Every organization – be it industrial or service-oriented – that seeks to develop, to compete effectively, and to create value needs to systemically generate and implement innovations across all its areas of operation. In economically developed countries, innovation is treated as a driving force (Hilmersson & Hilmersson, 2021, pp. 43‒49; Latif, 2024) that enables:

1) improved organizational economics,
2) opening up of new markets,
3) enriched knowledge resources and their creative application,
4) renewed industrial structures,
5) effective achievement of developmental goals,
6) expansion and diversification of products, services, and related markets,
7) implementation of new production, supply, and distribution methods,
8) the introduction of new methods of management and work organization, as well as changes in working conditions and staff qualifications,
9) staff integration and stronger relationships with customers,
10) improved quality of work, production standards, workplace health and safety, and environmental protection,
11) enhanced teamwork and collaboration with customers,
12) value creation,
13) increased living standards of societies, etc.

Therefore, it should be a guiding principle of management to systematically enhance the innovativeness of the organizations managed, continually striving to transform them into truly innovative enterprises. However, these issues are often marginalized in business operations. One hallmark of innovative organizations is the active involvement of managers and employees in fostering innovative activity, while remaining guided by shared values (Peters & Waterman, 2000, p. 47). This is supported by the strong correlation that has been found between the introduction of new products and the success of organizations (Tidd & Bessant, 2013, p. 26). Moreover, every manager needs to remember that any market advantage attained through innovation will inevitably diminish over time, due to innovative efforts on the part of other organizations. Therefore, successful organizations have to establish systematic, methodical, and organized processes to ensure the continued creation and practical implementation of innovations.

Innovation is of great economic and social importance, for organizations and societies alike. However, the various processes involved in creating, implementing, and managing innovations often encounter significant challenges. Numerous technical, technological, legal, economic, social and organizational barriers can hinder operational and development activities. These barriers, as highlighted in the literature, can be categorized into three groups (Ordoñez-Gutiérrez et al., 2023, pp. 1–22): 1) cost-related barriers (involving insufficient internal or external financial resources), 2) knowledge-related barriers (a lack of employment opportunities for employees with appropriate qualifications, limited knowledge of market rules, inadequate information about the company’s innovation needs), and 3) market knowledge related barriers (an inability to introduce innovations to the market effectively, making it impossible to recover the costs of their development).

Other scholars have proposed other classifications. Indrawati et al. (2020, p. 555) identified the following barriers: 1) those related to the financing of innovation in enterprises (high costs of innovation, difficulties in obtaining credit from financial institutions, high interest rates), 2) barriers related to government support (minimum financial assistance from the government, a lack of training from the government in the field of innovation, non-targeted government aid for innovative equipment), 3) those related to business partners (no suppliers as business partners, no marketing agencies as business partners), 4) those related to the quality of human resources (difficulties in recruiting high-quality employees, a lack of employee competence, resistance of employees to innovative changes, relatively high resistance of business owners to innovative changes, a lack of knowledge of business owners about innovation), 5) economic conditions (difficulty in obtaining innovative equipment, unstable economy, low purchasing power). Das et al. (2018, p. 99), in turn, have classified barriers into 1) internal (organizational strategy, organizational architecture, leadership, organizational culture, R&D organization, motivational incentives, negative attitude, inadequate innovative competences, unfavorable organizational structure); and 2) external (market dynamics, competitor behavior, market and technological turbulence, customer resistance, ecosystem dynamics, underdeveloped information network).

Recognizing such barriers can support rational decision-making and enhance innovation processes. One way to reduce the negative effects of these barriers to innovative activity is to engage in organized and rationally-managed collaboration among enterprises in the field of creating and implementing innovations.

The research problem addressed herein can be framed as follows: To what extent is collaboration in innovative activity prevalent among Polish enterprises? How dynamic is this collaboration, and is it an element of rational management? To address these questions, this study examines: 1) the proportion of innovative enterprises among the total number of companies, 2) the percentage of innovatively active enterprises, 3) the percentage of enterprises engaging in innovation-related collaboration, 4) the structure of collaborative partners, 5) the percentage of enterprises collaborating within cluster initiatives.

Via these issues, this study explores the role of managerial involvement in overcoming innovation barriers. By addressing these challenges, organizations can improve innovation management, enhancing competitiveness, value creation, knowledge expansion, and market growth.

A key assumption underlying this study is that the relatively low percentage of innovatively active organizations in Poland that decide to collaborate in the field of innovative activity is a consequence of a certain gap between theoretical advancements in innovative management and the willingness of managers to adopt and implement these concepts in practice.

Therefore, the objective of this publication is to assess the prevalence and dynamics of collaboration in innovation among Polish industrial and service enterprises and to demonstrate that such cooperation is not yet a common component of managerial decision-making. This state of affairs stands in contrast to the model solutions presented in the literature.

The article is structured into an introduction, followed by a critical literature review, research methodology, presentation of research findings and their analysis; and summary of the findings as well as suggestions for further research.

2. Literature review

Due to its high importance for the development of organizations, regions and entire economies – as well as in value creation – innovation has been extensively explored in the research literature, from a variety of technical, economic, management, organizational, sociological and psychological perspectives (Brzeziński, 2001; Sosnowska et al. 2000; Świtalski, 2005; Janasz & Kozioł-Nadolna, 2011; Zangara & Filice, 2024, pp. 360–383; Ullah et al., 2024, pp. 1967–1985). Authors have focused their attention on explaining the essence of innovation, classifying innovations, identifying innovation’s role in the development of organizations, increasing their competitiveness, improving management efficiency, improving management and the qualifications of employees, creating innovations as a team and organizing the national innovation system, etc. (Baruk, 2009, pp. 93–103; Świadek, 2021; Kozioł-Nadolna, 2022). Note that despite the extent of this literature, no uniform, universally applicable definition of innovation has yet been developed. The vagueness and diversity of definitions presented in the literature makes it difficult to understand the essence of innovation and hinders communication between theoreticians and practitioners, contributing to interpretative confusion (Baruk, 2022, pp. 10–23; Baregheh et al., 2009, p. 1334).

Since innovation activity faces various types of external and internal obstacles, some authors have attempted to identify such obstacles and their impact on the universality of creating and implementing innovations, as well as on the effectiveness of innovative activity. As noted above, three groups of barriers to innovative activity are most often indicated (Das et al., 2018, p. 99; Carvache-Franco et al., 2022, p. 1–17; Martínez-Azúa & Sama-Berrocal, 2022, p. 1–25): (a) cost and financial barriers, (b) knowledge barriers, (c) market barriers. Social barriers are also significant – managerial resistance, especially among middle management, and lack of employee engagement (Alshwayat et al., 2023, pp. 159–170).

Given the negative impact of these barriers on the efficiency of innovative activities, it is crucial to seek ways to eliminate or at least mitigate them. One such strategy widely discussed in the literature involves fostering collaboration with other business entities / research centers. Well-organized cooperation of this sort has been shown to have numerous advantages (Hardwick et al., 2013, pp. 4–21): reduced risk of failure, lower costs of innovation activities, improved effectiveness, rational use of knowledge possessed by cooperating organizations, expanding and enriching this knowledge, and shortened innovation development cycles, etc.

In general, cooperation in innovation can adopt four broad forms: distant, translated, definite and developed (Lind et al. 2013, pp. 70–91; Wong et al., 2018, pp. 316–332; Yunus, 2018, pp. 350–370). Collaboration is recognized as one of the four key elements of innovation – alongside ideas, implementation and value creation (Cowan et al., 2009; Watkins, 2024).

Since innovation relies on knowledge, numerous authors have explored the relationship between knowledge creation, innovation, and knowledge management (Baruk, 2023, pp. 43–55; Nonaka & Takeuchi, 2000; Kowalczyk & Nogalski, 2007; Baruk, 2009; Baruk, 2018, pp. 83–110; Baruk, 2011, pp.113–127). The function linking knowledge creation to innovation is undoubtedly the efficient management of knowledge and innovation within a single system. However, how to best achieve such a systemic approach remains an open problem challenge in the literature. Theoretical and empirical research on knowledge and innovation management continues to offer valuable insights, especially for leaders managing modern enterprises (Baruk, 2021, pp. 14–21; Baruk, 2022, pp. 10–23; Tidd & Bessant, 2013; Baruk, 2015, pp. 121–145).

5. Research methodology

This study is based on empirical research conducted by Poland’s Central Statistical Office (GUS) on the innovative activity of enterprises in Poland in 2014–2022. These surveys covered all industrial and service enterprises with 10 or more employees and were conducted as part of the international research program Community Innovation Survey (CIS), using the standardized PNT–02 questionnaire. The results of these studies were presented in the publications GUS (2017, 2019, 2020, 2023).

Numerical data taken from these publications enabled a detailed interpretation of the studied phenomenon in terms of its universality and dynamics. Additionally, they also allowed for the verification of the following detailed research questions:

1) Was innovation-related collaboration an element of rational decision-making processes in Polish industrial and service organizations?
2) How prevalent was collaboration in innovative activities?
3) What were the dynamics of such cooperation?
4) Who were the collaborating partners?
5) Was a cluster participation a significant form of cooperation?

The following research methods were employed in this study: 1) critical and cognitive analysis of selected literature on the subject, 2) descriptive and comparative methods, 3) statistical analysis, 4) the projective method. These methods facilitated the interpretation of key concepts, an overview of the current knowledge base, barriers accompanying innovative activity, as well as the universality and dynamics of the use of cooperation in Polish industrial and service organizations. Additionally, the projective method was used to outline potential strategies for improving the management of collaborative innovative activities.

Research results and discussion

1) The level of innovation at Polish enterprises and its dynamics in 2016–2022

The level of innovation can be assessed using various indicators, one of which is the proportion of innovative enterprises among the total number of business entities. As Table 1 shows, in 2016–2022, the share of innovative industrial enterprises in the total number of Polish enterprises in this sector was at an average level of 23.7%. This measure notably fluctuated over subsequent years, reaching its highest value in 2022 – over 32%. Compared to 2016, this represents an increase of 13.5 percentage point.

A key finding is the low percentage of industrial enterprises engaging in innovation cooperation, which remained below 10% throughout the study period (peaking at 9.1% in 2022). Additionally, industrial enterprises that were active in innovation undertook cooperation within the framework of cluster initiatives, with a participation rate of 14%. The highest values were observed in 2018 (21%) and 2019 (20.5%).

In the service sector, the average proportion of innovative enterprises was 19.7% – 4 percentage points less than for the industrial sector. Throughout the analyzed period, the percentage of innovative enterprises in services was consistently lower than in industry, with the largest gap coming in 2017, at 8.1 percentage points.

Engagement in collaborative innovation is typically influenced by the overall level of innovative activity within business entities. As shown in Table 2, the average percentage of innovatively active enterprises was 26% in the industrial sector and 20.8% in the services sector. A positive trend was the growing percentage of innovatively active entities in both sectors and within individual categories of enterprises. However, a decline was observed in the services sector in 2017–2019, where the share of innovatively active enterprises decreased by 0.8 percentage points compared to the previous period. A similar trend occurred among small enterprises, where in the corresponding period the proportion of innovatively active companies decreased by 1 percentage points.

A key characteristic of innovative activity is its correlation with enterprise size, measured by the number of employees. As shown in Table 2, the prevalence of innovatively active companies increases with enterprise size in both the industrial and service sectors. The lowest percentage of innovatively active firms was recorded among small enterprises, while the highest was observed among large enterprises. Notably, on average, in the European Union (2018–2020), 52.7% of enterprises engaged in innovative activities, whereas in Poland, the figure was only 34.9%, reflecting a 17.8 percentage point (p.p.) gap (EUROSTAT).

2) Prevalence of innovation-related collaboration among innovatively active enterprises

One of the key questions for this study is: What percentage of innovatively active enterprises engage in innovation-related cooperation? As Table 3 shows, in 2014–2016, almost one-third of innovatively active enterprises engaged in cooperation. However, this percentage declined by 9.4 p.p. in 2017–2019 and further by 8.1 p.p. in 2020–2022. Small enterprises were the least likely to cooperate, with only one in four firms engaging in collaborative innovation in 2014–2016. This figure further declined by 10.2 p.p. in 2017–2019 and by 8.3 p.p. in 2020–2022. The likelihood of cooperation increased with enterprise size. Among large enterprises, nearly 51% engaged in innovation cooperation in 2014–2016. However, this figure declined by 7.4 p.p. in 2017–2019 and by 0.5 p.p. in 2020–2022.

Similar trends in innovation-related collaboration were observed in the services sector. The most favorable period was between 2014 and 2016, when nearly 27% of innovatively active service companies engaged in cooperation. However, in the following years, this share declined by 8.4 percentage points and then by an additional 4.7 percentage points. A similar pattern was evident across service enterprises of different sizes, with small companies showing the lowest levels of collaboration and large enterprises the highest.

Between 2014 and 2016, in the industrial sector, companies that were actively engaged in innovation and cooperated with business entities in this field exhibited varying levels of collaboration depending on their industry. The highest levels of cooperation were seen among enterprises producing tobacco products, other transport equipment, and coke and refined petroleum products, where collaboration rates reached 60.0%, 59.3%, and 57.1%, respectively. In contrast, companies involved in furniture production, leather and leather products, and clothing manufacturing had the lowest levels of innovation-related cooperation, with rates of 16.1%, 15.4%, and 4.9% (GUS, 2017, pp. 87–88). A similar distribution was observed in the services sector during the same period 2014–2016, where enterprises in air transport, film and TV production, and scientific research and development demonstrated the highest levels of cooperation. In these industries, all air transport enterprises participated in innovation-related collaboration, while 66.7% of film and TV production companies and 59.6% of research and development firms engaged in such activities. On the other end of the spectrum, businesses involved in publishing, postal and courier services, and land and pipeline transport had the lowest levels of collaboration, with rates of 17.7%, 9.1%, and 8.0%, respectively (GUS, 2017, pp. 87–88).

Between 2017 and 2019, industrial enterprises exhibited significant variation in their engagement in innovation-related collaboration. The highest levels of cooperation were recorded in metal ore mining, where all innovatively active companies collaborated with other enterprises or institutions. Similarly, in the mining of hard coal and lignite, 60% of companies engaged in innovation-related cooperation, while 44.4% of enterprises producing coke and refined petroleum products did the same. The lowest levels of collaboration were observed in food product manufacturing, where only 14.2% of businesses participated, as well as in water collection, treatment, and supply at 13.8%, and furniture production at 13.5% (GUS, 2020, pp. 77–78). In the services sector during the same period, 2017–2019, scientific research and development remained the area with the highest prevalence of innovation cooperation, with nearly 59.7% of firms in this field engaging in such activities. Companies in architecture and engineering, as well as those involved in technical research and analysis, also showed significant collaboration, with 32.3% participating in innovation-related partnerships. Telecommunications companies followed, with 29.2% engaging in cooperation. In contrast, businesses in postal and courier services, warehousing, and transport support services demonstrated the lowest levels of participation, with cooperation rates of 5.6%, 4.2%, and 2.2%, respectively (GUS, 2020, pp. 77–78).

During the 2020–2022 period, in turn, innovation cooperation among industrial enterprises was most common in tobacco product manufacturing and the mining of hard coal and lignite, where 66.7% of innovatively active companies engaged in collaboration. The production of other transport equipment also exhibited a high level of cooperation, with 49.7% of enterprises in this sector participating. However, cooperation was much less common in industries such as wood, cork, straw, and wicker product manufacturing, where only 13.1% of firms engaged in collaborative innovation efforts. Similarly, clothing production had a cooperation rate of 12.5%, while reclamation activities showed the lowest level of engagement at just 10.0% (GUS, 2023, p. 77). In the services sector during the same period, scientific research and development remained the dominant area for innovation-related collaboration, with 65.6% of innovatively active organizations participating. Other sectors also demonstrated considerable cooperation, including insurance, reinsurance, and pension funds, where 41.1% of companies engaged in innovation partnerships, as well as architecture and engineering, where 33.6% collaborated. On the lower end of the spectrum, postal and courier services had a cooperation rate of 17.2%, land and pipeline transport had 12.9%, and water transport had the lowest level of participation at just 11.1% (GUS, 2023, p. 78).

In terms of geographical distribution, between 2014 and 2016 the highest percentage of industrial enterprises engaged in innovation cooperation was recorded in the Podkarpackie (41.4% of innovatively active companies), Śląskie (38.5%), and Małopolskie (38.1%) provinces. In contrast, the lowest levels of cooperation were observed in the Wielkopolskie (29.2%), Zachodniopomorskie (28.6%), and Lubuskie (27.1%) provinces. In the services sector during the same period, innovation-related collaboration was most common among enterprises in the Podkarpackie (73.4%), Warmińsko-Mazurskie (46.2%), and Świętokrzyskie (40.7%) provinces. On the other end of the spectrum, the lowest levels of cooperation were recorded in Łódzkie (14.9%), Opolskie (8.3%), and Lubelskie (7.3%) (GUS, 2017, p. 89).

In the 2017–2019 period, in turn, the pattern changed slightly for industrial enterprises, with the highest levels of innovation cooperation occurring in Lubelskie (29.2%), Śląskie (28.2%), and Opolskie (27.7%). The lowest rates were observed in Podlaskie (19.0%), Zachodniopomorskie (18.9%), and Warmińsko-Mazurskie (13.7%). For service enterprises during the same period, the highest levels of collaboration were recorded in Podkarpackie (39.7%), Łódzkie (31.8%), and Lubuskie (26.7%). In contrast, the lowest levels of cooperation were found in Podlaskie (10.0%), Wielkopolskie (7.4%), and Zachodniopomorskie (2.7%) (GUS, 2020, p. 79).

During 2020–2022, the territorial distribution of innovation cooperation changed once again. Among industrial enterprises, the highest prevalence was recorded in Kujawsko-Pomorskie (34.5%), Opolskie (30.1%), and Podlaskie (29.2%), while the lowest rates were seen in Łódzkie (18.8%), Świętokrzyskie (18.2%), and Warmińsko-Mazurskie (17.8%). In the services sector during the same period, the highest levels of cooperation in innovation were found in Zachodniopomorskie (48.5%), Podkarpackie (40.8%), and Lubuskie (35.5%), whereas the lowest levels were recorded in Opolskie (8.3%), Podlaskie (8.2%), and Kujawsko-Pomorskie (7.1%) (GUS, 2023, p. 79).

Analyzing innovation cooperation by technological level, it is evident that in the industrial processing sector, high-tech enterprises were the most engaged in collaboration, while low-tech enterprises showed the lowest participation. Between 2014 and 2016, innovation cooperation was undertaken by 46.7% of high-tech companies, compared to just 2.2% of low-tech firms (GUS, 2017, p. 90). A similar pattern persisted in 2017–2019, with 33.9% of high-tech enterprises engaging in cooperation, while low-tech firms exhibited a significantly lower rate of 14.6% (GUS, 2020, p. 80). Between 2020 and 2022, the trend remained consistent, with 36.4% of high-tech enterprises participating in innovation-related collaboration, compared to 20.2% of low-tech firms (GUS, 2023, p. 80).

3) Cooperation partners of enterprises in the field of innovative activities

Now that we know that Polish enterprises engaged in innovation-related collaboration, the next important question arises: Who were their key cooperation partners? Table 4 provides a detailed breakdown of these partnerships.

Among industrially active enterprises, collaboration with Polish universities was the most common. Between 2016 and 2018, nearly 48% of industrial enterprises cooperated with universities in Poland. This percentage increased to 56% between 2017 and 2019, before declining to 39% in 2020–2022. Collaboration with foreign universities was significantly less frequent. On average, 3.2% of industrial enterprises cooperated with universities in the EU and EFTA countries, while only 0.5% partnered with universities outside these regions.

Industrial enterprises also collaborated with public research institutes (including those of the Polish Academy of Sciences). Most often these were domestic Polish institutes. In the years 2016–2022, on average, less than 31% of innovatively active companies engaged in such cooperation. There were also cases, albeit rare, of cooperation with foreign institutes. On average, about 2.2% of industrial enterprises cooperated with institutes from the EU and EFTA countries in the analyzed period. On the other hand, about 0.5% of companies in the industrial sector undertook such cooperation with institutes in other countries.

Another common type of cooperation partner was companies belonging to the same group of companies. Most often these were domestic Polish companies, with which almost 26% of enterprises cooperated on average. Some enterprises also collaborated with affiliates from the EU and EFTA countries (16.2%) and from other countries (5.2%).

Industrial enterprises also cooperated with companies from outside their own group of enterprises. In this respect, domestic companies were preferred, with about 54% of industrial enterprises choosing Polish firms as cooperation partners. Meanwhile, 23.1% of partnerships involved EU and EFTA-based firms, and 9.5% involved companies from other countries.

Public sector entities also played a role in innovation cooperation, though at a smaller scale. On average, 11% of industrial enterprises collaborated with Polish public sector units, while partnerships with public sector entities from EU and EFTA countries involved only 0.83% of companies. Cooperation with public sector organizations outside these regions was rare, with only 0.33% of industrial enterprises reporting such collaborations.

Non-profit organizations accounted for a small share of innovation cooperation. In 6.1% of cases, Polish non-profits were cooperation partners for industrial enterprises. Cooperation with EU and EFTA-based organizations was recorded in 0.46% of cases, while 0.56% of partnerships involved non-profits from other countries.

In the service sector, the prevalence patterns of collaboration followed a similar trend. As seen in Table 5, service enterprises most frequently partnered with Polish firms from outside their corporate group. Between 2016 and 2018, only one in four innovatively active service enterprises engaged in such cooperation. However, this figure rose significantly in the following years, exceeding 70% in the 2020–2022 period.

