Chi‐Yih Yang, Boon Leing Tan and Xiaoming Ding
The purpose of this paper is to examine empirically whether corporate governance mechanisms have an effect on income‐smoothing behavior in the People's Republic of China.
Abstract
Purpose
The purpose of this paper is to examine empirically whether corporate governance mechanisms have an effect on income‐smoothing behavior in the People's Republic of China.
Design/methodology/approach
The sample comprises 1,358 companies listed in the Shanghai Stock Exchange and the Shenzhen Stock Market during the period 1999 to 2006. By comparing the variability of income to the variability of sales, an income smoother can be identified if income is less variable than sales.
Findings
The authors' empirical results show that income smoothing is more severe when the state is the controlling shareholder of the Chinese listed firm. Firms with more independent directors are more likely to engage in income smoothing. The governance mechanisms such as board of directors, supervisory board, audit committee, external auditors, and shareholders' participation are not effective in curtailing income smoothing in China.
Practical implications
For Chinese firms and especially government‐linked enterprises, the way in which they present themselves may be significant, since the image they present to potential strategic partners may be marred by suspicions of income smoothing.
Originality/value
The paper presents the current development of China's corporate governance system and indicates that agency conflicts between controlling shareholders and minority investors account for a significant portion of earnings management in China.
Details
Keywords
Xiangmeng Huang, Boon Leing Tan and Xiaoming Ding
The purpose of this paper is to empirically investigate the pressures and drivers that have been experienced by Chinese manufacturing small and medium enterprises (SMEs) in terms…
Abstract
Purpose
The purpose of this paper is to empirically investigate the pressures and drivers that have been experienced by Chinese manufacturing small and medium enterprises (SMEs) in terms of green supply chain management (GSCM).
Design/methodology/approach
The research framework and hypotheses are examined by a questionnaire survey through e-mails conducted in China in 2011. The empirical analysis is based on the data from 202 SME manufacturers in China. Validity and reliability of the items employed in the research is assessed through Cronbach’s α test. Hypotheses for the identification of GSCM pressures and drivers to SMEs as well as the differences that exist among different industrial sectors are tested by adopting descriptive statistics analysis and analysis of variance test.
Findings
This study finds that Chinese manufacturing SMEs have been under pressures from a variety of sources, including regulations, customers, suppliers and public awareness in terms of GSCM. Besides, internal drivers are also an important encouragement for SMEs to consider GSCM. Moreover, Chinese manufacturing SMEs from different industrial sectors show some differences in experiencing pressures or being motivated by drivers.
Research limitations/implications
The main limitations to this paper are the relatively small sample of SMEs and the potentially overlooked variables.
Practical implications
Chinese manufacturing SMEs and their larger customers, as well as governments, are likely to obtain some implications from this study if they are willing to consider any GSCM initiatives throughout the supply chain.
Originality/value
The paper clearly explores the GSCM pressures and drivers faced by the Chinese manufacturing SMEs where the results may differ from the findings through the studies on large enterprises or SMEs in other national context.
Details
Keywords
The purpose of this paper is to assess the application of the nascent corporate opportunity doctrine in China by comparison with its well-established English counterpart; in…
Abstract
Purpose
The purpose of this paper is to assess the application of the nascent corporate opportunity doctrine in China by comparison with its well-established English counterpart; in particular, it evaluates whether the fine balance between business integrity and business efficiency has been struck.
Findings
It is argued that the scope of application of the corporate opportunity doctrine in China should be extended, and the rules on the burden of proof should be amended. Moreover, a stricter approach should be adopted by the Chinese judiciary for the purpose of protecting the company’s interests and enhancing business integrity.
Research limitations/implications
This paper mainly focuses on the corporate opportunity doctrine. It does not discuss other duties of directors in detail.
Practical implications
It is useful for directors in balancing business integrity and business efficiency.
Originality/value
It is an original piece of work which assesses the corporate opportunity doctrine by making comparison with English law.
Details
Keywords
Huiyong Wang, Ding Yang, Liang Guo and Xiaoming Zhang
Intent detection and slot filling are two important tasks in question comprehension of a question answering system. This study aims to build a joint task model with some…
Abstract
Purpose
Intent detection and slot filling are two important tasks in question comprehension of a question answering system. This study aims to build a joint task model with some generalization ability and benchmark its performance over other neural network models mentioned in this paper.
