TY - JOUR A1 - Alnoor, Alhamzah A1 - Tiberius, Victor A1 - Atiyah, Abbas Gatea A1 - Khaw, Khai Wah A1 - Yin, Teh Sin A1 - Chew, XinYing A1 - Abbas, Sammar T1 - How positive and negative electronic word of mouth (eWOM) affects customers’ intention to use social commerce? BT - a dual-stage multi group-SEM and ANN analysis JF - International journal of human computer interaction N2 - Advances in Web 2.0 technologies have led to the widespread assimilation of electronic commerce platforms as an innovative shopping method and an alternative to traditional shopping. However, due to pro-technology bias, scholars focus more on adopting technology, and slightly less attention has been given to the impact of electronic word of mouth (eWOM) on customers’ intention to use social commerce. This study addresses the gap by examining the intention through exploring the effect of eWOM on males’ and females’ intentions and identifying the mediation of perceived crowding. To this end, we adopted a dual-stage multi-group structural equation modeling and artificial neural network (SEM-ANN) approach. We successfully extended the eWOM concept by integrating negative and positive factors and perceived crowding. The results reveal the causal and non-compensatory relationships between the constructs. The variables supported by the SEM analysis are adopted as the ANN model’s input neurons. According to the natural significance obtained from the ANN approach, males’ intentions to accept social commerce are related mainly to helping the company, followed by core functionalities. In contrast, females are highly influenced by technical aspects and mishandling. The ANN model predicts customers’ intentions to use social commerce with an accuracy of 97%. We discuss the theoretical and practical implications of increasing customers’ intention toward social commerce channels among consumers based on our findings. Y1 - 2022 U6 - https://doi.org/10.1080/10447318.2022.2125610 SN - 1044-7318 SN - 1532-7590 SP - 1 EP - 30 PB - Taylor & Francis CY - New York ER - TY - JOUR A1 - Bender, Benedict A1 - Körppen, Tim T1 - Integriert statt isoliert BT - Technologien für die erfolgreiche Umsetzung von datengetriebenem Management JF - Digital business : cloud N2 - Dass Daten und Analysen Innovationstreiber sind und nicht mehr nur einen Hygienefaktor darstellen, haben viele Unternehmen erkannt. Um Potenziale zu heben, müssen Daten zielführend integriert werden. Komplexe Systemlandschaften und isolierte Datenbestände erschweren dies. Technologien für die erfolgreiche Umsetzung von datengetriebenem Management müssen richtig eingesetzt werden. N2 - The fact that data and analyses are innovation drivers and no longer just represent a hygiene factor is nowadays understood by many companies. An important step for the development of this hidden potential is the target-oriented utilization of the existing data stocks in one's own company. In doing so, many companies face the hurdle of complex system landscapes and isolated data stocks. This article provides an overview of solutions for analysis-oriented data integration and helps decision-makers to select a suitable technology for their own company. KW - data analytics KW - data requirements KW - software selection Y1 - 2022 UR - https://www.wiso-net.de/document/DBC__584ddfcbfbc5ff400cb2ffb0f31eba6e6903fb3d SN - 2510-344X VL - 26 IS - 1 SP - 26 EP - 27 PB - WIN-Verlag GmbH & Co. KG CY - Vaterstetten ER - TY - JOUR A1 - Benlian, Alexander A1 - Wiener, Martin A1 - Cram, W. Alec A1 - Krasnova, Hanna A1 - Maedche, Alexander A1 - Mohlmann, Mareike A1 - Recker, Jan A1 - Remus, Ulrich T1 - Algorithmic management BT - bright and dark sides, practical implications, and research opportunities JF - Business and information systems engineering Y1 - 2022 U6 - https://doi.org/10.1007/s12599-022-00764-w SN - 2363-7005 SN - 1867-0202 VL - 64 IS - 6 SP - 825 EP - 839 PB - Springer Gabler CY - Wiesbaden ER - TY - JOUR A1 - Bläsius, Thomas A1 - Friedrich, Tobias A1 - Lischeid, Julius A1 - Meeks, Kitty A1 - Schirneck, Friedrich Martin T1 - Efficiently enumerating hitting sets of hypergraphs arising in data profiling JF - Journal of computer and system sciences : JCSS N2 - The transversal hypergraph problem asks to enumerate the minimal hitting sets of a hypergraph. If the solutions have bounded size, Eiter and Gottlob [SICOMP'95] gave an algorithm running in output-polynomial time, but whose space requirement also scales with the output. We improve this to polynomial delay and space. Central to our approach is the extension problem, deciding for a set X of vertices whether it is contained in any minimal hitting set. We show that this is one of the first natural problems to be W[3]-complete. We give an algorithm for the extension problem running in time O(m(vertical bar X vertical bar+1) n) and prove a SETH-lower bound showing that this is close to optimal. We apply our enumeration method to the discovery problem of minimal unique column combinations from data profiling. Our empirical evaluation suggests that the algorithm outperforms its worst-case guarantees on hypergraphs stemming from real-world