Airport Passenger Research Articles

Analysis of airport passenger satisfaction based on combined weight-fuzzy comprehensive evaluation

In order to make passengers' satisfaction with the airport improved again and the airport side to make passengers understand the improvement of the airport in recent years according to the evaluation results, this paper constructs an airport passenger satisfaction evaluation system based on fuzzy comprehensive evaluation by combining weight analysis with AHP-entropy weight method, and describes the specific evaluation process of the model. A case study of Lhasa Gonga Airport is conducted, and the results verify the reliability of the research method and the applicability of the evaluation model. The evaluation results can provide a reference for the passenger satisfaction analysis of this airport and similar airports.

On the Value of a Flexibly Planned Airport Passenger Building

Real options can be used to determine flexible strategic plans for airport facilities. Unlike conventional strategic plans, which prescribe in a rigid schedule specifying when and how capacity of a facility shall be adjusted, flexible plans specify decision rules that indicate under which conditions a decision to adjust capacity should be made best. In this study, optimal conventional and flexible facility requirements for a fictious passenger building (PB) at an airport are generated through the solution of the conventional and flexible capacity expansion problem. Subsequently, it is evaluated how the financial value of these optimal facility requirements is affected by the average aircraft size using the PB and the percentage of all aircraft handled at the PB. The results suggest that the value of the PB is positively affected by larger aircraft, while it is negatively affected if more aircraft are handled at the PB. Further, it can be concluded from the results that flexibly planned airport PB are more valuable than conventionally planned ones since flexible planning allows a PB to better cope with uncertainty in future demand. Indeed, a flexibly planned PB is more valuable, as both the risks of negative demand developments can be better mitigated, and future opportunities can be better capitalized than if conventional planning had been used.

Airport passenger movement, revenue and expenditure at non-major airports using panel data regression

This study aimed to identify factors influencing the performance of non-major airports, which were crucial for addressing their sustainability and the economic development of their adjoining region. It was based on actual time series and cross-section data of twenty non-major airports located in fifteen states of India. Ten-year panel data was used for panel data regression between model and random effect models. The influencing factors were assumed to comprise five city demographics (population, per-capita index, urbanization, human development index and wealth index) and fourteen airport-specific variables (three types of aircraft departures, drive time to metro airports, movement, of aircraft and cargo, terminal area, lease areas of land, retail, advertisement, car park, operational hours, aviation fuel and employees).It was observed that the per capita income of airport region, aircraft departures and urbanization positively affected the airport passenger movement. Passenger movement, area of advertisement and terminal and fuel upload influenced the revenue positively. Aircraft movement, terminal size, and employee number positively impacted expenditure. Increased airport passenger movement and income would be possible by operating at least two aircraft departures to metro airports and providing more advertisement areas for lease. Minimizing the number of regular employees by multi-tasking and outsourcing would reduce the expenditure.

The dynamics of the air transport development in the Warmia and Mazury region

Motives: Regional passenger airports are an important component of a developed transportation system that reflects the broader development of the region and the country. Due to the small number of studies examining air transport at the regional micro-scale, it is important to carry out a diagnostic of this mode of transport to determine the possibility of regional development. The article presents the reasons for the creation, stages of construction and transformation of selected airports of northeastern Poland. Aim: The main aim of the study was to determine the impact of the COVID-19 pandemic on the dynamics of air transport development in the area of northeastern Poland. The entire air transport system in the region was analyzed with a detailed inventory of the largest airport Olsztyn-Mazury. Results: As a result of the study, data on the number of passengers and directions of travel for the past six years were compared. It was determined that Olsztyn-Mazury Airport has a significant development potential, providing an opportunity to rebuild passenger air traffic in Warmia and Mazury hampered by the effects of the COVID-19 virus pandemic.

