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1 – 10 of 13Xiaoming Yang, Jianxin Ge, Vijaya Baskar Masilamani and Zhihao Yu
This paper aims to examine the impact of visualization tools on the financing ratio of crowdfunding platforms projects of social enterprises, and to sort out personal quality…
Abstract
Purpose
This paper aims to examine the impact of visualization tools on the financing ratio of crowdfunding platforms projects of social enterprises, and to sort out personal quality signals and project quality signals based on signaling theory. This paper also divides the emotions and feelings brought by the visualization tools into persuasive and informative styles, showing the functions of different tools on the crowdfunding performance of social ventures.
Design/methodology/approach
Linear regression and binary regression are applied to analyze data on social entrepreneurship projects from two internationally authoritative crowdfunding platforms, Kickstarter and Indiegogo.
Findings
In social entrepreneurship projects, the number of emotionally persuasive images has a significant positive impact on the financing ratio. Among them, the financing target has a negative regulatory effect.
Research limitations/implications
The study has not fully explored how different visual aspects (such as color and composition) impact investor perceptions. Future research should address these variables for a more accurate understanding of how visualization affects financing performance.
Practical implications
This paper summarizes the factors that affect the crowdfunding ratio and provides a visualization tool from an innovative perspective. The application provides reference value for all types of crowdfunding projects on the crowdfunding platforms.
Social implications
Social entrepreneurs should use the crowdfunding model to raise funds and deepen their understanding of crowdfunding investors, so that more people can participate in social entrepreneurship and thereby generate greater social value.
Originality/value
This paper provides a new perspective for the classification of visualization tools. This paper divides the emotions and feelings brought by the visualization tools to the information recipients, and classifies them into persuasive and informative styles, showing the functions of different tools.
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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/
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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.
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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.
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Xiaoming Chen and Jian Xu
The objective of this study is to investigate how the coronavirus disease 2019 (COVID-19) pandemic affects firms' financial management in China's manufacturing sector. In…
Abstract
Purpose
The objective of this study is to investigate how the coronavirus disease 2019 (COVID-19) pandemic affects firms' financial management in China's manufacturing sector. In addition, the authors analyze the changes in various financial indicators before and during the COVID-19 pandemic. Further, the authors make a cross-country comparison of the COVID-19's impact on financial management between China and Romania.
Design/methodology/approach
The study uses the balanced panel data of 2,272 manufacturing listed companies from 2019 to 2020, and applies the t-test method and multiple regression method.
Findings
The results show that firms' financial performance in most manufacturing sub-sectors decreased during the observed period. In addition, the authors find that equity financing, proper liquidity management and an expanded firm scale can improve firms' financial performance. The authors further compare the results with the Romanian results, and find that the negative impact of debt-to-equity ratio on firms' financial performance in Romania is greater than that in China and the positive impact of financial autonomy ratio and working capital ratios is greater in China than that in Romania.
Practical implications
The findings can help corporate managers make the best financial management decision in response to crisis.
Originality/value
This study is one of the pioneers that analyze how manufacturing companies carried out their financial management during the COVID-19 crisis in the Chinese context, and provides a cross-country analysis of corporate financial management practices in China and Romania.
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Chong Zhao, Manqi Yao, Xiaoming Han, Wei Qi, Linlin Su, Rong Fu and Fei Gao
This study aims to analyze the temperature difference between aluminum-based brake disc (ABD) and cast steel brake disc (CSBD) for rail vehicles in the braking process, which is…
Abstract
Purpose
This study aims to analyze the temperature difference between aluminum-based brake disc (ABD) and cast steel brake disc (CSBD) for rail vehicles in the braking process, which is related to the popularization and use of ABD.
Design/methodology/approach
Two friction pairs composed of ABD, CSBD and copper-based powder metallurgy brake pad were studied in this paper. The temperature characteristics of the two friction pairs were compared by 1:1 braking test and simulation calculation.
Findings
When the speed is 160–250 km/h and the braking pressure is 18 and 29 kN, the calculated maximum temperature of CSBD is 574°C and 681°C, respectively, which is higher than that of ABD 49°C–148°C and 73°C–217°C. Under the test conditions, the maximum temperature of CSBD is 487°C and 624°C respectively, which is higher than that of ABD 63°C–95°C and 63°C–188°C. The temperature difference between ABD and CSBD increases with the increase of braking pressure and speed. The surface temperature distribution of CSBD is “three-peak,” whereas that of ABD is “single-peak.”
Originality/value
This paper reveals the temperature difference between ABD and CSBD and provides data support for promoting the use of ABD.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2024-70320/
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Yalan Wang, Chengjun Wang, Wei Wang and Xiaoming Sun
This study aims to investigate the influence of inventors’ abilities to acquire external knowledge, provide broad and professional knowledge and patenting output (i.e. different…
Abstract
Purpose
This study aims to investigate the influence of inventors’ abilities to acquire external knowledge, provide broad and professional knowledge and patenting output (i.e. different types of inventors) on the formation of structural holes.
