Investigating the Effects of Social Media Risks on Business Performance within Microfinance in Zimbabwe

Zimbabwe’s microfinance sector has experienced growth, with social media users increasing by 750,000 (+57.7%) between 2023 and 2024, reaching 2 million users representing 12.2% of the population. Microfinance institutions increasingly utilise social media for business operations while facing significant risks. Nevertheless, the existing literature lacks a comprehensive understanding of how specific risk dimensions affect business outcomes in developing-economy contexts. Grounded in the Technology Acceptance Model (TAM) and the Social Identity Theory (SIT), this study aimed to investigate the effects of five distinct social media risk categories: financial, reputational, cybersecurity, legal, and misinformation, on business performance within Zimbabwe’s microfinance institutions. The research employed a quantitative correlational design using structured questionnaires distributed to microfinance staff across 41 institutions. Data collection yielded 344 valid responses from personnel aged 22-60 years, representing approximately 1,000 of the sector’s total workforce. Statistical analysis utilised simple regression, multiple regression, and hierarchical regression approaches to examine risk-performance relationships while controlling for confounding effects. Social media adoption reached 94.2% among participating institutions, with utilisation demonstrating positive effects on return on investment (accounting for 23.1% of variance) and market reach (14.0% of variance). All five risk dimensions showed significant negative relationships with business performance. Reputational risk emerged as the dominant predictor, explaining 24.5% of the variance in business performance independently (β = -0.732, p < 0.001). Cybersecurity risk ranked second in impact (β = -0.218, accounting for 6.7% of the variance), followed by misinformation risk (β = -0.114, accounting for 3.5% of the variance). Financial risk demonstrated suppression effects, becoming significant in multiple regression analysis (β = -0.127, p < 0.05). Legal risk showed moderate but consistent adverse effects (β = -0.086, accounting for 2.7% variance). Collectively, these five social media risks explained 24.3% of total business performance variance. The findings support evidence-based resource allocation frameworks that prioritise reputational risks (60-70% of resources), followed by cybersecurity infrastructure (15-20%), and proportionate attention to the remaining risk categories. Future research should examine longitudinal risk evolution, cross-national generalizability, and implementation effectiveness of social media risk management strategies.