Modeling Values for Anti-Terrorism Analysis

Decisions are made to achieve objectives. A qualitative list of the objectives for a decision is the foundation for a value model that unambiguously represents objectives in a quantitative manner. The objectives guide thinking and the value model provides a basis for analyzing alternatives to best meet the desired objectives. This article illustrates the usefulness of clearly identifying objectives and developing value models to support anti-terrorism analysis. It outlines procedures to develop value models for the Department of Homeland Security and for terrorist organizations. The later is useful to both design anti-terrorism alternatives and suggest possible terrorist priorities and actions. An example that develops a terrorist value model for the theft and misuse of plutonium is presented. Several uses of value models for anti-terrorist activities are discussed and suggestions for developing such value models are outlined.     

Incomplete Contracts: Where do We Stand?

The paper takes stock of the advances and directions for research on the incomplete contracting front. It first illustrates some of the main ideas of the incomplete contract literature through an example. It then offers methodological insights on the standard approach to modeling incomplete contracts; in particular it discusses a tension between two assumptions made in the literature, namely rationality and the existence of transaction costs. Last, it argues that, contrary to what is commonly argued, the complete contract methodology need not be unable to account for standard institutions such as authority and ownership; and it concludes with a discussion of the research agenda.     

The Value of Environmental Information without Control of Subsequent Decisions

The standard value of information approach of decision analysis assumes that the individual or agency that collects the information is also in control of the subsequent decisions based on the information. We refer to this situation as the “value of information with control (VOI‐C).” This paradigm leads to powerful results, for example, that the value of information cannot be negative and that it is zero, when the information cannot change subsequent decisions. In many real world situations, however, the agency collecting the information is different from the one that makes the decision on the basis of that information. For example, an environmental research group may contemplate to fund a study that can affect an environmental policy decision that is made by a regulatory organization. In this two‐agency formulation, the information‐acquiring agency has to decide, whether an investment in research is worthwhile, while not being in control of the subsequent decision. We refer to this situation as “value of information without control (VOI‐NC).” In this article, we present a framework for the VOI‐NC and illustrate it with an example of a specific problem of determining the value of a research program on the health effects of power‐frequency electromagnetic fields. We first compare the VOI‐C approach with the VOI‐NC approach. We show that the VOI‐NC can be negative, but that with high‐quality research (low probabilities of errors of type I and II) it is positive. We also demonstrate, both in the example and in more general mathematical terms, that the VOI‐NC for environmental studies breaks down into a sum of the VOI‐NC due to the possible reduction of environmental impacts and the VOI‐NC due to the reduction of policy costs, with each component being positive for low environmental impacts and high‐quality research. Interesting results include that the environmental and cost components of the VOI‐NC move in opposite directions as a function of the probability of environmental impacts and that VOI‐NC can be positive, even though the probability of environmental impacts is zero or one.     

基于新型图论聚类法的物流系统多设施选址策略研究

提出了一类基于图论的新型聚类算法并将其应用于物流系统中的多设施选址问题。与其他聚类算法相比,该新型算法聚类效率更高且具有更小的聚类树,从而使得有意义的聚类结果更加清晰。比较算例验证了该算法应用于多设施选址问题的高效性和实用性。     

Theory of integer-valued data envelopment analysis under alternative returns to scale axioms

Kuosmanen and Kazemi Matin [Theory of integer valued data envelopment analysis. European Journal of Operational Research 2009;192:658–67] developed an axiomatic foundation for a data envelopment analysis (DEA) model that assumes subsets of input and output variables to be integer valued. In this paper we extend and generalize the axiomatic foundation for the integer DEA under variable, non-decreasing and non-increasing returns to scale. These model variants are achieved by introducing new axioms of natural convexity and natural augmentability. We also develop mixed integer linear programming (MILP) formulations for computing efficiency scores in these environments. An empirical example illustrates the approach.     

Analysing complex decisions for electric utilities

This paper illustrates the use of decision analysis for high level policy making. A specific example describes an analysis of important long-range alternatives affecting the financial environment of the electric utility industry. The value of decision analysis for integrating and communicating the results of economic models is highlighted.     

Environmental impact analysis: A synthetic approach

The authors analyse approaches to environmental impact analysis each of which offers certain advantages. They suggest a new approach which synthesizes the best features of the available approaches and illustrates it with an example of an EIA of a coalfield.     

