Assessment of Financial Security of SMEs Operating in the Renewable Energy Industry during COVID-19 Pandemic

Abstract

Today, one of the main priorities in Europe is to introduce measures to increase environmental protection. Therefore, SMEs operating in the branch related to renewable energy are essential for several EU priorities. SMEs can also be vulnerable, especially during times of crisis, which could negatively affect renewable energy development. Therefore, this paper aims to evaluate and analyze the financial security management of renewable energy SMEs during the COVID-19 pandemic. The research is conducted on SMEs operating in the renewable energy sector in Poland. The research periods are 2019 (before the COVID-19 crisis) and 2020 (during the crisis). By analyzing different financial performance ratios, we found that SMEs operating in the energy sector have been able to stabilize and maintain their current economic position compared to the past. The results of this study indicate that the receivables collection period, cash conversion cycle, and operating cycle could have been insignificantly shorter during the COVID-19 crisis. Furthermore, to have stronger financial security, SMEs have adopted a conservative policy in which the share of accounts receivable in current assets has been significantly reduced during COVID-19. In contrast, an insignificant increase in liquidity, quick ratios, and inventory turnover have been observed. In general, Polish SMEs have chosen to adopt conservative strategies during COVID-19 to have better liquidity security.

1. Introduction

The COVID-19 pandemic has changed the rules of the market game in many sectors, which influence the creation, maintenance, and development of the value of an organization and its financial management. A key issue in corporate financial management is the management of liquidity and financial performance [1,2,3,4,5,6]. Research conducted from 2019 to 2020 during the COVID-19 pandemic confirms that liquidity management during a financial crisis of particular importance [7,8,9]. Working capital management is one of the most important areas in corporate financial management since liquidity directly impacts the company’s profit.

There is a lot of research available on the financial security of enterprises. There is also research available on financial liquidity in times of crisis. Financial security is closely related to the level of financial liquidity and the level of working capital in enterprises. In SMEs, these are the most important indicators that show the level of security the company is at. Today, in the times of the crises related to the COVID-19 pandemic or the war in Europe, it can be said that financial security can be defined as the ability of the company to settle current liabilities and increase their level of equity. Enterprises must maintain financial liquidity and working capital at a level that ensures the settlement of current payments as well as allowing obtaining of profits. Importantly, these profits should mostly remain in the enterprise and increase equity. They should not be paid in full as dividends to the owners. Today, in times of crisis, maintaining the appropriate levels of financial liquidity and the level of net working capital for the company and increasing the level of equity capital builds the financial security of the company.

Rapid changes in financial liquidity are characteristic of the periods preceding the financial crisis and some earlier research shows that financial liquidity is critical for getting through a crisis [10,11,12,13,14,15,16,17]. Our research focuses on SMEs operating in the renewable energy sector during the COVID-19 crisis. The SME sector was intentionally selected for this study because, during the financial crisis, such units are more vulnerable and their likelihood of bankruptcy is high [18,19]. Secondly, our research is the first one that takes the financial strategy of SMEs operating in the developing Renewable Energy Sources sector (RES) into concern. When firms operate in developing sectors, especially SMEs, it is difficult to obtain favorable financial results [20]. Renewable energy sources are said to be very popular, both on a global scale and in the European Union [21,22,23,24]. RES can also contribute to socio-economic development, especially in developing countries, by increasing the national income and offering new job opportunities [25,26,27]. Moreover, research on the financial strategy of SME enterprises in the RES sector could improve our understanding of financial supply chains.

During the COVID-19 period and individual lockdowns, the relationship between financial liquidity and profitability is significant for all industries and enterprises. Several studies show that the successive closures of the economy negatively affected the safety of SMEs operating in various industries [28,29]. There are currently no studies to show how the COVID-19 pandemic has affected the financial liquidity of renewable energy (RE) equipment companies. In the case of SMEs from the sector related to renewable energy, which operated practically continuously during the pandemic, the liquidity management process relies heavily on the management of current assets, especially inventories. Breaks in supply chains mean that SMEs in the sector related to renewable energy are trying to accumulate stocks above the safety reserve. It is expensive and negatively affects profitability. However, the renewable energy industry is still developing and companies can achieve high margins. In addition, the EU’s policy to move away from fossil energy sources means that the demand for equipment related to the renewable energy industry is still high. Therefore, SMEs operating in the renewable energy industry may use conservative liquidity management strategies during COVID-19, which may also be very profitable. However, there are many studies in which it is indicated that the use of a conservative liquidity management strategy negatively affects profitability [30,31,32].

In the paper the following research questions have been raised: To what extent had the COVID-19 pandemic affected the financial liquidity and financial policies of RE equipment SMEs, and to what extent has the conservative liquidity management strategy of the RE equipment sector companies affected the profitability of the surveyed companies?

In other words, the present study aims to evaluate and analyze the financial security management of renewable energy SMEs during the COVID-19 pandemic. We also want to know if the COVID-19 pandemic has affected the financial performance of SMEs operating in the renewable energy industry.

2. Literature Review

Financial liquidity and profitability are two of the most important pillars determining the position of companies in the market [33]. Consistent with Zimon [34], management in virtually every industry must decide which direction to lead the firm. Two contrasting decisions are to lead the firm in the direction of the highest possible profits or to keep the company safely in the market. Company executives know that maintaining high liquidity and high profitability simultaneously is almost impossible because the two are move in opposite directions in the market [34,35]. Therefore, companies should naturally seek to make a balance between them. Firms not only have to have the optimal level of liquidity in times of financial crisis so that they can show appropriate flexibility to unexpected events, but they also need to have reasonable profitability so that they can attract more investors and creditors. The critical point is that all companies in any industry need adequate financial liquidity for their economic growth; however, liquidity management is complicated since it relates to current assets, short-term liabilities, and profitability [34,35]. In the renewable energy sector, the complexity of technologies, climate change, climate policy, the shortage of qualified personnel, the lack of knowledge and experience in marketing and communication, and the lack of know-how technology have been listed as the most significant obstacles to achieving greater economic development [36,37,38,39,40]. However, the lack of financial resources is undoubtedly the most critical barrier to corporate development [34,35]. In fact, due to specific industry characteristics in the energy sector, adequate liquidity is essential for continuing the business activities of companies active in the industry [41,42].

