Pacific B usiness R eview (International)

A Refereed Monthly International Journal of Management Indexed With Web of Science(ESCI)
ISSN: 0974-438X
Impact factor (SJIF):8.603
RNI No.:RAJENG/2016/70346
Postal Reg. No.: RJ/UD/29-136/2017-2019
Editorial Board

Prof. B. P. Sharma
(Principal Editor in Chief)

Prof. Dipin Mathur
(Consultative Editor)

Dr. Khushbu Agarwal
(Editor in Chief)

Editorial Team

A Refereed Monthly International Journal of Management

Factors that Influence the Efficiency of Working Capital Requirements in Nepal

 

Abdul Rahman

Ph.D. Scholar,

Department of studied in commerce, Mangalore University,

Iam21rahman@gmail.com

 

Dr. Parameshwara

Associate Professor& Chairman

Department of studied in commerce, Mangalore University,

paramasiddhantha@gmail.com

Abstract

The purpose of this study is to assess the perception of financial professionals on the factors affecting the efficiency of working capital requirements in Nepal. These are the factors that influence the working capital requirements in Nepal. To know the perception of financial professions, this study considered a sample of 200 companies listed on the Nepal Stock Exchange (NSE). These companies are categorized into 9 groups. These are banks, development banks, finance companies, insurance companies, hotels, hydropower companies, trading companies, manufacturing and processing companies, and others in the others category. A quantitative cross-sectional survey research approach is used in this study. Through literature research and validation by experts and working capital management firm practitioners, eighteen major factors influencing working capital were discovered and shortlisted for inclusion in the questionnaire. The study was carried out using a structured questionnaire to examine the most crucial elements influencing the efficiency of working capital requirements in Nepal, and various statistical methods were used to analyse survey respondents' perspectives. This research contributes to the body of knowledge on the factors that influence working capital requirements and will benefit NSE-listed companies. The study is the first of its kind to look at the crucial aspects that contribute to working capital requirements in Nepal.

Keywords: Working Capital Requirements, Firm Growth, Operating efficiency, Operating Cycle, Firm Size,

Introduction

The goal of this study is to investigate the elements that impact the efficiency of working capital requirements in Nepal. The working capital need, in the context of this study, is defined as the minimal resources that a firm requires to properly pay the normal expenditures and expenses essential to operate the business. Working capital management deals with current assets and current liabilities. Working capital satisfies the short-term financial requirements of a company firm. Lower working capital requirements result in less need for financing and a lower cost of capital, which enhances cash available for shareholders (Ganesan, 2007).Inefficient working capital management may result in large losses, poor performance, and even bankruptcy. Having a lot of working capital means the firm has idle cash, which can lead to poor performance (Sri Nivas, 2013). Insufficient operating capital, on the other hand, means the firm cannot acquire inputs for manufacturing. Various research on working capital management reveals a substantial association between a company's profit and its working capital management efficiency. Working capital management influences the firm's profitability and liquidity (Taleb et al., 2010). Working capital management seeks to achieve a balance between the various components of working capital. Working capital management is critical to creating shareholder value (Nazir & Afza, 2008, p. 294). Thus, corporations strive to maintain a level of working capital that optimizes value (Deloof, 2003). Working capital management is a basic idea for financial executives like Chief Financial Officers (CFOs), but it has become one of the most critical concerns in enterprises. Many CFOs struggle to identify basic working capital drivers and optimal working capital levels (Lamberson, 1995). Inability to plan and handle working capital requirements may lead to insolvency and bankruptcy. Smith (1973) contends that finance managers' incapacity to plan and control their organisation’s existing assets and obligations contributes to many company failures. According to Nazir and Afza (2008), firms may reduce risk and increase overall performance by understanding working capital. To maximise working capital, it is critical to understand its components. Working capital is ideal when risk and efficiency are balanced. You must keep an eye on accounts receivable, payable, inventory, cash, and marketable securities to keep your working capital at its best.  Working capital management increases organisations competitiveness and profitability by protecting them from financial shocks. For example, increasing cash cycle speed through receivables and payables management increases profitability and liquidity. Also, proper inventory management is crucial to managing the firm's liquidity and profitability (Taleb et al., 2010). So, it's critical to balance each component of working capital.

