Ulteriori informazioni
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.
Sommario
Part 1: Data 1. Organizational Data and its Implications for Research and Theory 2. Using Other Peoples' Data: Implications of Reliance on Meta-analysis and Archival Data 3. Data sharing and Data Integrity 4. Using Data in Organizations Part 2: Methods 5. Evaluating data 6. Organic Data and the Design of Studies 7. Surviving the Statistical Arms Race Part 3: Theory 8. How do Theories in the Behavioral and Social Sciences Emerge, Develop and Decline?: The Evolution of Politics Perceptions Theory 9. The Data Revolution and the Interplay Between Theory and Data 10. Scholarly Course Corrections Needed to Advance Organizational Science: Field Tests of Theory-based Deductions are Long Overdue Part 4: Implications for Organizational Science 11. The Research Environment: Opportunities and Obstacles for Advancing Organizational Science 12. Training (and Retraining) in Data, Methods, and Theory in the Organizational Sciences 13. Rebuilding Relationships between Data, Method, and Theories: How the Scientific Method Can Help
Info autore
Kevin R. Murphy is Professor Emeritus at the University of Limerick, Ireland. He is a former SIOP President and Editor of the Journal of Applied Psychology, and has been published in areas ranging from performance appraisal and psychometrics to honesty in the workplace.
Riassunto
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.
