bluuebunny/crossref_metadata_2025 huggingface dataset:
Notes: Conditions for the Applicability of the Regenerative Method
Authors: Glynn Peter W. , Iglehart Donald L.
Published: November 2008

The regenerative method for estimating steady-state parameters is one of the basic methods in simulation output analysis. This method depends on central limit theorems for regenerative processes and weakly consistent estimates for the variance constants arising in the central limit theorems. A weak sufficient condition for both the central limit theorems and consistent estimates is given. Previous authors have implicitly made stronger moment assumptions which have led to strongly consistent variance estimates, more than is needed for the regenerative method to hold. The relationship between conditions for the validity of the regenerative method and those for the validity of standardized time series methods is also discussed.
On the Extensive Number of Plays to Achieve Superior Performance with the Geometric Mean Strategy
Authors: Aucamp Donald C.
Published: November 2008

The advantages of the Geometric Mean or Log Strategy have been well documented and recommended by many because a follower of this strategy will ultimately outperform in the long-run any other significantly different strategy, almost surely. This paper provides both theory and evidence to indicate that the “long-run” can be quite long in risky situations. These cases are typified by many business ventures and undiversified speculative investments in OTC securities. On the other hand, it is shown that the Log Strategy can “virtually dominate” in a moderate number of plays in cases when risk is low.
Leadership: A Frame of Reference
Authors: Tannenbaum Robert , Massarik Fred
Published: November 2008

The word “leadership” has been widely used. Political orators, business executives, social workers, and scholars employ it in speech and writing. Yet, there is widespread disagreement as to its meaning. Among social scientists, the theoretical formulations of the leadership concept have continued to shift, focusing first upon one aspect and then upon another. Much still needs to be done to develop a basic, systematic theory. The time seems ripe for attempting a careful statement of a frame of reference which may serve to make available research more meaningful, and which may guide future research and practice. Specifically, such a frame of reference can perform the useful function of pointing to the variables which need to be measured. It can help us to state hypotheses concerning the key variables underlying leadership effectiveness. It can also provide meaningful objectives for the development of more adequate leaders.
Communication Networks in Intermediate Markets
Authors: Balderston F. E.
Published: November 2008

Most commodities move from points of production through successive stages of processing or manufacture and further stages of intermediate distribution before reaching points of final purchase. The final value of a commodity, in fact, is often analyzed by observing the amounts of labor and capital services that are added to it at each of these stages by the firm which owns it at each stage.

The setting of the problem is this. Successive stages of dealing in a commodity are in general required on account of any of the following considerations: a) an activity may need to be undertaken at a different scale—i.e., plant size—than that at which a preceding or a succeeding activity needs to be conducted; b) changes in the combinations of commodities may be required from one stage to another; or c) information and contacts need to be mobilized in order to connect disparate groups of actors in the complex of activities.
The Use of a Large Scale Computer for Manufacturing Control
Authors: Carlin F. C.
Published: November 2008

Considerations which led to the selection of scientific Computers in preference to a business machine Data Processor for the preparation of Shop Orders, Scheduling and Control of Stock Status. Problems faced relative to the use of scientific Computers to handle large volumes of input and output data. Practical operating difficulties faced in the joint use of a Computer by Engineering and Accounting personnel. Problems encountered in attempting to capitalize to the maximum on the computer's potential capabilities. Advantage of having the programming and coding of a problem vested in one group of personnel. Management benefits accruing from the use of the Computer.
Notes on the Theory of Dynamic Programming—Transportation Models
Authors: Bellman Richard
Published: November 2008

The purpose of this paper is to illustrate some applications of the functional equation technique of the theory of dynamic programming to a general class of problems arising in the study of networks, particularly those arising in transportation theory.
Cost Horizons and Certainty Equivalents: An Approach to Stochastic Programming of Heating Oil
Authors: Charnes A. , Cooper W. W. , Symonds G. H.
Published: November 2008

Scheduling heating oil production is an important management problem. It is also a complex one. Weather and demand uncertainties, allocation of production between different refineries, joint- and by-product relations, storage limitations, maintenance of minimal supplies and many other factors need to be considered.

