bluuebunny/crossref_metadata_2025 huggingface dataset:
Multinomial Logit Market Share Models: Equilibrium Characteristics and Strategic Implications
Authors: Basuroy Suman , Nguyen Dung
Published: November 2008

We specify and analyze the conditions under which the MNL market share models are appropriate for equilibrium analysis. Our results show that a linear price response function as is often used in empirical research, in conjunction with the typical concavity assumed in a large range of marketing response functions, would yield an interior equilibrium solution. We then consider the optimal reactions on pricing and marketing spending to entry and potential market expansion. In the context of the MNL models, we demonstrate that the entry of a new brand evokes a decrease in the equilibrium prices of the existing brands as a defensive reaction. This is true in both an expanding market as well as a fixed market. However, while new entry into a fixed market would trigger the incumbents to lower the marketing expenditure, we show that firms tend to raise marketing activities as they experience market expansion. Consequently, there exist distinct possibilities that marketing efforts for the existing brands increase in view of entry in an expanding market. Further managerial and marketing implications for endogeneity of the number of firms are explored.
Process Innovation and Learning by Doing in Semiconductor Manufacturing
Authors: Hatch Nile W. , Mowery David C.
Published: November 2008

This paper analyzes the relationship between process innovation and learning by doing in the semiconductor industry where improvements in manufacturing yield are a catalyst for dynamic cost reductions. In contrast to most previous studies of learning by doing, the learning curve is shown here to be the product of deliberate activities intended to improve yields and reduce costs, rather than the incidental byproduct of production volume. Since some of the knowledge acquired through learning by doing during new process development is specific to the production environment where the process is developed, some knowledge is effectively lost when a new process is transferred to manufacturing. We find that dedicated process development facilities, geographic proximity between development and manufacturing facilities, and the duplication of equipment between development and manufacturing facilities are all significant in improving performance in introducing new technologies. Once in manufacturing, new processes are shown to disrupt the ongoing learning activities of existing processes by drawing away scarce engineering resources to “debug” the new processes.
Process Improvement, Quality, and Learning Effects
Authors: Li George , Rajagopalan S.
Published: November 2008

While quality has attracted significant attention in the past two decades, the debate is still on as to whether a firm should aim for zero defects or base its quality decisions on cost-benefit trade-offs. The continuous improvement advocates generally eschew the cost trade-off approach, but U.S. firms, after spending substantial sums on quality-related activities in the 1980s, appear to be focusing again on cost trade-offs and measures such as return on quality. This paper provides analytical support for the continuous improvement argument while relying on a cost trade-off analysis. We present a dynamic model of a monopolist making decisions on price, production, process improvement, and quality assurance efforts. The model is comprehensive and captures the effects of autonomous and induced learning on both productivity and quality and incorporates quality related costs in detail. Using this model, we show that quality improves over time, while process improvement effort and quality assurance effort decrease over time. In fact, as anecdotal and empirical evidence suggests, process improvement and quality assurance effort is high when quality level is low, and vice-versa. The optimal production rate is increasing and the optimal price is decreasing over time. We also provide valuable insights into the impact of changes in key parameters such as interest rates on production, price, process improvement effort, and quality assurance effort.
Logit Demand Estimation Under Competitive Pricing Behavior: An Equilibrium Framework
Authors: Besanko David , Gupta Sachin , Jain Dipak
Published: November 2008

Discrete choice models of demand have typically been estimated assuming that prices are exogenous. Since unobservable (to the researcher) product attributes, such as coupon availability, may impact consumer utility as well as price setting by firms, we treat prices as endogenous. Specifically, prices are assumed to be the equilibrium outcomes of Nash competition among manufacturers and retailers. To empirically validate the assumptions, we estimate logit demand systems jointly with equilibrium pricing equations for two product categories using retail scanner data and cost data on factor prices. In each category, we find statistical evidence of price endogeneity. We also find that the estimates of the price response parameter and the brand-specific constants are generally biased downward when the endogeneity of prices is ignored. Our framework provides explicit estimates of the value created by a brand, i.e., the difference between consumers' willingness to pay for a brand and its cost of production. We develop theoretical propositions about the relationship between value creation and competitive advantage for logit demand systems and use our empirical results to illustrate how firms use alternative value creation strategies to accomplish competitive advantage.
Knowledge Driven Quality Improvement
Authors: Mukherjee Amit Shankar , Lapré Michael A. , Van Wassenhove Luk N.
Published: November 2008

