bluuebunny/crossref_metadata_2025 huggingface dataset:
A Taxonomy of Manufacturing Strategies
Authors: Miller Jeffrey G. , Roth Aleda V.
Published: November 2008

This paper describes the development and analysis of a numerical taxonomy of manufacturing strategies. The taxonomy was developed with standard methods of cluster analysis, and is based on the relative importance attached to eleven competitive capabilities defining the manufacturing task of 164 large American manufacturing business units.

Three distinct clusters of manufacturing strategy groups were observed. Though there is an industry effect, all three manufacturing strategy types are observed in various industries. The two main dimensions along which the manufacturing strategy groups differ are the ability of the firms in them to differentiate themselves from competition with their products and services, and the scope of their product lines and markets. A general method for mapping manufacturing strategies on these dimensions is described. For each manufacturing group, the relationships between the competitive capabilities (which describe the manufacturing task), the business context (the business unit strategy), manufacturing activities (manufacturing strategy choices), and manufacturing performance measures are explored and compared.
Multi-Echelon vs. Single-Echelon Inventory Control Policies for Low-Demand Items
Authors: Hausman Warren H. , Erkip Nesim K.
Published: November 2008

Multi-echelon inventory systems are often controlled as a network of single-echelon inventory systems for simplicity of managerial authority, organizational control, and performance monitoring. This paper explores the amount of suboptimization in such a situation, using an actual demand data set provided by other researchers. We consider low-demand, high-cost items controlled on an (S − 1, S) basis, with all warehouse stockouts met on an emergency-ordering basis. We demonstrate that the suboptimality penalty for this data set is 3% to 5% when single-echelon systems are appropriately parameterized.
The Effect of Leadtime Uncertainty in a Simple Stochastic Inventory Model
Authors: Song Jing-Sheng
Published: November 2008

We study a basic continuous-time single-item inventory model where demands form a compound Poisson process and leadtimes are stochastic. The performance measure of interest is the long-run average cost. Order costs are linear, so a base-stock policy is optimal. We focus on the behavior of the optimal base-stock level in response to stochastically larger or more variable leadtimes. We also investigate the behavior of the corresponding long-run average costs. We show that a stochastically larger leadtime requires a higher optimal base-stock level. However, a stochastically larger leadtime may not necessarily result in a higher optimal average cost, because sometimes the variability effects may dominate. On the other hand, a more variable leadtime always leads to a higher optimal average cost. The effect of leadtime variability on optimal policies depends on the inventory cost structure: A more variable leadtime requires a higher optimal base-stock level if and only if the unit penalty (holding) cost rate is high (low).

Similar results regarding the effect of leadtime demand are also discussed. In this latter case, the compound Poisson assumption is not necessary.
Tatonnement Procedures for Linearly Constrained Convex Optimization
Authors: Kallio Markku , Salo Seppo
Published: November 2008

The emphasis in this article is to exploit the fact that precision requirements for solutions of most economic models in practice are moderate only. A simple approach is introduced for solving linearly constrained partial equilibrium models based on an iterative scheme similar to the simplex method. It allows large-scale models to be solved, within a practical tolerance, efficiently even in a micro computer environment. Extensions to linearly constrained convex optimization problems are presented. Finally, a set of computational tests on 68 linear programs from the NETLIB library is reported. Comparison of our approach with the simplex method (using MINOS 5.1) and with Karmarkar's algorithm is reported. For moderate precision requirements these preliminary results are highly encouraging.
Meta-Modeling Concepts and Tools for Model Management: A Systems Approach
Authors: Muhanna Waleed A. , Pick Roger Alan
Published: November 2008

We present a new framework for model management based on system concepts and theory. Underlying the framework is a set of meta-modeling concepts that are useful in capturing the semantics of the modeling process in a modeling environment. These concepts include the notions of a general-model type, type specialization, atomic and composite model versions, model instances, and parameterized versions. We describe these concepts both conceptually and formally and then briefly present a Model Description Language (MDL) that embodies them. While other researchers have suggested some of these concepts primarily in different contexts, this paper makes at least four valuable contributions: (1) the identification of fundamental issues and principles related to model management; (2) the development and enhanced treatment of meta-modeling concepts specifically for model management; (3) the synthesis of those concepts into a coherent, unifying framework for model management; and (4) a demonstration of the practicality of those concepts through a prototype system implementation. Our framework proposes a graph-oriented, nonprocedural, and hierarchical approach for model composition. The framework also supports both model-solver independence and model-data independence. Moreover, it offers general solutions to two critical issues in model management: model-model linkage and model-data linkage. We argue that the system framework can serve as a guide for an effective design of a flexible and extensible model management system. An architecture of such a system and its prototype implementation—called SYMMS—are briefly described. Examples are presented to illustrate the features and advantages of our approach.
Solving Large-Scale Tour Scheduling Problems
Authors: Jarrah Ahmad I. Z. , Bard Jonathan F. , deSilva Anura H.
Published: November 2008

