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Open Access
Article
Publication date: 25 October 2022

Andrea Valenzuela-Ortiz, Jorge Chica-Olmo and José-Alberto Castañeda

This research investigates the effect of accessibility to points of tourist interest (buffer) and direct and indirect spatial spillover effects of agglomeration economies…

Abstract

Purpose

This research investigates the effect of accessibility to points of tourist interest (buffer) and direct and indirect spatial spillover effects of agglomeration economies on tourism industry revenues in Spain.

Design/methodology/approach

Data were collected from the Bureau van Dijk's (BvD) Orbis global database. The data were analysed using a spatial econometric model and the Cobb–Douglas production function.

Findings

This study reveals that hotels located inside the buffer zone of points of tourist interest achieve better economic outcomes than hotels located outside the buffer. Furthermore, the results show that there is a direct and indirect spatial spillover effect in the hotel industry.

Practical implications

The results provide valuable information for identifying areas where the agglomeration of hotels will produce a spillover effect on hotel revenue and the area of influence of location characteristics. This information is relevant for hotels already established in a destination or when seeking a location for a new hotel.

Social implications

The results of this study can help city planners in influencing the distribution of hotels to fit desired patterns and improve an area's spatial beauty.

Originality/value

The paper provides insights into how investment, structural characteristics, reputation and location affect hotel revenue.

Details

European Journal of Management and Business Economics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2444-8451

Keywords

Book part
Publication date: 16 July 2019

James W. Hesford, Michael J. Turner, Nicolas Mangin, Charles R. Thomas and Kelly Hoffmann

This study examines how firms’ use of competitor-focused accounting information, specifically competitor monitoring information, impacts their pricing, demand, and overall…

Abstract

This study examines how firms’ use of competitor-focused accounting information, specifically competitor monitoring information, impacts their pricing, demand, and overall revenue performance. The monitoring activities examined are the scope of monitoring, monitoring above and below one’s own hotel class (i.e., market segment), and the extent of reciprocity of monitoring. Competitor analysis is a central element in strategic management accounting (SMA), yet little empirical research has been done since companies do not disclose competitor monitoring activities. Proving the value of competitive monitoring provides strong support for SMA. Archival, proprietary monitoring information regarding pricing, demand, and revenue were obtained from one of the largest hotel markets in the United States. Using regression, we modeled the relationships between performance measures (pricing, demand, and revenue) and monitoring behaviors, while controlling for quality (hotel characteristics and management skill), competitive intensity, hotel class, geographic location, and ownership type. Our results indicate that two aspects of competitor monitoring impact hotel pricing that, in turn, impacts hotel demand and revenue performance. Specifically, a hotel monitoring more competitors (what we refer to as Scope) achieves higher prices with unchanged demand, resulting in higher revenue performance. Most hotels monitor within their class. However, deviating from one’s class has profound outcomes: looking at lower (higher) quality hotels results in a hotel setting lower (higher) prices, resulting in higher (unchanged) demand and lower (higher) revenue performance. Surprisingly, we did not find support for the reciprocity of monitoring. That is, whether the competitors monitored by a hotel, in turn follow the target, has no impact on hotel revenue performance outcomes. While the SMA literature notes the importance of competitor monitoring, this study fills a gap in an important, under-researched area by documenting the link between competitor monitoring behaviors and organizational revenue performance. This may help promote greater diffusion of SMA practices.

Article
Publication date: 17 December 2018

David Egan and Natalie Claire Haynes

The purpose of this paper is to investigate the perceptions that managers have of the value and reliability of using big data to make hotel revenue management and pricing…

1691

Abstract

Purpose

The purpose of this paper is to investigate the perceptions that managers have of the value and reliability of using big data to make hotel revenue management and pricing decisions.

Design/methodology/approach

A three-stage iterative thematic analysis technique based on the approaches of Braun and Clarke (2006) and Nowell et al. (2017) and using different research instruments to collect and analyse qualitative data at each stage was used to develop an explanatory framework.

Findings

Whilst big data-driven automated revenue systems are technically capable of making pricing and inventory decisions without user input, the findings here show that the reality is that managers still interact with every stage of the revenue and pricing process from data collection to the implementation of price changes. They believe that their personal insights are as valid as big data in increasing the reliability of the decision-making process. This is driven primarily by a lack of trust on the behalf of managers in the ability of the big data systems to understand and interpret local market and customer dynamics.

Practical implications

The less a manager believes in the ability of those systems to interpret these data, the more they perceive gut instinct to increase the reliability of their decision making and the less they conduct an analysis of the statistical data provided by the systems. This provides a clear message that there appears to be a need for automated revenue systems to be flexible enough for managers to import the local data, information and knowledge that they believe leads to revenue growth.

Originality/value

There is currently little research explicitly investigating the role of big data in decision making within hotel revenue management and certainly even less focussing on decision making at property level and the perceptions of managers of the value of big data in increasing the reliability of revenue and pricing decision making.

