Supply Chain Inventory Research Articles

Strategies for reducing healthcare supply chain inventory costs

PurposeThis study aims to identify empirically proven strategies for reducing healthcare supply chain inventory costs.Design/methodology/approachThe author conducted in-depth interviews in 80 hospitals covering different supply chains. The author treated the healthcare firm as the unit of analysis and examined Vrat's taxonomy of inventory models based on the static and dynamic complexity theories of inventory models to identify an appropriate approach. The author addressed 33 highly priced and moderately priced stock-keeping units from 1,432 items and test several inventory policies. Next, the author applied combinations of inventory models, testing probabilistic hybrid inventory models.FindingsThe study finds that medical supplies, equipment, and medications are indispensable for a quality healthcare system. Hence, healthcare supply chain management (SCM) professionals must adopt basic inventory cost-reduction strategies, implementing inventory software functionalities effectively and efficiently. This study shows that probabilistic hybrid inventory techniques in healthcare SCM effectively determine an optimal stocking level, significantly reducing costs.Research limitations/implicationsThis study analyzes data from primary care and (to some extent) secondary care institutions. Although tertiary and quaternary care systems do not represent a large portion of the healthcare system, future research should also address these highly specialized organizations' needs.Practical implicationsThis study proposes practical strategies to help continuously improve supply chain operations in healthcare organizations worldwide.Originality/valueThis study suggests probabilistic hybrid inventory models as empirically proven solutions for evaluating stock-keeping units in the healthcare sector. In doing so, the study provides a new healthcare supply chain approach, proposing a modified taxonomy of inventory models.

E-commerce supply chain inventory decisions and contract design considering sales effort and risk aversion

We introduce vendor-managed inventory (VMI) modes and retailer-managed inventory modes and use conditional value-at-risk to quantify the inventory manager’s risk aversion. Then, we compare the supply chain (SC) members’ optimal decisions and expected utilities when the online retail platform or the supplier conducts sales effort under different inventory modes. The cost-sharing contracts are introduced to optimize the SC performance. Some interesting findings are achieved: for VMI SC, SC members’ sales-effort preferences change with the wholesale price; the inventory manager’s risk-aversion degree has a significant impact on the SC members’ preferences for inventory management modes; there always exists appropriate cost-sharing ratio regions in which the SC members’ expected utilities can be improved. The corresponding research results can help to improve the operational effectiveness of different kinds of SCs.

An improvement of suppliermanufacture inventory system integrated with stochastic periodic review modeling for SMEs in Indonesia

SME LCR is one of the handicrafts SME in Yogyakarta, Indonesia. This SME produces several handicraft products such as storage baskets with various variants, and furniture. The process of ordering raw materials for SMEs is carried out when there is a demand for incoming products with the order quantity based on the raw material needs in meeting product demand. This study intends to provide recommendations for improving raw material governance to overcome demand fluctuations during the lead time and reduce the total cost of supply chain inventory by implementing an integrated inventory system. To meet the study aim, the EOQ Probabilistic P system (Period Review Method) is utilized. The P inventory model is distinguished into two models namely model P with backorder and model P with lost sales. Next, the Purchase Cost (Ob) and Procurement Costs are applied to the P model. The research method comprises through 3 stages: the pre-field stage, field stage, and the advanced stage (laboratory analysis, data analysis, and reporting). Given the results regarding banana and mendong raw materials supply, it can be observed that for banana raw materials, the reorder time interval that can generate the minimum total inventory cost for banana raw materials is 0.1470 years or 53 days with a total cost of IDR 263,721,081.72. Moreover, it is seen that the suggested model generates the minimum total cost of supply chain inventory compared to the SME policy and the individual model, which justifies the economic feasibility of this model.

Impact of carbon emission in two-echelon supply chain inventory decision with controllable deterioration and two-level trade-credit period

Impact of carbon emission in two-echelon supply chain inventory decision with controllable deterioration and two-level trade-credit period

Towards measuring SMEs performance amid the COVID-19 outbreak: exploring the impact of integrated supply chain drivers

