Energy Policy 128 (2019) 431–439
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Energy companies and sizes: An opportunity? Some empirical evidences ⁎
Felicetta Iovino , Guido Migliaccio
T
1
Department of Law, Economics, Management and Quantitative Methods, Via Delle Puglie, 82, University of Sannio, Benevento 82100, Italy
A R T I C LE I N FO
A B S T R A C T
Keywords: Energy companies Finance Performance Ratios SME ROE
The wave of privatization and liberalization that since 1999 has characterized the European energy market has radically transformed the energy sector. The European Directives have allowed the entry of a plurality of new operators alongside the former monopolist. In this sense, the paper will pose two research questions: are there differences or similarities between the financial performance of large companies and those of small and mediumsized energy companies? What are the main reasons for such analogies? At this aim the analysis of the main financial ratios, a descriptive statistics analysis and ANOVA (one-way) have been used. The financial structure has been assessed using different ratios: quick ratio, debt to equity ratio, asset turnover ratio, ROS, ROA and ROE. The findings show that the size of energy suppliers do not significantly affect the performance of energy companies. Moreover, these factors do not produce statistically significant differences in the financial structure of energy companies. The main policy implication of the paper is the description and analysis of the performances of energy companies in a country regarding size may stimulate the entry of additional operators into the market, increasing competition and improving the service offered, which are the main objectives of the liberalization processes.
1. Introduction Since 1999 the European energy markets have undergone a major transformation to adapt the sector to changes agreed with the European Directives. Since 2007, the European energy markets have been liberalized completely and open to all customers. After the wave of privatization that characterized all public services, that is, all final customers were allowed to freely choose their energy, gas and electricity supplier on the market. In this way, every customer has seen the possibility of entering into supply contracts with companies other than the incumbent, i.e. the former monopolist, ENEL for electricity and ENI for gas, in Italy. This choice has been permitted to business clients and subsequently to residential clients, i.e. families and small firms. The liberalization of the market has allowed the entry into the market of a significant number of new companies in completely liberalized phases, i.e. production and sale of energy. Next to this, numerous small and medium-sized competitors have joined the large operators. This study focuses on the situation of energy companies in Italy in the years following liberalization. To this end, the main financial results have been analyzed in relation to the different sizes of the companies. In this sense, two key questions have been posed:
1) are there differences or similarities between the financial performance of large companies and those of small and medium-sized energy companies? 2) What are the main reasons for such analogies? On the basis of radical and innumerable transformations of the market, both on the demand side and on the supply side, it is possible to hypothesize (H1) that small and medium-sized energy companies can achieve financial performance similar or higher than those achieved by large companies and that these results have to be ascribed (H2) to the characteristics of small and medium-sized enterprises and to new instruments available to these companies and thus (H3) there aren’t statistically significant differences between the performances of large and small and medium-sized companies. This last hypothesis aims to verify and highlight that the performances of the companies are in some ways different, as the structures and types of companies are different. However, any major differences that exist are not statistically significant. To demonstrate the aforementioned hypotheses, the main financial and profitability ratios, are analyzed by representing them through histograms, by a descriptive statistics analysis and ANOVA (one-way),
⁎
Corresponding author. E-mail addresses:
[email protected] (F. Iovino),
[email protected] (G. Migliaccio). 1 The paper is the result of a collaborative work. However it is possible to attribute to Felicetta Iovino: the energy markets in Italy, theoretical analysis of characteristics of SMEs, methodology and data, results and discussion. The other sections are of Guido Migliaccio. https://doi.org/10.1016/j.enpol.2019.01.027 Received 9 August 2018; Received in revised form 28 November 2018; Accepted 12 January 2019 0301-4215/ © 2019 Elsevier Ltd. All rights reserved.
Energy Policy 128 (2019) 431–439
F. Iovino, G. Migliaccio
Fig. 1. Main steps in the European energy reforms. Source: Jamasb and Pollitt (2005).
