<![CDATA[Culinary small and medium-sized enterprises (SMEs) operate at the intersection of volatile demand, perishable inventories, labor-intensive processes, food-safety and halal-integrity requirements, and growing pressure to reduce waste and improve sustainability. Yet the relevant management literature remains fragmented. Digital transformation studies emphasize technology adoption and decision quality; Green Human Resource Management (Green HRM) research emphasizes employee capabilities and green behavior; food-service studies focus on waste prevention and forecasting; halal supply-chain studies focus on integrity and traceability; and supplier-selection research develops multi-criteria tools with limited integration into day-to-day SME decision cycles. This structured integrative review synthesizes recent peer-reviewed research published during 2022–2025 to develop a cross-functional framework for data-driven sustainability in culinary SMEs. Guided by recent good-practice recommendations for management reviews, the paper integrates evidence across digitalization, Green HRM, green operations, food-waste prevention, halal traceability, sustainable supplier selection, dynamic capabilities, and sustainable business performance. The resulting framework conceptualizes three antecedent capabilities—Green HRM capability, digital decision-support capability, and halal supply-chain integrity capability—that converge into a closed-loop green operational capability. This operational capability links sensing, decision, implementation, measurement, learning, and reconfiguration, thereby generating economic, environmental, human-organizational, and supply-chain integrity outcomes. Eight research propositions specify direct, mediated, and complementary relationships among the constructs. The paper contributes by shifting the debate from isolated green or digital practices toward an integrated decision architecture suitable for resource-constrained culinary SMEs. It also provides a research agenda for empirical validation and a design logic for future smart-green-halal decision-support systems without presuming that a particular technology has already been validated..]]>
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