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Modern airports face increasing challenges due to the growing number of passengers and evolving security threats. The successful operation of an airport requires a delicate balance between efficiency, security and passenger satisfaction. Artificial intelligence (AI) offers the potential to revolutionise airport operations by improving passenger experience, enhancing security and optimising efficiency. Implementing AI presents challenges, however, including the need for a strong data foundation and a focused approach. Organisations should avoid trying to do too much at once and focus on specific AI applications. Building a data-driven culture and investing in data teams and chief data officers (CDOs) are essential for successful AI adoption. By addressing these challenges and embracing AI, airports can create a more efficient, secure and passenger-friendly environment. [ABSTRACT FROM AUTHOR]

This paper introduces a simulation model designed as a decision-making tool to assess and analyze various crowd management strategies with a focus on enhancing sustainability in airport operations. This model specifically addresses the challenges and risks associated with managing passenger flows within airport terminals. By simulating different scenarios, the model aims to provide valuable insights into how to effectively handle crowd dynamics and enhance overall terminal efficiency, safety, and sustainability. This case study was conducted at Henri Coanda International Airport, ARENA 12 simulation software being used in order to model the passenger flows within the airport terminal. Two scenarios were considered: The first one involves maintaining a fixed number of security and check-in desks for the two airline groups. In contrast, the second scenario allows for a variable number of security and check-in desks for the same airline groups. By optimizing resource allocation and minimizing waiting time, this model contributes to more sustainable airport management operations. Three measures of performance (MOPs) were selected to assess the system activity: the average passenger waiting time, the average passenger number queue length, and the average utilization rate. Comparing the results, we concluded that the second scenario shows a relative improvement in almost all performance measures when compared to the first scenario. [ABSTRACT FROM AUTHOR]

This study leverages approximately 7500 reviews from Skytrax to explore the determinants of airport service quality and their influence on passenger recommendations. The dataset includes various features such as terminal cleanliness, terminal seating, terminal signs, food and beverages, airport shopping, WiFi connectivity, and airport staff. The research employs a comprehensive methodology encompassing statistical data analysis, predictive modelling, and interaction effects analysis. The descriptive analysis of time-series data highlighted trends and fluctuations in service quality and recommendations, providing insights into temporal dynamics. Multiple machine learning models, including logistic regression, Random Forest, SVM, KNN, Gradient Boosting, and Neural Networks, were developed in this study and cross-validated for airport recommendation based on Skytrax's online reviews. Among others, Gradient Boosting emerged as the most accurate model with an 88.15% mean accuracy. Interaction effects revealed significant combined influences, such as terminal cleanliness and terminal seating, on passenger recommendations. This multifaceted approach offers robust insights into factors influencing airport recommendations and guides improvements in airport management to enhance passenger satisfaction. Future work will focus on a general-purpose machine learning framework and its toolbox development for airport service quality analysis based on online reviews from various sources. [ABSTRACT FROM AUTHOR]

The Airport Pavement Condition Index (PCI) is important in developing a runway maintenance strategy, which is carried out on the entire surface using the ASTM D5340 method. However, a significant amount of time, money, and comprehensive observation is needed for the management of hundreds of airports, especially the middle of runway, which measures 18m with numerous aircraft wheels. Therefore, this research examined PCI in the lateral wander area and modeled the relationship with standard PCI values. The ASTM D5340 guidelines with two scenarios were used to analyze the overall runway pavement survey. In scenario 1 PCI was calculated on the entire runway surface, while in scenario 2 PCI it was evaluated only on the lateral wander area. The analysis results showed that the PCI value in Scenario 2 is 23.8% (PKY) to 49.7% (TJQ) lower than in Scenario 1 because the analyzed area comprised of aircraft wheels and the environment (heat, rain). This research succeeded in developing a model of the relationship between PCIoverall as a function of PCIlateral wander, which requires development by increasing the number of runway samples. However, using PCI calculations for the lateral wander area has the potential to improve flight safety and decrease the monitoring costs for airport pavement. [ABSTRACT FROM AUTHOR]

