273 Organizacija, Volume 52 Issue 4, November 2019Research Papers 1 Received: July 7, 2019; revised: November 6, 2019; accepted: November 15, 2019 Analysis of Internally Generated Goodwill Indicators: A Case Study of the Slovak Republic Ivana PODHORSKA1, Lubica GAJANOVA1, Jana KLIESTIKOVA1 and Gheorghe H. POPESCU2 1University of Zilina, The Faculty of Operation and Economics of Transport and Communications, Department of Economics, Univerzitna 1, 010 26 Zilina, Slovak Republic, ivana.podhorska@fpedas.uniza.sk, lubica.gajanova@fpedas.uniza.sk, jana.kliestikova@fpedas.uniza.sk. 2Dimitrie Cantemir Christian University, Bucharest, Romania, popescu_ucdc@yahoo.com Background and purpose: Knowing key indicators of goodwill value can contribute to its effective management and growth of the market value of the enterprise. The purpose of this research is to identify individual goodwill indicators. The paper aim is to obtain potential indicators of enterprise goodwill under the conditions of the Slovak Republic. Design/Methodology/Approach: Paper data included 11,483 financial statements of Slovak enterprises in 2017. The value of residual enterprise income represents the value of goodwill. Input data for the identification of goodwill indicators represented 15 financial-economic variables. Outliers in data were searched and removed through an interquartile range. Multicollinearity among input variables, by the coefficient of determination and variance inflation factor, was also analysed. A statistically significant correlation between goodwill and its potential indicator were tested by the significance test of the Pearson correlation coefficient and correlation matrixes. Results: Research results reveal the existence of a statistically significant correlation between goodwill and 8 input variables, which represent its potential vital indicators. Conclusion: Paper findings bring new possibilities for goodwill management, which may create an essential com- petitive advantage of a company. For the scientific community, the findings represent sources of potential goodwill indicators which can be used for the creation of the new model of goodwill valuation in future research. Keywords: Goodwill; Residual income; Key indicators; Correlation DOI: 10.2478/orga-2019-0017 1 Introduction In general, goodwill has often defined as the enterprise reputation, image, right name, prestige, as well as the brand. It is reflected in the relationship between enterprise and other market participants and enterprise perception in the eyes of its customers. Traditionally, we distinguish be- tween two types of goodwill: namely, purchased goodwill and internally generated goodwill. Purchased goodwill is the difference between the value paid for an enterprise as a going concern and the sum of its assets less the sum of its liabilities, each item of which has been separately identified and valued. It appears as a result of mergers and acquisition and its valuation is regulated by IFRS 3 Busi- ness Combination. On the other hand, internally generated goodwill is an asset that can significantly contribute to the business success of companies. Its value may be very high, although it is not visible directly in the financial state- ments. It can be defined as the potential intangible asset of the enterprise and it is expected that future economic future benefits, attributable to the asset, will flow to the enterprise. Its accounting is regulated by the International Accounting Standard 38 Intangible Assets (IAS 38). Ac- 274 Organizacija, Volume 52 Issue 4, November 2019Research Papers cording to IAS 38 internally generated goodwill cannot be recognized as an asset because it does not represent enter- prise´s resource that meet all listed criteria: (i) identifica- tion; (ii) control; (iii) measurable (Stefanovic et al., 2014). Internally generated goodwill will be the main subject of interest in the paper, hereinafter referred as to “Goodwill”. Enterprise with goodwill has more satisfied and loyal cus- tomers and employees. Its suppliers are more willing to cooperate, as well as its investors are more tolerant and willing to finance business development. “Goodwill has created for years, but it can be destroyed almost every day.” (Casson, 1997). Goodwill, as an economic phenomenon has attract- ed the attention of economic experts since the nineteenth century. During years have been created various methods for its valuation and quantification. This study primary works with the residual income valuation method. The issue enterprise goodwill is an interdisciplinary question; indicators of goodwill creation can be found in financial management, economics, law, marketing, sociologist, etc. However, knowledge and understanding of enterprise goodwill indicators and valuation is still a managerial challenge. Their identification can lead to its effective cre- ation and management, and ultimately to be a powerful tool in the competitive struggle. The topicality of this issue confirms the number of pa- pers published in the database Web of Science (more than 70 papers about goodwill valuation, measurement) or da- tabase Scopus (more than 50 papers). Importance of this issue proves an amount of authors, e.g. Lord Eldon (1842), Leake (1921), Nelson (1953), Hughes (1982), Feltham and Ohlson (1995), Lonergan (1995), Canibano et al. (2000), Fernandez (2002), Curtis and Fargher (2003), Begley et al. (2006), Bean (2011), Herz (2011). Recency of this issue proves and amount of current papers, e.g. Kariuki et al. (2013), Reilly (2015), Tsai (2012), Kimbro and Xu (2016), Kliestik et al. (2018), Sadaf et al. (2019). The body of paper consist of (i) literature review of en- terprise goodwill development; (ii) methodology; (iii) re- sults; and (iv) discussion, including limitations and exten- sions for future research. Research on possible indicators of enterprise goodwill, their analysis, selection, quantifi- cation, etc. represents a complicated and time-consuming process that requires a carefully compiled data sample. 