The purpose of this paper is to explore the reasons for the high‐frequency switches of lead underwriters by Chinese listed companies in their seasoned equity offerings. It…
Abstract
Purpose
The purpose of this paper is to explore the reasons for the high‐frequency switches of lead underwriters by Chinese listed companies in their seasoned equity offerings. It contributes to the literature by filling the gap and providing evidence that institutional and non‐market factors could affect listed companies' decisions to switch their lead underwriters in the Chinese capital market.
Design/methodology/approach
This paper employs a numerical measure of listed companies' loyalty to evaluate their frequency of switching lead underwriters, and employs a Logit model and an OLS model to identify the key determinants of switching lead underwriters by Chinese listed companies.
Findings
It is observed that the frequency of switching lead underwriters is very high among Chinese listed companies for their seasoned offerings. It is also found that underwriters' deficient reputation and the lack of industrial experience, together with the depreciation of relationship‐specific assets, could have important impacts on lead underwriters being frequently switched in China. Besides, the frequent switches of lead underwriters could also be attributable to the non‐market supervision and regulatory influences by Chinese authorities over the security underwriting market.
Originality/value
This paper could help further the understanding of the factors that could explain the listed companies' frequent switches of their lead underwriters for their seasoned offerings in China. In addition, this paper has policy implications on how to improve the listed companies' loyalty for regulators in China. These implications could help improve the regulatory environment and promote the overall performance of the Chinese security underwriting market.
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Dawei Jin, Jianghui Liu, Liuling Liu and Desheng Yin
– The purpose of this paper is to investigate the quality of financial reporting by banks in China, and the profit hiding behavior of banks in particular.
Abstract
Purpose
The purpose of this paper is to investigate the quality of financial reporting by banks in China, and the profit hiding behavior of banks in particular.
Design/methodology/approach
Reported profit is compared with actual profit using multiple regression analysis. The identification strategy allows the authors to quantify the degree of profit hiding in banking institutions.
Findings
Profit hiding exists in the whole banking sector in China regardless of the ownership structure of individual banks, though joint-stock banks have higher degree of profit hiding. Banks that are more financially constrained hide more profit than those less constrained ones. The competition in the banking industry competition impacts the extent of profit hiding, with higher competition being associated with lower degree of profit hiding.
Research limitations/implications
This paper documents the prevailing behavior of profit hiding in Chinese banks. It raises issues regarding the conventional methods of measuring bank efficiencies using accounting information reported by banking institutions.
Originality/value
This paper empirically examines the profit hiding behavior of banks in a transitional country.
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With the improvement of economic level, car ownership is growing, and the number of scrapped automobiles is increasing. Therefore, evaluation research for auto parts…
Abstract
Purpose
With the improvement of economic level, car ownership is growing, and the number of scrapped automobiles is increasing. Therefore, evaluation research for auto parts remanufacturing is particularly important. The purpose of this paper is to construct the evaluation index system of auto parts remanufacturing and research the grey clustering theory. The grey fixed weight clustering evaluation is used to evaluate automobile engine remanufacturability.
Design/methodology/approach
According to the policies and regulations of China about remanufacturing, economic, technical, resources, energy and the environment, four indexes are selected to set up the evaluation standard of auto parts remanufacturing scheme. Grey fixed weight clustering method is used to evaluate remanufacturability of the auto parts. Firstly, number index and grey determine the whitenization weight function, then based on the clustering weight of each index, the clustering coefficient matrix is calculated. Finally, the class that certain object belongs to, according to the clustering coefficient matrix is determined.
Findings
Results show that constructed indexes of auto parts remanufacturing scheme can be used for effective evaluation. And the proposed fixed weight grey cluster model can aggregate all indexes information well. Therefore, the proposed indexes and model in this paper are effective and can be used for auto parts remanufacturing.
Practical implications
According to the requirements of the current situation in China, this paper puts forward a method based on grey clustering decision, to evaluate different auto parts remanufacturing schemes, for manufacturing enterprises to provide theoretical basis for remanufacturing production, in order to realize the reasonable configuration of resources.
