The effect of working capital management on profitability

Transcription

1 The effect of working capital management on profitability Derek Venneman University of Amsterdam Economie en Bedrijfskunde Financiering en organisatie Abstract Working capital management is known as an important part of financial management and broadly discussed in previous studies. We study whether the effect of working capital management is significant on profitability in various industries. We find that the cash conversion cycle in most industries does not affect profitability. However, we do find that individual components of WCM affect profitability and we find differences between industries. The results are influenced by the positive influence of credit period on cash conversion cycle measure.

2 Verklaring eigen werk Hierbij verklaar ik, Derek Venneman, dat ik deze scriptie zelf geschreven heb en dat ik de volledige verantwoordelijkheid op me neem voor de inhoud ervan. Ik bevestig dat de tekst en het werk dat in deze scriptie gepresenteerd wordt origineel is en dat ik geen gebruik heb gemaakt van andere bronnen dan die welke in de tekst en in de referenties worden genoemd. De Faculteit Economie en Bedrijfskunde is alleen verantwoordelijk voor de begeleiding tot het inleveren van de scriptie, niet voor de inhoud. 1. Introduction Most firms have a well-diversified investment portfolio, but also have money invested in cash. The cash balance is necessary for any average business to manage working capital. Working capital is the need of cash to meet the firms current liabilities. It is a result of the lag in time between the purchase of raw materials and the collection of the payment for the finished goods sold (Shin and Soenen, 1998). Processing the inventory and the existence of trade credit causes the lag in time. This results in a money hold up in working capital (Deloof, 2003). Next to the lag in time caused by inventory turnover there are two other components in working capital. First, the time lag that arises as a result of the credit period given to your buyer that generates accounts receivable. Secondly, the time lag generated by the obtained trade credit from your supplier that generates accounts payables (Deloof, 2003). Working capital management is part of financial management and a component of the integral corporate strategy to add shareholder value (Johnson and Soenen, 2003). Managing the working capital contains making decisions regarding accounts payable, accounts receivable and inventory turnover. The trade-off between liquidity and profitability is essential at working capital management. Holding enough working capital ensures the firm of enough liquidity to meet her current liabilities and decrease risk. On the other hand holding too much working capital increases opportunity costs (Shin and Soenen, 1998). In business, working capital is mostly defined as net working capital, which is calculated by deducting the current liabilities from the current assets. In the short run, working capital management means borrowing money when there is a 2

3 majority of current liabilities and lending money when there is an abundance of current assets (Smith, 1973). In the longer run, more difficult factors are important, but key factor according to Smith (1973) is that current liabilities in the form of trade credit should be used as long-term debt when it is lowering the average cost of capital. Previous studies find significant effects of working capital management on profitability. In this study, we investigate whether the same effect is found for the datasets on the machinery manufacturing, food manufacturing, retail, fuel and healthcare industries in Europe. The dataset contains 351 companies during the period We run panel regressions during a period of five years on companies of different industries to investigate whether effective working capital management has effect on profitability. Working capital management is measured in total with the measurement cash conversion cycle (CCC) and with the different compartments collection period, credit period and inventory turnover. Previous studies mostly investigate entire national markets or single industries. This study adds to existing literature the comparison of different and broader perspective of industries and the analysis of individual compartments. Our results show that working capital management significantly affects profitability, but different per industry. Significance effect of CCC on profitability is found in the machinery manufacturing, retail and fuel industry, but not in the food manufacturing and healthcare industry. However, credit period significantly affects profitability in the food manufacturing industry and collection period and inventory turnover significantly affects profitability in the healthcare industry. This paper is structured as follows: Paragraph 2 relates literature on working capital management and different industries. Paragraph 3 explains the methodology by discussing the variables, dataset and hypotheses. Paragraph 4 shows the results of the panel regression analyses and paragraph 5 concludes these findings. 2. Related literature An important factor in working capital management, to ensure liquidity, is credit agreements. Strict agreements on payment details decrease the risk that accounts receivable payments are delayed or cancelled. The existence of an agreement where a 3

