bluuebunny/crossref_metadata_2025 huggingface dataset:
Information Distortion in a Supply Chain: The Bullwhip Effect
Authors: Lee Hau L. , Padmanabhan V. , Whang Seungjin
Published: November 2008

Consider a series of companies in a supply chain, each of whom orders from its immediate upstream member. In this setting, inbound orders from a downstream member serve as a valuable informational input to upstream production and inventory decisions. This paper claims that the information transferred in the form of “orders” tends to be distorted and can misguide upstream members in their inventory and production decisions. In particular, the variance of orders may be larger than that of sales, and the distortion tends to increase as one moves upstream—a phenomenon termed “bullwhip effect.” This paper analyzes four sources of the bullwhip effect: demand signal processing, rationing game, order batching, and price variations. Actions that can be taken to mitigate the detrimental impact of this distortion are also discussed.
Skill in Games
Authors: Larkey Patrick , Kadane Joseph B. , Austin Robert , Zamir Shmuel
Published: November 2008

Differences in players' skill are important determinants of relative player success in most real games such as poker, chess, basketball, business, and politics. Yet conventional game theory has concentrated primarily on games with no skill differences among players. This paper uses a simplified version of stud poker to better understand the concept of differential player skill in games. Players with very different strategies for playing this game are modeled algorithmically and pitted against one another in simulation tournaments.
Domestic Competitive Position and Export Strategy of Japanese Manufacturing Firms: 1971–1985
Authors: Ito Kiyohiko
Published: November 2008

This paper analyzes Japanese manufacturing firms' export behavior and their performance. In a slow growth era, leading firms' and minor firms' export ratio tended to be less than that of follower (medium market share) firms in the same industry; there appears to be an inverted-U shape between export ratio and relative size of firms. An affiliation with a large industrial group has no positive relationship with export ratio, while other firm-specific factors do not show consistent relationships with it in the years 1971 to 1985. Exports and firm performance do not have a positive relationship. Competitive environment in the domestic market is related to the export strategy of Japanese firms.
Metagraphs in Hierarchical Modeling
Authors: Basu Amit , Blanning Robert W. , Shtub Avraham
Published: November 2008

When using a decision support system (DSS) containing a large model base, a user has to decide which specific models are relevant for any particular task. When the model base is large and diverse, this task can be quite difficult. Furthermore, the number and variety of models available can be confusing. One way to simplify the user's interaction with the DSS, and facilitate more effective use of the system, is through the use of “views” of the model base. A view is an abstraction of a model base that limits attention to relationships between certain variables, and its purpose is to guide the development of DSS software that executes lower-level models in response to higher-level requests for information or analysis. Single views may be of use to individual decision makers who wish to abstract information from a model base, and multiple views may be of use to collections of decision makers who are using a model base to integrate their analyses to make a collective decision. In this paper, we show how representation of models using a graph theoretic structure called a metagraph can facilitate the construction and maintenance of model base views. In particular, we show how useful views can be constructed using a projection operation on a metagraph, and also present conditions under which views can be combined. The concepts developed in the paper are illustrated using an example from life cycle costing.
Middle Management Downsizing: An Empirical Investigation of the Impact of Information Technology
Authors: Pinsonneault Alain , Kraemer Kenneth L.
Published: November 2008

Nearly all Fortune 1000 firms claim to have downsized since the early eighties, and it is argued that information technology (IT) is responsible for this massive downsizing. However, earlier research has indicated that IT increases middle management. Even though the impact of IT on the middle management workforce has been studied for the last thirty years, research has failed to clearly explain this phenomenon. Quite the opposite, research has fueled controversy and has provided inconsistent findings. This article addresses the state of inconsistent findings across multiple studies by examining the impact of information technology on the number of middle managers using two additional variables: the degree of centralization of organizational decision authority and the degree of centralization of computing decision authority. One hundred and fifty-five city governments were surveyed. Information technology was found to be both positively and negatively associated with the size of the middle management workforce. The impact of information technology was fundamentally determined by who controlled computing decisions and what interests were being served, and by the roles of middle managers. Information technology was associated with a decrease in the size of the middle management workforce in organizations with centralized decision authority and with an increase in the number of middle managers in organizations where decision authority was decentralized.
Use of Convex Cones in Interactive Multiple Objective Decision Making
Authors: Prasad Srinivas Y. , Karwan Mark H. , Zionts Stanley
Published: November 2008