include the increased integration of renewables in the European electricity market, greater consumer involvement, transparency, greater security of supply and wider cooperation between Member States. A further category of interventions aims at the creation of a new directive on renewables and the revision of 2012/27 Directive on energy efficiency. Finally, a further proposal for new regulation concerns the regulation of risk in the electricity sector and the governance of the Energy Union. (Hancher and Winters, 2017). Thus following unbundling, the energy supply chain is characterized by five specific phases. The electricity phases are: production, transmission, dispatching, distribution and sales. The gas supply chain phases are: production, storage and dispatching, transport, distribution and sales. These phases, as shown below (Fig. 3) for electricity and (Fig. 4) for gas market, have been disaggregated, whereas previously they were entrusted to a single vertically integrated monopolistic firm (Migliaccio and Iovino, 2018). The incumbent was ENEL for electricity market, and ENI, for gas market, in Italy. The production and sale phases have been liberalized allowing the entry of a plurality of operators and therefore they are open to competition; on the other hand, the other phases are carried out by a single or few operators for technical reasons. In fact, they are subject to a natural monopoly. They are: transmission, dispatching and distribution. Specific companies perform these activities in Italy. In fact, dispatching and transmission of electricity are carried out by Terna, a joint-stock company controlled by the Ministry of Finance, while distribution activities are in local monopoly due to the concessions of the Ministry of Economic Development expiring in 2030. Storage of the gas is a regulated activity by concessions of the Ministry of Economic Development. Dispatching is a strategic phase which is executed by the incumbent, Snam (ENI), but in coordination with regional and location distributors. Nevertheless, the system is in transition from an “administrated” dispatching to a “market” dispatching by means of the implementation of the European Directive of 2009. The distribution of gas is a regulated activity and its operators have a concession by the local institution. In 2017 the main operators were about 200 distribution firms in Italy and the most important ones are Italgas and 2i Rete Gas.
whose description can be found in Hays (1994). The main literature propositions concerning the peculiar characteristics of small and medium-sized enterprises are also analyzed. In the following sections, a picture of the Italian energy markets, the literature analysis, the methodology, the results and the main policy implications will be presented.
2. The energy markets in Italy The Italian energy markets have been characterized by profound transformations in the last two decades. The European Directives (Directive 96/92/EC, Directive 2003/54/EC, Directive 2009/72/EC for electricity market, Directive 98/30/EC, Directive 2003/55/EC, Directive 2009/73/EC for gas market) imposed the unbundling of the supply chain allowing the entry of new operators in the phases open to competition, generation and sales (Iovino, 2012, 2015). The main transformations and objectives pursued by the European Directives are indicated in the following figures ( Figs. 1 and 2) (Jamasb and Pollitt, 2005; Vasconcelos, 2004). They may summarize as follows: a) the liberalization of the phases of the energy supply chain not constituting a natural monopoly (production and sale); b) unbundling; c) free choice of own energy supplier for eligible customers identified on the basis of consumption thresholds. The 2009 EU Directives repealed the 2003 Directives, substantially pushing for the achievement of the objectives already foreseen by the directives of previous years. The priority aspect of the so-called "third energy package" is constituted by the desire to achieve greater competition, through non-discriminatory access to the network by all parties other than the incumbent; effective separation of the activities of the transport and production and supply network; protection of noncivil customers with consumption of less than 50,000 m3; creation of the Agency for the Cooperation of National Energy Regulators (ACER) in order to create a single European energy market. On 30 November 2016, the European Commission approved the socalled "winter package". It is a package of legislative proposals that refer to different areas. A first type of measures concerns a new design of the electricity market through the proposal for a new directive and 3 regulations, which will replace Directive 2009/72 and specify a new regulation for ACER. The goal of these interventions are multiple. These
3. Theortical analysis of characteristics of SMEs The analysis of the characteristics of the SMEs has been carried out through a research in Web of Science database for the period 2016–2017 using keywords such as: SME, small firms, medium-sized 432
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Fig. 2. First electricity European directives. Source: Vasconcelo (2004).
firms. Moreover the snowball technique has been performed. An indepth analysis of the papers has been carried out. These papers have been selected on the basis of the peculiarities of the SMEs proposed by them. Thus, 38 texts have been identified. In this way, conclusions have been drawn about hypothesis H2. The in-depth analysis of the selected papers has been done on the basis of semantic analogies. In this ways, about 16 peculiar characteristics of the SMEs have been identified. These characteristics allow them to have financial performance similar or even higher than those ones of the big companies. The hypothesis H2 is verified by means of the analysis of the literature. The results of this analysis are summarized in the following table (Table 1). Pellegrino and McNaughton (2017) and Alvarez et al. (2016) underline that a specific characteristic of SMEs is the experiential learning and thus a creation of a repository of knowledge. These play a crucial role in the internationalization of SMEs both for the incremental and rapid way. Different authors (Granovetter, 1973; Hansen, 1995; Jack, 2005; Woolcock, 1998; Narooz and Child, 2017; Grimm et al., 2006; Lawrence et al., 2006; Simpson et al., 2004; Odlin and Benson Rea, 2017; Spence, 2007; Larran Jorge et al., 2016) highlight that SMEs have specific characteristics that distinguish them from large companies. Those are network ties, relationships, a small number of highly connected commercial relationships and personal relationships with
external agents. Close contact with local communities, customers and the satisfaction of their needs, due to the greater attention paid to the proximity market, are the characteristics identified by the studies of Spence (2007), Lofqvist (2017), Adamowicz and Machla (2016), Bos-Brouwers (2010), Falle et al. (2016), Bhattacharjee et al. (2009), Czarniewski (2016), Larran Jorge et al. (2016), Julien and Lafrance (1977), Stankovska et al. (2016). These studies suggest that SMEs have the opportunity to better customise their activities than large companies due to a less broad range of activities that they performance and a smaller market share. In this way, SMEs may achieve more positive performances than large companies. The studies of Spence (2007), Lofqvist (2017), Adamowicz and Machla (2016), Bos-Brouwers (2010), Falle et al. (2016), Czarniewski (2016), Larran Jorge et al. (2016), Julien and Lafrance (1977) and Stankovska et al. (2016) specify that flexibility is a distinctive factor of SMEs. In fact, these authors have carried out studies with different methodologies. These researches have found that SMEs have a competitive advantage by means of a most connatural flexibility than large companies. Innovation and creativity are verified as key elements of SMEs from Knight (2001), Guo et al. (2017), Lofqvist (2017), Adamowicz and Machla (2016), Hall et al. (2009) and Baumann and Kritikos (2016). In fact, they find a positive relationship between SME performance and opportunity of knowledge and that innovation has a mediate effect. Fig. 3. Disaggregation electricity chain. Source: our elaboration.
