Sustainable development model for measuring and managing sustainability in the automotive sector

A growing number of organizations across a variety of industries are now pursuing sustainable management business goals to improve business efficiency, manage stakeholder expectations, or for legislative compliance. This is also the case for automotive manufacturing organizations who are under pressure from their stakeholders to manage and improve sustainability performance. This requires the development of credible measurement tools and systems to enable capture and monitoring of sustainability. This paper describes the development process for an innovative model, named the Automotive Sustainability Assessment Model (A-SAM), to drive sustainable decision-making in the automotive sector. The process of developing the model consisted of four major steps, each of which contained series of intermediate steps, individual objectives, and research methods. The model measures, quantifies, and translates a broad range of external effects (both positive and negative) into their monetary equivalents, enabling large car manufacturers to evaluate options, identify win-wins, and optimize trade-off, while making complex and multidisciplinary sustainability decisions. It allows managers and design engineers in the automotive sector to develop a better understanding of the environmental, resource, and social impacts of their activities, products, processes, and materials used, while still ensuring cost-effectiveness when making decisions. The A-SAM shows promise as an effective tool for supporting sustainability decisions in a business environment. Although developed in the context of the automotive industry, it can be adapted by organizations of any type, operating across many different sectors for managing sustainability in a more holistic, comprehensive, and integrated manner.

Automated summary

A-SAM is an innovative model developed to drive sustainable decision-making in the automotive sector, enabling large car manufacturers to evaluate options and optimize decisions by quantifying external effects into monetary equivalents.