The economy of Bali heavily relies on the tourism sector, leading to economic vulnerability. There are numerous challenges in Bali's economy, with COVID-19 being one of the most prominent examples. During the COVID-19 pandemic, Bali's economy experienced the deepest contraction and slowest recovery compared to other provinces in Indonesia. Amid this economic vulnerability, it is important to conduct research on the financial resilience of SMEs in Bali. This research aims to analyze the influence of financial literacy on financial resilience, as well as the mediating role of financial performance and fintech adoption on the impact of financial literacy on financial resilience among SMEs in Bali. The research method used is a quantitative approach with a sample of 177 SMEs in Bali, selected through non-probability sampling techniques. Data were analyzed using descriptive and inferential statistics, with SEM-PLS in SmartPLS 3.0 program. The test results indicate that financial literacy has a positive and significant influence on financial resilience, financial performance, and fintech adoption. Financial performance and fintech adoption also have a positive and significant impact on financial resilience. Furthermore, financial performance and fintech adoption can partially mediate the influence of financial literacy on financial resilience in SMEs in Bali. The findings of this research are beneficial for the development of Knowledge-Based View theory and Technology Acceptance Model, as well as for SMEs in Bali and the government as policy makers in efforts to enhance financial resilience.

The global economy, including the banking sector in the ASEAN region, has experienced significant impacts due to the COVID-19 pandemic. To understand its impact more deeply, this research aims to evaluate banking stability and performance during the pandemic period, with a focus on risk governance and financial factors. A total of 272 banks in the ASEAN region were included in this study, using specific criteria depicting risk governance and financial factors. The research findings indicate a positive relationship between risk governance factors (RC, RCS, RCM and CRO) towards Financial Sustainability. The implications of these findings not only have theoretical relevance in understanding banking dynamics during crisis periods but also have important practical implications for decision-makers in the banking sector and financial regulation. Further discussion on theoretical and practical implications is provided, offering a better understanding of the challenges and opportunities in maintaining financial sustainability in the context of uncertain economic situations, such as those brought about by the global pandemic.

This study aims to examine the influence of the psychosocial work environment on the proclivity for asset misuse in the context of local government management, with a focus on the perceptions of administrators in Central Sulawesi Province. Employing purposive sampling, a total of 39 government units constituted the study's population, with a final sample size of 114 participants, comprising administrators, officers, and managers. WarpPLS software was employed to analyze the data. The findings reveal a positive relationship between rationalization and the inclination toward asset misuse. Additionally, rationalization exhibits a negative impact on the psychosocial work environment. Finally, the psychosocial work environment demonstrates a negative influence on the propensity for asset abuse. These outcomes suggest that the psychosocial work environment plays a pivotal role in mitigating the inclination for asset misuse within the local government of Central Sulawesi Province. This research sheds light on the significance of fostering a positive psychosocial work environment to enhance decision-making processes and reduce the likelihood of fraudulent activities in the management of government assets. Understanding these dynamics is crucial for the development of strategies to promote ethical and responsible asset management in local government entities.

This study examines the interaction effect between transformational leadership, transactional leadership, wireless IT competence, ambidexterity and supply chain management capability in increasing innovation capability. By using a knowledge-based view and dynamic capability theory basis, this research has provided an exploration of the supply chain of a merchant marine college and its impact on innovation capability using a quantitative method approach. The authors collected data from a cross-section of 673 questionnaires distributed to Managers in 3 managerial classifications from top, middle and bottom in the technical service unit of the merchant marine college under the Indonesian Ministry of Transportation. A total of 523 data were collected from questionnaires that could be continued for data analysis. The results of this study indicate that all the hypotheses put forward in this study are accepted, and the role of mediating variables in this research has succeeded in demonstrating their role in mediating each antecedent variable to increase innovation capability. The theoretical implication of this research is the growth of cloud or virtual supply chains facilitated by digital wireless communications, and internet technology is advancing logistics and supply chain innovations. Also, it can reinforce theory and dynamic capability.

This study examines the impact of relaxation of Foreign Direct Investment (FDI) access on the trans-regional investment behavior of Indonesian enterprises. Utilizing data from publicly listed companies between 2010 and 2022, this study investigates how easing FDI restrictions influences the geographic distribution of subsidiaries. The findings indicate that FDI access relaxation significantly promotes trans-regional investment, driven by reduced government subsidies and lower market intervention. These mechanisms enable enterprises to expand beyond local markets by decreasing their dependency on government support and lowering their transaction costs. Robustness tests, including first-order difference models and dynamic distribution tests, confirmed the reliability of the results. This study suggests that a further reduction in FDI restrictions can enhance domestic market integration, mitigate capital market segmentation, and promote inclusive economic growth. This study contributes to the literature by providing empirical evidence of the economic benefits of FDI access policies and offers new strategies for addressing market segmentation in Indonesia.

There were still contradictory results from earlier research on the relationship between organizational innovation, performance, and management control systems (MCS). In order to account for these contradictory results, future studies ought to concentrate on the empirical analysis of Simon's MCS theory. The purpose of the study was to assess the mediation and moderation model in relation to performance, innovation, and MCS. The study intends to broaden the scope by employing a more thorough definition and measurement of research variables. Because the Partial Least Square (PLS) can concurrently assess the existence of a dual dependency relationship of a latent variable, the study used PLS to test the hypothesis. The mediated hypothesis which holds that MCS indirectly affects performance through innovation seems to be supported by these data. All things considered, this study contributes to the understanding of the ambiguous and contradictory conclusions of earlier studies that examined the connection between MCS, innovation, and performance.

