Search results

This study aims to extend ambidexterity theory from the perspective of organisational learning and examine how process ambidexterity, which comprises operational flexibility and operational routine, responds to environmental uncertainty and ultimately reduces organisational risks.

This study tests the hypotheses by analysing 464 annual reports of 115 listed companies in the Chinese agricultural and food industry using content and secondary data analyses. Four case studies are also provided.

The results show that (1) environmental uncertainty has a positive effect on either operational flexibility or operational routine; (2) both operational flexibility and operational routine have negative effects on organisational risks, supporting the view that process ambidexterity mediates the relationship between environmental uncertainty and organisational risks; and (3) organisational slack plays the role of “double-edged sword” by negatively moderating the effect of environmental uncertainty on operational flexibility and positively moderating the effect of environmental uncertainty on operational routine.

In an uncertain environment, companies are exposed to greater risk. This study contributes to risk management in three ways: first, it extends ambidexterity theory to process management and proposes how process ambidexterity balances operational flexibility and routines. Second, it distinguishes between the different conditions under which flexibility or routines are superior. Third, it explains the mechanisms related to how organisations can resolve environmental uncertainty into risk through process ambidexterity.

Computer vision and deep learning (DL) methods have been investigated for personal protective equipment (PPE) monitoring and detection for construction workers’ safety. However, it is still challenging to implement automated safety monitoring methods in near real time or in a time-efficient manner in real construction practices. Therefore, this study developed a novel solution to enhance the time efficiency to achieve near-real-time safety glove detection and meanwhile preserve data privacy.

The developed method comprises two primary components: (1) transfer learning methods to detect safety gloves and (2) edge computing to improve time efficiency and data privacy. To compare the developed edge computing-based method with the currently widely used cloud computing-based methods, a comprehensive comparative analysis was conducted from both the implementation and theory perspectives, providing insights into the developed approach’s performance.

Three DL models achieved mean average precision (mAP) scores ranging from 74.92% to 84.31% for safety glove detection. The other two methods by combining object detection and classification achieved mAP as 89.91% for hand detection and 100% for glove classification. From both implementation and theory perspectives, the edge computing-based method detected gloves faster than the cloud computing-based method. The edge computing-based method achieved a detection latency of 36%–68% shorter than the cloud computing-based method in the implementation perspective. The findings highlight edge computing’s potential for near-real-time detection with improved data privacy.

This study implemented and evaluated DL-based safety monitoring methods on different computing infrastructures to investigate their time efficiency. This study contributes to existing knowledge by demonstrating how edge computing can be used with DL models (without sacrificing their performance) to improve PPE-glove monitoring in a time-efficient manner as well as maintain data privacy.

This study aims to examine the impact of board characteristics on firm performance while also exploring the influential mechanisms that help Chinese listed companies establish effective boards of directors and strengthen their corporate governance mechanisms.

This paper uses machine learning methods to investigate the predictive ability of the board of directors' characteristics on firm performance based on the data from Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges in China during 2008–2021. This study further analyzes board characteristics with relatively strong predictive ability and their predictive models on firm performance.

The results show that nonlinear machine learning methods are more effective than traditional linear models in analyzing the impact of board characteristics on Chinese firm performance. Among the series characteristics of the board of directors, the contribution ratio in prediction from directors compensation, director shareholding ratio, the average age of directors and directors' educational level are significant, and these characteristics have a roughly nonlinear correlation to the prediction of firm performance; the improvement of the predictive ability of board characteristics on firm performance in state-owned enterprises in China performs better than that in private enterprises.

The findings of this study provide valuable suggestions for enriching the theory of board governance, strengthening board construction and optimizing the effectiveness of board governance. Furthermore, these impacts can serve as a valuable reference for board construction and selection, aiding in the rational selection of boards to establish an efficient and high-performing board of directors.

The study findings unequivocally demonstrate the superiority of nonlinear machine learning approaches over traditional linear models in examining the relationship between board characteristics and firm performance in China. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. The study reveals that the predictive performance of board attributes is generally more robust for state-owned enterprises in China in comparison to their counterparts in the private sector.

