@inproceedings{47427, author = {{Schryen, Guido and Marrone, Mauricio and Yang, Jiaqi}}, booktitle = {{Proceedings of the 57th Hawaii International Conference on System Science (HICSS 2024)}}, title = {{{Adopting Generative AI for Literature Reviews: An Epistemological Perspective}}}, year = {{2024}}, } @inproceedings{47429, author = {{Betke, Hans and Sperling, Martina and Schryen, Guido and Sackmann, Stefan}}, booktitle = {{Proceedings of the 57th Hawaii International Conference on System Science (HICSS 2024)}}, title = {{{A Design Theory for Spontaneous Volunteer Coordination Systems in Disaster Response}}}, year = {{2024}}, } @article{50301, author = {{Schryen, Guido}}, journal = {{Journal of Parallel and Distributed Computing}}, title = {{{Speedup and efficiency of computational parallelization: A unifying approach and asymptotic analysis}}}, year = {{2024}}, } @article{52092, author = {{Stumpe, Miriam}}, issn = {{2352-1465}}, journal = {{Transportation Research Procedia}}, pages = {{402--409}}, publisher = {{Elsevier BV}}, title = {{{A new mathematical formulation for the simultaneous optimization of charging infrastructure and vehicle schedules for electric bus systems}}}, doi = {{10.1016/j.trpro.2024.02.051}}, volume = {{78}}, year = {{2024}}, } @article{42179, author = {{Burmeister, Sascha Christian and Schryen, Guido}}, journal = {{Energy Systems}}, publisher = {{Springer}}, title = {{{Distribution Network Optimization: Predicting computation times to design scenario analysis for network operators}}}, doi = {{10.1007/s12667-023-00572-5}}, year = {{2023}}, } @article{44361, author = {{Schryen, Guido and Sperling, Martina}}, journal = {{Computers & Operations Research}}, number = {{September}}, title = {{{Literature Reviews in Operations Research: A New Taxonomy and a Meta Review}}}, volume = {{157}}, year = {{2023}}, } @article{44383, author = {{Dieter, Peter and Caron, Matthew and Schryen, Guido}}, journal = {{European Journal of Operational Research (EJOR)}}, number = {{1}}, pages = {{283--300}}, title = {{{Integrating driver behavior into last-mile delivery routing: Combining machine learning and optimization in a hybrid decision support framework}}}, doi = {{https://doi.org/10.1016/j.ejor.2023.04.043}}, volume = {{311}}, year = {{2023}}, } @article{45816, author = {{Dieter, Peter and Stumpe, Miriam and Ulmer, Marlin Wolf and Schryen, Guido}}, journal = {{Transportation Research Part D}}, title = {{{Anticipatory Assignment of Passengers to Meeting Points for Taxi-Ridesharing}}}, volume = {{121}}, year = {{2023}}, } @inbook{46867, author = {{Dieter, Peter}}, booktitle = {{Lecture Notes in Computer Science}}, isbn = {{9783031436116}}, issn = {{0302-9743}}, publisher = {{Springer Nature Switzerland}}, title = {{{A Regret Policy for the Dynamic Vehicle Routing Problem with Time Windows}}}, doi = {{10.1007/978-3-031-43612-3_14}}, year = {{2023}}, } @article{47431, author = {{Burmeister, Sascha Christian and Guericke, Daniela and Schryen, Guido}}, journal = {{Flexible Services and Manufacturing Journal}}, title = {{{A Memetic NSGA-II for the Multi-Objective Flexible Job Shop Scheduling Problem with Real-time Energy Tariffs}}}, doi = {{10.1007/s10696-023-09517-7}}, year = {{2023}}, } @article{45112, author = {{Beverungen, Daniel and Kundisch, Dennis and Mirbabaie, Milad and Müller, Oliver and Schryen, Guido and Trang, Simon Thanh-Nam and Trier, Matthias}}, journal = {{Business & Information Systems Engineering}}, number = {{4}}, pages = {{463 -- 474}}, title = {{{Digital Responsibility – a Multilevel Framework for Responsible Digitalization}}}, doi = {{https://doi.org/10.1007/s12599-023-00822-x}}, volume = {{65}}, year = {{2023}}, } @misc{48335, author = {{Knorr, Lukas and Jungeilges, André and Pfeifer, Florian and Burmeister, Sascha Christian and Meschede, Henning}}, publisher = {{4. Aachener Ofenbau- und Thermoprozess-Kolloquium}}, title = {{{Regenerative Energien für einen effizienten Betrieb von Presshärtelinien}}}, year = {{2023}}, } @article{23415, author = {{Sperling, Martina and Schryen, Guido}}, journal = {{European Journal of Operational Research (EJOR)}}, number = {{2}}, pages = {{690 -- 705}}, title = {{{Decision Support for Disaster Relief: Coordinating Spontaneous Volunteers}}}, volume = {{299}}, year = {{2022}}, } @inproceedings{21093, abstract = {{Requirements for energy distribution networks are changing fast due to the growing share of renewable energy, increasing electrification, and novel consumer and asset technologies. Since uncertainties about future developments increase planning difficulty, flexibility potentials such as synergies between the electricity, gas, heat, and transport sector often remain unused. In this paper, we therefore present a novel module-based concept for a decision support system that helps distribution network planners to identify cross-sectoral synergies and to select optimal network assets such as transformers, cables, pipes, energy storage systems or energy conversion technology. The concept enables long-term transformation plans and supports distribution network planners in designing reliable, sustainable and cost-efficient distribution networks for future demands.