This paper is concerned with one of an integrated series of operations research studies directed toward improvement in such scheduling methods. Emphasis is on essentials of the mathematical model. Institutional features and other phases of the OR studies are brought in only as required.
Operating Flexibility, Global Manufacturing, and the Option Value of a Multinational Network
Authors: Kogut Bruce , Kulatilaka Nalin
Published: November 2008

The multinational corporation is a network of activities located in different countries. The value of this network derives from the opportunity to benefit from uncertainty through the coordination of subsidiaries which are geographically dispersed. We model this coordination as the operating flexibility to shift production between two manufacturing plants located in different countries. A stochastic dynamic programming model treats explicitly this flexibility as equivalent to owning an option, the value of which is dependent upon the real exchange rate. The model is extended to analyze hysteresis effects and within-country growth options. We show that the management of across-border coordination has led to changes in the heuristic rules used for performance evaluation and transfer pricing.
International Diversification of Investment Portfolios: U.S. and Japanese Perspectives
Authors: Eun Cheol S. , Resnick Bruce G.
Published: November 2008

In this paper, we analyze the gains from international diversification of investment portfolios from the Japanese as well as the U.S. perspectives. The major findings of this paper include: First, the ‘potential’ gains from international, as opposed to purely domestic, diversification are much greater for U.S. investors than for Japanese investors. For U.S. investors, the gains accrue not so much in terms of lower risk as in terms of higher return, and the opposite holds for Japanese investors. Second, using various ‘ex ante’ international investment strategies designed to control parameter uncertainty, U.S. investors can realize substantial gains from international diversification in out-of-sample periods. Japanese investors, however, can gain relatively little. Third, hedging exchange risk generally allows the U.S., but not Japanese, investors to benefit more from international diversification. For U.S. investors, the international bond diversification with exchange risk hedging offers a superior risk-return trade-off than the international stock diversification, with or without hedging.
A Tabu Search Heuristic for the Vehicle Routing Problem
Authors: Gendreau Michel , Hertz Alain , Laporte Gilbert
Published: November 2008

The purpose of this paper is to describe TABUROUTE, a new tabu search heuristic for the vehicle routing problem with capacity and route length restrictions. The algorithm considers a sequence of adjacent solutions obtained by repeatedly removing a vertex from its current route and reinserting it into another route. This is done by means of a generalized insertion procedure previously developed by the authors. During the course of the algorithm, infeasible solutions are allowed. Numerical tests on a set of benchmark problems indicate that tabu search out performs the best existing heuristics, and TABUROUTE often produces the best known solutions.
Impact of Electronic Data Interchange Technology on JIT Shipments
Authors: Srinivasan Kannan , Kekre Sundar , Mukhopadhyay Tridas
Published: November 2008

We investigates the degree to which increasing vertical information integration using Electronic Data Interchange technology enhances shipment performance of suppliers in a Just-in-Time environment. Our analysis of shipment data in the automobile industry suggests that shipment performance degrades substantially due to increases in part variety and trading partners from diverse industries. However, investments in information technology to support both the sharing of JIT schedules and the establishment of integrated information links are related to significant reduction in the level of shipment discrepancies.
Learning and Efficiency in a Gambling Market
Authors: Dana James D. , Knetter Michael M.
Published: November 2008

We present a statistical model which uses data on National Football League games and betting lines to study how agents learn from past outcomes and to test market efficiency. Using Kalman Filter estimation, we show that terms' abilities exhibit substantial week-to-week variation during the season. This provides an ideal environment in which to study how agents learn from past information. While we do not find strong evidence of market inefficiency, we are able to make several observations on market learning. In particular, agents have more difficulty learning from “noisy” observations and appear to weight recent observations less that our statistical model suggests is optimal.
Dominance Relations Among Standardized Variables
Authors: Milne Frank , Neave Edwin H.
Published: November 2008

This paper examines stochastic dominance relations among discrete random variables defined on a common integer domain. While these restrictions are minimal, they lead both to new theoretical results and to simpler proofs of existing one. The new results, obtained for dominance criteria of any degree, generalize an SSD result of Rothschild-Stiglitz to describe how for any dominance criterion a dominated variable is equal in distribution to a dominated variable plus perturbation terms. If the variables are comparable under FSD the perturbations are downward shift terms, while under SSD (TSD) all but two (three) of the perturbations are zero mean disturbance terms (noise). Under SSD the remaining perturbations are shift terms and under TSD noise and shift terms. However, under either SSD or TSD these remaining terms are identically zero if the variables to be compared have equal means. The paper also finds new proofs of well known results relating dominance criteria to preferences.
Note: The Impact of Leadtime and Years of Competitive Rivalry on Pioneer Market Share Advantages
Authors: Huff Lenard C. , Robinson William T.
Published: November 2008