2 Literature review The enterprise goodwill has represented as an essential and interdisciplinary topic for corporate finance in the eco- nomic community since the 19th century. Over the years have been created several approaches to the definition of enterprise goodwill. The first approach was “law direc- tion” – in the beginning, goodwill described as a part of lawsuits. The second approach was “economic direction”. This approach prevails to the present day. Goodwill has attracted several scientists from various disciplines over the years. The review of selected goodwill definitions cap- tured in Table 1. Author Year Definition Lord Eldon 1842 The good-will, which has been the subject of sale is nothing more than the probability that the old customers will resort to the old place. Lord Macnaghten 1845 Goodwill is composed of a variety of elements. It differs in its composition in different trades and different businesses in the same trade. One element may preponderate here and another element here. Lord Macnaughton 1901 What is goodwill? It is a thing straightforward to describe, challenging to define. Goodwill is the benefit and advantage of the proper name, reputation, and connection of a business. Lord Justice Lindely 1901 Goodwill, as a part of company assets, does not make sense. It only makes sense if it connected with some business. It means term goodwill includes everything that adds value to enterprise from various reasons, e.g. place, reputation, image, relationships, customer´s loyalty, etc. Paton 1922 Goodwill represents intangible assets, and its value represents the difference between the total value of the enterprise and the sum of every physical enterprise assets. Goodwill represents the enterprise ability to create abnormal earnings. Yang 1927 Goodwill represents the current value of expected future earnings of an established enterprise, which the new company would not achieve. Catlett et al. 1968 Goodwill is abnormal earnings capacity. Tearney 1973 Goodwill is an item which includes many other intangible items. Table 1: Summary of selected previous research – goodwill definition 275 Organizacija, Volume 52 Issue 4, November 2019Research Papers The issue of enterprise goodwill was also discussed by the authors Vojtovic (2016); Slavik and Zagorsek (2016); Cy- gler and Sroka (2017); Siekelova (2017); Dvorsky et al. (2017); Kliestik et al. (2018); Sadaf et al. (2019). Generally, one problem is the definition and content of the term goodwill itself. On the other hand, in practice exists another problem – quantification of its value. Eco- nomic experts from all the world have suggested several possibilities of its quantification. These methods include for example the super-profits theory of goodwill described by Leake (1921); the momentum theory of goodwill de- scribed by Nelson (1953); components goodwill analyse described by Lonergan (1995) or residual income valua- tion described by Preinreich (1936). This study works with the application of the residual income valuation method to evaluate enterprise goodwill. Preinreich described residual income valuation theory in 1936. Later, renewed attention paid to the residual income, as to an economic profit (Nauroth, 2002; Emerling and Wojcik-Jurkiewicz, 2018) or abnormal earnings (Ohlson, 1995). Based on their idea of residual income was cre- ated Residual Income Valuation Models. One of them is the model, which was created by Feltham and Ohlson in 1995. In their model, they supposed that the value of the enterprise is formed by the sum of the book value of the enterprise equity and the present value of expected future residual income. It is residual income, which creates the difference between the market value of the enterprise and the book value of the enterprise. Residual income repre- sents the source of difference between the market value of the enterprise and the book value of the enterprise. Subse- quently, the value of residual income should equal to the enterprise goodwill. 3 Hypothesis The purpose of this research is to identify individual good- will indicators. The paper aim is to obtain potential indi- cators of enterprise goodwill under the conditions of the Slovak Republic. Fulfilling the prerequisite and objective of this article also entails the formulation of the primary hypothesis: H: There is not a significant relationship between individ- ual indicator and goodwill. This hypothesis is tested for all of the individual poten- tial goodwill indicators which are chosen for this research and purpose. In total is it 15 hypotheses. 