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Appraising the corporate sustainability reports: text mining and multi-discriminatory analysis
List of Titles
Appraising the corporate sustainability reports: text mining and multi-discriminatory analysis
Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/82239
- Title
- Appraising the corporate sustainability reports: text mining and multi-discriminatory analysis
- Author(s)
- Modapothala, J. R.; Issac, B.; Jayamani, E.
- 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.
- Publication type
- Conference paper
- Research centre
- Swinburne University of Technology. Sarawak Campus
- Source
- Proceedings of 'Innovations in computing sciences and software engineering', the International Joint Conferences on Computer, Information and Systems Sciences and Engineering (CISSE 09), Bridgepost, United States, 04-12 December 2009 / Tarek Sobh and Khaled Elleithy (eds.), pp. 489-494
- Publication year
- 2010
- FOR Code(s)
- 080109 Pattern Recognition and Data Mining; 0804 Data Format; 0899 Other Information and Computing Sciences; 10104 Statistics; 150106 Sustainability Accounting and Reporting
- Keyword(s)
- Corporate sustainability reports; Global Reporting Initiative; Industrial sectors; Text mining
- Publisher
- Springer
- ISBN
- 9789048191116, 9048191114
- Publisher URL
- http://dx.doi.org/10.1007/978-90-481-9112-3_83
- Publisher URL
- http://books.google.com/books?id=IQ8h_d5rR0MC
- Copyright
- Copyright © 2010 Springer Science + Business Media B. V.
- Peer reviewed


