Relevant bibliographies by topics / Hotel Room Rate Pricing

Academic literature on the topic 'Hotel Room Rate Pricing'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Hotel Room Rate Pricing"

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Karunarathne, A. C. I. D., and D. A. C. Silva. "The impact of hotel attributes on room rate in star graded hotels in Colombo, Sri Lanka." Journal of Sustainable Tourism and Entrepreneurship 2, no. 3 (March 25, 2021): 159–70. http://dx.doi.org/10.35912/joste.v2i3.557.

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Abstract Purpose: The purpose of this study was to examine how the availability or absence of different hotel attributes affect the room rate during a given period. This study identified the impact of various hotel attributes on the room rate. Research methodology: Published data on available hotel attributes, and room rates of selected room categories of star-graded hotels in Colombo district, Sri Lanka, were gathered online through booking.com. The Ordinary Least Squares (OLS) method was used to estimate the impact of key determinants under hotel amenities, quality signals, and locational attributes. Results: The results revealed eleven key attributes of the room rate in star-graded hotels, illustrating the positive impact from seven determinants and the negative impact from four determinants. Hotel class or star grade was the most significant determinant in the room rate, which generally determines the pricing behavior and service quality and most of the attributes and characteristics in a hotel. Availability of a business center, location of the hotel, fitness center/spa, total number of rooms in the hotel, room size, and view from room also significantly determined the room rate. Limitations: Booking.com, as the most popular Online Travel Agent (OTA) used in Sri Lanka, it was assumed that the information is frequently updated. The study was extended for the hotels in the Colombo district, and hence, the results were based on the point data, which may not be an islandwide representation or year through data. Contribution: As theoretical applications are underused in pricing and revenue decisions in the Sri Lankan hotel sector, results will lead to advance the decision making of practitioners, and this study will be a complement to the lack of literature in the field of revenue management in Sri Lankan context and may encourage future researchers laying an inspiring beginning.
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Nadia, El-Nemr, Canel-Depitre Beatrice, and Taghipour Atour. "The Determinants of Hotel Room Rates in Beirut: A Hedonic Pricing Model." International Journal of Trade, Economics and Finance 12, no. 2 (April 2021): 33–42. http://dx.doi.org/10.18178/ijtef.2021.12.2.690.

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This work attempts to identify locational, structural and other attributes that have an effect on room rates in Beirut region. Therefore, a sample of 89 hotels were considered in this study. Data were collected from TripAdvisor website during March 2019, considered as a low season in Lebanon. An OLS regression analysis was used to identify significant variables. Results has shown a strong positive significance of star rating category and accessible rooms, and a strong negative significance of centrally located, business and safe labels. Hotel managers are advised to use current findings and analysis to adjust their pricing strategies and communicated image.
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Zheng, Tianxiang, Shaopeng Liu, Zini Chen, Yuhan Qiao, and Rob Law. "Forecasting Daily Room Rates on the Basis of an LSTM Model in Difficult Times of Hong Kong: Evidence from Online Distribution Channels on the Hotel Industry." Sustainability 12, no. 18 (September 7, 2020): 7334. http://dx.doi.org/10.3390/su12187334.

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Given the influence of the financial-economic crisis, hotel room demand in Hong Kong has experienced a significant drop since June 2019. Given that studies on the room rate aspect remains limited, this study considers the demand for hotel rooms from different categories and districts. This study makes forecast attempts for room rates from mid-October of 2019 to mid-June of 2020, which was a difficult period for Hong Kong owing to the onset of the social unrest and novel coronavirus outbreak. This study develops an approach to the short-term forecasting of hotel daily room rates on the basis of the Long Short-Term Memory (LSTM) model by leveraging the key properties of day-of-week to improve accuracy. This study collects a data set containing 235 hotels of the period from various online distribution channels and generates different time series data with the same day-of-week. This study verifies the proposed model through three baseline models, namely, autoregressive integrated moving average (ARIMA), support vector regression (SVR), and Naïve models. Findings shed light on how to lessen the impact of violent fluctuations by combining a rolling procedure with separate day-of-week time series for the hospitality industry. Hence, theoretical and managerial areas for hotel room demand forecasting are enriched on the basis of adjusting room pricing strategies for hoteliers in improving revenue management and making appropriate deals for customers in booking hotel rooms.
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Battiti, Roberto, Mauro Brunato, and Filippo Battiti. "RoomTetris: an optimal procedure for committing rooms to reservations in hotels." Journal of Hospitality and Tourism Technology 11, no. 4 (November 2, 2020): 589–602. http://dx.doi.org/10.1108/jhtt-08-2019-0108.

