An eco-friendly environment with green strategies can help to achieve better environmental performance. However, literature on the relationship between green human resource management practices (GHRMP) and sustainable environmental efficiency (SEF) is limited. Moreover, there is limited knowledge about the factors that could mediate the relationship between GHRMP and SEF. Therefore, the present study examines the impact of green human resource management practices mediating through green psychological climate (GPC) and green organizational culture (GOC) for better environmental efficacy. For this purpose, the primary data on variables are collected by using structured assessment tools and analyzed through regression models. Unlike previous studies, this study adopts a mediation model and unfolds not only the role of green human resource practices in psychological climate and green organizational culture but also clarifies the mediating role of GPC and GOC in sustainable environmental efficiency. The findings unfolded that ecological factors such as green psychological climate, green organizational culture, and sustainable environmental efficiency are positively affected by green human resources management. In addition, green organizational culture and green psychological climate positively mediate the relationship between GHRMP and SEF. This study recommends adopting green human resource management strategies and increasing technical innovations to improve sustainability and economic performance.
For asphalt pavement performance evaluation, pavement roughness, which is subject to cracks, potholes, road repairs and so on, is a major factor to influence riding quality. Therefore, riding quality is partly correlated with pavement distress, and the relationship can be transformed to that between pavement roughness and distress rate. However, this relationship is not clear, and not reflected in existing evaluation models. Thus, correlation analysis and non-parametric test of independent samples were applied in this paper to find that, international roughness index and pavement distress rate are significantly different due to different grades of roads, then, linear and nonlinear regression were used to analyze the relationships between international roughness index and pavement distress rate for different road grades. Furthermore, original data were processed by logarithmic transformation, radical transformation, exponential transformation and so on, based on which, corresponding relationships were analyzed by linear and nonlinear regression. Finally, best models to describe relationships between international roughness index and pavement distress rate for different road grades were solved out, and corresponding 90% confidence intervals were computed. Research in this paper offers a reference for improving asphalt pavement performance evaluation system and models, which is conducive to further theoretical research and practice.
This paper analyzed the statistical relationships among lane-changing, speed and density of traffic flow in different lanes of urban expressway weaving area under a given traffic condition and LOS two. A series of models was recommended. And then, the effectiveness between the recommended model and the existing model was compared. Although the optimization effect not very clear, but it shows that the lane-changing factors have some effects .
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