Due to competitive dynamics and a renewed emphasis on service experience, coupled with evolving passenger needs and preferences for world-class airport experiences, airport management is increasingly tasked with prioritizing airport service quality. The involvement of private parties and other stakeholders at Indian airports has led to structural and ownership changes, making service excellence a major differentiating factor for airlines and customers, elevating industry standards to new heights. In the current landscape, airport operators are placing greater focus on airport service quality to understand how to enhance customer service experience and improve airport business performance. Thus, this study aims to conduct an in-depth analysis of airport service quality parameters and the ranking of airports. The research proposes an integrated approach using the fuzzy analytic hierarchy process (FAHP) and Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) to benchmark Indian airports. This work is beneficial for airport and airline operators, as well as other stakeholders, to identify areas of focus such as customer touchpoints, customer service expectations, and airports' key selling points by evaluating airport service quality parameters. Subsequently, the proposed model is tested for its robustness to ensure its effectiveness in providing actionable insights for improving airport service quality. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Technology (Natural Science) is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Intelligent Transportation Systems & Applications is the property of Journal of Intelligent Transportation Systems & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The airside is a principal subsystem in the intricate airport systems. This study focuses on introducing a digital twin framework for analyzing the delays and capacity of airports. This framework encompasses a diverse array of authentic features pertaining to a civil airport for a mixture of both landing and departing flights. Being a decision support for the management of international airports, all sizes and weight categories of aircraft are considered permissible, each with their own unique service time and speed requirements in accordance with the global aviation regulations. The proposed discrete event simulation digital twin provides a real-time demonstration of the system performance with the possibility of predicting the future outcomes of managerial decisions. Additionally, this twin is equipped with an advanced and realistic 3D visualization that facilitates a more comprehensive understanding of the ongoing operations. To assess its efficiency in practice, the framework was implemented at an international airport. The statistical tests revealed the superior similarity between the proposed twin and the real system. Using this twin, we further optimized the studied system by analyzing its projected future performance under a set of scenarios. This resulted in a nearly 30% upgrade in the capacity of this airport while decreasing the expected delays by over 18% annually. [ABSTRACT FROM AUTHOR]

Accurately predicting taxi-in times for arrival flights is crucial for efficient ground handling resource allocation, impacting flight departure timeliness. This study investigates terminal layout characteristics, specifically decentralised layouts, to predict and analyse arrival flight taxi-in times. We develop a surface traffic flow calculation method considering arrival and departure flights, eliminating fixed thresholds. We introduce runway-crossing operations for decentralised airports, creating new prediction variables. We consider factors like runway, aircraft type, airline, taxi distance, and time periods. Gradient Boosting Regression Tree predicts taxi-in times, while Lasso analyses factor impact. Our approach yields highly accurate predictions for decentralised airports, with Surface traffic flow and Runway-crossing variables significantly influencing taxi-in times. This research informs airport managers in decentralised layouts, enabling tailored management strategies.

This study examines the nature of brand associations that air travellers form with airports and which associations are important when choosing between airports. Using semi-structured qualitative interviews, this study collected information about 240 participants’ most recent trips using air travel, encompassing 642 airport visits and 88 airports worldwide. The associations that participants made with the airports they travelled through were collected, as well as the sorts of associations that are important for choosing between airports and why those associations are important. The data were analysed using thematic analysis, revealing 13 themes each for airport brand associations and important associations for choosing between airports and 14 themes for reasons why those associations were important. Single-sample t-tests reveal that each of these themes has a different effect size in terms of its effect on airport brand association formation and its effect on attitudinal brand choice. This study contributes to the air transport and tourism literature by providing a detailed account of which associations air travellers form with airports and which are used for choosing between airports by contextualising these findings by viewing airports as compound brands. Managerial implications are also provided along with avenues for future research.

The density of fog is directly related to visibility and is one of the decision-making criteria for airport flight management and highway traffic management. Estimating fog density based on images and videos has been a popular research topic in recent years. However, the fog density estimated results based on images should be further evaluated and analyzed by combining weather information from other sensors. The data obtained by different sensors often need to be aligned in terms of time because of the difference in acquisition methods. In this paper, we propose a video and a visibility data alignment method based on temporal consistency for data alignment. After data alignment, the fog density estimation results based on images and videos can be analyzed, and the incorrect estimation results can be efficiently detected and corrected. The experimental results show that the new method effectively combines videos and visibility for fog density estimation. [ABSTRACT FROM AUTHOR]

