Scholarly article on topic 'Evaluation of an Eco-industrial Park Based on a Social Network Analysis'

Evaluation of an Eco-industrial Park Based on a Social Network Analysis Academic research paper on "Civil engineering"

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{"Industrial Ecology" / "Social Network Analysis" / "Industrial Ecology Park"}

Abstract of research paper on Civil engineering, author of scientific article — H.M. Zheng, Y. Zhang, N.J. Yang

Abstract The rapid development of eco-industrial parks is indicative of one practical pattern of theories and methods in industrial ecology. By using a social network analysis method, we could go into the interior of the network and analyze the structural attributes of it, therefore finding out the management problems in the corresponding eco-industrial park. In this paper, we provide a primary guide to establishing evaluation indicators for an eco-industrial park, including the nodal degree, centralization, density, average distance, core-periphery and cohesive sub-groups, as well as other structural attribute indicators like centralizing and closing degrees of the network, or relations of sub-groups. Through this kind of review, we could provide some theoretical bases for evaluating eco-industrial parks, as well as enrich the technologies and methods for the study of industrial ecology. © 2011 Published by Elsevier Ltd.

Academic research paper on topic "Evaluation of an Eco-industrial Park Based on a Social Network Analysis"

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Procedía

ELSEVIER

Environmental Sciences

Procedía Environmental Sciences 13) (20^12) 1624 - 1629

The 18th Biennial Conference of International Society for Ecological Modelling

Evaluation of an Eco-industrial Park Based on a Social

Network Analysis

H.M. Zheng, Y. Zhang , N.J. Yang

State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University,

Xinjiekouwai Street No. 19, Beijing 100875, China

Abstract

The rapid development of eco-industrial parks is indicative of one practical pattern of theories and methods in industrial ecology. By using a social network analysis method, we could go into the interior of the network and analyze the structural attributes of it, therefore finding out the management problems in the corresponding eco-industrial park. In this paper, we provide a primary guide to establishing evaluation indicators for an eco-industrial park, including the nodal degree, centralization, density, average distance, core-periphery and cohesive sub-groups, as well as other structural attribute indicators like centralizing and closing degrees of the network, or relations of subgroups. Through this kind of review, we could provide some theoretical bases for evaluating eco-industrial parks, as well as enrich the technologies and methods for the study of industrial ecology.

© 2011 Published by Elsevier B.'V. Selection and/or peer-review under responsibility of School of Environment, Beijing Normal University.

Keywords: Industrial Ecology; Social Network Analysis; Industrial Ecology Park

1. Introduction

With the development of industrial ecology, the eco-industrial park is developing as a brand-new research field [1-3]. The eco-industrial park is defined as: an industrial park in which enterprises cooperate with each other by using each other's by-products and wastes; through this kind of cooperation, they form an industrial symbiotic network. As one direct practical form of industrial ecology, eco-industrial parks are becoming important research content of industrial ecology.

Since the 1990s, Denmark, America, Japan and Austria have conducted a series of eco-industrial park projects. In China, Guangxi Guigang Company, Guangdong Nanhai, Hunan Changsha, Xinjiang Shihezi,

* Corresponding author. Tel: 81 10-5880-7591; fax: 81 10-5880-7591.

E-mail address: zhangyanyxy@121.com..

1878-0296 © 2011 Published by Elsevier B.V. Selection and/or peer-review under responsibility of School of Environment, Beijing Normal University. doi:10.1016/j.proenv.2012.01.155

Shanghai Wujing, Shandong Lubei, and Tianjin TEDA have also constructed eco-industrial parks. Current research in eco-industrial parks, however, has mostly been concerned with the economic and environmental benefits [4]. We can learn about the running status of symbiotic networks through these studies. However, in order to plan, simulate, optimize and regulate the symbiotic network, it is necessary to go into the interior of the network, so as to analyze its structural attributes, raise evaluation indicators that characterize the network's features, and finally distinguish problems of the network's operation.

