Analytic hierarchy process : An overview of applications

Data envelopment analysis (DEA) - Thirty years on

Multi-Criteria Decision Making (MCDM) methods have evolved to accommodate various types of applications. Dozens of methods have been developed, with even small variations to existing methods causing the creation of new branches of research. This paper performs a literature review of common Multi-Criteria Decision Making methods, examines the advantages and disadvantages of the identified methods, and explains how their common applications relate to their relative strengths and weaknesses. The analysis of MCDM methods performed in this paper provides a clear guide for how MCDM methods should be used in particular situations.

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An Analysis of Multi-Criteria Decision Making Methods

S COTT A. J. and S TORPER M. (2003) Regions, globalization, development , Reg. Studies 37 , 579-593. Regional economies are synergy-laden systems of physical and relational assets, and intensifying globalization is making this situation more and not less the case. As such, regions are an essential dimension of the development process, not just in the more advanced countries but also in less- developed parts of the world. Development theorists have hitherto largely tended to overlook this critical issue in favour of an emphasis on macroeconomic considerations. At the same time, conventional theories of the relationship between urbanization and economic development have favoured the view that the former is simply an effect of the latter. To be fully general, the theory of development must incorporate the role of cities and regions as active and causal elements in the economic growth process. This argument has consequences for development policy, especially in regard to the promotion of positive agglomeratio...

Regions, globalization, development

The purpose of this paper is to briefly trace the evolution of DEA from the initial publication by Charnes et al. (1978b) to the current state of the art (SOA). The state of development of DEA is characterized at four points in time to provide a perspective in both directions—past and future. An evolution map is provided which illustrates DEA growth during the 17-year period, the timing of the major events, and the interconnections and influences between topics. An extensive DEA bibliography is provided.

Data envelopment analysis: The evolution of the state of the art (1978–1995)

A unified framework for the selection of a Flexible Manufacturing System

Stochastic frontier production analysis: Measuring performance of public telecommunications in 24 OECD countries☆

The concept of allocative efficiency (AE) is discussed from the perspective of urban planning in China. The AE measurement is analytically achieved by data envelopment analysis/assurance region (DEA/AR) method. Using DEA/AR, this study illustrates the potential of AE to empirically measure the industrial performance of 35 selected Chinese cities. Besides the AE measurement, the current study explores the returns-to-scale (RTS) of these cities. The importance of the RTS measurement is that it does not assume uniqueness in its solution. This article thus presents an extended use of DEA in an attempt to improve the economic achievement within Chinese cities.

Measuring the industrial performance of Chinese cities by data envelopment analysis

This study presents an effectively-designed algorithm for measuring technical, allocative and overall efficiencies, using data envelopment analysis (DEA). The specially designed DEA code takes advantage of unique features related to the DEA algorithm. Computational efficiency of the proposed DEA algorithm is confirmed by a Monte Carlo simulation study.

https://link.springer.com/content/pdf/10.1057%2Fjors.1992.19.pdf

Measuring Technical, Allocative and Overall Efficiencies Using a DEA Algorithm

This study develops a new use of data envelopment analysis for estimating a stochastic frontier cost function that is assumed to have two different error components: a one-sided disturbance (representing technical and allocative inefficiencies) and a two-sided disturbance (representing an observational error). The two error components are handled by data envelopment analysis in combination with goal programming/constrained regression. The approach proposed in this study can avoid several statistical assumptions used in conventional methods for estimating a stochastic frontier function. As an important application, this study uses the estimation technique to obtain an AT&T stochastic frontier cost function. As a result, this study measures technical and allocative efficiencies of AT&T production process and review its natural monopoly issue. The estimated stochastic frontier cost function is also compared with the other cost function models used for previous studies concerning the divestiture of the telephone industry.

https://link.springer.com/content/pdf/10.1057%2Fjors.1991.95.pdf

Toshiyuki Sueyoshi

Papers

A unified framework for the selection of a Flexible Manufacturing System

Stochastic frontier production analysis: Measuring performance of public telecommunications in 24 OECD countries☆

Measuring the industrial performance of Chinese cities by data envelopment analysis

Measuring Technical, Allocative and Overall Efficiencies Using a DEA Algorithm

Estimation of Stochastic Frontier Cost Function Using Data Envelopment Analysis: an Application to the AT&T Divestiture