Global Journal of Management and Business Research

Global Journal of Management and Business Research Vol. 10 Issue 1 (Ver 1.0), Febuary 2010 P a g e | 140 Assessing of the SME‘s Financial Competitiveness Nicoleta Bărbuţă-Mişu Abstract - This paper evaluates the financial competitiveness or performance of SME’s acting in the building sector in Romania. The financial performance is evaluated using a model of determining the financial performance developed especially for features of the Romanian business environment in the construction sector. This model of prediction of the risk of bankruptcy was achieved by using the information from balance sheets of 11 enterprises acting in the building sector in the period 2001-2006. In this approach, for assessing the financial competitiveness has been used data from the balance sheets of these SME’s in the period 2007-2008. The conclusions show the relevance of the model in forecasting the financial performance and ranking the SME’s by their performance. Keywords- financial competitiveness, risk of bankruptcy, capital structure, returns on equity, financial performance, retained profit ratio, financial modelling, general leverage JEL Classification: G32, G. 33 I INTRODUCTION T his study evaluates and predicts the enterprise financial performance of the enterprises acting in the building sector using the model of determining the financial performance by financing designed in the paper ―Modelling the Financial Performance of the Building Sector Enterprises – Case of Romania‖ (Bărbuţă-Mişu, N., 2009a). Unlike those models known in the literature, that were designed taking into account the characteristics of economies in which they were performed, this model takes into account the specificity of the Romanian building sector. The bankruptcy prediction of the enterprises as well the financial performance is a great interest issue, which has continued such attention to researchers and specialists for several decades. The development of many bankruptcy prediction models, which made and still made the subject of numerous works of specialty in the country and abroad show the importance of the bankruptcy models. Sharma and Mahajah (1980) present a general pattern of bankruptcy in which the ineffectual management doubled by the inability of anticipating events cause a systematic deterioration of performance indicators. In the absence of the corrective actions, this deterioration to the financial conditions determines the bankruptcy (Sharma S. and Mahajah V., 1980). In this approach has been started to the model of determining the financial performance by financing that was used for 2 samples of enterprises Manuscript received ―29.01.2010‖ Lecturer PhD, Department of Finance and Economic Efficiency, „Dunarea de Jos‖ University of Galati, Address: 47 Domneasca Street, Galati, ROMANIA, Zip Code 800008, Phone: +40336130172, Nicoleta.Barbuta@ugal.ro The first sample includes 11 enterprises to which data on the period 2001-2006 were used to determine the variables and coefficients of the model mentioned above and the second sample of 10 enterprises that were used for testing the same model. The prediction of the bankruptcy in this paper was achieved by using information from the balance sheets of the enterprises of those 2 samples on the period 2007-2008. This prediction is used for ranking the enterprises by the financial competitiveness. II THEORETICAL AND EMPIRICAL LITERATURE The financial performance prediction for enterprises, banks and not only, the lack of ability in paying the contracted debts, is a topic of great interest, which for decennials continues to be of great interest for researchers and practitioners. Setting up a model for bankruptcy prediction was, and continues to be today, the subject of many scientific papers presented at national and international levels. The models proposed until today have the disadvantage that they may be applied only in the economies of the countries where the statistical study was performed, or within the branch or sector of activity studied, their use unable to be extended to a greater area. Furthermore, the periods marked by economic instability determine the alteration of the correlations examined by the developed score function, which limits in time the use of these models. This situation requires an update at regular intervals of time, or development of other models valid for the new conditions (Siminică, 2005). By studying the intervals found for the score function, some enterprises are classified as presenting a high bankruptcy risk, or a lower one, or without bankruptcy risk. From this it results that the enterprises that show a high bankruptcy risk obtain lower financial performances, and vice versa, the ones that fall outside the bankruptcy risk obtain a high financial performance. Researchers of the statistical models have used the financial rates for building some predictive functions of bankruptcy. All the predictive studies of enterprises bankruptcy