Inventory Strategy Research Articles

Two-stage supply chain inventory management based on system dynamics model for reducing bullwhip effect of sulfur product.

Bullwhip effect is prevalent in supply chains, creating supply and inventory risks that affect marketing, supply and production. However, there are limited researches on the optimization of chemical supply chain inventory management. In order to solve the above problem, this paper took the sulfur product supply chain of a sulfur plant as an example, combined with the idea of system dynamics, and systematically studied the inventory control strategy in the distributor-retailer two-level inventory system constituted by the supply chain. Firstly, the causal loop diagram was drawn according to the system relationship between variables in the two-level supply chain, and then the system dynamics model of sulfur product supply chain was formed. Finally, problems existing in the supply chain were explored through simulation, and optimization suggestions were submitted. It can be concluded from the simulation results that there was bullwhip effect in the sulfur product supply chain, and the delay of transportation time and the change of inventory adjustment time would have an impact on the inventory level of each node enterprise in the supply chain. Therefore, the method of building an information sharing platform, implementing visual information management, and adopting logistics transportation service outsourcing could enhance the information exchange among node enterprises, so as to improve the operational efficiency of the entire product supply chain.

Evaluation of inventory management practice in food processing industries in Lagos: Analytical hierarchy process approach

A survey of food processing industries was conducted to examine different inventory strategies in order to establish the most acceptable inventory practices in Lagos State, Nigeria. The criteria for selection of those inventory techniques are accuracy, cost, stock out, fraud, time, delivery, storage space, product type, features, efficiency, nature of production system, customer satisfaction, trained or qualified staff, the effectiveness of information technology system used, organizational factors, process capability, problem recurrence and characteristics of manufacturing systems. The purpose of the research is to select best inventory management practices in the food processing industry in Lagos State, Nigeria. Structured questionnaires were designed and given to various category of managers in one hundred and fifty (150) food processing industries between the period of October 2020 to December 2020. The Analytical Hierarchy Process (AHP) steps were implemented using Spice Logic Software to compute the criteria weights, criteria priority and the overall priority for inventory alternatives practiced. Based on the highest overall priority, the Analytical Hierarchy Process indicates that the best inventory strategies are Economics Order Quantity (EOQ), Minimum Order Quantity (MOQ), First-in-First Out / Last-in-First Out (FIFO/LIFO), and Safety Stock Inventory, in that order to enhance food processing industry for optimal production or manufacturing, preservation of foods, easy marketing and distribution tasks, increasing food consistency which includes availability of many foods, transportation of perishable foods over long distances, and ensuring the survival of modern supermarkets. The recommended inventory techniques for food processing industries are critical to minimizing inventory costs. As much as this study was designed for Lagos State, similar survey should be carried out for other states, including other industries apart from the food processing industries.

Research on the Impact of Inventory Management Practice on Organizational Performance in Telecommunication Companies

Abstract: This research study examined the impact of inventory management on organizational performance in telecom companies. The study used a descriptive study design, and SPSS was used to conduct statistical analysis. In order to choose the samples, the researcher used both purposive and simplerandom sampling methods. Data for the study was collected from 130 respondents out of which 92 responded making the research valid. The relationships and hypothesis proposed in theconceptual framework were tested using multi-linear regression equation model. The research results indicate that higher levels of inventory management practice can lead to an enhanced competitive advantage and improved organizational performance. The study also accepted the hypothesis that was tested that inventory management and organizational performance have a significant positive relationship. Therefore, it is recommended that telecom organizations in Uganda should adopt Vendor management inventory, maintain good communication with the suppliers as this helps to eventually transfer inventory management responsibilities from the company’s procurement function to the vendors thus revamping organizational performance and increasing their competitiveness. They should also update their inventory management system in order to improve effectiveness by investing more money in the latest IT systems and utilizing sophisticated technologies such as purchasing fuel sensors for inventory monitoring and management so as to minimize on downtime and as well as cost reduction. The research study alsosuggests that management should take a more proactive approach to the problem of inappropriate inventory management strategies being used by constantly exposing its employees to training ona regular basis in order to strengthen their inventory management skills and allow them to understand current inventory management systems thus if implemented it can enable the companyin lowering costs by ensuring that stock records are maintained accurately and kept in order to prevent the risk of overstocking or understocking. Key words: Inventory management, Organizational Performance, Telecommunication companies

A cleaner EPQ inventory model involving synchronous and asynchronous rework process with green technology investment

