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This study examines the problem of optimally dynamic joint decisions, including replenishment scheduling/quantity, retail price, wholesale price, and revenue-sharing allocation, in a vertically decentralised single-manufacturer Stackelberg and single-retailer channel over a multi-period planning horizon, subject to deteriorating goods and multivariate demand function. This study uses a calculus-based formulation combined with dynamic programming techniques to solve the channel coordination decision problem. Additionally, three arrangements, namely price-only contract, revenue-sharing contract, and revenue-sharing plus linear rebate and side-payment contract for channel coordination, are developed under retailer-managed inventory (RMI) and vendor-managed inventory (VMI) systems, respectively. The analysis reveals that the proposed policy under the VMI system with the revenue-sharing plus linear rebate and side-payment contract tends to obtain low retail prices and large demand quantity, and results in near-perfect coordination, including greater system efficiency and Pareto improvements, for the vertically decentralised dynamic channel. [ABSTRACT FROM PUBLISHER]

Motivated by empirical evidence, this article focuses on the behaviour of a store inventory exposed to inventory record inaccuracy. The inventory, controlled by an infinite horizon, single-stage, single-product periodic-review policy, is subject to shrinkage errors that cause a difference between the physical and information system inventory levels. We model a set of scenarios depending on the technology available to track shrinkage in the store. In scenarios where a technology such as Radio Frequency IDentification (RFID) is not used, inventory is controlled by estimating the expected shrinkage rate. We assume that an inspection process is performed at a regular frequency of N selling periods. We analyse two situations that permit management of the joint ordering and inspection policy based on the information the inventory manager has on shrinkage errors. A comparison between these two situations permits us to analyse the impact of shrinkage errors and the value of taking into account the inventory inaccuracy issue when optimising the inventory and inspection policies. The deployment of the RFID technology produces two benefits: total visibility of the shrinkage rate and the elimination of shrinkage errors. A comparison of the scenarios enables us to evaluate the economic impact of inventory record inaccuracies, which can be significant, particularly in systems with a poor estimation of the error parameter as well as with a high inspection cost. [ABSTRACT FROM PUBLISHER]

This paper revisits the traditional supplier-buyer integrated production-inventory model which deals with the problem of a manufacturer (supplier) supplying a product to a retailer (buyer) serving the consumer market with constant stationary demand. The product is manufactured in batches at a finite rate. The supplier's production batch is depleted by the buyer's replenishment orders at periodic intervals. The buyer's inventory is then consumed by the market demand at a fixed rate. The problem is the simultaneous computation of the manufacturer's production lot-size and the buyer's replenishment order quantity, i.e. the integrated production-inventory policy parameters. The key characteristic considered in this paper is that the manufacturing process is imperfect, and, hence, there are defective items in each production lot. As a result, each replenishment order shipped to the buyer includes defective products and the non-defective percentage in each such shipment is random. Considering the case where the supplier replenishes the buyer via equal-sized shipments, we develop an analytical expression of the total expected cost for the supplier-buyer system under consideration, with and without a considerable inspection time. We first examine the case where the inspection time is negligible, and then we present a generalisation to consider the inspection time explicitly. Our goal is to model the impact of random yield on the system performance. Our findings are useful for computing the integrated production-inventory policy parameters while considering the supply uncertainty due to an imperfect manufacturing process. Through numerical examples, we quantify the impact of supply with random yield on the system performance and illustrate its relationship with the demand and production rate. [ABSTRACT FROM AUTHOR]

Conventional wisdom in marketing holds that (1) retailer forward buying is a consequence of manufacturer trade promotions and (2) stockpiling units helps the retailer but hurts the manufacturer. This article provides a deeper understanding of forward buying by analyzing it within the context of manufacturer trade promotions, competition, and demand uncertainty. The authors find that regardless of whether the manufacturer offers a trade promotion, allowing the retailer to forward buy and hold inventory for the future can, under certain conditions, be beneficial for both parties. Disallowing forward buying by the retailer may lead the manufacturer to lower merchandising requirements and change the depth of the promotion. In competitive environments, there are situations in which retailers engage in forward buying because of competitive pressures in a prisoner's-dilemma situation. Finally, when the authors consider the case of uncertain demand, they find further evidence of strategic forward buying. In particular, the authors find cases in which the retailer orders a quantity that is higher than what it expects to sell in even the most optimistic demand scenario. [ABSTRACT FROM AUTHOR]

