Global System Research Articles

Organ Donation and Transplantation Registries Across the Globe: A Review of the Current State.

The current landscape of organ donation and transplantation (ODT) registries is not well established. This narrative review sought to identify and characterize the coverage, structure, and data capture of ODT registries globally. We conducted a literature search using Ovid Medline and web searches to identify ODT registries from 2000 to 2023. A list of ODT registries was compiled based on publications of registry design, studies, and reports. Extracted data elements included operational features of registries and the types of donor and recipient data captured. We identified 129 registries encompassing patients from all continents except Antarctica. Most registries were active, received funding from government or professional societies, were national in scope, included both adult and pediatric patients, and reported patient-level data. Registries included kidney (n = 99), pancreas (n = 32), liver (n = 44), heart (n = 35), lung (n = 30), intestine (n = 15), and islet cell (n = 5) transplants. Most registries captured donor data (including living versus deceased) and recipient features (including demographics, cause of organ failure, and posttransplant outcomes) but there was underreporting of other domains (eg, donor comorbidities, deceased donor referral rates, waitlist statistics). This review highlights existing ODT registries globally and serves as a call for increased visibility and transparency in data management and reporting practices. We propose that standards for ODT registries, a common data model, and technical platforms for collaboration, will enable a high-functioning global ODT system responsive to the needs of transplant candidates, recipients, and donors.

Multiple Disease Prediction System Using ML

Abstract: The increasing prevalence of diverse diseases presents a challenge to global healthcare systems, underscoring the need for innovative and efficient methods for early detection and preventive measures. This paper explores the application of machine learning algorithms in multiple disease prediction to enhance diagnostic accuracy and enable timely intervention. Leveraging diverse health-related data sources, including medical records and genomic information, comprehensive predictive models are developed. A multi-faceted machine learning approach integrates support vector machines, decision trees, neural networks, and ensemble learning methods to analyze complex data patterns. Feature selection and dimensionality reduction techniques optimize model performance and interpretability. The development of a predictive system involves essential steps such as data collection, preprocessing, and model training, followed by evaluation using metrics like accuracy and recall. Integration of Flask for web application development facilitates user interaction and prediction functionality. Deployment, testing, debugging, and ongoing maintenance ensure system efficiency and compliance with regulatory requirements for healthcare data security and privacy.

Wireless Caller ID Display for Bikers

Abstract: The project's primary focus is a Bluetooth-enabled mobile phone interface. The Arduino microcontroller in this project is also programmed using the Arduino IDE software through a USB port on the Arduino board. The Bluetooth module HC-05 operates on serial communicationand receives serial information via a software program. Thedata is sent through the Bluetooth module after being received from the app. The DC unit on the bike can be connected to the DC supply. The application begins to function in real time as soon as the bike is turned on. AfterBluetooth receives a serial transmission from the user's phone, it is sent to an Arduino board for processing before being displayed on an LCD screen to show caller ID details,including the user's mobile number. Additionally, the display alerts the user or provides a warning to stop the bike. In this instance, the cell phone serves as a transmitting tool.Because Android phones can operate software applicationsand use Bluetooth, they are the required device for the user's phone. Global systems for mobile communication (GSM) are not recommended since they could end up being more expensive.

A Study Comparing Waiting Times in Global and Local Queuing Systems with Heterogeneous Workers

A virtual marketplace or service-providing system must ensure minimal task response times. Varying working rates among the human workers in the system can lead to longer delays for certain tasks. The waiting time in the queue is crucially affected by the queueing architecture used in the system, whether global or local. Studies generally favor global queue systems over local ones, assuming similar processing rates. However, system behavior changes when workers are heterogeneous. In this research, we used simulation to compare the waiting times of tasks assigned to three categories of processing rates in both architectures and with various routing policies in local queues. We found that when using random tie-breaking, there was a correlation between waiting time duration and the proportion of tie-breaking events. Performance is improved when controlling these events using scheduling awareness of the workers’ processing rates. The global queue outperforms local queues when the workers are homogeneous. However, the push mechanisms that control the assignment processes and heterogeneity-aware algorithms improve local queue system waiting times and load balance. It is better than global queues when tasks are assigned to medium and fast workers, but it also enables specific slow workers’ assignments.