2. Evaluation of the Eco-industrial Park Based on Social Network Analysis: A Review

Professor Graedel used statistical indexes of the food web from natural ecosystems for reference in his evaluations of eco-industrial parks [5]. He assessed the business symbiosis in industrial systems through species richness (S) and connectness (C). Dai and Lu put forward the concept of eco-connectness for quantitative assessment of eco-industrial parks to measure the inter-linked relations among enterprises in eco-industrial parks [6]. Qu et al. used ecological community correlation in ecology for reference to put forward a social network index: network density [7]; Liu and Qiao put forward a connectness index study of eco-industrial parks based on the bidirectional nature of material metabolism in eco-industrial systems [8]. They then analyzed the total links, product links, wastes links, and proportion distribution of symbiosis networks. Wang et al. established the weight-considering eco-connectness [9]. Song studied network complexity and analyzed the features of ideal material networks and enterprise symbiotic networks from the aspects of scale, aggregation, connectedness, complexity, small world characteristics, scaleless prosperity, and node influences [10].

An eco-industrial park can be extracted as a symbiotic network, so it is reasonable to use social network analysis. The basic measurement variables of social network analysis have become the important method in the study of industrial symbiosis. An industrial symbiotic network is a network that consists of vertical and lateral links as well as social connectedness. Enterprises are controlled by human beings, so it is a brand new feeling to study symbiotic networks by the social network analysis method. Apparently, the structural attributes of the network, the status of all organizations in the network needed to be studied through social network analysis. Currently, in the field of eco-industrial parks, more and more scholars are using the social network analysis method to do empirical studies.

Ashton first introduced social network analysis into the field of industrial symbiosis in 2008 by analyzing the relations between enterprises and managers of Barceloneta, Puerto Rico. He found that there is a positive correlation between trust and the organization status in the social ranks. Through this study, he proved that social network analysis is an effective tool to detect different relations in industrial ecosystems [11].

Li et al. used social network analysis to study the relations of the key resources of industrial enterprises in terms of products, by-products, and waste [12]. Zheng et al. used the social network analysis method in a structure evolution analysis of the Kalundaborg industrial symbiotic network (changes of industrial symbiotic system in 1975, 1985 and 2000) [13]. He studied the symbiotic scale, the gathering level, mode changes, core nodes and network complexity. Some scholar studied the structure and pattern of Kalundaborg industrial symbiotic network by social network analysis. This helped to deeply understand the social connotation behind material and energy exchanges. For example, they analyzed the structural characteristics of the symbiotic network through network structure analysis and fully understood the roles that organizations play in the network. Up to now, social network analysis has developed into a comprehensive method, not only on the side of information relations but also materials, energy, and information relations. Based on this, social network analysis could be used to analyze the social relation structure and patterns behind the exchanges [14].

3. Conceptual model for eco-industrial Park

(1) Eco-industrial chains and networks of eco-industrial parks

We established eco-industrial chains and networks according to the constitution of the members, and the flowing situations of materials, energy, and information between members of eco-industrial parks. In order to do this, we first confirmed the members of the parks; then we learned about the relation types between members, including exchanges of products, by-products, wastes, and energy, as well as communication of information; finally, we established eco-industrial chains and networks.

(2) Adjacency matrixes of industrial symbiotic networks in eco-industrial parks

Using the administrative boundary as the network boundary, we added some members out of the park who exchange resources with members within the park. On the basis of confirmed members and communications among members, we established a relational data collection. Then we used the directive dichotomous assessment system to judge whether the relation existed or not, we called our system the adjacency matrix. The adjacency matrix is used to describe the direct paths by 0 and 1: build Matrix A, Matrix column position is on behalf of relationship senders, the row position is on behalf of relationship recipients. If there is at least one relation between longitudinal and transverse members, the crossover box should be filled with 1, that is aij =1; otherwise 0, that is aij =0.

