bluuebunny/crossref_metadata_2025 huggingface dataset:
Negotiation Analysis: A Characterization and Review
Authors: Sebenius James K.
Published: November 2008

“Negotiation analysis” seeks to develop prescriptive theory and useful advice for negotiators and third parties. It generally emphasizes the parties' underlying interests (as distinct from the issues on the table and the positions taken), alternatives to negotiated agreement, approaches to productively manage the inherent tension between competitive actions to “claim” value individually and cooperative ones to “create” value jointly, as well as efforts to change perceptions of the game itself. Since advice to one side does not necessarily presume the full game-theoretic rationality of the other side(s), negotiation analysts often draw on the findings of behavioral decision analysts and economists. Further, this approach does not generally assume that all the elements of the “game” are common knowledge. Thus, the negotiation analytic approach tends to de-emphasize the application of game-theoretic solution concepts or efforts to find unique equilibrium outcomes. Instead, to evaluate possible strategies and tactics, negotiation analysts generally focus on changes in perceptions of the “zone of possible agreement” and the (subjective) distribution of possible negotiated outcomes conditional on various actions. This approach is especially sensitive to potentially unrealized joint gains. It has been used to develop prescriptive advice for the simplest bilateral negotiations between monolithic parties, for negotiations through agents or with linked “internal” and “external” aspects, for negotiations in hierarchies and networks, as well as for more complex coalitional interactions.
Optimal Value Declaration in “Buy-Sell” Situations
Authors: Gerchak Yigal , Fuller J. David
Published: November 2008

Buy-Sell “Shotgun” clauses call for a partner who wishes to discontinue a partnership to declare a value for the business, and for the other partner to then buy her out or sell to her at this value. The resulting decision model for an expected utility maximizing individual, who is uncertain of the business' valuation by the partner, is analyzed. This model is also applicable to a “divide and choose” fair division method, as well as some historical tax/customs schemes, and is more general than comparable bidding/auctions models. After showing that the optimal declaration is always between the declarer's valuation and the fractile of the subjective distribution corresponding to the share owned, we show that the optimal declaration is always increasing in the valuation, and for a risk-neutral declarer also increasing in the share owned. We prove that the more risk-averse the declarer, the closer is the optimal declaration to the valuation, and the higher the probability that the partner who values the business more will end up owning it. Finally, we relate the optimal declaration to the degree of uncertainty concerning the partner's valuation.
Predicting Risk: Some New Generalizations
Authors: Karolyi G. Andrew
Published: November 2008

Existing adjustment techniques for forecasting systematic risk of individual firms have been based on relatively uniformative prior knowledge about the cross-sectional distribution of risk estimates. This study introduces prior information in the form of size and industry-based cross-sectional distributions of risk estimates. Such information is incorporated into forecasts using familiar and generalized adjustment techniques, the latter being based on recently developed multiple shrinkage methods. Improved forecast performance results.
Note—A Numerical Approach to Deriving Long-Run Equilibrium Solutions in Spatial Positioning Models
Authors: Choi S. Chan , Desarbo Wayne S. , Harker Patrick T.
Published: November 2008

Choi, DeSarbo and Harker (1990) have recently proposed a numerical methodology for optimal product positioning and pricing under the assumption that the incumbents react only with price changes in the short run. The current note extends this methodology to include incumbents' long-run strategy of competitive product repositioning, in addition to price reactions. This note also introduces the notion of product relocation cost to the equilibrium analysis, and applies the concept of (full and partial) adjustment processes toward an equilibrium to model various strategic behavior of firms. This methodology is illustrated using an existing set of data collected for a major telecommunication equipment manufacturer.
On Properties of Stochastic Inventory Systems
Authors: Zheng Yu-Sheng
Published: November 2008

For most order quantity/reorder point inventory systems, the stochastic model, which specifies the demands as stochastic processes, is often more accurate than its deterministic counterpart—the EOQ model. However, the application of the stochastic model has been limited because of the absence of insightful analytical results on the model.

