M. Tavana, M. Soltanifar, and F. J. Santos-Arteaga, “Analytical hierarchy process: revolution and evolution,”10.1007/s10479-021-04432-2__Annals of Operations Research, vol. 326, no. 2, pp. 879–907, 2023, doi:10.1007/s10479-021-04432-2 .

M. Tavana, M. S. Heidary, and H. Mina, “A fuzzy preference programming and weighted influence non-linear gauge system for mission architecture assessment at NASA,”10.1016/j.asoc.2023.110572__Applied Soft Computing, vol. 145, Art. no. 110572, 2023, doi:10.1016/j.asoc.2023.110572 .

F. J. Santos-Arteaga, D. Di Caprio, M. Tavana, and E. C. Tena, “A Credibility and Strategic Behavior Approach in Hesitant Multiple Criteria Decision-Making With Application to Sustainable Transportation,”10.1109/tfuzz.2022.3188875__IEEE Transactions on Fuzzy Systems, vol. 31, no. 2, pp. 460–474, 2023, doi:10.1109/tfuzz.2022.3188875 .

R. Marín, F. J. Santos-Arteaga, M. Tavana, and D. Di Caprio, “Value Chain digitalization and technological development as innovation catalysts in small and medium-sized enterprises,”10.1016/j.jik.2023.100454__Journal of Innovation &; Knowledge, vol. 8, no. 4, Art. no. 100454, 2023, doi:10.1016/j.jik.2023.100454 .

E. B. Tirkolaee, A. E. Torkayesh, M. Tavana, A. Goli, V. Simic, and W. Ding, “An integrated decision support framework for resilient vaccine supply chain network design,”10.1016/j.engappai.2023.106945__Engineering Applications of Artificial Intelligence, vol. 126, Art. no. 106945, 2023, doi:10.1016/j.engappai.2023.106945 .

M. Soltanifar, M. Tavana, F. J. Santos-Arteaga, and H. Sharafi, “A hybrid multi-attribute decision-making and data envelopment analysis model with heterogeneous attributes: The case of sustainable development goals,”10.1016/j.envsci.2023.06.004__Environmental Science &; Policy, vol. 147, pp. 89–102, 2023, doi:10.1016/j.envsci.2023.06.004 .

M. Deveci, D. Pamucar, I. Gokasar, and M. Tavana, “Spacecraft tracking control and synchronization: An assessment of conventional, unconventional, and combined methods,”10.1016/j.asr.2022.07.056__Advances in Space Research, vol. 71, no. 9, pp. 3534–3551, 2023, doi:10.1016/j.asr.2022.07.056 .

A. Dellnitz, M. Tavana, and R. Banker, “A novel median-based optimization model for eco-efficiency assessment in data envelopment analysis,”10.1007/s10479-022-04937-4__Annals of Operations Research, vol. 322, no. 2, pp. 661–690, 2023, doi:10.1007/s10479-022-04937-4 .

F. J. Santos-Arteaga, D. Di Caprio, and M. Tavana, “A combinatorial data envelopment analysis with uncertain interval data with application to ICT evaluation,”10.1016/j.techfore.2023.122510__Technological Forecasting and Social Change, vol. 191, Art. no. 122510, 2023, doi:10.1016/j.techfore.2023.122510 .

M. Hilbert, A. Dellnitz, A. Kleine, and M. Tavana, “A novel indicator for sustainability in production planning using Center of Gravity-based assessment of Pareto fronts,”10.1016/j.cie.2023.109618__Computers &; Industrial Engineering, vol. 185, Art. no. 109618, 2023, doi:10.1016/j.cie.2023.109618 .

S. Sorooshian, M. Tavana, and S. Ribeiro-Navarrete, “From classical interpretive structural modeling to total interpretive structural modeling and beyond: A half-century of business research,”10.1016/j.jbusres.2022.113642__Journal of Business Research, vol. 157, Art. no. 113642, 2023, doi:10.1016/j.jbusres.2022.113642 .

