www.jbcnet.com Internatonal Journal of Busness and Commerce Vol., No.: Jul 202[2-39] The Impact of Intellectual captal on Fnancal Reportng Qualty: An Evdence from Tehran Stock Exchange Roya Darab Assstant Professor Department of Accountng, South Tehran Branch, Islamc Azad Unversty Royadarab0@yahoo.com Tell : 009892394494 Fax : 0098288772328 Sedgheh Kamran Rad & H. Hedarbal Accountng Department, Payam Noor Unversty, Po Box, 9395-4697, Tehran, I. R. of Iran. se_kamranrad@yahoo.com alheadar@yahoo.com Acknowledgment: Ths research has been conducted as a research plan, The Impact of Intellectual Captal on Fnancal Reportng Qualty of the accepted Companes n Tehran Stock Exchange (TSE), wth the support of South Tehran Branch., Islamc Azad Unversty. Abstract Ths study nvestgates the effect of dfferent ntellectual captal components on the fnancal reportng qualty. In order to conduct ths study, a sample ncludng 84 accepted companes n Tehran Stock Exchange that work n deference ndustres between 2004 and 2009 have been selected. The methodology of the present study s co relatonal research and has an appled purpose. Co relatonal analyss and multple lnear regressons are the statstcal methods are used n ths study. The results from hypothess testng demonstrated among the dfferent components of ntellectual captal, two components of captal employed effcency and human captal effcency have sgnfcant postve effect on the dependent varable of fnancal reportng qualty and structural captal effcency has a sgnfcant negatve effect on the fnancal reportng qualty. Among these three components of ntellectual captal, the effect of human captal effcency on the fnancal reportng qualty s stronger wth than the other two factors. Key Words: Intellectual captal, Intellectual captal components, Fnancal Reportng, Fnancal Reportng Qualty, Qualty of Accruals. Publshed by Asan Socety of Busness and Commerce Research 2
www.jbcnet.com Internatonal Journal of Busness and Commerce Vol., No.: Jul 202[2-39]. Introducton Twenty frst century s the knowledge-centered economes century. In knowledge-centered economes, knowledge or ntellectual captal, gans prorty as one of the factors of wealth producton, n comparson to other physcal and tangble assets (Bonts, 998). So, as the most mportant captal knowledge has replaced fnancal and physcal captals of today's global economy. Wth the growth of knowledgecentered economes, we are consderably wtnessng the fact that n comparson wth other tangble assets, ntangble assets companes are sgnfcant factors n mantanng and accomplshng ther stable compettve advantage (Tayles et al. 2002). Therefore, nvestors and credtors are nterested n the ntellectual captal and ts components (human captal, captal employed and structural captal), thus, ther revealng plays an mportant role n decson-makngs of these two groups. By ntellectual captal, we mean the development and applcaton of sources of knowledge n the companes. Hence, n the thrd mllennum A.D., n whch ntellectual captal rather than physcal captal s the man foundaton of the future actvtes and success of the company n the knowledge-centered economes (Wllams, 2000), the ncrease of understandng and applcaton of ntellectual captal help frms to be more effcent, effectve, proft-makng and nnovatve (Chen, 2005). On the other hand, one of the most sgnfcant resources, whch the users use them to make decsons, s the group of reports called fnancal reports. Those accountng reports that are prepared and presented amng to meet the nformatonal needs of those users who are out of commercal unts, are wthn the scope of fnancal reports. Provson of fnancal reports wth ntellectual captal approach mproves the qualty of fnancal reports. The qualty of fnancal reportng, the accuracy and valdty of fnancal reports n expressng the data relevant to operatons of companes as well as declarng all the assets of companes, ncludng ntangble assets and ntellectual captal, nform the users. Accordng to the frst conceptual statement of the Fnancal Accountng Standard Board (FASB), fnancal reportng needs to "provde useful data to help potental nvestors make logcal decsons". Therefore, dsclosure of ntellectual captal n fnancal statements leads to usefulness of users' decson-makng and thus t wll be really necessary for organzatons to consder ntellectual captal. 2. Theoretcal Lterature of the Research Intellectual captal ncludes knowledge, nformaton, ntellectual asset and experence that can be used for creatng wealth. Intellectual asset refers to collectve ntellectual capablty or the key knowledge as a whole (Bonts et al. 2000). Some researchers such as Bonts (998), Roos et al. (997), Brookng (996), Stewart (998) and others had wrtten about ntellectual captal and all had reterated the mportance of ths ntangble asset. In recent decade, frms have devoted partcular attenton to measurement and dsclosure of ntellectual captal to present reports to the users. On the other hand, frms lke to enhance the qualty of the data that they present. The recent studes suggest that the ncrease n the fnancal reportng qualty whch can have mportant economc consequences (Healy and Palepo, 200; Bushman and Smth, 200; Lambert et al. 2006). The fnancal reportng qualty, accuracy and valdty of fnancal reports n expressng the data regardng frms' operatons, partcularly expected cash flows am are used to notfy the nvestors. Accordng to the Publshed by Asan Socety of Busness and Commerce Research 22