}}, author = {{Kirchhoff, Jonas and Burmeister, Sascha Christian and Weskamp, Christoph and Engels, Gregor}}, booktitle = {{Energy Informatics and Electro Mobility ICT}}, editor = {{Breitner, Michael H. and Lehnhoff, Sebastian and Nieße, Astrid and Staudt, Philipp and Weinhardt, Christof and Werth, Oliver}}, title = {{{Towards a Decision Support System for Cross-Sectoral Energy Distribution Network Planning}}}, year = {{2021}}, } @article{20212, abstract = {{Ideational impact refers to the uptake of a paper's ideas and concepts by subsequent research. It is defined in stark contrast to total citation impact, a measure predominantly used in research evaluation that assumes that all citations are equal. Understanding ideational impact is critical for evaluating research impact and understanding how scientific disciplines build a cumulative tradition. Research has only recently developed automated citation classification techniques to distinguish between different types of citations and generally does not emphasize the conceptual content of the citations and its ideational impact. To address this problem, we develop Deep Content-enriched Ideational Impact Classification (Deep-CENIC) as the first automated approach for ideational impact classification to support researchers' literature search practices. We evaluate Deep-CENIC on 1,256 papers citing 24 information systems review articles from the IT business value domain. We show that Deep-CENIC significantly outperforms state-of-the-art benchmark models. We contribute to information systems research by operationalizing the concept of ideational impact, designing a recommender system for academic papers based on deep learning techniques, and empirically exploring the ideational impact of the IT business value domain. }}, author = {{Prester, Julian and Wagner, Gerit and Schryen, Guido and Hassan, Nik Rushdi}}, journal = {{Decision Support Systems}}, keywords = {{Ideational impact, citation classification, academic recommender systems, natural language processing, deep learning, cumulative tradition}}, number = {{January}}, title = {{{Classifying the Ideational Impact of Information Systems Review Articles: A Content-Enriched Deep Learning Approach}}}, volume = {{140}}, year = {{2021}}, } @article{20844, abstract = {{Review papers are essential for knowledge development in IS. While some are cited twice a day, others accumulate single digit citations over a decade. The magnitude of these differences prompts us to analyze what distinguishes those reviews that have proven to be integral to scientific progress from those that might be considered less impactful. Our results highlight differences between reviews aimed at describing, understanding, explaining, and theory testing. Beyond the control variables, they demonstrate the importance of methodological transparency and the development of research agendas. These insights inform all stakeholders involved in the development and publication of review papers.}}, author = {{Wagner, Gerit and Prester, Julian and Roche, Maria and Schryen, Guido and Benlian, Alexander and Paré, Guy and Templier, Mathieu}}, journal = {{Information & Management}}, keywords = {{Literature review, review papers, scientometric, scientific impact, citation analysis}}, number = {{3}}, title = {{{Which Factors Affect the Scientific Impact of Review Papers in IS Research? A Scientometric Study}}}, volume = {{58}}, year = {{2021}}, } @article{23494, author = {{Stumpe, Miriam and Rößler, David and Schryen, Guido and Kliewer, Natalia}}, journal = {{EURO Journal on Transportation and Logistics}}, title = {{{Study on Sensitivity of Electric Bus Systems under Simultaneous Optimization of Charging Infrastructure and Vehicle Schedules}}}, doi = {{https://doi.org/10.1016/j.ejtl.2021.100049}}, volume = {{10}}, year = {{2021}}, } @article{17934, author = {{Wagner, Gerit and Prester, Julian and Schryen, Guido}}, journal = {{Communications of the Association for Information Systems}}, number = {{1}}, title = {{{Exploring the Scientific Impact of Information Systems Design Science Research}}}, volume = {{48}}, year = {{2021}}, } @techreport{17019, abstract = {{The scientific impact of research papers is multi-dimensional and can be determined quantitatively by means of citation analysis and qualitatively by means of content analysis. Accounting for the widely acknowledged limitations of pure citation analysis, we adopt a knowledge-based perspective on scientific impact to develop a methodology for content-based citation analysis which allows determining how papers have enabled knowledge development in subsequent research (knowledge impact). As knowledge development differs between research genres, we develop a new knowledgebased citation analysis methodology for the genre of standalone literature reviews (LRs). We apply the suggested methodology to the IS business value domain by manually coding 22 LRs and 1,228 citing papers (CPs) and show that the results challenge the assumption that citations indicate knowledge impact. We derive implications for distinguishing knowledge impact from citation impact in the LR genre. Finally, we develop recommendations for authors of LRs, scientific evaluation committees and editorial boards of journals how to apply and benefit from the suggested methodology, and we discuss its efficiency and automatization.