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liberalization
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Fig. 4. Disaggregation and liberalization gas chain. Source: our elaboration.
of the most difference between the two types of analyzed companies is the role played by the leadership within small and medium-sized firms. In fact, the leadership has a direct contact with employees. Furthermore, SMEs are found as niche differentiators by Miller and Toulouse (1986) and Onkelinx et al. (2016). SMEs compete globally choosing a strategic configuration based on superior innovation or superior quality. The studies of Onkelinx et al. (2016) and Rauch and Hatak (2016) demonstrate that high level of skills, abilities and knowledge of employees are particularly evident in SMEs. The results of these studies suggest that investments in human capital lead to a higher labor productivity and as a consequence to a greater level of internationalization. Adamowicz and Machla (2016) and Rauch and Hatak (2016) discuss as SMEs raise the quality of life of consumers and employees, motivation and empowerment. SMEs strength the growth of the whole local unit with relations which have a feed-back loop nature. Alvarez et al. (2016) highlight that a smaller number of employees is an advantage for SMEs compared with large companies. That permits highly shared values and beliefs achieving a fluid culture. However, the SMEs are not without disadvantages. The main limitations of these companies are limited financial resources and limited human resources to support, for example, the creation of numerous specialist departments. In fact, these companies do not implement a systematic development of human resources. Moreover, such companies often have conservative and patriarchal leadership. In fact, a leader who is also the owner of small and medium sized enterprises often decides the strategy. Thus, the lack of a corporate governance structure is evident (Mahmood, 2014). Such enterprises are also dependent on a few paths of knowledge, since they do not have in most cases strong links with large external centers, such as research institutes, for knowledge transfer (Wuest and Thoben, 2012). Finally, SMEs have
Innovation usually involves new products using known technology and towards established markets. A technology radical innovation is often excluded. Henrekson and Johansson (2010) and Gidehag and Lodefalk (2016) point out that a more instrumental role of recruited managers and professionals is played in the SMEs. Their researches demonstrate that recruited leading personnel have beneficial and important effects on the performances of SMEs. The analysis of Caves and Pugel (1980) shows that different strategies distinguish the path of SMEs and in particular Pisani et al. (2017) suggest international joint ventures. In fact, these types of strategies permit to SMEs to have a privilegiate access to resources and establish a limited commitment in each venture. Lofqvist (2017), Nolan and Garavan (2016), Julien and Lafrance (1977), Stankovska et al. (2016) discuss as fast decision making makes SMEs different from large companies. In particular, these studies suggest that SMEs have rapid implementation and execution of decisions. Lofqvist (2017), Bos-Brouwers (2010), Falle et al. (2016), Alvarez et al. (2016) and Durst and Edvardsson (2012) identify organizational aspects as characteristic of SMEs. Those are coordination allowing multifunctional roles and employees, low degree of formalization, informal, nonbureucratic and few roles, a small structure. The studies of Odoom et al. (2017), Iovino (2014), Iovino and Migliaccio (2016) and Stankovska et al. (2016) specify that social media marketing has a peculiar role in SMEs. SMEs achieve similar or higher results than large companies by means of the implementation of internet marketing and relationship marketing. The dominant role of owner is a characteristic element of SMEs in the studies of Mihai (2015), Mihai et al. (2017), Bos-Brouwers (2010), Falle et al. (2016), Reijonen and Komppula (2007), Fleming et al. (2016), Nolan and Garavan (2016) and Julien and Lafrance (1977). One Table 1 Main characteristics of SMEs. Source: our elaboration. Characteristics of SMEs
Source
Experiential learning/creation of a repository of knowledge Network ties, relationships, source of information and resources/small number of highlycommitted business relationships/interdependent sector networks/almost personal relationships with external agents Moral proximity with community and customers/close contact and communication with companies’ customers/satisfy various local needs/the local community are the stakeholders receiving the greatest attention/market proximity Flexibility
