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Most airlines utilize a revenue maximizing technique called yield management, which allows the airlines to allocate their fixed capacity of “perishable” seat inventory to various fare categories in the most profitable manner possible. Demand for these fare categories is usually defined in terms of the “business” vs “leisure” customer segments, while capacity is apportioned between discounted vs non‐discounted seats. The discriminatory pricing goal is to sell only non‐discounted seats to the business travel segment. Suggests that yield management techniques may also be appropriate in certain retail settings involving physical products. In the case of physical products, capacity (i.e. product inventory) is not necessarily “perishable” in the same sense as unsold seats on an airline flight; however, its value may decline with the culmination of a well‐defined shopping period or with a particular special event. Examines how the appropriate use of early discount pricing in markets defined by decreasing customer price sensitivity can maximize the revenue gained from sales of a “seasonal” product.

Revenue management has grown in popularity and is now a widely accepted discipline that has brought about significant improvements to businesses worldwide. With globalisation in recent times, there is now space for international hotels, fast food restaurants, automobile companies and other brands to offer their products in India. Educating people who are going to be part of such a process is a huge challenge. The aim of this paper is to present some of the challenges businesses and communities have to overcome.

The paper uses secondary sources to explore possible approaches to rapidly stimulate the uptake of revenue management through partnerships between hospitality and tourism businesses.

A growing middle class population and access to better education presents an opportunity to build a wider range of profitable services. Global brands with already established revenue management practices are in a position to share skills and knowledge with new and smaller players. Partnerships will be essential to rapidly and effectively develop the skills and knowledge required, starting with those in educational fields where the resources are already in place.

Revenue management has not been deployed widely in India. Being able to learn from the early adopters would allow Indian firms to leapfrog over issues and barriers, thus implementing practices more rapidly and effectively.

Yield management has been adopted by many hospitality organizations. An introduction to yield management concepts, resources and ideas for the design and implementation of price and capacity management tools is provided in the context of private club management. The use of contribution‐based yield statistics to monitor the performance of price and capacity decisions in high variable cost operations is discussed, along with reservations policies, perceptions of fairness and the use of coupons to obscure differential price policy.

This paper aims to explore the links between revenue management and business‐to‐business (B2B) relationships and explains how revenue management can both support and damage B2B relationships.

A single case study method was employed to conduct qualitative research into a company and its key accounts. In‐depth data were collected from three divergent sources (company revenue managers, company account managers and nine of the company's key accounts) through semi‐structured interviews, observations and document studies.

The research findings reveal that from the company's perspective, managers acknowledge that revenue management has positively influenced the process of identifying and analysing key account activities and conducting contractual decision making with key accounts. However, from the key accounts' perspective, revenue management practices were found to have significant negative consequences which damage trust and undermine long‐term relationships and commitment.

Although the research findings cannot be generalised to other service sectors because of the single‐case study research method, the implications of this study suggest that the impact of revenue management practice on B2B relationships should be further investigated in a wide range of organisational and industry settings.

The research findings confirm the long‐held assumption that revenue management can negatively affect B2B relationships. The benefits of revenue management primarily reward the company, whilst long‐term B2B relationship development suffers from the short‐term consequences of the company's opportunistic behaviour.

This paper bridges the gap in the literature between revenue management and key account management. It also explores the conceptual incompatibility between revenue management and a long‐term relational approach to B2B relationships and provides evidence to support this proposition.

This study aims to explain briefly the history and the future of revenue and yield management, offering a graphical visual model to identify the main internal and external elements to be faced by revenue managers.

Stemming from what happened in the past, the authors predict the key elements in revenue management moving forward.

The authors discuss four notable emerging themes for a fertile revenue management application: organizational culture; dynamic pricing, both in terms of intertemporal price discrimination and inventory controls; personalized pricing; and distribution channels.

The paper offers informative knowledge to revenue managers and academics working in the area of strategic yield and revenue management.

The objectives of this study are to investigate the relationship between hotel room demand and room rates, and to find a viable solution for the optimal room rate that maximizes the total profit.

There are various studies in the literature on how room rates affect profitability, and how the optimal room rate that maximizes the total revenue can be determined. Most of these studies assume an algebraic relationship between room rates and room demand, and obtain the optimal solution by applying calculus to the revenue or profit function. This study adopts the alternative approach of using a model with a demand function that has been shown to be a superior causal forecasting model in some markets, and develops a new method to optimize the total profit.

