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Your search keyword '"Kamble, Sachin"' showing total 420 results
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8. Investments in Industry 4.0 technologies and supply chain finance: approaches, framework and strategies.

Author

Gunasekaran, Angappa, Kamble, Sachin, Ghadge, Abhijeet, and Kumar, Vikas

Subjects
DURABLE consumer goods, INDUSTRY 4.0, RECESSIONS, WORKING capital, LOANS
Abstract

Investments in Industry 4.0 are making a significant impact on various sectors by integrating advanced digital technologies. The chances of financial losses for organisations' investments due to new technologies are high, and there is a low possibility of recovering the investments. Reduced spending on long-term costs by organisations due to low investments and consumer demand for durable goods has resulted in sluggish global trade in advanced and emerging markets. Challenges have arisen for companies in securing loans for investments due to past economic slowdowns, resulting in increased corporate borrowing expenses. The literature acknowledges Supply Chain Finance (SCF) as a vital approach to optimising efficiency. Industry leaders are turning to SCF as high costs persist during the transformation process for manufacturers. SCF can unlock substantial working capital by improving cash flow, which can be used to back essential business initiatives. This evolving environment presents opportunities and requires a deeper investigation of possibilities and challenges in advancing SCF to support Industry 4.0 efforts. Given this, the Special Issue released in the International Journal of Production Research pushes forward this crucial research focus. Nine articles accepted in this Special Issue used different methodologies, theories, and contexts to address research needs and offer valuable insights on supply chain finance and industry 4.0 investment challenges. This Editorial summarises these studies, emphasising possibilities for future research pathways. [ABSTRACT FROM AUTHOR]

Published
2024
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16. How to use no-code artificial intelligence to predict and minimize the inventory distortions for resilient supply chains.

Author

Jauhar, Sunil Kumar, Jani, Shashank Mayurkumar, Kamble, Sachin S., Pratap, Saurabh, Belhadi, Amine, and Gupta, Shivam

Subjects
MACHINE learning, ARTIFICIAL intelligence, SUPPLY chains, INVENTORY control, ELECTRONIC commerce, INVENTORIES, SUPPLY chain disruptions
Abstract

Consumers' dramatic demand has a pernicious effect throughout the supply chain. It exacerbates inventory distortion because of significant revenue loss caused by stock-level issues. Despite the availability of several forecasting techniques, large organisations, manufacturing firms, and e-commerce websites collectively lose around $1.8 trillion annually to inventory distortion. If this problem is solved, sales may increase by 10.3 percent. The businesses are concerned about mitigating this loss. Artificial intelligence (AI) can play a significant role in building resilient supply chains. However, developing AI models consumes time and cost. In this paper, we propose a No Code Artificial Intelligence (NCAI) enabling non-technical companies to build machine learning models based on production quantity and inventory replenishment. The development of the NCAI model is fast and inexpensive. However, little research deals with applying NCAI to operations and supply chain problems. Addressing the existing gap, we show the application of NCAI in the retail industry. [ABSTRACT FROM AUTHOR]

Published
2024
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