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 
LibreCat: /record/54000
DOI: 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 
LibreCat: /record/54002
DOI: 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 
LibreCat: /record/54005
DOI: 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 
LibreCat: /record/54006
DOI: 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 
LibreCat: /record/53999
DOI: 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 
LibreCat: /record/54004
DOI: 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 
LibreCat: /record/53998
DOI: 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 
LibreCat: /record/53994
DOI: 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 
LibreCat: /record/53995
DOI: 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 
LibreCat: /record/53996
DOI: 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 
LibreCat: /record/53997
DOI: 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 
LibreCat: /record/53992
DOI: 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 
LibreCat: /record/53993
DOI: 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.
LibreCat: /record/5692

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.
LibreCat: /record/5594

Schryen, G., &; Hristova, D. (2017). High-Performance Business Computing - Effizienzsteigerung durch Parallelisierung. Smart Data Radar (Deutsche Bank).
LibreCat: /record/5626

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.
LibreCat: /record/5633

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.
LibreCat: /record/5671

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 
LibreCat: /record/14857
DOI: 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 
LibreCat: /record/54029
DOI: 10.1080/13675567.2016.1219702