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Purpose Many hotels allocate guests to specific rooms immediately after reservation. This happens because individual rooms are sold (and there is no concept of room type) or because the assignment is done by hand at reservation or because of a connection with a channel manager, which is immediately fixing the room number after a reservation request. This early allocation is suboptimal, and it causes the unnecessary rejection of some reservations when the hotel has a high occupancy level. The purpose of this paper is to investigate different room allocation algorithms, including an optimal one (called RoomTetris), aiming at higher occupancy levels and profitability. Design/methodology/approach The methodology is based on theoretical results and experimentation. The optimality or the proposed RoomTetris algorithm is demonstrated. Experiments are executed in different contexts, including realistic ones, through the adoption of a hotel simulator, to measure the improvements in the occupancy rate of the optimal and heuristic strategies with respect to random or sub-optimal assignments of rooms. Findings The main results are that smart allocation algorithms can greatly reduce the rejection rate (reservation requests which cannot be fit into the hotel room plan) and improve the occupancy level, the percentage of available rooms or beds sold for the various periods. Research limitations/implications This analysis can be extended by considering cancellations and overbookings. A second possibility to add flexibility in room allocation for hotels having more than one type of rooms is that the hotel can upgrade and offer a high-price room to the customer, which given an even large flexibility to fix rooms by shifting customers to other compatible types. In addition, more complex integrations with revenue management can also be considered, for cases in which the cost of a room depends on the number of guests. Practical implications Given that the difference in occupancy rate of the optimal algorithm is particularly large in high season and high-request periods, periods which are usually associated to higher rates and higher volumes, the proposed algorithm will improve the main financial performance indicators such as revenue per available room by an even bigger multiplier, depending on the hotel pricing policy. Because the room allocation process can be completely automated, the adoption of appropriate smart allocation algorithms represents a low-hanging fruit to be picked by efficient hotel managers. Originality/value To the best of the knowledge this is the first proposal of an optimal algorithm (with proof of optimality) for the considered problem.
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Schwartz, Zvi. "A Dynamic Equilibrium Pricing Model: A Game Theoretic Approach to Modelling Conventions' Room Rates." Tourism Economics 2, no. 3 (September 1996): 251–63. http://dx.doi.org/10.1177/135481669600200304.

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Utilizing the theoretical framework of game theory, this study provides an economic model to describe the process of determining a convention's room rates. It provides a method to infer simultaneously the room rate and the number of rooms allocated at each price level. This approach exploits information both on consumers' utilities and expectations, and on the hotel's perceptions of its markets. Equilibria in pure strategies are derived for various combinations of the market segments' relative size, supply demand ratios, and levels of willingness to pay. The study extends the existing literature on price optimization in hotels by including the customers as active participants in this strategic behaviour framework. The model demonstrates that the effectiveness of price optimization depends on the validity of the assumptions one makes about the segments' characteristics. The model identifies the market conditions under which yield management (allocation of rooms to room rates) maximizes the hotel's revenue. It shows the importance of a credible commitment by the hotel to maintain high room rates as time draws closer to the date of stay and shows how discounts can be used effectively to segment the market.
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Barreda, Albert A., Sandra Zubieta, Han Chen, Marina Cassilha, and Yoshimasa Kageyama. "Evaluating the impact of mega-sporting events on hotel pricing strategies: the case of the 2014 FIFA World Cup." Tourism Review 72, no. 2 (June 19, 2017): 184–208. http://dx.doi.org/10.1108/tr-02-2017-0018.