One approach for solving decision problems involving multiple objectives is interactive optimization. Methods based on this approach assess the decision maker’s preference structure interactively, typically based on pairwise comparisons and tradeoffs, and guide the search process toward identifying improved solutions. A desirable feature of such approaches, that is based on minimizing the preference information requirements, is fast convergence. Toward this end, the use of convex cones as a preference structure representation has been proposed in the literature. In this work, new theory is developed that aids in further reducing preference information requirements and improving convergence. New cones termed p cones are developed. The efficiencies of solution alternatives are evaluated with respect to the p cones, and these are termed p cone efficiencies. Acceleration and Early Termination procedures that are based on these efficiencies are proposed. The procedures are presented within a solution framework for solving Multiple Objective Linear Programming (MOLP) problems along with computational results.
Moral Hazard in Corporate Investment and the Disciplinary Role of Voluntary Capital Rationing
Authors: Zhang Guochang
Published: November 2008

This paper compares three capital-budgeting rules, the NPV rule, a high hurdle rate and capital rationing, and explains why some firms may voluntarily impose capital rationing. Under both capital rationing and a high hurdle, a restrictive investment criterion is used to control managerial shirking. However, implementation of these budgeting rules requires a mechanism to prevent the firm from expanding the investment scale ex post. Capital rationing, in the form of a predetermined, fixed budget, differs from the high-hurdle-rate rule in that the former requires the firm to overcome the cost of raising additional capital before making further investment.
Incomplete Information, Task Assignment, and Managerial Control Systems
Authors: Sridhar Sri S. , Balachandran Bala V.
Published: November 2008

A firm typically assigns multiple tasks it must perform to either internal employees or outside vendors. This paper demonstrates the need to integrate a task assignment decision with the design of a managerial control system as each affects the other. An internal employee is distinguished from an outside supplier on four different informational dimensions: (i) at the time of contracting, the outside supplier has less information about the task environment more often than the internal employee; (ii) the principal observes the employee's information set more frequently than that of the supplier; (iii) the principal can exercise a greater control over information flow to the internal employee than to the outside supplier; and (iv) the principal may share the details of the outside supplier's contract with the internal employee but not vice versa. Under each of these four distinguishing dimensions, the principal is shown to outsource the upstream task and assign the downstream task to the internal employee more often than vice versa. Further, under the last two dimensions of the firm's boundary, the principal can eliminate inefficiencies arising from the agents' contracting with incomplete information by assigning the downstream task to the employee and not providing predecision information to him while assigning the upstream task to the supplier.
An Empirical Study on Intertemporal Decision Making Under Risk
Authors: Ahlbrecht Martin , Weber Martin
Published: November 2008

This study compares time preference in the cases of certainty and risk. We analyze both matching and choice behavior. We find that violations of the stationarity axiom are restricted to matching behavior, both for certainty and risk. We also compare the discounting of certain and risky outcomes as well as the discounting of gains and losses. In matching tasks, certain outcomes are discounted more than risky ones. We could not confirm these results in a choice task. Gains and losses are not found to be discounted at different rates.
Maximizing the Effectiveness of a Preventive Maintenance System: An Adaptive Modeling Approach
Authors: Gopalakrishnan Mohan , Ahire Sanjay L. , Miller David M.
Published: November 2008

The dynamic nature of an operating environment, such as machine utilization and breakdown frequency results in changing preventive maintenance (PM) needs for manufacturing equipment. In this paper, we present an approach to generate an adaptive PM schedule which maximizes the net savings from PM subject to workforce constraints. The approach consists of two components: (a) task prioritization based on a multi-logit regression model for each type of PM task, and (b) task rescheduling based on a binary integer programming (BIP) model with constraints on single-skilled and multi-skilled workforce availability. The task prioritization component develops a multi-logit regression for machine failure probability associated with each type of PM task at the beginning of the year, using historical data on machine utilization, PM, and machine breakdowns. At the start of each PM time-bucket (e.g., a month), we use the updated machine failure probability for each candidate PM task to compute its current contribution to net PM savings, which indicates its current priority. The task rescheduling BIP model incorporates the priorities in selecting tasks for the current bucket to maximize PM effectiveness subject to workforce availability, yielding an adaptive and effective PM schedule for each time-bucket of the master PM schedule. We examine the effect of using multi-skilled workforce on the overall PM effectiveness, and also provide an illustration from a newspaper publishing environment to explain the use of the approach. We have developed four heuristic algorithms to yield good solutions to large scale versions of this scheduling problem. The heuristics perform extremely well, and the best heuristic solution is within 1.4% of optimality on an average.
Forecasting a Cumulative Variable Using Its Partially Accumulated Data
Authors: Guerrero Victor M. , Elizondo J. Alan
Published: November 2008

