2013 Compendium

A compendium of 2012 publications of the Center for Hospitality Research

An approach to revenue management strategies in the hospitality industry

YM is characterized as integrating the techniques, formulas, and strategies used to manage inventory, pricing, and sales policies. When linked to the hotel and tourism sector, YM manages availability, accommodation control, and discounts applied to overnight stays. RM is the evolution of YM, where using the full potentiality of the elements allows for maximizing revenue in periods of high demand and maximizing demand in periods of low revenue. RM is based on demand forecasting, price and inventory management, distribution channels, and revenue management performance. The world of hotel distribution is very complex and there is no way to control it. The Revenue Manager must be vigilant for the large price disparities in the various distribution channels. The distribution channels allow the hotel to reach a wider market share and an increase its competitive range. The Crowne Plaza Porto has a wide network of distribution channels represented by direct bookings and contracted distributors: Direct reservations come from four sources: Central Reservations Office (CRO), direct contact with the reservations department, the IHG brand website, and the mobile app. This research presents a qualitative methodology, applied to the Hotel Crowne Plaza Porto, whose purpose is to identify the segmentation introduced by two main segments: Individuals and Groups. The results of this research suggest that each of these segments is divided into several subgroups according to the specificity of their characteristics, and adequately identified, allowing the hotel's Revenue Manager to apply different strategies to the different customer groups, equally justified.info:eu-repo/semantics/publishedVersio

Exploring online prices with an advance booking horizon on Booking.com

The online market enables hotels to enhance their visibility and drive up their revenue. This study analysed both the average room price and price count (i.e. the sum of the number of prices that hotels offer) on Booking.com for a period of 300 days prior to check-in, with data classified by official hotel category. Hotels’ number of rooms, day of the week, room type, room capacity (i.e. maximum number of guests per room) and length of stay were also tracked. This research was based on a stratified sample of hotels gathered by using random sampling and proportional allocation, as well as defining the strata by hotel categories. The dataset included 1,353,751 records. The results reveal that channel management activities are an important area of hotels’ operations, which generate a considerable workload in terms of the time devoted to updating data and other related tasks. However, hotels’ participation in online channels does not always match their importance in the market as measured by their relative numberof rooms. Most of the variables under study have a significantpositiveimpact on prices, except for hotels’ number of rooms, which failed to follow any discernible pattern of influence.FCT: UIDP/SOC/04020/2020;info:eu-repo/semantics/publishedVersio

Hospitality Sustainability Reporting: Slow, Steady Progress

In a far-reaching examination of the current status of sustainability reporting in the hospitality industry, the 2012 Cornell Sustainability Roundtable covered issues relating to sustainability reporting, customer perceptions of sustainability, supply-chain issues (both up and down the chain), the challenges of energy and water benchmarking, and innovation and best practices. The discussion highlighted the industry’s continuing efforts to provide the most useful possible information on its sustainability initiatives in a format that is useful for stakeholders at all levels. Of those stakeholders, guests’ attitudes seem inscrutable, since they say they support sustainability but often do not follow up on that principle in their purchasing decisions. Finding a key to unlock the guest conundrum remains a goal of all hospitality operators

A call for exploratory data analysis in revenue management forecasting: A case study of a small and independent hotel in The Netherlands

Using five years of data collected from a small and independent hotel this case study explores RMS data as a means to seek new insights into occupancy forecasting. The study provides empirical evidence on the random nature of group cancellations, an important but neglected aspect in hotel revenue management modelling. The empirical study also shows that in a local market context demand differs significantly per point of time during the day, in addition to seasonal monthly and weekly demand patterns. Moreover, the study presents evidence on the nonhomogeneous Poisson nature of the probability distribution that demand follows, a crucial characteristic for forecasting modelling that is generally assumed but not reported in the hotel forecasting literature. This implies that demand is more uncertain for smaller than for larger hotels. The paper concludes by drawing attention to the critical and often overlooked role of exploratory data analysis in hotel revenue management forecasting.Coherent privaatrech

