Human resource management and performance: A neural network analysis

2007 ◽  
Vol 181 (1) ◽  
pp. 453-467 ◽  
Author(s):  
Eleni T. Stavrou ◽  
Christakis Charalambous ◽  
Stelios Spiliotis
Keyword(s):  
Neural Network ◽  
Resource Management ◽  
Network Analysis ◽  
Human Resource Management ◽  
Human Resource ◽  
Neural Network Analysis ◽  
And Performance

scholarly journals The Influence of Management on Teacher Well-Being and the Development of Sustainable Schools

2021 ◽  
Vol 13 (5) ◽  
pp. 2909
Author(s):  
Esther Pagán-Castaño ◽  
Javier Sánchez-García ◽  
Fernando J. Garrigos-Simon ◽  
María Guijarro-García
Keyword(s):  
Resource Management ◽  
Human Resource Management ◽  
Human Resource ◽  
Negative Impact ◽  
Well Being ◽  
Structural Equations ◽  
Mediating Effect ◽  
Educational Performance ◽  
And Performance ◽  
The Relationship

Teaching is one of the professions with the highest levels of stress and disquiet at work, having a negative impact on teachers’ well-being and performance. Thus, well-being is one of the priorities in human resource management (HRM) in schools. In this regard, this paper studies the relationship between HRM, well-being and performance, observing the incidence of leadership and innovation in these relationships. The objective is to measure the extent to which it is necessary to encourage sustainable environments that promote the well-being of teachers and, by extension, students. The study used the methodology of structural equations and a sample of 315 secondary school teachers. The work validates the influence of leadership by example and information management on HRM and performance. In addition, we confirm the significant effect of human resource management on educational performance. The relationship is observed both directly and through the mediating effect on the improvement of well-being. On the other hand, the positive influence of innovation on performance, both in schools and in the classrooms, is reaffirmed. These results suggest the need to zero in on the human resources policies in schools linked to the improvement of teacher well-being and educational performance. They also highlight the role of school and classroom innovation as a key element in maintaining educational quality.

scholarly journals Policies and Practices of Green Human Resource Management

2019 ◽  
Vol 2 (2) ◽  
pp. 60
Author(s):  
Ira Gjika ◽  
Zana Koli
Keyword(s):  
Environmental Management ◽  
Resource Management ◽  
Human Resource Management ◽  
Human Resource ◽  
Management Practices ◽  
Environmental Management System ◽  
Green Management ◽  
Green Approach ◽  
And Performance ◽  
Green Human Resource Management

Social responsibility and environmental management have been for some years at the focus for a lot of companies, which do consider them as important part of their strategy. Human resource management is one of the functional strategies and part of top management in the organizations capable of playing a particular role in crafting and implementing policies that contribute to the environmental management and responsibility. This orientation, recently recognized as “Green HRM”, is broadly elaborated in the worldwide HRM literature and closely related to the environmental management system. The companies do implement practices of HRM by orienting them towards the engagement of employees in green management. Processes like recruitment, selection, training and performance compensation are perceived and “modeled” in the light of green management practices. This paper intends to present the green approach of HRM in the theoretical framework, based on the existing literature, and also to evidence how Albanian organizations are grasping it.  The objective is to bring out the good practices of leader companies in green HRM as a mean to draw the attention of as many other organizations as possible to highlight the importance of this approach in activities that are both profitable and socially responsible.

