Enric
Junqué de Fortuny

Assistant Professor of Managerial Decision Sciences

• Ph.D. in Applied Economics, University of Antwerp
• M.Sc. in Computer Science Engineering, University of Ghent
• B.Sc. in Computer Science, University of Ghent

Enric Junqué de Fortuny is an Assistant Professor of Managerial Decision Sciences. Prior to his appointment at IESE, he was an Assistant Professor in Information Systems and Business Analytics at New York University (Shanghai), an Assistant Professor in Marketing at the Rotterdam School of Management (Netherlands) and a Senior Research Fellow at INSEAD's eLab for Big Data (France/Singapore). He holds a Ph.D. in Applied Economics from the University of Antwerp, an M.Sc. in Computer Science Engineering, and a B.Sc. in Computer Science from the University of Ghent (Belgium).

Enric's research interests lie within the realm of data science, information systems, and how to bridge insights from academia to society. Specifically, he is focused on answering descriptive, predictive, and prescriptive questions involving fine-grained human behavior. His research has been recognized with the European Research Paper of the Year 2017 award, organized by CIO-NET and the Association for Information Systems. His findings have been published in well-known journals and top conferences such as Management Information Systems Quarterly (MISQ), Journal of Consumer Research (JCR), Machine learning (ML), IEEE Transactions on Neural Networks, and the Learning Systems, and Knowledge Discovery and Data Mining (KDD).

Publications

Journal Articles (refereed)

JUNQUÉ DE FORTUNY, E., ZHANG, Y. (2023). Exploring the new frontier. Decentralized financial services. Service Science, 15 (4), 266-282. doi:10.1287/serv.2021.0048. LEE, J., JUNQUÉ DE FORTUNY, E. (2022). Influencer-generated reference groups. Journal of Consumer Research, 49 (1), 25-45. doi:10.1093/jcr/ucab056. JUNQUÉ DE FORTUNY, E., MARTENS, S., PROVOST, F. (2018). Wallenius Bayes. MACHINE LEARNING (107), 1013-1037. doi:10.1007/s10994-018-5699-z. TOBBACK, E., NAUDTS, H., DAELEMANS, W., JUNQUÉ DE FORTUNY, E., MARTENS, D. (2018). Belgian economic policy uncertainty index. Improvement through text mining. International Journal of Forecasting, 34 (2), 355-365. doi:10.1016/j.ijforecast.2016.08.006. EVGENIOU, T., JUNQUÉ DE FORTUNY, E., NASSUPHIS, N., VERMAELEN, T. (2018). Volatility and the buyback anomaly. Journal of Corporate Finance (49), 32-53. doi:10.1016/j.jcorpfin.2017.12.017. MARTENS, D., PROVOST, F., CLARK, J., JUNQUÉ DE FORTUNY, E. (2016). Mining massive fine-grained behavior data to improve predictive analytics. MIS Quarterly, 40 (4), 869-888. JUNQUÉ DE FORTUNY, E., MARTENS, D. (2015). Active learning-based pedagogical rule extraction. IEEE Transactions on Neural Networks and Learning Systems, 26 (11). doi:10.1109/TNNLS.2015.2389037. MOEYERSOMS, J., JUNQUÉ DE FORTUNY, E., DEJAEGER, K., BAESENS, B., MARTENS, D. (2015). Comprehensible software fault and effort prediction. A Data mining approach. JOURNAL OF SYSTEMS AND SOFTWARE (100), 80-90. doi:10.1016/j.jss.2014.10.032. JUNQUÉ DE FORTUNY, E., DE SMEDT, T., MARTENS, D., DAELEMANS, W. (2014). Evaluating and understanding text-based stock price prediction models. INFORMATION PROCESSING & MANAGEMENT, 50 (2), 426-441. doi:10.1016/j.ipm.2013.12.002. JUNQUÉ DE FORTUNY, E., MARTENS, D., PROVOST, F. (2013). Predictive modeling with big data. Is bigger really better? Big Data, 1 (4), 215-226. doi:10.1089/big.2013.0037.