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#Gesellschaftslehre 7/8
(2022)
#Gesellschaftslehre 9/10
(2023)
'Tools' in public management
(2022)
Tools are methods or procedures, and thus operational patterns of action, applied in public administrations to solve standard problems. It is also possible to consider them as structured communication according to professional standards aiming at complexity reduction. Regularly, tools in management stem on a deductive-synoptic rationale offering a seemingly ‘objective’ decision basis. They have a strong formative influence on the organization, regularly also beyond the intended effects. The prominence of tools is sometimes confused with management as such, e.g. introducing tools is mistaken as equivalent to managing for a particular purpose. However, tools have to be closely and carefully managed regarding the objectives and purposes they should serve.
As AI technology is increasingly used in production systems, different approaches have emerged from highly decentralized small-scale AI at the edge level to centralized, cloud-based services used for higher-order optimizations. Each direction has disadvantages ranging from the lack of computational power at the edge level to the reliance on stable network connections with the centralized approach. Thus, a hybrid approach with centralized and decentralized components that possess specific abilities and interact is preferred. However, the distribution of AI capabilities leads to problems in self-adapting learning systems, as knowledgebases can diverge when no central coordination is present. Edge components will specialize in distinctive patterns (overlearn), which hampers their adaptability for different cases. Therefore, this paper aims to present a concept for a distributed interchangeable knowledge base in CPPS. The approach is based on various AI components and concepts for each participating node. A service-oriented infrastructure allows a decentralized, loosely coupled architecture of the CPPS. By exchanging knowledge bases between nodes, the overall system should become more adaptive, as each node can “forget” their present specialization.
In nowadays production, fluctuations in demand, shortening product life-cycles, and highly configurable products require an adaptive and robust control approach to maintain competitiveness. This approach must not only optimise desired production objectives but also cope with unforeseen machine failures, rush orders, and changes in short-term demand. Previous control approaches were often implemented using a single operations layer and a standalone deep learning approach, which may not adequately address the complex organisational demands of modern manufacturing systems. To address this challenge, we propose a hyper-heuristics control model within a semi-heterarchical production system, in which multiple manufacturing and distribution agents are spread across pre-defined modules. The agents employ a deep reinforcement learning algorithm to learn a policy for selecting low-level heuristics in a situation-specific manner, thereby leveraging system performance and adaptability. We tested our approach in simulation and transferred it to a hybrid production environment. By that, we were able to demonstrate its multi-objective optimisation capabilities compared to conventional approaches in terms of mean throughput time, tardiness, and processing of prioritised orders in a multi-layered production system. The modular design is promising in reducing the overall system complexity and facilitates a quick and seamless integration into other scenarios.
In nowadays production, fluctuations in demand, shortening product life-cycles, and highly configurable products require an adaptive and robust control approach to maintain competitiveness. This approach must not only optimise desired production objectives but also cope with unforeseen machine failures, rush orders, and changes in short-term demand. Previous control approaches were often implemented using a single operations layer and a standalone deep learning approach, which may not adequately address the complex organisational demands of modern manufacturing systems. To address this challenge, we propose a hyper-heuristics control model within a semi-heterarchical production system, in which multiple manufacturing and distribution agents are spread across pre-defined modules. The agents employ a deep reinforcement learning algorithm to learn a policy for selecting low-level heuristics in a situation-specific manner, thereby leveraging system performance and adaptability. We tested our approach in simulation and transferred it to a hybrid production environment. By that, we were able to demonstrate its multi-objective optimisation capabilities compared to conventional approaches in terms of mean throughput time, tardiness, and processing of prioritised orders in a multi-layered production system. The modular design is promising in reducing the overall system complexity and facilitates a quick and seamless integration into other scenarios.
A multidimensional and analytical perspective on Open Educational Practices in the 21st century
(2022)
Participatory approaches to teaching and learning are experiencing a new lease on life in the 21st century as a result of the rapid technology development. Knowledge, practices, and tools can be shared across spatial and temporal boundaries in higher education by means of Open Educational Resources, Massive Open Online Courses, and open-source technologies. In this context, the Open Education Movement calls for new didactic approaches that encourage greater learner participation in formal higher education. Based on a representative literature review and focus group research, in this study an analytical framework was developed that enables researchers and practitioners to assess the form of participation in formal, collaborative teaching and learning practices. The analytical framework is focused on the micro-level of higher education, in particular on the interaction between students and lecturers when organizing the curriculum. For this purpose, the research reflects anew on the concept of participation, taking into account existing stage models for participation in the educational context. These are then brought together with the dimensions of teaching and learning processes, such as methods, objectives and content, etc. This paper aims to make a valuable contribution to the opening up of learning and teaching, and expands the discourse around possibilities for interpreting Open Educational Practices.
