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Journal of Business Studies, Vol. XXXV, No. 1, April 2014
Impact of Working Capital Management on Firm’s
Profitability: Evidence from the Fuel and Power
Companies Listed on the Dhaka Stock Exchange
Shabnaz Amin*
Mohammad Anisul Islam**
Abstract: This study investigated the impact of working capital management on the
profitability of fifteen listed fuel and power companies in Bangladesh. The ratios
used for this study to measure the working capital efficiency included time interest
ratio (TIE), quick ratio (QR), cash conversion cycle (CCC), accounts receivables
collection period (ARCP), accounts payable payment period (APP), inventory
processing period (IPP), cash to current liability (CCL), cash to sales (CTS) ratios
and net working capital (NWC) turnover and debt to equity ratio (D/E). The
corporate profitability was measured by return on assets (ROA) and net profit
margin (NPM). The data were collected from the annual reports of the companies
from 2007 to 2011. Analysis of multiple regression and correlation matrix reveals
that measurable association exists between the dependent and selected independent
variables. NPM and TIE showed significant positive relations with ROA while CCL
and accounts payables payment period (APP) showed a significant positive
influence on NPM and D/E exhibited significant negative influence on NPM.
Keywords: Working Capital, Profitability, Cash Conversion Cycle, Average days of
collection period, Inventory turnover period, Deferred payables Period, Efficiency
ratio, Net working capital turnover.
Introduction
The importance of impact of working capital management on firms’ profitability is a
critical issue to conceive. In this study, fifteen fuel and power companies of Bangladesh
listed in Dhaka Stock Exchange (DSE) were selected to assess the relationship among the
working capital efficiency indicators and the profitability measures of the companies.
Dependency of profitability ratios over working capital components and liquidity
positions of these companies was figured out to justify the necessity of efficient working
capital management. Working Capital is the third critical decision field of corporate
financial management where proper concentration by management is essential. Working
* Assistant Professor, Department of Finance, University of Dhaka
** Erstwhile Intern, Research Division, Lanka Bangla Securities Limited
178 Journal of Business Studies, Vol. XXXV, No. 1, April 2014
Capital is intimately related to current account which basically measures the amount of
current assets and current liabilities of a firm. Working Capital can be defined as capital
required for maintaining day-to-day operations of the company. Companies need to
manage working capital as effectively as possible by financing or investing activities, so
that the optimum level of working capital can be maintained.
Profitability ratios like net profit margin, return on equity and return on assets are
commonly used ratio to measure efficiency and effectiveness of a particular company’s
operation. Increasing the efficiency of working capital is one of the ways to achieve
higher profitability. In connection with this, there are a number of ratios that can be used
to measure the efficiency of working capital of a company [(Hayajneh and Yassine
(2011)]. The first ratio is related to the liquidity factor of the company. Liquidity is
defined as the ability of the company to meet its financial obligations. Current ratio (as
one of the indicators of the company’s liquidity position) measures the company's ability
to meet its short term debts. Generally, the current ratio of two is satisfactory for the
company. Current ratio is too high when it indicates the presence of excess working
capital compared to what is needed presently. If this occurs, it is likely to create idle
funds and an increase in opportunity cost, such as storage costs and maintenance costs,
which in turn, also decrease the profitability and vice versa.
Another factor is the receivable turnover which measures the number of times the
average receivables are turned over during a year. The higher this ratio, the better it is
because it shows that the working capital invested in the form of receivables, is collected
at a rapid pace. This will have an impact on the increase in the profitability.
The third factor is the net working capital turnover. It measures the amount of sales
revenue earned for each company's net working capital. Net working capital is the
difference of current assets to current liabilities. The higher this ratio the better it is, as it
indicates that the company has been effective in managing net working capital. This will
naturally have a positive impact on the profitability. Based on the above arguments and in
line with the thinking of Hayajneh and Yassine (2011) paper, this study attempts to assess
the relationship between firm’s profitability and working capital management efficiency
to prove that the greater the working capital efficiency ratio, the more efficient
management of current assets by an enterprise to generate profit.
Impact of Working Capital Management on Firm’s Profitability: Evidence from the Fuel 179
Table 1: Comparison of Working Capital Ratio and Profitability Ratio over the
years
Variables/Period 2007 2008 2009 2010 2011
Current Ratio 1.74 1.79 1.83 2.13 1.99
Cash Conversion Cycle 338.27 297.76 350.87 48.60 66.05
Net Working Capital Turnover 16.44 15.10 13.62 -91.31 9.15
Return on Assets 5.31% 5.33% 6.76% 9.13% 9.12%
Net Profit Margin 13.98% 19.47% 18.93% 19.65% 19.30%
Source: Annual Reports of the selected companies in fuel and power sector of Bangladesh
Table 1 shows the key variables that are chosen to get a glimpse of the overall
performance of fuel and power sector of Bangladesh from 2007 to 2011. The fuel and
power industry’s current ratio had an increasing trend for last 4 years from 2007 to 2010
and it reached at 2.13 in 2010 and in 2011 it reached at standard level of two
approximately. In addition, cash conversion cycle showed a declining trend which is
undoubtedly a good indicator for working capital efficiency. ROA of the companies
increased to maximum 9.13 percent and 9.12 percent in 2010 and 2011 respectively. With
the decrease in cash conversion cycle over the last 5 years and increase in net profit
margin and return on assets over the period from 2007 to 2011, it can be said that overall
the industry performed well in terms of working capital management.
