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A stochastic bi-objective simulation–optimization model for cascade disaster location-allocation-distribution problems. <i>Annals of Operations Research</i>. 2022;309(1):103-141. doi:<a href=\"https://doi.org/10.1007/s10479-021-04191-0\">10.1007/s10479-021-04191-0</a>","mla":"Khalili-Damghani, Kaveh, et al. “A Stochastic Bi-Objective Simulation–Optimization Model for Cascade Disaster Location-Allocation-Distribution Problems.” <i>Annals of Operations Research</i>, vol. 309, no. 1, Springer Science and Business Media LLC, 2022, pp. 103–41, doi:<a href=\"https://doi.org/10.1007/s10479-021-04191-0\">10.1007/s10479-021-04191-0</a>.","chicago":"Khalili-Damghani, Kaveh, Madjid Tavana, and Peiman Ghasemi. “A Stochastic Bi-Objective Simulation–Optimization Model for Cascade Disaster Location-Allocation-Distribution Problems.” <i>Annals of Operations Research</i> 309, no. 1 (2022): 103–41. <a href=\"https://doi.org/10.1007/s10479-021-04191-0\">https://doi.org/10.1007/s10479-021-04191-0</a>.","short":"K. 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An Integrated Data Mining Framework for Organizational Resilience Assessment and Quality Management Optimization in Trauma Centers. <i>Operations Research Forum</i>. 2022;3(1). doi:<a href=\"https://doi.org/10.1007/s43069-022-00132-0\">10.1007/s43069-022-00132-0</a>"},"status":"public","user_id":"51811","volume":3,"_id":"53253","publisher":"Springer Science and Business Media LLC"},{"status":"public","volume":29,"user_id":"51811","_id":"53251","publisher":"Springer Science and Business Media LLC","page":"37291-37314","citation":{"short":"A. Afrasiabi, M. Tavana, D. Di Caprio, Environmental Science and Pollution Research 29 (2022) 37291–37314.","ama":"Afrasiabi A, Tavana M, Di Caprio D. An extended hybrid fuzzy multi-criteria decision model for sustainable and resilient supplier selection. <i>Environmental Science and Pollution Research</i>. 2022;29(25):37291-37314. doi:<a href=\"https://doi.org/10.1007/s11356-021-17851-2\">10.1007/s11356-021-17851-2</a>","chicago":"Afrasiabi, Ahmadreza, Madjid Tavana, and Debora Di Caprio. “An Extended Hybrid Fuzzy Multi-Criteria Decision Model for Sustainable and Resilient Supplier Selection.” <i>Environmental Science and Pollution Research</i> 29, no. 25 (2022): 37291–314. <a href=\"https://doi.org/10.1007/s11356-021-17851-2\">https://doi.org/10.1007/s11356-021-17851-2</a>.","bibtex":"@article{Afrasiabi_Tavana_Di Caprio_2022, title={An extended hybrid fuzzy multi-criteria decision model for sustainable and resilient supplier selection}, volume={29}, DOI={<a href=\"https://doi.org/10.1007/s11356-021-17851-2\">10.1007/s11356-021-17851-2</a>}, number={25}, journal={Environmental Science and Pollution Research}, publisher={Springer Science and Business Media LLC}, author={Afrasiabi, Ahmadreza and Tavana, Madjid and Di Caprio, Debora}, year={2022}, pages={37291–37314} }","mla":"Afrasiabi, Ahmadreza, et al. “An Extended Hybrid Fuzzy Multi-Criteria Decision Model for Sustainable and Resilient Supplier Selection.” <i>Environmental Science and Pollution Research</i>, vol. 29, no. 25, Springer Science and Business Media LLC, 2022, pp. 37291–314, doi:<a href=\"https://doi.org/10.1007/s11356-021-17851-2\">10.1007/s11356-021-17851-2</a>.","apa":"Afrasiabi, A., Tavana, M., &#38; Di Caprio, D. (2022). An extended hybrid