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Nowadays, green supply chain (SC) management acts as an important strategic issue for the manufacturers. The effective SC design requires the development of analytical models and design tools. Because of the key role of steel in the infrastructure of industries, this metal is called the development metal. Despite the importance of this industry and its economic and environmental impacts through its SC, the SC structure of this industry has been less studied at the macro level. Therefore, the purpose of this paper is twofold: first, to design the structure of a steel industry SC at three levels; and second, to find the most effective and efficient carbon dioxide emitted industry among the supplier industries of the steel industry SC in China as a case study.

In this paper, due to the relationships among different industries, DEMATEL as a multi-criteria decision-making method has been applied.

A SC structure for the steel industry has been designed at three levels. The results indicated that the industries that had the highest relationship with the steel industry are mine industry, electricity, water, and gas industry, and optical and electrical equipment industry, which were recognized as the first-level suppliers for the steel industry. On the other hand, considering the relationship among the embodied carbon dioxide emissions of various industries in China as a case study, it can be said that among the steel suppliers, the most important polluting industries, respectively, are mining industry, electricity, water, and gas industry, optical and electrical equipment industry, machinery industry, chemicals and chemical products industry and coke, refined petroleum and nuclear fuel industry.

The developed SC can help in providing the steel industries’ managers a basic model for their supplier selection problem at the macro level. This paper can also help the industrial managers to understand the causal relationships among the suppliers of their industries. Finally, this paper can help government and industries managers to discover the most polluted industrial suppliers in the steel industry.

The novelty of this study belongs to the usage of DEMATEL method based on the input-output table to discover the relationships among the industries as well as identifying the main raw material suppliers of the steel industry at three levels. Furthermore, this research discovers the relationships among the embedded carbon dioxide emission of various industries in steel SC to determine the most important polluting industries in steel SC.

The purpose of this paper is to determine the project completion time and cost under non-deterministic conditions using interval gray numbers (IGNs).

The earned value management (EVM) method based on the IGN has been developed.

The EVM method based on the IGN has been verified by a numerical example that can be applied to construction projects.

The EVM method, based on the gray numbers, reduces the budget and time shortage risk. Also, using this method, the managers would not be restricted to provide very exact values in their progress reports in the non-deterministic conditions.

One notable and significant point in all projects during the execution process is to estimate the project completion time and cost. However, non-deterministic conditions for both planned and actual physical completion percentage of projects have not been considered for predicting the project completion time and cost in the literature. Therefore, the novelty of this paper is the prediction of project completion time and cost under non-deterministic conditions using IGN.