Single-leg choice-based revenue management: a robust optimisation approach

A popular trend in revenue management captures the behaviour of customers that choose between different available products. The provided solution methods assume that there is no uncertainty in the parameters of the model. However, in practice the parameters may be uncertain, e.g., because of estimation errors. A relatively recent field of optimisation that takes into account uncertainty in the optimisation procedure is robust optimisation. Robust optimisation methods provide solutions where the worst-case scenario is optimised, taking into account uncertainty in parameters. This paper studies a robust optimisation approach to single-leg choice-based revenue management based on Talluri and van Ryzin (Manag Sci 50:15–33, 2004) and Sierag et al (Eur J Oper Res 246:170–185, 2015). The problem is modelled as a Markov decision process and solved using dynamic programming. This paper uses ϕ-divergence uncertainty sets to model the probability vectors of general choice-models. Novel robust optimisation techniques are applied to the dynamic program, taking into account uncertainty in the parameters. An important yet surprising insight from the numerical results is that the robust solution method performs better for smaller inventory than for larger inventory. Moreover, the robust solution method shows great performance when knowledge on cancellation behaviour is lacking: on average the expected reward then improves by 2.5–3.25 per cent

Business to business online revenue management.

With the emergence of the Internet, electronic commerce (e-commerce), revenue management and especially applications that combine both are becoming increasingly an area of innovation for service industries. E-commerce has introduced efficiencies across the service chain and it has allowed improvements to take place within and across organizations. Revenue management when combined with ecommerce and done online not only improves resource management but it can be used as a strategic tool to gain competitive advantage. This chapter examines the current approaches and future trends in these very exciting and promising areas

Price and distribution policy of seaside holiday hotels on the Bulgarian Black Sea coast in the conditions of the COVID crisis

The object of this article is pricing and distribution in the hospitality industry, and the subject is the relationship between pricing and distribution policy in seaside holiday hotels. Based on the literature review and direct observations of the author on the activities of seaside holiday hotels on the Bulgarian Black Sea coast, the author aims to reveal the importance of pricing for the successful distribution of the seaside holiday product. A special emphasis is placed on interdependence between pricing and distribution policy of seaside holiday hotels in the conditions of Covid- 19 crisis in tourism

Big data in hotel revenue management: exploring cancellation drivers to gain insights into booking cancellation behavior

n the hospitality industry, demand forecast accuracy is highly impacted by booking cancellations, which makes demand-management decisions difficult and risky. In attempting to minimize losses, hotels tend to implement restrictive cancellation policies and employ overbooking tactics, which, in turn, reduce the number of bookings and reduce revenue. To tackle the uncertainty arising from booking cancellations, we combined the data from eight hotels’ property management systems with data from several sources (weather, holidays, events, social reputation, and online prices/inventory) and machine learning interpretable algorithms to develop booking cancellation prediction models for the hotels. In a real production environment, improvement of the forecast accuracy due to the use of these models could enable hoteliers to decrease the number of cancellations, thus, increasing confidence in demand-management decisions. Moreover, this work shows that improvement of the demand forecast would allow hoteliers to better understand their net demand, that is, current demand minus predicted cancellations. Simultaneously, by focusing not only on forecast accuracy but also on its explicability, this work illustrates one other advantage of the application of these types of techniques in forecasting: the interpretation of the predictions of the model. By exposing cancellation drivers, models help hoteliers to better understand booking cancellation patterns and enable the adjustment of a hotel’s cancellation policies and overbooking tactics according to the characteristics of its bookings.info:eu-repo/semantics/acceptedVersio

Customers’ reaction to overbooking failures in hospitality industry - Framework of actions to remedy capacity management failures

This literature review discusses customers’ reaction to capacity management failures that result from overbooking. Even though not all hospitality businesses overbook, overbooking is widely used in the hospitality industry. However, research on overbooking effects is not yet thorough. Overbooking practices affect companies’ long-term profitability. For these reasons there is need for study on customers’ reaction to overbooking failures. This study shows that negative overbooking failures have effect on customers’ word-of-mouth behaviour and repurchasing intentions, while upgrading has no significant influence on customers purchasing behaviour. Customers’ reaction is influenced by customer specific reasons and how customers to face the failure are chosen are informed. Customers’ reaction can be improved by remedying three areas of perceived fairness: interactional fairness, procedural fairness and distributive fairness. These areas are interrelated and therefore successful remedy requires succeeding in all three. The cause for the failure affects customers’ reaction and this study suggests how the reasons behind the failures should be framed. It is also found that compensation’s type, amount and speed affect customers’ satisfaction. According to the findings encouraging complaining behaviour should be practised. To provide a tool for hospital management, this study introduces a framework of actions in managing customers’ reaction in capacity management failures. The framework brings together all relevant components that are needed to understand and enhance actions in capacity management failure situations

