Spillovers from foreign direct investment in Central and Eastern Europe:an index for measuring a country’s potential to benefit from technology spillovers

In the paper, we construct a composite indicator to estimate the potential of four Central and Eastern European countries (the Czech Republic, Hungary, Poland and Slovakia) to benefit from productivity spillovers from foreign direct investment (FDI) in the manufacturing sector. Such transfers of technology are one of the main benefits of FDI for the host country, and should also be one of the main determinants of FDI incentives offered to investing multinationals by governments, but they are difficult to assess ex ante. For our composite index, we use six components to proxy the main channels and determinants of these spillovers. We have tried several weighting and aggregation methods, and we consider our results robust. According to the analysis of our results, between 2003 and 2007 all four countries were able to increase their potential to benefit from such spillovers, although there are large differences between them. The Czech Republic clearly has the most potential to benefit from productivity spillovers, while Poland has the least. The relative positions of Hungary and Slovakia depend to some extent on the exact weighting and aggregation method of the individual components of the index, but the differences are not large. These conclusions have important implications both the investment strategies of multinationals and government FDI policies.

A computational approach to measuring the correlation between expertise and social media influence for celebrities on microblogs

Existing approaches of social influence analysis usually focus on how to develop effective algorithms to quantize users' influence scores. They rarely consider a person's expertise levels which are arguably important to influence measures. In this paper, we propose a computational approach to measuring the correlation between expertise and social media influence, and we take a new perspective to understand social media influence by incorporating expertise into influence analysis. We carefully constructed a large dataset of 13,684 Chinese celebrities from Sina Weibo (literally 'Sina microblogging'). We found that there is a strong correlation between expertise levels and social media influence scores. In addition, different expertise levels showed influence variation patterns: high-expertise celebrities have stronger influence on the 'audience' in their expertise domains.

A computational approach to measuring the correlation between expertise and social media influence for celebrities on microblogs

Social media influence analysis, sometimes also called authority detection, aims to rank users based on their influence scores in social media. Existing approaches of social influence analysis usually focus on how to develop effective algorithms to quantize users’ influence scores. They rarely consider a person’s expertise levels which are arguably important to influence measures. In this paper, we propose a computational approach to measuring the correlation between expertise and social media influence, and we take a new perspective to understand social media influence by incorporating expertise into influence analysis. We carefully constructed a large dataset of 13,684 Chinese celebrities from Sina Weibo (literally ”Sina microblogging”). We found that there is a strong correlation between expertise levels and social media influence scores. Our analysis gave a good explanation of the phenomenon of “top across-domain influencers”. In addition, different expertise levels showed influence variation patterns: e.g., (1) high-expertise celebrities have stronger influence on the “audience” in their expertise domains; (2) expertise seems to be more important than relevance and participation for social media influence; (3) the audiences of top expertise celebrities are more likely to forward tweets on topics outside the expertise domains from high-expertise celebrities.

Measuring graph similarity through continuous-time quantum walks and the quantum Jensen-Shannon divergence

In this paper we propose a quantum algorithm to measure the similarity between a pair of unattributed graphs. We design an experiment where the two graphs are merged by establishing a complete set of connections between their nodes and the resulting structure is probed through the evolution of continuous-time quantum walks. In order to analyze the behavior of the walks without causing wave function collapse, we base our analysis on the recently introduced quantum Jensen-Shannon divergence. In particular, we show that the divergence between the evolution of two suitably initialized quantum walks over this structure is maximum when the original pair of graphs is isomorphic. We also prove that under special conditions the divergence is minimum when the sets of eigenvalues of the Hamiltonians associated with the two original graphs have an empty intersection.

A comparison of two distributed large-volume measurement systems:the mobile spatial co-ordinate measuring system and the indoor global positioning system

Advances in the area of industrial metrology have generated new technologies that are capable of measuring components with complex geometry and large dimensions. However, no standard or best-practice guides are available for the majority of such systems. Therefore, these new systems require appropriate testing and verification in order for the users to understand their full potential prior to their deployment in a real manufacturing environment. This is a crucial stage, especially when more than one system can be used for a specific measurement task. In this paper, two relatively new large-volume measurement systems, the mobile spatial co-ordinate measuring system (MScMS) and the indoor global positioning system (iGPS), are reviewed. These two systems utilize different technologies: the MScMS is based on ultrasound and radiofrequency signal transmission and the iGPS uses laser technology. Both systems have components with small dimensions that are distributed around the measuring area to form a network of sensors allowing rapid dimensional measurements to be performed in relation to large-size objects, with typical dimensions of several decametres. The portability, reconfigurability, and ease of installation make these systems attractive for many industries that manufacture large-scale products. In this paper, the major technical aspects of the two systems are briefly described and compared. Initial results of the tests performed to establish the repeatability and reproducibility of these systems are also presented. © IMechE 2009.

Conceptualizing leadership perceptions as attitudes:using attitude theory to further the understanding of the relation between leadership and outcomes

Leadership is one of the most examined factors in relation to understanding employee wellbeing and performance. While there are disparate approaches to studying leadership, they share a common assumption that perceptions of a leader's behavior determine reactions to the leader. The concept of leadership perception is poorly understood in most theoretical approaches. To address this, we propose that there are many benefits from examining leadership perceptions as an attitude towards the leader. In this review, we show how research examining a number of aspects of attitudes (content, structure and function) can advance understanding of leadership perceptions and how these affect work-related outcomes. Such a perspective provides a more multi-faceted understanding of leadership perceptions than previously envisaged and this can provide a more detailed understanding of how such perceptions affect outcomes. In addition, we examine some of the main theoretical and methodological implications of viewing leadership perceptions as attitudes to the wider leadership area. The cross-fertilization of research from the attitudes literature to understanding leadership perceptions provides new insights into leadership processes and potential avenues for further research. (C) 2015 Elsevier Inc. All rights reserved

Price-cap regulation in the English and Welsh water industry:a proposal for measuring productivity performance

Privately owned water utilities typically operate under a regulated monopoly regime. Price-cap regulation has been introduced as a means to enhance efficiency and innovation. The main objective of this paper is to propose a methodology for measuring productivity change across companies and over time when the sample size is limited. An empirical application is developed for the UK water and sewerage companies (WaSCs) for the period 1991-2008. A panel index approach is applied to decompose and derive unit-specific productivity growth as a function of the productivity growth achieved by benchmark firms, and the catch-up to the benchmark firm achieved by less productive firms. The results indicated that significant gains in productivity occurred after 2000, when the regulator set tighter reviews. However, the average WaSC still must improve towards the benchmarking firm by 2.69% over a period of five years to achieve comparable performance. This study is relevant to regulators who are interested in developing comparative performance measurement when the number of water companies that can be evaluated is limited. Moreover, setting an appropriate X factor is essential to improve the efficiency of water companies and this study helps to achieve this challenge.