www.jbcnet.com Internatonal Journal of Busness and Commerce Vol., No.: Jul 202[2-39] frst conceptual statement of Fnancal Accountng Standard Board (FASB), fnancal reportng needs to "provde useful data to help potental nvestors make logcal decsons". Accordng to the vew suggestng that accruals mprove the nformaton value of proft by decreasng the effect of unstable nfatuatons durng cash flows, ths study uses the qualty ndex of accruals as an ndex for measurng the qualty of fnancal reportng. In addton, accruals are assessments of cash flows and future earnngs. Based on the studes conducted such as the one by Dechow & Dchev (2002), one of the factors affectng the fnancal reportng qualty s the qualty of accruals and thus the better qualty of accruals are the better the fnancal reportng qualty wll be. 2.. Background of the Study Snce no study was found to nvestgate the effect of ntellectual captal on fnancal reportng qualty, a number of studes whch have covered one aspect of the present study are presented below. Verd (2006) n an artcle ttled The Relatonshp between Fnancal Reportng Qualty and Effcency of Investment tested the relatonshp between fnancal reportng qualty and effcency of nvestment between 980 and 2003. He argued that ncrease n the fnancal reportng qualty can brng about sgnfcant economc consequences such as nvestment effcency. The results of hs study demonstrate that the qualty ndex of fnancal reportng, whch s called the qualty of accruals, s correlated wth nvestment. Chen et al. (200) have compared the qualty of accountng for the frms that are members of EU before and after acceptng nternatonal standards of fnancal reportng n 2005. Factors of smoothng, ncome management, qualty of accruals, and tmely dentfcaton of loss were consdered n order to assess accountng qualty. The researchers demonstrated that the hghest degree of accountng qualty has been related to the perod after acceptng nternatonal standards of fnancal reportng (Barth, 2007 and 2008). Rudez & Mhalc (2007) n the study ttled Investgaton of the Effect of the Components of Intellectual Captal on the Fnancal Performance of Hotel Industry dscovered that there s a sgnfcant relatonshp between the components of ntellectual captal and fnancal performance n ths ndustry and also ndcatng the great effect of captal employed effcency on the performance n comparson to other components of ntellectual captal. Ta & Chen (2009) n the study ttled The New Model of Assessment of Lngustc-Orented Intellectual Captal presented a new model to assess the performance of ntellectual captal by usng a combnaton of Fuzzy and then Tupe approaches wth a mult-varant decson makng technque whch was tested for hgh-tech frms n Tawan. The study results demonstrated the sgnfcant relatonshp between components of ntellectual captal and performance. Bramhandkar et al. (2007) nvestgated the effect of ntellectual captal on the performance of 39 pharmaceutcal frms and concluded that there s a sgnfcant relatonshp between components of ntellectual captal and performance of frms. Appuham (2007) n the study ttled The Effect of Intellectual Captal on Performance (Investors Proft), nvestgated the relatonshp between components of ntellectual captal, ncludng human captal, structural captal, and captal employed on the performance of frms n the bankng and nsurance ndustry of the country and concluded that there was a postve sgnfcant relatonshp between each sngle component of ntellectual captal and performance. Publshed by Asan Socety of Busness and Commerce Research 23
www.jbcnet.com Internatonal Journal of Busness and Commerce Vol., No.: Jul 202[2-39] Shu (2006) also nvestgated that there was a sgnfcant relatonshp between ntellectual captal and performance of 80 hgh-tech frms. Juma & McGee (2006) n ther study ndcated that there was a postve sgnfcant relatonshp between ntellectual captal and performance of hgh-tech frms n the US. Rcher et al. (2008) n ther study nvestgated that there was a sgnfcant postve relatonshp between the components of frms ntellectual captal and ther fnancal performance for the,000 bggest companes n Brazl for the perod between 2000 and 2005. 3. Methodology 3.. Statstcal communty and Sample Statstcal communty of the present study ncluded all the accepted companes n Tehran Stock Exchange between 2004 and 2009 n 6 ndustres as stated n table. Among the aforementoned ndustres, 84 frms that were workng n the under study years were nvestgated, but no samplng was performed. The number of frms for each ndustry s stated n table. (Table ) 3.2. Research Hypotheses Based on the theoretcal lterature and the conducted studes, research hypotheses were developed as follows. The present study has one prmary hypothess and three secondary hypotheses. Man hypothess: There s a sgnfcant relatonshp between the components of ntellectual captal and the fnancal reportng qualty. Secondary hypotheses: H : There s a sgnfcant relatonshp between human captal effcency and the fnancal reportng qualty. H 2 : There s a sgnfcant relatonshp between captal employed effcency and the fnancal reportng qualty. H 3: There s a sgnfcant relatonshp between structural captal effcency and the fnancal reportng qualty. 