2019 Asia and Pacific Mathematical Contest in Modeling
Problem B
Analysis and Decision-making of Regional Economic Vitality
and Its Influencing Factors
The regional (or urban or provincial) economic vitality is an important part of regional comprehensive competitiveness. In recent years, in order to improve the economic vitality, some regions have launched many preferential policies for stimulating the economy vitality, such as reducing the investment attraction approval steps, providing the capital support to start-ups and lowering the ttlement threshold to attract the talented. However, due to different resource endowments, the policies have different effects in different regions. How to ize the key factors and effectively improve the regional economic vitality is a worth study topic.
In order to study how to improve the regional economic vitality, we have obtained some data. Plea build a suitable model and solve the following problems bad on the data and your own data obtained through survey.
1. The regional (or urban or provincial) economic vitality is affected by variety of factors. Take
a region (or city or province) as an example, plea build the suitable relational model of influencing factors of economic vitality, and study the program of action to improve the regional economic vitality. Analyze the effects on the regional economic vitality change from the perspective of changing trend of population and enterpri vitality.
2. Select a region (or city or province), and analyze the short-term and long-term effects of economic policies transformation on the economic vitality of such region (or city ore province) bad on the suitable data surveyed by you.
3. Measuring the regional economic vitality is a complex issue. Plea lect the suitable index system, establish the mathematical model which analyzes and measures the regional (or urban or provincial) economic vitality, and rank the economic vitality of cities in Attachment 3.
4. If you are a decision-maker of regional economic development, according to the conclusions for Problems 1-3, provide a development proposal for the region (or city or province) discusd in Problem 2 so that the economic vitality in this region prents the benign sustainable development and the regional competitiveness is stronger.
Attachment
(5 attachments in total)
Attachment 1
The quantity of enterpris is an important index to measure the regional economic vitality. The quantity of enterpris has a direct effect on the available job opportunities, and to what extent the resource circulation is promoted, and decides the economic benefits. According to the data, from 2009 to 2018, there were 40,176,400 registered and established enterpris (excluding individual business, the same below) in total in 31 provinces/municipalities directly under the Central Government/autonomous regions (excluding Hong Kong, Macau and Taiwan Province). As of September 2019, 9,753,800 enterpris were cancelled (cancellation rate of 24.28%), and there were still 30,422,600 surviving enterpris. The quantity of enterpris which were registered and established from 2009 to 2018 and survive up in 2019 is as follows (Unit: 10,000):
Table 1: The quantity of enterpris which were registered and established from 2009 to 2018 and survive
up in 2019
Province Quantity of Surviving Enterpris in 2019 (Unit: 10,000)
Heilongjiang 43.6
Jilin 44.4
Liaoning 76.1
Beijing 118.3
Tianjin 43.7
Inner Mongolia 42.1
Xinjiang 31.8
Qinghai 10.0
Tibet 6.7
Ningxia 15.1
Shanxi 55.6
Hebei 134.8
Shandong 243.9
Henan 146.3
Shaanxi 73.0潮州小食
Gansu 43.3
Sichuan 122.4
Chongqing 69.8
Hubei 105.3
Anhui 113.8
Jiangsu 269.4
Shanghai 157.4
Zhejiang 188.5
Guizhou 64.0
Hunan 79.9
故宫景点介绍Jiangxi 66.1
Fujian 105.9
Yunnan 60.6
Guangxi 68.7
Guangdong 420.4
Hainan 21.5
Attachment 2
Since 2013, the growth of quantity of enterpris in China has accelerated. Although the growth in different economic regions is obviously different, the annual quantity of newly-added enterpris in all regions is more than that of last year basically. In terms of region, except the total quantity, in the difference of average quantity of newly-added enterpris per province in four economic regions, the eastern region still maintains a great advantage: the provinces in the eastern region have the largest average registration quantity of enterpris per province and the highest growth, followed by the central region. In the west and northeast, the enterpri vitality is relatively weak. The average quantity of newly-added enterpris per province in the northeast may be surpasd by the western region in recent years. In general, there is still a relatively great difference in the enterpri vitality between regions. However, regardless of region, the annual quantity of newly-added enterpris from 2009 to 2018 was relatively stable.
