Determinants of going-concern audit opinions: Empirical evidence from listed mining firms in Indonesia

____________________________________________________________ This study aims to ascertain how going concern audit opinions are affected by Profitability, liquidity, solvability, firm size, and audit quality. Profitability will be measured with Return on Asset, Liquidity with Current Ratio, Solvency with Debt to Asset Ratio, and Firm Size with Logaritma Natural of Total Assets. The data used in this study is secondary data. The mining businesses listed on the Indonesia Stock Exchange (IDX) in 2019 – 2021 comprise the study's population. Purposive sampling determines the sample, leaving 65 companies that satisfy the requirements. Logistic regression is the data analysis technique used in this study. In contrast, Audit Quality will be measured using the services of a public accounting firm hired by the company. The results indicate that while solvency had no impact on the going-concern opinion, variable Profitability, liquidity, firm size, and audit quality all significantly influenced going-concern opinion.


Introduction
The COVID-19 pandemic that emerged at the end of 2019 caused the government to restrict each area. The existence of restrictions in each region has resulted in trade routes being hampered, so the economy worldwide has been disrupted. This has also impacted the mining sector; as evidenced in the 2020-2021 financial reports, many companies have experienced a decrease in profits compared to the previous year. According to Ginting & Tarihoran (2017), companies that cannot generate profits or experience substantial losses repeatedly and in significant amounts will raise doubts about continuing their business.
Business continuity is one of the most considered factors because it is one of the basic assumptions in the financial statements that reflect the company's ability to continue its business operations and that there will be no liquidation in the future (Istiana, 2010). Business continuity is a form of corporate responsibility to shareholders as a return on investment (Jensen & Meckling, 1976).
To provide an evaluation of the financial statements prepared by internal parties, the company will appoint an independent auditor. The auditor will provide an evaluation of the company's ability to continue its operations in addition to assuring that the financial statements have been designed concerning the applicable accounting standards. The auditor must make a detailed assessment of the company regarding financial and non-financial factors before deciding on the opinion issued (Kartika, 2012). Companies considered problematic and whose ability to continue their business is doubtful will be given a going concern opinion. Going concern opinion needs to give a better picture of the company's potential and sustainability, which has an impact on eroding the company's reputation (Kristiana, 2012). A "warning" is given to users of financial statements when a going concern opinion is given.
This research is based on signal theory by Spence (1973), which explains that the owner of the information will provide a piece of information as a signal that the receiver can use to determine his following action. The opinion issued by the auditor will act as a signal for internal and external parties who use the financial statements. This theory also reduces the information gap owned by internal companies and external parties (Setiawan et al., 2021).
Many previous studies have yielded varying results on ongoing concern opinions. Research by Rakatenda & Putra (2016) states that Profitability does not affect going-concern opinion, while Listantri & Mudjiyanti (2016) conclude that Profitability affects going-concern opinion. Another study by Kusumaningrum & Zulaikha (2019) found that liquidity impacted going-concern opinion, but Yuliyani & Erawati (2017) stated that liquidity had no impact. Haryanto & Sudarno (2019) also researched going concern opinion and concluded that solvency influences the auditor's decision to give this opinion, in contrast to Jalil (2019), which states that going concern opinion is not affected by company solvency. Another study by Pradika & Sukirno (2017) concluded that company size affects the auditor's assessment. Another study by Tandungan & Mertha (2016) states that company size has no effect, but audit quality impacts going-concern opinion. Given the differences in the results of previous studies, this has come to the attention of researchers so that researchers are encouraged to review the variables of Profitability, liquidity, solvency, company size, and auditor quality, which can influence the auditor's assessment in giving going-concern opinion statements. What distinguishes this research from previous research is the sector and period used. In this study, testing will be carried out on the mining sector in 2019-2021. This study aims to determine the effect of financial performance, company size and auditor quality ongoing concern opinions. This research is expected to be useful for users of financial statements as a basis for paying more attention to factors that can influence going concern opinion. For internal parties, this information can be used to determine the company's next steps on the current state of the company. Whereas for external parties such as potential investors, this information helps determine investment decisions given to the company.