The amount of carbon emission in the atmosphere continues to grow, and production, storage and transportation are major contributors that are repeatedly unnoticed when it comes to solving the problem. A carbon levy and cap EPQ model has been explored in this study for a controlled carbon emission in view of cleaner production under imperfect production processes where a fraction of the products is faulty. The model incorporates emissions from transportation, production, and storage activities, which are meant to be decreased by green investment. The manufacturer employs a rework approach to rectify the faulty products. Flexible rework allows the manufacturer to choose the rework rate, which can differ from the manufacturing rate, as well as the process of rework, which can be asynchronous or synchronous. A linear rework cost function of the rework rate is assumed. We sought to obtain the lowest cost with respect to optimal lot size, and backorder under the effect of controlling carbon emissions by applying the exponential form of green investment. Keeping these in mind, several mathematical models derived for various rework rate and rework process assumptions with the objective emphases on gaining a trade-off between cost and emissions, thereby finding the optimal production-distribution inventory strategy and an appropriate sustainable plan for handling both synchronous and asynchronous rework process. We show a constrained non-linear programme (NLP) and derive a calculus optimization technique to solve it. An iterative solution technique is used to arrive at the optimal decisions, which are shown analytically and numerically. The results validate the impacts of controlled carbon emissions on the production strategies. The findings mainly suggest that increasing the carbon levy reduces emissions. The firm has more options to decrease emissions caused by industrial activity with the help of green technologies. Although green technology has a higher upfront cost, the producer will reap the advantages of lower emissions.

DEVELOPING A MULTI-ITEM, MULTI-PRODUCT, AND MULTI-PERIOD SUPPLY CHAIN NETWORK DESIGN AND PLANNING MODEL FOR PERISHABLE PRODUCTS

Background/Objectives: In this paper, a sustainable supply chain network design and planning model is developed for perishable products. The model aims to maximize total profit in addition to preventing the expiration of perishable products using the FIFO inventory strategy to reduce environmental impact by reducing waste.
 Methods/Statistical Analysis: A mathematical model is developed to design a sustainable, multi-item, multi-product, multi-period, three-echelon supply network including three potential suppliers, three potential factories, a warehouse, and three retailers. The model is formulated as mixed-integer nonlinear programming. It is solved by DICOPT/GAMS.
 Findings: The behavior of the model has been verified by solving six scenarios of different demand patterns. The results verify the ability of the developed model in assisting the SC organizations to manage their network more efficiently
 Novelty/Applications: The model considered the production, inventory, and transportation of two perishable products in multi-periods. It maximizes the profit in addition to preventing the expiration to minimize environmental impact to ensure sustainability of the supply chain. The model is solved by DICOPT/GAMS.

Inventory control policy for perishable products under a buyback contract and Brownian demands

In this study, we analyse the inventory management strategy for perishables, where customer demands are assumed to arrive continuously and modelled by a drifted Brownian motion. We apply the well-known (s, S) continuous review inventory policy; in this policy, an order is placed to increase the inventory level to S as soon as it falls below s. Benefitted from highly developed transportation and logistics industries, it is reasonable to employ the zero-leadtime assumption in our model. In addition, a buyback contract is granted for the retailer to recover the loss from perishing. We illustrate the sales cycle through Markov renewal approach and derive closed-form formulas for long-run profit rates. To evaluate the optimal ordering policy which maximises the profit rate of the retailer, we first analyse the condition for accepting backorder and derive the optimal backorder level s as a function of S, and then solve for the global optimal (s, S) policy through numerical studies. Moreover, we develop a heuristic approach to approximate the optimal policy. Sensitivity analyses are conducted to reveal the effect of different parameters on system behaviour. The conclusions provide managerial insights for formulating inventory policies for perishables under Brownian demand.

Resilience assessment of the downstream oil supply chain considering the inventory strategy in extreme weather events

As climate change intensifies and extreme weather events occur more frequently, the uncertainties of demand, production and inventory will affect the operation and management of supply chains. In this paper, a systematic method for evaluating the resilience of the supply chain is proposed, which is applied to the demand side management of an actual downstream oil supply chain. According to the practical operation of the downstream oil supply chain, several scenarios such as disruption of refineries, shutdown of pipelines and increasing demand are defined. Then, two indices are introduced to make a quantitative resilience assessment for the studied downstream oil supply chain. The inventory strategy is also proposed and applied to different scenarios. Finally, Monte Carlo simulation is used to make a comprehensive analysis with multiple scenarios. The results show that increasing the inventory of storage depots can improve the resilience of the supply chain by 2.67% to 14.83%. According to the sensitivity analysis for the failure rate and repair rate of each link, it is indicated that the resilience can be improved by 5.95% when the repair rate is doubled and be reduced to 16.04% when the repair rate is reduced by half.