Drivers of Sustainability Credentialling in the Red Meat Value Chain—A Mixed Methods Study

Sustainability credentialling is the communication of environmental, social, economic, or animal-welfare-related information about a producer or product. Demand for sustainability credentials has been increasing and the aim of this study was to describe the main drivers for this kind of information in Australian red meat value chains that reach consumers across Australia and internationally, mainly in Asia, the USA, and the Middle East. The mixed methods approach included consultation with red meat processors. Desk-based research explored drivers from outside the value chain identified in the consultation. Little evidence was found that consumers are a driver of sustainability credentialling. The main drivers were in the global financial system, expressed in coordinated climate action policies by financial service providers and emerging government climate-related financial legislation. The inclusion of Scope 3 emissions extends coverage to most value chain participants. Net zero transitioning presents many risks to red meat value chains, potentially involving costly interventions and greater difficulty accessing financial services, with direct implications for production costs and asset values. Urgent action is recommended to achieve the formal recognition and use of climate metrics that differentiate the management strategies that are applicable to short-lived biogenic methane compared to CO2 to achieve the Paris Agreement goals.

An Analysis of the Spatial and Temporal Synergy between Profiles of Aircraft-Based Observations and Operational Radiosonde Reports over the United States

Abstract Aircraft-based observations (ABOs) are an important component of the global observation system. Observations of pressure, temperature and wind are obtained from thousands of routine commercial flights daily via the Aircraft Meteorological Data Relay (AMDAR) program, while a subset of approximately 145 aircraft globally (and 135 within the continental United States) also produce observations of water vapor from the Water Vapor Sensing System–II (WVSS–II). Aircraft equipped with WVSS–II provide the basic parameters as radiosonde observations throughout most of the troposphere, often at higher temporal and spatial frequency. Since these aircraft are operated according to the demands of passenger and cargo, the availability of aircraft profiles varies significantly in space and time, with more profiles during daytime and early evening than overnight, more profiles on weekdays than weekends, and more during the summer months. The number of available profiles was significantly impacted by reductions in travel during the Covid-19 pandemic but has recovered substantially. The potential for aircraft profiles to support the operational radiosonde network is explored, including the effect of various spatial and temporal matching criteria. Radiosonde launches at 0000 UTC that are well-aligned with aircraft profiles are found across the continental United States, but well-covered 1200 UTC launches are strongly biased to the east. ABO coverage of asynoptic launch times is also explored. The busiest sites usually have multiple compatible aircraft profiles at both synoptic and asynoptic times. This redundancy lends robustness to the observation network and enables forecasters to monitor atmospheric evolution more continuously throughout the day.

Distribution and morphology of non-persistent contrail and persistent contrail formation areas in ERA5