A significant percentage of innovatively active service companies engaged in collaboration with Polish universities. However, this collaboration declined over time, decreasing from 46.4% in 2016–2018 to 43.1% in 2017–2019, and further dropping to 25.9% in 2020–2022. Cooperation with foreign universities remained limited, with only a small percentage of service enterprises establishing partnerships outside Poland. Service enterprises also collaborated with companies within their own corporate group, particularly those based in Poland. On average, 27.6% of service enterprises partnered with domestic companies from within their group, while 17.9% collaborated with firms from EU and EFTA countries, and 8.4% engaged in partnerships with companies from other regions. Collaboration with public research institutes, including those affiliated with the Polish Academy of Sciences, was another avenue for innovation-related cooperation. On average, 21.6% of service enterprises worked with Polish public research institutes, though partnerships with foreign institutions remained minimal. A smaller proportion of service enterprises partnered with public sector entities and non-profit organizations. On average, 11.1% of service enterprises collaborated with Polish public sector institutions, while 7.7% partnered with non-profits in the field of innovation.

4) Companies cooperating within the cluster initiative

One form that innovation-related collaboration among enterprises my take is participation in cluster initiatives. A cluster is a network that harnesses the innovative and organizational potential of a regional environment, supporting intellectual capital accumulation and its efficient utilization. (Encyclopedia.com, n.d.). This structure fits well into the modern innovation paradigm, emphasizing systematicity, holism, and interactivity. Clusters combine the flexibility of small businesses with the innovation and global reach of large enterprises, creating a network where businesses collaborate with the local community cooperates with the companies: state institutions, R&D centers, standardization bodies, quality control laboratories and universities, and even industry, political and cultural organizations.

The key question here is: To what extent did Polish companies take advantage of these opportunities? As shown in Table 6, between 2016 and 2018, only 3.5% of industrial enterprises participated in cluster initiatives. This figure declined to 3.2% in 2017–2019 and further dropped to 2.8% in 2020–2022.

In terms of enterprise size, large industrial companies demonstrated the greatest interest in cluster-based cooperation, with an average participation rate of 10.87% over the analyzed period. This figure showed an upward trend, indicating increasing involvement. In contrast, small industrial enterprises were far less engaged, with their participation rate averaging only 1.9%. Among service enterprises, in turn, only 2.2% of companies, on average, engaged in cluster cooperation. Large service enterprises participated the most, while small enterprises showed the least interest in this form of collaboration.

In terms of geographical distribution, in 2016–2018, the highest levels of industrial cluster cooperation were observed for industrial companies in the Lubelskie (8.1%) and Podkarpackie (7.6%) provinces. Meanwhile, the lowest levels were recorded in Opolskie (1.1%) and Wielkopolskie (2.0%). For service enterprises, the highest rates of participation were in Świętokrzyskie (6.6%) and Lubelskie (4.1%), whereas in Opolskie, no companies were recorded as participating in cluster initiatives during this period (GUS, 2019, p. 84).

By 2020–2022, the highest levels of cluster cooperation among industrial enterprises were in Podlaskie (6.3%) and Lubelskie (4.9%), while the lowest levels were recorded in Łódzkie (1.0%) and Lubuskie (1.6%). Among service enterprises, Lower Silesia (3.1%) and West Pomeranian (2.5%) recorded the highest levels of cooperation in this period, whereas Świętokrzyskie (0.5%) and Opolskie (0.6%) had the lowest (GUS, 2023, pp. 83–84).

Broken down by industry, between 2016 and 2018, cluster participation was highest among industrial companies engaged in hard coal and lignite mining (18.2%) and metal ore mining (16.7%). On the other hand, industries such as paper and paper product manufacturing and textile production had the lowest rates of participation, at only 1.2% each (GUS, 2019, pp. 86–87). By 2020–2022, the highest cluster participation in the industrial sector was recorded in the production of other transport equipment (12.5%), while no companies in the tobacco or clothing manufacturing sectors participated in cluster initiatives.

In the service sector, the highest level of cluster participation between 2016 and 2018 was found in scientific R&D (17.1%) and air transport (13.6%). In contrast, wholesale trade (1.5%) and land and pipeline transport (0.9%) had the lowest levels of participation. By 2020–2022, the research and development sector remained the most active in cluster initiatives, with 21.7% of enterprises engaged. However, in the water transport sector, no companies were recorded as participating in cluster cooperation (GUS, 2023, pp. 83–84).

More broadly, the statistical data presented in this paper indicate a certain regularity: industrial enterprises engaged in high-technology activities were the most likely to participate in cluster initiatives, with an average participation rate of 10.8%. Conversely, companies operating in low-technology industries had the lowest participation rate, at only 1.2% (GUS, 2023, p. 87).

4. Conclusions

The primary aims of this study were: 1) to analyze the prevalence of innovative activity among Polish industrial and service enterprises and, in this context, the prevalence of their innovation-related collaboration with other business entities, 2) to critically assess the extent of Polish enterprises’ innovation-related collaboration, demonstrating that such collaboration has occupied only a rather marginal place the managerial decision-making processes.

To achieve these goals, key measures were used to assess both innovation activity and innovation-related collaboration. These measures, outlined in six tables, were critically analyzed, resulting in the following key conclusions:

1. The share of innovative enterprises in the total number of businesses, both industrial and service-based, fluctuated across the years analyzed, without showing a clear upward trend.
2. The percentage of industrial enterprises engaged in innovation-related cooperation varied randomly over time and never exceeded 9.1% during the analyzed period.
3. Although the share of industrial enterprises participating in formalized cooperation structures was slightly higher, it remained inconsistent over time.
4. The percentage of innovatively active enterprises was slightly higher in the industrial sector than in the service sector. In both sectors, larger enterprises exhibited higher levels of innovative activity compared to smaller ones.
5. Cooperation in innovation activities was slightly more common in the industrial sector than in the service sector. Even during the most favorable period (2014–2016), cooperation rates did not exceed 33% in industry and 27% in services, and in subsequent periods, they were even lower. This suggests that decision-making processes related to innovation cooperation were highly inconsistent. Larger enterprises had a significantly higher level of participation, while small enterprises remained the least engaged.
6. When comparing innovation cooperation rates in Poland with those in other European countries, Poland ranked relatively low. In 2018–2020, 23.6% of industrial enterprises in Poland cooperated in innovation, whereas in Norway, this rate was 53.8%. Similarly, in the services sector, the Polish cooperation rate was 20.9%, compared to 43.2% in Cyprus (GUS, 2023, p. 87). Earlier data from 2016–2018 showed similarly unfavorable trends (GUS, 2020, p. 86). In 2020, the EU average for innovation cooperation stood at 25.7%, while in Poland, it was 22.4%, 3.3 percentage points lower (EUROSTAT 2020a, 2020b).
7. Both industrial and service companies undertook limited innovation-related collaboration with various partners. Most often these were: enterprises from outside their own group of enterprises; undertakings belonging to its own group of companies; higher education institutions; public research institutes; public sector entities and non-profit organizations. Collaboration was mainly with domestic partners from Poland, much less often with those from other countries. The low level of strategic organization in these collaborations suggests that cooperation was often ad hoc than systematically managed.
8. Cluster initiatives remained an underutilized form of innovation cooperation. The average participation rate was 3.16% for industrial enterprises and 2.16% for service enterprises, with a downward trend in later periods.

The relatively low level of innovation among Polish enterprises appears to stem from a lack of understanding of innovation’s role, its impact on business development, and weak innovation management practices that are not grounded in knowledge-based, research-driven models (Baruk, 2022, pp. 10–23; Baruk, 2021, pp. 14–27). Consequently, innovation activity and innovation-related collaboration remain limited.

Often, employees within companies lack the necessary knowledge to develop systematic or radical innovations. In such cases, it is crucial to access external knowledge through structured collaboration with scientific and economic institutions that possess the necessary expertise or can help co-create it. Therefore, managers must develop competencies in key areas related to innovation, such as knowledge management, strategy, organizational culture, systemic learning, teamwork, and cooperation with business partners and clients.

Effective innovation management should be based on a deep understanding of the impact of innovation on businesses, their employees, and end users. As a result, managers should strive to transform their organizations into leading innovators (Peters & Waterman, 2000, pp. 45–48). Achieving this goal requires implementing structured, research-backed innovation management strategies, as outlined in relevant scientific literature (Baruk, 2022, pp. 10–23; Baruk, 2021, pp. 14–27; Baruk, 2009; Baruk, 2015, pp. 121–145; Tidd & Bessant, 2013).

5. Suggestions for further research

Given the levels of enterprise innovation analyzed in this study, further theoretical and empirical research is warranted to assess the stability or variability of these measures over time. Conducting such an analysis would provide valuable insights into several key questions, including:

1. Are trends in enterprise innovation activity consistent over time, and if so, what patterns emerge?
2. What are the long-term tendencies in innovation-related cooperation?
3. How do these trends evolve dynamically across different periods?
4. Which scientific and economic entities are most commonly involved in innovation cooperation?
5. How widespread and dynamic is such cooperation across industries and sectors?
6. What tangible effects does innovation collaboration have on business performance?
7. How do information-sharing and decision-making processes influence the initiation of cooperation?
8. Do managers systematically analyze and evaluate innovation activity and collaboration trends?
9. Are the findings from these analyses effectively used to improve management processes and decision-making within enterprises?

Addressing these questions would deepen our understanding of innovation ecosystems, help identify barriers and facilitators of collaboration, and provide practical recommendations for improving innovation management strategies in business environments.

References

Alshwayat, D., Elrehail, H., Shehadeh, E., Alsalhi, N., Shamout, M. D., & Ur Rehman, S. (2023). An exploratory examination of the barriers to innovation and change as perceived by senior management. International Journal of Innovation Studies, 7(2), 159–170. https://doi.org/10.1016/j.ijis.2022.12.005

Baregheh, A., Rowley, J., & Sambrook, S. (2009). Towards a multidisciplinary definition of innovation. Management Decision, 4(8), 1334. https://doi.org/10.1108/00251740910984578

Baruk, J. (2009). Zarządzanie wiedzą i innowacjami [Management of knowledge and innovations]. Wydawnictwo Adam Marszałek w Toruniu.

Baruk, J. (2011). Wiedza w procesach tworzenia innowacji [Knowledge in the processes of creating innovations]. Organizacja i Kierowanie (4), 113–127.

Baruk, J. (2015). Zarządzanie działalnością innowacyjną w organizacjach naukowych i badawczo-rozwojowych [Managing innovative activities in scientific and research and development organizations]. Marketing Instytucji Naukowych i Badawczych, 17(3), 121–145; https://doi.org/10.14611/ minib.17.03.2015.04

Baruk, J. (2018). Wiedza i innowacje jako czynniki rozwoju organizacji – Podejście zintegrowane [Knowledge and innovation as factors of organizational development – An integrated approach]. Marketing Instytucji Naukowych i Badawczych, 29(3), 83–110. https://doi.org/10.14611/minib.29.09.2018.05

Baruk, J. (2021). Wspieranie zarządzania innowacjami rozwiązaniami modelowymi [Supporting innovation management with model solutions]. Marketing i Rynek, XXVIII(3), 14–27. https://doi.org/10.33226/1231-7853.2021.3.2

Baruk, J. (2022). Racjonalizacja zarządzania innowacjami – koncepcje modelowe [Rationalization of innovation management – Model concepts]. Marketing i Rynek, XXIX(5), 10–23. https://doi.org/10.33226/1231-7853.2022.5.2

Baruk, J. (2023). Znaczenie wiedzy w podnoszeniu sprawności działalności innowacyjnej przedsiębiorstw [The importance of knowledge in improving the efficiency of innovative activities of enterprises]. Marketing i Rynek, XXX(6), 43–55. https://doi.org/10.33226/1231-7853.2023.6.5

Brzeziński, M. (ed.). (2001). Zarządzanie innowacjami technicznymi i organizacyjnymi [Management of technical and organizational innovations]. Warszawa, Difin.

Carvache-Franco, O., Carvache-Franco, M., & Carvache-Franco, W. (2022). Barriers to Innovations and Innovative Performance of Companies: A Study from Ecuador. MDPI. Social Science, 11(2), 1–17.

Cowan, K. M., Haralson, L.E., & Weekly, F. (2009). The Four Key Elements of Innovation: Collaboration, Ideation, Implementation and Value Creation. Retrieved July 24, 2024, from https://www.stlouisfed.org/ publications/bridges/summer-2009/the-four-key-elements-of-innovation-collaboration-ideation-implementation-and-value-creation

Das, P., Verburg, R., Verbraeck, A., & Bonebakker, L. (2018). Barriers to innovation within large financial services firms: An in-depth study into disruptive and radical innovation projects at a bank. European Journal of Innovation Management, 21(1), 96–112. https://doi.org/10.1108/EJIM-03-2017-0028

Encyclopedia.com. (n.d.). Clusters. Retrieved July 28, 2024, from https://www.encyclopedia.com/ entrepreneurs/encyclopedias-almanacs-transcripts-and-maps/clusters

EUROSTAT. (2020a) Enterprises with innovation activities during 2018 and 2020 by NACE Rev. 2 activity and size class (2020). Retrieved July 26, 2024, from https://ec.europa.eu/eurostat/databrowser/ view/inn_cis12_inact/default/table?lang=en&category=scitech.inn.inn_cis12.inn_cis12_inno

EUROSTAT. (2020b). Innovative enterprises that co-operated on R&D and other innovation activities with other enterprises or organisations, by kind and location of co-operation partner, NACE Rev. 2 activity and size class (2020). Retrieved July 26, 2024, from https://ec.europa.eu/eurostat/databrowser/ view/inn_cis12_coop/default/table?lang=en&category=scitech.inn.inn_cis12.inn_cis12_inno

GUS. (2017). Działalność innowacyjna przedsiębiorstw w latach 2014-2016 [Innovative activity of enterprises in the years 2014-2016]. Central Statistical Office (GUS). Warszawa, Szczecin.

GUS. (2019). Działalność innowacyjna przedsiębiorstw w latach 2016-2018 [Innovative activity of enterprises in the years 2016-2018]. Central Statistical Office (GUS). Warszawa, Szczecin.

GUS. (2020). Działalność innowacyjna przedsiębiorstw w latach 2017-2019 [Innovative activity of enterprises in the years 2017-2019]. Central Statistical Office (GUS). Warszawa, Szczecin.

GUS. (2023). Działalność innowacyjna przedsiębiorstw w latach 2020-2022 [Innovative activity of enterprises in the years 2020-2022]. Central Statistical Office (GUS). Warszawa, Szczecin.

Hardwick, J., Anderson, A. R., & Cruickshank, D. (2013). Trust formation processes in innovative collaborations. European Journal of Innovation Management, 16(1), 4–21. https://doi.org/10.1108/ 14601061311292832

Hilmersson F.P. & Hilmersson M. (2021). Networking to accelerate the pace of SME innovations. Journal of Innovation and Knowledge, 6(1), 43–49. https://doi.org/10.1108/14601061311292832

Indrawati H., Caska, & Suarman. (2020), Barriers to technological innovations of SMEs: how to solve them?, International Journal of Innovation Science, 12(5), 545–564. https://doi.org/10.1108/IJIS-04-2020-0049

Janasz, W. & Kozioł-Nadolna, K. (2011). Innowacje w Organizacji [Innovations in the Organization]. Warszawa, PWE Polskie Wydawnictwo Ekonomiczne.

Kowalczyk, A. & Nogalski, B. (2007). Zarządzanie wiedzą. Koncepcje i narzędzia [Managing Knowledge: Concepts and Tools]. Warszawa, Difin.

Kozioł-Nadolna, K. (2022). Przywództwo a innowacyjność organizacji. Perspektywa teoretyczna i praktyczna [Leadership and Organizational Innovativeness: Theoretical and Practical Perspectives]. Warszawa, Difin.

Latif, Y. (2024). Importance of innovation. Retrieved July 26, 2024, from https://www.linkedin.com/ pulse/importance-innovation-yasir-latif-cipm-cipc-v0ed

Lind, F., Styhre, A., & Aaboen, L. (2013). Exploring university-industry collaboration in research centres. European Journal of Innovation Management. 16(1), 70–91. https://doi.org/10.1108/14601061311292869

Martínez-Azúa, B. C. & Sama-Berrocal, C. (2022). Objectives of and Barriers to Innovation: How Do They Influence the Decision to Innovate? Journal of Open Innovation: Technology, Market, and Complexity, 8(134), 1–25. https://doi.org/10.3390/joitmc8030134

Nonaka, I. & Takeuchi, H. (2000). Kreowanie wiedzy w organizacji [Generating Knowledge in the Organization]. Warszawa, Poltext.

Ordoñez-Gutiérrez A.V., Mendez-Morales A., & Herrera M.M. (2023). Barriers to Innovation: A Systematic Literature Review. Trilogia, Ciencia Tecnología Socieda, 29(15), 1–22. https://doi.org/10.22430/21457778.2614

Peters, T.J. & Waterman, R.H. (2000). Poszukiwanie doskonałości w biznesie [Seeking Excellence in Business]. Warszawa: Wydawnictwo MEDIUM. Polish edition of Peters, T. J., & Waterman, R. H. Jr. (1982). In search of excellence: Lessons from America’s best-run companies. Harper & Row.

Sosnowska, A., Łobejko, S., & Kłopotek, A. (2000). Zarządzanie firmą innowacyjną [Managing an Innovative Firm]. Warszawa, Difin.

Świadek, A. (2021). Krajowy system innowacji 2.0 [The National Innovation System 2.0]. Warszawa, CeDeWu.

Świtalski, W. (2005). Innowacje i konkurencyjność [Innovations and Competitiveness], Warszawa, WUW.

Tidd, J. & Bessant, J. (2013). Zarządzanie innowacjami. Integracja zmian technologicznych, rynkowych i organizacyjnych. Warszawa. Oficyna a Wolters Kluwer Business. Polish edition of Tidd, J. & Bessant, J. (1997), Managing Innovation: Integrating Technological, Market and Organizational Change.

Ullah, I., Hameed, R.M., Mahmood, A. (2024). The impact of proactive personality and psychological capital on innovative work behavior: evidence from software houses of Pakistan, European Journal of Innovation Management, 27(6), 1967–1985. https://doi.org/10.1108/EJIM-01-2022-0022

Watkins, M. (2024). The Power of Collaboration: How an Open Innovation Platform Fuels Your Company’s Success. Retrieved July 25, 2024, from https://www.wazoku.com/blog/open-innovation-crowdsourcing-external-innovation-collaboration/

Wong, J.-Y., Wan, T.-H., & Chen, H.-C. (2018). The innovative grant of university–industry–research cooperation: A case study for Taiwan’s technology development programs. International Journal of Innovation Science, 10(3), 316–332. https://doi.org/10.1108/IJIS-01-2017-0004

Yunus, E. N. (2018). Leveraging supply chain collaboration in pursuing radical innovation. International Journal of Innovation Science, 10(6), 350–370. https://doi.org/10.1108/IJIS-05-2017-0039

Zangara, G. & Filice, L. (2024). Innovating the management of supply chains for social sustainability: from the state of the art to an integrated Framework. European Journal of Innovation Management, 27(9), 360–383. https://doi.org/10.1108/EJIM-02-2024-0120

A rationally managed enterprise, systemically focussed on dynamic development at the stage of progress, competitiveness, conquering new markets, or increasing its position on existing markets, must be able to combine three spheres of activity into one systemic whole. Such spheres include: the pre-production sphere, the production sphere, and the postproduction sphere. A special role should be assigned to the pre-production sphere, because it involves the processes of generating/acquiring knowledge necessary to effectively solve all managerial, organisational, technical, and technological problems arising in the company and its environment. The ability to quickly and effectively conduct the processes of generating/acquiring knowledge requires a rational link between research and development (R&D) and innovation activities into one common whole research-development-innovation (R&D&I). The concept of treating the above phases together makes up the cycle of the research system, which can be considered the most important stimulus for the generation of knowledge in the structures of the modern economic entity (Mate & Molero, 2021, p. 1–14). The presented concept requires changes in the approach to managing individual spheres of the company’s activity, it requires innovation in management.

Particular emphasis should be placed on developing the ability to identify problems and acquire the knowledge necessary to solve them efficiently, materialised in the form of streamlining and radical innovations. Such knowledge is acquired as a result of organised R&D activities carried out within the enterprise or organised acquisition of external knowledge. Research and development is considered the cornerstone of the competitive advantage, the long-term success of the organisation (Heij et al., 2020, p. 277–294). In the absence of sufficient resources of up-to-date knowledge, effective solutions to even the smallest problems are not possible. Therefore, the management faces an important task consisting of organising R&D activities in such a way as to ensure a systematic supply of knowledge necessary to identify and solve problems and create innovations, especially product and process innovations.

Rational organisation of R&D and innovation activities, efficient management of these functions, should be based on the ability to identify the actual state, the knowledge of which would be the basis for designing and implementing structural and process changes covering both R&D and innovation activities (Heij et al., 2020, p. 277–294). Rational organisation of R&D activities and linking them with innovative activities is an important challenge for the management of modern business entities. However, in the context of daily practice, it may be doubtful whether managers feel the need to take such actions or improve them. Do they see a connection between the results of R&D and innovation activities and the technical and economic results of the company and its market position?

In general, there are significant differences in the perception of the essence of R&D&I activities presented in the literature and the daily activities of many business entities in this field. The European Commission’s report concludes that sound research and innovation policies can help build an inclusive, sustainable, competitive, and resilient Europe. R&D and innovation are a source of prosperity and a catalyst for social, economic, and environmental sustainability. Research and innovation are the basis for productivity growth and the competitiveness of the economy. They support the creation of new and better jobs and the development of knowledge-based sectors (Report, 2022a, p. 5).

