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Über dieses Buch

This book features both cutting-edge contributions on managing knowledge in transformational contexts and a selection of real-world case studies. It analyzes how the disruptive power of digitization is becoming a major challenge for knowledge-based value creation worldwide, and subsequently examines the changes in how we manage information and knowledge, communicate, collaborate, learn and decide within and across organizations. The book highlights the opportunities provided by disruptive renewal, while also stressing the need for knowledge workers and organizations to transform governance, leadership and work organization. Emerging new business models and digitally enabled co-creation are presented as drivers that can help establish new ways of managing knowledge. In turn, a number of carefully selected and interpreted case studies provide a link to practice in organizations.



Value Creation in the Digitally Enabled Knowledge Economy

This chapter discusses the critical question of how to manage knowledge for value creation in digitally enabled economies. We introduce the concept of “Knowledge 4.0” to set the developments of how companies and organisations use digital technologies for knowledge creation and sharing into a historic perspective. We explain the chain of activities that create value in the digitally enabled knowledge economy following the model of the “knowledge ladder 4.0”. The model helps to relate enabling technologies to changes and new forms of managing knowledge and knowledge work. In addition, this introductory chapter summarises the key findings of the contributions presented in the subsequent chapters that we group into the four topic areas: (1) digital enrichment of resources to leverage human performance, (2) collaboration and networking, (3) leading and learning and, finally, (4) new forms of digitally enabled knowledge intensive value creation.
Klaus North, Ronald Maier, Oliver Haas

Digitally Enabled Enrichment of Resources to Leverage Human Performance


Semantic Technologies: Enabler for Knowledge 4.0

Semantic technologies are a key enabler for Knowledge 4.0. Specifically, knowledge graphs have caused significant practical implications for managing knowledge in the digital economy. While most semantic technologies originate from the vision of representing the existing Web in a machine-processable format, it’s most notable success so far are large cross-domain knowledge graphs. They are created by collaborative human modelling and linking of structured and semi-structured data. So far, they exhibit only little but still very powerful semantics, which have shown benefits for numerous applications. This chapter introduces the latest innovations in modelling knowledge using knowledge graphs and explains how those knowledge graphs enable value creation by making unstructured content, like text documents accessible by machines and humans. Finally, we show how semantic technologies help to make hard- and software components in cyber physical systems interoperable.
Achim Rettinger, Stefan Zander, Maribel Acosta, York Sure-Vetter

MEDICINE 4.0—Interplay of Intelligent Systems and Medical Experts

Healthcare professionals often have to take decisions under time constraints within a highly complex patient situation. This risky and error-prone process is fuelled additionally by an information overload due to sensor data, guidelines and ongoing updates of clinical information. Healthcare professionals need all of their experience and a lot of good luck to manage their decisions in this complex context. Acting under serious time pressure means having not enough time to gather, analyse and combine existing information. Suboptimal or wrong decisions may occur. A solution to guide and support healthcare professionals are Clinical Decision Support (CDS) systems. Today, there are many isolated CDS systems in a clinical environment causing tremendous maintenance efforts. This is one of the main drivers to centralize the authoring, maintenance and use of clinical knowledge with the help of Clinical Knowledge Management (CKM). Digitization, Artificial Intelligence (AI) applications and CKM also involves new knowledge processes, job roles and organization principles. There are new ways how experts, knowledge engineers and information technology interacts. This article describes the components of a CKM and the interplay of related job roles, limitations and challenges, and the implications of AI, CDS and CKM systems for healthcare organisations and healthcare professionals.
Hans-Peter Schnurr, Dominik Aronsky, Dirk Wenke

