Inventory Management Strategies Research Articles

Assessment of Clinical Laboratory Personnel Protective Equipment Inventory Management During COVID-19 Pandemic in the Philippines

Introduction/ObjectiveCOVID-19 pandemic has brought a worldwide scarcity of personal protective equipment, which prompted medical technologists to explore the inventory management strategies, specifically the maintenance, conservation, and alternative use of personal protective equipment. The study aimed to assess the impact of these strategies on the personal protective equipment shortage in laboratories, as well as identify and describe the clinical laboratory supply and demand of personal protective equipment during the outbreak.Methods/Case ReportThe researchers utilized a quantitative survey involving one hundred thirty-six medical technologists working in an institution-based laboratory of Makati and Taguig City. The collated data were encoded in Microsoft Excel for descriptive statistics containing frequency distribution.Results (if a Case Study enter NA)27.9% of the respondents affirmed that they experienced a shortage of personal protective equipment in their workplace but most were unsure whether the contributing factors caused it. The respondents resorted to inventory management strategies to alleviate their lack of personal protective equipment. However, 41.9% and 38.2% of the respondents were undecided whether the efforts to conserve personal protective equipment and the supply management strategies were effective, respectively. Meanwhile, 40.4% of the respondents agreed that personal protective equipment alternatives can help in mitigating the demand for traditionally manufactured personal protective equipment.ConclusionNonetheless, they were able to utilize inventory management strategies in which they were unsure if conservation and maintenance of personal protective equipment were effective but affirmed with the competency of an alternative use for alleviation.

A new methodology for secured inventory management by average fitness‐based colliding bodies optimization integrated with block chain under cloud

AbstractThis article tries to develop the intelligent secured inventory management strategy by blockchain technology under cloud sector. Multiple suppliers, a manufacturer and multiple distributors are considered in the proposed model. The proposed inventory management is derived as a multi‐objective model, which is solved by the average fitness‐based colliding bodies optimization. A set of cost parameters like “transaction cost, inventory holding cost, shortage cost, transportation cost, time cost, setup cost, backordering cost, quality improvement cost, procurement cost, and stock‐out cost” is used for deriving the multi‐objective function. The optimal solution with the reduced cost function is stored in the block chain under cloud sector by each distributor, where a hash function is used by the distributor to secure the data that could not be visible to any other distributors. The proposed methodology aims to provide an important tool for the management of proposed echelon tree structured supply chains with block chain security under cloud sector that overcomes some of the deficiencies of competing methodologies.

Multi-Criteria Spare Parts Classification Using the Deep Convolutional Neural Network Method

Spare parts management is a critical issue in the industrial field, alongside planning maintenance and logistics activities. For accurate classification in particular, the decision-makers can determine the optimal inventory management strategy. However, problems such as criteria selection, rules explanatory, and learning ability arise when managing thousands of spare parts for modern industry. This paper presents a deep convolutional neural network based on graph (G-DCNN) which will realize multi-criteria classification through image identification based on an explainable hierarchical structure. In the first phase, a hierarchical classification structure is established according to the causal relationship of multiple criteria; in the second phase, nodes are colored according to their criteria level status so that the traditional numerical information can be visible through graph style; in the third phase, the colored structures are transferred into images and processed by structure-modified convolutional neural network, to complete the classification. Finally, the proposed method is applied in a real-world case study to validate its effectiveness, feasibility, and generality. This classification study supplies a good decision support to improve the monitor-focus on critical component and control inventory which will benefit the collaborative maintenance.

