Panos’ research program studies how information systems and technological artifacts affect the user behavior and transform business and society.
His research focuses on personalization, mobile and social commerce, and online education.
Much of this research is grounded in big data employing data science and machine-learning techniques to leverage the abundance of unstructured data in social media, while combining these approaches with more conventional econometric and other quantitative methods as well as experimental research designs.
Journal Publications
Panagiotis Adamopoulos, Vilma Todri: Consumer Social Connectedness and Persuasiveness of Automated Collaborative-Filtering Recommender Systems: Evidence from an Online-to-Offline Recommendation App. Production and Operations Management (POM)
Panagiotis Adamopoulos: The Spillover Effect of Fraudulent Reviews on Product Recommendations. Management Science (MS)
Nasim Mousavi, Panagiotis Adamopoulos, Jesse Bockstedt: The Decoy Effect and Recommendation Systems. Information Systems Research (ISR)
Marios Kokkodis, Panagiotis Adamopoulos, Sam Ransbotham: Asymmetric Reputation Spillover Effects from Digital Agencies in Online Markets. MIS Quarterly (MISQ)
Chenshuo Sun, Panagiotis Adamopoulos, Anindya Ghose, Xueming Luo: Predicting Stages in the Consumer Path-Purchase Journey: An Omnichannel Deep-Learning Model. Information Systems Research (ISR)
Vilma Todri, Panagiotis Adamopoulos, Michelle Andrews: Is Distance Really Dead in the Online World? How Geographical Distance Moderates the Effectiveness of Electronic Word-of-Mouth. Journal of Marketing (JM)
Panagiotis Adamopoulos, Anindya Ghose, Alexander Tuzhilin: Heterogeneous Demand Effects of Recommendation Strategies in a Mobile Application: Evidence from Econometric Models and Machine-Learning Instruments. MIS Quarterly (MISQ)
Panagiotis Adamopoulos, Vilma Todri, Anindya Ghose: Demand Effects of the Internet-of-Things Sales Channel: Evidence from Automating the Purchase Process. Information Systems Research (ISR)
Craig Jabaley et al.: Chronic Atypical Antipsychotic Use Is Associated with Reduced Need for Postoperative Nausea and Vomiting Rescue in the Post-Anesthesia Care Unit: A Propensity-Matched Retrospective Observational Study. Anesthesia & Analgesia
Panagiotis Adamopoulos, Anindya Ghose, Vilma Todri: Estimating the Impact of User Personality Traits on Word-of-Mouth: Text-mining Microblogging Platforms. Information Systems Research (ISR)
Panagiotis Adamopoulos, Alexander Tuzhilin: On Unexpectedness in Recommender Systems: Or How to Better Expect the Unexpected. ACM Transactions on Intelligent Systems and Technology (ACM TIST)
[2014 Impact Factor: 9.39 - Featured Article]
Under Review
Panagiotis Adamopoulos, Vilma Todri: Joint Demand Effects of Recommendations and Advertising: Synergistic or Antagonistic Strategies?
Nasim Mousavi, Panagiotis Adamopoulos, Jesse Bockstedt: Should Online Learning Platforms Facilitate Off-Topic Discussions? Randomized Field Experiment on a Massive Open Online Course.
Nasim Mousavi, Panagiotis Adamopoulos, Jesse Bockstedt: Personalization Systems and Sponsored Content.