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PurposeThis study aims to examine the impact of a mega-sporting event “2014 FIFA World Cup” on hotel pricing strategies and performance. Design/methodology/approachThe present project examines the host regions’ response to the 2014 FIFA World Cup which was established by the variance in the main hotel key performance indexes: occupancy, average daily rate, revenue per available room (RevPAR) and supply. Using data gathered from STR, this research distinctly shows how the Brazilian host regions reacted to the World Cup. FindingsResults suggest that the key performance indicators of Brazil’s lodging sector reacted differently to the World Cup. Although all hosting cities experienced significant RevPAR growth because of the increase in hotel room rates during the event, the supply and occupancy performed differed from each city. Research limitations/implicationsResearch is limited to the case of hotel performance at the country level for mega-events. The study focused on the reaction of revenue managers in the Latin America context. Other contexts may generate different results. Practical implicationsThe study helps revenue managers to examine how the FIFA World Cup travel demand affected pricing strategies and revenue management practices in the Brazilian hotel sector in areas undergoing seasonal growths in overnight tourism. This study serves to inform hoteliers and practitioners about revenue management pricing strategies to improve hotel performance during mega-sporting events. Social implicationsThis study reveals that the benefits brought by a mega-event are not always translated into strong hotel revenue performance. This study highlights an important but understudied research area of revenue management pricing strategies and the effect of mega-sporting events in the hotel sector. This study contributes to the literature as one of the few investigations to benefit hotel pricing strategies and overall revenue performance. Originality/valueThis study is one of the few studies about exploring the reaction of revenue managers during the execution of a mega-sporting event. The value of the present study lies in the fact that the authors extend previous studies examining the impact of the most important sporting event in the hotel industry at the country-level perspective. This study serves to inform hoteliers and practitioners about revenue management pricing strategies to improve hotel performance during mega-sporting events.
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Surya, Putu Rian Arde, Dewa Made Suria Antara, Ni Gst Nym Suci Murni, and Ni Luh Ayu Kartika Yuniastari Sarja. "The Implementation of E-Commerce Dynamic Rate to Generate Room Revenue." International Journal of Green Tourism Research and Applications 1, no. 1 (December 23, 2019): 34–54. http://dx.doi.org/10.31940/ijogtra.v1i1.1629.

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This study aims to determine the e-commerce dynamic rate structure to generate room revenue and the better implementation between dynamic rate and the static rate at a 3 star hotel in Kuta, Bali. Data collection methods used in this research as follows: interviews, observation, and documentation. The data analysis technique used is the mean analysis technique, dynamic pricing method, profit margin ratio, and descriptive analysis techniques. The results of the study showed the step by step of dynamic rate structure determination and the dynamic rate is better than the static rate. This is indicated by the results of the average profit margin ratio in 2016-2018 on the dynamic rate at 39.41% compared to the static rate at 2.00%. Based on the results of the analysis, any efforts that can be made are paying attention to the dynamic rate during decreasing the Price Points (PP), thus avoiding complaints from offline travel agents and implement the dynamic rates for offline travel agents, hence generate profits with a greater profit margin ratio for the hotel
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Zemke, Dina Marie V., Carola Raab, and Kaiyang Wu. "How does hotel design contribute to property performance?" International Journal of Contemporary Hospitality Management 30, no. 2 (February 12, 2018): 919–38. http://dx.doi.org/10.1108/ijchm-06-2016-0330.

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Purpose The purpose of this paper is to test the relationships between a hotel’s design quality and the property’s business performance. Design/methodology/approach Hotel guests’ assessments of the design quality of hotels that they recently visited are tested using the design quality indicator (DQI). Business performance is measured using indexed values for each property’s occupancy, average daily rate (ADR) and revenue per available room (RevPAR). The data are analyzed using exploratory factor analysis and a variation of a hedonic pricing model. Findings Factor analysis reduced the DQI instrument to 19 measurement items. Factors that measure navigability and signage positively impact occupancy index. Factors that measure flexible space usage negatively impact the RevPAR and ADR indices. Factors that reflect aesthetic constructs, including Urban & Social Integration and Character & Form, positively impact the RevPAR and ADR indices. Research limitations/implications The study examines a nationwide sample of guests from two full-service brands of a single multi-brand hotel company. The study provides a parsimonious, validated design measurement instrument and a revised hedonic pricing analysis. Practical implications Hoteliers can use this technique to assist with resource allocation decisions. Aesthetic elements, including the building’s Urban & Social Integration with its surroundings and its Character & Form, lead to higher ADR and RevPAR performance. Managers should ensure a coherent layout and good signage program to drive occupancy. Originality/value This study offers a technique to measure design quality and a new method of performing a hedonic pricing analysis.
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Yup Chung, Kyoo. "Hotel room rate pricing strategy for market share in oligopolistic competition — eight-year longitudinal study of super deluxe hotels in Seoul." Tourism Management 21, no. 2 (April 2000): 135–45. http://dx.doi.org/10.1016/s0261-5177(99)00043-6.

