Testing factors affecting finacial performance and impact of working capital management under cross industry Kiểm tra các yếu tố ảnh hưởng đến hiệu quả tài chính và tác động của quản lý vốn lưu động trong các ngành liên ngành
Background of the thesis
Vietnam is currently undergoing economic integration, leading to heightened competition both domestically and globally To thrive in this environment, businesses must effectively reform their production and business strategies A crucial focus for managers is on working capital management, which plays a significant role in enhancing overall business performance.
Effective working capital management is crucial for any organization, as it ensures the smooth operation of production processes In addition to fixed assets like machinery and factories, businesses need to allocate funds for purchasing goods and raw materials Proper management of working capital is essential, as a lack of it can hinder a firm's operational efficiency (Mukhopadhyay, 2004).
In this study, as we cannot take all industries into a single research, we select 3 industries - ICT, Food Manufacturing, and Supporting - to conduct a cross-industry analysis
Information Communication Technology (ICT) encompasses the various technologies utilized for creating, displaying, storing, manipulating, and exchanging information It includes all forms of communication, information processing hardware and networks, as well as software connections ICT is applicable across diverse fields and is essential to modern human life.
Vietnam's ICT industry market is very strong with an average growth rate of 8% between
Between 2016 and 2020, the ICT industry in Vietnam, particularly in software and services, is poised for significant growth as the country establishes itself as a key manufacturing hub for hardware and ICT services This trend indicates a rising adoption of technology by both businesses and the public sector.
The Government of Vietnam has recognized Information and Communication Technology (ICT) as a key driver of national development To support this vision, it has implemented a comprehensive information technology master plan with specific targets set for 2020, aiming to elevate Vietnam to the status of an advanced ICT nation.
Food manufacturing involves transforming raw ingredients into various food products through techniques like baking, fermenting, and chemical processes Vietnam boasts significant advantages in livestock raising and the cultivation of staple crops, industrial crops, vegetables, and fruits, providing a robust supply of raw materials for this industry With a substantial domestic and international market demand and a well-established technical infrastructure, including processing enterprises and factories, the food manufacturing sector is recognized as a key industry in Vietnam.
The COVID-19 pandemic significantly disrupted Vietnam's food industry, leading to a broken supply chain, decreased domestic consumption, and canceled export orders Logistics activities were stalled, resulting in shortages of goods and capital, while businesses struggled to uphold their social responsibilities Despite these challenges, the food manufacturing sector showed resilience, growing by 2.2% in 2020, with a notable 4.3% increase in the consumption index of food processing products.
The supporting industry plays a crucial role in the economy by supplying raw materials, accessories, spare parts, components, and semi-finished products to the manufacturing and processing sectors This industry not only enhances the competitiveness of primary industrial products but also serves as a direct catalyst for value creation and accelerates the industrialization of the country.
In 2018, Vietnam's supporting industry comprised approximately 2,000 enterprises producing spare parts and components, along with over 1,500 companies focused on materials for the textile, garment, leather, and shoe sectors, collectively representing nearly 4.5% of the total sales in the processing and manufacturing industries These enterprises provided employment for over 600,000 individuals, accounting for about 8% of the workforce in this sector The net sales from production and business activities in 2018 were estimated to exceed 900 trillion VND, contributing roughly 11% to the overall revenue of the processing and manufacturing industry.
The three industries play a significant role in boosting the economy and society by creating job opportunities, enhancing productivity, and supporting the state budget This importance is why we focus on the relationship between Working Capital Management and Financial Performance across these industries in Vietnam.
Objective of research
This research aims to analyze the relationship between Working Capital Management and Financial Performance across the ICT, Food Manufacturing, and Supporting industries from 2016 to 2020 It includes a cross-industry comparative analysis that evaluates additional factors influencing the financial performance of these three sectors, ultimately providing recommendations for investment opportunities.
Research questions
The research addresses 3 questions (RQ) below:
RQ 1 What factors effect on Financial Performance of ICT, Food and Supporting companies in Vietnam?
RQ 2 What is the relationship between Working Capital Management and Financial Performance in 3 industries?
RQ 3 What is the comparative performance of companies from 3 industries?
Scope of research
This dissertation will concentrate on publicly listed firms within three sectors: Information and Communication Technology (ICT), Food Manufacturing, and Supporting Industries, utilizing data sourced from Vietstock.vn Due to data availability challenges, the study will specifically analyze information from the years 2016 to 2020.
Significant of research
This study provides administrators with guidance on the optimal level of working capital that enhances profitability and positively impacts performance The findings emphasize the importance of identifying the right mix of working capital to improve financial outcomes Additionally, investors gain valuable insights to make informed decisions regarding investments, ultimately aiming for increased returns.
The working capital ratio is essential for creditors as it indicates a company's liquidity Current liabilities are settled using current assets such as cash, cash equivalents, and marketable securities The quicker an asset can be converted into cash, the more likely the company can meet its obligations When current assets surpass current liabilities, the business maintains sufficient capital for its operations.
Definitions and Concepts
Financial Performance
Performance is the good deployment and management of the components of the causal model(s) in order to promptly achieve the stated objectives of the firms (Lebas,
Financial performance is a crucial indicator of a company's ability to manage its assets effectively to generate revenue and maintain financial health over time It enables cross-industry comparisons and reflects a company's overall policies and operational effectiveness in monetary terms Key metrics such as return on equity (ROE), return on assets (ROA), and earnings per share (EPS) are commonly used to assess financial performance, with profitability being a primary evaluation criterion.
