The Effect of Profitability, Board Size, Woman on Boards, and Political Connection on Financial Distress Conditions

Abstract

This research proves the consistency of Agency Theory as a solution to explain the role of the influence of profitability, board size, woman on board, which is divided into two, namely woman on board of commissioner and woman on board of directors, as well as political connections to financial distress. Panel data from these variables were obtained from companies listed in LQ-45 in 2017–2021 which were then analyzed with a quantitative approach through the regression analysis of Ordinary Least Squares, Fixed Effects, Random Effects, and Robust, which was carried out simultaneously. The results of this analysis have a higher level of accuracy compared to partial testing. The first finding explains that the Profitability Ratio has a negative effect on financial distress, the second finding explains that board size has a positive effect on financial distress, the third finding explains that woman on board of commissioner has no effects on financial distress, however, the fourth finding explains that woman on board of director has a positive effect on financial distress, while the fifth finding explains the political connection has no positive effect to financial distress. Panel data-based research through simultaneous testing can be considered for principals in appointing agents to manage the company. Simultaneous analysis of panel data is a new breakthrough in research testing with more detailed results.

Keywords:

• Panel data
• simultaneous testing
• agency theory
• financial distress

JEL Classification:

• G02
• G32
• M1
• Z1
• G34

PUBLIC INTEREST STATEMENT

Entity sustainability is the main thing that is always the basis for determining the direction of policy and management of an entity, sustainability, or going concern is the main basis contained in the conceptual framework of financial reporting. However, maintaining an entity, especially in business activities is not an easy thing, because the entity will always be faced with the risk of financial distress.

1. Introduction

The importance of this study is to understand financial distress at the stage of declining financial conditions that occur in companies before the occurrence of bankruptcy or liquidation. A company can be categorized as experiencing financial distress if the company shows negative numbers on operating profit, net income, and book value of equity, and the company merges. Financial distress is a company that tends to experience liquidity difficulties as indicated by the company’s ability to decrease in fulfilling its obligations to creditors. Financial distress occurs when the company fails or is unable to meet the debtor’s obligations due to lack and insufficient funds to run or continue its business. The financial distress cycle in the company covers the initial period of declining performance to the lowest point and then the recovery phase.

Entity sustainability is one of the main things that has always been the basis for determining the direction of policies and management of an entity (Mensah & Ricart Casadevall, 2019; Asyik et al., 2022; Kalbuana et al., 2021; Tjaraka et al., 2019). In accounting, sustainability or going concern is the main basis contained in the conceptual framework of financial reporting (Gandhi et al., 2019; Sudaryanto et al., 2022; Utari et al., 2021). This shows that the survival of an entity is important. The survival of an entity is a state in which an entity can continue to show its existence in the field it is engaged in (Aliyyah et al., 2021; Jannah et al., 2020; Prasetio et al., 2021). However, maintaining an entity, especially in business activities, is not an easy thing, because the entity will always be faced with the risk of financial distress (Setiorini et al., 2022; B. Endarto et al., 2021; Indrawati et al., 2021).

The financial crisis is a stage of deterioration of the financial condition of an enterprise preceding liquidation or bankruptcy (Silalahi et al., 2018; Prasetyo, Aliyyah, Rusdiyanto, Utari et al., 2021; Utari, Iswoyo, et al., 2021). The ups and downs of a company are natural (N Kalbuana et al., 2021; Abadi et al., 2021; B Endarto et al., 2021); however, conditions that cause concern to investors and creditors if the company experiences financial distress that can lead to bankruptcy (Elloumi & Gueyié, 2001; Aliyyah, Prasetyo, et al., 2021b; Prasetyo, Aliyyah, Rusdiyanto, Kalbuana et al., 2021b).

Economic conditions from 2020 to 2021 in general cannot be called impressive either, or specifically for the capital market (Indrawati et al., 2021; N. Kalbuana et al., 2021; Rusdiyanto et al., 2021). The main mood and especially the trigger for the capital market outage in 2020 is none other than the emergence of the new Covid-19 virus, which has spread widely and finally turned into a global pandemic (Hastomo et al., 2021; N Kalbuana et al., 2021; Prasetyo, Aliyyah, Rusdiyanto, Kalbuana et al., 2021b). Indonesia is not spared from this pandemic, in real terms and in the financial sector. This condition poses a high risk that the company will experience financial difficulties, it can even result in the company experiencing bankruptcy. Research (Nasution et al., 2020; Prasetyo, Aliyyah, Rusdiyanto, Kalbuana et al., 2021b, 2021b) one of the adverse impacts of the COVID-19 pandemic on the economy is investment that makes people very careful in buying goods and even investing.

Market projections are also strongly influenced by the pandemic (Susanto et al., 2021). Supply chain uncertainty and market assumptions make investors less likely to invest (Luwihono et al., 2021; I; Prasetyo, Aliyyah, Rusdiyanto, Kalbuana et al., 2021b; Indra Prasetyo, Aliyyah, Rusdiyanto, Tjaraka, Kalbuana et al., 2021). If investors still want to invest in a company, it is wise to review financial statements (I Prasetyo, Aliyyah, Rusdiyanto, Utari, Kalbuana et al., 2021) so that they can research which companies are experiencing a decline in performance that could potentially experience financial distress.

The object of this study is LQ 45 companies because currently investors in Indonesia tend to invest in the group of stocks that are included in the calculation of the LQ 45 index, because LQ 45 shares are stocks that are included in the top 45 companies in Indonesia (Indonesia Stock Exchange, 2022; Luwihono et al., 2021; Shabbir et al., 2021). Large and well-known companies, companies that often make transactions to attract investors to invest, and the stocks owned have a high level of liquidity and market capitalization.

There are several factors that can affect financial distress. These factors include profitability, board size, woman on board of commissioner, woman on board of directors, and political connections. The profitability ratio describes an accounting calculation aimed at looking at the company’s ability to make gains at a certain time of time (Aliyyah et al., 2021; Prabowo et al., 2020; Susanto et al., 2021). This calculation can show the amount of efficiency and management power in the industry judging from the amount of margin obtained from trade and investment income made by the industry (Prasetio et al., 2021; Prabowo et al., 2020; Susanto et al., 2021). If the profitability ratio is large, the profit generated is large, and the company can carry out industrial activities properly in asset management so that it can overcome its liabilities. The opposite is true if the profitability ratio is low, the level of profit generated is low, making it difficult for the company to carry out industrial activities and if it is not treated until the industry will face the danger of bankruptcy (Gabriellita & Simbolon, 2021; Juanamasta et al., 2019).