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Koh, Yoon, Amanda Belarmino, and Min Gyung Kim. "Good fences make good revenue: An examination of revenue management practices at peer-to-peer accommodations." Tourism Economics 26, no. 7 (August 12, 2019): 1108–28. http://dx.doi.org/10.1177/1354816619867579.

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While hotel revenue managers utilize tools such as pricing, market segmentation, rate fences, and forecasting to maximize revenue, hosts in peer-to-peer (P2P) accommodations often have limited knowledge and lack the sophisticated pricing tools. Despite online resources for revenue management available, there has yet to be an examination regarding how widely spread these practices are in the P2P accommodation segment. Based on daily best available rates and booking restrictions information for P2P accommodations listed on Airbnb from top 10 cities with highest room inventories in the United States, this study aims to shed light on the current state of revenue management adoption on Airbnb. Utilizing a total of 307,955 Airbnb property’s daily data for 32 months, this study found that there are significant differences in revenue management practices by host characteristics (multi-unit hosts vs. single-unit hosts: Superhosts vs. non-Superhosts) for three revenue management tactics: dynamic pricing, minimum night’s stay, and restricted cancellation, and the hosts practices changes as their experience accumulates.
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Dissertations / Theses on the topic "Hotel Room Rate Pricing"

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Mattimoe, Ruth. "An institutional study of room rate pricing in the Irish hotel industry." Thesis, University of Manchester, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.556321.

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The research presented in this thesis is centred on a study of room rate pricing in the Irish hotel industry which, since the late 1980s, has enjoyed a period of unparalleled expansion and has been an engine of growth for the economy. There has been little research on this aspect of the industry. Overall, the main research objective was to inquire into the way reality is perceived by hoteliers and to find out how they grapple with room pricing decisions. Ontologically, the research views pricing as a social and organisational practice embedded in the contextual setting of each hotel, rather than being a technical tool used to achieve economic rationality, as in more mainstream functionalist / positivist research. Therefore, the interpretivist research methodology and the research methods of qualitative interviewing and case studies were chosen. Two contrasting major case sites provided detailed insights into the practicalities of room pricing. The empirical findings clearly show that the manager is boundedly rational in the face of the inter-connectivity of room pricing with other customer-related and marketing decisions. Room pricing is also time-dependent and subject to uncertainty of market demand. Uncertainty can be reduced to an extent, by controlling price setting and proactive planning by the manager. This can be seen in the formal routines for setting guiding parameters (ceiling rack rate, mid-point budgeted yield and minimum floor price) in advance of the season, rules for discounting, routines to allocate blocks of rooms to bulk business etc., other informal routines and good marketing. However, a balance of uncertain demand remains, which tends to be handled reactively by intuition and luck, as the season unfolds. The findings suggest that room pricing is a function of context, cannot be subject to general rules and is path dependent on a spectrum between floor price and ceiling rack rate. Hoteliers wish to move the room rate along the continuum towards the rack rate, but face conflicting forces at macro and micro levels, yielding trade-offs and extensive complexity. The rational, optimising decision-maker of the Neo-Classical (NCE) model is rejected, due to its ahistorical nature and lack of congruence with empirical reality. A FIVE LEVEL institutional explanation, which connects micro and macro levels, is proposed, using Old Institutional Economic (OIE) and New Institutional Sociology (NIS) concepts. 10
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Kefela, Mehari Semere. "Determinants of Hotel Room Rates in Stockholm : A Hedonic Pricing Approach." Thesis, Södertörns högskola, Institutionen för samhällsvetenskaper, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-23512.

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Using Lancaster’s characteristics approach to consumer theory the study investigates the impact of a variety of characteristics on the rates charged for hotel rooms in Stockholm. In particular, it examines how a number of these characteristics explain variations in room rates between weekdays and weekends. Data for 105 observations (weekday sample) and 110 observations (weekend sample) were extracted from 49 hotels in and around the Swedish capital of Stockholm from the Internet-based hotel booking site hotels.com. Based on semilog regression analysis three models for the whole sample, weekday sample and weekend sample were estimated. The results show that the provision of breakfast, distance from the city center, availability of minibar in a room, provision of free cancellation option, average room size, number of guest rooms (hotel size) and hotel star rating have significant effects on both weekday and weekend room rates. By contrast, the presence of bathroom and the provision of free parking space turned out to be insignificant in both models; whereas the provision of a 24-hour room service and association with hotel chain appear to be significant only in the weekday model. The impact of the star variable is also found to be more pronounced during the weekdays than weekends. These results are expected to shed light on which hotel characteristics consumers have to pay extra, and enhance hotel managers’ strategic pricing. The study also highlights the critical role of a proper definition and measurement of the hotel star rating in hedonic pricing.Many hedonic studies have regressed the number of stars, which are ordinal measures of quality that indicate the relative ranking of hotels, in their cardinal sense. As a result, they have failed to measure the impact of each rating independently. To solve this recurrent problem, the study attempts to provide another method of quantifying the star variable whereby one can accurately measure the star rating and capture the impact of each rating independently by creating “one less dummy variable than there are alternatives”. It is hoped that this will inspire further research and analysis.
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Chang, Cindy, and 張舒惠. "Impact of Room Pricing Strategy During and After Economic Crises on Hotel Total Revenue: The Case of International Hotel in Taipei City." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/99813349026318371693.

