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WORKING CAPITAL MANAGEMENT AND PROFITABILITY
DEPARTMENT OF BANKI
ONYIMBA ROSELINE CHIZOBAREG. NO: PG/M.sc/12/61705
WORKING CAPITAL MANAGEMENT AND PROFITABILITY
IN CHEMICAL AND PAINT SECTOR IN NIGERIA
DEPARTMENT OF BANKING AND FINANACE
FACULTY OF BUSINESS ADMINISTRATION
Fred Attah
Digitally signed by: Content manager’s
Name
DN : CN = Webmaster’s name
O= University of Nigeri
OU = Innovation Centre
ONYIMBA ROSELINE CHIZOBA
WORKING CAPITAL MANAGEMENT AND PROFITABILITY
IN CHEMICAL AND PAINT SECTOR IN NIGERIA
NG AND FINANACE
BUSINESS ADMINISTRATION
: Content manager’s
Webmaster’s name
O= University of Nigeria, Nsukka
OU = Innovation Centre
2
WORKING CAPITAL MANAGEMENT AND PROFITABILITY
IN CHEMICAL AND PAINT SECTOR IN NIGERIA
BY
ONYIMBA ROSELINE CHIZOBA REG. NO: PG/M.sc/12/61705
BEING A DESERTATION PRESENTED TO THE DEPARTMENT OF BANKING AND FINANCE, FACULTY OF BUSINESS
ADMINISTRATION, IN PARTIAL FULFILLMENT FOR THE REQUIREMENTS FOR THE AWARD OF DEGREE OF MASTERS (M. sc)
IN BANKING AND FINANCE, IN THE UNIVERSITY OF NIGERI A , ENUGU CAMPUS
SUPERVISOR:
ASSOCIATE PROF. NWUDE
JUNE, 2014
3
TITLE PAGE
WORKING CAPITAL MANAGEMENT AND PROFITABILITY IN CHEMICAL AND PAINT SECTOR
IN NIGERIA
BY
ONYIMBA ROSELINE CHIZOBA
REG. NO: PG/M.sc/12/61705
4
DEPARTMENT OF BANKING AND FINANCE
FALCULTY OF BUSINESS ADMINITRATION
UNIVERSITY OF NIGERIA, ENUGU CAMPUS
MAY, 2015
5
CERTIFICATION
This is to certify that the thesis prepared by Onyimba Roseline C., entitled:
Working Capital Management and Profitability in Chemical And Paint Sector
in Nigeria and submitted in partial fulfillment of the requirements for the degree of
Degree of Master of Business Administration in Banking and Finance complies
with the regulations of the university of Nigeria Nsukka and meets the accepted
standards with respect to originality and quality
……………………………… ………………………………
ASSOCIATE PROF. NWUDE Date
(SUPERVISOR)
………………………………... … ………………………………
ASSOCIATE PROF. NWUDE Date
(HEAD OF DEPATRMENT)
6
DEDICATION
This project work is dedicated to the Almighty God of Chosen whose love is endless towards me.
7
ACKNOWLEDGEMENTS
I want to use this medium to express my profound gratitude to those who in one
way or the other has contributed to the realization of this project work. My
heartfelt gratitude goes to almighty God of the chosen whom his marvelous
support has helped to make the accomplishment of this work possible and my
brother whom his financial support has helped me a lot. I will not forget my
supervisor Associate Prof. Nwude for his wonderful care and support during this
work, including my other lecturers; Prof. J.U.J Onwumere, Dr. Mrs. Modebe, Dr
Onah, and many others. I am also grateful to my family and to my friends for
support during my studies and especially during the thesis project. May God
almighty, bless, guide and protect them all Amen.
Onyimba Roseline C.
8
ABSTRACT
Working Capital Management plays an important role in financial decision making since it is a part of investment in assets and liabilities and it directly affects the profitability and liquidity of the firm. Firms can achieve optimal management of working capital by making the trade –off between profitability and liquidity. Cash Conversion Cycle is one of the important measuring tools to calculate the efficiency of working capital management. The study tries to investigate the impact of working capital management on profitability of the selected Chemical and Paint firms listed in Nigeria Stock Exchange, using a sampled of 5 firms for the period of 14 years from 2000-2013 , we had studied the effect of different variables of working capital management including the average collection period, inventory conversion period, average payment period cash conversion period and control for current ratio, debt ratio, size of the firm and financial assets to total assets ratio on the profitability measured by gross operating profitability of listed chemical and paint firms. The data is analyzed using descriptive and multiple regressions and the outcome shows that ACP had a positive and significant impact on the profitability, implied that firms can increase profitability measured by gross operating profit by lengthening collection period of account receivable as generous trade credit policy may lead to higher sales. A financial asset to total assets as a control variable has a significant positive relationship with firm’s value and profitability of firms. This means, increasing in the level of financial assets to total assets will lead to increase in the profitability of the firm and the value of the firm, since they are brought for profitability purposes.
9
TABLE OF CONTENTS
TITLE PAGE……………………………………………………………………… i
CERTIFICATION………………………………………………………………… ii
DEDICATION……………………………………………………………………… iii
AKNOWLEDGEMENT……………………………………………………………... iv
ABSTRACT………………………………………………………………………… v
TABLE OF CONTENTS…………………………………………………………….. vi
CHAPTER ONE: INTRODUCTION
1.1: Background to the Study……………………………………………….. … 1
1.2: Statement of the Problem……………………………………………….. …… 3
1.3 Objective of the Study………………………………………………………… 5
1.4: Research Question……………………………………………………………. 5
1.5: Research Hypotheses…………………………………………………………. 6
1.6: Scope of the Research…………………………………………………………. 6
1.7: Significant of the Study………………………………………………………. 6
References……………………………………………………………………………....8
CHAPTER TWO: REVIEW OF RELATED LITERATURE
2.1: CONCEPTUAL FRAME WORK……………………………………………… 11
2.1.1: Definition and Concept of Working Capital……………………………… 11
2.1.2: Working Capital Cycle……………………………………………………… 12
2.1.3: Working Capital Policy……………………………………………………… 14
2.1.4: Factor Influencing Working Capital Requirement………………………… 15
2.1.5: Rationale for Working Capital……………………………………………. 17
2.1.6: Working Capital and Liquidity…………………………………………… 18
2.1.7: Rationale for Working Capital Management…………………………….. 18
10
2.2: THEORITICAL FRAME WORK……………………………………………. 19
2.2.1: Theory of Working Capital Management……………………………………… 19
2.2.2: Impact of WCM on Company Profitability (Theoretical Base)……………… 20
2.2.3: Measuring Working Capital Management (WCM)………………………….. 21
2.3: Empirical Review………………………………………………………… 22
2.4: Summary Review ………………………………………………………… 44
2.4.1: Major Trend (Consensus on Argument)………………………………….. 45
2.4.2: Critic of Literature…………………………………………………………. 46
2.4.3: Research’s Personal Contribution………………………………………….. 46
References………………………………………………………………………….. 45
CHAPTER THREE: RESEARCH METHODOLOGY
3.1: Research Design………………………………………………………… 56
3.2: Nature and Source of Data……………………………………………… 56
3.3: Population and Sample size ……………………………………………… 56
3.4 Explanation of the Variables…………………………………………………. 57
3.5: Specification of Models…………………………………………………….. 59
3.6: Techniques of Analysis…………………………………………………….. 59
References…………………………………………………………………………… 61
CHAPTER FOUR: DATA PRESENTATION AND ANALYSIS
4.1 Data Presentation and Analysis………………………………………………. 64
4.2: The Overall Analysis of Descriptive Statistics……………………………….. 65
4.3 Test of Hypothesis………………………………………………………………… 66
4.3.1 Test of Hypothesis one…………………………………………………… 66
4.3.2 Test of Hypothesis two……………………………………………………… 68
4.3.3 Test of Hypothesis Three…………………………………………………… 70
11
4.3.4 Test of Hypothesis Four……………………………………………………. 72
4.4 Implication of the Results……………………………………………………… 73
4.5 Comparison of the Findings with the objective of the study ………………… 75 4.5.1 Research Objective One……………………………………………………… 75 4.5.2 Research Objective Two……………………………………………………… 76 4.5.3 Research Objective Three……………………………………………………… 76
4.5.4 Research Objective Four……………………………………………………… 76
References…………………………………………………………………………… 77
CHAPTER FIVE: SUMMARY OF FINDING, CONCLUSION AND COMMENDATION……………………………………………………………… 78
5.1 Summary of Findings…………………………………………………………… 78
5.2Conclusion……………………………………………………………………… 78 5.3 Recommendation……………………………………………………………… 79 5.4 Area of further study …………………………………………………………… 81 5.5 Contribution to Knowledge…………………………………………………… 81 References………………………………………………………………………… 86 Bibliography ……………………………………………………………………. 82
APPENDIX……………………………………………………………………… 90
12
CHAPTER ONE
INTRODUCTION
1.1 BACKGROUND TO THE STUDY
The main objective of any business organization is to maximize the profit. But preserving
liquidity of the firm is also an important objective too. A firm that did not make profit cannot
survive in business for a long time and also firm with insufficient liquidity will be insolvent in a
long-run which will disrupt the operational activities of the firm. In order words, effective and
efficient management of profitability and liquidity are very important for firms’ survival.
The management of working capital has a significant effect on firm’s profitability and liquidity,
irrespective of the nature and the size of the business. The management of working capital
involves the determination of optimum level of working capital to keep, monitoring and
controlling the level of individual component of working capital to ensure that the optimum level
is not exceeded, and provision of funds to finance current assets (Nwude, 2004:628).Popularly
known as trade-off between profitability and liquidity. Therefore the importance of working
capital management cannot be over-emphasized. It is obviously critical for smooth operation of
the firm, because it affects the profitability and liquidity of the firm.
Working capital components (i e. account receivable period, account payable period, inventory
period etc.) have implication for profitability among other variables. Hence, determining the
amount of liquidity available for day to day business activities and as Nwude (2004) as posits:
Working Capital is one of the most strategic assets holding of the firms. It is a
Circulating capital which flows and changes form as the firm pursues its goals and
performs its operation. It is a financial lubricant or life stream for the firm and maintains
constant process of circulation throughout the firm (Nwude, 2004:627).
Raheman & Nasr (2012) is of the view that if working capital management is not correct the
sales and consequently the profit of the company might decrease and the company may be
unable to pay its debt and commitment on time. However, the need for maintaining an adequate
working capital can hardly be questioned. Just as the circulation of the blood is very important in
human body to maintain life, the flow of fund is very necessary to maintain the business
(Ebenezer & Asied, 2013). How profitable or non-profitable a business or a firm can be partly
13
depends on how it effectively and efficiently manages its working capital (Adarquah and
Korankye 2013).
The chemical and paint industry has been in existence for a number of years. The industry has
gone through various based development from manual based process to more technologically
advanced production methods (Adewole B., 2008). However, the level of development of the
sector in Nigeria is still low when compare to other countries with more advanced technical
know-how (Adewole B., 2008). The Nigeria chemical and paint industry is a highly competitive
one. Unlike in other industries, many chemical and paint manufacturers do not have established
relationship with financial institutions (Adewole B., 2008). This limits their ability for organic
growth with many of the firms limiting their financial source to internal generated fund. Thus,
this situation will compel the managers of the industry to device various strategies of managing
their internal generated revenue to enhance their chance of making profit and meeting existing
shareholders expectation. Strategies which can be adopted within the firm to improve liquidity
and profitability include the management of working capital.
In addition, the importance of working capital to manufacturing firms cannot therefore, be over-
looked for not only do they significantly affect profitability but it concerns with the investment
required for the purchase of raw materials and conversion of the raw materials to finished goods.
It is a continuous circular process. For many manufacturing firms the current asset account for
over half of their total asset (Raheman & Nasr, 2012). Along with fixed assets such as plant and
equipment, working capital is generally the investment in current assets viz: inventory, account
receivable, short term security and cash which are required to carry on the day to day operation
of the firm. According to Barine:
Fixed assets are the core tools for functioning the organization to produce goods and
services to meet customers’ needs. Acquisitions of these fixed assets are not an end in
itself. Input materials are needed, for running through these fixed assets to produce
products and services that will meet the need of customers. Finance is also required to
ensure that these input materials are available when needed. These input materials and
finance for acquiring them regularly for firm use, ensure that fixed assets are in use and
working. (Barine, 2012:216)
Economic growth and development of many countries, especially the developing economies,
rely heavily on extent the manufacturing sector is being developed. For instance despite its poor
14
natural resources, and the hurdles it faced from 1920s chronic inflation, Germany has effectively
exploited the manufacturing sector and rose up to become the largest economy in Europe and the
fourth largest in the world.(The World Bank 2012).
In addition, Working Capital Management is of particular importance to both the small, medium
and large enterprises, as it most needed to ensure profitability and increase expansion which is an
essential prerequisite for solving the country unemployment problem. Also in this fast moving
world, firms are highly competing among them, so a well designed working capital management
is expected to contribute positively to creation of firm’s value. Of interest to us is Chemical and
Paint industry which are into the production of not only tertiary product but also secondary
product (i.e. chemical) which is in turn used as a raw material in other industry. In view of this it
has a major role to play in the system.
1.2 STATEMENT OF THE PROBLEM
The working capital management has an important role for the firm’s existence because of its
effect on firm’s profitability and liquidity in order words, liquidity management and profitability
are very important issues in the growth and survival of business and the ability to handle the
trade-off between the two are source of concern for financial managers. Reason because the
decisions that tend to maximize profitability tend to minimize liquidity and vice versa.
Profitability does not translate to liquidity in all cases, a company may be profitable without
necessarily being liquid (Owolabi & Obida, 2012). Liquidity should be managed in order to
obtain an optimal level, that is, a level that avoid excess liquidity which may incurs unnecessary
additional cost to the firm. Liquidity level should not fall below minimum requirement as it will
lead to the inability of the organization to meet short term obligation that are due. The main
problem facing all organizations is how to maintain the trade-off between profitability and
liquidity.
For managers of firms there are two main objectives concerning the management of their firms
(Telwolde 2002). First they want to maximize the profitability of the firm, maximizing the value
for the shareholders of the firm. Second they want to minimize the liquidity risk of the firm.
Liquidity risk is the risk that firms do not have enough cash or other short-term assets to satisfy
mostly their short-term financial obligation, which can cause difficulties for firms in maintaining
their operating activities.
15
Though, the ultimate objective of any firm is to maximize the profit. But, preserving liquidity of
the firm is also an important objective too. The problem is that increasing profit at the cost of
liquidity can invites serious problem to the firm. Therefore, there must be a trade-off between
these two objectives of the firms (Muhammad, Jan & ullah, 2012). Also the desire of all business
organizations is to be going concern, but achieving this basic idea also requires business
organizations to be simultaneously profitable and solvent irrespective of the profit-orientation,
size and the nature of business, all firms require an optimum level of working capital
management ( Jayarathne 2014). Inefficiency of working capital management leads the capital
into a pitfall (Niresh, 2012). Optimal working capital management positively contributes to the
creation of firm value. On one hand, cost of liquidity brings a serious problem and stands against
profitability (Dong, & su, 2010). On the other hand, a firm cannot survive without sufficient
liquidity because the firm may face the problem of insolvency. Therefore, a balance between
profitability and liquidity must always be maintained.
Poor management of working capitals results to liquidity problems which might lead to
bankruptcy in very severe cases (Nwude, 2004:628). When organization has insufficient working
capital, it will be difficult for them to survive in a competitive environment because they cannot
be able to meet the needs of their customers and also their short term creditors and it also makes
difficult the implementation of operating plans and achievements of profit targets. While
excessive working capital results in idle funds being unnecessarily tied down resulting in a loss
of profitability for the organization since idle funds can be invested elsewhere to earn returns for
the organization,(Nwude, 2004:628). Excessive working capital as well results in unnecessary
accumulation of inventories which in turn increases the dangers of obsolescence, deterioration,
and pilferage, mishandling, high insurance and carrying costs, idle assets, which are barren of
income accounts receivable, poor profitability (Nwude, 2004:628-629). Therefore, there is need
for effective working capital management which aims at an optimum working capital level. The
optimum working capital level is that level of working capital which avoids both insufficient and
excessive working capital taking the nature of the firm’s business and the level of operations into
consideration (Nwude, 2004:628).
In addition Kaur, & Singh, (2012) states that this working capital policy is an important issue in
any organization because without the proper management of working capital component it will
be difficult for the organizations to run its operation smoothly. Many financial managers are
finding it difficult to identify the important drivers of working capital management that can
16
enhance their company profitability (Huynh, 2012).If we do not care about profit; we cannot
survive for a longer period. On the other hand, if we do not care about liquidity, we may face the
problem of insolvency or bankruptcy (Raheman & Nasr, 2007). Therefore it is clear that, if
organization at any point in time does not have the enough funds to meet its short-term
obligations such as creditors, salaries, and the day-to-day expenses, then it is likely to become
technically insolvent. Conversely if the business or firm is so conservative it may have a surplus
of working capital, which will adversely, affects profits. Therefore, the trade-off between
profitability and liquidity is the key to working capital management (Aminu, 2012:55).
1.3: OBJECTIVE OF THE STUDY
• General objective
In respect of the above quest, our general research objective aims at “finding out whether
Working Capital Management can impact on profitability of selected firms in the chemical and
paints sector listed in Nigeria Stock Exchange and if so, whether it is positively or negatively
affected”.
• Specific objectives
To achieve the general objective, the following specific objectives were used;
I. To determine whether Average Collection Period has a positive and significant impact on
Profitability of selected firms in the chemical and paints sector in Nigeria.
II. To assess whether Inventory Conversion Period has a positive and significant impact on
Profitability of selected firms in the chemical and paints sector in Nigeria.
III. To ascertain whether Average Payment Period has a positive and significant impact on
Profitability of selected firms in the chemical and paints sector in Nigeria.
IV. To examine if Cash Conversion Period has a positive and significant impact on
Profitability of selected firms in the chemical and paints sector in Nigeria.
1.4: RESEARCH QUESTION
Our research questions for this study are as follows:
i. What is the impact of Average Collection Period on the profitability of the selected
firms?
17
ii. What is the impact of Inventory Conversion Period on the profitability of the selected
firms?
iii. What is the impact of Average Payable Period on the profitability of the selected firm?
iv. What is the impact of Cash Conversion Period on the Profitability of selected firms in the
chemical and paints sector in Nigeria?
1.5: HYPOTHESES OF THE STUDY
Our hypotheses for the study are as follows:
Ho1: Average Collection Period (ACP) has no positive and significant impact on Profitability of
selected firms.
Ho2: Inventory Conversion Period (ICP) has no positive and significant impact on Profitability
of selected firms.
Ho3: Average Payment Period (APP) has no positive and significant impact on Profitability of
selected firms.
Ho4: Cash Conversion cycle (CCC) has no positive and significant impact on Profitability of
selected firms in chemical and paints sector in Nigeria.
1.6: SCOPE OF THE STUDY
The research covers the five reputable firms in the Chemical and Paint sector in Nigeria, viz:
African Paint Plc, Berger Paints Plc, CAP Plc, DN Meyer Plc, and premier Paint plc. The sample
represent 71 percent of total of Chemical and Paint companies listed in Nigeria Stock Exchange
based on fourteen fiscal years (i.e.5 out of the total of 7 chemical and paint companies listed in
N.S.E.). With the availability of annual reports, the period of 2000-2013 was chosen and it
covers the particular part for preparing our data for statistical analysis.
1.7: SIGNIFICANCE OF THE STUDY
The significance of this study can be viewed from two major standpoints- Practical and
Academic.
18
(a) Practical Significance: The study will assist in broadening understanding of the
following or the scope of knowledge of the following:
• To manufacturing firms in general, it will expose the relationship existing between our
relevant variables, which will be of interest to them in their respective firms.
• Specifically to the manufacturers in the sector under study, it will expose to large extent
the activities or things going-on in their organizations with regard to our relevant
variables and a comparative analysis of their actions over some relevant years.
• More so, to policy makers, economic and business researchers, it will help to guide them
on future research, re-appraise current business practices and provide basic guideline for
policy makers in rapid changing of business environment.
• To management of the firm; among other things, the findings of the study may guide
managers of firms under study and other similar firms to understand how working capital
management affect their profitability which may enhance their short-term financial
decision making.
• To government, the important of efficient working capital management by manufacturing
firm in Nigeria cannot be over-emphasized as this is extremely needed to boost
profitability and increase expansion, which can help in solving the countries
unemployment issues and ensuring economic stability. Buttressing this point, the World
Bank Annual Report (2007) observes that developing countries can considerably resolve
their socio-economic challenge when they take significant step to revive and develop
their manufacturing base.
(b) Academic Significance
In the academic arena, this study will prove to be significant in the following ways:
• It will contribute to the enrichment of the literature on working capital management and
profitability
• It will throw more light on the relationship between profitability and such other variables
apart from working capital management component.
• It will also contribute to the enrichment of the literature on profitability and liquidity
management.
• The study will serve as a body of reserved knowledge to be referred to by researchers.
