Passenger Experience Research Articles

CRUISE TOURIST EXPERIENCE: AN ANALYSIS FROM TRIPADVISOR REVIEWS

Cruise tourism has grown in popularity, making it essential to understand the experiences of tourists who choose this unique mode of travel. This study examines the cruise tourist experience through the analysis of TripAdvisor reviews, focusing on key factors that shape customer satisfaction and overall travel experience. Utilizing content analysis, a comprehensive dataset of cruise reviews was analyzed to identify recurring themes such as service quality, onboard activity, and perceived value The results indicate that positive cruise experiences are heavily influenced by personalized service, high-quality food, and diverse entertainment offerings, while negative experiences often stem from overcrowding, service delays, and itinerary changes. This research provides valuable insights into the aspects of cruise tourism that enhance or diminish customer satisfaction. These findings offer practical implications for cruise operators looking to improve service quality and enhance the overall travel experience for cruise passengers. Further research recommendations are provided to explore variations in experience across different demographics and cruise types.

Advanced semantic segmentation of aircraft main components based on transfer learning and data-driven approach

Abstract The implementation of Smart Airport and Airport 4.0 visions relies on the integration of automation, artificial intelligence, data science, and aviation technology to enhance passenger experiences and operational efficiency. One essential factor in the integration is the semantic segmentation of the aircraft main components (AMC) perception, which is essential to maintenance, repair, and operations in aircraft and airport operations. However, AMC segmentation has challenges from low data availability, high-quality annotation scarcity, and categorical imbalance, which are common in practical applications, including aviation. This study proposes a novel AMC segmentation solution, employing a transfer learning framework based on a sophisticated DeepLabV3 architecture optimized with a custom-designed Focal Dice Loss function. The proposed solution remarkably suppresses the categorical imbalance challenge and increases the dataset variability with manually annotated images and dynamic augmentation strategies to train a robust AMC segmentation model. The model achieved a notable intersection over union of 84.002% and an accuracy of 91.466%, significantly advancing the AMC segmentation performance. These results demonstrate the effectiveness of the proposed AMC segmentation solution in aircraft and airport operation scenarios. This study provides a pioneering solution to the AMC semantic perception problem and contributes a valuable dataset to the community, which is fundamental to future research on aircraft and airport semantic perception. Graphical abstract

Integrating hybrid deep learning and path allocation for real-time inbound passenger flow prediction and anomaly detection in urban rail transit

This paper study the problem of real-time prediction of inbound passenger flow and the detection and alerting of abnormal passenger flows in urban rail transit (URT) networks. We propose a fused framework that combines a hybrid deep learning model and an evaluation strategy. Specifically, the learning model incorporates Graph Convolutional Networks (GCN), Gated Recurrent Units (GRU), and attention mechanisms to effectively capture spatial and temporal correlations in passenger flow data. The evaluation strategy utilizes a depth-first search algorithm to determine the optimal travel paths for each individual passenger. And based on the paths, we develop a real-time method for estimating the origin–destination (OD) matrix that utilizes both long-term and short-term historical destination trend vectors to reduce dimensions while improving predictive accuracy. Through extensive testing using data from the Shanghai rail transit system, we demonstrate that this fused framework achieves high prediction accuracy for inbound passenger flow at various stations while efficiently identifying and warning sudden large-scale events involving significant increases in passenger flow volume. This research contributes towards improving overall passenger experience as well as operational resilience within urban rail systems when dealing with large-scale influxes of passengers.

