E u r o p e a n I n t e g r a t i o n S t u d i e s 2 0 2 0 / 1 4 238 European Integration Studies No. 14 / 2020, pp. 238-248 doi.org/10.5755/j01.eis.1.14.25492 Abstract Restrictive Factors for Micro-Company Growth in Latvia http://dx.doi.org/10.5755/j01.eis.1.14.26567 Every country is interested in entrepreneurship development as entrepreneurs form the basis for economic de- velopment, so academic researchers are looking for supportive and restrictive factors in business development. In Latvia, the majority of companies are micro and small enterprises. The aim of the paper is to investigate the restrictive factors related to the successful development of the company in Latvia, depending on the number of employees. Tasks of the research - evaluate the limiting factors influencing the development of micro-com- panies; find the most important factors that limit the involvement of employees and experienced managers in companies in the country, regions; compare the impact on companies by number of employees. Applied research methods: scientific publications and previous research analysis; survey of companies related of differ- ent aspects of business development; deeper analysis on factors limiting entrepreneurship development. The general population consists of all active companies registered in the Register of Enterprises of the Republic of Latvia in strategically important sectors. A questionnaire of our survey was developed for companies selected at random and the replies of 2511 companies, of which 1879 were micro-enterprises, were considered valid. The technical fieldwork of the survey was conducted by the Marketing and Public Opinion Research Center (SKDS) (interviewers conducted as CAWI - computerized web interviews). Data analysis was performed by SPSS, the main indicators of descriptive statistics were used for the analysis of survey data: indicators of central tendency or location - arithmetic mean, mode, median; indicators of variability - standard deviation, standard error of mean, range; cross-tabulations by regions and by number of employees, analysis of variance - ANOVA and factor analysis with varimax rotation. The results point to the main restrictions on business growth: in- crease of expenses on labour or production and unavailability of qualified employees or experienced managers. KEYWORDS: company growth; micro-company; experienced managers; qualified employees; restrictive factors in company development.Introduction Every country is interested in entrepreneurship development as entrepreneurs form the basis for economic development, therefore academic researchers are looking for supportive and restric- tive factors in entrepreneurship development. In Latvia, most companies are micro and small enterprises. The aim of the paper is to investigate the limiting factors related to the successful involvement of employees in the development of micro-enterprises in Latvia. According to the researchers (European Commission, 2019) micro, small and medium-sized enterprises (SMEs) play a particularly important role in the non-financial business economy of Latvia. Although the total value added and employment share of SMEs and large enterprises Submitted 05/2020 Accepted for publication 07/2020 Restrictive Factots for Micro-Company Growth in Latvia EIS 14/2020 Ilona Beizītere RISEBA University of Applied Sciences Biruta Sloka Professor, University of Latvia Ieva Brence Latvia University of Life Sciences and Technologies http://doi.org/10.5755/j01.eis.0.13.23562 239 E u r o p e a n I n t e g r a t i o n S t u d i e s 2 0 2 0 / 1 4 increased at similar rates between 2014 and 2018, however the value added of SMEs increased by 29.9% and that of large enterprises by 29.1%. Employment growth for SMEs was significantly lower, rising by only 6.3% for SMEs and by only 5.0% for large companies. It should be empha- sized that the main drivers of SME value added growth were small enterprises with an increase of 36.7% in 2014-2018. In terms of employment growth, micro-enterprises showed an increase of 10.8% over the same period. Most recently, in 2017-2018, the total value added of SMEs in- creased sharply by 14.0%, while the growth of SME employment was much lower - 2.9%. Experts (European Commission, 2019) predict that the rapid growth of value added will continue, in- creasing by 14.5% in 2018-2020. Over the same period, employment in SMEs is projected to increase by 4.0%, with most of this increase coming from micro-companies, where employment is projected to increase by 6.1%. As a result, around 20 600 new jobs are likely to be created in SMEs by 2020. Therefore, the tasks of the research were: to evaluate the limiting factors influencing the devel- opment of micro-companies in Latvia; to find the most important