Energy Procedia 5 (2011) 1682–1688
1876–6102 © 2011 Published by Elsevier Ltd.doi:10.1016/j.egypro.2011.03.287
IACEED2010
Comprehensive evaluation research on circular economic
performance of eco-industrial parks
Li Wenbo
Economic and Management School, Zhejiang Normal University, Jinhua Zhejiang 321004, P.R.China
Abstract
Developing the circular economy is the only way to realize the new industrialization and building eco-industrial parks is an important means to promote circular economy performance. Based on literature mining, firstly, this paper constructs the comprehensive evaluation index system and the index system reflects fully “5R ” basic principles of circular economy. Secondly, considering the interaction among index system and the subjective evaluation of experts is nonlinear, we research the feasibility of applying analytic network process and describe its application steps. Finally, an instance is given and we use the super decision software to calculate the evaluation results.
© 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of RIUDS
Keywords: eco-industrial parks; circular economic performance; comprehnsive evaluation; analytic network process
1. Introduction
“Sustainable development ” was widely recognized in 1980 when the International Union for the Conservation of Nature (I UCN) published the “World Conservation Strategy ”. n accordance to sustainable development, a new form of industrial organization based on circular economy principle, which is called eco-industrial parks, has mushroomed around the world. These parks absorb dense economic power and cultivate a large number of world-class companies and industries. Eco-industrial parks are composed of many companies, nature ecology and residential areas, which establish “producers →consumers →decomposer ” cycle path of industrial systems through simulating the natural system. Establishing the food chain and food web of material flow and energy flow, eco -industrial parks can form
* Corresponding author. Tel.: 86-0579********; E-mail address : sxylwb@zjnu.cn.
dual optimization and coordination development between ecology environment and economy and the enterprise community groups seek ultimately a higher efficiency (Guo-qiang Sun, 2005; Zhi-xue Zhang, 2005). As the basis of eco-industrial parks research, the measurement of circular economy performance
has not a uniform evaluation model. The theory and application literature is still relatively scarce. Therefore, we need urgently an evaluation system and method to test rationally and effectively circular economy development, development potential and development coordination of eco-industrial parks. It is
of great significance both for the eco-industrial parks research and for the regional policy-making.
To improve the result accuracy and operational convenience of economy performance evaluation, qualitative and quantitative analysis should be taken to build evaluation model, in which index system construction and evaluation methods choice is very important. Chun-Wei R.Lin (2004) considered the decision attribute consisted of qualitative attribute and quantitative attribute, and we must pay attention to
the constraint relations. Ji-Feng Ding (2005) pointed out the evaluation index should include subjective
index and objective index. Kurup et al (2005) proposed KWR index of social benefits evaluation of eco-industrial parks: planning and design stage, construction phase, operation phase, refurbishment and decommissioning phase. Helge Bratteb et al (2005) evaluated the eco-efficiency of circular system, and in
his opinion, the key is the evaluation index choice, which included the mass production capacity, recycling rate, energy prices, transportation costs, the cost of waste emissions, secondary raw materials quality standards. Carin Labuschagne et al (2005) proposed economic criteria in judging sustainable development in the manufacturing areas, namely, financial health, economic performance, the potential financial benefits and business opportunities.
The present evaluation approaches on economy performance of eco-industrial parks mainly include analytic hierarchy process (Ming Lei, 2009), data envelopment analysis (Jie Xue, 2009), ecological feedback (Rourke, 1996), input and output analysis (Duchin, 1992) and fuzzy comprehensive evaluation method (Xiao-Peng Li, 2009). But these methods assume the elements of evaluation system are independent. In the real context, it is very difficult to meet these conditions and therefore, the evaluation
error may be very b ig. In 1996, Satty proposed a new evaluation method, called analytic network process,
which is widely used. The method takes into account the dependence among the elements and has a good adaptability for system evaluation processing complex structure. Thus, we introduce analytic network process to evaluate economy performance of eco-industrial parks. The remainder of this paper is organized as following: Firstly, we construct the evaluation index system. Secondly, we describe analytic network process in detail. Thirdly, using survey data on some eco-industrial parks, we test the feasibility
and rationality of this approach. Finally, some conclusions are given.