Inventory Management in SMEs Operating in Polish Group Purchasing Organizations during the COVID-19 Pandemic

The COVID-19 virus has hit the economy around the world. In Poland, SMEs have the greatest problems with doing business. Border blockades and the quarantine for enterprises in virtually all industries throughout Poland greatly complicated the supply systems and the inventory management process. Up to now, SMEs have acted in group purchasing organizations to improve their competitive position. This form of activity also positively affects their financial security. Therefore, in this paper, the inventory management among this group of companies during the COVID-19 pandemic was analyzed. The purpose of the paper was to show how inventory management strategies changed during the COVID-19 pandemic in SMEs operating in industry GPOs. The analysis was carried out on a group of 88 Polish commercial enterprises operating in purchasing groups. The research period covered the years 2017–2019 and March–June 2020. The research showed a change in inventory management strategy in SMEs during the pandemic time of COVID-19. For the first four months, managers of enterprises tried to pursue a conservative policy and to accumulate stocks in the event of a shortage of supplies. This article also presents the form of security that was applied for SMEs operating in group purchasing organizations (GPOs) to avoid forced downtime caused by the COVID-19 pandemic.

Inventory Management Strategies of Food Manufacturing Industries in a developing economy

Inventory Management Strategies of Food Manufacturing Industries in a developing economy

The challenges of drug shortages in the Canadian hospital pharmacy supply chain — a systematic literature review

The aim of this paper is to highlight current knowledge gaps that exist with regard to the factors which affect the supply chain, and the inventory management strategies that are utilized by hospital pharmacies in Canada which could lead to drug shortages. This research implements an optimal SLR (systematic literature review) method on drug shortages based on CHPSC (Canadian hospital pharmacy supply chain) literature and databases. This makes it possible to perform a wide review of Canadian hospital pharmacies and understand how continued disruption occurred in this process and caused drug shortages. The result of this research is contained in a systematic search methodology which consists of four main tasks, namely: a) building an optimal review process, b) defining search procedures, c) validating the search procedures, and d) conducting literature search. Furthermore, the researchers conducted a SLR which unveiled issues and factors such as raw materials availability and increases in demand which cause drug shortages. In conclusion, the proposed systematic methodology seeks to highlight possible solutions to the supply chain management issues which could cause drug shortages in Canada. Various solutions are proposed and explored, with the relevant information being obtained from studies conducted on how to mitigate the impact on supply chain management.

Revisiting Bertrand Competition in the Face of Customer Heterogeneity and Price Discrimination

This paper compares uniform vs. discriminative pricing strategies in a competitive setting featuring capacity restrictions, quality differentiation, and customer heterogeneity. It tackles this overarching question through operational lenses, by studying the joint impact of price discrimination and the allocation of limited inventory across customer segments. Thanks to advances in information technology, firms have developed new capabilities in terms of customer segmentation (by clustering customers into different segments) and price discrimination (by offering different prices to different customer segments). Price discrimination, although seemingly beneficial, can hurt firms in competitive environments. It is thus critical for firms to understand when to engage in price discrimination, and how to support discriminative pricing practices with appropriate inventory management strategies. We develop a Bertrand competition game featuring capacity restrictions, quality differentiation, and customer heterogeneity. We characterize (pure- or mixed-strategy) Nash equilibria for a single-stage game reflecting uniform pricing and for a two-stage inventory-price game reflecting discriminative pricing. We identify three sources of market friction in price competition, enabling firms to earn higher profits: capacity limitations, quality differentiation, and customer heterogeneity. Price discrimination eliminates the market frictions from customer heterogeneity, but strategic inventory allocation restores (or strengthens) the market frictions from capacity limitations. Ultimately, price discrimination is only beneficial when combined with optimal inventory allocation, thus underscoring the critical role of inventory allocation in the design of competitive pricing strategies.

Methodology Forming Strategies for Management of Commercial Resources of Trading Enterprises

The development of methodical approach to strategy formation of inventory management of trede enterprises. The aim of the paper is to develop a methodical approach to determining strategies for managing inventory on which may provide synchronization between the processes of formation of inventory and sales. Implementation of the proposed approach to study inventory management strategies will ensure synchronization between the processes of formation efficiency and effectiveness of inventory sales. Considered the impact of the most important factors, which we have identified, as forecast changing of population demand, quality inventory control and to determine the private areas within the overall strategy towards inventory management, describing the pursuit of optimization of inventory in the activities of commercial enterprise.

