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INTERDISCIPLINARY JOURNAL OF CONTEMPORARY RESEARCH IN BUSINESS

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THE EFFECT OF WORKING CAPITAL MANAGEMENT ON FIRM’S

PROFITABILITY:

EVIDENCE FROM SINGAPORE

Ebrahim Mansoori

PhD candidate, School of management,

University Sains Malaysia (USM), 11800 Pulu Penang, Malaysia

Corresponding author

Datin Dr. Joriah Muhammad,

Senior lecturer, School of Management,

University Sains Malaysia (USM), 11800 Pulu Penang, Malaysia

Abstract

The purpose of this research is to investigate the effect of working capital management on firm’s

profitability. Using panel data analysis, pooled OLS and Fixed Effect estimation, for a sample of Singapore firms

from 2004 to 2011, we find that managers can increase profitability by managing working capital efficiently.

Moreover, managers can improve firms’ profitability by shortening receivable conversion period and inventory

conversion period. The analysis is applied at the level of full sample as well as economic sectors. However, the

results of industry analysis suggested the effect of economic sector on relationship between working capital

management and profitability.

Keywords: Working capital management, cash conversion cycle, profitability, Singapore

1. Introduction

Working capital management, which consists of current assets and current liabilities management, is the

main function of financial managers in all corporations. While the working capital management takes up a major

part of executive manager’s attention and time, there is a deserved attention to working capital management in

finance literature. (Jose, Lancaster, & Stevens, 1996; Deloof, 2003; Ŝen & Oruč, 2009). The utmost important

component of working capital related to inventories, accounts receivables and accounts payables (Ross, Westerfield,

& Jaffe, 2002). Financial executives have to make different decisions about the level of these components in order to

the best results. The dynamic nature of short-term business emporium, the daily need to substituting current assets,

and liquidation current liabilities help to clarify the importance of working capital management and financial

executive duties. The direct effect of working capital management on profitability and liquidity position of firms

also refers the importance of working capital management (Nobanee, Abdullatif, & Al Hajjar, 2011). Firms may

face to bankruptcy if they select and use improper working capital strategies, even though they experience positive

profitability.(Śamiloġlo & Demirgũneş, 2008).

Based on risk-return trade off, there are three procedures about working capital management, including

aggressive, conservative, and moderate working capital strategies (weinraub & Visscher, 1998). Aggressive working

capital policy refers to maintain the lower amount of working capital elements, which accompanied with high risk of

liquidity and high return on working capital investment. Conservative working capital management strategy point

Electronic copy available at: http://ssrn.com/abstract=2185840

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out keeping higher volume of the working capital requirements, which connects with lower liquidity risk and lower

return on working capital investment. Finally, the moderate strategy is between two working capital policies as

mentioned above and explains keeping working capital elements in such volume that accompanied average risk-

return.

2. Working capital management

The main objective of working capital management is to ensure that companies have sufficient cash flow to

continue normal operations in such a way that minimize risk of inability to pay short-term commitment. Moreover,

managers should try to avoid from unnecessary investment in working capital. While, more investment in working

capital may reduce the risk of liquidity, insufficient amount of working capital may cause shortages and problems in

daily operations. However, more investment in working capital means more funds tighed up to business operation

and would increase the opprtunity cost of investment epecially when firms rely on external financing to finance

working capital. Therfore, efficiency of working capital management depends on balances between liquidity and

profitability. (Filbeck, Krueger, & Preece, 2007; Faulkender & Wang, 2006).The profound understanding of the role

of working capital and its effect on firms profitabolity would help managers to look for strategic plans for

management of working capital.

