A note on “A new approach for the selection of advanced manufacturing technologies: Data envelopment analysis with double frontiers”

Hossein Azizi

Abstract


Recently, using the data envelopment analysis (DEA) with double frontiers approach, Wang and Chin (2009) proposed a new approach for the selection of advanced manufacturing technologies: DEA with double frontiers and a new measure for the selection of the best advanced manufacturing technologies (AMTs). In this note, we show that their proposed overall performance measure for the selection of the best AMT has an additional computational burden. Moreover, we propose a new measure for developing a complete ranking of AMTs. Numerical examples are examined using the proposed measure to show its simplicity and usefulness in the AMT selection and justification.


Keywords


Data envelopment analysis; advanced manufacturing technology; optimistic and pessimistic efficiencies

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DOI: http://dx.doi.org/10.18187/pjsor.v11i2.851

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Title

A note on “A new approach for the selection of advanced manufacturing technologies: Data envelopment analysis with double frontiers”

Keywords

Data envelopment analysis; advanced manufacturing technology; optimistic and pessimistic efficiencies

Description

Recently, using the data envelopment analysis (DEA) with double frontiers approach, Wang and Chin (2009) proposed a new approach for the selection of advanced manufacturing technologies: DEA with double frontiers and a new measure for the selection of the best advanced manufacturing technologies (AMTs). In this note, we show that their proposed overall performance measure for the selection of the best AMT has an additional computational burden. Moreover, we propose a new measure for developing a complete ranking of AMTs. Numerical examples are examined using the proposed measure to show its simplicity and usefulness in the AMT selection and justification.


Date

2015-08-01

Identifier


Source

Pakistan Journal of Statistics and Operation Research; Vol. 11 No. 2, 2015



Print ISSN: 1816-2711 | Electronic ISSN: 2220-5810