Review Article - (2022) Volume 11, Issue 7
Received: 17-May-2022, Manuscript No. JBFA-22-63994;
Editor assigned: 20-May-2022, Pre QC No. JBFA-22-63994(PQ);
Reviewed: 06-Jun-2022, QC No. JBFA-22-63994;
Revised: 18-Jul-2022, Manuscript No. JBFA-22-63994(R);
Published:
26-Jul-2022
, DOI: DOI: 10.37421/2167-0234.2022.11.420
Citation: Najoua, Mabrouk. "The Effect of the
Interaction between Technological Performance and the Variables of the
Governance Structure Specific to Small and Medium-Sized Enterprises
on their Financial Performance (Case of the Tunisian LLCs)." J Bus
Fin Aff 11 (2022): 420.
Copyright: © 2022 Najoua M. This is an open-access article distributed under the terms of the creative commons attribution license which permits unrestricted
use, distribution and reproduction in any medium, provided the original author and source are credited.
The present work proposes to analyze the effect of the interaction between technological performance and the variables of governance structure specific to the SME-LLC on their financial performance.
The majority of studies dealing with Small and Medium-Sized Enterprises (SME-LLCs) have mainly focused on the governance structure of this type of organization and its relationship with financial performance in this particular context while neglecting any other external factors. Based on the necessary theoretical framework, this research attempts to fill the gap in thinking on this topic by studying the impact of the specific governance structure of SME-LLCs on financial performance when moderated by the effect of technological performance.
The statistical results showed us the existence of a moderating effect of technological performance. This moderating factor seems to be able to improve and deteriorate the financial performance of the LLC.
Corporate governance • Corporate social responsibility • Technological performance • Financial performance
The search for a theory of governance that applies and adapts to the reality of the SME requires a synthesis between contractual and cognitive theories. Indeed, in an SME one cannot speak of an agency relationship between the shareholder and the manager, since the main shareholder and the manager are the same. Hence the partnership approach seems more relevant for the SME.
The efforts made by a limited liability company to innovate can be understood as an investment that will eventually lead to its success. Nevertheless, all innovation involves risk taking and innovation does not mean success of the innovation (commercial success, efficiency gains, etc.) this raises questions about the link to performance. In the abundant literature, the link between innovation and performance is not easily demonstrated.
Conceptually, innovation is linked to performance through the Resource Based View theory (RBV). This theory states that the company is a combination of resources and capabilities. These resources, as soon as they are rare or correctly combined, become sources of competitive advantages [1,2]. This approach by the resources to explain the benefits of innovation is applicable to the SME, even if these last ones have specificities.
In this paper we will study the impact of the specific governance structure of SME-LLC on financial performance when moderated by the effect of technological performance.
What is the influence of the governance mechanisms specific to the SME-LLC on their financial performance when moderated by the effect of technological performance?
The answer to this research question will provide an interesting contribution to the existing literature and to practitioners. From a theoretical point of view, our research allows us to combine the influence of complementary theories, often mobilized separately, to understand the concept of governance in LLCs. Thus, the rest of this paper contains a review of the literature and the hypotheses, an empirical part and analysis of the results with econometric tests and ends with a conclusion.
SMEs cannot only be considered as a smaller version of large companies (especially when they are small family businesses): their mode of governance differs in many respects from large firms. This is particularly true of the control mechanisms in place. There may therefore be differences between the results obtained for large firms and those obtained for "SME-LLCs". Several favorable and unfavorable arguments concerning the capacity to innovate of "SME-LLCs" can be put forward: certain characteristics, such as the capacity to respond to changes in the environment, result in a high level of organizational flexibility and innovation. Proximity, or even dependence, on customers or external partners can also favor the deployment of innovations. Conversely, the lack of internal skills within "SME-LLCs" can be a hindrance to innovation or to its success on the market.
Among the recent works, some research shows a positive link between innovation and performance. This is the case of Hult, et al. who positively link innovation in 181 US industrial firms to different forms of performance (profitability, growth, market share, overall performance). Focusing on process innovation (the ability to implement innovative methods and processes), Das and Joshi show that innovation is positively related to the performance of firms (selfassessment of perceived performance, in relation to the performance of the respondent's competitors) following a declarative survey of 108 US firms in the technology services sector. Finally, it is also the case of Subramanian A. and Nilakanta S who finds that technological and administrative innovation is directly related to performance, this relationship being moderated, however, by the stability of the environment.
