Publishing In The Organizational Sciences Toward The Conceptualization Of An Hypothetico Deductive Scientific Research Framework

This book is designed to introduce doctoral and graduate students to the process of conducting scientific research in the social sciences, business, education, public health, and related disciplines. It is a one-stop, comprehensive, and compact source for foundational concepts in behavioral research, and can serve as a stand-alone text or as a supplement to research readings in any doctoral seminar or research methods class. This book is currently used as a research text at universities on six continents and will shortly be available in nine different languages.

Data, Methods and Theory in the Organizational Sciences explores the long-term evolution and changing relationships between data, methods, and theory in the organizational sciences. In the last 50 years, theory has come to dominate research and scholarship in these fields, yet the emergence of big data, as well as the increasing use of archival data sets and meta-analytic methods to test empirical hypotheses, has upset this order. This volume examines the evolving relationship between data, methods, and theory and suggests new ways of thinking about the role of each in the development and presentation of research in organizations. This volume utilizes the latest thinking from experts in a wide range of fields on the topics of data, methods, and theory and uses this knowledge to explore the ways in which behavior in organizations has been studied. This volume also argues that the current focus on theory is both unhealthy for the field and unsustainable, and it provides more successful ways theory can be used to support and structure research, and demonstrates the most effective techniques for analyzing and making sense of data. This is an essential resource for researchers, professionals, and educators who are looking to rethink their current approaches to research, and who are interested in creating more useful and more interpretable research in the organizational sciences.

This book encompasses a systematic exploration of Cybersecurity Data Science (CSDS) as an emerging profession, focusing on current versus idealized practice. This book also analyzes challenges facing the emerging CSDS profession, diagnoses key gaps, and prescribes treatments to facilitate advancement. Grounded in the management of information systems (MIS) discipline, insights derive from literature analysis and interviews with 50 global CSDS practitioners. CSDS as a diagnostic process grounded in the scientific method is emphasized throughout Cybersecurity Data Science (CSDS) is a rapidly evolving discipline which applies data science methods to cybersecurity challenges. CSDS reflects the rising interest in applying data-focused statistical, analytical, and machine learning-driven methods to address growing security gaps. This book offers a systematic assessment of the developing domain. Advocacy is provided to strengthen professional rigor and best practices in the emerging CSDS profession. This book will be of interest to a range of professionals associated with cybersecurity and data science, spanning practitioner, commercial, public sector, and academic domains. Best practices framed will be of interest to CSDS practitioners, security professionals, risk management stewards, and institutional stakeholders. Organizational and industry perspectives will be of interest to cybersecurity analysts, managers, planners, strategists, and regulators. Research professionals and academics are presented with a systematic analysis of the CSDS field, including an overview of the state of the art, a structured evaluation of key challenges, recommended best practices, and an extensive bibliography.

This book applies a reflective and critical gaze on the production of knowledge within management and organization studies. Seasoned scholars reflect on how we carry out research to provide insights into the assumptions and practices we employ, and how they affect the production and consumption of managerial knowledge and organization theory.

Researchers, historians, and philosophers of science have debated the nature of scientific research in education for more than 100 years. Recent enthusiasm for "evidence-based" policy and practice in educationâ€"now codified in the federal law that authorizes the bulk of elementary and secondary education programsâ€"have brought a new sense of urgency to understanding the ways in which the basic tenets of science manifest in the study of teaching, learning, and schooling. Scientific Research in Education describes the similarities and differences between scientific inquiry in education and scientific inquiry in other fields and disciplines and provides a number of examples to illustrate these ideas. Its main argument is that all scientific endeavors share a common set of principles, and that each fieldâ€"including education researchâ€"develops a specialization that accounts for the particulars of what is being studied. The book also provides suggestions for how the federal government can best support high-quality scientific research in education.

'Grounded Theory in Management Research' provides a comprehensive introduction to the widely used qualitative method of grounded theory.

This book provides principles on content analysis and its application into development of nursing theory. It offers clear guidance to students, lecturers and researchers to gain a deeper understanding of the method of content analysis, its implementation into their own research and criteria of trustworthiness evaluation. The book is written in user-friendly language with provided research examples and cases, and the content is illustrated by figures and tables. The authors offer their expertise in providing a well thought through explanation of content analysis in didactical style, which will enhance university education. The book includes highly experienced researchers who have published articles on content analysis and the trustworthiness of the method with more than 10 000 citations. Divided into two parts, this book explores the application of content analysis into nursing science. The first part presents the philosophical position of content analysis, inductive and deductive methods of using content analysis, trustworthiness of the method, and ethical consideration of using content analysis. The second part informs on the theory development based on content analysis, conceptualization of the concepts of content analysis into generation of items and instrument development, and statistical testing of a hypothetical model. The last chapter shows a new approach to using content analysis in systematic reviews and quality evaluation of methodology within systematic review process. The book is an essential tool for nursing science, providing instruction on key methodological elements in order to provide rigorously conducted empirical research for clinical practice and nursing education.