According to statistical data presented by EUROSTAT (2020), the percentage of enterprises conducting internal R&D was at the level of 17.1% in the European Union (EU). In Poland, on the other hand, the percentage of such companies was only 8.8% (https://ec.europa.eu/ databrowser/). According to the European Innovation Scoreboard, Poland is in the group of so-called emerging innovators (the fourth group-the lowest classified). In 2022, it reached 60.5% of the EU average (Report, 2022b, p. 20). Recent surveys conducted among 846 respondents from 17 countries (including Poland) indicate a 10% decrease in internal resources in the R&D sphere compared to the previous year (Ayming Report, 2023, p. 7).

Examples of data indicate the need to undertake systemic improvement activities leading to the popularisation of R&D&I activities in business entities. An important instrument for such changes should be innovations in management with particular emphasis on social aspects (shaping innovative behaviour among employees), organisational and financial aspects, which are the basis for ensuring the smooth course of R&D&I activities.

Literature Review

The literature on R&D activities can be divided into two groups focussed on: (1) analysis of theoretical aspects of the essence of R&D activities and its role in the development of the organisation, and (2) identification of the actual involvement and achievements of the organisation in the field of R&D. In the publications of the first group, many issues related to this activity, its level, and its management are raised (Kisielnicki, 2018, p. 25–43). In practice, managers of organisations are not always aware of the role of R&D in the development of business entities and entire societies, therefore they do not show interest in this sphere of activity, or this interest is weak and not supported by scientific research (Jasiński, 2021, p. 22; Mate & Molero, 2021, p. 1–14). One of the reasons for this may be the uncertainty about the unambiguously positive impact of R&D activities on innovation and the results of the entire organisation (Heij et al., 2020, p. 277–294; Salisu & Abu Bakar, 2019, p. 56–61). In the literature on the subject of R&D activity, an important function is attributed to generating knowledge (Świadek, 2017, p. 75–84). According to Nonaka and Takeuchi, an organisation’s ability to effectively solve problems and create innovations depends on the ability to efficiently create knowledge (Nonaka & Takeuchi, 2000, p. 66), which is created within the framework of rationally managed R&D activities (Baruk, 2006, p. 55–90; Ferreira et al., 2023, p. 322–338; Suomala & Jokioinen, 2003, p. 213–227). The lack of organised R+D activities in business entities is one of the main barriers to the efficient creation and implementation of innovations (Das et al., 2018, p. 96–112; Kozioł-Nadolna, 2022, p. 3192–3201; Okoń-Horodyńska, 2004, p. 141–163). However, the knowledge generated within the organisation is not always enough to efficiently create innovations. It is therefore necessary to acquire external knowledge (Klessova et al., 2023, p. 1–23; Serrano-Bedia et al., 2010, p. 439–465; Śliwa & Patalas-Maliszewska, 2015, p. 267–280; Smiljic et al., 2023, p. 260–278). It is believed that economic entities conducting their own R&D activity are more likely to reach for external knowledge (Yamaguchi et al., 2021, p. 114–126). Organisations that decide to implement technological changes based on R&D should also introduce changes in the social system. Such changes include innovations in management (Heij et al., 2020, p. 277–294). It seems that these issues are a weakness of the managers of Polish enterprises.

The second group of publications on R&D activities are empirical research reports. An example of such a study is the report on R&D activities in Poland. Surveys show that 65% of companies from the industrial sector and 49% from the trade and service sector were involved in R&D projects (own work or outsourced) (KPMG w Polsce, 2013, p. 1–48). The relatively low level of R&D activity in Poland is evidenced by the results of research conducted by the Polish Agency for Enterprise Development, published in a report in 2013 (PARP, 2013, p. 1–173).

Although subsequent studies indicate an increase in some measures of R&D activity in Poland, their level does not match, for example, the average values in the EU (Deloitte Polska, 2016, p. 1–40; European Commission – Joint Research Centre, 2021, p. 1–32; IDEA Instytut, 2021, p. 1–174; Polski Instytut Ekonomiczny, 2019, p. 1–38; Raport Ayming, 2019, p. 1–44). This thesis is also confirmed by the publications of the author of this text (Baruk, 2016, p. 57–78; Baruk, 2019, p. 1–26; Baruk, 2020, p. 21–48; Baruk, 2022, p. 25–52). As a consequence, Poland ranks among the ’emerging innovators’. A systemic improvement in the level and universality of R&D work should therefore be sought, among others, in the change in the concept of management of the R&D&I sphere.

Research problem: the article attempts to solve the research problem contained in the question: what is the level and dynamics of R&D activity in Polish business entities, treated as an important source of knowledge in the processes of generating innovations? Answering the question formulated in this way required the adoption of the following measures of R&D activity: (1) the number of entities conducting R&D activities; (2) percentage share of entities conducting R&D in the total number of business entities in the industry; (3) employment in R&D activities and its structure; 4) expenditure on R&D and its structure.

Aim: The aim of the publication is to analyse the level and dynamics of the adopted measures of R&D activity, to assess the prevalence of R&D activity in Polish business entities, and to propose directions of improvement in this area.

Research methods: The following research methods were used to develop the publication: (1) cognitive-critical analysis of selected literature on the subject, (2) descriptive and comparative method, (3) statistical method, and (4) projection method.

The first three methods were used to interpret R&D activities, treated as an important source of creating knowledge necessary to effectively solve problems occurring in innovative processes, with particular emphasis on assessing the level and dynamics of adopted measures of R&D activity. The projection method was used to propose improvement changes in R&D&I business management processes and to develop a rational management model for R&D functions and creating innovations.

Results: R&D activity is one of the basic functions generating knowledge necessary for the efficient creation and implementation of innovations in all functional areas of business entities. A prerequisite for the rational development of this activity is efficient management and combining it with innovative activities into one common system. In practice, R&D activity is rather sporadic, intuitive, and deviating from theoretical assumptions. The high rank of R&D activities as a source of knowledge materialised in innovative processes largely depends on the ability of the management to innovatively manage this functional area. However, the level and dynamics of the analysed measures of R&D activity indicate the accidental, rather than innovative nature of this management.

Research limitations/implications: It seems that, for many business managers, the current technical and economic performance of the organisation is a priority in the decision-making process. On the other hand, new management concepts focussed on the future of the organisation, on the knowledge generated in R&D processes, systemically related to innovative activities, are not the strengths of the managerial staff. Systemic changes in the mentality and substantive preparation of managers are necessary so that R&D&I activities fulfil the role assigned to them in the development of business entities.

Practical implications: Awareness of the high importance of R&D&I activities in the improvement of social, organisational, technological, and economic development of the company, its understanding and striving for practical use, determining the improvement of the efficiency of management of R&D&I processes, increasing their impact on the economics of the organisation, and improving customer relations.

Social implications: Efficient management of R&D&I activities can inspire to generate/acquire knowledge, learn, share knowledge, and systematically materialise it in innovations that provide new values to both employees and customers who are more willing to engage in shaping the internal R&D&I environment.

Originality: The content of the publication contributes to the theory of R&D management and its systemic connection with innovative activities. The concept of basing the information and decision-making process on the results of the assessment of the existing state in the field of R&D activities using specific measures and linking this activity with innovative activity was proposed. The concept of a model approach to the management of R&D spheres and an innovative one, constituting a model for practical management activities, was also proposed.

Type of publication: Theoretical-Research

Research Results and Discussion: Entities involved in R&D activities

According to the statistics of the Central Statistical Office (GUS), entities involved in R&D activities include those organisations in which R&D activity is the main type of economic activity, which implement R&D projects in addition to other basic activities or finance R&D works performed by other entities (GUS, 2022c, p. 20). As can be seen from Table 1, in the analysed period of time, the number of entities involved in R&D activities showed a slight upward trend from 5,779 in 2018 to 7,370 in 2021. Year-on-year, these increases amounted to: 1.5% in 2019, 8.8% in 2020, and 15.5% in 2021, which is a positive phenomenon.

A positive phenomenon is the systematic, albeit small, increase in the number of organisations involved in R&D. Compared to 2018, this increase was 1.45 % in 2019, 10.42% in 2020, and 27.53% in 2021. The analysis of the percentage share of entities carrying out R&D works in the total number of business entities in the industry indicates a small percentage of such organisations that dealt with this form of activity. This share remained at around 2.5%. Only in 2021, it slightly exceeded 3%.

Taking into account the size of business entities conducting R&D activities, measured by the number of employees, it should be stated that medium-sized entities employing from 50 to 249 employees were the most common in this area. Next came small entities. Large entities did it the least. On average, in the period under review, the prevalence of such work was at the level of 28.85% in medium-sized entities with a slight downward trend over time. In large organisations, this percentage was 19.2% also with a downward trend. Slightly higher prevalence of R&D activities was characteristic of the smallest entities employing up to 9 employees. On average, in the analysed period, it was at the level of 24.3% with a slightly upward trend. Greater universality of R&D activities was demonstrated by small entities employing from 10 to 49 employees. On average, 27.7% of such organisations carried out some work in this area. This prevalence was rather stable over the time interval considered.

R&D staff

The efficiency of R&D activities depends on the employment of properly prepared personnel. This group includes persons: (1) directly involved in the implementation of R&D work (persons working in an organisation conducting R&D activities and external collaborators), (2) persons providing direct services for R&D activities (e.g. managers of R&D works, administrative service employees, office workers, and technicians).

In general, these staff can be divided into two groups (GUS, 2022c, p. 34–35): (a) internal staff-including people working in an organisation carrying out R&D work and directly contributing to the implementation of R&D activities (persons employed on the basis of an employment relationship or service relationship; employers and self-employed persons; agents working on the basis of agency contracts; homeworkers; persons who are members of agricultural cooperatives) and (b) external staff, that is, independent (self-employed) or dependent workers (salaried) participating in the R&D activities of a given organisation, but not being formally employed by the organisation carrying out R&D work.

As can be seen from Table 2, 266,283 people worked in the R&D sphere in 2018. Most of them (76.5%) were internal staff. In 2019, the number of such employees increased to 271,025 people. Compared to the previous year, an increase of 4,742 people was recorded, that is, by 1.8%. Here, too, internal staff dominated. It accounted for 79.3% of the total staff. In 2020, there was a further increase in the number of people employed in the R&D sphere by 4.6% compared to the previous year. These were mainly internal staff (79.8% of the total staff). The next year of analysis (2021) was characterised by a further increase in the total number of employees in the R&D sphere, which is a positive phenomenon. Compared to the previous year, this number increased by 22,132 people, that is, by 7.8%. In that year, internal staff accounted for 81.5% of the total number of employees in the R&D sphere.

In general, in the analysed period, the total number of R&D staff increased in subsequent years from 266,283 people in 2018 to 305,563 people in 2021. The number of internal staff also increased steadily from 203,588 people in 2018 to 249,014 people in 2021. The second group of R&D employees were external staff, whose number varied from year to year. Compared to the previous year, the number of external staff decreased by 10.4% in 2019. In 2020, it increased by 1.95% compared to the previous year. In 2021, there was a further decrease in the number of external staff by 1.3% compared to 2020. Compared to 2018, the number of external staff decreased by 9.8% in 2021.

Referring to the number of R&D staff to the size of business entities, it should be stated that this number was the lowest in micro-enterprises employing up to 9 employees. During the period under review, this number increased from 5,979 in 2018 to 9,101 in 2021 – an increase of 52.1%. The largest number of R&D staff was characterised by large organisations employing 250 or more employees. In 2018, 197,433 people involved in research and development worked in them. In 2021, this number increased to 222,998 people. Thus, there was an increase in employment by 12.9%.

Overall, in 2018, the share of R&D staff of micro-enterprises in the total number of R&D staff was 2.2%. In small enterprises, this ratio was at the level of 6.4%; 17.2% in medium-sized enterprises and 74.1% in large enterprises. In 2019, these shares amounted to: 2.5% in micro-enterprises, 6.2% in small enterprises, 16.9% in medium-sized enterprises, and 74.4% in large enterprises. In 2020, R&D staff of micro-enterprises accounted for 3.3% of all R&D personnel; 7.2% in small enterprises, 15.5% in medium-sized enterprises, and 73.9% in large enterprises. Similar relations took place in 2021. In the case of micro-enterprises, this share was 3.0%; 7.7% in small enterprises, 16.3% in medium-sized enterprises, and 73.0% in large enterprises.

It should be noted that, in all groups of analysed business entities conducting R&D activities, the majority were the internal staff. The smallest difference between the number of internal and external staff appeared in micro-enterprises. It amounted to 107 employees in 2018, 834 in 2019, and 1,125 in 2021. In 2020 alone, external staff outnumbered internal staff by 356. The small differences in the number of internal and external staff involved in R&D in micro-enterprises are understandable. They result from the limited financial capacity of these economic operators and the small number of employees in total. In other groups of companies, the predominance of internal staff increased as their size increased. Between 2018 and 2021, there was an average of 8.65 internal staff per 1,000 employees. On the other hand, the number of researchers in internal R&D staff per 1,000 employees was on average 6.35 people in the same period.

The development of the number of R&D staff can also be analysed across groups and executive sectors. As Table 3 shows, the largest number of R&D staff was employed in the higher education sector. In 2018, 141,877 employees worked there. However, in the next 2 years, this number decreased by 1,071 people in 2019 and by 3,881 people in 2020. In 2021, this sector employed 2,197 employees less than in the base year. However, compared to the previous year, there was a slight increase (by 1,684 people) in R&D staff.

The second largest R&D staff was occupied by the corporate sector. In 2018, 113,395 R&D staff were employed there, that is, 28,482 people less than in the higher education sector. In contrast to the higher education sector, the number of R&D staff in the enterprise sector increased in the following years of the analysis. For 2018, this number increased by: 7,815 people in 2019 (6.9%), 21,332 people in 2020 (18.8%), and 42,289 people in 2021 (37.3%). Compared to the higher education sector, the employment of R&D staff in the enterprise sector was lower in subsequent years of the analysis by: 28,482 people in 2018, 19,596 people in 2019, and 3,269 people in 2020. The exception was 2021, when the number of employees in the R&D sphere of the enterprise sector was higher by 16,004 people compared to the higher education sector.

In terms of the number of employed R&D personnel, the government ministry was in third place. In 2018, 8,080 people worked there. In the following year, this number decreased by 1,356 people, that is, by 16.8%. The year 2020 was characterised by an increase in the number of B&R staff to 8,813 people. Compared to the base year, this increase amounted to 9.1%, and 31.1%, compared to the previous year. However, in 2021, employment decreased by 280 people, that is, by 3.2%, compared to the previous year. The variable level of R&D staff in the government sector indicates the lack of a prospective research and development policy in this sector.

By far, the least R&D staff was employed in the sector of private nonprofit institutions. In this sector, the total number of R&D employees decreased in subsequent years of the analysis. In 2018, it amounted to 2,931 people. In 2019, it decreased by 646 people (22.0%), in 2020, by 1,036 people (35.3%), and in 2021, by 1,265 people (43.2%). A characteristic feature of this sector is the higher number of external staff compared to internal staff during the period considered. At the same time, the number of employees in the R&D sphere, both internal and external, decreased in subsequent years of the analysis. It can therefore be assumed that R&D activity in this sector was of marginal importance. In other sectors, the number of internal staff far exceeded the number of external staff.

Expenditures on R&D activities

R&D activity, like any other form of activity, requires adequate financial resources. The basic statistical indicator in this area is gross domestic expenditure on R&D activities (GERD). They constitute the amount of total internal expenditures on R&D activities carried out on the territory of a given country in the indicated reporting period. Internal expenditures on R&D activities include all current expenditures and gross capital expenditures on fixed assets related to R&D activities conducted in a statistical unit in a given reporting period, regardless of the source of financing (GUS, 2022c, p. 19). As shown in Table 4, in 2018, GERD amounted to PLN 25,647.8 million. Compared to 2018, in subsequent years of the analysis, these expenditures gradually increased: by 18.1% in 2019, by 26.3% in 2020, and by 46.9% in 2021. Year-on-year, these increases were 18.1% in 2019, 7.0% in 2020, and 16.3% in 2021, respectively. The share of these inputs in the gross domestic product (GDP) in the period considered was on average at the level of 1.34%. A positive phenomenon is a slight increase in this indicator in subsequent years of analysis from 1.21% in 2018 to 1.44% in 2021. In 2018, PLN 668 of these expenditures accounted for per capita. In subsequent years of analysis, this amount gradually increased and in 2021, reached the level of PLN 992.

The source of financing for R&D activities was also the rest of the world. In 2018, PLN 1,804.5 million came from this source. In subsequent years, this amount increased by 18.3% in 2019, by 28.9% in 2020, and by 70.6% in 2021, reaching PLN 3,079.1 million. The share of foreign funds in GERD was on average at the level of 7.35% in the analysed period. It reached its highest value in 2021–8.2%.

The funds of the EC were also used to finance R&D works. In 2018, it was PLN 1,035.7 million. In subsequent years, these amounts increased by 37.5% in 2019, by 65.3% in 2020, and by 130.9% in 2021. However, the share of these measures in gross domestic inputs averaged 5.1%. On a positive note, it has gradually increased from 4.0% in 2018 to 6.3% in 2021. The European Commission’s funds for R&D activities were used by a relatively small number of entities. In 2018, it was 891 organisations, which accounted for only 15.4% of entities conducting R&D work. In subsequent years of analysis, the number of entities using EU funds for R&D activities increased slightly (year-on-year) by 15.7% in 2019, by 9.0% in 2020, and by 21.8% in 2021. In the last year, 1,369 entities benefited from EU funds, which accounted for 18.6% of all organisations conducting R&D work.

The level of internal expenditures on R&D activities considered in the cross-section of individual executive sectors and size classes of enterprises is interesting. As can be seen from Table 5, in total, in the country, the amount of expenditure on R&D increased along with the increase in the size of enterprises. For example, in 2021, the share of expenditures incurred by micro-enterprises accounted for 2.5% of the total expenditure incurred on R&D. In the case of small entities, this share increased to 7.7%. An even higher value–15.7%–was achieved in medium-sized entities and the highest in large entities–74.1%. In each enterprise size class, the volume of expenditures incurred increased, with the exception of mediumsized enterprises, where in 2020, PLN 172.4 million less was allocated to R&D than in the previous year.

Turning to the sector analysis, it should be stated that the largest expenditure on R&D took place in the corporate sector. In 2018, they amounted to PLN 16,950.8 million, which accounted for 66.1% of total expenditures on R&D. In subsequent years of analysis, these shares amounted to: 62.8% in 2019, 62.8% in 2020, and 63.1% in 2021, respectively. Total expenditures in the enterprise sector increased in subsequent years of analysis. In 2019, they increased (year-on-year) by PLN 2,080.1 million, by PLN 1,328.2 million in 2020, and by PLN 3,410 million in 2021.

In the enterprise sector, micro-enterprises spent the least funds on R&D. In 2018, they accounted for only 2.6% of the total expenditures incurred in the entire enterprise sector. In 2019, this share was 3.1%, and 3.5% in 2020. Much larger amounts on R&D were spent by small entities. In 2018, the share of expenditures for this purpose accounted for 9.9% of all expenditures incurred in the enterprise sector. In 2019, it was 9.6% and, in 2020, it was 10.5%. In terms of absolute value, medium-sized companies allocated even higher funds to R&D. In 2018, they accounted for 20.7% of total expenditures. In the following year, this share was 21% and in 2020, it was 19.2%. The highest expenditure on R&D was incurred by large entities in the enterprise sector. In 2018, it was PLN 11,319.0 million, which accounted for 66.8% of the total expenditures of this sector. In the following year, this share was at a similar level of 66.4%, to increase to 66.8% in 2020. The development of the considered measure in 2021 was omitted due to the lack of numerical data presented by the GUS.

The higher education sector ranked second in terms of internal expenditure on R&D activities, analysed in the cross-section of executive sectors and size classes of enterprises. Its expenditure for this purpose accounted for 31.7% of total expenditures in 2018. In subsequent years, these shares amounted to 35.6% in 2019 and 34.9% in 2020. In this sector, it is impossible to fully analyse the development of expenditures on R&D in the cross-section of size classes of entities due to the lack of data. Data for 2018–2020 indicate that large enterprises allocated the largest amounts to R&D. In 2018, PLN 7199.2 million was spent for this purpose. This amount accounted for 88.6% of total expenditure in the higher education sector. In 2019, PLN 2407.8 million more was allocated to R&D than in the previous year. They accounted for 89.1% of total expenditure in this sector.

Even higher expenditures were incurred by large enterprises in the higher education sector in 2020. Compared to the previous year, they increased by PLN 804.1 million, which amounted to 91.9% of the total expenditures of the sector considered. Much less internal expenditure on R+D was borne by the government sector. In 2018, PLN 498.6 million was spent there. The share of this amount in total expenditures is only 1.9%. In the following year of analysis, PLN 114.4 million less was spent for this purpose than in the previous year. These funds accounted for only 1.3% of total expenditures. In 2020, PLN 639.1 million was allocated to R&D in the government sector, that is, PLN 254.9 million more than in the previous year. The share of these expenditures in total expenditures is less than 2% (1.97%). Compared to the previous year, R&D expenses in 2021 increased by PLN 131.2 million. They accounted for only 2% of total domestic expenditure. The available figures indicate that large companies have invested the most in R&D in this sector. In 2018, they accounted for 44.8% of total government sector expenditures. In 2019, this ratio was 63.2%, and in 2020, 51.2%.

The least active entities in the field of financing R&D activities were recorded by entities from the sector of private non-commercial institutions. In subsequent years of analysis, a total of PLN 76.7 million was spent in 2018, that is, 0.3% of total expenditure. In 2019, these expenses increased to PLN 90.3 million. They accounted for 0.3% of total expenditures. In the following year, these expenditures decreased by PLN 10.8 million and their share in total expenditures amounted to 0.2%. In 2021, R&D expenditures fell further to PLN 77.5 million. This amount represented 0.2% of the total expenditure for this purpose. In the cross-section of size classes of entities in this sector, micro-enterprises and small enterprises incurred greater expenditures, but without regular increases in the amounts spent.

