Moderating role of modular innovation in sustainable development financing and SME performance in emerging economies

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Type of the article: Research Article

Abstract
Globally, small and medium-sized enterprises (SMEs) are facing increasing pressure to achieve sustainability goals through vital financing mechanisms, including green financing, social impact investments, and microfinancing. This study examines the impact of modular innovation on the relationship between sustainable development financing (SDF) and the performance of SMEs in an emerging economy. The research used a cross-sectional survey of 740 SMEs across Nigeria from January 2024 to March 2024. After cleaning the data, 612 responses were valid. These responses were analyzed using Partial Least Squares-Structural Equation Modeling (PLS-SEM). The findings reveal that all three sustainable financing mechanisms have a significant and positive influence on SME performance. Modular innovation, specifically incremental, architectural, and radical innovation, notably moderates these relationships. Incremental innovation exhibited the strongest moderating effect (β = 0.543), followed by radical innovation (β = 0.473), and architectural innovation (β = 0.441). This suggests that innovative capacity enhances the impact of sustainable financing. Consequently, these results underscore the crucial role of modular innovation in improving the effectiveness of sustainable financing for SMEs. They also emphasize the need to incorporate innovation policies that support SME growth via green financing, social impact investments, and microfinancing in emerging economies like Nigeria.

Acknowledgments
The authors express their gratitude to the anonymous reviewers, the journal editor, and all the scholars whose work was referenced in this study. They also sincerely thank the respondents who provided the data necessary for the research.

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    • Figure 1. Conceptual model
    • Figure 2. PLS-SEM model with moderating effect
    • Table 1. Characteristics of respondent SMEs
    • Table 2. Measurement instrument showing descriptive statistics
    • Table 3. Results of convergent validity for the measurement instrument
    • Table 4. Discriminant validity
    • Table 5. Summary of hypotheses testing and moderating results
    • Conceptualization
      Morgan Obong Morgan
    • Data curation
      Morgan Obong Morgan, Edet Okon, James Obriku Otiwa
    • Formal Analysis
      Morgan Obong Morgan, Edet Okon
    • Funding acquisition
      Morgan Obong Morgan, Inemesit Enobong Uwah, Edet Okon, Emmanuel E. Okon, James Obriku Otiwa
    • Investigation
      Morgan Obong Morgan, Inemesit Enobong Uwah, Edet Okon
    • Methodology
      Morgan Obong Morgan, Edet Okon, Emmanuel E. Okon
    • Software
      Morgan Obong Morgan, Inemesit Enobong Uwah, Edet Okon
    • Visualization
      Morgan Obong Morgan, Inemesit Enobong Uwah, Edet Okon
    • Writing – original draft
      Morgan Obong Morgan, Inemesit Enobong Uwah, Edet Okon
    • Project administration
      Inemesit Enobong Uwah, James Obriku Otiwa
    • Supervision
      Inemesit Enobong Uwah, Emmanuel E. Okon, James Obriku Otiwa
    • Writing – review & editing
      Inemesit Enobong Uwah, Edet Okon, Emmanuel E. Okon, James Obriku Otiwa