Tavassoli, Abbas (2017) A Multicriteria Framework for Benchmarking Sustainability Performance of Organizations. Masters thesis, Concordia University.
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Abstract
Sustainability involves meeting the needs of present generation without compromising the requirements of future generations. It involves focus on three main pillars: economic, environmental and social for realizing overall performance. Sustainability assessment is very essential for business organizations to improve their competition capacity. Majority of them are moving towards sustainability practices for corporate progress and improving the business appearance for long term effectiveness, thereby receiving economic benefits as well.
In this thesis, we propose a multi-criteria framework for benchmarking sustainability performance of organizations. The indicators for evaluation are obtained using Sustainalytics database. Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) and Data Envelopment Analysis (DEA) are used to generate sustainability rankings and determine targets for improvement. The proposed techniques are applied to evaluate performance of 24 companies in two major sectors: manufacturing and service. The selected companies come from the Canadian market. The results of TOPSIS study show manufacturing sector to be doing better than the service sector with average Relative Closeness (Ci) values as 0.5 and 0.36 respectively. The DEA method identified 10 inefficient companies in each sector and provided targets for improvement.
Future work can involve integration of financial Key Performance Indicators (KPIs), cross-sector investigation and involvement of Multi-Criteria Decision Making (MCDM) techniques such as Analytic Hierarchy Process (AHP) for criteria weighting in the proposed study.
Divisions: | Concordia University > Gina Cody School of Engineering and Computer Science > Concordia Institute for Information Systems Engineering |
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Item Type: | Thesis (Masters) |
Authors: | Tavassoli, Abbas |
Institution: | Concordia University |
Degree Name: | M.A. Sc. |
Program: | Quality Systems Engineering |
Date: | 17 May 2017 |
Thesis Supervisor(s): | Awasthi, Anjali |
ID Code: | 982596 |
Deposited By: | ABBAS TAVASSOLI |
Deposited On: | 10 Nov 2017 21:37 |
Last Modified: | 18 Jan 2018 17:55 |
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