2.Building evaluation index system
According to the following steps, we construct the comprehensive evaluation index system. Firstly, we collect 92 papers including 58 papers through EBSCO and 34 papers through CNKI. Secondly, based on frequency analysis of key words, we select 20 key words to reflect circular economy performance, as shown in table 1. Thirdly, through expert consulting and principle component analysis, we divide index system into five dimensions, including element, environment, economy, social and management.
Tab.1 The distribution of key words
Key words Circularity Ecology Performance environment resource index evaluation Frequency 68 62 54 51 49 45 39
Key words network process stakeholder system innovation Emission capital
Frequency 35 34 31 28 21 18 16
Key words CSR sustainable development standard management coexistence
Frequency 14 13 9 8 8 61684Li Wenbo / Energy Procedia 5 (2011) 1682–1688
(1) Element dimension. Not surprising, there are strong linkages between elements of eco-industrial
parks and circular economy performance. Through our investigation, Chinese eco-industrial parks are stressed mainly by four elements called dematerialization (A1), circularity (A2), coexistence (A3) and network (A4).
(2) Environment dimension. Environment is also related to circular economy performance of eco-
industrial parks. We can select four items to reflect environment dimension including resource utilization (B1), emission process (B2), interactions (B3) and situation management (B4).
(3) Economy dimension. Our survey in Zhejiang province showed that a large number of eco-industrial
parks focus on the economic benefits. Economy dimension includes four items called industrial output value (C1), industrial added value (C2), export earnings (C3) and net profit (C4).
(4) Social dimension. Social dimension is also an important part in evaluating system. Social dimension
mainly includes four items: internal human resource (D1), external capital (D2), stakeholders (D3) and social benefits (D4).
(5) Management dimension. Management dimension includes four items to reflect circular economy
performance: management innovation (E1), information system (E2), capability development (E3) and employment stability (E4).
Based on “5R” principle, we choose the specific evaluation index. “5R” principle is an important principle in new cycle economics, mainly including rethinking, reduce, reuse, recycle and re pair. The sustainable development theory has brought changes in production methods, and this change has promoted the development of circular economy. Finally, based on index refining, we construct the evaluation index system, see figure 1.
Fig.1 Comprehensive evaluation index system
3.Basic description and operating procedu res of ANP
3.1.Basic description of ANP
ANP is evolved from AHP, which can be used to evaluate multi-attribute network with feedback.
The theoretical core of ANP is considering fully all the interaction among the various elements. Through comprehensive evaluation on each program we can make the best decisions. ANP is an efficient decision-
Li Wenbo / Energy Procedia 5 (2011) 1682–16881685
making tool for organizations. The performance evaluation index system itself of eco-industrial parks is not independent, and many elements have mutual influence, such as internal human resources will affect the various indicators of economic performance, while innovation will affect the case management level based on environmental performance. For the evaluation of such complex systems, using network analysis method to construct the network structure model can evaluate systematically and scientifically the circular economy performance of eco-industrial parks.
ANP is composed of control layer and the network layer. Control layer includes the problem goals and decision-making criteria and decision criteria are independent, which are dominated by the target element. The control layer doesn ’t have decision-making criteria, but it must have at least one goal. The elements of network layer are interdependence with mutual domination and form an interdependent network structure with complex feedback. 3.2. Operating procedures of ANP
In general, the steps are as follows:
Step1. Describe the decision problem in detail including its objectives, criteria and sub-criteria, actors and their objectives and the possible outcomes of that decision. Give details of influences that determine how that decision may come out (Saaty, 2009).
Step2. Determine the most general network of clusters (or components) and their elements that apply to all the control criteria. For each control criterion or sub-criterion, determine the clusters of the general feedback system with their elements and connect them according to their outer and inner dependence influences (Saaty, 2009).