For a given planning horizon, workforce composition and set of labor requirements, personnel scheduling often reduces to solving three problems. The first is concerned with the assignment of days off; the second involves assigning workers to shifts during the day; and the third involves the construction of weekly tours. In many manufacturing facilities, tour scheduling is easy because the start and end times of shifts are invariant, and no work takes place on the weekend. But when daily patterns vary, such as in the airlines, processing, and public service industries, and when part-timers make up a portion of the workforce, the complexity of the overall problem increases dramatically.

This paper presents a new methodology for solving the combined shift and days-off scheduling problem when the labor requirements span less than 24 hours per day. We begin with an integer programming formulation and then introduce a set of aggregate variables and related cuts. When the aggregate variables are fixed the original problem decomposes into seven subproblems (one for each day of the week) that are much easier to solve. A partial enumeration scheme and a heuristic for ensuring feasibility are employed to find upper and lower bounds which converge rapidly to near-optima.

The methodology is applied to tour scheduling at general mail facilities (GMFs). These facilities are located in most urban areas and process millions of mail pieces daily for local and regional distribution. The model accounts for the principal constraints in the U.S. Postal Service labor contract, including half-hour breaks, minimum full-time to part-time ratios, and variable start times. Also considered are four and five day work weeks, and the possibility of assigning workers across labor categories. A full analysis of the Providence, Rhode Island facility is presented.
Efficient Estimation of Arc Criticalities in Stochastic Activity Networks
Authors: Bowman R. A.
Published: November 2008

An algorithm is described for estimating arc and path criticalities in stochastic activity networks by combining Monte Carlo simulation with exact analysis conditioned on node release times. These estimators are proved to be unbiased and to have lower variance than the corresponding standard Monte Carlo estimators. The algorithm is applied to a variety of standard and randomly generated test networks to establish that the estimators are significantly and robustly more efficient than the standard estimators when run time and statistical efficiency are properly combined.
Forecaster Diversity and the Benefits of Combining Forecasts
Authors: Batchelor Roy , Dua Pami
Published: November 2008

The expected error variance of a combined forecast is necessarily lower than that of an individual forecast, but in practice there may be considerable variation around these expected values. This paper introduces a measure of the benefit from combining, the probability of a reduction in error variance, which recognizes this problem. The measure is applied to data on the forecasts and forecasting methods of a panel of U.S. economists to determine how the benefits of combining vary with the number of forecasts combined, and with the diversity in theories and techniques among the component forecasts.
A Min Cost Flow Solution for Dynamic Assignment Problems in Networks with Storage Devices
Authors: Grossmann W. , Guariso G. , Hitz M. , Werthner H.
Published: November 2008

The paper presents a minimum-cost flow approach for dynamic assignment procedures for networks with storage devices over time. Decision variables are diversion of flow at specific nodes and the storage of material in buffers which have to meet upper and lower capacity constraints. Evaluation of a decision is based on utility functions which are assumed to be piecewise linear and concave. The solution is based on a transformation into a network flow problem as suggested by Kuczera (1989). The temporal dimension of the problem is handled by constructing a supergraph with a layer for each time period. These layers are connected by temporal arcs. Thus the problem can be solved entirely by well-known algorithms for the minimum-cost flow problem which yield the optimal solution and determine automatically whether a feasible solution exists or not. The complexity of the proposed algorithm is pseudopolynomial, i.e., linear in the size of the network (measured by nodes, arcs, and buffers), linear in the amount of inflow, and quadratic in the number of time periods under consideration.
Increasing Service Levels in Conference and Educational Scheduling: A Heuristic Approach
Authors: Sampson Scott E. , Weiss Elliott N.
Published: November 2008

This paper explores a technique for developing a conference (or class) schedule that maximizes the servicing of participant requests for sessions. Data regarding participant interests are collected before the time the schedule is generated. The problem contains two principal parts: (1) to feasibly assign session offerings to time periods and rooms, and (2) to assign participants to sections of multiple-offering sessions. A heuristic procedure that simultaneously solves both parts is described and tested. The procedure considers not only the participants’ requests for sessions, but also the relative importance of the various requests. Benefits of request prioritization are described. Results show that this approach can result in significantly improved participant satisfaction and equity when compared with traditional conference- and class-scheduling approaches.
Pricing a Class of American and European Path Dependent Securities
Authors: Hilliard Jimmy E. , Kau James B. , Keenan Donald C. , Muller Walter J.
Published: November 2008