Optimization on the multi-period empty container repositioning problem in regional port cluster based upon inventory control strategies

Within the area of regional port clusters, this paper establishes a multi-period mixed integer programming model to optimize the empty container repositioning between public hinterlands and ports, comprehensively considering the quantitative and periodic inventory control strategy. At the same time, this paper dynamically and heuristically determines the empty container inventory threshold (D, U) under quantitative strategy and S under periodical strategy at each port within the regional port clusters. On this basis, the empty container repositioning schemes between public hinterlands and ports are optimized by using Markov decision process combined with dynamic programming method. In addition, Liaoning coastal regional port cluster and its northeast hinterland are selected as the objects to solve this model and the results show that the total cost of shipping company can be saved by 14.16% and 11.92%, respectively, by the quantitative and periodical inventory control strategy. Selecting the quantity of public hinterland terminals, the empty container demand of public hinterland terminals and ports, the inventory threshold of empty containers and other factors, this paper carries on the sensitivity analysis. This paper validates inventory control strategy can weaken the shipping company in the influence of the external environment changes. And the quantitative inventory control strategy can reduce the total cost value to a greater extent and more effective in cost control than periodical strategy.

Disclosing opaque inventory information in a two-period sales setting: substitute products' selling strategy

PurposeThe purpose of this paper is to investigate the opaque inventory information disclosure strategy for an online retailer who sells two substitutable products to customers in two selling periods.Design/methodology/approachThe authors develop a two-period model where an online retailer sells two substitute products with two inventory composition structures to maximize profits. The authors investigate the optimal inventory disclosure decision from both ex post and ex ante perspectives. Sensitivity analysis is performed to investigate the effects that discount rate, transaction cost and the probability of agreeable inventory situation have on the equilibrium disclosure outcome. The authors also consider risk-averse customers and horizontally differentiated products to highlight the robustness of our results.FindingsThe authors find that the online retailer will choose the opaque information disclosure when attempting to increase revenue and reduce the mismatch of supply and demand in both ex post and ex ante inventory information conditions. Comparing with ex post disclosure strategies, ex ante opaque disclosure is optimal in a larger price region, and the total revenues gap between opaque disclosure and complete disclosure gradually increase as discount rate, transaction cost or the probability of agreeable inventory situation decreases. Furthermore, strategic customers may tend to be risk neutral when faced with opaque inventory information in a two-period sales setting.Originality/valueThis current paper is the first paper to study the online retailer's inventory information disclosure strategy in two selling periods. Moreover, this paper presents the conditions under which the online retailer should share complete or opaque inventory information with customers to maximize the online retailer's total revenues.

Research on Process Control Strategy of Asphalt Tank Inventory Based on Dynamic Programming Algorithm in Post Epidemic Era

Abstract Based on the background of post epidemic era, starting with the traditional industrial inventory process control, this paper discusses the dynamic inventory process control strategy under the asphalt tank inventory mode, and analyzes the intelligent inventory mode under the trend of intelligent logistics through the dynamic programming method, so as to provide reference for the development direction of intelligent inventory of unconventional storage materials such as chemical industry and energy. At the same time, with the recurrence of short-term epidemic and the dilemma of low return to work and production rate, through the integration and interconnection of mobile communication, intelligent analysis, digital management and other technologies with all links, the strategies of inventory dynamic control, inventory risk control, improving inventory efficiency and optimizing inventory cost are put forward.

Development of spreadsheet simulation models of gas cylinders inventory management

The solution of the problem of managing the inventory of an enterprise whose activities are related to the purchase and sale of gas cylinders is considered. To solve the problem, it was necessary to investigate and choose the best inventory management strategy that provides the minimum value of the average inventory balance in the warehouse with the established upper limit of the average deficit. The problem of determining the best strategy is presented as a discrete programming problem, the required variables of which depend on the replenishment method. With a periodic replenishment strategy, the controlled variables are the volume of the delivery line and the delivery interval, with a threshold one, the minimum inventory level and the volume of the delivery line. Let’s also consider replenishment with a predicted inventory level, where the delivery level and the minimum inventory level are used as control variables. Three tabular simulation models with a given delivery time and random demand are proposed. Using the Chi-square test, it was found that the quantity demanded has a normal distribution law. By carrying out computational experiments, the optimal values of controlled variables were determined. The best objective function values were obtained using a model with a predicted inventory level and a threshold replenishment strategy. Experiments conducted on the basis of historical data have shown the advantage of the two model strategies compared to the strategy currently used in the enterprise. The use of a model with a predictable inventory level would reduce the average inventory balance by 46 %, and, consequently, save working capital. The results of the study can be useful for managers of enterprises whose activities are related to inventory management