Optimizing the function of aircraft WiFi based on the Internet of Things

Abstract. This paper explores the potential of full-duplex wireless communication technology to mitigate interference in aircraft WiFi systems, thereby enhancing the internet access quality and passenger experience. The study focuses on the application of Internet of Things (IoT) technology to improve the resilience of aircraft WiFi systems against interference. Through a series of MATLAB simulations, the research demonstrates that full-duplex technology can effectively cancel out interference signals, leading to clearer and more stable communication quality. The results show that the combined signal, after cancellation, closely resembles the original communication signal, indicating a significant reduction in interference. Despite the promising results, the study acknowledges limitations such as idealized assumptions in the simulation, hardware and software constraints, and the lack of consideration for the complex electromagnetic environment encountered during actual flight operations. Future research should focus on developing more advanced interference detection and mitigation algorithms, and further investigation into the integration of full-duplex technology with existing aircraft WiFi systems, considering hardware constraints and environmental factors, is necessary to fully realize its potential in enhancing communication performance.

The Application of Near Field Communication (NFC) in Public Transportation: Current Practices, Challenges, and Future Prospects

In the field of public transportation, the introduction of NFC technology can realize contactless payment and automatic ticket checking functions, significantly improving system efficiency and passenger experience. The article first reviews the development history of the public transportation system and the basic principles of NFC technology, and then analyzes the technical architecture and working principle of the NFC payment system. Through the cases of public transportation systems in many cities around the world, the practical application and effect of NFC technology are demonstrated. This article also verifies the transaction speed, stability and user satisfaction of NFC technology in the public transportation system through a series of experimental evaluations. The results show that NFC technology has excellent performance in terms of processing speed, system stability and user satisfaction, especially during peak hours, its advantages are more obvious. At the same time, the research also pointed out the limitations of current NFC technology applications and the challenges faced in practical applications. In the future, NFC technology will become more complete and is expected to provide passengers with a more personalized and intelligent service experience.

Simulation modeling of passengers flow at airport terminals to reduce delay and enhance level of service

Passenger delays are considered as global issues that influence the overall efficiency of an airport and competitiveness as well as restricting terminal developments. This paper studied Kuwait International Airport Terminal 4 (T4); a new expansion of the old airport. This study mainly aims to analyze the influence of the design on passenger flow in T4 and how it affected the capacity in addition to obtain a path for the passenger movement from the terminal entrance until they reach the gate of the aircraft and vice versa through CAST simulation model. The effect of the T4 design on the overall efficiency was found, the current flow conditions were analyzed and compared with the required Level of Service (LOS) and several developments and expansions were suggested. Passengers flow was studied to improve passenger experience, increase operational efficiencies, maximize retail revenues and increase security effectiveness. It was indicated that customs and security facilities require expansion in areas during peak hours to maintain a high level of performance. However, the check in premium showed the minimum gap between queue capacity and the declared queuing size indicating the high level of service in this area. The results revealed that immigration queueing requires expansion. Moreover, queuing area provision indicates no capacity issues to cope with maximum queue size. The provision of immigration counters according showed no adequate queuing space to cope with MQS. It is recommended to increase the number of economy check-in counters.

Navigating the challenges of public transport and urban mobility in Thohoyandou, South Africa

Background: Transport systems are an essential feature of functional urban settlements. Yet, almost all of South Africa’s secondary cities and small towns lack a true public transportation system. Because of this, quasi-public, privately operated mini-bus taxis are the main form of transport for most urban residents. Thohoyandou, Limpopo, a town of over 70 000 people, is a typical South African town in this regard.Objectives: The purpose of this research was to understand passenger experiences of mini-bus taxis in Thohoyandou, Limpopo province, South Africa.Method: This study used semi-structured interviews to explore the mobility challenges faced by the residents of Thohoyandou.Results: This study revealed several negative aspects impacting passenger experiences. Passengers consistently reported concerns regarding driver’s behaviour that compromised safety and security. This included overloading of vehicles and disregard for traffic regulations. Passengers also highlighted the challenges posed by poor transport infrastructure and a lack of reliable service. Collectively, these factors contribute to limited mobility options, increased transportation costs and a reduced quality of life. Furthermore, the shortcomings of mini-bus taxi services disproportionately affect people with disability, who already face significant societal barriers, further marginalising them within the transportation system.Conclusion: The government should increase investment in transport infrastructure, the enforcement of traffic laws and better driver training. However, a strong government combined with much political will is required if passengers and safety are to be the main priorities of the mini-bus taxi industry.Contribution: This study highlights challenges faced by public transport users in Thohoyandou, where mini-bus taxis serve as the main mode of transport. The challenges experienced by transport users not only reduce their mobility but also contribute to marginalisation of vulnerable groups, especially people with disability.