Path dependent securities depend on current and past values of underlying state variables. Consequently, the usual backward evaluation technique is difficult to apply since state variable values existing earlier in real time are unknown. This paper develops a series of propositions which makes possible the pricing of a certain class of both American and European versions of these path dependent securities.
Using Common Random Numbers for Indifference-Zone Selection and Multiple Comparisons in Simulation
Authors: Nelson Barry L. , Matejcik Frank J.
Published: November 2008

We present a general recipe for constructing experiment design and analysis procedures that simultaneously provide indifference-zone selection and multiple-comparison inference for choosing the best among k simulated systems. We then exhibit two such procedures that exploit the variance-reduction technique of common random numbers to reduce the sample size required to attain a fixed precision. One procedure is based on the Bonferroni inequality and is guaranteed to be statistically conservative. The other procedure is exact under a specific dependence structure, but may be slightly liberal otherwise. Both are easy to apply, requiring only simple calculations and tabled constants. We illustrate the procedures with a numerical example.
Risk-Pooling Along a Fixed Delivery Route Using a Dynamic Inventory-Allocation Policy
Authors: Kumar Ashok , Schwarz Leroy B. , Ward James E.
Published: November 2008

This paper examines static and dynamic policies for replenishing and allocating inventories amongst N retailers located along a fixed delivery route. Each retailer faces independent, normally-distributed period demand and incurs a proportional holding or backorder cost on end-of-period net-inventory. A warehouse places a system-replenishment order every m periods which is received after a fixed leadtime of T periods. Immediately upon receipt, a delivery vehicle leaves the warehouse with the system-replenishment quantity and travels to the retailers along a fixed route with fixed leadtimes between successive retailers. The warehouse holds no inventory. Under the “static” policy, allocations are determined for all retailers simultaneously at the moment the delivery vehicle leaves the warehouse. Under the “dynamic” policy, allocations are determined sequentially upon arrival of the delivery vehicle at each retailer. Our major analytical results, under appropriate dynamic (static) allocation assumptions, are: (1) optimal allocations under each policy involve bringing each retailer's “normalized-inventory” to a corresponing “normalized” system inventory; (2) optimal system replenishments are base-stock policies; (3) the minimum expected cost per cycle of dynamic (static) policy can be derived from an equivalent dynamic (static) composite retailer. Given this, we prove that the “risk-pooling incentive”—a simple measure of the benefit from adopting dynamic allocation policies—is always positive. Our simulation tests confirm that dynamic allocation policies yield lower costs than static policies, regardless of whether or not their respective allocation assumptions are valid. However, the magnitude of the cost savings is very sensitive to some system parameters.
Optimal Operating Policy for a Bottleneck with Random Rework
Authors: So Kut C. , Tang Christopher S.
Published: November 2008

This paper presents a model of a bottleneck facility that performs two distinct types of operations: “regular” and “rework.” Each job is subjected to a test after completing the regular operation at the bottleneck. If the job passes the test, then it continues its process downstream. Otherwise, the job will cycle back to the bottleneck stage for rework operation. Upon the completion of a batch of regular jobs, the decision maker observes the amount of rework and decides on whether to switch over to process the reworks or continue to process another batch of regular jobs. It is assumed that both switch-over time and cost are incurred when the facility switches from performing one type of operation to a different type. The goal of the analysis is to characterize the optimal operating policy for the bottleneck so that the average operating cost is minimized. In order to characterize the optimal operating policy, we first formulate the problem as a semi-Markov decision process. Then we show that there exists an optimal “threshold” operating policy that can be described as follows: upon completion of a batch of regular jobs, switch over to process the reworks only if the number of reworks exceeds a critical value. In addition, we develop a simple procedure to compute the critical value that specifies the optimal threshold policy. Moreover, we evaluate the impact of batch sizes, yield, and switch-over time on the optimal threshold policy.
Insider Trading, Earnings Changes, and Stock Prices
Authors: Allen Steven , Ramanan Ramachandran
Published: November 2008

This study empirically examines the relation between reportable insider trading and the information captured by annual unexpected earnings for a large sample of firms, spanning a ten-year period (1978–87). Each observation is assigned to one of four groups based on the direction of net insider trading (Buy, Sell) and the sign (+, −) of unexpected earnings. For each of these groups, 15-month cumulative abnormal returns are regressed on annual unexpected earnings. The slope coefficient is the largest for the group where insiders are net purchasers and the sign of unexpected earnings is positive. This is consistent with an inference that insider buying interactively confirms the favorable information captured by positive unexpected earnings and this interaction reduces the noise in unexpected earnings. The result with regard to the unfavorable information captured by the group with insider selling and negative unexpected earnings is similar but less pronounced. The analysis also suggests that insider trading conveys information not fully captured by the year's earnings.
Performance Analysis of a Multi-Item Production-Inventory System Under Alternative Policies
Authors: Zipkin Paul H.
Published: November 2008