 

Review of Literature

2.1 The concepts of working capital

 

Working capital is the money utilised by firms to run their day-to-day operations. According to Adeniji (quoted by Atseye, Ugwu, and Tokon (2015), working capital is the capital accessible for day-to-day activities represented by net current assets. Even before the word was invented and employed by finance professionals, businesses have utilised working capital management. Working capital management includes control, optimization, and value measurement. Workers' compensation insurance (WC insurance) is a type of insurance that covers workers' compensation benefits. Current assets are assets that can be converted into cash quickly and then re-invested, thereby continually rotating. A firm pays cash for inventories or raw supplies. Produced items will be sold to earn cash from the inventory. Working capital can be interpreted in two ways: Gross Working capital comprises cash, short-term securities, debtors, bills receivables, and inventory (Tulsian, 2009). The gap between current assets and liabilities is net working capital (Ibrahimov, 2014). Trivedi (2010) calls this "current liabilities." Outsiders' claims should be paid quickly.

2.2 Working capital in companies

Managing current assets, such as cash and cash equivalents, inventory, and debtors, requires a mix of rules and strategies. Srinivasan (1999) defines cash management as cash forecasting, cash flow control, optimal cash level, and excess cash investment. Managing capital involves ensuring the availability of critical resources that help produce cash flow. This might lead to cost savings and better financial management. According to Moyer, Maguigan, and Kretlow (2001), small and medium-sized businesses need excellent cash management to develop loan budgets, reduce resource waste, support trade operations, and ensure effective and efficient cash usage.

2.3 Important of working capital management

 

Working capital management is critical for all organisations, according to empirical and theoretical data. A company may not have many fixed assets, but it must invest in current assets (Atseye et al., 2015). Smith contends, citing Atseye et al. (2015), that working capital management directly influences a firm's liquidity, profitability, and hence net value. Working capital tries to maintain a balance between liquidity and profitability while running a firm. Many businesses may boost their profitability by using a good working capital management system. Working capital management includes ratio analysis and component management. So, according to Mandiefe (2016), good working capital management is vital for a company's survival and success. Working capital, on the other hand, must be properly managed because it is considered the lifeblood of the company and its inefficient use can lead to its demise.

2.4 Empirical Literature Review- Global Trends in Working Capital Management

Ganesan (2007) examined the working capital management efficiency in the telecommunications equipment business.The connection between working capital management efficiency and profitability was explored using correlation analysis. By using a sample of 443 annual financial statements of 349 telecommunication equipment companies covering the period 2001–2007, this study found evidence that even though "days of working capital" is negatively related to profitability, it is not significantly impacting the profitability of firms in the telecommunication equipment industry. An empirical review of working capital management efficiency by Lemeri (2009) from the school of graduate studies at Strathmore University Nairobi, concluded that effective working capital management is one of the preconditions for the continuing survival of a company. It investigated a sample of 8 out of 31 institutions in Tanzania over the period 2005 to 2009. From its study effort, the regression result demonstrated that an appreciated return on assets has strong favorable connections with working capital management efficiency. The positive association confirms hypothesis one, which asserts that there is a positive link; this finding reveals that return on assets has a statistically significant positive relationship with working capital management efficiency. Aggressive working capital management in law manifests in current assets, impacting income optimism.