Overview of Fuel and Power Sector of Bangladesh
The Government of Bangladesh through the Ministry of Energy and Mineral Resources
(MEMR) bears overall responsibility for the power sub-sector in Bangladesh.
Consumption of commercial energy per head in Bangladesh is one of the lowest in Asia,
if not the world. A lack of commercially priced sources of electricity has been a major
factor in deterring foreign investment hindering GDP growth. Bangladesh Power
Development Board (BPDB) website shows that the country had 4,942 MW (with a
maximum generation capacity of 3,268 MW) installed power generation capacity on
January 6, 2009 and per capita electricity generation increased from 110 kWh in 1997-98
to 321 kWh per annum (including captive generation) in 2013. With about 62% of
households receiving electricity, most commercial energy is consumed by industrial and
residential customers. Bangladesh's installed electric generation capacity has increased
significantly from 4,942 MW in 2009 to 10,000 MW in October 2013. As the installed
180 Journal of Business Studies, Vol. XXXV, No. 1, April 2014
power generation facilities are now able to generate 6,000 MW of power consistently,
regular power outage for prolonged periods has been reduced significantly. If fuel supply
could be secured, additional 1,000 plus megawatt electricity could be generated (Source:
BPDB). There has been a reduction of natural gas-based power generation capacity to
nearly 68% (6,587 MW) and increase in imported fuel oil based power generation to
nearly 26% in 2013. The share of hydroelectricity and coal-fired power generation
remains limited within 5%. Bangladesh became grid connected with Indian power
transmission line for the first time from October 5, 2013, and 250 MW power has been
imported to our grid. It is expected that within the next few weeks 250 MW more
electricity would start to flow from Indian to Bangladeshi power networks (Source: The
Daily Star November 13, 2013).
Table: 2 Power Sector of Bangladesh at a glance
Sl. No. Items As of December 2013
1 Generation Capacity, MW 10,264 MW
2 Maximum Generation, MW 6080 MW
3 Net Generation, MkWh (FY 2012-September 2013) 47,357
4 Transmission Line (Ckt KM) 9,300
5 Distribution Line (KM) 290,000
6 Total Consumers (Million) 14.2
7 Per Capita Generation, KWH 321
8 Access to Electricity 62%
Source: Bangladesh Power Development Board (BPDB) website: http://www.bpdb.gov.bd/bpdb/
Until February 2013, 15 fuel and power companies have been listed in Dhaka and
Chittagong Stock Exchanges under fuel and power sector. These companies are leading
companies in fuel and power industry of Bangladesh. Although there are significant
differences among these companies in terms of ownership, business model, capital
structure, business operation and so forth. The Dhaka Stock Exchange has listed all these
companies in the same category. Table 3 states the category and the year of listing of
these companies.
Impact of Working Capital Management on Firm’s Profitability: Evidence from the Fuel 181
Table 3: List of Selected Companies by their Market Category and Listing Year
Companies Market
Category Listing
Year
Linde Bangladesh Limited A 1976
Eastern Lubricants A 1976
Padma Oil Company A 1976
Bd. Welding Electrodes B 1999
Summit Power A 2005
Dhaka Electric Supply Company Ltd. A 2006
Power Grid Company of Bangladesh Ltd. A 2006
Meghna Petroleum Limited A 2007
Jamuna Oil Company Limited A 2007
Titas Gas Transmission and Distribution Company Ltd. A 2008
Khulna Power Company Limited A 2010
Mobil Jamuna A 2011
Barakatullah Electro Dynamics Ltd. A 2011
GBB Power Ltd. A 2012
Summit Purbanchol Power Company Limited N 2013
Source: www.dsebd.org
Performance of Fuel and Power Companies
Table 4 summarizes the performance of listed fuel and power companies in terms of
average return on assets (ROA), average net profit margin (NPM), and average sales
growth of each incumbent company for the study period from of 2007 to 2011. Industry
average is calculated by taking average of ROA, NPM, and Sales Growth of all
companies. The industry average of return on assets (ROA) is 7.16%, net profit margin
(NPM) is 18.74%, and sales growth rate is 21.85%.
