Public participation in Michigan mining policy : the Kennecott Eagle Project case

Public participation is an important component of Michigan’s Part 632 Nonferrous Mining law and is identified by researchers as important to decision-making processes. The Kennecott Eagle Project, which is located near Marquette, Michigan, is the first mine permitted under Michigan’s new mining regulation, and this research examines how public participation is structured in regulations, how the permitting process occurred during the permitting of the Eagle Project, and how participants in the permitting process perceived their participation. To understand these issues, this research implemented a review of existing mining policy and public participation policy literature, examination of documents related to the Kennecott Eagle Project and completion of semi-structured, ethnographic interviews with participants in the decision-making process. Interviewees identified issues with the structure of participation, the technical nature of the permitting process, concerns about the Michigan Department of Environmental Quality’s (DEQ) handling of mine permitting, and trust among participants. This research found that the permitting of the Kennecott Eagle Mine progressed as structured by regulation and collected technical input on the mine permit application, but did not meet the expectations of some participants who opposed the project. Findings from this research indicated that current mining regulation in Michigan is resilient to public opposition, there is need for more transparency from the Michigan DEQ during the permitting process, and current participatory structures limit the opportunities for some stakeholder groups to influence decision-making.

Financial decision making about found oil and gas in Ghana : real options vs. traditional methods

This research is a study of the use of capital budgeting methods for investment decisions. It uses both the traditional methods and the newly introduced approach called the real options analysis to make a decision. The research elucidates how capital budgeting can be done when analysts encounter projects with high uncertainty and are capital intensive, for example oil and gas production. It then uses the oil and gas find in Ghana as a case study to support its argument. For a clear understanding a thorough literature review was done, which highlights the advantages and disadvantages of both methods. The revenue that the project will generate and the costs of production were obtained from the predictions by analysts from GNPC and compared to others experts’ opinion. It then applied both the traditional and real option valuation on the oil and gas find in Ghana to determine the project’s feasibility. Although, there are some short falls in real option analysis that are presented in this research, it is still helpful in valuing projects that are capital intensive with high volatility due to the strategic flexibility management possess in their decision making. It also suggests that traditional methods of evaluation should still be maintained and be used to value projects that have no options or those with options yet the options do not have significant impact on the project. The research points out the economic ripples the production of oil and gas will have on Ghana’s economy should the project be undertaken. These ripples include economic growth, massive job creation and reduction of the balance of trade deficit for the country. The long run effect is an eventually improvement of life of the citizens. It is also belief that the production of gas specifically can be used to generate electricity in Ghana which would enable the country to have a more stable and reliable power source necessary to attract more foreign direct investment.

Assessing Decision Making Strategies In Construction Management By Using A Schedule-Based Simulation Framework

During the project, managers encounter numerous contingencies and are faced with the challenging task of making decisions that will effectively keep the project on track. This task is very challenging because construction projects are non-prototypical and the processes are irreversible. Therefore, it is critical to apply a methodological approach to develop a few alternative management decision strategies during the planning phase, which can be deployed to manage alternative scenarios resulting from expected and unexpected disruptions in the as-planned schedule. Such a methodology should have the following features but are missing in the existing research: (1) looking at the effects of local decisions on the global project outcomes, (2) studying how a schedule responds to decisions and disruptive events because the risk in a schedule is a function of the decisions made, (3) establishing a method to assess and improve the management decision strategies, and (4) developing project specific decision strategies because each construction project is unique and the lessons from a particular project cannot be easily applied to projects that have different contexts. The objective of this dissertation is to develop a schedule-based simulation framework to design, assess, and improve sequences of decisions for the execution stage. The contribution of this research is the introduction of applying decision strategies to manage a project and the establishment of iterative methodology to continuously assess and improve decision strategies and schedules. The project managers or schedulers can implement the methodology to develop and identify schedules accompanied by suitable decision strategies to manage a project at the planning stage. The developed methodology also lays the foundation for an algorithm towards continuously automatically generating satisfactory schedule and strategies through the construction life of a project. Different from studying isolated daily decisions, the proposed framework introduces the notion of {em decision strategies} to manage construction process. A decision strategy is a sequence of interdependent decisions determined by resource allocation policies such as labor, material, equipment, and space policies. The schedule-based simulation framework consists of two parts, experiment design and result assessment. The core of the experiment design is the establishment of an iterative method to test and improve decision strategies and schedules, which is based on the introduction of decision strategies and the development of a schedule-based simulation testbed. The simulation testbed used is Interactive Construction Decision Making Aid (ICDMA). ICDMA has an emulator to duplicate the construction process that has been previously developed and a random event generator that allows the decision-maker to respond to disruptions in the emulation. It is used to study how the schedule responds to these disruptions and the corresponding decisions made over the duration of the project while accounting for cascading impacts and dependencies between activities. The dissertation is organized into two parts. The first part presents the existing research, identifies the departure points of this work, and develops a schedule-based simulation framework to design, assess, and improve decision strategies. In the second part, the proposed schedule-based simulation framework is applied to investigate specific research problems.

