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This study examines physicians' responses to complex information technologies (IT) in the health care supply chain. We extend individual-level IT adoption models by incorporating a new construct: system accessibility. The main premise of the study is, when faced with a decision between alternate IT systems, individual users tend to select and make use of the technology or system that is most readily accessible. We discuss both physical and logical dimensions of accessibility as they relate to adoption of electronic medical records (EMR). Physical accessibility refers to the availability of computers that can be used to access EMR, while logical accessibility refers to the ease or difficulty of logging into the system. Using data from a survey of 199 physicians practicing in a large U.S. hospital, we show that, when deciding between the paper chart and EMR, accessibility is an important consideration in a physician's decision to use the system. Both dimensions of accessibility act as barriers to EMR use intentions through their indirect effect on physicians' perceptions of EMR usefulness and ease of use. Logical access also has a direct effect on EMR use intentions. We conclude that accessibility is an important factor that limits acceptance of complex IT such as EMR. [ABSTRACT FROM AUTHOR]

Several behavioral scientists have contributed to special issues of the "Decision Science" journal. K. MacCrimmon and J. Siu tackled the significant problem of modeling and measuring and individual decision maker's inevitable trade-offs. The authors find that the choice mode consistently exceeds the equivalence mode in its predictive accuracy. R. Duncan's paper examined possible determinants of the structure of decision units within organization. A. Delbecq studied contextual variables affecting decision making in program planning. Lastly, V. Vroom and A. Jago wrote a paper about decision making as a social process.

This article focuses on Professor I.I. Cummings' timely and thought-provoking mapping of the current state of organizational behavior. It is suggested that an important challenge facing organizational behavior is to reconcile the approaches to research and to capitalize on the contributions made in developing the field. There should be integration in organizational behavior and behavioral decision-making literature. Alternate models of choice in organizational contexts should be developed. Research methods used in behavioral decision making should be re-evaluated. Emphasis should be given on the strategic aspects of behavioral decision making.

The article comments on several research articles contributed to the "Decision Sciences" periodical in 1974 by behavioral scientists who are producing scholarship contributory to effective decision making and implementation. The research articles offer a range of theory, new empirical data and critical review from multiple behavioral disciplines. The article discusses each research paper and examines its key contributions to studies on decision making and decision theory.

A call for papers from "Decision Sciences" journal for an issue devoted to novel advances in applications of the newsvendor model, is presented.

Project portfolio selection (PPS) is a complex problem faced by major companies whenever there are multiple funding opportunities with insufficient budget to fund them all. In this paper, we present our work on a PPS decision support tool that has become a fundamental part of the project portfolio decision process at Intel Corporation across its largest product and market divisions. The paper builds on a previous publication that outlines the decision support tool's bicriteria optimization model by providing a solution procedure that is capable of solving real‐life PPS problems within time frames acceptable to decision makers, as well as providing further details on the data collection and the decision‐making process. We also report on various analysis and visualization tools that have been built to allow decision makers to interact with promising solutions provided by the decision support tool. One of the contributions of the paper is to present a typology of the important dependencies between projects that needs to be considered, and provide details on how they are incorporated in the decision support tool's optimization engine. We discuss important implementation details on the decision‐making process and the agents involved, and conclude by describing real‐life experiences on how the framework can enable intuitive decision‐making when choosing portfolios that best satisfy the organization's business goals. [ABSTRACT FROM AUTHOR]

The article calls for papers for an issue of the journal "Decision Sciences" focusing on "Novel Advances in Applications of the Newsvendor Model."

A call for papers for the issue of "Decision Sciences" journal devoted to the interaction of product modularity and supply chain management, is presented.

A call for papers from "Decision Sciences" journal for an issue devoted to supply chain decisions in governmental organizations, is presented.

Manuscript data and criteria for the October 1971 issue of the "Decision Sciences" are presented. Members of the editorial board are listed together with their affiliations. A table of content is also given. The editorial policy and objectives of "Decision Sciences," the official journal of the American Institute for Decision Sciences (AIDS), are discussed. AIDS is an organization committed to promoting the development and application of quantitative methodology to functional and behavioral problems or administration by providing a forum for the exchange of ideas, experience and information among those who teach in collegiate schools of business and among those who have a special interest in the development and use of quantitative methodologies. The message of the last article of Albert J. Simone as periodical editor is discussed. Simone formally turn over the editorship responsibility to Professor William S. Peters.