Abstract. The contrail formation potential as well as its temporal and spatial distribution is estimated using meteorological conditions of temperature and relative humidity from the ERA5 re-analysis provided by the European Centre for Medium-Range Weather Forecasts. Contrail formation is estimated with the Schmidt–Appleman criterion (SAc), solely considering thermodynamic effects. The focus is on a region ranging from the Eastern United States (110–65° W) to central Europe (5° W–30° E). Around 18 000 flight trajectories from the In-service Aircraft for a Global Observing System (IAGOS) are used as a representative subset of transatlantic, commercial flights. The typical crossing distance through a contrail-prone area is determined based on IAGOS measurements of temperature T and relative humidity r and then based on co-located ERA5 simulations of the same quantities. Differences in spatial resolution between IAGOS and ERA5 are addressed from an aircraft-centered perspective, using 1 km segments, and a model-centered perspective, using 19 km flight sections. Using the aircraft-centered approach, 50 % of the crossings of persistent contrail (PC) regions based on IAGOS are shorter than 9 km, while in ERA5 the median is 155 km. Time-averaged IAGOS data lead to a median crossing length of 66 km. The difference between the two data sets is attributed to the higher variability of r in IAGOS compared to ERA5. The model-centered approach yields similar results, but typical crossing lengths are larger by only up to 10 %. Binary masks of PC formation are created by applying the SAc on the two-dimensional fields of T and r from ERA5. In a second step the morphology of PC regions is also assessed. Half of the PC regions in ERA5 are found to be smaller than ≈ 35 000 km2 (at 200 hPa), and the median of the maximum dimension is shorter than 760 km (at 200 hPa). Furthermore, PC regions tend to be of near-circular shape with a tendency to a slight oval shape and a preferred alignment along the dominant westerly flow. Seasonal, vertical distributions of PC formation potential 𝒫 are characterized by a maximum between 250 and 200 hPa. 𝒫 is subject to seasonal variations with a maximum in magnitude and extension during the winter months and a minimum during summer. The horizontal distribution of PC regions suggests that PC regions are likely to appear in the same location on adjacent pressure levels. Climatologies of T, r, wind speed U, and resulting PC formation potential are calculated to identify the constraining effects of T and r on 𝒫. PC formation is primarily limited by conditions that are too warm below and conditions that are too dry above the formation region. The distribution of PCs is slanted towards lower altitudes from 30 to 70° N, following lines of constant T and r. For an observed co-location of high U and 𝒫, it remains unclear whether PC formation and the jet stream are favored by the same meteorological conditions or if the jet stream itself favors PC occurrence. This analysis suggests that some PC regions will be difficult to avoid by rerouting aircraft because of their large vertical and horizontal extents.

Design and Experiment of an Autonomous Navigation System for a Cattle Barn Feed-Pushing Robot Based on UWB Positioning

The autonomous navigation system of feed-pushing robots is one of the key technologies for the intelligent breeding of dairy cows, and its accuracy has a significant influence on the quality of feed-pushing operations. Currently, the navigation methods of feed-pushing robots in the complex environment of cattle barns mainly include visual, LiDAR, and geomagnetic navigation, but there are still problems relating to low navigation accuracy. An autonomous navigation system based on ultra-wideband (UWB) positioning utilizing the dynamic forward-looking distance pure pursuit algorithm is proposed in this paper. First, six anchor nodes were arranged in the corners and central feeding aisle of a 30 × 86 m rectangular standard barn to form a rectangular positioning area. Then, utilizing the 9ITL-650 feed-pushing robot as a platform and integrating UWB wireless positioning technology, a global coordinate system for the cattle barn was established, and the expected path was planned. Finally, the pure pursuit model was improved based on the robot’s two-wheel differential kinematics model, and a dynamic forward-looking distance pure pursuit controller based on PID regulation was designed to construct a comprehensive autonomous navigation control system. Subsequently, field experiments were conducted in the cattle barn. The experimental results show that the static positioning accuracy of the UWB system for the feed-pushing robot was less than 16 cm under no-line-of-sight conditions in the cattle barn. At low speeds, the robot was subjected to linear tracking comparative experiments with forward-looking distances of 50, 100, 150, and 200 cm. The minimum upper-line distance of the dynamic forward-looking distance model was 205.43 cm. In the steady-state phase, the average lateral deviation was 3.31 cm, with an average standard deviation of 2.58 cm and the average root mean square error (RMSE) of 4.22 cm. Compared with the fixed forward-looking distance model, the average lateral deviation, the standard deviation, and the RMSE were reduced by 42.83%, 37.07%, and 42.90%, respectively. The autonomous navigation experiments conducted on the feed-pushing robot at travel speeds of 6, 8, and 10 m/min demonstrated that the maximum average lateral deviation was 7.58 cm, the maximum standard deviation was 8.22 cm, and the maximum RMSE was 11.07 cm, meeting the autonomous navigation requirements for feed-pushing operations in complex barn environments. This study provides support for achieving high-precision autonomous navigation control technology in complex environments.

