How Can Large Manufacturers Digitalize Their Business Models? A Framework for Orchestrating Industrial Ecosystems

For manufacturers, remaining competitive depends on their ability to digitalize their business models (i.e., offer digital and digitally enhanced products and services). To achieve this, they must engage with new digital partners and help their existing suppliers, partners, and other stakeholders to digitalize. Orchestrating this growing ecosystem is challenging. Manufacturers struggle with this endeavor because of specific barriers associated with their existing legacy business model and related to their lack of digital vision, product-centric value chains, and a bias toward firm-centered profit formulas. To overcome these barriers, leading manufacturers have developed new approaches to ecosystem orchestration.

Strategic Management of Industrial Ecosystems Based on the Platform Concept

Aim. The presented study aims to develop a structural model for industrial ecosystem management and to propose strategies for the industrial ecosystem orchestrator.Tasks. The authors systematize the landscape of existing research in the field of ecosystems; identify the problem and determine the research gap; develop the concept of ecosystem entity; determine the specific features of industrial ecosystem management; develop a structural model for industrial ecosystem management based on the platform concept; recommend strategies for the industrial ecosystem orchestrator.Methods. This study uses general scientific methods (synthesis, generalization, content analysis, graphical data interpretation), economic and statistical methods (correlation and regression analysis, mathematical statistics, expert methods, principal components analysis, hierarchical agglomerative clustering). As part of a study of economic sectors and digital technologies, the market structure is analyzed, and the dynamics of development indicators of digitalization processes is described.Results. The landscape of modern ecosystem research, types and properties of ecosystems, the composition of actors and exchange resources by ecosystem type are systematized, the concept of ecosystem entity is developed, and the specific features of industrial ecosystem management are determined. A structural model for industrial ecosystem management is developed. Four strategies for the industrial ecosystem orchestrator are recommended: increasing value, building trust, activating industrial ecology, institutionalization.Conclusions. In the context of digital transformation, it is advisable to implement strategic management of industrial ecosystems based on the platform concept. The results of managing an industrial ecosystem with the orchestrator function include enhancing the maturity and integration potential of synergetic interaction in the ecosystem, maintaining a high level of coherence (consistency) between actors at different hierarchical levels, creating long-term value and improving the quality of life.

Differences and similarities of concepts of industrial clusters and industrial ecosystems

The article considers the modern realities of the current period of time caused by the fourth industrial revolution, the technology of which is inextricably linked to the digitalization. The existing trends can lead to a decrease in social well-being due to the loss of jobs due to the introduction of self-learning machines in production, as well as environmental degradation due to the increased demand for natural resources. These possible consequences actualize the search for models for the organization of production, among which in foreign practice are recognized industrial clusters and ecosystems. In the scientific environment the definition of criteria allowing to differentiate these concepts is an insufficiently studied question. The similarities and differences between the definitions of industrial clusters and industrial ecosystems have been analyzed. There is considered the ecosystem approach for industry in terms of Industry 4.0 and digitalization. Using the method of content analysis the publications were distributed in the system of National Electronic Library (eLibrary) from 2004 to 2020. There were defined the key criteria for a comparative analysis of the studied concepts: dynamism, flexibility, openness to outside challenges, objectives, participants, territory, process chain, innovation, organizational structure. The relationship between goals and effects for industrial clusters and industrial ecosystems has been illustrated. It has been inferred that there are significant differences in the conceptual apparatus of an industrial ecosystem and an industrial cluster. It has been substantiated that industrial ecosystems are an evolutionarily more perfect form of organizing the system of interaction between industrial organizations than industrial clusters

Industrial ecosystem and revitalization of brownfields

The creation of climate-neutral industrial ecosystems based on digital leadership determines the movement of advanced countries towards competitiveness on the global stage. Industrial ecosystems of most regions of Ukraine are characterized by a low technological level of key industries and lack of organizational routines that can ensure their transition to a higher technological and resource-efficient level. The problem of forming a modern policy in the field of revitalization of abandoned areas of former industrial use (brownfields), in particular in the field of industrial waste processing, needs an urgent solution. The article is aimed at highlighting the theoretical foundations and practical aspects of creating a new industrial path through the revitalization of brownfields in underdeveloped industrial ecosystems on the example of old industrial mining regions. The paper proposes the use of a bricolage approach to create a new path of development of old industrial mining regions. This approach focuses not on the breakthrough development of the new industry, which is almost impossible in the conditions of insufficient development of industrial ecosystems, but on the gradual process of strategic cooperation of many participants (local and non-local enterprises, research institutes, local authorities, community, national and regional authorities, other stakeholders), coordination and pooling of resources at different levels, which will eventually have to evolve together, thus leading to a favorable institutional environment for the new industry. The establishment of an enterprises for the processing of coal preparation within the framework of the brownfield revitalization project is a kind of a kludge, the temporary adaptation of the community to the complex socio-economic and environmental situation, which is a consequence of the cessation of intensive coal mining, which will make it possible to create new routines of business behavior of institutions and citizens, the best of which in the process of evolutionary selection will be able to adapt to the new challenges of global technological transformations in industry and ecology. The practical implementation of the given approach is primarily represented in the creation of special institutions that are alternatives to the institutional traps of industrial development on the principles of the circular economy and relate to the introduction of more strict measures when implementing European waste management standards in national legislation and additional taxes that force enterprises to recycle waste; emergence of special enterprises (scavengers and decomposers) that use new effective disposal measures to restore and further use brownfields; creation of special community development corporations that promote economic development and environmental sustainability of the territory and ensure broad community participation in the creation of initiatives and decision-making; use of opportunities for Ukrainian integration in the field of innovation, science and education under the Association Agreement signed with the European Union in order to make effective decisions on the revitalization of brownfields.