Airport terminal passenger forecast under the impact of COVID-19 outbreaks: A case study from China

Passengers significantly affect airport terminal energy consumption and indoor environmental quality. Accurate passenger forecasting provides important insights for airport terminals to optimize their operation and management. However, the COVID-19 pandemic has greatly increased the uncertainty in airport passenger since 2020. There are insufficient studies to investigate which pandemic-related variables should be considered in forecasting airport passenger trends under the impact of COVID-19 outbreaks. In this study, the interrelationship between COVID-19 pandemic trends and passenger traffic at a major airport terminal in China was analyzed on a day-by-day basis. During COVID-19 outbreaks, three stages of passenger change were identified and characterized, i.e., the decline stage, the stabilization stage, and the recovery stage. A typical “sudden drop and slow recovery” pattern of passenger traffic was identified. A LightGBM model including pandemic variables was developed to forecast short-term daily passenger traffic at the airport terminal. The SHapley Additive exPlanations (SHAP) values was used to quantify the contribution of input pandemic variables. Results indicated the inclusion of pandemic variables reduced the model error by 27.7% compared to a baseline model. The cumulative numbers of COVID-19 cases in previous weeks were found to be stronger predictors of future passenger traffic than daily COVID-19 cases in the most recent week. In addition, the impact of pandemic control policies and passengers' travel behavior was discussed. Our empirical findings provide important implications for airport terminal operations in response to the on-going COVID-19 pandemic.

Overview of the Influence of Level of Service on the Airport Passenger Terminal Capacity

Establishing the desired quality of service (QoS) of the airport passenger terminal in order to improve operational performance is a challenge for every airport. Recent international research indicates a gradual recovery in air transport and, accordingly, the need to develop additional transport infrastructure. If the passenger terminal design in terms of infrastructure and operational capacity is not approached correctly, the level of service provided to passengers may decline. This research will focus on how the IATA Level of Service (LoS), which is provided to airport users can contribute to the optimisation of the level of service of the passenger terminal. Additionally, the impact of level of service on passenger terminal capacity assessment in relation to the diversity of air carrier business model will be analysed. Since there is no common link to uniformly describe and solve this problem, this paper will review the relevant literature in the field of passenger terminal capacity research and will analyse different approaches to solving this problem with the aim to develop a new unified concept in observing and optimising the capacity of the airport passenger terminal taking into account the types of air carrier business models.

Evaluation of Passenger Behavior in the Baggage Claim Area of the Airport Passenger Terminal

The importance of the baggage claim area as the gateway to the city is extremely high. Therefore, the initial impression of the quality of services provided at the destination airport is based on this area. In this research, an agent-based and discrete event approach using five parameters (speed and traffic of passengers, speed and arrangement of carousels, and air traffic) was applied in order to simulate passenger flow in the baggage claim area of Imam Khomeini International Airport, Tehran, Iran. In this regard, forty-eight scenarios were identified and simulated using AnyLogic software, and the waiting time and level of service for each scenario were obtained. Finally, it was revealed that changing the arrangement of the carousels from T-shaped to oval-shaped and expansion of the circumference by 10% had the greatest effect. Also, changing the speed of the carousels had the least influence on increasing the level of service and reducing waiting time.

Design of civil aviation security check passenger identification system based on residual convolution network

INTRODUCTION: A civil aviation security check passenger identification system based on residual convolution network is designed to improve the efficiency of airport passenger security check service. OBJECTIVES: The system uses the basic resource layer to provide communication and configuration services, collects the basic information of passengers, the images of passengers' faces and whole body, and the images of baggage security X-ray machine through the data layer, and stores the collected results in the unstructured database; METHODS: The image processing module of the business service layer calls the data in the database, and takes the STM32F103VBT6 microprocessor as the image processing control chip to complete the image data processing. The person, baggage, X-ray machine image and passenger basic information are associated through the person, baggage and X-ray machine information binding service module, and the association results are uploaded to the person and certificates integration unit of the client application layer. RESULTS: The face recognition module identifies the passenger identity through the residual convolution network with the attention mechanism, and realizes the ReID identification of passengers and baggage and the association of people and baggage through the transmission control unit. CONCLUSION: The experimental results show that the system can accurately identify the identity of civil aviation security passengers, and the identification efficiency of security passengers can reach more than 27 frames per second.