Night delivery is an approach increasingly used by motor carriers to improve the efficiency of business‐to‐business logistics. Many benefits of night deliveries have been reported in the literature, but in practice, not every carrier is benefitting from night deliveries. In fact, anecdotal evidence suggests that many carriers are losing money from night deliveries. While a limited number of past studies have discussed the disadvantages of night deliveries, in many cases, they cannot explain why carriers are not benefitting from night deliveries. This implies that some disadvantages of night deliveries may still be currently unknown. This paper seeks to identify such "hidden" disadvantages by studying this issue through the lens of transportation economics. Understanding such disadvantages can contribute to both theories and practice of night deliveries, especially for decision making on night‐delivery adoption by carriers, as it can lead to a better understanding of when and where night deliveries might be beneficial or detrimental. [ABSTRACT FROM AUTHOR]

A call for papers on the decisions of supply chain in governmental organization is presented.

In recent years, the area of Supply Chain Management has generated a substantial amount of interest both by managers and researchers. This interest has also been fueled by the growth in the development and application of e-business technologies. These technologies enable the supply chain manager to make coordinated decisions by integrating the diverse and sometimes conflicting objectives of the various trading partners in a chain. The purpose of this paper is to: (a) highlight strategic and tactical issues for analyzing supply chains in an e-business setting based on papers published in this special issue; and (b) describe future research opportunities in this emerging interdisciplinary area. [ABSTRACT FROM AUTHOR]

Operational risk management (ORM) is critical for any organization, and in the big data era, analytical tools for operational risk management are evolving faster than ever. This paper examines recent developments in academic ORM literature from the data analytics perspective. We focus on identifying present trends in ORM related to various types of natural and man‐made disasters that have been challenging all aspects of life. Although we examine the broader operations management (OM) literature, we keep the focus on the articles published in the well‐regarded OM journals, including both empirical and analytical outlets. We highlight how the use of data analytics tools and methods have facilitated ORM. We discuss the need for data monitoring and the integration of various analytical tools into decision making processes by classifying the literature on application fields, analytics techniques, and the strategies used for implementation. We summarize our findings and propose a process to implement data‐driven ORM with future research directions. [ABSTRACT FROM AUTHOR]

ABSTRACT This invited paper discusses theory development in operations management. Many stellar researchers have made excellent contributions to theory development in our field. Operations management is a maturing discipline. Recently, theory driven empirical research has become common in top-tier journals in our field. Impelled by this trend and due to the path dependency of research, in general, researchers have examined operations phenomena using theories from management and organizational science. How do we extend the frontiers of knowledge in our maturing discipline? How do we develop theories within the field of operations management? In examining some of the seminal ideas that have shaped our field, a common characteristic is that they relied on observational studies and conceptual reasoning. Is it time for us to stress the usefulness of qualitative research methods in our field? Could this lead to an intellectual renewal in our field and extend the frontier of a maturing discipline? This paper explores these questions and advances the notion that qualitative analysis needs to be emphasized more than it has been in recent past. This paper is meant to provoke discussion among empirical researchers in operations management. [ABSTRACT FROM AUTHOR]

Often, data in multi-criteria decision making (MCDM) problems are imprecise and changeable. Therefore, an important step in many applications of MCDM is to perform a sensitivity analysis on the input data. This paper presents a methodology for performing a sensitivity analysis on the weights of the decision criteria and the performance values of the alternatives expressed in terms of the decision criteria. The proposed methodology is demonstrated on three widely used decision methods. These methods are the weighted sum model (WSM), the weighted product model (WPM), and the analytic hierarchy process (AHP). This paper formalizes a number of important issues on sensitivity analysis and derives some critical theoretical results. Also, a number of illustrative examples and computational experiments further illustrate the application of the proposed methodology. [ABSTRACT FROM AUTHOR]