EFS-XGBoost: A robust framework for precision classification of COVID-19 cases

The emergence of the novel COVID-19 virus has had a profound impact on global healthcare systems and economies, underscoring the imperative need for the development of precise and expeditious diagnostic tools. Machine learning techniques have emerged as a promising avenue for augmenting the capabilities of medical professionals in disease diagnosis and classification. In this research, the EFS-XGBoost classifier model, a robust approach for the classification of patients afflicted with COVID-19 is proposed. The key innovation in the proposed model lies in the Ensemble-based Feature Selection (EFS) strategy, which enables the judicious selection of relevant features from the expansive COVID-19 dataset. Subsequently, the power of the eXtreme Gradient Boosting (XGBoost) classifier to make precise distinctions among COVID-19-infected patients is harnessed.The EFS methodology amalgamates five distinctive feature selection techniques, encompassing correlation-based, chi-squared, information gain, symmetric uncertainty-based, and gain ratio approaches. To evaluate the effectiveness of the model, comprehensive experiments were conducted using a COVID-19 dataset procured from Kaggle, and the implementation was executed using Python programming. The performance of the proposed EFS-XGBoost model was gauged by employing well-established metrics that measure classification accuracy, including accuracy, precision, recall, and the F1-Score. Furthermore, an in-depth comparative analysis was conducted by considering the performance of the XGBoost classifier under various scenarios: employing all features within the dataset without any feature selection technique, and utilizing each feature selection technique in isolation. The meticulous evaluation reveals that the proposed EFS-XGBoost model excels in performance, achieving an astounding accuracy rate of 99.8%, surpassing the efficacy of other prevailing feature selection techniques. This research not only advances the field of COVID-19 patient classification but also underscores the potency of ensemble-based feature selection in conjunction with the XGBoost classifier as a formidable tool in the realm of medical diagnosis and classification.

In Transit: The Making of Urban Migrants in India

The neo-liberal transformation of India was aided by the restructuring processes launched by the SAP in 1991 and brought the open market to the centre of economic imagination for new India. As the Indian economy opened up to the global financial capital systems and the private sector expanded, a large proportion of labour was relocated to the private, unorganized sector in India. This sector swallowed a majority of the migrant population that was flowing into the urban centers of India. The “middle class aspirations” that the migrants to the cities harbored materialize as a part of the larger neo-liberal aspiration of being upwardly mobile and living a ‘good life’. Based on an ethnographic study conducted in two phases, this paper accounts the narratives of men and women migrants who are employed in the various service sector units of two shopping malls in the city of New Delhi. This paper maps the diversity in the migrant experience by comparing the experiences of two distinct groups of migrants employed in these sectors in India- the indigenous migrants from North East India and the migrants from the rural hinterlands of North India. By comparing the narratives of two groups of migrants my paper tries to argue that in addition to education and credentials, classifications of caste, community and ethnicity play an important role in determining ‘life chances’ and employment opportunities for migrants in urban India.

RFID AND GSM BASED ATTENDANCE SYSTEM

We have developed a quick and simple solution to the challenge of tracking every student's presence in a class by using radio frequency identification (RFID) to control student attendance with little to no teacher intervention.This project is to use radio frequency identification (RFID) technology to streamline the attendance recording system. A web-based application called RFID based Attendance recorder with SMS alert system will be created to address the aforementioned issue. Database support and GSM (Global System for Mobile communication) technologies will be used in the development of the system. As a result, in addition to tracking students' attendance, the system notifies the students' parents by SMS when they are present or not. Key Words: Monitoring, Tracking, attendance, RFID

Spectrum of COVID-19 induced liver injury: A review report.

