bluuebunny/crossref_metadata_2025 huggingface dataset:
Research in Management Information Systems: The Minnesota Experiments
Authors: Dickson Gary W. , Senn James A. , Chervany Norman L.
Published: November 2008

The use of computer based information-decision systems to support decision making in organizations has increased significantly in the last decade. Very little effort has been devoted, however, to determine what relationships exist between the structure of information presented for decision making and the ensuing effectiveness of the decision. This article summarizes a series of experiments. The Minnesota Experiments, which were conducted to examine the significance of various information system characteristics on decision activity. Several research programs administered in the period 1970–1975 are discussed in this paper. By varying the manner in which information was provided to participants in each experiment, the impact of various information system characteristics and individual differences on decision effectiveness was investigated. Analysis of the results shows that, in many cases, the decisions/decision-making process of the participants was affected by the information system structure and/or attributes of individual decision makers. The results suggest guidelines for the designers of information systems and fruitful avenues for continued research.
Storage-Retrieval Interleaving in Automatic Warehousing Systems
Authors: Graves Stephen C. , Hausman Warren H. , Schwarz Leroy B.
Published: November 2008

This paper extends work previously reported on storage assignment rules for automatic warehousing systems to include interleaving; that is, the sequencing of storage and retrieve requests. Using both continuous analytical models and discrete evaluation procedures, this paper compares the operating performance of several storage assignment/interleaving policies. The results indicate that significant reductions in crane travel time (and distance) are obtainable in some real-world and/or previously modeled situations via the proposed storage assignment/interleaving policies. These reductions may be directly translated into increased throughput capacity for existing systems. The storage assignment/interleaving policies may also be used to improve the design of proposed systems to achieve a more desirable balance between throughput and storage capacity. Although the system examined is a high-rise automatic warehouse, the results presented have implications for the warehousing function in general.
On a Fleet Sizing and Allocation Problem
Authors: Parikh S. C.
Published: November 2008

This paper deals with a practical application of queueing theory. In particular, an approximate but quick method is developed for solving a fleet sizing and allocation problem. The problem concerns an optimal allocation of the total available transport vehicle units to many fleets in such a way that all fleets provide (as nearly as possible) a uniform level of service. The level of service is measured in terms of the fraction of arriving orders for shipment delayed due to the lack of immediate availability of a transport vehicle unit. The method employs some new results in queueing theory for approximating the delay probability and the service facility size in multi-server systems. An illustrative example is included to demonstrate a way of applying the method.
Electric Power System Planning with Explicit Stochastic Reserves Constraint
Authors: Scherer Charles R. , Joe Leland
Published: November 2008

The problem of optimal planning of an electric power system is formulated as a cost minimizing mixed-integer mathematical program. The model emphasizes system reliability, requiring reserve generating capacity such that a Loss of Load Probability criterion of one day in ten years is met. Integer variables are used in the model to express system reliability explicitly as a constraint on the system model. Results are given for several plant outage rates and demand levels. The results show that the reliability and “rule-of-thumb” approaches to system reserve planning can yield substantially different optimal system costs and configurations.
Exceptional Paper—Design and Implementation of Large Scale Primal Transshipment Algorithms
Authors: Bradley Gordon H. , Brown Gerald G. , Graves Glenn W.
Published: November 2008

A complete description is given of the design, implementation and use of a family of very fast and efficient large scale minimum cost (primal simplex) network programs. The class of capacitated transshipment problems solved is the most general of the minimum cost network flow models which include the capacitated and uncapacitated transportation problems and the classical assignment problem; these formulations are used for a large number of diverse applications to determine how (or at what rate) a good should flow through the arcs of a network to minimize total shipment costs. The presentation tailors the unified mathematical framework of linear programming to networks with special emphasis on data structures which are not only useful for basis representation, basis manipulation, and pricing mechanisms, but which also seem to be fundamental in general mathematical programming. A review of pertinent optimization literature accompanies computational testing of the most promising ideas. Tuning experiments for the network system, GNET, are reported along with important extensions such as exploitation of special problem structure, element generation techniques, postoptimality analysis, operation with problem generators and external problem files, and a simple noncycling pivot selection procedure which guarantees finiteness for the algorithm.
Communication—Reply to Sandison
Authors: Sinha Bani K. , Clelland Richard C.
Published: November 2008

Authors' reply to Sandison A. 1977. Communication—Modelling library collections. Management Sci. 24 (1) 113–114.
On Ordering Perishable Inventory when Both Demand and Lifetime are Random
Authors: Nahmias Steven
Published: November 2008

