The use of DEA for studying the link between environmental and manufacturing performance

2.50
Hdl Handle:
http://hdl.handle.net/10547/622182
Title:
The use of DEA for studying the link between environmental and manufacturing performance
Authors:
Ramanathan, Ramakrishnan ( 0000-0002-8861-2209 )
Other Titles:
Big data analytics using multiple criteria decision making models
Abstract:
In this era of big data and business analytics, huge data is available in public domain and it is important for researchers to analyse this data to be able to make business sense to help businesses grow and to help policy makers to obtain useful insights. In this chapter, we first outline various available Big Data in the public domain that can be used to investigate an important issue in environmental policy: the relationship between environmental expenditure and manufacturing efficiency. We then illustrate how a multi-criteria tool, namely the Data Envelopment Analysis, can be advantageously combined with other statistical models to help study the above relationship. DEA is used to obtain manufacturing efficiency scores of various sectors in the UK. DEA scores are then combined with further data on pollution abatement expenditure in these sectors. Using previous literature, we hypothesise that there is a positive relationship between environmental expenditure and manufacturing efficiency of sectors, and verify it using sector-level data from the UK manufacturing industry. Our study illustrates the use of MCDM tools in using publicly available Big Data for use in public policy analysis.
Citation:
Ramanathan R (2017) 'The use of DEA for studying the link between environmental and manufacturing performance', in Ramanathan R, Mathirajan M, Ravindran A R (ed(s).). Big data analytics using multiple criteria decision making models, 1 edn, Florida, USA: CRC Press, Taylor & Francis pp.303-313.
Publisher:
CRC Press, Taylor & Francis
Issue Date:
17-Jul-2017
URI:
http://hdl.handle.net/10547/622182
DOI:
10.1201/9781315152653-13
Additional Links:
https://www.crcpress.com/Big-Data-Analytics-Using-Multiple-Criteria-Decision-Making-Models/Ramanathan-Mathirajan-Ravindran/p/book/9781498753555
Type:
Book chapter
Language:
en
ISBN:
9781498753555
Appears in Collections:
Business and management

Full metadata record

DC FieldValue Language
dc.contributor.authorRamanathan, Ramakrishnanen
dc.date.accessioned2017-09-08T09:03:20Z-
dc.date.available2017-09-08T09:03:20Z-
dc.date.issued2017-07-17-
dc.identifier.citationRamanathan R (2017) 'The use of DEA for studying the link between environmental and manufacturing performance', in Ramanathan R, Mathirajan M, Ravindran A R (ed(s).). Big data analytics using multiple criteria decision making models, 1 edn, Florida, USA: CRC Press, Taylor & Francis pp.303-313.en
dc.identifier.isbn9781498753555-
dc.identifier.doi10.1201/9781315152653-13-
dc.identifier.urihttp://hdl.handle.net/10547/622182-
dc.description.abstractIn this era of big data and business analytics, huge data is available in public domain and it is important for researchers to analyse this data to be able to make business sense to help businesses grow and to help policy makers to obtain useful insights. In this chapter, we first outline various available Big Data in the public domain that can be used to investigate an important issue in environmental policy: the relationship between environmental expenditure and manufacturing efficiency. We then illustrate how a multi-criteria tool, namely the Data Envelopment Analysis, can be advantageously combined with other statistical models to help study the above relationship. DEA is used to obtain manufacturing efficiency scores of various sectors in the UK. DEA scores are then combined with further data on pollution abatement expenditure in these sectors. Using previous literature, we hypothesise that there is a positive relationship between environmental expenditure and manufacturing efficiency of sectors, and verify it using sector-level data from the UK manufacturing industry. Our study illustrates the use of MCDM tools in using publicly available Big Data for use in public policy analysis.en
dc.language.isoenen
dc.publisherCRC Press, Taylor & Francisen
dc.relation.urlhttps://www.crcpress.com/Big-Data-Analytics-Using-Multiple-Criteria-Decision-Making-Models/Ramanathan-Mathirajan-Ravindran/p/book/9781498753555en
dc.subjectdata envelopment analysisen
dc.subjectsecondary dataen
dc.subjectenvironmental performanceen
dc.subjectregression analysisen
dc.subjectefficiencyen
dc.subjectN100 Business studiesen
dc.titleThe use of DEA for studying the link between environmental and manufacturing performanceen
dc.title.alternativeBig data analytics using multiple criteria decision making modelsen
dc.typeBook chapteren
dc.date.updated2017-09-08T08:57:31Z-
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