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The labor market is confronted with social, environmental, and economic developments that affect working conditions and individual labor relations. Lately, the Covid-19 pandemic has demonstrated and reinforced the importance of inclusive growth and sustainable work relationships. In this chapter, the smart job factory, a metamodel that supports the creation of new forms of work by redefining roles in labor, is introduced. The smart job factory is based on social entrepreneurship principles to drive innovative, sustainable, and long-term solutions to social challenges. For practical application, the model can be translated into a software solution that supports employers in the assessment of current working conditions and job roles within their companies and helps to redefine work relationships and to create new jobs. Thus, the smart job factory supports the labor market transition by systematically and proactively shaping new forms of work based on the triple bottom line of sustainable development.

Supply chain collaboration has been widely discussed in the literature. With this maturity comes a plethora of heterogeneous research that is difficult to manage and navigate. This paper, therefore...

The diversification of study programs serves to impart knowledge and skills in a way that is appropriate to the target group and to individualize learning paths in a student-centered manner. Traditional hybrid forms of learning such as the combination of face-to-face and distance learning (blended learning) are extended by new hybrid approaches. However, these often appear rather by chance than on a sound basis due to the diversity of opportunities and digital tools available today. Hybrid forms of university teaching are increasingly combined in different contexts and degrees of digitization. The resulting increase of higher education teaching complexity can only be managed through structured, transparent, and evidence-based approaches when designing learning and teaching models. The suggested Hybridx university teaching reference model describes the combination of several teaching and learning dimensions. It builds a foundation for systematically restructuring university teaching using innovative, digital approaches. Next to the conceptualization of the novel Hybridx reference model, the paper provides case study examples and recommendations for using hybrid forms of learning and teaching.

This paper presents a novel method for the analysis and implementation of Artificial Intelligence (AI) inspired collaborative supply chain management (SCM) processes. The evolving nature of supply networks and the underlying information systems drives the application of AI in this context. Within information systems research, design-science approaches have become more relevant in recent years while systems thinking is proven to be a useful method for the analysis of complex issues. The paper thus aims to present a novel approach for the analysis and optimization of collaborative supply networks. For this purpose, the topicality of and potential gains from the integration of AI for supply chain collaboration as well as the shared characteristics of systems thinking and design-science research are discussed. The paper contributes to the academic debate on approaches towards future SCM and collaboration as the methodological and research theoretical focus consolidates systems thinking and design-science research and is transferable to other application areas with dynamic processes. Furthermore, this paper presents a valuable contribution to supply chain processes in organizations of all sectors by providing a macro level perspective on the topic of collaborative SCM. A systemic viewpoint enables better understanding and incorporation of all aspects of sustainability and thus facilitates the development and optimization of future digital, collaborative and resilient SCM and the underlying information systems through the application of AI.

The idea of “Education for All” is already explained in detail in the corresponding UNESCO World Declaration in the form of a “Framework for Action to Meet Basic Learning Needs” in 1990. Interestingly, challenges for global access to education are being worked out that are still relevant today: Universalising access and promoting equity, focusing on leaning acquisition, broadening the means and scope of basic education, enhancing the environment of learning, strengthening partnerships. Since then, many things have been turned to good, much remains to be done. However, today's omnipresent digitization offers completely new opportunities to live up to this vision. Serious changes and disruptive innovations are pushed by digital transformations. (UNESCO, 1990)

Dieses Kapitel befasst sich mit den durch die digitale Transformation hervorgerufenen Veranderungen, die Unternehmen mit intensiverem Wettbewerb, Leistungsdruck und wachsenden Kundenanforderungen konfrontieren. Das Streben nach gesteigerter Wettbewerbsfahigkeit und Effizienz findet vor allem in der Implementierung (innovativer) technologischer Losungen und der zunehmend durch Automatisierung und Datenanalyse bestimmten Entscheidungsprozesse Ausdruck. Die vorgestellte Methode, das TOCI-Modell (Technological and Organisational Coherence Implementation), wurde speziell fur die Implementierung innovativer Technologien in der Unternehmenspraxis entwickelt. Die Methode berucksichtigt die Koharenz vielfaltiger Faktoren, einschlieslich der erforderlichen Anderungen der organisatorischen Entscheidungsunterstutzungsprozesse. Das TOCI-Modell wurde basierend auf bekannten Modellen aus der akademischen Literatur, wie dem Technologieakzeptanzmodell, der agilen Prozessmanagementmethode Scrum, dem CRISP-DM-Prozessmodell und dem Stage-Gate-Modell entwickelt. Daruber hinaus werden sozio-technische Systemmethoden und Erkenntnisse aus der Theorie des situativen Fuhrens eingebunden.

