The impact of dynamic price variability on revenue maximization

Abrate, Graziano; Nicolau, Juan Luis; Viglia, Giampaolo

doi:10.1016/j.tourman.2019.03.013

Cited by 96 publications

(51 citation statements)

References 78 publications

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“…There are few managers that have training in how to make strategic pricing decisions (Nagle et al, 2014), means that many firms make pricing decisions in reaction to market changes (Rao and Kartono, 2009). In the specific case of hospitality, dynamic pricing plays a critical role (Abrate et al, 2019;Viglia et al, 2016). Furthermore, dynamic price variability leads to higher hotel revenues, as well as strategic room unavailability and review ratings (see Abrate et al, 2019).…”

Section: Pricing Strategiesmentioning

confidence: 99%

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Estimating the price range and the effect of price bundling strategies

Antunes¹

2019

EJMBE

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Purpose The purpose of this paper is to investigate and identify the price sensitivity of consumers of three- and five-star hotels and to determine the impact of bundling strategies on consumers’ price sensitivity. Design/methodology/approach To calculate price sensitivity, authors apply the van Westendorp’s price sensitivity meter (PSM). To understand the impact of bundling strategies, univariate and bivariate techniques are applied. Findings PSM results reveal the optimal prices and the range of acceptable prices for three- and five-star hotel. The bundling strategy results reveal that five-star customers are less sensitive to mixed-leader bundling. Regarding mixed-joint bundling, managers could improve sales through bundling strategies if they selected an attractive service (e.g. restaurants). Practical implications Findings assist hotel managers to understand the different price sensitivities, according to the hotel typology. Managers can manage prices without the risk of losing market share or revenue. The results help managers in deciding which bundling strategies they can create, as well as the services to be included to achieve highest profitability. Originality/value No research to date to the best of the authors’ knowledge has attempted to understand and compare the role of bundling strategies in three- and five-stars hotels. Moreover, no research has attempted to measure and compare customers’ price sensitivity of three- and five-stars hotels.

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Section: Pricing Strategiesmentioning

confidence: 99%

“…In the specific case of hospitality, dynamic pricing plays a critical role (Abrate et al, 2019;Viglia et al, 2016). Furthermore, dynamic price variability leads to higher hotel revenues, as well as strategic room unavailability and review ratings (see Abrate et al, 2019).…”

Section: Pricing Strategiesmentioning

confidence: 99%

Estimating the price range and the effect of price bundling strategies

Antunes¹

2019

EJMBE

View full text Add to dashboard Cite

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“…In its traditional sense, this form of intertemporal price discrimination entails price changes over time due to fluctuations in supply, demand, competition, or other factors (Krämer et al 2018). Prices thus vary depending on the time of purchase but are the same across consumers at a given time (Abrate et al 2019). Personalized dynamic pricing (PDP) also involves sellers dynamically setting prices for the same product or service across different consumers with the aid of consumer-specific data such as IP address, purchase or browsing history, or other consumer-identifying characteristics (Richards et al 2016).…”

Section: Introductionmentioning

confidence: 99%

A special price just for you: effects of personalized dynamic pricing on consumer fairness perceptions

Priester

Robbert

Roth

2020

J Revenue Pricing Manag

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Personalized dynamic pricing (PDP) involves dynamically setting individual-consumer prices for the same product or service according to consumer-identifying information. Despite its profitability, this pricing provokes strong negative fairness perceptions, explaining why managers are reluctant to implement it. This research provides important insights into the effect of two PDP dimensions (price individualization level and segmentation base) on fairness perceptions and the moderating role of privacy concerns. The results of two experimental studies indicate that consumers perceive individual prices as less fair than segment prices. They also evaluate location-based pricing as less fair than purchase history-based pricing. Consumer privacy concerns moderate these effects.

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“…Clearly, managers and researchers need data on the expected benefits related to changes in a company's pricing strategy. Surprisingly, the revenue management literature is largely silent on quantifying the effects of dynamic pricing strategies primarily due to the complexity of obtaining data (Abrate et al, 2019). Consulting companies publicize services in price consultancy by promising quick returns without providing the data that would allow independent verification.…”

Section: Introductionmentioning

confidence: 99%

Dynamic pricing assuming demand shifting: the alpine skiing industry

Malasevska

Haugom

Hinterhuber

et al. 2020

Journal of Travel & Tourism Marketing

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Changes in a company's pricing strategy have the potential to influence profitability. Data from choice-based conjoint questionnaire were used to estimate revenue-maximizing dynamic prices accounting for both demand shifting and market expansion. The results show that dynamic prices induce greater demand and could increase revenue by 0.5% to 7.5%. Moreover, skiers have a strong preference and higher willingness-to-pay for good weather-related skiing conditions, suggesting that skiers prefer skiing during the midweek at a higher price, instead of on the weekend, if the skiing conditions are better in the midweek. Relevant implications are provided for practitioners.

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The impact of dynamic price variability on revenue maximization

Cited by 96 publications

References 78 publications

Estimating the price range and the effect of price bundling strategies

Estimating the price range and the effect of price bundling strategies

A special price just for you: effects of personalized dynamic pricing on consumer fairness perceptions

Dynamic pricing assuming demand shifting: the alpine skiing industry

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