We consider the problem of ordering perishable inventory when there is uncertainty in both the demand and the lifetime of the product. Under the assumption that units outdate in the same order in which they enter inventory, it is shown that the structure of the optimal policy is essentially the same as in the case where the lifetime is deterministic. An explicit expression for the expected outdating of any order is derived. Two different bounds on the expected outdating are then used to construct two critical number approximations. Computations for a discrete version of the problem are performed to compare the expected costs of both approximations with the optimal. One approximation appeared to give slightly better results and produced an expected cost generally within a fraction of a percent of the optimal for the cases tested.
Heuristic 0-1 Linear Programming: An Experimental Comparison of Three Methods
Authors: Zanakis Stelios H.
Published: November 2008

This paper examines the performance of three heuristic methods (Senju-Toyoda, Kochen-berger et al. and Hillier) when applied to the 0-1 linear programming problem with nonnegative coefficients. Their effectiveness, measured in terms of computing time, error and relative error, is evaluated on a set of problems from the literature and randomly generated 0-1 test problems with nonnegative coefficients. Analysis of variance and stepwise regressions are employed to study the effect of the number of variables, number of constraints and degree of constraint slackness. The methods exhibited some similarities bui also marked differences in their behavior. Interestingly enough, the larger the number of variables the belter the accuracy of each method. Error differences among the three methods were significant (1:0.8:0.2) yet small (less than 2% on the average) for many practical situations. Hillier's algorithm was the most accurate but much slower and more core demanding than the other two, which makes it difficult or impossible to use for solving large 0-1 problems. Kochenberger's et al. heuristic was the fastest (most accurate) of the three in tightly (loosely) constrained problems. In general the Senju-Toyoda algorithm was the fastest, but least accurate on small and medium size problems. Suggestions are made for selecting the “best” heuristic based on the problem characteristics.
A Model for Planning Ambulatory Health Services
Authors: Ittig Peter T.
Published: November 2008

This paper reports results of a study that develops improved methods of planning ambulatory health services for a specified population. Some of the difficulties of the problem are discussed and a linear model is presented that aids the planning process by accounting for a wide range of data on the population, finances, and system dynamics. Sample results are shown and some implications for further research are discussed.
An Approach to Solving Multiple Criteria Macroeconomic Policy Problems and an Application
Authors: Wallenius Hannele , Wallenius Jyrki , Vartia Pentti
Published: November 2008

In this paper we propose an approach to solving multiple criteria macroeconomic policy problems and report on an application using an existing econometric model. This approach involves the use of a mathematical programming formulation of the macroeconomic policy problem with multiple objective functions. The multiple objectives are resolved by a man-machine interactive solution strategy. This approach was implemented in order to analyze macroeconomic problems in Finland.
Predicting Demand from Sales Data in the Presence of Stockouts
Authors: Wecker William E.
Published: November 2008

The effect of stockouts on prediction accuracy is analyzed. The forecasting bias that results and the effect on the prediction error variance are explored and are seen to depend on the frequency of stockouts, the coefficient of variation of demand, and the serial correlation of demand.
The Value of Data for a Quadratic Decision Problem
Authors: Rice Thomas Richard
Published: November 2008

A question that recurs in the decision analysis literature is: What is the value of additional data gathering? We use a very general definition of data that includes subjective probability distributions provided by experts, calculations from models, and traditional experimental data. General expressions for the expected value of data have little practical use because they involve probability distributions whose arguments are themselves probability distributions. The traditional approach to alleviate the problem of dimensionality is to introduce arbitrary parameterization of the data.

This paper shows that for an interesting class of decision problems, arbitrary parameterization is not necessary. For the class of decision problems in which the value function over outcomes is a quadratic function of the state and decision variables, the value of data depends on the state variables only through the prior covariances of the posterior means.

To use this result in the calculation of the approximate value of data for practical problems, it is necessary to simplify the value function. The paper suggests simplifying the value function by expanding it in a Taylor series with respect to the state and decision variables. The resulting expressions for the approximate value of information should be useful and inexpensive to evaluate for practical decision problems.
Organizational Context and the Success of Management Information Systems
Authors: Ein-Dor Phillip , Segev Eli
Published: November 2008

This paper identifies the organizational context variables affecting the success and failure of MIS. The variables are categorized as uncontrollable, partially controllable and controlled, and a conceptual scheme is suggested. In addition, current information on these variables and the interactions between them is surveyed; propositions are stated concerning relationships between the variables and the success or failure of MIS.
A Production-Inventory Control Model with a Mixture of Back-Orders and Lost-Sales
Authors: Doshi B. T. , van der Duyn Schouten F. A. , Talman J. J.
Published: November 2008

