Job characteristics and staying engaged in work of nurses: Empirical evidence from Malaysia

Objective: The purpose of this study is to examine the relationship between job characteristics (job autonomy,job feedback,skill variety,task identity,task significance) and work engagement of nurses in Malaysia.Methods: A survey using self-administered questionnaires was used to collect data from a sample of 856 staff nurses working in eight public hospitals in Malaysia.A shortened nine-item version of the Utrecht Work Engagement Scale(UWES-9) was used to measure work engagement.The UWES-9 comprises three dimensions,which was measured with three items each: vigor,dedication,and absorption.Job characteristics (job autonomy,job feedback,skill variety,task identity,task significance) were measured with the corresponding subscales of the Job Diagnostic Survey.Each subscale consisted of three items.Hypotheses were tested using hierarchical regression analysis.Results: Findings indicated that all the five demographic variables (age,marital status,education,organizational tenure,job tenure) were unrelated to work engagement.The results further revealed that job autonomy (β=0.19,P < 0.01),job feedback (β=0.10,P < 0.01),task identity (β=0.13,P < 0.01),and task significance (β=0.08,P< 0.05) were positively related to work engagement.Skill variety (β=0.03,P> 0.05),however,did not affect work engagement.Conclusion: Job autonomy,job feedback,task identity,and task significance are important factors in predicting work engagement.The findings of this study highlighted the need to incorporate these core dimensions in nursing management to foster work engagement.

Mediating effect of work engagement between job characteristics and nursing performance among general hospital nurses

Objective:This study aimed to determine the effects of job characteristics and work engagement on the nursing performance of nurses working in general hospitals.Methods:Data were collected from 169 nurses who are working in a general hospital in South Korea by using a cross-sectional descriptive survey design.Results:Nurses’job characteristics and work engagement showed positive effects on nursing performance.This effect was magnified when work engagement was used as a mediating variable.Conclusions:The findings elucidate the factors influencing job performance and provide managers with important information for developing programs to improve the job skills and work engagement of nurses.

Prediction of job characteristics for intelligent resource allocation in HPC systems:a survey and future directions

Nowadays,high-performance computing(HPC)clusters are increasingly popular.Large volumes of job logs recording many years of operation traces have been accumulated.In the same time,the HPC cloud makes it possible to access HPC services remotely.For executing applications,both HPC end-users and cloud users need to request specific resources for different workloads by themselves.As users are usually not familiar with the hardware details and software layers,as well as the performance behavior of the underlying HPC systems.It is hard for them to select optimal resource configurations in terms of performance,cost,and energy efficiency.Hence,how to provide on-demand services with intelligent resource allocation is a critical issue in the HPC community.Prediction of job characteristics plays a key role for intelligent resource allocation.This paper presents a survey of the existing work and future directions for prediction of job characteristics for intelligent resource allocation in HPC systems.We first review the existing techniques in obtaining performance and energy consumption data of jobs.Then we survey the techniques for single-objective oriented predictions on runtime,queue time,power and energy consumption,cost and optimal resource configuration for input jobs,as well as multi-objective oriented predictions.We conclude after discussing future trends,research challenges and possible solutions towards intelligent resource allocation in HPC systems.