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Nóra Fazekas Institute of Strategy and Management, Corvinus University of Budapest, Hungary

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Abstract

Workplace learning is always embedded in a context. The purpose of this study is to compare the characteristics of workplace learning in the market, public and civil sectors with the tool of literature review, and to identify the most important contextual factors for learning practice and effectiveness. The article thus contributes to the scientific discourse in the field of knowledge management and workplace learning research. In the following study, drawing upon classic literature and current empirical research findings, the characteristics of workplace learning in various sectors are first outlined along the themes of knowledge management, knowledge sharing, innovation, organizational learning, the purpose of learning, and the most significant knowledge elements. Subsequently, the main differences are summarized. Finally, factors for the analysis of comparative research on workplace learning are proposed, spanning individual, individual and organizational, organizational, and organizational and system levels.

Abstract

Workplace learning is always embedded in a context. The purpose of this study is to compare the characteristics of workplace learning in the market, public and civil sectors with the tool of literature review, and to identify the most important contextual factors for learning practice and effectiveness. The article thus contributes to the scientific discourse in the field of knowledge management and workplace learning research. In the following study, drawing upon classic literature and current empirical research findings, the characteristics of workplace learning in various sectors are first outlined along the themes of knowledge management, knowledge sharing, innovation, organizational learning, the purpose of learning, and the most significant knowledge elements. Subsequently, the main differences are summarized. Finally, factors for the analysis of comparative research on workplace learning are proposed, spanning individual, individual and organizational, organizational, and organizational and system levels.

The context of workplace learning

How does the sector of work determine individual on-the-job learning? What new trends and challenges are emerging in the labour market? Workplace learning is always embedded in a context. After the personal level of the individual, the next contextual level is typically the level of the organization, the sector, the sectoral environment, and the system, although additional intermediate levels can also be named (e.g., professional group, team, etc.). Although the effects of each level cannot be completely separated from each other, it is important to understand these environments in order to effectively develop workplace learning.

This study scrutinizes the level of the sector, a term that has a double meaning, as it is used in everyday discourse to demarcate the for-profit, non-profit, and public service spheres, and on the other hand, it is also an accepted term when distinguishing between different industries. In this study, we reserve the term sector to describe the three areas of the market, public service, and the civil sphere. It is important to emphasize that the market sectors and economic sectors form a complex system. It cannot be said that one includes the other or vice versa; the two approaches are subsets. As an example, we can cite a school, which can be state-, foundation-, or private-owned, but companies can also be owned by the state, or we can come across a social enterprise that is owned by a foundation.

The purpose of this study is to present the aspects of the sectoral context and identify its most important dimensions, which the profession and the research behind the study can rely on during the comparative analysis of learning taking place in different work areas. In line with this goal, the narrative approach was used as the methodology of the literature review. We employed a thoughtful and flexible approach, despite not following a formal systematic review methodology. Our criteria emphasized the direct relevance of articles to our research objective, publication quality, temporal considerations, methodological diversity, balance of perspectives, avoidance of redundancy, and adaptability. We aimed to provide readers with a comprehensive understanding of the research topic by including a range of articles, from seminal works to recent contributions, while ensuring credibility and diversity.

In the following study, the characteristics and aspects of workplace learning in the market, public service, and civil sectors are first listed, and then the main differences are summarized. Finally, analysis factors for workplace learning research are proposed along the examined dimensions identified in the literature.

Learning characteristics of sectors

In this chapter, we would like to provide an overview of the learning mechanisms typical of the three main economic sectors. Although knowledge management (KM) knowledge and practices previously flowed from the public sphere to the market sphere, today the market sphere is primarily decisive. The public and civil sectors also adopt and implement corporate practices in accordance with the needs of the sector, industry, and organization. Therefore, after a brief presentation of the characteristics of the market sphere, we present the main characteristics of each sector in comparison. Within each chapter, we take turns on the topics of knowledge management, knowledge creation, knowledge sharing, organizational learning, the purpose of learning and the most important knowledge elements.

Learning in the market sector

Knowledge management is a process that begins with the creation of knowledge, followed by the interpretation, sharing, use, preservation and refinement of knowledge (De Jarnett 1996 cited in McAdam & McCreedy, 1999). According to another definition, knowledge management is the critical management of knowledge to meet existing needs, identify and use internally and externally acquired knowledge resources, and create new opportunities (Quintas et al., 1997, 1996 cited in, McAdam & McCreedy, 1999).

Following the work of Strong, Davenport, and Prusak (2008), we can also talk about knowledge governance, which draws attention to the need for proper management of knowledge management programs. According to this, in order to maximize the efficiency and results of knowledge management and various learning programs, it is necessary to (1) define the program, i.e. define goals, the related budget and the learning portfolio; (2) establish the program environment, such as cultural norms, reporting guidelines, architectures and application standards, shared services, content and process standards, communication, procedures for handling deviations from standards; (3) program evaluation, exploration of real outcomes, a summary of lessons learned, reporting on actual expenditures. In this way, professionals specializing in the training of the working society take on the role of “change specialist” (Reischmann, 2017).

Intended workplace learning programs are only a part of knowledge management programs, and a strong appreciation is expected in this area in the near future. According to a survey, 40% of companies expect their employees to need up to 6 months of retraining, and 95% of managers expect their employees to learn new skills on the job. The latter shows an outstanding increase compared to 65% in 2018 (World Economic Forum, 2020).

Many models of the creation and flow, sharing and development of knowledge within organizations are known (see e.g., Huber, 1991; March, 1991; Weick, 1991), but perhaps the most comprehensive is Nonaka's (1994) SECI model (Fig. 1.). The model is based on Polanyi's theory of tacit and explicit knowledge. Tacit knowledge is hidden knowledge: it is difficult to grasp, cannot be codified well, it shows itself in skills, abilities, and intuition. In contrast, explicit knowledge can be easily codified, documented, stored, retrieved, and transmitted. By monitoring the flow of knowledge and exploring learning processes, the situations in the organization in which knowledge is shared and distributed become graspable: socialization (from tacit knowledge to tacit knowledge), externalization (from tacit knowledge to explicit knowledge), combination (from explicit to tacit knowledge), finally by internalization (from explicit to tacit knowledge) (Nonaka, Toyama, & Hirata, 2008) (Fig. 1). During these transformations, knowledge itself increases, which is symbolized by the spiral representation of the figure.

Fig. 1.
Fig. 1.

The SECI model of organizational knowledge creation

Source: Nonaka et al. (2008), own edit.

Citation: Journal of Adult Learning, Knowledge and Innovation 6, 2; 10.1556/2059.2023.00086

Innovation theory (Fagerberg, 2006) provides a good framework for investigating the creation, implementation and spread of new knowledge, within which the factors that encourage the creation of new knowledge and the contextual characteristics that support its dissemination are typically emphasized. Thus, for example, new practices that can be applied in a variety of ways, the strengthening of academic knowledge in the field, the cooperation of stakeholders, and technological development can be identified as important innovation pumps (OECD, 2004). Thus, for example, cloud solutions and big data applications will remain in focus in the coming years in a cross-sectoral manner, and it is expected that growing interest will be observed in the fields of encryption, non-humanoid robots and artificial intelligence (World Economic Forum, 2020).

