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基于计算实验的流域水环境治理模式研究
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摘要
在流域水环境的污染与治理的过程中存在复杂性,可能会涌现一些难以把握的复杂系统行为,使得认识流域污染问题及其制定有效的控制方案变得困难。这要求研究者和政策制定者必须改变观念、转变思路,更多地关注多主体行为以及他们之间的交互产生的复杂性。计算实验方法在社会科学各个领域的应用逐渐体现出其强大的优势,使用计算实验方法研究社会科学问题具有开创性的意义。水环境污染与治理系统作为一类典型的复杂社会经济环境系统,其复杂性特性对其研究方法提出了一定的要求,而计算实验方法则可以较好的解决这一问题。本文以太湖流域为例,主要采用计算实验和定性定量方法重点研究了流域水环境治理模式问题,主要结论有:
     (1)、太湖水污染问题是一个由人参与并主导的要素众多、层次复杂、关系错综、目标功能多样的社会经济自然复杂系统问题,问题的认识与解决应该考虑系统管理和复杂性管理的思想与方法。
     (2)、太湖水污染治理正处在协调对象和参与对象变化的转型期,当前以环境容量为总量为指导通过自上而下分配排污量和削减量的控制方案将面临极大挑战。为此提出了适应性管理模式,同时基于适应性管理提出了太湖水环境污染物排放控制体系的构建框架,突出适应性管理平台、适应性评审机制、科学研究及公众与基层单位参与在污染物控制中的重要作用。
     (3)、基于复杂自适应系统理论构建了社会经济环境系统模型,采用计算实验方法研究了系统在经济优先和水环境保护优先两种管理模式下的动态演化规律。结果表明:在综合考虑社会、经济、水环境的基础上,两种管理模式均能在一定程度上实现经济和就业的增长,同时改善水环境。环境保护优先模式虽能有效保护水环境,却会牺牲部分经济发展和就业保证。不同地区在演化过程中表现出差异性,常州和湖州经济获得较快增长;苏州、上海在就业上做出较大贡献;无锡和苏州水环境改善效果最为明显。
     (4)、针对污水处理项目运营风险高、企业偷排行为控制难问题,基于计算实验方法研究了污水处理项目运营与排污者行为在4种不同情景下的动态变化规律。结果表明:合理的静态定价策略要优于运营商动态定价策略;动态外部环境既给污水处理项目的运营带来风险,又给政府对企业的监管带来不便;单纯的市场价格机制或政府监管机制很难有效控制偷排现象,也不一定能实现居民的节水减排,企业和运营商的逐利行为可能会使得目标落空。
     (5)、考虑异质同类产品及不同类型的生产者与消费者,基于复杂自适应系统理论构建清洁生产技术演化模型,研究了产品竞争与供应链压力下清洁技术路径的演化规律。研究结果发现过分依赖市场的自由竞争不一定会提高产品的品质与环境水平,特别是在清洁生产技术处于萌发发展阶段;同样,过分地引进清洁生产技术则极有可能损害传统技术生产者的利益,给社会带来负面影响;而适度地引导与控制清洁技术的推广与应用,将有可能出现传统技术生产者与清洁技术生产者相互协调发展的良性竞争格局,既提升产品的品质与环境水平,又有效降低产品价格,形成社会多赢局面。计算实验结果还揭示了顾客消费行为偏好对技术系统演化的影响,发现传统技术产品将很难进入到一个环保型意识较高的地区或国家;相反,清洁技术产品进入一个环保意识较低的地区或国家却有机会获得一定的市场份额,形成细分市场的竞争格局。
The complexity during water pollution and governance in basin may emergence some complex system behavior and cause difficult between understanding basin contamination and formulating effective control plan. Simultaneously, it requests the researcher and the policy maker should translate concept and way with paying more attention to the complexity which caused by interactive behavior between multiply participants. Computational experiments show significance on the research of behaviors, emergency, and the relation between micro-level and macro-level systems. As a typical complex social economy environment system, the water environmental polluting and the governing system is a suitable study subject to the method of computational experiments which to be a good solution for solving basin complexity. This paper take the Tai Lake basin as an example to investigate governance modes of Water environment based on computational experiment and the qualitative quantitative method. The main conclusion included:
     (1) The problem of water pollution in Basin is a complex natural systematic issue leads by human with which numerous elements, different levels, complex relationship, and multi-objectives, will lead question understanding and the solution should consider the thought and the method of system management and complexity management
     (2) The current situation of Taihu can be seen as a transformation, which means domestic pollution, nonpoint source pollution and new source pollution are getting more serious, while an increasing number of stakeholders and scholars take Taihu issue as their research object. Such transformation brings about more uncertainty and complexity for pollution control, further challenge current control formula, which based on the total environmental volume and makes plan about how large amount one polluter can legally emission or should reduce from top to bottom. So that the method to make an adaptive management-based emission control formula for Taihu Lake, with a sepcial emphases on adaptive management platform, scientific research and public participation of pollution control, rose to meet the ever-changing stuation.