Several forecasting algorithms have been proposed to forecast a cumulative variable using its partially accumulated data. Some particular cases of this problem are known in the literature as the “style goods inventory problem” or as “forecasting shipments using firm orders-to-date”, among other names. Here we summarize some of the most popular techniques and propose a statistical approach to discriminate among them in an objective (data-based) way. Our basic idea is to use statistical models to produce minimum mean square error forecasts and let the data lead us to select an appropriate model to represent their behavior. We apply our proposal to some published data showing total accumulated values with constant level and then to two actual sets of data pertaining to the Mexican economy, showing a nonconstant level. The forecasting performance of the statistical models was evaluated by comparing their results against those obtained with algorithmic solutions. In general the models produced better forecasts for all lead times, as indicated by the most common measures of forecasting accuracy and precision.
The Multi-Item Setup-Reduction Investment-Allocation Problem with Continuous Investment-Cost Functions
Authors: Leschke John P. , Weiss Elliott N.
Published: November 2008

In this note, we analyze investment priorities for setup-reduction programs in a multi-product system. We provide an objective function transformation for the model developed by Porteus (Porteus, E. L. 1985. Investing in reduced setups in the EOQ model. Management Sci. 31(8, August) 998–1010.) that permits the use of marginal analysis in both the single- and multiple-item problems. For the multiple-item problem, we show that managers should not reduce the setup for each product to its optimum in sequential order. This is in contrast to recommendations found in the existing literature.
Using On-Line Sensors in Statistical Process Control
Authors: Gong Linguo , Jwo Wushong , Tang Kwei
Published: November 2008

As manufacturing technology moves toward more computerized automation, statistical process control (SPC) techniques must adapt to keep pace with the new environment and take advantage of the development in automated on-line sensors. In this paper, a two-phase procedure is proposed for combining an on-line sensor and a control chart to improve statistical process control decisions. In phase 1 of this procedure, a production process is monitored continually by a sensor. When a sensor warning signal is observed, phase 2 takes place: A sample of items is drawn from the process and inspected. If the sample mean is outside the predetermined control limits, the process is stopped, and a search is initiated to determine the actual process status for possible necessary adjustment. If the sample mean is within the control limits, the process continues. A mathematical model is formulated for jointly determining the sample size and the control limit of the control chart and a decision rule for sending out sensor warning signals. The model is based on the assumption that there is only a weak relationship between the sensor measurement and the process condition. A solution algorithm based on a numerical search is developed. A numerical example is used to show the advantage of the proposed model over the models based separately on the sensor and the control chart, and a sensitivity analysis is used to show the effects of several important model parameters on the optimal solution.
Decomposed Versus Holistic Estimates of Effort Required for Software Writing Tasks
Authors: Connolly Terry , Dean Doug
Published: November 2008

We examine decision analysis’ central “decomposition principle” in the context of work-time estimates of software writers. Two experiments examined the abilities of advanced programming students to estimate how long they would take to complete specific software projects. They estimated their own work times both for entire projects and for their constituent subtasks. Estimates showed varying degrees of overoptimism and overpessimism but all were much too tight, with almost half of actual outcomes falling in the 1% tails of estimated distributions. This overtightness was unaffected by task decomposition, question wording, question order, or training in estimation. It was, however, significantly reduced by a procedure aimed at inducing generous upper and lower plausible limits. An underlying model of incomplete search is used to connect these findings to existing themes in cognition and judgment research, as well as to practical application. The findings suggest that the best level of decomposition at which to elicit work-time estimates may depend on task, judge, and elicitation method.
Making a Case for Robust Optimization Models
Authors: Bai Dawei , Carpenter Tamra , Mulvey John
Published: November 2008

Robust optimization searches for recommendations that are relatively immune to anticipated uncertainty in the problem parameters. Stochasticities are addressed via a set of discrete scenarios. This paper presents applications in which the traditional stochastic linear program fails to identify a robust solution—despite the presence of a cheap robust point. Limitations of piecewise linearization are discussed. We argue that a concave utility function should be incorporated in a model whenever the decision maker is risk averse. Examples are taken from telecommunications and financial planning.
Tabu Search and Ejection Chains—Application to a Node Weighted Version of the Cardinality-Constrained TSP
Authors: Cao Buyang , Glover Fred
Published: November 2008

A cardinality-constrained TSP (CC-TSP) problem requires the salesman to visit at least L and at most U cities, represented by nodes of a graph. The objective of this problem is to maximize the sum of weights of nodes visited. In this paper we propose a tabu search method based on ejection chain procedures, which have proved effective for many kinds of combinatorial optimization problems. Computational results on a set of randomly generated test problems with various implementations of the algorithm are reported.
Garbage Collection in Chicago: A Dynamic Scheduling Model
Authors: Eisenstein Donald D. , Iyer Ananth. V.
Published: November 2008

