Appraising the corporate sustainability reports - Text mining and multi-discriminatory analysis

J. R. Modapothala; B. Issac; E. Jayamani

doi:10.1007/978-90-481-9112-3_83

Appraising the corporate sustainability reports - Text mining and multi-discriminatory analysis

J. R. Modapothala, B. Issac, E. Jayamani

Computer and Information Sciences Department

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

17 Citations (Scopus)

Abstract

The voluntary disclosure of the sustainability reports by the companies attracts wider stakeholder groups. Diversity in these reports poses challenge to the users of information and regulators. This study appraises the corporate sustainability reports as per GRI (Global Reporting Initiative) guidelines (the most widely accepted and used) across all industrial sectors. Text mining is adopted to carry out the initial analysis with a large sample size of 2650 reports. Statistical analyses were performed for further investigation. The results indicate that the disclosures made by the companies differ across the industrial sectors. Multivariate Discriminant Analysis (MDA) shows that the environmental variable is a greater significant contributing factor towards explanation of sustainability report.

Original language	English
Title of host publication	Innovations in Computing Sciences and Software Engineering
Editors	Tarek Sobh, Khaled Elleithy
Publisher	Springer
Pages	489-494
Number of pages	6
ISBN (Electronic)	9789048191123
ISBN (Print)	9789048191116
DOIs	https://doi.org/10.1007/978-90-481-9112-3_83
Publication status	Published - 1 Jun 2010
Event	2009 International Conference on Systems, Computing Sciences and Software Engineering, SCSS 2009, Part of the International Joint Conference on Computer, Information, and Systems Sciences, and Engineering, CISSE 2009 - Duration: 4 Dec 2009 → 12 Dec 2009

Conference

Conference	2009 International Conference on Systems, Computing Sciences and Software Engineering, SCSS 2009, Part of the International Joint Conference on Computer, Information, and Systems Sciences, and Engineering, CISSE 2009
Period	4/12/09 → 12/12/09

Keywords

Corporate Social Responsibility
Global Reporting Initiative
Sustainability Report
Voluntary Disclosure
Fisher Linear Discriminant

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-90-481-9112-3_83

Cite this

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title = "Appraising the corporate sustainability reports - Text mining and multi-discriminatory analysis",

abstract = "The voluntary disclosure of the sustainability reports by the companies attracts wider stakeholder groups. Diversity in these reports poses challenge to the users of information and regulators. This study appraises the corporate sustainability reports as per GRI (Global Reporting Initiative) guidelines (the most widely accepted and used) across all industrial sectors. Text mining is adopted to carry out the initial analysis with a large sample size of 2650 reports. Statistical analyses were performed for further investigation. The results indicate that the disclosures made by the companies differ across the industrial sectors. Multivariate Discriminant Analysis (MDA) shows that the environmental variable is a greater significant contributing factor towards explanation of sustainability report.",

keywords = "Corporate Social Responsibility, Global Reporting Initiative, Sustainability Report, Voluntary Disclosure, Fisher Linear Discriminant",

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Modapothala, JR, Issac, B & Jayamani, E 2010, Appraising the corporate sustainability reports - Text mining and multi-discriminatory analysis. in T Sobh & K Elleithy (eds), Innovations in Computing Sciences and Software Engineering. Springer, pp. 489-494, 2009 International Conference on Systems, Computing Sciences and Software Engineering, SCSS 2009, Part of the International Joint Conference on Computer, Information, and Systems Sciences, and Engineering, CISSE 2009, 4/12/09. https://doi.org/10.1007/978-90-481-9112-3_83

Appraising the corporate sustainability reports - Text mining and multi-discriminatory analysis. / Modapothala, J. R.; Issac, B.; Jayamani, E.
Innovations in Computing Sciences and Software Engineering. ed. / Tarek Sobh; Khaled Elleithy. Springer, 2010. p. 489-494.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Modapothala, J. R.

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AU - Jayamani, E.

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Y1 - 2010/6/1

N2 - The voluntary disclosure of the sustainability reports by the companies attracts wider stakeholder groups. Diversity in these reports poses challenge to the users of information and regulators. This study appraises the corporate sustainability reports as per GRI (Global Reporting Initiative) guidelines (the most widely accepted and used) across all industrial sectors. Text mining is adopted to carry out the initial analysis with a large sample size of 2650 reports. Statistical analyses were performed for further investigation. The results indicate that the disclosures made by the companies differ across the industrial sectors. Multivariate Discriminant Analysis (MDA) shows that the environmental variable is a greater significant contributing factor towards explanation of sustainability report.

AB - The voluntary disclosure of the sustainability reports by the companies attracts wider stakeholder groups. Diversity in these reports poses challenge to the users of information and regulators. This study appraises the corporate sustainability reports as per GRI (Global Reporting Initiative) guidelines (the most widely accepted and used) across all industrial sectors. Text mining is adopted to carry out the initial analysis with a large sample size of 2650 reports. Statistical analyses were performed for further investigation. The results indicate that the disclosures made by the companies differ across the industrial sectors. Multivariate Discriminant Analysis (MDA) shows that the environmental variable is a greater significant contributing factor towards explanation of sustainability report.

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KW - Sustainability Report

KW - Voluntary Disclosure

KW - Fisher Linear Discriminant

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Y2 - 4 December 2009 through 12 December 2009

ER -

Appraising the corporate sustainability reports - Text mining and multi-discriminatory analysis

Abstract

Conference

Keywords

UN SDGs

Access to Document

Fingerprint

Cite this