Little is known about the processes that make TQM effective. Why are some quality improvement projects more effective than others? We argue that TQM processes affect the way people create new knowledge, which in turn determines organizational effectiveness. We explore this by studying 62 quality improvement projects undertaken in one factory over a decade. Using a factor analysis we identify three learning constructs that characterize the learning process: scope, conceptual learning, and operational learning. We use OLS regressions to study the impact of these learning constructs on project performance. Conceptual and operational learning are found to play a crucial role in achieving goals, creating new technological knowledge, and changing factory personnel's attention. Contrary to the common practice of relying on operational learning, we suggest the application of conceptual learning as well, particularly if the technology is poorly understood. It facilitates the codification of knowledge, which enhances its dissemination for both present and future use.
Dynamic Asset Allocation in a Mean-Variance Framework
Authors: Bajeux-Besnainou Isabelle , Portait Roland
Published: November 2008

The aim of this article is to analyze the portfolio strategies that are mean-variance efficient when continuous rebalancing is allowed between the current date (0) and the horizon (T). Under very general assumptions, when a zero-coupon bond of maturity T exists, the dynamic efficient frontier is a straight line, the slope of which is explicitly characterized. Every dynamic mean-variance efficient strategy can be viewed as buy and hold combinations of two funds: the zero-coupon bond of maturity T and a continuously rebalanced portfolio. An appropriate dynamic strategy defining the latter is explicitly derived for two particular price processes and comparisons of the Efficient Frontiers (Static versus Dynamic) are provided in these cases.
Vehicle Scheduling in Public Transit and Lagrangean Pricing
Authors: Löbel Andreas
Published: November 2008

This paper investigates the solution of the linear programming (LP) relaxation of the multi-commodity flow formulation of the multiple-depot vehicle scheduling problems arising in public mass transit. We develop a column generation technique that makes it possible to solve the huge linear programs that come up there. The technique, which we call Lagrangean pricing, is based on two different Lagrangean relaxations.

We describe in detail the basic ingredients of our approach and give computational results for large-scale test data (with up to 70 million variables) from three German public transportation companies. Because of these results, we propose Lagrangean pricing as one of the basic ingredients of an effective method to solve multiple-depot vehicle scheduling problems to proven optimality.
Echelon Reorder Points, Installation Reorder Points, and the Value of Centralized Demand Information
Authors: Chen Fangruo
Published: November 2008

We consider a serial inventory system with N stages. The material flows from an outside supplier to stage N, then to stage N − 1, etc., and finally to stage 1 where random customer demand arises. Each stage replenishes a stage-specific inventory position according to a stage-specific reorder point/order quantity policy. Two variations of this policy are considered. One is based on echelon stock, and the other installation stock. The former requires centralized demand information, while the latter does not. The relative cost difference between the two policies is called the value of centralized demand information. For fixed order quantities, we develop efficient algorithms for computing both the optimal echelon reorder points and the optimal installation reorder points. These algorithms enable us to conduct an extensive computational study to assess the value of centralized demand information and to understand how this value depends on several key system parameters, i.e., the number of stages, leadtimes, batch sizes, demand variability, and the desired level of customer service.
Combining Expert Judgment by Hierarchical Modeling: An Application to Physician Staffing
Authors: Lipscomb Joseph , Parmigiani Giovanni , Hasselblad Vic
Published: November 2008

Expert panels are playing an increasingly important role in U.S. health policy decision making. A fundamental issue in these applications is how to synthesize the judgments of individual experts into a group judgment. In this paper we propose an approach to synthesis based on Bayesian hierarchical models, and apply it to the problem of determining physician staffing at medical centers operated by the U.S. Department of Veteran Affairs (VA).

Our starting point is the supra-Bayesian approach to synthesis, whose principal motivation in the present context is to generate an estimate of the uncertainty associated with a panel's evaluation of the number of physicians required under specified conditions. Hierarchical models are particularly natural in this context since variability in the experts' judgments results in part from heterogeneity in their baseline experiences at different VA medical centers.

We derive alternative hierarchical Bayes synthesis distributions for the number of physicians required to handle the (service-mix specific) daily workload in internal medicine at a given VA medical center (VAMC). The analysis appears to be the first to provide a statistical treatment of expert judgment processes for evaluating the appropriate use of resources in health care. Also, while hierarchical models are well established, their application to the synthesis of expert judgment is novel.
An Approximate Method for Sampling Correlated Random Variables from Partially-Specified Distributions
Authors: Lurie Philip M. , Goldberg Matthew S.
Published: November 2008

