Ass

Impact of Working Capital Management on Return of Shareholders: A Study on Lafarge Surma

Cement Ltd. in Bangladesh

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AssignmentOn

Working capital Management

Course code: FIN –

Topic: Impact of Working Capital Management on Return of Shareholders: A Study on Lafarge Surma Cement

Ltd. in Bangladesh

Prepared for

LecturerSchool of Business Studies

Southeast University

Prepared byKrishna Tithi KhanID:2007110000227

Batch – 16th Sec – 18(A)Semester – spring ‘11

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Date of submission: 28th April, 2011

SOUTHEAST UNIVERSITY

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Impact of Working Capital Management on Return of Shareholders: A Study on Lafarge Surma Cement Ltd. in

Bangladesh

Abstract

This study is designed to investigate the correlation between working capital management and the return of shareholders of the

Lafarge Surma Cement Ltd. and to justify whether the Profitability is affected by working capital management. Correlation Matrix

and Regression Analysis, with the help of SPSS, have been used to show correlation between working capital management and the

return of shareholders and the impact of working capital management on profitability respectively. For the source of data I mainly

relied on Annual Reports and official records as well as primary data collected through interview. It is observed from the study that

the managers of the company can create value for the shareholders by delaying payments to creditors and by reducing the credit

period granted to their customers, days inventory and cash conversion cycle to an optimum level.

Key Words: Profitability, Working Capital Management.

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Introduction:

A financial manager in any organization has to play three functions. Those functions are (i) the management of long-term assets, (ii) the

management of long-term capital and (iii) the management of short-term assets and liabilities. The management of short term assets and

liabilities refers to management of Working Capital (Khan, 2002). To produce the best possible returns, firm should keep no unproductive assets

and should finance with the cheapest available sources of funds. In general, it is often advantageous for the firm to invest in short-term assets and

to finance with short-term liabilities (Scherr, 2007). The management of working capital plays an important role in maintaining the financial

health of the firm during the normal course of business (Zariyawati, Annuar, Taufiq and Rahim, 2009).

A firm is required to maintain a balance between liquidity and profitability while conducting its day to day operations. Liquidity is a

precondition to ensure that firms are able to meet its short-term obligations and its continued flow can be guaranteed forms a profitable venture

(Padachi, 2006). Working Capital Management includes maintaining optimum balance of working capital components – receivable, inventory

and payables and using the cash efficiently for day-to-day operations. Optimization of working capital balance means minimizing the working

capital requirement and realizing maximum possible revenues (Ganesan, 2007). There is a strong relationship between the firm’s profitability

and its working capital efficiency (Shin, 1998; Dong and Su, 2010; Lazaridis and Tryforidis, 2006; Olufemi and Olubanjo, 2009, Gill, Biger and

Mathur, 2010).

Shareholders’ return often refers as the profitability. The term profitability refers to the ability (of a firm) to earn profit. Profit is determined by

matching revenue against cost associated with it (Salauddin, 2001). Profit of an enterprise in absolute figure gives an idea about the result of its

operation. Profitability is a widely used financial measure of performance. The concept of profitability may be used in two senses:

commercial/private profitability and public profitability. Although the use of public profitability which is based on economist’s notion of cost

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and benefits from social point of view, that is true opportunity cost and the benefits for the society as a whole, appears to be a more appropriate

measure of performance of public enterprises, the measure of commercial profitability has been used in this study.

This is because of the fact that commercial profitability is widely used to measure the performance of public enterprises in Bangladesh and even

in other countries of the world like India, UK, and France etc. and also for its general acceptance and ready understandability. Two major types

of profitability ratios are computed: (i) Profitability in relation to sales and (ii) Profitability in relation to investment. Gross Profit Margins

(GPM), Net Profit Margin (NOM), Return on Total Assets (ROTA), Return on Equity (ROE), and Return on Investment (ROI) are the main

measure of profitability. Therefore, profit is an absolute measure and profitability is a relative measure of efficiency of the operations of an

enterprise.

