1. Introduction
Since the 1972 United Nations Conference on the Human Environment, when the sustainable development term was launched and up to the present day, this term has been enriched with new attributes such as environmental issues and bio/green innovation related to ecological factors [
1,
2]. Thus, sustainable development became, for many companies, a goal in itself, integrated into their strategic mission and vision and now universally referred to as corporate social responsibility.
Most corporate social responsibility studies focused on large companies because large companies offer researchers a vast domain of their research, including good case studies (Google, Johnson and Johnson, and Ford Motor Company), as well as major ethical issues (Barclay’s, Deutsche Bank, Inditex, and Nestle). Some companies offer both, such as the Volkswagen Group, which is involved in social responsibility practices but at the same time, was strongly affected by the Diesel gate scandal in 2015 [
3].
The sustainability for small and medium sized enterprises (SMEs) consists of achieving a balance on the one hand between financial, human and material resources, and on the other hand with the social and economic environment in which it operates. Lack of financial resources and lack of time are often mentioned as factors that prevent SME to develop a sustainable strategy and to consider the investment in sustainability as a competitive advantage.
For large companies, operating in a competitive and turbulent environment is an accepted element of doing business, likewise, for small and medium sized enterprises (SMEs), the business environment can be both a challenge but also a source of opportunity. The challenges for SMEs include access to fewer resources (human, financial, physical and informational) and it can also be extremely difficult for SMEs to implement sustainable-driven innovation practices [
4,
5]. However, SMEs that take on the challenge of sustainable innovation may carve out new business opportunities and competitive advantage for their businesses.
This being said, we consider our study on SMEs appropriate, because it offers us the opportunity to analyse the advantages, disadvantages as well as the barriers and drivers of promoting sustainable development, at the small business level. We will investigate the relationship between the expenses and profit of SMEs from a sustainable point of view and we will discuss the factors that facilitate their sustainability.
SMEs from the two industries (Section F—construction companies and Section G—Wholesale and retail trade, maintenance and repair of vehicles and motorcycles) present a series of characteristics that contribute to their involvement in socially responsible and sustainable practices in the region. Thus, construction companies are socially responsible because, through their operations, they contribute either to the pollution (Harron Homes, Carillion) or the protection of the environment (Catterpillar, Dewalt), ensure the social and economic wellbeing of their communities and actively contribute to building the necessary infrastructure for the sustainable operation of SMEs from other industries.
In the South West Region of Romania, SMEs are an important source of employment and thus, our research aims to establish if there are direct correlations between the corporate social responsibility (CSR), innovation and training budgets and certain performance indicators (profit, profit/employee and debt ratio).
We base our research on financial indicators because, regardless of its size, any organization has a main purpose of making a profit. Under fierce competition and explosive development of technology, SMEs must maximize any competitive advantage created by human resources and which consists of training, innovation, and CSR.
The theoretical framework will be oriented to practice related to CSR and we will use the financial indicators for evaluating the effect of these practices on SMEs’ sustainability.
The main research question is the following:
Which indicators of sustainable development—corporate social responsibility, innovation, and training occur in SMEs and how they impact the financial indicators?
To answer this question, we have employed quantitative research based on certain financial indicators, measured from 2010 to 2017.
Based on our results, we developed an integrated framework for the sustainable development of South-West Oltenia Region’ SMEs, where we understand how sustainable indicators can impact the SMEs’ financial results.
3. Research Methods
The study is based on an analysis of SMEs from the South-West Oltenia Region, one of the eight Romanian development divisions created in 1998 (North West, Centre, North East, South East, South Muntenia, West, Bucharest Ilfov).
3.1. Sample
In the South-West Oltenia Region of Romania, according to the data publicly available on the County Statistics Office of Dolj [
147], small and medium sized enterprises represent more than 99% of the total number of companies. Thus, from the 14,950 companies that were active in 2017, 14,901 were small and medium sized enterprises according to the EU definition (less than 250 employees, less than €50 million turnover and less than €43 million total assets) and 49 were large companies. From these 14,901 SMEs, 13,290 were micro-enterprises (less than 10 employees, less than €2 million turnover and total assets), 1,407 were small enterprises (between 10 and 49 employees, between €2 and €10 million turnover and total assets), while only 204 were medium sized enterprises (between 50 and 249 employees, between €10 and €50 million turnover and between €10 and €43 million euro total assets).