A Study on Determinants of Inventory Turnover using Quantile Regression Analysis

Purpose - This study attempts to analyze the determinants of inventory turnover by applying quantile regression analysis. Design/methodology/approach - By selecting the gross margin, capital intensity, and sale surprise as the determinants of inventory turnover, we investigate their effects on inventory turnover at the several quartiles (10%, 25%, 50%, 75%, 90%) of inventory turnover with quantile regression analysis. Findings - The effects of gross margin and capital intensity on inventory turnover are different for each quartile. But the effects of sale surprise on inventory turnover are not different for each quartile. Research implications or Originality -This study is the first attempt to examine the effects of inventory turnover determinants on inventory turnover by applying quantile regression analysis was not employed in the prior studies. Thus, this study is meaningful in that it shows the possible way to review inventory management strategies that can be applied differently to the firms with different inventory turnover levels.

Optimal pricing and inventory control strategy for a continuous-review system with product return

We consider joint pricing and inventory control strategies for a stochastic inventory system with product return. Customer's demand and product return follow independent point processes with demand rate being price-dependent. Using a general verification theorem, we prove that an (s⁎,S⁎,p⁎) policy is optimal, where the optimal price p⁎(x) is a quasi-concave function of inventory level with a nonpositive changeover point. Furthermore, we propose an algorithm to search for the optimal policy parameters and numerically study the effect of product return.

A hybrid bi-objective optimization approach for joint determination of safety stock and safety time buffers in multi-item single-stage industrial supply chains

In material requirements planning (MRP) systems, safety stock and safety time are two well-known inventory buffering strategies to protect against supply and demand uncertainties. While the role of safety stocks in coping with uncertainty is well studied, safety time has received only scarce attention in the supply chain management literature. Particularly, most previous operations research models have typically considered the use of such inventory buffers in a separate fashion, but not together. Here, we propose a decision support system (DSS) to address the problem of integrating optimal safety stock and safety time decisions at the component level, in multi-supplier multi-item single-stage industrial supply chains under dynamic demands and stochastic lead times. The DSS is based on a hybrid bi-objective optimization approach that simultaneously optimizes upstream inventory holding costs and β-service levels, suggesting multiple non-dominated Pareto-optimal solutions to decision-makers. We further explore a weighted closed-form analytical expression to select a single Pareto-optimal point from a set of non-dominated solutions, thereby enhancing the practical application of the proposed DSS. We describe the implementation of our approach in a major automotive electronics company operating under a myriad of components with dynamic demand, uncertain supply and requirements plans with different degrees of sparsity. We show the potential of our approach to improve β-service levels while minimizing inventory-related costs. The results suggest that, in certain cases, it appears to be more cost-effective to combine safety stock with safety time compared to considering each inventory buffer independently.

Impact of carbon emission reduction on supply chain model with manufacturing decisions and dynamic lead time under uncertain demand

Consignment stock policy plays a crucial role in stock management to accomplish more significant benefits for supply chain players. Accordingly, in this research, we developed an inventory model based on the vendor managed inventory and consignment stock agreement by delivering a single item from the single vendor to a single buyer under controllable lead time. Manufacturing industries are a major source of worldwide greenhouse gas emissions. Consumption of larger energy through non-renewable sources increases the use of fossils and coal. Though, this produces more waste and has a negative impact on the environment. In contrast to earlier research, logarithmic investment is employed to control the amount of carbon generated throughout the manufacturing process. The demand rate is treated as a pentagonal fuzzy number to account for the uncertainty. The primary goal of this study is to maximize gross profit with various realistic factors and reduce carbon emissions from the production process. Five numerical experiments, comparison and sensitivity analysis are performed to validate the proposed model. Finally, the benefits of variable pricing and investing in carbon reduction will assist industry managers in effectively managing pricing and inventory strategies to adopt a sustainable supply chain in an uncertain environment.

