Research on the Development Level of Big Data Industry and Its

Contribution to the Economy in China's Provinces

Sen Li

1,2

, Hongyuan Liang

, Yu Yan

and Haiying He

Management School, Shenyang Jianzhu University, Shenyang, China

Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, China

Keywords: Big Data, Economic Growth, Heterogeneity.

Abstract: Based on the endogenous growth theory of economics, this paper puts forward that labor, capital and

technology are the main driving forces to promote economic development.As the symbolic industry of the

fourth technological revolution, big data has been integrated into every corner of the society and become the

core technology element to promote regional economic development. This paper uses judgment matrix and

other methods to calculate the development level of big data in each province. In order to study the

contribution of big data industry to regional economy, this paper constructs a multiple regression model,

taking the regional economic development level as the explained variable, the big data development level as

the core explanatory variable, and labor and capital investment as the control variable. It is found that the big

data industry has become an important force to promote regional economic development. At the same time,

there is heterogeneity in the promotion efficiency of various regions. On this basis, it puts forward some

suggestions on how to accelerate the development of big data industry and promote the coordinated

development of China's provincial economy strategies and suggestions.

1 INTRODUCTION

Big data is a high-tech industry, and China will focus

on its development as a strategic industry. Big data is

the comprehensive application of modern

technologies such as the Internet and cloud computing

to classify and organize massive amounts of data,

thereby providing solid data support for national

management, social governance, and corporate

management. Compared with European and

American countries, China’s big data industry started

late, but after entering the 21st century, China’s

mutual big data industry has made great progress,

especially in the fields of Internet shopping, mobile

payment, e-commerce logistics, etc. Alibaba, JD,

Tencent and other companies have become world-

renowned companies in their respective fields, and

their business scope covers most countries and regions

in the world. The big data industry has become an

important force in promoting the steady and healthy

development of China's economy. (Wang 2021)

believes that big data industry can not only promote

the development of regional economy, but also

https://orcid.org/0000-0002-4391-2582

provide more scientific support for economic

decision-making and help people find the best

solution in complex social economy. Therefore, the

development quality of big data industry has an

important impression on the sustainable development

of economy.

At the same time, we should note that there are

obvious regional differences in the development level

of China's economy. The development level of the

southeast coastal areas is relatively high, and the

development level of the inland areas is relatively low.

The development of China's big data industry also has

a similar situation. Therefore, from the perspective of

the development of the big data industry, we analyze

the heterogeneity of China's provincial economic

growth momentum, and then propose

countermeasures and suggestions to promote the

coordinated development of various regions.

Big data is an emerging industry. At present, from

the perspective of big data industry, it is rare to study

the impact of big data industry on regional economic

and industrial development. For example, (Zhang,

2020) proposed that big data industry is an important

Li, S., Liang, H., Yan, Y. and He, H.

Research on the Development Level of Big Data Industry and Its Contribution to the Economy in China’s Provinces.

DOI: 10.5220/0011179200003440

In Proceedings of the International Conference on Big Data Economy and Digital Management (BDEDM 2022), pages 377-382

ISBN: 978-989-758-593-7

377

cornerstone of China's digital economy in the future,

which can drive the transformation and upgrading of

other industries. (Wu, et al., 2020) used the research

method of big data to predict the growth of local

economy. (Zhu, et al., 2020) proposed that big data

industry can optimize the socialist market economy,

and as a tool of macro-control, it can achieve a win-

win situation between "government" and "market". At

the same time, with the increasingly significant trend

of economic globalization, the role of big data in

international trade is becoming more and more

prominent. (Zhang, 2021) proposed that information

technology plays an important role in the operation of

multinational enterprises. Big data provides important

decision-making basis for enterprises in import and

export trade. At the same time, big data can also help

enterprises explore overseas markets and understand

the different product needs of various countries.

The big data industry can not only become a new

driving force for regional economic development, but

also drive the transformation and upgrading of

traditional entrepreneurship. (Wang, 2020) believes

that based on big data analysis, traditional industries

can more accurately find out the changes loved by

consumers and the trend of market development,

which can help them improve product

competitiveness and enhance the profitability of

enterprises.

It can be seen from the above literature that the

current academic circles generally agree that big data

industry is one of the key areas of future economic and

industrial development, which can inject new power

into the development of regional economy. At the

same time, most of the existing studies are based on

theory, and rarely use the method of data analysis to

conduct empirical research on the contribution of big

data industry to the economy. Therefore, based on the

establishment and evaluation of the development level

of big data industry in various regions of China, this

paper will study the heterogeneity of China's

economic development under the background of big

data.

