Subtopic Deep Dive
Supply Chain Management
Research Guide
What is Supply Chain Management?
Supply Chain Management (SCM) involves the planning, execution, and control of the flow of goods, services, and information from raw material suppliers to end customers to achieve efficiency and resilience.
SCM research focuses on logistics optimization, supplier selection, inventory control, and disruption mitigation in global networks. Recent studies integrate AI and deep learning for performance enhancement, with over 400 citations across top papers since 2021. Key areas include resilience factors (Hashmi, 2022) and green practices (Santoso et al., 2022).
Why It Matters
SCM models improve operational efficiency in manufacturing, reducing costs by up to 20% through AI optimization (Olorunyomi Stephen Joel et al., 2024). Resilience strategies mitigate disruptions like COVID-19, enhancing supply chain performance via factors such as strategic partnerships (Tarigan and Siagian, 2021). Green SCM boosts sustainability in industries like nickel mining (Maskuroh et al., 2022) and supports ERP adoption for environmental compliance (Santoso et al., 2022). These approaches build competitive advantages in uncertain global trade.
Key Research Challenges
Disruption Risk Mitigation
Supply chains face vulnerabilities from events like earthquakes or pandemics, requiring robust risk management processes. Studies assess resilience through quantitative methods but struggle with predictive modeling (Hashmi, 2022; Mohd Rashid et al., 2014). Real-time adaptability remains limited in global networks.
AI Integration Scalability
Deploying AI and deep learning for optimization demands high computational resources and data quality. Reviews highlight gaps in practical frameworks for industrial applications (Olorunyomi Stephen Joel et al., 2024; Hosseinnia Shavaki and Ebrahimi Ghahnavieh, 2022). Standardization across diverse supply chains is challenging.
Sustainability Trade-offs
Balancing green practices with performance creates conflicts in resource-intensive sectors. Research shows ERP and green HRM improve outcomes but face adoption barriers in developing economies (Santoso et al., 2022; Maskuroh et al., 2022). Measuring long-term environmental impacts lacks unified metrics.
Essential Papers
LEVERAGING ARTIFICIAL INTELLIGENCE FOR ENHANCED SUPPLY CHAIN OPTIMIZATION: A COMPREHENSIVE REVIEW OF CURRENT PRACTICES AND FUTURE POTENTIALS
Olorunyomi Stephen Joel, Adedoyin Tolulope Oyewole, Olusegun Gbenga Odunaiya et al. · 2024 · International Journal of Management & Entrepreneurship Research · 78 citations
The integration of artificial intelligence (AI) technologies into supply chain management has emerged as a crucial avenue for enhancing efficiency, agility, and responsiveness in modern business op...
Applications of deep learning into supply chain management: a systematic literature review and a framework for future research
Fahimeh Hosseinnia Shavaki, Ali Ebrahimi Ghahnavieh · 2022 · Artificial Intelligence Review · 74 citations
Factors Affecting the Supply Chain Resilience and Supply Chain Performance
Aamir Rashid Hashmi · 2022 · South Asian Journal of Operations and Logistics · 45 citations
The key objective of this research study is to delve into the factors affecting supply chain resilience to enhance supply chain performance through the mediation of supply chain resilience. To perf...
Assessing the Benefit of Adopting ERP Technology and Practicing Green Supply Chain Management toward Operational Performance: An Evidence from Indonesia
Ruben Wahyu Santoso, Hotlan Siagian, Zeplin Jiwa Husada Tarigan et al. · 2022 · Sustainability · 41 citations
The recent concern on the environmental protection and COVID-19 issue is increasingly affecting the manufacturing industry. This research assessing the benefit of adopting ERP technology and practi...
The effects of strategic planning, purchasing strategy and strategic partnership on operational performance
Zeplin Jiwa Husada Tarigan, Hotlan Siagian · 2021 · Uncertain Supply Chain Management · 39 citations
The global competition in the manufacturing industry has obliged the companies to adopt an efficient and effective business process and adaptability of the company's competitive strategy following ...
Green human resource management and green supply Chain Management on Sustainable performance of nickel mining companies in Indonesia
Nihayatul Maskuroh, Winda Widyanty, R. Nurhidajat et al. · 2022 · Uncertain Supply Chain Management · 34 citations
The green economy with Islamic perspective is the primary discussion point in this study since it is seen as a potential solution to the current economic and environmental concerns. This study aims...
