Submitted:
01 October 2023
Posted:
02 October 2023
You are already at the latest version
Abstract
The medical sector is of the utmost importance in every country for well-known reasons such as their economic development, national security, quality of life, and so on. Many researchers were dedicated to this topic, however, in Romania there are limited studies on this subject. One reason is that most of the businesses in this sector are individual enterprises or small family businesses. In our research paper we deploy several analysis methods to see the financial sustainability of companies operating in the medical industry. By analyzing a sample of 23931 companies and we have concluded that their performance has increase in the peak of the pandemic and that the financial stability is high. Our results are in line with other similar studies that were conducted in other regions.
Keywords:
healthcare
; sustainability
; financial performance
1. Introduction
The medical sector is of the utmost importance in every country for well-known reasons such as their economic development, national security, quality of life, and so on. Many researchers were dedicated to this topic, however, in Romania there are limited studies on this subject. One reason is that most of the businesses in this sector are individual enterprises or small family businesses. For instance, in the case of Romania, 80% of the businesses operating in this area are individual enterprises.
Another reason for this fierce competition is represented by the fact that, in Romania, very limited funds are allocated from the (CNAS) for medical practices. The allocation in average of 2,000 lei (about 400 euros) per doctor per month, is so little, that it is usually consumed in the first or second day of the month and for the remaining period. This small amount is so unappealing that some of the medical practice even choose not to make a contract with the public health insurances house. However, the situation is radically different, in terms of public money allocation, for other areas like surgery.
Financial sustainability has become a crucial aspect of corporate management in recent years. Companies are expected to operate not only for their financial performance but also in a socially and environmentally responsible manner. The concept of financial sustainability encompasses the ability of a company to generate profits and cash flows over the long term while ensuring it does not negatively impact the environment or society. It has become increasingly critical for investors, regulators, and other stakeholders to assess a company’s long-term viability based on its financial sustainability.
This paper aims to provide a comprehensive overview of financial sustainability, its importance for SME in the health care sector, and its implications for stakeholders. The paper will begin by discussing the concept of financial sustainability, its definition, and its importance for companies. It will then measure the financial sustainability of the companies and compare these with other papers. The paper will also discuss the challenges that companies face in achieving financial sustainability and the strategies that companies can use to overcome these challenges.
Financial sustainability is a multidimensional concept that encompasses a company’s ability to generate profits and cash flows over the long term while operating in a socially and environmentally responsible manner.
The concept of financial sustainability has gained increasing attention in recent years due to several factors. First, the increasing awareness of environmental and social issues has led to a growing demand for companies to operate in a socially and environmentally responsible manner. Second, the global financial crisis of 2008 highlighted the importance of financial stability and sustainability in the corporate world. Finally, the increasing focus on corporate social responsibility (CSR) has led to a greater emphasis on financial sustainability as part of a company’s broader CSR strategy.
Several factors contribute to financial sustainability, including effective financial management, environmental and social responsibility, and corporate governance.
Small and medium-sized enterprises (SMEs) are businesses that are characterized by their size, revenue and number of employees. The definitions of SMEs vary across countries and regions, but generally, SMEs are considered to be businesses that have fewer than 250 employees and annual revenues of less than a certain threshold. In the United States, for example, small businesses are defined as those with fewer than 500 employees, while in the European Union, SMEs are defined as businesses with fewer than 250 employees and annual revenues of less than €50 million.
SMEs are often classified into two categories: small enterprises and medium-sized enterprises. Small enterprises typically have fewer than 50 employees and annual revenues of less than a certain threshold, while medium-sized enterprises have between 50 and 249 employees and annual revenues of less than a certain threshold.
SMEs play a vital role in the global economy, accounting for a significant portion of employment and economic growth. They are often the drivers of innovation and job creation, particularly in emerging markets. However, SMEs also face significant challenges, such as limited access to financing, regulatory hurdles, and competition from larger businesses.
Despite these challenges, SMEs have several advantages over larger businesses, including greater flexibility, agility and responsiveness to changing market conditions. They also often have closer relationships with their customers and can provide more personalized service.
