American Journal of Management Vol. 25(1) 2025 117 Factors Influencing Innovative Activities in Selected Enterprises Jacek Piotr Kwasniewski MBA Business School in Bydgoszcz The article aims to analyze the factors influencing innovative activities in construction companies in Wielkopolska. As a key strategic element, innovation plays an important role in ensuring competitiveness in a dynamically developing market environment. The research was conducted on a sample of 80 companies and 5136 employees, focusing on financial outlays on innovation, technological advancement and modern material techniques. In particular, attention was paid to the relationships between these factors, the inclination to undertake innovative activities, and the influence of sociodemographic variables (gender, age, education) on the approach to innovation. The statistical analysis results showed significant correlations, confirming the importance of appropriate investments and technological resources in stimulating innovative activity. The research that was conducted emphasizes the need for further monitoring of innovation factors and adapting companies’ strategies to the changing market and technological context, which can contribute to the sustainable development of the construction sector in Poland. Keywords: innovation, innovation activities, enterprise, innovation factors INTRODUCTION This article is a continuation of research on innovation and future innovations. Because innovations play a strategic role in the success of enterprises in a dynamically changing market, only original, innovative and sometimes risky actions can give them a competitive advantage. This article analyzes the main factors that influence innovative activities in enterprises to a greater or lesser extent. Particular attention was paid to factors influencing innovative activities in construction, among which those that can shape the construction of the future were analyzed, mainly technological and economic factors, such as financial outlay on innovative activities, technological advancement (digitalization and automation of processes) and advancement in the use of modern material techniques (ecological, energy-saving and efficient). These factors were confronted with sociodemographic factors, such as: gender, age and education of employees. Other factors, such as cultural, climate change, and extreme weather phenomena, equally important, were omitted due to the limited volume of the article. The article aimed to learn about and verify the factors influencing innovative activities in construction using the example of construction companies in Wielkopolska. The research subjects were the factors influencing innovative activities in these companies, and the subjects were the aforementioned construction companies. This article attempts to answer the following questions: 1) Is there a correlation between the propensity to undertake innovative activity and expenditure on innovative activities? 118 American Journal of Management Vol. 25(1) 2025 2) Is there a correlation between the tendency to undertake innovative activities and possessing advanced technology? 3) Is there a correlation between the tendency to undertake innovative activities and modern material techniques? 4) Can variables such as education, gender and age influence the innovative attitude? The main research method was a diagnostic survey method carried out in two stages: the first stage was addressed to 5,136 employees of these enterprises and the second stage was addressed to 80 managers. The article consists of two parts. The first part discusses the types of internal and external factors influencing innovation activities. The second part is devoted to the analysis of the impact of some factors on innovation activities in selected enterprises. It presents its research methodology, indicators selected for the study and statistical analysis of the impact of selected factors on innovation activities in construction. This part determines the propensity to undertake innovation activities depending on having resources for innovation activities, advanced technology, and modern material techniques. The frequency distribution for the assessment of innovation activities in the surveyed enterprises depending on the education of