The results of the analysis of internal expenditures on R&D activities considered according to types of costs and implementation sectors are interesting. The structure of internal expenditures on R&D consists of current (including personnel) and investment expenditures. Current expenditures include personnel expenditure on R&D personnel as well as other current expenditures related to R&D activities: services and items consumed within one year, annual fees, and rents. Personnel expenses include the remuneration of R&D staff and related costs or additional benefits. On the other hand, investment outlays are the annual gross amount paid for acquired fixed assets, repeatedly used in R&D activities for a period longer than one year (GUS, 2022c, p. 27).

As can be seen from Table 6, the total country was dominated by current expenditures over capital expenditures in individual years of the analysis. Current expenditures were characterised by their systematic growth (yearonyear): in 2019 by 22.4%, in 2020 by 9.3%, and in 2021 by 16.6%. The share of current expenditures in total expenditures was: 79.5% in 2018, 82.4% in 2019, 84.2% in 2020, and 84.4% in 2021. On the other hand, the share of capital expenditures in internal expenditures was much smaller, irregular, and amounted to: 20.5% in 2018, 17.6% in 2019, 15.8% in 2020, and 15.6% in 2021.

Current expenditures in R&D activities also dominated in individual executive sectors. In the enterprise sector, they increased in subsequent years of analysis, and their share in the total expenditures of this sector amounted to: 74.2% in 2018, 78.4% in 2019, 82.4% in 2020, and 84.3% in 2021. The higher education sector ranked second in terms of R&D expenditures. Most of them are current expenditures. In 2018, they accounted for 89.7% of total expenditures in this sector. In 2019, this share was 89.3%. In the next two years, current expenditures accounted for 87.4% and 84.9% of total expenditures, respectively.

Significantly, lower R&D expenditures were incurred in the government sector and in the sector of private non-profit institutions. In the first sector, the share of total expenditures in total domestic expenditures amounted to: 1.9% in 2018, 1.3% in 2019, and 2% each in 2020 and 2021. The private nonprofit institutions sector had even lower values of these shares: 0.3% in 2018, 0.3% in 2019, 0.2% in 2020, and 0.2% in 2021. Significantly less money was spent on investments in all sectors. They accounted for a small percentage of total expenditures.

The results of the structure of internal expenditures on R&D activities considered by types of activities and implementation sectors are interesting. As can be seen from Table 7, in total, development work absorbed the most funds in the country. The share of expenditures on these works in total expenditures was: 54.2% in 2018, 46.5% in 2019, 51.0% in 2020, and 53.4% in 2021. Year-on-year, these expenditures increased by: 1.21% in 2019, 17.5% in 2020, and 21.8% in 2021. In the second place in terms of the amount of expenditure on R&D was basic research. The share of these expenditures in total expenditures was: 32.5% in 2018, 40.1% in 2019, 33.2% in 2020, and 32.1% in 2021. In contrast to expenditure on development works, expenditure on basic research did not increase in subsequent years of analysis. In 2019, they increased by 45.5% compared to the previous year. In 2020, PLN 1,377.5 million less was spent on basic research than in the previous year. Therefore, there was a decrease in expenditures for this purpose by 11.3% compared to the previous year. In 2021, PLN 1,315.0 million more was spent on basic research than in 2020. Thus, there was an increase in expenditures by 12.2%.

The least popular was the funding of applied research. This is evidenced by the lowest amounts allocated for this purpose in individual years of the analysis. A positive feature of these expenditures was their systematic, albeit slight increase in subsequent years. They increased by 19.7% in 2019, 25.5% in 2020, and 6.9% in 2021.

Across the implementation sectors, the priorities in terms of the amount of expenditure on R&D were variable. The enterprise sector was dominated by expenditures on development works. The amount of these expenditures increased in subsequent years of the analysis (year-on-year): by PLN 134.7 million in 2019, by 17.3% in 2020, and by 18.1% in 2021. The share of expenditures on development works in the enterprise sector in total development expenditures in the country amounted to: 92.7% in 2018, 92.6% in 2019, 92.4% in 2020, and 89.6% in 2021.

In the enterprise sector, applied research was the second largest in terms of expenditure, with the exception of 2019, when more resources were spent on basic research. The difference amounted to PLN 662.9 million. A positive feature of expenditures on applied research was their successive but slight increase in subsequent years of analysis. Year-on-year, these amounts increased by: 21.9% in 2019, 22.3% in 2020, and 7.6% in 2021. In 2018, expenditures on applied research in the enterprise sector accounted for 64.5% of such expenditures incurred in total in the country. In subsequent years, these relations amounted to: 65.7% in 2019, 64.0% in 2020, and 64.4% in 2021.

In the enterprise sector, relatively, the smallest expenditure was spent on basic research. Most funds were spent in 2019, the least in 2020. The share of these expenditures in the total expenditures of the enterprise sector was at the level of: 11.0% in 2018, 17.5% in 2019, 8.9% in 2020, and 9.3% in 2021. Compared to the total expenditure on basic research in the country, expenditures for this purpose in the enterprise sector amounted to: 22.4% in 2018, 27.4% in 2019, 16.9% in 2020, and 18.3% in 2021.

In contrast to the business sector, basic research was the most financial resource in the higher education sector, followed by applied research. In third place were development works. A characteristic feature of all types of R&D activities in the higher education sector was a gradual increase in expenditures incurred in subsequent years of analysis. In relation to overall expenditure in the higher education sector, expenditure on basic research was 76.4% in 2018, 79.6% in 2019, 76.3% in 2020, and 73.2% in 2021. The amount of these expenditures in subsequent years of the analysis increased by: 38.3% in 2019, 0.6% in 2020, and 10.7% in 2021. Much lower investment in the higher education sector was spent on applied research.

Their share in the total expenditures of this sector was: 13.6% in 2018, 12.0% in 2019, 14.4% in 2020, and 13.7% in 2021. The least popular in the higher education sector was the development work, on which the least financial resources were spent during the period under review.

The share of R&D expenditures of the private non-profit sector in the total domestic expenditure was 0.3% in 2018, 0.3% in 2019, 0.2% in 2020, and 0.2% in 2021, respectively, with no clear emphasis on any type of R&D activity.

Conclusions

The analysis of empirical material indicates that, in the analysed period of time, a small percentage of business entities (less than 4%) conducted R&D activities. Medium-sized organisations were most often involved in R&D activities. However, their share in this work did not exceed 30% and had decreasing trends in subsequent years of analysis. There were between 8.1 internal staff per 1,000 employees in 2018 and 9.3 in 2021. By contrast, the share of researchers in internal R&D staff stood at 6.1 in 2018 and 2019, rising to 6.8 in 2021. A positive phenomenon was the increasing number of total R&D staff in subsequent years. These were mainly internal staff, constituting on average 79.3% of all R&D employees in the analysed period. While the number of internal staff increased in subsequent years, the number of external staff did not show an upward trend. In 2021, it accounted for 90.2% of the 2018 figure.

The number of R&D staff changed along with the change in the size of business entities measured by the number of employees. Micro-organisations had an increasing overall workforce until 2020 and a decline in 2021. The second feature was the slightly higher number of internal staff compared to the number of external staff. Along with the increase in the size of business entities, the number of B&R staff in total increased, which is a normal phenomenon. There was also a growing gap between the number of internal and external staff in favour of the former. On the other hand, there were no regular increases in the number of R&D employees in subsequent years of the analysis, especially with regard to external staff. In large organisations, the number of external R&D employees has been gradually decreasing, which suggests greater independence of such organisations in conducting R&D activities.

Across the overall implementation sectors, the higher education sector employed the largest number of R&D staff, with the exception of 2021, when the corporate sector took the lead. The sector of private non-profit institutions came last. In this sector, as the only one, the number of external staff exceeded the number of internal staff and decreased in subsequent years of the analysis, as did the total number of staff. Downward trends in the number of external R&D employees were also recorded in the higher education sector. In other sectors, there were irregularities in the development of this measure.

In general, the number of R&D employees increased with the size of business entities. This is a specific regularity resulting from the fact that the smallest organisations do not have the staff, organisational and financial conditions to separate R&D cells in their structures. Such entities are more likely to be assisted by external staff.

Another positive phenomenon is the increase in expenditure on R&D in the analysed period of time and their increasing amount per capita. There was also a slight increase in the share of gross domestic capital formation for R&D activities in GDP. However, this share was significantly lower than the EU average. In addition to national funds, the source of financing R&D activities were also funds from the European Commission (EC) and funds from the rest of the world. The share of foreign funds in domestic outlays was only 8.2% in 2021. The European Commission’s funds accounted for an even smaller share in national expenditures. In the most favourable 2021, this share was 6.3%. A small but increasing percentage of entities benefiting from EC funds was also beneficial. In 2021, it was 18.6%.

A characteristic feature of total internal expenditures on R&D was their increase in subsequent years of analysis. Similar trends occurred in operators considered by size classes, with the exception of medium-sized organisations. These outlays increased as the size of enterprises increased. In the cross-section of executive sectors, the largest internal expenditure on R&D was incurred in the corporate sector, and the lowest in the sector of private non-profit institutions.

In the structure of total internal expenditures on R&D, current expenditures dominated over capital expenditures. Similar relations occurred in all executive sectors without clear upward trends. The priority in this expenditure was the financing of development work, followed by basic research. In last place was applied research. The accents in R&D expenditures in individual sectors were slightly different. In the enterprise sector, the largest amount of funds was allocated to development work, followed by applied research (with the exception of 2019). At the end of the priorities were basic research. The exception was 2019, when expenditure on basic research exceeded expenditure on applied research. In the government sector, basic research has been the most resourced, as has the higher education sector. In the sector of private non-profit institutions, preferences in financing R&D activities were not as diverse as in other sectors.

In general, the level and dynamics of selected measures of R&D activity indicate that this activity was not a priority in the information and decisionmaking processes of managers. The actions taken were more focussed on overcoming current problems than on solving strategic issues. In many entities, the problem of systemic R&D work did not exist at all, as indicated by a small percentage of companies conducting R&D activities. The insufficient interest of management in systemic business development is also evidenced by the relatively low position of Poland compared to the average results in the EU.

The level, dynamics, and universality of R&D activity depend on many internal and external factors. One of the internal factors is the ability of the management to rationally, systemic, future-oriented management of the R&D&I sphere (Tidd & Bessant, 2013, p. 114–120). There are significant reserves in this area for improving management efficiency. It is necessary to give up accidental management, focussed on solving current problems and move to rational, systemic, future-oriented management of the enterprise, based on the knowledge and widespread use of modern management methods, especially management through innovation, innovation management, and knowledge management. The concept of such management is illustrated in Figure 1.

This concept emphasises the rational combination of the general strategy of development of the business entity with functional strategies. These strategies set the directions of internal R&D&I activities and cooperation with external organisations conducting external R&D. The consequence of such activity and cooperation should be the resources of knowledge necessary to efficiently identify and solve internal and market problems of an operational and strategic nature. The solution to problems results in streamlining radical innovations that efficiently meet current and future of own and market needs. The areas of activity of the business entity listed in the model should be subject to rational management. In process terms, it includes four basic management functions: setting goals and planning ways to achieve them; organising work in a structural and process sense; conduction; controlling (Griffin, 2007, p. 8). An indispensable condition for rational management according to the proposed concept is to change the mentality of the management staff and to realise the need to master and use modern management methods in information and decision-making processes (Bieniok, 2011; Błaszczyk, 2022; Zimniewicz, 2009).

Suggestions for further research

In the context of the issues discussed in this publication, it seems reasonable to undertake further empirical research aimed at verifying the correctness of the theoretical model of systemic management of R&D and innovative activities in the context of efficient implementation of the overall strategy of organisational development and the resulting functional strategies. The concept of such research should be guided by the following questions: 1. Do managers understand the importance of R&D activities and related innovation activities in the development of each business entity? 2. Do managers systematically follow the literature on the subject and get acquainted with new concepts of managing integrated R&D and innovation activities? 3. Do managers have the will to have these concepts empirically verified and why? 4. What advantages and disadvantages can result from the use of modern concepts of R&D and innovation management? It is also reasonable to answer the question: does the management of the organisation want, can, and can efficiently manage R&D&I activities?

References

1. Ayming Report. (2023). International innovation barometer 2023. Ayming Institute. p. 7.
https://www.aymingusa.com/insights/whitepapers/international-innovation-barometer-2023/ #download. Dostęp z dnia 05.04.2023 r.
2. Baruk, J. (2006). Zarządzanie wiedzą i innowacjami. Toruń: Wydawnictwo Adam Marszałek w Toruniu. pp. 55–90.
3. Baruk, J. (2016). Miejsce działalności badawczo-rozwojowej w polityce rozwojowej przedsiębiorstw. Marketing Instytucji Naukowych i Badawczych, 20(2), 57–78. https://doi.org/10.14611/minib.20.03.2016.04
4. Baruk, J. (2019). Finansowe aspekty polityki badawczej i rozwojowej w Unii Europejskiej. Marketing Instytucji Naukowych i Badawczych, 33(3), 1–26. https://doi.org/10.2478/minib-2019-0037
5. Baruk, J. (2020). The volume and dynamics of domestic expenditures on research and development in the European Union. Marketing of Scientific and Research Organizations, 38(4), 21–48. https://doi.org/10.2478/minib-2020-0025
6. Baruk, J. (2022). Research and development expenditures in the sector of polish enterprises as an instrument of research and development policy. Marketing of Scientific and Research Organizations, 43(1), 25–52. https://doi.org/10.2478/minib-2022-0002;
7. Bieniok, H. (2011). Metody sprawnego zarządzania. Warszawa: Placet.
8. Błaszczyk, W. (2022). Metody organizacji i zarządzania. Kształtowanie relacji organizacyjnych. Warszawa: Wydawnictwo Naukowe PWN.
9. Das, P., Verburg, R., Verbraeck, A., & Bonebakker, L. (2018). Barriers to innovation within large financial services firms. European Journal of Innovation Management, 21(1), 96–112. https://doi.org/10.1108/EJIM-03-2017-0028
10. Deloitte Polska. (2016). Badania i rozwój w przedsiębiorstwach 2016. Warszawa: Deloitte. pp. 1–40.
11. European Commission – Joint Research Centre. (2021). The 2020 EU Survey on Industrial R&D Investment Trends. Luxembourg: Publications Office of the European Union. pp. 1–32.
12. EUROSTAT. (2020). https://ec.europa.eu/eurostat/databrowser/view/INN_CIS12_INRD __custom_5561818/bookmark/table?lang=en&bookmarkId=588637df-57e9-4118-a02acd6270006c22.
Dostęp z dnia 27.03.2023 r.
13. Ferreira, J. J., Fernandes, C. I., Veiga, P. M., & Dooley, L. (2023). The effects of entrepreneurial ecosystems, knowledge management capabilities, and knowledge spillovers on international open innovation. R&D Management, 53(2), 322–338.
https://doi.org/10.1111/radm.12569.
14. Griffin, R. W. (2007). Podstawy zarządzania organizacjami. Warszawa: Wydawnictwo Naukowe PWN, s. 8.
15. GUS (2019). Działalność badawcza i rozwojowa w Polsce w 2018 r. Warszawa, Szczecin: GUS. tab. 1, s. 20, tab. 3, s. 22.
16. GUS (2020). Działalność badawcza i rozwojowa w Polsce w 2019 r. Warszawa, Szczecin: GUS. tab. 1, s. 20, tab. 3, s. 22.
17. GUS (2021). Działalność badawcza i rozwojowa w Polsce w 2020 r. Warszawa, Szczecin: GUS. tab. 3, s. 22.
18. GUS (2022a). Rocznik Statystyczny Rzeczypospolitej Polskiej 2022. Warszawa: GUS. tab.
6 (421), s. 516.
19. GUS (2022b). Rocznik Statystyczny Przemysłu 2021. Warszawa: GUS. tab. 1, s 33.
20. GUS (2022c). Działalność badawcza i rozwojowa w Polsce w 2021 r. Warszawa, Szczecin: GUS. tab. 1., s. 20; tab. 3, s. 22.
21. Heij, C. V., Volberda, H. W., Van den Bosch, F. A. J., & Hollen, R. M. A. (2020). How to leverage the impact of R&D on product innovation? The moderating effect of management innovation. R&D Management, 50(2), 277–294. https://doi.org/10.1111/ radm.12396
22. IDEA Instytut. (2021). Wpływ wsparcia działalności badawczo-rozwojowej w polityce spójności 2014–2020 na konkurencyjność i innowacyjność gospodarki – I etap: badanie w trakcie wdrażania. Warszawa: IDEA Instytut. pp. 1–174.
23. Jasiński, A. H. (2021). Współczesna scena innowacji. Warszawa: Poltext. p. 22.
24. Kisielnicki, J. (2018). Projekty badawczo-rozwojowe: charakterystyka i znaczenie. Studia i Prace. Kolegium Zarządzania i Finansów, (159), 25–43.
25. Klessova, S., Engell, S., & Thomas, C. (2023). The interplay between the contextual conditions and the advancement of the technological maturity in inter-organisational collaborative R&D projects: A qualitative study. R&D Management, 53(3), 1–23.
https://doi.org/10.1111/radm.12598
26. Kozioł-Nadolna, K. (2022). Innovation strategies used by companies in Poland during the pandemic. Procedia Computer Science, (207), 3192–3201. https://doi.org/ 10.1016/j.procs.2022.09.377
27. KPMG w Polsce. (2013). Działalność badawczo-rozwojowa w Polsce. Perspektywa 2020. Kpmg.pl, s. 1–48. https://assets.kpmg.com/content/dam/kpmg/pdf/2016/03/DzialalnoscBR-przedsiebiorstw-w-Polsce.pdf. Dostęp z dnia 14.04.2023r.
28. Mate, M., & Molero, J. (2021). The impact of public and private internal R&D investments on Spanish business performance during the period of crisis 2008–2012. International Journal of Advanced Research in Engineering & Management, 07(2), 1–14.
29. Nonaka, I., & Takeuchi, H. (2000). Kreowanie wiedzy w organizacji. Warszawa: Poltext. p. 66.
30. Okoń-Horodyńska, E. (2004). Działalność badawczo-rozwojowa i innowacje w Polsce a Strategia Lizbońska. Nauka i Szkolnictwo Wyższe, (1/23), 141–163.
31. PARP. (2013). Ocena zapotrzebowania przedsiębiorstw na wsparcie działalności badawczo-rozwojowej. Warszawa: PARP. pp. 1–173.
32. Polski Instytut Ekonomiczny. (2019). Polskie B+R. Dostępne narzędzia wsparcia i nowe możliwości. Warszawa: Polski Instytut Ekonomiczny. pp. 1–38.
33. Raport Ayming. (2019). Ulga B+R. Małymi krokami do większej innowacyjności. Warszawa: Ayming Polska. pp. 1–44
34. Report. (2022a). Science, Research and Innovation Performance of the EU 2022 – Building a sustainable future in uncertain Times. European Commission. DirectorateGeneral for Research and Innovation. B-1049 Brussels. p. 5.
35. Report. (2022b). European Innovation Scoreboard 2022. European Commission. Luxembourg: Publications Office of the European Union. 20. https://www.kpk.gov.pl/european-innovation-scoreboard-2022
36. Salisu, Y., & Abu Bakar, L. J. (2019). Technological, capability, innovativeness and the performance of manufacturing small and medium enterprises (SMEs) in developing economies of Africa. IOSR Journal of Business and Management, 21(1), 56–61.
https://doi.org/10.9790/487X-2101015661
37. Serrano-Bedia, A.M., Lopez-Fernandez, M.C., & Garcia-Piqueres, G. (2010). Decision of institutional cooperation on R&D. Determinants and sectoral differences. European Journal of Innovation Management, 13(4), 439–465. https://doi.org/10.1108/ 14601061011086285
38. Śliwa, M., & Patalas-Maliszewska, J. (2015). Model doboru jednostki badawczorozwojowej dla przedsiębiorstwa opartego na wiedzy. Modern Management Review, XX(3), 267–280. https://doi.org/10.7862/rz.2015.mmr.49
39. Smiljic, S., Aas, T. H., & Mention, A.L. (2023). To join or not to join? Insights from coopetitive RD&I Project. R&D Management, 53(2), 260–278. https://doi.org/ 10.1111/radm.12560
40. Suomala, P., & Jokioinen, I. (2003). The patterns of success in product development: A case study. European Journal of Innovation Management, 6(4), 213–227. https://doi.org/ 10.1108/14601060310500931
41. Świadek, A. (2017). Krajowy system innowacji w Polsce. Warszawa: CEDEWU. pp. 75–84.
42. Tidd, J., & Bessant, J. (2013). Zarządzanie innowacjami. Warszawa: Oficyna a Wolters Kluwer business. pp. 114–120.
43. Yamaguchi, S., Nitta, R., Hara, Y., & Shimizu, H. (2021). Who explorer further?
Evidence on R&D outsourcing from the survey of research and development. R&D Management, 51(1), 114–126.
44. Zimniewicz, K. (2009). Współczesne koncepcje i metody zarządzania. Warszawa: Polskie Wydawnictwo Ekonomiczne.

The strategic goal of every enterprise, both industrial and service, is to systematically introduce new products and services to the market or improve already manufactured products. Achieving such a goal may lead to the more rapid meeting of changing customer needs compared to competitors and the shaping of new needs in a competitive way, conducive to acquiring the economic value necessary for the further functioning and development of business entities (Ri, Wang & Zhan 2018, p. 38; Dieter & Schmitt, 2018, p. 64). One of the basic conditions for achieving this goal is the ability of management to acquire, deploy, update and use the resources necessary for the efficient design of new products that would arouse the interest of buyers (Areri, Kipchumba & Kamau, 2020, p. 48). We can talk about material, energy, financial, human resources (employees), information, knowledge, and so on. Rational use of such resources requires their proper organization in a static and dynamic sense, and efficient resource management, resulting in the design of new products or services arising in the pre-production sphere (see Figure 1).