Overall, SMEs are a critical component of the global economy, and their contributions to innovation, job creation, and economic growth cannot be overstated.
The current paper focuses on the medical sector because companies in the medical sector face significant financial challenges. These challenges are due to a variety of factors, including high research and development costs, regulatory hurdles, and the need to demonstrate the safety and efficacy of their products or services.
Regulatory hurdles also pose a significant challenge for medical companies. Medical products and services are heavily regulated, and companies must comply with numerous regulatory requirements before they can bring their products or services to market. The process of obtaining regulatory approval can be lengthy, complex, and expensive, and failure to comply with regulatory requirements can result in significant fines or even the withdrawal of products from the market.
In addition to regulatory hurdles, medical companies also face challenges related to reimbursement. In many countries, medical products and services are reimbursed by insurance companies or government programs, and companies must demonstrate the cost-effectiveness of their products in order to obtain reimbursement. This can be a significant challenge for medical companies, as they must balance the need to develop innovative products with the need to demonstrate cost-effectiveness.
Overall, the financial challenges facing companies in the medical sector are significant and complex.
In this paper, we intend to evaluate the economic sustainability of the medical practice sector in Romania by analyzing its stability and performance. The novelty of this study lies in the relation between the financial performance of these companies and their survival capacity in long run. Our main objective is to calculate ratios for profitability, financing capacity, debt, efficiency, and so on, in order to assess if this business can be sustainable as they are currently or mergers and acquisitions will happen, sooner or later, voluntarily or not, in this sector.
In our study we analyzed financial data for all the medical practice businesses in Romania for the past five years. However, because of the Covid pandemic, we deliberately left aside the last years that would have introduced major distortions in our analysis. In any case, it is our intention, in the near future, to study also the effects of the pandemic on the medical practice sector and the specific problems that occurred.
2. Literature Review
By reviewing the relevant literature, researchers can identify gaps, inconsistencies, and debates in the field, which can inform their research questions and hypotheses.
The aim of this literature review is to critically examine and synthesize the existing research on the topic. In our analysis we have noticed that most of the articles are focusing on general performance of the SMEs [1] [2], [3], [4], [5], [6], and the articles that are focusing on the healthcare or medical sector are not focusing so much on the financial performance of individual companies Thomson et al., 2009) , [7], [8], [9], [10], [11] . In our research we have seen that there also is no reference to the Romanian market and the performance of companies in the medical sector. As such, we believe that such research has relevance and is of interest.
When talking about the financial performance most of the authors are measuring the performance ratios: Return on Assets, Return on Equity and Net Profit Margin [3], [12], [13], [9]. Few articles are focusing also the turnover [2], [7], fixed assets Rostek, 2012) and even fewer on qualitative measures such as internationalization[5]
In their research paper [3] conclude that the financial leverage is important to boost the Return on Equity for companies. However their results are limited to the Spanish market and to the fact that number of observations was reduced. Rostek [10] developed a reference model for the competitiveness factor of SME dental clinics in Poland through extensive literature research and original investigations. The competitive factors included in the model were chosen through research conducted on both the SME sector and the dental services industry. The model is structured to include sets of measurable result areas, competitiveness factors, and their corresponding measures. The dominant role in the model is represented by the sales followed by personnel productivity, technological level, relationship with the customers and costs and expenses.
The study conducted by Elsaman [4] has focused on the SMEs concerned with medical devices. Their analysis focused on the changing landscape due to the new medical device reporting (MDR) regulation and its impact on the performance of SME in Germany. The study was conducted on 467 companies and revealed lower financial performance and growth due to the implementation of the new regulation. Some authors also studied the financial performance of companies in Romania, but did not look at the healthcare / medical sector [14], [15], [16]
3. Materials and Method
The data for the article was collected from the official database of the Ministry of Finance and represents the official filings of the companies. The data that was collected was based on 23.931 companies that have filled their financial reports to the authorities. The filings are based on the financial performance from 2021 as the results for the financial year 2022 have not yet been published. In our analysis we also compared the financial results of the companies in the county of Cluj with the results at national level. We wanted to see if the results from Cluj, a well-known medical center in Romania are better and if the companies from Cluj can somehow become a model for the others.