the employees, their gender and age is also given. The article ends with a discussion, conclusions and a conclusion. TYPES OF FACTORS INFLUENCING INNOVATION ACTIVITIES There are many classifications of the conditions of innovation activity. According to A. Kłopotek (2002, p. 30), the greatest influence on the conduct of innovation activity in an enterprise has its external and internal environment. The author includes organizational culture, knowledge management and human resources among internal factors, and competition, customer requirements and technological changes among external factors. T. Boczko (2018, p. 235) is of a similar opinion. According to this theory, the factors of enterprise innovation can be classified as follows (Pomykalski, 2001, pp. 80-81): • resource of scientific knowledge, research and development potential (it is a source of innovation), • science development strategy, innovation policy (decides on R&D expenditure (Kilian- Kowerko, 2023, p. 6), • the structure of the country’s economy (determines the general shape of the innovation mechanism), • the system of functioning of the economy (determines the effectiveness of the innovation mechanism), • socio-psychological and cultural factors (including motives for innovative activity, such as ambition or prestige). Another classification was proposed by W. Janasz (2006, p. 340) who divided the factors of innovation into economic (analysis of innovation costs and economic risk), internal (staff level and qualifications) and other (legal regulations, procedures, standards). According to I. Bielski ( 2005, p. 10), innovation activity is shaped by external and internal factors. M. Kolarz (2006, p. 57) distinguished the following external factors of innovation: • R&D work carried out in agreement with or on behalf of external entities, • exchange of technical knowledge between enterprises and universities, • provision of services to external entities, • foreign trade, • undertaking foreign investments, • license export/import. S. Rychtowski (2004, pp. 588-589) included the following among the external conditions of enterprise innovation: • socio-political climate, • service processes including scientific research, information systems, American Journal of Management Vol. 25(1) 2025 119 • legal norms and administrative orders, • market links with partners who are a source of technology, information, • economic calculation, • education and training system, • technical infrastructure. A. Francik and A. Pocztowski (1991, pp. 26-27), like most authors, divided factors into external and internal. They included the following innovativeness factors in the group of endogenous (internal) factors: • market knowledge, • the economic strength of the enterprise and its size, • willingness to take risks, • continuity of enterprise management. The exogenous (external) factors included: • competition, • the pace of technical progress, • the upward trend of the market, • economic situation, • industry synergy regarding innovation, • state influence on the economy. The influence of the state on innovative activities may be one of the most important factors of enterprise innovation. Appropriate policy creates appropriate conditions for the functioning of enterprises and creates a research base for innovation (Mroczko, 2004, pp. 434-435). Internal factors of innovation result from various components of enterprises themselves, which determine their innovativeness. This group of factors of innovation includes factors such as (Kolarz, 2006, p. 57): • own expenditure on innovation, • own expenditure on R&D work, • effectiveness of communication and motivation systems, • staff qualifications, research and marketing experience. The authors M. Dworczyk and R. Szlasa (2001, pp. 178-180) distinguished the following factors of innovation: • innovation needs, • financial, personnel and material resources for innovative projects, • managing the implementation of innovative projects, • designing innovative solutions, • implementation of innovative projects, • expanding research and development potential, • organizing funds for innovative activities, • using the innovative potential of the staff. According to A. The following two groups of factors stimulate Linowska ( Linowska, 2011), the development of