This paper presents an algorithm for generating correlated vectors of random numbers. The user need not fully specify the joint distribution function; instead, the user “partially specifies” only the marginal distributions and the correlation matrix. The algorithm may be applied to any set of continuous, strictly increasing distribution functions; the marginal distributions need not all be of the same functional form. The correlation matrix is first checked for mathematical consistency (positive semi-definiteness), and adjusted if necessary. Then the correlated random vectors are generated using a combination of Cholesky decomposition and Gauss-Newton iteration. Applications are made to cost analysis, where correlations are often present between cost elements in a work breakdown structure.
New Bounds and Heuristics for (Q, r) Policies
Authors: Gallego Guillermo
Published: November 2008

To clarify the impact of demand variability on single item stochastic inventory systems with setup costs, we subsume the distributional information of the lead time demand into its mean and variance and solve the resulting problem against the worst possible distribution in this class. For (Q, r) policies we obtain in closed form a distribution-free solution for Q and r, and upper bounds on the optimal long run average cost and on the optimal batch size. As a byproduct we develop a robust, distribution-free, batch size heuristic that causes a relative cost increase of no more than 6.07%. In addition, when the newsvendor cost is known, we obtain sharper lower and upper bounds on the long run average cost. These bounds clarify, in an exceedingly simple way, the cost impact of fixed setup costs, demand variability, and constraints on the batch size. We illustrate our bounds and heuristics on problems with Poisson and Compound Poisson demands.
Stability and Chaos in Input Pricing for a Service Facility with Adaptive Customer Response to Congestion
Authors: Rump Christopher M. , Stidham Shaler
Published: November 2008

We consider the stability of the equilibrium arrival rate and equilibrium admission price at a service facility, using a generalization of an input-pricing model introduced by Dewan and Mendelson and further examined by Stidham. At the equilibrium, the marginal value of service equals the admission price, that is, the sum of the admission fee and the expected delay cost. Stability means (roughly) that the system returns to the equilibrium after a perturbation, assuming the customers base their join/balk decisions on previous prices. We extend the discrete-time, dynamic-system pricing model of Stidham to allow adaptive expectations in which customers predict the future price based on a convex combination of the current price and the previous prediction. We show that this can lead to chaotic behavior when the equilibrium is unstable. That is, the price and arrival rate can follow aperiodic orbits, which appear to be completely random. Our results suggest an alternative explanation for observed variations in the mean arrival rate to a queueing system, which are often modeled by means of a random exogenous (e.g., Markovian) environment process.
Guided Local Search with Shifting Bottleneck for Job Shop Scheduling
Authors: Balas Egon , Vazacopoulos Alkis
Published: November 2008

Many recently developed local search procedures for job shop scheduling use interchange of operations, embedded in a simulated annealing or tabu search framework. We develop a new variable depth search procedure, GLS (Guided Local Search), based on an interchange scheme and using the new concept of neighborhood trees. Structural properties of the neighborhood are used to guide the search in promising directions. While this procedure competes successfully with others even as a stand-alone, a hybrid procedure that embeds GLS into a Shifting Bottleneck framework and takes advantage of the differences between the two neighborhood structures proves to be particularly efficient. We report extensive computational testing on all the problems available from the literature.
A Mixed Integer Programming Model for Solving a Layout Problem in the Fashion Industry
Authors: Degraeve Zeger , Vandebroek Martina
Published: November 2008

The cutting operation in the high fashion clothing industry essentially involves putting several layers of cloth on a long cutting table and fixing templates of the parts of several articles on top of the stack before the actual cutting can be initiated. This is a very time-consuming task giving raise to high setup costs in addition to waste production resulting from the cutting process. Total production costs can then be optimized by minimizing the number of these setups while at the same time producing little or no waste. In this paper a mixed integer programming model is proposed that searches for an optimal set of cutting patterns, each giving a combination of articles to be cut in one operation, and corresponding stack heights.
Adaptive Memory Tabu Search for Binary Quadratic Programs
Authors: Glover Fred , Kochenberger Gary A. , Alidaee Bahram
Published: November 2008

Recent studies have demonstrated the effectiveness of applying adaptive memory tabu search procedures to combinatorial optimization problems. In this paper we describe the development and use of such an approach to solve binary quadratic programs. Computational experience is reported, showing that the approach optimally solves the most difficult problems reported in the literature. For challenging problems of limited size, which are capable of being approached by exact procedures, we find optimal solutions considerably faster than the best reported exact method. Moreover, we demonstrate that our approach is significantly more efficient and yields better solutions than the best heuristic method reported to date. Finally, we give outcomes for larger problems that are considerably more challenging than any currently reported in the literature.
Approval Voting, Borda Winners, and Condorcet Winners: Evidence from Seven Elections
Authors: Regenwetter Michel , Grofman Bernard
Published: November 2008