Research has established that for surviving brands, market pioneers have a higher average market share than later entrants. By moving first, market pioneers often develop sustainable market share advantages. Longer leadtime, which is the time between entries, should increase these pioneer advantages. Using two leadtime measures, this prediction is supported across 34 categories of frequently purchased consumer goods. Increasing the years of competitive rivalry should help a later entrant slowly reduct the pioneer's market share advantage. After more than two decades in the market, second entants have eliminated the pioneer's market share advantage, but third and later entrants continue to trail the pioneer.
Stimulating Ideas Through Creative Software
Authors: MacCrimmon Kenneth R. , Wagner Christian
Published: November 2008

A central task of management is decision making and a crucial aspect of decision making is having good alternatives from which to choose. This paper investigates whether computer-based procedures for idea generation can help individuals to develop solution alternatives more creatively. Our conceptual framework considers creative processes, environments, outputs, and individuals. In particular, generating alternatives is viewed as a process of “making connections” —internal connections among problem elements and external connections between a problem and its environment. We have developed a computer program (GENI) which incorporates a variety of techniques to assist in making these different types of connections. The program is described and an experimental test with several managerial problems is presented. The results show that use of the program leads to the development of significantly more creative alternatives than does a control treatment. There is an amplification effect in that the performance of the more creative individuals is improved the most. Thus the findings suggest that computerized idea generation leads to more creative alternatives resulting in potentially better managerial decisions.
Stochastic Optimization by Simulation: Convergence Proofs for the GI/G/1 Queue in Steady-State
Authors: L'Ecuyer Pierre , Glynn Peter W.
Published: November 2008

Approaches like finite differences with common random numbers, infinitesimal perturbation analysis, and the likelihood ratio method have drawn a great deal of attention recently as ways of estimating the gradient of a performance measure with respect to continuous parameters in a dynamic stochastic system. In this paper, we study the use of such estimators in stochastic approximation algorithms, to perform so-called “single-run optimizations” of steady-state systems. Under mild conditions, for an objective function that involves the mean system time in a GI/G/1 queue, we prove that many variant of these algorithms converge to the minimizer. In most cases, however, the simulation length must be increased from iteration to iteration, otherwise the algorithm may converge to the wrong value. One exception is a particular implementation of infinitesimal perturbation analysis, for which the single-run optimization converges to the optimum even with a fixed (and small) number of ends of service per iteration. As a by-product of our convergence proofs, we obtain some properties of the derivative estimators that could be of independent interest. Our analysis exploits the regenerative structure of the system, but our derivative estimation and optimization algorithms do not always take advantage of that regenerative structure. In a companion paper, we report numerical experiments with an M/M/1 queue, which illustrate the basis convergence properties and possible pitfalls of the various techniques.
Metagraphs: A Tool for Modeling Decision Support Systems
Authors: Basu Amit , Blanning Robert W.
Published: November 2008

Most decision support systems (DSS) contain stored data, data analysis procedures, and decision models. However, many DSS have grown to the point that the average end user is presented with a bewildering array of information resources that are difficult to manage in an effective manner. As a result users often gravitate to a few familiar models and are unaware of the data resources available to them and how these resources relate to the various models. For example, they may think that a model requires data that is unavailable, when in fact that data has recently been added to the data base or could be calculated from another model. Or they may believe that all of the data needed to execute a set of models is available and find out well into the analysis that it is not. Existing tools for DSS design do not provide an effective and comprehensive foundation for modeling all the components of a DSS, or for addressing all the important DSS analysis and design issues. In this paper we show how a new graph-theoretic structure, called a metagraph, can be used as a unifying basis for addressing many important questions in DSS development and use.
Information Assets, Technology and Organization
Authors: Brynjolfsson Erik
Published: November 2008

Although there is good reason to expect that the growth of information work and information technology will significantly affect the trade-offs inherent in different structures for organizing work, the theoretical basis for these changes remains poorly understood. This paper seeks to address this gap by analyzing the incentive effects of different ownership arrangement in the spirit of the Grossman-Hart-Moore (GHM) incomplete contracts theory of the firm. A key departure from earlier approaches is the inclusion of a role for an “information asset,” analogous to the GHM treatment of property. This approach highlights the organizational significance of information ownership and information technology. For instance, using this framework, one can determine when 1) informed workers are more likely to be owners than employees of firms, 2) increased flexibility of assets will facilitate decentralization, and 3) the need for centralized coordination will lead to centralized ownership. The framework developed sheds light on some of the empirical findings regarding the relationship between information technology and firm size and clarifies the relationship between coordination mechanisms and the optimal distribution of asset ownership. While many implications are still unexplored and untested, building on the incomplete contracts approach appears to be a promising avenue for the careful, methodical analysis of human organizations and the impact of new technologies.
Fortune Favors the Prepared Firm
Authors: Cohen Wesley M. , Levinthal Daniel A.
Published: November 2008

