3 For instance, the prevalence of Internet in schools would ideally
be measured by computing the percentage of a country’s
schools that have Internet access. Similarly, the intensity of
competition would ideally be measured by computing a business
concentration index (Herfindahl–Hirschman Index). In both cases,
however, such statistics are not available for enough countries.
4 Eurostat and OECD 2005, p. 46; cited in Dutta et al. 2015.
5 Varian 2010.
6 For additional detailed case study evidence, see http://reports.
weforum.org/digital-transformation-of-industries/go-to-the-case-
studies/.
7 Mettler and Williams 2011, pp. 26–27.
8 Positive network effects arise from the fact that a larger number of
participants will lead to better and more frequent matches, which
in turn means higher value creation, making it more attractive still
for new participants to join.
9 Fox 2014.
10 Christensen 2012.
11 The change in the mean of the score distribution from 2015 to
2016 is positive and significantly different from zero at the 10
percent level.
12 BCG 2015. In addition, the following factors are often cited
as critical for innovation in the Digital Age: capitalizing on the
Internet of Things, high-quality broadband, increasing automation
and autonomy of production, a tech savvy and experimenting/
risk-loving customer base, availability of venture capital, and a
government that puts in place rules that inspire trust in the system
(World Economic Forum/Accenture, 2016).
13 See INSEAD’s Global Talent Competitiveness Index, which in its
2017 edition will focus on technology and talent: http://global-
indices.insead.edu/gtci/.
14 Fox 2014.
15 Autor 2010.
16 World Economic Forum 2016b.
17 Sundararajan 2016.
18 For example, these principles are embedded in the Europe 2020
strategy to create smart growth and the Horizon 2020 program
that defines tackling societal challenges as one of the main
priorities; see also, for example, Owen et al. 2012.
19 von Schomberg 2011.
20 Lund Declaration 2009.
21 European Commission 2012.
22 See the European Union’s Founding Principles of the Union,
available at http://europa.eu/scadplus/constitution/objectives_
en.htm.
23 United Nations 2000.
24 Note that the improvement in readiness is largely the result of a
large drop in fixed broadband tariffs; this drop occurred between
2014 and 2015, yet was not reflected in the data collected for the
2015 edition of the NRI. The price correction was made by the ITU
after the publication of the NRI in 2015.
25 ITU 2015.
26 Although there has been an upward movement in the NRI
rankings for Brazil this year, this is to some extent the result of a
reinstatement of indicator 5.03 (secondary education enrollment
rate), which was not available last year.
27 Note that Mexico is seeing a deterioration in its assessment of
Readiness this year because of the way in which the pricing of
broadband access is captured. The ITU reports the price of the
cheapest package provided by the market leader. The reported
price increase came at the same time as an increase in broadband
speed included in the package, so it can to some extent be
attributed to an increase in quality; nevertheless, accessibility is
reduced, which is what the rank move reflects.

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weforum.org/docs/WEF_WhitePaper_GAC_Digital_Media_
Readiness_Framework.pdf.
———. 2016e. Social Innovation: A Guide to Achieving Corporate and
Societal Value, prepared in collaboration with Oliver Wyman.
Geneva: World Economic Forum. http://www3.weforum.org/docs/
WEF_Social_Innovation_Guide.pdf.

The Global Information Technology Report series and the
Networked Readiness Index (NRI) were launched by the
World Economic Forum in 2001. This represented one
of the first attempts to make conceptual sense of the
complex information and communication technologies
(ICT) reality, identifying the common factors that enable
countries to use technology effectively. The networked
readiness framework that underpins the NRI was
intended to provide guidance for policymakers and civil
society on the factors that they need to take into account
to fully leverage ICTs in their growth strategies.
The economic literature has largely established the
fundamental role of innovation in boosting long-term
productivity and growth. Although networked readiness
represents only one ingredient in the innovation process,
it has become an increasingly important one. Several
studies have established the link between ICTs and
productivity gains, especially in advanced economies.1
This will be particularly important in the next decades
as the Fourth Industrial Revolution transforms the
way economies work and the way societies organize
themselves.
The impact of ICTs on our lives goes well beyond
their effects on productivity and growth; they also act
as a vector of social development and transformation.
ICTs can improve access to basic services, enhance
connectivity, and create new employment opportunities.
Ultimately, ICTs hold significant potential to improve the
quality of people’s lives and to enhance the way they live,
communicate, interact, and engage among themselves
and with their governments.
In recent years, the emphasis has moved from
the issue of ensuring access to the question of how to
make the best use of ICTs in order to improve business
innovation, governance, citizens’ political participation,
and social cohesion. In light of this shift in emphasis,
and after two years of research and consultations with
experts, the Impact subindex was added to the NRI
framework in 2012.2
Yet there is still room to improve
the way we measure the actual impact of ICTs because
the availability of data remains limited to only some of
the relevant areas of impact. In addition, the complex
relationships between ICTs and socioeconomic
performance are not fully understood and their causality
not fully established. However, our hope is to highlight
the opportunities offered by ICTs and provide an
indication of the ways they are transforming economies
and societies around the world.
The networked readiness framework, briefly outlined
in the chapter, rests on six principles:
• A high-quality regulatory and business environment
is critical in order to fully leverage ICTs and generate
impact.
• Similarly, ICT readiness—as measured by ICT
affordability, skills, and infrastructure—is a pre-
condition to generating impact.
• Fully leveraging ICTs requires a society-wide effort.
All stakeholders—the government, the business
sector, and the population at large—have a role to
play.
• ICT use should not be an end in itself. The impact
that ICTs actually have on the economy and society
is what ultimately matters.
• The set of drivers—the environment, readiness, and
use—interact, co-evolve, and reinforce each other
to create greater impact. In turn, greater impact
creates more incentives for countries to further
improve their framework conditions, their readiness
for ICTs, and their use of ICTs, thus creating a
virtuous cycle. Conversely, weaknesses in any
particular dimension are likely to hinder progress in
others.
• Finally, the networked readiness framework should
provide clear policy guidance.
STRUCTURE OF THE NETWORKED READINESS
INDEX
The networked readiness framework translates into the
NRI, a composite index made up of four main categories
(subindexes), 10 subcategories (pillars), and 53 individual
indicators distributed across the different pillars. The full
list of indicators, grouped by pillars and subindexes, is
provided below.
In this list, the number preceding the period
indicates the pillar to which the variable belongs (e.g.,
Appendix:
The Networked Readiness Index framework: A methodological note

indicator 2.05 belongs to the 2nd pillar; indicator 8.03
belongs to the 8th pillar). The numbering of the indicators
matches the numbering of the data tables at the end of
the Report.
The computation of the NRI is based on successive
aggregations of scores, from the indicator level (i.e., the
most disaggregated level) to the overall NRI score (i.e.,
the highest level). Scores for indicators derived from
the World Economic Forum’s Executive Opinion Survey
(the Survey) are always measured on a 1-to-7 scale
and therefore do not require transformation prior to
aggregation. These are identified in the list of indicators
by an asterisk (*). All the other indicators come from
external sources, as described in the Technical Notes
and Sources section at the end of the Report. In order to
align them with the Survey’s results, we apply a min-max
transformation, transforming them into a 1-to-7 scale.3
Unless noted otherwise, we use an arithmetic mean
to aggregate individual indicators within each pillar
and also for higher aggregation levels (i.e., pillars and
subindexes).4
Throughout the Report, scores in the various
dimensions of the NRI pillars are reported with a precision
of one decimal point. However, exact figures are always
used at every step of the computation of the NRI.
A description of each subindex and pillar are provided
below, along with the rationale for their inclusion.10
Environment subindex
The success of a country in leveraging ICTs depends in
part on the quality of the overall operating environment.
The Environment subindex therefore assesses the extent
to which a country’s market conditions and regulatory
framework support entrepreneurship, innovation, and ICT
development.
The Political and regulatory environment pillar (nine
indicators) assesses the extent to which a country’s
political and regulatory environments facilitate ICT
penetration and the development of business activities. It
does so by measuring the extent of intellectual property
rights protection, the prevalence of software piracy,
the efficiency and independence of the judiciary, the
efficiency of the law-making process, and the overall
quality of regulations pertaining to ICTs.
The Business and innovation environment pillar
(nine indicators) gauges the extent to which the business
environment supports entrepreneurship by taking into
account measures of red tape, the ease of starting a
business, and taxation. It also measures the conditions
that allow innovation to flourish by including indicators
on the overall availability of technology, the intensity
of competition, the demand conditions for innovative
products (as proxied by the development of government
procurement of advanced technology products), and
the availability of venture capital for funding innovation-
related projects.
Readiness subindex
The Readiness subindex measures the extent to which a
country has in place the infrastructure and other factors
to support the uptake of ICTs.
The Infrastructure pillar (four indicators) captures
the state of a country’s ICT infrastructure as well as
infrastructure that matters for ICT development: mobile
network coverage, international Internet bandwidth,
secure Internet servers, and electricity production.
The Affordability pillar (three indicators) assesses the
affordability of ICTs in a country through measures of
mobile telephony usage costs and broadband Internet
subscription costs, as well as an indicator that assesses
the state of liberalization in 17 categories of ICT services,
because more intense competition tends to reduce retail
prices in the long run.
The Skills pillar (four indicators) measures the
capacity of the population to make effective use of ICTs
by taking into account the enrollment rate in secondary
education, the overall quality of the education system,
and of mathematics and science education in particular,
and the adult literacy rate.
Usage subindex
The Usage subindex assesses the level of ICT adoption
by a society’s main stakeholders: government,
businesses, and individuals.
The Individual usage pillar (seven indicators)
measures the level of diffusion of selected ICTs among a
country’s population, using mobile telephony penetration,
Internet usage, personal computer ownership, and the
use of social networks.
The Business usage pillar (six indicators) captures
the extent to which businesses in a country use the
Internet for business-to-business (B2B) and business-
to-consumer (B2C) operations, as well as their efforts to
integrate ICTs in their operations. It also measures the
capacity of firms to come up with new technologies by
taking into account the number of patent applications
under the Patent Cooperation Treaty (PCT). Finally, it
measures the extent of staff training as a proxy for the
capacity of management and staff to innovate.
The Government usage pillar (three indicators)
assesses the leadership and success of the government
in developing and implementing strategies for ICT
development, as well as in using ICTs, as measured by
the availability and quality of government online services.
Impact subindex
The Impact subindex gauges the broad economic
and social impacts accruing from ICTs.
The Economic impacts pillar (four indicators)
measures the effect of ICTs on competitiveness
through technological and non-technological
innovations in a country—as measured by the
number of patent applications as well as by the

