Knowledge transfer

Knowledge transfer is the sharing or disseminating of knowledge and the providing of inputs to problem solving. In organizational theory, knowledge transfer is the practical problem of transferring knowledge from one part of the organization to another. Like knowledge management, knowledge transfer seeks to organize, create, capture or distribute knowledge and ensure its availability for future users. It is considered to be more than just a communication problem. If it were merely that, then a memorandum, an e-mail or a meeting would accomplish the knowledge transfer. Knowledge transfer is more complex because:
knowledge resides in organizational members, tools, tasks, and their subnetworks and
much knowledge in organizations is tacit or hard to articulate.
The subject has been taken up under the title of knowledge management since the 1990s. The term has also been applied to the transfer of knowledge at the international level.
In business, knowledge transfer now has become a common topic in mergers and acquisitions. It focuses on transferring technological platform, market experience, managerial expertise, corporate culture, and other intellectual capital that can improve the companies' competence. Since technical skills and knowledge are very important assets for firms' competence in the global competition, unsuccessful knowledge transfer can have a negative impact on corporations and lead to the expensive and time-consuming M&A not creating values to the firms.
History
Knowledge transfer between humans is a practice that likely dates back to the "Great Leap Forward" in behavioral modernity about 80,000 years ago, with the origin of speech initiating as far back as 100,000 BCE. Many scholars agree that modern human behavior can be characterized by abstract thinking, planning depth, symbolic behavior (e.g., art, ornamentation), music and dance, exploitation of large game, and blade technology, among others - "a set of traits that have come to be accepted as indicators of behavioral modernity"
The evolution of knowledge transfer from this prehistoric period can arguably be broken up into two key developments: speech and symbols.
Speech
A distinction can be drawn between speech and language. Language is not necessarily spoken: it might alternatively be written or signed. Speech is among a number of different methods of encoding and transmitting linguistic information, albeit arguably the most natural one. Language users have high-level reference (or deixis), the ability to refer to things or states of being that are not in the immediate realm of the speaker. This ability is often related to theory of mind, or an awareness of the other as a being like the self with individual wants and intentions.
Langugage may initially have been a cognitive development, with its "externalisation" to serving communicative purposes occurring later in human evolution. According to one such school of thought, the key feature distinguishing human language is recursion, (in this context, the iterative embedding of phrases within phrases). Other scholars—notably Daniel Everett—deny that recursion is universal, citing certain languages (e.g. Pirahã) which allegedly lack this feature.
Symbols
The oldest known cave painting is located within Chauvet Cave, dated to around 30,000 BC. These paintings contained increasing amounts of information: people may have created the first calendar as far back as 15,000 years ago. The connection between drawing and writing is further shown by linguistics: in Ancient Egypt and Ancient Greece the concepts and words of drawing and writing were the same (Egyptian: 's-sh', Greek: 'graphein').
Modern knowledge transfer
Argote & Ingram (2000) define knowledge transfer as "the process through which one unit (e.g., group, department, or division) is affected by the experience of another" (p. 151). They further point out the transfer of organizational knowledge (i.e., routine or best practices) can be observed through changes in the knowledge or performance of recipient units. Even though the benefits of knowledge transfer are well known, the effectiveness of the process varies considerably. The transfer of organizational knowledge, such as best practices, can be quite difficult to achieve.
Szulanski's doctoral dissertation ("Exploring internal stickiness: Impediments to the transfer of best practice within the firm") proposed that knowledge transfer within a firm is inhibited by factors other than a lack of incentive. How well knowledge about best practices remains broadly accessible within a firm depends upon the nature of that knowledge, from where (or whom) it comes, who gets it, and the organizational context within which any transfer occurs. "Stickiness" is a metaphor that comes from the difficulty of circulating fluid around an oil refinery (including effects of the fluid's native viscosity). It is worth noting that his analysis does not apply to scientific theories, where a different set of dynamics and rewards apply.
Three related concepts are "knowledge utilization", "research utilization" and "implementation", which are used in the health sciences to describe the process of bringing a new idea, practice or technology into consistent and appropriate use in a clinical setting. The study of knowledge utilization/implementation (KU/I) is a direct outgrowth of the movement toward evidence-based medicine and research concluding that health care practices with demonstrated efficacy are not consistently used in practice settings.
Knowledge transfer within organisations and between nations also raises ethical considerations particularly where there is an imbalance in power relationships (e.g. employer and employee) or in the levels of relative need for knowledge resources (such as developed and developing worlds).
Knowledge transfer includes, but encompasses more than, technology transfer.
