Rapid Adoption Research Articles

Impact and perceptions of distance learning among undergraduate nursing students: An exploratory cross-sectional study in Saudi Arabia

The COVID-19 pandemic necessitated the rapid adoption of e-learning in education. Nursing students, unprepared for this shift, faced unique challenges. This study explored these challenges and influencing factors using a 53-item questionnaire completed by 184 nursing students in Saudi Arabia. Data was analyzed with SPSS version 21 at a 0.05 significance level. Most students (71%) showed positive attitudes towards e-learning, finding it useful (mean score: 3.26±0.88), with links to self-efficacy (mean score: 3.04±0.82) and time-management (mean score: 3.39±0.73). Barriers included inadequate infrastructure and technical support (mean score: 3.14±1.3), lack of training (mean score: 3.03±1.3), and poor internet connections (mean score: 3.92±1.3). Students reported uneasiness (mean score: 2.77±1.5), confusion (mean score: 2.64±1.4), stress, and nervousness (mean score: 2.55±1.4). Younger students and females showed more positive attitudes towards e-learning (p-values < 0.01 and < 0.001, respectively). Despite positive attitudes, anxiety due to lack of training and infrastructure readiness persisted. Addressing these issues is crucial to enhance the effectiveness of e-learning.

Finding Our Lanes: A Roadmap for Collaboration Between Academic Medical Centers and Behavioral Telehealth Companies.

Outpatient mental health care in the United States is delivered by an uncoordinated patchwork of public and private entities that struggle to effectively differentiate the care they provide. The COVID-19 pandemic catalyzed transformative changes in this space, including rapid adoption of telehealth and escalating private sector investment to provide services for individuals wishing to obtain care through insurance. In this article, we briefly review the current landscape of ambulatory mental health care. Utilizing Kissick's Iron Triangle model of health care delivery, we compare the relative strengths and weaknesses of academic medical centers and the growing private sector, entities potentially positioned to synergistically foster a mental health ecosystem with improved quality, access, and cost-effectiveness. A roadmap for strategic integration is presented for how academic centers-institutions frequently overwhelmed by patient volume-might leverage partnerships with a private sector eager to utilize novel technology to improve access, demonstrate data-driven outcomes, and advocate for improved reimbursement from payers. We also assess the potential risks and pitfalls of such collaboration. In return, academic institutions can refocus on their strengths, including research, systems knowledge, quality-improvement initiatives, education and training, and specialty clinical care.

Automated Security Testing in DevOps Environments Using AI and ML

The rapid adoption of DevOps practices has transformed the software development landscape by emphasizing continuous integration, continuous delivery (CI/CD), and agile methodologies. However, this rapid pace of development often introduces significant security challenges, as traditional security testing methods struggle to keep up with the accelerated release cycles. To address these challenges, the integration of Artificial Intelligence (AI) and Machine Learning (ML) into automated security testing has emerged as a promising solution. This paper explores the use of AI and ML to enhance automated security testing within DevOps environments, offering a comprehensive approach to identifying, predicting, and mitigating security vulnerabilities in real time. Automated security testing leverages AI and ML algorithms to analyze code, detect anomalies, and predict potential security threats. These technologies enable the continuous monitoring of codebases, allowing for the early identification of vulnerabilities before they are exploited. By incorporating AI-driven security testing into the CI/CD pipeline, organizations can ensure that security is not an afterthought but a continuous process integrated into every stage of the software development lifecycle. AI and ML models can be trained to recognize patterns associated with security risks, such as code injection, unauthorized access, and data leakage. These models continuously learn from new data, improving their accuracy over time and adapting to evolving threats. The dynamic nature of AI-driven security testing makes it particularly suited for DevOps environments, where frequent code changes and updates can introduce new vulnerabilities. Moreover, AI and ML can assist in automating complex tasks, such as threat modeling, risk assessment, and the prioritization of security issues, enabling security teams to focus on higher-order tasks that require human expertise.

Limited waterpower contributed to rise of steam power in British "Cottonopolis".