Nonparametric Estimation of Triangular Simultaneous Equations Models

This paper presents a simple two-step nonparametric estimator for a triangular simultaneous equation model. Our approach employs series approximations that exploit the additive structure of the model. The first step comprises the nonparametric estimation of the reduced form and the corresponding residuals. The second step is the estimation of the primary equation via nonparametric regression with the reduced form residuals included as a regressor. We derive consistency and asymptotic normality results for our estimator, including optimal convergence rates. Finally we present an empirical example, based on the relationship between the hourly wage rate and annual hours worked, which illustrates the utility of our approach.     

Composite Forecasting with Dirichlet Priors*

In this paper, composite forecasting is considered from a Bayesian perspective. A forecast user combines two or more forecasts of an operationally relevant random variable. We consider the case where outperformance is modeled as a realization from a multinomial process. The user has prior beliefs about the probability that a particular method outperforms all others, information which is summarized by the Dirichlet distribution. An empirical example with hog prices in the United States illustrates the method.     

A Note on Compounded Conservatism

Compounded conservatism (or "creeping safety") describes the impact of using conservative, upper-bound estimates of the values of multiple input variates to obtain a conservative estimate of risk modeled as an increasing function of those variates. In a simple multiplicative model of risk, for example, if upper p -fractile (100 p th percentile) values are used for each of several statistically independent input variates, the resulting risk estimate will be the upper p' -fractile of risk predicted according to that multiplicative model, where p' > p . The amount of compounded conservativism reflected by the difference between p' and p may be substantial, depending on the number of inputs, their relative uncertainties, and the value of p selected. Particular numerical examples of compounded conservatism are often cited, but an analytic approach may better serve to conceptualize and communicate its potential quantitative impact. This note briefly outlines such an approach and illustrates its application to the case of risk modeled as a product of lognormally distributed inputs.     

A MODEL FOR EVALUATING IMPERFECT CONTROL SYSTEMS

A model is developed for evaluating alternative control systems for an ongoing managerial process in terms of expected contribution per unit time under conditions of imperfect information. A variety of process failure distributions and economic characteristics are accepted by the model. An example illustrates the versatility of this approach for comparing alternative systems and for performing sensitivity analysis on process and control system parameters.     

AN INTEGRATIVE APPROACH TO PROCESS PARAMETER SELECTION

This case study of a process improvement project from the Hewlett-Packard Analytic Products Group illustrates a number of important approaches for operations strategy. First, we show how process control in capillary tube manufacturing led to a significant improvement in tubing strength, a quality measure that relates to the frequency of tube defects at a particular stress level. Next, we show how one particular approach used for experimental design and process improvement was considerably more economical than another standard method. In conclusion, we link the process characteristics such as defect frequency to strategic measures such as company revenue and investment to underscore the strategic importance of process control.     

EOQ-based inventory management in single-machine multi-item systems

The present paper proposes an approach for including the finite capacity constraint in the EOQ model (and, in more general terms, in inventory systems) to study the context of single-machine multi-item systems. In particular, the proposed approach regulates the processing of different items by a shared resource according to a control model based on an ordering policy that combines the Economic Order Quantity with a policy based on minimum and maximum inventory levels (min–max policy). To achieve such a challenging result, the present work exploits the analogy between “switched arrival systems” (a particular class of hybrid systems) and min-max inventory systems. The development and parameterization of the abovementioned control model, therefore, refers to switched arrival systems control theory and mixed-integer linear programming. The present work also contributes to the integration of static tools (i.e., the EOQ model) and control tools, approaching these areas. The paper concludes with a real case application that illustrates the proposed approach and allows for a future research path to be drawn.     

DEA and ranking with the network-based approach: a case of R&D performance

This study enhances the network-based approach, which is a novel method to increase discrimination in data envelopment analysis. The enhancements include removing the bias caused by a scale difference among organizations and highlighting the approach's ability to identify the strengths and weaknesses of each organization. The former makes the approach applicable to both the constant returns of scale (CRS) and the variable returns of scale (VRS) models. The network-based approach applies the centrality concept developed in social network analysis to discriminate efficient decision making organizations as determined by standard data envelopment analysis (DEA). More specifically, the results of data envelopment analysis are transformed into a directed and weighted network in which each node represents a decision making organization and the link between a pair of node represents the referencing relationship between the pair. The centrality value for each efficient organization provides the base for discrimination and ranking. This network-based approach suggests aggregating DEA results of different input/output combinations such that the merits of each organization under various situations can be considered. The final ranking of this approach favors organizations that have their strengths evenly spread and tends to screen out specialized efficient organizations. As a real world example, the approach is applied to evaluate and rank the R&D (research and development) performance of Taiwan's government-supported research institutes. The cross-organizations and within-organization strengths for each efficient research institute are identified after applying the approach. A two-stage R&D evaluation model separates the R&D process into the technology development and technology diffusion stage. The resulting performance map differentiates the research institutes into four categories—Achievers, Marketers, Innovators, and Underdogs.     