3.3. Research Methodology The research methodology s comparatve-deductve n whch theoretcal foundatons related to the study have been obtaned through lbrary studes and comparatve methods. The related data was collected through observaton of fnancal statements and the accompanyng notes as found on www.rds.com. Ths study s an expermental nvestgaton that s shown the effect of ntellectual captal components on the fnancal reportng qualty n the accepted companes n Tehran Stock Exchange n partcular ndustres. Thus, ths study has an appled purpose, based on the analyss of the data collected from Tehran Stock Exchange. On the other hand, t s a co relatonal study whch s conducted usng multple lnear regressons. 3.4. Models Used n the Study In ths study, models of Dechow and Dchev (2002) and Francs et al. (2005) were used n order to calculate the qualty ndex of fnancal statement and Pulc s (2000) Value Added Intellectual Coeffcent (VAIC) model was used n order to measure ntellectual captal, and all these models wll be further descrbed. Publshed by Asan Socety of Busness and Commerce Research 24
www.jbcnet.com Internatonal Journal of Busness and Commerce Vol., No.: Jul 202[2-39] 3.4.. Model of measurng the qualty ndex of Fnancal Statements Qualty ndex of accruals consstent wth Dechow and Dchev s (2002) model and Francs et al. (2005) model s used to measure the qualty ndex of fnancal statements. The mentoned model has been presented n the form of the equaton (): cac B B cf B cf B cf B S B PPE, t 0, t 2, t 3, t 4, t 5, t, t () Where cac s current accruals, S s Changes n the sales, CF s cash resultng from the operatonal actvtes of the frm n the years t, t, + t, PPE s book value of property, tnalp atnempuqe dn (Cost prce of property, plant and equpment mnus accumulated deprecaton) and ɛ - CAC s error of assessment of accruals. In ths model, the operatng cash flow n ths year, last year and next year s used n order to assess the qualty of accruals. Snce accruals are not assocated wth cash flows, the smaller sze of corneal devaton of accruals of workng captal s operatng cash flows, the hgher qualty accruals wll be regarded. PPE and S have been defned as the control varables for ths model. 3.4.2. The model of measurng ntellectual captal ndex Several methods are presented to measure ntellectual captals (Hunter, Webster and Wyatt, 2005). In ths study, accordng to the followng reasons, Value Added Intellectual Coeffcent model (VAIC) (Pulc, 998; Pulc, 2000) was used to measure ntellectual captals: Ths model s based on two aspects of performance and value creaton from tangble and ntangble assets of a company (Tan et al., 2007). Ths model provdes a standard and consstent measurement bass (Pulc, 998; Sveby, 200). In fact, there are lmted approaches whch can exactly measure ntellectual captal. All data used n calculatng value added ntellectual coeffcent are based on standard accountng and fnancal nformaton whch are usually lsted n fnancal reports of companes. Therefore, purposebased calculatons can be consdered and approved (Pulc, 998; Tan et al. 2007). Most ntellectual captal methods are crtczed because they measure subjectvely and cause many problems durng measurement (Sveby, 2000; Wllams, 200). Formulaton of value added ntellectual coeffcent (VAIC) s as equaton (2): VAIC CE CEE SCE Where VAIC s value added ntellectual coeffcent, HCE s human captal effcency, CEE s captal employed effcency, and SCE s structural captal effcency. The frst step for calculatng the components of IC ncludes HCE, CEE and SCE s calculaton of value added for frm whch s descrbed as follows: The calculaton of value added (VA ) for frm I s as equaton (3): ( 2 ) VA I DP W D T R (3) Where I s total nterest expenses, DP s deprecaton expenses, W s payroll, D s dvdends, T s corporate tax and R s profts retan for the year. Publshed by Asan Socety of Busness and Commerce Research 25
www.jbcnet.com Internatonal Journal of Busness and Commerce Vol., No.: Jul 202[2-39] Based on Pulc s (998) theores, one of the ndces of human captal effcency of a frm s the sum of expenses of payroll. Thus, human captal effcency (HCE) s obtaned n equaton (4): HCE VA = ( 4 ) HC Where HCE s human captal effcency, VA s value added for frm and HC s nvestment n Human Captal durng the t perod or total salary and wage nclude all ncentves. CEE s obtaned n equaton (5): CEE VA = (5 ) CE Where CEE s captal employed effcency and CE s book value of net assets. SCE s obtaned n equaton (6): SCE SC VA Where SCE s structural captal effcency and SC s structural captal. In order to calculate SC n the above-mentoned formula, equaton (7) s used: (6 ) SC VA C 3.5. Research Varables Ths study uses ntellectual captal as an ndependent varable. The components of ntellectual captal nclude human captal effcency (HCE), Captal employed effcency (CEE) and structural captal effcency (SCE) and t s calculated on the bass of the VAIC model. The dependent varable of ths study s the fnancal reportng qualty and the qualty ndex of accruals s used to measure the qualty ndex of fnancal reportng. (7 ) 4. Data Analyss The data