Unveiling the potential: Novel metaphors as cognitive processes for discovery through imagination

According to the literature review, a comprehensive model of cross-cultural knowledge transfer within MNCs that can serve as a basis for more systematic empirical work seems to be missing. To respond to this need, a conceptual model of the knowledge transfer process across geographically dispersed units of MNCs is developed. As strategy, organizational structure and functions differ across MNCs, it is suggested that no single best way of transferring knowledge exists. On the contrary, the model proposes that the transfer of knowledge has to correspond to the strategic network position of the organizational unit as well as to the unit’s internal capabilities to manage knowledge.

From the perspective of organizational knowledge alliance this paper researches knowledge transfer and innovation issues, analysis of several existing shortage of knowledge transfer model, established knowledge integration model of knowledge transfer based on knowledge alliances. Combined with the knowledge of multinational coalition practice, proposed synergy innovation model of knowledge transfer to achieve inter-organizational knowledge sharing and complementary resources and enhance organizational capacity of knowledge innovation.

The Incident Report-Based Safety Knowledge Transfer (IRSKT) model found in this paper identifies the elements necessary for social systems in workplaces to extract, disseminate and use new safety knowledge emanating from incident reports. The purpose of this paper is twofold: to understand how recent developments in systems thinking and materiality of knowledge can influence understanding of safety knowledge transfer (SKT); and to propose a new systems-based safety knowledge transfer model founded on incident reports. The paper is a review of the literature on safety knowledge transfer, materiality of knowledge and systems thinking; leading to the proposal of a new SKT paradigm. This paper shows that the IRSKT model is well suited to analyzing safety knowledge transfer in both complex and small-scale systems. Empirical studies in various systems (of complexity) environments will help affirm and enrich the model. The paper sees that in organizations where safety of employees is important, the ability to extract knowledge from incidents reports – which is an accessible and ready estimate of safety situations in organizations - is vital for establishing safe workplaces. The capacity for effective exchange and utilization of safety information inherent in incident reports by employees, equipment manufacturers, professional bodies and government agencies as reflected in IRSKT will inform the decisions to build in safety in machinery, better safety rules, effective safety campaigns and enhance safety conscious behaviours in organizations. The paper offers a new safety knowledge transfer paradigm that views safety knowledge as a systemic, emergent, embedded and materially entangled representation of reality. The proposed knowledge transfer model is different from earlier attempts, concentrating movement of safety information in incident reports and the significance stakeholders must attach to them to minimize both human and machine error. Key words: Incident reports, accidents, knowledge transfer, safety knowledge, systems analysis.

Mobile money is an electronic wallet service that allows users to store, send, and receive money. Safe and easy electronic payments make mobile money a popular alternative to bank accounts. Despite the convenient services offered to users, the adoption of mobile money is still low. Due to that, the objective of this study is to assess the perceptions of users on mobile money services as a convenient payment alternative. This study adapted the intra-organizational knowledge transfer (KT) model to understand how users perceive mobile money services. This model has been chosen because it is well accepted and recognized among the researchers. Szulanski's intra-organizational KT model consists of four stages, namely initiation, implementation, ramp-up, and integration. This study adopted interpretive structural modeling (ISM) as the methodology. ISM is a well-established methodology for identifying relationships among specific items, which define a problem or an issue. This approach has been increasingly used by various researchers to represent the interrelationships among various elements related to the issue. The data were collected using the survey. The surveys were randomly distributed via e-mail to users in Malaysia. 481 responses answered the survey. On average 69% of the respondents know about mobile money and 31% of the respondents do not know about it. Having said that, 77% of the respondents have heard of mobile money services whereby only 23% have not heard about it. These results show that around 8% of the respondents heard of mobile money services but they do not find out what it means.

