Customer Perception of Pricing Strategies and Their Influence on Hotel Booking Decisions: Evidence from Rajasthan

Abstract

The growing competitiveness and fluctuating demands of tourism are a challenge to the hospitality industry, and the issue of prices is a critical issue that determines the choice of hotels to stay. Hotels commonly vary the price of their rooms using dynamic, seasonal, discount, and corporate pricing to maximize their occupancy and income. Price differences, however, are seen differently by customers, and this poses a challenge in ensuring price transparency, fairness, and customer satisfaction. Although pricing strategies are important in hotel revenue management, most of the current studies mainly concentrate on operation revenue optimization models instead of analyzing how customers interpret the pricing strategies in their position to make a given reservation. Additionally, there is a scarcity of empirical studies within up-and-coming tourism destinations like the state of Rajasthan, where the seasonal tourism demand and competitive hotel industries play an important role in what is happening in the pricing and the market. The current study is aimed to fill this research gap by answering the question about the effects of different pricing strategies on hotel reservation decision- making: Dynamic Pricing, Seasonal Pricing, Discount Pricing, Corporate Pricing, Psychological Pricing, and Price Fairness. A quantitative research design was followed with the help of a structured questionnaire survey including 100 respondents, who are in key tourism destinations within the state of Rajasthan. The data gathered were evaluated with the help of statistical methods such as correlation analysis, analysis of variance (ANOVA), the evaluation of effect size with the help of partial eta squared, and the multiple regression model. It shows that Price Fairness 1 has the highest impact on the reservation decision with an ANOVA F 0.241 and the effect size (η²) of (0.358), followed by Corporate Pricing (F ≈ 15.5, η² ≈ 0.265) and Psychological Pricing (F ≈ 11.1, η² ≈ 0.205). There is a good predictive power of the regression model, with the model having the value of R² = 0.67 and Adjusted R² = 0.63, which shows that almost 67% of the change in the reservation decision-making can be attributed to pricing strategies. The results show that clear, equitable, and strategically planned pricing systems play a key role in determining customer booking behavior. The research offers real-life knowledge that can be applied by hotel managers to come up with good pricing strategies to maximize reservations and customer satisfaction within the competitive tourism markets.