The researcher has used correlation matrix and regression analysis to examine the relationship between profitability and working capital

management. Some statistical tools like mean, standard deviation were also used to evaluate the performance.

Objectives of the study:

The major objective of the present study is to examine and evaluate the correlation between working capital management and shareholders’

return in Lafarge Surma Cement Ltd. over a period of five years from 2005 to 2009. The specific objectives of the study are as follows:

i. To assess the relationship between working capital management and shareholders’ return.

ii. To show the impact of working capital management on the return of shareholders.

iii. To suggest some measures for improvement in working capital management.

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Literature Review:

In attention to discover the relationship between working capital management and firms’ profitability, Zariyawati, Annuar, Taufiq and Rahim

(2009) used 1628 firm-year observations from listed firms in Bursa Malaysia to examine the relationship between working capital management

and firm profitability. They used cash conversion cycle as measure of working capital management. They found strong negative significant

relationship between cash conversion cycle and firm profitability.

Sayaduzzaman (2006) in his article on “Working capital management: A study on British American Tobacco Bangladesh Company Limited”

mentioned that the efficiency of working capital management of British American Tobacco Bangladesh Company Ltd. is highly satisfactory due

to the positive cash inflows, planned approach in managing the major elements of working capital. He found that working capital management

helps to maintain all around efficiency in operations.

Gill, Biger and Mathur (2010) researched the relationship between working capital management and profitability by using 88 American firms

listed on New York Stock Exchange fro a period from 2005 to 2007. They found statistically significant relationship between the cash

conversion cycle and profitability measured through gross operating profit. They also concluded that manager can create profits for their

company by handling correctly the cash conversion cycle and by keeping accounts receivable at an optimal level.

In the article “Liquidity-Profitability Tradeoff: An Empirical Investigation in an Emerging Market” Eljelly (2004) examined the relation between

profitability and liquidity by using correlation and regression analyses and found that the cash conversion cycle was of more importance as a

measure of liquidity than the current ratio that affects profitability.

Raheman (2007) studied the effect of different variables of working capital management including the Average Collection Period, Inventory

Turnover in Days, Average Payable Period, Cash Conversion Cycle and Current Ratio on the Net Operating Profitability of Pakistani Firms. By

using Pearson’s correlation and regression analysis he found that there was a strong negative relationship between variables of working capital

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management and profitability. He also found that as the cash conversion cycle increases it will lead to decrease in profitability of the firm and

managers can create a positive value for the shareholders by reducing the cash conversion cycle to a possible minimum level.

In the article “Working Capital Management and Corporate Profitability: Evidence from Panel Data Analysis of Selected Quoted Companies in

Nigeria”, Olufemi and Olubanjo examined the effects of working capital management on profitability performance for a panel made up of a

sample of Nigerian quoted non-financial firms for the period 1996-2005. The study revealed that there was a significant negative relationship

between net operating profitability and the average collection period, inventory turnover in days, average payment period and cash conversion

cycle.

Islam & Rahman (1994) conducted a study on working capital trends of enterprises in Bangladesh. They found that optimum working capital

enables a business to have its credit standing and permits the debts payments on maturity date and helps to keep itself fairly in liquid position

which enables the business to attract borrowing from the banks.

Deloof (2003) surveyed on Belgian Firms to find out whether the working capital management affects profitability. He found that most firms had

a large amount of cash invested in working capital. It can be expected that the way in which working capital is managed will have a significant

impact on the profitability of those firms. Using correlation and regression tests he found a significant negative relationship between corporate

profitability and number of days accounts receivable, inventories and accounts payable of Belgian firms. On the basis of these he suggested that

manager could increase corporate profitability by reducing the number of days accounts receivable and inventories to a reasonable minimum.

The negative relationship between accounts payable and profitability is consistent with the view that less profitable firms wait longer to pay their

bills.