One of the standard performance measures to evaluate how well a firm does managing the working capital

is Cash Conversion Cycle (CCC) that was introduced by Richards and Laughlin (1980). It refers to time-period

between buying raw material, convert to finished goods, sales products, and collect account receivables. Firms with

Shorter cash conversion cycle have fewer investment in working capital and as a result the the cost of financing are

less for these firms. The importance of cash conversion cycle well pointed out by a study that was conducted by

Shin & Soenen (1998). They compared two corporations with the same capital structure, Kmart and Wal-Mart. The

former had a CCC of 61 days and the latter had a CCC of 40 days. The differences of 19 days in cash conversion

cycle made Kmart to face 198.3 million US dollars extra to finance his working capital and faced more financial

constraints. Consequently, shorter cash conversion cycle would increase profitability, and would show the efficiency

of management performance in managing working capital. (Deloof, 2003; Nazir et al., 2009, Zariyawati et al, 2009).

Thus, Cash conversion cycle integrates three components of management efficiency include, production, inventory

management, as well as supply chain management (Moyer, Mcguigan, & Kretlow, 2003)

Exhibit 1 presents the procces of cash concersion cycle. Operation cycle includes both inventory

conversion period and receivables conversion period. The length of operation cycle should be financed by

corporations directly if they buy the raw materials on cash. But majority of corporations have strong tending to use

trade credits to financing some parts of operation cycle and also suppliers are willing to provide financial

intermediary services to corporations. (Niskanen & Niskanen, 2006). Inventory conversion period refers that how

long does it take a firm coverts the raw material to finished goods. This period just available in manufacturing firms

and it can not applied to services or banking sectors. Supply-chain management, economic order quantity, just in

time system and economic production quantity are common techniques to management inventories and managers

can use these tools to shorten the period of inventory conversion. Receivables conversion period is defined as the

time -period between sales products on credit and collecting the cash from the customers. Financial managers should

select and use appropriate credit policies not only to attract clients in a manner that enable firms to compete with

their competitors but also to minimize the financing cost of these credits. Last part of cash conversion cycle

connected to payables deferral period that refers to time-period between buying raw material on credit and paying

cash to suppliers. Although, extending the length of payable deferral period may reduce the length of cash

conversion cycle but it should be consider that more lengthening of deferral payable period may damage the firm’s

reputations (Nobanee et al,. 2011). The shorter the length of the cash conversion cycle means effective working

capital management and indicates the better management performance with regards to the inventory conversion

period, collecting receivables period and short term financing using payables.

This study contributes the body of knowledge by identifying how working capital management affect firm’s

profitability and how managers use working capital strategies to increase the firm’s market value. Moreover, This

study focus on the effect of working capital management on firm’s performance and shed more light to how

managers affect firm’s profitability by managing working capital efficiently. The theoretical contribution of this

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research is to enrich the existing literature by investigate the effect of working capital management on profitability

in Singapore firms as a developed market.

3. Literature Review

The cost of capital and the extent of access to external financing are some yardsticks to decide about the

level of investment and the amount of resources that would engage in the working capital. Kieschnick et al, (2006)

argued that the additional dollar invested in working capital would cause to decrease the value of firms. Moreover,

they showed that the worth of a dollar contributed to net working capital is less than the worth of a dollar from its

financing sources. However, they empirically presented the importance of working capital management in firm

value, while the financing sources of working capital should be considered as an important factor in firm’s

valuation. Deloof (2003) challenged the effect of working capital management on Belgian firm’s profitability. The

empirical results of his study stated that the profitability can increase by reducing the length of the accounts

receivable period and inventory conversion period. However, the results emphasized the importance of management

working capital efficiency to increase profitability. Lazaridis and Tryfonidis (2006) investigated the relationship

between profitability and working capital management in Athens Stock market Exchange (ASE) using a sample of

131 firms for the period from 2001 to 2004. Their findings showed that cash conversion cycle associated with gross

profit margin negativity.

From a different perspective, firm’s size, Teruel & Solano (2007) tried to make inquiries about working

capital management and profitability relationships in Small and Medium size firms (SME). For this purpose, they

collected a panel of 8872 Spanish corporations for the period from 1996 to 2002. Using panel data analysis with

both random effect and fix effect models, they revealed a negative relationship between return on asset and cash

conversion cycle, They argued that small and medium-size firms also can increase their profitability by shortening

cash conversion cycle. Śamiloġlo and Demirgũneş (2008) conducted a study to examine the relationship between

working capital management and profitability. Applying multiple regression analyses over a sample of

manufacturing firms listed in Istanbul stock exchange for the period of 1998-2007, they found that the accounts

receivable cycle, the inventory conversion period have negative impact on profitability, which means the shorter

cycle of these variables cause increasing in profitability.