A critical factor in industrial competitiveness is the ability of firms to exploit new technological developments. We term this ability a firm's absorptive capacity and argue that such a capability not only enables a firm to exploit new extramural knowledge, but to predict more accurately the nature of future technological advances. We develop a stylized model in which we focus exclusively on firms' decisions to invest in their absorptive capacities. We first examine a monopolist's investment decision, analyzing the path dependence of its investment and the effect of uncertainty. We then consider the effect of competition by modeling the impact of entry on an incumbent's investment behavior. Implications for management and public policy are then discussed.
Do People Rely on the Self-Interested Maximization of Others? An Experimental Test
Authors: Beard T. Randolph , Beil Richard O.
Published: November 2008

The assumption that agents engage in maximizing behavior, while ubiquitous in economic theory, differs from the assumption that agents are willing to rely on the maximizing behavior of others. This paper offers an empirical examination of this distinction using experimental methods. Utilizing a series of experimental treatments based on a simple, two player extensive form game of perfect information, we find strong evidence that apparently rational people are often unwilling to rely on the self-interested behavior of others, despite the observed near universality of maximizing play.
Multiple-Shift Workforce Scheduling Under the 3–4 Workweek with Different Weekday and Weekend Labor Requirements
Authors: Hung Rudy
Published: November 2008

Novel workweek arrangements have gained acceptance in many seven-days-a-week operations, such as hospitals and data processing centers. This note considers a multiple-shift workforce scheduling scenario for seven-days-a-week operations under a workweek arrangement called the 3–4 workweek. Our model seeks to minimize the workforce size subject to satisfying staffing requirements and workrules relating to off-days, off-weekends, and work-stretches. We provide an efficient optimal algorithm which is intuitive and simple enough to be implemented by hand.
Modeling Competitive Bidding: A Critical Essay
Authors: Rothkopf Michael H. , Harstad Ronald M.
Published: November 2008

In analyzing bidding, modeling matters. This paper is a critical analysis of the models available to aid competitive bidding decision making—bidding strategy and auction design—in real transactions. After an introductory overview, this paper describes the contexts in which auctions arise, reviews the “mainstream” theory of single, isolated auctions and discusses the important work involved in enrichment of this theory. In doing so, it indicates results that have been obtained and the sort of changes in analytical approach that are needed to tackle other critical enrichments. The paper summarizes briefly what is known about the direct use of models by bidders and auction designers. A general theme of this paper is that enriched models are needed to bring bidding theory closer to direct applicability in decision making.
Transient Analysis of a Two-Unit Standby System with Markovian Degrading Units
Authors: Van der Duyn Schouten Frank A. , Wartenhorst Pieter
Published: November 2008

A two-unit cold standby system with Markovian degrading units and one repair facility is considered. Two types of repair are possible: preventive and corrective, where the latter is supposed to be more time consuming than the first. The system is controlled by a repair policy of control limit type: a preventive repair on the working unit is carried out as soon as the state of this unit exceeds a certain threshold unless the repair facility is occupied by the other unit. In this paper we derive explicit expressions for the Laplace transforms of the up- and down-periods of this system, which provide insight in the availability of the system and which can be used to obtain approximations for the interval availability distribution. An iterative numerical procedure is presented for the special case of generalized Erlangian distributed repair times.
Contract-Based Motivation for Keeping Records of a Manager's Reporting and Budgeting History
Authors: Arya Anil , Fellingham John C. , Young Richard A.
Published: November 2008

This paper analyzes the role of the agent's bankruptcy constraints in multiperiod principal-agent models with asymmetric information. Conditions are provided under which commitment to a long-term contract involving N rounds of investment improves upon repetition of N identical single-period contracts. Further, when the agent's reservation wage is sufficiently low the optimal contract is always long term. Keeping records of a manager's history of reporting activity facilitates contracting, since optimal contracts may require a link between past reports and future investments over a duration of two or more periods.
A Network Model to Maximize Navy Personnel Readiness and Its Solution
Authors: Krass Iosif A. , Pinar Mustafa Ç. , Thompson Theodore J. , Zenios Stavros A.
Published: November 2008

The problem of optimally (re)allocating Navy personnel to combat units is compounded by several considerations: availability of trained personnel, staffing of positions by occupation groups or ranks, and maintaining an acceptable level of readiness. In this paper we model this problem as a nonlinear nondifferentiable optimization problem. A reformulation of the nonlinear optimization problem as a network flow problem is then developed. The formulation results in a network flow problem with side constraints. An additional, nonnetwork, variable measures the readiness level. This new formulation permits the use of network optimization tools in order to solve effectively very large problems.

