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This article describes a systematic literature search of research articles on the topics of ecological sustainability and production planning. Over 900 research articles deal intensively with these topics. These articles were catalogued and included in a database. They can be evaluated with an analysis tool, developed by the research group. The tool is available free of charge via a website of the research group.
In this paper a new method for placing bus stops is presented. The method is suitable for permanently installed new bus stops and temporarily chosen collection points for call busses as well. Moreover, our implementation of the Voronoi algorithm chooses new locations for bus stops in such a way that more bus stops are set in densely populated areas and less in less populated areas. To achieve this goal, a corresponding weighting is applied to each possible placement point, based on the number of inhabitants around this point and the points of interest, such as medical centers and department stores around this point. Using the area of Roding, a small town in Bavaria, for a case study, we show that our method is especially suitable for for rural areas, where there are few multi-family houses or apartment blocks and the area is not densely populated.
Although adopting Low Code Development Platforms (LCDPs) promises significant efficiency and effectiveness improvements for application development, its adoption still needs further empirical research. This paper uses a combinatorial approach to research LCDP adoption and presents the results of a multiple mini case study with 36 cases on LCDP adoption. A combination of the Socio-Technical Systems theory and the Technology-Organisational-Environment model is used as a theoretical lens. In this paper, we show that LCDP adoption is a multifaceted phenomenon and identify three archetypes for LCDP adoption (i.e., IT Resource Shortage Mitigators, Application Development Democratisers, and Synergy Realisers) and one archetype for LCDP non-adoption (i.e., Intricacy Adversaries). Each archetype can be interpreted as an individual path towards LCDP (non-)adoption. Based on these archetypes, we derive seven starting points for practitioners to adopt LCDPs in work systems. Moreover, by using the theoretical lenses, the paper shows that for an LCDP adoption to occur, an optimisation of the social and technical sub-systems is required.
In the realm of parallel computing, optimization plays a pivotal role in achieving efficient and scalable solutions. In this work, we present the parallelization of a hybrid genetic search for solving the Capacitated Vehicle Routing Problem with Pickup and Delivery (CVRPPD).It leverages the synergy between genetic algorithms and parallel computing to address the complex optimization problem. This hybrid algorithm combines a customized version of local search with a genetic algorithm to compute an effective solution. Our implementation makes use of the Message Passing Interface (MPI) for data distribution and parallel execution. In addition, we run multi-threaded processes on NVIDIA graphical processors using the CUDA technology, which further increases the computation speed and consequently minimizes the runtime. Parallelization also allows the best-improvement strategy to be used instead of the rst-improvement strategy while maintaining the same runtime. We store the resulting routes in a bus route database which we created as the basis of an extensive library of optimal routes for our specifc use case of optimizing bus routes in a rural area. The experimental results on real road data show that the parallel implementation of the Hybrid Genetic Search (HGS) achieves significant improvements in runtime over the sequential implementation above a certain problem size. We believe that our implementation of the parallel hybrid genetic search method can have a great in influence on optimization strategies in parallel computing and can also be applied to other subproblems of the VRP.
Adaptive Moment Estimation (Adam) is a very popular training algorithm for deep neural networks, implemented in many machine learning frameworks. To the best of the authors knowledge no complete convergence analysis exists for Adam. The contribution of this paper is a method for the local convergence analysis in batch mode for a deterministic fixed training set, which gives necessary conditions for the hyperparameters of the Adam algorithm. Due to the local nature of the arguments the objective function can be non-convex but must be at least twice continuously differentiable.
The endoscopic features associated with eosinophilic esophagitis (EoE) may be missed during routine endoscopy. We aimed to develop and evaluate an Artificial Intelligence (AI) algorithm for detecting and quantifying the endoscopic features of EoE in white light images, supplemented by the EoE Endoscopic Reference Score (EREFS). An AI algorithm (AI-EoE) was constructed and trained to differentiate between EoE and normal esophagus using endoscopic white light images extracted from the database of the University Hospital Augsburg. In addition to binary classification, a second algorithm was trained with specific auxiliary branches for each EREFS feature (AI-EoE-EREFS). The AI algorithms were evaluated on an external data set from the University of North Carolina, Chapel Hill (UNC), and compared with the performance of human endoscopists with varying levels of experience. The overall sensitivity, specificity, and accuracy of AI-EoE were 0.93 for all measures, while the AUC was 0.986. With additional auxiliary branches for the EREFS categories, the AI algorithm (AI-EoEEREFS) performance improved to 0.96, 0.94, 0.95, and 0.992 for sensitivity, specificity, accuracy, and AUC, respectively. AI-EoE and AI-EoE-EREFS performed significantly better than endoscopy beginners and senior fellows on the same set of images. An AI algorithm can be trained to detect and quantify endoscopic features of EoE with excellent performance scores. The addition of the EREFS criteria improved the performance of the AI algorithm, which performed significantly better than endoscopists with a lower or medium experience level.
Im vorliegenden Artikel werden Vorarbeiten zur Entwicklung eines Betriebsdatenverwaltungssystems für Intralogistikanlagen des Herstellers TGW Software Services beschrieben. Das beschriebene Vorgehen umfasst dabei im Wesentlichen vier Schritte.
Zunächst wird der aktuelle Stand in der Software des betrachteten Unternehmens hinsichtlich des Sammelns, Speicherns und Auswertens von Betriebsdaten analysiert.
Daran schließt sich eine Anforderungsanalyse für die Betriebsdatenverwaltung an. Zusammen mit den betroffenen Entwicklungsleitern werden die grundlegenden Ziele und Grenzen der zu entwickelnden Betriebsdatenverwaltung definiert. Es werden Quellen von Anforderungen für die Komponente gesammelt und alle funktionalen und nichtfunktionalen Anforderungen anhand dieser Quellen erarbeitet.
Basierend darauf wird ein erstes Modell erstellt, das die Entitäten, Beziehungen und Abläufe, die sich aus den ermittelten funktionalen Anforderungen ergeben, in konsolidierter Form zusammenfasst. Dieses wird zusammen mit einigen Überlegungen, die zu diesem Modell geführt haben, beschrieben.
Zuletzt werden dann verschiedene mögliche Konzepte zum grundlegenden technischen Aufbau einer Implementierung der Betriebsdatenverwaltung diskutiert, um schließlich anhand der definierten Qualitätsziele eine Empfehlung für einen Konzeptvorschlag abzugeben.
