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In January of 2012, Philadelphia Mayor Michael Nutter outlined the crime fighting measures that his administration would pursue during his second term as mayor. Included was a plan to introduce a multi-agency crime reduction program, which Philadelphia Police Commissioner Charles Ramsey and District Attorney Seth Williams would co-chair, called GunStat. GunStat was described as a collaborative effort to reduce gun violence through (1) identifying locations with a high incidence of violent crime, (2) pinpointing violent offenders responsible for these crimes, (3) focusing on arresting and prosecuting these offenders for crimes committed at these places, and (4) enhanced monitoring of offenders on probation and parole who are living and/or offending within these locations. In effect, GunStat was designed to target the right people (prolific, violent known offenders) at the right places (hot spots of violent crime). This dissertation is an in-depth, ex post facto evaluation of Philadelphia’s GunStat model as implemented over two phases and two years. It involved both a quasi-experimental research design which employed propensity score matching methods to generate comparisons, and a process-evaluation where several themes, including program implementation, were explored. The results here suggest that GunStat did not reduce crime relative to comparison locations. However, the qualitative data highlighted the importance of informal inter-agency networks that were developed during the course of the intervention, and suggested that GunStat put future collaborations on a solid footing. The implications for criminal justice policy, theory and evaluation design are discussed. / Criminal Justice

The theoretical frameworks of transaction cost economics and agency theory are widely used to design appropriate governance structure for constraining opportunism within marketing channels. These approaches generally assume that marketing channel managers are opportunistic, and only economic constraints deter opportunism in exchange relationships. However, some empirical studies have shown that managers do not always behave opportunistically even if conditions permit such behavior. In addition, some researchers have proposed a "cycle of self-fulfilling prophecy" and have argued that the uncritical assumption of opportunism and excessive use of control mechanisms such as monitoring only exacerbates the problem. Thus, it is important to identify conditions in which opportunism likely occurs. The present research argues that marketing channel managers exhibit differing propensities for opportunism (PFO), and it spans three levels of analysis to identify contributing factors. The individual-level analysis treats marketing channel managers as a heterogeneous population and investigates the impact of individual traits on their behaviors in business relationships. At the dyadic level, I modify standard microeconomics models to incorporate norms of fairness. Finally, the extra-dyadic level of analysis goes beyond the traditional dyadic focus to include network-wide social influence on a relationship. Using the data collected from 162 unit franchieees. the hypotheses were tested using structural path analyses. The findings of this dissertation provide guidance on the extent to which costly and potentially damaging control mechanisms are really necessary in a given marketing channel relationship. Overall, the research contributes to the existing literature by re-examining a fundamental behavioral assumption about marketing channel managers and providing an alternative framework that can meaningfully inform us as to when and why opportunism occurs. / Ph. D.

In this paper, a model to estimate personal savings is constructed using an estimate of permanent income. Traditional approaches to studying aggregate personal savings depend on many independent variables that serve as the determinants of personal saving. Because some of the determinants used in such approaches can be difficult to obtain, estimating aggregate saving in this manner can be time-consuming and arduous. Using an estimate of permanent income based on Friedman's Permanent Income Hypothesis (PIH), this paper creates a model to estimate personal savings and tests the model by examining the Marginal Propensity to Save (MPS) that is derived from it. Permanent income was estimated using a two-stage least squares (2SLS) method and aggregate personal savings is estimated using ordinary least squares (OLS). The empirical evidence reveals that savings estimates and marginal propensities to save are consistent with results obtained studies using conventional approaches except during periods in which a wealth effect occurs. During such periods, additional variables need to be added to the model to account for a wealth effect. This analysis therefore serves to further validate the PIH and shows that it can be applied to studying household savings as well as consumption. / Master of Arts