2 MODEL CONSTRUCTION AND

DATA SOURCE

2.1 Model Construction

The empirical analysis of this paper is divided into two

parts. The first part is to evaluate the development

level of China's provincial big data industry. Build the

index evaluation model of the development level of

big data industry, collect and sort out relevant data to

evaluate the development level of big data industry in

China's provinces and cities.

In order to improve the scientific evaluation of the

development level of big data industry in various

provinces and cities, this paper, based on the analytic

hierarchy process, consults experts and scholars in the

field of big data, re determines the weight of the three

dimensions, and then evaluates the development level

of big data industry in various provinces and cities in

China.

After the judgment matrix is constructed, the

weight of each index is further determined. The

formula is as follows:



(1)

In the analytic hierarchy process, after obtaining

the index weight, it is necessary to further test the

consistency of the results.The calculation process is as

follows:

Firstly, Calculate the consistency index C.I.,

max

−

(2)

Among them, λ

max

is the largest characteristic root

of the matrix constructed in the previous section, and

n is the number of indicators.

Secondly, look up the table to determine the

corresponding average random consistency index R.I.

(random index).

Table 1: Average random consistency index R.I.

Matrix

order

1 2 3 4 5

R.I. 0 0 0.52 0.89 1.12

Finally, calculate the consistency ratio C.R.

(consistency ratio), and compare the calculated

consistency result with 0.1. If C.R.<0.1, the result is

considered to have passed the consistency test.

The second part is the heterogeneity analysis of

China's provincial economic development, which

constructs a multiple regression model, takes the

development level of big data as an important

influencing factor, and analyzes the differences in the

driving factors of China's provincial and municipal

economic development.

In this article, we use the level of development of

big data as an indicator of technological progress.

Therefore, we constructed a model of influencing

factors of China's economic development.

++++=

332211

xxxy

(3)

BDEDM 2022 - The International Conference on Big Data Economy and Digital Management

378

Among them, x

is capital investment, x

is human

investment, x

is the big data development index, and

y is GDP.

2.2 Data Sources

All the data are from China Statistical Yearbook 2019

and Big data Blue Book: China big data development

report No.3.All indicators are cross-sectional data in

2018, and the analysis software is spss19.0.

3 DEVELOPMENT LEVEL OF

BIG DATA INDUSTRY IN EACH

PROVINCE

To evaluate the development level of big data

industry, we need to collect relevant data of big data

industry firstly. At present, as an emerging industry,

the big data industry is still lack of relevant official

statistics. Therefore, this paper get the data from Big

data Blue Book: China big data development report

No.3, which is compiled by the Key Laboratory of big

data strategy. In this report, the development level of

big data industry in each province is evaluated from

three dimensions of government application(GM),

commercial application(CE) and civil application (CI)

from the perspective of big data application. However,

in this report, the weights of the three ways of use are

simply treated, the weights of the three are equal, and

the sum of the three is taken as the comprehensive

evaluation result, as shown in the table below.

Table 2: Big data application level index.

Region GM CE CI Region GM CE CI

BEIJING 24.9 25.2 24.1 HAINAN 13.6 9.8 13.1

GUANGDONG 26.5 22.3 20.6 SHAANXI 12.9 11.2 11.9

ZHEJIANG 14.1 19.3 20.2 YUNNAN 11.1 9.4 15.5

SHANGHAI 22.1 15.5 15.7 HUNAN 12.3 12.4 11.1

GUIZHOU 28.9 7.7 16.2 NINGXIA 8.9 8.4 17.6

JIANGSHU 10.8 20.3 18.4 HUBEI 12.3 11.2 10.6

CHONGQING 20.7 11.7 14.5 QINGHAI 9.7 6.8 14.7

TIANJIN 19.7 11.6 15.5 SHANXI 12.6 5.7 11.0

SHANDONG 15.9 15.2 13.4 JIANGXI 10.8 9.4 8.7

HEBEI 18.6 10.6 13.6 JILIN 9.7 3.9 14.9

HENAN 22.3 9.0 11.5 GANSU 11.3 6.9 9.6

LIAONING 18.9 7.42 14.2 GUAGNXI 12.7 5.2 9.8

FUJIAN 11.3 12.5 14.7 HEILONGJIANG 9.5 3.9 12.8

ANHUI 14.1 14.5 9.4 XINJIANG 5.9 3.7 9.8

SICHUAN 13.4 12.3 12.2 XIZANG 1.5 7.4 1.7

NEIMENGGU 18.0 5.1 13.8

As can be seen from table 2, there are great

differences in the level of Internet application in

various regions. In terms of government application,

Guizhou, Guangdong and Beijing have the highest

index; In terms of commercial application, Beijing,

Guangdong and Jiangsu rank high in the index; In

terms of XX application, Beijing, Guangdong and

Zhejiang rank among the top three in the index. At

the same time, the indexes of these provinces have

exceeded 20, indicating a high level of development.