Pellegrino and McNaughton (2017), Alvarez et al. (2016) Granovetter (1973), Hansen (1995), Jack (2005), Woolcock (1998), Narooz and Child (2017), Grimm et al. (2006), Lawrence et al. (2006), Simpson et al. (2004), Odlin and Benson Rea (2017), Spence (2007), Larran Jorge et al. (2016) Spence (2007), Lofqvist (2017), Adamowicz and Machla (2016), Bos-Brouwers (2010), Falle et al. (2016), Bhattacharjee et al. (2009), Czarniewski (2016), Larran Jorge et al. (2016), Julien and Lafrance (1977), Stankovska et al. (2016) Spence (2007), Lofqvist (2017), Adamowicz and Machla (2016), Bos-Brouwers (2010), Falle et al. (2016), Czarniewski (2016), Larran Jorge et al. (2016), Julien and Lafrance (1977), Stankovska et al. (2016) Guo et al. (2017), Knight (2001), Lofqvist (2017), Adamowicz and Machla (2016), Hall et al. (2009), Baumann and Kritikos (2016) Henrekson and Johansson (2010), Gidehag and Lodefalk (2016) Caves and Pugel (1980) Pisani et al. (2017) Lofqvist (2017), Nolan and Garavan (2016), Julien and Lafrance (1977), Stankovska et al. (2016) Lofqvist (2017), Bos-Brouwers (2010), Falle et al. (2016), Alvarez et al. (2016), Durst and Edvardsson (2012) Odoom et al. (2017), Iovino (2014), Iovino and Migliaccio (2016), Stankovska et al. (2016) Mihai et al. (2017), Mihai (2015), Bos-Brouwers (2010), Falle et al. (2016), Reijonen and Komppula (2007), Fleming et al. (2016), Nolan and Garavan (2016), Julien and Lafrance (1977) Miller and Toulouse (1986), Onkelinx et al. (2016) Onkelinx et al. (2016), Rauch and Hatak (2016) Adamowicz and Machla (2016), Rauch and Hatak (2016) Alvarez et al. (2016)
Innovative/creativity A more instrumental role of recruited managers and professionals Different strategies International joint venture Fast decision making Coordination allowing multifunctional roles and employees/low degree of formalization/ informal, nonbureucratic and few roles/a small structure Social media marketing Dominant role of owner on his/her employees/dominant role of owner/entrepreneur/ centrality of owner managers/owner-managers control the composition of the top team Niche differentiators High level of skills, abilities and knowledge of employees/skills Raise the quality of life of consumers and employees/motivation/empowerment Smaller number of employees
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more difficulty implementing economies of scale. 4. Methodology and data 4.1. Data collection and sample characteristics To our aims, secondary data of AIDA database have been used. AIDA is a database that includes all financial data of companies that have at least a headquarter in Italy. Thus, the Italian energy companies operating in the sale phase have been analyzed. In this way, companies operating in the sale phase have been selected from the entire population of energy companies, electricity and gas ones. The total number is 428 companies. That number includes Single Buyer (AU) and Energy Services Operator (GSE), that are institutional entities of the Italian energy markets that have been excluded for the aim of the paper. Therefore, the total number of companies considered is 426 companies. The main financial metrics indicators such as, ROA (operating profit/ assets), ROE (net income/equity), ROS (operating profit/net sales) and quick ratio (liquid assets/current liabilities), debt to equity ratio (debt/ equity) and asset turnover ratio (net sales/assets) have been used to analyze the financial performance of these companies. These indices have been chosen, because in this way it is possible to analyze the financial and profitability structure of the companies under investigation. In fact, the quick ratio, asset turnover ratio, and debt to equity ratio are the main financial indicators. The quick ratio makes possible to check the immediate liquidity of the companies, while debt to equity ratio checks the level of indebtedness and therefore the risk towards third parties, but also if the company is levered. Asset turnover ratio indicates the number of times assets are depleted due to sales during the year. ROS, ROA and ROE are among the main indicators that measure the profitability of companies. In fact, ROS expresses the operating profitability deriving from the sales, ROA the operating profitability deriving from total assets and ROE the net profitability of the company. These profitability ratios have been chosen, because they provide a general and summary picture of the company's profitability, proceeding from the particular with ROS to the general with ROE. The used sample includes only the companies of which all the data of the aforementioned indices have been available for 2014, after liberalization and after a certain number of years from the complete opening of the energy market on the demand side. Therefore, the sample is made up of 270 companies. Subsequently, different groups have been identified using the size of the companies as a discriminating factor. The size has been identified by means of the volume of turnover, the balance sheet total and the number of employees. The used values of the aforementioned parameters are those specified in Recommendation 2003/361/EC implemented in Italy by decree of the Ministry of Production Activities of 18/04/2005 (Fig. 5). The attention has been focused on the number of employees as main factor. When that factor is on the limit value reported by the European recommendation the other factors have been used to classify the type of firm. The number of groups identified is 27.78% for large companies, 23.33% for medium-sized companies, 35.18% for small businesses and
Fig. 6. Distribution of enterprises for size. Source: our elaboration.
