Best-Worst Scaling: Theory, Methods and Applications

ISBN-13: 9781107043152 / Angielski / Twarda / 2015 / 360 str.

Jordan Louviere; Terry Flynn; Anthony A. J. Marley

Opis

Best-worst scaling (BWS) is an extension of the method of paired comparison to multiple choices that asks participants to choose both the most and the least attractive options or features from a set of choices. It is an increasingly popular way for academics and practitioners in social science, business, and other disciplines to study and model choice. This book provides an authoritative and systematic treatment of best-worst scaling, introducing readers to the theory and methods for three broad classes of applications. It uses a variety of case studies to illustrate simple but reliable ways to design, implement, apply, and analyze choice data in specific contexts, and showcases the wide range of potential applications across many different disciplines. Best-worst scaling avoids many rating scale problems and will appeal to those wanting to measure subjective quantities with known measurement properties that can be easily interpreted and applied.

Recenzje

'This is the definitive source work on best-worst scaling - the method is explained and illustrated by its original developers. A must-have for marketing research practitioners, consultants, and academics interested in the latest advances in stated-choice methods.' Robert J. Meyer, Frederick H. Ecker/Metlife Insurance Professor of Marketing and Co-Director, Wharton Center for Risk Management and Decision Processes, The Wharton School, University of Pennsylvania

Spis treści

Preface; Acknowledgments; Theory and Methods: 1. Introduction and overview of the book; 2. The BWS object case; 3. The BWS profile case; 4. The BWS multi-profile case; 5. Basic models; 6. Looking forward; Applications - Case 1: 7. BWS object case application: attitudes towards end-of-life care Terry N. Flynn, Elisabeth Huynh and Charles Corke; 8. How consumers choose wine: using best-worst scaling across countries Larry Lockshin and Eli Cohen; 9. Best-worst scaling: an alternative to ratings data Geoffrey N. Soutar, Jillian C. Sweeney and Janet R. McColl-Kennedy; Applications - Case 2: 10. When the ayes don't have it: supplementing an accept/reject DCE with a case 2 best-worst scaling task Richard T. Carson and Jordan J. Louviere; 11. BWS profile case application: preferences for treatment in dentistry Emma McIntosh and Terry N. Flynn; 12. BWS profile case application: preferences for quality of life in Australia Terry N. Flynn and Elisabeth Huynh; Applications - Case 3: 13. The stability of aggregate-level preferences in longitudinal discrete choice experiments Towhidul Islam and Jordan J. Louviere; 14. Case 3 best-worst analysis using delivered pizza and toothpaste examples Bart D. Frischknecht and Jordan J. Louviere; 15. Using alternative-specific DCE designs and best and worst choices to model choices Jordan J. Louviere; References; Subject index; Author index.