Therefore, managing financial liquidity is the most difficult area of financial management of a company, as the company managers are forced to simultaneously make numerous decisions regarding current assets and liabilities. These particular decisions build financial liquidity management strategies, shape the level of financial security of the company, and greatly impact the level of profitability. The choice between financial liquidity and profitability is one of the biggest dilemmas faced by managers when creating financial liquidity management strategies [41,42].

Profitability and financial liquidity are elements that those interested in the company’s financial data, i.e., managers, owners, competitors, or banks granting a loan, pay attention to. Thus, these measures in the enterprise must reach the best possible levels. Managers must often decide what is more important for enterprises and decide between management towards maintaining high financial liquidity or earning high profitability. Managers must, therefore, consider the trade-off between liquidity and profitability when developing an appropriate liquidity management strategy. It should be remembered that a faster increase in the costs of maintaining working capital in relation to the benefits associated with maintaining a larger number of inventories and offering long trade credit to clients may lead to a decrease in the profitability of enterprises [31,32,42,43,44,45]. In this case, the cost to maintain current assets continuously increases. Therefore, it is difficult to achieve the optimal level between financial liquidity and profitability. There are many studies in the literature whose results indicate that company managers must decide whether to maintain a high level of financial liquidity or aim for high profitability. Several global studies have confirmed the correlation between profitability and financial liquidity of enterprises [31,32,46,47,48,49].

Part of this research focuses on the most important liquidity ratios, namely, liquidity ratio and quick ratio. The liquidity ratio is one of the financial ratios obtained by dividing cash assets by current liabilities. The quick ratio is calculated by dividing current assets (excluding inventory and prepaid expenses) by current liabilities. In general, the liquidity ratio can show a company’s ability to meet its debts, while the quick ratio looks more cautiously at the firm’s ability to meet short-term liabilities and only examines the firm by considering assets with faster liquidity [45,46,47,48]. As previously stated, the complicated relationship between profitability and liquidity makes it difficult to choose the right liquidity management strategy, especially during a financial crisis [48].

Hence, after examining corporate profitability ratios, this paper analyzes if COVID-19 has changed financial liquidity management strategies such as liquidity and quick ratios. In this regard, companies adopt a variety of working capital management strategies. There are generally three types of strategies that are used by enterprises depending on the current market conditions. These aggressive, moderate, and conservative strategies take different approaches to inventory management. If a company invests heavily in working capital, i.e., adopts a conservative policy, it can lead to higher profits as a result of holding higher stock levels. This conservative strategy provides greater security and minimizes the cost of depletion, production downtime, delivery costs, and price volatility. This is confirmed by studies carried out in the chemical industry in Pakistan [10]. As stated in the introduction, a conservative strategy could be interesting for SMEs in a developing industry, even though earlier research indicates that the use of a conservative strategy could also negatively affect profitability [28,29,30].

Today, however, in times of pandemics, financial crises, climate crises, or armed conflicts, it seems that most management will try to use safe corporate management strategies. It can be expected that there will be a slow departure from the classic strategies of managing assets, liabilities, or the entire enterprise. It will surely be caused by problems related to logistics. The COVID-19 pandemic initially showed how the process of organizing supplies was lengthening. The inventory management strategy will play a key role in managing financial security. It used to be believed that excessive stockpiling had a negative effect on financial results and financial liquidity [39]. Now, it seems worthwhile to stock up due to increased safety. Even though longer storage causes higher inventory maintenance costs, it might also bring high revenues and profits in the future. It seems that in the future, logistics management will have a key impact on the company’s management strategies.

3. Method

3.1. Methodology Design

The study sample consists of 68 SMEs operating in the renewable energy industry in the Polish market from 2019 to 2020. In the fundamental sense, the definition of an SME is currently defined in the Act of 6 March 2018. Entrepreneurs’ law (i.e., Journal of Laws 2019, item 1292), in art. 7 of the Act. The basic criteria taken into account when determining the company’s status are as follows. Micro-, small- and medium-sized enterprises (SMEs) comprise enterprises that employ fewer than 250 persons and have an annual turnover not exceeding EUR 50 million or an annual balance sheet total not exceeding EUR 43 million. The analyzed data was obtained from the National Court Register.

The subject of activity was the first criterion to distinguish SMEs operating in the RE equipment branch (the analyzed enterprises are therefore indirectly related to the renewable energy sector, but are included in the renewable energy branch in Poland).

Only those enterprises whose business profile corresponded to PKD 46.74.Z (wholesale of metal products and equipment and additional plumbing and heating equipment) and PKD 46.73.Z (wholesale of wood, construction materials, and sanitary equipment) were selected. Then, the companies that submitted financial reports for 2019–2020 were chosen. Based on these reports, the enterprises, which can be classified as SMEs, were selected. The last step was to analyze and assess whether the companies in question carry out commercial activities related to trade in RE equipment. It was carried out based on information obtained from the internet and the commercial offer of individual enterprises. Based on the research, a sample of 68 enterprises classified as SMEs that run commercial activities in the field of RE equipment was obtained.