4 Methodology 4.1 Enterprise goodwill valuation Residual income represents income, which enterprise cre- ated over the level of the income required by its owners. Determination of required income for owners is necessary. According to the residual income theory by Feltham and Ohlson (1995), the required income for owners is equal to the cost of equity. Disadvantages are special barriers in the process of their quantification, especially under the condition of the inefficient capital market, as well as in Slovak Republic. Quantification of residual income has the following form: Hughes 1982 The debate around goodwill was possible because even though the origin of goodwill can be determined, its nature will always be prone to interpretation. Peasnell 1982 Goodwill is the amount of value that a good corporate reputation adds to its overall value. Shenkar and Yucht- manYaar 1997 Reputation, image, prestige, and goodwill are concepts used by different disciplines, e.g., eco- nomics, marketing, sociology, and accounting, to denote the general standing of organizations among their counterparts. Arnold 1992 Goodwill is a problem that will not go away. Casson 1977 Goodwill is like a health – unappreciated wealth that everyone wants to have, but few are willing to make efforts to preserve it. Maly 2002 Goodwill represents the excellent reputation of enterprise for its business partners, financial institutions, the public and customers in domestic country and also in abroad. Zelenka 2006 Goodwill is an enterprise reputation. Bloom 2008 There is a great controversy in detecting what is goodwill and what is it composed of because it is used interdisciplinary. Goodman 2016 None of us can buy goodwill; we must earn it. Charlynne et al. 2018 Goodwill is an interdisciplinary question and intangible assets. Table 1: Summary of selected previous research – goodwill definition (continued) 276 Organizacija, Volume 52 Issue 4, November 2019Research Papers RI = NI - equity charge (1) Where RI residual income NI net income The determination of equity charge represents the key calculation of the residual income. Due to the fact, equity charge is the product of the book value of equity and its cost. This fact depicted in the following equation: equity charge = rE* BVE (2) Where rE cost of equity BVE book value of equity The cost of equity is calculated by CAMP with coun- try risk premium (CRP). According to Damodaran (http:// pages.stern.nyu.edu/~adamodar/): re= rfUSA + β* ERPUSA + CRP (3) Where rfUSA risk-free rate; yield of bonds that calculate the risk premium of the market, i.e. the yield of US 10-year government bonds according to Damodaran web- site ERP equity risk premium (Rm - rf); Rm represents S&P500 according to Damodaran website β beta for emerging markets according to Damodaran website CRP risk premium for other markets according to Da- modaran website. 4.2 Data and sample The sample for the identification of significant indicators of enterprise goodwill creation consisted of financial state- ments of Slovak enterprises in 2017. These data obtained from the Amadeus database system1 – a comprehensive European database on public and private companies; avail- able at https://amadeus.bvdinfo.com/. Relevant sample for our research of enterprise goodwill consisted of 11,483 fi- nancial statements of Slovak enterprises in 2017. Sample creation contained 2 conditions: (i) limited companies; (ii) domestic ownership. The representation of the individual Slovak regions in the sample uninformed – approximately 10% for each region. The sample also diversified to com- panies with various SK NACE classification. Thanks to these conditions were created robust data sample which can provide general results (for all regions and all sectors). Working data included 11,483 financial statements of Slo- vak enterprises in 2017. Input data for the identification of goodwill indicators represented 15 financial-economic variables. 4.3 Data analysis Paper main aim was to obtain potential indicators of enter- prise goodwill under the conditions of the Slovak Repub- lic. For their identification were used several methods in the section of the data analysis. The detection of outliers was done by interquartile range. The detection of multi- collinearity between variables (potential indicators of en- terprise goodwill) was tested by the coefficient of determi- nation and variance inflation factor. Finally, the detection of correlation between residual income and potential in- dicators of its creation was tested by correlation matrixes for all variables and the test of significance of the Pearson correlation coefficient. All statistics test was tested at the significance level α=0.05. Discriminant validity was assessed by using two meth- ods: First,(Fornell & Larcker, 1981) method. He suggest- ed that to support for discriminant validity if the square root of the AVE for a latent construct is greater than the correlation values among all the latent variables. Table (5) shows that the square root of the AVE values of all the constructs is greater than the inter-construct correlations which supports the discriminant validity of the constructs. Second, (Hair et al., 2010) he suggests if AVE for a latent construct is larger than the maximum shared variance with other latent constructs that indicates discriminant validity can be maintained Thus, the measurement model indicates a good construct validity and desirable psychometric prop- erties. 1 1 Amadeus is a database of the comparable financial and business information on Europe's largest 520,000 public and private companies by total assets. 