PurposeThis study aims to identify effective strategies and practices for higher education institutions (HEIs) to enhance their knowledge recipients’ knowledge absorptive capacity.Design/methodology/approachQuestionnaire surveys and interviews were conducted to examine the effectiveness of a knowledge transfer (KT) project and these were administered by HEIs in Hong Kong. Pre- and post-test questionnaire surveys with t-tests were used to evaluate changes in the knowledge absorptive capacity of 1,014 participants from 20 schools. Qualitative interviews were conducted to investigate school leaders’ perception of the effectiveness of the KT strategies.FindingsResults revealed significant differences between the pre- and post-tests in all the elements of absorptive capacity. The processes of knowledge acquisition, contextualisation, internalisation and externalisation in a closed-loop mechanism were identified as effective KT strategies. Conducting training programmes, workshops, consultations, work-based studies and presentation seminars were found to be effective KT practices to support the recipients in acquiring, contextualising, internalising and externalising knowledge.Practical implicationsHEIs should provide consultative support to recipients by conducting work-based studies and presentations to enhance their knowledge absorptive capacities.Originality/valueThis study contributes empirical evidence to validate the application of Liyanage et al.’s (2009) KT model to HEIs’ KT model for the purpose of designing KT activities and enhancing the absorption capacities of the recipients. This research contributes an empirical closed-loop KT model, effective KT strategies and practices for HEIs to support their knowledge recipients so that they can internalise the acquired knowledge.

Topicality. In modern conditions, science and technology play a decisive role in the effective development of the economies of advanced countries. At the same time, in Ukraine during the years of independence science has lost its influence on socio-economic development due to the lack of an effective system of converting research results into concrete economic achievements, and the state's inability to create the necessary conditions and incentives for knowledge transfer.Aim and tasks. The purpose of the article is to substantiate the interactive model of scientific knowledge transfer to the national economy as a basis for developing practical recommendations for state regulation in this sphere, in the conditions of transition to the knowledge economy.Research results. The conceptual base of the interactive model of scientific knowledge transfer to the national economy is substantiated. In particular, the characteristics of the knowledge economy that determine the features of state regulation of the scientific knowledge transfer, namely, the emphasis on the dissemination of knowledge, not on their creation; resource approach to knowledge, and their focus on action. The classification of types of knowledge in the knowledge economy is given, and the special role of implicit knowledge is emphasized, which requires direct contact for its transfer or active participation and presence of persons who possess it. The models of the innovation process in the knowledge economy are considered and the predominance of the interactive model of innovations is shown, according to which the innovation arises as a result of interaction between knowledge producers and consumers of knowledge, which exchange both with codified and implicit knowledge.An interactive model of scientific knowledge transfer to the national economy has been developed and its distinction from the linear model of scientific knowledge transfer has been shown. Approaches to the state regulation of the scientific knowledge transfer have been formed, according to linear and interactive models based on the concept of "market failures".Conclusion. State regulation of the scientific knowledge transfer to the national economy of Ukraine should move away from a narrow understanding of this activity as the commercialization of technology, and reduction of regulatory measures in this area to intellectual property rights protection and "technology push" measures. There is a need for a broader understanding of knowledge transfer as an interactive process involving interaction between different stakeholders, and state regulation in this area should be aimed at mitigation the risks associated with the coordination and network failure of knowledge transfer actors; funding infrastructure and activities aimed at stimulating interaction between knowledge transfer stakeholders, encouraging the exchange and joint creation of knowledge.

This paper addresses the gap in the knowledge transfer literature around how universities choose specific organizational models for their knowledge transfer offices (KTOs). Organization theory points towards strong interlinkages between strategy, structure and processes in organizations. This motivates an exploration of similar links within the organizational setup of KTOs. In doing so, the paper provides a unified theoretical framework around a university's choice of structure, business model and strategic preferences for their KTOs linked to university‐specific contextual factors. A qualitative approach is used wherein four very distinct British universities are examined as individual case studies. The authors find that strategic aims of the university around practitioner engagement, the quantity of applied research and research specialization are key factors in determining the organizational characteristics of the KTO. The theoretical framework derived from the cases makes two key contributions to the university knowledge transfer literature. First, it links the university‐level contextual factors to the local model of knowledge transfer. Second, it allows us to develop a set of generic models of knowledge transfer, which can potentially guide universities to develop their own specific models.