Table 1.
Financial performance of companies in Romania in the medical sector.
| 2017 | 2018 | 2019 | 2020 | 2021 | |
|---|---|---|---|---|---|
| Total companies | 18.175 | 20.339 | 22570 | 23.931 | 23.931 |
| Total employees | 69.364 | 76.068 | 80.346 | 81.069 | 89.176 |
| Total Net Income | 1.645.299.071 | 2.143.955.114 | 2.689.944.516 | 3.048.314.797 | 3.444.595.721 |
| Total Net Loss | 312.950.992 | 343.778.228 | 386.364.910 | 378.321.266 | 427.503.031 |
| Total Revenue | 10.022.955.949 | 12.013.276.844 | 14.255.306.232 | 15.743.156.460 | 17.789.766.800 |
| Total Assets | 9.224.201.550 | 11.143.662.947 | 13.367.009.901 | 15.189.783.106 | 17.164.454.910 |
| Total Inventory | 339.907.931 | 413.934.169 | 518.846.093 | 660.159.887 | 745.980.672 |
| Total Cash | 1.641.259.446 | 2.150.729.780 | 2.557.437.356 | 3.348.473.682 | 3.783.775.261 |
| Total AR | 1.627.289.691 | 2.226.053.277 | 2.504.072.845 | 3.045.476.902 | 3.441.388.899 |
| Total Equity | 3.073.493.764 | 4.014.630.907 | 5.076.026.615 | 5.982.832.432 | 6.760.600.648 |
| Total Debt | 5.791.724.793 | 6.529.897.637 | 7.537.757.344 | 8.434.477.389 | 9.530.959.450 |
| Total Sales | 10.264.510.635 | 12.331.226.817 | 14.725.593.380 | 16.301.078.556 | 18.420.218.768 |
| Total Expenses | 8.791.136.381 | 10.379.509.526 | 12.244.537.890 | 13.434.986.363 | 15.181.534.590 |
| Net Profit Margin (%) | 16% | 18% | 19% | 19% | 19% |
| ROA | 18% | 19% | 20% | 20% | 20% |
| ROE | 54% | 53% | 53% | 51% | 51% |
| Total Debt / Total Equity | 188% | 163% | 148% | 141% | 141% |
Source: author’s own calculation based on data obtained from the Ministry of Finance.
From the analysis we can notice that the financial performance for the companies that have an income is high and that the financial leverage ratio is also high with the equity being in average for the studied period between 33% - 40% which we could say that is at an optimal level. A closer qualitative look in the sector will reveal that most of the debt accumulated is generated by the owner as the minimum shareholder equity level is 200 lei in Romania so most of the owners are borrowing money to the company and not increasing the equity level. Another information which was revealed during our data collection process shows that around 34% of the companies in this sector have 0 employees. This fact is possible due to the legislation which allows the owner / administrator of a company to work without an employment contract. In fact, this provision has generated around 7200 shell companies that are used by doctors to substitute their employment in private practices in service contracts and by this lowering their expenses with Social Security Contributions.
After looking at the landscape of the medical sector in Romania we wanted to see if the same situation is present also in the county of Cluj.
Table 2.
Financial performance of companies in Cluj in the medical sector.
