Knowledge that Transforms

New products are often launched sequentially, by different firms, and the purchasing decisions are sometimes made by dyads. This paper proposes a new model that explicitly considers dyadic decision making in drug prescription and allows assessment of the relative influence that physicians and patients have in making decisions concerning new as well as existing ethical drugs. Modeling sequentially launched competing products in a category allows for parsing out effects that are hard to differentiate in models designed to capture only a single product's dynamics. The proposed model is applied to prescription drug data sets in the pharmaceutical industry, and it also explicitly captures both physicians' and patients' pretrial and posttrial utilities of each drug in the therapeutic category. Based on the model's fit and out-of-sample forecasting performance, we find that, in many cases, the incorporation of the dyadic decision making leads to better performance vis-à-vis models where such decision making is not explicitly considered. We also find that in many cases the posttrial utility of a drug is greater than its corresponding pretrial utility, lending partial empirical support to the prevailing industry practice of spending on various activities (e.g., sampling to physicians) needed to get potential patients to try a new drug. The proposed model enables managers to predict in advance the sales of sequentially launched new drugs and plan the new product launch and strategy accordingly. The model is also applicable to other product categories involving more than a single decision maker, including business-to-business products (e.g., office equipment) as well as to products targeting children (e.g., toys).

We develop a multistakeholder, multicriteria decision-making framework for Eurocontrol, the European air traffic management organization, for evaluating and selecting operational improvements to the air traffic management system. The selected set of improvements will form the master plan of the Single European Sky initiative for harmonizing air traffic, in an effort to cope with the forecasted increase in air traffic, while maintaining safety, protecting the environment, and improving predictability and efficiency. The challenge is to select the set of enhancements such that the required performance targets are met and all key stakeholders are committed to the decisions. In this paper, we develop and implement a model to identify a preferred set of improvements to the arrival and departure procedures to and from airports. We provide an integrated approach for valuing a large number of alternatives, while considering interactions among them. The model combines quantitative and qualitative expert assessments of the possible enhancements and identifies commonalities and differences in the stakeholders' perspectives, ultimately recommending a preferred course of action. The model is currently being adopted by Eurocontrol as the formal trade-off analysis methodology supporting all enhancements' decision-making discussions throughout the construction of the master plan.

In a recent paper, Mishra and Raghunathan (Mishra, B. K., S. Raghunathan. 2004. Retailer- vs. vendor-managed inventory and brand competition. Management Sci. 50(4) 445–457) claimed that retailers prefer vendor-managed inventory (VMI) because it restores competition among manufacturers and encourages them to maintain a higher stock of their own brand under VMI than would be maintained under retailer-managed inventory (RMI). This paper shows that these results do not hold in general: each manufacturer's stocking level may be higher under RMI than under VMI and the retailer may lose by adopting VMI depending on the profit margin of the retailer relative to that of the manufacturers, the magnitude of the holding costs, and the intensity of brand competition. Numerical examples show that the effect of brand competition on the system is not so significant and the transfer of holding cost to the vendor is the key incentive for the retailer's adoption of VMI.

This paper studies the impact of strategic customer behavior on supply chain performance. We start with a newsvendor seller facing forward-looking customers. The seller initially charges a regular price but may salvage the leftover inventory at a lower salvage price after random demand is realized. Customers anticipate future sales and choose purchase timing to maximize their expected surplus. We characterize the rational expectations equilibrium, where we find that the seller's stocking level is lower than that in the classic model without strategic customers. We show that the seller's profit can be improved by promising either that quantities available will be limited (quantity commitment) or that prices will be kept high (price commitment). In most cases, both forms of commitment are not credible in a centralized supply chain with a single seller. However, decentralized supply chains can use contractual arrangements as indirect commitment devices to attain the desired outcomes with commitment. Decentralization has generally been associated with coordination problems, but we present the contrasting view that disparate interests within a supply chain can actually improve overall supply chain performance. In particular, with strategic customer behavior, we find that (i) a decentralized supply chain with a wholesale price contract may perform strictly better than a centralized supply chain; (ii) contracts widely studied in the supply chain coordination literature (e.g., markdown money, sales rebates, and buyback contracts) can serve as a commitment device as well as an incentive-coordinating device; and (iii) some of the above contracts cannot allocate profits arbitrarily between supply chain members because of strategic customer behavior.