4 discount is assigned when the payment is done before a certain date is also an incentive to pay early and decreases the risk (Deloof, 2003). However, the advantages of providing trade credit are also present. When no trade credit is offered, buyers are more likely to lend from a bank. The ability of monitoring the financial situation of the buyer is then diminished (Petersen and Rajan, 1997). Petersen and Rajan (1997) also mention the advantage of obtaining information. Discussing the trade credit gives insight to the buyers situation. According to Deloof (2003) the sales could be stimulated by the existence of the trade credit. The flexibility to pay after the goods or services are used could increase the numbers of buyers. Many companies also prefer flexibility on accounts payable. The ability to pay the liabilities a certain period after the purchase is specifically interesting to companies who have relative high cost of goods sold and are short of funds (Kuh, 1960). Firms usually use discounts within a trade credit and missing those discounts can make it costly. Giving discounts stimulates faster payments (Deloof, 2003). These trade credits differ over regions and industries (Ng et al, 1999). Trade credit given by companies appears to be higher in countries where the banking system is more stable and developed. Banks are a safety to default, because customers can lend extra funds from the bank. (Demigürç-Kunt & Maksimovic 2001). In most working capital studies working capital is measured as CCC. It is a measure in days, calculated by the sum of days in inventory and days in accounts receivable and subtracting the days in accounts payable (Deloof, 2003, Raheman and Nasr, 2007 and Juan Garcia-Teruel and Martinez-Solano, 2007). Another option is the use of the net trade cycle (Shin and Soenen, 1998). The alternative measurement net trade cycle (NTC) is developed to avoid problems when firms data on how many days the firms hold their receivables and payables is difficult to obtain (Shin an Soenen, 1998). The NTC measurement components are expressed in percentages of sales. The NTC measurement tells the firm how many days in sale the firm has to finance (shin and Soenen, 1998). A longer cash conversion cycle has different possible consequences. A longer payment period could be interesting to buyers and in that way increase sales and profitability. However, expending this trade credit and in that way average collection period is also costly (Deloof, 2003). The studies on working capital management are conducted in different regions. Where Deloof (2003) focused on Belgian firms, Juan Garcia-Teruel and Martinez Solano (2007) analyzed Spanish firms. 4

5 Shin and Soenen (1998) find a significant effect between working capital management and firm profitability in a study of 58,985 firms in the US. The most benefits from reducing the working capital are gained by shortening the accounts receivables and inventory days, rather than increasing the accounts payables Deloof (2003) based his research on 1009 Belgian firms in the period He states that most firms have a high amount of working capital, so a significant effect of working capital management on profitability is expected. He finds a significant negative relation between gross operating income and CCC. A negative relation is also found for small and medium sized Spanish firms (SME). According to Juan Garcia-Teruel and Martinez-Solano (2007) working capital management is particularly important for SME firms. This conclusion is the result of a study of 8872 SME s over the period They find a significant effect of accounts receivable and inventory on SME s profitability, but not a significant effect of accounts payable on SME s profitability. Where Juan Garcia-Teruel and Martinez-Solano (2007) find a significant effect of accounts receivable, it is also likely that increasing a debtor s collection period enforces customer relationship and so lead to an increase in sales (Ng et al, 1999). Robinson et al. (1986) confirm the importance of working capital management, in particularly inventory planning, at SME s. Knauer and Wohrmann (2013) also find in their recent study that working capital management affects profitability, but confirm it is important to analyze the components of CCC separately. The significance in CCC is in most times a result of accounts receivable and inventory management (Knauer and Wohrmann, 2013). Lazaridis and Tryfonidis (2006) find a highly significant negative relationship between gross operating profit and accounts payables at Athens stock exchange listed firms. The negative result is unexpected because higher accounts payables are lowering CCC. This result means that higher accounts payables decrease profits. This can be a result of less profitable firms who delay paying their payments (Deloof, 2003). On the other hand, profitable firms tend to make their payments faster (Raheman and Nasr, 2007). The effects of working capital management are also found significant for Pakistani firms. CCC and the separate compartments average collection period, average payment period and inventory turnover, all tested negatively significant on firms net operating profitability on a sample of 94 Pakistani firms for the period (Raheman and Nasr, 2007). Where most studies analyze entire national 5