Ressourcenbelegungsplanungsprobleme haben fast immer exponentiell wachsende Lösungsräaume. Ausnahmen sind einfachste Ressourcenbelegungsplanungsprobleme die sich im wesentlichen durch Sortierverfahren optimal lösen lassen.
Dadurch sind Ressourcenbelegungsplanungsprobleme NP-vollständig. Nach der Literatur haben Lösungsräume von einigen NP-vollständigen
Optimierungsproblemen günstige Eigenschaften, die Metaheuristiken, wie genetische Algorithmen und lokale Suche, ausnutzen, um in vertretbarer
Rechenzeit gute Lösungen zu finden. Zu Ihrer Erkennung gibt es in der Literatur etablierte Analysemöglichkeiten. Sie werden in dieser Arbeit auf die Ressourcenbelegungsplanung übertragen und ihre Wirkung bzw. die auftretenden Schwierigkeiten werden anhand von einfachen Problemen aufgezeigt.
Im vorliegenden Artikel wird ein Konzept zur Erkennung von Problematiken vorgestellt, welches bei einem führenden Automobilproduzenten umgesetzt wurde. Mit Hilfe dieses Konzeptes, werden Auffälligkeiten anhand der Reklamationsquote bei Standorten, Touren, Händlern und Materialnummern aufgedeckt. Das übergeordnete Ziel, das mit einer effizienten Ursachenanalyse erreicht werden soll, besteht in der langfristigen Senkung der Reklamationsquote. Basis dieses Konzeptes bilden dabei die Reklamationen der einzelnen Händler. Anhand von statistischen Methoden wird eine Grundlage geschaffen, um die Ursachen und Auffälligkeiten der jeweiligen Akteure zu ermitteln. Dabei wird auch die Struktur der Auslieferung näher betrachtet, um Standorte, Touren und Händler zu identifizieren, die bei gleichen Auslieferbedingungen unterschiedliche Werte aufweisen.In den folgenden Ausführungen wird eine Methodik erläutert, die eine Abbildung der „normalen“ Reklamationsquote ermöglicht und gleichzeitig Fahrgebiete, Touren und Händler kennzeichnet, die von dieser Reklamationsquote „auffällig“ abweichen. Des Weiteren wird ein Konzept vorgestellt, welches Materialnummern, die plötzlich häufig reklamiert werden und in diesem Sinn auffällig sind, identifizieren kann. Bei dem Automobilproduzenten wurde durch beide aufgezeigt, wo die Ursachenanalyse am effektivsten anzusetzen ist, um damit eine konstante Senkung der Reklamationsquote und eine Steigerung der Kundenzufriedenheit zu erreichen.
Hintergrund
Impfungen stellen eine bedeutende Präventionsmaßnahme dar. Grundlegend für die Eindämmung der Coronapandemie mittels Durchimpfung der Gesellschaft ist eine ausgeprägte Impfbereitschaft.
Ziel der Arbeit
Die Impfbereitschaft mit einem COVID‑19-Vakzin (Impfstoff gegen das Coronavirus) und deren Einflussfaktoren werden anhand einer Zufallsstichprobe der Gesamtbevölkerung in Deutschland untersucht.
Material und Methoden
Die Studie basiert auf einer telefonischen Zufallsstichprobe und berücksichtigt ältere und vorerkrankte Personen ihrem Bevölkerungsanteil entsprechend. Die Ein-Themen-Bevölkerungsbefragung zur Impfbereitschaft (n = 2014) wurde im November/Dezember 2020 durchgeführt.
Ergebnisse
Die Impfbereitschaft in der Stichprobe liegt bei rund 67 %. Vorerfahrungen mit Impfungen moderieren die Impfbereitschaft. Sie steigt bei Zugehörigkeit zu einer Risikogruppe. Der Glaube an die Wirksamkeit alternativer Heilmethoden und Befürwortung alternativer Behandlungsverfahren geht mit geringerer Impfbereitschaft einher. Ältere Menschen sind impfbereiter, kovariierend mit ihrer Einschätzung höherer Gefährdung bei Erkrankung. Ebenso ist die Ablehnung einer Impfung mit der Überschätzung von Nebenwirkungen assoziiert.
Schlussfolgerung
Die Impfbereitschaft hängt mit Impferfahrungen und Einstellungen zu Gesundheitsbehandlungsverfahren allgemein zusammen. Die Überschätzung der Häufigkeit ernsthafter Nebenwirkungen bei Impfungen weist auf weit verbreitete Fehlinformationen hin.
Ziel der Studie:
Ziel der Studie ist die Messung des Stands der Digitalisierung und die mit einer Anbindung an die Telematikinfrastruktur verbundenen Chancen und Herausforderungen für Rehabilitationseinrichtungen.
Methodik:
Teilstandardisierte Online-Befragung bei Trägern von Rehabilitationseinrichtungen in Bayern (n=33). Der Fragebogen mit 36 Fragen beinhaltet eine leicht veränderte Skala auf Basis des „Electronic Medical Record Adoption Model (EMRAM)“.
Ergebnisse:
Der Digitalisierungsgrad wurde in 70 Prozent der Rehabilitationseinrichtungen mit Stufe 0 angegeben (Stufenmodell bis 7). Die Übermittlung patientenbezogener Daten (Eingang und Ausgang) erfolgt häufig analog, wohingegen die Verarbeitung innerhalb der Einrichtung in vielen Fällen bereits überwiegend digital ist. Beim Anschluss an die Telematikinfrastruktur wird hoher Aufwand bei der Installation, aber auch der Schulung des Personals und der Anpassung der Arbeitsorganisation gesehen.
Schlussfolgerung:
Durch Änderung der gesetzlich-finanziellen Lage in Deutschland eröffnen sich für Rehabilitationseinrichtungen neue Möglichkeiten einer verstärkten Digitalisierung. Hürden hängen mit Anforderungen an IT-Sicherheit, Schulung des Personals und sowie dem ebenfalls geringen Digitalisierungsstand bei Krankenhäusern und Ärzt*innen sowie Patient*innen zusammen, die eine digitale Datenübermittlung erschweren.
Metadata management constitutes a key prerequisite for enterprises as they engage in data analytics and governance. Today, however, the context of data is often only manually documented by subject matter experts, and lacks completeness and reliability due to the complex nature of data pipelines. Thus, collecting data lineage—describing the origin, structure, and dependencies of data—in an automated fashion increases quality of provided metadata and reduces manual effort, making it critical for the development and operation of data pipelines. In our practice report, we propose an end-to-end solution that digests lineage via (Py‑)Spark execution plans. We build upon the open-source component Spline, allowing us to reliably consume lineage metadata and identify interdependencies. We map the digested data into an expandable data model, enabling us to extract graph structures for both coarse- and fine-grained data lineage. Lastly, our solution visualizes the extracted data lineage via a modern web app, and integrates with BMW Group’s soon-to-be open-sourced Cloud Data Hub.
