Zhe Dai, Yazhen Gong, Shashi Kant and Guodong Ma
This article aims to explore the impact of climate disasters on small-scale farmers’ willingness to cooperate and explore the mediating effect of social capital.
Abstract
Purpose
This article aims to explore the impact of climate disasters on small-scale farmers’ willingness to cooperate and explore the mediating effect of social capital.
Design/methodology/approach
The study investigates farmers’ willingness to cooperate through a framed field approach and surveys the information of individuals and villages, including climate disasters and social capital, using a structured questionnaire from rural communities in Jiangxi and Sichuan, China.
Findings
The results show that climate disasters and social capital are significant and positive determinants of farmers’ willingness to cooperate. In specific types of climate disasters, drought is positively associated with farmers’ cooperation willingness. Moreover, the mediation effect of drought on farmers’ willingness to cooperate through social capital has been demonstrated to be significant although negative, whereas the mediation effect of flood on farmers’ willingness to cooperate through social capital is significant and positive.
Originality/value
First, given the limited studies focusing on the impact of climate disasters on small-scale farmers’ willingness to cooperate, the authors complement the existing literature through a framed field experiment approach by designing a scenario that every farmer may encounter in their production activities. Second, the study figures out the roles of drought and flood as different kinds of climate disasters in farmers’ decision-making of cooperation and sheds light on the positive impact of climate disasters on small-scale farmers. Finally, this paper provides empirical evidence of social capital as a potential channel through which climate disasters could possibly affect farmers’ willingness to cooperate.
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Jiahao Wang, Guodong Xia, Ran Li, Dandan Ma, Wenbin Zhou and Jun Wang
This study aims to satisfy the thermal management of gallium nitride (GaN) high-electron mobility transistor (HEMT) devices, microchannel-cooling is designed and optimized in this…
Abstract
Purpose
This study aims to satisfy the thermal management of gallium nitride (GaN) high-electron mobility transistor (HEMT) devices, microchannel-cooling is designed and optimized in this work.
Design/methodology/approach
A numerical simulation is performed to analyze the thermal and flow characteristics of microchannels in combination with computational fluid dynamics (CFD) and multi-objective evolutionary algorithm (MOEA) is used to optimize the microchannels parameters. The design variables include width and number of microchannels, and the optimization objectives are to minimize total thermal resistance and pressure drop under constant volumetric flow rate.
Findings
In optimization process, a decrease in pressure drop contributes to increase of thermal resistance leading to high junction temperature and vice versa. And the Pareto-optimal front, which is a trade-off curve between optimization objectives, is obtained by MOEA method. Finally, K-means clustering algorithm is carried out on Pareto-optimal front, and three representative points are proposed to verify the accuracy of the model.
Originality/value
Each design variable on the effect of two objectives and distribution of temperature is researched. The relationship between minimum thermal resistance and pressure drop is provided which can give some fundamental direction for microchannels design in GaN HEMT devices cooling.
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Xiaobo Shi, Yan Liu, Kunkun Ma, Zixin Gu, Yaning Qiao, Guodong Ni, Chibuzor Ojum, Alex Opoku and Yong Liu
The purpose is to identify and evaluate the safety risk factors in the coal mine construction process.
Abstract
Purpose
The purpose is to identify and evaluate the safety risk factors in the coal mine construction process.
Design/methodology/approach
The text mining technique was applied in the stage of safety risk factor identification. The association rules method was used to obtain associations with safety risk factors. Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Interpretative Structural Modeling (ISM) were utilized to evaluate safety risk factors.
Findings
The results show that 18 safety risk factors are divided into 6 levels. There are 12 risk transmission paths in total. Meanwhile, unsafe behavior and equipment malfunction failure are the direct causes of accidents, and inadequate management system is the basic factor that determines the safety risk status.
Research limitations/implications
Due to the limitation of the computational matrix workload, this article only categorizes numerous lexical items into 18 factors. Then, the workshop relied on a limited number of experts; thus, the findings may be potentially biased. Next, the accident report lacks a universal standard for compilation, and the use of text mining technique may be further optimized. Finally, since the data are all from China, subsequent cross-country studies should be considered.
