Eastern Airlines Research Articles

Investigation of the Crash Process of China Eastern Airlines Flight MU5735 Based on Seismic Data

Abstract Investigating aircraft accidents is a critical and challenging endeavor in the field of aviation safety. Current practices in seismology-based air accident investigations focus on locating crash sites to aid in the search and recovery of missing aircraft. In this study, we conducted an analysis of the China Eastern Airlines Boeing 737–800 crash on 21 March 2022, by leveraging three-component seismic records acquired from a location 21 km away from the crash site, in conjunction with publicly available radar data from Flightradar24 (an online service). Our approach helps to reconstruct the flight state of the aircraft at the time of the impact by modeling the dynamics of the impact with the Earth’s surface. Through an inversion process, we successfully obtained the force–time function and determined the direction of the impact force. In addition, we conducted inquiries into the weight of the 737–800 airliner, which enabled us to estimate the speed of the aircraft at the time of the accident to be about 200–264 m/s using the momentum theorem. These results are in agreement with time of the last radar signal and the measured dive angle of the airplane, providing valuable insights into the circumstances surrounding the crash.

Analysis of China Eastern Airlines Financial Statements Based on Harvard Analysis Framework

The financial analysis method adopted in this paper refers to the analysis method in the "Harvard Analytical Framework System". Through the business strategy of the enterprise, the accounting policies adopted, the analysis of the company's finances and the analysis of the company's prospects, etc. The business situation, financial situation and development situation were analyzed and elaborated.This paper takes China Eastern Airlines' financial statements as an example, combines the characteristics of the air transport industry, analyzes the company's financial status, operating results and cash flow, and systematically evaluates the company's past and present operating results and financial status, and judges the company accordingly investment value.

Research on the Strategy of Using Option Hedging by China Eastern Airlines

Research on the Strategy of Using Option Hedging by China Eastern Airlines

Learning from Mistakes: A Thematic Analysis of Flight 401's Situational Awareness Lapses

Situational awareness is a fundamental pillar in aviation, essential for safety, operational efficiency, and crew training. This study focuses on the tragedy of Eastern Airlines Flight 401 as a case study to illustrate the importance of effective communication and Crew Resource Management (CRM) in preventing accidents. Through thematic analysis, the research reveals how pilot distractions, cockpit instrument malfunctions, and communication failures in critical conditions contributed to the accident. The findings indicate that comprehensive training that integrally incorporates technological aspects and human factors, as well as an emphasis on effective CRM, is crucial. Practical implications of this research include the development of training modules aimed at enhancing interactive and collaborative communication among crew members. The study also recommends future research focus on aviation technology, air traffic control dynamics, and human-machine interactions, with the goal of deepening understanding of situational awareness dynamics and advancing aviation safety practices. These findings are expected to make a significant contribution to the literature on situational awareness and aviation safety practices.

Analysis of the Key Factors of User Behavior Measurement in Unexpected Events based on Feature Extraction and Selection

Artificial intelligence is important for people’s daily life. In recent years, short video platforms have risen rapidly, and TikTok APP is one of the most outstanding among them. AI tools are applied to support their big data recommendation algorithm. In the era in which everyone is using the Internet, the public can often find the reflection of all kinds of attitudes and behaviors when unexpected events occur, and this influence will inevitably become more and more important as well as draw more and more attention. Therefore, taking the key factors of the user's behavior on the TikTok platform as the research object, this thesis takes “3.21 China Eastern Airlines Passenger Plane Accident” event as the background to extend the topic. Then, the existing data of TikTok platform such as Cicada Mama is used to capture and analyze the key factors of users’ behavior in the backdrop of unexpected events, such as user attention, user influence, the heat of the event itself. Next, according to AI methods of statistics-related data, the calculation method for each factor is proposed. Finally, the analytic hierarchy process is used to establish the method of key factor measurement, to analyze the weight of each factor in the emergency.