fuzzy multi-criteria decision model for sustainable and resilient supplier selection. <i>Environmental Science and Pollution Research</i>, <i>29</i>(25), 37291–37314. <a href=\"https://doi.org/10.1007/s11356-021-17851-2\">https://doi.org/10.1007/s11356-021-17851-2</a>","ieee":"A. Afrasiabi, M. Tavana, and D. Di Caprio, “An extended hybrid fuzzy multi-criteria decision model for sustainable and resilient supplier selection,” <i>Environmental Science and Pollution Research</i>, vol. 29, no. 25, pp. 37291–37314, 2022, doi: <a href=\"https://doi.org/10.1007/s11356-021-17851-2\">10.1007/s11356-021-17851-2</a>."},"intvolume":"        29","publication_status":"published","date_updated":"2024-04-15T13:19:42Z","author":[{"last_name":"Afrasiabi","first_name":"Ahmadreza","full_name":"Afrasiabi, Ahmadreza"},{"last_name":"Tavana","first_name":"Madjid","full_name":"Tavana, Madjid","id":"31858"},{"last_name":"Di Caprio","first_name":"Debora","full_name":"Di Caprio, Debora"}],"publication_identifier":{"issn":["0944-1344","1614-7499"]},"title":"An extended hybrid fuzzy multi-criteria decision model for sustainable and resilient supplier selection","year":"2022","doi":"10.1007/s11356-021-17851-2","language":[{"iso":"eng"}],"publication":"Environmental Science and Pollution Research","issue":"25","department":[{"_id":"277"}],"type":"journal_article","date_created":"2024-04-04T15:59:43Z"},{"intvolume":"         7","publication_status":"published","date_updated":"2024-04-15T13:19:52Z","publication_identifier":{"issn":["2444-569X"]},"author":[{"first_name":"Francisco J.","last_name":"Santos-Arteaga","full_name":"Santos-Arteaga, Francisco J."},{"last_name":"Tavana","first_name":"Madjid","full_name":"Tavana, Madjid","id":"31858"},{"full_name":"Di Caprio, Debora","last_name":"Di Caprio","first_name":"Debora"}],"title":"Information acquisition and assimilation capacities as determinants of technological niche markets","year":"2022","doi":"10.1016/j.jik.2022.100193","language":[{"iso":"eng"}],"article_number":"100193","publication":"Journal of Innovation & Knowledge","issue":"3","department":[{"_id":"277"}],"type":"journal_article","date_created":"2024-04-04T16:01:04Z","status":"public","volume":7,"user_id":"51811","publisher":"Elsevier BV","_id":"53252","citation":{"apa":"Santos-Arteaga, F. J., Tavana, M., &#38; Di Caprio, D. (2022). Information acquisition and assimilation capacities as determinants of technological niche markets. <i>Journal of Innovation &#38; Knowledge</i>, <i>7</i>(3), Article 100193. <a href=\"https://doi.org/10.1016/j.jik.2022.100193\">https://doi.org/10.1016/j.jik.2022.100193</a>","ieee":"F. J. Santos-Arteaga, M. Tavana, and D. Di Caprio, “Information acquisition and assimilation capacities as determinants of technological niche markets,” <i>Journal of Innovation &#38; Knowledge</i>, vol. 7, no. 3, Art. no. 100193, 2022, doi: <a href=\"https://doi.org/10.1016/j.jik.2022.100193\">10.1016/j.jik.2022.100193</a>.","short":"F.J. Santos-Arteaga, M. Tavana, D. Di Caprio, Journal of Innovation &#38; Knowledge 7 (2022).","chicago":"Santos-Arteaga, Francisco J., Madjid Tavana, and Debora Di Caprio. “Information Acquisition and Assimilation Capacities as Determinants of Technological Niche Markets.” <i>Journal of Innovation &#38; Knowledge</i> 7, no. 3 (2022). <a href=\"https://doi.org/10.1016/j.jik.2022.100193\">https://doi.org/10.1016/j.jik.2022.100193</a>.","mla":"Santos-Arteaga, Francisco