From Sustainability Recognition to Documented Outcomes: A Systematic Review and Study-Level Evidence Translation Analysis Across Productive Sectors

Sustainability is widely recognized in project-based and productive-sector research, yet published studies do not always make visible how this recognition enters control routines, resource-allocation rules, and documented outcomes. This systematic review and study-level evidence translation analysis examined 133 unique full-text studies drawn from Scopus and Web of Science evidence matrices covering publications from 2008 to 2026. A bilingual rule-based coding layer organized candidate evidence across ten sustainability-control domains and three stages: recognition (R), operationalization (O), and documented outcome evidence (E). Two independent university professor reviewers, one with a sustainability focus, and one with a statistics focus and each with more than five years of professional experience, then coded the complete corpus under the pre-specified protocol; disagreements were resolved through third-author adjudication. Observed agreement was 0.921 for R, 0.831 for O, and 0.883 for E. In the final matrix, R, O, and E were present in 53.1%, 34.7%, and 45.4% of study-domain observations, respectively, and full R-O-E completion occurred in 29.7%. The pattern was non-nested: documented outcomes were sometimes reported without an explicit account of the operational pathway. Generalized estimating equations confirmed lower odds for O (OR = 0.423, 95% CI 0.378–0.473) and E (OR = 0.703, 95% CI 0.619–0.799) relative to R. A four-class Bernoulli latent-class model minimized BIC and identified stakeholder-governance-transition, lifecycle-system integration, digital-data evidence, and measurement–performance profiles. The resulting Sustainability Evidence Translation Control Architecture locates documentary discontinuities between purpose, controls, decisions, and outcomes while avoiding unsupported claims about symbolic intent, implementation failure, or causal organizational transformation.