C. Hallmann and S. Kuhlemann, “Model Generator for Water Distribution Systems,” in Operations Research Proceedings, Cham, 2018.

B. Ebrahimi, M. Tavana, M. Rahmani, and F. J. Santos-Arteaga, “Efficiency measurement in data envelopment analysis in the presence of ordinal and interval data,”10.1007/s00521-016-2826-2__Neural Computing and Applications, vol. 30, no. 6, pp. 1971–1982, 2018, doi:10.1007/s00521-016-2826-2 .

Z. Banakar, M. Tavana, B. Huff, and D. Di Caprio, “A bank merger predictive model using the Smoluchowski stochastic coagulation equation and reverse engineering,”10.1108/ijbm-05-2017-0106__International Journal of Bank Marketing, vol. 36, no. 4, pp. 634–662, 2018, doi:10.1108/ijbm-05-2017-0106 .

S. H. Razavi Hajiagha, H. Amoozad Mahdiraji, M. Tavana, and S. S. Hashemi, “A novel common set of weights method for multi-period efficiency measurement using mean-variance criteria,”10.1016/j.measurement.2018.07.061__Measurement, vol. 129, pp. 569–581, 2018, doi:10.1016/j.measurement.2018.07.061 .

M. Mobin, S. M. Mousavi, M. Komaki, and M. Tavana, “A hybrid desirability function approach for tuning parameters in evolutionary optimization algorithms,”10.1016/j.measurement.2017.10.009__Measurement, vol. 114, pp. 417–427, 2018, doi:10.1016/j.measurement.2017.10.009 .

R. K. Shiraz, M. Tavana, and D. Di Caprio, “Chance-constrained data envelopment analysis modeling with random-rough data,”10.1051/ro/2016076__RAIRO - Operations Research, vol. 52, no. 1, pp. 259–284, 2018, doi:10.1051/ro/2016076 .

S. J. Chión, V. Charles, and M. Tavana, “Impact of incentive schemes and personality-tradeoffs on two-agent coopetition with numerical estimations,”10.1016/j.measurement.2018.03.075__Measurement, vol. 125, pp. 182–195, 2018, doi:10.1016/j.measurement.2018.03.075 .

M. Tavana, M. Zareinejad, and F. J. Santos-Arteaga, “An intuitionistic fuzzy-grey superiority and inferiority ranking method for third-party reverse logistics provider selection,”10.1080/23302674.2016.1256448__International Journal of Systems Science: Operations &; Logistics, vol. 5, no. 2, pp. 175–194, 2018, doi:10.1080/23302674.2016.1256448 .

M. Tavana, F. J. Santos-Arteaga, A. Mahmoodirad, S. Niroomand, and M. Sanei, “Multi-stage supply chain network solution methods: hybrid metaheuristics and performance measurement,”10.1080/23302674.2017.1316877__International Journal of Systems Science: Operations &; Logistics, vol. 5, no. 4, pp. 356–373, 2018, doi:10.1080/23302674.2017.1316877 .

M. Tavana, K. Khalili-Damghani, D. Di Caprio, and Z. Oveisi, “An evolutionary computation approach to solving repairable multi-state multi-objective redundancy allocation problems,”10.1007/s00521-016-2676-y__Neural Computing and Applications, vol. 30, no. 1, pp. 127–139, 2018, doi:10.1007/s00521-016-2676-y .

M. Tavana, D. D. Caprio, and F. J. Santos-Arteaga, “STRATEGIC SIGNALING AND NEW TECHNOLOGICALLY SUPERIOR PRODUCT INTRODUCTION: A GAME-THEORETIC MODEL WITH SIMULATION,”10.3846/tede.2018.4531__Technological and Economic Development of Economy, vol. 24, no. 4, pp. 1466–1498, 2018, doi:10.3846/tede.2018.4531 .

M. Izadikhah, M. Tavana, D. Di Caprio, and F. J. Santos-Arteaga, “A novel two-stage DEA production model with freely distributed initial inputs and shared intermediate outputs,”10.1016/j.eswa.2017.11.005__Expert Systems with Applications, vol. 99, pp. 213–230, 2018, doi:10.1016/j.eswa.2017.11.005 .