In Pakistan, the effect of aggressive working capital management procedures on firm’s profitability was

examined by Nazir & Afza (2009). The sample consisted of 204 non-financial firms active in Karachi Stock

Exchange (KSE) over the period from 1998 to 2005. Their findings showed that the rate of aggressiveness in

working capital polices and financing procedures associated negatively with both profitability ratios including return

on assets and Tobin’s q. In addition to, their results revealed that investors give more value to the corporations with

more aggressive policies in managing current liabilities.

Trade-off between working capital management and profitability is a controversial topic. Zariyawati et al,.

(2009) tried to pay attention to the relationship between profitability and working capital management in Bursa

Malaysia. The panel of Malaysian firms over the period from 1996 to 2006 was selected to investigate the

relationship between cash conversion cycle as a working capital proxy and ROA as a profitability ratio. The result of

using Pooled OLS regression indicated a negative relationship between working capital proxy and profitability

which means that managers can increase profitability by decreasing the length of cash conversion period.

Ŝen and Oruč (2009) investigated the efficiency of working capital management and its relationship with

profitability in Istanbul Stock market Exchange (ISE). They used three-month table data have issued by 49

production corporations for the period from 1993 to 2007 over five production sectors, including white goods and

electronic, Cement, food, chemistry and textile. These researchers utilized two models using panel data analysis.

Their results showed that aggressive working capital management which represents by shorter CCC and less current

ratio cause increasing in profitability. In sector's investigation, they revealed that there is a significant similarity

among sectors with regard to the relationship between working capital management and profitability except for the

chemistry sector.

Azhar and Noriza (2010) investigated the effect of working capital management on firm’s performance for

Malaysian firms. The sample involved 172 listed companies from Bursa Malaysia for the period covers five years

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from 2003 to 2007. The result of applying multiply regression analysis showed that managers can increase firm’s

market value and performance by managing working capital effectively.

In Japan, Nobanee & Abdullatif & Al Hajjar (2011) studied the relationship between working capital

management and firm’s profitability on a large cross-section of 2123 Japanese corporations active in the Tokyo

Stock Exchange covered the period from 1990 to 2004. Their results revealed that managers can improve firm’s

performance by managing working capital effectively. Moreover, they recommended that managers should be

careful with regard to the lengthening of payable deferral since it might harm the corporation’s credit reputation and

as a result decrease profitability in the long-run horizon.

In India, Vijay Kumar (2011) examined the relationship between working capital management and firm’s

profitability in automobile industries. The sample consisted of 20 firms for the period covers 13 years from 1996-

2009. The result of this study has shown that there is negative relationship between the length of cash conversion

cycle and firm profitability. His finding approved the recent literature in this area about affecting the profitability by

manager’s performance engaged to working capital management.

4. Research Methods

4.1 Data and Sample selection

The data need for empirical testing of the research hypotheses was collected from DataStream database that

included the secondary data of the financial statement of firms listed in the main board of Singapore stock market

exchange (SGE).The sample was putted up as follows. All active firms over the research period with completed

required data were selected, and firms with incomplete data were excluded from the sample. Because of the specific

nature of firms active in banking and finance, insurance, mutual funds and business services, these firms were

excluded from the sample. To investigate industry effects, the sectors with less than 10 firms eliminate from the

sample. Final sample consisted of 736 firm-year observations that include the observation of 92 firms for the 8 years

from 2004 to 2011. Table 1 presents the sample distribution based on economic sector. The electronic sector is the

major sample with 25 firms while the food sector is the least sector with 15 firms.

