Sustainable supply chain visibility assessment and proposals for improvements using fuzzy logic

Abstract

Purpose: Visibility management is essential to sustainable supply chains (SSCs), allowing the ability to see the chain end-to-end, with opportunities to derive benefits, including competitive advantage. Central to visibility management is visibility assessment and identification of areas for improvement. This paper aims to propose a method of assessing visibility in SSCs and the generation of proposals for improvement. Design/methodology/approach: A hierarchically structured assessment template is developed that comprises of dimensions, factors and attributes of visibility in SSCs. The template permits the use of linguistic variables. A fuzzy logic approach is adopted to calculate visibility levels and generate improvement areas based on linguistic data captured through the template. An industry-based case study is used to illustrate the process. Findings: This study reveals that visibility can be measured straightforwardly using the method developed in this paper. It is found that automation and contextual factors can significantly impact visibility levels, so also is sustainability awareness and practices adopted. Originality/value: This paper describes a visibility assessment model that incorporates linguistic variables, fuzzy logic and the use of an adaptable visibility assessment template. The assessment model can identify potential inhibitors of visibility for SSC under study.