Abstract
There has been a worldwide upsurge in environmental movements. The planet's ecosystem has degraded significantly over the years. The disturbing effects of environmental deterioration on Earth's physical geography cause concern among those concerned about the planet's future. While previous research has looked at various ecological elements, recent attention has turned to digital change and the need to make the most of it. Eco-efficiency is a critical component in reducing carbon output (CO2). Reaching carbon neutrality goals, getting carbon peaking, and achieving high-quality economic growth, digital transformation, and eco-efficiency are intense endeavors. A panel data set spanning G-15 economies from 1995 to 2022, this article examines the effects of digital transformation, eco-efficiency, and the food supply chain on carbon emissions. The unit root test established the stationarity of all indicators at the initial difference. In addition to Pedroni and Kao cointegration methods, the panel study uses ADF, DF-GLS, and PP unit root test, as well as dynamic ordinary least square (DOLS) and fully FMOLS stands for panel adjusted regular least square. Approaches for robustness: the present research additionally uses panel quantile regression to examine the effect of factors. In order to promote environmental sustainability and minimize CO₂ emissions, the findings highlighted the need for eco-efficiency, digital transformation, the food supply chain, and government policy. On the other hand, natural resource exploitation and energy transition worsen environmental quality and raise CO2 emissions in Great economies. We use the DH panel causality test to assess the factors' correlation further. Furthermore, carbon emissions (CO2) are affected in one way by changes in the energy sector and the food supply chain and in another by changes in eco-efficiency, digital transformation, and government policy. Environmental deterioration has many causes, and this study's results may help shed light on those reasons while suggesting solutions.
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