Knowledge that Transforms

A regular feature of Manufacturing & Service Operations Management, “In This Issue” briefly describes each issue’s articles and highlights their contributions.

A regular feature of Manufacturing & Service Operations Management, “In This Issue” briefly describes each issue's articles and highlights their contributions.

A regular feature of Manufacturing & Service Operations Management, “In This Issue” briefly describes each issue’s articles and highlights their contributions.

We develop a model and analyze reverse information sharing, a growing business practice in supply chain management in which a manufacturer shares information about supply with a retailer. We model the manufacturer as a production queue with finished goods warehouse, the retailer as an inventory location, and other customers as an external demand stream. In our model, the manufacturer allows the retailer access to inventory status at the warehouse. To take advantage of this new information, the retailer changes from a single-level base-stock policy to a two-level, state-dependent base-stock policy. We provide an exact method for computing performance and develop a procedure for evaluating optimal policy. We demonstrate the impact of the new policy on the manufacturer and other customers. Numerical computations lead to insights about the value of information to the retailer, and to guidelines for the manufacturer on sharing information.

This paper provides a model of the competitive newsvendor problem in which there is price competition following the inventory decisions. Using the biform game formalism of Brandenburger and Stuart (2004), the price competition is modeled by considering the core of the induced cooperative game. Such an analysis allows price competition to be modeled without a priori assumptions about price-setting power or pricing procedures. The paper shows that with no uncertainty, the inventory decision is equivalent to the capacity decision in Cournot competition. With uncertainty, the analysis again reduces to Cournot competition if the demand uncertainty is characterized by an appropriately constructed, expected demand curve. The results highlight the critical role of the fixed-price assumption in newsvendor models.

One way to organize workers that lies between traditional assembly lines, where workers are specialists, and craft assembly, where workers are generalists, are “bucket brigades.” We describe how one firm used bucket brigades as an intermediate strategy to migrate from craft assembly to assembly lines. The adoption of bucket brigades led to a narrowing of tasks for each worker and thus accelerated learning. The increased production more than compensated for the time lost when workers walk back to get more work, which was significant in this implementation. To understand the trade-offs in migrating from craft to assembly lines, we extend the standard model of bucket brigades to capture hand-off and walk-back times.

Motivated by the incentive programs that have been offered by energy companies under tight market conditions in the past few years, we consider a production control problem in which time alternates randomly between peak and nonpeak periods. During peak periods, the energy supplier offers the manufacturing firm—the energy user—an incentive program to reduce its energy usage by shutting down its production facility. Participation in the incentive program, however, is totally voluntary, and the user firm is rewarded for each unit of time that it participates in the program. We consider two problems that face the manufacturing firm. The first is whether it is worth shutting down production to participate in the incentive program when it is offered, and in which part (portion) of the peak period the firm should participate. The second problem is how the firm should decide on its production policy in both the peak and nonpeak periods in the presence of such an incentive program. In this paper, we provide simple models to give insight into the nature of these problems. Two cases are studied. In the first case, the peak duration is assumed to be exponentially distributed, and in the second, its length becomes known at the beginning of a peak period. In both cases, the occurrence times of the peak periods are uncertain. We characterize the optimal production and shutdown policy for both the peak and nonpeak periods. We also study the effect of seasonality on the optimal control policies.

We evaluate operations management–related journals based on a novel indicator of journal quality—the Author Affiliation Index (AAI). We explain the basic rationale behind the AAI, as well as its advantages and disadvantages with respect to other such indicators of journal quality. We provide a specific recipe for its calculation and apply it to 27 journals in which researchers in the field of operations management might wish to publish. We compare the resulting journal rankings to those from published survey reports and citation analyses and test AAI for sensitivity to its inputs. We find the rankings from AAI to be consistent with other studies and to be robust with respect to changes in inputs.

The standard treatment of fill rate relies on stationary and serially independent demand over an infinite horizon. Even if demand is stationary, managers are held accountable for performance over a finite horizon. In a finite horizon, the fill rate is a random variable. Studying the distribution is relevant because a vendor may be subject to financial penalty if she fails to achieve her target fill rate over a specified finite period. It is known that for a zero lead time, base-stock model, the expected value of a finite-horizon fill rate exceeds the long-run fill rate. In this paper, I investigate the behavior of the distribution of the finite-horizon fill rate when a stationary base-stock policy is used to control inventory. For a vendor facing a finite-horizon, fill-rate-level contract and using a stationary stocking policy, I examine how the the length of the review horizon (i.e., monthly or quarterly), the demand distribution, and the cost of failing to meet the target affect the stocking decision.

Order crossovers occur when replenishment orders arrive in a sequence that is different than the one in which they were placed. Order crossovers require that optimal reorder levels be set with regard to the inventory shortfall distribution rather than the lead-time demand distribution. Assuming periodic review and independent lead times, this paper suggests simple approximations of the shortfall distribution by showing that the variance of the number of orders outstanding is bounded above by the standard deviation of lead time divided by √3. Using this bound in a normal approximation improves significantly upon the common practice of basing policies on the lead-time demand distribution. A negative binomial approximation of the shortfall, based on its exact variance, offers even greater improvement, at the cost of some additional informational and computational requirements.