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Preferential Voting and Applications: Approaches Based on Data Envelopment Analysis (1st ed. 2023)
Loot Price: R4,630
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Preferential Voting and Applications: Approaches Based on Data Envelopment Analysis (1st ed. 2023)
Series: Studies in Systems, Decision and Control, 471
Expected to ship within 10 - 15 working days
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This book presents the theory and application of the models
presented in this regard and establishes a meaningful relationship
between data envelopment analysis and multi-attribute decision
making. The issue of "choice" using the aggregation of voters'
votes is one of the most important group decision-making issues
that are always considered by decision makers in electoral systems.
Voting is a method of group decision making in a democratic society
that expresses the will of the majority. Voting is perhaps the
simplest way to gather the opinions of experts, and this ease of
application has made it a multi-attribute decision-making method in
group decisions. Preferential voting is a type of voting that may
refer to electoral systems or groups of the electoral system. In
preferential voting, voters vote for multiple candidates, and how
the candidates are arranged on the ballot is important. Researchers
have made many efforts to provide models of voter aggregation, and
one of the best results of these efforts is the aggregation of
votes based on the policy of data envelopment analysis. Thus, in
group decisions, the opinions of experts are obtained in a simple
structure and consolidated in an interactive and logical structure,
and the results can be a powerful tool for decision support. This
book provides a complete set of voting models based on data
envelopment analysis and expressing its various applications in
industry and society. However, most decision-making methods do not
use the opinions of experts or reduce the motivation of experts to
participate in complex interactions and time, while voting methods
do not have this shortcoming. This book is suitable for graduate
students in the fields of industrial management, business
management, industrial engineering, applied mathematics, and
economics. It can also be a good source for researchers in decision
science, decision support systems, data envelopment analysis,
supply chain management, healthcare management, and others. The
methods presented in this book can not only offer a comprehensive
framework for solving the problems of these areas but also can
inspire researchers to pursue new innovative hybrid methods.
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