Research proposal on architectural copper-based antimicrobic solutions in high traffic spaces

This contribution investigates research opportunities in the field of architecture and design management focusing on user health in high traffic spaces. The field of application is Airport Passenger Terminals. Looking at the COVID-19 pandemic and anticipating the possibility of events of the same magnitude, it is necessary to approach the problem of the safety in public spaces. Based on the State of the Art about antimicrobial material studies, Science of Architecture could propose innovative solutions that are compliant with health safety and prevention for high-use surfaces. These solutions will combine antimicrobial materials with a digital solution that could manage data about surfaces, allowing the maintenance team to valuate and optimize operations. After few hours the hygiene level of copper-based surfaces is higher than any other material. Copper-based furniture could be paired with sensors that send data to management software. Combining the use of scientifically demonstrated antibacterial surfaces with high-performance management tools could be the best option to achieve health safety and contribute to social sustainability. Airport terminals are the ideal high-traffic buildings to use as test model because they have all the characteristics that could be analysed concerning the safety and the perception of safety of architectural spaces by users.

Decision Support Models for Predicting and Explaining Airport Passenger Connectivity From Data

Predicting if passengers in a connecting flight will lose their connection is paramount for airline profitability. We present novel machine learning-based decision support models for the different stages of connection flight management, namely for strategic, pre-tactical, tactical and post-operations. We predict missed flight connections in an airline’s hub airport using historical data on flights and passengers, and analyse the factors that contribute additively to the predicted outcome for each decision horizon. Our data is high-dimensional, heterogeneous, imbalanced and noisy, and does not inform about passenger arrival/departure transit time. We employ probabilistic encoding of categorical classes, data balancing with Gaussian Mixture Models, and boosting. For all planning horizons, our models attain an area under the curve (AUC) of the receiver operating characteristic (ROC) higher than 0.93. SHAP value explanations of our models indicate that scheduled/perceived connection times contribute the most to the prediction, followed by passenger age and whether border controls are required.

We learn more from our mistakes than from our successes: Lessons learned on ORAT and failed activation of airport passenger terminals

Building an airport is no easy task. Neither is delivering it in a state of operational readiness, which must encompass facility, system and people readiness. History is full of examples of (in)famous airport opening failures because of mistakes made during construction and activation. This paper will explore poor Operational Readiness Activation and Transition (ORAT) processes as a key reason for the failure of airport projects, with a thorough analysis of a recommended ORAT programme framework, comprising six core processes, three support processes and six project management processes. Each process is explained in a practical manner, in a recipe-like format and with the dos and do nots that increase the chances of successful delivery on opening day and daily operations thereafter. The paper highlights the real-life issues that come with tracking and improving every step of the construction and trials to ensure the operational readiness of the airport.

PERENCANAAN PENGEMBANGAN TERMINAL BANDARA UDARA DJALALUDDIN GORONTALO

The airport in Gorontalo is known as Djalaludin Airport which was taken from an Indonesian Air Force pilot who was the best son of Indonesia from the Gorontalo area, namely Lt. Col. Pnb Djalaluddin Tantu who was declared dead during the Dwikora operation in Malaysia. Before becoming Djalaludin Airport in 1974, initially this airport was named Tolotio Airport since it was founded in 1955 because of its location in Tolotio village, Tibawa district, Gorontalo regency. The purpose of this study is to find out whether the Djalaluddin airport terminal is feasible for the development of the terminal area of ​​​​the number of passengers. Data from the site survey and the results of the analysis of space requirements calculations with sources: (Airport Passenger Terminal, SKEP 347/XII/1999 (ICAO Annex 9 Reference on Facilities). The results show that Djalaluddin Airport is still feasible to accommodate passengers at this time. With Comparison of the actual area of ​​6122 m2 and the theoretical 5270 m2. And the results of the regression analysis show that in 2032 it was obtained 722,440 passengers. The actual area of ​​the Djalaludin airport terminal is 6032 m2, so it needs to be redeveloped so that it can accommodate the number of passengers in the coming year.

