Islam-based legal language and state governance: democracy,strength of the judiciary and human rights

Constitutional Political Economy - States embracing Islam-based laws are frequently seen as struggling with establishing democratic institutions, jeopardizing human rights and encouraging executive...     

Mood and Ethical Decision Making: Positive Affect and Corporate Philanthropy

Journal of Business Ethics - This study examines the influence of mood (‘affect’) on corporate philanthropic giving. Drawing on group emotions theory and affect-infused decision theory,...     

Analysis of the status and trends of applications of advanced manufacturing technologies in Russia

The article has analyzed trends in applying advanced manufacturing technologies in Russia in 2005–2014. The dynamics of technical process structures in the context of applications has been considered. The dynamics of the age structure and the structure of technologies in use in annual terms by the place of acquiring has been assessed. The start-up, availability, and removal balance of technologies has been formed, the effective start-up level, and possible ways to improve the state statistical indicators of innovation development have been determined.     

Training professionals' usage and understanding of Kirkpatrick's Level 3 and Level 4 evaluations

Training professionals have long acknowledged the necessity of conducting behavior‐based (Level 3) and results‐based (Level 4) evaluations, yet organizations do not frequently conduct such evaluations. This research examined training professionals' perceptions of the utility of Level 3 and Level 4 evaluations and the factors that facilitate or obstruct their attempts to perform them. The research was conducted using Brinkerhoff's Success Case Method and Gilbert's Behavior Engineering Model as its frameworks. The three key factors identified by study participants as having an impact upon their ability to conduct Level 3 and Level 4 evaluations were the availability of resources such as time and personnel, managerial support (organizational) and expertise in evaluative methodology (individual). The research findings indicated a need to further explore how training professionals interpret Level 3 and Level 4 and how they can better develop their evaluative expertise, which in turn may increase effectiveness in gaining organizational support for evaluation efforts.     

Workload control under continuous order release

Workload control is a production planning and control concept specifically designed for complex manufacturing environments. Past research on Workload control has been essentially focused on discrete order release. This means that release of orders to the shop floor takes places on a periodic basis. Continuous order release has been somehow neglected, in spite of its apparent potential for improving system performance, including the reduction of order flow times. This paper presents a simulation study of this order release approach. The study contributes for improving the basis for setting workload norms, selecting the workload control strategy and deciding upon routing alternatives under continuous order release.     

Nanotechnology and the new technological revolution: Expectations and reality

This paper reviews the existing mechanisms of innovative development in the world economy focusing on emerging technologies markets evolution on the example of nanotechnology. The question has been raised of whether nanotechnologies can provide the core of the new technological revolution, and whether these prospects exist for NBIC convergence. In this connection the development of the global market for nano-enabled products following the 2007–2009 crisis and the reliability of the related development forecasts have been assessed. Particular attention has been paid to peculiarities of nanoenabled product market structure and the impact of stagnating R&D costs in the field of nanotechnology.     

Assessment of the impact of human capital on economic growth

This paper presents updated figures on the dynamics of human capital in the Russian economy. Time series of human capital are obtained for major types of economic activity that cover up to 85–90% of the total human capital in the Russian economy for 1992–2012. An analysis of the impact of accumulated human capital on economic dynamics is performed by means of the production function model. An original approach to assessing the production function based on the method of principal components is introduced.     

Trading off learning and performance: Exploration and exploitation at work

Employees are increasingly given control over how they learn, and their choices for training are diverse and varied, yet employees must balance competing demands. On one hand, they are expected to be increasingly efficient in their current job duties – on the other hand, they are expected to develop new skills and competencies that enable them to adapt and respond to changing job demands. Drawing from the organizational learning literature, we propose a model of worker and work characteristics that inform choices between two mindsets related to learning at work. The first mindset is exploration, or the pursuit of learning outside one’s current knowledge domain; the second mindset is exploitation, the refinement/deepening of one’s existing knowledge stock focusing on the task at hand. We further propose that these strategic choices, or trade-offs, influence employee learning and performance in unique ways, with different implications for both routine and adaptive performance. Finally, we incorporate the notions of feedback loops and risk assessments that influence ongoing decisions between exploration and exploitation mindsets. Recommendations for future research and extensions of the theoretical model are also proposed.     

Reluctant Generalised Additive Modelling

Sparse generalised additive models (GAMs) are an extension of sparse generalised linear models that allow a model's prediction to vary non-linearly with an input variable. This enables the data analyst build more accurate models, especially when the linearity assumption is known to be a poor approximation of reality. Motivated by reluctant interaction modelling, we propose a multi-stage algorithm, called reluctant generalised additive modelling (RGAM), that can fit sparse GAMs at scale. It is guided by the principle that, if all else is equal, one should prefer a linear feature over a non-linear feature. Unlike existing methods for sparse GAMs, RGAM can be extended easily to binary, count and survival data. We demonstrate the method's effectiveness on real and simulated examples.