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In emergent high technology industries, entrepreneurs and their new ventures play a critical role in enhancing economic growth. In these industries, we can easily see some new ventures grow more rapidly to outperform their competitors. However, looking beyond the surface, new ventures’ growth path is idiosyncratic. More specifically, when growing, new ventures pursue different paths in terms of 1) which technologies they develop, 2) which products they make, and 3) what markets they enter. The question that has struck me is why high-tech new ventures differ on these key strategic choices. Building on literature on entrepreneurship, strategy, industry evolution, and network, this dissertation tries to answer this important question by focusing on intra-firm factors, more specifically, the individual and structural attributes of new ventures. Types of founder experience and new ventures’ knowledge structure are examined in depth. My three studies, each presented as a separate essay herein, investigate how individual (i.e. founder experience) and structural attributes (i.e. knowledge structure) affect key strategic choices regarding i) product market scope (Wernerfelt and Montgomery, 1988), ii) technological search scope (Katila and Ahuja, 2002), and iii) the types of new products (Sanchez and Mahoney, 1996; Henderson and Clark, 1990), respectively. In each, I discuss the relevant theories, methodology, data sources, results and implications. By investigating intra-firm factors that trigger different entrepreneurial strategies, my dissertation responds to an important call – micro-foundation of strategy formation – thus filling a key gap in the entrepreneurship literature. / Business Administration/Strategic Management

Introduction: The volume of antipsychotic medications prescribed to children and adolescents has risen sharply since second generation antipsychotics, also referred to as atypical antipsychotics, were introduced in the 1990’s. The concern surrounding the expanded use of antipsychotics was that the medications have significant adverse metabolic side effects and they were often prescribed to treat conditions in young children for which they have not been proven to be safe and effective. While it is not unlawful for health care providers to prescribe medications for uses beyond which they have been approved by the United States Food and Drug Administration, the lack of empirical evidence guiding much of the antipsychotic use in children had professional pediatric medical groups and policy makers concerned for the well-being of children receiving the medications. Several states, including Pennsylvania, enacted prior authorization policies in an attempt to restrict prescribing to children where a medical need has been established. However, the impact of the policies is largely unknown since published data on the topic is sparse. Methods: This retrospective, medical claims-based cohort study, used de-identified administrative Medicaid data from January 2008 to December 2010 to investigate the impact of Pennsylvania’s September 2008 antipsychotic prior authorization policy on antipsychotic prescribing prevalence in children targeted by the policy. Descriptive methods and segmented regression of the interrupted time series were used to assess the effects of the policy on monthly antipsychotic prescribing prevalence. A difference-in-difference analysis compared Pennsylvania’s prescribing to Ohio, a geographically proximate and demographically similar state without a prior authorization policy; and Delaware, a state that enacted a policy 3 years prior to Pennsylvania. The potential for compensatory prescribing was assessed by reporting the prevalence of other psychotropic medications over the study period. Results: An average of 99,074 Pennsylvania Medicaid enrollees ages 0-6 were identified as meeting the study criteria annually from 2008-10. Immediately following the policy intervention, an abrupt, significant reduction in monthly prescriptions of antipsychotics was observed (-51 prescriptions per 100,000; p=0.0052) and sustained over the observation period. The proportion of children filling prescriptions for antipsychotics dropped approximately 46% and the average number of antipsychotic prescriptions filled per month was reduced by 53% in 2010 compared to 2008. In Ohio, a state without such a policy, the proportion of children receiving an antipsychotic increased nearly 10% in 2010 compared to 2008 and the average number of monthly prescriptions increased 30%. Reductions in antipsychotic prescribing in Delaware, a state that had its antipsychotic policy in place since 2005, were comparable to Pennsylvania. There was no evidence that non-antipsychotic psychotropic medications were prescribed in place of the medications restricted by the policy. Conclusions: Pennsylvania’s 2008 prior authorization policy was associated with a significant decrease in annual and monthly antipsychotic prescribing prevalence in Medicaid-insured children targeted by the policy, those ages 0-6 years of age. Reductions in most other psychotropics was also observed, indicating changes in prescribing behavior may have extended beyond antipsychotics. While this analysis suggests the policy may have achieved its primary aim of reducing antipsychotic prescribing, more research is needed to better understand the complex array of factors influencing provider behavior and to explore potential unintended consequences of the policy. / Public Health

