Green Innovation and Core-Periphery Collaborative Networks: a multi-criteria decision-making perspective

The automotive manufacturing industry has a significant impact on economic growth, development and increasing the sustainability of societies. However, carbon emissions, energy and resource consumption, and generally negative environmental effects are among the issues arising from this industry. A practical solution to reduce destructive environmental effects and move towards sustainability in this industry is to adopt green innovation practices. Therefore, this study presents an evaluation approach consisting of multi-criteria decision-making methods with the aim of identifying the strengths and weaknesses of automotive manufacturing companies from the green innovation perspective. The proposed approach, in addition to evaluating automotive manufacturing companies, is also able to evaluate their collaborative networks. In the proposed approach, the independent weights of the criteria and their sub-criteria are determined through the improved fuzzy preference programming method, and the weighted influence non-linear gauge system technique is utilized to analyze the interdependencies among the criteria and calculate the dependent weights of the sub-criteria. Data from Kia Motors in South Korea, SAIPA in Iran, and their collaborative network were used to validate the proposed approach. Kia Motors and SAIPA were considered as core (knowledge-intensive) and peripheral (lagging-behind) companies, respectively. The results show that although the collaborative network performs better than SAIPA, it is weak compared to Kia Motors. Finally, the weaknesses of SAIPA and the collaborative network are identified, and strategies are presented to improve their performance.