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Crane plays a very important role in national economy with greatly reduced labor intensity, improved production efficiency and promoted social development as an indispensable auxiliary tool and process equipment. Therefore, its energy consumption becomes an unavoidable topic and in fact, energy consumption of crane is very huge. It has been proved to be the most cost-effective way for reducing energy consumption to establish and implement new energy efficiency standard. Thus, it is necessary to analyze and evaluate the energy efficiency for overhead crane so as to propose a new energy efficiency standard. The paper aims to discuss these issues.

In this paper, four kinds of energy consumption sources of overhead crane is considered, based on which, an energy efficiency grading model for overhead crane based on BP neural network is proposed. Second, DS evidential theory is analyzed and based on it, an energy efficiency evaluation model based on BP neural network and DS evidential theory is proposed. The evaluation procedure is discussed in detail. Then, a case is demonstrated how the evaluation is carried out.

If overhead cranes with different energy consumptions need to be graded according to energy efficiency, the criterions to establish the energy efficiency labels for overhead cranes is proposed in this paper.

The research results can provide energy efficiency standard proposal of overhead crane for relative departments to monitor the design, manufacturing and use of overhead crane.

An energy efficiency grading model for overhead crane based on BP neural network is proposed. An energy efficiency evaluation model based on BP neural network and DS evidential theory is proposed.

This study empirically examines, from the first quarter of 1981 until the fourth quarter of 2017, the relations across customary domestic issuer credit ratings (long-term, short-term and subordinate) and three popular corporate risk-taking measurements (the variability of operating profitability, net profitability, and research and development expenses).

The author deploys categorical regressions and robustness tests with control variables, interaction terms, fixed effect variables, lag variables and delta variables.

The author documents that both short-term and subordinate domestic credit ratings are key determinants of the volatility of operating profitability. The author also identifies long-term credit ratings as secondary factors, yet they do affect broader corporate risk-taking behavioral features (along all three measurements). Furthermore, the author finds that the higher (lower) the credit ratings assigned, i.e. the superior (inferior) the credit quality externally judged, the more (less) overall risk firms tend to undertake.

It is the first research to examine both the inclusive influence and the granular effects of credit ratings on corporate risk-taking (CRT) behavior. It is also the only enquiry to inspect the specific relationships along three types of domestic issuer credit ratings: long-term, short-term and subordinate ratings.