Perceived unfairness of revenue management pricing: developing a measurement scale in the context of hospitality

Abstract

Purpose This paper aims to offer a multi-dimensional scale for measuring the concept of perceived unfairness of revenue management pricing (RMP) in the context of hospitality. Design/methodology/approach To develop a measurement scale for the perceived unfairness of RMP, the authors conducted a qualitative study using the critical incident technique to identify the key components of our measurement tool. They then collected two samples of quantitative data enabling them to have compelling evidence of the scale’s reliability and validity. Findings This research identified three dimensions of perceived unfairness of RMP in the context of hospitality: perceived normative deviation, perceived opacity and negative effects. The new scale proposed here is an alternative measurement instrument that could be useful for detecting and correcting some negative aspects of RMP. Practical implications This measurement scale will help hotel managers to detect potential feelings of unfairness in relation to the RMP policies. It might also be used within the framework of market analyses and pricing strategy plans. Finally, the results of this research show that transparency, fairness and ethics based pricing could help hotel managers increase their revenue-per-available-room during and post COVID-19 pandemic. Originality/value This research develops a complete measurement scale for perceived unfairness of RMP, including cognitive and affective dimensions. The richness of this scale will help hospitality companies effectively identify the indicators that denote perceived unfairness of RMP, making them better equipped to handle customer dissatisfaction.

Cruise revenue management: cross-discipline literature review and development of an integrated cruise revenue management framework

“…There is much potential for cruise RM studies, Table 1 presents some broad agenda that can be elaborated on. For example, cruise RM research could adopt choice-based RM optimization models (Bodea et al, 2009) and determine customers' perceived values, price fairness (Meatchi et al, 2021), value proposition, willingness-to-pay in creating price discrimination (Chandler & Lusch, 2015), and the cross-elasticity estimation to be integrated into the RMS (Bayoumi et al, 2013). Interviewees divulged the importance of psychology in spending which goes beyond RM reference.…”

A longitudinal analysis of revenue management strategies and measures implemented in the hospitality industry during the COVID-19 crisis

“…As mentioned, there are few studies focussing on RM measures applied in hospitality during COVID-19 (Bandalouski et al ., 2021; Guillet and Chu, 2021; Hao et al ., 2020; Meatchi et al ., 2021; Nair, 2021; Piga et al. , 2022; Qiu, 2021; Smart et al ., 2021; Talón-Ballestero et al.…”

“…, 2020). The use of fair, transparent and ethical pricing would help hoteliers to manage hotels more effectively during the COVID-19 pandemic as well as in the long run (Meatchi et al ., 2021).…”

“…RM measures have proven to be effective in previous crises (Caudillo-Fuentes and Li, 2009; Gehrels and Blanar, 2013; Kimes, 2010; Kimes and Anderson, 2011; Mainzer, 2009) although there is scarce literature that analyses the measures applied during the COVID-19 crisis (Bandalouski et al ., 2021; Guillet and Chu, 2021; Hao et al ., 2020; Meatchi et al ., 2021; Nair, 2021; Piga et al. , 2022; Qiu, 2021; Smart et al ., 2021; Talón-Ballestero et al.…”

Forecasting hotel room prices when entering turbulent times: a game-theoretic artificial neural network model

“…The role of revenue managers in determining hotel pricing is crucial but can also lead to customers perceiving it as unfair (Meatchi et al , 2021). When hotels set prices that are perceived as unrealistic or unfair by consumers, it can lead to a shift in demand towards peer-to-peer accommodation options (Sainaghi, 2021), as consumers may view peer-to-peer options as more affordable (Chi et al , 2021).…”