New or improved designs for products/services are transferred to the production sphere, where they become materialized in manufacturing (operational) processes. The resulting products (innovations), through the post-production sphere, reach the market to provide customers with the expected value. In return, the company acquires economic value, information and knowledge from its customers (Peng, Lawrence & Koo, 2009, pp. 146–147). Management according to such a model is focused on the systemic link between research and development (R&D) activities and marketing research (Szopik-Depczyńska, 2018).

As can be seen from the model above, the management process covers all spheres that make up the company’s activity (Arandah, 2021, p. 47). One of these is the pre-production sphere, which fulfills the very important function of creating knowledge and processing it into specific projects for products or services (innovations) satisfying the current and future needs of real and potential customers (Emilyokwemba, 2018, pp. 16, 20; Kelemu, 2019, p. 35). Therefore, the systematic acquisition of information and knowledge from customers, combined with information and internal knowledge, can facilitate the creation of successful projects on the one hand, and on the other shape an environment conducive to interaction between customers and the company, resulting in the co-creation of the expected value in accordance with the principle: new knowledge enables the creation of new value (Baruk, 2017, pp. 20–28; Jasiński, 2020, p. 5).

The key elements of the co-creation process are as follows (Prahalad & Ramaswamy, 2005, pp. 31–39):

1) Dialog leading to loyal cooperation between customers and the company and its maintenance. Dialog inspires the sharing of information and knowledge, and shapes a new quality of mutual understanding and trust between enterprises and customers, as well as facilitating the introduction of the personal views of customers on the essence of value into the process of co-creation of value. Consequently, it leads to customer satisfaction, which is a key indicator of the level of customer service (Shete, 2021, p. 34);

2) Access to data, information, experiences, and services creates new opportunities for cooperation in new or existing markets, gives grounds to change the existing belief that only ownership allows customers to use value (offering customers access to new forms of services);

3) Risk assessment to ensure that customers have full access to information on the risks and benefits of engaging in the value co-creation process, facilitating trade-offs between risks and benefits. If customers are to be cocreators of value, they should be provided with more information about the potential dangers that may arise in the products and services they design, which requires greater customer responsibility for these risks;

4) Transparency resulting from the increasing availability of information about the products, indicators and operating systems of enterprises. Transparency of activities and market transactions promotes the growth of customer involvement in the co-creation of value, enables the establishment of a dialog with customers leading to the initiation or deepening of cooperation and leads to the formation of strong trust between customers and enterprises.

The role of managers of enterprises focused on co-creating value as part of R&D activities is to rationally shape the aforementioned components of value co-creation and give them the character of system solutions (Kolomiiets, Krzyżanowska & Mazurek, 2018, p. 31). This is a difficult task, requiring mental changes, new management knowledge, social innovation, the ability to shape rational policies (research and development, innovative, production, marketing, social), strategic thinking, the abandonment of traditional thinking from the perspective of the enterprise in favor of strategic, innovative thinking from the perspective of customers and new incentive instruments, etc. (Prahalad & Ramaswamy, 2005, pp. 45–48; Janasz & Kozioł, 2007, p. 81). The introduction of the concept of cocreation of value at the research and development (R&D) stage requires management to innovate in management, which helps to alleviate the tensions between the company and customers, manifested at the points of interaction (Heij, Volberda, Van den Bosch & Hollen, 2020, p. 278; Barbieri & Alvares, 2016, pp. 122–124).

The development of R&D activities in enterprises requires specific financial outlays, which are an instrument of R&D and innovation policy. Meanwhile, the lack or shortage of financial resources is one of the basic barriers to the dynamic development of R&D and innovation activities in enterprises, which translates into limiting or omitting this issue in decision-making processes (Matejun, 2015, p. 40; Jasiński, 2005, p. 39; Poznańska, 2017, p. 199; IDEA Institute, 2021, p. 112).

This article is organized based on the following concept: the implementation of each function in the enterprise requires incurring certain expenditures. One of such functions is the function of R&D activity. It is a source of knowledge materialized in innovation. Decisions on the amount of expenditure on R&D are made by the company’s management. These decisions result from a specific R&D policy, which is why the level, dynamics and structure of actual expenditures incurred reflect the quality of R&D policy.

The following measures were used to analyse the level, dynamics and structure of R&D expenditures: 1) the amount of gross domestic expenditure on R&D (GERD); 2) the share of gross domestic expenditure on R&D in gross domestic product (GDP); 3) the number of entities conducting R&D activities; 4) the number of research employees per 1,000 employees; 5) the sum of internal expenditure on R&D activities in total, by executive sectors, by number of employees in enterprises, by ownership sector and by type of R&D activity.

Research problem: The essence of the research problem is therefore contained in the following questions: 1) what is the level of financing of R&D activities in Poland and in Polish enterprises? 2) what are the dynamics of R&D expenditures? 3) what is the structure of these expenditures in terms of the type of research, the size of enterprises and the ownership sector?

Undoubtedly, these are basic and current issues in academic considerations on the identification of enterprise policy in the field of finansing R&D activities. The results may be the basis for changing this policy and directing it towards increasing the rationality of R&D management, treated as sources of knowledge for innovative activities. The importance of this research problem is particularly great in the light of the relatively low percentage of enterprises conducting R&D activities. According to research conducted in 2016 by Kantar Millward Brown, only 40% of Polish enterprises conducted R&D activities. This percentage rose to 55% in 2018 (Ayming Report, 2018, p. 16). In a similar study from October 2016, it was found that 60% of the surveyed companies in Poland did not conduct R&D activities. R&D activity was declared by only 16% of small companies, 50% of medium-sized companies and 64% of large companies (Ayming Report 2016, pp. 5, 17).

Purpose: The purpose of the publication is to identify the level, dynamics and structure of expenditures on R&D activities in Poland and in Polish enterprises. These parameters define the nature of the R&D policy pursued by managerial staff. At the same time, they form the basis for proposing improvements (in the form of model solutions) in this area.

Research methods: The following research methods were used to develop this paper: a cognitive-critical analysis of the literature to identify the research problem; the descriptive and comparative method for the presentation of the problem; the statistical method for calculating percentages of the level, dynamics and structure of R&D expenditures; and the projection method for proposing model solutions.

Results: The level of measures of R&D activity analyzed indicates that the enterprise sector played a leading role in the sectoral system. The priority for this sector was development work in all the cross-sections considered. The lowest expenditures were spent on basic research. Compared to the average results in the European Union, Poland and Polish enterprises achieved lower indicators in terms of finansing R&D activities. The relatively low level and diversified nature of the measures in the period under investigation indicates relatively low R&D activity among enterprises. One of the reasons for this is the random and ad hoc nature of R&D policy, which is aimed more at solving current problems.

Practical implications: Becoming aware of the real results in terms of R&D expenditure may serve as the basis for rationalising R&D policy and giving it a strategic dimension. The use of the proposed model solutions in this policy may lead to an increase in this rationality, and thus an increase in the integration of R&D work with innovative activities and the market. The consequence may be an improvement in the competitive position of enterprises, their economics and customer relations.

Social implications: Rationalization and strategic orientation of R&D management is conducive to the socialization of R&D processes, and the inclusion of the company’s own employees, institutional and individual clients in this activity. Because of changes in management and R&D policy, healthy relations between the company and individuals and institutions in the environment may be formed, as well as the willingness of employees to learn and share knowledge.

Originality: This article makes an empirical contribution in terms of the level, dynamics and structure of R&D expenditures in Poland and in the enterprise sector. It also makes a conceptual contribution in the form of organizing knowledge on the essence of R&D activity, R&D policy and model solutions facilitating the management of the R&D sphere and its integration with production and post-production activities. Scope of the study: The time range of the research covers the years 2015–2019 (or 2017–2019 in the case of the analysis of the enterprise sector). The scope concerns the financial aspects of R&D activity on a national scale and in the Polish enterprise sector. The scope of the survey covers the country and the enterprise sector that complete the annual PNT reports on R&D activities and send them to the Central Statistical Office (GUS), where aggregate results are prepared, edited in publications entitled „Science and technology in the years of…” and „Research and development activities in Poland in the years…”. It is the data contained in these studies that constitute the basic source of analysis of R&D expenditures.

The essence of R&D activity and R&D policy

R&D activity has become an integral part of modern economies, treated as a source of knowledge necessary for the dynamic and systemic pursuit of innovative activities, conditioning the increase in the competitiveness of enterprises and their ability to co-create value for customers (Jasiński, A.H. 2020, p. 6; Mate & Molero, 2021, p. 2; Kelemu, 2019, p. 36). R&D activities consist of creative work carried out in a methodical manner to acquire new knowledge resources — especially knowledge about humanity, culture and society — as well as to search for new applications for knowledge hitherto gained. This activity is aimed at new discoveries based on original concepts and their interpretations or hypotheses. Its aim is to achieve results that would be freely transferable and tradeable on the market (GUS, 2018b, p. 47; OECD, 2015, p. 44). R&D activity may be characterized by: innovativeness, creativity, unpredictability, methodicality, possibility of reproduction or transfer (GUS, 2018b, p. 47; OECD, 2015, p. 45).

R&D activities include the following three sets of activities (Witness, 2021, p. 89):

1) basic research, which is experimental or theoretical work carried out with a view to acquiring new knowledge about specific phenomena governing nature and specific facts without indicating specific applications;

2) applied research, also undertaken to acquire new knowledge but focused on a specific practical goal or intention. The results of such research are usually trial models of products, processes or methods;

3) development work, which is is methodically carried out activity based on knowledge obtained as a result of basic and applied research, practical experience and generating additional knowledge aimed at the production of new products or processes, or at improving already manufactured products and processes, including the preparation of prototypes or pilot installations. Usually, development work includes construction, structural, design-technological and experimental work (Baruk, 2014, p. 57).

R&D activities are carried out by organizations and cooperating natural persons whose work is creative and is undertaken in order to increase knowledge resources, as well as to create new possibilities for its application. In particular, the contractors of R&D work are statistical units established to conduct R&D activities in the following sectors (GUS, 2018b, p422; OECD, 2015, p. 98): enterprises, government, higher education and private non-commercial institutions. Innovation is a manifestation of such successful work. It should be realized that the development of innovations that can have a radical impact on the development of a company, increase its competitiveness, and increase the ability to originally meet the current and future needs of individual customers requires the generation of new knowledge. It is therefore necessary to conduct a rational R&D policy including: 1) organizing their own sphere of R&D, 2) systemic use of external knowledge arising in scientific and research organizations, in other enterprises, 3) acquiring knowledge and experience of individual customers or joint use of internal and external knowledge acquired as part of systemic cooperation or purchasing, 4) systemic shaping of the culture of learning and sharing knowledge, 5) creating an environment of experience, creating structural and process conditions for generating knowledge and materializing it in innovations, etc. (see Figure 2).

Since enterprises operate and develop in a dynamic environment, it becomes a natural necessity to systematically renew the resources of internal and external knowledge, multiply it, store it, as well as sharing silent knowledge and transforming it into knowledge commonly available to enterprises (Swaty & Kumar, 2021, p. 56; Probst, Raub & Romhardt, 2004, p. 143). The role of management is therefore to create a climate and culture conducive to creative behavior (social innovations), to organize teamwork integrating all categories of knowledge, experience, thinking styles, to stimulate knowledge employees to reveal it, share it with other people, etc. (Suvaci, 2018, p. 4). We should be aware that innovative activity is based on various categories of knowledge: technological, organizational, market, commercial, economic, managerial, social and methodological knowledge.

Skilful management of knowledge, i.e., its creation, acquisition, storage, processing, distribution, transformation (from hidden knowledge to available knowledge) and use, is becoming increasingly more important in today’s conditions of enterprise functioning than the mere transformation of raw materials into finished products in accordance with known manufacturing technologies and supplying customers with them. Particular attention should be paid to the creation of the company competences, i.e., those areas of knowledge that are (Baruk, 2007, p. 140):

1) key competences, determining the identity of the company, dynamizing its market position. An example of this type of competence is R&D. Key competences can be shaped through the implementation of social innovations, rational HR policy, employment, training, learning, knowledge management, rationally organized R&D and innovation activities and cooperation policy with scientific and research organizations,

2) unique competences, constituting the basis for the company to achieve an advantage over competitors in terms of originality, modernity, quality and compliance with customer expectations of all technical, technological, organizational and managerial solutions. This requires activity by management staff in the field of rational management of R&D work, hiring researchers and specialists from various scientific disciplines, providing them with significant freedom to choose research directions, unlimited contact with customers, innovative experience environment, etc.

In the processes of systemic creation of knowledge and its materialization in innovation, it is necessary to convince managers that: 1) the diffusion of knowledge through the innovation system is a key element in the effectiveness of any innovation process, which is why it should be rationally managed, 2) systematic expansion of the knowledge base in enterprises through organized R&D activities, cooperation with external entities and individual customers or acquisition of new knowledge through purchases, becoming a necessity today, 3) the most important role in R&D activities and innovation processes is played by people of knowledge, which is why they should be rationally managed, conditions for learning should be created, employees should be encouraged to share knowledge, as part of a systemic R&D and innovation policy (Janasz & Kozioł, 2007, pp. 78–79).

The term R&D policy and innovative enterprise should be understood as a specific set of managerial, economic, social, organizational, financial and technical decisions leading to the integration of science — technology — production — distribution, focused on the systemic acquisition of external and internal knowledge, materialized in innovations providing customers with the expected value faster than competitors. In other words, R&D policy and innovation policy are a series of rational decisions and actions resulting in the organization of efficient structures (in a static and dynamic sense), stimulating research resulting in the generation of knowledge, indicating ways to materialize it in product and business process innovations, solving an enterprises technological and financial problems, as well as satisfying individual and the institutional needs of customers (Baruk, 2020, p. 7). These policies include the creation of R&D and innovation objectives, as well as the selection of means and methods to achieve these goals (Janasz & Kozioł, 2007, p. 96). Primarily, this is about the economic, social, organizational, human resources, and financial solutions necessary for the efficient course of research work (acquiring knowledge, indicating the possibilities of its application) and development, as well as innovation creation processes.

Undoubtedly, rational answers to the following questions can facilitate the creation of an R&D policy for an enterprise: 1) what problems (internal, market) the company may encounter in the short, medium and long terms? 2) what innovations can be conducive to solving these problems? 3) what knowledge is necessary or will be required to generate innovation and solve these problems? 4) from what sources (internal, external, mixed) should this knowledge be acquired? 5) what material, financial and human resources will determine the smooth course of R&D and innovation processes? 6) what role can and should individual customers play in these processes? 7) what organizational (structural and process), technical and social changes should be introduced to ensure high efficiency of R&D and innovative processes? In general, R&D and innovation policies should be based on the following mechanism (see Figure 3):

When above considerations are compared to economic practice, two questions arise: 1) what are the level and dynamics of expenditures on R&D activity in Poland, treated as an instrument of R&D policy? 2) what are the level and dynamics of expenditures on R&D activity in the Polish enterprise sector, treated as an instrument of R&D policy?

Possible answers to these questions are presented in the following sections of the article.

Expenditures on R&D activities in Poland in 2015–2019

R&D activities require specific financial outlays. One of the basic measures of this activity is gross domestic inputs (GERD index). They constitute the amount of total internal expenditures on R&D activities carried out on the territory of a given country in the indicated reporting period (GUS, 2020a:19). The level of these expenditures in the years 2015–2019 is presented in Table 1. In 2015, they amounted to PLN 18.1 billion. In the following year, a decrease in this metric by 0.7% was recorded. In the following years, these expenditures increased compared to 2015 by 13.9% in 2017, by 42.0% in 2018 and by 67.7% in 2019, respectively, which should be considered a positive phenomenon, even after accounting for the inflation rate.

The ratio of gross domestic inputs to gross domestic product (GDP) was also used to analyse the dynamics of R&D activity. In the period analyzed, this indicator was characterized by a slight increase, except for 2016, when this ratio was 0.96%. In subsequent years, this rate exceeded 1% and in 2019 it amounted to 1.32%.

The universality of R&D activity may be measured by the number of entities that engage in it. In 2015, there were 4,427 such entities. Compared to 2015, their number increased by 444 in 2016, by 675 in 2017, by 1,352 in 2017 and by 1,436 in 2019. As in any job, people with appropriate professional training must also be involved in R&D activities. In this activity, one of the most important groups of employees are scientific and research workers. In the analyzed period, there was an average of from 5.1 research workers per 1,000 employees in 2015 up to 6.1 in 2019. Year on year, this measure slightly but successively increased by 0.5 in 2016 and in 2017, by 0.1 in 2018 and 2019.

Involvement in R&D activities can also be assessed on the basis of the internal expenditures, defined as all current expenditures and gross capital expenditures on fixed assets related to R&D activities, carried out in the entity (GUS, 2020a, p. 19). In total, these expenditures increased from PLN 18.1 billion in 2015 to PLN 30.3 billion in 2019. The exception was 2016, when compared to 2015, the sum of these expenditures decreased by PLN 118 million.

The basic classification used in the analysis of data on R&D activities is the classification of institutional sectors developed by the OECD, including: the corporate sector, the government sector, the higher education sector, the sector of private non-commercial institutions and abroad. According to the classification of executive sectors, entities conducting research and development activities are divided into four categories: the enterprise sector, the government sector, the higher education sector and the sector of private non-commercial institutions (GUS, 2020a , pp. 25–26).

As shown in Table 1, during the period considered, the largest expenditure on R&D was incurred by companies. In 2015, they amounted to PLN 8.4 billion, which accounted for 46.6% of gross domestic expenditures on R&D activities. Year on year, expenditures on R&D in enterprises increased by PLN 3.4 billion in 2016, by PLN 1.5 billion in 2017, by PLN 3.7 billion in 2018 and by PLN 2.1 billion in 2019. In the last year, enterprises spent PLN 19 billion on R&D activities. This amount represented 62.8% of gross domestic expenditure for this purpose. In other years, this indicator was: 65.7% in 2016, 64.5% in 2017, and 66.1% in 2018. In other executive sectors, these shares were: 1) in the government sector: 24.4% in 2015, 2.5% in 2016, 2.3% in 2017, 1.9% in 2018, and 1.3% in 2019; 2) in the higher education sector: 28.9% in 2015, 31.4% in 2016, 32.9% in 2017, 31.7% in 2018 and 35.6% in 2019; 3) in the sector of private non-profit institutions: 0.2% in 2015, 0.4% in 2016, 0.3% in 2017, 0.3% in 2018 and 0.3% in 2019.

The level of the measures of R&D activity above in individual executive sectors indicates the leading role of the enterprise sector. This sector was characterized by the highest internal expenditures on R&D, growing in successive years, and the largest share of these expenditures in gross domestic expenditures. This was followed by the ministries of higher education, government and private non-profit institutions. The latter sector was characterized by a marginal involvement in financing R&D activities.

Expenditures on R&D activities in the sector of Polish enterprises in 2017–2019

Since the enterprise sector was characterized by the greatest involvement in R&D activities, it is worth analyzing the development of internal expenditures in this sector depending on the size of enterprises and their sectoral affiliation. The development of this indicator in 2017–2019 is presented in Table 2.

The analysis of internal expenditures incurred on R&D indicates an increasing absolute value in all cross-sections, i.e., in total in the country, in total in enterprises and in individual categories of enterprises. Compared to 2017, in 2019 the total amount of these expenditures increased by PLN 9,706.3 million, i.e., by 47.2%. In the corporate sector, this increase was 30.3%. In the case of micro enterprises, expenditures increased by 44.9%, in small enterprises by 45.2%, in medium-sized enterprises by 34.3%, in large enterprises by 30.4%, and in great enterprises — by 52.1%. In private enterprises, an increase in expenditures by 47.5% was recorded, while in public enterprises by 22.7%.

Based on the sum of internal expenditures on R&D activities in 2017–2019, it can be concluded that R&D policy in Poland was first focused on development work, then on basic research and finally on applied research. This conclusion is confirmed not only by the absolute values of expenditures allocated to individual types of R&D activities, but also by the percentage shares of these expenditures in total expenditures. In 2017, these shares were 29% for basic research, 17.6% for applied research and 53.4% for development. In 2018, the ratios were 32.5%, 13.2% and 54.2%, respectively. Finally, in 2019, the share of expenditure on basic research in total expenditures accounted for 40.1%, for applied research — 13.4%, and for development work — 46.5%.

In the corporate sector, the priority for R&D policy was development work, which absorbed the most cash in the period analyzed. In 2017, they accounted for 76.4% of total expenditures. In the case of applied research, this share was 18.9%, and in the case of basic research — 4.6%. In 2018, these relations were at the level of: 11.0% in the case of basic research, 12.9% in the case of applied research, and 76.1% in the case of development work. In the next year of the analysis (2019), expenditures on basic research accounted for 17.5% of total expenditures, in the case of applied research — 14.0%, and 68.5% — in the case of development work. The level of these measures indicates that the priority of R&D policy in enterprises in general was development work, followed by applied research and finally basic research, with the exception of 2019, when the share of expenditure on basic research was slightly higher (by 3.5 percentage points) than on applied research.

Taking into account the size of enterprises expressed in the number of employees, it should be stated that the priority of R&D policy in the period under investigation was development work in all groups of company sizes. This is evidenced by the shares of expenditures on individual types of R&D activities in total expenditures. In the case of micro-enterprises, these shares amounted to: in 2017 for basic research, 8.8%, for applied research 27.8%, and for development work 63.3%. In 2018, these relations were as follows: 21.7% for basic research, 17.4% for applied research and 60.9% for development work. Finally, in 2019, these measures took the following values: 30.3% for basic research, 20.6% for applied research, and 49.1% for development work.

