Study of economic, environmental and social factors in sustainability reports using text mining and Bayesian analysis

Modapothala, Jashua R. and Issac, Biju (2009) Study of economic, environmental and social factors in sustainability reports using text mining and Bayesian analysis. In: ISIEA 2009 - 2009 IEEE Symposium on Industrial Electronics and Applications, 4th - 6th October 2009, Kuala Lumpur, Malaysia.

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Abstract

The increase in the number of corporate environmental reports (CERs) along with the growing interest among the various stakeholder groups created a new challenge to the researchers, academics, regulators and legislators, in measuring the effectiveness of these reports. The present study intends to measure the CERs in terms of economic, environmental and social performance indicators using Global Reporting Initiative (GRI) guidelines. A large sample (N=2415) is used to perform text mining so as to analyze the reports to come up with a scoring. The significant contribution made in the present study indicates that by adopting the GRI guidelines, it is observed that global CERs is now undergoing fragmented reporting in its incremental approach. Bayesian estimate confirms the probability that the true value of all the selected variable parameter falls within the confidence interval of 95%.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Bayesian estimate, Data mining, Environmental reports, Text mining
Subjects:	G200 Operational Research G400 Computer Science N200 Management studies
Department:	Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User:	Paul Burns
Date Deposited:	17 Jan 2019 17:13
Last Modified:	11 Oct 2019 14:31
URI:	http://nrl.northumbria.ac.uk/id/eprint/37640

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