This paper examines how computer-based support for strategic decision-making processes varies across the phases of decision making under a variety of conditions (represented by five contingency variables). The paper draws extensively from empirical research on the strategic decision-making processes, recognizing that these processes can be conducted in different ways. The relationships between the modes of the strategic decision process, the contingency variables, and the characteristics of computer based support are examined. The paper thus represents an important first step towards deriving prescriptive implications for designers of computer-based support, whereby they can understand and design tools/ systems for various phases and types of strategic decision-making processes. [ABSTRACT FROM AUTHOR]

This paper pertains to goal programming with fuzzy goals and fuzzy priorities, Hannan [1], in his paper on fuzzy goal programming, alludes to the difficulty of handling fuzzy priorities and further notes that a method that this author proposed [2] may lead to incorrect results. In this note, the general problem of goal programming with fuzzy priorities is reexamined, along with the solution to the specific example presented in my original paper[2]. It is shown that the method for handling fuzzy priorities originally proposed by this author does indeed capture the relative importance of goals. [ABSTRACT FROM AUTHOR]

Our reply to Curry, Louviere, and Augustines critique of our earlier paper focuses on differences in motivation between our research and theirs. Our interest in the problem relates to the possible incorporation of self-explicated evaluations in conjoint data collection methods; subsequent to the appearance of our original paper, we have developed hybrid models that combine elements of self-explicated (compositional) and conjoint (decompositional) data collection procedures. As far as we can surmise from their critique, Curry, Louviere, and Augustine are concerned with much broader strategic issues relating share of choices in the consumer population to changes in the shape of attribute weight distribution, shape of the Parero tradeoff boundary, and so on. [ABSTRACT FROM AUTHOR]

The model developed in this paper is interdisciplinary in that we incorporate the advertising decision into the capital asset pricing model (CAPM) for valuation of risky income streams. The advertising decision involves the purchase of media services whose effects on sales (profit) are hypothesized to vary with general economic activity. As in any asset expansion, the firm purchases an income distribution with a given expected value and covariance with the economy. By consulting the CAPM, we are able to obtain a value for the income distribution associated with the advertising expenditure. By failing to account for both risk and return, those previous studies which have examined the effect of advertising on profit or valuation are, at best, incomplete. We are able to demonstrate the inappropriateness of ranking alternative advertising strategies solely on the basis of expected income. [ABSTRACT FROM AUTHOR]

The topic of behavioral objectives has recently received considerable attention in the academic community. This paper contains a comprehensive overview of issues and explores the relevance of using the behavioral objective framework for teaching quantitative methods (QM) to undergraduate business administration students. Included in the paper are (1) a discussion of the nature and meaning of behavioral objectives, (2) arguments for and against their use, (3) a rationale for their use in a QM course, and (4) a series of examples demonstrating the use of behavioral objectives in a quantitative course. The evidence—consisting of expert opinion from professionals who have successfully used behavioral objectives for teaching quantitative material, the logic of the arguments for behavioral objectives, consideration of arguments against objectives along with rebuttal to these arguments, and the available empirical studies—indicates that behavioral objectives do appear to offer considerable potential for improving QM teaching. The use of behavioral objectives is worthy of thoughtful consideration by QM teachers. [ABSTRACT FROM AUTHOR]

The comments of Horowitz (1998) on the Prakash, Chang, Hamid, and Smyser (1996) paper are specifically directed towards Lemma 4 of the original paper. This reply proposes that Horowitz fails to recognize that the conditions stated are only necessary but not sufficient, and solutions can be obtained for some specific utility function for a given level of wealth in the case of a neutral gamble and for a range of wealth for unfair gambles. We derive the conditions to show that a risk preference function that satisfies the restrictions of Lemma 4 can exist for a given level of wealth. [ABSTRACT FROM AUTHOR]

The subject of this paper is modelling and forecasting of cash flows generated by a capital investment. The paper proposes the application of autoregressive, moving average, and mixed autoregressive moving-average processes to capital budgeting. In addition, models for deterministic, stochastic and seasonal trends are considered. For each class of cash flows, analytical expressions are developed for the mean and variance of a project's net present value (NPV). Also considered are several equilibrium pricing models. For two of them, the forecasting methodology developed here is integrated into the pricing equation. Although the overall emphasis of the paper is on modelling and forecasting of cash flows, the implications for NPV pricing and risk analysis are also investigated. Several examples are used to illustrate the impact of particular cash flow models on the price and risk of a project. [ABSTRACT FROM AUTHOR]

