A business capability map for data-value creation

Current data-driven transformation projects reveal a gap in understanding the business capabilities (BCs) needed to create value from data. This study introduces a business capability map (BCM) that organizes 34 BCs required for data-value creation. BCs comprise the specification of processes, roles, resources, and information an organization needs to perform its core tasks. The BCM, derived from a structured literature review and expert interviews, was demonstrated by applying it to two data-value projects from a leading German component and system manufacturer. This study contributes to the literature on BCs and facilitates practitioners in developing their BCs for data-value projects

A scoping review and quality assessment of machine learning techniques in identifying maternal risk factors during the peripartum phase for adverse child development

Maternal exposure to environmental risk factors (e.g., heavy metal exposure) or mental health problems during the peripartum phase has been shown to lead to negative and lasting impacts on child development and life in adulthood. Given the importance of identifying early markers within highly complex and heterogeneous perinatal factors, machine learning techniques emerge as a promising tool. The main goal of the current scoping review was to summarize the evidence on the application of machine learning techniques in predicting or identifying risk factors during peripartum for child development. A critical appraisal was also conducted to evaluate various aspects, including representativeness, data leakage, validation, performance metrics, and interpretability. A systematic search was conducted in PubMed, Web of Science, Scopus, and Google Scholar to identify studies published prior to the 14th of January 2025. Review selection and data extraction were performed by three independent reviewers. After removing duplicates, the searches yielded 10,336 studies, of which 60 studies were included in the final report. Among these 60 machine learning studies, a majority were pattern-focused, using machine learning primarily as a tool to more accurately describe associations between variables, while 16 studies were prediction-focused (26.7%), exploring the predictive performance of their models. For prediction-focused machine learning studies, a diverse range of methodologies was observed. The quality assessment showed that all studies had some important criteria that were not fully met, with deviations ranging from minor to major, limiting the interpretability and generalizability of the reported findings. Future research should aim at addressing these limitations to enhance the robustness and applicability of machine learning models in this field

Mid- and near-infrared spectroscopies for quantitative tracking of isocyanate content: streamlined development of monitoring tools for reactive extrusion synthesis of specialty polyurethanes

Robust in-situ monitoring can expedite the development and tuning of reactive extrusion (REX) processes, especially for the synthesis of polymers requiring insight into the reaction course, such as specialty polyurethanes (PUs). In order to advance the feasibility of such analysis, our research concentrated on a spectroscopic protocol that combines at-line mid-infrared (MIR) and on-line near-infrared (NIR) measurements in a laboratory extruder, assessing both their qualitative and quantitative capabilities. To mimic the depletion of the reactive species during polymerisation, a series of premixes were formulated and characterised under non-reactive conditions using a benchmark pair of a polyol and a diisocyanate. By this means, we identified suitable spectral features for quantifying isocyanate content via multivariate regression models. This approach achieved good calibration metrics for both MIR and NIR models and enabled a robust assessment of their predictive performance through cross-validation, using only a moderate number of spectral datasets. Our work is therefore the first step towards establishing a method for in-process NIR analysis with streamlined at-line MIR verification. It provides a shortcut for designing monitored REX syntheses of PUs and other material systems amenable to quantitative calibration based on spectroscopic data from raw reagents

How can international business-to-business partnerships in Africa contribute to achieving the sustainable development goals?

Following calls by international business scholars to pay attention to how multinational enterprises contribute to the Sustainable Development Goals, we make implementable recommendations for international B2B partnerships in Africa. We postulate that international businesses can alleviate extreme poverty and eradicate child labor by selecting ethical African suppliers. Furthermore, partners must exercise transparency in how they adopt clean and environmentally sound technologies. We also highlight that partners should demonstrate flexibility and open-mindedness to African indigenous know-how and sustainable practices to facilitate knowledge-sharing. International B2B partners may consider our recommendations to guide the building of ethical and responsible businesses in Africa

