Meta-analysis in Information Systems Research: Review and Recommendations
Meta-analysis has gained considerable momentum in information systems (IS) research over the last two decades. As the IS discipline has matured and grappled with various applications of information technology (IT) tools, meta-analysis has served as a powerful mechanism to enable the synthesis of prior findings, reconciliation of inconsistent findings, and resolution of relationships. Prior meta-analysis studies in IS have employed derived metrics and reported effect sizes in both exploratory and confirmatory approaches, and also conducted descriptive analysis, comparison of subgroup means, regression, and structural equation modeling methods. This paper conducts a review of prior meta-analysis studies published since 2000 using a 2 × 2 framework and identifies the state of meta-analysis research in IS. The challenges in conducting meta-analysis research and the opportunities for meta-analysis research in IS are also identified. Based on the challenges, several recommendations to handle publication bias, inclusion and exclusion of studies, effect sizes, coding, meta-analysis modeling, and sensitivity analysis are provided. Opportunities for meta-analysis such as clarifying constructs and relationships, identifying contingencies, and testing theories to advance IS research are also identified.
& Dwivedi, Y.
(2020). Meta-analysis in Information Systems Research: Review and Recommendations. International Journal of Information Management, 55, 102226.