This thesis assesses the impact of the Jepara Furniture Value Chain (FVC) project, which was conducted by the Center for International Forestry Research (CIFOR) to address challenges faced by small-scale furniture producers in Jepara, Indonesia. This assessment focuses on the effect of membership in the APKJ, a producer association started as part of the project. The propensity score for association membership was estimated using unchanging firm and owner characteristics, as well as information recalled about firm operations in 2009 (before the association was formed). Propensity score matching was used to compare outcome variables of association members and non-members. Results suggest that membership in the APKJ does not have a significant effect on profit levels. Using differenced current and recalled marketing and production behaviors as outcome variables with propensity score matching indicates that members have improved their bargaining position and marketing behaviors more than non-members since 2009. Additionally, APKJ members are more likely to have obtained certificates of timber legality / Master of Science

Although originally conceived as an educational intervention for at-risk students, modern career academies have expanded their scope to programs designed to promote critical thinking, problem solving, and analytical skills to be successful in an advanced career path. Through the integration of career and technical education courses and a rigorous, college preparatory academic curriculum, career academies serve as a key piece of a larger strategy for developing a well- prepared STEM workforce. This study focuses on the Virginia Governor's STEM Academies, a state-wide initiative containing programs designed to expand options for the general student population to acquire STEM literacy and other critical skills, knowledge and credentials that will prepare them for high-demand, high-wage, and high-skill careers. Currently, 22 Academies exist serving students across 36 Virginia School Divisions. Using educational administrative data housed within the Virginia Longitudinal Data System, I examined the Virginia Governor's STEM Academies regarding characteristics of student participation and the relationship between Academy participation and high school and postsecondary outcomes. Using multi-level regression modeling, I found that male students, Asian and Hispanic students, and non-economically disadvantage students have a higher rate of Academy participation. After matching students with propensity score matching on demographic and early academic characteristics, I find that Academy participants are more likely to take Algebra II at an earlier grade, enroll in more Career and Technical Education and dual enrollment courses, and declare a STEM major after enrolling at a postsecondary institution. This research provides a valuable new contribution to the study of career academies after such educational programs have undergone a paradigm shift to preparing students for high-demand, high-wage, and high-skill careers. By incorporating propensity score matching and multi-level regression model, I employ a statistically rigorous approach that can serve as important benchmarking of the enrollment and academic outcomes of the Virginia Governor's STEM Academies. / Doctor of Philosophy / Although originally conceived as an educational intervention for at-risk students, modern career academies have expanded their scope to programs designed to promote critical thinking, problem solving, and analytical skills to be successful in an advanced career path. Through the integration of career and technical education courses and a rigorous, college preparatory academic curriculum, career academies serve as a key piece of a larger strategy for developing a well- prepared STEM workforce. This study focuses on the Virginia Governor's STEM Academies, a state-wide initiative containing programs designed to expand options for the general student population to acquire STEM literacy and other critical skills, knowledge and credentials that will prepare them for high-demand, high-wage, and high-skill careers. Currently, 22 Academies exist serving students across 36 Virginia School Divisions. Using educational administrative data housed within the Virginia Longitudinal Data System, I examined the Virginia Governor's STEM Academies regarding characteristics of student participation and the relationship between Academy participation and high school and postsecondary outcomes. Using multi-level regression modeling, I found that male students, Asian and Hispanic students, and non-economically disadvantage students have a higher rate of Academy participation. After matching students with propensity score matching on demographic and early academic characteristics, I find that Academy participants are more likely to take Algebra II at an earlier grade, enroll in more Career and Technical Education and dual enrollment courses, and declare a STEM major after enrolling at a postsecondary institution. This research provides a valuable new contribution to the study of career academies after such educational programs have undergone a paradigm shift to preparing students for high-demand, high-wage, and high-skill careers. By incorporating propensity score matching and multi-level regression model, I employ a statistically rigorous approach that can serve as important benchmarking of the enrollment and academic outcomes of the Virginia Governor's STEM Academies.

This research explores whether differences in ethical reasoning levels exist between senior hospital managers and top level general industry executives. Similar comparisons are made between not-for-profit hospital managers and their peers in for-profit hospitals. Also examined are the ethical reasoning levels used most often by practicing executives, regardless of industry affiliation.