What Shapes Innovation Capability in Micro-Enterprises? New-to-the-Market Product and Process Perspective

: Innovation is an essential driver of companies’ growth and is important in securing and sustaining their competitive advantage and in the implementation of their entire strategies. In this process, a special role is played by companies’ capabilities, especially those related to innovation capability (IC). Despite many years of research into identifying the factors that inﬂuence IC, there are still many research gaps. One such concerns the IC of micro-enterprises. Only a few studies indicate certain factors that may affect micro-enterprise ICs. Thus, this article aims to analyse the determinants of micro-enterprises’ ICs from the perspective of implementing new-to-the-market product and process innovations. The theoretical framework adopted distinguishes between three groups of factors affecting micro-enterprise IC: personal, organizational and external environmental characteristics. The data examined come from an empirical study of a randomly selected representative sample of 1105 Polish micro-enterprises. To analyse these data, a logistic regression model was used. The results indicate that seven factors are common and signiﬁcant determinants that explain the new-to-the-market product and process dimensions of micro-enterprise IC. Among them, the following have the greatest inﬂuence: engagement in initiatives for solving social problems, intensive cooperation with research centers, experience/skills and ﬁnancial support.


Introduction
The search to find an answer to the question of how to build an enterprise's innovation potential is still ongoing [1][2][3]. This is especially important in the context of many opinions that a firm's success often depends on its ability to innovate [4]. Despite many years of research into identifying the factors that influence this process, there are still many research gaps. One of these gaps concerns the innovativeness of micro-enterprises. Although such enterprises are usually the most numerous entities in modern economies (EU-28-93% in 2018; Poland-96.4% in 2020) [5,6], they are ignored in most research on innovation, e.g., in the European Union Community Innovation Survey [7]. Only a few studies, such as those by Plotnikova et al. Romero [8][9][10][11][12][13]. The aim of this paper is to shed additional light on this issue.
Since Schumpeter [14] indicated that the individual person, by combining the factors of production to create something new, is a key part of creative destruction-the essential driver of economic development-innovativeness has become a crucial feature of entrepreneurship. Consequently, innovation has become one of the features by means of which we distinguish a true entrepreneur from ordinary business owners [15] or leaders from followers [16]. According to Roper and Hewitt-Dundas, micro-and small entrepreneurial companies, in accordance with Schumpeter's theory of creative destruction, are at the centre of the innovation process [10]. Despite this perspective, studies on microand small companies' innovativeness are still limited [17]. Roper and Hewitt-Dundas even Table 1. Summary of the literature on innovative capability.

Author(s) Innovative Capability-Concept or Definition Features or Elements
Lawson and Samson, 2001 [31] Innovation capability is defined as the ability to continuously transform knowledge and ideas into new products, processes and systems for the benefit of a firm and its stakeholders.
Romijn and Albaladejo, 2002 [26] Innovation capability is defined as the skills and knowledge needed to effectively absorb, master and improve existing technologies, and to create new ones. The innovation capability of a firm accumulates as a result of the various internal and external inputs.
Elements of the conceptual framework: (1) Innovation capability-concerns product innovations and is measured by: product innovation during the last 3 years, number of patents and product innovation index (innovative outputs generated during the 3 years prior to the survey); (2) Internal sources-professional background of founder/manager(s), skills of workforce, internal efforts to improve technology, (3) External sources-intensity of networking, proximity advantages related to networking, receipt of institutional support. Calantone et al., 2002 [30] Innovation capability is the most important determinant of firm performance. It is connected with organizational learning and is associated with the development of new knowledge.
Guan and Ma, 2003 [18] Innovation capability is a special asset of a firm. It is tacit and non-modifiable and is correlated closely with interior experiences and experimental acquirements. Innovation capability consists of core innovation assets-the ability of a firm to translate innovation concepts through R&D, manufacturing and marketing process and supplementary innovation assets-the ability of a firm to support and harmonize core innovation capability to play its role effectively.
Innovative capability consists of dependent and autonomous innovative capability and is measured by: (1) percent sales of products manufactured according to the design specification of the parent company, (2) percent sales of products using original equipment manufacturing, Innovation capability refers to a firm's ability to continuously transform knowledge and ideas into new products, processes and systems for the benefit of the firm.
Attributes of innovation capability: (1) service quality management system, (2) entering into newer service routes, (3) regularly improve company's operational systems, (4) exploring best methods to achieve corporate goals, (5) employee reward system for innovative ideas.