innovation: those occurring within the enterprise (innovative susceptibility) and those belonging to its environment. The author believes that the most important factors shaping the organization’s ability to innovate are ( Linowska, 2011, pp. 393-394): • the intellectual potential of employees (independence, critical thinking, creativity), • the ability to acquire scientific and technical knowledge and predict changes, • willingness to take risks, openness to the surroundings, • opportunities for support of innovative activities from the environment, Factors influencing the level of innovation occurring in the enterprise environment are (Linowska, 2011, p. 394): • investing in research and development, 120 American Journal of Management Vol. 25(1) 2025 • motivational intellectual property system, • availability of preferential credit supporting innovation, • high level of management staff, • knowledge flow between universities, • development of scientific research institutions (R&D), • creating pro-innovation policy, • efficient flow of information. The search for factors that influence the innovativeness of enterprises has been going on for a dozen or so years. A catalogue of universal factors has not yet been identified. Based on the above-mentioned theory, the following factors were adopted for research: • financial outlays for innovative activities, • technological advancement (digitization and automation of processes), • advancement in the use of modern material techniques (ecological, energy-saving and efficient), • education, age and gender of employees. Eighty enterprises employing more than 50 employees (a total of 5,136 people) were qualified for statistical analysis – Appendix Table No. 1 and 2. ANALYSIS OF THE IMPACT OF CERTAIN FACTORS ON INNOVATIVE ACTIVITIES IN SELECTED ENTERPRISES Own Research Methodology One of the most important issues in scientific research is the formulation of the research goal (Kowalska, 2016, pp. 7-8). Authors T. Pilch and T. Bauman defined the goal of scientific research as a certain action that allows for the examination of the significance of the impact of specific data (Pilch, Bauman, 2001, p. 36). This article adopted the following definition of the research goal: it is the scientific cognition of social reality, description of a phenomenon or institution or individual (Kowalska, 2016, p. 8). The article aims to learn about and verify the factors influencing innovative activities in construction using the example of construction companies located in Wielkopolska. The research subjects were the factors influencing innovative activities in these companies, and the subjects were the aforementioned construction companies. The definition of the research subject was taken from the works of AW Maszke, who assumed that these would be all phenomena subject to established processes and based on which research questions can be formulated ( Maszke, 2004, p. 44). The following research problems were adopted in this article: 1) Is there a correlation between the propensity to undertake innovative activity and expenditure on innovative activities? 2) Is there a correlation between the tendency to undertake innovative activities and the possession of advanced technology? 3) Is there a correlation between the tendency to undertake innovative activities and the use of modern material techniques? 4) Can variables such as education, gender and age influence the innovative attitude? A research problem is a question or a set of questions that will be answered after conducting the research. It concerns the research subject’s properties, conditions, dependencies, significance, and joint or exclusive impact (Kucinski, 2010, p. 84). Indicators Selected for the Study The empirical basis for the research is regional measurements carried out in the Wielkopolska province in October and December 2023. The relationship between the propensity to have resources for innovative activities, advanced technology, modern material techniques, and undertake innovative activities was analyzed within 80 enterprises and their 5,136 employees, according to education, gender, and age. The American Journal of Management Vol. 25(1) 2025 121 statistical analysis of the research results was performed using statistical tests of independence (t-Student, chi-square). The calculations were performed using Excel. Analysis of the Impact of Selected Factors on Innovative Activities in Construction The frequency distribution for the assessment of innovative activity in the surveyed construction enterprises depending on financial outlays is presented in Appendix Table No. 3. The preparation of data for calculating theoretical numbers is presented in Appendix Table No. 4. To apply the test 𝜒2 you can use the formula (Kończak, 2014, p. 41): 𝜒2 = ∑ ∑ (𝑛𝑖𝑗−𝑛𝑖𝑗 ′ ) 2 𝑛𝑖𝑗 ′ 𝑠 𝑗=1 𝑘 𝑖=1 (1) where: n ij - observed frequencies; n ij ´ - theoretical Statistical Relationships The variables: “Willingness to undertake innovative activity” and “Having resources for innovative activities” in the context of annual expenditure on innovative activity above PLN 100,000, demonstrate a statistically significant relationship: χ2 = 26.67; df = 5; significance = 0.000023 < 0.001. The variables: “Willingness to undertake innovative activity” and “Possession of advanced technology”, in the context of annual expenditure on innovative activity above PLN 100,000, demonstrate a statistically significant relationship: χ2 = 56.81; df = 5; significance = 0.000000000014 < 0.001. The variables: “Willingness to undertake innovative activity” and “Use of modern material techniques”, in the context of annual expenditure on innovative activity above PLN 100,000, demonstrate a statistically significant relationship: χ2 = 23.86; df = 5; significance = 0.000085 < 0.001. Statistical relationships for other variables: 1) by education: The frequency distribution for the assessment of innovative activity in the surveyed construction enterprises depending on the education of the employees is presented in Appendix Table No. 5. The variables: “The willingness of a given company to undertake innovative activities” and “Having resources for innovative activities” in the context of the number of employees with higher education employed there, show a statistically significant relationship: χ2 = 14.06; df = 5; significance 0,0071> 0.001 and significance 0,0071< 0.05. The variables: “The willingness of a given company to undertake innovative activities” and “Possession of advanced technology” in the context of the number of employees with higher education employed there, show a statistically significant relationship: χ2 = 12.81; df = 5; significance = 0,0122> 0.001 and significance = 0,0122< 0.05. The variables: “The willingness of a given company to undertake innovative activities” and “The use of modern material techniques” in the context of the number of employees with higher education demonstrate a strongly statistically significant relationship: χ2 = 24.10; df = 5; significance = 0,000076< 0.001. 2) by gender: The frequency distribution for the assessment of innovative activity in the surveyed construction enterprises depending on the employees’ gender is presented in Appendix Table No. 6. The variables: “The willingness of a given company to undertake innovative activities” and “Having resources for innovative activities” in the context of the gender of the employees employed there show a statistically insignificant relationship: χ2 = 7.93; df = 5; significance = 0,0941 > 0.001 and0,0941 > 0.05. The variables: “The willingness of a given company to undertake innovative activities” and “Possession of advanced technology” in the context of the gender of the employees employed there show a statistically significant correlation: χ2 = 31.21; df = 5; significance = 0,0000028< 0.001. 122 American Journal of Management Vol. 25(1) 2025 The variables: “The willingness of a given company to undertake innovative activities” and “The use of modern material techniques” in the context of the gender of the employees employed there show a statistically significant correlation: χ2 = 52.99; df = 5; significance = 0,000000000085< 0.001. 