NETWORKED READINESS INDEX 2016
Networked Readiness
Index = 1/4 Environment subindex
+ 1/4 Readiness subindex
+ 1/4 Usage subindex
+ 1/4 Impact subindex
Environment subindex = 1/2 Political and regulatory
environment
+ 1/2 Business and innovation
environment
1st pillar: Political and regulatory environment
1.01 Effectiveness of law-making bodies*
1.02 Laws relating to ICTs*
1.03 Judicial independence*
1.04 Efficiency of legal system in settling disputes*5
1.05 Efficiency of legal system in challenging
regulations*5
1.06 Intellectual property protection*
1.07 Software piracy rate, % software installed
1.08 Number of procedures to enforce a contract6
1.09 Number of days to enforce a contract6
2nd pillar: Business and innovation environment
2.01 Availability of latest technologies*
2.02 Venture capital availability*
2.03 Total tax rate, % profits
2.04 Number of days to start a business7
2.05 Number of procedures to start a business7
2.06 Intensity of local competition*
2.07 Tertiary education gross enrollment rate, %
2.08 Quality of management schools*
2.09 Government procurement of advanced technology
products*
READINESS SUBINDEX
Readiness subindex = 1/3 Infrastructure
+ 1/3 Affordability
+ 1/3 Skills
3rd pillar: Infrastructure
3.01 Electricity production, kWh/capita
3.02 Mobile network coverage, % population
3.03 International Internet bandwidth, kb/s per user
3.04 Secure Internet servers per million population
4th pillar: Affordability8
4.01 Prepaid mobile cellular tariffs, PPP $/min.
4.02 Fixed broadband Internet tariffs, PPP $/month
4.03 Internet and telephony sectors competition index, 0–2
(best)
5th pillar: Skills
5.01 Quality of education system*
5.02 Quality of math and science education*
5.03 Secondary education gross enrollment rate, %
5.04 Adult literacy rate, %
USAGE SUBINDEX
Usage subindex = 1/3 Individual usage
+ 1/3 Business usage
+ 1/3 Government usage
6th pillar: Individual usage
6.01 Mobile phone subscriptions per 100 population
6.02 Percentage of individuals using the Internet
6.03 Percentage of households with computer
6.04 Households with Internet access, %
6.05 Fixed broadband Internet subscriptions per 100
population
6.06 Mobile broadband Internet subscriptions per 100
population
6.07 Use of virtual social networks*
7th pillar: Business usage
7.01 Firm-level technology absorption*
7.02 Capacity for innovation*
7.03 PCT patent applications per million population
7.04 ICT use for business-to-business transactions*9
7.05 Business-to-consumer Internet use*9
7.06 Extent of staff training*
8th pillar: Government usage
8.01 Importance of ICTs to government vision*
8.02 Government Online Service Index, 0–1 (best)
8.03 Government success in ICT promotion*
IMPACT SUBINDEX
Impact subindex = 1/2 Economic impacts
+ 1/2 Social impacts
9th pillar: Economic impacts
9.01 Impact of ICTs on business models*
9.02 ICT PCT patent applications per million population
9.03 Impact of ICTs on organizational models*
9.04 Knowledge intensive jobs, % workforce
10th pillar: Social impacts
10.01 Impact of ICTs on access to basic services*
10.02 Internet access in schools*
10.03 ICT use and government efficiency*
10.04 E-Participation Index, 0–1 (best)

role of ICTs in the development of new products,
processes, and organizational models. It also measures
the overall shift of an economy toward more knowledge-
intensive activities.
The Social impacts pillar (four indicators) aims
to assess a country’s societal progress brought
about or enhanced by the use of ICTs. Such progress
includes—but is not limited to—access to education
and healthcare, energy savings, and more-active civil
participation. Currently, because of data limitations,
this pillar focuses on assessing the extent to which
ICTs allow access to basic services (education,
financial services, and healthcare); the use of the
Internet at school, as a proxy for the potential benefits
that are associated with the use of ICTs in education;
the impact of ICTs on government efficiency; and the
quality and usefulness of information and services
provided by a country for the purpose of engaging
its citizens in public policymaking through the use of
e-government programs.
Measuring the impacts of ICTs remains a complex
task, and the development of rigorous, international
comparable statistics is still in its infancy. As a result,
many of the areas where ICTs have a significant
impact—especially those where the impact does not
translate directly into commercial activities, as is the
case in environment, healthcare, and education—are
not captured in the NRI. Therefore the Impact subindex
should be regarded as work in progress.
METHODOLOGY AND DATA
The structure of the NRI is unchanged from the
previous edition.
About half of the 53 individual indicators used in the
NRI are sourced from international organizations. The
main providers are the International Telecommunication
Union (ITU); the World Bank; the United Nations
Educational, Scientific and Cultural Organization
(UNESCO); and other UN agencies. Carefully chosen
alternative data sources, including national sources, are
used to fill data gaps in certain cases. The other half of
the NRI indicators are derived from the World Economic
Forum’s annual Survey. The Survey is used to measure
concepts that are qualitative in nature or for which
internationally comparable statistics are not available for
enough countries.11
The Survey is administered annually to over 14,000
business executives in all the economies included in the
NRI (see Browne et al. 2015 for more details). The Survey
represents a unique source of insight into many critical
aspects related to a country’s enabling environment,
such as the extent of red tape and the degree of
intellectual property protection; aspects related to the
preparedness of its population, such as the quality of the
education system; to ICT usage, such as its capacity to
innovate and the importance of its government’s vision
for ICTs; and to ICT impacts, such as the contribution of
ICTs to the development of new products and services
and to improving access to basic services.
Some of the indicators composing the Index are
subject to significant changes in value from one year to
the next. In particular, the two price measures (indicators
4.01 and 4.02) used to calculate the affordability pillar
score can reflect changes in both the benchmarks used
by the ITU and in the Purchasing Power Parity (PPP)
estimates sourced from the World Bank. Although there
have been no changes to the PPP methodology this
year (the conversion factor used is still based on the
International Comparison Program 2011),12
figures for
the costs in local currencies of four different services
provided by the ITU have changed significantly for some
countries.
For two indicators, the number of missing data
points remains very high. Indicators 1.07 Software
piracy rate and 9.04 Share of workforce employed in
knowledge-intensive jobs are missing data for 35 and
29 economies, respectively, and were not included the
calculation for those economies. For each of the other
53 indicators of the NRI, the number of missing data
points does not exceed four. In addition, in the absence
of data on the adult literacy rate (indicator 5.04) for as
many as 22 Organisation for Economic Co-operation
and Development (OECD) member countries and Hong
Kong SAR, a value of 99 percent was assumed for the
purpose of calculating the Skills pillar score.
COUNTRY COVERAGE
The inclusion of an economy depends on the availability
and quality of indicators. To be included in the NRI,
the number of missing (or outdated) data points for
an economy cannot reach five, or 10 percent of all
indicators. Because almost half of the indicators entering
the NRI are derived from the Executive Opinion Survey,
which is the basis for the Global Competitiveness
Report (GCR), the coverage of a country in the GCR
is a necessary—but not a sufficient—condition for a
country’s inclusion in the NRI.
NOTES
1 Draca et al. 2006; Cardona et al. 2013.
2 Dutta et al. 2012.
3 Formally, we have:
6 x
country score – sample minimum
+ 1
(sample maximum – sample minimum )
The sample minimum and sample maximum are, respectively, the
lowest and highest country scores in the sample of economies
covered by the GCI. In some instances, adjustments were made
to account for extreme outliers. For those indicators for which
a higher value indicates a worse outcome (i.e., indicators 1.07,
1.08, 1.09, 2.03, 2.04, 2.05, 4.01, and 4.02), the transformation
formula takes the following form, thus ensuring that 1 and 7
still corresponds to the worst and best possible outcomes,
respectively:

–6 x
country score – sample minimum
+ 7
(sample maximum – sample minimum )
4 Formally, for a category i composed of K indicators, we have:
When two individual indicators are averaged (e.g., indicators 1.04
and 1.05 in the 1st pillar), each receives half the weight of a normal
indicator.
5 For indicators 1.04 and 1.05, the average of the two scores is
used in the computation of the NRI.
6 For indicators 1.08 and 1.09, the average of the two normalized
scores is used in the computation of the NRI.
7 For indicators 2.04 and 2.05, the average of the two normalized
scores is used in the computation of the NRI.
8 The affordability pillar is computed as follows: the average of
the normalized scores of indicators 4.01 Prepaid mobile cellular
tariffs and 4.02 Fixed broadband Internet tariffs is multiplied
by a competition factor, the value of which is derived from
indicator 4.03 Internet and telephony sectors competition index.
It corresponds to the score achieved by an economy on this
indicator normalized on a scale from 0.75 (worst) to 1.00 (best),
using the min-max transformation described above. A normalized
score of 0.75 is assigned to an economy with a competition index
score of 0, which means that a monopolistic situation prevails in
the 17 categories of ICT services considered. A normalized score
of 1.00 is assigned to an economy where all 17 categories are
fully liberalized. Where data are missing for indicator 4.03 (i.e.,
Mongolia and Venezuela), the score on the affordability pillar,
which is simply the average of the normalized scores of indicators
4.01 and 4.02, is used. The competition index score for Chinese
Taipei was derived from national sources.
9 For indicators 7.04 and 7.05, the average of the two scores is used
in the computation of the NRI.
10 See Dutta et al. 2012 for a more detailed description of each
component.
11 For instance, the prevalence of Internet in schools would ideally
be measured by computing the percentage of a country’s
schools that have Internet access. Similarly, the intensity of
competition would ideally be measured by computing a business
concentration index (Herfindahl–Hirschman Index). In both cases,
however, such statistics are not available for enough countries.
12 See http://icp.worldbank.org/ for more information about PPP and
the 2011 revision.
REFERENCES
Browne, C., A. Di Battista, T. Geiger, and T. Gutknecht. 2015. “The
Executive Opinion Survey: The Voice of the Business Community.”
In The Global Competitiveness Report 2015–2016. K. Schwab,
editor. Geneva: World Economic Forum. 75–85.
Cardona, M., T. Kretschmera, and T. Strobel. 2013. “ICT and
Productivity: Conclusions from the Empirical Literature.”
Information Economics and Policy 25 (3): 109–25.
Draca, M., R. Sadun, and J. Van Reenen. 2006. “Productivity and ICT: A
Review of the Evidence.” CEP Discussion Paper No. 749. Centre
for Economic Performance (CEP). August.
Dutta, S., B. Bilbao-Osorio, and T. Geiger. 2012. “The Networked
Readiness Index 2012: Benchmarking ICT Progress and Impacts
for the Next Decade.” In The Global Information Technology
Report 2012. S. Dutta and B. Bilbao-Osorio, editors. Geneva:
World Economic Forum. 3–34.
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CHAPTER 1.2
Cross-Border Data Flows,
Digital Innovation, and
Economic Growth
Robert Pepper
John Garrity
Connie LaSalle
CISCO SYSTEMS
Forty years ago, the queen of England became one
of the first individuals, and the first head of state, to
transmit real-time electronic data over national borders.1
In 1976, just three years after the United States
connected ARPANET to London’s University College and
the Royal Radar Establishment in Norway, Her Majesty
Queen Elizabeth II sent an email under the username
“HME2.”2
Today over 3.2 billion people across the world
have access to and use the Internet, and the flow of
digital communication between countries, companies,
and citizens, as a component of the “knowledge
economy,” has been recognized for years as a critical
driver of economic growth and productivity.3
Countries
adept at fostering digital activity have witnessed the
emergence of new industries as well as the accelerated
development of traditional sectors.4
However, despite
the intensive and extensive growth of the global Internet,
concerns over growing barriers to digital flows are
mounting.
This chapter explores the impact of the free flow
of data across national borders on innovation and
growth. First reviewed is the literature on the impact
of cross-border data flows on countries, companies,
and individuals. The chapter then presents an original
analysis of the growth of new services built on the free
flow of trade through global digitization, and concludes
by discussing policy guidelines that mitigate national
concerns over data transmission while simultaneously
maximizing the benefits of cross-border data flows.
THE GROWTH OF GLOBAL DIGITAL INDUSTRIES
AND THEIR NATIONAL ECONOMIC IMPACTS
The development of the commercial Internet has
occurred concurrently with a massive expansion of the
global economy, which has experienced 6.6-fold growth
in nominal terms—from US$11.1 trillion to US$73.5
trillion since 1980.5
Internet protocol (IP) traffic continues
to advance rapidly, with 2019 traffic projected to be
64 times its 2005 volume.6
Global Internet bandwidth
accounts for much of this growth, more than quadrupling
between 2010 (<50 terabytes per second) and 2014
(>200 terabytes per second).7
More importantly, total
cross-border Internet traffic increased 18-fold from 2005
to 2012.8
This cumulative growth impacts all facets of national
economies, not just their budding technology sectors—in
fact, an estimated 75 percent of the Internet’s benefit
is captured by companies in traditional industries.9
A
wide range of positive economic impacts stems from
the flow of digital data across borders. For example, 61
percent (US$383.7 billion) of total US service exports
were digitally delivered in 2012, and 53 percent of total
US imports were digitally delivered.10
In absolute terms,
the amount of digitally delivered exports and imports
is even larger in the European Union, which digitally
delivered US$465 billion in exports in 2012 and spent
US$297 billion on imports. Digital trade is credited with

