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A major source of external funding for US airports comes from issuing municipal bonds. Credit rating agencies evaluate the bonds using multiple factors, but the judgments behind the ratings are not well understood. This paper examines if airport rate-setting methods affect the bond ratings of US airports.

Using a set of unbalanced panel data for 58 hub airports from 2010 to 2019, we examine the effect of the rate-setting methods and other airport characteristics on Fitch’s airport bond rating.

We find that compensatory airports consistently receive a very high bond rating from Fitch. The probability of getting a very high Fitch rating increases by ∼28 percentage points for a compensatory airport. Additionally, the probability of getting a very high rating is about 33 percentage points higher for a legacy hub.

The study uses Fitch bond ratings. Future studies could examine if S&P’s and Moody’s ratings are also influenced by airport rate-setting methods and legacy hub status.

The results uncover the linkage between bond ratings and their determinants for US airports. This information is important for investors when assessing airport creditworthiness and for airport operators as they manage capital project financing.

This is the first study to evaluate the effects of rate-setting methods on airport bond rating and also the first to document a statistically significant relationship between airports’ legacy hub status and bond ratings.

The present paper answers two significant questions: (1) What are the relative consumer and firm-level effects of marketing through metaverse compared to conventional marketing endeavors? (2) What are the current trends in utilizing the metaverse as reported in the recent literature?

This study employs a systematic literature review methodology, utilizing a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flowchart to synthesize existing research. Thirty-five articles written in English were selected and analyzed from two databases, Web of Science and EBSCO Host.

The findings indicate that consumer-level effects of the metaverse include consumer loyalty and brand attachment. The firm-level benefits are decentralization and cost reductions. The paper proposes a framework indicating variables that could attenuate or enhance the association between immersive components of the metaverse and their resultant effects.

This study contributes to understanding the role of metaverse in marketing practices related to the marketing mix components. The study conceptualizes a novel framework for the metaverse and its resultant effects.

An important and challenging question for air transportation regulators and airport operators is the definition and specification of airport capacity. Annual capacity is used for long-term planning purposes as a degree of available service volume, but it poses several inefficiencies when measuring the true throughput of the system because of seasonal and daily variations of traffic. Instead, airport throughput is calculated or estimated for a short period of time, usually one hour. This brings about a mismatch: air traffic forecasts typically yield annual volumes, whereas capacity is measured on hourly figures. To manage the right balance between airport capacity and demand, annual traffic volumes must be converted into design hour volumes, so that they can be compared with the true throughput of the system. This comparison is a cornerstone in planning new airport infrastructures, as design-period parameters are important for airport planners in anticipating where and when congestion occurs. Although the design hour for airport traffic has historically had a number of definitions, it is necessary to improve the way air traffic design hours are selected. This study aims to provide an empirical analysis of airport capacity and demand, specifically focusing on insights related to air traffic design hours and the relationship between capacity and delay.

By reviewing the empirical relationships between hourly and annual air traffic volumes and between practical capacity and delay at 50 European airports during the period 2004–2021, this paper discusses the problem of defining a suitable peak hour for capacity evaluation purposes. The authors use information from several data sources, including EUROCONTROL, ACI and OAG. This study provides functional links between design hours and annual volumes for different airport clusters. Additionally, the authors appraise different daily traffic distribution patterns and their variation by hour of the day.

The clustering of airports with respect to their capacity, operational and traffic characteristics allows us to discover functional relationships between annual traffic and the percentage of traffic in the design hour. These relationships help the authors to propose empirical methods to derive expected traffic in design hours from annual volumes. The main conclusion is that the percentage of total annual traffic that is concentrated at the design hour maintains a predictable behavior through a “potential” adjustment with respect to the volume of annual traffic. Moreover, the authors provide an experimental link between capacity and delay so that peak hour figures can be related to factors that describe the quality of traffic operations.

The functional relationships between hourly and annual air traffic volumes and between capacity and delay, can be used to properly assess airport expansion projects or to optimize resource allocation tasks. This study offers new evidence on the nature of airport capacity and the dynamics of air traffic design hours and delay.

