Amer Obeidi

Adaptive Systems Thinking in Integrated Water Resources Management with Insights into Conflicts over Water Exports

Abstract Formal decision analysis techniques involving multiple stakeholders and multiple objectives are designed from a system of systems engineering perspective to address, within an adaptive integrative management framework, water resources problems of great importance to social policy and governance. The Graph Model for Conflict Resolution and other formal systems methodologies operationalize this management framework for real world decision support within the philosophical structures of operational research, systems engineering and integrative management. To illustrate how a formal systems methodology can produce better understanding of water conflicts and improved guidance for strategic decision making, the Graph Model for Conflict Resolution is explained and applied to controversies surrounding proposals for the bulk export of water from Canada. In particular, conflict analyses of bulk water disputes in Eastern Canada (Gisbourne Lake) and Western Canada (Sun Belt) reveal that future bulk water exports are strategically possible, and that dispute resolution mechanisms embedded within international trade agreements can potentially supersede national laws, allowing investors to take control of water resources even if there are irreparable environmental and ecological consequences.

Strategic and Dilemma Analyses of a Water Export Conflict

Abstract Two distinct approaches to formally studying conflict are described and compared by applying them to three different phases of an international controversy that arose when a private company was not allowed to export water from Canada. In each phase, the graph model for conflict resolution is employed for obtaining equilibria and strategic insights while confrontation analysis, a procedure for applying drama theory, is used to expose dilemmas faced by the decision makers. The results of the conflict analyses obtained for the three phases indicate thai the two techniques complement one another and thereby provide a broader understanding about what occurred and how the dispute evolved over time. A potential resolution to the conflict occurs at a strategically stable outcome when decision makers do not face any dilemmas and their emotions are dissipated.

Modeling Fuzzy and Interval Fuzzy Preferences Within a Graph Model Framework

A methodology is developed to model a decision makers (DMs) fuzzy and/or interval fuzzy preference over feasible scenarios or states within the framework of the graph model for conflict resolution. This technique uses the DMs fuzzy relative importance of its preference statements and their fuzzy truth values for the feasible states in a conflict under uncertain conditions. A preference statement of a DM is a preferable combination of DMs options or courses of action. The fuzzy importance for one preference statement over another, a value in the interval [0, 1], is interpreted as the degree to which the first preference statement is more important than the second to the DM. A fuzzy truth value of a preference statement at a feasible state is a number in the interval [0, 1] that represents the degree to which the statement is true at the state. When the DM is confident in its pairwise fuzzy importance degrees over the preference statements and their fuzzy truth values at the feasible states, the methodology provides a fuzzy preference over the states. When there is an ordinary or crisp importance ordering of preference statements and when the truth values of preference statements are classical or crisp at the feasible states, the technique generates a crisp preference over the states. The methodology is illustrated using a case study.

Coalition fuzzy stability analysis in the Graph Model for Conflict Resolution

Coalition fuzzy stability concepts are developed within the Fuzzy Preference Framework for the Graph Model for Conflict Resolution to investigate how decision makers can cooperate. The objective is to identify favorable outcome(s) in a multiple participant-multiple objective decision problem with fuzzy preference information. More specifically, coalition versions of fuzzy Nash stability, fuzzy general metarationality, fuzzy symmetric metarationality, and fuzzy sequential stability are proposed. They constitute a natural generalization of the corresponding non-cooperative fuzzy preference-based definitions for Nash stability, general metarationality, symmetric metarationality, and sequential stability, respectively. Coalition fuzzy stability definitions are employed to analyze an actual dispute over groundwater contamination in Elmira, Ontario, Canada, demonstrating how these new concepts can be conveniently applied to practical problems in order to gain valuable strategic insights.

The Keystone XL Pipeline Dispute Over Transferring Bitumen from the Alberta Oil Sands to US Refineries

A strategic investigation is carried out for the conflict arising over the construction of the Keystone XL pipeline to transfer unrefined bitumen from the Alberta oil sands in Canada to refineries located in the Southern part of the United States. Through categorizing the different aspects of this conflict into environmental (e.g. threats to water resources such as Ogallala Aquifer), political, and economic dimensions, this crucial real-world conflict can be better understood and more realistically investigated. In this study, decision makers are divided (based on their authority to decide over the destiny of the project) into two groups, main and influential. Then, based on real world events, occasions, and relationships, their current situations, future options, and preferences are identified. Using the knowledge developed in this process and through the use of the Graph Model for Conflict Resolution technique, the aforementioned pipeline conflict is formally modeled and analyzed to gain strategic insights into its resolution.

Strategic advice for decision-making under conflict based on observed behaviour

An improvement in the inverse engineering of preferences approach for the Graph Model for Conflict Resolution is introduced. In addition to providing decision-makers and analysts with up-to-date preference information about opponents, the methodology is now equipped with an Advice function which enriches the decision-making process by providing important information regarding potential moves. Decision-makers who use the methods introduced in this paper are provided with the expected value of each of their possible moves, with the probability of the opponent’s next response, and with the opponent reachable states. This insightful information helps establish an accurate picture of the conflict situation and in so doing, aids stakeholders in making strategic decisions.