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

Jashua R. Modapothala, Biju Issac

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Citations (Scopus)

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%.

Original languageEnglish
Title of host publication2009 IEEE Symposium on Industrial Electronics and Applications, ISIEA 2009 - Proceedings
PublisherIEEE
Pages209-214
Number of pages6
ISBN (Electronic)9781424446834
ISBN (Print)9781424446827
DOIs
Publication statusPublished - 18 Dec 2009
Event2009 IEEE Symposium on Industrial Electronics and Applications, ISIEA 2009 - Kuala Lumpur, Malaysia
Duration: 4 Oct 20096 Oct 2009

Conference

Conference2009 IEEE Symposium on Industrial Electronics and Applications, ISIEA 2009
Country/TerritoryMalaysia
CityKuala Lumpur
Period4/10/096/10/09

Keywords

  • Bayesian estimate
  • Data mining
  • Environmental reports
  • Text mining

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