Dynamic pricing in different Spanish resort hotels

Vives, Aldric; Jacob, Marta

doi:10.1177/1354816619870652

Cited by 8 publications

(6 citation statements)

References 17 publications

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“…At present, scholars have conducted research on traditional pricing methods, including cost-plus pricing, demand-based pricing, and competitive pricing. Vives and Jacob [1] studied seven four-star hotels belonging to the same multinational hotel chain. The goal is to maximize revenue for hotels during peak seasons.…”

Section: Literature Reviewmentioning

confidence: 99%

Dynamic Pricing Model for E-Commerce Products Based on DDQN

Sun,

Wang,

Qiao

et al. 2024

JCBAR

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This paper addresses the challenges of intense price competition, price elasticity, and significant demand fluctuations in e-commerce product markets by adopting a dynamic pricing approach. Focusing on a product from the JD.com e-commerce platform, historical data spanning the past three years are analyzed, considering factors such as shipping costs, product inventory, product costs, and the impact of holidays. The study employs the Double Deep Q Network (DDQN) for dynamic pricing optimization of the product and compares its performance with the DQN model. The results indicate that both the DQN algorithm and DDQN algorithm lead to varying degrees of profit improvement for dynamic pricing of products. Specifically, the pricing profit with the DQN algorithm increased by an average of 1.925% compared to the original pricing profit, while the pricing profit with the DDQN algorithm increased by an average of 11.975% compared to the original pricing profit. These findings demonstrate practical significance.

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Section: Literature Reviewmentioning

confidence: 99%

Dynamic Pricing Model for E-Commerce Products Based on DDQN

Sun,

Wang,

Qiao

et al. 2024

JCBAR

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show abstract

“…An overview shows that the studies dealing with the development and design of pricing are very diverse and focus on different pricing approaches. While different pricing approaches are used, the research done by Vives and Jacob (2021) shows that hotels located in the same destination and belonging to the same hotel chain follow similar pricing strategies.…”

Section: Research On Price Determinantsmentioning

confidence: 99%

Focal Points in Recent Tourism Price Research

Nemec Rudež

2024

Tourism (Zagreb, Online)

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The article aims to provide a comprehensive overview of recent academic studies on pricing in tourism and to deepen the understanding of the recently prevailing research streams on this topic. This article reviews research articles on tourism pricing published in journals in the Scopus database between 2017 and early 2023. An analysis of the selected literature identifies three research streams on pricing: research on price determinants, price development and customers’ price decisions. In terms of methodology, empirical studies predominate, and in terms of period, the distribution over the years shows a stable and consistent level of research activity. The article is essential for further research in the field by presenting a synthesis of recent academic work.

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“…In fact, hotels located at the same destination display completely different demand behaviors. Vives and Jacob (2021) observe that the booking horizon and price elasticity of demand directly affect optimal hotel pricing, while hotel characteristics like the hotel size and location and guest profiles are key factors in determining the price elasticity of demand. Vives et al (2019) and Mohammed et al (2021) find that last-minute booking prices usually rise as the date of stay draws closer, while the demand is segmented according to different hotel characteristics: tangible attributes, reputational variables and contextual factors.…”

Section: Hotel Demand and Price Elasticitymentioning

confidence: 99%

Sources of price elasticity of demand variability among Spanish resort hotels: a managerial insight

Vives

Jacob

2023

JHTT

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Purpose The purpose of this paper is to use demand behavior estimation to find the sources of price variability among resort hotels at different Spanish destinations. Design/methodology/approach This paper estimates online demand functions during high season for seven four-star resort hotels located at different Spanish destinations. Different price elasticity values are compared, and different factors affecting price elasticity are analyzed. Findings The main findings indicate that most of the high season periods display elastic demands, but factors such as a central location at a resort, recent refurbishments, the availability of additional facilities/services and a hotel targeted at the couples and/or half-board segments make the demand more inelastic; the Tenerife hotels had the most price-elastic demand; during the closest booking periods to the date of stay, the demand is usually more elastic; and a higher number of local competitors pushes down hotel prices. Originality/value This paper highlights the managerial implications of focusing on more profitable demand segments for hoteliers. This is especially useful for the development of revenue management software aimed at improving forecasts.

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Dynamic pricing in different Spanish resort hotels

Cited by 8 publications

References 17 publications

Dynamic Pricing Model for E-Commerce Products Based on DDQN

Dynamic Pricing Model for E-Commerce Products Based on DDQN

Focal Points in Recent Tourism Price Research

Sources of price elasticity of demand variability among Spanish resort hotels: a managerial insight

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