19
REFERENCES
Abdul, R. and Nasr, M. (2007), “Working Capital Management and Profitability: Case of Pakistani Firms,” International Review of Business Research Papers, Vol.3, No. 2, pp 279-300
Adarquan, R. S. and Korankye, T. (2013) Empirical Analysis of Working Capital Management and Its Impact on the Profitability of listed Manufacturing Firms in Ghana,” Research Journal of Finance and Accounting, Vol.4, No. 1, pp. 124-131
Aminu, Y. (2012) “A Nexus between Liquidity/ Profitability Trade-Off for Working Capital Management in Nigeria’s Manufacturing Sector,” International Journal of Arts and Commerce, Vol. 1, No. 6, pp. 55-58
Akoto, R. K., Vitor, D. A. and Angmar, P. L. (2013) “Working Capital Management and Profitability: Evidence from Ghanaian Listed Manufacturing Firms. Journal of Economics and International Finance, Vol. 5, No. 9, pp. 373-379
Alavinasab,S. M. and Davoudi, E. (2013) “The Relation between Working Capital Management and Profitability of listed Companies in Tehran Stock Exchange. Business Management Dynamics, Vol. 2, No. 7, pp. 1-8
Barine, M. N. (2012) “Working Capital Management Efficiency and Corporate Profitability: Evidence from Quoted Firm in Nigeria,” Journal of Applied Finance and Banking, Vol.2, No. 2, pp. 215-237
Dong, H. P. and Jyh S. (2010) “The Relationship between Working Capital Management and Profitability: A Vietnam Case” International Research Journal of Finance and Economics,” Vol. 49, 59-67
Ebenezer, A. B. and Asiedu M. K. (2013) “The Relationship between Working Capital Management and Profitability of listed Manufacturing Companies In Ghana,” International Journal of Business and Social Research, Vol.3, No. 2, pp. 25-34
Harsh, V. K. and Sukhdev, S. (2013) “Managing Efficiency and Profitability through Working Capital,” Asian Journal of Business Management, Vol. 5, No. 2, 197-207
Jayarathne, T.A.N.R. (2013) “Impact of Working Capital Management on Profitability: Evidence from Sri Lanka,” Proceeding of the 3rd International Conference on Management and Economics, Oral Presentation. Pp.269-274
Kaul, H. V. and Singh S. (2012) “Managing Efficiency and Profitability through Working Capital: An Empirical Analysis of BSE 200 Companies,” Asian Journal of Business Management, Vol. 5, No. 2, pp. 197-207
20
Leon, S. A. J. (2013) “The Impact of Working Capital Management on Profitability of the Listed Firms in Sri Lanka,” Global Journal of Commerce and Management Perspective, Vol. 2, No. 6, pp. 98-102
Melita, S. C. (2010) “The Effect of Working Capital Management on Firm’s Profitability: Empirical Evidence from an Emerging Market,” Journal of Business and Economic Research, Vol. 8, No. 12, pp. 63-68
Mobeen, U. R and Naveed, A. (2013) “ Determination of the Impact of Working Capital Management on Profitability: AN Empirical Study From the Cement Sector in Pakistan. Asian Economic and Financial Review, Vol. 3, No. 3, pp. 319-332
Mohammed, N. E. A. B and Saad, N. B. M. (2010) “Working Capital Management: The effect of Market Valuation and Profitability in Malaysia,” International Journal of Business Management” Vol. 5, No. 11, pp. 140-147
Muhammad, M., Jan W.U. & Ullah k. (2011) “Working Capital Management and Profitability: An Analysis of Firms of Textile Industry of Pakistan,” Journal of Management Sciences, Vol.4, No.2.pp.155-167
Nwude, C. E. (2004) “Basic Principles of Financial Management Second Edition, Enugu: Chuke Nwabude Nigeria
Onwumere, J.U.J (2009), Business and Economic Research Methods, Enugu: Vougasen Ltd
Owolabi, S. and Obida, S. (2012), “Liquidity Management and Corporate Profitability: A Study of Selected Manufacturing Companies,” Business Management Dynamics, Vol.2, No. 2, pp. 10-25
Raheman, A.and Nas,r M. (2007) “Working Capital Management and Profitability: Case of Pakistani Firms,” International Review of Business Research Papers, Vol.3, No.1, pp.279-300
Rekha, G. (2014) “Effect of Working Capital Management on Firms Profits: Evidence from the Pharmaceutical Sector,” International Journal of Management and Social Science Research, Vol. 3, No. 1, pp. 103-107
Sarbapriya, R. (2012) “Evaluating the Impact of Working Capital Management Components on Corporate Profitability: Evidence from Indian Manufacturing Firms. International Journal of Economic Practice and Theories, Vol. 2, No. 3, pp. 127-136
Solabomi, O. A. (2013) “Working Capital Management and Financing Decision: Synergetic Effect on Corporate Profitability,” International Journal of Management, Economics and Social Science, Vol. 2, No. 4, pp. 233-251
21
Tewolde, S. (2002) Working Capital Management: The Case Of Government Owned, Transnational and Privatized Manufacturing Firms in Eritrea,” University of Groningen, Faculty of Management and Organization.
Ullah, K. (2011) “Working Capital Management and Profitability: An Analysis of Firms of Textile Industry of Pakistan,” Journal of Management Science, Vol.6, No.2, pp. 155-165
Zubair, A. and Muhammad Y. G. (2013) “Impact of Working Capital Management on Profitability: A Case of the Pakistan Cement Industry,” Journal of Contemporary Research in Business, Vol. 5, No. 2, pp. 384-390
22
CHAPTER TWO
REVIEW OF RELATED LITERATURE
INTRODUCTION
This chapter reviews some of the related literature on impact of working capital management on
firms’ profitability among different countries. The theoretical point is divided into many sub
chapters concerning the subject of the thesis. For this point, much background information has
been collected from different articles and literature.
2.1: CONCEPTUAL FRAME WORK
2.1.1: Definition and Concept of Working Capital
The term “working capital” is that portion of total funding needed for day to day operation of an
entity (Nwude, 2004:627). Adarquah (2013) sees it as basically short-term resources available to
a company for financing its day-to-day activities. Ani, Okwo and Ugwunta (2013) is of the view
that working capital is the stock stored that has a conversion or resale value in order to gain
profit. On their part, Vallalnathan and Joriye (2012) equally view it as the flow of ready funds
necessary for the working concern. Sarbapriya (2012) sees it as the result of the time lag between
the expenditure for the purchase of raw material and the collection for the sale of finished goods.
Again Muhammad, Ullah Jan and Ullah (2011) see it as a financial metric which represents the
amount of day to day operating liquidity available to a business. Working capital is needed every
day until the on-going project is completed (Kumarel et al. 2002). Richards & Laughlin (1980)
discovered that working capital is needed in every step of the process but it changes after certain
steps. It is a circulating capital which flows and changes forms as the firm pursues its goal and
performs its operations (Nwude, 2004:627). Also according to Nwude, (2004:627) it is a
financial lubricant or life stream for firm and maintain constant process of circulation throughout
the firm. A narrow definition for the working capital is inventory plus account receivable minus
account payable. Working capital meets the short term financial requirement of a business
enterprise (Loen, 2013).
The major concepts of working capital are the gross working capital and the net working capital.
Gross working capital is the totality of firms’ investment in current assets such as inventory,
accounts receivable, short term marketable securities and cash. Net working capital is the totality
23
of firms’ investment in current assets less the totality of the firm’s current liabilities. Current
liabilities includes items such as accounts payable, notes payable, accruals, customers deposit
(i.e. prepayment) deferred taxes and short- term deposit obligation.
2.1.2: Working Capital Cycle
working capital cycle is the length of time it take a firm, from the time it paid cash for the raw
material purchases to the time the firm collect cash from its sales ( Nwude, 2004). It is also
defined as the amount of time it takes to turn the net current asset and current liabilities into cash.
The longer the cycle is, the longer a business is tying up capital in its working capital without
earning a return on it (www.divestopodia.com). According to mysafaribooksonline, working
capital or operating cycle refers to the period that an enterprise takes in converting the cash back
into the business from the cash initially invested in various operating activities of the enterprise.
The said cycle starts from the cash blocked by the way of purchase of raw materials and ends
with the realization of cash out of sales. Therefore, the said cycle is the time lag between the cash
investment in purchase of raw materials and the recovery of cash by the way of sales of goods. In
the mean period, the cash engaged in operation is being gradually converted into different forms
of working capital till its recovery from sales. The working capital cycle can be seen from the
figure 1
Figure 1, the working Capital Cycle (Nwude, 2004, pp.632)
Cash
Receivable
Finished goods
Work-in Progress
Raw materials
24
The basic activities of companies are purchasing, production, sales and collection of payment.
The cash is invested to the production cycle when resources are purchased. The tied up cash is
back to use after company has collected payment from the sales. The cash that is invested in
working capital cannot be invested to some profitable targets (Talonpoika, 2012). The four keys
dates in product cycle that influence the firm’s investment in working capital are as follows;
• Account Payable Period: The firm starts the cycle by purchasing raw materials, but does
not pay for them immediately. This delay is the account payable period.
• Inventory Period: the firm processes the raw materials and then sells the finished goods.
The delay between the initial investment in inventories and the sale date is the inventory
period.
• Account Receivable Period: sometimes after the firm has sold the goods to its customers
pay their bills. The delay between the date of sales and the date at which the firm is paid
is the account receivable period.
• Cash Conversion Cycle: The sum of the inventory period and account receivable period
gives the length of time it takes the purchased raw materials to transform into cash. The
cash conversion cycle can be calculated using the working capital ratio as shown below;
1. Inventory period = Average Inventory/ Annual cost of goods sold *365/1
2. Account Receivable Period = Average Account Receivable/ Annual sales*365/1
3. Account Payable Period/ Annual cost of goods sold*365/1
Cash Conversion Cycle = Inventory period + Receivable period – (Payable period).
Inventory Period = Raw materials period + work-in-progress + finished good period.
Raw Materials Period is the number of days raw materials are heed in store before they are
converted into worn-in-progress.
Work- In-Progress Period is the number of days the raw materials are in the process before
conversion into finished goods.
Finished Good Period is the number of days the finished goods held before they are sold
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2.1.3: Working Capital Policy
A company needs to closely monitor its working capital levels in order to keep its cash
requirements formally in check. Lack of attention to the investment in working capital (account
receivable, inventory and payables) may result in a runaway need of cash, especially when sales
are growing. A business can do this most effectively by instituting and enforcing a number of
policies.
Working capital policy involve decision about company’s assets and liabilities- what they consist
of, how they are used, and their mix affect the risk versus return characteristics of the company
(Soyemi and Olawale, 2014). However, it is basically about how much working capital the
company should maintain. According to Pieterson, (2012) Working capital policy involves
decision about company’s asset and liabilities-what it consist of, how they are used, and their
mix affect the risk versus return characteristics of the company. Through their effect on the firms
expected return, ultimately have an impact on shareholder wealth. Thus, an efficient working
capital management is critical for the long-term survival of a business (Padachi & Howorth,
2014).
These policies have been divided into two categories by Weinraub and Visscher (1998) they are;
1. Aggressive working capital policy
2. Conservative working capital policy
Aggressive: An aggressive working capital policy is one in which you try to squeeze by with a
minimal investment in current asset coupled with an extensive use of short-term credit. Your
goal is to put as much money to work as possible to decrease the time needed to produce
products, turnover inventory or deliver services. Speeding up your business cycle grows your
sales and revenues, you keep little money on hand, cut slow- moving inventory and unnecessary
supplies to the bone and stretch out your bill payments for as long as possible. The one payment
you cannot delay is interest- your creditors can sue you, force you into bankruptcy and liquidate
your assets. You could also want to avoid missing tax payments.
Conservative working capital policy is good for companies in volatile or seasonal industries
such as tourism; farming or construction might adopt conservative working capital policy to
buffer against risk. If you employ a conservative working capital policy, there is plenty of cash in
26
the bank, your warehouse are full of inventory and your payables are all up to date. If you
compute the working capital ratio- current asset/ current liabilities – a conservative policy might
yield a ratio above 2:0 that is, you have more than $2 in current asset for every dollar of short-
term liabilities. Conservative managed working capital will help lower your risk of short-term
cash shortages but might hurt your long-term profitability, because excess cash doesn’t earn
much of a return.
Generally, efficient working capital management depends on working capital policy adopted,
distinguished as conservative or aggressive policies. The conservative working capital policy
implies a higher investment in working capital accounts, such as higher level of inventories,
extending more trade credit to customers and reducing supplies financing, resulting in lower
profitability and lower risk (Gomes, 2013). In contrast, aggressive working capital policy implies
lower investment in working capital accounts, through lower level of investment in inventories,
shortening trade credit to customers and postponing payment to suppliers, resulting in an
increase of profitability & risk for firm (Blinder & Maccini, 1991).Therefore, more aggressive
working capital policies are associated with higher return and higher risk while conservative
working capital policies are concerned with the lower risk and return (Carpenter and Johnson,
1983; Gardner, et al., 1986; Weinraub and Visscher, 1998).
2.1.4: Factor Influencing Working Capital Requirement
According to Nwude, (2004:629) they are as follows;
1. Production Cycle
Production cycle is the period of time needed for a production process to produce a finished
product. It starts with the procurement of the relevant raw materials to the end of the
production. The time period includes the time it takes to procure the raw materials onto
production arena plus the time it takes to return the raw materials into finished product ready
for sale. The longer the productions cycle the longer the working capital requirement.
2. Nature of Business
Manufacturing, trading (whether wholesale or retail), service delivery and so on, each has its
influence on working capital requirements. If a business engaged in stock-piling inventories
with the hope of selling them during the season’s large working capital will be in stocks. If it
is a manufacturing concern, heavy working capital will be invested in raw materials to ensure
continuity in production. Therefore the nature of business has substantial influence on
working capital requirements.
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3. Size of Business
The level of activity also influences the working capital needs. A higher level of activity
requires additional stock of raw materials or finished goods to meet higher production or
sales request. Additional investment in account receivable will be needed, as a result of
increase in sales, which will equally attract increment in receivables. Equally a lower level of
activity will attract a lower level of investment in working capital.
4. Fluctuations in Business
Boom increases the scale of operation of a firm. Recession decreases the scale of operation of
the firm. Levels of stocks and debtors increase during boom thereby necessitating additional
investment in assets while the reverse is the case under recession.
5. Credit Policy
A conservative credit policy is expected to lead to low investment in receivables and by
extension lower working capital requirements. A liberal credit leads to increase in
receivables and by extension a higher working capital needs.
6. Credit Availability
A firm that enjoys liberal credit terms from its suppliers or bankers will operate with less
working capital than a firm without such facility.
7. Dividend Policy
Dividend is the portion of the earnings available to common shareholders that is share among
the common shareholders as reward for their ownership stake in the business. Cash is one of
the current assets or working capital items payment of cash dividend depletes cash and thus
reduces the working capital to that extent. If all earnings are retained or ploughed back in the
business, working capital position will be improved.
8. Efficiency in Operations
Efficiency in operation means optimal resources utilization at minimal operating costs.
Optimal utilization of resources improves profitability and by extension improve the earnings
ability of the firm. The enhanced earning capacity results in improved an retained earnings
which helps in increasing working capital.
9. Price Changes
In a period of rising price levels, cost of things will rise, and companies that need to maintain
the same level of current assets will need more working capital. The same level of the current
assets will need lower working capital when prices decrease.
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2.1.5: Rationale for Working Capital
Every business needs adequate working capital in order to maintain day to day cash flow. It
needs enough cash to pay wages & salaries as they all due and to pay creditors if it is to keep its
workforce and ensure its supplies. Maintaining adequate working capital is not just important in
the short-term because sufficient liquidity must be maintained in order to ensure the survival of
the business in the long-term as well. Working capital as the life blood of every business concern
for this reason, no business can be run successfully without adequate amount of working capital.
The advantages of maintaining adequate working capital are as follows;
• Continuous production: Adequate working capitals ensure regular supply of raw
materials and continuous production.
• Solvency and Goodwill: adequate working capital enables prompt payment to
creditors. This help in creating and maintaining goodwill.
• Easy loans: a concern having sufficient working capital enjoys high liquidity and
good credit standing. Hence it can secure loan from bank and other easy and
favorable terms.
• Cash Discount: adequate working capital enables a concern to avail cash discount on
the purchases, leading to a reduction in cost.
• Regular payment of Expenses: a company which has ample working capital can make
regular payment of salaries, wages and other day to day commitment. Such prompt
payment raises the morale of the employees and increases their efficiency. As a result
costs are minimized and profit increases.
• Exploitation of the Market Conditions: a concern with adequate working capital can
exploit favorable market conditions. It can buy its requirements of raw materials in
bulk when the market price is lower. Similarly, it can hold stock of finished goods to
realize better prices.
• Adequate working capitals enable a concern to face business crisis such as depression
because during that period there is much pressure on working capital.
• High Return on Investment: adequate of working capital facilitates continuous
production and effective utilization of fixed assts. Because of this, the concern is able
to generate more profits and ensure higher return on investment.
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2.1.6: Working Capital and Liquidity
Working capital is a common measure of company liquidity, efficiency and overall wealth.
Because it include cash, inventory, account receivable and account payable, the portion of debt
due within one year and other short-term account. It also can be looked at as the excess of total
current assets over total liabilities. Thus the larger the amount of working capital the stronger the
liquidity position of the business organization (Almazari, 2014). Nzioki et al., (2013) is of the
view that corporate liquidity is influenced by the cash cycle because cash cycle measures the
average amount of time that cash is tied up in operations process. Therefore a firm with a short
term cash cycle is expected to have high level of cash and marketable securities, all else being
equal. Working Capital is an indication of company’s operating liquidity. Having enough
working capital means that companies should be able to pay for all its short-term expenses and
liabilities. According to Smith (1980) there is a trade-off between liquidity and profitability,
which are the dual goal of working capital management. These goals imply that decisions that
tend to maximize profitability tend to minimize liquidity and vice versa. Conversely, focusing
almost entirely on liquidity will tend to reduce the potential profitability of the firm (Eljelly,
2004). Managing current assets directly affects the liquidity of the firm, so efficient management
of current assets leads to better liquidity position for the firm. The better the liquidity position of
the firm, the easier it becomes for the firm to manage its expenses and obligations. Firms have to
determine the individual and joint impact of the levels of short-term investment and financing on
the dual objectives of working capital management. According to Mohammed (2011) Liquidity
has so far been define as a pyramid of current assets in descending order of realizability which
cash holding at the top position and inventories the last. As it is clear by now, liquidity is one of
the most important goals of working capital management and central task of cash management
(Lamberg & Valmngm, 2009). Almazari (2014) sees it as the average time period required to
convert non-cash current assets into cash; the shorter the period required the stronger the
liquidity position of the business organization.
Liquidity of firm can be measure with the following liquidity ratios;
Current ratio = current assets/ current liabilities
Quick ratio = current asset- inventory/ current liabilities
2.1.7: Rationale for Working Capital Management
Working capital management is a very important component of corporate finance because it
directly affects the liquidity and profitability of the company (Raheman & Nasr, 2007). It can be
30
expected that the way in which working capital is managed will have a significant impact on the
profitability of the firm (Deloof, 2003).
Working capital management is important due to many reasons;
• Every organization needs proper management of working capital in order to avoid the
problem of illiquidity. Poor management of working capital results to liquidity problems
which might lead to bankruptcy in severe cases (Nwude, 2004).
• Proper working capital management helps to improve sale and consequently the profit of
the company.
• Working capital management increases cash flow speed, decreasing irrecoverable
receivables and decreasing the costs to create opportunities to maximize the wealth of the
shareholders.
• Effective working capital management consists of applying the methods which remove
the risk and lack of ability in paying short term commitments in one side and prevents
over investment in these assets the other side by planning and controlling current assets
and liabilities (Lazaridis, & Tryfonidis, 2006).
• For one thing, the current assets of a typical manufacturing firm account for over half of
its total assets. For a distribution company, they account for even more (Raheman &
Nasr, 2007).
2.2: THEORETICAL REVIEW
2.2.1: THEORY OF WORKING CAPITAL MANAGEMENT
The interaction between current assets and current liabilities is the main theme of the theory of
working capital management, is concerned with the problem that arises in attempting to manage
the current assets, the current liabilities and the inter-relationship that exit between them. The
goal of working capital management is to manage a firm’s current assets and liabilities in such a
way that a satisfactory level of working capital is maintained.
a Conservative theory
This approach suggests that the estimated requirement of total funds should be met from long term sources, the use of short term funds should be restricted to only emergency situations or there is unexpected outflow of funds.
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b Hedging theory
Hedging approach is more risky in comparison to conservative approach. There are two reasons for this. First, there is, as already observed, no NWC with the hedging approach because no long term funds are used to finance short term seasonal needs, that is, current assets are just equal to current liabilities. On the other hand, the conservative approach has a fairly high level of NWC. Secondary, the hedging plan is risky because it involves almost full utilization of the capacity to use short term funds and in emergency situations it may be difficult to satisfy the short term needs. Comparison of hedging approaches with conservative approach; a comparison of the approaches can be made on the basis of (i) cost considerations, and (ii) risk considerations. Cost considerations: the cost of these financing plans has a bearing on the profitability enterprise.
c Trade off theory
A Tradeoff between the Hedging and Conservative Approaches.
It has been shown that the hedging approaches are associated with high profits as well as high risk, while the conservative approach provide low profits and low risk. Obviously, neither approach by itself would serve the purpose of efficient WCM. A trade off between these two extremes would give an acceptable financing strategy. The third approaches strikes a balance and provides a financing plan that lies between these two extremes. The exact trade off between risk and profitability will differ from case to case depending on risk perception of the decision makers. One possible trade off could assume to be equal to maximum monthly requirements of funds during a given period manage. This level of requirement of fund may be financed through long run source and for any additional financing need short term fund may be used.