We investigate the scheduling of garbage trucks in the city of Chicago. Analysis of data collected from the system shows that city blocks differ in the rate at which garbage is collected. However, in the current system, each truck visits the dumpsite two times each day. Our approach is to devise a flexible routing scheme in which some routes visit the dumpsite only once per day, while others visit the dumpsite twice per day depending on the blocks assigned to the route. We use a Markov decision process to model the impact on capacity of using flexible routes. This provides a dynamic scheduling algorithm that adjusts the number of dumpsite visits throughout the week to maximize service level. Results of the model suggest a potential reduction in truck capacity of 12–16% for a set of five pilot wards. This paper shows that flexible schedules can significantly reduce the capacity required to operate a system in the presence of variability.
Tractable (Q, R) Heuristic Models for Constrained Service Levels
Authors: Platt David E. , Robinson Lawrence W. , Freund Robert B.
Published: November 2008

The fill rate (the proportion of demand that is satisfied from stock) is a viable alternative in inventory models to the hard-to-quantify penalty cost. However, a number of difficulties have impeded its implementation, among them that the existing cycle-based approximate solutions do not reflect the possibility of multiple outstanding orders and that the optimal policy cannot be found directly, but must be iteratively calculated. We show that for a large family of leadtime demand distributions, the optimal policy depends on only two parameters: the fill rate and the economic order quantity (EOQ) scaled by the standard deviation of demand over the constant leadtime. If we then assume that the leadtime demand is normally distributed, we can use the asymptotic results as the EOQ goes to zero and to positive infinity to fit atheoretic curves for the order quantity Q and the reorder point R. These fitted curves yield a good (Q, R) policy without iteration. We also find that, among the set of simple heuristics, the limit form as EOQ goes to positive infinity provides a better alternative to simply setting Q equal to the EOQ.
Calculating the Reserve for a Time and Usage Indexed Warranty
Authors: Eliashberg Jehoshua , Singpurwalla Nozer D. , Wilson Simon P.
Published: November 2008

Many products carry a warranty that offers protection for the consumer against low quality. These warranties are often two dimensional, such as an automobile warranty that guarantees repair up to a certain time and mileage after sale. This paper considers the problem of assessing the size of a reserve needed by the manufacturer to meet future claims for such a two-dimensional warranty. To do this, a class of failure models that describe failure by two scales—time and mileage, for example—must be developed. The first half of the paper is devoted to this development. Then the warranty reserve problem is considered in more detail. The problem is described and a decision-theoretic solution, making use of the newly developed reliability model, is proposed.
A Dynamic, Globally Diversified, Index Neutral Synthetic Asset Allocation Strategy
Authors: Novomestky Frederick
Published: November 2008

An investor with the ability to assess the prospective return and risk structure of the global capital markets can construct portfolios that, over time, will not only outperform actively or passively managed domestic asset portfolios but will also outperform passively managed global portfolios. A Bayesian approach to dynamic seemingly unrelated regression (DSUR) is a robust and effective means to forecast the one-step ahead, conditional distribution of asset returns. This approach recognizes the time-varying nature of the global capital markets. The predictive moments are used to derive a single-factor return model once an index portfolio is specified. The index portfolio represents an investor's underlying portfolio. Given the factor model that assesses the relative attractiveness and risk of the assets in relation to the index, an index neutral portfolio is constructed as an overlay to enhance the returns of the index portfolio. This portfolio is mean-variance optimal, is notional neutral (i.e., the sum of the asset exposures is zero), and has returns that are designed to be uncorrelated with the returns of the index portfolio. The implementation of such an index neutral portfolio using derivative securities is simulated over the period January 1988 to December 1993.
Aspiration-Based Search Algorithm (ABSALG) for Multiple Objective Linear Programming Problems: Theory and Comparative Tests
Authors: Lotfi Vahid , Yoon Yong. S. , Zionts Stanley
Published: November 2008

We develop an interactive method for multiple objective linear programming based on aspiration levels of a decision maker. The method assumes an unknown pseudoconcave preference structure of a decision maker throughout the decision process, and the decision maker's ability to select a preferred solution from p + 1 alternatives, where p is the number of objectives. In addition to presenting the supporting theory and algorithm, we perform a comparative study using a fictitious decision maker, comparing our approach to those of Steuer and Choo (Steuer, R. E., E. Choo. 1983. An interactive weighted Tchebycheff procedure for multiple objective programming. Math. Prog. 26 326–344.) and Reeves and Franz (Reeves, G. R., L. Franz. 1985. A simplified interactive multiple objective linear programming procedure. Comp. & Oper. Res. 12 589–601.). All three methods are interactive. During an iteration, each method presents several solution alternatives to the decision maker simultaneously. Our approach utilizes a Tchebycheff function that facilitates attainment of an optimum at a nonextreme point solution. The statistics collected in the comparative study provide insights into the nature of the algorithms and the behavior of the solution techniques with different categories of problem structure and different underlying utility functions.
Prudent Margin Levels in the Finnish Stock Index Futures Market
Authors: Booth G. Geoffrey , Broussard John Paul , Martikainen Teppo , Puttonen Vesa
Published: November 2008

