@article{54181, author = {{Tavana, Madjid and Govindan, Kannan and Nasr, Arash Khalili and Heidary, Mohammad Saeed and Mina, Hassan}}, issn = {{0254-5330}}, journal = {{Annals of Operations Research}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{A mathematical programming approach for equitable COVID-19 vaccine distribution in developing countries}}}, doi = {{10.1007/s10479-021-04130-z}}, year = {{2021}}, } @article{54191, author = {{Amoozad Mahdiraji, Hannan and Tavana, Madjid and Mahdiani, Pouya and Abbasi Kamardi, Ali Asghar}}, issn = {{1463-5771}}, journal = {{Benchmarking: An International Journal}}, number = {{2}}, pages = {{456--495}}, publisher = {{Emerald}}, title = {{{A multi-attribute data mining model for rule extraction and service operations benchmarking}}}, doi = {{10.1108/bij-03-2021-0127}}, volume = {{29}}, 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{53903, author = {{Hajipour, Vahid and Tavana, Madjid and Santos-Arteaga, Francisco J and Alinezhad, Alireza and Di Caprio, Debora}}, issn = {{2288-5048}}, journal = {{Journal of Computational Design and Engineering}}, number = {{4}}, pages = {{469--488}}, publisher = {{Oxford University Press (OUP)}}, title = {{{An efficient controlled elitism non-dominated sorting genetic algorithm for multi-objective supplier selection under fuzziness}}}, doi = {{10.1093/jcde/qwaa039}}, volume = {{7}}, year = {{2020}}, } @article{53902, author = {{Aziz, Azmin Azliza and Mousavi, Seyed Mohsen and Tavana, Madjid and Niaki, Seyed Taghi Akhavan}}, issn = {{2330-2674}}, journal = {{International Journal of Systems Science: Operations & Logistics}}, number = {{2}}, pages = {{172--181}}, publisher = {{Informa UK Limited}}, title = {{{An investigation of the robustness in the Travelling Salesman problem routes using special structured matrices}}}, doi = {{10.1080/23302674.2018.1551584}}, volume = {{7}}, year = {{2020}}, } @article{53905, author = {{Santos-Arteaga, Francisco Javier and Tavana, Madjid and Torrecillas, Celia and Di Caprio, Debora}}, issn = {{2029-4913}}, journal = {{Technological and Economic Development of Economy}}, number = {{6}}, pages = {{1366--1398}}, publisher = {{Vilnius Gediminas Technical University}}, title = {{{INNOVATION DYNAMICS AND FINANCIAL STABILITY: A EUROPEAN UNION PERSPECTIVE}}}, doi = {{10.3846/tede.2020.13521}}, volume = {{26}}, year = {{2020}}, } @article{53898, author = {{Jafari Songhori, Mohsen and Tavana, Madjid and Terano, Takao}}, issn = {{1381-298X}}, journal = {{Computational and Mathematical Organization Theory}}, number = {{1}}, pages = {{88--122}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Product development team formation: effects of organizational- and product-related factors}}}, doi = {{10.1007/s10588-019-09302-8}}, volume = {{26}}, year = {{2020}}, } @article{53904, author = {{Kaviani, Mohamad Amin and Tavana, Madjid and Kowsari, Fatemeh and Rezapour, Roghayeh}}, issn = {{1463-5771}}, journal = {{Benchmarking: An International Journal}}, number = {{6}}, pages = {{1929--1949}}, publisher = {{Emerald}}, title = {{{Supply chain resilience: a benchmarking model for vulnerability and capability assessment in the automotive industry}}}, doi = {{10.1108/bij-01-2020-0049}}, volume = {{27}}, year = {{2020}}, } @article{53906, author = {{Tavana, Madjid and Shaabani, Akram and Javier Santos-Arteaga, Francisco and Raeesi Vanani, Iman}}, issn = {{1996-1073}}, journal = {{Energies}}, number = {{15}}, publisher = {{MDPI AG}}, title = {{{A Review of Uncertain Decision-Making Methods in Energy Management Using Text Mining and Data Analytics}}}, doi = {{10.3390/en13153947}}, volume = {{13}}, year = {{2020}}, } @article{53900, author = {{Tavana, Madjid and Hajipour, Vahid and Oveisi, Shahrzad}}, issn = {{2542-6605}}, journal = {{Internet of Things}}, publisher = {{Elsevier BV}}, title = {{{IoT-based enterprise resource planning: Challenges, open issues, applications, architecture, and future research directions}}}, doi = {{10.1016/j.iot.2020.100262}}, volume = {{11}}, year = {{2020}}, } @article{53899, author = {{Tavana, Madjid and Amoozad Mahdiraji, Hannan and Beheshti, Moein and Abbasi Kamardi, Ali‐Asghar}}, issn = {{0143-6570}}, journal = {{Managerial and Decision Economics}}, number = {{7}}, pages = {{1365--1384}}, publisher = {{Wiley}}, title = {{{Optimal strategic alliance in multi‐echelon supply chains with open innovation}}}, doi = {{10.1002/mde.3181}}, volume = {{41}}, year = {{2020}}, } @article{53901, author = {{Tavana, Madjid and Hajipour, Vahid}}, issn = {{1463-5771}}, journal = {{Benchmarking: An International Journal}}, number = {{1}}, pages = {{81--136}}, publisher = {{Emerald}}, title = {{{A practical review and taxonomy of fuzzy expert systems: methods and applications}}}, doi = {{10.1108/bij-04-2019-0178}}, volume = {{27}}, year = {{2020}}, }