}}, author = {{Schryen, Guido and Wagner, Gerit and Benlian, Alexander}}, keywords = {{Scientific impact, knowledge impact, content-based citation analysis, methodology}}, title = {{{Distinguishing Knowledge Impact from Citation Impact: A Methodology for Analysing Knowledge Impact for the Literature Review Genre}}}, year = {{2020}}, } @inproceedings{17055, abstract = {{Understanding a new literature corpus can be a grueling experience for junior scholars. Nevertheless, corresponding guidelines have not been updated for decades. We contend that the traditional strategy of skimming all papers and reading selected papers afterwards needs to be revised. Therefore, we design a new strategy that guides the overall exploratory process by prioritizing influential papers for initial reading, followed by skimming the remaining papers. Consistent with schemata theory, starting with in-depth reading allows readers to acquire more substantial prior content schemata, which are representa-tive for the literature corpus and useful in the following skimming process. To this end, we develop a prototype that identifies the influential papers from a set of PDFs, which is illustrated in a case study in the IT business value domain. With the new strategy, we envision a more efficient process of exploring unknown literature corpora.}}, author = {{Wagner, Gerit and Empl, Philipp and Schryen, Guido}}, booktitle = {{28th European Conference on Information Systems (ECIS 2020)}}, keywords = {{Reading and skimming, Exploring literature, Review methodology, Design science research, Schemata theory}}, location = {{Marrakesh, Morocco}}, title = {{{Designing a Novel Strategy for Exploring Literature Corpora}}}, year = {{2020}}, } @article{15414, author = {{Schryen, Guido}}, journal = {{Communications of the ACM}}, number = {{9}}, pages = {{35 -- 37}}, title = {{{Integrating Management Science into the HPC Research Ecosystem}}}, volume = {{63}}, year = {{2020}}, } @article{15513, abstract = {{This interview is part of the special issue (01/2020) on “High Performance Business Computing” to be published in the journal Business & Information Systems Engineering. The interviewee Utz-Uwe Haus is Senior Research Engineer @ CRAY European Research Lab (CERL)). A bio of him is included at the end of the interview.}}, author = {{Schryen, Guido and Kliewer, Natalia and Fink, Andreas}}, journal = {{Business & Information Systems Engineering}}, number = {{01/2020}}, pages = {{21 -- 23}}, title = {{{Interview with Utz-Uwe Haus on “High Performance Computing in Economic Environments: Opportunities and Challenges"}}}, volume = {{62}}, year = {{2020}}, } @article{15022, author = {{Schryen, Guido}}, journal = {{European Journal of Operational Research}}, number = {{1}}, pages = {{1 -- 18}}, publisher = {{Elsevier}}, title = {{{Parallel computational optimization in operations research: A new integrative framework, literature review and research directions}}}, volume = {{287}}, year = {{2020}}, } @article{16249, abstract = {{Timing plays a crucial role in the context of information security investments. We regard timing in two dimensions, namely the time of announcement in relation to the time of investment and the time of announcement in relation to the time of a fundamental security incident. The financial value of information security investments is assessed by examining the relationship between the investment announcements and their stock market reaction focusing on the two time dimensions. Using an event study methodology, we found that both dimensions influence the stock market return of the investing organization. Our results indicate that (1) after fundamental security incidents in a given industry, the stock price will react more positively to a firm’s announcement of actual information security investments than to announcements of the intention to invest; (2) the stock price will react more positively to a firm’s announcements of the intention to invest after the fundamental security incident compared to before; and (3) the stock price will react more positively to a firm’s announcements of actual information security investments after the fundamental security incident compared to before. Overall, the lowest abnormal return can be expected when the intention to invest is announced before a fundamental information security incident and the highest return when actual investing after a fundamental information security incident in the respective industry.}}, author = {{Szubartowicz, Eva and Schryen, Guido}}, journal = {{Journal of Information System Security}}, keywords = {{Event Study, Information Security, Investment Announcements, Stock Price Reaction, Value of Information Security Investments}}, number = {{1}}, pages = {{3 -- 31}}, publisher = {{Information Institute Publishing, Washington DC, USA}}, title = {{{Timing in Information Security: An Event Study on the Impact of Information Security Investment Announcements}}}, volume = {{16}}, year = {{2020}}, } @article{11946, abstract = {{Literature reviews (LRs) play an important role in the development of domain knowledge in all fields. Yet, we observe a lack of insights into the activities with which LRs actually develop knowledge. To address this important gap, we (1) derive knowledge building activities from the extant literature on LRs, (2) suggest a knowledge-based typology of LRs that complements existing typologies, and (3) apply the suggested typology in an empirical study that explores how LRs with different goals and methodologies have contributed to knowledge development. The analysis of 240 LRs published in 40 renowned IS journals between 2000 and 2014 allows us to draw a detailed picture of knowledge development achieved by one of the most important genres in the IS field. An overarching contribution of our work is to unify extant conceptualizations of LRs by clarifying and illustrating how LRs apply different methodologies in a range of knowledge building activities to achieve their goals with respect to theory.