related to 84 frms, that have formed our statstcal communty, n the perod between 2004 and 2009 has been analyzed n order to nvestgate the relatonshp between varables to test the hypotheses of the study. The collected data was calculated usng the Excel software and was analyzed usng SPSS 7 and E vews 6. The analyss of data n the descrptve statstcs parts started wth the calculaton of man ndexed such as mean, medan, dstrbuton ndexes of standard devaton, skewness and Kurtoss. Then, test of normalty of the ndependent varable, whch was conducted usng Kolmogorov-Smrnov Test, was nvestgated. In order to analyze the models, Pearson correlaton co-effcent and n order to analyze the merged data, combned data analyss or Panel wthout fxed effects, wth fxed effects and wth random effects was used. In order to determne the approprateness of the model wth fxed effect model and random effect model, Hasman Test was used. Publshed by Asan Socety of Busness and Commerce Research 26
www.jbcnet.com Internatonal Journal of Busness and Commerce Vol., No.: Jul 202[2-39] 4.. Descrptve Statstcs In the descrptve statstcs part, analyss of the data has been done use the man ndces of average, medan, dstrbuton factors, standard devaton, skewness and kurtoss. The skewness and kurtoss of FRQ, HCE, and SCE s to the rght, skewness of CEE s to the left and skewness of LnFRQ s about 0 and s almost symmetrcal. The kurtoss of all varables except LnFRQ s hgher than normal dstrbuton (table 2). 5. Research Tests 5.. Normalty Test In order to nvestgate the normalty of the dependent varable, the null hypothess and the alternatve hypotheses n the study are wrtten as follows: 0 : : For the dependent varable, the data show normal dstrbuton. For the dependent varable, the data show un normal dstrbuton. Table 3 depcts the normalty state of the dstrbuton of the values of the dependent varable.(table 3) The meanngful level for FRQ s lower than 5% n all years, thus FRQ does not have normal dstrbuton. However, the level of meanngfulness for the logarthm varable of FRQ s hgher than 0.05% n all years, thus logarthm of FRQ has normal dstrbuton. 5.2. Process of Selectng the Best Model In Panel analyss, one of the most fundamental ssues s determnng the ntercept and determnng f the fttng should be for the model wthout ntercept (prevous model) or for the model wth ntercept. When the model has ntercept, the next queston s whether a model wth fxed effects s more proper or a model wth random effects. Therefore, the process for selectng the model s as follows:. The model wthout fxed effects (merged data) has been ftted. 2. The model wth fxed effects has been ftted and ths model has been analyzed n comparson to the model wthout effects, usng Chaw Test. 3. The model wth random effects has been ftted and t has been compared to the model wthout fxed effects usng Hasman Test. At the end, among the three models, the most proper wll be selected and the sgnfcance of each of the dependent varables wll be dscussed (See the Appendx). 5.3. Testng the Prmary Hypothess Wth regard to the abovementoned ssues and the nvestgaton, the model wth random effects was selected as the most proper model for fttng and the results ganed from use of ths model as follows: Man Hypotheses: There s a sgnfcant relatonshp between the components of ntellectual captal and the fnancal reportng qualty. The regresson model used for the prmary hypothess of the research can be stated as equaton (8): Publshed by Asan Socety of Busness and Commerce Research 27
www.jbcnet.com Internatonal Journal of Busness and Commerce Vol., No.: Jul 202[2-39] Ln ( FRQ ) CEE CE SCE (8) t 0 t 2 t 3 t t Where FRQ s dependent varable of fnancal reportng qualty, CEE s latpac employed effcency, HCE s latpac namuh effcency and SCE s latpac larutcurts effcency. Null hypothess and the alternatve hypothess for the meanngfulness of the model are as follows: 0 : : 0 2 3 0,2,3 0 : : Table 4 There s no sgnfcant model. There s a sgnfcant model. Probablty value of F s 0.000 and s lower than 0.05, thus the null hypothess s rejected wth 95% certanty and there s a sgnfcant model. Value of coeffcent of determnaton s 0.079 whch ndcates that dependent varables have strong and sgnfcant effect on the dependent varable. Durbn-Watson test of ths model shows that the observatons are ndependent of one another snce test statstc s.73 and s located between.5 2.5. T value for CEE s.67 and t s sgnfcant at the level of 90%. T value for HCE s 3.54 and t s -4.9 for SCE, thus HCE and CSE are sgnfcant at the level of 95%. The results ganed from the study ndcate that the two ndependent varables of captal employed effcency and human captal effcency have postve effect on the dependent varable of fnancal reportng qualty, whle the effect of the ndependent varable of structural captal effcency on the dependent varable s negatve. Therefore the fnal model of ths study can be defned as equaton (9): Ln ( FRQ ) 3 / 95 0 / 06 CEE 0 / 0 HCE 0 / 028 SCE t t t t 5.4. Testng the Secondary hypotheses Frst secondary hypothess: H There s a sgnfcant relatonshp between captal employed effcency and the fnancal reportng qualty. The regresson model used for the frst hypothess s presented n the form of equaton (0): Ln ( FRQ ) CEE t 0 t Second secondary hypothess: H 2 There s a sgnfcant relatonshp between human captal effcency and the fnancal reportng qualty. The regresson model used for the second hypothess s presented n the form of equaton (): Ln ( FRQ ) CE t 0 t Thrd secondary hypothess: H 3 There s a sgnfcant relatonshp between structural captal effcency and the fnancal reportng qualty. The regresson model used for the thrd hypothess s presented n the form of equaton (2): (9 ) (0 ) ( ) Ln ( FRQ ) SCE t 0 t (2 ) Publshed by Asan Socety of Busness and Commerce Research 28
