Analysis of corporate environmental reports using statistical techniques and data mining

TL;DR

This study employs statistical and data mining techniques to analyze corporate environmental reports, revealing significant industry differences and key factors influencing reporting practices, aligning with GRI frameworks.

Contribution

It introduces a comprehensive data mining and statistical analysis approach to evaluate the effectiveness and factors of corporate environmental reports.

Findings

Significant differences among industry types in environmental reporting.

Stakeholder, strategy, and industrial factors are significant influences.

Findings align with GRI conceptual framework.

Abstract

Measuring the effectiveness of corporate environmental reports, it being highly qualitative and less regulated, is often considered as a daunting task. The task becomes more complex if comparisons are to be performed. This study is undertaken to overcome the physical verification problems by implementing data mining technique. It further explores on the effectiveness by performing exploratory analysis and structural equation model to bring out the significant linkages between the selected 10 variables. Samples of five hundred and thirty nine reports across various countries are used from an international directory to perform the statistical analysis like: One way ANOVA (Analysis of Variance), MDA (Multivariate Discriminant Analysis) and SEM (Structural Equation Modeling). The results indicate the significant differences among the various types of industries in their environmental reporting, and the exploratory factors like stakeholder, organization strategy and industrial oriented factors, proved significant. The major accomplishment is that the findings correlate with the conceptual frame work of GRI.