Providing decision-support for sustainable development of the Brazilian automotive textile sector

Despite efforts to evaluate sustainability within the Brazilian automotive textile sector, there is still a lack of specific measures quantifying the social, environmental, and economic aspects. Consequently, the shift from a traditional profit-centric post-industrial culture to a modern, sustainable-focused culture presents ongoing challenges. Addressing this, a question arises: how can a decision-support framework be developed to ensure a balanced approach to sustainability management, highlighting system limitations without compromising the sector's performance? Decision support models aim to equip decision-makers with tools for making informed choices aligned with organizational objectives and goals. The proposed procedure comprises four key stages: sustainability diagnosis, creation of an illustrative panel, simulation, and normal distribution. The initial phase, sustainability diagnosis, uses the 5 SEnSU model, integrating indicators selection alongside their objectives and targets. Utilizing Goal Programming at its core, the Synthetic Indicator System Sustainability outlines the sector's performance relative to its objectives. Results are then presented in a dashboard format, offering a comprehensive view of sustainability performance trends. Subsequently, a simulation phase implements more stringent targets to identify the sector's limitations without jeopardizing its performance. These results are modeled through normal distribution curves, drawing parallels between sustainability within the system and Statistical Process Control Assessment, ensuring adherence to legal and corporate standards. Illustrating the procedure with the Brazilian textile automotive sector revealed that while the sector maintains economic sustainability, its progress has negatively impacted the environment and society. This process helped pinpoint critical areas in sustainability management and proposed strategies for optimizing resources to meet organizational sustainable objectives. Moreover, this model elevates informed decision-making and advocates for a more conscientious and efficient approach to business management across this sector and others.