The Relationship between Air Travel Service Quality and Factors of Theory of Planned Behavior: Evidence from Low-Cost Airlines in Thailand

Despite an increased emphasis on improvement in airline service quality concerning consumer behavior, such as passenger repurchasing as a result of their behavioral intention over the last several decades, there is still much less concern with the nature of airline service quality than should exist in the so-called "logistics service quality” and less concern with examining the specific behavioral intention preceding repurchasing behavior together with the theory of planned behavior. As such, this study aims to explore these issues, along with the psychological factors of the theory of planned behavior, that can lead to repurchasing behavior via word-of-mouth intention (WOMI). With an online survey of 383 respondents experienced with flying, the results reveal that the logistics service quality and each determinant in the theory positively influence a passenger's repurchasing behavior through WOMI. Accordingly, service marketers can implement service design and apply integrated marketing communication by learning from repurchasing behavior that was formed by the given factors to retain their existing customers. Moreover, this study is the first to empirically and explicitly validate dimensions of airline services through the lens of logistics that are deemed fit with the nature of the airlines. It advances the understanding of theory approaching and connects what has hampered its advancement in a body of knowledge, simultaneously in a context of airline context where it should not be relegated to transportation and consumer and service orientation.

A Three-Stage Hybrid SEM-BN-ANN Approach for Analyzing Airport Service Quality

The novel coronavirus (COVID-19) outbreak has impacted the aviation industry worldwide. Several restrictions and regulations have been implemented to prevent the virus's spread and maintain airport operations. To recover the trustworthiness of air travelers in the new normality, improving airport service quality (ASQ) is necessary, ultimately increasing passenger satisfaction in airports. This research focuses on the relationship between passenger satisfaction and the ASQ dimensions of airports in Thailand. A three-stage analysis model was conducted by integrating structural equation modeling, Bayesian networks, and artificial neural networks to identify critical ASQ dimensions that highly impact overall satisfaction. The findings reveal that airport facilities, wayfinding, and security are three dominant dimensions influencing overall passenger satisfaction. This insight could help airport managers and operators recover passenger satisfaction, increase trustworthiness, and maintain the efficiency of the airports in not only this severe crisis but also in the new normality.

Areas within the United States at the Highest Risk for African Swine Fever, Classical Swine Fever, and Foot-and-Mouth Disease Introduction

Domestic livestock production is a major component of the agricultural sector, contributing to food security and human health and nutrition and serving as the economic livelihood for millions worldwide. The impact of disease on global systems and processes cannot be understated, as illustrated by the effects of the COVID-19 global pandemic through economic and social system shocks and food system disruptions. This study outlines a method to identify the most likely sites of introduction into the United States for three of the most concerning foreign animal diseases: African swine fever (ASF), classical swine fever (CSF), and foot-and-mouth disease (FMD). We first created an index measuring the amount of potentially contaminated meat products entering the regions of interest using the most recently available Agricultural Quarantine Inspection Monitoring (AQIM) air passenger inspection dataset, the AQIM USPS/foreign mail, and the targeted USPS/foreign mail interception datasets. The risk of introduction of a given virus was then estimated using this index, as well as the density of operations of the livestock species and the likelihood of infected material contaminating the local herds. Using the most recently available version of the datasets, the most likely places of introduction for ASF and CSF were identified to be in central Florida, while FMD was estimated to have been most likely introduced to swine in western California and to cattle in northeastern Texas. The method illustrated in this study is important as it may provide insights on risk and can be used to guide surveillance activities and optimize the use of limited resources to combat the establishment of these diseases in the U.S.

Draft of Public Rail Passenger Transport during the COVID-19 Pandemic

During the COVID-19 pandemic, the railway sector experienced a significant worldwide decrease in the number of passengers due to the reduced transportation capacity of trains introduced for limiting social contacts and passengers fears from the disease. The reduction in population mobility resulting from national anti-pandemic measures led to the fact that carriers in the Slovak Republic began to optimize and limit the rail transport performance. Several measures were also implemented to reduce the risk of the spread of the COVID-19 disease so that passengers feel safe while traveling by train. Globally, we are entering the third year of coronavirus, and the pandemic is expected to continue even this year. For this reason, forecasting passenger demand for rail transport is becoming increasingly important and it is necessary to take measures in public passenger transport that will consider the reduced mobility due to the COVID-19 pandemic. The paper deals with the proposal of a methodology for planning transport services on selected regional railway lines during the COVID-19 pandemic. © 2023 Lenka Cerna et al., published by Sciendo.