Details

International Journal of Quality & Reliability Management, vol. 36 no. 1
Type: Research Article
ISSN: 0265-671X

Keywords

Article
Publication date: 12 February 2019

Han Chen, Rui Chen, Shaniel Bernard and Imran Rahman

This study aims to develop a parsimonious model to estimate US aggregate hotel industry revenue using domestic trips, consumer confidence index, international inbound…

Abstract

Purpose

This study aims to develop a parsimonious model to estimate US aggregate hotel industry revenue using domestic trips, consumer confidence index, international inbound trips, personal consumption expenditure and number of hotel rooms as predictor variables. Additionally, the study applied the model in six sub-segments of the hotel industry – luxury, upper upscale, upscale, upper midscale, midscale and economy.

Design/methodology/approach

Using monthly aggregate data from the past 22 years, the study adopted the auto-regressive distribute lags (ARDL) approach in developing the estimation model. Unit root analysis and cointegration test were further utilized. The model showed significant utility in accurately estimating aggregate hotel industry and sub-segment revenue.

Findings

All predictor variables except number of rooms showed significant positive influences on aggregate hotel industry revenue. Substantial variations were noted regarding estimating sub-segment revenue. Consumer confidence index positively affected all sub-segment revenues, except for upper upscale hotels. Inbound trips by international tourists and personal consumption expenditure positively influenced revenue for all sub-segments but economy hotels. Domestic trips by US residents added significant explanatory power to only upper upscale, upscale and economy hotel revenue. Number of hotel rooms only had significant negative effect on luxury and upper upscale hotel sub-segment revenues.

Practical implications

Hotel operators can make marketing and operating decisions regarding pricing, inventory allocation and strategic management based on the revenue estimation models specific to their segments.

Originality/value

It is the first study that adopted the ARDL bound approach and analyzed the predictive capacity of macroeconomic variables on aggregate hotel industry and sub-segment revenue.

Details

International Journal of Contemporary Hospitality Management, vol. 31 no. 4
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 1 October 2006

Stephen I. Harewood

To determine conditions under which a hotel in Barbados can benefit from the use of revenue management.

4851

Abstract

Purpose

To determine conditions under which a hotel in Barbados can benefit from the use of revenue management.

Design/methodology/approach

Monte Carlo simulation is used to compare a first‐come first‐served approach for accepting booking requests to a bid price approach. Comparisons are made using different assumptions about upgrading, downgrading and overbooking.

Findings

When demand intensity is high, the bid price method yields higher revenue than the first‐come first‐served method. If demand intensity is low, but some necessary resources are scarce and the hotel practises upgrading and downgrading, then the bid price approach can also lead to improved revenue. No evidence was found to suggest that overbooking or downgrading costs affect the relative performances of the two approaches if these costs are taken into consideration.

Research limitations/implications

This research was conducted for one type of hotel using a particular sample period and the conclusions will not necessarily be true for other sample periods and other types of hotels.

Practical implications

The results show that hotels, which practise upgrading, downgrading and overbooking, should consider adopting a revenue management approach, when allocating their scarce resources among competing market segments.

Originality/value

Existing linear programming models of the revenue management problem are extended here to allow for upgrading and downgrading, when one resource is substituted for another in a package, and to allow for overbooking, when the hotel cannot honour a booking because of the unavailability of some resource. This formulation emphasizes the efficient allocation of all of the hotel's scarce resources.

Details

International Journal of Operations & Production Management, vol. 26 no. 10
Type: Research Article
ISSN: 0144-3577

Keywords

Article
Publication date: 8 February 2011

Neamat Farouk El Gayar, Mohamed Saleh, Amir Atiya, Hisham El‐Shishiny, Athanasius Alkes Youhanna Fayez Zakhary and Heba Abdel Aziz Mohammed Habib

This paper aims to present an integrated framework for hotel revenue room maximization. The revenue management (RM) model presented in this work treats the shortcomings in…

8091

Abstract

Purpose

This paper aims to present an integrated framework for hotel revenue room maximization. The revenue management (RM) model presented in this work treats the shortcomings in existing systems. In particular, it extends existing optimization techniques for hotel revenue management to address group reservations and uses “forecasted demand” arrivals generated from the real data.

Design/methodology/approach

The proposed forecasting module attempts to model the hotel reservation process from first principles. In particular, it models hotel arrivals as an interrelated process of stochastic parameters like reservations, cancellations, duration of stay, no shows, seasonality, trend, etc. and simulates forward in time the actual process of reservations to obtain the forecast. On the other hand, the proposed optimization module extends existing optimization techniques for hotel revenue management to address group reservations, while including integrality constraints and using “forecasted demand” arrivals generated from the data. The optimization model is based on large‐scale integer programming model to optimize decision rules for accepting reservations.

Findings

A case study based on three different sets of reservation records of simulated hotel data was conducted to test the operation of the system on real data. Results showed that the model is able to generate effective recommendations to maximize revenue.

Originality/value

The main value of this paper is that it presents an integrated framework for hotel room revenue maximization. The novelty introduced in this approach is that it is based on an advanced room demand forecast model that simulated the reservation process from its first principles and produces demand scenarios that are used by an optimization model to generate proper recommendations.