M. Namazi, M. Tavana, E. Mohammadi, and A. Bonyadi Naeini, “A new strategic approach for R&;amp;D project portfolio selection using efficiency-uncertainty maps,”10.1108/bij-02-2022-0129__Benchmarking: An International Journal, vol. 30, no. 10, pp. 4193–4220, 2023, doi:10.1108/bij-02-2022-0129 .

V. Hajipour, S. T. A. Niaki, M. Tavana, F. J. Santos-Arteaga, and S. Hosseinzadeh, “A comparative performance analysis of intelligence-based algorithms for optimizing competitive facility location problems,”10.1016/j.mlwa.2022.100443__Machine Learning with Applications, vol. 11, Art. no. 100443, 2023, doi:10.1016/j.mlwa.2022.100443 .

H. A. Mahdiraji, M. Tavana, and A. Rezayar, “A Game-Theoretic Framework for Analyzing the Impact of Social Responsibility and Supply Chain Profitability,”10.1080/01969722.2022.2055402__Cybernetics and Systems, vol. 54, no. 1, pp. 104–137, 2023, doi:10.1080/01969722.2022.2055402 .

M. Sperling and G. Schryen, “Decision Support for Disaster Relief: Coordinating Spontaneous Volunteers,” European Journal of Operational Research (EJOR), vol. 299, no. 2, pp. 690–705, 2022.

M. Tavana, A. Khalili Nasr, H. Mina, and J. Michnik, “A private sustainable partner selection model for green public-private partnerships and regional economic development,”10.1016/j.seps.2021.101189__Socio-Economic Planning Sciences, vol. 83, Art. no. 101189, 2022, doi:10.1016/j.seps.2021.101189 .

M. Tavana, A. Azadmanesh, A. K. Nasr, and H. Mina, “A multicriteria-optimization model for cultural heritage renovation projects and public-private partnerships in the hospitality industry,”10.1080/13683500.2021.2015299__Current Issues in Tourism, vol. 25, no. 22, pp. 3709–3734, 2022, doi:10.1080/13683500.2021.2015299 .

K. Khalili-Damghani, M. Tavana, and P. Ghasemi, “A stochastic bi-objective simulation–optimization model for cascade disaster location-allocation-distribution problems,”10.1007/s10479-021-04191-0__Annals of Operations Research, vol. 309, no. 1, pp. 103–141, 2022, doi:10.1007/s10479-021-04191-0 .

M. Tavana, A. Shaabani, D. Di Caprio, and A. Bonyani, “A novel Interval Type-2 Fuzzy best-worst method and combined compromise solution for evaluating eco-friendly packaging alternatives,”10.1016/j.eswa.2022.117188__Expert Systems with Applications, vol. 200, Art. no. 117188, 2022, doi:10.1016/j.eswa.2022.117188 .

M. Tavana, H. Kian, A. K. Nasr, K. Govindan, and H. Mina, “A comprehensive framework for sustainable closed-loop supply chain network design,”10.1016/j.jclepro.2021.129777__Journal of Cleaner Production, vol. 332, Art. no. 129777, 2022, doi:10.1016/j.jclepro.2021.129777 .

M. Tavana, M. Ghasrikhouzani, and A.-R. Abtahi, “A technology development framework for scenario planning and futures studies using causal modeling,”10.1080/09537325.2021.1931672__Technology Analysis &; Strategic Management, vol. 34, no. 8, pp. 859–875, 2022, doi:10.1080/09537325.2021.1931672 .

A. Ebadi Torkayesh, M. Tavana, and F. J. Santos-Arteaga, “A multi-distance interval-valued neutrosophic approach for social failure detection in sustainable municipal waste management,”10.1016/j.jclepro.2022.130409__Journal of Cleaner Production, vol. 336, Art. no. 130409, 2022, doi:10.1016/j.jclepro.2022.130409 .

D. Pamucar, D. Macura, M. Tavana, D. Boeani, and N. Kneeevi, “An integrated rough group multicriteria decision-making model for the ex-ante prioritization of infrastructure projects: The Serbian Railways case,”10.1016/j.seps.2021.101098__Socio-Economic Planning Sciences, vol. 79, Art. no. 101098, 2022, doi:10.1016/j.seps.2021.101098 .

