This study examines the impact of Halal Supply Chain Management (HSCM) on the sustainability performance of food SMEs in Padang City, evaluating consumer trust as a mediator and Lean Green Practices as a moderator. Driven by low halal certification rates despite rising consumer demand for halal and sustainable products, data were collected from food SME owners using a survey method and analyzed via PLS-SEM.The results reveal that HSCM does not directly affect sustainability performance. However, consumer trust fully mediates this relationship, demonstrating that HSCM drives sustainability performance by fostering consumer confidence in halal integrity and quality. Additionally, Lean Green Practices do not significantly moderate the relationship between HSCM and sustainability performance. Overall, the findings emphasize the necessity for SMEs to build consumer trust and adopt eco-efficient operational strategies to ensure long-term business sustainability.
Contribution to SDGs:
SDG 3: Good Health and Well-beingSDG 8: Decent Work and Economic GrowthSDG 9: Industry, Innovation and InfrastructureSDG 12: Responsible Consumption and ProductionSDG 16: Peace, Justice and Strong Institutions
Leidina Zein, Nilda Tri Putri, Alizar Hasan et al.· AJARCDE | Asian Journal of A...· 0 citations
Small manufacturing enterprises remain economically important but continue to face recurring operational constraints in planning, scheduling, quality control, maintenance, and process-data use. Generative artificial intelligence offers increasingly accessible support for these bounded operational tasks, yet adoption remains uneven because many firms lack a coherent basis for linking digital opportunity to internal resources, organizational knowledge, and measurable operational improvement. This study develops a conceptual framework that integrates the resource-based view and the knowledge-based view to explain generative artificial intelligence adoption in small manufacturing enterprises. Using an evidence-grounded theory-development approach, the study builds a staged framework that separates foundational conditions, perceived operational AI opportunity, organizational translation mechanisms, and performance outcomes. The framework theorizes internal resources and knowledge assets as foundational antecedents, perceived generative artificial intelligence potential in operational functions as the adoption bridge, knowledge integration and dynamic capability as organizing mechanisms, and performance improvement as the downstream consequence. It further explains how conceptual clarity can support later empirical reduction without losing the richer logic needed for practical implementation. The study also clarifies how the framework can guide applied information-system design through data-readiness assessment, bounded decision-support use cases, human-in-the-loop verification, and operational KPI monitoring. The resulting architecture strengthens theoretical explanation and operational design logic for generative artificial intelligence adoption in constrained manufacturing environments, while preserving clear boundaries for subsequent validation and applied deployment.
Ikhwan Arief, Alizar Hasan, N. T. Putri et al.· Jurnal RESTI (Rekayasa Siste...· 0 citations
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