According to the purpose of our research, 2019 was defined as the period before the COVID-19 pandemic (BC), whereas 2020 was considered the time during the coronavirus pandemic (DC). Descriptive statistics were calculated using the statistical mean, median, maximum, and minimum values for the most important financial indicators related to the financial security management strategy. The Jarque–Bera test was also used in this study to measure the normality of the distribution of observations of variables [48,49,50,51]. A relatively comprehensive review of strategies of SMEs, which are the most crucial factor in Poland’s economic growth, has been conducted using financial liquidity, short-term receivables turnover ratio in days, short-term liabilities turnover ratio in days, inventory turnover ratio in days, cash conversion cycle (CCC), operating cycle (OC), the share of working capital, short-term receivables, short-term investment, and inventory ratios in the structure of current assets.

This study uses a paired comparison test to analyze accurately the effects of the COVID-19 crunch on companies’ financial security management policies. The results of paired comparison tests are reported using the t-test and Satterthwaite–Watch t-test. Based on the principles of paired comparison tests, test statistics were determined to be significant at the level of five percent. That level indicates a significant difference between the mean of the variable in the previous periods and during the COVID-19 crisis.

3.2. Definition of Variables

According to the view of Raczkowski [4,52,53,54,55], financial security is a process of constant limitation and elimination of money risk in order to secure capital adequacy in such a way that will be adjusted to the risk profile and preference of the entity. During the economic crisis of the COVID-19 pandemic, Zimon and Tarighi [56], in a very interesting work, tried to introduce another definition of financial security by presenting new indicators. It can be said that their attitude regarding financial security was largely based on high levels of liquidity, working capital, and equity. Following Zimon and Tarighi [56], this paper argues that financial security is closely related both to the level of financial liquidity and the level of working capital in enterprises. Today, when we are facing the economic crisis of COVID-19 or the war in Europe, maintaining the appropriate levels of financial liquidity and the level of net working capital for the company and increasing the level of equity builds the financial security of the company. In fact, enterprises must maintain financial liquidity and working capital at a level that ensures the settlement of current payments as well as allows the ability to obtain profits. Among SMEs, our variables in this study are the most important indicators that express financial security at the company level.

In order to compare the financial performance of Polish companies during and before the Coronavirus crisis, three different criteria called ROA, ROE, and ROS have been used in this research. For example, earnings before interest and taxes (EBIT) divided by the sum of a company’s assets is defined as return on asset (ROA) [47,48], while return on equity (ROE) is the measure of a company’s net income divided by its shareholders’ equity [57]. Return on sales (ROS) is also a standardized ratio describing an operation’s profits as a percentage of their sales revenue [56]. The variable of financial liquidity is the sum of cash and short-term investments divided by total assets [54,55,56,58,59]. Current assets minus inventory divided by current liabilities equal to quick ratio [56,58,59]. From the multiplication of the number of days of one year in the ratio of the account receivables divided by the sales, the receivables turnover variable can be calculated. If we divide the inventory by the sales, then multiply it by 365, it is equal to inventory turnover. Liabilities turnover is calculated by the ratio of account payables to sales multiplied by 365 [57,58,59]. Debt Ratio is a financial ratio that indicates the percentage of a company’s assets that are provided via debt. An operating cycle refers to the time it takes a company to buy goods, sell them, and receive cash from the sale of said goods. Cash Conversion Cycle (CCC) measures how long a firm will be deprived of cash if it increases its investment in inventory in order to expand customer sales. CCC is equal to the sum of the average collection period and inventory holding period minus the average payment period [56,60,61,62]. Finally, the ratio of Inventory in CA is obtained by dividing the inventories by the current assets, whereas variables of receivables in CA and short investment in CA are calculated by dividing accounts receivable and short-term investments on current assets, respectively [56].

4. Results

4.1. Winsorizing the Outliers

Observations that are much larger or smaller in size than other observations of the same category are called outliers. The presence of outlier observations may have an adverse effect on the results of research. In most cases, the rejection of the classic regression assumptions and bias of the coefficients of a regression model result from their existence. Conventional methods are usually used to detect outliers. In financial and accounting research, observations that are less than the fifth percentile and greater than the ninety-fifth percentile are usually considered outliers. Typically, two common behaviors to treat outlier data are (1) trimming (2) winsorizing [63,64,65]. In this study, we use the method of winsorizing, in which outlier observations are removed and replaced by other numbers such as the percentile. In this research, for observations less than the fifth percentile, the number of fifth percentile has been replaced, and for observations greater than the ninety-fifth percentile, the relevant number has been replaced. In fact, after winsorizing outlier data, the results of the Jarque–Bera test, shown in the last column of

Table 1. Comparative descriptive statistics.

