Vendor Managed Inventory Research Articles

Analysis of Deteriorating Inventory Work (2016-2019)

In the present review paper, we are presenting comprehensive information about the advances and recent researches made in the field of inventory supply chain for deteriorating items. This paper studied some characteristics which are playing important role in management area of deteriorating inventory supply chains. We have categorize our reviewed papers according to the keywords like demand rate, deterioration rate, two warehouses dispatching policy, green supply chain, permissible delay in payments and some strategies like vendor managed inventory (VMI), Stackelberg Game, sale, discount, effects of dynamic pricing of deteriorating items on income and deterioration, unexpected deterioration identification etc. The research work which is tabulated in this paper offer clear information about the inventory supply chain of deteriorating items. We have also provided future research directions in this area.

Heuristic analyses of separate and bundling sales for complimentary products under consignment stock policy

In the real world, various products are displayed simultaneously on the shelf; therefore, their demands/prices affect each other. This paper aims at studying a joint economic lot-sizing model with two complementary products in a supply chain consisting of a vendor and a buyer. The vendor sends items to the buyer's warehouse in equal-size batches applying vendor-managed inventory with consignment stock policy. The buyer stocks items at the warehouse and on the shelf. Two mixed-integer nonlinear models that consider bundling and separate sales have been proposed and solved through different solution algorithms such that the profit is maximized. The concavity of both models' objective functions is investigated and the effect of considering complementation between products and bundling strategy is studied. Numerical experiments indicate that the bundle's marginal profit is greater than a single product's marginal profit. Moreover, the supply chain members can also take advantage of economies of scale in bundling sales.

Key Components Identification in Vendor Managed Inventory (VMI) and their Evaluation Using ANOVA for Automobile Industry in Indian Context

The latest market trend shows that generation of dissimilarity in demand is because of variation is required by market in goods. Lot of complexities like planning, forecasting is generated due to this demand. Market always have uncertainty in demand starting from raw material to the final product delivered to the customer. To reduce this uncertainty, the entire approach must be changed to some new techniques. This can be achieved by managing the company supply chain in a very efficient manner and by doing so they can have competitive advantage over others. Few components of Vendor Managed Inventory (VMI) vital for both vendors and clients are discussed in this paper. A comparison of degree of difficulty and importance is also done in this paper.

Designing smart replenishment systems: Internet-of-Things technology for vendor-managed inventory at end consumers

Motivated by recent advances in Internet-of-Things (IoT) technology for household appliances, we analyze a Smart Replenishment system that leverages point-of-consumption (POC) information at end consumers to decide on deliveries of consumables. As such, we extend the classic Vendor-Managed Inventory (VMI) concept to end consumers. We model the system for a single manufacturer who directly serves N end consumers with uncertain demand. End consumers partially adopt the new Smart Replenishment mode, which results in a mix of VMI and non-VMI customers. We assume that unfulfilled demand is lost and that the manufacturer’s dispatch capacity is constrained. Customers compete for the same capacity while featuring different out-of-stock risks and service-level expectations, both of which are costly to the manufacturer. Considering various adoption levels, we decide on the design of such a system and focus on (i) inventory control, (ii) customer prioritization, and (iii) degree of smart, integrated decision-making. Using discrete-event simulation and a full-factorial experiment, we show that replenishment decisions can be significantly enhanced with POC information. It leads to substantial improvements in service levels and capacity utilization without loading customers with inventories. This improvement potential is highest for a low demand coverage of the replenishment quantity, a high gap in the ordering behavior of manufacturer and end consumers, and a long lead time. To realize this improvement potential, we propose a flexible reorder corridor to manage inventories at VMI customers that balances the trade-off between out-of-stock risk and service-level expectation inherent in the system.

A closed vendor managed inventory system under a mixed fleet of electric and conventional vehicles

In a closed-loop supply chain, where a Vendor Managed Inventory system is executed, the Closed-Loop Inventory Routing Problem is one of the main problems confronted by logistics decision-makers. This study addresses a Closed-Loop Inventory Routing Problem under a mixed fleet of electric and conventional vehicles. The problem is formulated as a Mixed-Integer Linear Programming model and a Fix&Optimize algorithm is developed to tackle larger problem instances. The proposed decision support models incorporate comprehensive estimation approaches for energy consumption of both electric and conventional vehicles that allow to better estimate fuel and electric cost and transportation emissions. The models respect uncertain reverse returnable transport items flow from customers as well. The numerical analyses demonstrate the benefits that could be obtained by means of the provided models. The Fix&Optimize heuristic yields in 5.72% lower costs within 59.23% shorter computation times on average compared to the Mixed-Integer Linear Programming model. The proposed models are capable to provide trade-off analyses for sustainable logistics management.