The positive effect of the capacity to innovate of enterprises on their performance is not always demonstrated. Dibrell, et al., based on a survey of 311 Chadian SMEs, underline the absence of a direct relationship between innovations (products and processes) and performance (measured by the profitability rate and the growth rate). In the same way, Jansen, et al. obtain on 238 firms (or divisions) an absence of direct effect of the innovations of exploration or exploitation on the financial performances of the units; however their study shows the moderating role of the dynamism and the competitiveness of the environment which generate significant crossed effects on the performance. The economic environment of companies thus appears to be a non-negligible context variable in the analysis of the link between innovation and performance.
Indeed, as Charreaux G and Desbrières P point out, insofar as the notion of created value is not reduced to the sole transaction between the firm and the shareholders, the analysis of the value creation process is not limited to the sole relationship with the shareholders and to the study of the influence of the control exercised by the latter on the managers. Our authors want to emphasize the importance of stakeholders in the value creation process and, therefore, in the sharing of the value created. In other words, the relationship between Corporate Social Responsibility (CSR) and wealth creation must now go beyond the financial aspect to become part of creation logic value .
This is what Steurer R emphasizes when they argue that in a globalized economy characterized by increasingly competitive capital markets, the objective of value creation is an unavoidable and legitimate goal that company managers must achieve over the long term. In this respect, the pluralist (partnership) approach to value offers interesting perspectives since it obliges company management to take into account not only the interests of shareholders, but also those of other stakeholders who actively participate in the wealth creation process.
The ultimate objective is therefore no longer to create value at all costs for the holders of property rights (the stockholders), but rather to integrate a managerial culture oriented towards the satisfaction of all stakeholders. However, although everyone agrees on the interest of a pluralist vision of the company, the practical implementation of such an acceptance comes up against cultural biases that considerably reduce its operational validity [3]. This thought by Reynaud E. underlines the undeniable impact of the context on managerial practices. Based on the existing literature, we will state a series of hypotheses on the effect of the interaction between technological performance and the variables of the governance structure specific to the SME-LLC on their financial performance.
Empirical research attempting to identify the link between CSR and financial performance has been rooted in the Anglo-Saxon literature for some thirty years [4,5]. However, it should be noted that there is no consensus in the empirical literature on the nature of the direction of the causal link. An examination of the results of existing studies shows, on the one hand, the influence of CSR on financial performance and, on the other hand, the feeling that the link is fragile or even non-existent and somewhat contrasted [6,7].
However, we find that these positive or negative linkages enrich or impoverish only the owners of capital without taking into account the other business and social partners of the company. Corporate performance is only one aspect of value creation. It is the shareholder conception of value that is demotivating for all stakeholders. The analysis of the impact of the link between CSR and value creation is part of a perspective of broadening the system of corporate governance from shareholders alone to all stakeholders [8].
However, whatever the context, Charreaux G stresses that any firm whose objective is to create value in the long term must have know-how and a competitive advantage that is difficult to imitate by its competitors. This is the reason why we suppose that corporate social responsibility could constitute a strong and favourable lever for value creation.
It should be recalled that several authors have been quick to identify the effect that sustainable and partnership based responsible governance can have on technological performance. At this level, we can cite the most cited works on the subject, notably those of Grayson and Hodges, Rennings et al., Little, Kramer, et al., Mendibil, and Jenkins. In turn, the technological performance of high growth opportunity firms has been found to have a positive and significant effect on measured financial performance. This relationship has been affirmed by the work of hausman, Hult, et al. Das and Joshi, Subramanian, Dibrell, et al. and Huang and Liu. Due to the fact that the relationship between these three concepts is difficult to analyze, it is sought to study the effect of the interaction between CSR and technological performance on the financial performance of LLC. In our case, CSR concerns two types of stakeholders which are customers and employees (named CSR1 and CSR2) [9].
Hypothesis 1: The interaction between CSR1 (responsibility to customers) and technological performance has a positive effect on the financial performance of the LLC.
The second sub-hypothesis will be as follows:
Hypothesis 2: The interaction between CSR2 (responsibility towards employees) and technological performance has a positive effect on the financial performance of the LLC.
Concentration of ownership, particularly when held by the managers of SME-LLCs, appears to be an effective governance mechanism for resolving the various problems between partners. Several studies seem to confirm the effectiveness of this governance mechanism in terms of value creation.