This paper examines some approaches to decision problems under uncertainty. Starr's domain criterion is presented and modified to take into account different philosophies concerning the desirability of winning versus the importance of avoiding losses. The concept of expected value of distribution information is defined and its computation is illustrated with a numerical example. Target values are then introduced into the model and a parametric procedure is used to maximize the chances of achieving a certain level of the given objective. Finally, we show how the concepts developed in this paper might provide further insight into some decision, situations reported in the literature. [ABSTRACT FROM AUTHOR]

Management does not directly observe cost variance processes from the production system; instead, management depends on a report from the cost variance information system as to whether a process is in control or out of control. Unfortunately, cost variance information systems are not always perfectly reliable. Accordingly, this paper extends the cost variance analysis model to include reliability of the cost variance information system. Reliability is introduced by distinguishing between the report from the information system and the actual cost variance. Although previous cost variance models do not include reliability, management is still likely to be aware of the lack of reliability in cost variance systems. To account for this lack of reliability, management is likely to use any of a number of heuristics. This paper demonstrates that ad hoc heuristics are unlikely to result in the same solutions suggested by the analytic model. In addition, it is shown analytically that not including reliability in cost variance models can lead to examining variances that do not require investigation and not examining variances that do require investigation. [ABSTRACT FROM AUTHOR]

This paper studies the impact of variable and fixed transaction costs on investment decisions under conditions of risk. The decision model is first formulated as a mixed-integer nonlinear program. The following subjects are then examined: the structure of the investment frontier facing the investor and the effects of transaction costs on this frontier, the impact of transaction costs on the investor's optimal investment strategy, and the conditions for the equilibrium structure of risky asset prices and risk-return relationships. The main finding is that the relaxation of the assumption of the absence of transaction costs eliminates some of the most unattractive implications of the classic capital asset pricing model (CAPM) while preserving the more attractive implications of this model. Also, our model provides explanations for some discrepancies between the theoretical CAPM and empirical findings and, therefore, is a step toward narrowing the gap between theory and practice. [ABSTRACT FROM AUTHOR]

An earlier paper and subsequent commentaries in Decision Sciences described purportedly new methods for formulating and solving goal programming problems with fuzzy goals. This note suggests that much of what these articles propose is but a rediscovery of well-known results. [ABSTRACT FROM AUTHOR]

This paper presents an application of fuzzy subsets to the problem of selecting sites for locating gas stations. Cost minimization and profit maximization models represent typical approaches to location decisions. These approaches are not well-suited to problems like site selection for gas stations because of the difficulty in identifying precise relationships, the uncertainties involved, and the qualitative and imprecise nature of much of the information used for decision making. This paper proposes the use of a model based on linguistic variables and a direct evaluation of the available alternatives via the use of fuzzy variables. Conclusions regarding the practical advantages and limitations of the approach are drawn based on the reported application. [ABSTRACT FROM AUTHOR]

This paper proposes a decision rule to rank actions under strict uncertainty, the available information being limited to the states of nature, the set of alternative rows, and the consequence of choosing every row if a given state occurs. This rule is suitable to moderately pessimistic individuals and social groups, these agents being neither maximax nor maximin decision makers but people who assume that the best outcome from the action will not occur. For these decision makers the paper shows the existence of a consistent weight system in which one and only one weight is attached to each state of the world under plausible conditions of domination. Most of the traditional axioms are satisfied by the proposed ranking approach. In the frame of disappointment (measured by ranges of column dispersion), the meaning of some controversial postulates used in the literature is explained. The proposed criterion is a departure from Laplace's (1825) rule and from the remaining standard criteria. Only in the special case of equal column dispersion do both Laplace's rule and the proposed weights lead to the same solution. [ABSTRACT FROM AUTHOR]

Three conceptual and methodological issues of the preceding paper by Bonoma and Johnston are identified and discussed. A theoretical integration of interpersonal trust and locus of control is made, and some necessary conditions for an interpersonal trust-relevant decision-making situation are pointed out. Implications for the design of future research into trust-relevant decision making are drawn. [ABSTRACT FROM AUTHOR]

