Uncovering Industry 4.0 technology attributes in sustainable supply chain 4.0: A systematic literature review

Srhir, Saoussane; Jaegler, Anicia; Montoya‐Torres, Jairo R.

doi:10.1002/bse.3358

Cited by 35 publications

(18 citation statements)

References 95 publications

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“…The present investigation adds to the growing academic research on the implementation of I4.0 in emerging countries, particularly in developing SCSCs in the case of the Moroccan textile sector. The study's findings are consistent with earlier research on I4.0 adoption, as it has been proved that I4.0 has a strong beneficial influence on implementing circular practices and sustainable approaches (Behl et al, 2023; Dey et al, 2022; Jayashree et al, 2022; Sharma et al, 2021; Srhir et al, 2023). The paper demonstrates substantial evidence regarding the influence of technological and environmental factors' effectiveness on the adoption of I4.0 technologies, aligning with earlier research findings.…”

Section: Discussionsupporting

confidence: 90%

“…Simultaneously, the I4.0 integration promotes sustainable practices and fosters a more environmentally conscious approach to economic activities (Srhir et al, 2023). Our findings additionally demonstrate that the adoption of CE and sustainable practices via the I4.0 path promotes organizational performance by reducing waste, improving operational efficiency, and boosting corporate profitability.…”

Section: Discussionmentioning

confidence: 99%

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The adoption of I4.0 technologies for a sustainable and circular supply chain: an industry‐based SEM analysis from the textile sector

Hmamed,

Cherrafi,

Benghabrit

et al. 2023

Bus Strat Env

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Currently, researchers have been particularly interested in Industry 4.0 (I4.0) as a combination of novel revolutionary digital technologies. This evolution is transforming how organizations operate to promote sustainable and circular practices. Consequently, this research empirically investigates the capabilities of I4.0 adoption to establish a sustainable and circular supply chain. The study investigates the impact of organizational factors on the deployment of I4.0 technologies to achieve sustainability objectives. Furthermore, this approach combines empirical and qualitative analyses within a methodological framework to investigate the relationship between organizational factors, I4.0 adoption, sustainable, and circular practices. In this context, survey responses have been collected from 323 supply chain professionals in the textile sector in Morocco. Consequently, employing structural equation modeling, our results reveal a strong link between I4.0 adoption and the promotion of circular and sustainable approaches. The study finds a positive association between I4.0 adoption, technological readiness, and environmental responsiveness while highlighting the challenges posed by organizational practices on I4.0 implementation in developing countries. This research contributes to the theoretical foundations of the potential influence of I4.0 technologies, and it provides practical contributions for stakeholders to effectively embrace I4.0 technologies and thereby drive more sustainable and efficient practices.

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Section: Discussionsupporting

confidence: 90%

Section: Discussionmentioning

confidence: 99%

The adoption of I4.0 technologies for a sustainable and circular supply chain: an industry‐based SEM analysis from the textile sector

Hmamed,

Cherrafi,

Benghabrit

et al. 2023

Bus Strat Env

View full text Add to dashboard Cite

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“…, 2021), suitability of using soft computing techniques like Genetic Algorithms (Roy et al. , 2005), and Industry 4.0 technologies (Srhir et al. , 2023) that may act as a catalyst for supply chain risk management.…”

Section: Discussionmentioning

confidence: 99%

“…This will enable the new approach to be applied as a robust risk management tool (or decision support system) by replacing the existing risk assessment system. The latest research demands quality 4.0 conceptualization (Antony et al, 2022), practical implications in line with lean manufacturing (Yu and Ye, 2023;Antony et al, 2021;Roy et al, 2021), suitability of using soft computing techniques like Genetic Algorithms (Roy et al, 2005), and Industry 4.0 technologies (Srhir et al, 2023) that may act as a catalyst for supply chain risk management. Approaches like big data, blockchain, Internet of Things (IoT) technology and soft computing are crucial elements that characterize the new digital age.…”

Section: Practical Implicationsmentioning

confidence: 99%

Supply chain risk prioritization: a multi-criteria based Intuitionistic Fuzzy TOPSIS approach