We solve a variation of a classic make‐to‐stock inventory problem introduced by Gavish and Graves. A machine is dedicated to a single product whose demand follows a stationary Poisson distribution. When the machine is on, items are produced one at a time at a fixed rate and placed into finished‐goods inventory until they are sold. In addition, there is an expense for setting up the machine to begin a production run. Our departure from Gavish and Graves involves the handling of unsatisfied demand. Gavish and Graves assumed it is backordered, while we assume it is lost, with a unit penalty for each lost sale. We obtain an optimal solution, which involves a produce‐up‐to policy, and prove that the expected time‐average cost function, which we derive explicitly, is quasi‐convex separately in both the produce‐up‐to inventory level Q and the trigger level R that signals a setup for production. Our search over the (Q, R) array begins by finding Q0, the minimizing value of Q for R = 0. Total computation to solve the overall problem, measured in arithmetic operations, is quadratic in Q0. At most 3 Q0 cost function evaluations are required. In addition, we derive closed‐form expressions for the objective function of two related problems: one involving make‐to‐order production and another for control of an N‐policy M/D/1 finite queue. Finally, we explore the possibility of solving the lost sales problem by applying the Gavish and Graves algorithm for the backorder problem. [ABSTRACT FROM AUTHOR]

We consider a decentralized supply chain (DSC) under resale price maintenance (RPM) selling a limited‐lifetime product to forward‐looking customers with heterogeneous valuations. When customers do not know the inventory level, double marginalization under RPM leads to a higher profit and aggregate welfare than without RPM under a two‐part tariff contract (TT). Both RPM and TT profits are higher and aggregate welfare is lower than in a centralized supply chain (CSC). When customers know the inventory, RPM coincides with CSC. Thus, overestimation of customer awareness may lead to overcentralization of supply chains with profit loss comparable with the loss from strategic customers. The case of RPM with unknown inventory is extended to an arbitrary number of retailers with inventory‐independent and inventory‐dependent demand. In both cases, the manufacturer, by setting a higher wholesale price, mitigates the inventory‐increasing effect of competition and reaches the same profit as with a single retailer. The high viability and efficiency of RPM in using double marginalization as a strategic‐behavior‐mitigating tool may serve as another explanation of why manufacturers may prefer DSC with RPM to a vertically integrated firm. [ABSTRACT FROM AUTHOR]

We consider a general two‐echelon distribution system consisting of a depot and multiple sales outlets, henceforth referred to as retailers, which face random demands for a given item. The replenishment process consists of two stages: the depot procures the item from an outside supplier, while the retailers' inventories are replenished by shipments from the depot. Both of the replenishment stages are associated with a given facility‐specific leadtime. The depot as well as the retailers faces a limited inventory capacity. Inventories are reviewed and orders are placed on a periodic basis. When a retailer runs out of stock, unmet demand is backlogged. We propose a new approach to the above class of dynamic programming models based on Lagrangian relaxation. Every choice of the vector of Lagrange multipliers generates a lower bound via the solution of a single dynamic program (DP) with a one‐dimensional state‐space. The best such bound is obtained by maximizing over the vector of multipliers. The strategy that is optimal for this (maximal) lower bound DP employs an (s, S) ordering policy (generally, with time‐dependent policy parameters). To arrive at an upper bound and an implementable heuristic, this (s, S) policy is paired with one of several possible allocation policies that allocate the system‐wide inventory across the different facilities. We report on an extensive numerical study with close to 14 000 instances which evaluates the accuracy of the lower bound and the optimality gap of the various heuristic policies. The study reveals that the lower bound and the heuristic strategy that is constructed on its basis perform exceedingly well, almost across the entire parameter spectrum, including instances where demands are rather volatile or the average cycle time between consecutive orders is relatively large. The exception arises when storage at the depot is as expensive as at the retailer level and the retailers have large storage capacities. [ABSTRACT FROM AUTHOR]

