A systematic review of trustworthy artificial intelligence applications in natural disasters

Computers & Electrical Engineering, Год журнала: 2024, Номер 118, С. 109409 - 109409

Опубликована: Июнь 29, 2024

Artificial intelligence (AI) holds significant promise for advancing natural disaster management through the use of predictive models that analyze extensive datasets, identify patterns, and forecast potential disasters. These facilitate proactive measures such as early warning systems (EWSs), evacuation planning, resource allocation, addressing substantial challenges associated with This study offers a comprehensive exploration trustworthy AI applications in disasters, encompassing management, risk assessment, prediction. research is underpinned by an review reputable sources, including Science Direct (SD), Scopus, IEEE Xplore (IEEE), Web (WoS). Three queries were formulated to retrieve 981 papers from earliest documented scientific production until February 2024. After meticulous screening, deduplication, application inclusion exclusion criteria, 108 studies included quantitative synthesis. provides specific taxonomy disasters explores motivations, challenges, recommendations, limitations recent advancements. It also overview techniques developments using explainable artificial (XAI), data fusion, mining, machine learning (ML), deep (DL), fuzzy logic, multicriteria decision-making (MCDM). systematic contribution addresses seven open issues critical solutions essential insights, laying groundwork various future works trustworthiness AI-based management. Despite benefits, persist In these contexts, this identifies several unused used areas disaster-based theory, collects ML, DL techniques, valuable XAI approach unravel complex relationships dynamics involved utilization fusion processes related Finally, extensively analyzed ethical considerations, bias, consequences AI.

Язык: Английский

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Co-Creating Value With Artificial Intelligence: A Bibliometric Approach to the Use of AI in Open Innovation Ecosystems

IEEE Access, Год журнала: 2024, Номер 12, С. 56860 - 56871

Опубликована: Янв. 1, 2024

Open innovation, which blurs the boundaries of organizations using inflows and outflows knowledge to boost their innovation processes, has transformed paradigm, evolving from higher degrees protectionism cooperative relationships. Nevertheless, frequently management huge amount information data generated in an open ecosystem requires use communication technologies. In this context, artificial intelligence can be a major help profit all opportunities derived innovation. Considering growing body academic literature dealing with tools context environments, objective article is revealing main references, trends hottest topics subject, disentangling structure research through bibliometric analysis carried out over 63 papers selected Web Science database, both co-word bibliographic coupling. The recent burst production anticipates potentially massive interest topic, studied by at three different levels (operational, managerial, social). This study reveals existence relevant opportunities, specially related potential conflicts that may stem fuzzy ownership intelligence, roles agents such context.

Язык: Английский

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Company Cybersecurity System: Assessment, Risks and Expectations

Production Engineering Archives, Год журнала: 2023, Номер 29(4), С. 379 - 392

Опубликована: Окт. 27, 2023

Abstract The consequences of Industry 4.0 have adverse side effects on cybercrime growth, which requires creating an effective cybersecurity system for companies. Therefore, this study aims to develop a composite indicator company assess its development needs. For purpose, the authors modified Porter’s method by constructing superposition matrix based growth rates cyber threats and risks, calculating their quantitative characteristics indicator. computations are indicators 2016-2022 characterizing vulnerabilities threats: share companies experiencing one, six or more successful cyberattacks, considering likely very success cyberattacks them in next 12 months, security threat concern indices, with growing budget affected ransomware shortage skilled IT personnel, cost stolen compromised credentials. As result, needs increased significantly 2020-2022, mainly due digital transformation after COVID-19 pandemic. A comparative analysis proposed those showed that need reliable is much important than active modern technologies. Spending also increasing, but not enough meet development, except 2022 results. defined worldwide, versatility allows methodology be applied enterprises various industries sizes.

Язык: Английский

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Research on the impact of artificial intelligence technology on urban public health resilience

Frontiers in Public Health, Год журнала: 2025, Номер 12

Опубликована: Янв. 7, 2025

Urban public health resilience has become a critical focus in the transition to high-quality development, especially addressing increasing challenges. This study explores role of artificial intelligence (AI) technology enhancing urban across 284 Chinese cities from 2011 2021. Using comprehensive index based on resistance, recovery, and innovation dimensions, quantifies AI levels through patent applications authorizations, further disaggregating these into invention, utility model, design patents. A two-way fixed effects regression model spatial econometric models are employed analyze direct spillover systems. The results demonstrate that significantly enhances by improving resource allocation response efficiency, with stronger impacts observed eastern central regions compared western regions, where economic technological capacities weaker. Spatial analysis reveals significant positive effects, particularly which enhance neighboring cross-regional collaboration sharing. Despite advancements, regional disparities development infrastructure limit AI's broader impact, underscoring need for targeted policies, enhanced funding, interdisciplinary training bridge digital divide. findings highlight transformative potential fostering call sustained investment maximize its benefits.