Knowledge transfer mechanisms
Two kinds of knowledge transfer mechanisms have been noticed in practice: Personalization and Codification. Personalization refers to the one-to-one transfer of [knowledge] between two entities in person. A very good example of this is the act of teaching a person how to ride a bicycle. On the other hand, codification refers to the act of converting knowledge into knowledge artifacts such as documents, images and videos that are consumed by the knowledge recipients asynchronously. Codification can also be described as a process of defining an idea into an object.
Personalized knowledge transfer results in better assimilation of knowledge by the recipient when knowledge tacitness is higher and/or when information content in a knowledge object is high. On the other hand, codification is driven by the need to transfer knowledge to large number of people and results in better knowledge reuse. Entropy of the knowledge objects can provide a measure of their information content or tacitness.
Argote & Ingram (2000) argue, that embedding knowledge in technology has been proved to be an effective way of transferring knowledge.
A 2009 survey of MIT professors found the following channels for knowledge transfer in order of importance:
1) formal consulting;
2) publications (journal and conference papers);
3) hiring former students by industry;
4) research collaboration;
5) co-supervising students;
6) patents and licenses;
7) informal conversations;
8) conference presentations.
Subtypes of knowledge transfer
Based on the number of sources and recipients, all types of knowledge transfer can be reduced to 3 subtypes, namely: linear, divergent, and convergent. Linear Knowledge Transfer occurs when there is one source and one recipient (e.g. when one person explains a specific topic to someone else). Divergent Knowledge Transfer occurs when there is one source and multiple recipients (e.g. when a team leader outlines specific tasks for the team). Convergent Knowledge Transfer occurs when one recipient acquires information from different sources. A typical example of Convergent Knowledge Transfer is when a patient receives information about a condition from several doctors. Convergent Knowledge Transfer is especially efficient in producing in-depth knowledge of a specific topic.
Between public and private domains
With the move of advanced economies from a resource-based to a knowledge-based production, many national governments have increasingly recognized "knowledge" and "innovation" as significant driving forces of economic growth, social development, and job creation. In this context the promotion of 'knowledge transfer' has increasingly become a subject of public and economic policy. However, the long list of changing global, national and regional government programmes indicates the tension between the need to conduct 'free' research – that is motivated by interest and by private sector 'short term' objectives – and research for public interests and general common good.
The underlying assumption that there is a potential for increased collaboration between industry and universities is also underlined in much of the current innovation literature. In particular the Open Innovation approach to developing business value is explicitly based on an assumption that Universities are a "vital source for accessing external ideas". Moreover, Universities have been deemed to be "the great, largely unknown, and certainly underexploited, resource contributing to the creation of wealth and economic competitiveness."
Universities and other public sector research organisations (PSROs) have accumulated much practical experience over the years in the transfer of knowledge across the divide between the domains of publicly produced knowledge and the private exploitation of it. Many colleges and PSROs have developed processes and policies to discover, protect and exploit intellectual property (IP) rights, and to ensure that IP is successfully transferred to private corporations, or vested in new companies formed for the purposes of exploitation. Routes to commercialization of IP produced by PSROs and colleges include licensing, joint venture, new company formation and royalty-based assignments.
Organisations such as AUTM in the US, the Institute of Knowledge Transfer in the UK, SNITTS in Sweden and the Association of European Science and Technology Transfer Professionals in Europe have provided a conduit for knowledge transfer professionals across the public and private sectors to identify best practice and develop effective tools and techniques for the management of PSRO/college produced IP. On-line Communities of Practice for knowledge transfer practitioners are also emerging to facilitate connectivity (such as The Global Innovation Network and the knowledge Pool).
Business-University Collaboration was the subject of the Lambert Review in the UK in 2003.
Neuro-education seeks to improve quality of didactic methods and reduce the so called research practice gap.
In the knowledge economy
With the production factors of the knowledge economy having broadly reshaped and supplanted those of prior economic models, researchers have characterized the management and processing of organizational knowledge as vital to organizational success, with knowledge transfer in particular playing a key role in the practice of technology sharing, personnel transfers, and strategic integration.
Knowledge transfer can also be achieved through investment programme, both intentionally and unintentionally in the form of skills, technology, and ‘tacit knowledge’ including management and organisational practices. For example, foreign investment in African countries have shown to provide some knowledge transfer.
Knowledge transfer as a competitive advantage in firm
Knowledge, and especially knowledge transfer, has emerged as a key resource in the post-industrial era. This makes it an important resource for creating a sustainable competitive advantage. The resource-based view (RBV) emphasizes knowledge as a main source of competitive advantage. Knowledge transfer thus becomes a rare, valuable, imperfectly imitable and also non-substitutable strategic axis for organizations. Moreover, according to the knowledge-based vision (KBV), the more knowledge an organization has, the more it will be able to learn new knowledge, so the competitive advantage based on knowledge will be sustainable over time.
