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

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. 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

Validating a Multi-criteria decision analysis (MCDA) framework for health care decision making: poster

OBJECTIVES: When evaluating healthcare interventions, decision-makers are increasingly asked to consider multiple criteria to support their decision. The MCDA-based EVIDEM framework was developed to support this process. It includes a simple weight elicitation technique, designed to be easily applicable by a broad range of users. The objective of this study was to compare the EVIDEM technique with more traditional techniques. METHODS: An online questionnaire was developed comparing the EVIDEM technique with four alternative techniques including AHP, best/worst scaling, ranking and point-allocation. A convenience sample of 60 Dutch and Canadian students were asked to fill out the questionnaires as if they were sitting in an advisory committee for reimbursement/prioritization of healthcare interventions. They were asked to provide weights for 14 criteria using two techniques, and to provide feedback on ease of use and clarity of concepts of the different techniques. RESULTS: Results based on the first 30 responses show that EVIDEM is easy to understand and takes little time to complete, three minutes on average. Criteria weights derived using the EVIDEM technique and best/worst scaling are divergent. Comparing the rank order of criteria respondents gave using these two techniques; there is more resemblance in rank order of criteria weighted with the EVIDEM technique. Compared to AHP/ranking/point-allocation, EVIDEM takes less time to complete but is only preferred by 33% of decision-makers. AHP/ranking and point allocation were often described as clearer and more reflective of the respondents’ opinion. CONCLUSIONS: The simple technique is proposed as a starting point for users wishing to adapt the EVIDEM framework to their own context. Other techniques may be preferred and their impact on the MCDA value estimate generated by applying the framework is being explored. This project is part of a large collaborative work that includes developing and validating this framework to facilitate sound and efficient MCDA-applications

Validating a Multi-criteria decision analysis (MCDA) framework for health care decision making (abstract)

OBJECTIVES: When evaluating healthcare interventions, decision-makers are increasingly asked to consider multiple criteria to support their decision. The MCDA-based EVIDEM framework was developed to support this process. It includes a simple weight elicitation technique, designed to be easily applicable by a broad range of users. The objective of this study was to compare the EVIDEM technique with more traditional techniques. METHODS: An online questionnaire was developed comparing the EVIDEM technique with four alternative techniques including AHP, best/worst scaling, ranking and point-allocation. A convenience sample of 60 Dutch and Canadian students were asked to fill out the questionnaires as if they were sitting in an advisory committee for reimbursement/prioritization of healthcare interventions. They were asked to provide weights for 14 criteria using two techniques, and to provide feedback on ease of use and clarity of concepts of the different techniques. RESULTS: Results based on the first 30 responses show that EVIDEM is easy to understand and takes little time to complete, three minutes on average. Criteria weights derived using the EVIDEM technique and best/worst scaling are divergent. Comparing the rank order of criteria respondents gave using these two techniques; there is more resemblance in rank order of criteria weighted with the EVIDEM technique. Compared to AHP/ranking/point-allocation, EVIDEM takes less time to complete but is only preferred by 33% of decision-makers. AHP/ranking and point allocation were often described as clearer and more reflective of the respondents’ opinion. CONCLUSIONS: The simple technique is proposed as a starting point for users wishing to adapt the EVIDEM framework to their own context. Other techniques may be preferred and their impact on the MCDA value estimate generated by applying the framework is being explored. This project is part of a large collaborative work that includes developing and validating this framework to facilitate sound and efficient MCDA-applications

Multi-Criteria Decision Analysis (MCDA) in Forest Operations – an Introductional Review

Decision making in forestry is very complex and requires consideration of trade-offs among economic, environmental, and social criteria. Different multi-criteria decision analysis (MCDA) methods have been developed for structuring and exploring the decision-making process of such problems. Although MCDA methods are often used for forest management problems, they are rarely used for forest operation problems. This indicates that scholars and practitioners working with forest operations are either unaware of MCDA methods, or see no benefit in using these methods. Therefore, the prime objective of this review was to make MCDA methods more intelligible (compared with current level of understanding) to novice users within the field of forest operations. For that purpose, basic ideas as well as the strengths and limitations of selected MCDA methods are presented. The second objective was to review applications of MCDA methods in forest operations. The review showed that MCDA applications are suitable for forest operation problems on all three planning levels – strategic, tactical, and operational – but with least use on the operational level. This is attributed to: 1) limited availability of temporally relevant and correct data, 2) lack of time (execution of MCDA methods is time consuming), and 3) many operational planning problems are solved with regards to an economic criterion, with other criteria serving more as frames. However, with increased importance of environmental and social aspects, incorporating MCDA methods into the decision-making process on the operational planning horizon (e.g., by developing MCDAbased guidelines for forestry work) is essential

Multi-Criteria Decision Analysis (MCDA) in Forest Operations – an Introductional Review

Decision making in forestry is very complex and requires consideration of trade-offs among economic, environmental, and social criteria. Different multi-criteria decision analysis (MCDA) methods have been developed for structuring and exploring the decision-making process of such problems. Although MCDA methods are often used for forest management problems, they are rarely used for forest operation problems. This indicates that scholars and practitioners working with forest operations are either unaware of MCDA methods, or see no benefit in using these methods. Therefore, the prime objective of this review was to make MCDA methods more intelligible (compared with current level of understanding) to novice users within the field of forest operations. For that purpose, basic ideas as well as the strengths and limitations of selected MCDA methods are presented. The second objective was to review applications of MCDA methods in forest operations. The review showed that MCDA applications are suitable for forest operation problems on all three planning levels – strategic, tactical, and operational – but with least use on the operational level. This is attributed to: 1) limited availability of temporally relevant and correct data, 2) lack of time (execution of MCDA methods is time consuming), and 3) many operational planning problems are solved with regards to an economic criterion, with other criteria serving more as frames. However, with increased importance of environmental and social aspects, incorporating MCDA methods into the decision-making process on the operational planning horizon (e.g., by developing MCDAbased guidelines for forestry work) is essential