www.jbcnet.com Internatonal Journal of Busness and Commerce Vol., No.: Jul 202[2-39] Table 5 depcts the test of the secondary hypotheses of the study. (Table 5) As t can be seen n table 5, the probablty values of Hasman test for the models of frst and second secondary hypothess are and for the thrd model s 0.638 snce ths value s not lower that 0.05, as for the prmary hypothess, use of a model wth random effects has prorty over other models. Therefore, the models presented wth random effects are as follows: 5.4.. Frst Model (frst secondary hypothess) The probablty value of F for captal employed effcency s 0.057 and snce ths value s not lower than 0.05, therefore the varable s not sgnfcant at the level of 95%, but t s sgnfcant wth 90% certanty. Coeffcent of determnaton of the model s 0.0 and t ndcates that the ndependent varable of CEE, on ts own, does not have a strong and sgnfcant effect on the dependent varable. Durbn-Watson of ths model ndcates that the observatons are ndependent of one another as ts value s.73 and s located between.5-2.5. The model of effectveness of the ndependent varable of captal employed effcency on the dependent varable s as stated n equaton (3): Ln ( FRQ ) 3 / 22 0 / 08 CEE (3 ) 5.4.2. Second Model (second supplementary varable) The probablty value of F for human captal effcency s 0.000 and snce ths value s lower than 0.05, therefore the varable s sgnfcant at the level of 95%. Coeffcent of determnaton of the model s 0.08 and t ndcates that the ndependent varable of HCE, on ts own, does not have a strong and sgnfcant effect on the dependent varable of the study. Durbn-Watson test of ths model s.72 and ths ndcates that the observatons are ndependent of one another. The model of effectveness of the ndependent varable of human captal effcency on the dependent varable s as stated n equaton (4): Ln ( FRQ ) 3 / 9 0 / 0 HCE 5.4.3. Thrd Model (thrd Secondary hypothess) The probablty value of F for structural captal s 0.002 and snce ths value s lower than 0.05, therefore the varable s sgnfcant at the level of 95%. Coeffcent of determnaton of the model s 0.0 and t ndcates that as for the other two ndependent varables, the ndependent varable of SCE, on ts own, does not have a strong and sgnfcant effect on the dependent varable of the study. Durbn-Watson test of ths model s.72 and ths ndcates that the observatons are ndependent of one another. The model of effectveness of the ndependent varable of structural captal effcency on the dependent varable s as stated n equaton (5): (4 ) Ln ( FRQ ) 3 / 26 0 / 027 SCE (5 ) Publshed by Asan Socety of Busness and Commerce Research 29
www.jbcnet.com Internatonal Journal of Busness and Commerce Vol., No.: Jul 202[2-39] 5.5. Investgatng the co relatonal coeffcent between varables: In order to prove the lnear relatonshp between two varables, Pearson co relaton coeffcent s used. The correlaton of the varables, n the form of null hypothess and the alternatve hypothess, s as follows: 0 : : XY XY 0 0 Pearson Correlaton matrx for nvestgatng the relatonshp between varables s calculated n table 6 and the man results are: (Table 6) As t can be seen n table 6, the correlaton between the dependent varable of fnancal reportng qualty (LnFRQ) and the captal employed effcency (CEE) s 0.085 and the correlaton between LnFRQ and human captal effcency (HCE) s 0.363, that both are sgnfcant. However, the correlaton between dependent varable and structural captal effcency (SCE) s 0.044 whch s not sgnfcant. 6. Dscusson and Concluson Frst ths study collect data requred to calculated of the dfferent components of ntellectual captal (IC), that s Captal employed effcency (CEE), human captal effcency (HCE) and structural captal effcency (SCE) as the ndependent varable, as well as the fnancal reportng qualty (FRQ) as the dependent varable for 84 accepted companes n Tehran Stock Exchange and work n chemcal and pharmaceutcal ndustres, other non-metal mnerals, cement, lme, plaster, tles and ceramcs, rubber and plastc, food and drnk productons, sugar and sugar cubes, ol, products of ol refnery and nuclear fuels for a 6-year-perod between 2004 and 2009 from audted fnancal statements of the companes and ther accompanyng notes. Second the varables used n the study were calculated usng Excel software. Eventually the sgnfcant relatonshp between ntellectual captal and fnancal reportng qualty for the companes under study was analyzed usng SPSS and E vews software. Results of the study are shown as follows: - Among the dfferent components of ntellectual captal as the ndependent varable, the effect of captal employed effcency (CEE) on the dependent varable of fnancal reportng qualty (FRQ) s postve and sgnfcant. - Among the dfferent components of ntellectual captal as the ndependent varable, the effect of human captal effcency (HCE) on the dependent varable of fnancal reportng qualty (FRQ) s postve and sgnfcant. - Among the dfferent components of ntellectual captal as the ndependent varable, the effect of structural captal effcency (SCE) on the dependent varable of fnancal reportng qualty (FRQ) s negatve and sgnfcant. - Among the three components of ntellectual captal, the effect of human captal effcency (HCE) on the fnancal reportng qualty (FRQ) s by far stronger than the other two factors. Publshed by Asan Socety of Busness and Commerce Research 30