| 2017 | 2018 | 2019 | 2020 | 2021 | |
|---|---|---|---|---|---|
| Total companies | 942 | 1.107 | 1231 | 1326 | 1401 |
| Total employees | 2517 | 2.916 | 3.149 | 3.008 | 3399,04 |
| Total Net Income | 92.805.492 | 119.615.083 | 152.916.705 | 164.127.433 | 185463999,3 |
| Total Net Loss | 12.087.300 | 18.198.945 | 20.556.166 | 24.764.884 | 27984318,92 |
| Total Revenue | 395.231.185 | 494.499.672 | 611.330.478 | 643.522.351 | 727180256,6 |
| Total Assets | 334.470.718 | 469.695.212 | 583.513.194 | 676.090.601 | 763982379,1 |
| Total Inventory | 10.104.536 | 15.719.252 | 18.505.176 | 22.311.397 | 25211878,61 |
| Total Cash | 85.670.045 | 105.697.759 | 126.128.559 | 159.918.601 | 180708019,1 |
| Total AR | 76.301.700 | 107.982.413 | 120.609.091 | 136.968.215 | 154774083 |
| Total Equity | 128.130.135 | 177.446.115 | 222.278.726 | 284.218.116 | 321166471,1 |
| Total Debt | 170.877.788 | 223.979.169 | 266.481.760 | 307.019.558 | 346932100,5 |
| Total Sales | 410.931.343 | 521.232.010 | 651.812.779 | 707.196.763 | 799132342,2 |
| Total Expenses | 323.927.624 | 413.514.639 | 511.678.806 | 559.654.500 | 632409585 |
| Net Profit Margin (%) | 23% | 24% | 25% | 25% | 26% |
| ROA | 28% | 25% | 26% | 24% | 24% |
| ROE | 72% | 67% | 69% | 58% | 58% |
| Total Debt / Total Equity | 133% | 126% | 120% | 108% | 108% |
Source: author’s own calculation based on data obtained from the Ministry of Finance.
By comparing the results of the companies in Cluj county with the ones at National level we can notice that the profitability of the ones in the county of Cluj is higher and that financial leverage is lower. This result could be due to the fact that from the average number of employee per company there is a difference. The lower number of employees in the county of Cluj can be explained by the existence of a higher number of these shell companies which are only used by doctors to avoid the payment of higher taxes.
Further on we wanted to develop a model to see which are the most important factors that are impacting the net income of companies operating in the medical industry.
Table 3.
Variables for the model and source.
| Variable | Source |
|---|---|
| Average revenue | From information obtained from the Ministry of Finance |
| Average assets | From information obtained from the Ministry of Finance |
| Average inventory | From information obtained from the Ministry of Finance |
| Average equity | From information obtained from the Ministry of Finance |
| Average debt | From information obtained from the Ministry of Finance |
| Average salary | From information obtained from the National Institute of Statistics |
| Population | From information obtained from the National Institute of Statistics |
By extracting data from the Ministry of Finance we managed to take the financial information of companies that have disclosed these. The disclosure of information to the Ministry of Finance is mandatory and done by each company by may of the following year.
Table 4.
Data at national level.
| Year | Average Net Income | Average Revenue |
Average Assets |
Average Inventory |
Average Equity |
Average Debt |
Average Salary |
Population |
|---|---|---|---|---|---|---|---|---|
| 2014 | 49526,16 | 477774,91 | 478392,84 | 17985,72 | 100880,42 | 349072,58 | 1697 | 19953089 |
| 2015 | 60817,23 | 515552,86 | 514982,82 | 18402,72 | 139800,21 | 349672,53 | 1859 | 19875542 |
| 2016 | 77089,43 | 516320,98 | 508546,94 | 17836,85 | 144554,85 | 344085,07 | 2046 | 19760585 |
| 2017 | 90525,40 | 551469,38 | 507521,41 | 18701,95 | 169105,57 | 318664,36 | 2338 | 19643949 |
| 2018 | 105411,04 | 590652,29 | 547896,30 | 20351,75 | 197385,86 | 321053,03 | 2642 | 19533481 |
| 2019 | 119182,30 | 631604,18 | 592246,78 | 22988,31 | 224901,49 | 333972,41 | 2986 | 19425873 |
| 2020 | 127379,33 | 657856,19 | 634732,49 | 27585,97 | 250003,44 | 352449,85 | 3217 | 19328838 |
| 2021 | 198794,36 | 568935,30 | 463143,96 | 13356,96 | 243671,87 | 199213,12 | 3879 | 19201662 |
Source: author’s own calculation based on data obtained from the Ministry of Finance.
By selecting from the data of the Ministry of Finance just the companies that are registered in the region of Cluj we have created our second data source. An important issue is to be mentioned here – companies in Romania report their revenue where these have their operations, so we do not have the possibility to have altered information.
Table 5.
