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Computerising inventory control procedures is usually an attempt to gain better control over stock availability. The effectiveness of the procedures depends on the time delays imparted by such events as order processing and delivery. Through these time delays, much of a finished goods physical distribution system is linked together through the inventory control procedures. Changing the length of any one time element through changes in inventory stocking rules, order processing methods or selected transportation services impacts on the economics of the entire physical distribution system. Little is understood about the effects of time change in such complex systems. In this article, the actual computer inventory control procedures of a chemical company were computer simulated. Physical distribution system design decisions and their associated time delay effects were explored by interrogating the model. Surprising effects were discovered, some of them being counter‐intuitive to what simple theory would predict. Management guidelines were provided as to the system‐wide economic consequences of change in individual elements of a physical distribution system.

In inventory theory the inventory holding cost per unit plays an important part. In most transactions concerning selling and buying a certain postponement of payment is offered or accepted by the seller. This should have some consequences for the order size and can be regarded as a kind of discount. Traditionally, when average costs (AC) are used, these kinds of effects are not explicitly incorporated in the classical formulas for economic order quantities (EOQs). On the other hand, such effects have been treated to a certain degree in the literature when a present value criterion (PVC) is used to estimate the inventory holding costs over a certain time interval. However, in these models one does not differentiate between the holding costs incurred by the capital tied up in the inventory and other costs incurred by storing an item. Approaches this problem in an AC manner, but, opposed to the PVC, splits the inventory holding costs into two parts. Offers an EOQ formula for the simple case of a single item stored; enhances this formula for a situation where a family of items are ordered in a co‐ordinated way, and into a situation with stochastic demand for a single item. Finally, interprets the postponed payment in terms of an all unit discount.

In estimating desired inventory holdings business organizations must use some estimate of their cost of funds. While conceptually the overall or weighted average cost of capital would seem to be the appropriate measure, survey of senior U.S. and Canadian financial executives at large firms revealed that most of the responding firms used their cost of borrowed funds. As is demonstrated in the paper, use of the cost of borrowed funds rather than the overall cost of funds can cause inventory positions to be excessive during certain periods and deficient during other periods.

To develop just‐in‐time (JIT) purchasing threshold value (JPTV) models for ready mixed concrete (RMC) suppliers to decide whether or not to switch from an economic order quantity (EOQ) approach to a JIT purchasing approach for the purchase of their raw materials, when a price discount is offered.

The existing economic order quantity (EOQ) with a price discount versus the JIT purchasing cost comparative models neglect some important cost components under the inventory management systems, for example, the out‐of‐stock costs and the impact of inventory policy on product quality and production flexibility. In addition, these models do not empirically study the capability of an inventory facility to hold the EOQ‐JIT cost indifference point's amount of inventory. These models suggest that the JIT purchasing approach is always preferred to the EOQ approach when the JIT purchasing approach can capitalize on physical plant space reduction. The JPTV models developed in this study overcome the two limitations of the existing EOQ and JIT purchasing cost comparative models.

By developing the JPTV models, this study suggests that the theoretical advantages of JIT purchasing may have been overstated.

The field studies conducted in the RMC industries in Chongqing, China and Singapore supported the propositions in this study. The JPTV models, if adopted, would help to enhance performance in the RMC industries in other cities as well.

The purpose of this paper is to consider the use of temporary storage offered by intermodal transshipment points to position some stock of fast moving consumer goods in advance of demand; this floating stock concept combines transport and inventory management. Intermodal transport is compared with direct road transport for a supply chain.

First an analytical comparison is made which shows that the floating stock concept has advantages in inventories over pure road and intermodal transport. Next, a simulation study of a real case is made which quantifies the cost‐differences in detail.

It is found that both storage costs can be lowered and shorter response times be gotten by sending shipments in advance to intermodal terminals. The advance positioning can offset the disadvantage of a longer transit time in intermodal transport.

Demand needs to be somewhat predictable. The pooling effects depend on geographical layout of the customers. The availability of intermodal transport options is based on the situation in Western Europe.

The floating stock concept considers both the transport and inventory issues. By positioning some of the stock at transshipment points close to the customer in anticipation of demand, the concept can yield lower inventory costs as well as a lower customer lead time. The benefit for logistics service providers is a more regular supply chain. Using intermodal transport provides an opportunity to green the supply chain as the environmental impact per ton/kilometer is lower than road transport.

This paper draws on the areas of logistics and inventory management to consider the choice of transport mode; most studies look at these issues in isolation. Considering the holding and storage costs in addition to the distribution strategy enables a more thorough comparison of the transport modes.

The purpose of this paper is to propose a virtual forward-buying model that allows for forward buying but reduces the channel cost with no major behavioral change on the part of manufacturers and retailers.

Using simulations, the authors compare the proposed virtual forward-buying model with the traditional forward-buying and everyday-low-price approaches.

The authors find that the proposed model leads to lower overall channel costs that are shared equitably between both the manufacturer and the retailer.

No primary or secondary is used, a situation that is usually very difficult to find in this area.

The paper presents a new method to improve trade promotion efficiencies that does not require a drastic change of habits for either the manufacturer or the retailer; allows the practice of forward buying to continue; and leads to channel cost reductions for both parties.

The paper presents research in an area that is under-researched due to lack of data.

Evolving production technologies are altering the cost structures on which many supporting inventory ordering systems are based; for example, fixed costs compared with variable costs are increasing significantly. Unfortunately, many inventory ordering formulations consider only the variable portions of inventory ordering costs and inventory holding costs. To address this deficiency, departs from traditional categorizations and offers an inventory classification schema based on the functional roles served by the inventory items. Functional roles of inventory include transition, buffer, investment, maintenance, supplies and dead stock. Extending the schema, assesses the implications each functional role has for inventory cost containment, emphasizing the impact of evolving production technologies on inventory ordering policies and their relevance to functional roles.

Recent models comparing inventory costs under just‐in‐time (JIT) purchasing plans and economic order quantity (EOQ) purchasing plans have tended to favor EOQ purchasing in situations where annual demand of inventory is moderately large. Contends that these cost models are lacking dynamic cost components inherent in virtually all JIT purchasing plans. Presents a series of inventory purchasing cost models that extend prior methodology by Fazel by including relevant physical distribution cost savings. Additional comparative models are presented to further demonstrate how other relevant costs factors can be included in a comparative EOQ/JIT model. A cost comparison with an existing problem from the literature is used to illustrate the informational efficacy of new models.

Traditional inventory replenishment decisions in distribution systems have been reactive, but the availability of information throughout the distribution system means that other methods should be considered.

Presents a mathematical model to assist companies in their decision to switch from the economic order quantity (EOQ) to the just‐in‐time (JIT) purchasing policy. Determines an upper limit for the JIT purchase price of an item below which the manufacturer will be better off using JIT purchasing. Also determines the annual demand level at which the costs of EOQ and JIT purchasing will be equal (the indifference point). For demand levels above this indifference point EOQ is the less costly method while JIT is preferable for demand levels below this point. The model also predicts that JIT will be preferred for inventory items with higher purchase price, holding costs, or ordering cost.