Decision making

Policy formation involves an interplay of decision-making processes that shape all policy process stages. A critical aspect of the design process is selecting policy tools to align with policy goals. The First Step Act (FSA) (2018) aims to reduce recidivism and reform sentencing through a robust policy tool portfolio. However, questions persist about how policy tools are selected. This dissertation evaluates the policy design, tool choices, and collaborative networks associated with these choices. Grounded in the social construction framework and using content analysis and discourse network analysis (DNA), this dissertation examines how policymakers select policy tools to achieve functionality.
Research question one explores the complementarity of the FSA’s policy tool portfolio, and results demonstrate alignment between policy goals and corresponding policy tools. Research question two examines how social constructions of target populations and political affiliations influence policy tool choices; hypothesis one reveals that liberal policymakers align with those with similar political affiliations. Results from hypothesis two indicate liberal policymakers adopt a rehabilitation orientation tool approach, viewing target populations as investments and deserving of support structures. The findings also highlight limited interaction with government agency officials, reflecting a need to incorporate more administrative voices into legislative discourse.

This empirical study examines decision-making in project selection in the face of overwhelming flood infrastructure needs and inadequate resources, particularly in vulnerable communities. The motivation for this study is to explore the interconnectedness between socioeconomic dimensions and environmental risks in the decision-making process for selecting projects. The study evaluates the Palm Beach County project selection framework and the impact of multi-criteria decision-making on project selection by proposing a new framework. The new project selection framework emphasizes the integration of flood risk and social vulnerability index criteria to evaluate the relationship between the new criteria in the decision-making framework and project selection.
The analysis is comprised of 24 models grouped into three distinct groups and compared using paired t-tests. The analysis reveals that of the three groups, the group which incorporates both flood risks and social vulnerability criteria consistently outperforms the others, demonstrating its effectiveness in providing a more equitable investment for vulnerable communities that are more susceptible to floods. The findings provide valuable insights and recommendations for practitioners and scholars, emphasizing the need for a theoretical framework with objectivity to guide optimal infrastructure investments for decision makers.

In this qualitative grounded theory study, I interviewed participants from and analyzed documents associated with three community/state colleges in Florida. Additionally, I have included the perspective of key informants from the state and/or the Florida College System. The purpose of this qualitative grounded theory study was to develop a substantive theory to explain the process by which senior administrative leaders engaged in fiscal decision-making due to shifting funding sources during the COVID-19 pandemic. Although prior decision-making theories exist, such as rational choice theory and garbage can theory, these theories do not address how fiscal decisions are made in higher education institutions during times of extended crisis exemplified by the COVID-19 pandemic. This research study found that during the COVID-19 pandemic leaders sought to establish resilience as part of their fiscal decision-making process to ensure their ability to lead and maintain viable institutions of higher education. Moreover, through the fiscal decision-making process, the leaders in this study did not permit themselves or their institutions to accept the status quo, rather they extended themselves and their organizations to stretch beyond prior capabilities to respond to ever changing needs of students as well as external stakeholders brought about from the COVID-19 pandemic. The collective experiences of these leaders during the COVID-19 pandemic resulted in the resilient stretching theory of community college fiscal decision-making, which will be further expounded upon throughout this research study.

Social influence is sought to distribute information processing for decision-making when data is limited. Undergraduate students selected information with normative or informational wording to supplement a fabricated academic integrity appeal from their university and decided whether to affirm the charge. A novel measure, the Adaptive Scale of Preference for Normative Versus Informational Social Influence (ASPNVISI), was piloted in comparison with a Polish scale of influence preference, individual difference measures in motivation (e.g., Need for Closure), and behavioral measures of influence-seeking. Results did not support the hypotheses that psychological needs would predict behavioral social influence preferences, though Need for Cognition and Need to Belong predicted self-reported preferences. The ASPNVISI was correlated with the existing scale of influence preference, providing support for its continued development. Contrary to the hypothesis, confidence in the decision on a charge of academic dishonesty was not related to selected influence; race and conservatism were related to confidence, and gender to the selections. Next steps include further pilot testing of the ASPNVISI and expansion of the behavioral task.

Assessment is frequently cited within the student affairs literature as a way of continuously improving programs, services, and events (Henning & Roberts, 2016; Upcraft & Schuh, 1996). However, the data collected through assessment is infrequently used to improve student affairs offerings due to practitioners’ fear, practitioner’s lack of training, a lack of leadership within the division or university, or an emphasis on assessment as a method of reporting results rather than improving offerings, such as programs, services, initiatives, or events (Cox et al., 2017; Fuller & Lane, 2017). In the limited published studies about how student affairs professionals use assessment data, many professionals admit they do not have a plan to use their assessment data and only a small number have a plan to use their assessment data to make changes (Beshara-Blauth, 2018; Cox et al., 2017; McCaul, 2015; Parnell et al., 2018; Ridgeway, 2014). The purpose of this qualitative study was to understand how student affairs directors who have been identified as exemplars use their assessment data to make changes. The research questions for the study were: 1) How do student affair directors use assessment data in their role to make changes? 2) How do student affairs directors learn to use their data to make changes? And, 3) What influences student affairs directors to use their data to make changes?

