The impact of artificial intelligence (AI) on employees’ skills and well-being in global labor markets: A systematic review

Oeconomia Copernicana, Journal Year: 2023, Volume and Issue: 14(3), P. 731 - 767

Published: Sept. 30, 2023

Research background: This article discusses how artificial intelligence (AI) is affecting workers' personal and professional lives, because of many technological disruptions driven by the recent pandemic that are redefining global labor markets. Purpose article: The objective this paper to develop a systematic review relevant literature identify effects change, especially adoption AI in organizations, on employees’ skills (professional dimension) well-being (personal dimension). Methods: To implement research scope, authors relied Khan's five-step methodology, which included PRISMA flowchart with embedded keywords for selecting appropriate quantitative data study. Firstly, 639 scientific papers published between March 2020 2023 (the end COVID-19 according WHO) from Scopus Web Science (WoS) databases were selected. After applying procedures techniques, 103 articles retained, focused dimension, while 35 component. Findings & value added: Evidence has been presented highlighting difficulties associated ongoing requirement upskilling or reskilling as an adaptive reaction changes. efforts counterbalance skill mismatch impacted employees' challenging times. Although emphasis digital widely accepted, our investigation shows topic still not properly developed. paper's most significant contributions found thorough analysis affects well-being, representative aspects researched academic due paradigm changes generated continuous disruptions.

Language: Английский

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Artificial intelligence algorithms and cloud computing technologies in blockchain-based fintech management

Oeconomia Copernicana, Journal Year: 2023, Volume and Issue: 14(3), P. 707 - 730

Published: Sept. 30, 2023

Research background: Fintech development shapes corporate investment efficiency and economic growth with innovative tools, can decrease financing constraints of enterprises, enabling direct indirect furthering inter-bank competition. Crowdfunding- blockchain-based fintech operations harness deep maching learning algorithms, augmented virtual reality technologies, big data analytics in mobile payment transactions. Purpose the article: We show that fintechs have reconfigured financial service delivery by harnessing AI-based data-driven algorithms cloud blockchain technologies. optimizes organization services, structures growth, analysis, digital banking performance. Machine streamline operation capabilities process promptness, ensuring smooth operational flows, assessing risks, detecting frauds money laundering historical customer behavior analysis across instant networks infrastructures. Methods: Quality tools: AXIS, Eppi-Reviewer, PICO Portal, SRDR. Search period: July 2023. terms: “fintech” + “artificial intelligence algorithms”, “cloud computing technologies”, “blockchain technologies”. Selected sources: 40 out 195. Published research inspected: Data visualization Dimensions VOSviewer. Reporting quality assessment tool: PRISMA. Findings & value added: enables organizational innovation mitigating information asymmetry limitations while providing assistance tax incentives relation to products services. The has influenced dynamic intermediary function institutions terms sustainability development. natural resources negatively influence, green innovations further, environmental sustainability.

Language: Английский

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Digital Twin Simulation Tools, Spatial Cognition Algorithms, and Multi-Sensor Fusion Technology in Sustainable Urban Governance Networks

Mathematics, Journal Year: 2023, Volume and Issue: 11(9), P. 1981 - 1981

Published: April 22, 2023

Relevant research has investigated how predictive modeling algorithms, deep-learning-based sensing technologies, and big urban data configure immersive hyperconnected virtual spaces in digital twin cities: tools, monitoring Internet-of-Things-based decision support systems articulate big-data-driven geopolitics. This systematic review aims to inspect the recently published literature on simulation spatial cognition multi-sensor fusion technology sustainable governance networks. We integrate developing blockchain-based twins, smart infrastructure sensors, real-time Internet of Things assist computing technologies. The problems are whether: data-driven urbanism requires visual recognition simulation-based twins; environment perception mechanisms cities; modeling, optimize city environments. Our analyses particularly prove that navigation geospatial mapping connected sensors enable governance. Digital simulation, visualization ambient sound software Virtual deep learning neural network architectures, cyber-physical cognitive networked cities. Throughout January March 2023, a quantitative was carried out across ProQuest, Scopus, Web Science databases, with search terms comprising “sustainable networks” + “digital tools”, “spatial algorithms”, “multi-sensor technology”. A Preferred Reporting Items for Systematic Reviews Meta-analysis (PRISMA) flow diagram generated using Shiny App. AXIS (Appraisal tool Cross-Sectional Studies), Dedoose, MMAT (Mixed Methods Appraisal Tool), Review Data Repository (SRDR) were used assess quality identified scholarly sources. Dimensions VOSviewer employed bibliometric through layout algorithms. findings gathered from our clarify environments 3D technology, intelligent devices, modeling.