13.70 for micro-enterprises (Fig. 6). 4.2. Method Data in 2014 for each ratio and group have been analyzed by means of histograms. Then a descriptive statistics analysis have been used distinguishing between big companies and SMEs and then in relation to each identified typology of enterprises. That year has been chosen as the year of analysis, since it is about 10 years since the complete opening on the demand side of the gas market in Italy and about 7 years from that of the electricity market. In this way, this year can be a useful benchmark for evaluating the financial performance of the various types of the Italian energy companies. An analysis of the literature about the characteristics of SMEs has been carried out. The related papers have been searched in the database Web of Science for the period 2016–2017. The keywords used have been: SME, small firms, medium-sized firms; the snowball technique has been also performed. Then, a desk and an in-deep analysis of the selected papers has been done. In this ways, the papers have been chosen and grouped on the bases of the specific characteristics of SMEs that they suggest. Thus, conclusions have been derived on the H2 hypothesis. Then, the analysis is been extended to the values reported by the analyzed indices in the period 2012–2014. In fact, ANOVA (one-way) has been performed for all energy sale companies to test the H3 hypothesis. ANOVA (one-way) has been chosen, as this type of analysis allows testing whether three or more groups are different (Saunders et al., 2009). In fact, the companies have been distinguished using the number of employees. In this way, 4 different dimensions have been identified. Hence, the main assumption of ANOVA according to which the value of each data must be independent is satisfied (Hays, 1994; Dancey and Reidy, 2008; Saunders et al., 2009). Moreover, the two further assumptions according to which the data in each group are normally distributed and they must have the same variance are negligible, since each group analyzed consists of a fairly large number of cases (Saunders et al., 2009). The main advantages of ANOVA (one-way) are the simplicity of the method and the possibility of verifying the existence of any differences when the number of groups analyzed is greater than 2. In this case, this method has greater statistical validity, since it allows verifying if the differences are statistically significant. The main limitation of the ANOVA (oneway) is that it does not indicate which samples are significantly different from each other and which are not and does not allow verifying the effects of regression towards the mean. 5. Results and discussion 5.1. Descriptive analysis The quick ratio or acid test ratio is a liquidity ratio that measures the ability of a company to pay its current liabilities using only liquid assets. Quick ratio is different from current ratio because it excludes inventory. Thus, this ratio expresses the immediate liquidity of a company. An its just value is equal to 1. However, a higher level, but
Fig. 5. The European main factors determining whether an enterprise is a SME. Source: Recommendation 2003/361/EC. 435
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within 2, ensures the company a greater ability to respond to any current and unexpected needs. This index shows values between 1.16 and 1.34 in the analyzed sample. The value of this index is 1.16 in large companies. Therefore, these companies record the value, among those detected, closer to that of equilibrium, in the analyzed year. In this way, the liquid assets are present in these companies for an amount almost exactly equal to that of current liabilities. Therefore, large companies are able to cope with their current means to their short-term commitments. With regard to this index, the SMEs, on the whole, and also analyzing the single types report higher values than large companies. In fact, these values are 1.33 for medium-sized, 1.19 for small and 1.34 for micro, and 1.26 for the whole. Therefore, these values show greater liquidity for SMEs compared to large companies. In fact, in the year analyzed the SMEs have the possibility of being able to count on liquid assets that exceed current liabilities. In this way, these companies have a certain positive margin that will allow them to cope also with unexpected commitments to third parties that may arise unexpectedly in the very short term and in the short term. The debt to equity ratio (debt/equity) is a type of leverage ratio and indicates that a portion of assets financing is being done through debt. A higher debt to equity ratio is not necessarily better than a lower one. In order to assess a company's financial structure, investors analyze other financial ratios. When cost of debts is lower than issue new shares company prefers increase debts for financing assets. A balanced value is almost equal to 1. However, the optimal value is strictly context dependent. A high level of this metric means a greater risk for the bonds deriving from the debts. However, a high debt to equity ratio also means that the company is levered. This last aspect is preferable when the company is substantially stable and with a significant cash flow. This index assumes values between 1.19 and 2.71 in the analyzed sample of companies. In fact, this index records a value of 1.22 for large companies, 1.93 for medium-sized businesses, 1.19 for small businesses and 2.71 for microenterprises. SMEs have recorded a value of 1.72 at the aggregate level. The best performance for this index is that reported by small businesses, while when considering SMEs at an aggregated level, the best result is big companies. In fact, these values are close to those of equilibrium. The debt to equity ratio is central to the analysis of the company's financial structure and also to its ability to profitably employ external sources of financing. Therefore, the higher values of this index reported by SMEs do not unequivocally indicate a worse performance than large companies. In fact, SMEs have better values for quick ratio. Thus, SMEs can rely on greater liquidity. In fact, the latter can allow them to respond in the short term to any additional requests that may have come from their lenders thus making sustainable a greater degree of debt. However, it has to be pointed out that micro businesses record a value that can be considered risky enough. In this way, the existence of these companies is called into question. The asset turnover ratio (net sales/ assets) expresses how many times as a result of sales, assets are renewed in the course of a year. It is clear that higher it is this ratio the better the situation of the company is. In fact, it does not need to use the capital of third parties to finance itself. Thus, this ratio shows efficiency of a company at employing its assets to produce revenues. The values are included between 1.20 and 2.74 in the sample. The highest values are recorded by large companies (2.74) and the lowest values by microenterprises (1.20), while both medium-sized and small businesses report appreciable values, respectively 1.96 and 1.77. The difference is reduced at the aggregate level. In fact, SMEs report an average value of 1.72 compared to 2.94 of large companies. Therefore, in the year analyzed, large companies recorded a higher value than the SMEs. This is in line with the lower indebtedness of these companies. In fact, in relation to the year analyzed, they manage to reproduce the capital invested more than once in relation to SMEs. In this way, large companies do not need to resort excessively to the capital of third parties. The following figure (Fig. 7) summarizes the financial evaluated ratios using histograms. In addition, as previously specified, three main profitability indices
