An introduction to helpful forecasting methods for hotel revenue management

Revenue management is a key tool for hotel managers’ decision-making process. Cutting-edge revenue management systems have been developed to support managers’ decisions and all have as an essential component an accurate forecasting module. This paper aims to introduce new time series forecasting models to be considered as a tool for forecasting daily hotel occupancies. These models were developed in a state space modelling framework which is capable of tackling seasonal complexities such as multiple seasonal periods and non-integer seasonality. An empirical study was carried out to illustrate how a practitioner may apply and compare the performance of different models when forecasting a hotel’s daily occupancy. Results showed that the trigonometric model based on the new modelling framework generally outperformed the majority of the other models. These findings are potentially useful to the entire revenue management community facing the challenge of accurately forecasting a hotel’s daily demand.     

Relationship or revenue: Potential management conflicts between customer relationship management and hotel revenue management

The concepts of customer relationship management (CRM) and revenue management (RevM) have been embraced by managers in the hospitality industry although, in practice, companies may find it difficult to accommodate both fully. This paper examines the compatibility between the two practices and discusses the possible management conflicts that occur from both account managers’ and revenue managers’ viewpoints. Findings gathered from an international hotel company reveal several causes of potential management conflicts including: management goals, management timescales, perceived business assets, performance indicators and management foci between CRM and RevM due to divergence occurring in managers’ priorities and in their approaches to achieving their individual set goals. These differences have rarely been comprehensively investigated in previous studies, yet are vital in integrating CRM and RevM practices.     

On revenue management and the use of occupancy forecasting error measures

This study aims to draw the attention of the revenue management academic community to inherent problems in forecasting accuracy measurement, and to initiate a critical discussion about forecast quality assessment in hotels. An exhaustive, literature-based set of seventeen forecasting accuracy measures was applied to hotel daily occupancy forecasting data of 2043 pairs of computer and human forecast/actuals, across multiple forecasting horizons. The empirical analysis demonstrates endemic inconsistencies across the accuracy measures, and a plethora of theoretical and practical challenges with regard to total hotel, as well as customer segment level forecast accuracy assessment. The analysis illustrates the difficulty of interpreting conflicting results, as well as issues like level of data aggregation and multiple forecasting horizons. The paper concludes by briefly discussing a more comprehensive approach to hotel forecasting quality assessment framework and serves to warn hotel revenue management academics, practitioners and solution providers against the unconsidered use of accuracy measures.     

Influences of consumer characteristics on fairness perceptions of revenue management pricing in the hotel industry

Fairness perceptions play an important role in customers’ behavior, and this study explores which consumer characteristics influence fairness perceptions of revenue management (RM) pricing in the hotel context. To examine such differentiating characteristics, the study conducts a logit analysis by comparing two groups: one group of customers who consider hotels’ RM practices to be fair and the other group considers the practices to be unfair. The findings provide an opportunity for hotel managers to identify customers’ particular characteristics that affect customer's perceptions of the fairness of hotels’ RM pricing practices.     

Strategic and tactical price decisions in hotel revenue management

Dynamic pricing techniques allow using a number of variables in a tactical way compared to standard catalogue prices. This study merges in a conceptual model the relevance of the tactical and the strategic dimension of these variables, classified according to their tangible, reputational or contextual nature.To empirically validate the hypotheses, a database of 21.596 price observations was retrieved from booking.com. The study presents a hedonic price function, using the Shapley-Owen decomposition of the R-squared to elicit the importance of each group of factors. Further, a hierarchical cluster analysis measures the presence of heterogeneity across operators.The results show that online reputation is gaining importance over the traditional star rating. Despite the tangible variables remain of paramount importance, the findings suggest the relevant role of contextual variables in short-run price variations. The players operating in the tourism and hospitality industries should integrate these findings when designing pricing strategies.     

Meeting revenue management challenges: Knowledge,skills and abilities

Hospitality industry increasingly recognizes importance of integrating revenue management into their operations and significance of their staff to do so. Yet revenue managers face major challenges from both internal and external sources. Hence revenue staff dealing with several sophisticated problems should possess various knowledge, skills and abilities (KSAs) to enable them effectively overcome these obstacles. However which specific capabilities are required to what extent are not clear. Therefore this study aims to match the challenges that are faced by hotel revenue managers with KSAs required in managing inventory and prices. A two step qualitative method is adopted; first 14 revenue managers were interviewed and secondly a focus group with eight participants was conducted in order to identify challenges and competencies required in improving revenue management effectiveness. Thus this study offers a typology of challenges faced by revenue managers and it also identifies KSAs that are required by revenue management staff.     

Game theoretic pricing models in hotel revenue management: An equilibrium choice-based conjoint analysis approach

This paper explores a game-theoretically founded approach to conjoint analysis that determines equilibrium room rates under differentiated price competition in an oligopolistic hotel market. Competition between hotels is specified in terms of market share functions that can be estimated using multinomial logit models of consumer choice. The approach is based on choice-based conjoint analysis that permits the estimation of attributes weights (“part-worths”) for an additive utility formulation of the utility function. From this, room rates that equilibrate the market, conditioned on the differences in services and facilities offered by competing hotels, can be determined. The approach is illustrated by an example.     