Working Capital Management
Working capital represents the difference between a company's current assets—like cash, accounts receivable, and inventory—and its current liabilities, such as accounts payable This financial metric indicates the readily available capital for business operations, reflecting the company's financial health and directly linking to its profitability and liquidity.
Working Capital Management is essential for optimizing a company's current assets and liabilities, ensuring efficient operations (Brigham & Daves, 2002) It involves strategically planning and controlling short-term assets and liabilities, utilizing short-term debt to finance current assets and meet operational expenses Key components include inventory management, which maintains sufficient stock for production while minimizing excess working capital; receivables management, which establishes an optimal credit policy based on the company's operating conditions; accounts payable management, which involves regular checks and reconciliations with suppliers to ensure timely repayments; and cash management, which aims to minimize cash holdings while maintaining a healthy balance between cash inflows and outflows (Falope & Ajilore, 2009).
Performance and Performance measurement
Performance models
Performance measurement models often provide minimal guidance on selecting and operationalizing business process performance indicators While they typically outline performance perspectives and may include examples or steps for deriving indicators, they frequently fall short of presenting concrete, actionable indicators for businesses to implement.
Organizational performance measurement models aim to offer a comprehensive assessment of an organization's performance by examining various perspectives The Balanced Scorecard (BSC) is a prominent model that outlines four key perspectives, enabling the alignment of objectives and performance indicators with both strategies and operations.
Why measuring performance?
The enterprises evaluate their efficiency and effectiveness through determining business’s external and internal environments Thus, measuring corporate financial performance has being a challenge for investigators and firms (Chang, D S., & Kuo, L
Establishing a system to measure corporate performance is a complex task due to the multifaceted nature of sustainability, which encompasses various terms and segments from different academic fields The analysis identifies three primary challenges: enhancing the specific sustainable interests of stakeholders, generating shared sustainable benefits, and empowering stakeholders to act as intermediaries for nature and sustainable development To effectively tackle these challenges, it is essential to organize sustainability information in a way that provides valuable data for managers, enabling informed decision-making and value creation for a diverse range of stakeholders (Hửrisch, Freeman, & Schaltegger, 2014).
To effectively monitor a company's operations, it is essential to develop an assessment of financial performance that evaluates corporate sustainability across three key parameters: social, environmental, and economic (Artiacha et al., 2010) A comprehensive framework should be established to measure both financial and non-financial contributions to sustainable development Goyal et al (2013) suggest various criteria for assessing corporate sustainability, including measurement units, the focus of sustainability methodology, and the nature of proposed indices Key financial indicators for performance measurement encompass profitability ratios, cash flow ratios, return on equity, return on assets, and leverage ratios (Ilinitch et al., 1998; Atkinson, 2000) Additionally, some researchers advocate for incorporating thresholds into composite indices to enable managers to effectively compare sustainability levels within firms.
Factors affecting Financial Performance
2.2.3.1 The impact of Capital Adequacy
Capital adequacy is a crucial financial indicator that assesses a financial institution's ability to manage its balance sheet and withstand unfavorable economic changes It reflects the organization's capital strength and insolvency risk, with capital defined as the funds available to absorb potential losses Commonly measured using the Equity to Asset ratio, capital adequacy can also be evaluated through various leverage ratios, including Debt to Equity and Debt to Total Asset Higher values in these ratios signify a stronger capital adequacy position for the institution.
Capital adequacy is a critical measure of a financial institution's ability to absorb unexpected losses and reflects its overall financial health It ensures compliance with additional capital requirements set by management, safeguarding depositors and reducing the risk of bankruptcy Furthermore, maintaining adequate capital supports the efficiency and stability of industries worldwide (Gupta et al., 2020).
Numerous studies highlight a positive correlation between high capitalization and profitability Obamuyi (2013) supports this by discussing the expected bankruptcy costs hypothesis and the signaling hypothesis, suggesting that increased capital enhances access to affordable funding and risk-taking capabilities This, in turn, facilitates investments in higher-quality assets, ultimately benefiting liquidity and profitability Conversely, some research, including that by Swarnapali, indicates that capital adequacy may negatively affect financial performance.
2.2.3.2 The impact of Firm Size
Larger firms typically exhibit greater diversification and lower default risk compared to smaller firms, which enhances their reputation in debt markets and reduces their borrowing costs Consequently, size significantly influences financial performance, as larger companies are more inclined to utilize debt financing for business expansion and profit opportunities During economic crises, lenders, such as banks and investment funds, face resource limitations and tend to favor established firms with a solid reputation and lower risk profiles (Nzioka, 2013).
2.2.3.3 The impact of Management Efficiency
Management efficiency ratio is a key performance measurement that reflects the ability to maximize revenue with minimal input Although assessing management quality can be challenging, researchers often utilize financial ratios such as efficient resource use, income maximization, reduced operating costs, and EBIT to Total Assets as proxies Additionally, management efficiency can be evaluated through various growth ratios, including assets growth, earnings growth, and profit growth.
Management efficiency is characterized by managers who demonstrate high integrity, professional competence, and quality service, leading to stable profits (Muhmad & Hashim, 2015) This efficiency is influenced by various factors, including management systems, organizational discipline, cost control, and staff quality, making it crucial for the growth and success of financial institutions and their overall financial performance One key metric is the operating expenses to total asset ratio, which reflects the impact of management decisions on firm performance; a lower ratio indicates efficient management practices, while a higher ratio may signal poor management (Nasserinia, 2014) Additionally, the Total Asset Turnover ratio serves as a general efficiency measure, assessing how effectively a company utilizes its assets, and is positively correlated with profitability.