J., et al. “Information Acquisition and Assimilation Capacities as Determinants of Technological Niche Markets.” <i>Journal of Innovation &#38; Knowledge</i>, vol. 7, no. 3, 100193, Elsevier BV, 2022, doi:<a href=\"https://doi.org/10.1016/j.jik.2022.100193\">10.1016/j.jik.2022.100193</a>.","ama":"Santos-Arteaga FJ, Tavana M, Di Caprio D. Information acquisition and assimilation capacities as determinants of technological niche markets. <i>Journal of Innovation &#38; Knowledge</i>. 2022;7(3). doi:<a href=\"https://doi.org/10.1016/j.jik.2022.100193\">10.1016/j.jik.2022.100193</a>","bibtex":"@article{Santos-Arteaga_Tavana_Di Caprio_2022, title={Information acquisition and assimilation capacities as determinants of technological niche markets}, volume={7}, DOI={<a href=\"https://doi.org/10.1016/j.jik.2022.100193\">10.1016/j.jik.2022.100193</a>}, number={3100193}, journal={Journal of Innovation &#38; Knowledge}, publisher={Elsevier BV}, author={Santos-Arteaga, Francisco J. and Tavana, Madjid and Di Caprio, Debora}, year={2022} }"}},{"doi":"10.1016/j.susoc.2021.09.002","user_id":"51811","volume":3,"page":"22-32","_id":"53255","language":[{"iso":"eng"}],"publisher":"Elsevier BV","date_updated":"2024-04-15T13:21:01Z","publication_status":"published","intvolume":"         3","status":"public","year":"2022","title":"A parameter tuned hybrid algorithm for solving flow shop scheduling problems with parallel assembly stages","publication_identifier":{"issn":["2666-4127"]},"author":[{"first_name":"Mona","last_name":"Jabbari","full_name":"Jabbari, Mona"},{"id":"31858","first_name":"Madjid","last_name":"Tavana","full_name":"Tavana, Madjid"},{"first_name":"Parviz","last_name":"Fattahi","full_name":"Fattahi, Parviz"},{"full_name":"Daneshamooz, Fatemeh","last_name":"Daneshamooz","first_name":"Fatemeh"}],"type":"journal_article","department":[{"_id":"277"}],"date_created":"2024-04-04T16:03:47Z","publication":"Sustainable Operations and Computers","citation":{"chicago":"Jabbari, Mona, Madjid Tavana, Parviz Fattahi, and Fatemeh Daneshamooz. “A Parameter Tuned Hybrid Algorithm for Solving Flow Shop Scheduling Problems with Parallel Assembly Stages.” <i>Sustainable Operations and Computers</i> 3 (2022): 22–32. <a href=\"https://doi.org/10.1016/j.susoc.2021.09.002\">https://doi.org/10.1016/j.susoc.2021.09.002</a>.","short":"M. Jabbari, M. Tavana, P. Fattahi, F. Daneshamooz, Sustainable Operations and Computers 3 (2022) 22–32.","apa":"Jabbari, M., Tavana, M., Fattahi, P., &#38; Daneshamooz, F. (2022). A parameter tuned hybrid algorithm for solving flow shop scheduling problems with parallel assembly stages. <i>Sustainable Operations and Computers</i>, <i>3</i>, 22–32. <a href=\"https://doi.org/10.1016/j.susoc.2021.09.002\">https://doi.org/10.1016/j.susoc.2021.09.002</a>","ieee":"M. Jabbari, M. Tavana, P. Fattahi, and F. Daneshamooz, “A parameter tuned hybrid algorithm for solving flow shop scheduling problems with parallel assembly stages,” <i>Sustainable Operations and Computers</i>, vol. 3, pp. 22–32, 2022, doi: <a href=\"https://doi.org/10.1016/j.susoc.2021.09.002\">10.1016/j.susoc.2021.09.002</a>.","ama":"Jabbari M, Tavana M, Fattahi P, Daneshamooz F. A parameter tuned hybrid algorithm for solving flow shop scheduling problems with parallel assembly stages. <i>Sustainable Operations and Computers</i>. 