Airline Passengers Research Articles

An Optimized Deep Learning Approach for Improving Airline Services

The aviation industry is one of the most competitive markets. The most common approach for airline service providers is to improve passenger satisfaction. Passenger satisfaction in the aviation industry occurs when passengers’ expectations are met during flights. Airline service quality is critical in attracting new passengers and retaining existing ones. It is crucial to identify passengers’ pain points and enhance their satisfaction with the services offered. The airlines used a variety of techniques to improve service quality. They used data analysis approaches to analyze the passenger point data. These solutions have focused simply on surveys; consequently, deep-learning approaches have received insufficient attention. In this study, deep neural networks with the adaptive moment estimation Adam optimization algorithm were applied to enhance classification performance. In previous studies, the quality of the dataset has been ignored. The proposed approach was applied to the airline passenger satisfaction dataset from the Kaggle repository. It was validated by applying artificial neural networks (ANNs), random forests, and support vector machine techniques to the same dataset. It was compared with other research papers that used the same dataset and had a similar problem. The experimental results showed that the proposed approach outperformed previous studies. It has achieved an accuracy of 99.3%.

Exploring access modes to Baghdad international airport

Baghdad International Airport receives nearly two million visitors annually. So it’s important to analyze the accessibility of the airport. This research aims to show the effect of several factors on the accessibility to the airport and diagnose the problems facing passengers, and identify some significant factors that affected user preference for an airport transfer, by making a questionnaire to the passengers who traveled from Baghdad International Airport. A structured questionnaire was developed in English and translated into Arabic for a high response, and to ensure the result with a 95% confidence level, 404 airline passengers will receive a questionnaire through an online survey. The accessibility was evaluated through about 20 factors, such as gender, age, passenger’s income, mode of transportation to the airport, car ownership, children on the trip, luggage, time, trip purpose, distance, origin, and destination, type of the flight, comfortable, and others. Statistical analysis for the variables by using the SPSS V.20 program was conducted, using the chi-square test to check for independence and the correlation between variables (gender, age, income, mode of transportation to the airport, flight time) was analyzed. The findings indicate that gender and income variables affected how people could access the airport.

The Effect of Domestic Air Travel on the Spread of COVID-19 in the U.S.

ABSTRACT We examine the relationship between passengers arriving from COVID-19 hotspots during the early period of the pandemic and the number of COVID-19 cases or deaths in a MSA during the first wave of the pandemic in the U.S. To do so, we link airline passenger flows with COVID-19 infection and mortality data. We control for MSA-level population and demographic data. We examine infection and mortality rates in MSAs receiving more versus fewer airline passengers from four early COVID-19 hotspots: New York City, Boston, Detroit, and New Orleans. We then compare the effect of airline passengers from these four hotspots with the effect of airline passengers from a set of eight cities with similar numbers of departing airline passengers. We find no evidence that passengers arriving from four early COVID-19 hotspots are positively correlated with local COVID-19 infection and death rates. More broadly, we find no evidence that passenger arrivals from COVID-19 hotspots increased the early spread of COVID-19 in the U.S. Our results indicate that banning domestic air travel may do little to slow the spread of infections.

ENSURING CYBER SECURITY IN AIRLINES TO PREVENT DATA BREACH

Using the data breach issues that happened in Cathay Pacific Airways (CX) and British Airways (BA) as case studies, the aim of this study is to focus on analyzing cyber security against data breach that affects airlines passengers’ privacy and induces greater financial losses for airlines. The objective is to investigate the possible leakages in airlines’ cyber security and explore how to strengthen cyber security in airlines. Based on the results, preventative, detective, and reactive measures were revealed which contribute to strengthening cyber security for the airlines. 
 Keywords: Cyber Security, Data Breach, Airlines.