Mukherjee,

De,

Roy

2024

IJQRM

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Purpose Identifying and prioritizing supply chain risk is significant from any product’s quality and reliability perspective. Under an input-process-output workflow, conventional risk prioritization uses a risk priority number (RPN) aligned to the risk analysis. Imprecise information coupled with a lack of dealing with hesitancy margins enlarges the scope, leading to improper assessment of risks. This significantly affects monitoring quality and performance. Against the backdrop, a methodology that identifies and prioritizes the operational supply chain risk factors signifies better risk assessment.Design/methodology/approach The study proposes a multi-criteria model for risk prioritization involving multiple decision-makers (DMs). The methodology offers a robust, hybrid system based on the Intuitionistic Fuzzy (IF) Set merged with the “Technique for Order Performance by Similarity to Ideal Solution.” The nature of the model is robust. The same is shown by applying fuzzy concepts under multi-criteria decision-making (MCDM) to prioritize the identified business risks for better assessment.Findings The proposed IF Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) for risk prioritization model can improve the decisions within organizations that make up the chains, thus guaranteeing a “better quality in risk management.” Establishing an efficient representation of uncertain information related to traditional failure mode and effects analysis (FMEA) treatment involving multiple DMs means identifying potential risks in advance and providing better supply chain control.Research limitations/implications In a company’s supply chain, blockchain allows data storage and transparent transmission of flows with traceability, privacy, security and transparency (Roy et al., 2022). They asserted that blockchain technology has great potential for traceability. Since risk assessment in supply chain operations can be treated as a traceability problem, further research is needed to use blockchain technologies. Lastly, issues like risk will be better assessed if predicted well; further research demands the suitability of applying predictive analysis on risk.Practical implications The study proposes a hybrid framework based on the generic risk assessment and MCDM methodologies under a fuzzy environment system. By this, the authors try to address the supply chain risk assessment and mitigation framework better than the conventional one. To the best of their knowledge, no study is found in existing literature attempting to explore the efficacy of the proposed hybrid approach over the traditional RPN system in prime sectors like steel (with production planning data). The validation experiment indicates the effectiveness of the results obtained from the proposed IF TOPSIS Approach to Risk Prioritization methodology is more practical and resembles the actual scenario compared to those obtained using the traditional RPN system (Kim et al., 2018; Kumar et al., 2018).Originality/value This study provides mathematical models to simulate the supply chain risk assessment, thus helping the manufacturer rank the risk level. In the end, the authors apply this model in a big-sized organization to validate its accuracy. The authors validate the proposed approach to an integrated steel plant impacting the production planning process. The model’s outcome substantially adds value to the current risk assessment and prioritization, significantly affecting better risk management quality.

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“…However, the benefits are as yet unproven, and empirical evidence relating to specific industries is lacking. For example, recent review of literature on the role of industry 4.0 technology in achieving supply chain sustainability recommends a thorough examination covering three pillars of sustainability performance with the application of industry 4.0 technologies in supply chains [2]. Another review of literature exploring the application of industry 4.0 technologies in AFSC management suggests the necessity for research on effective ways to enable AFSC sustainability [3].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Drivers of Industry 4.0 Technology Deployment to Achieve Agri-Food Supply Chain Sustainability: A Hybrid Approach

Zhao,

Jones,

Liu

et al. 2023

2023 IEEE International Symposium on Technology and Society (ISTAS)

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Agri-food supply chains (AFSCs) are struggling to achieve sustainability in the face of increasing social, environmental, and economic challenges. Industry 4.0 technologies are widely deployed to monitor, assess, and analyze their operational process, and thereby drive sustainable value. This study adopts a hybrid approach to analyze the drivers of industry 4.0 technology deployment to achieve AFSC sustainability. Thematic analysis of 24 interviews was carried out to identify 13 drivers, and these were used as inputs into the fuzzy analytic hierarchy process (AHP), total interpretive structural modeling (TISM), and fuzzy cross-impact matrix multiplications applied to classification (MICMAC). The results show that enhancing efficiency of water and fertilizer use, reducing carbon emissions, and reducing work intensity contribute significantly to economic, environmental, and social aspects of sustainability. We also identify that government subsidies for agricultural facilities and strengthening of farmers' agri-tech skills are key drivers that should be given priority.

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Uncovering Industry 4.0 technology attributes in sustainable supply chain 4.0: A systematic literature review

Cited by 35 publications

References 95 publications

The adoption of I4.0 technologies for a sustainable and circular supply chain: an industry‐based SEM analysis from the textile sector

The adoption of I4.0 technologies for a sustainable and circular supply chain: an industry‐based SEM analysis from the textile sector

Supply chain risk prioritization: a multi-criteria based Intuitionistic Fuzzy TOPSIS approach

Analysis of the Drivers of Industry 4.0 Technology Deployment to Achieve Agri-Food Supply Chain Sustainability: A Hybrid Approach

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