Using vendor management inventory system for goods inventory management in IoT manufacturing

ABSTRACT The revolution in the digital economy is forcing the manufacturing industry to develop new business models to achieve operational excellence. Vendor Management Inventory (VMI) is a key measure, aimed at increasing supply chain efficiency and mitigating the bullwhip effects on the Internet of Things (IoT). The problems encountered by the manufacturing supplier are the difficulty of obtaining inventory information at the hub, and being unable to easily integrate relevant inventory information in the IoT. The proposed method is to implement an integrated Hub VMI system to solve the inventory problem. This case study aims to implement an all-in-one integrated Hub VMI in an electronic manufacturing business. This proposal has two models: one comprises an Stock Transfer Order (STO)/Sales Order (SO) structure in which the purchase order is accepted and the product is manufactured onsite; the other consists of a Purchase Order (PO)/SO structure, whereby the PO is accepted onsite but the product is manufactured at another site. This case study designs an intelligent Radio Frequency Identified (RFID) system to extract product information from an inventory, and to provide a product, as recommended by customer services. The result and the contributions of this research include inventory management operation enhancements, a reduction in the cost and the total execution time, a reduction in the response time for the benefit of the customer and an increase in system performance efficiency.

The central role of IT capability to improve firm performance through lean production and supply chain practices in the COVID-19 era

Today, global competition entails companies having an advantage in supply chain networks to pursue superior performance. This work examines the link between information technology (IT) capability with the firm performance by adopting a lean production approach, vendor-managed inventory, and supply chain practices. The study has surveyed the population of the manufacturing company in East Java, Indonesia, using a questionnaire with a five-point Likert scale. A total of 111 manufacturing companies (medium and large) were selected from 5420 manufacturing companies listed in the Industrial Department of East Java. The partial least square (PLS) technique was used to analyze the data, using the SmartPLS software version 3.3. Thirteen hypotheses in this study were developed to investigate. The result revealed that all hypotheses of direct relationship were supported. IT capability directly affects lean production, vendor managed inventory, and supply chain practices. Moreover, lean production, vendor-managed inventory, and supply chain practices improve firm performance. Further analysis also indicated that all hypotheses of indirect hypotheses were supported except hypothesis one hypothesis (H9). IT capability indirectly improves firm performance through lean production, vendor-managed inventory, and supply chain practices. The result provides insight for managers and policymakers on enhancing firm performance by improving its IT capability, adopting lean production, vendor-managed inventory, and supply chain practices. This research contributes to reinforcing the supply chain management theory.

A Multi-Attribute Value Theory to assess the benefits of Vendor Managed Inventory

This paper aims to show the effect of the qualitative decision factors on the implementation of VMI solution in the grocery industry. The methodology used in the study is a combination of an analytical approach and empirical analysis. A multi-attribute value theory called simple multi-attribute rating theory was selected as a tool of analysis. This model was combined with the analytical hierarchical process to obtain a hybrid model to express subjective and objective decision-maker evaluations. Then, the empirical analysis was conducted to validate the research paradigm and to test the model generated. As a result, qualitative factors are considered essential elements for a supply chain collaboration project's success. For the literature, it is the first attempt to assess an analytical model combining both qualitative and quantitative factors for such a solution. For practitioners, the model may be used as a supporting tool for decision-making about VMI solution.

A Proposed Order Prediction Methodology for Vendor-Managed Inventory System in FMCG Sector Based on Interval-Valued Intuitionistic Fuzzy Sets

A Proposed Order Prediction Methodology for Vendor-Managed Inventory System in FMCG Sector Based on Interval-Valued Intuitionistic Fuzzy Sets

A buyer-vendor system with untimely delivery costs: Traditional coordination vs. VMI with consignment stock

This paper investigates the impact of coordinating a two-level supply chain that consists of a single-vendor and a single-buyer in the presence of untimely delivery costs. Specifically, early and late deliveries outside an agreed-upon delivery window are penalized. We investigate the replenishment policies of the vendor and the buyer with and without coordination. We show that untimely deliveries increase the replenishment cycle of the buyer, whether it coordinates with the vendor or not. More importantly, under untimely deliveries, coordination has a noticeable impact on aligning the decisions of both players, which is shown to be much more valuable in decreasing total costs. Implementing a coordinated solution becomes beneficial when the vendor’s penalty and holding costs are high, the delivery window is narrow, and the buyer’s holding and ordering costs are low. Next, we compare the traditional replenishment coordination mechanism with a vendor-managed-inventory (VMI) mechanism with consignment stock (CS) under untimely deliveries. We compare two coordination mechanisms, VMI-CS and traditional, and show that VMI-CS outperforms the other when the delivery times are random, but not so when the conditions are deterministic.