M. Esmaelian, M. Tavana, F. J. Santos-Arteaga, and M. Vali, “A novel genetic algorithm based method for solving continuous nonlinear optimization problems through subdividing and labeling,”10.1016/j.measurement.2017.09.034__Measurement, vol. 115, pp. 27–38, 2018, doi:10.1016/j.measurement.2017.09.034 .

M. Tavana, M. Izadikhah, D. Di Caprio, and R. Farzipoor Saen, “A new dynamic range directional measure for two-stage data envelopment analysis models with negative data,”10.1016/j.cie.2017.11.024__Computers &; Industrial Engineering, vol. 115, pp. 427–448, 2018, doi:10.1016/j.cie.2017.11.024 .

M. A. Sodenkamp, M. Tavana, and D. Di Caprio, “An aggregation method for solving group multi-criteria decision-making problems with single-valued neutrosophic sets,”10.1016/j.asoc.2018.07.020__Applied Soft Computing, vol. 71, pp. 715–727, 2018, doi:10.1016/j.asoc.2018.07.020 .

M. Tavana, A.-R. Abtahi, D. Di Caprio, and M. Poortarigh, “An Artificial Neural Network and Bayesian Network model for liquidity risk assessment in banking,”10.1016/j.neucom.2017.11.034__Neurocomputing, vol. 275, pp. 2525–2554, 2018, doi:10.1016/j.neucom.2017.11.034 .

M. Tavana, A.-R. Abtahi, D. Di Caprio, R. Hashemi, and R. Yousefi-Zenouz, “An integrated location-inventory-routing humanitarian supply chain network with pre- and post-disaster management considerations,”10.1016/j.seps.2017.12.004__Socio-Economic Planning Sciences, vol. 64, pp. 21–37, 2018, doi:10.1016/j.seps.2017.12.004 .

M. Tavana, A. Ebrahimnejad, F. J. Santos-Arteaga, S. M. Mansourzadeh, and R. K. Matin, “A hybrid DEA-MOLP model for public school assessment and closure decision in the City of Philadelphia,”10.1016/j.seps.2016.09.003__Socio-Economic Planning Sciences, vol. 61, pp. 70–89, 2018, doi:10.1016/j.seps.2016.09.003 .

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

M. Tavana, S. Shahdi-Pashaki, E. Teymourian, F. J. Santos-Arteaga, and M. Komaki, “A discrete cuckoo optimization algorithm for consolidation in cloud computing,”10.1016/j.cie.2017.12.001__Computers &;amp; Industrial Engineering, vol. 115, pp. 495–511, 2018, doi:10.1016/j.cie.2017.12.001 .

M. Tavana, F. J. Santos-Arteaga, and D. Di Caprio, “The value of information as a verification and regret-preventing mechanism in algorithmic search environments,”10.1016/j.ins.2018.03.032__Information Sciences, vol. 448–449, pp. 187–214, 2018, doi:10.1016/j.ins.2018.03.032 .

M. Tavana, D. Di Caprio, and F. J. Santos-Arteaga, “An extended stochastic VIKOR model with decision maker’s attitude towards risk,”10.1016/j.ins.2017.12.019__Information Sciences, vol. 432, pp. 301–318, 2018, doi:10.1016/j.ins.2017.12.019 .

H. Aziz, G. Rauchecker, G. Schryen, and T. Walsh, “Algorithms for Max-Min Share Fair Allocation of Indivisible Chores,” in Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), San Francisco, CA, USA, 2017, vol. 31, no. 1, pp. 1–7.

G. Wagner, J. Prester, and G. Schryen, “Exploring the Scientific Impact of Information Systems Design Science Research: A Scientometric Study,” in 38th International Conference on Information Systems, Seoul, South Korea, 2017.

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

G. Schryen et al., “Literature Reviews in IS Research: What Can Be Learnt from the Past and Other Fields?,” Communications of the AIS, vol. 40, pp. 557–569, 2017.

M. Scholz, V. Dorner, G. Schryen, and A. Benlian, “A configuration-based recommender system for supporting e-commerce decisions,” European Journal of Operational Research, vol. 259, no. 1, pp. 205–215, 2017.