A low-cost setup and procedure for measuring losses in inductors

Inductors are critical components in power electronic converters, determining their efficiency and size. A converter's performance is limited by the losses associated with inductors. In lower power applications, commercially available off-the-shelf inductors are usually used, but their losses are often difficult to predict solely based on datasheet values. Therefore, a direct measurement is typically required; here, a separate measurement of the dc and an ac loss is proposed to simplify the measurement process. This paper presents a low-cost setup based on affordable equipment, such as a self-built current probe, and uses simple compensation methods that allow developers to efficiently and cost-effectively measure losses in inductors. The setup is designed to emulate conditions comparable to real-world applications. The proposed procedure and setup are validated through experimental results, and potential sources of error and methods for compensation are discussed

Herman Hollerith Conference 2024

Moderne digitale Technologien und Konzepte wie KI, EAM, BPM und Cloud Computing sind wesentlich für die digitale Transformation von Unternehmen und Organisationen. Ohne die Grundlagen, Nutzungsaspekte und einem breiten Diskurs dieser Technologien und Konzepte im Allgemeinen ist die Wettbewerbsfähigkeit in Gefahr. Die 1. Herman Hollerith Conference 2024 widmet sich diesen Schwerpunkten und leistet einen Beitrag zur Beantwortung wichtiger, offener IT-Fragen. Die Beiträge entstammen einem wissenschaftlichen und einem Industry Track

Geopolitisches Risikomanagement in KMU

Geopolitische Risiken nehmen zu und können für international agierende mittelständische Unternehmen (KMU) schwerwiegende Folgen haben. Durch die konsequente Verankerung des Themas auf Geschäftsführungsebene sowie durch internes und externes Know-how können die Voraussetzungen für ein erfolgreiches Management im Umgang mit geopolitischen Ereignissen geschaffen werden

Juristische Problemlösung mit KI – Leistung und Grenzen großer Sprachmodelle

Große Sprachmodelle wie ChatGPT und Gemini zeigen inzwischen ein beachtliches Leistungsniveau bei der Lösung juristischer Prüfungsfragen. Auf Grundlage von 200 Multiple-Choice-Fällen dokumentiert der Beitrag die Entwicklung der maschinellen Entscheidungssicherheit zwischen 2023 und 2025. Die Analyse zeigt eine signifikante Steigerung der Trefferquoten, offenbart aber auch strukturelle Grenzen der Modelle bei komplexen, mehrgliedrigen Fallkonstellationen. Der Beitrag bewertet die Einsatzmöglichkeiten aktueller KI-Modelle im juristischen Alltag und zeigt, wo der Mensch der Maschine überlegen bleibt

Analysis and design of a low-complexity ZVS buck-boost converter

A circuit structure and operating method for achieving a soft-switching operation of a non-inverting buck-boost converter is proposed. The converter is derived from the two-switch buck-boost converter. It achieves ZVS by replacing a diode with an active switch, driven with a gate signal complementary to the main transistors’ control signals. In this way, the inductor current can be clamped and used to achieve soft-switching transitions of all transistors in the converter. The circuit achieves ZVS by design, and the ZVS range can be adjusted by adding a capacitor parallel to a diode or switch. The converter does not need a complex control or sensor circuit for proper operation. The operating principle and converter design are described in detail. The proposed converter operation is verified using simulations and experimental results

A replication approach for the evaluation of embedded options in German building savings contracts

From a financial mathematics point of view, German building savings contracts are complex financial instruments. In particular the valuation of embedded options places specific demands on actuaries due to the dynamic interactions between these multiple options and the partial lack of financial rationality of the contract holders. To date, German building societies use various models for the risk valuation of embedded options in building savings contracts. For this work, the concept of the replication portfolio, which has been used in life insurance for some time, was transferred to building savings contracts and implemented in a Jupyter Notebook framework. A specific cash flow approach and filtering algorithms were developed to deal with the problems arising in a standard approach. Initial test results on the contract portfolio of Bausparkasse Schwäbisch Hall AG are very promising. Further research and development work is required for practical application, but the authors believe that in the long term the approach has the potential to develop into a standard for the (risk) assessment of embedded building savings options. Furthermore, the developed concept might be helpful for other applications not restricted to German building societies