In organizations, knowledge is regularly passed on by employees to each other. Subsequently, organization resources are increased and/or updated, which allows employees to improve and adjust their practices. The acquisition of skills by employees is closely linked to the organization's performance, which is mainly the result of the skills accumulated and put into practice by employees.
One of the remarkable effects of knowledge transfer is the increase in profits and the development of competitive advantage. In a few words, a competitive advantage is the possibility for an organization to strengthen its core competencies by using knowledge from outside. For this, three elements have been defined to measure it:
Knowledge transfer contributes to the development of research and development capabilities;
Knowledge transfer provides the opportunity to replace old technologies with new ones;
Knowledge transfer contributes to reducing research and development time.
These three elements are possible when the organization possesses skills that are equal to or superior to those of its competitors, which allows it to gain a competitive advantage. In these situations, the transfer of knowledge acts on the evolution and in particular on the development of the basic knowledge already acquired by the organization. This acquisition manifests itself in the improvement of the organization's performance and therefore in the gain of a competitive advantage.
In landscape ecology
By knowledge transfer in landscape ecology, means a group of activities that increase the understanding of landscape ecology with the goal of encouraging application of this knowledge. Five factors will influence knowledge transfer from the view of forest landscape ecology: the generation of research capacity, the potential for application, the users of the knowledge, the infrastructure capacity, and the process by which knowledge is transferred (Turner, 2006).
Types of knowledge
Knowledge is a dominant feature in our post-industrial society, and knowledge workers are important in many enterprises. Blackler expands on a categorization of knowledge types that were suggested by Collins (1993):
Embrained knowledge is that which is dependent on conceptual skills and cognitive abilities. We could consider this to be practical, high-level knowledge, where objectives are met through perpetual recognition and revamping. Tacit knowledge may also be embrained, even though it is mainly subconscious.
Embodied knowledge is action oriented and consists of contextual practices. It is more of a social acquisition, as how individuals interact in and interpret their environment creates this non-explicit type of knowledge.
Encultured knowledge is the process of achieving shared understandings through socialization and acculturation. Language and negotiation become the discourse of this type of knowledge in an enterprise.
Embedded knowledge is tacit and resides within systematic routines. It relates to the relationships between roles, technologies, formal procedures and emergent routines within a complex system. In order to initiate any specific line of business knowledge transition helps a lot.
Encoded knowledge is information that is conveyed in signs and symbols (books, manuals, data bases, etc.) and decontextualized into codes of practice. Rather than being a specific type of knowledge, it deals more with the transmission, storage and interrogation of knowledge.
Knowledge transfer platforms
A recent trend is the development of online platforms aiming to optimize knowledge transfer and collaboration. Information technology (IT) systems are common computer platforms/systems that try to help organizations and people to share information and knowledge. IT systems can store, share and collect knowledge that is important to the organization. In practice, the need for IT systems or knowledge management systems is often strategic. Different knowledge management systems and platforms can provide big advantages for data systems looking to identify, transfer, share and display important metrics. Different knowledge transfer platforms are tools to share knowledge faster and more efficiently. The main idea is to help people work productively with data and knowledge.
Knowledge management systems (KMS) are computer-based systems designed to assist organizations with managing knowledge related actions. This usually involves for example: document administration, cooperation or social networking. Some of the most commonly used knowledge management systems are Microsoft SharePoint, Confluence and Documentum.
Learning management systems (LMS) are software applications, which aid with management, delivery and inspection of educational courses and training programs. They can be used in workplaces to back online or combined learning and trace learning outcomes. Among these systems are Blackboard or Moodle, although companies may use different systems such as Google Classroom, Second Life, Edmondo or others, if they are correctly adapted for the needs of the company.
Enterprise social networks (ESN) refer to specific social media platforms explicitly designed for usage within organizations. These platforms usually involve features such as instant, direct messaging and file sharing. ESNs are widely considered a form of knowledge management technology to gather their collective intelligence and improve productivity. Commonly used platforms are Microsoft Teams, Yammer or Slack.
Video conferencing tools have become increasingly popular as a tool to simplify knowledge transfer. The growth in popularity of video conferencing is mainly due to growing trend of remote work and online learning. The value of video conferencing for knowledge transfer comes from instantaneous communication, cooperation and feedback between team members. The usage of video conferencing tools is usually accompanied by the usage of other previously mentioned knowledge transfer platforms. Among these platforms belong Zoom, Microsoft Teams, Google Meet, Skype, Cisco Webex and others.
Virtual reality (VR) and Augmented reality (AR) platforms have been found to be effective due to their potential to create engaging experiences. These technologies allow real-world scenario simulations and interaction with digital objects. The engaging way in which these processes are conducted has been found to lead to improved work and learning outcomes. The usage of VR and AR is enabled by VR and AR headsets. Oculus Quest 2, Microsoft HoloLens, Google Glass and ZSpace are all among the examples for Virtual and Augmented reality headsets. These headsets run on various operating systems, some of which are specifically developed for the headsets, while others are modified versions of regular operating systems used by other smart devices.
