Mitigating Social Desirability Bias in Self-Reported Data of Social Science Research: A Systematic Literature Review

Social Desirability Bias (SDB) raises a persistent threat to the validity of social science research, mainly in studies relying on self-reported data. This systematic literature review synthesizes evidence on how social desirability bias is conceptualized, manifested, detected, and mitigated across social science disciplines, with a specific focus on management and organizational research in the era of social media. Guided by the PRISMA-2020 framework, 28 peer-reviewed journal articles published between 2000 and 2024 were systematically identified and analyzed using thematic synthesis. The findings reveal that social desirability bias is increasingly identified as a context-dependent and socially embedded phenomenon shaped by impression management motives, social norms, evaluation apprehension, and digitally mediated audiences. While a wide range of mitigation strategies has been proposed including indirect questioning, procedural safeguards, triangulation, and analytical controls, the review demonstrates that single method is not adequate. Instead, design-integrated and multi-strategy approaches are most effective. The review contributes theoretically by reframing social desirability bias as a substantive social mechanism than a peripheral methodological issue, and methodologically by offering evidence-based guidance for quantitative, qualitative, and mixed-methods research. Implications for management research and digitally mediated studies are discussed, alongside directions for future investigations.