Using a Prediction and Option Generation Paradigm to Understand Decision Making

In many complex and dynamic domains, the ability to generate and then select the appropriate course of action is based on the decision maker's "reading" of the situation--in other words, their ability to assess the situation and predict how it will evolve over the next few seconds. Current theories regarding option generation during the situation assessment and response phases of decision making offer contrasting views on the cognitive mechanisms that support superior performance. The Recognition-Primed Decision-making model (RPD; Klein, 1989) and Take-The-First heuristic (TTF; Johnson & Raab, 2003) suggest that superior decisions are made by generating few options, and then selecting the first option as the final one. Long-Term Working Memory theory (LTWM; Ericsson & Kintsch, 1995), on the other hand, posits that skilled decision makers construct rich, detailed situation models, and that as a result, skilled performers should have the ability to generate more of the available task-relevant options. The main goal of this dissertation was to use these theories about option generation as a way to further the understanding of how police officers anticipate a perpetrator's actions, and make decisions about how to respond, during dynamic law enforcement situations. An additional goal was to gather information that can be used, in the future, to design training based on the anticipation skills, decision strategies, and processes of experienced officers. Two studies were conducted to achieve these goals. Study 1 identified video-based law enforcement scenarios that could be used to discriminate between experienced and less-experienced police officers, in terms of their ability to anticipate the outcome. The discriminating scenarios were used as the stimuli in Study 2; 23 experienced and 26 less-experienced police officers observed temporally-occluded versions of the scenarios, and then completed assessment and response option-generation tasks. The results provided mixed support for the nature of option generation in these situations. Consistent with RPD and TTF, participants typically selected the first-generated option as their final one, and did so during both the assessment and response phases of decision making. Consistent with LTWM theory, participants--regardless of experience level--generated more task-relevant assessment options than task-irrelevant options. However, an expected interaction between experience level and option-relevance was not observed. Collectively, the two studies provide a deeper understanding of how police officers make decisions in dynamic situations. The methods developed and employed in the studies can be used to investigate anticipation and decision making in other critical domains (e.g., nursing, military). The results are discussed in relation to how they can inform future studies of option-generation performance, and how they could be applied to develop training for law enforcement officers.

Peer influence in NIPF landowner decision making in the western Upper Peninsula, Michigan

Non-industrial private forest (NIPF) owners hold the largest amount of privately owned forest in the United States. Activities undertaken by NIPF owners have the potential to drastically impact the forested landscape of the United States, along with its associated biodiversity and ecological services. Many government sanctioned programs are in place to discourage the conversion of forest to other uses as well as to ensure sustainable management and a continuous supply of timber. Reaching NIPF owners with information about these programs and other management information is therefore important to the forests of the United States. This thesis presents research on how the NIPF owners of the western Upper Peninsula of Michigan communicate about forest management with neighboring NIPF owners. The data were obtained from 34 telephone interviews with owners of NIPF properties in the western Upper Peninsula. The goal of this research was to understand the way information moves through NIPF owner dominated landscapes in order to provide recommendations to policy implementers on how to best reach NIPF owners with information. Understanding where NIPF owners get information about management and landowner assistance programs is vital to ensuring a sustainably managed forest landscape in the western Upper Peninsula of Michigan.

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.