RT journal article
T1 Restaurant revenue management: a systematic literature review and future challenges
A1 Bujalance López, Lourdes
A1 González Serrano, Lydia
A1 Lechuga Sancho, María Paula
A1 Talón Ballestero, Pilar
A2 Organización de Empresas
K1 Information management
K1 Systematic literature review
K1 Digitalisation
K1 Restaurant revenue management
K1 Price management
K1 Sales management
AB Purpose – This study aims to examine the evolution of restaurant revenue management (RRM), highlightingemerging research areas and challenges. It aims to provide a structured overview of revenue optimisationstrategies, emphasising the impact of digital transformation, customer behaviour shifts and technologicaladvancements. The study offers practical insights for restaurant operators on leveraging data-driven strategies,including dynamic pricing, artificial intelligence (AI)-powered forecasting and menu engineering, to enhanceprofitability and customer satisfaction. By mapping the field’s trajectory, the research identifies opportunities forfuture investigation, ensuring that restaurant managers and academics have a clear framework for optimisingrevenue performance in an increasingly digital and competitive environment.Design/methodology/approach – This study employs a systematic literature review (SLR) to analyse 108articles published between 1997 and 2023 from major academic databases. The methodology ensures astructured, transparent and replicable synthesis of research trends in RRM. Following a five-step process, thestudy identifies key strategic levers and methodological gaps, integrating recent developments in big dataanalytics, digital transformation and AI-driven forecasting models. By categorising RRM literature into fivestrategic levers, this research provides a comprehensive understanding of the field’s evolution and itsimplications for future revenue management practices in the restaurant industry.Findings – The impact of COVID-19 has accelerated digital transformation in the restaurant industry, driving afundamental shift in RM research. Adopting digital menus, consolidating online reservations and expandingdelivery services have prompted new research avenues in data analytics, capacity optimisation, pricepersonalisation and operational efficiency. As the industry evolves, academic literature reflects a clear transitiontoward data-driven RM, leveraging sophisticated tools to maximise profitability and enhance the customerexperience in the post-pandemic landscape.Originality/value – This is the first systematic review integrating post-pandemic digitalisation trends in RRM.The study introduces an expanded framework that incorporates information and sales management as keyrevenue levers. It explores AI-driven decision-making, real-time data analytics, and behavioural pricingstrategies, setting the foundation for future research in restaurant revenue optimisation. By addressing thesector’s ongoing digital transformation, this study provides valuable recommendations for industry practitionersand researchers, helping restaurants to implement innovative revenue strategies that improve financialperformance while enhancing customer experience in an evolving, technology-driven market.
PB Emerald Publishing
SN 0007-070X
YR 2025
FD 2025-04
LK http://hdl.handle.net/10498/39967
UL http://hdl.handle.net/10498/39967
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 07-nov-2026