We then develop two numerical methods for solving this problem. One method is based on a heuristic that solves (approximately) the nondifferentiable problem. The second method is based on a Linear-Quadratic Penalty (LQP) algorithm, and it exploits the embedded network structure by placing the side constraints into the objective function. The resulting nonlinear network program is solved using a simplicial decomposition of the network constraint set. Numerical results indicate the viability of this approach on problems with up to 36,000 arcs and 17,000 nodes with 3,700 side constraints.
Rule Management in Expert Database Systems
Authors: Segev Arie , Zhao J. Leon
Published: November 2008

Expert database systems combine database and expert systems technologies to support the effective management of both rules and data. This paper studies rule processing strategies in expert database systems involving rules that are conditional on joins of relational data. Auxiliary constructs for processing join rules are proposed, and a framework of join rule processing strategies is developed. Cost functions of several strategies are derived based on a stochastic model that characterizes the arrival processes of transactions and queries to the database. Performance evaluation shows that the proposed data constructs and strategies provide an effective method for processing rules.
An Analysis of the Risk in Discretely Rebalanced Option Hedges and Delta-Based Techniques
Authors: Robins Russell P. , Schachter Barry
Published: November 2008

The stochastic properties of discretely rebalanced option hedges have been studied extensively beginning with Black and Scholes (1973). In each analysis hedges were “delta-neutral” after rebalancing. We argue that the distributional properties of discretely rebalanced hedges are such that delta-based hedging is not the variance minimizing strategy. This paper obtains analytical expressions for the variance minimizing option hedge ratios. We also evaluate the hedge variance to assess the magnitude of the variance reduction over delta-based hedges. For representative parameter values, we show that systematic departures from delta-based hedges can yield significant reductions in hedge variance even for one day rebalancing intervals.
Competitive Pricing by a Price Leader
Authors: Roy Abhik , Hanssens Dominique M. , Raju Jagmohan S.
Published: November 2008

We examine the problem of pricing in a market where one brand acts as a price leader. We develop a procedure to estimate a leader's price rule, which is optimal given a sales target objective, and allows for the inclusion of demand forecasts. We illustrate our estimation procedure by calibrating this optimal price rule for both the leader and the follower using data on past sales and prices from the mid-size sedan segment of the U.S. automobile market. Our results suggest that a leader-follower system (Stackelberg) seems more consistent with the pricing behavior in this market, than a mutually independent pricing rule (Nash). We also find that our optimal price rule explains this market data better than other pricing schemes that do not account for optimizing behavior on the part of the leader and the follower.
A Decision Support Software on Bidding for Job Interviews in College Placement Offices
Authors: Lau Hon-Shiang , Kletke Marilyn G.
Published: November 2008

Many university placement offices employ a bidding system to allocate on-campus recruiter interview slots to students. Typically, a student is given (say) 700 points each week to bid on the firms visiting that week. Interview slots for each firm are assigned beginning with the highest bidder until all slots are filled. This paper describes the mathematical modeling behind a decision support system for helping students to bid in such a system. It has three components. The first component elicits a student's utilities of getting an interview with the various firms. The second component estimates the probability of getting an interview with a particular firm for a given bid amount. The final component considers our bidding problem as the maximization of a student's expected utility, which can be formulated as a nonlinear integer programming (IP) problem. It is shown that this IP problem can be transformed into a number of nonlinear programming problems without integer requirements, which can then be solved very rapidly to give on-line bidding recommendations to a large number of students.
A Rigorous Computational Comparison of Alternative Solution Methods for the Generalized Assignment Problem
Authors: Amini Mohammad M. , Racer Michael
Published: November 2008

Statistical experimental design and analysis is a cornerstone for scientific inquiry that is rarely applied in reporting computational testing. This approach is employed to study the relative performance characteristics of the four leading algorithmic and heuristic alternatives to solve the Linear Cost Generalized Assignment Problem (LCGAP) against a newly developed heuristic, Variable-Depth Search Heuristic (VDSH). In assessing the relative effectiveness of the prominent solution methodologies and VDSH under the effects of various problem characteristics, we devise a carefully designed experimentation of state-of-the-art implementations; through a rigorous statistical analysis we identify the most efficient method(s) for commonly studied LCGAPs, and determine the effect on solution time and quality of problem class and size.
Strategies for Combining Antithetic Variates and Control Variates in Designed Simulation Experiments
Authors: Kwon Chimyung , Tew Jeffrey D.
Published: November 2008