Data at Cluj level.
| Year | Average Net Income | Average Revenue |
Average Assets |
Average Inventory |
Average Equity |
Average Debt |
Average Salary |
Population |
|---|---|---|---|---|---|---|---|---|
| 2014 | 58551,46 | 380530,96 | 382180,95 | 10998,11 | 140778,07 | 201963,64 | 1857 | 699097 |
| 2015 | 69304,13 | 410349,32 | 393003,26 | 12555,01 | 151696,75 | 205738,93 | 2025 | 700982 |
| 2016 | 84766,11 | 400399,63 | 336799,72 | 11885,45 | 110519,88 | 200928,76 | 2340 | 701258 |
| 2017 | 98519,63 | 419566,01 | 355064,46 | 10726,68 | 136019,25 | 181398,93 | 2668 | 702780 |
| 2018 | 108053,37 | 446702,50 | 424295,58 | 14199,87 | 160294,59 | 202329,87 | 3026 | 704619 |
| 2019 | 124221,53 | 496612,90 | 474015,59 | 15032,64 | 180567,61 | 216475,84 | 3449 | 706952 |
| 2020 | 123776,34 | 485310,97 | 509872,25 | 16826,09 | 214342,47 | 231538,13 | 3744 | 709585 |
| 2021 | 205515,20 | 522543,77 | 422731,40 | 9472,43 | 256542,71 | 125395,61 | 4424 | 710284 |
Source: author’s own calculation based on data obtained from the Ministry of Finance.
4. Results
Starting from the results of our analysis we wanted to see if we can describe a model for the assumption that the variables are impacting the profitability of the companies: revenue, assets and inventory. We also considered that the financing of the company is playing an important role and this is why we took into account also the equity and debt as variables. The results of our model was:
| Regression Statistics | ||||||||||||||
| Multiple R | 0,996786298 | |||||||||||||
| R Square | 0,993582924 | |||||||||||||
| Adjusted R Square | 0,977540234 | |||||||||||||
| Standard Error | 7052,482486 | |||||||||||||
| Observations | 8 | |||||||||||||
| ANOVA | ||||||||||||||
| df | SS | MS | F | Significance F | ||||||||||
| Regression | 5 | 15402136398 | 3080427280 | 61,93368603 | 0,015965562 | |||||||||
| Residual | 2 | 99475018,43 | 49737509,22 | |||||||||||
| Total | 7 | 15501611417 | ||||||||||||
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |||||||
| Intercept | 263424,7791 | 94817,67167 | 2,778224507 | 0,108816747 | -144542,7347 | 671392,2929 | -144542,734 | 671392,2 | ||||||
| Revenue | -0,405181976 | 0,358651008 | -1,129738844 | 0,375854883 | -1,948332716 | 1,137968765 | -1,94833271 | 1,137968 | ||||||
| Assets | 0,283598951 | 0,820047917 | 0,34583217 | 0,762459074 | -3,244782459 | 3,811980361 | -3,24478245 | 3,811980 | ||||||
| Inventory | 1,666431523 | 3,477833028 | 0,479158001 | 0,679102741 | -13,29747625 | 16,6303393 | -13,2974762 | 16,63033 | ||||||
| Equity | 0,642012379 | 0,752663412 | 0,852987364 | 0,4835203 | -2,596436904 | 3,880461663 | -2,59643690 | 3,880461 | ||||||
| Debt | -0,724926717 | 0,762385892 | -0,95086586 | 0,442031039 | -4,005208457 | 2,555355023 | -4,00520845 | 2,555355 | ||||||
As we can notice no variable significantly influences the average net income (p>0.05), but the model is significant in relation to the set of factors (p=0.0159). as such we wanted to see if adding the net salary and the size of the population, we would get better results.