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碩士
輔仁大學
餐旅管理學系碩士班
101
Hotel revenue mainly generated by Rooms and Food & Beverage. This study used the quarterly statistics during 2006 to 2012 which provided by Taiwan Tourism Bureau, to analyzed 10 of international hotels located in Taipei City the performance before and after economic crisis to see if the hotel revenue performance had impacted by room pricing strategy. The results indicated that the hotels with higher ADR would generate higher food & beverage revenue than rooms revenue, but opposite revenue mix to the hotels with lower ADR. The Hotel ADR showed positive impact on both total revenue and food & beverage revenue before or after economic crisis. However, the results also showed the total revenue after economic crisis fall behind the figure before economic crisis when food & beverage revenue showed an increase on its performance. The decreasing of rooms revenue might due to the decrease of ADR. As the influence of guest room pricing strategy were not only on room revenue, but also on total revenue. It is suggested that the hotel management should condsider all factors when discounting room rates in order to maximize revenue performance.
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(9597320), Haejin Kim. "APPLICATION OF FINANCIAL MARKET MODELS IN THE HOTEL INDUSTRY." Thesis, 2020.

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In this dissertation, I investigated price dynamics in the hotel room-night market and attempted to explain pricing decisions from a market perspective. Since market dynamics of the hotel room-night market can be paralleled to those in the financial market, financial market models allowed for examination of various aspects of hotel room pricing decisions.

In the first study, advance-purchase discounts were estimated through application of an option pricing model considering property-specific attributes. Non-refundable advance-purchase discounts are a commonly used rate fence. One challenge to their implementation, however, is deciding upon the precise magnitude of the discount. Quan’s (2002) study on the price of room reservations is a good starting point, but it is a conceptual model that assumes away other property-specific factors. This study thus tested the idea that advance-purchase discounts are affected by various components, including the value of the right to cancel a reservation (e.g., cancelation option value) and the room- and property-specific factors in the hotel room-night market (e.g., uncertainty, reviews, and seasonality). The analysis supported this hypothesis and additionally revealed that advance-purchase discounts are smaller for rooms with high review ratings in a high-demand period. Interestingly, the divergence between advance-purchase discounts and cancelation option value components widened in a high-demand period, which implies a tendency by hotels to adjust their room rates rather than the amount of discount for customers who book their stay well in advance. Theoretically, this study thus contributes to finance literature by extending the application of the option pricing model to real options for non-financial assets. This study also contributes to the hospitality literature by demonstrating the effects of property-specific attributes on advance-purchase discount magnitude. The results also have implications to the hospitality industry by providing an analytical framework by which hoteliers can estimate property-specific advance-purchase discounts.

The second study concentrated on rate parity agreement’s effect on the hotel room-night market’s efficiency at reflecting product characteristics in room rates. This study examined the impact of rate parity agreement between hotels and online travel agencies by comparing hotel rates between Europe and the United States. This study found that room rates were less sensitive to property quality attributes under rate parity clauses. The reflection of property quality on room rates were less efficient when hotels have rate parity agreement with OTAs. Furthermore, the results supported the claim that rate parity exacerbates price increase in periods of high demand, which indicates possible collusion between suppliers (hotels) and distributors (OTAs). The findings provided theoretical implications by testing the market efficiency of the hotel room-night market and confirming the impact at the property level. This study also provided a perspective on pricing decision makers to understand how rate parity agreement influence their pricing decisions. Last, the findings provided support for recent policies in Europe that restrict rate parity agreements between hotels and OTAs.