Hypothesis Development Opinion Going Concerne
Referring to SPAP (2011), the going concern is the assumption that a business can continue to operate for a long time and will wait to file for bankruptcy. On the other hand, a going concern opinion results from an auditor's assessment where there are doubts about the company's ability to continue operating for a long time (Bahtiar et al., 2021). Before issuing an opinion, auditors must thoroughly evaluate every aspect of the business, including operating results, the economy, a company's ability to service debts, and anticipated future liquidity requirements.

Profitability on Going Concern Opinion
A profitability ratio calculation is used to evaluate a company's capacity to make a profit (Kasmir, 2018). Businesses that can turn a profit demonstrate their ability to stay in business. According to research by & Mudjiyanti (2016), Kusumawardhani (2018) and Darwis & Fatmawati (2022), Profitability affects whether or not a going concern audit opinion is accepted. Based on signal theory, Profitability becomes data information that auditors can use to evaluate the condition and performance of company management in managing and utilizing assets owned for profit. High Profitability shows that the company can earn significant profits; this shows that it can run well to reduce the opportunity to get a going concern opinion. H1: Profitability affects going concern opinion.

Liquidity on Going Concern Opinion
Liquidity is a calculation that assesses a company's capacity to repay its short-term obligations (Kasmir, 2018). The value of liabilities higher than assets can harm the company. Companies that cannot fulfil their obligations will open up opportunities to provide going-concern opinions (Bahtiar et al., 2021). Research by Saifudin & Trisnawati (2015), Utama et al. (2021), Sari (2020) and Haribowo (2013) provides results that support that liquidity has an impact on assessing going-concern opinion. Based on the signaling theory, the calculation of liquidity will be a sign that the auditor can consider when expressing his audit opinion. A low liquidity value indicates that the company's total current assets and liabilities do not significantly differ. This will open up a gap to receiving a going concern opinion because there are doubts about the company's ability to fulfil its current obligations. H2: Liquidity affects going concern opinion.

Solvability on Going Concern Opinion
Solvability is a formula used to assess how much a company's assets are funded by debt (Kasmir, 2018). This calculation also shows the company's capacity to control its debts to generate profits and repay its debts. Research by Haryanto & Sudarno (2019) and Adhityan & Taman (2016) supports the statement that solvency impacts whether or not a going concern opinion is accepted. In line with the understanding of signal theory, the solvency ratio will be the information needed by the auditor in evaluating the company. A high solvency value indicates that most of the company's assets are funded by debt. If this is not managed correctly, it will become a problem for the company. Unfavourable financial performance will raise doubts about the company's ability to continue its business. H3: Solvency affects going concern opinion.

Company Size
The number of assets held by a company shows how big the size of the company is. Based on signal theory, information about company size can be helpful for auditors in assessing the ability of businesses to continue their business. Businesses with a positive increase in assets accompanied by growth in operating performance results will increase the company's value and are a sign that the company is unlikely to file for bankruptcy soon (Achmad & Amanah, 2012). The study conducted by Miverna et al. (2022), Putra et al. (2021), and Amami & Triani (2021) prove that the size of a company has a positive impact on receiving goingconcern opinions. H4: Company size affects going concern opinion.

Auditor Quality on Going Concern Opinion
The study by Miverna et al. (2022) and Juanda & Lamury (2021) conclude that auditor quality has an influence on going concern opinion because auditors at Big Four KAPs have a higher level of independence and competence, more issues are found and disclosed, which can become the auditor's view when concluding going concern opinion. In signal theory, auditors are experienced and can express findings to produce more detailed information or signals about the company's condition. Big Four KAP auditors have work experience with various global and multinational companies; the higher the auditor's independence, the lower the level of fraud committed (Melania et al., 2016). H5: Auditor quality influences going-concern opinion.

Method
In this study, the attachment between the independent variables and the dependent variable will be examined. Profitability, Liquidity, Solvability, Company Size, and Auditor Quality are independent factors while going concern Opinion is the dependent variable.
The processed data is secondary data accessed through the Indonesia Stock Exchange (IDX). All mining business actors listed on the IDX in 2019-2021 comprise this study's population. Purposive sampling is a data sampling technique applied under the following conditions: 1.) Mining companies listed on the IDX in 2019-2021; 2.) Mining Companies that report financial reports and independent auditors' reports successively during the year of study.
Statistical analysis of the data applied to this test is logistic regression analysis. This analysis is applied considering that the dependent variable is a dummy variable, so the classical assumptions on the linear relationship between the dependent and independent variables are unnecessary (Ghozali, 2016). The data will be processed using statistical techniques by utilizing SPSS (Statistical Product and Service Solutions).

