Sustainable development performance in the semiconductor industry: A data-driven practical guide to strategic roadmapping

Abstract

Sustainable development performance (SDP) in the semiconductor industry, it is necessary to form a data-driven practical guide to strategic roadmapping by using a sustainable balanced scorecard (SBSC) because SDP perspectives have been addressed for several years and need to be further assessed through performance achievement. Additionally, the industry faces challenges in integrating technological innovation and stakeholder collaboration into the sustainable development (SD) perspectives. In light of these challenges, this study strives to develop an SBSC-based practical guide to strategic roadmapping utilizing the SD causal model under uncertainty. To attain this objective, this study employed a hybrid approach comprising content, bibliographic and cluster analyses, the entropy weight method (EWM), and the fuzzy Delphi method (FDM) are used to validate the data-driven SBSC measures. The fuzzy synthetic evaluation–decision-making trial and evaluation laboratory (FSE-DEMATEL) is used to develop the strategic roadmapping with interrelationships. The findings reveal that scientific and technological development, enhanced device performance, artificial intelligence, performance assessment and the Internet of Things are the main criteria that must be prioritized by decision makers for semiconductor SDP improvement. This study contributes to understanding the data-driven practical guide to strategic roadmapping for the semiconductor industry by using SDP data. Furthermore, by constructing a hierarchical framework and identifying prioritized key attributes that enhance SDP, this study makes a valuable contribution to the SD literature.