Civil Aviation Customer Satisfaction Automatic Evaluation System

In 2021, the airline industry was affected by COVID-19, and many airlines suffered losses. The main reason for the loss were the decline in revenue and the surge in costs. Therefore, in terms of creating the competitive advantage of airlines, "price war" is no longer applicable, and improving service quality has become an effective means. Customer satisfaction is the most effective indicator to measure service quality. In this study, a satisfaction evaluation system is established based on structural equation model and customer satisfaction importance matrix. Then, a questionnaire is designed to analyze the influence of different factors on customer satisfaction. The research finds that brand image and perceived quality have a great impact on customer satisfaction. In addition, some suggestions for airlines to improve customer satisfaction are given. © 2023 SPIE.

Tourism Development in Sub-Sahara Africa and Impact on Regional Airline Business Models

Tourism in Africa has experienced not only strong growth in terms of arrivals, but also in terms of expenditures and revenues and this has been driven primarily by a high number of international arrivals. The chapter examines some of Africa's high growth tourism markets with the largest international tourism receipts and compounded growth of approximately 6% per year. The chapter examines the multiple types of tourism and its economic benefit in terms of supporting national gross domestic product (GDP) growth. Tourism should be developed for its potential to enhance economies. Important aspects amongst tourism's benefits are that;it boosts economic regeneration;it offers a future, meaning that it holds out a promise for growth;it is one of the fastest growing economic activities;and it is a key driver towards economic growth. The tourism industry can provide considerable benefits to host communities through economic development, infrastructures development and as a medium for protecting the environment and culture. The chapter concludes by examining the future growth of the aviation industry, discusses international regulations and how this will affect tourism within the African region. The impact of COVID-19 on the tourism sector is revisited and discusses the overall impact on the travel and tourism industry. Finally, analysis on climate and environment is discussed and the International Civil Aviation Organization provides recommendations for the air transport industry to combat climate change and reduce carbon dioxide (CO2) emissions. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Stress Factors and the Impacts of COVID-19 Pandemic: A Review on the Aviation Industry

This study outlines the stress factors and the impact of the COVID-19 pandemic on the stress variables among aviation workers, which includes airline employees, flight crews, pilots, maintenance crews, air traffic controllers, airport or ground workers, engineers, training personnel, and other aviation-related personnel. A review was done on 37 research papers using systematic literature review (SLR) and discovered nine stress factors among aviation workers which are working hours, workloads, internal factors, ergonomic issues, job uncertainty, job demands, organizational issues, team conflict, and the COVID-19 itself. The findings of this study could provide insights to employers in the aviation industry for mitigation actions that could help to successfully reduce and eliminate stress factors in the workplace. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

The impact of security oversight on air cargo price and demand

This paper examines the effect of security oversight on air cargo price and demand. We exploit variations in security oversight instituted by the International Civil Aviation Organization (ICAO). We estimate a simultaneous equation model using proprietary operations data from a major airline in South Korea over the period 2009–2013. This study explores the shipping-charge behavior of a service provider through a modeling approach that considers air cargo security. Our findings show that security oversight increases air cargo demand, controlling for the effect of price. Improving security measures increases the air cargo price, but the magnitude of this increase is small. Our results should help policymakers gauge the benefit of improved security and help airlines design an effective model to determine future air cargo shipping charges under high uncertainty to mitigate short- and long-term financial risks.

Green Commercial Aviation Supply Chain—A European Path to Environmental Sustainability

The last century has witnessed European commercial aviation flourishing at the cost of environmental degradation by boosting greenhouse gas and CO2 emissions in the atmosphere. However, the outcry for net-zero emissions compels the sector's supply chain to a minimum 55% reduction of greenhouse gas emissions below the 1990 level by 2030 and zero CO2 emissions by 2050. This study examines a European environmental sustainability path toward a green commercial aviation supply chain. Driven by literature and a review of related documents, two propositions were advanced to orient perspectives on the relationship between pollution and the commercial aviation supply chain and actions being taken toward environmental sustainability. In semi-structured interviews, seventeen aerospace associates endorsed pollution sources in the commercial aviation supply chain during the four stages of the aircraft life cycle, including extracting the raw materials, manufacturing, ground and flight operations, and end-of-service. They recommended transitioning into green commercial aviation through the widespread deployment of innovative technologies, from modifying airframes to changing aviation fuel, utilizing alternative propulsion systems, adopting circular manufacturing, and improving air traffic management.