We analyze 10 three-candidate elections (and mock elections) conducted under approval voting (AV) using a method developed by Falmagne and Regenwetter (1996) that allows us to construct a distribution of rank orders from subset choice data. The elections were held by the Institute of Management Science, the Mathematical Association of America, several professional organizations in Britain, and the Institute of Electrical and Electronics Engineers. Seven of the 10 elections satisfy the conditions under which the Falmagne-Regenwetter method is suitable. For these elections we recreate possible underlying preferences of the electorate. On the basis of these distributions of preferences we find strong evidence that AV would have selected Condorcet winners when they exist and would have always selected the Borda winner. Thus, we find that AV is not just simple to use, but also gives rise to outcomes that well reflect voter preferences.

Our results also have an important implication for the general study of social choice processes. They suggest that transitive majority orderings may be expected in real-world settings more often then the formal social choice literature suggests. In six out of seven data sets we find social welfare orders; only one data set generates cycles anywhere in the solution space.
Staffing and Allocation of Workers in an Administrative Office
Authors: Lewis Gordon H. , Srinivasan Ashok , Subrahmanian Eswaran
Published: November 2008

The world of work is increasingly characterized by processing of records, forms, or cases. This processing is usually organized as a set of interdependent tasks within an administrative office. A major issue facing such administrative offices is how they should be organized to maximize productivity when short-term reassignment of workers is difficult, costly, or severely restricted. The present work grew out of a study conducted at a County Assistance Office in Western Pennsylvania and addresses three important productivity questions in organizational productivity: (1) How should a given number of workers be allocated across related tasks, (2) will the arrangement that seems best for productivity increase or decrease equity within the office, and (3) what is the optimal size of an office?

To answer question 1, we model the administrative office as a closed queueing network. Thus modeled, the problem has an optimal allocation of workers, and we propose an efficient method for finding it. In response to question 2, we show (1) that for offices of a fixed size, the allocation of workers that maximizes throughput also maximizes equity, and (2) that across offices of different sizes, throughput per worker is not monotonicly related to equity. Changes in the size of the office that improve productivity may have lower equity; conversely, changes in the size of the office that improve equity may have lower productivity. Finally, in response to question 3, we show that the previous results can be used to determine the optimal office size in terms of throughput. This result has relevance for situations in which there are multiple offices of the same type.

To the extent that worker satisfaction is related to equity, these results imply that managers may have to choose between worker satisfaction and output in setting the size of the office, but for offices of a fixed size, the allocation that maximizes output will also maximize worker satisfaction.
Simulating Weights Restrictions in Data Envelopment Analysis by Means of Unobserved DMUs
Authors: Thanassoulis E. , Allen R.
Published: November 2008

Data envelopment analysis (DEA) is a method for assessing the comparative efficiencies of decision making units (e.g., banks and schools) by relating their output to their input levels. Restrictions are often imposed in these assessments to reflect prior judgments on the values of input and/or output variables. This paper introduces a new approach to capturing and using value judgments in DEA, based on unobserved Decision Making Units. In so doing, it opens up a whole new approach for reflecting value judgments in DEA assessments, which can offer advantages in certain situations.
Similarity Judgments in Choice Under Uncertainty: A Reinterpretation of the Predictions of Regret Theory
Authors: Leland Jonathan W.
Published: November 2008

The Regret theory of Loomes and Sugden (1982) predicts choice anomalies implied by other alternatives to expected utility (e.g., violations of the independence axiom). It also makes unique and controversial predictions regarding the rational violation of stochastic dominance and invariance. All these predictions depend critically on assumptions regarding the statistical independence or dependence of the available alternatives. None of the predictions depend on the framing or representation of the alternatives. Leland (1994) shows that a model of choice based on similarity judgments predicts choices implied by Regret theory. In contrast to Regret theory, however, these predictions depend critically on the way the choices are framed and not on the dependence or independence of the alternatives. This paper presents experimental results indicating that the frequencies with which violations of independence, dominance, and invariance occur are, in most cases, insensitive to the statistical dependence or independence of the alternatives but sensitive to the way the choices are presented. These findings support the hypothesis that such behaviors arise as a consequence of reliance upon similarity judgments.
Optimal Batch Provisioning to Customers Subject to a Delay-Limit
Authors: Berg Menachem , van der Duyn Schouten Frank , Jansen Jorg
Published: November 2008

This work deals with batch provisioning and order aggregation. Two examples are: (i) a manufacturer that has to deliver items to customers in a remote destination, and (ii) a company that provides repair and replacement service to its clients. In both cases the remoteness of customers suggests order aggregation—a batch delivery in the first example, and a batch-visits journey in the other; the alternative is to provide individual services to customers. A key element is a contractual obligation of the company to provide service within an agreed delay-limit, and in that view the main decision problem is to determine the moments at which a batch service should be executed. That decision would depend on: (random) demand-arrival patterns, the costs associated with the two service modes (batch and individual), as well as the model used to describe operating conditions.

