Passenger Satisfaction Research Articles

An analytical study on Opinions of the sample passengers of Iraqi airways

The purpose of the study: Being one of the oldest airlines in the Middle East region, Iraqi Airways serves its customers with both domestic and regional travel flight services. This study aims to investigate the extent of satisfaction derived by the passengers of Iraqi Airways. Methodology: A survey was conducted with 300 customers who were using Iraqi Airways from Iraq. Thus, the passengers who used Iraqi Airways were contacted through travel agents. A self-administered questionnaire was sent to 300 customers using Google Forms, out of which 223 were filled in and returned by respondents. The descriptive-analytical method of analysis for this study took the dimension of examining the passengers’ satisfaction towards Iraqi Airways based on the in-flight service variables namely: Crew Friendliness, Food and beverage, Cabin cleanliness, Seat comfort, Digital Entertainment, Toilet comfort, Child care, using SPSS VERSION 11 Results: The findings of the study state that the level of satisfaction from in-flight services is not up to the mark and especially passengers are not happy with crew friendliness, seat and toilet comfort. So they are not ready to recommend others to fly in Iraqi Airways, rather do they care about using the airlines again? Also, the awareness of customers towards the promotion programs and advertisements of Iraqi Airways is very low. Conclusion and recommendation: Since the influence of in-flight services is considerably strong the airlines have to focus their efforts on bringing the satisfaction of passengers up-to the expected level rather than directly shifting to the fleet and route expansion.

Railway Service Dynamics: Factors Shaping Customer Satisfaction in Indian Railways

This paper explores how customer satisfaction and service quality are perceived in the context of Indian Railways, focusing on factors that significantly influence passenger experiences. Drawing from both extensive literature and empirical data collected through a structured questionnaire from 305 respondents in Vijayawada, the study identifies key elements such as punctuality, cleanliness, ticketing procedures, staff behavior, and overall service reliability. Analysis using ANOVA reveals varying impacts of these factors on customer satisfaction across different service dimensions. While punctuality and staff behavior emerged as significant influencers, amenities like seating comfort and digital services showed less impact. Managerial implications highlight the importance of customer-centric strategies, staff training, and infrastructure improvements to enhance service quality and passenger satisfaction. The study concludes with suggestions for future research, emphasizing the need for exploring additional variables and conducting longitudinal studies to track changes in customer perceptions over time. This research not only enriches understanding of service quality in Indian Railways but also offers insights applicable to global transportation systems.

Do Underlying Physical Specifications of a Servicescape Matter? The Case of the Cruise Industry

Understanding customer satisfaction in the cruise industry has mainly focused on intangible attributes like dining and spa experiences. This study explores the impact of cruise-ship servicescape, shaped by physical characteristics such as size and width. Our research confirms the impact of servicescape on passenger satisfaction within the cruise industry. Specifically, passengers typically prefer newer, stable, and less crowded ships. We advocate for greater attention to servicescape design for a distinct, sustainable competitive advantage. Recognizing its significance can enhance customer experiences and market positioning. In addition to contributing to the research on the cruise industry and servicescape literature, this study provides valuable insights for industry stakeholders to enhance their understanding and management of customer satisfaction.

How Has COVID-19 Affected Airline Passenger Satisfaction? Evaluating The Passenger Satisfaction of European Short-Haul Low-Cost Carriers Pre- and Post-COVID-19

This paper investigates whether there has been a change in passenger satisfaction drivers for the three largest short-haul low-cost carriers in Europe before and after COVID-19. User-generated content on the Skytrax platform was used as the data source for passenger satisfaction, and these secondary data were scraped using the Web Scraper tool. Binary logistic regression was used for the classification model related to passenger satisfaction, and ROC analysis was used to evaluate the classification performance of the model. The findings suggested that the service attributes of seat comfort, cabin staff services, and ground services are significant predictors of value for money, and the value for money is a significant determinant of overall satisfaction in both periods. Additionally, it was revealed that ground service is the most important determinant of the value for money perception. The results also indicate that in the post-COVID-19 period, the predictive power of seat comfort has decreased while the predictive power of ground services has increased.

