14,521 research outputs found
Corporate Social Responsibility: the institutionalization of ESG
Understanding the impact of Corporate Social Responsibility (CSR) on firm performance as it relates to industries reliant on technological innovation is a complex and perpetually evolving challenge. To thoroughly investigate this topic, this dissertation will adopt an economics-based structure to address three primary hypotheses. This structure allows for each hypothesis to essentially be a standalone empirical paper, unified by an overall analysis of the nature of impact that ESG has on firm performance. The first hypothesis explores the evolution of CSR to the modern quantified iteration of ESG has led to the institutionalization and standardization of the CSR concept. The second hypothesis fills gaps in existing literature testing the relationship between firm performance and ESG by finding that the relationship is significantly positive in long-term, strategic metrics (ROA and ROIC) and that there is no correlation in short-term metrics (ROE and ROS). Finally, the third hypothesis states that if a firm has a long-term strategic ESG plan, as proxied by the publication of CSR reports, then it is more resilience to damage from controversies. This is supported by the finding that pro-ESG firms consistently fared better than their counterparts in both financial and ESG performance, even in the event of a controversy. However, firms with consistent reporting are also held to a higher standard than their nonreporting peers, suggesting a higher risk and higher reward dynamic. These findings support the theory of good management, in that long-term strategic planning is both immediately economically beneficial and serves as a means of risk management and social impact mitigation. Overall, this contributes to the literature by fillings gaps in the nature of impact that ESG has on firm performance, particularly from a management perspective
PersonalfĂŒhrung im heterogenen Kollegium von Grund- und Mittelschulen in Bayern
PersonalfĂŒhrung bei zunehmend heterogenen LehrkrĂ€ften wird zusehends wichtiger fĂŒr Schulleitung. Eine theoretische und praktische Neuorientierung in diesem bisher ĂŒbersehenen Feld erscheint notwendig. Dazu werden in der Schulleitungsforschung Erkenntnisse zur differenzierenden PersonalfĂŒhrung gesucht. In der Betriebswirtschaftslehre sowie in der Praxis von Unternehmen werden Neuerungen im Umgang mit gröĂerer DiversitĂ€t bei den Mitarbeitern analysiert. Erfahrungen aus der Praxis von Schulleitungen werden mithilfe offener Interviews ausgewertet. Nach kritischer Auswahl der Ăbertragungsmöglichkeiten wird eine Integration zu einem neuen Ansatz von differenzierender PersonalfĂŒhrung versucht. Konkrete VorschlĂ€ge zur Reform der Ausbildung der Schulleitungen und zur Umsetzung in der Praxis zeigen mögliche Wege der nötigen Verbesserung auf
The Impact of M&As on Shareholdersâ Wealth:Â :Evidence from Greece
This study aims to investigate the effect of mergers and acquisitions (M&A) on shareholdersâ wealth. Additionally, this study investigates the impact of the economic crisis during 2007â2008 on the shareholdersâ perceptions of gaining additional value from mergers and acquisitions. In this paper, a sample of 84 M&As from 2006 to 2015 in Greece are studied to investigate the effect on shareholders of bidder companies. We find significantly negative abnormal returns just before the announcement of M&A, which negatively affects the bidder firmsâ value. It is also observed that after 2009 M&A cases decreased, maybe because of the crisis in Greece that changed the investorsâ perception of a value-destroying event. Companies that engage in M&A activities during economic downturns tend to experience a decline in shareholder value. This could be due to various factors, such as increased uncertainty and risk associated with such activities during economic uncertainty. By understanding the potential impact of such activities on shareholder value, companies can make more informed decisions about whether and when to pursue M&A opportunities
Planetesimal Initial Mass Functions following Diffusion Regulated Gravitational Collapse
The initial mass function (IMF) of planetesimals is of key importance for
understanding the initial stages of planet formation, yet theoretical
predictions so far have been insufficient in explaining the variety of IMFs
found in simulations. Here, we connect diffusion-tidal-shear limited
planetesimal formation within the framework of a Toomre-like instability in the
particle mid-plane of a protoplanetary disk to an analytic prediction for the
planetesimal IMF. The shape of the IMF is set by the stability parameter
, which in turn depends on the particle Stokes number, the Toomre
value of the gas, the local dust concentration and the local diffusivity.
