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This study aims to adopt a holistic approach to understand cruise revenue management (RM) practices that cover ticket and onboard revenues, through a cross-disciplinary literature review and practitioner interviews. An integrated cruise RM framework was developed and served as a blueprint for future cruise studies and practices.

A multi-stage approach was adopted, including a systematic literature review, two-waves of interviews with 26 cruise industry practitioners and the development of a holistic RM framework.

This study clarifies cruise RM functions across product planning, delivery stages and identifies ticket and onboard RM components. These are incorporated into the integrated framework, with weather and itinerary/ route attractiveness as additional considerations. Interviews revealed that there is no difference in the RM cycle before and during the COVID-19 pandemic, although strategies and tactics may vary in response to the market situation.

Suggestions are made regarding product and service bundling and ways for ticket and onboard revenue teams to work together to optimize total revenue. Future research directions are also provided under the categories of RM applications and concepts, ticket core activities, onboard core activities and overall issues.

To the best of the authors’ knowledge, this is the first paper to conduct a cross-disciplinary systematic literature review of cruise RM without imposing publication dates or specific databases and the first to develop an integrated cruise “total” RM framework that includes ticket and onboard revenues.

The increasing popularity of ERP solutions has provided dietary supplement manufacturing companies with modules to manage pricing and inventory. However, the decisions made by these modules are often independent and rely on deterministic forecasts. This paper studies a multi-product dietary supplement manufacturing system under stochastic demands. The purpose is to maximize the long-run expected profit by jointly considering pricing and inventory strategies.

The authors investigate both the general cases and three special cases including stable demand, negligible backlog and instantaneous replenishment. A two-stage algorithm named PAS is proposed. In the strategy construction stage, the constructed objective bounds are combined to provide estimates which then help to derive the optimal product prices. In the system operation stage, replenishment decisions are further made based on the prices generated from the previous stage.

It is proved that base-stock policy is optimal for the studied system, and the optimal based-stock level is provided. The global optimal strategies are obtained for three important special cases. For the general case, theoretical objective bounds are established. These bounds provide quick and reliable performance estimates for practical applications.

Very few studies have jointly considered pricing and inventory strategies with uncertainty demands in the dietary supplement industry. The PAS algorithm developed integrates these decisions and consistently generates high-quality solutions even under highly varying demands. Such algorithm could be a valuable add-on to the pricing and inventory management modules in ERP systems.

This paper aims to explore the impact of emerging technologies, such as virtual reality, voice search, artificial intelligence, robotics and the Metaverse on hotel sales, marketing and revenue optimization.

This paper uses a combination of articles published in Journal of Hospitality and Tourism Technology and industry case studies to examine the integration of innovative technologies in hotel sales, marketing and revenue optimization strategies, plus the role of fundamental practices in ensuring long-term success.

The analysis demonstrates that innovative technologies can significantly enhance customer engagement, streamline booking processes and unlock new revenue streams. However, this paper also highlights the importance of fundamental marketing practices, such as user-friendly websites, fast and reliable/mobile-friendly websites, search engine optimization, social media engagement, content marketing and data-driven revenue management, in maintaining a hotel’s competitive advantage in the dynamic world of hospitality.

The findings suggest that hoteliers need to strike a balance between embracing emerging technologies and maintaining traditional marketing fundamentals to remain competitive and drive revenue growth. This integrated approach ensures long-term success in the ever-evolving hospitality landscape.

This paper bridges the gap between academia and industry practitioners by providing practical insights and implications that can be applied directly to hotels’ marketing and operational practices. The paper highlights the importance of balancing innovation with fundamental marketing strategies, emphasizing the need for an integrated approach to ensure long-term success in the ever-evolving world of hotel sales, marketing and revenue optimization – as well as those same tools in a plethora of hospitality and tourism venues working alongside the accommodations sector.