The Service Experience Equity on Repatronage Intention within Public Transportation Services

In a highly competitive market, service providers are often expected to enhance their profitability by delivering superior service quality. This principle is evident among many public transportation providers in Malaysia, who strive to elevate the passenger experience through refined service offerings. The objective of this study is to examine the factors influencing repatronage intentions among public transportation users in Malacca, Malaysia, using the Service Experience Equity (SEE) framework. To demonstrate the causal connections between the variables, a regression analysis has been employed. The findings reveal that service atmosphere and personnel interactions significantly impact users' willingness to continue using these services. The study emphasizes the importance for management to prioritize customer experience by investing in service environment strategies that foster user engagement and discourage customer churn. It further underscores that both the overall service experience and the quality of employee-customer interactions are critical determinants of future patronage. Consequently, it is recommended that transportation service providers leverage these elements to create a competitive edge, thereby encouraging repeat usage and building long-term customer loyalty.

Exploring the Impact of Airport Services on Passenger Satisfaction in Tanzania: A Case Study of Julius Nyerere International Airport

Satisfying passengers at the airport has been the cornerstone for airlines and airports in air transport service. This study aimed to understand the effects of airline-related quality service dimensions on overall passenger satisfaction at airports. The study intended to analyse the effect of pre-flight, in-flight, and post-flight services on passenger satisfaction at the airport. Passengers begin to interact with air transport services when booking a ticket, and airline-related service dimensions are considered part of the broader concept of airport services, which should be integrated as they overlap in satisfying passengers at the airport. Previous research focused extensively on airport-related factors but overlooked the specific impacts of airline services on overall passenger satisfaction. The study was guided by Total airport experience framework considering holistic view of passenger satisfaction. The study used a descriptive research design which targeted all international passengers travelled through Julius Nyerere International Airport at the time of conducting this study. In this regard, the study included departing and arriving passengers from Terminal III at the final lounge and baggage claim area. The Webb et al (1996) guidelines were used to determine the sample size which suggests that for population above 2,000, a sample of 1% is appropriate; The population consisted of 18,000 passengers arriving and departing at Julius Nyerere international Airport during the time of conducting survey; thus 180 passenger were selected randomly ensuring that every passenger had an equal chance of being selected. Collection of data invloved questionnaires with close-ended and open-ended questions. Descriptive analysis of collected data was conducted to summarize the main variables through utilizing the Statistical Package for Social Science (SPSS) for data analysis to obtain percentages and frequencies. The findings indicated that several dimensions of airline-related service influence passenger satisfaction: pre-flight, in-flight, and post-flight dimensions. The findings revealed that these three dimensions positively affect passenger satisfaction. For instance, in pre-flight services, respondents reported satisfaction, highlighting the crucial role of effective management of pre-flight services in determining positive initial travel experiences. High satisfaction rates were also observed for in-flight services, emphasizing the importance of onboard amenities and crew responsiveness. However, post-flight services showed areas for improvement to enhance the overall passenger experience. Additionally, the results highlighted the strategic necessity for airlines and airports to prioritize service excellence across all touchpoints of the passenger journey. Enhancing service quality and responsiveness, particularly in mishap resolution and service delivery which are crucial for maintaining a competitive advantage and fostering customer loyalty. The study concluded that passenger satisfaction is highly influenced by three primary dimensions of airline related service: pre-flight, in-flight, and post-flight dimensions. The study recommends the Airline and airport operators to focus on improving service quality delivery across all touch points of passengers journey by implementing an integrated approach such as coordinated decision making.