databases. KW - Data profiling KW - Enumeration algorithm KW - Minimal hitting set KW - Transversal hypergraph KW - Unique column combination KW - W[3]-Completeness Y1 - 2022 U6 - https://doi.org/10.1016/j.jcss.2021.10.002 SN - 0022-0000 SN - 1090-2724 VL - 124 SP - 192 EP - 213 PB - Elsevier CY - San Diego ER - TY - JOUR A1 - Bonifati, Angela A1 - Mior, Michael J. A1 - Naumann, Felix A1 - Noack, Nele Sina T1 - How inclusive are we? BT - an analysis of gender diversity in database venues JF - SIGMOD record / Association for Computing Machinery, Special Interest Group on Management of Data N2 - ACM SIGMOD, VLDB and other database organizations have committed to fostering an inclusive and diverse community, as do many other scientific organizations. Recently, different measures have been taken to advance these goals, especially for underrepresented groups. One possible measure is double-blind reviewing, which aims to hide gender, ethnicity, and other properties of the authors.
We report the preliminary results of a gender diversity analysis of publications of the database community across several peer-reviewed venues, and also compare women's authorship percentages in both single-blind and double-blind venues along the years. We also obtained a cross comparison of the obtained results in data management with other relevant areas in Computer Science. Y1 - 2022 U6 - https://doi.org/10.1145/3516431.3516438 SN - 0163-5808 SN - 1943-5835 VL - 50 IS - 4 SP - 30 EP - 35 PB - Association for Computing Machinery CY - New York ER - TY - JOUR A1 - Chen, Junchao A1 - Lange, Thomas A1 - Andjelkovic, Marko A1 - Simevski, Aleksandar A1 - Lu, Li A1 - Krstić, Miloš T1 - Solar particle event and single event upset prediction from SRAM-based monitor and supervised machine learning JF - IEEE transactions on emerging topics in computing / IEEE Computer Society, Institute of Electrical and Electronics Engineers N2 - The intensity of cosmic radiation may differ over five orders of magnitude within a few hours or days during the Solar Particle Events (SPEs), thus increasing for several orders of magnitude the probability of Single Event Upsets (SEUs) in space-borne electronic systems. Therefore, it is vital to enable the early detection of the SEU rate changes in order to ensure timely activation of dynamic radiation hardening measures. In this paper, an embedded approach for the prediction of SPEs and SRAM SEU rate is presented. The proposed solution combines the real-time SRAM-based SEU monitor, the offline-trained machine learning model and online learning algorithm for the prediction. With respect to the state-of-the-art, our solution brings the following benefits: (1) Use of existing on-chip data storage SRAM as a particle detector, thus minimizing the hardware and power overhead, (2) Prediction of SRAM SEU rate one hour in advance, with the fine-grained hourly tracking of SEU variations during SPEs as well as under normal conditions, (3) Online optimization of the prediction model for enhancing the prediction accuracy during run-time, (4) Negligible cost of hardware accelerator design for the implementation of selected machine learning model and online learning algorithm. The proposed design is intended for a highly dependable and self-adaptive multiprocessing system employed in space applications, allowing to trigger the radiation mitigation mechanisms before the onset of high radiation levels. KW - Machine learning KW - Single event upsets KW - Random access memory KW - monitoring KW - machine learning algorithms KW - predictive models KW - space missions KW - solar particle event KW - single event upset KW - machine learning KW - online learning KW - hardware accelerator KW - reliability KW - self-adaptive multiprocessing system Y1 - 2022 U6 - https://doi.org/10.1109/TETC.2022.3147376 SN - 2168-6750 VL - 10 IS - 2 SP - 564 EP - 580 PB - Institute of Electrical and Electronics Engineers CY - [New York, NY] ER - TY - JOUR A1 - Gévay, Gábor E. A1 - Rabl, Tilmann A1 - Breß, Sebastian A1 - Madai-Tahy, Loránd A1 - Quiané-Ruiz, Jorge-Arnulfo A1 - Markl, Volker T1 - Imperative or functional control flow handling BT - why not the best of both worlds? JF - SIGMOD record / Association for Computing Machinery, Special Interest Group on Management of Data N2 - Modern data analysis tasks often involve control flow statements, such as the iterations in PageRank and K-means. To achieve scalability, developers usually implement these tasks in distributed dataflow systems, such as Spark and Flink. Designers of such systems have to choose between providing imperative or functional control flow constructs to users. Imperative constructs are easier to use, but functional constructs are easier to compile to an efficient dataflow job. We propose Mitos, a system where control flow is both easy to use and efficient. Mitos relies on an intermediate representation based on the static single assignment form. This allows us to abstract away from specific control flow constructs and treat any imperative control flow uniformly both when building the dataflow job and when coordinating the distributed execution. Y1 - 