This paper proposes and investigates several service-provision policies, with a simple enough structure to make them appealing for real-life implementation. Optimal service-provision procedures are obtained for these policies, minimizing the long-run expected cost per unit of time. The optimal costs of the proposed policies are compared and their relative performance is evaluated with respect to the global minimal cost (of the optimal policy) on one hand, and basic policies that employ either only batch or only individual services on the other hand. Finally, a range of model generalizations of interest is presented and the relationship of the problem here to broader issues is discussed.
An Exact Algorithm for the Resource-Constrained Project Scheduling Problem Based on a New Mathematical Formulation
Authors: Mingozzi Aristide , Maniezzo Vittorio , Ricciardelli Salvatore , Bianco Lucio
Published: November 2008

In this paper we consider the Project Scheduling Problem with resource constraints, where the objective is to minimize the project makespan. We present a new 0-1 linear programming formulation of the problem that requires an exponential number of variables, corresponding to all feasible subsets of activities that can be simultaneously executed without violating resource or precedence constraints. Different relaxations of the above formulation are used to derive new lower bounds, which dominate the value of the longest path on the precedence graph and are tighter than the bound proposed by Stinson et al. (1978).

A tree search algorithm, based on the above formulation, that uses new lower bounds and dominance criteria is also presented. Computational results indicate that the exact algorithm can solve hard instances that cannot be solved by the best algorithms reported in the literature.
Modifying Customer Expectations of Price Decreases for a Durable Product
Authors: Balachander Subramanian , Srinivasan Kannan
Published: November 2008

We study the introductory signalling strategy for a durable product that faces optimistic expectations among customers about price declines over time. The firm introducing the product knows that experiential learning is low for the product. However, customers, being uncertain about the extent of experiential learning, assign a nonzero probability that the firm's new product will enjoy a high cost reduction with cumulative experience. The optimistic expectations of customers reduce their willingness to pay a high price at the product's introduction while predisposing them to buying later. The challenge facing the low-experience firm is to choose an introductory strategy that will credibly convey the low experience-curve effect to customers. We use the sequential equilibrium concept in a game-theoretic framework to identify the firm's signalling strategy. We identify the unique separating equilibrium of the game after refining the set of separating equilibria. We demonstrate that a high introductory price credibly signals the low experiential learning to customers. We also show that signalling causes an artificial learning-curve effect.
Note: How Does Product Proliferation Affect Responsiveness?
Authors: Gupta Diwakar , Srinivasan Mandyam M.
Published: November 2008

In this note we consider some strategies that a manufacturing firm may use to deal with an increase in the variety of products it offers. We indicate how alternate strategies for dealing with product proliferation impact the firm's responsiveness, measured in terms of average production lead time and average work-in-process inventory. Focusing on the make-to-order environment and using queueing models, we derive conditions under which an increase in product variety can improve both individual product performance as well as system performance, thus contradicting a common belief that a greater degree of focus and greater responsiveness go hand in hand. These queueing models provide operations managers analytical tools for evaluating alternate strategies for coping with product proliferation.
Toward a Theory of Continuous Improvement and the Learning Curve
Authors: Zangwill Willard I. , Kantor Paul B.
Published: November 2008

Continuous improvement (CI) unceasingly strives to improve the performance of production and service firms. The learning curve (LC) provides1988 Department of Industrial Engineering and a means to observe and track that improvement. At present, however, the concepts of CI are abstract and imprecise and the rationale underpinning the LC is obscure. For managers to improve processes effectively, they need a more scientific theory of CI and the LC. This paper begins to develop such a theory. Our approach is based on learning cycles, that is, in each period management takes an action to improve the process, observes the results, and thereby learns how to improve the process further over time. This analysis suggests a differential equation that not only characterizes continuous improvement but also reveals how learning might occur in the learning curve. This differential equation might help management to evaluate the effectiveness of various procedures and to improve and enhance industrial processes more quickly.
On Pooling in Queueing Networks
Authors: Mandelbaum Avishai , Reiman Martin I.
Published: November 2008