Application of Statistics in HR Research

2017 ◽  
pp. 74-107
Author(s):  
Dipak Kumar Bhattacharyya
Keyword(s):  
Resource Management ◽  
Human Resource Management ◽  
Performance Management ◽  
Human Resource ◽  
Resource Planning ◽  
Statistical Tools ◽  
Specific Research ◽  
Critical Areas ◽  
And Performance

Application of statistics in HR research has been briefly explained in our introductory chapter. It is now acknowledged, with statistics, we can ensure our HR research is more effective. Such research results can also help to take critical HR decisions at organization level. In this chapter, we have discussed on application of statistics in HR research in two critical areas, i.e., human resource planning (HRP) and performance management. Both in HRP and performance management, we can make extensive use of various mathematical, econometric, and statistical tools. Also, we have many established models. However, here our focus is restricted to only some of the simple statistical tools that can help in research in this two-critical human resource management areas. As the purpose of this chapter is to explain use of statistics in two major areas of HR research, it will cover only some selected areas of application. At the outset focus is on the specific research nitty-gritty, as these may help prospective researchers to get their basics clear, before they proceed for research in HRP and performance management areas.

scholarly journals Analysis and Simulation of the Early Warning Model for Human Resource Management Risk Based on the BP Neural Network

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Xue Yan ◽  
Xiangwu Deng ◽  
Shouheng Sun
Keyword(s):  
Neural Network ◽  
Resource Management ◽  
Human Resource Management ◽  
Human Resource ◽  
Early Warning ◽  
Bp Neural Network ◽  
Back Propagation ◽  
Bp Network ◽  
Early Warning Model ◽  
Warning Model

Human resource management risks are due to the failure of employer organization to use relevant human resources reasonably and can result in tangible or intangible waste of human resources and even risks; therefore, constructing a practical early warning model of human resource management risk is extremely important for early risk prediction. The back propagation (BP) neural network is an information analysis and processing system formed by using the error back propagation algorithm to simulate the neural function and structure of the human brain, which can handle complex and changeable things that do not have an obvious linear relationship between output results and input factors, so as to find the objective connection between the two. Based on the summary and analysis of previous research works, this article expounded the research status and significance of early warning for human resource management risks, elaborated the development background, current status, and future challenges of the BP neural network, introduced the method and principle of the BP neural network’s connection weight calculation and learning training, performed the risk inducement analysis, index system establishment, and network node selection of human resource management, constructed an early warning model of human resource management risk based on the BP neural network, conducted the risk warning model training and detection based on the BP neural network, and finally carried out a simulation and its result analysis. The study results show that the early warning model of human resource management risk based on the BP network is effective, and this trained and tested BP network risk warning model can be used to conduct early warning empirical research on human resource risks to prevent human resource risks, ensure enterprise’s benign operation, and at the same time play a role in supervision and promotion of market order rectification.

scholarly journals Additive Effects of Performance- and Commitment-Oriented Human Resource Management Systems on Organizational Outcomes

2019 ◽  
Vol 11 (6) ◽  
pp. 1679
Author(s):  
KonShik Kim ◽  
Tack-Hyun Shin
Keyword(s):  
Human Capital ◽  
Resource Management ◽  
Human Resource Management ◽  
Human Resource ◽  
Social Sustainability ◽  
Organizational Outcomes ◽  
Management Systems ◽  
Additive Effects ◽  
Hrm Practices ◽  
And Performance

Exploring the duality and balance research on human resource management (HRM), this study established two different HRM systems or bundles based on distinct guiding principles—the performance-oriented HRM system and the commitment-oriented HRM system. This study investigated whether the performance- and commitment-oriented HRM systems or bundles with different philosophical backgrounds have their own independent and additive effects on organizational outcomes. The relationships between these HRM systems and organizational outcomes were examined with 1735 firm-period samples in the longitudinal setting. The empirical results show that the commitment-oriented HRM systems have independent and additive effects on organizational commitment and human capital. However, the performance-oriented HRM systems have no independent and additive effect on organizational outcomes. Our study also indicates that increasing the performance-oriented HRM practices can be redundant and unnecessary unless firms have sufficiently high levels of the commitment-oriented HRM practices. Given that the definition and measures of commitment-oriented HRM bundles nearly match the characteristics of sustainable HRM, we thus argue that the commitment-oriented HRM systems have more potential to improve not only organizational outcomes and performance, but also human and social sustainability, than the performance-oriented HRM systems.

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