PurposeThis study aims to explore supply chain disruptions during the COVID-19 pandemic in the small and medium enterprise (SME) sector in Oman. This study analyzes the impact on selected supply chain drivers – facilities, inventory, transportation and sourcing. It further intends to explore whether the supply chain challenges faced by the SME sector in Oman impact their overall performance.Design/methodology/approachThis study follows the quantitative technique of structural equation modeling to examine the proposed hypotheses. Data were collected electronically from SME managers/owners/entrepreneurs. All items were adopted and measured using a five-point Likert scale. One hundred and four complete and usable responses were received and considered.FindingsThe data was analyzed using SPSS and PLS statistical software. The model has been supported empirically, and the results showed a significant relationship between supply chain drivers and SMEs’ overall performance in Oman, except for supply chain inventory. The results have demonstrated that the COVID-19 pandemic has affected the SMEs’ supply chain drivers in Oman and, consequently, their overall performance.Practical implicationsThe results of this research can drive the development and implementation of a supply chain management strategy. This research will help policymakers induce the performance of SMEs affected by the COVID-19 pandemic. It would further enhance strategic sourcing and supplier performance considering the developed practices associated with the resource-based view.Originality/valueThe originality of the current study lies in its ability to empirically test two models within the Omani SMEs context while considering the supply chain drivers as a single variable or dividing it into four separate independent variables. This study would provide a preview for scholars for such empirical investigation and serve as a reference for policymakers and practitioners to maintain a management system of crises that may protect the SME supply chain drivers.

Applying digital twins for inventory and cash management in supply chains under physical and financial disruptions

ABSTRACT Supply chains (SCs) operate in a highly disruptive environment, where they face a variety of disruptions in product and cash flows. In such an environment, determining suitable inventory and cash replenishment policies ensures that cash and inventory are at the right place at the right time and provides a productive SC with high customer service levels. In this study, we first examine the impact of the disruptions in physical and financial flows on SC performance. We then, investigate the potential of a SC digital twin framework to help decision-makers in managing inventory and cash throughout the SC during disruption, currently absent from the literature. The proposed SC digital twin framework integrates machine learning (ML) and simulation to identify the inventory and cash replenishment policies that minimise the impact of the disruptions on SC performance. This approach proves effective in a SC disrupted by demand increase, capacity reduction, and credit purchase increase. Results show that employing the SC digital twin leads to a noticeable reduction in the cash conversion cycle for upstream members of the SCs. We observe that the cash conversion cycle for the upstream SC members is greatly impacted by the inventory policy employed by their immediate downstream members.

A Supply Chain Inventory Model for Deteriorating Products with Carbon Emission-Dependent Demand, Advanced Payment, Carbon Tax and Cap Policy

Emissions are a major contributor to climate change. Some nations are now concentrating their efforts on lowering carbon emissions. In many nations, carbon taxes and caps are the main tools that are used to attain this goal. The majority of the inventory retailer-supplier model assumed that the retailer’s order cost should be paid to the supplier at that time when he gets their order. Few suppliers can expect to receive the entire or a portion of the total cost in advance from retailers in this real-life situation, and others will offer prepayment in numerous equal installments. The advance payment offers the customer the lowest price for the order, but it has the largest carbon footprint. The advance payment has a great impact on carbon emissions and production. Therefore, this study looked at a carbon tax and cap supply chain inventory model for deterioration with carbon emission-dependent demand, and Three payment options: Preliminary, cash, and post-payment have been considered. The model was constructed by first assessing the overall cost of supply chain participants with carbon tax regulation. Finally, we illustrate numerical examples of the proposed approach and its outcomes. The implications of adjusting the various parameters on the optimal total cost are also graphically and tabularly discussed in depth. With the help of Mathematica version-12, a sensitivity analysis was also performed. Several management takeaways are also emphasized. These findings are incredibly managerial and enlightening for enterprises seeking profitability while still fulfilling their environmental duties, and this study is extremely useful for any country’s government policy.

An integrated lot-sizing policy for the inventory management of constrained multi-level supply chains: null-space method

ABSTRACT The null-space method (NSM) for solving the nonlinear programming (NLP) is used to transform an indefinite system into a symmetric positive definite one of a smaller dimension. In this paper, an NSM optimises the constrained NLP model of the inventories in multi-level supply chains (SCs). The presented NSM can give a direct method with a predictable level of fill without pivoting, decreasing the number of taken iterations to find the optimum solution. We transform the nonlinear equations into an NLP model, which NSM can solved. We also investigate the suitability of using null-space-based factorisations to derive sparse direct methods. Accordingly, an integrated lot-sizing model of the multi-level SC is designed and then optimised using the presented NSM. The paper's objectives are to find the optimum number of stockpiles and the economic period length for inventories. Some numerical examples demonstrate the applicability of the presented NSM to optimise the integrated lot-sizing policy of the multi-level SCs. The presented NSM shows satisfactory performance in optimum solutions, the number of iterations, infeasibility, optimality error, and complementarity.

