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This study aims to clarify influencing factors of overcapacity of new energy enterprises in China and accurately predict whether these enterprises have overcapacity.

Based on relevant data including the experience and evidence from the capital market in China, the research establishes a generic univariate selection-comparative machine learning model to study relevant factors that affect overcapacity of new energy enterprises from five dimensions. These include the governmental intervention, market demand, corporate finance, corporate governance and corporate decision. Moreover, the bridging approach is used to strengthen findings from quantitative studies via the results from qualitative studies.

The authors' results show that the overcapacity of new energy enterprises in China is brought out by the combined effect of governmental intervention corporate governance and corporate decision. Governmental interventions increase the overcapacity risk of new energy enterprises mainly by distorting investment behaviors of enterprises. Corporate decision and corporate governance factors affect the overcapacity mainly by regulating the degree of overconfidence of the management team and the agency cost. Among the eight comparable integrated models, generic univariate selection-bagging exhibits the optimal comprehensive generalization performance and its area under the receiver operating characteristic curve Area under curve (AUC) accuracy precision and recall are 0.719, 0.960, 0.975 and 0.983, respectively.

The proposed integrated model analyzes causes and predicts presence of overcapacity of new energy enterprises to help governments to formulate appropriate strategies to deal with overcapacity and new energy enterprises to optimize resource allocation. Ten main features which affect the overcapacity of new energy enterprises in China are identified through generic univariate selection model. Through the bridging approach, the impact of the main features on the overcapacity of new energy enterprises and the mechanism of the influence are analyzed.

This study aims to investigate the relationship between government subsidies, R&D expenditures and overcapacity, and to explore the heterogeneity effects in different time periods and different types of companies. It can provide theoretical and practical guidance for the development of the photovoltaic industry.

This paper constructs a mediation model to explore the impact of government subsidies on overcapacity and on R&D expenditures, and to propose an indirect way to disentangle the impact of government subsidies on the creation of overcapacity from the positive aspect of increased R&D expenditures. A total of 94 listed enterprises in the Chinese photovoltaic industry were selected as the sample over the period 2012–2019.

There was significant overcapacity in the photovoltaic industry. Government subsidies had a positive effect in promoting overcapacity and R&D expenditures. The influence of government subsidies on excess capacity increased and on R&D expenditures decreased over time. Compared with large enterprises, government subsidies the small enterprises received had a greater positive impact on the overcapacity and a smaller positive impact on R&D expenditure. R&D expenditures restrained the influence of government subsidies on overcapacity, but the suppression effect was limited and decreased over time. The indirect effect in small enterprises was greater than that of large enterprises.

This paper studied government subsidies, R&D expenditure and overcapacity in the same framework and used bias-corrected bootstrapping to explore the path of “government subsidies–R&D expenditures–overcapacity”. The heterogeneous effects in different periods and different types of firms are discussed.

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.

The purpose of this paper is to demonstrate that overcapacity and tariff deficit (external constraints) negatively affect the efficiency of distribution firms in the Spanish electricity sector. To do this, the paper is based on the theory of constraints and theory of economic regulation.

Data envelopment analysis (DEA) window methodology is carried out on the constant scales (I-C) with a sample consisting of five main distribution firms during the period from 2006 to 2015. In turn, an analysis of the Malmquist index is carried out to assess whether it has had a displacement with respect to the efficiency frontier.

The results show that the overcapacity and the tariff deficit negatively affect the efficiency of the distribution firms of the Spanish electricity sector. In addition, there is an existence of external constraints that affect the activities of regulated organisations and the importance of adequate legislation in regulated sectors.

This study defines a model that shows how the efficiency problems associated with electricity distribution companies such as productive overcapacity or tariff deficit can be measured based on the theory of constraints and theory of economic regulation.

The purpose of this paper is to review the four large and two small fluctuations in China’s economic growth since the reform and opening up, which can be further divided into five periods of economic upturn and six periods of economic downturn.

This paper also analyzes the performance, causes and practical countermeasures of these fluctuations and summarizes the experience and lessons from the eight aspects of dealing with economic downturn and stabilizing growth since the reform and opening up.

At last, the paper puts forward some measures to cope with economic downturn and stabilize growth under the new normal in the new era.

Any country’s economic growth is a tortuous process with many fluctuations. The rate of economic growth cannot rise or go down straight for a long time, and China’s economic growth is no exception. The drastic fluctuations of economic growth can lead to serious overproduction, waste of resources, increased unemployment, decreased income or supply shortages, rising prices and decline of living standards.

This paper examines the different features of China's economic development in different stages of economic globalization. The study finds that the investment- and export-based growth model drove China's high-speed economic growth between 2000 and 2007, which came into existence around 2000 when China plugged into the global production network.

This paper also finds that China slowed down to the New Normal because of the disruption to the socio-economic underpinnings of this growth model. As China adapts to and steers the New Normal, supply-side structural reforms can channel excess capacity to the construction of underground pipe networks in rural areas of central China and fix capital while advance rural revitalization.

At the same time, enterprises must strive to build a key component development platform for key component innovation and the standard-setting power in global manufacturing.

The establishment of a domestic production network integrating the integrated innovation-driven core enterprises and modular producers at different levels can satisfy the dynamic demand structure of China in which standardized demands and personalized demands coexist.

Discount is on the rise, as a retail format, as a product concept and as a behaviour. It has already made deep inroads on the Continent and will inevitably invade the UK too. The rapid development of discount formats – and of discount propositions within mainstream formats – is both the source and the result of overcapacity and the increasing commodity nature of the retail offering. Argues that Private Label profitability is likely to be squeezed between the new price‐based propositions and the strong national and international brands, which are fighting to maintain their share. Retailers will have to increase their efforts on Private Label and move their offering in two parallel directions: price‐driven propositions (designed for cost) and value‐driven propositions (to compete with brands). Manufacturers, in turn, will suffer unless they take initiatives to help retailers meet the growing challenge imposed by tertiary brand developments.

Based on the operation results of Chinese hotels from 1991‐2000, this paper analyzes problems facing the Chinese lodging industry and proposes solutions. Chinese hotels’ performance, in terms of both revenue and profit, has been deteriorating since the early 1990s. While overcapacity has undoubtedly contributed to the poor performance, declining operation scale and low efficiency on the part of domestically‐owned hotels have aggravated the situation. To improve its operation results, the Chinese lodging industry should grow prudently, tap into the domestic tourist market, close the efficiency gap between domestic‐ownership and foreign‐ownership hotels and pursue economies of scale.