Photovoltaic (PV) energy production in Western countries increases yearly. Its production can be carried out in a highly distributed manner, not being necessary to use large concentrations of solar panels. As a result of this situation, electricity production through PV has spread to homes and open-field plans. Production varies substantially depending on the panels’ location and weather conditions. However, the integration of PV systems presents a challenge for both grid planning and operation. Furthermore, the predictability of rooftop-installed PV systems can play an essential role in home energy management systems (HEMS) for optimising local self-consumption and integrating small PV systems in the low-voltage grid. In this article, we show a novel methodology used to predict the electrical energy production of a 48 kWp PV system located at the Campus Feuchtwangen, part of Hochschule Ansbach. This methodology involves hybrid time series techniques that include state space models supported by artificial intelligence tools to produce predictions. The results show an accuracy of around 3% on nRMSE for the prediction, depending on the different system orientations.

The nature of corporate communication has undergone significant changes in recent years. One notable trend is the increasing use of employees as brand ambassadors, as evidenced by the proliferation of corporate influencer programs. However, a critical question is often overlooked: under what conditions are employees genuinely willing to participate in such programs? This predicament poses a substantial challenge to companies, who must devise compelling strategies to attract and engage employees in these initiatives. This study aims to address this gap by examining the critical factors influencing employee participation in corporate influencer programs on LinkedIn through a conjoint analysis. More than 100 employees, representing a range of company types from start-ups to large corporations, were surveyed. The findings reveal that a modern and actively cultivated corporate culture is essential for employees, while external recognition and occasional support (such as social media guidelines) play only a minor role.

Purpose

For decades, the concept of Shared Service Centers (SSCs) has been recognized in management discourse as a strategic approach to restructuring organizational support functions. Scholars have extensively examined this organizational trend, consistently emphasizing cost savings as the primary rationale behind SSC implementation. However, a comprehensive synthesis of the existing research – encompassing both qualitative and quantitative evidence – to substantiate this critical claim is still lacking. The purpose of this study is to fill this gap by systematically analyzing the SSC literature and assessing the empirical support for cost savings as a central implementation motive.

Design/methodology/approach

A systematic literature review was conducted, involving a screening of scientific databases for SSC-related publications. Following a structured review procedure, 89 articles were identified as containing information on cost savings. These prioritized publications were subjected to a detailed framework-based analysis employing a Theories-Characteristics-Contexts-Methods scheme to extract both qualitative and quantitative data. Ultimately, 306 relevant commentaries were gathered, with 40 publications offering author-generated evidence that underwent an in-depth analysis.

Findings

The structured evaluation of the evidence highlights a significant research gap: the lack of quantitative evidence based on objective financial metrics to substantiate the reduction of administrative costs achieved by SSC organizations within a company-wide profit-and-loss context. Existing research predominantly emphasizes qualitative commentary, often referenced from non-scientific third-party sources. When quantitative evidence is presented, it is frequently derived from single case studies and lacks detailed information on the calculation methodology and the associated baseline.

Originality/value

This paper represents the inaugural publication providing a comprehensive mapping of cost-saving evidence within the research domain. The findings underscore the urgent need for the development of a standardized approach capable of effectively capturing the cost-saving contributions of SSCs. Greater transparency regarding the concrete effects of SSCs in this context would significantly enhance top management’s decision-making processes regarding the implementation and expansion of such concepts. Enhanced quantitative rigor would constitute a pivotal advancement in the scientific field, addressing longstanding debates and establishing a novel approach to validating such contributions.

Phasen hoher wirtschaftlicher Unsicherheit können das Interesse an Weiterbildung spürbar verringern. Dies zeigte sich während der Covid-19-Pandemie sehr deutlich. Zugleich nahm aber das Interesse an Online-Weiterbildungsmöglichkeiten in dieser Zeit stark zu.  Zu diesem Ergebnis kommt eine Auswertung einschlägiger Suchanfragen bei Google.

Influencer-Marketing ist eine etablierte Strategie der digitalen Markenkommunikation, die auf die Authentizität und Überzeugungskraft von Influencern setzt. Mit der zunehmenden Verbreitung von Künstlicher Intelligenz (KI) verändert sich dieser Bereich durch den Einsatz von KI-Influencern. Immer häufiger vermitteln virtuelle, computergenerierte Persönlichkeiten Markenbotschaften und beeinflussen Kaufentscheidungen. Ein zentrales Merkmal von KI-Influencern ist ihre digitale Perfektion, die durch idealisierte ästhetische Merkmale und makellose Darstellung charakterisiert ist. Dieser Beitrag untersucht die Wirkung dieser digitalen Perfektion auf die Wahrnehmung von KI-Influencern. Basierend auf dem Uncanny-Valley-Effekt und der Theorie der para-sozialen Interaktion wird ein konzeptionelles Wirkungsmodell abgeleitet und empirisch überprüft. In einer quantitativen Studie (n=100) wurden Konsumenten KI-Influencer mit unterschiedlichem Perfektionsgrad (unperfekt, moderat perfekt, perfekt) präsentiert. Die Ergebnisse zeigen, dass eine höhere digitale Perfektion zu einer geringeren wahrgenommenen Kompetenz, Menschlichkeit und Glaubwürdigkeit führt. Diese Befunde unterstreichen die Bedeutung gezielter Imperfektion bei der Gestaltung von KI-Influencern, um Konsumentenvertrauen zu stärken und eine positive Markenwahrnehmung zu fördern. Abschließend werden Empfehlungen und Implikationen für Forschung und Praxis aufgezeigt.