Photography and Destination Image: An Analysis of China Eastern Airline Facebook Photographs

ABSTRACT The main purpose of this study is to explore the projected destination image represented by photographs emerging in social media from a potential DMO member. The official page of China Eastern Airlines on Facebook (@CEAir) was selected as a case study, in which a total of 40 photographs were collected and classified into five groups according to their themes. To identify the destination image of China, five groups of photographs were analyzed by using visual analysis, semiotic analysis, and multimodal discourse analysis. The main findings show that Chinese food, architecture, natural landscape, people, and ethnic minorities are common signs engaging in constructing the destination image of China. These photographs mainly adopted wide shots and brilliant color tones, which convey to overseas tourists that China is a great power with a long history, full of charm, and a contributor to global development. More importantly, not only landscape photography but also still life photography, candid photography, and travel photography are all considered to be modes of representation of the destination image. Different genres of photography employ Chinese culture as a special gaze to shape the destination image.

A sentiment analysis and dual trust relationship-based approach to large-scale group decision-making for online reviews: A case study of China Eastern Airlines

With the rapid development of e-commerce, more and more people are willing to post their reviews and opinions about the products they buy online. Therefore, the use of online review data for decision-making appears to be more practical and universal, and how to effectively use this kind of data to support large-scale group decision-making (LSGDM) is a worthy research direction. In this paper, we firstly use sentiment analysis to analyze online review data to derive the decision maker's (DM's) sentiment value, and apply the sentiment value to construct a social network based on a dual trust relationship, which considers both familiarity-based trust and similarity-based trust. Secondly, a directed Louvain clustering algorithm in light of dual trust relationships and a method for solving the DM's intra-group weights and the group's weights are proposed based on this network. A two-stage clustering based consensus model in light of dual trust relationships is then proposed, in which the DMs in the agreement cluster can communicate with other DMs outside of such a cluster and dynamically update the grouping using the clustering algorithm. Finally, the practicality and effectiveness of the LSGDM method proposed in this paper are verified through a real case.

A classification and recognition algorithm of key figures in public opinion integrating multidimensional similarity and K-shell based on supernetwork

In online public opinion events, key figures are crucial to the formation and diffusion of public opinion, to the evolution and dissemination of topics, and to the guidance and transformation of the direction of public opinion. Based on the four-dimensional public opinion communication supernetwork (social-psychology-opinion-convergent), this study proposes a classification and recognition algorithm of key figures in online public opinion that integrates multidimensional similarity and K-shell to identify the key figures with differentiation in online public opinion events. The research finds that the evolutionary process of public opinion events is the joint action of key figures with different roles. The opinion leader is the key figure in the global communication of public opinion. The focus figure is the core figure that promotes the dissemination of public opinion on local subnetworks. The communication figure is the “bridge” node in the cross-regional communication of public opinion. Through the algorithm verification of the case “China Eastern Airlines Passenger Plane Crash Event”, we find that the algorithm proposed in this paper has advantages in feasibility, sensitivity, and effectiveness, compared with traditional algorithms such as CI, forwarding volume, degree centrality, K-shell, and multidimensional similarity. The classification and recognition algorithm proposed in this study can not only identify multirole key figures simultaneously but also improve the recognition granularity and eliminate the interference of core-like nodes.

Competing with Low Cost Carrier in a Sustainable Environment: Airline Ticket Pricing, Carbon Trading, and Market Power Structure

As the aviation industry embraces the carbon trading market, the competition between full-service carriers and low-cost carriers in ticket pricing is becoming more complicated and worth studying. To this end, we introduce carbon trading into game theoretical models under different market power structures and use real data from China Eastern Airlines and Spring Airlines on the route from Sanya to Shanghai to study this problem. This differs from the existing literature as empirical research is mainly used in this field. Our main results show that the disparity in market power (Stackelberg game) alleviates competition intensity under carbon trading and leads to higher equilibrium prices than in the Nash game model. Meanwhile, even when the two airlines have similar market power, Spring Airlines still has incentives to voluntarily act as a follower of China Eastern Airlines instead of maintaining equal market power with China Eastern Airlines. Under mild regulation, the uplift of carbon prices promotes higher equilibrium prices and supports larger profits. For the sake of consumer welfare, this suggests that the regulation department should impose stricter regulations and grant subsidies to motivate the airlines to mitigate emissions by introducing clean technologies.