Language: Английский

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Generative artificial intelligence of things systems, multisensory immersive extended reality technologies, and algorithmic big data simulation and modelling tools in digital twin industrial metaverse

Equilibrium Quarterly Journal of Economics and Economic Policy, Journal Year: 2024, Volume and Issue: 19(2), P. 429 - 461

Published: June 30, 2024

Research background: Multi-modal synthetic data fusion and analysis, simulation modelling technologies, virtual environmental location sensors shape the industrial metaverse. Visual digital twins, smart manufacturing sensory mining techniques, 3D twin predictive maintenance tools, big mobile analytics, cloud-connected spatial computing devices further immersive spaces, decentralized worlds, reality Purpose of article: We aim to show that extended cognitive systems, computer vision-based production neuro-engineering interoperability improve artificial intelligence-based metaverse hyper-immersive simulated environments. Geolocation tracking image processing computational robot motion algorithms, technologies economic business management environments Methods: Quality tools: AMSTAR, BIBOT, CASP, Catchii, R package Shiny app citationchaser, DistillerSR, JBI SUMARI, Litstream, Nested Knowledge, Rayyan, Systematic Review Accelerator. Search period: April 2024. terms: “digital metaverse” + “artificial Intelligence Things systems”, “multisensory technologies”, “algorithmic tools”. Selected sources: 114 out 336. Published research inspected: 2022–2024. PRISMA was reporting quality assessment tool. Dimensions VOSviewer were deployed as visualization tools. Findings & value added: Simulated augmented multi-sensory explainable decision support cloud-based robotic cooperation ambient intelligence deep learning-based analytics tools are instrumental in The necessitates connected enterprise reality-embedded twins.

Language: Английский

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The new normal: The status quo of AI adoption in SMEs

Journal of Small Business Management, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 35

Published: Aug. 13, 2024

The recent surge in the adoption of artificial intelligence (AI) by small and medium-sized enterprises (SMEs) has garnered significant research attention. However, existing literature reveals a fragmented landscape that hinders our understanding how SMEs use AI. We address this through systematic review wherein we analyze 106 peer-reviewed articles on AI categorize states trends into eight clusters: (1) compatibility, (2) infrastructure, (3) knowledge, (4) resources, (5) culture, (6) competition, (7) regulation, (8) ecosystem: according to technology–organization–environment model. Our provides valuable insights identifies gaps literature, notably overlooking identification as pivotal driver neglecting legal requirements. study clarifies implementation within SMEs, offering holistic theoretically grounded perspective empower researchers practitioners facilitate more effective application SME sector.

Language: Английский

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The adoption of Industry 4.0 technologies by using the technology organizational environment framework: The mediating role to manufacturing performance in a developing country

Business Strategy & Development, Journal Year: 2024, Volume and Issue: 7(2)

Published: April 22, 2024

Abstract The study aspires to identify the factors conditioning adaptation of fourth industrial revolution (4IR) within manufacturing industries in Bangladesh, embracing Industry 4.0 (I4.0) technology led by technology‐organizational‐environment (TOE) framework that links a number variables Bangladesh. I4.0 is going drastically change landscape extended TOE relate demographics with research for implementing developing country. findings are analyzed using SMART PLS SEM and SPSS 29 order diagnose technological contexts (IT resource availability, readiness, relative advantage), organizational (strategy leadership, capabilities, infrastructure), environmental (market pressure, government support, innovation decision making). study's data, which were collected bootstrap confidence range 95%, offered evidence favor both proposed mediating effects. A statistically significant indirect effect I4 .0 on manufacturing/industry performance was seen analysis. This conducted examine function performance, enhances comprehensiveness study. Through application framework, this investigates impact adoption performance. theoretical has been validated model, aims heighten integrating I4.0. practical implications study, organizations, governments, practitioners engaged implementation technologies nation contexts.

