Analysis and Key Findings
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This section begins with an overview of the NRI 2015 results, including a brief analysis of regional patterns and trends. It then presents some of the key findings and messages from this year’s edition and concludes with a short assessment of the performance of selected countries.
Results overview
Tables 1–5 report the results (ranks and values) for the overall NRI 2015, its four subindexes, and their respective pillars. Table 1 also contains the country classifications used throughout the analysis. Scores are reported with a precision of one decimal, but rankings were derived from the exact figures.
Table 1: The Networked Readiness Index 2015
NETWORKED READINESS INDEX | |||||
Rank | Country/Economy | Value | 2014 Rank (out of 148) | Income level* | Group† |
1 | Singapore | 6.0 | 2 | HI | ADV |
2 | Finland | 6.0 | 1 | HI-OECD | ADV |
3 | Sweden | 5.8 | 3 | HI-OECD | ADV |
4 | Netherlands | 5.8 | 4 | HI-OECD | ADV |
5 | Norway | 5.8 | 5 | HI-OECD | ADV |
6 | Switzerland | 5.7 | 6 | HI-OECD | ADV |
7 | United States | 5.6 | 7 | HI-OECD | ADV |
8 | United Kingdom | 5.6 | 9 | HI-OECD | ADV |
9 | Luxembourg | 5.6 | 11 | HI-OECD | ADV |
10 | Japan | 5.6 | 16 | HI-OECD | ADV |
11 | Canada | 5.5 | 17 | HI-OECD | ADV |
12 | Korea, Rep. | 5.5 | 10 | HI-OECD | ADV |
13 | Germany | 5.5 | 12 | HI-OECD | ADV |
14 | Hong Kong SAR | 5.5 | 8 | HI | ADV |
15 | Denmark | 5.5 | 13 | HI-OECD | ADV |
16 | Australia | 5.5 | 18 | HI-OECD | ADV |
17 | New Zealand | 5.5 | 20 | HI-OECD | ADV |
18 | Taiwan, China | 5.5 | 14 | HI | ADV |
19 | Iceland | 5.4 | 19 | HI-OECD | ADV |
20 | Austria | 5.4 | 22 | HI-OECD | ADV |
21 | Israel | 5.4 | 15 | HI-OECD | ADV |
22 | Estonia | 5.3 | 21 | HI-OECD | ADV |
23 | United Arab Emirates | 5.3 | 24 | HI | MENAP |
24 | Belgium | 5.3 | 27 | HI-OECD | ADV |
25 | Ireland | 5.2 | 26 | HI-OECD | ADV |
26 | France | 5.2 | 25 | HI-OECD | ADV |
27 | Qatar | 5.1 | 23 | HI | MENAP |
28 | Portugal | 4.9 | 33 | HI-OECD | ADV |
29 | Malta | 4.9 | 28 | HI | ADV |
30 | Bahrain | 4.9 | 29 | HI | MENAP |
31 | Lithuania | 4.9 | 31 | HI | EDE |
32 | Malaysia | 4.9 | 30 | UM | EDA |
33 | Latvia | 4.7 | 39 | HI | ADV |
34 | Spain | 4.7 | 34 | HI-OECD | ADV |
35 | Saudi Arabia | 4.7 | 32 | HI | MENAP |
36 | Cyprus | 4.7 | 37 | HI | ADV |
37 | Slovenia | 4.6 | 36 | HI-OECD | ADV |
38 | Chile | 4.6 | 35 | HI-OECD | LATAM |
39 | Barbados | 4.6 | 55 | HI | LATAM |
40 | Kazakhstan | 4.5 | 38 | UM | CIS |
41 | Russian Federation | 4.5 | 50 | HI | CIS |
42 | Oman | 4.5 | 40 | HI | MENAP |
43 | Czech Republic | 4.5 | 42 | HI-OECD | ADV |
44 | Puerto Rico | 4.5 | 41 | HI | — |
45 | Mauritius | 4.5 | 48 | UM | SSA |
46 | Uruguay | 4.5 | 56 | HI | LATAM |
47 | Macedonia, FYR | 4.4 | 57 | UM | EDE |
48 | Turkey | 4.4 | 51 | UM | EDE |
49 | Costa Rica | 4.4 | 53 | UM | LATAM |
50 | Poland | 4.4 | 54 | HI-OECD | EDE |
51 | Panama | 4.4 | 43 | UM | LATAM |
52 | Jordan | 4.3 | 44 | UM | MENAP |
53 | Hungary | 4.3 | 47 | UM | EDE |
54 | Croatia | 4.3 | 46 | HI | EDE |
55 | Italy | 4.3 | 58 | HI-OECD | ADV |
56 | Montenegro | 4.3 | 52 | UM | EDE |
57 | Azerbaijan | 4.3 | 49 | UM | CIS |
58 | Armenia | 4.2 | 65 | LM | CIS |
59 | Slovak Republic | 4.2 | 59 | HI-OECD | ADV |
60 | Georgia | 4.2 | 60 | LM | CIS |
61 | Mongolia | 4.2 | 61 | LM | EDA |
62 | China | 4.2 | 62 | UM | EDA |
63 | Romania | 4.2 | 75 | UM | EDE |
64 | Colombia | 4.1 | 63 | UM | LATAM |
65 | Sri Lanka | 4.1 | 76 | LM | EDA |
66 | Greece | 4.1 | 74 | HI-OECD | ADV |
67 | Thailand | 4.0 | 67 | UM | EDA |
68 | Moldova | 4.0 | 77 | LM | CIS |
69 | Mexico | 4.0 | 79 | UM | LATAM |
70 | Trinidad and Tobago | 4.0 | 71 | HI | LATAM |
71 | Ukraine | 4.0 | 81 | LM | CIS |
72 | Kuwait | 4.0 | 72 | HI | MENAP |
73 | Bulgaria | 4.0 | 73 | UM | EDE |
74 | Seychelles | 4.0 | 66 | UM | SSA |
75 | South Africa | 4.0 | 70 | UM | SSA |
76 | Philippines | 4.0 | 78 | LM | EDA |
77 | Serbia | 4.0 | 80 | UM | EDE |
78 | Morocco | 3.9 | 99 | LM | MENAP |
79 | Indonesia | 3.9 | 64 | LM | EDA |
80 | El Salvador | 3.9 | 98 | LM | LATAM |
81 | Tunisia | 3.9 | 87 | UM | MENAP |
82 | Jamaica | 3.9 | 86 | UM | LATAM |
83 | Rwanda | 3.9 | 85 | LI | SSA |
84 | Brazil | 3.9 | 69 | UM | LATAM |
85 | Vietnam | 3.9 | 84 | LM | EDA |
86 | Kenya | 3.8 | 92 | LI | SSA |
87 | Cape Verde | 3.8 | 89 | LM | SSA |
88 | Bhutan | 3.7 | 94 | LM | EDA |
89 | India | 3.7 | 83 | LM | EDA |
90 | Peru | 3.7 | 90 | UM | LATAM |
91 | Argentina | 3.7 | 100 | UM | LATAM |
92 | Albania | 3.7 | 95 | UM | EDE |
93 | Guyana | 3.7 | 88 | LM | LATAM |
94 | Egypt | 3.6 | 91 | LM | MENAP |
95 | Dominican Republic | 3.6 | 93 | UM | LATAM |
96 | Iran, Islamic Rep. | 3.6 | 104 | UM | MENAP |
97 | Lao PDR | 3.6 | 109 | LM | EDA |
98 | Kyrgyz Republic | 3.5 | 118 | LM | CIS |
99 | Lebanon | 3.5 | 97 | UM | MENAP |
100 | Honduras | 3.5 | 116 | LM | LATAM |
101 | Ghana | 3.5 | 96 | LM | SSA |
102 | Namibia | 3.5 | 105 | UM | SSA |
103 | Venezuela | 3.4 | 106 | UM | LATAM |
104 | Botswana | 3.4 | 103 | UM | SSA |
105 | Paraguay | 3.4 | 102 | LM | LATAM |
106 | Senegal | 3.3 | 114 | LM | SSA |
107 | Guatemala | 3.3 | 101 | LM | LATAM |
108 | Gambia, The | 3.3 | 107 | LI | SSA |
109 | Bangladesh | 3.3 | 119 | LI | EDA |
110 | Cambodia | 3.3 | 108 | LI | EDA |
111 | Bolivia | 3.3 | 120 | LM | LATAM |
112 | Pakistan | 3.3 | 111 | LM | MENAP |
113 | Suriname | 3.2 | 113 | UM | LATAM |
114 | Zambia | 3.2 | 110 | LM | SSA |
115 | Côte d’Ivoire | 3.2 | 122 | LM | SSA |
116 | Uganda | 3.2 | 115 | LI | SSA |
117 | Tajikistan | 3.2 | — | LI | CIS |
118 | Nepal | 3.2 | 123 | LI | EDA |
119 | Nigeria | 3.2 | 112 | LM | SSA |
120 | Algeria | 3.1 | 129 | UM | MENAP |
121 | Zimbabwe | 3.1 | 117 | LI | SSA |
122 | Gabon | 3.0 | 128 | UM | SSA |
123 | Tanzania | 3.0 | 125 | LI | SSA |
124 | Lesotho | 3.0 | 133 | LM | SSA |
125 | Swaziland | 3.0 | 126 | LM | SSA |
126 | Cameroon | 3.0 | 131 | LM | SSA |
127 | Mali | 3.0 | 127 | LI | SSA |
128 | Nicaragua | 2.9 | 124 | LM | LATAM |
129 | Mozambique | 2.9 | 137 | LI | SSA |
130 | Ethiopia | 2.9 | 130 | LI | SSA |
131 | Libya | 2.9 | 138 | UM | MENAP |
132 | Burkina Faso | 2.8 | 136 | LI | SSA |
133 | Malawi | 2.8 | 132 | LI | SSA |
134 | Timor-Leste | 2.8 | 141 | LM | EDA |
135 | Madagascar | 2.7 | 139 | LI | SSA |
136 | Yemen | 2.7 | 140 | LM | MENAP |
137 | Haiti | 2.5 | 143 | LI | LATAM |
138 | Mauritania | 2.5 | 142 | LM | MENAP |
139 | Myanmar | 2.5 | 146 | LI | EDA |
140 | Angola | 2.5 | 144 | UM | SSA |
141 | Burundi | 2.4 | 147 | LI | SSA |
142 | Guinea | 2.4 | 145 | LI | SSA |
143 | Chad | 2.3 | 148 | LI | SSA |
Note: Income level classification follows the World Bank classification by income (situation as of July 2014). Group classification follows the International Monetary Fund’s classification (situation as of October 2014).
* 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; CIS = Commonwealth of Independent States; EDA = Emerging and developing Asia; LATAM = Latin America and the Caribbean; MENAP = Middle East, North Africa, and Pakistan; SSA = Sub-Saharan Africa.