Within many real-world networks, the links between pairs of nodes change over time. Thus, there has been a recent boom in studying temporal graphs. Recognizing patterns in temporal graphs requires a proximity measure to compare different temporal graphs. To this end, we propose to study dynamic time warping on temporal graphs. We define the dynamic tem- poral graph warping (dtgw) distance to determine the dissimilarity of two temporal graphs. Our novel measure is flexible and can be applied in various application domains. We show that computing the dtgw-distance is a challenging (in general) NP-hard optimization problem and identify some polynomial-time solvable special cases. Moreover, we develop a quadratic programming formulation and an efficient heuristic. In experiments on real-world data, we show that the heuristic performs very well and that our dtgw-distance performs favorably in de-anonymizing networks compared to other approaches.
Computer-aided diagnosis using deep learning in the evaluation of early oesophageal adenocarcinoma
(2019)
Computer-aided diagnosis using deep learning (CAD-DL) may be an instrument to improve endoscopic assessment of Barrett’s oesophagus
(BE) and early oesophageal adenocarcinoma (EAC). Based on still images from two databases, the diagnosis of EAC by CAD-DL reached sensitivities/specificities of 97%/88% (Augsburg data) and 92%/100% (Medical Image Computing and Computer-Assisted Intervention [MICCAI]
data) for white light (WL) images and 94%/80% for narrow band images (NBI) (Augsburg data), respectively. Tumour margins delineated by
experts into images were detected satisfactorily with a Dice coefficient (D) of 0.72. This could be a first step towards CAD-DL for BE assessment. If developed further, it could become a useful
adjunctive tool for patient management.
Even though artificial intelligence and machine learning have demonstrated remarkable performances in medical image computing, their level of accountability and transparency must be provided in such evaluations. The reliability related to machine learning predictions must be explained and interpreted, especially if diagnosis support is addressed. For this task, the black-box nature of deep learning techniques must be lightened up to transfer its promising results into clinical practice. Hence, we aim to investigate the use of explainable artificial intelligence techniques to quantitatively highlight discriminative regions during the classification of earlycancerous tissues in Barrett’s esophagus-diagnosed patients. Four Convolutional Neural Network models (AlexNet, SqueezeNet, ResNet50, and VGG16) were analyzed using five different interpretation techniques (saliency, guided backpropagation, integrated gradients, input × gradients, and DeepLIFT) to compare their agreement with experts’ previous annotations of cancerous tissue. We could show that saliency attributes match best with the manual experts’ delineations. Moreover, there is moderate to high correlation between the sensitivity of a model and the human-and-computer agreement. The results also lightened that the higher the model’s sensitivity, the stronger the correlation of human and computational segmentation agreement. We observed a relevant relation between computational learning and experts’ insights, demonstrating how human knowledge may influence the correct computational learning.
In this article, we discuss energy consumption of producing firms on aggregate production planning. While almost constant energy consumption can be the case for a producing firm, highly fluctuating energy demand can occur as well. Together with volatile energy supply, e.g. due to renewable energy sources, this combination of fluctuating energy supply and demand can result in planning uncertainty and high energy costs. We propose different case studies in which such high deviation in the electricity consumption of a producing firm occurs due to aggregate production planning without appropriate consideration of energy consumption.
Nach einer Fraktur ist Mobilisierung Behandlungsziel und Therapiesäule. Das Festlegen von Outcomes basiert jedoch auf vielen Unsicherheiten, da Assessments nicht für alle Patient/-innen geeignet sind. Sie können agesabhängig beeinflusst und subjektiv geprägt sein. Sensorbasiertes Bewegungsmonitoring bietet eine Ergänzung zur Operationalisierung der Gehfähigkeit. Für Längsschnittuntersuchungen, die auch im häuslichen Umfeld durchgeführt werden, eignet sich die tägliche Schrittzahl als Variable. Sie kann durch einen handelsüblichen Fitnesstracker beobachtet
werden.
Beim Edelmetallcontrolling von Infineon sind Fehler nur mit hohem Aufwand analysierbar und es bewirkt widersprechende Berechnungshinweise. Alle vier Perspektiven des Edelmetallcontrollings werden verbessert und als einzige Datenquelle wird die von SAP festgesetzt.
Weitere Verbesserungen werden durch die Umwandlung einer monatlichen
Kursänderungserhebung in eine jährliche, durch die Verwendung des Marktwerts für den Bestandswert sowie durch Ermittlung eines
Normwerts für eine jährliche Recyclingquote erzielt.
Flexibility and in particular volume flexibility is an important topic for industrial manufacturing companies. In this context, the harmonization of the available and required capacity is a central task, especially with increasing fluctuations in customer demand. In classical approaches , this is considered only by the use of additional capacities and there are only a few approaches that combine aspects of personnel planning with production planning. Therefore, this article presents a linear optimization model for master production scheduling that includes aspects of personnel requirements planning. It is used to investigate different strategies for the use of overtime and temporary workers in order to achieve different levels of volume flexibility. With regard to the monetary and social impacts, the results indicate that overtime has a stronger influence to achieve volume flexibility than the use of temporary workers. However, both are affected by substantial deficits in human working conditions. But the results also imply a promising potential for improving the social aspects without a significant increase in costs.
Die Gestaltung der Distributionsflächen der Werksversandstellen bei der BMW Group resultiert aus unterschiedlichen und meist werksspezifischen Gegebenheiten. Im Zuge eines Referenzprojektes sollen einheitliche Standards und Vorgehensweisen für die Entwicklung einer Stellplatzorganisation untersucht und festgelegt werden. Im Rahmen dieses Projekts wird analysiert, worauf bei einer Lagergestaltung im Allgemeinen zu achten ist und wie diese Kriterien im Falle der Werksversandstellen im Speziellen umgesetzt werden können. Zusätzlich behandelt dieses Projekt auch die computerunterstützte Betrachtung der Lager- bzw. Stellplatzverwaltung.
