全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

An Overview of the Application of Big Data in Supply Chain Management and Adaptation in Nigeria

DOI: 10.4236/jcc.2024.128003, PP. 37-51

Keywords: Big Data, IoT, Optimization, Right Data, Supply Chain, Transport Management

Full-Text   Cite this paper   Add to My Lib

Abstract:

That the world is a global village is no longer news through the tremendous advancement in the Information Communication Technology (ICT). The metamorphosis of the human data storage and analysis from analogue through the jaguars-loom mainframe computer to the present modern high power processing computers with sextillion bytes storage capacity has prompted discussion of Big Data concept as a tool in managing hitherto all human challenges of complex human system multiplier effects. The supply chain management (SCM) that deals with spatial service delivery that must be safe, efficient, reliable, cheap, transparent, and foreseeable to meet customers’ needs cannot but employ bid data tools in its operation. This study employs secondary data online to review the importance of big data in supply chain management and the levels of adoption in Nigeria. The study revealed that the application of big data tools in SCM and other industrial sectors is synonymous to human and national development. It is therefore recommended that both private and governmental bodies should key into e-transactions for easy data assemblage and analysis for profitable forecasting and policy formation.

References

[1]  Bello-Orgaz, G., Jung, J.J. and Camacho, D. (2016) Social Big Data: Recent Achievements and New Challenges. Information Fusion, 28, 45-59.
https://doi.org/10.1016/j.inffus.2015.08.005
[2]  Chen, M., Mao, S. and Liu, Y. (2014) Big Data: A Survey. Mobile Networks and Applications, 19, 171-209.
https://doi.org/10.1007/s11036-013-0489-0
[3]  Chen, H., Chiang, R.H.L. and Storey, V.C. (2012) Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, 36, 1165-1188.
https://doi.org/10.2307/41703503
[4]  Murdoch, T.B. and Detsky, A.S. (2013) The Inevitable Application of Big Data to Health Care. JAMA, 309, 1351-1352.
https://doi.org/10.1001/jama.2013.393
[5]  Mayilvaganan, M. and Sabitha, M. (2013) A Cloud-Based Architecture for Big-Data Analytics in Smart Grid: A Proposal. 2013 IEEE International Conference on Computational Intelligence and Computing Research, Enathi, 26-28 December 2013, 1-4.
https://doi.org/10.1109/iccic.2013.6724168
[6]  Zhu, L., Yu, F.R., Wang, Y., Ning, B. and Tang, T. (2019) Big Data Analytics in Intelligent Transportation Systems: A Survey. IEEE Transactions on Intelligent Transportation Systems, 20, 383-398.
https://www.ieee.org/publications/rights/index.html
https://doi.org/10.1109/tits.2018.2815678
[7]  Fernandez, S. and Ito, T. (2015) Driver Behavior Model Based on Ontology for Intelligent Transportation Systems. 2015 IEEE 8th International Conference on Service-Oriented Computing and Applications (SOCA), Rome, 19-21 October 2015, 227-231.
https://doi.org/10.1109/soca.2015.44
[8]  Gudivada, V.N., Baeza-Yates, R. and Raghavan, V.V. (2015) Big Data: Promises and Problems. Computer, 48, 20-23.
https://doi.org/10.1109/mc.2015.62
[9]  Harford, T. (2014) Big Data: A Big Mistake? Significance, 11, 14-19.
https://doi.org/10.1111/j.1740-9713.2014.00778.x
[10]  Sha, K. and Zeadally, S. (2015) Data Quality Challenges in Cyber-Physical Systems. Journal of Data and Information Quality, 6, 1-4.
https://doi.org/10.1145/2740965
[11]  Sheppard, S.A. and Terveen, L. (2011) Quality Is a Verb: The Operationalization of Data Quality in a Citizen Science Community. Proceedings of the 7th International Symposium on Wikis and Open Collaboration, Mountain View, 3-5 October 2011, 29-38.
https://doi.org/10.1145/2038558.2038565