This paper explores the performance of a multi-item production-inventory system. We compare two alternative policies, representing different modes of collecting and utilizing information. We derive a closed-form measure of performance for one of them, the familiar first-come-first-served (FCFS) policy, and propose a comparable approximation for the other, the longest-queue (LQ) policy. These results are illustrated and tested through simulations. In this way we address several basic managerial issues: What is the value of centralized information in complex systems? How does the breadth of the product line affect performance?
The Influence of Supervisory Promotion and Network Location on Subordinate Careers in a Dual Ladder RD&E Setting
Authors: Katz Ralph , Tushman Michael , Allen Thomas J.
Published: November 2008

This longitudinal study examines the impacts of supervisors' promotion paths and gatekeeper status on the career outcomes of technical subordinates in a dual ladder system. Results indicate that project supervisors significantly affect the chances of one's promotion along each track. Professionals reporting to supervisors promoted to the technical ladder were significantly more likely to also be promoted technically, especially in research. On the other hand, professionals reporting to gatekeeping supervisors in development were significantly more likely to be promoted up the managerial ladder. Gatekeeper status was more important in influencing subordinates' communication activities and subsequent promotions than supervisors' promotion path. These results underscore the importance of managing socialization and the career paths of gatekeepers and those reporting to them for enhancing the success of dual ladder reward systems.
An EOQ Model with Random Variations in Demand
Authors: Brill Percy H. , Chaouch Ben A.
Published: November 2008

This paper presents a model that incorporates variations in the demand rate at random time points into the inventory planning decision. These changes in demand may occur due to economic recessions, labor strife starting or ending, or other events that result in a period of time during which the rate of demand is shifted up or down from its current level. The paper uses system-point level-crossing theory to derive expressions for the distribution and expected value of on-hand inventory, ordering rate, and the expected total cost rate for a given ordering policy. A sensitivity analysis is conducted, and a number of qualitative properties are provided to illustrate the use of the results to obtain optimal order quantities.
Dynamic Scheduling of a Production/Inventory System with By-Products and Random Yield
Authors: Ou Jihong , Wein Lawrence M.
Published: November 2008

Motivated by semiconductor wafer fabrication, we consider a scheduling problem for a single-server multiclass queue. A single workstation fabricates semiconductor wafers according to a variety of different processes, where each process consists of multiple stages of service with a different general service time distribution at each stage. A batch (or lot) of wafers produced according to a particular process randomly yields chips of many different product types, and completed chips of each type enter a finished goods inventory that services exogenous customer demand for that type. The scheduling problem is to dynamically decide whether the server should be idle or working, and in the latter case, to decide which stage of which process type to serve next. The objective is to minimize the long run expected average cost, which includes costs for holding work-in-process inventory (which may differ by process type and service stage) and backordering and holding finished goods inventory (which may differ by product type). We assume the workstation must be busy the great majority of the time in order to satisfy customer demand, and approximate the scheduling problem by a control problem involving Brownian motion. A scheduling policy is derived by interpreting the exact solution to the Brownian control problem in terms of the production/inventory system. The proposed dynamic scheduling policy takes a relatively simple form and appears to be effective in numerical studies.
Corporate Hedging of Exchange Risk When Foreign Currency Cash Flow Is Uncertain
Authors: Chowdhry Bhagwan
Published: November 2008

We analyze hedging policies for a corporation that generates a foreign currency cash flow that is not known with certainty. We obtain an intriguing result that the probability of bankruptcy for a firm that attempts to minimize this probability is lower when there is some uncertainty in the exchange rates than when there is no uncertainty in the exchange rates: the firm reduces the probability of bankruptcy by borrowing more than its financing needs through foreign currency borrowing alone and by investing the excess funds in domestic risk-free securities.
Trading Securities Using Trailing Stops
Authors: Glynn Peter W. , Iglehart Donald L.
Published: November 2008

In financial markets traders often protect their position from a significant decline by using a trailing stop. Assume the trader is long the market (owns the security). A trailing stop is an order to sell the security at the market, if the price of the security drops to the stop price. The stop price is always less than the market price when the stop is entered. As the price fluctuates, the stop is raised to remain a fixed distance from the maximum price at which the security trades. In this paper we consider two models for the price process: a discrete time random walk and continuous time Brownian motion, both with positive drift. For these price processes we compute the distribution, mean, and variance of the gain to the trader as well as the duration of the trade when a trailing stop strategy is used. Also discussed is the question of optimizing the distance from the current price to the stop.
The Invention of the Independence Condition for Preferences
Authors: Fishburn Peter , Wakker Peter
Published: November 2008