Up in the air! Airline passenger's brand experience and its impact on brand satisfaction mediated by brand love

This study aims at comprehending the significance of brand experience in impacting brand satisfaction in the aviation sector. Grounded on the theory of experiential marketing, the current research aims to explain the phenomena by which brand experience can be created through marketing communication channels. This study also tests the role of brand love as a mediator on the relationship between brand experience and brand satisfaction, by analyzing 480 responses. This research concludes that brand love partially mediates the relationship between brand experience and brand satisfaction in the aviation sector. Airline managers need to focus their strategies on event marketing and marketing communication as they have a significant effect on brand experience. The findings will also help in understanding the different dimensions of brand experience.

Masks and air rage: a qualitative content analysis using an interaction ritual framework.

During the pandemic, there was an alarming escalation in reports of air rage in the United States. Prior to the pandemic, the yearly average of unruly airline passenger behaviors was around 100 incidents per year. However, after mask mandates were issued, 5981 unruly passenger incidents in the United States were reported by the Federal Aviation Administration (FAA) in 2021 alone. Therefore, we conducted a qualitative content analysis pertaining to mask-related incidents of air rage, to learn more about this recent social problem. We also applied an interaction ritual (IR) framework to the results of our analysis, to provide sociological insight concerning this issue. The goal of our exploratory research is to understand what it is about masks that cause certain groups of people to lash out violently while on airplanes. To date, little or no scholarly efforts have researched incidents of air rage in relation to masks. Therefore, our research provides a contribution by updating the literature on this topic.

Impact of innovation characteristics of airport self-bag-drop service on attitude, trust, and behavioural intention: using trust transfer theory

ABSTRACT Although self-bag-drop (SBD) kiosks provide a fast and convenient way to check in bags at airports, many airline passengers are reluctant to use and accept this innovative technology. Using innovation diffusion theory, this study employs three characteristics of innovation (relative advantage, trialability, and compatibility) to examine which constructs influence airline passenger attitude toward, trust in, and intention to use SBD kiosks. Results of an online survey of 330 Koreans reveal that among the three characteristics of innovation, relative advantage and trialability positively affect attitude toward and trust in SBD service providers and kiosks, and compatibility affects only passenger attitude toward and trust in SBD kiosks. Results also show that trust in SBD service providers is positively related to trust in SBD kiosks, which in turn influences passenger intention to utilise SBD services. Several theoretical and practical implications are suggested.

PENGARUH KESADARAN MERK DAN PERSEPSI KUALITAS TERHADAP KEPUTUSAN PEMAKAIAN JASA PENERBANGAN GARUDA INDONESIA

This study aims to determine the effect of brand awareness and perceived quality and to find out the attributes of brand awareness and perceived quality on the Garuda Indonesia airline on the departure route from Pontianak at Supadio Pontianak Airport which needs to be developed. This research was conducted for one month, using three dimensions of service usage decisions, namely Confidence in using services, Stability in using services, Conformity of attributes to needs and desires. The sample of this research is Garuda Indonesia airline passengers. The sample for this research used purposive sampling method. Data were collected using questionnaires and literature studies. The research method uses a quantitative research design in the form of a survey with classical assumption tests, multiple regression analysis and hypothesis testing. The results of this study show that the data is normally distributed with a significance level of 0.150 or > 0.05 and shows a unidirectional relationship between the independent variable and the dependent variable. It can be concluded that Garuda Indonesia airline passengers at Supadio Pontianak airport were satisfied with the brand and quality provided with a value (51.9%). Each variable dimension can be developed in order to increase brand awareness and perceived quality in this study.

PENGARUH KINERJA PENANGANAN DAN KUALITAS PELAYANAN BAGASI TERHADAP KEPUASAN PENUMPANG DI MASKAPAI CITILINK RUTE MALANG – JAKARTA

This study aims to determine the effect of handling performance and service quality and determine the attributes of handling performance and service quality on the Citilink Airlines Malang - Jakarta route at Abdurrachman Salech Airport Malang that need to be developed.
 This research was conducted for one month, using the dimensions of passenger satisfaction, namely professionalism, service responsiveness, service availability, overall satisfaction, comfort. The sample of this research is Citilink airline passengers. The sample in this study used purposive sampling method. Data was collected by using questionnaires and literature studies. The research method uses a quantitative research design in the form of a survey with Classical Assumption Test, Multiple Regression Analysis and Hypothesis Testing.
 The results of this study indicate that the data is normally distributed with a significance level of 0.282 or greater than 0.05, and indicates that there is a unidirectional relationship between the independent variable and the dependent variable. It can be concluded that Citilink airline passengers at Abdurrachman Saleh Airport Malang are satisfied with the handling performance and service quality provided with a value (69.6%). Each variable dimension can be developed to be able to improve the handling performance and quality of baggage services in this study.

