Use of DEA for studying the link between environmental and manufacturing performance

In this era of big data and business analytics, huge data are available in public domain and it is important for researchers to analyze these 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 multicriteria tool, namely the data envelopment analysis (DEA), 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 United Kingdom. DEA scores are then combined with further data on pollution abatement expenditure in these sectors. Using previous literature, we hypothesize that there is a positive relationship between environmental expenditure and manufacturing efficiency of sectors, and verify it using sector-level data from the U.K. manufacturing industry. Our study illustrates the use of multicriteria decision-making tools in using publicly available big data for use in public policy analysis.