3) by age: The frequency distribution for the assessment of innovative activity in the surveyed construction enterprises depending on the age of employees is presented in Appendix Table No. 7. The variables: “The willingness of a given company to undertake innovative activities” and “Having resources for innovative activities” in the context of the age of the employees employed there show a statistically significant relationship: χ2 = 39.29; df = 5; significance =0,000000061 < 0.001. The variables: “The willingness of a given company to undertake innovative activities” and “Possession of advanced technology” in the context of the age of the employees employed there show a statistically significant relationship: χ2 = 20.40; df = 5; significance = 0,00042< 0.001. The variables: “The willingness of a given company to undertake innovative activities” and “The use of modern material techniques” in the context of the age of the employees employed there show a statistically significant relationship: χ2 = 16.77; df = 5; significance = 0,002137> 0.001, but 0,002137< 0.05. Relationship Between Having Resources for Innovation Activities and the Tendency to Undertake Innovation Activities The relationship between having resources for innovation activities and the willingness to undertake innovation activities was indicated most highly by people with higher education (52% - very high and high), then by men (50%) and people under 40 years of age (27%) – FIGURE 1. FIGURE 1 THE RELATIONSHIP BETWEEN HAVING RESOURCES FOR INNOVATION ACTIVITIES AND THE TENDENCY TO UNDERTAKE INNOVATION ACTIVITIES (BASED ON OWN RESEARCH RESULTS) The least likely to undertake innovative activities are people over 40 (49% – very low and low) and women (23%). The Relationship Between Having Advanced Technology and the Tendency to Undertake Innovative Activities The relationship between having advanced technology and the tendency to undertake innovative activities was indicated most highly by people with higher education (56% - very high and high), then by men (42%) and people under 40 years of age (26%) – FIGURE 2. 17.43 29.26 30.47 16.53 6.31 18.12 32.19 29.08 15.18 5.43 8.21 19.29 27.78 28.32 16.4 6.45 14.87 29.47 27.53 21.68 29.12 23.38 23.29 18.03 6.18 28.02 24.23 27.78 15.26 4.71 Very high High Average Low Very low Women Men Under 40 Over 40 Higher education Other education [%] American Journal of Management Vol. 25(1) 2025 123 FIGURE 2 THE RELATIONSHIP BETWEEN POSSESSION OF ADVANCED TECHNOLOGY AND THE TENDENCY TO UNDERTAKE INNOVATIVE ACTIVITIES (BASED ON OWN RESEARCH RESULTS) The least likely to undertake innovative activities were people over 40 years of age (45% – very low and low) and women (36%). The Relationship Between the Use of Modern Material Techniques and the Tendency to Undertake Innovative Activities The relationship between the use of modern material techniques and the tendency to undertake innovative activities was indicated most highly by people with higher education (53% - very high and high), then by men (38%) and people under 40 years of age (31%) – FIGURE 3. FIGURE 3 THE RELATIONSHIP BETWEEN THE USE OF MODERN MATERIAL TECHNIQUES AND THE TENDENCY TO UNDERTAKE INNOVATIVE ACTIVITIES (BASED ON OWN RESEARCH RESULTS) 11.55 23.31 29.31 26.57 9.26 12.25 29.42 25.54 25.36 7.43 7.85 18.58 33.16 26.98 13.43 6.61 16.68 31.3 27.93 17.48 27.9 27.69 23.12 15.51 5.78 26.62 23.81 25.1 16.36 8.11 Very high High Average Low Very low Women Men Under 40 Over 40 Higher education Other education [%] 12.67 19.15 30.75 22.97 14.46 10.42 27.56 28.92 20.76 12.34 5.76 25.84 29.35 21.79 17.26 6.22 22.57 27.7 22.47 21.04 27.31 26.18 25.13 16.23 5.15 24.92 22.32 26.01 17.5 9.25 Very high High Average Low Very low Women Men Under 40 Over 40 Higher education Other education [%] 124 American Journal of Management Vol. 25(1) 2025 The least likely to undertake innovative activities are people over 40 (43% – very low and low) and women (33%). DISCUSSION Many scientists have researched the factors influencing innovative activities in enterprises. Polish researchers of this phenomenon have mostly been described in the section on the types of factors influencing innovative activities (K. Szopik-Depczyńska 2006, A. Wziątek-Kubiak and E. Balcerowicz 2009, A. Linowska 2011, A. Rojek 2017, E. Stawasz 2014, E. Michalski 2015, M. Jakubiec 2016). Among foreign authors, we can distinguish VG Vol’ka 2104, M. Ehrenberg, P. Koudelkova and W. Strielkowski 2015. A. Wziątek-Kubiak and E. Balcerowicz (2009, p. 57) analyzed the determinants of the development of a company’s innovativeness in the context of the level of education of employees. The authors showed that the key factor of innovativeness is the level