Liquidity measures how efficiently an asset or security can be converted into cash, indicating the speed at which a company can transform its current assets into cash.
Liquidity is typically assessed through various ratios: Interest Coverage, Current Ratio (current assets divided by current liabilities), Quick Ratio (sum of cash, accounts receivable, and marketable securities divided by current liabilities), and Cash Ratio (cash and marketable securities divided by current liabilities) These measures indicate a firm's ability to swiftly convert assets into cash and effectively manage working capital under normal conditions Higher liquidity enables a company to handle unexpected challenges and fulfill its obligations during periods of reduced earnings (Liargovas, P G., & Skandalis, K S., 2008).
Liquidity ratios are crucial indicators for investors and creditors, revealing a company's ability to meet its short-term obligations A liquidity ratio between 2 and 3 signifies a strong financial position, while a ratio below 1 indicates potential liquidity issues and negative working capital, suggesting the company may be facing a liquidity crisis.
2.2.3.5 The impact of Working Capital
Working capital is essential for the success of any business, significantly influencing overall performance According to Hampton (1989), effective working capital management involves making informed decisions regarding the level of investment in current assets and the methods of financing that investment This management is crucial for maintaining liquidity, solvency, and profitability, making it a vital function in corporate management Insufficient working capital can lead to financial insolvency, resulting in legal issues, asset liquidation, and potential bankruptcy.
Relation between Financial Performance and Working Capital Management
Efficiency of Working Capital Management
Effective working capital management is crucial for enhancing company profits while mitigating risks It involves optimizing current assets and liabilities to ensure sufficient cash flow for meeting short-term obligations While excessive investment in working capital can harm profitability, it can also improve liquidity By carefully assessing the composition and level of investments in current assets, companies can develop strategies that ultimately increase shareholder value (Eljelly, 2004).
Effective working capital management varies among enterprises based on their production and business characteristics, impacting their operational efficiency When businesses invest in high current assets with quick inventory turnover and shorter customer debt collection periods, they can repay seller debts later, facilitating faster capital turnover and ultimately increasing revenue and profit Conversely, investing in low current assets results in longer inventory turnover and delayed customer payments, while requiring early payments to sellers This scenario incurs significant inventory preservation costs and reduces capital turnover opportunities, leading to diminished profits.
Effective working capital management aims to achieve an optimal balance between profit and risk by controlling the cash conversion cycle, which includes the inventory period, collection period, and payment period The inventory period reflects the average number of days a company takes to sell its inventory, allowing for reduced carrying and storage costs by monitoring purchasing patterns and sales trends The collection period indicates the time required for a business to receive payments from clients, ensuring sufficient cash flow to meet financial obligations Meanwhile, the payment period measures how long it takes a company to pay its suppliers, enabling managers to capitalize on discounts and favorable credit terms Overall, the cash conversion cycle is a vital metric that illustrates the duration it takes for a company to convert investments in inventory and other assets into revenue from sales.
Research by Deloof (2003) indicates that an organization's profitability significantly impacts its cash conversion cycle, which can influence profitability in both positive and negative ways For instance, a longer cash conversion cycle may lead to increased sales due to extended credit terms offered to clients, but the high cost of working capital can also diminish profits Additionally, findings by Jose, Lancaster, and Stevens (1996) reveal that companies with lower profitability typically experience longer cash conversion cycles compared to their more profitable counterparts, as they categorized firms into eight groups based on profitability and average cash conversion cycles.
Measurement model
The performance of an enterprise is determined by the relationship between its outcomes and the total costs incurred, reflecting the quality of its operations Various indicators, such as Return on Assets (ROA), Return on Equity (ROE), Return on Equity (RE), and Gross Operating Profit (GOP), can be utilized to assess this performance, particularly in relation to working capital management and operational efficiency.
Return on assets is a measure of the relationship between pre-tax profit and all assets that the business has spent
Return on equity is an indicator that shows the relationship between the profit earned and the total equity that the business has spent
Return on Economic Assets (RE)
The ratio of return on assets reflected in a comprehensive way the performance of the enterprise However, the profit result is also affected by the capital structure of the enterprise
Gross profit margin is a key financial metric that indicates the difference between the selling price and the cost of an entity's assets, excluding financial assets This ratio shows how much gross profit, measured in VND, is generated for each VND of assets involved in the core business operations.
This thesis focuses solely on the return on assets (ROA) as a key metric, defined as the ratio of profit to the assets utilized in production and business activities, to assess business efficiency.
Financial indicators
This paper depicts Financial Performance through six main factors: Working Capital Management, Capital Adequacy, Firm Size, Liquidity, Leverage and Management Efficiency
Effective Working Capital Management is crucial for businesses, and key indicators utilized by researchers to assess this include the Cash Conversion Cycle, Creditors Payment Period, Inventory Period, Debtors Collection Period, and Net Trade Cycle.
The second factor is Liquidity which measures the ability to pay for obligations Major indicators include (i) Current ratio; (ii) Quick ratio; (iii) Interest coverage
The third factor is Capital Adequacy, possible indicators include (i) Loan/Total Asset; (ii)
Equity/Total Asset; and (iii) Debt/Equity
The fourth factor is Firm Size with the only indicator is Natural log of Firm’s total assets
The fifth factor is Management Efficiency The indicators include (i) EBIT/Total Asset,
(ii) Earnings per share; (iii) Net profit margin; (iv) Receivable turnover; (v) Inventory turnover; (vi) Payable Turnover.
Empirical review
Effective working capital management is crucial for evaluating a business's performance, with numerous studies highlighting its significant impact on profitability However, the specific relationship between working capital and profitability varies based on the unique development circumstances of each enterprise.