2.5 Factors affecting working capital requirement

A business should prepare its financial plan in such a way that it has neither a surplus nor inadequate working capital (Rani, 2013). In business, there is no set of rules or formula to determine the working capital requirement. However, the amount of working capital required depends on various factors. These factors need to be considered when determining the requirement for working capital. (1) Nature of the business (2) Scale of operations (3) Operating Scale (4) Seasonal factors (5) Production cycle) (6) Credit allowed (7) Credit Availed (8) operating efficiency (9) Inventory management (10) Growth prospects (11) Level of Competition (12) Inflation (13) Account payable (14) Dividend policy, (15) Plant efficiency (16) Liquidity (17) Account Receivable (18) Taxation policy. The above factors, and a lot more, need to be carefully considered while determining the working capital requirement of a firm. These factors all affect working capital in different ways. Some businesses increase their working capital requirements, while others decrease their working capital requirements. Capital management focuses on cutting across both physical and financial needs, ensuring that related costs are minimized and all incomes are maximized. Working capital entails debtors, stock, and creditors.

 

3. Research Objectives

  1. To determine the Factors that influence the efficiency of Nepal working capital requirements.
  2. To assess the financial profession's consensus on the factors influencing the efficiency of working capital requirements in Nepal.
  3. To assess the perception of working capital requirements in Nepal among the demographic factors.
  4. To draw conclusions based on the study's findings.

 

 

4. Research Methodology

The discussion of the methodological instruments and methods used in the study to fulfil the study's objectives As a result, it addressed concerns such as study design, data gathering techniques, investigation strategy, and data analysis methodologies. The researcher attempted to emphasize and defend the method used to conduct the study. The approach and equipment utilised to collect data were discussed in this study. The population, sample, and sampling methodologies were also discussed. It also specified how the data would be gathered and presented.

4.1 Research Design

The study intends to investigate major financial professions' perceptions of the influencing factors for working capital requirements in the context of Nepal. “The study adopts a quantitative cross-sectional survey design to study a phenomenon at a given point in time. A structured questionnaire was designed and administered to collect data from the respondents. A questionnaire is a popular instrument for collecting data where the respondents can quickly answer the questions (Saunders et al., 2016). It also facilitates collecting information on the participants' perceptions, including their beliefs, attitudes, and opinions (Yamin & Sim, 2016).” In general, Denscombe (2012) says that a quantitative research design can use methods like surveys, which use closed questionnaires, to a large extent.

 

4.2 Research Instrument

The questionnaire was divided into two sections. The first section of the questionnaire asked about respondents' demographic data, while the second section asked about participant perceptions of variables impacting the efficiency of working capital requirements in the context of Nepal, a developing nation. According to Denscombe (2011), the questionnaire is based on written material provided directly by participants in answer to questions posed by the researcher. The questionnaire's components and causes were determined through a search of literature, mostly studies done in similar circumstances in poor nations. Unstructured interviews with project management practitioners in the industry were also conducted to further expand its content and incorporate the true failure drivers. Likert scales were used to assess the strength of each item. Items were graded on a five-point scale, with 1 being extremely unpleasant and 5 being extremely acceptable.

4.3 Validity and Reliability

Validity is concerned with whether a research tool, such as a questionnaire, genuinely measures what should be measured or if the results are useful to the respondent (Saunders et al., 2016). According to Saunders et al. (2012), conducting a literature review is one technique to ensure outstanding coverage of questions while also improving the validity of the research instrument. The researchers utilised the literature review as a guide to assure the validity of the questionnaire and, as a result, the study's outcomes. The research instrument for this study was developed from previous studies with minor adjustments to meet the needs of the current investigation. The questionnaire was also examined by specialists in the subject, who provided useful comments that were adopted.

A research instrument's dependability, on the other hand, relates to its consistency across time. In other words, the instrument's dependability relates to the degree to which it produces consistent findings while the variables being tested remain constant. Cronbach's alpha was utilised to measure the research tool's dependability. The questionnaire was pilot tested prior to its full delivery, and the outcome indicated a Cronbach alpha coefficient of 0.968, indicating good reliability. A Cronbach alpha coefficient of 0.7 or greater, in general, is a fair and reliable indicator of construct dependability. Nunnally (1978).