D. Pamucar, M. Deveci, I. Gokasar, M. Tavana, and M. Köppen, “A metaverse assessment model for sustainable transportation using ordinal priority approach and Aczel-Alsina norms,”10.1016/j.techfore.2022.121778__Technological Forecasting and Social Change, vol. 182, Art. no. 121778, 2022, doi:10.1016/j.techfore.2022.121778 .

O. Shahvari, R. Logendran, and M. Tavana, “An efficient model-based branch-and-price algorithm for unrelated-parallel machine batching and scheduling problems,”10.1007/s10951-022-00729-7__Journal of Scheduling, vol. 25, no. 5, pp. 589–621, 2022, doi:10.1007/s10951-022-00729-7 .

A. Ebrahimnejad, M. Tavana, and V. Charles, “Analytics under uncertainty: a novel method for solving linear programming problems with trapezoidal fuzzy variables,”10.1007/s00500-021-06389-7__Soft Computing, vol. 26, no. 1, pp. 327–347, 2022, doi:10.1007/s00500-021-06389-7 .

A. Vafadarnikjoo, M. Tavana, K. Chalvatzis, and T. Botelho, “A socio-economic and environmental vulnerability assessment model with causal relationships in electric power supply chains,”10.1016/j.seps.2021.101156__Socio-Economic Planning Sciences, vol. 80, Art. no. 101156, 2022, doi:10.1016/j.seps.2021.101156 .

D. Di Caprio, F. J. Santos-Arteaga, and M. Tavana, “A new algorithm for modeling online search behavior and studying ranking reliability variations,”10.1007/s10489-021-02856-8__Applied Intelligence, vol. 52, no. 7, pp. 7529–7549, 2022, doi:10.1007/s10489-021-02856-8 .

D. Di Caprio, F. J. Santos-Arteaga, and M. Tavana, “An information retrieval benchmarking model of satisficing and impatient users’ behavior in online search environments,”10.1016/j.eswa.2021.116352__Expert Systems with Applications, vol. 191, Art. no. 116352, 2022, doi:10.1016/j.eswa.2021.116352 .

S. Moazzeni, M. Tavana, and S. Mostafayi Darmian, “A dynamic location-arc routing optimization model for electric waste collection vehicles,”10.1016/j.jclepro.2022.132571__Journal of Cleaner Production, vol. 364, Art. no. 132571, 2022, doi:10.1016/j.jclepro.2022.132571 .

M. Tavana, S. Nazari-Shirkouhi, A. Mashayekhi, and S. Mousakhani, “An Integrated Data Mining Framework for Organizational Resilience Assessment and Quality Management Optimization in Trauma Centers,”10.1007/s43069-022-00132-0__Operations Research Forum, vol. 3, no. 1, Art. no. 17, 2022, doi:10.1007/s43069-022-00132-0 .

A. Afrasiabi, M. Tavana, and D. Di Caprio, “An extended hybrid fuzzy multi-criteria decision model for sustainable and resilient supplier selection,”10.1007/s11356-021-17851-2__Environmental Science and Pollution Research, vol. 29, no. 25, pp. 37291–37314, 2022, doi:10.1007/s11356-021-17851-2 .

F. J. Santos-Arteaga, M. Tavana, and D. Di Caprio, “Information acquisition and assimilation capacities as determinants of technological niche markets,”10.1016/j.jik.2022.100193__Journal of Innovation &; Knowledge, vol. 7, no. 3, Art. no. 100193, 2022, doi:10.1016/j.jik.2022.100193 .

M. Jabbari, M. Tavana, P. Fattahi, and F. Daneshamooz, “A parameter tuned hybrid algorithm for solving flow shop scheduling problems with parallel assembly stages,”10.1016/j.susoc.2021.09.002__Sustainable Operations and Computers, vol. 3, pp. 22–32, 2022, doi:10.1016/j.susoc.2021.09.002 .

