Schryen, G. (2020). Parallel computational optimization in operations research: A new integrative framework, literature review and research directions. European Journal of Operational Research, 287(1), 1–18.

Szubartowicz, E., &; Schryen, G. (2020). Timing in Information Security: An Event Study on the Impact of Information Security Investment Announcements. Journal of Information System Security, 16(1), 3–31.

Schryen, G., Wagner, G., Benlian, A., &; Paré, G. (2020). A Knowledge Development Perspective on Literature Reviews: Validation of a New Typology in the IS Field. Communications of the AIS, 46, 134–186.https://doi.org/10.17705/1CAIS.04607 

Schryen, G., Kliewer, N., &; Fink, A. (2020). High Performance Business Computing. Business &; Information Systems Engineering, 62(1), 1–3.https://doi.org/10.1007/s12599-019-00622-2 

Yasasin, E., Prester, J., Wagner, G., &; Schryen, G. (2020). Forecasting IT Security Vulnerabilities - An Empirical Analysis. Computers &; Security, 88(January).

Hajipour, V., Tavana, M., Santos-Arteaga, F. J., Alinezhad, A., &; Di Caprio, D. (2020). An efficient controlled elitism non-dominated sorting genetic algorithm for multi-objective supplier selection under fuzziness. Journal of Computational Design and Engineering, 7(4), 469–488.https://doi.org/10.1093/jcde/qwaa039 

Aziz, A. A., Mousavi, S. M., Tavana, M., &; Niaki, S. T. A. (2020). An investigation of the robustness in the Travelling Salesman problem routes using special structured matrices. International Journal of Systems Science: Operations &; Logistics, 7(2), 172–181.https://doi.org/10.1080/23302674.2018.1551584 

Santos-Arteaga, F. J., Tavana, M., Torrecillas, C., &; Di Caprio, D. (2020). INNOVATION DYNAMICS AND FINANCIAL STABILITY: A EUROPEAN UNION PERSPECTIVE. Technological and Economic Development of Economy, 26(6), 1366–1398.https://doi.org/10.3846/tede.2020.13521 

Jafari Songhori, M., Tavana, M., &; Terano, T. (2020). Product development team formation: effects of organizational- and product-related factors. Computational and Mathematical Organization Theory, 26(1), 88–122.https://doi.org/10.1007/s10588-019-09302-8 

Kaviani, M. A., Tavana, M., Kowsari, F., &; Rezapour, R. (2020). Supply chain resilience: a benchmarking model for vulnerability and capability assessment in the automotive industry. Benchmarking: An International Journal, 27(6), 1929–1949.https://doi.org/10.1108/bij-01-2020-0049 

Tavana, M., Shaabani, A., Javier Santos-Arteaga, F., &; Raeesi Vanani, I. (2020). A Review of Uncertain Decision-Making Methods in Energy Management Using Text Mining and Data Analytics. Energies, 13(15), Article 3947.https://doi.org/10.3390/en13153947 

Tavana, M., Hajipour, V., &; Oveisi, S. (2020). IoT-based enterprise resource planning: Challenges, open issues, applications, architecture, and future research directions. Internet of Things, 11, Article 100262.https://doi.org/10.1016/j.iot.2020.100262 

Tavana, M., Amoozad Mahdiraji, H., Beheshti, M., &; Abbasi Kamardi, A. (2020). Optimal strategic alliance in multiechelon supply chains with open innovation. Managerial and Decision Economics, 41(7), 1365–1384.https://doi.org/10.1002/mde.3181 

Tavana, M., &; Hajipour, V. (2020). A practical review and taxonomy of fuzzy expert systems: methods and applications. Benchmarking: An International Journal, 27(1), 81–136.https://doi.org/10.1108/bij-04-2019-0178 

Kaviani, M. A., Tavana, M., Kumar, A., Michnik, J., Niknam, R., &; Campos, E. A. R. de. (2020). An integrated framework for evaluating the barriers to successful implementation of reverse logistics in the automotive industry. Journal of Cleaner Production, 272, Article 122714.https://doi.org/10.1016/j.jclepro.2020.122714 

Hashemi Petrudi, S. H., Tavana, M., &; Abdi, M. (2020). A comprehensive framework for analyzing challenges in humanitarian supply chain management: A case study of the Iranian Red Crescent Society. International Journal of Disaster Risk Reduction, 42, Article 101340.https://doi.org/10.1016/j.ijdrr.2019.101340 

Farughi, H., Tavana, M., Mostafayi, S., &; Santos Arteaga, F. J. (2020). A novel optimization model for designing compact, balanced, and contiguous healthcare districts. Journal of the Operational Research Society, 71(11), 1740–1759.https://doi.org/10.1080/01605682.2019.1621217 