Padachi (2006) found in his research study that a firm is required to maintain a balance between liquidity and profitability while conducting its

day to day operations. The manager of a business entity is in a dilemma of achieving desired trade-off between liquidity and profitability in order

to maximize the value of a firm.

Lazaridis and Tryfonidis (2006) investigated relationship between working capital management and corporate profitability of listed companies in

the Athens Stock Exchange. The results of the article showed that there was a statistically significant relationship between profitability and the

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cash conversion cycle. Moreover manager could create profits for their companies by handling correctly the cash conversion cycle and keeping

each different components (accounts receivables, accounts payables, inventory) to an optimum level.

Ganesand (2007) suggested that efficient working capital management increases firms’ free cash flow, which in turn increased the firms’ growth

opportunities and return to shareholders.

Chowdhury and Amin (2007) work an article on “Working Capital Management Practices in Pharmaceutical Companies Listed in DSE”. Among

all the problems of financial management the problems of working capital management have probably been recognized as the most crucial one.

It is because of the fact that working capital always helps a business concern to gain vitality and life strength and to maximize profit.

Shin and Soenen (1998) suggested that efficient working capital management was very important for creating value for the shareholders. The

way working capital was managed had a significant impact on both profitability and liquidity. Using correlation and regression analysis they

justified the relationship between the length of net trading cycle, corporate profitability and risk adjusted stock return. They found a strong

negative relationship between lengths of the firm’s net trading cycle and its profitability. In addition, they also found that shorter net trade cycles

were associated with higher risk adjusted stock returns.

Methodology:

Data Collection:

Data were obtained from Lafarge Surma Ltd. which is enlisted in Dhaka Stock Exchange in Bangladesh. The study covered a period of five

years from 2006 to 2009. This study was based on both primary and secondary data. The primary data were collected through personal interview

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with officials of the company under study. Secondary time series data were taken to see the link between profitability and working capital

management. For that the published annual reports of the selected company for the study period were considered. Moreover extensive literature

survey was done by searching different libraries.

Variables:

The variables used in this study based on previous researches about the relationship between working capital and profitability. Net profit margin

(NPM) that is measure of profitability of firm and return on total assets (ROTA) that is measure of overall profitability are used as dependent

variables.

Number of days accounts receivable (ARD) used as proxy for the collection policy is an independent variable. Number of days inventories used

as proxy for the inventory policy is an independent variable. Number of days accounts payable used as proxy for the payment policy is an

independent variable. The cash conversion cycle used as a comprehensive measure of working capital management is another independent

variable. Various studies have utilized the control variables along with the main variables of working capital in order to have an opposite

analysis of working capital management on the firm’s profitability (Deloof,2003; Lazaridis and Tryfonidis, 2006; Dong and Su, 2010; Gill,

Biger and Mathur, 2010). The logarithm of sales used to measure size of a firm is control variable. In addition financial debt ratio used as proxy

for leverage and ratio of fixed financial assets to total assets are also control variables in the regression.

The collected data were analyzed and interpreted with the help of different financial ratios, statistical tools like Mean, Standard Deviation (S.D.)

and Correlation Coefficient etc. With the help of SPSS, Correlation Matrix and Regression analysis were also forced out for analysis.

Variables used in the analysis can be calculated as follows:

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Table 1

Variables Abbreviation FormulaNumber of days accounts receivable

ARD Average of accounts receivable/ Sales*365

Number of days inventory INVD Average of inventory/Cost of goods sold*365Number of days accounts payable

APD Average of accounts payable/ Cost of goods sold*365

Cash conversion Cycle in days CCCD ARD + INVD – APDFixed financial assets ratio FFAR Fixed financial assets/ Total assetsFinancial debt ratio FDR Financial debt/ Total assetsNatural logarithm of sales LNSALES ln (sales)Net profit margin NPM Net profit/ SalesReturn on total assets ROTA Profit before interest and taxes/ Total assets

Findings and Discussions:

This section has three parts. The first part of the section showed the descriptive statistics. The second part focused on correlation between

shareholders’ return and working capital management and the last part showed the impact of working capital management on the return of

shareholders.

