Because of the rapid development of strategies for promoting wider information use during the "information age", a family of terms – knowledge transfer, learning, transfer of learning, and knowledge sharing – are often used interchangeably or as synonyms. While the concepts of knowledge transfer, learning, and transfer of learning are defined in closely related terms, they are different notions. According to conventional usage in psychology, Transfer of Learning occurs in people when they apply already learned information, strategies, and skills to a new situation or context. Another concept of learning is attributed to all animals and even certain plants. Learning in humans starts before birth. According to cognitive psychology, learning begins from unaware and, even before birth during pregnancy, from non-perceptual processes of distinguishing sensory stimuli. In contrast to both above, knowledge transfer is a process in humans that requires intention from both sides: to share facts or skills from one side and acquire new knowledge from another (see the definition of knowledge transfer).
The most significant difficulties exist with separating the terms knowledge transfer and knowledge sharing. According to Paulin and Suneson (2012), their distinction is based on different representations of the relationship between knowledge and its context by different authors. Scientists who use the term knowledge transfer intend knowledge as an object without regard to the context; they amplify the enablers, suppress disabling conditions, and overcome obstacles, including the barriers, if they want to create good conditions for knowledge flow. Scholars who believe that knowledge is something that is constructed in a social context and which cannot be separated from the context (or the individual) use knowledge sharing and focus more on the development of "space" or "environment" to better fit individuals who need to develop personal knowledge with the help of those who have already developed it. Another approach suggests that knowledge sharing is a subset of knowledge transfer. Knowledge sharing refers to a linear (unidirectional) process using a personalization strategy. Knowledge transfer is a non-linear (bidirectional) process that may also proceed unidirectionally (as those linear in Knowledge sharing). According to Tangaraja and colleagues (2016), the essential peculiarity of knowledge transfer is that it is distinguished by the strategy used. Indeed, the meaning of the word transfer implies the aim since the dictionary defines it as the process "to move someone or something from one place, vehicle, person, or group to another". In contrast, sharing refers to "having or using something simultaneously as someone else" without targeting.
The brief overview of related fields of knowledge introduces the main concepts that scholars consider when studying the current topic.
In psychology, knowledge transfer is also based on the notion of cognitive schema and involves essential processes of Assimilation and Accommodation. Assimilation refers to an interpretation of new information within the framework of existing cognitive schema. It is the reuse of existing schemata to fit the new information. Accommodation refers to making minor changes to acquired knowledge to create a new schema for that knowledge to cope with things that do not fit existing schemas. In terms of psychology, knowledge transfer relates to the transformability of the transferred knowledge for assimilating by existing cognitive schemas and the translatability of the source practice for creating the new cognitive schema in the accommodation.
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.
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 scientific study of knowledge transfer began in the first half of the twentieth century, focusing mainly on innovation adoption by individuals. In 1943, Ryan and Gross (1943) recognized the diffusion of innovation as an essential social process where interpersonal contact may play a pivotal role.
The period since 1945 has been characterized as the information age that increased motivation to develop strategies for promoting its wider use. After the Second War, three principal demands encouraged academic research on the topic: (a) a desire for rapid technological change to stimulate more significant economic growth; (b) a desire to enhance the transfer of technology emerging from defence and space-related research; and (c) a desire to promote the adoption of innovations in health, education, and human services. Numerous research studies tested different strategies of knowledge distribution: print materials, films, videotapes, audiocassettes, consultation, organization development, technical assistance, network arrangements, training conferences and workshops, and participant observation.
In 1991, Backer (1991) proposed six crucial points for knowledge utilization:
During the first years after its reemergence, the notion of Knowledge transfer was usually treated in line with the notion of the knowledge-based theory of the firm. One of the most commonly cited authors here was Szulanski, who in numerous books and articles had developed the notion of knowledge transfer, especially regarding intra-firm knowledge. His early work clearly stated that knowledge is regarded as a firm's stock. 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.
Argote and Ingram (2000) defined 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 pointed 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.
Knowledge transfer can lead to a number of outcomes for organizations, including: greater decision making, improved customer relations, innovation performance, financial performance, transfer effectiveness, transfer efficiency, patent, new product development, and technological leadership. The growing body of literature shows two sets of research on knowledge transfer. One set of studies focus on understanding the individual level and extending to group dynamics, e.g. aiming to better understand trust, respect, relationships, self-efficacy. The second set of studies focus on the organizational level, e.g. discussing cultural aspects, structure, rewards and recognition, policy norms, training, relations.
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).
Translation of knowledge implies the decontextualization and contextualization of knowledge which the entity possess in explicit and tacit forms (also see the Section "Overview"). Explicit knowledge is an awareness of facts or skills that can be readily articulated, conceptualized, codified, formalized, stored and accessed. Tacit knowledge can be defined as skills, ideas and experiences that are possessed by people but are not codified and may not necessarily be easily expressed.
According to Professor Nonaka (2009), the distinction between explicit and tacit knowledge suggests four basic patterns for translating knowledge where they interact in a spiral manner.
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.
Communication studies systematize our understanding of the communication process by introducing models of communication that describe different modalities of message exchange (see also the section "Overview"). In the case of explicit knowledge, all models are reduced to the simple scheme. A source (a sender in terms of communication studies) encodes information as a message and sends it to the recipient (a receiver) through a channel. The recipient needs to decode the message to understand the initial idea and provides some form of feedback. In both cases, the third player is the noise that may interfere and distort the message. The two modes of knowledge transfer – the linear (a unidirectional process) and non-linear (a multi-directional) – encompass a set of different configurations of models.
For instance, according to Sailer and colleagues (2021), 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.
The transfer of tacit knowledge has yet to be studied.
Given the contributions of key theorists (see the above sections), a guide to the knowledge transfer process may be generalized in the following translation procedure:
1) The first stage aims at establishing the transfer design considering multiple actors, their different interests, perceptions, and interpretations in shaping translations that the existing theory suggests:
2) The second stage forms the transfer design rules based on the activity in the first stage:
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.
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, 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:
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.
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.
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