Identification and Assessment of Supply and Product Risks in Logistics of Advanced Products

In order to maintain the competitive advantage of advanced industries, thesupply outsourcing has provided a part of the requirements of research andmanufacture, logistics and supply chain with high sensitivity andcomplexity. In these industries, the logistics in a broader sense includes therole of the supply chain to prepare and manufacture a product from thephase of the raw materials supply to the distribution and delivery of thefinal product to the customers and its support. There are many factors, e.g.political concerns, technological alterations, regional threats, customers’demands, strategic objectives, financial instability and natural disasters,which have increased the uncertainties and the logistics risks. Themanagement of such risks is essential to reduce the vulnerability of thelogistics members. Thereby, the logistics risks should be identified,evaluated and ranked. The present study applies a comprehensive multiattributedecision-making model called the taxonomic analysis in order toidentify and assess the supply and product risks in the logistics, thereforeone of the manufacture industries of the advanced products have beenstudied. In this respect, the logistics have been introduced in this industryand the literature is reviewed and the experts’ notion on 44 risks of thesupply and product, and 16 assessment attribute have been identified andthen a statistics population of 30 experts in the relevant sections, as theiranswers were obtained via the questionnaire. The identified risks areassessed and ranked by taxonomic method. The results showed that the riskof monetary policy of upstream entities as the most important factor andthen the environmental risk (rules, governmental policies, taxation, andeconomic developments) and poor quality of raw materials used bycontractor have highest weight and significance in this model.

کلیدواژه ها:

logistics ، logistics management ، logistics risk management ، multi-attribute decision-making ، taxonomic analysis technique