A Categorization of Resilience: A Scoping Review

The COVID-19 pandemic exposed the existential public health and economic fragilities of the civil aviation industry. To prevent future public health disruptions, the civil aviation industry is gaining interest in becoming more "resilient” but rarely elaborates on its meaning, hampering decision-making and strategy development. When looking into the academic literature it seems that a proliferation of resilience-related concepts occurred. Although enriching resilience, it also dilutes its meaning and reduces its use for practice. This paper aims to create concept clarity regarding resilience by proposing a categorization of resilience. Based upon a scoping review, this categorization dissects resilience into four reoccurring aspects: fragility, robustness, adaptation, and transformation. This categorization is expected to support sensemaking in disruptive times while assisting decision-making and strategy development on resilience. When applying this categorization in the civil aviation and public health context, the transformative aspect seems underused. Further research will focus on maturing the categorization of resilience and its use as a sensemaking tool.

Safety Perception Evaluation of Civil Aviation Based on Weibo Posts in China: An Enhanced Large-Scale Group Decision-Making Framework

The massive spread of COVID-19 and the crash of China Eastern Airlines MU5735 have negatively impacted the public's perception of civil aviation safety, which further affects the progress of the civil aviation industry and economic growth. The aim of research is to investigate the public's perception of China's civil aviation safety and give the authorities corresponding suggestions. First, we use online comment collection and sentiment analysis techniques to construct a novel evaluation index system reflecting the public's greatest concern for civil aviation safety. Then, we propose two novel large-scale group decision-making (LSGDM) models for aggregating evaluation: (1) K-means clustering with a novel distance measure for evaluators combined with unsupervised K-means clustering in two-stage, (2) unsupervised K-means clustering for evaluators combined with unsupervised K-means clustering for processing evaluation in two-stage. Finally, we compare the characteristics of different models and use the average of the two models as the final evaluation results. © 2023, The Author(s) under exclusive licence to Taiwan Fuzzy Systems Association.

Bike Sharing and Health

Civil Aviation is a vital sector of the global economy. The US National Airspace System (NAS) provides a network of airspace, air navigation facilities, equipment, services, airports, technical information, and personnel needed for the operation of civil aviation in the United States. The capacity of the airspace in the current system is primarily limited by the ability of the air traffic controllers to maintain situational awareness and provide separation services to the aircraft. Currently, there is an unprecedented decline of between 56% and 60% in air traffic demand due to the outbreak of corona virus (COVID-19) pandemic in China and its rapid spread to the rest of the world. Before the pandemic, the 2020 FAA forecast predicted the air traffic demand to grow over the next 20 years with an annual growth rate of about 2%. This anticipated increase in traffic will put a further strain on the airports and the airspace;it will result in large delays, airline schedule breakdown, and adverse environmental impact. The system needs to address developments and anticipated explosive growth in low speed and low-cost urban air mobility vehicles. This article provides an overview of Air Traffic Management (ATM) in the United States, brief review of current aviation operations, research under development, and technology and infrastructure upgrades currently being deployed to enable the current aviation system to meet the needs of future aviation systems. Air traffic operations need to be harmonized across all parts of the globe to achieve standardization and efficiency of operations. © 2021 Elsevier Ltd. All rights reserved

Uncertainty quantification of CO2 emissions from China's civil aviation industry to 2050.

To mitigate aviation's carbon emissions of the aviation industry, the following steps are vital: accurately quantifying the carbon emission path by considering uncertainty factors, including transportation demand in the post-COVID-19 pandemic period; identifying gaps between this path and emission reduction targets; and providing mitigation measures. Some mitigation measures that can be employed by China's civil aviation industry include the gradual realization of large-scale production of sustainable aviation fuels and transition to 100% sustainable and low-carbon sources of energy. This study identified the key driving factors of carbon emissions by using the Delphi Method and set scenarios that consider uncertainty, such as aviation development and emission reduction policies. A backpropagation neural network and Monte Carlo simulation were used to quantify the carbon emission path. The study results show that China's civil aviation industry can effectively help the country achieve its carbon peak and carbon neutrality goals. However, to achieve the net-zero carbon emissions goal of global aviation, China needs to reduce its emissions by approximately 82%-91% based on the optimal emission scenario. Thus, under the international net-zero target, China's civil aviation industry will face significant pressure to reduce its emissions. The use of sustainable aviation fuels is the best way to reduce aviation emissions by 2050. Moreover, in addition to the application of sustainable aviation fuel, it will be necessary to develop a new generation of aircraft introducing new materials and upgrading technology, implement additional carbon absorption measures, and make use of carbon trading markets to facilitate China's civil aviation industry's contribution to reduce climate change.