Return on assets, or ROA, is a ratio that measures how efficiently a company is in managing its assets to create profits throughout one period. If the low ROA ratio displays the expertise of industrial assets less productive in generating profits, and conditions like this can make it difficult for industry finances to obtain internal funding for investment so that it can lead to the formation of a probability of bankruptcy (Islamiyatun et al., 2021; Silalahi et al., 2018).

Board size or number of commissioners is a company governance measure needed to reduce agency problems with owners and managers. The composition of the board of commissioners must be as simple as possible so as to maximize efficient, appropriate, and fast decision-making. The role of the Board of Commissioners is to ensure that the Board of Directors’ policies are carried out effectively. So that the end product is in shareholders’ best interests, the board of commissioners should oversee the board of directors’ efforts (Wardhani, 2007; Yuhertiana et al., 2020, 2022).

To study the proximity of company financial results in the gender diversity of the board of commissioners, further studies of companies in Indonesia are needed, taking into account the differences in company characteristics and culture in Indonesia (I Prasetyo, Aliyyah, Rusdiyanto, Kalbuana et al., 2021b). In this regard, the Global Gender Gap Index Report 2020 reports that Indonesia recorded the largest share when calculating women’s participation in senior and leadership positions (World Economic Forum, 2019; Yuhertiana, Izaak, et al., 2020; Yuhertiana, Rochmoeljati, et al., 2020). Female CEOs of manufacturing companies in Thailpand have a detrimental effect on the financial performance of enterprises, according to (Singhathep & Pholphirul, 2018; Zulvina et al., 2021). The results of the study (Salloum et al., 2016; Yuhertiana, Bastian, et al., 2019; Yuhertiana, Patrioty, et al., 2019) show that the presence of women in management in Lebanon has a negative impact on the financial performances of companies which can lead to financial difficulties. Additionally, the majority of the women in the sample who were being studied were married. Impactfully, their priorities become different, because they prioritize family over career development

A female director is a woman who is appointed as a director in the company’s board. Women tend to be less tolerant of self-serving behavior and less focused on their own needs (Krishnan & Parsons, 2008; Priono et al., 2019; Yuhertiana, Purwanugraha, et al., 2019). Women are generally more risk-averse and more cautious than men in decision-making. Women are also more assertive in their efforts to improve the quality of company profits because of their sensitivity to the risk of reputation loss and lawsuits (Gull et al., 2018; Rahma et al., 2016; Tatiana & Yuhertiana, 2014).

Political connections refer to the close ties between companies and political parties, senior government officials, and politicians. In the literature, there are two competing reasons about the consequences of political networks that can result in poor industrial governance and can increase financing of agencies because of the attitude of directors wanting to get better wages. Companies with politically connected boards of directors experienced sacrifices such as changing bribes or campaign funds for treatment that benefited the state. The advantages that can be obtained are having greater access to government financing, increasing the procurement of government contracts, protection from market competition, and favorable regulatory treatment (W.Carney et al., 2020; Rahma et al., 2016; Tatiana & Yuhertiana, 2014). Not only is there an advantage of a political network, it also has disadvantages, including the existence of incentives for directors to take over profits. Another drawback is that there are costs arising from affiliation with networks allied with powerful political leaders are patron–client relationships (W.Carney et al., 2020; Yuhertiana, 2011a, 2011b).

Financial distress is a situation where there are doubts about the company’s existence in the future due to financial difficulties. (Platt & Platt, 2020; Ahmed et al., 2022; Maulidi et al., 2022) define financial distress as the final process of falling productivity before facing bankruptcy. Financial distress happens when a company’s debts surpass its profit, size, and assets. Financial distress, which is quite disturbing to the company’s operational activities, is something that must be immediately watched out for and anticipated (Budi Endarto et al., 2021; Nuswantara, 2022; Nuswantara & Maulidi, 2021). The state of financial distress is a situation that is not desired by various parties. If there is financial distress, investors and creditors tend to be cautious in carrying out investments or distributing loans to the company. Stakeholders tend to react negatively to this state of affairs. Therefore, the management of the company must immediately take action to overcome the problem of financial distress and prevent bankruptcy (Murni, 2018; IRIANI et al., 2021; Nuswantara et al., 2018).

This study aims to examine and evaluate the Effect of Profitability, Board Size, Woman on Boards, and Political Connections on Financial Distress Conditions. Motivation in the study of Financial Distress Conditions is an important issue that must be understood as a policymaker in the field of financial accounting to provide the following justification or motivation: This study is supported by agency theory to obtain empirical evidence about the Effect of Profitability, Board Size, Woman on Boards, and Political Connections in Financial Distress Conditions. The sample of this study used the masculinity of male CEOs associated with leverage and research and development costs. The sample of this study uses LQ45 companies listed on the Indonesian stock exchange from 2017 to 2021.

2. Literature review and hypothesis development

2.1. Agency theory

Agency Theory was introduced by (Jensen & Meckling, 1976; Dian Anita Nuswantara & Maulidi, 2017). This theory deals with the contractual relationship between the members of an organization by using a model that focuses on two principal individuals and an agent, describing the bond between the principal and the agent. This theory states that the agent will behave self-interest which would probably be contrary to the interests of the principal. The company’s performance by minimizing costs and increasing efficiency is what is desired in the perceptive of this theory. The principal will delegate the work to the agent, and the agent is expected to act in the interests of the owner. Agency problems will arise if the interests of the principal and the agent are not in the same direction and the principal is ill-informed to accurately assess the agent’s behavior. Insightful methods for solving research problems can be found in the function of agency theory.

Agency costs are of three types: residual costs, bonding costs, and monitoring costs (Jensen & Meckling, 1976; Adi et al., 2022; Sudaryanto et al., 2021). Agency theory uses three assumptions of human nature, namely: generally selfish, limited in the future thinking and risk-averse (Eisenhardt, 1989; Hanim et al., 2019; Sudaryanto et al., 2020).