In small enterprises, R&D policy was also focused mainly on finansing development work. In 2017, the share of expenditure on development work in total expenditures was 64.1%, in the case of applied research — 25.6%, and in the case of basic research — 9.8%. In 2018, these indicators reached the following values: 67.4% for development work, 16.6% for applied research and 16.0% for basic research. In 2019, the share of expenditures on development works in total expenditures was 58.8%, in the case of applied research — 17.3%, and in the case of basic research — 23.8%.

Similar phenomena occurred in medium-sized enterprises, where R&D policy focused mainly on development work. This is evidenced by the indicators of the share of expenditures of individual types of research in total expenditures. In 2017, they amounted to: 67.5% for development work, 24.4% for applied research and 8.1% for basic research. The situation was similar in 2018: 71.4% of total expenditure was allocated to development, 16.7% to applied research and 11.8% to basic research. In 2019, these relations were at the level of: 63.0% for development work, 20.7% for basic research and 16.3% for applied research.

A similar structure of expenditure characterized large enterprises, in which in 2017 70.5% of total expenditures were allocated to financing development work, 24.0% to applied research and only 5.5% to basic research. In 2018, the percentages of these expenses were at the level of 71.7% for development work, 18.2% for applied research and 10.0% for basic research. In 2019, the structure of expenditure was similar. The largest amount of funding was allocated to development work — 65.3% of total expenditures, 17.1% to applied research and 17.5% to basic research.

The R&D policy of large enterprises was also dominated by development work. In 2017, 86.0% of total expenditure was allocated to it, with only 12.5% for applied research and 1.4% for basic research. A similar distribution of these indicators took place in 2018, when development work was mainly financed. It accounted for 82.1% of total expenditure, for applied research only 8.5% and for basic research — 9.4% of all funds. In 2019, a similar structure of expenditure was recorded. 74.8% of total expenditures on development work, 11.0% on applied research and 14.1% on basic research.

In general, the R&D policy of the enterprise sector was dominated by development work, to a much lesser extent was it decided to finance basic and applied research. There were years when slightly more money was spent on basic research than on applied research, e.g., 2019 (enterprises in general), 2018 and 2019 in micro-enterprises, 2019 in small, medium, large and great companies, and 2018 in large companies.

The last cross-section of the analysis is the distribution of internal expenditures on R&D in enterprises depending on the sector of their ownership. In both sectors, total expenditures increased in individual years of the analysis. The absolute amount was higher in the private sector by PLN 8.9 billion in 2017, i.e., by 80.2%; by PLN 11.9 billion in 2018, i.e., by 82.6% and by PLN 13.6 billion in 2019, i.e., by 83.5%. In each of these sectors, R&D policy was mainly focused on financing development work. This conclusion is confirmed by the shares of expenditures on individual types of activities in total expenditures. In 2017, the private sector accounted for 81.4% of total investment, for applied research for 15.3% and for basic research for 3.3%. In the following year, the level of the metric was: 79.2% for development work; 9.9% for applied research and 10.8% for basic research. In 2019, it was at the level of: 71.2% for development work, 11.3% for applied research and 17.5% for basic research.

In 2017, public sector enterprises accounted for 51.0% of total expenditure on development, 37.4% on applied research and 11.6% on basic research. In 2018, funds for development work accounted for 57.8% of total expenditure, 30.2% for applied research and 11.9% for basic research. In the last year of the period investigated, i.e., in 2019, 52.0% of the total financial resources were allocated to development work, while 17.4% and 30.6% of the expenditures incurred were allocated to basic and applied research respectively.

Summary

The assessment of the position of the Polish and the business sector in terms of its commitment to R&D finansing will be more objective if the results are compared with those obtained in the European Union (EU). Compared to the average values achieved in the EU, the share of domestic expenditures on R&D in the gross domestic product in Poland was lower by 0.82 p.p. in 2019, 0.9 p.p. in 2018, 1.05 p.p. in 2017, 1.08 p.p. in 2016 and 1.04 p.p. in 2015, in the years 2015–2019, the average value of this indicator in Poland was lower than its average value in the EU by 0.98 p.p.

It should be emphasized that in the enterprise sector, the share of internal expenditures on research and development in gross domestic expenditure on R&D activities in 2019 amounted to 62.8% (with a 66.6% share in the EU) and was much higher than such shares in other sectors: government by 61.5 percentage points, higher education by 27.2 percentage points. and private non-commercial institutions by 62.5 percentage points.

The ratio of internal expenditures on R&D activities to GDP, defined as the intensity of R&D work, in 2019 amounted to 1.32% and was lower than the value of this indicator for the EU by 0.82 p.p., which placed Poland 16th among member states. In 2019, the index increased by 0.11 p.p. compared to 2018 and by 0.32 p.p. compared to 2015 (GUS, 2021, p. 25). Thus, we can talk about the relative backwardness of the Polish and the corporate sector in relation to the EU in terms of the amount of expenditures on R&D and their share in the gross domestic product.

A valuable source of information about R&D policy is indicators of the share of expenditures on individual types of R&D activities. It turns out that in 2017–2019 this policy was focused mainly on finansing development work, to a lesser extent on finansing basic research and to the smallest extent — applied research. Interesting conclusions emerge from the analysis of the measure studied in the cross-section of types of R&D activities and executive sectors. In the analyzed period, the expenditures incurred on development work dominated in all executive sectors, i.e., in micro, small, medium, large and great enterprises, as well as in companies from the private and public sectors. This situation indicates the short-term nature of R&D policy.

The level and dynamics of expenditures on R&D activities in the sector of Polish enterprises indicate that: 1) R&D activity in the analyzed sector was relatively low, as evidenced by relatively low and diversified expenditures on R&D; 2) R&D activity, treated as a source of knowledge for innovative processes, was not a priority in the information and decisionmaking processes of the management of most companies, especially micro and small, as well as in the R&D policy; 3) in the sector of Polish enterprises, R&D policy had a more ad hoc, random character, to a small extent focused on the systemic creation of knowledge and its use in innovative processes; 4) in all cross-sections of the analysis, the real R&D policy of the enterprise sector was clearly focused on finansing development work consuming knowledge. Less importance was attached to the development of basic and applied research, aimed at creating knowledge and searching for the possibility of its practical use as part of development work, 5) R&D policy in the sector of Polish enterprises was more determined by current needs, to a lesser extent by the vision of development and the resulting strategy. This policy was not sufficiently focused on systemic cooperation with national and international organisations leading to rational results in R&D and innovation (Chen et al., 2021, p. 244).

The passive nature of R&D policies in the sector of Polish enterprises may be the result of the following factors:

1) insufficient involvement of company managers in identifying current and future problems (internal and external), the solution of which requires the creation of new knowledge, sharing silent knowledge and transforming it into organizational knowledge;

2) the dominance in management information and decision-making processes of thinking from the perspective of solving the current needs of the company and individual units, an organizational instead of a systemic approach to the implementation of the organization’s development goals through the integration of R&D, marketing and innovative activities. This entails a comprehensive combination of the concepts of research, development, innovative activity and marketing research (R&D+I+M) into one cycle of the research system (Jasiński, 2020, p. 5; Mate & Molero, 2021, p. :2);

3) a prevalence of managers thinking in terms of past successes instead of creating the future based on information systematically obtained from the market, from individual customers and offensive strategies for the development of the organization;

4) low ability and inclination of the management staff to introduce social innovations and innovations in management (Heij et al., 2020, p. 278);

5) limited financial, organizational, social capabilities, technical and managerial enterprises;

6) insufficient capacity and propensity to systematic learning and management of knowledge and innovation according to model indications, especially network models (Baruk, 2021, pp. 14–27);

7) lack of inclination in management to create an innovative experience environment, conducive to employee interaction with individual customers, aimed at co-creating knowledge, innovation and values (Prahalad & Ramaswamy, 2005, p. 62; Baruk, 2020, p. 5);

8) a relatively low level of organizational culture, limited interest among management in creating an organizational culture aimed at creating knowledge and materializing it in innovation;

9) an excessive preference for traditional organizational solutions and favoring them to the creation of changes based on the characteristics of excellent innovative companies, such as (Peters & Waterman, 2000, pp. 45–48): willingness to act; proximity to the customer (learning from people); autonomy and entrepreneurship; development in the stage of progress, efficiency thanks to employees and individual customers; active involvement, guided by values; remaining with what you know; simple form, less administration; a combination of slackness and rigidity;

10) the limited tendency of managers to systematically shape technical and social architecture supporting a culture of knowledge creation and innovation, learning and knowledge sharing (Prahalad & Krishnan, 2010, p. 66).

If there are weaknesses in R&D policies and management processes, systemic actions are necessary to eliminate these weaknesses and optimize existing solutions. Such action may involve the integration of R&D, innovative, production and market relations functions, achieved as a result of creating and implementing innovations in management, treated as a contextual variable, affecting the effectiveness of R&D work and innovative activities from the point of view of effective identification and solving an enterprise’s own problems, as well as customer problems. It should be realized that innovations in management dynamize R&D work, which in turn promotes an increase in the level of innovative activity that translates into the company’s economic results and customer satisfaction. Innovations in management are conducive to the effective creation of all categories of knowledge, which is a prerequisite for the effectiveness of innovative processes (Heij et al., 2020, p. 287).

R&D policy should therefore be aimed at increasing the dynamics of internal R&D activities based on the optimal use of internal resources with full openness to the acquisition and use of external resources, especially financial and human resources, in accordance with the open innovation model (Baruk, 2021, pp. 21–22; Mate and Molero, 2021, p. 8) and the models presented in Figures 1 and 2.

Proposals for further research

In the context of the results of the research presented in this article, further empirical research should be done on the methodology of shaping R&D and innovative policy in Polish enterprises and translating it into everyday activities. The following questions should be addresed:

1) Will these policies support the systemic, prospective development of enterprises, based on the use of various sources of knowledge materialized in innovation?

2) What is the culture of shaping and implementing R&D and innovation policy in enterprises?

3) What is the role of customers in R&D and innovation policy?

4) Are managers substantively and mentally prepared to create such a policy based on model solutions?

5) Are enterprises able to raise the funds necessary for the systemic development of R&D and innovation activities?

References

1. Arandah, W.M.M.A. (2021). Applying Value Management & Market-Oriented Economic Land Value Assessment as a Managerial Decision-Making Tool: Case Study. IOSR Journal of Engineering, Vol. 11(6).

2. Areri, D., Kipchumba, S., Kamau, G. (2020). Strategic Innovation and Growth of Public Universities in Kenya. IOSR Journal of Business and Management, Vol. 22(10).

3. Ayming Raport (2016): Ulga B+R. Wyzwania, szanse, rozwiązania [R&D Relief: Challenges, Opportunities, Solutions]. https://www.ayming.pl/analizy-i-aktualnosci/ raporty/raport-2016-ulga-br-wyzwania-szanse-rozwiazania/ (accessed 16.07.2021).

4. Ayming Raport (2018): Ulga B+R. Krok milowy w rozwoju innowacyjności przedsiębiorstw [R&D Relief: A milestone in the development of the innovation of companies]. https://www.ayming.pl/analizy-i-aktualnosci/raporty/raport-2018-ulgabr-krok-milowy-w-rozwoju-innowacyjnosci-przedsiebiorstw/ (accessed 18.07.2021)

5. Barbieri, J.C., Alvares, A.C.T. (2016). Sixth generation innovation model: description of a success model. Innovation & Management Review, Vol. 13(2).

6. Baruk, J. (2007). Poziom innowacyjności przedsiębiorstw jako skutek luki kompetencyjnej [The level of innovation at companies a s consequence of the competence gap]. W: A. Sitko-Lutek (ed.), Polskie firmy wobec globalizacji. Luka kompetencyjna (12, 140). Warszawa: Wydawnictwo Naukowe PWN.

7. Baruk, J. (2014). Zarządzanie wiedzą i innowacjami. Toruń: Wydawnictwo Adam Marszałek w Toruniu.

8. Baruk A. (2017). Zakres aktywności prosumpcyjnej nabywców a specyfika ich zachowań zakupowych [Scope of prosumer activity by purchasers and the nature of their purchase behaviors]. Przegląd Organizacji, 6.

9. Baruk J. (2020). Zarządzanie innowacjami ukierunkowane na współtworzenie wartości w ramach partnerskich relacji [Innovation management targeted towards co-creating value under the framework of partnership relations]. Marketing i Rynek, vol. XXVII (5).

10. Baruk J. (2021). Wspieranie zarządzania innowacjami rozwiązaniami modelowymi [Supporting innovation management with model solutions]. Marketing i Rynek, vol. XXVIII(3).

11. Chen, J., Di Minin, A., Minshall, T., Su, Y., Xue, L., Zhou, Y. (2021). The New Silk Road: R&D networks, knowledge diffusions, and open innovation. R&D Management, Vol. 51 (3).

12. Dieter, W., Schmitt, W. (2018). A Literature Review on Innovation Process. East African Scholars Journal of Economics, Business and Management, Vol. 1(3).

13. Eurostat. (2021). https://appasso.eurostat.ec.europa.eu/nui/print.do (accessed 29.06.2021)

14. GUS (2017). Działalność badawcza i rozwojowa w Polsce w 2016 r. Warszawa, Szczecin: GUS.

15. GUS (2018a). Działalność badawcza i rozwojowa w Polsce w 2017 r. Warszawa, Szczecin: GUS.

16. GUS (2018b). Podręcznik Frascati 2015. Zalecenia dotyczące pozyskiwania i prezentowania danych z zakresu działalności badawczej i rozwojowej. Warszawa: Główny Urząd Statystyczny.

17. GUS (2019a). Działalność badawcza i rozwojowa w Polsce w 2018 r. Warszawa, Szczecin: GUS. GUS (2019b). Nauka i technika w 2017 r. Warszawa, Szczecin: GUS.

18. GUS (2020a). Działalność badawcza i rozwojowa w Polsce w 2019 r. Warszawa, Szczecin: GUS.GUS (2020b). Nauka i technika w 2018 r. Warszawa, Szczecin: GUS.

19. GUS (2021). Nauka i technika w 2019 r. Warszawa, Szczecin: GUS. Heij C.V., Volberda H.W., Van den Bosch F.A.J., & Hollen R.M.A. (2020). How to leverage the impact of R&D on product innovation? The moderating effect of management innovation. R&D Management, Vol. 50(2).

20. IDEA Institute (2021). Wpływ wsparcia działalności badawczo-rozwojowej w polityce spójności 2014–2020 na konkurencyjność i innowacyjność gospodarki — I etap: badanie w trakcie wdrażania [Influence of support for R&D activity in the 2014–2020 cohesion policy on economic competitiveness and innovation]. Warszawa: IDEA Instytut sp. z o.o.

21. Janasz, W. & Kozioł, K. (2007). Determinanty działalności innowacyjnej przedsiębiorstw [Determinants of the innovative activity of companies]. Warszawa: Polskie Wydawnictwo Ekonomiczne.

22. Jasiński, A.H. (2005). Bariery transferu techniki na rynku dóbr zaopatrzeniowoinwestycyjnych [Barriers to the transfer of technology to the market of supply and investment goods]. Warszawa: Wydawnictwo Naukowe Wydziału Zarządzania Uniwersytet Warszawski.

23. Jasiński, A.H. (2020). Łączniki między innowacją i marketingiem [Links between innovation and marketing]. Przegląd Organizacji, 11.

24. Kelemu, N. (2019). A Survey on New Product Development, Market Orientation on Organizational Financial Performance: A Case Study on Selected Beer Factories in Ethiopia. International Journal of Business and Management Invention, Vol. 8(12).

25. Kolomiiets, O., Krzyżanowska, M., & Mazurek, G. (2018). Customer Disposition to Value Co-Creation Activities: The Case of the Clothing Industry. Journal of Management and Business Administration — Central Europe, Vol. 26(3).

26. Kumar, M. (2021). Knowledge Management: Process and Challenges. IOSR Journal of Business and Management, Vol. 23(5).

27. Mate, M. & Molero, J. (2021). The Impact of Public and Private Internal R&D Investments on Spanish Business Performance During the Period of Crisis 2008–2012. International Journal of Advanced Research in Engineering & Management, Vol. 7(2).

28. Matejun, M. (2015). Absorpcja wsparcia w zarządzaniu rozwojem mikro, małych i średnich przedsiębiorstw — podejście strategiczne [Absoption of support in managing the development of micro, small, and medium-sized enterprises — a strategic approach]. Łódź: Wydawnictwo Politechniki Łódzkiej.

29. OECD (2015), Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development, The Measurement of Scientific, Technological and Innovation Activities, OECD Publishing, Paris.

30. Okwemba, E. (2018). Influence of Knowledge Management Capabilities on Performance of Telecommunication Companies in Kenya. International Journal of Business and Management Invention, Vol. 7(6).

31. Peng, J., Lawrence, A., & Koo, T. (2009). Customer knowledge management in international project: a case study. Journal of Technology Management in China, Vol. 4 (2).

32. Peters, Th.J. & Waterman, R.H. (2000). Poszukiwanie doskonałości w biznesie [Seeking Excellence in Business]. Warszawa: Wydawnictwo MEDIUM.

33. Poznańska, K. (2017). Ograniczenia działalności innowacyjnej przedsiębiorstw przemysłowych w Polsce [Limitations on the innovative activity of industrial enterprises in Poland]. Studia I prace Wydziału Nauk Ekonomicznych i Zarządzania. Nr 48/3. Uniwersytet Szczeciński.

34. Prahalad, C.K. & Ramaswamy, V. (2005). Przyszłość konkurencji [The future of competition]. Warszawa: Polskie Wydawnictwo Ekonomiczne.

35. Prahalad, C.K., & Krishnan, M.S. (2010). Nowa era innowacji [The new era of innovation]. Warszawa: Wydawnictwo Profesjonalne PWN.

36. Probst, G., Raub, S., & Romhardt, K. (2004). Zarządzanie wiedzą w organizacji [Knowledge management in the organization]. Kraków: Oficyna Ekonomiczna.

37. Ri, K., Wang, Y., & Zhang, X. (2018). Innovator’s Innovate Genetic Model: From Biological to Social Perspective. Science Journal of Business and Management, Vol. 6(2).

38. Shete, M. (2021). A research paper on Customer Satisfaction Evaluation Process. Journal of Research in Business and Management, Vol. 9(1).

39. Szopik-Depczyńska, K. (2018). Koncepcja innowacji kreowanej przez użytkownika w działalności badawczo-rozwojowej przedsiębiorstw [The concept of user-created innovation in the R&D activity of companies], Szczecin: Wydawnictwo Uniwersytetu Szczecińskiego.

40. Suvaci, B. (2018). The Impact of Organizational Culture on Employees’ Protean and Boundaryless Career Attitudes: An Empirical Study of the Banking Sector in Turkey. Journal of Business and Management, Vol. 24(1).

41. Świadek, A. (2021). Krajowy system INNOWACJI 2.0 [The domestic system Innovation 2.0]. Warszawa: CEDEWU.

Podstawowymi elementami każdej gospodarki są podmioty gospodarcze różniące się celami i zakresem działania a także zasobami niezbędnymi do ich realizacji. Podmioty te mogą działać na rynku lokalnym, regionalnym, krajowym i światowym. Ogólnym celem ich funkcjonowania może być działalność produkcyjna, usługowa lub regulacyjna. Zazwyczaj podmioty te rozwijają się w warunkach: dynamicznych zmian zachodzących w ich otoczeniu ekonomicznym, politycznym i społecznym; silnej konkurencji na rynku; szybkich zmian techniki i technologii; utrudnionego dostępu do zasobów materialnych i niematerialnych — zwłaszcza wiedzy; dynamicznych zmian oczekiwań aktualnych i potencjalnych klientów; szybko zmieniających się metod zarządzania itp. W konsekwencji podmioty te muszą posługiwać się sprawnym systemem informacyjnym/informatycznym, pozwalającym możliwie szybko identyfikować wszelkie zmiany zachodzące zarówno w otoczeniu wewnętrznym, jak i zewnętrznym (ogólnym i zadaniowym) (Griffin, 2007, s. 75–89) celem: rejestracji wszelkich sygnałów (nawet słabych) o zmianach zachodzących w otoczeniu; reagowania na te zmiany poprzez dostosowywanie swoich rozwiązań strukturalnych, procesowych, technicznych, technologicznych, społecznych, kulturowych i zarządczych, których wdrożenie pozwoli zachować równowagę z otoczeniem, a nawet wyprzedzać zmiany zachodzące w środowisku, jak również tworzyć środowiska wzajemnych interakcji między przedsiębiorstwem a jego klientami (Li, Zhang i Wei, 2018, s. 22).

Niewątpliwie podstawowymi instrumentami zmian dostosowawczych i wyprzedzających są innowacje produktowe, procesowe, organizacyjne i marketingowe (Baruk, 2018, s. 88). Tworzenie takich innowacji powinno mieć systemowy charakter i wynikać z racjonalnej polityki innowacyjnej prowadzonej na poziomie kraju, regionu, każdego podmiotu gospodarczego (Chen, Xia i Yang, 2018, s. 39). Sprawne kreowanie innowacji uwarunkowane jest posiadaniem określonych zasobów wiedzy naukowej, rynkowej, technologicznej, ekonomicznej, bowiem każda innowacja powstaje w procesie materializowania posiadanych zasobów różnych kategorii wiedzy. Wiedza organizacyjna jest jednym z jej najważniejszych zasobów, podstawą stabilnego rozwoju, źródłem utrzymania konkurencyjnego charakteru organizacji (Wang i Chen, 2017, s. 96).