| Regression Statistics | |||||||||||||
| Multiple R | 1 | ||||||||||||
| R Square | 1 | ||||||||||||
| Adjusted R Square | 65535 | ||||||||||||
| Standard Error | 0 | ||||||||||||
| Observations | 8 | ||||||||||||
| ANOVA | |||||||||||||
| df | SS | MS | F | Significance F | |||||||||
| Regression | 7 | 15501611417 | 2214515917 | #NUM! | #NUM! | ||||||||
| Residual | 0 | 0 | 65535 | ||||||||||
| Total | 7 | 15501611417 | |||||||||||
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | ||||||
| Intercept | 1455319,02 | 0 | 65535 | #NUM! | 1455319,02 | 1455319,02 | 1455319,02 | 1455319,02 | |||||
| Revenues | -0,270957758 | 0 | 65535 | #NUM! | -0,270957758 | -0,270957758 | -0,270957758 | -0,2709578 | |||||
| Assets | 0,110491537 | 0 | 65535 | #NUM! | 0,110491537 | 0,110491537 | 0,110491537 | 0,11049154 | |||||
| Inventory | -1,831275157 | 0 | 65535 | #NUM! | -1,831275157 | -1,831275157 | -1,831275157 | -1,8312752 | |||||
| Equity | 0,172669253 | 0 | 65535 | #NUM! | 0,172669253 | 0,172669253 | 0,172669253 | 0,17266925 | |||||
| Debt | -0,046051696 | 0 | 65535 | #NUM! | -0,046051696 | -0,046051696 | -0,046051696 | -0,0460517 | |||||
| Net Salary | 38,6270987 | 0 | 65535 | #NUM! | 38,6270987 | 38,6270987 | 38,6270987 | 38,6270987 | |||||
| Population | -0,06831781 | 0 | 65535 | #NUM! | -0,06831781 | -0,06831781 | -0,06831781 | -0,0683178 | |||||
This model is the result of our analysis deployed based on all the results of the companies in Romania. The results are caused by the fact that average net salary and population are perfectly correlated according to the Spearman Rank Correlation. So the two variables are perfectly correlated from this point of view, which induces the phenomenon of multicollinearity. It affects the degree of significance of the model in relation to each variable but does not influence the estimates made based on the model. When looking at the model for the companies registered in the county of Cluj we get the following results:
| Regression Statistics | |||||||||||||||
| Multiple R | 1 | ||||||||||||||
| R Square | 1 | ||||||||||||||
| Adjusted R Square | 65535 | ||||||||||||||
| Standard Error | 0 | ||||||||||||||
| Observations | 8 | ||||||||||||||
| ANOVA | |||||||||||||||
| df | SS | MS | F | Significance F | |||||||||||
| Regression | 7 | 14583989329 | 2083427047 | #NUM! | #NUM! | ||||||||||
| Residual | 0 | 0 | 65535 | ||||||||||||
| Total | 7 | 14583989329 | |||||||||||||
| Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | ||||||||
| Intercept | 6330759,739 | 0 | 65535 | #NUM! | 6330759,739 | 6330759,739 | 6330759,73 | 6330759,74 | |||||||
| Average revenue | 0,377265739 | 0 | 65535 | #NUM! | 0,377265739 | 0,377265739 | 0,37726573 | 0,37726574 | |||||||
| Average assets | -0,491379733 | 0 | 65535 | #NUM! | -0,491379733 | -0,491379733 | -0,49137973 | -0,4913797 | |||||||
| Average inventory | 3,006834918 | 0 | 65535 | #NUM! | 3,006834918 | 3,006834918 | 3,00683491 | 3,00683492 | |||||||
| Average equity | 0,571857567 | 0 | 65535 | #NUM! | 0,571857567 | 0,571857567 | 0,57185756 | 0,57185757 | |||||||
| Average debt | 0,138180112 | 0 | 65535 | #NUM! | 0,138180112 | 0,138180112 | 0,13818011 | 0,13818011 | |||||||
| Net average Salary | 64,71647675 | 0 | 65535 | #NUM! | 64,71647675 | 64,71647675 | 64,7164767 | 64,7164768 | |||||||
| Population | -9,282880562 | 0 | 65535 | #NUM! | -9,282880562 | -9,282880562 | -9,2828805 | -9,2828806 | |||||||
We can see that the results are also caused by the fact that average net salary and population are perfectly correlated according to the Spearman Rank Correlation. So the two variables are perfectly correlated from this point of view, which induces the phenomenon of multicollinearity. It affects the degree of significance of the model in relation to each variable but does not influence the estimates made based on the model. When looking at the model for the companies registered in the county of Cluj we get the following results. But we can notice that the salary has a higher coefficient for the county of Cluj.