We consider a production-inventory control model of finite capacity, in which backordering up to a certain level is allowed. We assume that there exist two possible production rates. The control is based on two critical stock-levels and prescribes to change the production rate used only when one of these levels is reached. A fixed cost is associated with every switch-over. The rate at which customers arrive and the distribution of the demand of an arriving customer depend on the production rate used at that moment. A formula for the long-run average expected costs per unit time is obtained as a function of the chosen critical levels. From this formula we derive expressions for various interesting operating characteristics of this system, amongst which are the joint stationary distribution of the processes describing the production rate used and the inventory of the system and the average number of switch-overs and lost-sales per unit time.
Adaptive Forecasting Models Based on Predictive Distributions
Authors: Winkler Robert L. , Smith Wayne S. , Kulkarni Ram B.
Published: November 2008

The availability of data regarding variables of interest in forecasting problems is sometimes limited, but experts may possess a great deal of relevant information. The approach taken in this paper involves the development of adaptive forecasting models based on such information. Since the models and their parameters are difficult to consider intuitively, information from the experts is elicited in terms of predictive distributions of the variable to be forecasted. Various models can then be considered, and attempting to “fit” a model to the predictive distributions is analogous to attempting to fit a model to a set of observations. This general approach to forecasting is developed in this paper, and a specific model, a linear model with normally distributed errors, is considered in some detail. An actual application involving the forecasting of fatigue life of asphalt pavements illustrates the development of forecasting models from experts predictive distributions.
Modified Policy Iteration Algorithms for Discounted Markov Decision Problems
Authors: Puterman Martin L. , Shin Moon Chirl
Published: November 2008

In this paper we study a class of modified policy iteration algorithms for solving Markov decision problems. These correspond to performing policy evaluation by successive approximations. We discuss the relationship of these algorithms to Newton-Kantorovich iteration and demonstrate their covergence. We show that all of these algorithms converge at least as quickly as successive approximations and obtain estimates of their rates of convergence. An analysis of the computational requirements of these algorithms suggests that they may be appropriate for solving problems with either large numbers of actions, large numbers of states, sparse transition matrices, or small discount rates. These algorithms are compared to policy iteration, successive approximations, and Gauss-Seidel methods on large randomly generated test problems.
LIFO Inventory Systems
Authors: Cohen Morris A. , Pekelman Dov
Published: November 2008

In many perishable product inventory systems where the issuing of stock to meet demand is controlled by the consumer, the movement of units through the system obeys a LIFO discipline.

In this paper the evolution over time of the LIFO inventory stock age distribution in an environment of stochastic demand is analyzed. The inventory related processes are shown to be completely specified by the random walk ladder height process. This characterization of the LIFO system is then utilized to derive limiting distributions for the stock age distribution when a constant amount is ordered each period. The distribution is found from a Wiener-Hopf integral equation for the ladder height random variable. Transient results for the case of a fixed critical number order policy are also presented. Explicit closed form results are derived for an example in which demand is exponentially distributed. The paper concludes by demonstrating how the results on the steady-state age distribution can be used for devising upper and lower bounds on expected shortages and outdates.
State of the Art—Networks of Queues: A Survey of Weak Convergence Results
Authors: Lemoine Austin J.
Published: November 2008

This report is a sequel to our review paper, Lemoine [Lemoine, A. J. 1977. Networks of queues–A survey of equilibrium analysis. Management sci. 24 464–481.], on the equilibrium analysis of networks of queues. In this paper we review some weak convergence results for networks of queues, which include heavy traffic limit theorems for open networks and asymptotic results for large closed Markovian systems which are generalizations of the classical repairman problem. These weak convergence results justify certain approximation schemes for processes of interest. We also discuss some important open problems in the area of weak convergence results for networks of queues.
The Role of Attitude Toward Risk in Strictly Competitive Decision-Making Situations
Authors: Eliashberg Jehoshua , Winkler Robert L.
Published: November 2008

The impact of decision makers' attitudes toward risk has been studied extensively in the context of noncompetitive decision making but not in the context of competitive decision making. In this paper we study the effects of the utility functions of the players in a strictly competitive decision-making situation on (a) their strategies and (b) their expected monetary payoffs. The setting is that of a two-by-two, two-person, zero-sum (in money) game with exponential utility functions for the competitors. The monetary payoffs and utility functions are assumed to be public knowledge. Combinations of utility functions that preserve the zero-sum condition as well as combinations that do not preserve this condition are considered. As might be expected, results from noncompetitive decision making do not necessarily carry over into competitive situations. For example, an increase in the risk aversion of a player may actually increase that player's expected monetary payoff because of altered strategies on the part of the competitor. In general, the effects of nonlinear utility functions on a player's strategy and expected monetary payoff depend on the player's utility function, the opponent's utility function, and the relationship among the entries in the payoff table. Furthermore, it does not appear possible to express this dependence in the form of simple rules of thumb, although the results presented here indicate the direction of movement of strategies and expected payoffs as the inputs to the problem are varied in certain systematic ways.
Production Switching Heuristics for the Aggregate Planning Problem
Authors: Mellichamp Joseph M. , Love Robert M.
Published: November 2008

