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This dissertation explores the relationship between entrepreneurial passion and entrepreneurial persistence within small-size companies. Although prior literature has acknowledged that entrepreneurial passion enhances entrepreneurial persistence, a better understanding of the role of opportunity evaluation in this context is needed. Using data from 176 entrepreneurs, I suggest that gain estimation, loss estimation, and feasibility moderate the relationship between entrepreneurial passion and entrepreneurial persistence and that this relationship leads to the invention and development of new business opportunities. Implications for theory and practice as well as avenues for future research are discussed.
INDEX WORDS: Entrepreneurial passion, Entrepreneurial persistence, Opportunity evaluation
Although women and racial minority entrepreneurs make considerable contributions to society by creating their ventures, they often face additional barriers and limitations that explain the differential rate of new venture creation between men and women, White and racial minorities. Therefore, it is crucial to uncover mechanisms to help support women and racial minorities in the venture creation process. One such mechanism is supportive entrepreneurial figures such as entrepreneurial role models, mentors, and founders, all of which can play an essential role in the decision to become an entrepreneur. Despite understanding the positive influence that these supportive entrepreneurial figures can have on entrepreneurial behavior and outcomes, research has yet to examine how these relationships are shaped by the gender and race of the supportive entrepreneurial figure in the process of new venture creation. I test hypotheses with a sample of 417 entrepreneurs across two-time points. Results are intricate and complex, illustrating how in some cases, the positive influence of the entrepreneurial role model, mentor, or founder is dependent on the gender or race of that individual. My findings contribute to how supportive entrepreneurial figures shape new venture creation for women and racial minority entrepreneurs.
Organic-inorganic hybrids may offer material properties not available from their inorganic components. However, they are typically less stable and disordered. A group of highly ordered II-VI based hybrid structures has been shown to possess various unusual properties and potential applications. As a prototype, β-ZnTe(en)0.5 can be viewed as a superlattice with alternating layers of two-monolayer thick (110) ZnTe and single-molecule length ethylenediamine. In contrast to all the known inorganic superlattices where interfacial diffusion is inevitable, we demonstrate in this thesis that β-ZnTe(en)0.5 exhibits an unusually high degree of crystallinity, as is evidenced by < 25′′ XRD rocking curve linewidth and < 1 cm-1 Raman linewidth, which are comparable to many high-quality binaries. Besides manifesting in the macroscopic scale crystallinity characterization, it also shows an exceptionally low level of microscopic scale defects, as suggested by the observed linear dependence of PL intensity on the excitation density over 6 orders of magnitude, which has not been possible even for the very high-quality CdTe and GaAs.
β-ZnTe(en)0.5’s highly-ordered crystallinity enables a systematic investigation of its vibrational property. We apply the orthogonal polarization and the angle-resolved polarization Raman techniques to study β-ZnTe(en)0.5’s vibrational modes. A set of orthogonal polarizations are used to decouple the vibration modes according to their symmetries. A mode-by-mode analysis allows unambiguous assignment for the Raman-active modes. A few exceptions and additional features are discussed. With the assignment, we demonstrated that the Raman tensor could be estimated from both the orthogonal technique and the angle-resolved technique. The two independent measurements yield consistent estimations. In addition, it has been shown that a combination of the two techniques enables unambiguous determination of the crystal orientations.
A distinction among the hybrid materials is its unprecedented ambient long-term stability over 15 years, which is still limited by extrinsic mechanisms but is already the longest documented hybrid semiconductor. In this work, we used Raman spectroscopy to investigate its degradation in air and a protected condition and framed the factors contributing to its long-term stability into (1) intrinsic effect such as large formation energy and large activation barrier in excess of the formation energy; (2) extrinsic factors, including surface or edge effect, where degradation can initiate through processes such as oxidation, and the structural defects, which may provide more accessible paths for degradation. Based on this approach, we estimate the room-temperature lifetime of β-ZnTe(en)0.5 in a protected environment can achieve 1.9x10^8 years, while in the ambient air, its lifetime is on the order of 10^1 years.
