bluuebunny/crossref_metadata_2025_split huggingface dataset:
Some Guidelines and Guarantees for Common Random Numbers
Authors: Glasserman Paul , Yao David D. 
Published: November 2008

Common random numbers (CRN) is a widely-used technique for reducing variance in comparing stochastic systems through simulation. Its popularity derives from its intuitive appeal and ease of implementation. However, though CRN has been observed to work well with a broad range of models, the class of systems for which it is provably advantageous has remained rather limited. This paper has two purposes: We first discuss the effectiveness and optimality of CRN in a general setting, stressing the roles played by monotonicity and continuity properties. We then present specific, new classes of systems and comparisons for which CRN is beneficial and even optimal. Our conclusions for these systems are largely consistent with simulation practice and lend further theoretical support to folklore. Our results differ from those of previous analyses primarily because we put conditions on the timing of events, rather than the sequence of states, in a discrete-event simulation. We formulate our results in three settings corresponding to three applications of CRN: distributional comparisons, structural comparisons, and sensitivity analysis. In each case, we make use of conditions that simultaneously ensure monotonicity and continuity in the timing of events. These properties are established through explicit recursions for event epochs in terms of increasing, continuous functions.
An Empirical Investigation of Advertising Strategies in a Dynamic Duopoly
Authors: Chintagunta Pradeep K. , Vilcassim Naufel J. 
Published: November 2008

The equilibrium profit-maximizing advertising policies of firms operating in a dynamic duopoly are derived by linking in a single framework the econometric estimation of the market response function and the technique of differential games that characterizes dynamic competitive behavior. We use the Lanchester model of combat to represent the system dynamics that capture the competitive shifts due to investments in advertising by the two market rivals. We determine the equilibrium advertising levels using both closed- and open-loop policies. We also compare these equilibrium advertising policies for each firm to those obtained using an optimal control theory formulation wherein the advertising spending levels of the rival are assumed to be known. The empirical results obtained by analyzing the advertising rivalry between Coke and Pepsi for the period 1968–1981 under the above three alternative spending policies provide some interesting insights into the nature of competition between these two market rivals. A significant contribution of this paper is to extend the existing literature on advertising competition by integrating theoretical and empirical analyses.
The Analysis of Activity Networks Under Generalized Precedence Relations (GPRs)
Authors: Elmaghraby Salah E. , Kamburowski Jerzy 
Published: November 2008

We present a model for activity networks under generalized precedence relations (GPRs), discuss its temporal analysis and the issues that may arise relative to inconsistency among the specified relations and the activity durations. We also give more precise definition to the concept of criticality of an activity, and introduce the new concept of flexibility of an activity which is akin to the traditional concept of activity floats in regular CPM, with the latter taking on different meaning from its common interpretation in standard CPM. Issues of optimization are raised when one assumes, for each activity, a piecewise-linear time-cost function that permits positive and negative deviations from its least-cost duration between specified lower and upper bounds on that duration. We seek the optimal activity durations subject to the specified GPRs and a given due date λ. We also seek the construction of the complete project duration-cost function between the project minimum duration and its least-cost duration when the due date λ is interpreted, first, as a “deadline” and, second, as a “target date” with rewards for early, and penalties for late completion. The relations between the problems posed and the uncapacitated minimum cost flow problems are revealed and are utilized in the algorithmic solution of the problems.
The Impact of Perceived Environmental Uncertainty and Perceived Agent Effectiveness on the Composition of Compensation Contracts
Authors: Umanath Narayan S. , Ray Manash R. , Campbell Terry L. 
Published: November 2008

Recently, a stream of theoretical development concerning the design of optimal compensation plans has emerged in the marketing literature. Little empirical work has been done so far to validate the theoretical predictions. The findings from the few field studies are equivocal and conflicting which we ascribe to failure to account for the major assumptions underlying the theoretical predictions. We argue that, in order to enhance the rigor of ‘theory testing’, the field studies must be complemented by laboratory experiments where the conditions stipulated by the assumptions of the theory can be systematically imposed and/or relaxed. This should help in the reconciliation of the differences found in the field studies. The experiment reported in this paper is a first step towards filling this void in the empirical research in this area. Here, we assess the impact of perceived environmental uncertainty and perceived agent effectiveness on the magnitude (total pay) and composition (salary-incentive mix) of employment compensation. The hypotheses stem from propositions analytically derived by Basu, Lal, Srinivasan, and Staelin (1985) and Lal and Srinivasan (1988). The insurance industry middle management compensation problem served as the experimental context. The results of the experiment ratified the hypothesis that an increase in perceived agent effectiveness leads to award of compensation contracts of larger total expected value and a larger proportion of performance-contingent pay. However, the hypothesis that an increase in perceived environmental uncertainty prompts the principal to award compensation contracts of smaller total expected value and a smaller proportion of performance-contingent pay was rejected. We discuss possible alternative explanations for the conflicting results associated with the uncertainty variable and identify future research opportunities in this area.
Heuristics for Pricing and Positioning a Product-Line Using Conjoint and Cost Data
Authors: Dobson Gregory , Kalish Shlomo 
Published: November 2008