This paper analyzes the stochastic order quantity/reorder point model in comparison with a corresponding deterministic EOQ model. Based on simple optimality conditions for the control variables derived in the paper, a sensitivity analysis is carried out, and a number of basic qualitative properties are established for the optimal control parameters. Our main results include the following: (1) in contrast to the deterministic EOQ model, the controllable costs of the stochastic model due to selection of the order quantity (assuming the reorder point is chosen optimally for every order quantity) are actually smaller, while the total costs are clearly larger; the optimal order quantity is larger, but the difference is relatively small when the quantity is large; the cost performance is even less sensitive to choices of the order quantity; (2) the relative increase of the costs incurred by using the quantity determined by the EOQ instead of the optimal from the stochastic model is no more than 1/8, and vanishes when the ordering costs are significant relative to other costs.
Estimating Loyalty and Switching with an Application to the Automobile Market
Authors: McCarthy Patrick S. , Kannan P. K. , Chandrasekharan Radha , Wright Gordon P.
Published: November 2008

A brand switching model that considers the choices: previous choice, current choice, and substitute choice, if the current choice were not available, is developed and estimated. An important assumption of the model is that the market consists of two types of consumers: “Loyals” and “Shoppers.” The model provides estimates for: (1) the proportion of Loyals in a submarket, and (2) the success of each submarket in capturing Shoppers. We illustrate how the model can be used to characterize the competitive structure of a market. We also show how the estimated parameters of the model can be validated using simulation and a theoretically derived covariance matrix.

Our empirical application to automobile data from J. D. Power and Associates provides insights into several interesting marketing phenomena including: (1) the competitiveness of domestic versus foreign makes of automobiles, (2) competition between submarkets defined by form, and (3) the effect of previous dealer experience on loyalty and shopping.
New Search Spaces for Sequencing Problems with Application to Job Shop Scheduling
Authors: Storer Robert H. , Wu S. David , Vaccari Renzo
Published: November 2008

In this paper search heuristics are developed for generic sequencing problems with emphasis on job shop scheduling. The proposed methods integrate problem specific heuristics common to Operations Research and local search approaches from Artificial Intelligence in order to obtain desirable properties from both. The applicability of local search to a wide range of problems, and the incorporation of problem-specific information are both properties of the proposed algorithms. Two methods are proposed, both of which are based on novel definitions of solution spaces and of neighborhoods in these spaces. Applications of the proposed methodology are developed for job shop scheduling problems, and can be easily applied with any scheduling objective. To demonstrate effectiveness, the method is tested on the job shop scheduling problem with the minimum makespan objective. Encouraging results are obtained.
The CAPM and the Calendar: Empirical Anomalies and the Risk-Return Relationship
Authors: Cadsby Charles Bram
Published: November 2008

Tinic and West (1984) argue that a tradeoff between risk and return exists only in January. This study demonstrates that it is not just the January Effect on stock returns which is related to the measured risk-return relationship and how that measure is apparently affected by the calendar. Other returns anomalies can also be paired with a conclusion about the relationship between risk and return. For example, risk appears to be rewarded at the turn of the month but not during the rest of the year and late in the week but not early in the week. This paper argues that, given the returns anomalies, the corresponding calendar effects on the risk-return relationship are consistent with the CAPM. Thus, the anomaly to be explained is not the relationship between risk and return focused on by Tinic and West (1984) but rather the calendar related variations in the returns themselves.
The Pricing of Japanese Equity Warrants
Authors: Kuwahara Hiroto , Marsh Terry A.
Published: November 2008

Discrepancies between the Black-Scholes value of Japanese equity warrants and their observed prices are explained in part by the stochastic volatility of changes in prices of the underlying stocks. We fit GARCH and EGARCH models to the stochastic volatility and briefly compare their performance to the CEV model. A hopscotch algorithm is used to value the warrants in the presence of the stochastic stock price volatility. The stochastic volatility-hopscotch warrant values still differ substantially from corresponding prices; in contrast, away-from-the-money short-term Nikkei 225 options valued with the same stochastic volatility models are close to observed prices. A regression model is used to fit the differences between warrant values and prices as a function of proxies for market impediments.
Stochastic Network Programming for Financial Planning Problems
Authors: Mulvey John M. , Vladimirou Hercules
Published: November 2008