1.2: Cross-Border Data Flows, Digital Innovation, and Economic Growth
an estimated increase in US gross domestic product
(GDP) of 3.4 percent to 4.8 percent in 2011 and with the
creation of up to 2.4 million jobs, according to the United
States International Trade Commission (US ITC).11
The
United Nations Conference on Trade and Development
(UNCTAD) also estimates that about 50 percent of all
traded services is enabled by innovation stemming from
the technology sector, which includes the facilitation of
cross-border data flows.12
According to a newly released
report by McKinsey & Company, data flows account for
US$2.8 trillion of global GDP in 2014 and “cross-border
data flows now generate more economic value than
traditional flows of traded goods.”13
Beyond this economic impact, the free flow
of data is, itself, a significant driver of innovation. It
allows the sharing of ideas and information and the
dissemination of knowledge as well as collaboration and
cross-pollination among individuals and companies.
Internet-enabled innovation requires an environment
that encourages individuals to experiment with new
uses of the Internet. In places with severe restrictions
that inhibit digital collaboration, people are less likely
to experiment and, as a result, innovation is less likely
to emerge. Countries with an open Internet tend to be
more innovative, as demonstrated in Figure 1, which
illustrates the relationship between a country’s ability
to share information and its capacity for innovation.
The figure demonstrates that countries with a higher
capacity to share data internationally (as reflected by a
high international Internet bandwidth capacity per capita)
tend to have a greater degree of national innovation as
well, quantified in the figure by each country’s score on
the 2015 Global Innovation Index, a leading measure
of innovation capacity at the country level, which is
calculated according to 79 different indicators.14
Additionally, a high degree of correlation is observed
between various measures of potential data flow at the
country level and outcome measures. One measure of
potential data flow is Freedom House’s 2015 Freedom
on the Net indicator, which measures 65 countries
0 100 200 300 400 500 600
0
10
20
30
40
50
60
70
80
Figure 1: Cross-border data traffic and national innovation, by country
Sources: Cornell University, INSEAD, and WIPO 2015; ITU 2015b.
Note: The Global Innovation Index (GII) scores range from 0 to 100 (best). Kb/s = kilobits per second.
2015GIIscore
International Internet bandwidth capacity per capita (Kb/s, 2014)
R2
= 0.61499
Table 1: Correlation coefficients
Sources: Cornell University, INSEAD, and WIPO 2015; Freedom House 2015; ITU 2015b; World Economic Forum 2015.
Note: The Freedom on the Net scores range from 0 to 100, where 0 = most free and 100 = least free. Thus a lower score (greater freedom) for a given country is correlated with higher innovation
and better economic outcomes.899
Country correlation coefficients
Measures of potential data flows
International Internet bandwidth Freedom on the Net (inverse scale; high to low)
Outcome measures
Global Innovation Index score 0.72 –0.49
2015 NRI Economic impacts pillar 0.71 –0.49

on the basis of obstacles to Internet access, limits on
content, and violations of user rights. When correlated
with the Economic impacts pillar of the 2015 Networked
Readiness Index’s Impact subindex (Table 1), which
serves as an outcome measure, a clear relationship is
demonstrated.
THE IMPACT OF CROSS-BORDER DATA FLOWS:
FIRMS AND THE ENGINE OF ECONOMIC ACTIVITY
Cross-border data flows acutely impact the ability of
firms to conduct business internationally.
In a recent report, Business Roundtable identifies
at least six different areas of activity whereby firms
may transmit data across national borders to support
business operations. These include interconnected
machinery, big data analytics, back-office consolidation,
supply-chain automation, digital collaboration, and cloud
scalability.15
See Box 1.
Cross-border flows (data and voice, in particular)
reduce costs related to both trade and transactions.
This includes customer engagement (finding and fulfilling
orders) as well as other operational costs associated
with doing business. One recent report by the US ITC
estimates that the Internet reduces trade costs by 26
percent on average.16
Additionally, small- and medium-
sized enterprises that utilize the Internet to trade on
global platforms have a survival rate of 54 percent, which
is 30 percent higher than that of offline businesses.
Furthermore, those small- and medium-sized firms
that are online are almost as likely to export as large
businesses.17
At the firm level, a multitude of specific examples
illustrate how the ability to transmit data internationally
improves firm operations and performance. For example,
Unilever, the consumer goods company with over
174,000 employees and operations across 190 countries,
has developed a global enterprise data warehouse
wherein it collects information from all of its operations
to deliver full visibility into the entire system. The primary
objective of this effort was to compile a comprehensive
consumer database, enabling analysis at the most
granular level possible. Additionally, aggregating
information on the firm’s operations helps identify
areas where lowering costs and improving business
performance can drive more affordable products for
consumers.18
Similarly, Rio Tinto, the mining company with
operations in over 40 countries across six continents,
collects real-time data from its trucks and drills, which
are then transmitted to its Processing Excellence Center
(PEC) in Brisbane, Australia. Active monitoring and real-
time adjustment of Rio Tinto’s operations have already
driven significant savings from operational efficiencies,
with more savings certain to follow on the heels of new
and emerging process innovation.19
At Cisco, the ability to transfer data across borders
optimizes the company’s operations. For example, the
In a 2015 report, Business Roundtable—an industry
group representing companies with $7.2 trillion in annual
revenues and 16 million employees—identified the following
six mechanisms by which cross-border data flows drive
business benefits to firms.
Interconnected machinery. Companies improve
processes and optimize efficiency by interconnecting
elements of the production chain, such as real-time
monitoring of capital equipment to reduce downtime or to
be able to prepare for immediate service replacements.
Big data analytics. Companies collect data gathered from
various, or all, aspects of their operations across regions
and apply advanced statistical analysis to be able to make
better decisions, both for the business and for customer
satisfaction.
Back-office consolidation. Companies centralize
standard business operations to take advantage of
economies of scale (e.g., human resources, accounting,
payroll, support call centers, marketing, etc.) by improving
buying power and eliminating overlap.
Supply-chain automation. Companies track inventory
levels, process reordering automatically, and match supply
and demand.
Digital collaboration. Companies increase
communication and collaboration between teams.
Cloud scalability. Companies lower capital expenditure
and cost structure of information technology (IT) hardware,
infrastructure, software, and applications, all provided as a
service, and they reduce capital investment in idle capacity,
thus lowering the total cost of ownership and increasing
business agility and resilience to failures.
Source: Business Roundtable 2015.
Box 1: Firms’ uses of cross-border data flows
Research Triangle Park facility in Raleigh, North Carolina
(Cisco’s largest technical assistance center, which has
more than 4,500 employees) provides around-the-clock
tech support to customers 24 hours a day, 7 days a
week, anywhere in the world. When customers and
Cisco employees confront challenging hardware or
software problems, technical experts are able to log in
remotely, run diagnostic tools, and exchange data to
and from one another seamlessly. This type of business
activity fundamentally relies upon the free flow of data.20
As the appendix to this chapter further illustrates,
firms around the world innovate and optimize business
outcomes by transferring data across borders. Moreover,
when trade flows between businesses are curtailed,
innovation may decelerate through the interruption
of technology transfer or through the reduction of
competition-driven development, which is why the
uninhibited exchange of data is increasingly critical to
productivity and growth.

THE IMPACT OF CROSS-BORDER DATA FLOWS:
INDIVIDUALS AND ENTREPRENEURS
At the individual level, the ability to access cloud-based
information provides significant benefit. Individuals are
increasingly storing more of their personal information
online. Cisco’s Global Cloud Index estimates that,
by 2019, 2 billion Internet users (or 55 percent of all
consumer Internet users) will use personal cloud storage,
up from 1.1 billion users in 2014. Globally, consumer
cloud storage traffic per user will be 1.6 gigabytes per
month by 2019, compared to 992 megabytes per month
in 2014.21
Cloud-based services may be hosted in the
domestic market or in other countries.
New entrepreneurs also benefit from access to
infrastructure, platforms, and software from cloud-
based services, which may reside in other countries.
These include applications, data, middleware,
operating systems, virtualization, servers, storage, and
networking capabilities or equipment. Because of the
ability to access these services on a pay-as-you-go
model rather than committing to a large initial capital
investment, the financial barriers to new business entry
have fallen significantly. By one estimate, the cost for
an entrepreneur to establish a business with a working
prototype has fallen from around US$2 million in the
1990s down to less than US$50,000 and approximately
six weeks of work.22
Furthermore, depending on
the business model, in some cases startup costs—
when supported by the affordability of cloud-based
infrastructure—can be as low as US$3,000.23
THE FREE FLOW OF DATA AND THE DIGITAL
ECONOMY VALUE AT STAKE
Cisco’s data analysis demonstrates that the free flow
of data enables people and things to connect, which
can improve processes and add tremendous value to
any given economy. The potential bottom-line value at
stake (defined as the combination of increased revenues
and lower costs that is created or will migrate among
companies and industries as a result of increasing the
adoption of Internet technologies) is estimated to be
US$29.7 trillion over the 2015–24 period.24
This includes
up to US$23.8 trillion in the private sector, where up
to one-third of corporate profits may be at stake and
where telecommunications service providers have an
opportunity to capture US$1.8 trillion in new economic
value. Up to US$5.9 trillion may be generated in the
public sector as well. These improvements to the overall
digital economy represent a potential annual GDP upside
of 0.43 percent and potential employment creation of 2.7
million jobs worldwide.
Figure 2 highlights the relationship between the
value at stake that can be generated by the digital
economy and the Freedom on the Net score. The figure
suggests that countries with higher Freedom on the Net
scores are better poised to benefit from potential value
at stake from digitization.
In other words, those countries and companies
that have not positioned themselves in an environment
that fosters open Internet practices may find innovation
and economic growth hampered. Risks related to
Figure 2: Freedom on the Net as a driver of innovation, by country
Sources: Authors’ calculation; Barbier et al. 2016; Freedom House 2015; IMF 2015.
Note: Freedom on the Net scores range from 0 to 100, where 0 = most free, 100 = least free.
100 80 60 40 20 0
0
5
10
15
20
25
30
Valueatstake
(US$bycountry,normalizedbypopulation)
Freedom on the Net score