Revenue Management, Dynamic Pricing and Social Media in the Tourism Industry: A Case Study of the Name-Your-Own-Price Mechanism

The application of revenue management (RM) is changing more rapidly than ever before, driven as an important factor of the daily operation to keep prices competitive and to create real-time optimal pricing. In the age of the Internet and social media, negotiated fixed rates have become outmoded. Consumers now have access to online rate comparisons and real time reviews. They think more strategically when making purchasing decisions. Thus, they become more demanding. This research provides an empirical study of revenue management and pricing with an emphasis given to the hospitality industry. The aim of this research is to examine the gap between the theoretical approach and the empirical analysis, the rationality between the implementation of dynamic pricing approaches and the impact on the customer. Furthermore, the research examines the perception of consumers’ willingness to pay when using the Name-Your-Own-Price (NYOP) mechanism, which allows customers to have a greater influence on the amount they are prepared to pay. Instead of posting a price, the seller waits for a potential buyer’s offer, which he or she can either accept or reject. Finally, this study examines, whether the use of social media plays a decisive role in the online purchase environment used by the hospitality sector and the effect it has on a consumer’s willingness to pay. Accordingly, hotel revenue managers will be able to use the findings of this study to effectively plan their short-term, and long-term pricing strategies to generate a stronger revenue management performance for their property, namely to increase the RevPAR (revenue per available room). The research can be useful to businesses, as empirical data and tests were employed to determine what kind of impact the different pricing policies have on the long-term profit optimization. These practical and theoretical elements of the field reinforce each other‚ as well as to a large extent, the constructive interplay of theory and practice. The research is twofold, the holistic approach, which discusses the development of the theoretical dimension, is complemented by the practical analysis of the collected data of the surveys. This approach ensures the relevant observation of ‘real-time’ data and the evaluation of the set of hypotheses. The study conducted two large scale interrelated structured surveys. The first structural survey (NYOP) provides a better understanding of the final consumer, by using the name-your-own-price mechanism and by observing the extended role of social media in the booking procedure. Hypotheses were tested and in the second survey in-depth data from revenue managers and executives working across the tourism industry was collected, in an attempt to measure the use of pricing strategies within the industry. The research contributes to the theory by empirical testing how the extended RM objectives influence RM and pricing. It provides a clear picture of the necessary elements for a successful implementation of pricing strategies. Finally, the study has implications for the consumer. Thus, the researcher investigates consumer’s perception to the NYOP model and the expanding role of social media to the consumer-booking pattern

A Study in Three Practical Management Science Problems

This study of practical problems in Management Science (MS) describes novel mathematical models for three different decision settings. It addresses questions of: (a) what optimal route should be taken through a time-windows and topographically complex network; (b) what optimal sequencing of scheduled surgeries best coordinates flow of patients through central recovery; and (c) what prices should be charged and what stock amounts should be produced for two markets or channels to maximize profit explicitly, given various capacity and uncertainty conditions. The first problem is in a sport analytics context, using a novel Integer Programming and big data from Whistler-Blackcomb ski resort. The second is to coordinate dozens of surgeries at London Health Sciences Centre, using a novel Constraint Programming model mapped to and parameterized with hospital data, including a tool for visualizing process and patient flow. The third problem is relevant to almost any business with a secondary market or sales channel, as it helps them identify profit optimal prices based on simple demand estimates and cost information they can easily provide for their own setting. The studies use fundamentally different operational research techniques, in each case uniquely extended to the problem setting. The first two are combinatorial problems, neither one extremely beyond human cognitive ability, and both involving lots of uncertainty, and thus the sort of problem managers tend to dismiss as not efficient or practical to solve analytically. We show in the first study that vastly more skiers could achieve the challenge by following our route recommendation, unintuitive as are some of its elements, initially. In the second study, our scheduling model consistently outperforms currently unstructured-independent approach at the hospital. The final study is mathematical but demonstrates that by considering distinct market costs in pricing a firm can invariably earn more profit