The Voice of Major E-Tourism Players: An Expedia Group Perspective

This chapter outlines the approach of Expedia Group, the world's travel platform, and the role of technology in revolutionizing travel search, discovery, and booking. It covers innovations developed by online travel agencies (OTAs) and the unique challenges and opportunities provided by the breadth and depth of the data that global OTAs leverage to power travelers' online experiences. The focus is on accommodation, the largest revenue-generating, and most complex tourism segment. The chapter explores specific use cases where data are brought together with leading and innovative machine learning methodologies to improve traveler and supplier experiences. They include recommender systems, machine learning models that help Expedia Group manage the text and image content for over a million properties and revenue management systems for accommodation providers. The chapter concludes with a comment on the Expedia Group COVID- 19 response. © Springer Nature Switzerland AG 2022.

Social distancing and revenue management-A post-pandemic adaptation for railways.

The SARS-CoV-2 pandemic has had a significant impact on rail operations worldwide. Adopting control measures such as a 50% occupancy rate can contribute to a safer travel environment, though at the expense of operational efficiency. This paper addresses the issues of social distancing and revenue maximization for a train operating company in a post-pandemic world. Although the two objectives appear to be highly contradictory, we believe that judicious planning can optimize both to a great extent. Existing research on social distancing on public transport has only considered the risk of virus transmission during travel. This is the first attempt to recognize the risk of virus spread in different cities along with transmission risk as part of developing a social distancing plan. We study the problem of assigning seats to passenger groups on long-distance trains while ensuring social distancing within coaches. A novel seating assignment policy is proposed that takes into account several factors that govern the spread of virus. In an effort to reduce the spread of the virus and improve revenue simultaneously, a mixed-integer programming (MIP) model is proposed to assign seats to passengers. Several families of valid inequalities and preprocessing steps are proposed to strengthen the MIP formulation, which represents a substantial contribution to the literature on group seat assignment problem. The validity of the model and the effectiveness of the valid inequalities have been evaluated using real-life data from Indian Railways. The computational results demonstrate a significant reduction in the risk of contagion and an increase in seat utilization compared to the current approach employed by operators.

Cruise revenue management: cross-discipline literature review and development of an integrated cruise revenue management framework

Purpose: 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. Design/methodology/approach: 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. Findings: 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. Research limitations/implications: 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. Originality/value: 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. © 2023, Emerald Publishing Limited.

A longitudinal analysis of revenue management strategies and measures implemented in the hospitality industry during the COVID-19 crisis

Purpose: This research aims to answer two major research questions related to the COVID-19 crisis from a longitudinal approach: What is the revenue management (RM) role during the different periods subject to analysis? What are the RM strategies and measures implemented during this crisis in contrast with a non-crisis context? It also aims to propose an RM implementation model that provides a contingency plan to face future crises. Design/methodology/approach: This qualitative study, following a longitudinal approach, analyses three round-table discussions with 11 internationally renowned experts during three key scenarios of the COVID-19 crisis: the lockdown period (from March to June 2020) and the following two summer seasons (the post-lockdown period): Post-lockdown I (the summer campaign, 2020) and Post-lockdown II (the summer campaign, 2021). Based on a deductive approach, thematic analysis is conducted using NVivo. Findings: Further professionalisation of revenue managers, which has enabled the correct application of strategies and measures, highlighting the importance of not lowering prices, the flexibility of booking conditions, the development of other sources of income and the increase in the value of services, amongst others, are key factors in managing this crisis. The longitudinal analysis carried out in three different periods of this crisis shows how these measures have evolved and the contrast with RM application in a non-crisis context. The revenue manager's leadership and proactivity, the holistic organisation of RM marketing, commercial and sales departments and the quick adaptation of RM systems (RMSs) by modifying their algorithms are essential to reducing the impact of COVID-19 on the hospitality industry. This crisis has led the industry to rethink processes and strategies and to increase digitalisation. The proposed model, which considers the various RM strategies and measures implemented during COVID-19 in contrast to a non-crisis context, is the cornerstone for developing a graded contingency plan to face future crises. This research sheds light on the widely discussed role of RM during this crisis. Research limitations/implications: This study has various limitations. First, the three round-table discussions were held online due to the health crisis, and the chosen webinar format may have biased the participants' answers due to its public nature. Second, the survey was carried out in Spanish. Despite the strong international profiles of the participants, cultural distortion may appear, suggesting that the research should possibly be extended to other cultural contexts in the future. Third, some of the participants were unable to attend all the round-table discussions due to their professional duties, so people with similar profiles were invited to the rest of the sessions. Practical implications: The revenue manager's leadership and proactivity, the holistic organisation of RM marketing, commercial and sales departments and the quick adaptation of RMSs by modifying their algorithms are essential to reducing the impact of COVID-19 on the hospitality industry. This crisis has led the industry to rethink processes and strategies and to increase digitalisation. The proposed model, which considers the various RM strategies and measures implemented during COVID-19 in contrast to a non-crisis context, is the cornerstone for developing a graded contingency plan to face future crises. This research sheds light on the widely discussed role of RM during this crisis. Originality/value: This work contributes to the literature by providing a model that considers the various RM strategies and measures implemented during COVID-19 in contrast to a non-crisis context. The novelty of this research is mainly found in the conducting of a deductive and longitudinal study considering previous research focussed on RM strategies applied during the COVID-19 crisis and supplementing it with new measures by applying qualitative techniques. © 2023, Emerald Publishing Limited.

