What's in a name and when does it matter? The hot and cold market impacts on underpricing of certification, reputation and conflicts of interest in venture capital backed Korean IPOs

This article analyses the impact of the participation of venture capital (VC) firms on underpricing in 372 businesses brought to IPO during the period 1999-2001 in KOSDAQ. Korea's second-tier stock market, KOSDAQ, has grown dramatically since 1999 and about half of the firms listed in KOSDAQ during this period were VC-backed, thus providing a good testing ground for empirical analysis. We measure VC participation in terms of pre IPO share-ownership by VC firms and attempt to differentiate IPO impacts between VCs grouped in terms of their reputation (measured by their dominance of the VC market, and by their affiliation in terms of ownership by banks and security companies). In estimating impacts we control for a wide range of variables which may affect the extent of underpricing. These include uncertainty inducing factors such as the age, size, profitability, leverage, and technical riskiness (measured by sector and R&D intensity) of the firm brought to IPO. We also control for market conditions using proxies for hot and cold market effects based on the numbers of contemporaneous IPOs, underpricing trends and market price movements. Finally in addition to allowing for the impact of underwriting quality we control for share overhang and price revision effects. We find that, controlling for other relevant factors, pre-IPO ownership by VCs has an insignificantly negative impact on underpricing in both hot and cold markets. However in cold markets reputational effects within the VC group do matter. In those conditions the top 3 VCs and those owned by or affiliated with banks are significantly associated with lower underpricing. The same is true for the quality of underwriting. However in hot market conditions none of these effects are present.Initial Public Offering; Underpricing; Venture Capital; Certification; Conflict of Interest, Informational Advantage

Monitoring Challenges and Approaches for P2P File-Sharing Systems

Since the release of Napster in 1999, P2P file-sharing has enjoyed a dramatic rise in popularity. A 2000 study by Plonka on the University of Wisconsin campus network found that file-sharing accounted for a comparable volume of traffic to HTTP, while a 2002 study by Saroiu et al. on the University of Washington campus network found that file-sharing accounted for more than treble the volume of Web traffic observed, thus affirming the significance of P2P in the context of Internet traffic. Empirical studies of P2P traffic are essential for supporting the design of next-generation P2P systems, informing the provisioning of network infrastructure and underpinning the policing of P2P systems. The latter is of particular significance as P2P file-sharing systems have been implicated in supporting criminal behaviour including copyright infringement and the distribution of illegal pornograph

An SEA Guide for Identifying Evidence-Based Interventions for School Improvement

The Every Student Succeeds Act (ESSA) is the most recent reauthorization of the Elementary and Secondary Education Act and replaces the No Child Left Behind Act (NCLB). The law focuses on using research evidence to improve teaching and learning and at the same time passes considerable authority from federal to state policymakers. This means that responsibility largely falls on states and localities to effectively make sense of and use research evidence in their decisions around school improvement, teacher preparation, principal recruitment, and family engagement. With support from the Annie E. Casey Foundation, Overdeck Family Foundation, and the William T. Grant Foundation, the Florida Center for Reading Research (FCRR) has developed Guides for Identifying Evidence-Based Interventions for School Improvement

Extending sensor networks into the cloud using Amazon web services

Sensor networks provide a method of collecting environmental data for use in a variety of distributed applications. However, to date, limited support has been provided for the development of integrated environmental monitoring and modeling applications. Specifically, environmental dynamism makes it difficult to provide computational resources that are sufficient to deal with changing environmental conditions. This paper argues that the Cloud Computing model is a good fit with the dynamic computational requirements of environmental monitoring and modeling. We demonstrate that Amazon EC2 can meet the dynamic computational needs of environmental applications. We also demonstrate that EC2 can be integrated with existing sensor network technologies to offer an end-to-end environmental monitoring and modeling solution

WASHBACK AND THE ASSESSMENT PRACTICES OF ESL INSTRUCTORS AT JAPANESE UNIVERSITY

This study investigated awareness among native-English instructors teaching English to first year freshman students studying English at a university in Japan, and the potential effects of their chosen methods of oral evaluation on washback. Washback effect refers to the impact of testing – whether positive or negative - on teaching practices, curriculum design, and learning behaviors.  Oral washback, in particular, in evaluation has seen increased importance in recent years, with more consideration given to how to provide positive oral washback in evaluations to ensure that they are as effective as possible in improving English levels. A mixed methods approach was used – a survey and interviews – with five instructors to find out about how they assess their students and how aware and how much attention they gave to possible washback effects of their chosen methods of evaluation. It was found that there is quite a variance among different instructors and knowing more about how to promote more positive oral washback to be useful in improving evaluation methods used

