Improving Sustainability Management Decisions With Modified Life Cycle Assessment Method

Across the globe, organizations and institutions have publicly committed to reducing the environmental impacts associated with their operations. Despite these commitments, progress in integrating sustainability measurement information into core business processes and decision criteria has been limited. To avoid many of the ecological tipping points that society currently faces, it is essential that sustainability measurement systems and decision support tools are improved to be more practically incorporated into business operations and decisions. This dissertation explores the specific sustainability challenges and information gaps that are faced by core business operations in three separate case studies, thereby expanding the sustainability operations management literature in the areas of environmentally preferable procurement, sustainable manufacturing, and green supply chain management. Modified life cycle assessment (LCA) methods are demonstrated in the methodological designs of the respective case studies, which help reduce the complexity of environmental information and the costs of assessment, and increase the specificity to organizations by considering spatial and temporal aspects of operations. Altogether, methods enable optimal management options and trade-offs to be identified, priorities to be set, and increases overall understanding of and ability to manage risks. These elements greatly enhance the actionability of sustainability information to organizational decision makers, helping to lower the barriers for integrating into core organizational processes for reducing the environmental burden of production and consumption systems.;The first essay demonstrates methods in the context of a breakfast cereal manufacturer's purchasing portfolio. Budgets are optimized towards environmental product options that maximize reductions in environmental impacts, staying within specified budgets. The study highlights the additional performance benefits of internal cap and trade approaches, allowing greater flexibility for big impact reduction/high cost product opportunities to be seized. The second essay presents a modified LCA of a cellulosic biorefinery's dynamic co-product portfolio, revealing significant variation in the environmental and economic performance across market scenarios, production constraints and policy assumptions. Results provide guidance to production managers on optimal production pathways that can meet both economic and environmental objectives across scenarios. The third essay presents modified spatial LCA methods applied to company-specific supply chains in the U.S. pork industry. Results show significant variation across supply networks, providing strong support for such spatial assessments in prioritizing resources for supply chain improvement.