2.2. Research conceptual framework

The conceptual framework explains dependent and independent variables. Research places Profitability, Board of Size, Woman on Board of Commissioners, Woman on Board of Directors, Political Connection as independent variable, Financial Distress as dependent variable (Eisenhardt, 1989; Sudaryanto et al., 2019; Putri & Sudaryanto, 2018). Following from the above, the research’s conceptual framework can be defined as follows as shown in Figure 1:

Figure 1. Research conceptual framework.

2.3. Research hypothesis

2.3.1. Profitability ratio has a positive influence on financial distress

The profitability ratio calculates the performance of an enterprise in order to realize profit. At the level of assets, capital and sales. Profitability ratio is the profit obtained during one accounting period, if the profit obtained by the company is high, it can be used as an option by investors to invest in the company (Wiguna & Yusuf, 2019; N F Asyik et al., 2022; Wahidahwati & Asyik, 2022). The company’s ability to produce good financial performance will provide complete information so that it will gain high trust for its stakeholders. The company is able to fulfill the wishes of investors and creditors (Prasetio et al., 2021; Dewianawati & Asyik, 2021; Karimuna et al., 2021).

Profitability ratio is a method used by managers to measure management effectiveness and is used to recognize the size of the level of profit obtained from sales or investments (Abadi et al., 2021). Profitability for financial distress due to large profits can attract investors to make investments in the company so that it can be free from financial distress. Companies that have large profits mean that the company is less likely to experience financial difficulties.

Return On Asset is a proxy of the profitability ratio in this study, Return On Asset reveals the company’s expertise in returning assets that have been invested by investors and business owners (I Prasetyo, Aliyyah, Rusdiyanto, Kalbuana et al., 2021b; Sadimantara et al., 2019; Wijaya et al., 2020). The higher the Return On Assets of a company will make the stock price positive, and the entity will inform what activities are being carried out in order to make the stock price good (Brigham & Houston, 2019; Islamiyatun et al., 2021). By combining all the arguments described above, the hypotheses proposed in this research are:

H₁ = Profitability Ratio positively affects Financial Distress

2.3.2. Board size has a positive influence on financial distress

According to Articles of Association, the board of commissioners is the company’s body responsible for general and/or specific monitoring and for making recommendations to the board of directors in accordance with Law No. 40 of 2007 respecting Limited Liability Companies (Agustina & Anwar, 2021). The Board of Commissioners directs and controls the boards of directors in the management and representation of the company.

The size of the board of directors as measured through a larger number of board of commissioners at the organisation may be ineffective in carrying out its supervisory functions that can result in the performance of the board of directors decreasing. So, it is likely that the business will have financial distress (Agustina & Anwar, 2021). Significant research findings in a positive direction are supported by previous studies conducted (M Nasution, 2007). The results of the study explained that the number of commissioners’ boards has a positive influence on the possibility of financial distress. By combining all the arguments described above, the hypotheses proposed in this research are:

H₂ = Board size that positively affects Financial Distress

2.3.3. Woman on board of commissioners influences financial distress positively

The board of commissioners has a position to monitor or supervise and discipline upper management in a company (Terjesen et al., 2020). The characteristics of the board of commissioners is an interesting topic to be studied in their influence on financial distress. One of them is the presence of women in the ranks of the boards of commissioners.

Female leaders tend to be more cautious and risk-resisting compared to male leaders (Kristanti & Isynuwardhana, 2018). This will affect the concept of high risk high return, with the number of female leaders in the company will reduce the possibility of risk that will occur but with little risk taken, the company will also be small in getting returns. With a small return, it can also trigger financial distress. Research that has been carried out by (Kristanti & Isynuwardhana, 2018) and (Salloum et al., 2016) shows that the presence of women in the leadership ranks of a company has a significant positive correlation to financial distress. Based on the theory that has been presented, a hypothesis is obtained. By combining all the arguments described above, the hypotheses proposed in this research are:

H₃ = Woman on Board of Commissioner berpengaruh positif terhadap Financial Distress

2.3.4. Woman on board of directors influences financial distress positively

Woman on Board of Directors is the existence of women on boards in a company. Women’s council studies have been carried out several times by previous researchers, the results of studies conducted (Eynon, Hill et al., 1997a; Zulvina et al., 2021) which showed that women regard moral reasoning more highly than men.

Women are generally more cautious and risk-averse attitude when compared to men in decision-making. Research by (Singhathep & Pholphirul, 2018) on Thai enterprises in the industrial sector found that having a woman as CEO had a detrimental effect on the bottom line. This can result in financial distress. In Lebanon, having women in management roles is negatively connected with financial success, according to studies (Salloum et al., 2016).

Research that has been carried out by (Kristanti & Isynuwardhana, 2018) shows that the existence of women in the leadership ranks of a company has a significant positive correlation to financial distress. Based on the theory that has been presented, a hypothesis is obtained. By combining all the arguments described above, the hypotheses proposed in this research are:

H₄ = Woman on Board of Directors positively affects Financial Distress

2.3.5. Political connection influences financial distress positively

Companies that have political connections are companies that under exclusive rules have political ties or seek connections with the government (Sulistyowati & Prabowo, 2020). A company is defined as being politically connected if one of the company’s owners, board of commissioners or board of directors has served or is an official in the government, a military official, or a member of parliament during the research period (Supiandi, 2019). This study uses dummy variables to measure political connections, namely, the value of 1 for companies that are proven to have political connections, and the value of 0 for companies that do not have political connections.