Supply chain challenges have been significantly affected by both demand and supply on a global level. The selection of manufacturing countries has become critical to firms and their boards, even more so coming out of the COVID-19 global pandemic. The present study focuses on how firms select countries and regions to de-risk future global apparel sourcing, as countries that have been dependable in the past may not be in the future based on frequent environmental jolts, legacy supply chain failures, shifting government policy, and extreme volatility. The result of this study is a decision model for manufacturing country selection. This research was focused on the apparel industry; however, further research may indicate that it is applicable to other industries. A group of criteria was selected, the relative significance of these criterion was determined using the Analytical Hierarchy Process (AHP). The AHP methodology was applied in a case study as a decision-making tool to enable decision-makers to assess the most suitable countries for manufacturing country selection. The result of this study is a decision model for manufacturing country selection based on multiple criteria weighted by industry experts using Analytical Hierarchy Process (AHP). In developing the model we utilize data from 61 countries representing over 95% of all the global apparel exports, with criteria utilized originating from 10 indices.

High-profile police use-of-force events, like the deaths of Trevon Martin, Freddie Gray, Alton Sterling, and George Floyd, have increased scrutiny towards law enforcement, and many believe that racial disparities in the justice system are caused by biased decision-making. The subsequent protests and civil unrest have furthered the divide between the police and members of the public, which has damaged police legitimacy and led to depolicing and militarization. This study pilot tests the impact of implicit bias on decision-making for a student sample with a decision-making simulator and an experimental design with random assignment. Simulated police-public contacts, substantively, were found to be very complex and largely guided by legal factors; however, stressful stimuli can affect decision-making. The forthcoming protocol and methodology, moreover, provide insight to decision-making and create a framework to guide future research.

Florida has 906,465 residential properties facing substantial flood risk, making it imperative to understand how the public may perceive and respond to this risk. Providing people with scientific information may not be enough to impact behavior and decrease losses from flood events. We show participants (n = 20) scientific flood risk graphics and ask behavioral questions to evaluate responses based on the rational actor paradigm (RAP), psychometric paradigm, and cultural theory. We find results consistent with the RAP in 48% of cases, primarily in low risk scenarios. Participants from high income households are more likely to make rational decisions (80%) than those from low income households (~37%). Feelings of dread potentially help explain 40% of deviations from the RAP, while trust in flood experts helps explain 85% of non-RAP cases. Future flood risk communication should incorporate dread and trust in experts into messaging considerations as rationality alone is insufficient.

The purpose of this qualitative study was to explore the process of complex healthcare decision-making by parents for their children within the milieu of a pediatric palliative care team. As healthcare has advanced, the number of children living with complex chronic conditions has increased. Decision-making by parents for their children referred to palliative care has not, up to this point, been widely explored by nursing. A purposeful sample of 22 participants, parents of children in life-limiting or life-threatening situations were asked: What matters most during the process of complex healthcare decision-making?
A constant comparative method was used to analyze data collected from semistructured interviews and the theory of embodying parenting in the midst of conflicting complexity emerged. J. Watson’s (2020) theory of human caring grounded the researcher in living caritas processes throughout the study. All participants experienced a disruption of their expected parenting and family normal. Through constant comparative data analysis, the core category of embodying parenting was identified. Feeling respected as the parent, thoughtfully making right decisions, and maintaining presence support embodying parenting. The basic social process identified was finding a unique path. The process of finding a unique path included connecting with a supportive community, claiming decisional authority, moderating negative thoughts and feelings, and adjusting expectations. Living in peace was achieved by finding a unique path to embodying parenting in the midst of conflicting complexity. For the participants in this study, accepting circumstances, feeling gratitude, and perceiving life differently led to living in peace.

We have developed a method of quantifying multiple-choice test items in an
introductory physical science course in terms of the various tasks required to solve
the problem. We assign a numerical level of difficulty to each task so that any
question can be assigned a degree of difficulty, which is the sum of the individual
levels of difficulty associated in each steps. Using the questions and results from the
tests we have investigated the relationship between the degree of difficulty of each
question and the corresponding discrimination index. Our results indicate that as the
degree of difficulty increases so does the capability of the item to discriminate
between students with different abilities. There is a maximum degree of difficulty
beyond which the discrimination starts to decrease. At that point, test items become
too difficult. Thus, it should be possible in future to design items that will provide
optimum discrimination.