182 Journal of Business Studies, Vol. XXXV, No. 1, April 2014
Table 4: Performance Summary of Fuel and Power Companies (2007-2011)
Companies /Particulars
ROA (%)
Deviation
from
Industry (%)
NPM (%)
Deviation
from
Industry (%)
Sales Growth
(%)
Deviation
from
Industry (%)
Linde Bangladesh Limited 20.00 12.84 17.82 -0.93 15.58 -6.27
Eastern Lubricants 3.87 -3.30 98.38 79.63 42.02 20.16
Bd. Welding Electrodes 1.07 -6.09 3.39 -15.36 23.07 1.21
Summit Power 8.52 1.36 33.80 15.06 35.52 13.67
Dhaka Electric Supply Company 5.79 -1.38 12.94 -5.80 13.12 -8.73
Power Grid Company of
Bangladesh Ltd. 2.34 -4.82 24.14 5.40 5.36 -16.49
Padma Oil 11.61 4.45 0.58 -18.16 18.45 -3.40
Meghna Petroleum 2.90 -4.26 0.70 -18.04 14.32 -7.53
Jamuna Oil 4.78 -2.38 0.97 -17.78 18.44 -3.41
KPCL 8.42 1.26 5.74 -13.01 13.34 -8.52
Mobil Jamuna 7.80 0.64 10.22 -8.52 23.63 1.78
Titas Gas 13.95 6.78 10.79 -7.96 10.69 -11.16
GBB Power 2.95 -4.21 11.27 -7.47 27.61 5.76
Barakatullah Electro Dynamics 5.22 -1.95 23.28 4.54 35.22 13.37
Summit Purbanchol Power 8.22 1.06 27.12 8.38 31.43 9.57
Industry Average 7.16 - 18.74 - 21.85 -
In terms of ROA, Linde Bangladesh Limited, Summit Power, Padma Oil, KPCL, Mobil
Jamuna, Titas Gas, and Summit Purbanchol Power had outperformed the industry and
other companies underperformed the industry. In terms of NPM, Eastern Lubricants,
PGCB, Barkatullah Electro Dynamics and Summit Purbanchol Power outperformed the
industry and other companies underperformed the industry. Sales growth rate of the fuel
and power industry is much higher as consumption of fuel and power is highly correlated
with economic development. Eastern Lubricants, Bd. Welding Electrodes, Summit
Power, Mobil Jamuna, GBB Power, Barakatullah Electro Dynamics, and Summit
Impact of Working Capital Management on Firm’s Profitability: Evidence from the Fuel 183
Purbanchol Power ride on the wave of this high sales growth by outperforming the
industry while other companies’ sales growth is below than industry average.
Figure 1: Performance of Fuel and Power Companies
Figure 1 shows the performance graphically. Linde Bangladesh had standout
performance in industry in terms of both NPM and Sales Growth. Bangladesh
government has announced Fiscal incentives and incentives for foreign investors to
facilitate the investment in the power plants. Exemption from corporate income tax for a
period of 15 years has been announced for the investors. They are also allowed to import
plant and equipment and spare parts up to a maximum of ten percent (10%) of the
original value of total plant and equipment within a period of twelve (12) years of
commercial operation without payment of customs duties. For foreign investors,
government announced tax exemption on royalties, technical know-how and technical
assistance fees. The foreign investors are also exempted from paying tax on interest on
foreign loans. They are also enjoying tax exemption on capital gains from transfer of
shares by the investing company. These incentives dictates many fuel and power
companies will be established by investors in upcoming period which will make this fuel
and power industry vibrant and ensure social and economic development of Bangladesh.
Literature Review
Study conducted by Hayajneh and Yassine (2011) investigated the relationship between
working capital efficiency and profitability on the 53 Jordanian manufacturing firms
listed in Amman Exchange Market for the period from 2000 to 2006. Descriptive
statistics, Pearson correlation coefficients, ordinary least squares (OLS) and two stage
least squares (2SLS) regressions model were used to analyze the data series in this study.
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
60.00%
70.00%
80.00%
90.00%
100.00%
110.00%
Linde Bangladesh
Eastern Lubricants
Bd. Welding
…
Summit Power
Dhaka Electric
…
Power Grid
…
Padma Oil
Meghna Petroleum
Jamuna Oil
KPCL
Mobil Jamuna
Titas Gas
GBB Power
Barakatullah
…
Summit
…
ROA
NPM
Sales Growth
Industry ROA
Industry NPM
Industry Sales Growth
184 Journal of Business Studies, Vol. XXXV, No. 1, April 2014
The study found a negative significant relationship between profitability and the average
receivable collection period, average conversion inventory period and average payment
period, and also the cash conversion cycle which expresses the efficiency of working
capital. Their study revealed a positive significance between the size of the firm, growth
of sales and current ratio from this side and profitability from other side. Finally,
financial leverage correlated negatively with profitability. Regression results of this study
recommended the firms to manage its working capital efficiently to achieve the optimal
profitability.
Weinraub and Visscher, (1998) used quarterly data for the period 1984-93 of the US
firms to analyze the issue of aggressive and conservative working capital management.
To examine the relative relationship between aggressive/conservative working capital
policies, they considered 10 diverse industry groups and found that the industries had
distinctive and significantly different working capital management policies. These
researchers discovered the long stability of working capital policies over the 10-year
study period. The study found a high and significant negative correlation exist between
industry asset and liability policies and found that when relatively aggressive working
capital asset policies are followed, they are balanced by relatively conservative working
capital financial policies.
Moyer, Mcguigan and Kretlow (1995, p. 11) found that working capital consists of a
large portion of a firm’s total investment in assets, 40 percent in manufacturing and 50
percent to 60 percent in retailing and wholesale industries respectively. Scherr (1989, p.
16) claimed that by implementing best practices in working capital, companies can
strengthen strong cash flow levels, improve profitability, budgeting and forecasting
process.