From the literature research of Asrar-ul-Haq and Anwar (2016), we can see that publications between 2010 and 2015 identified trust as the most important factor in organizational knowledge sharing. This is naturally followed by several other factors, such as reward systems and motivation, the operational structure of the organization, social relationships and the relationship strength, network centrality and density of these networks, as well as culture, openness to change, communication, this is the willingness of individuals to share knowledge, the organization's ICT systems and the level of management support.

Technology is an extremely important element and basis for supporting organizational knowledge sharing, as it enables not only the storage and sharing of data, information and knowledge but also rich interaction between the parties, even in the case of large geographical distances. Of course, the existence of infrastructure alone is not enough; for the successful introduction of a system, it is also necessary to take into account the socio-cultural environment, i.e., the situation of trust, willingness to share knowledge, or even organizational conflicts and power structures (Omotayo, 2015). As Rangraz and Pareto (2021) warn us, that even well within the era of industry 4.0 and its cutting-edge technologies, the required skills seem to remain undefined. The literature underscores the urgency of training initiatives, emphasizing the need for learning, lifelong learning, and workplace-based training. However, such efforts have only recently started, leaving their scope and outcomes uncertain.

Based on Hager's 1998; Resnick's 1987 studies, Tynjälä (2008) characterizes workplace learning as follows: Workplace learning is usually unintentional, but there are also conscious and intentional forms. There is usually no formal curriculum or prescribed learning outcomes, so outcomes are limited in predictability. Embedded in a context, it builds holistically on the use of tools and mental activities and does not separate knowledge from skills. As a result, implicit and tacit knowledge is created, enriching the learner with situation-specific competencies. During learning, the focus is primarily on work and experience, so it primarily provides practical knowledge.

The learning environment can both support and constrain workplace learning. Fuller and Unwin (2004) distinguish between expansive and restrictive learning environments, which are located on a continuum. According to their research, it is necessary to enable three main learning methods in order to create an expansive learning environment: (1) the possibility for employees to participate in diverse, overlapping communities of practice even outside the workplace, (2) the design of jobs in such a way that employees can gain knowledge and experience in a variety of ways, (3) so that they can also participate in training that provides theoretical knowledge related to their work.

By operating knowledge management systems that support learning, the goal of market organizations is to increase their profits. They expect operational processes to become more efficient, quality to improve, and innovation activity and competitiveness to increase as a result of KM. And for this, the KM must support strategically important initiatives (Omotayo, 2015).

In addition to the knowledge management approach, the learning organization concept represents a softer, more holistic approach, which emphasizes the need for a learning culture to permeate the organization. Senge's (1990) approach to corporate management defines five closely related principles: (1) systems thinking draws attention to the need to understand complex systems in time and space in their entirety; (2) personal management means continuous monitoring, development and conscious management of oneself (individuals); (3) they represent the ability to continuously question and revise thought patterns, i.e., our core beliefs and principles; rising from the individual level to the organizational level; the requirement to develop a common vision (4) appears, which enables the members of the organization to progress together towards a clear and attractive goal accepted by everyone. On the way to this, Senge highlights the importance of (5) group learning, which should be based on dialogue and enables collective thinking and learning (Senge, 1990, pp. 8–15).

Garvin (1993) proposes a more practical definition and implementable learning organization practice. Accordingly, he defines the learning organization as an organization that is well able to create, acquire and transfer knowledge, and that is able to change its behaviour along the lines of newly acquired knowledge and understandings (80). According to his article, the most important characteristics of a learning organization are that it is capable of (1) systematic problem solving, (2) experimentation, (3) learning from past experiences, (4) learning from others, (5) knowledge transfer; it must also be able to measure and evaluate learning.

At the beginning of the millennium, the OECD DeSeCo project already dealt with the definition of key competencies. These were (1) the interactive use of various tools (language, knowledge and information, technology), (2) interaction with heterogeneous groups (connection, cooperation, conflict management), and (3) autonomous action (system approach, life management, rights, interests, boundaries and enforcement of needs) (OECD, 2005). After the 21st-century key competences, OECD's 2030 Learning Compass (OECD, 2019) identified a new trio of competences, which it calls transformative competences. These are (1) creating new values, (2) reconciling tensions and dilemmas, and (3) assuming responsibility.

According to the 2020 Future of Jobs report of the World Economic Forum (WEF), by 2025 the importance of competencies such as critical thinking and analysis, problem-solving, active learning, resilience, stress tolerance and flexibility will increase the most (World Economic Forum, 2020).

The WEF survey shows that by 2025, as a result of the increasing use of technology, 43% of companies plan to reduce their workforce, 41% would increase the proportion of task-specific contractual relationships, and 34% would specifically increase the number of employees. 85 million jobs may be displaced because of the strengthening of machine work, while 97 million new jobs may be created that are better able to adapt to the new division of labour between humans, machines and algorithms (World Economic Forum, 2020). Adaptation brings with it the training of human resources at a higher level, the competences to be acquired are becoming more and more complex, not only in the developed world but also - thanks to the replacement of dirty technologies outsourced to backward regions - in developing regions (Trautmann & Vida, 2021).

Learning in the public sector

McAdam and Reid (2000) compared knowledge management of the market and the public sector along the systematic capture of knowledge and showed that everywhere the weight of top management is the greatest, and after the declining role of middle managers and team leaders, the weight of employees is higher again. In the public sector, the role of employees is almost the same as that of middle managers, while in market organizations it is barely higher than that of team leaders. In addition, it was also shown that suppliers, competitors, benchmarked organizations, and day-to-day experiences play a larger role in market organizations' workplace learning situations. On the one hand, we can conclude from these that the knowledge used and accumulated during the work of employees working at the bottom of the hierarchy is greater than on the same level in companies, i.e., a higher level of knowledge management competencies is required. On the other hand, we can also see that the market sector is significantly more open, and several key focal points of knowledge point outside the organization. This is also a warning to the public sector that its knowledge systems are more closed and isolated. Networking initiatives (with actors from the market and civil sector) can be a solution to this, but along the lines of some specific programs, co-production (Verschuere, Brandsen, & Pestoff, 2012) and other solutions directly channelling citizen knowledge can also help the acquisition of external and local knowledge.

It is also characteristic of the KM practice of the public sector that the HR professionals working here have a relatively narrow scope for defining training plans, as they are often created at the political or managerial level, and the possibility of personalizing the plans is also negligible according to Poell and his colleagues (Poell, Berings, & Van der Krogt, 2007) in which he examined Dutch healthcare. Clarke (2006) also found in his research in the field of healthcare that despite the presence of more advanced HR and training development strategies in the public sector, measurement is mostly lacking, and formal learning situations continue to dominate to a significant extent. The weight of formal learning situations may also seem more significant since in many areas the state makes professional further education compulsory and regulated. The form of this continuing education is increasingly being transferred to eLearning and mLearning platforms (Csedő, Tamás, Égler, & Sára, 2014).

Although there are studies that show public sector organizations as winners in the field of knowledge management (McAdam & Reid, 2000), certain research results show that business organizations are more developed in all areas (Chawla & Joshi, 2010).

