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Contractor Accreditation: A Probabilistic Model
Author(s) -
Sarkar Sumit,
Ghosh Deb
Publication year - 1997
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.1997.tb01310.x
Subject(s) - accreditation , vendor , probabilistic logic , process (computing) , database transaction , function (biology) , computer science , business , operations research , marketing , economics , database , mathematics , artificial intelligence , evolutionary biology , biology , economic growth , operating system
The selection of competent contractors is a critical function in all business organizations. In contrast to other types of vendors (e.g., distributors, manufacturers, etc.), contractors are typically accredited before any business transaction takes place. In such situations, there is often a considerable amount of uncertainty associated with the accreditation process. This research presents a probabilistic model for accrediting contractors. We discuss a methodology in which probability measures are used to capture the uncertainty inherent in the decision process. These probabilities are estimated from data on (i) past applicants and (ii) their eventual performance, if accredited. Furthermore, these probabilities are used to determine when additional information about an applicant should be collected, as well as what kind of information would be most relevant for the vendor under consideration.