Descriptive Statistics:

Table 2 provides descriptive statistics of the collected variables from the company (Lafarge Surma Company Ltd.) which is enlisted in the Dhaka

Stock Exchange for a period of five years from 2006 to 2009 and for a total 90 firms-year observations. All variables were calculated using

balance sheet (book) values. The book value was used because the company did not provide any market value related to the variables that are

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used in this study. When market values are considered in such studies, there is always a legitimate question of the date for which the market

values refer. Hence, I relied on book values as of the date of the financial reports

Table 2: Descriptive Statistics (N=90)

Descriptive Statistics

N Minimum Maximum Mean Std. Deviation

ARD 4 2.20 30.68 12.8158 12.70042

INVD 4 66.56 1386.45 414.9226 648.22621

APD 4 32.77 787.61 236.9005 367.46647

CCCD 4 27.62 629.52 190.8379 293.03759

FFAR 4 .07 .11 .0899 .01759

FDR 4 .07 .76 .5330 .31454

LNSALES 4 12.49 16.35 15.0809 1.78014

GPM 4 .16 .49 .3045 .15716

NPM 4 -1.44 .06 -.3779 .71572

ROE 4 -.24 .15 -.0147 .18648

ROTA 4 -.07 .06 .0099 .05979

CASALES 4 .18 5.55 1.5733 2.65233

CLTA 4 .17 .42 .3277 .11380

Valid N (listwise) 4

Source: Annual Report and Official Records of Lafarge Surma Cement Ltd. (2006 to 2009)

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From the table2, it is seen that the average value of net profit margin is-37.79 % and standard deviation is 71.51%. This figure means that the

value of net profit can deviate from mean to both sides by 71.51%. The maximum and minimum values of gross profit margin are 1% to 62%

respectively. The overall profitability measured by return on total assets has a mean of 1% and standard deviation of 5.97% which indicates that

the value of return on total assets can deviate from mean to both sides by 5.97%. The maximum and minimum values of return on total assets are

6% to 7% respectively.

The mean of cash conversion cycle that used as a proxy to check the efficiency in managing working capital is 190.83 days and standard

deviation is 293.93.97days. The average of number of days accounts receivable is 12.81 days with standard deviation of 12.70 days. . Minimum

time taken by a cement company to collect cash from customers is 2.20 days while the maximum time for this purpose is 30.68days. The average

time of paying to suppliers is 236.90 days and the standard deviation is 367.67 days. Maximum time taken from firm to pay their suppliers is 287

days while minimum time taken for this purpose is 32.77days. Moreover, it takes an average 787.61days in order to sell inventory with standard

deviation of 107.58 days. Maximum time taken by a firm is 482 days, while minimum time to convert inventory into sales is 119 days.

Natural logarithm of sales that measure the size of the firm is used as a control variable. From Table 2 it can be seen that the mean of logarithm

of sales is 15.08 and standard deviation is 1.79. The maximum value of log of sales for a firm in a year is 16.35 while the minimum value is

12.47. Debt ratio is used to check the relationship between debt financing and the profitability. It is also used as a control variable. The result of

descriptive statistics indicates that the average of debt ratio is 53.30% with standard deviation of 31.45%. The maximum debt ratio financing

used by a firm is 76% which is unusual because of debt larger asset. However, it is also possible if the equity of the firm is negative. While the

minimum of debt ratio is 7%, this means that there is a company that uses a little debt in its operation.

Finally, the fixed financial assets to total assets ratio is used to check the ratio of fixed financial assets to the total assets of company of

Bangladesh. It is also utilized as a control variable. The mean value for this ratio is 8.99% with a standard deviation of 1.75%. The maximum

value of financial assets to total assets is 11% and the minimum value for this purpose is 7%.