Fig. 7. Financial ratios. Source: our elaboration.
have been analyzed namely ROS, ROA and ROE. ROS expresses the profitability on sales, ROA the profitability on total assets, while ROE the profitability on equity. It is evident that higher values these ratios have they express a situation of greater profitability of the company. ROS assumes values between 2.42 and 5.32. The lowest value is recorded by large enterprises, the highest is by micro-enterprises, while the medium and small companies have a value of respectively 3.15 and 2.47. Thus, in the analyzed year, SMEs are able to obtain greater results in terms of profitability on sales of large companies. The operating profitability of SMEs is higher than that of large companies. This implies that SMEs are able to obtain better results from the core business than large companies in the analyzed year. ROA assumes values between 3.91 and 6.49. In particular, it has a value of 5.97 in large companies, 6.49 in medium, 3.91 in small and 6.35 in micro-enterprises. Large companies have a slightly higher value than SMEs in average values. In fact, large companies are able to achieve from the total assets more profitability than SMEs, if we consider the average values at the aggregate level. However, analyzing the average values of the different types of SMEs, medium-sized companies and micro-enterprises obtain a profitability on the assets higher than that of large companies. This means that they are able to better exploit their assets in the selected year. Finally, large companies report higher values above the average for SMEs for ROE. In fact, these values are between 11.66 and 23.79. SMEs have a value of 20.18. Thus, large companies achieve overall profitability that is higher value than SMEs, with the exception of medium-sized enterprises (28.13). In this way, in the analyzed year, large companies have a better management, not only of the characteristic one, but also of the equity and financial ones. However, it is significant that at least medium-sized companies achieve a greater ROE than large companies. In this way, it is possible to see that at least one type of SMEs is able to reach overall profitability that is higher than that of the large companies in the selected year. The following figure (Fig. 8) is the summary of the profitability analysis. Thus, this first exploratory survey on the performance of just one year makes possible to state that even SMEs are able to obtain financial performance equal to or higher than those of large companies. In this sense, significant values are obtained for quick ratio and for ROS, if
Fig. 8. Profitability analysis. Source our elaboration. 436
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there is no substantial difference between the financial performance of energy companies in terms of size. Therefore, even smaller energy companies can achieve results similar to those ones of large companies. There is a statistically significant difference for the following indices, namely the quick ratio, ROS and ROA. In fact, the p-value for these indices is lower than 0.05. That confirms that the analyzed companies have different and specific characteristics. Instead, there is no significant difference for ROE, debt to equity ratio and asset turnover ratio. This allows to state that there are some statistically significant differences with respect to some of the analyzed indexes, because the kinds of companies are different. However, in the indices that express the overall profitability of the company such as ROE, such differences are not statistically significant. In fact, ROE constitutes the summary index to analyze the ability of a company to be adequately remunerative for investors. This index should not be considered individually, but together with other indices, and in particular together with the index that expresses the level of indebtedness of the company. The latter is highlighted by the debt to equity ratio. There are no statistically significant differences between the different types of companies also for this index. This implies that the overall profitability of the analyzed companies is sustained by a substantially similar use of the capital of third parties. In this way, they use an average leverage of the same entity to multiply the return on equity. Therefore, they are generally subject to a similar risk deriving from debt. The differences detected in some indexes relating to the core business, ROS and ROA, are filled by financial and extra operating management. To this the absence of statistically significant differences in asset turnover ratio has to be added. Therefore, all types of companies are able to obtain a similar return on the total assets as a result of sales of the core business. Therefore, the results that are obtained through ANOVA, allow to state that there are some statistically significant differences in some of the analyzed indexes, because the kinds of firms are different. However, the extremely summarized indices, ROE and those closely linked to it, i.e. the debt to equity ratio and asset turnover ratio, do not show such significant differences. Thus, hypothesis H3 is substantially verified. The types of companies are different, but SMEs are able to obtain financial performance similar to those of large companies. Moreover, as it can be seen from the exploratory analysis over a year, these performances may even be higher in some cases than those of large companies. The exploratory nature of this analysis in just one year means that there is no exact correspondence with the ANOVA results for the individual indices. However, it is consistent with ANOVA in signaling that SMEs can achieve similar financial performance to large companies, but they are diverse and specific types of companies.