The influence of service quality, passenger satisfaction, perceived value, and airline brand love on word-of-mouth behavior among domestic airline users in Indonesia

This study aims to analyze the impact of crucial dimensions in the Indonesian domestic airline industry, namely Service Quality, Passenger Satisfaction, Perceived Value, and Airline Brand Love, on Word of Mouth (WOM) behavior among passengers. Data was collected from respondents who are users of domestic airlines in Indonesia. The analysis revealed several key findings. Firstly, Passenger Satisfaction has a significant positive influence on both Airline Brand Love and Word of Mouth. This relationship is supported by the calculated t-value exceeding the critical t-value and the significance level (P-value) being less than 0.05. Therefore, to increase sales, improving passenger satisfaction levels should be a priority. Secondly, Perceived Value does not have a significant positive influence on either Airline Brand Love or Word of Mouth. This is evident from the calculated t-value being lower than the critical t-value and the P-value being greater than 0.05. Nevertheless, it's important to still consider the aspect of Perceived Value in efforts to enhance customer experience. Thirdly, Service Quality has a proven significant positive influence on Airline Brand Love, but not on Word of Mouth. This positive relationship is indicated by the calculated t-value exceeding the critical t-value and the significance level being less than 0.05. In this context, improving service quality can be a crucial factor in building brand love for the airline. Thus, this study provides insights into the factors influencing Word of Mouth behavior in the Indonesian domestic airline industry. The implications of these findings are the need for airline companies to focus on improving passenger satisfaction and service quality to strengthen the connection between Passenger Satisfaction, Airline Brand Love, and Word of Mouth. Additionally, although Perceived Value does not have a significant impact in this context, it remains important to consider this factor in efforts to maintain customer satisfaction and loyalty.

Does the Airport Servicescape Affect the Relationship between Airport Outcome Quality and Passenger Satisfaction?

Airports promote passenger satisfaction with superior service. Airport outcome quality (AOQ) is a part of Airport Service Quality (ASQ), which impacts daily service performance. In this study, the airport servicescape influenced the link between airport outcome quality and passenger satisfaction. The model was developed using the Hierarchical Service Quality Model (HSQM) and Stimulus-Organism-Response (SOR) theory, incorporating two direct and moderated paths. The study utilized a convenience sampling technique and conducted a cross-sectional survey of international travellers at critical airports in Tanzania. 389 respondents were evaluated using the PLS-SEM technique. Significant enhancements have been made in the direct and moderated relationships between airport outcome quality and passenger satisfaction. The airport environment was more effectively managed than the direct route. The environment of an airport improves the satisfaction of international airport passengers. Moreover, these findings have implications for theory, methodology, management, and policy. The study enhances the partial least squares research methodologies, specifically for higher-order structures. The study shows airport architects and officials that the airport servicescape is crucial for improving customer satisfaction at airport terminals.

Evaluation of digital solutions for passenger attitudes towards health measures at Dalaman airport during COVID-19 period

During the COVID-19 pandemic, the Ministry of Transport and Infrastructure and airline companies implemented various measures to prevent the spread of the virus and reduce the risk of transmission. Among the various measures implemented, those utilizing digital technologies to minimize contact between passengers at airport terminals and ground services personnel have been particularly noteworthy. Self-service technologies not only enhance time and space efficiency but also minimize interpersonal contact. This research aims to evaluate the positive impact of COVID-19 measures implemented at Dalaman Airport on passenger satisfaction and to examine the role of digital technologies in this effect. To this end, face-to-face surveys were conducted with at least 415 passengers at Dalaman Airport between October and November 2023. The data obtained were analyzed using the SPSS program to determine the effects of COVID-19 measures and digital technologies on passenger satisfaction. The research factor analysis, reliability analysis, correlation, and regression analyses to examine the relationships between satisfaction, digitization, and measures reducing discomfort, revealing significantly positive relationships. As a result, this research recommends airport management to realign technology investments and customer service policies centered on passenger satisfaction. Digitalisation efforts can facilitate passengers to better adapt to new norms and provide a safer and more comfortable travel experience. The research also highlights that future studies with generalized findings across a wider range of airports and passenger demographics will develop a more comprehensive understanding of how digital technologies can be used more effectively in the aviation sector.

Do We Scapegoat The Pandemic? Investigating The Changes in Satisfaction Drivers of Air Passengers With DWLS-SEM

This paper aims to investigate whether there is an alteration in the drivers of air passenger satisfaction before and after COVID-19. We conducted the multigroup structural equation modelling with the diagonally weighted least squares estimation method as the variables are categorical. Lastly, we performed ANOVA to spot if there is a change in the drivers of passenger satisfaction between before and after the pandemic. The results suggest all service attributes have a significant impact on satisfaction in the pre-COVID-19 era. Even if it seems that in-flight entertainment and in-flight WiFi are not as influential as before in the post-pandemic, ANOVA results revealed the difference between the pre-pandemic and the new-normal period was not statistically significant. Accordingly, airlines should not ignore the need to improve service attributes, called premium services, and holistically improve service design. In addition, after value for money, the most important attribute for passengers is ground handling. Hence, speeding up the boarding process would return carriers in the form of more satisfied customers. To the best of our knowledge, this is the first paper employing Multigroup DWLS SEM to focus on changes in determinants of air passenger satisfaction in a holistic approach, focusing on pandemic periods.

