| Title |
Forecasting number of ISO 14001 certifications of selected countries: application of even GM (1,1), DGM, and NDGM models |
| ID_Doc |
76946 |
| Authors |
Ikram, M; Mahmoudi, A; Shah, SZA; Mohsin, M |
| Title |
Forecasting number of ISO 14001 certifications of selected countries: application of even GM (1,1), DGM, and NDGM models |
| Year |
2019 |
| Published |
Environmental Science And Pollution Research, 26, 12 |
| DOI |
10.1007/s11356-019-04534-2 |
| Abstract |
The adaptability of ISO 14001 is considered as one of the most useful tools for environmental sustainability and worldwide competitive advantage; however, the future of ISO 14001 certification faces some uncertainties because of its uneven acceptance in various countries. These uncertainties, if not properly managed, can hinder the implementation of business management systems in these countries. In order to guide policymakers in better management of ISO 14001 in future with certainty, this study aims to forecast the ISO 14001 certifications for 10years for China, India, the USA, Italy, Japan, and Germany, the top six certified countries, through advanced mathematical modeling, namely grey models, even GM (1,1), discrete GM (1,1), and non-homogenous discrete grey model (NDGM). The benefits of mentioned models are ensured accuracy in assessment using small samples and poor information. Moreover, current research is a pioneer in the certifications growth analysis using the Synthetic Relative Growth Rate and Synthetic Doubling Time models. Finally, the empirical analysis indicated that China is constantly leading in terms of its ISO 14001 certifications till 2026 and the performance of developing countries was spectacular. Furthermore, the article has proposed some suggestions for the policymakers to make the environment more sustainable. |
| Author Keywords |
ISO 14001; Forecasting; Environmental sustainability; Competitive advantage; Doubling time; Relative growth rate |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000467887600029 |
| WoS Category |
Environmental Sciences |
| Research Area |
Environmental Sciences & Ecology |
| PDF |
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