Affiliation:
1. University of Georgia, Athens, Georgia 30602;
2. King’s College London, London WC2B 4BG, United Kingdom;
3. Simon Fraser University, Vancouver, British Columbia V6C 1W6, Canada
Abstract
A Theory of Information Compression: When Judgments Are CostlyHow useful to tourists are thousands of reviews of different five-star hotels in a city on a travel website when the mean rating is 4.5, and all the five-star hotels score around the mean? How insightful are reviews of physicians on a physician review website to potential patients when the ratings cluster tightly around an average for all physicians? Are there costs to the physicians, the patients, and to society as a whole? When all the students at a university score “A” grades on most courses, are there consequences for the university, the students, and potential employers? This paper calls the “clustering around a mean” phenomenon “information compression” and the systems in which it occurs (e.g., universities, students, employers) “judgment networks.” When there is extensive information compression in a system, measures such as ratings or grades have little value for decision makers. When all five-star hotels in a city score an average of 4.5 does it really matter which one a traveler chooses? The paper introduces a way of measuring information compression. It also suggests ways for organizations to overcome the negative consequences of information compression for themselves and their various stakeholders.
Publisher
Institute for Operations Research and the Management Sciences (INFORMS)
Subject
Library and Information Sciences,Information Systems and Management,Computer Networks and Communications,Information Systems,Management Information Systems
Cited by
3 articles.
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