Regional Airports Research Articles

Economical Impact of Regional Air Transportation

The influence of air transportation on regional economic development has garnered attention from scholars, policymakers, and industry leaders. This article aims to examine and assess how regional air transportation contributes to economic growth. The article highlights the impact of regional air travel on economic progress through a review of literature, statistical data, and previous studies. The findings indicate that regional air transportation is vital for economic development, improving connectivity, boosting trade and tourism, supporting infrastructure growth, and fostering entrepreneurship. Increased accessibility through regional airports stimulates business, facilitates goods and services movement, and drives productivity. Additionally, regional air networks support development initiatives by creating jobs and aiding local businesses.

Landslide Prediction Validation in Western North Carolina After Hurricane Helene

Hurricane Helene triggered 1792 landslides across western North Carolina and has caused damage to 79 bridges to date. Helene hit western North Carolina days after a low-pressure system dropped up to 254 mm of rain in some locations of western North Carolina (e.g., Asheville Regional Airport). The already waterlogged region experienced devastation as significant additional rainfall occurred during Helene, where some areas, like Asheville, North Carolina received an additional 356 mm of rain (National Weather Service, 2024). In this study, machine learning (ML)-generated multi-hazard landslide susceptibility maps are compared to the documented landslides from Helene. The landslide models use the North Carolina landslide database, soil survey, rainfall, USGS digital elevation model (DEM), and distance to rivers to create the landslide variables. From the DEM, aspect factors and slope are computed. Because recent research in western North Carolina suggests fault movement is destabilizing slopes, distance to fault was also incorporated as a predictor variable. Finally, soil types were used as a wildfire predictor variable. In total, 4794 landslides were used for model training. Random Forest and logistic regression machine learning algorithms were used to develop the landslide susceptibility map. Furthermore, landslide susceptibility was also examined with and without consideration of wildfires. Ultimately, this study indicates heavy rainfall and debris-laden floodwaters were critical in triggering both landslides and scour, posing a dual threat to bridge stability. Field investigations from Hurricane Helene revealed that bridge damage was concentrated at bridge abutments, with scour and sediment deposition exacerbating structural vulnerability. We evaluated the assumed flooding potential (AFP) of damaged bridges in the study area, finding that bridges with lower AFP values were particularly vulnerable to scour and submersion during flood events. Differentiating between landslide-induced and scour-induced damage is essential for accurately assessing risks to infrastructure. The findings emphasize the importance of comprehensive hazard mapping to guide infrastructure resilience planning in mountainous regions.

Testing of an indirect ice detection methodology in the Horizon 2020 project SENS4ICE

AbstractSupercooled large droplets (SLD) icing conditions have been the cause of severe aircraft accidents over the last decades. Existing countermeasures, even on modern airplanes, are not necessarily effective against the resulting ice formations, which raises a demand for reliable detection of SLD in all conditions for safe operations. The EU-funded Horizon 2020 project SENS4ICE focused on new ice detection approaches and innovative sensor hybridization to target a fast and reliable (SLD-)ice detection. The performance-based (indirect) ice detection methodology is key to this approach and based on the changes of airplane flight characteristics under icing influence. This paper provides a short overview of the development and implementation of the indirect ice detection (IID) algorithms in SENS4ICE. Moreover, it gives and discusses first exemplary results from the IID tests in classical icing conditions during the SENS4ICE North America flight test campaign conducted in February/March 2023 out of St. Louis Regional Airport in Alton (Illinois, USA).

Investigation of Critical Aspects of Roughness Assessment for Airfield Pavements

One of the main priorities of airport authorities is to maintain a high level of serviceability of runway pavements due to the high safety requirements for aircraft at high speeds. Accordingly, the assessment of the functional condition of airfield pavements is crucial for the proper operation of an airport. The most critical functional parameter appears to be pavement roughness. It characterizes the condition of the runway surface and is directly related to the safety of aircraft flights, as it affects the handling characteristics and braking performance of the aircraft, the increase in operating costs, and the wear of the aircraft. Worldwide, there are several indices for assessing the roughness of airfield pavements. This study aims to compare some of these indices to assess their ability to capture the characteristics of airfield pavement roughness. For this purpose, roughness data were collected along a runway with flexible pavement at a regional airport in southeast Europe and corresponding indices were estimated. The analysis of the data leads to the most efficient index for assessing the roughness of airfield surfaces to date. However, the need for a new index that expresses the response of the aircraft remains a critical issue.