Tourist Behavior in the Cruise Industry Post-COVID-19: An Examination of Service Quality, Corporate Image, and Intentions to Pay and Revisit

The COVID-19 outbreak has had detrimental consequences on the cruise industry due to the suspension of commercial cruise trips, and these effects remain apparent in Saudi Arabia. The offered service quality (SQ) in the post-COVID-19 era seems to be a critical element for improving customer experiences and satisfaction, enhancing destination attractiveness, increasing revenue, and maintaining repeat business. The current study aimed to assess the impact of service quality on tourists' satisfaction and corporate image as well as the intention to pay for cruise trips and revisit the destination among 315 tourists in Saudi Arabia. Service quality was measured using five subscales of the SERVQUAL scale, including reliability, tangibles, responsiveness, assurance, and empathy. Tourists' satisfaction was significantly influenced by four domains of SQ, whereas the intention to pay more, intention to revisit the destination, and corporate image were significantly predicted by ≤3 domains of SQ. The study's findings can help the cruise industry to improve its offerings and create more personalized and engaging experiences that meet the changing needs of customers in the recovery period after the COVID-19 outbreak.

A New Big Data Approach to Understanding General Traffic Impacts on Bus Passenger Delays

This paper presents a new method to quantify the potential user time savings if the urban bus is given preferential treatment, changing from mixed traffic to an exclusive bus lane, using a big data approach. The main advantage of the proposal is the use of the high amount of information that is automatically collected by sensors and management systems in many different situations with a high degree of spatial and temporal detail. These data allow ready adjustment of calculations to the specific reality measured in each case. In this way, we propose a novel methodology of general application to estimate the potential passenger savings instead of using simulation or analytical methods already present in the literature. For that purpose, in the first place, a travel time prediction model per vehicle trip has been developed. It has been calibrated and validated with a historical series of observations in real-world situations. This model is based on multiple linear regression. The estimated bus delay is obtained by comparing the estimated bus travel time with the bus travel time under free-flow conditions. Finally, estimated bus passenger time savings would be obtained if an exclusive bus lane had been implemented. An estimation of the passenger's route in each vehicle trip is considered to avoid average value simplifications in this calculation. A case study is conducted in A Coruña, Spain, to prove the methodology's applicability. The results showed that 18.7% of the analyzed bus trips underwent a delay exceeding 3 min in a 2,448 m long corridor, and more than 33,000 h per year could have been saved with an exclusive bus lane. Understanding the impact of different factors on transit and the benefits of a priority bus system on passengers can help city councils and transit agencies to know which investments to prioritize given their limited budget.

Research on Affective Interaction in Mini Public Transport Based on IPA-FMEA

In the promotion of sustainable modes of transport, especially public transport, reasonable failure risk assessment at the critical moment in the process of service provider touch with users can improve the service quality to a certain extent. This study presents a product service touch point evaluation approach based on the importance–performance analysis (IPA) of user and failure mode and effect analysis (FMEA). Firstly, the authors capture service product service touch points in the process of user interaction with the product by observing the user behavior in a speculative design experiment, and perform the correlation analysis of the service product service touch point. Second, the authors use the IPA analysis method to evaluate and classify the product service touch points and identify the key product service touch points. Thirdly, the authors propose to analyze the failure of key product service touch points based on user-perceived affective interaction and clarify the priority of each key touch point. Finally, reluctant interpersonal communication, as the key failure caused by high risk, is derived according to the evaluation report, which leads to establishing new product service touch points and improving the overall user experience to promote sustainable transports with similar forms and characteristics.

A Comprehensive Analysis of Clustering Public Utility Bus Passenger's Behavior during the COVID-19 Pandemic: Utilization of Machine Learning with Metaheuristic Algorithm

Public utility bus (PUB) systems and passenger behaviors drastically changed during the COVID-19 pandemic. This study assessed the clustered behavior of 505 PUB passengers using feature selection, K-means clustering, and particle swarm optimization (PSO). The wrapper method was seen to be the best among the six feature selection techniques through recursive feature selection with a 90% training set and a 10% testing set. It was revealed that this technique produced 26 optimal feature subsets. These features were then fed into K-means clustering and PSO to find PUB passengers' clusters. The algorithm was tested using 12 different parameter settings to find the best outcome. As a result, the optimal parameter combination produced 23 clusters. Utilizing the Pareto analysis, the study only considered the vital clusters. Specifically, five vital clusters were found to have comprehensive similarities in demographics and feature responses. The PUB stakeholders could use the cluster findings as a benchmark to improve the current system.

