Innovative Journal of Business and Management 6 : 3,May June (2017) 38-42. Contents lists available at www.innovativejournal.in INNOVATIVE JOURNAL OF BUSINESS AND MANAGEMENT Journal homepage: http://www.innovativejournal.in/ijbm/index.php/ijbm EFFECT OF WORKING CAPITAL MANAGEMENT ON THE FINANCIAL PERFORMANCE OF MANUFACTURING FIRMS IN SULTANATE OF OMAN G. Ramesh 1, Hamad Al-Habsi 2, Tammam Al-Sharji 2 1 Department of Business Studies, Ibra College of Technology,. 2 Bachelor degree students in Accounting & Finance, Ibra College of Technology,. ARTICLE INFO Corresponding Author: G. Ramesh Department of Business Studies, Ibra College of Technology, Sultanate of Oman. drrameshg@gmail.com Keywords: Effect of Working Capital, Working capital, financial performance, Ratios, Manufacturing firms, Firms in MSM. DOI:http://dx.doi.org/10.15520/ijbm. vol6.iss3.68.pp38-42 ABSTRACT Managing working capital in a manufacturing organization is an important aspect. It measures the company ability to pay off short-term liabilities. The of working capital effects on the primary objective (earning profit) of the organization. This motivated the researchers to study the effect of Working Capital Management on the Financial Performance of Manufacturing Firms in. The study period is 10 years and data have been collected from 19 manufacturing companies listed in MSM. Mean, standard deviation, correlation and regression are used in this research to analyse the effect of working capital in the profitability among the sample firms. The study concludes that the debtor, inventory, creditor and cash conversion cycle negatively effects on the financial performance of listed manufacturing firms in over the 10 years period. 2017, IJBM, All Right Reserved 1. INTRODUCTION Financial viability is an integral part of organization s success and survival. Each and every organization strives to achieve its financial goal through various efforts and measures. The organizations financial performance have been associated and analysed with different financial parameters. Many researches have been conducted to analyze the impact on firm s financial performance by attributing with capital structure (Saeedi & Mahmoodi, 2011; Salim & Yadav, 2012), ownership structure (Demsetz & Villalonga, 2001; Cheng & Tzeng, 2011) and working capital (Juan & Martinez- Solano, 2007; Sharma & Kumar, 2011). The working capital is one of the prominent financial functions in any organization as it effects on the liquidity and profitability directly. It represents the amount of money invested by an organization to meet the day-to-day operations. The working capital is the difference between the various current assets (cash, bank balances, inventories, trade and other receivables, marketable securities etc.) and current liabilities (trade and other payables, accrued expenses, short-term payables etc.). Therefore, the efficiency of working capital is primarily evaluated through the inventory, receivables, payables and current and quick ratio. 2. LITERATURE REVIEW Polycarp & Tabitha (2016) studied the effect of working capital on the profitability of manufacturing companies listed in Kenya. They mentioned that the of working capital aims to maintain an optimal balance between each of its components. Further, the working capital is relevant to the liquidity and profitability of the firm. They studied the effect of creditor, debtor, inventory and cash on the financial performance of 10 listed manufacturing firms in Kenya by covering a period of 10 years i.e., 2005 to 2014. They found that the relationship between creditor and the financial performance of the firms was positive while it was negative in case of debtor, inventory and cash. Bagh et al (2016) examined the impact of working capital on financial performance of 50 manufacturing firms listed in Karachi stock exchange (KSE) of Pakistan. The data has been taken for 10 years i.e., 2005 to 2014. They said that the company should maintain appropriate level of working capital and it should be the chief objective of working capital. They examined the effect of various components of working capital i.e., inventory turnover (ITO), cash conversion cycle (CCC), average collection period (ACP), and average payment period (APP) on firm performance by using three different proxies i.e., return on asset (ROA), return on equity (ROE) and earning per share (EPS). Through multiple regression analysis they found that the APP, ITO and CCC have negative and significant impact on ROA but ACP has positive and significant impact on ROA. Their result advocated that the financial performance of selected firms in Pakistan was influenced by working capital. Author(s) agree that this article remain permanently open access under the terms of the Creative Commons Attribution License 4.0 International License Page 38