The role of physical and social environments on the loyalty toward urban rail services: A consideration of stations and onboard

Although urban train services have been introduced in various developing countries, ridership for this mode of public transport (PT) remains low. In response, urban planning authorities are seeking ways to boost passenger loyalty to these services. However, the existing literature has scarcely examined the role of physical and social environments in fostering passenger loyalty. Additionally, how loyalty is developed throughout the passenger experience - both at stations and onboard - remains unclear. Addressing this gap, the current study develops a model based on the 'service quality-satisfaction-behavioural intentions' paradigm and the Stimulus-Organism-Response (S-O-R) model to examine how the physical and social environments, both at rail stations and onboard trains, impact passenger loyalty in the context of urban train services. Additionally, this study validates the multi-dimensionality of physical environments and social environments in this context. Data collected from urban rail passengers in Hanoi, Vietnam is analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that the physical and social environments onboard trains significantly influence loyalty towards the urban train services, while the environments at stations do not have the same impact. Furthermore, both satisfaction at stations and onboard trains significantly affect the loyalty, though the influence of satisfaction with the onboard experience is much stronger than that of satisfaction with the stations. Practically, the findings assist PT authorities in evaluating existing systems and devising future PT development strategies. Also, the study informs PT providers of ways to improve passenger satisfaction and loyalty.

Analysis of the Application and Prospects of Intelligent Technology in Sustainable Railway Operations

With the rapid development of technology, intelligent technology plays an increasingly important role in the sustainable operation of railways. This paper explores the application and prospects of intelligent technology in sustainable railway operations, emphasizing its key roles in enhancing operational efficiency, strengthening safety assurance, optimizing passenger experience, and promoting environmental protection and energy conservation. Through intelligent dispatching, real-time monitoring, big data prediction, personalized services, and mobile ticketing technologies, the railway system achieves efficient resource allocation and service innovation. The intelligent transformation of railways demonstrates significant economic and social benefits, contributing to emission reduction targets and sustainable development. Future efforts should focus on strengthening top-level design, technological innovation, standard construction, and network security to advance the intelligent railway process and co-create a new era of smart, green, and efficient railway transportation.

Exploring Smart Airports’ Information Service Technology for Sustainability: Integration of the Delphi and Kano Approaches

Airport digitalization has revolutionized service delivery at passenger touchpoints, which leads to sustainable passenger loyalty. However, it is critical to determine whether this rapid transition to digital services genuinely enhances passenger satisfaction with airport services. This study uses a mixed-method approach to identify key traditional and technology-driven information services in smart airports. The specific aim is to determine the optimal balance in which digital technologies can effectively replace human-provided services to establish sustainable passenger loyalty. Two rounds of Delphi surveys were conducted with panels of 23 and 21 experts, followed by an online Kano survey with 401 international passengers. The Delphi analysis identified 16 key information service attributes, while the Kano analysis revealed that the majority of technology-based services were attractive and positively influenced passenger satisfaction. By contrast, human-based services were mostly indifferent, although some were vital for boosting satisfaction and preventing dissatisfaction. These results advance the current airport service research and provide practical insights into optimizing passenger experiences through the strategic integration of technology for sustainable smart airports while maintaining essential human-provided services.

Human-Centric Design Model to Enhance the Passenger Experience of Airport Smart Security System

Many studies have overlooked the aspect of humans when it comes to the security system integration in an airport. Hence, this study aims to develop a human-centric smart security system at the Dubai International Airport (DXB) to enhance the passenger experience. This paper proposed a human-centric design model to assess passenger experience at the smart security gate in the DXB and uses the model to analyze the proposed model based on the feedback of passengers. The model is represented by the human-centric dimension of emotional/feeling, behavior, needs and requirements, usability, trust, cognitive, and ergonomics that has a relation with passenger experience. A survey was administered to 400 respondents who had experience using the airport security system at the DXB. Regression analysis was used to test the relationship within the model and establish a human-centric model. Usability tests were used to gain deeper insight and gauge a more in-depth opinion of the respondents. It was found that cognitive had a low influence on passenger experience, while most respondents viewed the model as very useful. The findings of the study will assist the airport industry and authorities in UAE airports to better position their security system and enhance the passenger experience.

