The rapid post-pandemic acceleration of digital transformation has triggered profound strategic restructuring and heightened competitive pressures for large-scale commercial banks in Indonesia. This study examines the empirical effects of operational efficiency, credit risk, and net interest margins on the profitability of commercial banks categorized under Core Capital-Based Bank Grouping (KBMI) Categories 3 and 4. From a population of 18 KBMI 3 and 4 banks, purposive sampling yields 13 banks listed on the Indonesia Stock Exchange as the final sample, constituting a balanced panel of 65 bank-year observations. The econometric analysis reveals that operational efficiency serves as the primary and most dominant driver of corporate profitability. Institutions that successfully leverage digital technologies to mitigate structural cost burdens demonstrate a superior capacity for generating sustainable returns. Asset quality delineated by credit risk occupies the secondary critical threshold, where deteriorating loan portfolios directly compress institutional yields through heightened loan loss provisions. Conversely, the net interest margin ceases to exert a statistically significant influence on profitability once bank-specific unobserved heterogeneity is controlled. This phenomenon substantiates a definitive structural shift in banking revenue models, moving away from conventional spread-based intermediation toward digital fee-based streams.
Amid accelerating structural change, organizations face mounting pressure to sustain employee performance, particularly as human resource interventions such as mutation are often introduced without sufficient regard for employee well-being. This study examines how mutation influences employee performance, with work-life balance positioned as a mediating variable. Using a quantitative, explanatory survey design, data were gathered from 142 outsourcing employees of a state-owned electricity company who had previously undergone mutation, selected through saturated sampling. An online questionnaire served as the primary data collection instrument, and the resulting data were analyzed through Structural Equation Modeling with Partial Least Squares (SEM-PLS) using SmartPLS software. Findings reveal that mutation exerts a significant positive effect on employee performance and on work-life balance, that work-life balance in turn significantly and positively affects employee performance, and that work-life balance significantly mediates the relationship between mutation and employee performance. Taken together, these results indicate that mutation contributes to employee performance through both a direct pathway and an indirect channel mediated by work-life balance, with the direct effect proving stronger in magnitude, underscoring the need for organizations to integrate employee well-being into the design of mutation policies.
Rural economic development continues to face multidimensional challenges, including low MSME competitiveness, limited market access, and unsustainable business practices. Despite growing global discourse on green entrepreneurship, empirical evidence on its application in rural, natural resource-based MSMEs in developing countries remains scarce. This study aims to analyze the understanding and implementation of green entrepreneurship among MSME actors in Darma District, Kuningan Regency; formulate applicable development strategies; and measure the contribution of green entrepreneurship to rural economic improvement. A convergent mixed-methods design was employed, integrating quantitative data from 30 structured questionnaires and qualitative data from in-depth interviews with 12 key informants. Findings reveal that MSME actors have culturally internalized eco-product and circular production practices rooted in local wisdom, though without formal conceptualization. A Pearson correlation test indicates a statistically significant positive relationship between green entrepreneurship and rural economic. However, the cross-sectional design and reliance on respondents’ self-reported perceptions limit causal interpretation. This study contributes an applicable Pentahelix collaboration-based strategy model as a transformative framework toward an inclusive and sustainable green entrepreneurship ecosystem in rural Indonesia.
This study aims to analyze the influence of board of directors and board of commissioners' characteristics on tax avoidance practices in companies from the raw materials, consumer goods, energy, and industrial sectors listed on the Indonesia Stock Exchange (IDX) since year 2022–2024. The characteristics of the board of directors are board size and gender diversity. Meanwhile, the characteristic of the board of commissioners is independent commissioners. The research uses 197 companies with a total of 591 firm-year observations. The data were analyzed using multiple linear regression to test the influence of commissioners indenpendence, board size, and board gender diversity on tax avoidance. The research results show that board size, board gender diversity, and commissioner independence do not have a significant effect on tax avoidance. Only the control variable, specifically the firm size, has a significant impact, where larger companies tend to engage in Lower tax avoidance. This research contributes to the tax avoidance literature by providing evidence that board and commisioner characteristics do not significantly influence corporate tax decisions, thus the Agency Theory and Upper Echelon Theory do not fully explain this behavior. From a practical standpoint, regulators can increase oversight of small-sized companies that tend to have a higher tax avoidance.
Carbon intensity has emerged as a critical financial risk factor in Indonesia amid the implementation of carbon economic policies, including Presidential Regulation No. 98 of 2021 and the launch of the Indonesia Carbon Exchange in 2023. This study examines the effect of carbon intensity on firm risk, measured through systematic risk and unsystematic risk, and investigates the moderating role of Artificial Intelligence (AI) innovation among companies listed on the Indonesia Stock Exchange over the period 2018–2024. Using panel data regression analysis with year fixed effects on 394 firm-year observations across 74 companies, carbon intensity is measured as CO₂ emissions divided by firm revenue, systematic risk is represented by stock beta, unsystematic risk is measured through residual volatility, and AI innovation is proxied by the natural logarithm of AI-related patent counts. The results show that carbon intensity has a positive and significant effect on both systematic risk and unsystematic risk, indicating that firms with higher carbon exposure face greater market sensitivity and firm-specific volatility. Furthermore, AI innovation significantly weakens the positive effect of carbon intensity on unsystematic risk, suggesting its role as a firm-level risk-absorbing mechanism during the carbon transition process. However, AI innovation does not significantly moderate the relationship between carbon intensity and systematic risk, indicating that macro-level carbon transition risks remain beyond the reach of individual firm-level technological capabilities. This study contributes to the literature by providing empirical evidence from an emerging market setting and by highlighting the differentiated moderating role of AI innovation across two dimensions of firm risk.