Take-off, turbulence and turnaround

PurposeThe aim of this paper is to explore the evolving nature of the work of cabin crew in a Scandinavian carrier in three eras, drawing on theories of gender and emotional labour.Design/methodology/approachThe paper draws on ethnographic data from fieldwork, interviews and documents.FindingsFrom being a feminized and temporary occupation for young, upper- and middle-class women in the 1970s, the occupation became a full-time job and with greater diversity of cabin crew. Today there are signs of the job becoming a precarious and temporary one of demanding and devalorized work in a polarized and class-divided labour market. Changing circumstances impact on the emotional labour requirement and terms and conditions at work.Research limitations/implicationsA limitation is that the research design was not initially longitudinal in the sense that the author does not have exactly the same kind of data from each era. The author has, however, been involved in this field for two decades, used multiple methods and interacted with different stakeholders and drew on a unique data material.Practical implicationsThe development in aviation is contributing to new discriminatory practices, driving employee conditions downwards and changing the job demands. This development will have practical consequences for the lives and families of cabin crew.Social implicationsThe analysis illustrates how work ‘constructs' workers and contributes in creating jobs that are not sustainable for the employees. Intensification of work, insecurity and tougher working conditions also challenge key features in the Nordic model such as proper pay, decent work and a life-long employment. Much indicates that the profession is again becoming a temporary one of demanding work with poor working conditions in a polarized and class-divided labour market.Originality/valueThe research contributes to the literature on emotional labour, gender and the evolving nature of the work of cabin crew. The unique data material, the longitudinal aspect of the research and the focus on a single network carrier are good in charting changes over time.

Station-Level Effects of the COVID-19 Pandemic on Subway Ridership in the Seoul Metropolitan Area.

This paper investigates the station-level impacts of the coronavirus disease (COVID-19) pandemic on subway ridership in the Seoul Metropolitan Area. Spatial econometric models are constructed to examine the association between ridership reduction caused by the pandemic and station-level characteristics during the pandemic years 2020 and 2021. The results reveal unequal effects on station-level ridership, based on the pandemic waves, the demographics, and the economic features of pedestrian catchment areas. First, the subway system was severely disrupted by the pandemic, with significant decreases in ridership-by about 27% for each of the pandemic years-compared with the pre-pandemic year (2019). Second, the ridership reduction was sensitive to the three waves in 2020 and responded accordingly; however, it became less sensitive to the waves in 2021, indicating that subway usage was less responsive to pandemic waves during the second year of the pandemic. Third, pedestrian catchment areas with higher numbers of younger residents (in their 20s) and older residents (65 years and older), those with more businesses requiring face-to-face interactions with consumers, and stations located in the employment centers were hit the hardest in ridership reduction caused by the pandemic.

Bioprotection of Transportation and Facilities from SARS-CoV-2 (COVID-19).

The recent COVID-19 pandemic has led to a nearly world-wide shelter-in-place strategy. This raises several natural concerns about the safe relaxing of current restrictions. This article focuses on the design and operation of heating ventilation and air conditioning (HVAC) systems in the context of transportation. Do HVAC systems have a role in limiting viral spread? During shelter-in-place, can the HVAC system in a dwelling or a vehicle help limit spread of the virus? After the shelter-in-place strategy ends, can typical workplace and transportation HVAC systems limit spread of the virus? This article directly addresses these and other questions. In addition, it also summarizes simplifying assumptions needed to make meaningful predictions. This article derives new results using transform methods first given in Ginsberg and Bui. These new results describe viral spread through an HVAC system and estimate the aggregate dose of virus inhaled by an uninfected building or vehicle occupant when an infected occupant is present within the same building or vehicle. Central to these results is the derivation of a quantity called the "protection factor"-a term-of-art borrowed from the design of gas masks. Older results that rely on numerical approximations to these differential equations have long been lab validated. This article gives the exact solutions in fixed infrastructure for the first time. These solutions, therefore, retain the same lab validation of the older methods of approximation. Further, these exact solutions yield valuable insights into HVAC systems used in transportation.