Resilience Evaluation on Air Transportation System Based on Bayesian Network

In order to accurately describe the security capability of the air transportation system，the concept of resilience is introduced to evaluate its risk resistance and recovery level. First，a hierarchical Bayesian network model is established，and the factors that affect the normal operation of the air transportation system are analyzed. Second，the system resilience is evaluated，and the resilience and changing trends of China's air transportation system from 2010 to 2019 are quantitatively analyzed. Third，the impact of factors on the overall resilience level is analyzed，and the change of the underlying nodes during the COVID-19 epidemic is taken as an example. Then，the overall resilience level of the system is evaluated through adjusting each node of the model. The research results show that the overall resilience evaluation value of the air transportation system is between 54% and 60.2%，and it exhibits a fluctuating upward trend with the continuous social and economic development. Under the influence of the COVID-19 epidemic，the service level of the system has been greatly affected，but the overall system can still maintain a certain degree of resilience. The Bayesian network model can better quantify the resilience of the air transportation system，and help improve the resilience of the system. This method provides effective control strategies and theoretical methods for the sustainable development and resistance to shocks of the air transportation industry. © 2022 Nanjing University of Aeronautics an Astronautics. All rights reserved.

Resilience Evaluation on Air Transportation System Based on Bayesian Network

In order to accurately describe the security capability of the air transportation system，the concept of resilience is introduced to evaluate its risk resistance and recovery level. First，a hierarchical Bayesian network model is established，and the factors that affect the normal operation of the air transportation system are analyzed. Second，the system resilience is evaluated，and the resilience and changing trends of China's air transportation system from 2010 to 2019 are quantitatively analyzed. Third，the impact of factors on the overall resilience level is analyzed，and the change of the underlying nodes during the COVID-19 epidemic is taken as an example. Then，the overall resilience level of the system is evaluated through adjusting each node of the model. The research results show that the overall resilience evaluation value of the air transportation system is between 54% and 60.2%，and it exhibits a fluctuating upward trend with the continuous social and economic development. Under the influence of the COVID-19 epidemic，the service level of the system has been greatly affected，but the overall system can still maintain a certain degree of resilience. The Bayesian network model can better quantify the resilience of the air transportation system，and help improve the resilience of the system. This method provides effective control strategies and theoretical methods for the sustainable development and resistance to shocks of the air transportation industry. © 2022 Nanjing University of Aeronautics an Astronautics. All rights reserved.

