Financial Literacy in Micro-Scale Enterprises Operating in Forest Products Sector: Sample of Gumushane, Turkey

• Enterprises are one of the main components of the economic system and they are indispensable for maintaining the sustainability of economic activities. The majority of these enterprises are small and medium-sized enterprises (SMEs). Sustainability of SMEs depends on their good financial management. Inadequate finan -cial literacy causes SMEs’ owners to make inaccurate financial decisions. The forest products sector is mostly composed of micro-scale enterprises in which financial problems are common. Therefore, this study aims to reveal the financial literacy status of the owners of micro-scale and wood-processing enterprises. For this purpose, 78 enterprises were selected as study population. Data were collected by applying a structured questionnaire to 43 of these companies by the face-to-face interview method. The structured questionnaire consisted of multiple-choice and open-ended questions and statements prepared on the Five Likert scales. Data were analysed by using the Independent-Sample T-Test, Mann-Whitney U-Test and correlation test. The reliability coefficient of the data was found to be 0.791. Of the enterprises, 58 % produced in the furniture sub-sector and 42 % in the wood products sub-sector. This study provides evidence that there was no statistically significant difference between the knowl -edge means of economics and financial behaviour of the furniture and wood products sectors. However, the enter -prise owners’ knowledge of financial analysis positively affected their financial literacy and financial behaviour.


UVOD
An economic system consists of three main units: household, enterprise and the state. Enterprises perform the most important duty in the continuation of economic activities in this system. Especially small and medium-sized enterprises (SMEs) need to be well managed financially to ensure the sustainability of their activities. In general, SMEs are managed by owners that take all business decisions and for this reason, the financial literacy level of the enterprise owners has a far-reaching effect especially on the success of SMEs.
Management of limited financial resources is important for SMEs. Successful financial management requires having a certain level of financial knowledge. Persons who access, interpret and use financial knowledge are called financial literate. The most important concept of financial literacy is knowledge. SME owners, who are likely to experience economic difficulties, should have financial knowledge, such as credit, interest, capital, budget management, balance sheet, inflation and risk management. The lack of financial information and financial management will make the owner/ manager take inaccurate, incomplete and ineffective financial decisions (Agyapong and Attram, 2019).
Enterprises should observe and analyse the inside and outside environmental conditions of their enterprises while making decisions about their economic future. In this context, financial knowledge enables the interpretation of internal unit activities of enterprises as well as read the external environmental economic indicators. Persons with low financial literacy can make mistakes in their finance-related decisions and thus waste their scarce resources (Şahin and Serin, 2018). Entrepreneurs with knowledge about basic financial concepts such as budgeting, savings, borrowing and investment and the ability to use this information in their decisions (Banks Association of Turkey, 2020) can use their scarce resources more rationally. Karadağ (2015) reported that financial difficulties are common for the majority of the SMEs in Turkey as in many developing countries and that the past experiences and knowledge of owners have an important role in solving financial problems.
KLJUČNE RIJEČI: proizvodi od drva; financijska pismenost; mikropoduzeća; namještaj SMEs 1 constitute the largest part of the total number of enterprises in the countries where they are located. For example, in countries such as America, Germany, Japan and South Korea, SMEs comprise 97.2 %, 99.8 %, 99.4 % and 97.8 % of the total number of enterprises, respectively (Demir and Sütçü, 2002). Micro-sized enterprises (1-9 employees) constitute the majority of the SMEs and consist of the micro, small and medium-scale enterprises. The micro-sized enterprises in Turkey comprised 96 % of all sized enterprises according to result of the latest census of industry and business carried out in 2002 (Anonym, 2006). SMEs account for 99 % of all businesses in 28 countries of the European Union (EU). Of these 99 %, 93 % are micro, less than 6 % are small and less than 1% are medium-sized businesses (Rotar et al., 2019). Microsized enterprises in the EU account for about 30 % of total employment and therefore play an important role in creating economic growth and employment (Rotar et al., 2019).