4.4 Target Papulation and Sample

We constructed the questionnaire in such a manner to ensure that the study included representatives from important financial professions. Financial professionals were the study's target group(such as financial analysts, financial advisors, financial planners, financial managers, and chartered accountants) working for major manufacturing companies, the service industry, banking, and funding agencies. The sample included financial professions, mainly those who had good knowledge management and a minimum level of experience. FP was selected randomly from 200 companies listed on the Nepal Stock Exchange (NSE). These companies are categorized into 9 groups. These are banks, development banks, finance companies, insurance companies, hotels, hydropower companies, trading companies, manufacturing and processing companies, and others in the others category. A total of 650 questionnaires were sent out to the five groups of respondents using the purposive and convenience probability sampling methods. A usable sample of 400 people (83 from financial analysts, 60 from financial advisors, 98 from financial planners, 121 from financial managers, and 38 from chartered accounts) was chosen for the analysis. The questionnaires were sent out online and printed.

 

5. Analysis and Results

5.1 Descriptive Analysis

Table 1 shows the personal profiles of the respondents. It is observed that the vast majority of participants fall into the age groups of 20–29 years and 30–39 years, almost the same. More than 63.5 percent of respondents are men, while only 36.5 percent are women. Table 1 further indicates that most respondents have a tertiary education (173 degrees, 182 Master’s Degrees, 8 Doctorates, and 37 others). It is also seen that 37.3 percent of the surveyed sample are those working with 0.5

 

years of experience, and about 40.5 percent have 6–10 years of experience. Finally, Table 1 reveals that the majority of financial professions (30.3 percent) of the respondents are financial managers. 24.5 percent are financial planners, 20.8 percent are financial analysts and financial advisors, and 9.5% are chartered accountants. Candidates for the job are well-qualified and experienced enough to give accurate information about the subject matter of the study.

5.2Anova Analysis

ANOVA provides researchers to determine the statistical significance of differences between groups of data. It works by assessing the degree of variation within the groups using representative samples from each. In this paper it is used to check the level of Financial Professionals consensus on the factors influencing the working capital requirement in Nepal.

To test the Financial Professionals consensus ANOVA test were used and the results are showed in the table 2. Table 2 provide evidence that all the eighteen identified factors that influence the efficiency of working capital requirement in Nepal are (p<0.05). Table 2 indicate that Account Payable, Tax Policy and Level of competition are factors which are noted highly positive influence factors on working capital requirement in Nepal based on the financial profession response and other factors means value are also consider satisfactory.

 

Table 1

Personal Profile of Respondents

Profile

Categories

Frequency

Percentage

Age group (in years)

20-29

30-39

40-49

50-59

60+ years

Total

160

163

36

25

16

400

40.0

40.8

9.0

6.3

4.0

100

Gender

Male

Female

Total

254

146

400

63.5

36.5

100

Academic Qualifications

Degree

Master’s Degree

Doctorate

Others

Total

173

182

8

37

400

43.3

45.5

2.0

9.3

100

Total Experience (in years)

0-5

6-10

11-15

Above 15 years

Total

149

162

70

19

400

37.3

40.5

17.5

4.8

100

Financial Professions

Financial Analyst

Financial Advisor

Financial planner

Financial Manager

Chartered Accountant

Total

83

60

98

121

38

400

20.8

15.0

24.5

30.3

9.5

100

Source: Survey data

 

 

 

Table 2

Financial Professionals consensus on the factors influencing the working capital requirement in Nepal

 

ANOVA

 

Sum of Squares

d.f

Mean Square

F

Sig.

