Predicting environmental sustainability performances of firms using trigonometric grey prediction model

Abstract

Environmental sustainability performance predictions can help firms to set benchmarks for improvement and comparison. Although several works in literature have attempted in measuring environmental sustainability performances, predicting the same remains an area less explored. This is certainly due to the requirement of large datasets for constructing efficacious time-series prediction models. We attempt in this direction to forecast the environmental sustainability performances of firms based on the three indicators of performance provided by Thomson Reuters, the Resource use score, the Emissions score, and the Environmental innovation score. We propose a prediction model, which is best suited for prediction, when the available datasets are small. A trigonometric grey prediction model is employed, where the GM (1, 1) model for prediction is used initially, and later on, an error prediction model is built, based on a trigonometric residual prediction model. The model has been applied for real data of ten Indian firms to predict their future environmental sustainability performances. From the results, we observe an increasing consideration for environmental sustainability by the majority of Indian firms for the predicted year. The results of the study agree with the remarks reported in existing literatures. Hence, managers of firms are recommended to use the proposed prediction model for forecasting and improving their environmental sustainability performances for the future.