The relationship of cash conversion cycle with firm size and profitability for firms listed
at Istanbul Stock Exchange was studied by Uyar, (2009) using ANOVA and correlation
analysis. The results showed retail/wholesale industry has shorter Cash Conversion Cycle
(CCC) than manufacturing industries. Furthermore, study found significant negative
correlation between CCC and profitability as well as between CCC and firm size.
Padachi, (2006) has examined the trends in working capital management and its impact
on firm’s performance for 58 Mauritian small manufacturing firms during 1998 to 2003.
He explained that a well designed and implemented working capital management is
expected to contribute positively to the creation of firm’s value. The results indicated that
high investment in inventories and receivables is associated with low profitability and
also showed an increasing trend in the short term component of working capital
financing.
Impact of Working Capital Management on Firm’s Profitability: Evidence from the Fuel 185
To test the relationship between working capital management and corporate profitability,
Deloof (2003) used a sample of 1,009 large Belgian non-financial firms for a period of
1992-1996. By using correlation and regression tests, he found significant negative
relationship between gross operating income and the number of days accounts receivable,
inventories, and accounts payable of Belgian firms.
Tahmina, (2011) took the companies enlisted with the cement industry of Dhaka Stock
Exchange to investigate the effects of working capital management efficiency as well as
maintaining liquidity on the profitability of these companies. Her analysis covered a time
period from year 2005 to 2009. The purpose of her paper was to establish a relationship
between working capital components efficiency of cement companies and profitability of
these companies which is statistically significant. The other purpose was to help explain
the necessity of firms optimizing their level of working capital management and
maintaining enough liquidity as it affects the profitability. Her study revealed a
significant relationship exists between liquidly as well as working capital components
and profitability of these cement companies.
Naimulbari (2012) in his study found that all the components of working capital have a
significant effect on the profitability in the pharmaceuticals industry in Bangladesh. His
study disclosed a negative relationship between corporate profitability and cash
conversion cycle which indicates that the cash conversion cycle is longer, profitability is
smaller. As the cash conversion cycle has the negative relationship with the profitability,
this cycle should be short as much as possible without hurting the operations. This would
improve profits, because the longer the cash conversion cycle, the greater the need for
external financing, and that financing has a cost. Pharmaceuticals companies have much
scope to reduce their cash conversion cycle by compressing the debtor conversion period.
Lots of studies have been conducted showing the relationship between working capital
efficiency and its impact on overall profitability of firms both home and abroad on
different industries. But no such study has been done so far on fuel and power industry of
Bangladesh. So this study is expected to reduce that gap in the literature and will
contribute to the knowledge of different stakeholders associated with this sector to take
informed decision about how managing working capital efficiently will impact the
profitability of a firm.
Objective of the Study
The major objective of this study is to assess the relationship between working capital
efficiency and the profitability of selected power and fuel companies listed in DSE. The
specific objectives of the study can be summarized as follows:
186 Journal of Business Studies, Vol. XXXV, No. 1, April 2014
a. To identify the working capital efficiency indicators that influence the profitability
measures
b. To measure the nature and extent of dependence of profitability on working capital
management
c. To analyze the relationship between the liquidity and the profitability
d. To assess the relationship between financial leverage position and the profitability
e. To recommend measures for enhancing firm’s profitability
Data and Methodology
The study was primarily based on the secondary source of information. The secondary
data were collected from annual reports of fifteen listed fuel and power companies in the
Dhaka Stock Exchange from 2007 to 2011. Padma Oil Company Limited (POCL),
Jamuna Oil Company Limited (JOCL), and Meghna Petroleum Limited (MPL) work as
affiliated companies for Bangladesh Petroleum Corporation (BPC). These companies are
considered as oil marketing companies rather than producers. Prior to using the
secondary source of data, they were carefully scanned and their reliability was verified.
While analyzing the data, descriptive as well as inferential statistical tools were used.
Besides, ratios were calculated to assess the relationship between working capital
efficiency and the profitability of the selected companies. Stata 11 had been used to
conduct the descriptive analysis to describe relevant aspects of phenomena of cash
conversion cycle and provide detailed information about each relevant variable.
In this analysis two methods were applied. Firstly, Pearson correlation matrix was used to
measure the degree of association between different variables under consideration.
Secondly, to account for the effects of other construct, multivariate linear regression was
applied for the hypotheses.
The variables that were used in this study were as follows: Return on Asset (ROA), Net
Profit Margin (NPM), Time Interest Earned Ratio (TIE), Quick Ratio (QR), Cash
Conversion Cycle (CCC), Accounts Receivables Collection Period (ARCP), Accounts
Payable Period (APP), Inventory processing Period (IPP), Cash to Current Liability
(CCL), Cash to Sales (CTS), Debt-Equity Ratio (D/E), and Net Working Capital
Turnover (NWC turnover) ratios.
