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The Energy Performance of Buildings Directive (EPBD) is the mandato-ry framework for the EU member states to develop clear target paths to reduce their building related greenhouse gas emissions: By 16 % until 2030 and by 26 % until 2033 (1990 = 100 %). Finally, in 2050 all build-ings should be zero-emission buildings (§3, 2b).
Focusing on residential buildings in Germany, this paper shows the pos-sible paths to reach the goals with respect to the revitalisation rates and the improvements of energy efficiency per revitalisation measure to reach zero-emissions of CO2 and greenhouse gases until 2045 (individual German target).
For all existing residential buildings in Germany, the potential develop-ments of renovation progress and building energy demands are exam-ined.
This is done by a self-written Python program which considers different revitalisation rates as well as revitalization depth. Best-case (5 % revitali-sation rate) and worst-case (0.7 % revitalisation rate) scenarios show the gap between demands and potential paths of energy consumption. Target orientated paths show the needed effort to reach the targets for 2045.
Finally, the question of sourcing renewable energy for the heating of Germany’s buildings is addressed as the energy transition is running in parallel. Building renovation is consequently accompanied by a transi-tion to green electrical energy sources.
The research aim is to show the constrains for the path to zero-emission build-ings using the example of residential buildings and show the im-pact of potential improvement measures on the future energy demand.
The General Data Protection Regulation (GDPR) has been in force since May 2018. Organizations and individuals must comply with this legislation if they collect or process the personal information of residents of the European Union. Prior research has focused on the examination of the privacy policies of the most frequently visited websites or mobile applications with the highest number of installations. The present study assesses the privacy policies of a less explored field: medium-sized town administrations. For this purpose, we analyzed and evaluated 644 privacy policies collected in Austria, Germany, and Ireland, focusing on their coverage of different data practice categories and GDPR-related dictionary phrases. We employed semi-automated data collection methods, deep learning and NLP techniques, and manual labor to perform this analysis. Our findings provide insight into the privacy policy landscape of medium-sized town administrations, where Austria and Germany exhibit a highe r average coverage of GDPR data practice categories than Ireland.
Anthropomorphism and trust are two variables that are measured in a multitude of HRI studies. These two variables are often treated as dependent variables influenced by a particular robot design or behavior. However, psychological literature suggests that people have individual tendencies to anthropomorphize, influencing these two variables. We ran an experiment in which 70 participants were confronted with two robots, a humanoid and a non-humanoid robot. Before exposing them to the robots, they were screened for their individual tendency to anthropomorphize. After exposure, they rated the robots in terms of anthropomorphism and trust. With this experiment, we show that the individual tendency to anthropomorphize has a clear impact on measuring anthropomorphism and trust with frequently used questionnaires. Given our results, we emphasize that future studies should screen participants for their tendency to anthropomorphize to avoid unwanted biases.
Wirtschaft, Psychologie und Nachhaltigkeit sind heute enger miteinander verbunden denn je. Die 29. Fachtagung der Gesellschaft für angewandte Wirtschaftspsychologie widmet sich diesem Zusammenspiel und rückt die Frage in den Mittelpunkt, wie ökologische, ökonomische und soziale Transformation so gestaltet werden kann, dass sie von Menschen verstanden, mitgetragen und aktiv mitgestaltet wird.
Die Tagung an der Westfälischen Hochschule in Gelsenkirchen bringt Studierende, Wissenschaftler*innen und Führungskräfte aus der Praxis an einem Ort zusammen, an dem die Erfahrung von Strukturwandel und Fragen der Zukunftsfähigkeit seit Jahrzehnten zum Alltag gehören. Vor diesem Hintergrund bietet die GWPs ein Forum, in dem wissenschaftlich fundierte und empirisch belastbare Erkenntnisse mit praxisnahen Gestaltungsansätzen verbunden werden. Sie steht für angewandte Forschung mit Anspruch an Rigor und Relevanz.
Die in diesem Band versammelten Beiträge machen deutlich, wie vielfältig und zugleich unmittelbar relevant wirtschaftspsychologische Perspektiven für die Nachhaltigkeitstransformation sind. Sie widmen sich Fragen der Arbeitswelt, Gesundheit und Motivation ebenso wie demokratischen Einstellungen und gesellschaftlicher Teilhabe. Sie beleuchten Akzeptanzprozesse in Mobilität, Technologie und Künstlicher Intelligenz, diskutieren Konsumentenverhalten, soziale Verantwortung, Bildungs- und Hochschulentwicklung sowie organisationale Veränderungen. Damit zeigen sie eindrücklich, dass nachhaltige Transformation nicht allein eine technische, politische oder wirtschaftliche Aufgabe ist, sondern in besonderem Maße eine psychologische.
Wir verstehen diese Tagung daher als Einladung zum Dialog: zwischen Disziplinen, zwischen Forschung und Praxis sowie zwischen den unterschiedlichen Handlungsfeldern, in denen Nachhaltigkeit konkret wird und den Akteur*innen, die sie gestalten. Unser Ziel ist es, Orientierungswissen bereitzustellen, konstruktive Perspektiven zu eröffnen und Impulse zu geben, wie wirtschaftspsychologische Erkenntnisse dazu beitragen können, nachhaltige Entwicklungen wirksam, akzeptiert und menschlich zu gestalten.
Wir danken allen Autor*innen für ihre engagierten Beiträge sowie allen Beteiligten, die durch Organisation, Diskussion und Mitwirkung zum Gelingen dieser Tagung beitragen. Wir wünschen Ihnen eine inspirierende Lektüre, erkenntnisreiche Diskussionen und viele Impulse für Forschung, Praxis und Lehre.