are based on original contribution of Beaver's (1966) and Altman (1968). Beaver has brought the most important contribution to the univariate analysis of bankruptcy for an enterprise. The technique of the univariate analysis implies the use of a single financial rate in a model of bankruptcy prediction. Beaver separately analysed few financial rates and selected the critical point for each rate, so as to maximize the prediction accuracy. Altman realized a multivariate analysis of bankruptcy that supposes to develop a multiple discriminate analysis. The main idea of the multivariate analysis is represented by P a g e |141 Vol. 10 Issue 1 (Ver 1.0), January2010 combining information related to few financial rates in a single function (weighted index). Beaver and Altman had many successors who developed the performances of models for analysis the bankruptcy risk, initiating alternate analysis methods. Thus, for bankruptcy prediction had been shown by two schools (Anghel, I., 2002): the Anglo-Saxon school represented by the Beaver model, the models developed by Altman, the Edmister models (1972), the Diamond model (1976), the Deakin probabilistic model (1977), the Springate model (1978), the Koh and Killough model (1980), the Ohlson model (1982), the Zavgren study (1983), the Fulmer model (1984), the Koh model (1992), the Shirata model (1999) designed in Japan on the basis of Anglo-Saxon school studies; the continental school represented by the Yves Collongues model (1976), the Conan and Holder model (1979), the model of Balance Exposure of France Bank, the model of the French Commercial Credit (CCF), Chartered Accountants model (CA Score – 1987), the Score Function AFDCC 2 (1999). Unlike the Anglo-Saxon school and continental school, the Romanian school is more distinguished by theoretical contributions. The economic and financial modelling made history in traditional domains: multi-criteria models for the financial and macroeconomic equilibrium and for the quantification of this equilibrium (Bărbuţă-Mişu, N., 2009b). The Romanian school (Anghel, I., 2002) is represented by following empirical models: Manecuta and Nicolae model (Mânecuţă C., Nicolae, M., 1996) proposed in the metallurgical industry, Model B – Bailesteanu (Băileşteanu Ghe., 1998) and Model I – Ivonciu (Ivonciu P., 1998). Siminica, M. I. has achieved a Model for analysis of bankruptcy risk in the Romanian industrial firms (Siminică, M. I., 2005). Also, I designed an aggregate index of financial performance for the building sector enterprises from Galati (Bărbuţă-Mişu, N., 2009a) that will be used for financial performance prediction in this paper. Bankruptcy risk prediction models have a predominantly statistical character, being designed with a starting point that takes into account the past financial status of bankrupt enterprises (thus with very low financial performance) and of some enterprises that experienced no financial difficulties (thus, with high financial performance). As the obtained results will be generalized for all enterprises showing the same features with those under focus, mention must be made from the start that the features and the activity sector of the selected enterprises for the study must be presented. III THE MODEL OF DETERMINING THE FINANCIAL PERFORMANCE DESCRIPTION This study asses the enterprise financial performance of the enterprises acting in the building sector using the model of determining the financial performance by financing (Bărbuţă-Mişu, N., 2009a). The main conditions that must be met by all enterprises from the sample are: to be included in the building sector; to grasp the evolution in time of the financial performance of the enterprises under study; to have a continuous activity throughout the analysed period; the selected sample must include not only enterprises showing Global Journal of Management and Business Research high financial performance, but also low financial performance. The time period considered for data collection from the first sample of enterprises is of 6 years that is 2001 – 2006, which means that we managed to grasp the time evolution of financial performance for the enterprises under study. One essential condition taken into account when establishing the sample was that the enterprises active in this sector to show continuous activity during the chosen time interval. This condition greatly reduced the number of potentially sampled enterprises, as a great number of enterprises closed their activity while other was only beginning it. The greatest problem we faced was to identify the building sector enterprises active in Galati County, for which the site of the Ministry of Finance has yet to give a solution. Thus, searching for these enterprises was mainly based on their notoriety. Thus there were identified 11 enterprises. The selected and analysed enterprises are representative for Galati County. In the year 2006, they represented 0.93% of the total number of active enterprises in the building