Regarding the industry, 47.14% of the total number of SME’s were represented by two industries: Section F—Construction (1087 SMEs structured as following: 917 micro-enterprises, 152 small enterprises and 18 medium sized enterprises), Section G—Wholesale and retail trade, maintenance and repair of vehicles and motorcycles (5.938 SMEs structured as following: 5,420 micro-enterprises, 470 small enterprises and 48 medium sized enterprises).
In order to conduct our research, we analysed 200 SMEs from the South-West Region of Romania, which were selected based on the following criteria:
- (1)
It is from one of the main industries from the region, according to data from the Dolj Statistics County Office [
147],
- (2)
The company must have been operational for of whole period 2010 to 2017,
- (3)
The company must have allocated for each year from 2010 to 2017, a specific budget for CSR, innovation or training.
Our sample, taking into account the industry code had the following structure: Section F—construction companies—40 SMEs (20%), and Section G—Wholesale and retail trade, maintenance and repair of vehicles and motorcycles—160 SMEs (80%).
3.2. Variables
The variables used in our study are explained in
Table 1.
Based on the financial data, this study extracted seven performance indicators pertaining to the following two aspects: profit (Profiti and ProfitEi), expenditure (CSRBi, InnovBi, TrainingBi, DebtRi, and Expensesi).
Profit is the most important indicator because it reflects an SME’s performance over the period 2010 to 2017 and the fluctuation in profit on a year to year basis, we analyse the correlation between profit and three budgets (state what the budgets are) that, if they are efficiently/effectively used, they can turn into profit, in the near future.
4. Results and Discussions
The Descriptive Statistics of variables used in our research are explained in
Table 2.
The Mean number of employees was 22.74, with a minimum of 2 employees and maximum of 175 employees (see
Table 2) and the mean profit was 155,397.5 (RON) lower than the mean of budgets allocated for Corporate Social Responsibility (263,477.6 RON), Innovation (304,997.5 RON) and Training (260,007.6 RON).
From the study of the three budget variables, we can see that the largest budget was for innovation, followed by CSR and then training (the difference between CSR and training was minimal).
We tested the structural model and the multi-item interval scales were used to assess the use of this technique as a strategic practice of SMEs [
148].
We controlled for the size of SMEs (number of employees) and also for industry (constructions and wholesale and retail trade, maintenance and repair of vehicles and motorcycles) to rule our structural model.
Multiple regression analysis estimates that effect of the three covariates (corporate social responsibility budget—CSRBi, innovation budget—InnovBi, and training budget—TrainingBi) on the number of employees (NoEmpi) and on the financial indicators (profit—Profiti, profit by employee—ProfitEi, expenses—Expensesi, and debt ratio—DebtRi).
Our analysis continued with three Model Summaries for a set of three dependent variables: CSRBi (Model 1), InnovBi (Model 2), and TrainingBi (Model 3) in order to evaluate several combinations of control variables until a particular set led to the largest possible R2.
Furthermore, we applied the Durbin-Watson test in order to verify the existence of independent errors (Durbin and Watson, 1951). Thus, we calculated how Profit
i, DebtR
i, ProfitE
i, and Expenses
i i variables predicted the subsequent increase of the CSRB
i, (
Table 3), InnovB
i (
Table 4) and TrainingB
i (
Table 5) in SMEs.
The values of the multiple correlation coefficient (R) between the predictors and the dependent variable CSRBi registered a high value (0.986), which shows a strong influence of all predictors on the CSRBi of the SMEs.
The value of R2 measures how much of the variability in the dependent variable is accounted for by the predictors. In our model, its value is (0.972), which means that the predictors account for 97.2% of the variation of the SMEs’ CSRBi.