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Correlation Analysis:

The correlation between working capital management and return of shareholders of Lafarge Surma Cement Ltd. can be assessed through

Pearson’s Correlation Coefficient. The following Table 3 shows the relationship between the efficiency of working capital position and

profitability of company for the study period. The efficiency of working capital has been shown through the current ratio (CR), accounts

receivable days (ARD), inventory days (INVD), accounts payable days (APD) and cash conversion cycle days (CCCD) of the company. The

profitability position has been shown through net profit margin (NPM) and return on total assets (ROTA).

Table: 3

Pearson Correlation Coefficient on Efficiency in Working Capital and Profitability, 2005-2009: Years Observations

ARD INVD APD CCCD FFAR FDR LNSALES GPM NPM ROE ROTA CASALES CLTAARD 1 .951 .951 .955 -.456 -0.935 -.862 -.634 -.833 0.006 .037 .935 -.796INVD 1 1 1 -.706 -.982 -966 -.631 -.982 -.247 -.192 .999 -.922APD 1 .999 -.704 -.985 -.962 -.645 -.980 -.236 -.178 .998 -.916CCCD 1 -.699 .977 -.968 -.613 -.982 -.251 -.199 .998 -.925FFAR 1 .668 .831 .275 .819 .789 .713 -.741 .872FDR 1 .912 .766 .947 .131 .057 -.978 .851LNSALES 1 .447 .995 .487 .440 -.976 .991GPM 1 .534 -.371 -.478 -.615 .338NPM 1 .422 .365 -.990 .975ROE 1 .991 -.292 .597ROTA 1 -.234 .556CASALES 1 -937CLTA 1

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It is seen from the table 3 that accounts receivable days has a negative correlation with net profit margin (--.833) and return on total assets (.037). The relation between accounts receivable days and net profit margin is statistically significant at 1% level of significance. This means that if

number of days accounts receivable increase then net profit margin and return on total assets decrease and vice versa. The number of days

inventory has a negative relation with net profit margin (-.982) and return on total assets (-.192). But these relations are not statistically

significant. The relation states that if the number of days inventory increase then net profit margin, return on equity and return on total assets

decrease and vice versa.

It has been found that the number of days accounts payable has a negative relation with the net profit margin ( -.980) and return on total assets

(-.916). The relation between the number of days accounts payable and return on total assets is statistically significant at 5% level. The relation

implies that if the number of days accounts payable increase return on total assets increase and vice versa. It is also revealed from the table that

the cash conversion cycle has negative relation with net profit margin (-.982) and return on total assets (-.925). The relation between cash

conversion cycle and return on total assets is statistically significant at 5% level. Result of analysis also shows a positive significant correlation

between natural logarithm of sales that is used to measure the size of a firm and net profit margin (.995). The natural logarithm of sales has a

positive correlation with return on total assets (.440) which is not statistically significant. It shows that as size of the firm increases, it will

increase net profit margin and it will increase return on total assets.

The earnings in terms of sales can be assessed through the profit margin. Net profit margin reveals the overall profitability of the concern, that’s

why it is very useful to the proprietors and prospective investors. It also indicates management efficiency in manufacturing, administrating and

selling of the products. Return on total assets is calculated to measure the profit after the tax against the amount invested in total assets to

ascertain whether assets are being utilized properly or not. Therefore, to conclude it can be said from the analysis that the overall profitability

(return on total assets) and net profit margin (NPM) can be increased by decreasing accounts receivable days, inventory days and cash

conversion cycle in days and by delaying payments to creditors.