A number of approaches to the aggregate planning problem have been proposed in the literature, yet experience suggests that industrial concerns seldom use these models in actual planning situations. This paper describes a modified random walk production-inventory heuristic for the problem which should appeal to managers on the basis of simplicity as well as efficiency. The proposed approach is contrasted with linear programming, parametric programming, and linear decision rule optimal and near optimal solutions for several well known production situations. The simple production switching heuristic produces schedules which exceed optimal schedules by only 1 to 2 percent of total production costs in all cases.
A Patrol Car Allocation Model: Capabilities and Algorithms
Authors: Chaiken Jan M. , Dormont Peter
Published: November 2008

A computer program has been designed for specifying the number of police patrol cars that should be on duty in each geographical command of a city at various times of day on each day of the week. It incorporates, by user option, nearly all the desirable features of earlier allocation programs, together with several improvements. It calculates performance statistics for the current allocation of patrol cars or any allocation proposed by the user. In addition, it has two prescriptive capabilities: (1) determining the minimum number of patrol cars needed during each tour in each command to meet specified constraints on performance measures, and (2) allocating a specified total number of car-hours by time and/or geography so as to optimize one of several available objective functions. The main technical innovation in the model is that it allows one tour in each day to overlay two other tours. A heuristic algorithm allocates car-hours when there is such an overlay tour; it is optimal when the overlay tour has the same duration as the tours it overlays.
Police Sector Design Incorporating Preferences of Interest Groups for Equality and Efficiency
Authors: Bodily Samuel E.
Published: November 2008

This paper proposes and illustrates by example a decision model for a resource allocation problem in urban management—the design of service areas for police mobile units. Estimates of the performance of alternative designs are given by existing analytic models of spatially distributed emergency service systems. Using multiattribute utility theory, alternatives are evaluated according to the preferences for efficiency and equality of service of three interest groups: citizens, police, and administrators. Meaningful measures of inequality are developed and an algorithm is created for generating improved sector designs.
Consumer Preference Axioms: Behavioral Postulates for Describing and Predicting Stochastic Choice
Authors: Hauser John R.
Published: November 2008

This paper draws on econometrics, von Neumann-Morgenstern utility theory, stochastic choice theory, and consumer behavior to develop five basic axioms or postulates of stochastic choice behavior. These axioms imply the existence and uniqueness of a preference function which identifies how consumers evaluate products in terms of product attributes. The preference function produces a scalar goodness measure for each product in a consumer's choice set. These goodness measures then predict choice probabilities for each product in a consumer's choice set. The advantage of these axioms is that they extend the strengths of von Neumann-Morgenstern theory to stochastic choice and make possible the determination of consistent choice probabilities.
The Application of a Product Mix Linear Programming Model in Corporate Policy Making
Authors: Byrd Jack , Moore L. Ted
Published: November 2008

This paper reports a real-life application of linear programming to corporate policy making. The model used in the study was designed to analyze the company's marketing and production policies. The model structure is unique, incorporating features of product mix, sequencing and blending models. The model's structure is described as well as typical results it produced. The recommendations for corporate actions arising from the model are also explained. Recommendations were made to alter the existing corporate policies on brand proliferation and limited inventory levels. The product line has been reduced as a result of the study, and a policy decision to expand the inventory has been made. The process of implementation is sketched to provide a feeling for the difficulties involved in corporate policy making.
Optimal Dispatching of a Finite Capacity Shuttle
Authors: Deb Rajat K.
Published: November 2008

We consider the problem of determining the optimal operating policy of a two terminal shuttle with fixed capacity Q ≤ ∞. The passengers arrive at each terminal according to Poisson processes and are transported by a single carrier operating between the terminals. The interterminal travel time is a positive random variable with finite expectation. Under a fairly general cost structure, we show that the policy which minimizes the expected total discounted cost over infinite time horizon has the following form: Suppose the carrier is at one of the terminals with x passengers waiting there and y passengers waiting at the other terminal. Then the optimal policy is to dispatch the carrier if and only if x ≥ G(y), where G(y) is a monotone decreasing control function. Furthermore, G(y) is always less than or equal to the carrier capacity Q. This control function can be approximated by the linear function G(y) = K − βy.
A By-Product Production System with an Alternative
Authors: Deuermeyer Bryan L. , Pierskalla William P.
Published: November 2008

