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

The Indian tourism sector, while economically significant, faces increasing pressure to address itsenvironmental impact. Although carbon taxes have not yet been introduced in India, the growingemphasis on climate responsibility indicates that such regulations may soon become standard. Thishighlights 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 10leading firms on the National Stock Exchange, the research proposes the Emission Reduction Progress Factor, a composite index combining emissions performance, financial outcomes, and customersatisfaction. A blockchain-based matching system using Entropy Optimal Transport ensures secure,peer-to-peer carbon credit exchanges, minimizing transaction costs and enhancing transparencythrough decentralized smart contracts. The framework also includes a cost model to estimate energyuse, trading fees, and penalties. Strategic decision-making is supported by a nonlinear optimization model based on particle swarm optimization, which aligns emissions reduction with operationalprofitability. Findings indicate that high-emission firms benefit financially from trading, while low-emission firms gain through surplus credit sales and enhanced market positioning. The frameworkoffers a scalable model to institutionalize sustainable tourism practices in India.