The mortality rate of small and medium enterprises is very high. In Turkey, 109 722 enterprises were opened and 33 094 enterprises were closed in total in all sectors in 2019. The ratio of closed businesses to opened businesses was 30 %. In other words, 10 enterprises were opened while 3 were closed in 2019. In the manufacturing sector, which is a subsector of all sectors, 16 332 enterprises were opened and 3 227 enterprises were closed in the same year. The ratio of enterprises closed was 19.7 % in the manufacturing sector. The rate of closure in the manufacturing sector, which also includes the forest products sector, was less than the overall rate (The Union of Chambers and Commodity Exchanges of Turkey, 2020). 80 % of enterprises established in Turkey were closed within the first 5 years and 96 % of them within the first 10 years. The failure of getting new technologies and low cost finance were in the first place among factors that shorten the life of SMEs (Capital, 2007). This situation is not unique to Turkey. For ex-1 "The category of micro, small and medium-sized enterprises (SMEs) is made up of enterprises which employ fewer than 250 persons and which have an annual turnover not exceeding EUR 50 million, and/or an annual balance sheet total not exceeding EUR 43 million" as defined by European Commission (2003/361/EC). ample, in Nigeria, 80 % of SMEs are closed within the first five years and some are closed within 6 to 10 years. Only 5-10 % of these businesses survive, grow and reach maturity. This means that the survival rate of SMEs in Nigeria is less than 5 %. There are various reasons for the high mortality rates of enterprises in Nigeria, but the "lack of financing" is one of these reasons (Sharma, 2019).
Studies on financial literacy was focused on three main cases: (i) measuring the level of financial literacy in a country, (ii) determining how financial literacy affects financial decisions, and (iii) determining the relationship between financial literacy and financial education (Shen et al., 2016). This study has the chara cteristics of the first case (i) and the third case (iii) according to the above classifications. However, the subject of this study was not a country but two sub-sectors of the manufacturing industry. Micro-sized enterprises, which are considered to be more important in having financial literacy, were selected within these sub-sectors. Hakim et al. (2017) reported that there is a large number of studies on factors that contribute to financial literacy, whereas research on the financial literacy levels of small and medium-sized business owners is still limited (Hakim et al., 2017).
According to the Industry Report of the Turkish Furniture Products Assembly, financial difficulties and high credit costs are one of the important issues faced by enterprises in this sector and it is considered among the 10 main issues which should be solved to gain a place in the international markets in the long term (The Union of Chambers and Commodity Exchanges of Turkey, 2012). Akyüz et al. (2004) examined the financial structure of 14 sectors making up the manufacturing sector and found that the wood products and furniture industries, which make up the forest products industry, were in the last place in terms of financial structure. In a SWOT analysis carried out for the furniture sector, capital and financing limitations were found to be one of the weaknesses of the sector (Istanbul Chamber of Industry, 2015). Özgülbaş and Koyuncugil (2011) reported that 36 % of the enterprises in the furniture sector perceived funding problems as the biggest issue. The shortness of capital was found to be the most frequent problem faced by enterprises operating in forest products sectors in Gumushane with 28.1 % (Top et al., 2014). In this context, the primary aim of this study was to measure and compare financial analysis, general economy, financial behaviour and financial literacy knowledge of micro-sized business owners manufacturing furniture and wood products. The second aim was to investigate the bilateral correlations between business owners' financial analysis, general economy, financial behaviour and financial literacy knowledge, without discriminating the sector.

Materijali
The International Standard Industrial Classification of All Economic Activities Rev.4 (ISIC Rev.4) consists of 21 sectors and 99 sub-sectors. The manufacturing sector, which is one of these 21 sectors and coded with C, consists of the sub-sectors arranged from 10 to 33. Forest products sectors are also classified as 3 different sub-sectors within the manufacturing sector, which are (i) Manufacture of wood and of products of wood and cork (C16), (ii) Manufacture of paper and paper products (C17) and (iii) Manufacture of furniture (C31) (United Nations, 2008).