Several authors have asserted the existence of a link between ownership concentration and technological performance. Similarly, the technological performance of high growth opportunity firms has been found to have a positive and significant effect on financial performance measured by Tobin's Q, ROA, ROE or EBS (equity by share). This relationship has been affirmed by the work of Hausman, Hult, et al., Das and Joshi, Subramanian, Dibrell, et al. and Huang and Liu [10].
Thus, the relationship between ownership concentration, technological performance and technological performance turns out to be a bit complicated. For this purpose, we seek to examine the effect of the interaction between ownership concentration and technological performance on the financial performance of the LLC.
Hypothesis 3: The interaction between ownership concentration and technological performance has a positive effect on the financial performance of the LLC.
The presence of the auditor influences technological performance. This means allows the regulation of information asymmetries and the resolution of agency conflicts. Indeed, the presence of the CAC in the LLC is a guarantor of the quality of the financial information disclosed by the company to its recipients. This can encourage the manager to act in the interest of the associates while adopting investments in innovation and thus improving technological performance.
The latter also influences financial performance, an idea asserted by hausman and hult, et al. Das and Joshi, Subramanian, Dibrell, et al. and Huang and Liu. So to understand and test the relationship between these three concepts, which is a bit complicated, it is sought to examine the effect of the interaction between the auditor and technological performance on the financial performance of the LLC.
Hypothesis 4: The interaction between the auditor and technological performance has a positive effect on the financial performance of the LLC.
Model presentation
Taking into account the effect of the interaction of governance variables with technological performance on the financial performance of the LLC refers us to the existence of a moderating effect.
According to Baron and Kenny and James and Brett, a moderator variable is a variable that modulates the direction and/or strength of the effect of X on Y. Detecting the presence of a moderator effect can be crucial since, on the one hand, a non-significant total relationship between X and Y can be systematically significant in the different subgroups of this relationship and, on the other hand, not identifying the presence of a moderator can lead to the erroneous conclusion of the absence of influence of the X variable on the Y variable.
Different statistical techniques can be used to test the effect of the interaction: multiple regressions, multiple regressions with dummy variables, multiple subgroup regression and ANOVA. The choice of which type of statistical analysis to use will depend on how the variables were measured.
However, a distinction must be made between pure moderators and quasi-moderators. The pure moderator is a variable that interacts with the independent variable (s) but is only negligibly associated with the dependent variable. Thus, there is no "simple" effect of the moderator on Y. However, this last condition is not required for quasimoderators.
The regression equation identifying the existence of a moderating effect is as follows:
Y= β0+β1*X+β2*Z+β3*XZ
As marked by Baron and Kenny, three relationships can be drawn from this equation. A first relationship to be evaluated by the factor (β1) and reflected in the influence of X on Y. The second relationship to be evaluated by the factor (β2) and summarizes the impact of Z on Y while the third relationship and the one of most interest to us is evaluated by the factor (β3) and reflects the moderating effect of Z. The latter is detected when the relationship (β3) is significant (Figure 1).
Figure 1. X-Y relationship: moderating effect of Z.
This effect can be summarized as follows:
If Z is a moderator of the X-Y relationship, it is also correct to say that X is a moderator of the Z-Y relationship. It is only the conceptual framework and justifications of the theoretical model that determine which of X or Z is the moderator variable; statistically it is hardly possible to make this distinction (X and Z are both independent variables, they are at the same level) (James and Brett, Sharma, Durand and Gur-Arie). In our case the variable Y is the financial performance, X represents the specific governance structure of the LLC while the variable Z indicates the technological performance
The model equation is as follows:
We would like to point out that three control variables (size, sector and plurality) have been introduced in this model given their effects on the innovation decision [11].
