The Role of Cognitive Decision Effort in Electronic Commerce Recommendation System
The purpose of this paper is to explore the role of
cognitive decision effort in recommendation system, combined with
indicators "information quality" and "service quality" from IS success
model to exam the awareness of the user for the "recommended system
performance". A total of 411 internet user answered a questionnaire
assessing their attention of use and satisfaction of recommendation
system in internet book store. Quantitative result indicates following
research results. First, information quality of recommended system
has obvious influence in consumer shopping decision-making process,
and the attitude to use the system. Second, in the process of consumer's
shopping decision-making, the recommendation system has no
significant influence for consumers to pay lower cognitive
decision-making effort. Third, e-commerce platform provides
recommendations and information is necessary, but the quality of
information on user needs must be considered, or they will be other
competitors offer homogeneous services replaced.
[1] O. Commerce, D.o., 2008 Yearbook of the Republic of China
e-commerce2009, Taipei: Institute for Information Industry.
[2] Bo, X. and I. Benbasat, E-commerce Product Recommendation Agents:
Use, Chracteristics, and Impact, in MIS Quarterly2007, MIS Quarterly &
The Society for Information Management. p. 137-209.
[3] Davis, F.D., Perceived Usefulness, Perceived Ease of Use, and User
Acceptance of Information Technology, in MIS Quarterly1989, MIS
Quarterly & The Society for Information Management. p. 319-340.
[4] DeLone and McLean, Information systems success: the quest for the
dependent variable. Information systems research, 1992. 3(1): p. 60-95.
[5] Brown, D.L. and D.R. Jones, Factors that Influence Reliance on Decision
Aids: A Model and an Experiment, in Journal of Information
Systems1998, American Accounting Association. p. 75-94.
[6] Blackwell, R.D., P.W. Miniard, and J.F. Engel, Consumer behavior. 10th
ed2006, Mason, Ohio: Thomson Business and Economics. xlii, 774 p.
[7] Creyer, E.H., J.R. Bettman, and J.W. Payne, The impact of accuracy and
effort feedback and goals on adaptive decision behavior. Journal of
Behavioral Decision Making, 1990. 3(1): p. 1-16.
[8] Todd, P. and I. Benbasat, An experimental investigation of the impact of
computer based decision aids on decision making strategies. Information
systems research, 1991. 2(2): p. 87-115.
[9] Todd, P. and I. Benbasat, The use of information in decision making: an
experimental investigation of the impact of computer-based decision aids.
MIS Quarterly, 1992. 16(3): p. 373-393.
[10] Todd, P. and I. Benbasat, An Experimental Investigation of the
Relationship Between, Decision Makers, Decision Aids and Decision
Making Effort. INFOR-OTTAWA-, 1993. 31: p. 80-80.
[11] Todd, P. and I. Benbasat, The influence of decision aids on choice
strategies: an experimental analysis of the role of cognitive effort.
Organizational Behavior and Human Decision Processes, 1994. 60(1): p.
36-74.
[12] Todd, P. and I. Benbasat, Evaluating the impact of DSS, cognitive effort,
and incentives on strategy selection. Information systems research, 1999.
10(4): p. 356.
[13] Todd, P. and I. Benbasat, Inducing compensatory information processing
through decision aids that facilitate effort reduction: an experimental
assessment. Journal of Behavioral Decision Making, 2000. 13(1): p.
91-106.
[14] Taylor, A.R., Perceived Effort Saved¡¦s Influence on Perceptions of Effort
and Accuracy.
[15] Fogg, B. and C. Nass. How users reciprocate to computers: an experiment
that demonstrates behavior change. 1997. ACM.
[16] Bechwati, N. and L. Xia, Do computers sweat? The impact of perceived
effort of online decision aids on consumers' satisfaction with the decision
process. Journal of Consumer Psychology, 2003: p. 139-148.
[17] DeLone and McLean, The DeLone and McLean Model of Information
Systems Success: A Ten-Year Update, in Journal of Management
Information Systems2003, M.E. Sharpe Inc. p. 9-30.
[18] Pitt, L., R. Watson, and C. Kavan, Service quality: a measure of
information systems effectiveness. MIS Quarterly, 1995. 19(2): p.
173-187.
[19] Wathen, C. and J. Burkell, Believe it or not: Factors influencing
credibility on the Web. Journal of the American Society for Information
Science and Technology, 2002. 53(2): p. 134-144.
[20] Fan, X., B. Thompson, and L. Wang, Effects of sample size, estimation
methods, and model specification on structural equation modeling fit
indexes. Structural Equation Modeling: A Multidisciplinary Journal,
1999. 6(1): p. 56-83.
[21] Bagozzi, R. and Y. Yi, On the evaluation of structural equation models.
Journal of the academy of marketing science, 1988. 16(1): p. 74-94.
[22] Hair, J., et al., Multivariate analysis. Englewood: Prentice Hall
International, 1998.
[23] Browne, M. and R. Cudeck, Alternative ways of assessing model fit.
Testing structural equation models, 1993. 154: p. 136¡V162.
[1] O. Commerce, D.o., 2008 Yearbook of the Republic of China
e-commerce2009, Taipei: Institute for Information Industry.