In this study, micro-sized enterprises producing furniture and wood products in the Gumushane province were selected for analysis. The Gumushane province is located in the north of Turkey, as shown in Figure 1, and is one of Turkey's 81 provinces. Its surface area covers 6575 km 2 of which about 29 % is forested. Its population was 141702 in 2020. Enterprises in sectors C16 and C31 in Gumushane constituted 0.12 % and 0.1 % of the number and employment in sectors C16 and C31 in Turkey, respectively (Top et al., 2014). There is no company that manufactures paper and paper products in Gumushane. In terms of employment, the total of sectors C16 and C31 constituted 26.8 % of the manufacturing sector employment and 4.4 % of the total of all sectors in Gumushane (Anonym, 2006). The enterprises that make up the forest products sector in Gumushane were divided into scale groups as follows: all 46 enterprises in C16 were included in the microsized group and 32 of 33 enterprises in C31 were micro-sized (96.9 %) and 1 out of 33 enterprises was in medium-sized (3.1 %) group (Anonym, 2006). However, one enterprise in the medium-sized group was Micro-scale enterprises are important for the country's economy. The number of micro-sized enterprises, their contribution to employment and other characteristics may be similar or different between countries. For example, when the number of enterprises and employment in Turkey and Croatia (Organization for Economic Co-operation and Development, 2021) in Table 1 are evaluated, it is seen that the rates of micro-scale enterprises in the total sector are different. According to Table 1, the ratio of employment created by micro-scale enterprises in Croatia accounted for 20.6 % of the total employment created by all size enterprises in the sector C31 in 2014, while the employment ratio created by enterprises in the same sector in Turkey was 35.8 %. Micro-scale enterprises operating in the sector C16 in 2017 constituted 18.8 % and 46.2 % of the employment created by all enterprises in this sector in Croatia and Turkey, respectively.

Data collection 2.2.1. Prikupljanje podataka
The face to face interview method, which is a type of survey method, was used as a data collection tool. The structured questionnaire was applied to 43 enterprises that made up 55 % of the study population in the time between March and April, 2020. Previous  Table 2 prepared on a five-point Likert scale as part two and ability of calculation of inflation and interest and risk reduction as part three. Participants rated whether they agree with the statements presented to them about knowledge of financial analysis, knowledge of general economics, knowledge of financial behaviour, and knowledge of financial literacy. The rating was designed as «I totally agree» (1), «I agree» (2), «I am indecisive» (3), «I disagree» (4) and «I strongly disagree» (5). Simple random sampling method was used in the determination of the enterprises to be surveyed.

Data analyses 2.2.2. Analiza podataka
In order to examine statistical differences between the averages of forest products sub-sectors, the following analyses were performed. First, it was tested whether the distribution of variables approximated the normal distribution. Those satisfying the normal distribution were then tested for homogeneity of variance. The comparison of the averages of the variables that met these two conditions was made according to the Independent-Sample T-Test. In cases where the normal distribution and variance homogeneity condition were not met, the Mann-Whitney U-Test, which is the nonparametric equivalent of Independent-Sample T-Test, was performed for comparison. The suitability of the data for normal distribution was determined according to the Shapiro-Wilk test. The Levene test was used for the homogeneity test of variances. In these tests, the H o hypothesis is accepted if the p value is greater than 0.05 and rejected if it is smaller than 0.05. The Cronbach Alpha coefficient was calculated for the reliability of the data. All analyses were carried out for the 0.05 significance level. To investigate the relationships between variables, the Pearson correlation coefficient was used to analyse normally distributed data and the Spearman correlation coefficient was calculated for non-normally distributed data (Bursal, 2017).

Model and hypotheses 2.2.3. Model i hipoteze
The model used to measure the correlations between variables was designed as in Figure 2. In this model, no sector distinction was made. The model has two independent variables such as knowledge of finan-cial analysis and economics of enterprise owners, an intermediary variable such as knowledge of financial literacy and a dependent variable such as financial behaviour.

REZULTATI I RASPRAVA
To determine whether the data collected were reliable, the Cronbach Alpha Test was performed and the reliability coefficient was found to be α = 0.791. Since this coefficient (α) was greater than 0.70, the data were accepted as reliable (Bursal, 2017). Serin et al. (2016) reported a reliability coefficient of 0.76 in their research to determine the economic literacy levels of the forest products industry (Serin et al., 2016).
