With the explosion of social media, consumers are gaining control in social reach and can utilize online platforms to create and share misleading information when doing so helps to meet an end. This dissertation, consisting of three separate essays, represents an attempt to address how misleading information is created, how it is disseminated, and how it can be eliminated. Essay One (Chapter 2) uses a mixed-method approach to explore the Dark Triad, proactivity, and vigilantism in driving self-created misleading information sharing. Additionally, this essay introduces a dual-process model of inoculation theory to the marketing and consumer literature that shows how consumers autoinoculate when building justification to engage in malicious behavior. This process includes both automatic and analytical components that initiate a Negative Cascade. Without a larger number of posts, these initial messages may be overlooked. However, herd inoculation can develop when a message begins to sway larger groups. Essay Two (Chapter 3) determines that authentic messages from the original poster are most believable and most likely to initiate a Negative Cascade. This confirmation through mere exposure can then initiate herd inoculation as it flows to other consumers and develops further credibility. The implicit bystander effect is active when in the presence of larger groups. Findings suggest herd inoculation may go unbroken since posters exposed to a positive counter-cascade are less likely to both participate in a forum and post positive messages. Essay Three (Chapter 4) shows that when a consumer shares a message that develops into a Negative Cascade, additional effort is required to halt the consumer herd inoculation. The studies uncover the need for an overt response from the original poster to stop future sharing of misleading information and the role of brand-enacted quarantines in the prevention of the autoinoculation of consumer vigilantes. This dissertation shows how one message can become a much bigger problem for a brand when misinformation spreads. Insights within the dissertation provide numerous outlets for future research and numerous tools and recommendations for both academics and practitioners that hope to understand how misleading information is created, disseminated, and can be eliminated.

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Agricultural literacy has been a topic of concern as most of the population have little to no understanding of agriculture, and the impact it has on society. Agricultural literacy can be defined as “having knowledge and understanding of agriculturally related scientific and technologically based concepts and processes required for personal decision making” (Meischen & Trexler, 2003, p.44). Numerous studies have been conducted to determine the significance of agricultural literacy beginning with elementary aged children and continuing through high school. The majority of studies conducted focus on public school students and teachers. This has led to a gap in the knowledge of students’ agricultural literacy in private schools. There are few studies that indicate if agriculture is being taught in private schools, subsequently there is little known about private school teachers’ willingness to incorporate agriculture into their classrooms. To improve agricultural literacy, it is necessary to place an emphasis on agricultural education.

Low energy availability (LEA) has been identified as the underlying etiology of the Female Athlete Triad and Relative Energy Deficiency in Sport (REDs) syndrome. The term energy availability (EA) describes the amount of dietary energy intake (EI) that is remaining to support physiological function after accounting for the energy cost of exercise. Exposure to LEA stimulates metabolic adaptations that may disrupt certain biological systems, such as endocrine function, and impair sports performance. Controlled laboratory research has shown suppression of bone formation biomarkers with accelerated rates of bone resorption after only three to five days of LEA in active females. Correcting LEA by increasing EI or decreasing exercise energy expenditure (EEE) may not be feasible for all athletes and additional approaches for protecting bone health during LEA require further investigation. Recent evidence suggests that brief bouts of high-impact exercise attenuate the increased rate of bone resorption in females with diet-induced LEA. However, it is unknown whether similar exercises have a protective effect on bone health when LEA is induced through a combination of dietary restriction and exercise. A gap also remains in the understanding of how EA fluctuates throughout the athletic season and what potential effect that has on body composition and performance outcomes. To address these gaps, we conducted two studies to investigate the interactions of EA, bone health, and body composition. The first investigation employed a randomized crossover design in which female runners underwent two, five-day experimental conditions of LEA consisting of dietary restriction and daily running (EA = 15 kcal·kg FFM-1·day-1). During one of the experimental conditions, participants also completed a bout of 50 jumping exercises daily. Serum markers of bone resorption (C-terminal cross-linking telopeptide of type 1 collagen [CTX-I]), bone formation (N-terminal propeptide of type 1 procollagen [PINP]), and hormonal profiles were compared between baseline and post-intervention using linear mixed effects modeling. We hypothesized that daily high-impact exercise would have a positive effect on bone by attenuating the rise in bone resorption. In contrast to our hypothesis, bone resorption marker CTX-I increased following both LEA conditions (+12%, P=0.004) with no difference in the response between the jumping and non-jumping conditions. Bone formation was not suppressed following either LEA condition. Concentrations of free triiodothyronine (T3), insulin-like growth factor-1, leptin, and insulin decreased in response to five days of LEA independent of condition (P<0.05); however, when taking into account condition, the decrease in free T3 was only statistically significant following the LEA condition without jumping (-27%, P=0.022, Cohen's d=0.87). Our findings suggest that high-impact jumping exercises are not an effective countermeasure to protect bone health during short-term LEA in female runners who continue to run routinely. In a second study, we conducted a longitudinal, observational study in collegiate male soccer players to investigate seasonal changes in EA and body composition. Measurements of EA, body composition, and sports performance were assessed at the start and end of the non-championship Spring athletic season. We hypothesized that EA would be positively associated with changes in body composition at the end of the three-month season. Despite most athletes reporting desires to gain total and/or lean body mass, no changes in EA or body composition were detected at the end of the season compared to the start. Furthermore, sports performance and bone density improved across the season regardless of individual changes in EA. These results indicate EA of collegiate male soccer players during the Spring season is sufficient to maintain current body composition and improve sports performance, but insufficient to support total and/or lean body mass gains. / Doctor of Philosophy / Adequate energy intake (EI) is essential for fueling athletic performance and supporting general health. Low energy availability (LEA) occurs when EI is insufficient to meet the energy demands of both exercise and basic health functions. Athletes with LEA may experience various repercussions such as suppressed metabolism, hormonal changes, and impaired bone health. Training adaptations may also be impaired by LEA, thereby affecting athletic performance. Daily high-impact jumping exercises have been shown to have a positive effect on bone health in women, even during periods of LEA caused by dietary restriction. However, this type of exercise intervention has not been tested in combination with other forms of daily exercise in women exposed to a controlled period of LEA. The purpose of these studies was to examine how exercise and EA affect bone health and body composition in recreational and competitive athletes. The first study investigated the effects of daily jumping exercises on markers of bone formation and breakdown during five days of LEA in female runners. The completion of 50 jumping exercises each day along with running on a treadmill was not shown to provide additional bone-protective benefits during LEA compared to running alone, as shown by similar rates of bone breakdown observed under both conditions. The second study investigated whether changes occur in EA or body composition in male collegiate soccer players over an athletic season. Despite most of the athletes reporting desires to gain weight or muscle during the season, there were no differences in body composition or EA at the end of the season compared to the start. However, there were significant improvements in aerobic fitness, relative strength, and bone density throughout the season.