Interspecific competition underlying mutualistic networks

The architecture of bipartite networks linking two classes of constituents is affected by the interactions within each class. For the bipartite networks representing the mutualistic relationship between pollinating animals and plants, it has been known that their degree distributions are broad but often deviate from power-law form, more significantly for plants than animals. Here we consider a model for the evolution of the mutualistic networks and find that their topology is strongly dependent on the asymmetry and non-linearity of the preferential selection of mutualistic partners. Real-world mutualistic networks analyzed in the framework of the model show that a new animal species determines its partners not only by their attractiveness but also as a result of the competition with pre-existing animals, which leads to the stretched-exponential degree distributions of plant species.Comment: 5 pages, 3 figures, accepted version in PR

A Bayesian localised conditional auto-regressive model for estimating the health effects of air pollution

Estimation of the long-term health effects of air pollution is a challenging task, especially when modeling spatial small-area disease incidence data in an ecological study design. The challenge comes from the unobserved underlying spatial autocorrelation structure in these data, which is accounted for using random effects modeled by a globally smooth conditional autoregressive model. These smooth random effects confound the effects of air pollution, which are also globally smooth. To avoid this collinearity a Bayesian localized conditional autoregressive model is developed for the random effects. This localized model is flexible spatially, in the sense that it is not only able to model areas of spatial smoothness, but also it is able to capture step changes in the random effects surface. This methodological development allows us to improve the estimation performance of the covariate effects, compared to using traditional conditional auto-regressive models. These results are established using a simulation study, and are then illustrated with our motivating study on air pollution and respiratory ill health in Greater Glasgow, Scotland in 2011. The model shows substantial health effects of particulate matter air pollution and nitrogen dioxide, whose effects have been consistently attenuated by the currently available globally smooth models

THE RELATIONSHIP BETWEEN PRINCIPAL SUPPORT AND TEACHER RETENTION IN HARD TO STAFF SCHOOLS

This dissertation examines the relationship between principal support and retention of teachers in hard to staff schools. The purpose of this study was to, (a) to determine the relationship between teacher retention and principal support, (b) to examine the perception of support between teachers and principals and how these perceptions affect teacher retention in hard to staff schools, and (c) to discover if there is a correlation between the principal\u27s supports and teacher retention. Within these school environments, the participants were both administrators and teachers who are employed in the sample schools. Findings in this study verified information found within the literature review and were consistent with prior research and studies indicating that support of teachers have a large impact on teacher retention in hard to staff schools. Teachers that participated in this study provided insight as to which forms of support they valued most from their principals. The recommendations that are provided are intended to be a guide for administrators working in hard to staff schools to improve their programs so that they face less teacher attrition in hard to staff schools. The recommendations are also intended to encourage leaders to look more closely at their programs and their own styles of leadership and support as to improve their communication and support of their teachers in these hard to staff schools. Specific recommendations are made for administrators, institutions, teachers, working in hard to staff schools. As well as researchers interested in pursuing more information in this area of research

Social Capital and Disasters: A Study of Post-Hurricane Behavior & Attitudes in the United States

This thesis examines what effect disasters have on social capital. Given the ambiguity in the literature on the relationship between social capital and disasters, it is important to study this intersection further. This relationship is analyzed through a quantitative inquiry of Hurricane Irene (2011), Hurricane Sandy (2012), and Hurricane Matthew (2016) in the US as well as a qualitative case study from news sources in Hoboken, NJ following Hurricane Sandy. I break down social capital into attitudinal and behavioral components. My findings suggest that social capital generally increases following hurricanes. What is notable about these findings is that not all components of social capital reacted uniformly, with formal membership in civil society groups declining overall. There was evidence in the case study to suggest that this trend was offset by informal group behavior and effective government, business, and philanthropic aid. My findings demonstrate that both informal groups and governmental aid can promote post-disaster social capital

Highly prevalent but not always persistent: undergraduate and graduate student's misconceptions about psychology.

Although past research has documented the prevalence of misconceptions in introductory psychology classes, few studies have assessed how readily upper-level undergraduate and graduate students endorse erroneous beliefs about the discipline. In Study 1, we administered a 30-item misconception test to an international sample of 670 undergraduate, Master’s and doctoral students. Analyses indicated that participants identified and rejected the majority of misconceptions, with doctoral students performing better than their Master’s or undergraduate peers. In Study 2, we administered a revised version of our questionnaire to a novel sample of 557 students while controlling for number of years spent at university, psychology courses completed and need for cognition. Once again, we found that graduate students rejected more, affirmed less and reported lower levels of uncertainty than their undergraduate counterparts. Educational implications and future research directions are discussed