Social implications
The results can help China coal mine project managers to have a clear understanding of safety risks, efficiently carry out risk hazard identification work and take timely measures to cut off the path of transmission with risks identified in this study. This helps reduce the economic losses of coal mining enterprises, thus improving the safety standards of the entire coal mining industry and the national standards for coal mine safety policy formulation.
Originality/value
Coal mine construction projects are characterized by complexity and difficulties in construction. Current research on the identification and assessment of safety risk factors in coal mine construction is insufficient. This study combines objective and systematic research approaches. The findings contribute to the safety risk management of China coal mine construction projects by providing a basis for the development of safety measures.
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Guodong Ni, Qi Zhou, Xinyue Miao, Miaomiao Niu, Yuzhuo Zheng, Yuanyuan Zhu and Guoxuan Ni
New generation of construction workers (NGCWs) who were born in the 1980s and later have gradually become the main workforce of Chinese construction industry. They may behave…
Abstract
Purpose
New generation of construction workers (NGCWs) who were born in the 1980s and later have gradually become the main workforce of Chinese construction industry. They may behave differently when dealing with knowledge-related activities due to divergent characteristics caused by generational discrepancy. To provide a theoretical foundation for construction companies and safety managers to improve safety management, this research explores the factors and paths impacting the NGCWs' ability to share their safety knowledge.
Design/methodology/approach
Based on literature review, main factors that influence the safety knowledge sharing of the NGCWs were identified. Decision-Making Trial and Evaluation Laboratory and Interpretive Structural Modeling were applied to identify the hierarchical and contextual relations among the factors influencing the safety knowledge sharing of the NGCWs.
Findings
The results showed that sharing atmosphere ranked first in centrality and had a high degree of influence and being influenced, indicating itself an extremely important influencing factor of safety knowledge sharing of NGCWs. Six root influencing factors were identified, including individual characteristics, work pressure, sharing platform, incentive mechanism, leadership support and safety management system.
Research limitations/implications
The number of influencing factors of safety knowledge sharing of the NGCWs identified in this study is limited, and the data obtained by the expert scoring method is subjective. In future studies, the model should be further developed and validated by incorporating experts from different fields to improve its integrity and applicability.
Practical implications
The influencing factors identified in this paper can provide a basis for construction companies and safety managers to improve productivity and safety management by taking relevant measures to promote safety knowledge sharing. The research contributes to the understanding knowledge management in the context of the emerging market. It helps to answer the question of how the market can maintain the economic growth success through effective knowledge management.
Originality/value
This paper investigates the influencing factors of NGCWs' safety knowledge sharing from the perspective of intergenerational differences, and the 13 influencing factor index system established expands the scope of research on factors influencing safety knowledge sharing among construction workers and fills the gap in safety knowledge sharing research on young construction workers. Furthermore, this paper establishes a multi-layer recursive structure model to clarify the influence path of the influencing factors and contributes to the understanding of safety knowledge sharing mechanism.
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Jianping Zhang, Leilei Wang and Guodong Wang
With the rapid advancement in the automotive industry, the friction coefficient (FC), wear rate (WR) and weight loss (WL) have emerged as crucial parameters to measure the…
Abstract
Purpose
With the rapid advancement in the automotive industry, the friction coefficient (FC), wear rate (WR) and weight loss (WL) have emerged as crucial parameters to measure the performance of automotive braking systems, so the FC, WR and WL of friction material are predicted and analyzed in this work, with an aim of achieving accurate prediction of friction material properties.
Design/methodology/approach
Genetic algorithm support vector machine (GA-SVM) model is obtained by applying GA to optimize the SVM in this work, thus establishing a prediction model for friction material properties and achieving the predictive and comparative analysis of friction material properties. The process parameters are analyzed by using response surface methodology (RSM) and GA-RSM to determine them for optimal friction performance.
