European Journal of Accounting, Auditing and Finance Research (EJAAFR)

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Markov Chain and Inventory Management of Manufacturing Companies in Nigeria

Abstract

The inability to adapt and accept the deployment of new technologies in solving inventory-related problems have been some of the challenges manufacturing companies face in Nigeria. Some studies have suggested that the use of the Markov chain is capable of improving inventory management, however, the capabilities and effectiveness of the Markov chain in enhancing inventory management in manufacturing companies remain quite unclear. This study reviewed the Markov chain and inventory management of manufacturing companies as used in prior studies. The study adopted an exploratory research design in reviewing prior studies using relevant materials from journals, periodicals and relevant documented materials. The study through the review observed that the Markov chain has the ability to improve inventory management in manufacturing companies. The study also recommended that managers in manufacturing companies should improve their inventory management and manufacturing operations by adopting quantitative and scientifically aided decision-making modelling for their inventory management systems, such as linear programming, stochastic programming, mixed integer programming, genetic algorithms and the Markov chain decision-making processes.

Citation: Ajibade T, A.; Odunayo, J; Osunusi. A. K; Aguguom T. A. (2022) Markov Chain and Inventory Management of Manufacturing Companies in Nigeria, European Journal of Accounting, Auditing and Finance Research, Vol.10, No. 11, pp.21-35

Keywords: inventory management; Markov chain; mathematical estimations; stochastic process; supply-chain; warehousing.

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This work by European American Journals is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 Unported License

 

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Email ID: editor.ejaafr@ea-journals.org
Impact Factor: 7.77
Print ISSN: 2053-4086
Online ISSN: 2053-4094
DOI: https://doi.org/10.37745/ejaafr.2013

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