Table 2: Environment subindex and pillars
ENVIRONMENT SUBINDEX | Political & regulatory environment | Business & innovation environment | ||||
Rank | Country/Economy | Value | Rank | Value | Rank | Value |
1 | Singapore | 5.9 | 2 | 5.9 | 1 | 6.0 |
2 | New Zealand | 5.7 | 1 | 5.9 | 6 | 5.4 |
3 | Finland | 5.6 | 4 | 5.8 | 11 | 5.4 |
4 | United Kingdom | 5.5 | 5 | 5.7 | 9 | 5.4 |
5 | Hong Kong SAR | 5.5 | 12 | 5.4 | 3 | 5.6 |
6 | Norway | 5.5 | 6 | 5.6 | 7 | 5.4 |
7 | Netherlands | 5.5 | 7 | 5.5 | 8 | 5.4 |
8 | Canada | 5.4 | 11 | 5.4 | 4 | 5.5 |
9 | Switzerland | 5.4 | 9 | 5.5 | 10 | 5.4 |
10 | Luxembourg | 5.4 | 3 | 5.8 | 27 | 5.0 |
11 | United Arab Emirates | 5.4 | 20 | 5.1 | 2 | 5.7 |
12 | Ireland | 5.3 | 14 | 5.3 | 13 | 5.3 |
13 | Sweden | 5.3 | 10 | 5.4 | 19 | 5.2 |
14 | United States | 5.3 | 21 | 5.0 | 5 | 5.5 |
15 | Qatar | 5.3 | 17 | 5.3 | 16 | 5.3 |
16 | Denmark | 5.2 | 16 | 5.3 | 18 | 5.2 |
17 | Australia | 5.2 | 15 | 5.3 | 23 | 5.1 |
18 | Japan | 5.2 | 8 | 5.5 | 35 | 4.9 |
19 | Germany | 5.1 | 13 | 5.4 | 31 | 4.9 |
20 | Malaysia | 5.1 | 23 | 5.0 | 21 | 5.1 |
21 | Belgium | 5.1 | 22 | 5.0 | 24 | 5.1 |
22 | Iceland | 5.0 | 27 | 4.9 | 17 | 5.2 |
23 | Estonia | 5.0 | 26 | 4.9 | 25 | 5.0 |
24 | Austria | 5.0 | 18 | 5.2 | 43 | 4.7 |
25 | Israel | 5.0 | 28 | 4.6 | 15 | 5.3 |
26 | France | 4.8 | 25 | 5.0 | 45 | 4.7 |
27 | Chile | 4.8 | 35 | 4.3 | 14 | 5.3 |
28 | Taiwan, China | 4.8 | 38 | 4.3 | 12 | 5.3 |
29 | Saudi Arabia | 4.8 | 32 | 4.5 | 26 | 5.0 |
30 | Portugal | 4.8 | 33 | 4.4 | 20 | 5.2 |
31 | South Africa | 4.8 | 24 | 5.0 | 55 | 4.5 |
32 | Rwanda | 4.7 | 19 | 5.2 | 71 | 4.3 |
33 | Mauritius | 4.7 | 31 | 4.5 | 38 | 4.8 |
34 | Korea, Rep. | 4.6 | 42 | 4.1 | 22 | 5.1 |
35 | Puerto Rico | 4.6 | 29 | 4.6 | 49 | 4.6 |
36 | Malta | 4.6 | 30 | 4.5 | 51 | 4.6 |
37 | Barbados | 4.5 | 37 | 4.3 | 40 | 4.8 |
38 | Jordan | 4.5 | 39 | 4.2 | 36 | 4.9 |
39 | Cyprus | 4.5 | 41 | 4.1 | 30 | 4.9 |
40 | Bahrain | 4.5 | 45 | 4.1 | 29 | 5.0 |
41 | Latvia | 4.5 | 48 | 4.1 | 28 | 5.0 |
42 | Lithuania | 4.5 | 49 | 4.1 | 33 | 4.9 |
43 | Oman | 4.5 | 36 | 4.3 | 46 | 4.7 |
44 | Turkey | 4.4 | 54 | 3.9 | 37 | 4.9 |
45 | Zambia | 4.4 | 64 | 3.8 | 32 | 4.9 |
46 | Macedonia, FYR | 4.4 | 59 | 3.9 | 39 | 4.8 |
47 | Czech Republic | 4.3 | 44 | 4.1 | 58 | 4.5 |
48 | Hungary | 4.3 | 46 | 4.1 | 57 | 4.5 |
49 | Uruguay | 4.3 | 51 | 4.0 | 56 | 4.5 |
50 | Spain | 4.3 | 60 | 3.9 | 47 | 4.7 |
51 | Slovenia | 4.2 | 81 | 3.6 | 34 | 4.9 |
52 | Panama | 4.2 | 73 | 3.6 | 41 | 4.8 |
53 | Poland | 4.2 | 65 | 3.8 | 54 | 4.6 |
54 | Indonesia | 4.2 | 62 | 3.8 | 59 | 4.5 |
55 | Kazakhstan | 4.2 | 61 | 3.9 | 61 | 4.5 |
56 | Montenegro | 4.1 | 90 | 3.5 | 42 | 4.8 |
57 | Jamaica | 4.1 | 58 | 3.9 | 65 | 4.4 |
58 | Croatia | 4.1 | 87 | 3.5 | 44 | 4.7 |
59 | Namibia | 4.1 | 34 | 4.4 | 103 | 3.8 |
60 | Thailand | 4.1 | 89 | 3.5 | 48 | 4.7 |
61 | Ghana | 4.1 | 50 | 4.0 | 88 | 4.1 |
62 | Georgia | 4.0 | 76 | 3.6 | 62 | 4.4 |
63 | Russian Federation | 4.0 | 79 | 3.6 | 63 | 4.4 |
64 | Romania | 4.0 | 72 | 3.7 | 66 | 4.3 |
65 | Cape Verde | 4.0 | 55 | 3.9 | 90 | 4.0 |
66 | Costa Rica | 4.0 | 63 | 3.8 | 78 | 4.1 |
67 | Slovak Republic | 4.0 | 78 | 3.6 | 64 | 4.4 |
68 | Mongolia | 4.0 | 94 | 3.4 | 60 | 4.5 |
69 | Kuwait | 3.9 | 74 | 3.6 | 70 | 4.3 |
70 | Guyana | 3.9 | 68 | 3.7 | 73 | 4.2 |
71 | Botswana | 3.9 | 47 | 4.1 | 106 | 3.8 |
72 | Kenya | 3.9 | 66 | 3.8 | 89 | 4.1 |
73 | Lao PDR | 3.9 | 53 | 3.9 | 96 | 3.9 |
74 | Azerbaijan | 3.9 | 69 | 3.7 | 79 | 4.1 |
75 | Bhutan | 3.9 | 43 | 4.1 | 114 | 3.7 |
76 | Bulgaria | 3.9 | 108 | 3.2 | 50 | 4.6 |
77 | China | 3.9 | 52 | 4.0 | 104 | 3.8 |
78 | Armenia | 3.9 | 107 | 3.2 | 53 | 4.6 |
79 | Seychelles | 3.9 | 56 | 3.9 | 101 | 3.8 |
80 | Morocco | 3.9 | 71 | 3.7 | 83 | 4.1 |
81 | Mexico | 3.9 | 70 | 3.7 | 87 | 4.1 |
82 | Gambia, The | 3.8 | 40 | 4.2 | 126 | 3.5 |
83 | El Salvador | 3.8 | 85 | 3.5 | 75 | 4.2 |
84 | Philippines | 3.8 | 75 | 3.6 | 85 | 4.1 |
85 | Lesotho | 3.8 | 67 | 3.7 | 93 | 3.9 |
86 | Sri Lanka | 3.8 | 77 | 3.6 | 92 | 4.0 |
87 | Senegal | 3.8 | 92 | 3.5 | 82 | 4.1 |
88 | Greece | 3.8 | 106 | 3.2 | 68 | 4.3 |
89 | Trinidad and Tobago | 3.8 | 99 | 3.4 | 76 | 4.2 |
90 | Italy | 3.8 | 102 | 3.3 | 72 | 4.2 |
91 | Dominican Republic | 3.7 | 101 | 3.4 | 80 | 4.1 |
92 | Tajikistan | 3.7 | 57 | 3.9 | 123 | 3.5 |
93 | Iran, Islamic Rep. | 3.7 | 100 | 3.4 | 86 | 4.1 |
94 | Albania | 3.7 | 113 | 3.1 | 69 | 4.3 |
95 | Côte d’Ivoire | 3.7 | 84 | 3.5 | 99 | 3.9 |
96 | Peru | 3.7 | 117 | 3.0 | 67 | 4.3 |
97 | Colombia | 3.7 | 98 | 3.4 | 94 | 3.9 |
98 | Vietnam | 3.6 | 93 | 3.5 | 105 | 3.8 |
99 | Guatemala | 3.6 | 118 | 3.0 | 74 | 4.2 |
100 | Serbia | 3.6 | 110 | 3.1 | 84 | 4.1 |
101 | India | 3.6 | 82 | 3.6 | 115 | 3.7 |
102 | Kyrgyz Republic | 3.6 | 114 | 3.1 | 81 | 4.1 |
103 | Tunisia | 3.6 | 96 | 3.4 | 108 | 3.8 |
104 | Ukraine | 3.6 | 122 | 3.0 | 77 | 4.2 |
105 | Mali | 3.6 | 91 | 3.5 | 116 | 3.7 |
106 | Uganda | 3.6 | 86 | 3.5 | 117 | 3.6 |
107 | Lebanon | 3.5 | 139 | 2.5 | 52 | 4.6 |
108 | Malawi | 3.5 | 80 | 3.6 | 128 | 3.4 |
109 | Honduras | 3.5 | 109 | 3.2 | 102 | 3.8 |
110 | Swaziland | 3.5 | 88 | 3.5 | 125 | 3.5 |
111 | Brazil | 3.5 | 95 | 3.4 | 121 | 3.6 |
112 | Moldova | 3.5 | 124 | 3.0 | 91 | 4.0 |
113 | Ethiopia | 3.5 | 105 | 3.2 | 110 | 3.8 |
114 | Tanzania | 3.5 | 83 | 3.6 | 130 | 3.4 |
115 | Cameroon | 3.5 | 112 | 3.1 | 107 | 3.8 |
116 | Nepal | 3.4 | 120 | 3.0 | 100 | 3.9 |
117 | Pakistan | 3.4 | 121 | 3.0 | 97 | 3.9 |
118 | Burkina Faso | 3.4 | 103 | 3.3 | 122 | 3.5 |
119 | Mozambique | 3.4 | 104 | 3.3 | 120 | 3.6 |
120 | Nigeria | 3.4 | 116 | 3.1 | 111 | 3.8 |
121 | Madagascar | 3.4 | 126 | 2.9 | 95 | 3.9 |
122 | Cambodia | 3.4 | 119 | 3.0 | 113 | 3.7 |
123 | Egypt | 3.3 | 115 | 3.1 | 124 | 3.5 |
124 | Gabon | 3.3 | 111 | 3.1 | 129 | 3.4 |
125 | Bolivia | 3.3 | 97 | 3.4 | 135 | 3.2 |
126 | Paraguay | 3.3 | 133 | 2.6 | 98 | 3.9 |
127 | Timor-Leste | 3.2 | 129 | 2.7 | 109 | 3.8 |
128 | Argentina | 3.2 | 128 | 2.8 | 118 | 3.6 |
129 | Nicaragua | 3.2 | 123 | 3.0 | 131 | 3.4 |
130 | Bangladesh | 3.2 | 135 | 2.6 | 112 | 3.7 |
131 | Zimbabwe | 3.1 | 125 | 2.9 | 132 | 3.3 |
132 | Suriname | 3.1 | 130 | 2.7 | 127 | 3.5 |