Semantic segmentation is an essential task in medical imaging research. Many powerful deep-learning-based approaches can be employed for this problem, but they are dependent on the availability of an expansive labeled dataset. In this work, we augment such supervised segmentation models to be suitable for learning from unlabeled data. Our semi-supervised approach, termed Error-Correcting Mean-Teacher, uses an exponential moving average model like the original Mean Teacher but introduces our new paradigm of error correction. The original segmentation network is augmented to handle this secondary correction task. Both tasks build upon the core feature extraction layers of the model. For the correction task, features detected in the input image are fused with features detected in the predicted segmentation and further processed with task-specific decoder layers. The combination of image and segmentation features allows the model to correct present mistakes in the given input pair. The correction task is trained jointly on the labeled data. On unlabeled data, the exponential moving average of the original network corrects the student’s prediction. The combined outputs of the students’ prediction with the teachers’ correction form the basis for the semi-supervised update. We evaluate our method with the 2017 and 2018 Robotic Scene Segmentation data, the ISIC 2017 and the BraTS 2020 Challenges, a proprietary Endoscopic Submucosal Dissection dataset, Cityscapes, and Pascal VOC 2012. Additionally, we analyze the impact of the individual components and examine the behavior when the amount of labeled data varies, with experiments performed on two distinct segmentation architectures. Our method shows improvements in terms of the mean Intersection over Union over the supervised baseline and competing methods. Code is available at https://github.com/CloneRob/ECMT.
Erweiterung des Workflow-Moduls des ERP-Systems FactWork um Möglichkeiten zur Benutzerinteraktion
(2018)
Durch Workflow-Systeme computergestützt abgewickelte
Geschäftsprozesse benötigen neben den Aktivitäten, die sie
komplett automatisiert ausführen können, von Zeit zu Zeit
Feedback durch einen oder mehrere Benutzer. Dazu muss
es geeignete Formen der Kommunikation und Interaktion
der Workflow-Engine mit dem Benutzer geben. Der folgende
Artikel beschreibt die Erweiterung des bestehenden
Workflow-Moduls eines Enterprise Resource Planning
(ERP)-Systems, welches um solche Fähigkeiten ergänzt
wird.
Despite the relevance and maturity of the Chief Information Officer (CIO) research field, no studies exist that exhaustively summarize the current body of knowledge, focusing on the development of the field over its entire timespan. The paper at hand addresses this research gap and presents an exhaustive literature review on the CIO research field using main path analysis. We identify the central papers in CIO research and eight main research streams by quantitatively and qualitatively analyzing 466 papers. We find that established research streams, e.g., ‘Evolving role of the CIO’ and ‘CIO hierarchical position and relationships’ as well as recently emerging research streams, e.g., ‘CIO as business enabler’ and ‘CIOs and IT security,’ draw growing attention. Based on our findings, we develop promising further avenues for research in the CIO field.
To prepare their IT landscape for future business challenges, companies are changing their IT sourcing arrangements by using selective sourcing approaches as well as multi-sourcing with more but smaller sourcing contracts. Companies therefore have to reconsider and re-evaluate their IT sourcing setup more frequently. Collecting data from 251 global experts, we empirically tested the effect of service quality, relationship quality, and switching costs on IT sourcing decisions using partial least squares (PLS) analysis. Drawing on previously conducted expert interviews, our model extends previous studies and introduces a decision maker’s sourcing preferences as a not yet examined moderator on IT sourcing decisions. This allows us to investigate the influence of the decision maker’s beliefs on the decision process. We were able to confirm the negative effect of switching costs on a decision in favor of backsourcing, however we could not find significant support for the remaining hypotheses. We further discuss potential reasons for our findings and suggest future research opportunities based on our contribution.
Most large-scale organizations adopted Cloud Computing (CC) on a company level in recent years. Managers now face the challenge to appropriately implement CC "operationally", i.e., for information systems (ISs). We refer to this as post-adoption, addressing the extent of technology usage after adoption. Specifically, managers need to choose among the CC delivery models Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and Software-asa-Service (SaaS). We differentiate the determinants of this post-adoption decision for IaaS, PaaS, and SaaS. Based on this analysis, we derive criteria that guide managers' delivery model selection: Adopt 1) IaaS for ISs requiring flexibility and reduced time to market, 2) PaaS to access specialized resources, and 3) SaaS to focus on core competencies. Moreover, we analyze the impact on the CC strategy and postulate them as recommendations: I) acknowledge the interplay between governance and time-to-market, II) realize cost savings on company level, and III) consider strategically important ISs for CC.
Hintergrund:
Eltern stehen im Rahmen der eigenen Impfung und der Kinderimpfung mit einem COVID-19-Vakzin vor einer Impfentscheidung. Zum aktuellen Zeitpunkt gibt es keine (vollständige) Impfempfehlung.
Fragestellung:
Die Studie untersucht die Impfbereitschaft von Eltern minderjähriger Kinder und Personen ohne minderjährige Kinder, wobei insbesondere Geschlechtsunterschiede überprüft werden.
Methoden:
Die Studie basiert auf einer Zufallsstichprobe (Telefon-Survey, n = 2014, Erhebung zwischen 12.11.2020 und 10.12.2020). Die Auswertung stützt sich insbesondere auf die Teilstichprobe von Personen mit minderjährigen Kindern im Haushalt (n = 461).
Ergebnisse:
Eltern weisen durchgängig eine geringere Impfbereitschaft mit einem COVID-19-Vakzin auf als Befragte ohne minderjährige Kinder (54,1 % vs. 71,1 %). Väter weisen eine stärker ausgeprägte eigene Impfbereitschaft auf als Mütter. Darüber hinaus sind Männer eher als Frauen bereit, das eigene Kind mit einem COVID-19-Vakzin impfen zu lassen.
Schlussfolgerungen:
Bei Eltern und insbesondere Müttern ist eine erhebliche Fehleinschätzung von Impfrisiken und häufiger Glaube an Impfverschwörungstheorien zu beobachten. Empfohlen werden anschauliche und leicht verständliche Informationen über die Wirkung und Nebenwirkungen der Impfung mit einem COVID-19-Vakzin durch zuständige Institutionen und Ärzte.
Aims
Congenital breast asymmetry represents a particular challenge to the classic techniques of plastic surgery given the young age of patients at presentation. This study reviews and compares the long-term results of traditional breast augmentation using silicone implants and the more innovative technique of lipografting.
Methods
To achieve this, we not only captured subjective parameters such as satisfaction with outcome and symmetry, but also objective parameters including breast vol-ume and anthropometric measurements. The objective examination was performed manually and by using the Vectra H2 photogrammetry scanning system.