The Industrial Revolution precipitated a pivotal shift from waterpower to coal-fueled steam power in British textile mills. Although it is now widely accepted that steam was chosen to power factories despite the availability of sufficient waterpower resources across most of Britain, the location and suitability of that waterpower during the early 19th century remain underexplored. Here, we employ quantitative fluvial geomorphology alongside historical climate data, factory records, and a catalog of over 26,000 mill sites to reveal that waterpower was abundant for most of early 19th century Britain, except in the central hub of British cotton production: Greater Manchester in the Mersey Basin. Our findings show that surging factory mechanization and overcrowding on key waterways in the Mersey Basin compounded waterpower scarcity arising from a drier 19th century climate. Widespread adoption of coal-fueled steam engines in certain key industrial centers of Britain was a strategy aimed at ameliorating some of the reduced reliability of waterpower. The fact that steam engines were frequently used in water-powered factories in many industrial regions until the third quarter of the 19th century to recirculate water to provide that power, or as a power supplement when waterpower availability was restricted, adds further weight to our argument. Rapid adoption of coal-powered steam engines reshaped the social and structural landscape of industrial work, firmly established Britain's prominence as an industrial powerhouse, and had lasting global industrial and environmental impacts.

CMAPLE: efficient phylogenetic inference in the pandemic era.

We have recently introduced MAPLE (MAximum Parsimonious Likelihood Estimation), a new pandemic-scale phylogenetic inference method exclusively designed for genomic epidemiology. In response to the need for enhancing MAPLE's performance and scalability, here we present two key components: (1) CMAPLE software, a highly optimized C++ reimplementation of MAPLE with many new features and advancements; and (2) CMAPLE library, a suite of Application Programming Interfaces to facilitate the integration of the CMAPLE algorithm into existing phylogenetic inference packages. Notably, we have successfully integrated CMAPLE into the widely used IQ-TREE 2 software, enabling its rapid adoption in the scientific community. These advancements serve as a vital step towards better preparedness for future pandemics, offering researchers powerful tools for large-scale pathogen genomic analysis.

COVID-19 significantly impacted initial consultation for idiopathic scoliosis.

Since the outbreak of the COVID-19 pandemic, reduction of social activities and rapid adoption of telemedicine, decreasing face-to-face encounters seems to have negatively affected the timely Idiopathic Scoliosis (IS) referral with a spine specialist. We aim to document the progression of IS curves during COVID-19 pandemic reflected by the late presentation of patients at the initial visit with higher Cobb angles and to evaluate its influence on health-related quality of life scores. All IS patients scheduled for surgery between April 2019 and September 2021 were recruited in a prospective cohort study. The patients were divided into five cohorts of 6month duration each according to their booking date: 2 periods before the 1st COVID-19 wave, one period during and two periods afterwards. In each cohort, patients were divided into 3: those who were scheduled for posterior spinal fusion (PSF) at 1st visit, those booked for vertebral body tethering (VBT) at 1st visit, and those scheduled for surgery but who have failed brace treatment. Variables included age, gender, Risser grade and preoperative SRS-22 scores. Chi2 and ANOVA tests were used for comparison. 173 patients were analyzed. 33 patients (13.1 ± 3 y.o.) were scheduled between Apr and Sept 2019; 38 (13.1 y.o. ± 2) between Oct 2019 and Mar 2020; 31 (13.4 ± 3 y.o.) between Apr and Sept 2020; 30 (14.3 ± 2 y.o.) between Sept 2020 and Mar 2021; and 41 patients (13.8 ± 2 y.o.) between Apr and Sept 2021. Non-statistically significant differences were found between periods before, during or after the COVID-19 first wave regarding patients' age, gender, Risser grade and SRS-22 scores. Average Cobb angles of patients at their 1st visit after the beginning of the COVID-19 pandemic were significantly higher than those before COVID-19 (52.2° ± 7° and 56.6° ± 13° vs 47.8° ± 12° and 45.2° ± 13°; p = 0.0001). More patients were booked for PSF (p < 0.0000) through the five evaluated periods, while the indication of VBT or surgery in patients previously braced progressively decreased. Patients presented at the scoliosis clinic for the 1st time after the 1st COVID-19 wave with significantly larger Cobb angles, and likely contributed to an increased proportion of PSF, as the potential window for bracing or VBT was missed due to a delayed consultation.

Reverse social contagion as a mechanism for regulating mass behaviors in highly integrated social systems.