Performance Optimization of Industrial Supply Chain Using Artificial Intelligence
Madani Abdu Alomar · 2022 · Computational Intelligence and Neuroscience · 29 citations
Nowadays, organized retailing has witnessed a newer trend in the upcoming generations. Globally, these changes are attributed to growing family income, increased female participation, the transform...
Reading Guide
Foundational Papers
Start with Mohd Rashid et al. (2014) for SCRM practices post-disaster and Tsiakkouri (2010) for disruption processes, as they establish core risk frameworks cited in modern resilience studies.
Recent Advances
Study Olorunyomi Stephen Joel et al. (2024) for AI review (78 citations), Hashmi (2022) for resilience factors, and Setiawan et al. (2023) for digital-green integration.
Core Methods
Core techniques encompass deep learning applications (Hosseinnia Shavaki and Ebrahimi Ghahnavieh, 2022), ERP-green SCM modeling (Santoso et al., 2022), and leadership-performance analysis (Purwanto and Juliana, 2022).
How PapersFlow Helps You Research Supply Chain Management
Discover & Search
PapersFlow's Research Agent uses searchPapers and citationGraph to map SCM literature from Olorunyomi Stephen Joel et al. (2024), revealing 78 citations and clusters on AI optimization. exaSearch uncovers niche resilience studies like Hashmi (2022), while findSimilarPapers expands to deep learning applications (Hosseinnia Shavaki and Ebrahimi Ghahnavieh, 2022).
Analyze & Verify
Analysis Agent employs readPaperContent on Tarigan and Siagian (2021) to extract strategic partnership metrics, then verifyResponse with CoVe checks claims against datasets. runPythonAnalysis simulates inventory models from Alomar (2022) using pandas for performance stats, with GRADE grading evaluating evidence strength in green SCM (Maskuroh et al., 2022).
Synthesize & Write
Synthesis Agent detects gaps in disruption mitigation between foundational (Mohd Rashid et al., 2014) and recent AI papers, flagging contradictions via exportMermaid diagrams. Writing Agent uses latexEditText and latexSyncCitations to draft SCM reviews citing Santoso et al. (2022), with latexCompile generating polished manuscripts and gap detection proposing research extensions.
Use Cases
"Analyze resilience factors from Hashmi 2022 with statistical verification"
Research Agent → searchPapers('supply chain resilience') → Analysis Agent → readPaperContent + runPythonAnalysis (pandas correlation on performance data) → GRADE-verified statistical summary of mediation effects.
"Draft LaTeX review on AI in SCM citing Olorunyomi 2024"
Research Agent → citationGraph → Synthesis Agent → gap detection → Writing Agent → latexEditText + latexSyncCitations + latexCompile → camera-ready LaTeX PDF with integrated figures.
"Find GitHub repos for supply chain optimization code from recent papers"
Research Agent → paperExtractUrls (Alomar 2022) → Code Discovery → paperFindGithubRepo → githubRepoInspect → executable Python scripts for AI-based performance models.
Automated Workflows
Deep Research workflow conducts systematic reviews of 50+ SCM papers, chaining searchPapers → citationGraph → structured reports on AI trends (Olorunyomi Stephen Joel et al., 2024). DeepScan applies 7-step analysis with CoVe checkpoints to verify green SCM claims (Setiawan et al., 2023). Theorizer generates hypotheses on digitalization-resilience links from Tarigan et al. (2021, 2022).
Frequently Asked Questions
What is Supply Chain Management?
SCM is the oversight of materials, information, and finances as they move from supplier to consumer, optimizing efficiency and resilience.
What are key methods in SCM research?
Methods include AI integration (Olorunyomi Stephen Joel et al., 2024), deep learning frameworks (Hosseinnia Shavaki and Ebrahimi Ghahnavieh, 2022), and quantitative resilience modeling (Hashmi, 2022).
What are seminal papers in SCM?
Foundational works cover risk management (Mohd Rashid et al., 2014; Tsiakkouri, 2010). Recent high-impact papers are Olorunyomi Stephen Joel et al. (2024, 78 citations) and Santoso et al. (2022, 41 citations).
What open problems exist in SCM?
Challenges include scalable AI deployment, balancing sustainability with performance, and real-time disruption prediction in global networks (Setiawan et al., 2023; Maskuroh et al., 2022).
Research Management and Optimization Techniques with AI
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