We view each station in a Jackson network as a queue of tasks, of a particular type, which are to be processed by the associated specialized server. A complete pooling of queues, into a single queue, and servers, into a single server, gives rise to an M/PH/1 queue, where the server is flexible in the sense that it processes all tasks. We assess the value of complete pooling by comparing the steady-state mean sojourn times of these two systems. The main insight from our analysis is that care must be used in pooling. Sometimes pooling helps, sometimes it hurts, and its effect (good or bad) can be unbounded. Also discussed briefly are alternative pooling scenarios, for example complete pooling of only queues which results in an M/PH/S system, or partial pooling which can be devastating enough to turn a stable Jackson network into an unstable Bramson network. We conclude with some possible future research directions.
Strategic Growth Options
Authors: Kulatilaka Nalin , Perotti Enrico C.
Published: November 2008

We provide a strategic rationale for growth options under uncertainty and imperfect competition. In a market with strategic competition, investment confers a greater capability to take advantage of future growth opportunities. This strategic advantage leads to the capture of a greater share of the market, either by dissuading entry or by inducing competitors to “make room” for the stronger competitor. As a result of this strategic effect, payoffs are in a rough sense more convex than in the case of no investment in a growth option. When the strategic advantage is strong, increased uncertainty encourages investment in growth options: higher uncertainty means more opportunity rather than simply larger risk. If the strategic effect is weak, the reverse is true. On the other hand, an increase in systematic risk discourages the acquisition of growth options. Our results contradict the view that volatility is a strong disincentive for investment.
Evaluating Environmental Investments: A Real Options Approach
Authors: Cortazar Gonzalo , Schwartz Eduardo S. , Salinas Marcelo
Published: November 2008

The paper presents a model that determines when (at which output price level) it is optimum for a firm to invest in environmental technologies and which are the main parameters that affect this decision. Our analysis shows that firms require high output price levels to be induced to invest in environmental technologies, because they optimally would not want to commit to a heavy irreversible investment that could turn out to be unprofitable in the event of a price fall. A comparative static analysis predicts that firms in industries with high output price volatility would be more reluctant to invest in environmental protection technologies and would be more willing to operate at low output levels (thus attaining low emission levels). Increases in the interest rate would also reduce optimal environmental investment levels.
When Does Forced Idle Time Improve Performance in Polling Models?
Authors: Cooper Robert B. , Niu Shun-Chen , Srinivasan Mandyam M.
Published: November 2008

Sarkar and Zangwill (1991) showed by numerical examples that reduction in setup times can, surprisingly, actually increase work in process in some cyclic production systems (that is, reduction in switchover times can increase waiting times in some polling models). We present, for polling models with exhaustive and gated service disciplines, some explicit formulas that provide additional insight and characterization of this anomaly. More specifically, we show that, for both of these models, there exist simple formulas that define for each queue a critical value z* of the mean total setup time z per cycle such that, if z z*, then the expected waiting time at that queue will be minimized if the server is forced to idle for a constant length of time z* − z every cycle; also, for the symmetric polling model, we give a simple explicit formula for the expected waiting time and the critical value z* that minimizes it.
Validation in Simulation: Various Positions in the Philosophy of Science
Authors: Kleindorfer George B. , O'Neill Liam , Ganeshan Ram
Published: November 2008

There is still considerable doubt and even anxiety among simulation modelers as to what the methodologically correct guidelines or procedures for validating simulation models should be. Epistemically, the approaches one finds in the simulation literature run the gamut from objectivist to relativist with shades in between. At present in the philosophy of science, there appears to be a convergence toward a nonalgorithmic but discursive and nonrelativistic view of the argumentation involved in warranting scientific theorizing. The present paper attempts to give a description of the various philosophical positions as well as to summarize their problems and the kinds of evidentiary arguments they would each allow in arriving at defensible simulation models. From the debate, we attempt to set out a perspective that frees the practioner to pursue a varied set of approaches to validation with a diminished burden of methodological anxiety. Reciprocally this perspective does not let the modeler off of the hook but rather converts the validation problem into an ethical problem in which the practitioner must responsibly and professionally argue for the warrant of the model.
Quality and Competition
Authors: Banker Rajiv D. , Khosla Inder , Sinha Kingshuk K.
Published: November 2008