The traditional method of applying calculus to the profit function based on a causal forecasting model leads to unrealistic solutions. This gives rise to the paradox that, on the one hand, there is a superior causal forecasting model based on room rates, but on the other hand, the traditional method does not yield a realistic solution for room rate optimization. This study analyzes the underlying causes of this paradox and proposes a method to resolve it.

The findings can be used by hotels to fine‐tune the room rates determined by conventional methods to arrive at a realistic and definitive value for the optimal room rate.

This study highlights the problems that arise with the traditional method of applying calculus to revenue and profit optimization and proposes a new method to resolve it.

To determine conditions under which a hotel in Barbados can benefit from the use of revenue management.

Monte Carlo simulation is used to compare a first‐come first‐served approach for accepting booking requests to a bid price approach. Comparisons are made using different assumptions about upgrading, downgrading and overbooking.

When demand intensity is high, the bid price method yields higher revenue than the first‐come first‐served method. If demand intensity is low, but some necessary resources are scarce and the hotel practises upgrading and downgrading, then the bid price approach can also lead to improved revenue. No evidence was found to suggest that overbooking or downgrading costs affect the relative performances of the two approaches if these costs are taken into consideration.

This research was conducted for one type of hotel using a particular sample period and the conclusions will not necessarily be true for other sample periods and other types of hotels.

The results show that hotels, which practise upgrading, downgrading and overbooking, should consider adopting a revenue management approach, when allocating their scarce resources among competing market segments.

Existing linear programming models of the revenue management problem are extended here to allow for upgrading and downgrading, when one resource is substituted for another in a package, and to allow for overbooking, when the hotel cannot honour a booking because of the unavailability of some resource. This formulation emphasizes the efficient allocation of all of the hotel's scarce resources.

Argues that in order to sustain the long‐term profitability and growth of hotel organizations, yield management decisions must incorporate two critical constraints: the cost implications of the customer mix and guest ancillary spend. Proposes that customer profitability analysis (CPA), which reports revenues, costs and profit by customer group, will give management the ancillary spend and cost information that will enhance customer mix decisions over a long‐term horizon. Identifies that the key to CPA lies in the application of an appropriate method of allocating costs to customers and proposes that activity‐based costing is the optimal costing solution.

Definitions of yield management vary in terms of their content and focus. Develops a “best fit” definition of yield management of the hotel sector by reviewing the literature in this area and extracting the key words and central meanings used. In addition, produces a list of eight features using a comparison and analysis of the views of London‐based front office managers and features of yield management applications promoted through vendors′ sales literature. Together these eight features illustrate what an ideal yield management application would offer. While all of the applications currently for sale within the UK offer some of these features, none of them are capable of performing the complete range.

The static world of flight scheduling where schedules rarely change once published is becoming more responsive with schedule change updates leading up to the departure date due to demand volatility and unpredictable demand patterns. Innovation in cash flow generation will take center stage to operate the business in these uncertain times. Forecasting demand for future flights is a challenge since historical demand patterns are not meaningful which requires a new adaptive robust revenue management approach that monitors key metrics, detects anomalies and quickly takes corrective action when performance targets cannot be achieved.

The novel COVID-19 pandemic decimated the travel industry in 2020 and continues to plague us with no end in sight. With the steep drop in revenues, airlines need to adapt to a new marketing planning process of scheduling, pricing and revenue management that is more nimble to adapt quickly to changing market conditions. This new approach will continue to be relevant in a post-COVID-19 world during and after economic recovery.

A methodology for airline revenue planning: scheduling, airline pricing and revenue management, has been proposed that will also work in a post-COVID-19 era.

The limitation of the proposed model is that it needs to be applied in practice to determine the true benefits of this novel approach to airline revenue planning.

Flight scheduling will rely more on clean sheet scheduling, schedule revisions and close in refleeting to better match demand to supply. The office of the chief financial officer will have a permanent task force to monitor cash flow and come up with innovative solutions to generate cash flow for liquidity. Adaptive robust revenue management workflows will be integrated into traditional revenue management workflows in the future for competitive advantage.

In a post-COVID-19 world it is anticipated that airline business processes will transform to be nimbler and more proactive in making timely decisions at a greater velocity.

The approach to airline revenue planning for scheduling, pricing and revenue management is a new business process that does not exist today at scale in the airline industry.