The authors propose a new model of response pattern to a direct marketing campaign. They estimate their model and tour competing model forms using a new maximum likelihood procedure for response data from tour different campaigns. Their proposed model fits the data very well. The authors then offer a method to use the model to estimate the eventual number of responses to a campaign using early return data and knowledge of past campaigns. Finally, the authors suggest an application to predicting returns to mail surveys. [ABSTRACT FROM AUTHOR]

The effects of brand salience on brand recall were investigated in five experiments, each involving a different product category. The authors demonstrate that increasing the salience of a single brand can significantly impair unaided recall of competing brands. The effect was observable even in the early stages of the recall process. [ABSTRACT FROM AUTHOR]

A graphical method is proposed as a tool for evaluating the impact of different control rules or different shop configurations upon shop performance. The shop operating characteristics curve simultaneously displays indices for the throughput rate, the flow time, and the level of work-in-process. The method of constructing and applying the shop operating characteristics curve is illustrated using several examples. The invariance property of the curve also is discussed. [ABSTRACT FROM AUTHOR]

Marketing executives and mathematicians have joined forces in a search for improved decision models to handle such problems as new-product development, media selection, retail inventory control, and size of sales force. The author of this article explains and illustrates those operations research models which hold the greatest promise in the marketing area. [ABSTRACT FROM AUTHOR]

The discount house is the latest American marketing innovation to be exported and to be met with the cry "it can't happen here." In an article in the April, 1962 "Journal of Marketing," the author generalized that marketing activities that would work in the United States would usually work in Australia. Here he examines the discount house against the Australia marketing scene and in Mexico, another market which has shown some willingness to accept American marketing ideas but not without resistance. [ABSTRACT FROM AUTHOR]

A section of abstracts summarizes recent articles relating to retailing, including "Drug Store Failures in 1958," published in the April 6, 1959, issue of "American Druggist," as well as "Organizing Chain Variety Stores to Sell More Goods," by DeFord C. Mills, published in the Summer 1959 issue of the "Journal of Retailing," and "About Department Store Selling," by R. H. Myers, published in the May 1959 issue of "Delta Sig."

The article presents abstracts from various publications on the topic of statistical data in marketing, including "Census Bureau Pretest of Retail Inventory Survey," "Census Bureau Survey of Multiunit Companies," and "The Functional Distribution of Income in the United States, 1850-1952."

The article presents information on the flow of merchandise in the men's clothing industry. A survey is presented showing a measure of unit sales from retailers to consumers, purchases by retailers from manufacturers, and the ratio of retail stocks to consumer sales. The author looks at demand for men's suits and analyzes the retail stocks at several retail stores. Details related to the principal uses of merchandise flow analysis and the practical application of survey results are presented. Methods of applying merchandise flow analysis to other industries are mentioned.

The article presents an inventory stocking plan for small businesses. The author states that the marketplace favors the sellers, but expects the future to see buyers' power increase with improved retail store volume. An ideal stock plan is described; it would involve complete inventory turnover and the customers' preferences for sizing, colors, price lines, materials and styles all being met. Examples are provided in which store owners improperly gauged the market, made incorrect guesses, or accepted a salesman's misinformed advice. A discussion of which type and size stores utilize the stock planning is presented.

The article discusses the practice of measuring retail inventories. Knowledge of monthly inventory trends is recognized as a useful guide for business management and an important factor in economic analysis and planning. Trends of orders, production and sales require this additional item in order to be the basis of policy-making on a large or small scale. In 1940 the U.S. Bureau of Census sought to assess the usefulness and validity of measuring monthly retail inventories. Preliminary analysis found that there would be inherent difficulties in obtaining and assessing the data.