The adjusted R2 offers us details about the degree of the generality of our model and its value is very close to the value of R2 (the difference between the values is 0.001) indicating that the cross-validity of our models is very good.
From the analysis of
Table 4, we can see that the values of the multiple correlation coefficient (R) between the predictors and the dependent variable InnovB
i registers a high value (.987), which shows a strong influence of all predictors on the InnovB
i of the SMEs.
For our model, the value of the R2 is (0.975), which means that the predictors account for 97.5% of the variation of the SMEs InnovBi. Moreover, the value is the same for both R2 and adjusted R2 indicating that the cross-validity of our models is very good.
An analysis of
Table 5 proves that the values of the multiple correlation coefficient (R) between the predictors and the dependent variable TrainingB
i registers a high value (0.988), which shows a strong influence of all predictors on the TrainingB
i of the SMEs.
The value of the R2 is (0.976), which means that the predictors account for 97.6% of the variation of the SMEs TrainingBi. The value is the same for both R2 and adjusted R2 indicating that the cross-validity of our models is very good.
The statistical analysis unveils that TrainingB
i is the variable with the highest level of influence (0.988
a) on the other indicators, followed by InnovBi, (0.987
a) and CSRB
i (0.986
a). The three variables influence the dependent variable to a similar extend, which comes to confirm other research findings showing that the sustainability of SMEs is highly dependent on their financial performance [
42,
149].
The significance R
2 was tested using F-ratio which is significant with a probability of less than 0.001 [
150]. For our models, this change was significant for Model 1, Model 2 and Model 3 (0.000).
We observe that the value of the Durbin-Watson test is between 1.876 (Model 1) and 2.077 (Model 3) which demonstrates a serial correlation between errors because a value less than 1 or a value greater than 3 is problematic for the model validity.
The Durbin-Watson test value stays within the 1.5–2.5 reference interval [
150,
151]. Thus, the hypothesis regarding the lack of autocorrelation between the residuals of the multiple regression model is validated.
The regression results of our models suggest that F values are significant at the 0.000 level, indicating the regression analysis is meaningful (F for CSRBi, = 1691.2, F for InnovBi = 1911.2, and F for TrainingBi = 1986.6). The following variables: ProfitEi, Profiti, Expensesi are found to be positively associated with SMEs’ sustainable factors (CSRBi, InnovBi, and TrainingBi) and the variable DebtRi is found to be negatively associated with SMEs sustainable factors. SMEs have limited and often lack financial resources and as a consequence the resources allocated for sustainable activities are not provided in their annual budgets.
Pearson’s correlation coefficient can take values between 0 (no effect) and 1 (perfect effect) [
152]. It is also important to discuss if the coefficient is positive or negative because it indicates the direction of the relationship between the variables (
Table 6).
Correlated with CSRB
i (0.982 **) and with TrainingB
i (0.987 **), InnovB
i has the potential to successful position SMEs in niche markets. Hoffrén and Apalajahti [
153] consider that innovation, especially radical innovation has a positive impact on the SMEs’ sustainability because it highlights the owner-manager’s entrepreneurial behaviour.
Compared to the other indicators, the analysis demonstrates a statistically significant causal effect on most performance indicators, except for DebtRi which demonstrates that an increase in expenses limits the DebtRi of SMEs.
The analysis of the findings suggests that all the independent factors (the predictors) contributed in a significant way to explaining the dependent variable (the level of statistical significance is lower that 0.05 or 5% for all factors). Moreover, we observed that between the value of the Profiti and the CSRBi, there is a direct influence relationship.
Our findings prove that CSRBi is significantly and positively correlated with the following indicators: Expenses
i, Profit
i, and ProfitE
i, and it is negatively correlated with DebtR
i. The fact that the stronger correlation is between CSRB
i and Expenses
i (0.985) and the stronger negative one is between CSRB
i and DebtR
i (−0.113), indicates that the CSRB
i is an indicator that contributes to the limitation of DebtR
i of SMEs. Analysing the relationship between CSRB
i and the other indicators leads us to the conclusion that CSRB
i contributed significantly and in a positive way to the increase in profit and a decrease in expenses [
154].