Mohammad (2011) investigated the effect of working capital on the financial performance of industrial firms listed in Tehran Stock Exchange in Iran. By using 6 years data from 1063 companies, he found a negative relationship between profitability and cash conversion cycle, inventory turnover in days, average collection period. On the other hand, the average payment period has positive effects in financial performance. He advocated that the improper of working capital might lead to decrease in sales and consequently the profit of the company. It may put into a situation where the firm would unable to repay its debts. A study by Sharma & Kumar (2011) was conducted to examine the effect of working capital on profitability of Indian firms listed in Bombay Stock Exchange. They have used a sample of 263 Indian companies and the study period was 2000 to 2008. They used Return on Assets (ROA) as a proxy to represent profitability. The effect of each components of working capital on ROA has been analysed through pooled linear regression individually. The researchers have used sales growth, current ratio and leverage as control variables. The result of the study shows that the inventory holding period, number of days accounts payable are negatively correlated with a firm s profitability, whereas number of days accounts receivables and cash conversion period exhibit a positive relationship among the manufacturing firms in India. Rahman & Nasr (2007) emphasized that the working capital has its effect on liquidity as well on profitability. They have chosen 94 Pakistani firms listed in Karachi Stock Exchange for a period of 6 years from 1999 2004 to measure the effect of different variables of working capital on profitability. By using, Pearson s correlation, and regression analysis (Pooled least square and general least square with cross section weight models) they identified that there is a strong negative relationship between the working capital variables (average collection period, inventory turnover in days, average payment period and cash conversion cycle) and profitability of the firm. Moreover, they found positive relationship between size of the firm and its profitability and negative relationship between amount of debt and firm profitability. Objective of the study To determine the effect of working capital on profitability of manufacturing firms in. 3. Methodology Sampling and Data As this research is intended to analyse the relationship between working capital and profitability of manufacturing company over a period of 10 years i.e., 2006 to 2015, it uses quantitative research design. It is purely based on the secondary data. As on 1 st February, 2017 there were 120 listed companies in MSM that belongs to different sectors and sub sectors. However, as this study is related to manufacturing firm, the researchers have considered the Industrial sector companies only. In this sector, 45 listed companies were there in MSM as on 1 st February, 2017. Since, studying the entire population is not possible due to various reasons, the researchers have adopted sampling technique. By considering the availability of time and resources, we have decided to choose 20 companies as sample size which comes to 44.44%. The researchers have adopted simple random sampling to select the sample companies. However, one company was excluded from the sample size as its financial performance abnormally affected the result of the entire sample. Hence, the revised sample size is 19 firms. The required annual reports of the sample manufacturing firms have been downloaded from MSM website (www.msm.gov.om). The data were collected manually from the respective annual reports. Variables Profitability or financial performance of the manufacturing firm in the sultanate of Oman is the dependent variable for this study. The different components of working capital viz., debtors, inventory, creditors and cash are considered as the independent variables. The proxy used for each variables and the formulae are presented in the following table. Variables and its proxy Variable Proxy Formulae Profitability ROA Earnings After Tax / Total Assets x 100 Debtors ACP [Debtors / Sales] * Days in a year Inventory ICP [Inventory / COGS] * Days in a year Creditor APP [Creditors / COGS] * Days in a year Cash CCC ICP + ACP APP Research Models Pooled OLS regression analysis is performed to analyse the effect of working capital on the financial performance of manufacturing firms listed in MSM. The financial performance (ROA) of the firm could be analysed through the various components of working capital. The effect of debtors (ACP), creditors (APP), inventory (ICP) and cash conversion cycle have been investigated using the following regression model. ROAit = β0 + β1app + β2acp + β3icp + β4cccit + μ Where; ROA = Return on Assets APP = Average Payment Period ACP = Average Collection Period ICP = Inventory Conversion Period CCC = Cash Conversion Cycle μ = error term of the model β1- β4 = regression model coefficients 4. Limitation The present study focuses the effect on working capital on profitability. The variables representing the working capital and profitability have been selected based on the previous studies. Hence, the effects of those representing variables alone have been studied through this research. The study uses manufacturing firm as sample industry. Therefore, the result of the study cannot be generalized to any other industry in. Further, the study is related to the listed companies in MSM in. 39 P a g e