METHODS FOR FORECASTING DEMAND IN REPAIRING AN AIRLINE'S REPAIRABLE LINE REPLACEABLE UNIT PARTS

Verspreide mislukkingsfrekwensie, veranderlike en komplekse bei'nvloedende faktore, en 'n lae akkuraatheid in die voorspelling van voorraadaanvraag is kenmerke van lynvervangbare eenheid (LRU) onderdele. Sommige duur herstelbare LRU (HR-LRU) onderdele het 'n aansienlike impak op die koste van vliegtuigonderdele. Baie lugrederye stel baie belang om die vraag na HR-LRU-onderdele te voorspel. Hierdie studie bied prosedures aan om die optimale model vir die voorspelling van die vraag na HR-LRU-onderdele te identifiseer. Eerstens is 'n tradisionele voorspellingsmodel, sewe enkelmetingsmodelle en vier gekombineerde modelle gekies en gebruik om mislukkingsdata te voorspel. Vervolgens is evalueringsindekse vir assessering gekies om die optimale model te verkry. Laastens het ons die werklike en voorspelde waardes vergelyk om die gevolgtrekkings wat tydens die vorige evalueringstap gemaak is, te verifieer. Die resultate het aangedui dat, onder die enkelmodelle, die negatiewe binomiale regressiemodel en die Holt-Winters model die mees geskikte was vir HR-LRU dele. Die SSE en MAE van die negatiewe binomiale regressie was die laagste op 118.4114 en 1.97352 onderskeidelik, en die Holt-Winters model se MAE was die laagste op 1. 13270. Die IOWA operateur voorspellingsmodel en die fout wederkerige veranderlike gewig kombinasie metode het voorspellings opgelewer wat die naaste aan die werklike waardes was onder die gekombineerde modelle. Die voorspellingsfoute van die negatiewe binomiale regressiemodel en die IOWA-operateurmodel was slegs 0,169 3 en 1,411 3 in 2018. Benewens die samestelling van 'n stel prosesse om die vraag na HR-LRU-onderdele te voorspel, bespreek ons ook die graad van passing van verskillende metodes, die redes vir die verandering in die gewaarborgde koers van HR-LRU-onderdele, en die redes vir die voorkoms van spesiale jare. Ons vergelyk ook die ooreenkomste en verskille tussen hierdie artikel en ander navorsingsartikels.Alternate :Scattered failure frequency, variable and complex influencing factors, and a low accuracy in predicting inventory demand are characteristics of line replaceable unit (LRU) parts. Some high-priced repairable LRU (HR-LRU) parts have a considerable impact on the cost of aircraft spare parts.This study presents procedures to identify the optimal model for forecasting the demand for HR-LRU parts. First, a traditional prediction model, seven single measurement models, and four combined models were selected and used to predict failure data. Subsequently, evaluating indexes were selected for assessment to obtain the optimal model. Finally, we compared the actual and predicted values to verify the conclusions drawn during the previous evaluation step. The results indicated that, among the single models, the negative binomial regression model and the Holt-Winters model were most suitable for HRLRU parts. The SSE (sum of squares error) and MAE (mean absolute error) of the negative binomial regression were the lowest at 118.4114 and 1.97352 respectively, and the Holt-Winters model's MAE was the lowest at 1. 13270. The IOWA operator prediction model and the error reciprocal variable weight combination method produced predictions closest to the actual values among the combined models. In addition to constructing a set of processes to prediction, we also discuss the fit of different methods, the reasons for the change in the guaranteed rate, and the reasons for the occurrence of special years. We also compare the similarities and differences between this article and other papers.

MAJOR TRENDS IN AVIATION INDUSTRY DURING COVID-19

The purpose of the research in this article is to identify the main trends in the development of aviation industry during COVID-19 pandemic. The authors identify the main problems facing aviation industry in the context of the developing world crisis and possible ways to solve them. As a working hypothesis, it is proposed to form the basic concepts necessary for preliminary preparation and implementation of operational measures to restore passenger and cargo aviation. Taking into account the main threats facing the aviation industry during COVID-19, the article proposes the organizational and economic mechanisms to restore the industry. Short-term, medium-term and long-term recovery scenarios are considered, taking into account the relevant factors that have a certain impact. The study is based on a comprehensive analysis of documentary data provided by government agencies in a number of European countries. Openly printed materials from the International Civil Aviation Organization (ICAO) are also used in the analytical report "Consequences of new coronavirus COVID-19 in civil aviation: analysis of economic impact". The research methods are working papers from the European and North Atlantic Offices of ICAO aimed at rebuilding the aviation industry after COVID-19 pandemic. An analysis of global and Russian passenger traffic for Q1-Q4 (quartile) of 2021 and a development forecast for Q1-Q2 of 2022 is provided. The scenario problems facing the aviation industry in the context of COVID-19 crisis are identified. There are key concepts necessary to start preparation and implementation of effective measures to restore the aviation industry. © 2022 Institut za Istrazivanja. All rights reserved.