The HIAL storm: Resisting the technological transformation of air traffic control

AbstractWhether and under what conditions the implementation of technology can be resisted hinges on how labour can mobilise structural, associational, institutional, coalitional and ideational power resources. The failed attempt of Highlands and Islands Airports Limited (HIAL) to create a remote tower centre at Inverness to control air traffic at seven regional airports, with the loss of well‐paid jobs in local communities, demonstrates the importance of the composition and interaction of different power resources. By analysing a group of workers with abundant power resources during a ‘storm’ as well as a period of calm, we demonstrate how different power resources can complement but also compromise workers' interests, thereby explaining why unions might be hesitant to utilise specific resources over time and place.

Beyond the Airports Act: Investigating the Privatisation of Airports by Local Governments in Regional Australia

Costs associated with running local airports are spurring some local governments to pursue alternative governance arrangements. Some regional councils are considering privatisation, with four having already gone down this path. Although some of these arrangements broadly follow those specified by the Airports Act 1996, other arrangements have led to fragmented processes and reduced public engagement in local communities. The study reveals that, while long‐term leasing aims to alleviate the council's financial burden, it can negatively impact the broader public interest. The findings suggest the need for more transparent and adaptable governance models to ensure that regional airports serve both commercial interests and public needs.

Aviation Discontinuity and Regional House Prices: A Quasi-Experiment in New Zealand

Although there is evidence that more regional airport activities can increase regional house prices, no study has examined the relevant impacts of aviation discontinuity. My unique quasi-experiment data comes from New Zealand where Jetstar withdrew its domestic services from four airports/regions in December 2019. The synthetic control method (SCM)'s results reveal that the withdrawal created different impacts on the house prices of the regions involved, in which the overall effect was negative in the short run but the housing market in New Zealand has recovered in the long run.

Analyzing India's National Civil Aviation Policy and Global Trends in Contemporary Civil Aviation Policies

The expansion of the Indian economy is expected to extend to remote regions, and while market-driven processes are ideal for regional air connectivity, there is recognition of the valuable role of public policy in this endeavor. The UDAN Scheme follows a market-oriented approach where operators assess demand, propose routes, and navigate variables like traffic rights, slot allocation, regulatory restrictions, and infrastructure limitations. Global airline industry deregulation has introduced healthy competition, enhancing efficiency and service quality, leading to increased passenger traffic. Studies have highlighted the constructive impact of improved air connectivity on the economic development of regions. Efficient airports are vital economic catalysts, but research suggests that some regional airports operate inefficiently, missing opportunities for profitability. Government subsidies and policies for enhancing regional and remote air connectivity are common practices worldwide, with schemes like EAS in the United State and PSO in Europe bridging the accessibility gap. Research is crucial to understand policy effects on air connectivity and identify factors that improve outcomes. Route dispersal guidelines, such as those in India, can create financial redistribution between route categories, affecting airlines' profitability and serving state capitals over remote regions. Policymakers must find effective ways to enhance air transport to underserved areas where market dynamics might not naturally establish viable transportation links. In summary, this study emphasizes the importance of government-supported policies like UDAN and the role of market-oriented approaches in promoting regional air connectivity. It underlines the need for research to assess policy impacts and identifies the challenges and opportunities in enhancing air connectivity to remote and underserved regions.