Predictive Modeling of Flight Delays at an Airport Using Machine Learning Methods

Flight delays represent a significant challenge in the global aviation industry, resulting in substantial costs and a decline in passenger satisfaction. This study addresses the critical issue of predicting flight delays exceeding 15 min using machine learning techniques. The arrival delays at a Turkish airport are analyzed utilizing a novel dataset derived from airport operations. This research examines a range of machine learning models, including Logistic Regression, Naïve Bayes, Neural Networks, Random Forest, XGBoost, CatBoost, and LightGBM. To address the issue of imbalanced data, additional experiments are conducted using the Synthetic Minority Over-Sampling Technique (SMOTE), in conjunction with the incorporation of meteorological data. This multi-faceted approach ensures robust forecast performance under varying conditions. The SHAP (SHapley Additive exPlanations) method is employed to interpret the relative importance of features within the models. The study is based on a three-year period of flight data obtained from a Turkish airport. The dataset is sufficiently extensive and robust to provide a reliable foundation for analysis. The results indicate that XGBoost is the most proficient model for the dataset, demonstrating its potential to deliver highly accurate predictions with an accuracy of 80%. The impact of weather factors on the predictions is found to be insignificant in comparison to scenarios without weather data in this dataset.

Assessment of Passengers Satisfaction with Intra – Urban Transport Services in Owerri Municipal

Assessment of Passengers Satisfaction with Intra – Urban Transport Services in Owerri Municipal

The New Norm, a reality or a fiction? A longitudinal passenger satisfaction study on the persisting effects of COVID-19

The concept of the "new norm" implies a shift in societal behavior, and the COVID-19 pandemic is suspected to have long-term effects on customer perceptions of public transportation service factors such as crowdedness and cleanliness as mentioned in the literature. To assess the existence of a new norm in passenger behavior, a six-wave longitudinal customer satisfaction survey was conducted, comprising four waves before the pandemic and two waves after, in addition to an interview panel survey. Employing the SEM-MGA approach, we modelled the longitudinal sample, utilizing a confirmatory factor analysis framework grounded in passenger satisfaction literature specific to the Tehran metro. A MGA model was introduced, and the Importance-Performance Analysis was employed to identify alterations in the significance and execution of satisfaction factors across each survey wave and model. Three main factors of cleanliness, crowdedness, ventilation, were examined to assess the new norm. Each factor consistently emerged as a significant factor in passenger satisfaction, pre and post-COVID-19. In conclusion, our findings indicate that the COVID-19 pandemic did not have an observable long-term impact on public transportation passengers' perceptions of cleanliness and ventilation. This suggests that authorities may consider returning to pre-pandemic operational practices to conserve valuable resources. Moreover, our study underscores passengers' adaptability and the system's reversion to pre-pandemic norms in this regard.

A City Shared Bike Dispatch Approach Based on Temporal Graph Convolutional Network and Genetic Algorithm.

Public transportation scheduling aims to optimize the allocation of resources, enhance efficiency, and increase passenger satisfaction, all of which are crucial for building a sustainable urban transportation system. As a complement to public transportation, bike-sharing systems provide users with a solution for the last mile of travel, compensating for the lack of flexibility in public transportation and helping to improve its utilization rate. Due to the characteristics of shared bikes, including peak usage periods in the morning and evening and significant demand fluctuations across different areas, optimizing shared bike dispatch can better meet user needs, reduce vehicle vacancy rates, and increase operating revenue. To address this issue, this article proposes a comprehensive decision-making approach for spatiotemporal demand prediction and bike dispatch optimization. For demand prediction, we design a T-GCN (Temporal Graph Convolutional Network)-based bike demand prediction model. In terms of dispatch optimization, we consider factors such as dispatch capacity, distance restrictions, and dispatch costs, and design an optimization solution based on genetic algorithms. Finally, we validate the approach using shared bike operating data and show that the T-GCN can effectively predict the short-term demand for shared bikes. Meanwhile, the optimization model based on genetic algorithms provides a complete dispatch solution, verifying the model's effectiveness. The shared bike dispatch approach proposed in this paper combines demand prediction with resource scheduling. This scheme can also be extended to other transportation scheduling problems with uncertain demand, such as store replenishment delivery and intercity inventory dispatch.

