Innovation

Digital technologies are crucial for the competitiveness and innovative capacity of industry. While Industry 4.0 strives for greater efficiency through the intelligent networking of people, machines and information systems, the concept of Industry 5.0 focuses on people—and defines their well-being and identification capabilities as crucial to the success of digitalization. An analysis of their success factors can only help.

The EU Strategy for sustainable and circular textiles aims to reduce the industry’s environmental impact while at the same time increasing its competitiveness. In this transition towards circularity, firms in the highly fragmented textile value chains need solutions that help overcome barriers and provide support. This paper presents digital solutions that are particularly suited for SMEs and that have been developed with public funding. It aims at encouraging SMEs, not only from the textile industry, to specify their individual transition paths towards circularity and to use digitalization to foster implementation.

Companies with traditional working and manufacturing structures face the challenge of progressive digitalization and internationalization. In order to adapt, many companies aim to develop digital and agile working skills and competences. This paper describes the conception of a digital platform to promote agility in innovation of small and mediumsized enterprises (SMEs) in structurally weak regions and to contribute to their innovativeness and future viability.

The topic of Openness is of growing importance for industry, especially in Europe. However, the term Openness is used very differently. Openness includes several concepts, including Open Source Hardware, Open Source Software, Open Data, Open Standards, Open Innovation, Open Science and Open Education. The concepts address different dimensions of Openness, all based on some kind of participation and with the goal to create more transparency and accessibility. This article defines the concepts and provides a basic understanding of their importance for industry and for greater sustainability.

Auf Basis von 36 aktuellen Literaturquellen wurden zehn Erfolgskriterien für Innovationen ermittelt. Die am häufigsten genannten Erfolgsfaktoren sind dabei zum einen das Verständnis gelebter Innovation als fester Teil der Unternehmenskultur und deren feste Verankerung auf der strategischen, taktischen und operativen, sowie die gezielte Förderung von Kundenorientierung in allen Abteilungen. Mitarbeiter von sechs ausgewählten Unternehmen wurden in persönlichen Interviews befragt, inwieweit diese Kriterien erfüllt worden sind. Aus diesen Erkenntnissen werden Best-Practice-Ideen zur Entwicklung einer optimalen Innovationskultur im Unternehmen abgeleitet.

An increased awareness of risks and rising incidents prompt companies to enhance the resilience of their supply chains. While various measures can be employed to increase resilience, a parallel consideration of a multitude of metrics is necessary to explicitly evaluate its impact on supply chain resilience. The paper presents approaches that facilitate the comparability of resilience across alternative supply chain designs by combining various metrics into a single numerical index. Additionally, innovative technologies are highlighted that can help to create resilient supply chains.

The use of artificial intelligence (AI) is becoming more important for a variety of industries, which is why enterprise resource planning (ERP) systems also offer many possible uses of AI. Due to their newly acquired, AI-based adaptability and learning abilities, modern AI-integrated ERP systems are able to develop competencies, plan processes, make forecasts and interact intelligently with humans. It is not uncommon for such systems to initiate major structural changes for companies and to open up new markets and design areas [1]. In order to measure the progress of an ERP system in terms of AI, the Center for Enterprise Research (CER) has developed an AI maturity model. Building on this model, a tool for evaluating AI integration in an ERP system should be able to showcase potential for development and enable market comparison.