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Multiple Regression Analysis:

In this section it has been constructed a model that indicates the impact of working capital policy on the return on shareholders. Return on

shareholders can be measured by NPM (net profit margin) and overall profitability ROA (Return on Total Assets) of the company. For this

purpose the secondary time series data have been used. In this model an attempt has been made to trace out the impact of overall working capital

policy on the shareholders’ return. In the study, it was selected a number of variables to construct the model and finally settled with the

following best variables on the basis of their partial correlation coefficient. Thus the model is:

Y=f (ARD, APD, INVD, CCCD, FFAR, FDR, LNSALES)

Yit=β0+β1ARDit+β2FFARit+β3FDRit+ β4LNSALES+єit

Yit=β0+β1INVDit+ β2FFARit+β3FDRit+ β4LNSALES+єit

Yit=β0+β1APDit+ β2FFARit+β3FDRit+ β4LNSALES+єit

Yit=β0+β1CCCDit+ β2FFARit+β3FDRit+ β4LNSALES+єit

Where, Y= NPM, ROTA

Where, the subscript i denoting Lafarge Surma Cement Ltd. company ranging from 1 to 18 and t denoting years (time series dimension) ranging

from 1 to 5. The variables are NPM, ROTA, ARD, APD, INVD, CCCD, FFAR, FDR, and LNSALES. In the model NPM and ROTA are the

dependent variables. ARD, INVD, APD and CCCD are independent variables.

While, FFAR, FDR and LNSALES are used as control variables.

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After applying partial correlation coefficient the model is:

When Y= NPM

NPMit=-5.200-ARDit+2.1520.086FFARit+0.600FDRit+0.2861LNSALES+єit

NPMit=-0.338-0.001INVDit+9.549FFARit-0.718FDRit+LNSALES+єit

NPMit=-3.320+0.000APDit+4.854FFARit+FDRit+ 0.180LNSALES+єit

NPMit=-0.650-0.002CCCDit+10.376FFARit-0.391FDRit+LNSALES+єi

Table: 4 Model Summaryb

Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

Change Statistics

Durbin-Watson

R Square

Change F Change df1 df2 Sig. F Change

1 1.000a 1.000 . . 1.000 . 3 0 . 1.623

a. Predictors: (Constant), CLTA, GPM, ROE

b. Dependent Variable: NPM

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The adjusted R-square of the model indicates 100% variation in NPM of Lafarge Surma Cement Ltd. company can be explained by the

regression model. The unexplained part of the model is the error term. The Durbin-Watson test indicates that there exists no auto-correlation in

the model where the value of D-W statistic= 1.623

Table:5 Coefficientsa

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig.

Collinearity Statistics

B Std. Error Beta Tolerance VIF

1 (Constant) -5.200 .000 . .

FFAR 2.152 .000 .053 . . .261 3.839

LNSALES .286 .000 .711 . . .079 12.683

FDR .600 .000 .263 . . .141 7.079

a. Dependent Variable: NPM

The above table 5 indicates the coefficient of the regression equation. From the table it can also be inferred that the variables have a coefficient

that are not statistically significant at d.f. =17. Another thing is that the variables in the model are free from Multicollinearity.

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Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

Change Statistics

Durbin-Watson

R Square


1 1.000a 1.000 . . 1.000 . 3 0 . 1.925

a. Predictors: (Constant), INVD, FFAR, FDR






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Coefficientsa

Model


Standardized

Coefficients

t Sig.



1 (Constant) -.338 .000 . .

FFAR 9.549 .000 .235 . . .483 2.070

FDR -.718 .000 -.315 . . .035 28.818

INVD -.001 .000 -1.126 . . .031 31.856



that are not statistically significant at d.f. =17. Another thing is that the variables in the model are free from Multicollinearity.


Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

Change Statistics

Durbin-Watson

R Square


1 1.000a 1.000 . . 1.000 . 3 0 . .567

a. Predictors: (Constant), APD, FFAR, LNSALES


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the model where the value of D-W statistic= .567

Table:9 Coefficients

Coefficientsa

Model


Standardized

Coefficients

t Sig.



1 (Constant) -3.320 .000 . .

FFAR 4.854 .000 .119 . . .188 5.331

LNSALES .180 .000 .449 . . .028 35.944

APD .000 .000 -.465 . . .045 22.039



that are not statistically at d.f. =17. Another thing is that the variables in the model are free from Multicollinearity.