     (3) The system model has been built on the basis of complex adaptive system theory in order to explore evolution law of socio-economic environment system under different governance modes. Taking computational experiment method, it demonstrates the dynamics of economic growth, employment, and water pollutants discharge which are caused by agriculture and industry development under the governance modes of economic development priority as well as environmental protection priority. The evolutionary result demonstrates that both the two modes not only promote economical growth and employment, on the basis of comprehensive consideration of society, economics and water environment, but also improve water environment protection. However, environment protection priorities mode is more efficient in water environment protection, although it sacrifice economic and employment growth on certain extent meanwhile. There are some discrepancies in different regions of Taihu Lake basin. Their detail discrepancies can be illustrated as follows:economics accesses the faster growth in Changzhou and Huzhou, employment gets greater increase in Suzhou and Shanghai, and water environment has the most obvious improvement in Wuxi and Suzhou. In addition, the evolutionary process shows less insatiability for the environment protection priorities mode.
     (4) Aiming at the high-risk of sewage treatment projects operation and the difficulty of control illegal emission, four kinds of computational experiment scenarios are constructed based on whether fluctuations between discharge information and sewage disposal price or not. Then the mechanism of formation of pollution charge, polluters'behaviors, government regulation and public restriction are built, simultaneity, some indexes, such as tolerance degree, demand elasticity, were chosen to analysis the changes of behaviors and nature of enterprises or residences under the triple restriction from economic pressure, social influence and governmental regulation. Finally, computational experiment was used to simulate the dynamic changing of sewage treatment project operation and polluters'behavior in four kinds of situations. The result shows that reasonable static pricing strategy superior to dynamic operator-leading pricing strategy, dynamic external environment lead to high risk for both sewage treatment project operation and illegal emission control, neither pure market-driven pricing regime nor governmental regulation can prevent illegal emission or improve residents to save water and reduce emission, the profit-pursuiting nature of firms and operators will fail to fulfill the objective.
     (5) Considering heterogeneous but similar product and different type producer and consumer, a clean technology evolutionary modeling is built based on the theory of complex adaptive systems to study the evolution law of clean technology trajectories under competitive selection and supply chain pressure. Computational experiment was used to simulate dynamic changes, demonstrate diversity of evolution characteristics, and analysis evolution influence of different competition situation and initial customer proportion. The results shows that free completion intensity-dependent cannot be ensure enhance product quality and environment level, especially as primary stage of clean technology development, as same as clean technology import intensity-dependent will damage to traditional technology adaptor and causing negative influence to local society. However, it will have the possibility to appear multi-win phenomenon of positive competition and harmonious development between clean and traditional technology, concomitancy with promoting product quality and environment level, and reducing product price, when moderately guidance and control clean technology promotion and application. The computation experiment results have also disclosed how the customer consumer behaviors influence of technology evolution system. The product of traditional technology will be very difficult to enter to a mature market with high environmental protection consciousness; on the contrary, the clean technical product would have opportunity to obtain certain market share in a less-consciousness environmental protection market and will form market segmentation in the late evolution period. In addition, the result indicated system will keep a status of relatively balance with the producer lacking motivation of technical innovation after some experience periods under gradual innovation.
引文
[1]Allan C, Curtis A. Nipped in the Bud:Why regional scale adaptive management is not blooming [J]. Environmental Management,2005,36(3):414-425.
    [2]Arora C. Do community characteristics influence environmental outcomes? Evidence from the toxics release inventory [J]. Southern Economic Journal,1999, (4):691-716.
    [3]Arora S, Gangopadhyay S.Towards a Theoretical Model of Voluntary over Compliance [J]. Journal of Economic Behavior Organization,1995, (28):289-309.
    [4]Arthur, W.B., J.H. Holland, B. LeBaron et al. Asset Pricing Under Endogenous Expectations In an Artificial Stock Market [A]. In:W.B. Arthur, S. Durlauf, D. Lane(Ed.), The Economy As an Evolving Complex System Ⅱ [C]. Boston:Addison-Wesley,1997
    [5]Axelrod R. The evolution of cooperation. New York:Basic Books,1984
    [6]Bailey P D. IEA:A new methodology for environmental policy [J]. Environmental Impact Assessment Review,1997,17(4):221-226.
    [7]Barr, J., Hananki, N., Tassier, T. Firm organization in complex and uncertain environments. The Third Internatinal Meeting "Complex Behavior in Economics:Modeling, Computing and Mastering Complexity" COMPLEXITY 2006, Aix en Provence, France,17-21 May 2006.
    [8]Barr, J., Saraceno, F. Cournot competition, organization and learning. Journal of Economic Dynamics and Control,2005,29:277-295.
    [9]Barrett, C.L., Eubank, S. G., Smith, J. P. If Smallpox strikes Portland. Scientific American, 2005,292(3):42-49.
    [10]Belis-Bergouignan M C, Oltra V, and Jean M S. Trajectories towards clean technology: example of volatile organic compound emission reductions [J].Ecological Economics,2004, 48(2):201-220.
    [11]Berkes F, Colding J and Folke F. Navigating Social-ecological Systems:Building Resilience for Complexity and Change [M]. Cambridge:Cambridge University Press,2003.
    [12]Berkes F. Evolution of Co-management:Role of Knowledge Generation, Bridging Organizations and Social Learning [J]. Journal of Environmental Management,2009, 90:1692-1702.
    [13]Biglan A. The Role of Advocacy Organizations in Reducing Negative Externalities [J]. Journal of Organization Behavior management,2009,29 (3-4):215-230.
    [14]Borger B D. The Behavior of Public Enterprises Offering a Quasi-public Good [J]. European Journal of Political Economy,1995, (11):265-290.
