Modelling Antecedents Influencing Business Performance of Agro-Processing Manufacturing Firm in Zimbabwe: A Structural Modeling Approach
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Abstract
The agro-processing manufacturing sector constitutes a critical engine of economic growth and employment generation in Zimbabwe, yet its business performance has been undermined by a confluence of structural, technological, and managerial challenges. This study investigates the antecedents influencing the business performance of agro-processing manufacturing firms in Zimbabwe, drawing on the Technology, Innovation, People and Systems (TIPS) philosophy and grounded in Resource-Based View (RBV) theory, Systems Theory, the Balanced Scorecard, and Michael Porter's Five Forces Model. Four key constructs are examined as antecedents of business performance: technological capability (TC), organisational innovation (OI), human capital (HC), and knowledge management systems (KMS). A descriptive, quantitative, cross-sectional survey design was adopted, with data collected from 220 employees of Zimbabwe's leading agro-processing manufacturer using a structured, self-administered questionnaire. Data were analysed using IBM SPSS (version 24) for descriptive statistics and SmartPLS 3.0 for Partial Least Squares Structural Equation Modelling (PLS-SEM). Nine hypotheses were tested. The results confirm that KMS positively and significantly influences OI (β = 0.327, p < 0.05) and HC (β = 0.462, p < 0.001); HC positively and significantly influences OI (β = 0.471, p < 0.001); OI positively and significantly influences business performance (β = 0.234, p < 0.05); and HC exerts the strongest significant positive effect on business performance (β = 0.987, p < 0.001). TC yielded positive but statistically insignificant effects on both OI and business performance. These findings confirm that OI and HC are the primary performance drivers in this agro-processing context, while providing nuanced theoretical and practical insights for manufacturing firms navigating Zimbabwe's turbulent economic environment
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