The significance of smart mobility practices in shaping cities from a smart perspective has grown in recent years, influencing policies and the choices made by inhabitants. This transformation has led to the emergence of novel services and strategies, creating a new, vibrant and highly personalised urban environment that caters to the needs and preferences of both local residents and visitors. The purpose of this study is to evaluate the influence of smart mobility practices on tourism flows in cities, considering the moderating effect of airport activities on this relationship.

Using a generalised method of moments estimation and focusing on 20 Italian cities over an eight-year period, the authors highlight the current relationship between smart mobility practices and tourism flows. Moreover, the authors demonstrate that the yearly advancement of airports positively moderates this relationship.

The findings indicate a significant relationship between smart mobility practices in modern cities and tourism inflows because they influence the development of tourism services and emerging trends such as smart tourism and smart destinations. Furthermore, airport activities as a proxy for city openness play a crucial role in this link. The study shows that airports have an incremental impact on tourism and on the relationship between tourism and sustainable practices.

The limitations of this quantitative approach include the focus on a single country, the challenge of measuring the development of smart mobility practices due to a lack of standardised variables and the need for future research to expand the sample to different countries in relation to tourism inflows.

This study has practical implications for policymakers and governance in their task of effectively coordinating internal smart mobility practices and managing incoming tourism flows.

This study has social implications, highlighting the need for policymakers and governance to address the societal impacts of smart mobility practices and tourism inflows, ensuring inclusive and sustainable outcomes for local communities.

This study contributes to the existing literature as one of the first attempts to examine the interplay between smart mobility practices in smart cities and tourism flows. Furthermore, it emphasises the role of airports in this relationship, highlighting how the interaction between these variables benefits both stakeholders.

Connecting autonomous drones to ground operations and services is a prerequisite for the adoption of scalable and sustainable drone services in the built environment. Despite the rapid advance in the field of autonomous drones, the development of ground infrastructure has received less attention. Contemporary airport design offers potential solutions for the infrastructure serving autonomous drone services. To that end, this paper aims to construct a framework for connecting air and ground operations for autonomous drone services. Furthermore, the paper defines the minimum facilities needed to support unmanned aerial vehicles for autonomous logistics and the collection of aerial data.

The paper reviews the state-of-the-art in airport design literature as the basis for analysing the guidelines of manned aviation applicable to the development of ground infrastructure for autonomous drone services. Socio-technical system analysis was used for identifying the service needs of drones.

The key findings are functional modularity based on the principles of airport design applies to micro-airports and modular service functions can be connected efficiently with an autonomous ground handling system in a sustainable manner addressing the concerns on maintenance, reliability and lifecycle.

As the study was limited to the airport design literature findings, the evolution of solutions may provide features supporting deviating approaches. The role of autonomy and cloud-based service processes are quintessentially different from the conventional airport design and are likely to impact real-life solutions as the area of future research.

The findings of this study provided a framework for establishing the connection between the airside and the landside for the operations of autonomous aerial services. The lack of such framework and ground infrastructure has hindered the large-scale adoption and easy-to-use solutions for sustainable logistics and aerial data collection for decision-making in the built environment.

The evolution of future autonomous aerial services should be accessible to all users, “democratising” the use of drones. The data collected by drones should comply with the privacy-preserving use of the data. The proposed ground infrastructure can contribute to offloading, storing and handling aerial data to support drone services’ acceptability.

To the best of the authors’ knowledge, the paper describes the first design framework for creating a design concept for a modular and autonomous micro-airport system for unmanned aviation based on the applied functions of full-size conventional airports.

This study aims to provide a meaningful comparison of airports’ performance and better understand the differences observed in the analysed airport performance by presenting a model to analyse the relationship between operational and financial performance and airport characteristics.

This study uses a quantitative analysis approach. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and entropy weight were utilised to analyse 17 airports in three Airports Council International regions: Asia, Europe and North America. Through operational and financial factors, these sample airports identified the most efficiently operated airports from 2016 to 2019.

Overall, Asian airports were superior in operational and financial efficiency. Unlike operating performance, the sample airport’s financial and total performance results show a similar trend. There were no noticeable changes in operational factors. Therefore, differences in financial variables for each airport may affect the total performance.

This study provides insightful implications for airport policymakers to establish a standardised information disclosure foundation for consistent analysis and encourage airports to provide this information.

