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Philip Barton

As seen in: Color Research & Application, Wiley, Wiley Online Library, The Conversation, Australian Geographic, HospitalityNet, Law Institute Journal
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Articles

An Empirical Test of Scale-Dependence of β-Diversity in a Large Temperate Forest Region

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By Liqi Lu, Philip Barton, Senxuan Lin
| Wiley Online Library Verified
Conflicts of Interest The authors declare no conflicts of interest. Data Availability Statement The data and code supporting this study's findings have been archived in a public repository: https://figshare.com/s/f7ecee598741d27ddb19. Supporting Information Filename Description jbi70281-sup-0001-Supinfo.docxWord 2007 document , 4.8 MB Appendix S1: Explanation of the two different types of spatial scale defined. Appendix S2: Sampling effort.
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Rebuilding hotel tech stacks for the Agentic AI era Philip Barton

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By Philip Barton
| HospitalityNet
A new kind of traveller is emerging, one who may never visit your website, click an ad, or speak to a human. Instead, they rely on their personal AI agent to plan, compare, negotiate, and book every aspect of their trip. This shift marks a seismic change in how travel is discovered and transacted, demanding a fundamental rethink of hotel technology stacks. Are hoteliers ready for this new class of guests and their digital representatives?
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From data to action - driving ROI from data in hospitality

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By Philip Barton
| HospitalityNet
"We have so much data, but we still don´t really get much out of it," was a recent lament from a major hotel chain. This is a common problem, so why is it so hard to turn data into quantifiable ROI? The hospitality industry sits on a goldmine of data, be it guest preferences, booking behaviors, demand patterns, revenue trends, or operational insights. Theoretically, this data should be a game-changer for driving revenue and enhancing customer experiences.
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