Nature of Business

Between Groups

9.992

4

2.498

3.021

.018

Within Groups

326.652

395

.827

 

 

Total

336.644

399

 

 

 

Scale of operations

Between Groups

16.543

4

4.136

4.849

.001

Within Groups

336.881

395

.853

 

 

Total

353.424

399

 

 

 

Operating Scale

Between Groups

16.351

4

4.088

4.584

.001

Within Groups

352.244

395

.892

 

 

Total

368.594

399

 

 

 

Seasonal factor

Between Groups

23.257

4

5.814

4.021

.003

Within Groups

571.133

395

1.446

 

 

Total

594.390

399

 

 

 

Production Cycle

Between Groups

20.158

4

5.040

3.815

.005

Within Groups

521.819

395

1.321

 

 

Total

541.978

399

 

 

 

Credit Allowed

 

Between Groups

12.415

4

3.104

2.448

.046

Within Groups

500.762

395

1.268

 

 

Total

513.178

399

 

 

 

Credit Availed

Between Groups

15.014

4

3.754

3.157

.014

Within Groups

469.696

395

1.189

 

 

Total

484.710

399

 

 

 

Operating efficiency

Between Groups

19.348

4

4.837

4.943

.001

Within Groups

386.511

395

.979

 

 

Total

405.859

399

 

 

 

Inventory Managment

Between Groups

23.771

4

5.943

7.389

.000

Within Groups

317.699

395

.804

 

 

Total

341.469

399

 

 

 

Growth Prospects

Between Groups

23.436

4

5.859

4.121

.003

Within Groups

561.524

395

1.422

 

 

Total

584.960

399

 

 

 

Level of competition

Between Groups

26.034

4

6.509

4.545

.001

Within Groups

565.663

395

1.432

 

 

Total

591.698

399

 

 

 

Inflation

Between Groups

11.143

4

2.786

2.181

.070

Within Groups

504.535

395

1.277

 

 

Total

515.678

399

 

 

 

Liquidity

Between Groups

15.853

4

3.963

4.266

.002

Within Groups

366.973

395

.929

 

 

Total

382.826

399

 

 

 

Account receivable

Between Groups

11.720

4

2.930

3.150

.014

Within Groups

367.363

395

.930

 

 

Total

379.083

399

 

 

 

Account Payable

 

Between Groups

25.685

4

6.421

6.319

.000

Within Groups

401.393

395

1.016

 

 

Total

427.077

399

 

 

 

Dividend Policy

Between Groups

10.711

4

2.678

2.124

.077

Within Groups

497.999

395

1.261

 

 

Total

508.710

399

 

 

 

Plant efficiency

Between Groups

20.269

4

5.067

3.894

.004

Within Groups

514.028

395

1.301

 

 

Total

534.298

399

 

 

 

Tax Policy

Between Groups

20.517

4

5.129

4.280

.002

Within Groups

473.323

395

1.198

 

 

Total

493.840

399

 

 

 

Source: Survey data

Hence Statistical analysis of Mean is very significant if (M= from 1 to 1.8 means strongly disagree), (M= 1.81 to 2.60 means disagree), (M= from 2.61 to 3.40 means Neutral), (M= from 3.41 to 4.20 means agree) and (M= from 4.21 to 5 means strongly agree).

 

5.3Inferential Analysis

The independent sample t-test -The dependent variable should be approximately normally distributed. The dependent variable should also be measured on a continuous scale. Compares the means of two independent groups to ascertain whether statistical evidence exists that the associated population means are statistically significantly different. The independent sample t-test was considered appropriate to do so.

The hypothesis is set out as follows:

H1: There is significant difference in the perception of working capital requirement in Nepal among the demographic factors.

Sub1: There is significant difference in the perception among Gender

Sub2: There is significant difference in the perception between age group

Sub3: There is significant difference in the perception among academic qualification group

Sub4: There is significant difference in the perception among different experience group

Sub5: There is significant difference in the perception among financial profession group

 

5.3.1 There is significant difference in the perception among Gender

In order to get a response from the respondent, the gender group consists of male and females.