Operational Variables and Measurements
There are independent variables and dependent variables in this test. The dependent variable is going concern opinion, and the independent variables include Profitability, liquidity, solvency, company size, and auditor quality.

Variable Measurement
Opinion Going Concern Dummy variable. Companies that get a going concern opinion will be marked with the number 1 while companies that get a non going concern opinion are marked with the number 0.

Company Size ln Total Assets
Auditor Quality Dummy variable. Companies that rely on Big Four KAP services are marked with the number 1 and companies that rely on non-Big Four KAP services will be marked with the number 0.
Referring to Ghozali (2016), hypothesis testing with logistic regression will be implemented through several stages, namely testing the entire model, testing the feasibility of the regression model, testing the coefficient of determination and classification matrix, and testing the regression coefficient. The hypothesis testing model is carried out using the equation below: GCO = a +β 1 ROA + β 2 CR + β 3 DAR + β 4 UP + β 5 KA+ε Information: GCO is Going concern opinion, a is constant, β1-β4 is Regression Coefficient, ROA is Profitability proxied by ROA, CR is Liquidity proxied by CR, DAR is Solvability is proxied by DAR, UP is Firm Size, KA is Quality Auditor.

Result and Discussion
The population of this study are Mining Companies listed on the IDX in 2019-2021, with a total of 74 companies. Mining companies that did not report their financial statements and independent auditors' reports successively during the year of study were nine companies. The sample that can be used in this study is 65 companies with three years of research, so the observed data amounted to 195.

Descriptive statistics
Descriptive statistics is an analysis that aims to provide an overview of the characteristics of each research variable. This test provides basic information about the data seen from the average value (mean), minimum value, maximum value, and standard deviation of the independent and dependent variables. (1) The amount of data tested in this study was 195 with the following data characters: (2) The profitability variable has a minimum value of -1.54, a maximum value of 0.52 with an average of 0.025 and a standard deviation of 0.161. (4) The solvency variable has a minimum value of 0.01, a maximum value of 3.32 with an average of 0.546 and a standard deviation of 0.384. (5) The company size variable has a minimum value of 24.04, a maximum value of 32.32, an average of 28.723 and a standard deviation of 1.745. (6) The auditor quality variable, as measured by the dummy variable, shows that the frequency of companies that use the Big Four KAPs is 61, while the other 134 use the services of non-Big Four KAPs. (7) The going concern opinion variable was measured using a dummy variable. It showed that 44 companies received a going concern opinion while the other 151 did not receive this opinion. The Overall Model Fit Test was conducted to see the fit data model by comparing -2 Log Likelihood (-2LL) before and after adding the independent variables. The model will be declared fit with the data if there is a decrease in value at the final -2LL. Table 4 above shows a decrease in the number at -2LL at Block Number = 1 to 167.746 after previously -2LL at Block Number = 0 was 222.015. This shrinkage indicates that the regression model is good and fits the data. To determine the feasibility of the regression model, Hosmer and Lemeshow's Goodness of Fit test will be carried out by looking at the sig. of the chi-square value. Table 5 shows a chi-square value of 4.094 with sig. 0.849, where the value exceeds 0.05, so it can be interpreted that this research model fits the data, and there is no difference between the model and the data. This test aims to describe the capability of the independent variables in describing the dependent variable. If the Nagelkerke R Square value is close to 1, the capacity of the independent variables to describe the dependent variable is considered higher. From The prediction accuracy of the independent and dependent variables can be seen in the classification table.

Determination Coefficient Test
In the table above, it can be seen that the accuracy of the prediction model on the dependent variable is 80.5%.

Profitability and Going Concern Opinion
Return on Assets (ROA), a proxy for the profitability variable, produces a regression coefficient of -6.411 with a sig. 0.008. From this significance, it can be concluded that this variable impacts the dependent variable because its significance is less than 0.05. Therefore, the going concern opinion-dependent variable negatively affects the profitability variable. This finding is the same as that of (Listantri & Mudjiyanti, 2016;Pradika, 2017;Melania et al., 2016). The damaging nature of the relationship between Profitability and going concern opinion shows that a business with a significant rate of return on assets will have a smaller chance of obtaining a going concern opinion. This follows signal theory, where a considerable profitability value becomes information showing that a company manages its assets well to generate large profits. A company that can make a profit can continue its business operations.