In this paper we examine three methods for combining the variance reduction techniques of antithetic variates and control variates to estimate the mean response in a designed simulation experiment. In Combined Method I, we perform h independent pairs of simulation runs as follows—on the second run of each such pair, we use random number streams that are antithetic (complementary) to the streams used on the first run of the pair to drive the non-control-variate components of the simulation model; and we use independent random number streams to drive the control-variate components of the simulation model. In Combined Method II, we also perform h independent pairs of runs; but on each pair of runs we use independent random number streams to drive the non-control-variate model components, and we use antithetic random number streams to drive the control-variate components. In Combined Method III, all of the random number streams driving the second run of each pair of runs are antithetic to the streams driving the first run of the pair. For each of these three methods we drive the variance of the resulting estimator of the mean response to make a theoretical comparison of the efficiency of each method. We implemented these three methods, along with the classical method of control variates, in a simulation model of a resource-constrained activity network to show how each combined method is implemented in practice and to evaluate the performance of each combined method experimentally. The results indicate that: (a) Combined Method III outperformed all other methods, and (b) the effectiveness of Combined Method III as well as the choice of whether to use Combined Method I or Combined Method II depends on the degree of correlation between the control variates and the response.
Investment in Knowledge: A Generalization of Learning By Experience
Authors: Dorroh James R. , Gulledge Thomas R. , Womer Norman K.
Published: November 2008

Learning is often perceived as a cost-reducing endogenous by-product of production processes. In many applications this by-product is modeled as a learning curve; that is, a simple function of time or of cumulative production experience. In an earlier paper we presented an alternative explanation where managers decide what resources to devote to knowledge acquisition. In this paper we expand those results to a situation using a more flexible production technology and emphasizing discounted cost. Our model explains resource and output behavior for a firm that is producing specialized units to contractual order. However, the results are quite general and have implications for investment in research, engineering, science and technology, software development, and worker training. We provide examples where the cost-minimizing producer will choose to invest in knowledge creation early in the production program and then have the rate of investment decline over time. Other interesting results are noted by examining the optimal time paths of the control and state variables in a comparative dynamic analysis.
Incentive Efficient Production Frontiers: An Agency Perspective on DEA
Authors: Bogetoft Peter
Published: November 2008

In this paper, we examine how empirical production frontiers may contribute to the incentives of production units. We consider a series of Data Envelopment Analysis (DEA) frontiers, and we show when these may be incentive efficient in the sense that they contain all the information that are relevant for optimal incentive provision. The frontiers considered include the so-called constant, decreasing and varying return to scale models, the free disposability and the free replicability models, as well as the increasing and decreasing return to scale models based on a relaxed set of assumptions. Also, we illustrate how to design optimal incentive schemes based on such frontiers.

Contents: 1. Introduction, 2. The Incentive Problem, 3. Production Frontiers and Productivity Measures, 4. Incentive Efficient Production Frontiers, 5. Extensions, 6. An Example, 7. Final Remarks, Mathematical Appendix, References.
Optimal Dynamic Pricing of Inventories with Stochastic Demand over Finite Horizons
Authors: Gallego Guillermo , van Ryzin Garrett
Published: November 2008

In many industries, managers face the problem of selling a given stock of items by a deadline. We investigate the problem of dynamically pricing such inventories when demand is price sensitive and stochastic and the firm's objective is to maximize expected revenues. Examples that fit this framework include retailers selling fashion and seasonal goods and the travel and leisure industry, which markets space such as seats on airline flights, cabins on vacation cruises, and rooms in hotels that become worthless if not sold by a specific time.

We formulate this problem using intensity control and obtain structural monotonicity results for the optimal intensity (resp., price) as a function of the stock level and the length of the horizon. For a particular exponential family of demand functions, we find the optimal pricing policy in closed form. For general demand functions, we find an upper bound on the expected revenue based on analyzing the deterministic version of the problem and use this bound to prove that simple, fixed price policies are asymptotically optimal as the volume of expected sales tends to infinity. Finally, we extend our results to the case where demand is compound Poisson; only a finite number of prices is allowed; the demand rate is time varying; holding costs are incurred and cash flows are discounted; the initial stock is a decision variable; and reordering, overbooking, and random cancellations are allowed.
Coordinating Buyer-Seller Transactions Across Multiple Products
Authors: Kohli Rajeev , Park Heungsoo
Published: November 2008

Joint ordering policies are examined as a method for reducing the transactions cost for multiple products sold by a seller to a homogeneous group of buyers. The problem of determining efficient joint ordering policies has the same structure as the previously-examined problem of determining the efficient ordering policy for a single product. Efficient joint lot-sizes are independent of prices, and are supported by a range of average-unit prices that permit every possible allocation of the transactions-cost saving between the buyer and the seller. Product bundling supports efficient joint orders across products, just as a quantity discount supports efficient transactions for a single product.
Modeling Goes to Hollywood: Predicting Individual Differences in Movie Enjoyment
Authors: Eliashberg Jehoshua , Sawhney Mohanbir S.
Published: November 2008

