Port logistics prediction with ARMA modeling: evidence of container flow in southern Ecuador
DOI:
https://doi.org/10.62451/rep.v3i3.133Keywords:
Logistics planning, container flow, ARMA model, time series, port operationsAbstract
ABSTRACT
The increasing operational complexity of ports and the volatility of container traffic have revealed structural limitations in logistics planning processes, particularly in Latin America. In this context, the present study proposes the application of an ARMA model to anticipate the weekly flow of import containers at a port in southern Ecuador, with the objective of strengthening operational response capacity through empirically validated estimates. The research followed a quantitative approach, with a non-experimental, cross-sectional design. Daily administrative records of port operations from January 2022 to May 2025 were used and aggregated into weekly frequency to reduce variability and capture more stable logistics patterns. The resulting weekly series, consisting of 174 observations, was subjected to stationarity tests and subsequently modeled under an ARMA (2,3) scheme, selected based on correlogram analysis and information criteria. The results indicate high dispersion in weekly container volumes, with a mean of 63.38 containers and notable asymmetries. The estimated model yielded statistically significant coefficients, with stationary, homoskedastic, and non-autocorrelated residuals, as well as a robust structure free from influential observations. The in-sample comparison revealed a strong alignment between observed and predicted values, validating the ARMA (2,3) model as a useful tool for port logistics planning in highly variable operational contexts.
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