We compare our prediction to high-resolution numerical simulations of the
streaming instability and planetesimal formation via gravitational collapse. We
find that our IMF prediction agrees with numerical results, and is consistent
with both the `planetesimals are born big' paradigm and the power law
description commonly found in simulations.Comment: Accepted in ApJ, 16 pages, 10 figures, 1 tabl
Bayesian Implications for the Primordial Black Holes from NANOGrav's Pulsar-Timing Data Using the Scalar-Induced Gravitational Waves
Assuming that the common-spectrum process in the NANOGrav 12.5-year dataset
has an origin of scalar-induced gravitational waves, we study the enhancement
of primordial curvature perturbations and the mass function of primordial black
holes, by performing the Bayesian parameter inference for the first time. We
obtain lower limits on the spectral amplitude, i.e.,
at 95\% confidence level, when assuming the power
spectrum of primordial curvature perturbations to follow a log-normal
distribution function with width . In the case of ,
we find that the primordial black holes with solar
mass are allowed to compose at least a fraction of dark matter. Such
a mass range is shifted to more massive regimes for larger values of ,
e.g., to a regime of solar mass in the case of .
We expect the planned gravitational-wave experiments to have their best
sensitivity to in the range of to , depending
on the experimental setups. With this level of sensitivity, we can search for
primordial black holes throughout the entire parameter space, especially in the
mass range of to solar masses, where they could account
for all dark matter. In addition, the importance of multi-band detector
networks is emphasized to accomplish our theoretical expectation.Comment: 15 pages, 5 figures, 1 table, version publishe
Technologies and Applications for Big Data Value
This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part âTechnologies and Methodsâ contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part âProcesses and Applicationsâ details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems
Does Access to Patent Information Help Technological Acquisitions?
Technology acquirers face significant information asymmetry when identifying appropriate acquisition targets. Employing plausibly exogenous variation in technological information gathering costs caused by staggered openings of patent libraries, we find that firms become more active in technological acquisitions following local patent library openings. In addition, acquirers prefer targets that are geographically close or are similar in technological space to a lesser extent, technology M&A completion rates increase, acquirersâ abnormal announcement returns are higher, and long-term stock returns of combined firms are better. Acquirersâ access to patent libraries also leads to greater post-merger innovation output through fostering more collaboration between acquirersâ and targetsâ inventors. Overall, our study sheds new light on the importance of information gathering costs in corporate takeovers and the search for human capital synergies
Cultivating Agrobiodiversity in the U.S.: Barriers and Bridges at Multiple Scales
The diversity of crops grown in the United States (U.S.) is declining, causing agricultural landscapes to become more and more simplified. This trend is concerning for the loss of important plant, insect, and animal species, as well as the pollution and degradation of our environment. Through three separate but related studies, this dissertation addresses the need to increase the diversity of these agricultural landscapes in the U.S., particularly through diversifying the type and number of crops grown. The first study uses multiple, openly accessible datasets related to agricultural land use and policies to document and visualize change over recent decades. Through this, I show that U.S. agriculture has gradually become more specialized in the crops grown, crop production is heavily concentrated in certain areas, and crop diversity is continuing to decline. Meanwhile, federal agricultural policy, while having become more influential over how U.S. agriculture operates, incentivizes this specialization. The second study uses nonlinear statistical modeling to identify and compare social, political, and ecological factors that best predict crop diversity across nine regions in the U.S. Factors of climate, prior land use, and farm inputs best predict diversity across regions, but regions show key differences in how factors are important, indicating that patterns at the regional scale constrain and enable further diversification. Finally, the third study relied on interviews with farmers and key informants in southern Idahoâs Magic Valley â a cluster of eight counties that is known to be agriculturally diverse. Interviews gauge what farmers are currently doing to manage crop diversity (the present) and how they imagine alternative landscapes (the imaginary). We found that farmers in the Magic Valley manage current diversity mainly through cover cropping and diverse crop rotations, but daily struggles and political barriers make experimenting with and imagining alternative landscapes difficult and unlikely to occur. Together, these three studies provide an integrated view of how and why U.S. agriculture landscapes simplify or diversify, as well as the barriers and bridges such pathways of diversification
- âŠ