Futures market officials are confronted with the difficult task of setting appropriate margin levels that must balance the costs of trader default and the benefits of increased market liquidity. One way to guard against default is prudent margin setting practices designed to protect futures positions from extreme price movements. The objective of this research is to extrapolate the probabilities of encountering extreme price movements by applying statistical extreme value theory to the Finnish stock index futures market. The extreme value technique is found to be appropriate since it generates theoretical margin violation probabilities that closely follow the empirical probability distribution. The extrapolated results provide decision makers information on extreme events that have not yet occurred.
Inspection for Circuit Board Assembly
Authors: Chevalier Phillipe B. , Wein Lawrence M.
Published: November 2008

Several stages of tests are typically performed in circuit board assembly, and each test consists of one or more noisy measurements. We consider the problem of jointly optimizing the allocation of inspection and the testing policy in a system with a predefined inspection configuration; that is, at which stages should a board be inspected, and at these stages, whether to accept or reject a board based on noisy test measurements. The objective is to minimize the expected costs for testing, repair, and defective items shipped to customers. We analyze the problem and document an application of the model to an industrial facility. Since we were unable to gather all the necessary data, the model was applied in a limited and piecemeal fashion. Nevertheless, the proposed policy significantly improves upon the facility's historical policy.
Large-Sample Results for Batch Means
Authors: Chien Chiahon , Goldsman David , Melamed Benjamin
Published: November 2008

In analyzing the output process generated by a steady-state simulation, we often seek to estimate the expected value of the output. The sample mean based on a finite sample of size n is usually the estimator of choice for the steady-state mean; and a measure of the sample mean's precision is the variance parameter, i.e., the limiting value of the sample size multiplied by the variance of the sample mean as n becomes large. This paper establishes asymptotic properties of the conventional batch-means (BM) estimator of the variance parameter as both the batch size and the number of batches become large. In particular, we show that the BM variance estimator is asymptotically unbiased and convergent in mean square. We also provide asymptotic expressions for the variance of the BM variance estimator. Exact and empirical examples illustrate our findings.
Control of a Stochastic Production System with Estimated Parameters
Authors: Denardo Eric V. , Tang Christopher S.
Published: November 2008

For an uncertain production system, the rule that controls the flow of material relies on parameters, such as the yield rates and the demand rate. These parameters are estimates, and they are usually inaccurate. In this paper, we analyze a type of “pull” rule called a proportional restoration rule. We show that these rules are stable; they do not lead to erratic behavior even when the estimation error is significant. We also show that these rules localize the effect of mis-estimates; e.g., underestimating the demand rate lowers the level of finished goods inventory, but has scant effect within the line. We show that these rules exhibit other desirable attributes—that they are efficient, that they are easy to interpret, and that they recover from disruptions quickly.
R&D and Global Manufacturing Performance
Authors: Ettlie John E.
Published: November 2008

R&D intensity and manufacturing performance were evaluated in this study of 600 durable goods firms in 20 countries. In a path-analytic model, R&D intensity was significantly associated with improvements in market share (R2= 34%), controlling for firm size, previous market share, and regardless of industry or region of the world. Market share increases were also significantly correlated with improvements in manufacturing agility (R2= 4%). Agility improvement was significantly correlated with R&D intensity, and computerization in manufacturing, controlling for firm size and region, and did exhibit industry effects, with electronic equipment firms elevated on this measure. Computerization exhibited regional (not industry) differences, with South American firms depressed on this measure. The role of computerization in manufacturing and agility in firm innovativeness are discussed.
Equilibrium Play in Large Group Market Entry Games
Authors: Rapoport Amnon , Seale Darryl A. , Erev Ido , Sundali James A.
Published: November 2008

