Bharatbook.com from its exhaustive collection has come out with a report, which covers the latent demand outlook for advertising for social media Web sites across the regions of Greater China, including provinces, autonomous regions (Guangxi, Nei Mongol, Ningxia, Xinjiang, Xizang - Tibet), municipalities (Beijing, Chongqing, Shanghai, and Tianjin), special administrative regions (Hong Kong and Macau), and Taiwan (all hereafter referred to as “regions”).

Latent demand (in millions of U.S. dollars), or potential industry earnings (P.I.E.) estimates are given across some 1,100 cities in Greater China. For each major city in question, the percent share the city is of the region and of Greater China is reported. Each major city is defined as an area of “economic population”, as opposed to the demographic population within a legal geographic boundary. For many cities, the economic population is much larger that the population within the city limits; this is especially true for the cities of the Western regions.

For the coastal regions, cities which are close to other major cities or which represent, by themselves, a high percent of the regional population, actual city-level population is closer to the economic population (e.g. in Beijing). Based on this “economic” definition of population, comparative benchmarks allow the reader to quickly gauge a city’s marketing and distribution value vis-à-vis others. 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.

Table Of Contents:

1 INTRODUCTION 9
1.1 Overview 9
1.2 What is Latent Demand and the P.I.E.? 9
1.3 The Methodology 10
1.3.1 Step 1. Product Definition and Data Collection 11
1.3.2 Step 2. Filtering and Smoothing 12
1.3.3 Step 3. Filling in Missing Values 12
1.3.4 Step 4. Varying Parameter, Non-linear Estimation 13
1.3.5 Step 5. Fixed-Parameter Linear Estimation 13
1.3.6 Step 6. Aggregation and Benchmarking 13
2 SUMMARY OF FINDINGS 15
2.1 The Latent Demand in Greater China 15
2.2 Top 100 Cities Sorted By Rank 16
3 ANHUI 20
3.1 Latent Demand by Year - Anhui 20
3.2 Cities Sorted by Rank - Anhui 21
3.3 Cities Sorted Alphabetically - Anhui 22
4 BEIJING 24
4.1 Latent Demand by Year - Beijing 24
4.2 Cities Sorted by Rank - Beijing 25
4.3 Cities Sorted Alphabetically - Beijing 25
5 CHONGQING 26
5.1 Latent Demand by Year - Chongqing 26
5.2 Cities Sorted by Rank - Chongqing 27
5.3 Cities Sorted Alphabetically - Chongqing 28
6 FUJIAN 29
6.1 Latent Demand by Year - Fujian 29
6.2 Cities Sorted by Rank - Fujian 30
6.3 Cities Sorted Alphabetically - Fujian 31

For more information kindly visit: http://www.bharatbook.com/detail.asp?id=187386&rt=The-2011-2016-Outlook-...

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