Mass behavior is the rapid adoption of similar conduct by all group members, with potentially catastrophic outcomes such as mass panic. Yet, these negative consequences are rare in integrated social systems such as social insect colonies, thanks to mechanisms of social regulation. Here, we test the hypothesis that behavioral deactivation between active individuals is a powerful social regulator that reduces energetic spending in groups. Borrowing from scaling theories for human settlements and using behavioral data on harvester ants, we derive ties between the hypermetric scaling of the interaction network and the hypometric scaling of activity levels, both relative to the colony size. We use elements of economics theory and metabolic measurements collected with the behavioral data to link activity and metabolic scalings with group size. Our results support the idea that metabolic scaling across social systems is the product of different balances between their social regulation mechanisms.

Revisiting the current and emerging concepts of postharvest fresh fruit and vegetable pathology for next-generation antifungal technologies.

Fungal infections of fresh fruits and vegetables (FFVs) can lead to safety problems, including consumer poisoning by mycotoxins. Various strategies exist to control fungal infections of FFVs, but their effectiveness and sustainability are limited. Recently, new concepts based on the microbiome and pathobiome have emerged and offer a more holistic perspective for advancing postharvest pathogen control techniques. Understanding the role of the microbiome in FFV infections is essential for developing sustainable control strategies. This review examines current and emerging approaches to postharvest pathology. It reviews what is known about the initiation and development of infections in FFVs. As a promising concept, the pathobiome offers new insights into the basic mechanisms of microbial infections in FFVs. The underlying mechanisms uncovered by the pathobiome are being used to develop more relevant global antifungal strategies. This review will also focus on new technologies developed to target the microbiome and members of the pathobiome to control infections in FFVs and improve safety by limiting mycotoxin contamination. Specifically, this review stresses emerging technologies related to FFVs that are relevant for modifying the interaction between FFVs and the microbiome and include the use of microbial consortia, the use of genomic technology to manipulate host and microbial community genes, and the use of databases, deep learning, and artificial intelligence to identify pathobiome markers. Other approaches include programming the behavior of FFVs using synthetic biology, modifying the microbiome using sRNA technology, phages, quorum sensing, and quorum quenching strategies. Rapid adoption and commercialization of these technologies are recommended to further improve the overall safety of FFVs.

Watching intensity and media franchise engagement

The rapid adoption of online streaming and over-the-top services has fundamentally changed at-home entertainment media consumption and given rise to new behaviors which are often characterized by a high intensity of watching (e.g., binge-watching). In this paper, we investigate how the watching intensity affects consumers’ engagement with media franchises in two areas: personal and interactive engagement. The former involves consumers’ adoption and consumption of franchise extensions and the latter concerns consumers’ content generation related to a focal media product they watched. Using individual-level data from an online anime (Japanese cartoons) platform, we find inverse U-shaped effects of watching intensity with the largest effects around three to five hours of watching per day on personal engagement and two to four hours a day on interactive engagement. The positive effects of watching intensity are larger for sequels than other types of franchise extensions. For interactive engagement, our results show that conditional on rating submission, higher watching intensity is associated with higher valence of anime ratings, the most prevalent form of UGC on the platform. We interpret this result as evidence that watching intensity can induce liking.

Factors Associated with Overweight/Obesity among Rural Secondary School Children in Bangladesh

Background &amp; Objective: Unhealthy dietary patterns in combination with a sedentary lifestyle could be contributing to some major health issues worldwide. Obesity in children and adolescents can have short- and long-term adverse health consequences including early mortality. Although previously limited to urban areas, with the rapid adoption of urban lifestyle by the rural people the problem is now ubiquitous. It is difficult to develop a policy for promoting health and reducing obesity among adolescents living in rural regions since there is a lack of information on the factors that contribute to this problem. The present study was, therefore undertaken to evaluate the factors influencing overweight and obesity among rural adolescents. Methods: This cross-sectional study was done based on data collected by students of Rajshahi Medical College as part of their RFST (Rural Field-site Training) in 2019 from a rural area of Rajshahi, Bangladesh. A total of 535 students from two rural secondary schools participated in the study. Every alternate student of those schools from class VI-X was then included in the study as a respondent. The weight and height of the selected students were first taken followed by data collection on variables of interest. Using weight and height data, the body mass index (BMI) of the respondents was first determined and was plotted on a growth chart (recommended by CDC, Atlanta) to find the percentile. Then the nutritional status of the individual respondents was determined based on their percentile status and was classified as underweight, normal, overweight, or obese. Results: Almost one-fifth (18.2%) of the respondents was found overweight or obese. Upon comparing respondents’ demographic characteristics, food and exercise behaviour between overweight &amp; obese and normal &amp; underweight groups, the former group was found younger than the latter group. Respondents’ socioeconomic status (SES) was associated with their nutritional status with overweight &amp; obese adolescents being significantly higher in the Middle- and rich SES group (78.4%) than in the poor and lower middle-class (61.4%). Neither dietary nor exercise behaviour was associated with the nutritional status of the respondents. Although the majority (84.2%) of normal &amp; underweight adolescents preferred low to medium-calorie snacks, overweight and obese adolescents were more likely to choose high-calorie snacks. Fast walking and running were the more common forms of exercise behaviour and of longer duration among the overweight &amp; obese cohort than those among normal &amp; underweight cohorts. Conclusion: The study concluded that the period of early adolescence is vulnerable to developing obesity. Adolescents belonging to middle and well-off SES are more prone to be overweight or obese than those belonging to lower middle &amp; poor SES. However, exercise, physical activity, and dietary habits of adolescents do not influence their nutritional status. Ibrahim Card Med J 2023; 13 (1&amp;2): 19-25