Organizational knowledge is a critical source of competitive advantage for professional service firms. Learning from experience and sustaining past knowledge are critical to the success of such knowledge-driven firms. We use learning curve theory to evaluate learning and depreciation in professional services. Our results, based on seven years of project data collected from an architectural engineering (A/E) firm, show that (a) professional services exhibit learning curves, (b) there is virtually no depreciation of knowledge and, (c) the rate of learning accelerates with experience.

Objectives have long been considered a basis for sound decision making. This research examines the ability of decision makers to generate self-relevant objectives for consequential decisions. In three empirical studies, participants consistently omitted nearly half of the objectives that they later identified as personally relevant. More surprisingly, omitted objectives were perceived to be almost as important as those generated by participants on their own. These empirical results were replicated in a real-world case study of strategic decision making at a high-tech firm. Overall, our research suggests that decision makers are considerably deficient in utilizing personal knowledge and values to form objectives for the decisions they face.

Due to lack of detention capacity (the U.S. government measures capacity by the number of detention beds), tens of thousands of apprehended illegal aliens are released into the U.S. interior each year, instead of being removed from the country. This vulnerability can be exploited by terrorist groups wanting to enter the United States. We construct a queueing model of the U.S. detention and removal operations, and derive approximate analytical expressions for key performance measures, including a simple normal approximation for the required number of beds. Due to shortcomings in the U.S. government's data collection procedures, we cannot directly estimate all of the model's parameter values. Consequently, we use the approximate analytical expressions and the 2003 U.S. government data quantifying these key performance measures to estimate several unknown parameter values. Although current funding is for approximately 21,000 detention beds, we estimate that approximately 34,500 beds are needed to remove all potential detainees (this does not include nonviolent, noncriminal Mexicans, who are returned to Mexico within several hours) based on 2003 data. The dramatic increase in the arrivals of potential detainees since 2003 suggests that approximately 50,000 beds are currently required, although the estimation of future arrival rates is very difficult due to uncertainties about the future direction of U.S. immigration policy. Our estimated bed requirements are approximately 25% higher than naive estimates that fail to account for right censoring of residence times due to some detainees being released from detention before removal to make way for higher-priority detainees.

This research uses dual-process cognitive theory to describe how people process information differently when it is delivered via videoconference rather than when it is delivered face-to-face. According to this theory, relative to face-to-face communication, people in videoconferences tend to be more influenced by heuristic cues—such as how likeable they perceive the speaker to be—than by the quality of the arguments presented by the speaker. This is due to the higher cognitive demands that videoconferencing places on participants. We report on a field study of medical professionals in which we found differences in information processing as predicted: participants attending a seminar via videoconference were more influenced by the likeability of the speaker than by the quality of the arguments presented, whereas the opposite pattern was true for participants attending in-person. We also found that differences in cognitive load explain these effects. The discussion on the theoretical model and associated findings explains why prior videoconference studies have not consistently found main effects for media. The findings also show that videoconferencing is not like face-to-face communication, despite apparent similarities.

Modularity has been heralded as an organizational and technical architecture that enhances incremental and modular innovation. Less attention has been paid to the possible implications of modular architectures for imitation. To understand the implications of modular designs for competitive advantage, one must consider the dual impact of modularity on innovation and imitation jointly. In an attempt to do so, we set up three alternative structures that vary in the extent of modularity and hence in the extent of design complexity: nonmodular, modular, and nearly modular designs. In each structure, we examine the trade-offs between innovation benefits and imitation deterrence. The results of our computational experiments indicate that modularization enables performance gains through innovation but, at the same time, sets the stage for those gains to be eroded through imitation. In contrast, performance differences between the leaders and imitators persist in the nearly modular and the nonmodular structures. Overall, we find that design complexity poses a significant trade-off between innovation benefits (i.e., generating superior strategies that create performance differences) and imitation deterrence (i.e., preserving the performance differences). We also examine the robustness of our results to variations in imitation accuracy. In addition to documenting the overall robustness of our principal finding, the ancillary analyses provide a more nuanced rendering of the relationship between the architecture of complexity and imitation efforts.

Voluntary standard-setting organizations (SSOs) are a common feature of systems industries, where firms supply interoperable components for a shared technology platform. These institutions promote coordinated innovation by providing a forum for collective decision making and a potential solution to the problem of fragmented and overlapping intellectual property rights. This paper examines the economic and technological significance of SSOs by analyzing the flow of citations to a sample of U.S. patents disclosed during the standard-setting process. Our main results show that the age distribution of SSO patent citations is shifted toward later years (relative to an average patent) and that citations increase substantially following standardization. These results suggest that SSOs identify promising technologies and influence their subsequent adoption.