}}, author = {{Schryen, Guido and Wagner, Gerit and Benlian, Alexander and Paré, Guy}}, issn = {{ 1529-3181}}, journal = {{Communications of the AIS}}, keywords = {{Literature review, knowledge development, knowledge building activities, knowledge-based typology, information systems research}}, pages = {{134--186}}, title = {{{A Knowledge Development Perspective on Literature Reviews: Validation of a New Typology in the IS Field}}}, doi = {{10.17705/1CAIS.04607}}, volume = {{46}}, year = {{2020}}, } @article{14985, author = {{Schryen, Guido and Kliewer, Natalia and Fink, Andreas}}, journal = {{Business & Information Systems Engineering}}, number = {{1}}, pages = {{1--3}}, title = {{{High Performance Business Computing}}}, doi = {{10.1007/s12599-019-00622-2}}, volume = {{62}}, year = {{2020}}, } @article{13175, abstract = {{Today, organizations must deal with a plethora of IT security threats and to ensure smooth and uninterrupted business operations, firms are challenged to predict the volume of IT security vulnerabilities and allocate resources for fixing them. This challenge requires decision makers to assess which system or software packages are prone to vulnerabilities, how many post-release vulnerabilities can be expected to occur during a certain period of time, and what impact exploits might have. Substantial research has been dedicated to techniques that analyze source code and detect security vulnerabilities. However, only limited research has focused on forecasting security vulnerabilities that are detected and reported after the release of software. To address this shortcoming, we apply established methodologies which are capable of forecasting events exhibiting specific time series characteristics of security vulnerabilities, i.e., rareness of occurrence, volatility, non-stationarity, and seasonality. Based on a dataset taken from the National Vulnerability Database (NVD), we use the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) to measure the forecasting accuracy of single, double, and triple exponential smoothing methodologies, Croston's methodology, ARIMA, and a neural network-based approach. We analyze the impact of the applied forecasting methodology on the prediction accuracy with regard to its robustness along the dimensions of the examined system and software package "operating systems", "browsers" and "office solutions" and the applied metrics. To the best of our knowledge, this study is the first to analyze the effect of forecasting methodologies and to apply metrics that are suitable in this context. Our results show that the optimal forecasting methodology depends on the software or system package, as some methodologies perform poorly in the context of IT security vulnerabilities, that absolute metrics can cover the actual prediction error precisely, and that the prediction accuracy is robust within the two applied forecasting-error metrics.}}, author = {{Yasasin, Emrah and Prester, Julian and Wagner, Gerit and Schryen, Guido}}, issn = {{0167-4048}}, journal = {{Computers & Security}}, number = {{January}}, title = {{{Forecasting IT Security Vulnerabilities - An Empirical Analysis}}}, volume = {{88}}, year = {{2020}}, } @article{5674, abstract = {{In disaster operations management, a challenging task for rescue organizations occurs when they have to assign and schedule their rescue units to emerging incidents under time pressure in order to reduce the overall resulting harm. Of particular importance in practical scenarios is the need to consider collaboration of rescue units. This task has hardly been addressed in the literature. We contribute to both modeling and solving this problem by (1) conceptualizing the situation as a type of scheduling problem, (2) modeling it as a binary linear minimization problem, (3) suggesting a branch-and-price algorithm, which can serve as both an exact and heuristic solution procedure, and (4) conducting computational experiments - including a sensitivity analysis of the effects of exogenous model parameters on execution times and objective value improvements over a heuristic suggested in the literature - for different practical disaster scenarios. The results of our computational experiments show that most problem instances of practically feasible size can be solved to optimality within ten minutes. Furthermore, even when our algorithm is terminated once the first feasible solution has been found, this solution is in almost all cases competitive to the optimal solution and substantially better than the solution obtained by the best known algorithm from the literature. This performance of our branch-and-price algorithm enables rescue organizations to apply our procedure in practice, even when the time for decision making is limited to a few minutes. By addressing a very general type of scheduling problem, our approach applies to various scheduling situations.