@inproceedings{BenderWinterSchmidtetal.2024, author = {Bender, Benedict and Winter, Robert and Schmidt, Pamela and Narasimhan, Sathya}, title = {Minitrack introduction: Enterprise Ecosystems}, series = {Proceedings of the 57th Annual Hawaii International Conference on System Sciences}, booktitle = {Proceedings of the 57th Annual Hawaii International Conference on System Sciences}, editor = {Bui, Tung X.}, publisher = {Hawaii International Conference on System Sciences}, address = {Honolulu, HI}, isbn = {978-0-9981331-7-1}, issn = {2572-6862}, pages = {6370 -- 6371}, year = {2024}, abstract = {While Information Systems Research exists at the individual and workgroup levels, research on IS at the enterprise level is less common. The potential synergies between the study of enterprise systems (ES) and related fields have been underexplored and often treated as separate entities. The ongoing challenge is to seamlessly integrate technological advances and align business processes across organizations. While systems integration within an organization is common, changes occur when industry and ecosystem perspectives come into play. The four selected papers address different facets of the future role of enterprise ecosystems, including implementation challenges, ecosystem boundaries, and B2B platform specifics.}, language = {en} } @article{SchoknechtRoehmSchlesewskyetal.2022, author = {Schoknecht, Pia and Roehm, Dietmar and Schlesewsky, Matthias and Bornkessel-Schlesewsky, Ina}, title = {The interaction of predictive processing and similarity-based retrieval interference}, series = {Language, cognition and neuroscience}, volume = {37}, journal = {Language, cognition and neuroscience}, number = {7}, publisher = {Routledge, Taylor \& Francis Group}, address = {Abingdon}, issn = {2327-3798}, doi = {10.1080/23273798.2022.2026421}, pages = {883 -- 901}, year = {2022}, abstract = {Language processing requires memory retrieval to integrate current input with previous context and making predictions about upcoming input. We propose that prediction and retrieval are two sides of the same coin, i.e. functionally the same, as they both activate memory representations. Under this assumption, memory retrieval and prediction should interact: Retrieval interference can only occur at a word that triggers retrieval and a fully predicted word would not do that. The present study investigated the proposed interaction with event-related potentials (ERPs) during the processing of sentence pairs in German. Predictability was measured via cloze probability. Memory retrieval was manipulated via the position of a distractor inducing proactive or retroactive similarity-based interference. Linear mixed model analyses provided evidence for the hypothesised interaction in a broadly distributed negativity, which we discuss in relation to the interference ERP literature. Our finding supports the proposal that memory retrieval and prediction are functionally the same.}, language = {en} } @article{NicenboimVasishthRoesler2020, author = {Nicenboim, Bruno and Vasishth, Shravan and R{\"o}sler, Frank}, title = {Are words pre-activated probabilistically during sentence comprehension?}, series = {Neuropsychologia : an international journal in behavioural and cognitive neuroscience}, volume = {142}, journal = {Neuropsychologia : an international journal in behavioural and cognitive neuroscience}, publisher = {Elsevier Science}, address = {Oxford}, issn = {0028-3932}, doi = {10.1016/j.neuropsychologia.2020.107427}, pages = {27}, year = {2020}, abstract = {Several studies (e.g., Wicha et al., 2003b; DeLong et al., 2005) have shown that readers use information from the sentential context to predict nouns (or some of their features), and that predictability effects can be inferred from the EEG signal in determiners or adjectives appearing before the predicted noun. While these findings provide evidence for the pre-activation proposal, recent replication attempts together with inconsistencies in the results from the literature cast doubt on the robustness of this phenomenon. Our study presents the first attempt to use the effect of gender on predictability in German to study the pre-activation hypothesis, capitalizing on the fact that all German nouns have a gender and that their preceding determiners can show an unambiguous gender marking when the noun phrase has accusative case. Despite having a relatively large sample size (of 120 subjects), both our preregistered and exploratory analyses failed to yield conclusive evidence for or against an effect of pre-activation. The sign of the effect is, however, in the expected direction: the more unexpected the gender of the determiner, the larger the negativity. The recent, inconclusive replication attempts by Nieuwland et al. (2018) and others also show effects with signs in the expected direction. We conducted a Bayesian random-ef-fects meta-analysis using our data and the publicly available data from these recent replication attempts. Our meta-analysis shows a relatively clear but very small effect that is consistent with the pre-activation account and demonstrates a very important advantage of the Bayesian data analysis methodology: we can incrementally accumulate evidence to obtain increasingly precise estimates of the effect of interest.