6 markets (Deloof, 2003; Shin and Soenen, 1998; and Juan Garcia-Teruel and Martinez- Solano, 2007) However, Hawawini et al. (1986) argue that working capital decisions are influenced by the industry the firm is operating in. Comparing industries can show differences within a market. Fazzari and Petersen (1993) emphasize the importance of working capital management at firms in modern time. Nowadays, the amount of working capital roughly corresponds to the amount of fixed assets, but at manufacturing firms the amount of working capital is more than half as large as the fixed assets (Fazzari and Petersen, 1993). Raheman et al. (2010) find a significant effect of working capital management on the profitability on Pakistani manufacturing firms in the period 1998 to Where Raheman and Nasr (2007) already found significant results on the whole Pakistani market, excluding financial firms, again significant results are found at manufacturing firms. Important detail is that the manufacturing industry occupied an important role with covering over 19% of the nationals GDP during the analyzed period (Raheman et al., 2010). The amount of days given as trade credit and the average collection period differs over different industries. Juan Garcia-Teruel and Martinez-Solano (2007) find the lowest average collection period at the retail industry with 38 days. Compared to the construction sector with 145 days and other industries, the retail industry seems interesting with a short operating cycle (Juan Garcia-Teruel and Martinez-Solano, 2007). The retail industry is characterized with lower turnover ratios and smaller profit margin on sales. Another key difference with manufacturing industries is that retail companies have relative more current assets than fixed assets (Gombola and Ketz, 1983). The main account on the balance sheet is inventory and the profitability is gained by turning over that inventory as quickly as possible with the highest possible profit margin. Gombola and Ketz (1983) find that retail firms have fewer accounts receivable than manufacturing firms, but more debt. The supply chain, where the retail firms buy goods at bigger firms on trade credit and sell the goods to customers where direct payment is common, can explain these findings. You would thus expect that inventory is more important. Shah and Sana (2006) concentrated on the oil and gas industry in Pakistan. They find significant results for all components of CCC on gross profit. Shah and Sana (2006) find the existence of a negative value of CCC and negative relation between sales growth 6

7 and profitability, but also commented that these results are not abnormal for the oil and gas industry. On the other hand, Pincus and Rajgopal (2002) find that oil and gas firms have the same accounts receivable and accounts payable as any other firms. Accounts receivable are created in a situation of overproduction what causes excess supply and a drop in price or an enhancement in buyer terms. Postponing the payment is a solution what causes the value in accounts receivable. Accounts payables are created in the opposite direction, in a situation of underproduction (Pincus and Rajgopal, 2002). Analyzing the previous studies on WCM shows the greater interest in entire markets of countries rather than specific industries. However, the industrial influence on WCM is found (Hawawini et al, 1986). This study adds, not only analyzing different industries, but more important, comparing them. The industries we analyze are the oil, gas and electric power, manufacturing, retail and healthcare industries. The oil, gas and electric power industry is defined as the fuel industry in this paper. In 2010, the manufacturing industry in the EU covered 26.8 percent of total GDP (Eurostat, 2013). The manufacturing industry contains many different smaller industries manufacturing different products. It is likely that efficient WCM at manufacturing firms with smaller products and profit margins differs from bigger products and profit margins. In the EU the manufacturing of food and machinery are two of the largest manufacturing sectors with both over 9 percent of manufacturing total (Eurostat, 2013). The food manufacturing industry differs from the machinery manufacturing industry with lower prices and less labor-intensity (Biniasz and Golaś, 2011). The averages of credit and collection periods are most likely different. So, in this study the manufacturing industry is divided into two major manufacturing industries to additionally analyze whether there is a difference within the manufacturing industry. Oil and gas are fossil fuels are common sources for fuels in the past. Nowadays, renewable fuels, like wind and solar power, are used more often. Since July 2007, the European Union consumers had the choice to choose their own energy suppliers, where consumers of a few north- and west European countries already had that choice. The average share of renewable energy in gross energy consumption in the EU has increased from 16.1 percent in 2007 to 25.4 percent in 2013(Eurostat, 2015). Adding the renewable energy to the oil and gas industry is interesting because of the increased share and importance of renewable energy in Europe. In this study the oil gas and renewable energy industry is defined as the fuel industry. 7