Four economic regions are divided as follows:
Eastern region: Beijing, Hebei, Tianjin, Shandong, Jiangsu, Shanghai, Zhejiang, Fujian, Guangdong, Hainan
Central region: Shanxi, Henan, Hubei, Hunan, Jiangxi, Anhui
Western region: Chongqing, Sichuan, Guangxi, Guizhou, Yunnan, Shaanxi, Gansu, Ningxia, Xinjiang, Qinghai, Tibet
Northeastern region: Heilongjiang, Jilin, Liaoning, Inner Mongolia
Table 2: Trend in Incremental Changes to Enterpris in Four Economic Regions from 2009 to 2018
(Unit: 10,000)
Year Eastern
Region
Central
Region
Northeastern
Region
Western
Region
2009 7.9 4.4 3.3 2.3
2010 9.4 5.0 3.6 2.6
2011 10.3 5.6 3.8 2.9
2012 9.9 5.7 3.6 3.1
2013 12.7 7.2 4.6 3.7
2014 19.5 11.1 7.0 6.0
2015 23.8 12.9 7.1 7.0
2016 30.3 16.4 8.6 8.6
2017 32.8 19.6 10.1 9.8
2018 35.8 22.6 10.3 10.5
散文《最美的遇见》
Attachment 3
If we look away from economic region and province, and focus on city, in addition to Beijing, Shanghai, Guangzhou and Shenzhen, the cond-tier cities are also worth attention. The data of stock and cancellation distribution of enterpris in Beijing, Shanghai, Guangzhou and Shenzhen and some cond-tier cities are given as follows. (Unit: 10,000)
Table 2: The data of stock and cancellation distribution of enterpris in Beijing, Shanghai, Guangzhou and
Shenzhen and some cond-tier cities (Unit: 10,000)
City
Quantity of Newly-
established Enterpris
from 2009 to 2018音乐卡通图片
Quantity of Surviving
Enterpris in 2019
网购团购网>绿色产品
Quantity of Cancelled
Enterpris from 2009
to 2018
Shanghai 204.8 157.4 47.4 Shenzhen 203.1 174.1 29.0 Beijing 152.1 118.3 33.8 Guangzhou 110.2 89.6 20.6 Chongqing 97.5 69.8 27.7 Chengdu 85.0 60.6 24.4 Nanjing 64.6 55.8 8.8 Hangzhou 64.1 48.7 15.4 Suzhou 63.8 53.6 10.2 Tianjin 62.0 43.7 18.3 Qingdao 55.6 41.0 14.6 Dongguan 53.4 43.4 10.0 Zhengzhou 53.3 43.1 10.2 Wuhan 52.6 39.8 12.8
Xi’an 51.4 37.5 13.9
Ningbo 44.4 31.1 13.4
Changsha 36.8 28.5 8.3红烧狮子头
中国水城Shenyang 33.4 21.8 11.6
Kunming 33.2 23.5 9.7
Attachment 4
The registered capital is an index to measure the enterpri size. In the distribution of enterpri size, there is not so large difference as imagined between the cond-tier cities and Beijing, Shanghai, Guangzhou and Shenzhen. The distribution data of registered capital of enterpri entity are given as follows:
Table 3: Distribution Data of Registered Capital of Enterpri Entity from 2009 to 2018 (Unit: 10,000)
Nationwide Beijing Shanghai Guangzhou Shenzhen Second-tier Cities
>10,000,000 9% 13% 9% 9% 8% 9%
5,000,000-
10,000,000
13% 16% 14% 11% 12% 12%
2,000,000-
5,000,000
16% 16% 16% 13% 12% 15%
1,000,000-
2,000,000
21% 21% 22% 25% 25% 22%
0-1,000,000 40% 35% 39% 42% 44% 42%
Attachment 5
How to narrow the difference in the quantity of enterpris between the cond-tier cities and Beijing, Shanghai, Guangzhou and Shenzhen? “Investment attraction” and “talent attraction policy” may be common methods. Therefore, the “talent attraction” between cities prently becomes increasingly fierce. In fact, the resident population in a region is cloly related to the quantity of enterpris in this region. The data of resident population in 2019 are given as follows.
Table 4: Data of Resident Population and Quantity of Surviving Enterpris in Some Second-tier Cities in
2019
City Quantity of Surviving Enterpris in 2019
Unit: 10,000
Resident Population in 2019
Unit: 10,000
Shanghai 157.4 2419.70 Shenzhen 174.1 1190.84
