Huijun Ren’s research while affiliated with Xi'an Branch of China Coal Research Institute and other places

The water-energy crisis seriously affects the sustainable development of China's steel industry chain. To achieve a coordinated development new path from the perspective of circular economy, it is necessary to analyze “water-energy-economy” dependency relationship of the steel products. This study analyzes a variety of steel products from the perspective of industry chain and simulates the “water-energy-economy” potential changes of products under different scenarios by developing a multi-objective optimization model. In this model, Random Forest (RF) and GEne Network Inference with Ensemble of trees (GEINIE3) algorithms are combined to evaluate the 2013–2019 “water-energy-economy” dependency relationships firstly. Then, improved Quantum Particle Swarm Optimization (QPSO) algorithm is applied to dynamically simulate potential changes of water, energy and economic performance in the steel industry chain under different scenarios, and to design an optimal development path from the perspective of optimizing economic performance within minimum water and minimum energy use constraints. Results firstly point out the current “water-energy-economy” triple dimension dependency relationship of China's steel industry is weak. Secondly, the “water-economy” dependence has changed from one-way dependence to two-way dependence, and the “energy-economy” relationship still shows a one-way dependence. Finally, when improving resource utilization rate, assigning priority to the reuse of scrap steel, while restricting pig iron and primary steel use, may help maximize the coordinated development of “water-energy-economy” in the steel industry chain. Policy implications are proposed based on the results and provided decision-making basis for the country and relevant enterprises to promote sustainable development of the steel industry chain.

Capturing the interactive shareholding relations among agents of the oil & gas industry chain is an important topic for obtaining a better understanding of the ownership and structure of the global oil & gas market. This paper proposes a multilayer cross-shareholding network method to map the multiplex cross-shareholding relations in the global oil & gas industry chain from the reciprocated, trilateral and largest component perspectives. The results show the following: (1) The cross-shareholding behavior among the listed oil & gas companies is a more popular shareholding pattern for the energy giants (the top 17.49% of companies that make up approximately 60.43% of the total market value). (2) Few (only 9 pairs between different companies) are reciprocated, and most of them belong to Israel, Japan, India, etc. (3) The “co-shareholder type” is the most critical trilateral relation in the global oil & gas industry. (4) The companies from Israel, Japan, and the Marshall Islands formed powerful alliances in different single layers, and the companies from Japan and India formed powerful alliances with cross-layer cross-shareholding relations. This paper is useful for understanding the ownership and alliance structures and the interactions of the oil & gas industry chain, and it can also provide a new perspective to determine the systemic risk paths.