Liquidity and Going Concern Opinion
Liquidity produces a regression coefficient of -0.545 with a sig. of 0.048. From this significance, the liquidity variable impacts going concern opinion decisions. This finding aligns with the signal theory in which information about a company's liquidity becomes a signal for auditors to consider in assessing a company's business continuity. The negative relationship between liquidity and going concern opinion shows that the smaller the liquidity, the greater the chance for the company to receive the going concern opinion. Through these results, it can be formulated that the auditor will consider the company's capacity to be responsible

Non-GC GC
Step 1  for paying its short-term obligations when assessing the company's condition. Companies that fail to pay their urgent obligations indicate a problem in company performance. This finding is by previous research conducted by (Saifudin & Trisnawati, 2019;Kusumaningrum & Zulaikha, 2019;Khasanah et al., 2021). Table 8 above lists the logistic regression hypothesis test findings, which shows that DAR has a regression coefficient of 0.979 and sig. 0.120. Because the significance exceeds 0.05, it can be interpreted that solvency does not impact receiving a going concern opinion. This result is inconsistent with a signal theory which explains that information about solvency serves as a helpful signal in determining whether a company will be able to continue operating. The findings of Jalil (2019) and Nurcahyono et al. (2021), who also claim that solvency has no impact on going concern audit conclusions, are consistent with this. Even though many assets are funded by debt, the company can still generate profits. It can continue to fulfil its obligations, so it is acceptable for the company to continue its business operations. This indicates that in giving his assessment, the auditor also pays attention to the big picture of a business. These results differ from research conducted by Haryanto & Sudarno (2019) and Adhityan & Taman (2018), which state that solvency impacts whether or not a going-concern opinion is accepted.

Company Size and Going Concern Opinion
The regression coefficient in this variable produces a value of 0.339 and sig. 0.013. A significance of less than 0.05 concludes that H4 is accepted; going concern opinion is influenced by the company's size. This conclusion aligns with the findings by Miverna et al. (2020) and Akbar & Ridwan (2019), who stated that company size influences going-concern opinion. This finding is by the signal theory, which describes that information about company size becomes a signal for the auditor in formulating the results of an audit opinion. The relationship between company size and going concern opinion is positive, indicating that a company's size will also significantly impact the company's chances of getting a going concern opinion. Companies categorized as significant will have more assets and liabilities than smaller companies; if the management cannot manage the assets appropriately owned, it will cause losses that can harm the company and provide an opportunity for the auditor to express a going concern opinion.

Going Concern Opinion and Audit Quality
Based on the hypothesis test results table above, audit quality produces a regression coefficient of -1.336 and a sig. 0.013. The significance is not more than 0.05, which means that H5 is accepted, namely, audit quality affects the going concern opinion of a company. Based on these findings, the Big Four KAPs can assess the viability of a company in detail because they have broader experience and a higher level of independence so that they can process information or signals obtained in more detail to produce quality opinions. This finding is similar to that of Miverna et al. (2020) and Sari & Wahyuni (2014), who also examined the effect of audit quality on going concern opinion.

Conclusion and Recommendation
The assessment given by the auditor has a significant influence on users of financial statements to plan appropriate actions by the company's current state. The test results with SPSS 21 yielded several conclusions, including company size, which positively affected going-concern opinion, while Profitability, liquidity and audit quality had a negative effect. This finding is consistent with signalling theory, which postulates that information about a firm's Profitability, liquidity, audit quality, and size serves as a signal or warning about an organization's ability to continue operating. In addition, it can also be concluded that solvency has no impact on going concern opinion. This finding is inconsistent with the signal theory, which explains that information about solvency serves as a helpful signal in determining whether a company will continue to operate.
This research still needs to be improved by several limitations, namely, the Nagelkerke R Square number tends to be low, which means that additional factors can be used to predict acceptance of going concern opinion. Suggestions for future researchers to be able to carry out research expansion by examining other factors such as audit tenure, opinion shopping, audit lag or financial distress and expanding the object of research in companies in various other sectors.  A., & Erawati, N. M. A. (2017). Pengaruh financial distress, profitabilitas, leverage, dan likuiditas pada opini audit going concern. E-Jurnal Akuntansi, 19(2), 1490-1520.