D-Side: A Facility and Workforce Planning Group Multi-criteria Decision Support System for Johnson Space Center

"To understand and protect our home planet, to explore the universe and search for life, and to inspire the next generation of explorers" is NASA's mission. The Systems Management Office at Johnson Space Center (JSC) is searching for methods to effectively manage the Center's resources to meet NASA's mission. D-Side is a group multi-criteria decision support system (GMDSS) developed to support facility decisions at JSC. D-Side uses a series of sequential and structured processes to plot facilities in a three-dimensional (3-D) graph on the basis of each facility alignment with NASA's mission and goals, the extent to which other facilities are dependent on the facility, and the dollar value of capital investments that have been postponed at the facility relative to the facility replacement value. A similarity factor rank orders facilities based on their Euclidean distance from Ideal and Nadir points. These similarity factors are then used to allocate capital improvement resources across facilities. We also present a parallel model that can be used to support decisions concerning allocation of human resources investments across workforce units. Finally, we present results from a pilot study where 12 experienced facility managers from NASA used D-Side and the organization's current approach to rank order and allocate funds for capital improvement across 20 facilities. Users evaluated D-Side favorably in terms of ease of use, the quality of the decision-making process, decision quality, and overall value-added. Their evaluations of D-Side were significantly more favorable than their evaluations of the current approach. Keywords: NASA, Multi-Criteria Decision Making, Decision Support System, AHP, Euclidean Distance, 3-D Modeling, Facility Planning, Workforce Planning

Multi-Stakeholder Consensus Decision-Making Framework Based on Trust and Risk

Indiana University-Purdue University Indianapolis (IUPUI)This thesis combines human and machine intelligence for consensus decision-making, and it contains four interrelated research areas. Before presenting the four research areas, this thesis presents a literature review on decision-making using two criteria: trust and risk. The analysis involves studying the individual and the multi-stakeholder decision-making. Also, it explores the relationship between trust and risk to provide insight on how to apply them when making any decision. This thesis presents a grouping procedure of the existing trust-based multi-stakeholder decision-making schemes by considering the group decision-making process and models. In the first research area, this thesis presents the foundation of building multi-stakeholder consensus decision-making (MSCDM). This thesis describes trust-based multi-stakeholder decision-making for water allocation to help the participants select a solution that comes from the best model. Several criteria are involved when deciding on a solution such as trust, damage, and benefit. This thesis considers Jain's fairness index as an indicator of reaching balance or equality for the stakeholder's needs. The preferred scenario is when having a high trust, low damages and high benefits. The worst scenario involves having low trust, high damage, and low benefit. The model is dynamic by adapting to the changes over time. The decision to select is the solution that is fair for almost everyone. In the second research area, this thesis presents a MSCDM, which is a generic framework that coordinates the decision-making rounds among stakeholders based on their influence toward each other, as represented by the trust relationship among them. This thesis describes the MSCDM framework that helps to find a decision the stakeholders can agree upon. Reaching a consensus decision might require several rounds where stakeholders negotiate by rating each other. This thesis presents the results of implementing MSCDM and evaluates the effect of trust on the consensus achievement and the reduction in the number of rounds needed to reach the final decision. This thesis presents Rating Convergence in the implemented MSCDM framework, and such convergence is a result of changes in the stakeholders' rating behavior in each round. This thesis evaluates the effect of trust on the rating changes by measuring the distance of the choices made by the stakeholders. Trust is useful in decreasing the distances. In the third research area, this thesis presents Rating Convergence in the implemented MSCDM framework, and such convergence is a result of changes in stakeholders' rating behavior in each round. This thesis evaluates the effect of trust on the rating changes by measuring the perturbation in the rating matrix. Trust is useful in increasing the rating matrix perturbation. Such perturbation helps to decrease the number of rounds. Therefore, trust helps to increase the speed of agreeing upon the same decision through the influence. In the fourth research area, this thesis presents Rating Aggregation operators in the implemented MSCDM framework. This thesis addresses the need for aggregating the stakeholders' ratings while they negotiate on the round of decisions to compute the consensus achievement. This thesis presents four aggregation operators: weighted sum (WS), weighted product (WP), weighted product similarity measure (WPSM), and weighted exponent similarity measure (WESM). This thesis studies the performance of those aggregation operators in terms of consensus achievement and the number of rounds needed. The consensus threshold controls the performance of these operators. The contribution of this thesis lays the foundation for developing a framework for MSCDM that facilitates reaching the consensus decision by accounting for the stakeholders' influences toward one another. Trust represents the influence