Language: Английский

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How to support innovative small firms? Bibliometric analysis and visualization of start-up incubation

Journal of Innovation and Entrepreneurship, Journal Year: 2024, Volume and Issue: 13(1)

Published: Jan. 16, 2024

Abstract Supporting the birth and development of innovative small firms, i.e., start-up incubation, has emerged as a critical factor in fostering entrepreneurship, innovation, regional development, more recently, sustainability. This bibliometric review aims to comprehensively understand visualize different research perspectives on how start-ups are successfully incubated. A total 1116 Scopus articles were selected synthesized using qualitative approach. The study applies novel visualization techniques (Citation Network Analysis, Global Citation Score, Burst Detection Analysis Co-Occurrence Networks Keywords) map scientific structure incubation research, including clusters leading topics based citation networks, most cited articles, keywords with substantial bursts well their co-occurrence. We evaluate from 1972 2023 show topic advanced by scholars’ changing interests over time. identify five that reflect distinct themes references. findings contribute comprehensive understanding evolution which developed focus biotechnology technology transfer toward current trends accelerators (entrepreneurial) ecosystems. paper also provides insights for policymakers managers make informed decisions.

Language: Английский

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Plant simulation for robot automation system of deep-frying process of Kimbugak

Food Science and Biotechnology, Journal Year: 2025, Volume and Issue: 34(2), P. 503 - 514

Published: Jan. 1, 2025

Language: Английский

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Automation and Its Influence on Sustainable Development: Economic, Social, and Environmental Dimensions

Sustainability, Journal Year: 2025, Volume and Issue: 17(4), P. 1754 - 1754

Published: Feb. 19, 2025

This study investigates the complex duality of automation and its impact on sustainable development, encompassing factors economic growth, social equity, environmental sustainability. Innovations in artificial intelligence, robotics, machine learning are driving transforming industries through improved production, operational efficiency, resource optimization. However, rapid integration has created a paradox. While it offers opportunities for optimization technological advancement, exacerbates challenges such as income inequality, degradation, displacement. These issues underline need balanced inclusive approaches to automation’s implementation. Automation contributes substantively GDP growth because raises labor productivity, yet arguably enhanced inequality by eliminating low-skilled jobs. improves energy efficiency aids renewable but increases overall effectiveness, leading concerns regarding ecological applied quantitative methodology using longitudinal data from 2000 2023 regression models examine sustainability metrics influenced automation. The findings highlight potential reform effective forms manufacturing, encourage innovation, identify systemic governmental policies. Specifically, results indicate that contributed 25% increase productivity across sectors, 15% reduction intensity per unit GDP, 12% rise Gini index, signaling growing inequality. outcomes emphasize both posed By integrating advancements with goals, can act transformative instrument promote conservation, equitable justice. paper concludes recommendations governments industry leaders incorporate into development objectives, ensuring distribution advantages, while alleviating socio-environmental hazards.

Language: Английский

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Recent Advances and Challenges in Industrial Robotics: A Systematic Review of Technological Trends and Emerging Applications

Processes, Journal Year: 2025, Volume and Issue: 13(3), P. 832 - 832

Published: March 12, 2025

Industrial robotics has shifted from rigid, task-specific tools to adaptive, intelligent systems powered by artificial intelligence (AI), machine learning (ML), and sensor integration, revolutionizing efficiency human–robot collaboration across manufacturing, healthcare, logistics, agriculture. Collaborative robots (cobots) slash assembly times 30% boost quality 15%, while reinforcement enhances autonomy, cutting errors energy use 20%. Yet, this review transcends descriptive summaries, critically synthesizing these trends expose unresolved tensions in scalability, cost, societal impact. High implementation costs legacy system incompatibilities hinder adoption, particularly for SMEs, interoperability gaps—despite frameworks, like OPC UA—stifle multi-vendor ecosystems. Ethical challenges, including workforce displacement cybersecurity risks, further complicate progress, underscoring a fragmented field where innovation outpaces practical integration. Drawing on systematic of high-impact literature, study uniquely bridges technological advancements with interdisciplinary applications, revealing disparities economic feasibility equitable access. It critiques the literature’s isolation trends—cobots’ safety, ML’s perception’s precision—proposing following cohesive research directions: cost-effective modularity, standardized protocols, ethical frameworks. By prioritizing interoperability, sustainability, paper charts path evolve inclusively, offering actionable insights researchers, practitioners, policymakers navigating dynamic landscape.

Language: Английский

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