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Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

Change Statistics

Durbin-Watson

R Square


1 1.000a 1.000 . . 1.000 . 3 0 . 1.779

a. Predictors: (Constant), CCCD, FFAR, FDR


The adjusted R-square of the model indicates 100% variation in NPM of Pharmaceutical industry can be explained by the regression model. The

unexplained part of the model is the error term. The Durbin-Watson test indicates that there exists no auto-correlation in the model where the

value of D-W statistic= 1.779


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Coefficientsa

Model


Standardized

Coefficients

t Sig.



1 (Constant) -.650 .000 . .

FFAR 10.376 .000 .255 . . .506 1.976

FDR -.391 .000 -.172 . . .046 21.861

CCCD -.002 .000 -.971 . . .042 23.700



that are not statistically d.f. =17. Another thing is that the variables in the model are free from Multicollinearity.

When Y= ROTA

ROTAit=-0.160- 0.007ARDit+5.710FFARit-0.472FDRit+LNSALES+єit

ROTAit=0.089+0.000INVDit+ 3.413FFARit-0.556FDRit+LNSALES+єit

ROTAit=-1.780+0.000APDit+0.655FFARit+FDRit+ 0.107LNSALES+єit

ROTAit=0.035+-0.00CCCDit+3.558FFARit-0.499FDRit+LNSALES+єit


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Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

Change Statistics

Durbin-Watson

R Square


1 1.000a 1.000 . . 1.000 . 3 0 . 1.059

a. Predictors: (Constant), ARD, FFAR, FDR

b. Dependent Variable: ROTA

The adjusted R-square of the model indicates 100% variation in ROTA of Lafarge Surma Cement Ltd. company can be explained by the




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Coefficientsa

Model


Standardized

Coefficients

t Sig.



1 (Constant) -.160 .000 . .

FFAR 5.710 .000 1.680 . . .330 3.028

FDR -.472 .000 -2.484 . . .053 18.986

ARD -.007 .000 -1.519 . . .075 13.282

a. Dependent Variable: ROTA




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Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

Change Statistics

Durbin-Watson

R Square


1 1.000a 1.000 . . 1.000 . 3 0 . 1.854

a. Predictors: (Constant), INVD, FFAR, FDR





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Coefficientsa

Model


Standardized

Coefficients

t Sig.



1 (Constant) .089 .000 . .

FFAR 3.413 .000 1.004 . . .483 2.070

FDR -.556 .000 -2.923 . . .035 28.818

INVD .000 .000 -2.352 . . .031 31.856





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Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

Change Statistics

Durbin-Watson

R Square


1 1.000a 1.000 . . 1.000 . 3 0 . 1.237

a. Predictors: (Constant), APD, FFAR, LNSALES






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Coefficientsa

Model


Standardized

Coefficients

t Sig.



1 (Constant) -1.780 .000 . .

FFAR .655 .000 .193 . . .188 5.331

LNSALES .107 .000 3.188 . . .028 35.944

APD .000 .000 3.024 . . .045 22.039





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Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of the

Estimate

Change Statistics

Durbin-Watson

R Square


1 1.000a 1.000 . . 1.000 . 3 0 . 1.351

a. Predictors: (Constant), CCCD, FFAR, FDR




the model where the value of D-W statistic=1.351


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Coefficientsa

Model


Standardized

Coefficients

t Sig.



1 (Constant) .035 .000 . .

FFAR 3.558 .000 1.047 . . .506 1.976

FDR -.499 .000 -2.623 . . .046 21.861

CCCD .000 .000 -2.029 . . .042 23.700




Conclusion:

Considering the coefficients and their significance level it can be concluded that in Lafarge Surma Cement Ltd., Number of days accounts

receivable (ARD), Number of days inventory (INVD), Number of days accounts payable (APD), Cash conversion Cycle in days (CCCD), Fixed

financial assets ratio (FFAR), Financial debt ratio (FDR), Natural logarithm of sales (LNSALES) play an important role in determining the

company’s Net profit margin (NPM), overall profitability Return on Total Assets (ROTA).