The last decade has seen rapid developments in the area of artificial intelligence (AI). While research focuses on technical challenges and enablers of AI, the number of publications examining application approaches at the buyer-supplier interface is increasing. To accelerate the related discussion and to add clarity and richness to this fragmented research field, a systematic overview of the existing comprehensive body of literature is essential. We contribute to the academic debate by applying a combined systematic literature review with a text mining and machine learning-based literature review. Thus, we categorize and cluster different research streams and analyze the application of AI at the buyer-supplier interface. Subsequently, we identify gaps resulting from the comparison of the technology and the application domain and derive the main points of discussion from the literature. As a result, we present ten central questions outlining future requirements and research opportunities in the field of AI application at the buyer-supplier interface.

This paper deals with the development of a generic process model for the implementation of digital Supply Chain Collaboration (SCC) concepts in future supply chains. The research undertaken in the course of this paper follows a systems theory and Action Design Research (ADR) approach to allow the researchers to take a holistic and systems-oriented perspective on Supply Chain Management (SCM). The research results were obtained through a systemic and systematic approach. This paper presents a review of the current literature as well as the theories relevant for the conceptualization of the process model, among which systems theories, Action Research (AR), ADR and interoperability play an important role. The implementation process model adapts the four iterative stages proposed by the ADR method, thereby allowing for more participation by practitioners and end-users, and potentially a more successful implementation of digital SCC processes in future supply chains. It was found that the ADR method is well-suited for the development of the implementation model as the complexity and interconnectedness of supply chain networks requires all agents to be involved in order to enable a comprehensive system innovation and digitalization.

The Triple Helix Model is used for describing innovation processes as a co-operational approach of universities, industry, and government. It is used for the development of knowledge-based relational networks of these three subsystems and influences the subdomain of sustainable education. One prerequisite for the successful application is a common understanding of quality. In a society of highly-developed countries, comprehensive quality consensus and culture is one of the most important success factors. If experience is to be transferred and cooperation is to be developed, the quality systems must be coordinated with one another. This also applies to education. However, due to the cultural peculiarities that influence the understanding of quality, an adjustment makes more sense than a simple adoption.

Intrapreneurship became a research topic of wide academic interest in recent times. Building upon previous work that focused on single aspects or influence factors that impact the success of intrapreneurial activities, this paper suggests a holistic systems theory-based approach to assess possible barriers of intrapreneurship in organizations. After an outline of previous work on intrapreneurship in general and possible related threads and risk specifically, an adapted sensitivity analysis method of Vester (2000) is applied to develop a draft model of interconnected influence factors for intrapreneurial activities in organizations. This conceptual model should serve as a basis for further empirical research on the subject and supports the understanding of interdependencies between variables in an organizational system. In accordance with findings from analyzing the literature, the application of the method to a single-case study suggests that possible barriers to intrapreneurship can be a lack of skills, creativity, knowledge or motivation of employees to act as intrapreneurs on the individual level; the organizational culture, its management, the provided working environment and a lack of agility and rule breaking tolerance on the organizational level as well as the current market situation. Future research could make use of this approach and empirically validate the results or extend them through comparative studies of successful and unsuccessful intrapreneurial activities. It could be further enhanced through semantic modelling to illustrate and capture the network of interdependencies.