Właśnie systemowe poszukiwanie i transfer nowej wiedzy lub twórcze połączenie istniejących pomysłów lub technologii stało się kluczowym warunkiem udanych innowacji (Xie, Hall, McCarthy, Skitmore i Shen, 2016, s.

71) Takimi zasobami wiedzy należy racjonalnie zarządzać poprzez realizację zbioru logicznych działań obejmujących pozyskiwanie wiedzy, jej magazynowanie, oczyszczanie (aktualizowanie), dystrybucję, wykorzystanie i monitorowanie. Ułatwieniem realizacji procesu zarządzania wiedzą mogą być modele zarządzania wiedzą (Baruk, 2009, s. 32, 35–46). Postępowanie zarządzających zgodne ze wskazaniami modeli sprzyja kształtowaniu gospodarki opartej na wiedzy, charakteryzującej się systemowo prowadzoną działalnością badawczą i rozwojową (B+R) oraz innowacyjną. Taka konstatacja jest szczególnie istotna w świetle względnie niskiej świadomości prac B+R, ich rozumienia i potrzeby identyfikacji przez kadrę kierowniczą w polskich firmach (Deloitte, 2016, s. 10).

Działalność badawcza i rozwojowa stanowi więc źródło wiedzy dla procesów innowacyjnych dlatego powinna być istotnym elementem polityki badawczo-rozwojowej i innowacyjnej na poziomie makro- i mikroekonomicznym. Polityka ta umożliwia kreowanie nowej wiedzy, rozwój technologii zwiększających zdolności podmiotów gospodarczych w zakresie tworzenia innowacji i ich praktycznego wykorzystania. Generalnie, prace B+R wspomagają organizacje w systemowym zwiększaniu zasobów wiedzy (zwłaszcza podstawowej), wiedzy pracowników, umożliwiają ujawnianie i wykorzystanie talentów, pozyskiwanie wiedzy zewnętrznej i usprawnianie zdolności innowacyjnych. Dzięki racjonalnie organizowanym pracom B+R organizacje biznesowe nabywają lub opracowują ważne technologie wewnętrznie lub zewnętrznie — poprzez wspólne przedsięwzięcia, licencje, sojusz strategiczny i przejęcia (Salisu i Bakar, 2019, s. 58).

Wysoka ranga działalności B+R, traktowanej jako źródło wiedzy materializowanej w procesach tworzenia i wdrażania innowacji, wymaga kreatywnego zaangażowania się menedżerów w systemowy jej rozwój. Zakres takiego zaangażowania kadry kierowniczej można wyrazić pośrednio za pomocą miernika w postaci procentowego udziału wydatków ponoszonych na badania i rozwój w produkcie krajowym brutto. Analizie poddano kształtowanie się tego miernika w odniesieniu do: wszystkich sektorów działania; w sektorze przedsiębiorstw; w sektorze rządowym; w sektorze szkolnictwa wyższego; w sektorze prywatnych instytucji niekomercyjnych. Poziom tych mierników, ukształtowanych w latach 2008; 2010; 2013; 2015 i 2017, odniesiono do UE, Polski oraz wybranych krajów członkowskich charakteryzujących się względnie najwyższymi i najniższymi udziałami.

Celem publikacji jest więc próba identyfikacji i krytycznej oceny udziału wydatków na B+R w produkcie krajowym brutto (PKB), ponoszonych przez podmioty gospodarcze skupione w czterech sektorach (przedsiębiorstw, rządowym, szkolnictwa wyższego i prywatnych instytucji niekomercyjnych) oraz łącznie we wszystkich sektorach, traktowanych jako pośrednia miara stopnia aktywności kadry kierowniczej w kształtowanie polityki badawczo-rozwojowej. Analizą objęto średnie wyniki notowane w UE, a także w wybranych krajach członkowskich (w tym w Polsce) oraz w wybranych krajach pozaeuropejskich.

Drugim celem opracowania jest próba weryfikacji tezy, że wydatki na B+R są zmienne i zróżnicowane w poszczególnych państwach członkowskich i nie dają jednoznacznie pozytywnego obrazu systematycznego i dynamicznego wzrostu aktywności badawczo-rozwojowej w tych krajach.

Do opracowania publikacji wykorzystano następujące metody badawcze: analizę krytyczno-poznawczą piśmiennictwa; analizę statystycznoporównawczą wtórnego materiału empirycznego Eurostatu; metodę projekcyjną.

Istota działalności badawczo-rozwojowej

Działalność badawczo-rozwojowa obejmuje systematycznie prowadzone prace twórcze, realizowane w celu zwiększenia zasobów wiedzy, w tym wiedzy o człowieku, kulturze i społeczeństwie, a także — znalezienia nowych możliwości zastosowania pozyskanej (odkrytej) wiedzy (GUS, 2019, s. 27).

Działalność B+R powinna być ukierunkowana na nowe odkrycia, oparte na oryginalnych koncepcjach lub hipotezach a także na ich interpretację. Cechą tej działalności jest brak pewności co do ostatecznego wyniku lub przynajmniej co do ilości czasu i zasobów potrzebnych do jego osiągnięcia. Celem tej działalności jest osiągnięcie wyników, które można byłoby swobodnie przenosić do praktyki lub sprzedawać na rynku. Działalność tę można uznać za działalność badawczą i rozwojową, jeżeli spełnia ona następujące kryteria (OECD, 2015, s. 47):

1) nowatorskość — ukierunkowanie na nowe odkrycia,
2) twórczość — oparcie się na oryginalnych, nieoczywistych koncepcjach i hipotezach,
3) nieprzewidywalność — niepewność co do ostatecznego wyniku oraz kosztu, w tym poświęconego czasu,
4) metodyczność — prowadzona w sposób zaplanowany (z określonym celem projektu B+R oraz źródłem finansowania),
5) możliwość do przeniesienia lub odtworzenia — skutkująca wynikami, które mogą być odtwarzane.

Na działalność B+R składają się:

1) badania podstawowe (czyste i ukierunkowane),
2) badania stosowane,
3) prace rozwojowe.

Badania podstawowe (basic research) to prace eksperymentalne lub teoretyczne podejmowane głównie w celu zdobycia nowej wiedzy na temat podłoża określonych zjawisk i obserwowalnych faktów, bez nastawienia na konkretne jej zastosowanie lub wykorzystanie. Badania te dzielą się na:

• „czyste” badania podstawowe (pure basic research) prowadzące do postępu wiedzy, bez nastawienia na osiąganie korzyści ekonomicznych czy społecznych i bez podejmowania aktywnych działań w celu zastosowania wyników badań do rozwiązywania problemów o charakterze praktycznym lub w celu przekazania wyników do sektorów zajmujących się ich zastosowaniem;
• ukierunkowane badania podstawowe (oriented basic research) nastawione na stworzenie szerokiej bazy wiedzy, stanowiącej podstawę rozwiązywania problemów lub wykorzystywania możliwości, zarówno istniejących, jak i przewidywanych w przyszłości.

Badania stosowane (applied research) to oryginalne prace badawcze podejmowane w celu zdobycia nowej wiedzy. Są one ukierunkowane głównie na osiągnięcie konkretnych celów praktycznych. Badania te polegają na uwzględnieniu istniejącej już wiedzy i jej „poszerzeniu” z myślą o rozwiązywaniu konkretnych problemów. Badania stosowane umożliwiają operacjonalizację pomysłów. Takie rozwiązania oparte na wiedzy mogą być chronione za pomocą instrumentów ochrony własności intelektualnej, włącznie z zapewnieniem tajemnicy handlowej. Skutkami badań stosowanych mogą być modele próbne wyrobów, procesów lub metod.

Prace rozwojowe (experimental development) obejmują metodyczną pracę opierającą się na wiedzy uzyskanej w wyniku działalności badawczej oraz doświadczeniach praktycznych i mającą na celu wytworzenie dodatkowej wiedzy ukierunkowanej na stworzenie nowych lub istotnie udoskonalonych materiałów, urządzeń, wyrobów, procesów, systemów lub usług, łącznie z przygotowaniem prototypów doświadczalnych oraz instalacji pilotażowych (Baruk, 2016, s. 61; Bogers, 2011, s. 94).

Działalność B+R, traktowana jako systemowe tworzenie wiedzy wykorzystywanej do tworzenia innowacji oraz rozwiązywania aktualnych i przyszłych problemów, może być prowadzona przez pojedynczy podmiot gospodarczy, jeżeli posiada on odpowiednie warunki organizacyjne, technologiczne, finansowe i kadrowe. W przypadku braku takich warunków podmiot gospodarczy może korzystać z wyników działalności B+R realizowanej w innych podmiotach gospodarczych. Możliwe jest też rozwiązanie pośrednie, polegające na wspólnym prowadzeniu prac B+R z innymi organizacjami (przemysłowymi, naukowymi i badawczymi) w ramach struktur sieciowych. Korzystanie z takich rozwiązań wymaga racjonalnej polityki B+R, innowacyjnej i rozwojowej na wszystkich szczeblach zarządzania. Koncepcję takiego podejścia do zarządzania przedstawiono na rysunku 1.

Funkcjonowanie podmiotu gospodarczego obrazują cztery logicznie następujące po sobie zbiory działań: działalność badawczo-rozwojowa kreująca zasoby wiedzy; działalność innowacyjna materializująca pozyskaną wiedzę; oparta na innowacjach działalność operacyjna polegająca na wytwarzaniu innowacyjnych wyrobów i świadczeniu innowacyjnych usług; działalność marketingowa/zbyt — umieszczenie na rynku innowacyjnych wyrobów lub usług. Zarządzanie tymi zbiorami działań powinno opierać się na założeniach wzajemnie powiązanych polityk: B+R, innowacyjnej i rozwojowej, a także na systemowo pozyskiwanej wiedzy naukowej, technologicznej, ekonomicznej, rynkowej, handlowej i klientów.

Udział wydatków na badania i rozwój w PKB poniesionych we wszystkich sektorach działania

Działalność B+R jest działalnością kosztochłonną dlatego wymaga racjonalnych decyzji w zakresie pozyskiwania środków na ten cel, wymaga też skoordynowanej polityki w skali całej gospodarki, w skali regionów oraz w skali poszczególnych podmiotów gospodarczych. Zasadne jest więc przeanalizowanie jak radzą sobie państwa członkowskie w kształtowaniu polityki B+R. Syntetycznym miernikiem takiego zaangażowania może być udział wydatków na B+R w dochodzie krajowym brutto. W tabeli 1 przedstawiono kształtowanie się tego miernika dla UE, Polski i wybranych krajów członkowskich w wybranych latach.

W rozważanych latach udział wydatków na B+R w PKB był zróżnicowany pod względem wartości i tendencji zwyżkowych. Na poziomie UE w latach 2008 i 2010 udział ten nie przekraczał 2%, natomiast w trzech pozostałych latach przekroczył granicę 2% z nieznaczną tendencją wzrostową. Do takiego stanu przyczyniły się kraje członkowskie, wyraźnie zróżnicowane pod względem poziomu PKB przeznaczanego na B+R. Pozytywnie wyróżniały się takie kraje jak: Finlandia, Szwecja, Dania, Niemcy i w mniejszym stopniu Francja. W krajach tych poziom analizowanego miernika był wyższy od średniej wartości dla UE w poszczególnych latach. Szczególnie wyróżniała się Szwecja, gdzie udział ten przekraczał 3%, jednak bez wyraźnej tendencji wzrostowej. W Finlandii w początkowych trzech latach przekraczał on 3%, ale w kolejnych dwóch latach miał tendencje malejące. Przeciwna sytuacja miała miejsce w Danii, gdzie w latach 2008, 2010 i 2013 miernik ten utrzymywał się na poziomie poniżej 3%, ale z nieznaczną tendencją wzrostową, by w kolejnych latach przekroczyć granicę 3%. Nieco niższy poziom miernik ten osiągał w Niemczech, wykazując nieznaczną tendencję wzrostową i w 2017 r. przekroczył granicę 3%.

Przeciwstawną grupę stanowiły kraje o względnie małych udziałach wydatków na B+R w PKB. Głównie chodzi tu o Cypr, Rumunię, Łotwę i Bułgarię. W krajach tych poziom analizowanego miernika nie przekraczał 1% i miał nieregularne tendencje wzrostowe. W poszczególnych latach udziały te znacznie odbiegały od średnich wartości w UE.

W Polsce wydatki na B+R kształtowały się na znacznie niższym poziomie niż średnio w UE. Pozytywnym zjawiskiem był niewielki ale wzrostowy charakter rozważanego miernika od 0,6% w 2008 r. (mniej o 1,23 pproc. w porównaniu do średniego wyniku w UE) do 1,03% w 2017 r. (mniej o 1,04 pproc. w stosunku do średniego wyniku w UE). Udziały wydatków na B+R w PKB plasują Polskę w grupie państw, które muszą nadrabiać dystans dzielący ich od czołówki europejskiej.

W kontekście prowadzonej analizy nasuwa się pytanie, jaką pozycję zajmuje UE i poszczególne kraje członkowskie na tle poziomu rozważanego miernika charakteryzującego kraje przodujące pod tym względem, takie jak: USA, Japonia, czy Korea Południowa? Okazuje się, że średnie wyniki dla UE były niższe od wyników osiąganych w USA w 2008 r. — o 0,94 pproc., w 2010 r. — o 0,82 pproc., w 2013 r. — o 0,71 pproc., w 2015 r. — o 0,72 pproc., dla 2017 r. brak danych dla USA. Przedstawione liczby wskazują na utrzymywanie się luki technologicznej między UE a USA, Japonią i Koreą Południową, mimo optymistycznych założeń strategii „Europa 2020” zakładającej poprawę warunków prowadzenia działalności badawczo-rozwojowej, między innymi, poprzez przeznaczanie 3% PKB UE na inwestycje w badania i rozwój (Strategia, 2015, s. 1).

Wśród państw członkowskich tylko Szwecja spełniła ten warunek w analizowanych latach. Natomiast Finlandia — w latach 2008, 2010 i 2013. Dania osiągnęła poziom zakładanego miernika w latach 2015 i 2017, podczas gdy Niemcy tylko w 2017 r.

Jeszcze większe różnice w poziomie udziału wydatków na B+R w PKB pojawiły się między UE a Japonią oraz Koreą Południową. W Japonii wydatki na B+R stanowiły ponad 3% PKB. Jeszcze korzystniejsza sytuacja panowała w Korei Południowej, gdzie w latach 2013 i 2015 udziały te przekroczyły 4%.

Udział wydatków na badania i rozwój w PKB w sektorze przedsiębiorstw

Do sektora przedsiębiorstw zalicza się (OECD, 2015, s. 34): 1) wszystkie przedsiębiorstwa mające status rezydenta, w tym nie tylko przedsiębiorstwa posiadające osobowość prawną, bez względu na miejsce zamieszkania lub siedzibę ich akcjonariuszy czy udziałowców. Zalicza się tutaj zarówno przedsiębiorstwa prywatne (przedsiębiorstwa notowane na giełdzie i będące przedmiotem obrotu giełdowego lub też nie), jak i przedsiębiorstwa sektora publicznego (tj. przedsiębiorstwa kontrolowane przez sektor rządowy),

2) nieposiadające osobowości prawnej oddziały przedsiębiorstw niemających statusu rezydenta, które uznaje się za rezydentów i element tego sektora, ponieważ zajmują się produkcją na danym obszarze gospodarczym w perspektywie długofalowej,

3) wszystkie instytucje niekomercyjne mające status rezydenta, które są producentami wyrobów lub usług na rynku bądź świadczą usługi na rzecz biznesu.

W kontekście prowadzonej analizy zasadne jest pytanie: jaki był udział wydatków na B+R w PKB, ponoszonych w sektorze przedsiębiorstw? Jak wynika z tabeli 2, poziom tego miernika przyjmował różne wartości w poszczególnych państwach członkowskich.

Średnio w UE wydatki te osiągały poziom przekraczający 1% PKB i miały tendencję wzrostową od 1,16% w 2008 r. do 1,36% w 2017 r. Jednak w krajach członkowskich uwidoczniły się znaczne różnice w poziomie tego miernika względem innych państw, a także w poszczególnych latach. Pozytywnie wyróżniały się sektory przedsiębiorstw w Szwecji i w Finlandii. W państwach tych rozważany miernik znacznie przekraczał średnie wyniki dla UE osiągając ponad 2% wartość z wyjątkiem Finlandii, gdzie w 2015 r. obniżył się do 1,93%. Pozytywne tendencje zanotowano w przedsiębiorstwach austriackich i niemieckich, gdzie analizowane udziały cechowały się stałą, aczkolwiek niewielką tendencją wzrostową. W przypadku Austrii od 1,78% w 2008 r. do 2,22% w 2017 r.

W przypadku Niemiec od 1,8% w 2008 r. do 2,09% w 2017 r. Na wyższym poziomie niż średnio w UE miernik ten kształtował się również w Danii lecz miał on względnie stabilny charakter.

Część państw członkowskich UE charakteryzowała się znacznie niższymi poziomami rozważanego miernika. Konstatacja ta dotyczy szczególnie Cypru, Rumunii, Łotwy, Litwy i Słowacji. W krajach tych wydatki na B+R ponoszone przez sektor przedsiębiorstw kształtowały się na względnie niskim i zróżnicowanym poziomie. Najgorsza sytuacja panowała wśród przedsiębiorstw cypryjskich, gdzie w 2008 r. rozważany miernik osiągnął poziom 0,09%, by w 2017 r. wzrosnąć do zaledwie 0,2%. Pozytywnym zjawiskiem w sektorach przedsiębiorstw litewskich i słowackich były niewielkie ale systematyczne wzrosty badanego miernika w analizowanych latach. W przypadku Litwy od 0,19 w 2008 r. do 0,31% w 2017 r. a w przypadku Słowacji od 0,2% w 2008 r. do 0,48% w 2017 r.

Udział wydatków na B+R w PKB w sektorze polskich przedsiębiorstw był wyraźnie mniejszy w porównaniu ze średnimi wynikami w UE.

W Polsce w 2008 r. miernik ten był niższy o 0,97 pproc., w 2010 r. — o 1 pproc., w 2013 r. — o 0,9 pproc., w 2015 r. — o 0,84 p. proc. i w 2017 r. — o 0,67 pproc. Mimo stosunkowo niskiego udziału wydatków na B+R w PKB ponoszonych przez sektor przedsiębiorstw w Polsce można dostrzec pozytywne tendencje przejawiające się malejącą luką w stosunku do średnich wyników w UE i nieznacznym wzrostem miernika w kolejnych latach z wyjątkiem 2010 r. Jednak bezwzględne wartości tego miernika plasują polskie przedsiębiorstwa w grupie państw o względnie niskim poziomie finansowania działalności B+R.

Również w tym przekroju analizy średnie wyniki dla UE w porównaniu do wyników cechujących USA, a zwłaszcza Japonię i Koreę Południową, nie są zadowalające. W USA miernik ten zbliżony był do 2% w poszczególnych latach i przewyższał średnie wartości w UE o 0,79 pproc. — w 2008 r., o 0,67 pproc. — w 2010 r., o 0,64 pproc. — w 2013 r., o 0,66 pproc. — w 2015 r. W Japonii i w Korei Południowej wyniki te kształtowały się średnio na poziomie odpowiednio 2,53% i 2,87%.

Udział wydatków na badania i rozwój w PKB poniesionych przez sektor rządowy

Jednym z ważnych podmiotów kreujących politykę badawczą i rozwojową są rządy poszczególnych państw i ich agendy. Miarą takiego zaangażowania może być udział wydatków na B+R w PKB ponoszonych przez sektor rządowy, na który składają się (OECD, 2015, s. 35):

1) wszystkie jednostki władz szczebla centralnego/federalnego, regionalnego/stanowego oraz lokalnego/gminnego, w tym zakłady ubezpieczeń społecznych, z wyjątkiem tych jednostek, które odpowiadają opisowi instytucji szkolnictwa wyższego,

2) pozostałe organy administracji publicznej: agencje wykonujące lub finansujące B+R oraz wszystkie nierynkowe instytucje niekomercyjne, które są kontrolowane przez jednostki sektora rządowego, a które same nie należą do sektora szkolnictwa wyższego.

Poziom tego miernika przedstawiono w tabeli 3.

Na poziomie UE, średnia wartość udziału wydatków na B+R w PKB poniesionych przez rządy państw członkowskich wynosiła około 0,25% i miała stabilny charakter. W przekroju państw członkowskich wartości analizowanego miernika odbiegały od średnich wyników dla UE. Różniły się też między poszczególnymi krajami. W krajach takich jak: Niemcy, Czechy, Luksemburg, Słowenia i Finlandia udział rządowych wydatków na B+R w PKB był nieco wyższy od średnich wyników w UE, jednak nie miał on jednoznacznie wzrastającego charakteru w kolejnych latach. Najbardziej wyróżniającym się krajem były Niemcy, gdzie sektor rządowy na B+R przeznaczał około 0,4% PKB w poszczególnych latach.

Na przeciwnym końcu skali znalazły się: Malta, Irlandia, Cypr, Dania i Portugalia. W państwach tych poziomy analizowanego miernika były wyraźnie niższe od średnich wartości dla UE. Wyniki te wskazują na śladowe zaangażowanie sektora rządowego w finansowanie badań i rozwoju. Przykładowo na Malcie udział sektora rządowego w finansowaniu B+R w latach 2008, 2010 utrzymywał się na poziomie 0,02% PKB. Jeszcze gorsza sytuacja była w 2017 r. W Portugalii wartość analizowanego miernika spadła z 0,11% w 2008 r. do 0,07% w 2017 r.

W Polsce finansowanie badań i rozwoju przez sektor rządowy mierzony procentowym udziałem wydatków na B+R w PKB zbliżony był do średnich wyników w UE i utrzymywało się na poziomie nieco przekraczającym 0,2% z wyjątkiem 2017 r., kiedy wartość tego miernika spadła do zaledwie 0,02%. Wynik ten plasuje Polskę na drugim miejscu od końca państw członkowskich przed Maltą.