of education of employees, which, according to the authors, results from its complementary role to other innovation factors. This factor is the main source of knowledge accumulation. Therefore, it has a priority significance for the ability to absorb, create, introduce and implement innovations. VG Vol’ka (2104, pp. 134-135) studied the factors that influenced the innovativeness of enterprises. The author proved their relationship and mutual influence. He constructed graphic reflections on the influence of external and internal environmental factors on the innovative features of the enterprise. He distinguished the factors of indirect influence (political, legal, economic, scientific-technical, social and natural-climatic) and direct (suppliers, consumers, employees). He introduced a system of internal and external environmental factors that influence the innovativeness of the enterprise and determined their influence on the main features of innovation. By analyzing these factors, he proved that it is possible to reduce the uncertainty of the environment to improve the enterprise management level. Factors influencing innovation in small and medium-sized enterprises were the subject of interest of M. Ehrenberg, P. Koudelkova and W. Strielkowski (2015, pp. 81-82). The authors analyzed data from surveys among 1,144 small- and medium-sized enterprise employees. The authors presented the following as key factors of innovation: the legal form of the enterprise (limited liability companies are more innovative than other legal forms), government support for investment activities, employee education and export expansion into new markets. Azimovna and UD Ilkhomovna (2022, pp. 146-148) dealt with the factors influencing the innovation activity of industrial enterprises. The authors emphasized the importance of external factors in innovation activity, which may be the subject of business strategy, coordinated social actions or public policy. They analyzed factors such as environmental or contextual, spatial and locational, related to the external market, the flow of knowledge, politics and the natural environment. None of the cited authors conducted a statistical calculation of the actual impact of the examined factors on the enterprise’s innovativeness. CONCLUSIONS The results of the research confirm that innovative activities in selected construction companies in Wielkopolska are strongly related to specific financial and technological factors. Statistical analysis showed significant relationships between financial outlays on innovation and the tendency to undertake innovative activities, which indicates the importance of appropriate investments in the development of innovation in this industry. Thanks to the applied methodology, it was possible to answer the problematic questions posed at the beginning concerning the impact of advanced technology and modern material techniques on innovation activity, which confirms the thesis that enterprises that invest in technologies and modern materials are more likely to implement innovative projects. Observations on the impact of sociodemographic factors, such as gender, age and education, on the innovativeness of enterprises, although less clear, still indicate significant differences in the approach of American Journal of Management Vol. 25(1) 2025 125 different groups of employees to innovation. The analysis shows that younger generations and people with higher education show greater openness to innovation and willingness to engage in innovative activities. Certainly, further research on innovation factors in various economic sectors should also take into account the cultural and regulatory context, as well as the development of pro-innovation policy, which may influence the shaping of an innovation-friendly environment. The research indicates a significant correlation between financial outlays on innovation and the willingness to undertake innovative activities in enterprises. High investments in technologies and modern materials are conducive to implementing innovative projects. Enterprises with advanced technology and modern material techniques demonstrate greater innovation activity. This phenomenon suggests that the development and adoption of new technologies are necessary to stimulate