Knowledge that Transforms

We study the joint decisions of offering mail‐in rebates (MIRs) in a single‐manufacturer–single‐retailer supply chain using a game theoretic framework. Either party can offer an MIR to the end consumer if it is in his best interest. The consumer demand is stochastic and depends on the product price and the amount of MIRs. When the retail price is exogenous, we show the existence of a unique Nash equilibrium under both additive and multiplicative demand functions and characterize it completely. We show that any of the following four scenarios can be the equilibrium: both parties offer MIR, only one party offers MIR, none offers MIR. When the retail price is a decision variable for the retailer and the rebate redemption rate increases with the amount of MIR, we once again prove the existence of a unique Nash equilibrium where both the retailer and the manufacturer offer MIRs. Using a numerical study, we show that the average post‐purchase price of the product is higher not only than the perceived pre‐purchase price but also than the newsvendor optimal price without an MIR. This implies that an MIR makes a product look cheaper while the consumers actually pay more on average.

This paper develops and tests a privacy‐preserving business process that supports the selection of a contract manufacturer by an original equipment manufacturer (OEM), and the determination of whether the OEM or the chosen contract manufacturer will procure each of the components to be used in the manufacture of the OEM's branded product. Our “secure price‐masking (SPM)” technology contributes to procurement theory and practice in four significant ways: First, it preserves the privacy of every party's individual component prices. Second, SPM assures that the contract manufacturers will bid their own private purchase cost (i.e., not add a margin to their cost). Third, SPM is not invertible; i.e., none of the participants can “solve” for the private inputs of any other participant based on its own inputs and the outputs provided to it by SPM. Fourth, the posterior distribution of any other participant's private inputs is practically indistinguishable from its prior distribution. We also describe the results of a proof‐of‐concept implementation.

We study an inventory system in which a supplier supplies demand using two mutually substitutable products over a selling season of T periods, with a single replenishment opportunity at the beginning of the season. As the season starts, customer orders arrive in each period, for either type of products, following a nonstationary Poisson process with random batch sizes. The substitution model we consider combines the usual supplier‐driven and customer‐driven schemes, in that the supplier may choose to offer substitution, at a discount price, or may choose not to; whereas the customer may or may not accept the substitution when it is offered. The supplier's decisions are the supply and substitution rules in each period throughout the season, and the replenishment quantities for both products at the beginning of the season. With a stochastic dynamic programming formulation, we first prove the concavity of the value function, which facilitates the solution to the optimal replenishment quantities. We then show that the optimal substitution follows a threshold rule, and establish the monotonicity of the thresholds over time and with respect to key cost parameters. We also propose a heuristic exhaustive policy, and illustrate its performance through numerical examples.

Motivated by interest in making delay announcements in service systems, we study real‐time delay estimators in many‐server service systems, both with and without customer abandonment. Our main contribution here is to consider the realistic feature of time‐varying arrival rates. We focus especially on delay estimators exploiting recent customer delay history. We show that time‐varying arrival rates can introduce significant estimation bias in delay‐history‐based delay estimators when the system experiences alternating periods of overload and underload. We then introduce refined delay‐history estimators that effectively cope with time‐varying arrival rates together with non‐exponential service‐time and abandonment‐time distributions, which are often observed in practice. We use computer simulation to verify that our proposed estimators outperform several natural alternatives.

Consider a buyer, facing uncertain demand, who sources from multiple suppliers via online procurement auctions (open descending price‐only auctions). The suppliers have heterogeneous production costs, which are private information, and the winning supplier has to invest in production capacity before the demand uncertainty is resolved. The buyer chooses to offer a push or pull contract, for which the single price and winning supplier are determined via the auction. We show that, with a pull contract, the buyer does not necessarily benefit from a larger number of suppliers participating in the auction, due to the negative effect of supplier competition on the incentive of supplier capacity investment. We thus propose an enhanced pull mechanism that mitigates this effect with a floor price. We then analyze and compare the outcomes of auctions for push and (enhanced) pull contracts, establishing when one form is preferred over the other based on the buyer's profits. We also compare our simple, price‐only push and pull contract auctions to the optimal mechanisms, benchmarking the performance of the simple mechanisms as well as establishing the relative importance of auction design and contract design in procurement auctions.