sector, with a turnover of 100.61 million euros, respectively 35.85% of the turnover obtained in the Galati county building sector and, respectively, 5.78% of the total turnover of the Galati county. Within the sampled enterprises in 2006 there were 3.639 employees, that is 29.55% of the workforce employed in the building sector of the county, and, respectively, 3.28% of the total employed in Galati County. The collection of data required to the study was provided by the Register of Commerce by studying the balances filed by those 11 enterprises. The financial information was extracted individual, for each enterprise above the period 2001-2006 and aggregate to the building sector. After a long analyse of many financial rates the enterprises from sample were grouped in two categories: performant enterprises or with a low risk of bankruptcy and nonperformant enterprise or with a high risk of bankruptcy. The discriminate analysis had shown significant differences between the two groups of enterprises (performant and nonperformant), for each ratio employed. Thus, was proved the representativeness of the chosen sample for setting up the model of determining the financial performance. From the financial diagnosis of the enterprise, in Romanian and foreign literature and also in financial practice, can be derived a plethora of ratios that can be used as variables for various models. From the whole of the financial ratios presented in the literature, were selected only 8 for the discriminate analysis, which were thought the most significant. Finally, out of these were selected just 5 for the model variables: return on equity, general leverage, retained profit ratio, general liquidity and the weight of financial debts within the total debts. The return on equity measures the profitability of owners‘ capital that is the financial investment made by shareholders when buying the enterprise shares (Stancu, 2002) and is influenced by the way of asset securing and, thus, by the financial structure of the enterprise (La Bruslerie, 2002). Global Journal of Management and Business Research The return on equity ( R f ) is calculated in accordance with Rf  Net result Owners' capital the formula: and quantifies the remuneration of capital invested by shareholders, including the net profit at the disposal of the enterprise for self financing (Lumby, Jones, 2003). The reasons for which were chosen the return on equity as first variable took into account the fact that, as the intention was to design a parameter of financial performance, we appreciate it as being the most relevant parameter of this variable, ensuring the best predictions, a fact demonstrated also by Zmijewski (1983) in a study performed on 75 enterprises filing for bankruptcy, and 3.573 non-bankrupt enterprises; also, for the owner, this is the most expressive parameter for measuring the result as it is superior (as compared to owner‘s concern) to economic profitableness, to expenses or turnover. On the other hand, it is a parameter widely used by Romanian banks when performing the analysis of enterprise worthiness, for example Raiffeisen Bank and the Commercial Bank. General leverage ( Gig ) calculated as follows: Gig  Total debts Own assets reflects the degree in which own assets ensures the financing of the enterprise activity. This parameter can be also interpreted as a ratio of financial autonomy of the enterprise, as it indicates the degree in which its long and short term commitments are guaranteed by own assets. The majority of Romanian banks use as trust indicator the general leverage, but many times this is calculated as a ratio between total debts and total liabilities (Raiffeisen Bank, Commercial Bank, Romanian Bank for Development). As the intention was to set up a model of financial performance by financing, the general leverage mentioned in the above formula is considered the most relevant parameter of the decision for financing. R The reinvested profit ratio ( pr ) is a ratio less used in the Romanian literature and in banking, but it was chosen to use it within the model as Romanian enterprises used extensively the profits for reinvesting. The reasons for doing this refers to enhancing the enterprise position on the competitive market, increasing the degree of capitalization, redimensioning the social asset, and even taxation. The retained profits are an alternative and cheaper method of increasing owners‘ capital in comparison with new shares issued and is the most important source of capital used for financing intangibles. More frequently, the literature deals with the ratio of dividends distribution ( RDv ) by the shareholders (Krainer, 2003), computed as: ( 1  R pr ). This is because the investors, especially the ones who speculate, are interested mainly in the level of earnings on short term and in the time of recovering their investment by cashed dividends. Vol. 10 Issue 1 (Ver 1.0), Febuary 2010 P a g e | 142 The general liquidity ( Rlg ) computed as: Circulatin