Nexus between green financial management and sustainable competitive advantage: Evidence from Indonesia

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With increasing environmental and strategic challenges, achieving sustainable competitive advantage is crucial for businesses. This study aims to examine the impact of strategic risk and green financial management on sustainable competitive advantage, focusing on the mediating role of sustainable business resilience and the moderating effect of government policy. A quantitative approach was utilized, applying the SMART-PLS methodology to analyze data gathered through a survey of 316 small and medium-sized enterprise (SME) owners in Indonesia, selected for their direct involvement in daily operations and strategic decision-making. The response rate was 63.2%, representing various industry sectors. The results indicate that strategic risk significantly enhances sustainable business resilience (β = 0.796 and p-value < 0.01), which is strongly associated with sustainable competitive advantage (β = 0.458 and p-value < 0.01). Green financial management, however, does not significantly impact resilience (β = 0.008 and p-value = 0.89). Both strategic risk and green financial management, nonetheless, indirectly influence competitive advantage through resilience, reflecting partial mediation (β = 0.112, p-value = 0.02 and β = 0.053, p-value = 0.04, respectively). Additionally, government policy strengthens the effect of green financial management on resilience (β = 0.556 and p-value < 0.01). These findings underscore the importance of firms managing strategic risks proactively and providing supportive regulations to encourage sustainable business practices by governments. The study provides practical insights for businesses and policymakers aiming to foster corporate resilience and enhance sustainable competitive positioning.

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    • Figure 1. PLS-SEM analysis
    • Table 1. Respondents’ information
    • Table 2. Descriptive statistics
    • Table 3. Goodness of fit
    • Table 4. Path coefficients and p-values
    • Table 5. Direct and indirect effects
    • Table A1. Measurement items, validity, and reliability
    • Conceptualization
      Mursalim Nohong, Sabir, Muhammad Try Dharsana, Fakhrul Indra Hermansyah, Bahtiar Herman, Yeni Absah, Andi Iqra Pradipta Natsir
    • Data curation
      Mursalim Nohong, Sabir, Muhammad Try Dharsana, Yeni Absah, Andi Iqra Pradipta Natsir
    • Formal Analysis
      Mursalim Nohong, Sabir, Fakhrul Indra Hermansyah, Bahtiar Herman, Andi Iqra Pradipta Natsir
    • Funding acquisition
      Mursalim Nohong, Sabir, Muhammad Try Dharsana, Fakhrul Indra Hermansyah, Andi Iqra Pradipta Natsir
    • Investigation
      Mursalim Nohong, Muhammad Try Dharsana, Fakhrul Indra Hermansyah, Bahtiar Herman, Yeni Absah, Andi Iqra Pradipta Natsir
    • Methodology
      Mursalim Nohong, Sabir, Muhammad Try Dharsana, Yeni Absah
    • Project administration
      Mursalim Nohong, Muhammad Try Dharsana, Bahtiar Herman
    • Resources
      Mursalim Nohong, Sabir, Muhammad Try Dharsana, Bahtiar Herman, Yeni Absah, Andi Iqra Pradipta Natsir
    • Software
      Mursalim Nohong, Muhammad Try Dharsana, Fakhrul Indra Hermansyah, Yeni Absah, Andi Iqra Pradipta Natsir
    • Supervision
      Mursalim Nohong, Sabir, Muhammad Try Dharsana, Fakhrul Indra Hermansyah, Yeni Absah, Andi Iqra Pradipta Natsir
    • Validation
      Mursalim Nohong, Sabir, Muhammad Try Dharsana, Fakhrul Indra Hermansyah, Bahtiar Herman, Andi Iqra Pradipta Natsir
    • Visualization
      Mursalim Nohong, Sabir, Muhammad Try Dharsana, Fakhrul Indra Hermansyah, Bahtiar Herman
    • Writing – original draft
      Mursalim Nohong, Sabir, Bahtiar Herman, Yeni Absah
    • Writing – review & editing
      Mursalim Nohong, Muhammad Try Dharsana, Fakhrul Indra Hermansyah, Yeni Absah, Andi Iqra Pradipta Natsir