Abstract
An effort to improve data accuracy that yields poorer information accuracy when the data are processed would normally be labeled a major failure. While popular belief discounts the likelihood of such an event, research of conjunctive and disjunctive decision rules suggests that a negative association between input accuracy and decision accuracy is a deeply rooted phenomenon. In this paper we extend the understanding of this phenomenon through an empirical investigation of conjunctive decision rules using Monte Carlo simulations. The implications of this research are not limited to data accuracy; other data deficiencies can generate a comparable effect.
Recommended Citation
Askira Gelman, Irit, "An Empirical Study of the GIGO Axiom in Satisficing Decisions" (2012). AMCIS 2012 Proceedings. 12.
https://aisel.aisnet.org/amcis2012/proceedings/DataInfoQuality/12
An Empirical Study of the GIGO Axiom in Satisficing Decisions
An effort to improve data accuracy that yields poorer information accuracy when the data are processed would normally be labeled a major failure. While popular belief discounts the likelihood of such an event, research of conjunctive and disjunctive decision rules suggests that a negative association between input accuracy and decision accuracy is a deeply rooted phenomenon. In this paper we extend the understanding of this phenomenon through an empirical investigation of conjunctive decision rules using Monte Carlo simulations. The implications of this research are not limited to data accuracy; other data deficiencies can generate a comparable effect.