Coordination behavior is studied experimentally in a class of noncooperative market entry games featuring symmetric players, complete information, zero entry costs, and several randomly presented values of the market capacity. Once the market capacity becomes publicly known, each player must decide privately whether to enter the market and receive a payoff, which increases linearly in the difference between the market capacity and the number of entrants, or stay out. Payoffs for staying out are either positive, giving rise to the domain of gains, or negative, giving rise to the domain of losses. The major findings are substantial individual differences that do not diminish with practice, aggregate behavior that is organized extremely well in both the domains of gains and losses by the Nash equilibrium solution, and variations in the population action strategies with repeated play of the stage game that are accounted for by a variant of an adaptive learning model due to Roth and Erev (1995).
Sensitivity Analysis of Efficiency Scores: How to Bootstrap in Nonparametric Frontier Models
Authors: Simar Léopold , Wilson Paul W.
Published: November 2008

Efficiency scores of production units are generally measured relative to an estimated production frontier. Nonparametric estimators (DEA, FDH, ⋯) are based on a finite sample of observed production units. The bootstrap is one easy way to analyze the sensitivity of efficiency scores relative to the sampling variations of the estimated frontier. The main point in order to validate the bootstrap is to define a reasonable data-generating process in this complex framework and to propose a reasonable estimator of it. This paper provides a general methodology of bootstrapping in nonparametric frontier models. Some adapted methods are illustrated in analyzing the bootstrap sampling variations of input efficiency measures of electricity plants.
Deterrence, Reputations, and Competitive Cognition
Authors: Clark Bruce H. , Montgomery David B.
Published: November 2008

This study examines an aspect of competitive interactions that has attracted increasing research attention: the relationship between deterrence and competitive reputations. We build a conceptual model of the antecedents and consequences of a firm's reputation for being a credible defender of its markets. Theory and limited empirical evidence suggests a firm with this reputation should deter competitive attacks against it. We explore how a manager's competitive cognition about her opponents' (1) patterns of activity in the marketplace and (2) previous success can lead her to perceive a competitor as a credible defender. We test the framework using MBA students in a quasi-field setting, the Markstrat2 simulation game. The results of this study suggest that reputation deters attack only when the potential attacker considers the target firm a minor competitor. Managers consider defenders that have previously been successful as credible defenders of their markets. They also weigh consistency of activity relative to industry average in making inferences about credibility. The study indicates that the deterrence-reputation link is more complex than previous theory and evidence might imply, and suggests considerable promise for a psychological approach to examining competitive interactions.
Foundations 2025: A Value Model for Evaluating Future Air and Space Forces
Authors: Parnell Gregory S. , Conley Harry W. , Jackson Jack A. , Lehmkuhl Lee J. , Andrew John M.
Published: November 2008

Air Force 2025 was a study directed by the Chief of Staff of the United States Air Force to identify key system concepts and technologies for achieving air and space dominance in the year 2025. The study was a large effort in which over 200 military experts participated for more than one year. We developed a Value-Focused Thinking model, which we used to evaluate which futuristic system concepts have the greatest potential to ensure future U.S. air and space dominance. We named the value model Foundations 2025 because it represented a return to the basics of air and space dominance. We used the “silver standard” approach for value hierarchy development. The participants identified key verbs to describe tasks that must be performed in 2025 to ensure air and space dominance. The value hierarchy was developed bottom-up by aggregating these verbs into higher order tasks using affinity diagrams. Using the value hierarchy, we used multiattribute decision analysis techniques to develop an additive value model with 134 attributes. The Foundations 2025 value model was successfully used to score 43 futuristic system concepts and provide insights about the most promising system concepts and technologies. The analysis results directly supported the study director and the senior leadership of the United States Air Force.
A Subpath Ejection Method for the Vehicle Routing Problem
Authors: Rego César
Published: November 2008

Generically, ejection chains are methods conceived to allow solution transformations to be efficiently carried out by modifying a variable number of their components at each step of a local search algorithm.

We consider a subpath ejection chain method for the vehicle routing problem (VRP) under capacity and route length restrictions. The method undertakes the identification of a substructure named the flower reference structure which, besides coordinating moves during an ejection chain construction, allows the creation of neighborhood structures with interesting combinatorial characteristics. Specifically, we base the method on a fundamental property of creating alternating paths and cycles during an ejection chain construction.

