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The aspire of the study is to examine the inventory management procedure and to differentiate the key factors that collision inventory management practices, explore the proficient and viable inventory management approaches. Inventory management is a significant area of the developed industry. If the company fails to manage inventory, it will face failure. It is a challenge for the company to maintain a fair inventory. There are different inventory management techniques available for maintaining a fair inventory level in the company. The essential purpose of this article is to revise inventory management techniques used in the steel industry and find out some methods for the development of the inventory management process of the concerned company.

The traditional way retailer keeps their sales and inventory details is in spreadsheets which are not effective anymore when the size of the shop gets bigger. This is because more items will be made available in a larger quantity, thus tracking the sales made with inventory level in the shop would be complicated and time consuming for the retailer. this project will provide solution for retailers that are still using traditional way in keeping their inventory data like ‘Yochang Store’ in Ising Carmen Davao del Norte by creating inventory system. Sales and Inventory Management System is a computer- based system that provides the shop structure for maintaining and controlling goods to be stocked. The approach of Sales and Inventory Management System is commonly used to avoid product overstock or outrages by integrating daily ‘Point of Sales’ with store’s inventory level

This paper studies an inventory management problem faced by an upstream supplier who is in a collaborative agreement, such as vendor managed inventory (VMI), with a retailer. A VMI partnership provides the supplier an opportunity to manage inventory for the supply chain, in exchange for point-of-sales (POS) and inventory level information from the retailer. However, retailers typically posses superior local market information and, as has been the case in recent years, are able to capture and analyze customer purchasing behavior beyond the traditional POS data. Such analyses provide the retailer, access to market signals that are otherwise, hard to capture using POS information. We demonstrate and quantify the implication of the fi nancial obligations of each party in VMI that renders communication of such important market signals as non-credible. To help institute a sound VMI collaboration, we propose a learn-and-screen dynamic inventory mechanism for the supplier to effectively manage inventory and information in the supply chain. The proposed mechanism combines the ability of the supplier to learn about market conditions from POS data (over multiple selling periods) and to dynamically determine when to screen the retailer and acquire his private demand information. Inventory decisions in the proposed mechanism serve a strategic purpose in addition to their classic role of satisfying customer demand. We show that our proposed dynamic mechanism signi cantly improves the supplier's expected pro t and increases the e fficiency of the overall supply chain operations under a VMI agreement. In addition, we determine the market conditions in which a strategic approach to VMI results in signi cant pro t improvements for both rms, in particular, when the retailer has high market power (i.e., when the supplier highly depends on the retailer) and when the supplier has relatively less knowledge about the end customer/market compared to the retailer.

In this paper, we consider a stochastic inventory system of two products where a fi xed proportion of the unsatisfied ed demand for one product purchases the other product as a substitute. We formulate the optimal inventory control problem as a dynamic program; and by developing two key technical results, we derive several important structural properties (including joint concavity and submodularity) of the value functions. Based on these properties, we show that the optimal inventory policy for each product in each period is a base-stock policy where the base-stock level is a decreasing function of the maximum of the initial inventory level of the other product and a critical control number. We further prove that, as the initial inventory level of the other product increases, the base-stock level of each product converges to the optimal base-stock level of an auxiliary single-product lost-sales inventory system. We also provide intuitive interpretations and a numerical example to facilitate the understanding of our analytical results.

This study aims to understand the impact of product price discount program taken by PTK toward PT EPM logistic performance as their logistical subsidiary. Product named MBF is being used in this research as it represents the characteristics of discounted products in the company. Using actual sale, sale forecast, inventory product 2013-2014 datas, and system dynamics approach, we intend to show that price discount policy causes fluctuation of sales and inventory level which in turn affect the company's profits. Research concludes that the coordination between marketing and logistics company in prder to respond the price discount prolicy provides a /- 3,5% higher profit for the company along with 7,69% reduction in transportation cost and 20% stock out reduction.