The coronavirus disease 2019 (COVID-19) pandemic has caused changes in the global health system, causing significant setbacks in healthcare systems worldwide. This pandemic has also shown resilience, flexibility, and creativity in reacting to the tragedy. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection targets most of the respiratory tract, resulting in a severe sickness called acute respiratory distress syndrome that may be fatal in some individuals. Although the lung is the primary organ targeted by COVID-19 viruses, the clinical aspect of the disease is varied and ranges from asymptomatic to respiratory failure. However, due to an unorganized immune response and several affected mechanisms, the liver may also experience liver cell injury, ischemic liver dysfunction, and drug-induced liver injury, which can result in respiratory failure because of the immune system's disordered response and other compromised processes that can end in multisystem organ failure. Patients with liver cirrhosis or those who have impaired immune systems may be more likely than other groups to experience worse results from the SARS-CoV-2 infection. We thus intend to examine the pathogenesis, current therapy, and consequences of liver damage concerning COVID-19.

The Role of Notaries/Land Deed Officials in Combating Money Laundering Crimes with the Know Your Customer Principle

This research delves into the alarming intersection of notaries/land deed officials and money laundering crimes, highlighting the role of notarial services as potential facilitators in illicit financial activities. While notaries traditionally serve as impartial witnesses to document signings, their involvement in verifying transactions has increasingly attracted scrutiny due to the potential for abuse by money launderers. This study examines the vulnerabilities within the notarial system that may be exploited for money laundering purposes, including lax regulatory frameworks, inadequate due diligence practices, and the lack of standardized reporting mechanisms. The abstract also explores the challenges in detecting and preventing such illicit activities, emphasizing the need for enhanced regulatory oversight, improved training for notarial professionals, and increased collaboration between regulatory bodies, law enforcement, and the notarial community and also implementing the principle of know your customer. As the findings suggest, addressing these issues is crucial for safeguarding the integrity of notarial services and fortifying the global financial system against the insidious threat of money laundering.

Breaking bottlenecks: Power Distribution Dynamics in Industry Evolution

Many firms vie to attain a strategic bottleneck position in their industry, as it promises superior value appropriation over an extended period. Using a mixed-methods approach, we investigated the power dynamics between bottleneck and challenger segments in the airline ticket distribution sector. Our study of the bottleneck formed by the Global Distribution System (GDS) firms reveals the mechanisms that these firms employed to maintain power, as well as the mechanisms that airlines in the challenger segment used to attain power. These mechanisms strongly influenced the momentum of power shifts as the industry evolved towards greater modularization; we show how they worked recursively in a process of power distribution dynamics during that evolution. In addition, these mechanisms explain the dynamics at work between the incumbent and challenger segments, with airlines increasing the pressure to modularize and the GDS firms resisting that pressure. Our findings contribute to the literature on industry architectural change and industry evolution by providing a comprehensive understanding of the power dynamics that affect when and how strategic bottlenecks dissolve.