Altawalbeh (2020) investigated the link between working capital management and profitability in 33 Jordanian manufacturing firms listed on the Amman Stock Exchange from 2013 to 2017 The study utilized the Cash Conversion Cycle (CCC) and its components—Average Collection Period (ACP), Average Age of Inventory (AAI), and Average Payment Period (APP)—to assess working capital management, while Return on Assets (ROA) and Net Profit Margin (NPM) were used to evaluate profitability The findings revealed a significant negative relationship between the working capital components and ROA, with a less pronounced impact on NPM The study concluded that improving profitability is possible if managers maintain optimal levels of working capital components However, the results are limited to manufacturing companies similar to those in the study.
Lazaridis I and Tryfonidis D (2006) examined the relationship between working capital management and financial performance in a study of 131 companies listed on the Athens Stock Exchange from 2001 to 2004 Utilizing Pearson correlation and regression analysis, they measured working capital through the Cash Conversion Cycle (CCC), Financial Debt Ratio, and Fixed Financial Assets Ratio, while gross operating profit (GOP) served as the performance indicator Their findings revealed a negative correlation between profitability and the cash conversion cycle, indicating that operational productivity significantly influences how managers and owners handle the firm's working capital.
In their 2010 study, Rezazadeh and Heidarian analyzed data from 1,356 Iranian companies listed on the Tehran Stock Exchange between 1997 and 2007, focusing on the Cash Conversion Cycle (CCC) as an independent variable to assess its impact on profitability, measured by Net Operating Profitability (NOP) The findings indicated that effective working capital management, particularly through reducing inventory levels and shortening the collection period, can enhance organizational value and improve overall profitability.
In a study conducted by Mai (2018) on working capital management in Vietnam from 2012 to 2016, a significant relationship was found between working capital and profitability, measured by gross operating profit (GOP) The research revealed that a positive correlation exists between the cash conversion cycle, inventory turnover period, accounts payable period (APP), and GOP Notably, the findings indicate that a shorter time for collecting receivables and turning over inventory leads to a higher gross profit ratio for businesses However, the study was limited in its exploration of differences in working capital management across various industry groups, lacking insights into how these differences affect operational efficiency.
In her 2018 study, Hoang Lan explored the connection between profitability and working capital management by analyzing the cash conversion cycle across 69 firms listed on the HOSE from 2014 to 2016 Utilizing correlation and regression analysis, she provided empirical evidence on how effective working capital management influences profitability.
A study conducted by Hoang Lan Le in 2018 revealed a significant positive relationship between Cash Conversion Cycle (CCC) and Return on Assets (ROA), indicating that a longer CCC correlates with improved firm performance Additionally, the research found that high growth rates positively impact profitability, suggesting that increased growth can lead to greater returns on investments.
Research gap
In Vietnam, we have not seen any study showing the differences of performance across industries that serve as basis for investment analysts
The sample comprised all companies in ICT, manufacturing and supporting industries as at the end of 2020
Methodology of the research
This chapter outlines the methodologies and data sources utilized in this research, beginning with an analysis of the sector's context to clarify the variations in financial ratios Subsequently, the study measures the fluctuations in the ICT and food sectors, supported by sustainability indicators.
This section details the research strategy, including data collection methods, sample selection, the overall research process, types of data analysis employed, and the limitations encountered during the study.
Analytical framework to guide this research
This study examines how Working Capital Management influences Financial Performance, focusing on key independent variables such as the Cash Conversion Cycle, Debtors Collection Period, Inventory Period, and Creditors Payment Period Additionally, other factors impacting Financial Performance are also considered.
Depending on literature review, we establish an analytical framework for the study as below:
Figure 1: Factors affecting Financial Performance
Hypotheses
3.3.1.1 Financial performance and Firm Size
Larger firms are generally more diversified and exhibit lower default risk than smaller firms, which enhances their reputation in debt markets and reduces their borrowing costs Consequently, these firms are more inclined to utilize debt financing During financial crises, lenders face resource constraints and favor established firms with a strong reputation and lower risk profiles for new loans (Nzioka, 2013).
Days of inventory on hand
Number of days of payable Total asset log Firm Size
Capital Adequacy Equity to Asset
Specifically, the following hypothesis will be tested:
Hypothesis 1: Financial Performance will be positively associated with Firm Size 3.3.1.2 Financial performance and Capital Adequacy
In troublesome financial conditions, it is necessary to have a cautious relationship between capital and the volume of advances so that the company can run effectively It is
The capital adequacy ratio is a crucial indicator of a company's financial health, helping to prevent bankruptcy and ensuring the sustainability of firms Companies with higher capital can mitigate risks associated with business loans and credit While capital adequacy can be assessed through various indicators, this study focuses solely on the Equity to Total Asset ratio to evaluate the hypothesis.
Specifically, the following hypothesis will be tested:
Hypothesis 2: Financial Performance will be positively associated with Capital
Liquidity ratios are crucial for investors and creditors as they assess a company's ability to meet short-term obligations Key liquidity measures include the Interest Coverage Ratio, Current Ratio, Quick Ratio, and Cash Ratio This analysis focuses on the Quick Ratio to evaluate the influence of liquidity risk on financial performance (Liargovas & Skandalis, 2008).
Specifically, the following hypothesis will be tested:
Hypothesis 3: Financial Performance will be positively associated with Liquidity 3.3.1.4 Financial performance and Management Efficiency
Effective management is crucial for decision-making, as inadequate management can lead to increased operating expenses, while efficient management enhances a firm's return on investment Management efficiency is assessed through various metrics, including EBIT to total assets, earnings per share, net profit margin, receivable turnover, inventory turnover, payable turnover, and total return.