Designing and pricing a product-line is the very essence of every business. In recent years quantitative methods to assist managers in this task have been gaining in popularity. Conjoint analysis is already widely used to measure preferences for different product profiles, and build market simulation models. In the last few years several papers have been published that suggest how to optimally choose a product-line based on such data. We formalize this problem as a mathematical program where the objective of the firm is either profit or total welfare. Unlike alternative published approaches, we introduce fixed and variable costs for each product profile. The number of products to be introduced is endogenously determined on the basis of their desirability, fixed and variable costs, and in the case of profits, their cannibalization effect on other products. While the problem is difficult (NP-complete), we show that the maximum welfare problem is equivalent to the uncapacitated plant location problem, which can be solved very efficiently using the greedy interchange heuristic. Based on past published experience with this problem, and on simulations we perform, we show that optimal or near optimal solutions are obtained in seconds for large problems. We develop a new greedy heuristic for the profit problem, and its application to simulated problems shows that it too runs quickly, and with better performance than various alternatives and previously published heuristics. We also show how the methodology can be applied, taking existing products of both the firm and the competition into account.
Moment Methods for Decision Analysis
Authors: Smith James E. 
Published: November 2008

Decision models involving continuous probability distributions almost always require some form of approximation. The usual approach to evaluating these kinds of models is to construct a discrete approximation for each continuous distribution and compute value lotteries and certain equivalents using these discrete approximations. Although decision analysts are quite comfortable with this approach, there has been relatively little consideration of how these discrete approximations affect the results of the analysis. In the first part of this paper, we review three common methods of constructing discrete approximations and compare their performance in a simple example. The results of the example suggest a different approach that offers potential improvements in accuracy and efficiency over the usual approach. The basic idea is that given discrete approximations that accurately represent the moments of assessed “input” distributions, we may easily and accurately compute the moments of the “output” distribution or value lotteries. These moments then summarize what we know about the value lottery and certain equivalent, and provide the basis for computing approximate value lotteries and certain equivalents. In this paper, we discuss the methods supporting this moment approach and evaluate their performance in the context of the example.
Zero-Tolerance Policies: Do They Inhibit or Stimulate Illicit Drug Consumption?
Authors: Caulkins Jonathan P. 
Published: November 2008

Some have suggested fighting the drug problem with so-called “zero-tolerance” policies that impose stiff sanctions for possession of even trace amounts of illicit drugs. Such policies can swamp the criminal justice system and violate the principle that the punishment should fit the crime, but these objections have often been suppressed by an overriding desire to minimize consumption. This paper argues to the contrary that under plausible conditions zero-tolerance policies may actually encourage controlled users to consume more, not less, than they would if the punishment increased in proportion to the quantity possessed at the time of arrest. This result holds even if for every quantity the punishment under the proportional policy is less than or equal to that under the zero-tolerance policy. The argument relies on a mathematical model that describes how a typical controlled user's purchasing habits are affected by the punishment anticipated as a function of the quantity possessed. A variety of possible punishment policies are evaluated. The consumption minimizing policy for a given individual user is obtained, as well as the consumption minimizing policy that belongs to a restricted class of policies that are more likely to be politically feasible.
A Synthesis of Decision Models for Tool Management in Automated Manufacturing
Authors: Gray Ann E. , Seidmann Abraham , Stecke Kathryn E. 
Published: November 2008

The evidence is clear that a lack of attention to structured tool management has resulted in the poor performance of many manufacturing systems. Plant tooling systems affect product design options, machine loading, job batching, capacity scheduling, and real-time part routing decisions. With increasing automation in manufacturing systems, there is a growing need to integrate tool management more thoroughly into system design, planning and control. This paper critically evaluates various tool management approaches, identifying the operational tradeoffs and analyzing the models developed to address management decisions involving tooling. These decisions range from selecting the optimal machining parameters and the most economic processing rate for a particular operation, to the loading of tools and jobs on machines and the determination of the optimal tool-mix inventories needed for a particular production schedule. We present an integrated conceptual framework for resource planning to examine how tool management issues, depending upon their scope, can be classified into tool-level, machine-level, and system-level concerns. This framework specifies how decisions made at one level constrain those at lower levels, and how information from lower levels feeds back to higher level decisions. The framework structures our critical evaluation of the modeling approaches found in the academic literature and points to promising directions for future research.
Optimal Power-of-Two Replenishment Strategies in Capacitated General Production/Distribution Networks
Authors: Federgruen A. , Zheng Yu-Sheng 
Published: November 2008