Table 2 Average values for the analyzed ratios. Source: our elaboration.
Big Medium Small Micro
Quick ratio
Debt to Equity ratio
Asset turnover
ROS
ROA
ROE
1,16 1,33 1,19 1,34
1,22 1,93 1,19 2,71
2,74 1,96 1,77 1,2
2,42 3,15 2,47 5,32
5,97 6,49 3,91 6,35
23,79 28,13 18,23 11,66
Table 3 Average values for the analyzed ratios for big and SMEs firms. Source: our elaboration.
Big SME
Quick ratio
Debt to Equity ratio
Asset turnover
ROS %
ROA%
ROE%
1,16 1,26
1,22 1,72
2,74 1,72
2,42 3,23
5,97 5,21
23,79 20,18
reference is made to the synthesis analysis. In addition, the values that are assumed by the debt to equity ratio, ROA and ROE are also significant for some types of SMEs compared to large companies. Therefore, the hypothesis H1 can be considered substantially demonstrated. The data summarized in the following tables (Tables 2, 3) highlight the above statements and the best results of SMEs are shown in bold. The aforementioned analysis is also confirmed by means of a descriptive statistics analysis. It has been carried out previously in relation to the different types of companies, distinguished by size and then by comparison with the two groups, large enterprises and SMESs, as shown in the following tables (Tables 4, 5). In fact, it is possible to notice how the standard deviance assumes contained values for almost all the indices in the descriptive statistics analysis. Thus, the performance of all kind of companies is almost all around the market average.
5.2. Analysis of variance ANOVA (one-way) has been performed on all the investigated indexes to test hypothesis H3. The different ratios have been considered as dependent variables, while the sizes as an independent variable. The distinction of the dimensions has been done by referring only to the number of employees. When the relative value of this variable is placed around the limit value with a range of ± 3, the other two parameters indicated above (revenues, total assets) have been taken into consideration for the purposes of classification. As it can be seen from the values summarized in the Table 6 there is no statistically significant difference for some indices, while this difference is significant for some others. The last ones are shown in bold in the Table 6. In case the difference is not statistically significant the null hypothesis is accepted. As a result
6. Conclusion and policy implications SME energy companies may achieve the same or higher financial performances than those ones of big companies. In fact, the explorative analysis on a year suggests that the overall profitability measured by ROE is higher for medium-sized companies, while it is slightly lower if SMEs are considered as a whole also including micro businesses. This
Table 4 Analysis of descriptive statistics of the data in Table 2. Source: our elaboration.
Mean SE Median SD Variance Interval Min Max
Quick ratio
Debt to Equity ratio %
Asset turnover
ROS (%)
ROA (%)
ROE (%)
1,21 0,05 1,21 0,07071067 0,005 0,1 1,16 1,26
1,47 0,25 1,47 0,353553391 0,125 0,5 1,22 1,72
2,23 0,51 2,23 0,72124891 0,5202 1,02 1,72 2,74
2,825 0,405 2,825 0,57275649 0,32805 0,81 2,42 3,23
5,59 0,38 5,59 0,53740115 0,2888 0,76 5,21 5,97
21,985 1,805 21,985 2,5526554 6,51605 3,61 20,18 23,79
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Table 5 Analysis of descriptive statistics of the data in Table 3. Source: our elaboration.
