Warehouse Automation Implementation Environment: Case of Central Warehouse Management in Mali, West Africa

Maricel Co; Rohana Sham; Noraini Ahmad; Steve Acesor

doi:10.21834/e-bpj.v8i26.5127

Authors

Maricel Co School of Business, Asia Pacific University of Technology and Innovation, Malaysia
Rohana Sham School of Business, Asia Pacific University of Technology and Innovation, Malaysia
Noraini Ahmad School of Business, Asia Pacific University of Technology and Innovation, Malaysia
Steve Acesor School of Business & Accountancy, Manuel S. Enverga University, Philippines

DOI:

https://doi.org/10.21834/e-bpj.v8i26.5127

Keywords:

Automation, Environment, Implementation, Warehouse

Abstract

The implementation of warehouse automation has proven to be an effective way to increase productivity and inventory accuracy, lower labor costs, and improve safety in the warehouse environment. This research aims to investigate the factors contributing to the success of warehouse automation implementation. This study offers a unique and modern warehouse automation environment model as a solution for complete implementation in warehouse automation operations. The study was conducted in Mali, West Africa. A total of 100 responses were collected among warehouse managers through an online Microsoft Forms survey. Smart PLS version 4.0 software was used to analyze the data.

References

Adamczak, M., Cyplik, P., & Fidlerova, H. (2022). The Relationship between the level of Choosing Competences of Operational Employees and the Acceptance of Work in an Automated Warehouse. DOI: https://doi.org/10.35808/ersj/2953

Adenigbo, A. J., Mageto, J., & Luke, R. (2023). Effect of the adoption of technology innovations in the air cargo logistics industry in South Africa. Southern African Transport Conference.

Arasu, R. (2022). Stock Accuracy During The Warehouse Transfer Process Of India Distribution Centre (Idc), Caterpillar. Journal of Production, Operations Management and Economics (JPOME) ISSN 2799-1008, 2(02), 7-9. DOI: https://doi.org/10.55529/jpome.22.7.9

Baid, G., Cook, D. E., Shafin, K., Yun, T., Llinares-López, F., Berthet, Q., ... & Carroll, A. (2023). DeepConsensus improves the accuracy of sequences with a gap-aware sequence transformer. Nature Biotechnology, 41(2), 232-238. DOI: https://doi.org/10.1038/s41587-022-01435-7

Basaldúa, M. S., & Cruz Di Palma, R. J. (2023). Production, Supply, Logistics, and Distribution. In Springer Handbook of Automation (pp. 893-907). Cham: Springer International Publishing. DOI: https://doi.org/10.1007/978-3-030-96729-1_40

Co & Baldovino (2023). Fixed Assets Inventory Management of an International Organization: Issues and Challenges Amidst Covid-19 Pandemic Proceedings of the 10th International Conference on Business, Accounting, Finance and Economics (BAFE 2022) Atlantis Press https://doi.org/10.2991/978-2-494069-99-2_18 DOI: https://doi.org/10.2991/978-2-494069-99-2_18

Đurđević, D., Andrejić, M., & Pavlov, N. (2022). „Framework for improving warehouse safety”. In Proceedings of the 5th LOGIC Conference (pp. 304-314).

Fuller, D., Colwell, E., Low, J., Orychock, K., Tobin, M. A., Simango, B., ... & Taylor, N. G. (2020). Reliability and validity of commercially available wearable devices for measuring steps, energy expenditure, and heart rate: systematic review. JMIR mHealth and uHealth, 8(9), e18694. DOI: https://doi.org/10.2196/18694

Hair, J. F., Hult, G. T. M., Ringle, C. M., and Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 3rd Ed., Sage: Thousand Oaks. DOI: https://doi.org/10.1007/978-3-030-80519-7

Hair, J.F., Risher, J.J., Sarstedt, M., Ringle, C.M., 2019.When to use and how to report the results of PLS-SEM. Eur. Bus. Rev. 31 (1), 2–24. DOI: https://doi.org/10.1108/EBR-11-2018-0203