Definition of the variables
The Table 1 below summarizes the variables used in this study and their respective measures.
| Variable | Coding | Measures |
|---|---|---|
| Dependent variable | ||
| Financial performance | Perfin | measured by proxy ROA |
| Independent variables | ||
| Technological performance | Perftech | A composite index calculated on the basis of a combination of several items reflecting the level of innovation companies |
| Corporate Social Responsibility | CSR1 CSR2 | Constructed of 9 items |
| Concentration of ownership | CP | binary variable that takes 1 if the main shareholder holds more than 50%, 0 in the opposite case |
| External Auditor | CAC | Binary variable that takes 1 if the LLC uses an auditor, 0 in the opposite case. |
| Control variables | ||
| Business sector | SECT | Binary variable that takes 1 if the company belongs to a technological sector, 0 in the opposite case. |
| Plurality of leaders (co-management) | Plura | Binary variable that takes 1 if the company has more than one manager, 0 in the opposite case. |
| Size | Size | Metric variable measured by number of employees |
Sample and study data
Our attention was focused in this research on the effect of the interaction between technological performance and the variables of the governance structure specific to the SME-LLC on their financial performance. To achieve this, the choice of the population was guided by an essential criterion, namely the legal criterion. It follows that the first criterion of our choice of population is the limited liability company. Our sample contained a total of 192 companies.
MethodologyThe study of the effect of the interaction between technological performance and the variables of the governance structure specific to SME-LLCs on their financial performance is tested using the ordinary least squares multiple linear regression method. The regression is performed using SPSS software.
Results of the exploratory factor analysis
Before assessing the goodness of fit of the model to the data, it should be recalled that the EFA is used at this level to account for the unidimensionality of the measurement scales for each variable, i.e. to reduce the set of observed variables into a smaller number of factors or principal components.
The method used for AFE is Principal Component Analysis (PCA). Any determination of the factor structure is subject to rotation of the axes to ensure better assignment of the items in each factor. Assuming that the dimensions of this research are independent, we opted for the orthogonal rotation, also called VARIMAX; "it is a method that minimizes the number of variables with a strong correlation on each variable and facilitates the interpretation of the factors".
We will apply all of the above tests on the data of our study. In a first step, we start with statistical analyses to evaluate the unidimensionality of the measurement scales, their reliability and validity.
The variables in this study are both quantitative and qualitative. Therefore, only the qualitative variables will be examined.
Study of the unidimensionality of the measurement scales and reliability: The unidimensionality of the measurement scales is verified using PCA, which is a very useful means of purifying the measurement of each variable to be retained. We retained the items with a factorial contribution higher than 0.4 and the factors with an eigen value higher than 1. The results of the statistical analyses performed with PCA to structure the variables of the research model and the reliability tests are presented in the following.
The corporate social responsibility variable: The CSR variable is a construct composed of 9 items. The results indicate that the value of the KMO is equal to 0.732, it is thus acceptable since it is higher than 0.5. The quality of representation of the items is also satisfactory with communities higher than 0.4. It follows from these values that the conditions of application of the PCA are verified (Table 3).
In addition to these conditions, the application of PCA is carried out according to a Varimax rotation, which is an orthogonal rotation method that minimizes the number of variables with high correlations on each factor and facilitates the interpretation of the factors [12-16]. In other words, it ensures a better assignment of the items of each factor. To achieve this, it is necessary to remove all contributions below a given level. In general, this level is set at 40%, so we retained only those items whose factorial contribution is greater than 0.4. The unidimensionality is quite strong since the number of factors needed to recover 54.392% of the information is quite low, namely two factors. We notice that the first factor is the most important factor since it recovers up to 37.668% of the explained variance [17,18].
In this work we retained the first two factors with a percentage of explained variance of 37.483% for the first and 16.910% of the total variance of the original data.
Examination of the factorial contributions shows that the items; CSR2 to CSR6 belong to the first factor that can be called responsibility towards customers (CSR1). These contributions are greater than 0.753 which confirms the unidimensional factorial structure (Table 2).
| Items | Quality of representation | Factor contribution |
|---|---|---|
| CSR1 | 589 | 753 |
| CSR2 | 462 | 678 |
| Total variance explained | 54.39% | |
| Eigen value | 4.895 | |
| KMO | 0.732 |
However, the second factor, which can be called responsibility towards employees (CSR2), consists of the following three items: CSR7 to CSR9. These contributions are greater than 0.678, which confirms the unidimensional factor structure (Table 2).
Verification of the conditions for using the regression and preliminary analyses
The first condition for using the regression is the nature of the variables. The dependent variable analyzed is calculated by the ROA proxy (financial performance). The explanatory variables are of a metric and binary nature. Therefore, this condition, concerning the nature of the variables, is well verified. The verification of the conditions of application of the multiple linear regression is carried out by the software SPSS (version 20) under windows.