Author(s) Innovative Capability-Concept or Definition Features or Elements
Forsman, 2011 [22] Innovation capacity is composed of internal resources, capabilities and external input gained through networking.
Dimensions of innovation capabilities: (1) knowledge exploitation, (2) entrepreneurial capabilities, Innovation is a dynamic capability, i.e., a learned and stable pattern of collective activity through which the organization systematically generates and modifies its operating routines in pursuit of improved effectiveness.
Rajapathirana and Hui, 2018 [63] Innovation capability is considered as a valuable asset for firms to provide and sustain a competitive advantage and in the implementation of overall strategy.
Zhang and Merchant, 2020 [34] Innovation capability is the ability to create better or more effective products, processes, services, technologies or ideas that are accepted by markets, governments and society.
Items of innovation capability construct: (1) firm uses knowledge from different sources for product development activities efficiently and rapidly; (2) firm supports and encourages workers to participate in activities, such as product development, innovation process improvement and idea generation; (3) firm continuously evaluates new ideas that come from customers, suppliers, etc., and includes them in product development activities; (4) firm can adapt to environmental changes easily by making suitable improvements and innovations in a short time.
Walter et al., 2021 [64] Innovation capability in the context of open innovation is the ability of companies to acquire, generate and apply knowledge.

The Personal Characteristics of a Micro-Enterprise's Owner or Manager
Personal characteristics appear in many studies [65]. Martinez-Roman et al. indicate that when studying the innovativeness of the self-employed, it is worth analysing their general and business education as well as their motivation and previous experience as an employee [9]. Plotnikova et al. point to the same features but in the context of small businesses and the implementation of process innovations [8]. A manager's, business owner's or entrepreneur's educational background was underlined by Koellinger as an important factor explaining innovation in small businesses [66]. In turn, being a university graduate was analysed as a factor in SME innovativeness by Martinez-Roman et al. [24]. Roper et al. analysed the drivers of new-to-market innovations in micro-enterprises and researched the gender (female), background, university education and age of entrepreneurs [10]. In turn, Zastempowski and Cyfert examined the impact of entrepreneur gender on innovation activities from the perspective of small businesses [67]. Dobić et al. examined the gender, age, education and experience in the context of employees' intellectual agility and its influence on SMEs innovativeness [68]. De Martino et al. also indicate the importance of qualified staff [69]. In turn, from the perspective of open innovation, Naz et al. indicate the role of proactive personalities [70].
In light of the above, and from the perspective of the two analysed IC dimensions, it is possible to formulate the following research question: RQ 1. Do the personal characteristics of a micro-enterprise owner or manager exert an impact on the new-to-the-market product and process dimensions of innovation capability?
Organisational characteristics are given various names and consist of various elements. Malik et al. researched them in the context of Quadruple Helix [78]. Adler and Shenhar, analysing the dimensions of an organization's technological capability, describe two internal assets: technological and organizational [79]. Among the important categories of organizational characteristics of the capacity to innovate, Hurley and Hunt indicated structural and process characteristics, as well as cultural characteristics [32]. In turn, Guan and Ma divided interorganizational IC capabilities into the seven following dimensions: learning, R&D, manufacturing, marketing, organizational, resource exploitation and strategic capability [18]. The same approach can be found in research by Yam et al. [43,51] and Yang [52], and a similar approach is presented in research by Wang et al. [80]. In the context of open innovation, Walter et al. suggest the importance of intangible assets [64].
Assink, who analysed disruptive innovation capability, focused on such endogenous determinants as resources, corporate structure and corporate culture [81], while Martinez-Roman et al., in their description of the SME innovative capability-based model, distinguished three IC determinants-knowledge, organization and the human factor [24,57]. Also inspiring is the proposition of Saunila and Ukko, who divided IC factors into external knowledge, work climate and well-being, ideation and organizing structures, regeneration, participatory leadership culture, individual activity and know-how development [55]. Huarng et al. indicated that knowledge is the source of innovation and new knowledge is an antecedent of innovation [82]. Dyduch et al. emphasised the role of dynamic capabilities, value creation and value capture [83], while Cyfert et al. highlighted the role of the developing dynamic capabilities process [84,85]. In turn, Rajapathirana and Hui indicated the following determinants of innovation capability: organizational culture, use of knowledge from different sources, involvement of workers and customers, etc. [63]. Dziallas and Blind, analysing innovation indicators throughout the innovation process, pointed to the following company-specific dimensions: strategy, innovation culture, competence and knowledge, organizational structure, R&D activities and input, and financial performance [86].
As can be seen above, organisational characteristics appear as IC determinants in a number of studies conducted so far. As a consequence, the following research question can be formulated: RQ 2. Do the organisational characteristics of a micro-enterprise exert an impact on the new-to-the-market product and process dimensions of innovation capability?