cybersecurity also slow innovation, as demonstrated by
new Cisco survey research, wherein senior executives
have determined that cybersecurity concerns have
forced their companies to drop some mission-critical
projects. Specifically, 39 percent of the 1,014 executives
surveyed state that their organization has “halted a
mission-critical initiative due to cybersecurity concerns.”
In Cisco’s survey, 71 percent of all respondents
somewhat or strongly agree that cybersecurity
threats—both potential and actual—hinder innovation.
Furthermore, 60 percent somewhat or strongly agree
that cybersecurity risk dampens smart and connected
product development, a critical element on the path to
digitization.25
RESTRICTIONS ON CROSS-BORDER DATA FLOWS
The Internet was architected with protocols to identify
the fastest possible route to transmit packets of data
between any two points. However, increasing concerns
of national governments around privacy, security, and
local competition have resulted in some policy and
regulatory impediments. Difficulties arise when overly
restrictive regulations on cross-border data flows create
trade barriers and impact business models. Overly
burdensome regulations can slow or prevent business
transactions, which increases costs and obstructs the
delivery of products to the market. Examples of these
restrictions, as noted by Business Roundtable, are
included in Table 2.
The number and impact of restrictions that are
implemented around the world appear to be increasing.
The US ITC identifies localization requirements as a
barrier for 82 percent of large firms and 52 percent
of small- and medium-sized enterprises in the digital
communications sector. Localization mandates are the
most frequently identified digital trade barrier.26
These restrictions impose significant business
costs. The burden of compliance related to both cost
and logistics can slow or stop business activity and
limit innovation. For example, one analysis estimates
that disruptions to cross-border data flows and services
trade could result in a negative impact on the European
Union of up to 1.3 percent of GDP as well as a potential
drop in EU manufacturing exports to the United States
of up to 11 percent.27
In seven different countries and
regions of the world studied in one analysis, data
localization requirements would also result in lower
GDP.28
Conversely, efforts to decrease barriers to cross-
border data traffic have been shown to drive growth and,
based on 2014 estimates, the removal of obstacles to
the flow of data could increase GDP by 0.1 percent to
0.3 percent in the United States.29
THE PATH FORWARD: BALANCING GROWTH, DATA
FLOWS, AND NATIONAL CONCERNS
As demonstrated above, the benefits of cross-border
data flows are significant. Additional empirical work
needs to be done, however.30
And there are still cases
where national concerns over privacy, security, and local
economic activity may prompt regulations to curb some
flows. In those instances, we propose the following
guidelines (see Box 2 for examples):
• Minimize fragmentation by ensuring that any
policy actions are least-trade-restrictive to achieve
legitimate public policy objectives.
• Carefully craft regulations that are as narrow in
scope as possible, with clearly articulated goals.
• Coordinate globally to minimize conflicts in
regulations between different jurisdictions.
• Evaluate the full costs of any proposed regulation
and ensure that costs of compliance do not
outweigh the quantifiable benefits.
• Adhere to trade obligations.
In sum, any limitations on cross-border data
flows should address specific concrete—not merely
Table 2: Examples of cross-border data flow restrictions
Source: Business Roundtable 2015.
Restriction type Restriction description
Local data storage Restricts data flows by requiring specified data—often but not always personal information—to be stored on local
servers. May also require specific applications or services to operate in-country, processing data locally to avoid
offshore transfer.
Data protection Restricts data flows through the application of data privacy laws with adequacy and/or consent requirements that
cannot reasonably be met without local data storage.
Geolocation data privacy Restricts data flows by preventing the collection, disclosure, transfer, or storage of geolocation data without an
individual’s consent.
Traffic routing Affects data flows by requiring communications providers to route Internet traffic in a specific way.

theoretical—problems, be least intrusive, be minimally
restrictive, and, if possible, be time-bound. In cases
where market-driven forces justify fragmentation
because of business-enhancing reasons, such as when
intellectual property may be affected, segmentation
should be driven by the market rather than by
government requirements.
These actions would minimize any collateral damage
done to the economy imposing restrictions, and they
would ensure that the Internet continues to serve as
a driver of innovation, economic growth, and social
development.
NOTES
1 Wired.com 2012.
2 History.com Staff 2010.
3 Katz 2012; ITU 2015a.
4 Pélissié du Rausas 2011.
5 IMF 2015.
6 Cisco VNI 2015.
7 TeleGeography, available at https://www.telegeography.com/
research-services/global-bandwidth-research-service/.
8 Manyika et al. 2014.
9 Pélissié du Rausas 2011.
10 Meltzer 2014. Note that a major challenge for understanding just
how potent this impact is, however, is the lack of data available.
11 US ITC 2014.
12 Lee-Makiyama 2015; UNCTAD 2009.
13 Manyika et al. 2016, p. 2.
14 Cornell University, INSEAD, and WIPO 2015.
15 Business Roundtable 2015.
16 US ITC 2014, p. 65.
17 Austin and Olarreaga 2012.
18 Castro and McQuinn 2015.
19 Castro and McQuinn 2015.
20 Moore 2015.
21 Cisco 2015.
22 Center for an Urban Future 2012; Mulas, Minges, and Applebaum
2015.
23 Mulas, Minges, and Applebaum 2015; Mytton 2010.
24 Barbier et al. 2016.
25 Barbier et al. 2016.
26 US ITC 2014.
27 Bauer et al. 2013, p. 3; Castro and McQuinn 2015.
28 Bauer et al. 2014.
29 Castro and McQuinn 2015; US ITC 2014.
30 For example, quantifying firm-level impact of new or existing
processes enabled by cross-border data flows.
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on the Global Stage. An eBay Report. Brussels: eBay EU Liaison
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Riegel. 2016. “Where to Begin Your Journey to Digital Value in
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Castro, D. and A. McQuinn. 2015. “Cross-Border Data Flows Enable
Growth in All Industries.” Washington, DC: ITIF.
Steps taken in several economies embody the spirit of
the proposed guidelines, illustrating the feasibility of their
implementation across national boundaries. For example,
the government of Singapore has promoted data centers
in an effort to attract their establishment by private or third
party entities within its borders.1
Additionally, Singapore’s
Personal Data Protection Commission (PDPC) has actively
engaged industry in the development of good practices in
data management, including those that regard the transfer
of data.2
Furthermore, guidelines for industry compliance
with the Personal Data Protection Act (2014) developed by
the PDPC have been narrow in scope and organized by
sector, and developed in consultation with industry.
While Singapore has enhanced its presence as a
global leader in digital transfer by emerging as a major
hub for finance and services, the Netherlands has done
so by serving as a major port for traded goods as well as
a hub for European data traffic. Despite taking different
routes to become more connected, both economies
have recognized the importance of digital flows, including
those both internally and externally facing. Supporting this
notion, in the March 2016 report on digital globalization,
the McKinsey Global Institute (MGI) finds that global flows
of goods, foreign direct investment, people, and data
contribute structurally to economic growth by increasing
productivity.3
Assessing MGI’s two most highly ranked
economies in country connectedness, Singapore (1st) and
the Netherlands (2nd) both also rank in the top 10 for data
flow, underscoring the crucial significance of open borders
for data transfer and, subsequently, global competitiveness
and innovation.
Notes
1 See the Singapore, Ministry of Communications and
Information website at http://www.mci.gov.sg/web/content/
infocomm-media-masterplan/preliminary-ideas/establish-agile-
pervasive-and-trusted-icm-infrastructure/digital-harbour.
2 See PDPC Singapore 2016.
3 Manyika et al. 2016.
Box 2: Country examples: Singapore and the
Netherlands

Center for an Urban Future. 2012. New Tech City. New York: Center for
an Urban Future. Available at https://nycfuture.org/pdf/New_Tech_
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next-generation-network/white_paper_c11-481360.html.
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external/pubs/ft/weo/2015/02/weodata/index.aspx.
ITU (International Telecommunication Union). 2015a. “ITU Releases
2015 ICT Figures: Statistics Confirm ICT Revolution of the Past 15
Years.” Press Release, May 26. Available at https://www.itu.int/net/
pressoffice/press_releases/2015/17.aspx.
———. 2015b. World Telecommunication/ICT Indicators database 2015,
18th edition. Available at http://www.itu.int/ITU-D/ict/publications/
world/world.html.
Katz, R. 2012. The Impact of Broadband on the Economy: Research to
Date and Policy Issues. Broadband Series. April 2012. Geneva:
ITU https://www.itu.int/ITU-D/treg/broadband/ITU-BB-Reports_
Impact-of-Broadband-on-the-Economy.pdf.
Lee-Makiyama, H. 2015. “Digital Trade in the U.S. and Global
Economies.” Submission to the USITC investigation. European
Centre for International Political Economy Available at http://www.
ecipe.org/app/uploads/2014/12/USITC_speech.pdf.
Manyika, J., J. Bughin, S. Lund, O. Nottebohm, D. Poulter, S. Jauch,
and S. Ramaswamy. 2014. Global Flows in a Digital Age: How
Trade, Finance, People, and Data Connect the World Economy.
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age.
Manyika, J., S. Lund, J. Bughin, J. Woetzel, K. Stamenov, and D.
Dhringra. 2016. Digital Globalization: The New Era of Global Flows.
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functions/mckinsey-digital/our-insights/digital-globalization-the-
new-era-of-global-flows.
Meltzer, J. 2014. “The Importance of the Internet and Transatlantic Data
Flow for U.S. and EU Trade and Investment.” Brookings Institute
Working Paper 74, October.
Moore, G. 2015. “How Free Trade Supports NC Jobs.” The
News&Observer, Op-Ed, March 6. Available at http://www.
newsobserver.com/opinion/op-ed/article12878609.html.
Mulas, V., M. Minges, and H. Applebaum. 2015. “Boosting Tech
Innovation Ecosystems in Cities: A Framework for Growth and
Sustainability of Urban Tech Innovation Ecosystems.” Discussion
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Mytton, D. 2010. “How Much Does It Cost to Start a Tech Company?”
Server Density Blog, February 15. Available at https://blog.
serverdensity.com/how-much-does-it-cost-to-start-a-tech-
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advisory-guidelines.
Pélissié du Rausas, M., J. Manyika, E. Hazan, J. Bughin, M. Chui, and
R. Said. 2011. Internet Matters: The Net’s Sweeping Impact on
Growth, Jobs, and Prosperity. Report, May. McKinsey Global
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tech_telecoms_internet/internet_matters.
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unctad.org/en/docs/ier2009_en.pdf.
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Wired.com. 2012. “How the Queen of England Beat Everyone to the
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the-internet/.
World Economic Forum. 2015. The Global Information and Technology
Report 2015: ICTs for Inclusive Growth. Geneva: World Economic
Forum.

