The use of DEA for studying the link between environmental and manufacturing performance
Subjectsdata envelopment analysis
N100 Business studies
MetadataShow full item record
Other TitlesBig data analytics using multiple criteria decision making models
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.
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.
PublisherCRC Press, Taylor & Francis