S. E. Hashemi, M. Tavana, and M. Bakhshi, “A New Particle Swarm Optimization Algorithm for Optimizing Big Data Clustering,”10.1007/s42979-022-01208-8__SN Computer Science, vol. 3, no. 4, Art. no. 311, 2022, doi:10.1007/s42979-022-01208-8 .

M. Tavana, A. Shaabani, I. Raeesi Vanani, and R. Kumar Gangadhari, “A Review of Digital Transformation on Supply Chain Process Management Using Text Mining,”10.3390/pr10050842__Processes, vol. 10, no. 5, Art. no. 842, 2022, doi:10.3390/pr10050842 .

J. Kirchhoff, S. C. Burmeister, C. Weskamp, and G. Engels, “Towards a Decision Support System for Cross-Sectoral Energy Distribution Network Planning,” in Energy Informatics and Electro Mobility ICT, 2021.

J. Prester, G. Wagner, G. Schryen, and N. R. Hassan, “Classifying the Ideational Impact of Information Systems Review Articles: A Content-Enriched Deep Learning Approach,” Decision Support Systems, vol. 140, no. January, Art. no. 113432, 2021.

G. Wagner et al., “Which Factors Affect the Scientific Impact of Review Papers in IS Research? A Scientometric Study,” Information &; Management, vol. 58, no. 3, Art. no. 103427, 2021.

M. Stumpe, D. Rößler, G. Schryen, and N. Kliewer, “Study on Sensitivity of Electric Bus Systems under Simultaneous Optimization of Charging Infrastructure and Vehicle Schedules,”https://doi.org/10.1016/j.ejtl.2021.100049__EURO Journal on Transportation and Logistics, vol. 10, Art. no. 100049, 2021, doi:https://doi.org/10.1016/j.ejtl.2021.100049 .

G. Wagner, J. Prester, and G. Schryen, “Exploring the Scientific Impact of Information Systems Design Science Research,” Communications of the Association for Information Systems, vol. 48, no. 1, Art. no. 37, 2021.

G. Schryen, G. Wagner, and A. Benlian, Distinguishing Knowledge Impact from Citation Impact: A Methodology for Analysing Knowledge Impact for the Literature Review Genre. 2020.

G. Wagner, P. Empl, and G. Schryen, “Designing a Novel Strategy for Exploring Literature Corpora,” in 28th European Conference on Information Systems (ECIS 2020), Marrakesh, Morocco, 2020.

G. Schryen, “Integrating Management Science into the HPC Research Ecosystem,” Communications of the ACM, vol. 63, no. 9, pp. 35–37, 2020.

G. Schryen, N. Kliewer, and A. Fink, “Interview with Utz-Uwe Haus on “High Performance Computing in Economic Environments: Opportunities and Challenges",” Business &; Information Systems Engineering, vol. 62, no. 01/2020, pp. 21–23, 2020.

G. Schryen, “Parallel computational optimization in operations research: A new integrative framework, literature review and research directions,” European Journal of Operational Research, vol. 287, no. 1, pp. 1–18, 2020.

E. Szubartowicz and G. Schryen, “Timing in Information Security: An Event Study on the Impact of Information Security Investment Announcements,” Journal of Information System Security, vol. 16, no. 1, pp. 3–31, 2020.

G. Schryen, G. Wagner, A. Benlian, and G. Paré, “A Knowledge Development Perspective on Literature Reviews: Validation of a New Typology in the IS Field,”10.17705/1CAIS.04607__Communications of the AIS, vol. 46, pp. 134–186, 2020, doi:10.17705/1CAIS.04607 .

G. Schryen, N. Kliewer, and A. Fink, “High Performance Business Computing,”10.1007/s12599-019-00622-2__Business &; Information Systems Engineering, vol. 62, no. 1, pp. 1–3, 2020, doi:10.1007/s12599-019-00622-2 .

E. Yasasin, J. Prester, G. Wagner, and G. Schryen, “Forecasting IT Security Vulnerabilities - An Empirical Analysis,” Computers &; Security, vol. 88, no. January, 2020.