In recent years, the practitioner literature in operations management has seen a dramatic surge in articles on quality management. It reflects the increased emphasis on quality by U.S. firms, which has been attributed largely to increased competition faced by them. The question of how quality is influenced by competitive intensity, however, has not received much attention, either in the practitioner or the academic research literatures. The notion of competitive intensity itself has not been defined precisely. In this paper, we develop formal models of oligopolistic competition to investigate whether equilibrium levels of quality increase as competition intensifies. We consider three different competitive settings: (i) asymmetric duopolistic competition where the dominant firm's intrinsic demand potential decreases; (ii) a symmetric duopoly where the firms are precluded from cooperating in setting quality levels; and (iii) symmetric oligopolistic competition where the number of firms increases. We find that the relation between equilibrium quality and competitive intensity depends on what is understood by increased competition and, in addition, the relation is contingent on the values of parameters describing the cost and demand structure for the industry.
Cross-Cultural Differences in Risk Perception, but Cross-Cultural Similarities in Attitudes Towards Perceived Risk
Authors: Weber Elke U. , Hsee Christopher
Published: November 2008

In this study, respondents from the P.R.C., U.S.A., Germany, and Poland were found to differ in risk preference, as measured by buying prices for risky financial options. Chinese respondents were significantly less risk-averse in their pricing than Americans when risk preference was assessed in the traditional expected-utility framework. However, these apparent differences in risk preference were associated primarily with cultural differences in the perception of the risk of the financial options rather than with cultural differences in attitude towards perceived risk. In all cultures, an equal proportion (the majority) of respondents was willing to pay more for options perceived as less risky, i.e., were perceived-risk averse. These results are most naturally explained within a risk-return conceptualization of risky choice. They have practical implications for cross-cultural negotiation and commerce by suggesting the locus of cultural differences in risky choice that may allow for the creation of joint gains.
JIT Manufacturing: A Survey of Implementations in Small and Large U.S. Manufacturers
Authors: White Richard E. , Pearson John N. , Wilson Jeffrey R.
Published: November 2008

Since the early 1980s, the diffusion of Just-In-Time (JIT) manufacturing from Japanese manufacturers to U.S. manufacturers has progressed at an accelerated rate. At this stage of the diffusion process, JIT implementations are more common and more advanced in large U.S. manufacturers than in small; consequently, U.S. businessmen’s understanding of issues associated with JIT implementations in large manufacturers is more developed than that of small manufacturers. When small manufacturers represent about 96 percent of all U.S. manufacturers, investigation of JIT implementations in small, as well as large, manufacturers is warranted.

This survey study investigates JIT implementation differences between small and large U.S. manufacturers. Ten management practices that constitute the JIT concept are used to examine implementation of JIT manufacturing systems. Odds ratio were constructed to determine if an association exists between implemented versus not implemented and manufacturer size for each JIT practice. Ten changes in performance attributed to JIT implementation are also assessed and examined in the study. Logistic regression models are used to examine the relationships between implementation status of each of the JIT practices and of each of the changes in performance in small and large manufacturers. The results of the study show that the frequencies of the 10 JIT management practices implemented differ between the two groups of manufacturer size, and an association exists between the JIT practices implemented and manufacturer size. Moreover, the changes in performance attributed to JIT implementation vary, depending on implementation status of specific JIT management practices and manufacturer size.
Value of Information in Capacitated Supply Chains
Authors: Gavirneni Srinagesh , Kapuscinski Roman , Tayur Sridhar
Published: November 2008

We incorporate information flow between a supplier and a retailer in a two-echelon model that captures the capacitated setting of a typical supply chain. We consider three situations: (1) a traditional model where there is no information to the supplier prior to a demand to him except for past data; (2) the supplier knows the (s, S) policy used by the retailer as well as the end-item demand distribution; and (3) the supplier has full information about the state of the retailer. Order up-to policies continue to be optimal for models with information flow for the finite horizon, the infinite horizon discounted and the infinite horizon average cost cases. Study of these three models enables us to understand the relationships between capacity, inventory, and information at the supplier level, as well as how they are affected by the retailer’s (S − s) values and end-item demand distribution. We estimate the savings at the supplier due to information flow and study when information is most beneficial.
Measures of Effectiveness for Governmental Organizations
Authors: Gawande Kishore , Wheeler Timothy
Published: November 2008