Step3. Placing the resulting relative importance weights in pair wise comparison matrix within the super matrix, where the general structure of super matrix ˗
1c
2c
n c
n e e e 11211,,,
n e e e 22221,,,
Ă nn n n e e e ,,,21
1c
n e e e 11211,,, 11W 12W n W 1
2c
n e e e 22221,,,
21W
22W
n W 2
Ă
n c
nn n n e e e ,,,21
1n W 2n W
nn W
Step4. Conducting pair wise comparisons and weighting the blocks of the unweighted super matrix, by the corresponding priorities. Raising the weighted super matrix to limiting powers until the weights converge and remain stable (limit super matrix). The weighted super matrix can be calculated as:
N J N i w a W ij ij ,,1;,,1, . The matrix is as follows:
»»
»»
»
¼
º
«««
««¬ª j i i i
j j jn in j in j in jn i j i j i jn i j i j i ij w w w w w w w w w W 212
22121
2111
Step5. Perform sensitivity analysis on the final outcome and interpret the results of sensitivity observing how large or s mall these ratios are. In practical applications, due to the complex calculations computer software is generally used, such as the Super Decision software.
4.Nu merical example and analysis
4.1.The evaluation index weight
Based on 9 scale, our research group designed a questionnaire in order to obtain the ration of each indicator. By E-mail, postal mail, face to face interviews and telephone Q/A, 157 questionnaires were distributed to the relative experts. 96 questionnaires were returned, and the response rate is 61.15%. 58 questionnaires were valid and the effective response rate is 36.94%, as shown in table 2.
Tab.2 Statistical results of questionnaires
Method Questionnaires returned ratio valid ratio Expert distribution
E-mail 80 45 56.25% 33 41.25% Teachers 22 37.93% Postal 55 29 52.73% 5 9.09% Ph. D 16 27.59% Interview 12 12 100% 12 100% Industry expert 12 20.69% Phone 10 10 100% 8 80% Government officials 8 13.79% total 157 96 61.45% 58 36.94% total 58 100% Using super decision software, based on the questionnaires and analytic network proces s, we calculate the index weights, as shown in table3. For comparison, the table also lists the index weights based on analytic hierarchy process. The results in theory reveal the eco-industrial parks in China have been “heavy economic, light cycle”. The table also shows the ANP method takes into account the system feedback between the upper levels and lower levels and can describe complex dynamic systems. The index weights are more rational and ANP method can be effectively applied to circular economy performance evaluation. We can obtain some implications for the policy, such as step by step promoting the industrial park into a virtuous cycle of economic development track.
Tab. 3The weight of each index based on AHP and ANP
Index Weight Index ANP Rank AHP Rank Gap
Element dematerialization 0.0606 5 0.0741 3 0.0135
ANP 0.2475 circularity 0.0749 1 0.0584 6 -0.0165
AHP 0.2023 coexistence 0.0417 15 0.0521 10 0.0104
gap -0.0452 network 0.0561 8 0.0398 16 -0.0163 Environment resource utilization 0.0712 2 0.01 1 0.0179 ANP 0.2181 emission process 0.0572 7 0.0574 7 0.0002
AHP 0.1670 interactions 0.0396 16 0.0406 13 0.001
gap -0.0511 situation management 0.0509 11 0.0428 12 -0.0081 Economy industrial output value 0.0519 10 0.0399 15 -0.012
ANP 0.2019 industrial added value 0.0446 14 0.0562 8 0.0116
AHP 0.2710 export earnings 0.0618 4 0.0561 9 -0.0057
gap 0.0691 net profit 0.0384 18 0.04 14 0.0105
Social internal human resource 0.0599 6 0.0614 5 0.0015
ANP 0.1992 external capital 0.0477 13 0.0508 11 0.0031
AHP 0.2043 stakeholders 0.0560 9 0.0652 4 0.0091
gap 0.0051 social benefits 0.0694 3 0.0826 2 0.0132 Management management innovation 0.0502 12 0.0369 17 -0.0133 ANP 0.1333 information system 0.0201 19 0.0105 19 -0.0096
AHP 0.1554 capability development 0.0091 20 0.0103 20 0.0013
gap 0.0221 employment stability 0.0387 17 0.0269 18 -0.0118Li Wenbo / Energy Procedia 5 (2011) 1682–16881687
4.2.Evaluation application
I n 1999, China started to build eco-industrial parks and established the first national-level eco-industrial park-Guigang national eco-industrial demonstration zone. Now, china has 30 eco-industrial parks. In Jiangsu province, there are five eco-industrial parks. With the help of environment certification centre, we achieved the data about five parks: Nanjing Economic and Technological Development Zone
(P1); Wuxi New District (P2); Kunshan Economic Development Zone (P3); Yangzhou Economic Development (P4) and Zhangjiagang Free Trade Zone Area (P5). Based on the score of experts, we calculate the average value of each indicator, as shown in table4. All survey items were asked on 9-point
scale measurement.
