<![CDATA[The rapid digitalization of legal documents has intensified the need for advanced legal information retrieval (LIR) systems, particularly in business law, where regulatory complexity, corporate governance, and cross-jurisdictional norms intersect. Traditional LIR approaches, which rely heavily on keyword matching and textual similarity, often fail to capture legal authority, contextual relevance, and jurisprudential influence. In response to these limitations, bibliometric-enhanced legal information retrieval (B-LIR) has emerged as an interdisciplinary approach that integrates citation-based indicators with semantic and textual analysis. This study provides a systematic and critical review of bibliometric-enhanced LIR methods and their applications in business law. The study analyzes peer-reviewed publications indexed in Scopus and Web of Science between 2023 and 2025. Bibliometric mapping and thematic synthesis are employed to identify methodological trends, conceptual clusters, and influential works. The findings reveal a clear methodological evolution from keyword-based retrieval toward hybrid models that combine deep semantic representations with citation-based authority measures. Results indicate that integrating bibliometric indicators such as citation frequency, co-citation networks, and authority ranking enhances retrieval relevance, interpretability, and decision-support potential in business law contexts. However, the review also identifies significant research gaps, including limited domain-specific validation, ethical concerns related to citation bias, and underutilization of bibliometric signals for predictive legal analytics. This study contributes theoretically by framing B-LIR as a complementary synthesis of legal semantics and bibliometric authority, and practically by highlighting its potential for corporate compliance, legal decision support, and regulatory intelligence systems. The paper concludes by outlining future research directions involving hybrid AI-bibliometric frameworks, citation context analysis, and explainable legal information systems tailored to business law]]>