The study intended to assess the relationship between profitability indicators and other
working capital components and liquidity positions. To cover the liquidity position, few
cash position ratios were considered along with traditional liquidity ratios. And for the
Impact of Working Capital Management on Firm’s Profitability: Evidence from the Fuel 187
purpose, multiple regression analysis was conducted as well. So the basic model for the
study that had been followed is-
Profitability of the Firm = f (Quick Ratio (QR), Cash Conversion Cycle (CCC), Accounts
Receivables Collection Period (ARCP), Accounts Payable Payment Period (APP) ,
Inventory Processing Period (IPP), Cash to Current Liability (CCL) , Cash to Sales
(CTS), Time Interest Earned Ratio (TIE), Debt to Equity Ratio (D/E), Net working
Capital (NWC ) Turnover)
Figure 3 Conceptual Framework of Study
Hypothesis of the Study
Hypothesis that were applied to analyze the impact of working capital components on the
profitability of the firm statistically were as follows:
H 1: There is negative relationship between the components of working capital efficiency
and the profitability.
H 2: There is negative relationship between liquidity and the profitability.
H 3: There is negative relationship between financial leverage position and the
profitability.
Expected Findings
a. A significant level of relationship between the profitability indices and various
liquidity indices as well as working capital components.
b. A negative relationship between working capital and its components’ conversion cycle
and profitability of the Firm.
Independent Variables
Quick Ratio, TIE, D/E
Cash Conversion Cycle, A/C Rec
Collection Period, A/P
Payable Period, Inventory
processing Period, NWC TO
Cash to Current Liability, CTS
ca Cash to Sales
Dependent Variables
Return on Assets
Net Profit Margin
188 Journal of Business Studies, Vol. XXXV, No. 1, April 2014
c. Positive relationship of profitability with the firms’ cash holding position along with
other indicators.
d. Efficient management of working capital and liquidity contributes firms’ profitability
positively.
Empirical Analysis:
Descriptive Statistics
Table 5 presents the descriptive statistics of the study variables for 15 fuel and power
firms from 2007 to 2011.This descriptive statistics include median, maximum, mean, and
standard deviation of all collected variables.
The mean and median of net profit margin are more than two times of ROA, which
means in most of the years these firms had a total asset turnover less than one. Firms are
not using their total assets rigorously to generate more and more sales. Firms may
maintain large amount assets to avoid probable breakdown of assets which may shrink
future sales if not addressed timely.
Table 5: Descriptive Statistics on Parameters of Working Capital and Profitability
Ratios Mean Median Standard
Error Standard
Deviation Minimum Maximum Confidence
Level
(95.0%)
ROA 0.0726 0.0497 0.0080 0.0666 -0.0158 0.2665 0.0160
NPM 0.1841 0.1109 0.0317 0.2634 -0.0631 1.4466 0.0633
TIE 43.2816 5.1074 16.3417 135.7443 0.0000 800.7640 32.6093
QR 1.4985 0.9219 0.1621 1.3467 0.0009 8.0045 0.3235
ARCP 490.6082 59.0893 215.7245 1791.9426 0.1046 9746.2409 430.4716
IPP 93.3733 49.7845 15.8728 131.8494 0.0000 551.6615 31.6737
APP 372.9374 38.3107 152.9559 1270.5467 0.0000 6599.0142 305.2186
CCC 211.0441 81.0682 73.2274 608.2729 -763.5285 3147.2267 146.1231
CCL 0.7436 0.3602 0.1172 0.9732 0.0149 4.7413 0.2338
CTS 1.2719 0.1019 0.4628 3.8444 0.0054 22.2831 0.9235
D/E Ratio 3.9696 1.7500 0.7192 5.9744 0.0024 30.4682 1.4352
NWC TO -9.3953 2.2455 21.6913 180.1813 -1472 90.1667 43.2843
Impact of Working Capital Management on Firm’s Profitability: Evidence from the Fuel 189
The minimum value of NPM as a measure of the profitability is -6.31% but the maximum
value of NPM is 144.66%. While the mean of net profit margin is 18.41%, and the
standard deviation of net profit margin from its mean is about 26.34%. This indicates the
existence of moderate variations in the NPM of different companies.
The average receivables collection period (ARCP) is 0.1046 days (approximately) as
minimum to collect its receivables from the customers but it takes 9746 days as
maximum to pay its creditors. The average inventory processing period (IPP) is about 93
days with standard deviation of 132 days and takes 552 days as maximum. About the
average payment period (APP), the firm requires 6599 days as a maximum time. It takes
an average 373 days to pay its purchases with standard deviation of 1271 days. This is
indicative of existence of significant variations in ARCP, IPP, APP and CCC of different
companies.
Net working capital turnover (NWC Turnover) measures the dollar sales generated from
per dollar invested in net working capital. Negative average NWC turnover indicates
firms’ ability to finance its current assets is more than sufficient. The firms need 3147
days as a maximum time from making payments to receive cash inflow and on an
average 211 days from making its payments to receive its cash inflow with standard
deviation of 608 days, which is significant.
Analysis of Interrelationships
The interrelationships between the chosen variables have been analyzed using correlation
coefficients. The correlation matrix contains the simple Pearson correlation coefficients
(Table 6). It is evident from the correlation matrix that the ROA and IPP are negatively
correlated with the cash conversion cycle. This indicates that more profitable firms either
delay their payment towards their suppliers-creditors or accelerate their receivables.
These results are consistent with the view that the shorter the period between production
and sale of products the larger is the firm’s profitability.