External Environmental Characteristics
External environmental characteristics-the last group of IC determinants-are also examined in many studies [23]. A review of the literature shows that in this area there is also a lot of diversity. Jenson et al. suggested four major approaches to the study of innovation systems: national, regional, sectoral and technological [103]. Russell, who explored innovation in organizations, focused on the phenomenon of environmental uncertainty [58]. The same approach can be found in the research of Özsomer et al. [104]. Adler and Shenbar analysed the relations that a firm establishes with current and potential allies, rivals, suppliers, consumers, political actors and local communities [79]. Romijn et al. and Bessant et al. perceived the important role of the intensity of networking and proximity advantages related to networking [26,105]. In turn, Quintana-Garcia et al. drew attention to the various relations among competitors [44]. Gupta et al. analysed the relation between marketing innovations and competitiveness [28]. Zhao et al., exploring the determinants of IC, suggested that a significant role was played by the competitive environment [33]. In addition, Assink [81] and Martinez-Roman et al. [24] note the role of rivalry and competition dynamics. Xu et al. and De Martino et al. analysed the financial support for SMEs [69,106] and Veronica et al. analysed government support for firms' international growth [107]. Recently, scholars have also suggested the need to focus more on the external determinants of open innovation in order to increase the competitiveness of economies [64,108].
It is worth underlining that many researchers analysing external conditions concentrate, also, on the VUCA environment [109], the different aspects of cooperation [110], environmental and climatic changes [111], ecology [112], sustainable development [113], renewable and green energy [111,114], green innovation [115] and climate neutrality [116]. It is also worth emphasizing the important role of Porter's theory of competitive advantage [117,118].
In light of the above, the following research question can be formulated: RQ 3. Do external environmental characteristics exert an impact on the new-to-themarket product and process dimensions of innovation capability?

Conceptual Model
Finally, the literature review presented above suggests the following factors within each group of possible IC determinants seen from the perspective of micro-enterprises. The results of this work are shown in Table 2.  As a consequence, the following conceptual model was formulated ( Figure 1). Its structure was mainly inspired by the models of Russell [58], Hurley and Hult [32], Martinez-Roman et al. [9,24] and Mendoza-Silva [23]. As a consequence, the following conceptual model was formulated ( Figure 1). Its structure was mainly inspired by the models of Russell [58], Hurley and Hult [32], Martinez-Roman et al. [9,24] and Mendoza-Silva [23].

Data Collection and Sample
The As can be seen in Table 3, the surveyed sample represented all types of economic activity. Only two of these had a higher representation than in the REGON register-manufacturing (22.6%) and wholesale and retail trade (5.85%)-while one had lower representation, namely, transport and storage (4.11%).  Table 4 presents the description, label and scale for all of the variables included in the model. As can be observed, the final model includes: (1) explained variables, labelled from y 1 to y 3 , and (2) explanatory variables, labelled from x 1 to x 19 and divided into four groups: personal characteristics of micro-enterprise owners or managers, organizational characteristics, external environmental characteristics and control variables. The descriptive statistics of all variables are presented in Table 5.