    [15]Bormann B T, Cunningham P G, Brookes M H, et al. Adaptive Ecosystem Management in the Pacific Northwest[R]. Portland:US Department of Agriculture, Forest Service, Pacific Northwest Research Station,1994.
    [16]Bousqueta F, Pageb C L. Multi-agent simulations and ecosystem management:a review [J]. Ecological Modelling,2004,176(3-4):313-332.
    [17]Broderick K. Adaptive Management for Water Quality Improvement in the Great Barrier Reef Catchments:Learning on the Edge [J]. Geographical Research,2008,46(3):303-313.
    [18]Brooks, JS. Economic and Social Dimensions of Environmental Behavior:Balancing Conservation and Development in Bhutan [J]. CONSERVATION BIOLOGY. 2010,24(6):1499-1509.
    [19]Chan, H. K., Chan, F. T. S. Comparative analysis of negotiation based information sharing in agent-based supply chains.2005 3rd IEEE International Conference on Industrial Informatics (INDIN),2005,813-818.
    [20]Chang, M.H., Harrington, J.E. Jr. Multi-market competition, consumer search, and the organizational structure of multi-unit firms. Management Science,2003,49:541-552.
    [21]Christmann P, Taylor G. Globalization and the Environment:Determinants of Firm Self-regulation in China [J]. Journal of International Business Studies,2001, (32):439-458.
    [22]Coase R H. The Problem of Social Cost [J]. The Journal of Law and Economics,1960,3: 1-44.
    [23]Cobb C W, Douglas P H. A Theory of Production [J]. The American Economic Review,1928, 18(1):139-165.
    [24]Cohen, March, Olsen:A garbage can model of organizational choice [J]. Administrative Scienece.1972,10(17):1-25.
    [25]Costanza R, JΦrgensen S E理解和解决21世纪的环境问题[M].徐中民,张志强等译.郑州:黄河水利出版社,2004.
    [26]Costanza R, Low B, Ostrom E. Institutions, Ecosystems and Sustainability [M]. Boca Raton: Lewis Publishers,2001.
    [27]Daniel Kammerer. The effects of customer benefit and regulation on environmental product innovation.:Empirical evidence from appliance manufacturers in Germany [J]. Ecological Economics,2009,68(8-9):2285-2295
    [28]Dewulf A, Craps M, Bouwen R, et al. Integrated Management of Natural Resources:Dealing with Ambiguous Issues, Multiple Actors and Diverging Frames [J]. Water, Science and Technology,2005,52(6):115-124.
    [29]Donella H. Meadows, Jorgen Randers, Dennis L. Meadows. The Limits to Growth:The 30-year Update [M]. Chelsea Green Pub,2004.
    [30]Dorney R S. The professional practice of environmental management [M]. New York: Springer-Verlag,1989.
    [31]Dosi G, Freeman C, Nelson R, Silverberg G, Soete L. Technical change and economic theory [M]. London and New York:Columbia University Press,1988.
    [32]Drobny N L. Strategic Environmental Management-Competitive Solutions for the Twenty-first Century [J]. Cost Engineering,1994,36(8):19-23.
    [33]Drucker P F. Managing in a time of great change [M]. USA:Plume,1998.
    [34]Earnhart D. Regulatory Factors Shaping Environmental Performance at Publicly-Owned Treatment Plants [J]. Journal of Environmental Economics and Management,2004,48 (1): 655-681.
    [35]Epple D, Michael V. Environmental Pollution:Modeling Occurrence, Detection, and Deterrence [J]. Journal of Law and Economics,1984,27(1):29-60.
    [36]Epstein, J.M. Generative Social Science:Studies in Agent-Based Computational Modeling. Princeton University Press, Princeton, NJ,2005.
    [37]Epstein, J.M., and Axtell, R.:Growing artificial societies. Social science from the bottom up. Washington:Brookings Institution Press,1996
    [38]Florida Davison. Gaining from green management:Environment Management Systems inside and outside the Factory [J] California Management Review,2001, (3):64-72.
    [39]George Luger. Artificial Intelligence:Structures and Strategies for Complex Problem Solving [M], Addison Wesley,2004.
    [40]Gray W, Deily M E. Compliance and Enforcement:Air Pollution Regulation in the U.S. Steel Industry [J]. Journal of Environmental Economics and Management,1996,31(1):96-111.
    [41]Gunderson L, Holling C, Light S. Barriers and Bridges to the Renewal of Ecosystems and Institutions [M]. New York:Columbia University Press,1995.
    [42]Guneralp F, Barlas Y. Dynamic modeling of a shallow freshwater lake for ecological and economic sustainability [J]. Ecological Modelling,2003,167(1-2):115-138.
    [43]Hall J. Environmental supply chain dynamics [J].Journal of Cleaner Production,2000,8(6): 455-471.
    [44]Harris G. Integrated assessment and modelling:an essential way of doing science [J]. Environmental Modelling and Software,2002,17(3):201-207.
    [45]Henriques I, Sadorsky P. The Determinants of an Environmentally Responsive Firm:An Empirical Approach [J]. Journal of Environmental Economics and Management,1996,30 (3): 381-395.
    [46]Herbert A. Simon. The Sciences of the Artificial [M].The MIT Press,1981
    [47]Holling C. Adaptive Environmental Assessment and Management [M]. New York:John Wiley and Sons,1978.