factors limiting employees and experienced managers involvement in micro-companies in the country, in the regions and by the number of employees. In our study, we focused on micro-companies (i.e. enterprises with less than 10 employees and a turnover or balance sheet total of less than EUR 2 million) as defined in the European classification system (European Commission, 2003). Applied research methods were used to perform the tasks: scientific publications and previous realized research analysis; survey of micro-companies related of different aspects of the company development; deeper analysis on factors limiting entrepreneurship development. The general population consists of all active companies registered in the Register of Enterprises of the Republic of Latvia in 11 strategically important sectors that were entitled to receive state aid. A total of 32 308 enterprises were selected by NACE codes. The questionnaire of survey was sent for compa- nies selected at random from publicly available e-mail addresses in January 2018. In order to explore in depth the question of what factors significantly limit the growth of the company, the respondents were asked to answer on a scale of 1-5, where 1-not limiting, 5-limiting. The technical fieldwork of the survey was performed by the Marketing and Public Opinion Research Center (SKDS), the interviewers conducted as CAWI - computerized web interviews. The responds were provided by the managers, board members, directors or accountants of companies representing all regions of Latvia, and, ensur- ing greater representativeness, the data were weighted according to the share of sectors. Data analysis of survey was performed by SPSS, the main indicators of descriptive statistics were used for the analysis of survey data: indicators of central tendency or location - arithme- tic mean, mode, median; indicators of variability - standard deviation, standard error of mean, range; cross-tabulations by regions and by number of employees, analysis of variance - ANOVA and factor analysis with varimax rotation. Theoretical findings Researchers in many countries are looking for the best possible conditions for the company's development - several aspects are mentioned, including the size of the company, employees, in- novation, intellectual capital, local regulations (Block et al., 2012; Bolen et al., 2016; Corvino et al., 2019; Daugeliene & Liepinyte, 2012; Ferraro & Veltri, 2011; Gherhes et.al., 2016; Hanley & O'Gor- man, 2004; Tu et al., 2014). Different countries have diverse and specific approach (Long Kweth et al., 2014). Co-operation with educational institutions, including universities and SME are on researchers agenda (Cantù et al., 2015; Matlay, 1999; Zekos, 2003). In many cases labour force, clever and experienced managers are on key importance for success of the company (Maurer et al., 2011, McQueen & Yin, 2014). In different regions, it could be different results even if the man- agers are well experienced, employees are trying their best and innovative entrepreneurship is taking place (Andreeva et al., 2016, Daugeliene, 2016). The authors (Andreejeva et al., 2016) have https://datubazes.lanet.lv:5879/insight/search?q=Michael Hanley https://datubazes.lanet.lv:5879/insight/search?q=Bill O'Gorman https://datubazes.lanet.lv:5879/insight/search?q=Bill O'Gorman https://datubazes.lanet.lv:5879/insight/search?q=Harry Matlay https://datubazes.lanet.lv:5879/insight/search?q=Georgios I. Zekos https://datubazes.lanet.lv:5879/insight/search?q=Robert J. McQueen https://datubazes.lanet.lv:5879/insight/search?q=Zhaowen Yin E u r o p e a n I n t e g r a t i o n S t u d i e s 2 0 2 0 / 1 4 240 proposed and tested the hypothesis that, in this environment, the economic growth in the country and the region is increasingly determined not so much by large businesses, but by many small innovative companies. The study (Andreeva et al., 2016) confirms that the most justified strategy for the development of innovative entrepreneurship in the region is the strategy of cooperation between different types of companies in order to overcome their weaknesses, enhance existing opportunities and activate the innovation and entrepreneurial capacity. Access to financing by enterprises are on regular evaluation agenda (Kwaak et al., 2019) preparing also comparisions of performance by different countries. The researchers (Lussier & Sonfield, 2015) were examining six significant differences were: “small” firms are more likely to employ non-family member managers, are more likely to en- gage in the formulation of succession plans, are more likely to utilize outside advisory services, make greater use of sophisticated financial management methods, and have a more formal management style than “micro” firms; but