G. Rauchecker and G. Schryen, “An Exact Branch-and-Price Algorithm for Scheduling Rescue Units during Disaster Response,” European Journal of Operational Research, vol. 272, no. 1, pp. 352–363, 2019.

G. Rauchecker and G. Schryen, “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, no. 104, pp. 338–357, 2019.

V. Schuhbeck, N. Siegfried, V. Dorner, A. Benlian, M. Scholz, and G. Schryen, “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, Siegen, Germany, 2019, pp. 55–64.

S. Kuhlemann, M. Sellmann, and K. Tierney, “Exploiting Counterfactuals for Scalable Stochastic Optimization,” in Lecture Notes in Computer Science, Cham, 2019.

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

G. Rauchecker and G. Schryen, “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, 2018.

J. Prester, G. Wagner, and G. Schryen, “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, 2018.

R. Schillinger and G. Schryen, Security in Highly Connected IT Systems – Results of the Bavarian Research Alliance FORSEC. University of Regensburg, 2018.

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

R. Schuster, G. Wagner, and G. Schryen, “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, 2018.

C. Hallmann, S. C. Burmeister, M. Wissing, and L. Suhl, “Heuristics and Simulation for Water Tank Optimization,” in Communications in Computer and Information Science, Cham, 2018.

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

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.

G. Rauchecker and G. Schryen, “Projekt KUBAS: Koordination ungebundener Vor-Ort-Helfer,” Im Einsatz, vol. 23, pp. 44–46, 2016.

G. Wagner, J. Prester, M. Roche, A. Benlian, and G. Schryen, “Factors Affecting the Scientific Impact of Literature Reviews: A Scientometric Study,” in International Conference on Information Systems, 2016.

G. Schryen, G. Wagner, and A. Schlegel, “Development of two novel face-recognition CAPTCHAs: a security and usability study,” Computers &; Security, vol. 60, no. July, pp. 95–116, 2016.

G. Rauchecker and G. Schryen, “High-Performance Computing for Scheduling Decision Support: A Parallel Depth-First Search Heuristic,” in Australasian Conference on Information Systems, 2015, pp. 1–13.

T. Püschel, G. Schryen, D. Hristova, and D. Neumann, “Revenue Management for Cloud Computing Providers: Decision Models for Service Admission Control under Non-probabilistic Uncertainty,” European Journal of Operational Research, vol. 244, no. 2, pp. 637–647, 2015.

E. Yasasin and G. Schryen, “Requirements for IT Security Metrics - An Argumentation Theory Based Approach,” in 23rd European Conference on Information Systems (ECIS 2015), 2015.

E. Weishäupl, E. Yasasin, and G. Schryen, “A Multi-Theoretical Literature Review on Information Security Investments using the Resource-Based View and the Organizational Learning Theory,” in International Conference on Information Systems, 2015.

E. Weishäupl, E. Yasasin, and G. Schryen, “IT Security Investments Through the Lens of the Resource-Based View: A new Theoretical Model and Literature Review,” in 23rd European Conference on Information Systems (ECIS 2015), 2015.

E. Weishäupl et al., “Towards an Economic Approach to Identity and Access Management Systems Using Decision Theory,” in 2nd International Workshop on Security in highly connected IT Systems (SHCIS?15), 2015.

G. Schryen and E. Weishäupl, “IT-Sicherheit: Ökonomisch Planen und Bewerten,” Managementkompass, no. 2, pp. 17–18, 2015.

G. Schryen, G. Wagner, and A. Benlian, “Theory of Knowledge for Literature Reviews: An Epistemological Model, Taxonomy and Empirical Analysis of IS Literature,” in International Conference on Information Systems (ICIS), 2015.

G. Schryen, G. Rauchecker, and M. Comes, “Resource Planning in Disaster Response - Decision Support Models and Methodologies,” Business &; Information Systems Engineering (BISE), vol. 57, no. 4, pp. 243–259, 2015.

G. Schryen, “Writing qualitative IS literature reviewsf? Guidelines for synthesis, interpretation and guidance of research,” Communications of the AIS, vol. 37, no. Art 12, pp. 286–325, 2015.