Results
Differences between patients undergoing either implant augmentation or lipograft were revealed not to be significant with respect to patient satisfaction with surgical outcome (p= 0.55) and symmetry (p= 0.69). Furthermore, a breast symmetry of 93 % was reported in both groups. Likewise, no statistically significant volume difference between the left and right breasts was observed in both groups (p\0.41). However, lipograft patients needed on average 2.9 procedures to achieve the desired result, compared with 1.3 for implant augmentation. In contrast, patients treated with implant augmentation may require anumber of implant changes during their lifetime.
Conclusion
Both methods may be considered for patients presenting with congenital breast asymmetry.
Background
This study evaluated the effect of an artificial intelligence (AI)-based clinical decision support system on the performance and diagnostic confidence of endoscopists in their assessment of Barrett’s esophagus (BE).
Methods
96 standardized endoscopy videos were assessed by 22 endoscopists with varying degrees of BE experience from 12 centers. Assessment was randomized into two video sets: group A (review first without AI and second with AI) and group B (review first with AI and second without AI). Endoscopists were required to evaluate each video for the presence of Barrett’s esophagus-related neoplasia (BERN) and then decide on a spot for a targeted biopsy. After the second assessment, they were allowed to change their clinical decision and confidence level.
Results
AI had a stand-alone sensitivity, specificity, and accuracy of 92.2%, 68.9%, and 81.3%, respectively. Without AI, BE experts had an overall sensitivity, specificity, and accuracy of 83.3%, 58.1%, and 71.5%, respectively. With AI, BE nonexperts showed a significant improvement in sensitivity and specificity when videos were assessed a second time with AI (sensitivity 69.8% [95%CI 65.2%–74.2%] to 78.0% [95%CI 74.0%–82.0%]; specificity 67.3% [95%CI 62.5%–72.2%] to 72.7% [95%CI 68.2%–77.3%]). In addition, the diagnostic confidence of BE nonexperts improved significantly with AI.
Conclusion
BE nonexperts benefitted significantly from additional AI. BE experts and nonexperts remained significantly below the stand-alone performance of AI, suggesting that there may be other factors influencing endoscopists’ decisions to follow or discard AI advice.
Sustainability is an important topic in production plan-ning and control. This article contributes in particular the to further research on the social dimension. It pre-sents a linear optimisation model for Master Produc-tion Scheduling in order to improve human working conditions. Existing approaches have already identified a considerable potential for improvements. Further-more, this article analyses the influence of the compa-ny size on workload and costs using an application with a high proportion of manual activities. It is demonstrat-ed that human working conditions can be improved independently from the company size without increas-ing costs. In addition, smaller companies tend to have a higher exhaustion and the workload affects the total costs more in smaller companies. Therefore, smaller companies might benefit more from an improvement in human working conditions.
Mit PowerPoint oder LaTeX Beamer erstellte Vorlesungsfolien sind meist statisch und dienen hauptsächlich der Präsentation von Lehrinhalten. Als Alternative dazu werden drei Erweiterungen für das HTML- und JavaScript-basierte Präsentationsframework reveal.js vorgestellt, die für mehr Interaktion in der Datenbankenlehre sorgen sollen: (1) Eine Live-Ausführung von SQL-Anfragen und eine Darstellung des Anfrageergebnisses direkt auf der Folie; mit Möglichkeit zur Anpassung der Anfrage im Präsentationsbetrieb, (2) eine JSON-basierte Beschreibung von ER-Diagrammen, welche graphisch auf den Folien dargestellt werden sollen und (3) eingebettete Smartphone-Umfragen, um zwischendurch – ohne einen Kontextwechsel – Quiz-Fragen zu stellen.
We present the Regensburg Breast Shape Model (RBSM)—a 3D statistical shape model of the female breast built from 110 breast scans acquired in a standing position, and the first publicly available. Together with the model, a fully automated, pairwise surface registration pipeline used to establish dense correspondence among 3D breast scans is introduced. Our method is computationally efficient and requires only four landmarks to guide the registration process. A major challenge when modeling female breasts from surface-only 3D breast scans is the non-separability of breast and thorax. In order to weaken the strong coupling between breast and surrounding areas, we propose to minimize the variance outside the breast region as much as possible. To achieve this goal, a novel concept called breast probability masks (BPMs) is introduced. A BPM assigns probabilities to each point of a 3D breast scan, telling how likely it is that a particular point belongs to the breast area. During registration, we use BPMs to align the template to the target as accurately as possible inside the breast region and only roughly outside. This simple yet effective strategy significantly reduces the unwanted variance outside the breast region, leading to better statistical shape models in which breast shapes are quite well decoupled from the thorax. The RBSM is thus able to produce a variety of different breast shapes as independently as possible from the shape of the thorax. Our systematic experimental evaluation reveals a generalization ability of 0.17 mm and a specificity of 2.8 mm. To underline the expressiveness of the proposed model, we finally demonstrate in two showcase applications how the RBSM can be used for surgical outcome simulation and the prediction of a missing breast from the remaining one. Our model is available at https://www.rbsm.re-mic.de/.
This paper connects research from business model innovation and information systems by exploring critical IT capabilities for servitized business models. The adoption of servitized business models is a major business model innovation strategy. At the same time, digitalization drives the evolution of IT capabilities at these business models. Scholars argue that it remains unclear how IT capabilities enable servitized business models to build a competitive advantage by achieving cost advantages or differentiation. This paper explores IT capabilities that enable building a competitive advantage for servitized business models based on a qualitative analysis of multiple published case studies. The authors identify configurations of IT capabilities among servitized business models. The findings contribute to servitization research by exploring IT capabilities
and how they are combined among servitized business models.
The insights help practitioners deploy digital technologies and IT
assets effectively as building blocks of IT capabilities to advance
their servitized business model.
Identifying different functional regions during a brain surgery is a challenging task usually performed by highly specialized neurophysiologists. Progress in this field may be used to improve in situ brain navigation and will serve as an important building block to minimize the number of animals in preclinical brain research required by properly positioning implants intraoperatively. The study at hand aims to correlate recorded extracellular signals with the volume of origin by deep learning methods. Our work establishes connections between the position in the brain and recorded high-density neural signals. This was achieved by evaluating the performance of BLSTM, BGRU, QRNN and CNN neural network architectures on multisite electrophysiological data sets. All networks were able to successfully distinguish cortical and thalamic brain regions according to their respective neural signals. The BGRU provides the best results with an accuracy of 88.6 % and demonstrates that this classification task might be solved in higher detail while minimizing complex preprocessing steps.