Alliance Medical
Alliance Medical has been a pioneer in the trend of
remote interpretation and diagnosis of medical images—
such as x-rays, ultrasounds, and magnetic resonance
imaging (MRI) images. This service reduces wait times
and improves the expediency of diagnoses. In addition
to the efficiency cost savings, offloading these tasks also
allows doctors to spend more time with patients.
Caterpillar
Caterpillar is a global leader in the manufacture of
heavy machinery and engines for use in industries from
construction and mining to heavy-duty transportation.
Real-time sensors in their products monitor performance
data and transmit via cellular and satellite connectivity,
allowing users to remotely analyze and monitor
assets. This allows customers to identify underutilized
machines, thus maximizing efficiency, and to make
better equipment placement decisions, thus creating
substantial cost savings for customers. Cross-border
data flow restrictions, such as constraints on the
movement of Global Positioning System (GPS) data, may
limit Caterpillar’s ability to offer such advanced services
in certain markets.
Boeing
Boeing has developed a real-time information tool, the
Airplane Health Management (AHM), that gathers and
transmits data in real time to maintenance crews on the
ground. The data are sent across borders (while aircraft
are in the air) and helps to reduce delays, midflight
turn-backs, and cancellations. A single Boeing 737
engine produces up to 20 terabytes of data every hour
in flight. Data are analyzed in real time, even mid-flight,
to find and diagnose problems. Any issues are relayed
to waiting airline maintenance personnel at the aircraft’s
next airport destination. The crews can then meet the
aircraft with the appropriate airplane parts to make
necessary repairs. This sort of intelligence aids operators
in spotting trends, eliminating inefficiencies, saving
money, and reducing wait times.
General Electric (GE)
GE has embedded advanced sensors in a wide array
of machinery to improve the performance of industrial
equipment and machines purchased by its customers.
The sensors remotely capture performance data from
around the globe; these data are used to improve
product reliability, safety, and efficiency. For example, in
aviation, GE monitors sensor data from aircraft engines
around the globe, thus optimizing engines, to help
airlines anticipate maintenance issues and address them
before aircraft need to be grounded, saving time and
money for airlines and travelers. This sensor system
saves airlines more than US$2 billion per year worldwide
because the sensor technology reduces delays and
cancellations caused by aircraft maintenance needs—a
capability predicated on the ability to aggregate and
analyze sensor data supplied from locations to generate
savings for individuals, governments, and businesses
across the globe.
MasterCard
As a global payments industry leader, MasterCard
connects consumers, financial institutions, merchants,
governments, and businesses through electronic
payments. The company processes payment
transactions initiated in more than 40 million locations
in more than 210 countries and territories. Global
payment services are inherently dependent on cross-
border data flows because each payment transaction
requires transfers of payment transaction data between
the merchant, the merchant’s bank, MasterCard, and
the consumer’s bank. MasterCard enables merchants
to engage in international trade and sell goods and
services to foreign travelers. Even when the merchant,
the consumer, and their banks are all based in the same
country, MasterCard may leverage its global operations
hub to add value to the transaction and facilitate safe,
efficient, and cost-effective transactions. However,
some countries impose restrictions that require local
processing of all electronic payment transactions. In
doing so, restrictions can force the building or replication
of costly infrastructure domestically; this cost may then
be passed onto consumers.
Appendix:
Examples of firm-level cross-border data flows

1.2 Appendix: Examples of firm-level cross-border data flows
Royal Dutch Shell
Royal Dutch Shell has over 150,000 employees across
90 countries and is headquartered in the Netherlands.
As one of the world’s largest oil and gas companies,
it also has a global computing footprint with three
main global data centers. Shell uses these computing
resources to manage and analyze the data generated
by sensors in its wells, particularly from sensitive, low-
power sensors that generate high-resolution seismic
data. Transmitting data to the global data centers, these
sensors are able to detect resources in wells thought to
have run dry.
Tesco
Tesco is a global retailer with stores in 12 countries
in Asia, Europe, and North America. The consumer
goods giant processes real-time data from its electronic
shelves to make national pricing changes instantly as
well as to predict when products on its shelves need to
be reordered, thus preventing understocking and lost
revenue. These benefits are passed on to customers
in the form of better service, fresher ingredients, lower
prices, boosted convenience, and fully stocked shelves.
Tesco also combines weather forecasts for each
location, updated several times a day, to adjust deliveries
and refrigeration needs to prevent food spoilage.
Volvo
Volvo is a Swedish vehicle manufacturer employing over
115,000 people, with operations in over 190 countries.
The company embeds real-time vehicle location data
and diagnostic information and transmission capabilities
into its vehicles and allows for their systems to alert
drivers to needed repairs or software upgrades, as well
as locating lost or stolen vehicles during emergencies.
The company enables customers to gather data on all
of their trucks for real-time monitoring, optimizing vehicle
and fleet fuel efficiency.
Walmart
Walmart is the world’s largest retailer, with over 11,000
stores in 27 countries employing over 2.2 million people
worldwide; it maintains e-commerce websites in 10
countries. The company tracks its performance and
global operations by collecting data on all aspects of
its business, centralizing data, and deploying shared
services (such as human resources support with
cloud-based platforms). Virtualizing support operations
and back-office consolidation helps to reduce the
duplication of hardware and software and to increase
operating efficiency through economies of scale. Data
flow restrictions can prevent such efficiency-enhancing
innovations and in the long run discourage larger job-
creating investments in other areas of the business.
Sources: Business Roundtable 2015; Castro and McQuinn 2015.

How to Read the Country/Economy Profiles
The Country/Economy Profiles section presents a profile
for each of the 139 economies covered in The Global
Information Technology Report 2016. Each profile
summarizes an economy’s performance in the various
dimensions of the Networked Readiness Index (NRI).
PERFORMANCE HIGHLIGHTS
The first section of the profile presents the economy’s
performance in the overall NRI, the four main
components, and the 10 pillars. For each of these
dimensions, the economy’s rank (out of 139 economies)
and score (on a 1-to-7 scale) are reported.
On the radar chart to the right of the table, a blue
line plots the economy’s score on each of the 10
pillars. The gray line represents the average score of all
economies in the income group to which the economy
under review belongs. The country classification by
income group is defined by the World Bank and reflects
the situation as of July 2015. Note that the two high-
income groups in this classification, High income: OECD
and High income: non-OECD, were merged into a single
group for the purpose of the analysis.
THE NETWORKED READINESS INDEX IN
DETAIL
This section presents an economy’s performance in
each of the 53 indicators composing the NRI. The
indicators are organized by pillar. The numbering of the
variables matches that of the data tables in the next
section of the Report, which provides descriptions,
rankings, and scores for all the indicators. The indicators
derived from the 2014 and 2015 editions of the World
Economic Forum’s Executive Opinion Survey are
identified by an asterisk (*). These indicators are always
measured on a 1-to-7 scale (where 1 and 7 correspond
to the worst and best possible outcomes, respectively).
For more information on the Executive Opinion Survey
and a detailed explanation of how scores are computed,
refer to Chapter 1.3 of The Global Competitiveness
Report 2015–2016, available for free on the World
Economic Forum website at www.weforum.org/gcr.
For those indicators not derived from the Executive
Opinion Survey, the scale is reported next to the title.
The Technical Notes and Sources at the end of this
Report provide further details on each indicator, including
its definition, method of computation, and sources. Note
that for the sake of readability, the years were omitted.
However, the year of each data point is indicated in
the corresponding data table. For more information on
the framework and computation of the NRI, refer to
Chapter 1.1.
THE GITR ONLINE
In complement to the analysis presented in this Report,
the GITR’s portal—available at www.weforum.org/gitr—
offers additional analysis and a number of analytical tools
and visualizations, including sortable rankings and maps.
The portal also offers the option of downloading portions
of the NRI dataset.
2: Country/Economy Profiles
Note: Indicators followed by an asterisk (*) are measured on a 1-to-7 (best) scale. For
further details and explanation, please refer to the section “How to Read the
Country/Economy Profiles” on page 53.
1. Political and
regulatory environment
6. Individual usage
5. Skills7. Business
usage
4. Affordability8. Government
usage
3. Infrastructure9. Economic
impacts
2. Business and innovation
environment
10. Social
impacts
1
2
3
4
5
6
7
The Networked Readiness Index in detail
INDICATOR RANK/139 VALUE
1.01 Effectiveness of law-making bodies* ..................58 ......... 3.9
1.02 Laws relating to ICTs* ......................................111 ......... 3.1
1.03 Judicial independence* ....................................119 ......... 2.6
1.04 Efficiency of legal system in settling disputes*..120 ......... 2.8
1.05 Efficiency of legal system in challenging regs*..108 ......... 2.9
1.06 Intellectual property protection*........................110 ......... 3.2
1.07 Software piracy rate, % software installed..........76 .......... 75
1.08 No. procedures to enforce a contract ................89 .......... 39
1.09 No. days to enforce a contract ..........................66 ........ 525
2.01 Availability of latest technologies*.....................115 ......... 3.9
2.02 Venture capital availability* ...............................132 ......... 1.9
2.03 Total tax rate, % profits ......................................66 ....... 36.5
2.04 No. days to start a business ..............................28 ............ 6
2.05 No. procedures to start a business....................54 ............ 6
2.06 Intensity of local competition*...........................133 ......... 4.0
2.07 Tertiary education gross enrollment rate, %........38 ....... 62.7
2.08 Quality of management schools*........................61 ......... 4.3
2.09 Gov’t procurement of advanced tech* ...............31 ......... 3.8
3.01 Electricity production, kWh/capita......................74 ... 2401.8
3.02 Mobile network coverage, % pop. .....................49 ....... 99.8
3.03 Int’l Internet bandwidth, kb/s per user................74 ....... 32.1
3.04 Secure Internet servers/million pop. ...................80 ....... 23.8
4th pillar: Affordability
4.01 Prepaid mobile cellular tariffs, PPP $/min.........134 ....... 0.71
4.02 Fixed broadband Internet tariffs, PPP $/month ....7 ..... 14.98
4.03 Internet & telephony competition, 0–2 (best) ......80 ....... 1.86
5th pillar: Skills
5.01 Quality of education system*..............................29 ......... 4.5
5.02 Quality of math & science education*.................28 ......... 4.8
5.03 Secondary education gross enrollment rate, %..59 ....... 96.4
5.04 Adult literacy rate, %..........................................35 ....... 97.6
6.01 Mobile phone subscriptions/100 pop.................88 ..... 105.5
6.02 Individuals using Internet, %...............................57 ....... 60.1
6.03 Households w/ personal computer, % ...............94 ....... 23.5
6.04 Households w/ Internet access, % ....................87 ....... 26.6
6.05 Fixed broadband Internet subs/100 pop............78 ......... 6.6
6.06 Mobile broadband subs/100 pop.......................84 ....... 30.9
6.07 Use of virtual social networks* ...........................50 ......... 5.8
7.01 Firm-level technology absorption* ....................112 ......... 4.1
7.02 Capacity for innovation* ...................................103 ......... 3.6
7.03 PCT patents, applications/million pop. ..............87 ......... 0.2
7.04 ICT use for business-to-business transactions*113 ......... 4.0
7.05 Business-to-consumer Internet use* ..................78 ......... 4.2
7.06 Extent of staff training*.......................................37 ......... 4.3
8.01 Importance of ICTs to gov’t vision*.....................75 ......... 3.9
8.02 Government Online Service Index, 0–1 (best).....72 ....... 0.45
8.03 Gov’t success in ICT promotion*........................98 ......... 3.6
9.01 Impact of ICTs on business models* ................118 ......... 3.7
9.02 ICT PCT patents, applications/million pop. .......86 ......... 0.1
9.03 Impact of ICTs on organizational models* ........134 ......... 2.9
9.04 Knowledge-intensive jobs, % workforce.............80 ....... 17.7
10.01 Impact of ICTs on access to basic services* ....128 ......... 3.0
10.02 Internet access in schools* ................................45 ......... 4.8
10.03 ICT use & gov’t efficiency* .................................78 ......... 3.8
10.04 E-Participation Index, 0–1 (best).........................59 ....... 0.53
Rank Value
(out of 139) (1–7)
Networked Readiness Index........................84..3.9
Networked Readiness Index 2015 (out of 143)........................... 92..... 3.7
A. Environment subindex......................................................... 88..... 3.8
1st pillar: Political and regulatory environment...................... 109..... 3.2
2nd pillar: Business and innovation environment.................... 61..... 4.4
B. Readiness subindex ............................................................ 68..... 4.8
3rd pillar: Infrastructure .......................................................... 75..... 4.1
4th pillar: Affordability............................................................. 92..... 4.7
5th pillar: Skills....................................................................... 29..... 5.7
C. Usage subindex................................................................... 86..... 3.6
6th pillar: Individual usage...................................................... 83..... 3.6
7th pillar: Business usage ...................................................... 93..... 3.4
8th pillar: Government usage................................................. 76..... 3.7
D. Impact subindex.................................................................. 97..... 3.3
9th pillar: Economic impacts................................................ 121..... 2.6
10th pillar: Social impacts...................................................... 76..... 4.0
Albania
Albania Upper-middle-income group average