For businesses high quality is an extremely important criterion to maintain and improve their competitiveness. To ensure the required quality standards for example in the automotive sector, sampling methods are common practice. This means taking a number of products out of the production line into a special quality measurement facility at the end of a specified timeframe. New 3D measurement approaches use optical systems, consisting of a variable number of stereo camera units, which can be integrated into a production line. They allow a highly precise measurement of 3D surfaces in a short time interval and therefore enable companies to check agreed quality of each product within the tact of their production line. These measurement systems use stereo photography and photogrammetry to create a 3D model of the scanned product, which can be compared with the belonging predefined standard 3D model. If this comparison detects deviations between the compared models the quality management system is able to identify these deviations by utilizing knowledge from a predefined failure catalogue and is thereby enabled to identify the fault's cause as well as its origin. In the next step the information about the faults origin is used to inform the relevant positions along the supply chain about the fault and its cause. It is furthermore used to supply the maintenance staff with guidelines for the necessary maintenance steps to allow a swift removal of possible defects as well as to trigger intrapreneurial behaviour. This paper gives an overview of the measuring system, as well as the concept for an automated failure detection and correction based on the data gained from the optical measurement process and the application of a rule based system.

Because of its positive impact on organizational growth and innovation, intrapreneurship has attracted interest in recent times. While its positive impact on organizations benefitted from extensive research over the last years, research on the willingness of employees to adopt intrapreneurial behavior remains low. This paper therefore aims to evaluate the attitudes of employees towards intrapreneurial behavior at work and what kind of working environments are suitable to encourage such behavior. Thereby, the potential risk related to such behavior is placed in the wider risk literature and then critically analyzed. The paper provides a theoretical background on intrapreneurship evincing the development of terms and definitions and identifying relevant authors in this research area. Based on previous research, the analysis of data provides new insights on employees' willingness to adopt intrapreneurial behavior and what working environments might be appropriate to support such behavior and enriches and deepens the understanding of these aspects. The findings show most respondents tended to aspire to intrapreneurial behavior and felt positively motivated towards shaping the organization's future. However, the related working environments are not always suitable and supportive for intrapreneurial behavior. Future research and the collection of further data could further enhance the understanding of employees' behavior and motivation related to intrapreneurship and a distinction of employees' and employers' thoughts might help to gain new knowledge in this field.

One more and more upcoming challenge for IT systems used in the Facility Management domain is the automated acquisition and processing of distributed heterogeneous data. Especially for approval or maintenance processes the mobile access to necessary data constantly gains significance. But because of their limited size particularly mobile devices require new ways for representing the needed amount of information. This conceptual paper discusses new approaches of knowledge acquisition and representation, which enable the efficient support of facility managers in their daily tasks. The underlying research project develops concepts and solutions for the semantic modelling and linking of distributed data as well as its context-based representation on a mobile device via Augmented Reality.

Kurzfassung Dieser Artikel beschreibt eine Konzeption zur Verbesserung des Informationsmanagements (IM) durch Integration von Informationstechnologien (IT) in globale Unternehmensnetzwerke. Die Kontrolle der Geschäftsprozesse ist unabdingbar für den unternehmerischen Erfolg. Mit der gezielten Unterstützung durch geeignete Informationstechnologien lassen sich interne und externe Geschäftsprozesse effizienter gestalten. Projekterfahrungen mit verschiedenen Unternehmen zeigen, dass für erfolgreiches IM ein netzwerkweit integriertes IT-Konzept notwendig ist. Als Konsequenz daraus wurde ein strategisches Modell entwickelt, das aus technischen und prozessorientierten Ebenen für die IT-Integration besteht. Ergänzend werden in diesem Beitrag Maßnahmen zur Realisierung der aus dem Modell resultierenden Anforderungen zusammengestellt.

Mobile Maintenance is currently a major issue for the future of the Computer Aided Facility Management (CAFM) industry. This is one of the results of a CAFM trend survey in 2013, conducted by the German Facility Management Association (Hohmann 2014). Thus, access to FM-relevant information via mobile devices gains significance. However a seamless integration of mobile devices in FM processes lacks both a systematic and sustainable use of facility life cycle data as well as an intuitionally understandable presentation of these data. The conceptual paper focusses on approaches associated with the context-based provision of information and their presentation on mobile devices, by means of Augmented Reality (AR). The underlying research project FMstar develops concepts and technologies for semantic modeling and linking of distributed life cycle data of industrial properties and their flexible and context-based utilization via AR.