Findings
The results indicate that the GA-SVM prediction model has the smallest error for FC, WR and WL, showing that it owns excellent prediction accuracy. The predicted values obtained by response surface analysis are closed to those of GA-SVM model, providing further evidence of the validity and the rationality of the established prediction model.
Originality/value
The relevant results can serve as a valuable theoretical foundation for the preparation of friction material in engineering practice.
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Linhua Sang, Dongchun Xia, Guodong Ni, Qingbin Cui, Jianping Wang and Wenshun Wang
The purpose of this paper is to explore the influence mechanism of job satisfaction and positive affect on knowledge sharing among project members in Chinese construction…
Abstract
Purpose
The purpose of this paper is to explore the influence mechanism of job satisfaction and positive affect on knowledge sharing among project members in Chinese construction industry, and test the moderating role of organizational commitment between them in order to find a new approach from the perspective of psychology to improve the knowledge sharing performance within project management organizations in China constantly.
Design/methodology/approach
An empirical study was used based on confirmatory factor analysis and hierarchical regression analysis with a sample of 540 project members from 80 project management organizations in China.
Findings
Research results showed that job satisfaction and positive affect of project members both have a significant positive impact on knowledge sharing; organizational commitment could moderate the influence of job satisfaction and positive affect on knowledge sharing among project members partially within the Chinese context.
Research limitations/implications
A questionnaire study from China only represents the relationship and regular pattern within a shorter time interval in the Chinese context. It is necessary to continue to implement a longitudinal study in a relatively long period in future research.
Practical implications
Knowledge sharing among project members can be enhanced through improving job satisfaction and positive affect, and strengthening project members’ organizational commitment can amplify the influence effect of job satisfaction and positive affect on knowledge sharing.
Originality/value
This paper clarifies the direct influence mechanism of project members’ job satisfaction and positive affect on explicit knowledge sharing (EKS) and tacit knowledge sharing (TKS), and further tests the partial moderating effect of organizational commitment on the influence relationship of job satisfaction and positive affect on EKS and TKS.
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Guodong Liang and Motoko Akiba
– The purpose of this paper is to examine the characteristics of teacher incentive pay programs used by midsize to large school districts in Missouri.
Abstract
Purpose
The purpose of this paper is to examine the characteristics of teacher incentive pay programs used by midsize to large school districts in Missouri.
Design/methodology/approach
This study primarily used the Teacher Compensation Programs (TCP) survey data. The TCP survey was developed by the authors to understand the nature and characteristics of financial incentives that Missouri districts used to recruit, reward, and retain quality teachers.
Findings
The data showed that, during the 2009-2010 academic year, 32 percent of the districts offered at least one financial incentive to recruit or retain teachers. Districts were more likely to reward teachers for obtaining National Board certification and for assuming extra duties than for teaching in the subject areas of shortage or in hard-to-staff schools. Larger districts with higher teacher salary were more likely than small districts to offer a larger number of incentive pay programs.
Originality/value
The findings of this study advance our knowledge of local incentive pay policies. It also contributes to the global discourse of teacher compensation and incentives and can be informative to policymakers in the USA and around the world when designing and implementing incentive pay programs to teachers. Further, it sheds light on the important policy question of whether disadvantaged local educational agencies are more likely to use incentive pay programs to recruit and retain teachers and promote an equitable distribution of the teacher workforce. This informs the decision making of providing targeted support to those in need.
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Damian Tago, Henrik Andersson and Nicolas Treich
This study contributes to the understanding of the health effects of pesticides exposure and of how pesticides have been and should be regulated.
Abstract
Purpose
This study contributes to the understanding of the health effects of pesticides exposure and of how pesticides have been and should be regulated.
Design/methodology/approach
This study presents literature reviews for the period 2000–2013 on (i) the health effects of pesticides and on (ii) preference valuation of health risks related to pesticides, as well as a discussion of the role of benefit-cost analysis applied to pesticide regulatory measures.
