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This paper aims to present an integrated framework for hotel revenue room maximization. The revenue management (RM) model presented in this work treats the shortcomings in existing systems. In particular, it extends existing optimization techniques for hotel revenue management to address group reservations and uses “forecasted demand” arrivals generated from the real data.

The proposed forecasting module attempts to model the hotel reservation process from first principles. In particular, it models hotel arrivals as an interrelated process of stochastic parameters like reservations, cancellations, duration of stay, no shows, seasonality, trend, etc. and simulates forward in time the actual process of reservations to obtain the forecast. On the other hand, the proposed optimization module extends existing optimization techniques for hotel revenue management to address group reservations, while including integrality constraints and using “forecasted demand” arrivals generated from the data. The optimization model is based on large‐scale integer programming model to optimize decision rules for accepting reservations.

A case study based on three different sets of reservation records of simulated hotel data was conducted to test the operation of the system on real data. Results showed that the model is able to generate effective recommendations to maximize revenue.

The main value of this paper is that it presents an integrated framework for hotel room revenue maximization. The novelty introduced in this approach is that it is based on an advanced room demand forecast model that simulated the reservation process from its first principles and produces demand scenarios that are used by an optimization model to generate proper recommendations.

The revenue management (RM) discipline is built on the principle of demand-based pricing. This study aims to examine how and to what extent RM can be implemented in the hotel industry during low-demand periods, particularly during the coronavirus disease 2019 (COVID-19) crisis.

This paper used semi-structured interviews to gather information from hotel RM executives, RM consultants and RM system providers. Participants were asked to think about the impact of COVID-19 on their RM practices. This paper interviewed 26 revenue executives between January and March 2020.

Core RM processes are still relevant during the COVID-19 crisis; however, not all components are equally important. Business analysis, pricing strategy and demand modeling and forecasting are the most critical RM processes. Inventory and price optimization and setting booking controls are not as important at this time; along with distribution channel management, these processes will become more relevant as demand picks up.

Future research in this area should focus on each core RM process separately and in-depth to understand how implementation changes during the crisis and recovery periods. Future studies should also investigate how these processes operate during the recovery period. The full breadth of consequences of the COVID-19 crisis in hotel RM will likely manifest gradually. Therefore, the core RM processes should also be examined when the crisis is over.

Apart from a few studies that touched on RM-related strategies during economic downturns, to the knowledge, this is the first study to systematically examine the extent to which RM can be implemented during a crisis.

This study aims to adopt a holistic approach to understand cruise revenue management (RM) practices that cover ticket and onboard revenues, through a cross-disciplinary literature review and practitioner interviews. An integrated cruise RM framework was developed and served as a blueprint for future cruise studies and practices.

A multi-stage approach was adopted, including a systematic literature review, two-waves of interviews with 26 cruise industry practitioners and the development of a holistic RM framework.

This study clarifies cruise RM functions across product planning, delivery stages and identifies ticket and onboard RM components. These are incorporated into the integrated framework, with weather and itinerary/ route attractiveness as additional considerations. Interviews revealed that there is no difference in the RM cycle before and during the COVID-19 pandemic, although strategies and tactics may vary in response to the market situation.

Suggestions are made regarding product and service bundling and ways for ticket and onboard revenue teams to work together to optimize total revenue. Future research directions are also provided under the categories of RM applications and concepts, ticket core activities, onboard core activities and overall issues.

To the best of the authors’ knowledge, this is the first paper to conduct a cross-disciplinary systematic literature review of cruise RM without imposing publication dates or specific databases and the first to develop an integrated cruise “total” RM framework that includes ticket and onboard revenues.

This paper aims to study the corresponding optimal service strategies and pricing in the styled non-preemptive M/M/1 service systems from different objectives, which consider both heterogeneous waiting costs of customers and service values in customer segmentation.

In this paper, the authors consider two service situations where customers cannot leave the service system (i.e. monopoly service system) and customers can leave the service system freely (i.e. non-monopoly service system), respectively. The authors study the following four different perspectives that are revenue, social welfare, social cost and utility of customers. The authors first build up a new model, then propose the related objective functions. Further, the authors optimize the corresponding functions and achieve the optimal results. Later, the authors propose the corresponding optimal strategies. Finally, the authors use a practical numerical case to verify the proposed results.

The results of this paper indicates that the service provider should adopt classification services to gain the maximum revenue, the maximum social welfare and the minimum social costs by charging a priority fee in above two service systems. However, the service provider should cancel customer classification and keep regular customer only to obtain maximum utility. In the monopoly service system, both the optimal proportion priority customers and the revenue decrease with the increasing of the service rate, while in a non-monopoly service system, both of them are increasing with the service rate improving.