g actives measures the capacity of cash Short term debts flow of the enterprise that is short term solvency and reflects the degree in which the turning into cash flow of circulating actives can satisfy the exigible payment obligations. There was chosen the ratio of general liquidity as it reflects the short-term financial balance of the enterprise, although this has proven to be a bad bankruptcy predictor, in accordance with Zmijewski study. Yet, it is a parameter widely used by banks, for example Raiffeisen Bank. With the Commercial Bank and the Romanian Bank for Development, in the above mentioned formula, the circulating actives are corrected (diminished) with the value of non valorised stock and of uncertain clients. The weight of financial debts within the total debts ( D f %  ) Rlg  is computed as: D f %   Financial debts and reflects the ratio Total debts of financial debts with a view of pointing out the nature of enterprise financing. This parameter shows the dependency of enterprise towards banks and other business partners. This is not a ratio that is used by banks, but it was considered useful as a relevant indicator in what concerns the temporal stability of financing sources used by the enterprise. Using these variables, the model for financial performance assessment (Bărbuţă-Mişu, N., 2009a) obtained is: Pf  0,32  R f  0,4554  Gig  4,0207  Ri  0,8787  Rlg  10,7815  D f % This model allows for framing an enterprise with the characteristics of those enterprises selected for the sample, in a certain performance area. For this there are firstly calculated the 5 financial ratios involved in the analysis, on the basis of which the score P f is determined. In accordance with its value, the enterprise will fall in one of the following 5 performance areas: - if Pf ≥ 4,25 the enterprise has a very high financial performance; - if 2,75 ≤ P f < 4,25 the enterprise has a medium financial performance; - if 1,25 ≤ P f < 2,75 the enterprise has a satisfactory financial performance; - if -0,25 ≤ P f < 1,25 the enterprise has a low financial performance; - if P f < -0,25 the enterprise has a very low financial performance. The limits agreed for setting up the intervals represent the simple arithmetic average of scores granted for two consecutive groups of enterprises. The higher the value of score P f determined for an enterprise, more than the value of 1.25, (the limit that mathematically separates the enterprises with high financial P a g e |143 Vol. 10 Issue 1 (Ver 1.0), January2010 performance apart from the low financial performance ones), the greater the possibility of obtaining a higher performance. To always have a higher financial performance, the recurrent calculation of the score P f is needed, as its reduction in value implies a reduction in the financial performance and, in these conditions, the managers should take measures for recovery. This model was later tested both for enterprises from the first sample under study, and also for other enterprises in the posterior sample, obtaining an average success ratio. Thus, the following results were obtained after model testing for the 11 enterprises in the initial sample: In 2006, for performant enterprises, the success ratio (comparing the predictive classification with the known data on the initial sample enterprises) being of 85.71%, and based on medium financial ratios (calculated for the latest six years) 71.43% of enterprises were correctly included. In 2006, for enterprises with low performances, the success ratio was 50%, and based on medium financial ratios 100% of enterprises were included correctly. Overall of tested enterprises included in the initial sample, the success ratio of establishing the financial performance (calculated on the basis of medium values of the financial ratios involved in our analysis) was of 81.82% and for the year 2006 was of 72.73%. Furthermore, the model was tested for also enterprises in the same sector, which were not included in the first sample. In the given conditions, it was noticed a prediction success degree lower than the aprioric one, where only 60% of the performant enterprises, and, respectively, only 60% of enterprises with low financial performance, were correctly grouped for the year 2006 and 80% of the performant enterprises and 60% of non-performant enterprises were correctly grouped for 2001 - 2006 period. Global Journal of Management and Business Research In conclusion, comparing the well-known models to the international level for assessing the risk of bankruptcy with this model for determining the financial performance adapted to the specificity of the Romanian economy there are clear the significant differences, and it results as models for assessing the risk of bankruptcy are relevant only if there are satisfied conditions related to the presence of some similar economic characteristics in the analyzed period and enforceability on some enterprises in the sector of activity had referred to. IV METHODOLOGY AND