Knowledge Externalization Research Articles

The vision of the circular factory for the perpetual innovative product

Abstract The growing scarcity of global resources demands a transition from linear to circular production patterns. This article presents a novel vision for integrating linear and circular production processes within a flexible and autonomous production system to achieve perpetual product use. The approach aims to preserve the added value of products and to integrate the design of product generations and production systems. Within the circular factory, the following core aspects must be examined: predicting functions of products, managing uncertainty in used products and process sequences, learning human action for complex tasks, implementing changeable, autonomous production systems, and enabling knowledge modeling for the circular factory across domains. Aspired results are a design for circular factory, effective strategies for uncertainty management and autonomous systems adaptation as well as the externalization of operational knowledge. This research is part of the Collaborative Research Center (CRC) 1574, which explores these aspects in detail. For an in-depth understanding of specific components, it is referred to other publications by the CRC 1574.

EXTERNALIZATION OF TACIT KNOWLEDGE IN THE MENTAL MODEL OF A USER OF AN ARTIFICIAL INTELLIGENCE SYSTEM

The subject of the study is the processes of forming the user's mental model in artificial intelligence systems. The construction of such a model is associated with solving the problem of opacity and incomprehensibility of the decision-making process in such systems for end users. To solve this problem, the system user needs to receive an explanation of the obtained decision. The explanation should take into account the user's perception of the decision and the decision-making process, which is formalized within the user's mental model. The mental model considers the user's use of explicit and implicit knowledge, the latter of which usually lacks formal representation. The externalization of such knowledge ensures its transformation into a formal form. The aim of the work is to develop an approach to the externalization of implicit knowledge based on identifying patterns and causal dependencies for the decision-making process in an intelligent system when constructing the user's mental model. To achieve this goal, the following tasks are solved: developing a user's mental model of an artificial intelligence system that takes into account both explicit and implicit knowledge and developing an approach to the externalization of implicit knowledge of the user of the artificial intelligence system. A user's mental model of an artificial intelligence system that accounts for both explicit and implicit knowledge of the user is proposed. The model considers the connections between the user's explicit and implicit knowledge regarding the artificial intelligence system, the decision-making process, the method of using the decisions, and the general concept of the intelligent system. This creates conditions for the externalization of the user's implicit knowledge and the subsequent use of this knowledge in forming explanations regarding the decision-making process in the artificial intelligence system. An approach to the externalization of knowledge from the statistical and semantic layers of the user's mental model is proposed. In practical terms, the approach makes it possible to translate into explicit form the conditions and constraints regarding the formation and use of decisions in the artificial intelligence system.

BERT-based transfer learning in tacit knowledge externalization: A study case of history teachers

There has been significant progress in the field of transfer learning. However, there are still issues with inconsistent results in professional domain applications, with low-resource learning being a considerable problem. This paper proposes a language processing model for historical education built using BERT's pre-training techniques. Two experiments were conducted to obtain comparative results and choose the appropriate model method for explicating implicit expertise in secondary school history teaching. It compares traditional methods, represented by naive Bayes, to popular continuation pre-processing techniques such as domain adaptive learning and task adaptive learning to improve the effectiveness of transfer learning. Finally, this study builds targeted models based on real application needs and selects professional rules consistent with the scene application. The use of continued pre-training helps to enhance the accuracy of the professional domain model.

An Empirical Study on the Relationship between Internalization and Externalization of Chinese Wushu Tacit Knowledge Transfer

In view of the unclear relationship between internalization and externalization of current martial arts knowledge, and the unclear interaction mechanism, this study firstly analyzes the master-apprentice model of martial arts dissemination, and then uses the questionnaire survey method, factor analysis method and structural equation model method to discuss The relationship between master-apprentice relationship, master’s ability to transmit knowledge, apprentice’s ability to receive knowledge, organizational culture and its characteristics, and the relationship between the tacit degree of martial arts knowledge and the internalization and externalization effects of tacit knowledge transfer, the internalization effect of martial arts tacit knowledge is obtained with influence on externalizing effects. The conclusion is that in the process of Wushu tacit knowledge transfer, the degree of internalization of tacit knowledge has a positive impact on the degree of externalization, and it is also affected by the master’s ability to send knowledge, the apprentice’s ability to accept knowledge, and the transfer environment.