The results of the study penelitian (Wulandari & Rahardja, 2012) and (Nugrahanti et al., 2020) concluded that the sutau companies found to have political connections were found to have low performance when compared to companies that did not have political connections, other research results were found by (AT Kristanto, 2019) this political relationship has a positive and significant effect on financial distress, meaning that the higher the political connection of a company, the lower the performance, which can result in on the possibility of financial distress getting worse. By combining all the arguments described above, the hypotheses proposed in this research are as follows:

H5 = Political Connection has a positive effect on Financial Distress

3. Research methods

3.1. Types and approaches to research

The research takes a quantitative approach, offering empirical proofs for how to decipher numerical data. This study aims to provide empirical evidence of the influence of Profitability, Board Size, Woman on Board of Commissioner, Woman on Board of Directors, and Political Connections to Financial Distress. The research approach uses explanatory research with population and research samples using companies registered in LQ 45 for the 2017–2021 period. The sample consisted of 45 companies but there were 7 companies that suffered losses during the research period and 9 companies that issued financial statements using currencies other than rupiah so that 29 companies were obtained. The data in this study used panel data in the form of annual reports of companies listed on LQ 45 for the 2017–2021 period. The Indonesia Stock Exchange’s official website was used to collect the research data (www.idx.co.id).

This research employed a panel data analysis approach involving the Regression Ordinary Least Squares, Fixed Effects, Random Effects, and Robust model, which was carried out simultaneously with the help of Stata Software. This analyst model is one of the regression completeness technique with a great deal of leeway in the kinds of theoretical, conceptual, and empirical studies that can be conducted on the variables of interest. The results of the analysis on the four models are presented in the form of a table so that information with a higher level of accuracy is obtained compared to partial testing so that it makes it easier to determine hypotheses.

3.2. Operational definitions and measurements

Profitability, Board Size, Woman on Board of Commissioners, Woman on Board of Directors, Political Connection is an independent variable, while Financial Distress is a dependent variable.

3.2.1. Independent variables

The term-dependent variable is defined as a variable that can be influenced by other variables (Nur Fadjrih Asyik et al., 2022). This study used the variables Profitability, Board Size, Woman on Board of Commissioners, Woman on Board of Directors, Political Connection as independent variables:

3.2.1.1. Profitability ratio

Profitability ratio is a method used by managers to measure the effectiveness of management and recognize the size of the level of profit obtained from sales or investments. Profitability ratios measured by ROA are used as a tool to assess a company’s financial performance (Brigham & Houston, 2019). The profitability ratio is proxied with the Return On Asset calculated according to the formula:

$\mathit{\text{ROA}}=\frac{\mathit{\text{net profit}}}{\mathit{\text{total Assets}}}$

3.2.1.2. Board size

The Board of Commissioners directs and controls the board of directors in the management and representation of the corporation/company. A larger number of boards of commissioners at the organisation may be ineffective in carrying out its supervisory functions, which can result in the performance of the board of directors decreasing. In this study, the board size was measured based on the number of boards of commissioners in the company (Chandra, marcella octavia, 2015) which was calculated based on the formula:

Board size = Σ Board of Commissioners.

3.2.1.3. Woman on board of commissioner

The Board of Commissioners has a position to monitor or supervise and discipline the upper managements in a company. The characteristics of the board of commissioners is an interesting topic of research into their effect on financial distress. One of them is the existence of women in the ranks of board of commissioners (Terjesen et al., 2020). The female board of commissioner variables in this study are formulated with a formula:

$\mathit{\text{WOMC}}=\frac{\mathit{\text{Total of Female Members of the Board of Commissioners}}}{\mathit{\text{Total of Members of the Board of Commissioners}}}$

3.2.1.4. Woman on board of director

Female representation on a company’s boards of directors is what is meant by the term “woman board of directors.” Investigations (Eynon, Hills et al., 1997b), showed that women had a higher moral reasoning value than men, and these findings have been replicated in several studies of all-female boards of directors (Darmadi, 2013; Zulvina et al., 2021). In this study, the Female Board of Directors is formulated with a formula:

$\mathit{\text{WOMD}}=\frac{\mathit{\text{Total of Female Members of the Board of Directors}}}{\mathit{\text{Total of Members of the Board of Directors}}}$

3.2.1.5. Political connection

Companies that have political connections are companies that under exclusive rules have political ties or seek connections with the government or politicians (Sulistyowati & Prabowo, 2020). A company is defined as being politically connected if one of the company’s owners, board of commissioners or board of directors has served or is an official in the government, a military official, or a member of parliament during the research period (Supiandi,). This study uses dummy variables to measure political connections, namely, the value of 1 for companies that are proven to have political connections, and the value of 0 for companies that do not have political connections.

3.2.2. Variable dependent

Factors whose values can be affected by other variables called dependent variables (Tjaraka et al., 2019). Variable dependence in the study used Financial Distress. Financial distress is a situation where there are doubts about the company’s existence in the future due to financial difficulties. (Platt & Platt, 2020) define financial distress as the final process of falling productivity before facing bankruptcy. Financial distress happens when a company’s debts surpass its assets, size, and profit. Small cash flow prevents the industry from maximizing industrial operations, reducing profits, and threatening its survival (Siahaan et al.,). The financial distress in this study is formulated with the formula:

$\mathit{\text{DER}}=\frac{\mathit{\text{Total Liability}}}{\mathit{\text{Total Equity}}}$

3.3. Data analysis techniques

After the step of choosing and gathering research data, the data testing procedure includes research data analysis. The basic definition of data analysis is the estimation of the size of the quantitative impact of a change in one event on another, as well as the prediction or estimation of additional events.

3.3.1. Descriptive statistics

It is hoped that this descriptive statistical data will obtain an overview of the object of research by analytical data, without analyzing from the data of the variables Profitability, Board Size, Woman on Board of Commissioners, Woman on Board of Directors, Political Connection, and variable Financial Distress.