In Proceedings
Nasim Mousavi, Panagiotis Adamopoulos, Jesse Bockstedt: Discussion Types and User Behavior in MOOCs. In Proceedings of the 43rd International Conference on Information Systems (ICIS 2022)
Nasim Mousavi, Panagiotis Adamopoulos, Jesse Bockstedt: Personalization and the Decoy Effect. In Proceedings of the 42nd International Conference on Information Systems (ICIS 2021)
Panagiotis Adamopoulos, Anindya Ghose, Vilma Todri: Demand Effects of the Internet-of-Things Sales Channel. In Proceedings of the 39th International Conference on Information Systems (ICIS 2018)
Panagiotis Adamopoulos, Vilma Todri: The Effectiveness of Marketing Strategies in Social Media: Evidence from Promotional Events. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2015)
[INFORMS social media analytics best paper award finalist]
Panagiotis Adamopoulos, Alexander Tuzhilin: The Business Value of Recommendations: A Privacy-Preserving Econometric Analysis. International Conference on Information Systems (ICIS 2015)
Panagiotis Adamopoulos, Alexander Tuzhilin, Peter Mountanos: Measuring the Concentration Reinforcement Bias of Recommender Systems. ACM Conference on Recommender Systems (RecSys 2015)
Panagiotis Adamopoulos, Vilma Todri: Personality-Based Recommendations: Evidence from Amazon.com. ACM Conference on Recommender Systems (RecSys 2015)
Vilma Todri, Panagiotis Adamopoulos: Social Commerce: An Empirical Examination of the Antecedents and Consequences of Commerce in Social Network Platforms. International Conference on Information Systems (ICIS 2014)
Panagiotis Adamopoulos, Vilma Todri: Social Commerce Analytics: The Effectiveness of Promotional Events on Brand Fan Base in Social Media. International Conference on Information Systems (ICIS 2014)
Panagiotis Adamopoulos, Alexander Tuzhilin: On Over-Specialization and Concentration Bias of Recommendations: Probabilistic Neighborhood Selection in Collaborative Filtering Systems. ACM Conference on Recommender Systems (RecSys 2014)
[Video]
[nominated for best paper award]
Panagiotis Adamopoulos, Alexander Tuzhilin: Estimating the Value of Multi-Dimensional Data Sets in Context-based Recommender Systems. ACM Conference on Recommender Systems (RecSys 2014)
[Data]
Panagiotis Adamopoulos,
Alejandro Bellogín,
Pablo Castells,
Paolo Cremonesi, and
Harald Steck: Recommender Systems Evaluation: Dimensions and Design. ACM Conference on Recommender Systems (RecSys 2014)
Panagiotis Adamopoulos: On Discovering non-Obvious Recommendations: Using Unexpectedness and Neighborhood Selection Methods in Collaborative Filtering Systems. ACM Conference on Web Search and Data Mining (WSDM 2014): 655-660
Panagiotis Adamopoulos: Novel Perspectives in Collaborative Filtering Recommender Systems. International World Wide Web Conference (WWW 2014)
Panagiotis Adamopoulos: What Makes a Great MOOC? An Interdisciplinary Analysis of Student Retention in Online Courses. International Conference on Information Systems (ICIS 2013) [The most heavily-cited paper from the ICIS 2013 proceedings (as of September 22nd, 2015), according to Google Scholar]
Panagiotis Adamopoulos, Alexander Tuzhilin: Recommendation Opportunities: Improving Item Prediction Using Weighted Percentile Methods in Collaborative Filtering Systems. ACM Conference on Recommender Systems (RecSys 2013): 351-354
Panagiotis Adamopoulos: Beyond Rating Prediction Accuracy: On New Perspectives in Recommender Systems. ACM Conference on Recommender Systems (RecSys 2013): 459-462
Panagiotis Adamopoulos, Alexander Tuzhilin: On Unexpectedness in Recommender Systems: Or How to Expect the Unexpected. Workshop on Novelty and Diversity in Recommender Systems (DiveRS 2011), at the ACM Conference on Recommender Systems (RecSys 2011): 21-28
Doctoral Dissertation
Dissertation Committee: Gediminas Adomavicius, Daria Dzyabura, Anindya Ghose, Srikanth Jagabathula, Foster Provost, Alexander Tuzhilin (Chairperson), Akhmed Umyarov
Thesis: Unexpectedness and Non-Obviousness in Recommendation Technologies and Their Impact on Consumer Decision Making
Software and Data Sets
ConcertTweets: A Multi-Dimensional Data Set for Recommender Systems Research