the influence of the founder is greater in “micro” firms. Interest of academic researchers (Paoloni & Dumay, 2015) was devoted to the relational capital of micro-enterprises run by women in the startup phase. They have developed the CAOS mod- el of micro-entrepreneurship consisting of the following components: examining the personal characteristics of the female entrepreneur (C); the environment in which the micro-enterprise operates (A); organizational and managerial aspects (O); and the motivations for starting a new business (S). Using this model, the authors are able to link these factors and classify different types of connections, as a result, it is possible to identify the kind of existing relations. The anal- ysis revealed that networks with informal and permanent relationships are predominant, which support the need to reconcile work with family and involve relatives and friends in the network. The authors' study highlights the lack of strategy in women-run micro-enterprises (Paoloni & Dumay, 2015). Women in microenterpise management is on importance (Sandberg, 2003), and they pointed to the need for government support for networking activities and other programs that promote collaboration and pooling of resources. Different technical and IT solutions (Arendt, 2008; Flynn, 2017; Roberts & Wood, 2002; Teague, 1994) influence good organisation of microen- terprises. Researchers world-wide (Budhwar et al, 2002; Fielden et al., 2000; Keen & Etemad, 2012; Matlay et.al., 2005; Prijadi et al., 2020) have found that financing is one of the most impor- tant driving forces of microenterprise development. According to experts (European Commission, 2019) SMEs policy priorities for Latvia lies in the area of “skills & innovation”. They point out that, despite significant progress since 2008, Latvia is still well below the EU average in terms of skills and innovation. This is Latvia's weakest perfor- mance in the area implementing the Small Business Act for Europe. However, little progress has been made here: although the percentage of SMEs innovating is well below the EU average, the figure shows a slight improvement (15.2% in 2016 compared to 10.2% in 2014). Unfortunately, Latvia lags behind most of the EU in terms of the integration of companies' digital technologies. Researchers have found that one of the factors hindering this development is the shortage of qualified specialists and the still low proportion of ICT specialists. More than half of all Latvian companies wishing to hire ICT specialists report difficulties in filling vacancies. According to this development, Latvia is characterized by a high percentage of companies that prepare their own employees, and their indicators are well above the EU average. The percentage of companies that provide ICT skills training to their employees improved, reaching 9.6% in 2018 (8.6% in 2017). Among other things, new and nascent entrepreneurs who claim that their product or service is new to customers are in line with the EU average (European Commission, 2019). Experts have pointed to other factors that need to be overcome in SME policy in Latvia and prac- Situation analysis https://datubazes.lanet.lv:5879/insight/search?q=Robert N. Lussier https://datubazes.lanet.lv:5879/insight/search?q=Matthew C. Sonfield https://datubazes.lanet.lv:5879/insight/search?q=Paola Paoloni https://datubazes.lanet.lv:5879/insight/search?q=John Dumay https://datubazes.lanet.lv:5879/insight/search?q=Paola Paoloni et.lv:5879/insight/search?q=John Dumay https://datubazes.lanet.lv:5879/insight/search?q=Karl W. Sandberg https://datubazes.lanet.lv:5879/insight/search?q=Martyn Roberts https://datubazes.lanet.lv:5879/insight/search?q=Michael Wood https://datubazes.lanet.lv:5879/insight/search?q=Paul Teague 241 E u r o p e a n I n t e g r a t i o n S t u d i e s 2 0 2 0 / 1 4 tical realisation of entreprenurship. The lack of private investment in research and development, as well as the recent difficulties faced by SMEs in accessing bank finance, limit economic devel- opment in all sectors. Focusing on increasing productivity and expanding export opportunities, especially in the field of cross-border e-commerce, will be crucial for the development of the Latvian economy (European Commission, 2019). In a survey aimed at identifying the problem that is most pressing to the company, respondents were asked to assign a degree rating to each of the problems given. The ranking is calculated (Kwaak et al., 2019) based on grades by survey respondents. Given the highest problem identi- fied, they were ranked as follows: 1 the availability of skilled staff; 2 finding customers for their products or services; 3 the costs of production or labour (Labour costs include wages, employee benefits and payroll