Navigating Consumer Behaviour in E-Waste Disposal: a Bibliometric Exploration Aligned with SDG

Journal of Lifestyle and SDGs Review, Journal Year: 2025, Volume and Issue: 5(3), P. e05364 - e05364

Published: March 10, 2025

Objective: E-waste recycling is a critical research area due to environmental issues caused by discarded electronic devices. Aligned with the Sustainable Development Goals (SDG), particularly Goal 12 (Responsible Consumption and Production) 13 (Climate Action), this study emphasizes need for sustainable e-waste management. Despite insights into publication growth impacts, gap persists in understanding how consumers manage or respond various types. This examines customer behaviour conducted from 1997 2024. Theoretical Framework: The draws upon consumer theories understand complexities of management explores patterns responses types, including functional hazardous electronics. Method: analyzes 651 papers Scopus database, spanning contributions 136 prominent publications. Using VOSviewer scientific mapping, identifies significant trends globally. Results Discussion: findings highlight countries like China, United States, India, Kingdom, Australia. Esteemed journals, Journal Cleaner Production Resources Conservation Recycling, have advanced sustainability waste research. reveals differences disposal methods categories. Functional electronics, such as computers mobile phones, are commonly donated resold, whereas products batteries major appliances require specialized their hazards. Research Implications: Understanding variances crucial promoting effective, techniques. align SDG framework, providing actionable policymakers, researchers, practitioners design targeted strategies improving practices globally while supporting responsible production climate resilience. Originality/Value: By addressing recycling, enhances management's role fostering sustainability, making contribution literature on practices.

Language: Английский

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Impact of green technology and flexible production on multi-stage economic production rate (EPR) inventory model with imperfect production and carbon emissions

Journal of Cleaner Production, Journal Year: 2025, Volume and Issue: unknown, P. 145187 - 145187

Published: April 1, 2025

Language: Английский

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A sustainable framework to address e-waste management solutions: an Indian perspective

Journal of Material Cycles and Waste Management, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

Language: Английский

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Determinants of adopting web-based systems for e-waste management and ensuring sustainable environment: Evidence from Bangladesh

Cleaner Waste Systems, Journal Year: 2025, Volume and Issue: unknown, P. 100282 - 100282

Published: April 1, 2025

Language: Английский

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Revolutionizing E-waste Classification: The Role of AI and Image Processing Techniques in Sustainable Recycling

Studies in computational intelligence, Journal Year: 2025, Volume and Issue: unknown, P. 111 - 120

Published: Jan. 1, 2025

Language: Английский

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Revolutionizing Open-Pit Mining Fleet Management: Integrating Computer Vision and Multi-Objective Optimization for Real-Time Truck Dispatching

Applied Sciences, Journal Year: 2025, Volume and Issue: 15(9), P. 4603 - 4603

Published: April 22, 2025

The implementation of fleet management software in mining operations poses challenges, including high initial costs and the need for skilled personnel. Additionally, integrating new with existing systems can be complex, requiring significant time resources. This study aims to mitigate these challenges by leveraging advanced technologies reduce minimize reliance on highly trained employees. Through integration computer vision multi-objective optimization, it seeks enhance operational efficiency optimize open-pit mining. objective is truck-to-excavator assignments, thereby reducing excavator idle deviations from production targets. A YOLO v8 model, six hours mine video footage, identifies vehicles at excavators dump sites real-time monitoring. Extracted data—including truck assignments ready times—is incorporated into a binary integer programming model that waiting times discrepancies target assignments. epsilon-constraint method generates Pareto frontier, illustrating trade-offs between objectives. Integrating image analysis optimization significantly improves efficiency, enabling adaptive truck-excavator allocation. highlights potential techniques mining, leading more cost-effective data-driven decision-making.

Language: Английский

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Artificial Intelligent and Internet of Things framework for sustainable hazardous waste management in hospitals

Waste Management, Journal Year: 2025, Volume and Issue: 203, P. 114816 - 114816

Published: May 1, 2025

Language: Английский

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Intelligent X-ray waste detection and classification via X-ray characteristic enhancement and deep learning

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 435, P. 140573 - 140573

Published: Jan. 1, 2024

Language: Английский

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Effective waste management in service industry: Fuzzy-based modelling approach for strategic decision-making

Waste Management & Research The Journal for a Sustainable Circular Economy, Journal Year: 2024, Volume and Issue: unknown

Published: April 6, 2024

Hospitals need to identify issues of greater importance on waste management because the implementation many different strategies may lead an unconscious increase in costs. Accordingly, purpose this study is define most effective service industry. For purpose, a novel fuzzy decision-making model proposed that has two stages. In context, six JCI-based indicators are weighted by using sine trigonometric Decision Making Trial and Evaluation Laboratory (DEMATEL) methodology. Additionally, comparative evaluation also been conducted with Criteria Importance Through Intercriteria Correlation (CRITIC) technique check reliability findings. On other hand, five strategy alternatives selected considering principles integrated hierarchy approach. These items evaluated Technique for Order Preference Similarity (TOPSIS). side, these factors ranked help Additive Ratio Assessment (ARAS) test consistency results. The main contribution prior can be presented hospitals have appropriate process defining important factors. weighting alternative ranking results same all combinations. Therefore, it seen creates coherent consistent It defined efficient storage key issue process. Moreover, ‘reduce’ found as critical stage

Language: Английский

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E-waste prediction and optimal route selection using adaptive deep Markov random field and block chain

Kybernetes, Journal Year: 2024, Volume and Issue: unknown

Published: May 29, 2024

Purpose An efficient e-waste management system is developed, aided by deep learning techniques. Here, a smart bin using Internet of things (IoT) sensors generated. The detect the level waste in dustbin. data collected IoT sensor stored blockchain. an adaptive Markov random field (ADMRF) method implemented to determine weight wastes. performance ADMRF boosted optimizing its parameters with help improved corona virus herd immunity optimization algorithm (ICVHIOA). main objective developed ADMRF-based prediction minimize root mean square error (RMSE) and absolute (MAE) rate at time testing. If bins more than 80%, then alert message will be sent collector directly. Optimal route selection carried out ICVHIOA for collection wastes from bin. objectives optimal are reduce distance operational cost environmental impacts. considered recycling. blockchain-based dustbin evaluated comparing it other existing dustbins management. Design/methodology/approach used collect avoid certain diseases caused dumped waste. Disposal recycling necessary decrease pollution manufacture new products Findings RMSE framework was 33.65% better convolutional neural network (CNN), 27.12% increased recurrent (RNN), 22.27% advanced Resnet 9.99% superior long short-term memory (LSTM). Originality/value proposed E-waste has given enhanced also when compared conventional methods.

Language: Английский

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