探讨新兴技术（如虚拟现实、语音搜索、人工智能、机器人技术和元宇宙）对酒店销售、营销和收入优化的影响。

本文结合发表在《酒店旅游科技杂志》（JHTT）的文章和行业案例, 研究了创新技术在酒店销售、营销和收入优化策略中的整合, 以及基础实践在确保长期成功方面的作用。

分析表明, 创新技术可以显著增强客户参与度, 简化预订流程, 并开拓新的收入来源。此外, 文章强调了基本营销实践, 如用户友好的网站、快速可靠/移动友好的网站、搜索引擎优化、社交媒体参与、内容营销和数据驱动的收入管理, 在保证酒店在充满变化的行业竞争中维持优势的重要性。

研究结果表明, 酒店经营者需要在使用新兴技术和保持传统营销基本原则之间取得平衡, 以保持竞争力并推动收入增长。这种综合方法确保在不断发展的酒店销售、营销和收入优化领域取得长期成功。

本文通过提供可直接应用于酒店营销和运营实践的实际见解和影响, 弥合了学术界与行业从业者之间的鸿沟。文章强调了创新与基本营销策略的平衡的重要性, 强调了综合方法的必要性, 以确保在不断发展的酒店销售、营销和收入优化领域取得长期成功, 以及这些工具在众多酒店和旅游场所与住宿部门一起工作的多样性领域中的应用。

From a supply chain perspective, logistics firms collaborate with other supply chain members to extend their business scope. Investment in circular economy projects in the supply chain can not only broaden the scope of business but also increase the value of the entire supply chain. Third-party logistics companies are gradually participating in the construction and operation of many circular economy projects. How to coordinate multiple circular economy supply chain projects is at the core of its operation.

This paper first analyzes some typical supply chain projects in China and summarizes the main features of these projects. Secondly, considering the benefits of the project and the stakes of each project, a multi-stage stochastic programming model is established. Finally, Cplex, nested decomposition, LocalSolver and other methods are adopted to simulate and analyze the model.

The final experimental results find that the importance of coordinating multiple circular economy supply chain projects to increase the value of the entire supply chain. The multi-stage stochastic programming model presented in this research can provide a useful tool for logistics enterprises and third-party logistics companies to optimize their investment decisions and maximize their profits in the context of a circular economy.

There are still some limitations to this study; for example, it is limited to the analysis of circular economy supply chain projects in China. The study focused on third-party logistics companies, and other enterprises in the circular economy supply chain were not considered. The research also assumed that the benefits of each circular economy project and the stakes of each project were known, which may not always be the case in real-world scenarios.

This manuscript found that investing in other circular economy projects in the supply chain can broaden the scope of business and increase the value of the entire supply chain. Third-party logistics companies are gradually participating in the construction and operation of many circular economy projects, such as recycling and repurposing initiatives. It highlights the importance of coordinating multiple circular economy supply chain projects to increase the value of the entire supply chain. The multi-stage stochastic programming model presented in this research can provide a useful tool for logistics enterprises and third-party logistics companies to optimize their investment decisions and maximize their profits in the context of a circular economy.

The learning outcomes of this study are to recall the fundamental concept of revenue management in the hotel industry (remembering); explain the various performance measures used to evaluate room revenue in hotels (understanding); use revenue management strategies to improve room revenue in hotel operations (applying); and examine and evaluate the optimal solution for revenue enhancement, considering factors such as capacity management, duration control and differential pricing (analyzing).

This case study delves into the challenges faced by Hotel King’s Cross, a business hotel located in Pune, Maharashtra, in the year 2022. A week before Christmas Eve, Soham Dande, the hotel’s revenue manager, sought a meeting with Rohan Chopra, the director of sales and marketing, to discuss “revenue optimization for the hotel.”

During their meeting, Dande mentioned that the hotel had fallen behind its budgeted room sales targets for 2022 across various metrics, such as room booking nights, occupancy percentage, average room rate and revenue per available room. Furthermore, the hotel was trailing behind its competitors. The situation was compounded by the management’s decision to raise the targets for 2023 by 5%–7%, factoring in upcoming events, competitive performance and pandemic-related losses over the past two years. Chopra faced the dilemma of formulating an action plan to achieve the ambitious 2023 targets and establish Hotel King’s Cross as a market leader.

Students undertaking executive development programs and graduate-level courses in non-profit hospitality and tourism management, as well as revenue management courses in the executive MBA, management development and graduate MBA programs, may all benefit from this case study.

Teaching notes are available for educators only.

CSS12: Tourism and hospitality.

The main stance of this paper is to draw an authentic and rigorous outlook in terms of the financial and operational performance of small lodging establishments (SLEs) and put forth achievable and practical economic solutions that demonstrate the relative effectiveness of the adopted measures. This paper also suggests practical solutions to help minimize SLEs' financial vulnerability to long-term crisis and to boost their resilience with relative measures by applying recovery revival strategies for this particular segment of the lodging industry.