Several financial planning problems are posed as dynamic generalized network models with stochastic parameters. Examples include: asset allocation for portfolio selection, international cash management, and programmed-trading arbitrage. Despite the large size of the resulting stochastic programs, the network structure can be exploited within the solution strategy giving rise to efficient implementations. Empirical results are presented indicating the benefits of the stochastic network approach for the asset allocation case.
Complete Prepayment Models for Mortgage-Backed Securities
Authors: Kang Pan , Zenios Stavros A.
Published: November 2008

The estimation of prepayment rates for pools of mortgages is a critical component in determining the value of mortgage-backed securities—MBS for short—and derivative products. This paper discusses the development of prepayment models for pools of fixed-rate mortgages. The models are complete: calibrated functional forms are given for all of the factors that determine prepayment rates. Hence, the models can be used as benchmarks against the simple models of the Public Securities Association, the Federal Housing Administration experience, or the variety of projected prepayment rates generated by proprietary industry models.

The key factors that determine prepayment rates are: (1) refinancing incentive, (2) seasonal variations, (3) seasoning of the mortgage pool, and (4) burnout effect. Each factor is modeled separately and is calibrated using historical data. A multiplicative relationship determines the prepayment rate of the mortgage pool. A novel feature of our model is the use of basis functions that capture the complex interactions between the control variables, i.e., interest rate differentials and time, and the response parameter, i.e., prepayment rates.
Strategic Risk: An Ordinal Approach
Authors: Collins James M. , Ruefli Timothy W.
Published: November 2008

Strategic management researchers have shown increasing awareness of the importance of the concept of risk at the strategic level. In recognition of this interest, this research adopts a commonly used conceptualization of risk and shows how this conceptualization leads to a new measure of risk, based upon the chance of loss of relative position within a set of firms. This framework is shown to be particularly appropriate for strategy research. Information contained in probability distributions describing the relative positions of sets of firms over time is shown to be partitionable on the basis of gain or loss in position as well as on firm identity, leading to the derivation of a new measure of strategic risk for an individual firm. This development also provides a hierarchical quantification of risk at the levels of the industry, group and individual firm. The ordinal risk measure is applied to both hypothetical data for illustration and to data on the U.S. airline industry.
Empirical Analysis of Closed-Loop Duopoly Advertising Strategies
Authors: Erickson Gary M.
Published: November 2008

Closed-loop (perfect) equilibria in a Lanchester duopoly differential game of advertising competition are used as the basis for empirical investigation. Two systems of simultaneous nonlinear equations are formed, one from a general Lanchester model and one from a constrained model. Two empirical applications are conducted. In one involving Coca-Cola and Pepsi-Cola, a formal statistical testing procedure is used to detect whether closed-loop equilibrium advertising strategies are used by the competitors rather than open-loop strategies. In the second application, involving Anheuser-Busch and Miller, the general model is estimated. Results indicate that closed-loop equilibria better explain dynamic advertising competition than do open-loop equilibria. Also, closed-loop equilibrium advertising strategies implied by model estimates show that competitive advertising levels may or may not be monotonic in market share.
Optimal Workload Allocation in Open Networks of Multiserver Queues
Authors: Calabrese Joel M.
Published: November 2008

In this paper, we examine the general problem of workload allocation in an open Jackson network of multiserver queues. We show that use of the open network model leads to a separable, convex formulation of the problem with relatively simple optimality conditions. Using these conditions, we prove in general that server groups with the same number of servers should be loaded equally and larger groups should be loaded more heavily than smaller groups. It is also shown that server pooling, combining servers into larger groups, will always reduce congestion and/or increase throughput. We discuss the significance of our results for job shop applications and also for the concept of a production bottleneck. In systems with an unbalanced configuration of servers, traditional, deterministic bottleneck analysis is distinctly nonoptimal; our results provide a simple way to locate production bottlenecks in shops with significant queueing effects.
Contracting for Software Development
Authors: Whang Seungjin
Published: November 2008