Does historical data still matter for demand forecasting in uncertain and turbulent times? An extension of the additive pickup time series method for SME hotels

Demand forecast accuracy is critical for hotels to operate their properties efficiently and profitably. The COVID-19 pandemic is a massive challenge for hotel demand forecasting due to the relevance of historical data. Therefore, the aims of this study are twofold: to present an extension of the additive pickup method using time series and moving averages;and to test the model using the real reservation data of a hotel in Italy during the COVID-19 pandemic. This study shows that historical data are still useful for a SME hotel amid substantial demand uncertainty caused by COVID-19. Empirical results suggest that the proposed method performs better than the classical one, particularly for longer forecasting horizons and for periods when the hotel is not fully occupied. © 2023, The Author(s).

EMSRtrc: relaxation of booking limits by total revenue control for expected marginal seat revenue.

The Covid-19 pandemic has negatively affected life worldwide and caused catastrophic loss of life. It has also been harming the economic activities of businesses, and airline companies are among the sectors most affected by this situation. One of the goals for survival in such a situation is to make the best in airline revenue management (ARM). The most helpful model for ARM is Expected Marginal Seat Revenue (EMSR), widely used in the literature and industry. In this study, the simple and effective models that simulated EMSRa, EMSRb, and EMSRc were developed, called EMSR Total Revenue Control (EMSRtrc). The proposed three models aim to keep the simplicity of the original EMSR models while creating a new perspective and methodology. The developed EMSRtrc models were tested with numerical examples and compared with EMSRa, EMSRb, and EMSRc models proposed previously in the literature. Numerical examples show that the developed EMSRtrc models perform better than the EMSRa, b, and c. For the minimum revenue category, the developed EMSRtrc models exhibit outstanding performance. The results show that the proposed models guarantee a higher minimum revenue of 9.900, 11.619, and 2.537%, respectively. The EMSRtrc models have generated higher revenue and achieved a higher load factor rate of up to 98% simultaneously. Considering the third numerical example, the approximate number of empty seats is 1.3 for the EMSRtrc-(a), 2.65 for the EMSRtrc-(b), and 7.85 for the EMSRtrc-(c). The overall results demonstrate that the proposed model is an effective tool for ARM.

Will COVID-19 be the trigger point for developing visitor attraction revenue management?

Purpose The purpose of the paper is to explore how the effects of the COVID-19 pandemic will influence the development of revenue management practice in the visitor attractions sector. Design/methodology/approach This viewpoint paper builds on the argument that tracking previous patterns of behaviour and trends can be used to predict future actions and developments. Findings The paper identifies how historically the development of revenue management practice has been driven by major external trigger points often linked to sudden increases in competitive pressures, such as the deregulation of the airline industry, and expands on this to argue that the pandemic is one such trigger point that has fundamentally changed the approach to revenue management through a refocusing on key principles to manage demand and that this could potentially accelerate its development within the visitor attraction sector. Originality/value Pre-COVID, the practice of revenue management in the visitor attraction sector was underdeveloped, and the opportunities to develop revenue management had not been discussed in the academic literature. This paper suggests that the challenges of the pandemic that forced visitor attractions to focus on visitor demand management can now begin to be extended to incorporate the management of revenue and will consequently be of value for academics and practitioners.