8 Previous studies focus mostly on industrial industries with clear credit periods and inventories. Additionally to comparing the industries food manufacturing, machinery manufacturing, retail and oil, gas and renewable energy, it is interesting to analyze a non-industrial industry. The healthcare industry is interesting because of the importance in daily life and the availability to measure inventories, where in most service industries inventories are more difficult to measure. Healthcare companies have a tradeoff between good healthcare and economic durability. Chu et al. (1991) find that hospitals need to focus more on financial management and that specifically working capital is an important part. Harrell and Folk (1994) find that the American healthcare industry needs more effective working capital management and already find a trend where companies secure their accounts receivable with securitizations. Though, the American healthcare industry is easier to compare with other industrial industries. The healthcare industry in most European countries can be more focused on actual care, because most people are insured. So, next to comparing different industries, this study adds a working capital management analysis on the healthcare industry and compares it with industrial industries. Based on previous studies and economic theory, the expectations differ by industry. The differences between industries are expected to arise within the individual compartments collection period, credit period and inventory turnover. Normally the collection period and turnover ratio are expected to be found negatively significant and credit period to be found positively significant both to lower the CCC. However, most studies do find negatively significant collection period and turnover ratio, but not a significant effect of credit period. All industries are compared with these findings from previous studies and compared with the other industries. For all industries, except the fuel industry, the credit period is not expected to find significant, based on previous studies. For both the manufacturing industries, the CCC is expected to find significantly negative, according to previous studies. The inventory turnovers and collection periods are expected to find significantly negative at both industries based on previous studies. Because of smaller profit margins at the food industry we especially expect negatively significance of inventory turnover (Raheman and Nasr, 2007). CCC is expected to find significantly negative for the retail industry matching most industries. However, the most important compartment is expected to be inventory 8

9 turnover because of the smaller profit margins and turnover rates (Gombola and Ketz, 1983). The collection period is on average smaller compared with other industries, because direct payment is common. As a result, it is not expected to find significance for the collection period in the retail industry (Juan Garcia-Teruel and Martinez-Solano, 2007). The expectations for the fuel industry are based on previous studies of oil and gas companies. Previous studies on the oil and gas industry find all compartments significant on profitability. Negatively significance is expected for the collection period and inventory turnover and positively significance for the credit period. (Shah and Sana, 2006). Adding the renewable energy does not change the expectations, but could affect significance, because competition can lower prices and profitability. The healthcare industry expectations cannot be based on previous studies. However, Chu et al. (1991) find that working capital management becomes an important factor in financial management in the healthcare industry. Significance of the collection period and credit period are more likely than significantly inventory turnover, because healthcare often involves services. 3. Method and data The focus in this study on working capital management is the relationship between effective working capital management and profitability among different industries. As common in working capital management studies we use panel regressions. To check whether a fixed or random effects panel regression is needed a Hausman test is conducted for every industry. We are mainly interested in the effect of CCC and the individual compartments on return on assets (ROA) among different industries. We use the following regression: ROAit = β0 + βф Xit + β5 CURit + β6 lnsizeit + β7 GDPGit + β8 OILPit + εit 3.1 Variables We run four regressions on ROA for CCC, collection period (COLP), credit period (CRED) and inventory turnover (INVT). Variable ф stands for numbers 1-4 for the variables CCC, 9

10 COLP, CRED and INVT, displayed as variable X. The variable oil price (OILP) is added for industry specific control variable, only for the fuel industry regression. Profitability can be measured in multiple ways. Popular measurements are gross operating profit (Deloof, 2003; Lazaridis and Tryfonidis, 2006) and ROA (Shin and Soenen, 1998; Juan Garcia-Teruel and Martinez-Solano, 2007). In this study ROA is used as dependent variable to measure profitability. ROA is known as a good measurement for profitability and has good availability. Most studies on working capital management used CCC as a measure for working capital (Deloof, 2003; Lazaridis and Tryfonidis, 2006; Juan Garcia-Teruel and Martinez-Solano, 2007; and Raheman and Nasr, 2007). CCC = collection period + inventory turnover credit period In this study we chose for the CCC measurement. Variables COLP, CRED and INVT are implemented in the regression to test the individual effects of the compartments of CCC. Variables COLP and CRED are respectively the average collection and credit period in days. Inventory turnover is calculated as 365 days!"#$"%&'(!"#$, where inventory is the sum of the three compartments finished goods, work-in-progress and finished goods. For individual industries finished goods or raw materials would be enough to test, but because of the approach of different industries, all inventory compartments are needed. In this study we used control variables that where necessary for all industries and an industry specific control variable. Control variable lnsizeit is calculated as a natural logarithm of sales to account for company size. Another control variable, CURit, is calculated by the current ratio for the differences in asset structure. These control variables are common in previous WCM studies (Shin and Soenen, 1998; Raheman and Nasr, 2007). GDPGit is the growth rate of GDP, added as a control variable to account for the economy s situation (Juan Garcia-Teruel, 2007). For the fuel industry the extra control variable OILPit) is added. Pincus and Rajgopal (2002) find that oil prices are a big risk for oil and gas firms, but Malmquist (1990) says the oil prices risk can be hedged away cheaply. However, Pincus and Rajgopal (2002) find that not all firms hedged their risk on oil prices. Therefore OILP is added as extra control variable for this industry. 10