SDG: A global large-scale airport perception disparity cognition modeling method based on deep learning and geographic knowledge

Global airport perception levels vary due to natural geographical factors and economic development disparities. Understanding these differences is crucial for assessing regional airport development and its correlation with geographical patterns. However, there are limited methods available to effectively comprehend these disparities. To address this issue, this paper proposes a Salience, Disturbance, and Geographic-knowledge (SDG) approach for the cognitive analysis of global large-scale airport perception differences. Salience is assessed using a two-class deep learning model to evaluate the prominence of known airports. Disturbance is evaluated using an object detection model to measure background interference in large-scale airport perception. Geographic-knowledge analysis considers the correlation between regional airports and their surrounding geographic environment. The results rank perception difficulties for 17 regions worldwide, with Tajikistan exhibiting the highest difficulty at 0.922, while the Jiangsu–Zhejiang–Shanghai region in China has the lowest at 0.102. We also performed correlation analyses to validate the effectiveness of our model. To our knowledge, this paper pioneers the cognitive analysis of target perception difficulty differences across multiple global regions.

A Copula Discretization of Time Series-Type Model for Examining Climate Data

The study presents a comparative analysis of climate data under two scenarios: a Gaussian copula marginal regression model for count time series data and a copula-based bivariate count time series model. These models, built after comprehensive simulations, offer adaptable autocorrelation structures considering the daily average temperature and humidity data observed at a regional airport in Mobile, AL.

Factors affecting the cessation of commercial air services at English regional airports

Although much of the existing research on regional airports focuses on their contribution to regional economic development, regional airports in England, as in other deregulated markets, operate in a highly competitive market and not all have been able to sustain commercial flights. This paper examines the factors that have led to the cessation of commercial air services at English regional airports following liberalisation of the European air transport market in 1992. Six factors which have contributed to air service cessation are identified and potential futures for smaller regional airports discussed.

The Possibility of Cross-Border Cooperation of Regional Airports Through the Example of Osijek and Pécs-Pogány

Abstract On January 1st 2023, Croatia joined the Schengen area, which means that border controls on persons will no longer be carried out at the common Croatian-Hungarian border. This will facilitate traffic between the counties of Baranya and Osijek-Baranya, which will be further enhanced by the opening of the 20 km final section of the M6 motorway, scheduled for the first quarter of 2024. In this situation, new opportunities will open up for exploiting the mutual benefits of cooperation between these counties, such as the cross-border cooperation between the regional airports near Pécs and Osijek. The study will explore the specificity of both facilities and important conclusions could provide useful lessons to other regional airports facing similar issues.

Investigating the impact of spatial dependence and heterogeneity on airport relationships: Empirical evidence from China

This research focused on the relationships among 34 major airports in China, analyzing how these relationships are influenced by spatial dependence and heterogeneity. Using a spatial econometric model, it found that passenger traffic in China’s airports displays a mutually driven aggregation effect. Furthermore, the study revealed that the airport relationship changes from complementarity to competition as the geographic distance between them decreases. The study also classified the main airports in China into three hierarchical levels and found significant complementarity and competition among those within the hub-and-spoke network structure. Specifically, this study identified a complementary relationship among regional trunk and local branch airports, as-well-as significant competition among hub airports. Crucially, the study suggests that the absence of a hub airport weakens the collaborative interactions between different types of airports, emphasizing the critical importance of hub airports for the connectivity and operational efficiency of China’s airport network.

Navigating Regional Airport System Economics: Insights from Central Europe and Croatia

This paper delves into regional airport system economics in Central Europe, with a particular focus on Slovakia, Czechia, Poland, Hungary, and Croatia. This research aimed to identify key indicators that shape optimal business models for regional airport systems by analyzing data from 24 airports between 2016 and 2019. Through cluster analysis, airports were categorized based on performance metrics, economic indicators, and ownership structures. The findings reveal distinct groupings among regional airports and shed light on critical factors influencing their operational and financial dynamics. By offering insights into the relationships between airport system characteristics and business model effectiveness, this paper aimed to provide valuable guidance for stakeholders, policymakers, and airport management teams. It facilitates informed decision-making and strategic planning for sustainable aviation infrastructure development in the region.

