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The 2022 Report on Deep Packet Inspection (DPI) Test Equipment: World Market Segmentation by City

  • ID: 5385348
  • Report
  • July 2021
  • Region: Global
  • 504 Pages
  • ICON Group International
This report was created for global strategic planners who cannot be content with traditional methods of segmenting world markets. With the advent of a "borderless world", cities become a more important criteria in prioritizing markets, as opposed to regions, continents, or countries. This report covers the top 2,000 cities in over 200 countries. It does so by reporting the estimated market size (in terms of latent demand) for each major city of the world. It then ranks these cities and reports them in terms of their size as a percent of the country where they are located, their geographic region (e.g. Africa, Asia, Europe, Middle East, North America, Latin America), and the total world market.

In this report the author defines the sales of deep packet inspection (DPI) test equipment as including all commonly understood products falling within this broad category, such as tools for computer network packet filtering that examines the data and/or header part of a packet as it passes an inspection point, searching for non-protocol compliance, viruses, spam, intrusions or predefined criteria to decide if the packet can pass or if it needs to be routed to a different destination, or for the purpose of collecting statistical information, irrespective of product packaging, formulation, size, or form. Companies participating in this industry include Solera Networks, Inspect Solutions, merging Technologies, Bivio Networks, and GE Fanuc Intelligent Platforms. In addition to the sources indicated, additional information available to the public via news and/or press releases published by players in the industry was considered in defining and calibrating this category. All figures are in a common currency (U.S. dollars, millions) and are not adjusted for inflation (i.e., they are current values). Exchange rates used to convert to U.S. dollars are averages for the year in question. Future exchange rates are assumed to be constant in the future at the current level (the average of the year of this publication's release in 2021).
Note: Product cover images may vary from those shown
1 Introduction & Methodology
1.1 Overview and Definitions
1.2 Market Potential Estimation Methodology
1.2.1 Overview
1.2.2 What is Latent Demand and the P.I.E.?
1.2.3 The Methodology
1.2.3.1 Step 1. Product Definition and Data Collection
1.2.3.2 Step 2. Filtering and Smoothing
1.2.3.3 Step 3. Filling in Missing Values
1.2.3.4 Step 4. Varying Parameter, Non-Linear Estimation
1.2.3.5 Step 5. Fixed-Parameter Linear Estimation
1.2.3.6 Step 6. Aggregation and Benchmarking
1.3 Frequently Asked Questions (FAQ)
1.3.1 Category Definition
1.3.2 Units
1.3.3 Methodology

2 Using the Data

3 City Segments Ranked by Market Size
3.1 Top 15 Markets
3.2 Markets 16 to 30
3.3 Remaining Cities by Market Rank

4 City Segments in Alphabetical Order
4.1 A: From Aalborg to Azul
4.2 B: From Babahoyo to Byumba Town
4.3 C: From Caaguazu to Częstochowa
4.4 D: From Da Lat to Dzuunmod
4.5 E: From Ebebiyin to Eunos Grc
4.6 F: From Facatativá to Fuzhou
4.7 G: From Gabes to Gyumri
4.8 H: From Ha Long (Hong Gai) to Hyesan
4.9 I: From Ialta (Yalta) to Izmit
4.10 J: From Jabalpur to Jyvaskyla
4.11 K: From Kabankalan to Kyzylorda
4.12 L: From La Banda to Lysychans'k
4.13 M: From Ma`Arrat an Nu`Man to Mzuzu
4.14 N: From Naberezhnye Tchelny to Nzerekore
4.15 O: From Oakville to Ozamis City
4.16 P: From Pabna to Pyongyang
4.17 Q: From Qaemshahr to Quito
4.18 R: From Ra'annana to Rzeszów
4.19 S: From Saanich to Szombathely
4.20 T: From Tabaco to Tyumen
4.21 U: From Uberaba to Uzhhorod
4.22 V: From Vacoas-Phoenix to Vung Tau
4.23 W: From Wa to Wuxi
4.24 X: From Xai-Xai to Xuzhou
4.25 Y: From Yakutsk to Yuhua
4.26 Z: From Zaanstad to Zwolle