Originality/value
This paper firstly establishes the evaluation index system of auto parts remanufacturing, the grey clustering theory is introduced into the evaluation of remanufacturing. The fixed-weight grey cluster model is proposed to aggregate indexes’ information.
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Jun-peng Shao, Guang-dong Liu, Xiao-dong Yu, Yan-qin Zhang, Xiu-li Meng and Hui Jiang
The purpose of this paper is to describe a simulation and experimental research concerning the effect of recess depth on the lubrication performance of a hydrostatic thrust…
Abstract
Purpose
The purpose of this paper is to describe a simulation and experimental research concerning the effect of recess depth on the lubrication performance of a hydrostatic thrust bearing by constant rate flow.
Design/methodology/approach
The computational fluid dynamics and finite volume method have been used to compute the lubrication characteristics of an annular recess hydrostatic thrust bearing with different recess depths. The performances are oil recess pressure, oil recess temperature and oil film velocity. The recess depth has been optimized. A test rig is established for testing the pressure field of the structure of hydrostatic thrust bearing after recess depth optimization, and experimental results show that experimental data are basically identical with the simulation results, which demonstrates the validity of the proposed numerical simulation method.
Findings
The results demonstrate that the oil film temperature decreases and the oil film pressure first increases and then decreases with an increase in the recess depth, but oil film velocity is constant. To sum up comprehensive lubrication performance, the recess depth of 3.5 mm is its optimal value for the annular recess hydrostatic thrust bearing.
Originality/value
The computed results indicate that to get an improved performance from a constant flow hydrostatic thrust bearing, a proper selection of the recess depth is essential.
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The purpose of this paper is to study a novel grey possibility degree approach, which is combined with multi-attribute decision making (MADM) and applied MADM model for solving…
Abstract
Purpose
The purpose of this paper is to study a novel grey possibility degree approach, which is combined with multi-attribute decision making (MADM) and applied MADM model for solving supplier selection problem under uncertainty information.
Design/methodology/approach
The supplier selection problem is a typical MADM problem, in which information of a series of indexes should be aggregated. However, it is relatively easy for decision makers to define information in uncertainty, sometimes as a grey number, rather than a precise number. By transforming linguistic scale of rating supplier selection attributes into interval grey numbers, a novel grey MADM method is developed. Steps of proposed model were provided, and a novel grey possibility degree approach was proposed. Finally, a numerical example of supplier selection is utilized to demonstrate the proposed approach.
Findings
The results show that the proposed approach could solve the uncertainty decision-making problem. A numerical example of supplier selection is utilized to demonstrate the proposed approach. The results show that the proposed method is useful to aggregate decision makers’ information so as to select the potential supplier.
Practical implications
The approach constructed in the paper can be used to solving uncertainty decision-making problems that the certain value of the decision information could not collect while the interval value set could be defined. Obviously it can be utilized for other MADM problem.
Originality/value
The paper succeeded in redefining interval grey number, constructing a novel interval grey number based MADM approach and providing the solution of the proposed approach. It is very useful to solving system forecasting problem and it contributed undoubtedly to improve grey decision-making models.
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Hongyi Chen, Jianghui Chen and Gaofeng Han
This chapter studies banks’ loan pricing behavior in mainland China during 2003–2013 by applying panel regressions to firm-level loan data and the estimated default likelihood for…
Abstract
This chapter studies banks’ loan pricing behavior in mainland China during 2003–2013 by applying panel regressions to firm-level loan data and the estimated default likelihood for listed companies. The authors find that with the progress of market-oriented financial reforms, banks generally require compensation for their exposure to borrowers’ default risks. It is even more so if the borrower is a non-state-owned enterprise (non-SOE), mainly due to the pricing behavior of the Big Four banks. Bank lending rates are shown to be less sensitive to the default risks of state-owned enterprises (SOEs). Our results also reveal that banks priced in firm default risks before 2008 financial crisis, but not necessarily so after the crisis. As for industries, we find that after the 2008 Global Financial Crisis, the real estate sector and other government-supported industries tended to enjoy better terms on loan pricing in terms of default risks. We believe the main reason is that the government stimulus policies tilted toward those industries that have played crucial roles in China’s economic growth.