Yazdani, M., Tavana, M., Pamudar, D., &; Chatterjee, P. (2020). A rough based multi-criteria evaluation method for healthcare waste disposal location decisions. Computers &;amp; Industrial Engineering, 143, Article 106394.https://doi.org/10.1016/j.cie.2020.106394 

Khanjani Shiraz, R., Tavana, M., &; Fukuyama, H. (2020). A random-fuzzy portfolio selection DEA model using value-at-risk and conditional value-at-risk. Soft Computing, 24(22), 17167–17186.https://doi.org/10.1007/s00500-020-05010-7 

Ebrahimi, B., Dellnitz, A., Kleine, A., &; Tavana, M. (2020). A novel method for solving data envelopment analysis problems with weak ordinal data using robust measures. Expert Systems with Applications, 164, Article 113835.https://doi.org/10.1016/j.eswa.2020.113835 

Ebrahimi, B., Tavana, M., Toloo, M., &; Charles, V. (2020). A novel mixed binary linear DEA model for ranking decision-making units with preference information. Computers &; Industrial Engineering, 149, Article 106720.https://doi.org/10.1016/j.cie.2020.106720 

Zaretalab, A., Hajipour, V., &; Tavana, M. (2020). Redundancy allocation problem with multi-state component systems and reliable supplier selection. Reliability Engineering &; System Safety, 193, Article 106629.https://doi.org/10.1016/j.ress.2019.106629 

Santos-Arteaga, F. J., Tavana, M., &; Di Caprio, D. (2020). A new model for evaluating subjective online ratings with uncertain intervals. Expert Systems with Applications, 139, Article 112850.https://doi.org/10.1016/j.eswa.2019.112850 

Vafadarnikjoo, A., Tavana, M., Botelho, T., &; Chalvatzis, K. (2020). A neutrosophic enhanced best–worst method for considering decision-makers’ confidence in the best and worst criteria. Annals of Operations Research, 289(2), 391–418.https://doi.org/10.1007/s10479-020-03603-x 

Tavana, M., Khalili-Damghani, K., Santos Arteaga, F. J., &; Hashemi, A. (2020). A Malmquist productivity index for network production systems in the energy sector. Annals of Operations Research, 284(1), 415–445.https://doi.org/10.1007/s10479-019-03173-7 

Tavana, M., Mousavi, S. M. H., Mina, H., &; Salehian, F. (2020). A dynamic decision support system for evaluating peer-to-peer rental accommodations in the sharing economy. International Journal of Hospitality Management, 91, Article 102653.https://doi.org/10.1016/j.ijhm.2020.102653 

Jafarian, A., Rabiee, M., &; Tavana, M. (2020). A novel multi-objective co-evolutionary approach for supply chain gap analysis with consideration of uncertainties. International Journal of Production Economics, 228, Article 107852.https://doi.org/10.1016/j.ijpe.2020.107852 

Tavana, M., Khosrojerdi, G., Mina, H., &; Rahman, A. (2020). A new dynamic two-stage mathematical programming model under uncertainty for project evaluation and selection. Computers &; Industrial Engineering, 149, Article 106795.https://doi.org/10.1016/j.cie.2020.106795 

Rauchecker, G., &; Schryen, G. (2019). An Exact Branch-and-Price Algorithm for Scheduling Rescue Units during Disaster Response. European Journal of Operational Research, 272(1), 352–363.

Rauchecker, G., &; Schryen, G. (2019). Using High Performance Computing for Unrelated Parallel Machine Scheduling with Sequence-Dependent Setup Times: Development and Computational Evaluation of a Parallel Branch-and-Price Algorithm. Computers &; Operations Research, (104), 338–357.

Schuhbeck, V., Siegfried, N., Dorner, V., Benlian, A., Scholz, M., &; Schryen, G. (2019). Walking the Middle Path: How Medium Trade-off Exposure Leads to Higher Consumer Satisfaction in Recommender Agents. In Proceedings of the 14. Internationale Tagung Wirtschaftsinformatik (pp. 55–64). Siegen, Germany.

Kuhlemann, S., Sellmann, M., &; Tierney, K. (2019). Exploiting Counterfactuals for Scalable Stochastic Optimization. In Lecture Notes in Computer Science. Cham.https://doi.org/10.1007/978-3-030-30048-7_40 

Schryen, G., Kliewer, N., Borndörfer, R., &; Koch, T. (2019). High-Performance Business Computing – Parallel Algorithms and Implementations for Solving Problems in Operations Research and Data Analysis. OR News, 65, 34–35.