Handling a large number of preferences in a multi-level decision-making process

The complexity of a decision is related to the number of persons that are involved, as well as to the diversity of their preferences based on their knowledge, experience or area of expertise. Consequently, it is a challenge to adequately handle a large number of heterogeneous preferences considering that all the participants are considered to be an important source of information to make better motivated decisions. Addressing this challenge constitutes the main motivation in this dissertation because these days decision makers seem to be increasingly interested in the opinions (or preferences) given by persons around a community (and sometimes around the world) through different sources including social media channels. This PhD study provides a set of tools that helps a decision maker to make better motivated decisions by a proper handling of a large number of preferences, identifying and evaluating relevant preferences and handling multiple perspectives. Herein, by 'preference' is meant a greater interest expressed by an individual for a particular alternative over others; by 'relevant' is meant a variety of preferences which are significant (or important) to a particular person acting as a decision maker; and by 'perspective' is understood a position (e.g., social, technical, financial or environmental) adopted by a decision maker when expressing his/ her preferences or constraints

Systems Analysis: Exploring the Spectrum of Diversity

Complex problem spaces, such as those addressed by knowledge management or systems analysis projects, call for complex methods of inquiry. A phenomenon in contextual analysis means that there is a need to go beyond consensus and recognized ‘best practice’. As part of a complex method, for contextual analysis, inter-analysis may be conducted, in which individuals explore one another’s perspectives by discussing individually-created narratives. The purpose is not to seek consensus, but to focus on diversity in viewpoints among participants. In this paper, the authors present an approach in which multiple modelling of problem experiences can bring about shifts of perspectives, create new insights and help deepened understandings to emerge. Techniques are presented that support participants to keep an overview of diversity of in-depth inquiries, while not suffocating under information overload due to the large number of narratives. Participants identify clusters of similar/dissimilar narratives in order to limit the number, but not the range of alternative perspectives. The techniques presented are formally described to promote development of decision support systems

Experimental Investigations on Fairness and Social Norms in Allocation Settings

The research agenda that guides this dissertation is characterized by the three aspects specified in the title. First, all of the projects are experimental investigations. That is, I apply the method of incentivized economic experiments in order to answer research questions through the generation of behavioral data in the "laboratory". Second, all of the experiments involve the elicitation of fairness perceptions or perceptions of social norms. Third, the experimental paradigms used in the projects represent allocation settings, where some active individuals decide about how resources are allocated, while some passive subjects depend on these decisions. Finally, the majority of the projects is connected through a methodological aspect, since most of the experiments contain coordination games, through which I try to draw inferences about the subjects´ traits on the individual level. The combined data of the projects indicate large potential to apply coordination games as an incentivized crowd wisdom device and to use coordination choices on the individual level as a tractable tool to extract private information

Doctor of Philosophy

dissertationClinical decision support systems (CDSS) and electronic health records (EHR) have been widely adopted but do not support a high level of reasoning for the clinician. As a result, workflow incongruity and provider frustrations lead to more errors in reasoning. Other successful fields such as defense, aviation, and the military have used task complexity as a key factor in decision support system development. Task complexity arises during the interaction of the user and the tasks. Therefore, in this dissertation I have utilized different human factor methods to explore task complexity factors to understand their utility in health information technology system design. The first study addresses the question of generalizing complexity through a clinical complexity model. In this study, we integrated and validated a patient and task complexity model into a clinical complexity model tailored towards healthcare to serve as the initial framework for data analysis in our subsequent studies. The second study addresses the question of the coping strategies of infectious disease (ID) clinicians while dealing with complex decision tasks. The study concluded that clinicians use multiple cognitive strategies that help them to switch between automatic cognitive processes and analytical processes. The third study identified the complexity contributing factors from the transcripts of the observations conducted in the ID domain. The clinical complexity model developed in the first study guided the research for identifying the prominent complexity iv factors to recommend innovative healthcare technology system design. The fourth study, a pilot exploratory study, demonstrated the feasibility of developing a population information display from querying real complex patient information from an actual clinical database as well as identifying the ideal features of population information display. In summary, this dissertation adds to the knowledge about how clinicians adapt their information environment to deal with complexity. First, it contributes by developing a clinical complexity model that integrates both patient and task complexity. Second, it provides specific design recommendations for future innovative health information technology systems. Last, this dissertation also suggests that understanding task complexity in the healthcare team domain may help to better design of interface system