43 countries are covered. Amadeus is published by Bureau van Dijk/Moody's Analyt- ics. Amadeus provides standardised annual accounts (consol- idated and unconsolidated), financial ratios, sectoral activities and ownership data. The database is suitable for research on competitiveness, economic integration, applied microeco- nomics, business cycles, economic geography and corporate finance. Amadeus is updated weekly, providing standardised annual accounts with up to ten years archive. EUI users can access Amadeus campus-wide via this Catalogue record (two simultaneous users). There is no off-campus access. 277 Organizacija, Volume 52 Issue 4, November 2019Research Papers 5 Results 5.1 Goodwill indicators Potential indicators of enterprise goodwill creation (ob- tained from the robust analysis of domestic and foreign scientific literature dealing with the value of enterprise and goodwill. These indicators are grouped in the three cat- egories: (i) financial-economic analysis; (ii) analysis of financial statements; and (iii) other. Category (i) includes financial ratios from enterprise liquidity, profitability, ac- tivity and indebtedness. These indicators represent the level of enterprise financial health. The causality between enterprise financial ratios and goodwill was examined by authors Curtis & Fargher, 2003 examined the causality be- tween enterprise financial ratios and goodwill; Begley et al., 2006; Maleki et al., 2010; Jakubec et al., 2011; Sponte, 2018. Category (ii) includes indicators from enterprise fi- nancial statements; they focused on intangible assets and specific cost, e.g. marketing cost. The causality between enterprise status indicators and goodwill was separately examined and recommended by authors Courtis, 1983; Kohlbeck & Warfield, 2002; Siekelova, 2017; Nica et al., 2017; Olah et al., 2019. Last category (iii) includes oth- er indicators. Finally, the following 15 variables were se- lected into this paper (Table 2); the last column represents their quantification. Table 2: Potential indicators of enterprise goodwill Variable Mark Calculation cash ratio CR (cash + cash equivalents)/current liabilities debt-equity ratio DER equity/total liabilities the turnover ratio from short- term payables TUR (short-term payables from business/costs)*365 return on equity ROE earnings after taxes/equity net income previous year NIP earnings after taxes from the previous year from the balance sheet retained earnings prior years RE retained earnings from previous year from the balance sheet valuable rights VR valuable rights from the balance sheet research and development costs* R&D research and development costs from the balance sheet marketing costs* MC (15 % * service costs from the income statement) staff training costs* SC (10% * service costs from the income statement) investments into the plant* INP (annual change from the balance sheet (brutto)) investments into the equipment* INE (annual change from the balance sheet (brutto)) investments into the property (buildings)* INB (annual change from the balance sheet (brutto)) age of enterprise AE time since the enterprise establishment to 2015 market share MS sales from operating activities/sales from operating activities in the industry *Note: necessary to take into account the time effect of the variable to the residual income (goodwill), e.g. for marketing costs assumed the effect of two years and so on. **Note: for or all variables were set up recommended values – what are the values the indicators of residual income (good- will) should achieve to be considered as potential indicators of its production. Most variables should be higher than zero, except cash ratio (<0.2-0.8>), debt-equity ratio (≥ 0.04) and turnover ratio from short-term payables (≤ 60), in accordance with (Kohlbeck & Warfield, 2002; Podolna, 2008; Bean, 2011; Rajnoha & Lesnikova, 2016; Da Silva et al., 2015; Szkutnik & Szkutnik, 2018; Valaskova et al., 2018; Fanelli & Ryden, 2018). 278 Organizacija, Volume 52 Issue 4, November 2019Research Papers 5.2 Data analysis For the identification of potential indicators of enterprise goodwill we used several methods presented in the section of the data analysis. The detection of outliers was done by interquartile range. The detection of multicollinearity between variables (potential indicators of enterprise good- will) was tested by the coefficient of determination and variance inflation factor. Finally, the detection of correla- tion between residual income and potential indicators of its creation was tested by correlation matrixes for all variables and the test of significance of the Pearson correlation coef- ficient. Table 3 (Appendix) shows the value of descriptive statistics in data. Outliers detection and missing data Detection of outliers contained searching for outliers, missing values and economic consequences. Enterprises with a negative residual income had to be removed from the database as well as enterprises with missing values and finally, outliers of individual model indicators. Table 4 (Appendix) shows the number of removed enterprises from further research. Overall, 2,478 outliers and missing data removed from the database. Finally, the database for searching for potential indicators of enterprise goodwill contained 9,005 enterprises (11,483 original data - 2,478 outliers and missing data). Multicollinearity detection Tables 5 and 6 (Appendix) show the results of the test of multicollinearity between all potential goodwill indicators. Table 5 shows the correlation matrix of all goodwill indica- tors. Finally, the values of the coefficient of determination R2 and variance inflation factor VIF were calculated based on the results of correlation and inverse matrixes (Table 