A new algorithm based on a Tabu search framework is proposed, and computational results on a set of academic and real-world problems indicate that the algorithm may be a good alternative to the best heuristic algorithms for the VRP.
Long-Run Abstinence After Narcotics Abuse: What Are the Odds?
Authors: Dekimpe Marnik G. , Van de Gucht Linda M. , Hanssens Dominique M. , Powers Keiko I.
Published: November 2008

We consider the long-run odds that narcotics users remain abstinent after methadone treatment. A flexible split-hazard specification that allows for individual-level differences in both the long-run probability of eventual relapse and the short-run timing of relapse is developed. The model is applied to a comprehensive data set involving individual drug abuse and treatment histories for over 800 addicts. Our findings indicate (1) that the short-run success of methadone programs does not automatically translate into long-run abstinence, which suggests the need for aftercare, (2) the value of preventing a teenager or young adult from initiating, and (3) the possibility of identifying high-risk groups, both in terms of age of first daily use and in terms of ethnicity.
ACLIPS: A Capacity and Lead Time Integrated Procedure for Scheduling
Authors: Lambrecht Marc R. , Ivens Philip L. , Vandaele Nico J.
Published: November 2008

We propose a general hierarchical procedure to address real-life job shop scheduling problems. The shop typically produces a variety of products, each with its own arrival stream, its own route through the shop and a given customer due date. The procedure first determines the manufacturing lot sizes for each product. The objective is to minimize the expected lead time, and therefore we model the production environment as a queueing network. Given these lead times, release dates are set dynamically. This in turn creates a time window for every manufacturing order in which the various operations have to be sequenced. The sequencing logic is based on an Extended Shifting Bottleneck Procedure. These three major decisions are next incorporated into a four-phase, hierarchical, operational implementation scheme. A small numerical example is used to illustrate the methodology. The final objective however is to develop a procedure that is useful for large, real-life shops. We therefore report on a real-life application.
An Analysis of Bid-Price Controls for Network Revenue Management
Authors: Talluri Kalyan , van Ryzin Garrett
Published: November 2008

Bid-prices are becoming an increasingly popular method for controlling the sale of inventory in revenue management applications. In this form of control, threshold—or “bid”—prices are set for the resources or units of inventory (seats on flight legs, hotel rooms on specific dates, etc.) and a product (a seat in a fare class on an itinerary or room for a sequence of dates) is sold only if the offered fare exceeds the sum of the threshold prices of all the resources needed to supply the product. This approach is appealing on intuitive and practical grounds, but the theory underlying it is not well developed. Moreover, the extent to which bid-price controls represent optimal or near optimal policies is not well understood. Using a general model of the demand process, we show that bid-price control is not optimal in general and analyze why bid-price schemes can fail to produce correct accept/deny decisions. However, we prove that when leg capacities and sales volumes are large, bid-price controls are asymptotically optimal, provided the right bid prices are used. We also provide analytical upper bounds on the optimal revenue. In addition, we analyze properties of the asymptotically optimal bid prices. For example, we show they are constant over time, even when demand is nonstationary, and that they may not be unique.
The Effects of R&D Team Co-location on Communication Patterns among R&D, Marketing, and Manufacturing
Authors: Van den Bulte Christophe , Moenaert Rudy K.
Published: November 2008

Reducing the physical distance among R&D engineers and between R&D and marketing is widely believed to result in more frequent communication, and hence higher product development performance. However, the empirical evidence for the effect of co-location on communication frequency is problematic for two reasons: (1) the evidence often features either little contextual realism or doubtful internal validity, and (2) the analysis does not deal with the statistical problems typical of network data. Our study avoids the first problem by using sequential network data collected from a quasi-experiment at an industrial company that regrouped its R&D teams into a new facility. We avoid the second problem by using Wasserman and Iacobucci's (1988) method for the statistical analysis of sequential network data. Our results show that communication among R&D teams was enhanced after co-locating these teams. Surprisingly, communication frequency between R&D and marketing was not affected by the increased physical distance. This may suggest that business procedures accompanying the relocation prevented a widening gap between R&D and marketing. Alternatively, it may indicate that the effect of co-location depends on the content and medium of the communication flows.
Applying Robust Optimization to Capacity Expansion of One Location in Telecommunications with Demand Uncertainty
Authors: Laguna Manuel
Published: November 2008

The problem of expanding the capacity of a single facility in telecommunications network planning is addressed. This problem can be formulated as a time-dependent knapsack, when relevant information is assumed to be known. We introduce the use of scenarios to model uncertainty in key data. The problem is formulated within the robust optimization framework and solved exactly in two phases. The first phase consists of a dynamic programming recursion and the second one of a shortest path procedure. Experiments show that a large number of scenarios can be handled with this technique, because computational times are more sensitive to the maximum demand across all scenarios than to the number of scenarios considered. A user-interface based on Microsoft Excel is developed as a decision support system for network planners.
Hierarchical Bayes Methods for Multifactor Model Estimation and Portfolio Selection
Authors: Young Martin R. , Lenk Peter J.
Published: November 2008