While airport shopping has garnered extensive attention in the literature, the significance of integrating luxury stores within airport environments remains an underexplored facet. In this qualitative study, grounded in established theories of luxury behavior and airport management, we delve into the perceptions of tourists regarding the presence of luxury stores in airports. Drawing on in-depth interviews, we demonstrate that tourists' favorable reception of luxury stores can be connected to the idea of making luxury more accessible. Our findings also suggest how luxury shopping enhances the overall passenger experience and contributes to the reinforcing of the airport's reputation. This study adds theoretical and empirical depth to the discourse on airport retail, shedding light on the nuanced interplay between luxury commerce, tourist perception, and airport management practices. [ABSTRACT FROM AUTHOR]

In the evolving landscape of airport management, leveraging public data emerges as a transformative strategy to enhance operational efficiency and customer satisfaction. This paper explores the integration of data analytics in airport operations, illustrating through case studies how airports can utilise open data to optimise performance, improve passenger experience and streamline security processes. We highlight the significant benefits of adopting data-driven approaches, including increased operational transparency, improved decision making and enhanced service quality. Our findings underscore the pivotal role of public data in driving innovation and sustainability in airport management, offering actionable insights for airport authorities and stakeholders. This paper serves as a stimulus on how to benefit from the use of open data. [ABSTRACT FROM AUTHOR]

This article explores the strategic use of sports event-related activities by airports as a means of business development. Utilizing a documentary research methodology, it draws on gray literature accessible in the online public domain to present various airport case studies. Through content analysis employing an inductive method, two primary keywords emerge: "traveler engagement" and "airport as a lifestyle platform." These terms underscore the ways in which airports harness sports event-related activities to foster business growth. [ABSTRACT FROM AUTHOR]

The aviation industry, which has an important place in the world economy, has a much higher growth rate compared to many other sectors. Considering that today, approximately 2% of global greenhouse gas emissions originate from this sector and that these emissions will increase in parallel with the growth rates of the sector in the coming years, it would be appropriate to take the necessary measures without delay. While the ecosystem is negatively affected during the construction activities of airports, high energy needs of airport infrastructures, significant amounts of waste materials generated during the operation phase, noise emissions resulting from airport operations, etc. These reasons can significantly affect the well-being of local people. Considering that the practices carried out at airports affect the environment and local people, corrective measures should be implemented by airport managements without using economic reasons as an excuse. By evaluating the environmental problems mentioned in this study, it is aimed to make a risk assessment and determine the environmental effects during the operation of Erzurum Airport. In the study, environmental risk factors were determined and the possible effects of the risks on the environment were tried to be revealed by using the L-type matrix method and Fine-Kinney method. In this regard, offices, kitchens, carpentry shops, warehouses, maintenance and repairs etc. within the airport. Environmental risk factors that are thought to cause environmental damage in the units were evaluated. As a result of the evaluations made at the airport, 11 medium, 243 tolerable and 39 insignificant level risks were identified with the L-type matrix method, while 7 high, 31 important, 136 possible and 119 insignificant environmental risks were identified with the Fine-Kinney method. It shows that the measures to be taken will greatly reduce the possible environmental impacts of the airport. [ABSTRACT FROM AUTHOR]

The evaluation of the comfort of landing operations through pilot scores may be a viable quality indicator to be adopted in airport runway management. However, some factors, such as the aircraft model, can influence this perception. This paper aims to evaluate the physical characteristics of aircraft that affect the pilots' assessment related to comfort during landing operations at runways. We analyzed 11 runways with different conditions of roughness and measured using the International Roughness Index (IRI), associated with the scores given by pilots in the same runways. In addition, we performed a statistical analysis of four physical characteristics of the aircraft: wingspan, length, base, and gauge. The results indicate a relationship between pilot scores and runway roughness, where the gauge is the physical characteristic with the greatest influence on pilot scores. More specifically, for IRI values between 2.0 and 2.5 m/km , these characteristics influenced the perception, with better comfort during landings attributed to smaller aircraft. [ABSTRACT FROM AUTHOR]

While research has shown that customer-to-customer (C2C) value co-creation leads to positive outcomes for people with disabilities, these studies have not addressed how collective C2C can improve value outcomes for families with children with autism spectrum (FwAS) in airports. Our focus is on accessible family tourism and travel in a European airport context, using a value co-creation approach to explore this gap in the literature. To achieve this goal, a collaboration was established with Josep Tarradellas Barcelona-El Prat Airport and Vueling Airlines to enable 25 FwAS to visit the airport in 2016. The study extends social situation analysis and uses a multi-method approach combining qualitative techniques such as ethnography and post-visit interviews. Collective C2C social practices were identified in which families, as a unit of study, engage with airport sites. These include standard practices (observing the practices of others), enhancing practices (sharing airport experiences and knowledge with others) and atypical social practices, such as deviating social practices. Our findings will enable airport and airline managers to create more inclusive experiences based on the actual needs of FwAS, thus bringing them closer to truly accessible tourism. [ABSTRACT FROM AUTHOR]