(3) Social network models of eco-industrial parks

With social network analysis, we abstracted the park into a network system. The system consists of nodes and paths and it is called the symbiotic network. According to the adjacency matrix of the symbiotic network, we could obtain the symbiotic network models of typical eco-industrial parks under UCINET 6 (see Fig. 1). The models are useful for analyzing social essence reflected in the delivering of materials, energy, and information. Nodes in the network represent members in the park; directed line segments between nodes represent the transferring directions of materials, energy, or information. Since each eco-industrial park is not isolated, they are inevitably connected with rivers, farmland, residential areas, local government, and business organizations outside the park. Therefore, in order to build a relatively complete symbiotic network model, we increased members outside the geographic area in order to truly reflect the symbiotic status of the entire park.

Fig. 1 Social network model of an eco-industrial park

4. Evaluation indicators for eco-industrial park by Social network analysis

There are some basic indicators for network measurement through which we could find out the structure and node position of the network [15]. All indicators can be divided into two categories: 1. Indicators aiming at single node: nodal degree, betweenness degree, and so on; 2. Indicators aiming at the entire network: centralization, density, average distance, core-periphery structure, cohesive sub-group, etc.

Tab. 1 Node characteristic indicators and whole network characteristics analysis

Indicator Connotation Formula

Nodal degree Measure one node's local centralizing ability C Cid(Í)= Li/(n-1) CoD(i)=W(n-1) rd(Í)=(Cid(Í) + Cod(Í))/2

Betweenness degree Measure one node's resource controlling ability C RB n n 2ZZ (i) (i) = 2 k n2 — 3n + 2

Nodal centralization network' s centralizing tendency to minority actors Crd n 2 (Crd max — Crdí) _ 2=1 n — 2

Betweenness centralization Tendency of resources controlled by minority actors Crb n 2 (Crb max — Crbí) _ 2=1 n-1

Density Complete degree-direct ties between nodes D=L/n(n-1)

Average distance Delivery speed-indirect ties between nodes L = 2 * n ( n — 1)

Core-periphery structure Relationship types

Cohesive sub- Overlapping Resource delivery speed

groups degree

Betweeners' Resource delivering mode

(1) Node characteristics evaluation indicators

Centrality is the core indicator that can describe the characteristics of nodes. It reflects the nodes' power, status, and influence distribution in the network. The higher nodal degree one node has, the more it is able to control and influence other members' exchanges. Centrality contains the nodal degree and betweenness degree; the former represents the ability by which one actor connects with other actors; while the latter stands for the ability by which one actor controls other actors.

(2) Whole network characteristics evaluation indicators

Based on the analysis of node characteristics, we should pay attention to the overall features of the entire network in order to compare different networks. Analysis on network overall features mainly contains gathering tendency, close degree, difficulty level of resource delivery, core-periphery structure and cohesive sub-groups, etc. All these lead to concepts of network centralization, density, average distance, core-periphery structure, and cohesive sub-groups.

Centrality describes to what extent one node is in the center of the network; while centralization describes the overall centrality of the network. Additionally, the density of the network indicates how

close it is between different node pairs. It means the direct connection of network members, while the average distance shows any two nodes' average shortest distance, indicating indirect distances among network members. These two indexes both could reflect the closeness degree of the network. Core-periphery structure and cohesive sub-groups are both methods of dividing the network into sub-groups according to connectedness among network members to analyze relations between the sub-groups of the network. To this end, we mainly studied the above characteristics of industrial symbiotic networks in eco-industrial parks.

5. Conclusions and outlooks

In this paper, we provide some evaluation indicators to analyze quantitatively nodes' power and status as well as the centralizing tendency, closeness degree, and sub-group relations of the whole network. All these analyses could support the study of eco-industrial parks in methods and technologies.

Social network analysis is a vast and complex technical system. The characteristics between nodes and the overall characteristics of the network need to be further improved. Combining with the structure of networks such as star structure and symmetrical structure, it is necessary to further analyze the correlation between structure and node characteristics, or between structure and whole network characteristics; then we can analyze the structural patterns of symbiosis networks.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (no. 41171068 and 40701004), the Program for Changjiang Scholars and Innovative Research Team in University (no. IRT0809), the Special Funds of State Key Joint Laboratory of Environment simulation and pollution control (10Z02ESPCN), and the Fundamental Research Funds for the Central Universities.

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