Beyond the efficiency score: a critical meta-analysis of methodological rigor and data gaps in the blue bioeconomy

Background The transition toward a sustainable Blue Bioeconomy (BBE) relies on accurate efficiency measurements; however, methodological fragmentation often obscures real progress. Objective This study aims to evaluate the methodological rigor and identify data gaps in the BBE through a systematic review and meta-analysis of 30 global studies. Methods We employed a random-effects meta-analysis and a meta-regression using the Restricted Maximum Likelihood (REML) estimator to explore sources of heterogeneity (I 2 ). Results The overall pooled efficiency score across BBE studies was 0.74. Meta-regression revealed that while analytical estimators (DEA, SFA, TFP) do not drive outcome variation ( R 2 = 0.00%), economic sector taxonomy serves as the primary determinant, accounting for 65.57% of total heterogeneity. High-tech marine biotechnology and renewable energy sectors demonstrated superior efficiency levels, whereas coastal conservation and small-scale artisanal fisheries exhibited significant efficiency lags due to under-capitalization and regulatory fragmentation. Conclusions This meta-analysis demonstrates that estimated efficiency in the Blue Bioeconomy is not an artifact of estimator mechanics (DEA vs. SFA vs. TFP, p = 0.62), but is fundamentally dictated by economic sector characteristics ( R 2 = 65.57%). To overcome current measurement fragmentation and align governance with ecological realities, future assessments must adopt natural-capital integrated distance functions that account for ecosystem flow metrics and biological fund dynamics. Consequently, policy frameworks must transition from blanket blue-growth strategies toward sector-differentiated interventions—scaling capital and regulatory streamlining for high-tech marine sectors while redirecting resource-dependent fisheries and coastal conservation policies toward net natural capital stewardship and biological replenishment incentives.