bluuebunny/crossref_metadata_2025 huggingface dataset:
Integrating Replenishment Decisions with Advance Demand Information
Authors: Gallego Guillermo , Özer Özalp
Published: December 2003

There is a growing consensus that a portfolio of customers with different demand lead times can lead to higher, more regular revenues and better capacity utilization. Customers with positive demand lead times place orders in advance of their needs, resulting in advance demand information. This gives rise to the problem of finding effective inventory control policies under advance demand information. We show that state-dependent (s, S) and base-stock policies are optimal for stochastic inventory systems with and without fixed costs. The state of the system reflects our knowledge of advance demand information. We also determine conditions under which advance demand information has no operational value. A numerical study allows us to obtain additional insights and to evaluate strategies to induce advance demand information.
Improving Discrete Model Representations via Symmetry Considerations
Authors: Sherali Hanif D. , Smith J. Cole
Published: December 2003

In this paper, we focus on a useful modeling concept that is frequently ignored while formu lating discrete optimization problems. Very often, there exists a natural symmetry inherent in the problem itself that, if propagated to the model, can hopelessly mire a branch-and-bound solver by burdening it to explore and eliminate such alternative symmetric solutions. We discuss three applications where such a symmetry arises: a telecommunications network design problem, a noise pollution problem, and a machine procurement and operation problem. For each case, we identify the indistinguishable objects in the model that create the problem symmetry and show how imposing certain decision hierarchies within the model significantly enhances its solvability, while using a popular modern-day commercial branch-and-cut software (CPLEX 6.5).
Note: The Newsvendor Model with Endogenous Demand
Authors: Dana James D. , Petruzzi Nicholas C.
Published: December 2003

This paper considers a firm's price and inventory policy when it faces uncertain demand that depends on both price and inventory level. The authors extend the classic newsvendor model by assuming that expected utility maximizing consumers choose between visiting the firm and consuming an exogenous outside option. The outside option represents the utility the consumer forgoes when she chooses to visit the firm before knowing whether or not the product will be available. The authors investigate both the case in which the firm's price is exogenous and the case in which price is chosen optimally. The paper makes two contributions. First, the authors show that the firm holds more inventories, provides a higher fill rate, attracts more customers, and earns higher profits when it internalizes the effect of its inventory on demand. Second, the authors show that in the endogenous price case the firm's two-dimensional decision problem can be reduced to two, sequential, single-variable optimizations. As a result, the endogenous-price case is as easy to solve as the exogenous-price case.
Pricing for a Durable-Goods Monopolist Under Rapid Sequential Innovation
Authors: Kornish Laura J.
Published: December 2003

A durable-goods monopolist who will be introducing new and improved versions of his product must decide how to price his products, keeping in mind the relative attractiveness of the current and future products. Dhebar (1994) has shown that if technology is changing too quickly and the producer cannot credibly commit to future prices and quality, then no equilibrium strategy exists. That is, there is no credible strategy for the future product that the producer can commit to in the first period. We show that an equilibrium pricing strategy exists if the monopolist does not offer upgrade pricing, that is, special pricing to consumers who have bought an earlier version. The author shows the possible purchase patterns in equilibrium and derives the optimal pricing strategy.
Strategic Factor Market Intelligence: An Application of Information Economics to Strategy Formulation and Competitor Intelligence
Authors: Makadok Richard , Barney Jay B.
Published: December 2003

This paper develops a model of information-acquisition decisions by firms that are competing in a “strategic factor market” (Barney 1986) to purchase a scarce resource whose value is unknown and differs across firms. The model builds on the argument that more accurate expectations about the firm-specific value of resources is, other than luck, the only way for firms to obtain the specific resources required for competitive advantage. We address the more specific question of what types of information firms should gather to accomplish this goal. The model generates a series of testable hypotheses about how a firm's optimal mix of different types of information is affected by a number of factors, including the level of uncertainty about the value of the resource being acquired; the rarity, imitability, and nonsubstitutability of that resource; the level of inscrutability of firms' pre-existing stocks of resources; and firms' information-gathering and information-processing capacities.
What Determines the Shape of the Probability Weighting Function Under Uncertainty?
Authors: Kilka Michael , Weber Martin
Published: December 2003

Decision weights are an important component in recent theories of decision making under uncertainty. To better explain these decision weights, a two-stage approach has been proposed: First, the probability of an event is judged and then this probability is transformed by the probability weighting function known from decision making under risk. We extend the two-stage approach by allowing the probability weighting function to depend on the type of uncertainty. Using this more general approach, properties of decision weights can be attributed to properties of probability judgments and/or to properties of probability weighting. We present an empirical study that shows that it is indeed necessary to allow the probability weighting function to be source dependent. The analysis includes an examination of properties of the probability weighting function under uncertainty that have not been considered yet.
The Dynamic Value of Hierarchy
Authors: Knott Anne Marie
Published: December 2003