Innovation efforts in the sector are most often triggered by the reduction of expenses or the need to save, or, for example, political interventions at the ministerial level (Dunleavy et al., 2006). Mazzucato (2011) strongly criticizes this approach and argues that this myth should be dispelled, as the state was the main investor in all major inventions of the modern era, i.e., it should be considered entrepreneurial.

The willingness to share knowledge and knowledge-sharing culture is not self-evident. In addition to the general factors in the public sector, it can be said that fewer hierarchical structures, the reduction of excessive bureaucratic systems, and the power resulting from knowledge withholding have a positive effect on the sharing of knowledge and information (Henttonen, Kianto, & Ritala, 2016). Compared to the market sector, in the public sphere it is more typical to facilitate the sharing of knowledge by organizing workshops, forums, discussions, defining learning processes, and mapping training needs, whereas, in the market sphere, knowledge sharing through presentations and creative techniques is more present (McAdam & Reid, 2000).

The level of knowledge sharing between organizations and sectors and the spillover effect is typically lower in the public sector. We can distinguish between voluntary and non-voluntary knowledge sharing. In the market sector, the sharing of knowledge is typically involuntary, resulting from competition and therefore automatic. However, in the public sector, the dissemination of knowledge is less automatic, and administrative measures and “reforms” aimed at the dissemination of new knowledge and practice do not achieve as much impact as the mechanisms of the competitive market (Foray & Hargreaves, 2003).

The dimensions of many models of organizational learning and learning organizations are also influenced by certain sector-specific elements. Jarvie and Stewart (2018) argue in their study that while legal regulations often limit the learning potential of public sector organizations (Kinder, 2012), organizations that are located further away from ideological battles, have a stable mandate, and employ colleagues with a professional background (Stewart & Jarvie, 2015) have higher learning potential. This is also supported by organizational practices that promote reflection and criticism (Jarvie & Stewart, 2018).

In the study by Jarvie and Stewart (2018), several typical sector-specific learning types are named, which were identified in connection with a case study (Australian Centre for International Agricultural Research, ACIAR): 1) project planning, implementation and evaluation (e.g. formal and informal learning situations of projects to be implemented), 2) program-based learning situations (e.g. national workshops), 3) operational learning (e.g. HR information, databases, informal channels, financial operations), 4) strategic learning (e.g. external surveillance surveys, independent evaluations).

However, according to the assessment of several researchers in the field, the learning potential of the public sector is very limited and is only capable of single-loop learning. This is because knowledge transfer activities and learning from change are decentralized and might be a low priority for public service decision-makers, creating short-term learning practices. Double-loop and triple-loop (deutero) learning already requires political decision-making, since without it the industrial or institutional policy is ignored (Gilson, Dunleavy, & Tinkler, 2007). Real learning is also hindered by resistance to change, limited changeability of organizational behavioural structures, continuity broken by election cycles and changes of government, strong social responsibility for mistakes (while learning often takes place in a “trial-and-error” model), and distortion of actual performance information in order to maintain a good image towards public opinion (Olsen & Peters, 1996 in Gilson et al., 2007).

According to the logic of the public sector, the purpose of learning is also different. While the primary goal in the market sector is to increase competitiveness and maximize profit, some public services (mainly in public administration) do not encounter substantial competition in most cases, they can only shape their activities to a limited extent, and their effectiveness is evaluated by a much more complex group of stakeholders. That is why the goal of learning in the public sector can be to survive, to fulfil ministerial expectations, or even to just perform the obligatory service, or to perform the task more efficiently and effectively (Jarvie & Stewart, 2018). This is also supported by the 2006 NAO report, according to which the focus of innovations in the sector is less on effectiveness (output-outcome), and more on improving efficiency (input-output) (Dunleavy et al., 2006). Although, according to the above, survival is a sufficient goal for certain actors of the public sector, it is characteristic of the public sector that some of its organizations are almost eternal, they survive regardless of their learning competence (Gilson et al., 2007), which also affects the organizational culture and the learning patterns of public sector employees.

While the weight of most knowledge elements mostly follows each other in proportion in the two spheres, in the public sphere political issues, values and tacit information, as well as education and training, are given a more prominent role, while for the market sphere, soft and difficult-to-grasp information, the weight of decisions and experiences is greater (McAdam & Reid, 2000). From this, we can read that public sector workers must have deeper socio-political knowledge elements, and that, compared to a corporate environment, a higher ability to tolerate hierarchy is required, since we can speak of lower decision-making powers. In the bureaucratic system knowledge acquired through formal learning is considered more valid. However, according to Pillay's (2008) research, e.g., as directors of private and public hospitals, managers must have the same skills; in the case of the same professional position, the differences between the market and the public sector do not affect the required skills. It should be noted, however, that in his research public sector hospital directors marked the importance of each competence as significantly higher, for which the author formulated two possible explanations: a) public sector managers work in a more challenging environment, b) managers in the public sector are indeed less prepared compared to their colleagues working in the market sector.

In addition to all this, a shift can be observed at the management levels in the public sector compared to previous traditions, according to which modern leadership skills and the development of emotional and spiritual intelligence are increasingly expected, in addition to the administratively focused management practices of classical bureaucratic leadership (Fazekas, 2018; Pillay, 2008).

However, the necessary and valid elements of knowledge cannot be completely generalized even in the same sector and profession. In his article, Pillay (2008) draws attention to the role of cultural differences, which can lead to differences in the most essential knowledge elements of professionals (hospital directors) occupying the same position in the same sector.

Learning in the civil sector

The transfer of KM practices to civil organizations initially took place from for-profit organizations (McAdam & Reid, 2000), and later from other non-profits and public sector organizations (Cong & Pandya, 2003). The non-profit sector can be considered a highly knowledge-based sector (Hume & Hume, 2008), which is characterized by the fact that the knowledge present is often fragmented, heterogeneous, non-formalized and temporary due to the high turnover of volunteers (Hume & Hume, 2008; Lettieri, Borga, & Savoldelli, 2004).

A fundamental characteristic, due to the lack of resources and the social mission of the organizations operating in the sector (i.e. to direct their resources to the core activity rather than to the supporting processes), is that the implementation of the KM toolkit is significantly more sparse and unstructured (Bloch & Borges, 2002; Downes & Marchant, 2016; Hume & Hume, 2008) than in the other two sectors. In addition to the lack of resources (operational budget, human resources, IT), the availability of financial resources is also generally unpredictable (Soakell-Ho & Myers, 2011; Zbuchea, Ivan, Petropoulos, & Pinzaru, 2020). Another challenge, as Bloch and Borges (2002) draw our attention to, is that the incorporation of the market and public sector management techniques without adaptation in the civil sector often runs into serious limitations, and business models are usually implemented incorrectly (Hume & Hume, 2008). Even in the case of organizations where KM tools are used, it is typical that they only enable single-loop learning in organizations (Bloch & Borges, 2002). Civil organizations are generally sceptical about the effectiveness of these systems, which can be considered both a consequence and a root cause.