133 | Libya | 3.0 | 142 | 2.4 | 119 | 3.6 |
134 | Algeria | 3.0 | 127 | 2.9 | 136 | 3.1 |
135 | Yemen | 2.9 | 140 | 2.5 | 133 | 3.2 |
136 | Burundi | 2.9 | 136 | 2.5 | 134 | 3.2 |
137 | Haiti | 2.9 | 134 | 2.6 | 137 | 3.1 |
138 | Mauritania | 2.8 | 131 | 2.7 | 139 | 3.0 |
139 | Myanmar | 2.7 | 132 | 2.7 | 141 | 2.8 |
140 | Guinea | 2.7 | 137 | 2.5 | 140 | 2.9 |
141 | Venezuela | 2.6 | 143 | 2.2 | 138 | 3.0 |
142 | Chad | 2.5 | 138 | 2.5 | 143 | 2.5 |
143 | Angola | 2.5 | 141 | 2.4 | 142 | 2.6 |
Table 3: Readiness subindex and pillars
READINESS SUBINDEX | Infrastructure | Affordability | Skills | |||||
Rank | Country/Economy | Value | Rank | Value | Rank | Value | Rank | Value |
1 | Finland | 6.7 | 5 | 7.0 | 9 | 6.6 | 1 | 6.5 |
2 | Taiwan, China | 6.4 | 1 | 7.0 | 13 | 6.5 | 23 | 5.8 |
3 | Iceland | 6.4 | 6 | 7.0 | 25 | 6.3 | 13 | 5.9 |
4 | Sweden | 6.4 | 3 | 7.0 | 18 | 6.4 | 28 | 5.7 |
5 | Norway | 6.4 | 1 | 7.0 | 27 | 6.2 | 12 | 5.9 |
6 | Austria | 6.3 | 12 | 6.6 | 5 | 6.7 | 27 | 5.7 |
7 | Australia | 6.3 | 6 | 7.0 | 28 | 6.2 | 17 | 5.9 |
8 | Singapore | 6.3 | 19 | 6.2 | 30 | 6.1 | 2 | 6.5 |
9 | Germany | 6.2 | 13 | 6.6 | 41 | 5.9 | 10 | 6.1 |
10 | Switzerland | 6.2 | 10 | 6.8 | 65 | 5.4 | 3 | 6.4 |
11 | Canada | 6.2 | 6 | 7.0 | 60 | 5.5 | 9 | 6.1 |
12 | United States | 6.1 | 4 | 7.0 | 53 | 5.6 | 33 | 5.6 |
13 | Denmark | 6.0 | 20 | 6.2 | 33 | 6.1 | 19 | 5.8 |
14 | Belgium | 6.0 | 21 | 6.1 | 56 | 5.6 | 4 | 6.3 |
15 | Japan | 6.0 | 17 | 6.3 | 43 | 5.8 | 15 | 5.9 |
16 | Korea, Rep. | 6.0 | 11 | 6.6 | 45 | 5.8 | 39 | 5.5 |
17 | Hong Kong SAR | 6.0 | 28 | 5.8 | 20 | 6.4 | 22 | 5.8 |
18 | Netherlands | 6.0 | 14 | 6.4 | 72 | 5.3 | 6 | 6.2 |
19 | Luxembourg | 5.9 | 18 | 6.3 | 50 | 5.7 | 18 | 5.8 |
20 | Cyprus | 5.9 | 30 | 5.6 | 34 | 6.1 | 11 | 6.0 |
21 | United Kingdom | 5.9 | 15 | 6.3 | 51 | 5.7 | 31 | 5.6 |
22 | Estonia | 5.8 | 23 | 6.1 | 62 | 5.5 | 16 | 5.9 |
23 | Slovenia | 5.8 | 25 | 5.9 | 58 | 5.6 | 24 | 5.8 |
24 | New Zealand | 5.8 | 9 | 6.9 | 101 | 4.2 | 7 | 6.2 |
25 | Malta | 5.7 | 16 | 6.3 | 76 | 5.1 | 29 | 5.7 |
26 | France | 5.7 | 24 | 6.0 | 73 | 5.2 | 14 | 5.9 |
27 | Russian Federation | 5.6 | 39 | 5.0 | 15 | 6.5 | 52 | 5.3 |
28 | Ukraine | 5.6 | 46 | 4.7 | 10 | 6.6 | 36 | 5.6 |
29 | Ireland | 5.6 | 26 | 5.9 | 87 | 4.7 | 8 | 6.1 |
30 | Poland | 5.6 | 36 | 5.1 | 26 | 6.2 | 43 | 5.4 |
31 | Lithuania | 5.6 | 50 | 4.6 | 22 | 6.3 | 25 | 5.7 |
32 | Italy | 5.5 | 37 | 5.0 | 36 | 6.0 | 37 | 5.6 |
33 | Portugal | 5.5 | 41 | 4.9 | 35 | 6.0 | 34 | 5.6 |
34 | Spain | 5.5 | 33 | 5.3 | 40 | 5.9 | 56 | 5.3 |
35 | Kazakhstan | 5.5 | 49 | 4.6 | 11 | 6.6 | 49 | 5.4 |
36 | Czech Republic | 5.5 | 22 | 6.1 | 80 | 5.0 | 53 | 5.3 |
37 | Israel | 5.4 | 31 | 5.6 | 68 | 5.3 | 48 | 5.4 |
38 | Latvia | 5.4 | 43 | 4.8 | 47 | 5.8 | 32 | 5.6 |
39 | Croatia | 5.4 | 47 | 4.7 | 42 | 5.9 | 40 | 5.5 |
40 | Bahrain | 5.3 | 35 | 5.2 | 66 | 5.4 | 41 | 5.5 |
41 | Turkey | 5.3 | 53 | 4.6 | 8 | 6.6 | 80 | 4.8 |
42 | Mongolia | 5.3 | 75 | 4.0 | 6 | 6.7 | 55 | 5.3 |
43 | Mauritius | 5.3 | 77 | 3.9 | 3 | 6.7 | 50 | 5.4 |
44 | Armenia | 5.3 | 57 | 4.4 | 31 | 6.1 | 54 | 5.3 |
45 | Georgia | 5.3 | 59 | 4.3 | 7 | 6.6 | 78 | 4.9 |
46 | Macedonia, FYR | 5.3 | 58 | 4.4 | 29 | 6.1 | 64 | 5.2 |
47 | Romania | 5.2 | 52 | 4.6 | 59 | 5.5 | 38 | 5.5 |
48 | Serbia | 5.2 | 42 | 4.8 | 61 | 5.5 | 66 | 5.1 |
49 | Montenegro | 5.2 | 45 | 4.7 | 75 | 5.2 | 35 | 5.6 |
50 | Panama | 5.2 | 63 | 4.3 | 19 | 6.4 | 82 | 4.8 |
51 | Costa Rica | 5.2 | 91 | 3.3 | 16 | 6.4 | 26 | 5.7 |
52 | Trinidad and Tobago | 5.1 | 67 | 4.3 | 52 | 5.7 | 46 | 5.4 |
53 | Moldova | 5.1 | 69 | 4.2 | 37 | 6.0 | 71 | 5.0 |
54 | United Arab Emirates | 5.1 | 27 | 5.8 | 114 | 3.6 | 21 | 5.8 |
55 | Barbados | 5.0 | 38 | 5.0 | 100 | 4.3 | 20 | 5.8 |
56 | Qatar | 5.0 | 29 | 5.7 | 126 | 3.1 | 5 | 6.3 |
57 | Puerto Rico | 5.0 | 80 | 3.8 | 14 | 6.5 | 87 | 4.7 |
58 | Mexico | 5.0 | 81 | 3.7 | 4 | 6.7 | 92 | 4.5 |
59 | Colombia | 4.9 | 68 | 4.2 | 55 | 5.6 | 77 | 4.9 |
60 | Greece | 4.9 | 40 | 5.0 | 96 | 4.4 | 58 | 5.3 |
61 | Seychelles | 4.9 | 44 | 4.7 | 93 | 4.5 | 42 | 5.4 |
62 | Oman | 4.9 | 61 | 4.3 | 67 | 5.4 | 75 | 4.9 |
63 | Malaysia | 4.9 | 70 | 4.2 | 79 | 5.1 | 57 | 5.3 |
64 | Azerbaijan | 4.9 | 60 | 4.3 | 77 | 5.1 | 68 | 5.1 |
65 | Slovak Republic | 4.8 | 71 | 4.1 | 69 | 5.3 | 69 | 5.1 |
66 | Kuwait | 4.8 | 48 | 4.6 | 85 | 4.8 | 70 | 5.0 |
67 | Uruguay | 4.8 | 51 | 4.6 | 74 | 5.2 | 84 | 4.7 |
68 | Hungary | 4.8 | 65 | 4.3 | 86 | 4.8 | 47 | 5.4 |
69 | Tunisia | 4.8 | 86 | 3.4 | 32 | 6.1 | 76 | 4.9 |
70 | Sri Lanka | 4.8 | 110 | 2.7 | 38 | 6.0 | 30 | 5.6 |
71 | Bulgaria | 4.8 | 34 | 5.2 | 110 | 3.8 | 60 | 5.3 |
72 | Venezuela | 4.7 | 93 | 3.2 | 12 | 6.5 | 90 | 4.5 |
73 | Thailand | 4.7 | 66 | 4.3 | 84 | 4.9 | 73 | 5.0 |
74 | Chile | 4.7 | 54 | 4.5 | 91 | 4.5 | 72 | 5.0 |
75 | Saudi Arabia | 4.7 | 32 | 5.4 | 122 | 3.2 | 45 | 5.4 |
76 | China | 4.7 | 92 | 3.2 | 57 | 5.6 | 59 | 5.3 |
77 | Jamaica | 4.6 | 78 | 3.9 | 71 | 5.3 | 83 | 4.7 |
78 | Bhutan | 4.6 | 72 | 4.1 | 44 | 5.8 | 106 | 3.9 |
79 | Argentina | 4.6 | 62 | 4.3 | n/a | n/a | 79 | 4.9 |
80 | El Salvador | 4.6 | 74 | 4.0 | 63 | 5.4 | 97 | 4.3 |
81 | Jordan | 4.6 | 96 | 3.0 | 70 | 5.3 | 44 | 5.4 |
82 | Kyrgyz Republic | 4.6 | 100 | 3.0 | 39 | 6.0 | 86 | 4.7 |
83 | India | 4.6 | 115 | 2.6 | 1 | 7.0 | 102 | 4.1 |
84 | Vietnam | 4.5 | 127 | 2.1 | 2 | 6.8 | 88 | 4.6 |
85 | Philippines | 4.5 | 73 | 4.1 | 103 | 4.2 | 61 | 5.3 |
86 | Iran, Islamic Rep. | 4.5 | 97 | 3.0 | 46 | 5.8 | 85 | 4.7 |
87 | Morocco | 4.5 | 87 | 3.4 | 24 | 6.3 | 110 | 3.8 |
88 | Albania | 4.4 | 84 | 3.5 | 92 | 4.5 | 65 | 5.2 |
89 | Paraguay | 4.4 | 64 | 4.3 | 81 | 5.0 | 105 | 3.9 |
90 | Egypt | 4.3 | 99 | 3.0 | 17 | 6.4 | 118 | 3.6 |
91 | Brazil | 4.3 | 56 | 4.5 | 89 | 4.6 | 108 | 3.9 |
92 | Cape Verde | 4.3 | 104 | 2.9 | 83 | 5.0 | 74 | 4.9 |
93 | Peru | 4.3 | 90 | 3.3 | 78 | 5.1 | 96 | 4.3 |
94 | Libya | 4.2 | 76 | 3.9 | 98 | 4.3 | 93 | 4.4 |
95 | Suriname | 4.2 | 55 | 4.5 | 119 | 3.4 | 81 | 4.8 |
96 | Indonesia | 4.2 | 98 | 3.0 | 99 | 4.3 | 63 | 5.2 |
97 | Algeria | 4.2 | 83 | 3.7 | 94 | 4.5 | 94 | 4.4 |
98 | Lebanon | 4.1 | 82 | 3.7 | 117 | 3.4 | 51 | 5.3 |