This study develops a dual-routines view of the dynamic value of hierarchy, and tests it against the implicit null hypothesis that hierarchy merely provides static advantages over markets. The view holds that hierarchical managers perform two roles that create value for firms in perpetuity—an administrative role of enforcing operational routine, and an entrepreneurial role of executing a metaroutine that continually revises operational routine to keep pace with changes in the environment. The test consists of a natural experiment comparing the behavior and performance of establishments that leave a franchise, “lose their hierarchical managers,” with those that remain.

I find support for the view. In the absence of the franchisor, establishment behavior drifts from the operational routine, and establishments fail to adopt innovation. Both responses lead to significant decay in performance. Thus hierarchical managers are necessary to actively enforce routine, even after the routine been assimilated, and to introduce innovation, even in this unique setting of perfect incentives.
Comparisons with a Standard in Simulation Experiments
Authors: Nelson Barry L. , Goldsman David
Published: December 2003

We consider the problem of comparing a finite number of stochastic systems with respect to a single system (designated as the “standard”) via simulation experiments. The comparison is based on expected performance, and the goal is to determine if any system has larger expected performance than the standard, and if so to identify the best of the alternatives. In this paper we provide two-stage experiment design and analysis procedures to solve the problem for a variety of scenarios, including those in which we encounter unequal variances across systems, as well as those in which we use the variance reduction technique of common random numbers and it is appropriate to do so. The emphasis is added because in some cases common random numbers can be counterproductive when performing comparisons with a standard. We also provide methods for estimating the critical constants required by our procedures, present a portion of an extensive empirical study, and demonstrate one of the procedures via a numerical example.
The Trade-off Between Efficiency and Learning in Interorganizational Relationships for Product Development
Authors: Sobrero Maurizio , Roberts Edward B.
Published: December 2003

This paper analyzes the performance implications of interorganizational relationships in the development of technological innovations, focusing on the characteristics of the tasks partitioned between a manufacturer and its suppliers in the development of new products. We identify two critical dimensions: (1) the design scope and (2) the level of task interdependency. The design scope dimension characterizes the type of problem-solving activities outsourced by the manufacturer. The level of task interdependency dimension characterizes the influence of any given supplier-manufacturer interaction on other activities within an overall innovation process. Data analyses on 50 supplier-manufacturer relationships drawn from three new product development projects show that the type of problem-solving activities being partitioned and their level of interdependency with the rest of the project are important predictors of performance outcomes of the relationship, controlling for contractual differences. Further, the analyses demonstrate a clear trade-off between short-term efficiency-increasing and longer-term learning-enhancing outcomes.
Fast Simulation of Markov Chains with Small Transition Probabilities
Authors: Juneja Sandeep , Shahabuddin Perwez
Published: December 2003

Consider a finite-state Markov chain where the transition probabilities differ by orders of magnitude. This Markov chain has an “attractor state,” i.e., from any state of the Markov chain there exists a sample path of significant probability to the attractor state. There also exists a “rare set,” which is accessible from the attractor state only by sample paths of very small probability. The problem is to estimate the probability that starting from the attractor state, the Markov chain hits the rare set before returning to the attractor state. Examples of this setting arise in the case of reliability models with highly reliable components as well as in the case of queueing networks with low traffic. Importance-sampling is a commonly used simulation technique for the fast estimation of rare-event probabilities. It involves simulating the Markov chain under a new probability measure that emphasizes the most likely paths to the rare set. Previous research focused on developing importance-sampling schemes for a special case of Markov chains that did not include “high-probability cycles.” We show through examples that the Markov chains used to model many commonly encountered systems do have high-probability cycles, and existing importance-sampling schemes can lead to infinite variance in simulating such systems. We then develop the insight that in the presence of high-probability cycles care should be taken in allocating the new transition probabilities so that the variance accumulated over these cycles does not increase without bounds. Based on this observation we develop two importance-sampling techniques that have the bounded relative error property, i.e., the simulation run-length required to estimate the rare-event probability to a fixed degree of accuracy remains bounded as the event of interest becomes more rare.
An Empirical Examination of Dynamic Quality-Based Learning Models
Authors: Ittner Christopher D. , Nagar Venky , Rajan Madhav V.
Published: December 2003