In the field of computer- and robot-assisted minimally invasive surgery, enormous progress has been made in recent years based on the recognition of surgical instruments in endoscopic images and videos. In particular, the determination of the position and type of instruments is of great interest. Current work involves both spatial and temporal information, with the idea that predicting the movement of surgical tools over time may improve the quality of the final segmentations. The provision of publicly available datasets has recently encouraged the development of new methods, mainly based on deep learning. In this review, we identify and characterize datasets used for method development and evaluation and quantify their frequency of use in the literature. We further present an overview of the current state of research regarding the segmentation and tracking of minimally invasive surgical instruments in endoscopic images and videos. The paper focuses on methods that work purely visually, without markers of any kind attached to the instruments, considering both single-frame semantic and instance segmentation approaches, as well as those that incorporate temporal information. The publications analyzed were identified through the platforms Google Scholar, Web of Science, and PubMed. The search terms used were “instrument segmentation”, “instrument tracking”, “surgical tool segmentation”, and “surgical tool tracking”, resulting in a total of 741 articles published between 01/2015 and 07/2023, of which 123 were included using systematic selection criteria. A discussion of the reviewed literature is provided, highlighting existing shortcomings and emphasizing the available potential for future developments.
One of the most popular training algorithms for deep neural networks is the Adaptive Moment Estimation (Adam) introduced by Kingma and Ba. Despite its success in many applications there is no satisfactory convergence analysis: only local convergence can be shown for batch mode under some restrictions on the hyperparameters, counterexamples exist for incremental mode. Recent results show that for simple quadratic objective functions limit cycles of period 2 exist in batch mode, but only for atypical hyperparameters, and only for the algorithm without bias correction. We extend the convergence analysis to all choices of the hyperparameters for quadratic functions. This finally answers the question of convergence for Adam in batch mode to the negative. We analyze the stability of these limit cycles and relate our analysis to other results where approximate convergence was shown, but under the additional assumption of bounded gradients which does not apply to quadratic functions. The investigation heavily relies on the use of computer algebra due to the complexity of the equations.
On analytic properties of the standard zeta function attached to a vector-valued modular form
(2022)
We proof a Garrett–Böcherer decomposition of a vector-valued Siegel Eisenstein series E2l,0 of genus 2 transforming with the Weil representation of Sp2(Z) on the group ring C[(L′/L)2]. We show that the standard zeta function associated to a vector-valued common eigenform f for the Weil representation can be meromorphically continued to the whole s-plane and that it satisfies a functional equation. The proof is based on an integral representation of this zeta function in terms of f and E2l,0.
Organizations are under increasing pressure to develop applications within budget and time at high quality. Therefore, multiple organizations adopt Low Code Development Platforms (LCDP) to develop applications faster and cheaper compared to traditional application development. However, current research on LCDP adoption lacks empirical grounding as well as a deeper understanding of the importance of adoption drivers and inhibitors. We conducted semi-structured interviews and a Delphi study with seventeen experts to address these gaps. As a result, we identified twelve drivers and nineteen inhibitors for adopting LCDPs. We show that the experts have a consensus on the most and the least important drivers and inhibitors for LCDP adoption. Yet, the ranking of the drivers and inhibitors between the most and least important is highly context dependent. For some drivers and inhibitors, the experts’ ranking is similar to academic literature, whereas, for others, it differs. In conclusion, the study at hand empirically validates drivers and inhibitors for LCDP adoption, adds six new drivers and six new inhibitors to the body of knowledge, and analyses the importance of these factors.
The prospect of achieving computational speedups by exploiting quantum phenomena makes the use of quantum processing units (QPUs) attractive for many algorithmic database problems. Query optimisation, which concerns problems that typically need to explore large search spaces, seems like an ideal match for the known quantum algorithms. We present the first quantum implementation of join ordering, which is one of the most investigated and fundamental query optimisation problems, based on a reformulation to quadratic binary unconstrained optimisation problems. We empirically characterise our method on two state-of-the-art approaches (gate-based quantum computing and quantum annealing), and identify speed-ups compared to the best know classical join ordering approaches for input sizes that can be processed with current quantum annealers. However, we also confirm that limits of early-stage technology are quickly reached.
Current QPUs are classified as noisy, intermediate scale quantum computers (NISQ), and are restricted by a variety of limitations that reduce their capabilities as compared to ideal future quantum computers, which prevents us from scaling up problem dimensions and reaching practical utility. To overcome these challenges, our formulation accounts for specific QPU properties and limitations, and allows us to trade between achievable solution quality and possible problem size.
In contrast to all prior work on quantum computing for query optimisation and database-related challenges, we go beyond currently available QPUs, and explicitly target the scalability limitations: Using insights gained from numerical simulations and our experimental analysis, we identify key criteria for co-designing QPUs to improve their usefulness for join ordering, and show how even relatively minor physical architectural improvements can result in substantial enhancements. Finally, we outline a path towards practical utility of custom-designed QPUs.
Die zunehmende Digitalisierung der Fertigung führt zu einer zunehmenden Vernetzung von Maschinen, Werkstücken, Werkzeugen, Transporteinrichtungen usw. mit dem Ziel einer weitgehenden Selbstorganisation. Dies stellt zwangsläufig Anforderungen an die bisher verwendeten IT-Systemen zur Steuerung von Unternehmen. Enterprise Ressource Planning Systeme (ERP-Systeme) sind wegen ihres Einflusses auf Produktionsprozesse davon besonders betroffen. Zugleich sind sie wegen ihrer umfangreichen Unterstützung von anderen Unternehmensbereichen wie Controlling für Unternehmen sehr relevant. Dies führt bei ERP-System-Herstellern wie der SAP SE zu umfangreichen Erweiterungen. Mit diesem Projekt wird untersucht, in wie weit sich die neue Produktgeneration von SAP SE (SAP S/4HANA) als Enabler zur Smart Factory der AUDI AG eignet.