DATA PREDICTION The capacity of prediction of this model was tested on those 2 samples of enterprises in the period 2007-2008. The first sample includes 11 enterprises to which data on the period 2001-2006 were used to determine the coefficients and variables of the model for determining the financial performance (Bărbuţă-Mişu, N., 2009a) and the second sample of 10 enterprises that were used for testing the mentioned model. The data for period 2007-2008 were collected from the balance sheets of the enterprises. There were calculated the values of the variables considered and determined the P f score for both samples. Firstly, starting to the model of determining the financial performance it was achieved the prediction of financial competitiveness for the period 2007-2008 for the first sample (a priori). The ranking and appreciation of enterprises after the financial performance in 2007 and 2008 are presented in the Table 1 and 2. Table 1. Ranking of the enterprise after the financial performance in 2007 (a priori sample) Enterprise Appreciation Interval P f P f score CONSTRUCŢII AVRAM IANCU SRL ARCADA COMPANY SA CONFORT SA ARCADA SRL SOREX SA VEGA 93 SRL CONSAL SRL MOLDOVULCAN SA CONSTRUCŢII ŞI REPARAŢII SA ICMRS SA CONSTRUCŢII FEROVIARE SA 10.693 6.688 5.872 5.708 4.879 2.449 1.852 1.788 1.047 0.945 0.028 Pf ≥ 4,25 Enterprise has a very high financial performance P 1,25 ≤ f < 2,75 Enterprise has a financial performance P -0,25 ≤ f < 1,25 Enterprise has a low financial performance Source: Calculus performed by author satisfactory Global Journal of Management and Business Research Vol. 10 Issue 1 (Ver 1.0), Febuary 2010 P a g e | 144 of the financial performance was registered by Confort that in 2006 was in the uncertainty area, with a satisfactory performance, in 2007 registered a high financial performance and in 2008 was ranged in the enterprises with low financial performance, that proves the significant changes that took place in the building sector caused by the effects of the economic and financial crisis.Also, we can observe in the Tables 1 and 2 that if in 2007, there were only 3 intervals of performance, in 2008 the financial performance of the enterprises was dispersed in all 5 ranges of the model. If in 2006, the enterprises Arcada Company and Sorex, were classified as having a high financial performance (BărbuţăMişu, N., 2009), the Table 2 show that in 2007, when was the largest development of the building market, both enterprises are maintaining to the same level of performance, as well as in 2008. In 2007, the enterprises Construcţii Avram Iancu, Confort and Arcada were included in this range of performance and in 2008 only Arcada maintain this position. In 2006 and there wasn‘t any enterprise classified as having a medium financial performance but in 2008 Construcţii Avram Iancu is framed in this range of performance. The most fluctuating evolution Table 2. Ranking of the enterprise after the financial performance in 2008 (a priori sample) Enterprise Appreciation Interval P f P f score ARCADA SRL CONSAL SRL VEGA 93 SRL ARCADA COMPANY SA SOREX SA 9.555 6.565 6.131 5.934 5.021 Pf CONSTRUCŢII AVRAM IANCU SRL 3.865 2,75 ≤ Pf < 4,25 MOLDOVULCAN SA 1.792 1,25 ≤ Pf < 2,75 CONFORT SA ICMRS SA CONSTRUCŢII FEROVIARE SA 1.093 0.428 -0.332 -3.463 -0,25 ≤ Pf < 1,25 CONSTRUCŢII ŞI REPARAŢII SA Pf ≥ 4,25 < -0,25 Enterprise has a very high financial performance Enterprise has a medium financial performance Enterprise has a satisfactory financial performance Enterprise has a low financial performance Enterprise has a very low financial performance Source: Calculus performed by author bankruptcy in conditions which in the preview period had a risk of bankruptcy less. The enterprise Moldovulcan has passed from a high competitiveness in 2006 to the uncertainty area in 2007 and 2008. The whole analyzed period, the enterprises ICMRS, Construcţii feroviare and Constructii şi reparaţii where within the range with high bankruptcy risk. Studding the individual values of the model variables we can conclude that more affected by the crisis effects were enterprises that have established large debts unpaid or with large terms of collection (that means a low current liquidity), those enterprises who have several works in progress and need more source of financing to complete the work (a high degree of debts). This is an explanation for enterprise Confort that in 2008 presents a high risk of Enterprise Table 3. Ranking of the enterprise after the financial performance in 2007 (a posteriori sample) Appreciation Interval P f P f score DRUMURI ŞI PODURI SA VIVA CONSTRUCT SRL TRIPLEX SRL COMTIEM SRL KATY SRL CIVICA SA BAZA SRL 12.177 8.210 6.774 5.014 3.960 3.766 3.385 BRICO SRL VÎLCEANA SA UNICOM SA Pf ≥ 4,25 Enterprise has a very high financial performance 2,75 ≤ Pf < 4,25 Enterprise has a medium financial performance 1.667 1,25 ≤ Pf < 2,75 Enterprise has a satisfactory financial performance -0.477 Pf < -0,25 Enterprise has a very low financial