Dla porównania w kilku państwach na świecie wartość badanego miernika kształtowała się na wyższym poziomie niż średnio w UE. Do takich państw należą: Korea Południowa, USA, Rosja i Hong Kong, gdzie poziom rządowych wydatków na B+R kształtował się nieco powyżej 0,3% PKB, natomiast w Korei Południowej oscylował między 0,38% w 2008 r. a 0,5% w 2015 r.

Luka w poziomie analizowanego miernika między UE a USA wynosiła: 0,07 pproc. w 2008 r., 0,1 pproc. w 2010 r., 0,06 pproc. w 2013 r. i 0,07 pproc. w 2015 r.

Udział wydatków na badania i rozwój w PKB poniesionych w sektorze szkolnictwa wyższego

Jednym z sektorów, który powinien być silnie zaangażowany w działalność B+R jest sektor szkolnictwa wyższego, do którego zalicza się (OECD, 2015, s. 36):

1) wszystkie uniwersytety, uczelnie techniczne i inne instytucje prowadzące formalne programy kształcenia na poziomie wyższym, bez względu na ich źródło finansowania i status prawny,

2) wszystkie instytuty badawcze, ośrodki, stacje doświadczalne i kliniki, które prowadzą działalność B+R pod bezpośrednią kontrolą lub zarządem instytucji szkolnictwa wyższego.

Przejawem takiego zaangażowania może być finansowanie badań i rozwoju. Rodzi się więc pytanie: jaki był udział wydatków na B+R w PKB ponoszonych przez sektor szkolnictwa wyższego w UE i w wybranych państwach członkowskich w analizowanym okresie? Wartości tego miernika przedstawiono w tabeli 4.

Okazuje się, że średnio w UE wydatki na B+R ponoszone przez sektor szkolnictwa wyższego kształtowały się na poziomie powyżej 0,4% PKB i miały raczej stabilny charakter w poszczególnych latach. Natomiast w poszczególnych państwach członkowskich udziały te wyraźnie różniły się, co pozwoliło na wyodrębnienie grupy państw o najwyższych udziałach, znacznie przekraczających średnie wyniki w UE, takich jak: Dania, Szwecja, Finlandia i Austria oraz grupy państw o najniższych udziałach, kształtujących się wyraźnie poniżej średniej dla UE, takich jak: Bułgaria, Rumunia, Luksemburg i Węgry. W pierwszej grupie państw szczególnie wyróżniała się Dania, gdzie w latach 2013, 2015 i 2017 wydatki sektora szkolnictwa wyższego na B+R przekroczyły 1% PKB. Takiego poziomu finansowania na zanotowano w żadnym z pozostałych państw członkowskich.

Wśród państw drugiej grupy najniższe wartości analizowanego miernika cechowały Bułgarię. Kształtowały się one na poziomie 0,04% w latach 2008 i 2017 oraz 0,07% w 2010 r. Niewiele lepsze wyniki w tym zakresie zanotowała Rumunia, zwłaszcza w 2017 r.

W Polsce sektor szkolnictwa wyższego przeznaczał na B+R od 0,2% PKB w 2008 r. do 0,34% PKB w 2017 r. Wyniki te były niższe od średnich dla UE o 0,22 pproc. w 2008 r., o 0,2 pproc. w 2010 r. o 0,22 pproc. w 2013 r., o 0,18 p. proc. w 2015 r. i o 0,12 pproc. w 2017 r. Pozytywną tendencją jest fakt stopniowego, aczkolwiek nieznacznego zwiększania się poziomu analizowanego miernika w kolejnych latach analizy.

Porównując średni poziom badanego miernika w UE z wynikami charakterystycznymi dla krajów przodujących należy zauważyć, że w UE, w porównaniu do USA, udział wydatków na B+R w PKB poniesionych przez sektor szkolnictwa wyższego był wyższy o 0,05 pproc. w 2008 r., o 0,07 pproc. w 2010 r., o 0,09 pproc. w 2013 r. i o 0,1 pproc. w 2015 r.

W rozważanym przekroju analizy średnie wartości analizowanego miernika w UE przewyższały też taki sam parametr charakteryzujący Japonię i Koreę Południową, co jest zjawiskiem korzystnym.

Udział wydatków na badania i rozwój w PKB poniesionych przez prywatne instytucje niekomercyjne

Instytucje niekomercyjne (non-profit institutions) to osoby prawne lub podmioty społeczne utworzone w celu wytwarzania wyrobów i usług, przy czym ich status nie pozwala na to, aby były one źródłem dochodu, zysku lub innych korzyści finansowych dla jednostek je zakładających, kontrolujących lub finansujących. Instytucje te mogą prowadzić produkcję rynkową lub nierynkową. W skład tego sektora wchodzą (OECD, 2015, s. 110):

1) wszystkie instytucje niekomercyjne działające na rzecz gospodarstw domowych, z wyjątkiem instytucji zaliczonych do sektora szkolnictwa wyższego;

2) gospodarstwa domowe i osoby prywatne zaangażowane w działalność rynkową lub nieuczestniczące w niej.

Przykładami jednostek zaliczanych do tego sektora mogą być niezależne stowarzyszenia zawodowe i naukowe oraz organizacje dobroczynne, które nie są kontrolowane przez jednostki należące do sektora rządowego lub sektora przedsiębiorstw.

Udział wydatków na B+R w PKB takich organizacji przedstawiono w tabeli 5.

Średnio w UE miernik ten kształtował się na poziomie 0,02% w latach 2008–2015. Jego wartość różniła się jednak w przekroju państw członkowskich. Największe wartości zanotowano na Cyprze od 0,04 w 2008 r. do 0,07 w 2015 i w 2017 r. We Włoszech udział wydatków na B+R w PKB w sektorze prywatnych instytucji niekomercyjnych utrzymywał się na poziomie 0,04%, by w 2017 r. obniżyć się do 0,02%. Miernik ten nieznacznie mniejsze wartości przyjmował w Wielkiej Brytanii i we Francji.

W grupie państw członkowskich były też takie, w których prywatne instytucje niekomercyjne zachowywały całkowitą bierność w finansowaniu badań i rozwoju. Do takich państw należały: Hiszpania, Rumunia, Słowacja i Polska. Natomiast w Słowenii tylko w 2017 r. organizacje te na B+R przeznaczyły 0,01% PKB.

Dla porównania w USA miernik ten utrzymywał się na poziomie 0,11% a w 2010 r. na poziomie 0,12%. W porównaniu ze średnimi wartościami w UE był on wyższy o 0,09 p. proc. w 2008 r., o 0,1 p. proc. w 2010 r., o 0,09 p. proc. w 2013 i 2015 r.

W Japonii prywatne instytucje niekomercyjne na B+R wydatkowały 0,05% PKB w 2008 r. i w 2010 r. oraz 0,04% w latach 2013 i 2015. O ile w Japonii udziały te nieznacznie zmalały to w Korei Południowej zanotowano nieznaczny ich wzrost od 0,04% w 2008 r. do 0,06% w 2010 i 2013 r. oraz do 0,07% w 2015 r.

Zakończenie

W publikacji podjęto próbę realizacji dwóch celów polegających na:

1) dokonaniu analizy i krytycznej oceny udziału wydatków na B+R w produkcie krajowym brutto (PKB), ponoszonych przez podmioty gospodarcze skupione w czterech sektorach (przedsiębiorstw, rządowym, szkolnictwa wyższego i prywatnych instytucji niekomercyjnych) oraz łącznie we wszystkich sektorach, traktowanych jako pośrednia miara stopnia aktywności kadry kierowniczej w kształtowanie polityki badawczorozwojowej na wszystkich szczeblach struktury zarządzania. Analizą objęto średnie wyniki notowane w UE, a także w wybranych krajach członkowskich (w tym w Polsce) oraz w wybranych krajach pozaeuropejskich.

2) weryfikacji tezy, że wydatki na B+R w poszczególnych państwach członkowskich są zmienne w czasie oraz zróżnicowane pod względem udziału w PKB i nie dają jednoznacznie pozytywnego obrazu dynamicznego wzrostu aktywności badawczo-rozwojowej w tych krajach.

Analiza krytyczno-poznawcza dostępnego materiału empirycznego potwierdziła powyższą tezę. Wartości liczbowe przyjętego miernika charakterystyczne dla UE, a także dla wybranych państw członkowskich o najwyższych i najniższych udziałach wydatków na badania i rozwój w PKB pozwalają uszeregować rozważane sektory od największej aktywności do najmniejszej. Na pierwszym miejscu znalazł się sektor przedsiębiorstw, następnie sektor szkolnictwa wyższego przed sektorem rządowym i sektorem prywatnych instytucji niekomercyjnych. W sektorze przedsiębiorstw średnie wartości miernika w UE miały wzrastający charakter, co jest zjawiskiem pozytywnym, sugerującym pewną racjonalność polityki B+R. Podobna sytuacja miała miejsce w Niemczech i w Austrii — wśród państw o najwyższych udziałach oraz na Litwie. Jednak w wielu krajach członkowskich udziały te zmieniały się nieregularnie pod względem wartości w poszczególnych latach np. od 2,8% w Niemczech do 0,14% na Łotwie (w 2017 r.); od 2,63% w Finlandii do 0,09% na Cyprze (w 2008 r.).

Pod względem udziału wydatków na B+R w PKB sektor przedsiębiorstw w Polsce cechował się niewielkim, aczkolwiek systematycznym wzrostem w kolejnych latach analizy (co jest zjawiskiem pozytywnym), jednak udziały te były znacznie niższe (grubo poniżej 1%) od średnich wyników dla UE, co plasuje Polskę w grupie państw maruderów, wyraźnie odstających od średniego poziomu w UE, zwłaszcza od państw przodujących.

Na drugim miejscu pod względem poziomu analizowanego miernika znalazł się sektor szkolnictwa wyższego, w którym udział wydatków na B+R w PKB (średnie wyniki dla UE) utrzymywał się na poziomie poniżej 0,5% i był w miarę stabilny w poszczególnych latach. Jednak w przekroju państw członkowskich analizowane udziały znacznie odbiegały od średnich wyników w UE zarówno w górę, jak i w dół. Przykładowo w 2008 r. w Danii wynosił on 0,75%, natomiast w Bułgarii tylko 0,04%; w 2017 r. w Danii kształtowały się na poziomie 1,01% a w Bułgarii na poziomie 0,04%, w Rumunii miał on wartość 0,05%.

Należy podkreślić, że w poszczególnych latach wartości tego miernika zmieniały się nieregularnie, nie posiadały jednoznacznie wzrostowych tendencji.

W Polsce sektor szkolnictwa wyższego charakteryzował się znacznie mniejszymi udziałami wydatków na B+R w PKB w porównaniu do średnich wyników w UE. Jednak pozytywnym zjawiskiem był ich wzrost od 0,2% w 2008 r. do 0,34% w 2017 r.

Na kolejnym miejscu pod względem udziału wydatków na B+R w PKB uplasował się sektor rządowy. Średnio w UE jego udziały nie przekraczały 0,25% i od 2013 r. miały malejącą tendencję.

W przekroju wybranych państw członkowskich udziały te były zróżnicowane co do wartości i w poszczególnych latach. Przykładowo, w Niemczech miernik ten utrzymywał się na poziomie nieco powyżej 0,4%, ale na Malcie nie przekraczał 0,1% z wyjątkiem 2015 r.

Najniższe i nieregularne wartości badanego miernika zanotowano w sektorze prywatnych instytucji niekomercyjnych. Średnio w UE utrzymywały się one na poziomie 0,02%, natomiast w krajach wyróżniających się od 0,03% do 0,07%. W takich krajach jak: Hiszpania, Rumunia i Słowacja prywatne instytucje niekomercyjne nie wydały na B+R żadnych środków.

Poziomy badanego miernika wskazują na istnienie luki między UE a USA, Japonią i Koreą Południową. Luka ta występuje zarówno w przekroju wszystkich sektorów działania (tabela 1), jak i w poszczególnych sektorach, tj. przedsiębiorstw, rządowym oraz prywatnych instytucji niekomercyjnych. Wyjątkiem jest sektor szkolnictwa wyższego, w którym udział wydatków na B+R w PKB średnio w UE był wyższy niż w USA, Japonii i Korei Południowej.

Zmienny i zróżnicowany w czasie poziom badanego miernika pozwala przypuszczać, że w państwach członkowskich UE nie wypracowano skutecznych instrumentów polityki B+R ukierunkowanej na racjonalne kreowanie wiedzy, która byłaby materializowana w innowacjach, zwłaszcza radykalnych (strategicznych), systemowo zaspokajających bieżące i przyszłe potrzeby klientów. Konstatacja ta dotyczy szczególnie państw cechujących się względnie niskimi udziałami wydatków na B+R w PKB, w tym również Polski. W państwach tych polityki rozwojowe bardziej ukierunkowane są na realizację zadań operacyjnych niż na kreowanie przyszłości. Przyczynami takiego stanu mogą być bariery: zewnętrzne, wewnętrzne, ekonomiczne, społeczne, kulturowe, organizacyjne, techniczne, mentalne itp. Zapewne wielu menedżerów w obawie przed ryzykiem towarzyszącym działalności B+R unika inwestowania w systemowy rozwój tej działalności traktowanej jako źródło wiedzy niezbędnej w kreowaniu innowacji, zwłaszcza radykalnych. Można przypuszczać, że jedną z takich barier jest brak umiejętności kształtowania polityki badawczo-rozwojowej zarówno na poziomie kraju, jak i regionu oraz podmiotu gospodarczego, koordynacji jej na wszystkich szczeblach zarządzania.

Do względnie niskiego poziomu prac B+R przyczyniają się błędy w zarządzaniu, przejawiające się słabą znajomością nowoczesnych metod zarządzania (w tym zarządzania wiedzą i innowacjami), dominacją w procesach decyzyjnych działalności operacyjnej, ograniczone zainteresowanie zarządzaniem strategicznym, niedocenianie wpływu kultury organizacyjnej (innowacyjnej) na wzrost zainteresowania pracowników i indywidualnych klientów tworzeniem wiedzy i jej wykorzystaniem w rozwiązywaniu pojawiających się problemów. Zarządzanie wiedzą należy traktować na równi z zarządzaniem zasobami ludzkimi i materialnymi organizacji, nie tylko jako dyskretną funkcję zarządzania, ale także jako wyjątkową umiejętność, ponieważ stanowi ono znaczący katalizator tworzenia innowacji i zawartej w nich wartości dla organizacji i dla klientów.

Zintegrowane zarządzanie wiedzą i innowacjami musi służyć usprawnianiu i wspieraniu procesów tworzenia i wdrażania innowacji, rozwoju tych procesów jako podstawowej kompetencji podmiotów gospodarczych (Gloet i Samson, 2019, s. 20). Znacznym ułatwieniem dla zarządzających działalnością B+R i innowacyjną może być postępowanie zgodne z wybranymi modelami innowacji, bowiem każdy z nich oparty jest na ścisłym związku B+R z działalnością innowacyjną. Modele innowacji stanowią grupę zasad, przepisów, procedur i praktyk, racjonalizujących procesy innowacji (Barbieri i Alvares, 2016, s. 116).

W kontekście względnie niskich i zróżnicowanych wydatków na B+R zasadne byłoby skoncentrowanie się menedżerów na systemowym postępowaniu zgodnym z założeniami czwartej generacji metod zarządzania działalnością B+R. Istotą tej koncepcji jest racjonalna koordynacja strukturalnych i procesowych aspektów tej działalności realizowanej wewnątrz podmiotu gospodarczego z organizacjami zewnętrznymi. W ten sposób powstaje badawcza struktura sieciowa wspomagana systemem informatycznym, racjonalnie wykorzystująca zasoby osobowe, organizacyjne, techniczne i finansowe. W konsekwencji powstają elastyczne struktury składające się z jednostek badawczo-rozwojowych funkcjonujących w strukturach różnych podmiotów gospodarczych. Jednostki te, dzięki posiadanym zasobom intelektualnym, metodycznie rozwiązują pojawiające się problemy, wymieniają się danymi, informacjami oraz wiedzą o wynikach prowadzonych prac, umieszczając je we wspólnych bazach danych. Powstałe w ten sposób struktury nazywane są niekiedy wirtualnymi strukturami B+R. Praca w takich strukturach może przebiegać według dwóch koncepcji polegających na (Baruk, 2009, s. 62–67):

1) przydzielaniu zadań do wykonania poszczególnym partnerom zlokalizowanym niekiedy w różnych krajach, w różnych strefach geograficznych, według modułowej struktury produktu, co oznacza, że określona jednostka odpowiada za opracowanie określonego modułu we wszystkich fazach jego rozwoju,

2) przydzielaniu zadań do wykonania poszczególnym partnerom według fazy cyklu prac B+R. W konsekwencji takiego rozdziału zadań każda organizacja należąca do sieci odpowiada za realizację innej fazy procesu B+R (np. opracowanie: koncepcji, projektu, prototypu, przeprowadzenie prób i badań itp.).

W obu przypadkach sprawność działania uwarunkowana jest zachowaniem interaktywnej komunikacji między uczestnikami procesów B+R, zapewnianej przez systemy informatyczne.

Wydaje się, że słabością dotychczas stosowanych polityk w zakresie B+R jest niewystarczające ich ukierunkowanie znajomością podstawowych relacji, takich jak:

1) produkt — technologia,

2) produkt — rynek,

i wynikających z nich strategii działalności B+R. Szczególną rolę należy przypisać strategiom ofensywnym, typowym dla wysokiej atrakcyjności rynku i wysokiej pozycji konkurencyjnych podmiotu gospodarczego.

Z uwagi na wysokie koszty prac B+R, często przekraczające możliwości finansowe pojedynczych podmiotów gospodarczych, zasadne jest ukierunkowanie polityki B+R na współpracę wielu instytucji dysponujących odpowiednimi zasobami, zwłaszcza kadrowymi (głównie w zakresie badań podstawowych i stosowanych), których brakuje w wielu przedsiębiorstwach. Zasadne jest też, w większym niż dotychczas stopniu, wspomaganie działalności B+R racjonalną polityką B+R rządu obejmującą: opracowanie rozwiązań regulacyjnych, inicjowanie programów B+R, szkoleniowych, kształtowanie infrastruktury sprzyjającej działalności B+R, kultury B+R i innowacyjnej, finansowanie lub współfinansowanie prac B+R itp.

Bibliografia

1. Barbieri, J. C., Alvares, A. C. T. (2016). Sixth generation innovation model: description of a success model. Innovation & Management Review, Vol. 13, No. 2, (116).
2. Baruk, J. (2009). Zarządzanie wiedzą i innowacjami. Toruń: Wydawnictwo Adam Marszałek w Toruniu.
3. Baruk, J. (2018). Wybrane aspekty innowacyjności przedsiębiorstw funkcjonujących w UE. Kwartalnik Nauk o Przedsiębiorstwie, nr 1, (88).
4. Baruk, J. (2016). Miejsce działalności badawczo-rozwojowej w polityce rozwojowej przedsiębiorstw. Marketing Instytucji Naukowych i Badawczych, 20 (2), (61).
5. Bogers, M. (2011). The open innovation paradox: knowledge sharing and protection in R&D collaborations. European Journal of Innovation Management, Vol. 14, No. 1, (94).
6. Chen, X., Xia, Y., Yang, J. (2018). Analysis on the Impact of Government-Enterprise Cooperation on Technological Innovation and its Economic Consequences. Business and Management Studies, Vol. 4, No. 4, (39).
7. Deloitte (2016). Badania i rozwój w przedsiębiorstwach 2016. Deloitte. (10).
8. Gloet, M., Samson, D. (2019). Knowledge and Innovation Management: Creating Value. Effective Knowledge Management Systems in Modern Society. IGI Global. Chapter 2, (20).
9. Griffin, R. W. (2007). Podstawy zarządzania organizacjami. Warszawa: Wydawnictwo Naukowe PWE.
10. GUS (2019). Nauka i Technika w 2017 r. Warszawa, Szczecin: Główny Urząd Statystyczny.
11. Li, W., Zhang, Y., Wei, Y. (2018). Management Capabilities and Corporate Environmental Performance: The Moderating Role of Top Management Team Faultlines. Science Journal of Business and Management, Vol. 6 No. 1, (22).
12. OECD (2015). Podręcznik Frascati 2015. Zalecenia dotyczące pozyskiwania i prezentowania danych z zakresu działalności badawczej i rozwojowej. Warszawa: GUS.
13. OECD (2015). Frascati Manual 2015: Guidelines for Collecting and Reporting Data on Research and Experimental Development. OECD. 2018 Statistics Poland for this Polish editio.
14. Salisu, Y., Abu Bakar, L. J. (2019). Technological Capability, Innovativeness and the Performance of Manufacturing Small and Medium Enterprises (SMEs) in Developing Economies of Africa. Journal of Business and Management, Vol. 21, No. 1, (58).
15. Strategia „Europa 2020” (2015). Ministerstwo Gospodarki. Warszawa http://www.mg.gov.pl/Bezpieczeństwo+gospodarcze/Strategia+Europa+2020 (dostęp z dnia 09.10.2015).
16. Wang, T., Chen, M. (2017). Perceiving Organisational Culture Influence on Knowledge Management Performance. Science Journal of Business and Management, Vol. 5 No. 3, (96).
17. Xie, Z., Hall, J., McCarthy, I. P., Skitmore, M., Shen L. (2016). Standardization efforts: The relationship between knowledge dimensions, search processes and innovation outcomes. Technovation, Vol. 48–49.
18. https://ec.eurostat/tgm/printTable. (dostęp z dnia 31.12.2018 r.).