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Inventory control model based on Big Data, EOQ, ABC and forecast to increase productivity in a hardware SME

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Authors
Quiroz-Flores, Juan Carlos
Caceres-Paitan, Darien
Avila-Nolasco, Rocio
Issue Date
2023-02-01
Keywords
ABC analysis
Big Data
EOQ
Increased productivity
inventory control
SMEs
Commercial sector
SMEs (Small and Medium-sized Enterprises)
GDP (Gross Domestic Product)
Peruvian economy
Inventory management
Hardware sector
Profitability
Inventory control model
Distribution efficiency
Simulation
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Metadata
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Publisher
Association for Computing Machinery
Journal
ACM International Conference Proceeding Series
URI
http://hdl.handle.net/10757/668736
DOI
https://doi.org/10.1145/3588243.3588245
Additional Links
https://dl.acm.org/doi/10.1145/3588243.3588245
Abstract
Within the commercial sector, SMEs represent more than 90% of all companies; they are responsible for 50% of GDP and generate between 60% and 70% of employment worldwide, which is why they are critical in the Peruvian economy. However, through an exhaustive review of the literature and sectoral analysis, we concluded they have a high risk of failure in the short term due to various problems, such as poor inventory management. In Peru, the provisions for carrying out inventories usually have a ratio of between 1% and 1.4% of the total inventory stock; thus, SMEs belonging to the hardware sector more frequently present this problem that affects the profitability of their companies. For this reason, the need arises to design an inventory control model that increases the productivity of hardware SMEs. After the pilot implementation of the first component, an increase in distribution efficiency of 11% is achieved, and its effectiveness is supported by simulating the entire model, obtaining the same results.
Type
info:eu-repo/semantics/article
Rights
info:eu-repo/semantics/embargoedAccess
Language
eng
ae974a485f413a2113503eed53cd6c53
https://doi.org/10.1145/3588243.3588245
Scopus Count
Collections
Ingeniería de Gestión Empresarial

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