4.2 Variables

To examine the relationship between working capital management and corporation’s profitability, the ratio

of Return on Assets (ROA), which calculate as the net income divided by total assets, was used as the dependent

variable. Several recent studies have used ROA as a proxy for firms profitability such as (Teruel & Solano, 2007)

(Nazir & Afza, 2009; Śamiloġlo & Demirgũneş, 2008; Zariyawati, et al., 2009; Azhar & Noriza, 2010;

Vijayakumar, 2011) Cash Conversion Cycle was used as the independent variable that have utilized by several

recent studies as a comprehensive measure for working capital management (Wang, 2002; Deloof, 2003; Lazaridis

& Tryfonidis, 2006; Śamiloġlo & Demirgũneş, 2008; Caballero et al., 2009; Vijayakumar, 2011). The Cash

Conversion Cycle defines as the sum of the Receivables Collection Period (RCP), plus the Inventory Conversion

Period (ICP), minus the Payment Deferral Period (PDP). Receivables collection period is calculated as accounts

receivables/ (sales/365), which refers to the time-period to collect receivable from firm’s customers. Inventory

conversion period is calculated as inventories / (Cost of good sold/365) that represent the time- span, which a firm

should invest cash while firms’ materials are converted into a sale. The payment deferral period is calculated as

accounts payable / (cost of good sold/ 365). This measure represents days payable outstanding.

In addition, firm size (the natural logarithm of total assets), debt ratio (total debt to total assets), sales

growth ([current year sales – previous year sales/ previous year sales]) and GDP rate was included in the regression

analysis. Table 2 presents the summary of data measurement.

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4.3 Descriptive statistics

Table 3 presents the descriptive statistics for all variables, which used in this research. The average return

on assets for whole sample is 2.9 % while the construction and material sector with average 8.58 % have highest

return on assets; the technology hardware sector has lowest return on assets with average – 2.46%. Moreover,

electronic and technology hardware are two sectors that experienced negative return on assets on the average. With

regard to cash conversion cycle , it is appeared that technology hardware sector with average 79 days has lowest

CCC while the construction and material sector with average 181 days has highest length for CCC. The food

producers sector has lowest receivable collection period with average 57 days and electronic sector has highest

receivable collection period with average 136 days. The lowest inventory conversion period is belonged to

technology hardware sector with 73 days on the average and the highest of this period is related to construction and

material sector with average 162 days. In addition to, food producers has lowest payable deferral period with

approximately 45 days on the average while the highest period is belonged to construction and material sector with

96 days averagely. The descriptive statistics for the control variables were demonstrated at table 3.

4.4 Model specification

To investigate the effect of working capital management and firm’s profitability, we conducted four

models. The first model tries to investigate the relationship between cash conversion cycle and return on assets. The

second model investigates relationship between account receivables and firms profitability. Third model is related to

the relationship between inventory conversion period and return on asset. Finally, last model analysis the effect of

payable deferral period on profitability. All the models presented as follows;

Model 1) ROA = β0 + β1 CCC + β2 SIZE + β3 LEV + β4 GROWTH + β5 GDP + €

Model 2) ROA = β0 + β1 RCP + β2 SIZE + β3 LEV + β4 GROWTH + β5 GDP + €

Model 3) ROA = β0 + β1 ICP + β2 SIZE + β3 LEV + β4 GROWTH + β5 GDP + €

Model 4) ROA = β0 + β1 PDP + β2 SIZE + β3 LEV + β4 GROWTH + β5 GDP + €

Where;

ROA is return on assets, CCC is the cash conversion cycle, Size is the firm’s size, Lev is total debt to total

assets, Growth is the firm’s sales growth, GDP is annual growth domestic product, and € id regression residuals.

All equations was estimated by regression analysis as utilized by Deloof (2003), Lazaridis & Tryfonidis (2006), Ŝen

& Oruč (2009). The main differences related to control variables that used in this study. The GDP was introuduced

in the models to control for the effect of macroeconomic conditions, and firm size was applyied to control for the

effect of corporation’s size on profitability. Moreover, Spearman correlation coefficient analysis was used to

present the relationship between working capital management and firm’s profitability.

