Energy and performance impact of aggressive volunteer computing with multi-core computers

Author(s):  
Jiangtian Li ◽  
A. Deshpande ◽  
J. Srinivasan ◽  
Xiaosong Ma
Author(s):  
Fred Luthans ◽  
Carolyn M. Youssef

Over the years, both management practitioners and academics have generally assumed that positive workplaces lead to desired outcomes. Unlike psychology, considerable attention has also been devoted to the study of positive topics such as job satisfaction and organizational commitment. However, to place a scientifically based focus on the role that positivity may play in the development and performance of human resources, and largely stimulated by the positive psychology initiative, positive organizational behavior (POB) and psychological capital (PsyCap) have recently been introduced into the management literature. This chapter first provides an overview of both the historical and contemporary positive approaches to the workplace. Then, more specific attention is given to the meaning and domain of POB and PsyCap. Our definition of POB includes positive psychological capacities or resources that can be validly measured, developed, and have performance impact. The constructs that have been determined so far to best meet these criteria are efficacy, hope, optimism, and resiliency. When combined, they have been demonstrated to form the core construct of what we term psychological capital (PsyCap). A measure of PsyCap is being validated and this chapter references the increasing number of studies indicating that PsyCap can be developed and have performance impact. The chapter concludes with important future research directions that can help better understand and build positive workplaces to meet current and looming challenges.


2008 ◽  
Vol 29 (10) ◽  
pp. 1094-1097 ◽  
Author(s):  
G. Dewey ◽  
M.K. Hudait ◽  
Kangho Lee ◽  
R. Pillarisetty ◽  
W. Rachmady ◽  
...  

Author(s):  
Michael P. Leimbach

The importance of learning transfer in ensuring that learning contributes to an organization's competitive advantage has been undermined in organizational practice. There are two major reasons for this: 1) few studies directly explore the relationship between transfer and performance improvement, and 2) most existing transfer models are too complex for practitioners to implement. The purpose of this chapter is to explore the link between learning transfer activities and performance outcomes, and to create a framework for implementing an effective learning transfer solution. A targeted literature review meta-analysis was used to explore the performance impact of training vs. training plus transfer activities. The authors compute “difference scores” representing the percentage of improvement from the transfer activities over training alone. Activities are categorized into a framework of eleven critical learning transfer actions. They then implement the elements of the Learning Transfer Framework in three demonstration projects. By incorporating findings from the literature review, meta-analysis, and the demonstration projects, the authors propose a new transfer framework that is effective and easy to implement. Implications and directions for future researchers are advanced.


2017 ◽  
Vol 34 (3) ◽  
pp. 210-241 ◽  
Author(s):  
Osama Isaac ◽  
Zaini Abdullah ◽  
T. Ramayah ◽  
Ahmed M. Mutahar

Purpose The internet technology becomes an essential tool for individuals, organizations, and nations for growth and prosperity. The purpose of this paper is to integrate the DeLone and McLean IS success model with task-technology fit (TTF) to explain the performance impact of Yemeni Government employees. Design/methodology/approach Questionnaire survey method was used to collect primary data from 530 internet users among employees within all 30 government ministries-institutions in Yemen. The four constructs in the proposed model were measured using existing scales. The data analysis starts with initial exploratory factor analysis, then confirmatory factor analysis and lastly structural equation modeling via AMOS. Findings The results showed that the proposed integrated model fits the data well. Findings of the multivariate analysis demonstrate four main results. First, actual usage has a strong positive impact on user satisfaction, TTF, and performance impact. Second, user satisfaction has a great influence on performance impact. Third, TTF has a strong positive impact on user satisfaction and performance impact. Fourth, both user satisfaction and TTF mediate the relationship between the actual usage and performance impact. Research limitations/implications The public sector in Yemen contains three parts: Yemeni prime minister, Yemeni ministries, and government agencies. This study focuses only on the Yemeni employees among Yemeni ministries; hence the results are not necessarily generalizable. Moreover, there are biases when the researcher measures the actual Internet usage variable through asking a participant about their opinion regarding their usage because these are generally found to differ from the true score of system usage. Practical implications The findings should be very useful for the Yemeni Government in presenting the importance of information technology effects on individual efficiency and effectiveness. Therefore, the information from these findings should encourage and support the formation of future policy at the organizational level and national level. If the government utilizes these findings by setting up strategies to promote internet usage, this may, in turn, improve professional practice, personal development, and quality of working life. Originality/value This paper adds to the existing literature of information systems by combining actual technology usage, user satisfaction, and TTF to predict performance impact within the organizations. Furthermore, this study proposed a second-order model of performance impact in order to increase the power of explaining the output by the model, which contains four first-order constructs: process, knowledge acquisition, communication quality, and decision quality. The predictive power of the proposed model has a higher ability to explain and predict performance impact compared to those obtained from some of the previous studies.


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