Using detailed data on defect rates and quality costs from twelve plants of a Fortune 500 company, we provide the first direct tests of predictions arising from two sets of dynamic quality-based learning models. We find greater support for quality-based learning models that assume learning is a function of both proactive investments in quality improvement and autonomous learning-by-doing, than for models that assume learning is a function of reactive investments in quality improvement alone. We then extend these two sets of models to examine the impact of individual prevention activities and past nonconformance expenditures on defect rates. We find that benefits from different types of prevention expenditures vary, and that past nonconformance expenditures provide learning opportunities that allow the organization to more efficiently cope with future failures, thereby reducing subsequent nonconformance costs. These important implications are absent in current quality-based learning models, providing an opportunity for future theoretical development.
Parallel and Sequential Testing of Design Alternatives
Authors: Loch Christoph H. , Terwiesch Christian , Thomke Stefan
Published: December 2003

An important managerial problem in product design in the extent to which testing activities are carried out in parallel or in series. Parallel testing has the advantage of proceeding more rapidly than serial testing but does not take advantage of the potential for learning between tests, thus resulting in a larger number of tests. We model this trade-off in the form of a dynamic program and derive the optimal testing strategy (or mix of parallel and serial testing) that minimizes both the total cost and time of testing. We derive the optimal testing strategy as a function of testing cost, prior knowledge, and testing lead time. Using information theory to measure the test efficiency, we further show that in the case of imperfect testing (due to noise or simulated test conditions), the attractiveness of parallel strategies decreases. Finally, we analyze the relationship between testing strategies and the structure of design hierarchy. We show that a key benefit of modular product architecture lies in the reduction of testing cost.
Comparative Reliability of Verdicts
Authors: Klausner Amir , Pollak Moshe
Published: December 2003

We consider the problem of evaluating the reliability of a verdict given by a panel of judges. Given no information other than the number of panelists for and against, we address the question of when is a verdict that was obtained by a majority of k1 vs. j1 more or less reliable than one reached by k2 vs. j2. We define criteria and investigate which verdicts are comparable and which are not. Consequences of this study may have bearing on choice of panel size and decision rule for decision-making bodies, such as courts, juries, committees, and boards. As implied by the above, our perspective is a posterior view of reliability, though it also entails prior concern regarding how the reliability of a verdict will be perceived after being delivered. As an example, we apply our results to comparing the reliability of different verdicts handed down by the Supreme Court of the State of Israel and assessing the option of expanding a hearing on a case from a bench of three judges to a larger panel.
Competition and Structure in Serial Supply Chains with Deterministic Demand
Authors: Corbett Charles J. , Karmarkar Uday S.
Published: December 2003

Supply chains often consist of several tiers, with different numbers of firms competing at each tier. A major determinant of the structure of supply chains is the cost structure associated with the underlying manufacturing process. In this paper, we examine the impact of fixed and variable costs on the structure and competitiveness of supply chains with a serial structure and price-sensitive linear deterministic demand. The entry stage is modeled as a simultaneous game, where the players take the outcomes of the subsequent post-entry (Cournot) competition into account in making their entry decisions. We derive expressions for prices and production quantities as functions of the number of entrants at each tier of a multitier chain. We characterize viability and stability of supply-chain structures and show, using lattice arguments, that there is always an equilibrium structure in pure strategies in the entry game. Finally, we examine the effects of vertical integration in the two-tier case. Altogether, the paper provides a framework for comparing a variety of supply-chain structures and for studying how they are affected by cost structures and by the number of entrants throughout the chain.
An Adaptive, Distribution-Free Algorithm for the Newsvendor Problem with Censored Demands, with Applications to Inventory and Distribution
Authors: Godfrey Gregory A. , Powell Warren B.
Published: December 2003

We consider the problem of optimizing inventories for problems where the demand distribution is unknown, and where it does not necessarily follow a standard form such as the normal. We address problems where the process of deciding the inventory, and then realizing the demand, occurs repeatedly. The only information we use is the amount of inventory left over. Rather than attempting to estimate the demand distribution, we directly estimate the value function using a technique called the Concave, Adaptive Value Estimation (CAVE) algorithm. CAVE constructs a sequence of concave piecewise linear approximations using sample gradients of the recourse function at different points in the domain. Since it is a sampling-based method, CAVE does not require knowledge of the underlying sample distribution. The result is a nonlinear approximation that is more responsive than traditional linear stochastic quasi-gradient methods and more flexible than analytical techniques that require distribution information. In addition, we demonstrate near-optimal behavior of the CAVE approximation in experiments involving two different types of stochastic programs—the newsvendor stochastic inventory problem and two-stage distribution problems.
The Relationship Between Initial Quality Perceptions and Maintenance Behavior: The Case of the Automotive Industry
Authors: Conlon Edward , Devaraj Sarv , Matta Khalil F.
Published: December 2003

