@inproceedings{17140, author = {{Thiess, Tiemo and Müller, Oliver and Tonelli, Lorenzo}}, booktitle = {{International Conference on Wirtschaftsinformatik}}, title = {{{Design Principles for Explainable Sales Win-Propensity Prediction Systems}}}, doi = {{https://doi.org/10.30844/wi_2020_c8-thiess}}, 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}}, } @inproceedings{15499, author = {{Wolf, Verena and Lüttenberg, Hedda}}, booktitle = {{Proceedings of the 15th International Conference on Wirtschaftsinformatik}}, title = {{{Capabilities for Ambidextrous Innovation of Digital Service}}}, year = {{2020}}, } @inproceedings{15501, author = {{Wolf, Verena and Franke, Alena and Bartelheimer, Christian and Beverungen, Daniel}}, booktitle = {{Proceedings of the 15th International Conference on Wirtschaftsinformatik}}, title = {{{Establishing Smart Service Systems is a Challenge: A Case Study on Pitfalls and Implications}}}, 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}}, } @inproceedings{15210, author = {{Seutter, Janina and Neumann, Jürgen and Kundisch, Dennis}}, booktitle = {{Tagungsband der 15. Internationalen Tagung Wirtschaftsinformatik 2020 (WI)}}, location = {{Potsdam, Germany}}, title = {{{Nudging in Judging- Differences in Online Rating Behavior for Utilitarian and Hedonic Service Aspects}}}, year = {{2020}}, } @inproceedings{15211, author = {{Szopinski, Daniel and Schoormann, Thorsten and Kundisch, Dennis}}, booktitle = {{Tagungsband der 15. Internationalen Tagung Wirtschaftsinformatik 2020 (WI)}}, location = {{Potsdam, Germany}}, title = {{{Visualize different: Towards researching the fit between taxonomy visualizations and taxonomy tasks}}}, year = {{2020}}, } @inproceedings{15225, author = {{Poniatowski, Martin and Neumann, Jürgen}}, booktitle = {{Tagungsband der 15. Internationalen Tagung Wirtschaftsinformatik 2020 (WI)}}, location = {{Potsdam, Germany}}, title = {{{You Write What You Are - Exploring the Relationship between Online Reviewers' Personality Traits and Their Reviewing Behavior}}}, 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}}, } @inproceedings{16285, abstract = {{To decide in which part of town to open stores, high street retailers consult statistical data on customers and cities, but they cannot analyze their customers’ shopping behavior and geospatial features of a city due to missing data. While previous research has proposed recommendation systems and decision aids that address this type of decision problem – including factory location and assortment planning – there currently is no design knowledge available to prescribe the design of city center area recommendation systems (CCARS). We set out to design a software prototype considering local customers’ shopping interests and geospatial data on their shopping trips for retail site selection. With real data on 500 customers and 1,100 shopping trips, we demonstrate and evaluate our IT artifact. Our results illustrate how retailers and public town center managers can use CCARS for spatial location selection, growing retailers’ profits and a city center’s attractiveness for its citizens.}}, author = {{zur Heiden, Philipp and Berendes, Carsten Ingo and Beverungen, Daniel}}, booktitle = {{Proceedings of the 15th International Conference on Wirtschaftsinformatik}}, keywords = {{Town Center Management, High Street Retail, Recommender Systems, Geospatial Recommendations, Design Science Research}}, location = {{Potsdam}}, title = {{{Designing City Center Area Recommendation Systems }}}, doi = {{doi.org/10.30844/wi_2020_e1-heiden}}, year = {{2020}}, } @inproceedings{16300, author = {{Wolf, Verena and Bartelheimer, Christian}}, booktitle = {{16th International Research Conference in Service Management}}, location = {{ La Londe les Maures}}, title = {{{Transformation of Actors’ Roles in Service Systems: A Multi-Level Analysis }}}, year = {{2020}}, } @inproceedings{13584, author = {{Szopinski, Daniel and Schoormann, Thorsten and Kundisch, Dennis}}, booktitle = {{Proceedings of the 53rd Hawaii International Conference on System Sciences (HICSS)}}, location = {{Maui, Hawaii}}, title = {{{Criteria as a prelude for guiding taxonomy evaluation}}}, 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{13770, author = {{Karl, Holger and Kundisch, Dennis and Meyer auf der Heide, Friedhelm and Wehrheim, Heike}}, journal = {{Business & Information Systems Engineering}}, number = {{6}}, pages = {{467--481}}, publisher = {{Springer}}, title = {{{A Case for a New IT Ecosystem: On-The-Fly Computing}}}, doi = {{10.1007/s12599-019-00627-x}}, volume = {{62}}, year = {{2020}}, } @inproceedings{17095, abstract = {{In order to sustain their competitive advantage, data driven organizations must continue investing in business intelligence and analytics (BI&A) while mitigating inherent cost increases. Research shows that examining outlays by individual BI&A artifact (e.g. reports, analytics) is necessary, but introduction in practice is cumbersome and adoption is slow. BI&A service-oriented cost allocation (BIASOCA) represents an improvement to this situation. This approach enables to render the BI&A cost pool accountable and improves cost transparency, which leads to a higher BI&A penetration of economically viable applications in organizations. Against this background, this paper aims at designing and implementing BIASOCA in a medium-sized company. To record organizational impact and increase customer acceptance, this study is carried out as action design research (ADR). Our findings indicate improvements in BI&A management from working with consumers to locate cost savings and drivers. After invoicing, consumers’ BI&A awareness increased, releasing resources while also making a better understanding of BIASOCA necessary. We detail how to implement BIASOCA in a real-life setting and the challenges attendant in so doing. Our research contributes to theory and practice with a set of design principles highlighting, besides the accuracy of cost accounting, the importance of collaboration, model comprehensibility and strategic alignment.}}, author = {{Grytz, Raphael and Krohn-Grimberghe, Artus and Müller, Oliver}}, booktitle = {{European Conference on Information Systems}}, title = {{{Business Intelligence & Analytics Cost Accounting: An Action Design Research Approach}}}, 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{35723, abstract = {{The development of renewable energies and smart mobility has profoundly impacted the future of the distribution grid. An increasing bidirectional energy flow stresses the assets of the distribution grid, especially medium voltage switchgear. This calls for improved maintenance strategies to prevent critical failures. Predictive maintenance, a maintenance strategy relying on current condition data of assets, serves as a guideline. Novel sensors covering thermal, mechanical, and partial discharge aspects of switchgear, enable continuous condition monitoring of some of the most critical assets of the distribution grid. Combined with machine learning algorithms, the demands put on the distribution grid by the energy and mobility revolutions can be handled. In this paper, we review the current state-of-the-art of all aspects of condition monitoring for medium voltage switchgear. Furthermore, we present an approach to develop a predictive maintenance system based on novel sensors and machine learning. We show how the existing medium voltage grid infrastructure can adapt these new needs on an economic scale.}}, author = {{Hoffmann, Martin W. and Wildermuth, Stephan and Gitzel, Ralf and Boyaci, Aydin and Gebhardt, Jörg and Kaul, Holger and Amihai, Ido and Forg, Bodo and Suriyah, Michael and Leibfried, Thomas and Stich, Volker and Hicking, Jan and Bremer, Martin and Kaminski, Lars and Beverungen, Daniel and zur Heiden, Philipp and Tornede, Tanja}}, issn = {{1424-8220}}, journal = {{Sensors}}, keywords = {{Electrical and Electronic Engineering, Biochemistry, Instrumentation, Atomic and Molecular Physics, and Optics, Analytical Chemistry}}, number = {{7}}, publisher = {{MDPI AG}}, title = {{{Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions}}}, doi = {{10.3390/s20072099}}, volume = {{20}}, year = {{2020}}, } @article{17862, author = {{Schlangenotto, Darius and Schnedler, Wendelin and Vadovic, Radovan}}, journal = {{Games}}, number = {{3}}, pages = {{1----24}}, title = {{{Against All Odds: Tentative Steps Toward Efficient Information Sharing in Groups}}}, volume = {{11}}, year = {{2020}}, }