99 | Guyana | 4.1 | 103 | 2.9 | 102 | 4.2 | 62 | 5.2 |
100 | Bangladesh | 4.0 | 109 | 2.8 | 21 | 6.3 | 125 | 3.0 |
101 | Lao PDR | 4.0 | 107 | 2.8 | 64 | 5.4 | 112 | 3.7 |
102 | South Africa | 4.0 | 85 | 3.5 | 107 | 4.1 | 95 | 4.4 |
103 | Cambodia | 3.9 | 108 | 2.8 | 48 | 5.7 | 120 | 3.3 |
104 | Nepal | 3.9 | 133 | 1.9 | 23 | 6.3 | 117 | 3.6 |
105 | Honduras | 3.9 | 113 | 2.6 | 82 | 5.0 | 101 | 4.1 |
106 | Dominican Republic | 3.9 | 88 | 3.3 | 97 | 4.4 | 104 | 4.0 |
107 | Kenya | 3.8 | 94 | 3.1 | 106 | 4.1 | 100 | 4.1 |
108 | Uganda | 3.8 | 112 | 2.7 | 54 | 5.6 | 126 | 3.0 |
109 | Pakistan | 3.6 | 119 | 2.5 | 49 | 5.7 | 133 | 2.6 |
110 | Bolivia | 3.6 | 102 | 2.9 | 120 | 3.3 | 91 | 4.5 |
111 | Ghana | 3.5 | 124 | 2.3 | 105 | 4.1 | 103 | 4.0 |
112 | Gabon | 3.3 | 118 | 2.6 | 108 | 3.9 | 116 | 3.6 |
113 | Nicaragua | 3.3 | 79 | 3.8 | 134 | 2.4 | 114 | 3.7 |
114 | Namibia | 3.3 | 101 | 3.0 | 123 | 3.2 | 113 | 3.7 |
115 | Rwanda | 3.3 | 106 | 2.8 | 111 | 3.7 | 121 | 3.2 |
116 | Botswana | 3.3 | 114 | 2.6 | 131 | 2.6 | 89 | 4.6 |
117 | Guatemala | 3.2 | 95 | 3.0 | 124 | 3.1 | 119 | 3.5 |
118 | Côte d’Ivoire | 3.2 | 89 | 3.3 | 127 | 3.0 | 123 | 3.2 |
119 | Zimbabwe | 3.2 | 128 | 2.1 | n/a | n/a | 99 | 4.2 |
120 | Yemen | 3.1 | 129 | 2.0 | 88 | 4.7 | 134 | 2.5 |
121 | Lesotho | 3.1 | 130 | 2.0 | 121 | 3.3 | 107 | 3.9 |
122 | Swaziland | 3.0 | 116 | 2.6 | 136 | 2.2 | 98 | 4.2 |
123 | Nigeria | 3.0 | 121 | 2.3 | 104 | 4.1 | 135 | 2.5 |
124 | Tajikistan | 3.0 | 136 | 1.6 | 137 | 2.1 | 67 | 5.1 |
125 | Tanzania | 3.0 | 117 | 2.6 | 112 | 3.7 | 132 | 2.6 |
126 | Timor-Leste | 2.8 | 105 | 2.9 | 129 | 2.8 | 130 | 2.8 |
127 | Gambia, The | 2.8 | 125 | 2.2 | 128 | 3.0 | 122 | 3.2 |
128 | Myanmar | 2.8 | 131 | 2.0 | n/a | n/a | 115 | 3.6 |
129 | Senegal | 2.7 | 120 | 2.5 | 130 | 2.6 | 128 | 2.9 |
130 | Mozambique | 2.6 | 137 | 1.3 | 90 | 4.6 | 140 | 2.1 |
131 | Angola | 2.6 | 122 | 2.3 | 118 | 3.4 | 138 | 2.2 |
132 | Burundi | 2.6 | 123 | 2.3 | 133 | 2.4 | 124 | 3.1 |
133 | Ethiopia | 2.6 | 135 | 1.7 | 113 | 3.6 | 137 | 2.3 |
134 | Guinea | 2.5 | 134 | 1.8 | 115 | 3.6 | 141 | 2.1 |
135 | Haiti | 2.5 | 142 | 1.0 | 116 | 3.5 | 127 | 3.0 |
136 | Cameroon | 2.4 | 141 | 1.2 | 132 | 2.4 | 111 | 3.7 |
137 | Zambia | 2.4 | 132 | 2.0 | 138 | 1.6 | 109 | 3.8 |
138 | Chad | 2.4 | 143 | 1.0 | 95 | 4.4 | 143 | 1.8 |
139 | Mauritania | 2.3 | 139 | 1.2 | 109 | 3.8 | 142 | 2.0 |
140 | Malawi | 2.3 | 111 | 2.7 | 139 | 1.5 | 131 | 2.6 |
141 | Burkina Faso | 2.2 | 140 | 1.2 | 125 | 3.1 | 139 | 2.2 |
142 | Madagascar | 2.1 | 126 | 2.2 | 140 | 1.3 | 129 | 2.8 |
143 | Mali | 1.9 | 138 | 1.2 | 135 | 2.3 | 136 | 2.4 |
Table 4: Usage subindex and pillars
USAGE SUBINDEX | Individual usage | Business usage | Government usage | |||||
Rank | Country/Economy | Value | Rank | Value | Rank | Value | Rank | Value |
1 | Sweden | 5.9 | 2 | 6.7 | 3 | 5.9 | 20 | 5.1 |
2 | Singapore | 5.9 | 11 | 6.2 | 14 | 5.3 | 1 | 6.2 |
3 | Finland | 5.9 | 5 | 6.6 | 4 | 5.9 | 17 | 5.2 |
4 | Japan | 5.9 | 13 | 6.2 | 2 | 6.0 | 7 | 5.4 |
5 | Netherlands | 5.9 | 7 | 6.5 | 6 | 5.8 | 13 | 5.3 |
6 | Korea, Rep. | 5.9 | 9 | 6.4 | 12 | 5.4 | 3 | 5.7 |
7 | Luxembourg | 5.8 | 6 | 6.5 | 11 | 5.4 | 11 | 5.4 |
8 | Norway | 5.7 | 3 | 6.7 | 10 | 5.5 | 24 | 5.1 |
9 | Denmark | 5.7 | 1 | 6.8 | 8 | 5.7 | 40 | 4.6 |
10 | United States | 5.7 | 18 | 6.0 | 7 | 5.7 | 14 | 5.3 |
11 | Switzerland | 5.6 | 10 | 6.4 | 1 | 6.1 | 48 | 4.4 |
12 | United Kingdom | 5.6 | 4 | 6.6 | 16 | 5.1 | 16 | 5.2 |
13 | United Arab Emirates | 5.6 | 20 | 5.9 | 27 | 4.5 | 2 | 6.2 |
14 | Germany | 5.5 | 17 | 6.0 | 5 | 5.8 | 31 | 4.8 |
15 | Israel | 5.5 | 28 | 5.6 | 9 | 5.7 | 15 | 5.2 |
16 | New Zealand | 5.4 | 22 | 5.9 | 19 | 5.0 | 10 | 5.4 |
17 | Qatar | 5.4 | 19 | 6.0 | 25 | 4.6 | 5 | 5.5 |
18 | Austria | 5.3 | 21 | 5.9 | 13 | 5.4 | 32 | 4.7 |
19 | Hong Kong SAR | 5.3 | 12 | 6.2 | 18 | 5.1 | 36 | 4.7 |
20 | Australia | 5.3 | 15 | 6.1 | 24 | 4.7 | 23 | 5.1 |
21 | Iceland | 5.3 | 8 | 6.5 | 21 | 4.9 | 42 | 4.5 |
22 | Taiwan, China | 5.3 | 26 | 5.7 | 17 | 5.1 | 21 | 5.1 |
23 | Estonia | 5.3 | 16 | 6.0 | 28 | 4.4 | 6 | 5.5 |
24 | France | 5.3 | 24 | 5.8 | 20 | 4.9 | 18 | 5.1 |
25 | Bahrain | 5.2 | 14 | 6.2 | 49 | 3.9 | 4 | 5.7 |
26 | Canada | 5.2 | 29 | 5.6 | 23 | 4.8 | 22 | 5.1 |
27 | Belgium | 5.1 | 25 | 5.8 | 15 | 5.1 | 43 | 4.5 |
28 | Ireland | 5.1 | 27 | 5.7 | 22 | 4.8 | 33 | 4.7 |
29 | Saudi Arabia | 4.9 | 36 | 5.3 | 42 | 4.0 | 8 | 5.4 |
30 | Malaysia | 4.9 | 57 | 4.6 | 26 | 4.6 | 9 | 5.4 |
31 | Malta | 4.8 | 23 | 5.8 | 37 | 4.0 | 38 | 4.7 |
32 | Lithuania | 4.7 | 37 | 5.3 | 31 | 4.3 | 35 | 4.7 |
33 | Spain | 4.7 | 31 | 5.4 | 45 | 3.9 | 37 | 4.7 |
34 | Portugal | 4.7 | 46 | 4.9 | 33 | 4.2 | 26 | 4.9 |
35 | Oman | 4.6 | 41 | 5.1 | 73 | 3.5 | 19 | 5.1 |
36 | Latvia | 4.6 | 30 | 5.6 | 41 | 4.0 | 51 | 4.3 |
37 | Chile | 4.5 | 52 | 4.7 | 47 | 3.9 | 29 | 4.8 |
38 | Uruguay | 4.4 | 45 | 5.0 | 89 | 3.4 | 27 | 4.8 |
39 | Russian Federation | 4.4 | 43 | 5.1 | 66 | 3.6 | 47 | 4.4 |
40 | Kazakhstan | 4.4 | 51 | 4.7 | 67 | 3.6 | 28 | 4.8 |
41 | Azerbaijan | 4.3 | 59 | 4.5 | 58 | 3.7 | 34 | 4.7 |
42 | Slovenia | 4.3 | 34 | 5.3 | 36 | 4.1 | 84 | 3.6 |
43 | Barbados | 4.3 | 40 | 5.2 | 30 | 4.3 | 101 | 3.5 |
44 | Costa Rica | 4.3 | 56 | 4.6 | 39 | 4.0 | 54 | 4.3 |
45 | Czech Republic | 4.3 | 32 | 5.3 | 32 | 4.2 | 113 | 3.3 |
46 | Italy | 4.2 | 33 | 5.3 | 60 | 3.7 | 76 | 3.7 |
47 | Puerto Rico | 4.2 | 63 | 4.4 | 29 | 4.4 | 68 | 3.9 |
48 | Slovak Republic | 4.2 | 35 | 5.3 | 55 | 3.8 | 88 | 3.6 |
49 | Hungary | 4.2 | 42 | 5.1 | 64 | 3.7 | 69 | 3.9 |
50 | Cyprus | 4.2 | 50 | 4.7 | 51 | 3.9 | 66 | 4.0 |
51 | Jordan | 4.1 | 69 | 4.0 | 50 | 3.9 | 44 | 4.5 |
52 | Macedonia, FYR | 4.1 | 49 | 4.8 | 85 | 3.5 | 59 | 4.1 |
53 | Mauritius | 4.1 | 66 | 4.1 | 57 | 3.8 | 46 | 4.4 |
54 | Poland | 4.1 | 44 | 5.1 | 71 | 3.6 | 86 | 3.6 |
55 | Montenegro | 4.1 | 60 | 4.5 | 83 | 3.5 | 52 | 4.3 |
56 | Croatia | 4.1 | 39 | 5.2 | 92 | 3.4 | 83 | 3.6 |
57 | China | 4.1 | 80 | 3.6 | 46 | 3.9 | 39 | 4.7 |
58 | Kuwait | 4.1 | 38 | 5.2 | 93 | 3.4 | 91 | 3.6 |
59 | Colombia | 4.0 | 77 | 3.8 | 81 | 3.5 | 30 | 4.8 |
60 | Brazil | 4.0 | 62 | 4.4 | 52 | 3.8 | 71 | 3.9 |