Findings
This study indicates that the health literature has focused on individuals with direct exposure to pesticides, i.e. farmers, while the literature on preference valuation has focused on those with indirect exposure, i.e. consumers. The discussion highlights the need to clarify the rationale for regulating pesticides, the role of risk perceptions in benefit-cost analysis, and the importance of inter-disciplinary research in this area.
Originality/value
This study relates findings of different disciplines (health, economics, public policy) regarding pesticides, and identifies gaps for future research.
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Yongliang Deng, Zedong Liu, Liangliang Song, Guodong Ni and Na Xu
The purpose of this study is to identify the causative factors of metro construction safety accidents, analyze the correlation between accidents and causative factors and assist…
Abstract
Purpose
The purpose of this study is to identify the causative factors of metro construction safety accidents, analyze the correlation between accidents and causative factors and assist in developing safety management strategies for improving safety performance in the context of the Chinese construction industry.
Design/methodology/approach
To achieve these objectives, 13 types and 48 causations were determined based on 274 construction safety accidents in China. Then, 204 cause-and-effect relationships among accidents and causations were identified based on data mining. Next, network theory was employed to develop and analyze the metro construction accident causation network (MCACN).
Findings
The topological characteristics of MCACN were obtained, it is both a small-world network and a scale-free network. Controlling critical causative factors can effectively control the occurrence of metro construction accidents. Degree centrality strategy is better than closeness centrality strategy and betweenness centrality strategy.
Research limitations/implications
In practice, it is very difficult to quantitatively identify and determine the importance of different accidents and causative factors. The weights of nodes and edges are failed to be assigned when constructing MCACN.
Practical implications
This study provides a theoretical basis and feasible management reference for construction enterprises in China to control construction risks and reduce safety accidents. More safety resources should be allocated to control critical risks. It is recommended that safety managers implement degree centrality strategy when making safety-related decisions.
Originality/value
This paper establishes the MCACN model based on data mining and network theory, identifies the properties and clarifies the mechanism of metro construction accidents and causations.
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YuBo Sun, Juliang Xiao, Haitao Liu, Tian Huang and Guodong Wang
The purpose of this paper is to accurately obtain the deformation of a hybrid robot and rapidly enable real-time compensation in friction stir welding (FSW). In this paper, a…
Abstract
Purpose
The purpose of this paper is to accurately obtain the deformation of a hybrid robot and rapidly enable real-time compensation in friction stir welding (FSW). In this paper, a prediction algorithm based on the back-propagation neural network (BPNN) optimized by the adaptive genetic algorithm (GA) is presented.
Design/methodology/approach
Via the algorithm, the deformations of a five-degree-of-freedom (5-DOF) hybrid robot TriMule800 at a limited number of positions are taken as the training set. The current position of the robot and the axial force it is subjected to are used as the input; the deformation of the robot is taken as the output to construct a BPNN; and an adaptive GA is adopted to optimize the weights and thresholds of the BPNN.
Findings
This algorithm can quickly predict the deformation of a robot at any point in the workspace. In this study, a force-deformation experiment bench is built, and the experiment proves that the correspondence between the simulated and actual deformations is as high as 98%; therefore, the simulation data can be used as the actual deformation. Finally, 40 sets of data are taken as examples for the prediction, the errors of predicted and simulated deformations are calculated and the accuracy of the prediction algorithm is verified.
Practical implications
The entire algorithm is verified by the laboratory-developed 5-DOF hybrid robot, and it can be applied to other hybrid robots as well.
Originality/value
Robots have been widely used in FSW. Traditional series robots cannot bear the large axial force during welding, and the deformation of the robot will affect the machining quality. In some research studies, hybrid robots have been used in FSW. However, the deformation of a hybrid robot in thick-plate welding applications cannot be ignored. Presently, there is no research on the deformation of hybrid robots in FSW, let alone the analysis and prediction of their deformation. This research provides a feasible methodology for analysing the deformation and compensation of hybrid robots in FSW. This makes it possible to calculate the deformation of the hybrid robot in FSW without external sensors.