}}, author = {{Rauchecker, Gerhard and Schryen, Guido}}, journal = {{European Journal of Operational Research}}, keywords = {{OR in disaster relief, disaster operations management, scheduling, branch-and-price}}, number = {{1}}, pages = {{352 -- 363}}, publisher = {{Elsevier}}, title = {{{An Exact Branch-and-Price Algorithm for Scheduling Rescue Units during Disaster Response}}}, volume = {{272}}, year = {{2019}}, } @article{6512, abstract = {{Scheduling problems are essential for decision making in many academic disciplines, including operations management, computer science, and information systems. Since many scheduling problems are NP-hard in the strong sense, there is only limited research on exact algorithms and how their efficiency scales when implemented on parallel computing architectures. We address this gap by (1) adapting an exact branch-and-price algorithm to a parallel machine scheduling problem on unrelated machines with sequence- and machine-dependent setup times, (2) parallelizing the adapted algorithm by implementing a distributed-memory parallelization with a master/worker approach, and (3) conducting extensive computational experiments using up to 960 MPI processes on a modern high performance computing cluster. With our experiments, we show that the efficiency of our parallelization approach can lead to superlinear speedup but can vary substantially between instances. We further show that the wall time of serial execution can be substantially reduced through our parallelization, in some cases from 94 hours to less than six minutes when our algorithm is executed on 960 processes.}}, author = {{Rauchecker, Gerhard and Schryen, Guido}}, journal = {{Computers & Operations Research}}, keywords = {{parallel machine scheduling with setup times, parallel branch-and-price algorithm, high performance computing, master/worker parallelization}}, number = {{104}}, pages = {{338--357}}, publisher = {{Elsevier}}, title = {{{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}}}, year = {{2019}}, } @inproceedings{6514, abstract = {{Recommender Agents (RAs) facilitate consumers’ online purchase decisions for complex, multi-attribute products. As not all combinations of attribute levels can be obtained, users are forced into trade-offs. The exposure of trade-offs in a RA has been found to affect consumers’ perceptions. However, little is known about how different preference elicitation methods in RAs affect consumers by varying degrees of trade-off exposure. We propose a research model that investigates how different levels of trade-off exposure cognitively and affectively influence consumers’ satisfaction with RAs. We operationalize these levels in three different RA types and test our hypotheses in a laboratory experiment with 116 participants. Our results indicate that with increasing tradeoff exposure, perceived enjoyment and perceived control follow an inverted Ushaped relationship. Hence, RAs using preference elicitation methods with medium trade-off exposure yield highest consumer satisfaction. This contributes to the understanding of trade-offs in RAs and provides valuable implications to e-commerce practitioners.}}, author = {{Schuhbeck, Veronika and Siegfried, Nils and Dorner, Verena and Benlian, Alexander and Scholz, Michael and Schryen, Guido}}, booktitle = {{Proceedings of the 14. Internationale Tagung Wirtschaftsinformatik}}, keywords = {{Recommender Agents, Preference Elicitation Method, Trade-off Exposure, Customer Satisfaction}}, location = {{Siegen, Germany}}, pages = {{55--64}}, title = {{{Walking the Middle Path: How Medium Trade-off Exposure Leads to Higher Consumer Satisfaction in Recommender Agents}}}, year = {{2019}}, } @inbook{14890, author = {{Kuhlemann, Stefan and Sellmann, Meinolf and Tierney, Kevin}}, booktitle = {{Lecture Notes in Computer Science}}, isbn = {{9783030300470}}, issn = {{0302-9743}}, title = {{{Exploiting Counterfactuals for Scalable Stochastic Optimization}}}, doi = {{10.1007/978-3-030-30048-7_40}}, year = {{2019}}, } @article{14540, author = {{Schryen, Guido and Kliewer, Natalia and Borndörfer, Ralf and Koch, Thorsten}}, journal = {{OR News}}, pages = {{34--35}}, title = {{{High-Performance Business Computing – Parallel Algorithms and Implementations for Solving Problems in Operations Research and Data Analysis}}}, volume = {{65}}, year = {{2019}}, } @inproceedings{5675, abstract = {{When responding to natural disasters, professional relief units are often supported by many volunteers which are not affiliated to humanitarian organizations. The effective coordination of these volunteers is crucial to leverage their capabilities and to avoid conflicts with professional relief units. In this paper, we empirically identify key requirements that professional relief units pose on this coordination. Based on these requirements, we suggest a decision model. We computationally solve a real-world instance of the model and empirically validate the computed solution in interviews with practitioners. Our results show that the suggested model allows for solving volunteer coordination tasks of realistic size near-optimally within short time, with the determined solution being well accepted by practitioners. We also describe in this article how the suggested decision support model is integrated in the volunteer coordination system which we develop in joint cooperation with a disaster management authority and a software development company.