Consumer behavior researchers are getting more interested in the experiential aspect of consumption, which focuses on the fun and enjoyment that consumers derive from hedonic experiences. We build upon the experiential view of consumer behavior, and present an innovative modeling approach to studying the dynamics of hedonic consumption experiences. We develop a conceptual framework for the enjoyment of a hedonic experience, in which we propose that the enjoyment of the experience is an outcome of the dynamic interaction between stable individual difference factors, temporary moods, and the emotional content of the experience. We present an application of the conceptual framework in the context of a movie viewing experience. We model the interaction between the temporary moods of an individual and the emotional content of the movie as a stochastic process. This interaction determines the individual's instantaneous emotional states. We develop analytical expressions for the dynamic evolution of the probability distribution of the levels of achieved emotional stimulation, and, through individual difference factors, the expected enjoyment. All measurements are taken prior to watching the movie. We use these measurements to predict individual differences in the ex-post enjoyment of the movie. We present an empirical test of the movie enjoyment model (ENJMOD), and find encouraging results at the individual and segment level. We discuss the implications of our modeling approach for the segmentation and testing of movies, and for the prediction of consumer response to similar experiential products.
Optimal Mean-Squared-Error Batch Sizes
Authors: Song Wheyming Tina , Schmeiser Bruce W.
Published: November 2008

When an estimator of the variance of the sample mean is parameterized by batch size, one approach for selecting batch size is to pursue the minimal mean squared error (mse). We show that the convergence rate of the variance of the sample mean, and the bias of estimators of the variance of the sample mean, asymptotically depend on the data process only through its marginal variance and the sum of the autocorrelations weighted by their absolute lags. Combining these results with variance results of Goldsman and Meketon, we obtain explicit asymptotic approximations for mse, optimal batch size, optimal mse, and robustness for four quadratic-form estimators of the variance of the sample mean.

Our empirical results indicate that the asymptotic approximations are reasonably accurate for sample sizes seen in practice. Although we do not discuss batch-size estimation procedures, the empirical results suggest that the explicit asymptotic batch-size approximation, which depends only on a summary measure (which we refer to as the balance point) of the nonnegative-lag autocorrelations, is a reasonable foundation for such procedures.
Optimal Monopolist Pricing Under Demand Uncertainty in Dynamic Markets
Authors: Raman Kalyan , Chatterjee Rabikar
Published: November 2008

We examine pricing policy for a monopolist facing uncertain demand in a market characterized by dynamics on the demand side (such as diffusion or saturation effects) and/or on the cost side (experience curve effects). Our model explicitly incorporates the impact of demand uncertainty, and thus allows us to analyze the implications of uncertainty on the optimal price path, by contrasting the stochastic policy with the corresponding deterministic policy. We begin with an analysis of the general model and then focus on several special cases based on well known demand specifications to gain more specific insights and to suggest directional guidelines for dynamic pricing decisions in an uncertain environment. In general, the interaction among uncertainty, demand and/or cost dynamics, and firm's discount rate. Thus, farsighted firms operating under dynamic market conditions with high demand uncertainty, such as high tech companies with innovative products for consumer or industrial markets, should attach particular importance to the formal consideration of uncertainty in their long term pricing decisions.
The Crucial Interrelationship Between Manufacturing Strategy and Organizational Culture
Authors: Bates Kimberly A. , Amundson Susan D. , Schroeder Roger G. , Morris William T.
Published: November 2008

This paper proposes a relationship between manufacturing strategy and organizational culture, based on an examination of the research literature. Survey data were collected from 822 respondents in 41 plants in the transportation, electronics, and machinery industries in the U.S. These plants included random samples of U.S.-owned and Japanese-owned manufacturers in the U.S., and manufacturers reputed to use advanced manufacturing practices. Analysis indicates that manufacturing strategy and organizational culture are related, and that a manufacturer with a well-aligned and implemented manufacturing strategy exhibits a collectivist or group-oriented organizational culture with coordinated decision making, decentralized authority, and a loyal work force.
A Psychological Perspective on Service Segmentation Models: The Significance of Accounting for Consumers’ Perceptions of Waiting and Service
Authors: Carmon Ziv , Shanthikumar J. George , Carmon Tali F.
Published: November 2008