61 | Panama | 4.0 | 72 | 3.9 | 40 | 4.0 | 57 | 4.2 |
62 | Turkey | 4.0 | 67 | 4.0 | 53 | 3.8 | 55 | 4.2 |
63 | Greece | 3.9 | 48 | 4.8 | 96 | 3.4 | 82 | 3.6 |
64 | Morocco | 3.9 | 70 | 3.9 | 105 | 3.3 | 41 | 4.6 |
65 | Armenia | 3.9 | 74 | 3.8 | 100 | 3.3 | 45 | 4.5 |
66 | Romania | 3.9 | 61 | 4.5 | 76 | 3.5 | 85 | 3.6 |
67 | South Africa | 3.9 | 68 | 4.0 | 34 | 4.2 | 105 | 3.4 |
68 | Trinidad and Tobago | 3.8 | 58 | 4.5 | 86 | 3.5 | 96 | 3.5 |
69 | Sri Lanka | 3.8 | 106 | 2.6 | 48 | 3.9 | 25 | 5.0 |
70 | Seychelles | 3.8 | 65 | 4.2 | 68 | 3.6 | 79 | 3.7 |
71 | Moldova | 3.8 | 64 | 4.2 | 114 | 3.2 | 65 | 4.0 |
72 | Georgia | 3.8 | 76 | 3.8 | 104 | 3.3 | 50 | 4.3 |
73 | Bulgaria | 3.8 | 47 | 4.9 | 91 | 3.4 | 118 | 3.1 |
74 | Philippines | 3.8 | 89 | 3.2 | 38 | 4.0 | 61 | 4.1 |
75 | Thailand | 3.7 | 75 | 3.8 | 54 | 3.8 | 80 | 3.7 |
76 | Argentina | 3.7 | 54 | 4.6 | 101 | 3.3 | 115 | 3.3 |
77 | Indonesia | 3.7 | 97 | 3.0 | 35 | 4.1 | 63 | 4.1 |
78 | Mongolia | 3.7 | 88 | 3.3 | 69 | 3.6 | 53 | 4.3 |
79 | Mexico | 3.7 | 87 | 3.3 | 72 | 3.6 | 56 | 4.2 |
80 | Serbia | 3.7 | 55 | 4.6 | 126 | 3.0 | 111 | 3.3 |
81 | Tunisia | 3.6 | 81 | 3.5 | 106 | 3.3 | 58 | 4.2 |
82 | Vietnam | 3.6 | 86 | 3.3 | 87 | 3.5 | 60 | 4.1 |
83 | Kenya | 3.6 | 110 | 2.5 | 43 | 3.9 | 49 | 4.4 |
84 | El Salvador | 3.6 | 96 | 3.0 | 59 | 3.7 | 64 | 4.0 |
85 | Rwanda | 3.6 | 132 | 1.8 | 70 | 3.6 | 12 | 5.4 |
86 | Lebanon | 3.6 | 53 | 4.6 | 108 | 3.2 | 130 | 2.8 |
87 | Albania | 3.5 | 79 | 3.6 | 103 | 3.3 | 78 | 3.7 |
88 | Jamaica | 3.5 | 84 | 3.4 | 63 | 3.7 | 94 | 3.5 |
89 | Cape Verde | 3.5 | 82 | 3.4 | 97 | 3.4 | 77 | 3.7 |
90 | Egypt | 3.5 | 73 | 3.9 | 125 | 3.1 | 102 | 3.5 |
91 | Peru | 3.4 | 94 | 3.0 | 90 | 3.4 | 70 | 3.9 |
92 | Botswana | 3.4 | 85 | 3.3 | 102 | 3.3 | 81 | 3.7 |
93 | Dominican Republic | 3.4 | 90 | 3.1 | 77 | 3.5 | 93 | 3.6 |
94 | Ukraine | 3.4 | 78 | 3.7 | 78 | 3.5 | 124 | 2.9 |
95 | Namibia | 3.4 | 95 | 3.0 | 61 | 3.7 | 97 | 3.5 |
96 | Ghana | 3.4 | 91 | 3.1 | 84 | 3.5 | 92 | 3.6 |
97 | Venezuela | 3.3 | 71 | 3.9 | 128 | 3.0 | 117 | 3.1 |
98 | Senegal | 3.3 | 111 | 2.5 | 62 | 3.7 | 73 | 3.8 |
99 | Honduras | 3.3 | 103 | 2.7 | 56 | 3.8 | 106 | 3.4 |
100 | Gambia, The | 3.3 | 115 | 2.3 | 74 | 3.5 | 67 | 4.0 |
101 | Guatemala | 3.3 | 99 | 2.9 | 44 | 3.9 | 123 | 2.9 |
102 | Guyana | 3.2 | 107 | 2.6 | 82 | 3.5 | 89 | 3.6 |
103 | India | 3.2 | 121 | 2.0 | 88 | 3.5 | 62 | 4.1 |
104 | Nigeria | 3.2 | 114 | 2.4 | 79 | 3.5 | 95 | 3.5 |
105 | Bhutan | 3.1 | 108 | 2.6 | 120 | 3.1 | 74 | 3.8 |
106 | Bolivia | 3.1 | 101 | 2.7 | 123 | 3.1 | 98 | 3.5 |
107 | Zambia | 3.1 | 122 | 2.0 | 65 | 3.7 | 87 | 3.6 |
108 | Iran, Islamic Rep. | 3.1 | 100 | 2.9 | 129 | 3.0 | 109 | 3.4 |
109 | Paraguay | 3.1 | 93 | 3.1 | 111 | 3.2 | 125 | 2.9 |
110 | Suriname | 3.0 | 83 | 3.4 | 122 | 3.1 | 133 | 2.7 |
111 | Zimbabwe | 3.0 | 104 | 2.6 | 112 | 3.2 | 112 | 3.3 |
112 | Mali | 3.0 | 113 | 2.4 | 117 | 3.1 | 99 | 3.5 |
113 | Lao PDR | 3.0 | 128 | 1.9 | 75 | 3.5 | 90 | 3.6 |
114 | Cambodia | 3.0 | 105 | 2.6 | 99 | 3.4 | 120 | 3.1 |
115 | Kyrgyz Republic | 3.0 | 98 | 2.9 | 113 | 3.2 | 126 | 2.9 |
116 | Cameroon | 3.0 | 130 | 1.9 | 80 | 3.5 | 103 | 3.5 |
117 | Côte d’Ivoire | 2.9 | 119 | 2.1 | 95 | 3.4 | 114 | 3.3 |
118 | Pakistan | 2.9 | 123 | 2.0 | 94 | 3.4 | 110 | 3.3 |
119 | Gabon | 2.9 | 109 | 2.5 | 118 | 3.1 | 119 | 3.1 |
120 | Bangladesh | 2.9 | 129 | 1.9 | 124 | 3.1 | 75 | 3.7 |
121 | Tajikistan | 2.9 | 116 | 2.3 | 107 | 3.3 | 116 | 3.1 |
122 | Uganda | 2.7 | 135 | 1.7 | 110 | 3.2 | 107 | 3.4 |
123 | Swaziland | 2.7 | 118 | 2.2 | 109 | 3.2 | 127 | 2.9 |
124 | Tanzania | 2.7 | 137 | 1.6 | 121 | 3.1 | 100 | 3.5 |
125 | Burkina Faso | 2.7 | 133 | 1.8 | 131 | 2.9 | 104 | 3.5 |
126 | Ethiopia | 2.7 | 140 | 1.5 | 135 | 2.8 | 72 | 3.8 |
127 | Mozambique | 2.7 | 136 | 1.6 | 116 | 3.1 | 108 | 3.4 |
128 | Nicaragua | 2.7 | 112 | 2.5 | 119 | 3.1 | 137 | 2.5 |
129 | Algeria | 2.7 | 102 | 2.7 | 137 | 2.7 | 134 | 2.7 |
130 | Madagascar | 2.7 | 138 | 1.6 | 98 | 3.4 | 122 | 3.1 |
131 | Nepal | 2.6 | 120 | 2.1 | 127 | 3.0 | 129 | 2.8 |
132 | Malawi | 2.6 | 141 | 1.5 | 115 | 3.2 | 121 | 3.1 |
133 | Mauritania | 2.6 | 117 | 2.2 | 132 | 2.9 | 138 | 2.5 |
134 | Lesotho | 2.5 | 124 | 2.0 | 130 | 3.0 | 135 | 2.7 |
135 | Yemen | 2.5 | 127 | 2.0 | 133 | 2.9 | 132 | 2.7 |
136 | Libya | 2.5 | 92 | 3.1 | 141 | 2.5 | 143 | 1.8 |
137 | Timor-Leste | 2.4 | 125 | 2.0 | 138 | 2.6 | 131 | 2.7 |
138 | Angola | 2.4 | 126 | 2.0 | 143 | 2.4 | 128 | 2.8 |
139 | Haiti | 2.4 | 131 | 1.9 | 134 | 2.8 | 140 | 2.5 |
140 | Guinea | 2.3 | 134 | 1.7 | 136 | 2.8 | 141 | 2.5 |
141 | Myanmar | 2.2 | 139 | 1.6 | 139 | 2.6 | 139 | 2.5 |
142 | Chad | 2.1 | 142 | 1.3 | 142 | 2.5 | 136 | 2.6 |
143 | Burundi | 2.1 | 143 | 1.3 | 140 | 2.5 | 142 | 2.4 |
Table 5: Impact subindex and pillars
IMPACT SUBINDEX | Economic impacts | Social impacts | ||||
Rank | Country/Economy | Value | Rank | Value | Rank | Value |
1 | Singapore | 6.0 | 4 | 5.8 | 1 | 6.2 |
2 | Netherlands | 5.9 | 5 | 5.8 | 3 | 6.1 |
3 | Finland | 5.8 | 1 | 6.1 | 12 | 5.6 |
4 | Sweden | 5.7 | 2 | 6.0 | 16 | 5.5 |
5 | Korea, Rep. | 5.6 | 10 | 5.2 | 4 | 6.0 |
6 | United States | 5.6 | 7 | 5.6 | 11 | 5.6 |
7 | Israel | 5.5 | 6 | 5.7 | 19 | 5.4 |
8 | Switzerland | 5.5 | 3 | 5.9 | 34 | 5.0 |
9 | United Kingdom | 5.5 | 13 | 5.1 | 6 | 5.8 |
10 | Norway | 5.4 | 11 | 5.2 | 7 | 5.7 |
11 | Japan | 5.4 | 12 | 5.1 | 13 | 5.6 |
12 | Luxembourg | 5.3 | 8 | 5.3 | 20 | 5.4 |
13 | Canada | 5.3 | 14 | 5.1 | 9 | 5.6 |
14 | Estonia | 5.3 | 25 | 4.6 | 5 | 6.0 |
15 | Taiwan, China | 5.3 | 17 | 4.9 | 8 | 5.7 |
16 | Hong Kong SAR | 5.2 | 16 | 5.0 | 18 | 5.4 |
17 | Germany | 5.2 | 9 | 5.3 | 31 | 5.1 |
18 | United Arab Emirates | 5.2 | 27 | 4.3 | 2 | 6.1 |
19 | Australia | 5.1 | 24 | 4.6 | 14 | 5.6 |
20 | New Zealand | 5.0 | 26 | 4.5 | 15 | 5.5 |
21 | Denmark | 5.0 | 18 | 4.9 | 30 | 5.1 |
22 | Iceland | 5.0 | 21 | 4.7 | 24 | 5.3 |
23 | France | 5.0 | 22 | 4.7 | 25 | 5.3 |
24 | Ireland | 5.0 | 15 | 5.0 | 38 | 4.9 |
25 | Belgium | 4.9 | 20 | 4.8 | 29 | 5.1 |
26 | Austria | 4.9 | 23 | 4.7 | 26 | 5.2 |
27 | Qatar | 4.8 | 32 | 4.0 | 10 | 5.6 |
28 | Portugal | 4.7 | 30 | 4.0 | 22 | 5.4 |