11 3.2 Data All the necessary data is retrieved from the Orbis database, developed by Bureau van Dijk. Orbis contains all kinds of financial data over companies around the world, but specially focused on Europe. The dataset contains information on European countries over five industries. Oil prices and GDPG s are retrieved from the world databank. The window with annual periods is analyzed for all industries. Outliers with abnormal ROA s were removed from the dataset. Table 1 shows the means, standard deviations, minimums and maximums for all independent variables per industry sample. The sample size of the healthcare industry is considerable lower, because of the difficult availability of data. The standard deviations are relatively high for all variables, because there is a broad selection of different companies per industry, with widely separated values. As expected, the average collection period in the retail industry is the lowest. Table 1. Summary statistics. Food manufacturing Machinery manufacturing Retail Fuel Healthcare CCC Mean St.dev Min Max Collection Mean St.dev Min Max Credit Mean St.dev Min Inventory turnover Max Mean St.dev Min Max N

12 4. Results Tables 2 to 5 show the results of the panel regressions of the different industries. The results differ over the industries and are not all expected. Table 2 shows the results of the food manufacturing industry panel regressions. The Hausman test conducted for the food manufacturing caused the use of fixed effects. The effect of CCC is not found significant in model 1. The only control variable found significant is current ratio with a positive effect on ROA. The compartments of CCC are also tested individually on ROA. Credit period is found negatively significant in model 3. These results are not in line with most other WCM studies that mostly find significant effects of collection period and inventory turnover, but less often for the credit period. However, the significantly negative beta for credit period can be a result of less profitable companies who delay their payments (Deloof, 2003). Table 2. Food manufacturing (standard errors in parentheses) model (1) (2) (3) (4) CCC -.01 COLP -.01 (.02) CRED -0.05* (.03) INVT CUR 3.14** (.67) 2.99** (.68) 3.33** (.67) 3.00** (.68) lnsize -.16 (1,24).32 (1.19).47 (1.19) -.11 (1.25) GDPG (.09) (.09) (.08) Constant (16.44) (15.65) (15.67) N R * p<0.05; ** p<0.01 (.09) 2.30 (16.76) The Hausman test for the machinery manufacturing industry led to the use of fixed effects. The results of the machinery manufacturing panel regressions in table 3 show that there are differences within the manufacturing industry. Contrary to the food manufacturing industry, the CCC is found significant. The negatively significant CCC is 12

13 expected, as well for the significantly negative collection period and inventory turnover. These two compartments were not tested significant at the food manufacturing industry. However, similar to the food manufacturing industry the credit period is also found significantly negative. All control variables show positively significance in the four models. Table 3. Machinery manufacturing industry (standard errors in parentheses) Model (1) (2) (3) (4) CCC -0.02* (0.01) COLP -.09** (.02) CRED -.11** (.03) INVT -.02* CUR 3.08** (.69) 2.81** (.69) 2.50** (.71) 3.04** (.69) lnsize 8.76** (1.27) 8.92** (1.16) 9.41** (1.14) 8.90** (1.27) GDPG.49**.51**.54**.49** (.08) (.08) (08) Constant (17.42) (15.82) (15.50) N R * p<0.05; ** p<0.01 (.08) (17.48) Table 4 shows, as expected, the importance of CCC in the retail industry. The Hausman test result caused the use of random effects. Model 1 shows negatively significant CCC as expected. The insignificance of collection period in model 2 also confirms expectations. The average collection period of days gave an indication of the unimportance of the credit period in the retail industry. The compartment inventory turnover is found significantly negative following expectations based on the need to turn over inventory faster because of smaller profit margins (Juan Garcia-Teruel, 2007). Similar to the manufacturing industries the credit period is also found significantly negative. 13