5. Descriptive statistics Table-1: Descriptive statistics - Working Capital Ratios ACP ICP APP CCC Year N Mean % Change S.D. Mean % Change S.D. Mean % Change S.D. Mean % Change S.D. 2006 19 123.33-144.39 115.62-66.00 101.07-53.11 137.89-174.89 2007 19 105.24-14.66 110.82 100.41-13.15 51.83 87.06-13.86 44.56 118.60-13.99 136.42 2008 19 85.08-19.16 64.61 116.17 15.69 116.77 80.67-7.34 48.93 120.57 1.67 111.86 2009 19 92.77 9.04 52.83 125.48 8.02 68.60 91.35 13.24 49.87 126.90 5.25 91.49 2010 19 95.13 2.54 50.26 132.43 5.54 106.55 98.78 8.14 61.37 128.78 1.48 83.12 2011 19 99.76 4.87 60.50 125.08-5.55 127.92 97.77-1.03 52.05 127.07-1.32 97.48 2012 19 102.63 2.88 61.90 133.64 6.84 120.96 98.35 0.59 42.54 137.92 8.53 105.47 2013 19 113.98 11.05 68.21 130.45-2.39 106.60 96.67-1.71 40.57 147.75 7.13 104.23 2014 19 176.73 55.06 311.42 130.28-0.13 113.43 105.75 9.40 69.25 201.25 36.21 328.63 2015 19 182.96 3.53 322.29 134.29 3.08 134.55 107.01 1.19 102.36 210.25 4.47 348.02 Source: SPSS output - data compiled from the Annual Reports. The table presents the descriptive statistics of working capital ratios for the sample companies for the period of 10 years. The Mean value of Average Collection Period (ACP) shows that the lowest number of days could be seen as 85 days in the year 2008 and the highest was 183 days in the year 2015. The range between the highest and lowest is around 98 days. A huge increase in the ACP is observed in the years 2014 & 2015. The percentage of change in ACP was seen highest, around 55%, in the year 2014 in comparison with the base year 2006. The statistical measure of dispersion, standard deviation, shows that there is more deviation between the sample company ACP during the years 2014 & 2015. However, the variations between the years 2008 to 2013 are almost similar. The Inventory Conversion Period (ICP) of the sample companies ranges between 100 days to 134 days. The mean value shows that the ICP is almost similar between the years 2009 to2015. The percentage of change in ICP shows highest (15.62%) in the year 2008 and lowest in the year 2014 with 0.13%. The standard deviation of average ICP is less in 2007, 51.83, and more in the year 2015 with 134.55. It shows that there are significant variations in ICP among the sample companies. The Mean value of Average payment period (APP) shows the highest number of days in the year 2015 and the lowest number of days in the year 2008. The range between the highest and lowest APP found is around 27 days. The year 2014 witnessed highest percentage (9.40%) of change in APP and the lowest percentage was in the year 2007 with -13.86%.The standard deviation of APP present was highest in the year 2015 with a value of 102.36 in comparison with the base year. The mean value of average cash conversion cycle (CCC) presents that the lowest number of days was in the year 2007 which is around 118 days and the highest was 210 days in 2015. The mean value shows that the CCC is almost similar between the years 2007 to 2011.The year 2007 shows the lowest percentage of change of CCC which is around -14%. The statistical measure of dispersion, standard deviation, shows that there is less deviation between the sample companies CCC during the years 2009 & 2010. The table shows the descriptive statistics of profitability ratio for the sample companies for the period of 10 years. According to table-2, the mean value of average of Return On Assets (ROA) presents that the highest value of ROA for the manufacturing firms was 10.20 in year 2007 while the lowest value of ROA was 6.24 in the year 2012. However, the mean value shows that the range in average ROA is less over the period of study. The change of ROA shows that higher change could be seen in the years 2008, 2011 and 2013. The standard deviation of ROA presents that it was more in 2009 with 11.14 while the less deviation was 6.96 in the year 2012. Table-2: Descriptive statistics ROA Year N Mean % Change S.D. 2006 19 9.29-7.06 2007 19 10.20 9.79 7.08 2008 19 8.48-16.85 10.47 2009 19 9.04 6.65 11.14 2010 19 9.12 0.86 9.72 2011 19 6.89-24.42 8.02 2012 19 6.24-9.51 6.96 2013 19 7.85 25.89 7.37 2014 19 7.76-1.13 10.47 2015 19 7.03-9.44 7.74 Source: SPSS output - data compiled from the Annual Reports. 