In Downes and Marchant's (2016) research, 86.5 per cent of Australian NGOs had a formal (23.6%) or informal (62.9%) KM system. Two indexes were created and measured in the research. The first index examined the extent of KM, the average of which among the surveyed organizations was a value of 64.26 on a scale of 100. Both NGOs with formal and informal KM were in the moderate range, but those with a formal KM policy scored consequently higher. The other index measured the effectiveness of KM, the average of which showed a significantly higher value of 72.91. Although the examined civil organizations had mechanisms in place with which knowledge was transformed into action plans, new ideas or methods were developed from existing practices, and previous lessons were used, in fact, the systematic application of existing knowledge was moderately typical. Incentives for knowledge sharing typically occurred at a low rate. The mission-oriented environment of NGOs is unique in this respect: individuals have an internal motivation to share knowledge. As a result, the transfer of knowledge takes place through socialization and externalization practices, and the role of other tools and technology is secondary.

However, we know from the work of Lettieri et al. (2004) that the formalization and effective use of knowledge management depends, for example, on the type of organizational unit. That is, in the accounting-administrative, managerial-organizational, fund-raising-PR-marketing and operational departments, knowledge is typically well codified, and knowledge sharing is also well organized.

In general, knowledge management has a strongly technology-supported toolkit, which in previous research, especially for organizations with entry-level competencies in the field of KM, was excessively complex and expensive (Hume & Hume, 2008). Now we can see that organizations use many ICT tools and applications to perform organizational and management tasks (Rathi & Given, 2017). In the 2010s, the use of intranets, wiki systems and social media became typical in these organizations as well (Downes & Marchant, 2016), today the use of cloud solutions and various online applications can also be considered widespread. However, Downes and Marchant (2016) draw our attention to the fact that NGO volunteers may not be proficient in the use of technology, or management does not provide them with access to sensitive data. Of course, other limiting factors can arise, so these organizations often have to learn to manoeuvre between the online and offline worlds.

The research of Downes and Marchant (2016) also shows that knowledge creation is active in the civil sector, and organizations are able to collect knowledge from various sources, such as volunteers, customers, donors or competitors. It is typical that the main producers of knowledge in the sector are volunteers, which brings with it serious knowledge management challenges in the construction of knowledge-based resources, due to the typically high turnover of volunteers (Le & Tuamsuk, 2021; Zbuchea et al., 2020).

The civil sector is generally characterized as lacking in resources and, as a result, slower or different in its way of development. However, foundations, due to their nature, can use their resources for innovation activities more efficiently than even the government or individual donors, because there is no political pressure on them and they have the economies of scale, time horizon, procedural flexibility and the professional management that makes this possible (Jaskyte, Amato, & Sperber, 2018). International civil organizations are also characterized by a higher degree of knowledge management, similar to the for-profit sphere (Walsh & Lannon, 2020).

In the civil sphere, learning, individual development and self-training are often a goal in themselves in the lives of workers and volunteers participating in the life of organizations, and this is particularly noticeable among the Y generation (Forgács-Fábián, 2021). Since this motivational factor presumably arises from their current stage of life, we can conclude that this may also be true for the following generations.

Civil organizations themselves often appear as knowledge centres. For example, their dedicated goal can be the dissemination of knowledge on a specific topic, they can be mediating parties between international organizations or even governments, but also between local communities. In many cases, the shared knowledge is obtained specifically from the local communities where they carry out their activities. Thus, the organizations of the civil sector fulfil the role of knowledge mediator on the one hand, and knowledge legitimation on the other (Walsh & Lannon, 2020).

In relation to the most important knowledge elements of the sector, it can be generally said that in the case of non-profit organizations, knowledge-based resources are built up from intangible organizational resources, and most of the knowledge that can be found is tacit (Le & Tuamsuk, 2021). If we group the essential knowledge elements in the civil sphere according to 1) technical, 2) operational and 3) personal knowledge elements, according to the research of Rathi, Given, and Forcier (2016), we can see that the most important knowledge is the personal type of knowledge, which stems from the organization's focus on the clients, the community, and their needs. This is followed by operational knowledge, which refers to the operation of the organization, and lastly, we mention technical knowledge, which covers expert knowledge and experience. The research also assessed the knowledge needs of nonprofits in detail, and the following main areas were defined: 1) knowledge of management and organizational practices within the organization; 2) knowledge of the organization's financial, physical, human and intellectual resources; 3) knowledge about the community of individuals representing the organization as members, volunteers, donors, stakeholders and beneficiaries; 4) knowledge of the sector or social topic in which the non-profit organization operates, including the expertise necessary to achieve organizational goals; and 5) embedded or context-dependent external knowledge (i.e., external to the organization, community, or sector) that may affect the organization's operations (30–31).

The shift from the former civil identity to a new one is typical, in which instead of or in addition to the primacy of professional knowledge about the basic activities of the organization based on social needs, a management-centric competence package comes to the fore; which results in the civil sphere becoming more and more project-based (Soakell-Ho & Myers, 2011; Walsh & Lannon, 2020).

Conclusions

Reviewing the above literature, we can see that although sectoral differences arise in the context of workplace learning, the continuous structural change of the sectors, the overlaps between each other, the development of technology, and the cooperation networks between the sectors make it increasingly difficult to distinguish them sharply from each other. As Marsick, Watkins, Scully-Russ, and Nicolaides (2017) also stated, the nature of workplace learning can increasingly only be described with complex and dynamic models. Below, some of the main characteristics of these learning environments are outlined.

Learning in the market sector is demand-driven, while in the public sphere, it is typically highly regulated and even limited. In organizations of the civil sector, learning can be very organic, but it is highly fragmented, so in many cases it does not produce lasting knowledge at the level of the organization.

While the goal of learning in the market sphere is ultimately to increase profit while satisfying customer needs, the public sector tends to follow efficiency and effectiveness aspects in the implementation of mandatory public services, and civil sector organizations organize their learning activities in order to deliver their mission with greater social impact.

Reviewing essential knowledge, we can see that the market sector is characterized by the priority of 21st-century key competences, and although these are increasingly coming to the fore in the other two sectors, the importance of substantive and procedural knowledge is still decisive in the public sector, and in the case of NGOs, customer or beneficiary-oriented knowledge.

In the case of knowledge creation and innovative practices, the market sector can be singled out as a “winner”, although a significant part of state activities, typically through financing, also produces a significant amount of innovation and creates a knowledge- and learning-intensive environment. In the organizations of the civil sphere, the creation of new knowledge is realized by learning in the field and channelling local knowledge upwards.

Along the lines of the characteristics of knowledge management, it can be said that its systems are clearly the most consciously organized in the market sector. Although due to the huge amounts of data present in the state administration and the extensive network of services KM systems in the public sector are indispensable and developed, the types of these knowledge elements are different. In the civil sector, KM differs significantly due to the basic activity and the personality and motivation of the organizational members, and the technological support is the weakest here as well.

The sharing of knowledge in the market sphere is typically more limited due to competition than in the other two sectors, which can be characterized both at the individual and organizational level; although knowledge withholding can occur within organizations of all sectors. The public service and the civil sector characteristically aim to share and distribute knowledge as part of their mission.

The literature review above also allows us to make suggestions regarding research into the process and effectiveness of workplace learning. The identified factors in Fig. 2 have been grouped according to the level of analysis at which they can be interpreted. These levels are factors that can be identified at (1) individual, (2) individual and organizational, (3) organizational, and (4) organizational and system levels. With the collected and listed factors we aim to build a comprehensive analytic framework applicable to all three investigated sectors' workplace learning, hence, they are a common section of the reviewed literature. Purely systemic factors (marked red in Fig. 2.) were not identified, which is due on the one hand to the analysed, mainly management literature, and on the other hand to the nature and purpose of the research to be carried out based on the review. The system level extending to the individual level in the diagram represents that the regulation of the labour and training system can directly affect the level of individual workplace learning (e.g., the mandatory training of qualified accountants or teachers).