3.3.2. Testing Pearson correlations

Testing Pearson correlation is applied to evaluate the relation between dependent and independent variables under the assumption that Pearson correlations have a normal distribution. Correlation testing results in positive (+) or negative (-) number. If the value of the correlation is (+) positive, which means that the relationship is unidirectional. Unidirectional shows when the independent variables are large, which is followed by the greater the magnitude of the dependent variable. If the correlation value is negative, the relationship is not unidirectional at a time when the independent variables are big/large and the dependent variables get small, Pearson’s correlation formulation:

$r_{\mathit{\text{xy}}}=\frac{n\sum \mathit{\text{XY}}-(\sum X)(\sum Y)}{\sqrt{\{n\sum X^2-(\sum X{)}^2\}\{n\sum Y^2-(\sum Y{)}^2\}}}$

Information:

Table

r	=	Correlation value
X	=	Variable X
Y	=	Variable Y

3.3.3. Model regression research

Using regression analysis, we may examine how strongly two variables are related to one another. The goal of regression analysis is to estimate how much a value of a dependent variable (X) will shift for a given change in an independent variable (Y). Regression analysis of panel data is used in this research method. Panel data is called data pool, longitudinal data, and micropanel data. Profitability, Board Size, Woman on Board of Commissioners, Woman on Board of Directors, and Political Connections on Financial Distress were analyzed using regression analysis of panel data. The following applications of the equation model produced from the specified independent and dependent variables and their interrelationships:

(1) $\mathrm{F}{\mathrm{D}}_{\mathrm{i},\mathrm{t}}= {\beta }_0+ {\beta }_1\mathrm{RO}{\mathrm{A}}_{\mathrm{i},\mathrm{t}},+ {\beta }_2\mathrm{B}{\mathrm{Z}}_{\mathrm{i},\mathrm{t}}+ {\beta }_3\mathrm{WOM}{\mathrm{C}}_{\mathrm{i},\mathrm{t}},+ {\beta }_4\mathrm{WOM}{\mathrm{D}}_{\mathrm{i},\mathrm{t}}+ {\beta }_5\mathrm{C}{\mathrm{P}}_{\mathrm{i},\mathrm{t}},+ \epsilon$(1)

To explain from the variable model the Effects of Profitability, Board Size, Woman on Boards of Commissioner, Woman on Board of Directors, Political Connection To Financial Distress, it can be explained as follows in Table 1:

Table 1. Description of variable

Data		Variable—Description
i	=	Data cross-section company
t	=	Data time series company
ROA	=	Profitabilitas
BZ	=	Board Size
WOMC	=	Woman on Board of Commissioner
WOMD	=	Woman on Board of Director
PC	=	Political Connection
FD	=	Financial Distress
α	=	Constant
β1, β2, β3, β4, β5	=	Variable regression coeff. FD, ROA, BZ, WOMC, WOMD, PC
є	=	Error

4. Results and discussion

4.1. Descriptive Statistics

The descriptive statistics results can be provided as a mean, maximum, minimum, and standard deviation of a sample of companies. The presentation of the data based on a sample of companies registered in the LQ-45 period 2017–2021 can be seen in the below table 2 :

Table 2. Descriptive statistics

Variables	Obs	Mean	Std. Dev.	Min.	Max.	p1.	p99.	Skew.	Kurt.
FD	145	2.257	2.759	.144	16.079	.155	15.308	2.461	10.502
ROA	145	.085	.080	.001	.467	.003	.370	2.036	8.198
BZ	145	5.959	2.048	300	120	300	100	.402	2.671
WOMC	145	.081	.116	000	.429	000	.429	1.168	3.261
WOMD	145	.124	.179	000	.667	000	.667	1.788	5.469
PC	145	.897	.306	000	100	000	100	−2.604	7.782

From the above output table, we can see that the number of observations (N) is 145, out of these 145 observations the value of Financial Distress (minimum) is .144, and the value of Financial Distress (maximum) is 16,079. The mean value of 145 observations is 2,257 with a stand. dev. of 2,759, the Profitability value (minimum) is .001, and value (maximum) is .467. The mean value of 145 observations is .085 with a stand. deviation of .08, the Board of Size value (minimum) is 300, and the Board of Size value (maximum) is 120. The mean value of 145 observations is 5,959 and the amount of standard deviation of 2,048, the Value of Woman on Board of Commissioners (minimum) is 000, and the Woman on Board of Commissioners (maximum) is .429. The mean value of 145 observations is .081 with a stand. deviation of .116, the Value of Woman on Board of Directors (minimum) is 000, and the value of Woman on Board of Directors (maximum) is .667. The mean value of 145 observations is .124 with a stand. deviation of .179, the Political Connection value (minimum) is 000, and the Political Connection value (maximum) is 1. The mean value of 145 observations is .897 with a stand. deviation of .306.

4.2. Pearson correlation test

Pearson's correlation test measures the strength of the relationship between the Effects of Profitability, Board Size, Woman on Boards of Commissioners, Woman on Board of Directors, Political Connections To Financial Distress. If the r value from Pearson correlation test is greater than 0.05 (5%), it indicates a significant relationship with the independent variables; if it is less than 0.05 (5%), it indicates that the Effects of Profitability, Board Size, Woman on Boards of Commissioners, Woman on Board of Directors, and Political Connections to Financial Distress are not significantly related as shown in Table 3.

Table 3. Test of Pearson correlation

Variable	(1)	(2)	(3)	(4)	(5)	(6)
(1) FD	1.000
(2) ROA	−0.369	1.000
	(0.000)
(3) BZ	0.288	−0.259	1.000
	(0.000)	(0.002)
(4) WOMC	−0.060	0.121	0.204	1.000
	(0.477)	(0.147)	(0.014)
(5) WOMD	−0.022	0.422	−0.260	−0.108	1.000
	(0.791)	(0.000)	(0.002)	(0.198)
(6) PC	0.202	0.042	0.237	−0.007	0.114	1.000
	(0.015)	(0.615)	(0.004)	(0.936)	(0.173)
(1) FD	1.000
(2) ROA	−0.369*	1.000
(3) BZ	0.288*	−0.259*	1.000
(4) WOMC	−0.060	0.121	0.204	1.000
(5) WOMD	−0.022	0.422*	−0.260*	−0.108	1.000
(6) PC	0.202	0.042	0.237*	−0.007	0.114	1.000

*** p < 0.01, ** p < 0.05, * p < 0.1

Based on the table, variables Financial Distress, Profitability, Board Size, Woman on Board of Commissioners, Woman on Board of Directors, Political Connection have values above 0.05 (5%). All of these variables have thus been declared to be appropriate for use in model validation. Values greater than 0.05 (5%) can be rationalized by the aforementioned reliability test outcomes. This demonstrates that, if tested, all of the variables in use yield the same results.