Asset Turnover However, the hypothesis will be tested by using Total Asset Turnover ratio (Sangmi, Mohi-ud-Din & Nazir, Tabassum , 2010)
Specifically, the following hypothesis will be tested:
Hypothesis 4: Financial Performance will be positively associated with Management
Efficiency 3.3.1.5 Financial performance and Working Capital Management
Businesses often face the challenge of investing in fixed assets and working capital to achieve optimal results Determining the ideal level of working capital is crucial for profitability This study examines Working Capital Management through the Cash Conversion Cycle, which includes key components such as Days of Sales Outstanding, Days of Inventory on Hand, and Days Payable, to assess their impact on financial performance (Afza, T & Nazir, M., 2009).
Specifically, the following hypothesis will be tested:
Hypothesis 5: Financial Performance will be negatively associated with Days of sales outstanding
Hypothesis 6: Financial Performance will be negatively associated with Days of inventory on hand
Hypothesis 7: Financial Performance will be negatively associated with Number of days of payable.
Sample selection
The study analyzes publicly traded non-financial firms from the Food Manufacturing, ICT, and Supporting industries during the period from 2016 to 2020 To facilitate industry comparisons, we established subsets of companies within these three sectors.
The data utilized in this study is sourced from the audited annual reports available on Vietstock.vn, ensuring reliability, accuracy, and consistency over time Additionally, market value information is also derived from this platform By compiling the financial statements of the selected firms, we have developed a comprehensive database for analysis.
We exclude firms that have too small market share or firms missing data for any indicator determinants
The study analyzed a total of 162 listed firms, excluding those with missing data Additionally, numerous firm-year observations were removed due to incomplete data required for statistical analyses Ultimately, the final sample comprises 162 firms and over 60,000 firm-year observations.
Research design
In line with established methodologies from prior research, we employ a regression model to analyze the impact of various determinant factors on the dependent variable, Financial Performance, while also testing our hypotheses.
The regression model evaluates the impact of Working Capital Management, Capital Adequacy, Management Efficiency, Size, and Liquidity on Financial Performance This equation provides insights into the key factors influencing financial outcomes.
Financial Performance = f (CCC, SIZE, CA, LQ, ME)
➔ ROA = β 1 *DSO + β 2 *DOH + β 3 *DPO + β 4 *SIZE + β 5 *LQ + β 6 *CA + β 7 *ME + ε
Where: β1, β2, β3, β4, β5, β6, β7 = Regression coefficients; ε = Error terms Coefficient are used to measure the sensitivity of the dependent variable (financial performance ROA)
We predict positive coefficients for all Table below shows the measurement of the variables used as proxy indicators for each factor used in our study
Cash Conversion Cycle CCC Days of inventory on hand + Days of sales outstanding –
Number of days of payable Days of sales DSO Average Collection Period
Variable Notation Measurement outstanding = 365/ Receivable turnover
Days of inventory on hand
DOH Average Age of Inventory
Number of days of payable
= 365/Payable turnover Firm size SIZE Natural logarithm of total asset
= (Current asset - inventory)/ Current liability
Capital Adequacy CA Equity to Asset
Management Efficiency ME Total Asset Turnover
= Earnings before interest and tax / Total assets
= Profit before tax/ Total assets
This study focuses on measuring percent changes rather than unit changes between independent variables (xi, factors) and dependent variables (y variable, or financial performance) By utilizing a regression model that takes the logarithm of the variables, the analysis effectively captures percent changes, which is particularly beneficial when working with medium to large datasets.
Data collection
The research paper utilized both primary and secondary data for information gathering, with primary data being specifically collected for the study's objectives Secondary data was sourced from audited annual reports and financial statements available on finance.vietstock.vn, a platform that provides investors and researchers with real-time quotes, financial news, and comprehensive data on Vietnam’s stock market Users can access current quotes, analyze historical data through price charts, splits, and dividends, and apply various technical analysis techniques Additionally, finance.vietstock.vn offers detailed company-specific information, including annual and quarterly financials, key statistics, ratios, and external links for analyst estimates.
4 STATISTICAL ANALYSIS, RESULTS, AND FINDINGS
Statistical analysis results
Descriptive Statistics
The table below shows the descriptive statistics of ratios reflecting impacts of 5 factors on Financial Performance of companies
Industry N Minimum Maximum Mean Std Deviation
Manufacturing Days of inventory on hand 360 0.00 766 82.85 76.67
Number of days of payables 360 0.00 266 29.16 32.62
ICT Days of inventory on hand 201 0.00 686 64.87 63.20
Number of days of payables 201 1 568 64.52 60.49
Supporting Days of inventory on hand 111 14 424 88.55 64.51
Number of days of payables 111 2 194 41.89 30.46
From Table 2 above, there were 672 observations in total which were from 3 industries
In the Food Manufacturing industry, key financial metrics reveal significant insights: the average Days Outstanding Held (DOH) is 82.85 days, Days Sales Outstanding (DSO) is 68.39 days, and Days Payable Outstanding (DPO) stands at 29.16 days, with respective standard deviations of 76.67, 351.79, and 32.62 days The mean Total Assets amount to approximately 3,562,221.36, accompanied by a standard deviation of 9,442,226.34 The Quick Ratio averages 0.6, with a standard deviation of 1.16, while the Equity to Assets ratio is 46.09, reflecting a standard deviation of 52.79 Additionally, the mean Total Asset Turnover is 1.57, with a standard deviation of 0.99, and the Return on Assets (ROA) averages 4.41, with a standard deviation of 12.62.
