Refine
Year of publication
- 2021 (98) (remove)
Document Type
- Article (55)
- Part of a Book (14)
- Conference Proceeding (11)
- Postprint (6)
- Doctoral Thesis (5)
- Monograph/Edited Volume (4)
- Report (2)
- Contribution to a Periodical (1)
Is part of the Bibliography
- yes (98)
Keywords
- bibliometric analysis (4)
- digital platforms (4)
- COVID-19 (3)
- ERP (3)
- Industrie 4.0 (3)
- artificial intelligence (3)
- automation (3)
- co-citation analysis (3)
- knowledge management (3)
- production control (3)
Institute
- Fachgruppe Betriebswirtschaftslehre (98) (remove)
Chinas neuer langer Marsch
(2021)
The idea of the continuous improvement process (CIP) helps companies to continuously improve their operation and thereby contributes to their competitiveness. Through digi tization, new potentials emerge to solve known CIP issues. This contribution specifically addresses the individual motivation of employees to contribute to the CIP. Typically, related initiatives lack contributions over time. The use of gamification is a promising way to achieve continuous participation by addressing the individual needs of participants. While the use of extrinsic motivation elements is common in practice, the idea of this approach is to specifically address intrinsic motivations which serve as a long-term motivator. This article contributes to a gam-ification concept for the continuous improvement process. The main results include an adapted CIP, a gamification concept, and a market mechanism. Furthermore, the concept is implemented and demonstrated as a prototype in an online platform.
Software platforms allow for the extension of features by third-party contributors. Thereby, platform innovation is an important aspects of platforms attractiveness for users and complementors. While previous research focused the introduction of new features, the aspect of feature removal and discontinued features on software platforms has been disregarded. To explore the phenomenon and motivations for feature removal on software platforms, a review of recent literature is provided. To illustrate the existence of and motivations for feature removal, a case study of the browser platform Mozilla Firefox is presented. The results reveal feature removal to regularly occur on browser platforms for user- and developer-related features. Frequent reasons for feature removal involve unused features, security concerns, and bugs. Related motivations for feature removal are discussed from the platform owner's perspective. Implications for complementors and users are highlighted.
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.
The German system of public sector employment (including civil servants and public employees) qualifies as a classical European continental civil service model moulded in traditional forms of a Weberian bureaucracy. Its features include a career-based employment system with entry based on levels of formal qualification. Coordinated by legal frames and centralised collective bargaining, the civil service is, at the same time, decentralised and flexible enough to accommodate regional differences and societal changes. In comparison, the civil service system stands out for its high degrees of professionalism and legal fairness with low levels of corruption or cronyism.
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 digitalization of value networks holds out the prospect of many advantages for the participating compa- nies. Utilizing information platforms, cross-company data exchange enables increased efficiency of collab- oration and offers space for new business models and services. In addition to the technological challenges, the fear of know-how leakage appears to be a significant roadblock that hinders the beneficial realization of new business models in digital ecosystems. This paper provides the necessary building blocks of digital participation and, in particular, classifies the issue of trust creation within it as a significant success factor. Based on these findings, it presents a solution concept that, by linking the identified building blocks, offers the individual actors of the digital value network the opportunity to retain sovereignty over their data and know-how and to use the potential of extensive networking. In particular, the presented concept takes into account the relevant dilemma, that every actor (e. g. the machine users) has to be able to control his commu- nicated data at any time and have sufficient possibilities for intervention that, on the one hand, satisfy the need for protection of his knowledge and, on the other hand, do not excessively diminish the benefits of the system or the business. Taking up this perspective, this paper introduces dedicated data sovereignty and shows a possible implementation concept.
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.