Details

International Journal of Contemporary Hospitality Management, vol. 23 no. 1
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 15 February 2019

Basak Denizci Guillet and Xinchen Shi

The purpose of this study is to understand how and to what extent Hong Kong hotels have integrated customer relationship management (CRM) into their revenue management…

1910

Abstract

Purpose

The purpose of this study is to understand how and to what extent Hong Kong hotels have integrated customer relationship management (CRM) into their revenue management (RM) practices at individual customer level.

Method

Semi-structured interviews were used to gather information from experienced interviewees holding hotel RM- and marketing-related executive positions. In total, 11 revenue and 9 marketing executives were interviewed in 2016-2017 over a period of 13 weeks. The data were transcribed and then Nvivo was used for data organization and analysis.

Findings

The hotels do not systematically segment customers by value because of restraints on the RM systems’ capabilities and the industry’s conventional segmentations. The revenue and marketing executives’ attitudes toward integration, IT system infrastructure support to enable integration, loyalty and membership programs as a means for integration and executive management level support for integration influence the hotel’s potential for RM and CRM integration.

Research Limitations/implications

Only the perspectives of revenue and marketing executives were considered. Incorporating the insights of different parties may achieve a more comprehensive result. In addition, because it seems that there is no systematic RM and CRM integration within the Hong Kong hotel industry, relevant decision-makers’ opinions toward the practice may change once they evaluate the performance of the pioneering practitioner.

Originality

This study reveals what has been done in practice to integrate RM and CRM compared with the theoretical approach, proposes an integration framework and discusses the potential for further development together with the challenges to integration.

Details

International Journal of Contemporary Hospitality Management, vol. 31 no. 2
Type: Research Article
ISSN: 0959-6119

Keywords

Book part
Publication date: 10 June 2021

Miguel Bendrao Baltazar and Yuan Li

Unlike manufacturing firms where the production of goods can be adjusted according to the demand of customers, hospitality firms do not have the ability to alter the…

Abstract

Unlike manufacturing firms where the production of goods can be adjusted according to the demand of customers, hospitality firms do not have the ability to alter the capacity of the changing demand of guests in a short period of time. Given the relatively fixed capacity or supply, maximizing revenue through inventory control is essential for hospitality operations. This chapter covers operations inventory control extracted from the field of revenue management. First, the concept of capacity management and planning is enclosed and various capacity management tactics and inventory control strategies are explored. Next, the management and principles of space inventory through inventory-based restrictions, strategic pricing, displacement analysis, and distribution channel management are addressed. Finally, the respective applications of these principles, strategies, and tactics in several hospitality sectors are discussed.

Details

Operations Management in the Hospitality Industry
Type: Book
ISBN: 978-1-83867-541-7

Keywords

Article
Publication date: 25 May 2012

Tony S.M. Tse and Yiu Tung Poon

The objectives of this study are to investigate the relationship between hotel room demand and room rates, and to find a viable solution for the optimal room rate that…

5903

Abstract

Purpose

The objectives of this study are to investigate the relationship between hotel room demand and room rates, and to find a viable solution for the optimal room rate that maximizes the total profit.

Design/methodology/approach

There are various studies in the literature on how room rates affect profitability, and how the optimal room rate that maximizes the total revenue can be determined. Most of these studies assume an algebraic relationship between room rates and room demand, and obtain the optimal solution by applying calculus to the revenue or profit function. This study adopts the alternative approach of using a model with a demand function that has been shown to be a superior causal forecasting model in some markets, and develops a new method to optimize the total profit.

Findings

The traditional method of applying calculus to the profit function based on a causal forecasting model leads to unrealistic solutions. This gives rise to the paradox that, on the one hand, there is a superior causal forecasting model based on room rates, but on the other hand, the traditional method does not yield a realistic solution for room rate optimization. This study analyzes the underlying causes of this paradox and proposes a method to resolve it.

Practical implications

The findings can be used by hotels to fine‐tune the room rates determined by conventional methods to arrive at a realistic and definitive value for the optimal room rate.

Originality/value

This study highlights the problems that arise with the traditional method of applying calculus to revenue and profit optimization and proposes a new method to resolve it.

Details

International Journal of Contemporary Hospitality Management, vol. 24 no. 4
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 19 June 2017

Albert A. Barreda, Sandra Zubieta, Han Chen, Marina Cassilha and Yoshimasa Kageyama

This study aims to examine the impact of a mega-sporting event “2014 FIFA World Cup” on hotel pricing strategies and performance.

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Abstract

Purpose

This study aims to examine the impact of a mega-sporting event “2014 FIFA World Cup” on hotel pricing strategies and performance.

Design/methodology/approach

The 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.

Findings

Results 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/implications

Research 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 implications

The 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 implications

This 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/value

This 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.

Details

Tourism Review, vol. 72 no. 2
Type: Research Article
ISSN: 1660-5373

Keywords

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