In the ICT industry, the average Days Outstanding Hours (DOH), Days Sales Outstanding (DSO), and Days Payable Outstanding (DPO) are 64.87 days, 77.39 days, and 64.52 days, respectively, with standard deviations of 63.20, 60.45, and 60.49 days The mean Total Assets amount to 2,819,924.72, accompanied by a substantial standard deviation of 9,613,723.26 Additionally, the average Quick Ratio stands at 1.23, with a standard deviation of 1.76 The Equity to Assets ratio averages 59.06, showing a standard deviation of 21.63 Furthermore, the mean Total Asset Turnover is 1.53, with a standard deviation of 1.08, while the average Return on Assets (ROA) is 5.79, accompanied by a standard deviation of 17.91.
In the Supporting industry, the average Days Outstanding in Hand (DOH), Days Sales Outstanding (DSO), and Days Payable Outstanding (DPO) were 88.55 days, 79.01 days, and 41.89 days, respectively, with standard deviations of 64.51 days, 54.41 days, and 30.46 days The mean Total Assets stood at 1,401,388.01, accompanied by a standard deviation of 2,128,507.40 The average Quick Ratio was 0.53, with a standard deviation of 1.29 Additionally, the mean Equity to Assets ratio was 53.69, with a standard deviation of 20.78, while the mean Total Asset Turnover was 1.39, showing a standard deviation of 0.84 Finally, the mean Return on Assets (ROA) was 4.75, with a standard deviation of 10.58.
Correlation
CCC DOH DSO DPO TOTA
** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2- tailed)
Table 3 illustrates the relationship between Financial Performance, as measured by Return on Assets (ROA), and various factors of Working Capital Management, represented by the Cash Conversion Cycle and its indicators Additionally, it highlights the correlation with Capital Adequacy, indicated by the Equity to Assets ratio.
Efficiency (reflected by Total asset turnover), Liquidity (reflected by the Quick ratio), and Size of the firm (indicated by the Total asset)
CCC DOH DSO DPO TOTAL
Sig (2-tailed) 136 890 388 000 Quick ratio Pearson
** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed)
Table 3: Correlation between Factors and Financial Performance
The analysis reveals that Return on Assets (ROA) exhibits a negative relationship with Cash Conversion Cycle (CCC), Days of Inventory on Hand (DOH), Days Sales Outstanding (DSO), and Days Payable Outstanding (DPO), while showing a positive correlation with Total Assets, Quick Ratio, Equity to Assets, and Total Asset Turnover Most indicators demonstrate low pair correlations (below 0.3), indicating that the model is robust and unlikely to face collinearity issues Notably, Equity to Assets has a moderate correlation with ROA at 0.432**, highlighting its significant impact on financial performance in terms of ROA.
between Cash Conversion Cycle (CCC) and Days Sales Outstanding (DSO) According to Gujarati (2008), a correlation coefficient exceeding 80 indicates potential multicollinearity issues Consequently, since CCC and DSO's correlation surpasses this threshold, it is necessary to eliminate one independent variable from the regression model to address this problem Given that CCC is derived from Days of Inventory Held (DOH), DSO, and Days Payable Outstanding (DPO), we will remove CCC Notably, CCC exhibits a positive relationship with DOH and DSO, with coefficients of 218 and 996, respectively, at a 1% significance level, indicating that as DOH and DSO increase, CCC is also likely to rise.
Regression analysis
Square Std Error of the Estimate
Supporting 1 536 a 287 239 9.2282828 a Predictors: (Constant), Size, Quick ratio, Total asset turnover, Equity to assets, Days of sales outstanding,
Number of days of payables, Days of inventory on hand b Dependent Variable: ROA b
R Square (R²) indicates the extent to which the model accounts for the percentage variation in financial performance, specifically Return on Assets (ROA), through the combined effects of Working Capital Management, Capital Adequacy, Liquidity, Management Efficiency, and Company Size The remaining percentage (100% - R²) represents the influence of other variables not included in the model.
The regression model demonstrates a significant ability to explain financial performance variations, accounting for 54.4% in the Food Manufacturing industry, while only capturing 28.7% in the Supporting industry and a mere 2.4% in the ICT industry.
About Collinearity Statistics, the VIF values of all variables fall within 1 to 5 in both 3 table, indicating that there is no collinearity of variables in the model
B Std Error Beta Tolerance VIF
FOO D M AN UFA CTUR ING i n du s try
Days of inventory on hand
Number of days of payables
Table 5: Coefficients of Food Manufacturing industry
Table 5 indicates that the Size factor significantly influences Financial Performance, with a coefficient of 3.42 and a p-value less than 5% This provides strong evidence in support of Hypothesis 1, which posits that Financial Performance is positively associated with Firm Size.
The Capital Adequacy factor has positive impact on the Financial Performance the Hypothesis 2: Financial Performance will be positively associated with Capital Adequacy
The Liquidity factor shows a negative correlation with Financial Performance, indicated by a coefficient of -0.477 However, the significance level (p-value) exceeds 5%, suggesting that this positive impact is likely coincidental rather than statistically significant Consequently, there is no evidence to support Hypothesis 3, which posits that Financial Performance is positively associated with Liquidity.
The Management Efficiency factor significantly influences Financial Performance, with a coefficient of 3.033 and a p-value of less than 0.5% This provides statistical evidence supporting Hypothesis 4, indicating a positive association between Financial Performance and Management Efficiency.
