Preferential Voting and Applications

Models for combining ballots are the focus here, and the book ties them to multi-attribute decision making through data envelopment analysis. Choosing among options by pooling the ballots of many voters is among the central problems of group decision making, and it is a question that electoral systems must handle constantly. Voting is a democratic procedure for revealing what the majority wants. It is also an easy way to collect expert judgments, and that simplicity is why it counts as a multi-attribute method in group settings. Preferential voting can describe an entire electoral system or a component of one. Each voter backs several candidates, and the order in which those candidates appear on the ballot matters.

Researchers have produced many aggregation models, and one of the strongest results is an approach built on data envelopment analysis. Under this approach, expert opinions are gathered in a straightforward format and merged within an interactive, logically structured process, producing outcomes that can serve as a strong basis for decisions. The book sets out a full collection of voting models grounded in data envelopment analysis and shows how they apply in industry and in society at large. It also points out that many other decision methods either leave out expert input or demand so much interaction and time that experts lose interest, a weakness that voting avoids.

The text is aimed at graduate students in industrial management, business management, industrial engineering, applied mathematics and economics. It will also appeal to researchers in decision science, decision support systems, data envelopment analysis, supply chain management, healthcare management and related fields. Beyond supplying a broad framework for the problems in these areas, the methods are meant to encourage readers to develop new hybrid techniques of their own.