Shared Taxonomy for the Implementation of Responsible Innovation Approach in Industrial Ecosystems

Symbolic narratives, such as an “ivory tower”, a “grey zone”, or a “black box” tell us about the gap between university and society, and academia and industry. Recently, they have been replaced by the Quadruple Helix model, which closes the gap by connecting four main stakeholders—government, university, industry, and society, into an innovation ecosystem. However, the roles of the different stakeholders are often blurred and difficult to define, and it is difficult to develop a basic approach to implement responsible innovations in industrial ecosystems in general. On the other hand, the interactions between stakeholder groups, especially universities and industry, are not sufficiently demonstrated in both scientific literature and empirical studies. We note that the responsible research and innovation (RRI) approach should facilitate a framework of shared taxonomy among stakeholders. By highlighting this situation, we follow the paradigm of emerging thinking and we seek to fill this knowledge gap theoretically and empirically. Therefore, in this study, we combined several strategies and perspectives. First, we conducted survey research concerning social capital in Poland and Lithuania to understand the impact of social capital and trust on stakeholder cooperation. Second, we conducted interviews with scientists who actively work to transfer knowledge into industry. Third, we utilized field notes from working experiences in research management. This work has theoretical and practical implications. The theoretical contribution of the paper demonstrates the construction of methodology based on emerging perspectives, and new theoretical insights, on professional discourses for implementing the responsible innovation approach in industrial ecosystems, by highlighting the commitments of main stakeholder groups. Practical input: our insights and empirical research will contribute toward sustainability policymaking and achieving substantial results in industrial ecosystems. The results indicate that if there is trust, then the government, companies, and society (in Poland and Lithuania) would be willing to cooperate with each other. However, there is a lack of trust and cooperation between universities and businesses. Stakeholders have become increasingly aware of the emergence of a science and industry cooperation as an open platform, enlarged with society and policies. They note the problem of making research public and transparent as part of a new mode of cooperation; however, they articulate RRI as a framework of shared taxonomy.

Methodology for sustainable development of industrial ecosystems

The article contains methodological aspects of sustainable development of industrial ecosystems. The relevance of the study is confirmed by the fact that the promotion of inclusive and sustainable industry and further investment in physical infrastructure, innovation and research are essential for long-term economic development. It has been concluded that the COVID-19 pandemic has such destabilizing consequences that it threatens to halt or even reverse progress towards the Sustainable Development Goals. However, a fairly rapid recovery of industry after coping with the coronavirus pandemic is possible, unlike the economy as a whole, which will require a much longer recovery period. The article proposes the architecture of the methodology for the sustainable development of industrial ecosystems, which includes five levels (paradigm, meta-level, ontology, meanings and directly ecosystem level). The paradigm in the study is the super task, the mental model of the transition to a new economy, to a new way of industrial production, to a new thinking. The meta-level of methodology is represented by the principles of sustainable development of industrial ecosystems, theoretical provisions (hypotheses, fundamental approaches, basic theories, laws of development). At the ontological level, the methodology for the sustainable development of industrial ecosystems uses digital twins, basic organizational and managerial mechanisms (procedures, tools, structures). The semantic level includes a conceptual apparatus (glossary), as well as applied theories and concepts of the sustainable development of industrial ecosystems. The ecosystem level of the methodology for sustainable development of industrial ecosystems combines the concepts of economic, ecological and natural-biological systems. The sustainable development of the industrial ecosystem is proposed to be managed at six levels (methodological, ideological, conceptual, modelling, application and technology). The conclusion concluded that an ecosystem-based economic model achieves the highest production efficiency compared to a traditional economy model and a platform-based digital model.

Digital Innovation Hubs for Enhancing the Technology Transfer and Digital Transformation of the European Manufacturing Industry

The European manufacturers are dealing with shorter product life-cycles and smaller batch sizes. Especially, the high-value products tend to be fully personalised, which makes the automatisation of the production difficult. However, the trend is that the production needs to be predictable and fully traceable to the process and even to the tool level. This adds pressure to have better data collection methods and also to increase of automation in different levels of production. The emergence of new technologies in the field of robotics allows the utilisation of automation in flexible manner. Within all areas of robotics, the demand for collaborative systems is rising as well. The level of desired collaboration and increased flexibility will only be reached if the systems are developed as whole e.g. perception, reasoning and physical manipulation. However, at the same time there is concerns on how to attract capable personnel to the factories. In order to fully implement and utilise the new robotics technologies the industry needs capable resources. For answering these needs there has been several attempts to build different types of industrial ecosystems to facilitate better the technology and knowledge transfer, and share of expertise. The main aim of the paper is to review recent actions regarding the robotics projects forming industrial ecosystems in the Horizon 2020 framework programme, and then introduce the TRINITY Digital Innovation Hub (DIH) project approach to form an industrial ecosystem in the field of robotics.