Human-automation teaming (HAT) is gaining importance in military and commercial applications with autonomous vehicles because it promises to improve performance, reduce the cost of operating and designing platforms, and increase adaptability to new situations. Given that both humans and automation systems are subject to misses, faults, or errors, to ensure the HAT performance in unpredictable conditions, it is critical to address the hand-off problem -- how to transition control between a human driver and automation system. Current solutions for control transfer in semi-automated ground vehicles face issues such as protracted transfer time, misinterpretations, or misappropriations of responsibility, and incomplete or inaccurate understandings of the vehicle and environment state. Transitions involving such issues are often "bumpy'' and implicated in safety compromises.
In this dissertation, we designed and tested an adaptive haptic shared control wherein a driver and an automation system are physically connected through a motorized steering wheel. We model the structure of the automation system like the structure of the human-driver, including a higher-level intent generator and lower-level impedance controller. In the first phase of the project, we developed a
nonlinear stochastic model predictive approach to determine how automation's impedance should be modulated in different interaction modes to enable the smooth and dynamic transition of control authority. Then, we tested our controller through a set of human-subject studies using a fixed-base driving simulator. Our findings showed that by adaptively modulating the impedance of the automation system, the control transfer time is reduced, and the performance of HAT is significantly improved.
In the second phase of this dissertation, we studied the principles of convention formation in a haptic shared control framework to narrow down the many possible strategies for resolving a conflict to those that a driver might be more gravitated. To this end, we proposed a modular platform to separate partner-specific conventions from task-dependent representations and use this platform to learn various forms of conventions between a human-driver and automation system. Using this platform, we will create a map from human-automation interaction outcomes to the space of conventions. This map will then be used to design an adaptable automation system. To design an adaptable automation system, we developed a reinforcement-learning model predictive controller wherein the characteristic of the model-predictive controller, including the weights of its cost function, is updated in different interaction modes using the learned convention map. Finally, we tested the proposed platform on the problem of intent negotiation between the driver and the automation system. The results demonstrated that the conflict between humans and automation could be further reduced using the convention-based approach.
Improving the design of undergraduate gateway STEM courses is a high priority, particularly courses with large enrollment and high failure rates. Effective course design has been noted as a key strategy for improving higher education teaching. This has resulted in the need for faculty to enact the role of a faculty-designer to redesign courses. This embedded qualitative case study investigated how faculty design knowledge influences design practice. Three faculty participated in a 6-hour course modeling workshop and used the Learning Environment Modeling (LEM) toolkit to generate 13 visual lesson blueprints while engaging in design discussions and interviews. A two-phased, hybrid inductive-deductive analysis approach was used for data collection, data preparation, and data analysis. Results discuss: (1) “design patterns of practice” emergent among activity sequences and lesson sequences in visual blueprints; (2) contextual factors that drive faculty design decisions in STEM lesson design; and (3) key influencers to faculty design knowledge and design practice. Findings offer a deeper understanding of design knowledge that guides STEM faculty as they make design decisions. The study offers implications to qualitative visual research methods as well as to university centers for teaching and learning as key stakeholders in supporting faculty as designers.
Motivated by the government's clean energy targets, the penetration of Distributed Energy Resources (DER) is increasing. These DERs interconnections bring the added generation and storage capacity at the distribution level. Also, with the increasing implementation of smart inverters and Advanced Distribution Management Systems (ADMS), the flexibility of the DERs can be leveraged to solve the distribution grid issues like over abnormal voltages, intermittencies, and thermal overloads. The proposed work focuses on the development of a robust distributed control architecture to control and optimally manage the load and PV variations using energy storage by creating the virtual clusters of the distribution grid.