[2] Bo, X. and I. Benbasat, E-commerce Product Recommendation Agents:
Use, Chracteristics, and Impact, in MIS Quarterly2007, MIS Quarterly &
The Society for Information Management. p. 137-209.
[3] Davis, F.D., Perceived Usefulness, Perceived Ease of Use, and User
Acceptance of Information Technology, in MIS Quarterly1989, MIS
Quarterly & The Society for Information Management. p. 319-340.
[4] DeLone and McLean, Information systems success: the quest for the
dependent variable. Information systems research, 1992. 3(1): p. 60-95.
[5] Brown, D.L. and D.R. Jones, Factors that Influence Reliance on Decision
Aids: A Model and an Experiment, in Journal of Information
Systems1998, American Accounting Association. p. 75-94.
[6] Blackwell, R.D., P.W. Miniard, and J.F. Engel, Consumer behavior. 10th
ed2006, Mason, Ohio: Thomson Business and Economics. xlii, 774 p.
[7] Creyer, E.H., J.R. Bettman, and J.W. Payne, The impact of accuracy and
effort feedback and goals on adaptive decision behavior. Journal of
Behavioral Decision Making, 1990. 3(1): p. 1-16.
[8] Todd, P. and I. Benbasat, An experimental investigation of the impact of
computer based decision aids on decision making strategies. Information
systems research, 1991. 2(2): p. 87-115.
[9] Todd, P. and I. Benbasat, The use of information in decision making: an
experimental investigation of the impact of computer-based decision aids.
MIS Quarterly, 1992. 16(3): p. 373-393.
[10] Todd, P. and I. Benbasat, An Experimental Investigation of the
Relationship Between, Decision Makers, Decision Aids and Decision
Making Effort. INFOR-OTTAWA-, 1993. 31: p. 80-80.
[11] Todd, P. and I. Benbasat, The influence of decision aids on choice
strategies: an experimental analysis of the role of cognitive effort.
Organizational Behavior and Human Decision Processes, 1994. 60(1): p.
36-74.
[12] Todd, P. and I. Benbasat, Evaluating the impact of DSS, cognitive effort,
and incentives on strategy selection. Information systems research, 1999.
10(4): p. 356.
[13] Todd, P. and I. Benbasat, Inducing compensatory information processing
through decision aids that facilitate effort reduction: an experimental
assessment. Journal of Behavioral Decision Making, 2000. 13(1): p.
91-106.
[14] Taylor, A.R., Perceived Effort Saved¡¦s Influence on Perceptions of Effort
and Accuracy.
[15] Fogg, B. and C. Nass. How users reciprocate to computers: an experiment
that demonstrates behavior change. 1997. ACM.
[16] Bechwati, N. and L. Xia, Do computers sweat? The impact of perceived
effort of online decision aids on consumers' satisfaction with the decision
process. Journal of Consumer Psychology, 2003: p. 139-148.
[17] DeLone and McLean, The DeLone and McLean Model of Information
Systems Success: A Ten-Year Update, in Journal of Management
Information Systems2003, M.E. Sharpe Inc. p. 9-30.
[18] Pitt, L., R. Watson, and C. Kavan, Service quality: a measure of
information systems effectiveness. MIS Quarterly, 1995. 19(2): p.
173-187.
[19] Wathen, C. and J. Burkell, Believe it or not: Factors influencing
credibility on the Web. Journal of the American Society for Information
Science and Technology, 2002. 53(2): p. 134-144.
[20] Fan, X., B. Thompson, and L. Wang, Effects of sample size, estimation
methods, and model specification on structural equation modeling fit
indexes. Structural Equation Modeling: A Multidisciplinary Journal,
1999. 6(1): p. 56-83.
[21] Bagozzi, R. and Y. Yi, On the evaluation of structural equation models.
Journal of the academy of marketing science, 1988. 16(1): p. 74-94.
[22] Hair, J., et al., Multivariate analysis. Englewood: Prentice Hall
International, 1998.
[23] Browne, M. and R. Cudeck, Alternative ways of assessing model fit.
Testing structural equation models, 1993. 154: p. 136¡V162.
@article{"International Journal of Information, Control and Computer Sciences:61356", author = "Cheng-Che Tsai and Huang-Ming Chuang", title = "The Role of Cognitive Decision Effort in Electronic Commerce Recommendation System", abstract = "The purpose of this paper is to explore the role of
cognitive decision effort in recommendation system, combined with
indicators "information quality" and "service quality" from IS success
model to exam the awareness of the user for the "recommended system
performance". A total of 411 internet user answered a questionnaire
assessing their attention of use and satisfaction of recommendation
system in internet book store. Quantitative result indicates following
research results. First, information quality of recommended system
has obvious influence in consumer shopping decision-making process,
and the attitude to use the system. Second, in the process of consumer's
shopping decision-making, the recommendation system has no
significant influence for consumers to pay lower cognitive
decision-making effort. Third, e-commerce platform provides
recommendations and information is necessary, but the quality of
information on user needs must be considered, or they will be other
competitors offer homogeneous services replaced.", keywords = "Recommender system, Cognitive decision-making
efforts, IS success model, Internet bookstore.", volume = "5", number = "10", pages = "1141-5", }