Checking the conditions for using multiple linear regression
The following conditions must be verified. The absence of multicollinearity between the explanatory variables: To ensure the existence or absence of this problem, we refer to the Pearson coefficient, the Variance Inflation Factor (VIF), the conditioning index and the tolerance values.
Based on the correlation matrix (Table 3 and 4), the Pearson coefficients are always less than 0.8, which leads us to conclude that the problem of bivariate multicollinearity is perfectly absent.
| variables | SECT | CAC | CP | Plura | Size | perftech | CSR1 | CSR2 |
|---|---|---|---|---|---|---|---|---|
| SECT | 1 | |||||||
| CAC | -0.026 | 1 | ||||||
| CP | 0.029 | -0.121 | 1 | |||||
| Plura | 0.101 | 0.09 | 0.014 | 1 | ||||
| Size | 0.069 | 0.015 | 0.061 | -0.084 | 1 | |||
| perftech | -0.014 | -0.064 | -0.026 | -0.097 | 0.068 | 1 | ||
| CSR1 | -0.155 | -0.014 | -0.126 | -0.054 | 0.036 | 0.002 | 1 | |
| CSR2 | 0.044 | -0.003 | 0.05 | -0.035 | 0.014 | 0.107 | 0.001 | 1 |
| Tests/var iables | SEC T | Size | CAC | CP | perfte ch | Plur a | CSR1 | CSR2 | CAC per ftech | CPper ftech |
|---|---|---|---|---|---|---|---|---|---|---|
| Tolerance | 0.927 | 0.952 | 0.102 | 0.122 | 0.954 | 0.858 | 0.149 | 0.135 | 0.093 | 0.11 |
| Tests/variables | RSE1 perftech | RSE2 perftech | ||||||||
| Tolerance | 0.147 | 0.137 | ||||||||
From the various indicators of multicollinearity, we can conclude that the multicollinearity problem is absent. The absence of autocorrelation of residues: To ensure that there is not an autocorrelation problem between the residuals, we refer to the Durbin-Watson test. The optimal value for this test would be about two. The value obtained for the sample is 1.266 (Table 5). Therefore, the independence of the residuals can be expected and therefore the postulate of independence of the residuals is met. This proves that there is no autocorrelation problem between the residuals.
| Test/Regression | Financial performance (perfin) |
|---|---|
| Durbin-Watson test | D-W= 1 .266 |
Indicators for interpreting the results: Three indicators are used to interpret the results of this study:
• The R-two (coefficient of determination) which is interpreted as the percentage of the variance of the variable to be explained returned by the model
• The F-statistic which allows to assess the significance of the relationship at the global level
• Student's t-statistic which evaluates the significance of each regression coefficient on each variable.
The assessment of the linear goodness of fit of the regression equation between the dependent variable and the independent variables is determined by the coefficient of determination Rtwo (R2=SCR/SCT with 0<R2<1). The proportion that remains unexplained 1-R2 is attributable either to the omission of explanatory variables that could contribute to the explanation of the level of innovation of firms or to experimental error.
However, adjusted R-two allows for the comparison of multiple regression equations with the same dependent variable but with equations that differ either in the number of observations n or in the number of explanatory variables. This criterion can be very useful in the search for the best model to explain the phenomenon under analysis.
The significance test of the regression as a whole induces the following hypotheses:
• (no significant contribution from explanatory variables)
• H1: at least one of the i is different from 0 (at least one variable makes a significant contribution).
Multivariate testing and overall model quality: The study of the multiple regression model relies on the significance of the regression as a whole as well as the parameters of the model to verify the contribution of each variable in explaining the variation of the dependent variable.
The results found show that the applied multiple linear regression model is globally significant in terms of the coefficient of determination and the F (Fisher-Snedecor) statistic.
This is a statistic (F) that measures the overall significance of the model. It compares the significance of the explanation provided by the model with the variations provided by the residuals. If the model is correct, the correlation coefficient is large, the influence of the residuals is negligible and therefore the F value will be large.
The empirical results show that 71.6% of the variation in financial performance is explained by the effect of the interaction of the variables related to the LLC specific governance structure and technological performance as well as the control variables.
The Fisher statistic (F) which is equal to (39.978), confirms the good quality of the model at a significance level less than 1% . In the same way, the explanatory power of the model appears satisfactory since the Fisher F statistic is significant at the 1% level. Thus, we reject H0 and state that the regression is significant as a whole.
