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In the process of undertaking overseas construction projects, relational governance has become indispensable for project stakeholders. This study examines how relational governance influences contractors' adaptability to foreign situations and whether such associations are positively moderated by international environmental complexity.

A crosssectional survey methodology was applied to collect primary data through questionnaires sent to domestic contractors in China and South Korea (hereafter Korea). Multiple regression analysis was used to test the effects of four dimensions of relational governance on contractor adaptability. Thereafter, the Chinese and Korean subsamples were tested separately through moderated regression analysis to explore differences in the influence of relational governance on adaptability.

The results showed that quality communication, favor exchange and establishing an emotional relationship significantly and positively affected a contractor’s adaptability. However, there were significant differences between the Chinese and Korean international contractors in terms of the moderating effects of international environment complexity.

East Asian engagement in international development is not limited to China and Korea alone, and the study should be replicated using large representative samples from more countries, such as Japan, to gain a fuller understanding of the influence of relational governance.

The results have great significance for the managers of international contractors in East Asian countries and contribute to the research on relational governance and contractor adaptability.

This paper takes the seven overcapacity industries such as the textile industry, electricity and heat, steel, coal, automobile manufacturing, nonferrous metals and petrochemical industry as research objects and proposes a TOPSIS grey relational projection group decision method with mixed multiattributes, which is used for the ranking of the seven industries with overcapacity and provided relevant departments with a basis for decision-making.

First, an evaluation index system from four aspects is established. Secondly, the attributes of linguistic information are converted into two-dimensional interval numbers and triangular fuzzy numbers, and an evaluation matrix is constructed and normalized. This paper uses the AHP method to determine the subjective weights and uses the coefficient of variation method to determine the objective weights. Moreover, this paper sets up the optimization model with the largest comprehensive evaluation value to determine the combined weights. Finally, the TOPSIS grey relational projection method is proposed to calculate the closeness of grey relational projections and to rank them.

This paper analyzes the problem of overcapacity in seven industries with the TOPSIS grey relational projection method. The results show that the four industries of automobile manufacturing, textile, coal and petrochemical are all in serious overcapacity levels, while the three industries of steel, nonferrous metals and electric power are relatively in weak overcapacity level in the three years of 2016–2018. TOPSIS grey relational projection method ranks the overcapacity degree of the seven major overcapacity industries, making the relative overcapacity degree of each industry more clear and providing a reference for the government to formulate targeted policies and measures for each industry.

By using TOPSIS grey relational projection method to evaluate the overcapacity of the seven major overcapacity industries, on the one hand, it makes the relative overcapacity degree of each industry more clear, on the other hand, it can provides the basis for the government and decision-making departments. This helps them promote better the healthy and orderly economic development of the seven major industries and avoid resource waste caused by overcapacity.

This article solves the single evaluation method caused by the limited indicators in the past, combines TOPSIS and the grey relational projection method and applies it to the overcapacity evaluation of the industry, not only applies it to the evaluation of overcapacity for the first time but also involves novel problems and methods, which expands the scope of application of the model.