    [48]Huq M, Wheeler D. Pollution Reduction without Formal Regulation:Evidence from Bangladesh [M]. Mimeo:The World Bank,1992.
    [49]J. Stanley Metcalfe. Evolutionary Economics and Creative Destruction [M], Published by Routledge,1998:135-149
    [50]Jager W, Janssen M A, H J M De Vries, et al. Behaviour in commons dilemmas:Homo economicus and Homo psychologicus in an ecological-economic model [J]. Ecological Economics,2000,35,375-379
    [51]Jean M S. Analysis of the co-evolution of suppliers and users through an evolutionary modeling the case of environmental innovations [J].European Journal of Economic and Social Systems,2005,18(2):255-284.
    [52]Jean M S. Polluting emissions standards and clean technology trajectories under competitive selection and supply chain pressure [J]. Journal of Cleaner Production,2008,16(1):113-123.
    [53]Jiang Chengzhi, Sheng Zhaohan. Case-based reinforecement learning for dynamic inventory control in a multi-agent supply chain system [J]. Expert Systems with Application,2009, 36(3):6520-6526.
    [54]Jiang Chengzhi, Sheng Zhaohan. Learing framework for multi-agent simulation of supply chain systems. Procedings of International Conference on Computer Science and Information Technology, Singapore,2008,524-431.
    [55]Jiang Chengzhi,Xu Feng, Sheng Zhaohan.Pricing stratege in a dual-channel and remanufacturing supply chain system [J]. International Journal of Systems Science,2010, 41(7):909-921.
    [56]Jiao, J. X., You, X., Kumar, A. An agent-based framework for collaborative negotiation in the global manufacturing supply chain network. Robotics and Computer-Integrated Manufacturing,2006,22:239-255.
    [57]John H.隐秩序—适应性造就复杂性[M].周晓牧等译.上海:上海科技教育出版社,2006.
    [58]Jorgen W.Weibull. Evolutionary Game Theory [M]. The MIT Press,1996.
    [59]Khanna A. Corporate Environmental Management:Regulatory and Market-based Pressure[J]. Land Economics,2002, (4):78.
    [60]Kotler P,Armstrong GPrinciples of Marketing [M].New Jersey:Prentice Hall,2007
    [61]Kwasnicki W. Comparative analysis of selected Neo-Schumpeterian models of industrial dynamics [C]. DRUID, Aalborg,2001.
    [62]Kwon, O., Im, G. P., Lee, K. C. MACE-SCM:A multi-agent and case-based reasoning collaboration mechanism for supply chain management under supply and demand uncertainties. Expert Systems with Applications,2007,33(3):690-705.
    [63]L. von Bertranffy. General Systems Theory:Foundation, Development, Applications. New York:George Braziller,1968.
    [64]Ladson A R, Argent R M. Adaptive management of environmental flows:Lessons for the Murray-Darling basin from three large North American rivers [J]. Australian Journal of Water Resources,2001,5(1):89-101.
    [65]Lee K. Appraising Adaptive Management [J]. Conservation Ecology,1999,3(2):3-16.
    [66]Li G, Yang H, Sun L, Feng L. The evolutionary complexity of complex adaptive supply networks- A simulation and case study [J].International Journal of Production Economics, 2010,124(2):310-330.
    [67]Li Jing, Zhou Yuejin. Experimental analysis of self-organizing team's behaviors [J]. Expert Systems with Applications,2010(37),727-732.
    [68]Li Jing. Multi-agent simulation for the dominant players'behavior in supply chains [J]. Simulation Modelling Practice and Theory,2010(18),850-859.
    [69]Liu Y, Gupa H, Springer E and Wagener T. Linking science with environmental decision making:Experiences from an integrated modeling approach to supporting sustainable water resources management [J]. Environmental Modelling,2008,23(7):846-858.
    [70]Loucks D P, Gladwell J S. Sustainability criteria for water resource systems [M]. Cambridge: Cambridge University Press,1999.
    [71]Ludwig D, Hilborn R, Walters C. Uncertainty, Resource Exploitation, and Conservation: Lessons from History [J]. Science,1993,260 (17):17-36.
    [72]Magat W A, Viscusi W K. Effectiveness of the EPA's Regulatory Enforcement:The Case of Industrial Effluent Standards [J]. Journal of Law and Economics,1990,33:331-360.
    [73]MaLain R J, Lee R G. Adaptive management:promises and pitfalls. Environmental Management,1996,20(4):437-448
    [74]Malerba F, Nelson R, Orsenigo and L Winter S. Public policies and changing boundaries of firms in a "history-friendly" model of the co-evolution of the computer and semiconductor industries [J]. Journal of Economic Behavior and Organization,2008,67(2):355-380.
    [75]Malerba F, Nelson R, Orsenigo L, Winter S. "History-friendly" models of industry evolution: the computer industry [J]. Industrial and Corporate Change,1999,8(1):3-40.
    [76]Meadows D H, Randers J, Meadows D L. The limits to growth:the 30-year updates [M]. Vermont:Chelsea Green,2004:174-175.
    [77]Meretsky V J, Wegner D L, Stevens L E. Balancing endangered species and ecosystems:A case study of adaptive management in Grand Canyon [J]. Environmental Management,2000, 25(6):579-586.