Factors Affecting the International Flight Delays and Their Impact on Airline Operation and Management and Passenger Compensations Fees in Air Transport Industry: Case Study of a Selected Airlines in Europe

This paper aims to analyze the causes of flight delays of a selected airline operating in Europe and identify potential risks and reasons for delays in air transport, which carry risk, especially in connection with passenger dissatisfaction and the resulting need to pay compensation for delayed flights, according to EU law, which brings significant financial costs for airlines. Data collected from the years 2013–2019 have been used for the purposes of this article, including data on the duration and causes of the delays and the characteristics of individual flights, such as the flight type, aircraft type, time of departure, aircraft capacity, and the load factor. Multidimensional statistics methods have been applied for data processing, namely tests of independence and correspondence analysis. Dependencies have been presented in graphical form using correspondence maps. The analysis shows that the total share of delayed flights of the company in question does not increase over the mentioned period of time. The analysis furthermore proved that higher capacity aircraft were rather prone to longer delays. The share of delayed charter flights declined slightly over the period under review, while the number of delays caused by airline operating reasons, aircraft clearance by supplier companies, technical maintenance and aircraft defects, operating procedures, and crew flight standards and airport restrictions is increasing. The analysis also shows that the delays propagated by the delays of the previous flights are becoming more frequent, with the exception of the year 2019. In the last pre-COVID year, air traffic control could boast about a positive trend regarding the number of produced delays over the years, contributing to greater air passenger satisfaction and airline service quality. Due to the gradual revival of air transport after the COVID pandemic lockdowns, the topic of flight delays, passenger customer satisfaction and financial costs for the resulting delays is once again an actual issue for air management and operation.

Mediating Role of Perceived Health Risk on Customer Experience and Customer Satisfaction: Evidence from the Airline Industry in India During COVID-19

With a steep decrease in the rate of COVID-19 infection, and a corresponding increase in the number of vaccinated people, countries have begun to re- open borders to foreign travellers, triggering the resumption of aviation services. However, people are still apprehensive, and are avoiding travel, hindering air travel to get back to the pre-COVID era. This paper determines the experience of air travellers’ during the pandemic applying EXQ model. Additionally, it investigates the role of perceived health risk as a mediating variable in an extended EXQ model. We collected data from a sample of 122 air travelers during the pandemic and analyzed it using IBM SPSS. The outcome of this study sheds light on the experiences of pandemic-affected airline passengers, revealing in the process, factors that passengers value much more now than ever before. The findings confirm that perceived health risk significantly mediates the relationship between customer experience and satisfaction.

The Impact of COVID-19 on Malaysian Airline Passengers’ Willingness to Pay for Carbon Offset.

Airline industries have been impacted by the COVID-19 pandemic, which has spread to nearly every country worldwide. Multiple countries have imposed travel restrictions to halt this virus’s spread. This precarious situation has significantly impacted the airline industry, reducing passenger volume, flight frequency, and airline flow patterns. Although most scholars have examined changes in passenger volume before and during the COVID-19 outbreak, none of it has been done in Malaysia. Therefore, this study aims to investigate the effect of COVID-19 on airline passengers’ willingness to pay for carbon offset decisions and the value of willingness to pay among Malaysians. The research employed a scenario-based experiment with 150 respondents as the samples. Convenience sampling was adopted and was analyzed using the Contingent Valuation Method (CVM) via STATA version 16. The results showed that Malaysian airline passengers are willing to pay for carbon offset even as many have stopped flying due to COVID-19, with a mean value of RM20.68. This study also revealed that most passengers are still aware of climate change, even though not many are flying during the endemic. The psychological changes in air travelers caused by the pandemic are examined, with managerial and policy implications for the pandemic’s normalization of the pandemic and the airline market’s recovery in the post-pandemic period.