This paper discusses the history and interrelations of three central ideas in preference theory: the independence condition in decision under risk, the sure-thing principle in decision under uncertainty, and conjoint independence for multiattribute decisions and consumer theory. Independence was recognized as an important component of decision under risk in the late 1940s by Jacob Marschak, John Nash, Herman Rubin, and Norman Dalkey, and first appeared in publication in Marschak (Marschak, J. 1950. Rational behavior, uncertain prospects, and measurable utility. Econometrica 18 111–141.) and Nash (Nash, J. F. 1950. The bargaining problem. Econometrica 18 155–162.). The sure-thing principle can be credited to Savage (Savage, L. J. 1953. Une Axiomatisation du Comportement Raisonnable Face à l'Incertitude. Colloq. Internal. Centre National Rech. Sci. 40 Econométrie 29–40; Savage, L. J. 1954. The Foundations of Statistics. Wiley, New York (2nd edn., Dover, New York, 1972.). Conjoint independence for consumer theory was introduced by Sono (Sono, M. 1943. The effect of price changes on the demand and supply of separable goods (in Japanese). Kokumin Keisai Zasshi 74 1–51.) and Leontief (Leontief, W. W. 1947a. A note on the interrelation of subsets of independent variables of a continuous function with continuous first derivatives. Bull. Amer. Math. Soc. 53 343–350; Leontief, W. W. 1947b. Introduction to a theory of the internal structure of functional relationships. Econometrica 51 361–373.); a form of it can also be recognized in Samuelson (Samuelson, P. A. 1947. Foundations of Economic Analysis. Harvard University Press, Cambridge, MA.), presented earlier in Samuelson (Samuelson, P. A. 1940. Foundations of analytical economics, the observational significance of economic theory. Ph.D. dissertation, Harvard University, Boston, MA.).

Independence and the sure-thing principle are equivalent for decision under risk, but in a less elementary way than has sometimes been thought. The sure-thing principle for decision under uncertainty and conjoint independence are identical in a mathematical sense.

The mathematics underlying our three preference conditions has an older history. The independence condition for decision under risk can be recognized in the characterization of “associative means,” and conjoint independence for multiattribute decisions in solutions to the “generalized associativity functional equation.”
Interactive Approaches for Discrete Alternative Multiple Criteria Decision Making with Monotone Utility Functions
Authors: Köksalan M. Murat , Sagala Paul N. S.
Published: November 2008

In this paper we develop interactive approaches for the discrete alternative multiple criteria decision making problem. We develop an algorithm that finds the most preferred alternative of a decision maker (DM) assuming only that the DM has a monotonic utility function. The algorithm divides the criteria space into a number of smaller subspaces and then uses the ideal points of these subspaces to eliminate alternatives. We also develop a more efficient version of the algorithm for the more restrictive case of a monotonic quasiconcave utility function. We present favorable computational results in terms of the required number of pairwise comparisons for both versions of the algorithm. We then develop a general algorithm that first identifies the type of the DM's utility function and then employs the approach that is compatible with the identified utility function type. We also present computational results for the general algorithm.
The Discrete Resource Allocation Problem in Flow Lines
Authors: Karabati Selcuk , Kouvelis Panagiotis , Yu Gang
Published: November 2008

In this paper we address the discrete resource allocation problem in a deterministic flow line. We assume that the processing times are convex and nonincreasing in the amount of resources allocated to the machines. We consider the resource allocation problem for a fixed sequence of jobs for various performance criteria (makespan, weighted sum of completion times, cycle time for cyclic schedules), and develop a formulation of the problem as a convex program, where the number of constraints grows exponentially with the number of jobs and machines. We also present a generalization of the formulation for resource allocation problems in acyclic directed graphs. We demonstrate that the problem is NP-complete in the strong sense and present an effective solution procedure. The solution procedure is an implicit enumeration scheme where a surrogate relaxation of the formulation is used to generate upper and lower bounds on the optimal objective function value. Finally, we address the simultaneous scheduling and resource allocation problem, and we present an approximate and iterative solution procedure for the problem.
A Multiechelon Inventory Model with Fixed Replenishment Intervals
Authors: Graves Stephen C.
Published: November 2008

This paper develops a new model for studying multiechelon inventory systems with stochastic demand. For the model we assume that each site in the system orders at preset times according to an order-up-to policy, that delivery times are deterministic, and that the demand processes are stochastic with independent increments. We introduce a new scheme for allocating stock in short supply, which we call virtual allocation and which permits significant tractability. We exercise the model on a set of test problems for two-echelon systems to get insight into the structure of good policies. The primary findings are that both the central warehouse (upper echelon) and the retail sites (lower echelon) should hold safety stock, but that most of the safety stock should be at the retail sites. Consequently, the central warehouse will stock out with high probability. Furthermore, we show that the virtual allocation rule is near optimal for the set of test problems.
Periodic Review Production Models with Variable Capacity, Random Yield, and Uncertain Demand
Authors: Wang Yunzeng , Gerchak Yigal
Published: November 2008