5. Results

In the first stage, the spearman correlation coefficient between cash conversion cycle and its components,

and firm’s profitability is examined. In the next stage, regression analysis for both pooled sample and five sectors is

applied.

5.1 Correlation analysis

The results of spearman correlation coefficients are presented in the table 4. The satisfactory performance

of managers would increase profitability by reducing the length of cash conversion cycle. In these situations, a

negative relationship between cash conversion cycle and return on assets would be expected. The results indicate a

negative relationship between cash conversion cycle and profitability that support the expectation about working

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capital management and firm’s performance. That is, managers can use working capital strategies to increase

profitability that connects the proper performance of working capital managers to increase market value. Moreover,

the negative relationship between RCP and ICP with ROA also are in line with the literature that indicate longer

receivables period and inventory conversion period means more finance sources engaged in working capital, which

increase opportunities cost of extra financing. The negative relationship between PDP and ROA stem from the fact

that more lengthening the accounts payable period may damage the corporation’s credit reputation and decrease the

firm’s profitability as mentioned by Nobanee et al.( 2011). With regard to control variables, the results reveal a

direct relationship between profitability and three control variables including; firm size, firm growth and gross

domestic products. These results indicate that profitability increase with size of the firms, more growth firms have

more profitability, and economic boom increase corporations profitability. However, it is appeared that increasing in

firms leverage associated to decrease in profitability.

5.2 Regression analysis

Regression analyses are applied to investigate the relationship between working capital management and

profitability. To avoid heteroscedastisity problem, all regression models was estimated using the regression-based

framework Pooled Ordinary Least Squares model (OLS) as used by Gill et al,.(2010), and Raheman & Nasr (2007)

with cross section weight of five industries including electronic, construction and material, technology hardware,

industrial engineering and food producers. In OLS regression, a common intercept is calculated for all variables and

allocated a weight. Models of this study differ by entering the components of cash conversion cycle as independent

variables as well as by using two different control variables involving firm size and gross domestic products. To

apply the pooled OLS regression, the data set is pooled across firms and years for a balanced data set of 736 firm-

year observations. Moreover, the result of Hausman test indicates that we should use fixed effect estimation. The

fixed effects model suppose that the slope coefficient of the regressors does not vary across firms and is constant,

but the intercept varies over time or across firms. Therefore, the changing of the firms intercepts presents the effect

of unobserved explanatory variables. (Hsiao, 2003).

Table 5 presents the regression results for both pooled OLS and Fixed effects estimations. The results of

model 1 show a highly negative relationship between cash conversion cycle and return on assets in both pooled OLS

(P-value- 0.0001 ) and fixed effect estimation (P-value 0.0000). These results imply that managers can increase

firm’s profitability (0.01 % according to OLS and 0.02 % according to fixed effect estimation) by reducing one day

in length of cash conversion cycle. The coefficient of regression in model 2 offers a negative and highly significant

relationship (P-value 0.000) between receivable collection period and return on assets. It means that management

policies with regard to account receivables can serve as a tool to improve corporation’s performance. In Regression

3, we found a strong negative relationship between inventory conversion period and firm’s profitability (P-value

0.0043 & 0.0006) and point out that increasing the length of inventory turnover by one day is accompanied with the

decreasing in return on assets by 0.01 % according to OLS and 0.02 % according to fixed effect estimation.

Moreover, the coefficient of the payable deferral period is negative and significant in both regression modes. The

negative relationship between payable deferral period and corporate profitability may stem from the fact that less

profitable corporations have to wait longer for paying their bills as was mentioned by Deloof, (2003) or from the

fact that more lengthening the number of account payable days may damage firm’s reputations and consequently

firm’s profitability as was mentioned by Nobanee (2011). The results of all regression models in both pooled OLS

and fixed effect estimation suggested that managers can increase firm profitability by decreasing the length of

receivables collection period and inventory conversion period. The OLS regression estimation in all models point

out a strong evidance of a negative relationship between working capital management and returm on assets. The

regression coefficients of control variables in all models are highly significant. Return on assets increases with size

of the firms as measured by natural logarithm of assets in both OLS and fixed effect estimation. In addition, return

on assets increases with GDP rate and firm’s growth. However, a negative and highly significant relationship

between debt ratio and firms profitability is found.