Index of Countries/Economies
Country/Economy Page
Albania 56
Algeria 57
Argentina 58
Armenia 59
Australia 60
Austria 61
Azerbaijan 62
Bahrain 63
Bangladesh 64
Belgium 65
Benin 66
Bhutan 67
Bolivia 68
Bosnia and Herzegovina 69
Botswana 70
Brazil 71
Bulgaria 72
Burundi 73
Cambodia 74
Cameroon 75
Canada 76
Cape Verde 77
Chad 78
Chile 79
China 80
Chinese Taipei 81
Colombia 82
Costa Rica 83
Côte d'Ivoire 84
Croatia 85
Cyprus 86
Czech Republic 87
Denmark 88
Dominican Republic 89
Ecuador 90
Egypt 91
El Salvador 92
Estonia 93
Ethiopia 94
Finland 95
France 96
Gabon 97
Gambia, The 98
Georgia 99
Germany 100
Ghana 101
Greece 102
Guatemala 103
Guinea 104
Guyana 105
Haiti 106
Honduras 107
Hong Kong SAR 108
Hungary 109
Iceland 110
India 111
Indonesia 112
Iran, Islamic Rep. 113
Ireland 114
Israel 115
Italy 116
Jamaica 117
Japan 118
Jordan 119
Kazakhstan 120
Kenya 121
Korea, Rep. 122
Kuwait 123
Kyrgyz Republic 124
Lao PDR 125
Latvia 126
Lebanon 127
Lesotho 128
Liberia 129
Lithuania 130
Luxembourg 131
Macedonia, FYR 132
Madagascar 133
Malawi 134
Malaysia 135
Mali 136
Malta 137
Mauritania 138
Mauritius 139
Mexico 140
Moldova 141
Mongolia 142
Montenegro 143
Morocco 144
Mozambique 145
Myanmar 146
Namibia 147
Nepal 148
Netherlands 149
New Zealand 150
Nicaragua 151
Nigeria 152
Norway 153
Oman 154
Pakistan 155
Panama 156
Paraguay 157
Peru 158
Philippines 159
Poland 160
Portugal 161
Qatar 162
Romania 163
Russian Federation 164
Rwanda 165
Saudi Arabia 166
Senegal 167
Serbia 168
Seychelles 169
Singapore 170
Slovak Republic 171
Slovenia 172
South Africa 173
Spain 174
Sri Lanka 175
Swaziland 176
Sweden 177
Switzerland 178
Tajikistan 179
Tanzania 180
Thailand 181
Trinidad and Tobago 182
Tunisia 183
Turkey 184
Uganda 185
Ukraine 186
United Arab Emirates 187
United Kingdom 188
United States 189
Uruguay 190
Venezuela 191
Vietnam 192
Zambia 193
Zimbabwe 194

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
1.01 Effectiveness of law-making bodies*...................58.......... 3.9
1.02 Laws relating to ICTs*.......................................111.......... 3.1
1.03 Judicial independence*.....................................119.......... 2.6
1.04 Efficiency of legal system in settling disputes*...120.......... 2.8
1.05 Efficiency of legal system in challenging regs*...108.......... 2.9
1.06 Intellectual property protection*.........................110.......... 3.2
1.07 Software piracy rate, % software installed...........76........... 75
1.08 No. procedures to enforce a contract.................89........... 39
1.09 No. days to enforce a contract...........................66......... 525
2.01 Availability of latest technologies*......................115.......... 3.9
2.02 Venture capital availability*................................132.......... 1.9
2.03 Total tax rate, % profits.......................................66........ 36.5
2.04 No. days to start a business...............................28............. 6
2.05 No. procedures to start a business.....................54............. 6
2.06 Intensity of local competition*............................133.......... 4.0
2.07 Tertiary education gross enrollment rate, %.........38........ 62.7
2.08 Quality of management schools*.........................61.......... 4.3
2.09 Gov’t procurement of advanced tech*................31.......... 3.8
3.01 Electricity production, kWh/capita.......................74.... 2401.8
3.02 Mobile network coverage, % pop.......................49........ 99.8
3.03 Int’l Internet bandwidth, kb/s per user................74........ 32.1
3.04 Secure Internet servers/million pop.....................80........ 23.8
4.01 Prepaid mobile cellular tariffs, PPP $/min..........134........ 0.71
4.02 Fixed broadband Internet tariffs, PPP $/month.....7...... 14.98
4.03 Internet & telephony competition, 0–2 (best).......80........ 1.86
5th pillar: Skills
5.01 Quality of education system*...............................29.......... 4.5
5.02 Quality of math & science education*..................28.......... 4.8
5.03 Secondary education gross enrollment rate, %...59........ 96.4
5.04 Adult literacy rate, %...........................................35........ 97.6
6.01 Mobile phone subscriptions/100 pop..................88...... 105.5
6.02 Individuals using Internet, %...............................57........ 60.1
6.03 Households w/ personal computer, %................94........ 23.5
6.04 Households w/ Internet access, %.....................87........ 26.6
6.05 Fixed broadband Internet subs/100 pop.............78.......... 6.6
6.06 Mobile broadband subs/100 pop........................84........ 30.9
6.07 Use of virtual social networks*............................50.......... 5.8
7.01 Firm-level technology absorption*.....................112.......... 4.1
7.02 Capacity for innovation*....................................103.......... 3.6
7.03 PCT patents, applications/million pop. ...............87.......... 0.2
7.04 ICT use for business-to-business transactions*.113.......... 4.0
7.05 Business-to-consumer Internet use*...................78.......... 4.2
7.06 Extent of staff training*........................................37.......... 4.3
8.01 Importance of ICTs to gov’t vision*......................75.......... 3.9
8.02 Government Online Service Index, 0–1 (best)......72........ 0.45
8.03 Gov’t success in ICT promotion*.........................98.......... 3.6
9.01 Impact of ICTs on business models*.................118.......... 3.7
9.02 ICT PCT patents, applications/million pop. ........86.......... 0.1
9.03 Impact of ICTs on organizational models*.........134.......... 2.9
9.04 Knowledge-intensive jobs, % workforce..............80........ 17.7
10.01 Impact of ICTs on access to basic services*.....128.......... 3.0
10.02 Internet access in schools*.................................45.......... 4.8
10.03 ICT use & gov’t efficiency*..................................78.......... 3.8
10.04 E-Participation Index, 0–1 (best).........................59........ 0.53
Rank Value
(out of 139) (1–7)
Networked Readiness Index........................guatda.com/cmx.p84...3.9
Networked Readiness Index 2015 (out of 143)............................ 92...... 3.7
A. Environment subindex.......................................................... 88...... 3.8
1st pillar: Political and regulatory environment....................... 109...... 3.2
2nd pillar: Business and innovation environment..................... 61...... 4.4
B. Readiness subindex............................................................. 68...... 4.8
3rd pillar: Infrastructure........................................................... 75...... 4.1
4th pillar: Affordability.............................................................. 92...... 4.7
5th pillar: Skills........................................................................ 29...... 5.7
C. Usage subindex.................................................................... 86...... 3.6
6th pillar: Individual usage....................................................... 83...... 3.6
7th pillar: Business usage....................................................... 93...... 3.4
8th pillar: Government usage.................................................. 76...... 3.7
D. Impact subindex................................................................... 97...... 3.3
9th pillar: Economic impacts................................................. 121...... 2.6
10th pillar: Social impacts....................................................... 76...... 4.0
Albania
Albania Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
1.01 Effectiveness of law-making bodies*.................110.......... 3.0
1.03 Judicial independence*.......................................95.......... 3.3
1.04 Efficiency of legal system in settling disputes*.....85.......... 3.4
1.05 Efficiency of legal system in challenging regs*.....85.......... 3.3
1.08 No. procedures to enforce a contract...............125........... 45
2.02 Venture capital availability*..................................79.......... 2.6
2.03 Total tax rate, % profits.....................................136........ 72.7
2.04 No. days to start a business.............................102........... 20
2.05 No. procedures to start a business...................125........... 12
2.08 Quality of management schools*.......................117.......... 3.4
3.04 Secure Internet servers/million pop...................122.......... 2.0
4.01 Prepaid mobile cellular tariffs, PPP $/min............79........ 0.28
4.02 Fixed broadband Internet tariffs, PPP $/month.101...... 49.98
4.03 Internet & telephony competition, 0–2 (best).....105........ 1.33
5th pillar: Skills
5.02 Quality of math & science education*................105.......... 3.3
6.01 Mobile phone subscriptions/100 pop................105........ 92.9
6.02 Individuals using Internet, %.............................106........ 18.1
6.07 Use of virtual social networks*..........................123.......... 4.7
7.05 Business-to-consumer Internet use*.................128.......... 3.3
7.06 Extent of staff training*......................................126.......... 3.3
8.01 Importance of ICTs to gov’t vision*....................119.......... 3.1
8.02 Government Online Service Index, 0–1 (best)....130........ 0.08
8.03 Gov’t success in ICT promotion*.......................115.......... 3.4
10.02 Internet access in schools*...............................128.......... 2.8
10.03 ICT use & gov’t efficiency*................................116.......... 3.3
10.04 E-Participation Index, 0–1 (best).......................132........ 0.08
Rank Value
(out of 139) (1–7)
Networked Readiness Index......................guatda.com/cmx.p117...3.2
Networked Readiness Index 2015 (out of 143).......................... 120...... 3.1
A. Environment subindex........................................................ 131...... 3.1
2nd pillar: Business and innovation environment................... 133...... 3.2
5th pillar: Skills........................................................................ 89...... 4.6
C. Usage subindex.................................................................. 125...... 2.8
6th pillar: Individual usage..................................................... 103...... 2.8
7th pillar: Business usage..................................................... 133...... 2.9
8th pillar: Government usage................................................ 130...... 2.7
D. Impact subindex................................................................. 129...... 2.6
10th pillar: Social impacts..................................................... 132...... 2.7
Algeria
Algeria Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
2.03 Total tax rate, % profits.....................................139...... 137.4
2.09 Gov’t procurement of advanced tech*..............134.......... 2.5
3.02 Mobile network coverage, % pop.....................109........ 94.1
4.01 Prepaid mobile cellular tariffs, PPP $/min...........n/a.......... n/a
4.02 Fixed broadband Internet tariffs, PPP $/month..n/a.......... n/a
4.03 Internet & telephony competition, 0–2 (best).........1........ 2.00
5th pillar: Skills
5.01 Quality of education system*.............................108.......... 3.1
5.03 Secondary education gross enrollment rate, %...28...... 106.3
6.05 Fixed broadband Internet subs/100 pop.............52........ 15.6
7.02 Capacity for innovation*......................................74.......... 3.9
9.03 Impact of ICTs on organizational models*...........85.......... 3.8
Rank Value
(out of 139) (1–7)
4th pillar: Affordability............................................................. n/a...... n/a
5th pillar: Skills........................................................................ 71...... 5.0
C. Usage subindex.................................................................... 73...... 3.8
9th pillar: Economic impacts................................................... 87...... 3.0
Argentina
Argentina High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
1.02 Laws relating to ICTs*.........................................50.......... 4.2
1.06 Intellectual property protection*...........................93.......... 3.5
2.01 Availability of latest technologies*........................87.......... 4.4
2.04 No. days to start a business.................................9............. 3
2.05 No. procedures to start a business.......................3............. 2
2.06 Intensity of local competition*..............................85.......... 4.8
3.02 Mobile network coverage, % pop.........................1...... 100.0
4.02 Fixed broadband Internet tariffs, PPP $/month...24...... 21.04
5th pillar: Skills
5.04 Adult literacy rate, %.............................................8........ 99.8
7.04 ICT use for business-to-business transactions*...70.......... 4.7
9.01 Impact of ICTs on business models*...................62.......... 4.5
10.01 Impact of ICTs on access to basic services*.......63.......... 4.3
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 51...... 5.4
C. Usage subindex.................................................................... 65...... 4.0
Armenia
Armenia Lower-middle-income group average