[12]  Xu, H. (2015) What Are the Most Important Factors for Accounting Information Quality and Their Impact on AIS Data Quality Outcomes? Journal of Data and Information Quality, 5, 1-22.
https://doi.org/10.1145/2700833
[13]  Barnaghi, P., Bermudez-Edo, M. and Tönjes, R. (2015) Challenges for Quality of Data in Smart Cities. Journal of Data and Information Quality, 6, 1-4.
https://doi.org/10.1145/2747881
[14]  Bansal, S.K. and Kagemann, S. (2015) Integrating Big Data: A Semantic Extract-Transform-Load Framework. Computer, 48, 42-50.
https://doi.org/10.1109/mc.2015.76
[15]  Martin, N., Poulovassilis, A. and Wang, J. (2014) A Methodology and Architecture Embedding Quality Assessment in Data Integration. Journal of Data and Information Quality, 4, 1-40.
https://doi.org/10.1145/2567663
[16]  Na’im, A., Crawl, D., Indrawan, M., Altintas, I. and Sun, S. (2010) Monitoring Data Quality in Kepler. Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing, Chicago, 21-25 June 2010, 560-564.
https://doi.org/10.1145/1851476.1851558
[17]  Sneed, H.M. and Majnar, R. (2011) A Process for Assessing Data Quality. Proceedings of the 8th International Workshop on Software Quality, Szeged, 4 September 2011, 50-57.
https://doi.org/10.1145/2024587.2024599
[18]  Gudivada, V.N., Baeza-Yates, R. and Raghavan, V.V. (2015) Big Data: Promises and Problems. Computer, 48, 20-23.
https://doi.org/10.1109/mc.2015.62
[19]  Qin, Y., Sheng, Q.Z., Falkner, N.J.G., Dustdar, S., Wang, H. and Vasilakos, A.V. (2016) When Things Matter: A Survey on Data-Centric Internet of Things. Journal of Network and Computer Applications, 64, 137-153.
https://doi.org/10.1016/j.jnca.2015.12.016
[20]  Batini, C., Cappiello, C., Francalanci, C. and Maurino, A. (2009) Methodologies for Data Quality Assessment and Improvement. ACM Computing Surveys, 41, 1-52.
https://doi.org/10.1145/1541880.1541883
[21]  Ganti, V. and Sarma, A.D. (2013) Data Cleaning: A Practical Perspective (Synthesis Lectures on Data Management). Morgan & Claypool Publishers.
[22]  Loshin, D. (2010) The Practitioner’s Guide to Data Quality Improvement. Morgan Kaufmann.
[23]  Federal Highway Administration (FHWA) (2011) Summary of Travel Trends: 2009 National Household Travel Survey. Report No. FHWA-PL-ll-022.
[24]  European Union Agency for Railways (EUAR) (2016) ‘Big Data in Railways’ Common Occurrence Reporting Programmed, Technical Document on Big-Data in Railways. ERA-PRG-004-TD-003V1.0.
[25]  Nwanga, M.E., Onwuka, E.N., Aibinu, A.M. and Ubadike, O.C. (2015) Impact of Big Data Analytics to Nigerian Mobile Phone Industry. 2015 International Conference on Industrial Engineering and Operations Management (IEOM), Dubai, 3-5 March 2015, 1-6.
https://www.researchgate.net/publication/283802052_Impact_of_Big_Data_Analytics_to_Nigerian_mobile_phone_industryl
https://doi.org/10.1109/ieom.2015.7093810
[26]  Blumenstock, J., Lain, J., Smythe, I., and Vishwanath, T. (2021) Using Big Data and Machine Learning to Locate the Poor in Nigeria.
https://blogs.worldbank.org/en/opendata/using-big-data-and-machine-learning-locate-poor-nigeria
[27]  Michael, O.T., Paul, O.A., Wade, D., Kaniki, F.R., Ayosanmi, O.S., Faith, A.O., et al. (2019) Blockchain and Big Data Analytics in the Optimization of Nigeria Vaccine Supply Chain. Global Scientific Journals, 7, p9529.
https://www.globalscientificjournal.com/
https://doi.org/10.29322/IJSRP.9.11.2019.p9529
[28]  Ibanga, I. (2021) Big Data, Entertainment and the Digital Economy In Nigeria, in Contributors, Opinion, Premium Times.
https://www.premiumtimesng.com/opimiom/44064-big-data-entertainment-and-the-digital-economy--in-nigeria-by-iyene-ibanga.html
[29]  Ojoye, T. (2017) Maximising Big Data in Africa.
https://punchng.com/maximising-big-data-in-africa/

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133