Стратегирование коммерциализации инноваций в условиях отечественной экономики данных

Professor A.G. Aganbegyan defines a new transport and logistics infrastructure as a key factor of economic growth, welfare, and transformation of Russia’s socio-economic system. This new infrastructure should include two-way highways, high-speed railways, regional airports, and major logistics centers in key transport hubs. Unfortunately, such projects have a very long payback cycle that may last up to 20–25 years. Moreover, the investments may be as high as 3 trillion rubles annually. As a result, transport and logistics suppliers alone cannot support such a large-scale initiative. Domestic logistics is currently going through all the stages from 1PL to 5PL, which places very high requirements on the multimodality of transport and logistics in physical infrastructure, software, and hardware. These processes encourage research cooperation between industries aimed at developing novel interoperable R&D solutions. Russian transport and logistics infrastructure depends heavily on the railway industry: its main operational task is to maintain passenger and cargo traffic, as well as to provide safety. Under the current sanctions, Russian railroads face the challenge of developing and scaling advanced scientific and technical reserves. Technological independence relies on end-to-end production technologies, e.g., artificial intelligence algorithms, digital twins, etc., which impose requirements on data interoperability. This article describes the potential that domestic railway enterprises have for improving commercialization of innovations and technology transfer. The authors used the theory of strategy and the methodology of strategizing developed by Professor V.L. Kvint to design several recommendations on how railroad companies may increase their economic motivation to overcome various barriers.

Evaluating Attractiveness of Newly Introduced Flights – Results of a Study for the Ostrava International Airport

Abstract The paper addresses the issue of evaluating the attractiveness of new airport connections, one of which is a global transfer hub and the other is a regional European international airport. The attractiveness of new connections expressed, for example, by predicting the demand for new flight routes has long been studied, mainly using gravity models. The aim of the presented paper is to check whether an approach based on gravity models could be replaced with other approaches, in this case by multi-criteria evaluation methods. Questions of substitution of approaches based on gravity models, compiled for demand prediction, are relevant in cases where there are not enough input data for existing gravity models. The absence of input data occurs especially in cases where either there is no historical data on the operation of flights, or historical data do not have current significance, e.g. the operation of the flight has been interrupted for a longer time. The results of a study carried out for Ostrava International Airport located in the Czech Republic, show that gravity models for which relevant data are not available can be fully replaced by multi-criteria evaluation methods.

Study on the temporal and spatial relationship between public health events and the development of air transport scale: A case of the Southwest China.

The spread of the COVID-19 had profoundly affected the development of the air transportation. In order to determine the changes in air transportation volume associated with the development of the epidemic, this paper takes Southwest China as the study area. Monthly data and methods, such as the coefficient of variation, rank-size analysis and spatial matching index, were applied. The results found that: (1) during 2020-2022, there was a positive relationship between passenger volume and epidemic development, while freight volume increased for most airports in the first quarter of 2020-2022, particularly in the eastern region; (2) From the perspective of changes in air transportation volume under the development of the COVID-19, among various types of airports, the changes in transportation volume of main trunk airports were more significant than those of regional feeder airports in remote areas; (3) however, under the influence of the epidemic, main trunk airports still exhibited stronger attraction in passenger volume. That is to say, the passengers who chose to travel by air still tended to choose the main trunk airports and formed the agglomeration distribution pattern which around high-level airports in the provincial capital. Whereas the freight volume had a tendency of equalization among airports in Southwest China; (4) Over the course of time, the consistency of the spatial distribution of the number of cases and the passenger or freight volume in southwest China gradually increased. Among them, the spatial matching rate of the passenger volume and the number of COVID-19 cases was always higher than that of the cases and freight volume, which might indicate that there was a stronger correlation relationship. Therefore, it is proposed that the construction of multi-center airport system should be strengthened, the resilience of the route network for passenger transportation should be moderately enhanced, and the risk-resistant capacity of mainline airports and airports in tourist cities should be upgraded, so as to provide references for the orderly recovery of civil aviation and regional development.