Tab. 4 Indicator data of five parks
Ă
P1 6.75 7.33 6.50 6.00 6.50 5.80 6.67 6.75 7.33 6.00 6.00 6.33 Ă 6.00 6.50
P2 6.75 5.33 6.50 7.33 6.25 5.60 7.33 6.25 7.00 6.75 6.25 5.67 Ă 6.50 6.20
P3 6.50 6.33 6.75 6.67 6.25 4.80 6.00 5.25 6.33 6.25 6.25 7.67 Ă 6.50 6.75
Ă
P5 5.75 6.67 4.75 6.00 6.00 5.40 4.67 6.50 7.33 6.25 6.50 7.33 5.25 6.00 Based on ANP, we get the circular economy performance evaluation results of five eco-industrial parks, as shown in figure 2. For comparison, we also calculated the economy performance evaluation
value based on AHP. Table 6 also shows level indicator scores of five parks. The highest score is P1,
which has the higher scores in environmental and social indicators. It is also consistent with the actual situation. In 2003, P1 as the national economic and technological development zone pass ed the ISO14001 environmental management system certification. Using the port and advanced technology industry as the
basis and international trade as a precursor, the construction of the park has made remarkable achievements. More than 1,000 companies as members of system structure in electronic information, precision machinery and consumer goods category, p3 achieved circular economy by building a flexible
and open network. The lowest score is P5, which has low scores in environmental, social and governance indicators. There are many prominent problems in the two parks. Such as co-industrial park management support system to be further improved, lack of ecological industrial innovation in key technologies which restricts the advanced concepts, applying effectively management and tools, flexible construction of ecological networks.
Fig. 2 Circular economy performance evaluation results of five parks
Tab 6 Level indicator scores of five parks
1688Li Wenbo / Energy Procedia 5 (2011) 1682–1688
parks element environment economy social management
P1 1.5657 2 1.4023 1 1.2619 4 1.1845 2 0.6662 2
P2 1.4905 5 1.3737 2 1.2683 3 1.1534 3 0.6276 4
P3 1.5237 3 1.2244 5 1.2881 2 1.1202 5 0.6770 1
P4 1.5805 1 1.2440 4 1.2583 5 1.2181 1 0.6210 5
P5 1.3827 4 1.2519 3 1.3423 1 1.1435 4 0.6381 3
5.Conclusions
This paper uses network analysis method to evaluate circular economy performance of eco-industrial parks. We first construct the evaluation index system and evaluation results basically reflect the actual situation of the object being evaluated. Empirical research on Jiangsu eco-industrial parks illustrates the feasibility and rationality of this approach. Based on the Super Decision software, evaluation results can be easily translated into the real value, which will help us better understand their situation. The method can provide more scientific information to enhance their performance and basis for decision-making. Of course, this approach also has some limitations in application. For example, quantified indicators are largely dependent on the selection of experts. These deficiencies need to be further improved.
Acknowledgements
This paper is supported by human-society science research project of education ministry (program No. 10YJC630314).
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