Nexus of Intellectual capital efficiency components and firm value in listed Sub-Saharan Africa insurance companies: A static and dynamic approach
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Author(s)Thabiso Sthembiso MsomiLink to ORCID Index: https://orcid.org/0000-0003-3941-6815
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Odunayo Magret OlarewajuLink to ORCID Index: https://orcid.org/0000-0002-4366-040X
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Mabutho SibandaLink to ORCID Index: https://orcid.org/0000-0002-8656-7539
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DOIhttp://dx.doi.org/10.21511/ins.16(2).2025.10
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Article InfoVolume 16 2025, Issue #2, pp. 124-140
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Type of the article: Research Article
Abstract
This study investigates the nexus between Intellectual Capital efficiency (ICE) components and firm value in Sub-Saharan African (SSA) insurance companies. The study employed a modified Value-Added Intellectual Coefficient (VAIC™) model, incorporating components such as Value-Added Capital Coefficient (VACA), Structural Capital Value-Added Coefficient (SCVA), Value-Added Human Capital Coefficient (VAHC), and Innovation Capital Efficiency (VAHC2). These components were integrated to calculate the VAIC, offering a holistic assessment of value-creation efficiency within SSA insurance firms. Static and dynamic panel data analyses were employed to estimate the relationship between the ICE components and Tobin’s Q ratio, serving as a proxy for firm value. A positivist approach and descriptive quantitative methods were used in this study. The study analyzed panel data from 122 insurance firms across 46 SSA countries over the period 2010–2022, sourced from databases including Wharton Research Data Services, S&P CapitalIQ, and Refinitiv Eikon. The VAIC™ model was applied by integrating various ICE components to comprehensively evaluate the value creation efficiency in SSA insurance firms. The findings indicate significant variation in the impact of ICE components on firm value across SSA insurance companies. Specifically, higher VAIC™ values are associated with enhanced firm performance, underscoring the critical role of intellectual capital in value creation within this sector. This research contributes to the body of knowledge by demonstrating the applicability of the VAIC™ Model in SSA’s insurance sector and underscoring the relevance of intellectual capital management in driving financial outcomes. Practical implications include informing policymakers, executives, and investors about optimizing intellectual resources to foster sustainable growth and resilience in SSA insurance.
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JEL Classification (Paper profile tab)G20, G22
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References61
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Tables8
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Figures0
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- Table 1. Descriptive statistics
- Table 2. Correlation matrix
- Table 3. Stationarity or unit root test
- Table 4. Panel least square method (TOBINS’Q, VACA, SCVA, VAHC, VAHC2, RISK, SIZE, LEVE)
- Table 5. Correlated random effects – Hausman test
- Table 6. Residual cross-section dependence test for the fitted panel models
- Table 7. Predictive power of the fitted models
- Table 8. Dynamic panel GMM (TOBINS’ Q, VACA, SCVA, VAHC, VAHC2, RISK, SIZE, LEVE)
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