Prospects for Increasing the Flight Network in the Ukrainian Aviation Market in the Context of the COVID-19 Pandemic in the Context of the Agreement on a Common Aviation Area

The article examines the prospects for increasing the flight network in the context of the COVID-19 pandemic in the context of the agreement on a Common Aviation Area (CAA). The authors stressed that Ukraine is one of the few countries in the world with a completed aviation development cycle and occupies a leading position in the global market of transport and regional passenger aviation. It is proved that COVID-19 has become a unique challenge and threat to the existence and functioning of one of the largest and most important industries, such as civil aviation. A brief analysis of the work of aviation enterprises in Ukraine testifies to the catastrophic economic situation that has developed at the airfields of our country under the influence of the Covid-19 pandemic. It is proved that the Common Aviation Area agreement allows the gradual introduction into the legislation of Ukraine of more than 60 EU standards and directives in the field of flight safety, aviation security and air traffic management. It was noted that an important factor in signing the Agreement on the establishment of CAA is the production and renewal of the airline fleet with modern aircraft, increasing the level of passenger service and further modernization of airports. With the entry into force of the CAA Agreement, Ukrainian airlines can easily participate in any European airport and compete in different directions with European airlines. The authors highlight the prospects for increasing the flight network in the context of the COVID-19 pandemic in the context of the agreement on a common aviation area. © 2022 Kaunas University of Technology. All rights reserved.

Air transportation encounters inflationary headwinds on its recovery from pandemic

Puranik et al discuss air transportation which encounters inflationary headwinds on its recovery from pandemic. A strong and growing global air travel demand, supported by the lifting of air travel restrictions in most countries, fueled the global airline industry's continued recovery this year from the impacts of covid-19. In June, the International Air Transport Association projected a total of 3.8 billion passengers for the year--83% of pre-pandemic levels--and a record high air cargo volume of more than 68 million tons, resulting in a global airline industry loss of $9.7 billion this year down from $42.1 billion in 2021. Only the North America region was expected to achieve profitability, with an estimated $8.8 billion profit. In October, member states of the International Civil Aviation Organization adopted the goal of achieving net-zero carbon emissions by 2050, a target that IATA member airlines had committed to in Oct 2021.

[Analysis of the stressors and mental status of civil aviation pilots under the background of the major infectious disease].

Objective: To study the stressors and mental status of civil aviation pilots under the background of major infectious disease. Methods: From January to March 2021, a cluster sampling method was used to select 143 airline pilots in service as the research objects. The self-made emotion and stress source questionnaire, Chinese version of stress perception scale (CPSS) , self rating Anxiety Scale (SAS) and self rating Depression Scale (SDS) were used to investigate the airline pilot population. 136 valid questionnaires were collected, with an effective recovery rate of 95.1%. The measurement data conform to the normal distribution and are expressed by (x±s) . T-test and analysis of variance are used for comparison between groups, and Pearson correlation is used for correlation analysis. The data that do not conform to the normal distribution are expressed by the median and quartile [M (Q(1), Q(3)) ], and the non parametric test is used for the comparison between groups. Multiple linear stepwise regression was used to analyze the influencing factors of pressure perception. In addition, Amos 23.0 software was used to construct structural equation models of stress perception and negative emotions. Results: Under the background of the epidemic, the main sources of stress for civil aviation pilots are: the risk of possible reduction in income, the risk of contracting COVID-19, the pressure at work, and the risk of possible slow progress of upgrading. Among them, the first co pilot was more worried about the possible reduction of income than the instructor (P=0.009) ; The first co pilot and the captain of the airline were more worried about the possible slowdown of the upgrade progress than the instructor (P<0.001, P=0.014) . The mean pressure perception of pilots was higher than that of Chinese norm (t=3.11, P=0.002) . The standard scores of anxiety and depression were slightly higher than the standard scores of the Chinese norm under the non epidemic situation (t=7.00, 4.07, all P<0.001) . The results of multiple linear stepwise regression analysis showed that stress perception was negatively correlated with good family relations (t=-8.50, P=0.000) , and positively correlated with worries about slow progress of upgrading, COVID-19 infection, lack of interpersonal communication and income reduction (t=3.31、3.86、2.88、2.06, P<0.05) . Pressure perception was positively correlated with negative emotion (all P<0.001) . The results of structural equation model show that stress perception affects pilots' negative emotions directly or indirectly, and its standardized total effects on anxiety, depression, hypochondriac, fear, compulsion and irritability are 0.719, 0.811, 0.403, 0.355, 0.295 and 0.244 respectively. Conclusion: Public health emergencies have an impact on the mental status of pilots. Should pay attention to the stressors and psychological conditions of pilots in time, and consider formulating measures to relieve the stress of pilots.