}}, author = {{Rauchecker, Gerhard and Schryen, Guido}}, booktitle = {{Proceedings of the 15th International Conference on Information Systems for Crisis Response and Management}}, keywords = {{Coordination of spontaneous volunteers, volunteer coordination system, decision support, scheduling optimization model, linear programming}}, location = {{Rochester, NY, USA}}, title = {{{Decision Support for the Optimal Coordination of Spontaneous Volunteers in Disaster Relief}}}, year = {{2018}}, } @inproceedings{5681, author = {{Prester, Julian and Wagner, Gerit and Schryen, Guido}}, booktitle = {{Proceedings of the 2018 International Conference on Information Systems (ICIS 2018)}}, location = {{San Francisco, CA, USA}}, title = {{{Classifying the Ideational Impact of IS Review Articles: A Natural Language Processing Based Approach}}}, year = {{2018}}, } @book{6164, author = {{Schillinger, Rolf and Schryen, Guido}}, isbn = {{978-3-88246-374-3}}, publisher = {{University of Regensburg}}, title = {{{Security in Highly Connected IT Systems – Results of the Bavarian Research Alliance FORSEC}}}, doi = {{10.5283/epub.36264}}, year = {{2018}}, } @article{5586, abstract = {{The need to protect resources against attackers is reflected by huge information security investments of firms worldwide. In the presence of budget constraints and a diverse set of assets to protect, organizations have to decide in which IT security measures to invest, how to evaluate those investment decisions, and how to learn from past decisions to optimize future security investment actions. While the academic literature has provided valuable insights into these issues, there is a lack of empirical contributions. To address this lack, we conduct a theory-based exploratory multiple case study. Our case study reveals that (1) firms? investments in information security are largely driven by external environmental and industry-related factors, (2) firms do not implement standardized decision processes, (3) the security process is perceived to impact the business process in a disturbing way, (4) both the implementation of evaluation processes and the application of metrics are hardly existent and (5) learning activities mainly occur at an ad-hoc basis.}}, author = {{Weishäupl, Eva and Yasasin, Emrah and Schryen, Guido}}, journal = {{Computers & Security}}, keywords = {{Information Security Investments, Multiple Case Study, Organizations, Single Loop Learning, Double Loop Learning}}, pages = {{807 -- 823}}, publisher = {{Elsevier}}, title = {{{Information Security Investments: An Exploratory Multiple Case Study on Decision-Making, Evaluation and Learning}}}, volume = {{77}}, year = {{2018}}, } @inproceedings{5600, author = {{Schuster, Richard and Wagner, Gerit and Schryen, Guido}}, booktitle = {{Proceedings of the 2018 International Conference on Information Systems (ICIS 2018)}}, location = {{San Francisco, CA, USA}}, title = {{{Information Systems Design Science Research and Cumulative Knowledge Development: An Exploratory Study}}}, year = {{2018}}, } @inbook{14856, author = {{Hallmann, Corinna and Burmeister, Sascha Christian and Wissing, Michaela and Suhl, Leena}}, booktitle = {{Communications in Computer and Information Science}}, isbn = {{9783319962702}}, issn = {{1865-0929}}, title = {{{Heuristics and Simulation for Water Tank Optimization}}}, doi = {{10.1007/978-3-319-96271-9_5}}, year = {{2018}}, } @inbook{14861, author = {{Hallmann, Corinna and Kuhlemann, Stefan}}, booktitle = {{Operations Research Proceedings}}, isbn = {{9783319899190}}, issn = {{0721-5924}}, title = {{{Model Generator for Water Distribution Systems}}}, doi = {{10.1007/978-3-319-89920-6_34}}, year = {{2018}}, } @inproceedings{5692, abstract = {{We consider Max-min Share (MmS) fair allocations of indivisible chores (items with negative utilities). We show that allocation of chores and classical allocation of goods (items with positive utilities) have some fundamental connections but also differences which prevent a straightforward application of algorithms for goods in the chores setting and viceversa. We prove that an MmS allocation does not need to exist for chores and computing an MmS allocation - if it exists - is strongly NP-hard. In view of these non-existence and complexity results, we present a polynomial-time 2-approximation algorithm for MmS fairness for chores. We then introduce a new fairness concept called optimal MmS that represents the best possible allocation in terms of MmS that is guaranteed to exist. We use connections to parallel machine scheduling to give (1) a polynomial-time approximation scheme for computing an optimal MmS allocation when the number of agents is fixed and (2) an effective and efficient heuristic with an ex-post worst-case analysis.