Meningkatkan Kapasitas Terminal dan Kepuasan Penumpang Bandara Hang Nadim Batam Menggunakan Regresi Linear Sederhana dan Customer Satisfaction Index (CSI)

Evaluation and analysis of terminal capacity and user satisfaction is one of the things that needs to be done to prepare for all post-COVID-19 conditions. Airport passenger satisfaction is an important component in airport service management because it affects the demand for travel accessand airport revenue. The purpose of this study is to evaluate capacity and analyze passenger satisfaction at Hang Nadim airport in Batam post-COVID-19. The method used is Simple Linear Regression and Customer Satisfaction Index (CSI). Sampling was done by probability sampling with the population of Hang Nadim airport passengers. The data collected in the form of data on the number of passengers departing during 2012 to 2021. Direct observations were carried out by distributing questionnaires to 50 respondents. With the linear regression method, passenger flows will be obtained until the post-covid-19 pandemic, so that a capacity evaluation will be carried out at the airport. Based on the results of the evaluation and analysis carried out, it was found that the estimated number of passengers after the COVID-19 pandemic in In 2022 the predicted number of arriving passengers is 1,553,669 and in 2023 as many as 1,444,876 people.. There is one facility that needs to be improved, namely the arrival hall which was originally 3,452 m² to 4,525 m². While other facilities are still in the category of fulfilling. The level of passenger satisfaction with the quality of Batam's Hang Nadim airport is 53.96 percent, which is quite satisfied according to the Customer Satisfaction Index approach.

Ultrafine Particle Ground-Level Impacts During Aircraft Approach and Climb-out Operations at a Major Cargo Hub

Ultrafine particles (UFP) contribute to adverse health outcomes such as asthma, obstructive pulmonary disease, cardiovascular disease, and lung cancer. Recent research draws attention to elevated ambient UFP number concentrations near airports. In this study, high time-resolution UFP measurements were conducted along public roads near Mohammad Ali International Airport (SDF; Louisville, KY) which is a commercial passenger airport and a major air cargo hub. Short-duration (∼3 h) measurements with two instrumented vehicles were designed and executed to capitalize on the distinct features of the air cargo hub including periods of high flight activity (and either all landings or all take-offs) at night and early morning when the atmospheric mixing layer depth is shallow. We present preliminary measurements for quantifying individual aircraft contributions and showcase the complexities involved in interpreting these data. For example, during periods with high arrivals frequency, UFP plumes from multiple aircraft on approach are superposed and it is challenging to apportion impacts to individual aircraft. Ground-level impacts for individual aircraft on climb-out are difficult to discern because the planes rapidly ascend above the atmospheric mixed layer height and take different flight paths soon after take-off. Elevated UFP concentrations are observed downwind of the airport, in some cases admixed with approach/climb-out emissions. Although from these data UFP concentrations are difficult to associate with specific aircraft characteristics, UFP concentrations are elevated downwind of the airport. These impacts decrease with increasing distance from the airport yet are clearly discernible at least 3 km downwind.

The Impact of Airport Facility Service Quality on Brand Experience and Passenger Satisfaction: Considering the Mediating Role of Brand Engagement

In the past decade, as more and more passengers choose to fly on trips, China’s airport infrastructure construction has achieved world-renowned achievements. Despite the growing opportunities and demands for using brand research to assist airport industry services in improving, few studies have investigated the impact of service quality in terminal facilities on brand due to the diversity of service. This study uses structural equation models based on empirical research to explore the impact of facility service quality, including processing facility and non-processing facility, on airport brand experience and passenger satisfaction. This study also aims to assess the mediating effect of brand engagement on the relationship between facility service quality, brand experience, and passenger satisfaction. At the same time, this study also uses importance–performance map analysis (IPMA) to find specific items influencing brand engagement. The sampling method used a random sampling approach, with a total of 186 questionnaires distributed at Shanghai Pudong International Airport for data analysis. The results show that airport facility service quality is significant for brand engagement and experience, as well as for satisfaction, especially for processing facilities. In addition, the IPMA results show that facility services involved in the check-in process is of high importance, which requires more attention from managers. Overall, the findings of this study extend the understanding of service quality, brand engagement, brand experience, and passenger satisfaction in the context of an international airport, and they offer implications for Shanghai Pudong International Airport regarding the improvement of its facilities and brand.

Value Assessment of Airport Billboards Based on Passenger Big Data.