Structured acoustic materials for mitigating low-frequencybroadband aircraft noise: transfer matrix method

This study investigates, by numerical modeling, the mitigation of low-frequency broadband aircraft noise using a structured assembly of acoustic materials using the Transfer Matrix Method. The prevalence of low-frequency aircraft noise poses challenges to environmental sustainability and passenger comfort. The investigation focuses on an approach that employs strategically arranged structured acoustic materials to attenuate undesirable noise frequencies. The Transfer Matrix Method is used to model the acoustic behavior of the structured assembly, enabling a comprehensive analysis of sound transmission and absorption properties. This method supports the design and optimization of the assembly. The performance of the structured assembly to selectively attenuate low-frequency broadband noise is assessed through numerical simulations. The paper discusses implications for aircraft design, considering factors such as weight and cost. The benefits for environmental impact and passenger experience are also explored. Challenges and limitations in the implementation of structured acoustic materials are examined. The configuration studied presents an assembly of structured metamaterials arranged in series and in parallel which are integrated into a layer of glass wool. Present research contributes to the development of sustainable solutions for low-frequency aircraft noise. The structured assembly analyzed shows promise for significant noise reduction while considering practical constraints.

Evaluation of the Impacts of On-Demand Bus Services Using Traffic Simulation

This paper uses smart card data from Melbourne’s public transport network to model and evaluate the impacts of a flexible on-demand transport system. On-demand transport is an emerging mode of urban passenger transport that relies on meeting passenger demand for travel using dynamic and flexible scheduling using shared vehicles. Initially, a simulation model was developed to replicate existing fixed-schedule bus performance and was then extended to incorporate on-demand transport services within the same network. The simulation results were used to undertake a comparative analysis which included reliability, service quality, operational efficiency, network-wide effectiveness, and environmental impacts. The results showed that on-demand buses reduced average passenger trip time by 30%, increased vehicle occupancy rates from 8% to over 50%, and reduced emissions per passenger by over 70% on an average weekday compared to fixed-schedule buses. This study also offers insights for successful on-demand transport implementation, promoting urban sustainability. It also outlines future research directions, particularly the need for accurate short-term passenger demand prediction to improve service provision and passenger experience.

Uncovering airline service quality dimensions from passengers' online reviews: A text mining approach to validate and extend Servqual

This study investigates airline service quality dimensions by employing text-mining techniques to analyse passengers' emotional responses and experiences with airlines as reflected in their online reviews. The study aims to identify the relationship between these and SERVQUAL dimensions to confirm its reliability in the airline industry and reveal new and promising dimensions of airline service quality. The study contributes to academia by enriching literature on airline service quality and text mining applications, identifying areas for enhancement, and suggesting strategic directions for continuous improvement to practitioners based on passengers' quality perceptions of airline service experiences. With a large dataset from 100 airlines obtained from Skytrax, the study offers a deeper understanding of airline service quality. It encourages using big data and text-mining techniques to explore consumer preferences. The study's findings challenge traditional models and bring out new, context-specific service quality characteristics to provide a greater understanding of passenger experiences. These give the airlines insightful guidance on improving service offerings and fulfilling customer expectations, eventually improving customer satisfaction, loyalty, and competitive positioning.

Robustness-Based Approach for Slack Time Optimization in Tram Timetables

AbstractConsidering the unique interplay of trams with road traffic, this study explored the issue of instability in tram operations—a prominent medium-capacity rail transit. Our goal was to design a timetable slack time optimization method for scheduling slack time to improve the stability of tram operations. To facilitate this, we derived the travel/dwelling time distribution from historical data, which assisted in estimating interference times and evaluating the requisite slack time. We then developed an integer programming model to calculate both the punctuality rate and expected delay under varying travel times, enabling the creation of alternative slack time schemes. Using a unique tram operation simulation logic, we assessed the operational efficiency and reliability of these alternate schemes based on specific operational indicators. The results suggest that our novel approach to timetable optimization significantly enhances the tram’s adaptability to disruptions, directly improving the passenger experience and tram competitiveness. This work offers a robust framework for timetable optimization for semi-independent right-of-way public transportation.

