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The purpose of this study is to examine the association between revenue-based earnings management in the periods immediately before and after firms’ initial public offerings (IPOs) and regulatory scrutiny by the United States Securities and Exchange Commission (SEC) during review of IPO firms’ registration statements.

This paper uses conditional discretionary revenues (Stubben, 2010) as its measure of earnings management, and revenue recognition comments delivered by the SEC as its measure of regulatory scrutiny. The authors use ordinary least squares regression (OLS) models, as well as a supplemental count model, to assess the association between conditional discretionary revenues and revenue recognition comments delivered by the SEC.

This study finds evidence of a positive association between earnings management measures in the pre-IPO period and the number of revenue recognition comments received by those firms during the SEC’s review. Furthermore, this study provides evidence that greater numbers of comments are associated with declining earnings management measures in the post-IPO period. However, the evidence suggests that these associations apply only to income-decreasing earnings management.

This paper extends the IPO earnings management literature by using conditional discretionary revenues as the measure of earnings management, and contributes to a nascent research stream in the accounting literature by investigating the SEC’s comment letter process and its association with, and impact upon, earnings management in the IPO process.

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.

Restaurants typically have small profit margins and with the pressure of increasing food and labor costs, management is looking to revenue as a way to maintain and drive profits. One technique to increase revenue is through revenue management practices, but management needs to be aware of their customers’ reactions to these practices prior to implementation. The paper aims to discuss this issue.

This study utilizes linear regression to determine the impact of select restaurant revenue management practices, customers’ familiarity with revenue management in general and in restaurants specifically, and customers’ demographics on perceived fairness of revenue management practices in casual and fine-dining restaurants.

Results indicate that customers find certain restaurant revenue management practices, such as charging premium prices on certain days of the week, fair in both casual and fine-dining restaurants, while others are not in either. Non-refundable reservation fees were found to be fair for fine-dining establishments only. Increased familiarity with restaurant revenue management was associated with higher perceptions of fairness for both casual and fine dining. Age was the only demographic studied that affected perceived fairness.

This study is the only known study to simultaneously evaluate the impact of price and duration restaurant revenue management techniques in combination with customer demographics and revenue management familiarity on consumer perceptions of fairness.

The purpose of this paper is to develop a framework for the systematic examination of management accounting practices in small businesses using a revenue management perspective. This highlights the multi-faceted nature of size as a contextual factor and emphasises the role of management accounting in supporting profit-oriented decision-making, rather than its traditional role of co-ordination, control, and accountability.

The framework is theoretically derived from the management accounting, revenue management, and small business literature. An illustrative case study of a small fast-food business is presented to demonstrate the applicability of this framework to practice.

The paper identifies that various dimensions of business size have different and sometimes opposing effects on management accounting practices. Given heterogeneity is a common feature of small businesses, the framework considers alternative specifications of the size contingency variable.

The synthesis of small business characteristics and revenue management perspective offers a more incisive understanding of what has traditionally been considered a simple practice. The case study illustrates some of the influences of small business characteristics identified in the framework. Given its narrow scope, the findings are used for theorisation rather than offering generalisable results. Further cross-sectional comparisons of small businesses are needed to confirm size influences.

The framework can assist practitioners to gauge the strengths and weaknesses of their management accounting practices and can help assess the value of adopting more sophisticated management accounting practices, given their particular business environment. A synthesis of these small business attributes can help practitioners identify key barriers to implementation.

The revenue management perspective and the inclusion of key characteristics of small businesses provide a new approach to evaluating management accounting practices in small businesses.

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.

This paper aims to recommend opportunities for professional sport leagues in the USA and Canada to apply the art and science of revenue management in order to minimize potential losses and maximize profits.

The evolution of current key revenue management concepts is presented from their initial stages to their current level of implementation. In addition, the literature regarding the strongest business models is reviewed and examined in the context of current successes and challenges across the major sport leagues in North America.

Five revenue streams in sports organizations are identified and analysed. Five key elements for revenues are highlighted as strategic tools used to maximize effectiveness in achieving revenue management goals. A series of recommendations is made to best use revenue management including careful negotiation of television contracts, the use of dynamic pricing models, maximization of partnerships and sponsorships, acceptance of new approaches to food and beverage and accessibility of sport merchandise to customers.

At the regional, national and international levels, sports organizations should review their current business practices to identify areas to improve their revenue management in light of the recommendations in this paper.

Although the use of the concept of revenue management in sectors of tourism has evolved since early 1970s, its application in professional sports is relatively new. Therefore, this paper provides value to professional sports organizations to optimize their profitability.