Passenger satisfaction assessment in the aviation industry using Type-2 fuzzy TOPSIS

Assessment of passenger satisfaction (PS) ratings is a noteworthy component of evaluating the service quality metrics used by airline companies. One of the most popular ways for airline companies to gauge customer satisfaction (CS) and determine what needs to be improved is by conducting surveys of their customers. In this study, we used an extended version of the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) technique, which is one of the most important multi-criteria decision-making (MCDM) methods, with type-2 fuzzy sets to evaluate PS for the first time in the literature. Using this systematic technique, we have reflected to the model the uncertainty that may affect the evaluations of the passengers when making their assessments. Our study is considerably beneficial since it enables not only the PS evaluation of airline companies but also it is a generalization to analyze any type of CS that may be found in the aviation sector. We used our technique on questionnaires answered by 129,880 US Airlines passengers concerning 14 criteria and compared our results with studies in the literature using the same dataset. Unlike the literature, in this paper, passenger segmentation has been done to obtain effective results. Different scenarios are created for each emerging segment. While creating the scenarios, the passenger profiles of overall satisfaction, flight class, and customer loyalty are considered and different priorities are given to these variables in each scenario. We have utilized these scenarios to help airlines determine the demands of each consumer segment to improve service quality. Our study provides airline companies with an integrated decision system, with a holistic perspective, in which they can take into account not only their customers as one type, but also the differences they may experience in evaluating both their flight habits and flight experiences.

Exploring Passenger Satisfaction in Multimodal Railway Hubs: A Social Media-Based Analysis of Travel Behavior in China’s Major Rail Stations

Exploring Passenger Satisfaction in Multimodal Railway Hubs: A Social Media-Based Analysis of Travel Behavior in China’s Major Rail Stations

The Impact of Using Airline Mobile Applications on Passenger Satisfaction in Egypt Air

The Impact of Using Airline Mobile Applications on Passenger Satisfaction in Egypt Air

Service Quality Assessment of Sharedautorickshaws Using Subsets-Based Confirmatory Factor Analysis

Abstract Shared mobility is changing urban transportation in India by providing transportation services without the need for ownership. Sharedautorickshaws (also called as share-autos) are a popular mode of shared mobility in the country. These informal vehicles can hold six to ten passengers and operate on a hail-to-board basis. It is important to evaluate the service quality of share-autos as they gain popularity. While research on passenger satisfaction with shared mobility services exists, studies on service quality perception related to share-autos are limited. To address this research gap, a survey was conducted with 581 shareauto users in India. The study created a Confirmatory Factor Analysisbased model with five latent variables and 22 manifest variables. The results revealed that 18 variables significantly influenced service quality. Variables that had weaker factor loading in the overall analysis were found more important when analysed for different subsets of the sample population. For instance, female-only or low-income-group respondents may prioritize different factors than the overall sample, and the ranking of factor loading changes across the subsets. The study shows that subset-based analysis can provide a more nuanced understanding of the passenger experience in share-autos, identifying potential opportunities to improve the quality of these services.