The authors have picked a locally owned resort hotel in Central Florida area and structured a real-life, case study-based inductive approach that is purposeful and offers rich economic outlook and analysis for the entire lodging industry, especially for the resort-hotel type of accommodation facilities. The main reason for why they only focus on one company is that they can fully understand the financial effects of COVID-19 on resort type of hotels and layout countering strategies. To achieve paper objectives, they have implemented cost–benefit (C–B), break-even (B-E) analyses along with a sensitivity testing approach.

The most striking result was that during the state-mandated shutdown period in 2020, overhead and overall operational costs associated with room sales and revenues were very high during this period that shrank the contribution margin ratio for rooms CMRw (room) and eventually yielded high sales volumes to be achieved at the B-E points vs lower sales volumes with almost the same average daily rate (ADR) levels needed for the B-E levels.

Future studies should specifically delve further into a portfolio of SLEs in the region or state or nation wise because the units comprising the SLEs might be too small to muster the changes required to bounce forward for the entire lodging industry in the world.

The resort's revenue re-optimization focus should center on financial re-benchmarking and business re-viability stress under different levels of shock scenarios. According to the different scenarios and calibrations for the ADRs, room nights, net present values (NPVs) of cash flows and profit margins derived from our main analyses, minimizing expenses and preserving cash would be the best key strategy for financial recovery during an ongoing COVID-19 pandemic.

It is obvious that the lodging, hospitality and tourism industry are the hardest-hit industries by the harsh and adverse effects of COVID-19. The effects of pandemic are differently shaped on operations in different industries and subsectors. Therefore, the operational and financial evaluation for the SLEs as the core and a catalyst in the entire lodging industry can shed a light on the strategic financial recovery procedures with broadly applicable real-life and endogenous capabilities and reasoning.

The purpose of this study is to review and synthesize the literature on in-app advertising, identify gaps and propose future research directions.

The authors use a systematic literature review (SLR) approach, following the PRISMA guidelines, to investigate the current state of research in in-app advertising. The study uses 44 shortlisted articles from the Scopus and Web of Science databases. Using the Theory-Context-Characteristics-Methodology (TCCM) framework, the authors analyze the gaps in theory, context, characteristics and methods.

Using thematic analysis, the authors identify five main themes in the in-app advertising literature, namely, ad platform optimization; mobile app user psychology and behavior; ad effectiveness; ad fraud; and security, privacy and other user concerns. The findings show the need for empirical research, with a strong theoretical foundation in emerging ad formats of in-app advertising, user behavior and buy-side of in-app advertising.

This is a maiden study to conduct a domain-based SLR in the emerging field of in-app advertising using the TCCM framework. The authors highlight the key differences between in-app advertising and mobile web advertising. The authors propose theories in the advertising field that could be used in future empirical studies of in-app advertising.

El propósito de esta investigación es revisar y sintetizar la literatura sobre la publicidad en Apps, identificar lagunas y proponer futuras direcciones de investigación.

Utilizamos un enfoque de revisión sistemática de la literatura, siguiendo las directrices PRISMA, para investigar el estado actual de la investigación en publicidad en aplicaciones. El estudio utiliza 44 artículos preseleccionados de las bases de datos Scopus y Web of Science (WoS). Utilizando el marco Teoría-Contexto-Características-Metodología (TCCM), analizamos las lagunas en teoría, contexto, características y métodos.

Mediante un análisis temático, identificamos cinco temas principales en la literatura sobre publicidad en aplicaciones, a saber: optimización de plataformas publicitarias; psicología y comportamiento de los usuarios de aplicaciones móviles; eficacia publicitaria; fraude publicitario; seguridad, privacidad y otras preocupaciones de los usuarios. Nuestros hallazgos muestran la necesidad de investigación empírica, con una sólida base teórica en los formatos publicitarios emergentes de la publicidad en Apps, el comportamiento del usuario y el buy-side de la publicidad en Apps.

Se trata de un estudio pionero para realizar una revisión sistemática de la literatura basada en el dominio en el campo emergente de la publicidad en Apps utilizando el marco TCCM. Destacamos las principales diferencias entre la publicidad en aplicaciones y la publicidad en la web para móviles. Proponemos teorías en el campo de la publicidad que podrían utilizarse en futuros estudios empíricos sobre la publicidad en Apps.