How the hospitality industry reacts to COVID-19: structural, managerial and tactical factors

This paper investigates hoteliers’ short-term recovery strategies during the pandemic. Stemming from management crisis theory and the resource-based view of the firm, this article focuses on two environments differently hit by COVID-19, i.e. London and Munich. The findings show that hotels with a more managerial approach have more proactively applied dynamic pricing strategies. When dealing with high severity levels of the pandemic, hoteliers make use of a more streamlined booking portfolio to cope with the crisis. We provide theoretical implications and actionable managerial levers for hoteliers and the wider pricing community on how to maximize revenues during the pandemic.

Demand change detection in airline revenue management

Demand shocks—unobservable, sudden changes in customer behavior—are a common source of forecast error in airline revenue management systems. The COVID-19 pandemic has been one example of a highly impactful macro-level shock that significantly affected demand patterns and required manual intervention from airline analysts. Smaller, micro-level shocks also frequently occur due to special events or changes in competition. Despite their importance, shock detection methods employed by airlines today are often quite rudimentary in practice. In this paper, we develop a science-based shock detection framework based on statistical hypothesis testing which enables fast detection of demand shocks. Under simplifying assumptions, we show how the properties of the shock detector can be expressed in analytical closed form and demonstrate that this expression is remarkably accurate even in more complex environments. Simulations are used to show how the shock detector can successfully be used to identify positive and negative shocks in both demand volume and willingness-to-pay. Finally, we discuss how the shock detector could be integrated into an airline revenue management system to allow for practical use by airline analysts. © 2022, The Author(s), under exclusive licence to Springer Nature Limited.

The Antecedent Factors for Distribution of Improving Hotel Performance During Covid-19: Evidence from Five-Star Hotels in Bali-Indonesia

Purpose: Since the emergence of the Covid-19 pandemic, almost all the hospitality industry has experienced a decrease in the distribution of room occupancy. Therefore, this study aims to examine how to improve the performance of 5-star hotels in Bali by involving market orientation, revenue management orientation, competitive advantage, dynamic capability, and pricing capability. Research design, data and methodology: This study involved 127 managers in 62 five-star hotels in Bali. Analysis of this study using structural equation modelling (SEM) with SmartPLS software. Results: This study reveals that the performance of five-star hotels in Bali is influenced by factors such as market orientation, revenue management orientation, competitive advantage, dynamic capability, and pricing capability. In addition, revenue management orientation, competitive advantage, and dynamic capability have been shown to mediate the effect of market orientation on the performance of five-star hotels in Bali. Finally, pricing capability has been proven to have not been able to increase the revenue and performance of five-star hotels in Bali. Conclusions: Hotel performance is largely determined by several important factors which include market orientation, revenue management orientation, competitive advantage, dynamic capability, and pricing capability. This study provides important implications for hospitality practitioners to improve the distribution of hotel performance. © 2022. The Author(s). All Rights Reserved.

Revenue Management Within COVID-19

Hotels want to provide the best service to its customers, making them feel unique, and adding value and self-fulfilment to their lives. These requirements demand high performance and efficiency. Revenue Management (RM), being mutually an art and a technique, can be a practice to help decision making enhancing profitability as well as Human Resources wellbeing in Hotels. Computer systems to support RM are critical and industry 4.0 can play an important role in a new industrial revolution era based on connection between virtual and real world. This study intends to contribute to empirical evidence about the existing Information Technology Communications in the Portuguese hotel units, which are directly related to the revenue. The study centred on the validated response of 120 hotels located in Portugal showed that RM support systems in general is an area in continuous growth and is increasingly being introduced in Portuguese hotels, which already adhere to their price management support systems. However, even if most of the units use Property Management System (97%), Channel Manager (91%) and Booking Engine (94%), in what concerns Revenue Management System most hotels (51%) do not use it. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Pricing Strategies of Porto's Airbnb New Listings

