Manufacturing & Service Operations Management current issue

OM Practice--Work Expands to Fill the Time Available: Capacity Estimation and Staffing Under Parkinson's Law

Hasija, S., Pinker, E., Shumsky, R. A. — Wed, 10 Feb 2010 10:44:36 PST

We develop a method to estimate the capacity of agents who answer e-mail in a contact center, given aggregate historical data that have been distorted both by constraints on work availability and by internal incentives to slow down when true capacity exceeds demand. We use the capacity estimate to find a contact center's optimal daily staffing levels. The implementation results, from an actual contact center, demonstrate that the method provides accurate staffing recommendations. We also examine and test models in which agents exhibit speed-up behavior and in which capacity varies over time. Finally, we use the capacity estimates to examine the implications of solving the staffing problem with two different model formulations, the service-level constraint formulation used by the contact center and an alternate profit-maximization formulation.

Effect of Supply Reliability in a Retail Setting with Joint Marketing and Inventory Decisions

Liu, S., So, K. C., Zhang, F. — Wed, 10 Feb 2010 10:44:37 PST

This paper studies the impact of supply reliability on a retail firm's performance under joint marketing and inventory decisions. The firm sells a product in a single selling season and can exert marketing effort to influence consumer demand. We develop a modeling framework to quantify the value of improving supply reliability and investigate how this value depends on different model parameters. Our results provide useful insights into how firms should make investment decisions on adopting new technologies to improve supply reliability. First, we establish a necessary and sufficient condition under which the maximum unit cost a firm is willing to pay to improve supply reliability increases in product price. We further show that this condition would hold in most practical situations. Thus, with some caveats, our result supports the intuition that a firm is willing to pay more to improve supply reliability for products with a higher price. Next, we show that for two products with the same price, a firm is willing to pay more to improve supply reliability for the product with a higher product cost. This implies that it is not necessarily true that emerging technologies for improving supply reliability should be first adopted for products with the highest unit contribution margin. Finally, we show that a product with a lower marketing cost function always benefits more from improved supply reliability than a product with a higher marketing cost function. This finding suggests that the priority of adopting new technologies should be given to situations where the firm can effectively induce greater demand through promotional effort.

Buy Now and Match Later: Impact of Posterior Price Matching on Profit with Strategic Consumers

Lai, G., Debo, L. G., Sycara, K. — Wed, 10 Feb 2010 10:44:37 PST

With a posterior price matching (PM) policy, a seller guarantees to reimburse the price difference to a consumer who buys a product before the seller marks it down. Such a policy has been widely adopted by retailers. We examine the impact of a posterior PM policy on consumers' purchasing behavior, a seller's pricing and inventory decisions, and their expected payoffs, assuming that the seller cannot credibly commit to a price path, but can implement a posterior PM policy. We find that the PM policy eliminates strategic consumers' waiting incentive and thus allows the seller to increase price in the regular selling season. When the fraction of strategic consumers is not too small and their valuation decline over time is neither too low nor too high, the PM policy can substantially improve the seller's profit, as well as the inventory investment. In such situations, the strategic consumers' waiting incentive and the loss if they wait are both high. However, to adopt this policy, the seller also bears the refund cost. The seller must either pay the refund that consumers will claim or forgo the salvage value of any leftover inventory. The PM policy can be detrimental when there are only a few strategic consumers or the strategic consumers' valuation decline is very low or very high. We find that the performance of this policy is insensitive to the proportion of consumers who claim the refund. From the consumers' perspective, the PM policy generally reduces consumer surplus; however, there are cases where consumer surplus can be increased, typically when the variance of the potential high-end market volume is high. As a result, a Pareto improvement on both the seller's and the consumers' payoffs is possible. Finally, we find that the ability to credibly commit to a fixed price path is not very valuable when the seller can implement price matching.