The proposed approach adopts a distributed control approach by partitioning the grid into manageable clusters through an improved spectral clustering-based approach. The cluster of the distribution grid represents a good balance of local load and DER generation. An approach for reactive power to voltage sensitivity is also proposed for voltage regulation purposes at the cluster level based on the grid measurements. The clusters configurations adapt to accommodate the varying grid topology or changing load and DER generation. For the distribution grids receiving the set-points at the substation level for management of transmission power flow, an Alternating Direction Methods of Multipliers (ADMM) based sharing optimization is proposed to share the area set-points among the clusters based on the state of charge of each cluster. The controllable assets of each cluster (BESS) are managed through model predictive control. The improvement in the grid resiliency is demonstrated through the implementation of the complete framework to support the loads on the healthy part of the grid without interruptions during the contingency/outage scenarios on the distribution grid.
Social networks such as Twitter enable people to interact with each other and share health-related concerns in an effective and novel way, as evidenced during the COVID-19 pandemic when in-person communication became inconvenient under social-distancing policies. Public emotions mined from these social network data have increasingly attracted scholars’ attention because of their significant role in predicting public behaviors. However, little attention has been paid to the impacts of health policy and local political ideology on the trends of spatiotemporal emotions related to COVID-19. This study examines 1) the spatial-temporal clustering trends of negative emotions (or spillover effects); 2) whether health policies such as social distancing policy are associated with spatiotemporal emotion patterns towards COVID-19. This article finds that: COVID-19 related negative emotions detected by social media have spillover effects and that counties with stay-at-home policy or counties that are predominantly democratic exhibit a higher observed number of negative emotions toward COVID-19. These results suggest that scholars and policymakers may want to consider the impacts of interventions caused by public policy and political polarization on spatial-temporal patterns of public health concerns detected by social media.
MARK EDWARD VERBURG. NCAA Transfer Student-athletes, Athletic Identity, and the Impact of COVID-19
(Under the direction of Dr. MARK D’AMICO)
Transfer students are an increasingly important piece of the college athletics puzzle; however, little is known about the athletic identity of this important population and the effects of COVID on their commitment to sport. The purpose of this study was to measure and compare the athletic identity levels of NCAA student-athletes who transferred to their current institutions versus the athletic identity levels of fellow student-athletes who did not transfer. Additionally, the study sought to explore relationships between athletic identity and a student-athlete’s view of the personal impact of the COVID-19 pandemic. The sample included 413 student-athletes from all three NCAA divisions and a variety of transfer situations. Noteworthy findings include: student-athletes who transfer are likely to have a higher athletic identity than those who have not transferred, student-athlete’s strength of commitment to their sport during the pandemic influenced their athletic identity scores, and student-athletes who had negative academic experiences exhibited higher athletic identity scores. Considering the increasing prevalence of transfer student athletes, these findings will inform athletic personnel from administrators to coaches to academic advisors about the transfer population and the influence of the pandemic on student-athletes. Recommendations include: intentionally discussing the concept of athletic identity with student-athletes throughout their collegiate careers, encouraging student-athletes to develop multiple roles or identities outside of sport, and understand that the pandemic impacted student-athletes in a multitude of ways including influencing how they viewed the role of sport in their lives.
Educators and researchers have been exploring alternative approaches to school discipline such as School-wide Positive Interventions and Supports (SW-PBIS) and Restorative Justice. There has been little research analyzing the effectiveness of both approaches implemented in tandem. Using an autoethnographic design, this study critically analyzes the beliefs and perceptions of one white, female school principal as she combines SW-PBIS and Restorative Practices at her racially diverse, Title I elementary school. The following research questions were addressed in this study 1) How has implementing restorative practices and PBIS simultaneously within a diverse, Title, urban-like school helped to shape my beliefs as a white female administrator? 2) As a white female principal, what are my perceptions of the staff response to a blended model of SW-PBIS and Restorative Practices? 3) How do I, as a white, female principal, contribute to the environment that produces discipline disparities? How do I combat it? Four themes emerged during the data analysis: A Pollyanna Principal, Deficit Mindsets, Zero Tolerance for Zero-Tolerance, and White Savior. The findings revealed connections between the themes and Critical Race Theory, exposing the impact of race in student discipline through my eyes as a white, female principal.