2.2.2: Impact of Working Capital Management on Company Profitability: Theoretical base
When the cash conversion cycle shortens, cash becomes free for other usages such as investing
on equipment and infrastructure or innovating manufacturing and selling process or lowering the
total investment in current assets (Huynh, 2012). It accordingly brings company with higher
operating profitability. In contrast, when the cash conversion cycle lengthens cash is tied up in
firm’s operation activities, leaving little chance for other investments of this cash flow. Company
profitability is decreased as a result. In those cases cash conversion cycle is said to have a
negative relationship with company profitability. On the other hand, cash conversion cycle can
also have positive influence on company profitability. It could be interpreted through a chain of
positive impact of inventory periods and account receivable period with a negative impact of
accounts payable period on the company profitability. The longer the inventory, the lower the
cost involved in procrastinating of goods and/ or service supplied.
32
In mean time, the longer the account receivable period, the higher credit sales earned. And the
lower the accounts payable period, the higher the reputation earned for borrowing opportunities.
Converge the three effects into one place, we can explain for an increase in company profitability
due to the long cash conversion cycle. In contrast, shortening the cash conversion cycle could
harm the company profitability. The company could face inventory shortages as reducing
inventory conversion period, lose good credit customers as reducing account receivable period,
and hamper its credit reputation as lengthening the account payable period. In those cases, cash
conversion cycle is said to have a positive relationship with company profitability.
2.2.3: Measuring Working Capital Management
Most popular measurement of working capital management is cash conversion cycle (CCC)
which is the time lag between purchase of raw materials or render of services and the collection
of cash from the sale of goods or services rendered (Vural, Sokmen & Cetenak, 2012). One of
the criteria for evaluating working capital is cash conversion cycle (Abbasali, Esmail & Moein,
2013).Which they defined as the time between the purchase of raw materials and collecting the
proceeds from the sale of the made goods. If the time lag is longer, it means greater investment
to working capital components and this causes greater financing needs. But if the time lag
shortens, it means lower investment to working capital components as well and this will result to
a lower financing need. In the mean time, cash conversion cycle starts from the very moment
payment in cash is made for the raw materials purchased to the time debtors paid-up their debts
(Nwude, 2004; 631). In general, cash conversion cycle is computed as the sum of inventory
period and accounts receivable period less accounts payable period.
Cash Conversion Cycle = Inventory Period + Account Receivable Period -
(Accounts Payable Period).
Cash conversion cycle tells us how cash is moving through a company in terms of duration. The
cycle start with a cash outflow by which the company pays back to suppliers for obtaining raw
materials then end with a cash inflow when receiving money back from its customers for selling
its goods or services (Huynh,2012). For the working capital components (Inventory Period,
Account Receivable Period and Accounts Payable Period) the meaning and the computation
techniques has been stated above under working capital cycle page 12-13.
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2.3: EMPIRICAL REVIEW
INTRODUCTION
There have been a number of studies and academic researches to find out the relationship
between working capital management and profitability. Working capital management is
important for enhancing profitability and creating shareholders value, and was found in so many
studies in different countries that it has a significant impact on profitability and liquidity. So this
section presents the chronology of major studies related to this study in order to assess and
identify the research gap.
Almazari (2014) investigated the relationship between the working capital management and the
firm’s profitability of Saudi Cement manufacturing companies. Only 8 companies were studied
which are listed in the Saudi Stock Exchange market for the period of 5 years from 2008-2012.
The dependent variable of the study was gross operating profit as a proxy for profitability.
Independent variables were cash conversion cycle (CCC), Inventory Conversion Period (INV,
Receivables Collection Period (DSO), Payables Deferral Period (PAY). In addition to these
variables, some other variables were used which include Firm Size (lnSales) Fixed Financial
Asset Ratio (FixEDFA), and Financial Debt Ratio (Debt). Using Pearson correlation and linear
regression test, they found a significant negative correlation relationship between gross as
dependent variable, and five independent variables namely; PAY, CCC, INV and DSO. At the
same time, there is a significant positive correlation relationship between gross and Lnsales,
FixEDFA respectively. They concluded that current ratio is the most important liquidity measure
which affects profitability in Saudi Cement Industry.
Iqbal, Ahmad& Riaz (2014) Studied the Relationship between Working Capital Management
and Profitability: Evidence from Pakistan. A database was built from a selection of
approximately 50 financial-reports that were made public by publicly traded companies of
Pakistan between January 1, 2009 and December 31, 2009. Secondary data is used for analysis of
working capital on profitability using descriptive, ANOVA and correlation analysis, the result
revealed a significant negative relationship between net operating profitability and the average
collection period, inventory turnover in days, average payment period and cash conversion cycle
for a sample of Pakistani firms listed on Karachi stock exchange.
34
Jayarathne (2014) this paper attempted to assess the effect of Working Capital Management on
profitability of listed companies in Sri Lanka. Using five years (2008-2012) dataset on 20
manufacturing firms listed in Colombo stock exchange. Profitability was measured using Return
on Asset (ROA) as dependent variable. Account Receivable (AR), Inventory (INV), Account
Payable (AP) and Cash Conversion Cycle (CCC) were independent variables while firm size
(Slog), Sales Growth (SG) and Debt Ratio (DR) were used as control variables. Using OLS
regression analysis, the result shows that AR, INV, AP, DR and CCC have a negative impact on
profitability while Slog and SG have a positive impact on profitability. Generally they suggested
that a liberal credit policy tends to decrease the profitability.
Agha and Mphil (2014) investigate the impact of working capital management on profitability.
To investigate this relationship between these two, the author collected data from Glaxo Smith
Kline Pharmaceutical Company registered in Karachi Stock Exchange for the period of 1996-
2011. Return on Asset ratio (ROA) was used to measure profitability (dependent variable) and
Account Receivable Turnover (ART), Creditor Turnover (CTO), Inventory Turnover (DTO) and
Current ratio as independent variables. Using correlation and regression analysis, the results
shows that CTO, DTO, and ITO have a positive significant impact on ROA, but there is no
significant impact of CR ON ROA.
Gulia (2014) threw light on the impact of working capital management on the firm profit after
tax and cash profit of the leading Pharmaceutical firms. 6 firms were identified and data was
collected for five years (2009-2013). Liquidity, turnover conversion cycle and net working
capital ratio are selected represent the independent variables on profit of the firm ( i.e dependent
variable). Using correlation and multiple regressions, the outcome shows that there exist
correlation among variables and the networking capital and debt ratio of the firm have significant
impact on the profit of the firms.
Jafari, Salahinezhad and Jalili (2014) examined the effects of working capital management on
firm’s bankruptcy probability listed in Tehran Stock Exchange. The financial data of 54 firms
listed in Tehran Stock Exchange during the years of 2002-2010. To measure the working capital
management in this study, cash conversion cycle was used and to measure the probability of
bankruptcy, Altman model was also used. Using regression and ANOVA the results indicated
that, there is a negative relationship between working capital management and the risk of
35
bankruptcy, and that this means that, whenever a firm’s cash conversion cycle is longer, it will
be in a worse situation of bankruptcy risk.
Padachi, Howorth & Narasimhan (2012) investigated into the small medium sizes manufacturing
firms approach to working capital management routines. The research objectives are addressed
using a survey based approach, supplemented by 12 mini case studies. Statistical analysis was
perform using ANOVA and t-test and Whitney and Kruskal- Wallis tests, chi-square test for
continuous, ordinal and binary variable respectively. The findings consistently high lighted that
Mauritian SMEs are not homogenous group with regard to working capital management
routines.
Mobeen & Naveed(2013) examined the impact of the working capital management on the profitability of Pakistan Cement Sector. Figures was collected from Annual Reports and sample consist of 10 Pakistani Cement Companies listed at KSE from 2003-2008. The association between working capital management and profitability are examined with correlation and regression analysis, the results indicated negative as well as positive relationship between the variables. Current asset to sales, working capital turnover ratio registered negative correlation with return on asset. The slopes of the ROA equation portray that negative and positive association of variation in the independent variables on the productivity of the company.
Akoto, Vitor and Angmar (2013) analyzed relationship between working capital management
practice and profitability of listed manufacturing firms in Ghana. The study used data collected
from annual report of all the 13 listed manufacturing firms in Ghana covering the period from
2005-2009. Using panel data mythology and regression analysis, the study found a significant
negative relationship between profitability and account receivable days. However, the firm’s
cash conversion cycle, current asset ratio, size and current asset turnover significantly positively
influence profitability. The study suggests that managers can create value for their shareholders
by creating incentives to reduce their account receivable to 30days.
Arshal (2013) studied to find out empirical impact of the relationship between working capital
management and profitability of 21 Pakistan Cement Companies listed in Karachi stock
exchange during the period of 2004-2010. Simple linear regression analysis was done for return
on assets (dependent variable) with independent variables; current ratio(CR), quick ratio (QR) ,
net current assets to total assets ratio (NCA/TA), working capital turnover ratio (WCT) and
36
inventory turnover ratio(ITR). The result showed that there is significant negative relationship
between working capital management on profitability of the firms.
Alavinasab & Davoudi (2013) examined the relationship between working capital management
and profitability of 147 companies listed on Tehran stock exchange during the period of 2005-
2009. The effect of various variables of working capital management including cash conversion
cycle (CCC), the current ratio (CR), current asses to total asset ratio ( CATAR), current liabilities
to total asset ratio (CLTAR) and debt to total asset ratio (DTAR) on return on assets and return
on equity are studied. Multivariate regression and Pearson correlation are used to test hypothesis
and the result showed a negative significant relationship exist between CCC and return on assets
and there is also a negative significant relation between CCC and return on equity. However the
relationship between current ratio and return on equity is insignificant.
Ajibolade (2013) this study provided empirical evidence on the interaction between working
capital management and corporate debt structure, and the effect of this on corporate profitability.
The assumption the study was based is that, if internal fund become the preferred source of
finance for Investment projects, then working capital composition is interfered, making both
decision co- dependent. Using a two year (2011-2012) data set on 35 manufacturing companies
listed on the Nigeria stock exchange. Panel exploration and factorial- ANOVA estimation
techniques were used to estimate the econometric models. the results suggested a significant
negative relationship between firm’s working capital composition and their debt structure choice.
Additionally, on individual basis, the study found a positive significant relationship between debt
structure and capital composition and profitability.
Ramana, Ramakrishnaiah & Chengalrayulu (2013) studied the impact of impact of Receivables
management on working capital profitability. Data was collected from the annual report of 4
cement companies India for the period from 2001 to 2010. The ratios whish highlight the
efficiency of receivable management viz; Receivables to current assets ratio, receivables to total
assets ratio, receivables to sales ratio, receivables turnover, average collection period, working
capital ratio and profitability ratio was computed using ANOVA to know the impact on working
capital and profitability. Working capital and profitability are considered as dependent variable
and the investigation revealed that the receivable management across cement industry is efficient
and showed significant impact on working capital and profitability.
37
Warrad (2013) conducted to approve the impact of capital turnover as measure of efficiency on
Jordanian chemical companies profitability listed on the Amman stock exchange for the period
2009-2011.Using a simple linear regression to test the impact of working capital turnover on
Jordanian chemical industries profitability through Return on Assets (ROA). The result showed a
significant impact of independent variable working capital turnover on dependent variable return
on assets.
Gomes (2013) analyzed the relationship between working capital management and firm’s
profitability for Portugal. Database used was firm- level financial data with a matched employee
data, for the period from 2004-2009 and observations was 41436 firm. The relationship between
working capital management and profitability is analyzed using panel data, applied fixed effect
model with robust standard errors. The findings showed that there was a concave relationship
between working capital management and profitability indicating that firms have an optional
working capital level where firms should stand to maximize profitability.
Nzioki et al. (2013) analyzed the effect of working capital management on the profitability of 6
manufacturing firms in Kenya listed on the Nairobi securities exchange. The data was obtained
through documented analysis of consolidated financial reports of years ending December 2006-
2010 of the 6 companies. The data collected was analyzed using multiple regression and
correlation analysis to establish relationship between the independent variables of working
capital; Accounts Collection Period (ACP), Accounts payable Period (APP), Inventory Turnover
on Days (ITID), Cash Conversion Cycle (CCC) and the dependent variable is Gross Operating
Profit (GOP). Liquidity (CR), Financial Assets (FATA), Debt Ratio (DR) are control variables.
The result revealed that gross operating profit was positively correlated with ACP and APP but
negatively correlated with CCC. The relationship between ITID and GOP was insignificant. It
argued that managers should focus on reducing cash conversion cycle and try to collect
receivables as soon as possible.
Loen (2013) attempted to take result of comparison among industries based on working capital
management. The relationship between based on working capital management practices and its
effects on profitability of selected industries listed on Colombo Stock Exchange for the period of
five years 2003- 2007. Working capital components current ratio, quick ratio, cash ratio and debt
ratio (i.e independent variables) while Return on Assets or Return Equity or Return on Capital
38
Employed are proxy for profitability (dependent variable). Using correlation and regression
analysis, results concluded that working capital has significant impact on profitability of the
sector. Therefore, the significant indicates that closed relationship between working capital and
profitability. It may be positive or negative.
Tufail (2013) examined the impact of working capital policies on profitability of Textile firm in
Pakistan listed on Karachi Stock Exchange for the period of six years 2005-2010. Return on
Assets is used as a measure of profitability. Current assets to total assets ratio is used to compute
the investment policy of working capital management and to determine financing policy of
working capital management , current liabilities to total assets ratio is used. Other variables that
are used are quick ratio, debt to equity ratio and size of the firms. Using correlation and
regression analysis the results revealed with profitability. Moreover liquidity and size of the firm
have positive relation with profitability whereas debt to equity ratio is negatively correlated with
profitability.
Ani, Okwo & Ugwunta (2013) studied working capital management as measured by the cash
conversion cycle (CCC) and how the individual components of the CCC influence the
profitability of the world leading Beer Brewery Firms for twelve years period (2000-2011).
Multiple regression equation were applied to a cross sectional time series data of 5 firms after
ensuring that the data are stationary and co- integrated. The outcome clearly pointed that
working capital management represented by the cash conversion cycle, sales growth and lesser
debtors collection period impacts on beer brewery firm’s profitability.
Ebenezer & Asiedu (2013) examined the effect of working capital management on the
profitability of companies listed on the Ghana stock exchange for the period five years (2007-
2011). Using panel data regression analysis of cross sectional and time series data. The result
showed that, the major component of working capital management such as inventory days,
accounts payable and cash conversion cycle have influence on the profitability of manufacturing
companies. He argued that, manufacturing companies should adopt efficient and effective ways
of efficient managing these components of working capital management.
Abbasali, Esmail & Moein (2013) provided empirical evidence about the effects of working
capital management on viability of listed automotive companies in the Tehran stock exchange
39
during the period of five years (2006-2010).Using three models; consolidation method, fixed
effects and random effects for analysis. Result from the first model estimation indicated that all
studied independent variables (leverage degree, firm size, & liquidity) have significant and
positive effect on the profitability index of companies. The second and third model estimation
also showed that inventory turnover and cash conversion cycle have significant and negative
effect on the return on assets.
Makarani and Bineshian (2013) examined the relationship between the working capital
management and profitability for a real world case study in Iran over the period 2004- 2012.
There three components associated with working capital management, accounts payable period,
inventory turnover period and receivable accounts period. The study used cash conversion cycle
to investigate the impacts of working capital management on profitability, simultaneously. Using
Pearson correlation as well as regression techniques, the result indicates an inverse relationship
between variables of working capital and profitability.
Makori & Jagongo (2013) analyzed the effect of working capital management on firm’s
profitability in Kenya. Observation of 5 manufacturing firms listed in Narobi securities exchange
for the period of 2003 to 201 2. Pearson ‘s correlation and ordinary least square regression
models were used to establish relationship between working capital management and firms
profitability. The study found negative relationship between profitability and number of day
accounts receivable and cash conversion cycle, but a positive relationship between profitability
and number of inventory and number of days payable. Moreover the financial leverage sales
growth, current ratio and firm size also have significant effects on the firm’s profitability.
Adarquah and Korankye (2013) analyzed working capital management and its impact on firm
profitability. Panel data was obtained from 6 financial statement of listed manufacturing firms in
Ghana from 2004-2011. They used working capital cycle and gross operating profit as proxies
for working capital management and profitability respectively. While leverage, interest cover
and the ratio of current asset to total assets are used as control variable. The study employed
descriptive statistics, Pearson correlation and ordinary least square regression analysis. The result
revealed that working capital cycle significantly affects firm profitability negatively. From the
correlation analysis, the study also found that inventory turnover, account receivables collection
period and account payables payment period each negatively correlated with profitability.
40
Arunkumar & Ramanan (2013) analyzed the effect of working capital management on the
profitability of manufacturing firms. The data analysis was carried for 1198 manufacturing firm
listed in Centre for Monitoring Indian Economy for a period f 5 years. The relationship of
debtor’s days, inventory days, creditor’s days, current ratio, ratio of current liability to total
assets, assets turnover ratio, financial assets to total assets and size with return on assets
employed is analyzed. Using correlation analysis and group wise weighted least squares
regression analysis to identify the effects of these variables on profitability. The correlation
analysis showed that the firms’ profitability is highly influenced by the variables relating to
assets. They found a positive relationship between profitability and debtors’ days and inventory
days. Creditor’s days shows a significant positive relationship.
Priya (2013) the study examined the working capital management of the Food and Beverage
Corporations from the U.S.A. and Canada during the 10 years study period from year 2000 to
2000 and the efficiency of working capital management was checked using performance index,
utilization index and efficiency index rather than using the conventional turnover ratios, the
distribution of working capital measure i.e. cash conversion cycle and factors affecting viz.
leverage, growth, size, age, cash flow and fixed assets to total assets ratio has been studied. The
results suggest the existence of concave relationship between the working capital management
and profitability. The findings also revealed that the corporations were efficient during the study
period.
Egbide, Olubukunola & Uwuigbe (2013) investigated the relationship between liquidity and
profitability the analysis is based on a sample of 30 manufacturing companies listed on the
Nigeria Stock Exchange for the period 2006-2010. Using correlation, ANOVA and correlation
the result suggests that current ratio and liquid ratio are positively associated with profitability
while cash conversion period is negatively related with profitability of manufacturing companies
in Nigeria. Hence, the overall state of liquidity should be improved by establishing more realistic
credit policy which would engender shorter cash conversion period (CCP), hence have a
favorable impact on the profitability of the company.
41
Bose (2013) examine the trends in working capital management and its impact on firms’
profitability. The dependent variable, return on total assets (ROTA) is used as a measure of
profitability and the relation between working capital management is investigated for a sample of
30 manufacturing firms using panel data analysis for the period 2004-2012. The data for analysis
was collected from the financial statements published in the annual reports and some of the data
has been collected through interviews and questionnaire.ANOVA and correlation analysed was
used and the result reveal negative relationship with the independent variables except Cash
Position Ratio. It also found that working capital management of the company is very effective
and also the firm has to maintain the liquidity and solvency position to repay its obligations in
time.
Ganesamoorthy & Rajavathana(2013) effects of Working Capital Management on Profitability
of Select Automobile Companies in India. The study is analytical in nature and it primarily
depended on secondary data. For this purpose annual reports of the selected companies were
collected and calculations were made from it. The period of the study was nine years from 2003-
2004 to 2011-2012 and the study selected two automobile companies such as Tata Motors
limited (TATA) and Mahindra and Mahindra limited (M&M). Correlation analysis to know the
relationship between working capital management and profitability of the select companies, The
ratio of Return on Assets (RoA) was taken as proxy for profitability. Current Ratio (CR),
Average Collection Period (ACP), Average Payment Period (APP), Inventory Conversion Period
(ICP) and Cash Conversion Cycle (CCC) were considered as proxy for working capital
management of the select companies. Working capital management of both the companies had
insignificant relationship with profitability. Current ratio of TATA had positive relationship with
profitability, whereas it had negative relationship incase of M&M. Average Collection Period
and Average Payment Period had negative relationship with profitability of both the companies.
But the quantum of relationship was high in case of M&M. Inventory Conversion Period of
TATA had positive relationship with profitability, but in case of M&M it was negative. Cash
Conversion Cycle of both the companies had positive relationship with profitability, but the
quantum of TATA was higher than M&M. It was summarized that working capital management
had insignificant relationship with profitability of Tata Motors Ltd. and Mahindra and Mahindra
Ltd.
42
Nejad1, Bandarian, & Ghatebi (2013) investigated the relationship between working capital
management and profitability of listed companies in Tehran Stock Exchange. Research data was
analyzed using population of 116 listed companies in Tehran Stock Exchange for the period of
2006-2011 by applying combination method of all data (pooled data) and ordinary least squares
regression (OLS). The research results indicate that, there is a significant inverse relationship
between cash conversion cycle and its components, including the collection period, inventory
turnover period and accounts payable turnover period, and profitability of the firms. The results
revealed that corporate managers can increase the profitability of their company desirably by
reducing the collection period and inventory turnover period.
Jacob (2013) examined the working capital management and profitability: a study of selected
cement industry in India. The source of financial and economic data of selected companies is
based on the NSE (national stock exchange). Five companies are randomly selected from all
listed companies in the NSE, The time dimension of panel data runs yearly from 2011 to 2012.
The findings confirm that correlation between long-term debt and other independent variables
has been checked. The results shows that longer the current assets, operating profit, liquidity and
interest coverage ratio is negative relationship with LTD (long term debt) and other three
components of working capital management have a positive relationship LTD. Accordingly, the
findings of our results indicate that debt used by the firm are negatively associated with firm's
profitability. Results show that companies could make a low debt ratio tend to have a shorter
period to keep their inventory. Company will use the Internal finance may earn the high
profitability.
Egbide, Uwuigbe and Uwalomwa (2013) studied Liquidity Management and Profitability of
Manufacturing Companies in Nigeria. The analysis is based on a sample of 30 manufacturing
companies listed on the Nigeria Stock Exchange for the period 2006-2010. Using Correlation
and Regression ,the result suggests that current ratio and liquid ratio are positively associated
with profitability while cash conversion period is negatively related with profitability of
manufacturing companies in Nigeria. The association in all the cases was however, statistically
insignificant, indicating low degree of influence of liquidity on the profitability of manufacturing
companies.