Method
Due to the fact that the explained variables were dichotomous, binary regression was used to estimate the models. The most common binary regression models are the logit model (logistic regression) and the probit model (probit regression). Both of these methods are frequently used to test the influences of the explanatory variables on the dichotomous innovation variables [8,9]. In this study, the logistic regression method was used.
The logistic regression model is of the form: . The subjects of estimation in this model are the parameters β 0 , β 1 , β 2 , . . . , β k , these being elements of the vector β [127].
To interpret the results of the logit model estimation, odds ratios (ORs) were used. If the likelihood is denoted as: then the odds ratios with the variable X mi increase by a unit and the odds without this increase equal: where x m i is the vector x i without the variable X mi . Formula (3) shows that the increase in the value of X mi by one unit is related, ceteris paribus, to an exp(β m )-fold change in the odds ratio. In the case of exp(β m ) > 1, there is an increase, and, in the case of exp(β m ) < 1, there is a decrease in the odds ratio.
The maximum likelihood estimation method was used to estimate the models. All analyses were made on the basis of STATA 16.1 software.

Results
In the first step, using Kendall's tau-b coefficient, the correlation between all the variables was analysed. The results are presented in Table 6.
As can be seen, many correlation coefficients between the explanatory and explained variables are statistically significant. Nevertheless, the coefficients are always below 0.2, so the relationship is very poor. Moreover, the coefficients among the explanatory and control variables are below 0.5, indicating that multicollinearity in not a concern. In the next step, in order to eliminate common method variance (CMV) bias, Harman's single factor test was checked. The results showed that a single factor explained 25.3% of variance, so there is no CMV bias [128].
The results of the estimations for new-to-the-market product innovation (y 1 ) are presented in Table 7, for new-to-the-market process innovation (y 2 ) in Table 8 and for both types of new-to-the-market innovations together (y 3 ) in Table 9. Robust standard errors (S.E.) are presented in the tables. Table 7. Logistic regression for new-to-the-market product innovation (y 1 ).    Firstly, the basic model is presented in each case, which is built on variables related to personal characteristics (Model 1). Next, a second estimation is put forward which includes organizational characteristics as regressors (Model 2). In the third step, the estimated model also contains external environmental characteristics (Model 3). After this, in the final model, the control variables were also included (Model 4). As the percentages of correct predictions (94.03% for y 1 , 94.21% for y 2 and 95.66% for y 3 ) and pseudo-R2 vales (0.2082 for y 1 , 0.2304 for y 2 and 0.2297 for y 3 ) show, all these additions improved the goodness of fit of the estimations.