Variable Name	Mean	Median	Max	Min	Std. Dev.	Jarque–Bera
Return on Asset (ROA)—BC	0.0811	0.0760	0.2075	0.0090	0.0545	0.0995
Return on Asset (ROA)—DC	0.0902	0.0775	0.2001	0.0109	0.0571	0.1300
Return on Equity (ROE)—BC	0.1495	0.1285	0.4179	0.0172	0.1040	0.0903
Return on Equity (ROE)—DC	0.1525	0.1390	0.3989	0.0225	0.0988	0.0735
Return on Sales (ROS)—BC	0.0375	0.0300	0.0810	0.0100	0.0230	0.0622
Return on Sales (ROS)—DC	0.0438	0.0400	0.1000	0.0100	0.0282	0.0519
Financial Liquidity—BC	3.2527	2.3500	9.7300	0.9000	2.4218	0.1094
Financial Liquidity—DC	3.4779	2.6500	9.1000	0.8000	2.4591	0.0758
Quick Ratio—BC	1.6627	1.1000	4.9000	0.2900	1.3552	0.1317
Quick Ratio—DC	1.7705	1.2500	5.1100	0.2900	1.4026	0.1950
Receivables turnover—BC	62.4779	65.5000	93.5000	17.8000	19.4546	0.0835
Receivables turnover—DC	59.1264	61.0000	88.2000	26.0000	17.0237	0.3363
Inventory turnover—BC	66.5258	63.0000	102.5200	40.8000	16.8921	0.1294
Inventory turnover—DC	67.8529	68.6000	97.6000	41.4000	15.5344	0.3353
Operation Cycle—BC	129.6965	127.1000	168.7200	94.0000	20.7658	0.2719
Operation Cycle—DC	127.1268	131.5000	156.8400	87.7000	20.4118	0.1564
Liabilities turnover—BC	62.4588	60.0000	132.8000	17.9000	33.8577	0.0673
Liabilities turnover—DC	62.1994	57.0000	142.4000	20.7200	36.3005	0.1169
Debt Ratio—BC	0.4936	0.5150	0.7610	0.1090	0.1902	0.0798
Debt Ratio—DC	0.4593	0.4950	0.7320	0.1090	0.1877	0.1108
Cash Conversion Cycle—BC	67.1926	61.6000	140.1000	−3.1000	42.1091	0.1939
Cash Conversion Cycle—DC	65.6517	72.0000	132.2400	−11.3000	41.9680	0.1878
Inventory in CA—BC	0.4784	0.4800	0.7220	0.3070	0.1000	0.1334
Inventory in CA—DC	0.4921	0.5100	0.7060	0.2990	0.1022	0.9198
Receivables in CA—BC	0.4475	0.4700	0.6130	0.1590	0.1171	0.0604
Receivables in CA—DC	0.4108	0.4400	0.5910	0.1590	0.1149	0.1127
Short Investment in CA—BC	0.0704	0.0450	0.2540	0.0100	0.0680	0.0592
Short Investment in CA—DC	0.0876	0.0600	0.2870	0.0190	0.0768	0.0835

Source: Own research.

, also confirms that all variables are free of outlier data because they have a normal distribution.

4.2. Descriptive statistics

The research was carried out on a group of 68 Polish SMEs. The research involved commercial units operating within the largest purchasing groups in Poland operating in the construction industry. After winsorizing the outlier data, our purpose is to provide a table of descriptive statistics showing a general picture of the state of distribution of observations of each variable. In other words, for a better understanding and accurate comparison between data values in the period before COVID-19 (BC) and during the COVID-19 pandemic (DC), comparative descriptive statistics are shown in Table 1.

What stands out from the table one is that the average annual rate of return on assets (ROA), return on equity (ROE), and return on sales (ROS) have improved slightly during COVID-19 compared to before the pandemic. In addition, during COVID-19, the range of fluctuations related to the ratio of ROA is between 0.0109 and 0.2001, the ratio of ROE is between 0.0225 and 0.3989, and the ratio of ROS is between 0.010 and 0.1. However, the difference in volatility between the two variables of ROA and ROE was equal to (0.2075 − 0.0090 = 0.1985) 0.1985 and (0.4179 − 0.0179 = 0.4007) 0.4007, respectively, which was higher when compared to the Corona crisis. In general, the closeness of the average of the three financial performance measures during and before the COVID-19 crisis confirms the fact that Polish SMEs have tried to maintain their financial security in the uncertainty economic situation of the pandemic by adopting appropriate strategies so they can compete with others.

Regarding the liquidity ratios, the averages related to liquidity and quick ratios increased during COVID-19 compared to the previous period. This implies that the SMEs studied have adopted conservative strategies. They have resorted somewhat to more cash during the crisis to be more financially resilient in necessary situations. Moreover, let us look at the descriptive statistics of efficiency ratios such as Receivables turnover, Liabilities turnover, Inventory turnover, and operation cycle. The results show that companies have adopted more conservative policies during the crisis than in the past. For instance, since the average collection period of the company’s receivables is shorter than before, the firms are said to be less under financial pressure to secure their credit and increase working capital, thus increasing their revenue. Consistent with the conservatism strategy, we find that the average receivables turnover is shorter than liabilities turnover during the COVID-19 pandemic. This is beneficial for the company as evidenced by research (Habib). The company credits its activities with the cheapest source of financing, which is a trade credit. Furthermore, given that the average operation cycle has become shorter than before the crisis, it indicates that SMEs operating in the renewable energy industry need less working capital because their receivables collection periods are shorter. It will take less time for the produced goods to become cash. However, an increase in average inventory turnover compared to before the crisis could be due to the company’s decreased inventory investment. In addition, the operational cycle of converting materials and goods into cash may be short. Suppose the structure of current assets of Polish SMEs in the energy sector is analyzed. In that case, we see that the average share of inventory and short-term investments in current assets has increased during the crisis, while the amount of accounts receivable dropped. Finally, the last column of descriptive statistics focuses on evaluating the normality of the distribution of observations of variables. According to the results of the Jarque–Bera test, as the amount of probability of all variables in this study is greater than five percent, the normality assumption of the variables is supported.

