Address-Specific Sustainable Accommodation Choice Through Real-World Data Integration
<|reference_start|>Address-Specific Sustainable Accommodation Choice Through Real-World Data Integration: Consumers wish to choose sustainable accommodation for their travels, and in the case of corporations, may be required to do so. Yet accommodation marketplaces provide no meaningful capability for sustainable choice: typically CO2 estimates are provided that are identical for all accommodation of the same type across an entire country. We propose a decision support system that enables real choice of sustainable accommodation. We develop a data-driven address-specific metric called EcoGrade, which integrates government approved datasets and uses interpolation where data is sparse. We validate the metric on 10,000 UK addresses in 10 cities, showing the match of our interpolations to reality is statistically significant. We show how the metric has been embedded into a decision support system for a global accommodation marketplace and tested by real users over several months with positive user feedback. In the EU, forty percent of final energy consumption is from buildings. We need to encourage all building owners to make their accommodation more efficient. The rental sector is one area where change can occur rapidly, as rented accommodation is renovated frequently. We anticipate our decision support system using EcoGrade will encourage this positive change.<|reference_end|>
@article{bentley2024address-specific,
    title={Address-Specific Sustainable Accommodation Choice Through Real-World
  Data Integration},
    author={Peter J. Bentley, Rajat Mathur, Soo Ling Lim, Sid Narang},
    journal={The International Conference on Intelligent Data Science
  Technologies and Applications (IDSTA2024)},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.12934},
    primaryClass={cs.CY cs.CE cs.IR}
}