5 City Segments Ranked by Country
5.1 Afghanistan
5.2 Albania
5.3 Algeria
5.4 American Samoa
5.5 Andorra
5.6 Angola
5.7 Antigua and Barbuda
5.8 Argentina
5.9 Armenia
5.10 Aruba
5.11 Australia
5.12 Austria
5.13 Azerbaijan
5.14 Bahrain
5.15 Bangladesh
5.16 Barbados
5.17 Belarus
5.18 Belgium
5.19 Belize
5.20 Benin
5.21 Bermuda
5.22 Bhutan
5.23 Bolivia
5.24 Bosnia and Herzegovina
5.25 Botswana
5.26 Brazil
5.27 Brunei
5.28 Bulgaria
5.29 Burkina Faso
5.30 Burundi
5.31 Cambodia
5.32 Cameroon
5.33 Canada
5.34 Cape Verde
5.35 Chad
5.36 Chile
5.37 China
5.38 Christmas Island
5.39 Colombia
5.40 Comoros
5.41 Costa Rica
5.42 Cote D'ivoire
5.43 Croatia
5.44 Cuba
5.45 Cyprus
5.46 Denmark
5.47 Djibouti
5.48 Dominica
5.49 Ecuador
5.50 Egypt
5.51 El Salvador
5.52 Equatorial Guinea
5.53 Eritrea
5.54 Estonia
5.55 Eswatini
5.56 Ethiopia
5.57 Fiji
5.58 Finland
5.59 France
5.60 French Polynesia
5.61 Gabon
5.62 Georgia
5.63 Germany
5.64 Ghana
5.65 Greece
5.66 Greenland
5.67 Grenada
5.68 Guam
5.69 Guatemala
5.70 Guinea
5.71 Guinea-Bissau
5.72 Guyana
5.73 Haiti
5.74 Honduras
5.75 Hong Kong
5.76 Hungary
5.77 Iceland
5.78 India
5.79 Indonesia
5.80 Iran
5.81 Iraq
5.82 Ireland
5.83 Israel
5.84 Italy
5.85 Jamaica
5.86 Japan
5.87 Jordan
5.88 Kazakhstan
5.89 Kenya
5.90 Kiribati
5.91 Kosovo
5.92 Kuwait
5.93 Kyrgyzstan
5.94 Laos
5.95 Latvia
5.96 Lebanon
5.97 Lesotho
5.98 Liberia
5.99 Libya
5.100 Liechtenstein
5.101 Lithuania
5.102 Luxembourg
5.103 Macau
5.104 Macedonia
5.105 Madagascar
5.106 Malawi
5.107 Malaysia
5.108 Mali
5.109 Malta
5.110 Mauritania
5.111 Mauritius
5.112 Mexico
5.113 Micronesia
5.114 Moldova
5.115 Monaco
5.116 Mongolia
5.117 Montenegro
5.118 Morocco
5.119 Mozambique
5.120 Myanmar
5.121 Namibia
5.122 Nauru
5.123 Nepal
5.124 New Caledonia
5.125 New Zealand
5.126 Nicaragua
5.127 Niger
5.128 Nigeria
5.129 Niue
5.130 Norfolk Island
5.131 North Korea
5.132 Norway
5.133 Oman
5.134 Pakistan
5.135 Palau
5.136 Palestine
5.137 Panama
5.138 Papua New Guinea
5.139 Paraguay
5.140 Peru
5.141 Poland
5.142 Portugal
5.143 Puerto Rico
5.144 Qatar
5.145 Romania
5.146 Russia
5.147 Rwanda
5.148 Samoa
5.149 San Marino
5.150 Sao Tome E Principe
5.151 Saudi Arabia
5.152 Senegal
5.153 Serbia
5.154 Seychelles
5.155 Sierra Leone
5.156 Singapore
5.157 Slovakia
5.158 Slovenia
5.159 Somalia
5.160 South Africa
5.161 South Korea
5.162 South Sudan
5.163 Spain
5.164 Sri Lanka
5.165 St. Kitts and Nevis
5.166 St. Lucia
5.167 St. Vincent and the Grenadines
5.168 Sudan
5.169 Suriname
5.170 Sweden
5.171 Switzerland
5.172 Syria
5.173 Taiwan
5.174 Tajikistan
5.175 Tanzania
5.176 Thailand
5.177 The Bahamas
5.178 The British Virgin Islands
5.179 The Cayman Islands
5.180 The Central African Republic
5.181 The Cook Islands
5.182 The Czech Republic
5.183 The Democratic Republic of the Congo
5.184 The Dominican Republic
5.185 The Falkland Islands
5.186 The Gambia
5.187 The Maldives
5.188 The Marshall Islands
5.189 The Netherlands
5.190 The Northern Mariana Islands
5.191 The Philippines
5.192 The Republic of the Congo
5.193 The Solomon Islands
5.194 The U.S. Virgin Islands
5.195 The United Arab Emirates
5.196 The United Kingdom
5.197 The United States
5.198 Timor-Leste
5.199 Togo
5.200 Tonga
5.201 Trinidad and Tobago
5.202 Tunisia
5.203 Turkey
5.204 Turkmenistan
5.205 Tuvalu
5.206 Uganda
5.207 Ukraine
5.208 Uruguay
5.209 Uzbekistan
5.210 Vanuatu
5.211 Venezuela
5.212 Vietnam
5.213 Wallis and Futuna
5.214 Western Sahara
5.215 Yemen
5.216 Zambia
5.217 Zimbabwe

6 Disclaimers, Warranties, and User Agreement Provisions
6.1 Disclaimers & Safe Harbor
6.2 User Agreement Provisions
Note: Product cover images may vary from those shown
This study covers the world outlook for deep packet inspection (DPI) test equipment across more than 2,000 cities. For the year reported, estimates are given for the latent demand, or potential industry earnings (P.I.E.), for the city in question (in millions of U.S. dollars), the percent share the city is of the region, and of the globe. These comparative benchmarks allow the reader to quickly gauge a city vis-à-vis others. Using econometric models which project fundamental economic dynamics within each country and across countries, latent demand estimates are created. This report does not discuss the specific players in the market serving the latent demand, nor specific details at the product level. The study also does not consider short-term cyclicalities that might affect realized sales. The study, therefore, is strategic in nature, taking an aggregate and long-run view, irrespective of the players or products involved.

This study does not report actual sales data (which are simply unavailable, in a comparable or consistent manner in virtually all of the cities of the world). This study gives, however, Professor Parker's estimates for the worldwide latent demand, or the P.I.E., for deep packet inspection (DPI) test equipment. It also shows how the P.I.E. is divided across the world's cities. In order to make these estimates, a multi-stage methodology was employed that is often taught in courses on international strategic planning at graduate schools of business.
Note: Product cover images may vary from those shown
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