Application of revenue management practices to the theme park industry

Revenue management (RM) has been an essential strategy to maximize revenue for many capacity-limited service industries. Considering the common industry characteristics of traditional RM industries, the nature of the theme park industry suggests potential for enhancing revenue by exercising a variety of RM techniques. This study suggests practices for theme park operators for successful RM application. In addition, this study examines how customers perceive RM practice in the theme park industry compared to a traditional RM industry, hotel industry. The findings indicate that customers seem to perceive RM practice in the theme park industry as relatively fair practices as similarly perceived for the hotel industry. The findings are encouraging for the theme park industry because a relatively similar level of its customers’ perceived fairness of the RM practice compared to the hotel industry suggests that adoption and implementation of the RM practice has great potential to become successful as it has been in traditional RM industries, such as hotels.     

Hotel revenue management and the Internet: The effect of price presentation strategies on customers’ willingness to book

A decision that is intrinsic to the application of hotel best available rate (BAR) pricing is how to present the BARs for individual nights within a multiple-night stay to prospective hotel guests. We discuss two alternative price presentation strategies, a blended and a nonblended rate approach, and examine their effect on customers’ willingness to pay in the context of Internet-based reservation requests. Study findings indicate that a nonblended rate presentation approach generates higher willingness to book ratings than a blended rate presentation approach. Furthermore, when it comes to nonblended rates, familiarity with BAR pricing moderates the effect of rate sequence on customers’ willingness to book.     

Marketing research and revenue optimization for the cruise industry: A concise review

This paper presents a concise review of the cruise industry mainly from marketing research and revenue optimization prospects. In recent years, the cruise industry has experienced an exciting growth. However, as one of the fastest growing and most profitable categories in the entire leisure market, this industry has hardly received any research attention. Given the limited academic articles, this paper presents a concise review about this budding research topic. First of all, a discussion about global cruise industry is conducted. Then, academic studies of the cruise industry on general marketing research, revenue management, itinerary design/optimization, optimal market segmentation, demand infiltration and economic issues are reviewed. Finally, some promising directions for future research are presented.     

Knowledge sharing in revenue management teams: Antecedents and consequences of group cohesion

The practice of Revenue Management has received widespread acceptance in the international hospitality industry yet a lack of best practice in terms of organizational integration persists. This paper follows the notion that revenue management is first and foremost a human activity, dependent on knowledge exchange and concerted decision within revenue management teams. One critical attribute of effective teams is group cohesion. The authors contrasted communication networks of 38 revenue management teams by means of social network analysis to identify the antecedents and consequences of group cohesion. It was found that industry employment, age and revenue management experience define the structure of communication networks and that awareness of other's expertise is central in explaining differences team performance across the sample. The findings highlight the issue of knowledge asymmetry in teams and suggest that the Revenue Manager occupies a more active role as an information broker in order to enhance group decision making.     

Revenue management forecasting: The resiliency of advanced booking methods given dynamic booking windows

Forecasting is the initial component of the hospitality revenue management (RM) cycle. The accuracy of the forecast is critical for RM systems to make appropriate recommendations to optimize revenue. Over recent years the industry has cited shifting booking windows due to a variety of macro (e.g., technology and economy) and micro (e.g., promotion) factors. These shifts pose challenges for RM forecasting algorithms particularly in the domain of pick-up based techniques. In this paper, we review the literature on hotel RM forecasting, particularly with respect to popular techniques used in practice. We then introduce a neural network approach to the advance booking environment to address issues related to booking window shifts. The models are estimated and tested for accuracy, and then re-tested years later after the booking window has shifted. The results are synthesized with discussion as to which models are more suitable for forecasting in dynamic booking windows.     

Availability management of hotel rooms under cooperation with online travel agencies

Hotels are required to pay high commission fees when cooperating with online travel agencies (OTAs) to manage online marketing channels. Thus, to maximize their revenues, hotels protect their income through their own (traditional) marketing channels and save on considerable commissions by optimizing room availability for their cooperative OTAs. The present paper proposes a method to manage such availability in the context of a hotel cooperating with an OTA on room booking service. Customers can make reservations directly through the distribution channel of the hotel or indirectly through the OTA, if applicable, during the selling period. The hotel then forecasts room demand base on distribution information after receiving enough room bookings and optimizes room availability with respect to its maximum revenue by determining whether on-hand rooms are available for the OTA. Results indicate when hotel rooms become unavailable for the cooperative OTA. Numerical studies reveal that this method is conducive to the improvement of hotel revenue.     

Revenue management strategies under the lunar–solar calendar: Evidence of Chinese restaurant operations

This paper discusses the lunar–solar calendar-driven festivals that affect Chinese restaurant operations. In-depth interviews and a survey were carried out with 50 catering professionals to provide information that was subsequently used to estimate the change of restaurant turnover due to the identified festivals. Four core common lunar–solar calendar-driven festivals that create more demand for dining out across China were identified. They generated extra revenue, which was nearly 10% of total annual business for restaurants. The study also ascertained 21 measures related to revenue management strategies to cope with these demand variations. In addition, a new restaurant revenue management strategy framework was developed. Recommendations based on this study were suggested to multi-functional restaurants and hotel systems.     

