The COVID-19 pandemic has caused a dramatic reshaping of passenger risk perception for airline industry. The sharp increase in risk aversion by air passenger has caused a disastrous impact on the tourism service industry, particularly airline industry. Although the existing literature has provided a lot of studies on the impact of the pandemic on travel industry, there are very few studies discussing the impact of change in passenger risk perception on the stock market performance of airline industry. This study considers two types of airline companies, full-service and low-cost. In order to overcome the traditional problem of the Chow test, Quandt-Andrews test is used to identify structural change points during the pandemic in the stock prices of United States airline companies. The result shows that an industry-wide structural change in the stock market performance indeed is found to take place during the pandemic for United States airline companies. Meanwhile, no significant difference is found in the structural change date between the two types of airline companies. The selected airline companies are found to be clustered toward the end of 2020 (November and December) in their structural change dates. Although the strike of the COVID-19 pandemic on airline industry has proven to be widespread and profound, our investigation implies that air passengers have gradually adapted to the new normal of travel activities at some level and partly rebuild their sense of safety under the strict epidemic-control measures.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8764145PMC
http://dx.doi.org/10.3389/fpsyg.2021.795940DOI Listing

Publication Analysis

Top Keywords

airline industry
20
airline companies
20
structural change
16
passenger risk
12
risk perception
12
covid-19 pandemic
12
united states
12
stock market
12
airline
10
pandemic airline
8

Similar Publications

Jet fuel plays a crucial role as an essential energy source in aerospace and aviation operations. The recent increase in fuel prices has presented airlines with the new challenge of managing jet fuel costs to ensure consistent cash flow and minimize operational uncertainties. The conventional risk prediction models used by airlines often assume that risks are normally distributed according to the classical Central Limit Theorem, which can lead to under-hedging.

View Article and Find Full Text PDF

Sleep tracking by consumers is becoming increasingly prevalent; yet, few studies have evaluated the accuracy of such devices. We sought to evaluate the accuracy of three devices (Oura Ring Gen3, Fitbit Sense 2, and Apple Watch Series 8) compared to the gold standard sleep assessment (polysomnography (PSG)). Thirty-five participants (aged 20-50 years) without a sleep disorder were enrolled in a single-night inpatient study, during which they wore the Oura Ring, Fitbit, and Apple Watch, and were monitored with PSG.

View Article and Find Full Text PDF

Forecasting air passenger traffic and market share using deep neural networks with multiple inputs and outputs.

Front Artif Intell

October 2024

School of Business, Department of Management, SUNY-Farmingdale, Farmingdale, NY, United States.

Introduction: In this study, we address the challenge of accurate time series forecasting of air passenger demand using historical market demand data from the U.S. commercial aviation industry in the 21st century.

View Article and Find Full Text PDF

Background: Work-related stress is a critical area of research in civil aviation, given the potential for severe consequences when airline pilots (APs) are overwhelmed or unable to perform optimally. While pilots are traditionally considered to be exposed to various stressors, the impact of specific occupational characteristics on stress in the aviation industry remains inadequately understood. Considering that biomarkers are increasingly being utilized as objective measures of stress in human research, this cross-sectional study investigated the association between occupational variables and serum levels of cortisol and dehydroepiandrosterone sulfate (DHEAS) as stress biomarkers in commercial APs.

View Article and Find Full Text PDF
Article Synopsis
  • * Improvements include architectural changes, attention mechanisms, multiscale feature extraction, and better optimization algorithms to boost accuracy and efficiency in complex environments.
  • * Experimental results demonstrate that the new model significantly outperforms existing models, achieving high accuracy (0.942), precision (0.967), recall (0.951), and F1-score (0.934), along with superior prediction stability and adaptability.
View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!