From the correlation matrix it is clear that there is negative correlation between working capital efficiency and profitability ratios of the selected

Firm with some exception where the correlation is positive. It can be concluded from the correlation matrix the net profit margin and return on

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total assets can be increased by collecting cash from credit sales as early as possible and by reducing days inventory and by reducing cash

conversion cycle at minimum possible level. On the other hand the net profit margin and return on total assets can be increased by delaying

payments to the creditors. From the regression model for NPM it is seen that the coefficients of ARD, INVD and CCCD are negative and the

coefficient is positive for APD which is consistent with the correlation matrix. It is also revealed from the regression model of ROTA, the

coefficients of ARD, INVD and CCCD are negative and the coefficient of APD is positive. This is evident from the study that the manager of

Lafarge Surma Comapany can create value for their shareholders by reducing accounts receivable days, inventory days and cash conversion

cycle days and by increasing accounts payable days.

References

YEARS ARD INVD APD CCCD FFAR FDR LNSALES GPM NPM ROE ROTA CASALES CLTA

2006 30.68 1386.45 787.6 629.52 7.05% 6.96% 12.49 15.58%-

143.82% -9.15% -0.95% 555.09% 16.88%

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2007 2.1 66.55 32.77 35.98 8.175 75.53% 15.36 48.76% -18.26% -24.19% -6.61% 31.57% 32.26%2008 12.78 127.86 70.42 70.22 11.10% 69.63% 16.12 38.18% 6.32% 15.23% 5.33% 24.32% 40.0452009 5.5 78.82 56.8 27.62 9.63% 61.06% 16.35 19.27% 4.60% 12.26% 6.17% 18.32% 41.87%

1. Number of days accounts receivable (ARD)= Average of accounts receivable/ Credit Sales*365

2. Number of days inventory (INVD)= Average of inventory/Cost of goods sold*365

3. Number of days accounts payable (APD)= Average of accounts payable/ Cost of goods sold*365

4. Cash conversion Cycle (CCCD) in days= ARD + INVD – APD

5. Fixed financial assets ratio (FFAR)= Fixed financial assets/ Total assets

6. Financial debt ratio (FDR)= Financial debt/ Total assets

7. Natural logarithm of sales (LNSALES)= ln (sales)

8. Gross profit margin (GPM)= Gross profit/ Sales

9. Net profit margin (NPM)= Net profit/ Sales

10. Return on equity (ROE)= Net profit after tax/ Equity

11. Return on total assets (ROTA)= Profit before interest and taxes/ Total assets

12. Current Assets to Sales (CASALES)= Current Asset/ Sales

13. Current Liabilities to Total Assets (CLTA)= Current Liabilities to Total Assets

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Notes:

What Does Financial Asset Mean?

An asset that derives value because of a contractual claim. Stocks, bonds, bank deposits, and the like are all examples of financial assets.

Financial Assets include cash and bank accounts plus securities and investment accounts that can be readily converted into cash. Excluded are

illiquid physical assets such as real estate, automobiles, art, jewelry, furniture, collectibles, etc., which are included in calculations of Net

Worth. A financial asset is an intangible representation of the monetary value of a physical item. It obtains its monetary value from a

contractual agreement of what it represents. While a real asset, such as land, has physical value, a financial asset is a document that has no

fundamental value in of itself until it is converted to cash. Common types of financial assets include certificates, bonds, stocks, and bank

deposits.

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http://www.wisegeek.com/what-is-a-real-asset.htm

http://financecareers.about.com/od/jp/g/Net-Worth.htm

http://financecareers.about.com/od/jp/g/Net-Worth.htm

http://financecareers.about.com/od/financialadvisor/a/Art.htm

Ass

Documents

working capital requirement

firms profitability

term profitability

concept of profitability

main measure of profitability

management of longterm

use of public profitability

return of shareholders