适应性治理是应对社会生态系统复杂性和不确定性的新途径. 它从“学习”能力的角度考察个体行为决策特征和治理路径. 本文基于Experience Weighted Attraction (EWA) 理论和系统动力学分析影响人类行动选择和决策的因素,并融合社会学习和行为博弈理论设计水资源适应性治理下多回路、多层面的EWA演化学习模式,以应对气候变化等不确定性因素的影响. 同时结合哈密地区水权转让实例,通过仿真分析模拟适应性治理下行动主体(工业和农业)在水权转让中的行动选择规律,发掘促进主体行动概率改善的影响因素,形成水资源适应性治理的学习规则,并在学习规则指导下进行的适应性的政策调整,更好地促进水权转让实现和持续.
Abstract
Adaptive governance is a new choice to solve the problem of water resource governance which caused by the increasing complexity and uncertainty. It offers a great feasible approach with the learning capacity to settle issues caused by climate change, etc. This paper proposed the experience-weighted attraction (EWA) transformational learning based on the EWA learning theory, social learning theory and behavioral game theory. The EWA transformational learning has characteristics of multi-level and triple loop characters to promote the knowledge sharing and communication between individuals. Meanwhile, the paper analyzed the factors which may affect the human behavior pattern by system dynamics. Then, the paper modeled the dynamic system of water transfer in Hami region to analyze the law of the human behavior pattern, identify the key factors which affected human decision-making, and offer the plan for policy adjustment. The outcome of simulation proved that the learning rule of adaptive governance could improve the effective and the continuity of water transfer.
关键词
水资源适应性治理 /
学习规则 /
EWA演化学习 /
水权转让
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Key words
adaptive water governance /
learning rule /
EWA transformational learning /
water transfer
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中图分类号:
F062.1
C931.2
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参考文献
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基金
国家社科基金重大项目(12&ZD214);国家社会科学基金重点项目(10AJY005);国家重点基础研究发展计划(973计划)(2010CB951104);新疆经济需水结构调整与控制技术研究(200901068);国家社会科学基金(10CGL069);教育部人文社会科学研究项目(09YJC790125)
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