To test the significant difference in the perception of working capital requirement between male and female, independent sample t test was used and the results are showed in the table No 3.

 

 

Table 3

Independent Sample T test result

Perception among Gender

 

Gender

Mean

T value

d.f

Sig.

Remark

Male

3.95

3.322

398

.001

Null Hypothesis rejected

Source: Survey data

Table 3 explains that there exists a significant difference in the perception of working capital efficiency between male and female respondents (p<0.05), which indicates that male (M=3.95) respondents have more positive perception about factors influencing working capital efficiency than female (M=3.67). 

 

5.3.2 There is significant difference in the perception between age group.

One-Way ANOVA- To Measures of population aging are important because they shape our perception of demo- graphic trends. This study consists minimum age 0-5 and maximum 60 above.

To test the significant difference in the perception of working capital efficiency among age groups, one way ANOVA test were used and the results are showed in the table 4,

 

Table 4

One-Way ANOVA result

Perception between age group

 

Sum of Squares

d.f

Mean Square

F

Sig.

Between Groups

31.321

4

7.830

12.855

.000

Within Groups

240.601

395

.609

 

 

Total

271.922

399

 

 

 

 

Source: Survey data

 

Table 4 explains that there exists a significant difference in the perception of working capital efficiency among age groups of the respondents (p<0.05). Table 4 indicates that age group between 30-39 (Mean=4.13) respondents have more positive perception about factors influencing working capital efficiency than others age groups.

 

5.3.3 There is significant difference in the perception among academic Qualification groups

 

Academic Qualification lower from Degree to maximum till Doctorate was taken to know the perception of respondent. 

To test the significant difference in the perception of working capital efficiency among age groups, one way ANOVA test were used and the results are showed in the table 5;

 

Table 5

One-Way ANOVA result

Perception among academic Qualification groups

ANOVA

 

Sum of Squares

d.f

Mean Square

F

Sig.

Between Groups

1.981

3

.660

.969

.407

Within Groups

269.941

396

.682

 

 

Total

271.922

399

 

 

 

Source: Survey data

 

Table 5 indicates Anova test results on difference in the perception among academic qualification. Since p-value greater than 0.05, therefore researcher fails to reject null hypothesis that is means there is no significant difference in the perception among academic Qualification groups.

 

5.3.4 There is significant difference in the perception among different experience group

 

Demographic information provides data regarding research participants and is necessary for the determination of whether the individuals in a particular study are a representative sample of the target population for generalization purposes.

To test the significant difference in the perception of working capital efficiency among different experience group, one way ANOVA test were used and the results are showed in the table 6;

 

Table 6

One-Way ANOVA result

Perception among different experience group

 

ANOVA

 

Sum of Squares

d.f

Mean Square

F

Sig.

Between Groups

17.131

3

5.710

8.875

.000

Within Groups

254.790

396

.643

 

 

Total

271.922

399

 

 

 

Source: Survey data

 

Table 6 explains that there exists a significant difference in the perception of working capital requirement among experience group of the respondents (p<0.05). Table 6 indicates that experience group between 11-15 (Mean=3.82) respondents have more positive perception about factors influencing working capital requirement than others experience group.

 

5.3.5 There is significant difference in the perception among financial profession group

 

Respondents in financial profession research have the freedom to choose whether or not to engage in a study and for how long. Finally, the replies participants contribute present the research project with the data it requires. To test the significant difference in the perception of working capital requirement among different financial profession group, one way ANOVA test were used and the results are showed in the table 7.

 

Table 7

One-Way ANOVA result

Perception among financial professions group

 

ANOVA

 

Sum of Squares

d.f

Mean Square

F

Sig.

Between Groups

15.688

4

3.922

6.046

.000

Within Groups

256.234

395

.649

 

 

Total

271.922

399

 

 

 

Source: Survey data

 

Table 7 explains that there exists a significant difference in the perception of working capital requirement among financial professions group of the respondents (p<0.05). Table 7 indicates that between five financial professions, financial planner (Mean=4.04) respondents have more positive perception about factors influencing working capital requirement than others financial professions.