The analysis of Working Capital Management reveals that Days of Holding (DOH) has a significant negative impact on financial performance, with a coefficient of -0.015 and a significance level below 5% In contrast, Days Sales Outstanding (DSO) shows a negligible negative effect (coefficient = -0.001), while Days Payable Outstanding (DPO) demonstrates a positive influence with a coefficient of 0.035 However, only the negative association between financial performance and DSO supports Hypothesis 5, while there is insufficient evidence to support Hypothesis 7.
B Std Error Beta Tolerance VIF
Days of inventory on hand
Number of days of payables
Table 6: Coefficients of ICT industry
The analysis presented in Table 6 indicates that the Size factor (coefficient = 1.583), Capital Adequacy factor (coefficient = 0.07), Management Efficiency factor (coefficient = 1.236), and Liquidity factor (coefficient = 0.285) all show a positive influence on Financial Performance However, since their significance values exceed 5%, this positive impact is likely random rather than statistically significant.
1, Hypothesis 2, Hypothesis 3, and Hypothesis 4 do not have evidence to support them
The analysis of Working Capital Management reveals that the Days of Holding (DOH) has a negative impact with a coefficient of -0.03, while Days Sales Outstanding (DSO) and Days Payable Outstanding (DPO) show positive impacts with coefficients of 0.008 and 0.001, respectively However, all significant values exceed 5%, indicating that these effects are random rather than statistically significant Consequently, there is insufficient evidence to support Hypotheses 5, 6, and 7.
Standardized Coefficients t Sig Collinearity Statistics
B Std Error Beta Tolerance VIF
SUPPO RTING i nd us try
Days of inventory on hand
Number of days of payables
Table 7: Coefficients of Supporting industry
Table 7 indicates that the Size factor positively influences Financial Performance, with a coefficient of 2.217 and a p-value of less than 5% This provides strong evidence in support of Hypothesis 1, which asserts that Financial Performance is positively correlated with Firm Size.
The Capital Adequacy factor positively influences Financial Performance, with a coefficient of 0.124 and a p-value of less than 5% This provides statistical evidence to support Hypothesis 2, indicating that Financial Performance is positively associated with Capital Adequacy.
The Management Efficiency and Liquidity factors show a positive influence on Financial Performance, with coefficients of 2.099 and 0.135, respectively However, their significant values exceed 5%, indicating that this positive effect is likely random Consequently, there is insufficient evidence to support Hypothesis 4 and Hypothesis 5.
The analysis of Working Capital Management reveals that Days of Inventory on Hand (DOH), Days Sales Outstanding (DSO), and Days Payable Outstanding (DPO) have negative coefficients of -0.038, -0.036, and -0.03, respectively However, only DOH demonstrates a statistically significant value below 5%, indicating its detrimental effect on Financial Performance This finding supports Hypothesis 6 while providing no evidence for Hypotheses 5 and 7.
Days of inventory on hand
Number of days of payable
Capital Adequacy (Equity to assets)
Management Efficiency (Total asset turnover)
Table 8: Cross-industry comparison of factors affecting Financial Performance
A cross-industry analysis is important because the impacts of each factor would be different in different sector
The DOH indicator significantly negatively affects the financial performance of the food manufacturing industry, with a coefficient of -0.015 and a p-value of less than 5% Similarly, it adversely impacts the supporting industry, showing a coefficient of -0.038 and a p-value below 5% In contrast, while the DOH indicator also has a negative coefficient of -0.03 for the ICT industry, the p-value exceeds 5%, indicating that this negative impact is not statistically significant.
Both DSO and DPO appear to have impact on Financial Performance but their significant value is greater than 5% Thus, this impact is not statistically proven
The size factor significantly enhances the financial performance of the food manufacturing industry, with a coefficient of 3.42 and a p-value less than 5% Similarly, the supporting industry also benefits from this size factor, exhibiting a coefficient of 2.217 and a p-value under 5% In contrast, the ICT industry does not experience this positive impact, as indicated by a coefficient of 1.583 and a p-value exceeding 5%.
The Capital Adequacy factor positively influences the Financial Performance (FP) of the Food Manufacturing industry, with a coefficient of 0.154 and a p-value of less than 5% Similarly, it positively affects the Supporting industry, showing a coefficient of 0.124 and a p-value below 5% In contrast, while there is a positive impact on the Financial Performance of the ICT industry, indicated by a coefficient of 0.07, the p-value exceeds 5%, rendering this effect statistically insignificant.
Findings
The thesis presents two types of data analysis: descriptive and inferential Descriptive analysis utilizes measures such as mean, standard deviation, and minimum and maximum values to effectively illustrate the key aspects of the phenomena being studied and provide insights into each relevant variable In contrast, inferential analysis employs Pearson correlation and regression models to conduct a deeper examination of the data.
Descriptive analysis reveals that the Food Manufacturing industry exhibits the highest values for Days of Holding (DOH) and Days Sales Outstanding (DSO), while the Supporting industry records the highest Days Payable Outstanding (DPO) Notably, the Food Manufacturing sector also boasts the largest company, valued at 97,297,251 Additionally, the ICT industry leads in Quick Ratio and Total Asset Turnover, whereas the Supporting industry has the highest Equity to Assets ratio.
According to inferential analysis, the study indicated following result
Working Capital Management, assessed through the Cash Conversion Cycle (CCC), significantly impacts the financial performance of food manufacturing and supporting industries Specifically, an increase in Days of Inventory on Hand (DOH) results in a decline of 0.015 to 0.038 units in financial performance.
Contrary to expectations, there is no statistical evidence indicating that Days Sales Outstanding (DSO), Days Payable Outstanding (DPO), and liquidity significantly affect financial performance This finding suggests that these factors do not play a role in influencing a company's financial outcomes.
