Multi-Criteria Decision Analysis (MCDA) for Agricultural Sustainability Assessment

Multi-Criteria Decision Analysis (MCDA) for Agricultural Sustainability Assessment

Wilfrid Laurier University Scholars Commons @ Laurier Theses and Dissertations (Comprehensive) 2016 Multi-Criteria Decision Analysis (MCDA) for Agricultural Sustainability Assessment Byomkesh Talukder Wilfrid Laurier University, [email protected] Follow this and additional works at: https://scholars.wlu.ca/etd Part of the Agriculture Commons, Environmental Studies Commons, Geography Commons, Natural Resources Management and Policy Commons, and the Sustainability Commons Recommended Citation Talukder, Byomkesh, "Multi-Criteria Decision Analysis (MCDA) for Agricultural Sustainability Assessment" (2016). Theses and Dissertations (Comprehensive). 1838. https://scholars.wlu.ca/etd/1838 This Thesis is brought to you for free and open access by Scholars Commons @ Laurier. It has been accepted for inclusion in Theses and Dissertations (Comprehensive) by an authorized administrator of Scholars Commons @ Laurier. For more information, please contact [email protected]. Multi-Criteria Decision Analysis (MCDA) for Agricultural Sustainability Assessment By Byomkesh Talukder MSc. Development Science, Hiroshima University, Japan, 2008 Masters in Environmental Studies, Queen’s University, 2012 DISSERTATION Submitted to the Department of Geography, Faculty of Arts in partial fulfillment of the requirements for Doctor of Philosophy in Environmental Resource Management Wilfrid Laurier University © Byomkesh Talukder, 2016 Originality statement I hereby certify and declare that to the best of my knowledge this thesis is entirely my own work. No part of this thesis has been published anywhere. This thesis has been prepared honoring the laws of copyright and property right. Any ideas or intellectual works that are incorporated in this thesis are fully acknowledged with standard procedures of referencing. This is the true copy as approved by my PhD committee and Faculty of Graduate Office. I also certify that this thesis has not been submitted in any educational institute or anywhere for the purpose of gaining a higher degree except Wilfrid Laurier University. i Abstract Multi Attribute Utility Theory (MAUT), Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) and Elimination methods of Multi-Criteria Decision analysis (MCDA) are tested to assess and compare the sustainability of different agricultural systems. Indicators and composite indicators are derived from data gathered using the agricultural sustainability categories of Productivity, Stability, Efficiency, Durability, Compatibility and Equity (PSEDCE). Agricultural systems around the world face challenges from current agricultural practices, over- exploitation of natural resources, population growth and climate change. As a result, understanding agricultural sustainability has become a global issue. Assessment is a first step in benchmarking and tracking agricultural sustainability and can support related policy and programmes. This thesis applied the PSEDCE categories to understand more about the complexities inherent to agricultural sustainability assessment. Agricultural sustainability assessment (ASA) requires a wide variety of ecological, economic and social information with various methods. In the first part of this thesis, a systematic analysis of the scientific soundness and user-friendliness of eight ASA approaches revealed that MCDA based ASA is the preferred holistic method. MCDA can take into account both qualitative and quantitative indicators of all dimensions of sustainability and analyze them to draw a comprehensive picture. As a multifaceted, complex issue, agricultural sustainability assessment is well-suited to MCDA, which is able to handle large data sets including stakeholders’ perspectives. Given that it is a relatively new analysis procedure in the study of agriculture, only a few researchers have applied this technique to measure sustainability. Considering these findings, three MCDA methods, MAUT, PROMETHEE and Elimination, were tested to measure the relative sustainability of five agricultural systems in coastal Bangladesh. To investigate the performance of MAUT, PROMETHEE, and Elimination, a total of 50 indicators from agricultural sustainability categories of PSEDCE were tested. From these 50 indicators, 15 composite indicators were developed through proportionate normalization and hybrid aggregation rules of arithmetic mean and geometric mean. The 15 composite indicators were used in MAUT and PROMETHEE analysis, and the 50 indicators were used in Elimination analysis. ii The analyses show that MAUT is able to aggregate diverse information and stakeholders’ perspectives to generate a robust score that enables a comparison of sustainability across the different agricultural