2022;3:22-32. doi:<a href=\"https://doi.org/10.1016/j.susoc.2021.09.002\">10.1016/j.susoc.2021.09.002</a>","bibtex":"@article{Jabbari_Tavana_Fattahi_Daneshamooz_2022, title={A parameter tuned hybrid algorithm for solving flow shop scheduling problems with parallel assembly stages}, volume={3}, DOI={<a href=\"https://doi.org/10.1016/j.susoc.2021.09.002\">10.1016/j.susoc.2021.09.002</a>}, journal={Sustainable Operations and Computers}, publisher={Elsevier BV}, author={Jabbari, Mona and Tavana, Madjid and Fattahi, Parviz and Daneshamooz, Fatemeh}, year={2022}, pages={22–32} }","mla":"Jabbari, Mona, et al. “A Parameter Tuned Hybrid Algorithm for Solving Flow Shop Scheduling Problems with Parallel Assembly Stages.” <i>Sustainable Operations and Computers</i>, vol. 3, Elsevier BV, 2022, pp. 22–32, doi:<a href=\"https://doi.org/10.1016/j.susoc.2021.09.002\">10.1016/j.susoc.2021.09.002</a>."}},{"volume":3,"user_id":"51811","_id":"53256","publisher":"Springer Science and Business Media LLC","status":"public","citation":{"ieee":"S. E. Hashemi, M. Tavana, and M. Bakhshi, “A New Particle Swarm Optimization Algorithm for Optimizing Big Data Clustering,” <i>SN Computer Science</i>, vol. 3, no. 4, Art. no. 311, 2022, doi: <a href=\"https://doi.org/10.1007/s42979-022-01208-8\">10.1007/s42979-022-01208-8</a>.","apa":"Hashemi, S. E., Tavana, M., &#38; Bakhshi, M. (2022). A New Particle Swarm Optimization Algorithm for Optimizing Big Data Clustering. <i>SN Computer Science</i>, <i>3</i>(4), Article 311. <a href=\"https://doi.org/10.1007/s42979-022-01208-8\">https://doi.org/10.1007/s42979-022-01208-8</a>","chicago":"Hashemi, Seyed Emadedin, Madjid Tavana, and Maryam Bakhshi. “A New Particle Swarm Optimization Algorithm for Optimizing Big Data Clustering.” <i>SN Computer Science</i> 3, no. 4 (2022). <a href=\"https://doi.org/10.1007/s42979-022-01208-8\">https://doi.org/10.1007/s42979-022-01208-8</a>.","short":"S.E. Hashemi, M. Tavana, M. Bakhshi, SN Computer Science 3 (2022).","mla":"Hashemi, Seyed Emadedin, et al. “A New Particle Swarm Optimization Algorithm for Optimizing Big Data Clustering.” <i>SN Computer Science</i>, vol. 3, no. 4, 311, Springer Science and Business Media LLC, 2022, doi:<a href=\"https://doi.org/10.1007/s42979-022-01208-8\">10.1007/s42979-022-01208-8</a>.","bibtex":"@article{Hashemi_Tavana_Bakhshi_2022, title={A New Particle Swarm Optimization Algorithm for Optimizing Big Data Clustering}, volume={3}, DOI={<a href=\"https://doi.org/10.1007/s42979-022-01208-8\">10.1007/s42979-022-01208-8</a>}, number={4311}, journal={SN Computer Science}, publisher={Springer Science and Business Media LLC}, author={Hashemi, Seyed Emadedin and Tavana, Madjid and Bakhshi, Maryam}, year={2022} }","ama":"Hashemi SE, Tavana M, Bakhshi M. A New Particle Swarm Optimization Algorithm for Optimizing Big Data Clustering. <i>SN Computer Science</i>. 2022;3(4). doi:<a href=\"https://doi.org/10.1007/s42979-022-01208-8\">10.1007/s42979-022-01208-8</a>"},"doi":"10.1007/s42979-022-01208-8","language":[{"iso":"eng"}],"article_number":"311","intvolume":"         3","publication_status":"published","date_updated":"2024-04-15T13:21:12Z","author":[{"first_name":"Seyed Emadedin","last_name":"Hashemi","full_name":"Hashemi, Seyed Emadedin"},{"id":"31858","first_name":"Madjid","last_name":"Tavana","full_name":"Tavana, Madjid"},{"full_name":"Bakhshi, Maryam","last_name":"Bakhshi","first_name":"Maryam"}],"publication_identifier":{"issn":["2661-8907"]},"year":"2022","title":"A