    [78]Mikhail Anufriev, Pietro Dindo.Wealth-driven selection in a financial market with heterogeneous agents [J] Journal of Economic Behavior & Organization,2010,73(3):327-358
    [79]Mitsch W J, Jorgensen S E. Ecological Engineering:A Field Whose Time has Come[J]. Ecological Engineering,2003, (20):363-377.
    [80]Moberg F, Galaz V. Resilience:Going from Conventional to Adaptive Freshwater Management for Human and Ecosystem Compatibility[R]. Sweden:Stockholm International Water Institute,2005.
    [81]National Research Council. Adaptive Management for Water Resources Project Planning [M]. Washington, D.C.:National Academies Press,2004.
    [82]Nelson R, Winter S. An evolutionary theory of economic change [M]. The Belknap Press of Harvard University Press,1982.
    [83]North D C. Structure and Change in Economic History [M]. New York:W.W.Norton & Company,1982.
    [84]Olson M. Agency Rulemaking, Political Influences, Regulation, and Industry Compliance [J]. Journal of Law, Economics, and Organization,1999,15(3):573-601.
    [85]Oltra V, Jean M S.Variety of technological trajectories in low emission vehicles (LEVs):A patent data analysis [J]. Journal of Cleaner Production,2009,17(2):201-214.
    [86]Ortolano L.环境管理域影响评价[M].郭怀成,梅凤乔译.北京:化学工业出版社,2004.
    [87]Ortolano L.Environmental Regulation and Impact Assessment [M].New Jersey:Wiley,1997.
    [88]Ostrom E, Schroeder L, Wynne S. Institutional Incentives and Sustainable Development [M]. Boulder:Westview Press,1993.
    [89]Owens P. Adaptive Management Frameworks for Natural Resource Management at the Landscape Scale:Implications and Applications for Sediment Resources [J]. Journal of Soils and Sediments,2009,9(6):578-593.
    [90]Pahl-Wostl C, Hare M. Processes of Social Learning in Integrated Resources Management [J]. Journal of Community and Applied Social Psychology,2004,14:193-206
    [91]Pahl-Wostl C, Mostert E and Tabara D. The growing importance of social learning in water resources management and sustainability science [J]. Ecology and Society,2008,13(1): 24-28.
    [92]Pahl-Wostl C, Sendzimir J, Jeffrey P, et al. Managing Change toward Adaptive Water Management through Social Learning [J]. Ecology and Society,2007,12(2):30.
    [93]Pahl-Wostl C. The Implications of Complexity for Integrated Resources Management [J]. Environmental Modeling & Software,2007,22:561-569.
    [94]Pahl-Wostl C. Transitions towards adaptive management of water facing climate and global change [J]. Water Resource Management,2007,21(1):49-62.
    [95]Parker C, Nielsen V L. Corporate Compliance Systems Could They Make Any Difference?[J]. Administrationr & Society, MAR 2009,41(1):3-37.
    [96]Parker P, Letcher R, Jakeman A, et.al. Progress in integrated assessment and modeling [J]. Environmental Modelling & Software,2002, (17):209-217.
    [97]Pearson B. Market failure:why the Clean Development Mechanism won't promote clean development [J]. Journal of Cleaner Production,2007,15(2):247-252.
    [98]Pigou A C. The Economics of Welfare [M]. London:Macmillan,1920
    [99]Porter M, van der Linde C. toward a new conception of the environment-competitiveness relationship. Journal of Economic Perspectives,1995,9(4):97-118.
    [100]Prato T. Adaptive Management of Large Rivers with Special Reference to the Missouri River[J]. Journal of the American Water Resources Association,2003,39(4):935-946.
    [101]Prato T. Bayesian adaptive management of ecosystems [J]. Ecological Modelling,2005, 183(2-3):147-156.
    [102]Railsback S F.Concepts from complex adaptive systems as a framework for individual-based modeling [J].Ecological Modeling,2001,139(1):47-62.
    [103]Robin G, Lee F, Paul H. Adaptive management and environmental decision making:A case study application to water use planning [J]. Ecological Economics,2006,58(2):434-447.
    [104]Roland C S. Effects of water conservation on the operation of sewage treatment plants [M]. Rockville:Interstate Commission on the Potomac River Basin,1986.
    [105]Samuelson P, Nordhaus W. Microeconomics [M]. Columbus:McGraw-Hill/Irwin,2009.
    [106]Schelling T C. Micromotives and Macrobehavior [M]. New York:W W Norton & Co Lt, 1978.
    [107]Schellnhuber H J. "Earth system" analysis and the second Copernican revolution [J]. Nature, 1999,402(2):19-23.
    [108]Scheurer, F. Getting complexity organized using self-organization in architectural construction. Automation in Construction,2007,16:78-85.
    [109]Scott A J. The changing global geography of low-technology, labor-intensive industry: clothing, footwear, and furniture [J]. World Development,2006,34(9):1517-1536.
    [110]Shuai Jin, Zhaohan Sheng. Modeling and simulation research on diffusion of the public voice[C]. IEEE World Congress on Computational Intelligence,2008,3866-3873.
    [111]Smith J. A Critical Appreciation of the "Bottom-up" Approach to Sustainable Water Management:Embracing Complexity rather than Desirability [J]. Local Environment,2008, 13(4):353-366.