A cryptographic cloud-based approach for the mitigation of the airline cargo cancellation problem

In order to keep in good long-term relationships with their main customers, Airline Cargo companies do not impose any fee for last minute cancellations of shipments. As a result, customers can book the same shipment on several cargo companies. Cargo companies try to balance cancellations by a corresponding volume of overbooking. However, the considerable uncertainty in the number of cancellations does not allow to fine-tune the optimal overbooking level, causing losses. In this work, we show how the deployment of cryptographic techniques, enabling the computation on private information of customers and companies data can improve the overall service chain, allowing for striking and enforcing better agreements. We propose a query system based on proxy re-encryption and show how the relevant information can be extracted, still preserving the privacy of customers\u2019 data. Furthermore, we provide a Game Theoretic model of the use case scenario and show that it allows a more accurate estimate of the cancellation rates. This supports the reduction of the uncertainty and allows to better tune the overbooking level

The use of yield management within the kingdom of Saudi Arabia hotels

The airline industry has successfully adopted yield management (YM), particularly after the industry was deregulated in the late 1970s. In this study, YM is applicable to the hotel industry as a strategy to maximise profits. Thus, it involves the allocation of resources among various customers in hotel rooms relative to the existing market characteristics. In doing so, YM’s core concept is the provision of the right service to customers at the right prices. The aim of this study is to examine the practices and perceptions concerning YM as per the understanding and awareness of hotel managers. The study investigates several Saudi hotels of various sizes that use YM, and it identifies revenue management strategies and general practices within the hotel industry. The investigation took place in seven key areas of the hotel industry: location, occupancy, pricing strategy, price-adjustment strategies, HR management, customer satisfaction and third-party websites. The study involved two steps to achieve its purpose. First, YM practices were investigated in comparison to the seven key areas that influence revenue. Moreover, there was an emphasis on determining whether there was an attempt to manage revenue within the hotel industry. The results from the investigation are presented using a descriptive approach. The second step involved establishing the use of YM as a tool for managing revenue in hotel operations. This shows how revenue management through YM should be conducted. These results are presented using a normative approach. In the methodology, qualitative research is applied. Through this approach, 13 revenue managers and seven general managers from various Saudi hotels in Riyadh, the Eastern Province and Mecca were interviewed. Further, documents and direct observations were used to collect vital data to compare room rates through the use of direct and indirect distribution channels. Here, direct distribution channels involve making direct calls to hotels, as well as the use of official hotel websites. Conversely, indirect distribution channels involve the use of Booking.com and Agoda.com. These different options were then compared to observe the option that was more efficient in revenue management. From the comparison, the results showed that the practices and perceptions of YM were reasonable in the cities’ hotels. Of particular interest was the fact that respondents were aware of some key principles of YM. Consequently, many of these principles had been adhered to in room revenue management. For instance, stakeholders understood the significance of segmenting potential and current customers into various groups. This is critical, as these groups have different priorities, income levels and goals. As a rule, attention focuses on criteria such as ability and willingness to pay. The study recommends strategies that can be adopted by Saudi hotels to overcome the misconceptions and perceptions of YM. For instance, the system must be interlinked with location, occupancy, pricing strategy, price-adjustment strategy, HR, customer relations and the Internet. Interlinking the system with these key concepts is essential to maximise profits in the hotel industry. In essence, this paper offers knowledge to further the research on the applicability of the YM concept within the hotel industry in Saudi Arabia

Tourism in the Digital Age: E-booking Perspective

Digitization in the tourism sector beside hospitality information systems application as its integral part has also led to the application of on-line booking systems, which enable the booking of the desired tourist arrangement via the Internet. Consequently, the emergence of the e-booking concept has made it possible reducing administrative and operational costs, since the e-booking system is also used on smartphones with appropriate applicative support. This paper aims to point out the importance of e-booking in the digital age of tourism, especially from monitoring the most common destinations, customer preferences and performing predictive analytics by collecting large amounts of data. In this way, the implementation of big data and cloud computing concept enhances tourism services, since it is possible to analyse destination history and tourist potential of the client via the Internet. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.</p

Single-dimensional leg-level dynamic programming with booking-time dependent cancellation probabilities for revenue management

In this paper, an optimisation method is introduced that accounts for cancellations. We do so by estimating the opportunity cost of a booking between the time of booking and the expected time of cancellation. The formulation involves an estimate of the value of the state of the system at the time of cancellation (which is in the future), found through novel heuristics we introduce. The fare that is used to determine whether a product is available for sale, is adjusted by the risk the airline faces. We introduce an example which shows that there may be cases where it is optimal to reject a higher-priced product if the risk of cancellation is high, while accepting a lower-priced product. Simulations show increases in revenues against a traditional formulations that does not explicitly models cancellations. We show our method is robust against choice of heuristic, misjudgement of cancellation probability and forecasting errors