6). The multicollinearity test showed that absolute mul- ticollinearity is found between the MC and SC variables (the value of R2 is equal to 1, and the value of VIF ap- proaches infinity). As in the methodology, the simplest solution is removing one of the two variables between which the dependency exists. In this research was removed variable SC - staff training costs. It was removed because it can be assumed the higher correlation between enter- prise goodwill and marketing costs. Subsequently, the test of multicollinearity was repeated. The results of the retest are shown in Tables 7 and 8 (Appendix). The second test of multicollinearity did not show the existence of multicollin- earity among any input variables. Detection of correlation Based on the results of the correlation matrixes (Appen- dix, Table 9), it may be stated the existence of direct lin- ear dependence between residual income and all potential indicators of its creation. However, the tightness of this dependency is diverse. There is a weak linear relationship between the variable residual income and variables CR, DER, TUR, VR, MC, INP, INB, EA and MS. There is a medium linear relationship between the variable residual income and variables ROE, NIP, RE and INE. Based on the results of correlation matrixes, the existence of a strong relationship of none of the input variables has not been confirmed. Table 10 (Appendix) shows a summary results of the statistical testing of significance of correlation coefficient for all input variables. This test shows whether there is or there is not a statistically significant relationship between variables, which means between residual income and po- tential indicators of its creation. Based on the data shown in the Table 10 can be noted that the value of test statistic is lower than the critical value for CR, DER, TUR, INP and AE. In accordance with the level significance α = 0.05 the null hypothesis was accept- ed, and there was not the dependence between them and residual income. For variables ROE, NIP, RE, VR, MC, INB, INE and MS was the value of test statistic higher than the critical value, at the significance level α=0.05 the null hypothesis was rejected, indicating there was the statistical significant dependence between them and residual income. These facts and results of test statistics create a ba- sis for future research in the area of the creation of an econometric model of enterprise goodwill quantification. Quantification of the dependent variable and independ- ent variables, detection of outliers and multicollinearity test are basic assumptions for regression analysis, among others. Especially, for future research and creation of an econometric model of enterprise goodwill quantification regression analysis can be used. The advantage of cor- relation matrixes results for future econometric model is confirmation of existence of potential sources of enterprise goodwill creation, represent by medium linear relationship between individual indicators and residual income. On the other hand, the disadvantage of correlation analysis is the number indicators with weak linear relationship between them and residual income. However, we can assume that these variables will be removed by regression analysis it- self. For future econometric model and regression analysis multicollinearity analysis is very important. An existence of milticollinearity between input variables could lead to incorrect results and misinterpretation. Our research high- lights potential existence of multicollinearity between variables as marketing costs, staff training costs or maybe R&D costs, it depends on basis of their calculation. In this case is necessary to consider the contribution of individual indicators to overall value of enterprise goodwill and ac- cept suitable decision about their future role in economet- ric model and goodwill creation as a whole. 279 Organizacija, Volume 52 Issue 4, November 2019Research Papers 6 Discussion Paper main aim was to obtain potential indicators of enter- prise goodwill under the conditions of the Slovak Repub- lic. Our research demonstrated the existence of a signif- icant relationship between enterprise goodwill and some ratios which can be considered as its indicators. Various authors separately examined the causality between enter- prise goodwill and financial ratios, status indicators and another ratio. Paper research showed as statistical significant good- will indicators: return on equity, net income previous years, retained earnings prior years, valuable rights, mar- keting costs, investments into the property, investments into the equipment and market share. These findings are partly consistent with the conclusion of Da Silva et al. (2015) where researched the linear correlation between the variables such as assets, equity, net income, income before a financial transaction, the consolidated profit and loss and indices such as ROE. Similarly, Tsai et al. (2012) consider investing, advertising, research and development as sig- nificant indicators of enterprise goodwill. Our research confirmed the existence of significant causality between goodwill and advertising/marketing costs. Our research brought the space for research extension. Future research may be focused on the application of the multiple linear regression analysis to these data. Where re- sidual income will represent the dependent variable and indicators/potential sources of its value will represent in- dependent variables. This