The skilled trade industry is a significant driving force for the development and prosperity of society and constitutes the backbone of the German economy with its small and medium-sized enterprises. Currently, waiting times for craftsmen stand at approximately three months. This trend is on the rise due to the continued and severe shortage of apprentices and skilled workers. Potential trainees are representatives of Generation Z and best reached through social media channels. Consequently, many companies deliberately utilize corporate influencers in employer branding efforts to win young talents. Corporate influencers have the ability to present specifically job-related content and offer more authentic insights into the daily work environment. However, do they genuinely influence the career preferences of potential trainees? The aim of this study is to investigate if and to what extent corporate influencer influence the perception of the skilled trades industry and career preferences of potential applicants. To investigate the impact of corporate influencers on the perception of the skilled trade industry and the respective career preferences of potential applicants, we conducted a study with 66 students from a secondary school in Germany. (1) First, we measured the perception of the skilled trades industry and career preferences of the participants. (2) Then we exposed them to previously selected content of two corporate influencers from the skilled trades sector. (3) After the exposure, we measured the perception of the skilled trades industry and career preferences of the participants again. For the statistical analysis we used regression analyses and T-tests. The findings of the study show that corporate influencer on social media positively influenced both, the perception of the skilled trades industry and the career preferences of potential applicants. Particularly, insights into daily work routines prove to be effective. Simultaneously, the study reveals that the employer attractiveness of the skilled trades industry in general significantly influences the perception of the industry and enhances applicants' interest in craft professions.

Additive manufacturing has transformed the production process by enabling the construction of components in a layer-by-layer approach. This study integrates Artificial Neural Networks to explore the nuanced relationship between process parameters and mechanical performance in Fused Filament Fabrication. Using a fractional Taguchi design, seven key process parameters are systematically varied to provide a robust dataset for model training. The resulting model confirms its accuracy in predicting tensile strength. In particular, the mean squared error is 0.002, and the mean absolute error is 0.024. These results significantly advance the understanding of 3D manufactured parts, shedding light on the intricate dynamics between process nuances and mechanical outcomes. Furthermore, they underscore the transformative role of machine learning in precision-driven quality prediction and optimization in additive manufacturing.

This study provides a comprehensive review of the intellectual structure and current dynamics of onboarding and socialization research. Using the Web of Science (WoS) database, we found 452 research articles that met the inclusion criteria. Biblioshiny R-package and VOSviewer were used for the bibliometric analysis. We lay out the most prolific authors, journals, institutions and articles in this rapidly growing field. We find that current research is scattered all over different topics and disciplines. We identify five research fronts that authors have pursued in the last 5 years. Researchers have focused on: psychological contracts; the role of networks and relationship building; the changing work contexts in which organizational socialization takes place; the effects of newcomer proactivity and interactions with supervisors; onboarding in distinct areas like software engineering. Promising research avenues in this field can be distinguished in: different groups of newcomers; examining interactive effects between newcomers and socialization agents; and analyzing the evolving area of digital and virtual onboarding and organizational socialization.

Die Herausforderung beim Einsatz von generativer Text-KI, wie ChatGPT, besteht darin, die Potenziale effizient zu nutzen und im Hinblick auf die Erreichung von Qualitätszielen optimal einzusetzen. Dabei ist die menschliche Eingabe in die Künstliche Intelligenz (KI) – der Prompt – entscheidend. Der vorliegende Beitrag widmet sich der Frage, wie die KI-basierte Textausgabe bei ChatGPT durch Prompt Engineering gezielt gesteuert werden kann, damit die Textqualität der generativen KI den Erfolgskriterien für Content Marketing Texte entspricht. Die Ergebnisse identifizieren eine effektive Prompt-Struktur für qualitativ hochwertige Content Marketing Texte mit ChatGPT. Insbesondere das Zero-shot Chain-of-Thought und das One-shot bzw. Few-shot Prompting erweisen sich als erfolgreich, da diese Techniken eine gezielte Steuerung des ChatGPT-Outputs in Richtung der Erfolgskriterien ermöglichen. Darüber hinaus werden die aktuellen Schwächen von KI-generierten Texten beschrieben. Dabei werden auch die Grenzen von ChatGPT deutlich, die durch eine kollaborative Wertschöpfung von Mensch und KI zur gemeinsamen Erreichung von Qualitätszielen überwunden werden können. Die theoretisch und praktisch fundierten Ergebnisse und Implikationen der Untersuchung bieten eine Orientierungshilfe für Content Marketer zur effizienten Nutzung von ChatGPT.

In times of digitalisation, visual assistance systems in assembly are increasingly important. The design of these assembly systems needs to be highly complex to meet the requirements. Due to the increasing number of variants in production processes, as well as shorter innovation and product life cycles, assistance systems should improve quality and reduce complexity of assembly processes. However, many large kitchen manufacturers still assemble kitchen cabinets manually, due to the high variety of components, such as rails and fittings. This paper focuses on the analysis and evaluation of virtual assistance systems to improve quality and usability in individualised kitchen cabinet assembly processes at a large German manufacturer. A solution is identified and detailed.

Tourism recommendation systems have the potential to alleviate choice overload for travelers. Social robots offer a promising avenue for delivering recommendations in tourist information settings, presenting an engaging and intuitive interface. This research explores tourists’ perceptions of the effectiveness and satisfaction of tourism recommendations provided by social robots as well as their preferences for human-like versus robotic interactions. An experiment was conducted at a tourist information office involving 60 participants exposed to either a human-like or robotic version of the social robot recommender system. Feedback was collected via survey, revealing that the participants responded positively to the social robot across various evaluation criteria. These findings suggest that tourists are receptive to social robots in real-world tourism contexts and would consider using them in the future.