Developing a Novel Hybrid Model for Industrial Environment Analysis: A Study of the Gourmet and Tourism Industry in Taiwan

This study applies fuzzy set theory in attempting to evaluate important attributes of the tourism and gourmet business environment in Taiwan. This business environment is composed of various attributes that are difficult to measure. To overcome these challenges, we integrated the fuzzy Delphi method, the decision-making trial and evaluation laboratory method, and the analytic network process to evaluate the business environment. We found that the most significant aspect of the tourism and gourmet business environment is human resources and that the least significant aspect of this industry is market development. The most significant criteria are enhanced industry competitiveness and opportunities to develop the industry.     

New performance indicators for restaurant revenue management: ProPASH and ProPASM

Measuring business performance is the first step of the improvement process but without knowledge there can be no purposeful action. Revenue per Available Seat Hour (RevPASH) is an effective and reliable indicator of a restaurant's performance, however, it may not provide the whole picture of a restaurant's business performance. In restaurants, the contribution margin of each menu item is different and it should be taken into consideration when evaluating restaurants’ performance, because the goal of restaurant revenue management is to maximize profit, not just revenue. Although several researchers have explored various issues regarding restaurants’ revenue management (RM) strategy, there has been little discussion on how to measure the performance of RM strategies as they apply to restaurants, except RevPASH. Therefore, this study proposes new metrics, ProPASH (Profit per Available Seat Hour) and ProPASM (Profit per Available Square Meter) and discusses how they can be applied to measure the effectiveness of restaurants’ RM strategies.     

An integrated approach for selecting corporate social responsibility programs and costs evaluation in the international tourist hotel

The purpose of this paper is to present an integrated approach and scientific techniques for corporate social responsibility (CSR) programs selection decisions and costs evaluation in the hotel industry. First, experts are chosen to conduct the analytic structure construction for CSR programs selection by identifying cost and differentiation advantage criteria and CSR program candidates that can benefit society and competitive advantage for hotels. Second, the DEMATEL (Decision Making Trial and Evaluation Laboratory) method is used to detect complex relationships and build a network structure among the cost and differentiation advantage criteria. Third, the ANP (Analytic Network Process) is used where the criteria are dependent. Fourth, the ANP results are applied to ZOGP (Zero–One Goal Programming) formulation to find the optimal CSR program portfolio under limited resources and constrained situations. Finally, ABC (Activity-Based Costing) model is used to calculate each chosen CSR program's costs in order to acquire accurate cost information. The result shows that the improvement on the image of an organization is the major dispatch for driving the international tourist hotel to fulfill CSR goals. The integrated approach can help international tourist hotels’ managers to select CSR programs more scientifically and to make decisions conforming to the reality.     

Establishing attributes of an environmental management system for green hotel evaluation

This study establishes attributes of an environmental management system (EMS) for the hotel industry in Taiwan to create an instrument to help address green hotel auditing. Hotel EMS indicators were initially selected from ISO14000 and nine representative foreign green hotel assessment systems. The Delphi method conducted on twenty five experts with government officials, scholars and hotel managers for item modification to identify the preliminary EMS evaluation framework. An indicator selection process was employed to determine the dimensional indicators of the system. The data analysis reveals that a total of 64 indicators into ten dimensions were identified and prioritized in terms of their relative importance and feasibility. Moreover, 38 indicators are suitable for use and 18 of them should be implemented firstly in Taiwan hotel industry. The results also reveal the comparison with Taiwan government's environmental standards. Finally the EMS approach of this study provides managerial implications for government, hoteliers and consumers to improve their environmental management.     

The impact of information technology on hotel operations,service management and transaction costs: A conceptual framework for full-service hotel firms

This paper develops a conceptual framework that describes the impact of information technology (IT) on service management and transaction costs in full service hotel firms. It details how IT would help such firms to lower operations-related transaction costs. Further, the underpinnings of how IT would impact service management in full service hotel firms is discussed more specifically from a customer satisfaction point of view while focusing on two aspects, i.e. managing customer delight and the customer's role as a co-producer. Propositions are developed and a discussion on the impact of IT on firm profitability from a transaction cost perspective ensues while concluding with managerial implications.     

Determinants of revenue per available room: Influential roles of average daily rate,demand, seasonality and yearly trend

Determining price per room to be charged to customers is an important decision to be taken by hotel management. Hotels frequently change their room rates based on the demand of room, occupancy rate, seasonal pattern, and strategies undertaken by other hotels on pricing. We formulated four models to analyse how various influencing variables, such as hotel price, demand, yearly trend and monthly seasonality influence hotel revenue per available room (RevPar). To analyse a case, we used monthly accommodation statistics for Sweden taken for Swedish Agency for Economic and Regional Growth and Statistics from January 2008 to July 2017. We carried out data analysis using both multiple regression and Multivariate Adaptive Regression Splines (MARS) model and found that application of MARS can help establishing a nonlinear relationship of RevPar with other determining variables in a superior way. We also proposed the possibility of developing a better forecasting model using MARS.