The Journal of Revenue Management and Pricing is one of the engines of science and discovery within this field. Science recognises that the pursuit of objectivity in research thus generates knowledge and understanding by attempting to eliminate potential sources of bias, often through controlled experiments. This pursuit of objectivity increases the credibility of scientific advances and expands society’s willingness to take up and use the new knowledge and understanding science provides. The journal is taking science and theoretical concepts and making them real—hence the importance of utility value and application. This is what the journal is about. Huang and colleagues’ study about when is the right time to book is an insightful piece of writing: as customers are uncertain about the best time to get the lowest airfares due to the practice of dynamic pricing in revenue management. Even with the help of price-prediction platforms, the optimal time to buy the lowest-priced airfare remains unclear. This study compares airfare forecasts across the prediction outcomes suggested by Hopper, KAYAK and FareHack. In conclusion, the best deals are to follow Hopper’s suggestions when the time is still early (77 days before departure to 61 days before departure) compared to the first-time search suggestions. Fiig asks the question, can demand forecast accuracy be linked to airline revenue? Since accurate demand forecasts are a key input to any airline revenue management system, it is reasonable to assume that an improvement in demand forecast accuracy would lead to increased revenues. However, this relationship has often been called into question. Past work has not conclusively proven that more accurate demand forecasts lead to higher revenue, causing researchers and practitioners to debate whether the concept of demand forecast accuracy itself is myth or reality and conclude that under some mild assumptions that minimizing conditional demand forecast error will maximize revenue under any fare structure and customer choice behaviour.

Şahin proposes a joint pricing model that combines the advantages of variable and dynamic ticket pricing models, where optimal dynamic prices are calculated for sporting events based on game-, time-, and inventory-related factors. Three different pricing scenarios were formulated to reveal the most effective dynamic pricing model, and each model was analysed in detail. The results show that they were able to increase the expected revenue by between 14.12 and 35.27% compared to a traditional static pricing model, meaning that all three of the proposed joint pricing models were more effective than the traditional pricing strategy. Sur and colleagues adopted the Stackelberg model to analyse the optimal revenue sharing rates between these two parties when the platform provider acts as a leader, while the service providers are followers. The results of the study conclude previous revenue sharing studies assumed a cooperative relationship between platform providers and app developers: optimal revenue sharing rates change situationally. The paper supported these arguments.

Wagner’s paper is about the role of pay-what-you-want pricing mechanism (PWYW). Retailers often use monetary promotions (e.g. discounts) to sell excess capacity, increase short-term revenue, and create a low-price image. However, the frequent use of discounting may lower consumers’ internal reference price, until consumers are not willing to pay anything above the promotional price. This issue can be solved using participative pricing mechanisms, under which the retailer does not set an explicit price to be paid. Thus, the results show that the PWYW mechanism usually creates a much lower price image than the posted price mechanism. Da Silva and colleagues investigate how consumers often categorize companies as either cheap or expensive. This overall pricing impression is called price image. Consumers’ price image is formed during the processing of qualitative and intrinsic information, such as advertisement repetition. This study investigated the role of advertisement repetition on consumers’ price image towards a higher education institution, and the moderating role of announced discounts and the institution’s nationality.