Software contracting is a multi-faceted issue that involves legal, economic, managerial and technological considerations. To better understand the economic aspect of software contracting, this paper provides a summary review of software development contracts, followed by a gametheoretic model developed to incorporate incentive and information issues associated with software contracting. In the model an outside contractor is hired to develop a software system over multiple periods. Due to the uncertainties about costs or technology, the developer faces the risk of having to abandon the project at an intermediate phase. The user is better informed of the benefit of the system, while the developer privately discovers the development costs as the project advances. Given the limited information, the contracting parties make decisions in their own interest, leaving each party vulnerable to the other's opportunistic behavior. In this setting, we construct a viable contract that aligns the incentives of the contracting parties and produces the same equilibrium outcome as in in-house development. We also relate the implications of the model to the actual contract cases.
Joint Coherence in Games of Incomplete Information
Authors: Nau Robert F.
Published: November 2008

Decisions are often made under conditions of uncertainty about the actions of supposedly-rational competitors. The modeling of optimal behavior under such conditions is the subject of noncooperative game theory, of which a cornerstone is Harsanyi's formulation of games of incomplete information. In an incomplete-information game, uncertainty may surround the attributes as well as the strategic intentions of opposing players. Harsanyi develops the concept of a Bayesian equilibrium, which is a Nash equilibrium of a game in which the players' reciprocal beliefs about each others' attributes are consistent with a common prior distribution, as though they had been jointly drawn at random from populations with commonly-known proportions of types. The relation of such game-theoretic solution concepts to subjective probability theory and nonstrategic decision analysis has been controversial, as reflected in critiques by Kadane and Larkey and responses from Harsanyi, Shubik, and others, which have appeared in this journal. This paper shows that the Bayesian equilibrium concept and common prior assumption can be reconciled with a subjective view of probability by (i) supposing that players elicit each others' probabilities and utilities through the acceptance of gambles, and (ii) invoking a multi-agent extension of de Finetti's axiom of coherence (no arbitrage opportunities, a.k.a. “Dutch books”). However, the Nash property of statistical independence between players is weakened, and the probability distributions characterizing a solution of the game admit novel interpretations.
Stochastic Dominance and Expected Utility: Survey and Analysis
Authors: Levy Haim
Published: November 2008

While Stochastic Dominance has been employed in various forms as early as 1932, it has only been since 1969–1970 that the notion has been developed and extensively employed in the area of economics, finance, agriculture, statistics, marketing and operations research.

In this survey, the first-, second- and third-order stochastic dominance rules are discussed with an emphasis on the development in the area since the 1980s.
A New Graph-Theoretic Heuristic for Facility Layout
Authors: Leung Janny
Published: November 2008

The facility layout problem is important in the modern manufacturing environment because increased machine flexibility and product diversification create additional complexities in scheduling and material handling. An important first step in facility layout is the determination of which machines should be adjacent. This problem can be modelled as that of finding a maximum weight planar subgraph of a graph, given a measure of the desirability that two machines be adjacent based on the anticipated flows and technological constraints. We present a new heuristic that is a generalization of previous work of Foulds and Robinson. Preliminary computational results are presented which suggest that this heuristic performs well.
Multiple Criteria Decision Making, Multiattribute Utility Theory: The Next Ten Years
Authors: Dyer James S. , Fishburn Peter C. , Steuer Ralph E. , Wallenius Jyrki , Zionts Stanley
Published: November 2008

Management science and decision science have grown exponentially since midcentury. Two closely-related fields central to this growth are multiple criteria decision making (MCDM) and multiattribute utility theory (MAUT). This paper comments on the history of MCDM and MAUT and discusses topics we believe are important in their continued development and usefulness to management science over the next decade. Our aim is to identify exciting directions and promising areas for future research.
Current Issues in Frequency Domain Experimentation
Authors: Sargent Robert G. , Som Tapas K.
Published: November 2008

