Purpose: This study presents a systematic literature review that provides a broad and holistic view of how machine learning can be used and integrated to enhance decision-making in various areas of the supply chain, highlighting its combination with other techniques and models....

The survival of a company is highly dependent on the management of its working capital. Effective working capital management can lead to greater profitability. Insufficient working capital or liquidity shortages can severely hinder profitability and operational sustainability. The primary...

Purpose: The main purpose of this article is to systematically review the papers published in the period 2005-2020 about the integration of production, inventory and distribution activities in perishable supply chains. Design/methodology/approach: The proposed research methodology is based on...

Background: The advancement of Industry 4.0 technologies has affected every aspect of supply chains. Recently, enterprises have tried to create more value for their businesses by tapping into these new technologies. Warehouses have been one of the most critical sections in a supply chain...

Background: Stocks of raw materials and finished products are found in all units of logistics systems and require significant financial means of management. For this reason, scientifically justified approaches to stock management and cost minimisation must be explored. Despite the existence of...

Purpose: Demand-Driven Distribution Resource Planning (DDDRP) has recently been proposed in the literature to deal with higher supply networks complexity, shorter customer tolerance times, and inaccurate forecasts. The DDDRP requires to position inventory buffers in critical network nodes, where...

We study a multi-product maritime inventory routing problem (MIRP) with sailing time uncertainty. We explicitly consider the replanning that happens after uncertainty is revealed. The objective is to determine the stability of the adjusted plans after the occurrence of an uncertain event and to...

Purpose: This study extends previous research by exploring the key lessons learned by the pharmaceutical industry in South Africa from the COVID-19 pandemic supply chain disruptions. Design/methodology/approach: Having embraced the interpretivist paradigm, 25 supply chain professionals were...

This research focuses on accurately forecasting steel wire mesh demand to ensure timely order fulfillment. Various univariate time series forecasting methods were employed, including Prophet, Support Vector Regression (SVR), 1-Dimensional Convolutional Neural Network (1D-CNN), Recurrent Neural...

This study examines the challenges of two warehouses operating under Last-In-First-Out (LIFO) order policies in inventory management, including unpredictable demand patterns, the decay of Weibull distribution, and the need to reduce carbon emissions by adopting green technology. The research...

Purpose - Inventory is a crucial part of a systematic supply chain of a business. Small firms mostly neglect inventory management (IM) by accumulating excessive inventory for a time. The study aims to examine the IM practices of small and medium enterprises (SMEs) in Bangladesh....

Background: A logistics network plan could be a major key issue due to its effect on supply chain effectiveness and responsiveness. This study aims to investigate the inventory location in the humanitarian logistics response stage using a three-level logistics network to integrate...

This study investigates a non-instantaneous deteriorating two-warehouse inventory problem with allowable delay payments under inflation. The objective is to maximize the total profit per unit of time by determining the optimal order quantity, the product's selling price, and the business cycle...

Spare parts are particularly challenging to forecast due to their lumpiness and representing a significant part of companies’ expenditures, so even small improvement in new approaches can considerably reduce these items’ total inventory. This paper aims to present a new hybrid forecasting...

Spare parts are particularly challenging to forecast due to their lumpiness and representing a significant part of companies' expenditures, so even small improvement in new approaches can considerably reduce these items' total inventory. This paper aims to present a new hybrid forecasting method...

Background: Traditional procurement and price negotiation methods in public hospitals in Thailand involve group purchasing agreements and bulk orders, posing challenges to improving inventory management efficiency. The vendor-managed inventory (VMI) model is a promising alternative for enhancing...

Background: In the current global market, supply chains are increasingly complex, necessitating agile and sustainable management strategies. Traditional analytical methods often fall short in addressing these challenges, creating a need for more advanced approaches. Methods: This study leverages...

Background: Efficient inventory management is critical for sustainability in supply chains. However, maintaining adequate inventory levels becomes challenging in the face of unpredictable demand patterns. Furthermore, the need to disseminate demand-related information throughout a company often...

Even in the context of Industry 4.0, conventional warehouse management continues to encounter challenges. Amidst these obstacles, innovative solutions are imperative. Order picking, a critical process with significant implications for customer service, remains labor-intensive within warehousing...