G. Rauchecker, E. Yasasin, and G. Schryen, “A Decision Support System for IT Security Incident Management,” in 11th International Conference on Trust, Privacy, and Security in Digital Business (TRUSTBUS), 2014.

A. Fink et al., “Model-based Decision Support in Manufacturing and Service Networks,” Business &; Information Systems Engineering (BISE), vol. 6, no. 1, pp. 17–24, 2014.

A. Fink et al., “Modellbasierte Entscheidungsunterstützung in Produktions- und Service-Netzwerken,” Wirtschaftsinformatik, vol. 56, no. 1, pp. 21–29, 2014.

G. Schryen, The Epistemological Impact of Literature Reviews in Information Systems Research. 2014.

E. Yasasin, G. Rauchecker, J. Prester, and G. Schryen, “A Fuzzy Security Investment Decision Support Model for Highly Distributed Systems,” in 1st Workshop on Security in highly connected IT systems (SHCIS 14), 2014.

F. Wex, G. Schryen, S. Feuerriegel, and D. Neumann, “Emergency Response in Natural Disaster Management: Allocation and Scheduling of Rescue Units,” European Journal of Operational Research, 2014.

G. Schryen and F. Wex, “Risk Reduction in Natural Disaster Management Through Information Systems: A Literature review and an IS design science research agenda,” International Journal of Information Systems for Crisis Response and Management (IJISCRAM), vol. 6, no. 1, 2014.

G. Schryen and D. Hristova, “Duality in fuzzy linear programming: A survey,” OR -Spectrum, vol. 37, no. 1, pp. 1–48, 2014.

G. Schryen, “Writing qualitative IS literature reviewsf? Guidelines for synthesis, interpretation and guidance of research,” Communications of the AIS, 2014.

H. de Meer et al., “Sicherheitsherausforderungen in hochverteilten Systemen,” PIK - Praxis der Informationsverarbeitung und Kommunikation, vol. 36, no. 3, pp. 153–159, 2013.

F. Wex and G. Schryen, “Effektiver Einsatz von Rettungskräften bei Naturkatastrophen - Modelle und Verfahren zur Entscheidungsunterstützung,” Blick in die Wissenschaft, no. 28, pp. 27–32, 2013.

F. Wex, G. Schryen, and D. Neumann, “Assignments of Collaborative Rescue Units during Emergency Response,” International Journal of Information Systems for Crisis Response and Management, vol. 5, no. 4, pp. 63–80, 2013.

F. Wex, G. Schryen, and D. Neumann, “Decision Modeling for Assignments of Collaborative Rescue Units during Emergency Response,” in Proceedings of the 46th Hawaii International Conference on System Science, 2013.

G. Schryen, “Revisiting IS Business Value Research: What we already know, what we still need to know, and how we can get there,” European Journal of Information Systems (EJIS), vol. 22, no. 2, pp. 139–169, 2013.

T. Püschel, G. Schryen, D. Hristova, and D. Neumann, “Cloud Service Revenue Management,” in European Conference on Information Systems, 2012.

F. Lang, G. Schryen, and A. Fink, “Elicitating, modeling, and processing uncertain human preferences for software agents in electronic negotiations: An empirical study,” in International Conference on Information Systems, 2012.

C. Bodenstein, G. Schryen, and D. Neumann, “Energy-Aware Workload Management Models for Operating Cost Reduction in Data Centers,” European Journal of Operational Researchf: EJOR, vol. 222, no. 1, pp. 157–167, 2012.

F. Wex, G. Schryen, and D. Neumann, “A Fuzzy Decision Support Model for Natural Disaster Response under Informational Uncertainty,” International Journal of Information Systems for Crisis Response and Management, vol. 4, no. 3, pp. 23–41, 2012.

F. Wex, G. Schryen, and D. Neumann, “Operational Emergency Response under Informational Uncertainty: A Fuzzy Optimization Model for Scheduling and Allocating Rescue Units,” in International Conference on Information Systems for Crisis Response and Management (ISCRAM) 2012, 2012.