innovation in the construction industry. Analysis of the impact of sociodemographic variables, such as gender, age and education, reveals certain differences in the approach to innovation. Younger people and employees with higher education are more likely to engage in innovation activities, which may indicate changes in attitudes and skills among various social groups. The author of the article emphasizes the need to continue research on innovation factors, taking into account the cultural and regulatory context. The construction sector requires continuous adjustment of strategies to changing market and technological conditions, which is important for sustainable development. The conclusions suggest that pro-innovation policy and state support are key to creating favourable conditions for innovation development. Effective actions can increase Polish enterprises’ competitiveness in domestic and international markets. Innovations are a key element of competitiveness strategy. Construction companies that effectively implement modern solutions can gain an advantage over the competition, which directly impacts their development and the industry’s sustainable development. Innovation in the construction sector in Wielkopolska is closely related to appropriate investments, technologies, and human resources, and diverse approaches to innovation depend on sociodemographic factors. The article indicates the need for an active and comprehensive approach to innovation in construction companies, favoring their long-term competitiveness. REFERENCES Azimovna, M.S., Ilkhomovna, U.D. (2018). Measuring external factors influencing innovation in companies. OSLO MANUAL - OECD/European Union, pp. 145–162. Baczko, T. (2018). Product innovations. Polish Academy of Sciences, 3, 22–251. Baj, W., & Pietucha, I. (2006). Factors stimulating the creation of innovations in an enterprisem. Przegląd Organizacji, 7/8, 32–36. Bielski, I. (2005). Factors influencing innovativeness. Nowator, 21(1), 10–12. Central Statistical Office. (2022). Innovation activity of enterprises in Poland in 2019-2021. Warsaw. Decision No 1608/2003 of the European Parliament and of the Council of 22 July 2003 concerning the production and development of Community statistics on science and technology. Dworczyk, M., & Szlasa, R. (2001). Innovation management. PW, Warsaw. 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Age Under 40 years old 3015 58.7 Over 40 years old 2121 41.2 2. Sex Woman 2517 49.0 Man 2619 51.0 3. Education Higher 1004 19.5 Other 4132 80.4 4. Sources of innovation The work of management staff 2465 48.0 Customers, suppliers, competitors 2003 39.0 Purchase of license 360 7.0 Other 308 6.0 5. Annual number of implemented innovations 1-3 5008 97.5 4-6 103 2.0 Above 6 25 0.5 6. Type of implemented innovations Product 192 3.7 Process 32 0.6 Marketing 1241 24.1 Organizational 3139 61.1 Imitation-adaptive 532 10.3 7. Information and communication technologies 1264 24.6 Renewable energy 2342 45.6 Logistics 978 19.0 American Journal of Management Vol. 25(1) 2025 127 Areas of Planned Future Innovations Artificial intelligence 320 6.2 Decentralized Data Registry 232 4.5 8. Type of planned future innovations Robotics 132 2.5 5G connectivity 2821 54.9 Smart sensors 1813 35.3 Intelligent production or service implementation systems 176 3.4 Augmented reality 28 0.5 Digital twin 89 1.7 Additive manufacturing 54 1.0 TABLE 2 SUMMARY OF SURVEY RESULTS FROM OWN RESEARCH (PART OF THE SURVEY COMPLETED BY MANAGERS) 1. Annual financial outlays for innovation activities < 10,000 6 7.5 11,000 to 100,000 60 75.0 101,000 to 1,000,000 12 15.0 > 1,000,000 2 2.5 2. Technological advancement (digitization and process automation) Very high 3 3.7 High 16 20.0 Medium 52 65.0 Low 5 6.2 Very low 4 5.0 3. Advancement in the use of modern material techniques (ecological, energy-saving and efficient) Very high 9 11.2 High 15 18.7 Medium 42 52.5 Low 8 10.0 Very low 6 7.5 128 American Journal of Management Vol. 25(1) 2025 TABLE 1 FREQUENCY DISTRIBUTION FOR THE ASSESSMENT OF WILLINGNESS TO UNDERTAKE INNOVATIVE ACTIVITY, ACCORDING TO EXPENDITURE ON INNOVATIVE ACTIVITIES (OWN STUDY BASED ON TABLE 1) Willingness to undertake innovative activities Having resources for innovation activities Possession advanced technology