1 See the “Technical Notes and Sources” section.
1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
1.07 Software piracy rate, % software installed.............5........... 21
2.06 Intensity of local competition*................................9.......... 5.9
2.07 Tertiary education gross enrollment rate, %...........6........ 86.6
3.01 Electricity production, kWh/capita.......................11.. 10765.5
3.04 Secure Internet servers/million pop.....................14.... 1348.6
5th pillar: Skills
5.03 Secondary education gross enrollment rate, %.....3...... 137.6
5.04 Adult literacy rate, %..........................................n/a.........n/a1
6.06 Mobile broadband subs/100 pop........................10...... 112.2
7.01 Firm-level technology absorption*.......................22.......... 5.6
7.03 PCT patents, applications/million pop. ...............22........ 76.4
8.02 Government Online Service Index, 0–1 (best)........8........ 0.93
9.02 ICT PCT patents, applications/million pop. ........20........ 24.0
10.02 Internet access in schools*...................................6.......... 6.1
10.04 E-Participation Index, 0–1 (best)...........................7........ 0.94
Rank Value
(out of 139) (1–7)
1st pillar: Political and regulatory environment......................... 13...... 5.4
3rd pillar: Infrastructure............................................................. 7...... 7.0
5th pillar: Skills........................................................................ 13...... 6.0
C. Usage subindex.................................................................... 22...... 5.4
10th pillar: Social impacts......................................................... 9...... 5.7
Australia
Australia High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
1.08 No. procedures to enforce a contract...................4........... 25
5th pillar: Skills
7.02 Capacity for innovation*........................................8.......... 5.4
7.03 PCT patents, applications/million pop. ...............11...... 169.0
10.01 Impact of ICTs on access to basic services*.........9.......... 5.9
Rank Value
(out of 139) (1–7)
B. Readiness subindex............................................................... 6...... 6.3
4th pillar: Affordability................................................................ 5...... 6.7
5th pillar: Skills........................................................................ 28...... 5.7
C. Usage subindex.................................................................... 21...... 5.4
Austria
Austria High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
1.09 No. days to enforce a contract.............................6......... 277
5th pillar: Skills
8.01 Importance of ICTs to gov’t vision*........................8.......... 5.2
8.03 Gov’t success in ICT promotion*...........................8.......... 5.4
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 68...... 5.1
C. Usage subindex.................................................................... 41...... 4.4
Azerbaijan
Azerbaijan Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
2.03 Total tax rate, % profits.........................................4........ 13.5
3.01 Electricity production, kWh/capita.........................3.. 19205.2
3.04 Secure Internet servers/million pop.....................43...... 177.0
5th pillar: Skills
6.01 Mobile phone subscriptions/100 pop....................5...... 173.3
6.03 Households w/ personal computer, %..................7........ 94.6
6.06 Mobile broadband subs/100 pop..........................4...... 126.2
9.04 Knowledge-intensive jobs, % workforce.............n/a.......... n/a
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 31...... 5.7
C. Usage subindex.................................................................... 24...... 5.3
8th pillar: Government usage.................................................... 3...... 5.7
Bahrain
Bahrain High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
1.07 Software piracy rate, % software installed.........100........... 87
1.09 No. days to enforce a contract.........................138....... 1442
2.05 No. procedures to start a business...................105............. 9
2.07 Tertiary education gross enrollment rate, %.......107........ 13.4
3.01 Electricity production, kWh/capita.....................116...... 337.5
3.03 Int’l Internet bandwidth, kb/s per user..............110.......... 6.6
4.01 Prepaid mobile cellular tariffs, PPP $/min..............3........ 0.04
5th pillar: Skills
5.03 Secondary education gross enrollment rate, %.112........ 58.3
5.04 Adult literacy rate, %.........................................102........ 61.5
6.02 Individuals using Internet, %.............................126.......... 9.6
6.03 Households w/ personal computer, %..............124.......... 6.9
6.04 Households w/ Internet access, %...................119.......... 6.5
6.06 Mobile broadband subs/100 pop......................107........ 13.4
7.03 PCT patents, applications/million pop. .............112.......... 0.0
9.02 ICT PCT patents, applications/million pop. ......100.......... 0.0
Rank Value
(out of 139) (1–7)
3rd pillar: Infrastructure......................................................... 107...... 2.8
5th pillar: Skills...................................................................... 122...... 3.1
C. Usage subindex.................................................................. 111...... 3.0
Bangladesh
Bangladesh Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
2.08 Quality of management schools*...........................2.......... 6.0
3.03 Int’l Internet bandwidth, kb/s per user................11...... 263.9
5th pillar: Skills
5.01 Quality of education system*.................................5.......... 5.5
5.02 Quality of math & science education*....................3.......... 6.0
6.05 Fixed broadband Internet subs/100 pop...............8........ 36.0
Rank Value
(out of 139) (1–7)
5th pillar: Skills.......................................................................... 4...... 6.4
C. Usage subindex.................................................................... 27...... 5.2
Belgium
Belgium High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
1.07 Software piracy rate, % software installed..........n/a.......... n/a
1.09 No. days to enforce a contract.........................112......... 750
2.04 No. days to start a business...............................72........... 12
3.01 Electricity production, kWh/capita.....................138........ 16.8
4.02 Fixed broadband Internet tariffs, PPP $/month.125.... 113.62
5th pillar: Skills
6.01 Mobile phone subscriptions/100 pop..................96........ 99.7
6.05 Fixed broadband Internet subs/100 pop...........116.......... 0.4
6.06 Mobile broadband subs/100 pop......................130.......... 2.8
Rank Value
(out of 139) (1–7)
Networked Readiness Index 2015 (out of 143)........................... n/a...... n/a
B. Readiness subindex........................................................... 128...... 2.6
4th pillar: Affordability............................................................ 126...... 2.9
5th pillar: Skills...................................................................... 133...... 2.4
C. Usage subindex.................................................................. 122...... 2.8
Benin
Benin Low-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 103...... 4.1
C. Usage subindex.................................................................. 101...... 3.3
Bhutan
Bhutan Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
6.04 Households w/ Internet access, %...................101........ 17.0
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 90...... 4.6
C. Usage subindex.................................................................. 108...... 3.1
Bolivia
Bolivia Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 84...... 4.7
C. Usage subindex.................................................................. 107...... 3.2
Bosnia and Herzegovina
Bosnia and Herzegovina Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
6.03 Households w/ personal computer, %..............106........ 14.8
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 87...... 4.6
C. Usage subindex.................................................................... 96...... 3.4
Botswana
Botswana Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
3.02 Mobile network coverage, % pop.......................35...... 100.0
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 91...... 4.5
C. Usage subindex.................................................................... 57...... 4.0
Brazil
Brazil Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 52...... 5.4
C. Usage subindex.................................................................... 64...... 4.0
Bulgaria
Bulgaria Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
2.07 Tertiary education gross enrollment rate, %.......131.......... 4.4
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 119...... 3.3
C. Usage subindex.................................................................. 139...... 2.1
Burundi
Burundi Low-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
9.04 Knowledge-intensive jobs, % workforce............104.......... 4.1
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 120...... 3.3
C. Usage subindex.................................................................. 110...... 3.1
Cambodia
Cambodia Low-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 107...... 3.8
C. Usage subindex.................................................................. 114...... 2.9
Cameroon
Cameroon Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
2.07 Tertiary education gross enrollment rate, %........n/a.......... n/a
5th pillar: Skills
Rank Value
(out of 139) (1–7)
2nd pillar: Business and innovation environment....................... 4...... 5.5
5th pillar: Skills........................................................................ 11...... 6.1
C. Usage subindex.................................................................... 26...... 5.2
Canada
Canada High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 75...... 5.0
C. Usage subindex.................................................................... 87...... 3.6
Cape Verde
Cape Verde Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
4.02 Fixed broadband Internet tariffs, PPP $/month.137.. 1275.69
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 139...... 1.9
C. Usage subindex.................................................................. 138...... 2.2
Chad
Chad Low-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 67...... 5.1
C. Usage subindex.................................................................... 39...... 4.5
Chile
Chile High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
2.09 Gov’t procurement of advanced tech*..................9.......... 4.3
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 47...... 5.4
C. Usage subindex.................................................................... 51...... 4.1
China
China Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
3.04 Secure Internet servers/million pop.......................9.... 1752.0
5th pillar: Skills
7.03 PCT patents, applications/million pop. ..............n/a.......... n/a
8.02 Government Online Service Index, 0–1 (best).....n/a.......... n/a
9.02 ICT PCT patents, applications/million pop. .......n/a.......... n/a
10.04 E-Participation Index, 0–1 (best)........................n/a.......... n/a
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 23...... 5.8
C. Usage subindex.................................................................... 16...... 5.5
Chinese Taipei
Chinese Taipei High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 79...... 4.9
C. Usage subindex.................................................................... 54...... 4.1
Colombia
Colombia Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 30...... 5.7
C. Usage subindex.................................................................... 46...... 4.3
Costa Rica
Costa Rica Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 123...... 3.1
C. Usage subindex.................................................................. 100...... 3.3
Côte d’Ivoire
Côte d’Ivoire Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 42...... 5.5
C. Usage subindex.................................................................... 58...... 4.0
Croatia
Croatia High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 16...... 6.0
C. Usage subindex.................................................................... 52...... 4.1
Cyprus
Cyprus High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 39...... 5.5
C. Usage subindex.................................................................... 37...... 4.5
Czech Republic
Czech Republic High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
1.03 Judicial independence*.........................................5.......... 6.3
3.03 Int’l Internet bandwidth, kb/s per user..................9...... 341.7
5th pillar: Skills
6.02 Individuals using Internet, %.................................3........ 96.0
6.04 Households w/ Internet access, %.......................8........ 93.1
7.03 PCT patents, applications/million pop. .................8...... 209.3
Rank Value
(out of 139) (1–7)
Networked Readiness Index 2013 (out of 144).............................. 8...... 5.6
5th pillar: Skills........................................................................ 17...... 5.9
C. Usage subindex.................................................................... 10...... 5.8
6th pillar: Individual usage......................................................... 1...... 6.9
7th pillar: Business usage......................................................... 9...... 5.7
Denmark
Denmark High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 104...... 4.0
C. Usage subindex.................................................................... 97...... 3.4
Dominican Republic
Dominican Republic Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 63...... 5.2
C. Usage subindex.................................................................... 82...... 3.7
Ecuador
Ecuador Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 111...... 3.7
C. Usage subindex.................................................................... 89...... 3.5
Egypt
Egypt Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
3.01 Electricity production, kWh/capita.......................97...... 958.2
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 98...... 4.2
C. Usage subindex.................................................................... 90...... 3.5
El Salvador
El Salvador Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
1.02 Laws relating to ICTs*...........................................2.......... 5.9
5th pillar: Skills
7.04 ICT use for business-to-business transactions*.....5.......... 6.0
7.05 Business-to-consumer Internet use*.....................9.......... 5.8
9.03 Impact of ICTs on organizational models*.............5.......... 5.6
10.03 ICT use & gov’t efficiency*....................................4.......... 5.8
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 19...... 5.9
C. Usage subindex.................................................................... 23...... 5.4
Estonia
Estonia High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 131...... 2.5
C. Usage subindex.................................................................. 123...... 2.8
Ethiopia
Ethiopia Low-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
1.01 Effectiveness of law-making bodies*.....................8.......... 5.5
1.04 Efficiency of legal system in settling disputes*.......3.......... 5.8
1.05 Efficiency of legal system in challenging regs*.......1.......... 5.8
1.06 Intellectual property protection*.............................1.......... 6.3
2.01 Availability of latest technologies*..........................1.......... 6.6
2.02 Venture capital availability*....................................6.......... 4.5
5th pillar: Skills
9.01 Impact of ICTs on business models*.....................1.......... 5.9
9.02 ICT PCT patents, applications/million pop. ..........2...... 149.0
Rank Value
(out of 139) (1–7)
Networked Readiness Index..........................guatda.com/cmx.p2...6.0
A. Environment subindex............................................................ 5...... 5.6
1st pillar: Political and regulatory environment........................... 4...... 5.8
5th pillar: Skills.......................................................................... 2...... 6.5
C. Usage subindex...................................................................... 7...... 5.8
D. Impact subindex..................................................................... 4...... 5.8
9th pillar: Economic impacts..................................................... 1...... 6.1
Finland
Finland High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 18...... 5.9