Two factors that their influence on the demand has been investigated in many papers are (i) the shelf space allocated to a product and to its complement or supplement products and (ii) the instantaneous inventory level seen by customers. Here we analyze the joint shelf space allocation and inventory decisions for multiple items with demand that depends on both factors. The traditional approach to solve inventory models with a state‐dependent demand rate uses a time domain approach. However, this approach often does not lead to closed‐form expressions for the profit rate with both dependencies. We analyze the problem in the inventory domain via level crossing theory. This approach leads to closed‐form expressions for a large set of demand rate functions exhibiting both dependencies. These closed‐form expressions substantially simplify the search for optimal solutions; thus we use them to solve the joint inventory control and shelf space allocation problem. We consider examples with two products to investigate the significance of capturing both demand dependencies. We show that in some settings it is important to capture both dependencies. We consider two heuristics, each one of them ignores one of the two dependencies. Using these heuristics it seems that ignoring the dependency on the shelf space might be less harmful than ignoring the dependency on the inventory level, which, based on computational results, can lead to profit losses of more than 6%. We demonstrate that retailers should use their operational control, e.g., reorder point, to promote higher demand products.

This paper investigates the effect of learning and forgetting on production scheduling decisions. Numerous papers have appeared on this topic in the last four decades; they show that firms are better off producing in larger batches in the presence of learning and forgetting. However, these papers fail to consider one or more of realistic features of learning and forgetting; factors such as (1) the amount forgotten increases with break length between two batches and (2) the forgetting could be slow over an initial short interval followed by fast forgetting. Our paper contributes by demonstrating that a consideration of these realistic features leads to a different conclusion—firms may be better off producing in smaller batches in the presence of learning and forgetting. This is a new insight that provides one more justification for producing in small batches.

Mass customization has been viewed as desirable but difficult to achieve in the volume automotive sector. Here we consider flexibility in automotive order fulfillment systems to enhance the ability to satisfy customers with their desired vehicle variants within acceptable delivery lead times. Two types of flexibility are compared in a Virtual-Build-to-Order system—reconfiguration in the planning pipeline and interdealer trading. A representative simulation model is used to investigate the impact of the two types of flexibility across a wide spectrum of product variety levels. The impacts on major stakeholders in the system—the producer, dealers, and customers—are considered. The study shows that both types of flexibilities can bring significant benefits in terms of reductions in lead time and inventory holding. The level of product variety strongly influences the observed effects—an important finding in the mass customization context. Upstream reconfiguration flexibility brings greater benefits than downstream trading flexibility. Reconfiguration tends to dominate trading as a fulfillment mechanism when both are in operation. The findings have implications for the design and management of automotive order fulfillment systems in improving their ability to offer mass customization. The study has relevance for companies in other sectors with high levels of variety that seek to combine efficiency, speed, and flexibility in order fulfillment.

Carriers (airlines) use medium‐term contracts to allot bulk cargo capacity to forwarders who deliver consolidated loads for each flight in the contractual period (season). Carriers also sell capacity to direct‐ship customers on each flight. We study capacity contracts between a carrier and a forwarder when certain parameters such as the forwarder's demand, operating cost to the carrier, margin, and reservation profit are its private information. We propose contracts in which the forwarder pays a lump sum in exchange for a guaranteed capacity allotment and receives a refund for each unit of unused capacity according to a pre‐announced refund rate. We obtain an upper bound on the informational rent paid by the carrier for a menu of arbitrary allotments and identify conditions under which it can eliminate the informational rent and induce the forwarder to choose the overall optimal capacity allotment (i.e., one that maximizes the combined profits of the carrier and the forwarder).

Mass customization has been viewed as desirable but difficult to achieve in the volume automotive sector. Here we consider flexibility in automotive order fulfillment systems to enhance the ability to satisfy customers with their desired vehicle variants within acceptable delivery lead times. Two types of flexibility are compared in a Virtual‐Build‐to‐Order system—reconfiguration in the planning pipeline and interdealer trading. A representative simulation model is used to investigate the impact of the two types of flexibility across a wide spectrum of product variety levels. The impacts on major stakeholders in the system—the producer, dealers, and customers—are considered. The study shows that both types of flexibilities can bring significant benefits in terms of reductions in lead time and inventory holding. The level of product variety strongly influences the observed effects—an important finding in the mass customization context. Upstream reconfiguration flexibility brings greater benefits than downstream trading flexibility. Reconfiguration tends to dominate trading as a fulfillment mechanism when both are in operation. The findings have implications for the design and management of automotive order fulfillment systems in improving their ability to offer mass customization. The study has relevance for companies in other sectors with high levels of variety that seek to combine efficiency, speed, and flexibility in order fulfillment.