IFRS 9 misalignment and its impact on Sukuk investment strategies: Evidence from Jordan

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Type of the article: Research Article

Abstract
The emergence of Islamic finance has positioned Sukuk as a moral substitute for traditional bonds. However, misalignment with International Financial Reporting Standard 9, especially in Jordan, erodes investor confidence and reduces integration into world markets. This paper attempts to quantitatively evaluate how classification difficulties under International Financial Reporting Standard 9 affect investment strategies, decision-making, and market attractiveness of Sukuk within Jordan’s financial system.
Data were collected from a stratified sample of 346 finance professionals from banks, investment businesses, insurance companies, and regulatory authorities. Each participant had at least three years of work experience and suitable academic credentials. Utilizing partial least squares structural equation modeling, the survey was carried out between September 2024 and January 2025. The results indicate that classification issues have a significant adverse effect, reducing investment strategy efficacy by 46% (β = –0.46, p < 0.01), decision-making clarity by 37% (β = –0.37, p < 0.05), and Sukuk attractiveness by 52% (β = –0.52, p < 0.001). These significant effects are reinforced by vigorous diagnostics of the model, with variance inflation factor measures between 1.15 and 1.23, and by superb fit indices of the model, such as a standardized root mean square residual of 0.06 and a comparative fit index of 0.95.
The results underline the need for a coordinated international classification system and the structural influence of regulatory inconsistencies on Sukuk viability. Promoting openness, restoring investor confidence, and enabling wider acceptance in foreign markets all depend on aligning Islamic financial instruments with global reporting standards.

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    • Table 1. Sample characteristics
    • Table 2. Convergent validity and composite reliability
    • Table 3. Discriminant validity (Fornell-Larcker criterion)
    • Table 4. Discriminant validity (HTMT)
    • Table 5. Multicollinearity (VIF values)
    • Table 6. Model fit indices
    • Table 7. Hypothesis testing results
    • Conceptualization
      Abdulhadi Ramadan, Laith Khrais
    • Funding acquisition
      Abdulhadi Ramadan
    • Investigation
      Abdulhadi Ramadan
    • Project administration
      Abdulhadi Ramadan
    • Resources
      Abdulhadi Ramadan
    • Software
      Abdulhadi Ramadan, Laith Khrais
    • Supervision
      Abdulhadi Ramadan
    • Validation
      Abdulhadi Ramadan
    • Visualization
      Abdulhadi Ramadan
    • Writing – review & editing
      Abdulhadi Ramadan, Laith Khrais
    • Data curation
      Amer Morshed
    • Formal Analysis
      Amer Morshed, Laith Khrais
    • Methodology
      Amer Morshed
    • Writing – original draft
      Amer Morshed