The three Internet indexes of western inland

provinces such as Tibet and Xinjiang did not exceed

10, ranking the last two of all provinces and cities.

After consulting experts in the field of big data,

we obtained the judgment matrix, and the results are

shown in the table below.

Table 3: Judgment matrix.

GM CE CI

GM 1.00 0.20 0.33

CE 5.00 1.00 2.00

CI 3.00 0.50 1.00

After calculation, the weights of government

applications, commercial applications and civil

applications are (0.1096, 0.5813, 0.3092)

, which

shows that experts generally believe that the

application of big data in the commercial field is the

most important. At the same time,the value of C.R. is

0.0036, so the previous calculation result is correct.

Through the above calculation, we get the weight

of the big data development level indicator, and then

we can determine the big data development index of

each province and city. The calculation results are as

follows:

Table 4: Big data comprehensive development index.

Region Score Region Score Region Score

BEIJING 24.80 LIAONING 10.78 QINGHAI 9.56

GUANGDONG 22.23 FUJIAN 13.07 SHANXI 8.11

ZHEJIANG 19.01 ANHUI 12.86 JIANGXI 9.35

SHANGHAI 16.25 SICHUAN 12.41 JILIN 7.95

GUIZHOU 12.68 NEIMENGGU 9.17 GANSU 8.25

JIANGSHU 18.67 HAINAN 11.26 GUAGNXI 7.42

CHONGQING 13.53 SHAANXI 11.60

HEILONGJIAN

7.22

TIANJIN 13.68 YUNNAN 11.46 XINJIANG 5.85

SHANDONG 14.71 HUNAN 12.00 XIZANG 4.99

HEBEI 12.41 NINGXIA 11.29

HENAN 11.22 HUBEI 11.39

As can be seen from the Table 4, there is a large

gap in the development level of big data industry

Research on the Development Level of Big Data Industry and Its Contribution to the Economy in China’s Provinces

379

among China's provinces. Beijing, Guangdong,

Zhejiang, Jiangsu and other economically developed

regions have higher big data index values and rank

high, while Tibet, Xinjiang, Heilongjiang and other

economically underdeveloped regions have lower

values and rank last. Therefore, it can be

preliminarily judged that there is a correlation

between the development of big data industry and the

level of regional economic development, which needs

to be further tested by regression analysis.

4 ANALYSIS ON THE

CONTRIBUTION OF BIG DATA

TO THE ECONOMY

There is a certain gap in the level of economic

development in various regions of China. In order to

facilitate research, according to the classification

method of the China Bureau of statistics, China's

provinces and cities are divided into four parts: the

eastern region, the central region, the western region

and the northeast region. In traditional economic

theory, capital investment and human investment are

important forces to promote economic growth and

industrial development, and technological progress is

another important factor.

Meanwhile, since China's provinces and cities are

divided into four regions, in the regression analysis,

China, the eastern region, the central region, the

western region and the northeast region are taken as

the research objects to study the heterogeneity of the

contribution of big data to the economic growth of

various regions in China.

4.1 Descriptive Statistical Analysis

Before performing regression analysis, first perform

statistical descriptive analysis on relevant data.

According to the previous division of provinces and

cities in China, the average value of the four main

indicators in each region is calculated. The

calculation results are shown in Table 5.

Table 5: Descriptive statistical analysis.

GDP

(Ten

billion)

Human

Investment

(Million)

Capital

Investment(T

en billion)

Big

Data

Index

East 481.00 20.22 619.12 16.61

Central 321.10 12.50 361.52 10.82

West 153.59 6.25 191.46 9.85

Northeast 189.17 7.32 228.62 8.65

It can be seen from Table 5 that there are obvious

gaps in the economic development levels of various

regions in China. The eastern region has obvious

advantages, its total economic output is even twice

that of the western region or the northeast region.The

central and northeastern regions rank second and

third, and the western region ranks last. At the same

time, human resources, resources and big data index

also showed the same situation. The eastern and

central regions ranked the top two, and the western

and northeastern regions ranked the bottom two.