Knowledge transfer unit
The transfer of knowledge can be viewed as the transmission of a chain of small, interchangeable, semantic units. A Knowledge Transfer Unit was defined as the smallest amount of information that can be accurately communicated.
Challenges
Factors that complicate knowledge transfer include:
The inability to recognize & articulate "compiled" or highly intuitive competencies - tacit knowledge idea
Different views on explicitness of knowledge
Geography or distance
Limitations of Information and Communication Technologies (ICTs)
Lack of a shared/superordinate social identity
Language
Areas of expertise
Internal conflicts (for example, professional territoriality)
Generational differences
Union-management relations
Incentives
Problems with sharing beliefs, assumptions, heuristics and cultural norms.
The use of visual representations to transfer knowledge (Knowledge visualization)
Previous exposure or experience with something
Misconceptions
Faulty information
Organizational culture non-conducive to knowledge sharing (the "Knowledge is power" culture)
Motivational issues, such as resistance to change and power struggles
Lack of trust
Capabilities of the receptor to interpret and absorb knowledge
Context of the knowledge (tacit, context-specific knowledge)
Inability to detect the opportunity of knowledge sharing
Everett Rogers pioneered diffusion of innovations theory, presenting a research-based model for how and why individuals and social networks adopt new ideas, practices and products. In anthropology, the concept of diffusion also explores the spread of ideas among cultures.
Process
Identifying the knowledge holders within the organization
Motivating them to share
Designing a sharing mechanism to facilitate the transfer
Executing the transfer plan
Measuring to ensure the transfer
Applying the knowledge transferred
Monitoring and evaluating
Practices
Mentorship
Guided experience
Simulation
Guided experimentation
Work shadowing
Paired work
Community of practice
Narrative transfer
Practices
Incorrect usage
Knowledge transfer is often used as a synonym for training. Furthermore, information should not be confused with knowledge, nor is it, strictly speaking, possible to "transfer" experiential knowledge to other people. Information might be thought of as facts or understood data; however, knowledge has to do with flexible and adaptable skills—a person's unique ability to wield and apply information. This fluency of application is in part what differentiates information from knowledge. Knowledge tends to be both tacit and personal; the knowledge one person has is difficult to quantify, store, and retrieve for someone else to use.
Knowledge transfer (KT) and knowledge sharing (KS) are sometimes used interchangeably or are considered to share common features. Since some knowledge management researchers assume that these two concepts are rather similar and have overlapping content, there is often confusion, especially among researchers and practitioners, about what a certain concept means. For this reason, terms such as KS and KT get used incorrectly without any respect to their real meaning and these meanings can change from paper to paper.
See also
Ignorance management
Institutional memory
Instructional theory
Knowledge management
Knowledge tagging
Knowledge translation
Communities of practice
Technology brokering
Technology transfer
Transfer of learning
Value presentation
Media richness theory
Customer knowledge
Industrial knowledge theft
Information society
Explicit knowledge
References
Further reading
Argote, L. et al. (2000). "Knowledge Transfer in Organizations: Learning from the Experience of Others", Organizational Behavior and Human Decision Processes, 82(1) (May): 1–8
Castells, M. (1996). Conclusion, The Rise of the Network Society. The Information Age: Economy, Society & Culture, Volume 1. (pp. 469–478). Oxford: Blackwell
Leonard, D.; and Swap, W. (2005) Deep Smarts: How to cultivate and transfer enduring business wisdom, HBSP.
Lipphardt, Veronika / Ludwig, David: Knowledge Transfer and Science Transfer, European History Online, Mainz: Institute of European History, 2011, retrieved: January 11, 2012
Shaw, M. (2001). "Integrating Learning Technologies: The social-cultural, pragmatic and technology design contexts", Teaching and Learning with Technology, (6)
Trautman, Steve (2006). "Teach What You Know: A Practical Leader's Guide to Knowledge Transfer", Addison-Wesley
Davenport, Thomas H.; and Prusak, Laurence (2000). Working Knowledge: How Organizations Manage What They Know, Boston Massachusetts, Harvard Business School Press
Turner, (2006). Knowledge Transfer in Forest Landscape Ecology: A Primer. In: Forest landscape ecology, transferring knowledge to practice. Perera. A.H., Buse, L.J. and Crow, T.R. (Eds), New York, Springer, 1–2.
External links
Project of knowledge transfer of the CIPRA "Future in the Alps"
"Knowledge Transfer Study – 2 Year study project for the European Commission"
Educational psychology
Information society