Short lifetime product supply chain coordination and social benefit considering cannibalization effect and market segmentation

Short lifetime product retailers often face the challenge of cannibalization between new and old products, which can negatively impact their profitability. They attempt to influence consumers’ choices through price differentiation, resulting in internal competition regarding products’ age and price. The pricing decisions affect market demand, sales volume, and as a result, the whole supply chain (SC) profit. This paper coordinates inventory and pricing decisions in a short lifetime product supply chain (SLPSC), considering the cannibalization effect. The investigated SLPSC includes a supplier and a retailer operating in a segmented market. Firstly, the optimal decisions of the SLPSC members are obtained under decentralized and centralized decision-making structures. Then, a new coordination contract named wholesale price and double compensation (WPDC) is designed to motivate the SC members to shift from the decentralized structure to the centralized one. The findings indicate that the coordinated model creates more economic profitability for the whole SLPSC than the decentralized one. Furthermore, the proposed WPDC contract is more beneficial for the SLPSC from a social viewpoint, as it increases consumer surplus. The results also demonstrate that when consumers are more sensitive to the product’s freshness, a price differentiation policy is more profitable than the same pricing.

Effect of Preservation Technology on a Supply Chain Inventory Model with Time Varying Holding Cost, Price and Stock Dependent Demand under Replenishment Policy

Effect of Preservation Technology on a Supply Chain Inventory Model with Time Varying Holding Cost, Price and Stock Dependent Demand under Replenishment Policy

Providing a Mathematical Routing‐Inventory Model for the Drug Supply Chain Considering the Travel Time Dependence and Perishability on Multiple Graphs

High turnover in the pharmaceutical industry, the location of placebos in urban spaces, and the high rate of corruption of products in this industry are the distinguishing features of the drug supply chain. Thus, to survive and maintain competitive advantages in the current business environment, managers are active in this background to implement the theoretical foundations of supply chain management. One of the influential areas in this category is integrated inventory management, inventory control, and vehicle routing. Therefore, this study mainly aims to analyze and define a routing problem, inventory in the drug supply chain with perishable products, and travel time dependence on multiple graphs with travel time dependence. The Box–Jenkins forecasting method has been utilized to meet the study’s aim and deal with demand uncertainty. This method can identify the best pattern governing the data. Finally, the mathematical model is validated, and managerial perspectives are provided. The study results demonstrated the possibility of achieving cost‐saving and reducing product spoilage. Applying the solutions of this model can provide some inherent social and environmental advantages, including reducing traffic load and emissions.

Using digital twins for inventory and cash management in supply chains

In this paper, we investigate the potential of a supply chain (SC) digital twin framework to help decision makers in managing inventory and cash flows throughout the SCs. The proposed SC digital twin framework integrates machine learning (ML) and simulation to identify the inventory replenishment policies that minimize the cash conversion cycle of an SC, currently absent from the literature. The results show that the upstream member of an SC plays a pivotal role in mitigating the bullwhip effect and consequently minimizing the cash conversion cycle of the SC.

Impact of combining cross-docking and vendor managed inventory in a retail supply chain

Impact of combining cross-docking and vendor managed inventory in a retail supply chain

Optimization of the product service supply chain under the influence of presale services

<p style='text-indent:20px;'>For some high-value and technology-intensive products, customers first ask service integrators to provide presales consulting services for products with potential demand. Improving the service level of presales service will increase service costs and reduce profits, but it can also increase the demand for products. The change in market demand under the influence of services will result in a series of chain reactions, such as changes in supply chain inventory costs and distribution costs. Thus, this paper considers the changes in the product service supply chain (PSSC) network caused by changes in presale service levels and service prices from the overall perspective of the supply chain and chooses a reasonable service level and price so that service integrators and product suppliers in PSSCs can achieve a win-win situation while meeting customer needs. First, a PSSC network optimization model is established considering the presale service level and price. Then, a double-layer nested genetic algorithm with constraint reasoning is proposed to solve this problem. Finally, by calculating the PSSC case of a building material company that produces a water mist spray system for ships, the feasibility and practicability of the algorithm was verified.</p>

Study on Optimization of Supply Chain Inventory Management Based on Particle Swarm Optimization

Study on Optimization of Supply Chain Inventory Management Based on Particle Swarm Optimization

A Sustainable Supply Chain Inventory Model with Environmental Preferences for Shortages

Supply chain management has become more and more focused on environmental sustainability. We study several cooperation contracts within a green product supply chain and investigate their environmental performance. Throughout this paper, we examine a two-tier supply chain comprising a manufacturer and retailer, in which a manufacturer designs and produces a green product, and a retailer successfully markets it in its marketplace through green marketing. The demand is based on the selling price, the green degree, and the preferences of the consumers. Shortages are allowed and fully backlogged. We have provided a closed-form solution for determining the optimal values of green degree, selling price, and replenishment cycle. Moreover, the global optimality of the objective function is discussed analytically and numerically, along with a perfect counter plot, which provides a peek at the center of the plot. A sensitivity analysis of key parameters is provided, along with numerical examples with graphical representations, to validate the model.