New Particle Swarm Optimization Algorithm for Optimizing Big Data Clustering","department":[{"_id":"277"}],"type":"journal_article","date_created":"2024-04-04T16:04:20Z","issue":"4","publication":"SN Computer Science"},{"type":"journal_article","department":[{"_id":"277"}],"date_created":"2024-04-04T16:02:12Z","issue":"5","publication":"Processes","doi":"10.3390/pr10050842","article_number":"842","language":[{"iso":"eng"}],"date_updated":"2024-04-15T13:20:49Z","publication_status":"published","intvolume":"        10","title":"A Review of Digital Transformation on Supply Chain Process Management Using Text Mining","year":"2022","author":[{"id":"31858","first_name":"Madjid","last_name":"Tavana","full_name":"Tavana, Madjid"},{"full_name":"Shaabani, Akram","first_name":"Akram","last_name":"Shaabani"},{"last_name":"Raeesi Vanani","first_name":"Iman","full_name":"Raeesi Vanani, Iman"},{"full_name":"Kumar Gangadhari, Rajan","last_name":"Kumar Gangadhari","first_name":"Rajan"}],"publication_identifier":{"issn":["2227-9717"]},"citation":{"mla":"Tavana, Madjid, et al. “A Review of Digital Transformation on Supply Chain Process Management Using Text Mining.” <i>Processes</i>, vol. 10, no. 5, 842, MDPI AG, 2022, doi:<a href=\"https://doi.org/10.3390/pr10050842\">10.3390/pr10050842</a>.","bibtex":"@article{Tavana_Shaabani_Raeesi Vanani_Kumar Gangadhari_2022, title={A Review of Digital Transformation on Supply Chain Process Management Using Text Mining}, volume={10}, DOI={<a href=\"https://doi.org/10.3390/pr10050842\">10.3390/pr10050842</a>}, number={5842}, journal={Processes}, publisher={MDPI AG}, author={Tavana, Madjid and Shaabani, Akram and Raeesi Vanani, Iman and Kumar Gangadhari, Rajan}, year={2022} }","ama":"Tavana M, Shaabani A, Raeesi Vanani I, Kumar Gangadhari R. A Review of Digital Transformation on Supply Chain Process Management Using Text Mining. <i>Processes</i>. 2022;10(5). doi:<a href=\"https://doi.org/10.3390/pr10050842\">10.3390/pr10050842</a>","ieee":"M. Tavana, A. Shaabani, I. Raeesi Vanani, and R. Kumar Gangadhari, “A Review of Digital Transformation on Supply Chain Process Management Using Text Mining,” <i>Processes</i>, vol. 10, no. 5, Art. no. 842, 2022, doi: <a href=\"https://doi.org/10.3390/pr10050842\">10.3390/pr10050842</a>.","apa":"Tavana, M., Shaabani, A., Raeesi Vanani, I., &#38; Kumar Gangadhari, R. (2022). A Review of Digital Transformation on Supply Chain Process Management Using Text Mining. <i>Processes</i>, <i>10</i>(5), Article 842. <a href=\"https://doi.org/10.3390/pr10050842\">https://doi.org/10.3390/pr10050842</a>","short":"M. Tavana, A. Shaabani, I. Raeesi Vanani, R. Kumar Gangadhari, Processes 10 (2022).","chicago":"Tavana, Madjid, Akram Shaabani, Iman Raeesi Vanani, and Rajan Kumar Gangadhari. “A Review of Digital Transformation on Supply Chain Process Management Using Text Mining.” <i>Processes</i> 10, no. 5 (2022). <a href=\"https://doi.org/10.3390/pr10050842\">https://doi.org/10.3390/pr10050842</a>."