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6. Analysis for economic sectors

Different industries might select and use different working capital strategies. Weinraub & Visscher (1998)

and Filbeck & Krueger (2005) did argued that the industry effect on firms’ working capital policies are not similar,

which might be explained by variation in different trade credits or divergence in investment policies in inventories

across industries. To investigate the effect of cash conversion cycle on firm’s profitability in each industry, the

regression analysis was applied to each industry sector in the sample separately. Table 6 summarizes the result of

regression analysis between cash conversion cycle and return on assets for each industry. The results of both models,

OLS and fixed effects estimation, indicate the effect of industry on relationship between cash conversion cycle and

profitability. According to the OLS model, the results show a negative relationship between cash conversion cycle

and firms profitability in all sectors. Although the relationship between cash conversion cycle and return on assets

was significant in construction and material, and electronic sectors but there were no significant relationship

between cash conversion cycle and return on assets for the rest sectors (food producers, industrial engineering, and

technology hardware). With regard to control variables, the debt ratio significantly and negatively has correlated to

the return on assets in all sectors based on OLS regression. Moreover, there is a positive and significant relationship

between Sales Growth (SG) and CCC in all sectors except technology hardware sector, which was not significant

(P-vale 0.1656). The results also reveal that firm size positively correlated to the ROA in all sectors that means

larger firms relatively have greater returns. Finally, OLS regression point out a positive and significant relationship

between gross domestic products and return on assets in industrial engineering, and technology hardware sectors.

Moreover, the results of the fixed effect estimation show that there is a significant negative relationship

between working capital management and profitability in electronic (at 5% level), industrial engineering (at 1%

level), and technology hardware (at 10% level) sectors. We did not find a significant relationship between cash

conversion cycle and profitability in construction and material (P-value, 0.9333), and food producers (P-value,

0.8325) sectors. In all sectors, a significant and negative relationship between debt ratio and profitability, and a

significant and positive relationship between cash conversion cycle and return on investment was found. In addition,

the gross domestic product has positive relationship on profitability in all sectors, while this relationship was not

statistical significant in construction and material sector (P-value, 0.3120).

7. Conclusions

Working capital management is important because it affects both profitability and liquidity, and

consequently firm’s value. Management performance would be improved by managing working capital efficiently.

Applying panel data analysis including pooled OLS regression and fixed effect estimation we find that cash

conversion cycle negatively associated to the Return on Assets (ROA). These results show that managers can

improve their performance by managing working capital efficiently. All the components of cash conversion cycle

(receivable conversion period, inventory conversion period, and payable deferral period) have negative relationship

with profitability. These results demonstrate that firm’s profitability is increased by decreasing in receivable

conversion period and inventory conversion period. The negative relationship between payable conversion period

and profitability might stem from the fact that more lengthening of payable deferral period would damage firm’s

reputation, and consequently decrease profitability.

The results of industry analysis suggested the effect of economic sector on relationship between working

capital management and profitability. According to OLS regression, we find a negative and significant relationship

between cash conversion cycle and return on assets in construction and material, and electronic sectors. In addition,

based on fixed effect estimation, the negative and significant relationship between cash conversion cycle and return

on assets was found in electronic, industrial engineering, and technology hardware sectors. These results indicate

that industries would affect the relationship between profitability, and working capital management.

Several policy implications would be derived from the findings of the study. First, managers would improve their

performance, and increase firm profitability by shortening cash conversion cycle. Second, shortening receivable

conversion period, and inventory conversion period would result in increasing firm profitability. Third, more

shortening in payable conversion period would decrease firm profitability. Finally, the relationship between working

capital management and profitability would be affected by industry differences.

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One of the limitations of the study is related to the period of the study between 2004 -2011. We could not

collect the data for 2012 year. Moreover, we could not investigate other industries because of incomplete data.