U.S. network and low-cost carriers' performance in response to COVID-19: Strictness of government policies and passengers' panic

Coronavirus outbreak has been highly disruptive for aviation sector. There is strong correlation between COVID-19 related news, volatility in transportation, low confidence in travel safety, and uncertainty in this era. In this research, we study and distinguish the COVID-19's impact on U.S. airlines' performance. The network and low-cost carriers responded differently to it in terms of capacity reduction, market share reduction, scheduled flights reduction, flight cancellations, and service quality in the year 2020. We illustrate low-cost carrier had higher efficiency compared to network ones during pandemic by applying Network Data Envelopment Analysis. Furthermore, the effects of two key factors that emerge from COVID-19, the government's stringency actions and passengers' panic, on U.S. airlines efficiency are studied. Our analysis demonstrate that the negative effect is more significant for passengers' panic than it is for governments' stringency measures. In addition, we show that passengers' panic has more impact on the efficiency of network carriers compared to low-cost carrier.

Energy Sufficiency in the Passenger Transport of Lithuania

This paper aims to understand the significance of energy sufficiency (ES) in passenger transport for the long-term resolution of energy, climate, and sustainable development issues in Lithuania. It computes related indicators, by fixing the passenger-kilometres (pkm) travelled by various modes of transportation and applying a scenario analysis with the MESSAGE model. The findings indicated that the country's final energy consumption (FEC) in transportation could be reduced by 21.8% by 2050 due to slowing growth rate of distances travelled by passenger car but increasing use of public transport and bicycles. This would result in a decrease in the growth rate of primary energy consumption (PEC) by half (to 0.3% a year), an increase in the use of renewable energy sources (RES) to 67.2% in the PEC structure, savings of oil products by 6.4 TWh, and savings of new electricity generation capacity by 550 MW. Furthermore, 20 MtCO2eq. in greenhouse gas (GHG) emission reductions could be realised between 2021 and 2050. To take advantage of the potential of ES, the policy measures of passenger car demand containment and a shift to non-motorised and less polluting modes of transportation should be implemented. Furthermore, priority should be given to policy measures that encourage use of public transportation.

Estimating the number of undetected COVID-19 cases among travellers from mainland China [version 1, peer review: awaiting peer review]

Background: Since the start of the COVID-19 epidemic in late 2019, there have been more than 152 affected regions and countries with over 110,000 confirmed cases outside mainland China. Methods: We analysed COVID-19 cases among travellers from mainland China to different regions and countries, comparing the region- and country-specific rates of detected and confirmed cases per flight volume to estimate the relative sensitivity of surveillance in different regions and countries. Results: Although travel restrictions from Wuhan City and other cities across China may have reduced the absolute number of travellers to and from China, we estimated that more than two thirds (70%, 95% CI: 54% - 80%, compared to Singapore;75%, 95% CI: 66% - 82%, compared to multiple countries) of cases exported from mainland China have remained undetected. Conclusions: These undetected cases potentially resulted in multiple chains of human-to-human transmission outside mainland China.

Impact of COVID-19 restrictions on South African air transport and tourism indicators

Background: Air travel restrictions to prevent the spread of coronavirus disease 2019 (COVID-19) impacted air travel to and from and within South Africa significantly. The duration of the pandemic was more protracted than initially expected as new variants of the pandemic (in ‘waves') resulted in additional restrictions. Objectives: To determine the nature of COVID-19-related air travel restrictions, their impact on annual passenger demand, the number of flights operated (supply of services), the related average passenger loads carried as well as on tourism indicators of the direct contribution of travel and tourism, the total contribution to Gross Domestic Product (GDP) and employment. Method: The study identifies the number of passengers carried and flights operated and calculates the average passenger load per flight and trends. The impact on tourism indicators is based on the unit values of metrics published by the World Travel and Tourism Council for the 2019 calendar year, adapted for the reduction in passengers in the first and second years following the COVID-19 lockdown. Results: Significant decreases in the annual number of passengers carried, flights operated (in the three geographic areas), and their impact on tourism and employment indicators were identified. Conclusion: The decline in passengers exceeded the decrease in flights operated, which resulted in a decline in the average load of passengers carried per flight. The significance of COVID-19 restrictions on tourism indicators and employment was also calculated. Contribution: The study identifies the impact of COVID-19 air travel restrictions on both air transport and tourism indicators for South Africa.