taxes paid by an employer); 4 regulations (European and national laws and industrial regulations); 5 competitions; 6 the access to finance. Table 1 Most pressing problems during April to September 2019 for SMEs in the EU28 and in Latvia. Percentages in the table indicate the percentage of SMEs that consider a specific problem to be the most urgent problem Most pressing problem In the EU28 In Latvia availability of skilled staff 26 25 finding customers 22 10 costs of production or labour 12 16 regulations 12 10 competitions 12 19 access to finance 7 10 other 8 10 Source: Based on data from Kwaak et al., 2019. The results of the survey (Kwaak et al., 2019) showed that in 2019, the availability of qualified staff and experienced managers, which has become an increasingly important issue over the years, is the most pressing problem facing EU28 SMEs. According to 26% of SMEs, this is the most urgent problem. Small (10-49 employees) and medium-sized (50-249 employees) companies are most likely to express shortages of qualified staff or experienced managers (29% and 30%, respec- tively), large companies (with 250 or more employees) consider this problem to be important to a lesser extent (26%), while micro-enterprises (with no more than 9 employees) express this problem the most urgency are the least (22%) compared to other size-classes. The survey found that the cost of inputs for the production process deteriorated more often than improved in the six months from April to September 2019. From 2014 onwards, a net deteriora- tion of costs has been observed in each survey year. In terms of the proportion of SMEs reporting them, these deteriorations in costs outweigh the improvements in turnover. An important restrictive factor on growth is the deterioration in labour costs (including social contributions). This is reported by 58% of all SMEs in the EU-28, but only 5% have experienced an improvement in labour costs. There are no reports of net improvements from SMEs in any EU Member State. There is a clear link between changes in company size and changes in labour Empirical research results E u r o p e a n I n t e g r a t i o n S t u d i e s 2 0 2 0 / 1 4 242 costs. The largest deterioration in labour costs was experienced by large companies (net 62%), the least by micro- companies (net 45%). However, there is not always a relation between the size of the enterprise and changes in other costs (consisting, inter alia, of material and energy costs). Small and medium-sized companies have experienced the most deteriorations in other costs (net 57%), micro-companies (net 53%) and large companies (net 52%) experienced deteriorations in other costs less often (Kwaak et al., 2019). Such aspects are mentioned also in other publications. In this paper, the empirical research is based on the survey of companies in Latvia on their limiting factors for company development. The main statistical indicators of the factors limiting the devel- opment of company in Latvia are included in Table 2 and Table 3. Thirteen key restrictive factors were used in the business questionnaire which was used in survey of entrepreneurs in Latvia iden- tified in the various studies of researchers in many countries and recommended by local experts. Empirical research results Table 2 Main statistical indicators of limitating factors for company development in Latvia (part 1) Statistical indicators Market for products/ service realisation Competition Access to finance Increase of expenses on labour or production Unavailability of qualified employees or experienced managers Changes in laws and regulation N Valid 2511 2511 2511 2511 2511 2511 Missing 0 0 0 0 0 0 Mean 2,84 2,99 2,93 3,45 3,34 3,49 Std. Error of Mean 0,029 0,025 0,028 0,025 0,027 0,026 Median 3 3 3 4 3 4,00 Mode 1 3 3 3 5 5 Std. Deviation 1,437 1,266 1,384 1,254 1,377 1,315 Variance 2,066 1,603 1,914 1,572 1,897 1,730 Range 4 4 4 4 4 4 Minimum 1 1 1 1 1 1 Maximum 5 5 5 5 5 5 Source: Authors’ calculations based on the survey of companies in Latvia, n=2511. Evaluation scale 1-5, where 1-not limiting, 5-limiting. Table 3 Main statistical indicators of limitating factors for company development in Latvia (part 2) Statistical indicators Tax burden Unstable company cash-flow Bureaucracy in public institutions Changing rules of regulation Shadow economy Political situation Lack of innovations N Valid 2511 2511 2511 2511 2511 2511 2511 Missing 0 0 0 0 0 0 0 Mean 3,96 3,10 3,22 3,65 2,74 2,49 2,29 Std. Error of Mean 0,023 0,026 0,027 0,027 0,028 0,027 0,024 Median 4 3 3 4 3 2 2 Mode 5 3 5 5 1 1 1 Std. Deviation 1,161 1,319 1,365 1,328 1,384 1,339 1,196 Variance 1,349 1,739 1,864 1,764 1,916 1,792 1,429 243 E u r o p e a n I n t e g r a t i o n S t u d i e s 2 0 2 0 / 1 4 Source: Authors’ calculations