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.

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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

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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).