Scaling up and scaling down supply chains in volatile resource-based economies.

The growth of mobile workforces to support diversified resource extraction activities, compared to historically single-industry towns, represents a key change in rural and remote resource landscapes that has accelerated since the 1980s. Mobile workforces can present many opportunities to rural communities and economies. However, the capacity, viability and competitiveness of rural-based businesses to engage in supply chains serving mobile labour may be undermined by limited attention to how businesses manoeuvre downturns while maintaining a level of readiness to recover and scale-up in order to meet emerging mobile workforce needs. Drawing upon interviews with businesses in Fort St. John, British Columbia, Canada, our research uses the concept of resiliency to examine challenges and strategies associated with business capacity and agility to scale-up and scale-down in response to changing economic conditions associated with large-scale mobile workforces and related economic sectors. Our findings suggest that the capacity to scale-up and scale-down is shaped by capital, human resource and infrastructure strategies, inventory management and contract management strategies. Industry and state policies may also play a role supporting the conditions that will improve the agility, capacity and readiness of businesses operating in volatile resource-based economies.

Management of Drilling Operations in Surface Mines Using Reliability Analysis and Discrete Event Simulation

Low commodity prices have forced many mining companies to explore new strategies to minimize operating costs. One cost-saving strategy is to increase drilling efficiency and performance, specifically in open pit mines; drilling operations are expensive, and they directly and indirectly affect most aspects of the mining process. A substantial portion of drilling costs is associated with drill bit consumption due to bit wear. Bit wear decreases the rate of penetration, which reduces drilling efficiency, but changing the bit unnecessarily early increases drilling costs. In addition to this decision-making dilemma, the inventory management strategy is also crucial to cost minimization. The innovative aspect of this paper is to propose an approach for determining the number of bits required in a given period and compute the number of holes to be drilled in drilling operations through reliability analysis and discrete event simulation under uncertainty. Reliability analysis is an effective method to monitor the efficiency and performance of mining equipment and ensure that performance goals and quality criteria are met. In this paper, reliability analysis of drilling machines and drill bits was performed and the relationship between reliability and machine performance was established. The range of drillable holes was also determined. Results of 100 simulations showed that the proposed approach can be an effective tool to facilitate production scheduling and asset management.

Application of Lateral Transshipment in Cost Reduction of Decentralized Systems

COVID-19 has exposed the global supply chains to great vulnerability. In such extreme circumstances, product availability becomes a primary concern. This paper studies a basic inventory management strategy—lateral transshipment—under decentralized systems, which may play an important role in dealing with stockouts during unexpected crises. Lateral transshipments not only react quickly to stockout, but are also environmentally friendly due to the significant reduction of production and transportation pollution. This paper studies optimal lateral transshipment and replenishment decisions under a decentralized setting. We construct a multi-stage stochastic model that captures demand uncertainty and customer switching behavior. We demonstrate that, similar to the centralized setting, the optimal transshipment decision follows a double-threshold structure. The optimal replenishment quantities are determined under two pricing mechanisms—individual mechanism (IP) and negotiated mechanism (NP). Numerical examples are provided to demonstrate the impact of lateral transshipment on supply chain cost reduction.

Working Capital Management, Macroeconomic Impacts, and Firm Profitability: Evidence from Indian SMEs

The present study investigates the relationship between working capital management and SME profitability. It also analyzes the impact of macroeconomic impulses on firm profitability through efficient management of working capital in the case of Indian small and medium scale enterprises over the time period spanning from 2010 to 2017 using Feasible Generalized Least Square (FGLS) regression models. The study concludes the negative relationship of account receivables together with a positive relationship of inventories and account payables with SME profitability. It implies the firm managers can maximize SME’s profitability by converting the credit sales to cash as early as possible, by increasing the days of accounts payable and following a conservative inventory management strategy. Changes in economic growth and commercial bank advances to small scale industries are the key macroeconomic determinants that are impacting SME profitability. The results from this paper may guide the firm managers to shape their working capital management strategies to maximize profitability. Policymakers may find the study interesting to identify the macroeconomic parameters that significantly influence Indian SMEs.