Sentiment-topic dynamic collaborative analysis-based public opinion mapping in aviation disaster management: A case study of the MU5735 air crash

In the new media era, public opinion guidance for major emergencies is significant for enhancing social governance capabilities and ensuring social stability. Constructing a public opinion map based on sentiment-topic dynamic collaborative analysis can serve as a valuable reference for government-led public opinion guidance. This paper firstly develops a sentiment dictionary for major disaster events to aid in recognizing netizen emotions and uses a relevance formula-based Latent Dirichlet Allocation (LDA) model to conduct topic text mining. Then, through the division of public opinion cycles and different methods-based topic classification, sentiment-topic dynamic collaborative analysis is performed to create a visual public opinion map. By examining the case of the China Eastern Airlines MU5735 crash, the results indicate a close relationship between netizens’ sentiments and the topic content, primarily influenced by mainstream media news reports during different stages of public opinion. Furthermore, it is find that certain key node events can trigger emotional resonance among the masses during different stages of the public opinion cycle, resulting in completely different sentiments such as “sorrow”, “good” and “anger” for different topics. The visual public opinion map generated in this study offers valuable insights for the public opinion guidance and supervision of related disaster events. Simultaneously, it can also help identify and understand potential public opinion risks of disaster events, such as the spread of rumors and the amplification of panic. This provides both researchers and government administrators with a comprehensive and intuitive tool to better understand public opinion and effectively mitigate the public opinion risks associated with disaster events, thus safeguarding public safety and interests.

Carbon Emission Intensity and Its Abatement Choices: A Case of China Eastern

Air transportation, which is a derived demand, is booming following the rapid development of the world economy, and carbon emissions from the air transportation industry, which takes fossil fuels as its main energy source, have been increasing. Therefore, with global warming attracting considerable attention, the issue of how to reduce carbon emissions from air transportation has become a hot issue. We take China Eastern Airlines Corporation Limited (China Eastern) as an example to analyze the main factors influencing airlines’ carbon emissions, specifically around the impact of airline internal operating indicators, such as available seat kilometers (ASK), passenger load factor (PLF), fuel consumption per unit passenger kilometer, the average age of operated aircraft, on-time performance (OTP), etc. This paper uses a correlation analysis, panel regression analysis, and other ways to explore the influence mechanism of the above factors on carbon emission intensity. The conclusions for China Eastern are the following: first, PLF has a significant negative relationship with carbon emission intensity; second, fuel consumption per passenger kilometer has a significant negative relationship with carbon emission intensity. Third, OTP has a significant positive relationship with carbon emission intensity. Fourth, fleet size has a significant positive relationship with carbon emission intensity. Finally, we propose several targeted carbon abatement measures for China Eastern, such as improving PLF and OTP, reducing fuel consumption per unit passenger kilometer, speeding up fleet renewal, etc.

Financial Analysis on Air China Limited

The outbreak of COVID-19 has caused a significant decline in the aviation service industry's operating conditions due to the decrease in people's travel volume. This study conducts a fundamental performance analysis of Air China, in comparison with China Southern and China Eastern Airlines, using critical accounting analysis and data disclosed in the 2021 annual financial statements. The analysis includes liquidity, solvency, efficiency, and return on investments, providing a measurement of the potential of Air China in the Chinese civil aviation industry in the post-pandemic era. The study provides suggestions for investors based on the value of Air China. The results of the analysis show that Air China has maintained good liquidity with a current ratio of 0.51, indicating that the company can meet its short-term liabilities. Solvency analysis indicates that the company has a debt-to-equity ratio of 1.05, which is lower than China Southern and China Eastern Airlines, indicating that Air China has less financial risk. The efficiency analysis shows that Air China has a better asset turnover ratio than its peers, indicating better management of its assets. Return on investment analysis indicates that Air China has a better return on equity than other two competitors, indicating a higher potential for investor returns. Overall, the study suggests that Air China has the potential to perform well in the Chinese civil aviation industry in the post-pandemic era. Investors should consider Air China as a viable investment option, given its good liquidity, solvency, efficiency, and return on investment.