This paper presents an examination of certain issues in Frequency Domain Experimentation (FDE) for discrete event simulation. Experimental results are presented to demonstrate that (i) conclusions drawn from FDE are dependent on the oscillation frequency and unless frequencies are chosen carefully, misleading results can be obtained; (ii) interpretation of results from frequency domain experiments are fundamentally different from the interpretation of results from regression analysis—specifically, a term found significant by FDE is not to be interpreted as a term able to explain a significant portion of the variation in the response over the experimental region; and (iii) basic assumptions required for FDE, in particular the assumption that input and output processes constitute a time-invariant linear system, do not hold for M/M/1 queues. Other issues discussed are indexing, run length determination, computational effort, and why FDE is not applicable for terminating simulations. It is concluded that further developments are needed before FDE can be used by practitioners.
Stopped Myopic Policies in Some Inventory Models with Generalized Demand Processes
Authors: Lovejoy William S.
Published: November 2008

This paper considers single-item inventory systems with immediate delivery and no economies of scale. Bounds are provided on the value loss relative to optimal cost for restricting attention to the class of inventory stocking policies that behave myopically up to a specified stopping time. The stopping time may be random, and may depend on demand histories as well as information exogenous to the firm. The bounds are robust to the nature of the demand process faced after the stopping time, so are applicable when the statistics of demand after the stopping time are unknown. Stopping times that are large with high probability imply that near-term decisions are completely specified with high probability. The general bounding results allow one to consider demand processes that may otherwise be analytically intractable.

It is shown that the class of demand models for which the assumption of additive i.i.d. shocks is appropriate is the same class admitting effective myopic stocking policies. The bounds also make rigorous the intuitive notion that myopic policies are least effective in systems with precipitous drops in demand coupled with an inability to recover cash invested in inventory. The option of selling inventory at discount is a reality in many real systems and enhances the attractiveness of the myopic stocking policy.

In numerical examples, the myopic policy is shown to be an effective competitor in a range of systems for which optimal policies are not known. The results suggest that for systems with immediate delivery, no economies of scale, and no currently known optimal policy, the myopic stocking rule is a reasonable default policy to adopt.
The Relationship of Industry Evolution to Patterns of Technological Linkages, Joint Ventures, and Direct Investment Between U.S. and Japan
Authors: Auster Ellen R.
Published: November 2008

Although economic activity between the U.S. and Japan has skyrocketed in the last decade, there are few large sample, cross-industry studies analyzing multiple forms of investment by the Japanese in the U.S. This study analyzes the key characteristics of each stage of industry evolution and the costs and benefits of each form of resource investment to predict the patterns of technological linkages, joint ventures, and direct investment of Japanese companies in the U.S. The results find support for a model predicting a predominance of technological linkages in emerging industries, joint ventures in growing industries, and direct investment in maturing industries. Technological linkages are most attractive in emerging industries as firms struggle to acquire technology, information and expertise and share cost and risk, yet retain flexibility. Joint ventures proliferate in growing industries because they offer a means of acquiring and expanding customer bases, yet reducing vulnerability. In maturing industries, where firms' key competencies are more developed, direct investment allows the company to generate demand in new markets without the disadvantage of joint governance.
Brand Extensions: When to Use Them
Authors: Sullivan Mary W.
Published: November 2008

This empirical study investigates whether brand extensions should be introduced early or late in the life cycle of a product category. The longitudinal/cross-category sample of frequently purchased consumer brands is used to analyze how the performance of brand extensions depends on order of entry. The results indicate that early-entering brand extensions do not perform as well on average as either early-entering new-name products or late-entering brand extensions. This conclusion is based on four findings. First, the brand extensions were introduced later on average than the new-name products. Second, the early brand extensions had a lower probability of surviving than either the early-entering new-name products or the late-entering brand extensions. Third, the brand extensions earned higher market shares on average than new-name products, controlling for order of entry. Fourth, the extensions obtained smaller market share premia from entering early than did new-name products.
Estimating the Impact of Uncertainty on a Deterministic Multiattribute Evaluation
Authors: Kirkwood Craig W.
Published: November 2008

