3,487 research outputs found

    The competitiveness of nations and implications for human development

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    This is the post-print version of the final paper published in Socio-Economic Planning Sciences. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.Human development should be the ultimate objective of human activity, its aim being healthier, longer, and fuller lives. Thus, if the competitiveness of a nation is properly managed, enhanced human welfare should be the key expected consequence. The research described here explores the relationship between the competitiveness of a nation and its implications for human development. For this purpose, 45 countries were evaluated initially using data envelopment analysis. In this stage, global competitiveness indicators were taken as input variables with human development index indicators as output variables. Subsequently, an artificial neural network analysis was conducted to identify those factors having the greatest impact on efficiency scores

    International competitiveness power and human development of countries

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    Human development should be the ultimate objective of human activity and its aim should be healthier, longer, and fuller lives. It is expected that if the competitiveness of a country is suitably managed, human welfare will be enhanced as a consequence. The research described here seeks to explore the relationship between the competitiveness of a country and its use for human development. For this purpose, 45 countries were evaluated using data envelopment analysis, where the global competitiveness indicators are taken as input variables and the human development index indicators as output variables. A detailed analysis is also conducted for the emerging economies

    Multi-level DEA Approach in Research Evaluation

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    It is well known that the discrimination power of DEA models will be diminishing if too many inputs or outputs are used. It is a dilemma if the decision makers want to select comprehensive indicators to present a relatively holistic evaluation using DEA. In this work we show that by utilizing hierarchical structures of input-output data DEA can handle quite large numbers of inputs and outputs. We present two approaches in a pilot evaluation of 15 institutes for basic research in Chinese Academy of Sciences using DEA models

    Efficiency analysis of Policies against desertification by applying DEA: a case study in the river Guadalentin catchment (Almeria, Spain)

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    This paper deals about an attempt to evaluate the different policies against desertification carried out during a twenty five year period (1978-2003) in the eight municipalities which compound the river Guadalentín catchment (Murcia, Spain). The approach is based on DEA and the European Environmental Agency indicator studies, the former to measure the efficiency and the second to select the best environmental indicators. The analysis has been reiterated with three different sets of outputs related to the different levels and aspects of the desertification process- from the merely soil losses to the overall desertification process in which population losses are considered. As a result a set of efficiency indexes has been obtained for each municipality, which show clearly the contribution of each action against desertification. These results are very valuable to establish future long term desertification policies in similar territories

    Insights and Challenges about the use of VNA on Airport/Hinterland Linkages

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    Airport operators, planners and regulatory agencies to measure the economic contribution of an airport to its local and regional surroundings, frequently use economic impact studies. The most common methods to measure airport economic impacts have been the Input-Output method, the Collection of Benefits method and most recently the Catalytic method. The most used measured variables include employment, wages, local and regional spending and air traffic levels. This paper is a new approach to these impact studies in which is used a new tool to identify the added values generated within airports and surrounding community interactions to better catch real socio-economic impacts. The VNA – Value Network Analysis, is used as an integrated methodology to identify these interactions and added values generated (tangibles and intangibles) in the business system of landside airports. To define the system it is used the matrix key airport performance benchmarking areas of ACI (Airport Council International) that are in the range of landside of the airport. Key words: Social Networks, Airport Landside, Value Network Analysis, Key Performance Indicators, Business System.

    Comparative Efficiency Assessment of Primary Care Models Using Data Envelopment Analysis

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    This paper compares the productive efficiencies of four models of primary care service delivery in Ontario, Canada, using the data envelopment analysis (DEA) method. Particular care is taken to include quality of service as part of our output measure. The influence of the delivery model on productive efficiency is disentangled from patient characteristics using regression analysis. Significant differences are found in the efficiency scores across models and within each model. In general, the fee-for-service arrangement ranks the highest and the community-health-centre model the lowest in efficiency scoring. The reliance of our input measures on costs and number of patients, clearly favours the fee-for-service model. Patient characteristics contribute little to explaining differences in the efficiency ranking across the models.Productive Efficiency; DEA; Primary Health Care

    Solving multiple-criteria R&D project selection problems with a data-driven evidential reasoning rule

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    In this paper, a likelihood based evidence acquisition approach is proposed to acquire evidence from experts'assessments as recorded in historical datasets. Then a data-driven evidential reasoning rule based model is introduced to R&D project selection process by combining multiple pieces of evidence with different weights and reliabilities. As a result, the total belief degrees and the overall performance can be generated for ranking and selecting projects. Finally, a case study on the R&D project selection for the National Science Foundation of China is conducted to show the effectiveness of the proposed model. The data-driven evidential reasoning rule based model for project evaluation and selection (1) utilizes experimental data to represent experts' assessments by using belief distributions over the set of final funding outcomes, and through this historic statistics it helps experts and applicants to understand the funding probability to a given assessment grade, (2) implies the mapping relationships between the evaluation grades and the final funding outcomes by using historical data, and (3) provides a way to make fair decisions by taking experts' reliabilities into account. In the data-driven evidential reasoning rule based model, experts play different roles in accordance with their reliabilities which are determined by their previous review track records, and the selection process is made interpretable and fairer. The newly proposed model reduces the time-consuming panel review work for both managers and experts, and significantly improves the efficiency and quality of project selection process. Although the model is demonstrated for project selection in the NSFC, it can be generalized to other funding agencies or industries.Comment: 20 pages, forthcoming in International Journal of Project Management (2019

    Multi crteria decision making and its applications : a literature review

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    This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM
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