This paper considers the optimal control of a production system which is composed of two distinct production processes, types A and B, that produce two different products, 1 and 2, having distinct random demands. Production type A produces both products in amounts determined by a fixed set of production coefficients. Type B can only be used to make product 2. Costs consist of linear production costs and convex holding and shortage costs. Each period, the optimal production level of each type must be determined. The criterion is the minimum expected discounted total cost. Results show that the decision space of each period is partitioned into four regions by three monotone functions and a point. Extensions include capacitated production, nonstationary costs, lost sales, fixed lead times aid the general m process-n product system.
Order-Level Inventory Systems with Independent Stochastic Leadtimes
Authors: Zalkind David
Published: November 2008

Inventory systems where leadtimes are stochastic and independent, so that orders are not restricted to arrive in the same sequence in which they were placed, can arise if the vendor with whom orders are placed is unreliable in processing them or if orders for the same item are placed with different vendors at different times. We present a procedure for finding the optimal order-level Z (stock on hand plus on order) for a pre-determined scheduling-period t (time interval between decisions about placing orders), that is, a tZ policy. Backordering of shortages is assumed.

Most results are derived when both the demand distribution and the leadtime distribution are discrete and bounded. The main concept employed in the derivation is the use of the distribution of the number of outstanding orders to find the distribution of the amount of stock on order. It is then shown that for tZ policies, the solution can be interpreted as the weighted average of constant leadtime systems. Further results that may be helpful in constructing heuristic decision rules are given.

The nonoptimality of the sZ policy (i.e., order to Z whenever inventory falls to s) for independent stochastic leadtime systems is also discussed.
Market Share Models as Approximators of Aggregated Heterogeneous Brand Choice Behavior
Authors: Givon Moshe , Horsky Dan
Published: November 2008

The commonly used market share models are all based on the implicit assumption of a homogeneous population. However, studies of individual brand choice behavior tend to reject this basic premise. In this paper we attempt to explain why market share models perform well in spite of this underlying misspecification. A model which describes the individual's brand choice behavior is presented. This model allows an individual to follow either the Bernoulli, Markov or Linear Learning process as well as have different parameters from other people following the same process. A market share model which takes full account of this heterogeneity is derived and is compared to the traditional market share model in which homogeneous of consumers is assumed. The error in prediction which would result from the use of the homogeneous model is specified and its properties are examined. Conditions for the use, of the gravitational-type market share model, and, the first order lagged market share model are provided. It is shown that the homogeneous market share model will do well in time-series estimation but that the results will not always be appropriate for use in managerial decisions regarding forecasting and optimization.
A Procedure for Air Monitoring Instrumentation Location
Authors: Lee Thomas D. , Graves Robert J. , McGinnis Leon F.
Published: November 2008

The attainment and enforcement of air quality standards is a complicated process. A crucial element in this process is the measurement of ambient air quality. The selection of locations for a limited number of monitors and their sampling frequencies is an important problem in the design of a regional air quality measurement system. This paper presents a mathematical model and procedure for solving the problem and demonstrates the conflicting nature of the principal guidelines specified by EPA. The method uses atmospheric simulation to assess the likelihood of standards violations, and linear programming to select the monitor locations and sampling frequencies. Since atmospheric simulation is required by EPA, the method appears to be accessible to virtually all local agencies. The use of linear programming permits extensive sensitivity analysis, which is illustrated in a case study. In particular, the trade-offs between conflicting EPA guidelines can be explicitly analyzed. The computational burden is primarily in the atmospheric simulation and is roughly proportional to the area of the region being studied. The added computational burden represented by the model solution is quite small.
A Trajectory Method for the Optimization of the Multi-Facility Location Problem With lp Distances
Authors: Drezner Z. , Wesolowsky G. O.
Published: November 2008

We consider the multi-facility location problem of placing m new facilities optimally among n demand points (or existing facilities) so that the sum of all weighted lp distance pairs (facility to facility and facility to demand point) is minimized. A method involving the solution of differential equations by numerical integration is presented. This method is computationally comparable to many existing heuristic and iterative methods. It avoids the frequent convergence difficulties associated with many iterative methods for p > 1 and has no difficulties in dealing with Targe “clusters” of facilities of p = 1.
Integer Programming Solution of a Classification Problem
Authors: Liittschwager J. M. , Wang C.
Published: November 2008

