缩放比例
多样性(控制论)
集合(抽象数据类型)
上诉
扩展(谓词逻辑)
计算机科学
最佳实践
航程(航空)
简单(哲学)
数据科学
比例(比率)
度量(数据仓库)
管理科学
人工智能
数学
数据挖掘
认识论
工程类
政治学
几何学
航空航天工程
程序设计语言
法学
哲学
物理
量子力学
作者
Jordan J. Louviere,Terry N. Flynn,A. A. J. Marley
出处
期刊:Cambridge University Press eBooks
[Cambridge University Press]
日期:2015-09-23
被引量:470
标识
DOI:10.1017/cbo9781107337855
摘要
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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