Design/methodology/approach
The authors collected 59,798 patents applied for and granted in the USA by 33 of the largest firms worldwide in the pharmaceutical industry between 1975 and 2014. A random-effects tobit model was used to test the hypotheses.
Findings
The inventors’ ability to acquire external knowledge contributes to the formation of structural holes. While inventors’ ability to provide broad knowledge positively affects the formation of structural holes, their ability to provide professional knowledge works otherwise. In addition, key inventors and industrious inventors are more likely to form structural holes than talents.
Originality/value
The results identify individual factors that affect the formation of structural holes and improve the understanding of structural hole theory. This study is unique in that most scholars have studied the consequences of structural hole formation rather than their antecedents. Studies on the origin of structural holes neglect the effect of inventors’ knowledge abilities and patenting output. By addressing this gap, this study contributes to a more comprehensive theoretical understanding of structural holes. The results can guide managers in managing structural holes in accordance with inventors’ knowledge abilities and patenting outputs, which optimize the allocation of network resources.
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Jiaping Zhang and Xiaomei Gong
The research attempts to estimate how the use of WeChat, the most popular mobile social networking application in contemporary China, affects rural household income.
Abstract
Purpose
The research attempts to estimate how the use of WeChat, the most popular mobile social networking application in contemporary China, affects rural household income.
Design/methodology/approach
Our materials are 4,552 rural samples from the Chinese General Social Survey, and a treatment effect (TE) model is employed to address the endogeneity of WeChat usage.
Findings
The results prove that WeChat usage has a statistically significant and positive correlation with rural household income. This conclusion remains robust after using alternative variables to replace the explanatory and dependent variables. Our research provides two channels through which WeChat usage boosts rural household income, namely, it can promote their off-farm employment and participation in investment activities.
Originality/value
Theoretically, the study provides several micro-evidences for understanding the impact of mobile social networks on rural household welfare. Further, our findings may shed light on the importance of digital technology applications in rural poverty alleviation for developing countries.
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Peng Gao, Xiuqin Su, Zhibin Pan, Maosen Xiao and Wenbo Zhang
This study aims to promote the anti-disturbance and tracking accuracy performance of the servo systems, in which a modified active disturbance rejection control (MADRC) scheme is…
Abstract
Purpose
This study aims to promote the anti-disturbance and tracking accuracy performance of the servo systems, in which a modified active disturbance rejection control (MADRC) scheme is proposed.
Design/methodology/approach
An adaptive radial basis function (ARBF) neural network is utilized to estimate and compensate dominant friction torque disturbance, and a parallel high-gain extended state observer (PHESO) is employed to further compensate residual and other uncertain disturbances. This parallel compensation structure reduces the burden of single ESO and improves the response speed of permanent magnet synchronous motor (PMSM) to hybrid disturbances. Moreover, the sliding mode control (SMC) rate is introduced to design an adaptive update law of ARBF.
Findings
Simulation and experimental results show that as compared to conventional ADRC and SMC algorithms, the position tracking error is only 2.3% and the average estimation error of the total disturbances is only 1.4% in the proposed MADRC algorithm.
Originality/value
The disturbance parallel estimation structure proposed in MADRC algorithm is proved to significantly improve the performance of anti-disturbance and tracking accuracy.
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Farhan Mirza and Naveed Iqbal Chaudhry
Civil service workers are valuable resources for any nation and play a crucial role in driving their country’s economic development. Per the supervisor, this research examines the…
Abstract
Purpose
Civil service workers are valuable resources for any nation and play a crucial role in driving their country’s economic development. Per the supervisor, this research examines the impact of mindfulness, proactive personality, and career competencies on employee job performance. The study also analyzes the effects of career adaptability and identity on this aspect.
Design/methodology/approach
To test the model of this study, questionnaires were administered to a sample of 500 civil service employees whose career-based knowledge and skills were measured in various cities in the province of Punjab, Pakistan.
Findings
Mindfulness and career competencies significantly impact supervisor-rated task performance, whereas a proactive personality does not substantially relate to supervisor-rated task performance. Research indicated that the two hypotheses about mediation were accepted. However, career adaptability does not play a significant role in the link between mindfulness and how well a supervisor rates task performance. Regarding moderation, career identity did not significantly moderate the relation between proactive personality and supervisor-rated task performance. However, the other two moderate hypotheses have been proven to be significant.
Research limitations/implications
The findings offer compelling support for career construction theory (CCT) in this study area by analyzing the connections related to career adaptability and identity within the framework. In the future, researchers can build on this model by adding theories like conservation of resources (COR), looking into possible moderators that might change specific pathways in this network of relationships and using longitudinal designs to find stronger causal relationships.
Originality/value
Considering the evolving workplace due to the COVID-19 pandemic, the study offers fresh perspectives on the post-COVID situation, understanding and integrating various variables. For future studies, more variables can be explored in this model with the expansion of sample size and change of context.
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