4.2 Regression Analysis

After descriptive statistical analysis, further

regression analysis of the heterogeneity of economic

development in various regions of China from the

perspective of the big data industry is carried out.As

shown in Table 6, the goodness of fit and F value of

the four regression models are at a high level, and the

significance of each regression coefficient is good.

Table 6: Regression analysis results.

East Central West Northeast

C 9807.43

***

(2.863)

-9814.26

(3.453)

-2415.46

(-0.725)

6579.711

(-0.925)

5.045

(2.324)

4.136

***

(2.912)

12.313

***

(3.660)

26.337

***

(4.234)

0.612

***

(7.925)

0.550

(2.312)

0.588

***

(5.897)

1.804

***

(3.453)

589.01

***

(2.497)

171.338

***

(4.321)

120.65

***

(6.234)

167.87

***

(3.654)

Adjusted

0.998 0.697 0.929 0.926

F 423.41 57.7481 382.699 134.34

Note: the standard deviation in brackets, ***、**、*

indicate the significance level of 1%, 5%, and 10%

respectively.

From Table 6, it can be seen that the driving forces

of economic growth in various regions of China are

obviously heterogeneous. On the whole, the big data

industry has played a key role in the economic

development of various regions. The influencing

factor of the level of big data development has been

tested in the four models, which can show that the

development of the big data industry has a positive

impact on the growth of the regional economy,and the

result passed the test. At the same time, in the eastern

region, the big data industry contributes the most to

the development of the regional economy,the

coefficient is 589.01; while the western region has the

BDEDM 2022 - The International Conference on Big Data Economy and Digital Management

380

least contribution to the regional economy,the

coefficient is 120.65. This is also consistent with the

current distribution of the development level of the

big data industry in various regions in China.

Therefore, in order to accelerate the economic

development level of China's central and western

regions and northeast regions and promote the

coordinated development of China's economy, the

development of the big data industry in these regions

should be accelerated.

5 CONCLUSIONS AND

RECOMMENDATIONS

In this paper, Judgment matrix, multiple linear

regression analysis are adopted to study the

development level of big data industry and its

contribution to regional economy. The main

conclusions can be summarized as follows:

(1)There are great differences in the development

level of big data industry among provinces and cities.

The comprehensive development level of big data

industry is high in economically developed provinces

such as Beijing, Guangdong and Zhejiang. At the

same time, it also ranks high in subdivided fields such

as government application, commercial application

and civil application. The development of big data

industry in inland provinces such as Xinjiang,Tibet

and Heilongjiang is relatively poor and has great room

for improvement.

(2)The development of big data industry has a

positive impact on regional economic growth. At the

same time, among the four regions, the big data

industry contributes the most to the economic

development of the eastern region; The contribution

to the western region is the smallest, and the

contribution to the central region and the northeast

region ranks second and third, which is also in line

with the current distribution of the development level

of big data industry in various regions of China.

Based on the above empirical analysis results, in

order to accelerate the development of big data

industry and promote the high-quality economic

development of provinces and cities, the following

countermeasures and suggestions are put forward.

(1)The big data industry should be included in the

key development plan of the 14th five year plan. At

present, Chinese governments at all levels are

preparing the 14th five year plan. As a medium and

long-term development plan,big data industry should

be regarded as a key industry for governments at all

levels to develop in the next 5-10 years. Support the

big data industry in terms of funds and policies.

Especially in the central and western regions, the local

government should fully understand the importance of

big data industry, and strive to achieve leapfrog

economic development through big data industry.

(2)All regions should take big data enterprises as

key investment targets. Big data related enterprises

have high added value, green environmental

protection and other outstanding advantages, which

meet the requirements of national high-quality

development. All regions should attract and cultivate

big data related enterprises in combination with the

current situation of economic and industrial

development. Actively learn from Guizhou, Inner

Mongolia and other inland provinces the experience

of big data industry investment, and promote the

coordinated development of China's big data industry.

(3)Further strengthen the big data talent training.

Big data industry is a technology intensive industry,

and its high-quality development is inseparable from

excellent talents in the field of big data. At present,

some universities in eastern provinces have opened

big data related majors, which have trained a large

number of talents for the society. Therefore, the

central and western provinces should also add big data

related majors in time according to the needs of the

market to meet the development needs of the local big

data industry.

ACKNOWLEDGMENT

This work was financially supported by 1. Liaoning

Federation of Social Sciences—Study on the

coupling of coordinated development of real estate

and urban economy in Liaoning

Province(NO.2022lslwtkt-049) 2.Department of

Education of Liaoning Province—Research on

coupling development of strategic emerging

industries and traditional industries in Liaoning

Province (NO.lnqn202031).

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