We examine the relationship between quality, represented by consumer ratings, and quality-related activities by the customer, represented by maintenance activities in the automotive industry. Based on several converging theoretical perspectives, we present and test a model relating vehicle initial quality ratings to consumers' routine maintenance. Three types of data were collected for the study: (1) vehicle service records at a local dealership, (2) primary data from a survey of vehicle owners, and (3) Consumer Reports data on quality ratings and initial purchase prices. The results of a structural equation analysis of the proposed model indicate a significant link between quality and customers' quality behavior. This link has important strategic implications for both automotive manufacturers and distributors, particularly as “leasing” becomes more prevalent in the industry.
Channel Coordination Under Price Protection, Midlife Returns, and End-of-Life Returns in Dynamic Markets
Authors: Taylor Terry A.
Published: December 2003

This paper examines three channel policies that are used in declining price environments: Price protection (P) is a mechanism under which the manufacturer pays the retailer a credit applying to the retailer's unsold inventory when the wholesale price drops during the life cycle; midlife returns (M) allow the retailer to return units partway through the life cycle at some rebate; and end-of-life returns (E) allow the retailer to return unsold units at the end of the life cycle. Under declining retail prices, if the wholesale prices and the return rebates are set properly, then EM (i.e., midlife and end-of-life returns) achieves channel coordination. However, such a policy may not be implementable because it may require the manufacturer to be worse off as a result of coordination. If P is used in addition to EM and the terms are set properly, then PEM guarantees both coordination and a win-win outcome. If the retail price is constant over time, then EM is sufficient to guarantee both coordination and a win-win outcome.
Representing and Solving Decision Problems with Limited Information
Authors: Lauritzen Steffen L. , Nilsson Dennis
Published: December 2003

We introduce the notion of LImited Memory Influence Diagram (LIMID) to describe multistage decision problems in which the traditional assumption of no forgetting is relaxed. This can be relevant in situations with multiple decision makers or when decisions must be prescribed under memory constraints, such as in partially observed Markov decision processes (POMDPs). We give an algorithm for improving any given strategy by local computation of single policy updates and investigate conditions for the resulting strategy to be optimal.
Analysis of a Forecasting-Production-Inventory System with Stationary Demand
Authors: Toktay L. Beril , Wein Lawrence M.
Published: December 2003

We consider a production stage that produces a single item in a make-to-stock manner. Demand for finished goods is stationary. In each time period, an updated vector of demand forecasts over the forecast horizon becomes available for use in production decisions. We model the sequence of forecast update vectors using the Martingale model of forecast evolution developed by Graves et al. (1986, 1998) and Heath and Jackson (1994). The production stage is modeled as a single-server, discrete-time, continuous-state queue. We focus on a modified base-stock policy incorporating forecast information and use an approximate analysis rooted in heavy traffic theory and random walk theory to obtain a closed-form expression for the (forecast-corrected) base-stock level that minimizes the expected steady-state inventory holding and backorder costs. This expression, which is shown to be accurate under certain conditions in a simulation study, sheds some light on the interrelationships among safety stock, stochastic correlated demand, inaccurate forecasts, and random and capacitated production in forecasting-production-inventory systems.
Links and Impacts: The Influence of Public Research on Industrial R&D
Authors: Cohen Wesley M. , Nelson Richard R. , Walsh John P.
Published: December 2003

In this paper, we use data from the Carnegie Mellon Survey on industrial R&D to evaluate for the U.S. manufacturing sector the influence of “public”(i.e., university and government R&D lab) research on industrial R&D, the role that public research plays in industrial R&D, and the pathways through which that effect is exercised. We find that public research is critical to industrial R&D in a small number of industries and importantly affects industrial R&D across much of the manufacturing sector. Contrary to the notion that university research largely generates new ideas for industrial R&D projects, the survey responses demonstrate that public research both suggests new R&D projects and contributes to the completion of existing projects in roughly equal measure overall. The results also indicate that the key channels through which university research impacts industrial R&D include published papers and reports, public conferences and meetings, informal information exchange, and consulting. We also finnd that, after controlling for industry, the influence of public research on industrial R&D is disproportionately greater for larger firms as well as start-ups.
Technology Selection and Commitment in New Product Development: The Role of Uncertainty and Design Flexibility
Authors: Krishnan V. , Bhattacharya Shantanu
Published: December 2003