This study examines the nature of brand associations that air travellers form with airports and which associations are important when choosing between airports. Using semi-structured qualitative interviews, this study collected information about 240 participants' most recent trips using air travel, encompassing 642 airport visits and 88 airports worldwide. The associations that participants made with the airports they travelled through were collected, as well as the sorts of associations that are important for choosing between airports and why those associations are important. The data were analysed using thematic analysis, revealing 13 themes each for airport brand associations and important associations for choosing between airports and 14 themes for reasons why those associations were important. Single-sample t-tests reveal that each of these themes has a different effect size in terms of its effect on airport brand association formation and its effect on attitudinal brand choice. This study contributes to the air transport and tourism literature by providing a detailed account of which associations air travellers form with airports and which are used for choosing between airports by contextualising these findings by viewing airports as compound brands. Managerial implications are also provided along with avenues for future research. [ABSTRACT FROM AUTHOR]

In the airport pavement management systems (APMSs), a focus point is the decision-making process. It enables finding the optimal strategy for maintaining a flight infrastructure in adequate condition over a given period, while considering the operating conditions of the airside. In this context, the present study analyzes the factors involved in the optimization processes by investigating how much they influence the solutions. Using the analysis processes connected to the APMS, the present study also includes the identification of specific intervention areas through clustering algorithms, minimizing the fixed operating costs. More specifically, the use of K-means clustering and the heuristic algorithms connected to the choices of the maintenance activities, allow possible scenarios replicating the different needs of managers to be investigated. In this way, the research work analyzes the influence of the alternatives in terms of pavement quality and total activities duration. Through this study it is shown that there is not a unique optimal strategy, but several possible solutions that can be undertaken by the airport managers according to their needs. However, the comparison of the results obtained in this study could become a useful tool for airport managers for better planning and management of the flight infrastructures. [ABSTRACT FROM AUTHOR]

This research addresses the crucial issue of pollution from aircraft operations, focusing on optimizing both gate allocation and runway scheduling simultaneously, a novel approach not previously explored. The study presents an innovative genetic algorithm‐based method for minimizing pollution from fuel combustion during aircraft take‐off and landing at airports. This algorithm uniquely integrates the optimization of both landing gates and take‐off/landing runways, considering the correlation between engine operation time and pollutant levels. The approach employs advanced constraint handling techniques to manage the intricate time and resource limitations inherent in airport operations. Additionally, the study conducts a thorough sensitivity analysis of the model, with a particular emphasis on the mutation factor and the type of penalty function, to fine‐tune the optimization process. This dual‐focus optimization strategy represents a significant advancement in reducing environmental impact in the aviation sector, establishing a new standard for comprehensive and efficient airport operation management. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Engineering Management / Gongcheng Guanli Xuebao is the property of Journal of Engineering Management Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The construction and operation of large airports typically result in noticeable ground subsidence. Therefore, regular monitoring of surface deformation is essential to ensure the safe operation and maintenance of airports. However, limited research has been conducted on geological subsidence in the vicinity of the Beijing Daxing International Airport (BDIA)—completed and operating since 2019—and the surface deformation following its operational phase. Here, time series interferometric synthetic aperture radar (TS‐InSAR) was performed using Sentinel‐1A data to investigate the BDIA temporal and spatial ground displacement before, July 2017 to June 2019, and after, August 2019 to April 2020, operations. The results revealed significant ground surface deformation in the airport and its surrounding areas before operations. The maximum deformation velocity recorded here reached −70 mm/year with the areas experiencing deformation primarily being the cargo and maintenance areas, with the largest cumulative deformations reaching 115 and 80 mm, respectively. Additionally, a noticeable deformation was observed in the northern part of the airport work area, whereas the airport terminal and four runways remained relatively stable. After completion, substantial ground subsidence persisted in both the airport and its surrounding regions, with the maximum deformation velocity exceeding −70 mm/year. The abandoned mounds to the east of the cargo area and south of the maintenance area exhibited continuous subsidence, with maximum cumulative deformations exceeding 60 and 50 mm, respectively. However, the work area, terminal, and four airport runways exhibited relative stability. These results hold substantial practical value, offering valuable insights into airport management and ensuring safe and efficient airport operations. [ABSTRACT FROM AUTHOR]