To review knowledge transfer and exchange frameworks used in health, to analyse the core concepts of these frameworks and appraise their potential applicability to palliative care. Although there are over 60 different models of knowledge transfer and exchange designed for various areas of the fields of health care, many remain largely unrefined and untested. There is a lack of studies that create guidelines for scaling-up successful implementation of research findings and of proven models ensuring that patients have access to optimal health care, guided by current research. The protocol for this scoping review was devised according to the guidelines proposed by Arksey and O'Malley (2005) and Levac et al. (2010). The protocol includes decisions about the review objectives, inclusion criteria, search strategy, study selection, data extraction, quality assessment, data synthesis and plans for dissemination. The review will allow us to identify the currently used models of knowledge transfer and exchange in healthcare setting and analyse their applicability to the complex demands of palliative care. Results from this review will identify effective way of translating different types of knowledge to different PC providers and could be used in hospital, community and home based PC and future research.

The Intergovernmental Panel on Climate Change report unambiguously demonstrated the critical and serious nature of climate change. It specifically outlined the urgent need for new practices and technologies within the built environment, and this in turn needs effective and quick knowledge development and transfer. While, historically, construction research has presupposed the ‘pipeline’ model of knowledge transfer from academics to practitioners, often in a slow and piecemeal process, there has been a recent move towards greater involvement of practitioners in research, following theories from the social sciences about the roles of social networks and communities of practice in the co-production of knowledge. However, there is little empirical evidence to show whether the involvement of practitioners in construction research is changing either research practices or the acquisition of new knowledge by practitioners. This paper provides some of this evidence, by summarising the results from four studies to investigate how knowledge is being created within the Sustainable Urban Environment research consortia and how it is being accessed by the construction industry. It describes some of the successful approaches that are currently being followed and also highlights some of the continuing discontinuities between research and practice. Some recommendations for further improvement are suggested.

This article investigates the links between knowledge transfer activities and innovation performance in Germany and Britain through a detailed comparison of matched samples of electronics production and research establishments in the two countries. In contrast to mature industries such as mechanical engineering, German performance in electronics is not found to be greatly enhanced by the role played by intermediate research institutes in “bridging the gap” between the academic science base and business enterprises.

A transferência de conhecimentos (TC) entre projetos de desenvolvimento de produtos é um processo composto por diversas etapas. Na literatura, há vários trabalhos que apresentam essas etapas e observa-se heterogeneidade nas nomenclaturas e na organização das mesmas. Além disso, existem várias linhas de pesquisa que têm estudado a TC com diferentes propostas para a interpretação desse processo. Em razão disso, este artigo apresenta uma comparação de nove modelos de TC apresentados por autores de diferentes linhas de pesquisas que compõem dois enfoques diferentes: a dinâmica e interação de equipes (enfoque emergente) e a gestão e organização do conhecimento (enfoque de engenharia). Como resultado dessas análises comparativas, propõe-se um novo modelo de TC que apresenta uma reorganização das ideias discutidas na literatura e uma integração das diferentes propostas existentes, de maneira a se obter um modelo completo e consistente. O trabalho também ressalta as contribuições das diversas linhas de pesquisas da TC e as principais diferenças entre elas.

This article is based on the theory of knowledge transfer and takes the implementation of ERP for example. It analyses the knowledge transfer system and establishes a comprehensive system of knowledge transfer model. The purpose is to improve the effectiveness of ERP implementation. Firstly, starts with the basic principles, the whole text explains the concept of knowledge transfer, the activities of organization in knowledge transfer systems, the knowledge transfer process, the types of knowledge transfer, knowledge transfer system and so on; Secondly, it introduces the problems of knowledge transfer among the three parties, including the corporate, the software implementation party and the consulting company; Finally, it establishes an integrated system of the ERP knowledge transfer model and illustrates the degree of importance about knowledge transfer system in ERP implementation by using the upper theories and methods.