In this paper we develop a model for a capacitated production/distribution network of general (but acyclic) topology with a general bill of materials, as considered in MRP (Material Requirement Planning) or DRP (Distribution Requirement Planning) systems. This model assumes stationary, deterministic demand rates and a standard stationary cost structure; it is a generalization of the uncapacitated model treated in the seminal papers of Maxwell and Muckstadt (1985) and Roundy (1986). The capacity constraints consist of bounds on the frequency with which individual items can or need to be replenished. We derive a pair of simple and efficient algorithms capable of determining an optimal power-of-two policy. These algorithms consist of a limited number of maximum flow computations in networks closely related to the production/distribution network. The complexity of these algorithms, even when applied to the uncapacitated model, compares favorably with that of the existing alternative solution methods.
Massaging Mean-Variance Inputs: Returns from Alternative Global Investment Strategies in the 1980s
Authors: Chopra Vijay K. , Hensel Chris R. , Turner Andrew L. 
Published: November 2008

This paper explores the impact of adjustments to the inputs on total returns, terminal wealth, and portfolio turnover in an unconstrained monthly mean-variance (MV) asset allocation over time. It is well known that MV allocations are very sensitive to small forecast errors in the means and covariances. This sensitivity is especially pronounced for errors in means. One way to control this sensitivity to forecast errors is to use Stein estimation. We examined three naive applications of Stein estimation for six individual country stock indexes, five country bond indexes and five cash indexes. This study has two major conclusions. First, any of the suggested adjustments to inputs dominate the results of an unadjusted-input MV optimization. Adjusted-input portfolios have higher mean return, less variance and greater terminal wealth than unadjusted-input portfolios. Second, these improvements become even greater with transaction costs.
Greenfield vs. Acquisition: The Strategy of Japanese Investors in the United States
Authors: Hennart Jean-François , Park Young-Ryeol 
Published: November 2008

Multinational firms can enter a foreign market by taking over existing local firms (acquisitions) or by setting up new ventures (greenfield investments). Surprisingly, there has been limited empirical work on this topic. This paper examines the determinants of this choice by looking at Japanese entries into the United States. By focusing on firms of one country entering a single market, we are able to separate the impact of a firm's strategy from that of the characteristics of the target industry or country. This paper tests simultaneously a number of competing hypotheses. The results suggest that acquisitions are used by Japanese investors with weak competitive advantages, while investors with strong advantages find that greenfield investments are a more efficient way to transfer these advantages to the U.S. Acquisitions are also chosen to enter industries with either very high or very low growth rates, when entry is at a scale that is large relative to the parent, and when entry is into a different industry. The Japanese investor's previous experience of the U.S. market, its financial situation, and its status as a follower in an oligopolistic industry have no statistically significant impact on the entry mode. Neither do U.S. stock market conditions.
Two-Interval Inventory-Allocation Policies in a One-Warehouse N-Identical-Retailer Distribution System
Authors: McGavin Edward J. , Schwarz Leroy B. , Ward James E. 
Published: November 2008

For a system of N-identical-retailers we construct a model for determining warehouse inventory-allocation policies which minimize system lost sales per retailer between system replenishments. An allocation policy is specified by: (a) the number of withdrawals from warehouse stock; (b) the intervals between successive withdrawals; (c) the quantity of stock to be withdrawn from the warehouse in each interval; and (d) the division of withdrawn stock among the retailers. We show that in the case of two withdrawals, available stock in each interval should be divided to “balance” retailer inventories. We also develop an infinite-retailer model and use it to determine two-interval allocation heuristics for N-retailer systems. Simulation tests suggest that the infinite-retailer heuristic policies are near-optimal for as few as two retailers. Simulation tests indicate that the risk-pooling benefits of allocation policies with two well-chosen intervals are comparable to those of base-stock policies with four equal intervals.
Management Models and Industrial Applications of Linear Programming
Authors: Charnes A. , Cooper W. W. 
Published: November 2008