The Complete Inpatient Record Using Comprehensive Electronic Data (CIRCE) project: A team‐based approach to clinically validated, research‐ready electronic health record data

AbstractIntroductionThe rapid adoption of electronic health record (EHR) systems has resulted in extensive archives of data relevant to clinical research, hospital operations, and the development of learning health systems. However, EHR data are not frequently available, cleaned, standardized, validated, and ready for use by stakeholders. We describe an in‐progress effort to overcome these challenges with cooperative, systematic data extraction and validation.MethodsA multi‐disciplinary team of investigators collaborated to create the Complete Inpatient Record Using Comprehensive Electronic Data (CIRCE) Project dataset, which captures EHR data from six hospitals within the University of Pennsylvania Health System. Analysts and clinical researchers jointly iteratively reviewed SQL queries and their output to validate desired data elements. Data from patients aged ≥18 years with at least one encounter at an acute care hospital or hospice occurring since 7/1/2017 were included. The CIRCE Project includes three layers: (1) raw data comprised of direct SQL query output, (2) cleaned data with errors removed, and (3) transformed data with standardized implementations of commonly used case definitions and clinical scores.ResultsBetween July 1, 2017 and December 31, 2023, the dataset captured 1 629 920 encounters from 740 035 patients. Most encounters were emergency department only visits (n = 965 834, 59.3%), followed by inpatient admissions without an intensive care unit admission (n = 518 367, 23.7%). The median age was 46.9 years (25th–75th percentiles = 31.1–64.7) at the time of the first encounter. Most patients were female (n = 418 303, 56.5%), a significant proportion were of non‐White race (n = 272 018, 36.8%), and 54 625 (7.4%) were of Hispanic/Latino ethnicity.ConclusionsThe CIRCE Project represents a novel cooperative research model to capture clinically validated EHR data from a large diverse academic health system in the greater Philadelphia region and is designed to facilitate collaboration and data sharing to support learning health system activities. Ultimately, these data will be de‐identified and converted to a publicly available resource.

Revolutionizing smart grid-ready management systems: A holistic framework for optimal grid reliability

Existing energy management systems are becoming increasingly insecure and inefficient due to the rapid adoption of smart grid technology. Current research indicates that effectively managing dynamic energy flows, adjusting to changing needs, and protecting against new cyber threats remain significant challenges for the smart grid system. An advanced and comprehensive plan for managing smart grids is therefore required, capable of addressing these delicate and multifaceted problems. The proposed framework addresses these challenges through unifying several key aspects, it includes an advanced data acquisition system that captures real-time data from various grid sources, enabling comprehensive energy monitoring and dynamic flow analysis. By integrating predictive algorithms, the framework provides precise energy demand forecasting, which is essential for adaptive grid management. A significant contribution is the incorporation of an AI-based module for diagnostics and prognostics, which leverages machine learning techniques to shift from reactive to proactive maintenance strategies. The optimal power flow (OPF) optimization module represents a central component of the framework. It employs advanced computational methods to ensure efficient and cost-effective power distribution, particularly in grids incorporating renewable energy sources. Additionally, the architectural framework is strengthened by a robust cybersecurity module designed to safeguard against a wide range of cyber threats, maintaining the integrity of both operational and consumer data. This paper also addresses practical implementation challenges such as compatibility with existing infrastructure, investment costs, and the need for specialized training. This solution represents a new benchmark for smart grid operations, ensuring more sustainable and efficient energy systems.

