The document discusses cluster management in China. It outlines challenges facing economic development zones in China, such as lack of facilities and weak business linkages. Theoretical research on identifying and mapping industry clusters is discussed, but current methods in China are limited by lack of public data and inability to reflect dynamic cluster boundaries. The document then presents a method using input-output tables and enterprise data to identify 24 industry clusters in China, and uses geocoding and kernel analysis to map the automobile industry cluster in 2002 and 2007. Finally, it proposes a 4-step approach to cluster management in China, and identifies priorities for building management platforms and collecting more data.

1. Cluster Management in China
Tiyan Shen
Parallel 3.1 Cluster implementation in different parts of the world
12 November 2014

2. CLUSTER MANAGEMENT IN CHINA
TIYAN SHEN
PEKING UNIVERSITY

3. OUTLINE
• Actual Challenges
• Theoretical Research
• Data and Method
• Cluster Management
17 TH TCI GLOBAL CONFERENCE | CREATING SHARED VALUE THROUGH CLUSTERS FOR A SUSTAINABLE FUTURE

4. ACTUAL CHALLENGES
 Economic Development Zone Phenomenon in China
 Facing problems
 Solution

5. Chinese economy has passed through three stages of development
STAGE 1
Building
infrastructure
Economic Development Zone
STAGE 2
Agglomeration
without linkage
STAGE 3
Cluster and
innovation
One of the creations in China since its market reforms began in 1979
Types
Economic and technological development zone; High-tech zone; Industry park etc.
Function
Promoting industry agglomeration and forming industrial cluster to stimulate
economic growth

6. There are 171 national economic development zones in China up to 2012
which become support points for local government to expand domestic demand
and promote job growth, and the number is growing.

7. There are a lot of problems with
economic development zones
—Lack of supporting facilities
—Weak linkages between
enterprises
—Low creativeness
—Disorder competition in land
sales market
—Poor public service
Empty city in Ordos, Inner Mongolia, China

8. Kew way of solving those problems:
Forming industry clusters
—Building linkage between enterprises
—Promoting creativity
—Expanding employment
—Accelerating economic growth

9. THEORETICAL RESEARCH
Research Focus
Industry Cluster Quantitative Identification
Cluster Mapping
Deficiency

10.  A lot of research about cluster mainly focus on identification and
explanation
——Cluster identification : definition, recognition, estimation
——Cluster explanation: analyzing the cluster structure, mechanism and
evolutionary process by investigated case

11. Industry Cluster Quantitative Identification
Method Measure For instance
Space Gini
coefficient
Agglomeratio
n
Gleaser;Elson(19
97)
location Quotient Specializatio
n
Alexander(1958)
Input-output
Relatedness
between a
Pair of
Traded
Industries
Leontief(1936)
Principal Component
Analysis
Feser;Bergman(1
990)
Algorithm Porter(2013,2014)
Network Analysis Duque;Rey(2008)

12. ! Above research did not implement in space
—Cluster mapping solved this problem
http://www.clustermapping.us/cluster

13. Cluster mapping does not work in China
—There is no rich public statistic data in China
—Administrative region does not reflect cluster boundary
—How the clusters change over time

14. DATA AND METHOD
Data
Cluster Identification
Geocoding
Kernal Analysis

15. Data Source
2002 and 2007 Input-Output Table of China
1998-2011 China's industrial enterprises above designated size data
Designated size:
1998-2010:
prime operating revenue
> 5 million yuan(about 0.75 million USD)
2011:
prime operating revenue
> 20 million yuan(about 3 million USD)

16. Industrial Enterprises Attribute Table

17. Cluster Identification
Step1 : According to algorithm(Delgado, M., M.E. Porter, and S.
Stern, 2013), we choose three most important indicators in consideration of
Chinese available data
 Locational Correlation ：
 LC-Employmentij=Correlation（Employmentir，Employmentjr）
 LC-Establishmentsij= Correlation（Establishmentsir，Establishmentsjr）
 Input-Output Links
 IOij=max{Inputi→j, Inputi←j ,outputi→j, outputi←j}
Similarity Matrix Mij=[(LC-Employmentij+ LC-Establishmentsij )/2+IOij]/2

18. Step2 : Broad Parameter Choices
Step 3: Clustering Function
7980828144586577788384 23288 5495051454647 613 8 7161215111735102666 91814192023222125244285272829304031343639373843414857746269727576596063616467738789687071 133 35253545586 456
1.6
1.5
1.4
1.3
1.2
1.1
1
0.9
0.8
0.7
Result:
87 Industry Professions -> 24 clusters

19. Industry
code
Industry profession
372 Auto manufacturing
354 Pumps, calves, compressors and similar
machinery manufacturing
335 Industry of colored metals smelting and pressing
391 Electric manufacturing
393 Wire, cable, fiber optic cable, and electrical
equipment manufacturing
395 Other electrical machinery and equipment
manufacturing
399 Household electricity and the electric appliance
manufacturing industry
e.g., Automobile Industry

20. Geocoding
Makeing use of data from Baidu(similar to Chinese Google) mapping web
service
Enriching geographic
coordinates with the address
of China's industrial
enterprises above designated
size

21. Kernel estimation
—Define a window of fixed size and imagine
—Centring this on a number of locations in turn,
—Producing a more spatially ‘smooth’ estimate of variation in λ( s )
—Obtaining by using a fixed grid of quadrats.

22. Automobile Industry Cluster in China(2002)
The exchange rate is 8.3 Yuan per US Dollar (end of 2002)

23. Automobile Industry Cluster in China(2007)
The exchange rate is 7.3 Yuan per US Dollar (end of 2007)

24. CLUSTER MANAGEMENT
Four Steps about Cluster Management in China
Future work

25. Step 1 : Choosing Competitive Industries
According to new structural economics(Justin Yifu
Lin, 2013), when choosing potential competitive
industries, government could consult other regions
where average wage is twice or triple as high as local.

26. Step 2 : Estimating Situation
After choosing competitive industries, government
obtains information(gross industry value, employment,
new products output, average wage, development and so
on ) of the same cluster in local and other region from
space database.

27. Step 3 : Attracting Business
Cluster management cloud is a platform which helps
governments to attract business from a huge number of
enterprise information database according to their own
advantages and competitiveness.
This platform will reduce search cost and improve
the efficiency of matching.

28. Step 4 : Building the infrastructure and soft
environment
What government need to do is to build the
infrastructure and soft environment to produce “pools”,
including labor pool, fund pool, creativity pool, project
pool and so on.

29. Future work:
a) Building cluster management platform

30. Future work:
b) Collecting more data
Web Crawlers Registration on the platform

31. Thanks!
Tiyan Shen
tyshen@pku.edu.cn
Jie Guo
guojie0414@126.com