}}, author = {{Aziz, Haris and Rauchecker, Gerhard and Schryen, Guido and Walsh, Toby}}, booktitle = {{Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17)}}, location = {{San Francisco, CA, USA}}, number = {{1}}, pages = {{1--7}}, title = {{{Algorithms for Max-Min Share Fair Allocation of Indivisible Chores}}}, volume = {{31}}, year = {{2017}}, } @inproceedings{5594, abstract = {{Design science is a fundamental research stream that contends its position in the information systems discipline. While ongoing debates address the relative importance of design science contributions in the information systems community, insights into the scientific impact of design science research (DSR) are missing and this lack of understanding arguably poses challenges to an informed discourse. To identify the most influential papers and those factors that explain their scientific impact, this paper presents an exploratory study of the scientific impact of DSR papers published in the AIS Senior Scholars' Basket of Journals. We uncover the current DSR landscape by taking stock of influential papers and theories and develop a model to explain the scientific impact of DSR papers. Our findings show that scientific impact is significantly explained by theorization and novelty. We discuss how the implications of our work can be projected on the overarching discourse on DSR.}}, author = {{Wagner, Gerit and Prester, Julian and Schryen, Guido}}, booktitle = {{38th International Conference on Information Systems}}, location = {{Seoul, South Korea}}, title = {{{Exploring the Scientific Impact of Information Systems Design Science Research: A Scientometric Study}}}, year = {{2017}}, } @article{5626, author = {{Schryen, Guido and Hristova, Diana}}, journal = {{Smart Data Radar (Deutsche Bank)}}, title = {{{High-Performance Business Computing - Effizienzsteigerung durch Parallelisierung}}}, year = {{2017}}, } @article{5633, abstract = {{Literature reviews (LRs) are recognized for their increasing impact in the information systems literature. Methodologists have drawn attention to the question of how we can leverage the value of LRs to preserve and generate knowledge. The panelists who participated in the discussion of ?Standalone Literature Reviews in IS Research: What Can Be Learnt from the Past and Other Fields?? at ICIS 2016 in Dublin acknowledged this significant issue and debated a) what the IS field can learn from other fields and where IS-specific challenges occur, b) how the IS field should move forward to foster the genre of LRs, and c) what best practices are to train doctoral IS students in publishing LRs. This article reports the key takeaways of this panel discussion. Guidance for IS scholars is provided on how to conduct LRs that contribute to the cumulative knowledge development within and across the IS field to best prepare the next generation of IS scholars.}}, author = {{Schryen, Guido and Benlian, Alexander and Rowe, Frantz and Shirley, Gregor and Larsen, Kai and Petter, Stacie and Par{\'e}, Guy and Wagner, Gerit and Haag, Steffi and Yasasin, Emrah}}, issn = {{1529-3181}}, journal = {{Communications of the AIS}}, keywords = {{Literature Review, Review Methodology, Research Methodology, Doctoral Training}}, pages = {{557 -- 569}}, publisher = {{Association for Information Systems (AIS)}}, title = {{{Literature Reviews in IS Research: What Can Be Learnt from the Past and Other Fields?}}}, volume = {{40}}, year = {{2017}}, } @article{5671, abstract = {{Multi-attribute value theory (MAVT)-based recommender systems have been proposed for dealing with issues of existing recommender systems, such as the cold-start problem and changing preferences. However, as we argue in this paper, existing MAVT-based methods for measuring attribute importance weights do not fit the shopping tasks for which recommender systems are typically used. These methods assume well-trained decision makers who are willing to invest time and cognitive effort, and who are familiar with the attributes describing the available alternatives and the ranges of these attribute levels. Yet, recommender systems are most often used by consumers who are usually not familiar with the available attributes and ranges and who wish to save time and effort. Against this background, we develop a new method, based on a product configuration process, which is tailored to the characteristics of these particular decision makers. We empirically compare our method to SWING, ranking-based conjoint analysis and TRADEOFF in a between-subjects laboratory experiment with 153 participants. Results indicate that our proposed method performs better than TRADEOFF and CONJOINT and at least as well as SWING in terms of recommendation accuracy, better than SWING and TRADEOFF and at least as well as CONJOINT in terms of cognitive load, and that participants were faster with our method than with any other method. We conclude that our method is a promising option to help support consumers' decision processes in e-commerce shopping tasks.