43
Sarbapriya (2012) investigated the relationship between working capital relationship components
and the profitability of 311 Indian manufacturing firms for a period of fourteen years from
1996-97 to 2009- 10. They studied the effect of different variables of working capital
management including Average Collection Period (ACP), Inventory turnover in Days (INVT),
Average Payment Period (APP), Cash Conversion Cycle (CCC) and Current Ratio (CR) Debt
Ratio (DR), Size of firm (LnS) and Financial Assets to Total Assets Ratio (FDR) ON operating
profitability of Indian firms. Using Pearson correlation and regression analysis the result
suggested a strong negative relationship between ACP and CCC, FDR with corporate
profitability and insignificant negative relationship between LnS and its net operating profit
ratio.
Kaur and Singh (2012) studied on managing efficiency and profitability through working capital.
The study analyzed the working capital performance of 164 manufacturing, listed in Bombay
Stock Exchange for period of eleven years (2000-2010). Working capital score was calculated by
using normalized value of cash conversion efficiency, days operating cycle and days working
capital. The relationship between working capital score and profitability was tested using
correlation analysis. The result revealed that efficient management of working capital
significantly affect profitability.
Vural, Sokmen and Cetenak (2012) studied the effect of working capital management on firm’s
performance in Turkey. The study is based on secondary data collected from 75 manufacturing
firms listed on Istanbul stock exchange market for the period 2002- 2009. Using descriptive,
correlation and regression statistics analysis. The results demonstrated that firms can increase
profitability measured by Gross Operating Profit by shortening collecting period of account
receivable and cash conversion cycle. Also leverage as a control variable has a significant
negative relationship firm value and profitability of firms.
Asharaf (2012) examined the effect of different variables of working capital management
including the Debt Ratio (DR) Account Collection Period (ACP) Inventory turnover in Days
(Inv), Account Payable Period (APP) Cash Conversion Cycle(CCC) and Current Ratio (CR) on
the net operating profit of 16 Indian firm, listed on BSE from 2006- 2011. Using descriptive,
regression analysis, the results showed a strong negative relationship between variable of
working capital management and profitability of the firm except sales and also a positive
44
relationship between size of the firm and it profitability. Finally there is as well a significant
negative relationship between debt used by the firm and its profitability.
Owolabi and Obida (2012) measured the relationship between liquidity management and
corporate profitability. Liquidity management of a company was measure in term of it Debtor
Collection Period, Credit Payment Period and Cash Conversion Cycle. Using data from selected
manufacturing companies quoted on the floor of the Nigeria Stock Exchange. Using descriptive
analysis, the findings showed that liquidity management measured in terms of the companies
credit policies, cash flow management and cash conversion cycle have significant impact on
corporate profitability.
Barine (2012) studied working capital management efficiency and corporate profitability. A
sample of 22 quoted firm on the NSE for the year 2010. Using descriptive statistics, the results
showed that returns on improved working capital position of quoted firms in Nigeria are less
than the cost of working capital of these firms; indicated that there is inefficiency in the use of
working capital by these firms which affected their profitability negatively.
Pieterson (2012) studied the working capital management practice of small and medium scale
enterprises in the Western Religion of Ghana. A sample 199 based on secondary and primary
date. The study used descriptive and analytical sample survey for the representation and the
analysis of the findings. The result showed that 87.4% of the entrepreneurs functioned as sole
proprietors, whiles 14.1% as partnership and the remaining 1.5% as cooperative societies. The
results again showed that 46.1% received credit from suppliers and the average credit period
given by SMEs to their credit customers ranged between seven to sixty days(7- 60days).From the
study , two main problems faced by SMEs in dealing with credit customers are late payment and
bad debts. The results shows that 52.8% of the respondents use note books to represents cash
books whiles non(0%) of the respondents use computer inventory control. 65.3% of the
respondents have bank accounts for their businesses. Personal savings accounted for about
35.7% of the startup capital and SMEs consider inflation /price increases to be more problematic
than even high debtors turnover period and low stock turnover.
Rehn (2012) studied the effects of working capital management on company profitability in
swidish. A sample of 1789 for the period ten years (2002-2010).introduced research question
method and descriptive statistics was used. The result showed that there is a significant effect of
45
working capital management on corporate profitability. The net trade cycle and the cash
conversion cycle were used as determinants of working capital management efficiency and gross
operating profitability as the profitability variable. By testing the two variables with corporate
profitability, we were seen that finished and Swedish corporations can increase their gross
operating profitability by reducing the cash conversion cycle and net trade cycle.
Talonpoika (2012) studied the relationship between advance payment and profititability of 108
companies listed in Helsinki stock exchange. Using statistical analysis like histogram the result
indicated that 68 percent of the studied companies are receiving advance payments and the
average cycle time for received advanced payments is 13 days and there is negative correlation
between profitability and advance payments.
Onwumere, Ibe, & Ugbam (2012) investigated the impact of working capital management
policies of 28 Nigeria firms profitability quoted in Nigeria Stock Exchange for period 2004-
2008. Adopting the aggressive investment working capital policies and aggressive financing
policies as independent variables and return on assets as dependent variable, then size and
leverage as control variable. The result revealed that aggressive financing policies have a
positive non- significant impact on profitability.
Vuorikari (2012) optimized working capital management from processes perspective using
qualitative research method, the results conclude that working capital management can be
improved by actions with little effort, however, the most important process determined in the
studied that needed reformation were inventories purchasing and credit management.
Napompech (2012) examined the effects of working capital management on profitability. The
regression analysis was based on a panel sample of 255 companies listed on the Stock Exchange
of Thailand from 2007 through 2009. The results revealed a negative relationship between the
gross operating profits and inventory conversion period and the receivables collection period.
Therefore, managers can increase the profitability of their firms by shortening the cash
conversion cycle, inventory conversion period, and receivables collection period. However, they
cannot increase profitability by lengthening the payables deferral period. The findings also
demonstrated that industry characteristics have an impact on gross operating profits.
46
Natarajan & Getachew (2012) investigated the impact of WCM on the profitability of
cooperative unions in East Showa, Ethiopia. The quantitative research approach was employed to
accomplish the objectives of the study. The secondary data were collected from eight sample
cooperative unions in East Showa, Ethiopia that fulfill the criteria of the data availability from
the financial statement of the unions during the period from1999-2003 Ethiopian Calender
(E.C.). Random effect multiple regression model was used to analyze the panel data for the
standard determinants of working capital. The Generalized Least Square (GLS) estimator was
used as an efficient estimator for the Breusch Pagan test. The results showed that Average
Collection Period (ACP) has a negative effect on the profitability of the unions and also
indicated that as the unions decreased, ACP has increased the profitability of the unions. The
results from regression Inventory Turnover Period (ITP) has a positive effect on the profit of the
unions and also revealed that the comprehensive measure of WCM i.e. Cash Conversion Cycle
(CCC) showed a positive effect on the profitability.
Uremadu, Egbide and Enyi (2012) investigated Working Capital Management, Liquidity and
Corporate Profitability among quoted Firms in Nigeria Evidence from the Productive Sector. The
data were analysed using descriptive statistics and an OLS methodology, result found a positive
effect of inventory conversion period, debtors’ collection period, and negative effect of cash
conversion period, creditor payment period, on return on asset.
Huynh (2012) examined the influence of Working Capital Management on Profitability of listed
Companies in Netherlands. Analysis was employed to indentify the association between the
determination of Working Capital Management and the company profitability. In addition, the
fixed effect models and ordinary least square were chosen to conduct regression analysis for
examining how Working Capital Management affects profitability of companies. Fixed effect
regression indicated that company profitability in both sector ( manufacturing and service
sectors) is all negatively influenced by number of days accounts receivable, also number of days
inventory and cash conversion cycle are showed to be negatively affect the profitability of
companies operating in manufacturing area whereas they have positive influences on
profitability of service companies. In addition, manufacturing and service sectors respectively
witness negative influences of number of days account payables and aggressive financing policy
on their company profitability.
47
Muhammad, Jan & Ullah (2011) examined working capital management and
profitability. A sample of 25 textile industries in Pakistan listed in Karachi Stock
Exchange for the period of 2001- 2006. Using correlation and regression analysis,
result showed that there was a strong positive relationship between profitability and
cash, accounts receivable and inventory while there is a negative relationship between
profitability and accounts payable. Fast collection of accounts receivable is correlated
with high profitability.
Mohammed (2011) studied the effects of management of working capital policies on
firms’ profitability in developing countries. Thus, the study examined the effect of
working capital investment and financing policies on firms’ profitability by using
audited financial statements of a sample of 11 manufacturing private limited companies
in Tigray region, Ethiopia for the period of 2005 to 2009. The study used return on
assets, return on equity and operating profit margin as dependent profitability variables.
Accounts receivable period, inventory holding period and accounts payable period are
used as independent working capital investment policy variables. financial leverage
and annual GDP growth rate as control variables. Both correlation analysis and pooled
panel data regression models of cross-sectional and time series data were used for
analysis. The results show that longer accounts receivable and inventory holding
periods are associated with lower profitability. There is also negative relationship
between accounts payable period and profitability measures; however, except for
operating profit margin this relationship is not statistically significant. The results also
show that there exists significant negative relationship between cash conversion cycle
and profitability measures of the sampled firms. No significant relationship between
current assets to total assets ratio and profitability measures has been observed.
Bieniasz & Golas (2011) studied the Influence of Working Capital Management on the
Food Industry Enterprises Profitability. The research was conducted on the basis of the
unpublished data by the Polish Central Statistical Office in the trade structure and
dimension of food industry enterprises in Poland in the period of 2005-2009, and
comparatively, in respect of the food sector in selected Euro zone countries. The
working capital management efficiency was assessed by means of the inventory,
48
accounts receivables, current liabilities turnover cycles, cash conversion cycle, and in
respect of the obtained rates of return from non-financial assets. Using linear regression
and the linear correlation analysis, the research proved that in the food industry sector
with the shortest working capital cycles, relatively higher rates of profitability were obtained. A
favorable influence of working capital cycles reduction of the profitability was also verified by
means of a multiple regression analysis.
Quayyum (2011) investigated the effects of working capital management efficiency as well as
maintaining liquidity on the profitability of corporations. For this purpose, corporations enlisted
with the cement industry of Dhaka Stock Exchange have been selected and the analysis covers a
time period from year 2005 to 2009. The purpose of this paper was to establish relationship
which was 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. Using correlation and regression analysis the result clearly showed
significant level of relationship between the profitability indices and various liquidity indices as
well as working capital components.
Ali (2011) studied the association between working capital management and the profitability of
textile firms in Pakistan. The efficiency of working capital management is reflected by three
variables: cash conversion efficiency, days operating cycle, and days of working capital. They
used return on assets, economic value added, return on equity, and profit margin on sales as
proxies for profitability. A balanced panel dataset covering 160 textile firms for the period 2000–
05 was analyzed and estimated with an ordinary least squares model and a fixed effect model.
Return on assets is found to be significantly and negatively related to average days receivable,
positively related to average days in inventory, and significantly and negatively related to
average days payable. Also, return on assets has a significant positive correlation with the cash
conversion cycle, which would suggest that a longer cash conversion cycle is more profitable in
the textiles business. The findings of the regression analysis show that average days in inventory,
average days receivable, and average days payable have a significant economic impact on return
on assets. The findings of the fixed effect model reveal that average days in inventory and
average days receivable both have a significant impact on return on assets.
49
Garcia (2011) studied the impact of working capital management and its components upon the
profitability of European companies. Cash Conversion Cycle is used as a comprehensive
measure for working capital management and Gross Operating Profitability used as a measure
for profitability. The was study is based on a sample of 2,974 non - financial companies listed in
11 European Stock Exchanges for a period of 12 years: 1998 - 2009. Using GLS and OLS
regression analysis, the results found a significant negative relationship between Receivables
Collection Period, Inventory Conversion Period, Payables Deferral Period, Cash Conversion
Cycle and profitability. This suggested that companies can improve their profitability by
reducing the time span during which working capital is tied up within the company. An inverse
relationship between liquidity measured by Current Ratio and profitability was also found and an
additional analysis revealed that different levels of liquidity lead to differentiated impacts of the
Cash Conversion Cycle upon operating profitability.
Rahman (2011) studied working capital management and profitability of textiles firms in
Baggladesh for period of three years 2005-06 to 2007-08. The study was on both primary and
secondary data. Using correlation matrix and regression analysis, result revealed that correlation
exists between working capital management and profitability and also showed that working
capital management has a positive impact on profitability.
Alipour (2011) studied the relationship between working capital management and profitability.
Cash conversion cycle is one of the important measuring tools to calculate the efficiency of
working capital management. The time realm of the research was 2001-2006 and the studied
companies have been the ones accepted in Tehran stock exchange. In general, out of 2628
companies; the company has been selected as a top company for 1063. Then multiple regression
and Pearson’s correlation was used for the analysis and the results indicated that there is a
negative significant relation between number of days accounts receivable and profitability, a
negative significant relation between Inventory turnover in days and profitability, a direct
significant relation between number of day’s accounts payables and profitability and there is a
negative significant relation between cash conversion cycle and profitability. The results also
showed that in the studied companies, there is a significant relation between working capital
management and profitability and working capital management has a great effect on the
profitability of the companies and the managers can create value for shareholders by means of
decreasing receivable accounts and inventory.
50
Saghir, Hashmi & Hussain (2011) investigated the relationship between profitability and
working capital management. A sample of 60 textile companies listed at karachi stock exchange
(KSE) for the period of 2001- 2006 and the firms observations are 360. the purpose of this study
is to establish a relationship that is of statistical significant between profitability, the cash
conversion cycle and its components (number of days accounts receivables, number of days
accounts payables and number of days inventory). Using Pearson correlation and ANOVA, the
results of our research showed that there is statistically negative significance between
profitability, measured through return on asset, and the cash conversion cycle. Moreover
managers can create profits for their companies by handling correctly the cash conversion cycle
and keeping Number of days Accounts receivables, Number of days Accounts payables and
Number of days Inventory to an optimum level.
Mamoun (2011) examined the relationship between profitability and working capital
management measures for industrial companies listed on Amman Stock Exchange in Jordan
during the period 2001-2010. The final number of companies included in all analyses is (77)
companies and (552) company-year observations after deleting outliers defined as the top and
bottom 1% of the observations on each of the study variables. Using correlation and regression
analysis the results showed that indicated that profitability of business organizations is affected
negatively by the length of time required to sell their products, the length of time required to
collect their accounts receivable, and the length of time required to pay their accounts payable.
Zhman et al. (2011) examined the relationship between working capital management and
profitability by using data of fourteen companies in cement industry in the Khyber
Pakhtonkhuwa Province (KPK) of Pakistan. The study is based on secondary data collected from
financial reports which is listed in Karachi Stock Exchange for the period of six years from
2004-2009. The data was analyzed using the techniques of correlation coefficient and multiple
regression analysis. The result concludes that there is a moderate relationship between working
capital management and profitability in the specific context of cement industry in Pakistan.
Chary, Kasturi & Kumar (2011) studied relationship between working capital and profitability -
a statistical approach. The data used in the study is obtained from the published results of the
company during 2003-2008. The study has been conducted through simple statistical methods
51
such as correlation, regression and Chi-square test. PBT as a measure of profitability has been
compared with various measures of working capital to understand the association between the
variables. In analyzing working capital, the components of working capital, sources of working
capital, estimation of working capital, Net working capital, and the relationship of various
components of working capital with profitability played a vital role.
Ching, Novazzi & Gerab (2011) investigated the relationship between working capital
management and profitability in Brazilian listed companies. to identify the variables that most
affect profitability, the profitability was measured in three different ways: return on sales (ROS),
on asset (ROA) and on equity (ROE). The independent variables used are cash conversion
efficiency, debt ratio, days of working capital, days receivable and days inventory. Two samples
were obtained consisting of 16 Brazilian listed companies in each group for the period 2005-
2009. Multiple linear regressions has identified that, as far as ROS and ROA are concerned, to
manage working capital properly is equally relevant for the two groups of companies. However
the impact of debt ratio and days of working capital are relevant in the company profitability in
the fixed capital group as opposed to the working capital group. From ANOVA it is evident that
days inventory has negative relationship with ROS and ROA but has no statistical evidence in
ROE improvement in working capital intensive group. It has also identified days of working
capital as the variable that influences ROS in the second group (positive relationship) while debt
ratio was the only variable that affects ROA (negative relationship). These results showed that
regardless the type of company, whether working capital or fixed capital intensive, managing
working capital properly is equally important.
Ikram, el al. (2011) investigated The Relationship between Working Capital Management and
Profitability: A Case Study of Cement Industry in Pakistan. Using data of fourteen companies in
cement industry in the Khyber Pakhtonkhuwa Province (KPK) of Pakistan. The study is based on
secondary data collected from financial reports which is listed in Karachi Stock Exchange for the
period of six years from 2004-2009. The data was analyzed using the techniques of correlation
coefficient and multiple regression analysis. The result concludes that there is a moderate
relationship between working capital management and profitability in the specific context of
cement industry in Pakistan.
52
Adina (2010) analyzed the efficiency of working capital management of companies from Alba
County. The relation between the efficiency of the working capital management and profitability
is examined using Pearson correlation analyses and using a sample of 20 annual financial
statements of companies covering period 2004-2008. The result revealed that there is a weak
negative linear correlation between working capital management indicators and profitability
rates.
Karaduman et al. (2010) effects of working capital management on the profitability of selected
Companies in the Istanbul Stock Exchange for the period of 2005-2008. The panel data methods
are employed in order to analyze the mentioned effects. In the light of the results of the estimated
models for Turkey, working capital management unquestionably influences the companies listed
in the ISE. The findings are similar to the previous studies (Deloof, 2003; Lazaridis and
Tryfonidis, 2006; Garcia-Teruel and Martinez-Solano, 2007; et al., 2009). The companies should
focus on working capital management in order to increase their profitability by seriously and
professionally considering the issues on their cash conversion cycle which is derived from the
number of day’s accounts payable, the number of day’s accounts receivable, and the number of
days of inventories.
Guimarães (2010) the purpose of this study is to analyze the adequacy of a Working Capital
Management normative model, in terms of profitability, liquidity and solvency. Through an
Empirical and analytical research, the analysis of variance results (ANOVA) of a sample
Containing financial information from 621 healthcare insurance companies for the year 2006,
Show that different working capital structures are associated with different levels of Profitability,
liquidity and solvency, suggesting a preference order different from the one Theorized by
Fleuriet / Braga. The results indicate that a certain structure – where financial Current assets
exceed onerous current liabilities, and cyclical current assets exceed cyclical Current liabilities –
is associated with higher levels of profitability, liquidity and solvency. In Addition, the study
reiterates the importance of efficient management of working capital to the performance and
survival of healthcare insurance companies.
Mohammad & Saad (2010) working capital management and its effect to the performance of
Malaysian listed companies from the perspective of market valuation and profitability. The
secondary data for analysis is retrieved from Bloomberg’s Database of 172 listed companies
53
randomly selected from Bursa Malaysia main board for five year period from2003 to 2007. The
study aims to explore the effects of working capital component i.e. cash conversion cycles
(CCC), current ratio (CR), current asset to total asset ratio (CATAR), current liabilities to total
asset ratio (CLTAR), and debt to asset ratio (DTAR) to the firm’s performance by looking at
firm’s value i.e. Tobin Q (TQ) and profitability i.e. return on asset (ROA) and return on invested
capital (ROIC). Applying correlations and multiple regression analysis, the result showed that
there are significant negative associations between working capital variables with firm’s
performance.
Melita (2010) investigated the effect of working capital management on firm’s financial
performance in an emerging market. They hypothesized that working capital management leads
to improved profitability. Data set consists of firms listed in the Cyprus Stock Exchange for the
period 1998-2007. Using multivariate regression analysis, results supported their hypothesis.
Specifically, results indicate that the cash conversion cycle and all its major components;
namely, days in inventory, days sales outstanding and creditors payment period – are associated
with the firm’s profitability. The results of this study should be of great importance to managers
and major stakeholders, such as investors, creditors, and financial analysts, especially the recent
global financial crisis and the latest collapses of giant organizations world -wide.
Lamberg &Vålming (2009) studied was to examine if the change in liquidity strategies was
related to the profitability of the company, as measured by ROA. The population of interest
consisted of the companies listed on the Stockholm Stock Exchange’s Small and Mid cap lists,
the aim was to study the whole population, the aim also was to get at least 50 replies in order to
make a generalizations and to have statistically significant results. Using Descriptive statistics,
Pearson correlation and Multiple regression, the working capital ratio was found to be the most
important key ratio and the importance of DIO as the ratio which had increased the most.
Solvency ratios and certain ratios for external users such as the banks and lenders were also of
importance. No relationship between the key ratios and profitability was found but as it was
stated in theoretical part, WCM touches upon several parts of the organization and it can be
difficult to separate a direct impact on company’s performance but instead several parts of the
organization benefit from improved WCM.
54
Afza, & Nazir, (2008) investigated the relationship between the aggressive/conservative
working capital policies for seventeen industrial groups of public limited companies listed at
Karachi Stock Exchange for a period of 1998-2003. The ordinary least square regression model
was used to investigate into the relationship of working capital approaches and the returns of
firms. The study found significant different among their working capital investment and
financing policies across different industries. Moreover, these significant differences are
remarkably stable over the period of six years. The aggressive investment working capital
policies are accompanied by aggressive working capital financing policies. Finally, we found a
negative relationship between the profitability measures of firms and degree of aggressiveness of
working capital investment and financing policies.