www.jbcnet.com Internatonal Journal of Busness and Commerce Vol., No.: Jul 202[2-39] Based on the results of the present study and accordng to the sgnfcant effect of the components of ntellectual captal as one ntangble asset on the fnancal reportng qualty and snce based on the frst statement of concept of the fnancal accountng standard board (FASB), fnancal reportng needs to "provde useful data so to help potental nvestors n ther logcal decson-makngs", dsclosure of ntellectual captal n fnancal statements wll lead to the usefulness of decson-makngs of the users and thus the sgnfcance of proper dsclosure of ntellectual captal n fnancal reports of frms s more evdent n order to contrbute to ther accomplshng of goals. References Appuham, B., and Ranjth, A. (2007). The Impact of Intellectual Captal on Investors Captal Gans on Shares: An Emprcal Investgaton of Tha Bankng, Fnance & Insurance Sector. Internatonal Management Revew, 3(2), 4-25. Barth, M., and Landsam, W., and Lang, M. (2008). Internatonal Accountng Standards and Accountng Qualty. Journal of Accountng Research, 46(3), 467-498. Barth, M., & Landsman, W., Lang, M. and Wllams, C. (2007). Accountng qualty: Internatonal Accountng Standards and US GAAP. Workng paper (Stanford Unversty and Unversty of North Carolna), (November). Bonts, N. 998. Intellectual Captal: An Exploratory Study That Develops Measures and Models. Management Decson, 36(2), 63-76. Bonts, N., Chua, W. and Rchardson, S. (2000). Intellectual Captal and the Nature of Busness n Malaysa. Journal of Intellectual Captal, (), 85-00. Brookng, A. (996). Intellectual Captal: Core Asset for the Thrd Mllennum Enterprse, Internatonal Thomson Busness Press, New York. Bramhandkar, A., and Erckson, S. and Applebee, I. (2007). Intellectual Captal and Organzatonal Performance: an Emprcal Study of the Pharmaceutcal Industry. the Electronc Journal of Knowledge Management, 5(4), 357-362. Bushman, R., and Smth, A. J. (200). Fnancal Accountng Informaton and Corporate Governance. Journal of Accountng and Economcs, 32 (Aprl), 237-333. Chen, H., and Tang, Q.,& Jang, Y.,& Ln, Z. ( 200). the Role of Internatonal Fnancal Reportng Standards And Accountng Qualty: Evdence from the European Unon. Journal of Internatonal Fnancal Management & Accountng, 2(3), 220-278. Chen, M-C. and Cheng, S-J. and Hwang, Y. (2005). An Emprcal Investgaton of the Relatonshp between Intellectual Captal and Frms Market Value and Fnancal Performance. Journal of Intellectual captal, 6(2), 59-76. Chen, P. (2005). Intellectual Captal Performance of Commercal Banks n Malaysa. Journal of Intellectual Captal, 6(3), 385-396. Dechow, P.M., and Dchev, I.D. (2002). the Qualty of Accruals and Earnng: The Role of Accrual Estmaton Errors. the Accountng Revew, 77(), 35-59. Francs, J., and LaFond, R.,& Olsson, P., and Schpper, K. (2005). the Market Prcng of Accruals Qualty. Journal of Accountng and Economcs, 39(2), 295-327. Hunter, L., and Webster, E., and Wyatt, A. (2005). Measurng Intangble Captal: A revew of current Practce. Australan Accountng Revew, 5(36), 4-2. Publshed by Asan Socety of Busness and Commerce Research 3
www.jbcnet.com Internatonal Journal of Busness and Commerce Vol., No.: Jul 202[2-39] Healy, P., and Palepu, K. (200). Informaton Asymmetry, Corporate Dsclosure, and the Captal Markets: A Revew of the Emprcal Dsclosure Lterature. Journal of Accountng & Economcs, 3(-3), 405 440. Juma, N., and McGee, J. (2006). the Relatonshp between Intellectual Captal and New Venture Performance: An Emprcal Investgaton of the Moderatng Role of the Envronment. Internatonal Journal of Innovaton and Technology Management, 3(4), 379-405. Lambert, R., and Lenz, CH., and Verreccha, R. E. (2006). Accountng Informaton Dsclosure & the Cost of Captal. Journal of Accountng Research, 45(2), 385-420. Pulc, A. (998). Measurng the Performance of Intellectual Potental n the Knowledge Economy. Avalable onlne: http://www.measurng-p.at/opapers/pulc/ Vactxt /vactxt.html. Pulc, A. (2000). VAICTM- An Accountng Tool for IC Management. Internatonal Journal of Technology Management, 20(58), 702-74. Rcher, F.L., and Cruz Basso, L. F., and Leva Martn, D. De. (2008). Intellectual Captal and the Creaton of Value n Brazlan Companes. Electronc copy avalable at: http:// ssrn.com. (January): -22. Roos, J., and Roos, G.,& Dragonett, N. C., and Edvnsson, L. (997). ntellectual Captal: Navgatng the New Busness Landscape. Macmllan, New York, NY. Rudez, H. N., and Mhalc, T. (2007). Intellectual Captal n the Hotel Industry: A Case Study from Slovena. Internatonal Journal of Hosptalty Management, 