A Semantic Web framework to enable sustainable lodging best management practices in the USA

Abstract

Due to the negative environmental impact, corporate social responsibility is an important concept in today's competitive lodging industry. Hotels attribute 75% of the overall lodging industries consumption of energy, water and non-durable goods. To remain competitive, organizations implement green lodging programs to demonstrate social responsibility. However, the understanding and implementation of best practices in sustainable tourism in the United States (US) is hampered because the standards that mandate the criteria are disparate. This paper describes a framework to aggregate the variety of best management practice standards so lodging properties and patrons can more easily identify gaps in compliance to the sustainable tourism standard's criteria. The proposed framework uses standards compliance information found on property sites to infer a ranking in green tourism across twelve third party US standards bodies. Herein, a hierarchy of pre-existing and newly developed domain-specific ontologies has been combined in a semantic knowledge base to describe the relationship between best management practices and accreditation criteria from each of the sustainable tourism standards bodies. Then, inference is used to automatically evaluate a properties conformance to all other green lodging programs based on an evaluation from one. This theoretical framework could better inform hotels and tourism operators on their best management practices and consumers when choosing between green lodging properties.

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