Data Driven Knowledge Discovery for Continuous Process Improvement

Knowledge is recognized as an organizational resource for business value creation. The work with knowledge—knowledge work—is thus an important part of value-adding processes in organizations. The ability of knowledge workers to analyze complex phenomena, interpret them and develop meaningful actions is one central part of knowledge work. The advancements of digital aids and especially the ability to analyze big amounts of data is a new phenomenon that is increasingly seen in organizations. In this work, we assume that there needs to be an interplay between digital aids and knowledge workers to allow new, deep insights into phenomena and support business value creation. We develop a model that describes how this interplay could look like and critically discuss it using real-world cases. From that, we find that it is crucial (1) separating data-driven and expert-based analysis in knowledge discovery, (2) clearly describing the problem that should be solved by the analysis, (3) understand the particular domain that analysis is applied to, (4) complement data-driven with expert-based analysis and (5) understand the entanglement of analysis and action implementation.
Michael Kohlegger, Christian Ploder

Digital Change—New Opportunities and Challenges for Tapping Experience and Lessons Learned for Organisational Value Creation

Digital change and Industry 4.0 do not erase the need for human insight or experience. This has been shown by a recent survey conducted among managers in the German-speaking world who still consider experience a highly valuable asset. Digital change, however, has shifted the focus from products to customers and implies new roles for employees such as supervising machines and processes, and assessing data analysis results. At the same time, new digital trends and tools open up new opportunities for automatically capturing, exchanging and preserving lessons learned, and offer support that is both context-aware and situation-specific. Since they should not require any additional effort, digital trends and tools may also help remove a key obstacle to innovation, i.e. the failure to learn from mistakes.
Edith Maier, Ulrich Reimer

Socializing with Robots

The term Industry 4.0 symbolizes new forms of technology and artificial intelligence, which will soon be embedded within production technologies. Smart robots are the game changers within smart factories, and they will work with humans in indispensable teams within the value chain. With this fourth industrial revolution, classical production lines are going through comprehensive modernization, which is commonly oriented to in-the-box manufacturing. Humans and machines will work side by side in so-called “hybrid teams.” Thus, the success of these future production concepts will strongly depend on the successful implementation of direct cooperation between humans and robots. Hybrid teams will, more than ever, support demographic and diverse team structures. The difficulties behind physical limitations of workers are already being compensated through human-robot-cooperation, for example, through robots assisting with heavy lifting or physical duties. As a step further, robots should be able to identify and adapt to individual strengths and weaknesses and take over the role of a workmate, helping to construct knowledge in social, teamwork-oriented processes. What is necessary to change the role of a robot from a tool to a workmate? Can appearance and behaviour of the robot influence the team building processes? This chapter seeks to blend human demands of communication and cooperation in teams with empirical results of an experiment in a virtual factory of the future. The empirical study researches if the appearance of the robot and its behaviour influences the reception of the robot as a partner and the human cooperation behaviour, for instance, in terms of a shared understanding.
Anja Richert

Collaboration and Networking


IT Support for Knowledge Processes in Digital Social Collaboration

IT support for collaboration has gone through quite some change since the beginning of the century and is providing more and more support for knowledge workers. Although single systems are getting easier to use, they are often not replacing former systems but accompany them, which makes the overall system landscape harder to oversee for knowledge workers. Future information systems should therefore combine the existing building blocks under a consistent user interface and assist the user in storing information at the right place. Seamlessly switching between formats, so that the user doesn’t have to decide upfront whether a blog entry, a wiki page or a text processor document is better suited for the information. This section discusses the development of digital collaboration solutions and shows how social software has changed them to better support knowledge processes.
René Peinl

Digital Knowledge Mapping

In this chapter, we propose that visual knowledge mapping is a very effective way of sharing, integrating and creating knowledge and value for collaborative work in organizations. We present online visual collaboration tools that enable digital change in organizations and present the theoretical bases which explains the benefits of visualization for facilitating digital collaboration. We provide illustrative examples and further propose a classification of ten visual tools to show organizations what these tools are useful for, and which criteria are relevant to assess and select visual collaborative tools. We conclude with key learnings and a checklist for the integration of visual collaboration tools in organizations.
Sebastian Kernbach, Sabrina Bresciani