A classification problem is presented in which it is desired to assign a new individual or observation with k characteristics to one of two distinct populations based upon historical sets of samples from the two populations. The resulting classification problem is formulated as a mixed-integer programming problem. The solution, which can be obtained through use of a partitioning algorithm based on Benders decomposition, provides a nonparametric classification statistic which minimizes the expected total cost of misclassification. Also, an enumeration algorithm is developed for the special case of k = 2. Monte Carlo studies are reported which compare the results of the enumeration algorithm with Anderson's “normal” procedure for different underlying distributions. The performance of the enumeration algorithm is shown to be significantly better than Anderson's normal procedure for distributions with uncorrelated normal populations with unequal covariance matrices and for uncorrelated skewed populations with equal covariances.
Optimal Resource Allocation in Community Hypertension Programs
Authors: Nichols Albert L. , Weinstein Milton C.
Published: November 2008

This paper presents a simple model to guide the efficient allocation of resources in community programs to detect and treat hypertension. We model such programs as n-component series systems, where each stage must function in sequence in order for the system as a whole to operate. The model differs from standard series reliability models in that, if a component fails, costs at subsequent stages are not incurred. This “pay-as-you-go” aspect implies that widespread screening is inefficient, and that resources could be better spent ensuring continued treatment of identified hypertensives. Calculations based on actual programs suggest that an optimal allocation of a fixed budget could increase significantly the number of hypertensives controlled, by about 40 percent in our example. This conclusion is robust under all but the most pessimistic assumptions.
The Role of Team and Task Characteristics in R&D Team Collaborative Problem Solving and Productivity
Authors: Daley Robert C.
Published: November 2008

Antecedents of collaborative problem solving in R&D teams have received little attention. Furthermore, the relationship between this form of problem solving and R&D team productivity remains unarticulated. This lacuna is addressed in the present study be analyzing the relationships between task and team, properties, collaborative problem solving and team productivity. Multiple regression was used to study the relationships among these variables. Results indicated that team cohesiveness and task certainty were robust predictors of collaborative problem solving and productivity for 45 R&D project groups. It was found that collaborative problem solving did not have a linear relationship with team productivity The collaborative problem solving-productivity relationship was further examined and it was shown that the relationship was sensitive to high and low levels for each of four predictors used in the research design (task certainty, task interdependence, team size, and team cohesiveness). These empirical findings were then translated into implications for R&D managers.
Innovation Diffusion in a Dynamic Potential Adopter Population
Authors: Mahajan Vijay , Peterson Robert A.
Published: November 2008

Existing single-adoption diffusion models assume a static (constant) ceiling on the number of adopters, that is, a constant population of potential adopters, over the entire time frame of the diffusion process. However, for most innovations this assumption is tenuous. Rather, the ceiling, or the potential adopter population is more likely to be dynamic. The present paper relaxes this assumption and presents a dynamic diffusion model. To illustrate the application of this model, data from two innovations are analyzed.
Strategic Planning for Management Information Systems
Authors: Ein-Dor Phillip , Segev Eli
Published: November 2008

This paper deals with strategic planning for management information systems. Specifically, those variables of the strategic plan which impact on the success or failure of MIS are identified, and propositions are formulated relating states of the variables to system conditions. The variables concerned are the system development strategy, the purpose of MIS, the priority scheme, functions assigned the system, goals, definitions of requirements and documentation of the strategic plan.

Two factors predominate in determining the appropriateness of strategic plans for MIS explicitness (the degree to which the process is conscious, formal and documented) and situational fit (the degree to which the MIS is compatible with the specific organization and its members). It is concluded that there is no one optimal, strategic plan for MIS. Each organization must develop that strategy which best fits its particular situation.
On the Feasibility of Scheduling Lot Sizes for Two Products on One Machine
Authors: Vemuganti R. R.
Published: November 2008

We are concerned with scheduling several products that, require processing or a single machine. Routine application of the economic lot size formula to each product separately, often yields an infeasiable schedule in the sense that there are times when it specifies simultaneous production of two or more products. Feasibility is guaranteed if a common cycle length (and thus equal set-ups per year per product) is chosen. However it is possible to find schedules by allowing variations in the number of set-ups among the products which cost less than the cost of the common cycle length schedule. In this paper we present a necessary and sufficient condition for the feasibility of scheduling two products, when the number of set-ups for each product are givers. Also a method of constructing the schedules is discussed.
An Algorithm for the Dynamic Lot-Size Problem with Time-Varying Production Capacity Constraints
Authors: Baker Kenneth R. , Dixon Paul , Magazine Michael J. , Silver Edward A.
Published: November 2008