A novel method for reducing the effect of doppler frequency shift in high-speed railway mobile communication using machine learning

Currently, high-speed railway systems are rapidly expanding worldwide, necessitating reliable and efficient mobile communication solutions. However, the Doppler frequency shift caused by the high speeds of trains presents significant challenges to communication systems, particularly those using OFDM in LTE. This paper presents a novel for Doppler frequency compensation in high-speed railway communication based on the results of estimating the train's velocity using machine learning algorithms. By leveraging advanced algorithm such as neural networks, our method dynamically predicts and compensates for Doppler shifts in real-time. In this proposed novel, the Doppler frequency value is calculated based on the actual train’s velocity and the scenario of a high-speed railway, then the Doppler frequency is used to compensate the carrier frequency offset (CFO) directly at the Access Point (AP) device on the train. We conduct simulations to evaluate the effectiveness of our proposed solution in a high-speed railway scenario. The results demonstrate a marked improvement in communication reliability and data integrity, highlighting the potential of machine learning to enhance the performance of mobile communication systems in high-speed railways. The results of the proposed model are evaluated based on the system’s bit error rate BER after the CFO compensation decreases and the ratio of average energy per bit (Eb) to noise power density (N0) (Eb/N0) increases. This shows that the proposed solution works effectively and reduces the system’s bit errors while improving the communication performance. This study opens new avenues for integrating intelligent systems in transportation networks, ensuring seamless connectivity, and improving passenger experience

Industry 4.0 for passenger railway companies: A maturity model proposal for technology management

The railway sector is a relevant segment for the transportation of people and goods, and its efficiency and sustainability are crucial for fostering economic development and minimizing environmental impact. This research proposes an Industry 4.0 maturity model for passenger railway companies to manage emerging technologies, aiming to enhance them holistically to leverage the internal and external business dimensions. An exploratory and qualitative approach was employed, involving semi-structured interviews with experts in Brazilian railway transport. Based on the opportunities and Key Performance Indicators identified within the sector, we developed an Industry 4.0 maturity model for companies and subsequently tested it in collaboration with a transport operator. The findings suggest that the proposed Industry 4.0 maturity model can effectively guide practitioners in applying advanced technologies for robust and efficient train operations, prescriptive maintenance, strong supply chain management, and improved passenger experience and worker performance. This research provides a noteworthy and substantial contribution by introducing unprecedented frameworks that offer a holistic view of Industry 4.0 in the context of passenger railways. The study's practical impact is aiding passenger railway companies to navigate their Industry 4.0 journey. Academically, the research contributes to advancing the holistic understanding of Industry 4.0 as an ongoing phenomenon, enriching the academic discourse by discussing published works and presenting empirical data from railway companies.

How IGA Istanbul Airport leverages IoT and automation for improved efficiency, safety and passenger experience

iGA Istanbul Airport is the first and only airport established with a wireless Internet of Things (IoT). IoT systems offer an effective solution for receiving data from many points with advantages such as fast implementation, low installation costs and long lifetime. In addition to standard products, special wireless IoT sensors designed for specific needs are also used in iGA Istanbul Airport. This infrastructure provides data for the execution, improvement and development of airport processes. The big data and analysis application created with the data collected from IoT devices and system integrations manages efficiency and predictive maintenance activities. With the effective use of IoT systems, iGA Istanbul Airport has achieved significant gains in increasing customer satisfaction, managing predictive maintenance from a more proactive perspective, reducing environmental impacts and increasing operational efficiency. This paper discusses the use of the IoT infrastructure at iGA Istanbul Airport and the benefits it provides.