Abstracts for CRSA/ACRS First Annual Virtual Conference

1. Optimization of Industrial Distribution
Based on Small-world Networks
—A Case Study of Chaoyang District, Beijing, China
Yibo Yang
Beijing University of Technology
October 2011

2. Outline
 Introduction
○ Networks is everywhere
 Small-world Network and Application
○ Evolving of Small-world Networks
○ Application in Industrial Distribution
○ Proof of Feasibility
 A Case Study of Chaoyang District, Beijing, China
○ Introduction to Chaoyang District
○ Industrial Networks Structure Networks
○ Critical Chain Analysis
○ Distribution Networks Buffer
○ Brief AON Chart
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3. Introduction
• Networks is everywhere
Related to statistical physics, applied mathematics, information
engineering, sociology, biology, management science, etc.
World Wide Web Food Web Social Networks
Copyright: http://marlonacosta.com/ Copyright: www.tutorvista.com Copyright: www.pixmule.com
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4. Small-world Network Model and Application
• Small-world Network Model
○ Systems can be highly clustered, like regular lattices.
○ Systems have small characteristic path lengths, like random graphs.
The structure of Small-world network
Copyright: www.urbagram.net
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5. • Evolving of Small-world Networks
○ Growth: the network initially has m0 nodes and e0 edges, each time
adding 1 new nodes and m edges.
○ Preferential attachment: selected M nodes (M ≥ m) as a new small
world from the existing network randomly. Newly joined nodes
according to the priority of connection probability to select connect
to the local world's m nodes.
○ Ki: vertex degree of the i node
○ SW: Small-world Networks composed of new selected M nodes
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6. • Application in Industrial Distribution
○ Growth: after years of development, the city has a relatively stable
industrial system which formed by a relatively independent industry.
○ Preferential attachment: when a new industry appears, it will give
priority to the related industries of the city; then, In the following
time, Industrial systems will follow a similar law of evolution.
A Case of Industry Evolution
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7. • Proof of Feasibility:
• Characteristic of industries linked
adaptability
exogeneity transitivity
reactivity
imbalance
jump
path
dependence
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8. R(v j ) 1 dvi 1 dvi R(v j )
(ki )  R(vi )  (1   )      (1   )    
jB ( vi ) N (v j ) vi dt vi dt jB(vi ) N (v j )
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9. • System Dynamics Equations
ki 1 R(v j ) 1 R(v j )
 (l  n)  (l  m  n)[(1   )     ]  (l  n) [(1   )     ]
t N jB ( vi ) N (v j ) N jB ( vi ) N (v j )
into the initial conditions: ki (ti )  m
3l  3m  n   2l  2m  
   1  2
l mn l mn
Evolution of the industrial system of urban
area has a characteristic of scale-free
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10. Introduction to Chaoyang District
• Chaoyang District is a district of northeastern Beijing, China,
occupying 475 square kilometers urban area. It is the
largest district
• A total population of
3,642,000 in 2005
• Commercial center
○ over 3,000 foreign
companies
○ 112 Global 500
Companies
○ 47 headquarters of
multinational
companies Chaoyang-World
Chaoyang-beijing
Copyright: http://www.bing.com/maps
Copyright: WWW. wikipedia.org/wki/Chaoyang_District,_Beijing`
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11. Industrial Networks Structure Overall
High-tech manufacturing industry Public software services industry
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12. • Overall structure shows the feature of “small
world networks”
• Obvious characteristics of scale-free networks
○ The distribution of each node (degree) is uneven
• Degree of majority of nodes is small
• Degree of small classes of nodes is large
○ The characteristics of the local concentration
• High-tech manufacturing industry
• Public software services industry
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13. Small Sub-world Networks 1
• High-tech manufacturing industry
Bb2 : food manufacturing industry Bb4 : tobacco industry
Bb5 : textile industry Bb9 : furniture manufacturing industry
Bb13: petroleum ,nuclear fuel industry Bb18: plastic products industry
Bb19 : non-metallic mineral industry Bb21 :non-ferrous metal refining industry
Bb22: metal products industry Bb25 :automotive industry
Bb27 :high-tech manufacturing and software services industry
Bb29: handicrafts and other manufacturing
Ca6 :Loading, Unloading and Other Transport Services
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14. Node ID Clustering Coefficients Nrm Degree
Bb2 —— 50.746
Bb4 —— 44.776
Bb5 1.000 46.269
Bb9 0.500 52.239
Bb13 1.000 40.299
Bb18 0.667 49.254
Bb19 0.667 46.269
Bb21 0.800 46.269
Bb22 0.667 49.254
Bb25 1.000 44.776
Bb27 0.429 47.761
Bb29 0.600 46.269
Ca6 0.242 58.209
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15. Small Sub-world Networks 2
• Public software services industry
Cb2： computer services industry
Cb3： software industry
Bc1： electricity, heat production and supply industry
Ca1： transport industry
Ce1 ：Banking
Ce3 ：insurance
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16. Node ID Clustering Coefficients Nrm Degree
Bc1 1.000 82.090
Ca1 1.000 79.104
Cb2 1.000 82.090
Cb3 1.000 83.582
Ce1 1.000 98.507
Ce3 1.000 98.507
Both high-tech manufacturing industry
and public software services industry are
all in their own “small world”
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17. Critical Industrial Chain Analysis
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18. Industrial Distribution Networks Buffer
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19. Brief AON Chart
18 17 16 14 13 12 1
15 9 6 11 2 5 4
3 10 7
8
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20. References
• Aldrich, H. E., & Kim, P. H. (2007). Small worlds, infinite possibilities? How social networks
affect entrepreneurial team formation and search. Strategic Entrepreneurship Journal, 1(1-
2), 147-165.
• ChinaTouristMaps. (2011). Map of Chaoyang District Beijing. from
http://www.chinatouristmaps.com/provinces/beijing/chaoyang-district.html
• Engel, J. S., & Del-Palacio, I. (2009). Global networks of clusters of innovation:
Accelerating the innovation process. Business Horizons, 52(5), 493-503.
• Frommer, I., & Pundoor, G. (2003). Small-worlds: A review of recent books. Networks,
41(3), 174-180.
• Jerome S. Engel, Itxaso del-palacio. Global Networks of Clusters of Innovation:
Accelerating the Innovation Process[J].Business Horizons,2009,25(5):493-503
• Kristian Moller, Senja Svahn How to Influence the Birth of New Business Fields
[J].Industrial Marketing Management,2009(38):450-458
• Möller, K., & Svahn, S. (2009). How to influence the birth of new business fields —
Network perspective. Industrial Marketing Management, 38(4), 450-458.
• Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of `small-world' networks.
nature, 393(6684), 440-442.
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21. Thank you!
Contact us:
yiboobaby@gmail.com;
yiboobaby@163.com
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