The equipment of airport security screening checkpoints undergoes frequent modifications due to technological or organizational changes. New solutions complement or replace existing ones to improve the effectiveness of the equipment or formal requirements. An example of this process is the replacement of the walk-through metal detection gate with a newer solution: the body scanner. The present study aimed to analyze the capacity of an airport security checkpoint under different operational conditions, depending on the equipment used. For this purpose, a previously created model (implemented as a colored, timed, stochastic Petri net) was used. Simulation studies were performed in four real-world operational scenarios, and their results were compared to those of a nominal scenario. The results show that, in terms of capacity, it may be advantageous to redirect a more significant stream of passengers to a station equipped with a specific device, depending on the specific operational situation. The results demonstrate the necessity of analyzing the applied strategy of operation with each change in the operational environment. In particular, for an airport with characteristics similar to Katowice Airport, using older technology is beneficial under nominal conditions and after increasing the staffing so that both genders work simultaneously. In other cases, the more intensive use of Body Scanner-equipped security screening checkpoints is advantageous. [ABSTRACT FROM AUTHOR]

The study analyzed the impact of non-aeronautical revenues on airport performance at Julius Nyerere International Airport in Dar es salaam, Tanzania. The study used longitudinal design in which time series data from financial statements and integrated reports for the financial years 2017/18 to 2020/21 was undertaken. The Multiple linear regression models were employed in analyzing the contribution of non- aeronautical revenues on improving the airport facilities. Findings of the study demonstrated that, i) rental fees and car parking charges impacted positively the improvement of the airport facilities, ii) advertisement also positive and significantly contributed on the improvement of the airport facilities at Julius Nyerere International Airport. This implies that, JNIA can further increase its total revenues by expanding the scope of retail operations at the airports under its jurisdiction as additional sources of income. It is recommended that airport managements and other stakeholders responsible for airports' infrastructure and transport to expand more use of NARVs sources so as to improve the service delivery for their passengers and gain more revenues for future financial stability. [ABSTRACT FROM AUTHOR]

Building new airports requires extensive investment. In principle, airport development projects should be well-planned and thoughtfully designed. Despite this, the Department of Airports (DOA), a part of the Thai bureaucracy, has allegedly continued constructing remote airports that do not appear economically viable. The reasons for these unexplained projects have also been studied. Political, economic, social, technological, legal, and ecological analyses were used to explore and evaluate the macroenvironmental factors that influence the DOA in initiating project decisions. The newly opened Betong International Airport in the southernmost district of Yala Province was used as a case study. By examining the macroenvironmental setting, the findings showed that the DOA’s bureaucratic culture was the key condition responsible for the flawed and defective layout of the nation’s southernmost airport. This, in turn, made Betong International Airport economically unfeasible for local airlines servicing routes from Betong to other destinations.

Storm Water Management Model and Geographic Information System can provide prediction and management for airport flood problems. Efficient and accurate acquisition of sensitive parameters is the key to real-time model calibration. Due to the influence of special land types, functional zoning, and use requirements of airports, there are many problems in parameter sensitivity analysis, such as large sampling parameters, large amount of calculation, and nonlinear correlation between input and output variables. In this paper, the SWMM of airport airfield area is built, combining GIS and Python programming technology and using Latin hypercube sampling, and a correlation analysis method is proposed to study whether the input parameters have nonlinear correlation with the output results and its strength and compared with the improved Morris screening method. The results show that, the sensitivity of parameters is more balanced for the total inflow, there is no very sensitive parameter, and the nonlinear correlation between the parameters and the total inflow is weak. Manning-N is sensitive to average depth, hour of maximum flooding, and time to peak, which indicates that there is a strong nonlinear correlation between them and Manning-N. From the improved Morris screening analysis, it can be seen that there are no highly sensitive parameters for peak flow, and the sensitive parameters are Zero-Imperv and Manning-N. Highly sensitive parameters for time to peak are Manning-N, N-perv, S-Imperv, and N-Imperv. This paper quantitatively analyzes the influence of input parameters of the storm water management model on the output results, effectively identify the important parameters that affecting the output results, and analyze the nonlinear correlation between the input parameters and the output results. The results can greatly improve the accuracy of airport flood model and provide theoretical guidance for the application and parameter calibration of SWMM in airport. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