Raheman & Nasr (2007) examined the impact of Working Capital Management and Profitability
– Case Of Pakistani firms listed on Karachi Stock Exchange for a period of 6 years from 1999 –
2004, using different variables of working capital management including the Average collection
period, Inventory turnover in days, Average payment period, Cash conversion cycle and Current
ratio on the Net operating profitability of Pakistani firms. Debt ratio, size of the firm (measured
in terms of natural logarithm of sales) and financial assets to total assets ratio have been used as
control variables. Pearson’s correlation, and regression analysis (Pooled least square and general
least square with cross section weight models) are used for analysis and The results showed
significant and negative relationships between profitability and all WCM and liquidity measures.
Furthermore, size showed a significant and positive relationship with profitability, leverage and
the ratio of financial assets to total assets showed significant and negative sign with profitability
Padachi (2006) examined the relationship between profitability and selected WCM measures
using 58 small manufacturing Mauritian companies over the period 1997-2003. They sub-
classified their sample companies into five sub-classifications for analysis purposes. The study
models were estimated using the regression based framework (Fixed and Pooled ordinary least
squares). The dependent variable used in all models was the return on assets. The independent
variables were the RCP, the ICP, the PDP, and the CCC. The models also included control
variables that may affect the profitability of the company, these control variables were; size,
gearing ratio, working capital turnover ratio, current assets to total assets ratio, and current
liabilities to total assets ratio. The results of all types of the regression models used showed that
the only significant, with the expected negative sign, WCM measure is the average RCP. Size
55
and the current assets to total assets ratio were the only significant control variables with positive
signs
Eljelly (2004) tested the relationship between profitability and liquidity measures for 27 Saudi
companies, from three non-financial sectors, over the period 1996-2000. The independent
variables used in the regression models as measures of liquidity were the current ratio and the
CCC. Size was included as a control variable. The dependent variable was measured using net
operating income before depreciation deflated by sales. The overall results showed that liquidity
measures are significant and have negative relationship with profitability, and the importance of
those measures differ across industries.
Deloof (2003) investigated the relationship between working capital management measures and
profitability for a sample of 1009 large Belgian non-financial companies over the period 1992-
1996. He used regression models with fixed effects1 and OLS regressions with dummy variable
for time and industries. The dependent variable was measured using gross profit deflated by
(total assets minus financial assets), the WCM measures used were the RCP, the ICP, the PDP,
and the CCC. Control variable were also included to the regression models measuring size,
financial leverage, sales growth, and financial assets to total assets ratio. The results for the
regression models estimated with fixed effects showed that profitability increases with the
decrease in the RCP, the ICP, PDP, and financial leverage. On the other hand, profitability
increases with the increase in company size, sales growth, and fixed financial assets ratio. The
CCC was not significant. The results of the OLS regressions were not significantly different
from those mentioned above. However, the CCC was significant and showed a negative sign.
56
2.4: SUMMARY REVIEW
Working capital is a financial metric which represents the operating liquidity available to a
business (Huynh, 2012). Along with fixed assets such as plants and equipment, working capital
is considered as a part of a company’s capital, referring to assets such as cash at hand, cash on
bank account, raw materials, work in progress, finished goods, account receivable and etc. The
major concepts of working capital are the gross working capital and the net working capital.
Gross working capital is the totality of firms’ investment in current assets such as inventory,
accounts receivable, short term marketable securities and cash. Net working capital is the totality
of firms’ investment in current assets less the totality of the firm’s current liabilities. Current
liabilities includes items such as accounts payable, notes payable, accruals, customers deposit
(i.e. prepayment) deferred taxes and short- term deposit obligation.
Working capital management is a very important component of corporate finance because it
directly affects the liquidity and profitability of the company. It deals with current assets and
current liabilities. Moreover, it involves planning and controlling of current assets and current
liabilities in a manner that eliminates the risk of inability to meet due short-term obligations on
one hand and avoid excessive investment in these assets on the other hand (Eijelly, 2004). There
are combination of policies and techniques for the management of a company’s working capital.
These policies involve the two working capital policies; aggressive and conservative policies and
inventory, debtors’ and short-term financing management techniques respectively. A popular
measure for evaluating working capital management is cash conversion cycle (account collection
period plus inventory conversion period minus account payment period), which tells us how cash
is moving through a company in terms of duration. Many researchers have studied working capital
management and profitability from different views and in different environments. But to the best of the
knowledge of the researcher, none has been carried out in Chemical and Paints sector within the research
geographical location. The aim of the study was to empirically examine the impact of working capital
management on profitability of selected firms in the Chemical and Paints sector listed on Nigeria Stock
Exchange (NSE).
2.4.1: MAJOR TREND (CONSENSUS ON ARGUMENT)
Researchers have examined working capital management issues, specifically on how companies
manage its working capital by shortening or lengthening its cash conversion cycle in order to
57
contribute for a superior operating profitability. Though the results on the kind of relationship
that exist between working capital management indicators and profitability are quite mixed
among researchers, but major studies concluded strong negative relationship between working
capital management (WCM) and profitability while others argue that there is a positive
relationship between them. However, the growing consensus of opinion on this issue argued that
WCM has a strong negative impact on of firm’s Profitability, in order words, if the length of the
cycle (CCC) decreased or shortened, firm’s profitability will increase. It is so according to
following authors; Jayarathne, 2014; Almmazari, 2014; Gulia, 2014; Igbal, Ahnad & Raiz, 2014;
Jafari , Salahinezhad & Jalili, 2014; Rehman, 2013; Alavinasab & Davoudi, 2013; Gomes,2013;
Nziko et al, 2013; Leon, 2013; Tufail, 2013;; Adarqual, 2013; Egbide, Olubukunola &
Uwuigbe,2013; Bose,2013; Nejadi, Bandarian,& Ghatebi, 2013; Ray, 2012; and many others.
2.4.2: CRITIC OF LITERATURE
The bad quality of this literature is that, the decrease in the length of CCC is said to bring about
an increase in profitability, while an increases in the length of CCC lead to increase in sales
volume which will results to an increase in profitability and liquidity if the amount incurred from
lengthening CCC is properly collected. Reason because the rate of sales determines the amount
of firm’s profitability. Firm can increase their sales through sales promotion, allowing credit
sales and providing sales discount to their customers. In order words, reducing the period
Between the expenditure for the purchase of raw materials and collection of sales from finished
goods could harm the firm’s profitability.
2.4.3: RESEARCHER’S PERSONAL CONTRIBUTION
Among the four indicators of WCM (ACP, ICP, APP & CCC), Account Collection management
(ACP) is the key stimulator of the other variables as it plays a key role in the maximizing firms
value. The way an organization manages it ACP has direct significant impact on its profitability
and liquidity. Because the higher the ACP the higher the sales volume (Which leads to increase
in profitability), and cash flow/liquidity can be significantly enhance if the amounts owing to the
customers are properly collected faster. Then the cash collected can be used to pay up their trade
creditors, taking advantage of discounts from early payment there by shortening the length of
58
APP. Again, when the rate of sales is high, it will consequently leads to an increase in the rate of
out -going inventories, in order words, shortening the length of ICP. However, if the amount in
ACP is not properly collected, it will have an adverse effect on both liquidity and profitability of
the firm. So converging the three above effects into one place, we can explain to an increase in
firm profitability due to the long CCC (ACP plus (ICP) minus (APP) = positive CCC). In
contrast, shortening the CCC could harm the firm profitability. The firm could incurred cost from
lengthening the days of ICP, as a result of unnecessary accumulation of inventories which in
turn increases the dangers of obsolescence pilferage, mishandling, high insurance and carrying
cost, idle assets, which are barren to accounts receivable, poor profitability, lose good credit
customers as reducing ACP, and hamper its credit reputation as lengthening the APP, as waiting
of the APP for a short period is advantageous for the sector to minimize the cost of purchasing
goods from suppliers. In those cases, CCC is said to have a positive relationship with firm
profitability. Therefore, the theory is that with positive impact of ACP + (negative impact of
ICP) – (negative impact of APP) = positive impact of CCC increase in sales volume
Increase in firm’s Profitability.
59
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CHAPTER THREE
RESEARCH METHODOLOGY
3.1: RESEARCH DESIGN
This research will employ ex-post facto design. This suits our purpose and is appropriate for this
study because the data already exist and will be extracted from the company’s financial
statement. Again, cost is effective when these methods are adopted and employed.
3.2: NATURE AND SOURCE OF DATA
The data required for the Purpose of the study will be obtained from secondary source. For
secondary data being already processed and collated, data are easily found in publications of
organization. So the research data collection is based on library method and required information
is developed from the site of stock exchange market while the source is from published materials
(Annual Reports) of the relevant companies. Secondary data will take the following forms-
Working capital components comprising some items on current assets and liabilities, which are;
Cash, Accounts Receivable, Inventory, and Accounts Payable and will be collected from balance
sheet of Chemical and Paint firms listed in Nigeria Stock Exchange (NSE).
Gross Operating Profit: comprises profit before tax of the relevant companies. The figures will
be collected from the end of the year income statement of the relevant companies.
3.3: POPULATION AND SAMPLE SIZE
Secondary data were obtained from annual reports of 5 Chemical and Paint firms listed in NSE
during the fourteen year period (2000 to 2013).viz: African Paint Plc, Berger Paints Plc, CAP
Plc, DN Meyer Plc, and premier Paint plc. These 5 firms have been chosen out of 7 listed
chemical and paint firms in NSE using purposive sampling technique where firms basically into
the production of chemical and paint and with availability of annual reports in Nigeria stock
exchange from 1999-2013 were considered. This will cover 71% of the population for the period
of fourteen years (2000-2013).
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3.4: EXPLAINATION OF THE VARIABLES
This study will undertakes the issue identifying key variables that influence working capital
management of listed chemical and paint firms in Nigeria. Choice of the variables will be
influenced by the previous studies on working capital management, but it will basically be
consistent with (Mohammad Alipour, 2011) and Nzioki, et al. (2013).
In writing the models of our relationship, the following alphabets will be used to denote their
respective variables:
DEPENDENT VARIABLE;
GOP is gross operating profit and is the dependent variable in the study. This ratio has been
used by several authors in the financial literature including (Deloof, 2003; Amarjit, Nahum and
Neil, 2010; Mamoun, 2011; Vural, Sokmen and Cetenak, 2012). To obtain dependent variable
(gross operating profit), we subtract cost of goods sold from total sales and divide the results
with total assets minus financial assets. The reason for using this variable instead of earnings
before interest tax depreciation amortization (EBITDA) or profit before or after tax is that we
want to associate operating “success” or “failure” with an operating ratio and relate this variable
with other operating variables (e.g., cash conversion cycle). Furthermore, we want to exclude the
participation of any financial activity from operating activity that might affect overall
profitability. Therefore, we subtracted financial assets from total assets (Amarjit, Nahum and
Neil, 2010).
GOP = sale –cost of goods sold
Total asset – financial asset
INDEPENDENT VARIABLES;
Accounts Collection Period (ACP): is the Average required time for changing the company’s
receivables into cash (Alipour, 2011).it is calculated in this way:
ACP = average receivable * 365
Annual sales
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Inventory Conversion Period (ICP): is the average required time it takes to change the
materials into the product and then sell the goods (Alipour, 2011). It is calculated in this way:
ICP = average inventory * 365
Annual cost of goods sold
Average Payment Period (APP): is the average time between buying materials and using
labour force and cash payment relates to them from receipt of production related materials and
payment for those materials. Average payment period is calculated in this way:
APP = average payment * 365
Annual cost of goods sold
Cash Conversion Cycle (CCC): is the time lag between purchase of raw materials or render of
services and the collection of cash from the sale of goods or services rendered (Vural, Sokmen &
Cetenak, 2012). Cash conversion cycle is calculated in this way:
CCC = (Inventory Conversion Payment Period + Average Collection Period - Average
Payment Period)
CONTROL VARIABLES;
Liquidity (CR): The companies with more liquidity have more profitability, so liquidity variable
will be use as control variable in order to make its effect on profitability neuter. Current ratio has
been used as Liquidity criterion (Nzioki, et al, 2013).
CR = Current assets
Current liabilities
Financial Assets (FATA): some amount out of the total assets in chemical and paint firms are
financial assets and since they are brought for profitability purposes, so these assets affect
profitability. Therefore this variable will be use as control variable in order to make its effect
neutral on the company profitability. Long and short term investment in stock and bills of
exchange of the other companies or investment in its subsidiary and also cash, bank deposit,
certificates and bonds are considered as financial assets (Nzioki, et al, 2013).
70
FATA = Financial assets
Total assets
The Company Size (lnS): The companies which have more sales naturally have more
profitability too. So the company size variable will be use to control the effect of this issue
(Nzioki, et al, 2013).
Company size is natural logarithm (sale).
Debt Ratio (DR): will be used as proxy for leverage and is calculated by dividing Total Debt by
Total Assets (Nzioki, et al, 2013).
DR = Total debts
Total assets
3.5: SPECIFICATION OF MODELS
The general form of the study will be specified as:
GOPit = β0 + βi X it +ε
Where:
GOPit = : Gross Operating Profit of firm i at time t
β0 = : The intercept of equation
βi = :Coefficient of X it variable
X it = : The different independent variable for working capital management of firm i
at time t
i = : Paint and chemical firms = 1,2, 3, 4, 5 firms
t = : Time = 1, 2, 3, 4, 5, 6. 7, 8, 9, 10 years
ε = : The error term
The following four models will be used to analyze the relationship between the variables:
71
General: GOP = f (ACP, ICP, APP, CCC, CR, SIZE, LEV, FATA)
First model: The relation between Average Collection Period and Profitability:
Model 1 : GOPit = β0 + β1ACPit + β2 CRit + β3SIZEit + β4LEV it +β5FATA it + εit
Second model: The relation between Inventory Conversion Period and Profitability:
Model 2 : GOPit = β0 + β1ICPit + β2 CRit + β3SIZEit + β4LEV it +β5FATA it + εit
Third model: The relation between Average Payment Period and Profitability:
Model 3 : GOPit = β0 + β1APPit + β2 CRit + β3SIZEit + β4LEV it +β5FATA it + εit
Fourth models: The relation between Cash Conversion Cycle and Profitability:
Model 4 : GOPit = β0 + β1CCCit + β2 CRit + β3SIZEit + β4LEV it +β5FATA it + εit
TABLE 3.6: A PRIORI EXPECTATION FOR THE INDEPENDENT VARIABLES
Independent Variable Expected Signs
ACP Time required to collect cash Average Debtors X365 Net Credit Sales Upward trend Positive
ICP Time required to convert Average Stock Value X 365 Cost of sales Downward Trend Negative
APP Time required to pay cash To creditors Average Creditors X 365
Cost of Sales Downward Trend Negative
CCC The time lag between the
purchase of inv and the
receipt of cash from doctors CCC= ACP+ICP-APP Upward Trend Positive
CR Liquidity ratio Current assets
Current liabilities Upward Trend: Ideally 2:1 Positive
FATA Ratio of financial assets Financial assets
Total assets upward Trend Positive
DR Leverage ratio Total debts
Total assets Moderate Negative/Positive
COYSIZE Size of revenue Natural logarithm (sale) Upward Trend Positive
Gross operating profit
(Measurement of firm ‘s
Performance) Sale-cost of goods sold Moderate Negative/Positive Total assets-financial asset
From debtors
Inventory to cash
GOP
Expected Behavior
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3.7: TECHNIQUES OF ANALYSIS
To test the four hypotheses, three stages analysis will be conducted; first the data will be
analyzed using financial analysis, secondly a descriptive analysis of the selected variables will be
conducted and lastly statistical analysis will be carried out by using regression techniques to
determine the impact of relation between the dependent variable and independent variables
(ACP, ICP, APP, CCC etc).
73
REFERENCES
Alipour, M. (2011) “Working Capital Management and Corporate Profitability: Evidence from Iran,” World Applied Science Journal, Vol.12, No. 7, pp. 1093-1099
Beenink H.J. (2010) “Effect of Working Capital Management on Profitability for a Sample of European Firms,” Erasmus University Rotterdam, Faculty of Economics of Business Department of Economics.
Danuletin, A. E. (2010) “Working Capital Management and Profitability: A Case of Alba County Companies” Annales University Apulensis Series Oeconomica, Vol. 12, No. 1, pp.364-374
Deloof, M. (2003) “Does Working Capital Management affect Profitability of Bekgian Firms? Journal of Business Finance and Accounting,Vol. 30, No. (3-4), 573-588
Ebenezer, A. B. and Asiedu, M. K. (2013) “The Relationship between Working Capital Management and Profitability of listed Manufacturing Companies In Ghana,” International Journal of Business and Social Research, Vol.3, No. 2, pp. 25-34
Garcia, J. F. L. (2011) “The Impact of Working Capital Management upon Companies Profitability: Evidence from European Companies,” Research Work in Progress/ Feb Working Papers, 438, pp.1-35
Amarjit, G., Nahum, B. and Neil, M. (2010) “The Relationship between Working Capital Management And Profitability: Evidence From The United States,” Business and Economics Journal, 10, pp 1-9
Jayarathne, T.A.N.R. (2013) “Impact of Working Capital Management on Profotability: Evidence from Sri Lanka,” Proceeding of the 3rd International Conference on Management and Economics, Oral Presentation. Pp.269-274
Makoni, D. M. and Jagongo, A. (2013) Working Capital Management and Firm Profitability: Empirical Evidence from Manufacturing and Construction Firms in Kenya,” International Journal of Accounting and Taxation, Vol.1 No.1 pp.1-14
Mamoun, M. A. (2011) “Working Capital Management and Profitability: the Case of Industrial Firms in Jordan,” European Journal of Economic, Finance and Administrative Sciences, Vol.36, 75-86
Muhammad, M., Jan W.U. & Ullah, k. (2011) “Working Capital Management and Profitability: An Analysis of Firms of Textile Industry of Pakistan,” Jouirnalof Management Sciences, Vol.4, No.2.pp.155-167
Nzioki, P.M.,Kimeli, S.K. & Abudho, M. R. ( 2013) “Management of Working Capital and Its effect on Profitability of Manufacturing Companies Listed on Nairobi Securities Exchange
74
Kenya,” International Journal of Business and Finance Management Research, Vol.1.pp.35-42
Owolabi, S. and Obida, S. (2012), “Liquidity Management and Corporate Profitability: A Study of Selected Manufacturing Companies,” Business Management Dynamics, Vol.2, No. 2, pp. 10-25
Pauraghajan, A., Rekabdarkolaei, E. A. and Shafie, M. (2013) “Investigation the Effects of Working Capital Management and Capital Structure on Profitability and Return on Assets: A selection from the Automotive Companies in Iran,” Journal Basic Applied Science Research, Vol.3, No.4, pp. 847-854
Ramana, N. U., Ramakrishnaiah, K. and Chengakrayulu, P. (2013) “ Impact of Receivables Management on Working Capital and Profitability: A study on Selected Cement Companies in India,” International Journal of Marketing, Financial Service and Management Research, Vol.2 No.3, pp.163-171
Tufail, S. (2013) “Impact of Working Capital Management on Profitability,” 3rd International Conference on Business Management, pp. 1-29
Vallalnathan, N. Joriye, G. ( 2012) “ Impact of Working Capital Management on the Profitability of cooperative Unions in East Showa, Ethiopia,” Greener journal of Business and Management Studies, Vol.3, No.6, pp.251-269
Vural, G., Sokmen, A. G. and Cetenak, E. H. (2012) “Effects OF Working Capital Management
ON firm’s Performance: Evidence from Turkey,” International Journal of Economics and
Financial Issues, Vol.2, No.4 pp. 488-495
Blinder, A. S. & Maccini, L. J. (1991) “The Resurgence of Inventory Research: What Have We
Learned?,” Journal of Economic Survey, Volume 5, pp. 291-328.
Weinraub, H.J. and Visscher, S. (1998) “ Industry Practice Relating To Aggressive Conservative
Working Capital Policies,” Journal of Financial and Strategic Decision, Vol.11, No.2,
pp.11-18.
Smith, K. (1980) “ Profitability versus Liquidity Tradeoffs in Working Capital Management, in
Readings on the Management of Working Capital,” New York: St. Paul, West Publishing
Company, pp. 549-562.
75
CHAPTER FOUR
4.1 DATA PRESENTATION AND ANALYSIS
In this chapter of the study, the panel data, which was prepared from the financial statement of
the sampled companies, are presented in table and analyzed through E-View 7.1. The results
from the Descriptive and Regression analysis are represented in table and discussed.
Moreover, the impact of WCM on profitability was analyzed with panel data multiple regression
analysis. The panel multiple regression requires the use of either of REM or FEM for estimating
the parameters of the empirical data. As it was observed in the beginning of this study, the choice
of the two models depends on Hausman specification tests. Hausman test examines whether the
unique errors (ni) are correlated with regressors (independent variables). The null hypothesis for
this test they are not correlated to each other E (ni / Xit) = 0. If the test rejects this null hypothesis
then the decision is taken to employ a FEM. Then, if the effects are considered to be fixed, the
model is then estimated by OLS. If the null hypothesis is not rejected, we would have random
effects, and the model is then estimated by GLS. By running the Hausman specification test, the
p-value obtained from it is 0.0000 < 0.05, rejecting the null hypothesis and accordingly
indicating that there is significant correlation between ni and regressors. Accordingly the FEM
shall be employed. Again, strong negative correlation was observed between SIZE and FATA,
and between APP and CCC, but to prevent the collinearity between FATA and SIZE, SIZE was
dropped and to avoid the effects of multi-collinearity between APP and CCC, stepwise
remodeling was done by separately entering the variables in different models.
