Behavioral Social Choice: Probabilistic Models, Statistical Inference, and Applications

<p>Looking at the probabilistic foundations of collective decision-making rules, the authors challenge much of the existing theoretical wisdom about social choice processes, and seek to restore faith in the possibility of democratic decision-making. In particular, they argue that worries about the supposed prevalence of majority rule cycles, that would preclude groups from reaching a final decision about what alternative they prefer, have been greatly overstated. In practice, majority rule can be expected to work well in most real-world settings. They provide new insights into how alternative model specifications can change our estimates of social orderings.</p>

Business & Money

Grofman, Bernard

Marley, A. A. J.

Regenwetter, Michel

Tsetlin, Ilia

Economics

Cambridge University Press

Looking at the probabilistic foundations of collective decision-making rules, the authors challenge much of the existing theoretical wisdom about social choice processes, and seek to restore faith in the possibility of democratic decision-making. In particular, they argue that worries about the supposed prevalence of majority rule cycles, that would preclude groups from reaching a final decision about what alternative they prefer, have been greatly overstated. In practice, majority rule can be expected to work well in most real-world settings. They provide new insights into how alternative model specifications can change our estimates of social orderings.

<p>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.</p>

Best-Worst Scaling: Theory, Methods and Applications

Louviere, Jordan J.

Flynn, Terry N.

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