For organizations whose objective is not necessarily the maximization of a financial quantity, there is little written in the economics and management literature about methods that quantify their effectiveness. Potential users of such methodologies are typically governmental organizations and agencies to whom Congress allocates funding periodically, but may also include many nonprofit organizations. Such research is importantly needed because government is no longer making outlay allocations on a merely historical basis, but is using as a criterion how effectively an organization uses its resources in meeting its objectives. In this paper we analyze the Maritime Safety Program of the U.S. Coast Guard (USCG), which is responsible for monitoring the quality of vessels that sail in U.S. waters, and present measures of effectiveness (MOEs) for the Program. We do this at two levels of activity: at an overall program level (Level I) and at a component activity level (Level II). Poisson models are used to construct the MOEs using data on maritime casualties (accidents) between 1990–1993 from the real-time Marine Safety Management System (MSMS) database maintained by the Coast Guard. A feature of the empirical methodology is the Bayesian imputation of missing data. The MOEs constructed here have at least four important uses. First, as the name suggests, they perform the function that financial quantities such as returns on equity or returns on sales perform for private-sector organizations—that is, they are indicators of efficiency. Second, they can be used as inputs into allocative decisions within the organization. For example, the Level II MOEs can be used as inputs into a programming problem that determines the optimal allocation of resources among component activities. Third, internal performance evaluation across USCG Programs or across Port Units (called Marine Safety Offices) can be based on their respective Level I MOEs. Fourth, and possibly the most important long-run consideration, MOEs provide the basis for better regulation by the government. Without MOEs the nature of regulation is probably suboptimal. By adopting these MOEs as criteria, it will be easier for the government to redesign those aspects of its regulation of the Coast Guard which curtail incentives.
On the Effects of Downstream Entry
Authors: Tyagi Rajeev K.
Published: November 2008

We study the effects of entry in a downstream market where firms (e.g., Compaq and IBM; CVS and Safeway) buy an input (e.g., microprocessor, grocery items) from an upstream supplier (e.g., Intel, Procter & Gamble) and sell their output to consumers. We show demand conditions where, contrary to conventional wisdom, entry of a new downstream firm lowers the downstream-market output and increases the consumer price. Thus consumers may be better off with fewer sellers in such markets. We also show that this entry may cause the profit of each incumbent downstream firm to: (i) remain unchanged; (ii) decrease; or (iii) even increase. Also, for a class of widely used demand conditions, the supplier’s optimal price is shown invariant to the entry/exit of its downstream buyer firms. We classify all possible effects of downstream entry in terms of fundamental market demand conditions.
Fast Approximation Methods for Sales Force Deployment
Authors: Drexl Andreas , Haase Knut
Published: November 2008

Sales force deployment involves the simultaneous resolution of four interrelated subproblems: sales force sizing, salesman location, sales territory alignment, and sales resource allocation. The first subproblem deals with selecting the appropriate number of salesman. The salesman location aspect of the problem involves determining the location of each salesman in one sales coverage unit. Sales territory alignment may be viewed as the problem of grouping sales coverage units into larger geographic clusters called sales territories. Sales resource allocation refers to the problem of allocating scarce salesman time to the aligned sales coverage units. All four subproblems have to be resolved in order to maximize profit of the selling organization. In this paper a novel nonlinear mixed-integer programming model is formulated which covers all four subproblems simultaneously. For the solution of the model we present approximation methods capable of solving large-scale, real-world instances. The methods, which provide lower bounds for the optimal objective function value, are benchmarked against upper bounds. On average the solution gap, i.e., the difference between upper and lower bounds, is about 3%. Furthermore, we show how the methods can be used to analyze various problem settings of practical relevance. Finally, an application in the beverage industry is presented.
A General Additive Data Perturbation Method for Database Security
Authors: Muralidhar Krishnamurty , Parsa Rahul , Sarathy Rathindra
Published: November 2008

The security of organizational databases has received considerable attention in the literature in recent years. This can be attributed to a simultaneous increase in the amount of data being stored in databases, the analysis of such data, and the desire to protect confidential data. Data perturbation methods are often used to protect confidential, numerical data from unauthorized queries while providing maximum access and accurate information to legitimate queries. To provide accurate information, it is desirable that perturbation does not result in a change in relationships between attributes. In the presence of nonconfidential attributes, existing methods will result in such a change. This study describes a new method (General Additive Data Perturbation) that does not change relationships between attributes. All existing methods of additive data perturbation are shown to be special cases of this method. When the database has a multivariate normal distribution, the new method provides maximum security and minimum bias. For nonnormal databases, the new method provides better security and bias performance than the multiplicative data perturbation method.
Broadly Decreasing Risk Aversion
Authors: Gelles Gregory M. , Mitchell Douglas W.
Published: November 2008

This paper considers decision-making in the presence of two additive risk sources, with no restrictions on the relation between the two risks. A utility function is said to exhibit broad DARA if and only if a rise in wealth always decreases the magnitude of the risk premium for one of the risks vis-a-vis the other. A condition on utility functions giving this property is derived: utility must be of the linear plus exponential form. It is shown that certain problems involving portfolios and risk-averse firms give unambiguous comparative statics if and only if utility exhibits broad DARA.