The factor model is an important construct for both portfolio managers and researchers in modern finance. For practitioners, factor model coefficients are used to guide the construction of optimal portfolios. For academicians, factor model parameters play a fundamental role in explaining equilibrium asset prices and other market phenomena. This paper presents a hierarchical modeling procedure that can substantially improve the accuracy of factor model parameter estimates through incorporation of cross-sectional information. It is shown that this improvement in parameter estimation accuracy translates into substantial improvement in portfolio performance. Expressions are derived that characterize the sensitivity of portfolio performance to parameter estimation error. Evidence with NYSE data suggests that the hierarchical estimation technique leads to superior out-of-sample portfolio performance when compared to alternative estimation approaches.
A Note on Approximating Peak Congestion in Mt/G/∞ Queues with Sinusoidal Arrivals
Authors: Green Linda V. , Kolesar Peter J.
Published: November 2008

We study the Mt /G/∞ queue where customers arrive according to a sinusoidal function λ t = λ + A sin(2πt/T) and the service rate is μ. We show that the expected number of customers in the system during peak congestion can be closely approximated by (λ + A)/μ for service distributions with coefficient of variation between 0 and 1. Motivated by a result derived by Eick, Massey, and Whitt that the time lag of the peak congestion from the peak of the customer arrivals is 1/2μ for models with deterministic service times, we show that the time lag for exponential service times is closely approximated by 1/μ. Based on a cycle length of 24 hours and regardless of the values of other system parameters, these approximations are of the order of 1% accuracy for μ = 1, and the accuracy increases rapidly with increasing μ.
Leasing and Selling: Optimal Marketing Strategies for a Durable Goods Firm
Authors: Desai Preyas , Purohit Devavrat
Published: November 2008

This paper analyzes the problems associated with marketing a durable through leases and sales. Academic research in this area has argued that in a monopolistic environment, leasing dominates selling. Hence, leasing and selling should not co-exist and the firm should concentrate its efforts solely on leasing. We show that the relative profitability of leasing and selling hinges on the rates at which leased and sold units depreciate. In particular, we find that leasing does not dominate selling in all cases; if sold units depreciate at a significantly higher rate than leased units, a monopolistic firm is better off by only selling its product. In addition, we find that if leaded and sold products depreciate at different rates, then the optimal strategy for the firm involves a combination of both leasing and selling. We conclude the paper with an empirical analysis of the depreciation rates of leased and sold units of a popular car model. We find that the depreciation rate of leased cars has been significantly lower than the depreciation rate of sold cars.
Managing New Product Definition in Highly Dynamic Environments
Authors: Bhattacharya Shantanu , Krishnan V. , Mahajan Vijay
Published: November 2008

In highly dynamic environments, characterized by changing customer preferences and uncertainty about competitive products, managing the development of a new product is a complex managerial task. The traditional practice, recommended in the literature, of reaching a sharp definition early in the new product development (NPD) process may not be optimal, desirable or even feasible in such dynamic situations. Under high uncertainty, forcing early finalization of specifications may result in a firm getting locked into an incorrect definition. Based on our study of NPD in the high technology industry, we present a model of an approach called real-time definition, in which a firm adapts its product definition process to the market and competitive environment. Uncertainty in the product definition is resolved through frequent, repeated interactions with customers and using a flexible development process. We find that early definition is optimal only in a limited set of situations. To maximize its anticipated profits, a firm should tune its definition process to the prevailing level of market uncertainty, the marginal value of information obtained from the customer during the NPD process, and its own risk-profile and internal development capabilities. Effects of competition on a firm's definition approach are also examined, and implications for managers of a NPD process are presented using a conceptual framework.
A Multi-Agent Framework for the Coordination and Integration of Information Systems
Authors: Sikora Riyaz , Shaw Michael J.
Published: November 2008

This paper describes a framework for the coordination and integration of information systems. By modeling typical enterprise information systems as consisting of multiple agents with different functionalities, the methodology provides the representational formalism, coordination mechanisms, and control schemes necessary for integrating heterogeneous units of an information system while meeting such performance criteria as overall effectiveness, efficiency, responsiveness, and robustness.

The framework is applied to the development of a manufacturing information system for managing the production processes for making printed circuit boards. Performance results confirm that the system integration framework is important to support complex business processes that involve multiple steps of activities processed by a group of agents across a variety of functionalities.
A Bilevel Model of Taxation and Its Application to Optimal Highway Pricing
Authors: Labbé Martine , Marcotte Patrice , Savard Gilles
Published: November 2008

We consider a bilevel model where the leader wants to maximize revenues from a taxation scheme, while the follower rationally reacts to those tax levels. We focus our attention on the special case of a toll-setting problem defined on a multicommodity transportation network. We show that the general problem is NP-complete, while particular instances are polynomially solvable. Numerical examples are given.