PurposeThe purpose of this paper is to propose a process model for knowledge transfer in using theories relating knowledge communication and knowledge translation.Design/methodology/approachMost of what is put forward in this paper is based on a research project titled “Procurement for innovation and knowledge transfer (ProFIK)”. The project is funded by a UK government research council – The Engineering and Physical Sciences Research Council (EPSRC). The discussions are mainly grounded on a thorough review of literature accomplished as part of the research project.FindingsThe process model developed in this paper has built upon the theory of knowledge transfer and the theory of communication. Knowledge transfer, per se, is not a mere transfer of knowledge. It involves different stages of knowledge transformation. Depending on the context of knowledge transfer, it can also be influenced by many factors; some positive and some negative. The developed model of knowledge transfer attempts to encapsulate all these issues in order to create a holistic framework.Originality/value of paperAn attempt has been made in the paper to combine some of the significant theories or findings relating to knowledge transfer together, making the paper an original and valuable one.

People learn from prior experiences. We first learn how to use a spoon and then know how to use a different size of spoon. We first learn how to sew and then learn how to embroider. Transferring knowledge from one situation to another related situation often increases the speed of learning. This observation is relevant to human learning, as well as machine learning. This thesis focuses on the problem of knowledge transfer — an area of study in machine learning. The goal of knowledge transfer is to train a system to recognize and apply knowledge acquired from previous tasks to new tasks or new domains. An effective knowledge transfer system facilitates learning processes for novel tasks, where little information is available. For example, the ability to transfer knowledge from a model that identifies writers born in the U.S. to identify writers born in Kiribati, a much lesser known country, would increase the speed of learning to identify writers born in Kiribati from scratch. In this thesis, we investigate three dimensions of knowledge transfer: what, how, and why. We present and elaborate on these questions: What type of knowledge to transfer? How to transfer knowledge across entities? Why a certain pattern of knowledge transfer is observed? We first propose Segmented Transfer — a novel knowledge transfer model — to identify and learn from the most informative partitions from prior tasks. The proposed model is applied to Wikipedia vandalism detection problem and to entity search and retrieval problem and improves the predictions. Based on the foundation of knowledge transfer and network theory, we propose Knowledge Transfer Network (KTN), a novel type of network describing transfer learning relationships among problems. KTN is not only a knowledge representation, but also a framework to select an effective and efficient ensemble of learners to improve a predictive model. This novel type of network provides insights on identifying ontological connections that were initially obscured. For example, we may observe knowledge transfer occurs among dissimilar tasks, such as transferring from using a knife and fork to using chopsticks.

As the most commonly used attack strategy by Botnets, the Domain Generation Algorithm (DGA) has strong invisibility and variability. Using deep learning models to detect different families of DGA domain names can improve the network defense ability against hackers. However, this task faces an extremely imbalanced sample size among different DGA categories, which leads to low classification accuracy for small sample categories and even classification failure for some categories. To address this issue, we introduce the long-tailed concept and augment the data of small sample categories by transferring pre-trained knowledge. Firstly, we propose the Data Balanced Review Method (DBRM) to reduce the sample size difference between the categories, thus a relatively balanced dataset for transfer learning is generated. Secondly, we propose the Knowledge Transfer Model (KTM) to enhance the knowledge of the small sample categories. KTM uses a multi-stage transfer to transfer weights from the big sample categories to the small sample categories. Furthermore, we propose the Knowledge Distillation Transfer Model (KDTM) to relieve the catastrophic forgetting problem caused by transfer learning, which adds knowledge distillation loss based on the KTM. The experimental results show that KDTM can significantly improve the classification performance of all categories, especially the small sample categories. It can achieve a state-of-the-art macro average F1 score of 84.5%. The robustness of the KDTM model is verified using three DGA datasets that follow the Pareto distributions.