How to Achieve Better Knowledge Utilization with Knowledge Externalization Mechanisms in Social Intranets

Organizations rely on employees to externalize their tacit knowledge in order to effectively conduct knowledge-intensive work processes. Tacit knowledge externalization is particularly important in times of digital transformation where product and service innovation cycles become shorter and require creative, quick decision-making. Our understanding of mechanisms that constitute tacit knowledge externalization and how this relates to knowledge use is, however, limited. This paper contributes towards closing this gap by testing whether the suggested mechanisms of content generation, storytelling, organizational communication, professional collaboration, and practice demonstration are associated with knowledge use when supported by corporate social media. The implications for research and practice are discussed.
Vanessa Bachmaier, Isabella Seeber

Balancing Knowledge Protection and Sharing to Create Digital Innovations

The creation of digital innovations requires active participation and knowledge sharing on behalf of all collaboration partners in inter-organisational settings. However, while the participants collaborate, they also have their own interests and as they are competitors in many cases, they have to protect their competitive knowledge. Collaboration thus requires balancing of knowledge sharing and protection on both the organizational and individual level. This paper reviews literature from several domains to assess how the balancing act is scoped and what kind of measures to achieve this balance prior research has identified. The balancing act is examined on the channel, partner and artefact levels. The paper identifies the balancing act as decisions made over the course of the collaboration both by the organizations as a whole, and by individuals on concrete knowledge artefacts in their daily work. Implications from the point of view of creating digital innovation are presented.
Stefan Thalmann, Ilona Ilvonen

Localizing Knowledge in Networks of SMEs—Implication of Proximities on the IT Support

The concentration of knowledge development around the economy’s big players and into few regions leads to rising inequalities of knowledge distribution. Due to shorter innovation cycles, more and more knowledge is ephemeral. To stay competitive, both trends force organizations to absorb increasingly more distant knowledge faster and with less opportunities of reuse. This situation is particularly challenging for small and medium-sized enterprises (SMEs) with their limited resources. Joining networks focused on the acquisition of external knowledge and is one promising solution for SMEs. So far, there is little research on strategies that facilitate localization of knowledge, particularly in networks of SMEs. In this paper, therefore, we first identified the phases of localizing external knowledge, followed by an investigation on the role of proximities during the localization process and the potential for supportive IT.
Stefan Thalmann, Stephan Schäper

Leading and Learning 4.0


Digital Leadership

We are living in a complex environment with dynamic and fundamental changes. A core aspect of these changes is the exponential development of new technologies. In addition to new competencies and the dynamic capability to adapt the competencies within a company, this dynamic and complex environment also leads to new leadership challenges. In an age of acceleration, managers have to juggle with different options and be agile. A pragmatic test, measure and learn approach is often more successful than very detailed analysis and long-term planning. In addition, single managers are often overstrained in such an environment. Therefore, leadership in the digital economy needs to be more decentralized and should use the collective competence and intelligence in the company. This article describes the characteristics of leadership in the digital economy as well as some adequate leadership tools. However, the article ends with a “but”, i.e. leaders should not push too hard and dump all traditional management tools. A successful leadership will typically require some kind of ambidexterity—efficient business execution and agile business adaption.
Thorsten Petry

Autosomes as Managers—A Commented Case

This chapter discusses the problems arising from the development of more and more capable and independent thinking machines, so-called “autosomes”. With this development, even the top level of knowledge workers in business are challenged, and it is not clear how things will play out. Adding autosomes to all levels of work will clearly make work-streams more efficient, but as machines start making decisions, the criteria for good and bad decisions, as well as loyalty (to the firm to the stakeholders, to mankind) may lead to unexpected results.
Daniel Weihs

Who’s in Charge?—Dealing with the Self-regulation Dilemma in Digital Learning Environments

