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Titlebook: Regional Performance Measurement and Improvement; New Developments and Soushi Suzuki,Peter Nijkamp Book 2017 The Editor(s) (if applicable)

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书目名称Regional Performance Measurement and Improvement
副标题New Developments and
编辑Soushi Suzuki,Peter Nijkamp
视频video
概述Facilitates an in-depth understanding of regional performance measurement and improvement based on data envelopment analysis.Provides a detailed explanation of a new efficiency improvement approach, t
丛书名称New Frontiers in Regional Science: Asian Perspectives
图书封面Titlebook: Regional Performance Measurement and Improvement; New Developments and Soushi Suzuki,Peter Nijkamp Book 2017 The Editor(s) (if applicable)
描述This is the first book to fully introduce a newly developed distance friction minimization (DFM) model, which is one of the new efficiency improvement projection approaches in data envelopment analysis (DEA). The DFM model can produce a most effective solution in efficiency improvement projections for inefficient spatial entities (decision-making units). .The book provides a set of fresh contributions to a quantitative assessment of the performance of such policy entities. First it offers a state-of-the art overview of current DEA models and approaches, followed by the operational design of various new types of DEA models, each of them addressing weaknesses in traditional DEA approaches. Then it illustrates the assessment potential of DEA — and its new variants, in particular, the DFM model and subsequent extensions — on the basis of a broadly composed collection of empirical case studies, centering mainly but not exclusively on Japan and other Asian nations..
出版日期Book 2017
关键词Data Envelopment Analysis (DEA); Efficiency; Improvement Projection; Performance Improvement; Regional P
版次1
doihttps://doi.org/10.1007/978-981-10-0242-7
isbn_softcover978-981-10-9114-8
isbn_ebook978-981-10-0242-7Series ISSN 2199-5974 Series E-ISSN 2199-5982
issn_series 2199-5974
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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Book 2017 projection approaches in data envelopment analysis (DEA). The DFM model can produce a most effective solution in efficiency improvement projections for inefficient spatial entities (decision-making units). .The book provides a set of fresh contributions to a quantitative assessment of the performan
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Introduction,he necessity of regional performance measurement in the light of the Japanese socioeconomic and spatial development from the end of WW2 up to the present, while we also highlight the future challenges of a changing population in this country. We discuss the main evaluation methods for each era and h
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Overview of DEA and Its Improvementsnes et al. (Eur J Oper Res, 2:429–444, 1978) and based on the seminal article by Farrell (J Roy Stat Soc 120:253–290, 1957) aims to develop a comparative measure for production efficiency. We present first a brief history of the development of DEA. Next, we make a comparison of DEA and stochastic fr
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Significance of DEA for Regional Performance Measurement rules of application to regional performance measurement from the viewpoint of economies of scale, treatment of input and output items, and the number of DMUs, inputs and outputs. Furthermore, in applications of DEA, we usually need to pay attention to the influence on efficiency scores by the numb
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The Distance Friction Minimization (DFM) Model in DEA). This model generates an appropriate (nonradial) efficiency-improvement projection model, for both an input reduction and an output increase. In this approach, a generalized distance function, based on a Euclidean distance metric in weighted spaces, is proposed to assist a decision making unit (DM
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Performance Measurement of Local Government Finance in Japan: Combination of Goals-Achievement ModelA) approach on the basis of the Charnes-Cooper-Rhodes (CCR) method – in order to generate a more satisfactory efficiency-improvement projection model in conventional DEA. Another novelty of our approach is the introduction of prior goals set by a DMU by using a GA approach. The GA model specifies a
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