 

  1. Conclusion and Implications

 

The following conclusions were reached as a result of the findings of the research: It was concluded that the nature of the business, the scale of operations, business cycles, seasonal factors, production cycles, credit allowed, credit availed, operating efficiency, industry competition, and inflation, among other factors, have the greatest impact on working capital requirements in Nepal. It has been found that components of working capital management, such as liquidity management, inventory management, accounts receivable management, and accounts payable management, are not correctly handled, resulting in an increase in the total system's working capital demand requirement. According to the findings of this study, the operating cycle, the size of operation, operational efficiency, inventory management, and plant efficiency are the internal elements that have the greatest impact on working capital needs. Working capital needs and management procedures vary from industry to industry and from nation to nation, as well as within an industry. This might be one of the reasons why some of the conclusions are in direct conflict with those of well-known earlier writers (e.g., Nazir and Afza, 2008, 2009; Taleb et al., 2010). When investors buy debt or equity instruments, they should do a lot of research on the companies before they buy them. This is because working capital needs and working capital management can change from industry to industry and country to country.

 

 

 

  1. Limitations

 

The limitation of this study is confined to a sample of firms that are publicly traded on the Nepal Stock Exchange (NSE). The firms on this list are divided into nine groups. Banks, development banks, finance firms, insurance companies, hotels, hydropower companies, trade companies, manufacturing and processing companies, and others are included in the "others" category, as are other types of businesses. The conclusions of this study could only be applied to manufacturing and service companies that were identical to those that were included in this study, and not to any other types of businesses. Furthermore, the sample size is relatively small.

 

  1. Scope for future research

 

Future research should investigate the generalization of the findings beyond the companies listed on the Nepal Stock Exchange (NSE). These companies are categorized into 9 groups. Future studies may include economic factors such as real GDP growth and external factors that influence more than the variables that were used in this study. Further research on the same topic with a change in methodology and a wider scope to cover a large population is needed.

 

References

 

Appuhami, B.A. (2008). The impact of firms’ capital expenditure on working capital management: an empirical study across industries in Thailand. International Management Review, 4(1), 8-21.

 

Pitambar Lamichhane (2019). Efficiency of Working Capital Management and Profitability: Evidence from Manufacturing Firms of Nepal. Journal of management Dynamic Shanker Dev Campus, Vol. 22, No. 1: 21-34.

 

Phadindra Kumar Poudel and Pujan Maharjan (2020). Effect of working capital management on profitability: A case of Nepalese Manufacturing Firms. International Research Journal of Management Science, Vol.5, Issue 1 -Dec 2020.

 

Samiloglu, F., & Demirgunes, K. (2008). The effect of working capital management on firm profitability: Evidence from Turkey. The International Journal of Applied Economics and Finance, 44-50.

 

Sharma, A., & Kumar, S. (2011). Effect of Working Capital Management on Firm Profitability: Empirical Evidence from India. Global Business Review, 159-173.

 

Sultan, D., & Murtaza, M. M. (2019). Impact of aggressiveness of working capital management on firm's profit. Humanities & Social Sciences Reviews, 612-618.

 

 Tahir, M., & Anuar, M. B. (2015). The determinants of working capital management and firms’ performance of textile sector in Pakistan. Quality & Quantity, 605-618.

 

Teruel, P. J. (2007). Effects of working capital management on SME profitability. International Journal of Managerial Finance, 164-177.

 

Wang, Y.-J. (2002). Liquidity management, operating performance, and corporate value: Evidence from Japan and. Journal of Multinational Financial Management, 159-169.

 

Chiou, J.R., Cheng, L., & Wu, H.W. (2006). The determinants of working capital management. Journal of American Academy of Business, 10(1), 149-155.