Robust Controls for Network Revenue Management

Perakis, G., Roels, G. — Wed, 10 Feb 2010 10:44:37 PST

Revenue management models traditionally assume that future demand is unknown but can be described by a stochastic process or a probability distribution. Demand is, however, often difficult to characterize, especially in new or nonstationary markets. In this paper, we develop robust formulations for the capacity allocation problem in revenue management using the maximin and the minimax regret criteria under general polyhedral uncertainty sets. Our approach encompasses the following open-loop controls: partitioned booking limits, nested booking limits, displacement-adjusted virtual nesting, and fixed bid prices. In specific problem instances, we show that a booking policy of the type of displacement-adjusted virtual nesting is robust, both from maximin and minimax regret perspectives. Our numerical analysis reveals that the minimax regret controls perform very well on average, despite their worst-case focus, and outperform the traditional controls when demand is correlated or censored. In particular, on real large-scale problem sets, the minimax regret approach outperforms by up to 2% the traditional heuristics. The maximin controls are more conservative but have the merit of being associated with a minimum revenue guarantee. Our models are scalable to solve practical problems because they combine efficient (exact or heuristic) solution methods with very modest data requirements.

The Coordination of Pricing and Scheduling Decisions

Chen, Z.-L., Hall, N. G. — Wed, 10 Feb 2010 10:44:37 PST

This paper considers the coordination of pricing and scheduling decisions in a make-to-order environment. Following common industry practice, we assume knowledge of a deterministic demand function that is nonincreasing in price. We consider three alternative measures of scheduling cost: total work-in-process inventory cost of orders, total penalty for orders delivered late to customers, and total capacity usage. The objective is to maximize the total net profit, i.e., revenue less scheduling cost, resulting from the pricing and scheduling decisions. We develop computationally efficient optimal algorithms for solving the three pricing and scheduling problems. Because these problems are formally intractable, much faster algorithms are not possible. We develop a fully polynomial time approximation scheme for each problem. We also estimate the value of coordinating pricing and production scheduling decisions by comparing solutions delivered by (a) an uncoordinated approach where pricing and scheduling decisions are made independently, (b) a partially coordinated approach that uses only general information about scheduling that a marketing department typically knows, (c) a simple heuristic approach for solving the coordinated problem, and (d) our optimal algorithm for solving the coordinated problem. Our main managerial insight is that there is a significant benefit even if pricing and scheduling are only heuristically or partially coordinated. Moreover, heuristic and partial coordination are simple to achieve.

Supplier Competition in Decentralized Assembly Systems with Price-Sensitive and Uncertain Demand

Jiang, L., Wang, Y. — Wed, 10 Feb 2010 10:44:37 PST

In a decentralized assembly supply chain, independent suppliers produce a set of complementary components from which an assembler assembles a final product and sells it to the market. In such a channel, several competitive forces interact with one another to affect the price and quantity decisions of the firms involved. These include: (1) the direct competition each supplier faces for producing the same component, (2) the indirect competition among the suppliers producing the set of complementary components needed for assembling the final product, and (3) the vertical interaction between the assembler and the component suppliers. This paper shows that the direct competition that one supplier faces helps improve the performance of the assembler and all the other suppliers in the channel; and surprisingly, it can help improve the performance of this particular supplier facing the competition as well. Second, the assembler benefits from a merger of suppliers producing different components in the complementary set. Furthermore, the assembler prefers a merger of suppliers with less direct competition over a merger of suppliers with more direct competition.