We investigate a production planning problem in a periodic review environment with variable production capacity, random yields, and uncertain demand. The implications of random yields and variable capacity for lot sizing previously have been explored separately, but not jointly. Many production environments are likely to be subject to both types of uncertainties. To minimize the total discounted expected costs (production, holding, and shortage costs), we formulate the problem as a stochastic dynamic program. For the finite-horizon problem, we prove that the objective function is quasi-convex and that the structure of the optimal policy is characterized by a single critical point for the initial stock level at each period. That is, if the initial stock is greater than this critical point, the optimal planned production is zero; otherwise, it is greater than zero. Expressions for solving the critical point and the optimal planned production are obtained. We further show that the solution for the finite-horizon problem converges to that of the infinite-horizon problem.
Pricing Strategies in a Dynamic Duopoly: A Differential Game Model
Authors: Chintagunta Pradeep K. , Rao Vithala R.
Published: November 2008

We formulate a differential game model for dynamic pricing in a duopolistic market. Firms' demand functions are derived from utility maximizing behavior of consumers with the demand for a brand given by the logit model. Preferences for brands are assumed to evolve over time in the market in a manner akin to learning models postulated in the marketing literature. We derive the differential equations governing the equilibrium open-loop price paths over time and show that in steady state, the brand with the higher preference level charges the higher price. The formulation is extended to include the effects of consumer heterogeneity, and equilibrium steady-state prices are compared with those obtained when heterogeneity is ignored. A comparison of steady-state dynamic prices with myopic prices is provided. An empirical example is discussed to show how steady-state model predictions may be obtained from actual longitudinal purchase data.
Network Externalities in Microcomputer Software: An Econometric Analysis of the Spreadsheet Market
Authors: Brynjolfsson Erik , Kemerer Chris F.
Published: November 2008

Because of network externalities, the success of a software product may depend in part on stalled base and its conformance to industry standards. This research builds a hedonic model to determine the effects of network externalities, standards, intrinsic features and a time trend on microcomputer spreadsheet software prices. When data for a sample of products during the 1987–1992 time period were analyzed using this model, four main results emerged: 1) Network externalities, as measured by the size of a product's installed base, significantly increased the price of spreadsheet products: a one percent increase in a product's installed base was associated with a 0.75% increase in its price. 2) Products which adhered to the dominant standard, the Lotus menu tree interface, commanded prices which were higher by an average of 46%. 3) Although nominal prices increased slightly during this time period, quality-adjusted prices declined by an average of 16% per year. 4) The hedonic model was found to be a good predictor of actual market prices, despite the fact that it was originally estimated using list prices. Several variations of the model were examined, and, while the qualitative findings were robust, the precise estimates of the coefficients varied somewhat depending on the sample of products examined, the weighting of the observations and the functional form used in estimation, suggesting that the use of hedonic methods in this domain is subject to a number of limitations due, inter alia, to the potential for strategic pricing by vendors.
Organizational Consultant: Creating a Useable Theory for Organizational Design
Authors: Baligh Helmy H. , Burton Richard M. , Obel Børge
Published: November 2008

Organization theory is a positive science; organizational design is a normative science “concerned with how things ought to be, with devising structures to attain goals.” The Organizational Consultant is a knowledge base expert system to help design organizations. That is, it takes facts about the environment, size, strategy, technology, ownership, and management preferences and applies the knowledge base to recommend the design structure and properties such as complexity, formalization, centralization, and span of control, among others.

Organization theory is comprised of numerous positive contingency theories, which are not integrated. The main issue is to create a comprehensive and consistent knowledge base from what we know, i.e., create a useful synthesis. We utilize four fit criteria as a guide: contingency fit, design parameter fit, situation fit, and total parameter fit. Contingency fit demands that the knowledge base of “if-then” rules follow what we know from the literature. Design parameter fit requires a balance, or weighting, among the supporting and opposing design recommendations. Situation fit assures us that the situation itself is not inconsistent. Finally, total design fit requires that it is useable and helpful to recommend structure and properties to attain goals.

The development of the Organizational Consultant is a continuing validation exercise. The size of an organization is an important design contingency. Yet, an operational definition of size for design purposes has been wanting. We discuss how a useful definition of size was developed for the Organizational Consultant.