Fig. 2.
Fig. 2.

Identified factors affecting workplace learning

Source: own edit based on the literature review.

Citation: Journal of Adult Learning, Knowledge and Innovation 6, 2; 10.1556/2059.2023.00086

It is essential to emphasize that the figure is based on the reviewed literature. The actual number of influencing factors is more extensive, and further categorization is possible based on various organizing principles. An expansion of the identified factors is warranted through additional exploration of literature pertaining to individual, organizational, sectoral, and systemic levels of learning. However, it is important to note that such an extensive inquiry goes beyond the scope of this study.

Acknowledgment

The present study was funded by the Matthias Corvinus Collegium's Institute for Learning Research, within the framework of the WoRLD (Workplace Research and Learning Development Group) research group’s work.

References

  • Asrar-ul-Haq, M., & Anwar, S. (2016). A systematic review of knowledge management and knowledge sharing: Trends, issues, and challenges. Cogent Business and Management, 3(1). https://doi.org/10.1080/23311975.2015.1127744.

    • Search Google Scholar
    • Export Citation
  • Bloch, D., & Borges, N. (2002). Organisational learning in NGOs: An example of an intervention based on the work of Chris Argyris. Development in Practice, 12(3–4), 461472. https://doi.org/10.1080/0961450220149807a.

    • Search Google Scholar
    • Export Citation
  • Chawla, D., & Joshi, H. (2010). Knowledge management initiatives in Indian public and private sector organizations. Journal of Knowledge Management, 14(6), 811827. https://doi.org/10.1108/13673271011084871.

    • Search Google Scholar
    • Export Citation
  • Clarke, N. (2006). Why HR policies fail to support workplace learning: The complexities of policy implementation in healthcare. International Journal of Human Resource Management, 17(1), 190206. https://doi.org/10.1080/09585190500367589.

    • Search Google Scholar
    • Export Citation
  • Cong, X., & Pandya, K. V. (2003). [JCR] issues of knowledge management in the public sector. Electronic Journal of Knowledge Management, 1(2), 2533. www.ejkm.com.

    • Search Google Scholar
    • Export Citation
  • Csedő, Z., Tamás, T., Égler, A., & Sára, Z. (2014). Online képzési stratégiák és módszerek a közszolgálati továbbképzésekben. Információs Társadalom, 14(1), 928.

    • Search Google Scholar
    • Export Citation
  • Downes, T., & Marchant, T. (2016). The extent and effectiveness of knowledge management in Australian community service organisations. Journal of Knowledge Management, 20(1), 4968. https://doi.org/10.1108/JKM-11-2014-0483.

    • Search Google Scholar
    • Export Citation
  • Dunleavy, P., Margetts, H., Bastow, S., Tinkler, J., Pearce, O., & Bartholomeou, P. (2006). Achieving innovation in central government organisations. July.

    • Search Google Scholar
    • Export Citation
  • Fagerberg, J. (2006). Innovation: A guide to the literature. In J. Fagerberg, D. C. Mowery, & R. Nelson (Eds.), Oxford handbook of innovation (pp. 127). Oxford University Press.

    • Search Google Scholar
    • Export Citation
  • Fazekas, Á (2018). The impact of EU-funded development interventions on teaching practices in Hungarian schools. European Journal of Education, 53(3), 377392. https://doi.org/10.1111/ejed.12295.

    • Search Google Scholar
    • Export Citation
  • Foray, D., & Hargreaves, D. (2003). The production of knowledge in different sectors: A model and some hypotheses. London Review of Education, 1(1), 719. https://doi.org/10.1080/14748460306689.

    • Search Google Scholar
    • Export Citation
  • Forgács-Fábián, S. (2021). Fenntartható önkéntesség. De hogyan? – Az Y-generációs egyetemista önkéntesek motivációjának szervezeti vizsgálata a hosszú távon fenntartott önkéntességre vonatkozóan. Kovász, 24(1–4), 124.

    • Search Google Scholar
    • Export Citation
  • Fuller, A., & Unwin, L. (2004). Expansive learning environments: Integrating organisational and personal development. In A. Fuller, A. Munro, & H. Rainbird (Eds.), Workplace learning in context (pp. 126144). Routledge. https://doi.org/10.4324/9780203571644.

    • Search Google Scholar
    • Export Citation
  • Garvin, D. A. (1993). Building a learning organization. Harvard Business Review, 7891, July–August.

  • Gilson, C., Dunleavy, P., & Tinkler, J. (2007). Organizational learning in government sector organizations: Literature review contact (pp. 143). LSE Public Policy Group. www.academia.edu+PPG_OrgLearninginGovLit_review.pdf.

    • Search Google Scholar
    • Export Citation
  • Henttonen, K., Kianto, A., & Ritala, P. (2016). Knowledge sharing and individual work performance: An empirical study of a public sector organisation. Journal of Knowledge Management, 20(4), 749768. https://doi.org/10.1108/JKM-10-2015-0414.

    • Search Google Scholar
    • Export Citation
  • Huber, G. P. (1991). Organizational learning: The contributing processes and the literatures. Organization Science, 2(1), 88115. https://doi.org/10.1287/orsc.2.1.88.

    • Search Google Scholar
    • Export Citation
  • Hume, C., & Hume, M. (2008). The strategic role of knowledge management in nonprofit organisations. International Journal of Nonprofit and Voluntary Sector Marketing, 13(2), 129140. https://doi.org/10.1002/nvsm.316.

    • Search Google Scholar
    • Export Citation
  • Jarvie, W., & Stewart, J. (2018). Conceptualizing learning in the public sector: The importance of context. International Journal of Public Sector Management, 31(1), 1430. https://doi.org/10.1108/IJPSM-08-2016-0137.

    • Search Google Scholar
    • Export Citation
  • Jaskyte, K., Amato, O., & Sperber, R. (2018). Foundations and innovation in the nonprofit sector. Nonprofit Management and Leadership, 29(1), 4764. https://doi.org/10.1002/nml.21312.

    • Search Google Scholar
    • Export Citation
  • Kinder, T. (2012). Learning, innovating and performance in post-new public management of locally delivered public services. Public Management Review, 14(3), 403428. https://doi.org/10.1080/14719037.2011.637408.

    • Search Google Scholar
    • Export Citation
  • Le, Q. N., & Tuamsuk, K. (2021). Knowledge and technology resources for knowledge management practices of nonprofit organizations in Thailand. Journal of Information Science Theory and Practice, 9(3), 4255. https://doi.org/10.1633/JISTaP.2021.9.3.4.

    • Search Google Scholar
    • Export Citation
  • Lettieri, E., Borga, F., & Savoldelli, A. (2004). Knowledge management in non-profit organizations. Journal of Knowledge Management, 8(6), 1630. https://doi.org/10.1108/13673270410567602.

    • Search Google Scholar
    • Export Citation
  • March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 7187.