Spatiotemporal characteristics and influencing factors of airport service quality in China

Airport service quality (ASQ) is essential for determining the quality of ground civil aviation services. In this study, ASQ was assessed using the monthly airport aviation complaint data from 2015 to 2019 of 196 airports in mainland China (except for airports in Hong Kong, Macao, and Taiwan, which are not included in the statistics). First, we constructed a seasonal index of aviation complaints to evaluate and compare the overall temporal characteristics of ASQ in China. Second, the spatial distribution pattern of ASQ in China was determined using the aviation complaint concentration index and hot spot analysis model. Finally, the major influencing factors and categories of ASQ in China were analyzed considering spatiotemporal dimensions using the correspondence analysis method. The results revealed that there were clear seasonal differences among ASQ in China, with a high–low–low–high distribution during all four seasons. The regional agglomeration trend of airport aviation complaints was obvious, and the spatial difference in ASQ was large. Northern and western China performed better than southern China. Spatiotemporal and influencing factors of ASQ were the most strongly correlated factors in each quarter and region. The predominant source of aviation complaints across all types of airports is related to fundamental services, with check-in services identified as the most impactful category affecting ASQ. This study, based on 60 months of statistical data, offers a comprehensive evaluation of ASQ throughout the entire airport network in mainland China, from the perspective of aviation complaints. Additionally, a systematic ASQ evaluation method and research system encompassing time, space, and elements were established. This framework not only stimulates the improvement and enhancement of ASQ but also provides a theoretical foundation for differentially enhancing ASQ in regional airports. Overall, our results contribute to breaking through the qualitative research thinking system in ASQ research from a theoretical perspective, paving the way for exploring broader research in enhancing the quality of ground civil aviation services.

Regional airports revisited: Unveiling pressing research gaps and proposing a uniform definition

This paper aims to identify gaps in the literature and present a future research agenda for investigations on regional airports. The research topics appearing from the systematic literature review are linked to the roles that regional airports have held and currently hold. In this way, challenges and research gaps that deserve extra attention are identified. Moreover, the paper deals with one of the most pressing research gaps, the definition of a regional airport. The literature and accompanying industry review reveal a diverse use of the term regional airport, and ACI Europe (2017) and the European Parliament (2021) even indicate that there is currently no definition for a regional airport in Europe. To address future research and challenges of regional airports in a more unified and structured manner, a proposal is made to capture the term ‘regional airport’ based on objective criteria. With the dual outcome of possibilities for future research and a proposal for a common use of a definition of regional airports, we aim at a more coordinated and impactful progress in research concerning regional airports.

A hybrid robust SBM-DEA, multiple regression, and MCDM-GIS model for airport site selection: Case study of Sistan and Baluchestan Province, Iran

This study focuses on the strategic decision-making process for selecting airport locations in developing countries, where investment constraint is a significant concern. Recognizing that airport location decisions are influenced by a multitude of factors, often in the absence of comprehensive data and amidst uncertain forecasts, there is a need for a methodology capable of adeptly handling various factors under uncertainty. The goal is to provide solutions that remain feasible and near-optimal, even with some variations in input parameters, ensuring robustness. To this end, this research introduces a decision tool incorporating Slack-Based Measurement in Robust Data Envelopment Analysis (SBM-RDEA). The Slack-based method is beneficial in cases with multiple inputs and outputs where their relationships are not strictly proportional, as in the airport location selection problem. DEA, in conjunction with Multiple Regression analysis, leverages available data on the attributes of operational regional airports to compute the significance of these criteria in shaping the success factors of these facilities. Furthermore, these weightings can be employed to evaluate the suitability of airport locations currently under development and assess their potential for contributing to regional development. Additionally, to address the uncertainty of input data, a Robust optimization approach is employed to ensure a reliable response for this strategic decision-making process. This weighting framework is utilized twice within the research methodology: first, to assess the potential of different counties in the state for hosting a new regional airport, and second, to identify the optimal location for the airport in an MCDM-GIS analysis. This methodology has been applied to a case study in Sistan and Baluchistan, Iran. The result of the proposed method has been compared with one of the most common existing methodologies. This method identifies Zahedan County as having the highest potential and selects the location (29.48° N, 60.90° E), in the east of Zahedan city, as the optimal site for airport construction. Validation results confirm the efficacy of this solution.