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Thomas L. Saaty
Researcher at University of Pittsburgh
Publications - 376
Citations - 103418
Thomas L. Saaty is an academic researcher from University of Pittsburgh. The author has contributed to research in topics: Analytic hierarchy process & Analytic network process. The author has an hindex of 92, co-authored 375 publications receiving 95026 citations. Previous affiliations of Thomas L. Saaty include College of Business Administration & Politécnico Grancolombiano.
Papers
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Book ChapterDOI
Criteria for Evaluating Group Decision-Making Methods
Thomas L. Saaty,Luis G. Vargas +1 more
TL;DR: This chapter is concerned with the development of criteria for evaluating different methods of group decision-making that range from the strictly technical, to the psychophysical and social, and finally, toThe logical and scientific.
Journal ArticleDOI
Decision making, new information, ranking and structure
TL;DR: In this article, the rank of a set of alternatives can change if a new criterion is introduced into the set of criteria, but it can also change if the importance of the criteria depend on the number of alternatives and on the strength of their ranking.
Journal ArticleDOI
Résumé of Useful Formulas in Queuing Theory
TL;DR: This paper is intended as a convenient summary of some results in queuing, which in the author's opinion would be of value to investigators applying the theory to operational problems.
Journal ArticleDOI
The scope of human values and human activities in decision making
Thomas L. Saaty,Nina Begičević +1 more
TL;DR: A very broad framework is provided in this paper to address the issue of structuring decisions in a reliable way to serve the needs of decision makers.
Journal ArticleDOI
Evaluating and Optimizing Technological Innovation Efficiency of Industrial Enterprises Based on Both Data and Judgments
TL;DR: An evaluation method based on data and judgments to rank the technological innovation capability and technological innovation efficiency of enterprises of various sizes in China and design a model for the government to optimally allocate innovation resource to businesses.