Rahimidehban, Kian (2023) Performance Measurement in Supply Chain Greenhouse Gas Accounting: Assessing the State of the Practice. Masters thesis, Concordia University.
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Abstract
Supply chain (upstream scope 3) greenhouse gas emissions often account for the majority of a company's total greenhouse gas emissions; however, they are often more challenging to measure and manage than emissions from direct sources (scope 1) or purchased energy (scope 2). Companies use various calculation methodologies and data sources to estimate supply chain emissions. This study evaluated manufacturing and services industry companies' supply chain emissions disclosures to CDP through the lens of GHG Protocol accounting and Supply Chain Performance Measurement (SCPM) principles. A set of indicators for assessing accounting practices according to three GHG Protocol accounting principles –measurement should be complete, accurate, and transparent– and two SCPM metric elements –metrics should show what is happening in a supply chain and be verifiable– were proposed. The results showed that, at most, 32% of disclosures follow both SCPM elements and GHG Protocol principles, and at most, emissions for 6% of supply chain categories are calculated using the emission data collected from suppliers. The results also showed that at least 39% and 32% of supply chain categories have transparency and completeness issues, respectively. This study also found that supply chain disclosures that are more transparent are more likely to be verified by a third party than those that are less transparent. However, a significant number of disclosures that lack transparency is still verified. Overall, the current completeness, accuracy, and transparency issues likely impede companies from reaching scope 3 emissions calculating goals.
Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Mechanical, Industrial and Aerospace Engineering |
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Item Type: | Thesis (Masters) |
Authors: | Rahimidehban, Kian |
Institution: | Concordia University |
Degree Name: | M.A. Sc. |
Program: | Industrial Engineering |
Date: | January 2023 |
Thesis Supervisor(s): | Shannon, Lloyd |
ID Code: | 991708 |
Deposited By: | Kian Rahimidehban |
Deposited On: | 21 Jun 2023 14:36 |
Last Modified: | 21 Jun 2023 14:36 |
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