Inventory management strategies for the Calabrian hospitals system

This paper addresses some inventory management problems arising in the Italian health care system. We aim at defining inventory management strategies for the hospitals located in Calabria, a Region in the South of Italy. We present some classical inventory management formulations together with the description of a new model, devised to take into account some peculiarities of the case under study. An extensive testing phase is carried out on real data. Numerical results show that the use of the presented mathematical models can be valuable in the decision making process.

Length of stay control: Is it a fair inventory management strategy in hotel market?

According to past revenue management (RM) research, length of stay control (LOSC) plays a significant role in building effective RM systems and increasing revenues in the hotel industry. While LOSC has been widely implemented in the hotel’s online booking systems, little attention has been paid to this important non-pricing RM practices. Thus, the current study aims to provide a holistic view of customers’ perceptions toward hotel’s LOSC practice. In particular, this study (1) investigates the impact of LOSC practice on customers’ perceived fairness and subsequent behaviors and (2) tests the moderating role of customers’ membership status on perceived fairness. A between-subjects factorial design and partial least squares structural equation modeling (SEM) analysis were employed to test the structured relationships. Research findings demonstrate that customers perceive LOSC as unfair, such poor fairness perceptions leading to negative word-of-mouth and a decrease in willingness to book. Hotels’ loyalty program members are likely to perceive LOSC as much more unfair than those who are not. The current study is the first study to reveal the critical roles of hotels’ LOSC practice and loyalty membership on customers’ perceived fairness and subsequent behavior intentions.

An Intelligent Approach for Demand Forecasting in E-commerce

With the growth of e-commerce, accurate demand forecasting has become a critical aspect of successful business operations. Traditional demand forecasting techniques such as time-series analysis, moving averages, and exponential smoothing have been used for years, but they have limitations in capturing the complex and dynamic nature of e-commerce demand. In this paper, we explore innovative approaches to demand forecasting in e-commerce. Specifically, we discuss the use of tree-based Machine Learning (ML) techniques as well as advanced statistical models such as Bayesian networks and hierarchical models. We provide a case study of successful implementations of innovative demand forecasting techniques in e-commerce companies. The results show that our approach can significantly improve inventory management and logistics strategies, leading to increased profitability and customer satisfaction.

Inventory Management and Reorder Point (ROP) Strategy Using ABC Analysis Methods in Textile Manufacture

Tight competition encourages textile companies to increase their competitiveness to efficient in all fields, especially by reducing material stock to its optimum figures without disrupting production operations. Currently this textile manufacture has implemented SAP as an Enterprise Resource Planning (ERP) software. SAP is currently used as Material Resources Planning (MRP), purchasing and inventory control software. Purchases are made automatically using Reorder Point (ROP) and inventory control using the ABC analysis method. In time being there is no relationship between the ABC analysis method to inventory control and ROP. With this condition, the purchase order for material is raised when the stock level is lower than ROP even these unnecessary, causing the stock to become slow moving and dormant when it reaches six months laying on the warehouse and causing excess inventory. This study aims to design and implement how the ABC method can be used to determine purchasing decisions and which ROP calculations should be used. The ABC multi criteria analysis in this study shows that ABC categorization is acceptable for deciding ROP determination. This method of inventory management has the potential to reduce inventory levels up to 17% and eliminate dormant and slow moving

Inventory Management and Reorder Point (ROP) Strategy Using ABC Analysis Methods in Textile Manufacture