What we can also notice from our analysis is that if we look at the financial performance of companies in Cluj county compared to the results at national level the companies in Cluj have better ratios. Return on Equity (ROE) is a financial ratio that measures a company’s profitability and efficiency in generating earnings from the shareholders’ equity invested in the business. It’s important to note that a high ROE alone does not guarantee a successful or healthy company. It should be considered alongside other financial metrics, industry benchmarks, and qualitative factors. In our case we notice that the high return could be generated by the fact that the companies do not have a high equity value. This would be in line with the industry as the average medical business does not rely on too much investment in assets or does not need much funding. By assessing the 2 regions (Cluj vs. National level) we do not notice significant changes. Return on Assets (ROA) is a financial ratio that measures a company’s ability to generate profits or earnings from its total assets. It is an important financial metric for assessing a company’s efficiency in utilizing its assets to generate income. It’s essential to keep in mind that the ideal ROA can vary by industry and as we mentioned the medical industry does not require heavy investments in assets. As such the ROA for the analyzed companies are high.
Another issue that we wanted to investigate is if there is a difference in the financial leverage of the companies in the two groups. Financial leverage refers to the use of borrowed funds (debt) to finance investments or operations with the goal of increasing the potential return on equity (ROE) for shareholders. Financial leverage is measured using the debt-to-equity ratio. A difference between the two data sets could appear due to the environment in the market. If the ecosystem supports investments and makes it easier to raise capital then we could see differences between the two groups. We can notice that the national level has started with a higher financial leverage but has improved this by 2021. Surprisingly of not the year 2021 which was the toughest during the pandemic crisis for the economy was the best year for the medical industry due to the fact that most of the public hospitals were closed down and people had only access to private healthcare for nonemergency care. This fact can be seen also from the dynamic of the average net income which indicates a constant growth but a spike of more than 50% in 2021 compared to 2020.
5. Conclusions
In conclusion, our analysis of the profitability of companies has provided valuable insights into the factors that contribute to financial success. Our findings indicate that profitability is not solely determined by a company’s revenue, but rather by a combination of factors, including cost management which is impacting the assets and inventory, strategic decision-making in deciding the funding of the company – equity or debt, and market positioning which refers to the pricing strategy.
Our research also underscores the importance of adopting a long-term perspective when evaluating profitability. While short-term gains can provide a boost to a company’s bottom line, sustained profitability requires consistent performance over time. This may involve investing in equipment, improving operational efficiency, and developing strong partnerships and collaborations. Companies that are able to innovate and pivot quickly are more likely to remain profitable over the long-term. Our results show that there are no significant differences between companies from Cluj county and nation wide. The only difference is in the financial leverage where we see that companies in Cluj are using less debt than the national sample.
Ultimately, our study underscores the critical role of profitability in sustaining a company’s growth and success. By focusing on the factors that contribute to profitability, companies can develop strategies that will help them weather economic challenges and emerge as leaders in their respective markets.
Author Contributions
For research articles with several authors, a short paragraph specifying their individual contributions must be provided. The following statements should be used “Conceptualization, D.P. and F.D.; methodology, C.C.; software, D.P.; validation, D.XP, and C.C.; formal analysis, D.P.; investigation, D.P.; resources, D.P.; data curation, D.P.; writing—original draft preparation, D.P.; writing—review and editing, F.D.; visualization, C.C.; project administration, D.P.; funding acquisition, D.P. All authors have read and agreed to the published version of the manuscript.” Please turn to the CRediT taxonomy for the term explanation. Authorship must be limited to those who have contributed substantially to the work reported.
Funding
The publication of this article was supported by the 2020 Development Fund of the Babes, - Bolyai University/Publicarea acestui articol a fost finant, ată prin Fondul de Dezvoltare al Universităt, ii Babes, -Bolyai 2020
Conflicts of Interest
The authors declare no conflict of interest.
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