Mean SE Median SD Variance Interval Min Max
Quick ratio
Debt to Equity %
Asset turnover
ROS %
ROA %
ROE
1,21 0,05 1,21 0,070711 0,005 0,1 1,16 1,26
1,47 0,25 1,47 0,353553 0,125 0,5 1,22 1,72
2,23 0,51 2,23 0,721249 0,5202 1,02 1,72 2,74
2,825 0,405 2,825 0,572756 0,32805 0,81 2,42 3,23
5,59 0,38 5,59 0,537401 0,2888 0,76 5,21 5,97
21,985 1,805 21,985 2,552655 6,51605 3,61 20,18 23,79
60% of the added value produced in the OECD area. The vital role of SMEs in achieving inclusive growth has become evident from the global financial crisis of 2008. SMEs are particularly important for total employment and added value created in the retail trade (OECD, 2017). It should be added that SMEs that consider sustainability in their strategic planning, realize a development that seeks a balance between resilience and growth and pursues the creation of economic, social and environmental value, and preserves the wealth for new generations (Giddings and O’Brien, 2002; Moore and Manring, 2009). Thus, the positive performances of the energy SMEs and a greater intervention of the policy makers help to create a climate of trust in the banking and financial system towards energy SMEs. In this way, a virtuous circle will be triggered with an incentive to invest through a lowering of the charged interest rates. The immediate consequence of these financial policies will be a reduction in financial burdens for the SMEs, which have a high weight from the empirical verification. All this will lead to a further improvement in the financial performance of energy SMEs and a greater convenience in investing in such companies. The analysis carried out in this paper provides the identification of the particular characteristics of SME enterprises on which to focus the attention in order to obtain performances similar or higher than those ones of large enterprises. Thus, the sector will be able to improve both on the demand side and on the supply side through the entry of new operators, even of limited size. Therefore, these operators can also make nonsubstantial investments to enter into the market. All this will allow an increase in competition, the priority of liberalization of energy sector, a more broad choice among different suppliers, reduction of prices and an improvement of service quality. The descriptive statistics analysis and ANOVA confirm mainly that there are no significant differences in the performances of companies. This paper is not without limitations. First, the analysis has been carried out on the values of the indices of just one year and only some indices have been considered among the possible ones. Then, only companies existing in 2014 have been analyzed and not the results of those that disappeared from the sector in previous years. Thus, the results of the strongest companies and those ones of the most recent companies have been taken in consideration. It is evident that they have a better financial structure. Nevertheless, all available data of companies have been considered in ANOVA (one-way). Another limitation is that the analysis assesses the companies of a single country, Italy, which is also representative of the European energy situation. The analysis of further financial metrics can improve certainly the significance of the research. In fact, it can grow through a longitudinal analysis of the indices by comparing the values over several years. A further element of improvement will be achieved by carrying out a comparative analysis of the performances of energy companies in different European countries, but also the U.S. and Latin American countries, as well as South-East Asia.
Table 6 Analysis of variance. Source: our elaboration. Ratio (Dependent variable)
Dimension
F
P- value*
F crit
Quick ratio
Big Medium < 250 Small < 50 Micro < 10 Big Medium < 250 Small < 50 Micro < 10
18.14852
0.000628
4.066181
3.090179 0.089735
4.066181
3.282821 0.079425
4.066181
8.851383 0.006381
4.066181
7.896322 0.008927
4.066181
1.991724 0.193881
4.066181
Debt to equity ratio
Asset turnover ratio
ROS
ROA
ROE
Big Medium < 250 Small < 50 Micro < 10 Big Medium < 250 Small < 50 Micro < 10 Big Medium < 250 Small < 50 Micro < 10 Big Medium < 250 Small < 50 Micro < 10
* p < 0.05.
last figure highlights the trend towards the capitalization of income in small companies and the higher cost of money. Therefore, the collected data highlight a general profitability also for medium-sized companies in the energy markets. Reflecting on the financial performance arising from the size of the company provides useful policy implications. First, analysis of size of energy companies helps entrepreneurs to make the most convenient investment choices. In fact, the investments in energy companies with restricted dimensions permit entrepreneurs to limit the general firm risk. Policy makers may achieve different objectives by the definition of many kinds of incentives for energy SMEs. Administrative simplifications, contributory and fiscal incentives can make more attractive the creation of energy SMEs. In this way, policy makers can contribute to improve the production environment, obtaining positive effects both in the short term and in the long term on the economic and social system of a country. The positive effects arising from a growth in the number of energy companies on the national energy strategy cannot be ignored. Greater security, greater resilience, greater competitiveness of each country are pursued through the diffusion of energy SMEs. Indeed, SMEs are one of the main tools for job creation, economic growth and social inclusion through the star-ups and self-employment of disadvantaged and under-represented people. In this way, unemployment is combated and participation in the labor market is increased (OECD/EU, 2017). Furthermore, in 2013 the SMEs make up around 60% of the total employment and generate between 50% and
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Felicetta Iovino is Ph.D. student and expert of Business Administration and Accounting at the University of Sannio. She has a Ph.D. in Public Sector Management (2008) by the University of Salerno. She has written articles about energy companies. Guido Migliaccio is Associate Professor of Business Administration and Accounting at the University of Sannio. He has a Ph.D. in Public Sector Management (2007) and another Ph.D. in Marketing and Communication (2010) both awarded by the University of Salerno. He has written many books and articles.
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