14 Table 4. Retail industry (standard errors in parentheses) Model (1) (2) (3) (4) CCC -.04** (.02) COLP -.08 (.05) CRED -.11** (.04) INVT -.05** (0.02) CUR 8.43** (1.05) 7.95** (1.04) 6.84** (1.12) 8.05** (1.03) lnsize.58 (.45).72 (.47) 1.01* (.43) 0.67 (.43) GDPG.16 (.08).15 (.08).15 ( (.08) Constant (6.70) (6.75) (6.56) N R * p<0.05; ** p<0.01 Table 5 presents the results regarding the fuel industry. Random effects panel regressions are performed as a consequence of the Hausman test. According to expectations CCC is found significantly negative. However, not all individual compartments are found significant as expected. Collection period and inventory turnover are tested insignificantly where they were expected significantly positive. Additionally remarkable is the negatively significant credit period where positively significant was expected. Although, the negatively significant credit period is in line with the other industries. Industry specific control variable oil prices, is tested significantly negative in all models. Higher oil prices would affect ROA negatively, what can be explained by economic theory. Higher prices deteriorate competitiveness position versus other fuel sources. 14

15 Table 5. Fuel industry (standard errors in parentheses) Model (1) (2) (3) (4) CCC.02* COLP -.01 (.02) CRED -.06** (.02) INVT.01 CUR -.65 (0.38) -.75 (.39) -.86* (.39) -.71 (.39) lnsize.42 (.26) (.24).39 (.26) GDPG.33** (.07).33** (.07).32** (.07).33** (.07) OILP -.06** -.06** -.05** -.06** Constant 4.93 (4.00) 7.41 (3.89) 8.00* (3.63) 6.49 (3.97) N R * p<0.05; ** p<0.01 Table 6 shows the results of the panel regressions conducted on the healthcare industry. Random effects were used after the result of a Hausman test. CCC is not found significant in model 1. However, individual compartments collection period and inventory turnover are found significant. Both variables are found negatively significant, in line with the other industries expectations. The average of days collection increases the CCC and decreases profitability. The relative long period healthcare companies wait on their receivables can be a consequence of insurance companies handling customer payments. The negatively significant collection period shows that decreasing the collection period increases profitability. Control variable GDPG is not found significant in any model, what can be explained by the need of healthcare regardless economy s situation. 15

16 Table 6. Healthcare industry (standard errors in parentheses) model (1) (2) (3) (4) CCC.02 COLP -.07** (.03) CRED -.04 (.03) INVT.02* CUR 3.49** (.50) 3.03** (.49) 3.61** (.53) 3.31** (.48) lnsize 12.72** (2.16) 11.55** (2.15) 10.85** (2.06) 13.51** (2.25) GDPG (.50) (.48) (.51) Constant ** ** ** (23.17) N R * p<0.05; ** p<0.01 (.48) ** Comparing the results of the different industries shows differences in significance of CCC and the individual compartments. CCC is tested negatively significant for the machinery manufacturing, retail and fuel industries, but not for the food and healthcare industries. However, individual compartments of CCC are tested significant in the industries that show insignificance of CCC. The negatively significance of credit period in all industries, except the healthcare industry, is against expectations and economic theory, but can be a result of less profitable firms who delay their payment (Deloof, 2003). 5. Conclusion In this study, we test the effect of WCM on profitability over different industries using five datasets of 436 companies in the period Using panel regressions, significance of CCC is found in the machinery manufacturing, retail and fuel industry. Significant effects of individual compartments collection period, credit period and inventory turnover are found along different industries. Most outstanding results are found regarding the credit period in all industries, except for healthcare. Where most studies do not find significant results or even significantly positive effect of credit period 16

17 on profitability, we found negative significant effects for credit period on profitability. This is in line with the study of Deloof (2003), who states that it can be the result of less profitable companies who delay their payments. Comparing the different industries shows us that working capital management is affecting profitability in different ways along different industries. Comparing the two manufacturing industries shows us that CCC affects profitability at the machinery manufacturing, but not in the food manufacturing industry. Also, the collection period does affect profitability in the machinery manufacturing industry, but not in the food manufacturing industry. This can be explained by the lower prices of food manufacturing with less custom to use trade credit. Therefore, these results suggest that managing working capital is effective in both the manufacturing industries, but should be limited to the credit period only in the food manufacturing industry. In the retail industry managing working capital in total is effective, with focusing on the credit period and inventory turnover. Managers in the fuel industry can effectively manage working capital, but not on individual compartments collection period and inventory turnover. Effective working capital management in the healthcare industry is practicable in the compartments collection period and inventory turnover. From these results we conclude that working capital management does significantly affect profitability, but it is valuable for firms to manage the individual compartments collection period, credit period and inventory turnover, taken into account that strategies and customs varies by industry. For new research it is interesting to further investigate the effect of credit period on profitability and whether this effect is a consequence of less profitable firms who delay their payments or truly effective managing effect. Second, further research is interesting into industries selling services rather than goods. A working capital measurement different from CCC could be needed, because of the irrelevant inventories. 17

