Multi-objective Decision Support System for Sustainable Supplier Management

Open Access
Author:
Torres, Aineth
Graduate Program:
Industrial Engineering
Degree:
Doctor of Philosophy
Document Type:
Dissertation
Date of Defense:
February 20, 2015
Committee Members:
  • Arunachalam Ravindran, Dissertation Advisor
  • Arunachalam Ravindran, Committee Chair
  • Gul Kremer, Committee Member
  • Charles David Ray Sr., Committee Member
  • Paul M Griffin, Committee Member
Keywords:
  • Supply Chain
  • Green Supply Chain
  • Procurement
  • Supplier
  • Sustainability
  • Eco-efficiency
  • Portfolio Management
  • Supply Risk
Abstract:
For some supply chains, up to 90% of their environmental impact is linked to their suppliers. A recent study indicates that pressures from climate change will be most keenly felt in markets where companies see important opportunities for growth, such as Brazil, China, Mexico and the USA. Therefore, assessing the carbon footprint, environmental impact and other sustainability measures of suppliers in these countries is key to targeting weak areas in the supply chain. However, to make an efficient allocation of their limited resources and reduce the vulnerability of supply disruptions, companies need to match procurement decisions with the levels of risk brought by the different suppliers. In this dissertation, we develop decision making models that align sustainability goals with the corporate goals from the perspective of the purchasing function. First, we develop a Supplier Sustainability Risk Assessment Framework (SSRAF) to quantify the potential risks to the sustainability of the supply chain for different supplier segments. The supplier segments are represented through a 4x4 matrix (8 quadrants) with the cost of products on the x-axis (Low/High), supply risk on the y-axis (Low/High) and sustainability impact on the z-axis (Low/High). We are interested in assessing only the sustainability risk of four supplier segments representing a High impact on sustainability. They include: (1) Tactical items with low supply risk and cost, (2) Leverage items with low supply risk/high cost, (3) Critical items with high supply risk/low cost and (4) Strategic items with high supply risk and cost. A supply risk score is determined from a qualitative assessment of three factors: hazard, vulnerability, and risk management practice incorporating the perspective of different stakeholders. We apply the SSRAF to quantify the suppliers’ sustainability risks for a global manufacturer of consumer products located in México and develop supplier management methods based on the risks identified for the different items. For each of the four supplier segments considered, we formulate different optimization models and solve them using goal programming and other methods. For Tactical items, we propose a goal programming model that incorporates all unit quantity discounts based on the dollar value of all items purchased. The objective function evaluates total purchase price, quality, late delivery and sustainability performance to determine what product to order from which supplier. We use trade-off matrices to summarize the achievements for the various objectives under different scenarios. For Leverage items, we use a three phase methodology. In phase one, Data Envelopment Analysis (DEA) is used to pre-qualify a large set of initial suppliers by the estimation of their eco-efficiency scores. Then, a Multiple Criteria Ranking method is applied for a single sourcing strategy and a Bi-criteria Optimization Model (BOM) is used for a multiple sourcing strategy, with eco-efficiency scores and total purchase price as conflicting objectives. The BOM also incorporates all unit quantity discounts based on the total dollar value. In the third phase, we monitor supplier eco-efficiency changes for adjoining time periods using an Eco-efficiency Productivity Index (EPI). Furthermore, we decompose EPI to distinguish between the eco-efficiency changes due to innovations in technology and those due to the sustainability initiatives of the suppliers. The methodology is applied to an autoparts manufacturer in Mexico. For Critical products, which are items representing a small proportion of the overall costs but a very high level of service disruption, we assume that a global sourcing strategy is in place and propose a multi-criteria optimization model for identifying primary and backup suppliers to mitigate disruption risks. The quantitative model optimizes total purchase cost, lead time, supplier risk and total greenhouse gas (GHG) emissions. Total purchase cost includes product costs, transportation costs and costs resulting from exceeding GHG emissions. Finally, Strategic items represent high supply risk and high profits. As climate change and other sustainability threats gain relevance, it becomes fundamental for purchasing managers to assess not only the capacities and risks of the strategic suppliers but also the economic benefits gained by investing in long-term partnerships. We propose a modified form of the Supplier Sustainability Risk Assessment Framework (SSRAF) using Multiple Criteria Ranking and Rating methods to improve the risk assessment given by individual decision makers. In addition, the cost avoided by implementing a long-term environmental risk avoidance strategy with the supplier is used along with the supplier sustainability risk score to build a pay-off matrix and interactively obtain the buyer preferences among different suppliers. The optimization models for Critical and Strategic segments are also evaluated using the data collected from a global manufacturer of consumer products and from bibliographic sources.