After the border lockdown, global traffic has returned, making green airports a government goal to reach carbon neutrality by 2050. Sustainable aviation fuel (SAF) use for commercial aircraft alone won't help achieve net-zero emissions (NEZ). An independent renewable energy supply system at airports is urgently needed to implement green airports worldwide. This study develops a renewable energy power supply system that integrates wind, photovoltaic (PV), and waste-to-energy (WTE) sources to investigate a new adaptive model predictive control (MPC) energy management strategy based on airport operational characteristics. Simulations of Copenhagen Airport's energy programme confirmed this energy management strategy's feasibility. Energy management scenarios for two typical summer and winter load days were simulated for case studies. Field data from Copenhagen was used for simulation analysis, and experimental modelling of the airport's energy scheme proved the energy management program's practicality. The simulations show that Copenhagen airport renewable energy generates half of its electricity in winter and 81.0% in summer. A total operating cost of USD 36,087.83/day in summer and USD 102,061.20/day in winter is needed to reduce carbon emissions by 41.19 Mt/day in summer and 43.96 Mt/day in winter. This approach should help deploy green airports worldwide and reach carbon neutrality by 2050. [ABSTRACT FROM AUTHOR]

The development of airport security screening systems requires the use of increasingly sophisticated and effective equipment to detect prohibited or hazardous items and substances. However, this can lead to a reduction in the throughput of the security checkpoint (SCP). This paper addresses the operationally important problem of the dilemma between screening effectiveness and screening checkpoint throughput, which is important to the real operational capabilities of an airport. In this paper, a comparison of traditional walk-through metal detectors (WTMD) gates and newer technology body scanners (BSs) was carried out in terms of SCP throughput as an element determining the operational capabilities of the airport. For this purpose, a simulation model was developed to study throughput based on a colored timed Petri net. The analysis showed that, depending on the characteristics of the available staff, the level of terrorist and epidemic threat, as well as the time of year, it is advantageous to use different strategies to vary the size of the stream of passengers directed for screening by the WTMD gate and BS. [ABSTRACT FROM AUTHOR]

The principal objective of this study is to analyze the spatial and temporal variation of ground transportation airport demand and provide demand forecast to inform planning capability and explore alternatives for investments to accommodate airport growth. Because of its good adaptability and strong generalization ability for dealing with high-dimensional input, small-sample, and nonlinear spatial data, Gaussian process (GP) regression is used to provide forecast estimates using data from transportation network company (TNC) trips and urban rail passengers at Chicago’s O’Hare International Airport. TNC airport trips differ significantly, with three times more distance, more than twice the travel time, and half of the share requests compared with nonairport trips. This highlights the need for separate demand models. Hourly analysis of the rail service indicates that this is likely heavily used by airport workers, whereas TNC services focus on travelers because of variations in the peak demand hours. Heteroscedastic GP regression is implemented because of differences in trip variance between night and day hours. Estimates are given for weekdays and weekend trips, and the 95% confidence intervals are calculated. The introduction of flight schedule information into the models shows marginal improvements in their performance. However, fitting a GP regression becomes computationally expensive with increased sample size and the introduction of spatial components. Transportation planners and policymakers can use the results and methods implemented in this study to optimize transportation assets and provide long-range simulations of the current and future conditions in the area. [ABSTRACT FROM AUTHOR]

Airport service quality ratings found on social media such as Airline Quality and Google Maps offer invaluable insights for airport management to improve their quality of services. However, there is currently a lack of research analysing these reviews by airport services using sentimental analysis approaches. This research applies multiclass models based on Aspect-Based Sentimental Analysis to conduct a comprehensive analysis of travellers' reviews, in which the major airport services are tagged by positive, negative, and non-existent sentiments. Seven airport services commonly utilised in previous studies are also introduced. Subsequently, various Deep Learning architectures and Machine Learning classification algorithms are developed, tested, and compared using data collected from Twitter, Google Maps, and Airline Quality, encompassing travellers' feedback on airport service quality. The results show that the traditional Machine Learning algorithms such as the Random Forest algorithm outperform Deep Learning models in the multiclass prediction of airport service quality using travellers' feedback. The findings of this study offer concrete justifications for utilising multiclass Machine Learning models to understand the travellers' sentiments and therefore identify airport services required for improvement. [ABSTRACT FROM AUTHOR]