C. Usage subindex.................................................................... 20...... 5.4
France
France High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
3.02 Mobile network coverage, % pop.....................138.......... 1.9
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 116...... 3.5
C. Usage subindex.................................................................. 119...... 2.9
Gabon
Gabon Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
3.03 Int’l Internet bandwidth, kb/s per user..............100........ 10.9
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 121...... 3.2
C. Usage subindex.................................................................. 102...... 3.3
Gambia, The
Gambia, The Low-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 64...... 5.1
C. Usage subindex.................................................................... 72...... 3.8
Georgia
Georgia Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills.......................................................................... 8...... 6.1
C. Usage subindex.................................................................... 14...... 5.6
Germany
Germany High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
9.04 Knowledge-intensive jobs, % workforce..............96.......... 9.6
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 102...... 4.1
C. Usage subindex.................................................................... 91...... 3.5
Ghana
Ghana Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
2.07 Tertiary education gross enrollment rate, %...........1...... 110.2
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 58...... 5.3
C. Usage subindex.................................................................... 62...... 4.0
Greece
Greece High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 118...... 3.4
C. Usage subindex.................................................................. 106...... 3.2
Guatemala
Guatemala Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
4.02 Fixed broadband Internet tariffs, PPP $/month..n/a.......... n/a
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 137...... 2.1
C. Usage subindex.................................................................. 135...... 2.3
Guinea
Guinea Low-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 78...... 4.9
C. Usage subindex.................................................................. 105...... 3.2
Guyana
Guyana Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 124...... 3.0
C. Usage subindex.................................................................. 136...... 2.3
Haiti
Haiti Low-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 97...... 4.2
C. Usage subindex.................................................................... 93...... 3.4
Honduras
Honduras Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
3.03 Int’l Internet bandwidth, kb/s per user..................2.... 3721.8
5th pillar: Skills
7.03 PCT patents, applications/million pop. ..............n/a.......... n/a
8.02 Government Online Service Index, 0–1 (best).....n/a.......... n/a
9.02 ICT PCT patents, applications/million pop. .......n/a.......... n/a
10.04 E-Participation Index, 0–1 (best)........................n/a.......... n/a
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 10...... 6.1
C. Usage subindex.................................................................... 25...... 5.3
Hong Kong SAR
Hong Kong SAR High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 56...... 5.3
C. Usage subindex.................................................................... 48...... 4.2
Hungary
Hungary High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
6.07 Use of virtual social networks*..............................1.......... 6.7
7.01 Firm-level technology absorption*.........................1.......... 6.2
9.04 Knowledge-intensive jobs, % workforce................6........ 48.2
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 15...... 6.0
C. Usage subindex.................................................................... 18...... 5.5
Iceland
Iceland High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
3.01 Electricity production, kWh/capita.......................98...... 932.8
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 101...... 4.1
C. Usage subindex.................................................................. 103...... 3.3
India
India Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 65...... 5.1
C. Usage subindex.................................................................... 78...... 3.8
Indonesia
Indonesia Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 80...... 4.8
C. Usage subindex.................................................................... 99...... 3.3
Iran, Islamic Rep.
Iran, Islamic Rep. Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills.......................................................................... 9...... 6.1
C. Usage subindex.................................................................... 28...... 5.2
Ireland
Ireland High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 38...... 5.5
C. Usage subindex.................................................................... 15...... 5.5
Israel
Israel High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 37...... 5.6
C. Usage subindex.................................................................... 43...... 4.4
Italy
Italy High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 86...... 4.6
C. Usage subindex.................................................................... 85...... 3.6
Jamaica
Jamaica Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
7.06 Extent of staff training*..........................................6.......... 5.4
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 14...... 6.0
C. Usage subindex...................................................................... 2...... 5.9
Japan
Japan High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 59...... 5.3
C. Usage subindex.................................................................... 53...... 4.1
Jordan
Jordan Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 45...... 5.4
C. Usage subindex.................................................................... 44...... 4.4
Kazakhstan
Kazakhstan Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 96...... 4.2
C. Usage subindex.................................................................... 84...... 3.6
Kenya
Kenya Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 35...... 5.6
C. Usage subindex...................................................................... 6...... 5.8
Korea, Rep.
Korea, Rep. High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 77...... 4.9
C. Usage subindex.................................................................... 47...... 4.3
Kuwait
Kuwait High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 81...... 4.8
C. Usage subindex.................................................................. 104...... 3.2
Kyrgyz Republic
Kyrgyz Republic Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
9.04 Knowledge-intensive jobs, % workforce............101.......... n/a
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 106...... 3.9
C. Usage subindex.................................................................. 117...... 2.9
Lao PDR
Lao PDR Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 36...... 5.6
C. Usage subindex.................................................................... 35...... 4.6
Latvia
Latvia High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 55...... 5.3
C. Usage subindex.................................................................... 77...... 3.8
Lebanon
Lebanon Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 108...... 3.8
C. Usage subindex.................................................................. 128...... 2.7
Lesotho
Lesotho Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 132...... 2.4
C. Usage subindex.................................................................. 130...... 2.6
Liberia
Liberia Low-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 26...... 5.8
C. Usage subindex.................................................................... 31...... 4.9
Lithuania
Lithuania High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 20...... 5.9
C. Usage subindex...................................................................... 5...... 5.9
Luxembourg
Luxembourg High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 66...... 5.1
C. Usage subindex.................................................................... 50...... 4.2
Macedonia, FYR
Macedonia, FYR Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 129...... 2.8
C. Usage subindex.................................................................. 132...... 2.6
Madagascar
Madagascar Low-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 130...... 2.7
C. Usage subindex.................................................................. 134...... 2.5
Malawi
Malawi Low-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 46...... 5.4
C. Usage subindex.................................................................... 30...... 5.1
Malaysia
Malaysia Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 135...... 2.4
C. Usage subindex.................................................................. 115...... 2.9
Mali
Mali Low-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 44...... 5.5
C. Usage subindex.................................................................... 33...... 4.7
Malta
Malta High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 138...... 1.9
C. Usage subindex.................................................................. 133...... 2.5
Mauritania
Mauritania Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 53...... 5.3
C. Usage subindex.................................................................... 55...... 4.1
Mauritius
Mauritius Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 92...... 4.5
C. Usage subindex.................................................................... 74...... 3.8
Mexico
Mexico Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 70...... 5.0
C. Usage subindex.................................................................... 76...... 3.8
Moldova
Moldova Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
4.03 Internet & telephony competition, 0–2 (best)......n/a.......... n/a
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 62...... 5.2
C. Usage subindex.................................................................... 71...... 3.9
Mongolia
Mongolia Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 50...... 5.4
C. Usage subindex.................................................................... 56...... 4.1
Montenegro
Montenegro Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 110...... 3.7
C. Usage subindex.................................................................... 60...... 4.0
Morocco
Morocco Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 136...... 2.1
C. Usage subindex.................................................................. 124...... 2.8
Mozambique
Mozambique Low-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 113...... 3.6
C. Usage subindex.................................................................. 137...... 2.3
Myanmar
Myanmar Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 109...... 3.8
C. Usage subindex.................................................................... 94...... 3.4
Namibia
Namibia Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 115...... 3.6
C. Usage subindex.................................................................. 129...... 2.6
Nepal
Nepal Low-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
9.02 ICT PCT patents, applications/million pop. ..........8........ 59.1
Rank Value
(out of 139) (1–7)
5th pillar: Skills.......................................................................... 6...... 6.2
C. Usage subindex...................................................................... 3...... 5.9
Netherlands
Netherlands High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills.......................................................................... 7...... 6.2
C. Usage subindex.................................................................... 17...... 5.5
New Zealand
New Zealand High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 112...... 3.6
C. Usage subindex.................................................................. 131...... 2.6
Nicaragua
Nicaragua Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 134...... 2.4
C. Usage subindex.................................................................. 109...... 3.1
Nigeria
Nigeria Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 12...... 6.0
C. Usage subindex...................................................................... 9...... 5.8
Norway
Norway High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 76...... 5.0
C. Usage subindex.................................................................... 36...... 4.5
Oman
Oman High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 127...... 2.8
C. Usage subindex.................................................................. 118...... 2.9
Pakistan
Pakistan Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 93...... 4.5
C. Usage subindex.................................................................... 61...... 4.0
Panama
Panama Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 105...... 3.9
C. Usage subindex.................................................................. 112...... 3.0
Paraguay
Paraguay Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 94...... 4.5
C. Usage subindex.................................................................... 92...... 3.5
Peru
Peru Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 54...... 5.3
C. Usage subindex.................................................................... 66...... 3.9
Philippines
Philippines Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 40...... 5.5
C. Usage subindex.................................................................... 49...... 4.2
Poland
Poland High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 34...... 5.6
C. Usage subindex.................................................................... 34...... 4.7
Portugal
Portugal High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills.......................................................................... 5...... 6.4
C. Usage subindex.................................................................... 19...... 5.4
Qatar
Qatar High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 41...... 5.5
C. Usage subindex.................................................................... 68...... 3.9
Romania
Romania Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 48...... 5.4
C. Usage subindex.................................................................... 40...... 4.5
Russian Federation
Russian Federation High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
4.02 Fixed broadband Internet tariffs, PPP $/month.136.. 1040.24
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 117...... 3.5
C. Usage subindex.................................................................... 83...... 3.6
Rwanda
Rwanda Low-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 49...... 5.4
C. Usage subindex.................................................................... 29...... 5.1
Saudi Arabia
Saudi Arabia High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills...................................................................... 128...... 2.8
C. Usage subindex.................................................................... 95...... 3.4
Senegal
Senegal Lower-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 61...... 5.2
C. Usage subindex.................................................................... 79...... 3.7
Serbia
Serbia Upper-middle-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
Rank Value
(out of 139) (1–7)
5th pillar: Skills........................................................................ 74...... 5.0
C. Usage subindex.................................................................... 70...... 3.9
Seychelles
Seychelles High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
9.02 ICT PCT patents, applications/million pop. ..........9........ 55.8
Rank Value
(out of 139) (1–7)
5th pillar: Skills.......................................................................... 1...... 6.5
C. Usage subindex...................................................................... 1...... 6.0
Singapore
Singapore High-income group average

1. Political and
6. Individual usage
usage
usage
impacts
environment
10. Social
impacts
1
2
3
4
5
6
7
5th pillar: Skills
9.01 Impact of ICTs on business models*...................57..........

Global information technology report 2016 wef

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Global information technology report 2016 wef