Distributed Maritime Operations and the Medical Challenge: How a Medical Common Operating Picture Can Help Bridge the Gap.

This work explores the challenges of delivering medical care in the geographically dispersed and resource-constrained environment of Distributed Maritime Operations (DMO) and Expeditionary Advanced Base Operations (EABO). Traditional medical planning approaches may struggle to adapt to the vast operational space, extended evacuation times, and limited medical force present in these scenarios. The concept of a Medical Common Operating Picture (COP) emerges as a potential solution. By providing a shared view of the medical situation across the theater, encompassing logistics, personnel, and patient data, a medical COP has the potential to facilitate medical command and control (MED C2) in DMO/EABO. The implementation of a medical COP has the potential to optimize resource allocation, enhance situational awareness, streamline medical evacuation, and reduce healthcare provider moral injury in large-scale combat operations. A medical COP will allow medical planners to make informed decisions on triage, resupply, and evacuation, ensuring the best use of limited medical resources. This is done by leveraging a comprehensive understanding of the medical landscape, enabling informed clinical and operational decision-making by humanitarian and combat personnel respectively. A fully realized medical COP system will enable a dynamic theater evacuation policy, balancing the conflicting needs of patient care at higher echelons with the operational expediency of returning servicemembers to their operational units, thereby maximizing evacuation effectiveness. It will further enable medical personnel to perform dynamic casualty triage based on operational realities, mitigating potential ethical dilemmas. Implementing such a medical COP system will require overcoming communication limitations to facilitate data exchange and potentially integrating clinical decision support tools for real-time data analysis and recommendations. It will also require the rapid adoption of modernized operational medicine documentation solutions by medical assets within the operational forces. Ultimately, this work suggests that a medical COP has the potential to bridge the gap between traditional medical planning and the unique demands of DMO/EABO, ultimately optimizing casualty care, maximizing resource efficiency, and preserving the fighting force.

Paying attention to safety of posterior chamber phakic intraocular lens implantation

Posterior chamber phakic intraocular lens implantation is a type of intraocular surgery. With advancements in implant materials and design, this procedure has seen rapid adoption and widespread use in ophthalmology clinics in recent years. However, the changes in surgical techniques and the occurrence of postoperative complications have raised safety concerns that require significant attention in clinical practice. This paper aims to address the key factors influencing the safety of posterior chamber phakic intraocular lens implantation, exploring relevant characteristics, mechanisms, and current challenges. By emphasizing the importance of this surgery and proposing effective measures, it aims to provide guidance for clinical practice, enhance the safety of posterior chamber phakic intraocular lens implantation, and foster the healthy advancement of this surgical technique.

The linguistic leap: Understanding, evaluating, and integrating AI in language education

The landscape of language education is undergoing a pivotal transformation, spurred by the integration of Generative Artificial Intelligence (Gen-AI) into every facet of traditional and new methodologies and practices. Given the rapid societal adoption of AI, we believe that all language instructors – from the most technologically savvy to the most tech-averse – must engage critically and ethically with AI. To ensure that AI tools are brought into language education in pedagogically appropriate and ethical ways, we have developed two large projects at our university: 1) an AI Working Group in our Modern Languages Department and 2) a chatbot that all instructors can incorporate into their classroom practices. In this article, we describe the rationale for these projects and the steps we took to implement them. We hope that this work can help other departments come together to address the challenges and achieve a balance between technological advancement and the intrinsically human facets of language education.

The Dynamics of Rewards and Penalties: Governmental Impact on Green Packaging Adoption in Logistics

The widespread use of traditional packaging materials poses significant environmental challenges. Adopting green packaging is essential for reducing pollution and conserving natural resources. This paper aims to examine the effectiveness of government incentives and penalties in promoting the adoption of green packaging by logistics companies. We developed an evolutionary game theory model that involves governments and logistics companies, comparing the impacts of static and dynamic reward and penalty policies. The results indicate that (1) static policies often lead to oscillatory adoption rates of green packaging without achieving a stable equilibrium, while dynamic policies generally promote steadier adoption of sustainable practices. (2) Different combinations of dynamic policies have varying influences on logistics companies’ propensity to adopt green packaging solutions. Specifically, dynamic rewards and static penalties are particularly effective at encouraging logistics companies to adopt green packaging. (3) A combination of dynamic rewards and penalties tends to facilitate more rapid and consistent adoption of green packaging by logistics companies. (4) An increase in government supervision costs is associated with reduced regulatory actions and a lower prevalence of green packaging. These insights are critical for policymakers aiming to craft regulations that successfully encourage sustainability within logistics operations.