本研究旨在回顾和总结有关应用内广告的文献, 找出差距并提出未来的研究方向。

我们采用系统性文献综述方法, 遵循 PRISMA 指南, 调查应用内广告的研究现状。研究使用了 Scopus 和 Web of Science (WoS) 数据库中的 44 篇入围文章。利用理论-背景-特征-方法（TCCM）框架, 我们分析了理论、背景、特征和方法方面的差距。

通过主题分析, 我们确定了应用内广告文献的五大主题, 即广告平台优化; 移动应用用户心理和行为; 广告效果; 广告欺诈; 安全、隐私和其他用户关注点。我们的研究结果表明, 有必要在应用内广告的新兴广告形式、用户行为和应用内广告买方等方面开展实证研究, 并奠定坚实的理论基础。

这是一项首次使用 TCCM 框架对新兴的应用内广告领域进行基于领域的系统性文献综述的研究。我们强调了应用内广告与移动网络广告的主要区别。我们提出了广告领域的理论, 可用于未来的应用内广告实证研究。

This study aims to examine consumer perception during COVID-19 and identifies cruise industry marketing strategies to fill a gap in crisis management and product pricing literature.

This study developed and validated two-factor measurement scales (vaccine perception and protective behavior), which predicted cruise intents well. This study revealed how geo-regional factors affect consumer psychology through spatial analysis.

This study recommended pricing 7-day cruises at $1,464 (the most preferred length). The results also showed that future price hikes would not affect demand and that coastal marketing would help retain customers.

This study contributed to the business, hospitality and tourism literature by identifying two new and unique factors (vaccine perception and protective behaviors), which were found to affect consumers’ intention to travel by cruise significantly. The result provided a better understanding of cruise tourists’ pricing preferences and the methods utilized could easily be applied to other cruise markets or tourism entities.

Digitalization and marketing technologies have made it possible to overcome some barriers to pricing – a multidisciplinary field between marketing, finance and IT – and have set the stage for a paradigm shift in the pricing profession. Value creation, the pricing process, and price communication have been transformed by innovative business models and advanced algorithmic and human–machine solutions. This chapter synthesizes the literature to date and provides a comprehensive framework for an all-encompassing 360° pricing approach that broadens the understanding of pricing in the context of digital business across all steps of the price management process. Starting from product attributes and motivational beliefs in consumers' value assessment and adoption of (technological or digital) products or services, new business models and pricing models emerge in the digital economy, human–machine solutions for price implementation and repricing are increasingly applied, and price search and communication take place through a variety of digital communication channels. Each stage of this framework discusses concrete examples, highlighting the freemium strategy, the subscription model, price tracking and repricing tools, and digital price information channels such as e-commerce, marketplace, or price comparison platforms. The implications for price management in a digital, technology-driven landscape are discussed from the executive level to the analyst level.

This research aims to determine the ideal fare for various aircraft itineraries by modeling prices using a neural network method. Dynamic pricing has been studied from the airline’s point of view, with a focus on demand forecasting and price differentiation. Early demand forecasting on a specific route can assist an airline in strategically planning flights and determining optimal pricing strategies.

A feedforward neural network was employed in the current study. Two hidden layers, consisting of 18 and 12 neurons, were incorporated to enhance the network’s capabilities. The activation function employed for these layers was tanh. Additionally, it was considered that the output layer’s functions were linear. The neural network inputs considered in this study were flight path, month of flight, flight date (week/day), flight time, aircraft type (Boeing, Airbus, other), and flight class (economy, business). The neural network output, on the other hand, was the ticket price. The dataset comprises 16,585 records, specifically flight data for Iranian airlines for 2022.

The findings indicate that the model achieved a high level of accuracy in approximating the actual data. Additionally, it demonstrated the ability to predict the optimal ticket price for various flight routes with minimal error.

Based on the significant alignment observed between the actual data and the tested data utilizing the algorithmic model, airlines can proactively anticipate ticket prices across all routes, optimizing the revenue generated by each flight. The neural network algorithm utilized in this study offers a valuable opportunity for companies to enhance their decision-making processes. By leveraging the algorithm’s features, companies can analyze past data effectively and predict future prices. This enables them to make informed and timely decisions based on reliable information.

The present study represents a pioneering research endeavor that investigates using a neural network algorithm to predict the most suitable pricing for various flight routes. This study aims to provide valuable insights into dynamic pricing for marketing researchers and practitioners.