4.3. Significance Testing

The main purpose of this study is to compare financial security strategies during the pandemic and to determine the types of approaches managers adopt to deal with the crisis. There is a comparison of financial security management strategies during and before COVID-19. These strategies are conservative and aggressive strategies for managing financial liquidity and net working capital. Among the types of paired tests, the Student t-test can be employed to compare mean differences between data when the observations have been obtained in pairs. In this paper, to compare the mean value of the two sets of data during and before COVID-19 and to evaluate its significance, the statistics of the paired t-test, Satterthwaite–Watch t-test, and Welch F-test can be used. In general, the paired Student t provides a hypothesis test of the difference between population means for a pair of random samples whose differences are approximately normally distributed [54,60]. According to the research literature, we generally have three types of t-tests called one sample t-test, independent samples t-test, and paired samples t-test [57,65]. Our study includes the third type. The paired t-test is employed to compare mean dissimilarities when the observations have been gained in pairs, and are thus dependent. In fact, the null hypothesis of the t-test states that both means are statistically equal, while the alternative hypothesis refers to the opposite of this claim [57,65]. In this research, examining the differences between financial management policies in the era before and after the COVID-19 crisis can be a very good example of the application of the paired t-test. In this study, we assume there are 68 pairs of observations and that each pair is independent of the other pairs. It is assumed that the paired observations as $X_i$ and $Y_i$ for two periods during the COVID-19 pandemic (DC) and before the COVID-19 (BC) and their differences as $d_i$ for i = 1, 2, … n. As mentioned earlier, the evidence shows that our observations are normally distributed with means ${\mu }_x$ and ${\mu }_y$. The random variable D = X − Y is then normally distributed with mean ${\mu }_{d=} {\mu }_{x-}{\mu }_y$ and variance $Q_d^2$. Accordingly, the null hypothesis is $H_0$: ${\mu }_d=0$ [53]. In short, the formula to calculate the Student t-test is as follows:

$$\mathrm{t}=\frac{d}{(S_{d/\sqrt{n}})}$$

Similar to the Student t-test, the Welch t-test assumes that the population of the two groups are normal. However, the Student t-test presumes that the two populations have the same variance while the Welch t-test does not make any assumption on the variances. According to Ahad and Yahaya [65], the Welch t-test is the parametric test for comparing means between two independent groups without assuming equal population variances. This statistic is even robust for testing the mean equality when the homogeneity hypothesis is not satisfied. Unlike the Student t-test, the Welch t-test does not pool across heterogeneous sources of variability where the denominator is not based on the pooled variance estimate. The Welch t-test is defined by the following formula [65];

$$\mathrm{t} = \frac{\overleftarrow{X1}-\overleftarrow{X2}}{\sqrt{\frac{s_1^2}{n_1}+\frac{s_2^2}{n_2}}}$$

In other words, under the null hypothesis, t is roughly distributed as the t-distribution with degrees of freedom. Finally, in statistics and uncertainty investigation, the Welch–Satterthwaite equation is used to calculate an approximation to the effective degrees of freedom of a linear combination of independent sample variances, also known as the pooled degrees of freedom [66,67], corresponding to the pooled variance. Various researchers have made many efforts to calculate a suitable degree of freedom for the Welch’s t statistics [67,68,69,70], but all of them are considered as approximate degree of freedom (ADF) [65]. The degrees of freedom associated with this variance estimate is approximated from the sample data using the Welch–Satterthwaite equation, shown below:

$$\mathrm{df}={(\frac{S_1^2}{n_1}+\frac{S_2^2}{n_2})}^2/{(\frac{S_1^4}{n_1^2(n_1-1)}+\frac{S_2^4}{n_2^2(n_{2-1)}})}^2$$

The null hypothesis of equal population mean is rejected when p-value ≤ α, where α is the significance value. The p-value of one tail test is then defined as:

$$\mathrm{p}=P\left(t>t_0|t~t_{\alpha ,df}\right)$$

where $t_0$ is the calculated t value. The p-value of two tailed test considered in this study is given by [54]:

$$\mathrm{p}=2P\left(t>t_0|t~t_{\alpha ,df}\right)$$

Based on the existing research literature, the ratios of the return on assets (ROA), return on equity (ROE), and return on sales (ROS) have been used in various types of research as a criterion for evaluating the financial performance of companies [35,36]. Before analyzing the various financial policies, we first want to show that the economic crisis caused by COVID-19 has worsened the financial performance of Polish SMEs within the energy sector. Hence, these results are presented by comparing the average of the above three ratios during COVID-19 (DC) and before COVID-19 (BC) in

Table 2. The result of ROA.

Variable	Mean	Std. Dev.	Std. Err. of Mean
Return on Asset (ROA)—(DC)	0.090265	0.057140	0.006929
Return on Asset (ROA)—(BC)	0.081199	0.054510	0.006610
Method	df	Value	Probability
t-test	134	0.946703	0.3455
Satterthwaite–Welch t-test	133.7034	0.946703	0.3455
Welch F-test	(1133.703)	0.896247	0.3455

Source: Own research.

,

Table 3. The result of ROE.

Variable	Mean	Std. Dev.	Std. Err. of Mean
Return on Equity (ROE)—(DC)	0.152591	0.098841	0.011986
Return on Equity (ROE)—(BC)	0.149578	0.104088	0.012623
Method	df	Value	Probability
t-test	134	0.173106	0.8628
Satterthwaite–Welch t-test	133.6431	0.173106	0.8628
Welch F-test	(1133.643)	0.029966	0.8628

Source: Own research.

and

Table 4. The result of ROS.

Variable	Mean	Std. Dev.	Std. Err. of Mean
Return on Sales (ROS)—(DC)	0.043824	0.028286	0.003430
Return on Sales (ROS)—(BC)	0.037544	0.023029	0.002793
Method	df	Value	Probability
t-test	134	1.419638	0.1580
Satterthwaite–Welch t-test	128.7090	1.419638	0.1581
Welch F-test	(1128.709)	2.015371	0.1581

Source: Own research.

as follows:

The results show that the average ROA and ROE during the COVID-19 crunch have improved compared to the past, while the trend of ROS ratio has moved in the opposite direction; however, none of these results are meaningful and reliable because the p-value of statistics of the student t-test, Satterthwaite–Welch t-test, ANOVA F-test, and Welch F-test are greater than five percent. It seems that Polish SMEs operating in the RE sector have been able to stabilize and maintain their previous economic position. In fact, they have neither progressed nor regressed significantly; they have only maintained their economic position in the market. As their financial position in the market stabilizes, they may be waiting to see what the future holds for the market.