Models that facilitate analysis of decision making in hierarchial systems, for example involving wholesalers and retailers, can ultimately be of significance not only to academic people concerned with economics, distribution and production but to others as well. The whole idea of a hierarchy of interdependent decision processes within a system may be more realistic for many purposes than some of the more widespread single decision concepts. The focus on inventory decisions, as one class of a potentially larger species, provides both a tangible beginning and a problem area where some mathematical work has been done. The purpose is to explain a relatively single model as a means of establishing the need for theory in this area and the potentially useful though unexplored generalizations from this model. [ABSTRACT FROM AUTHOR]

In this study, an integrated economic order quantity inventory model for deteriorating items with inventory level and ware house capacity constraint is considered. The proposed model allows shortage for buyer and demand to be considered as a constant. By using Lagrange's multiplier technique optimum order quantity is obtained to minimize the system cost while satisfies the both constraints. Numerical examples are also illustrating developed model. [ABSTRACT FROM AUTHOR]

We study a single‐stage, continuous‐time inventory model where unit‐sized demands arrive according to a renewal process and show that an (s, S) policy is optimal under minimal assumptions on the ordering/procurement and holding/backorder cost functions. To our knowledge, the derivation of almost all existing (s, S)‐optimality results for stochastic inventory models assume that the ordering cost is composed of a fixed setup cost and a proportional variable cost; in contrast, our formulation allows virtually any reasonable ordering‐cost structure. Thus, our paper demonstrates that (s, S)‐optimality actually holds in an important, primitive stochastic setting for all other practically interesting ordering cost structures such as well‐known quantity discount schemes (e.g., all‐units, incremental and truckload), multiple setup costs, supplier‐imposed size constraints (e.g., batch‐ordering and minimum‐order‐quantity), arbitrary increasing and concave cost, as well as any variants of these. It is noteworthy that our proof only relies on elementary arguments. [ABSTRACT FROM AUTHOR]

We analyze not-for-profit Medical Surplus Recovery Organizations (MSROs) that manage the recovery of surplus (unused or donated) medical products to fulfill the needs of underserved healthcare facilities in the developing world. Our work is inspired by an award-winning North American non-governmental organization (NGO) that matches the uncertain supply of medical surplus with the receiving parties' needs. In particular, this NGO adopts a recipient-driven resource allocation model, which grants recipients access to an inventory database, and each recipient selects products of limited availability to fill a container based on its preferences. We first develop a game theoretic model to investigate the effectiveness of this approach. This analysis suggests that the recipient-driven model may induce competition among recipients and lead to a loss in value provision through premature orders. Further, contrary to the common wisdom from traditional supply chains, full inventory visibility in our setting may accelerate premature orders and lead to loss of effectiveness. Accordingly, we identify operational mechanisms to help MSROs deal with this problem. These are: (i) appropriately selecting container capacities while limiting the inventory availability visible to recipients and increasing the acquisition volumes of supplies, (ii) eliminating recipient competition through exclusive single-recipient access to MSRO inventory, and (iii) focusing on learning recipient needs as opposed to providing them with supply information, and switching to a provider-driven resource allocation model. We use real data from the NGO by which the study was inspired and show that the proposed improvements can substantially increase the value provided to recipients. [ABSTRACT FROM AUTHOR]

Present study, we have developed inventory models with allowable delay in payment facility. Linearly time increasing demand rate is presumed. It is assumed that items deteriorate with Weibull distribution decay rate. During the trade-credit period retailer can earn interest and there is no need to pay to the supplier at this time. Now days in spirited market it is additional convenient to provide the trade-credit facility to attract customers. A mathematical illustrations are provided to validate the concept of model and finally sensitivity analysis has been carried out to understand the behavior of model. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to investigate a single-vendor single-retailer production-inventory model with immediate return for imperfect items under an unequal-sized policy. It is assumed that the batch quantity will be received by the retailer innshipments. The first shipment is of small size followed by (n?1) equal-sized shipments of size just equal to the first shipment size times the ratio of the production rate to the demand rate. Moreover, it is assumed that a 100% inspection process is conducted to screen out the defectives contained in the received lot and the defectives screened out during the 100% inspection process will be returned to the vendor immediately. First, the expected annual integrated total profit is constructed. Next, by maximizing the expected annual integrated total profit, the optimal number of shipments in a cycle and the optimal sizes of the shipments in a cycle are determined. Finally, a numerical example is provided to illustrate the proposed model and demonstrate the usefulness of the proposed model when compared with the integrated model under equal-sized policy. [ABSTRACT FROM AUTHOR]