The demographic values of the enterprise owners regarding age, working year in the sector and monthly income were found as shown in Table 3. According to this table, 58 % of the researched enterprises were ac- The education levels of enterprise owners by sectors were found as in Table 4. Approximately half of the total number of enterprise owners were high school graduates (44.2 %) and constituted the largest category. Top et al. (2014) found in enterprises, where the structural attitudes of forestry products industry in the Gumushane province were examined, that the largest group of enterprise owners had high school education. These two studies are similar in this respect. However, Şahin and Serin (2018) found that 66.7 % of enterprise owners were high school graduates in the study in which the financial literacy level of furniture industry in the Gaziantep province was investigated. This percentage was considerably higher than reported in our study. Özgülbaş and Koyuncugil (2011) reported in a furniture and shoemaking sector analysis study that 91.2 % of the manager positions in the furniture sector were at high school level and under. Of the enterprises studied by Özgülbaş and Koyuncugil (2011), 81.8 % were micro-sized enterprises. The observed difference between our findings may be due to the fact that their study included enterprises in a different sector than the forest products sector, such as shoemaking, and the geographical region differences. Another reason for the huge difference between our and their results (44.2 % and 91.2 %, respectively) is that they gathered primary, secondary and high school graduates under one group as "high school level and under". However, in our study, each school type is considered separately.
The averages of the analysed variables, including financial analysis, economy, financial behaviour and financial literacy knowledge are summarised in terms of sectors in Table 5. Means with a value less than 2.5    Tests were performed to see if the difference between the sector means of each variable in Table 5 was statistically significant. For this, we first tested whether the variable data followed a normal distribution. The results are presented in Table 6. Since the sub-sector degrees of freedom (df) were less than 30, the decision was made according to the Shapiro-Wilk Test result (Bursal, 2017). Accordingly, at least one of the p-values of economic (p=0.021) and financial behaviour knowledge (p=0.014) belonging to sectors was less than 0.05, and therefore did not meet the normal distribution condition. Since the p-values of financial analysis and financial literacy data were p>0.05, they were found to meet the normal distribution requirement.
Data of financial analysis and financial literacy variables, which comply with the normal distribution between sectors, should secondly meet the condition of homogeneous variances between sectors. If this condition was met, an Independent-sample T-test could be   (Pallant, 2017). The test result showing that the variances of the sectors for these two variables were homogeneous are summarised in Table 7. The Levene's Test resulted in a p>0.05 for the knowledge of financial analysis (p=0.623) and p>0.05 for the knowledge of financial literacy (p=0.339). Therefore, the condition of homogeneity of variances was met.
According to the T-test values in Table 7, the equality of means under the H o hypothesis was accepted since the p value of financial analysis (p=0.809) was p>0.05 and the p value (p=0.386) of financial literacy was p>0.05. There was no further significant difference between the financial analysis knowledge and financial literacy averages of the sectors. In other words, the differences between the financial analysis knowledge mean of the furniture manufacturing enterprise owners and the financial analysis knowledge mean of the wood products manufacturing enterprise owners were not statistically significant. The same result was true for financial literacy.
The economic and financial behaviour knowledge variables of the sectors did not show a normal distribution. Therefore, a Mann-Whitney U-Test was used to investigate whether there were differences between the means of these variables and results are shown in Table 8. According to these results, neither economic knowledge (p=0.261) nor financial behaviour knowledge (p=0.152) in terms of sector were statistically significant (p>0.05).
According to the results of the Independent-Sample T-test and Mann-Whitney U-Test, the difference between the means of financial analysis, financial literacy, financial behaviour and economic knowledge of furniture and wood products enterprises' owners was not statistically significant. In other words, the owners of the enterprises in the furniture and wood products sectors are similar in terms of the knowledge mentioned above or they belong to the same population.
Correlation analyses between financial analysis, financial literacy, economy and financial behaviour knowledge variables were also conducted. The correlation between financial analysis and financial literacy knowledge, both following a normal distribution, were tested using the Pearson's correlation coefficient. Nonnormally distributed variables were analysed by Spearman correlation as shown in Table 9.
Correlation analysis between financial analysis and financial behaviour resulted in p=0.013 . Therefore, the H 5 hypothesis was accepted and it was concluded that there was a significant relationship between these two variables. According to the Spearman's correlation coefficient r s = 0.376, the relationship was positive and of medium strength. In addition, due to p=0.002 for the relationship analysis between economics and financial behaviour knowledge, the H 4 hypothesis was accepted. This means that there was a significant relationship between these two variables. According to the Spearman's correlation coefficient r s =0.450, the relationship was positive and of medium strength. According to the The relationship between financial analysis and financial literacy variables was determined according to Pearson's correlation coefficient, since these two variables met the normality requirement. As summarised in Table 10, the value of p=0.008 was smaller than 0.05 and for this reason, the H 3 hypothesis was accepted. It was concluded that there was a significant positive relationship between these two variables. According to correlation coefficient r s =0.402, the relationship was positive and of medium strength.
