Peer Reviewed Journal Papers
Yahav Inbal, Goldstein Anat, Geva Tomer, Shahar Meir, and Onn Shehori (2025). Quality Control for Crowd Workers and for Language Models: A Framework for Free-Text Response Evaluation with No Ground Truth, Information Systems Research. Forthcoming.
Ron, Yonina, Ron Tchelet, Fridman Naomi, and Goldstein Anat (2025). Predicting Onset of Myopic Refractive Error in Children Using Machine Learning on Routine Pediatric Eye Examinations Only. Nature Scientific Reports. Forthcoming
Geva H., Barzilay O., Oestreicher-Singer G., Goldstein A. (2024). Equal Opportunity for All? The Long Tail of Crowdfunding: Evidence from Kickstarter. MIS Quarterly (48: 3) pp.1223-1238.
Goldstein A., Hajaj. (2023) Measuring Flight-Destination Similarity: A Multidimensional Approach. Expert Systems with Applications. Volume 238, Part A, 15 March 2024, 121802. https://doi.org/10.1016/j.eswa.2023.121802.
Raphaeli, O.; Statlender, L.; Hajaj, C.; Bendavid, I.; Goldstein, A.; Robinson, E.; Singer, P. (2023). Using Machine-Learning to Assess the Prognostic Value of Early Enteral Feeding Intolerance in Critically Ill Patients: A Retrospective Study. Nutrients 2023, 15, 2705. https://doi.org/10.3390/nu15122705
Goldstein A. and Cohen S. (2023), “Self-Report Symptom-Based Endometriosis Prediction using Machine Learning”, in Nature Scientific Reports 13, 5499, https://doi.org/10.1038/s41598-023-32761-8
Goldstein A., Barzilay O., Oestreicher-Singer G. (2022). Are We There Yet? Analyzing Progress in the Conversion Funnel Using the Diversity of Searched Products. MISQ (Forthcoming, December 2022). https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2962960
Goldstein A., Fink L. and Ravid G. (2022), "A Cloud-Based Framework for Agricultural Data Integration: A Top-Down-Bottom-Up Approach," in IEEE Access, vol. 10, pp. 88527-88537, https://doi.org/10.1109/ACCESS.2022.3198099
Goldstein A., Hajaj C. (2022). The Hidden Conversion Funnel of Mobile and Desktop Consumers. Electronic Commerce Research and Applications. Volume 53, May–June 2022, 101135. DOI: https://doi.org/10.1016/j.elerap.2022.101135
Goldstein A., Fink O., Ravid G. (2021) A Framework for Evaluating Agricultural Ontologies. Sustainability 13 (11).
Goldstein A., Fink O., Raphaeli O., Hetzroni A., Ravid G. (2020). Addressing the "Tower of Babel" of Pesticide Regulations: An Ontology for Supporting Pest-control Decisions, The Journal of Agricultural Science.
Goldstein A., Johandeiter T., & Frank U. (2018). Business Process Runtime Models: Towards Bridging the Gap between Design, Enactment, and Evaluation of Business Processes. Inf Syst E-Bus Manage. https://doi.org/10.1007/s10257-018-0374-2
Goldstein A., Fink L, Meitin A., Bohadana S., Lutenberg O., & Ravid R. (2018). Applying Machine Learning on Sensor Data for Irrigation Recommendations: Revealing the Agronomist’s Tacit Knowledge. Precision Agriculture, Volume 19, Issue 3. pp.421-444. Available at: https://link.springer.com/article/10.1007/s11119-017-9527-4
Raphaeli O., Goldstein A., & Fink L. (2017). Analyzing Online Consumer Behavior in Mobile and PC Devices: A Novel Web Usage Mining Approach. Electronic Commerce Research and Applications. Electronic Commerce Research and Applications, Volume 26. DOI: 10.1016/j.elerap.2017.09.003 Available at: http://www.sciencedirect.com/science/article/pii/S1567422317300637
Goldstein A. & Ulrich F. (2016): Components of a multi-perspective modeling method for designing and managing IT security systems. Information Systems and e-Business Management. DOI: 10.1007/s10257-015-0276-5. Available at: http://link.springer.com/article/10.1007%2Fs10257-015-0276-5#page-2
Goldstein & G. Ariav (2012): Configuring Systems of Massively Distributed Autonomous and Interdependent Decision Makers. International Journal of Decision Support System Technology, 4(2), 17-41, April-June 2012.
Papers in Refereed Conferences
Goldstein, Anat; Alony, Amit; and Hajaj, Chen, "Warm Recommendation: Enhancing Cold Start Recommendations Using Multimodal Product Representations" (2024). ICIS 2024 Proceedings. 9. https://aisel.aisnet.org/icis2024/digital_comm/digital_comm/9
Goldstein, Anat and Hajaj, Chen, "Warming Up the Cold Start: A Multimodal Approach" (2023). Proceedings of the 2023 Pre-ICIS SIGDSA Symposium. 4. https://aisel.aisnet.org/sigdsa2023/4
Geva T., Goldstein A, Yahav I. (2023. Evaluating Language Models and Humans: A Framework for Free-Text Response Evaluation with No Ground Truth, CIST 2023
Geva T., Goldstein A., Yahav I. (2022) "A Framework for Automated Worker Evaluation Based on Free-Text Responses with No Ground Truth”, WITS 2022, Copenhagen, Denmark
Goldstein A. and Hajaj C. (2022), “Measuring Product Similarity: A Multidimensional Approach”, SCECR 2022 – The Eighteen Symposium on Statistical Challenges in Electronic Commerce Research, Madrid, Spain
Raphaeli O., Hajaj, C., Bendavid, I., Goldstein, A., Chen, E., Singer, P. (2021) Using machine learning to support early prediction of feeding intolerance in critically ill patients. In ESICM LIVES 2021, Digital, Oct. 2021.