Design/methodology/approach
This study used a deep-learning-based approach for the joint modeling of question intent detection and slot filling. Meanwhile, the internal cell structure of the long short-term memory (LSTM) network was improved. Furthermore, the dataset Computer Science Literature Question (CSLQ) was constructed based on the Science and Technology Knowledge Graph. The datasets Airline Travel Information Systems, Snips (a natural language processing dataset of the consumer intent engine collected by Snips) and CSLQ were used for the empirical analysis. The accuracy of intent detection and F1 score of slot filling, as well as the semantic accuracy of sentences, were compared for several models.
Findings
The results showed that the proposed model outperformed all other benchmark methods, especially for the CSLQ dataset. This proves that the design of this study improved the comprehensive performance and generalization ability of the model to some extent.
Originality/value
This study contributes to the understanding of question sentences in a specific domain. LSTM was improved, and a computer literature domain dataset was constructed herein. This will lay the data and model foundation for the future construction of a computer literature question answering system.
Details
Keywords
Jin Zhang, Xiaoming Qian and Jing Feng
Under the global climate change, carbon footprint has become a hot issue at home and abroad. However, there is no consensus on the concept, measurement and application of carbon…
Abstract
Purpose
Under the global climate change, carbon footprint has become a hot issue at home and abroad. However, there is no consensus on the concept, measurement and application of carbon footprint.
Design/methodology/approach
In this paper, first, the concept and connotation of carbon footprint are reviewed; then, different methods of carbon footprint measurement are compared, and it is found that “bottom-up” life cycle assessment and “top-down” input–output analysis are applicable to different research scales.
Findings
Finally, the problems in the process of carbon footprint assessment in textile industry are analyzed and further research directions are proposed.
Originality/value
Analyzed and further research directions are proposed.
Details
Keywords
Xiaoliang Liu, Xiaoming Huang, Jian Zhang and Weitao Sun
The purpose of this study is to investigate the influence mechanism of different interface component surface textures on the ultrasonic motor (USM) output performance.
Abstract
Purpose
The purpose of this study is to investigate the influence mechanism of different interface component surface textures on the ultrasonic motor (USM) output performance.
Design/methodology/approach
The energy transmission mechanism of the traveling-wave ultrasonic motor 60 (TRUM-60) was numerically and experimentally investigated by fabricating dimple textures with different feature types on the friction material and the stator.
Findings
Textured friction material can increase the contact range effectively, and thus, can improve the friction characteristics of the interface and the output performance of the TRUM-60. The experimental results verified the expected influence mechanism and demonstrated that the use of either a textured friction material or stator has a very different effect on USM output performance. A textured PI-based friction material improved the TRUM-60 output performance, resulting in a maximum energy conversion efficiency of 57.11%. However, a textured stator degraded the TRUM-60 output performance, resulting in a minimum energy conversion efficiency of only 44.92%.
Originality/value
The results of this study provide a theoretical foundation for improved USM designs with textured interfaces.
Details
Keywords
Zeqian Wang, Chengjun Wang, Xiaoming Sun and Tao Feng
The role of inventors' creativity is crucial for technological innovation within enterprises. The mobility of inventors among different enterprises is a primary source for…
Abstract
Purpose
The role of inventors' creativity is crucial for technological innovation within enterprises. The mobility of inventors among different enterprises is a primary source for companies to acquire external knowledge. The mechanism of “learning-by-hiring” is widely recognized by companies. Therefore, it is important to determine how to allocate network resources to enhance the creativity of inventors when companies hire mobile inventors.
Design/methodology/approach
The study suggests an analytical framework that analyzes alterations in tie strength and structural holes resulting from the network embeddedness of mobile inventors as well as the effect of the interaction between these two variables on changes in inventor’s creativity after the mobility. In addition, this paper examines the moderating impact of cognitive richness of mobile inventors and cognitive distance between mobile inventors and new employers on the correlation between network embeddedness and creativity.
Findings
This study found that: (1) The increase of tie strength has a significant boost in creativity. (2) Increasing structural holes can significantly improve the creativity of mobile inventors. (3) When both the tie strength and the structural holes increase, the creativity of the mobile inventors significantly increases. (4) It is important to note that when there is a greater cognitive distance, stronger tie strength promotes the creativity of mobile inventors. Additionally, cognitive richness plays a significant role in moderating the relationship between changes in structural holes and the creativity of mobile inventors.