A method is presented to estimate the impact of uncertainty on the results of a multiattribute evaluation prior to conducting a complete probabilistic multiattribute utility analysis. The method assumes that a deterministic analysis has been completed using a weighted-additive multiattribute value (evaluation) function and that either an additive or multiplicative utility function is appropriate for the multiattribute utility analysis. An approximation procedure is developed to estimate whether uncertainty about attribute levels could change the deterministic evaluation results. An illustrative application investigates the accuracy of the procedure and its use to simplify analysis of the effects of uncertainty.
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.
A Broader View of the Job-Shop Scheduling Problem
Authors: Wein Lawrence M. , Chevalier Philippe B.
Published: November 2008

We define a job-shop scheduling problem with three dynamic decisions: assigning due-dates to exogenously arriving jobs, releasing jobs from a backlog to the shop floor, and sequencing jobs at each of two workstations in the shop. The job-shop is modeled as a multiclass queueing network and the objective is to minimize both the work-in-process (WIP) inventory on the shop floor and the due-date lead time (due-date minus arrival date) of jobs, subject to an upper bound constraint on the proportion of tardy jobs. A general two-step approach to this problem is proposed: (1) release and sequence jobs in order to minimize the WIP inventory subject to completing jobs at a specified rate, and (2) given the policies in (1), set due-dates that will attempt to minimize the due-date lead time, subject to the job tardiness constraint. A simulation study shows that this approach easily outperforms other combinations of traditional due-date setting, job release, and priority sequencing policies for two cases (moderately loaded and heavily loaded) of a particular shop. As a result of the study, three scheduling principles are proposed that can significantly improve the performance of a two-station job-shop; in particular, better due-date performance can be achieved by ignoring due-dates on the shop floor. Although we have only considered a two-station shop, the approach and scheduling principles presented here might also be useful for larger shops.
Congestion and Network Externalities in the Short Run Pricing of Information System Services
Authors: Westland J. Christopher
Published: November 2008

Transfer pricing provides management with an efficient tool for coordinating the use of information system services. In practice these services, if they are charged out to end users, are priced via an allocation of historical costs based on individual usage, or are assigned a price based on the fair market value of outside alternatives. Both approaches encourage suboptimal usage of information systems resources: they ignore three constituents of optimal transfer prices: (1) the reaction of other users to any change in a given user's consumption of service; (2) the technical response to additional use of an information system service, in the form of congestion and network externalities; and (3) end-user preferences for the information system service. Together, these influences on demand contribute to an externality. Two types of externalities are significant in information systems—congestion externalities decrease, and network externalities increase the utility of services. This research provides a complete model for computing optimal transfer price which corrects several existing problems in information system service valuation. When full absorption cost allocations contain significant fixed, precommitted or sunk cost components, it is not possible to balance the budget. Direct costing improves on full absorption costing, but misspecifies costs when demand is nonlinear. To balance the budget with a minimum of disutility to end users management must resort to second-best pricing. Inefficiency arises from two sources when externalities are ignored in transfer pricing. End users cannot plan service usage, and thus encounter unanticipated congestion which lowers morale and efficiency, and increases costly expediting. Where congestion effects are highly nonlinear, congestion may effectively shut down the system. On the other hand, incorrect transfer prices can motivate usage too low to take advantage of network benefits. End users may confuse externality effects and intrinsic value of an information system service. In these cases, the price and performance of outside alternatives exert a complex and subtle influence on use and pricing of services. Where there exist identical outside and inside processing alternatives, and transfer pricing does not reflect this, there is a significant tendency to overprice and underutilize internal services. In this case there may be a tendency to outsource when processing should be kept in-house. Future markets for information systems will favor technologies which exhibit strong network externalities, and pricing of these technologies will become increasingly complex because of the interrelationship of hardware, software and data originated externalities. The models provided in this research will allow management to take advantage of these opportunities.
A Two-Echelon Inventory System with Priority Shipments
Authors: Dada Maqbool
Published: November 2008

A two-echelon system for spare parts is analyzed. The system allows the use of priority inventory pooling to expedite service when a stock-out occurs. First, a tractable aggregate model is derived. This model is then disaggregated to approximate the performance of the exact system. Results of computer tests are also presented.
Optimal Service Speeds in a Competitive Environment
Authors: Kalai Ehud , Kamien Morton I. , Rubinovitch Michael
Published: November 2008