Selecting the right technologies to incorporate in new products is a particularly challenging aspect of new product definition and development. While newer advanced technologies may offer improved performance, they also make the product development process more risky and challenging. In this paper, we focus on the problem of technology selection and commitment under uncertainty, a major challenge to firms in turbulent environments. We argue that the "pizza-bin" approach of rejecting prospective technologies outright may not serve firms well when the pressure to differentiate products is enormous. After motivating the challenges and decisions facing firms using a real-life application from Dell Computer Corporation, we formulate a mathematical model of a firm that must define its products in the presence of technology uncertainty. Specifically, the firm faces two options: (i) a proven technology that is known to be viable and (ii) a prospective technology that offers superior price to performance results but whose viability is not a fully certain outcome. To minimize the impact of technology uncertainty, we consider two approaches to design flexibility, termed parallel path and sufficient design, which allow the firm to concurrently develop its products while the technology is being validated. Our analysis helps understand appropriateness of the different flexible design approaches. We illustrate our model with the Dell portable computer example and note the managerial implications of our analysis.
Simultaneous Capacity and Production Management of Short-Life-Cycle, Produce-to-Stock Goods Under Stochastic Demand
Authors: Angelus Alexandar , Porteus Evan L.
Published: December 2003

This paper derives the optimal simultaneous capacity and production plan for a shortlife-cycle, produce-to-stock good under stochastic demand. Capacity can be reduced as well as added, at exogenously set unit prices. In both cases studied, with and without carryover of unsold units, a target interval policy is optimal: There is a (usually different) target interval for each period such that capacity should be changed as little as possible to bring the level available into that interval. Our contribution in the case of no carry-over, is a detailed characterization of the target intervals, assuming demands increase stochastically at the beginning of the life cycle and decrease thereafter. In the case of carry-over, we establish the general result and show that capacity and inventory are economic substitutes: The target intervals decrease in the initial stock level and the optimal unconstrained base stock level decreases in the capacity level. In both cases, optimal service rates are not necessarily constant over time. A numerical example illustrates the results.
A Mean-Variance Analysis of Self-Financing Portfolios
Authors: Korkie Bob , Turtle Harry J.
Published: December 2003

This paper develops the analytics and geometry of the investment opportunity set (IOS) and the test statistics for self-financing portfolios. A self-financing portfolio is a set of long and short investments such that the sum of their investment weights, or net investment, is zero. This contrasts with a standard portfolio that has investment weights summing to one. Examples of self-financing portfolios are hedges, overlays, arbitrage portfolios, swaps, and long/short portfolios. A standard portfolio plus the IOS of self-financing portfolios form a restricted IOS hyperbola with restricted efficient set constants that differ from the usual constants. The restrictions affect statistical tests of portfolio efficiency, which are developed for the self-financing restrictions. As an application, we consider the self-financing portfolios formed by Fama and French (1992, 1993, 1995), based on market capitalization and value. In contrast to Fama and French (1992, 1993, 1995), we find that their restricted IOS is significantly different from the unrestricted IOS with the implication that the Fama-French tests are misspecified.
Information Flows in Capacitated Supply Chains with Fixed Ordering Costs
Authors: Gavirneni Srinagesh
Published: December 2003

Many organizations have only recently recognized that sharing information with other members in their supply chain can lead to signficant reduction in the total costs.Usually these information flows are incorporated into existing operating policies at the various parties.In this paper we argue that, in some cases, it may be necessary to change the way the supply chain is managed to make complete use of the information flows. We support this argument by analyzing a supply chain containing a capacitated supplier and a retailer facing i.i.d. demands. In addition there are fixed ordering costs between the retailer and the supplier.In this setting, we consider two models: (1) the retailer is using the optimal (s,S) policy and providing the supplier information about her inventory levels; and (2) the retailer, still sharing information on her inventory levels, orders in a period only if by the previous period the cumulative end-customer demand since she last ordered was greater than δ. Thus, in Model 1, information sharing is used to supplement existing policies; while, in Model 2, we have redefined operating policies to make better use of the information flows. We will show, via a detailed computational study, that the total supply chain costs of Model 2 are 10.4% lower, on the average, than that of Model 1. We noticed that this reduction in costs is higher at higher capacities, higher supplier penalty costs, lower retailer penalty costs, moderate values of set-up cost, and at lower end-customer demand variances.
Neuronal Substrates for Choice Under Ambiguity, Risk, Gains, and Losses
Authors: Smith Kip , Dickhaut John , McCabe Kevin , Pardo José V.
Published: December 2003

