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Forecasting number of ISO 14001 certifications of selected countries: application of even GM (1,1), DGM, and NDGM models

pmid: 30850983
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 10 years 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.
- International Islamic University Pakistan
- Nanjing University of Aeronautics and Astronautics China (People's Republic of)
- Islamic Azad University of Falavarjan Iran (Islamic Republic of)
- European College of Economics and Management Bulgaria
- Islamic Azad University of Shiraz Iran (Islamic Republic of)
China, Conservation of Natural Resources, Certification, Commerce, India, Models, Theoretical, Italy, Japan, Germany, Humans, Forecasting
China, Conservation of Natural Resources, Certification, Commerce, India, Models, Theoretical, Italy, Japan, Germany, Humans, Forecasting
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).155 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 0.1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
