Solving the Inventory Problem for the Sale of Seasonal Merchandise
针对小型零售商在孤立市场中销售季节性商品时面临的库存困境，分析了传统库存模型的不足，并提出了一个初步成功的新模型。
SOLVING THE INVENTORY PROBLEM FOR THE SALE OF SEASONAL MERCHANDISE The Problem Tom Morgan, owner and manager of Mountain Sporting Goods, faces his typical early February inventory dilemma. The Blue Ridge cross country ski tour will occur in three days; tourists have flooded into town for the event and business at Mountain Sporting Goods has been brisk for all kinds of Nordic ski equipment. If sales continue at the same pace for the rest of the season, Tom's Nordic department manager believes they will run out of the most popular items by the end of February. The manager wants to order more inventory immediately. Since most ski equipment is manufactured overseas, orders must normally be placed in July for October delivery. To acquire additional inventory for this season, Mountain Sporting Goods will have to buy from a wholesaler at premium prices. The inventory debacle from two years ago still haunts Tom. Anticipating a good ski season, he ordered aggressively in July. Unfortunately, the snow came late that year and Christmas sales were slow. While Tom was still pondering what to do with all his inventory, two competitors started their spring sales several weeks early. By the time Mountain Sporting Goods had its sale, the market had been saturated. In the tiny resort town in which Mountain Sporting Goods operates, you can't even give ski equipment between late March and early November. Tom ended up carrying the excess inventory all summer and then dumping it at a ski swap at a large city several hundred miles away in November. Thus Tom faced the problem which is typical for retailers of very seasonal goods in an isolated market: What will business be like for the rest of the season? Should I try to get more inventory? When should I start marking down to make sure I don't get stuck holding excess inventory all summer? Over the years, many inventory control models have been developed. Most, unfortunately, do not address the types of problems faced by small retailers. In this article, we briefly review traditional inventory models and why they are unsuitable for small retailers. A new model is developed with which we have experienced limited early success. Economic-Order-Quantity-Based Models Even though the Economic Order Quantity (EOQ) model is considered obsolete by many organizations, some version of a simple EOQ model is still the starting point for most inventory control discussions. If a book on small business management discusses an inventory model at all, the EOQ model is the one that will be considered (Broom, Longenecker, and Moore 1983; Hodgetts and Kuratko 1986; Tate et al. 1985). In the simplest version, this model involves determining the correct order quantity by solving an equation of the form: EOQ = [[2DC.sub.o]/[C.sub.h]].sup.1/2], where: EOQ = economic order quantity, D = demand per time period, [C.sub.o] = cost of placing one order, [C.sub.h] = cost of holding one item in [C.sub.h] = inventory. While the EOQ model is easy to understand, it does not address the problem faced by small retailers because EOQ assumes that demand is known and relatively constant and that multiple orders can be placed at a constant cost. Even expanded versions of the basic EOQ model do not address the seasonal nature of much retail business. Profit Matrix Models Profit matrix models determine the optimum order quantity by comparing the profit for all combinations of likely sales (outcomes) and orders (decisions). The order quantity is determined such that some decision criterion--maximum profit, minimum loss, highest expected profit, etc.--is satisfied. To be effective this model requires the decision maker to be able to identify the set of likely sales, and the revenues and costs associated with each possible order size. Let's assume the following situation. …