Model
The significance of all the estimated models was assessed by the pseudolikelihood ratio test. The obtained results show that each of the estimated models (y 1 , y 2 , y 3 ) was significant. The goodness of fit between the estimated models and the data was also analysed. Consequently, the accuracy of forecasting on their basis was checked. Such prediction is based on the estimated probabilityp l , which is a function of F x iβ . It is usually assumed that if F x iβ ≥ 0.5, then the prediction equalsŷ l = 1. If F x iβ < 0.5, then the forecast from the model is equal toŷ l = 0. The results are shown in Tables 7-9.
For the final model 4, the ROC curve was also used. The area under the ROC curve for the y 1 model 4 was 0.8422, 0.8497 for y 2 and 0.8633 for y 3 . The results are shown in Figure 2. The significance of all the estimated models was assessed by the pseudolikelihood ratio test. The obtained results show that each of the estimated models (y1, y2, y3) was significant. The goodness of fit between the estimated models and the data was also analysed. Consequently, the accuracy of forecasting on their basis was checked. Such prediction is based on the estimated probability , which is a function of . It is usually assumed that if 0.5, then the prediction equals = 1. If < 0.5, then the forecast from the model is equal to = 0. The results are shown in Tables 7-9. For the final model 4, the ROC curve was also used. The area under the ROC curve for the y1 model 4 was 0.8422, 0.8497 for y2 and 0.8633 for y3. The results are shown in Figure 2. The odds ratios for the regression coefficients for each of the final model 4 results are presented in Table 10.  The odds ratios for the regression coefficients for each of the final model 4 results are presented in Table 10.  8 1.184 1.069 1.229 ** x 9 1.115 1.235 ** 1.264 ** x 10 1.072 1.062 1.028 x 11 1.054 1.154 1.068 The results in Tables 7-9 show that three variables are common, statistically significant factors, at a confidence level of either 0.05 or 0.01, explaining both the new-to-the-market product and process innovations (y 3 ) in model 4: experience/skills (x 4 ), engagement in initiatives for solving social problems (x 12 ) and financial support (x 15 ). It is worth underlining that, in the case of x 4 and x 15 , the value is negative.
However, some differences can be found between the determinants of new-to-themarket product and process innovations. Thus, the variable concerning work climate (x 6 ) is significant for new-to-the-market product innovation but not for new-to-the-market process innovation. In turn, good coordination of cooperation between employees (x 9 ) and intensive cooperation with research centres (x 16 ) and other companies (x 17 ) are significant variables for new-to-the-market process innovation but not for product innovation.
It is worth underlining that one of the control variables, size (x 21 ), turned out to be a statistically significant factor for both analysed IC dimensions. Interestingly, it showed a negative impact. Thus, each additional employee in a micro-enterprise reduces its chance for new-to-the-market product and process innovation. In turn, the second control variable, age of enterprise (x 20 ), is statistically significant in the case of new-to-the-market product innovation (with a positive sign).
Next, let us concentrate on those micro-enterprises that introduced both new-to-themarket product and process innovations (Table 9). In this case the statistically significant variables, at the confidence level of either 0.05 or 0.01, are the following: experience/skills (x 4 ), with a negative sign; having a marketing unit (x 8 ); good coordination of cooperation between employees (x 9 ); engagement in initiatives for solving social problems (x 12 ); financial support (x 15 ), with a negative sign; intensive cooperation with research centres (x 16 ) and with other companies (x 17 ), with a negative sign. As indicated earlier, one control variable-size (x 21 )-is significant here. Additionally, supporting employees in improving their qualifications (x 6 ) and having a research and development unit (x 7 ), both with negative signs, are marginally significant factors influencing the introduction of both new-to-the-market product and process innovations (with a confidence level of 0.10).
As shown in Figure 3, among them, the largest odds ratios have, with increasing chances, engagement in initiatives for solving social problems (x 12 ) and intensive cooperation with research centres (x 16 ), and, with decreasing chances, experience/skills (x 4 ) and financial support (x 15 ).

Discussion
The main objective of this paper was to analyse the determinants of two dimensions of innovation capability-new-to-the-market product and process innovation-among micro-enterprises. The proposed conceptual model divided the possible determinants into three groups: personal, organisational and external environmental characteristics of micro-enterprises.
Looking at the obtained results from the perspective of the first research question, it should be noted that it is difficult to give an unambiguous answer for several reasons.
Only one of the analysed personal characteristics of micro-enterprise owners and managers had an impact on the new-to-the-market product and process dimensions of micro-enterprise innovation capability, i.e., experience/skills (x4). However, the impact turned out to be negative. There is a lower likelihood of owners or managers with more experience introducing new-to-the-market product and process innovations in micro-enterprises. This is probably due to the fact that more experienced micro-enterprise owners or managers are attached to more traditional business models. Hurley and Hunt suggest, also, that this may be related to the fact that, the older the organization, the more bureaucratic and the less receptive it is to innovation [32]. Perhaps it is also the result of a decline