Язык: Английский

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Leveraging AI in recruitment: enhancing intellectual capital through resource-based view and dynamic capability framework

Journal of Intellectual Capital, Год журнала: 2025, Номер unknown

Опубликована: Янв. 25, 2025

Purpose The rapid evolution of artificial intelligence (AI) is revolutionizing organizational operations and altering competitive landscapes. This study examines the influence resources on AI adoption in recruitment, focusing their role achieving advantage through effective implementation. Design/methodology/approach research utilizes a cross-sectional quantitative approach, applying partial least squares structural equation modeling (PLS-SEM) to data from 290 human resource (HR) professionals. It grounded resource-based view (RBV) dynamic capability framework (DCF). Findings results reveal that HR competencies open innovation significantly capabilities, which are essential for integration, supported by financial support information technology (IT) infrastructure. These capabilities enable adoption, leading advantage. Research limitations/implications this captures current landscape providing snapshot present scenario rapidly evolving technological environment. Practical implications offers professionals managers strategic guidance effectively integrating into recruitment processes. By enhancing competencies, fostering collaboration ensuring sufficient infrastructural support, organizations can navigate challenges secure landscape. Social reduce biases, enhance diversity improve fairness standardized assessments. However, as technologies evolve, continuous oversight ensure ethical use modify systems needed, further reducing biases addressing societal concerns AI-driven Originality/value introduces novel underscores importance expertise with advanced tools successful A key contribution not only facilitate integration but also accuracy, accountability configure most suitable collaborating developers meet specific needs organization.

Язык: Английский

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Intellectual Property Management in Open Innovation

IGI Global eBooks, Год журнала: 2025, Номер unknown, С. 227 - 254

Опубликована: Фев. 21, 2025

Open innovation represents a paradigm shift in the way organizations approach research and development, emphasizing value of external ideas collaborations alongside internal efforts. This model acknowledges that valuable knowledge expertise are often dispersed outside organizational boundaries, leveraging these sources can significantly enhance outcomes. By engaging with customers, suppliers, academic institutions, even competitors, tap into broader pool ideas, technologies, insights, ultimately driving more effectively efficiently. collaborative is particularly relevant today's fast-paced competitive landscape, where rapid evolution technology changing consumer preferences necessitate agile adaptive strategies. Organizations must establish robust IP strategies not only protect their innovations but also facilitate collaboration.

Язык: Английский

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Government policy on ensuring food security: Bibliometric analysis

Problems and Perspectives in Management, Год журнала: 2025, Номер 23(1), С. 496 - 514

Опубликована: Март 19, 2025

Understanding the role of government policy in advancing sustainable development goals and food sovereignty is key to building security system resilience. This study leverages bibliometric analysis Scopus data using tools like Biblioshiny explore global research trends on interrelationship between policies agrarian sector security. The methodology involves structured collection, cleaning, metadata keywords, revealing growth publications since 1980s, with significant increases post-2000 due heightened concerns. peak publication 2023 connected war Ukraine, disruptions it caused security, functioning grain corridor agreements. From 1922 2000, studies focused broad themes agricultural Between 2001 2010, attention shifted markets, sovereignty, production, Common Agricultural Policy. 2011 2025, expanded climate-smart agriculture, dietary diversity, foreign investment, technological advancements remote sensing, highlighting technology’s growing core such as “agricultural policy,” “food security,” “climate change,” “sustainable agriculture” emerged dominant areas focus. Advanced topics “machine learning,” “remote sensing,” “climate-smart highlight a shift toward data-driven, technologically integrated solutions for China USA were identified leading contributors, producing most participating highest number international collaborations.

Язык: Английский

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Unveiling Critical Innovation Factors in Sustainable Coffee Production: A Colombian Perspective

Production Engineering Archives, Год журнала: 2024, Номер 30(4), С. 431 - 441

Опубликована: Ноя. 21, 2024

Abstract The coffee sector stands as a cornerstone of Colombia’s economy, ranking third in the nation’s export portfolio. Despite Colombian esteemed global reputation, it has yet to fully exploit its potential for diversification into differentiated products. Present agro-industrial paradigms emphasize trade and sustainable, efficient agricultural practices, underscoring imperative innovation across production, marketing, distribution channels. This study aims pinpoint pivotal factors within farm production processes. To this end, sample 66 farms was selected through simple random sampling. Drawing from 2018 Oslo model, types associated with sustainable specialty certifications were delineated. Within framework, seven fundamental emerged investigation: economic, social, environmental, knowledge, technology, change management. Through cluster analysis, became evident that technological, management are indispensable fortifying industry.

Язык: Английский

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Artificial Intelligence in Open Innovation Project Management: A Systematic Literature Review on Technologies, Applications, and Integration Requirements

Journal of Open Innovation Technology Market and Complexity, Год журнала: 2024, Номер unknown, С. 100445 - 100445

Опубликована: Ноя. 1, 2024

Язык: Английский

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Navigating innovation in the age of AI: how generative AI and innovation influence organizational performance in the manufacturing sector

Journal of Manufacturing Technology Management, Год журнала: 2024, Номер unknown

Опубликована: Дек. 12, 2024

Purpose Generative artificial intelligence (GenAI) is one of the most diffused AI technologies, capable generating manifold forms content, including music, text, images and synthetic data. The purpose this study to analyze determinants that affect GenAI acceptance its outcomes on both explorative exploitative innovation. Design/methodology/approach employs a conceptual framework based technology-organization-environment (TOE) paradigm. Through Smart-PLS analysis, it examines empirical data retrieved from an online survey where 302 manufacturing companies took part. Findings It found has potential facilitate exploratory innovation, particularly via moderating effect environmental dynamism. Hence adoption improve organizational performance. Originality/value first project investigate factors influence firms' GenAI. As have integrated TOE paradigm when examining impact dynamism emphasizes double innovation in performance improvement.

Язык: Английский

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