The size of a company positively influences financial performance in both the food manufacturing and supporting industries, with a unit increase in size resulting in an increase of 3.42 and 2.217, respectively However, this effect does not extend to the ICT sector.
Capital Adequacy plays a crucial role in enhancing the Financial Performance of Food Manufacturing and Supporting industries, demonstrating that a unit increase in Capital Adequacy results in an increase of 0.154 and 0.124 in their financial performance, respectively However, this impact is not observed in the ICT sector.
Management Efficiency positively influences the Food Manufacturing industry, resulting in a notable increase of 3.033 in Financial Performance with each unit increase in efficiency However, this effect is not observed in the ICT and Supporting industries, where no impact on financial performance is recorded.
Implication
The impacts of different factors are different on different industries; thus, the managers should pay different focuses in different industries
The study emphasizes the importance of a well-managed inventory policy in Food Manufacturing and Supporting industries Implementing an effective stock administration system is crucial to prevent excess inventory, which can lead to wasted investment By reducing the Days of Inventory on Hand, managers can significantly enhance the firm's profitability, while neglecting this aspect may negatively impact financial performance.
Secondly, the study suggested that the bigger firms are at a more noteworthy benefit as they can utilize the full use of their resources for produce profit
A higher total asset turnover indicates that a company is generating significant sales, which in turn contributes to increased profits Therefore, enhancing management efficiency is essential for improving financial performance in the food manufacturing industry.
An increase in the capital-to-assets ratio signifies improved financial performance for food manufacturing and supporting industries, highlighting the essential role of capital in driving operational activities and generating operating income alongside other investment endeavors.
Finally, to predict the Financial Performance of companies,
• In the FM, investment analysts could use DOH, Total Asset, Equity to Total Asset, and Total Asset Turnover to estimate
• In the Supporting, investment analysts could use DOH, Equity to Total Asset, and Total Asset to estimate.
Conclusion
The study has investigated the relationship between working capital management firms
‘financial performance for 162 firms listed from 3 industries in Viet Nam Data have been analyzed by applying both descriptive and inferential statistics for the time period of
The study indicates that Days of Inventory on Hand (DOH) negatively impacts Return on Assets (ROA), suggesting that companies can enhance profitability by reducing inventory days While Days Sales Outstanding (DSO) and Days Payable Outstanding (DPO) show positive and negative relationships with ROA, these associations are insignificant, indicating they do not influence financial performance in the three industries examined Furthermore, the research highlights that Total Assets and Equity to Assets have a significant positive effect on the financial performance of the Food Manufacturing and Supporting industries Ultimately, the findings conclude that both Size and Capital Adequacy are critical factors affecting financial performance, with Management Efficiency positively influencing the Food Manufacturing industry through improved Total Asset turnover.
This study focuses exclusively on the financial factors influencing the financial performance of companies, without quantifying social and environmental effects By analyzing comparative cross-industry evidence, we identify high-performing companies and provide valuable insights for investors and shareholders This thesis serves as a reliable reference for financial analysts and investors looking to make informed decisions in sectors such as ICT, food manufacturing, and supporting industries, ultimately aiding in the creation of a profitable investment portfolio.
Limits of study
There should be highlight of problems related to the estimation of the model The thesis has certain limits
Due to time and financial constraints, the analysis was unable to include the anticipated number of financial reports, which may result in a misrepresentation of the current market situation.
This study is unable to perform the proposed analysis due to the limited data provided by the source finance.vietstock.vn, which lacks a sufficient number of historical observations for effective analysis.
The data collected for this study spans a period of five years, which, while not extensive, provides valuable insights into the relevance of three specific industries.
Future directions
Further studies are necessary to conduct a comprehensive analysis over an extended timeframe Additionally, a similar investigation should be carried out on the working capital management and financial performance of three industries, incorporating a broader range of financial metrics.
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INTERNATIONAL SCHOOL Independence – Freedom - Happiness
EXPLANATORY REPORT ON CHANGES / ADDITIONS BASED ON THE DECISION OF GRADUATION THESIS COMMITTEE
FOR UNDERGRADUATE PROGRAMS WITH DEGREE AWARDED BY
VIETNAM NATIONAL UNIVERSITY, HANOI Student’s full name: Cao Khanh Linh
Major: Accounting, Analyzing and Auditing
On June 18, 2021, VNU-IS issued decision no 547 QĐ/KQT to establish a Graduation Thesis Committee for Bachelor programs at Vietnam National University, Hanoi, leading to the defense and subsequent modifications of the thesis in specific sections.
No Change/Addition Suggestions by the Committee Detailed Changes/ Additions Page
Testing factors affecting financial performance and impact of Working capital Management under cross- industry perspective in Viet Nam
Adding definition of working capital and working capital management
Working capital represents the difference between a company's current assets—like cash, accounts receivable, and inventories of raw materials and finished goods—and its current liabilities, such as accounts payable.
5 operation of the company with the best utilization of business current assets and liabilities
When reviewing factors affecting financial performance,
Identifying working capital as a factor
Working capital is the lifeblood of any business, significantly influencing overall performance According to Hampton (1989), effective working capital policy involves two key decisions: determining the right level of investment in current assets and selecting suitable financing methods Efficient working capital management is crucial for organizational success, as it plays a vital role in maintaining liquidity, solvency, and profitability Regardless of size or industry, every organization—whether profit-oriented or not—requires adequate working capital and effective management Insufficient working capital can lead to financial insolvency, jeopardizing the company's stability and operations.