Suchergebnisse

AbstractWater option trading could facilitate water conservation in irrigation areas to achieve optimal allocation of agricultural water resources. However, the risk associated with water‐saving decisions increases due to the uncertainties of tradeable water and water‐saving benefits, which makes farmers in the irrigation area with heterogeneous risk tolerances exhibit varied option water‐saving willingness (OWSW) in response to the water option contract. Thus, this article provides a novel framework for prior assessing the OWSW in the irrigated area that considers farmers' heterogeneous risk tolerance and proposes the optimal contractual water demand to stimulate the OWSW. First, a multiobjective optimal allocation model for cropping water is constructed to predict tradeable water, and then risk trust, risk‐return perception and reference are integrated into water‐saving return analysis for proposing a willingness calculation model involving forecast information. Finally, the influence of heterogeneous risk tolerance on farmers' water‐saving path choices and the irrigation area's OWSW is analyzed with three sets of comparative data from 2014 to 2021. Results indicate that the intensity and stability of OWSW in water‐scarce irrigation areas increase as farmers' risk tolerance rises, but the enhancement utility exhibits a diminishing marginal trend. When both prediction accuracy and farmers' risk tolerance are low, contracts with relatively adventurous and differentiated water demands are more likely to stimulate OWSW. This study provides insights into activating water options trading and stimulating water conservation in agriculture from a risk management perspective.

Increasing carbon dioxide emissions from large-scale human activities have resulted in climate change and an increase in extreme weather events all around the world, resulting in significant human development crises. To overcome this issue, scientific consensus has been encouraging a global focus towards low carbon economics. For this purpose, the development of a framework for regional development cybernetics is an innovative approach. While the cybernetics approach requires that all sectors, such as industry, government, and citizens, and all levels, including global, national, and regional levels, engage in this closed-loop action, the implementation of climate strategies depends heavily on the regional level. Through the establishment of an innovative pedigree of model technologies, this book develops systematic quantificational methods, such as uncertain multi-objective programming models, systems dynamics model, econometric models, and ecological carrying capacity models, to simulate and solve the key issues affecting regional low carbon development, including greenhouse gas control, ecological capacity evaluation, regional economic prediction, energy structure optimization, land resource utilization, industrial structure adjustment, low carbon industrial chains, low carbon transportation systems and low carbon tourism. At the same time, decision makers are provided with many effective strategies to plan for regional low carbon development. This book also provides researchers with a new perspective from which to pursue solutions to key social problems using quantitative techniques. This book, with its focus on climate change, social science, economic development, low carbon economics, and management science, is ideal for researchers, practitioners, engineers, graduate students, and upper-level undergraduates.

AbstractThe risk of medical waste pollution and huge demand of daily medical waste disposal pose great difficulties to medical waste management. Establishing medical waste disposal centers (MWDCs) is considered one of the ways to reduce the environmental and public risk of medical waste pollution. However, how to serve the medical waste disposal demand in optimal MWDCs' locations is a key challenge due to the complexity of the whole system and relationships among stakeholders. This article develops a soft‐path solution for reducing risks as well as mitigating the related costs by optimizing the MWDC location‐allocation problem. A risk mitigation‐oriented bilevel equilibrium optimization model is developed for modeling the Stackelberg game behavior between the local government and the medical institutions. The objectives of the local government are minimizing the total risk of loss, the subsidy costs, and the investment cost of building the MWDCs, while minimizing the disposal and transportation costs are the objectives at the medical institution level. Fuzzy random variables are introduced by combining insufficient historical data with expert knowledge via consulting surveys to describe the coexisting uncertainties in the data. To solve the model, a hybrid approach combined with the interactive fuzzy programming technique and an Entropy‐Boltzmann selection‐based genetic algorithm are designed and tested. The Chengdu Medical Waste Disposal Centers Planning Project is used as a practical application. The results show that it is possible to achieve a balanced market with higher economic efficiency and significantly reduced risk through an appropriate principle of interactive actions between the bilevel stakeholders.