Originality/value
These findings provide theoretical guidance for firms to effectively manage mobile inventors and optimize collaborative networks within organizations.
Details
Keywords
Xiaoming Han, He Zhang and Kangjian Yang
This study aims to investigate the temperature rise characteristics of vibrating rolling bearings under the influence of the polarization force of unbalanced eccentric blocks. A…
Abstract
Purpose
This study aims to investigate the temperature rise characteristics of vibrating rolling bearings under the influence of the polarization force of unbalanced eccentric blocks. A thermal-fluid-solid mechanics coupled finite element model is established to analyze the effects of different loads and rotational speeds on bearing temperature to prevent overheating, wear and thermal damage.
Design/methodology/approach
A thermal-fluid-solid mechanics coupled finite element model of the vibrating rolling bearing is developed based on the principles of heat transfer. Finite element analysis software is used to conduct numerical simulations and study the temperature distribution of the bearing system under different loads and speeds. The model’s accuracy is verified by experimentally measuring the actual temperature of the bearing under the same working conditions.
Findings
This study successfully established a thermal-fluid-solid mechanics coupled finite element model of a vibrating rolling bearing, verifying its accuracy and reliability. The research results provide an essential reference for optimizing bearing design, preventing overheating and extending service life.
Research limitations/implications
By analyzing the temperature rise characteristics under various load and rotational speed conditions, the law governing the internal temperature distribution of bearings is revealed. This finding offers a theoretical foundation for comprehending the thermal behavior of bearings.
Practical implications
This study offers a scientific foundation for the maintenance and fault diagnosis of shaker rolling bearings, aiding in the timely identification and resolution of thermal damage issues. Through the optimization of bearing design and usage conditions, the equipment’s lifespan can be prolonged, maintenance expenses can be minimized and production efficiency can be enhanced.
Originality/value
A thermal-fluid-solid mechanics coupled finite element model of a vibrating rolling bearing was established, considering the interaction of multiple physical fields. The influence of the polarization force from the unbalanced eccentric block on the bearing temperature is analyzed in detail, which is close to the actual working conditions.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2024-0396/
Details
Keywords
Zhiqiang Zhang, Xiaoming Li, Xinyi Xu, Chengjie Lu, Yihe Yang and Zhiyong Shi
The purpose of this study is to explore the potential of trainable activation functions to enhance the performance of deep neural networks, specifically ResNet architectures, in…
Abstract
Purpose
The purpose of this study is to explore the potential of trainable activation functions to enhance the performance of deep neural networks, specifically ResNet architectures, in the task of image classification. By introducing activation functions that adapt during training, the authors aim to determine whether such flexibility can lead to improved learning outcomes and generalization capabilities compared to static activation functions like ReLU. This research seeks to provide insights into how dynamic nonlinearities might influence deep learning models' efficiency and accuracy in handling complex image data sets.
Design/methodology/approach
This research integrates three novel trainable activation functions – CosLU, DELU and ReLUN – into various ResNet-n architectures, where “n” denotes the number of convolutional layers. Using CIFAR-10 and CIFAR-100 data sets, the authors conducted a comparative study to assess the impact of these functions on image classification accuracy. The approach included modifying the traditional ResNet models by replacing their static activation functions with the trainable variants, allowing for dynamic adaptation during training. The performance was evaluated based on accuracy metrics and loss profiles across different network depths.
Findings
The findings indicate that trainable activation functions, particularly CosLU, can significantly enhance the performance of deep learning models, outperforming the traditional ReLU in deeper network configurations on the CIFAR-10 data set. CosLU showed the highest improvement in accuracy, whereas DELU and ReLUN offered varying levels of performance enhancements. These functions also demonstrated potential in reducing overfitting and improving model generalization across more complex data sets like CIFAR-100, suggesting that the adaptability of activation functions plays a crucial role in the training dynamics of deep neural networks.
Originality/value
This study contributes to the field of deep learning by introducing and evaluating the impact of three novel trainable activation functions within widely used ResNet architectures. Unlike previous works that primarily focused on static activation functions, this research demonstrates that incorporating trainable nonlinearities can lead to significant improvements in model performance and adaptability. The introduction of CosLU, DELU and ReLUN provides a new pathway for enhancing the flexibility and efficiency of neural networks, potentially setting a new standard for future deep learning applications in image classification and beyond.