Work

From waste to Watts: Causal evidence on AI-enabled waste-to-energy and financial performance in tourism and hospitality using an empirics-first investigation

Year: 2026

Type: article

Abstract: 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.

Source: Tourism Management

DOI: 10.1016/j.tourman.2026.105517

Author: Gomaa Agag

Institution: Nottingham Trent University

Language: English

Topic: Environmental Sustainability in Business

Subfield: Marketing

Field: Business, Management and Accounting

Domain: Social Sciences

SDGs: Decent work and economic growth, Affordable and clean energy, Responsible consumption and production, Industry, innovation and infrastructure, Climate action

Open Access status: hybrid

Estimated APC paid: $4,690