26(),88-99. Shu, H. (2006). Applcaton of the VAIC Method to Measures of Corporate Performance: A Quntle Regresson Approach. The Journal of Amercan Academy of Busness, 8(2), 56-60. Stewart, T.A. (998). Intellectual Captal: The New Wealth of Organzatons. Performance Improvement, 37(7), 56 59. Sveby, K.E. ( 2000). Intellectual Captal and Knowledge Management'. Avalable onlne: http:// www. Sveby.com.au/book contents.html, accessed: (May). Sveby, K.E. (200). A Knowledge-Based Theory of the Frm to Gude n Strategy Formulaton. Journal of Intellectual Captal, 2(4), 344-358. Ta, W-S., and Chen, C-T. (2009). A New Evaluaton Model for Intellectual Captal Based on Computng wth Lngustc Varable. Expert Systems wth Applcatons, 36(2): 3483-3488. Tan, H.P., Plowman, D., and Hancock, P. (2007). Intellectual Captal and Fnancal Returns of Companes. Journal of Intellectual Captal, 8(), 76-95. Tayles, M., and Bramley, A.,& Adshead, N., and Farr, J. (2002). Dealng wth the Management of Intellectual Captal : The Potental Role of Strategc Management Accountng. Accountng, Audtng & Accountablty Journal, 5(2), 25-267. Verd, R.(2006). Fnancal Reportng Qualty and Investment Effcency. Workng Paper (Massachusetts Insttute of Technology (MIT), (September). Wllams, S. Mtchel. (2000). Is Company s Intellectual Captal Performance and Intellectual Captal Dsclosure Practces Related? Evdence from Publcly Lsted Companes from the FTSE 000. Workng Paper (Presented at McMasters Intellectual Captal Conference, Hamlton Ontaro). Wllams, M. (200). Is Intellectual Captal Performance and Dsclosure Practce Related?. Journal of Intellectual Captal, 2(3), 92-203. Publshed by Asan Socety of Busness and Commerce Research 32
www.jbcnet.com Internatonal Journal of Busness and Commerce Vol., No.: Jul 202[2-39] Table Lst of under study ndustres meti yrtsudni Sub-ndustres Other non-metallc mneral products, Non-metal mnerals glass, cement, lme, plaster, tles and ceramc chemcal and 2 pharmaceutcall 3 Ol food products except 4 sugar and sugar cubes 5 sugar and sugar cubes 6 rubber and plastc latot chemcal and pharmaceutcal products Coke products, products from ol refnery and nuclear fuel food products sugar and sugar cubes products rubber and plastc products rebmun 6 56 5 32 7 3 84 Table 2 Descrptve statstcs of the research varables elbarav egareva nadem dradnats notaved ssenweks ssotruk CEE /74 /40 /49-2/278 28/468 HCE 5/027 3/44 0/657 4/593 29/29 SCE 0/700 0/726 0/824 3/272 4/79 FRQ 64507 2040 50400 5/89 42/6 Ln FRQ 3/247 3/00 0/792 /028 /273 Publshed by Asan Socety of Busness and Commerce Research 33
www.jbcnet.com Internatonal Journal of Busness and Commerce Vol., No.: Jul 202[2-39] Table 3 Kolmogorov -Smrnov Test elbarav raey rebmun Z value of Kolmogorov- Smrnov Test ytlbaborp seulav FRQ 83 84 3/946 84 84 4/30 85 83 4/05 86 84 4/468 87 84 4/29 88 84 3/726 LnFRQ 83 84 /29 0/03 84 83 /049 0/22 85 82 /349 0/053 86 83 /33 0/058 87 83 /54 0/39 88 84 /36 0/5 Varables Fxed value CEE HCE SCE Table 4 Analyss of the panel data wth random effect Estmated T Coeffcent of F Durbn Watson value value determnaton value Test 3/95 57/535 0/06 /67 0/079 /730 0/00 3/542-0/028-4/87 Probablty of Hasman Test /000 Publshed by Asan Socety of Busness and Commerce Research 34
www.jbcnet.com Internatonal Journal of Busness and Commerce Vol., No.: Jul 202[2-39] Table 5 Assessment of the co-effcent for the smple lnear models varables Fxed value CEE Fxed value HCE assessed value 3/222 0/08 3/94 0/00 T value 5/764 /908 56/567 3/565 Fxed 3/263 50/90 value SCE -0/027-3/90 coeffcent of determnaton 0/00 0/080 0/00 F value 0/057 0/002 Durbn Watson value /73 /72 /72 probablty of Hasman Test /000 /000 0/638 Table 6 Pearson correlaton coeffcent LnFRQ CEE HCE SCE Correlaton coeffcent 0/085** 0/363** 0/044 Level of sgnfcance 0/005 0/43 number 096 099 099 Publshed by Asan Socety of Busness and Commerce Research 35
www.jbcnet.com Internatonal Journal of Busness and Commerce Vol., No.: Jul 202[2-39] Appendx Indenton n the paper selecton process was the best model to acheve the best ft model for study models, dfferent models were studed. Accordng to the results, the model wth random effects was chosen as a sutable model and ts results were presented n the man text. Here other models are used n ths research and ther results are presented as follows:. The models used n ths research. Model wthout fxed effects and random effects In ths secton, panel analyss s used for the analyss and estmaton of general model. Due to the nature of the data, ths knd of method s used because n panel analyss, cross-sectonal tme data are collected. In the way that data are collected, ndependence of observatons cannot be mantaned because there are several vews of each company n dfferent years that these observatons are nterdependent. In other words, n ths analyss, the numbers of data nclude the number of frms multpled by the number of years. The estmated model s as equaton (): () Ln ( FRQ ) CEE CE SCE t 0 t 2 t 3 t t The null hypothess and the alternatve hypotheses for sgnfcance of model are wrtten as follows: 0 : 2 0 : 0,2,3 3 Panel analyss s gven n table : Table Data ntegraton analyss Varables Estmated value T value Fxed value 3/052 49/42 CEE 0/037 2/977 HCE 0/027 3/350 SCE 0/023 /39 0 : There s no sgnfcant model : There s sgnfcant model Coeffcent of determnaton F value 0/38 Durbn Watson Test /720 Probablty value of F s 0.000 and s lower than 0.05, so the null hypothess s rejected wth 95% certanty and there s a sgnfcant model. Value of coeffcent of determnaton s 0/38. T value for CEE s 2.98, for HCE s 3/35 and t s /39 for SCE. Thus, only two ndependent varables of human captal effcency and captal employed effcency are sgnfcant at the level of 95% and the effects of both varables are postve. Durbn-Watson test of ths model shows that the observatons are ndependent of one another snce test statstc s /72 and s located between /5 2/5..2 Model wth fxed effects In ths secton, model wth fxed effects s estmated that offered as equaton (2): Ln ( FRQ ) SCE (2) t CEE CE 0 t 2 t 3 t t Publshed by Asan Socety of Busness and Commerce Research 36
www.jbcnet.com Internatonal Journal of Busness and Commerce Vol., No.: Jul 202[2-39] Table 2 Analyss of data ntegraton - fxed effects Varables Fxed value CEE HCE Estmated value 3/29 0/06 0/006 T value 267/48 /904 2/880 Coeffcent of determnaton 0/870 F value Durbn-Watson Test /730 Probablty of Chaw Test 0/00 SCE -0/030-3/272 Probablty value of F s 0.000 and s lower than 0.05, so the null hypothess s rejected wth 95% certanty and there s a sgnfcant model. Value of coeffcent of determnaton s 0/87. T value for CEE s /904 (sgnfcant at the level of 90%), for HCE s 2/88 and t s -3/272 for SCE and thus the two ndependent varables of human captal effcency and latpac larutcurts effcency are sgnfcant at the level of 95%. The effects of two ndependent varables of captal employed effcency and human captal effcency s postve and the effect of ndependent varable of latpac larutcurts effcency s negatve. Durbn-Watson test of ths model shows that the observatons are ndependent of one another snce test statstc s /73 and s located between /5 2/5. The estmated model s as equaton (3): (3 ) Ln ( FRQ ) 3 / 2 0 / 06 CEE 0 / 006 HCE 0 / 03 SCE t t t t In next step to determne whether the model wth fxed effects s more approprate or the ntegrated model, Chaw test s used. In other words, Chaw test wll test the followng hypothess: 0 : : The ntegrated model s approprate The Model wth fxed effects s approprate Probablty value to determne the approprateness of model wth fxed effects s 0/00. So, the null hypothess s rejected. The rejecton of the null hypothess shows that model wth fxed effects s more approprate than ntegrated model and fnally model wth random effects compared wth model wth fxed effects that s presented n detal n the man paper. 2. Study of correlaton between varables Correlaton between varables has been nvestgated n the man paper n general. In ths secton, Pearson correlaton coeffcent s stated n table 3 to examne the relatonshp between varables for each ndustry: Table 3 - Pearson correlaton coeffcent to examne the relatonshp between varables for each ndustry Publshed by Asan Socety of Busness and Commerce Research 37
www.jbcnet.com Internatonal Journal of Busness and Commerce Vol., No.: Jul 202[2-39] Table 3 - Pearson correlaton for each ndustry Industry LnFRQ CEE HCE SCE Pearson correlaton Rubber and Plastc -.008.027 -.057 Chemcal.065.683**.086 Pharmaceutcall -.009.2**.334** Cement -.69*.239**.494** Food products.0.206** -.096 Sugar and Sugar cubes.306**.38** -.062 Tle.224.554**.062 Non-metal mnerals -.022.99*.053 Ol.435*.598** -.03 Sg. (2-taled) Rubber and Plastc.945.86.622 Chemcal.393.000.26 Pharmaceutcall.93.007.000 Cement.026.002.000 Food products.29.004.85 Sugar and Sugar cubes.002.00.544 Tle.088.000.637 Non-metal mnerals.805.022.545 Ol.06.000.87 N Rubber and Plastc 76 77 77 Chemcal 74 74 74 Pharmaceutcall 62 62 62 Cement 74 74 74 Food products 9 9 9 Sugar and Sugar cubes 98 99 99 Tle 59 60 60 Non-metal mnerals 32 32 32 Ol 30 30 30 Publshed by Asan Socety of Busness and Commerce Research 38
www.jbcnet.com Internatonal Journal of Busness and Commerce Vol., No.: Jul 202[2-39] As observed n table 3, captal employed effcency n Cement ndustry has sgnfcant negatve relatonshp wth LnFRQ (-0/7) n Sugar ndustry has sgnfcant postve relatonshp (0/3) and also n Ol ndustry has sgnfcant postve relatonshp (0/435) wth LnFRQ. In other ndustres the relatonshp between these two varables s meanngless. Human captal effcency varable n all ndustres has sgnfcant postve relatonshp wth LnFRQ. Just n Rubber & Plastc ndustry, ths relatonshp s meanngless. The hghest correlaton n Chemcal ndustry s 0/68, n Ol ndustry s 0/60 and n Tle ndustry s 0/55. Structural captal effcency n Cement and Pharmaceutcall ndustry has sgnfcant postve relatonshp wth LnFRQ respectvely 0/33 and 0/49. In other ndustres the relatonshp between these two varables s meanngless. 3. The remanng dstrbuton dagrams n contrast wth the estmated values to dentfy the consstency of the varance The remanng dstrbuton dagrams n contrast wth the estmated values s contaned mportant nformaton ncludng no regular pattern n dstrbuton of these ponts can ndcate the consstency of varance whch s one of the assumptons of regresson modelng. In the followng dagrams, ths pont s consdered and approxmately dstrbuton s random n all dagrams. Publshed by Asan Socety of Busness and Commerce Research 39