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 

Hajipour, V., Tavana, M., Di Caprio, D., Akhgar, M., &; Jabbari, Y. (2019). An optimization model for traceable closed-loop supply chain networks. Applied Mathematical Modelling, 71, 673–699.https://doi.org/10.1016/j.apm.2019.03.007 

Tavana, M., Khosrojerdi, G., Mina, H., &; Rahman, A. (2019). A hybrid mathematical programming model for optimal project portfolio selection using fuzzy inference system and analytic hierarchy process. Evaluation and Program Planning, 77, Article 101703.https://doi.org/10.1016/j.evalprogplan.2019.101703 

Rauchecker, G., &; Schryen, G. (2018). Decision Support for the Optimal Coordination of Spontaneous Volunteers in Disaster Relief. In Proceedings of the 15th International Conference on Information Systems for Crisis Response and Management. Rochester, NY, USA.

Prester, J., Wagner, G., &; Schryen, G. (2018). Classifying the Ideational Impact of IS Review Articles: A Natural Language Processing Based Approach. In Proceedings of the 2018 International Conference on Information Systems (ICIS 2018). San Francisco, CA, USA.

Schillinger, R., &; Schryen, G. (2018). Security in Highly Connected IT Systems – Results of the Bavarian Research Alliance FORSEC. University of Regensburg.https://doi.org/10.5283/epub.36264 

Weishäupl, E., Yasasin, E., &; Schryen, G. (2018). Information Security Investments: An Exploratory Multiple Case Study on Decision-Making, Evaluation and Learning. Computers &; Security, 77, 807–823.

Schuster, R., Wagner, G., &; Schryen, G. (2018). Information Systems Design Science Research and Cumulative Knowledge Development: An Exploratory Study. In Proceedings of the 2018 International Conference on Information Systems (ICIS 2018). San Francisco, CA, USA.

Hallmann, C., Burmeister, S. C., Wissing, M., &; Suhl, L. (2018). Heuristics and Simulation for Water Tank Optimization. In Communications in Computer and Information Science. Cham.https://doi.org/10.1007/978-3-319-96271-9_5 

Hallmann, C., &; Kuhlemann, S. (2018). Model Generator for Water Distribution Systems. In Operations Research Proceedings. Cham.https://doi.org/10.1007/978-3-319-89920-6_34 

Ebrahimi, B., Tavana, M., Rahmani, M., &; Santos-Arteaga, F. J. (2018). Efficiency measurement in data envelopment analysis in the presence of ordinal and interval data. Neural Computing and Applications, 30(6), 1971–1982.https://doi.org/10.1007/s00521-016-2826-2 

Banakar, Z., Tavana, M., Huff, B., &; Di Caprio, D. (2018). A bank merger predictive model using the Smoluchowski stochastic coagulation equation and reverse engineering. International Journal of Bank Marketing, 36(4), 634–662.https://doi.org/10.1108/ijbm-05-2017-0106 

Razavi Hajiagha, S. H., Amoozad Mahdiraji, H., Tavana, M., &; Hashemi, S. S. (2018). A novel common set of weights method for multi-period efficiency measurement using mean-variance criteria. Measurement, 129, 569–581.https://doi.org/10.1016/j.measurement.2018.07.061 

Mobin, M., Mousavi, S. M., Komaki, M., &; Tavana, M. (2018). A hybrid desirability function approach for tuning parameters in evolutionary optimization algorithms. Measurement, 114, 417–427.https://doi.org/10.1016/j.measurement.2017.10.009 

Shiraz, R. K., Tavana, M., &; Di Caprio, D. (2018). Chance-constrained data envelopment analysis modeling with random-rough data. RAIRO - Operations Research, 52(1), 259–284.https://doi.org/10.1051/ro/2016076 

Chión, S. J., Charles, V., &; Tavana, M. (2018). Impact of incentive schemes and personality-tradeoffs on two-agent coopetition with numerical estimations. Measurement, 125, 182–195.https://doi.org/10.1016/j.measurement.2018.03.075 

Tavana, M., Zareinejad, M., &; Santos-Arteaga, F. J. (2018). An intuitionistic fuzzy-grey superiority and inferiority ranking method for third-party reverse logistics provider selection. International Journal of Systems Science: Operations &; Logistics, 5(2), 175–194.https://doi.org/10.1080/23302674.2016.1256448 

Tavana, M., Santos-Arteaga, F. J., Mahmoodirad, A., Niroomand, S., &; Sanei, M. (2018). Multi-stage supply chain network solution methods: hybrid metaheuristics and performance measurement. International Journal of Systems Science: Operations &; Logistics, 5(4), 356–373.https://doi.org/10.1080/23302674.2017.1316877 