Financial reports provide information about a company's assets, liabilities, equity, income, expenses and cash flow. This information can be used by various parties such as investors, creditors, government and management to make business decisions and assess company performance. Companies in obtaining good financial reports need to detect fraudulent financial statements first. Financial statement fraud can be detrimental to investors and creditors because it gives a wrong picture of a company's financial performance. This study aims to examine the effect of big data competence and the tone of the top internal auditors on the detection of financial statement fraud, as well as to mediate the effect of big data competence on the detection of financial statement fraud through self-efficacy. This research uses a sample of 183 respondents who are internal auditors in companies in Indonesia. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results of the study show that big data competence has no significant effect on the detection of financial statement fraud, but has a positive and significant effect on self-efficacy. In addition, the internal auditor's tone of the top also has a positive and significant effect on the detection of financial statement fraud. Finally, self-efficacy partially mediates the relationship between big data competence and fraud detection of financial statements. This research provides important implications for practitioners and decision makers in developing internal auditor competence in the field of big data and paying attention to tone of the top as an important factor in detecting fraudulent financial statements. In addition, this research also contributes to strengthening the understanding of the relationship between big data competence, tone of the top, self-efficacy, and fraud detection of financial statements in the Indonesian context.

This research examined the connections of efficiency, regulatory and good corporate governance (GCG) variables on the achievement or performance of financial aspects and social reporting from Indonesia’s Shariah banks generally. Data and samples collected in this research include 34 Shariah banks, which are administered in the central bank, Bank of Indonesia for the year of 2009 until 2022. The financial achievement was determined with return on assets, and social reporting was determined with dummy 1 if the banks issue Islamic social reporting, and 0 otherwise. Regulation variables were measured with nonperforming financing (NPF), capital adequacy ratio (CAR), financial to deposit ratio (FDR), and net operating margin (NOM). Corporate governance variables were measured with firm age, board education, and board meeting. Efficiency variable was assessed with operating costs to revenue. The results show that regulation variables significantly impact financial achievement and social reporting, except NPF and CAR have nothing significant influence on Islamic social reporting. Efficiency variables significantly impact Islamic social reporting and financial achievement. Corporate governance variables significantly influence financial achievement and Islamic social reporting. Meanwhile firm age and board meetings have no remarkable influence on financial achievement.

Changes are occurring in customers demanding that companies produce environmentally friendly products. Apart from that, there is pressure from the government so that companies carrying out business activities can follow the rules and regulations set. The company has developed a system that uses technology to support production process activities properly and adequately. Blockchain technology makes green supply chain implementation faster and more flexible to continue improving supply chain performance. Data is collected on companies implementing blockchain technology and environmentally friendly programs. Data was collected at 512 manufacturing companies in Indonesia using Google Forms, which was distributed via email and social media. Data analysis used PLS to answer all research hypotheses. The research results showed that blockchain technology significantly influenced green supply chain management of 0.816, green practice of 0.370, supply chain flexibility of 0.115, and green supply chain performance of 0.150. Green supply chain management is a commitment for companies that have become top management commitments to adopt by reducing consumption of materials that impact the environment, which affects green supply practices of 0.473, supply chain flexibility of 0.244, and green supply chain performance of 0.247. Green supply practice, as a form of company best practice application, can influence supply chain flexibility by 0.428 and green supply chain performance by 0.214. Supply chain flexibility that has been running in manufacturing companies has had a significant impact on green supply chain performances of 0.331. This research provides a practical contribution to top management's commitment to running a green supply chain to increase company performance. Contribution for regulators and rule makers to continue to carry out continuous monitoring of business actors. Theoretical contributions to enrich theories about the green environment, green supply chain management, and blockchain technology.

Several models have been developed to predict financial difficulties and corporate bankruptcy. In this research various models were employed, including the Altman model (referred to as the Z-Score), the Springate model (known as the S-Score), the Zmijewski model (designated as the X-Score), and the Grover model (referred to as the G-Score). These techniques serve the purpose of evaluating the likelihood of encountering financial difficulties, which in turn determines the probability of PT Garuda Indonesia (Persero) Tbk going bankrupt. The study utilized secondary data sourced from financial statements spanning the years from 2020 to 2022. The application of the Altman model for bankruptcy prediction revealed that PT Garuda Indonesia (Persero), Tbk experienced financial distress throughout the period from 2020 to 2022. According to the Springate model, the company was in a state of distress and declared bankruptcy in 2020 and 2022, while 2021 fell into a grey area. The Zmijewski model indicated that the company was on the brink of bankruptcy, with financial difficulties and a potential risk of bankruptcy within the next three years. Grover's model predicted bankruptcy for the company in 2020 and 2022, but indicated safety in 2021. Notably, the Taffler model emerged as the most accurate in forecasting bankruptcy, boasting a 100% accuracy rate with no errors. Meanwhile, the Zmijewski model achieved an 81.25% accuracy rate with an error rate of 18.75%, and the Springate model exhibited the lowest accuracy in bankruptcy prediction, scoring only 12.50% accuracy with an error rate of 87.50%.