As an important element of the airport ecosystem, airport billboards are playing a crucial role in publicizing the city image and facilitating humanistic airport construction. At the same time, airport billboards have great commercial value and is a popular channel for enterprises to prompt their products and to build their brand image. Currently, most airports in China adopt a simple fixed pricing mechanism for airport billboards. Specifically, for any type of billboard, the advertising price is mainly determined by considering historical prices and the total passenger flow of the entire airport during a whole year. However, this seemingly crude pricing mechanism only considers macro-level data of passenger flow and fails in reflecting the real value of billboards in different locations effectively, since the value of a particular billboard depends not only on its media form, but also on the number of passengers flowing through and whether these passengers are the target customers of the advertising content. Based on big data on airport layout, flight information, and passenger attributes, this paper proposes a time- and location-based value assessment model for airport billboards. Using sample data collected from the Beijing Capital International Airport, the assessment model is adopted to evaluate the value of two real billboards in Terminal T3. Application of this model can reflect the difference in the value of airport billboards located in different spots during various periods. Furthermore, this model provides a solid foundation for airport executives to develop differentiated/dynamic pricing and flexible advertisement scheduling strategies, thereby improving the overall efficiency.

Masked Face Recognition and Temperature Monitoring Systems for Airplane Passenger Using Sensor Fusion

Transportation is currently an unavoidable necessity. However, the COVID-19 pandemic has impacted all lines of industry, including the Indonesian aviation transportation industry. Technology is one of the solutions to deal with these problems. The monitoring system of masked face recognition and body temperature detection for the check-in process of passengers at the airport is aimed to be developed in this research. The contribution of this research is that the system can distinguish the type of face mask used. Therefore, this monitoring system classified only medical masks and N95/KN95 respirator masks as ‘Good Masked’. IP camera and thermal camera are used to identify a masked face and body temperature, respectively. The sensor fusion method was used for decision-making on passengers whether they can be departed or not. The decision was taken based on the measured body temperature, the use of standardized face masks, and the face recognition of the airport passengers. Convolutional neural network (CNN) method was used for face and face mask recognition. The CNN model training was conducted four times according to the four proposed scenarios. The CNN model that has been trained can distinguish a masked face and a face without a mask. The best results were obtained in the fourth scenario with the comparison of the training dataset to the testing dataset was 9:1 and the epoch was 500 times. The basic deep learning model used for face detection was the single shot multibox detector (SSD) using the ResNet-10 architecture. Meanwhile, the CNN method with the MobileNetV2 architecture was used to detect the use of masks. The accuracy of the CNN model for face recognition and mask recognition was 100%. All check-in monitoring and verification process data were displayed on the web application which was built on the localhost.

An evaluation of non-aviation revenues based on passenger satisfaction and quantity of commercial establishments at terminals: A case study of a Brazilian airport

This paper provides an approach to evaluate the influence of airport manager practices and passenger satisfaction at the terminal on non-aviation revenues. We used a quarterly dataset from 2013 to 2019 and robust passenger research provided by the Brazilian National Civil Aviation Secretary with more than 170,000 passengers interviewed at the Guarulhos International Airport. We estimated a multiple linear regression model to explain the non-aviation revenues generation given the dataset. The results strongly demonstrate that the actions provided by the airport management body, such as opening a new passenger terminal in 2014, had a significant positive impact on non-aviation revenues. The new terminal operation generates an average quarterly growth of 56.57 million R$ in non-aviation revenues. The mathematical model also indicates that the passenger satisfaction level with the quantity and quality of commercial establishments does not imply any significant impact on nonaviation revenues. In contrast, a higher satisfaction level with the products price at the commercial establishments has a negative impact on non-aviation revenues.

Scent dogs in detection of COVID-19: triple-blinded randomised trial and operational real-life screening in airport setting

ObjectiveTo estimate scent dogs’ diagnostic accuracy in identification of people infected with SARS-CoV-2 in comparison with reverse transcriptase polymerase chain reaction (RT-PCR). We conducted a randomised triple-blinded validation trial, and...

Benefits of Glulam Timber Roof Structure for Airport Passenger Terminal Building

Benefits of Glulam Timber Roof Structure for Airport Passenger Terminal Building