Ulteriori informazioni
This collection provides a primer to the process and promise of computational modeling for industrial-organizational psychologists.
Sommario
Part I: The Call for Computational Modeling in I/O
1. Better Theory, Methods, and Practice through Computational Modeling
Jeffrey B. Vancouver, Mo Wang, and Justin M. Weinhardt
2. Toward Integrating Computational Models of Decision-making into Organizational Research
Shannon N. Cooney, Michelle S. Kaplan and Michael T. Braun
3. Computational Modeling in Organizational Diversity and Inclusion
Hannah L. Samuelson and Jaeeun Lee, Jennifer L. Wessel and James A. Grand
4. Computational Models of Learning, Training, and Socialization: A Targeted Review and a Look Toward the Future
J. H. Hardy III
5. Models of Leadership in Teams
Le Zhou
6. Using Simulations to Predict the Behavior of Groups and Teams
Deanna M. Kennedy
Part II: Creating and Validating Computational Models
7. Agent-Based Modeling
Chen Tang and Yihao Liu
8. Computational Modeling with System Dynamics
Jeffrey B. Vancouver and Xiaofei Li
9. Evaluating Computational Models
Justin M. Weinhardt
10. Fitting Computational Models to Data: A Tutorial
Timothy Ballard, Hector Palada, and Andrew Neal
11. How to Publish and Review a Computational Model
Andrew Neal, Timothy Ballard, and Hector Palada
Info autore
Jeffrey B. Vancouver is Professor and Byham Chair in Industrial Organizational Psychology at Ohio University, USA.
Mo Wang is University Distinguished Professor and Lanzillotti-McKethan Eminent Scholar Chair at Warrington College of Business at the University of Florida, USA.
Justin M. Weinhardt is Associate Professor of Organizational Behavior and Human Resources at the University of Calgary, Canada.
Riassunto
This collection provides a primer to the process and promise of computational modeling for industrial-organizational psychologists.