We describe the development of the Organizational Consultant—a knowledge-based expert system that utilizes a synthesis of the elements of organizational contingency, theory through a validation process. The four fit criteria were applied to guide the development process.
Learning in Setups: Analysis, Minimal Forecast Horizons, and Algorithms
Authors: Tzur Michal
Published: November 2008

We analyze the dynamic lot-sizing model in which the cost of a setup depends on the number of setups that have occurred prior to it. This arises, for example, when there exist learning effects in setups. Our model is more general than most learning models in the literature since it allows the total setup cost to be a general nondecreasing (but not necessarily concave) function of the number of setups.

We explore tight relationships between our model and special cases of the classical dynamic lot-sizing model. On the basis of these we find minimal forecast and planning horizons for our model, which determine the first decision when the model is solved on a rolling horizon basis. When a forecast horizon cannot be found, we provide guidelines regarding the optimal first decision. We also provide an algorithm to solve the finite horizon problem, which uses as sub-problems variations of the classical dynamic lot-sizing problem. The advantage of this approach is the ability to use the extensive literature available on the latter, to generalize the results of this paper. As many of our results are qualitative in nature, they provide insights which can be useful for other models with a similar setup cost behavior.
Interval Coverage in Multiclass Queues Using Batch Mean Estimates
Authors: Johnson M. Eric , Jackman John
Published: November 2008

We investigate the fixed, sample-size, batch-mean procedure for creating confidence intervals from simulated data obtained from a stochastic queueing system with multiple customer classes. We show that, for a multiclass M/M/1 queue, serial correlation between customers of the same class decreases to zero as the number of customer classes increases. We also derive a closed-form expression for the asymptotic variance of waiting time by customer type. We then empirically examine batch-mean estimator coverage for a simple queue with multiple customer classes. We find that batch-mean estimators perform better in terms of coverage and interval half width in multiclass queues, with a fixed number of observations per class, than in the traditionally studied single-class systems. We also examine the effect of multiple classes where the total computational effort remains fixed.
Note: Microcomputer Performance of OptPack on Hoffmann's Data Sets: Comparison with Eureka and FABLE
Authors: Nourie Francis J. , Venta Enrique R.
Published: November 2008

OptPack (Nourie and Venta [Nourie, Francis J., E. R. Venta. 1991. Finding optimal line balances with OptPack. Oper. Res. Letters 10(April) 165–171.]) was published between the publication times of FABLE and EUREKA. This communication reports microcomputer computational experience with OptPack on Hoffmann's data sets following the pattern of Johnson (Johnson, Roger V. 1993a. Microcomputer performance of ‘FABLE’ on Hoffmann's data sets. Management Sci. 39(10) 1190–1192.). Some insights about the computational effectiveness of the algorithms and some additional difficult problems are also presented.
A Stochastic Optimization Model to Improve Production Planning and R&D Resource Allocation in Biopharmaceutical Production Processes
Authors: Schmidt Robert L.
Published: November 2008

The increasing cost of health care has brought pressure to reduce pharmaceutical costs, and because manufacturing and R&D are significant cost factors, these areas have been targeted as potential sources of cost reduction. Manufacturing costs are particularly high in the biotechnology industry because process technologies are relatively new. Contamination, genetic instability, and other factors complicate production planning and make bioprocess systems unreliable. This paper presents a Markov decision process model that combines features of engineering design models and aggregate production planning models to obtain a hybrid model that links biological and engineering parameters to optimize operations performance. Using tissue plasminogen activator as a specific example, the paper shows how the hybrid modeling approach not only improves production planning, but also provides accurate information on the operating performance of bioprocesses that can be used to predict the financial impact of process changes. Therefore, the model can be used to guide investments in manufacturing process improvement and R&D (e.g., genetic modifications). Although stochastic production models are not commonly used in process design, this paper shows how a combined engineering/production model can facilitate a concurrent design approach to reduce cost in bioprocess development.
Commonalities in Reengineered Business Processes: Models and Issues
Authors: Buzacott John A.
Published: November 2008

Process reengineering advocates making radical changes in how processing systems are structured, such as moving away from systems that use the principles of division of labor and division of management. Using formal system models from queueing theory, this paper explores the conditions under which such radical changes in system structure are likely to be appropriate. In general, a fairly high degree of variability in task times seems to be necessary.
Genetic Algorithms for Product Design
Authors: Balakrishnan P. V. (Sundar) , Jacob Varghese S.
Published: November 2008