The Impact of COVID-19 on the Cybersecurity in Civil Aviation: Review and Analysis

The significance of cybersecurity and cyber resilience in the aviation sector cannot be ignored, and this fact has been highlighted time and again due to frequent cyberattacks prior and during the COVID-19 pandemic. This paper presents an analysis of the relevant studies that addressed the impact of the COVID-19 pandemic on cybersecurity generally, and in the aviation sector in particular, including identifying the most common increased cyber-attacks associated with the outbreak of COVID-19. Our analysis shows that commonly increased cyber-attacks associated with the outbreak of COVID-19 in aviation are phishing and ransomware. Furthermore, the likelihood of phishing and ransomware attacks is very likely during the pandemic than before it while the impact on flight operations is low, and the subsequent risk level is tolerable during the pandemic. Additionally, we propose a set of possible mitigation measures for those cyber-attacks. © 2022 IEEE.

Forecast of Aviation Traffic in Indonesia Based on Google Trend and Macroeconomic Data using Long Short-Term Memory

The COVID-19 pandemic has impacted many sectors. For example, in the aviation sector, flight traffic went down drastically with no certainty of being recovered. This calls for a methodology to predict the flight traffic to provide strategic planning on flight schedules operational, route structuring, and flight navigation service cost determination. However, current developments mainly focus on flight traffic forecasting based on historical data without considering external factors. In this study, we propose the Long Short-Term Memory (LSTM) technique to forecast flight traffic in Indonesia involving external variables such as macroeconomic variables and Google Trends. LSTM is proposed because of its flexibility to model non-linear time series data and has a good reputation for predictive accuracy. We first select a few among Google Trends and macroeconomic variables using nonlinearity analysis and cross-correlation function (CCF). We then employ the selected variables to forecast the flight traffic and compare it to the one using only historical flight traffic data. Our results concluded, based on the Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE), that the model involving google trend outperforms the other three models, i.e., the model with only historical data, the model with macroeconomics, and the model with both macroeconomic and Google Trends. It is because, in this digital era, Google Trends can reflect population psychology in an up-to-date manner. © 2022 IEEE.

Student Paper: Study of COVID-19 Impact on Aviation Maintenance Training in Indonesia

Globally, the aviation industry including the airlines, maintenance, and manufacturing has faced an unprecedented crisis during the COVID-19 pandemic. Aviation training in Indonesia is no exception in experiencing the pandemic's negative impacts, such as disruptions in aviation training, mental health issues, and economic uncertainty. Teachers were forced to adjust instruction from in-person training to online or hybrid learning. This shift increases much concern, especially on the training effectiveness and the quality of its outcome. Perceptions of instructors need to be examined to gain a clearer understanding of the effectiveness and whether there were positive or negative consequences as well as costs from the aforementioned changes. The researchers of this study conducted seven semi-structured interviews with aviation maintenance instructors in Indonesia to determine the challenges of changing teaching methods during COVID-19. Moreover, a questionnaire was collected from 83 students in four maintenance training programs to investigate the COVID-19 learning method changes in their practical skills as learning outcomes. The Incorporation of Technology (T), Individual (I), Pedagogical (P), and Enabling Condition (EC) or 'TIPEC' Framework and Resilience Engineering Framework will be utilized as the basis to develop the questionnaire and to analyze the results of how the students responded to the new learning method. In the end, this study suggested the most effective teaching methods that can improve practical skilled aviation maintenance professionals in Indonesia during the pandemic situation. © American Society for Engineering Education, 2022.

Impact of moving an international aviation design competition to a virtual environment: challenges, benefits, and lessons learned (Evaluation)

Starting in early 2020, the COVID-19 pandemic has had a significant impact on STEM competitions for high school students. With the shutdowns during the early part of the pandemic, competitions with an in-person component were forced to either cancel or adapt as virtual. The Real World Design Challenge (RWDC) competition was no exception. In April of each year, teams invited to participate in the National/International portion of the RWDC competition travel to the Washington, DC area to give presentations before a panel of judges. In a little over a month in 2020, RWDC was able to successfully transition the National/International competition to a virtual event. With the success from 2020, the 2021 competition again went virtual, and with the continued uncertainties related to the pandemic, the 2022 event was virtual. This paper discusses the impact that a virtual final event has had on the RWDC competition. The move to a virtual event in 2020 and the subsequent virtual events led to many challenges but also provided several benefits. © American Society for Engineering Education, 2022