test could bring the new model for goodwill valuation and prediction. This research has various limitations. It is crucial to highlight the impact of various possibilities to calculate individual variables on the final calculations. These pos- sibilities represent limitations as well as possible exten- sions of this research. The calculation of the cost of equity has a significant impact on the calculation of the value of residual income according to the Feltham-Ohlson model (1995). The cost of equity was calculated according to the capital asset pricing model (similarly to Da et al., 2012 or Feltham-Ohlson, 1995). Methods for quantification of the cost of equity represents another limitation of this research. The presented study tried to determine potential indicators of enterprise goodwill in the Slovak conditions. Therefore, the main limitations were in the selected goodwill indica- tors used as independent variables. The selection of other variables could have led to different results, which can be a subject of analysis in future studies. Prerequisite values of input variables give another significant limitation. These were specified according to the provided literature review and respecting specifics of the Slovak environment, but not so strict determination of values of indicators can pro- vide different results. The last limitation is represented by used data. The results cannot be generalized yet because of used data only from the Slovak Republic. The findings presented in this study have opened a space for a more in-depth insight into the dimensions of the goodwill evaluation in the Slovak enterprises that ab- sent in the scientific studies not only in specific conditions of Slovakia but also worldwide, particularly for its meth- odological difficulty and data limitations. The issue of en- terprise goodwill is an interdisciplinary task and manageri- al challenge. Searching for potential indicators of goodwill can lead to its effective creation and management, and ul- timately to be a powerful tool in the competitive struggle. So there was a need to found out the possible indicators of its creation in Slovak enterprises through which can help enterprise management increase its value. 7 Conclusion The market economy brings a situation where the market value of the enterprise is higher than the book value of the enterprise. This difference is known as enterprise good- will. The value of enterprise goodwill adds value to the enterprise in the market. The management of critical indi- cators of enterprise goodwill still represents a managerial challenge. Although the enterprise goodwill has represent- ed as an essential and interdisciplinary topic for corporate finance in the economic community since the 19th century, it is still a relatively unknown area. Knowing goodwill val- ue key indicators can contribute to its effective manage- ment and growth of the market value of the enterprise. Research theoretical findings bring a review of the sci- entific literature development for issue of goodwill. Subse- quently, the possibility of goodwill quantification focused on residual income valuation. Besides the theoretical implications, this study pro- vides practical implications. The purpose of this research was to identify individual goodwill indicators. The paper aim was to obtain potential indicators of enterprise good- will under the conditions of the Slovak Republic. Tested hypothesis: There is a statistically significant relationship between indicator and goodwill, confirmed the existence of a statistically significant correlation between goodwill and 8 input variables, which represent its potential key in- dicators. Research aim and purpose have fulfilled. Paper findings bring new possibilities for its manage- ment and may create an important competitive advantage. For the scientific community, the findings represent sourc- es of potential goodwill indicators which can be used for the creation of the new model of goodwill valuation in fu- ture research. Paper research brought the space for research extension. Future research may be focused on the appli- cation of the multiple linear regression analysis to these data. Where residual income will represent the dependent variable and indicators/potential sources of its value will represent independent variables. This test could bring the new model for goodwill valuation and prediction. 280 Organizacija, Volume 52 Issue 4, November 2019Research Papers Acknowledgement The research leading to these results has received funding from the project titled "Integrated model of management support for building and managing the brand value in the specific conditions of the Slovak Republic" in the frame of the program of Slovak Research and Development Agency under the grant agreement number APVV-15-0505. Literature Arnold, J. (1992). Goodwill: A Problem that will not Go Away. Trade Publication Accountancy. 109(1186), 35. Bean, A. (2011). Hunting Goodwill: Personal Good- will as Property in Corporate Acquisitions. Journal of Corporate Accounting & Finance, 23(2), 55-61. https://doi.org/10.1002/jcaf.21737 Begley, J., Chabmerlman, S. L. & Li, Y. H. (2006). 