This is a study of the economic behavior of vendors of service in competition. A simple model with two competing exponential servers and Poisson arrivals is considered. Each server is free to choose his own service rate at a cost (per time unit) that is strictly convex and increasing. There is a fixed reward to a server for each customer that he serves. The model is designed to study one specific aspect of competition, namely, competition in speed of service as a means for capturing a larger market share in order to maximize long-run expected profit per time unit. A two-person strategic game is formulated and its solutions are characterized. Depending on the revenue per customer served and on the cost of maintaining service rates, the following three situations may arise: (i) a unique symmetric strategic (Nash) equilibrium in which expected waiting time is infinite; (ii) a unique symmetric strategic equilibrium in which expected waiting time is finite; and (iii) several, nonsymmetric strategic equilibria with infinite expected waiting time. An explicit expression for the market share of each server as a function of the service rates of the two servers is also given.
Regression Metamodels for Simulation with Common Random Numbers: Comparison of Validation Tests and Confidence Intervals
Authors: Kleijnen Jack P. C.
Published: November 2008

Linear regression analysis is important in many fields. In the analysis of simulation results, a regression (meta)model can be applied, even when common pseudorandom numbers are used. To test the validity of the specified regression model, Rao (1959) generalized the F statistic for lack of fit, whereas Kleijnen (1983) proposed a cross-validation procedure using a Student's t statistic combined with Bonferroni's inequality. This paper reports on an extensive Monte Carlo experiment designed to compare these two methods. Under the normality assumption, cross-validation is conservative, whereas Rao's test realizes its nominal type I error and has high power. Robustness is investigated through lognormal and uniform distributions. When simulation responses are distributed lognormally, then cross-validation using Ordinary Least Squares is the only technique that has acceptable type I error. Uniform distributions give results similar to the normal case. Once the regression model is validated, confidence intervals for the individual regression parameters are computed. The Monte Carlo experiment compares several confidence interval procedures. Under normality, Rao's procedure is preferred since it has good coverage probability and acceptable half-length. Under lognormality, Ordinary Least Squares achieves nominal coverage probability. Uniform distributions again give results similar to the normal case.
To Be or Not to Be? That is Conception! Managing In Vitro Fertilization Programs
Authors: Kaplan Edward H. , Hershlag Avner , DeCherney Alan H. , Lavy Gady
Published: November 2008

The performance of in vitro fertilization-embryo transfer (IVF-ET) programs is summarized typically as the average probability of achieving pregnancy per cycle. Variation in conception probabilities across women reduces the usefulness of such an aggregate measure. More relevant is the conditional probability of achieving pregnancy on a given cycle following a number of failed IVF-ET attempts. We construct a model that accurately describes 1,257 treatment cycles performed at Yale over 571 different women. The model assumes a split population, where some women can never conceive via IVF-ET, while the remaining women have identical and constant per cycle probabilities of conception. This model produces estimates that are highly consistent with the data, and suggests that continuing treatment beyond some threshold number of cycles is not efficacious. Recognizing this, we determine cutoffs beyond which treatment should not continue for IVF-ET programs with fixed capacities. We also consider cutoff policies where program participants may belong to one of several different split populations, detailing the case of two groups. Finally, we show how one may reduce the average time in treatment (including waiting time) considerably with minimal impact on the probability of achieving pregnancy.
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.
Behavioral Consequences of Corporate Incentives and Long-Term Bonuses: An Experimental Study
Authors: Schotter Andrew , Weigelt Keith
Published: November 2008

This paper examines whether long-term managerial bonus schemes change the allocative behavior of subjects in a laboratory setting. Using four different compensation schemes, we show that a necessary condition for reconciling divergent time preferences between principals and agents is a compensation scheme that induces behavior consistent with lower discount rates. Within subject results show that subjects recognize changes across compensation schemes and change their behavior as predicted by formal theory. Results also suggest that subjects become more myopic in their investment decisions if compensation contracts are incorrectly structured.
Analysis of the Deterministic (s, S) Inventory Problem
Authors: Iyer Ananth V. , Schrage Linus E.
Published: November 2008

