A decision framework for SMEs to address sustainability issues with Industry 4.0 technologies

Annals of Operations Research, Год журнала: 2025, Номер unknown

Опубликована: Март 12, 2025

Abstract This study investigates the adoption of Industry 4.0 technologies in Small and Medium Enterprises (SMEs) within emerging economies, focusing on sustainability resource efficiency. Extant research often targets larger firms or developed leaving SMEs markets underexplored. proposes a holistic framework for to enhance adoption, addressing goals while improving competitiveness. Twenty-five enablers were identified through systematic literature review validated their significance survey 233 Indian manufacturing SMEs. Using Exploratory Factor Analysis, clustered into five groups: Digital Physical Technologies, Organizational, Supply Chain, Environmental, Social. Fuzzy-AHP prioritized enablers, Fuzzy-DEMATEL explored interrelationships. Sensitivity analysis results, ensuring robustness. Analyzed results highlight organizational readiness, such as dedicated R&D teams managerial support. Inter-organizational factors, supply chain integration social with effective policies, also found be pivotal. environmental strategies emerged factors dependent robust policy Practical recommendations include targeted allocation, skill development, interventions support digital transformation. bridges gaps advances SME participation sustainable global chains.

Язык: Английский

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A metaverse framework for sustainable waste management considering circular economy

Chemical Engineering Journal, Год журнала: 2025, Номер unknown, С. 162283 - 162283

Опубликована: Апрель 1, 2025

Язык: Английский

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Knowledge flows in industry 4.0 research: a longitudinal and dynamic analysis

Journal of Data Information and Management, Год журнала: 2025, Номер unknown

Опубликована: Апрель 7, 2025

Язык: Английский

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Advancing Sustainable Cities and Communities with Internet of Things: Global Insights, Trends, and Research Priorities for SDG 11

Results in Engineering, Год журнала: 2025, Номер unknown, С. 104917 - 104917

Опубликована: Апрель 1, 2025

Язык: Английский

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Data-Driven Insights into Greener Technologies for Waste Valorization: Advancing Circular Economy Practices

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Апрель 24, 2025

The advancement of circular economies requires efficient waste management, yet dozens countries still face difficulties with landfills as well sorting problems and inadequate resource extraction. A data-based analysis municipal solid (MSW) management uses economic demographic indicators the main components this study. data processing was conducted utilizing Python in Google Colab, after which exploratory evaluation construction regression model to find valorization inefficiencies ensued. Sankey diagram provided evidence patterns movements along prime locations recycling recovery process inefficiencies. results demonstrate that produces 60% waste, landfill consumption consumes 20% energy production receives support from 50% recovered waste. Regression established predictive power both linear polynomial models unsatisfactory (R-squared: 0.102) because policy enforcement, technological integration public participation, steered efficiency. Geographical differences output ability demand specific policies need development across regions. This research endorses AI-driven together blockchain-based tracking public-private collaborations strategies boost efforts. Extended Producer Responsibility (EPR) must be strengthened while waste-to-energy technology should receive financial for improving sustainability through rates on disposals. Effective approaches are available Germany, Japan Sweden can adopted globally. offers a comprehensive optimization guide brings advancements legislative needs community engagement foster Sustainable Development Goals (SDGs) enhance economy.

Язык: Английский

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New Era of Tourism: Innovative Transformation Through Industry 4.0 and Sustainability

Sustainability, Год журнала: 2025, Номер 17(9), С. 3841 - 3841

Опубликована: Апрель 24, 2025

At the beginning of third millennium, human civilization faces a paradox significant proportions: on one hand, industrial and technological growth is causing extensive environmental degradation, threatening both current future generations. On other acceleration development essential, requiring profound transformation society as only viable solution. With advent Fourth Industrial Revolution shifts in economy, especially regarding sustainability, process transformative tourism becomes crucial. Transformative not aligns with sustainable principles but also fosters deeper connection between economic preservation natural resources, ensuring that progress benefits humanity planet. The goal this research to identify how key factors Industry 4.0 can contribute tourism. methodological approach study uses systematic literature review (SLR), which allows for detailed analysis existing scientific papers identification trends challenges field. included published 2013 2025, applying predefined criteria relevance, quality, focus sustainability digitalization findings indicate automation improving tourist experiences, optimizing destination management reducing ecological footprint This analyses changes prompted by fastest-growing global activity. paper stem from focuses closely aspects 4.0, including digitization, automation, use innovative technologies results arising include improvements enhancement marketing activities tourism, implications through impacts provides an overview effects are transforming enabling it become more resilient face posed modern world.

Язык: Английский

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Enabling Sustainable Urban Transportation with Predictive Analytics and IoT

MATEC Web of Conferences, Год журнала: 2024, Номер 392, С. 01179 - 01179

Опубликована: Янв. 1, 2024

This research explores the integration of predictive analytics and Internet Things (IoT) to transform sustainable urban transportation systems. project intends examine transformational effect on mobility, using empirical data gathered from IoT devices. The includes information vehicle speed, traffic density, air quality index (AQI), meteorological conditions. study use modeling estimate congestion, volume. allows for evaluation prediction accuracy its correspondence with actual data. reveals a direct relationship between increased density decreased while unfavorable weather conditions correspond congestion. Predictive models demonstrate significant in forecasting congestion quality, accurate volume poses inherent complications. comparison expected real results demonstrates dependability AQI, thereby confirming their effectiveness. interventions led by 25% decrease levels, as well notable 12.7% enhancement despite little 1.4% rise impact highlights efficacy these solutions, showcasing favorable mitigating promoting environmental sustainability. Ultimately, this emphasizes that may have improving transportation, enabling more intelligent decision-making, creating environments driven data-driven insights proactive actions.

Язык: Английский

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IoT-Enabled Predictive Maintenance for Sustainable Transportation Fleets

E3S Web of Conferences, Год журнала: 2024, Номер 511, С. 01012 - 01012

Опубликована: Янв. 1, 2024

This research examines the profound effects of integrating IoT-enabled predictive maintenance in sustainable transportation fleets. By using real-time sensor data, this implementation aims to enhance fleet dependability and operational efficiency. The fleet, including a variety vehicles such as electric buses, hybrid cars, trucks, CNG-powered vans, is constantly monitored IoT sensors that capture important characteristics like engine temperature, battery voltage, brake wear percentages. algorithms adapt schedules response live enabling proactive strategy tackles prospective problems before they result major failures. examination records reveals prompt actions, showcasing system’s efficacy reducing interruptions improving overall fleet. Moreover, percentage change confirms flexibility, demonstrating its capacity anticipate fluctuations wear. findings highlight ability various operating situations contribution lowering expenses while enhancing effectiveness. established approach incorporates ethical issues, data security privacy, ensure responsible adoption technology. study has broader ramifications beyond particular dataset, providing detailed plan for incorporating IoTenabled into contemporary infrastructures. study’s offer valuable insights potential strategies transform industry towards sustainability. contributes future where fleets operate with increased efficiency, reduced environmental impact, improved reliability.

Язык: Английский

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Enhancing environmental sustainability with federated LSTM models for AI-driven optimization

Alexandria Engineering Journal, Год журнала: 2024, Номер 108, С. 640 - 653

Опубликована: Сен. 19, 2024

Язык: Английский

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Sustainable digital fashion in a metaverse ecosystem

Journal of Retailing and Consumer Services, Год журнала: 2024, Номер 82, С. 104099 - 104099

Опубликована: Окт. 4, 2024

Язык: Английский

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