The recent manufacturing environment is characterized as having diverse products due to mass customization, short production lead-time, and unstable customer demand. Today, the need for flexibility, quick responsiveness, and robustness to system uncertainties in production scheduling decisions has increased significantly. In traditional job shops, tooling is usually assumed as a fixed resource. However, when tooling resource is shared among different machines, a greater product variety, routing flexibility with a smaller tool inventory can be realized. Such a strategy is usually enabled by an automatic tool changing mechanism and tool delivery system to reduce the time for tooling setup, hence allows parts to be processed in small batches. In this research, a dynamic scheduling problem under flexible tooling resource constraints is studied. An integrated approach is proposed to allow two levels of hierarchical, dynamic decision making for job scheduling and tool flow control in Automated Manufacturing Systems. It decomposes the overall problem into a series of static sub-problems for each scheduling window, handles random disruptions by updating job ready time, completion time, and machine status on a rolling horizon basis, and considers the machine availability explicitly in generating schedules. Two types of manufacturing system models are used in simulation studies to test the effectiveness of the proposed dynamic scheduling approach. First, hypothetical models are generated using some generic shop flow structures (e.g. flexible flow shops, job shops, and single-stage systems) and configurations. They are tested to provide the empirical evidence about how well the proposed approach performs for the general automated manufacturing systems where parts have alternative routings. Second, a model based on a real industrial flexible manufacturing system was used to test the effectiveness of the proposed approach when machine types, part routing, tooling, and other production parameters closely mimic to the real flexible manufacturing operations. The study results show that the proposed scheduling approach significantly outperforms other dispatching heuristics, including Cost Over Time (COVERT), Apparent Tardiness Cost (ATC), and Bottleneck Dynamics (BD), on due-date related performance measures under both types of manufacturing systems models. It is also found that the performance difference between the proposed scheduling approach and other heuristics tend to become more significant when the number of machines is increased. The more operation steps a system has, the better the proposed method performs, relative to the other heuristics. This research also investigates in what conditions (e.g. the number of machines, the number of operation steps, and shop load conditions) the proposed approach works the best, and how the performance of this proposed approach changes when these conditions change. When tooling resource is shared, parts can be routed to machines that do not have all the required tools. This may result in higher routing flexibility. However, research work to date in sharing of tooling resources often places more emphasis on the real-time control and manipulation of tools, and pays less attention to the loading of machines and initial tool allocation at the planning stage. In this research, a machine-loading model with shared tools is proposed to maximize routing flexibility while maintaining minimum resident tools. The performance of the proposed loading heuristic is compared to that of a random loading method using hypothetically generated single stage system models. The study result indicates that better system performances can be obtained by taking into account the resident tooling ratio in assigning part types and allocating tools to machines at the initial planning stage. / Ph. D.