Analisis Keberlanjutan Energi Pada Industri Gula Menggunakan Multi-Criteria Decision Analysis (MCDA)

Adanya masalah keberlanjutan energi, industri gula mulai melihat rencana untuk menjual listrik untuk mengatasi masalah keberlanjutan energi. Skenario dengan potensi untuk memanfaatkan surplus energi memotivasi penelitian ini untuk menganalisis strategi pengembangan industri gula. Dalam situasi seperti ini, multi-criteria decision analysis (MCDA) sangat berguna untuk pemilihan alternatif yang tepat. Tiga metode MCDA yaitu analytic hierarchy process (AHP), analytic network process (ANP) dan swing weight method (SWM) diterapkan untuk pemilihan strategi yang tepat. Studi ini menganalisis potensi penjualan listrik pada dua strategi pengembangan pabrik alternatif dari tiga industri tebu yang dari hasil tersebut, strategi A (skema pengembangan masing-masing pabrik menjadi pabrik kogenerasi) memungkinkan untuk menjual listrik selama 223-293 hari sementara strategi B (skema pengembangan salah satu pabrik untuk menjadi pembangkit tunggal) memungkinkan untuk menjual sepanjang tahun. Studi ini menganalisa lima skenario metode pemilihan yakni satu model AHP, tiga model skenario ANP dan satu model SWM. Hasilnya menunjukkan bahwa dengan menggunakan MCDA, ditemukan bahwa strategi B lebih baik daripada strategi A dengan hasil bobot prioritas antara strategi A dan B untuk metode AHP, ANP-0, ANP-1, ANP-2 dan SWM berturut-turut adalah 0,42:0,58; 0,49:0,51; 0,48:0,52; 0,52:0,48 dan 0,28:0,72. Studi ini juga membandingkan alternatif pengembangan pabrik dan menganalisis perbandingan alternatif menggunakan ketiga metode MCDM, dimana secara umum didapatkan bahwa strategi B lebih baik dibandingkan dengan strategi A. ========================================================= Given the problem of energy sustainability, the sugar industry is beginning to figure plans to sell electricity to address the issue of energy sustainability. Scenarios with the potential to utilize energy surplus motivate this research to analyze the strategy of developing the sugar industry. In situations like this, multi-criteria decision analysis (MCDA) is very useful for selecting the right alternative. Three MCDA methods, analytic hierarchy process (AHP), analytic network process (ANP) and swing weight method (SWM), are applied for the selection of appropriate strategies. This study analyzes the potential for the sale of electricity in two alternative plant development strategies from the three sugarcane industries, which the strategy A (the development scheme of each plant to a cogeneration plant) makes it possible to sell electricity for 223-293 days while strategy B (development scheme of one factory to become a independent power plant) allows to sell throughout the year. This study analyzes five scenarios of the selection method which are one AHP model, three ANP scenario models and one SWM model. The results show that by using MCDA, it is found that strategy B is better than strategy A which the priority weighting results between strategy A and B for AHP, ANP-0, ANP-1, ANP-2 and SWM methods respectively were 0.42: 0.58; 0.49: 0.51; 0.48: 0.52; 0.52: 0.48 and 0.28: 0.72. This study also compares plant development alternatives and analyzed alternative comparisons using the three MCDM methods, where it is generally found that strategy B is better than strategy A

A participatory approach for assessing alternative climate change adaptation responses to cope with flooding risk in the upper Brahmaputra and Danube river basins

This work illustrates the preliminary findings of a participatory research process aimed at identifying responses for sustainable water management in a climate change perspective, in two river basins in Europe and Asia. The paper describes the methodology implemented through local workshops, aimed at eliciting and evaluating possible responses to flooding risk. Participatory workshops allowed for the identification of four categories of possible responses and a set of nine evaluation criteria, three for each of the three pillars of sustainable development. The main result of such activities consists in the ranking of broad response categories, to contribute to the orientation of the Brahmatwinn research project towards the identification of Integrated Water Resource Management Strategies (IWRMS) well grounded upon the issues and preferences elicited from local experts. The mDSS tool was used to facilitate transparent and robust management of the information collected through Multi-Criteria Decision Analysis (MCDA) and the communication of the outputs.Participatory process, Climate Change, Flooding Risk, Decision Support System, MCDA

Structuring an MCDA model using SSM: A case study in energy efficiency

This work presents the use of a problem structuring method, Soft Systems Methodology (SSM), to structure a Multi-Criteria Decision Analysis (MCDA) model, aimed at appraising energy efficiency initiatives. SSM was useful to help defining clearly the decision problem context and the main actors involved, as well as to unveil the relevant objectives for each stakeholder. Keeney’s Value Focused Thinking approach was then used to refine and structure the list of objectives according to the perspective of the main evaluators identified. In addition to describing this particular case study, this paper aims at providing some general guidelines on how SSM may facilitate the emergence of objectives for MCDA models.info:eu-repo/semantics/publishedVersio