Vendor Managed Inventory for Multi-Vendor Single-Manufacturer Supply Chain: A Case Study of Instant Noodle Industry

This paper develops a vendor-managed inventory (VMI) model for a multiple-vendor, single-manufacturer supply chain, in which the first stage members can be traders and/or producers and the second stage member is a manufacturer. The model utilizes a realistic transportation cost which is dependent on the sizes (small- or medium-sized) of trucks. It can determine suitable sizes and numbers of trucks that minimize the transportation cost. A genetic algorithm (GA) technique, implemented in MATLAB software, is used to determine the best solution to the problem. A case study in the instant noodle industry is conducted to demonstrate the usefulness of the proposed model. Based on the experimental results, the VMI model has reasonable behaviors using sensitivity analysis. To reduce the inventory level of raw materials, the penalty cost may be set at a relatively high level or the upper inventory limits may be set at relatively low levels, without significantly affecting the average total cost per period of the entire supply chain. When the vendors are allowed to make decision independently, the solution is still the same as the solution from the proposed VMI model, which means that the manufacture does not take advantage of the vendors.

Optimal Inventory Level Control and Replenishment Plan for Retailers

In vendor managed inventory (VMI) operations, it is necessary for both the suppliers and the customers to reach an agreement on the maximal and minimal inventory level. In practice, in VMI, inventory levels are decided manually by planning personnel, based on their experience and past operating records. From a system optimization point of view, the determination of the upper and lower inventory levels in storage areas is complicated, necessitating analysis of many factors. Consequently, it may not be possible to obtain the best planning results, to determine and maintain the optimum levels of inventory. In this study, we utilize network flow techniques to build a replenishment model to deal with the upper-and-lower inventory level control problem, with the objective of minimizing the total cost in short-term operations, subject to inventory level control and other operating constraints. The model is formulated as an integer network flow problem with side constraints and is characterized as NP-hard in terms of optimization. To efficiently and effectively solve the large-scale problems that occur in the real world, a solution algorithm is also developed. Finally, numerical tests are conducted using real data from a major retail company in northern Taiwan. The results demonstrate the usefulness of the proposed model and solution algorithm for replenishment planning in actual practice.

Smart Supply Chains with vendor managed inventory, coordination, and environmental performance

A dynamic brick-and-mortar Supply Chain (SC) evaluates the benefits of implementing smart applications and intelligent systems to improve the efficiency of a Vendor Managed Inventory (VMI). In the SC game, the manufacturer sets the production rate and replenishes the inventory at the retailer’s store. The retailer sets the price, which affects both the sales and the inventory. Firms share the revenues and the inventory costs through a sharing agreement. The inventory dynamics increase in the production rate, decrease in the sales and vary according to some stochastic and time-independent error terms. The adoption of a smart application allows the SC to remove these error terms. Nevertheless, the consulting company implementing the intelligent system charges fees that depend on the error term amplitude and inventory level. Furthermore, intelligent solutions allow the SC to better satisfy the consumers, although their impact on production and emissions may be detrimental questioning whether they lead to a responsible digitalization. We identify the conditions under which the adoption of a smart system is economically beneficial for the whole SC as well as its operational, environmental, and SC coordination implications.

A variable MIP neighborhood descent for the multi-attribute inventory routing problem

In this paper we study a Multi-Attribute Inventory Routing Problem (MAIRP). A mathematical formulation and exact solution algorithms are introduced for this problem. More precisely, we extend the Multi-Depot Inventory Routing Problem (MDIRP) in order to consider the multi-product case with a heterogeneous fleet of vehicles and explicit constraints for the route duration. The MAIRP is an NP-hard problem more complex than the classical Inventory Routing Problem. Moreover, it captures many features that can be found in real applications of a vendor-managed inventory strategy. We introduce a hybrid exact algorithm to solve it, in which several Mixed Integer Programming (MIP) models are solved to explore the neighborhoods of a Variable Neighborhood Search (VNS) scheme applied to the MAIRP. We design several neighborhoods that are based on the features of the problem. The impact of this hybridization is a faster convergence of the model and an accelerated resolution process with respect to a branch-and-cut algorithm applied to the regular MIP formulation. Extensive computational results on new and existing instances from the literature on two benchmark problems and a real data set confirm the high efficiency of our algorithm.

Improving Interorganizational Information Sharing for Vendor Managed Inventory: Toward a Decentralized Information Hub Using Blockchain Technology

Supply chain literature has long recognized the benefits of information sharing. Researchers and practitioners see high potential for improving processes, enabling new replenishment policies, and enhancing supply chain integration. Even though information technology represents a vital role as a driver and a success factor for implementing information sharing, established technologies still do not reflect the highly decentralized and fragmented characteristics of complex and often global supply chains. Early research shows that blockchain might be an enabler for the supply chain management. However, little is known about how blockchain might improve information sharing for complex, multitier supply chains. Therefore, this article aims at analyzing how and to what extent blockchain can facilitate information sharing for vendor managed inventory by designing a software prototype based on Hyperledger Fabric using the design science research approach. This research took place in close cooperation with a leading German healthcare technology manufacturer, which allowed us to base our study both on literature and practical insights. With our results, we contribute to the supply chain knowledge base by introducing the decentralized information hub model, describing how companies utilize decentralized technologies, such as blockchain, to facilitate information sharing.