Use of modern material techniques Annual expenditure over 100,000 PLN The remaining Annual expenditure over 100,000 PLN The remaining Annual expenditure over 100,000 PLN The remaining n % n % n % n % n % n % Very high 8 (2) 57.2 4 (10) 6.1 7 (1) 50.0 0 (6) 0 6 (1) 42.8 2 (7) 3.0 High 3 (2) 21.4 9 (10) 13.6 5 (1) 35.8 2 (6) 3.0 3 (2) 21.4 7 (8) 10.6 Mean 2 (4) 14.2 22 (20) 33.4 1 (4) 7.1 23 (20) 34.8 3 (5) 21.4 23 (21) 34.8 Low 1 (4) 7.2 19 (17) 28.8 1 (5) 7.1 25 (21) 37.9 2 (5) 14.2 25 (22) 37.8 Very low 0 (2) 0.0 12 (10) 18.1 0 (3) 0.0 16 (13) 24.3 0 (2) 0.00 9 (7) 13.6 Total: 14 100 66 100 14 100 66 100 14 100 66 100 () – theoretical numbers American Journal of Management Vol. 25(1) 2025 129 TABLE 4 PREPARATION OF DATA FOR CALCULATING THEORETICAL NUMBERS (OWN STUDY BASED ON TABLE 1) Willingness to undertake business activity Having resources for innovation activities Possession advanced technology Use of modern material techniques Annual expenditure over 100,000 PLN The remaining SUM Annual expenditure over 100,000 PLN The remaining SUM Annual expenditure over 100,000 PLN The remaining SUM Very high 8 4 12 7 0 7 6 2 8 High 3 9 12 5 2 7 3 7 10 Mean 2 22 24 1 23 24 3 23 26 Low 1 19 48 1 25 26 2 25 27 Very low 0 12 96 0 16 16 0 9 9 Total: 14 66 192 14 66 80 14 66 80 TABLE 5 FREQUENCY DISTRIBUTION FOR THE ASSESSMENT OF WILLINGNESS TO UNDERTAKE INNOVATIVE ACTIVITIES IN CONSTRUCTION ENTERPRISES, ACCORDING TO EMPLOYEE EDUCATION (OWN STUDY BASED ON TABLE 1) Willingness to undertake innovative activities Having resources for innovation activities Possession advanced technology Use of modern material techniques Higher education Other Higher education Other Higher education Other n % n % n % n % n % n % Very high 292 (283) 29.12 1158 (1167) 28.02 280 (270) 27.9 1100 (1110) 26.62 274 (255) 27.31 1030 (1049) 24.92 High 235 (242) 23.38 1001 (994) 24,23 278 (247) 27.69 984 (1015) 23.81 263 (232) 26.18 922 (953) 22.32 Mean 234 (270) 23.29 1147 (1112) 27.78 232 (248) 23.12 1037 (1021) 25.1 252 (259) 25.13 1075 (1068) 26.01 Low 181 (159) 18.03 631 (653) 15.26 156 (163) 15.51 676 (669) 16.36 163 (173) 16.23 723 (713) 17.5 Very low 62 (50) 6.18 195 (206) 4.71 58 (77) 5.78 335 (316) 8.11 52 (85) 5.15 382 (349) 9.25 Total: 1004 100 4132 100 1004 100 4132 100 1004 100 4132 100 130 American Journal of Management Vol. 25(1) 2025 TABLE 2 FREQUENCY DISTRIBUTION FOR THE ASSESSMENT OF WILLINGNESS TO UNDERTAKE INNOVATIVE ACTIVITIES IN CONSTRUCTION ENTERPRISES, BY EMPLOYEE GENDER (OWN STUDY BASED ON TABLE 1) Willingness to undertake innovative activities Having resources for innovation activities Possession advanced technology Use of modern material techniques Men Women Men Women Men Women n % n % n % n % n % n % Very high 475 (466) 18.2 439 (448) 17.4 321 (312) 12.2 291 (300) 11.5 273 (302) 10.4 319 (290) 12.7 High 843 (805) 32.2 736 (774) 29.3 771 (692) 29.5 587 (666) 23.4 722 (614) 27.6 482 (590) 19.2 Mean 761 (779) 29.1 767 (749) 30.5 668 (717) 25.6 738 (689) 29.4 757 (781) 28.9 774 (750) 30.8 Low 398 (415) 15,1 416 (399) 16.5 664 (679) 25.3 668 (653) 26.5 544 (572) 20.8 578 (550) 22.9 Very low 142 (153) 5.4 159 (148) 6.3 195 (218) 7.4 233 (210) 9.2 323 (350) 12.3 364 (337) 14.4 Total: 2619 100 2517 100 2619 100 2517 100 2619 100 2517 100 American Journal of Management Vol. 25(1) 2025 131 TABLE 7 FREQUENCY DISTRIBUTION FOR THE ASSESSMENT OF WILLINGNESS TO UNDERTAKE INNOVATIVE ACTIVITIES IN CONSTRUCTION ENTERPRISES, BY EMPLOYEE AGE (OWN STUDY BASED ON TABLE 1) Willingness to undertake innovative activities Having resources for innovation activities Possession advanced technology Use of modern material techniques Age below 40 years Age over 40 Age below 40 years Age over 40 Age below 40 years Age over 40 n % n % n % n % n % n % Very high 248 (226) 8.2 137 (159) 6.4 237 (221) 7.89 140 (156) 6.6 174 (179) 5.8 132 (126) 6.2 High 582 (527) 19.3 315 (370) 14.9 560 (537) 18.7 354 (377) 16.7 779 (738) 25.8 479 (519) 22.6 Mean 838 (859) 27.8 625 (604) 29.5 1000 (977) 33.1 664 (687) 31.4 885 (864) 29.3 588 (608) 27.7 Low 853 (844) 28.3 584 (594) 27.5 813 (825) 26.9 592 (581) 27.9 657 (665) 21.8 476 (468) 22.5 Very low 494 (560) 16.4 460 (394) 21.7 405 (455) 13.4 371 (320) 17.4 520 (567) 17.3 446 (399) 21.0 Total: 3015 100 2121 100 3015 100 2121 100 3015 100 2121 100