Toloo, M., Tavana, M., &; Santos-Arteaga, F. J. (2019). An integrated data envelopment analysis and mixed integer non-linear programming model for linearizing the common set of weights. Central European Journal of Operations Research, 27(4), 887–904.https://doi.org/10.1007/s10100-017-0510-y 

Mousavi, S. M., Tavana, M., Alikar, N., &; Zandieh, M. (2019). A tuned hybrid intelligent fruit fly optimization algorithm for fuzzy rule generation and classification. Neural Computing and Applications, 31(3), 873–885.https://doi.org/10.1007/s00521-017-3115-4 

Ebrahimnejad, A., Tavana, M., Nasseri, S. H., &; Gholami, O. (2019). A New Method for Solving Dual DEA Problems with Fuzzy Stochastic Data. International Journal of Information Technology &;amp; Decision Making, 18(01), 147–170.https://doi.org/10.1142/s0219622018500396 

Tavana, M., Khalili-Damghani, K., Santos Arteaga, F. J., &; Hosseini, A. (2019). A fuzzy multi-objective multi-period network DEA model for efficiency measurement in oil refineries. Computers &; Industrial Engineering, 135, 143–155.https://doi.org/10.1016/j.cie.2019.05.033 

Di Caprio, D., Santos-Arteaga, F. J., &; Tavana, M. (2019). The role of anticipated emotions and the value of information in determining sequential search incentives. Operations Research Perspectives, 6, Article 100106.https://doi.org/10.1016/j.orp.2019.100106 

Asadi Bagloee, S., Tavana, M., Withers, G., Patriksson, M., &; Asadi, M. (2019). Tradable mobility permit with Bitcoin and Ethereum – A Blockchain application in transportation. Internet of Things, 8, Article 100103.https://doi.org/10.1016/j.iot.2019.100103 

Razavi Hajiagha, S. H., Amoozad Mahdiraji, H., &; Tavana, M. (2019). A new bi-level data envelopment analysis model for efficiency measurement and target setting. Measurement, 147, Article 106877.https://doi.org/10.1016/j.measurement.2019.106877 

Aghayi, N., Tavana, M., &; Maleki, B. (2019). A Malmquist Productivity Index with Directional Distance Function and Uncertain Data. Scientia Iranica, 0(0), 0–0.https://doi.org/10.24200/sci.2018.5259.1173 

-, S., Tavana, M., Shabani, A., &; Singh, R. (2019). The impact of interwoven integration practices on supply chain value addition and firm performance. Journal of Industrial Engineering International, 15(Suppl 1), 39–51.https://doi.org/10.1007/s40092-019-0316-8 

Mousavi, S. M., Alikar, N., Tavana, M., &; Di Caprio, D. (2019). An improved particle swarm optimization model for solving homogeneous discounted series-parallel redundancy allocation problems. Journal of Intelligent Manufacturing, 30(3), 1175–1194.https://doi.org/10.1007/s10845-017-1311-9 

Zare, H., Tavana, M., Mardani, A., Masoudian, S., &; Kamali Saraji, M. (2019). A hybrid data envelopment analysis and game theory model for performance measurement in healthcare. Health Care Management Science, 22(3), 475–488.https://doi.org/10.1007/s10729-018-9456-4 

Santos Arteaga, F. J., Tavana, M., Di Caprio, D., &; Toloo, M. (2019). A dynamic multi-stage slacks-based measure data envelopment analysis model with knowledge accumulation and technological evolution. European Journal of Operational Research, 278(2), 448–462.https://doi.org/10.1016/j.ejor.2018.09.008 

Santos-Arteaga, F. J., Torrecillas, C., &; Tavana, M. (2019). Dynamic effects of learning on the innovative outputs and productivity in Spanish multinational enterprises. The Journal of Technology Transfer, 44(1), 97–131.https://doi.org/10.1007/s10961-017-9597-5 

Talaei-Khoei, A., Tavana, M., &; Wilson, J. M. (2019). A predictive analytics framework for identifying patients at risk of developing multiple medical complications caused by chronic diseases. Artificial Intelligence in Medicine, 101, Article 101750.https://doi.org/10.1016/j.artmed.2019.101750 

Tavana, M., Khanjani Shiraz, R., &; Di Caprio, D. (2019). A chance-constrained portfolio selection model with random-rough variables. Neural Computing and Applications, 31(), 931–945.https://doi.org/10.1007/s00521-017-3014-8 

Nasiri, M. M., Ranjbar, M., Tavana, M., Santos Arteaga, F. J., &; Yazdanparast, R. (2019). A novel hybrid method for selecting soccer players during the transfer season. Expert Systems, 36(1).https://doi.org/10.1111/exsy.12342 

Aghayi, N., &; Tavana, M. (2019). A novel three-stage distance-based consensus ranking method. Journal of Industrial Engineering International, 15(1), 17–24.https://doi.org/10.1007/s40092-018-0268-4