AIRLINE PRICING: HOW AIRLINES USE PRICING STRATGEIES

Airline pricing strategies play a pivotal role in the aviation industry's revenue management. This abstract explores the intricate mechanisms behind airline pricing, delving into the fundamental principles, factors, and techniques utilized by airlines to set fares. Drawing from a combination of academic research, industry reports, and real-world examples, this abstract provides a concise overview of the dynamic landscape of airline pricing. The abstract begins by elucidating the core objectives of airline pricing strategies, emphasizing the dual goals of maximizing revenue and optimizing capacity utilization. It then delineates the key determinants that shape pricing decisions, including demand forecasting, market segmentation, competition analysis, cost considerations, and consumer behavior. Furthermore, the abstract elucidates various pricing tactics employed by airlines, such as dynamic pricing, yield management, fare differentiation, and ancillary revenue generation. It examines how advanced analytics and revenue management systems enable airlines to dynamically adjust fares in response to fluctuating demand patterns, market conditions, and competitor actions. Moreover, the abstract explores the role of distribution channels in airline pricing, highlighting the importance of direct bookings, online travel agencies (OTAs), global distribution systems (GDS), and partnerships with intermediaries. It also discusses the emergence of personalized pricing strategies, leveraging big data analytics and machine learning algorithms to tailor fares based on individual preferences and purchasing behavior. Additionally, the abstract touches upon the regulatory frameworks and ethical considerations surrounding airline pricing practices, including transparency, fairness, and consumer protection. It underscores the need for airlines to strike a balance between revenue optimization and customer satisfaction, fostering trust and loyalty among passengers. In conclusion, this abstract offer valuable insights into the complex ecosystem of airline pricing strategies, shedding light on the multifaceted interplay between market dynamics, technological advancements, and business objectives. By understanding the underlying principles and tactics of airline pricing, stakeholders can navigate the competitive landscape more effectively, driving sustainable growth and profitability in the aviation industry.

Effects of Microtopography on Soil Microbial Community Structure and Abundance in Permafrost Peatlands.

Soil microorganisms play crucial roles in the stability of the global carbon pool, particularly in permafrost peatlands that are highly sensitive to climate change. Microtopography is a unique characteristic of peatland ecosystems, but how microtopography affects the microbial community structures and their functions in the soil is only partially known. We characterized the bacterial and fungal community compositions by amplicon sequencing and their abundances via quantitative PCR at different soil depths in three microtopographical positions (hummocks, flats, and hollows) in permafrost peatland of the Greater Xing'an Mountains in China. The results showed that the soil of hummocks displayed a higher microbial diversity compared to hollows. Microtopography exerted a strong influence on bacterial community structure, while both microtopography and soil depth greatly impacted the fungal community structure with variable effects on fungal functional guilds. Soil water content, dissolved organic carbon, total phosphorus, and total nitrogen levels of the soil mostly affected the bacterial and fungal communities. Microtopography generated variations in the soil water content, which was the main driver of the spatial distribution of microbial abundances. This information stressed that the hummock-flat-hollow microtopography of permafrost peatlands creates heterogeneity in soil physicochemical properties and hydrological conditions, thereby influencing soil microbial communities at a microhabitat scale. Our results imply that changes to the water table induced by climate warming inducing permafrost degradation will impact the composition of soil microbes in peatlands and their related biogeochemical functions, eventually providing feedback loops into the global climate system.

Forgotten Gems: Exploring the Untapped Benefits of Underutilized Legumes in Agriculture, Nutrition, and Environmental Sustainability.

In an era dominated by conventional agricultural practices, underutilized legumes termed "Forgotten Gems" represent a reservoir of untapped benefits with the unique opportunity to diversify agricultural landscapes and enhance global food systems. Underutilized crops are resistant to abiotic environmental conditions such as drought and adapt better to harsh soil and climatic conditions. Underutilized legumes are high in protein and secondary metabolites, highlighting their role in providing critical nutrients and correcting nutritional inadequacies. Their ability to increase dietary variety and food security emerges as a critical component of their importance. Compared to mainstream crops, underutilized legumes have been shown to reduce the environmental impact of climate change. Their capacity for nitrogen fixation and positive impact on soil health make them sustainable contributors to biodiversity conservation and environmental balance. This paper identifies challenges and proposes strategic solutions, showcasing the transformative impact of underutilized legumes on agriculture, nutrition, and sustainability. These "Forgotten Gems" should be recognized, integrated into mainstream agricultural practices, and celebrated for their potential to revolutionize global food production while promoting environmental sustainability.