Historically aviation has gone through periods of immense innovative growth. Today the air transport industry is in the midst of yet another revolutionary period. Advanced Air Mobility (AAM) includes technological advancements in electric and hydrogen propulsion, battery capacity and autonomy, resulting in the development of a new generation of electric and hybrid-electric aircraft. These emerging technologies and new aircraft show promise in addressing historical concerns such as noise, safety, and negative environmental impacts. AAM has the potential to revolutionise the way we live by serving as the catalyst to robust, sustainable transport systems for people and goods. AAM can assist with emergency response, medical transport, reduced travel times, improve accessibility and reduce harmful emissions. Airports are an essential part of the transport infrastructure, serving as hubs for air travel, cargo shipments and emergency response centres in the wake of natural disasters. With the rise of AAM technologies, airports will need to adapt and prepare to accommodate these new types of aircraft. Each airport is unique and airport management will need to understand not only the potential of AAM but the capabilities of the airport itself. This paper aims to capture what the aviation industry has been, what it could be through AAM, lessons learned while planning for AAM, and how airports can use critical success factors to evaluate their readiness and plan for this innovative era. [ABSTRACT FROM AUTHOR]

Culture and human factors in aviation environment are not new concepts. They have been primary components of the aviation safety system and have become fundamental to the operations of air carriers. Their significance in ensuring safe aviation practices is widely recognised and accepted today. These concepts have been seamlessly integrated into the organisational DNA of aviation safety, shaping core principles and practices. In contrast, aviation security has historically lagged behind, often seen merely as a component of the broader safety framework. Over the years, safety and security have evolved separately, reflecting their distinct natures. While aviation safety has reached a high level of maturity, aviation security is now in a position where it must catch up. Current aviation security staff recruitment and retention challenges need to be addressed by creating better strategy for future recruitment, professionalisation of security workforce and improved airport environment. Embedding strong and effective security culture, consideration of human factors and their impact on staff performance and development of mission valence can positively affect airport working environment, leading to better staff retention and positive perception of aviation security roles. [ABSTRACT FROM AUTHOR]

Copyright of Baghdad Science Journal is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Boletín Económico de ICE is the property of S.G.E.E.I.P.C., Secretaria de Estado de Comercio, Ministerio de Industria, Comercio y Turismo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Architecture principles affect a software system holistically. Given their alignment with a business strategy, they should be incorporated within the validation process covering aspects of sustainability. However, current research discusses the influence of architecture principles on sustainability in a limited context. Our objective was to introduce a reusable process for monitoring and evaluating the impact of architecture principles on sustainability from a software architecture perspective. We sought to demonstrate the application of such a process in professional practice. A qualitative case study was conducted in the context of a Dutch airport management company. Data collection involved a case analysis and the execution of two rounds of expert interviews. We (i) identified a set of case-related key performance indicators, (ii) utilized commonly accepted measurement tools, and (iii) employed graphical representations in the form of spider charts to monitor the sustainability impacts. The real-world observations were evaluated through a concluding focus group. Our findings indicated that architecture principles were a feasible mechanism with which to address sustainability across all different architecture layers within the enterprise. The experts considered the sustainability analysis valuable in guiding the software architecture process towards sustainability. With the emphasis on principles, we facilitate industry adoption by embedding sustainability in existing mechanisms. [ABSTRACT FROM AUTHOR]

Airport business management literature commonly evaluates the performance of these organizations based on the number of passengers and cargo processed, aircraft movements, number of runways, number of employees, and passengers' terminal dimension, among other factors concerning commercial aviation, commonly applied to large structures, with gaps being identified in the literature of small airports. The identification and analysis of the main factors that interfere with the performance of airport business, and the strategic and operational management of small public airports have been analyzed from 24 small Brazilian airports. The study employed the Data Envelopment Analysis method based on the Charnes, Cooper, and Rhodes model, as well as the Banker, Charnes, and Cooper model, adapted for Visual Basic Analysis. The main results demonstrate that infrastructural characteristics, such as runway width, pavement classification number, runway length, buldings' age, maximum take-off weight of the critical aircraft, passenger terminal size, and air cargo and passengers processed, show significant relevance to the operational performance of small airports. The main theoretical implications of the study are the definition of strategic and operational parameters that impact the performance of small airports, which can be used as a reference by air transport decision-makers. [ABSTRACT FROM AUTHOR]