In the next step of this research, we intend to examine two of the most important liquidity ratios: liquidity ratio and quick ratio. Here, we analyze if COVID-19 has changed financial liquidity management strategies such as liquidity and quick proportions among the SMEs.

Given that the probabilities of the different statistics in

Table 5. The result of the financial liquidity ratio.

Variable	Mean	Std. Dev.	Std. Err. of Mean
Liquidity ratio—(DC)	3.477941	2.459150	0.298216
Liquidity ratio—(BC)	3.252794	2.421832	0.293690
Method	df	Value	Probability
t-test	134	0.537918	0.5915
Satterthwaite–Welch t-test	133.9687	0.537918	0.5915
Welch F-test	(1133.969)	0.289355	0.5915

Source: Own research.

are more than five percent, the results insignificantly show that companies are inclined to have a larger share of their current assets in cash during the crisis. Therefore, they have a higher ability to pay off short-term debt and more financial flexibility than unexpected events and continue competing with others. As the amount of p-value of all statistics is insignificant, the results of the quick ratio in

Table 6. The result of the quick ratio.

Variable	Mean	Std. Dev.	Std. Err. of Mean
Quick ratio—(DC)	1.770558	1.402608	0.170091
Quick ratio—(BC)	1.662794	1.355256	0.164349
Method	df	Value	Probability
t-test	134	0.455791	0.6493
Satterthwaite–Welch t-test	133.8423	0.455791	0.6493
Welch F-test	(1133.842)	0.207709	0.6493

Source: Own research.

also state that mining firms have adopted a conservatism approach in which the companies’ ability to meet their short-term obligations with their most liquid assets has increased unimportantly compared to the past. As the results in the previous step confirmed that most companies have sought to maintain their economic position in the market, the liquidity ratios now show that companies have tried to improve their liquidity situation slightly. This is because the profitability index should not be seriously affected, which is in line with the policy of balancing liquidity and profitability. Furthermore, as far as we know, short-term receivables turnover, short-term liabilities turnover, inventory turnover, cash conversion cycle (CCC), and operating cycle (OC) are defined as corporate efficiency ratios focusing directly on corporate liquidity management [27]. Therefore, we want to know if the economic crisis has led to fundamental changes in the above working capital management policies. The results for each are presented in

Table 7. The result of short-term receivables turnover.

Variable	Mean	Std. Dev.	Std. Err. Of Mean
Receivables turnover—(DC)	59.12647	17.02376	2.064434
Receivables turnover—(BC)	62.47794	19.45465	2.359222
Method	df	Value	Probability
t-test	134	−1.069072	0.2870
Satterthwaite–Welch t-test	131.6816	−1.069072	0.2870
Welch F-test	(1131.682)	1.142915	0.2870

Source: Own research.

,

Table 8. The result of short-term liabilities turnover.

Variable	Mean	Std. Dev.	Std. Err. Of Mean
Liabilities turnover—(DC)	62.19941	36.30058	4.402092
Liabilities turnover—(BC)	62.45882	35.85870	4.105849
Method	df	Value	Probability
t-test	134	−0.043094	0.9657
Satterthwaite–Welch t-test	133.3548	−0.043094	0.9657
Welch F-test	(1133.355)	0.001857	0.9657

Source: Own research.

,

Table 9. The result of inventory turnover.

Variable	Mean	Std. Dev.	Std. Err. of Mean
Inventory turnover—(DC)	67.89294	15.53447	1.883832
Inventory turnover—(BC)	66.52588	16.89215	2.048475
Method	df	Value	Probability
t-test	134	0.476845	0.6342
Satterthwaite–Welch t-test	133.0702	0.476845	0.6342
Welch F-test	(1133.07)	0.227381	0.6342

Source: Own research.

,

Table 10. The result of the cash conversion cycle (CCC).

Variable	Mean	Std. Dev.	Std. Err. of Mean
Cash conversion cycle—(DC)	65.65176	41.96809	5.089379
Cash conversion cycle—(BC)	67.19265	42.10918	5.106489
Method	df	Value	Probability
t-test	134	−0.213727	0.8311
Satterthwaite–Welch t-test	133.9985	−0.213727	0.8311
Welch F-test	(1133.998)	0.045679	0.8311

Source: Own research.

and

Table 11. The result of the operating cycle (OC).

Variable	Mean	Std. Dev.	Std. Err. of Mean
The operating cycle—(DC)	127.1268	20.41182	2.475297
The operating cycle—(BC)	129.6965	20.75581	2.518224
Method	df	Value	Probability
t-test	134	−0.727739	0.4680
Satterthwaite–Welch t-test	133.9604	−0.727739	0.4680
Welch F-test	(1133.96)	0.529604	0.4680

Source: Own research.

, respectively.

The COVID-19 pandemic has led companies to adopt a more conservative policy towards customers and suppliers for better liquidity security. The results of Table 7 show that mining enterprises receive much faster receivables from their customers. In contrast, the outputs of Table 8 confirm that the duration of their debts to suppliers and creditors has been almost the same as in the past. Given the insignificance of the above statistical results, it can be concluded that the risk of lack of liquidity could not pose a serious threat to SMEs operating in the energy sector that forces them to collect more receivables faster and pay their debts later. Before the occurrence of the COVID-19 economic crisis, managers had a conservative mindset and had enough cash reserves for their companies to be able to prepare themselves in advance to face difficult situations without surprised.