Table 6 Correlation Coefficient Matrix
Ratios ROA CCC QR NPM IPP TIE CCL CTS D/E NWC
TO
ROA 1.000
CCC -0.203 1.000
QR 0.042 -0.048 1.000
NPM -0.038 0.582* 0.089 1.000
190 Journal of Business Studies, Vol. XXXV, No. 1, April 2014
IPP -0.214 0.155 -0.077 -0.194 1.000
TIE 0.563* -0.069 0.213 -0.018 -0.055 1.000
CCL 0.093 -0.016 0.836* 0.133 0.033 0.317* 1.000
CTS -0.190 0.812* 0.009 0.813* -0.140 -0.083 0.058 1.000
D/E -0.108 -0.166 -0.224 -0.28* -0.24* -0.153 -0.207 -0.13 1.000
NWC TO -0.36* 0.011 0.028 0.038 0.035 0.017 0.0270 0.016 -0.16 1.0000
* mark indicates the significance at 5%
There is a significant positive correlation between the cash conversion cycle and net
profit margin. It means if a firm loosens its credit period and hereby enhances average
receivables collection period, it will increase the profitability through attracting more
customers by providing them with favorable credit terms and generating more sales in
this process. There is significant positive correlation between timed interest earned (TIE)
and return on assets (ROA) which is quite logical. The cash to sales (CTS) and cash
conversion cycle (CCC) are significantly positively related meaning when the firm
reduces the length time required converting raw materials into finished goods, selling
those goods and collecting receivable early; can hold more cash in response to sales.
Significant positive correlation exists between cash to current liability and quick ratio as
cash contributes to quick asset and between cash to sales (CTS) and net profit margin
(NPM). So if the firms make their sales more in cash, it will reflect positively on
profitability. Significant positive correlation between cash to current liability (CCL) and
times interest earned (TIE), indicates that firms have capability to bear debt from holding
more cash. All of the above correlations are consistent with the hypothesis and with
previous studies. The financial leverage position of the firm (measured by D/E ratio) is
negatively related to profitability (NPM), and also significant. All of the above
correlation coefficients are consistent with the findings of the previous studies.
Dependence of Firm’s Profitability: Multiple Regression Analysis
For assessing the nature and degree of dependence of criterion variable (profitability) on
selected working capital efficiency indicators (explanatory variables) multiple regression
analyses were performed. In Table 7, the summary of multiple regression of the return on
assets (ROA) on selected predictor variables is shown. These variables are indicators of
working capital components as well as working capital efficiency.
Impact of Working Capital Management on Firm’s Profitability: Evidence from the Fuel 191
Table 7: Output of Multiple Regression of ROA on Selected Predictor Variables
Dependent
Variable Predictors R
Square Adjusted R
Square Coefficient T-Stat P Value Standard
Error
ROA
Intercept
59.68% 51.89%
0.071897 4.394430 0.000049 0.016361
NPM 0.115544 2.104147 0.039788 0.054913
TIE 0.000226 4.604565 0.000024 0.000049
QR -0.048155 -2.082739 0.041773 0.023121
ARCP 0.000011 0.568082 0.572211 0.000019
IPP -0.000175 -3.158573 0.002536 0.000055
APP -0.000039 -1.381758 0.172438 0.000028
CCL -0.003950 -0.325856 0.745727 0.012121
CTS -0.002348 -0.514141 0.609141 0.004566
D/E Ratio -0.001403 -1.229400 0.223973 0.001141
CR 0.040644 1.881325 0.065038 0.021604
NWC
Turnover -0.000144 -4.540699 0.000030 0.000032
Based on the coefficients given in Table 7 the following regression model can be
constructed:
ROA = 0.0711 + 0.116 NPM + 0.0002226 TIE - 0.0482 QR + 0.000011 ARCP-
0.000175 IPP - 0.000039 APP - 0.00395 CCL - 0.00235 CTS- 0.0014 D/E Ratio +
0.0406 CR - 0.00014 NWC Turnover
Output of Multiple Regression is indicative of the dependence of profitability indicator
on selected parameters of working capital management efficiency. The value of the
coefficient of multiple determination indicates that the independent variables all together
explained 59.68 percent of total variations in return on asset (ROA). The results were also
found statistically significant as a whole (Appendix 1). But an analysis of the coefficient-
wise significance of relationship between the criterion variable and a specific predictor
variable reveals that the said relationship was significant only in five cases out of eleven.
It is evident from t-stat and p-value that significant relationship exists between ROA and
NPM, TIE, QR, IPP and NWC turnover.
An examination of the nature and magnitude of relationship between criterion and
explanatory variables reveals that the net profit margin (NPM) and time interest earned
192 Journal of Business Studies, Vol. XXXV, No. 1, April 2014
(TIE) have positive relationship with the ROA. The coefficients indicate that ROA
increases by 0.116 and 0.0002226 units for a unit change in NPM and TIE respectively,
provided all other predicted variables remain constant. Other critical factors over the
ROA, as observed from the above stated multiple regression model, are quick ratio (QR)
and inventory processing period (IPP), which are important measures of working capital
efficiency of the firm; firms which are better at reducing inventory processing period can
minimize their cash conversion cycle which in turn increases their profitability. Standard
quick ratio to be maintained is 2 for manufacturing firm. The negative coefficient of
quick ratio indicates accumulation of unnecessary large number of current assets can cut
off profitability of firms. Net working capital turnover (NWC Turnover) measures the
dollar sales generated from per dollar invested in net working capital. Net working capital
should be invested at optimum level in firms’ operation.