This article provides a perspective on how an internet of heterogeneous self-service airport terminal systems can be used for data collection, which is stored on a private or consortium blockchain depending on the ownership or operations of an airport or both. Such a setup would help to increase efficiency, reduce costs, and improve traveler experience at airport terminals. Moreover, it would allow airports to gather data directly from passengers as opposed to waiting to receive the same data from airlines. Subsequently, this data, now on a blockchain system, becomes a data source for other applications such as machine learning. In this way, meaningful insights for immediate and long-term decision-making can be derived. This article can be useful to airport management, blockchain application developers, academics, and researchers who are interested in automating airport terminal systems. [ABSTRACT FROM AUTHOR]

The airline industry is among those industries that deal with a large number of customers for the purpose of travelling. However, COVID-19 impacted the revenue streams of the airline industry as travelling by air observed a significant decline. Since airports are an important element of airline operations, they were more affected than airlines as their revenue streams were mainly generated from different consumer spending and rental services. It was realized during COVID-19 that the diversification of revenue streams played a vital role in airports' sustainability and self-sufficiency. This study aims to determine the role of airports' tangible and intangible features as alternate or additional sources of revenue and observe the mediating role of customer satisfaction. After a careful literature analysis and flipping over various studies, it appears that a lot of research is done on the contribution of the non-aeronautical revenue towards the financial stability of airports, but no study focuses on the role of airport physical features on airport retail revenue and how it can affect airport revenue streams. Therefore, this research study aims to analyze the mediating impact of Customer Satisfaction on the relationship between Airport Environment factors and Airport retail Revenue. Cronbach's alpha, Reliability, discriminant validity, SD. analysis is used for analysis. The result shows that airport environment and airport design have a significant positive impact on airport retail revenue, while the result also shows that the airport facility has a weak relation with airport retail revenue. It is evident from the results that airport environment and airport design, with an indirect effect on customer satisfaction, can increase the airport retail revenue. [ABSTRACT FROM AUTHOR]

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Air transport is the only way to reach Lithuania from abroad in the short and medium term. Despite a well-developed road network in the country, connections to other European capitals are long and inconvenient. 2014 July. Vilnius, Kaunas and Palanga airports were merged into one state-owned company, Lithuanian Airports (LTOU). Since then, the efficiency and overall profitability of LTOU operations have increased significantly. However, maintaining the airport’s current infrastructure is costly and needs upgrading and further investment. The company has repeatedly asked itself whether it can get more benefits by building one new Lithuanian airport or focusing on developing the existing three airports net. Stakeholders’ views and recommendations should be heard to make timely and appropriate decisions without a new airport’s technical and financial feasibility. An in-depth interview and secondary data analysis were selected for the empirical study. Thirteen employees of SE Lithuanian Airports and three of the Ministry of Transport and Communications of the Republic of Lithuania participated in the research. The following was used to analyse secondary data: SE Lithuanian Airport strategic plan, the material of strategic sessions, and a survey of the country’s population on the need for a new airport. The study found that stakeholders positively assess the long-term development projects of SE Lithuanian Airports, fully understanding the importance of airports and their contribution to the welfare of the state. Stakeholders can significantly impact results, so airport managers must consider whether they effectively involve stakeholders and, if not, how they can improve or encourage stakeholder involvement. [ABSTRACT FROM AUTHOR]

The successive growth of the aviation industry has progressively heightened the importance of airport pavement management systems. Existing research has primarily focused on the technological advancements of optimization models, with limited applicability in practice. In this study, we introduce condition cases optimization (CCO) to address these limitations while incorporating multi-facility and multi-year network optimization models. We developed condition index, serviceability level, integrated assessment indices and performance models for decision-making criteria. As a result, a practical decision-making strategy was proposed which can flexibly reflect budget constraints. Sensitivity analysis highlighted the impact of initial budget, maintenance methods, costs, and thresholds on decision outcomes. Using a case study, we validated the effectiveness and practicality of the CCO method as an efficient decision-making tool. [ABSTRACT FROM AUTHOR]

Purpose: 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. Design/methodology/approach: 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. Findings: 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. Practical implications: 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. Originality/value: 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. [ABSTRACT FROM AUTHOR]