systems. PROMETHEE is a non-compensatory approach that can also accommodate a variety of information and provide thresholds for ranking relative agricultural sustainability for each of the five agricultural systems. Elimination ranks the sustainability of agricultural systems through a set of straightforward decision rules expressed in the form of “if … then …” conditions. Elimination appears to be quick and less complex, whereas MAUT and PROMETHEE are regarded as fairly complicated and require software to find potential solutions. Overall, the study shows that MAUT, PROMETHEE and Elimination can handle multidimensional data and can be applied for relative assessment of sustainability of agricultural systems. However, selection of the appropriate criteria, stakeholders’ perspectives and the purpose of the assessment are very important and must be considered carefully for inclusion in MCDA methods for agricultural sustainability assessment. The results of the case studies also demonstrate that these approaches have the potential to become a useful framework for agricultural sustainability assessment and related policy development and decision-making. iii Acknowledgements I am eternally grateful to my supervisor, Dr. Alison Blay-Palmer, Associate Professor, Department of Geography and Environmental Studies, Wilfrid Laurier University. My thesis is the output of my perfect relationship with my supervisor. I can honestly say that Dr. Blay-Palmer has the best personality for generous, thoughtful, and dedicated mentoring that I have ever encountered in my life. She has been supportive in all stages of my research both technically and personally. She has allowed me to make independent decisions about my research and then given me a lot of feedback so that I can become a better independent researcher. I am grateful to her for providing me with the opportunity to have this rewarding research experience. I could not have completed my PhD without her encouragement, help, support and flexibility. I appreciate that I could share my doubts and problems about the research with her. I have a debt of thankfulness and grateful to Professor Gary W. vanLoon, Emeritus Professor, School of Environmental Studies, Queen’s University, Canada, for his continuous generous guidance, encouragement, help and support in research and in my life. His thoughtful and important advice always kept my research focused. I am also grateful to Professor Keith W. Hipel, Professor, Department of System Design Engineering, University of Waterloo, Canada. I do not have enough words to thank him. What makes him very special is that in his excellent supervisory role he became a mentor and guide with whom I can discuss not only research-related issues but other issues related to academic success. I am also greatly indebted to Professor Rob Milne, Associate Professor, Department of Geography and Environmental Studies, Wilfrid Laurier University, for his consistent guidance and motivation in the right doses for my research. I would like to thank Dr. Donald Noakes, current chair of the mathematics and statistics department and incoming dean of the faculty of science and technology at Vancouver Island University for graciously agreeing to be the external in my PhD defence. His feedback was invaluable as I finalized my dissertation. I am also grateful to my friend Erik, Waterloo University, for his unceasing help to understand the application of PROMTHEE. I would love to work with Erik in the future. iv Big thanks to the Social Sciences and Humanities Research Council (SSHRC) for their financial support for this research. The financial support of SSHRC through the Joseph-Armand Bombardier Canada Graduate Scholarships Program Doctoral Scholarships allowed me to concentrate on my research. Thanks to the Faculty of Graduate & Postdoctoral Studies, Wilfrid Laurier University, for their financial support too. I am thankful to Dr. Michael English, Professor and Chair, Department of Geography and Environmental Studies, Wilfrid Laurier University, and Dr. Brent Wolfe, Professor & Graduate Coordinator, Department of Geography and Environmental Studies, Wilfrid Laurier University, for supporting me during my research. I appreciate the support of all the staff in the Department of Geography and Environmental Studies. They were always very helpful. Huge thanks go to Jo-Anne Horton, Senior Administrative Assistant for the Graduate Program, Department of Geography and Environmental Studies, Wilfrid Laurier University. Her quick support helped me to solve the administrative and bureaucratic issues that accompanied my PhD. I would like to thank Pam Shaus for all her help in creating my poster. I am also grateful to all the staff of the Faculty of Graduate Office, especially Deborah Russell, Graduate Admissions & Records Officer,

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