Stepping Up and Stepping Out of COVID-19: Malaysian Airline Passengers’ Travel Behaviour and Does It Impact Willingness to Pay for Carbon Offset

The COVID-19 crisis has become the most intense and long-lasting in aviation history. There is significant literature on the immediate impact of the outbreak, as well as speculation on the industry’s future evolution. This paper seeks to contribute to this discussion by examining flying patterns among Malaysian airline passengers and whether they are willing to contribute to carbon offset when flying during and post COVID-19. Specifically, the paper aims to measure the Malaysian airline passengers’ travel behavior during and after COVID-19 in Malaysia and whether the traveling behavior will impact passengers’ willingness to pay for carbon offset when flying. Many airlines recognize the importance of environmental protection. The airlines implement several environment-friendly activities related to in-flight services and wish to trigger passengers’ support and inquire about their preferences. Using an online survey, 150 respondents completed the survey as the sample for this study. The majority (77%) reported their travel behavior would change due to current cases of COVID-19 and the main reason is that COVID-19 worries them and will kill the patient if not prevented. Even though Malaysian traveling behavior has changed, they are still willing to pay for carbon offset as 69% of respondents are still willing to contribute. The findings have important implications for air transport management and decision-makers to tolerate the traveling behavior among Malaysian passengers and how they will support Sustainable Development Goals: Goal 13 (Climate Action), contributing to carbon offset.

A geographical and operational deep graph convolutional approach for flight delay prediction

Flight delay prediction has attracted great interest in civil aviation community due to its significant role in airline planning, flight scheduling, airport operation, and passenger service. Flight delay is affected by numerous factors and irregularly propagates in air transportation networks owing to flight connectivity, which brings critical challenges to accurate flight delay prediction. In recent years, Graph Convolutional Networks (GCNs) have become popular in flight delay prediction due to the advantage in extracting complicated relationships. However, most of the existing GCN-based methods have failed to effectively capture the spatial–temporal information in flight delay prediction. In this paper, a Geographical and Operational Graph Convolutional Network (GOGCN) is proposed for multi-airport flight delay prediction. The GOGCN is a GCN-based spatial–temporal model that improves node feature representation ability with geographical and operational spatial–temporal interactions in a graph. Specifically, an operational aggregator is designed to extract global operational information based on the graph structure, while a geographical aggregator is developed to capture the similar nature among spatially close airports. Extensive experiments on a real-world dataset demonstrate that the proposed approach outperforms the state-of-the-art methods with a satisfying accuracy improvement.

Recommend or not? The influence of emotions on passengers’ intention of airline recommendation during COVID-19

Due to the COVID-19 pandemic, the airline industry has undoubtedly suffered serious losses. Investigation of passenger's intention to recommend an airline is urgently needed for airline companies to formulate specific retention strategies and revitalize the industry. Therefore, this study mainly sought to identify the latent factors that determine airline passenger's recommendation intention during the COVID-19 period, and investigate how the emotions expressed in passenger reviews affect their intention to recommend an airline. From the period between January 2020 and October 2021, 6798 online reviews were collected and analyzed. The results indicate that four out of eight emotional dimensions, including joy, trust, anger, and disgust, significantly influence passengers' intention to recommend. This study not only extended the applications of the expectancy-disconfirmation theory and Plutchik's emotional theory but also provided instructive suggestions for airline businesses that need to formulate marketing strategies, especially during the COVID-19 period.