},"user_id":"51811","volume":10,"publisher":"MDPI AG","_id":"53254","status":"public"},{"language":[{"iso":"eng"}],"_id":"29317","doi":"10.21314/JOR.2022.044","user_id":"36049","jel":["C14","C51","C52","G17","G32"],"author":[{"last_name":"Letmathe","first_name":"Sebastian","full_name":"Letmathe, Sebastian","id":"23991"},{"full_name":"Feng, Yuanhua","last_name":"Feng","first_name":"Yuanhua","id":"20760"},{"orcid":"https://orcid.org/0000-0002-8058-8857","last_name":"Uhde","first_name":"André","full_name":"Uhde, André","id":"36049"}],"year":"2022","status":"public","title":"Semiparametric GARCH models with long memory applied to Value at Risk and Expected Shortfall","date_updated":"2024-04-17T13:34:54Z","publication_status":"inpress","date_created":"2022-01-13T11:23:02Z","department":[{"_id":"186"},{"_id":"19"}],"type":"journal_article","keyword":["Semiparametric","long memory","GARCH models","forecasting","Value at Risk","Expected Shortfall","traffic light test","Basel Committee on Banking Supervision"],"citation":{"mla":"Letmathe, Sebastian, et al. “Semiparametric GARCH Models with Long Memory Applied to Value at Risk and Expected Shortfall.” <i>Journal of Risk</i>, doi:<a href=\"https://doi.org/10.21314/JOR.2022.044\">10.21314/JOR.2022.044</a>.","ama":"Letmathe S, Feng Y, Uhde A. Semiparametric GARCH models with long memory applied to Value at Risk and Expected Shortfall. <i>Journal of Risk</i>. doi:<a href=\"https://doi.org/10.21314/JOR.2022.044\">10.21314/JOR.2022.044</a>","bibtex":"@article{Letmathe_Feng_Uhde, title={Semiparametric GARCH models with long memory applied to Value at Risk and Expected Shortfall}, DOI={<a href=\"https://doi.org/10.21314/JOR.2022.044\">10.21314/JOR.2022.044</a>}, journal={Journal of Risk}, author={Letmathe, Sebastian and Feng, Yuanhua and Uhde, André} }","apa":"Letmathe, S., Feng, Y., &#38; Uhde, A. (n.d.). Semiparametric GARCH models with long memory applied to Value at Risk and Expected Shortfall. <i>Journal of Risk</i>. <a href=\"https://doi.org/10.21314/JOR.2022.044\">https://doi.org/10.21314/JOR.2022.044</a>","ieee":"S. Letmathe, Y. Feng, and A. Uhde, “Semiparametric GARCH models with long memory applied to Value at Risk and Expected Shortfall,” <i>Journal of Risk</i>, doi: <a href=\"https://doi.org/10.21314/JOR.2022.044\">10.21314/JOR.2022.044</a>.","chicago":"Letmathe, Sebastian, Yuanhua Feng, and André Uhde. “Semiparametric GARCH Models with Long Memory Applied to Value at Risk and Expected Shortfall.” <i>Journal of Risk</i>, n.d. <a href=\"https://doi.org/10.21314/JOR.2022.044\">https://doi.org/10.21314/JOR.2022.044</a>.","short":"S. Letmathe, Y. Feng, A. Uhde, Journal of Risk (n.d.)."},"publication":"Journal of Risk","abstract":[{"lang":"eng","text":"In this paper new semiparametric GARCH models with long memory are in- troduced. The estimation of the nonparametric scale function is carried out by an adapted version of the SEMIFAR algorithm (Beran et al., 2002). Recurring on the revised recommendations by the Basel Committee to measure market risk in the banks' trading books (Basel Committee on Banking Supervision, 2013), the semi- parametric GARCH models are applied to obtain rolling one-step ahead forecasts for the Value at Risk (VaR) and Expected Shortfall (ES) for market risk assets. In addition, standard regulatory traffic light tests (Basel Committee on Banking Supervision, 1996) and a newly introduced traffic light test for the ES are carried out for all models. The practical relevance of our proposal is demonstrated by a comparative study. Our results indicate that semiparametric long memory GARCH models are an attractive alternative to their conventional, parametric counterparts."}]}]