The Environmental Impact on the Airline Industry and Financial Analysis of Air China, China Southern Airlines, and China Eastern Airlines

This paper presents a comprehensive overview of the environmental impact on the airline industry, focusing on three of China's largest airlines - Air China, China Southern Airlines, and China Eastern Airlines. It provides a financial analysis of these airlines using the Capital Asset Pricing Model (CAPM). It includes a literature review to underline the importance of environmental factors on the industry and its financial performance. Scrutinizes the reciprocal relationship between the environment and the airline industry, focusing on how environmental factors influence the industry. The study involves reviewing the literature on physical environmental factors, policy-related factors, and the industry's response to these influences. The objective is to comprehensively understand the ecological impacts on the industry and the consequent strategic adjustments and technological innovations being undertaken.

Stock Price Prediction based on LSTM and XGBoost Combination Model

In recent years, many machine learning and deep learning algorithms have been applied to stock prediction, providing a reference basis for stock trading, and LSTM neural network and XGBoost algorithm are two typical representatives, each with advantages and disadvantages in prediction. In view of this, we propose a combination model based on LSTM and XGBoost, which combines the advantages of LSTM in processing time series data and the ability of XGBoost to evaluate the importance of features. The combination model first selects feature variables with high importance through XGBoost, performs data dimensionality reduction, and then uses LSTM to make predictions. In order to verify the feasibility of the combination model, we built XGBoost, LSTM and LSTM-XGBoost models, and carried out experiments on three data sets of China Eastern Airlines, China Merchants Bank and Kweichow Moutai respectively. Finally, we concluded that the proposed LSTM-XGBoost model has good feasibility and universality in stock price prediction by comparing the accuracy of the predicted images and their performance in RMSE, RMAE, and MAPE indicators.

A Comparative Study on Debt Risks of Chinese Civil Aviation Companies Under the Covid-19 Epidemic

As a highly indebted industry, the civil aviation transportation industry's debt risk management is crucial to its everyday operations. After the emergence of COVID-19 in early 2020, a number of airlines have been adversely affected by variables such as a reduction in the number of passengers, and their operating revenue has been severely impacted, with some even facing the possibility of insolvency. How to control the size and risk of debt is particularly crucial when income is low. On the basis of empirical analysis, this paper collects and sorts the financial data of three large state-owned civil aviation enterprises (China Southern Airlines, Air China, and China Eastern Airlines), selects several debt risk measurement indicators to analyse the impact of the epidemic on the debt risk of civil aviation enterprises, and offers corresponding recommendations for the management of airline debt risk.

Clear-Air Turbulence (CAT) Encounters on 13 November 2019 over Central and Eastern China: Numerical Simulation and Generation Mechanism

Abstract On 13 November 2019, seven commercial aircraft of China Eastern Airlines encountered nine severe-or-greater clear-air turbulence (CAT) events over central and eastern China within 12 h (0000–1200 UTC). These events mainly occurred at altitudes between 6.0 and 6.7 km. A high-resolution nested numerical simulation is carried out using the Weather Research and Forecasting (WRF) Model to investigate the generation mechanism of these CAT events, with a horizontal resolution of 1 km over the inner domain. In addition, seven CAT diagnostics with outstanding performances are employed for the mechanism analysis. The WRF Model can reasonably reproduce both synoptic-scale systems (Siberian high and upper-level jet stream) and local vertical structures (temperature, dewpoint temperature, and wind field). The simulation indicates that an upper-level front–jet system with a remarkable meridional temperature gradient intensifies over central and eastern China, with the maximum wind speed increasing from 59.0 to 67.3 m s−1. The intensification of the front–jet system induces the tropopause folding, and nine localized CAT events occur in the region with large vertical wind shear (VWS) (1.55 × 10−2–2.53 × 10−2 s−1) and small Richardson numbers (Ri) (0.42–0.85) below the cyclonic side of the jet stream. Diagnostic analysis reveals that Kelvin–Helmholtz instability plays an important role in CAT generation, while convective and inertial instability is not directly associated with CAT generation in this study. A typical flight case with continuous CAT events also suggests that large VWS (greater than 1.3 × 10−2 s−1) accompanied with small Ri (less than 1) favors CAT generation in a front–jet system environment. Significance Statement A high-resolution nested numerical simulation is carried out using the Weather Research and Forecasting (WRF) Model to investigate the generation mechanism of nine severe-or-greater clear-air turbulence (CAT) events over central and eastern China. Intensification of a front–jet system induces tropopause folding, and nine CAT events occur in the region with large vertical wind shear (greater than 1.55 × 10−2 s−1) and small Richardson numbers (less than 0.85) below the cyclonic side of the jet stream. Kelvin–Helmholtz instability plays an important role in the CAT generation, rather than convective and inertial instability.

