To reduce flood disasters and optimize of the comprehensive benefit of the water basin, the allocation of regional flood drainage rights is of great significance. Using the “top-down” allocation mode, we consider the influence of the social, economic, and ecological environments, flood drainage demand and efficiency, and other factors on the allocation of flood drainage rights. A bi-level multi-objective programming model from the perspective of fairness and efficiency is established for the allocation. The Sunan Canal is taken as a typical case study. The model is solved by the multi-objective optimal allocation method and the master–slave hierarchical interactive iteration algorithm. After three iterations of the initial solution, the allocation of flood drainage rights in six flood control regions finally reach an effective state. The results of the model were compared with results based on historical allocation principles, showing that the bi-level multi-objective programming model, based on the principles of fairness and efficiency, is more in line with the current social and economic development of the canal. In view of the institutional background of water resources management in China and the flood drainage pressure faced by various regions, the allocation of flood drainage rights should be comprehensively considered in combination with various factors, and the market mechanism should be utilized to optimize the allocation.

Large-scale projects play an important role in social and economic development. Recently, large-scale projects are becoming more complex with more uncertainties and risks during the construction, which leads to more complex and extensive management problems. In a large-scale project, there is a principal-agent relationship between the contractor and owner. The contractor may take moral hazard behavior to pursue his/her own interests due to the information asymmetry and conflict of interest, which could damage to the public and owner’s interests. Based on the principal-agent theory, a dynamic incentive model combining explicit and implicit incentives was constructed in large-scale projects, after analyzing the mechanism of reputation effects. A comparison was made between two scenarios. One scenario considered reputation effects; the other did not consider reputation effects. The results show that the contractor would be more inclined to make optimal efforts in the large-scale project after reputation effects are introduced, and this optimal effort level will improve with the increased influence degree of reputation effects. However, the contractor’s degree of risk aversion will weaken the incentive effects. In addition, compared to an explicit incentive, the reputation mechanism of an implicit incentive will increase the owner’s benefits. The findings not only provide important support for the owner to formulate relevant incentive clauses in the construction contract, but also has important practical significance for the construction of the micro-institutional environment in construction projects. This study did not take into account factors such as regulatory efficiency when establishing the reputation incentive model. How to combine reputational incentives with the degree of supervision will be the direction of future research.

In December 2016, the prominent New York Mercantile Exchange CAPP coal future contract was delisted by the CME, owner of the NYMEX. At that time, all four giant US coal miners were under the protection of Chapter 11. These events illustrate the collapse of coal consumption in the US and the loss of relevance of the Appalachian coal index whose futures were used as a hedging instrument across the world. Our goal in this paper is to revisit the problem of integration of coal markets and to exhibit through multiple perspectives, including a lead/lag analysis of pairs of major indexes, that the world coal market is moving East.

No abstract