  • Marsick, V. J., Watkins, K. E., Scully-Russ, E., & Nicolaides, A. (2017). Rethinking informal and incidental learning in terms of complexity and the social context. Journal of Adult Learning, Knowledge and Innovation, 1(1), 2734. https://doi.org/10.1556/2059.01.2016.003.

    • Search Google Scholar
    • Export Citation
  • Mazzucato, M. (2011). The entrepreneurial state. In Governing cross-border higher education. Demos. https://doi.org/10.4324/9781315764016-2.

    • Search Google Scholar
    • Export Citation
  • McAdam, R., & McCreedy, S. (1999). A critical review of knowledge management models. The Learning Organization, 6(3), 91101. https://doi.org/10.1108/09696479910270416.

    • Search Google Scholar
    • Export Citation
  • McAdam, R., & Reid, R. (2000). A comparison of public and private sector perceptions and use of knowledge management. Journal of European Industrial Training, 24(6), 317329. https://doi.org/10.1108/03090590010346424.

    • Search Google Scholar
    • Export Citation
  • Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 5(1), 1437. http://www.jstor.org/stable/2635068.

    • Search Google Scholar
    • Export Citation
  • Nonaka, I., Toyama, R., & Hirata, T. (2008). Managing flow: A process theory of the knowledge-based firm. Palgrave Macmillan.

  • OECD (2004). Innovation in the knowledge economy. Implications for Education and Learning.

  • OECD (2005). The definition and selection of key Competencies.

  • OECD (2019). OECD future of education and skills 2030. In OECD learning Compass. 2030 https://www.oecd.org/education/2030-project/teaching-and-learning/learning/learning-compass-2030/OECD_Learning_Compass_2030_Concept_Note_Series.pdf.

    • Search Google Scholar
    • Export Citation
  • Omotayo, F. O. (2015). Knowledge management as an important tool in organisational management: A review of literature. Library Philosophy and Practice. 2015.

    • Search Google Scholar
    • Export Citation
  • Pillay, R. (2008). Defining competencies for hospital management: A comparative analysis of the public and private sectors. Leadership in Health Services, 21(2), 99110. https://doi.org/10.1108/17511870810870547.

    • Search Google Scholar
    • Export Citation
  • Poell, R. F., Berings, M. G. M. C., & Van der Krogt, F. J. (2007). Tailoring learning programmes to every-day employee learning: Customisation strategies of HRD practitioners in health care Cross-Cultural Management View project. https://www.researchgate.net/publication/254806330.

    • Search Google Scholar
    • Export Citation
  • Rangraz, M., & Pareto, L. (2021). Workplace work-integrated learning: Supporting industry 4.0 transformation for small manufacturing plants by reskilling staff. International Journal of Lifelong Education, 40(1), 522.

    • Search Google Scholar
    • Export Citation
  • Rathi, D., & Given, L. M. (2017). Non-profit organizations’ use of tools and technologies for knowledge management: A comparative study. Journal of Knowledge Management, 21(4), 718740. https://doi.org/10.1108/JKM-06-2016-0229.

    • Search Google Scholar
    • Export Citation
  • Rathi, D., Given, L. M., & Forcier, E. (2016). Knowledge needs in the non-profit sector: An evidence-based model of organizational practices. Journal of Knowledge Management, 20(1), 2348. https://doi.org/10.1108/JKM-12-2014-0512.

    • Search Google Scholar
    • Export Citation
  • Reischmann, J. (2017). Lifewide learning – Challenges for andragogy. Journal of Adult Learning, Knowledge and Innovation, 1(1), 4350. https://doi.org/10.1556/2059.01.2017.2.

    • Search Google Scholar
    • Export Citation
  • Senge, P. M. (1990). The fifth discipline. The art and practice of the learning organization. Doubleday.

  • Soakell-Ho, M., & Myers, M. D. (2011). Knowledge management challenges for nongovernment organizations: The health and disability sector in New Zealand. Vine, 41(2), 212228. https://doi.org/10.1108/03055721111134826.

    • Search Google Scholar
    • Export Citation
  • Stewart, J., & Jarvie, W. (2015). Haven’t we been this way before? Evaluation and the impediments to policy learning. Australian Journal of Public Administration, 74(2), 114127. https://doi.org/10.1111/1467-8500.12140.

    • Search Google Scholar
    • Export Citation
  • Strong, B., Davenport, T. H., & Prusak, L. (2008). Organizational governance of knowledge and learning. Knowledge and Process Management, 15(2), 150157. https://doi.org/10.1002/kpm.306.

    • Search Google Scholar
    • Export Citation
  • Trautmann, L., & Vida, C. (2021). Tudásalapú gazdaság – Iparpolitika – Felsőoktatás. Köz-Gazdaság, 16(4), 4976. https://doi.org/10.14267/retp2021.04.04.

    • Search Google Scholar
    • Export Citation
  • Tynjälä, P. (2008). Perspectives into learning at the workplace. Educational Research Review, 3(2), 130154. https://doi.org/10.1016/j.edurev.2007.12.001.

    • Search Google Scholar
    • Export Citation
  • Verschuere, B., Brandsen, T., & Pestoff, V. (2012). Co-production: The state of the art in research and the future agenda. Voluntas, 23(4), 10831101. https://doi.org/10.1007/s11266-012-9307-8.

    • Search Google Scholar
    • Export Citation
  • Walsh, J. N., & Lannon, J. (2020). Dynamic knowledge management strategy development in international non-governmental organisations. Knowledge Management Research and Practice, 00(00), 112. https://doi.org/10.1080/14778238.2020.1785348.

    • Search Google Scholar
    • Export Citation
  • Weick, K. E. (1991). The nontraditional quality of organizational learning. Organizational Learning, 2(1), 116124.

  • World Economic Forum (2020). The future of jobs report 2020 | world economic forum. The Future of Jobs Report October, 1163 https://www.weforum.org/reports/the-future-of-jobs-report-2020/digest.

    • Search Google Scholar
    • Export Citation
  • Zbuchea, A., Ivan, L., Petropoulos, S., & Pinzaru, F. (2020). Knowledge sharing in NGOs: The importance of the human dimension. Kybernetes, 49(1), 182199. https://doi.org/10.1108/K-04-2019-0260.

    • Search Google Scholar
    • Export Citation
  • Asrar-ul-Haq, M., & Anwar, S. (2016). A systematic review of knowledge management and knowledge sharing: Trends, issues, and challenges. Cogent Business and Management, 3(1). https://doi.org/10.1080/23311975.2015.1127744.

    • Search Google Scholar
    • Export Citation
  • Bloch, D., & Borges, N. (2002). Organisational learning in NGOs: An example of an intervention based on the work of Chris Argyris. Development in Practice, 12(3–4), 461472. https://doi.org/10.1080/0961450220149807a.

    • Search Google Scholar
    • Export Citation
  • Chawla, D., & Joshi, H. (2010). Knowledge management initiatives in Indian public and private sector organizations. Journal of Knowledge Management, 14(6), 811827. https://doi.org/10.1108/13673271011084871.

    • Search Google Scholar
    • Export Citation
  • Clarke, N. (2006). Why HR policies fail to support workplace learning: The complexities of policy implementation in healthcare. International Journal of Human Resource Management, 17(1), 190206. https://doi.org/10.1080/09585190500367589.

