Evidence map›Paper›PMID 41541915›Full record

ArticleF1000Research2025

Decoding e-waste challenges with hybrid AHP and ISM Model approach: An initiative towards a cleaner future in India.

Ashok Kumar Singhdeo, Sushanta Tripathy, Deepak Singhal

Abstract read
In one paragraph

Article in F1000Research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

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No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Ashok Kumar SinghdeoSchool of Mechanical Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, 751024, India.
Sushanta TripathySchool of Mechanical Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, 751024, India.ORCID https://orcid.org/0000-0003-2470-4080
Deepak SinghalSchool of Mechanical Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, 751024, India.ORCID https://orcid.org/0000-0002-1336-7819

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: E-waste has rapidly become the fastest growing waste stream in the world, posing serious threats to environmental sustainability and the global agenda for a cleaner, greener, and more prosperous future. Countries that are relatively new to e-waste management as India, face significant challenges in identifying and addressing the barriers to effective mitigation efforts. Methods: This study employs the Interpretive Structural Modelling (ISM) technique to decode and structure six levels of barriers leading to the seventh and most critical barrier: lack of sustainable design practices. In addition, a MICMAC analysis is used to classify the identified e-waste challenges as either driving or dependent variables, offering strategic insights for stakeholders. To further validate the findings, the Analytic Hierarchy Process (AHP), a multi-criteria decision-making (MCDM) method, is applied to assign weightage to each challenge based on expert input and to assess the robustness of the data. Results: The analysis reveals the absence of autonomous factors in the e-waste challenge ecosystem. Key dependent factors include fluctuating supply chains, underdeveloped R&D practices, lack of safety protocols, and poor integration of sustainable design practices. These are influenced by key driving constraints such as illegal e-waste practices, inconsistent policies and regulations, poor coordination, and limited accessibility. These driving challenges act as precursors to the ultimate barrier: the lack of sustainable design practices. Conclusions: The study provides actionable insights and prioritization of challenges that can guide policymakers and business leaders in developing effective e-waste mitigation strategies. The structured model offers a foundational framework for countries-whether newly engaged or planning to implement e-waste management to adopt it as a national agenda for achieving sustainable development goals.

Indexed as

Electronic WasteModels, TheoreticalWaste ManagementIndiaAHPchallengese wastee-waste mitigationISMsustainability.

Identifiers

PMID41541915
PMCPMC12800603

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.