Similar studies in other countries with different financial systems are suggested as future researches to

investigate the relationship between working capital management and profitability. However, different proxies for

working capital management, and different proxies for profitability can investigate by future researchers.

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Annexure

Exhibit 1 Cash Conversion Cycle procces

Source: Richards & Laughlin, (1980)

Table 1 Sample distribution for year 2004-2011

Economic sector Number of firms

Electronic (EL) 25

Construction & Material (CO & M) 19

Technology hardware (TH) 17

Industrial engineering (IE) 16

Food producers (FP) 15

Total 92

Table 2 summary of data measurement

Variables calculation symbol

Return on assets Net income/ total assets ROA

Receivables collection period Accounts receivables/ (sales/365) RCP

Inventory conversion period Inventories / (Cost of goods sold/365) ICP

Payable deferral period Accounts payable / (cost of goods sold/ 365) PDP

Cash conversion cycle RCP + ICP – PDP CCC

Firm size The natural logarithm of total assets SIZE

Leverage (Debts ratio) Total debts / total assets LEV

Sales growth (current year sales – previous year sales)/ previous year sales GROWTH

Gross domestic product Gross domestic product GDP

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Table 3 Eight years means and standard deviation for the variables

Variables

Economic Sectors

All EL CO TH IE FP

ROA Mean 0.029887 -0.0052 0.0858 -0.0246 0.0443 0.0639

Std.Dev 0.55334 0.2097 1.1628 0.2399 0.0974 0.1253

PDP Mean 79.37065 82.6245 96.1464 87.2487 78.2922 44.9201

Std.Dev 72.51898 50.2595 94.3417 104.0457 47.6213 24.8322

RCP Mean 103.2405 136.0950 115.4342 92.9191 91.2813 57.4917

Std.Dev 105.6709 177.3756 79.9924 43.3003 29.4048 28.2129

CCC Mean 134.209 149.8028 181.5660 79.1395 126.5493 118.8161

Std.Dev 204.0092 249.6902 289.5519 104.8429 124.8862 101.3084

LEV Mean 0.247016 0.2192 0.4736 0.1681 0.1749 0.1726

Std.Dev 1.125977 0.2127 2.4474 0.1500 0.1132 0.1730

GDP Mean 0.0545 0.0545 0.0545 0.0545 0.0545 0.0545

Std.Dev 0.0350 0.0350 0.0351 0.0351 0.0351 0.0351

ICP Mean 110.3391 96.3323 162.2782 73.4691 113.5602 106.2445

Std.Dev. 165.6501 120.7889 285.1430 54.2201 146.3696 101.7681

SIZE Mean 11.97915 11.6629 12.1033 11.8376 11.5868 12.9279

Std.Dev 1.396946 1.3608 1.4468 1.2734 0.9583 1.4822

GROWTH Mean 1.196954 0.2280 0.1278 0.1274 0.1698 6.4740

Std.Dev 25.99522 2.3522 0.6408 0.5946 0.3927 64.2640

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Table 4 profitability and Spearman correlation coefficients

Variables ROA APD ARD CCC DBT GDP ICP LNA SG

ROA 1.0000

-----

PDP -0.1190 1.0000

(0.0012) -----

RCP -0.2867 0.3806 1.0000

(0.0000) (0.0000) -----

CCC -0.1507 -0.1796 0.4155 1.0000

(0.0000) (0.0000) (0.0000) -----

LEV -0.1459 0.0232 0.0052 0.1160 1.0000

(0.0001) (0.5294) (0.8887) (0.0016) -----

GDP 0.1554 0.0430 -0.0447 -0.0894 0.0645 1.0000

(0.0000) (0.2439) (0.2258) (0.0153) (0.0805) -----

ICD -0.0906 0.1229 0.1533 0.7312 0.1832 -0.0425 1.0000

(0.0139) (0.0008) (0.0000) (0.0000) (0.0000) (0.2492) -----

SIZE 0.2318 -0.1294 -0.2710 -0.1191 0.1890 0.0038 -0.0920 1.0000

(0.0000) (0.0004) (0.0000) (0.0012) (0.0000) (0.9182) (0.0126) -----

GROWTH 0.2997 -0.1085 -0.1884 -0.1080 0.0188 0.0491 -0.0535 0.2139 1.0000

(0.0000) (0.003)2 (0.0000) (0.0033) (0.6115) (0.1837) (0.1470) (0.0000) -----

The p-value is given in parentheses

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Table 5 Regression for profitability on working capital management