    [112]Sprigg Jr., J. A., Jorgensen, C. R., Pryor, R. J. Approach and development strategy for an agent-based model of economic confidence. Sandia Report, Sand2004-4218,2004.08.
    [113]Stafford S. The Effect of Punishment on Firm Compliance with Hazardous Waste Regulations [J]. Journal of Environmental Economics and Management,2002,44 (2): 290-308.
    [114]Stalley P. Can Trade Green China? Participation in the Global Economy and the Environmental Performance of Chinese Firms [J]. Journal of Contemporary China,2009, 18 (61):567-590.
    [115]Sterman J. Business Dynamics:System Thinking and Modeling for a Complex World[M]. Boston:McGraw-Hill,2000.
    [116]Tatiana Filatova, Alexey Voinov, Anne van der Veen. Land market mechanisms for preservation of space for coastal ecosystems:An agent-based analysis [J]. Environmental Modelling & Software,2011,26(2):179-190
    [117]Tesfatsion L. Agent-based computational economics:modeling economies as complex adaptive systems [J].2003,149(4):262-268.
    [118]Volberda, H.W, A.Y. Lewin. Co-evolutionary dynamics with and between firms [J], Jouranal of Management Studies,2003,40(8):2105-2130.
    [119]W. Brian Arthur, John H. Holland, Blake LeBaron, Richard Palmer, and Paul Tayler. Asset Pricing Under Endogenous Expectations in an Artificial Stock Market [D]. Working Papers from Santa Fe Institute,1996.
    [120]Wang Feng, Ann Reisner.Factors influencing private and public environmental protection behaviors-Results from a survey of residents in Shaanxi, China [J]. Journal of Environmental Management,2011,92:429-436
    [121]Wang, D.S., Nagalingam, S.V., Lin, G.C.I. Development of an agent-based virtual CIM architecture for small to medium manufactures. Robotics and Computer-Integrated Manufacturing,2007,23:1-16.
    [122]Wang, G. H., Jiang, X. Y., Yu, T. B., Gong, Y. D, Wang, W. S. Research on supply chain negotiation under networked manufacturing environment. Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications (ISDA'06).
    [123]Wiedemann P M, Femers S. Public participation in water management decision making: Analysis and management of conflicts [J]. Journal of Hazardous Materials,1993, (33):355-368.
    [124]Xiaofeng Liu, Guohua Chen, Xiaochun Zhang, Jianxiong Gong. Simulating Evolutionary Dynamics in complex adaptive retail networks [J]. Journal of Information and Decision Science,2009,4(3):243-256.
    [125]Yeqiao Wang, Xingsheng Zhang. A dynamic modeling approach to simulating socioeconomic effects on landscape changes [J]. Ecological Modelling,2001,140,141-162.
    [126]Yu-Long Chao,San-Pui Lam. Measuring Responsible Environmental Behavior-Self-Reported and Other-Reported Measures and Their Differences in Testing a Behavioral Model [J]. Environment and Behavior,2011,43(1) 53-71.
    [127]蔡游飞,曾宪钊.基于计算实验的复杂作战系统研究方法[J].系统仿真学报,2005,17(29):2239-2243.
    [128]常杪,林挺.我国城市污水处理厂BOT项目建设现状分析[J].给水排水,2006,32(2):101-106.
    [129]陈荷生.面向21世纪的太湖流域水资源统一管理[J].水利水电科技进展,2000,20(3):2-5.
    [130]陈若航.基于计算实验的计算机软件扩散模式及知识产权管理策略研究[D],南京大学博士论文,2010.
    [131]陈宜瑜,王毅,李利锋,于秀波,等.中国流域综合管理战略研究[M].北京:科学出版社,2007.
    [132]陈莹,刘昌明.大江大河流域水资源管理问题讨论[J].长江流域资源与环境,2004,13(3):239-245.
    [133]陈莹,袁建辉,李心丹,肖斌卿.基于计算实验的协同羊群行为与市场波动研究[J].管理科学学报,2010,13(9):119-127.
    [134]陈禹,钟佳佳.系统科学与方法概论[M].中国人民大学出版社,2005.
    [135]崔霞,戴汝为.以人为中心的综合集成研讨厅体系——人工社会(二).复杂系统与复杂性科学,2006,3(2):9-20.
    [136]崔霞,戴汝为.以人为中心的综合集成研讨厅体系——人工社会(一).复杂系统与复杂性科学,2006,3(2):1-8.
    [137]高洁,盛昭瀚.产品竞争的产业演化模型研究[J].中国管理科学,2004,12(6):96-102.
    [138]顾佳,贺仲雄.人工生命、人工社会、人工涌现的和谐仿真.2006系统仿真技术及其应用学术交流会论文集:335-338.
    [139]国家统计局,国家环境保护总局.中国环境统计年鉴——2009[M].北京:中国统计出版社,2009.
    [140]韩筱璞,周涛,汪秉宏.基于元胞自动机的国家演化模型研究.复杂系统与复杂性科学,2004,1(4):74-78.
    [141]侯怀霞.收取排污费和规定排放标准的比较[J].同济大学学报(自然科学版).2008,36(6):777-781.
    [142]侯云章.基于计算实验的人工供应链建模及其实现[D],,南京大学博士论文,2008.
    [143]候云章,盛昭瀚,王晓灵,陈国华.复杂网络中基于记忆长度的合作行为[J].系统工程理论与实践,2008,2:119-152.