We consider the situation of a single item having a deterministic, time-varying demand pattern. Production lot sizes, so as to minimize the total of setup and carrying costs, are to be determined subject to production capacity restrictions that can vary with time. Two important theorems concerning properties of the optimal solution are exploited in developing a tree search algorithm. In addition, other properties are utilized to reduce the amount of search necessary. Results of extensive tests are presented and discussed.
Note—On Optimal Resource Allocation in Community Hypertension Programs
Authors: Ahmed Roken
Published: November 2008

In Management Science (Vol. 24, No. 14, October, 1978), Nichols and Weinstein describe a model of a hypertension detection and treatment program, in which individuals proceed through a series of stages with transition probabilities that depend on expenditures at each stage. We generalize the model to include the case where the number of persons in the first stage is a decision variable. Surprisingly, this more general model is simpler to solve since it is shown that optimal transition probabilities and expenditures at any stage do not depend on probabilities and expenditures at later stages. The result is applied to simple cost functions fitted to data from the numerical example of Nichols and Weinstein. We also consider a more general form of the objective function, and present an algorithm for solving the resulting optimality conditions.
Note—Optimal Strategies on Fourth Down
Authors: Carter Virgil , Machol Robert E.
Published: November 2008

An attempted field goal on fourth down, with short yardage required for first down, is a considerably poorer strategy than is generally thought.
Note—Single and Double Vertex Substitution in Heuristic Procedures for the p-Median Problem
Authors: Eilon Samuel , Galvão Roberto D.
Published: November 2008

The p-median problem is an uncapacitated minisum network location problem where it is required to site p facilities in a network, so that the sum of the shortest distances from each of the nodes of the network to its nearest facility is minimized. An existing heuristic procedure for this problem is extended, and computational experience is provided for several cases. A simple vertex addition heuristic and its use as a “pre-processor” to the extended procedure is described and tested for a number of problems.
A Composite Heterogeneous Model of Brand Choice and Purchase Timing Behavior
Authors: Zufryden Fred S.
Published: November 2008

A stochastic model of purchase behavior is developed to aid marketing managers analyze and predict consumer purchase behavior. The model is based upon a composite structure, that is, it integrates several submodel components (e.g., brand choice and purchase incidence behavior) within its structure. Although the overall model is founded upon individual consumer behavior assumptions, it provides measures of market behavior by aggregating individual behavior parameters over a heterogeneous population of consumers. Thus, the model is developed from assumptions of relevant probability laws that relate to individual consumer's probability of brand choice and the time between product class purchases; as well as the distributions of brand choice probability and the average product class purchase rate of individuals over the population of consumers. The model provides aggregate market behavior measures including brand market share, expected brand sales and the distribution of brand purchase probability over the consumer population through time. Other measures of market behavior of potential use to marketing managers, such as the cumulative penetration, trial and repeat purchase ratio for a given brand, are also derived from the brand's aggregate theoretical purchase distribution.
Workforce Scheduling with Cyclic Demands and Day-Off Constraints
Authors: Baker Kenneth R. , Magazine Michael J.
Published: November 2008

We examine the problem of scheduling days off in continuous (seven-day-a-week) operations under a variety of day-off policies, when demand for manpower is N on weekdays and n on weekend days. We consider a number of policies governing employee work assignments and in each case we give a formula for the minimum workforce size and a schedule construction algorithm.
Successful Information System Development Projects
Authors: Debrabander Bert , Edström Anders
Published: November 2008

It is generally agreed between researchers and practitioners that user involvement is a key to the success of computer based information systems. This paper treats user involvement within the framework of a dyadic (two party) communication relationship between user and specialist. We add to previous work in three respects. First, the theoretical framework is enriched by specifying what we consider to be important contingency factors for the interaction between user and specialist. Second, a formal theory for predicting the success of information system development projects is developed. Third, one important managerial tool to establish effective user-specialist communication is suggested.
Assessment of Alternative Management Forms in Academic Interdisciplinary Research Projects
Authors: Birnbaum Philip H.
Published: November 2008

Interdisciplinary research projects in academic institutions are classified using cluster analysis on their structural properties of size, stability of membership, number of hierarchical levels, division of labor, and the proportion of professional staff with doctoral degrees, masters degrees but not doctorates, and bachelors degrees but neither a masters degree nor a doctoral degree. Within each type, management actions such as time spent planning and assembling resources together with task and relationship oriented behaviors were evaluated for differences between high and low performing projects within each structural type and across types in order to identify those which enhance effective performance. Large stable projects with highly educated personnel performed best. Leaders who exhibited task oriented behaviors had higher performing projects regardless of structural type. Findings that time spent planning interdisciplinary research is not associated with higher performance are different from previous findings for noninterdisciplinary research.
Statistical Model Comparison in Marketing Research
Authors: Barry Christopher B. , Wildt Albert R.
Published: November 2008