Hair, J.F., Sarstedt, M., Hopkins, L., Kuppelwieser, V.G., 2014. Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. Eur. Bus. Rev. 26 (2), 106–121. https://doi.org/10.1108/EBR-10-2013-0128. DOI: https://doi.org/10.1108/EBR-10-2013-0128

He, Z., Zhang, X., Jones, S., Hauert, S., Zhang, D., & Lepora, N. F. (2023). TacMMs: Tactile Mobile Manipulators for Warehouse Automation. IEEE Robotics and Automation Letters. DOI: https://doi.org/10.1109/LRA.2023.3287363

Karim, N. H., Abdul Rahman, N. S. F., Md Hanafiah, R., Abdul Hamid, S., Ismail, A., Abd Kader, A. S., & Muda, M. S. (2021). Revising the warehouse productivity measurement indicators: Ratio-based benchmark. Maritime Business Review, 6(1), 49-71. DOI: https://doi.org/10.1108/MABR-03-2020-0018

Karpova, N. P. (2022). Modern Warehouse Management Systems. In Digital Technologies in the New Socio-Economic Reality (pp. 261-267). Springer International Publishing. DOI: https://doi.org/10.1007/978-3-030-83175-2_34

Kosmol, F. Reimann, L. Kaufmann (2019). You’ll never walk alone: why we need a supply chain practice view on digital procurement J. Purch. Supply Manag., 25 (4) (2019), p. 100553, DOI: https://doi.org/10.1016/j.pursup.2019.100553

Lee, C. C., He, Z. W., & Yuan, Z. (2023). A pathway to sustainable development: Digitization and green productivity. Energy Economics, 124, 106772. DOI: https://doi.org/10.1016/j.eneco.2023.106772

Lee, H., Hong, J., & Jeong, J. (2022). MARL-Based Dual Reward Model on Segmented Actions for Multiple Mobile Robots in Automated Warehouse Environment. Applied Sciences, 12(9), 4703. DOI: https://doi.org/10.3390/app12094703

Lin, Y. S., Chai, C. W., & Chao, T. W. (2022, February). Case study on the safety and disaster prevention system of factory intelligent warehouse. In 2022 IEEE 5th Eurasian Conference on Educational Innovation (ECEI) (pp. 391-395). IEEE. DOI: https://doi.org/10.1109/ECEI53102.2022.9829509

Mohamud, I. H., Kafi, M. A., Shahron, S. A., Zainuddin, N., & Musa, S. (2023). The Role of Warehouse Layout and Operations in Warehouse Efficiency: A Literature Review. Journal Européen des Systèmes Automatisés, 56(1). DOI: https://doi.org/10.18280/jesa.560109

Olalere, A. (2022), Impact of Data Warehouse on Organization Development and Decision making (A Case study of United Bank for Africa and Watchlocker PLC).

Pandey, A., Flam, R., Mohammed, R., & Kalidindi, A. (2023). Emulation and digital twin framework for the validation of material handling equipment in warehouse environments.

Pollock, D., Peters, M. D., Khalil, H., McInerney, P., Alexander, L., Tricco, A. C., ... & Munn, Z. (2023). Recommendations for the extraction, analysis, and presentation of results in scoping reviews. JBI evidence synthesis, 21(3), 520-532. DOI: https://doi.org/10.11124/JBIES-22-00123

Rose, J., & Johnson, C. W. (2020). Contextualizing reliability and validity in qualitative research: Toward more rigorous and trustworthy qualitative social science in leisure research. Journal of leisure research, 51(4), 432-451. DOI: https://doi.org/10.1080/00222216.2020.1722042

Sham, R., Wei, V. L., Setapa, M., & Kamal, M. A. (2023). Online Purchase Environment Using Blockchain-Based Solutions: An acceptance of online grocers. Environment-Behaviour Proceedings Journal, 8(23), 223-229. DOI: https://doi.org/10.21834/ebpj.v8i23.4518

Sharma, P. (2023). Cloud Computing for Supply Chain Management and Warehouse Automation: A Case Study of Azure Cloud. DOI: https://doi.org/10.47893/IJSSAN.2023.1227

Sihombing, P. R., & Arsani, A. M. (2022). Aplikasi SmartPLS Untuk Statistisi Pemula.