Abstract

Background: Price fairness has been defined as consumers’ assessment, together with associated emotions, of whether the difference, or lack of difference, between a seller’s price and the price offered to a comparative other party is reasonable, acceptable, or justifiable (Xia et al., 2004). Building on this definition, the present study re-examines price fairness in the context of contemporary tourism markets, where comparison tools, multiple distribution channels, increased price and information transparency, and algorithmic pricing substantially alter how consumers evaluate prices. An in-depth examination of price fairness in tourism is particularly relevant, as prior research suggests that consumers are more likely to perceive price unfairness in services than in products (Bolton et al., 2003).

At the same time, tourism and hospitality research has shown growing interest in prospect theory and its core principles, including reference points, loss aversion, and diminishing sensitivity (Park & Yi, 2025). However, applications of prospect theory (Kahneman & Tversky, 1979; Tversky & Kahneman, 1992) in tourism remain at an early stage, with fragmented research topics and theoretical inconsistencies that require further validation (Lin et al., 2024). In parallel, despite the widespread adoption of algorithmic pricing, the concept remains insufficiently defined, with limited agreement on a simple and consistent conceptualization (Seele et al., 2021; Spann et al., 2025). These developments create a need to revisit price fairness through the combined lenses of prospect theory, algorithmic pricing, and tourism market complexity.

Research Aim and Methodology: This study aims to develop and refine critical constructs related to price fairness and algorithmic pricing in the context of the hospitality market, and to formulate propositions concerning the relationships among these constructs. Building on the theories-in-use (TIU) approach, which explores individuals’ perspectives and mental models regarding how phenomena operate in specific contexts (Argyris & Schön, 1974; Zeithaml et al., 2020), the study examines how hospitality professionals understand and define price fairness in contemporary pricing environments. TIU is particularly suitable for constructing organic marketing theory because it reflects the practical world and treats market stakeholders as holders of theory-relevant knowledge (Zeithaml et al., 2020).

More specifically, the study seeks to:

• explore the boundaries of price fairness and unfairness in light of prospect theory and AI-based technologies, including algorithmic pricing;
• identify antecedents, moderators, and mediators linking price fairness, AI use, and related tourism behavior constructs, such as price transparency, information transparency, price complexity, price confusion, anchoring, reference points, and perceived value; and
• examine the outcomes of price fairness perceptions and algorithmic pricing for customer behavior, including strategic behaviors, perceived gains and losses, loss aversion, emotions, reactions, and concerns.

To address these aims, in-depth interviews were conducted with 22 experienced marketing and sales managers working in the hospitality industry. This sample size aligns with Zeithaml et al.’s (2020) recommendation that a typical TIU research project should involve in-depth interviews with approximately 15–25 participants selected in successive phases. The qualitative design enables the identification of working definitions, construct boundaries, and complex if–then relationships involving antecedents, consequences, moderators, and mediators of price fairness in algorithmically mediated pricing contexts.

Findings: Preliminary findings offer valuable insights into price fairness in hospitality. The subjective nature of price fairness evaluations is confirmed, with participants emphasizing the role of multiple reference points, including competitors’ prices, seasonality effects, location parameters, previous booking experiences, expected prices, and prices observed across distribution channels. Algorithmic pricing emerges as a significant market-shaping force for marketers, customers, and intermediaries. However, participants also acknowledge uncertainty regarding its full implications and the respective concerns, suggesting that algorithmic pricing remains a developing phenomenon from managerial, behavioral and policy making perspectives.

The findings further indicate that price and information transparency are central to fairness evaluations, although complex price structures and dynamically changing prices and offers may also generate price confusion. Within this environment, hotel customers appear to adopt increasingly strategic behaviors, including systematic price comparisons, negotiations, delayed booking, and the use of digital technologies to monitor and evaluate offers. Overall, the study contributes to the development of organic marketing theory by clarifying how hospitality professionals conceptualize price fairness, algorithmic pricing, and consumer responses in contemporary tourism markets.