Algarve hotel price determinants: A hedonic pricing model

Soler, Ismael P.; Gémar, Germán; Correia, Marisol B.; Serra, Francisco

doi:10.1016/j.tourman.2018.08.028

Cited by 63 publications

(75 citation statements)

References 73 publications

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“…Also, the existence of a fitness center in Portugal and the distance from Lisbon to downtown are also attributes to create a premium for room rates. Soler et al (2019) used a database of 9,992 cases from Trip Advisor to evaluate customers' willingness to pay for the various characteristics and attributes of hotels in the Algarve region of Portugal. It showed that hotel positioning as environmentally responsible has no impact on prices, while other positions do influence room prices.…”

Section: B Room Pricing By Using Hedonic Price Modelmentioning

confidence: 99%

The Hidden Price of Hotel Features Forming Room Rate: Focused on Star-type Segmented Market in China

Xiao-ning¹,

Chung²

2020

Glob Bus Financ Rev

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This study is to analyze the price characteristics of three-to five-star hotel room prices in Beijing Central Business District to find the hidden prices of hotel rooms in the area. Design/methodology/approach: This research used the hedonic price model to analyze the data collected by the network search engine to find hidden elements that affect the price of hotel rooms. The feature variables of the hotel are divided into three categories including internal features, external features and time features in two different markets: the overall market and the star-type segmented market in China. Findings: In the overall market, among hotel room interior features, hotel star rating, room area, free breakfast, food & beverage service quality, hotel facilities & equipment and free internet service have an impact on the hotel room price, with an implied price. For the hotel room exterior features, distance and the hotel-owned business district have a significant relationship with the price of the hotel room, with an implied price. In the star-type segmented market, all hotel room interior features have a significant relationship with the hotel price. Also, the features of competitors have very significant implied prices, which will greatly impact the pricing of hotel rooms in the star-type segmented market. Research limitations/implications: Managers can decide whether to improve the investment in a feature to increase the quality of the feature, or to control the cost of the feature to reduce unnecessary expenditure through the calculation results. Since the study was conducted only in the Beijing area, extended research must be carried out beyond Beijing to achieve more universal applicability. Originality/value: This study investigated the pricing of hotel rooms based on the hedonic price method to explore the price elasticity of the relevant features of hotel room products, and understand the needs and preferences of consumers in different market segments. It established different star segment market models and analyzed the differences in the types and elasticity of the features of significant implied prices in different star market models.

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Section: B Room Pricing By Using Hedonic Price Modelmentioning

confidence: 99%

The Hidden Price of Hotel Features Forming Room Rate: Focused on Star-type Segmented Market in China

Xiao-ning¹,

Chung²

2020

Glob Bus Financ Rev

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“…Thus, recently, scholars proposed new hedonic models characterized by a broad market‐oriented approach including competitors, the general environment, and a special attention to price dynamics (e.g. Abrate & Viglia, ; Alegre & Sard, ; Soler et al, ). Short‐term pricing tactics are specifically recognized as fundamental to compete (Guizzardi, Pons, & Ranieri, ) maximizing revenue performance (Mauri, Sainaghi, & Viglia, ), influencing the attractiveness of products and hence, both the customers' transaction‐specific, cumulative satisfaction, and willingness to pay (Homburg, Koschate, & Hoyer, ; Varini, Engelmann, & Claessen, ).…”

Section: Review Of the Literaturementioning

confidence: 99%

“…On price correlation, Soler et al () and Soler and Gémar () notice that an autoregressive component AR(1) must be added to control for autocorrelation. Although aware that results for a given location may not be generalizable to other cities or regions, Soler et al () notice that the price of the previous day is the most important explanatory variable in their hedonic model for hotel room rates in Algarve, which highlights the importance that managers place on price stability.…”

Section: Review Of the Literaturementioning

confidence: 99%

“…This evidence could be related to the fact that we are observing online prices of expensive hotels located in a central area. The internet is clearly the core distribution channel for leisure tourism, whereas hotels mostly focused on the business sector could be prone to competing on BARs because they are less attractive to holiday tourists (see Soler et al, ).…”

Section: Modelling Price Dynamicsmentioning

confidence: 99%

“…However, the focus on the “time effect” is often limited to price correlation among successive arrival dates (e.g. Soler, Gémar, Correia, & Serra, ) or to the effect seasonality and special events have on the consumer's perceptions of the marginal contribution of service attributes (e.g. Herrmann & Herrmann, ).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Does advance booking matter in hedonic pricing? A new multivariate approach

Guizzardi

Angelini

Pons

2019

Journal of Tourism Research

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We consider prices across the advance bookings as a multivariate variable, modelling the time effect by means of a structural vector autoregression. Its unit-specific fixed effect is taken as the dependent variable in a set of hedonic regressions allowing us to estimate the marginal contribution to price of the (time-invariant) attributes along the price trajectory. Results from our two-step approach indicate that although past occupancy rates, events, bank holidays, and seasonality differentiate pricing strategies across advance bookings, time-invariant services/attributes tend to increase in hedonic value as the advance booking period decreases, reducing the contribution of dynamic pricing. K E Y W O R D Sbusiness tourism, dynamic pricing, fairs, Milan, seasonality, structural vector autoregression

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