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of KF KF was developed as a composite index incorporating multiple evaluation elements to maximize stability while minimizing possible biases of single parameter indices (Korea Research Foundation 2007 ). A single parameter index that uses

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address the study aim. First, we developed a new composite index to assess the whole range of CSBD symptoms. This index relied on three previously validated scales for the assessment of CSBD: the Hypersexual Behavior Inventory (HBI, Reid, Garos

Open access

Abstract  

In Open Access (OA) environment where article-based or author-based evaluation is important, a new evaluation system is needed to accommodate characteristics of Open Access Resources (OAR) and to overcome limitations of pre-existing evaluation systems such as journal-based evaluation. Primary and secondary evaluation factors were selected. Primary factors include hits and citations that constitutes composite index. Several secondary factors each for article and author evaluation were selected for normalization of the indexes. To validate superiority of newly developed normalized composite index systems compared to the monovariable index system, time-driven bias and power of discrimination were adopted. The results led to the conclusion that composite index proved to be a more stable index offsetting the negative effects from one element to another and normalization makes the composite index even more stable by controlling the bias from external elements.

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Summary  

Both quantitative and qualitative evaluation of publications of research teams or institutes requires several scientometric indicators. In this paper a new composite indicator is introduced for the assessment of publications of research institutes working in different fields of science. The composite indicator consists of three part-indicators (Journal Paper Productivity, Relative Publication Strategy and Relative Paper Citedness). The different methods of calculating the composite index have only a slight effect on the value, whereas application of diverse weights for the individual part-indicators results in significant changes.

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Spillovers from foreign direct investment in Central and Eastern Europe

An index for measuring a country’s potential to benefit from technology spillovers

Society and Economy
Authors: Balázs Szent-Iványi and Gábor Vigvári

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.

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://statswiki.unece.org/display/AAI/Active+Ageing+Index+Home, accessed 02/04/2018. Antony , G. – Visweswara Rao, K. ( 2007 ): A Composite Index to Explain Variations in Poverty, Health, Nutritional Status and Standard of Living: Use of Multivariate Statistical Methods . Public Health 121 ( 8 ): 578 – 587

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ESRI (2013): Guide for Using Diffusion Indexes and Composite Indexes . ESRI. Guide for Using Diffusion Indexes and Composite Indexes 2013

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. Lindsey , D 1978 Corrected quality ratio: A composite index of scientific contribution to knowledge . Social Studies of Science 8 : 349 – 354 10.1177/030631277800800307 . Ma , N

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. Although there are some papers that have proposed the use of a composite index, here we follow the approach pioneered by Han – Goetz (2015) because their indicator captures the two aforementioned dimensions of resilience jointly. 11 This indicator

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Research initiative (launched in 2010) 1 , which follows the earlier Research Quantum Composite Index (since 1995), New Zealand's Performance-Based Research Fund (2006), and in Italy, the first Triennial Research Evaluation (2006), soon to be followed by a

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