4.3. Testing the goodness of fit model

(Asyik et al., 2022) stated testing hypotheses are important in research since it helps to establish how scientific the study was. Based on four Regression tests of Ordinary Least Squares, Fixed Effects, Random Effects, and Robustness, the following outputs are used to determine the scientific viability of the model as shown in Table 4:

Table 4. Testing the goodness-of-fit model

	(Model 1)	(Model 2)	(Model 3)	(Model 4)
VARIABLES	OLS	Fixed Effects	Random Effects	Robust
ROA	−13.617***	−13.833***	−13.617***	−13.617***
	(2.959)	(3.038)	(2.959)	(3.553)
	0.000	0.000	0.000	0.000
BZ	.273**	.273**	.273**	.273***
	(.113)	(.114)	(.113)	(.098)
	0.017	0.018	0.016	0.006
WOMC	−.789	−.767	−.789	−.789
	(1.859)	(1.886)	(1.859)	(1.337)
	0.672	0.685	0.671	0.556
WOMD	2.716**	2.804**	2.716**	2.716**
	(1.312)	(1.349)	(1.312)	(1.088)
	0.040	0.040	0.039	0.014
PC	1.36*	1.357*	1.36*	1.36***
	(.705)	(.715)	(.705)	(.33)
	0.056	0.060	0.054	0.000
Constant	.305	.314	.305	.305
	(.865)	(.877)	(.865)	(.594)
Observations	145	145	145	145
R-squared	.232	.233		.232
Number of YEAR		5	5
Country FE		YES
Country RE			YES

Standard errors in parentheses *** p < 0.01, ** p < 0.05, and * p < 0.1

4.4. Discussion and results research

4.4.1. Profitability ratio influences financial distress positively

Profitability Ratio shows that the resulting negative coefficient estimation does not match the null hypothesis. The T-test explained that the Profitability Ratio had a negative and significant effect on Financial Distress at the p-value significant level of 0.000 ≤ 0.05 (5%) on the four models (OLS, FE, RE, and Robust). The results of empirical testing prove that the higher the profitability ratio has an impact on reducing Financial Distress, and otherwise the lower the profitability ratio has an impact on increasing Financial Distress. These empirical findings do not support the hypothesis that the proposed profitability ratio has a positive influence on financial distress, accepted hypotheses (p-value significant 0.000 ≤ 0.05 (5%). The direction of the null hypothesis is presented based on favorable results from earlier studies (Dewi et al., 2019). The difference in the direction of the initial hypothesis with the findings empirically is due to the results of the coefficient of the ratio of the profitability of the company with the result of the ratio coefficient profitability of companies listed on LQ-45 for the period 2017–2021 in the opposite direction. The result of the coefficient of determination leads to negative indicates the result of the profitability ratio in the opposite direction to the profitability ratio of the previous enterprise. This empirical inequality of findings will have an impact on profitability policy making on Financial Distress.

This finding is supported by the theory of agency theory basically discussing the form of agreement among principals and agents in managing the company, the agent carries a great responsibility for the success of the company he manages. There are three kinds of agency costs: residual costs, bonding costs, and monitoring costs (Jensen & Meckling, 1976). Agency theory uses three assumptions of human nature, namely: generally selfish, limited in the future thinking and risk-averse (Eisenhardt (1989). Principals enter into agency relationships when they employ agents to provide services for them and subsequently invest in those agents with discretionary authority. Agents, in their capacity as business managers, have access to more confidential and up-to-date information than do their employers’ principals (Malau, 2020). As a result, the agent must report to the principals on the state of the company.

4.4.2. Board size has a positive influence on financial distress

The Board Size shows the results of the estimate of positive coefficients according to the null hypothesis. The T-test explained that the Board of Size had a significant positive effect on Financial Distress at p-value significant 0.017 ≤ 0.05 (5%) on the OLS model, a p-value of 0.018 ≤ 0.05 (5%) on the Fixed Effects model, a p-value of 0.016 ≤ 0.05 (5%) on the Random Effects model, and a p-value of 0.006 ≤ 0.05 (5%) on the Robust model. The results of empirical testing prove that the higher the board size has an impact on increasing Financial Distress, contrary the lower the board size has an impact on reducing Financial Distress. These empirical findings support the hypothesis proposed that a board of size has a positive influence on financial distress, this hypothesis is accepted (p-value significant 0.006 ≤ 0.05 (5%). Submission of the null hypothesis’s direction based on the results of previous studies, which also led to positive results (Kristanti & Isynuwardhana, 2018).

The similarity of direction the initial hypothesis with the findings empirically is caused by the results of the company’s board size coefficient with the results of the board size coefficient listed in the LQ-45 period 2017–2021 in the same direction. The results of the coefficient of determination leading positively show that the company’s board of size is in the same direction as the previous board of size so the empirical findings state that the higher the company’s board of size has an impact on increasing Financial Distress, and vice versa. Organizations with large board sizes are less able to communicate, coordinate, supervise, and make decisions better when compared to companies that have fewer boards. So that the performance of a company that has a lot of boards is likely to be lower if compared with the company that has.

This finding is supported by agency theory basically discussing the form of agreement between shareholders and agents in managing the company, the agent carries a great responsibility for the success of the company he manages. There are three kinds of agency costs: residual costs, bonding costs, and monitoring costs (Jensen & Meckling, 1976). Principals enter into agency relationships when they employ agents to provide services for them and subsequently invest in those agents with discretionary authority. Agents, in their capacity as business managers, have access to more confidential and up-to-date information than do their employers’ principals (Malau, 2020). As a result, the agent must report to the principals on the state of the company.

4.4.3. Woman on board of commissioners influences financial distress positively

Woman on Board of Commissioners showed that the results of the negative coefficient estimate did not match the null hypothesis. T-test explained that the Woman on Boards of Commissioners had a negative insignificant effect on Financial Distress at a p-value significant 0.672 ≥ 0.05 (5%) on the OLS model, a p-value of 0.685 ≥ 0.05 (5%) in the Fixed Effects model, a p-value of 0.671 ≤ 0.05 (5%) on the Random Effects model, and a p-value of 0.556 ≤ 0.05 (5%) on the Robust model. The results of empirical testing prove that the higher the Woman on Boards of Commissioners has an impact on reducing Financial Distress, and vice versa the lower the Woman on Boards of Commissioners has an impact on increasing Financial Distress.