This study identifies and assesses a more specific relationship between the online instructor presence and the online learner's experience than is currently offered in previous studies. Guided by three questions, the study asked: (a) What is the relationship between the online instructor communication style and the learning experience, as defined by the adult learner's cognitive achievement, ratings of the overall course experience, and perceptions of the instructor's performance; (b) What is the relationship between the strength (contact frequency with the learner) of that communication style (facilitating or non-facilitating) and the learning experience; and (c) What is the relationship between selected learner demographic variables (previous subject experience on the job and previous experience with the vendor's online learning environment) and the learning experience. The study included an examination of ex post facto data that depicted the interactions between 89 students and 9 instructors in 358 asynchronous, professional development class discussions. The examination revealed the presence and frequency of select instructor behaviors more acutely define the communication style and strength of the online instructor's relationship to the professional adult's online learning experience. The study's additional findings support earlier research that suggests prior learner experience relates positively to online learning outcomes. These findings contribute to the larger body of knowledge related to online instruction. / Ph. D.

Environmental education (EE) programming has been found to lead to positive behavioral and attitudinal outcomes in student participants. Among a variety of factors, the characteristics of EE program instructors have been found to play a role in driving these outcomes. This thesis investigates the specific motivators of EE instructors and the links between instructor autonomy, prior experience, and program outcomes. I used a multi-methods approach to investigate these themes and have organized the results between two chapters that are manuscripts intended as separate journal publications. Chapter 2 presents a qualitative study that identifies the salient motivators of EE instructors, as well as organizational practices that affect EE instructor feelings of autonomy, competence, relatedness, and the meaningfulness these instructors feel within their jobs. Chapter 3 presents a quantitative study analyzing the impact of autonomy and prior experience on program outcomes by linking instructor and student participant survey responses from a sample of 166 EE programs performed throughout 57 different organizations across the US. Results led to the following recommendations for EE organizations: (1) promote job enrichment elements for their instructional staff, including the implementing of participatory evaluation processes; (2) encourage instructors to take "ownership" of programming, such that they continue to practice and develop competence over time; (3) increase instructor autonomy as they gain further experience. / Master of Science / Environmental education (EE) programming has been found to lead to positive behavioral and attitudinal outcomes in student participants. Among a variety of factors, the characteristics of EE program instructors have been found to play a role in driving these outcomes. This thesis investigates the specific motivators of EE instructors and the links between instructor autonomy, prior experience, and program outcomes. I used a multi-methods approach, employing semi-structured interviews and surveys to investigate these themes, and have organized the results between two chapters that are manuscripts intended as separate journal publications. Chapter 2 presents a qualitative study that identifies the salient motivators of EE instructors, as well as organizational practices that affect EE instructor feelings of autonomy, competence, relatedness, and the meaningfulness these instructors feel within their jobs. Chapter 3 presents a quantitative study analyzing the impact of autonomy and prior experience on program outcomes by linking instructor and student participant survey responses from a sample of 166 EE programs performed throughout 57 different organizations across the US. Results led to the following recommendations for EE organizations: (1) promote job enrichment elements for their instructional staff, including the implementing of participatory evaluation processes; (2) encourage instructors to take “ownership” of programming, such that they continue to practice and develop competence over time; (3) increase instructor autonomy as they gain further experience. This research provides information to better EE organizational management in the aims of promoting motivated employees and ultimately effective program outcomes.

