IMPACT OF BIG DATA AND ARTIFICIAL INTELLIGENCE ON SUPPLY CHAIN PERFORMANCE

Authors

  • sohail yousuf Karachi University Business School

Keywords:

Big Data, Artificial Intelligence, Supply Chain Performance, Demand Planning, forecasting uncertainties, competitiveness

Abstract

This study aimed to explore the influence of the various factors that may increase the supply chain performance in the Pakistani organizations. Using a quantitative research design, this study uses an adopted questionnaire to measure the perception of the mobile phone users based on their brands recommendations. The questionnaire had a demographic section and the constructs section that was having 5 points likert scale. The findings of the study show that the variables including artificial intelligence, demand planning, forecasting uncertainties, and competitiveness have a significant impact on the supply chain performance. Furthermore, the stakeholders should also consider the Big Data to improve the performance of the supply chain performance.

References

Addo-Tenkorang, R., & Helo, P. (2016). Big data applications in operations/supply-chain management: A literature review. Computers & Industrial Engineering

Baryannis, G., Validi, S., Dani, S., & Antoniou, G. (2018). Supply chain risk management and artificial intelligence: state of the art and future research directions. International Journal of Production Research

Duian, Y., Edwards, J., & Dwivedi, Y. (2019). Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda. International Journal Of Information Management

Govindan, K., Cheng, T., Mishra, N., & Shukla, N. (2018). Big data analytics and application for logistics and supply chain management. Transportation Research Part E: Logistics And Transportation Review

Hazen, B., Boone, C., Ezell, J., & Jones-Farmer, L. (2014). Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications. International Journal Of Production Economics

Kersten, W., Blecker, T., & Ringle, C. (2019). Artificial Intelligence and Digital Transformation in Supply Chain Management: Innovative Approaches for Supply Chains. Berlin: Epubli Gmbh

Mishra, D., Gunasekaran, A., Papadopoulos, T., & Childe, S. (2016). Big Data and supply chain management: a review and bibliometric analysis. Annals Of Operations Research

Pasonen, P. (2020). The Use of Artificial Intelligence in the Supply Chain Management in Finnish Large Enterprises

Singh Jain, A., Mehta, I., Mitra, J., & Agrawal, S. (2017). Application of Big Data in Supply Chain Management. Materials Today: Proceedings,

Toorajipour, R., Sohrabpour, V., Nazarpour, A., Oghazi, P., & Fischl, M. (2021). Artificial intelligence in supply chain management: A systematic literature review. Journal Of Business Research

Zhan, Y., & Tan, K. (2020). An analytic infrastructure for harvesting big data to enhance supply chain performance. European Journal Of Operational Research

Zhan, Y., & Tan, K. (2020). An analytic infrastructure for harvesting big data to enhance supply chain performance. European Journal Of Operational Research

Zhong, R., Newman, S., Huang, G., & Lan, S. (2016). Big Data for supply chain management in the service and manufacturing sectors: Challenges, opportunities, and future perspectives. Computers & Industrial Engineering,

Hassani, H., & Silva, E. (2015). Forecasting with Big Data: A Review. Annals Of Data Science,

He, Q., & Wang, J. (2018). Statistical process monitoring as a big data analytics tool for smart manufacturing. Journal Of Process Control,

O’Donovan, P., Leahy, K., Bruton, K., & O’Sullivan, D. (2015). An industrial big data pipeline for data-driven analytics maintenance applications in large-scale smart manufacturing facilities. Journal Of Big Data

Song, H., & Liu, H. (2016). Predicting Tourist Demand Using Big Data. Analytics In Smart Tourism Design,

Tao, F., Qi, Q., Liu, A., & Kusiak, A. (2018). Data-driven smart manufacturing. Journal Of Manufacturing Systems,

Usuga Cadavid, J., Lamouri, S., Grabot, B., Pellerin, R., & Fortin, A. (2020). Machine learning applied in production planning and control: a state-of-the-art in the era of industry 4.0. Journal Of Intelligent Manufacturing

Zheng, K., Zhang, Z., & Song, B. (2020). E-commerce logistics distribution mode in big-data context: A case analysis of JD.COM. Industrial Marketing Management,

Additional Files

Published

2021-08-24

How to Cite

yousuf, sohail. (2021). IMPACT OF BIG DATA AND ARTIFICIAL INTELLIGENCE ON SUPPLY CHAIN PERFORMANCE . Journal of Entrepreneurship and Business Innovation, 1(1). Retrieved from https://brjournals.comsresearch.com/index.php/jebi/article/view/59

Issue

Section

Articles