RevEmo: A Conceptual Framework for Measuring the Economic Contribution of Human Moments in AI-Mediated Hospitality
- 1Altavella
Abstract
As artificial intelligence takes over an increasing share of the hotel guest journey, a fundamental question emerges: which human interactions remain worth investing in, and how can hotels measure the economic value they create?
Hospitality has long recognised the importance of personal attention, emotional connections and memorable experiences. Yet traditional performance metrics struggle to distinguish the value of these interactions from the broader guest experience, let alone establish whether investing in them produces measurable financial returns.
This paper introduces RevEmo (Revenue per Emotional Moment), a conceptual framework designed to address that gap. It connects personally meaningful, guest-validated staff interactions with a structured approach to evaluating their economic contribution, while examining where human judgement can complement increasingly automated service environments.
Drawing on established research in service management, customer relationships and artificial intelligence, the paper develops four testable propositions linking context-sensitive human service to guest recognition, trust, favourable recall and subsequent purchasing behaviour.
Importantly, RevEmo challenges the assumption that more memorable interactions necessarily translate into better financial performance. Through formal analysis and synthetic simulations, it demonstrates how incomplete recording, changing encounter populations and misleading performance ratios can distort investment decisions. An illustrative 90-day hotel investment model translates these insights into incremental contribution, break-even requirements and operational capacity constraints.
The resulting framework combines a six-category taxonomy of meaningful human interactions with a financial evaluation model and practical guidance for hotel management.
Its central contribution is to move the discussion beyond whether human hospitality matters, towards understanding where, why and under what conditions investing in it creates measurable economic value.
As AI reshapes hospitality operations, RevEmo offers researchers, hotel operators and investors a structured foundation for evaluating the economic contribution of human service without reducing the human experience to a financial transaction.
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BibTeX
@misc{vasconcelos2026revemo,
title = {{RevEmo: A Conceptual Framework for Measuring the Economic Contribution of Human Moments in AI-Mediated Hospitality}},
author = {Rui Vasconcelos},
howpublished = {Zenodo},
year = {2026},
month = oct,
doi = {10.5281/zenodo.23537712},
url = {https://zenodo.org/records/23537712},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - UNPB
TI - RevEmo: A Conceptual Framework for Measuring the Economic Contribution of Human Moments in AI-Mediated Hospitality
AU - Rui Vasconcelos
PY - 2026
DA - 2026/10/21
PB - Zenodo
DO - 10.5281/zenodo.23537712
UR - https://zenodo.org/records/23537712
AB - As artificial intelligence takes over an increasing share of the hotel guest journey, a fundamental question emerges: which human interactions remain worth investing in, and how can hotels measure the economic value they create? Hospitality has long recognised the importance of personal attention, emotional connections and memorable experiences. Yet traditional performance metrics struggle to distinguish the value of these interactions from the broader guest experience, let alone establish whether investing in them produces measurable financial returns. This paper introduces RevEmo (Revenue per Emotional Moment), a conceptual framework designed to address that gap. It connects personally meaningful, guest-validated staff interactions with a structured approach to evaluating their economic contribution, while examining where human judgement can complement increasingly automated service environments. Drawing on established research in service management, customer relationships and artificial intelligence, the paper develops four testable propositions linking context-sensitive human service to guest recognition, trust, favourable recall and subsequent purchasing behaviour. Importantly, RevEmo challenges the assumption that more memorable interactions necessarily translate into better financial performance. Through formal analysis and synthetic simulations, it demonstrates how incomplete recording, changing encounter populations and misleading performance ratios can distort investment decisions. An illustrative 90-day hotel investment model translates these insights into incremental contribution, break-even requirements and operational capacity constraints. The resulting framework combines a six-category taxonomy of meaningful human interactions with a financial evaluation model and practical guidance for hotel management. Its central contribution is to move the discussion beyond whether human hospitality matters, towards understanding where, why and under what conditions investing in it creates measurable economic value. As AI reshapes hospitality operations, RevEmo offers researchers, hotel operators and investors a structured foundation for evaluating the economic contribution of human service without reducing the human experience to a financial transaction.
ER -