6. Analysis of Relationship between Profitability and Working capital ratios In this part of the project report, the relationship between profitability ratios (ROA, ROCE, NPR and EPS) and working capital ratios (ACP, ICP, APP and CCC) have been analyzed using multiple correlations. Each profitability ratios is taken as dependent variable and the four working capital ratios were taken as independent variables. The relationship between the dependent and independent variables are presented in the following tables. Table-3: Correlation Matrix between ROA and working capital variables ROA ACP ICP APP CCC RPearson 1 OA Correlation Sig. (2- APearson -.303 1 CP Correlation Sig. (2-.395 IPearson.717*.338 1 CP Correlation Sig. (2-.020.339 APearson -.462.761*.645* 1 PP Correlation Sig. (2-.178.011.044 CPearson -.438.971**.522.762* 1 CC Correlation Sig. (2-.206.000.121.010 *. Correlation is significant at the 0.05 level (2-. **. Correlation is significant at the 0.01 level (2-. H o: There is no statistically significant correlation between ROA and working capital ratios.the Pearson s correlations analysis was then conducted at 95% 40 P a g e
confidence interval and 5% confidence level 2- tailed. Results of the Pearson s correlation shows that there is a strong negative relationship between inventory and the return on assets (r= -0.717, p-value <0.05). This is consistent with the result of Knauer and Wohrmann (2013) who envisaged that inventory conversion period (or inventory ) negatively related to the financial performance. From the analysis we could see that there is also a negative relationship between ACP (r= - 0.303), APP (r=-.462) and CCC (r= -0.438). However, the p-values is >0.05 and hence, we failed to reject null hypothesis statistically. In contrast, Ganesan (2007) has shown that average payment period positively affected the profitability of the firms. 7. Regression Analysis Tests of Normality Use of inferential parametric statistical procedures requires that the assumptions of such tests of normality are tested. This is to assist the graphical tests to be performed Table-4 Tests of Normality Kolmogorov-Smirnov a about the normality of the data to check for skewness and kurtosis coefficients. These tests help to confirm whether the data follows a normal distribution or not. If the normality is not achieved, the results may not depict the true picture relationship amongst the variables. In this study, normality was tested using Kolmogorov-Smirnov Test and the Shapiro-Wilk Test. The Shapiro-Wilk Test is more appropriate for this study as the sample sizes is < 50 but can also handle sample sizes as large as 2000. For this reason, this study used the Shapiro-Wilk test as our numerical means of assessing normality. If the Sig. value of the Shapiro-Wilk Test is greater than 0.05, (P-value test statistic) the data is normal. If it is below 0.05, the data significantly deviate from a normal distribution. The table- 4.1 presents the result of normality test. The result shows that the significance value in both in Kolmogorov-Smirnov and Shapiro-Wilk tests are more than 0.05 which shows that the dependent variable is distributed normally and hence regression test could be done. Shapiro-Wilk Statistic df Sig. Statistic df Sig. ROA.152 10.200*.969 10.885 *. This is a lower bound of the true significance. a. Lilliefors Significance Correction 8. Result and Analysis In order to test the hypotheses, pooled OLS regression analysis has been conducted to determine the whether there is significant relationship between working capital and profitability. Results in following tables provide results for the models tested in the present study. In order to check the presence of autocorrelation and multicollinearity in the data, Durbin Watson (D-W) Table-5 Model Summary b Model R R Square statistics was used. The table-4 shows that the Durbin- Watson statistic is 1.800 which is between 1.5 and 2.5 and therefore the data is not auto-correlated. The R 2 indicates how much the dependent variable, profitability (ROA), can be explained by the independent variables and in this case, 52.4% of the variation in the dependent variable (ROA) can be explained by the predictor variables (CCC, ICP and APP) in our model. Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change f1 f2 Sig. F Change 1 724a.524.286 1.0553595.524 2.201.189 1.800 a. Predictors: (Constant), CCC, ICP, APP b. Dependent Variable: ROA Durbin- Watson Table-6 Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. 