    • Search Google Scholar
    • Export Citation
  • Cong, X., & Pandya, K. V. (2003). [JCR] issues of knowledge management in the public sector. Electronic Journal of Knowledge Management, 1(2), 2533. www.ejkm.com.

    • Search Google Scholar
    • Export Citation
  • Csedő, Z., Tamás, T., Égler, A., & Sára, Z. (2014). Online képzési stratégiák és módszerek a közszolgálati továbbképzésekben. Információs Társadalom, 14(1), 928.

    • Search Google Scholar
    • Export Citation
  • Downes, T., & Marchant, T. (2016). The extent and effectiveness of knowledge management in Australian community service organisations. Journal of Knowledge Management, 20(1), 4968. https://doi.org/10.1108/JKM-11-2014-0483.

    • Search Google Scholar
    • Export Citation
  • Dunleavy, P., Margetts, H., Bastow, S., Tinkler, J., Pearce, O., & Bartholomeou, P. (2006). Achieving innovation in central government organisations. July.

    • Search Google Scholar
    • Export Citation
  • Fagerberg, J. (2006). Innovation: A guide to the literature. In J. Fagerberg, D. C. Mowery, & R. Nelson (Eds.), Oxford handbook of innovation (pp. 127). Oxford University Press.

    • Search Google Scholar
    • Export Citation
  • Fazekas, Á (2018). The impact of EU-funded development interventions on teaching practices in Hungarian schools. European Journal of Education, 53(3), 377392. https://doi.org/10.1111/ejed.12295.

    • Search Google Scholar
    • Export Citation
  • Foray, D., & Hargreaves, D. (2003). The production of knowledge in different sectors: A model and some hypotheses. London Review of Education, 1(1), 719. https://doi.org/10.1080/14748460306689.

    • Search Google Scholar
    • Export Citation
  • Forgács-Fábián, S. (2021). Fenntartható önkéntesség. De hogyan? – Az Y-generációs egyetemista önkéntesek motivációjának szervezeti vizsgálata a hosszú távon fenntartott önkéntességre vonatkozóan. Kovász, 24(1–4), 124.

    • Search Google Scholar
    • Export Citation
  • Fuller, A., & Unwin, L. (2004). Expansive learning environments: Integrating organisational and personal development. In A. Fuller, A. Munro, & H. Rainbird (Eds.), Workplace learning in context (pp. 126144). Routledge. https://doi.org/10.4324/9780203571644.

    • Search Google Scholar
    • Export Citation
  • Garvin, D. A. (1993). Building a learning organization. Harvard Business Review, 7891, July–August.

  • Gilson, C., Dunleavy, P., & Tinkler, J. (2007). Organizational learning in government sector organizations: Literature review contact (pp. 143). LSE Public Policy Group. www.academia.edu+PPG_OrgLearninginGovLit_review.pdf.

    • Search Google Scholar
    • Export Citation
  • Henttonen, K., Kianto, A., & Ritala, P. (2016). Knowledge sharing and individual work performance: An empirical study of a public sector organisation. Journal of Knowledge Management, 20(4), 749768. https://doi.org/10.1108/JKM-10-2015-0414.

    • Search Google Scholar
    • Export Citation
  • Huber, G. P. (1991). Organizational learning: The contributing processes and the literatures. Organization Science, 2(1), 88115. https://doi.org/10.1287/orsc.2.1.88.

    • Search Google Scholar
    • Export Citation
  • Hume, C., & Hume, M. (2008). The strategic role of knowledge management in nonprofit organisations. International Journal of Nonprofit and Voluntary Sector Marketing, 13(2), 129140. https://doi.org/10.1002/nvsm.316.

    • Search Google Scholar
    • Export Citation
  • Jarvie, W., & Stewart, J. (2018). Conceptualizing learning in the public sector: The importance of context. International Journal of Public Sector Management, 31(1), 1430. https://doi.org/10.1108/IJPSM-08-2016-0137.

    • Search Google Scholar
    • Export Citation
  • Jaskyte, K., Amato, O., & Sperber, R. (2018). Foundations and innovation in the nonprofit sector. Nonprofit Management and Leadership, 29(1), 4764. https://doi.org/10.1002/nml.21312.

    • Search Google Scholar
    • Export Citation
  • Kinder, T. (2012). Learning, innovating and performance in post-new public management of locally delivered public services. Public Management Review, 14(3), 403428. https://doi.org/10.1080/14719037.2011.637408.

    • Search Google Scholar
    • Export Citation
  • Le, Q. N., & Tuamsuk, K. (2021). Knowledge and technology resources for knowledge management practices of nonprofit organizations in Thailand. Journal of Information Science Theory and Practice, 9(3), 4255. https://doi.org/10.1633/JISTaP.2021.9.3.4.

    • Search Google Scholar
    • Export Citation
  • Lettieri, E., Borga, F., & Savoldelli, A. (2004). Knowledge management in non-profit organizations. Journal of Knowledge Management, 8(6), 1630. https://doi.org/10.1108/13673270410567602.

    • Search Google Scholar
    • Export Citation
  • March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 7187.

  • Marsick, V. J., Watkins, K. E., Scully-Russ, E., & Nicolaides, A. (2017). Rethinking informal and incidental learning in terms of complexity and the social context. Journal of Adult Learning, Knowledge and Innovation, 1(1), 2734. https://doi.org/10.1556/2059.01.2016.003.

    • Search Google Scholar
    • Export Citation
  • Mazzucato, M. (2011). The entrepreneurial state. In Governing cross-border higher education. Demos. https://doi.org/10.4324/9781315764016-2.

    • Search Google Scholar
    • Export Citation
  • McAdam, R., & McCreedy, S. (1999). A critical review of knowledge management models. The Learning Organization, 6(3), 91101. https://doi.org/10.1108/09696479910270416.

    • Search Google Scholar
    • Export Citation
  • McAdam, R., & Reid, R. (2000). A comparison of public and private sector perceptions and use of knowledge management. Journal of European Industrial Training, 24(6), 317329. https://doi.org/10.1108/03090590010346424.

    • Search Google Scholar
    • Export Citation
  • Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 5(1), 1437. http://www.jstor.org/stable/2635068.

    • Search Google Scholar
    • Export Citation
  • Nonaka, I., Toyama, R., & Hirata, T. (2008). Managing flow: A process theory of the knowledge-based firm. Palgrave Macmillan.

  • OECD (2004). Innovation in the knowledge economy. Implications for Education and Learning.

  • OECD (2005). The definition and selection of key Competencies.

  • OECD (2019). OECD future of education and skills 2030. In OECD learning Compass. 2030 https://www.oecd.org/education/2030-project/teaching-and-learning/learning/learning-compass-2030/OECD_Learning_Compass_2030_Concept_Note_Series.pdf.

    • Search Google Scholar
    • Export Citation
  • Omotayo, F. O. (2015). Knowledge management as an important tool in organisational management: A review of literature. Library Philosophy and Practice. 2015.

    • Search Google Scholar
    • Export Citation
  • Pillay, R. (2008). Defining competencies for hospital management: A comparative analysis of the public and private sectors. Leadership in Health Services, 21(2), 99110. https://doi.org/10.1108/17511870810870547.