DaedalusData: Exploration, Knowledge Externalization and Labeling of Particles in Medical Manufacturing - A Design Study.

In medical diagnostics of both early disease detection and routine patient care, particle-based contamination of in-vitro diagnostics consumables poses a significant threat to patients. Objective data-driven decision-making on the severity of contamination is key for reducing patient risk, while saving time and cost in quality assessment. Our collaborators introduced us to their quality control process, including particle data acquisition through image recognition, feature extraction, and attributes reflecting the production context of particles. Shortcomings in the current process are limitations in exploring thousands of images, data-driven decision making, and ineffective knowledge externalization. Following the design study methodology, our contributions are a characterization of the problem space and requirements, the development and validation of DaedalusData, a comprehensive discussion of our study's learnings, and a generalizable framework for knowledge externalization. DaedalusData is a visual analytics system that enables domain experts to explore particle contamination patterns, label particles in label alphabets, and externalize knowledge through semi-supervised label-informed data projections. The results of our case study and user study show high usability of DaedalusData and its efficient support of experts in generating comprehensive overviews of thousands of particles, labeling of large quantities of particles, and externalizing knowledge to augment the dataset further. Reflecting on our approach, we discuss insights on dataset augmentation via human knowledge externalization, and on the scalability and trade-offs that come with the adoption of this approach in practice.

Unveiling the Crucial Role of Tacit Knowledge in Shaping Competition Within Mexican Higher Education Institutions

This study relied on a quantitative approach and used a questionnaire to gather data on elements of tacit knowledge in the university environment. The results revealed that promoting values such as peace education and respect are fundamental to the development of tacit knowledge. Additionally, it was observed that the importance of collaboration and organizational wisdom in generating tacit knowledge, as well as the relevance of teachers' technical skills, are significant factors. In conclusion, there is a need to establish channels to adequately identify tacit intangible assets in universities. It has also been suggested that a knowledge management unit can be highly useful for this purpose. It is emphasized that developing capabilities for the externalization of knowledge is essential to fully harness the potential of tacit knowledge in the university environment.

Interact: A visual what-if analysis tool for virtual product design

Virtual prototyping is increasingly used by businesses to streamline operations, cut costs, and enhance daily operations. This often includes a variety of modeling techniques among which, complex, black-box models. The path from model development to utilization in applied contexts is yet long. Domain experts need to be convinced of the validity of the models and to trust their predictions. To be used in the field, model capabilities need to be affordable, that is, allow rapid and interactive scenario building, even for non-experts. Complex relations governed by statistical interactions must be unveiled for users to understand unexpected predictions. We propose Interact, a model-agnostic, visual what-if tool for regression problems, supporting (1) the visualization of statistical interactions between features, (2) the creation of interactive what-if scenarios using predictive models, (3) the evaluation of model quality and building trust, and (4) the externalization of knowledge through model explainability. While the approach applies in various industrial contexts, we validate the application purpose and design with a detailed case study and a qualitative user study with engineers in the tire industry. By unraveling statistical interactions between features, the INTERACT tool proves to be useful to increase the transparency of black-box machine learning models. We also reflect on lessons learned concerning the development of visual what-if tools for virtual product development and beyond.

Engaging Participants in Online Interviews: Lessons Learned from Implementing a Participatory Visual Approach in Two Explorative Health Information Behavior Studies

ABSTRACTThis article provides a theoretical background on participatory approaches in (health) information behavior studies. Furthermore, it introduces and discusses the implementation of a visual participatory approach applied in two explorative health information behavior studies, each conducted online via Zoom and with the virtual whiteboard Miro. One study examined the health information behavior and digital well‐being of individuals with social anxiety (n = 22), while the other explored health information behavior in the context of false information and scientificity (n = 21). The approach aimed to actively engage participants within the interview setting through creative and visual elaboration and representation of health information interactions using the virtual whiteboard Miro. Findings show that using visual materials during face‐to‐face interviews facilitated the communication about sensitive health content and supported to capture key statements in situ, promoting the externalization of tacit knowledge during the interviews. Despite the content differences of the two studies, the unifying aspect examined in this article is how the implementation of the visual participatory approaches could enhance interview settings and lead to gathering rich data. This article fills a gap for methodological considerations of participatory techniques within (health) information behavior studies.