We are now facing an ever-increasing amount of knowledge, which is becoming obsolete at an ever-faster rate. This requires us to select from this virtually infinite amount of digital information and decide what to consume and when. Fast evolving technological innovations facilitate guidance and assistance during the learning processes. Sensors emerging from novel devices such as face-readers, eye-trackers and wearables are promising to help learners to show and develop appropriate learning behaviour, strategies or processes. Such technological opportunities may deliver more accurate data for decision-making than students can access through their own self-perception. These developments lead to further questions: Who makes the better decisions about the right learning process and material—the learner or an intelligent system? Does the learner benefit from free choice or is he/she distracted and overburdened by too much freedom of decision? The dilemma of how much self-regulation (control) should be left to the learner is discussed here and different approaches from formal and informal learning environments are presented.
Per Bergamin, Franziska S. Hirt

Towards a Learning Oriented Architecture for Digitally Enabled Knowledge Work

Despite large investments and research, many Knowledge Management platforms still are not used to their full potential. In this paper, we present the learning oriented architecture for the implementation of knowledge management technology to ensure that it would contribute to a better connection of employees’ just in time learning with business demands. The framework draws on Knowledge Organisation Systems to establish this connection. We introduce four case studies in the professional services industry that have informed the framework. A key insight gained through this analysis is that Knowledge Management platforms need to better account for individual and collective perspectives in learning to realize their full potential.
Jörgen Jaanus, Nina Suomi, Tobias Ley

Competence Development for Work 4.0

Digitalization permeates nearly every sphere of life. This transformation does not only change the technical field but also the collaboration at all levels of work. This is often referred to as work 4.0. In this new world of work, an organization’s managers as well as employees need competencies enabling them to cope with the challenges of a digitized working place. Based on the findings of the major effects of the digitalization three essential categories and their corresponding competencies are outlined and described. Straightforward approaches for the development of these competencies are introduced. At the individual level the ‘Fitness Circuit for Personal Knowledge Management’ is suggested for mastering personal knowledge management. At the organizational level the ‘Agile Competence Development Cycle’ is proposed to enable organizations to establish effective and sustaining learning environments embedded in the working processes.
Angelika Mittelmann

Learning 4.0

Didactical methods and models of learning are determined by the questions of where learning content is stored and how it is accessed. The digital transformation of information storage and access therefore necessitates new models of learning and dramatic changes in educational systems. In this article, these new learning paradigms are outlined, classified and weighted for their disruptive impact on societal and industrial processes—ranging from the everywhere, every-time of digital mobile devices to human strategies for coping with information overflow.
Peter A. Henning

Transfer of Theoretical Knowledge into Work Practice: A Reflective Quiz for Stroke Nurses

Managing knowledge in periods of digital change requires not only changes in learning processes but also in knowledge transfer. For this knowledge transfer, we see reflective learning as an important strategy to keep the vast body of theoretical knowledge fresh and up-to-date, and to transfer theoretical knowledge to practical experience. In this work, we present a study situated in a qualification program for stroke nurses in Germany. In the seven-week study, 21 stroke nurses used a quiz on medical knowledge as an additional learning instrument. The quiz contained typical quiz questions (“content questions”) as well as reflective questions that aimed at stimulating nurses to reflect on the practical relevance of the learned knowledge. We particularly looked at how reflective questions can support the transfer of theoretical knowledge into practice. The results show that by playful learning and presenting reflective questions at the right time, participants reflected and related theoretical knowledge to practical experience.
Angela Fessl, Gudrun Wesiak, Viktoria Pammer-Schindler