Research on Enterprise Supply Chain Optimization Model and Algorithm Based on Fuzzy Clustering

Reasonable logistics distribution network structure can not only effectively reduce the cost of logistics enterprises themselves but also reduce the social cost. Through effective supply chain management, enterprises can significantly reduce costs, improve competitiveness, and enhance their ability to resist risks. Because the single-level distribution network structure of production enterprises is not suitable for large-scale logistics distribution, this paper proposes a distribution network structure design that accords with economies of scale and establishes an enterprise supply chain optimization model based on the fuzzy clustering algorithm. Using this optimization method to optimize the inventory of enterprise logistics supply chain, the operation is fast, the result is correct and reasonable, and it can provide good decision support for the distribution network of logistics enterprises. Through information technology and modern management technology, we should effectively control and coordinate the logistics, information flow, and capital flow in the production and operation process and organically integrate the internal supply chain with the external supply chain for management, so as to achieve the goal of global optimization.

Input Quantity Decision and Coordination Mechanism with Two Production Chances and Yield Uncertainty

Conducting a second production run can improve the company’s capability of meeting the market demand. Few works examine optimal input quantity decisions under the mode with two production chances considering demand and yield uncertainty. We propose a vendor-managed inventory (VMI) supply chain with one supplier and one retailer. The supplier has two production chances and faces yield uncertainty in each production run. It is necessary for the supplier to make trade-offs between the cost and benefit of the second production run, then decide whether to conduct the second production run. We investigate the supplier’s optimal input quantity decision in each production run and obtain the supply chain members’ expected profits. As a comparison, the mode with one production chance is also developed. We find that two production chances can help improve the performance of the supply chain under yield uncertainty. A revenue-sharing contract is introduced to coordinate the supply chain with two production chances, and efficient profit allocation is achieved through adjusting the revenue-sharing ratio and the wholesale price. An extension is conducted for a sensitivity analysis of unit punishment cost on the supplier’s input quantity decisions.

Impact of Variable Deterioration Rate of Perishable Food Items on Multi-Echelon Distribution Chains

Customer satisfaction is the backbone of any business entity and supply chain optimization plays a vital role in customer satisfaction efforts. Supply chain inventory control is one of the scientific supply chain optimization methods for determining proper inventory levels at different stages or echelons of the supply chain to meet the requirements of the customers. The intention is to supply right type of material at exact time in appropriate quantities and at competitive rates. Supply chain inventory costs consist of costs to store, track and insure materials. Inventories that mishandled create substantial financial problems for a business, whether the mismanagement results in an inventory accumulation or an inventory shortage. Therefore, an examination of the right quantities to be kept in stock to meet the requirements, the strategic location, storage facilities and recordings of the goods or items should be done systematically such that the desired degree of service can be provided at competitive prices or at minimum ultimate cost. Major objective of inventory control in a multi echelon supply chain is to optimize inventory cost elements like transportation cost, carrying cost, holding cost and all other inventory related costs at all supply chain stages with an elevated service level at the end customer point. The supply chain inventory control becomes tough when the handling material is a perishable one as its deterioration rate is variable rather than constant. This article provides the study results of the deterioration rate of a perishable edible inventory at different selected environmental conditions. The focus of this article is to introduce a mathematical equation for the deterioration rate of the selected perishable inventory which is inevitable for the formulation of inventory models for its supply chain echelons.

Dynamic interactive control of inventory in a dual-channel supply chain under stochastic demand: Modelling and empirical studies

Demand uncertainties and delivery delays are the fundamental causes of poor inventory control, especially in a dual-channel supply chain. Considering the impact of stochastic demand on the dual-channel inventory. this study explores the dynamic interactions of online–offline purchase–sale–stock systems under the decentralised, centralised, and cross-replenishment inventory controls. Hence, this study constructs a dynamic inventory model with delivery delays, based on the feedback and proportional–integral–derivative control, to optimise the influences between the replenishment cycles and online–offline channels’ interactions. The results show that, when the channels follow different sales strategies and the warehouses are proximally located, the cross-replenishment inventory strategy reduces the residual inventory. When the channels follow the same sales strategies, the centralised inventory control reduces the residual inventory. These findings demonstrate that the dynamic interactive inventory model can contribute towards optimising inventory operations. This study presents substantial insights for improving the overall performances of the dual-channel supply chain from the perspectives of dynamic and interactive inventory control, warehouse and retail network optimisation, and resource allocation.