Cluster Management in ChinaTiyan Shen

Parallel 3.1 Cluster implementation in different parts of the world

12 November 2014

CLUSTER MANAGEMENT IN CHINA

TIYAN SHEN

PEKING UNIVERSITY

17 TH TCI GLOBAL CONFERENCE | CREATING SHARED VALUE THROUGH CLUSTERS FOR A SUSTAINABLE FUTURE

OUTLINE

• Actual Challenges

• Theoretical Research

• Data and Method

• Cluster Management

Economic Development Zone Phenomenon in China

Facing problems

Solution

ACTUAL CHALLENGES

Economic Development Zone

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

STAGE 1Building

infrastructure

STAGE 2Agglomeration without linkage

STAGE 3Cluster and innovation

Chinese economy has passed through three stages of development

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.

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 serviceEmpty city in Ordos, Inner Mongolia, China

Kew way of solving those problems: Forming industry clusters

—Building linkage between enterprises

—Promoting creativity

—Expanding employment

—Accelerating economic growth

THEORETICAL RESEARCH

Research Focus

Industry Cluster Quantitative Identification

Cluster Mapping

Deficiency

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

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)

Industry Cluster Quantitative Identification

http://www.clustermapping.us/cluster

! Above research did not implement in space

—Cluster mapping solved this problem

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

Data

Cluster Identification

Geocoding

Kernal Analysis

DATA AND METHOD

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)

Industrial Enterprises Attribute Table

Cluster Identification

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

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

Step2 : Broad Parameter Choices

Step 3: Clustering Function

7980828144586577788384 23288 5495051454647 613 8 7161215111735102666 91814192023222125244285272829304031343639373843414857746269727576596063616467738789687071 133 35253545586 456

0.7

0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

Result: 87 Industry Professions -> 24 clusters

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 Cluster

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

Geocoding

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.

Automobile Industry Cluster in China(2002)

The exchange rate is 8.3 Yuan per US Dollar (end of 2002)

Automobile Industry Cluster in China(2007)

The exchange rate is 7.3 Yuan per US Dollar (end of 2007)

CLUSTER MANAGEMENT

Four Steps about Cluster Management in China

Future work

Step 1 : Choosing Competitive Industries

According to new structural economics(Justin YifuLin, 2013), when choosing potential competitive industries, government could consult other regions where average wage is twice or triple as high as local.

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.

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.

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.

Future work:

a) Building cluster management platform

Future work:

b) Collecting more data

Web Crawlers Registration on the platform

Tiyan Shen

tyshen@pku.edu.cn

Thanks!

Jie Guo

guojie0414@126.com