Tavana, M., Khalili-Damghani, K., Di Caprio, D., &; Oveisi, Z. (2018). An evolutionary computation approach to solving repairable multi-state multi-objective redundancy allocation problems. Neural Computing and Applications, 30(1), 127–139.https://doi.org/10.1007/s00521-016-2676-y 

Tavana, M., Caprio, D. D., &; Santos-Arteaga, F. J. (2018). STRATEGIC SIGNALING AND NEW TECHNOLOGICALLY SUPERIOR PRODUCT INTRODUCTION: A GAME-THEORETIC MODEL WITH SIMULATION. Technological and Economic Development of Economy, 24(4), 1466–1498.https://doi.org/10.3846/tede.2018.4531 

Izadikhah, M., Tavana, M., Di Caprio, D., &; Santos-Arteaga, F. J. (2018). A novel two-stage DEA production model with freely distributed initial inputs and shared intermediate outputs. Expert Systems with Applications, 99, 213–230.https://doi.org/10.1016/j.eswa.2017.11.005 

Esmaelian, M., Tavana, M., Santos-Arteaga, F. J., &; Vali, M. (2018). A novel genetic algorithm based method for solving continuous nonlinear optimization problems through subdividing and labeling. Measurement, 115, 27–38.https://doi.org/10.1016/j.measurement.2017.09.034 

Tavana, M., Izadikhah, M., Di Caprio, D., &; Farzipoor Saen, R. (2018). A new dynamic range directional measure for two-stage data envelopment analysis models with negative data. Computers &; Industrial Engineering, 115, 427–448.https://doi.org/10.1016/j.cie.2017.11.024 

Sodenkamp, M. A., Tavana, M., &; Di Caprio, D. (2018). An aggregation method for solving group multi-criteria decision-making problems with single-valued neutrosophic sets. Applied Soft Computing, 71, 715–727.https://doi.org/10.1016/j.asoc.2018.07.020 

Tavana, M., Abtahi, A.-R., Di Caprio, D., &; Poortarigh, M. (2018). An Artificial Neural Network and Bayesian Network model for liquidity risk assessment in banking. Neurocomputing, 275, 2525–2554.https://doi.org/10.1016/j.neucom.2017.11.034 

Tavana, M., Abtahi, A.-R., Di Caprio, D., Hashemi, R., &; Yousefi-Zenouz, R. (2018). An integrated location-inventory-routing humanitarian supply chain network with pre- and post-disaster management considerations. Socio-Economic Planning Sciences, 64, 21–37.https://doi.org/10.1016/j.seps.2017.12.004 

Tavana, M., Ebrahimnejad, A., Santos-Arteaga, F. J., Mansourzadeh, S. M., &; Matin, R. K. (2018). A hybrid DEA-MOLP model for public school assessment and closure decision in the City of Philadelphia. Socio-Economic Planning Sciences, 61, 70–89.https://doi.org/10.1016/j.seps.2016.09.003 

Tavana, M., Khalili-Damghani, K., Santos Arteaga, F. J., Mahmoudi, R., &; Hafezalkotob, A. (2018). Efficiency decomposition and measurement in two-stage fuzzy DEA models using a bargaining game approach. Computers &; Industrial Engineering, 118, 394–408.https://doi.org/10.1016/j.cie.2018.03.010 

Tavana, M., Shahdi-Pashaki, S., Teymourian, E., Santos-Arteaga, F. J., &; Komaki, M. (2018). A discrete cuckoo optimization algorithm for consolidation in cloud computing. Computers &;amp; Industrial Engineering, 115, 495–511.https://doi.org/10.1016/j.cie.2017.12.001 

Tavana, M., Santos-Arteaga, F. J., &; Di Caprio, D. (2018). The value of information as a verification and regret-preventing mechanism in algorithmic search environments. Information Sciences, 448–449, 187–214.https://doi.org/10.1016/j.ins.2018.03.032 

Tavana, M., Di Caprio, D., &; Santos-Arteaga, F. J. (2018). An extended stochastic VIKOR model with decision maker’s attitude towards risk. Information Sciences, 432, 301–318.https://doi.org/10.1016/j.ins.2017.12.019 

Aziz, H., Rauchecker, G., Schryen, G., &; Walsh, T. (2017). Algorithms for Max-Min Share Fair Allocation of Indivisible Chores. In Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17) (Vol. 31, pp. 1–7). San Francisco, CA, USA.