Dynamical Component Analysis (DyCA) and Dynamic Mode Decomposition (DMD), both data-driven dimension reduction methods, are introduced. After application to multivariate simulated signals the techniques of mode selection and the resulting amplitudes are compared with respect to noise robustness and sampling periods. The results indicate that DyCA is a useful alternative to DMD and outperforms DMD under certain conditions. These conditions are based on the underlying dynamics in the terms of differential equations and on the noise ratios of the signals.

Geometric deviations play a crucial role in the quality of additive manufacturing, particularly in parts made with biodegradable resins. Accurately controlling dimensional and geometric variations in manufactured components is critical for achieving defect-free production and meeting functional standards. However, defining a final quality score can be challenging due to numerous dimensional and geometric deviations associated with a part. An innovative metric for evaluating geometric performance was created to measure dimensional precision in components produced through VAT photopolymerization. The index measures the dimensional and geometrical deviations, revealing that external surfaces exhibit greater precision than internal ones. This difference is likely due to internal surfaces overcoming heat dissipation challenges during the cooling process, resulting in less shrinkage for external surfaces. This index is essential in various stages of the manufacturing process, including part design, design for manufacturing and assembly, quality assurance, and process planning, helping to select the appropriate additive manufacturing technology and optimal process parameters.

This paper discusses the challenges and methods for source reconstruction of evoked potentials using deep learning in the context of electroencephalography (EEG). We propose the use of deep learning to address known challenges and improve traditional approaches. We explain the creation of a suitable dataset for solving the inverse problem, including the simulation of neural activity and the use of lead field matrices for the forward solution. Furthermore, we undertake a comparative analysis of some initial deep learning models with similar classical methods.

The manifold of essential matrices is equipped with a one-parameter family of (pseudo-)Riemannian metrics. For the whole family, explicit formulas for geodesics are derived. Moreover, specific curves, so-called quasi-geodesics, are studied and a closed form expression for a quasi-geodesic connecting two given essential matrices is obtained.

In this paper, we show an application of spatiotemporal persistence landscapes to real world time series. Spatiotemporal persistence landscapes are a recent extension of persistence landscapes to time series that capture features of the data that are persistent with respect to time and space. We perform our analysis on EEG data to detect absence epileptic seizures. Further, we compare two dimension reduction techniques (DyCA and PCA) with no dimension reduction and show that the combination of DyCA and persistent landscapes yields the best results.

Splined assemblies ensure precise torque transmission and alignment in mechanical systems. Three-dimensional printing, especially FDM, enables fast production of customized components with complex geometries, reducing material waste and costs. Optimized printing parameters improve dimensional accuracy and performance. Dimensional accuracy is a critical aspect in the additive manufacturing of mechanical components, especially for splined shafts and hubs, where deviations can impact assembly precision and functionality. This study investigates the influence of key FDM 3D printing parameters—layer thickness, infill density, and nominal diameter—on the dimensional deviations of splined components. A full factorial experimental design was implemented, and measurements were conducted using a high-precision coordinate measuring machine (CMM). To optimize dimensional accuracy, artificial neural networks (ANNs) were trained using experimental data, and a genetic algorithm (GA) was employed for multi-objective optimization. Three ANN models were developed to predict dimensional deviations for different parameters, achieving high correlation coefficients (R2 values of 0.961, 0.947, and 0.910). The optimization process resulted in an optimal set of printing conditions that minimize dimensional errors. The findings provide valuable insights into improving precision in FDM-printed splined components, contributing to enhanced design tolerances and manufacturing quality.

Over the last four decades, the shared service centres idea has emerged as a predominant solution to reorganise the support processes of companies worldwide. A stream of academic literature emphasises their potential for ambitious cost savings, shaping the impression that the 'holy grail' for managing companies' administrative costs has been found. However, quantitative evidence based on publicly available financial data is scarce. With the assistance of an umbrella review, this article aims for a structured evaluation of secondary and tertiary SSC literature in that regard. The analysis of 22 publications confirmed initial perceptions. Quantitative data evaluating the impact of SSC organisations on firms administrative cost structure are absent. Furthermore, heterogeneous research procedures yield diverse outputs, deviating from established standards for structured literature reviews. The gathered results substantiate the need for additional investigations at the primary research level, to finalise evidence search and devise a research agenda to address identified gaps.

