| Do recommender systems manipulate consumer preferences? A study of anchoring effects G Adomavicius, JC Bockstedt, SP Curley, J Zhang Information Systems Research 24 (4), 956-975, 2013 | 276 | 2013 |
| Impact of data characteristics on recommender systems performance G Adomavicius, J Zhang ACM Transactions on Management Information Systems (TMIS) 3 (1), 1-17, 2012 | 185 | 2012 |
| Stability of recommendation algorithms G Adomavicius, J Zhang ACM Transactions on Information Systems (TOIS) 30 (4), 1-31, 2012 | 146 | 2012 |
| Effects of online recommendations on consumers’ willingness to pay G Adomavicius, JC Bockstedt, SP Curley, J Zhang Information Systems Research 29 (1), 84-102, 2018 | 138 | 2018 |
| Consumption and performance: Understanding longitudinal dynamics of recommender systems via an agent-based simulation framework J Zhang, G Adomavicius, A Gupta, W Ketter Information Systems Research 31 (1), 76-101, 2020 | 90 | 2020 |
| Exploring explanation effects on consumers’ trust in online recommender agents J Zhang, SP Curley International Journal of Human–Computer Interaction 34 (5), 421-432, 2018 | 72 | 2018 |
| Recommender systems, consumer preferences, and anchoring effects G Adomavicius, J Bockstedt, S Curley, J Zhang RecSys 2011 workshop on human decision making in recommender systems, 35-42, 2011 | 65 | 2011 |
| De-biasing user preference ratings in recommender systems G Adomavicius, J Bockstedt, S Curley, J Zhang RecSys 2014 Workshop on Interfaces and Human Decision Making for Recommender …, 2014 | 63 | 2014 |
| Reducing recommender systems biases: An investigation of rating display designs G Adomavicius, J Bockstedt, S Curley, J Zhang SSRN, 2021 | 39 | 2021 |
| Classification, ranking, and top-K stability of recommendation algorithms G Adomavicius, J Zhang INFORMS Journal on Computing 28 (1), 129-147, 2016 | 37 | 2016 |
| Improving stability of recommender systems: a meta-algorithmic approach G Adomavicius, J Zhang IEEE Transactions on Knowledge and Data Engineering 27 (6), 1573-1587, 2014 | 33* | 2014 |
| The hidden side effects of recommendation systems G Adomavicius, J Bockstedt, SP Curley, J Zhang, S Ransbotham MIT Sloan Management Review 60 (2), 1, 2019 | 31 | 2019 |
| Reducing recommender systems biases: An investigation of rating display designs G Adomavicius, J Bockstedt, S Curley, J Zhang MIS Quarterly 43 (4), 19-18, 2019 | 22 | 2019 |
| Effects of Online Recommendations on Consumers' Willingness to Pay. G Adomavicius, JC Bockstedt, SP Curley, J Zhang Decisions@ RecSys, 40-45, 2012 | 20 | 2012 |
| Understanding Effects of Personalized vs. Aggregate Ratings on User Preferences. G Adomavicius, JC Bockstedt, SP Curley, J Zhang IntRS@ RecSys, 14-21, 2016 | 19 | 2016 |
| Anchoring effects of recommender systems J Zhang Proceedings of the fifth ACM conference on Recommender systems, 375-378, 2011 | 18 | 2011 |
| A texture-based methodology for identifying tissue type in magnetic resonance images M Barnathan, J Zhang, E Miranda, V Megalooikonomou, S Faro, ... 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to …, 2008 | 18 | 2008 |
| When Algorithms Err: Differential Impact of Early vs. Late Errors on Users’ Reliance on Algorithms A Kim, M Yang, J Zhang ACM Transactions on Computer-Human Interaction 30 (1), 1-36, 2023 | 15 | 2023 |
| Effects of personalized recommendations versus aggregate ratings on post-consumption preference responses G Adomavicius, J Bockstedt, S Curley, J Zhang Forthcoming, MIS Quarterly, Kelley School of Business Research Paper, 2021 | 13 | 2021 |
| Understanding the impact of individual users’ rating characteristics on the predictive accuracy of recommender systems X Cheng, J Zhang, L Yan INFORMS Journal on Computing 32 (2), 303-320, 2020 | 13 | 2020 |
Gediminas AdomaviciusProfessor of Information and Decision Sciences, University of MinnesotaVerified email at umn.edu