The third study empirically examined hoteliers’ response to the demand by observing the price movement of two rates with different cancelation policies—free cancelation rates and non-refundable rates. By modifying Hasbrouck’s (1995) information share approach, this study examined the non-refundable rates’ contribution to the price discovery process. The perceived quality of accommodation by customers, one of the primary determinants of the price discovery process, was included in analysis. The results suggested that non-refundable rates were contribute more to the information variance than free cancelation rates did. The findings also suggested that consumers’ perceived quality and volatility influence non-refundable rates’ contribution to the price discovery process. The results also have practical implications for market participants, as they help to build an understanding of aggregated demand and its impact on pricing. Non-refundable rates are generally regarded as just one of many kinds of discounted rates, but the results of this study suggest that hoteliers should carefully consider the role that non-refundable rates play in their pricing strategy.

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Ying-Ru, Hsieh, and 謝盈如. "A Study of Using Grey Prediction GM (1, 1) in Forecasting Revenue Rate of Room / Food & Beverage, Operating Revenue and Profit before Tax- A Case of International Tourist Hotel in Taiwan." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/jn8w6n.

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碩士
大葉大學
休閒事業管理學系碩士班
104
The GM(1, 1) of grey system theory has been adopted in a variety of ranges, and it features forecasting through small amounts of data. This research predicts revenue rate of room / food & beverage, operating revenue, profit before tax of the international tourist hotels by using GM(1, 1) and other two kinds modified GM(1, 1), which are modified 2-years-period GM(1, 1) model and modified 3-years-period GM(1, 1) model. Among these three methods, the result of re-modified 3-years-period GM(1, 1) is the best, and the mean error of re-modified 3-years-period GM(1, 1) is 5.71%. This result approaches excellent. The major findings of this study were summarized as follows. First, GM(1, 1) prediction is precise in forecasting revenue rate of room / food & beverage, operating revenue, profit before tax of the International tourist hotels. Second, re-modified 3-year-period GM(1, 1) is a better prediction method but it would be affected by external factors. Third, the According to the result of prediction, the hotels in Taipei have the best operating revenue and profit before tax from now on to the future. Through the study of the paper, except the results can be used as further reference for the government and further researchers that who want to touch this filed.
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Book chapters on the topic "Hotel Room Rate Pricing"

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Sun, Sunny, Rob Law, Markus Schuckert, and Lawrence Hoc Nang Fong. "An Investigation of Hotel Room Reservation: What Are the Diverse Pricing Strategies Among Competing Hotels?" In Information and Communication Technologies in Tourism 2015, 723–34. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-14343-9_52.

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Cavenaghi, Emanuele, Lorenzo Camaione, Paolo Minasi, Gabriele Sottocornola, Fabio Stella, and Markus Zanker. "A Re-rank Algorithm for Online Hotel Search." In Information and Communication Technologies in Tourism 2023, 53–64. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-25752-0_5.

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AbstractRecommender Systems were created to support users in situations of information overload. However, users are consciously or unconsciously influenced by several factors in their decision-making. We analysed a historical dataset from a meta-search booking platform with the aim of exploring how these factors influence user choices in the context of online hotel search and booking. Specifically, we focused our study on the influence of (i) ranking position, (ii) number of reviews, (iii) average ratings and (iv) price when analysing users’ click behaviour. Our results confirmed conventional wisdom that position and price were the “two elephants in the room” heavily influencing user decision-making. Thus, they need to be taken into account when, for instance, trying to learn user preferences from clickstream data. Using the results coming from this analysis, we performed an online A/B test on this meta-search booking platform comparing the current policy with a price-based re-rank policy. Our online experiments suggested that, although in offline experiments items with lower prices tend to have a higher Click-Through Rate, in an online context a price-based re-rank was only capable to improve the Click-Through Rate metric for the first positions of the recommended lists.
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Nong, Sunny Zhenzhen, and Lawrence Hoc Nang Fong. "“Better Not Let Me Know”: The Mediating Role of Regret on the Relation Between Social Comparison Discrepancy in Online Hotel Review and Revisit Intention." In Information and Communication Technologies in Tourism 2022, 87–96. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94751-4_9.