This study aims to process multi-agent system with kinds of limitations and constraints, and consider the robot in-hand manipulation as a problem of coordination and cooperation of multi-fingered hand.

A cooperative distributed model predictive control (MPC) algorithm is proposed to perform robot in-hand manipulation.

A cooperative distributed MPC approach is formulated for robot in-hand manipulation problem, which enables address complex limitation and constraint conditions in object motion planning, and realizes tracking trajectory of the object more than tracking position of the object.

This method to implement the moving object task uses the kinematic parameters without the knowledge of dynamic properties of the object. The cooperative distributed MPC scheme is designed to guarantee the movement of the object to a desired position and trajectory at algorithmic level.

The purpose of this paper is to quantitatively investigate the effect of process parameters (including welding current, voltage and speed) and plate thickness on in-plane inherent deformations in typical fillet welded joint; meanwhile, the plastic strains remaining in the weld zone are also analyzed under different influencing factors.

To achieve the purpose of this study, a thermal-elastic-plastic finite element (TEP FE) model is developed to analyze the thermal-mechanical behavior of the T-welded joint during the welding process. Experimental measurements have verified the validity of the established TEP FE model. Using the effective model, a series of numerical experiments are performed to obtain the inherent deformations under the conditions of different influencing factors, and then the calculation results are discussed based on the relevant data obtained.

Through numerical simulation analysis, it is found that the longitudinal and transverse inherent deformations decrease with the increase of welding speed and plate thickness, whereas as the nominal heat input increases, the inherent deformations increase significantly. The longitudinal shrinkage presents a quasi-linear and nonlinear distribution in the middle and end of the weld, respectively. The plastic strains in the cross section of the T-joint also vary greatly because of the process parameters and plate thickness, but the maximum value always appears near the location of the welding toe, which means that this point faces a relatively large risk of fatigue cracking. The inherent deformations are closely related to the plastic strains remaining in the weld zone and are also affected by many influencing factors such as process parameters and plate thickness.

In this study, relatively few influencing factors such as welding current, voltage, speed and plate thickness are considered to analyze the inherent deformations in the T-welded joint. Also, these influencing factors are all within a certain range of parameters, which shows that only limited applicability can be provided. In addition, only in-plane inherent deformations are considered in this study, without considering the other two out-of-plane components of inherent deformations.

This study can help to expand the understanding of the relationship between the inherent deformations and its influencing factors for a specific form of the welded joint, and can also provide basic data to supplement the inherent deformation database, thereby facilitating further researches on welding deformations for stiffened-panel structures in shipbuilding or steel bridges.

This paper aims to improve the scene sense of a virtual scene, the welding model of a virtual reality system of riser automatic equipment was constructed using Unity3D and UG software, which mainly included a welding car, welding guide rail, welding power supply, virtual camera and other equipment and the model was rendered.

The human-computer interaction page and simulation test of the system was produced using the user interface GUI system for creating a human-computer interaction scene. The operator could capture the welding status of the physical equipment accurately and in real-time so the virtual reality technology was very suitable for the remote monitoring operation integrated with the welding system.

Human-computer interaction design and collision detection were realized. In addition, the system simulation experiment was accomplished. With the continuous improvement and development of virtual reality technology real-time virtual simulation and monitoring, technology will become the main development trend.

Based on virtual reality, the monitoring system can capture the operation status of physical welding equipment in real-time and accurately, which is very suitable for remote monitoring operation integrated with the welding system and also conducive to improving the monitoring level of the welding process.

This technology is time-saving and money-saving, for the operators do not have to be in a real welding environment and therefore they can get away from dangerous places. Consequently, it can avoid unnecessary injuries and problems.

This technology can replace people to enter the dangerous and extreme environment to carry out welding operation, so it becomes the most effective means of nuclear power plant maintenance, space structure construction and marine engineering construction. In addition, it is time-saving and money-saving.