Mathematical Model for Centralized Supply Chains with Decisions Involving Shared Resources

Context: Cooperation in supply chain management is an important issue considering the global performance of the different echelons of a specific supply chain. In this sense, applying logistic strategies such as VMI (Vendor Managed Inventory) allows a system to manage distribution processes from a central point or depot. Additionally, the components of the chain work more closely with it, which allows increasing global performance, instead of individually developing each sector. Method: A stochastic mathematical model is proposed which considers a network of customers, where products are delivered from a central depot. These customers can share part of their product with the central depot for redistribution, aiming to minimize shortage for other customers. A mathematical model is proposed which includes the elements involved in distribution processes. It is then reformulated to consider shortage and the linearization of some of its elements. Results: Results show that implementing or adapting logistic strategies, such as managing from a central point and sharing resources along the supply chain, allows companies to reduce the complexity of some decisions and improve performance. Conclusions: Implementing logistic strategies such as centralized management and sharing resources along a supply network allows companies to reduce the complexity of some decisions and, in turn, improve their performance.

Vendor-managed inventory supply chain coordination based on commitment-penalty contracts with bilateral asymmetric information

ABSTRACT Vendor Managed Inventory (VMI) is adopted to improve the efficiency of overall supply chain. Research shows that asymmetric information might cause supply chain inefficiency. This study looks at how VMI supply chain coordination can be achieved in an asymmetric information environment. We propose a commitment penalty contract to improve the performance of a VMI supply chain where the manufacturer holds private production cost information and the retailer holds private demand information. The replenishment quantity and contract under symmetric information and bilateral asymmetric information are solved respectively. We find that the commitment penalty contract may reveal the private information of the manufacturer and the retailer can coordinate the supply chain under the asymmetric information of bilateral information. We present numerical examples to illustrate the effectiveness of the contract and develop managerial guidelines.

Coordination of VMI supply chain with replenishment tactic under risk aversion and sales effort

This paper considers a vendor-managed inventory (VMI) supply chain consisting of a risk-averse supplier and a risk-neutral retailer engaging in sales promoting efforts. Under the conditional risk at value, we examine three different types of contracts with the replenishment option for coordinating the VMI supply chain, namely, a risk diversification and cost sharing (RDCS) contract, an option and cost sharing contract, and a subsidy and cost sharing contract. Firstly, we derive the optimal production strategy and analyze the capability of each of the proposed contracts in coordinating the VMI supply chain. We find that all of those contracts can achieve coordination of the supply chain with Pareto improvement. Secondly, we also show that both the supplier and the retailer prefer the RDCS contract over the other two contracts. Finally, we use numerical experiments to analyze the impact of risk aversion on contracts’ parameters.

Application of Vendor Managed Inventory Cooperation Model to Encourage Distribution of Products in Ud. Sari Jaya

UD. Sari Jaya is a home industry that produces cassava and other tubers into chips. Cassava chips are the main product because of their high level of consumer interest in the product compared to others. The Problems faced by UD. Sari Jaya is that they are unable to meet the market demand more effectively. In the process of providing the needs, UD. Sari Jaya often performs several deliveries to each Stall caused by the lack of product availability at Stall, causing demand to be unfulfilled. The number of Retailers to be served, the lack of information on needs is one of the obstacles in the process of inventory replenishment. Vendor Managed Inventory (VMI) is one of the Collaboration Model in the supply chain between producers and retailers where collaboration is expected to make arrangements regarding the number of lot sizes order as well as the frequency of deliveries to each Stall with a minimum total cost, by thus UD. Sari Jaya can have good control in the process of fulfilling the needs of this Cassava Chips.

A geometric programming approach for a vendor managed inventory of a multiretailer multi-item EPQ model

Due to the uncertain situations of the world, considering inventory management in a stochastic environment gains a lot of interest. In this paper, we propose a multi-item economic production quantity (EPQ) model with a shortage for a single-vendor, multi-retailer supply chain under vendor managed inventory (VMI) policy in a stochastic environment. Three stochastic constraints are developed in the model. Geometric programming (GP) approach is employed to find the optimal solution of the nonlinear stochastic programming problem to minimize the mean-variance of the total inventory cost of the system. Since the problem is in the Signomial form, first, an algorithm is used to convert the model into the standard GP form. The performance of the addressed model and the solving method are evaluated based on computational experiments and sensitivity analysis. A case study in an Iranian furniture supply chain is conducted to show the applicability of the proposed model and 17.78% improvement in terms of total cost is gained.