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Bankruptcy Models: Verifying Their Validity As a Predictor of Corporate 281 Organizacija, Volume 52 Issue 4, November 2019Research Papers Failure. Polish Journal of Management Studies, 18(1), 167-179. https://doi.org/10.17512/pjms.2018.18.1.13 Kliestik, T, Kovacova, M., Podhorska, I., & Kliestiko- va, J. (2018). Searching for Key Sources of Good- will Creation as New Global Managerial Challenge. Polish Journal of Management Studies, 17(1), 144- 154. https://doi.org/10.17512/pjms.2018.17.1.12 Leake, P.D. (1921). Commercial Goodwill. Its History, Value and Treatment in Accounts, London: Sir Isaac Pitman and Sons, Ltd. Lonergan, W. (1995). Goodwill and Bad Ideas; Fact and Fiction in the Amortisation Debate. Jassa, 4, 2-7. Maly, J. (2002). Intangible Goods Trade, Praha: C.H. Beck. Maleki, M. A. et al. (2010). Value Relevance of Account- ing-based Valuation Models: The Accuracy of the Ab- normal Earnings Growth and Residual Income Mod- el: Evidence from Europe. University of Amsterdam. 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The Impact of the Structur- al Funds on Competitiveness of Small and Medi- um-Sized Enterprises. Journal of Competitiveness, 8(4), 30-45. https://doi.org/10.7441/joc.2016.04.02 Yang, J. M. (1972). Goodwill and Other In- tangible Assets. Ronald Press. New York. Zelenka, V. (2006). Goodwill Principles of Com- pany Reporting. Praha: Ekopress, s.r.o. Ivana Podhorska (Ph.D.) is a university teacher at the Department of Economics, Faculty of Operation and Economics of Transport and Communications, University of Zilina (Slovak Republic). Research interests: financial management, financial-economic analysis, corporate finance. She has 17 papers in Web of Science. 282 Organizacija, Volume 52 Issue 4, November 2019Research Papers Lubica Gajanova (Ph.D.) is a university teacher at the Department of Economics, Faculty of Operation and Economics of Transport and Communications, University of Zilina (Slovak Republic). Research interests: marketing, brand, customer relationship management, corporate social responsibility, accounting. She has 32 papers in Web of Science. Jana Kliestikova (doc., Ph.D.) is a university teacher at the Department of Economics, Faculty of Operation and Economics of Transport and Communications, University of Zilina (Slovak Republic). Research interests: marketing, brand, customer relationship management, corporate social responsibility, law. She has 37 papers in Web of Science. Gheorghe H. Popescu is full professor at Dimitrie Cantemir Christian University, Bucharest. He has published more than 50 papers in peer reviewed journals indexed in ISI/Web of Science, Scopus, EconLit, ProQuest and others. He is the editor of three international peer reviewed journals: Economics, Management, and Financial Markets (since 2012), Journal of Self-Governance and Management Economics (since 2013), and American Journal of Medical Research (since 2014). Analiza interno ustvarjenih kazalnikov dobrega imena: Študija primera Slovaške republike Ozadje in namen: Poznavanje ključnih kazalnikov vrednosti dobrega imena lahko prispeva k učinkovitemu upravlja- nju dobrega imena in rasti tržne vrednosti podjetja. Namen te raziskave je prepoznati posamezne kazalnike dobrega imena. Cilj prispevka je pridobiti potencialne kazalnike dobrega imena za podjetja pod pogoji Slovaške republike. Oblikovanje / metodologija / pristop: Podatki, ki smo jih analizirali v članku so vključevali 11.483 računovodskih izkazov slovaških podjetij iz leta 2017. Vrednost preostalega dohodka podjetja predstavlja vrednost dobrega ime- na. Vhodni podatki za identifikacijo kazalnikov dobrega imena so 15 finančno-ekonomskih spremenljivk. Analizirali smo tudi multikolinearnost med vhodnimi spremenljivkami s koeficientom določitve in faktorjem inflacije. Statistično pomembna korelacija med dobrim imenom in njegovim potencialnim kazalnikom je bila preizkušena s testom značil- nosti koeficienta Pearsonove korelacije in korelacijskih matrik. Rezultati: Obstaja statistično pomembna korelacija med dobrim imenom in 8 vhodnimi spremenljivkami, ki predsta- vljajo njegove potencialne vitalne kazalnike. Zaključki: Ugotovitve iz članka prinašajo nove možnosti za upravljanje dobrega imena in lahko bistveno pripomo- rejo bistveno h konkurenčni prednosti podjetja. Za znanstveno skupnost ugotovitve predstavljajo vire potencialnih kazalcev dobrega imena, ki jih je mogoče uporabiti za oblikovanje novega modela vrednotenja dobrega imena v prihodnjih raziskavah. Ključne besede: dobro ime; preostali dohodek; ključni kazalci; korelacija. 283 Organizacija, Volume 52 Issue 4, November 2019Research Papers Appendix: List of Measurement Items Table 3: Descriptive statistic in data Mean StE Med StDev SVar Range Min Max CR 0.46 0.01 0.44 0.17 0.03 0.60 0.20 0.80 DER 1.88 0.52 0.77 13.21 174.5 329.9 0.04 329.9 TUR 20.33 0.67 16.78 16.97 287.8 59.64 0.00 59.64 ROE 0.42 0.03 0.30 0.73 0.54 15.11 0.00 15.11 NIP 59,448.2 7,656.06 8,822.75 193,078.5 3.73E+10 2,226,686.5 0.00 2,226,686,5 RE 130,151.1 24,385.3 0.00 614,975.0 3.78E+11 12,099,487 0.00 12,099,487 VR 748.28 420.53 0.00 10,605.4 1.12E+8 186,4 0.00 186,4 R&D 80.48 80.48 0.00 2,029.58 4,119,185.31 51,1 0.00 51,1 MC 32,752 4,622.7 5,945.5 116,580.3 13,590,983,369 1,957,849.9 0.23 1,957,850.1 SC 21,834 3,081.8 3,963.7 77,720.2 6,040,437,053.1 1,305,233.3 0.15 1,305,233.4 INP 178.89 61.27 0.00 1,545.09 2,387,315.9 22,393.2 0.00 22,393.2 INE 10,620,6 1,597.8 0.00 40,296 1,623,767,606.8 376,923 0.00 376,923 INB 86,310.63 12,123.1 13,280.3 305,733.9 93,473,229,651.5 4,908,964,8 0,00 4,908,964,8 AC 12.47 0.19 11.00 4.87 23.72 18.00 7.00 25.00 MS 0.01 0.00 0.00 0.07 0.01 1.00 0.00 1.00 RI 92,753.1 10,632.5 16,829.2 268,143.6 71,901,037,863.7 3,815,511.4 39.3 3,815,550.7 Source: calculation