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Amiri, A., Tavana, M., &; Arman, H. (2024). An Integrated Fuzzy Analytic Network Process and Fuzzy Regression Method for Bitcoin Price Prediction. Internet of Things, 25, Article 101027.https://doi.org/10.1016/j.iot.2023.101027 
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Habernal, I., Faber, D., Recchia, N., Bretthauer, S., Gurevych, I., Spiecker genannt Döhmann, I., &; Burchard, C. (2023). Mining legal arguments in court decisions. Artificial Intelligence and Law.https://doi.org/10.1007/s10506-023-09361-y 
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Fumagalli, F., Muschalik, M., Hüllermeier, E., &; Hammer, B. (2023). Incremental permutation feature importance (iPFI): towards online explanations on data streams. Machine Learning.https://doi.org/10.1007/s10994-023-06385-y 
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Artelt, A., Visser, R., &; Hammer, B. (2023). “I do not know! but why?”https://doi.org/10.1016/j.neucom.2023.126722__— Local model-agnostic example-based explanations of reject. Neurocomputing, 558, Article 126722.https://doi.org/10.1016/j.neucom.2023.126722 
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Hoppe, J. A., Tuisku, O., Johansson-Pajala, R.-M., Pekkarinen, S., Hennala, L., Gustafsson, C., Melkas, H., &; Thommes, K. (2023). When do individuals choose care robots over a human caregiver? Insights from a laboratory experiment on choices under uncertainty. Computers in Human Behavior Reports, 9, Article 100258.https://doi.org/10.1016/j.chbr.2022.100258 
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Groß, A., Schütze, C., Brandt, M., Wrede, B., &; Richter, B. (2023). RISE: an open-source architecture for interdisciplinary and reproducible human–robot interaction research. Frontiers in Robotics and AI, 10.https://doi.org/10.3389/frobt.2023.1245501 
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Leffrang, D. (2023). AI Washing: The Framing Effect of Labels on Algorithmic Advice Utilization. International Conference on Information Systems, 10.
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Fumagalli, F., Muschalik, M., Hüllermeier, E., &; Hammer, B. (2023). Incremental permutation feature importance (iPFI): towards online explanations on data streams. Machine Learning, 112(12), 4863–4903.https://doi.org/10.1007/s10994-023-06385-y 
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Vieluf, S., Hasija, T., Kuschel, M., Reinsberger, C., &; Loddenkemper, T. (2023). Developing a deep canonical correlation-based technique for seizure prediction. Expert Systems with Applications, 234, Article 120986.https://doi.org/10.1016/j.eswa.2023.120986 
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Tavana, M., Khalili Nasr, A., Ahmadabadi, A. B., Amiri, A. S., &; Mina, H. (2023). An interval multi-criteria decision-making model for evaluating blockchain-IoT technology in supply chain networks. Internet of Things, 22, Article 100786.https://doi.org/10.1016/j.iot.2023.100786 
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Tavana, M., Soltanifar, M., Santos-Arteaga, F. J., &; Sharafi, H. (2023). Analytic hierarchy process and data envelopment analysis: A match made in heaven. Expert Systems with Applications, 223, Article 119902.https://doi.org/10.1016/j.eswa.2023.119902 
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Santos-Arteaga, F. J., Di Caprio, D., Tavana, M., &; Tena, E. C. (2023). A Credibility and Strategic Behavior Approach in Hesitant Multiple Criteria Decision-Making With Application to Sustainable Transportation. IEEE Transactions on Fuzzy Systems, 31(2), 460–474.https://doi.org/10.1109/tfuzz.2022.3188875 
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Tirkolaee, E. B., Torkayesh, A. E., Tavana, M., Goli, A., Simic, V., &; Ding, W. (2023). An integrated decision support framework for resilient vaccine supply chain network design. Engineering Applications of Artificial Intelligence, 126, Article 106945.https://doi.org/10.1016/j.engappai.2023.106945 
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Mahdiraji, H. A., Tavana, M., &; Rezayar, A. (2023). A Game-Theoretic Framework for Analyzing the Impact of Social Responsibility and Supply Chain Profitability. Cybernetics and Systems, 54(1), 104–137.https://doi.org/10.1080/01969722.2022.2055402 
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Kucklick, J.-P. (2022). Visual Interpretability of Image-based Real Estate Appraisal. 55th Annual Hawaii International Conference on System Sciences (HICSS-55). Hawaii International Conference on System Science (HICSS), Virtual.
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Kucklick, J.-P. (2022). Towards a model- and data-focused taxonomy of XAI systems. Wirtschaftsinformatik 2022 Proceedings. Wirtschaftsinformatik 2022 (W), Nürnberg (online).
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Meyer, M., Fichtler, T., Koldewey, C., &; Dumitrescu, R. (2022). Potentials and challenges of analyzing use phase data in product planning of manufacturing companies. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 36, Article e14.https://doi.org/10.1017/s0890060421000408 
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Hoffmann, C., &; Thommes, K. (2022). Seizing the Opportunity for Automation—How Traffic Density Determines Truck Drivers’ Use of Cruise Control. IEEE Transactions on Human-Machine Systems, 1–11.https://doi.org/10.1109/thms.2022.3212335 
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Rohlfing, K., Altvater-Mackensen, N., Caruana, N., van den Berghe, R., Bruno, B., Tolksdorf, N. F., &; Hanulíková, A. (2022). Social/dialogical roles of social robots in supporting children’s learning of language and literacy—A review and analysis of innovative roles. Frontiers in Robotics and AI, 9.https://doi.org/10.3389/frobt.2022.971749 
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