On uncertainty in supply chain risk management. Issue 1 (6th May 2014)

• Record Type: Journal Article
• Authors: Vilko, Jyri; Ritala, Paavo; Edelmann, Jan
• Is Part Of: International journal of logistics management. Volume 25:Issue 1(2014)
• Page Start: 3
• Page End: 19
• Publication Date: 2014-05-06
• Subjects: Uncertainty -- Risk -- Supply chain risk management -- Conceptual framework; Business logistics -- Management -- Periodicals; Physical distribution of goods -- Management -- Periodicals; Web sites; 658.5
• DOI: 10.1108/IJLM-10-2012-0126
• Languages: English
• ISSNs: 0957-4093

Abstract

Abstract : Purpose: – The concept of uncertainty is a relevant yet little understood area within supply chain risk management. Risk is often associated with uncertainty, but in reality uncertainty is a much more elaborate concept and deserves more in-depth scrutiny. To bridge this gap, the purpose of this paper is to propose a conceptual framework for assessing the levels and nature of uncertainty in this context. Design/methodology/approach: – The aim of the study is to link established theories of uncertainty to the management of risk in supply chains, to gain a holistic understanding of its levels and nature. The proposed conceptual model concerns the role of certainty and uncertainty in this context. Illustrative examples show the applicability of the model. Findings: – The study describes in detail a way of analysing the levels and nature of uncertainty in supply chains. Such analysis could provide crucial information enabling more efficient and effective implementation of supply chain risk management. Practical implications: – The study enhances understanding of the nature of the uncertainties faced in supply chains. Thus it should be possible to improve existing measures and analyses of risk, which could increase the efficiency and effectiveness of supply chain and logistics management. Originality/value: – The proposed conceptual framework of uncertainty types in the supply chain context is novel, and therefore could enhance understanding of uncertainty and risk in supply and logistics management and make it easier to categorise, as well as initiate further research in the field.