Global manufacturing, low-cost country sourcing and adoption of lean principles have provided organisations with opportunities for cost minimisation. However, such opportunities often concur to increase companies’ exposure and vulnerability to risks that might lead to supply chain disruptions, which can seriously affect companies’ revenues and credibility with stakeholders.
Therefore, supply chain risk management (SCRM) represents a growing concern; ensuring supply and distribution continuity without disruptions has become a challenging task for supply chain managers. In practice, SCRM is gaining more and more attention in companies as supply chain managers realise that continued physical and financial flows are key components of business growth and success.
To manage risks in today’s complex and uncertain supply chains, companies need effective decision support systems (DSS) to analyse different scenarios and assess the impact of potential risks on their supply chain from end to end. To achieve this, companies can today leverage the availability of huge amount of data (big data) that requires specific tools and approaches to detect potential problems earlier, and with sufficient accuracy. Furthermore, DSS may enable the identification and assessment of risk mitigation and management strategies, providing evidence-based and quantitative support to decision makers.
This special issue aims to promote the publishing of cutting-edge, relevant and rigorous research in the area of SCRM with particular emphasis on the decision making process and support systems. We invite papers on cutting-edge research employing both quantitative and qualitative research methodologies. Particularly, we welcome submissions in the form of conceptual, case-based or empirical papers offering insights in the area of DSS for SCRM.
Suitable topics include but are not limited to:
- Supply/demand risk identification and management strategy assessment approaches
- Decision support system architectures for SCRM
- Decision making processes for risk management strategy design
- Evidence-based reactive and proactive strategies for SCRM
- Collaborative decision making process for SCRM
- Information sharing as risk mitigation strategy
- Supply/demand risk measures and assessment approaches
- Agent-based or web-based systems for SCRM
- ICT support for SCRM
- Big data analysis for supply chain risk identification and management
- Cases studies and surveys on SCRM
Important Dates
Full-paper submission: 15 March, 2014
Notification to authors: 30 April, 2014
Final versions due: 31 May, 2014
Final manuscript acceptance: 15 July, 2014
Notification to authors: 30 April, 2014
Final versions due: 31 May, 2014
Final manuscript acceptance: 15 July, 2014
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