Structured decision making as a tool for facilitating stakeholder engagement in non-renewable resource management: using the case study of hydraulic fracturing in the Green Point Shale formation in western Newfoundland

This thesis examines the importance of effective stakeholder engagement that complies with the doctrines of social justice in non-renewable resources management decision-making. It uses hydraulic fracturing in the Green Point Shale Formation in Western Newfoundland as a case study. The thesis uses as theoretical background John Rawls’ and David Miller’ theory of social justice, and identifies the social justice principles, which are relevant to stakeholder engagement. The thesis compares the method of stakeholder engagement employed by the Newfoundland and Labrador Hydraulic Fracturing Review Panel (NLHFRP), with the stakeholder engagement techniques recommended by the Structured Decision Making (SDM) model, as applied to a simulated case study involving hydraulic fracturing in the Green Point Shale Formation. Using the already identified social justice principles, the thesis then developed a framework to measure the level of compliance of both stakeholder engagement techniques with social justice principles. The main finding of the thesis is that the engagement techniques prescribed by the SDM model comply more closely with the doctrines of social justice than the engagement techniques applied by the NLHFRP. The thesis concludes by recommending that the SDM model be more widely used in non- renewable resource management decision making in order to ensure that all stakeholders’ concerns are effectively heard, understood and transparently incorporated in the nonrenewable resource policies to make them consistent with local priorities and goals, and with the social justice norms and institutions.

The relationship between health literacy and indicators of informed decision making for colorectal cancer screening among African Americans

African Americans are disproportionately affected by colorectal cancer (CRC) incidence and mortality. CRC early detection leads to better treatment outcomes and, depending on the screening test, can prevent the development of CRC. African Americans, however, are screened less often than Whites. Aspects of decision making (e.g., decisional conflict, decision self-efficacy) can impact decision making outcomes and may be influenced by social determinants of health, including health literacy. However the relationship between social determinants of health and indicators of decision making in this population is not fully understood. Additionally, individuals have a choice between different CRC screening tests and an individual’s desire to use a particular screening test may be associated with social determinants of health such as health literacy. This study aimed to examine the relationship between social determinants of health and indicators of decision making for CRC screening among African Americans. A total of 111 participants completed a baseline and 14-month follow-up survey assessing decisional conflict, decision self-efficacy, decisional preference (shared versus informed decision making), and CRC test preference. Health literacy was negatively associated with decisional conflict and positively associated with decision self-efficacy (ps < .05). Individuals who were unemployed or working part-time had significantly greater decisional conflict than individuals working full-time (ps < .05). Individuals with a first-degree family history of CRC had significantly lower decision self-efficacy than individuals without a family history (p < .05). Women were significantly more likely to prefer making a shared decision rather than an informed decision compared to men (p < .05). Lastly, previous CRC screening behavior was significantly associated with CRC test preference (e.g., individuals previously screened using colonoscopy were significantly more likely to prefer colonoscopy for their next screening test; ps < .05). These findings begin to identify social determinants of health (e.g., health literacy, employment) that are related to indicators of decision making for CRC among African Americans. Furthermore, these findings suggest further research is needed to better understand these relationships to help with the future development and improvement of interventions targeting decision making outcomes for CRC screening in this population.

Computational approaches to emotional decision making

Findings on the role that emotion plays in human behavior have transformed Artificial Intelligence computations. Modern research explores how to simulate more intelligent and flexible systems. Several studies focus on the role that emotion has in order to establish values for alternative decision and decision outcomes. For instance, Busemeyer et al. (2007) argued that emotional state affects the subjectivity value of alternative choice. However, emotional concepts in these theories are generally not defined formally and it is difficult to describe in systematic detail how processes work. In this sense, structures and processes cannot be explicitly implemented. Some attempts have been incorporated into larger computational systems that try to model how emotion affects human mental processes and behavior (Becker-Asano & Wachsmuth, 2008; Marinier, Laird & Lewis, 2009; Marsella & Gratch, 2009; Parkinson, 2009; Sander, Grandjean & Scherer, 2005). As we will see, some tutoring systems have explored this potential to inform user models. Likewise, dialogue systems, mixed-initiative planning systems, or systems that learn from observation could also benefit from such an approach (Dickinson, Brew & Meurers, 2013; Jurafsky & Martin, 2009). That is, considering emotion as interaction can be relevant in order to explain the dynamic role it plays in action and cognition (see Boehner et al., 2007).