This paper proposes a method, canonical rotation analysis, which facilitates the substantive interpretation of results in multivariate analysis. Canonical rotation analysis is developed as a model which integrates multivariate least squares approaches and the varimax rotation criterion. The generalized applicability of the model to canonical correlation, multiple discriminant analysis, and multivariate analysis of variance is developed. The advantages and limitations of canonical rotation analysis are discussed and illustrated in the context of an industrial marketing research problem. [ABSTRACT FROM AUTHOR]

While many problems of uncertainty are commonly analyzed by means of stochastic models, under certain circumstances this may not be an appropriate approach. The latter situation arises when the decision maker knows that the uncertain variables are not generated by a stochastic process, or when he is unwilling, or unable, to compute subjective probabilities. One of the nonstochastic approaches to uncertainty is the expectational approach in which the decision maker forms deterministic expectations about the uncertain aspects of his environment. This paper is concerned with some criteria for selecting among available expectations, or anticipations functions, and the possibility of ordering them according to these criteria. This study focuses especially on the learning criterion. The discussion brings out conceptual problems in connection with the definition of learning, as well as some technical difficulties that one encounters when attempting to compare different anticipations functions from the point of view of the learning criterion. As an illustration of the issues discussed, the paper reports on the results of some simulated decision rules. These show that decision rules in which no learning takes place, and in which some information is ignored, may perform better than more sophisticated rules. [ABSTRACT FROM AUTHOR]

Beginning with the information economics framework and a multi-period decision model, this paper considers the use of computer simulation methods within an information system choice environment. Actual decision behavior is replaced by optimal decision rules, and simulation is used to evaluate the effects of parameter changes in the environmental model. Simulation is shown to be functional (1) in estimating the value of alternative information structures within a fifteen period decision model and (2) in providing sensitivity and statistical data which would be useful both for different decision maker utility functions and for a variety of information system design questions. [ABSTRACT FROM AUTHOR]

This paper examines the judgmental processes of individuals involved in stock selection through the use of discrimination nets. Research has shown that there is no incompatibility in the so-called random walk model and the fundamentalist or intrinsic approach. Doing systematically better than the average investor implies that the superior investor has a superior way of evaluating existing information. An improved market success depends in part on an increased understanding of investors decision making processes. Thus, if a superior investor's judgmental processes can be demonstrated and readily modeled, then, the next step would be to compare these decision processes with those of the average investors and note differences. The results of this study showed that the decision-making processes of individuals not only can be adequately programmed, but that the decision process is rather stable for a given investor. The paper also shows, however, that while the model accurately predicted accept or reject decisions, in most cases it was limited in its ability to rank order securities from the set of accepted investments. [ABSTRACT FROM AUTHOR]

This paper deals with the problems of hotel overbooking and the scientific determination of hotel booking policies. The general hotel reservations system is described, and a Markovian sequential decision model is proposed for it. An application of the model is presented, based on an actual sample of hotel data. Because of the significance of the cancellation phenomena in the sample, the model prescribes a substantial amount of overbooking. The paper concludes with comments regarding the necessity for and course of future research in this area. [ABSTRACT FROM AUTHOR]

Most of the initial work on perishable asset revenue management (PARM) situations assumed no possibility of customer diversion from one product class to another when the former is made unavailable. In this paper, an evaluation is made of the few published decision rules that incorporate the realistic and common behavior of customer diversion (or sell-up). We present a new heuristic approach that incorporates diversion and could be used by airlines and other relevant industries to achieve improvements in expected contribution of 0.25 to 2.5% over the approach currently used. The sensitivity of the difference in expected contribution between these rules is tested relative to changes in the input parameters, and managerial insights are presented. [ABSTRACT FROM AUTHOR]

This paper describes the properties of nonlinear dynamical systems in demand data and assesses the implications for inventory management. A test from Brock, Dechert, and Scheinkman (BDS) [6] for detecting nonlinearities is presented. This test assists inventory managers with two issues. First, it can be used to detect departures from the independence and stationarity assumptions of particular inventory models, thereby identifying the need for more suitable models. Second, the BDS test can determine whether forecasting model improvements are possible, and can measure improvements in the forecasting model process. The corresponding reductions in forecast errors improve inventory management and lead to reduced inventory costs. Using actual weekly demand for oil filters, this paper demonstrates the use of the BDS test and the effects of nonlinearities in demand data on inventory model performance. [ABSTRACT FROM AUTHOR]