Wagner, G., Prester, J., &; Schryen, G. (2017). Exploring the Scientific Impact of Information Systems Design Science Research: A Scientometric Study. In 38th International Conference on Information Systems. Seoul, South Korea.

Schryen, G., &; Hristova, D. (2017). High-Performance Business Computing - Effizienzsteigerung durch Parallelisierung. Smart Data Radar (Deutsche Bank).

Schryen, G., Benlian, A., Rowe, F., Shirley, G., Larsen, K., Petter, S.,  Yasasin, E. (2017). Literature Reviews in IS Research: What Can Be Learnt from the Past and Other Fields? Communications of the AIS, 40, 557–569.

Scholz, M., Dorner, V., Schryen, G., &; Benlian, A. (2017). A configuration-based recommender system for supporting e-commerce decisions. European Journal of Operational Research, 259(1), 205–215.

Beckschäfer, M., Malberg, S., Tierney, K., &; Weskamp, C. (2017). Simulating Storage Policies for an Automated Grid-Based Warehouse System. In Lecture Notes in Computer Science. Cham.https://doi.org/10.1007/978-3-319-68496-3_31 

Tavana, M., Yazdani, M., &; Di Caprio, D. (2017). An application of an integrated ANP–QFD framework for sustainable supplier selection. International Journal of Logistics Research and Applications, 20(3), 254–275.https://doi.org/10.1080/13675567.2016.1219702 

Tavana, M., Khalili-Damghani, K., Santos-Arteaga, F. J., &; Zandi, M.-H. (2017). Drone shipping versus truck delivery in a cross-docking system with multiple fleets and products. Expert Systems with Applications, 72, 93–107.https://doi.org/10.1016/j.eswa.2016.12.014 

Tavana, M., Santos-Arteaga, F. J., &; Di Caprio, D. (2017). The effect of preference similarity on the formation of clusters and the connectivity of social networks. Computers in Human Behavior, 72, 208–221.https://doi.org/10.1016/j.chb.2017.02.049 

Tavana, M., Santos Arteaga, F. J., Mohammadi, S., &; Alimohammadi, M. (2017). A fuzzy multi-criteria spatial decision support system for solar farm location planning. Energy Strategy Reviews, 18, 93–105.https://doi.org/10.1016/j.esr.2017.09.003 

Alikar, N., Mousavi, S. M., Tavana, M., &; Niaki, S. T. A. (2017). A multi-objective multi-state series-parallel redundancy allocation model using tuned meta-heuristic algorithms. International Journal of Systems Science: Operations &; Logistics, 4(3), 275–296.https://doi.org/10.1080/23302674.2016.1193254 

Di Caprio, D., Santos-Arteaga, F. J., &; Tavana, M. (2017). The emergence of inclusive and exclusive virtual communities determined by the preferences of their users. Journal of Ambient Intelligence and Humanized Computing, 8(3), 315–328.https://doi.org/10.1007/s12652-017-0447-y 

Tavana, M., Shabanpour, H., Yousefi, S., &; Farzipoor Saen, R. (2017). A hybrid goal programming and dynamic data envelopment analysis framework for sustainable supplier evaluation. Neural Computing and Applications, 28(12), 3683–3696.https://doi.org/10.1007/s00521-016-2274-z 

Khanjani Shiraz, R., Tavana, M., Fukuyama, H., &; Di Caprio, D. (2017). Fuzzy chance-constrained geometric programming: the possibility, necessity and credibility approaches. Operational Research, 17(1), 67–97.https://doi.org/10.1007/s12351-015-0216-7 

Toloo, M., &; Tavana, M. (2017). A novel method for selecting a single efficient unit in data envelopment analysis without explicit inputs/outputs. Annals of Operations Research, 253(1), 657–681.https://doi.org/10.1007/s10479-016-2375-1 

Santos-Arteaga, F. J., Di Caprio, D., Tavana, M., &; O’Connor, A. (2017). Innovation dynamics and labor force restructuring with asymmetrically developed national innovation systems. International Business Review, 26(1), 36–56.https://doi.org/10.1016/j.ibusrev.2016.05.005 

Esmaelian, M., Tavana, M., Di Caprio, D., &; Ansari, R. (2017). A multiple correspondence analysis model for evaluating technology foresight methods. Technological Forecasting and Social Change, 125, 188–205.https://doi.org/10.1016/j.techfore.2017.07.022 

Khalili-Damghani, K., Tavana, M., Santos-Arteaga, F. J., &; Ghanbarzad-Dashti, M. (2017). A customized genetic algorithm for solving multi-period cross-dock truck scheduling problems. Measurement, 108, 101–118.https://doi.org/10.1016/j.measurement.2017.05.027