Izvorni znanstveni članak
https://doi.org/10.20867/thm.32.1.9
Revenue management reinvented: Leveraging technical know-how to unlock hotel efficiency
Karam Zaki
orcid.org/0000-0001-6070-5449
Sažetak
Purpose – Revenue management (RM) is no longer just a tool for optimizing revenue but
a strategic framework for driving net profits and sustainable growth. This study reimagines
RM in green hotels as a dynamic, innovation-driven process, leveraging digitalization
to create smarter, data-driven decision-making ecosystems. It explores the role of RM
enablers—organizational culture (OC), demand prediction (DP), distribution networks (DN),
competition analysis (CA), tailored pricing (TP), and regular evaluations (RE)—in boosting
hotel efficiency. Additionally, it investigates how technical know-how (TKH) acts as a
catalyst, mediating the link between RM practices and hotel efficiency.
Methodology/Design/Approach – A multiple case study approach was applied, targeting green
hotels in Saudi Arabia. Data were collected through 405 self-designed questionnaires distributed
among hotel executives. Data envelopment analysis (DEA) was employed to calculate hotel
efficiency scores. The random forest (RF) algorithm was utilized as a machine learning tool to
predict model performance and identify feature importance metrics. Finally, structural equation
modeling (SEM) was used to test the proposed hypotheses and mediation effects.
Findings – The study identified a significant positive relationship between RM enablers
and hotel efficiency. TP, DP, and CA emerged as the most influential enablers, with high
contributions to model accuracy and node purity. While, OC, DN, and RE showing limited
effects. Machine learning analysis confirmed the predictive accuracy and feature importance
of the proposed model. The mediation analysis revealed that TKH strengthens the relationship
between RM actions and hotel efficiency.
Originality of the research – This study integrates advanced machine learning techniques
with RM enablers to provide a comprehensive framework for enhancing hotel efficiency. It
highlights the mediating role of TKH, offering new perspectives for RM literature.
Ključne riječi
Revenue management, technical know-how, efficiency, green hotels, machine learning, random forest
Hrčak ID:
345105
URI
Datum izdavanja:
4.3.2026.
Posjeta: 299 *