Table 8 furnishes the multiple regression summary of net profit margin (NPM) on other
independent variables which are indicators of working capital components as well as
working capital efficiency.
Table 8: Output of Multiple Regression of NPM on Selected Predictor Variables
Dependent
Variable Predictors R
Square Adjusted
R Square Coefficient T-Stat P Value Standard
Error
NPM
Intercept
84.99% 82.41%
0.157002 4.721960 0.000015 0.033249
TIE 0.000016 0.139028 0.889910 0.000117
QR 0.052756 0.961812 0.340137 0.054850
ARCP -0.000104 -2.359766 0.021673 0.000044
IPP -0.000052 -0.394330 0.694783 0.000132
APP 0.000303 5.563625 0.000001 0.000055
CCL 0.058688 2.100502 0.040043 0.027940
CTS 0.005380 0.493821 0.623297 0.010896
D/E Ratio -0.008486 -3.406806 0.001200 0.002491
CR -0.066498 -1.306048 0.196692 0.050915
NWC
Turnover -0.000010 -0.131676 0.895696 0.000076
Impact of Working Capital Management on Firm’s Profitability: Evidence from the Fuel 193
The regression equation of NPM on selected working capital parameters can be written as
follows:
NPM = 0.157 + 0.000016 TIE + 0.05276 QR - 0.000104 ARCP - 0.000052 IPP +
0.000303 APP + 0.0587 CCL + 0.0054 CTS - 0.00849 D/E Ratio - 0.0665 CR –
0.000010 NWC Turnover
As seen from the results contained in Table 8, the independent variables jointly as a
whole explained 84.99% of total variations in net profit margin (NPM). The results
obtained through regression model were found to be statistically significant as a whole (F
value in Appendix 2), but marked variations were observed from coefficient to
coefficient. From the t-stat and p-value, it is observed that significant relationship exists
between criterion variable NPM and the predictor variables of ARCP, APP, CCL and
debt equity ratio (D/E Ratio).
This equation shows that critical factors over the NPM are accounts receivables
conversion period (ARCP), accounts payables payment period (APP), cash to current
liabilities (CCL) and debt to equity ratio (D/E). Firms which are better at increasing
ARCP, and APP can minimize their cash conversion cycle which in turn increases their
profitability. Sufficient cash enables firm to meet its current liability instantly which
gives firm opportunity to take favorable buying terms from suppliers. Debt to Equity ratio
increases firms’ exposure to financial risk which can reduce profitability of firm if
financing cost increases over time for debt usage.
The findings of the study confirm the validity of the hypotheses that working capital
management significantly affects profitability of listed fuel and power companies in
Bangladesh. In the same way, first research hypothesis (H1) indicating that working
capital management significantly affects profitability was proved and accepted. Working
capital management has its effect on liquidity as well on profitability of the firm;
therefore, the companies should maintain a balance between both.
The second hypothesis (H2) which indicated that liquidity position has a significant
negative impact on profitability of the firm was proved. It was found that, higher the
quick ratio, lower was the ROA of firms and therefore, the firms must set a trade-off
between these two objectives so that, neither the neither liquidity nor profitability suffers.
The third hypothesis (H3) concerning that, there exist a relationship between debt
financing and profitability was proved. D/E ratio has significant negative relation with
NPM. So when the debt financing increased, profitability declined. In fact, debt financing
affects the financial cost which would lead to decreasing profitability.
194 Journal of Business Studies, Vol. XXXV, No. 1, April 2014
Findings and Recommendations
This study investigated the inter-linkages of working capital management and
profitability using the financial statement variables of fifteen listed fuel and power
companies in Bangladesh from 2007 to 2011. Analysis of multiple regression and
correlation matrix revealed that measurable association exists between the dependent and
selected independent variables. Out of eleven independent variables, only two variables
namely, net profit margin (NPM) and time interest earned (TIE) have significant positive
relationship and quick ratio (QR), inventory processing period (IPP) and net working
capital turnover (NWC turnover) showed a significant negative relationship with return
on assets (ROA). The other independent variables, irrespective of their nature of
relationship with the criterion variable, were found to have no significant relationship
with ROA.
Among the determinants of net profit margin (NPM), cash to current liability (CCL) and
accounts payables payment period (APP) showed a significant positive influence, while
ARCP and debt-equity ratio (D/E) exhibited a significant negative influence on net profit
margin (NPM)
Quick ratio (QR) and cash to current liability both had positive relation with both return
on assets (ROA), and net profit margin (NPM). Inventory processing period (IPP), and
debt-equity ratio (D/E) both had negative relation with both return on assets (ROA), and
net profit margin (NPM).
Based on the findings of the study, it is recommended that fuel and power firms should
manage their working capital efficiently to achieve the optimal profitability. These firms
should maintain optimum current assets for their daily business processing as well as for
meeting their short term maturities otherwise their profitability would be affected. The
firms should manage their working capital through reducing the length time between sell
the goods and receive cash of sales by accelerating its collections. Besides, they should
reduce the length time between conversions of the raw materials into finished goods to
sell these goods. The firms should try to shorten the length time between purchase goods
to pay their purchases. All of these measures will lead to a reduced cash conversion cycle
and then could ensure optimal profitability.