    [144]胡璇,栾胜基.从环境协议收费现象看排污收费政策的缺陷[J].北京大学学报(自然科学版),2004,40(2):303-309.
    [145]黄春蕾.论我国城市污水处理市场化过程中的政府职能[J].中国人口·资源与环境,2004,14(5):99-102.
    [146]金帅,盛昭瀚,刘小峰.排污权交易系统效率的实验研究[J].预测,2010,29(6):25-31.
    [147]李刚,邢书宝.资源承载力人工社会模型研究.计算机技术与发展,2007,17(9):217-219.
    [148]李建会,张江.数字创世纪人工生命的新科学.北京:科学出版社,2006.
    [149]李建会.生命和计算:人工生命的生命观研究.北京大学哲学博士学位论文,2002.
    [150]李静.供应链研究计算实验平台及其应用研究[D],南京大学博士论文,2010.
    [151]李旭.社会系统动力学:政策研究的原理、方法和应用[M].上海:复旦大学出版社,2008:124-146.
    [152]刘小峰,陈国华,李真.零售网络的结构建模与演化分析[J],管理科学,2009,22(4),23-30.
    [153]刘小峰,陈国华,盛昭瀚.不同供需关系下的食品安全与政府监管策略分析[J].中国管理科学,2010,18(2):143-150.
    [154]刘永,郭怀成.湖泊-流域生态系统管理研究[M].北京:科学出版社,2008.
    [155]刘月芹.污水处理厂投资项目特许经营期中的水价调整[J].中国给水排水,2007,23(18):75-78.
    [156]卢方元.环境污染问题的演化博弈分析[J].系统工程理论与实践,2007,9:148-152.
    [157]卢良进,万健,徐向华.基于人工社会网络的P2P实时流媒体协助分发模型.计算机应用,2007,27(11):2680-2682,2693.
    [158]罗批,胡晓峰,司光亚,张忠海.战争系统人工社会的研究实践与几点思考.系统仿真学报,2006,18(12):3589-3592.
    [159]马世骏,王如松.社会-经济-自然复合系统[J].生态学报,1984,4(1):1-9.
    [160]马巍,禹雪中,翟淑华,等.太湖限制排污总量及其管理应用研究[J].科技导报,2008,26(18):49-53.
    [161]孟庆峰,李真,盛昭瀚,杜建国.企业环境行为影响因素研究现状及发展趋势[J].中国人口·资源与环境,2010,20(9):100-107.
    [162]穆贤清,黄祖辉.流域水环境管理的经济学思考:以太湖流域为例[J].经济理论与经济管理,2002,(6):18-22.
    [163]穆昕,王浣尘,李雷鸣.基于差异化策略的环境管理与企业竞争力研究[J].系统工程理论与实践,2005(3):26-31.
    [164]钱学森,等.论系统工程(增订本)[M].长沙:湖南科学技术出版社,1988.
    [165]钱学森,于景元,戴汝为.一个科学新领域——开放的复杂巨系统及其方法论[J].自然杂志,1990,13(2):3-10.
    [166]钱学森.新技术革命与系统工程—从系统科学看我国今后60年的社会革命[J].世界经济,1985,4-9.
    [167]秦伯强.太湖生态与环境若干问题的研究进展及其展望[J].湖泊科学,2009,21(4):445-455.
    [168]任勇.日本环境管理及产业污染防治[M].北京:中国环境科学出版社,2000.
    [169]任远.太湖流域水污染实质与集成化流域管理[J].中国人口·资源与环境,2002,12(4):73-76.
    [170]盛昭瀚,李静,陈国华.社会科学计算实验基本教程[M].上海:三联出版.2010.
    [171]盛昭瀚,张军,杜建国.社会科学计算实验理论与应用[M].上海:三联书店,2009.
    [172]盛昭瀚,高洁,杜建国.基于NW模型的新熊彼特式产业动态演化模型[J].管理科学学报,2007,10(1):1-8.
    [173]盛昭瀚,蒋德鹏.演化经济学[M].上海:上海三联书店,2002.
    [174]盛昭瀚,游庆仲等.大型工程综合集成管理——苏通大桥工程管理理论思考和探索[M].科学出版社,2009.
    [175]世界银行.中国:空气、土地和水——新千年的环境优先领域[M].北京:中国环境科学出版社,2001.
    [176]宋国君,谷一桢,刘永.中央政府投资城市污水处理厂的理论和实证分析[J].上海环境科学,2002,21(11):658-661.
    [177]苏魏,杜鹏飞,陈吉宁.城市污水处理厂运行评估系统的开发与应用[J].清华大学学报(自然科学版),2005,45(3):371-374.
    [178]孙建.适应性管理[M].北京:中国社会科学出版社,2006.
    [179]谭劲松.关于管理研究及其理论和方法的讨论[J].管理科学学报,2008,11(2):145-152.
    [180]佟金萍,王慧敏.流域水资源适应性管理研究[J].软科学,2006,20(2):59-61.
    [181]王飞跃,蒋正华,戴汝为.人口问题与人工社会方法:人工人口系统的设想与应用.复杂系统与复杂性科学,2005,2(1):1-9.
    [182]王飞跃,史帝夫·兰森.从人工生命到人工社会——复杂社会系统研究的现状和展望.复杂系统与复杂性科学,2004,1(1):33-41.