How can technology leverage university teaching & learning innovation? A longitudinal case study of diffusion of technology innovation from the knowledge creation perspective

This paper expands the innovation diffusion framework by adding a conceptual and empirical exploration of knowledge creation into understanding university technology-enhanced teaching and learning innovation. Institutional innovation research has largely focused on people and products while neglecting the underlying knowledge creation process for innovation that substantiates and sustains the diffusion of innovation across stages. Guided by a combined framework of organisational knowledge creation theory with the diffusion of technology-enhanced teaching & learning (T&L) innovation, this 4-year longitudinal qualitative study focused on a Chinese case of Tsinghua University, which has pioneered the adoption of digital teaching and learning, and generating exemplary sustainable whole-institutional teaching and learning innovation. We explored how technology leverages the interactions between technologies, adopters, and leadership within a university to build capacities for digital T&L innovation by tracing the technology innovation trajectory of Tsinghua University. The case study identified four stages of knowledge creation related to technology adoption and innovation. Of these stages, knowledge externalisation processes were found to be critical for leveraging the co-creation of knowledge for institutional innovation in the university context. Additionally, the study showed that the middle-up-down leadership strategy and middle managements’ knowledge management ability facilitated the sustainable transition from individual and group exploration to organisational innovation. The implications for strategic technology adoption and sustainable teaching and learning innovation in the university contexts are also discussed.

Tacit knowledge acquisition & sharing, and its influence on innovations: A Polish/US cross-country study

This study measures the relationship between tacit knowledge sharing and innovation in the Polish (n = 350) and US (n = 379) IT industries. Conceptually, the study identifies the potential sources of tacit knowledge development by individuals. That is, the study examines how “learning by doing” and “learning by interaction” lead to a willingness to share knowledge and, as a consequence, to support process and product/service innovation. This study empirically demonstrates that tacit knowledge internalization and externalization (awareness and sharing) significantly mediate between tacit knowledge experimentation and socialization (acquisition) and its final combination (knowledge in action). While such theoretical assumptions already exist, they have not yet been empirically explained and revealed in a single structural model. Further, this empirical approach enabled a demonstration that internalization and externalization of tacit knowledge may occur consciously or unconsciously with equal success. Even so, the study also showed conscious tacit knowledge’s greater impact on innovation. Therefore, an organizational effort to manage autonomous, informal, and strongly contextual tacit knowledge is worthwhile and creates the capacity for superior competitive advantage. Finally, this study also demonstrates that national context influences tacit knowledge acquisition. In the US, “learning by doing” is dominant, whereas in Poland, “learning by interaction” and critical thinking are more common. This might be related to factors such as risk acceptance that could be studied in more detail and provide opportunities for future research.

Looking at the tourism industry through the lenses of industry 4.0: a bibliometric review of concerns and challenges