Airbnb hosts' pricing decisions are the choices hosts make when setting the daily rate for their listing of properties. Some Airbnb hosts have a long run approach, charging lower prices to attract more customers and achieve higher occupancy rates, while others have a short-run approach, charging higher prices to maximize the short-run opportunities from the market. The pricing strategy of Airbnb hosts is the key to their eventual success and plays an important role, since it influences their relationship with customers. Airbnb listings can be hard to price. Therefore, each Airbnb host faces an important decision when entering the market: What is the perfect daily rate to charge such that to achieve their goal? Major aspects, such as property location, type (private room, entire home, etc.) and amenities, target customers, other Airbnb competitors, thinking like a guest, the safety and beauty of the neighborhood, seasonality, etc., must be considered. Considering Airbnb's exponential growth since it started in 2007, it is obvious that establishing a suitable pricing strategy is vital for any new host. The present paper uses information from the new listings in 2020 to investigate different hypotheses that explore the pricing strategies of Airbnb hosts for their new listings on the market. This study highlights, on one hand, the great need for Airbnb to encourage dynamic pricing among its new hosts and, on the other hand, the challenges faced by these hosts when they establish the price. An important characteristic of this article is the set of theoretical and methodological implications for the pricing strategy for the new Airbnb new hosts. Furthermore, this document reinforces the idea that the pricing strategy differs between cities and countries, emphasizing the strategy in the case of the new Airbnb new hosts.

Outsmarting Human Design in Airline Revenue Management

The accurate estimation of how future demand will react to prices is central to the optimization of pricing decisions. The systems responsible for demand prediction and pricing optimization are called revenue management (RM) systems, and, in the airline industry, they play an important role in the company’s profitability. As airlines’ current pricing decisions impact future knowledge of the demand behavior, the RM systems may have to compromise immediate revenue by efficiently performing price experiments with the expectation that the information gained about the demand behavior will lead to better future pricing decisions. This earning while learning (EWL) problem has captured the attention of both the industry and academia in recent years, resulting in many proposed solutions based on heuristic optimization. We take a different approach that does not depend on human-designed heuristics. We present the EWL problem to a reinforcement learning agent, and the agent’s goal is to maximize long-term revenue without explicitly considering the optimal way to perform price experimentation. The agent discovers through experience that “myopic” revenue-maximizing policies may lead to a decrease in the demand model quality (which it relies on to take decisions). We show that the agent finds novel pricing policies that balance revenue maximization and demand model quality in a surprisingly effective way, generating more revenue over the long run than current practices.

A cross-cultural study of competitive intelligence in revenue management

This paper extends the examination of competitive intelligence to revenue management. Revenue management decisions are contingent upon the actions and reactions of competitors. The current study used a cross-cultural approach that compared the use of competitive intelligence by US and Turkish revenue managers by conducting a qualitative study of revenue managers in these locations. Both sets of revenue managers share a similar definition of competitive intelligence and use technology to gather competitive intelligence. The findings also suggest integrity issues for data in Istanbul and that ethical challenges are a central part of competitive intelligence usage.

An optimization model to assign seats in long distance trains to minimize SARS-CoV-2 diffusion.

The unprecedented spread of SARS-CoV-2 has pushed governmental bodies to undertake stringent actions like travel regulations, localized curfews, curb activity participation, etc. These restrictions assisted in controlling the proliferation of the virus; however, they severely affected major economies. This compels policymakers and planners to devise strategies that restrain virus spread as well as operationalize economic activities. In this context, we discuss some of the potential implications of seat inventory management in long-distance passenger trains and create a balance between operators' operational efficiency and passengers' safety. The paper introduces a novel seat assignment policy that aims to mitigate virus diffusion risk among passengers by reducing interaction among them. A mixed-integer linear programming problem has been formulated that concomitantly maximizes the operator's revenue and minimizes virus diffusion. The validity of the model has been tested using real-life data obtained from Indian Railways. The computational results show that a mere 50% capacity utilization may distress operators' economics and prove ineffectual in controlling SARS-CoV-2 transmission. The proposed model produces encouraging results in restricting virus diffusion and improving revenue even under 100% capacity utilization.

Revenue management during the COVIDization of the economy

The purpose of this article is to prove the need to perceive revenues as a manageable variable by applying an active approach to companies' management during the COVIDization of the economy. In this regard, the article illustrates the role of revenues as a factor and as a result. Revenues underlie the formation of all major financial indicators. They are key measures of a company's growth and performance. This dual nature of revenues is revealed in the context of economics, accounting and financial management. Their importance determines the need to adopt an active approach to revenue management of the economy during COVID-19 pandemic or other similar future occurrences. From a theoretical point of view, the active approach has been justified in the context of the classical strategic management methods emphasising the leading role of marketing. The main research hypothesis tested is that in the conditions of a sharp change in the economy during COVIDization, the importance of the active approach of operating revenue management as the main variable (KPI), cannot be understated. © 2022. Transnational Press London. All Rights Reserved.

