Digital Pathways to Low-Emission Tourism: AI and Blockchain for Carbon Market Integration in India

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:AIとブロックチェーンを組み合わせた炭素クレジット取引の新規フレームワークと最適化手法を参考に。

🏢実務担当者:炭素クレジット取引の効率化と透明性向上を目指す企業は、提案された指標と取引メカニズムを検討可能。

🏛政策担当者:炭素市場の設計や規制整備において、テクノロジー活用の可能性と課題を認識する必要。

The Indian tourism sector, while economically significant, faces increasing pressure to address its environmental impact. Although carbon taxes have not yet been introduced in India, the growing emphasis on climate responsibility indicates that such regulations may soon become standard. This highlights the urgent need for a proactive, technology-led decarbonization strategy. This study introduces a framework integrating artificial intelligence and blockchain technology to support transparent and efficient carbon credit trading tailored to Indian tourism enterprises. Based on data from 10 leading firms on the National Stock Exchange, the research proposes the Emission Reduction Progress Factor, a composite index combining emissions performance, financial outcomes, and customer satisfaction. A blockchain-based matching system using Entropy Optimal Transport ensures secure, peer-to-peer carbon credit exchanges, minimizing transaction costs and enhancing transparency through decentralized smart contracts. The framework also includes a cost model to estimate energy use, trading fees, and penalties. Strategic decision-making is supported by a nonlinear optimization model based on particle swarm optimization, which aligns emissions reduction with operational profitability. Findings indicate that high-emission firms benefit financially from trading, while low-emission firms gain through surplus credit sales and enhanced market positioning. The framework offers a scalable model to institutionalize sustainable tourism practices in India.

• openalex https://doi.org/10.3727/194339926x1765292075901059010first seen 2026-07-20 04:58:59