For this, all the regression models FEM are done separately with multiple regression analysis
using single predictor of operating profit and the control variables. This choice of determining
separate influence is of consistent with most of researchers found in my literature review (Nzioki
et al., 2013; Amarjit, Nahum and Neil, 2010; (Makori & Jagongo, 2013: Deloof, 2003; Huynh,
2011; Sarbapriya, 2012; Quayyum, 2011; Alipour, 2011; Padachi, 2006).
76
4.2 THE OVERALL ANALYSIS OF DESCRIPTIVE STATISTICS
This section dealt with the results of descriptive statistics for the sampled Chemical and Paint
Companies. It shows the mean, standard deviation, minimum and maximum values of the
variables employed in the study and it also gives a clear picture about these values, which help in
understanding the different dimensions of variables. The descriptive statistics are calculated and
presented in Table 4.2.
Table 4.2 Descriptive Statistics of Independent, Dependent, and Control Variables
2000-2013).
Descriptive Statistics (N=70)
N=Number of observations
The mean value of gross operating profitability is 55% of total assets and standard deviation is
42%.It means that the value of the profitability can deviate from mean to both minimum and
maximum side by 42%. The minimum and maximum values of the profitability are 5.3% and
191% respectively. Since the standard deviation is small than the mean, it indicates that the
Chemical and Paint sector is quite enough effective in maintaining its profitability. The cash
conversion cycle, which is used as a proxy of the working capital management, is on an average
of 27 days. This value indicated the length of time, which the companies wait on average to
cash conversion and it goes with a standard deviation of 161days. Since the value of standard
deviation is much larger than its mean, it indicates that the Chemical and Paint companies CCC
deviate too much. The maximum CCC for the companies is 202 days while minimum CCC is
(653) and indicated the good management of CCC because the negative sign indicated that
Variable Minimum Maximum Mean Std.Div
GOP 0.053000 1.910000 0.554986 0.418870
ACP 10.18000 2210000 48.13500 30.68918
ICP 32.8000 263.4000 102.3557 49.91251
APP 11.37000 1094.510 129.4074 195.3746
CCC -653.1200 202.7000 27.49243 161.9991
CR 0.030000 2.350000 1.044429 0.679601
FATA 0.000300 0.690000 0.233510 0.261907
COY.SIZE 13.67000 29.180000 17.62629 2.993367
DR 0.310000 1.380000 0.657429 0.213831
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number of days for APP is greater than the number of days that the companies wait for ACP and
ICP.
Companies receive payments against sales after an average of 48 days with a standard deviation
30 days. The minimum time taken by a company to collect cash from the receivable is 10 days,
while the maximum time take is 212 days. The table also shows that the companies take an
average of 102 days to sell their inventory (ICP) with a standard deviation of 49 days. The
minimum and maximum time taken by a firm in this regard is 32 days and 263 days respectively.
In order to make the payment to their purchases (APP) the companies wait on an average of 129
days with a standard deviation of 195 days. Here the minimum time taken by a company to pay
its purchases is 11 days while maximum time taken is 1094 days. The maximum APP is 1094
days is a very much long period. The average current ratio of the firms is 1.04. The standard
deviation is 0.68 while the minimum and maximum current ratio for a company in a year is 0.03
and 2.35 respectively. This shows that the Chemical and Paint companies’ current assets exceed
their current liabilities. To check the size of the firms and its relationship with profitability,
natural logarithm of sales is used as a proxy. The mean value of log of sales is 17.62629 and it
implies that sector made sales on average this much, the standard deviation is 2.993367. The
maximum value of log of sales for the sector within a year is 29.18000 and minimum is
13.67000. The debt ratio is used to check the relation of debt financing with the profitability and
the firm average debt ratio is 66% with standard deviation of 21%. The maximum debt financing
used by the companies is 138% while the minimum is 31%. The financial assets to total assets
ratio is also used as one of the control variable. The mean value for this ratio is 23% and the
standard deviation of 26%. The maximum portion of assets in the form of financial a particular
company is 69% and the minimum is 0.03%.
4.3 TEST OF HYPOTHESIS
4.3.1 Test of Hypothesis one
Step One: Restatement of Hypothesis
H0: Average Collection Period (ACP) has no positive and significant impact on the Profitability
of the firms in Nigeria Chemical and Paint Industries.
H1: Average Collection Period (ACP) has a positive and significant impact on the profitability of
the firms in Nigeria Chemical and Paint Industries.
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Step two: Decision criterion
1. Reject H0 if the sign of the coefficient estimate of the relevant independent variable is
positive and the t-value is positive and greater than two and the P-value of the coefficient
estimate is less than 0.05.
2. Accept H0 if the sign of the relevant coefficient estimate is not positive and the sign of
the t-value is not positive and less than two, and the P-value of the coefficient estimate is
greater 0.05.
Step Three: Analysis of E-view Results
Table 4.3 Ordinary least square result of hypothesis one
Dependent Variable: GOP
Sample: 2000 2013
Included observation: 70
Variable
Coefficient Std. Error t-Statistic Prob.
C 0.167448 0.275319 0.608194 0.5459 ACP 0.002326 0.001122 2.073238 0.0435 CR 0.082233 0.124603 0.659958 0.5124 FATA 0.883926 0.327470 2.699261 0.0096 DR -0.025393 0.241700 -0.105062 0.9168 R-squared 0.757648 Mean dependent var 0.554986 Adjusted R-squared 0.651619 S.D. dependent var 0.418870 S.E. of regression 0.247233 Akaike info criterion 0.294306 Sum squared resid 2.933958 Schwarz criterion 1.000975 Log likelihood 11.69931 Hannan-Quinn criter. 0.575003 F-statistic 7.145663 Durbin-Watson stat 1.943636 Prob(F-statistic) 0.000000
Model Equation GOP = 0.167+ 0.002ACP + 0.08CR +0.88FATA - 0.03DR + 0.001
As observed in 4.3 above, the result indicates that Average Collection Period (ACP) has a
positive and significant impact on profitability of selected chemical and paint sector in Nigeria
Source: The Researcher’s E-view Result
79
listed in NSE (coefficient of account collection period = 0.002, t-value = 2.07. thus a one
percent( 1%) increase in account collection period result in 0.002326 increase in total gross
operating profit. The coefficient of determination (R2) is 76%, implying that 76% variation in the
dependent variable (GOP) is explained by the change in the independent variable (ACP), while
the unexplained part of 24% is the effect of the other variables impacting on profitability that is
not included in the regression. The variation was properly adjusted by the adjusted R2 of (65%).
The coefficient of one other variable included in the model is also positive and significant. Gross
operating profit increases with financial assets (FATA).
Step Four: Decision
From the analysis above, the null hypothesis is rejected while the alternative hypothesis
accepted, implying that account collection period has a positive and significant impact on the
profitability of selected chemical and paint sector of Nigeria (NSE).
4.3.2 Test of Hypothesis two
Step one: Restatement of Hypothesis
H0: Inventory Conversion Period has no positive significant impact on profitability of the firms
in Nigeria Chemical and Paint Industries.
H1: Inventory Conversion Period has a positive significant impact on profitability of the firm in
Nigeria Chemical and Paint Industries.
Step Two Decision Criterion
1. Reject H0 if the sign of the coefficient estimate of the relevant independent variable is
positive and the t-value is positive and greater than two and the P-value of the coefficient
estimate is less than 0.05.
2. Accept H0 if the sign of the relevant coefficient estimate is not positive and the sign of
the t-value is not positive and less than two, and the P-value of the coefficient estimate is
greater 0.05.
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Step Three: Analysis of E-view Results Table
4.4 Table Ordinary least square result of hypothesis two
Dependent Variable: GOP
Sample: 2000 2013
Included observation: 70
Variable Coefficient Std. Error t-Statistic Prob. C 0.327635 0.304150 1.077213 0.2868 ICP -0.000817 0.000961 -0.849523 0.3998 CR 0.091511 0.129032 0.709213 0.4816 FATA 0.788457 0.342453 2.302377 0.0257 DR 0.047512 0.248488 0.191206 0.8492 R-squared 0.739857 Mean dependent var 0.554986 Adjusted R-squared 0.626044 S.D. dependent var 0.418870 S.E. of regression 0.256147 Akaike info criterion 0.365145 Sum squared resid 3.149338 Schwarz criterion 1.071815 Log likelihood 9.219912 Hannan-Quinn criter. 0.645843 F-statistic 6.500661 Durbin-Watson stat 1.682697 Prob(F-statistic) 0.000000 Source: The Researcher’s E-view Result
Model Equation GOP = 0.33 -0.0008ICP + 0.09CR + 0.79FATA + 0.05DR + 0.001
As observed in table 4.4 above, the result indicates that inventory conversion period (ICP) has
negative and non-significant impact on profitability of the firms. (Coefficient of inventory
conversion period = (0.0008), t-value = (0.85). ICP is not statically significant at 5% significance
level (p˃ 0.05).This suggest that, though short ICP is good for explaining the financial success of
listed chemical and paint firms in Nigeria, it is not a critical factor to consider when taking
decision to improve profitability. However the overall model is highly statistically significant, as
it is indicated by the F-value of 6.501 (p-value = 0.0000). The coefficient of determination (R2)
is 74%, implying that 74% variation in the dependent variable (GOP) is explained by the change
in the independent variable (ACP). The model is properly adjusted by the adjusted R2 (63%).
81
The coefficient of one other variable included in the model is also positive and significant. Gross
operating profit increases with financial assets (FATA).
Step Four: Decision
From the analysis above, the null hypothesis is accepted, implying that inventory conversion
period does not have a positive and significant impact on profitability of the profitability of
selected chemical and paint firms in NSE.
4.3.3 Test of Hypothesis Three
Step One: Restatement of Hypothesis
H0: Account Payment Period has no positive significant impact on profitability of the firms in
Nigeria Chemical and Paint Industries.
H1: Account Payment Period has a positive significant impact on profitability of the firms in
Nigeria Chemical and Paint Industries.
Step Two: Decision Criterion
1. Reject H0 if the sign of the coefficient estimate of the relevant independent variable is
positive and the t-value is positive and greater than two and the P-value of the coefficient
estimate is less than 0.05.
2. Accept H0 if the sign of the relevant coefficient estimate is not positive and the sign of
the t-value is not positive and less than two, and the P-value of the coefficient estimate is
greater 0.05.
Step three: Analysis of E-view Results
Table 4.5 Ordinary Least Square Results of Hypothesis Three
Dependent Variable: GOP
Sample: 2000 2013
82
Included observation: 70
Variable Coefficient Std. Error t-Statistic Prob. C 0.244190 0.289740 0.842790 0.4035 APP -5.54E-05 0.000266 -0.208712 0.8356 CR 0.095171 0.129957 0.732330 0.4675 FATA 0.828960 0.341389 2.428197 0.0190 DR 0.038024 0.250149 0.152006 0.8798 R-squared 0.736185 Mean dependent var 0.554986 Adjusted R-squared 0.620766 S.D. dependent var 0.418870 S.E. of regression 0.257948 Akaike info criterion 0.379162 Sum squared resid 3.193790 Schwarz criterion 1.085831 Log likelihood 8.729345 Hannan-Quinn criter. 0.659859 F-statistic 6.378369 Durbin-Watson stat 1.690314 Prob(F-statistic) 0.000000 Source: The Researcher’s E-view Result
GOP = 0.244 - 5.54E-05APP + 0.095CR + 0.829FATA + 0.0380DR + 0.0003
From the Table 4.5, the regression indicates that the coefficient of APP is negative with -5.54E-
05, but it is not significantly different from zero (p-value = 0.836) and the (t-value = (0.209).
This also suggests that APP is not statistically significant at 5% significance level (p˃0.05). This
also suggest that, though short APP is good for explaining the financial success of listed
chemical and paint firms in Nigeria, it is not a critical factor to consider when taking decision to
improve profitability. However the overall model is highly statistically significant, as it is
indicated by the F-value of 6.38 (p-value = 0.0000). The coefficient of determination (R2) is
74%, implying that 74% variation in the dependent variable (GOP) is explained by the change in
the independent variable (ACP). The model is properly adjusted by the adjusted R2 (62%). The
coefficient of one other variable included in the model is also positive and significant. Gross
operating profit increases with financial assets (FATA).
Step Four: Decision
From the analysis above, the null hypothesis is accepted, implying that account payment period
does not have a positive and significant impact on profitability of the selected chemical and paint
firms in NSE.
83
4.3.4 Test of Hypothesis Four
Step One: Restatement of Hypothesis
H0: Cash Conversion Period has no positive significant impact on profitability of the firms in
Nigeria Chemical and Paint Industries.
H1: Cash Conversion Period has a positive and significant impact on profitability of the firms in
Nigeria Chemical and Paint Industries.
Step Two: Decision Criterion
1. Reject H0 if the sign of the coefficient estimate of the relevant independent variable is
positive and the t-value is positive and greater than two and the P-value of the coefficient
estimate is less than 0.05.
2. Accept H0 if the sign of the relevant coefficient estimate is not positive and the sign of
the t-value is not positive and less than two, and the P-value of the coefficient estimate is
greater 0.05.
Step Three: Analysis of E-view Results Table 4.6 Ordinary Least square Results of Hypothesis Three Dependent Variable: GOP Sample: 2000 2013 Included observation: 70
Source: The Researcher’s E-view Result
Variable Coefficient Std. Error t-Statistic Prob. C 0.257112 0.287167 0.895338 0.3751 CCC 0.000192 0.000325 0.590781 0.5574 CR 0.088806 0.130045 0.682887 0.4980 FATA 0.827569 0.339783 2.435580 0.0186 DR 0.010024 0.254196 0.039433 0.9687 R-squared 0.737852 Mean dependent var 0.554986 Adjusted R-squared 0.623162 S.D. dependent var 0.418870 S.E. of regression 0.257132 Akaike info criterion 0.372824 Sum squared resid 3.173612 Schwarz criterion 1.079494 Log likelihood 8.951171 Hannan-Quinn criter. 0.653522 F-statistic 6.433455 Durbin-Watson stat 1.696797 Prob(F-statistic) 0.000000
84
GOP = 0.257 + 0.0002CCC + 0.089CR + 0.082FATA +0.010DR + 0.0003
As observed in table 4.6 above, the result indicates that cash conversion period has positive and
non significant impact on profitability of the firms. The regression indicates that the coefficient
of CCC is positive with 0.0002, but it is not significantly different from zero (p-value = 0.557)
while the (t-value = 0.591). This suggests that, though longer CCC is good for explaining the
financial success of listed chemical and paint firms in Nigeria, it is not a critical factor to
consider when taking decision to improve profitability. However, the overall model is highly
significant, as it indicated by the F- value of 6.43 (p-value = 0.0000). The coefficient of
determination (R2) is 74%, implying that 74% variation in the dependent variable (GOP) is
explained by the change in the independent variable (CCC), The model is properly adjusted by
adjusted R2 (62%).The coefficient of one other variable included in the model is also significant.
Gross operating profit increases with financial assets (FATA).
Step Four: Decision
From the analysis above, the null hypothesis is accepted, while the alternative hypothesis is
rejected, implying that cash conversion period has a positive and non-significant impact on
profitability of the selected chemical and paint firms in NSE.
4.4: IMPLICATION OF THE RESULTS
To determine the individual and joint impact of the level of the average collection period,
inventory collection period and accounts payment period on the dual objectives of working
capital management, the manager applies a number of working capital policies, viz aggressive
and conservative policy.
The results show that for the sampled chemical and paint firms, only average collection period
out of working capital management variables has a significant impact on profitability of the firms
and play a key role in value creation for shareholder as shorter average collection period leads to
decrease in profitability. The positive effect of the average collection period on gross operating
profit is because of the generous trade credit offer by the firms to the customers for increasing
sales volume ( which leads to an increments in profitability), and cash flow/liquidity can be
significantly enhance if the amounts owing to the customers are collected faster. As a result firms
85
are able to generate high profit on one hand, and if firms sell only on credit basis and hence
increase account receivable but not collected properly then it is negative sign for the liquidity of
the firm, on the other hand. So the firm must keep optimal level of average collection period and
formulate a strong credit policy. In order words, the positive impact of average collection period
on gross operating profit helps the management in setting credit policy for the sector in general
for the firms in chemical and paint sector in Nigeria.
The negative and non significant impact between inventory period and gross operating profit
shows that as inventory period decreases the profitability of the firms’ increases but the impact is
statically insignificant. This implies that, either longer or shorter, it takes the companies to sell
their inventories, has no influence on profitability.
Again, the result accounts payment period has a negative impact on profitability though non-
significant, has economic implications. It means that when the management implements policy
by applying either aggressive or conservative financing policy, the profitability of the firm will
also experience the effect of the policy applied especially on its liquidity level, thereby ensuring
that the effects of working capital policy are transmitted to the rest of the firm’s performance.
However, the negative and non significant impact of APP on gross operating profit suggests that
though shorter account payable period are good for explaining the financial success of the listed
chemical and paint firms in Nigeria, but it is not a critical factor to consider when taking decision
to improve profitability. Indeed the most plausible explanation for the negative relationship
between accounts payable and profitability is that less profitable firms wait longer to pay their
bills. It reflects that if accounts payable will boost then as a result profitability will drop off
rather than increase, because late payments of invoice can be very costly if the firm is offered a
discount for early payment.
The results also show that cash conversion cycle has a positive though non-significant impact on profitability; this clearly implies that a longer period between the expenditure for the purchase of raw materials and the collection of sales from finished goods has a good influence on profitability of the firms but has no statically significant impact on profitability. That is, it clearly indicates that the period between the expenditure for the purchase of raw materials and the collection of sales from finished goods has no impact on the profitability of the sampled chemical and paint firms in Nigeria. It is not an important factor to consider while taking cooperate decision.
Theoretically, Cash conversion cycle can also have positive influence on company profitability and it could be interpreted through a chain of positive impact of inventory periods and account
86
receivable period with a negative impact of accounts payable period on the company profitability. But in this study, according to the nature of the firms, the inventory conversion period shows negative relationship with non significant impact on the firm’s profitability, this means that the shorter the length of time it takes the sector to produce and sell its goods the higher the profitability. While the average collection period shows positive significant impact on profitability which implies that the longer the account collection period, the higher credit sales earned. And with a negative average payment period (non-significant) means that the lower the accounts payable period, the higher the reputation earned for borrowing opportunities. Converge the three effects into one place, we can explain for an increase in company profitability due to the long cash conversion cycle. In contrast, shortening the cash conversion cycle could harm the company profitability. The company could lose good credit customers as reducing account receivable period, incur unnecessary carrying cost if the inventory period is lengthened and hamper its credit reputation as lengthening the account payable period. In those cases, cash conversion cycle is said to have a positive relationship with company profitability. The study further reveals that the ratio of financial asset to total asset (FATA) is also significant and positively impact on the firm’s profitability. The management of chemical and paint companies listed in Nigeria stock exchange should keep enough financial assets to match their total assets. This implies that an increase in the amount of financial asset will also cause an increase in the profitability since they are brought for profitability purposes.
4.5 COMPARISON OF THE FINDINGS WITH THE OBJECTIVE O F THE STUDY
4.5.1 Research Objective One
To determine whether there is a positive and significant impact of Account Collection
Period (ACP) on Profitability of the selected firms.
The result obtained from the regression model indicates that Account Collection Period has a
positive and significant impact on profitability of the firms. With the positive and significant
impact of account collection period on profitability, it follows that average collection period is a
useful tool of working capital management in increasing the profitability of chemical and paint
firms listed in Nigeria stock exchange. This in line with theoretical base that Cash conversion
cycle can also have positive influence on company profitability and it could be interpreted
through a chain of positive impact of inventory periods and Account Receivable Period with a
negative impact of accounts payable period on the company profitability. Our finding is
consistent with the work of Muhammad, Jan, and Ullah (2011).
87
4.5.2 Research Objective Two
To assess whether there is a positive and significant impact of Inventory Conversion Period
(ICP) on Profitability of the selected firms.
The result obtained from the regression model shows that Inventory Conversion Period has a
negative and non-significant impact on profitability of the selected firms. With the negative
impact of inventory conversion period on profitability, it follows that shorter inventory
conversion period is a useful tool of working capital management in maintaining profitability.
This is consistent with the work of Ashraf (2012), Nimalathasan (2010) and Vural, Sokmen &
Cetenak (2012).
4.5.3 Research Objective Three
To ascertain whether there is a positive and significant impact of Average Payment Period (APP) on Profitability of the selected firms.
The result obtained from the regression model indicates that Average Payment Period has a
negative and non-significant impact on profitability of the selected chemical and paint sector in
NSE. With the negative impact of average payment period on profitability, it follows that shorter
average payment period affect the volume of liquidity and the firm’s profitability. This findings
is consistent with Deloof (2003) and Muhammad,Jan and Ullah, (2011).
4.5.4 Research Objective Four
To examine whether there is a positive and significant impact on Cash Conversion Period on Profitability of the selected firms.
The result obtained from the regression model indicates that Cash Conversion Cycle (CCC) has a
positive and non-significant impact on profitability of the selected chemical and paint sector in
NSE. With the positive impact of cash conversion cycle on profitability, it follows that shorter
cash conversion cycle affect the volume of liquidity and the firm’s profitability. This findings is
consistent with the work of Ebenezer & Asiedu, (2013); Ganesamoorthy & Rajavathana, (2013);
Muhammad, Jan & Ullah ,(2012); Natarajan & Getachew ,(2012); Ali,(2011); Ani, Okwo &
Ugwunta, (2013).