The important point is that inventories will increase financial liquidity ratios when security reserves are generated [10,23]. The findings of Table 9 highlight the fact that inventory turnover in days during the COVID-19 period are longer than before, even though it is not statistically meaningful. The high inventory turnover during the crisis may be because SMEs’ investment in inventories has decreased or the operational cycle of converting materials and inventories into cash is short.

Regarding the ratio of cash conversion cycle (CCC), it can be stressed that CCC has been widely applied as a useful and comprehensive measure of working capital management because it measures the liquidity risk entailed by growth [28,29,30,31,55,56]. CCC evaluates how long a firm will be deprived of cash when it upturns its investment in inventory to develop customer sales. A short CCC means a quick collection of receivables and delays in payments to suppliers, which is connected with positive financial performance because it affects the effective use of working capital [56]. As mentioned, mining companies seem to have had conservative policies before the crisis and saved enough cash. Hence, due to the lack of significant impact of the Corona crisis on the shortening of the cash conversion cycle, we can conclude that SMEs did not need working capital and high cash because they had already considered the necessary measures before the COVID-19 crisis. Table 11 presents the results of enterprise management efficiency indicators (operating cycle).

Companies that have managed the crisis well before and need less cash are usually expected to have shorter operating cycles during the economic crisis. Since the amount of p-value for relevant statistics is more than five percent, the outcomes are not statistically significant. However, we realized that the COVID-19 pandemic has significantly caused companies to reduce their operating cycle. A company with a shorter operating cycle needs less working capital. Because these companies have a lower receivables collection period, it will take less time for their goods to be converted into cash; therefore, they do not need to increase current assets to support their current debt. Another key question in this study is whether mining companies prefer to source most of their assets from debt during the economic crisis. To this end, analyzing the debt ratio results in

Table 12. The result of the debt ratio.

Variable	Mean	Std. Dev.	Std. Err. of Mean
Debt ratio—(DC)	0.459309	0.187729	0.022765
Debt ratio—(BC)	0.493676	0.190204	0.023066
Method	df	Value	Probability
t-test	134	−1.060463	0.2908
Satterthwaite–Welch t-test	133.9770	−1.060463	0.2908
Welch F-test	(1133.977)	1.124583	0.2908

Source: Own research.

can determine the answer to this question.

The statistical outputs from Table 12 indicate that the average debt ratio during COVID-19 has declined insignificantly in comparison with before. In fact, since lower debt ratios indicate less business risk, Polish companies in uncertain economic conditions have sought to build safer and less risky business environments. However, this finding is not statistically meaningful.

Regarding the structure of current assets, it can be generally said that there are two strategies called aggressive and conservative. It is obvious is that if small- and medium-sized companies do not adopt a suitable working capital strategy, their financial security will be jeopardized [60], and they may collapse during the Corona financial crisis. Since SMEs do not have huge capital and are largely dependent on bank loans and commercial credits compared to larger companies, they are more vulnerable to working capital fluctuations and are less inclined to take on high risks [61]. In order to understand this concept more deeply, we attempted to analyze the components of current assets structure of Polish SMEs to determine which of the aggressive or conservative approaches were aligned during the COVID-19 crunch. Hence, the last fundamental question of this paper is whether small- and medium-sized enterprises in the energy sector have made fundamental changes to their current asset structure policies during the COVID-19 crisis. To find this answer, this study compares the structure of SMEs’ current assets before and during the crisis in

Table 13. The result of the share of inventories in current assets.

Variable	Mean	Std. Dev.	Std. Err. of Mean
Share of inventories in CA—(DC)	0.492132	0.102287	0.012404
Share of inventories in CA—(BC)	0.478485	0.100017	0.012129
Method	df	Value	Probability
t-test	134	0.786641	0.4329
Satterthwaite–Welch t-test	133.9325	0.786641	0.4329
Welch F-test	(1133.933)	0.618804	0.4329

Source: Own research.

,

Table 14. The result of the share of receivables in current assets.

Variable	Mean	Std. Dev.	Std. Err. of Mean
Share of receivables in CA—(DC)	0.410882	0.114913	0.013935
Share of receivables in CA—(BC)	0.447588	0.117140	0.014205
Method	df	Value	Probability
t-test	134	−1.844585	0.0473 *
Satterthwaite–Welch t-test	133.9507	−1.844585	0.0473 *
Welch F-test	(1133.951)	3.402495	0.0473 *

Source: Own research. Note: (*): 95% Confidence level.

and

Table 15. The result of the share of short investment in current assets.

Variable	Mean	Std. Dev.	Std. Err. of Mean
Share of investment in CA—(DC)	0.087618	0.076818	0.009316
Share of investment in CA—(BC)	0.070471	0.068038	0.008251
Method	df	Value	Probability
t-test	134	1.377932	0.1705
Satterthwaite–Welch t-test	132.0734	1.377932	0.1705
Welch F-test	(1132.073)	1.898696	0.1705

Source: Own research.

.

If we look carefully at the results of Table 13, it is clear that the share of inventories in the current assets portfolio increased insignificantly during the Coronavirus pandemic compared to before. According to the conservative working capital perspective, maintaining high levels of inventory in current assets cannot only reduce risk of liquidity associated with the opportunity cost of funds that may have been invested in long-standing assets, but it also declines the cost of interruptions in the production process, provides cost, and protects against price variation and loss of business owing to shortage of product [67]. In general, from a statistical point of view, the non-significant coefficient ratio of inventories in CA shows that the companies have moved very slightly and unimportantly towards a conservative approach in relation to inventories. If we analyze the results in Table 15 well, we can find such a similar scenario regarding short-term investments. Since maintaining financial security and having better liquidity conditions is more important to Polish SMEs, they have tried to have a non-significant increase in short-term investments so that they can quickly convert them into cash to have better flexibility during the COVID-19 pandemic. Finally, the results of Table 14 witness a significant decrease in the share of receivables in current assets structure during the COVID-19 pandemic in comparison with before, supporting the conservative approach. In other words, during the COVID-19 crisis, which has reduced the income of many people, companies have preferred to set structure their current assets in such a way that they take less risk in obtaining the necessary liquidity and have fewer credit sales. In the conditions of the Coronavirus crisis, when the economic situation is uncertain and the general livelihood situation is not very favorable, it seems that cash sales and having less accounts receivable from customers can be a more suitable solution to maintain the financial safety of SMEs.