Discussion
The main objective of this paper was to analyse the determinants of two dimensions of innovation capability-new-to-the-market product and process innovation-among micro-enterprises. The proposed conceptual model divided the possible determinants into three groups: personal, organisational and external environmental characteristics of micro-enterprises.
Looking at the obtained results from the perspective of the first research question, it should be noted that it is difficult to give an unambiguous answer for several reasons.
Only one of the analysed personal characteristics of micro-enterprise owners and managers had an impact on the new-to-the-market product and process dimensions of microenterprise innovation capability, i.e., experience/skills (x 4 ). However, the impact turned out to be negative. There is a lower likelihood of owners or managers with more experience introducing new-to-the-market product and process innovations in micro-enterprises. This is probably due to the fact that more experienced micro-enterprise owners or managers are attached to more traditional business models. Hurley and Hunt suggest, also, that this may be related to the fact that, the older the organization, the more bureaucratic and the less receptive it is to innovation [32]. Perhaps it is also the result of a decline in creativity and a growing reluctance to change. This type of relationship is indicated by Berkeley psychologists, who suggest that creativity generally tends to decline as we age [129].
Another interesting result is the lack of impact on the introduction of new-to-themarket product and process innovation exerted by business education, as research in the field of self-employed innovativeness, e.g., by Martinez-Roman et al., shows that there is such a relationship [9].
It is also worth noting that, in the case of model 1 (y 1 -y 3 ), gender (x 1 ) also turned out to be a statistically significant factor. These results may suggest that women are more involved in creating an appropriate working atmosphere in micro-enterprises. Only a few studies seem to confirm the important role of women as entrepreneurs, owners or managers in the process of creating innovation [130,131]. Unfortunately, gender lost its statistical significance in further estimates (models 2, 3 and 4).
Analysing the obtained results from the point of view of the second research question, it is again impossible to give an unambiguous answer. Only three of the possible characteristics assessed were found to have a statistically significant impact on the analysed dimensions of IC, i.e., having a marketing unit (x 8 ), good coordination of cooperation between employees (x 9 ) and engagement in initiatives for solving social problems (x 12 ). The obtained results indicate that, among organizational characteristics, the most important, from the perspective of introducing new-to-the-market product and process innovation, is involvement in initiatives for solving social problems. This suggests an important role for micro-enterprises in creating social innovations [132] and corresponds to their willingness to create a good working atmosphere and direct relations between employees [133][134][135][136]. It also indicates the closeness of relations with the nearest environment in which microcompanies operate.
It is also worth underlining that it is surprising that employees' creativity (x 14 ) has no impact. After all, many studies show the relationship between creativity and innovation [137][138][139], e.g., Martinez-Roman et al. suggested the impact of managers' creativity on SME innovations [24]. On the other hand, this may be the result of the use of only one item to describe employee creativity. Anderson et al. indicated that creativity is a nuanced concept that incorporates a number of distinct but closely related processes which result in distinct but often closely related outcomes [140]. Given the complex and dynamic nature of creativity as a construct [140][141][142], it is perhaps unsurprising that it has proven difficult to define and measure. A number of previous studies in the field of personality traits and their influence on innovativeness or entrepreneurship showed the need to use more extensive scales [143][144][145] based on creativity-relevant skills (e.g., intrinsic motivation to perform a task, skills in the task domain, creative thinking skills [146] or having a proactive personality, intrinsic motivation and creative self-efficacy [147]). The observed lack of influence of creativity may also be a result of the innovations introduced to the market that have been studied, while prior research into creativity has typically examined the stage of idea generation [140]. This also creates an interesting area for further possible research.
The last research question concerned the possible impact on micro-enterprise newto-the-market product and process innovation exerted by characteristics of the external environment. Three of the five characteristics studied proved to be statistically significant for all IC dimensions, i.e., external financial support from public administration (x15) and intensive cooperation with research centres (x 16 ) and with other companies (x 17 ). The first and third results were surprising because they indicated a negative impact.
In the first case (x 15 ), the obtained result is in contradiction with other studies, e.g., Martinez-Roman et al.'s. In their results, backing received for SMEs from public administration positively influenced product and process innovativeness [24]. This may have been a result of the differences between the surveyed enterprises (micro-versus SME) and of the fact that, in these models, only financial support was included. In turn, the positive impact of cooperation with research centres (x16) confirms the results of previous research [18,[148][149][150], e.g., Roper et al. [10]. On the other hand, the negative impact of cooperation with other enterprises (x 17 ) seems puzzling. This is probably due to the fact that a specific kind of innovation-only new-to-the-market innovation-was studied. The innovations of this type, which may be radical [40] or disruptive [151], arise within the company rather than in cooperation with other entities.

