Table 3 Regression equations Formative... | Emerald Publishing

Table 3

Regression equations

Formative measurement model:
$AC Composition = λ 1 \times AC size + λ 2 \times AC independence + λ 3 \times AC expertise + λ 4 \times AC NED + λ 5 \times AC gender + ϵ$ Where: AC Composition is the latent variable representing Audit Committee Composition AC size, AC independence, AC expertise, AC NED, and AC gender are the formative indicators $λ 1, λ 2, λ 3, λ 4, λ 5$ ⁠, are the weights of each indicator on the latent variable $ϵ$ represents the error term
Structural model:
$ROA = β 1 \times AC Composition + β 2 \times Asset Turnover + β 3 \times Leverage + β 4 \times Leverage + ζ$ $MAC = γ 1 \times AC Composition + γ 2 \times Asset Turnover + γ 3 \times Leverage + γ 4 \times Firm Size + η$ Where: ROA and MAC are dependent variables representing Return on Assets and Market Capitalization, respectively AC Composition is the independent latent variable representing Audit Committee Composition Asset Turnover, Leverage, and Firm Size are control variables $β 1$ ⁠, and $γ 1$ are the path coefficients between AC Composition and ROA and MAC, respectively $β 2$ ⁠, and $γ 2$ are the path coefficients between Asset Turnover and ROA and MAC, respectively $β 3$ ⁠, and $γ 3$ are the path coefficients between Leverage and ROA and MAC, respectively $β 4$ ⁠, and $γ 4$ are the path coefficients between Firm Size and ROA and MAC, respectively $ζ$ ⁠, and $η$ represents the error terms for ROA and MAC, respectively

Source(s): Authors' computation