Similarly, the adjusted R-two value is equal to 70.2% (Table 6). In other words, 70% of the variation in financial performance is explained by LLC specific governance variables and technological performance retained by this study. We can conclude that the model is statistically significant and explanatory of the studied phenomenon. A positive result of the Fisher test means that at least one of the coefficients is significantly different from zero [19,20].
| Explanatory variables | Coef. | T- Student | Sig |
|---|---|---|---|
| Constant | 0.025 | 13.572 | 0.000*** |
| Concentration of property ( CP) | -0.353 | -3.17 | 0.002** |
| Auditor (CAC) | -0.527 | -4.309 | 0.000*** |
| Sector of activity (SECT) | 0.062 | 1.521 | 0.130(n.s) |
| Company size (Size) | -0.04 | -0.992 | 0.323(n.s) |
| Plurality of leaders (Plura) | 0.037 | 0.877 | 0.382(n.s) |
| Corporate Social Responsibility (CSR-1) | 0.126 | 1.25 | 0.213(n.s) |
| Corporate Social Responsibility (CSR-2) | 0.068 | 0.646 | 0.519(n.s) |
| Technological performance (perftech) | -0.097 | -2.441 | 0.016* |
| CAC perftech | 1.07 | 8.379 *** | 0 |
| CP perftech | 0.641 | 5.471 | 0.000*** |
| RSE1 perftech | -0.133 | -1.304 | 0.194 (n.s) |
| RSE2 perftech | -0.078 | -0.736 | 0.463 (n.s) |
R2= 0.728 Adjusted R2=0.710 F=39.978 Sig. 0.000 R2=0.728 Adjusted R2=0.710 F=39.978 Sig. 0.000
***: significant at the 1 level%; **: significant at the 5% level %; level; *: significant at the 10; n.s : not significant.
Regarding the significance of the independent variables, we can say that all the variables are statistically significant except that of the variable (CSR). Regarding the control variables introduced in the model, the results show that the variables are statistically insignificant. Table 6 below presents the explanatory power of the model, the beta coefficients, the Student t's, the F-statistic and its significance, and a summary of the regression results for all explanatory variables in this second model.
The results indicate that only the first hypothesis is statistically insignificant. However, the other two assumptions are statistically significant. For the control variables of this model, they are statistically insignificant.
Analysis of the effect of the interaction between CSR1 and technological performance on the financial performance of the LLC (H1): The statistical results showed that this variable has a negative and insignificant effect on financial performance for CSR1 (t=1.250; p=0.213). In addition, the technological performance variable was taken in interaction with CSR1 and it was assumed in a first hypothesis that the effect of CSR1 on financial performance is moderated positively by technological performance. This hypothesis was not confirmed which is equivalent to saying that technological performance has no effect on financial performance (t=-1.304, p=194).
However, the effect of interaction variable between CSR and technological performance is insignificant. Our first hypothesis ( H1) was rejected and it can be stated that the effect of CSR1 on the financial performance of LLC is not moderated by technological performance [21,22].
Analysis of the effect of the interaction between CSR2 and technological performance on the financial performance of the LLC (H2): The statistical results showed that this variable has a negative and insignificant effect on financial performance (CSR-2 (t=0.646; p=0.519)).
In addition, the technological performance variable was taken in interaction with CSR and it was assumed in a first hypothesis that the effect of CSR2 on financial performance is moderated positively by technological performance. This hypothesis was not confirmed which is equivalent to saying that technological performance has no effect on financial performance (t= -0.736, p=0.463).
However, the effect of interaction variable between CSR and technological performance is insignificant. Our first hypothesis (H2) was rejected and it can be stated that the effect of CSR2 on the financial performance of the LLC is not moderated by technological performance.
Analysis of the effect of the interaction between ownership concentration and technological performance on the financial performance of the LLC (H3): The statistical results showed that ownership concentration has a negative and significant effect on financial performance (t=-3.170; p=0.002).
In addition, the technological performance variable was taken in interaction with ownership concentration and it was assumed in a first hypothesis that the effect of ownership concentration on financial performance is positively moderated by technological performance. This hypothesis was confirmed which is equivalent to saying that technological performance positively influences financial performance (t=5.471; p=0.000).
However, the effect of the interaction variable between ownership concentration and technological performance is significant. Our second hypothesis (H3) was confirmed and it can be stated that the effect of ownership concentration on LLC financial performance is positively moderated by technological performance.