PurposeThe technological and digital revolution has introduced important changes in the tourism industry. However, capturing the extent of the new tourism 4.0 paradigm is still difficult. This study aims to assess the dimensions related to the concepts of industry 4.0 in tourism and hospitality, tourism innovation and tourism ecosystem when considered simultaneously, and their role in promoting a new wave of competitiveness in the tourism industry.Design/methodology/approachA bibliometric study was conducted based on tourism 4.0, hotel 4.0, tourism innovation and tourism ecosystem using 120 eligible articles published between 2008 and 2021 from the Web of Science database.FindingsThis study demonstrated the advances in industry 4.0 in tourism and hospitality publications over 13 years and identified five interconnected dimensions: (1) knowledge transfer in tourism; (2) networking tourism innovation; (3) sources of tourism innovation; (4) smart tourism ecosystem and (5) innovation research in tourism. It was also concluded that tourism development should be a regional competence based on strategic networking and externalisation of regional knowledge flows.Research limitations/implicationsThis bibliometric review provides important implications and recommendations for several players of industry 4.0 in tourism and hospitality and policymakers. Not only did it make it possible to create a state of art, but also to categorise the existing interconnections between the dimensions of Tourism 4.0, Hotel 4.0, Tourism innovation and Tourism ecosystem to optimise its implementation and generate greater value. In addition, practical implications were inferred that improve the tourism sector’s competitiveness, helping strategic decision-making at the level of policymakers and actors in this sector.Practical implicationsApart from state of the art, this bibliometric review made it possible to categorise the existing interconnections between the dimensions of tourism 4.0, hotel 4.0, tourism innovation and tourism ecosystem to optimise its implementation and generate greater value. Practical implications were inferred that improve the tourism sector’s competitiveness, helping strategic decision-making at the level of policymakers and several players in this sector.Originality/valueThis study addresses the existing literature gap in the interconnection of industry 4.0 with tourism and hospitality by describing the most relevant conceptual interconnections and setting practical implications for improving the competitiveness of the tourism industry. Furthermore, it integrates previous studies and outlines future lines of investigation.

Improving decision making through visual knowledge calibration

PurposeThis article aims to explore the so-called illusion of explanatory depth (IOED) of managers regarding their understanding of digital technologies and examines the effect of knowledge visualization one’s current understanding and decision making. Its purpose is to show that managers think they know more than they do and that this affects decision making but can be reduced through knowledge visualization.Design/methodology/approachIn two experiments with experienced managers, the authors investigate the size and impact of the IOED bias in decision making and examine if sketched self-explanations are as effective as written self-explanations to reduce the bias.FindingsThe findings show that experienced managers suffer from a significant illusion concerning their explanatory understanding of digital technologies and that sketching one’s current level of explanatory understanding of these technologies supports the accurate calibration of one’s knowledge. The findings indicate that sketching knowledge is a helpful modality for the detection and subsequent recalibration of biased knowledge in domain-dependent decision making.Originality/valueThis article is the first to explore the effect of sketched knowledge externalization on the calibration of explanatory knowledge of managers. It extends the literature on both, the IOED and on knowledge visualization as an instrument of knowledge calibration.

Tracing teacher knowledge transformation across multiple levels in collaborative curriculum design: A comparative case study in China

This study, using the knowledge conversion framework, investigated teacher knowledge transformation occurring across individual, group and organization levels when teachers collaboratively design and enact curriculum materials. Participants from two primary schools were interviewed, accompanied by observation of teachers’ classrooms and meetings and collection of curriculum materials. Findings revealed four mechanisms through which teachers’ tacit and explicit knowledge was mutually transformed across the individual (knowledge internalization), group (knowledge externalization and socialization) and organization (knowledge combination) levels. Two different paths of teacher knowledge transformation are summarized: the top-down and unidirectional pattern, and the bottom-up and double-loop pattern. Social-contextual factors that potentially provide explanations, and practical implications are discussed.

“The old order Changeth!” Building sustainable knowledge management post COVID-19 pandemic

PurposeThe global pandemic and the resulting rapid and large-scale digitization changed the way firms recognized and understood knowledge curation and management. The changing nature of work and work systems necessitated changes in knowledge management (KM), some of which are likely to have a long-term impact. Using the lens of technology in practice, the purpose of this study is to examine the impact of technology agency on KM structures and practices that evolved across five knowledge-intensive global organizations. This study then argues that sustainable knowledge management (SKM) systems evolve in specific contexts.Design/methodology/approachThis study adopts a qualitative case study design to examine five multinational knowledge-intensive global organizations’ KM systems and practices across diverse industry sectors.FindingsBased on the findings, the authors develop SKM systems and practices model relevant to a post-pandemic organizational context. The authors argue that KM digitization and adoption support socialization in knowledge sharing. Further formalization through organizational enabling systems aids the externalization of knowledge sharing. Deliberate practices promoted with leadership support are likely to sustain in the post-COVID era. Further, organizations that evolved ad-hoc or idiosyncratic approaches to managing hybrid working are more likely to revert to legacy KM systems. The authors eventually theorize about the socialization of human-to-human and technology-mediated human interactions and develop the three emerging SKM structures.Originality/valueThis study contributed to practitioners and researchers by developing the various tenets of SKM.

