Analysis of the Influence of Supply Chain Management on the Operational Efficiency of Capture Fisheries Business in Ambon City: Multiple Linear Regression Approach
DOI:
https://doi.org/10.61132/digitalinnovation.v3i3.753Keywords:
Ambon City, Capture Fisheries, Multiple Linear Regression, Operational Efficiency, Supply Chain ManagementAbstract
The fisheries sector plays a vital role in Indonesia's maritime economy, yet capture fisheries enterprises in Ambon City continue to face persistent operational constraints, including limited cold-chain facilities, seasonal catch dependency, and poorly structured coordination among fishermen, collectors, and end consumers, all of which contribute to information asymmetry and suboptimal supply chain performance. This study aims to describe the current condition of supply chain management practices, assess the level of operational efficiency achieved, and examine the influence of supply chain management on operational efficiency among capture fisheries businesses in Ambon City. A quantitative associative approach was employed, involving 110 respondents selected through purposive sampling, with data analyzed using multiple linear regression after classical assumption testing confirmed normality, absence of multicollinearity, and homoscedasticity. The findings reveal that demand planning, procurement and distribution, and information integration each exert a significant and positive partial effect on operational efficiency, with demand planning demonstrating the strongest contribution (B=0.438), followed by procurement and distribution (B=0.353) and information integration (B=0.205). Simultaneously, these three dimensions explain 45.5 percent of the variance in operational efficiency (R²=0.455; F=29.53; p=0.000). These results indicate that although supply chain management awareness exists among business actors, implementation remains fragmented due to infrastructure and communication limitations. It is recommended that future research expand the sampling area, incorporate additional variables such as institutional capacity and policy support, and apply mediation or moderation approaches to deepen understanding of the underlying mechanisms.
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