Designing Efficient Subsidy Policies in a Regional Economy: A Multicriteria Decision-Making (MCDM)-Computable General Equilibrium (CGE) Approach

Since policy-makers usually pursue several conflicting objectives, policy-making can be understood as a multicriteria decision problem. Following the methodological proposal by André and Cardenete (2005) André, F. J. and Cardenete, M. A. 2005. Multicriteria Policy Making. Defining Efficient Policies in a General Equilibrium Model, Seville: Centro de Estudios Andaluces. Working Paper No. E2005/04, multi-objective programming is used in connection with a computable general equilibrium model to represent optimal policy-making and to obtain so-called efficient policies in an application to a regional economy (Andalusia, Spain). This approach is applied to the design of subsidy policies under two different scenarios. In the first scenario, it is assumed that the government is concerned just about two objectives: ensuring the profitability of a key strategic sector and increasing overall output. Finally, the scope of the exercise is enlarged by solving a problem with seven policy objectives, including both general and sectorial objectives. It is concluded that the observed policy could have been Pareto-improved in several directions.

Attitudes towards risk in financial decision making

Doutoramento em Gestão

Assessing Decision Making Skill in Complex and Dynamic Environments Using Representative and Simulated Tasks

Traditional decision making research has often focused on one's ability to choose from a set of prefixed options, ignoring the process by which decision makers generate courses of action (i.e., options) in-situ (Klein, 1993). In complex and dynamic domains, this option generation process is particularly critical to understanding how successful decisions are made (Zsambok & Klein, 1997). When generating response options for oneself to pursue (i.e., during the intervention-phase of decision making) previous research has supported quick and intuitive heuristics, such as the Take-The-First heuristic (TTF; Johnson & Raab, 2003). When generating predictive options for others in the environment (i.e., during the assessment-phase of decision making), previous research has supported the situational-model-building process described by Long Term Working Memory theory (LTWM; see Ward, Ericsson, & Williams, 2013). In the first three experiments, the claims of TTF and LTWM are tested during assessment- and intervention-phase tasks in soccer. To test what other environmental constraints may dictate the use of these cognitive mechanisms, the claims of these models are also tested in the presence and absence of time pressure. In addition to understanding the option generation process, it is important that researchers in complex and dynamic domains also develop tools that can be used by `real-world' professionals. For this reason, three more experiments were conducted to evaluate the effectiveness of a new online assessment of perceptual-cognitive skill in soccer. This test differentiated between skill groups and predicted performance on a previously established test and predicted option generation behavior. The test also outperformed domain-general cognitive tests, but not a domain-specific knowledge test when predicting skill group membership. Implications for theory and training, and future directions for the development of applied tools are discussed.

Enabling effective operational decision making on a Combined Heat and Power System using the 5C architecture

The use of Cyber Physical Systems (CPS) to optimise industrial energy systems is an approach which has the potential to positively impact on manufacturing sector energy efficiency. The need to obtain data to facilitate the implementation of a CPS in an industrial energy system is however a complex task which is often implemented in a non-standardised way. The use of the 5C CPS architecture has the potential to standardise this approach. This paper describes a case study where data from a Combined Heat and Power (CHP) system located in a large manufacturing company was fused with grid electricity and gas models as well as a maintenance cost model using the 5C architecture with a view to making effective decisions on its cost efficient operation. A control change implemented based on the cognitive analysis enabled via the 5C architecture implementation has resulted in energy cost savings of over €7400 over a four-month period, with energy cost savings of over €150,000 projected once the 5C architecture is extended into the production environment.

