Sustainability performance assessment of industrial corporation using Fuzzy Analytic Network Process

Nowadays, sustainability is one of the leading value-increasing strategies of industrial corporations. In order to implement a sustainable strategy, it is necessary to assess the sustainability performance. Nevertheless, this still represents a relevant gap in the literature and practice. There are a number of frameworks and tools for sustainability performance assessment. Most of them are based on a set of indicators. However, in many corporations the sets are applied and kept disaggregated. Due to this deficiency, aggregated sustainability assessment approaches are often explored by researchers and practitioners. One of the main approaches is the use of multi criteria decision making methods which transform multiple indicator values to a single dimension. Since there are many complex interdependencies among the used sustainability key performance indicators and their relations are uncertain, Fuzzy Analytic Network Process (FANP) appears to be an appropriate tool for aggregated assessing the sustainability performance. The aim of this paper is to develop and verify a methodology for aggregated sustainability performance assessment of an industrial corporation using the FANP approach. Based on analysis of the existing FANP approaches and discussion of their advantages and disadvantages, Logarithmic Fuzzy Preference Programming Methodology was selected for this purpose. Our developed methodology provides a comprehensive aggregated sustainability performance assessment system based on combining three evaluation methods (basic evaluation, trend evaluation, and categorization), and Action matrix, which defines appropriate corrective actions level to achieve the sustainability performance targets. A case study from metallurgical industry was used to verify the developed methodology and to identify critical points and recommendations for its implementation. (C) 2019 The Authors. Published by Elsevier Ltd.