With the rapid development of virtual reality technology in recent years, it is a new research direction to apply virtual reality technology to the remote welding operation. This technology is different from the traditional way of welding for the operators can stay away from the welding scene especially some dangerous places.

This paper aims to explore the mechanism of influence on the subordinate's sense of gain at work (SGW) in terms of the coaching leadership behavior (CL), supervisor-subordinate guanxi (SSG) and commitment-based practice of human resource management (CHRM).

Based on the survey of 584 employees from 50 firms operating in China, this study explores the effect of CL on employees’ SGW, which concerns two dimensions: sense of material gain and sense of spiritual gain.

Results show that the CL has a significant positive influence on both the subordinate’s sense of material gain and his/her sense of spiritual gain, in which there exists a mediating effect of SSG and moderating effects of CHRM for the influence.

This study not only develops the theory of SGW, but also provides a scientific basis and policy suggestions for employers to implement in order to enhance their employees’ SGW.

Few integrative studies have examined the impact of CL on employees’ SGW. Based on the Need-to-Belong Theory, this study adds new empirical evidence and constructs a theoretical model for the mechanism of influence on the SGW, examines the influence of CL on the subordinate’s SGW and finds a mechanism of transmission (SSG) and a boundary condition (CHRM) for the influence.

This paper aims to propose a diverless weld bead maintenance welding technology to prevent the leakage of subsea oil and gas pipeline and solve the key problems in the maintenance of subsea pipeline.

Based on the analysis of the cross-section of the fillet weld, the multi-layer and multi-pass welding path planning of the submarine pipeline sleeve fillet weld is studied, and thus a multi-layer and multi-pass welding path planning strategy is proposed. A welding seam filling method is designed, and the end position of the welding gun is planned, which provides a theoretical basis for the motion control of the maintenance system.

The trajectory planning and adjustment of multi-layer and multi-pass fillet welding and the motion stability control of the rotating mechanism are realized.

It provides the basis for the prototype design of the submarine pipeline maintenance and welding robot system, and also lays the foundation for the in-depth research on the intelligent maintenance system of submarine pipeline.

The maintenance of diverless subsea pipeline is a new type of maintenance method, which can solve the problem of large amount of subsea maintenance work with high efficiency.

As demographic changes impact the workplace, governments, organizations, and workers are looking for ways to sustain optimal working lives at higher ages. Workplace flexibility has been introduced as a potential way workers can have more satisfying working lives until their retirement ages. This chapter presents a critical review of the literature on workplace flexibility across the lifespan. It discusses how flexibility has been conceptualized across different disciplines, and postulates a definition that captures the joint roles of employer and employee in negotiating workplace flexibility that contributes to both employee and organization benefits. Moreover, it reviews how flexibility has been theorized and investigated in relation to older workers. The chapter ends with a future research agenda for advancing understanding of how workplace flexibility may enhance working experiences of older workers, and in particular focuses on the critical investigation of uses of flexibility in relation to older workers.

This paper aims to gain a clear understanding of the ventilated cavity evolution around an NACA0015 hydrofoil by using both experimental and numerical investigation.

The bubble evolution around an NACA0015 hydrofoil with or without air injection was observed in a water tunnel, and the simulation was conducted using a modified turbulence model and homogeneous cavitation model.

The present simulation method can successfully predict the bubble evolutions around the NACA0015 hydrofoil with or without air injection. Air injection can alleviate the nature cavitation oscillation, and the suppression effect on nature cavitation depends on the air-entrant coefficient. It is confirmed that the air and vapor cavity have the same shedding frequency. It is seen that the air sheet closely attaches to the hydrofoil surface and is surrounded by the vapor sheet. Thus, the injected air promotes vapor growth and results in an increase in the cavity shedding frequency. Further, with a large air-entrant coefficient, the pressure fluctuation is suppressed completely.

The new simulation method is adopted to explore the mechanism of ventilated cavitation. The bubble evolutions with and without air injection have been comprehensively studied by experimental and numerical investigation. The effects of air injection on natural cavity oscillations and pressure fluctuations have been revealed in the present study.