Information from managing information systems as a fundamental element to support decision-making in hospitals

This article deals with the activity of defining information of hospital systems as fundamental for choosing the type of information systems to be used and also the organizational level to be supported. The use of hospital managing information systems improves the user`s decision -making process by allowing control report generation and following up the procedures made in the hospital as well.

Decision making in fuzzy environment and multicriteria power engineering problems

This paper presents results of research into the use of the Bellman-Zadeh approach to decision making in a fuzzy environment for solving multicriteria power engineering problems. The application of the approach conforms to the principle of guaranteed result and provides constructive lines in computationally effective obtaining harmonious solutions on the basis of solving associated maxmin problems. The presented results are universally applicable and are already being used to solve diverse classes of power engineering problems. It is illustrated by considering problems of power and energy shortage allocation, power system operation, optimization of network configuration in distribution systems, and energetically effective voltage control in distribution systems. (c) 2011 Elsevier Ltd. All rights reserved.

Multicriteria analysis in decision making under information uncertainty

This paper presents results of research related to multicriteria decision making under information uncertainty. The Bell-man-Zadeh approach to decision making in a fuzzy environment is utilized for analyzing multicriteria optimization models (< X, M > models) under deterministic information. Its application conforms to the principle of guaranteed result and provides constructive lines in obtaining harmonious solutions on the basis of analyzing associated maxmin problems. This circumstance permits one to generalize the classic approach to considering the uncertainty of quantitative information (based on constructing and analyzing payoff matrices reflecting effects which can be obtained for different combinations of solution alternatives and the so-called states of nature) in monocriteria decision making to multicriteria problems. Considering that the uncertainty of information can produce considerable decision uncertainty regions, the resolving capacity of this generalization does not always permit one to obtain unique solutions. Taking this into account, a proposed general scheme of multicriteria decision making under information uncertainty also includes the construction and analysis of the so-called < X, R > models (which contain fuzzy preference relations as criteria of optimality) as a means for the subsequent contraction of the decision uncertainty regions. The paper results are of a universal character and are illustrated by a simple example. (c) 2007 Elsevier Inc. All rights reserved.

Risk-based decision making method for maintenance policy selection of thermal power plant equipment

This study presents a decision-making method for maintenance policy selection of power plants equipment. The method is based on risk analysis concepts. The method first step consists in identifying critical equipment both for power plant operational performance and availability based on risk concepts. The second step involves the proposal of a potential maintenance policy that could be applied to critical equipment in order to increase its availability. The costs associated with each potential maintenance policy must be estimated, including the maintenance costs and the cost of failure that measures the critical equipment failure consequences for the power plant operation. Once the failure probabilities and the costs of failures are estimated, a decision-making procedure is applied to select the best maintenance policy. The decision criterion is to minimize the equipment cost of failure, considering the costs and likelihood of occurrence of failure scenarios. The method is applied to the analysis of a lubrication oil system used in gas turbines journal bearings. The turbine has more than 150 MW nominal output, installed in an open cycle thermoelectric power plant. A design modification with the installation of a redundant oil pump is proposed for lubricating oil system availability improvement. (C) 2009 Elsevier Ltd. All rights reserved.

Sequential decision making with partially ordered preferences

This paper presents new insights and novel algorithms for strategy selection in sequential decision making with partially ordered preferences; that is, where some strategies may be incomparable with respect to expected utility. We assume that incomparability amongst strategies is caused by indeterminacy/imprecision in probability values. We investigate six criteria for consequentialist strategy selection: Gamma-Maximin, Gamma-Maximax, Gamma-Maximix, Interval Dominance, Maximality and E-admissibility. We focus on the popular decision tree and influence diagram representations. Algorithms resort to linear/multilinear programming; we describe implementation and experiments. (C) 2010 Elsevier B.V. All rights reserved.