If quantity uncertainty exists in a first price auction that specifies a fixed bid, a participant must answer two questions when evaluating a candidate bid: "What are my chances of winning?" and "What is the effect of the winner's curse on my quantity estimate?" The winner's curse is the tendency of the winner of a first-price sealed-bid auction to be the bidder that most overvalues the items being offered. When value uncertainty is due to quantity uncertainty, the winner's curse implies that the bidder that most overestimates the quantity tends to win. Thus, if there is quantity uncertainty, a participant must adjust its bid for this tendency to overestimate quantities. This paper presents an empirical method to answer the above questions by estimating predictive distribution of the highest competing bid and the quantity bias caused by the winner's curse. The method is developed for timber auctions but is general to auctions where a fixed bid is called for and there is uncertainty in the mix and quantities of items being offered. An example that uses data from timber auctions is used to demonstrate the method. [ABSTRACT FROM AUTHOR]

Decision support system (DSS) researchers and designers continue to look for unstructured organizational tasks where there is a critical need for intelligent computer-based support. One such decision task is information requirements determination. Requirements determination is recognized as the most crucial phase of the systems development life cycle. Unfortunately, most methodologies and CASE tools focus only on how to specify the requirements once they are determined. There is very little computer support for the process of determining requirements. This paper discusses the conceptual design and development of a knowledge-based DSS to support information analysts in the critical decision task of determining requirements for the design of effective information systems. The expert modeling support system has the expertise to assist the analyst in studying the organization as a whole and in modeling the system under study in the context of the overall organization's goals and needs. The focus of the paper is on the problems associated with building the knowledge base component of the intelligent decision support system. A prototype implementation of the system is described. [ABSTRACT FROM AUTHOR]

Most models of investor behavior assume a time-state independent utility function and result in a deterministic solution where a given set of inputs uniquely specifies the decision. In contrast, a state preference model using a time-state dependent utility function is derived in this paper. The model allows the investment choice decision to be analyzed in a game theoretic context. The general solution is a mixed strategy which allows for a probabilistic interpretation of the decision. The approach presented in this paper can accommodate anomalies such as intransitivity of preference and satisficing as rational behavior. An example of a possible implementation is given along with interpretations of the outcomes. [ABSTRACT FROM AUTHOR]

This paper proposes an object-oriented approach to the development of interactive software for the purpose of managerial problem solving. A prototype is being developed using CSM causal mapping to represent each manager's perceptions of the relationships between key variables of a firm's strategic situation. This paper suggests the design of GDSS that would enable a group of managers to discuss, learn from each other, and possibly develop consensus about decisions or their causes. Issues involving future development are discussed. [ABSTRACT FROM AUTHOR]

In an earlier paper, the problems of rank reversals and invalid composite priorities in AHP were addressed by modifications to the AHP procedure. That solution was subsequently criticized. In this paper, we rebut these criticisms, and we show how rank reversals in AHP can arise merely from the process of normalizing local priorities. [ABSTRACT FROM AUTHOR]

This paper presents a framework that links strategic MIS planning and business strategy and relates it to competitive advantage and company performance. To achieve this objective, the paper first delineates the dimensions of strategic MIS planning, focusing on both content and process issues. The notion of fit within dimensions, between sets of dimensions (process and content), and between MIS planning and competitive strategy is also introduced. Next, employing the Miles-Snow typology of business strategy, the paper posits normative differences in the dimensions of strategic MIS planning along different business (or competitive) strategies. The implications of our study for both decision makers and scholars are discussed. Propositions that tie competitive strategy, strategic MIS planning, and company financial performance are then presented. The paper concludes by providing direction for future research. [ABSTRACT FROM AUTHOR]

A criticism of linear programming has been that the data which are available in practice are too inexact and unreliable for linear programming to properly work. Managers are therefore concerned with how much actual values may differ from the estimates that were used in the model before the results become irrelevant. Sensitivity analysis emerged to help deal with the uncertainties inherent in the linear programming model. However, the ranges calculated are generally valid only when a single coefficient is varied. An extension of sensitivity analysis, the 100 Percent Rule, allows the simultaneous variation of more than one element in a vector, but does not permit the independent variation of the elements. A tolerance approach to sensitivity analysis enables the consideration of simultaneous and independent change of more than one coefficient. However, the ranges developed are unnecessarily restricted and may be reduced in width to zero when primal or dual degeneracy exists. This paper presents an extension of the tolerance approach which reduces the limitations of both the traditional and tolerance approaches to sensitivity analysis. [ABSTRACT FROM AUTHOR]