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AbstractOnline review is powerful in influencing tourists’ travel decision. However, understanding of how online reviews affect tourist emotion and decision at the post-trip stage is limited. The present study examines whether encountering travel experiences shared on social media by other users with disparity in the cost of same accommodation after a trip will cause regret and alter the intention to revisit from a retrospective point of view. Drawing from the experimental study, the result showed that regret mediates the negative effect of comparison discrepancy (in the case of differences in the paid room rate) on intention to stay in the hotel again. The current study of the effects of social comparison on revisit intention adds to the literature and establishes the groundwork for future scholarly work on post-trip online review management. Meaningful implications and strategies are recommended to online review platform and hotel marketing management.
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Kojima, Satoshi, and Kenji Asakawa. "Expectations for Carbon Pricing in Japan in the Global Climate Policy Context." In Economics, Law, and Institutions in Asia Pacific, 1–21. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6964-7_1.

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Abstract Realizing a decarbonized society in consistent with the Paris Agreement, a fundamental transformation of the entire economic and social system is needed, and not only carbon intensive sectors but also all sectors and all stakeholders including households must be decarbonized. This chapter demonstrates increasing expectations for carbon pricing in Japan in this global policy context. After the review of the global trend of carbon pricing, historical progress of carbon pricing in Japan and the existing nation-wide carbon tax, i.e. the Global Warming Countermeasure Tax, is explained. There are also two sub-national carbon pricing schemes in Japan, Tokyo ETS and Saitama ETS, which are explained in Chaps. 10.1007/978-981-15-6964-7_6 and 10.1007/978-981-15-6964-7_7 respectively, and not focused in this chapter. We examine the claim that Japan has already implemented high level carbon pricing in terms of various forms of energy taxes. Based on the effective carbon rate which is defined by OECD as the sum of explicit carbon prices and fossil fuel taxes per carbon emission, the nationwide average effective carbon rate of Japan is lower than the average effective carbon rates of OECD countries and its key partner countries. The current carbon pricing schemes in Japan are too modest to realize decarbonization transition and there is a room to upgrade them to exploit full potential of carbon pricing. This chapter discusses adequate levels of carbon prices in compatible with decarbonization transition.
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VANDERREST, J. "Room rate pricing: a resource-advantage perspective." In Accounting and Financial Management, 211–39. Elsevier, 2006. http://dx.doi.org/10.1016/b978-0-7506-6729-6.50019-4.

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"Room rate pricing: a resource-advantage perspective." In Accounting and Financial Management, 230–58. Routledge, 2012. http://dx.doi.org/10.4324/9780080492483-20.

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Organ, Arzu, and Cansu Tosun Gavcar. "Forecasting Hotel Occupancy Rates With Artificial Neural Networks in the COVID-19 Process." In Handbook of Research on the Impacts and Implications of COVID-19 on the Tourism Industry, 583–602. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-8231-2.ch028.

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In the tourism sector, accommodation business demand forecasting provides a great benefit for tourism professionals, especially hotel managers, in the strategic decision-making process. For demand estimation, the artificial neural networks (ANN) method, which works similar to a human brain cell and makes realistic predictions, has been preferred. The aim of this study was to develop an eight input and output variable of the feedforward radiated back an ANN is in a specially certified hotel room occupancy rate in Turkey to investigate the applicability of the method to predict. Four different alternative network structures were created from the data set with the K-fold cross validation method. As a result of the test simulation, it was determined that the estimated and actual occupancy rates of the network with the lowest error were close to each other. According to this designed model, the monthly occupancy rate for the years 2019 and 2020 has been estimated. As a result, the effect of COVID-19 was revealed by comparing the hotel occupancy rate with the actual rates.
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Noordzy, Gert, and Richard Whitfield. "Root Causes of New Hotel Opening Delays in China." In Educational Strategies for the Next Generation Leaders in Hotel Management, 43–72. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-8565-9.ch003.

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In China, at least three new 150+ room hotels will be opened every day for the next 25 years according to available development pipeline data (Yang, 2011; Lodging Econometrics, 2013). This phenomenal rate of hotel construction has major implications for how new hotels are opened on such a large scale. China is a vital growth market for the global hotel industry, yet many of these hotel openings are being considerably delayed. This chapter reviews the future growth strategies and plans of the major international hotel companies in China, and examines the causes for these setbacks. The authors used a Causal Chain Analysis on data that were acquired from over 80 interviews with hotel management professionals in 2009. There was an overwhelming general lack of understanding of project management methodologies, concepts, and structures. These were found to be key problem areas (Thomas, Delisle, & Jugdev, 2001).
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Coulson, The Rt Hon Lord Justice. "Errors of Law and Fact." In Coulson on Construction Adjudication. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198822110.003.0011.