}, language = {en} } @article{GronauBenderBertheauetal.2021, author = {Gronau, Norbert and Bender, Benedict and Bertheau, Clementine and Lauppe, Hannah}, title = {Robotic Process Automation statt neuem ERP-System}, series = {ERP-Management : Auswahl, Einf{\"u}hrung und Betrieb von ERP-Systemen}, volume = {17}, journal = {ERP-Management : Auswahl, Einf{\"u}hrung und Betrieb von ERP-Systemen}, number = {1}, publisher = {GITO mbH Verlag}, address = {Berlin}, issn = {1860-6725}, doi = {10.30844/ERP_21-1_29-32}, pages = {29 -- 32}, year = {2021}, abstract = {Robotic Process Automation (RPA) steht f{\"u}r die softwareunterst{\"u}tzte Bedienung von Softwarel{\"o}sungen {\"u}ber deren Benutzeroberfl{\"a}che. Das prim{\"a}re Ziel, das mit RPA erreicht werden soll, ist die automatisierte Ausf{\"u}hrung von Routineaufgaben, die bisher einen menschlichen Eingriff erforderten. Das Potenzial von RPA, Prozesse langfristig zu verbessern, ist allerdings stark begrenzt. Die Automatisierung von Prozessen und die {\"U}berbr{\"u}ckung von Medienbr{\"u}chen auf der Front-End-Ebene f{\"u}hrt zu einer Vielzahl von Abh{\"a}ngigkeiten und Bedingungen, die in diesem Beitrag zusammengefasst werden. Der Weg zu einer nachhaltigen Unternehmensarchitektur (bestehend aus Prozessen und Systemen) erfordert offene, adaptive Systeme mit moderner Architektur, die sich durch ein hohes Maß an Interoperabilit{\"a}t auf verschiedenen Ebenen auszeichnen.}, language = {de} } @article{HodappGrimm2021, author = {Hodapp, Alice and Grimm, Sabine}, title = {Neural signatures of temporal regularity and recurring patterns in random tonal sound sequences}, series = {European journal of neuroscience : EJN / European Neuroscience Association}, volume = {53}, journal = {European journal of neuroscience : EJN / European Neuroscience Association}, number = {8}, publisher = {Wiley}, address = {Oxford}, issn = {0953-816X}, doi = {10.1111/ejn.15123}, pages = {2740 -- 2754}, year = {2021}, abstract = {The auditory system is highly sensitive to recurring patterns in the acoustic input - even in otherwise unstructured material, such as white noise or random tonal sequences. Electroencephalography (EEG) research revealed a characteristic negative potential to periodically recurring auditory patterns - a response, which has been interpreted as memory trace-related and specific, rather than as a sign of periodicity-driven entrainment. Here, we aim to disentangle these two possible contributions by investigating the influence of a periodic sound sequence's inherent temporal regularity on event-related potentials. Participants were presented continuous sequences of short tones of random pitch, with some sequences containing a recurring pattern, and asked to indicate whether they heard a repetition. Patterns were either spaced equally across the random sequence (isochronous condition) or with a temporal jitter (jittered condition), which enabled us to differentiate between event-related potentials (and thus processing operations associated with a memory trace for a repeated pattern) and the periodic nature of the repetitions. A negative recurrence-related component could be observed independently of temporal regularity, was pattern-specific, and modulated by across trial repetition of the pattern. Critically, isochronous pattern repetition induced an additional early periodicity-related positive component, which started to build up already before the pattern onset and which was elicited undampedly even when the repeated pattern was occasionally not presented. This positive component likely reflects a sensory driven entrainment process that could be the foundation of a behavioural benefit in detecting temporally regular repetitions.}, language = {en} } @inproceedings{BenderBertheauGronau2021, author = {Bender, Benedict and Bertheau, Clementine and Gronau, Norbert}, title = {Future ERP Systems}, series = {Proceedings of the 23rd International Conference on Enterprise Information Systems (ICEIS 2021)}, booktitle = {Proceedings of the 23rd International Conference on Enterprise Information Systems (ICEIS 2021)}, number = {2}, publisher = {Science and Technology Publications}, address = {Set{\´u}bal}, isbn = {978-989-758-509-8}, issn = {2184-4992}, doi = {10.5220/0010477307760783}, pages = {776 -- 783}, year = {2021}, abstract = {This paper presents a research agenda on the current generation of ERP systems which was developed based on a literature review on current problems of ERP systems. The problems are presented following the ERP life cycle. In the next step, the identified problems are mapped on a reference architecture model of ERP systems that is an extension of the three-tier architecture model that is widely used in practice. The research agenda is structured according to the reference architecture model and addresses the problems identified regarding data, infrastructure, adaptation, processes, and user interface layer.