In supply chain management of port operations querying and visualizing network data often requires complex joins, nested queries and predefined reporting templates, which can hinder exploratory analysis and decision-making. When relational databases become too rigid and cumbersome for transactional processing, we envision an alternative approach using graph data models, provided by transforming entities (e.g. containers, vessels, terminals) into nodes and their relationships (e.g. arrival, loading, handling) into edges. To investigate the potential benefits of transforming relational supply chain data into a graph-based model, we designed and implemented a structured approach that integrated data processing, transformation and performance analysis across both relational and graph databases.
As the student population becomes increasingly heterogeneous, providing effective feedback is crucial for personalized education. However, human feedback is resource-intensive, while large language models can be unreliable. Our method bridges this gap by offering informative, similarity-based feedback on mathematical inputs. In an experiment with 207 students, we found that this approach encourages engagement, facilitates the completion of harder exercises, and reduces quitting after incorrect inputs. Compared to traditional feedback mechanisms that struggle with unforeseen error patterns, our method increases student perseverance and confidence. By balancing reliability, resources, and robustness, our solution meets the diverse needs of contemporary students. With its potential to enhance self-learning and student outcomes, this research contributes to the growing conversation on personalized education and adaptive learning systems.
The relevance of e-learning for higher education has resulted in a wide variety of online self-learning materials over the last decade like pedagogical agents (PA) or learning games. Regardless of this variety, educators wonder whether they can make use of these tools for their goals and if so, which tool to choose and in which context a specific tool performs best. To do so, the collection and analysis of learning data – referred to as Learning Analytics (LA) – is required. Along with digital learning environments the possibilities of applying LA are growing. Often, LA focuses on data that can easily be quantified: drop-out quota, time or grade performance. To facilitate learning in a more procedural sense, a deeper understanding of learners’ behavior in specific contexts with specific exercise designs is desired. This study therefore focuses on usage patterns. Learners’ movements through three different designs of mathematical exercises – (i) plain exercises, (ii) PA supported and (iii) fantasy game design – are analyzed with Markov chains. The results of an experiment with 503 students inform about which design facilitates what kind of learning. While the PA design lets learners enter more partial solutions, the fantasy game design facilitates exercise repetition.
Leaders’ Psychological Costs and Benefits of Servant Leadership: A Conservation of Resources View
(2025)
Servant leadership is widely recognized for its positive effects on followers, but its impact on leaders' mental health remains understudied. This gap is crucial, as servant leadership might place significant demands on leaders' psychological resources, without sufficient social, psychological, or organizational rewards. Drawing on the Conservation of Resources Theory (COR), we investigate how and when servant leadership affects leaders' mental health, viewing its role not only as resource-depleting but also as resource-generating for leaders, depending on the organizational context. Two cross-sectional studies were conducted using leader self-assessments (N = 101; N = 170). Study 1 focused on the relationship between servant leadership, experienced meaningfulness, emotional exhaustion, and flourishing, emphasizing the resource-generating potential of servant leadership. Study 2, examined the moderating effect of the distributive justice climate (DJC) on the link between servant leadership and emotional exhaustion, exploring the possibility of resource depletion under conditions of low organizational fairness. Results. In Study 1, servant leadership was found to mitigate emotional exhaustion by enhancing experienced meaningfulness at work. Moreover, it fostered leaders' flourishing through the same mechanism, suggesting that servant leadership can be a source of leaders’ well-being. Study 2 demonstrated that DJC moderates the servant leadership–emotional exhaustion relationship. Specifically, when DJC is low, servant leaders are more susceptible to emotional exhaustion, indicating that unfair organizational climates can exacerbate the resource-depleting aspects of servant leadership. Servant leadership has the potential to both reduce and exacerbate emotional exhaustion in leaders. While it generates psychological resources like experienced meaningfulness, which enhances well-being, its effectiveness is influenced by the organizational context. In unjust environments, servant leadership's emotional demands may lead to resource depletion. These findings are in line with COR and highlight the complex impact of servant leadership on the well-being of leaders. Limitations remain to issues of causality.
Phishing is an increasing threat to the security of end-users, networks, and organizations. Phishing simulations via email are a widespread tool used to measure user awareness, especially in workplace settings. However, current studies focusing on large-scale analysis of phishing simulations often have issues: The phishing simulations were conducted using a small sample size (mostly one or two organizations), or while many emails are sent, the analysis focuses only on specific companies. This study analyzes phishing simulations conducted over three years at 36 organizations with over 68 000 delivered emails. We compare different dimensions of the organizations where these simulations were conducted, such as the economic sector and departments. Furthermore, we evaluate various dimensions of phishing simulation campaigns, such as detection difficulty and the scenario under which the simulation occurs. Our findings indicate significant disparities in the results, such as the industry sector in which the company operates. Moreover, we find substantial differences between the success rates of varying scenarios used for phishing emails.
Hybrid broadcast broadband television (HbbTV) is an evolving technology that connects linear TV with modern HTML5 applications, delivering extras like games, videos, and online shopping. However, its bidirectional transmission functionality raises privacy concerns, as it introduces new tracking methods for TV channels. While previous studies focused on security issues or user awareness of HbbTV privacy challenges, a detailed examination of the tracking and transparency mechanisms of the HbbTV ecosystem is still missing. This study fills this gap by extensively analyzing these features within the European HbbTV ecosystem, and in particular within German-language TV channels. We monitored more than 350 TV channels for over 400 hours, evaluating 1) prevalent HbbTV tracking methods, 2) consent notice prevalence and user interactions, and 3) privacy policy disclosures. Our findings indicate that the HbbTV tracking system operates independently of the Web, consent notices exploit system constraints to influence users, and privacy policies often do not align with actual data practices.