by authors Table 4: Detection of outliers and missing data Indicator Outliers and Missing data RI 1,369 CR 185 DER 35 TUR 66 ROE 209 NIP 64 RE 30 VR 78 R&D 49 MC 101 SC 2 INP 70 INE 37 INB 83 AE 6 MS 94 Total 2,478 Adjusted Sample 9,005 Source: calculation by authors 284 Organizacija, Volume 52 Issue 4, November 2019Research Papers Table 5: C orrelation m atrix Variables C R D E R T U R R O E N IP R E V R M C SC IN P IN E IN B A E M S C R 1.000 0.024 -0.068 0.051 -0.026 -0.094 -0.017 -0.093 -0.093 -0.033 -0.111 -0.099 0.004 -0.066 D E R 0.024 1.000 -0.194 -0.204 0.112 0.182 0.022 -0.092 -0.092 -0.034 -0.006 0.001 -0.006 -0.011 T U R -0.068 -0.194 1.000 0.022 0.000 0.121 0.020 0.196 0.196 -0.038 0.114 0.073 0.053 -0.021 R O E 0.051 -0.204 0.022 1.000 0.201 -0.235 0.011 0.069 0.069 -0.028 -0.116 -0.030 -0.064 -0.020 N IP -0.026 0.112 0.000 0.201 1.000 0.454 0.037 0.208 0.208 0.003 0.163 0.342 0.084 0.165 R E -0.094 0.182 0.121 -0.235 0.454 1.000 0.110 0.207 0.207 0.052 0.393 0.441 0.163 0.260 V R -0.017 0.022 0.020 0.011 0.037 0.110 1.000 0.110 0.110 -0.012 0.182 0.017 -0.017 -0.020 M C -0.093 -0.092 0.196 0.069 0.208 0.207 0.110 1.000 1.000 0.019 0.015 0.294 0.078 0.129 SC -0.093 -0.092 0.196 0.069 0.208 0.207 0.110 1.000 1.000 0.019 0.015 0.294 0.078 0.129 IN P -0.033 -0.034 -0.038 -0.028 0.003 0.052 -0.012 0.019 0.019 1.000 0.143 0.187 0.045 0.103 IN E -0.111 -0.006 0.114 -0.116 0.163 0.393 0.182 0.015 0.015 0.143 1.000 0.310 0.244 0.039 IN B -0.099 0.001 0.073 -0.030 0.342 0.441 0.017 0.294 0.294 0.187 0.310 1.000 0.168 0.215 A E 0.004 -0.006 0.053 -0.064 0.084 0.163 -0.017 0.078 0.078 0.045 0.244 0.168 1.000 -0.040 M S -0.066 -0.011 -0.021 -0.020 0.165 0.260 -0.020 0.129 0.129 0.103 0.039 0.215 -0.040 1.000 Source: calculation by authors Table 6: Test statistic of m ulticollinearity Statistic C R D E R T U R R O E N IP R E V R M C SC IN P IN E IN B A E M S R 2 0.030 0.134 0.106 0.214 0.344 0.481 0.063 1.000 1.000 0.061 0.271 0.319 0.087 0.113 V IF 1.031 1.154 1.119 1.273 1.524 1.927 1.067 - - 1.065 1.372 1.468 1.095 1.128 Source: calculation by authors 285 Organizacija, Volume 52 Issue 4, November 2019Research Papers Va ri ab le s C R D E R T U R R O E N IP R E V R M C IN P IN E IN B A E M S C R 1. 00 0 0. 02 4 -0 .0 68 0. 05 1 -0 .0 26 -0 .0 94 -0 .0 17 -0 .0 93 -0 .0 33 -0 .1 11 -0 .0 99 0. 00 4 -0 .0 66 D E R 0. 02 4 1. 00 0 -0 .1 94 -0 .2 04 0. 11 2 0. 18 2 0. 02 2 -0 .0 92 -0 .0 34 -0 .0 06 0. 00 1 -0 .0 06 -0 .0 11 T U R -0 .0 68 -0 .1 94 1. 00 0 0. 02 2 0. 00 0 0. 12 1 0. 02 0 0. 19 6 -0 .0 38 0. 11 4 0. 07 3 0. 05 3 -0 .0 21 R O E 0. 05 1 -0 .2 04 0. 02 2 1. 00 0 0. 20 1 -0 .2 35 0. 01 1 0. 06 9 -0 .0 28 -0 .1 16 -0 .0 30 -0 .0 64 -0 .0 20 N IP -0 .0 26 0. 11 2 0. 00 0 0. 20 1 1. 00 0 0. 45 4 0. 03 7 0. 20 8 0. 00 3 0. 16 3 0. 34 2 0. 08 4 0. 16 5 R E -0 .0 94 0. 18 2 0. 12 1 -0 .2 35 0. 45 4 1. 00 0 0. 11 0 0. 20 7 0. 05 2 0. 39 3 0. 44 1 0. 16 3 0. 26 0 V R -0 .0 17 0. 02 2 0. 02 0 0. 01 1 0. 03 7 0. 11 0 1. 00 0 0. 11 0 -0 .0 12 0. 18 2 0. 01 7 -0 .0 17 -0 .0 20 M C -0 .0 93 -0 .0 92 0. 19 6 0. 06 9 0. 20 8 0. 20 7 0. 11 0 1. 00 0 0. 01 9 0. 01 5 0. 29 4 0. 07 8 0. 12 9 IN P -0 .0 33 -0 .0 34 -0 .0 38 -0 .0 28 0. 00 3 0. 05 2 -0 .0 12 0. 01 9 1. 00 0 0. 14 3 0. 18 7 0. 04 5 0. 10 3 IN E -0 .1 11 -0 .0 06 0. 11 4 -0 .1 16 0. 16 3 0. 39 3 0. 18 2 0. 01 5 0. 14 3 1. 00 0 0. 31 0 0. 24 4 0. 03 9 IN B -0 .0 99 0. 00 1 0. 07 3 -0 .0 30 0. 34 2 0. 44 1 0. 01 7 0. 29 4 0. 18 7 0. 31 0 1. 00 0 0. 16 8 0. 21 5 A E 0. 00 4 -0 .0 06 0. 05 3 -0 .0 64 0. 08 4 0. 16 3 -0 .0 17 0. 07 8 0. 04 5 0. 24 4 0. 16 8 1. 00 0 -0 .0 40 M S -0 .0 66 -0 .0 11 -0 .0 21 -0 .0 20 0. 16 5 0. 26 0 -0 .0 20 0. 12 9 0. 10 3 0. 03 9 0. 21 5 -0 .0 40 1. 00 0 Ta bl e 7: A dj us te d co rr el at io n m at ri x So ur ce : c al cu la tio n by a ut ho rs St at is tic C R D E R T U R R O E N IP R E V R M C IN P IN E IN B A E M S R 2 0. 03 0 0. 13 4 0. 10 6 0. 21 4 0. 34 4 0. 48 1 0. 06 3 0. 17 7 0. 06 1 0. 27 1 0. 31 9 0. 08 7 0. 11 3 V IF 1. 03 1 1. 15 4 1. 11 9 1. 27 3 1. 52 4 1. 92 7 1. 06 7 1. 21 5 1. 06 5 1. 37 2 1. 46 8 1. 09 5 1. 12 8 Ta bl e 8: A dj us te d te st st at is tic o f m ul tic ol lin ea ri ty So ur ce : c al cu la tio n by a ut ho rs 286 Organizacija, Volume 52 Issue 4, November 2019Research Papers Table 9: Correlation matrixes Variables RI CR Variables RI DER RI 1 0.003 RI 1 0.064 CR 0.003 1 DER 0.064 1 Variables RI TUR Variables RI ROE RI 1 0.026 RI 1 0.322 TUR 0.026 1 ROE 0.322 1 Variables RI NIP Variables RI RE RI 1 0.790 RI 1 0.404 NIP 0.790 1 RE 0.404 1 Variables RI VR Variables RI MC RI 1 0.169 RI 1 0.292 VR 0.169 1 MC 0.292 1 Variables RI INP Variables RI INE RI 1 0.056 RI 1 0.170 INP 0.056 1 INE 0.170 1 Variables RI INB Variables RI AE RI 1 0.344 RI 1 0.074 INB 0.344 1 AE 0.074 1 Variables RI MS RI 1 0.128 MS 0.128 1 Source: calculation by authors 287 Organizacija, Volume 52 Issue 4, November 2019Research Papers Variable T (test statistic) Tcrit (critical value) p-value (two-tailed) alpha CR 0.054995 1.965013 0.956 0.05 DER 1.396096 1.965013 0.163 0.05 TUR 0.57502 1.965013 0.566 0.05 ROE 7.387359 1.965013 < 0.0001 0.05 NIP 27.93862 1.965013 < 0.0001 0.05 RE 9.585949 1.965013 < 0.0001 0.05 VR 3.725166 1.965013 < 0.0001 0.05 MC 6.617913 1.965013 < 0.0001 0.05 SC 1.223255 1.965013 0.222 0.05 INP 3.732676 1.965013 < 0.0001 0.05 INE 7.947842 1.965013 < 0.0001 0.05 INB 1.616102 1.965013 0.107 0.05 AE 2.811178 1.965013 < 0.0001 0.05 Table 10: The test statistic of significant correlation Source: calculation by authors