10/27/16 | 4:15pm | E51-315
Reception to follow.
Abstract: In view of the challenges of meeting the goals set at the recent Climate Change Conference in Paris, it should be noted that the 2,500 largest global corporations account for more than 20% of global greenhouse gas (GHG) emissions, and that companies' direct emissions average only 14% of their supply chain emissions prior to use and disposal. Therefore, rationalizing CO2 emissions in supply chains could make an important contribution to the efforts of mitigating climate change. Walmart has embraced its role to protect the environment and reduce emissions in its vast supply chain, and in 2007 has started to collect data to assess GHG emissions of its supply chain. However, since approximately 85% of all industrial use occurs in basic material manufacturing, which is far upstream at the supply chain, Walmart needs to engage with upstream suppliers. Indeed, aside for assigning responsibilities to suppliers for their own direct emissions, to improve their environmental performance, supply chain leaders should be in a position to assign indirect responsibilities to firms whose actions and decisions regarding, e.g., product design, packaging design, material selection, or operating decisions, adversely affect GHG emissions by other firms in the supply chain.
In this talk we consider supply chains with a motivated dominant leader, such as Walmart, that has the power or authority to assign their suppliers responsibilities for both direct and indirect GHG emissions. Given these responsibility assignments, we use cooperative game theory methodology to derive an allocation scheme of responsibilities for the total GHG emissions in the supply chain. The allocation scheme, which is the Shapley value of an associated cooperative game, is shown to have several desirable properties. In particular, (i) it allocates responsibilities for all the emissions in the supply chain without double counting, (ii) it is transparent and easy to compute, (iii) it lends itself to several intuitive axiomatic characterizations which magnify and clarify its appropriateness as a fair allocation of pollution responsibilities in a supply chain, and (iv) it is shown to incentivize suppliers to exert pollution abatement efforts that, among all footprint-balanced responsibility allocation schemes, minimize the maximum deviation from the socially optimal pollution level.
Joint work with Sanjith Gopalakrishnan, Frieda Granot, Greys Sosic, and Hailong Cui
University of British Columbia
Bio: Daniel Granot is the Affiliates Professor of Management at the Operations and Logistics Division, Sauder School of Business, University of British Columbia. He held visiting positions at Stanford University, Tel Aviv University and IBM. His main research interests are game theory, combinatorial optimization and supply chain management. He has published extensively in operations research journals as well as game theory journals, and he is an INFORMS Fellow.