29 | Lithuania | 4.7 | 28 | 4.2 | 27 | 5.2 |
30 | Malaysia | 4.6 | 31 | 4.0 | 28 | 5.2 |
31 | Malta | 4.5 | 33 | 4.0 | 33 | 5.0 |
32 | Latvia | 4.5 | 35 | 3.9 | 32 | 5.1 |
33 | Bahrain | 4.5 | 48 | 3.5 | 17 | 5.5 |
34 | Spain | 4.5 | 34 | 4.0 | 36 | 4.9 |
35 | Chile | 4.4 | 44 | 3.5 | 23 | 5.3 |
36 | Uruguay | 4.4 | 56 | 3.4 | 21 | 5.4 |
37 | Barbados | 4.3 | 19 | 4.9 | 86 | 3.7 |
38 | Saudi Arabia | 4.3 | 41 | 3.7 | 37 | 4.9 |
39 | Slovenia | 4.3 | 29 | 4.0 | 53 | 4.5 |
40 | Puerto Rico | 4.2 | 37 | 3.8 | 51 | 4.5 |
41 | Costa Rica | 4.1 | 47 | 3.5 | 41 | 4.8 |
42 | Russian Federation | 4.1 | 39 | 3.7 | 48 | 4.6 |
43 | Jordan | 4.1 | 42 | 3.6 | 44 | 4.6 |
44 | Kazakhstan | 4.1 | 52 | 3.5 | 42 | 4.8 |
45 | Oman | 4.1 | 62 | 3.3 | 35 | 4.9 |
46 | Panama | 4.1 | 45 | 3.5 | 46 | 4.6 |
47 | China | 4.0 | 71 | 3.2 | 40 | 4.9 |
48 | Azerbaijan | 4.0 | 49 | 3.5 | 49 | 4.5 |
49 | Hungary | 4.0 | 38 | 3.8 | 63 | 4.3 |
50 | Cyprus | 4.0 | 43 | 3.6 | 59 | 4.4 |
51 | Kenya | 4.0 | 59 | 3.4 | 52 | 4.5 |
52 | Colombia | 3.9 | 69 | 3.2 | 43 | 4.7 |
53 | Czech Republic | 3.9 | 36 | 3.9 | 74 | 4.0 |
54 | Armenia | 3.9 | 50 | 3.5 | 58 | 4.4 |
55 | Macedonia, FYR | 3.9 | 53 | 3.4 | 55 | 4.4 |
56 | Rwanda | 3.9 | 98 | 3.0 | 39 | 4.9 |
57 | Montenegro | 3.9 | 46 | 3.5 | 61 | 4.3 |
58 | Slovak Republic | 3.9 | 57 | 3.4 | 57 | 4.4 |
59 | Turkey | 3.9 | 63 | 3.3 | 50 | 4.5 |
60 | Sri Lanka | 3.9 | 75 | 3.1 | 47 | 4.6 |
61 | Mauritius | 3.8 | 65 | 3.3 | 56 | 4.4 |
62 | Philippines | 3.8 | 55 | 3.4 | 67 | 4.2 |
63 | Croatia | 3.8 | 40 | 3.7 | 80 | 3.9 |
64 | Georgia | 3.8 | 97 | 3.0 | 45 | 4.6 |
65 | Mongolia | 3.8 | 83 | 3.1 | 54 | 4.4 |
66 | Italy | 3.7 | 51 | 3.5 | 75 | 4.0 |
67 | Moldova | 3.7 | 79 | 3.1 | 60 | 4.3 |
68 | Greece | 3.7 | 74 | 3.1 | 65 | 4.3 |
69 | Poland | 3.7 | 54 | 3.4 | 78 | 4.0 |
70 | Thailand | 3.6 | 86 | 3.1 | 66 | 4.2 |
71 | Vietnam | 3.6 | 101 | 2.9 | 62 | 4.3 |
72 | Mexico | 3.6 | 72 | 3.2 | 76 | 4.0 |
73 | India | 3.6 | 92 | 3.0 | 68 | 4.2 |
74 | Indonesia | 3.6 | 78 | 3.1 | 72 | 4.1 |
75 | Brazil | 3.6 | 76 | 3.1 | 73 | 4.0 |
76 | El Salvador | 3.6 | 94 | 3.0 | 69 | 4.2 |
77 | Bulgaria | 3.6 | 61 | 3.3 | 84 | 3.8 |
78 | Senegal | 3.6 | 66 | 3.3 | 81 | 3.8 |
79 | Peru | 3.5 | 96 | 3.0 | 70 | 4.1 |
80 | Romania | 3.5 | 85 | 3.1 | 77 | 4.0 |
81 | Tunisia | 3.5 | 103 | 2.9 | 71 | 4.1 |
82 | Ukraine | 3.5 | 67 | 3.3 | 89 | 3.7 |
83 | Morocco | 3.4 | 120 | 2.6 | 64 | 4.3 |
84 | Egypt | 3.4 | 60 | 3.3 | 100 | 3.5 |
85 | Seychelles | 3.4 | 90 | 3.0 | 85 | 3.8 |
86 | Honduras | 3.4 | 64 | 3.3 | 99 | 3.5 |
87 | Mali | 3.4 | 68 | 3.2 | 98 | 3.5 |
88 | Dominican Republic | 3.4 | 70 | 3.2 | 96 | 3.6 |
89 | Serbia | 3.4 | 80 | 3.1 | 90 | 3.7 |
90 | Cape Verde | 3.4 | 77 | 3.1 | 94 | 3.6 |
91 | Gambia, The | 3.4 | 89 | 3.0 | 88 | 3.7 |
92 | South Africa | 3.4 | 58 | 3.4 | 110 | 3.3 |
93 | Trinidad and Tobago | 3.4 | 84 | 3.1 | 92 | 3.6 |
94 | Argentina | 3.3 | 91 | 3.0 | 91 | 3.7 |
95 | Bhutan | 3.3 | 111 | 2.7 | 79 | 4.0 |
96 | Lao PDR | 3.3 | 88 | 3.0 | 95 | 3.6 |
97 | Guyana | 3.3 | 107 | 2.8 | 83 | 3.8 |
98 | Guatemala | 3.2 | 73 | 3.2 | 109 | 3.3 |
99 | Tajikistan | 3.2 | 93 | 3.0 | 103 | 3.5 |
100 | Bolivia | 3.2 | 108 | 2.8 | 93 | 3.6 |
101 | Jamaica | 3.2 | 82 | 3.1 | 106 | 3.4 |
102 | Kuwait | 3.2 | 119 | 2.7 | 87 | 3.7 |
103 | Albania | 3.2 | 125 | 2.5 | 82 | 3.8 |
104 | Nigeria | 3.1 | 81 | 3.1 | 116 | 3.2 |
105 | Pakistan | 3.1 | 102 | 2.9 | 108 | 3.4 |
106 | Bangladesh | 3.1 | 106 | 2.8 | 105 | 3.4 |
107 | Côte d’Ivoire | 3.1 | 99 | 3.0 | 114 | 3.3 |
108 | Venezuela | 3.1 | 116 | 2.7 | 97 | 3.5 |
109 | Namibia | 3.1 | 105 | 2.8 | 107 | 3.4 |
110 | Cameroon | 3.1 | 87 | 3.0 | 118 | 3.1 |
111 | Botswana | 3.1 | 113 | 2.7 | 101 | 3.5 |
112 | Zambia | 3.1 | 109 | 2.7 | 104 | 3.4 |
113 | Ghana | 3.0 | 121 | 2.6 | 102 | 3.5 |
114 | Kyrgyz Republic | 3.0 | 114 | 2.7 | 112 | 3.3 |
115 | Paraguay | 3.0 | 95 | 3.0 | 124 | 3.0 |
116 | Iran, Islamic Rep. | 3.0 | 110 | 2.7 | 115 | 3.2 |
117 | Lebanon | 2.9 | 104 | 2.9 | 125 | 2.9 |
118 | Cambodia | 2.9 | 112 | 2.7 | 123 | 3.1 |
119 | Mozambique | 2.9 | 117 | 2.7 | 120 | 3.1 |
120 | Zimbabwe | 2.9 | 128 | 2.5 | 113 | 3.3 |
121 | Burkina Faso | 2.9 | 100 | 2.9 | 131 | 2.8 |
122 | Tanzania | 2.9 | 132 | 2.4 | 111 | 3.3 |
123 | Uganda | 2.8 | 122 | 2.5 | 122 | 3.1 |
124 | Madagascar | 2.8 | 129 | 2.5 | 121 | 3.1 |
125 | Malawi | 2.8 | 115 | 2.7 | 127 | 2.8 |
126 | Swaziland | 2.7 | 123 | 2.5 | 126 | 2.9 |
127 | Nepal | 2.7 | 137 | 2.3 | 119 | 3.1 |
128 | Ethiopia | 2.7 | 139 | 2.2 | 117 | 3.2 |
129 | Suriname | 2.6 | 118 | 2.7 | 133 | 2.6 |
130 | Gabon | 2.6 | 130 | 2.5 | 129 | 2.8 |
131 | Nicaragua | 2.6 | 126 | 2.5 | 132 | 2.7 |
132 | Timor-Leste | 2.6 | 131 | 2.4 | 130 | 2.8 |
133 | Lesotho | 2.5 | 138 | 2.2 | 128 | 2.8 |
134 | Algeria | 2.5 | 127 | 2.5 | 136 | 2.6 |
135 | Haiti | 2.4 | 135 | 2.3 | 134 | 2.6 |
136 | Angola | 2.4 | 134 | 2.3 | 135 | 2.6 |
137 | Mauritania | 2.4 | 124 | 2.5 | 139 | 2.3 |
138 | Yemen | 2.4 | 133 | 2.3 | 137 | 2.5 |
139 | Myanmar | 2.4 | 136 | 2.3 | 138 | 2.4 |
140 | Chad | 2.1 | 140 | 2.1 | 140 | 2.2 |
141 | Burundi | 2.1 | 141 | 2.1 | 142 | 2.2 |
142 | Guinea | 2.1 | 142 | 2.0 | 141 | 2.2 |
143 | Libya | 1.8 | 143 | 1.8 | 143 | 1.7 |
Not unexpectedly, advanced economies are better than developing ones at leveraging ICTs. High-income economies dominate the NRI, taking the first 31 places in the overall NRI rankings (see Table 1). The performance of countries in the NRI largely mirrors their position on the development ladder: a higher level of income is typically associated with a higher NRI score (see Figure 2). Forty-four of the 50 high-income economies covered in the NRI rank in the top 50, which otherwise features six upper-middle-income countries, the highest-ranked being Malaysia at 32nd place. At the bottom of the rankings, 26 of the 30 worst-performing countries are low-income or lower-middle-income countries. The only exceptions are Algeria (120th), Gabon (122nd), Libya (131st), and Angola (140th). These oil-rich countries belong to the upper-middle-income category, and they all face major challenges across all components of the Index.