This paper first considers both heterogeneity of service values and waiting costs in queuing system, then the author set up a new model based on this assumption. Moreover, the authors draw the corresponding management insights based on the optimal results, which were unavailable before.

The purpose of this study was to examine hospitality revenue management (RM) research in the recent decade, to identify emergent issues/topics and suggest directions for future research.

A systematic process of literature review involving content analysis was adopted. The process involved searching for published articles in three major online databases for hospitality and tourism journals, evaluating and selecting the relevant articles, analyzing and synthesizing the findings of the selected papers and organizing the findings to determine what is known and what is yet to be known.

The paper established a broad range of topics that have engaged the attention of hospitality and tourism researchers in contemporary times. These topics were structured into seven major themes constituting the core activities of hospitality RM process and another eight themes covering the factors influencing the practice of RM.

The classification of the literature into core activities of RM process and factors influencing RM serves as a useful guide for practitioners and academics to trace relevant literature on various aspects of RM and to visibly notice the gaps in the existing literature.

By developing an RM framework and using it to evaluate existing literature, this study brings cohesion into the hospitality and tourism RM literature.

Revenue management has grown in popularity and is now a widely accepted discipline that has brought about significant improvements to businesses worldwide. With globalisation in recent times, there is now space for international hotels, fast food restaurants, automobile companies and other brands to offer their products in India. Educating people who are going to be part of such a process is a huge challenge. The aim of this paper is to present some of the challenges businesses and communities have to overcome.

The paper uses secondary sources to explore possible approaches to rapidly stimulate the uptake of revenue management through partnerships between hospitality and tourism businesses.

A growing middle class population and access to better education presents an opportunity to build a wider range of profitable services. Global brands with already established revenue management practices are in a position to share skills and knowledge with new and smaller players. Partnerships will be essential to rapidly and effectively develop the skills and knowledge required, starting with those in educational fields where the resources are already in place.

Revenue management has not been deployed widely in India. Being able to learn from the early adopters would allow Indian firms to leapfrog over issues and barriers, thus implementing practices more rapidly and effectively.

The purpose of this research study is to present an overview of hotel revenue management (RM) research articles published in scholarly journals during the 2001-2013 period while offering a direction for future research that focuses on RM in the hotel industry context.

Using Boolean search keywords across the period of 2001 to 2013, a total of 83 hotel RM-related research journal articles were queried. To ensure that all the identified articles were hotel-RM related, each article was independently reviewed; 70 research journal articles were identified as relevant for inclusion in this study.

RM has been and will continue to be a critical tool for the hotel industry, especially since the rise of its perceived strategic role among hoteliers. The RM process is shifting from a tactical to a strategic approach. Also, RM has become more technology driven and it is becoming more customer-centric. Hoteliers should spend more effort and resources on training and educating revenue managers.

The content analysis is limited to the databases available to the research team.

This study serves as a resource for scholars interested in RM research in the hotel industry and documents the focus of RM research and the key issues offered by scholars.

No study has previously offered an overview of RM research articles focusing on the hotel industry (covering the years since 2000). The manuscript serves as framework for scholars who may wish to identify existing research patterns and pursue new directions.

This paper aims to propose an operation policy of multi-capacity room service robots traveling within a hotel. As multi-capacity robots can serve many requests in a single trip, improved operation policy can reduce the investment cost of robots.

Using a mathematical model-based optimization technique, an optimal set of robots with minimum installation cost is derived while serving the entire room service demands. Through testing a variety of scenarios by changing the price and function of robots to be installed, insights that consider the various situations are offered.

Though the increase in capacity saves much time for room service at a lower capacity level, the amount of time saved gradually decreases as the capacity increases. Besides, the installation strategy is divided into two cases depending on the purchase cost of robots.

Currently, the studies focusing on the adoption of service robots from an operations view are rarely be found. To reduce the burden of investment cost, this study takes the unique approach to improve the operation policy of service robots by using the multi-capacity robots.

This study guides the hotel to install an adequate set of robots. The result confirms that the optimal installation set of robots is affected by various factors, such as the room service information, the hotel structure and the unit execution cycle.

After the outbreak of COVID-19, people avoid face-to-face contact and interest in non-contact service is growing. This paper deals with the efficient way to implement non-contact delivery through logistic robots, a timely and important topic.