Customer-Driven vs. Retailer-Driven Search: Channel Performance and Implications

Jiang, L., Anupindi, R. — Wed, 10 Feb 2010 10:44:37 PST

A common phenomenon that occurs in any decentralized multilocation system is stock imbalance, whereby some locations have unsatisfied demands while others are overstocked. The system can be rebalanced by using a search process that is driven by either the customers or the retailers. In a customer-driven search (CDS), the customer with unmet demand may search for the product at another location and, if it is available, complete the purchase. In a retailer-driven search (RDS), the retailer with unsatisfied demand searches for product and schedules transshipment to fulfill the unmet demand at his location. Of course, the revenues generated through search in RDS need to be shared between the parties according to a transfer pricing scheme. In a setting of one manufacturer and two retailers with price-dependent and random demand, we explore the impact of the search method and the transfer price scheme used on the preferences of the manufacturer, the retailers, and the customers. With endogenous retail prices, we find that both the manufacturer and the retailers prefer RDS over CDS when they can design the transfer pricing scheme in RDS. Interestingly, neither party prefers the fixed transfer pricing scheme commonly assumed in the literature. Instead, transfer price that is proportional to the price of the retailer with either excess stock or excess demand is preferred. However, although both parties favor an RDS system when they can design the transfer pricing scheme in RDS, they may prefer RDS or CDS when the other party designs the RDS. Thus, the interests of the manufacturer and the retailers are rarely aligned. Customers benefit from a lower price in an RDS but at the expense of lower availability (as measured by the level of safety stock).

Continuous Review Inventory Model with Dynamic Choice of Two Freight Modes with Fixed Costs

Jain, A., Groenevelt, H., Rudi, N. — Wed, 10 Feb 2010 10:44:37 PST

We analyze a continuous review (Q, r) stochastic inventory model in which orders placed with a make-to-order manufacturer can be shipped via two alternative freight modes differing in lead time and costs. The costs of placing an order and using each freight mode consist of fixed components and hence exhibit economies of scale. We derive an optimal policy for using the two freight modes for shipping each order. This freight-mode decision is delayed until manufacturing is complete and the optimal policy uses information about the demand incurred in the meantime. Furthermore, given that the two freight modes are used optimally for shipping each order, we solve our model for reorder point and order quantity that minimizes cost. We analyze the cost savings achieved from postponing the freight-mode decision and provide analytical and numerical comparisons between the solutions to our two-freight model and single-freight models. Finally, we illustrate the properties of the solution to our model using an extensive set of numerical examples.

Feasting on Leftovers: Strategic Use of Shortages in Price Competition Among Differentiated Products

Porteus, E. L., Shin, H., Tunca, T. I. — Wed, 10 Feb 2010 10:44:37 PST

Two single-product firms with different quality levels and fixed limited capacities engage in sequential price competition in an essentially deterministic model where customers have heterogeneous valuations for both products. We develop conditions under which the leader (she) can take strategic advantage of her limited capacity by pricing relatively low, purposefully creating shortages and leaving some leftovers for the follower (him) to feast on, avoiding direct competition. The extent to which the leader benefits in this Leftovers Equilibrium depends on operational variables such as the capacity levels of the two firms and the sequence in which customers arrive at the market. We spell out the details for three different known arrival sequences within a specific subset of plausible fixed-capacity levels. The follower's strategic shadow price can be positive even when not all his capacity is used, and the leader's can be negative when all her capacity is used. We illustrate that Leftovers Equilibria can arise when some of our assumptions are relaxed.

Testing the Validity of a Demand Model: An Operations Perspective

Besbes, O., Phillips, R., Zeevi, A. — Wed, 10 Feb 2010 10:44:37 PST

The fields of statistics and econometrics have developed powerful methods for testing the validity (specification) of a model based on its fit to underlying data. Unlike statisticians, managers are typically more interested in the performance of a decision rather than the statistical validity of the underlying model. We propose a framework and a statistical test that incorporate decision performance into a measure of statistical validity. Under general conditions on the objective function, asymptotic behavior of our test admits a sharp and simple characterization. We develop our approach in a revenue management setting and apply the test to a data set used to optimize prices for consumer loans. We show that traditional model-based goodness-of-fit tests may consistently reject simple parametric models of consumer response (e.g., the ubiquitous logit model), while at the same time these models may "pass" the proposed performance-based test. Such situations arise when decisions derived from a postulated (and possibly incorrect) model generate results that cannot be distinguished statistically from the best achievable performance—i.e., when demand relationships are fully known.

MSOM Society Student Paper Competition: Abstracts of 2009 Winners

Wed, 10 Feb 2010 10:44:37 PST

No abstract available.

Call for Nominations--2010 M&SOM Best Paper Award

Wed, 10 Feb 2010 10:44:37 PST

No abstract available.