performance - Source: Calculus performed by author P a g e |145 Vol. 10 Issue 1 (Ver 1.0), January2010 The return on equity that has been significantly reduced due to the economic crisis there is another cause that has generated the increasing of the bankruptcy risk to the assessed enterprises. Secondly, the same model was applied for prediction the risk of bankruptcy on the period 2007-2008 for the second sample of enterprises (a posteriori) used in the testing of the above model. The ranking and appreciation of enterprises after the financial performance in 2007 and 2008 are presented in the Table 3 and 4. If in 2006, the enterprises Katy and Baza were classified as having a high financial performance (Bărbuţă-Mişu, N., 2009a), the Table 3 show that in 2007 both registered a medium performance, and in 2008 (Table 4) only enterprise Baza returns to the same class of competitiveness. This proves that the enterprises acting in the building sector were affected by the economic and financial crisis as well as the first sample. This situation appears to be a generalized evolution in the building sector and not only. The enterprise Global Journal of Management and Business Research Unicom, classified in 2006 as having a high risk of bankruptcy becomes bankrupt and from 2007 was removed from the Register of Commerce. If in 2006, the enterprises Viva Construct and Comtiem were classified as having a medium performance, in 2007 and 2008 progressed, entering in the class of companies with high financial performance, despite of the financial and economic crisis, which did not affect its activity. These companies were involved in small-scale works, which no required important sources of funding or had worked with materials provided by the client. Brico is the enterprise that overall period maintained in the uncertainty area, but from one year to another, the performance index slow down. A very fluctuating evolution had the enterprise Drumuri şi poduri that in 2006 and 2008 had a high risk of bankruptcy and in 2007 had a financial performance very high to the sample level. Table 4. Ranking of the enterprise after the financial performance in 2008 (a posteriori sample) Enterprise Appreciation Interval P f P f score VIVA CONSTRUCT SRL 11.056 BAZA SRL 9.231 TRIPLEX SRL 7.345 COMTIEM SRL 5.225 CIVICA SA 4.346 KATY SRL 3.531 VÎLCEANA SA 1.598 BRICO SRL DRUMURI ŞI PODURI SA UNICOM SA P f ≥ 4,25 Enterprise has a very high financial performance 2,75 ≤ P f < 4,25 Enterprise has a medium financial performance 1.472 1,25 ≤ P f < 2,75 Enterprise has a satisfactory financial performance -2.191 P f < -0,25 Enterprise has a very low financial performance Source: Calculus performed by author Global Journal of Management and Business Research V CONCLUSIONS In conclusion, the model for determining the financial was created using financial data of the enterprises in the period 2001-2006, a relatively stable period that generated some exigency in assessing the financial performance of the enterprises. If the model had taken into account and the period 2007-2008 or 2009 (when the effects of economic and financial crisis had made felt this) then the model exigency would be lower. Under these conditions, it is possibly that some companies evaluated in this paper having a low financial performance may actually be in the area of uncertainty and the enterprises from uncertainty area may be in fact assessed having a high degree of competitiveness. This means that such models requires an update at regular intervals of time, or development of other models valid for the new conditions Anyway, the capacity of prediction of this model was proved and the most important advantage of it is that provide a way of ranking of the enterprises after their financial performance. Also, the model provide the financial performance forecasting for an enterprise in the case in which we can make a prevision as real as possible of the financial rates that constitute the model variables. The model may offer some other benefits: listing enterprises in certain performance areas according to the value of the financial performance aggregated index; at a certain moment, the management of the enterprise can take decisions related to the activity, investments, financing etc., according to the values of the financial performance index; starting from a sought level of financing rates that constitute the model variables, the enterprise management can timely acknowledge the performance level their enterprise will take, and can take corresponding decisions. VI ACKNOWLEDGEMENTS This research was performed on the base of the model proposed in the doctoral thesis „Enterprise Financing within the National Strategy of Development Converging to the European Integration Process‖ and published in the article Modelling the Financial Performance of the Building Sector Enterprises – Case of Romania, in Romanian Journal of Economic Forecasting, No. 4/2009. 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