Economic forces shape the behavior of individuals and institutions. Forces affecting individual behavior are attitudes about payoffs (gains and losses) and beliefs about outcomes (risk and ambiguity). Under risk, the likelihoods of alternative outcomes are fully known. Under ambiguity, these likelihoods are unknown. In our experiment, payoffs and outcomes were manipulated independently during a classical choice task as brain activity was measured with positron emission tomography (PET). Here, we show that attitudes about payoffs and beliefs about the likelihood of outcomes exhibit interaction effects both behaviorally and neurally. Participants are risk averse in gains and risk-seeking in losses; they are ambiguity-seeking in neither gains nor losses. Two neural substrates for choice surfaced in the interaction between attitudes and beliefs: a dorsomedial neocortical system and a ventromedial system. This finding reveals that the brain does not honor a prevalent assumption of economics—the independence of the evaluations of payoffs and outcomes. The demonstration of a relationship between brain activity and observed economic choice attests to the feasibility of a neuroeconomic decision science.
Strategic Equilibrium for a Pair of Competing Servers with Convex Cost and Balking
Authors: Christ Duane , Avi-Itzhak Benjamin
Published: December 2003

A two-person game is formulated for a queuing situation involving a pair of exponential servers competing for arriving customers. The servers have identical characteristics except for their service rates. Each server is free to select its own service rate. The objective of each server is to select a service rate that will maximize its own profit. Arrivals are Poisson. The probability that an arriving customer enters the queue is allowed to depend on the queue length at the time of arrival. The proportion of arrivals to a given server is shown to be strictly concave in the server's own service rate and decreasing in the other service rate. Furthermore, we show that when the cost function is convex and increasing, there exists a unique pure strategy Nash equilibrium point for the resulting game.
Truth or Consequences: An Experiment
Authors: Brandts Jordi , Charness Gary
Published: December 2003

This paper presents evidence that the willingness to punish an unfair action is sensitive to whether this action was preceded by a deceptive message. One player first sends a message indicating an intended play, which is either favorable or unfavorable to the other player in the game. After the message, the sender and the receiver play a simultaneous 2×2 game, in which the sender may or may not play according to his message. Outcome cells may, hence, be reached following true or false messages. In the third stage, the receiver may (at a cost) punish or reward, depending on which cell of the simultaneous game has been reached. We test whether receivers' rates of monetary sacrifice depend on the process by which an outcome is reached. We study two decision-elicitation methods: the strategy and the direct response methods. For each method, deception more than doubles the punishment rate as a response to an action that is unfavorable to the receiver. We also find evidence that 17–25% of all participants choose to reward a favorable action choice made by the sender, even though doing so leaves one at a payoff disadvantage. Our results reflect on current economic models of utility and have implications for organizational decision-making behavior.
The Role of the Management Sciences in Research on Personalization
Authors: Murthi B. P. S. , Sarkar Sumit
Published: December 2003

We present a review of research studies that deal with personalization and synthesize current knowledge about these areas. We identify issues that we envision will be of interest to researchers working in the management sciences, taking an interdisciplinary approach that spans the areas of economics, marketing, information technology (IT), and operations research. We present a framework for personalization that allows us to identify key players in the personalization process as well as key stages of personalization. The framework enables us to examine the strategic role of personalization in the interactions between a firm and other key players in the firm's value system. We conceptualize the personalization process as consisting of three stages: (1) learning about consumer preferences, (2) matching offerings to customers, and (3) evaluation of the learning and matching processes. This review focuses on the learning stage, with an emphasis on utility-based approaches to estimate preference functions using data on customer interactions with a firm.
A Bayesian Model for Prelaunch Sales Forecasting of Recorded Music
Authors: Lee Jonathan , Boatwright Peter , Kamakura Wagner A.
Published: December 2003

In a situation where several hundred new music albums are released each month, producing sales forecasts in a reliable and consistent manner is a rather difficult and cumbersome task. The purpose of this study is to obtain sales forecasts for a new album before it is introduced. We develop a hierarchical Bayesian model based on a logistic diffusion process. It allows for the generalization of various adoption patterns out of discrete data and can be applied in a situation where the eventual number of adopters is unknown. Using sales of previous albums along with information known prior to the launch of a new album, the model constructs informed priors, yielding prelaunch sales forecasts, which are out-of-sample predictions. In the context of new product forecasting before introduction, the information we have is limited to the relevant background characteristics of a new album. Knowing only the general attributes of a new album, the meta-analytic approach proposed here provides an informed prior on the dynamics of duration, the effects of marketing variables, and the unknown market potential. As new data become available, weekly sales forecasts and market size (number of eventual adopters) are revised and updated. We illustrate our approach using weekly sales data of albums that appeared inBillboard'sTop 200 albums chart from January 1994 to December 1995.
The Financial Rewards of New Product Introductions in the Personal Computer Industry
Authors: Bayus Barry L. , Erickson Gary , Jacobson Robert
Published: December 2003