2022 U6 - https://doi.org/10.1145/3542700.3542715 SN - 0163-5808 VL - 51 IS - 1 SP - 60 EP - 67 PB - Association for Computing Machinery CY - New York ER - TY - CHAP A1 - Hagemann, Linus A1 - Abramova, Olga T1 - Crafting audience engagement in social media conversations BT - evidence from the U.S. 2020 presidential elections T2 - Proceedings of the 55th Hawaii International Conference on System Sciences N2 - Observing inconsistent results in prior studies, this paper applies the elaboration likelihood model to investigate the impact of affective and cognitive cues embedded in social media messages on audience engagement during a political event. Leveraging a rich dataset in the context of the 2020 U.S. presidential elections containing more than 3 million tweets, we found the prominence of both cue types. For the overall sample, positivity and sentiment are negatively related to engagement. In contrast, the post-hoc sub-sample analysis of tweets from famous users shows that emotionally charged content is more engaging. The role of sentiment decreases when the number of followers grows and ultimately becomes insignificant for Twitter participants with a vast number of followers. Prosocial orientation (“we-talk”) is consistently associated with more likes, comments, and retweets in the overall sample and sub-samples. KW - mediated conversation KW - big data KW - engagement KW - sentiment analysis KW - social media Y1 - 2022 SN - 978-0-9981331-5-7 SP - 3222 EP - 3231 PB - HICSS Conference Office University of Hawaii at Manoa CY - Honolulu ER - TY - JOUR A1 - Ihde, Sven A1 - Pufahl, Luise A1 - Völker, Maximilian A1 - Goel, Asvin A1 - Weske, Mathias T1 - A framework for modeling and executing task BT - specific resource allocations in business processes JF - Computing : archives for informatics and numerical computation N2 - As resources are valuable assets, organizations have to decide which resources to allocate to business process tasks in a way that the process is executed not only effectively but also efficiently. Traditional role-based resource allocation leads to effective process executions, since each task is performed by a resource that has the required skills and competencies to do so. However, the resulting allocations are typically not as efficient as they could be, since optimization techniques have yet to find their way in traditional business process management scenarios. On the other hand, operations research provides a rich set of analytical methods for supporting problem-specific decisions on resource allocation. This paper provides a novel framework for creating transparency on existing tasks and resources, supporting individualized allocations for each activity in a process, and the possibility to integrate problem-specific analytical methods of the operations research domain. To validate the framework, the paper reports on the design and prototypical implementation of a software architecture, which extends a traditional process engine with a dedicated resource management component. This component allows us to define specific resource allocation problems at design time, and it also facilitates optimized resource allocation at run time. The framework is evaluated using a real-world parcel delivery process. The evaluation shows that the quality of the allocation results increase significantly with a technique from operations research in contrast to the traditional applied rule-based approach. KW - Process Execution KW - Business Process Management KW - Resource Allocation KW - Resource Management KW - Activity-oriented Optimization Y1 - 2022 U6 - https://doi.org/10.1007/s00607-022-01093-2 SN - 0010-485X SN - 1436-5057 VL - 104 SP - 2405 EP - 2429 PB - Springer CY - Wien ER - TY - JOUR A1 - Kaya, Adem A1 - Freitag, Melina A. T1 - Conditioning analysis for discrete Helmholtz problems JF - Computers and mathematics with applications : an international journal N2 - In this paper, we examine conditioning of the discretization of the Helmholtz problem. Although the discrete Helmholtz problem has been studied from different perspectives, to the best of our knowledge, there is no conditioning analysis for it. We aim to fill this gap in the literature. We propose a novel method in 1D to observe the near-zero eigenvalues of a symmetric indefinite matrix. Standard classification of ill-conditioning based on the matrix condition number is not true for the discrete Helmholtz problem. We relate the ill-conditioning of the discretization of the Helmholtz problem with the condition number of the matrix. We carry out analytical conditioning analysis in 1D and extend our observations to 2D with numerical observations. We examine several discretizations. We find different regions in which the condition number of the problem shows different characteristics. We also explain the general behavior of the solutions in these regions. KW - Helmholtz problem KW - Condition number KW - Ill-conditioning KW - Indefinite KW - matrices Y1 - 2022 U6 - https://doi.org/10.1016/j.camwa.2022.05.016 SN - 0898-1221 SN - 1873-7668 VL - 118 SP - 171 EP - 182 PB - Elsevier Science CY - Amsterdam ER -