Some Comments on the Validity of EOQ Formula under Inflationary Conditions

In an earlier issue of Decision Sciences, Jesse, Mitra, and Cox [1] examined the impact of inflationary conditions on the economic order quantity (EOQ) formula. Specifically, the authors analyzed the effect of inflation on order quantity decisions by means of a model that takes into account both inflationary trends and time discounting (over an infinite time horizon). In their analysis, the authors utilized two models: Current-dollars model and Constant-dollars model. These models were derived, of course, by setting up a total cost equation in the usual manner then finding the optimum order quantity that minimizes the total cost. Jesse, Mitra, and Cox [1] found that EOQ is approximately the same under both conditions; with or without inflation. However, we disagree with the conclusion drawn by [2] and show that EOQ will be different under inflationary conditions, provided that the inflationary conditions are properly accounted for in the formulation of the total cost model.     

Standard Container Size Discounts and the Single-Period Inventory Problem*

This paper analyzes the problem of choosing the optimal order quantity and its associated number of standard containers making up the order for single-period inventory models under standard container size discounts. A range is determined that contains the optimal order quantity. Two algorithms are presented. The first algorithm solves the general case in which there is no restriction on the types of containers included in an order. The second algorithm solves a more restricted policy that requires the buyer to accept the order with successively smaller container sizes.     

A Decision Model for the Robot Selection Problem Using Robust Regression*

Industrial robots are increasingly used by many manufacturing firms. The number of robot manufacturers has also increased with many of these firms now offering a wide range of models. A potential user is thus faced with many options in both performance and cost. This paper proposes a decision model for the robot selection problem. The proposed model uses robust regression to identify, based on manufacturers' specifications, the robots that are the better performers for a given cost. Robust regression is used because it identifies and is resistant to the effects of outlying observations, key components in the proposed model. The robots selected by the model become candidates for testing to verify manufacturers' specifications. The model is tested on a real data set and an example is presented.     

The Individually Responsible and Rational Decision Approach to Economic Lot Sizes for One Vendor and Many Purchasers

Banerjee's [2] joint economic lot size (JELS) model, along with related works by Monahan [12] and Lal and Staelin [10], represents one approach to minimizing the total inventory carrying and ordering costs of a vendor and his purchaser(s). Noting that JELS philosophy requires a coordinated system and that its practical implementation is problematic, we present an alternative approach to the same problem: the individually responsible and rational decision (IRRD) approach. The IRRD approach is consistent with a free enterprise system and easy to implement. In order to show that the IRRD approach is also more economical than the JELS approach, we first build a more refined JELS model for the case of one vendor and many identical purchasers. Drawing on earlier criticisms of specific JELS models, our refinement relaxes the lot-for-lot assumption commonly used by JELS scholars. To be comparable with earlier works, we retain the assumption of deterministic conditions and demonstrate the economic advantages of IRRD over JELS through a numerical example. An algebraic proof of IRRD's superiority over JELS is offered in the more general and realistic case of a vendor dealing with K nonidentical purchasers with reasonably predictable annual demand but uncertain order quantities and timings.     

Resource Flexibility Issues in Multistage Manufacturing

We test the situational impact of two types of resource flexibility, machine flexibility and labor flexibility, in a material requirements planning (MRP)-driven production system. Machine flexibility has not been treated in prior multistage research, only labor flexibility. Machine flexibility is closely related to a plant's positioning strategy. A process-focused plant opts for considerable machine flexibility by choosing general-purpose equipment. Resource flexibility, if effective, can be an attractive alternative to two other types of buffers, inflated inventories and costly capacity cushions. Our simulation results, using factor settings established earlier by a panel of managers, show that resource flexibility is indeed an effective buffer against uncertainties such as end-item demand variability, capacity bottlenecks, equipment failures, and yield losses. Machine flexibility is especially helpful in environments characterized by high uncertainties, tight capacities, and large lot sizes. Worker flexibility has a similar, but less dramatic, impact. Benefits are most striking with customer service, rather than with inventory or labor productivity. Finally, we show that simultaneous introduction of both machine and labor flexibility yields only marginal improvements over either kind of flexibility alone.     

Interactive Effects of Major Response Facilitators

Practitioners and researchers have long been interested in achieving the highest response rate within resource constraints on their mailed surveys. Achieving this high response rate typically has required the selection of the right mix of response-facilitating techniques. The selection decisions were generally made under the assumption that the response-facilitating techniques act independently of one another. The authors have examined the validity of this independence assumption by identifying the major response facilitators in use and then analyzing the results of 531 independent mail survey studies. The authors conclude that major facilitators do not function independently. In fact, it was found that significant joint action interactive effects on response rates do exist. Practitioners and researchers who are faced with the survey design decisions of choosing response facilitators can receive assistance by reviewing the results of this diverse collection of reported experiences.     

Multi-Item Grouping Algorithm Yielding Near-Optimal Logistics Cost

This article describes an algorithm used to formulate an inbound consolidation strategy when multi-items are replenished in groups and when total logistics cost is to be minimized. The importance of this algorithm is threefold (1) no optimal procedure exists for grouping multi-items when minimizing total logistics cost, (2) a complete enumeration of all possible groups (from which the optimal grouping set can be identified) is impractical due to the combinatorial nature of the grouping problem, and (3) no other heuristics have been developed that adequately reflect shipping cost in the analysis like this one does. We report the experience of using this algorithm to group and reorder 75 selected ensembles containing a total of 517 inventory items of a retail merchandising firm.     

Bringing Japanese Continuous Improvement Approaches to U.S. Manufacturing: The Roles of Process Orientation and Communications*

Continuous improvement (CI) has played a key role in Japan's quality management. U.S. companies have begun to adopt CI in recent years. This paper studies the implementation of CI in seven U.S. manufacturing companies. We view values as the core concept of culture that impacts CI effectiveness. Using both qualitative and quantitative data with a sample of seven companies, we observe empirically a relationship between process-oriented values and CI effectiveness. We also find that communications involving workers is strongly associated with CI effectiveness. Finally, we find an association between process orientation and communication frequency, and argue that communications act as an intervening variable between process orientation and effectiveness.