 

 

 

 

 

 

 

 

 

 

 

Deloof, M. (2003). Does working capital management affect profitability of Belgian firms? Journal of Business Finance and Accounting, 30(3/4), 573-588.

 

Filbeck, G. & Krueger, T. (2005). An analysis of working capital management results across industries. Mid-American Journal of Business, 20(2), 11-18.

 

Ganesan, V. (2007). An analysis of working capital management efficiency in telecommunication equipment industry. Rivier Academic Journal, 3(2), 1-10.

 

Gill, A., Biger, N., & Mathur, N. (2010). The relationship between working capital management and profitability: Evidence from United States. Business and Economics Journal, 2010, 1-9.

 

Lamberson, M. (1995). Changes in working capital of small firms in relation to changes in economic activity. Mid- American Journal of Business, 10(2), 45-50.

 

Nazir, M.S. & Afza, T. (2008). On the factors determining working capital requirements. Proceedings of ASBBS, 15(1), 293-301.

 

Nazir, M.S. & Afza, T. (2009). Working Capital Requirements and the Determining Factors in Pakistan. IUP Journal of Applied Finance, 15(4), 28-38.

 

Sathyamoorthi, C.R. & Wally-Dima, L.B. (2008). Working capital management: the case of listed retail domestic companies in Botswana. The Icfaian Journal of Management Research, 7(5), 7-24.

 

Shin, H.H. & Soenen, L. (1998). Efficiency of working capital management and corporate profitability. Financial Practice and Education, 8(2), 37-45.

 

Smith, K.V. (1973). State of the art of working capital management. Financial Management, 2, 50-55.

 

Soenen, L.A. (1993). Cash conversion cycle and corporate profitability. Journal of Cash Management, 13(4), 53-58.

 

Taleb, G.A., Zoued, A.N. & Shubiri, F.N. (2010). The Determinants of Effective Working Capital Management Policy: A Case Study on Jordan. Interdisciplinary Journal of Contemporary Research in Business, 2(4), 248-264.

 

Weinraub, H.J. & Visscher, S. (1998). Industry practices relating to aggressive conservative working capital policies. Journal of Financial and Strategic Decisions, 11(2), 11-18.

 

Bryman, A. & Bell, E. (2007). Business research methods (2nd ed.). New York: Oxford Conceptual framework of working capital management. (2017, June 22).

 

Cooper, R. D. & Schindler, S. P. (2014). Business Research Methods. Boston: Irwin McGraw Hill. Corporate finance and portfolio management. (2016). CFA Institute. Charlottesville. USA. Level 1, Volume 4. Wiley. 142-145, 172

 

Daniel, C., & Ibrahim, A. (2019). Project failure and its influence on the performance of construction firms in Nigeria. International Journal of Research in Business, Economics and Management, 3(2), 86-95

 

Nazir, M.S. & Afza, T. (2009). Working Capital Requirements and the Determining Factors in Pakistan. IUP Journal of Applied Finance, 15(4), 28-38.

 

Kappelman, L., McKeeman, R. & Zhang, L. (2006). Early warning signs of IT project failure: The Dominant Dozen. IT Project Management, 23(1), 31-37.

 

 

Khang, D.B. & Moe, T.L. (2008), Success criteria and factors for international development projects: a life-cycle-based framework. Project Management Journal, 39(1), 72-84.

 

Padachi, K. (2006). Trends in working capital management and its impact on firms’ performance: An analysis of Mauritian small manufacturing firms. International review of Business research papers, 2(2), 45-58.

 

Niklas, H. & Viktor, J. (2014). Working capital management: a study about how Swedish 102 companies manage working capital in relation to revenue growth over time. Master’s Thesis, 30 Credits, Uppsala University, Spring 2014

 

Sharma, A.K. & Kumar, S. (2009). Effect of working capital management on firm profitability: Empirical evidence from India. Research journal, 25, 36-53.