The composition of the top 10 would seem to suggest that “smaller” nations are at an advantage when it comes to networked readiness: seven of the 10 best performers have a population of less than 20 million. Yet, when considering the full sample of economies, Figure 3 reveals that this relationship does not hold and that size is not a key determinant of networked readiness.
Singapore tops the rankings this year, and even though Finland drops to 2nd place, seven of the top 10 economies this year are European. That is one more than in 2014, thanks to Luxembourg (9th), which—along with Japan—enters the top 10 at the expense of the Republic of Korea (12th, down two spots) and Hong Kong SAR (14th, down six). As a result, Singapore is now the only representative of the Asian Tigers in the top 10. Taiwan (China) (18th, down four) also loses significant ground.8 Meanwhile, Japan (10th, up six) continues its progression and enters the top 10. Besides Singapore and Japan, the United States (stable at 7th) is the only other non-European country in the top 10.
In Europe, Northern and Western Europe are home to some of the best connected and most innovation-driven economies in the world. In particular, the Nordics—Finland (2nd), Sweden (3rd), Norway (5th), Denmark (15th), and Iceland (19th)—continue to perform well in the NRI. Indeed, these five countries have featured in the top 20 of every edition since 2012.
The group performance of Western European countries is also strong. The Netherlands (4th), Switzerland (6th), the United Kingdom (8th), and Luxembourg (9th) all appear in the top 10. Ireland (25th) has been stable since 2012, and France (26th)—which has lost three places since 2012—closes the group in the subregion. In Southern Europe, Portugal (28th, up five), Italy (55th, up three), and Greece (66th, up eight) improve significantly from last year on the back of major improvements in government usage, whereas Malta (29th, down one), Spain (34th), and Cyprus (36th, up one) remain quite stable. These largely positive trends contribute to narrowing Southern Europe’s gap with the rest of the region, which had been widening since 2012.
Farther east, thanks to the strong performance of Estonia (22nd) and the steady rise of Latvia (33rd, up six), which is catching up with Lithuania (31st), the Baltic countries are slowly but surely bridging the gap with the Nordics—a remarkable achievement for the three former Soviet Republics. While Estonia has always been in the vanguard, Lithuania and Latvia are breaking away from what was once a fairly homogenous group of Eastern European countries that have joined the European Union (EU) since 2004: Slovenia (37th, down one), the Czech Republic (43rd, down one), Hungary (53rd, down six), Croatia (54th, down eight), and the Slovak Republic (59th, no change) are either stable or losing ground. Meanwhile, Poland has jumped four places to enter the top 50, and Romania—once the worst performer in the European Union—has leapfrogged 12 positions to reach 63rd place, ahead of Bulgaria (73rd, no change).
The divide within the Middle East, North Africa, and Pakistan (MENAP) is the largest among all regions. The United Arab Emirates (UAE; 23rd, up one) and Qatar (27th, down four) continue to lead, ahead of Bahrain (30th), Saudi Arabia (35th), and Oman (42nd), which are all members of the Gulf Cooperation Council (GCC). All owe their success to a very strong commitment to ICT development by their respective governments. Kuwait’s performance (72nd) stands at odds with that of its GCC peers. In the rest of the region, only Jordan (52nd) features in the top half of the rankings. Morocco follows at a middling 78th, but it is the country that has improved the most (21 places) over the past year. Mauritania (138th) remains the region’s worst-performing country, 115 places behind the UAE.
Emerging and developing Asia also presents contrasting pictures. Over 100 places separate the region’s best- and worst-performing economies. Second, with only Malaysia (32nd) featured in the top 60, two-thirds of the countries from the region appear in the bottom half of the rankings; Mongolia (61st), Sri Lanka (65th), and Thailand (67th) all lag some 30 places behind. China is stable in 62nd position, while India continues its decline, dropping a further six to 89th place, both contributing to the disappointing group performance of the BRICS.
Chile (38th, up one) leads in Latin America and the Caribbean, almost 100 places ahead of Haiti (137th), the region’s worst performer. Overall, though, trends in the region are encouraging: 14 of the 23 countries in the region have increased their score since last year; 19 of them have done so since 2012. In particular, Costa Rica (49th, up nine since 2012), Panama (51st, up six), El Salvador (80th, up 23), Peru (90th, up 16), and Bolivia (111th, up 16) have posted some of the largest score gains since 2012.
The performance of sub-Saharan Africa is particularly poor: 30 of the 31 countries included in the sample appear in the bottom half of the NRI rankings. The only exception is Mauritius, at 45th. The country has progressed three places since last year and eight since 2012. Among the large economies of the region, Nigeria drops seven places to 119th. South Africa drops five to 75th—it is now third in the region behind Mauritius and Seychelles (74th). In contrast, Kenya (86th, up six) has been slowly improving since 2012.
When considering the results of the different pillars of the NRI, the relationship with income is very strong for eight of the ten pillars, the two exceptions being the Affordability and the Government usage pillars. Advanced economies outperform the rest of the world in every pillar (see Figure 4) except Affordability. Sub-Saharan Africa is the worst-performing region in all pillars except for the Political and regulatory environment, in which Latin America and the Caribbean obtains the lowest average score.
The divide among the best- and worst-performing countries runs the deepest in terms of Infrastructure, Affordability, and Individual usage. Not unexpectedly, the results in the Infrastructure and Individual usage pillars are similar, because a well-developed infrastructure is a pre-condition to ICT adoption. In addition, although ICTs are becoming increasingly affordable in many developing countries, most sub-Saharan Africa countries lag behind. The difficulty faced by this region in mastering the infrastructure-affordability-usage nexus is particularly worrisome.
Finally, looking at the trends since 2012 reveals that all regions have improved their overall performance to some extent (see Figure 5).9With an average NRI score up 0.5 points since 2012, the Commonwealth of Independent States (CIS) has seen the most progress as a whole. Five of the 10 countries that have improved their NRI score the most are from the CIS, including Armenia and Georgia (see Table 6). Emerging and developing Europe improves by 0.2 points, as does Latin America and the Caribbean. The other regions posts small gains of about 0.1 points, with the exception of sub-Saharan Africa, whose performance has remained stable since 2012.
Key findings
Among the many insights that emerge from the NRI results, five key findings stand out because of their important policy implications: (1) the persistence of digital divides, (2) the need for an Internet revolution, (3) the policymakers’ low-hanging fruit to boost ICT use, (4) ICTs’ contributions to shared prosperity, and (5) a call for better data.
The limits of the mobile revolution and the persistence of digital divides
In the span of just two decades, the number of mobile telephone subscriptions exploded from essentially zero to 6.9 billion.10 The mobile revolution originated in the rich world, and by the year 2000, high-income OECD countries already boasted 50 subscriptions per 100 population. In low-income countries, however, the rate was still less than 1 subscription per 100 population (see Figure 6).11 Thanks to fast-paced growth, the developing world started to bridge this “mobile divide.” Whereas high-income countries still boasted 18 times more subscriptions per 100 population than low-income countries in 2005, this ratio had dropped to 2 times by 2013.
Arguably, the mobile revolution’s influence has been greatest in the developing world, where it has helped address the critical lack of telecommunication infrastructure and improve access and productivity in sectors such as agriculture, health, education, and finance. While this is truly remarkable, one must acknowledge the limits of this mobile revolution.
First, even though there are almost as many mobile telephone subscriptions as people on the planet, this does not imply that everyone owns or is using a mobile phone. The number of mobile subscriptions far exceeds the number of mobile phone users.12 Based on the GSM Association’s estimates that unique mobile subscribers account for about half of mobile cellular subscriptions, ITU reckons that mobile telephony penetration has reached approximately 48 percent globally and 30 percent in least-developed countries.
Second, even in countries where penetration rates exceed 50 percent, vast disparities exist between urban and rural areas. Indeed, parts of the developing world are not yet covered by a mobile network signal. ITU calculates that, at the end of 2012, around 450 million people worldwide still lived out of reach of a mobile signal.13
Third, only so much can be done through 2G mobile telephony, which can carry only voice and text messages. The most compelling and promising solutions for development require more sophisticated technologies: first and foremost is fast and reliable access to the Internet, be it mobile, wireless, or wired access. But the Internet is neither as ubiquitous nor is it spreading as fast as many believe. Beyond mobile telephony, the digital divide still runs deep.
Figure 7 reveals the stubbornly high correlation between income and performance in the ICT usage pillar. In this category, the score gap between high-income economies and the rest of the world is large and has actually been widening since 2012: lower-middle-income and low-income countries are now farther behind than they were in 2012 (see Figure 9). Figure 8 shows that the relationship between income and ICT impacts is almost as strong, providing an illustration of the new digital divide as we termed it in 2013.14
The need for an Internet revolution
The United Nations’ Open Working Group (OWG) on Sustainable Development Goals recommends that the international community “… strive to provide universal and affordable access to internet in least-developed economies by 2020.”15 In light of the current levels and growth trends described below, this milestone appears highly optimistic and will most likely be missed.
Indeed, the Internet remains nonexistent, scarce, unaffordable, or too slow in vast swaths of the developing world. Figure 10 shows the Internet penetration rate by income group and by year since 1997, when data coverage became sufficiently large.16 At the end of 2013, 81 percent of the population of high-income OECD countries used the Internet. The rate among low-income countries was 10 times less—a mere 7.6 percent, which is lower than the penetration rate among OECD countries was in 1997.
In 2013, among the 25 low-income countries studied, five had a penetration rate above 10 percent and only one—Kenya—had a rate exceeding 20 percent. Kenya liberalized its telecommunications sector in the late 1990s and created the Kenya Internet Exchange Point in 2002, which led to a dramatic fall in providers’ operating costs and retail prices and an increase in local content.17 As a result, Internet penetration in Kenya increased from 1 percent in 2002 to 39 percent today—five times the low-income group’s average.