Die vorliegende Studie untersucht Schlüsselfaktoren erfolgrei-
cher CIOs in deutschen Großunternehmen. Mit einer mittleren Verweildauer (Median) von 4,0 Jahren weisen deutsche CIOs, die mit 43 % noch überwiegend an den CFO berichten, im Vergleich zu anderen C-Level-Positionen eine deutlich kürzere Verweildauer im Amt auf. Die Ergebnisse aus 60 Interviews mit erfolgreichen deutschsprachigen CIOs, die primär über eine überdurchschnittlich lange Verweildauer verfügen, lassen verschiedene Schlüsselfaktoren für den Erfolg erkennen: Grundvoraussetzung ist stets die Gewährleistung eines sicheren und effizienten IT-Betriebs. Über effektive und innovative Change-Projekte machen die interviewten CIOs den IT-Mehrwert transparent und agieren als Brückenbauer zwischen IT und Fachbereichen. Dadurch wirken sie positiv auf die Firmenkultur ein und etablieren die IT nachhaltig in den Fachbereichen als Erfolgsfaktor. Erfolgreiche CIOs selbst sind keine „Techies“, sondern zeichnen sich durch hohe Führungskompetenz und ein hohes Geschäftsverständnis, gepaart mit visionärem Denken aus. Dadurch gelingt es ihnen, die IT zukunftsorientiert auszurichten und Anforderungen und Potenziale für und aus den Fachbereichen frühzeitig zu antizipieren. Die zukünftige Entwicklung der CIO-Organisation und der Paradigmen in der IT wird durch die Studienteilnehmer hingegen teilweise kontrovers diskutiert – so gibt es beispielsweise bei der Beurteilung der Sinnhaftigkeit und Relevanz der CDO-Position noch kein einheitliches Meinungsbild.
In capacitated production systems at high utilization there exists a nonlinear relationship between the orders which are in process and the output. This nonlinear relationship can be described by nonlinear Clearing Functions. We show how a Clearing function will be estimated and integrate it into a model of order releases planning. We compare our model with two inventory management policies under different demand conditions.
Although the average tenure of CIOs has increased over the last years, the majority of CIOs have been in their positions for only three years or less. Nevertheless, some CIOs have been successful in their position for a long time. In this study, we use tenure as a proxy for success as a CIO. The goal of this paper is to examine factors that are critical to the success of long-term CIOs. For this purpose, we created and analyzed resumes of 384 CIOs. Out of these 384, we conducted 19 interviews with CIOs from top-tier companies and collected and analyzed both qualitative and quantitative data. In the process, we were able to identify nine factors that are critical for the success (CSF) of CIOs. These factors fall into three categories. Category “Personality” includes “Accepting and embracing change” (CSF #1), “Being perseverant to pursue long-term goals” (CSF #2), “Anticipating the future through visionary thinking” (CSF #3), and “Being empathetic to deal with uncertainty felt by co-workers” (CSF #4). The “Role Fulfilment” category includes “Cross-functional involvement and integration of the IT organization” (CSF #5), “Positioning and restructuring of the IT organization” (CSF #6), and “Well-connected and communicative leadership” (CSF #7). The “Organizational Environment” category consists of “Availability of skilled workforce” (CSF #8) and “Reporting line to the CEO” (CSF #9). CSFs 1, 2, and 3 were perceived as most important by the participating CIOs. The results may be of particular interest both to aspiring CIOs and equally their employing organizations, as they reflect what long-term CIOs value during their time in office.
In der Krones AG werden alle Blasmaschinen eines neuen Kundenauftrags ¬ sowohl als Teil einer Komplettanalage als auch einzeln – Vortests unterzogen, um sicherzustellen, dass die Maschine die kundenspezifischen Anforderungen an die speziellen Konfigurationen der Flaschenform erfüllt. Diese Prüfungen erfordern Testmaterialien, bei denen es sich im Fall der Blasmaschinen um Behälter ¬– auch Preforms genannt – handelt, die als Ausgangsprodukt für die Herstellung der eigentlichen Flaschen verwendet werden. Aus diesem Grund müssen mit jedem neuen Kundenauftrag, der eine Blasmaschine beinhaltet, Testmaterialien in ausreichender Anzahl angefordert werden. Diese werden firmenintern produziert und müssen je nach Maschinenkonfiguration in der benötigten Anzahl bereitgestellt werden, um ausführliche Tests durchzuführen. Die Bestellungen erfolgen bisher stets mittels Formulare in Form von Word-Dokumenten, auch Flaschenanforderungen genannt, die manuell vom Vertrieb ausgefüllt werden. Dieser Vorgang erfordert viel Zeit und Ressourcen und soll aus diesem Grund automatisierter ablaufen. Ziel dieses Projekts ist eine Konzeption und Umsetzung einer neuen Funktion, die den alten Prozess ablöst und durch eine effizientere Lösung ersetzt. Hierbei soll zunächst die Funktionalität als eigenständiges Programm entwickelt werden. Benötigt wird eine Konzeption und Implementierung einer geeigneten graphischen Oberfläche sowie ein Programm, das automatisch die benötigten Daten zusammenfasst und diese in übersichtlicher Form darstellt.
In this paper, the risks of a Smart Factory are to be examined and structured in order to be able to evaluate the status of the Smart Factory. This thesis thus serves as an overview of the technical components of a Smart Factory and the associated risks. The study takes a holistic view of the smart factory. The results show that the greatest need for action lies in the technological field. Thus, the topics of standardization, information security, availability of IT infrastructure, availability of fast internet and complex systems were prioritized. The organizational and financial risks, which also play an important role in a Smart Factory transformation, are addressed.
This paper summarizes six presentations in a session of the track “Use of Simulation for Manufacturing Applications”. The research work deals with the following key issues of this track: Modelling of process problems in manufacturing; Solutions of planning problems in manufacturing; Simulation of processes in manufacturing. This publication shows that the contributions in this track address research questions that are of high importance for industrial practice as well as current research directions such as stochastic optimization or the efficient search of large solution spaces.
PURPOSE
IT outsourcing (ITO) has developed into an established practice for organizations but the interorganizational and oftentimes international collaboration it involves comes at a price: Reports from academia and practice suggest that more than 25% of all ITO projects fail, many because of cultural differences between client and provider organizations. Against this background, this paper analyzes the complex nature of cultural distance and its multi-faceted effect on ITO success.
DESIGN/METHODOLOGY/APPROACH
This paper builds upon extant literature on culture on the national, organizational and team level, conceptualizes its effect on relationship quality and ITO success, and hypothesizes a model on potential moderators and management techniques to offset culture-induced challenges. It then evaluates and refines the model by means of an interpretive qualitative research design for an in-depth single-case study of ProSiebenSat.1 Media SE (P7S1), a leading European media company that reconfigured its IT sourcing model three times in 10 years.
FINDINGS
The results from interviews with top managers from client and provider organizations represent one of the first integrated views on the critical importance of cultural compatibility on multiple levels, provide manifold examples for its complex effect on ITO success, as well as moderators and potential management techniques to promote ITO success.
RESEARCH LIMITATIONS/IMPLICATIONS
This paper contributes relevant empirical insights to the growing body of literature on culture and its underestimated role in ITO success. It builds on tentative theory that is confirmed and refined.