The study suggests that there is much to be done in the area of working capital
management in Fuel and Power sector of Bangladesh in future. More analytical research
studies could be conducted on the same topic by extending the sample coverage by
companies and time and incorporating other predictor and criterion variables and using
more tests to assess the impact of working capital management and firm’s profitability.
Impact of Working Capital Management on Firm’s Profitability: Evidence from the Fuel 195
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196 Journal of Business Studies, Vol. XXXV, No. 1, April 2014
Appendix
1. Multiple Regressions on ROA
Regression Statistics for all Working Capital Components
Multiple R 0.772501
R Square 0.596757
Adj. R Square 0.518939
Standard Error 0.046210
Observations 69.000000
ANOVA
Df SS MS F Significance F
Regression 11.000000 0.180127 0.016375 7.668557 0.000000
Residual 57.000000 0.121716 0.002135
Total 68.000000 0.301843
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 0.071897 0.016361 4.394430 0.000049 0.039135 0.104659
NPM 0.115544 0.054913 2.104147 0.039788 0.005584 0.225505
TIE 0.000226 0.000049 4.604565 0.000024 0.000128 0.000324
QR -0.048155 0.023121 -2.082739 0.041773 -0.094453 -0.001856
ARCP 0.000011 0.000019 0.568082 0.572211 -0.000028 0.000050
IPP -0.000175 0.000055 -3.158573 0.002536 -0.000286 -0.000064
APP -0.000039 0.000028 -1.381758 0.172438 -0.000096 0.000018
CCL -0.003950 0.012121 -0.325856 0.745727 -0.028221 0.020322
CTS -0.002348 0.004566 -0.514141 0.609141 -0.011491 0.006796
D/E Ratio -0.001403 0.001141 -1.229400 0.223973 -0.003688 0.000882
CR 0.040644 0.021604 1.881325 0.065038 -0.002617 0.083904
NWC Turnover -0.000144 0.000032 -4.540699 0.000030 -0.000207 -0.000080
Impact of Working Capital Management on Firm’s Profitability: Evidence from the Fuel 197
Autocorrelation Problem and Solution
. tsset year
time variable: year, 2007 to 2011
. dwstat
Durbin-Watson d-statistic( 12, 5) = .9276092
. archlm, lags (1 2 3)
LM test for autoregressive conditional heteroskedasticity (ARCH)
---------------------------------------------------------------------------
lags(p) | chi2 df Prob > chi2
-------------+-------------------------------------------------------------
1 | 1.096 1 0.2952
2 | 3.000 2 0.2231
3 | 2.000 3 0.5724
---------------------------------------------------------------------------
H0: no ARCH effects vs. H1: ARCH(p) disturbance
Heteroskedasticity Problem and Solution
. hettest
Breusch-Pagan / Cook-Weisberg test for heteroskedasticity
Ho: Constant variance
Variables: fitted values of roa
chi2(1) = 0.20
Prob > chi2 = 0.6527
198 Journal of Business Studies, Vol. XXXV, No. 1, April 2014
2. Multiple Regressions on NPM
Regression Statistics for all Working Capital Components
Multiple R 0.921916
R Square 0.849929
Adj. R Square 0.824055
Standard Error 0.110497
Observations 69.000000
ANOVA
df SS MS F Significance F
Regression 10.000000 4.010636 0.401064 32.848352 0.000000
Residual 58.000000 0.708154 0.012210
Total 68.000000 4.718790
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 0.157002 0.033249 4.721960 0.000015 0.090446 0.223558
TIE 0.000016 0.000117 0.139028 0.889910 -0.000218 0.000251
QR 0.052756 0.054850 0.961812 0.340137 -0.057039 0.162551
ARCP -0.000104 0.000044 -2.359766 0.021673 -0.000192 -0.000016
IPP -0.000052 0.000132 -0.394330 0.694783 -0.000317 0.000213
APP 0.000303 0.000055 5.563625 0.000001 0.000194 0.000413
CCL 0.058688 0.027940 2.100502 0.040043 0.002760 0.114616
CTS 0.005380 0.010896 0.493821 0.623297 -0.016429 0.027190
D/E Ratio -0.008486 0.002491 -3.406806 0.001200 -0.013473 -0.003500
CR -0.066498 0.050915 -1.306048 0.196692 -0.168415 0.035420
NWC Turnover -0.000010 0.000076 -0.131676 0.895696 -0.000161 0.000141
Impact of Working Capital Management on Firm’s Profitability: Evidence from the Fuel 199
Autocorrelation Problem and Solution
. tsset year
time variable: year, 2007 to 2011
. dwstat
Durbin-Watson d-statistic( 11, 5) = 1.252004
Heteroskedasticity Problem and Solution
. hettest
Breusch-Pagan / Cook-Weisberg test for heteroskedasticity
Ho: Constant variance
Variables: fitted values of npm
chi2(1) = 6.19
Prob > chi2 = 0.0129