}}, author = {{Scholz, Michael and Dorner, Verena and Schryen, Guido and Benlian, Alexander}}, journal = {{European Journal of Operational Research}}, keywords = {{E-Commerce, Recommender System, Attribute Weights, Configuration System, Decision Support}}, number = {{1}}, pages = {{205 -- 215}}, publisher = {{Elsevier}}, title = {{{A configuration-based recommender system for supporting e-commerce decisions}}}, volume = {{259}}, year = {{2017}}, } @inbook{14857, author = {{Beckschäfer, Michaela and Malberg, Simon and Tierney, Kevin and Weskamp, Christoph}}, booktitle = {{Lecture Notes in Computer Science}}, isbn = {{9783319684956}}, issn = {{0302-9743}}, title = {{{Simulating Storage Policies for an Automated Grid-Based Warehouse System}}}, doi = {{10.1007/978-3-319-68496-3_31}}, year = {{2017}}, } @article{5676, author = {{Rauchecker, Gerhard and Schryen, Guido}}, journal = {{Im Einsatz}}, pages = {{44--46}}, publisher = {{Stumpf & Kossendey}}, title = {{{Projekt KUBAS: Koordination ungebundener Vor-Ort-Helfer}}}, volume = {{23}}, year = {{2016}}, } @inproceedings{5595, author = {{Wagner, Gerit and Prester, Julian and Roche, Maria and Benlian, Alexander and Schryen, Guido}}, booktitle = {{International Conference on Information Systems}}, title = {{{Factors Affecting the Scientific Impact of Literature Reviews: A Scientometric Study}}}, year = {{2016}}, } @article{5617, abstract = {{CAPTCHAs are challenge-response tests that aim at preventing unwanted machines, including bots, from accessing web services while providing easy access for humans. Recent advances in artificial-intelligence based attacks show that the level of security provided by many state-of-the-art text-based CAPTCHAs is declining. At the same time, techniques for distorting and obscuring the text, which are used to maintain the level of security, make text-based CAPTCHAs diffcult to solve for humans, and thereby further degrade usability. The need for developing alternative types of CAPTCHAs which improve both, the current security and usability levels, has been emphasized by several researchers. With this study, we contribute to research through (1) the development of two new face recognition CAPTCHAs (Farett-Gender and Farett-Gender&Age), (2) the security analysis of both procedures, and (3) the provision of empirical evidence that one of the suggested CAPTCHAs (Farett-Gender) is similar to Google's reCAPTCHA and better than KCAPTCHA concerning effectiveness (error rates), superior to both regarding learnability and satisfaction but not effciency.}}, author = {{Schryen, Guido and Wagner, Gerit and Schlegel, Alexander}}, journal = {{Computers & Security}}, keywords = {{CAPTCHA, Usability, Facial features, Gender classiffcation, Age classification, Face recognition reverse Turing test}}, number = {{July}}, pages = {{95--116}}, publisher = {{Elsevier}}, title = {{{Development of two novel face-recognition CAPTCHAs: a security and usability study}}}, volume = {{60}}, year = {{2016}}, } @inproceedings{5678, abstract = {{Many academic disciplines - including information systems, computer science, and operations management - face scheduling problems as important decision making tasks. Since many scheduling problems are NP-hard in the strong sense, there is a need for developing solution heuristics. For scheduling problems with setup times on unrelated parallel machines, there is limited research on solution methods and to the best of our knowledge, parallel computer architectures have not yet been taken advantage of. We address this gap by proposing and implementing a new solution heuristic and by testing different parallelization strategies. In our computational experiments, we show that our heuristic calculates near-optimal solutions even for large instances and that computing time can be reduced substantially by our parallelization approach.}}, author = {{Rauchecker, Gerhard and Schryen, Guido}}, booktitle = {{Australasian Conference on Information Systems}}, keywords = {{scheduling, decision support, heuristic, high performance computing, parallel algorithms}}, pages = {{1--13}}, title = {{{High-Performance Computing for Scheduling Decision Support: A Parallel Depth-First Search Heuristic}}}, year = {{2015}}, } @article{5679, abstract = {{Cloud computing promises the flexible delivery of computing services in a pay-as-you-go manner. It allows customers to easily scale their infrastructure and save on the overall cost of operation. However Cloud service offerings can only thrive if customers are satisfied with service performance. Allow-ing instantaneous access and flexible scaling while maintaining the service levels and offering competitive prices poses a significant challenge to Cloud Computing providers. Furthermore services will remain available in the long run only if this business generates a stable revenue stream. To address these challenges we introduce novel policy-based service admission control mod-els that aim at maximizing the revenue of Cloud providers while taking in-formational uncertainty regarding resource requirements into account. Our evaluation shows that policy-based approaches statistically significantly out-perform first come first serve approaches, which are still state of the art. Furthermore the results give insights in how and to what extent uncertainty has a negative impact on revenue.}}, author = {{Püschel, Tim and Schryen, Guido and Hristova, Diana and Neumann, Dirk}}, journal = {{European Journal of Operational Research}}, keywords = {{admission control, informational uncertainty, revenue management, cloud computing}}, number = {{2}}, pages = {{637--647}}, publisher = {{Elsevier}}, title = {{{Revenue Management for Cloud Computing Providers: Decision Models for Service Admission Control under Non-probabilistic Uncertainty}}}, volume = {{244}}, year = {{2015}}, }