Based on data from firms in the personal computer industry, we study the effect of new product introductions on three key drivers of firm value: profit rate, profit-rate persistence, and firm size as reflected in asset growth. Consistent with our theoretical development, we find that new product introductions influence profit rate and size; however, we find no effect on profit-rate persistence. Interestingly, we also find that the effect of new product introductions on profit rate stems from a reduction in selling and general administrative expenditure intensity rather than through an increase in gross operating return. Notably, firms decrease their advertising intensity in the wake of a new product introduction. Firm profitability in this industry apparently benefits from new product introductions because new products need less marketing support than older products.
Old Is Gold? The Value of Temporal Exploration in the Creation of New Knowledge
Authors: Nerkar Atul
Published: December 2003

In this paper, knowledge creation is considered as a path-dependent evolutionary process that involves recombining knowledge spread over time. The findings of the paper suggest that a balance in combining current knowledge with the knowledge available across large time spans is an important factor that explains the impact of new knowledge. These ideas are empirically tested using patent data from the pharmaceutical industry. Results from the analysis offer support for the hypotheses developed in the paper.
Note: Optimal Policies for Serial Inventory Systems Under Fill Rate Constraints
Authors: Axsäter Sven
Published: December 2003

A continuous review serial production/distribution system with discrete compound Poisson demand for the end product is considered. Unmet demand is back-ordered. Production/transportation times are constant. All deliveries from one stage to the next must be multiples of given batch sizes. We consider the problem of minimizing the holding costs under a fill rate constraint. Using recent results by Chen (2000), we show that under a set of restricted but plausible assumptions, the optimal policy is an echelon stock multistage (R, nQ) policy with one of the reorder points varying over time. We provide a simple procedure for the determination of the optimal policy.
Performance Impacts of Information Technology: Is Actual Usage the Missing Link?
Authors: Devaraj Sarv , Kohli Rajiv
Published: December 2003

The relationship between investment in information technology (IT) and its effect on organizational performance continues to interest academics and practitioners. In many cases, due to the nature of the research design employed, this stream of research has been unable to identify the impact of individual technologies on organizational performance. This study posits that the driver of IT impact is not the investment in the technology, but the actual usage of the technology. This proposition is tested in a longitudinal setting of a healthcare system comprising eight hospitals.

Monthly data for a three–year period on various financial and nonfinancial measures of hospital performance and technology usage were analyzed. The data analysis provides evidence for the technology usage–performance link after controlling for various external factors. Technology usage was positively and significantly associated with measures of hospital revenue and quality, and this effect occurred after time lags. The analysis was triangulated using three measures of technology usage. The general support for the principal proposition of this paper that “actual usage” may be a key variable in explaining the impact of technology on performance suggests that omission of this variable may be a missing link in IT payoff analyses.
Using Neural Network Rule Extraction and Decision Tables for Credit-Risk Evaluation
Authors: Baesens Bart , Setiono Rudy , Mues Christophe , Vanthienen Jan
Published: December 2003

Credit-risk evaluation is a very challenging and important management science problem in the domain of financial analysis. Many classification methods have been suggested in the literature to tackle this problem. Neural networks, especially, have received a lot of attention because of their universal approximation property. However, a major drawback associated with the use of neural networks for decision making is their lack of explanation capability. While they can achieve a high predictive accuracy rate, the reasoning behind how they reach their decisions is not readily available. In this paper, we present the results from analysing three real-life credit-risk data sets using neural network rule extraction techniques. Clarifying the neural network decisions by explanatory rules that capture the learned knowledge embedded in the networks can help the credit-risk manager in explaining why a particular applicant is classified as either bad or good. Furthermore, we also discuss how these rules can be visualized as a decision table in a compact and intuitive graphical format that facilitates easy consultation. It is concluded that neural network rule extraction and decision tables are powerful management tools that allow us to build advanced and userfriendly decision-support systems for credit-risk evaluation.
Relational Embeddedness and Learning: The Case of Bank Loan Managers and Their Clients
Authors: Uzzi Brian , Lancaster Ryon
Published: December 2003

As a complement to the literature on learning in firms, we investigate learning in markets, a nascent area of study that focuses on how learning occurs between, rather than within, firms. The core idea behind our framework is that networks shape knowledge transfer and learning processes by creating channels for knowledge trade and reducing the risk of learning. In developing our framework, we elaborate on the knowledge transfer capabilities of different types of social ties, the informational properties of public and private knowledge, and how types of knowledge transfer and forms of learning follow from the networks within which firms embed their exchanges. We conducted fieldwork at Chicago-area banks to examine our framework's plausibility and application to learning in financial lending markets, a setting relevant to most firms. Findings indicate that learning is located not only in actors' cognitions or past experiences, but also in relations among actors, and that viewing learning as a social process helps solve problems regarding knowledge transfer and learning in markets.
Valuing Internal vs. External Knowledge: Explaining the Preference for Outsiders
Authors: Menon Tanya , Pfeffer Jeffrey
Published: December 2003