A multidimensional and analytical perspective on Open Educational Practices in the 21st century
(2022)
Participatory approaches to teaching and learning are experiencing a new lease on life in the 21st century as a result of the rapid technology development. Knowledge, practices, and tools can be shared across spatial and temporal boundaries in higher education by means of Open Educational Resources, Massive Open Online Courses, and open-source technologies. In this context, the Open Education Movement calls for new didactic approaches that encourage greater learner participation in formal higher education. Based on a representative literature review and focus group research, in this study an analytical framework was developed that enables researchers and practitioners to assess the form of participation in formal, collaborative teaching and learning practices. The analytical framework is focused on the micro-level of higher education, in particular on the interaction between students and lecturers when organizing the curriculum. For this purpose, the research reflects anew on the concept of participation, taking into account existing stage models for participation in the educational context. These are then brought together with the dimensions of teaching and learning processes, such as methods, objectives and content, etc. This paper aims to make a valuable contribution to the opening up of learning and teaching, and expands the discourse around possibilities for interpreting Open Educational Practices.
Purpose - The purpose of this study is to analyze whether negotiators stick to one single negotiation style or whether their styles vary during the negotiation process. The paper seeks to identify different combinations of phase-specific negotiation styles and investigates the relationship between these combinations and negotiation performance and satisfaction. Design/methodology/approach - The study is based on a large online negotiation simulation that allows a phase-specific analysis of negotiation styles via an elaborate coding scheme. Findings - The findings reveal that negotiators generally do not limit themselves to a single negotiation style. Instead, they vary their style in the course of different negotiation phases. The authors distinguish between five distinct phase-specific negotiation style patterns that differ with regard to their impact on negotiation performance but not negotiation satisfaction. Practical implications - Negotiation practitioners get to know different phase-specific negotiation style patterns and get insights into which pattern is the most promising for negotiation performance. As a result, they can acquire this phase-specific negotiation style pattern to enhance their performance. Originality/value - The paper contributes to existing negotiation style literature, because it is the first to analyze negotiation styles from a phase-specific point of view.
The digital transformation sets new requirements to all classes of enterprise systems in companies. ERP systems in particular, which represent the dominant class of enterprise systems, are struggling to meet the new requirements at all levels of the architecture. Therefore, there is an urgent need to reconsider the overall architecture of the systems and address the root of the related issues. Given that many restrictions ERP pose on their adaptability are related to the standardization of data, the database layer of ERP systems is addressed. Since database serve as the foundation for data storage and retrieval, they limit the flexibility of enterprise systems and the chance to adapt to new requirements accordingly. So far, relational databases are widely used. Using a systematic literature approach, recent requirements for ERP systems were identified. Prominent database approaches were assessed against the 23 requirements identified. The results reveal the strengths and weaknesses of recent database approaches. To this end, the results highlight the demand to combine multiple database approaches to fulfill recent business requirements. From a conceptual point of view, this paper supports the idea of federated databases which are interoperable to fulfill future requirements and support business operation. This research forms the basis for renewal of the current generation of ERP systems and proposes to ERP vendors to use different database concepts in the future.
Manufacturing companies still have relatively few points of contact with the circular economy. Especially, extending life time of whole products or parts via remanufacturing is an promising approach to reduce waste. However, necessary cost-efficient assessment of the condition of the individual parts is challenging and assessment procedures are technically complex (e.g., scanning and testing procedures). Furthermore, these assessment procedures are usually only available after the disassembly process has been completed. This is where conceptualization, data acquisition and simulation of remanufacturing processes can help. One major constraining aspect of remanufacturing is reducing logistic efforts, since these also have negative external effects on the environment. Thus regionalization is an additional but in the end consequential challenge for remanufacturing. This article aims to fill a gap by providing an regional remanufacturing approach, in particular the design of local remanufacturing chains. Thereby, further focus lies on modeling and simulating alternative courses of action, including feasibility study and eco-nomic assessment.
Higher eco-efficiency will not be enough to slow global warming caused by climate change. To keep global warming to 2 degrees, people also need to reduce their consumption. At present, however, many who would be able to do so seem unwilling to comply. Given the threats of a runaway climate change, urgent measures are needed to promote less personal consumption. This study, therefore, examines whether social marketing consume-less appeals can be used to encourage consumers to voluntarily abstain from consumption. As part of an online experiment with nearly 2000 randomly sampled users of an online platform for sustainable consumption, we tested the effectiveness of five different “consume-less” appeals based on traditional advertising formats (including emotional, informational, and social claims). The study shows that consume-less appeals are capable of limiting personal desire to buy. However, significant differences in the effectiveness of the appeal formats used in this study were observed. In addition, we found evidence of rebound effects, which leads us to critically evaluate the overall potential of social marketing to promote more resource-conserving lifestyles. While commercial consumer-free appeals have previously been studied (e.g., Patagonia’s “Don’t Buy This Jacked”), this study on the effectiveness of non-commercial consume-free appeals is novel and provides new insights.