Identifying airline passengers satisfaction and ground airport services perception of kolkata airport during COVID19- ASQ (Airport Service Quality) perspective

Background: The research on the airlines' ground services in airports is central to the business environment, impacting the departure and arrival functions, while COVID-19 has adversely affected service capabilities, impacting passenger safety and satisfaction. Aims: The aim is to find the factors influencing airport services during COVID-19 from the passenger perspective using the Airport Service Quality (ASQ) framework.Methods- ASQ (Airport service quality) scale was used with 39 items for a sample of 200, tested in SPSS for reliability and validity, and underwent factor analysis. Results-Airport management of Kolkata has emphasize the role of leadership management to focus on the airport ground services, with a new set of service protocols by WHO adapted to Kolkata ground services. Moderately satisfactory COVID-19 arrangements with, hand washing provision, facilities for immediate quarantine facility, disposal procedure, and way finding within Kolkata airport also have passengers who do not exhibit social conformance behaviour towards social distancing. Conclusion- Airport leadership management in airport ground services has accommodated the new COVID19 service that needs to match passenger behaviour aberrations to eliminate issues of contamination. Visual signage and way-finding guide passengers' well-being and satisfaction, while passengers must in the face of increased service time when following COVID19 service protocols.

Passengers' service perceptions emerging from user-generated content during the pandemic: the case of leading low-cost carriers

PurposeAlthough a vast amount of research has been started to gauge customer satisfaction using surveys, the influence of COVID-19 on passengers' satisfaction has not received enough attention. Hence, the primary purpose of this research is to determine the dominant themes that emerged from airline travelers' online reviews and to determine attributes that are pertinent to the satisfaction of passengers flying with low-cost carriers (LCC) during the COVID-19 outbreak. In addition, this study investigates whether the salient themes of passengers' overall experiences vary by traveler origin, which may give more insight into airline sector market segmentation.Design/methodology/approachLeximancer software was used to construct concepts from words, followed by themes in the data analysis.FindingsThe analyses revealed eight themes in descriptions of “travel experiences” for airline passengers. These are “flights,” “staff,” “service,” “hygiene,” “cancellations,” “legroom,” “COVID-19” and “test”. Negative reviews associated with “cancellations,” “refund,” “waiting” and “baggage” (handling) concepts.Originality/valueThe findings provide important information about airline passengers' overall experiences. Limited studies have comprehensively considered various satisfaction categories of airline travelers using online reviews.

Recognition of Air Passengers' Willingness to Pay for Seat Selection for Imbalanced Data Based on Improved XGBoost

Passenger-paid seat selection is one of the important sources of ancillary revenue for airlines, and machine learning-based willingness-to-pay identification is of great practicality for airlines to accurately tap potential willing passengers. However, affected by periodic statistical errors, air passenger order data often has some problems such as high noise, high latitude, and unbalanced category. In view of this, this paper proposes a method for identifying air passengers' willingness to pay for seat selection based on improved XGBoost, which is improved and integrated from three stages: data, feature, and algorithm. The feasibility of the proposed multi-stage improved integration method is verified by real airline passenger dataset, and the experimental results show that the proposed improved method has better classification effect when compared with the classical six imbalance classification models, which provides a basis for accurate marketing of airline paid seat selection programs.

Performance Comparison of K-Means and DBSCAN Methods for Airline Customer Segmentation

Organizations are now fully embracing ideas such as customer success, customer loyalty, customer experience management and customer satisfaction. The application of these concepts must be based on three pillars of technology, process and people, to ensure that the organization ultimately has satisfied, loyal and successful customers. In today's competitive environment, as in all sectors, gaining great services in the aviation industry can provide a competitive advantage. With this study, it is aimed to help aviation companies to know how their services should meet the needs of customers and to obtain passenger satisfaction. Customer segmentation is widely used, which groups objects according to the similarity difference on each object and provides a high level of homogeneity in the same cluster or a high level of heterogeneity between each group. The aim of this study is to examine airline passenger satisfaction by using data mining methods including K-Means and Density-based spatial clustering of applications with noise (DBSCAN) clustering algorithms to reveal the service quality importance for customer satisfaction. K-Means algorithm achieved slightly better results than DBSCAN algorithm with a Silhouette value of 0.1450671.

Application of Support Vector Machines and Holt Winters Exponential Smoothing Modelling Approaches in Airlines Passengers' Time Series Forecasting

Application of Support Vector Machines and Holt Winters Exponential Smoothing Modelling Approaches in Airlines Passengers' Time Series Forecasting