5. Discussion and Conclusions

This article focused on questions related to the extent in which the COVID-19 pandemic affected the financial liquidity and financial policies of RE equipment SMEs. It also studied the extent to which the profitability of the surveyed companies was affected. The research was conducted on SMEs operating in the renewable energy sector in Poland. The research periods are 2019 (before the COVID-19 crisis) and 2020 (during the crisis). By analyzing different financial performance ratios, we find that Polish SMEs have chosen to adopt conservative strategies to cope with the difficult economic situation caused by the COVID-19 crunch in order to have better liquidity security.

The detailed analysis showed that the companies studied operating during the COVID-19 pandemic did not record worse financial results than in 2019. Renewable energy is a dynamically developing industry; therefore, the demand for materials and devices related to it is constantly high. In Poland, the construction industry is also in an upward trend, which positively affects the trade in devices related to renewable energy. In addition, inflation, which is high in Poland, prompted the search for places where investors could safely allocate funds. And recently, investments in the housing market have been a good opportunity to deposit cash.

As a result of all this, in the case of commercial SMEs operating in the sector related to renewable energy, in the COVID year, compared to 2019, a non-significant increase in the level of current financial liquidity, quick liquidity, and maintaining the profitability of assets, equity, and sales profitability at practically the same level was recorded. In the case of the return on assets, an increase was even recorded.

In the literature, one can find a number of studies where the authors [29,31,33,71,72,73,74] indicate that the increase in the level of financial liquidity negatively affects profitability. Interestingly, this phenomenon is not visible in the enterprises analyzed. This is because, in the case of a growing industry, demand drives sales, which has a positive effect on margins. High margins, in turn, can cover growing costs, such as the costs of maintaining inventories. In the enterprises, in the structure of current assets, an increase in the level of inventories and short-term investments was observed compared to the results from 2019. The increase in the level of inventories certainly increases the costs.

During COVID-19, there was a problem with the supply of goods, which is why companies operating in the RE industry were often forced to suspend sales. Managers often choose the direction of stockpiling over the demand at a given moment.

In turn, an increase in short-term investments positively affects the level of financial liquidity. In the analyzed entities, the general debt ratio was observed to be maintained in 2020. In these enterprises, the strategy of managing liabilities was based on their prompt payment. As they had free cash, enterprises immediately settled their liabilities to avoid a situation in which the producer would block them due to the failure to pay the liabilities on time, which would benefit competing enterprises.

In summary, the data indicates that during COVID-19, the analyzed companies operating in the renewable energy sector that were not closed during the COVID-19 pandemic and operated in an industry that is in an upward trend, did not lose money. However, they had to slightly adjust their liquidity management strategies. During the financial crisis, the share of inventories and short-term investments in the portfolio of current assets increased slightly. However, the share of accounts receivable from customers decreased significantly, indicating a movement to the moderate-aggressive strategy. In fact, by adopting a risky, aggressive policy, companies seem to have tried to benefit from out-of-company financial resources in times of crisis.

The increase in the level of liquidity caused by the high level of inventories is shaping the entire financial liquidity management strategy towards a new strategy that can be described as totally conservative [35]. Today, maintaining high current and fast financial liquidity, the same level of profitability and changes consisting in increasing the degree of financial liquidity in the structure of current assets (decrease in receivables and increase in cash in hand and in bank accounts, and an increase in the level of inventories for which there is a high demand) is an exemplary and new approach to liquidity management, especially in SMEs in Poland during the COVID-19 pandemic.

Our research also has some limitations. First, panel data were used for the research. Panel data point to datasets based on observations examined by many sectional variables often selected randomly during a given period. Since the panel data contain both aspects of time series data and sectional ones, employing appropriate statistical explanatory models that describe the specifications of the variables is more complicated than the models used in sectional and time-series data [23,35]. The second limitation is that part of 2020 was not affected by COVID-19. Third, the research sample size is an issue which only applies to the SMEs operating in the RE sector. It can be assumed that focusing attention on larger companies would reveal the existing variation in the financial strategies used and thus the response of companies during the COVID-19 pandemic. In order to confirm whether this strategy of managing current assets and short-term liabilities is effective, it is worth conducting research in other industries and among large companies as well.

Future research could look at benchmarking of companies operating in the RE sector in new countries that have joined the European Union, such as Poland and the old EU countries. Increasing the number of countries studied would improve the level of generalization for conclusions, relating to the effectiveness of strategies for managing current assets and short-term liabilities. Including large companies operating in the RE sector in the study would also make it possible to assess whether and how company size shapes financial strategies.

Research around the world shows that COVID-19 negatively affects all industries. Analyzing the period of 2022 would be a new stage of research. COVID-19 in China and the resultant market closure in China is causing an economic slowdown, which has a large impact on markets around the world. The war in Ukraine has severely hit individual markets and has caused supply problems. The decisions of OPEC countries also harm the economy of European countries.

It seems that in times of crisis, the only chance to create a sound safety management strategy for SMEs operating in the renewable energy sector is the use of multi-entity organizations such as purchasing groups or clusters. Working together will allow them to provide access to materials and goods and ensure the continuity of business operations.