based on the survey of companies in Latvia, n=2511. Evaluation scale 1-5, 1 - not limiting, 5 - limiting. Statistical indicators Tax burden Unstable company cash-flow Bureaucracy in public institutions Changing rules of regulation Shadow economy Political situation Lack of innovations Range 4 4 4 4 4 4 4 Minimum 1 1 1 1 1 1 1 Maximum 5 5 5 5 5 5 5 Data indicate that the most limiting factors for company development are changes in laws, in- crease of expenses on labour or production, unavailability of qualified employees or experienced managers. To find common aspects of analysed 13 factors which were selected as limiting com- pany development. As thirteen factors are a lot and it can make difficulties in decision-making it was decided to apply dimension reduction with keeping all information using one of the most commonly used methods of multivariate analysis - factor analysis with varimax rotation which was concluded in six iterations. Results of the factor analysis are included in Table 4. Source: Authors’ calculations based on the survey of companies in Latvia, n=2511. Evaluation scale 1-5, where 1 - not limiting, 5 - limiting. Initial limitating factors for micro-cpompany development Component 1 2 3 4 Market for products/service realisation 0,063 0,175 0,026 ,794 Competition 0,040 0,090 0,190 ,795 Access to finance 0,039 0,656 0,319 -0,254 Increase of expenses on labour or production 0,316 0,133 0,725 0,222 Unavailability of qualified employees or experienced managers 0,131 0,197 0,753 0,049 Changes in laws and regulation 0,837 0,013 0,196 0,087 Tax burden 0,700 0,053 0,374 0,102 Unstable company cash-flow 0,027 0,580 0,304 0,118 Byrocracy in public institutions 0,768 0,293 0,053 -0,018 Changig rules of regulation during the process 0,861 0,140 0,099 0,006 Shadow economy 0,251 0,548 0,127 0,188 Political situation 0,506 0,558 -0,148 0,136 Lack of innovations 0,100 0,660 -0,017 0,241 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 6 iterations. Table 4 Complex factors of limitating factors for micro-company development in Latvia (rotatted component matrix) The authors have named four complex factors, and they are: 1 Legislation determined conditions 2 Financing conditions 3 Labour market restrictions 4 Production realisation conditions. E u r o p e a n I n t e g r a t i o n S t u d i e s 2 0 2 0 / 1 4 244 More detailed are analysed labour market restricting factor consisting of initial factors: in- crease of expenses on labour or pro- duction and unavail- ability of qualified employees or expe- rienced managers. Main results are in- cluded in Table 5. As the data in Ta- ble 5 show, there are differences in the assessments of these factors in the regions of Latvia. To assess the signifi- cance of the evalu- ations by entrepre- neurs in different regions, the testing of significance of the average estimates in the regions using analysis of variance ANOVA was applied. The ANOVA results are shown in Table 6. As data of the Table 6 indicate there are differences in evalu- ations of those fac- Table 5 Main statistical indicators of labour market restricting factors for micro- company development in regions of Latvia Region where company is located Increase of expenses on labour or production Unavailability of qualified employees or experienced managers Rīga Mean 3,38 3,29 N 1238 1238 Std. Deviation 1,267 1,394 Median 4 3 Pierīga Mean 3,51 3,42 N 330 330 Std. Deviation 1,248 1,368 Median 4 4 Vidzeme Mean 3,42 3,32 N 318 318 Std. Deviation 1,243 1,352 Median 3 3 Kurzeme Mean 3,45 3,44 N 275 275 Std. Deviation 1,259 1,353 Median 4 4 Zemgale Mean 3,57 3,32 N 190 190 Std. Deviation 1,214 1,352 Median 4 3 Latgale Mean 3,76 3,44 N 160 160 Std. Deviation 1,168 1,386 Median 4 4 Total Mean 3,45 3,34 N 2511 2511 Std. Deviation 1,254 1,377 Median 4 3 Source: Authors’ calculations based on the survey of companies in Latvia, n=2511. Evaluation scale 1-5, where 1 - not limiting, 5 - limiting. Table 6 ANOVA on evaluations of labour market restricting factors for micro- cpompany development in regions of Latvia Labour market restricting factors Sum of Squares Sum of Squares (values) df Mean Square F Sig. Increase of expenses on labour or production Between Groups 26,522 5 5,304 3,391 0,005 Within Groups 3918,023 2505 1,564 Total 3944,546 2510 Unavailability of qualified employees or experienced managers Between Groups 9,519 5 1,904 1,004 0,414 Within Groups 4751,392 2505 1,897 Total 4760,910 2510 Source: Authors’ calculations based on the survey of companies in Latvia, n=2511. Evaluation scale 1-5, where 1 - not limiting, 5 - limiting. 