Operational Risks Faced by Financial Institutions in the Digital Age: A Case of Nigeria

Purpose: The aim of the study was to examine operational risks faced by financial institutions in the digital age: a case of Nigeria. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study found that financial institutions in Nigeria are confronted with a myriad of operational risks in the digital age, stemming from the rapid adoption of technology and the evolving cyber threat landscape. The shift towards digital banking and fintech innovations has introduced new vulnerabilities, including cyberattacks, data breaches, and fraudulent activities, posing significant challenges to the security and integrity of financial systems in Nigeria. Operational risks associated with technological disruptions, such as system failures, IT outages, and disruptions to digital payment platforms, can undermine the reliability and efficiency of financial services, leading to customer dissatisfaction and financial losses. The proliferation of mobile banking and digital payment channels has heightened concerns about financial inclusion, data privacy, and regulatory compliance, necessitating robust risk management frameworks and regulatory oversight to safeguard the stability and resilience of Nigeria's financial sector. Unique Contribution to Theory, Practice and Policy: Technology Acceptance Model (TAM), Agency Theory &amp; Resource Dependence Theory may be used to anchor future studies on operational risks faced by financial institutions in the digital age: a case of Nigeria. Financial institutions should prioritize the implementation of robust cybersecurity measures, including regular security audits, penetration testing, and employee training programs. By enhancing cybersecurity awareness and preparedness, institutions can mitigate the risk of cyberattacks and data breaches. Regulatory authorities play a crucial role in shaping the regulatory landscape to address operational risks in the Digital Age. Policymakers should collaborate with industry stakeholders to develop robust regulatory frameworks that promote innovation while safeguarding financial stability and consumer protection.

India's Digital Transformation: Opportunities and Challenges in the Digital Economy

India's digital transformation has emerged as a critical driver of economic growth, innovation, and social development. This paper explores the opportunities and challenges presented by India's digital economy. With the government's Digital India initiative and the rapid adoption of digital technologies, India stands at the forefront of global digital innovation. However, challenges such as digital divide, cybersecurity threats, and regulatory complexities pose significant hurdles to realizing the full potential of India's digital transformation. By analyzing current trends, identifying key opportunities, and addressing challenges, this study aims to provide insights into India's digital economy and its impact on various sectors.

Preferences for Remote and Hybrid Work: Evidence from the COVID-19 Pandemic

The COVID-19 pandemic created an opportunity for many American workers to work from home. Did the rapid and widespread adoption of remote work arrangements influence workers’ preferences? This study analyzes the early pandemic work experiences of 52 participants (20 men and 32 women) in dual-earner households with children through in-depth interviews conducted in 2021 and 2022 via Zoom. The study explores respondents’ desire for remote and hybrid work, considering job satisfaction as well as job characteristics, family structure, and household organization. Unless their jobs were poorly suited to remote work, most workers with pandemic-era remote work opportunities—and even some who had not worked remotely—wished to keep remote access in their post-pandemic work arrangements. Respondents reported enhanced job satisfaction and productivity from remote work, as a result of greater schedule control and flexibility. We found that some workers were willing to change jobs to maintain their preferred work arrangement, while others acquiesced to employers’ return-to-work policies. The study highlights the need to understand workers’ preferences in supporting flexible work arrangements and contributes to the understanding of remote work on family dynamics during the pandemic and afterwards.

The Emerging and Disruptive Technologies – A Risk-Based Approach

Abstract The accelerating pace of technological advance and its emergent and disruptive trends related to new innovations and adopted technologies have a great impact on our society. The technological, geopolitical, environmental, economic, and disruptive trends are expected to reshape the evolution of businesses and how people interact with each other. Negative effects, threats, vulnerabilities, and consequences of a rapid adoption and implementation of any emerging technologies lead to specific risks which require organizations to rethink their strategy, governance and architecture of the business models. This paper aims to emphasize the adoption evolution and implementation effects of emerging and disruptive technologies that could lead to certain challenges in the majority of fields of activity. A bibliometric analysis was conducted in order to highlight the associated risks and consequences that could result from disruptive trends concerning the adoption and implementation over time of the emerging and disruptive technologies.