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The starting point for any discussion of this topic is not a case concerned with adjudication at all. In Nikko Hotels (UK) Ltd v MEPC plc, a rent review case, the lease contained a formula for increasing the rent, which necessitated the determination of the average hotel room rate. The independent expert, whose determination of the issue was provided for by the terms of the lease, construed that expression as meaning the average of the published prices at which rooms were said to be available, rather than the average room rate actually achieved. This interpretation of the lease naturally meant that the rate was higher than it would otherwise have been, and the tenants issued an originating summons, alleging that the decision was a nullity because it was based on a misconstruction of the rent review clause.
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Laohavichien, Tipparat, and Lawrence D. Fredendall. "Sustainable Inventory Management in Hotels." In Handbook of Research on Sustainable Tourism and Hotel Operations in Global Hypercompetition, 255–76. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-4645-4.ch013.

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The objectives of this chapter are to present inventory planning and control systems in the hotel industry and to examine how to use the existing inventory management practices in the hotel industry to promote sustainability based on the concept of a triple bottom line (i.e., economic, social, and environmental sustainability). Yield or revenue management is the method most hotels use to manage their perishable inventory (rooms). The basic principle of yield management is that hotels achieve maximum revenue by matching customer needs with the right room rate and the right time of sale. Yield management directly promotes economic and social sustainability but indirectly fosters environmental sustainability. In addition, techniques and models for managing nonperishable hotel inventory are discussed, including the EOQ model, JIT and Lean systems, and the ABC classification. Moreover, radio-frequency identification (RFID), the technology used to support the effectiveness of a sustainable inventory management system, is discussed, and finally, further research is provided.
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Conference papers on the topic "Hotel Room Rate Pricing"

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Ramadiani, Nurhidayat Wardani, Awang Harsa Kridalaksana, Muhammad Labib Jundillah, and Azainil. "Forecasting the Hotel Room Reservation Rate in East Kalimantan Using Double Exponential Smoothing." In 2019 Fourth International Conference on Informatics and Computing (ICIC). IEEE, 2019. http://dx.doi.org/10.1109/icic47613.2019.8985916.

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Fadly, Muhammad, Ari Yanuar Ridwan, and Mohammad Deni Akbar. "Hotel Room Price Determination Based on Dynamic Pricing Model Using Nonlinear Programming Method to Maximize Revenue." In 2019 2nd International Conference on Applied Information Technology and Innovation (ICAITI). IEEE, 2019. http://dx.doi.org/10.1109/icaiti48442.2019.8982154.

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Işık, Cem, and Nilgün Bilici. "The Analysis of Hotel Room Rates Using Hedonic Model: The Case of Erzurum." In International Conference on Eurasian Economies. Eurasian Economists Association, 2016. http://dx.doi.org/10.36880/c07.01653.

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In this study, it is aimed to analyze the relationship between the hotel room rates and its features by using hedonic price approach. In this context, the data of 26 factors of 20 hotels in Erzurum have been tested by setting log-log regression model on EViews 8 program. It has been determined that these 15 factors in 26 are significant and it has been also found that 13 factors of them (chain hotel, room size, bathroom, breakfast, LCD TV, a bar, Wi-Fi, shuttle, conference room, restaurant, night club, fitness center and fax/copier) increase the hotel room rate and two of them (location and skiing facilities) reduce the room rates.
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Asadi, Ehsan, Manuel Gameiro da Silva, and Jose´ J. Costa. "Measurement and Simulation of Indoor Air Quality and CO2 Concentration in a Hotel Room." In ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2010. http://dx.doi.org/10.1115/esda2010-25143.

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Indoor air quality (IAQ) is nowadays universally recognized as an important issue that affects the comfort and health of people, as well as their productivity. This paper describes the relationship of indoor CO2 concentration to building air quality and ventilation, with a focus on how CO2 can be used to evaluate and predict air quality and ventilation performance, namely the infiltration airflow rate. Besides it shows the ability of ESP-r building simulation software for predicting the CO2 concentration and the air exchange rate in a building. For this purposes a room of a hotel located in the urban area of Coimbra was chosen. The developed simulation model was then validated against empirical results. It was shown that a fair degree of agreement between ESP-r results and the experimental observation exist for the zones. High accuracy of the simulation model showed that building simulation software, namely ESP-r can provide a better understanding of indoor environmental conditions and be a powerful tool in finding the best modification measures for improving the indoor air quality in a building.
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