Unveiling the role of sustainable supply chain drivers toward knowledge-based economy via a novel permutation approach: implications from an emerging economy

Knowledge-based supply chains (KBSC) focus on cutting-edge technologies of industry 4.0 and are highly focused on knowledge and human-centric skills. On this account, their prominent role in the context of knowledge economies is undoubtedly confirmed. On the other hand, many scholars and activists have considered the sustainability triple bottom line (TBL) theory as the fundamental pillar of development, including the economy, environment, and society. As a result, the main purpose of this study is to demonstrate the role of sustainable supply chain drivers (SSCDs) in achieving a knowledge-based economy. To this aim, after extraction of the main features of the knowledge-based economy (KBE) and sustainable supply chain drivers from relevant literature, a new method based on an efficient mixed-integer linear programming (MILP) model is developed to relax the computational complexity of the classical QUALIFLEX (QUALItative FLEXible multiple criteria method) in dealing with the problem with more alternatives. The results presented that among identified features of KBE, the literacy rate, life-long training, learning, and technical publications per capita are essential features. Furthermore, long-term orientation, globalization process, and professional associations are the most crucial supply chain sustainability drivers. These findings can empower organizations to prepare for moving toward sustainability in a knowledge-based economy environment.

Automated summary

Knowledge-based supply chains (KBSC) with cutting-edge technologies of industry 4.0 play a significant role in knowledge economies. Sustainable supply chain drivers (SSCDs) are crucial in achieving a knowledge-based economy. This study develops a new method based on an efficient mixed-integer linear programming (MILP) model to address the complexity of the problem.