An advanced data analytic approach for reallocating green gas emissions in cap-and-trade context

The swift economic growth experienced by nations has exacerbated the challenge of global warming over the years. Cap-and-trade stands out as the most effective approach for managing and reducing greenhouse gas emissions. This study aims to construct a data envelopment analysis model to redistribute authorized emissions among decision-making units (DMUs). Notably, the model accounts for the intricate relationship between the production of desirable and undesirable outputs within the cap-and-trade framework. Furthermore, the model adapts the current mathematical modelling by addressing undesirable output as an inherent by-product of the desirable output. Emphasis is placed on maximizing the collective efficiency scores of all DMUs. Additionally, to confront the presence of multiple potential optimal solutions in the cap-and-trade context, the model computes the efficiency interval of DMUs. Finally, the paper showcases the model's capabilities by presenting a comprehensive case study, demonstrating its practical application and effectiveness in addressing emissions reallocation within the cap-and-trade system.