PRACTICAL IMPLICATIONS
The paper helps in substantiating the complex and intangible nature of culture and demonstrates means for its effective management.
ORIGINALITY/VALUE
The results from interviews with top managers from client and provider organizations represent one of the first integrated views on the critical importance of cultural compatibility on multiple levels, provide manifold examples for its complex effect on ITO success, as well as moderators and potential management techniques to promote ITO success.
Companies often use specially-designed production systems and change them from time to time. They produce small batches in order to satisfy specific demands with the least tardiness. This imposes high demands on high-performance scheduling algorithms which can be rapidly adapted to changes in the production system. As a solution, this paper proposes a generic approach: solutions were obtained using a widely-used commercially-available tool for solving linear optimization models, which is available in an Enterprise Resource Planning System (in the SAP system for example) or can be connected to it. In a real-world application of a flow shop with special restrictions this approach is successfully used on a standard personal computer. Thus, the main implication is that optimal scheduling with a commercially-available tool, incorporated in an Enterprise Resource Planning System, may be the best approach.
Utility of Smartphone-based Three-dimensional Surface Imaging for Digital Facial Anthropometry
(2024)
Background
The utilization of three-dimensional (3D) surface imaging for facial anthropometry is a significant asset for patients undergoing maxillofacial surgery. Notably, there have been recent advancements in smartphone technology that enable 3D surface imaging.
In this study, anthropometric assessments of the face were performed using a smartphone and a sophisticated 3D surface imaging system.
Methods
30 healthy volunteers (15 females and 15 males) were included in the study. An iPhone 14 Pro (Apple Inc., USA) using the application 3D Scanner App (Laan Consulting Corp., USA) and the Vectra M5 (Canfield Scientific, USA) were employed to create 3D surface models. For each participant, 19 anthropometric measurements were conducted on the 3D surface models. Subsequently, the anthropometric measurements generated by the two approaches were compared. The statistical techniques employed included the paired t-test, paired Wilcoxon signed-rank test, Bland–Altman analysis, and calculation of the intraclass correlation coefficient (ICC).
Results
All measurements showed excellent agreement between smartphone-based and Vectra M5-based measurements (ICC between 0.85 and 0.97). Statistical analysis revealed no statistically significant differences in the central tendencies for 17 of the 19 linear measurements. Despite the excellent agreement found, Bland–Altman analysis revealed that the 95% limits of agreement between the two methods exceeded ±3 mm for the majority of measurements.
Conclusion
Digital facial anthropometry using smartphones can serve as a valuable supplementary tool for surgeons, enhancing their communication with patients. However, the proposed data suggest that digital facial anthropometry using smartphones may not yet be suitable for certain diagnostic purposes that require high accuracy.
Die Krones AG verwendet zur Materialidentifikation Haftetiketten, die die produktbezogenen Informationen beinhalten. Aufgrund eines fehlenden Unternehmensstandards in Bezug auf die Gestaltung des Etikettenlayouts soll im Zuge eines Projektes die Vereinheitlichung der Materialetiketten thematisiert werden.
Neben der Gestaltung eines einheitlichen Layouts erfolgt die Festlegung der Form der Informationen. Durch maschinenlesbare Abbildung der Informationen wird die automatische systemseitige Informationsverarbeitung möglich. Dies führt einerseits zu kürzeren Prozesszeiten, da der Eingabeaufwand entfällt. Gleichzeitig garantiert man so die fehlerfreie Datenübertragung, da manuelle Eingabefehler verhindert werden.
Im Rahmen dieser Ausarbeitung wird aufgezeigt, welche Vorgaben und Richtlinien bezüglich einer Standardisierung existieren und wie diese am Beispiel der Krones AG umgesetzt werden. Nach umfassender Aufnahme und Analyse des derzeitigen Ist-Zustandes folgen Festlegungen für die zukünftige Struktur. Somit wird die Basis für die systemseitige Implementierung des Änderungsvorhabens geschaffen.
Weiter werden alternative Möglichkeiten zur Warenidentifikation und -nachverfolgbarkeit aufgezeigt und erläutert, welche Herausforderungen es dabei im Zeitalter von Industrie 4.0 zu meistern gilt.
In this study, we aimed to develop an artificial intelligence clinical decision support solution to mitigate operator-dependent limitations during complex endoscopic procedures such as endoscopic submucosal dissection and peroral endoscopic myotomy, for example, bleeding and perforation. A DeepLabv3-based model was trained to delineate vessels, tissue structures and instruments on endoscopic still images from such procedures. The mean cross-validated Intersection over Union and Dice Score were 63% and 76%, respectively. Applied to standardised video clips from third-space endoscopic procedures, the algorithm showed a mean vessel detection rate of 85% with a false-positive rate of 0.75/min. These performance statistics suggest a potential clinical benefit for procedure safety, time and also training.
We have a platform, but nobody builds on it – what influences Platform-as-a-Service post-adoption?
(2022)
When higher-level management of a company has strategically decided to adopt Platform-as-a-Service (PaaS) as a Cloud Computing (CC) delivery model, decision-makers at lower hierarchy levels still need to decide whether they want to post-adopt PaaS for building or running an information system (IS) – a decision that numerous companies are currently facing. This research analyzes the influential factors of this managerial post-adoption decision on the IS-level. A survey of 168 business and Information Technology (IT) professionals investigated the influential factors of this PaaS post-adoption decision. The results show that decision-makers’ perceptions of risks inhibit post-adoption. Vendor trust and trialability reduce these perceived risks. While competitive pressure increases perceived benefits, it does not significantly influence PaaS post-adoption. Controversially, security and privacy, cost savings, and top management support do not influence post-adoption, as opposed to findings on company-level adoption. Subsamples constructed by the form of post-adoptive use (migration of IS, enhancement of IS, new IS development) exhibit better goodness-of-fit measures than the full sample. Future research should explore this interrelation of the form of post-adoptive use and the post-adoption influence factors.
Dieses Projekt beschäftigt sich mit der bereichsübergreifenden Personalsteuerung in Form von Leihungen und Verleihungen, einem Teilbereich der monatlichen Personalplanung. Durch diese Thematik entstandene Über-/Unterkapazitäten sollen durch die Einführung eines IT-Tools vermieden werden. Leihungen bzw. Verleihungen dienen dem kurzfristigen Ausgleich von Personalüberdeckungen bzw. Personalunterdeckungen. In der Montage des BMW Werks Regensburg wird üblicherweise auch aus anderen Gründen wie beispielsweise der Hilfe bei dem Anlauf eines neuen Modells geliehen.