95.0% Confidence Interval for B B Std. Error Beta Lower Bound Upper Bound 1 (Constant) 17.636 5.264 3.350.015 4.756 30.516 ICP -.082.043 -.709-1.920.103 -.187.023 APP.017.075.110.227.828 -.166.200 CCC -.006.017 -.151 -.347.740 -.046.035 a. Dependent Variable: ROA The regression result in table-6 shows that independent variables are not significantly correlated with inventory conversion period, accounts payable period and the profitability among the manufacturing firms in cash conversion cycle. The standard coefficients value. In contrary, many international findings reveals that there is a strong negative relationship between on such variables have significant correlation with inventory conversion period and dependent variable, that is, returns on assets. The inventory conversion period is considered as an important indicator of manufacturing firm profitability (For example, Padachi (2006), Deloof (2003) and Raheman and Nasr (2007)). The result of ANOVA output in table-7 shows that performance that generally found to be inversely the F value for this test is 2.201 with a p- value of 0.189 correlated with profitability. Therefore, lesser the with p-value >0.05, indicating that the overall contribution conversion period, more will be the profitability. The other of CCC, ICP, APP variables is not statistically significant. Table-7 ANOVA a Model Sum of Squares df Mean Square F Sig. 1 Regression 7.353 3 2.451 2.201.189b Residual 6.683 6 1.114 Total 14.035 9 a. Dependent Variable: AVROA b. Predictors: (Constant), AVCCC, AVICP, AVAPP 9. CONCLUSIONS This study investigates how relatively the listed companies in Muscat Securities Market in Sultanate of Oman can manage their working capital in the most profitable way. Working capital is an important part of financial decisions in all 41 P a g e
firms. Management performance would be improved by managing working capital efficiently. The mean, standard deviation, correlation and regression are the tools used in this research to analyze the effect of working capital in the profitability among the sample firms. The results show that though there are relationships among the working capital variables with profitability variable, statistically it failed to establish such relationship among the sample firms in. The study concludes that the debtor, inventory and cash conversion cycle negatively effects on the financial performance of listed manufacturing firms in over the 10 years period. The creditor which should positively affect the on the financial performance, effects negatively on the financial performance of listed manufacturing firms in over the 10 years period. This study is focused on selective manufacturing firms listed in MSM, therefore future research could be done by including more firms in the sample size. Further, instead of ROA, other financial performance ratios (for example ROCE, Net Profit) could be taken as dependent variable to analyze the effect in different profitability elements. REFERENCES 1. Alipour, M. (2011). Working capital and corporate profitability: Evidence from Iran. World Applied Sciences Journal, 12(7), pp.1093-1099. 2. Charitou, M.S., Elfani, M. and Lois, P. (2010). The effect of working capital on firms profitability: Empirical evidence from an emerging market. Journal of Business & Economics Research (JBER), 8(12). 3. Bagh, T., Nazir, M.I., Khan, M.A., Khan, M.A. and Razzaq, S. (2016). The Impact of Working Capital Management on Firms Financial Performance: Evidence from Pakistan. International Journal of Economics and Financial Issues, 6(3). 4. Cheng, M. C., & Tzeng, Z. C. (2011). How Does Ownership Structure Effect Capital Structure and Firms Performance? Evidence from Taiwan. Global Review of Accounting and Finance, 2(2), 68. 5. Deloof, M. (2003). Does working capital affect profitability of Belgian firms? Journal of Business Finance & Accounting, 30(3&4), 573 587. 6. Demsetz, H. and Villalonga B. (2001). Ownership Structure and Corporate Performance, Journal of Corporate Finance, 7, pp. 209-233. 7. Ganesan, V. (2007). An analysis of working capital efficiency in telecommunication equipment industry. Rivier academic journal, 3(2), 1-10. 8. Juan García-Teruel, P., & Martinez-Solano, P. (2007). Effects of working capital on SME profitability. International Journal of managerial finance, 3(2), 164-177. 9. Knauer, T., &Wohrmann, A. (2013). Working capital and firm profitability. Journal of Management Control, 24(1), 77-87. 10. Padachi, K. (2006). Trends in working capital and its impact on firms performance: An analysis of Mauritian small manufacturing firms. International Review of Business Research Papers, 2(2),45 58. 11. Polycarp, W. and Tabitha, N. (2016). Effect of Working Capital Management on the Financial Performance of Listed Manufacturing Firms in Kenya. Asian Journal of Business and Management.Volume 04 Issue 05, October 2016, pp. 195-208. 12. Raheman, A., & Nasr, M. (2007). Working capital and profitability-case of Pakistani firms. International Review of Business Research Papers, 3(1), 279 300. 13. Saeedi, A & Mahmoodi I. (2011). Capital Structure and Firm Performance: Evidence from Iranian Companies, International Research Journal of Finance and Economics, 70: 21-28. 14. Salim, M., & Yadav, R. (2012). Capital structure and firm performance: Evidence from Malaysian listed companies. Procedia-Social and Behavioral Sciences, 65, 156-166. 15. Sharma, A.K. and Kumar, S. (2011). Effect of working capital on firm profitability empirical evidence from India. Global Business Review, 12(1), pp.159-173. 42 P a g e