TY - JOUR
T1 - The division of labor between human and computer in the presence of decision support system advice
AU - Jones, Donald R.
AU - Brown, Darrell
N1 - Funding Information:
We appreciate helpful comments from Ramji Balakrishnan, Marlys Lipe, Tanya Benford, Bill Messier and Patrick Wheeler. We are also grateful for suggestions from workshop participants at Georgia State University, Oklahoma State University, Portland State University, the State University of New York at Buffalo, the University of Oklahoma, the University of Utah, and the 1999 American Accounting Association National Meeting. This project was partially funded by Georgia State University and Portland State University.
PY - 2002/8
Y1 - 2002/8
N2 - Prior research suggests that decision support system (DSS) provide model advice and display non-modeled information for decision makers. We investigate whether decision makers (1) delegate the processing of the modeled information to the model, (2) cognitively process the non-modeled information, and (3) decide based on the model's advice adjusted for the non-modeled information. Experimentally, decision makers were no more likely to execute normative strategies when they had requisite knowledge for the strategy than when they did not have the requisite knowledge. We observed alternative processing, including ignoring the advice altogether, and evaluating the advice. Our findings suggest that DSS builders must encourage decision strategies that capitalize on the relative strengths of human and computer in using those features.
AB - Prior research suggests that decision support system (DSS) provide model advice and display non-modeled information for decision makers. We investigate whether decision makers (1) delegate the processing of the modeled information to the model, (2) cognitively process the non-modeled information, and (3) decide based on the model's advice adjusted for the non-modeled information. Experimentally, decision makers were no more likely to execute normative strategies when they had requisite knowledge for the strategy than when they did not have the requisite knowledge. We observed alternative processing, including ignoring the advice altogether, and evaluating the advice. Our findings suggest that DSS builders must encourage decision strategies that capitalize on the relative strengths of human and computer in using those features.
KW - DSS development
KW - Decision model reliance
KW - Decision strategies
KW - Human/computer interaction
UR - http://www.scopus.com/inward/record.url?scp=0036681006&partnerID=8YFLogxK
U2 - 10.1016/S0167-9236(02)00005-2
DO - 10.1016/S0167-9236(02)00005-2
M3 - Article
AN - SCOPUS:0036681006
SN - 0167-9236
VL - 33
SP - 375
EP - 388
JO - Decision Support Systems
JF - Decision Support Systems
IS - 4
ER -