Conclusions
In this paper, the determinants of two dimensions of the intangible construct that is innovation capability have been studied from the perspective of micro-enterprise characteristics. From the theoretical perspective, the division of IC determinants into three groups was indicated: personal, organisational and external environmental characteristics.
The proposed model is original in the following aspects: (a) it explains new-to-themarket product and process dimensions of a micro-enterprise's innovation capability, (b) it includes a wide spectrum of factors specific to micro-enterprises that have not been sufficiently researched so far and (c) it gives the possibility of a new look at micro-enterprise innovativeness and predicts some possible new aspects of their functioning, important from a management and support policy point of view.
The results indicate that seven factors are common and significant determinants that explain the new-to-the-market product and process dimensions of micro-enterprise IC. These are experience/skills (personal characteristics), having a marketing unit, good coordination of cooperation between employees, engagement in initiatives for solving social problems (organizational characteristic), financial support and intensive cooperation with research centres and with other companies (external environmental characteristics)

Practical Implications
This research has direct managerial and policy implications. Firstly, an important role is demonstrated for micro-enterprises' engagement in initiatives for solving social problems. If we wish to increase the new-to-the-market innovativeness of a given region, micro-enterprises should be encouraged to become more involved in local social initiatives. Possible activities include practical policies and educational programmes and financial support for local social initiatives.
Secondly, micro-enterprises should be encouraged to cooperate with research centres. Stimulating this kind of cooperation directly increases micro-enterprises' new-to-the-market product and process innovation and thus the level of innovation in a given region. Therefore, it is worth taking various actions in the field of regional policy to support the exchange of information between micro-enterprises and research centres.

Limitations and Future Directions
This study has certain limitations which point to possible avenues for future research. Firstly, this research is based on cross-sectional data. Therefore, it should be noted that, between different sectors (e.g., trade, production, services), the determinants of microenterprises' ICs could be different. Future research could concentrate on the investigation of a specific sector.
Secondly, the study concentrated on micro-enterprises that did not include the selfemployed. Future research could be focused squarely on the self-employed. Taking into account their characteristics, such research could offer interesting and valuable insights into the determinants of IC for the theory of entrepreneurship and innovation.
Thirdly, the presented research was based on the single-respondent interview method. It should be emphasised that such an approach could have deformed the results due to the variety of the surveyed areas and to subjectivity.
Fourthly, this research was based only on new-to-the-market product and process innovations. Considering the important role of open innovation, it would be worth analysing micro-enterprise innovation capability in this context too.
Fifthly, this study was geographically limited. The results of the research may be applied to the Kuyavian-Pomeranian Voivodeship and, to a certain extent, to similar regions in Poland.
Lastly, the research shows the determinants of micro-enterprise IC at a specific moment. It would be valuable to examine whether the determinants change over time. Therefore, the conduction of a longitudinal survey is suggested.
Funding: This research was funded by the National Centre for Research and Development in Poland, grant number GOSPOSTRATEG1/385453/3/NCBR/2018.

Institutional Review Board Statement:
In this research I examined the group of micro-enterprises, however my research involved human participants, since I asked entrepreneurs or managers to answer the survey questions. The research was carried out by a specialized marketing research agency -Soma Social and Marketing Research Laboratory, in accordance with ICC / ESOMAR International Code on Market and Social Research (https://iccwbo.org/publication/iccesomarinternational-code-on-market-and-social-research/ (accessed on 17 March 2022)). All participants were informed that the survey is anonymous. I also analysed data anonymously, and I did not ask about any personal information. Therefore, my research, in accordance with the recommendations of the Polish National Science Centre (based on document in polish: https://www.ncn.gov.pl/ aktualnosci/2016-03-24-zalecenia-dot-etyki-badan (accessed on 17 March 2022)) which are the basis for drawing up guidelines for conducting research at Nicolaus Copernnicus University (based on document in polish: https://dokumenty.umk.pl/d/5665/5/ (accessed on 17 March 2022)) did not require approval of the ethics committees.
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.

Data Availability Statement:
The data presented in this study are available on request from the corresponding author.