We examine how service should be divided and scheduled when it can be provided in multiple separate segments. We analyze variants of this problem using a model with a conventional function describing the waiting cost, that is modified to account for some aspects of the psychological cost of waiting in line. We show that consideration of the psychological cost can result in prescriptions that are inconsistent with the common wisdom of queuing theorists derived according to the conventional approach (e.g., equal load assignments). More generally, our intention in this paper is to illustrate that aspects of the psychological cost of waiting can be accounted for in the analysis of queuing systems, and that this may have significant implications for the service schemes that are derived.
Operational Control of the Transportation of Hazardous Materials: An Assessment of Alternative Decision Models
Authors: Beroggi Giampiero E. G. , Wallace William A.
Published: November 2008

Commercially available tracking systems based on advanced communications and computing technology allow a dispatcher of hazardous material transports to monitor the movement of vehicles on a transportation network in real time. When unexpected events occur, a dispatcher working with this new technology can identify the regions surrounding the transportation network that are affected by these events and determine safe and cost-effective routes for the vehicles that plan to drive through those regions. Four decision models for rerouting hazardous material vehicles in real-time have been assessed in an experimental setting. The first model supports a dispatcher in finding alternative routes (visually), while the second model adds to the display, for each vehicle, an alternative route based on a conservative heuristic. The other two models are based on an ordinal preference and a numerical utility structure to support the dispatcher in determining the impact of the events on transportation safety and costs. The models were embedded into four decision support systems that use multimedia technology to simulate the dispatchers workstations. These systems were then used in an experiment at the dispatching school in Wil, Switzerland, with 32 experienced dispatchers and truck drivers to assess efficiency and accuracy of the four models. The results show that assessing risks and costs with the ordinal preference structure, prior to making routing decisions, is significantly more efficient and accurate than searching directly for new routes. Using a numerical scale for safety and cost assessment was disliked by the subjects and led to inferior results.
An Analytical Process Model of Two-Party Negotiations
Authors: Balakrishnan P. V. (Sundar) , Eliashberg Jehoshua
Published: November 2008

There has been a call to investigate the negotiation process (Gale [Gale, D. 1986. Bargaining and competition part I: Characterization. Econometrica 54(4) 785–806.], Shubik [Shubik, M. 1982. Game Theory in the Social Sciences: Concepts and Solutions. M. I. T. Press, Boston, MA.]), as it is felt that this would yield important insights beyond those obtained by outcome-oriented theories (Roth [Roth, A. E. 1979. Axiomatic Models of Bargaining. Springer-Verlag.]). This paper proposes a new analytical process model that captures both behavioral and economic aspects related to two-party negotiations. The proposed model, inspired by Pruitt's (Pruitt, D. G. 1981. Negotiation Behavior. Academic Press, New York.) work, explicitly incorporates concepts which are both relevant and crucial, such as the negotiators' power, concession points, aspiration level, limit, and time pressure. Based on this process model, it is possible to predict (1) conditions under which agreements will not be reached despite the existence of a zone of agreement, (2) conditions under which agreements will be reached, and (3) the patterns of the negotiators' offers and counteroffers.
An Experimental Study of Buyer-Seller Negotiation with One-Sided Incomplete Information and Time Discounting
Authors: Rapoport Amnon , Erev Ido , Zwick Rami
Published: November 2008

We study a multiperiod bargaining mechanism in which a seller negotiates with a buyer over the price of an indivisible good. It is common knowledge that the good has zero value to the seller. Its value to the buyer is privately known, distributed independently of the seller’s value according to a distribution that is common knowledge. Bargaining proceeds as follows. The seller sets a price and offers the buyer an opportunity to purchase the good. The buyer either waits for at least one more period or agrees to purchase the good at the given price. If the buyer refuses the offer, then the process is repeated with seller making a new offer on the next period. Our findings reveal several behavioral regularities, which do not support the sequential equilibrium for this bargaining mechanism. In line with recent developments in behavioral decision theory and game theory, which assume bounded rationality, we find that subjects follow simple rules of thumb in choosing strategies, reflected in the behavioral consistencies observed in the study.
Chance Constrained Efficiency Evaluation
Authors: Olesen O. B. , Petersen N. C.
Published: November 2008

A model for efficiency evaluation based upon the theory of chance constrained programming is developed. The model uses a piecewise linear envelopment of confidence regions for observed stochastic multiple-input multiple-output combinations in the Data Envelopment Analysis (DEA) tradition. The model allows for an exogenous decomposition of the total variation in data for each Decision Making Unit (DMU). By varying certain probability levels the model can provide estimates of the sensitivity of efficiency scores regarding an unknown amount of noise in date. An application of the method in an evaluation of the research activities in economic departments at Danish Universities is presented.