Unlike in a traditional store environment where inventory is directly visible to customers, Internet retailers can selectively choose how to divulge inventory level information to customers. For example, when viewing a particular item page, online shoppers may either see merely “in stock” or a specific inventory level. By choosing the appropriate inventory-level cue to display, a retailer can selectively signal stock-out risk to customers. In this paper, we analyze the optimal structure of an online retailer’s inventory disclosure and pricing policy, in a two-period setting — a regular selling period followed by a clearance period. Consumers may potentially face uncertainty regarding the firm’s inventory level, as well as the overall market demand. We show that there exists an inventory level threshold below which a retailer should optimally disclose inventory, and above which masking (i.e., showing only “in stock”) is optimal. Even though the optimal price decreases in the stock level, we show that equilibrium sales may increase or decrease, highlighting the non-intuitive consumer behavior implications of selective inventory disclosure. The optimal “threshold-type” inventory disclosure that we derive reflects the practice of several prominent online retailers selling fashion products, and is new to the literature as prior models of inventory sharing invoked assumptions that led to either consistent disclosure or consistent masking to be optimal. We also extend the model to consider a stochastic market size, and thus highlight that the threshold policy structure continues to hold with demand uncertainty.

A behavioral study on the newsvendor problem without demand distribution knowledge or realized demands is conducted. We configure a censored-information scenario where only sales data are provided. With laboratory experiments, we analyze participants ordering levels and ordering oscillations. It is observed that participants perform a significant learning process in the censored-information scenario. Moreover, we find that participants make orders by anchoring on the previous-period sales and adjusting to an adapted inventory level. Based on the observations, we propose an exponential-type learning model to describe the behavior of decision makers. The model outperforms several models in the literature.

We show simple yet optimal results to update the inventory/capacity levels, expected profit, fill rates, and service levels of substitutable resources, in response to an updating of the mean demand forecasts for the resources. We find that a change in the mean demand of one resource does not affect the optimal inventory level of any other resource. The results are obtained for demands with location-scale distributions, and for a revenue structure satisfying a triangle property such that the manager will always use the inventory of a resource to meet its own demand first before using it for substitution. The results for updating the performance measures also extend to managers who maintain non-optimal inventory/capacity levels. Implications for procurement, sales and operational planning, and multi-store operations are discussed.

Trust has a substantial impact in supply chain relationships. While the effect of trust on supply chain performance has been extensively studied, relatively little is known about the link between trust, inventory replenishment decision-making, and inventory behavior. This paper examines the impact of inventory manager’ trust perception on their replenishment decision and their extended inventory. We design an experiment with unknown market demand, local information, and under continuous replenishment review. We analyze the experimental data on the individual and echelon levels. We find that lower trust in customer leads to higher order quantity, lengthen order time intervals, and higher extended inventory at the individual levels. Results at the echelon level also show some supports. Moreover, our results show that inventory managers prefer to hold higher inventory level when they have lower trust in their upstream supplier. We find that distributor exhibits the lowest trust in customer, highest order quantity and longest order time intervals among echelons. Furthermore, we find that retailer is the only echelon that considers trust in supplier while placing order quantities to upstream supplier.

We consider preventive transshipments between two stores in a decentralized system with two demand subperiods. Replenishment orders are made before the first subperiod, and the stores may make transshipments to one another between the subperiods. We prove that the transshipment decision has a dominant strategy, called a control-band conserving transfer policy, under which each store chooses a quantity to transship in or out that will keep its second-subperiod starting inventory level within a range called a control band. We prove that the optimal replenishment policy is a modified base-stock policy in which the order-up-to level depends on the initial inventory and capacity level at the other store. Finally, we prove that there does not exist a transfer price that coordinates the decentralized supply chain. Our research also explains many of the differences between preventive and lateral transshipments, including differences in the optimal transfer policies and the existence or nonexistence of transfer prices that coordinate the system.

A lack of reliable storage data has significantly restricted studies of futures markets. By explicitly incorporating storage data, we report several new findings and provide quantitative guidance on the importance of storage for determining convenience yields and risk premia, and hence for risk management and (real) options valuation. Using a unique storage dataset from the crude oil, copper, gold and natural gas markets we show that storage possesses forecast power for commodity futures. Inventories can forecast up to 4.7 percent of the weekly variation in futures returns. This predictable variation is both statistically and economically significant for crude oil, copper and natural gas. Moreover, our empirical evidence quantifies inventory level dependence in convenience yields, documenting that up to 40 percent of the weekly variation in convenience yields can be explained by inventories.

The paper empirically investigates market makers' behavior on Nasdaq Europe. The impact of market makers' competition and some other microstructure effects on spreads are analyzed. We perform a decomposition of the spread into its components in both Huang & Stoll (1997) and Lin, Sanger & booth (1995) settings. The main finding is the small adverse selection component on this rather thin market, together with a high serial correlation in the order flow. Although the spread decomposition does not succeed in identifying inventory costs, we show that market makers manage their inventories effectively. However, reversion to a desired inventory level appears to be slow, compared to what has been documented on more active markets.