The Macroeconomic Results of Diligent Resource Revenues Management: The Norwegian Case

Many commodity-exporting countries saw their revenues plummet and experienced fiscal deficits during the pandemic. The economic rebound will restore resource exports/revenues and a new round of debate will be initiated on revenues utilization. Countries will decide either to internalize revenues or capitalize them with investments abroad. Our autoregressive distributed lag (ARDL) models provide evidence of the benefits Norway enjoys since it has not internalized revenues. The currency rate, long-term bond yields, and GDP growth are insulated from prices volatility. Furthermore, the country can absorb currency appreciations/devaluations and long-term credit rate hikes through government expenditure. However, monetary steering is favored in the long term (absorbs yield increases), while in the short run it can allow for speculative activities by credit investors. Countries should not internalize resource revenues to avoid experiencing decreased competitiveness and economic growth and increased credit rates. However, the temptation will be high enough since deficits and support packages cost a lot. This study also includes years of low prices. Thus, our research reveals the extent and limitations of diligent revenue management from a country considered as a role model.

Implementing dynamic revenue management in hotels during Covid-19: value stream and wavelet coherence perspectives

Purpose: Practicing flexible revenue management (RM) at hotels during Covid-19 is essential. The well-performed hotels ponder how to transform the target from revenue to net profits. This paper aims, first, to develop a value stream mapping (VSM) model for a productive RM based on six key drivers: organizational culture, demand forecasting, dynamic distribution channels, competition breakdown, dynamic and customized pricing and daily reviewing, and, second, to examine the nexus between RM and hotel’s efficiency during Covid-19 using the wavelet analysis (WA) to visualize this relationship’s time and frequency-based lead–lag dynamics. Design/methodology/approach: Using time-series data, a multiple case study of 31 luxury hotels in Egypt was applied based on semi-structured interviews and self-administered questionnaires. Findings: The first phase results showed that consensus toward the RM framework was achieved, regardless of current challenges, indicating that RM managers and scholars could use it. In Phase 2, the WA confirmed a positive correlation and significant influence between Covid-19 and RM practices at most business cycle frequencies. Furthermore, overall high causal relationships between RM practices and hotel efficiency were discovered in the short and medium terms and through different occurrence cycles. Though, the dynamic pricing in the long term was apart from this relationship. The causal effects between Covid-19 and hotel efficiency are not observable in the long-run spectra, indicating that resilience efforts with Covid-19 perhaps mitigated the impact. Research limitations/implications: Hotel managers could use the RM model developed from this study during the downturn to improve efficiency. The outcome may lead to the recovery of the hotel market and the whole economy. WA maps display possible directions for hotel managers to be more efficient based on the time and frequency domains. Originality/value: This study shows opportunities for RM implementation during Covid-19 based on the VSM and the WA approaches in hotels. © 2022, Emerald Publishing Limited.

Optimization of Capacity Allocation Models with Effort Dependent Demand in Global Supply Chain

In a demand driven market, optimal allocation of capacity to the demand has been one of the major issues. In this paper, we consider a single global freight firm allocating its capacity to its own regional sales offices. The firm sells cargo space based on two types of contracts: long-term and spot sales. Regional sales offices utilize their effort to generate more demand in their designated region. In other words, it is assumed that the demand is dependent on their efforts. First, we find a closed-form solution for the optimal level of the efforts of a single sales office in a specific region. Then, we study the case when the firm allocates its limited total capacity to two sales offices. We investigate different methods of capacity allocation: decentralization, centralization, and mixed, by conducting numerical studies. Different from the traditional finding, we suggest that the decentralization method is not always dominated by the centralization method.

An empirical assessment of pricing efficiency across the European rail market

Over the last decades liberalization in the European Rail market has led to a significant development of the industry, an increase in competition and an overall improvement of the service offered. In this context the implementation of dynamic pricing policies plays a crucial role. The main aim of this work is to empirically assess whether the Rail liberalization reforms in the EU have enhanced the adoption of dynamic pricing policies by the companies operating in the European Passenger Rail market. The study focuses on 14 European Rail companies. The efficiency of a dynamic pricing approach was measured through eight performance indicators built on data collected during July 2020. The impact of the Covid-19 crisis on the pricing strategies was also investigated by comparing the offers before and after the first wave of the pandemic. Companies were ranked in terms of pricing efficiency by using an outranking methodology. The results clearly show that there are front runners in terms of pricing efficiency, other companies which are midway through the journey to full efficiency and other operators still anchored to legacy fixed pricing, which have room to improve their pricing methodology.