Raphaeli O., Hajaj, C., Bendavid, I., Goldstein, A., Chen, E., Singer, P. (2021) Using machine learning to compare gastric residual volume thresholds as predictors of clinical outcomes in critically ill patients. In ISICEM, Brussels, Belgium, Sep. 2021.
Raphaeli O., Hajaj, C., Bendavid, I., Goldstein, A., Chen, E., Singer, P. (2021) Feeding intolerance as a predictor of clinical outcomes in critically ill patients: a machine learning approach. In ESPEN 2021, Digital, Oct. 2021.
Raphaeli O., Hajaj, C., Bendavid, I., Goldstein, A., Chen, E., Singer, P. (2021) Feeding intolerance as a predictor of clinical outcomes in critically ill patients: a machine learning approach. In ICMI 2021, Ariel (Digital), Oct. 2021.
Goldstein A., Hajaj C. (2020). The Different Path to Purchase of Mobile and Desktop Consumers: Analyzing Consumers’ Progress in the Conversion Funnel Using Hidden Markov Models. SCECR’2020, Madrid, Spain.
Barzilay O., Geva H., Goldstein A., Oestreicher-Singer G. (2018). Open to Everyone? The Long Tail of the Peer Economy: Evidence from Kickstarter. The International Conference on Information Systems (ICIS’18). San Francisco, CA, USA. [acceptance rate 25%], Nominated for ICIS’18 best paper award.
Barzilay O., Geva H., Goldstein A., Oestreicher-Singer G. (2018). Equal Opportunity for All? The Long Tail of Crowdfunding: Evidence from Kickstarter. Conference on Information Systems and Technology (CIST’18), Phoenix, Arizona, USA. [acceptance rate less than 20%]
Goldstein A. Barzilay O., Oestreicher-Singer G. (2017) Are We There Yet? Estimating Time-to-Conversion Using Search Diversity. The Workshop on Information Systems and Economics (WISE’17), Seoul, Korea. [acceptance rate less than 20%]
Goldstein A. Barzilay O., Oestreicher-Singer G. (2017) Deep into the funnel? Predicting Online Conversion Using Search Diversity. Conference on Information Systems and Technology (CIST’17), Houston, Texas, USA. [acceptance rate less than 20%]
Ravid G., Goldstein A., Raphaeli O., Fink L., Hetzroni A. (2017) Integrated information system for pest monitoring and control: A cloud-based approach. EFITA 2017, Montpellier, France.
Goldstein A., Raphaeli O., Reichman S. (2016). Engagement, Search Goals and Conversion - The Different M-Commerce Path to Conversion. The International Conference on Information Systems (ICIS’16)
Goldstein A., Meitin M., Bohadana S., Fink L., and Ravid G. (2016). Internet of Things in Agriculture: An Engine for Increasing Farm Productivity and Efficiency. The Israeli Conference on Robotics.
Anat Goldstein, Chen Karmona, Adi Shemesh, Anna Chernov, Lior Fink, Gilad Ravid, Orit Raphaeli and Amots Hetzroni (2015): A Cloud-based Service for Analyzing Red Palm Weevil Spread. ICCESEN’2015, Antalya, Turkey
Raphaeli O., Fink L., Berman S. and Goldstein A. (2014): M-Commerce vs. E-Commerce: Exploring Web Session Browsing Behavior. ECIS 2014. Available at: http://ecis2014.eu/E-poster/files/0729-file1.pdf
Goldstein A. & Overbeek S. (2013): Enterprise Models as Drivers for IT Security Management at Runtime. In Proceedings of AMINO'13 workshop at MODELS 2013. Available at: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.403.3238
Johanndeiter T., Goldstein A. & Frank U. (2013): Towards Business Process Models at Runtime. In Proceedings of The 8th Workshop on Models@run.time (MRT'13) at MODELS 2013 workshops Available at: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.403.700
Goldstein A. & Frank U. (2012) Augmented Enterprise Models as a Foundation for Generating Security-Related Software: Requirements and Prospects. Proceedings of Model Driven Security, the MODELS’12 workshops, Innsbruck, Austria. Available at: http://mdsec2012.pst.ifi.lmu.de/accepted_papers/mdsec2012_submission_12.pdf [Acceptance rate 33%]
Goldstein A. & Frank U. (2012) A method for Multi-Perspective Modelling of IT Security: Objectives and Analysis of Requirements. M. La Rosa and P. Soffer (Eds.): BPM 2012 Workshops, LNBIP 132, pp. 636–648, 2012. Available at: http://www.inf.unibz.it/sbp12/papers/P1-Goldstein.pdf [Acceptance rate 25%]
Goldstein & G. Ariav (2010): Modeling Interdependence of Users in Massively Distributed Decision Support Systems: Are We Pushing the Limits of PEPA-based Modeling? Proceedings of the 9th Workshop on Process Algebra and Stochastically Timed Activities, PASTA/Bio-PASTA 2010, Imperial College London, pp.12-17.
Goldstein (2010): Supporting Massively Distributed Decisions: Assessing the Performance of Massively Distributed Decision Support Systems. Proceedings of the Fifth Mediterranean Conference on Information Systems: Professional Development Consortium, Sprouts: Working Papers on Information Systems, 10(35), pp.29-37.
Ron, Yonina and Ron, Tchelet and Fridman, Naomi and Goldstein, Anat, Predicting Myopia in Children Through the Application of Machine Learning on Routine Pediatric Eye Examinations Only (July 01, 2024). Available at http://dx.doi.org/10.2139/ssrn.5016052