Analysis for marketing decisions often involves the consideration of several alternative statistical models. As an intermediate step prior to making policy decisions, a single model is typically selected and used to guide subsequent decisions. In this paper, Bayesian model comparison methods are shown to lead to a predictive distribution for the decision problem without the intermediate step of model selection. This approach utilizes all available information bearing on the validity of the alternative models, as well as information concerning model parameters, in order to draw inferences regarding the criterion of interest relative to the decision to be made. The procedure is illustrated in the context of an advertising budget decision in which the functional form of sales response to advertising is unknown.
Solving the Project Time/Cost Tradeoff Problem Using the Minimal Cut Concept
Authors: Phillips Steve , Dessouky Mohamed I.
Published: November 2008

This paper introduces a solution procedure for solving the project time/cost tradeoff problem of reducing a project duration at a minimum cost. The solution to the time/cost problem is achieved by locating a minimal cut in a flow network derived from the original project network. This minimal cut is then utilized to identify the project activities which should experience a duration modification in order to achieve the total project reduction. The paper will document this cut-based procedure and provide a practical application to a project situation.
A Bayesian Approach to a Generalized House Selling Problem
Authors: Albright S. Christian
Published: November 2008

The problem of choosing the one best or several best of a set of sequentially observed random variables has been treated by many authors. For example, the seller of a house has this problem when deciding which bids on the house to accept and which to reject. We assume that the bids are identically distributed random variables and at most n can be observed. Each bid is accepted or rejected when received; a bid rejected now cannot be accepted later on. The object is to maximize the expected value of the bid actually accepted. Unlike most previous authors, we examine the case where one or more parameters of the common underlying distribution are unknown and information on these is updated in a Bayesian manner as the successive random variables are observed. Using the properties of location and scale parameters, an explicit form for the optimal policy is found when the underlying distribution is normal, uniform, or gamma and the prior is from the natural conjugate family. Simulation results concerning sensitivity of the value obtained to the amount and correctness of the prior information for these three families is then presented.
Job-Shop Scheduling by Implicit Enumeration
Authors: Lageweg B. J. , Lenstra J. K. , Rinnooy Kan A. H. G.
Published: November 2008

The classical combinatorial optimization problem of minimizing maximum completion time in a general job-shop has been the subject of extensive research. In this paper we review and extend this work. A general bounding approach is developed which includes all previously presented lower bounds as special cases. The strongest bound obtainable in this way is combined with two enumeration schemes, the relative merits of which are discussed. The results of some computational experiments and a large bibliography are included as well.
State-of-the-Art—Networks of Queues—A Survey of Equilibrium Analysis
Authors: Lemoine Austin J.
Published: November 2008

Queueing network models abound in applications, but despite their importance many of the results for these models, both classical and recent, are not well known. The intent of this paper is to provide an overview of available equilibrium results for “general Jackson systems,” that is, queueing network models of the sort introduced in the classical papers of Jackson [Jackson, J. R. 1957. Networks of waiting lines. Oper. Res. 5 518–521; Jackson, J. R. 1963. Jobshop-like queueing systems. Management Sci. 10 131–142.]. In addition, we discuss methodology which has been employed to obtain the equilibrium results and we call attention to some important open problems. Detailed discussions are limited to a small group of papers which seem important to us, and there is considerable emphasis on recent work appearing in the applied probability literature. The list of references does include, however, work not reviewed here, along with other survey and background material.
Stochastic Horizons for the Aggregate Planning Problem
Authors: Kleindorfer Paul , Kunreuther Howard
Published: November 2008

This paper develops a methodology for showing how forecast horizons for stochastic planning problems relate to the planning procedures and the information system within the organization. To illustrate the approach we have chosen a relatively straightforward production problem where the firm can meet a fluctuating demand pattern through a combination of overtime and inventory-related options. We show that the optimal production plan is monotonically non-decreasing in the demand sequence so that bounds can be placed on the optimal first period production plan for an N-period problem. These bounds together with information and computationally-related costs are used in specifying a methodology for determining forecast horizons. An illustrative example suggests that such horizons are likely to be small in many realistic cases. The concluding section indicates how this methodology can be utilized for specifying stochastic horizons for more general aggregate planning decisions in organizations.