M. Beckschäfer, S. Malberg, K. Tierney, and C. Weskamp, “Simulating Storage Policies for an Automated Grid-Based Warehouse System,” in Lecture Notes in Computer Science, Cham, 2017.

M. Tavana, M. Yazdani, and D. Di Caprio, “An application of an integrated ANP–QFD framework for sustainable supplier selection,”10.1080/13675567.2016.1219702__International Journal of Logistics Research and Applications, vol. 20, no. 3, pp. 254–275, 2017, doi:10.1080/13675567.2016.1219702 .

M. Tavana, K. Khalili-Damghani, F. J. Santos-Arteaga, and M.-H. Zandi, “Drone shipping versus truck delivery in a cross-docking system with multiple fleets and products,”10.1016/j.eswa.2016.12.014__Expert Systems with Applications, vol. 72, pp. 93–107, 2017, doi:10.1016/j.eswa.2016.12.014 .

M. Tavana, F. J. Santos-Arteaga, and D. Di Caprio, “The effect of preference similarity on the formation of clusters and the connectivity of social networks,”10.1016/j.chb.2017.02.049__Computers in Human Behavior, vol. 72, pp. 208–221, 2017, doi:10.1016/j.chb.2017.02.049 .

M. Tavana, F. J. Santos Arteaga, S. Mohammadi, and M. Alimohammadi, “A fuzzy multi-criteria spatial decision support system for solar farm location planning,”10.1016/j.esr.2017.09.003__Energy Strategy Reviews, vol. 18, pp. 93–105, 2017, doi:10.1016/j.esr.2017.09.003 .

N. Alikar, S. M. Mousavi, M. Tavana, and S. T. A. Niaki, “A multi-objective multi-state series-parallel redundancy allocation model using tuned meta-heuristic algorithms,”10.1080/23302674.2016.1193254__International Journal of Systems Science: Operations &; Logistics, vol. 4, no. 3, pp. 275–296, 2017, doi:10.1080/23302674.2016.1193254 .

D. Di Caprio, F. J. Santos-Arteaga, and M. Tavana, “The emergence of inclusive and exclusive virtual communities determined by the preferences of their users,”10.1007/s12652-017-0447-y__Journal of Ambient Intelligence and Humanized Computing, vol. 8, no. 3, pp. 315–328, 2017, doi:10.1007/s12652-017-0447-y .

M. Tavana, H. Shabanpour, S. Yousefi, and R. Farzipoor Saen, “A hybrid goal programming and dynamic data envelopment analysis framework for sustainable supplier evaluation,”10.1007/s00521-016-2274-z__Neural Computing and Applications, vol. 28, no. 12, pp. 3683–3696, 2017, doi:10.1007/s00521-016-2274-z .

R. Khanjani Shiraz, M. Tavana, H. Fukuyama, and D. Di Caprio, “Fuzzy chance-constrained geometric programming: the possibility, necessity and credibility approaches,”10.1007/s12351-015-0216-7__Operational Research, vol. 17, no. 1, pp. 67–97, 2017, doi:10.1007/s12351-015-0216-7 .

M. Toloo and M. Tavana, “A novel method for selecting a single efficient unit in data envelopment analysis without explicit inputs/outputs,”10.1007/s10479-016-2375-1__Annals of Operations Research, vol. 253, no. 1, pp. 657–681, 2017, doi:10.1007/s10479-016-2375-1 .

F. J. Santos-Arteaga, D. Di Caprio, M. Tavana, and A. O’Connor, “Innovation dynamics and labor force restructuring with asymmetrically developed national innovation systems,”10.1016/j.ibusrev.2016.05.005__International Business Review, vol. 26, no. 1, pp. 36–56, 2017, doi:10.1016/j.ibusrev.2016.05.005 .

M. Esmaelian, M. Tavana, D. Di Caprio, and R. Ansari, “A multiple correspondence analysis model for evaluating technology foresight methods,”10.1016/j.techfore.2017.07.022__Technological Forecasting and Social Change, vol. 125, pp. 188–205, 2017, doi:10.1016/j.techfore.2017.07.022 .