Using Tacit Expert Knowledge to Support Shop-floor Operators Through a Knowledge-based Assistance System

The increasing complexity of industrial production systems is challenging employees on the shop-floor in their daily work. Specific knowledge about manufacturing processes is often not available in explicit form but mainly as tacit knowledge of experienced shop-floor workers. A systematic approach to knowledge externalization and reuse is required to make this operational knowledge available. This paper proposes a method to systematically capture and structure expert knowledge while incorporating knowledge management and social research methods. The proposed method's application and evaluation occur in a continuous manufacturing scenario, externalizing tacit knowledge about coping with manufacturing anomalies. A digital assistance system is designed and prototypically implemented to manage and reuse the externalized knowledge. The early involvement of shop-floor workers in the development phase of the prototype ensures usability and user acceptance of the assistance system. The assistance system is developed as a collaboration supporting artifact in the shop-floor's common information space. To observe the resulting productivity performance improvements in the manufacturing scenario, a KPI-based evaluation of the assistance system is presented. Finally, a discussion about the major contributions of this paper, namely the development of an approach for knowledge externalization and a human-centered design of an assistance system, takes place. To assess the novelty of these approaches, they are contrasted with the state of the art identified in the literature before a final summary of the results is presented.

Developing the Framework of Tacit Knowledge Externalization in International Construction Projects

Although tacit knowledge management has gained increasing attention in international construction projects, little effort has been devoted to the externalization of tacit knowledge for project managers and members. This research aims to explore various factors that affect the process of tacit knowledge externalization (TKE) in international construction projects and analyze the influencing mechanism and degree of these factors on the externalization effect. Based on the comprehensive literature review and in-depth investigations, a theoretical model and ten hypotheses were established. Then, data collected from 302 respondents were used to test the model and hypotheses. The results indicated that the differences among project members (i.e., culture distance and knowledge distance) reduce members' willingness to convert tacit knowledge, which negatively impacts the externalization effect. Furthermore, organizational management (i.e., organizational climate and incentive mechanism) plays an active role in increasing members' externalization willingness. Incentive mechanism and information technology are beneficial to increasing the coding level of knowledge, which positively impacts the externalization effect. Moreover, a strong willingness to convert tacit knowledge helps enhance the coding level of knowledge, thereby improving the effect of TKE. This study advances previous research by developing a framework for TKE in international construction projects, thereby offering recommendations for project managers and members to promote the externalization process.

Sustainability knowledge management and organisational learning in tourism: current approaches and areas for future development

Tourism is one of the major drivers of socio-economic growth. For tourism organisations to remain competitive, they must be able to adapt to the current dynamic scenario where the sector operates. Organisational learning strategies can provide the sector with the knowledge required to transform tourism research and intellectual property into capabilities for the industry and stimulate tourism models with a minimal effect on the environment. Knowledge management involves managing tacit and explicit information in a way that ensures it is available where and when needed. From a knowledge management perspective, environmental learning refers to the processes of acquiring, distributing and using knowledge of the natural environment, involving the processes of socialisation, externalisation, combination and internalisation of knowledge and its central aim is to improve performance. This article describes how knowledge management and organisational learning can help to achieve a sustainable tourism sector. Sustainability in this context is understood as efforts to progress simultaneously in environmental, societal and economic development. The article argues that the principles of sustainable tourism lead to both improved strategies and avenues for future research, provided they are informed and supported by learning and knowledge management; value co-creation; co-operation and trust-building; corporate social responsibility and pro-environmental behaviour.