88
REFERENCES
Alipour, M. (2011) “Working Capital Management and Corporate Profitability: Evidence from Iran,” World Applied Science Journal, Vol.12, No. 7, pp. 1093-1099
Deloof, M. (2003) “Does Working Capital Management affect Profitability of Bekgian Firms? Journal of Business Finance and Accounting,Vol. 30, No. (3-4), 573-588
Amarjit, G., Nahum, B. and Neil, M. (2010) “The Relationship between Working Capital Management And Profitability: Evidence From The United States,” Business and Economics Journal, 10, pp 1-9
Huynh,N.T. (2012) “ The Influence Of Working Capital Management On Profitability of listed
Companies In The Netherlands,” Master Of Research In Business Administration, pp.1-58
Makori, D.M.& Jagongo, A. (2013) “Working Capital Management and Firm Profitability: Empiricval Evidence from Manufacturing and Contruction Firms in Nairobi,” International Journal of Accounting and Taxation, Vol.1 No.1.pp.1-14
Nzioki P.M.,Kimeli S.K. & Abudho M. R. ( 2013) “Management of Working Capital and Its effect on Profitability of Manufacturing Companies Listed on Nairobi Securities Exchange Kenya,” International Journal of Business and Finance Management Research, Vol.1.pp.35-42
Nzioki, P.M.,Kimeli S.K. & Abudho, M. R. ( 2013) “Management of Working Capital and Its effect on Profitability of Manufacturing Companies Listed on Nairobi Securities Exchange Kenya,” International Journal of Business and Finance Management Research, Vol.1.pp.35-42
Padachi, K., Howorth, C. and Narasimhan M. S. (2012) “Working Capital Financing Preferences: The Case Of Mauritian Manufacturing Small And Medium-Sized Enterprises,” Asian Academy Of Management Journal Of Accounting And Finance, Vol. 8, No. 1, 125–157
Quayyum, S. T. (2011) “ Effect of Working Capital Management and Liquidity: Evidence from thevCement Industries of Banglash,” Journal of Business and Technology, Vol.6, No. 1, pp.37-47
Sarbapriya,, R. (2012) “Evaluaing the Impact of Working Capital Management Components on Corporate Profitability: Evidence from India Manufacturing Firms,” International Journal of Economic Practical and Theories, Vol.2, No.3.pp.127-136
Vural, G., Sokmen, A. G. and Cetenak, E. H. (2012) “Effects OF Working Capital Management on firm’s Performance: Evidence from Turkey,” International Journal of Economics and Financial Issues, Vol.2, No.4 pp. 488-495
89
CHAPTER FIVE
SUMMARY OF FINDING, CONCLUSION AND RECOMMENDATIONS
5.1 SUMMARY OF FINDINGS
The following are the findings which emanate from the study:
1. Account Collection Period has a positive and significant impact on profitability of the
selected chemical and pant firms.
2. Inventory Conversion Period has a negative and non-significant impact on profitability of
the selected chemical and paint firms.
3. Average Payment Period has negative and non-significant impact on the profitability of
the selected chemical and paint firms.
4. Cash Conversion Cycle has positive and non-significant impact on the profitability of the
selected chemical and paint firms listed in Nigeria Stock Exchange.
5.2 CONCLUSION
The study used four measures of working capital to test whether working capital management
has a positive and significant impact on profitability. The above findings indicated clearly that
two of the measures (ACP and CCC) in research have positive but the former shows significant
impact on profitability while the later shows non-significant impact on the profitability of listed
chemical and paint sector in Nigeria. The later, Implies that longer CCC is good for explaining
the financial success of listed chemical and paint firms in Nigeria, but it is not a critical factor to
consider when taking decision to improve profitability.
Notwithstanding, the other two variables (ICP and APP) in the study have negative coefficient
but both have non-significant impact on profitability of the firms.
These results suggest that managers can create value for their shareholders by increasing the
number of days, account receivable and cash conversion cycle to a reasonable maximum time.
The negative effect of average payable and inventory period on profitability is consistent with
the view that less profitable firms wait longer to pay their bills. The result suggest that managers
can increase profitability of listed chemical and paint sector by reducing the number of day’s
90
inventory and accounts payables. However, short ICP and APP is good for explaining the
financial success of a firm, but it is also not a critical factor to be considered while taking
decision to improve profitability.
Again, the positive impact of CR and FATA on profitability indicates that a firm, which has
large CR and FATA, has more profit than the rest.
5.3 RECOMMENDATION
Based on the summary and conclusions the following recommendations are forwarded
1. The results of the study revealed that ACP has positive significant impact on profitability.
This implies that firm with long collection period of their collectibles are more profitable
than those firms that take a short period to convert their receivables into cash, because the
longer the ACP, the higher credit sales earned. Therefore, it is recommended that the
listed chemical and paint firms in Nigeria should increase the period of converting
receivables into cash to a reasonable maximum time as this increases profitability. Thus,
the generous trade credit offered by the firms to the customers for increasing sales
volume, and cash flow can be significantly enhance if the amounts owing to the
customers are collected faster and in contrast, the company could lose good credit
customers as reducing accounts receivable period.
2. The results from the regression showed that ICP has a negative and non-significant
impact on profitability. This implies that as the number of days for inventory conversion
decreases the profitability of the firms is increased and this protects the sector against
unnecessary accumulation of inventories which in turn increases the dangers of
obsolescence, deterioration and pilferage, mishandling, high insurance and carrying costs.
The waiting of the inventory conversion for a short period is advantageous for the sector
to minimize the cost of supplying inventories to customers. However, it is not an
important factor to consider while making profitability decision. But as per the results
from the study, we recommend that it is better for the firms to take a short period for ICP
since it increases the profitability of the sector.
91
3. The result from the study showed that APP has a negative impact on profitability and
non-significant. This implies that as the number of days for accounts payables decrease
the profitability of the firms is increased and this protect the sector against losing the
discounts gained from early payment. The waiting of the accounts payables for a short
period is advantageous for the sector to minimize the cost of purchasing goods from
suppliers. As per the results from the study, we recommend that it is better for the firms
to take short period for APP since it increases the profitability of the sector.
4. The results from the study imply that CCC has a positive though non-significant impact
on profitability. CCC is a comprehensive measure of WCM and it’s the difference
between the summation of ACP and ICP minus APP. The results imply that as the CCC
is increased the profitability of the firms also increases. Therefore it is preferable for the
sector to take relatively long period for cash conversion. If the length of cash conversion
period increases the sales of the firms also increased relatively.
5. The regression results also revealed that CR has a positive impact on the profitability of
the listed chemical and paint firms in NSE. This is to mean that a firm with large CR has
earned more profit than those who have small value of CR. For this reason it
recommended that, the sector has to enlarge the amount of their CR or to its maximum
and increase their profitability. The accepted value of CR is 2:1, taking this into account
the sector may keep their current assets to current liabilities to the standard that they are
going to make profit from operation.
6. The result of the study also showed that there a positive and significant impact of FATA
on profitability. From this finding, one can understand that when FATA of the firms
increases the profitability will also increase. This indicates that managers of chemical and
paint firms have to prefer large FATA to small amount of FATA in order to increase their
profitability, since the financial assets are brought for profitability purposes.
7. The results from the study showed that DR has negative impact on profitability with ACP
and positive impact with ICP,APP and CCC This implies that as the DR of the firms
increase the profitability is also decreased, therefore it is advisable to the managers to
hold minimal amount of DR so as to increase profitability.
92
8. The results from the study also showed that size has a positive impact on firm’s
profitability, though it was dropped due its negative correlation between FATA. So the
positive impact indicated that a firm that has large sales volume will have more profit
than firm, which has less volume of sales. Therefore, we would like to recommend the
firms to increase their sales volume in order to increase their profitability. Firms can
increase their sales through sales promotion, allowing credit sales, and providing sales
discount to their customers.
5.4 AREA FOR FURTHER STUDY
Future research could make an in-depth and extended analysis on the impact of working capital
management on profitability. For instance, the research study at sector level within the European
or American context could be undertaken. The concept of factoring and credit default of
customers may be interfering with the way companies manage their working capital. And also
there are various factors affecting working capital and profitability but in this research some
factors are considered. So in future when decide to conduct this research, various other factors
should also be taken into consideration.
5.5 CONTRIBUTION TO KNOWLEDGE
This study contributes to knowledge by examining the impact of working capital component on
the profitability. Specifically, the study contributes:
i. Geographically, by studying the impact of working capital components and
profitability in the Nigeria listed chemical and paint firms. The study has come to
affirm reactions of several observers and business researchers that the firms should
adopt efficient and effective working capital management polices to keep working
capital at optimal level.
ii. By validating existing researcher findings on the impact of working capital
management on profitability.
93
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101
APPENDIX
DATA PRESENTATION
TABLE 4.1.1 VALUE OF MODEL PROXIES FOR CROSS SECTION FIRM 1 (CAP PLC)
COMPUTATION FOR DEPENDENT VARIABLE: GOP
YEARS SALES COGS S-C TA FA TA-FA GOP
2000 878884 631906 246978 399380 5028 394352 0.626288
2001 1051489 708643 342846 788313 384057 404256 0.848091
2002 1093199 702615 390584 918075 464829 453246 0.861748
2003 1203038 758263 444775 1118352 689737 428615 1.037703
2004 1466765 910332 556433 1243371 761439 481932 1.154588
2005 1525426 914407 611019 1361395 551223 810172 0.754184
2006 1986247 1216406 769841 1545108 933482 611626 1.258679
2007 2099929 1150016 949913 1978401 1359808 618593 1.535603
2008 2679857 1464302 1215555 2221429 1486432 734997 1.653823
2009 3027604 1710913 1316691 2163208 1271559 891649 1.476692
2010 3644934 1919169 1725765 2370301 1430350 939951 1.836016
2011 4312774 2255466 2057308 2924512 1827199 1097313 1.87486
2012 5231330 2771534 2459796 2875802 1307718 1568084 1.568663
2013 6195824 3040720 3155104 3035012 1523854 1511158 2.087872
COMPUTATION FOR DEPENDENT VARIABLES; ACP, ICP, APP& CCC: 1A
YEARS 0P AR CL AR OP /CL AR AVG AR SALES ACP OP AP CLO AP
2000 156663 125548 282211 141105.5 878884 58.6010298 26272 133338
2001 125548 27411 152959 76479.5 1051489 26.5480832 34922 76272
2002 27411 54180 81591 40795.5 1093199 13.620903 21225 34922
2003 54180 92990 147170 73585 1203038 22.3255832 96783 21225
2004 92990 131333 224323 112161.5 1466765 27.9110474 26982 96783
2005 131333 173151 304484 152242 1525426 36.4280732 59963 26982
2006 173151 134500 307651 153825.5 1986247 28.2675355 44340 59963
2007 134500 107938 242438 121219 2099929 21.069729 27316 44340
2008 107938 86171 194109 97054.5 2679857 13.2189488 80949 27316
2009 86171 137427 223598 111799 3027604 13.4781943 150441 80949
2010 137427 119746 257173 128586.5 3644934 12.8765219 92427 150441
2011 119746 72848 192594 96297 4312774 8.14983697 151230 92427
2012 72848 72782 145630 72815 5231330 5.08044321 151873 151230
2013 72782 59267 132049 66024.5 6195824 3.88954601 152948 151873
102
COMPUTATION FOR INDEPENDENT VARIABLES; ACP, ICP, AP P&CCC: 1B
OP /CL AP AVG AP COGS APP 0P INV CLO INV OP/CL INV AVG INV ICP CCC
159610 79805 631906 46.09676914 343924 247249 591173 295586.5 170.736 183.24021
111194 55597 708643 28.63628795 247249 255802 503051 251525.5 129.553 127.46477
56147 28073.5 702615 14.58384393 255802 233339 489141 244570.5 127.0514 126.08848
118008 59004 758263 28.40236171 233339 292968 526307 263153.5 126.6724 120.59567
123765 61882.5 910332 24.81195048 292968 246261 539229 269614.5 108.1026 111.20174
86945 43472.5 914407 17.35273516 246261 378478 624739 312369.5 124.6872 143.76256
104303 52151.5 1216406 15.6488027 378478 173273 551751 275875.5 82.78039 95.399118
71656 35828 1150016 11.37133744 173273 113714 286987 143493.5 45.54296 55.241347
108265 54132.5 1464302 13.49336578 113714 193020 306734 153367 38.22911 37.954688
231390 115695 1710913 24.68195344 193020 333893 526913 263456.5 56.20486 45.001099
242868 121434 1919169 23.09510523 333892 307498 641390 320695 60.99185 50.77327
243657 121828.5 2255466 19.71539473 307498 492001 799499 399749.5 64.6911 53.125538
303103 151551.5 2771534 19.95872953 533202 975123 1508325 754162.5 99.3202 84.441914
304821 152410.5 3040720 18.29495399 975123 577852 1552975 776487.5 93.20751 78.802101
COMPUTATION FOR CONTROL VARIABLES; CR, DR, FATA COY SIZE
YEARS CA CL TA TL FA CR DR FATA COY SIZE
2000 333098 305984 399380 360151 5028
1.088612 0.901775 0.01259 13.67
2001 713114 323631 788313 380908 384057
2.203479 0.483194 0.487188 13.86
2002 786400 370330 918075 437066 464829
2.123511 0.476068 0.506308 13.9
2003 963404 482501 1118352 569561 689737
1.996688 0.509286 0.616744 14
2004 1023168 559377 1243371 648625 761439
1.829121 0.521667 0.612399 14.2
2005 1146684 488892 1361395 565078 551223
2.345475 0.415073 0.404896 14.24
2006 1325760 598188 1545108 688043 933482
2.216293 0.445304 0.604153 14.5
2007 1804953 871736 1978401 977581 1359808
2.070527 0.494127 0.687327 14.8
2008 1984455 1402393 2221429 1534968 1486432
1.415049 0.690982 0.669133 14.8
2009 1918054 1274230 2163208 1408765 1271559
1.505265 0.651239 0.587812 14.92
2010 2033084 1203922 2370301 1349004 1430350
1.688717 0.569128 0.603447 15.12
2011 2616262 1278775 2924512 1466854 1827199
2.045913 0.501572 0.624788 15.28
2012 2423767 1682098 2875802 1757230 1307718
1.440919 0.61104 0.454732 15.47
2013 2554584 1684572 3035012 3035012 1523854
1.516459 1 0.502092 15.64
Source: Calculation Based on Annual Reports of the CAP PLC from 2000-2013
Notes 1- AVG = AVERAGE, 2- AR= ACOUNT RECEIVABLE, 3- AP= ACCOUNT PAYABLE, 4- INV = INVENTORY, 5- ACOGS = ANNUAL COST OF GOODS SOLD, 6- TCA = TOTAL CURRENT ASSETS, 7- TCL = TOTAL CURRENT LIABILITIES, 8- TA = TOTAL ASSETS, 9- TL = TOTAL LIABILITIES, 10- FA = FINANCIAL ASSETS. DEPENDENT VARIABLE: 11- GROSS OPERATING PROFIT = SALES-ACOGS/TA-FA, INDEPENDENT VARIABLES: ACCOUNTS COLLECTION PERIOD = AVG.DR/ANNUAL SALES * 365, 12- ACCOUNTS PAYABLE PERIOD = AVG. CR/ACOGS *365, 13- INVENTORY CONVERSION PERIOD = AVG. INV/ACOGS * 365, 14- CASH CONVERSION PERIOD = ACP + ICP – APP, CONTROL VARIABLES: 15- LIQUIDITY RATIO = TCA/TCL, 16- LEVERAGE RATIO = TL/TA, 17- FINANCIAL ASSETS TO TOTAL ASSETS = FA/TA, COMPANY SIZE = LOG.SALES, 18-OP= OPENING, 19-CL= CLOSING,20-S=SALES, 21-C= COGS
TABLE 4.1.2 VALUE OF MODEL PROXIES FOR CROSS SECTION FIRM 2 (BEGER PLC)
103
COMPUTATION FOR DEPENDENT VARIABLE: GOP
SALES COGS S-C TA FA TA-FA GOP
1118933 696378 422555 923190 59836 863354 0.489434
1483915 903362 580553 984386 101888 882498 0.657852
1406301 763198 643103 1236601 87398 1149203 0.559608
1822202 1170071 652131 1711435 69551 1641884 0.397185
1723605 996354 727251 1459803 83812 1375991 0.528529
1892290 1155836 736454 2055479 85855 1969624 0.373906
2124150 1291602 832548 1977994 70033 1907961 0.436355
2139252 1267949 871303 2003085 70051 1933034 0.450744
2370721 1438215 932506 2029739 375682 1654057 0.563769
2225468 1266502 958966 2270055 631582 1638473 0.58528
1371772 1371772 1197695 2600602 742442 1858160 0.64456
2375563 1415962 959601 2654532 850242 1804290 0.531844
2513664 1536612 977052 2848115 928424 1919691 0.508963
2708448 1639886 1068562 3536641 1322952 2213689 0.482706
COMPUTATION FOR INDEPENDENT VARIABLES; ACP, ICP, AP P&CCC: 1A
YEARS OP INV CL INV OP/CL INV AVG INV COGS ICP OP AR CL AR SALES
2000 428182 376622 804804 402402 696378 210.9152 146711 146342 1118933
2001 442665 428182 870847 435423.5 903362 175.9312 155994 146711 1483915
2002 489395 442665 932060 466030 763198 222.8792 155440 155994 1406301
2003 534416 489395 1023811 511905.5 1170071 159.6873 195395 155440 1822202
2004 496682 534416 1031098 515549 996354 188.864 174385 195395 1723605
2005 383529 496682 880211 440105.5 1155836 138.9804 138709 174385 1892290
2006 366212 383529 749741 374870.5 1291602 105.9365 179283 138709 2124150
2007 416679 366212 782891 391445.5 1267949 112.684 258792 179283 2139252
2008 326574 416679 743253 371626.5 1438215 94.3139 169108 258792 2370721
2009 298109 326574 624683 312341.5 1266502 90.01537 203437 169108 2225468
2010 534817 298109 832926 416463 1371772 110.8121 204129 203437 1371772
2011 560291 534817 1095108 547554 1415962 141.1459 106220 204129 2375563
2012 537857 560291 1098148 549074 1536612 130.4246 258356 106220 2513664
2013 512204 537857 1050061 525030.5 1639886 116.8594 204045 258356 2708448
104
COMPUTATION FOR INDEPENDENT VARIABLES; ACP, ICP, AP P&CCC: 1B
OP/CL AR AVG AR ACP OP AP CL AP OP/CL AP AVG AP APP CCC
293053 146526.5 47.79748 121033 100485 221518 110759 58.05329 200.6594
302705 151352.5 37.22832 140914 121033 261947 130973.5 52.91935 160.2402
311434 155717 40.41575 142441 140914 283355 141677.5 67.75737 195.5376
350835 175417.5 35.13737 167254 142441 309695 154847.5 48.30419 146.5205
369780 184890 39.15332 181846 167254 349100 174550 63.94389 164.0734
313094 156547 30.19603 193446 181846 375292 187646 59.25649 109.9199
317992 158996 27.32083 207910 193446 401356 200678 56.71056 76.54672
438075 219037.5 37.37226 196695 170718 367413 183706.5 52.88294 97.17335
427900 213950 32.94008 170718 196695 367413 183706.5 46.62229 80.6317
372545 186272.5 30.55064 164770 170718 335488 167744 48.34304 72.22296
407566 203783 54.22242 150158 164770 314928 157464 41.8979 123.1367
310349 155174.5 23.84222 249457 150158 399615 199807.5 51.50543 113.4827
364576 182288 26.46938 313129 249457 562586 281293 66.81709 90.07689
462401 231200.5 31.15739 208269 313129 521398 260699 58.02546 89.99136
COMPUTATION FOR CONTROL VARIABLES; CR, DR FATA, &CO YSIZE
CA CL TA TL FA CR DR FATA COY SIZE
733538 503465 923190 5261669 59836 1.456979 5.699443 0.064814 13.93
764449 529388 984386 567624 101888 1.444024 0.576627 0.103504 14.21
979818 728225 1236601 809135 87398 1.345488 0.654322 0.070676 14.16
1468642 1174445 1711435 1277450 69551 1.250499 0.74642 0.040639 14.42
1172070 902276 1459803 964253 83812 1.299015 0.660536 0.057413 14.36
767051 1042762 2055479 1211962 85855 0.735595 0.589625 0.041769 14.45
717196 887702 1977994 1065139 70033 0.807924 0.538495 0.035406 14.57
784310 788690 2003085 973242 70051 0.994446 0.485872 0.034972 14.58
929662 674317 2029739 864551 375682 1.378672 0.425942 0.185089 14.68
1201008 780553 2270055 983225 631582 1.538663 0.433128 0.278223 14.62
1538749 847562 2600602 989565 742442 1.8155 0.380514 0.285489 14.76
1430014 759796 2654532 928662 850242 1.882103 0.34984 0.320298 14.68
1538464 874960 2848115 1112632 928424 1.758325 0.390656 0.325978 14.74
1978847 877196 3536641 1100939 1322952 2.255878 0.311295 0.37407 14.81
Source: Calculation Based on Annual Reports of Berger Paint from 2000-2013
Notes 1- AVG = AVERAGE, 2- AR= ACOUNT RECEIVABLE, 3- AP= ACCOUNT PAYABLE, 4- INV = INVENTORY, 5- ACOGS = ANNUAL COST OF GOODS SOLD, 6- TCA = TOTAL CURRENT ASSETS, 7- TCL = TOTAL CURRENT LIABILITIES, 8- TA = TOTAL ASSETS, 9- TL = TOTAL LIABILITIES, 10- FA = FINANCIAL ASSETS. DEPENDENT VARIABLE: 11- GROSS OPERATING PROFIT = SALES-ACOGS/TA-FA, INDEPENDENT VARIABLES: ACCOUNTS COLLECTION PERIOD = AVG.DR/ANNUAL SALES * 365, 12- ACCOUNTS PAYABLE PERIOD = AVG. CR/ACOGS *365, 13- INVENTORY CONVERSION PERIOD = AVG. INV/ACOGS * 365, 14- CASH CONVERSION PERIOD = ACP + ICP – APP, CONTROL VARIABLES: 15- LIQUIDITY RATIO = TCA/TCL, 16- LEVERAGE RATIO = TL/TA, 17- FINANCIAL ASSETS TO TOTAL ASSETS = FA/TA, COMPANY SIZE = LOG.SALES, 18-OP= OPENING, 19-CL= CLOSING,20-S=SALES, 21-C= COGS.