As in the case of mobile telephony, the rural-urban gap in terms of Internet penetration is large. According to ITU, it is even widening in parts of the world.18Data are extremely scant, but the few data points that do exist are telling. In Guatemala, for instance, an urban household is 12 times more likely to be connected to the Internet than a rural one. And ITU reckons that this ratio could be much higher in low-income countries.
The difference in the speed of Internet adoption across countries is striking, too (see Table 7). It took only six years on average for high-income OECD countries to attain 20 percent penetration.19 In contrast, only half of lower-middle-income countries have reached this mark and it took those almost twice as much time. Furthermore, while 90 percent of high-income countries have exceeded the 60 percent threshold, only 15 percent of upper-middle-income countries—and not a single lower-middle-income or low-income country—have reached this mark yet.
In low-income countries, Internet penetration has been growing at double-digit rates, but from a very low base and growth has been slowing lately (see Figure 11). If penetration continued to grow at the same rate as it did from 2011 to 2013—an optimistic supposition given the trajectory usually assumed by technology diffusion—it will take at least another 12 years for the Internet to reach 75 percent of the world’s population. This is very far from the objective set out by the OWG to achieve universal penetration by 2020.
Finally, beyond affordability and infrastructure, the lack of availability of digital content and services represents another significant obstacle to more widespread adoption. Many individuals do not get online simply because there is little content relevant to them. Chapter 1.3 points to solutions for jumpstarting digital content and services ecosystems.
As developing countries leapfrog to 4G technology, thus enabling owners of smartphones to access the Internet, Internet diffusion may accelerate in coming years. Prices of 4G smartphones remain high, but—thanks to innovation and competition—prices are expected to keep falling. Already one-sixth of smartphones sold in 2013 cost less than US$100.20 Leapfrogging and falling prices could usher in the mobile revolution 2.0, a rapid expansion of mobile broadband throughout the world.
At the same time that prices fall, innovative projects could address the lack and cost of infrastructure that hampers the use of smartphones. For instance, Google’s Loon project plans a network of balloons placed in the stratosphere to broadcast a 4G wireless signal in rural and remote areas. This project, still in a pilot phase, is not expected to provide a solution in the short term, but it does indicate the role that breakthrough innovations could play in alleviating the obstacle represented by poor or lacking infrastructure.
Yet it would be ill-advised to assume that the Internet will become ubiquitous soon without further policy action. Policymakers must accelerate liberalization, boost public investment, and work closely with international and domestic businesses to attract private investment and encourage innovation. In this effort, connecting rural areas of developing countries to broadband networks must be a priority. Since those areas lack other infrastructure and access to public services, the benefits brought about by ICTs will have especially momentous impact. Improving the framework conditions and the readiness of the population will also increase the potential of this impact.
Policymakers’ low-hanging fruit to boost ICT use
To achieve this Internet revolution and bridge the digital divides, countries need to build their ICT readiness. This implies long-term, costly investments in infrastructure and in education. But a low-hanging fruit exists in the policymaker toolkit. Governments can accelerate the process through sound regulation and more intense competition. By displaying leadership, they can create an enabling environment and orient private operators toward the best solutions for the system’s long-term cost-effectiveness, quality, and sustainability.
Of course, liberalization bears political costs because it implies breaking the dominant position of well-connected or government-owned firms. However, countries can and must overcome these costs to reap the benefits, which are significant. Liberalization attracts more players and creates competition, which in turn tends to increase the quality of products and services and reduce retail prices. This better system lures more customers and encourages investment, both domestic and foreign, which is used to improve infrastructure and the availability of services. Larger markets also generate economies of scale for operators, thus reducing retail prices further and attracting even more customers. In short, liberalization creates a virtuous circle with lasting and far-reaching effects across the economy.
Figure 12 shows the state of liberalization in 17 categories of ICT services on a scale from 0 (monopoly in all services) to 2 (all services fully liberalized). The blue bars delineate the interquartile range within each region, while the black squares and the blue dots identify the median value and outliers, respectively. Although advanced economies perform better on average than any other group of economies, countries from all regions and at different development stages have liberalized their ICT markets.
The performance of sub-Saharan Africa is noteworthy: on average, the region performs better in terms of liberalization than Emerging and developing Asia or the MENAP regions. Many sub-Saharan African countries have fully liberalized their ICT markets, including several Least Developed Countries (LDCs) and fragile economies: Burkina Faso, Cape Verde, Kenya, Lesotho, Madagascar, Mauritius, Nigeria, Tanzania, and Uganda. This strategy bodes well for the future, and some countries—such as Kenya and Tanzania—are already reaping the benefits of this liberalization in the form of increased investments and use and the introduction of new business models and services.
A byproduct of market liberalization is the creation of Internet exchange points (IXPs). IXPs are physical infrastructures for the exchange of traffic between Internet service providers (ISPs) and other content providers. As countries develop their digital infrastructure, IXPs are used to route domestic traffic exclusively within the country without needing to exchange data through international carriers. This significantly improves the network performance in terms of latency and stability, and it also decreases costs for domestic ISPs.
IXPs can be established with the direct support of the government (as in Nigeria) or by a group of private ISPs (as in Kenya). In both cases, governments provide an essential element, either by playing an active, leadership role in spurring the adoption of this type of technology, or by creating an enabling, competitive environment and properly regulating the existence and provision of this type of services. Governments also play a strategic role in developing IXPs through the construction of Internet backbone networks to connect IXPs to potential users both domestically and abroad.21
ICTs’ contributions to shared prosperity
If harnessed properly, ICTs can create economic opportunities and foster social and political inclusion, ultimately contributing to shared prosperity. The socioeconomic benefits brought about by ICTs are precisely what the Impact subindex of the NRI aims to measure.
ICTs hold the potential for transforming our economies through multiple channels. They boost productivity and reduce transaction and information costs. They allow new models of collaboration that increase workers’ efficiency and flexibility for better work-life balance.
ICTs foster entrepreneurship and create new business models. The past two decades have witnessed the emergence of startups that have disrupted entire industries or created entirely new ones. Some of these startups have since become corporate giants that are transforming our world. Startup incubators now exist in most major cities and provide affordable training, mentorship, and resources to those who wish to start a business. Associated with 3D printing and other technologies, user-friendly, open-source software and inexpensive hardware are contributing to the spread of digital manufacturing among aspiring entrepreneurs, especially among the youth (see Box 2).
Box 2: Fab Labs and digital makers: How information technology is fostering youth entrepreneurship
With the advent of digital manufacturing, “fabrication laboratories” are spreading around the world. These centers provide access to hardware, machines, and open-source software, along with affordable training and mentoring. They encourage collaboration among stakeholders and across disciplines, and are increasingly seen as a powerful way to spur entrepreneurship, address the skills gap, and alleviate youth unemployment while revolutionizing production processes.
In June 2013, the French Ministry for the Economy and Finance (Ministère de l’économie, de l’Industrie et du Numérique) called for projects to finance 14 new fabrication laboratories. In doing so, the government recognized the key role of such structures in spreading a culture of innovation and creating bridges between civil society, the private sector, and the education system. The projects were presented by firms, universities, and private associations. All of these projects were based on partnerships among different stakeholders. Moreover, in the context of the Initiative French Tech—a program launched by the French government to support the creation of startups—the presence of a fabrication lab is one of the requirements for a city (or any geographic entity) to be officially recognized as a “Métropole French Tech.”1
In Italy, the North East Foundation (Fondazione Nord Est), a public-private foundation partnered by local business associations and public institutions, is leading an effort to create a fabrication lab in every high school of the northeast of the country. An online crowdfunding platform was launched in January 2015 to finance labs in 10 schools and a professional training centre.2 Within the current context of reforming the school system, in 2015 the Italian government also plans to launch introductory courses on digital manufacturing in some secondary schools, teaching pupils how to code and use digital technologies to make objects on their own or connecting existing ones to the Internet.3
The largest network of labs is one supported by the Fab Foundation, born as an educational outreach component of MIT’s Center for Bits and Atoms. Today, this community is composed of 472 “Fab Labs” in 71 countries (see Figure A).4 It engages schools, academia, entrepreneurs, and research institutions. To be certified as a Fab Lab by the Fab Foundation, a fabrication laboratory must provide a common set of tools and services and share the objectives and the principles of the “Fab Charter.”
Through crowdfunding and equity-crowdfunding platforms, ICTs also provide alternative sources of credit for individuals and entrepreneurs who do not have access to traditional sources of funding, or even for more established businesses that need to finance their operations. Online marketplaces, such as Lending Club, allow borrowers and lenders to connect directly online, while big data makes it possible to compute a credit score for virtually every human being.
ICTs offer significant social benefits, notably by enabling access to basic services, including financial services and education. Perhaps one of the best examples of how the mobile revolution is changing financial services is M-PESA, the mobile-based money transfer system that was launched in Kenya and Tanzania and is now spreading to the rest of the developing world. In the education arena, the proliferation of massive online open courses (MOOCS) allows people around the world to upgrade their skills, train, or re-train more frequently, more flexibly, and more cheaply than through traditional channels.
Technology is also allowing for a more direct interaction between populations and governments. Improved government online presence can significantly increase the efficiency of public administration. The Internet provides new ways for citizens to participate in the policy- and decision-making processes, especially for those whose voice is usually further from the boardrooms. Open-data initiatives and stronger commitments by governments to making information available online improve transparency, governance, and accountability, because citizens and civil society can now monitor more closely the conduct of civil servants.
Most governments have responded—more or less promptly—to demand for e-participation and have enhanced the provision of e-information, the launch of e-consultation initiatives, and the use of e-decision-making. As a result, we observe significant improvement by most countries in the latest edition of the E-participation Index (indicator 10.04) compiled by UNPAN.
Widespread ICT use by businesses, government, and the population at large is a pre-condition for all these benefits and opportunities to materialize, as confirmed by the NRI results. Figure 13 reveals the nearly perfect relationship between the Usage and Impact subindexes—a linear regression of the latter on the former yields a coefficient of determination (R2) of 0.94.
Better data for better policies
The lack of good data on some of the most basic indicators of socioeconomic performances, let alone ICT-related concepts, is truly alarming, as it can lead to misguided policies and misallocation of resources. In August 2014, UN Secretary-General Ban Ki-moon appointed an Independent Expert Advisory Group (IEAG) on a Data Revolution for Sustainable Development. In its report Mobilising for the Data Revolution, the IEAG referred to data as “the lifeblood of decision-making and the raw material for accountability.”22
To a certain extent, the NRI also suffers from data paucity. Like any benchmarking exercise, it is only as good as its underlying data. The World Economic Forum is fully aware of the limitations of the data and acknowledges the gaps, particularly when it comes to measuring the impacts of ICTs. A handful of data points composing the NRI pre-date 2006, a lag of 10 years, which by ICT standards is appallingly long.
Echoing the UN Secretary-General, the plea for more and better data is reiterated. Governments around the world need to strengthen the capacity of national statistical offices to collect data and preserve their independence, and to support the United Nations’ agencies and other international institutions in their hugely important efforts to collect more reliable, more granular, more timely, more complete, and more harmonized data.
ICTs will both contribute to ushering in the data revolution and benefit from it. ICTs—in all their forms, such as mobile phones, the Internet of things, satellite imagery, and sensors—are revolutionizing the way data are being collected. The new data thus collected will in turn further our understanding of how ICTs are impacting our society.