    [183]王飞跃.人工社会、计算实验、平行系统—关于复杂社会经济系统计算研究的讨论.复杂系统与复杂性科学,2004,1(4):25-35.
    [184]王飞跃.计算实验方法与复杂系统行为分析和决策评估[J].系统仿真学报,2004,16(5):893-897.
    [185]王红卫,孙长银,沈轶,余明晖.系统科学与系统工程学科发展战略研究[J].中国科学基金,2009,2,70-78.
    [186]王佳伟,张天柱,陈吉宁.污水处理厂COD和氨氮总量削减的成本模型[J].中国环境科学,2009,29(4):443-448.
    [187]王其藩.复杂大系统综合动态分析与模型体系[J].管理科学学报,1999,2(2):16-20.
    [188]王希希,陈吉宁.我国污水处理理想价格及合理投资结构测算分析[J].给水排水,2004,30(11):43-46.
    [189]王毅,王学军,于秀波,王亚华.推进流域综合管理的相关政策建议[J].环境保护,2008,(19):22-24.
    [190]吴伟,陈功玉,王浣尘,陈明义.环境污染问题的博弈分析[J].系统工程理论与实 践,2001(10):115-119.
    [191]吴亚琼,岳超源,赵 勇,吴相林.排污申报控制方式的博弈分析[J].系统工程理论与实践,2006,26(8):81-85.
    [192]谢红彬,陈雯.太湖流域制造业结构变化对水环境演变的影响分析—以苏锡常地区为例[J].湖泊科学,2002,14(1):53-59.
    [193]谢平.太湖蓝藻的历史发展与水华灾害[M].北京:科学出版社,2008.
    [194]熊熊,郭翠,张维,张永杰.中小企业贷款利率定价的计算实验方法[J].系统工程理论与实践,2009,29(12):9-143.
    [195]徐迪,李煊.商务模式创新复杂性研究的计算实验方法[J].管理科学学报,2010,13(11):12-19.
    [196]许振成,王俊能,彭晓春,郭梅.中国环境管理的战略创新[J].生态环境学报,2009,18(3):1189-1193.
    [197]杨桂山,王德建等.太湖流域经济发展·水环境·水灾害[M].北京:科学出版社,2003:132-142.
    [198]杨荣金,傅伯杰,刘国华,马克明.生态系统可持续管理的原理和方法[J].生态学杂志,2004,23(3):103-108.
    [199]杨卫华,戴大双,韩明杰.基于风险分担的污水处理BOT项目特许价格调整研究[J].管理学报,2008,5(3):366-370.
    [200]余瑞祥,朱清.企业环境行为研究的现在与未来[J].工业技术经济,2009,28(8):2-6
    [201]约翰.L.卡斯蒂.虚实世界.王千祥,等译.上海:上海科技教育出版社,1998.
    [202]曾思育,傅国伟.混合博弈在水污染系统控制中的应用[J].系统工程理论与实践,2001,21(5):132-136.
    [203]曾贤刚,程磊磊.不对称信息条件下环境监管的博弈分析[J].经济理论与经济管理,2009,(8):56-59.
    [204]詹歆晔,刀谞,郭怀成,周丰,刘慧.中国与美国环境规划差异比较与成因分析[J].环境保护,2009,424(7):59-61.
    [205]张炳,毕军,袁增伟,王仕,葛俊杰.企业环境行为:环境政策研究的微观视角[J].中国人口·资源与环境,2007,17(3):40-44
    [206]张道海,杜建国.基于Repast平台的太湖水环境承载力研究[J].环境工程,2010,28(4):29-31.
    [207]张江,李学伟.人工社会——基于Agen t的社会学仿真.系统工程,2005,23(1):13-20.
    [208]张军,盛昭瀚.组织行为演化研究的计算实验方法[J].复杂系统与复杂性科学,2005,4(2):29-36.
    [209]张军.计算管理研究方法及其实现[D],南京大学博士论文,2007.
    [210]张燎.城市水务改革的模式选择与比较[J].中国水利,2006,(10):20-23.
    [211]张晓颖,刘小峰.工业增加值与废水排放量之间的关系研究[J].环境科学与管理,2010,35(11):5-9.
    [212]张艳艳.试论太湖富营养化的发展、现状及治理[J].环境科学与管理,2009,34(5):126-130.
    [213]张永杰,张维,熊熊.投资策略与投资收益:基于计算实验金融的研究[J].管理科学学报,2010,13(9):107-118.
    [214]中国环境与发展国际合作委员会.给中国政府的环境与发展政策建议[M].北京:中国环境科学出版社,2005:167-183.
    [215]中国科学院可持续发展战略研究组.2007中国可持续发展战略报告——水治理与创新[M].北京:科学出版社,2007.
    [216]钟玉秀,吴志平.对太湖流域水资源管理体制改革的探索[J].水利发展研究,2007,(10):4-8.
    [217]周耀东,余晖.政府承诺缺失下的城市水务特许经营—成都、沈阳、上海等城市水务市场化案例研究[J],管理世界,2005,(8):58-64.
    [218]朱德米.构建流域水污染防治的跨部门合作机制—以太湖流域为例[J].中国行政管理,2009,(4):86-91.
    [219]朱立言,孙健.适应性管理的兴起及其理念[J].湖南社会科学,2008,(6):63-68.

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