105
TABLE 4.1.3 VALUE OF MODEL PROXIES FOR CROSS SECTION FIRM 3 (DN MEYER PLC)
COMPUTATION FOR DEPENDENT VARIABLE: GOP
SALES COGS S-C TA FA TA-FA GOP
628134 432511 195623 462780 128966 333814 0.586024
903755 626522 277233 526108 156103 370005 0.749268
1142995 794135 348860 729835 38554 691281 0.504657
1500188 1057680 442508 787934 56543 731391 0.605022
1760874 1278069 482805 1085430 15749 1069681 0.451354
1368935 1098733 270202 971763 43745 928018 0.29116
2008794 1491512 517282 1097222 15764 1081458 0.478319
2094034 1435749 658285 1920638 34381 1886257 0.34899
2266913 1679618 587295 3219652 517366 2702286 0.217333
1894487 1449738 444749 2637019 217758 2419261 0.183837
1184594 749771 434823 2715977 286088 2429889 0.178948
1362715 855991 506724 2728698 174999 2553699 0.198427
1472734 910200 562534 2577673 233653 2344020 0.239987
1500112 926124 573988 2627558 217758 2409800 0.238189
COMPUTATION FOR INDEPENDENT VARIABLES; ACP, ICP, AP P&CCC: 1A
YEARS OP INV CL INV COGS OP/CL INV AVG INV ICP SALES OP AR CL AR
2000 164258 1303232 432511 1467490 733745 619.2141 628134 41588 41518
2001 130323 146880 626522 277203 138601.5 80.74664 903755 50609 41588
2002 146880 268324 794135 415204 207602 95.41795 1142995 131303 50609
2003 268324 236049 1057680 504373 252186.5 87.02828 1500188 205754 131303
2004 236049 303392 1278069 539441 269720.5 77.02869 1760874 458973 205754
2005 303392 406924 1098733 710316 355158 117.9838 1368935 232614 458973
2006 406924 329009 1491512 735933 367966.5 90.04807 2008794 466580 232614
2007 329009 522811 1435749 851820 425910 108.276 2094034 564810 466580
2008 522811 629537 1679618 1152348 576174 125.2091 2266913 350026 564810
2009 629537 402542 1449738 1032079 516039.5 129.9231 1894487 146617 350026
2010 402542 446691 749771 849233 424616.5 206.7098 1184594 51494 146617
2011 280246 213660 855991 493906 246953 105.3023 1362715 24539 51494
2012 342020 242276 910200 584296 292148 117.1545 910200 265640 24539
2013 242279 210110 926124 452389 226194.5 89.1468 1500112 335680 265640
106
COMPUTATION FOR INDEPENDENT VARIABLES; ACP, ICP, AP P&CCC: 1B
OP/CL AR AVG AR ACP OP AP CL AP OP/CL AP AVG AP APP CCC
83106 41553 24.14587 52138 45642 97780 48890 41.25872 602.1013
92197 46098.5 18.61783 45642 68439 114081 57040.5 33.23073 66.13374
181912 90956 29.04557 68439 97518 165957 82978.5 38.13854 86.32497
337057 168528.5 41.00346 97518 130838 228356 114178 39.40225 88.6295
664727 332363.5 68.89345 130838 150973 281811 140905.5 40.24079 105.6813
691587 345793.5 92.19914 150973 134849 285822 142911 47.47515 162.7078
699194 349597 63.52215 134849 167775 302624 151312 37.02879 116.5414
1031390 515695 89.88807 167775 235712 403487 201743.5 51.28778 146.8763
914836 457418 73.64975 235712 378988 614700 307350 66.79063 132.0682
496643 248321.5 47.84269 378988 408538 787526 393763 99.13756 78.6282
198111 99055.5 30.52122 408538 426184 834722 417361 203.1777 34.05331
76033 38016.5 10.18263 426184 434313 860497 430248.5 183.4607 -67.9757
290179 145089.5 58.18245 434313 300783 735096 367548 147.3907 27.94624
601320 300660 73.15514 300783 306738 607521 303760.5 119.7168 42.58516
COMPUTATION FOR CONTROL VARIABLES; CR, DR FATA, &CO YSIZE
CA CL TA TL FA CR DR FATA COY SIZE
311857 153345 462780 159572 128966 2.033695 0.344812 0.278677 20.26
371026 207279 526108 213506 156103 1.789984 0.405822 0.296713 20.62
457296 382460 729835 441471 38554 1.19567 0.604892 0.052826 20.86
510951 436445 787934 498359 56543 1.170711 0.632488 0.071761 21.13
810725 701731 1085430 772282 15749 1.155322 0.711499 0.014509 21.29
720525 800071 971763 869159 43745 0.900576 0.894415 0.045016 21.04
836299 735621 1097222 933865 15764 1.136861 0.851118 0.014367 21.42
1155260 1217017 1920638 1317195 34381 0.949255 0.685811 0.017901 21.46
1143893 1592171 3219652 1785580 517366 0.718449 0.554588 0.16069 21.54
635267 1490048 2637019 1830016 217758 0.42634 0.693971 0.082577 21.36
807103 1686625 2715977 2128593 286088 0.478531 0.78373 0.105335 20.9
695748 859098 2728698 2049602 174999 0.809859 0.751128 0.064133 21.03
613437 795795 2577673 1924685 233653 0.770848 0.746675 0.090645 21.11
615028 710169 2627558 1934550 217758 0.86603 0.736254 0.082875 21.19
Source: Calculation Based on Annual Reports of DN Meyer PLC from 2000-2013
Notes 1- AVG = AVERAGE, 2- AR= ACOUNT RECEIVABLE, 3- AP= ACCOUNT PAYABLE, 4- INV = INVENTORY, 5- ACOGS = ANNUAL COST OF GOODS SOLD, 6- TCA = TOTAL CURRENT ASSETS, 7- TCL = TOTAL CURRENT LIABILITIES, 8- TA = TOTAL ASSETS, 9- TL = TOTAL LIABILITIES, 10- FA = FINANCIAL ASSETS. DEPENDENT VARIABLE: 11- GROSS OPERATING PROFIT = SALES-ACOGS/TA-FA, INDEPENDENT VARIABLES: ACCOUNTS COLLECTION PERIOD = AVG.DR/ANNUAL SALES * 365, 12- ACCOUNTS PAYABLE PERIOD = AVG. CR/ACOGS *365, 13- INVENTORY CONVERSION PERIOD = AVG. INV/ACOGS * 365, 14- CASH CONVERSION PERIOD = ACP + ICP – APP, CONTROL VARIABLES: 15- LIQUIDITY RATIO = TCA/TCL, 16- LEVERAGE RATIO = TL/TA, 17-FINANCIAL ASSETS TO TOTAL ASSETS = FA/TA, COMPANY SIZE = LOG.SALES, 18-OP= OPENING, 19-CL= CLOSING,20-S=SALES, 21-C= COGS.
107
TABLE 4.1.4 VALUE OF MODEL PROXIES FOR CROSS SECTION FIRM 4 (PREMIER PLC)
COMPUTATION FOR DEPENDENT VARIABLE: GOP
SALES COGS S-C TA FA TA-FA GOP
172191.26 131269.178 40922.08 84523.737 1821.622 82702.12 0.494813
247914.99 189359.06 58555.93 113090.04 6574.029 106516 0.549738
195614.48 151132.537 44481.94 107950.48 681.765 107268.7 0.414678
279977 187317 92660 100216.69 3152.064 97064.62 0.954622
185508.31 150389.075 35119.24 144957.58 733.574 144224 0.243505
189053.46 149787.101 39266.36 148184.38 1438.036 146746.3 0.26758
203082.29 150854.608 52227.68 158805.3 873.895 157931.4 0.330698
186017.71 137864.76 48152.95 163650.81 1121.15 162529.7 0.296272
234925046 165816231 69108815 226126775 7043182 2.19E+08 0.315445
223511 148862 74649 213953 1677 212276 0.35166
166062 133499 32563 167982 754 167228 0.194722
182740 143055 39685 179171 1835 177336 0.223784
257886 187488 70398 291702 5550 286152 0.246016
279977 187317 92660 285772 3793 281979 0.328606
COMPUTATION FOR INDEPENDENT VARIABLES; ACP, ICP, AP P&CCC: 1A
YEARS 0P INV CL INV COGS OP/CL INV AVG INV ICP SALES OP AR
2000 27135182 27268644 131269178 54403826 27201913 75.63617 172191.261 23441.449
2001 27268644 28328046 189359060 55596690 27798345 53.58284 247914.986 33855.397
2002 28328046 24566346 151132537 52894392 26447196 63.87259 195614.481 49630.058
2003 24566346 22464316 155420523 47030662 23515331 55.22498 279977 50682.921
2004 22464316 14220579 150389075 36684895 18342448 44.51782 185508.313 46461.744
2005 14220579 20092053 149787101 34312632 17156316 41.80637 189053.462 19637.703
2006 20092053 32480844 150854608 52572897 26286449 63.60133 203082.286 29148.218
2007 32480844 28036954 137864760 60517798 30258899 80.1111 186017.71 15367.823
2008 28036954 36431381 165816231 64468335 32234168 70.95488 234925046 22161979
2009 36431.381 30665 148862 67096.381 33548.19 82.25799 223511000 26678992
2010 30665 10119 133499 40784 20392 55.75383 166062 28114
2011 10119 18412 143055 28531 14265.5 36.39794 182740 13784
2012 18412 18800 187488 37212 18606 36.222 257886 20886
2013 18800 23750 187317 42550 21275 41.45579 279977 49693
COMPUTATION FOR INDEPENDENT VARIABLES; ACP, ICP, AP P&CCC: 1B
CL AR OP/CL AR AVG AR ACP OP AP CL AP OP/CL AP AVG AP APP CCC
33855.397 57296.85 28648.42 60.72709 24764111 30241293 55005404 27502702 76.47253 59.89073
49630.058 83485.46 41742.73 61.45694 30241293 41879067 72120360 36060180 69.50798 45.5318
50682.921 100313 50156.49 93.58775 41879067 42886305 84765372 42382686 102.3584 55.10197
108
46461.744 97144.67 48572.33 63.32271 42886305 38895167 81781472 40890736 96.03055 22.51714
19637.703 66099.45 33049.72 65.02754 38895167 16038013 54933180 27466590 66.66246 42.8829
29148.218 48785.92 24392.96 47.09478 16038013 31177580 47215593 23607797 57.52729 31.37386
15367.823 44516.04 22258.02 40.00436 31177580 38865895 70043475 35021738 84.73678 18.86891
22161.979 37529.8 18764.9 36.82009 38865895 34624768 73490663 36745332 97.28408 19.64712
26678992 48840971 24420486 37.94179 34624768 33666327 68291095 34145548 75.16227 33.7344
28114000 54792992 27396496 44.73928 33666327 19202000 52868327 26434164 64814.86 -64687.9
13784 41898 20949 46.04536 19202 20923 40125 20062.5 54.85294 46.94625
20886 34670 17335 34.62447 20923 18817 39740 19870 50.69763 20.32477
49693 70579 35289.5 49.94714 18817 25926 44743 22371.5 43.55264 42.6165
49249 98942 49471 64.49428 25926 31687 57613 28806.5 56.13144 49.81864
COMPUTATION FOR CONTROL VARIABLES; CR, DR FATA, &CO YSIZE
CA CL TA TL FA CR DR FATA COY SIZE
67560.616 51263.606 84523.737 5763.606 1821.622 1.317906 0.068189 0.021552 19
89221.253 77954.077 113090.035 80254.077 6574.029 1.144536 0.709648 0.058131 19.33
81001.943 80639.895 107950.484 82939.895 681.765 1.00449 0.768314 0.006316 19.09
77530826 78694.318 100216.687 82994.318 3152.064 985.215 0.828149 0.031452 19.11
40862006 52895.061 144957.577 58475.737 733.574 772.5108 0.403399 0.005061 19.04
50678310 47964.843 148184.378 53545.519 1438.036 1056.572 0.361344 0.009704 19.06
48722562 58782.141 158805.302 80936.636 873.895 828.8667 0.50966 0.005503 19.13
51449.083 77815.163 163650.809 78395.839 1121.15 0.66117 0.479043 0.006851 19.04
70398.056 59703.785 226126.775 103589.417 7043182 1.179122 0.458103 31.14705 19.27
63207 86393 213953 141593 1677 0.731622 0.661795 0.007838 19.22
25707 108959 167982 182704 754 0.235933 1.08764 0.004489 18.93
42487 132242 179171 246876 1835 0.321282 1.377879 0.010242 19.02
68048 177369 291702 279806 5550 0.383652 0.959219 0.019026 19.37
71652 207713 285772 295006 3793 0.344957 1.032312 0.013273 19.45
Source: Calculation Based on Annual Reports of Premier Paint PLC from 2000-2013
Notes 1- AVG = AVERAGE, 2- AR= ACOUNT RECEIVABLE, 3- AP= ACCOUNT PAYABLE, 4- INV = INVENTORY, 5- ACOGS = ANNUAL COST OF GOODS SOLD, 6- TCA = TOTAL CURRENT ASSETS, 7- TCL = TOTAL CURRENT LIABILITIES, 8- TA = TOTAL ASSETS, 9- TL = TOTAL LIABILITIES, 10- FA = FINANCIAL ASSETS. DEPENDENT VARIABLE: 11- GROSS OPERATING PROFIT = SALES-ACOGS/TA-FA, INDEPENDENT VARIABLES: ACCOUNTS COLLECTION PERIOD = AVG.DR/ANNUAL SALES * 365, 12- ACCOUNTS PAYABLE PERIOD = AVG. CR/ACOGS *365, 13- INVENTORY CONVERSION PERIOD = AVG. INV/ACOGS * 365, 14- CASH CONVERSION PERIOD = ACP + ICP – APP, CONTROL VARIABLES: 15- LIQUIDITY RATIO = TCA/TCL, 16- LEVERAGE RATIO = TL/TA, 17- FINANCIAL ASSETS TO TOTAL ASSETS = FA/TA, COMPANY SIZE = LOG.SALES, 18-OP= OPENING, 19-CL= CLOSING,20-S=SALES, 21-C= COGS.
109
TABLE 4.1.5 VALUE OF MODEL PROXIES FOR CROSS SECTION FIRM 5 (AFRICAN PAINT PLC)
COMPUTATION FOR DEPENDENT VARIABLE: GOP
SALES COGS S-C TA FA TA-FA GOP 212283089 140649011 71634078 379339098 11895649 367443449 0.19495266 226849538 149352638 77496900 387811464 9131022 378680442 0.20464986 228215000 146777000 81438000 367337887 9918000 357419887 0.22784966 213571 135911 77660 278436 3647 274789 0.28261684 79412 58978 20434 376514 3520 372994 0.05478372 70387 61515 8872 330817 1259 329558 0.02692091 78113 47811 30302 319725 1450 318275 0.09520698 59905 45203 14702 292711 2025 290686 0.05057691 42579 35005 7574 375990 1723 374267 0.02023689 50941 41421 9520 377692 5283 372409 0.02556329 52203 42670 9533 357122 489 356633 0.02673056 58719 54475 4244 347539 149 347390 0.01221682 23490 34114 -10624 403553 101 403452 -0.0263327 10433 19817 -9384 394864 3453 391411 -0.0239748
COMPUTATION FOR INDEPENDENT VARIABLES; ACP, ICP, AP P&CCC: 1A
YEARS OP INV CL INV COGS OP/CL INV AVG INV ICP SALES OP AR
2000 111991282 91012211 140649011 203003493 101501747 263.4084 212283.089 58227.882
2001 91012211 65340092 149352638 156352303 78176152 191.0532 226849.538 20938.524
2002 65340092 42512021 146777000 107852113 53926057 134.1015 228215 26637.942
2003 42512 29443 135911 71955 35977.5 96.62049 213571 43712
2004 29443 24665 58978 54108 27054 167.4304 79412 68998
2005 24665 17143 61515 41808 20904 124.0341 70387 27167
2006 17143 16821 47811 33964 16982 129.6444 78113 7073
2007 16821 3141 45203 19962 9981 80.59343 59905 7127
2008 3141 5036 35005 8177 4088.5 42.63112 42579 1221
2009 5036 7728 41421 12764 6382 56.2379 50941 0
2010 7728 5825 42670 13553 6776.5 57.96631 52203 1596
2011 5825 3809 54475 9634 4817 32.27545 58719 0
2012 3809 3402 34114 7211 3605.5 38.57676 23490 4989
2013 3402 2938 19817 6340 3170 58.38674 10433 995
COMPUTATION FOR INDEPENDENT VARIABLES; ACP, ICP, AP P&CCC: 1B
CL AR OP/CL AR AVG AR ACP OP AP CL AP
OP/CL AP AVG AP APP CCC
20938.524 79166.41 39583.203 68.05944441 50585123 48650979 99236102 49618051 128.7644 202.7035
26637.942 47576.47 23788.233 38.27517182 48650979 56333056 1.05E+08 52492018 128.2842 101.0441
110
43712 70349.94 35174.971 56.25775876 56333056 75994 56409050 28204525 70.13804 120.2212
68998 112710 56355 96.31258457 75994 90904 166898 83449 224.109 -31.176
27167 96165 48082.5 221.0007618 90904 104101 195005 97502.5 603.4184 -214.987
7073 34240 17120 88.77775726 104101 137625 241726 120863 717.1421 -504.33
7127 14200 7100 33.17629588 137625 149113 286738 143369 1094.511 -931.691
1221 8348 4174 25.43210083 149113 38919 188032 94016 759.1496 -653.124
0 1221 610.5 5.233389699 38919 18442 57361 28680.5 299.0539 -251.189
1596 1596 798 5.71779117 18442 35100 53542 26771 235.9049 -173.949
0 1596 798 5.579564393 35100 34039 69139 34569.5 295.7082 -232.162
4989 4989 2494.5 15.50592653 34039 33647 67686 33843 226.759 -178.978
995 5984 2992 46.49127288 33647 32466 66113 33056.5 353.6854 -268.617
689 1684 842 29.45749065 32466 33705 66171 33085.5 609.3863 -521.542 COMPUTATION FOR CONTROL VARIABLES; CR, DR FATA, &CO YSIZE
CA CL TA TL FA CR DR FATA
COY
SIZE
131100 308658 415339 308658 131096 0.424741 0.743148 0.315635 19.17
112496 344170 387811 361670 9131.02 0.326861 0.932593 0.023545 19.24
106212 309426 367338 325426 9918 0.343254 0.885905 0.027 19.25
103052 245515 278436 259514 3647 0.419738 0.932042 0.013098 19.18
56973 255525 376514 269224 3520 0.222964 0.715044 0.009349 18.19
25702 272937 330817 286636 1259 0.094168 0.866449 0.003806 18.07
29978 281494 319725 295193 1450 0.106496 0.923272 0.004535 18.17
16466 280907 292711 284606 2025 0.058617 0.972311 0.006918 17.91
9131 326542 375990 326542 1723 0.027963 0.868486 0.004583 17.57
17508 326542 377692 294866 5283 0.053616 0.780705 0.013988 17.75
8739 288685 357122 288685 489 0.030272 0.808365 0.001369 17.77
10732 329350 347539 329350 149 0.032585 0.947663 0.000429 17.89
7345 260343 403553 287487 101 0.028213 0.71239 0.00025 16.97
10434 128814 394864 151451 3453 0.081001 0.383552 0.008745 16.16
Source: Calculation Based on Annual Reports of African Paint PLC from 2000-2013 Notes 1- AVG = AVERAGE, 2- AR= ACOUNT RECEIVABLE, 3- AP= ACCOUNT PAYABLE, 4- INV = INVENTORY, 5- ACOGS = ANNUAL COST OF GOODS SOLD, 6- TCA = TOTAL CURRENT ASSETS, 7- TCL = TOTAL CURRENT LIABILITIES, 8- TA = TOTAL ASSETS, 9- TL = TOTAL LIABILITIES, 10- FA = FINANCIAL ASSETS. DEPENDENT VARIABLE: 11- GROSS OPERATING PROFIT = SALES-ACOGS/TA-FA, INDEPENDENT VARIABLES: ACCOUNTS COLLECTION PERIOD = AVG.DR/ANNUAL SALES * 365, 12- ACCOUNTS PAYABLE PERIOD = AVG. CR/ACOGS *365, 13- INVENTORY CONVERSION PERIOD = AVG. INV/ACOGS * 365, 14- CASH CONVERSION PERIOD = ACP + ICP – APP, CONTROL VARIABLES: 15- LIQUIDITY RATIO = TCA/TCL, 16- LEVERAGE RATIO = TL/TA, 17- FINANCIAL ASSETS TO TOTAL ASSETS = FA/TA, COMPANY SIZE = LOG.SALES, 18-OP= OPENING, 19-CL= CLOSING,20-S=SALES, 21-C= COGS.