Product design is increasingly recognized as a critical activity that has a significant impact on the performance of firms. Consequently, when firms undertake a new (existing) product design (redesign) activity, it is important to employ techniques that will generate optimal solutions. As optimal product design using conjoint analysis data is an NP-hard problem, heuristic techniques for its solution have been proposed. This research proposes the use of and evaluates the performance of Genetic Algorithms (GA), which is based on the principles of natural selection, as an alternative procedure for generating “good” (i.e., close to optimal) solutions for the product design problem. The paper focuses on (1) how GA can be applied to the product design problems, (2) determining the comparative performance of GA vis-à-vis the dynamic programming (DP) heuristic (Kohli and Krishnamurti [Kohli, R., R. Krishnamurti. 1987. A heuristic approach to product design. Management Sci. 33(12) 1523–1533.], [Kohli, R., R. Krishnamurti. 1989. Optimal product design using conjoint analysis: Computational complexity and algorithms. Eur. J. Oper. Res. 40 186–195.]) in generating solutions to the product design problems, (3) the sensitivity of the GA solutions to variations in parameter choices, and (4) generalizing the results of the dynamic programming heuristic to product designs involving attributes with varying number of levels and studying the impact of alternate attribute sequencing rules.
Single-Machine Scheduling with Release Dates, Due Dates and Family Setup Times
Authors: Schutten J. M. J. , van de Velde S. L. , Zijm W. H. M.
Published: November 2008

We address the NP-hard problem of scheduling n independent jobs with release dates, due dates, and family setup times on a single machine to minimize the maximum lateness. This problem arises from the constant tug-of-war going on in manufacturing between efficient production and delivery performance, between maximizing machine utilization by batching similar jobs and maximizing customers' satisfaction by completing jobs before their due dates. We develop a branch-and-bound algorithm, and our computational results show that it solves almost all instances with up to about 40 jobs to optimality. The main algorithmic contribution is our lower bounding strategy to deal with family setup times. The key idea is to see a setup time as a setup job with a specific processing time, release date, due date, and precedence relations. We develop several sufficient conditions to derive setup jobs. We specify their parameters and precedence relations such that the optimal solution value of the modified problem obtained by ignoring the setup times, not the setup jobs, is no larger than the optimal solution value of the original problem. One lower bound for the modified problem proceeds by allowing preemption. Due to the agreeable precedence structure, the preemptive problem is solvable in O(n log n) time.
The Feasibility of an Index-Contingent Trading Mechanism
Authors: Wohl Avi
Published: November 2008

“Auction” or “call” trading systems are used in many stock exchanges. An essential problem in the application of these systems is that orders in one security cannot be conditioned on prices of other securities. This paper proposes and analyzes the feasibility of an index-contingent trading system. In this system, limit orders may be conditioned on an index (any weighted average of the security prices that is determined simultaneously with the prices) in addition to the asset price. Without any assumptions about traders' behavior it is shown that under a reasonable restriction on the structure of the limit orders, there is a unique solution (vector of prices) to any set of orders in all securities. Moreover, the paper presents a quick and simple algorithm that converges to the solution. This algorithm is based on an extension of the current mechanisms; therefore it can be implemented easily in any computerized auction system.
The Lagged PSA for Estimating Peak Congestion in Multiserver Markovian Queues with Periodic Arrival Rates
Authors: Green Linda V. , Kolesar Peter J.
Published: November 2008

We propose using a modification of the simple peak hour approximation (SPHA) for estimating peak congestion in multiserver queueing systems with exponential service times and time-varying periodic Poisson arrivals. This lagged pointwise stationary approximation (lagged PSA) is obtained by first estimating the time of the actual peak congestion by the time of peak congestion in an infinite server model and then substituting the arrival rate at this time in the corresponding stationary finite server model. We show that the lagged PSA is always more accurate than the SPHA and results in dramatically smaller errors when average service times are greater than a half an hour (based on a 24 hour period). More importantly, the lagged PSA reliably identifies proper staffing levels to meet targeted performance levels to keep congestion low.
Designing a Firm's Coordinated Manufacturing and Supply Decisions with Short Product Life Cycles
Authors: Parlar Mahmut , Weng Z. Kevin
Published: November 2008

In this paper we consider a problem of joint coordination between a firm's manufacturing and supply departments. The manufacturing department is responsible for meeting random demand of a product with a short life cycle. The supply department's responsibility is to provide the sufficient amount of raw materials so that the required production level can be achieved. When coordination prevails, both departments' decisions are jointly made; otherwise, decisions are made independently without an exchange of information. If the random demand exceeds the amount produced, a second production run can be expedited at a substantially higher cost. Our analysis yields insightful results to such a coordination problem between the two departments. We provide conditions under which it is desirable to coordinate, resulting in a significant increase in expected profit. If coordination is optimal, then the supply department would purchase additional reserved material for the second run. Under this scenario, we analyze the effects of joint coordination on the expected profit. We also find explicit conditions for which joint coordination is not beneficial, i.e., the supply department should only order sufficient material to meet the first production run requirements. We provide a detailed set of numerical examples and generate response surfaces indicating the desirability of coordination for different pairs of parameter combinations.