Assessing the potential economic effects of mesopelagic fisheries as a novel source of fishmeal

AbstractThe continuous growth of the aquaculture industry implies increased demand for efficient sources of aquafeed, such as fishmeal. Pelagic fish are a desirable source of fishmeal due to their high nutritional content. Nevertheless, several pelagic stocks that have been exploited extensively for fishmeal production face ecological limits due to commercial exploitation, and the aquaculture industry is now seeking novel, efficient, and sustainable sources of aquafeed. The mesopelagic zone, an ecosystem with many scientific uncertainties, is being considered as a potential source for fishmeal, largely owing to the abundance of mesopelagic fish and their robust nutritional profile. However, both the ecological and economic viability of commercial exploitation of mesopelagic fish are not yet well understood. To understand the conditions that would make such an endeavor economically viable in the context of global fishmeal production systems, we use a bioeconomic model that assesses the economic consequences of including mesopelagic fish as a fishmeal source. Through simulations, we assess the economic implications of this hypothetical mesopelagic fishery on major pelagic fishmeal production systems. The mesopelagic fishery can be economically profitable for harvesters, and its addition to global fishmeal production reduces fishmeal market price, thus making it more accessible to aquaculture farmers and less profitable for pelagic fishers. While this may reduce fishing pressure on pelagic forage‐fish stocks, the implications of commercial exploitation of mesopelagic on key ecosystem services remain a concern.

Long-Term Evolution of Significant Wave Height in the Eastern Tropical Atlantic between 1940 and 2022 Using the ERA5 Dataset

Studies on the variability in ocean wave climate provide engineers and policy makers with information to plan, develop, and control coastal and offshore activities. Ocean waves bear climatic imprints through which the global climate system can be better understood. Using the recently updated ERA5 dataset, this study evaluated the spatiotemporal distribution and variability in significant wave height (SWH) in the Eastern Tropical Atlantic (ETA). The short-term trends and rates of change were obtained using the Mann–Kendall trend test and the Theil–Sen slope estimator, respectively, and decadal trends were assessed using wavelet transformation. Significant, positive monthly and yearly trends and a prevailing decadal trend were observed across the domain. Observed trends suggest that stronger waves are getting closer to the coast and are modulated by the Southern and Northern Atlantic mid-latitude storm fields. These observations have implications for the increasing coastal erosion rates on the eastern coast of the Tropical Atlantic.

Travel insurance behaviors of digital nomads

PurposeThis study aims to reveal the travel insurance behavior of digital nomads systematically. For this purpose, the habits and preferences of digital nomads for travel and health insurance were investigated based on the problems they experience during their travels.Design/methodology/approachWithin the scope of multimethod qualitative research, the insurance behaviors of digital nomads were investigated in depth by using both interview and content analysis techniques for social media comments. In the first stage of the study, the interview technique was used to describe the main factors underlying the insurance behaviors of digital nomads. In the second stage, the comments of digital nomads on social media platforms were evaluated by content analysis and themes regarding the insurance behaviors of digital nomads were reached.FindingsThe inadequacies of the current global system and national order determine the travel insurance behavior of digital nomads, who are generally opposed to the existing order and tend to escape from authority and routine. It was found that digital nomads care about the speed at which insurance companies meet their demands, the coverage of insurance policies (medical and travel-related components of insurance) and the cost of insurance behavior.Research limitations/implicationsThis study aims to provide a new perspective to the literature by conducting multimethod qualitative research within the scope of the risks experienced by digital nomads and their travel insurance behavior. The study shows that digital nomads cannot escape from national regulations. They have to take out insurance in countries with low cost of living due to problems with the health system and security, and in some countries, it is due to country regulations. In practice, the study provides conclusions and recommendations for current and potential digital nomads, insurance companies and governments regarding the insurance behavior of digital nomads. In particular, the study concludes with recommendations for insurance companies in terms of insurance product development and the use of social policy tools for governments.Originality/valueThis study offers a perspective on the key factors underlying the travel insurance behavior of digital nomads.