New Forms of Knowledge-Intensive Digitally Enabled Value Creation


The Digital Transformation of Healthcare

In all areas of society we are experiencing a paradigm shift from thinking in terms of closed systems to thinking in terms of open networks. We live in a “networked” world that is characterized by networks both online and offline. Networks are non-hierarchical, inclusive, connected, complex, and open. They are constructed out of both humans and nonhumans. Networks today have become a kind of blueprint for the way in which society is being organized, including healthcare. Healthcare is no longer primarily something that takes place in the intimacy and confines of the doctor-patient relationship. Instead, health care is distributed throughout a complex network of both human and nonhuman actors such as databases, hospital information systems, digital health records, electronic health cards, online patient communities, health related apps, smart homes with ambient assisted living technologies, etc. Networks operate most efficiently when they conform to norms such as connectivity, flow of information, communication, participation, transparency, and authenticity. These norms guide the production and uses of health related information and knowledge. They condition how health related knowledge can create value both with regard to efficiency and quality of care. In this article, we take a look at how the norms of digital transformation have changed managing knowledge in health care networks.
Andréa Belliger, David J. Krieger

Piloting Digitally Enabled Knowledge Management to Improve Health Programs in Rural Bangladesh

Until recently, digitally enabled Knowledge Management (KM) activities in developing countries have more often than not been dismissed as unrealistic given challenges with access to electricity and the internet. However, a number of recent examples of holistic KM activities, including digital elements, have demonstrated a measurable contribution to improved outcomes for some of the world’s poorest people. This chapter focuses on such a case, looking at how a digitally enabled KM program was designed, piloted, and measured in two districts in Bangladesh. The program aimed to help rural community-based health workers be more informed about, and helpful in, providing health and nutrition guidance to some of the world’s poorest people.
Piers J. W. Bocock, Tara M. Sullivan, Rebecca Arnold, Rupali J. Limaye

Ubiquity and Industry 4.0

The 4.0 industry is a new productive paradigm based on digitalization. The phenomenon is based, among other factors, in so-called cyber-physical systems—that allow absolute control of what takes place inside the factory, and even outside it, allowing full awareness of the entire process in the production chain. This awareness can be understood as ubiquity, that is, virtual presence in many places simultaneously. Thus, extensive bibliographic research—carried among articles published in the last five years—reveals that the new emerging business models with 4.0 Industry are essentially based on the ubiquity of information, products, and consumers. Therefore, ubiquity expresses new models of relationships with customers and suppliers, as well as innovative ways of producing and managing organizations.
Fabricio Foresti, Gregorio Varvakis

The DAO Case—Block Chain Technology Based Knowledge Intensive Business Models

The DAO, the world’s first “distributed autonomous organization” was founded on May 15, 2016. In just a few weeks, the investment fund managed to bring in USD 119.5 million from more than 50,000 investors. The DAO was not only the biggest crowdfunding campaign of all times, it was also ground zero for the biggest cybercrime in IT history. Just a month after its launch, hackers succeeded in siphoning USD 50 million out of the fund.
Patrick Hofer

Startup and Technology Hubs

Digital transformation is affecting the economy. Startups act as role models for new software-driven business solutions by benefiting from a global innovation eco-system. To assure constant innovation, they are run on flat organizational models. A key success factor lies on their collaboration around open source software, and on how it sets a standard for the future of open innovation.
Christian Kreutz

Digital Science: Cyberinfrastructure, e-Science and Citizen Science

Digital change and scientific development have mutual implications. On one hand, science and technology development has been a major factor to digital change. On the other hand, the digital era has brought major changes to scientific knowledge production. First, there is a cyberinfrastructure—not only infrastructure for computing, but a major virtual lab where all professionals in science and technology (e.g., researchers, engineers, technicians) can collaborate and exchange data, information, and knowledge. In Europe, this new infrastructure is referred to as e-science. Second, the digital era has increased coproduction beyond frontiers of traditional players, bringing other participants to scientific development. Such kind of co-work is central to both citizen science and transdisciplinary knowledge coproduction, where non-academic players engage in activities such as planning, data gathering, and impact assessment of science. In this chapter, we define digital science as a convergent phenomenon of cyberinfrastructure, e-science, citizen science and transdisciplinarity. We examine how digital science has been a disruptive factor to traditional scientific development, changing productivity, expanding frontiers and challenging traditional processes in science, such as planning and assessment.
Roberto C. S. Pacheco, Everton R. Nascimento, Rosina O. Weber


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