An accelerating increase in linear programming applications to industrial problems has made it virtually impossible to keep abreast of them, not only because of their number (and diversity) but also because of the conditions under which many are carried out. Industrial (and governmental) secrecy is often present. Other conditions also bar access to ascertainment and assessment of the pattern of applications. Lack of a tradition for publication is one. Failure to ascertain the general significance of particular findings is another, as is discouragement arising from the fact that similar applications have previously been published by others. Immediate remedies are not available for these difficulties. Presumably conventions such as this will help, over a period of time, by encouraging informal contacts between interested persons. A talk on “industrial applications of linear programming” must be altered to suit these circumstances. In place of a survey or evaluation of industrial studies, two broad issues which are relevant to all such applications will be discussed. These are, (1) use of linear programming models as guides to data collection and (2) analysis (and prognosis) of fruitful areas of additional research, especially those which appear to have been opened by industrial applications.
Programming of Economic Lot Sizes
Authors: Manne Alan S. 
Published: November 2008

This paper studies the planning problem faced by a machine shop required to produce many different items so as to meet a rigid delivery schedule, remain within capacity limitations, and at the same time minimize the use of premium-cost overtime labor. It differs from alternative approaches to this well-known problem by allowing for setup cost indivisibilities. As an approximation, the following linear programming model is suggested: Let an activity be defined as a sequence of the inputs required to satisfy the delivery requirements for a single item over time. The input coefficients for each such activity may then be constructed so as to allow for all setup costs incurred when the activity is operated at the level of unity or at zero. It is then shown that in any solution to this problem, all activity levels will turn out to be either unity or zero, except for those related to a group of items which, in number, must be equal to or less than the original number of capacity constraints. This result means that the linear programming solution should provide a good approximation whenever the number of items being manufactured is large in comparison with the number of capacity constraints.
An Analysis of Decisions
Authors: Salveson M. E. 
Published: November 2008

Most analyses of decision making define decision as choosing from among alternative courses of action. Usually, the criterion of choice is assumed to be some function of probability and utility of the different outcomes associated with each course of action. It is shown here that decision is more realistically concerned with constructive, purposive, or creative aspects of human behavior. In addition to the usual decisions of action, other classes of decision include decisions of understanding, of recognition, and of enterprise. These classes are interdependent and their members interrelated in any realistic situation. Organization planning is shown to be concerned largely with interrelating decisions and with providing criteria for decision. The quality of organization planning affects the quality of decisions, the degree of human satisfaction, and the effectiveness of the organization.
Towards a Behavioral Theory of Communication
Authors: Ackoff Russell L. 
Published: November 2008

This paper presents a conceptualization of information as related to the decision problems of the recipient. The orientation is toward a formal definition of behavioral elements in an individual's “purposeful state”: specifically, these elements are his objectives, his valuation of each objective, his possible courses of action, the efficiency of each course of action in achieving each objective, and his probability of choice for each course of action. The amount of information in a purposeful state is explicitly defined in terms of the probabilities of choice of the available courses of action. The amount of information in a message is defined as the difference between the amount of information in the purposeful state following the message, and the amount of information in the purposeful state preceding the message. The amount of instruction in a purposeful state is defined in terms of the efficiencies of the available courses of action; and the amount of motivation is defined in terms of the values of the objectives. The amounts of instruction and motivation in a message are defined, just as information is, by comparing the amounts in a purposeful state before and after receipt of the message. The value of a purposeful state to an individual is defined as a function of the amount of information, the amount of instruction, and the amount of motivation in the state. This concept can be generalized to express the value of the state to some other individual.
A Model for the Location of a Railroad Classification Yard
Authors: Mansfield Edwin , Wein Harold H. 
Published: November 2008

The evaluation of alternative locations for an automatic classification yard has become an important problem for railroad managements. Because of the lower classification costs in these yards and the importance of such costs, many railroads have installed these newer facilities. An automatic yard represents an investment of $5,000,000 or more. Hence, the decision to install such a yard and the question regarding its location merit considerable thought and attention. In this paper, a simple model is constructed to aid a railroad management in choosing among alternative locations. This model is being used by one firm, and it should prove useful to many operations researchers interested in the industry. Although it was constructed primarily to deal with the problem of yard location, the model seems sufficiently flexible to deal with other railroad problems. A few of these other problems are also discussed briefly. The plan of the paper is as follows. Sections I and II contain some introductory material concerning freight yards and some definitions of terms. Section III contains a full description of the location problem we consider. Sections IV–VI deal with the model and procedure we propose. Section VII contains a numerical example, and Section VIII contains some concluding remarks.