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Das B2B Digital Marketing Playbook ist nichts, was Du von vorne bis hinten durchackern musst. Benutzt es wie ein Handbuch: Immer dann, wenn eine Frage oder ein Thema im Job auftaucht – nachschlagen, lesen, umsetzen.

Ein Buch aus der Praxis für die Praxis – ein Buch für B2B-Marketers, die Ihre Marketing-Performance für alle sichtbar steigern wollen. Diese zweite Auflage wurde vollständig aktualisiert und erweitert.

Since October 2017, 3D audio recordings have been made every month at the Vogelinsel nature reserve on Lake Altmühlsee, Germany. The recordings start one hour before and end one hour after sunset. The microphone, position and recording device are identical for all recordings. Each recording is analysed by hand using the same analysis method, whereby the content of the recordings is annotated. The weather data for the recording days is collected. The recording and weather conditions at the recording location are documented photographically. This data set is highly unique due to the 3D recording technique and the long duration of the acoustic observation of nature at one spot. In addition to collecting further data, the project aims to compare the recordings with known algorithmic bioacoustic analysis methods in order to better understand the changes in nature at the recording site (possibly caused by climate/biodiversity change), to develop further algorithmic methods of soundscape analysis and to use the recordings and additional data for nature education, medical-therapeutic and wellness contexts. The article describes the data collection in detail, outlines the comparative results achieved so far, presents our additional analysis methods and gives an outlook on the future of the project.

The possibilities and limitations of auralizing an acoustic
laboratory with the “WWISE Spatial Audio” are discussed
by 3d modeling and auralizing a door test laboratory in VR,
designed for sound reduction index measurements. The
simulated results are compared to real measurements with
the acoustic parameters: Reverberation Time [T30] and
Sound Reduction Index [R], with three binauralization
methods compared and further optimizations conducted
with Dolby Atmos for Headphones. The results showed a
deviation and partly a correlation within the “Just
Noticeable Differences [JND]” for T30 values and a precise
reproduction of the sound reduction index within WWISE
was possible for test components with the lowest real R
values. The frequency dependent Rw values were subtracted
from the audio file using bandpass filters - before using
“WWISE” for sound playback in VR. The results of this
work can be a seen as a technical analysis and fundament
for future research regarding realtime auralization
capabilities of audio middlewares.

The positive effects that bioacoustic environments in nature can have on people raise the question of the extent to which bioacoustic recordings can have positive effects as well when played back via VR in the context of a hospital. This paper presents a study in which the effect of a 3D soundscape recording including a 360° still image on geriatric patients in a clinic was investigated. 28 test subjects each spent 15 minutes in a 360° VR room, surrounded by six projection screens and 14 loudspeakers. The study was conducted in a geriatric rehabilitation ward. The recording location was chosen in a nearby recreation and nature reserve. The subjects' state of mind was measured at four points in time using a standardised psychological measurement procedure. During the 15-minute stay in the virtual nature, biosignals of various vital parameters were recorded. In addition, the room was opened to patients and staff at defined times and their use was recorded. The staff were asked about their experiences. The results show that playback increased the well-being of most participants. The therapeutic possibilities of using 3D bioacoustic recordings are discussed and future research and application scenarios for the system are presented.

The interactive soundscape education project, ‘Klangwelt-Entdecker’, aims to raise awareness of the soundscape in a nature reserve. By scanning QR codes with their smartphones at six listening stations on a circular route along the bird island on Lake Altmühlsee, Germany, visitors can experience the diversity of the soundscape of the site throughout the year and obtain information about the bioacoustics of the local nature and birdlife via the project website. The initiative places a special focus on the effects of climate change on the soundscape and aims to convey a greater understanding of the acoustic facets of nature. Sounds are used from a database that has been fed with monthly 3D sound recordings of the bird island for more than 7 years. The impact of the project with regard to the soundscape educational objectives will be analysed by means of a study among participants of the circular walk. The results of the study will be presented and discussed in the context of existing similar projects. Based on this, well-founded demands are made on nature education and, in particular, bioacoustics and soundscape education.

The development of digital musical instruments is often pursued from a substance-ontological functional and physical perspective. However, many musicians talk less about music from a functional and physical perspective but more about the experienced phenomena they encounter when making music. In this article, instrumental playing and musical interaction will be considered from two perspectives: the broadly used substance-ontological view and the process-ontological approach as drafted by Alfred North Whitehead. The instrumental focus here is on digital and traditional bowed stringed instruments and varying descriptions of the interaction on the instrument. Related works and these descriptions are looked at from the two perspectives mentioned. It is shown why it often comes to a bifurcation of nature into primary and secondary qualities of musical interaction during the interface design process. Furthermore, it is shown that musicians' requirements for digital musical instruments are sometimes unfavourably excluded. These problems will be exemplified and suggestions for a process-ontological perspective on the design of musical interaction will be presented. Also an example of a highly market relevant design principle of a musical sound synthesis system fitting to the process-ontological understanding of musical interaction is presented and discussed.