Minimizing Energy Usage and Makespan of Elevator Operation in Rush Hour Using Multi-Objective Variable Neighborhood Strategy Adaptive Search with a Mobile Application

The purpose of this study is to address two major issues: (1) the spread of epidemics such as COVID-19 due to long waiting times caused by a large number of waiting for customers, and (2) excessive energy consumption resulting from the elevator patterns used by various customers. The first issue is addressed through the development of a mobile application, while the second issue is tackled by implementing two strategies: (1) determining optimal stopping strategies for elevators based on registered passengers and (2) assigning passengers to elevators in a way that minimizes the number of floors the elevators need to stop at. The mobile application serves as an input parameter for the optimization toolbox, which employs the exact method and multi-objective variable neighborhood strategy adaptive search (M-VaNSAS) to find the optimal plan for passenger assignment and elevator scheduling. The proposed method, which adopts an even-odd floor strategy, outperforms the currently practiced procedure and leads to a 42.44% reduction in waiting time and a 29.61% reduction in energy consumption. Computational results confirmed the effectiveness of the proposed approach.

A Model Statistical during Covid-19 Future E-Commerce Revenue for Indonesia Aviation

Until today, Information Technology (IT) has been felt by aviation industry showed by positive growth of operating revenue before Covid-19 pandemic. The pandemic of Covid-19 changes the world especially the aviation industry by slowing down the business transaction. This study presents statistical model on recent e-commerce revenue of aviation, the number of passengers and the IT investments then predicts future of e-commerce revenue, the number of passengers and the IT spending using Neural Networks. This method is useful to predict the future because it follows the time being. The chosen variables are intended whether IT has an impact during the pandemic for passenger generation year by year. The results show that for the next few years, the revenue, the number of passengers and the IT spending are significantly increasing, while there are problems faced in aviation industry because of Covid-19. This model also can be applied for other industry.

AIR PASSENGER RIGHTS IN TIMES OF PANDEMIC BETWEEN EXTRAORDINARY CANCELLATIONS, DENIED REIMBURSEMENTS AND FORCED VOUCHERS

The Covid-19 pandemic has taken its toll on air transport, forcing many airlines to cancel flights as a result of the restrictive measures adopted by the authorities or due to other reasons related to the emergency. The remedies, stemming from EU law, of ticket refunds and compensation for damages may expose carriers to serious liquidity crises and bankruptcy. The aim of this article is to discuss the opportunity to provide for compulsory vouchers in lieu of immediate reimbursement, which passengers could not refuse on condition that they have a reasonable content, with a view to enhancing competition in the European air transport market. © 2022 Ibero-American Law Institute. All rights reserved.

An Analysis Air Traffic Prediction during a Pandemic

Air transportation during the covid-19 pandemic experienced a very drastic decline. The decrease in the number of passengers was caused by national and international restrictions. The troublesome administration makes passengers discouraged from traveling using Air transportation. Based on the National Statistics Agency, air transportation experienced a decline from early 2020 to 2021. This study focuses on air traffic predictions, namely the number of aircraft passengers during the COVID-19 pandemic at Indonesia's main airports, namely Kuala Namu, Sukarno Hatta, and Juanda airports., Ngurah Rai and Hasanuddin. The method used to predict the number of airplane passengers during a pandemic is the backpropagation algorithm using the Fletcher Reeves method. © 2022 IEEE.

Impact of COVID-19 Prevention and Control Measures on Expressway Transportation in Guangdong-Hong Kong-Macao Greater Bay Area

Under the background of normalized COVID-19 prevention and control, regional epidemics occur frequently in China. How to quantify the impact of COVID-19 prevention and control measures on economic operation and passenger and freight transportation has become an urgent problem. To this end, we design a calculation method for expressway transportation indicators, propose the level and stage division process of COVID-19 prevention and control measures, and then establish a difference-in-difference model to further analyze their impact on expressway transportation indicators. Taking major cities in the Guangdong-Hong Kong-Macao Greater Bay Area as an example, case studies are conducted based on the expressway toll data and COVID-19 prevention and control information from May 2020 to April 2022. The results show that in the level I (strengthened) stage, the passenger vehicle flow has dropped significantly, the drop in each case is between 8% and 27%, and the freight indicators have not changed significantly. In Shenzhen and Dongguan, both passenger and freight indicators dropped sharply in the level II (strict) stage. Passenger vehicle flow in the two cities dropped by 46.3% and 33.7%, and truck flow by 42.7% and 27.6%, respectively, and cargo and turnover decreased as much as truck flow. The average inter- city distance of expressway passenger cars has a downward trend under the level I stage, but under the level II stage, the average inter-city distance of passenger cars and trucks has increased significantly. This study can provide a certain reference value for the formulation and implementation of COVID-19 prevention and control measures in cities and urban agglomerations. © 2022 Science Press. All rights reserved.