An Application of the Blin-Whinston Algorithm for Resolving Fuzzy Group Preferences

Earle Steinberg and Dan Rinks
Additional contact information
Earle Steinberg: University of Houston
Dan Rinks: West Virginia University

Management Science, 1979, vol. 25, issue 2, 159-170

Abstract: Important decisions regarding governmental expenditures for the public welfare require accurate assessment of preferences of the citizenry as one input. Often, strong disagreement exists regarding relative merit of various projects competing for limited resources. This paper proposes a procedure for establishing a complete social preference ordering on the set of alternative projects when the group preference is fuzzy because of individual differences. An extension of current algorithms is developed-and applied to a problem concerning public preferences for expenditures on civic projects in Houston, Texas. One thousand male and female heads-of-household were interviewed in depth to determine their preferences for investment among forty-one projects in the areas of social services, business and job development, public transportation, arts and leisure, and education. A complete preference order for group decision was obtained for a situation in which significant disagreement exists among group members and where funding is limited.

Keywords: unlity/preference: applications; group decisions: voting; planning: community (search for similar items in EconPapers)
Date: 1979
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.25.2.159 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:25:y:1979:i:2:p:159-170

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().