18 References Bieniasz, A., Gołaś, Z. (2011). The Influence of Working Capital Management on the Food Industry Enterprises Profitability. Contemporary Economics, 5(4), Available at SSRN: Chu, D.K.W., Zollinger, T.W.,Kelly, A.S., Saywell, R.M. (1991) An empirical analysis of cash flow, working capital, and the stability of financial ratio groups in the hospital industry. Journal of Accounting and Public Policy, Elsevier, 10(1), Deloof, M. (2003). Does Working Capital Management Affect Profitability of Belgian Firms? Journal of Business, Finance and Accounting, 30,(3&4), Demirgüç-Kunt, A., Maksimovic, V. (2001). Firms as Financial Intermediaries : Evidence from Trade Credit Data. World Bank, Washington, DC. Retrieved from: Diamond, D. W., & Rajan, R. G.. (2001). Banks and Liquidity. The American Economic Review, 91(2), Retrieved from Eurostat (2013). Manufacturing statistics - NACE Rev. 2. Retrieved from Manufacturing_ statistics_-_nace_rev._2 Eurostat (2015). Sustainable development - climate change and energy. Retrieved from: _energy_statistics Fazzari, S. M., & Petersen, B. C.. (1993). Working Capital and Fixed Investment: New Evidence on Financing Constraints. The RAND Journal of Economics, 24(3), Retrieved from Gombola, M.J. and Ketz, J.E. (1983). Financial Ratio Patterns In Retail And Manufacturing Organizations. Financial Management 12 (2), Harrell, C. E., & Folk, M. D. (1994). Financing American Health Security: The S Securitization of Healthcare Receivables. The Business Lawyer, 50(1), Retrieved from Hawawini, G., Viallet, C., Vora, A. (1986). Industry influence on corporate working capital decisions. Sloan Management Review 27(4), Juan Garcia-Teruel P., Martinez Sonano, P. (2007). Effects of Working Capital M Management on SME Profitability. International Journal of Managerial Finance, 3(1), Knauer, T., Wöhrmann, A. (2013). Working capital management and firm profitability, UNSW Journal of Management Control, 24(1), Kuh, E. (1960). [Review of Studies in Company Finance, A Symposium on the Economic Analysis and Interpretation of British Company Accounts.] Journal of the American Statistical Association, 55(291), Lazaridis, I., Tryfonidis, D. (2006). Relationship Between Working Capital Management and Profitability of Listed Companies in the Athens Stock Exchange. Journal of Financial Management and Analysis, 19(1). Available at SSRN: Malmquist, D.H. (1990). Efficient contracting and the choice of accounting method in the oil and gas industry. Journal of Accounting and Economics,12(1-3), Ng, C. K., Smith, J. K., & Smith, R. L. (1999). Evidence on the Determinants of Credit Terms Used in Interfirm Trade. The Journal of Finance, 54(3), Retrieved from 18

19 Petersen, M.A., Rajan, R.G. (1997). Trade credit: Theories and Evidence. The review of Financial Studies, 10(3), Pincus, M., & Rajgopal, S. (2002). The Interaction between Accrual Management and Hedging: Evidence from Oil and Gas Firms. The Accounting Review, 77(1), Retrieved from Raheman, A., Nasr, M. (2007). Working capital management and profitability case of Pakistani firms. International Review of Business Research Papers, 3(1), Raheman, A., Afza, T., Qayyum, A., & Bodla, M. A. (2010). Working capital management and corporate performance of manufacturing sector in Pakistan. International Research Journal of Finance and Economics, 47(1), Robinson, R.B., Jr., Logan, J. E., and Salem, M. Y. (1986), Strategic versus optional planning in small retail firms, American Journal of Small Business, Vol. 10, pp Shah, S.M.A., Sana, A.,(2006). Impact of Working Capital Management on the Pofitability of Oil and Gas Sector of Pakistan. European Journal of Scientific Research, 15(3), Smith, K. V. (1973). State of the Art of Working Capital Management. Financial M Management, 2(3), Retrieved from Shin, H.H. and L. Soenen (1998), Efficiency of Working Capital and Corporate Profitability. Financial Practice and Education, 8(2),