An integrated approach to redesign inventory management strategies for achieving sustainable development of small and medium‐sized enterprises: Insights from an empirical study in India

AbstractEfforts to incorporate inventory management (IM) strategies in small and medium‐sized enterprises (SMEs) are very limited due to the lack of cost‐effective and easy‐to‐use techniques. This research article suggests an effective and proven IM strategy that can improve the productivity and competitiveness of SMEs. The purpose of this research article is twofold: first, to develop an integrated IM strategy for SMEs to reduce inventory carrying costs; second, to design individual replenishment policies for each product. This article discusses an integrated approach considering rank order clustering (ROC) technique, a forward version of the Wagner–Whitin (W–W) lot‐sizing algorithm, and quantity discounts. First ROC is used to form clusters of different assemblies consisting of common components for aggregating the demand. The W–W algorithm is tested next over 1 year of time horizon followed by quantity discounts. Insights derived from a case study proved that the proposed integrated IM approach could save a substantial amount of total cost compared to the existing purchase policy. In addition, this approach can be a promising approach to determine appropriate replenishment quantities for each planning period. In addition, stock‐out situations can be minimized. The novelty of this study is that it proposes a practical, simple‐to‐implement, and proven IM technique for increasing productivity and achieving sustainable development of SMEs, which are working in growing economies like India.

OPTIMISATION OF PURCHASING STRATEGY OF TOOLS AND COMPONENTS BASED ON EXCHANGE CURVE THEORY

The optimal inventory control of tools and components in manufacturing systems plays an important role in the success of sustainable operation from financial and ecologic point of view. This study discusses an inventory control method, which is based on the transformation of investment of inventory into annual order cost or vice versa. The study presents the mathematical model of the exchange curve model for tools and components in the case of economic order quantity inventory strategy. The described methodology makes it possible to optimise available purchasing strategies for tools and components. The approach was tested with a scenario analysis, where different parameters of the purchasing process including inventory related constraints were taken into consideration. The computational results validated the exchange curve based inventory control methodology and showed that the inventory strategy can be improved with cost transformation Practical implications of the proposed model and method regard the possibility of finding optimal inventory policies that can affect the operation costs of manufacturing systems.

Optimal inventory strategies for deteriorating items with price-sensitive investment in preservation technology

With recent developments in the technological world, the issue of deterioration has been addressed efficiently through preservation technology by numerous researchers. The fundamental concept of preservation technology involves an investment that is majorly dependent on the initial deterioration rate, irrespective of the selling price of the product. Owing to this, two different products having the same deterioration rate but different selling price requires equal investment, which is irrational. Further, the investment in preservation technology was considered to be per unit time irrespective of the number of units being held, which is again a major drawback of the existing literature. Thus, this paper attempts to bridge the gap by proposing a realistic way of implementing preservation technology, where not only the investment is per unit, but also depends on the selling price of that unit. The model jointly optimizes the selling price, the fraction of per unit profit to be invested in preservation technology, and cycle length to maximize the overall profit. The proposed model proves out to be economically more viable, through superior cost management, when compared with the existing model. The model is further illustrated with comparative numerical examples and graphical representations. Moreover, sensitivity analysis is performed to convey model characteristics.

Reducing platelet wastage in a regional Australian haematology centre: Impact of phone calls to clinical staff for expiring platelet stock

Background: Inventory management of platelets is critically important to avoid shortage and minimise wastage.1 In our centre this is challenging with a platelet order to delivery time of 12–24 hours and no other stock within a 400 km radius. Aim: To examine if phoning clinical haematology staff reduced platelet wastage. Methods: Our senior transfusion scientist introduced routine calls to haematology clinical staff when platelets were expiring in the next 12 hours. We compared Discards as Percentage Issued (DAPI) published in National Blood Authority reports for July–December 2016 prior to the intervention with DAPI for July–December 2018 after this intervention was routinely established. Excel spread sheets of platelet inventory and logs of phone calls to clinicians were also reviewed. Results: We observed an absolute reduction of 9.2% in DAPI between the two time periods (23.0% July–December 2018 vs 32.2% for July–December 2016). From July–December 2018 66 phone calls were made to clinical staff regarding expiring platelet stock. The total number of platelets issued in the two time periods was similar (391 July–December 2016 vs 387 July–December 2018). Discussion: Our results demonstrate a simple yet effective best practice inventory management strategy to reduce platelet wastage. We are not aware of any other centres who are utilising this strategy. Reference 1. National Blood Authority. National Blood and Blood Product Wastage Reduction Strategy 2013–2017. Canberra: National Blood Authority, 2013. https://www.blood.gov.au/system/files/documents/nba-wastage-strategy.pdf

A research agenda to reflect reality: On being responsive

A research agenda to reflect reality: On being responsive