These empirical findings do not support the Hypothesis proposed that the Woman on Board of Commissioners Has a Positive Influence on Financial Distress, and this Hypothesis is Rejected (p-value significant 0.556 ≥ 0.05 (5%). The direction of this hypothesis is not in line with the findings of previous studies that lead positively (Kristanti & Isynuwardhana, 2018) and (Salloum et al., 2016). The direction of the initial hypothesis with the results of the empirical findings is due to the results of the company’s Woman on Board of Commissioner coefficient with the results of the ratio coefficient of Woman on Board of Commissioner companies listed in LQ-45 for the 2017–2021 period in the opposite direction. The results of the coefficient of determination leading to a negative point show that the results of the Woman on Board of Commissioners are in line with the company’s previous Woman on Board of Commissioners. This empirical inequality of findings will have an impact on policy making for the position of Woman on Board of Commissioners for Financial Distress.

Results of this finding are supported by agency theory basically discussing the form of agreement between shareholders and agents in managing the company, the agent carries a great responsibility for the success of the company he manages. There are three kinds of agency costs: residual costs, bonding costs, and monitoring costs (Jensen & Meckling, 1976). Agency theory uses three assumptions of human nature, namely: generally selfish, limited in future thinking and risk-averse (Eisenhardt (1989). Principals enter into agency relationships when they employ agents to provide services for them and subsequently invest in those agents with discretionary authority. Agents, in their capacity as business managers, have access to more confidential and up-to-date information than do their employers’ principals (Malau, 2020). As a result, the agent must report to the principals on the state of the company.

4.4.4. Woman on board of directors influences financial distress positively

Woman on Board of Directors shows the results of the estimate of the positive coefficient according to the null hypothesis. T-test explained that the Woman on Board of Directors had positive and significant effects on Financial Distress at a significant level of p-value of 0.040 ≤ 0.05 (5%) in the OLS model, a p-value of 0.040 ≤ 0.05 (5%) in the Fixed Effects model, a p-value of 0.039 ≤ 0.05 (5%) in the Random Effects model and a p-value of 0.014 ≤ 0.05 (5%) in the Robust model.

The results of empirical testing prove that the higher the Woman on Boards of Directors has an effect on the increase in Financial Distress, and vice versa the lower the Woman on Boards of Directors has an effect on the decrease in Financial Distress. These empirical findings support the Hypothesis proposed that the Woman on Boards of Directors Has a Positive influence on Financial Distress, the Hypothesis Accepted (p-value 0.039 ≤ 0.05 (5%) is consistent with (Kristanti & Isynuwardhana, 2018). Submission in the direction of the initial hypothesis is based on the findings of previous studies, which also lead to positive (Kristanti & Isynuwardhana, 2018).

The direction of the initial hypothesis with the empirical findings is due to the results of the company’s Woman on Board of Directors coefficient with the results of the Woman on Board of Directors coefficient of companies listed in the LQ-45 period 2017–2021 in the same direction. The results of the coefficient of determination leading positively show that the results of the Woman on Board of Directors are in the same direction as the woman on board of directors of the previous company. This empirical similarity of findings will have an impact on Woman on Board of Directors policy making towards Financial Distress.

Findings of this research are supported by the theory of agency theory basically discussing the form of agreement among principals and agents in managing the company, the agent carries a great responsibility for the success of the company he manages. There are three kinds of agency costs: residual costs, bonding costs, and monitoring costs (Jensen & Meckling, 1976). Principals enter into agency relationships when they employ agents to provide services for them and subsequently invest in those agents with discretionary authority. Agents, in their capacity as business managers, have access to more confidential and up-to-date information than do their employers’ principals (Malau, 2020). As a result, the agent must report to the principals on the state of the company.

4.4.5. Political connection influences financial distress positively

Political Connection shows the results of the estimate of positive coefficients according to the initial hypothesis. Results of t-test explained that Political Connection has a positive and significant effect on Financial Distress at a significant level of p-value of 0.056 ≥ 0.05 (5%) using the OLS model, significant p-value of 0.060 ≥ 0.05 (5%) Fixed Effects, significant p-value of 0.054 ≥ 0.05 (5%) Random Effects, significant p-value of 0.054 ≤ 0.05 (5%) Random effects, while in the Robust model the p-value significant 0.000 0.000 ≤ 0.05 (5%).

Results of empirical testing prove that the higher the Political Connection has an impact on the increase in Financial Distress, and vice versa, the lower the Political Connection has an impact on reducing Financial Distress. These empirical findings support the hypothesis proposed that Political Connection Influences Financial Distress Positively because p-value significant 0.000 ≤ 0.05 (5%), the Accepted Hypothesis is consistent with (Idah, 2013). Significant results and a positive direction, mean political connections can be detrimental to the company because these connections can incur agency costs by (Khan et al., 2016) over investment industry (Zhong-qin et al., 2019) earning management (Chaney et al., 2011) and a great tendency to corruption (Arrow et al., 2009). Consistent results encountered by (AT Kristanto, 2019) and (Nugrahanti et al.,) show that if political connection is positive and has a significant effect on financial distress, the higher the political relationship can reduce performance, which has an impact on the possibility of financial distress in the company. The result of the coefficient of determination leads positively shows the result of the political connection in the same direction as the political connection of the previous company. The Board of Directors’ approach to Financial Distress will be influenced by the striking congruence between theory and actual research.

The results of this finding are supported by the theory of agency theory basically discussing the form of agreement among principals and agents in managing the company, the agent carries a great responsibility for the success of the company he manages. Principals enter into agency relationships when they employ agents to provide services for them and subsequently invest in those agents with discretionary authority. Agents, in their capacity as business managers, have access to more confidential and up-to-date information than do their employers’ principals (Malau, 2020). As a result, the agent must report to the principals on the state of the company.