}, language = {en} } @article{BenderGronau2020, author = {Bender, Benedict and Gronau, Norbert}, title = {Auswahl von ERP-Systemen im Kontext von Individuall{\"o}sungen}, series = {ERP Management}, volume = {16}, journal = {ERP Management}, number = {4}, publisher = {Gito}, address = {Berlin}, issn = {1860-6725}, pages = {37 -- 40}, year = {2020}, abstract = {Die Auswahl von Standardsoftware stellt viele Unternehmen vor Herausforderungen. Gerade im deutschen Mittelstand kommen vermehrt eigenentwickelte Individuall{\"o}sungen zum Einsatz. Ent- sprechende Unternehmen sind daher nicht mit komplexen Soft- wareauswahlprojekten vertraut. Das breite Angebot an ERP-Systemen erschwert die Vergleichbarkeit der L{\"o}sungen und die zielgerichtete Auswahl des idealen Systems zus{\"a}tzlich.}, language = {de} } @book{Gronau2021, author = {Gronau, Norbert}, title = {ERP-Systeme}, series = {De Gruyter Studium}, journal = {De Gruyter Studium}, edition = {4. Auflage}, publisher = {De Gruyter Oldenbourg}, address = {Berlin ; Boston}, isbn = {978-3-11-066339-6}, issn = {2365-7197}, doi = {10.1515/9783110663396}, pages = {XIII, 372}, year = {2021}, language = {de} } @phdthesis{Schumacher2022, author = {Schumacher, Jochen}, title = {Entwicklung eines Industrie 4.0 Reifegradindex f{\"u}r produzierende Unternehmen}, doi = {10.25932/publishup-55464}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-554642}, school = {Universit{\"a}t Potsdam}, pages = {VI, 275}, year = {2022}, abstract = {Das Ziel dieser Arbeit ist die Entwicklung eines Industrie 4.0 Reifegradindex f{\"u}r produzierende Unternehmen (KMU und Mittelstand) mit diskreter Produktion. Die Motivation zu dieser Arbeit entstand aus dem Z{\"o}gern vieler Unternehmen - insbesondere KMU und Mittelstand - bei der Transformation in Richtung Industrie 4.0. Im Rahmen einer Marktstudie konnte belegt werden, dass 86 Prozent der befragten produzierenden Unternehmen kein f{\"u}r ihr Unternehmen geeignetes Industrie 4.0 Reifegradmodell gefunden haben, mit dem sie ihren Status Quo bewerten und Maßnahmen f{\"u}r einen h{\"o}heren Grad der Reife ableiten k{\"o}nnten. Die Bewertung bestehender Reifegradmodelle zeigte Defizite hinsichtlich der Industrie 4.0 Abdeckung, der Betrachtung der sozio-technischen Dimensionen Mensch, Technik und Organisation sowie der Betrachtung von Management und Unternehmenskultur. Basierend auf den aktuellen Industrie 4.0 Technologien und Handlungsbereichen wurde ein neues, modular aufgebautes Industrie 4.0 Reifegradmodell entwickelt, das auf einer ganzheitlichen Betrachtung aller sozio-technischen Dimensionen Mensch, Technik und Organisation sowie deren Schnittstellen basiert. Das Modell ermittelt neben dem Overall Industry 4.0 Maturity Index (OI4MI) vier weitere Indizes zur Bewertung der Industrie 4.0 Reife des Unternehmens. Das Modell wurde bei einem Unternehmen validiert und steht nun als Template f{\"u}r darauf aufbauende Forschungsarbeiten zur Verf{\"u}gung.}, language = {de} } @misc{BridwellCavanaghCollinsetal.2018, author = {Bridwell, David A. and Cavanagh, James F. and Collins, Anne G. E. and Nunez, Michael D. and Srinivasan, Ramesh and Stober, Sebastian and Calhoun, Vince D.}, title = {Moving Beyond ERP Components}, series = {Frontiers in human neuroscienc}, volume = {12}, journal = {Frontiers in human neuroscienc}, publisher = {Frontiers Research Foundation}, address = {Lausanne}, issn = {1662-5161}, doi = {10.3389/fnhum.2018.00106}, pages = {17}, year = {2018}, abstract = {Relationships between neuroimaging measures and behavior provide important clues about brain function and cognition in healthy and clinical populations. While electroencephalography (EEG) provides a portable, low cost measure of brain dynamics, it has been somewhat underrepresented in the emerging field of model-based inference. We seek to address this gap in this article by highlighting the utility of linking EEG and behavior, with an emphasis on approaches for EEG analysis that move beyond focusing on peaks or "components" derived from averaging EEG responses across trials and subjects (generating the event-related potential, ERP). First, we review methods for deriving features from EEG in order to enhance the signal within single-trials. These methods include filtering based on user-defined features (i.e., frequency decomposition, time-frequency decomposition), filtering based on data-driven properties (i.e., blind source separation, BSS), and generating more abstract representations of data (e.g., using deep learning). We then review cognitive models which extract latent variables from experimental tasks, including the drift diffusion model (DDM) and reinforcement learning (RL) approaches. Next, we discuss ways to access associations among these measures, including statistical models, data-driven joint models and cognitive joint modeling using hierarchical Bayesian models (HBMs). We think that these methodological tools are likely to contribute to theoretical advancements, and will help inform our understandings of brain dynamics that contribute to moment-to-moment cognitive function.}, language = {en} }