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The final sample of the study for the estimated model

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The final sample of the study for the estimatedmodel consists of 66 SMEs in the manufacturingsector. The purpose for selecting manufacturingfirms is because manufacturing mostly deals withinventory at almost every stage of production(raw-materials until finished goods) compared toother sectors. Multiple regressions method areusedtoevaluatetherelationshipbetweenworkingcapitalcomponentsandSMEsprofitability measures by using the ordinary leastsquares(OLS)regression.Themultipleregressions method was conducted by usingEViews version 8. Correlation analysis and thedescriptive statistics are analyzed using SPSSversion 20. The models run are consistence withthe models used in previous studies García-Teruel and Martínez-Solano [27], Shah and Sana[24] and Zariyawati, Annuar, Taufiq and Rahim[30],Samiloglo and Demirguneş[31].4. RESULTS AND DISCUSSIONThe descriptive statistic show the average valueof the return on asset (ROA), net operating profit(NOP) and return on equity (ROE) are 8.4%,86.6 and 6.7% respectively. This finding showsthat SMEs in Malaysia are cost effective ingenerating more profit from their operations byutilizing their total assets. Furthermore the returnto equity holders is considered to be is relativelyto be moderate. The maximum value for ROA,NOP and ROE are 54.0% and 14.93% and95.30% respectively. This indicates that SMEs inmanufacturing sector shown a higher ROE withthe maximum value of 95.30%.The SME firms receive payment from theircustomers at an average of days accountreceivables of 55.91 days. Moreover the SMEs inMalaysia tend to make earlier payment to theirsuppliersatanaverageofdaysaccountpayablesof44.35daysbeforereceivingmoney/payments from their customers. Thismaybe as a result of discount offered by thesuppliers and also SMEs do not rely much ontrade debt due to the ample initiatives andsupport from the government to finance theirbusiness operations see Table 1 for details.The regression analyses are run to see if there isa presence of autocorrelation in the data, usingDurbin Watson (DW) statistics. The scores ofthese statistical tests are accepted, implicatingthat there is no presence of autocorrelation in thedata. The athour Makridakis and Wheelwright[32] consider D-W statistics values lie between1.413 and 1.55, where a score of 2 indicate thatthere is no autocorrelation and 0 score indicatingthat there is autocorrelation. The authors Jose,Lancaster and Stevens [22] consider D-W valuebetween1.5and2.5asacceptablelevelindicating no presence of autocorrelation. Someof these scores are somewhat lower than 1.5, butsince the common rule indicate that score lowerthan 1.0 may cause alarm, these score are stillaccepted.Pearson correlation test is conducted to examinethe relationship between the dependent andindependent variables. Table 2 demonstrates thecorrelation analysis all the variables used in the

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Term
Fall
Professor
NoProfessor
Tags
Balance Sheet, Working Capital, Abdullahi Hassan Gorondutse

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