9781107043152-1107043158-Best-Worst Scaling: Theory, Methods and Applications

Best-Worst Scaling: Theory, Methods and Applications

ISBN-13: 9781107043152
ISBN-10: 1107043158
Author: A.A.J. Marley, Jordan J. Louviere, Terry N. Flynn
Publication date: 2015
Publisher: Cambridge University Press
Format: Hardcover 360 pages
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Book details

ISBN-13: 9781107043152
ISBN-10: 1107043158
Author: A.A.J. Marley, Jordan J. Louviere, Terry N. Flynn
Publication date: 2015
Publisher: Cambridge University Press
Format: Hardcover 360 pages

Summary

Best-Worst Scaling: Theory, Methods and Applications (ISBN-13: 9781107043152 and ISBN-10: 1107043158), written by authors A.A.J. Marley, Jordan J. Louviere, Terry N. Flynn, was published by Cambridge University Press in 2015. With an overall rating of 4.0 stars, it's a notable title among other Econometrics & Statistics (Economics) books. You can easily purchase or rent Best-Worst Scaling: Theory, Methods and Applications (Hardcover) from BooksRun, along with many other new and used Econometrics & Statistics books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.62.

Description

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.

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