245 E u r o p e a n I n t e g r a t i o n S t u d i e s 2 0 2 0 / 1 4 Table 7 Main statistical indicators of labour market restricting factors for company development by number of employees in Latvia tors in the regions of Latvia. To assess the significance of the evaluations by en- trepreneurs in differ- ent regions, the test- ing of significance of average evaluations of companies by number of employ- ees using analysis of variance ANOVA was applied. Results of ANOVA are in- cluded in Table 7. As data of the Ta- ble 7 indicate there are differences in evaluations of those factors in com- panies depending from their size in of Latvia. To assess the significance of the evaluations by entrepreneurs in different regions, the testing of sig- nificance of aver- age evaluations in companies by their size using analysis of variance ANOVA was applied. Re- sults of ANOVA are included in Table 8. Number of employees in the company Increase of expenses on labour or production Unavailability of qualified employees or experienced managers 1–4 employees Mean 3,31 3,11 N 1413 1413 Std. Deviation 1,318 1,430 Median 3 3 5–9 employees Mean 3,56 3,61 N 466 466 Std. Deviation 1,210 1,313 Median 4 4 10–49 employees Mean 3,69 3,66 N 477 477 Std. Deviation 1,094 1,205 Median 4 4 50–249 employees Mean 3,67 3,71 N 136 136 Std. Deviation 1,068 1,155 Median 4,00 4,00 250–499 employees Mean 3,33 3,33 N 15 15 Std. Deviation 1,047 1,291 Median 3,00 3,00 500 employees and more Mean 3,25 2,75 N 4 4 Std. Deviation 0,957 1,258 Median 3,5 3 Total Mean 3,45 3,34 N 2511 2511 Std. Deviation 1,254 1,377 Median 4 3 Source: Authors’ calculations based on the survey of companies in Latvia, n=2511. Evaluation scale 1-5, where 1 - not limiting, 5 - limiting. Table 8 ANOVA on evaluations of labour market restricting factors for company development by number of employees in Latvia Labour market restricting factors Sum of Squares Sum of Squares (values) df Mean Square F Sig. Increase of expenses on labour or production Between Groups 70,810 5 14,162 9,158 0,000 Within Groups 3873,736 2505 1,546 Total 3944,546 2510 Unavailability of qualified employees or experienced managers Between Groups 174,074 5 34,815 19,013 0,000 Within Groups 4586,836 2505 1,831 Total 4760,910 2510 Source: Authors’ calculations based on the survey of companies in Latvia, n=2511. Evaluation scale 1-5, where 1 - not limiting, 5 - limiting. E u r o p e a n I n t e g r a t i o n S t u d i e s 2 0 2 0 / 1 4 246 Conclusions As result of factor analysis the authors have named four complex factors, and they are: 1 Legislation determined conditions; 2 Financing conditions; 3 Labour market restrictions; 4 Production realisation conditions. The overall conclusion is that, despite the fact that in the review of Latvia (European Commission, 2019) admits that „Skills & innovation has been the Latvian government’s priority for the past few years, giving SMEs opportunities to fund creation of new products and services, up-skill and re- skill the labour force and transfer knowledge and technologies from scientific institutions to SMEs”, the results of our study point to the inadequacy of the measures taken by business policy makers. Acknowledgements We are grateful to the Marketing and Public Opinion Research Center (SKDS) for assistance in conducting the survey of entrepreneurs and processing the data. References Andreeva, E.L, Simon, H., Karkh, D.A. & Glukhikh, P.L. (2016). Innovative entrepreneurship: A source of economic growth in the region. Economy of Region, 12(3), 899-910. https://doi.org/10.17059/2016-3-24 Arendt, L. (2008). Barriers to ICT adoption in SMEs: how to bridge the digital divide?. 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Address Meža iela 3, Riga, Latvia, LV 1048, Phone + 37126566887 E-mail: Ilona.Beizitere@gmail.com SLOKA BIRUTA Dr.oec., Professor, Senior Researcher University of Latvia Fields of interests Mmarketing, qualified labour, application of quantitative analysis. Address Aspazijas bulv. 5, Riga, Latvia, LV 1050, Phone + 37129244966 E-mail: Biruta.Sloka@lu.lv BRENCE IEVA Dr.sc.admin., senior researcher Latvia University of Life Sciences and Technologies Fields of interests Micro-company financing, qualified labour, experienced managers. Address Liela iela 2, Jelgava, LV-3001, Latvia. Phone +37126363506. E-mail: Ieva.Brence3@gmail.com Research was supported by the National Research Program “INTERFRAME-LV” and the National Research Pro- gramme Project “Towards the Post-pandemic Recovery: Economic, Political and Legal Framework for Preser- vation of Latvia's Growth Potential and Increasing Competitiveness” (“reCOVery-LV”). Zekos, G.I. (2003). MNEs, globalisation and dig- ital economy: legal and economic aspects. Managerial Law, 45(1/2), 1-296. https://doi. org/10.1108/03090550310770875 This article is an Open Access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 (CC BY 4.0) License (http://creativecommons.org/licenses/by/4.0/).