Tight competition encourages textile companies to increase their competitiveness to efficient in all fields, especially by reducing material stock to its optimum figures without disrupting production operations. Currently this textile manufacture has implemented SAP as an enterprise resource planning (ERP) software. SAP is currently used as material resources planning (MRP), purchasing and inventory control software. Purchases are made automatically using reorder point (ROP) and inventory control using the ABC analysis method. In time being there is no relationship between the ABC analysis method to inventory control and ROP. With this condition, the purchase order for material is raised when the stock level is lower than ROP even these unnecessary, causing the stock to become slow moving and dormant when it reaches six months laying on the warehouse and causing excess inventory. This study aims to design and implement how the ABC method can be used to determine purchasing decisions and which ROP calculations should be used. The ABC multi criteria analysis in this study shows that ABC categorization is acceptable for deciding ROP determination. This method of inventory management has the potential to reduce inventory levels up to 17% and eliminate dormant and slow moving

Effect of Accounting Policies on Effectiveness of Inventory Management Strategies

In the continuous battle to cut costs, firms focus on efficiency throughout the entire supply chain. Well-designed inventory management strategies are a crucial part of overall supply chain effectiveness. The days of large inventories is becoming a thing of the past. Unfortunately, companies using the Last In – First Out (LIFO) inventory accounting method may find that implementing inventory reduction best practices in the supply chain has some undesired results. This article includes a case study of a real-life industrial distributor who uses the Dollar Value LIFO accounting method. Using inventory stratification with data collected from 1978 to 2014, this study describes the potential burden experienced from reducing inventory levels when using LIFO and shows a path towards achieving the desired inventory management strategy. The impact on key financial metrics such as Cost of Goods Sold (COGS) and Gross Margins are shown. Existing and new companies can both learn from this company’s example when making inventory management decisions.

A drug association based inventory control system for ambulatory care

The purpose of the research is to explore an innovated drug inventory control system for medical organization to improve the system performance in terms of daily patients’ prescriptions and drugs flows. It is not easy to well control drugs inventory due to large numbers of stock keeping units and huge quantities of them in a medical organization. In order to maintain both the daily jobs of ambulatory care and the rights of the patients, the availability of all drugs keeping at a reasonable stock level for medical staffs and patients is required. Also, to avoid increase of cost due to over stocking to overcome the prediction of possible shortage of drugs is a must. In traditional control system, cost is always be considered as the decision variable. Based on the total cost of each item in an inventory management within a planning cycle, and to calculate out the quantity for that particular item within the total inventory, the total amount of inventory ratio for that item will also be derived and be classified to make different inventory management strategies for different catalogues. There are hundreds of variable pharmaceutical goods in medical organization, hence, large number of prescription data and critical information will be ignored if the inventory classification is determined by the traditional cost approach. This study used association rules analysis to mining the patient treatments database, in order to derive prescription-oriented association rules for improving cost-oriented categories inventory management. In this research, data mining technology is utilized to detect hiddenly issues, which might cause drug shortages. Around 480,000 data, ranges from January to March, 2010, were extracted from Taiwan’s National Health Insurance files, and applied with multi-level association rule analysis, 19 association rules were obtained. In conclusion, the potential relationship in a huge database, found by data mining technique, can be used to support managing staff to adjust inventory policies accordingly.

Post-shipment financial flows in supply chains: A study of small- to medium-sized enterprise importers

Background: Global sourcing has impacted inventory levels, lead times and the availability of working capital, affecting the standard financial flow of a supply chain. Poorly managing the link between the financial and physical supply chains could therefore lead to unnecessarily high inventory investments or to a short supply of inventory, affecting cash flow, working capital, sales and, subsequently, a firm’s profitability.Objectives: The aim of this generic qualitative study was to explore how firms manage their financial supply chain alongside their physical supply chain.Method: Data were collected from 12 semi-structured interviews with senior managers across six small- to medium-sized enterprise (SME) importing firms in various industries.Results: The research finds that the buyer is the driver of both upstream and downstream financial supply chain management (FSCM) as SME importers in Gauteng are proactively managing their financial alongside their physical supply chains. Through the continuous evaluation of sourcing strategies, exchange rate risk management strategies and inventory investment management strategies, firms can align their physical and financial supply chains.Conclusion: This study highlights the lead time and disruption risks and costs of global sourcing and identifies FSCM tools that can be used to alleviate the financial burden associated with long lead times.