This paper investigates the mathematical programming (MP) approach for decision making and cost allocation in the context of joint products. Through analysis of the MP approach to marginalvalue-based cost allocations, an algorithm is developed to show that the allocations contain two elements: an element that is specific to individual joint products due to differences in demand elasticities, and an element based on relative adjusted sales values. If demand elasticities are identical for all joint products, then the traditional sales value method will generate the same cost allocation as the MP method. The new algorithm, the demand-adjusted-sales-value algorithm (DASV), is especially helpful for solving the MP model with linear demand functions. The DASV algorithm provides an easy way to generate costs that are useful for optimal decision making. [ABSTRACT FROM AUTHOR]

Drawing upon the choice models developed in the multiple criteria decision making (MCDM) area, this paper proposes an architecture for designing an intelligent decision support system (DSS) that is intended to aid in making choices among multiple alternatives along multiple dimensions. It argues that effective support can be provided to the decision maker when the knowledge-based DSS is capable of dynamically selecting choice models appropriate to the domain and context of a particular problem being specified by the decision maker, and of properly applying them to the problem solution. Development of a prototype intended to partially represent application of the architecture is described. The paper concludes with suggestions for research extensions. [ABSTRACT FROM AUTHOR]

This paper investigates optimal lot-splitting policies in a multiprocess flow shop environment with the objective of minimizing either mean flow time or makespan. Using a quadratic programming approach to the mean flow time problem, we determine the optimal way of splitting a job into smaller sublots under various setup times to run time ratios, number of machines in the flow shop, and number of allowed sublots. Our results come from a deterministic flow shop environment, but also provide insights into the repetitive lots scheme using equal lot splits for job shop scheduling in a stochastic environment. We indicate those conditions in which managers should implement the repetitive lots scheme and where other lot-splitting schemes should work better. [ABSTRACT FROM AUTHOR]

This paper considers the question of how much time and effort should be spent in preparing a bid for a single item of known value sold at a first-price sealed-bid auction. A decision-theoretic approach to this bid decision summarizes the decision maker's knowledge of the competitive environment through his or her subjective probability distribution of the highest competing bid. Research activities such as collecting and analyzing bid histories are efforts to obtain additional information that reduces the uncertainty in the highest competing bid. The decision-theoretic concepts of expected value of perfect and imperfect information are used to place an economic value on such research activities. The results presented allow the decision maker to quantify the expected value of imperfect information when the uncertainty is normally distributed. The results show that additional research is most valuable prior to auctions the bidder expects to win. [ABSTRACT FROM AUTHOR]

This paper defines and solves a set of new problems for two-level hierarchical transportation networks. Given a set of points, the objective is to find the path of a primary link such that a weighted sum of the lengths of the perpendiculars from each point to the primary link and the distance between the feet of the two extreme perpendiculars is minimized. The perpendiculars are the connecting or secondary links and the primary link could be a straight line or a curve. The paper provides an algorithm and computational results for the case in which the primary link is a straight line. Implementation approaches are also discussed. [ABSTRACT FROM AUTHOR]

The paper discusses the value of information when a number of independent sources provide information related to a common set of states of nature. The starting point is the information economic model of information structures. The model is augmented to represent independence of informational sources by means of orthogonality of the information structures. A new mathematical operator, orthogonal product, is defined and its properties are probed. It is shown that this operator maintains some mathematical properties such as closure, association, unity element, null element, and so forth. It is demonstrated how the orthogonal product represents the notion of multisource information. The paper proves that an orthogonal product is generally more informative than its multipliers, namely, if cost is not considered a constraining factor, then there is a nonnegative value to obtaining a second opinion. An appendix to the paper expands this result to a case of partially dependent signals. The paper concludes with a numerical example and a discussion of the model's applicability for practical problems such as cost estimates. [ABSTRACT FROM AUTHOR]