It was also tested whether there was a significant relationship between variables and sectors. The Spearman correlation test was used to investigate the effect of the sector on the variable, since the sector variable is of the ordered data type. There was no significant relationship between sector and financial analysis (p>0.05); sector and financial literacy (p> 0.05); sector and economy (p>0.05) and sector and financial behaviour (p>0.05). Mashizha et al. (2019) found that there was a significant difference in the mean scores between sector and financial literacy. These findings are different from our study, which may be due to the fact that Mashizha et al. (2019) surveyed SMEs operating in 10 different sectors.
Business owners were asked for a simple interest account and 95.3 % of the participants chose the correct answer. 32.6 % of enterprise owners answered correctly the question of whether or not investing in different assets would increase the risk of losing money. 44.2 % of the enterprise owners indicated that this would increase the risk. In a circle where the annual inflation rate is 10 %, the question about the purchasing power of money invested in the bank for one year with 6 % interest, 83.7 % of the participants correctly chose to decrease the purchasing power of the money. Mashizha et al. (2019) revealed that ratios of respondents' knowledge of interest, risk reduction and inflation were 74.5 %, 68.7 %, and 71.6 % respectively. Considering the sector and scale differences, it can be said that these rates are close to our values. In addition, the fact that the knowledge of interest calculation is the highest and the risk distribution is the lowest is the common point of our and their results.

ZAKLJUČAK
Scarce resources require economic units to be cautious in their decisions related to finance. Therefore, especially micro-scale enterprises need to be more sensitive to working environment and analyse this environment well. The financial skills of business managers are important in outsourcing and capital procurement, inventory management and determining real needs.
In the current study, financial literacy levels of business owners operating in the forest products sector were determined, while knowledge of financial analysis and general economic and financial behaviour patterns were evaluated. The mean of financial analysis knowledge levels of business owners was the highest. The mean of general economy knowledge levels was the lowest among other factors. However, if the mean of general knowledge levels was less than 2.5, this would mean that the knowledge level of the business owners operating in the micro-scale forest products sector was sufficient. Therefore, it can be concluded that the lack of knowledge of business owners was not the basis of the financing problems common in the forest products sector in literature.
It was investigated whether the differences among the averages of financial analysis, economy, financial behaviour and financial literacy knowledge levels between wood products and furniture sub-sectors were significant and whether there was a correlation between these knowledge levels and the sectors. It was concluded that the differences between knowledge levels by sectors were not significant. In other words, there was no difference between the financial analysis, economy, financial behaviour and financial literacy knowledge of the furniture and wood products sector business owners. It can be concluded that business owners in both sectors belong to the same universe. In addition, no correlation was observed between knowledge levels and sectors. In other words, there was no correlation between, for example, the knowledge means of the financial behaviour of the wood products industry and the furniture industry. The same results were valid for knowledge means of the general economy, financial analysis and financial behaviour.
When correlations among knowledge levels were investigated, regardless of sectors, positive and moderate correlations were obtained between some of the variables. There was no correlation between some variables. Financial analysis information of the business owners positively affects their financial literacy and financial behaviour. Again, economic information of business owners has a positive effect on their financial behaviour. However, there was no relationship between financial literacy and financial behaviour. Finan-cial literacy of business owners is not always reflected on their financial behaviour.
Business owners can accurately calculate the simple interest calculation and the depreciation of money against inflation at a very high rate. However, the ability to analyse requires the basic knowledge, and knowledge is one of the most important components of financial literacy. If it is stated that business owners within the scope of our study have an average of 17 years of work experience, showing that they can obtain enough information about their market. Therefore, this information gained through experience affects positively both financial literacy levels and financial behaviour pattern of business owners. Considering that financial behaviour and financial literacy are affected by two channels such as education and financial socialization, it can be concluded that micro-scale business owners operating in the forest products sector have strong financial socialization aspects. Enterprises surveyed by this study were able to analyse their environment well while continuing their activities and made the right financial decisions with this analysis capability.