The purpose of this paper is to investigate the perceptions that managers have of the value and reliability of using big data to make hotel revenue management and pricing decisions.

A three-stage iterative thematic analysis technique based on the approaches of Braun and Clarke (2006) and Nowell et al. (2017) and using different research instruments to collect and analyse qualitative data at each stage was used to develop an explanatory framework.

Whilst big data-driven automated revenue systems are technically capable of making pricing and inventory decisions without user input, the findings here show that the reality is that managers still interact with every stage of the revenue and pricing process from data collection to the implementation of price changes. They believe that their personal insights are as valid as big data in increasing the reliability of the decision-making process. This is driven primarily by a lack of trust on the behalf of managers in the ability of the big data systems to understand and interpret local market and customer dynamics.

The less a manager believes in the ability of those systems to interpret these data, the more they perceive gut instinct to increase the reliability of their decision making and the less they conduct an analysis of the statistical data provided by the systems. This provides a clear message that there appears to be a need for automated revenue systems to be flexible enough for managers to import the local data, information and knowledge that they believe leads to revenue growth.

There is currently little research explicitly investigating the role of big data in decision making within hotel revenue management and certainly even less focussing on decision making at property level and the perceptions of managers of the value of big data in increasing the reliability of revenue and pricing decision making.

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.

The purpose of this study is to understand how and to what extent Hong Kong hotels have integrated customer relationship management (CRM) into their revenue management (RM) practices at individual customer level.

Semi-structured interviews were used to gather information from experienced interviewees holding hotel RM- and marketing-related executive positions. In total, 11 revenue and 9 marketing executives were interviewed in 2016-2017 over a period of 13 weeks. The data were transcribed and then Nvivo was used for data organization and analysis.

The hotels do not systematically segment customers by value because of restraints on the RM systems’ capabilities and the industry’s conventional segmentations. The revenue and marketing executives’ attitudes toward integration, IT system infrastructure support to enable integration, loyalty and membership programs as a means for integration and executive management level support for integration influence the hotel’s potential for RM and CRM integration.

Only the perspectives of revenue and marketing executives were considered. Incorporating the insights of different parties may achieve a more comprehensive result. In addition, because it seems that there is no systematic RM and CRM integration within the Hong Kong hotel industry, relevant decision-makers’ opinions toward the practice may change once they evaluate the performance of the pioneering practitioner.

This study reveals what has been done in practice to integrate RM and CRM compared with the theoretical approach, proposes an integration framework and discusses the potential for further development together with the challenges to integration.

Customs risk management has been widely recognized as a powerful tool to balance between trade facilitation and revenue maximization. However, most customs administrations worldwide, particularly in developing countries, are suffering from a lack of experience and knowledge to assess their risk management systems for revenue protection (RP). Customs risk management has a very limited legacy in the literature. Academic research is quite scarce and very limited, although its relevance to customs administrations. This paper aims to identify the key risk profiles and indicators that contribute to the protection of customs revenue and investigate the role of these risk profiles and indicators on customs RP using the case of Jordan Customs.

This study adopts a panel data approach by using the case of Jordan Customs. Data were collected from the risk targeting and selectivity system at Jordan Customs for the year 2019, a total of 600 observations.

The findings show that all risk targeting criteria except random selectivity (RS) and HS code have a significant positive association with RP. The findings also revealed that RS is an effective tool to prevent traders with fraud and offenses history from a prediction of targeting patterns and to assess the traders’ compliance and make sure their declarations are free from fraud or offenses. Moreover, the findings of this study indicate that customs administrations should adopt alternative programs such as authorized economic operator and post clearance audit as an effective means to measure and improve compliance.

The main contribution of this study lies in proposing a model to assist customs administrations in assessing the performance of risk management systems to protect revenue. This model provides a comprehensive conceptualization and explanations necessary for numerous aspects of risk management projects and it assists to predict the outcomes based on formulated indicators.

This study provides guidelines for risk analysts on how to identify and assess the key risk profiles and indicators that effect on maximizing the detection of revenue leakage and to obtain interpretable and predictable results. In addition, the findings of this study will assist customs administrations in supporting revenue collection, minimizing uncertainty, allocating resources more effectively to target high-risk consignments, while simplifying the procedures for the safe consignments.

This paper is of significant value because it is one of the preliminary studies that empirically identify the risk indicators/profiles that contribute to the protection of revenue and investigate the predictive power of these risk indicators/profiles as a key predictor to protect customs revenue.