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Introduction
(2021)
Im Zuge der Digitalisierung bietet Business Analytics das Potenzial, die Budgetierung insbesondere durch eine Automatisierung von Prozessschritten der Budgetierung maßgeblich weiterzuentwickeln. Dieser Beitrag zeigt mittels einer empirischen Untersuchung den Status quo des Einsatzes von Business Analytics im Rahmen der Budgetierung in Deutschland und geht auf die Beurteilung einer Automatisierung der Budgetierung durch Unternehmen ein.
As overconsumption has negative effects on ecological balance, social equality, and individual well-being, reducing consumption levels among the materially affluent is an emerging strategy for sustainable development. Today's youth form a crucial target group for intervening in unsustainable overconsumption habits and for setting the path and ideas on responsible living. This article explores young people's motivations for engaging in three behavioural patterns linked to anti-consumption (voluntary simplicity, collaborative consumption, and living within one's means) in relation to sustainability. Applying a qualitative approach, laddering interviews reveal the consequences and values behind the anti-consumption behaviours of young people of ages 14 to 24 according to a means-end chains analysis. The findings highlight potential for and the challenges involved in motivating young people to reduce material levels of consumption for the sake of sustainability. Related consumer policy tools from the fields of education and communication are identified. This article provides practical implications for policy makers, activists, and educators. Consumer policies may strengthen anti-consumption among young people by addressing individual benefits, enabling reflection on personal values, and referencing credible narratives. The presented insights can help give a voice to young consumers, who struggle to establish themselves as key players in shaping the future consumption regime.
Federal Administration
(2021)
The federal administration is significantly small (around 10 percent of all public employees). This speciality of the German administrative system is based on the division of responsibilities: the central (federal) level drafts and adopts most of the laws and public programmes, and the state level (together with the municipal level) implements them. The administration of the federal level comprises the ministries, subordinated agencies for special and selected operational tasks (e.g. the authorisation of drugs, information security and registration of refugees) in distinct administrative sectors (e.g. foreign service, armed forces and federal police). The capacity for preparing and monitoring government bills and statutory instruments is well developed. Moreover, the instruments and tools of coordination are exemplary compared with other countries, although the recent digital turn has been adopted less advanced than elsewhere.
Shortening product development cycles and fully customizable products pose major challenges for production systems. These not only have to cope with an increased product diversity but also enable high throughputs and provide a high adaptability and robustness to process variations and unforeseen incidents. To overcome these challenges, deep Reinforcement Learning (RL) has been increasingly applied for the optimization of production systems. Unlike other machine learning methods, deep RL operates on recently collected sensor-data in direct interaction with its environment and enables real-time responses to system changes. Although deep RL is already being deployed in production systems, a systematic review of the results has not yet been established. The main contribution of this paper is to provide researchers and practitioners an overview of applications and to motivate further implementations and research of deep RL supported production systems. Findings reveal that deep RL is applied in a variety of production domains, contributing to data-driven and flexible processes. In most applications, conventional methods were outperformed and implementation efforts or dependence on human experience were reduced. Nevertheless, future research must focus more on transferring the findings to real-world systems to analyze safety aspects and demonstrate reliability under prevailing conditions.
Organizations frequently try to incentivize employees to develop highly creative solutions. In this study, we examine self-set salaries as a specific type of incentive design. We investigate whether self-set salaries affect employees’ motivation and overall (creative) performance. Moreover, because self-set salaries potentially risk opportunistic employee behavior, we consider the effect of the observability of peer performance on employees’ level of self-set salaries. Using a laboratory experiment, we hold the average employee compensation constant and demonstrate that, in comparison with fixed-pay contracts, self-set salaries increase the quantitative performance in creative tasks without affecting the average creativity. However, we do not find significant differences between the amount of individuals’ self-set salaries with observability of peer performance and the amount for individuals without the chance to observe peer performance. Our findings are important for firms that rely on the development of creative ideas but are unsure about the effects of the introduction of self-set salaries
The design of qualitative, excellent teaching requires collaboration between teachers and learners. For this purpose, face-to-face teaching benefits from a long-standing tradition, while digital teaching is comparatively still at the beginning of its dissemination. A major developmental step toward the digitization of teaching was achieved in the context of university teaching during the Covid 19 pandemic in spring 2020, when face-to-face teaching was interrupted for months. During this time, important insights into the opportunities and limitations of digital teaching were gained. This paper presents selected results of a study conducted at four German universities and with 875 responses in spring 2020. The study uncovers opportunities and limitations of digital teaching from the students’ perspective and against the background of their experience in the completely digital semester. The results are used as a basis for deriving design guidelines for digital teaching and learning offerings. Based on a model for analyzing the design of teaching and learning formats, these indications are structured according to the elements learners, teachers, teaching content, environment and teaching style.
CO₂-Fußabdrücke sind ein aktuell viel diskutiertes Thema mit weitreichenden Implikationen für Individuen als auch Unternehmen. Firmen können einen proaktiven Beitrag zur Transparenz leisten, indem der unternehmens- oder produktbezogene CO₂-Fußabdruck ausgewiesen wird. Ist der Entschluss gefasst einen CO₂-Fußabdruck auszuweisen und die entstehenden Treibhausgase zu erfassen, existiert eine Vielzahl unterschiedlicher Normen und Zertifikate, wie die publicly available specification 2050, das Greenhouse Gas Protokoll oder die ISO 14067. Das Ziel dieses Beitrags ist es, diese drei Normen zur Berechnung des produktbezogenen CO₂-Fußabdrucks zu vergleichen, um Gemeinsamkeiten und Unterschiede sowie Vor- und Nachteile in der Anwendung aufzuzeigen. Die Übersicht soll Unternehmen bei der Entscheidungsfindung hinsichtlich der Eignung eines CO₂-Fußabdrucks für ihr Unternehmen unterstützen.
Robotic Process Automation (RPA) steht für die softwareunterstützte Bedienung von Softwarelösungen über deren Benutzeroberfläche. Das primäre Ziel, das mit RPA erreicht werden soll, ist die automatisierte Ausführung von Routineaufgaben, die bisher einen menschlichen Eingriff erforderten. Das Potenzial von RPA, Prozesse langfristig zu verbessern, ist allerdings stark begrenzt. Die Automatisierung von Prozessen und die Überbrückung von Medienbrüchen auf der Front-End-Ebene führt zu einer Vielzahl von Abhängigkeiten und Bedingungen, die in diesem Beitrag zusammengefasst werden. Der Weg zu einer nachhaltigen Unternehmensarchitektur (bestehend aus Prozessen und Systemen) erfordert offene, adaptive Systeme mit moderner Architektur, die sich durch ein hohes Maß an Interoperabilität auf verschiedenen Ebenen auszeichnen.