This study investigates the effect of different anticonsumption constructs on consumer wellbeing. The study assumes that people will only lower their level of consumption if doing so does not also lower personal wellbeing. More precisely, this research investigates how specific subtypes of sustainable anticonsumption (e.g., voluntary simplicity, collaborative consumption, and debt-free living) relate to different states of consumer's wellbeing (e.g., financial, psychosocial, and subjective wellbeing). This work also examines whether consumer empowerment can improve personal wellbeing and strengthen the anticonsumption wellbeing relationship. The results show that voluntarily foregoing consumption does not reduce wellbeing and consumer empowerment plays a significant role in supporting sustainable pathways to consumer wellbeing. This study reasons that empowerment improves consumer sovereignty, but may be detrimental for consumers heavily concerned about debt-free living. The present investigation concludes by proposing implications for public and consumer policymakers wishing to promote appropriate sustainable (anticonsumption) pathways to consumer wellbeing.
Purpose:
The purpose of this paper is to examine the expectations, perceptions and role understanding of academic staff using a model of academic competencies (i.e. time management, learning skills, technology proficiency, self-monitoring and research skills).
Design/methodology/approach:
Semi-structured interviews were conducted with ten members of academic staff at a German university. Participants’ responses to the open-ended questions were coded inductively, while responses concerning the proposed model of academic competencies were coded deductively using a priori categories.
Findings:
Participating academic staff expected first-year students to be most competent in time management and in learning skills; they perceived students’ technology proficiency to be rather high but their research skills as low. Interviews indicated a mismatch between academic staff expectations and perceptions.
Practical implications:
These findings may enable universities to provide support services for first-year students to help them to adjust to the demands of higher education. They may also serve as a platform to discuss how academic staff can support students to develop the required academic competencies, as well as a broader conversation about higher education pedagogy and competency assessment.
Originality/value:
Little research has investigated the perspectives of academic staff concerning the academic competencies they expect of first-year students. Understanding their perspectives is crucial for improving the quality of institutions; their input into the design of effective support services is essential, as is a constructive dialogue to identify strategies to enhance student retention.
Accelerating knowledge
(2019)
As knowledge-intensive processes are often carried out in teams and demand for knowledge transfers among various knowledge carriers, any optimization in regard to the acceleration of knowledge transfers obtains a great economic potential. Exemplified with product development projects, knowledge transfers focus on knowledge acquired in former situations and product generations. An adjustment in the manifestation of knowledge transfers in its concrete situation, here called intervention, therefore can directly be connected to the adequate speed optimization of knowledge-intensive process steps. This contribution presents the specification of seven concrete interventions following an intervention template. Further, it describes the design and results of a workshop with experts as a descriptive study. The workshop was used to assess the practical relevance of interventions designed as well as the identification of practical success factors and barriers of their implementation.
In social networks or, more specifically, online communities on tech-products, opinion leaders are important sources of advice for other consumers in the adoption and diffusion of new products. However, possibilities for potential users to exert their influence on opinion leadership are ignored. This study determines whether and how lead users may serve as opinion leaders in social networks and advise other consumers in the adoption and diffusion of new products. Our survey with 308 users in the Xiaomi and Huawei communities suggests that higher lead userness is positively and significantly associated with the likelihood of opinion giving and passing. Product-possessing innovativeness has a higher impact compared with information-possessing innovativeness. Product involvement does not enhance the effect of information-possessing innovativeness. The findings provide a better understanding of the formation of opinion leadership in social networks for an accelerated diffusion of new products.
A growing number of business processes can be characterized as knowledge-intensive. The ability to speed up the transfer of knowledge between any kind of knowledge carriers in business processes with AR techniques can lead to a huge competitive advantage, for instance in manufacturing. This includes the transfer of person-bound knowledge as well as externalized knowledge of physical and virtual objects. The contribution builds on a time-dependent knowledge transfer model and conceptualizes an adaptable, AR-based application. Having the intention to accelerate the speed of knowledge transfers between a manufacturer and an information system, empirical results of an experimentation show the validity of this approach. For the first time, it will be possible to discover how to improve the transfer among knowledge carriers of an organization with knowledge-driven information systems (KDIS). Within an experiment setting, the paper shows how to improve the quantitative effects regarding the quality and amount of time needed for an example manufacturing process realization by an adaptable KDIS.
Für die Wettbewerbsfähigkeit von Unternehmen hat der Kontinuierliche Verbesserungsprozess (KVP) eine hohe Bedeutung. Hinsichtlich der Qualität und Quantität der Beiträge für den KVP durch die Mitarbeitenden stoßen Unternehmen, insbesondere KMU, jedoch auf vielfältige Herausforderungen. Diesen Problemen können Unternehmen durch das KVP-Tool begegnen, welches im Projekt „Adaptive Spielifizierung im KVP“ entwickelt wird. Durch die Digitalisierung und Spielifizierung des Prozes- ses im KVP-Tool wird die kontinuierliche Beteiligung nachhaltig durch intrinsische Anreize gefördert. Die Neuartigkeit des Projektes ergibt sich aus der Adaptivität der Spielifizierung, also die Wechselwirkung zu den Nutzenden. Dabei werden zwei Aspekte fokussiert: unterschiedliche Spielertypen und Marktdynamik.