Purpose – The aim of this paper is that of individualizing a framework for the management of uncertainty in supply chain finalized to reduce the firm risks. Design/methodology/approach – Since a way for reducing the damages deriving from uncertainty sources is increasing the level of flexibility inside the supply chain, and the real option theory allows the increase of the flexibility level, in order to achieve the aim of this work, we utilize the real options theory to coverage of one or more risks inside the supply chain. Findings – A useful theoretical framework has been individualized enabling the selection of possible options to protect the firm against the risk originating from every source of uncertainty. In particular, on two types of risks, using Matlab software, a test has been conducted that proves the ability of the outsource option to cover risks under examination. Practical implications – In the paper a framework providing useful information for the supply chain management is presented. Originality/value – The paper attempts to provide an original tool for the risks management deriving from production activities inside a supply chain.

Sustainability’s growth, year after year, continues to be staggering, becoming a reference point for those working on these issues

The value chain refers to the source of competition to facilitate organizations to maximize and sustain value for their consumers. Value chain flexibility is necessary to build sustainable initiatives in addressing ambiguity. In the literature, there is a lack of framework to highlight the challenges to sustainable initiatives in value chain flexibility. This study fills this research gap by suggesting a framework for challenges to sustainable initiatives in value chain flexibility. In this study, thirteen potential challenges to sustainable initiatives in value chain flexibility are identified and an integrated model is developed. It adopts the modified Total Interpretive Structure Model and the Cross-Impact Matrix Multiplication Applied to Classification methodology. The mixed approach is used as the modified Total Interpretive Structure Model organizes the binary interactions among the challenges, while Cross-Impact Matrix Multiplication Applied to Classification analysis organizes specific precise assessments of the driving power and dependence of the challenges. The results of the study reflect that (i) lack of supplier commitment to sustainable products and (ii) lack of knowledge toward sustainability in value chains are the challenges that achieved the highest driving power. The challenge ‘inadequate communication among the suppliers in the value chain’ is at the highest level in the analysis. The proposed framework could help government and non-government bodies to formulate policies to efficiently address challenges to sustainable initiatives in value chain flexibility.