A WELL-DEVELOPED SOFTWARE TO INTEGRATE KNOWLEDGE MANAGEMENT PROCESSES INTO THE SUPPLY CHAIN PHASES

t— The paper introduces a new software called Software Service Supply Chain Knowledge Base CLOUD (SSSC KB CLOUD). The software provides a novel solution for knowledge capture and sharing during the development of the clients’ software projects. The main aim of this software is to facilitate sharing, transferring, retrieving, and retaining of knowledge among the experts’ group who are engaged in the different phases of the software development process. The software also provides a comprehensive management tool for daily work and tasks. It provides functions and abilities to ensure effective communication, search, and knowledge retrieval. In addition, the proposed software forms the group of experts who will complete and work on the new project and provides a mechanism to perform monitoring, reporting, tracking, and knowledge mining. The research also conducts quantitative testing to confirm the software’s functionality and efficiency; a questionnaire was welldeveloped and distributed among users in two different settings: three universities and a software company, then data was collected, and results were verified on whether the software improved the overall business productivity and knowledge externalization.

When and Why Did Human Brains Decrease in Size? A New Change-Point Analysis and Insights From Brain Evolution in Ants

Human brain size nearly quadrupled in the six million years sinceHomolast shared a common ancestor with chimpanzees, but human brains are thought to have decreased in volume since the end of the last Ice Age. The timing and reason for this decrease is enigmatic. Here we use change-point analysis to estimate the timing of changes in the rate of hominin brain evolution. We find that hominin brains experienced positive rate changes at 2.1 and 1.5 million years ago, coincident with the early evolution ofHomoand technological innovations evident in the archeological record. But we also find that human brain size reduction was surprisingly recent, occurring in the last 3,000 years. Our dating does not support hypotheses concerning brain size reduction as a by-product of body size reduction, a result of a shift to an agricultural diet, or a consequence of self-domestication. We suggest our analysis supports the hypothesis that the recent decrease in brain size may instead result from the externalization of knowledge and advantages of group-level decision-making due in part to the advent of social systems of distributed cognition and the storage and sharing of information. Humans live in social groups in which multiple brains contribute to the emergence of collective intelligence. Although difficult to study in the deep history ofHomo, the impacts of group size, social organization, collective intelligence and other potential selective forces on brain evolution can be elucidated using ants as models. The remarkable ecological diversity of ants and their species richness encompasses forms convergent in aspects of human sociality, including large group size, agrarian life histories, division of labor, and collective cognition. Ants provide a wide range of social systems to generate and test hypotheses concerning brain size enlargement or reduction and aid in interpreting patterns of brain evolution identified in humans. Although humans and ants represent very different routes in social and cognitive evolution, the insights ants offer can broadly inform us of the selective forces that influence brain size.

Supporting interdisciplinary collaborative concept mapping with individual preparation phase

Concept mapping facilitates the externalisation and internalisation of knowledge by individuals during collaborative knowledge construction. However, not much is known about the individual and collaborative learning processes during collaborative concept mapping (CCM) in interdisciplinary knowledge construction. Premised on literature on collaboration scripts to scaffold the collaboration process, this study investigates the effect of an individual preparation phase prior to collaborative work on the epistemic and social processes of knowledge co-construction, as well as the degree of interdisciplinary knowledge integration in collaborative concept mapping. A total of N = 42 third year university students were put into one of the two experimental conditions: with individual preparation phase (WIP) and without individual preparation phase (WOIP). Students worked on a collaborative assignment to integrate interdisciplinary knowledge in collaborative concept mapping. Data for analysis was derived from audio recordings of the collaborative discourse in both experimental conditions. Chi-square test was conducted to investigate if there were significant differences between the effects of WIP and WOIP on the epistemological and social dimension. Findings showed that groups in the WIP condition showed significantly more verification, clarification and positioning statements in the epistemic dimension and also significantly more integration-oriented and conflict-oriented consensus building in the social dimension as compared to groups in the WOIP condition. On the degree of interdisciplinary knowledge integration, independent sample t-tests showed that there was no significant difference for concepts, domains and cross-links between the two experimental conditions. However, there was significant difference in types of cross-links for the CCMs in the WIP condition.