Indeed, our empirical results validate our idea that the cognitive contribution of the shareholder is reinforced by the margin of control he enjoys. Nevertheless, in a specific setting, such as the development of innovation projects, the ownership of financial and cognitive capital is an asset to stimulate these activities. As a result, concentration of ownership, particularly if the appropriate shareholders maintain their holdings for long periods, stimulates longterm investment in innovation. Ownership concentration can thus be seen as a form of financial commitment and integration that is necessary for the most innovative firms [23-25].
The financial performance of the sampled LLCs improves with the inclusion of intangible investments. This means that financial performance improves with such strategic choices. It turns out that Tunisian LLCs tend to give great importance to their specific assets which represent for them a guarantee of the company's future competitiveness. The overriding need to maximize the wealth of the partners pushes the managers to take risky investments that are potentially very profitable if successful [26]. Analysis of the effect of the interaction between the presence of an auditor and technological performance on the financial performance of the LLC (H4): The statistical results showed that the presence of an auditor has a negative and significant effect on financial performance (t=-4.309; p=0.000).
In addition, the variable relating to technological performance was taken in interaction with the presence of an auditor and it was assumed in a first hypothesis that the effect of the presence of an auditor on the financial performance is positively moderated by the technological performance. This hypothesis was confirmed, which is equivalent to saying that technological performance positively influences financial performance (t=8.379; p=0.000).
However, the effect of the interaction variable between the presence of an auditor and technological performance is significant. Our fourth hypothesis (H4) was confirmed and it can be stated that the effect of the presence of an auditor on the financial performance of the LLC is positively moderated by the technological performance.
In fact, the auditor is one of the elements that seems very important to safeguard the interests of the partners, ensuring that the mandated managers, act on behalf of the latter and other stakeholders involved in the business and seek to maximize and create value while adopting innovative projects capable of improving the performance of the LLC [27,28]. Analysis of the impact of control variables on financial performance: Statistical tests show that the control variables are significant.
The business sector: The statistical results show that there is a positive relationship between industry and financial performance (beta=0.062). The t-statistic, which tests the significance of this result, shows that this relationship is not significant (t=1.521, p=0.130). Therefore, the sectoral affiliation has a positive and insignificant impact on the financial performance of LLCs [29].
The size of the company: The statistical results show that there is a negative relationship between firm size and financial performance (the regression coefficient is equal to (-0.040). The tstatistic, which tests the significance of this coefficient, shows that this relationship is not significant (t=-0.992, p=0. 323).
The size of the company is considered as a non-significant variable
The plurality of managers: The plurality of managers is positively related to financial performance (the statistical coefficient is equal to 0.037). The t-statistic shows that this relationship is not significant (t=0.877, p=0.382). This result would tend to show that the plurality of managers is an explanatory variable of the financial performance of LLCs. We could conclude that the plurality of managers is not a determining element in the development of innovation in Tunisian LLCs in this sample and therefore the effect of co-management on their financial performance is not significant (Table 7).
| Dependent variable: perftech | |||
|---|---|---|---|
| Control variables | Coefficient | T | Meaning |
| Business sector | 0.062 | 1.521 | 0.13 |
| Size | -0.04 | -0.992 | 0.323 |
| plurality | 0.037 | 0.877 | 0.382 |
The statistical results showed us the existence of a moderating effect of technological performance. Indeed, the financial profitability of the companies in the sample improves with the inclusion of intangible investments. This means that financial performance improves with such strategic choices. It turns out that Tunisian LLCs tend to give great importance to their specific assets which represent for them a guarantee of the company's future competitiveness. The overriding need to maximize the wealth of the partners pushes the managers to take risky investments that are potentially very profitable if successful.
As a result, value creation is reduced to the company's capacity for innovation. In addition, the adoption of intangible investments, which are often risky and generate problems of information asymmetry, increases the need for adequate financial profitability. This pushes managers to seek an efficient use of the equity and assets available to the company in order to maximize the wealth of the partners.
On the one hand, the exercise of innovation has become the central issue of the company. It would therefore be logical to include it in the explanation of financial performance. In this sense, its performance results from the realization of specific investments.
Indeed, by introducing the moderator effect, additional explanations and outcomes appear in the investigation of the link between the specific governance structure and financial performance. The moderating factor which is the technological performance seems to be able to improve and deteriorate the financial performance of the LLC.
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