The adoption of Earnings Before Interest, Taxes, Depreciation, and Amortisation (EBITDA) to debt ratio and EBITDA per passenger, which had previously been underutilised in the previous study as financial factors, demonstrated differences between airports for airport stakeholders. In addition, the study presented a model that facilitates producing more intuitive results using TOPSIS, which was relatively underutilised compared to other methodologies such as date envelopment analysis.

In this context, this study aims to obtain information about the noise levels emitted to the environment by modeling the noise map of Dalaman Airport and correlating these noise values according to the Environmental Noise Directive (END) and World Health Organization (WHO) limits.

Dalaman Airport Aeronautical Information Publication and 2022 flight data from the airport were analyzed. The noise levels exposed to schools and health institutions were determined using the Cnossos–Eu calculation method.

Maximum noise levels were obtained as L_den 92.29 dB(A), L_day 85.24 dB(A), L_evening 89.00 dB(A) and L_night 85.23 dB(A) according to the noise indicators. Limit values recommended by the END and WHO according to noise indicator types and measurement results were correlated and evaluated.

In the noise modeling of Dalaman Airport, there has previously been no evaluation of the noise limits recommended according to END or WHO in the literature.

The next generation of mobility is arising, and various challenging mobilities have entered the limelight. One of the most exciting of these is urban air mobility (UAM), and one of its challenges is constructing effective and efficient UAM service network. This study took a quantitative approach to the problem in an effort to support and facilitate the UAM service industry.

This study derived a multi-objective and multi-period (MOMP) location optimization model to support strategic UAM service network design. The model, based on its long-term service plan, determines where and when to open UAM airports. In addition, this study applied a modified e-constraint algorithm to derive managerial decisions on the Pareto relationship in consideration of multiple objectives and multiple periods.

Each Pareto solution represents a different UAM service network configuration. Thus, the model can analyze the trade-offs between Pareto decisions for the UAM service network. A case study of UAM service network design in South Korea demonstrates the validity of the proposed mathematical model and algorithm.

The design of a UAM service network should consider various aspects. Its construction and operation would require significant investments of time, capital and people, which would redound to society over a significant span of time. The results of this study provide quantitative guidelines for derivation and analysis of various UAM service network configurations in consideration of multiple objectives and multiple periods.

This paper proposes MOMP optimization, which approach is suitable to the fundamental characteristics of expanding UAM service networks and their design. It is expected that the present study will make significant contributions to the efforts of those deriving and analyzing future UAM service networks.

Impulse purchases are a phenomenon of interest in recent years that provides a high revenue stream for companies compared to planned purchases. Airports are a unique shopping environment. Travellers usually need to arrive at the airport early and can only utilise limited time to shop at duty-free stores, which makes the shopping experience time-constrained and has the potential to make impulse purchases. The main purpose of this research is to create a model to examine whether “time pressure” and “hedonic shopping motivation” lead to impulse shopping through the formation of “positive emotion” in the context of airport duty-free shops.

A questionnaire-based survey was conducted in this study. The data collection for this study targeted individuals who had previously used airline services for international travel and visited duty-free shops at international airports. A total of 502 valid subjects participated in this survey.

The findings indicated that time pressure and consumers’ hedonic motivations have a positive impact on emotions. Positive emotions have a positive impact on the occurrence of impulse purchases. Music and light can moderate the impact of hedonic motivation on emotion but cannot reduce the influence of time pressure on emotion. Social factor significantly moderates the positive association between hedonic shopping motivation and emotion.

The research collected data from various international airports and social media, enabling the findings to be generalised.

This study examines the issues affecting learning and development (L&D) interventions to enhance operational efficiency in airport companies.

This study adopted a case study design following a qualitative approach for data collection and analysis procedure. A purposive sample of fifteen executives, including 6 Chief Executive Officers, along with 9 operational managers from the aviation industry in Namibia were suitable participants to gather information about issues affecting L&D for specific interventions to improve operational efficiency in airport companies. The data was collected using face-to-face interviews. The transcripts generated from the recordings were organized using thematic analysis via NVivo version 12.

The results showcased a lack of training needs assessment and process, inadequate specialized training and poor levels of commitment. Hence, specialized L&D interventions will impact commitment and work outcomes, which are essential for operational efficiency in airport companies.

There is a paucity of literature on how to address L&D issues for operational efficiency in the aviation sector.