5. Conclusions

The higher the profitability ratio has an impact on decreasing Financial Distress and vice versa the lower the Profitability ratio has an impact on increasing Financial Distress, the higher the Board of Size has an impact on increasing Financial Distress and vice versa the lower the Board of Size has an impact on reducing Financial Distress. Temporaryly the higher or lower the Woman on Boards of Commissioners has no impact on Financial Distress, The higher of the Woman on Boards of Directors has an impact on the increase in Financial Distress, and vice versa the lower the Woman on Boards of Directors has an impact on increasing Financial Distress. The higher a Political Connection has an effect on increasing Financial Distress, and vice versa the lower the Political Connection has no impact on increasing Financial Distress.

Descriptive statistics

Pairwise correlations

Pairwise correlations

Regresion

Table

Variables	Obs	Mean	Std. Dev.	Min	Max	p1	p99	Skew.	Kurt.
Y	145	2.257	2.759	.144	16.079	.155	15.308	2.461	10.502
X1	145	.085	.08	.001	.467	.003	.37	2.036	8.198
X2	145	5.959	2.048	3	12	3	10	.402	2.671
X3	145	.081	.116	0	.429	0	.429	1.168	3.261
X4	145	.124	.179	0	.667	0	.667	1.788	5.469
X5	145	.897	.306	0	1	0	1	−2.604	7.782

Table

Variables	(1)	(2)	(3)	(4)	(5)	(6)
(1) Y	1.000
(2) X1	−0.369	1.000
	(0.000)
(3) X2	0.288	−0.259	1.000
	(0.000)	(0.002)
(4) X3	−0.060	0.121	0.204	1.000
	(0.477)	(0.147)	(0.014)
(5) X4	−0.022	0.422	−0.260	−0.108	1.000
	(0.791)	(0.000)	(0.002)	(0.198)
(6) X5	0.202	0.042	0.237	−0.007	0.114	1.000
	(0.015)	(0.615)	(0.004)	(0.936)	(0.173)

Table

Variables	(1)	(2)	(3)	(4)	(5)	(6)
(1) Y	1.000
(2) X1	−0.369*	1.000
(3) X2	0.288*	−0.259*	1.000
(4) X3	−0.060	0.121	0.204	1.000
(5) X4	−0.022	0.422*	−0.260*	−0.108	1.000
(6) X5	0.202	0.042	0.237*	−0.007	0.114	1.000

*** p < 0.01, ** p < 0.05, * p < 0.1

Table

	(Pooled Least Square (PLS)	(Fixed Effect Model (FE)	(Random Effect Model (RE)	(Robust)
	Financial Distress	Financial Distress	Financial Distress	Financial Distress
X1	−13.617***	−13.833***	−13.617***	−13.617***
	(2.959)	(3.038)	(2.959)	(3.553)
	0.000	0.000	0.000	0.000
X2	.273**	.273**	.273**	.273***
	(.113)	(.114)	(.113)	(.098)
	0.017	0.018	0.016	0.006
X3	−.789	−.767	−.789	−.789
	(1.859)	(1.886)	(1.859)	(1.337)
	0.672	0.685	0.671	0.556
X4	2.716**	2.804**	2.716**	2.716**
	(1.312)	(1.349)	(1.312)	(1.088)
	0.040	0.040	0.039	0.014
X5	1.36*	1.357*	1.36*	1.36***
	(.705)	(.715)	(.705)	(.33)
	0.056	0.060	0.054	0.000
_cons	.305	.314	.305	.305
	(.865)	(.877)	(.865)	(.594)
Observations	145	145	145	145
R-squared	.232	.233	.z	.232

Standard errors are in parentheses *** p < .01, ** p < .05, * p < .1

5.1. Implications of research results

These results provide empirical accounting evidence on decision-making Profitability, Board Size, Woman on Board of Commissioners, Woman on Board of Directors, Political Connections to Financial Distress related to Agency Theory. It clarifies the role of agents in policy making, Profitability, Board Size, Woman on Board of Commissioners, Woman on Board of Directors, and Political Connections to Financial Distress. These research findings also have consequences for corporate management in areas, such as profitability policy making, Board Size, Woman on Board of Commissioners, Woman on Board of Directors, and Political Connections to Financial Distress. Accounting theory is supported by these empirical data, which consider Profitability, Board Size, Woman on Board of Commissioners, Woman on Board of Directors, and Political Connections to Financial Distress. It also serves as a benchmark for future accounting studies and provides further empirical depth to existing findings.

5.2. Research limitations

This study has limitations that cannot be avoided. Disclosure of limitations aims to make this research understandable with a non-misleading interpretation. In addition, the disclosure of limitations also has the aim that further research can fill in the blanks, which are the limitations of this study: The elements in conducting content analysis in taking companies are obtained from the annual report of LQ 45 companies listed on the Indonesian stock exchange in the 2017–2021 period and the use of search results. On Google, the sample used in this study is limited to the annual report of LQ 45 companies listed on the Indonesian stock exchange in the 2017–2021 period and the use of google searches.

Author’s contribution

NK, MT, and LU carried out the research, and wrote and revised the article DR, LU, and NK conceptualised the central research idea and provided the theoretical framework. NK, MT, LU, and DR designed the and research and supervised research progress; NK and LU anchored the review and revisions and approved the article submission.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data Availability Statement

The study did not involve any data sets, and the articles collected were sourced from https://www.scopus.com/home.uri, accessed in 2022 and https://scholar.google.com/, accessed in 2022.

Additional information

Funding

Funders in this study used personal funds, because this journal was used as one of the requirements for graduation from the doctoral program in Accounting at the Faculty of Economics and Business at Sultan Ageng Tirtayasa University, Banten, Indonesia.

Notes on contributors

Nawang Kalbuana

Nawang Kalbuana, SE, M. Ak, Ak, CA. Bachelor’s and Master of Accounting at Mercu Buana University Jakarta, Accountant Profession at Jenderal Sudirman University. Currently studying Doctor of Accounting Science at Sultan Ageng Tirtayasa University, Banten. Lecturer at the Indonesian Aviation Polytechnic Curug (PPI Curug), Ministry of Transportation of the Republic of Indonesia

Muhamad Taqi

Dr Muhamad Taqi, SE, MMSI, CRP. Associate Professor at the Faculty of Economics and Business at Sultan Ageng Tirtayasa University, Banten, Indonesia. Completed a Doctor of Economics degree in Accounting in the Graduate Program at Sebelas Maret University, Indonesia, in 2019.