Using Artificial Intelligence in Inbound Logistics Decision-Making
DOI:
https://doi.org/10.5281/zenodo.20834318Keywords:
artificial intelligence, inbound logistics, logistics decision-making, inventory management, operational efficiencyAbstract
In dynamic business environments, efficiency in inbound logistics decision-making emerged as a key factor for organizational competitiveness. In this context, artificial intelligence (AI) emerged as a strategic tool for optimizing procurement processes, inventory management, and resource planning. The objective of this study was to analyse the influence of artificial intelligence on inbound logistics decision-making in a private company located in Chimbote. The research was conducted using a quantitative approach, with a non-experimental and correlational design. The population consisted of 50 employees, and a census method was applied. Data were collected through a structured questionnaire using a five-point Likert scale, which achieved a Cronbach’s alpha coefficient of 0.85, indicating high reliability. The results showed that 40% of employees considered the adoption of artificial intelligence important, while 36% rated it as very important, representing an overall positive assessment of 76%. Furthermore, more than 70% of respondents perceived improvements in supply planning, inventory management, and resource optimization. Inferential analysis revealed a moderate and statistically significant positive relationship between artificial intelligence and inbound logistics decision-making (ρ = 0.545; p < 0.001). It was concluded that the implementation of AI-based tools significantly contributed to improving operational efficiency, reducing uncertainty, and strengthening procurement management within the organization.
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