The traditional or textbook approach for finding an (s, S) inventory policy is to take a demand distribution as given and then find a reorder point s and order up to point S that are optimal for this demand distribution. In reality, the demand distribution may have been obtained by fitting it to some historical demand stream. In contrast, the deterministic (s, S) inventory problem is to directly determine the (s, S) pair that would have been optimal for the original demand stream, bypassing the distribution fitting step. The deterministic (s, S) inventory problem thus chooses parameters s and S which minimize setup, holding and backorder costs when the corresponding (s, S) policy is implemented over n periods with known demands d1, d2,…, dn. Our contributions are two: (a) a polynomial time algorithm for finding an optimal (s, S) for the deterministic problem, and (b) an empirical comparison of the two approaches. In (b) we compare the long term average costs of the two approaches as a function of the amount of data available, distributional assumptions, and order lead time.
Lot Sizing to Reduce Capacity Utilization in a Production Process with Defective Items, Process Corrections, and Rework
Authors: Lee Hau L.
Published: November 2008

This paper deals with the lot sizing problem in which the key features of imperfections in a production process are explicitly modelled. These features include: process shifting to out-of-control states, detection of the out-of-control shifts, corrective actions following the detections, and the fixed setup and variable processing times of reworks. The problem is motivated by the wafer probe operation in semiconductor manufacturing. The key objective that drives the lot sizing decision is to reduce the total processing time on a critical resource. Such an objective is aimed at reducing the congestion level at this resource.
A Lagrangean Relaxation Approach for Very-Large-Scale Capacitated Lot-Sizing
Authors: Diaby Moustapha , Bahl Harish C. , Karwan Mark H. , Zionts Stanley
Published: November 2008

In this paper, we develop a Lagrangean relaxation-based heuristic procedure to generate near-optimal solutions to very-large-scale capacitated lot-sizing problems (CLSP) with setup times and limited overtime. Our computational results show that large problems involving several thousand products and several thousand 0/1 integer variables can be solved in a reasonable amount of computer time to within one percent of their optimal solution. The proposed procedure is general enough to be applied directly or with slight modification to real-life production problems.
Notes: Toward Characterizing the Optimal Allocation of Storage Space in Production Line Systems with Variable Processing Times
Authors: Hillier Frederick S. , So Kut C. , Boling Ronald W.
Published: November 2008

This investigation considers certain issues regarding the optimal design of unpaced production lines with variable processing times. Under certain assumptions, including an equal allocation of buffer storage space between the respective pairs of stations, it is known that the optimal allocation of work is characterized by the “bowl phenomenon” whereby the interior stations (especially the center ones) are given preferential treatment (less work) over the end stations. The key question now being posed is: given an equal allocation of work to the respective stations, does the optimal allocation of buffer storage space between the respective pairs of stations follow an analogous pattern (the “storage bowl phenomenon”) whereby the interior buffers (especially the center ones) are given preferential treatment (more space) over the end buffers? Because the decision variables now are discrete instead of continuous, the answer found in this study is: sometimes, but not in general. Characterizing the optimal allocation of storage space is a surprisingly subtle and complex problem. Despite the ambiguities, one dominant theme that runs throughout all of the results obtained is that, to the extent that preferential treatment in storage space allocations should be given, priority should be given to the interior buffers (especially the center ones) over the end buffers. The other key conclusion is that, when the total amount of storage space also is a decision variable, the overall optimal solution commonly follows a storage bowl phenomenon whereby the allocation of buffer storage space fits an inverted bowl pattern.
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.
A Procedure for Ranking Efficient Units in Data Envelopment Analysis
Authors: Andersen Per , Petersen Niels Christian
Published: November 2008

Data Envelopment Analysis (DEA) evaluates the relative efficiency of decision-making units (DMUs) but does not allow for a ranking of the efficient units themselves. A modified version of DEA based upon comparison of efficient DMUs relative to a reference technology spanned by all other units is developed. The procedure provides a framework for ranking efficient units and facilitates comparison with rankings based on parametric methods.