The Impact of Service Innovation on Passenger Satisfaction in Dubai Metro

Abstract: The metro systems have witnessed a significant growth and development over recent decades due to the advancement in innovated technologies in transport industries. Dubai Metro is a result of the tremendous development in the United Arab Emirates. However, metro service operations have become challenging, especially in urban areas that are characterized by the dynamic increase in population so passenger satisfaction could be a difficult objective to obtain. The particular mechanisms by which service innovation influences passenger satisfaction have not been well investigated in the literature, especially in the case of Dubai Metro. Due to that, studying passenger satisfaction allows for the identification of areas that require attention and improvement, leading to more efficient and effective metro transportation systems. Therefore, this paper aims to highlight the role of service innovation on passenger satisfaction in Dubai Metro. A study on Dubai Metro is based on the perspective of disruptive innovation theory to help this company to attain a high level of passenger satisfaction due to service innovation. The analysis of literatures reveals a substantial relationship between service innovation in metro transport sector and passenger satisfaction. the research on passenger satisfaction is critical for the development of public transport in general and metro systems in particular because it provides valuable insights into the needs and preferences of commuters. By understanding what makes passengers satisfied, transport authorities can make informed decisions to improve the quality of services, enhance overall customer experience, and ultimately increase ridership. Abstrak: Sistem metro telah menyaksikan pertumbuhan dan pembangunan yang ketara sejak beberapa dekad kebelakangan ini disebabkan oleh kemajuan dalam teknologi berinovasi dalam industri pengangkutan. Metro Dubai adalah hasil daripada pembangunan yang luar biasa di Emiriah Arab Bersatu. Walau bagaimanapun, operasi perkhidmatan metro telah menjadi mencabar, terutamanya di kawasan bandar yang bercirikan dinamik pertambahan penduduk sehingga kepuasan penumpang boleh menjadi objektif yang sukar diperoleh. Walaupun mekanisme tertentu yang mana inovasi perkhidmatan mempengaruhi kepuasan penumpang belum disiasat dengan baik dalam literatur, terutamanya dalam kes metro Dubai. Untuk itu, mengkaji kepuasan penumpang membolehkan mengenal pasti kawasan yang memerlukan perhatian dan penambahbaikan, yang membawa kepada sistem pengangkutan metro yang lebih cekap dan berkesan. Oleh itu, tujuan kertas kerja ini adalah untuk menonjolkan peranan inovasi perkhidmatan terhadap kepuasan penumpang di metro Dubai. Kajian mengenai metro Dubai adalah berdasarkan perspektif teori inovasi yang mengganggu untuk membantu syarikat ini mencapai tahap kepuasan penumpang yang tinggi dalam inovasi perkhidmatan yang wajar. Analisis literatur mendedahkan hubungan yang ketara antara inovasi perkhidmatan dalam sektor pengangkutan metro dan kepuasan penumpang. penyelidikan dalam kepuasan penumpang adalah penting untuk pembangunan pengangkutan awam amnya dan sistem metro khususnya kerana ia memberikan pandangan berharga tentang keperluan dan keutamaan penumpang. Dengan memahami perkara yang membuatkan penumpang berpuas hati, pihak berkuasa pengangkutan boleh membuat keputusan termaklum untuk meningkatkan kualiti perkhidmatan, meningkatkan keseluruhan pengalaman pelanggan dan akhirnya meningkatkan jumlah penumpang.

A deep learning and large group consensus based cruise satisfaction evaluation model with online reviews

Cruise satisfaction assessment is pivotal for both passenger experiences and the enterprise's industry competitiveness. To do that, this research proposes a deep learning based cruise satisfaction evaluation model by integrating cruise online reviews and a large group consensus model. In order to acquire the dimensions influencing cruise passenger satisfaction, attribute extraction is employed. Unlike traditional methods that rely on word-based attribute representation, this method employs sentence-level information to comprehensively capture attributes that are of genuine concern to users, including implicit ones. Additionally, it utilizes the pre-trained language model, BART, to accurately predict sentiment polarity by treating sentiment analysis as a generation task based on online reviews from the CruiseCritic website. Subsequently, the proposed consensus model is implemented to determine the final satisfaction level, taking into consideration subgroup weights and an ideal solution-based feedback mechanism. This mechanism facilitates the provision of reasonable adjustment recommendations tailored to the context of online evaluations. Ultimately, the research findings contribute valuable insights to enhance service quality within the Royal Caribbean International cruise line.

DelayDetect: Pre-takeoff Delay Anticipation

Abstract: Flight delays pose significant challenges to both passengers and airlines, leading to inconvenience, financial losses, and operational disruptions. A comprehensive system is introduced to address the issue of airline flight delays through the application of machine learning models. Leveraging comprehensive datasets encompassing historical flight records, meteorological data, airport congestion patterns and other variables, this model aims to construct predictive models capable of accurately forecasting the probability of flight delays. Various machine learning methodologies including random forests and regression models, are systematically examined in this predictive task. Performance evaluation is conducted employing established metrics such as accuracy and precision. In conclusion, flight delay anticipation is a valuable tool that can revolutionize the aviation industry by minimizing disruptions, reducing costs, and increasing passenger satisfaction.

Analisis Tingkat Kepuasan Penumpang terhadap Kualitas Layanan di Pelabuhan Feri Kendari- Wawonii

Indonesia as an archipelagic country requires reliable sea transportation. One of the means of sea transportation is the port. One of the roles of the port is the main gateway for the flow of goods, both exports and imports, and the transfer of cargo between modes of transportation and plays an important role in the country's economy to create economic growth. This research aims to analyze passenger satisfaction with the quality of services provided at the Kendari-Wawonii Ferry Port. The implementation method is quantitative descriptive. The research sample was 384 passengers who referred to Permenpan RB Number 14 of 2017 concerning Guidelines for Preparing Community Surveys for Public Service Organizing Units. The research results found that public satisfaction at the Kendari-Wawonii Ferry Port in 2023, which is mandated by Law Number 25 of 2008 concerning Public Services, by assessing 9 elements resulted in a figure of 76,824 (not good). The elements that received the highest scores were the system elements, mechanisms and procedures, while the elements that received the lowest scores by the research respondents were the complaint handling elements and the facilities and infrastructure elements.