    • Search Google Scholar
    • Export Citation
  • Poell, R. F., Berings, M. G. M. C., & Van der Krogt, F. J. (2007). Tailoring learning programmes to every-day employee learning: Customisation strategies of HRD practitioners in health care Cross-Cultural Management View project. https://www.researchgate.net/publication/254806330.

    • Search Google Scholar
    • Export Citation
  • Rangraz, M., & Pareto, L. (2021). Workplace work-integrated learning: Supporting industry 4.0 transformation for small manufacturing plants by reskilling staff. International Journal of Lifelong Education, 40(1), 522.

    • Search Google Scholar
    • Export Citation
  • Rathi, D., & Given, L. M. (2017). Non-profit organizations’ use of tools and technologies for knowledge management: A comparative study. Journal of Knowledge Management, 21(4), 718740. https://doi.org/10.1108/JKM-06-2016-0229.

    • Search Google Scholar
    • Export Citation
  • Rathi, D., Given, L. M., & Forcier, E. (2016). Knowledge needs in the non-profit sector: An evidence-based model of organizational practices. Journal of Knowledge Management, 20(1), 2348. https://doi.org/10.1108/JKM-12-2014-0512.

    • Search Google Scholar
    • Export Citation
  • Reischmann, J. (2017). Lifewide learning – Challenges for andragogy. Journal of Adult Learning, Knowledge and Innovation, 1(1), 4350. https://doi.org/10.1556/2059.01.2017.2.

    • Search Google Scholar
    • Export Citation
  • Senge, P. M. (1990). The fifth discipline. The art and practice of the learning organization. Doubleday.

  • Soakell-Ho, M., & Myers, M. D. (2011). Knowledge management challenges for nongovernment organizations: The health and disability sector in New Zealand. Vine, 41(2), 212228. https://doi.org/10.1108/03055721111134826.

    • Search Google Scholar
    • Export Citation
  • Stewart, J., & Jarvie, W. (2015). Haven’t we been this way before? Evaluation and the impediments to policy learning. Australian Journal of Public Administration, 74(2), 114127. https://doi.org/10.1111/1467-8500.12140.

    • Search Google Scholar
    • Export Citation
  • Strong, B., Davenport, T. H., & Prusak, L. (2008). Organizational governance of knowledge and learning. Knowledge and Process Management, 15(2), 150157. https://doi.org/10.1002/kpm.306.

    • Search Google Scholar
    • Export Citation
  • Trautmann, L., & Vida, C. (2021). Tudásalapú gazdaság – Iparpolitika – Felsőoktatás. Köz-Gazdaság, 16(4), 4976. https://doi.org/10.14267/retp2021.04.04.

    • Search Google Scholar
    • Export Citation
  • Tynjälä, P. (2008). Perspectives into learning at the workplace. Educational Research Review, 3(2), 130154. https://doi.org/10.1016/j.edurev.2007.12.001.

    • Search Google Scholar
    • Export Citation
  • Verschuere, B., Brandsen, T., & Pestoff, V. (2012). Co-production: The state of the art in research and the future agenda. Voluntas, 23(4), 10831101. https://doi.org/10.1007/s11266-012-9307-8.

    • Search Google Scholar
    • Export Citation
  • Walsh, J. N., & Lannon, J. (2020). Dynamic knowledge management strategy development in international non-governmental organisations. Knowledge Management Research and Practice, 00(00), 112. https://doi.org/10.1080/14778238.2020.1785348.

    • Search Google Scholar
    • Export Citation
  • Weick, K. E. (1991). The nontraditional quality of organizational learning. Organizational Learning, 2(1), 116124.

  • World Economic Forum (2020). The future of jobs report 2020 | world economic forum. The Future of Jobs Report October, 1163 https://www.weforum.org/reports/the-future-of-jobs-report-2020/digest.

    • Search Google Scholar
    • Export Citation
  • Zbuchea, A., Ivan, L., Petropoulos, S., & Pinzaru, F. (2020). Knowledge sharing in NGOs: The importance of the human dimension. Kybernetes, 49(1), 182199. https://doi.org/10.1108/K-04-2019-0260.

    • Search Google Scholar
    • Export Citation
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Senior editors

Editor(s)-in-Chief: Helga DORNER

Associate Editors 

  • Csíkos, Csaba (Eötvös Lorand University, Hungary)
  • Csizér, Kata (Eötvös Lorand University, Hungary)
  • Dorner, Helga (Central European University, Hungary)

 

Editorial Board

  • Basseches, Michael (Suffolk University, USA)
  • Billett, Stephen (Griffith University, Australia)
  • Cakmakci, Gültekin (Hacettepe University, Turkey)
  • Damsa, Crina (University of Oslo,Norway)
  • Dörnyei, Zoltán (Nottingham University, UK)
  • Endedijk, Maaike (University of Twente, The Netherlands)
  • Fejes, Andreas (Linköping University, Sweden)
  • Guimaraes, Paula (University of Lisbon, Portugal)
  • Halász, Gábor (Eötvös Loránd University, Hungary)
  • Hansman, Catherine A. (Cleveland State University, USA)
  • Kroeber, Edith (Stuttgart University, Germany)
  • Kumar, Swapna (University of Florida, USA)
  • MacDonald, Ronald (University of Prince Edward Island, Canada)
  • Marsick, Victoria J. (Columbia University, USA)
  • Martensson, Katarina (Lund University, Sweden)
  • Matei, Liviu (Central European University, Hungary)
  • Matyja, Malgorzata (Wroclaw University of Economics, Poland)
  • Mercer, Sarah (University of Graz, Austria)
  • Nichols, Gill (University of Surrey, UK)
  • Nokkala, Terhi (University of Jyvaskyla, Finland)
  • Ostrouch-Kaminska (Uniwersytet Warminsko-Mazurski, Poland)
  • Pusztai, Gabriella (University of Debrecen, Hungary)
  • Ramesal, Ana (Barcelona University, Spain)
  • Reischmann, Jost (Bamberg University, Germany)
  • Rösken-Winter, Bettina (Humboldt, Germany)
  • Ryan, Stephen (Waseda University, Japan)
  • Török, Erika (Pallasz Athéné University, Hungary)
  • Wach-Kakolewicz, Anna (Poznan University of Economics and Business, Poland)
  • Watkins, Karen E. (University of Georgia, Athens, Georgia)

 

 

 

Journal of Adult Learning, Knowledge and Innovation
Editorial Office
Eötvös Loránd University
Faculty of Education and Psychology
Institute of Research on Adult Education and Knowledge Management
Address: 1075 Budapest, Kazinczy u. 23-27. HUNGARY

E-mail: jalki@ppk.elte.hu

2020  
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Journal of Adult Learning, Knowledge and Innovation
Publication Model Gold Open Access
Submission Fee none
Article Processing Charge none
Subscription Information Gold Open Access

Journal of Adult Learning, Knowledge and Innovation
Language English
Size A4
Year of
Foundation
2016
Volumes
per Year
1
Issues
per Year
2
Founder Eötvös Loránd Tudományegyetem
Founder's
Address
H-1053 Budapest, Hungary Egyetem tér 1-3.
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 2631-1348 (Online)

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