Engaging the student's prior knowledge is considered by educational researchers to be an important part of constructing a strong foundation for new learning. Diagrams are one technique used in the classroom. Jill Larkin and Herbert Simon described the computational advantages of diagrams over text when used to communicate information in their 1987 article entitled 'Why a Diagram is (Sometimes) Worth Ten Thousand Words.' This case study describes a novel abstract diagramming technique facilitated in four separate university classroom settings. Using paper and crayons, the students created three diagrams that represented the externalization of their unconscious perceptions of their own prior knowledge. The study illustrates how differences in prior knowledge can be visualized using diagrams with greater speed in less time than the traditional use of text-based descriptions. The use of the abstract diagramming technique led to an unexpected finding. The student diagrams were shown to contain a hidden conceptual topology, one that is described by Egenhofer in his 1991 article entitled 'Reasoning About Binary Topological Relations.' This topology is recommended as a framework for structuring and facilitating student collaboration and sharing of prior knowledge and new learning. The present study recommends the diagramming technique as the basis for the establishment of a standard diagram research framework that can be used across multiple research disciplines and subject domains. This dissertation describes a domain-general abstract diagram technique that can be adapted for domain-specific subjects and made operational using basic materials (paper and crayons). The study also describes the instructors' responses to questions about the diagram technique used in their classes. The case study offers recommendations for future diagram research. / Ph. D.

Veterans who served our country, return with a wealth of experience that transfer into military credit for prior service. These transfer credits in institutions of higher education apply towards education degree attainment. With colleges and universities implementing individual policies for acceptance of credits, veterans experience a loss of credits leading to a duplication of required classes to achieve degrees. To understand inconsistent practices, both federal and institutions of higher education polices are examined. Framed by institutionalization theory, this research sheds light on the public policy process and administration of credit at the organization over time. The study provides findings for how the largest public college and higher education institution in the state of California awards academic credit for military education. Evidence suggests that public higher education institutions adapt based on effective leaders who define and defend the organization's institutional values and mission. This study provides findings on institutional adaptations to create policies and practices that public administrators use to apply transfer military credit into postsecondary academic credit. The focus is on postsecondary credit transferred, or articulated, by entering military first-year students using the GI Bill. The study asks how have major institutions of higher education formalized institutional policies and practices on awarding academic credit for military education? / Doctor of Philosophy / This study provides findings on institutional adaptations to create policies and practices that public administrators use to apply transfer military credit into postsecondary academic credit. The focus is on postsecondary credit transferred, or articulated, by entering military first-year students using the GI Bill. The study asks how have major institutions of higher education formalized institutional policies and practices on awarding academic credit for military education?

With the abundance of biological data, computational prediction of gene regulatory networks (GRNs) from gene expression data has become more feasible. Although incorporating other prior knowledge (PK), along with gene expression, greatly improves prediction accuracy, the accuracy remains low. PK in GRN inference can be categorized into noisy and curated. Several algorithms were proposed to incorporate noisy PK, but none address curated PK. Another challenge is that much of the PK is not stored in databases or not in a unified structured format to be accessible by inference algorithms. Moreover, no GRN inference method exists that supports post-prediction PK. This thesis addresses those limitations with three solutions: PEAK algorithm for integrating both curated and noisy PK, Online-PEAK for post-prediction interactive feedback, and DeTangle for visualization and navigation of GRNs. PEAK integrates both curated as well as noisy PK in GRN inference. We introduce a novel method for GRN inference, CurInf, to effectively integrate curated PK, and we use the previous method, Modified Elastic Net, for noisy PK, and we call it NoisInf. Using 100% curated PK, CurInf improves the AUPR accuracy score over NoisInf by 27.3% in synthetic data, 86.5% in E. coli data, and 31.1% in S. cerevisiae data. Moreover, we developed an online algorithm, online-PEAK, that enables the biologist to interact with the inference algorithm, PEAK, through a visual interface to add their domain experience about the structure of the GRN as a feedback to the system. We experimentally verified the ability of online-PEAK to achieve incremental accuracy when PK is added by the user, including true and false PK. Even when the noise in PK is 10 times more than true PK, online-PEAK performs better than inference without any PK. Finally, we present DeTangle, a Web server for interactive GRN prediction and visualization. DeTangle provides a seamless analysis of GRN starting from uploading gene expression, GRN inference, post-prediction feedback using online-PEAK, and visualization and navigation of the predicted GRN. More accurate prediction of GRN can facilitate studying complex molecular interactions, understanding diseases, and aiding drug design. / Ph. D.