This paper compares how managers value knowledge from internal and external sources. Although many theories account for favoritism toward insiders, we find that preferences for knowledge obtained from outsiders are also prevalent. Two complementary case studies and survey data from managers demonstrate the phenomenon of valuing external knowledge more highly than internal knowledge and reveal some mechanisms through which this process occurs. We found evidence that the preference for outsider knowledge is the result of managerial responses to (1) the contrasting status implications of learning from internal versus external competitors, and (2) the availability or scarcity of knowledge-internal knowledge is more readily available and hence subject to greater scrutiny, while external knowledge is more scarce, which makes it appear more special and unique. We conclude by considering some consequences of the external knowledge preference for organizational functioning.
Interruptive Events and Team Knowledge Acquisition
Authors: Zellmer-Bruhn Mary E.
Published: December 2003

Interruptions have commonly been viewed as negative and as something for managers to control or limit. In this paper, I explore the relationship between interruptions and acquisition of routines—a form of knowledge—by teams. Recent research suggests that interruptions may play an important role in changing organizational routines, and as such may influence knowledge transfer activities. Results suggest that interruptions influence knowledge transfer effort, and both knowledge transfer effort and interruptions are positively related to the acquisition of new work routines. I conclude with implications for research and practice.
Exploration and Exploitation in the Presence of Network Externalities
Authors: Lee Jongseok , Lee Jeho , Lee Habin
Published: December 2003

This paper examines the conditions under which exploration of a new, incompatible technologyis conducive to firm growth in the presence of network externalities. In particular, this study is motivated by the divergent evolutions of the PC and the workstation markets in response to a new technology: reduced instruction set computing (RISC). In the PC market, Intel has developed new microprocessors by maintaining compatibility with the established architecture, whereas it was radically replaced by RISC in the workstation market. History indicates that unlike the PC market, the workstation market consisted of a large number of power users, who are less sensitive to compatibility than ordinary users. Our numerical analysis indicates that the exploration of a new, incompatible technology is more likely to increase the chance of firm growth when there are a substantial number of power users or when a new technology is introduced before an established technology takes off.
How Communication Links Influence Coalition Bargaining: A Laboratory Investigation
Authors: Bolton Gary E. , Chatterjee Kalyan , McGinn Kathleen L.
Published: December 2003

Complexity of communication is one of the important factors that distinguishes multilateral negotiation from its bilateral cousin. We investigate how the communication configuration affects a three-person coalition negotiation. Restricting who can communicate with whom strongly influences outcomes, and not always in ways that current theory anticipates. Competitive frictions, including a tendency to communicate offers privately, appear to shape much of what we observe. Our results suggest that parties with weaker alternatives would benefit from a more constrained structure, especially if they can be the conduit of communication, while those endowed with stronger alternatives would do well to work within a more public communication structure that promotes competitive bidding.
Salesforce Compensation Scheme and Consumer Inferences
Authors: Kalra Ajay , Shi Mengze , Srinivasan Kannan
Published: December 2003

We investigate the salesforce compensation strategy of a firm selling products in a category that several consumers find technically sophisticated, such as electronics or financial products with legal fine print. Consumers are unable to judge the value difference between a baseline product and a product upgrade with add-on features. While the firm and the salespeople are informed of the value of these features, consumers are uncertain. Thus, consumers have to rely on sales assistance to evaluate alternatives. The salesperson decision variables include selling effort and whether to “oversell” the consumer by overclaiming the value of added features. Because sales revenue depends on both the salesperson's selling effort and consumers' valuation of the added features, the salesforce incentive scheme (which can consist of salary, sales commission, or consumer satisfaction-based commission) may induce the short-term oriented salesperson to misrepresent the value of the upgrade. Exaggeration of the value of the added features, however, results in reduced satisfaction levels leading to lower profits for the firm. We show that a salesperson selling products where the value of the upgrade is low prefers to make higher claims when the sales commission rate is sufficiently high. We conjecture that consumers aware of the incentive structure facing the salesperson expect the true value of the add-on feature to be lower than the claimed value. We study the optimal compensation scheme of a firm, which has to communicate her true type and retain its salesforce credibility. We identify the conditions under which a high-upgrade-type firm indicates its true value by altering sales commission rate and satisfaction-based commission rate.