Panel study demonstrates improved financial performance following AI-enabled waste-to-energy adoption in hospitality firms, indicating substantial economic value from operational efficiency.
This study examines whether artificial intelligence enabled waste to energy adoption improves financial performance in tourism, travel, and hospitality firms and identifies the mechanisms and conditions shaping these effects. Using an empirics first mixed methods design, we combine interviews with 41 managers and a firm year panel of United Kingdom listed tourism, travel, and hospitality firms from 2015 to 2025. Difference in differences models with firm and year fixed effects show that adoption is associated with significantly higher financial performance, particularly at greater levels of adoption intensity. The findings indicate that energy cost savings and operational efficiency partially explain these gains. Performance benefits are also stronger in firms with higher baseline waste intensity and during periods of elevated energy prices. The study demonstrates that AI enabled waste to energy functions as an operational capability that can generate measurable economic value when integrated into organisational routines and governance systems.
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Gomaa Agag (2026) studied this question.
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