K. Khalili-Damghani, M. Tavana, F. J. Santos-Arteaga, and M. Ghanbarzad-Dashti, “A customized genetic algorithm for solving multi-period cross-dock truck scheduling problems,”10.1016/j.measurement.2017.05.027__Measurement, vol. 108, pp. 101–118, 2017, doi:10.1016/j.measurement.2017.05.027 .

A. Hatami-Marbini, P. J. Agrell, M. Tavana, and P. Khoshnevis, “A flexible cross-efficiency fuzzy data envelopment analysis model for sustainable sourcing,”10.1016/j.jclepro.2016.10.192__Journal of Cleaner Production, vol. 142, pp. 2761–2779, 2017, doi:10.1016/j.jclepro.2016.10.192 .

F. J. SANTOS-ARTEAGA, D. D. CAPRIO, M. Tavana, and A. O’CONNOR, “FORMALISING THE DEMAND FOR TECHNOLOGICAL INNOVATIONS: RATIONAL HERDS, MARKET FRICTIONS AND NETWORK EFFECTS,”10.1142/s1363919617500189__International Journal of Innovation Management, vol. 21, no. 02, Art. no. 1750018, 2017, doi:10.1142/s1363919617500189 .

D. Di Caprio, F. J. Santos-Arteaga, and M. Tavana, “A Novel Decision Support Framework for Computing Expected Utilities from Linguistic Evaluations,”10.1142/s0218488517500441__International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol. 25, no. 06, pp. 1005–1018, 2017, doi:10.1142/s0218488517500441 .

N. Alikar, S. M. Mousavi, R. A. R. Ghazilla, M. Tavana, and E. U. Olugu, “A bi-objective multi-period series-parallel inventory-redundancy allocation problem with time value of money and inflation considerations,”10.1016/j.cie.2016.12.006__Computers &; Industrial Engineering, vol. 104, pp. 51–67, 2017, doi:10.1016/j.cie.2016.12.006 .

N. Alikar, S. M. Mousavi, R. A. Raja Ghazilla, M. Tavana, and E. U. Olugu, “Application of the NSGA-II algorithm to a multi-period inventory-redundancy allocation problem in a series-parallel system,”10.1016/j.ress.2016.10.023__Reliability Engineering &; System Safety, vol. 160, pp. 1–10, 2017, doi:10.1016/j.ress.2016.10.023 .

R. Khanjani Shiraz, V. Charles, M. Tavana, and D. Di Caprio, “A redundancy detection algorithm for fuzzy stochastic multi-objective linear fractional programming problems,”10.1080/07362994.2016.1248780__Stochastic Analysis and Applications, vol. 35, no. 1, pp. 40–62, 2017, doi:10.1080/07362994.2016.1248780 .

S. A. Bagloee, M. Tavana, D. Di Caprio, M. Asadi, and M. Heshmati, “A multi-user decision support system for online city bus tour planning,”10.1007/s40534-017-0126-x__Journal of Modern Transportation, vol. 25, no. 2, pp. 59–73, 2017, doi:10.1007/s40534-017-0126-x .

S. Asadi Bagloee, M. Heshmati, M. Tavana, and D. Di Caprio, “A logit-based model for measuring the effects of transportation infrastructure on land value,”10.1080/03081060.2016.1266164__Transportation Planning and Technology, vol. 40, no. 2, pp. 143–166, 2017, doi:10.1080/03081060.2016.1266164 .

A. Mardani, M. Nilashi, J. Antucheviciene, M. Tavana, R. Bausys, and O. Ibrahim, “Recent Fuzzy Generalisations of Rough Sets Theory: A Systematic Review and Methodological Critique of the Literature,”10.1155/2017/1608147__Complexity, vol. 2017, pp. 1–33, 2017, doi:10.1155/2017/1608147 .

M. Tavana, D. Di Caprio, and F. J. Santos-Arteaga, “A multi-criteria perception-based strict-ordering algorithm for identifying the most-preferred choice among equally-evaluated alternatives,”10.1016/j.ins.2016.11.021__Information Sciences, vol. 381, pp. 322–340, 2017, doi:10.1016/j.ins.2016.11.021 .