Pooled OLS Fixed effect estimation

Model 1 Model 2 Model 3 Model 4 Model 1 Model 2 Model 3 Model 4

LEV -0.0943 -0.0924 -0.0909 -0.0947 -0.2331 -0.2651 -0.2024 -0.2082

(0.0000) (0.0000) (0.0000) (0.0000) (0.0000) (0.0000) (0.0000) (0.0000)

GROWTH 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002

(0.0170) (0.0182) (0.02060 (0.0211) (0.0000) (0.0000) (0.0000) (0.0000)

SIZE 0.0146 0.0142 0.0161 0.0167 0.0377 0.0362 0.0436 0.0457

(0.0000) (0.0000) (0.0000) (0.0000) (0.0019) (0.0005) (0.0000) (0.0000)

GDP 0.4547 0.4249 0.4703 0.4776 0.5771 0.5441 0.5893 0.5876

(0.0000) (0.0000) (0.0000) (0.0000) (0.0000) (0.0000) (0.0000) (0.0000)

CCC -0.0001 -0.0002

(0.0001) (0.0000)

RCP -0.0003 -0.0005

(0.0000) (0.0000)

ICP -0.0001 -0.0002

(0.0043) (0.0006)

PDP -0.0002 -0.0002

(0.0046) (0.0157)

R-squared 0.2008 0.2181 0.2004 0.1916 0.5192 0.5690 0.5215 0.5447

Adjusted R-squared 0.1909 0.2084 0.1905 0.1816 0.4469 0.5042 0.4496 0.4763

The p-value (robust for heteroscedasticity) is given in parentheses

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Table 6 Regression for profitability on each industry

Economic

Sector CCC Debt SG Size GDP R Adj.R

CO & M

OLS -0.0001 -0.0201 0.0458 0.0031 0.3000 0.2599 0.2398

(0.0000) (0.0000) (0.0062) (0.0250) (0.2913)

Fixed Effect 0.0000 -0.1609 0.0453 0.0515 0.2041 0.3338 0.2141

(0.9333) (0.0610) (0.0059) (0.0599) (0.3120)

EL

OLS -0.0004 -0.3228 0.0026 0.0071 0.7408 0.2785 0.2637

(0.0000) (0.0000) (0.6374) (0.0035) (0.0432)

Fixed Effect -0.0001 -0.3327 0.0032 0.2738 0.6773 0.6478 0.5877

(0.0242) (0.0002) (0.0755) (0.0001) (0.0133)

FP

OLS 0.0000 -0.1127 0.0003 0.0065 0.0370 0.1302 0.1000

(0.6963) (0.0104) (0.0026) (0.0000) (0.7693)

Fixed Effect 0.0000 -0.0559 0.0003 0.0150 0.1835 0.7766 0.7342

(0.8325) (0.1840) (0.0133) (0.0474) (0.0297)

IE

OLS -0.0001 -0.0154 0.0252 0.0046 0.1647 0.1315 0.1032

(0.2888) (0.7566) (0.0700) (0.0000) (0.2276)

Fixed Effect -0.0002 -0.2501 0.0124 0.0691 0.4143 0.6098 0.5369

(0.0030) (0.0002) (0.3375) (0.0000) (0.0003)

TH

OLS -0.0001 -0.2353 0.0333 0.0006 1.0657 0.2358 0.2125

(0.6106) (0.0012) (0.1656) (0.7525) (0.0000)

Fixed Effect -0.0001 -0.5831 -0.0178 0.1342 1.2087 0.6048 0.5320

(0.0590) (0.0000) (0.5300) (0.0004) (0.0000)

The p-value (robust for heteroscedasticity) is given in parentheses

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