Fundamental pricing analysis of temperature related stalling derivatives of aerospace fibers

Telecommunication has experienced a lot of explosion in bandwidth because of its capacity to transmit large data. Though, there are several cogent benefits, there are also prices like temperature rise during life-threatening events. Recent tragedy of China Eastern Airlines Boeing 737-800 plane that killed 133 passengers on board is a price of poor aerospace communication. The cut-off communication during stalling is connected with temperature rise in the OFT used without loss of generality. This article presents an OFT called the OWTOF with higher-than-expected temperature resistance especially when the lunch power increases the temperature at fusion point. Numerical approximation shows that the OWTOF is a significant improvement of the WTOF implying that real-time OWTOF could be the solution of stalling without loss of quality and speed.

Sensor fault analysis of aero-engine using ensemble SCNN and Bayesian interval estimation

Sensors of an aircraft engine have the problems of multiple kinds of faults and difficulty to diagnose. Moreover, the diagnosis performance cannot meet practical demands. Therefore, this paper proposes a novel approach for sensor fault diagnosis integrating the advantages of selective ensemble learning, siamese convolutional neural network (SCNN), and Bayesian interval estimation (BIE). The Bayesian interval estimation with hypothesis testing is developed with real-time data update to reduce the confidence interval. The attention mechanism is introduced to enhance fault diagnosis performance. Moreover, ensemble selection learning with Akaike information criteria is proposed to obtain optimal SCNNs. The theorems of convergence and optimal confidence data in ensemble learning are proven. Furthermore, this paper develops a novel improved learning algorithm based on AdaMod (Adaptive and momental bound method) and SGD (stochastic gradient descent), and achieves a new fault diagnosis algorithm to improve the diagnosis performance. The sensor data of aircraft engines from China Eastern Airlines is adopted for validation and experimental results show that proposed approach reaches an excellent tradeoff between sensor diagnosis performance, confidence interval, and runtime. The ablation studies are performed to analyze the role of leaner’s components. The proposed method improves training accuracy by 6.2%, fault diagnosis performance by 5.1%, fault prediction mean result by 4.6%, and fault prediction variance is reduced by 38.1% than the state-of-the-art methods.

Analyzing the Financial Risks and Investment Values of Chinese Airline Companies

This paper aims to examine the financial risks faced by Chinese airline companies and provide useful information to investors who are interested in investing in these firms. The study will conduct valuations on the three largest airline companies in China, namely China Southern Airlines, Air China, and China Eastern Airlines, and assess the differences in the financial risks taken by these companies. The methodology used will be the Capital Asset Pricing Model (CAPM) and the metric of beta, which is used to assess the volatility of a stock or portfolio compared to the entire market. The paper provides a literature review of related research on the use of beta, risk factor models, and other financial measures to evaluate the performance and risk profile of firms in various industries. The study aims to contribute to the existing knowledge of the financial risks of airline companies and their potential impact on investor decisions.

The influence of safety-specific transformational leadership on safety behavior among Chinese airline pilots: The role of harmonious safety passion and organizational identification

Safety is a key consideration in the worldwide civil aviation industry, in which an increasing number of aviation accidents are related to flight crew performance. Based on social exchange theory and social identity theory, the primary objective of this study is to examine the relationships among safety-specific transformational leadership, harmonious safety passion, organizational identification, and safety behavior among Chinese airline pilots. Data was collected from 332 commercial airline pilots from China Eastern Airlines Co., Ltd. using self-report questionnaires. Correlation analysis, mediation analysis and moderated analysis were conducted. The results show that safety-specific transformational leadership has a positive effect on safety behavior and an indirect effect on safety behavior through the influence of harmonious safety passion. Harmonious safety passion acts as a mediating role, whereas organizational identification acts as a moderating role in the relationship between safety-specific transformational leadership and safety behavior. The managerial implications stemming from the findings of this study may promote pilots’ safety behavior, improve airline management and maintain safety of flight operation.