Purpose The retail revolution swing from traditional distribution to e-tailing services and unprecedented increase in internet adoption insist practitioners to diversely plan warehousing strategies. More than practically required storage space has been identified as wastes, and also it does not improve performance. An organized framework integrating storage design policies, operational performance and customer value improvement for retail-distribution management is lacking. Therefore, the purpose of this paper is to develop broad guidelines to design the “just-right” amount of forward area, i.e., “lean buffer” answering the following questions: “What should be lean buffer size? How effective the forward area is? As per demand variations, which storage waste (SKU) should be allocated with how much storage space? What is the amount of storage waste (SW)? How smooth the material flow is in between reserve-forward area?” for storage allocation in cosmetics distribution centers.Design/methodology/approach After forecasting static storage allocation between two planning horizons, if a particular SKU is less or non-moving, then it will cause SW, as the occupied location can be utilized by other competing SKUs, and also it impedes material flow for an instance. A dynamically efficient and self-adaptive, knapsack instance based heuristics is developed in order to make effective storage utilization.Findings The existing state-of-the-art under study is supported with a distribution center case, and the study investigates the need of a model adopting lean management approach in storage allocation policies along with test results in LINGO. The sensitivity analysis describes the impact of varying demand and buffer size on performance. The results are compared with uniform and exponential distributed demands, and findings reveal that the proposed heuristics improves efficiency and reduce SWs in forward-reserve area.Originality/value The presented model demonstrates a novel thinking of lean adoption in designing storage allocation strategy and its performance measures while reducing wastes and improving customer value. Future research issues are highlighted, which may be of great help to the researchers who would like to explore the emerging field of lean adoption for sustainable retail and distribution operations. [ABSTRACT FROM AUTHOR]

This article examines Accounting Standards Update 2015-11, Simplifying the Measurement of Inventory. Through the accounting simplification initiative, the Financial Accounting Standards Board is reviewing areas of U.S. generally accepted accounting principles (GAAP) that can be simplified while still maintaining high-quality accounting standards. Under this new standard, companies will be required to value inventory using the lower of cost or net realizable value. Companies using the last-in, first-out (LIFO) and retail inventory methods will be scoped out of applying the new standard. © 2016 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

This paper examines the differences in the behaviors of high (HIT) and low inventory turnover (LIT) retailers in responding to demand shocks. We identify quantity and price responsiveness as two mediating mechanisms that distinguish how high and low inventory turnover retailers manage demand shocks. Using quarterly firm-level data of 183 U.S. retailers between 1985 and 2012, we find that HIT retailers are able to respond quickly by changing their purchase quantities in response to demand shocks, whereas LIT retailers primarily rely on price changes to manage demand shocks. In addition, we examine the differential implications of these mechanisms on the financial performance of HIT and LIT retailers. We find price responsiveness to be a less effective strategy, compared to quantity responsiveness, in reducing excesses and shortages of inventory. Finally, the negative financial impact of a given amount of excess and shortage of inventory is eight times more severe for LIT retailers compared to HIT retailers. [ABSTRACT FROM AUTHOR]

Which, if any, of a firm's inventions should it patent? Should it patent at all? Many companies engaged in an innovation race seek a patenting strategy that balances protection of their intellectual property against the knowledge spillovers resulting from disclosure requirements. Not much is known about factors that determine the patenting strategy best able to resolve this trade-off. Although scholars in various management, economics, and engineering disciplines have researched patents and patenting regimes, little work has addressed the normative issues that pertain to forming an appropriate firm-level patenting strategy. We develop an inventory of real-life patenting strategies and integrate them into a coherent framework. Our simulation model characterizes the optimal patenting choices for different environmental and firm-level contingencies while capturing the dynamics between competing firms.We identify the firm's research and development strategy as the most salient determinant of its optimal patenting strategy. Our research contributes to establishing a contingency theory of patenting strategies. [ABSTRACT FROM AUTHOR]