Negotiations between buyers and suppliers directly influence a company’s costs, revenue, and consequently its profits. The outcome of these negotiations relies heavily on the companies’ as well as the negotiators’ power position. Across three empirical articles the author demonstrates how the own power position can first be identified as well as improved and subsequently used to maximize profits in negotiations between sellers and buyers. In the first paper the sources underlying buyer and supplier power are identified and weighted. The results of the first paper show the impact of each single sources on the buyer and supplier power. The number of suppliers available for one product is by far the most important source of power for both sides. The results indicate that a higher number of suppliers leads to a better power position of the buyer and simultaneously to an inferior power position of a single supplier. The second paper aims to examine the impact of the number of suppliers on the outcome of buyer-seller-negotiations thereby considering the innovation level of the products purchased. The results of the second study which are based on real negotiation data from a German car manufacturer indicate that the number of available suppliers has a stronger impact on the negotiation outcome for innovative than for functional, less innovative products. The third paper analyzes how the ability to take the counterpart’s perspective (perspective taking ability) influences the negotiation outcome. This relationship is examined for different power positions. The results indicate that a negotiator’s high perspective taking ability leads to a more unfavorable negotiation outcome compared to low perspective taking ability. Simultaneously, high perspective taking ability causes a more positive perception of the conducted negotiation than low perspective taking ability. This contradictory effect of perspective taking ability bears the risk for buyers and suppliers to assess an unfavorable outcome as positive. Finally, the results of the papers are summarized and discussed. The dissertation concludes with implications for practice, limitations of the work, and approaches for future research.
Industry 4.0, i.e. the connection of cyber-physical systems via the Internet in production and logistics, leads to considerable changes in the socio-technical system of the factory. The effects range from a considerable need for further training, which is exacerbated by the current shortage of skilled workers, to an opening of the previously inaccessible boundaries of the factory to third-party access, an increasing merging of office IT and manufacturing IT, and a new understanding of what machines can do with their data. This results in new requirements for the modeling, analysis and design of information processing and performance mapping business processes.
In the past, procedures were developed under the name of “process-oriented knowledge management” with which the exchange and use of knowledge in business processes could be represented, analyzed and improved. However, these approaches were limited to the office environment. A method that makes it possible to document, analyze and jointly optimize the new possibilities of knowledge processing by using artificial intelligence and machine learning in production and logistics in the same way and in a manner compatible with the approach in the office environment does not exist so far. The extension of the modeling language KMDL, which is described in this paper, will contribute to close this research gap.
This paper describes first approaches for an analysis and design method for a knowledge management integrating man and machine in the age of Industry 4.0.
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.
Since more and more business tasks are enabled by Artificial Intelligence (AI)-based techniques, the number of knowledge-intensive tasks increase as trivial tasks can be automated and non-trivial tasks demand human-machine interactions. With this, challenges regarding the management of knowledge workers and machines rise [9]. Furthermore, knowledge workers experience time pressure, which can lead to a decrease in output quality. Artificial Intelligence-based systems (AIS) have the potential to assist human workers in knowledge-intensive work. By providing a domain-specific language, contextual and situational awareness as well as their process embedding can be specified, which enables the management of human and AIS to ease knowledge transfer in a way that process time, cost and quality are improved significantly. This contribution outlines a framework to designing these systems and accounts for their implementation.
Faced with the triad of time-cost-quality, the realization of knowledge-intensive tasks at economic conditions is not trivial. Since the number of knowledge-intensive processes is increasing more and more nowadays, the efficient design of knowledge transfers at business processes as well as the target-oriented improvement of them is essential, so that process outcomes satisfy high quality criteria and economic requirements. This particularly challenges knowledge management, aiming for the assignment of ideal manifestations of influence factors on knowledge transfers to a certain task. Faced with first attempts of knowledge transfer-based process improvements [1], this paper continues research about the quantitative examination of knowledge transfers and presents a ready-to-go experiment design that is able to examine quality of knowledge transfers empirically and is suitable to examine knowledge transfers on a quantitative level. Its use is proven by the example of four influence factors, which namely are stickiness, complexity, competence and time pressure.