During the years the SMEs kept allocating a budget for sustainable activities and it is proved by the positive correlation between CSRB
i and ProfitE
i (0.196) and by the results of the research of Deng and Long [
155] that consider the value of financial performance as a boundary.
SMEs can use training and innovation to improve the impact of CSR on their sustainability with a focus on positive financial indicators (i.e. a slow but steady growth of profit according to the degree of awareness and implementation of sustainability strategies and policies). The external environment and the public community might pressure SME owners to engage in CSR activities, in order to encourage the connection between the triple-bottom-line and the financial results. This is underlined by the results of the Irish Small and Medium Enterprises study [
156], which states that SMEs provide 69% of all employment in Ireland and are successful due to constant training, development, and investment in innovation.
A summary of the findings which demonstrates that our all hypotheses are supported is depicted in
Figure 2.
The results emphasize the interactions among the different financial elements of the SME’s sustainable investments and the regional context [
157] and also prove that SMEs perceive CSRB
i, TrainingB
i, and InnovB
i as important factors for their competitive advantage as proved Shen and Benson [
158] by their research. Moreover, it is already well established that a significant relationship exists between InnovB
i and CSR outcomes and between innovation and SMEs obligations to their stakeholders [
159].
5. Conclusions, Limitations and Future Research
Our research offers new insights into the SME management literature because it can be used to understand the relevance of financial sustainable factors mechanism in different types of SMEs and the way in which SMEs can use these financial instruments in order to achieve a strategic competitive advantage.
The importance of our study consists of an analysis of the impact of the budget related to three sustainable factors (CSR, innovation, and training) on financial results of SMEs from two important industries from the South West region of Romania. Research on SMEs has traditionally focused on human resources strategies and our research is oriented to the sustainable elements of SMEs—entities which are in continuous transformation and which are characterized by a high degree of instability (each year, many SMEs come and go from the local, national and European business environment). Moreover, the originality of the article consists of the analysis of the triple-bottom-relationships between CSR-Innovation-Training as predictors of SME sustainability based on financial results. This is important because not many sustainability studies conducted at the level of SMEs were based on complex financial factors analysis, more of them where based on a deductive or inductive analysis of the content or from a theoretical point of view [
160,
161,
162].
CSR, training, and innovation is being implemented more and more by Romanian SME owners because they are starting to understand their potential. As a result, the role of all three factors as predictors of SMEs’ sustainability will be increased by a new perspective that underlines the importance of their mechanisms on financial performance of SMEs. In the last years, the owners-managers of Romanian SMEs started to become aware of these advantages and invest in sustainable practices, due to the impact of these activities upon the company’s financial performance.
Another practical contribution of this paper consists is the study of the financial indicators for a long period of time (eight years, from 2010 to 2017) which contributes to the reliability of the study. Our research is relevant for SMEs from the two chosen industries, the same industries used in the ISME study [
156].
The main limitation of our research consists, first of all, in the fact that we only used SMEs from two industries in our sample (F = Construction, G = Wholesale and retail, repair of motor vehicles and motorcycles) and one region of Romania (South West Oltenia Region). Another limitation is the use of financial results to measure CSR and innovation.
As for the future of our research, we aim to do the following:
- (1)
We want to expand our research to include SMEs from the same industries (construction industry and wholesale and trade industry) from all the development regions of Romania (North West, Centre, North East, South East, South Muntenia, West, Bucharest Ilfov).
- (2)
We want to study SMEs from other important industries (C = Manufacturing, I = Hotels and restaurants, K = Financial and insurance intermediation), taking into account the research of Hull and Rothenberg [
163] who arrived at the conclusion that SMEs operating in different activity sectors may have different benefits in the pursuit of sustainable factors.
- (3)
Our research will further address the qualitative study of the impact of CSR on the sustainability of SMEs.