Using data envelopment analysis for the assessment of technical efficiency of units with different specialisations: An application to agriculture

In this paper we consider the use of data envelopment analysis (DEA) for the assessment of efficiency of units whose output profiles exhibit specialisation. An example of this is found in agriculture where a large number of different crops may be produced in a particular region, but only a few farms actually produce each particular crop. Because of the large number of outputs, the use of conventional DEA models in such applications results in a poor efficiency discrimination. We overcome this problem by specifying production trade-offs between different outputs, relying on the methodology of Podinovski (J Oper Res Soc 2004;55:1311–22). The main idea of our approach is to relate various outputs to the production of the main output. We illustrate this methodology by an application of DEA involving agricultural farms in different regions of Turkey. An integral part of this application is the elicitation of expert judgements in order to formulate the required production trade-offs. Their use in DEA models results in a significant improvement of the efficiency discrimination. The proposed methodology should also be of interest to other applications of DEA where units may exhibit specialization, such as applications involving hospitals or bank branches.     

A Duration‐sensitive Measure of the Unemployment Rate: Theory and Application

The measurement of unemployment, like that of poverty, involves two distinct steps: identification and aggregation. In this two‐step process, the issue of identifying the unemployed has received considerable attention but, once the unemployed have been identified, the aggregation issue has been addressed by simply ‘counting heads’: the unemployment rate is conventionally defined as the proportion of the labour force that, on a given date, is unemployed. This, in particular, leads to differences between individuals, in their unemployment experiences being ignored when the unemployment rate is being computed. This paper — predicated on the proposition that what matters to a person is not just the fact of unemployment but also its duration — proposes a methodology, derived from the measurement of income inequality, for adjusting unemployment rates so as to make them ‘duration‐sensitive’. In consequence, different values of the ‘duration‐sensitive’ rate will, depending upon the degree of inequality in the distribution of unemployment duration, and upon the extent to which society is averse to such inequality, be associated with the same value of the conventionally defined unemployment rate. A numerical example, based on published data for seven major OECD counties, illustrates the methodology.     

Der Körper als Ressource in individuellen Veränderungsprozessen

Nowadays the focus on the rational mind dominates big parts of our society. The body and emotions as helpful information are underestimated. The integration and systematical utilization of body based information in coaching processes is an adjuvant approach. This article reports the neurophysiological and -biological basis of behavioural patterns and outlines how to change these patterns applying different methods which use body based information. An example case illustrates the practical implication of the referred theories.     

A Contingent Claims Model of Corporate Pension Obligations*

This study develops a contingent claims model for valuing the implicit market value of the pension claim associated with defined benefit pension plans. In this model, the firm issues pension, debt, and equity claims. These claims have joint access to two underlying portfolios: corporate and pension. The changes in the market values of these two portfolios are assumed to follow a joint lognormal diffusion process. By imposing terminal boundary conditions implied by Employment Retirement Income Security Act (ERISA) rules and the pension insurance provisions of the Pension Benefit Guaranty Corporation (PBGC) on the partial differential equation, a solution for the pension value is obtained. This quasi-market measure of the value of the pension claim may be represented by a portfolio consisting of four components: (1) a risk-free discount bond with face value equal to promised pension benefits; (2) a short put on pension assets with exercise price equal to pension benefits; (3) a long call on 30 percent of corporate assets with exercise price equal to the face value of secured corporate debt; and (4) a short call on 30 percent of corporate assets with a stochastic exercise price which depends on the terminal value of the pension fund. A numerical example using 1992 and 1993 financial statement data from six major U.S. corporations is provided. This example illustrates the usefulness of the model's prediction and the potential effect of theoretical pension values on corporate debt-equity ratios.     

A fuzzy logic evaluation system for commercial loan analysis

This paper introduces an application of fuzzy logic to commercial loan analysis. It describes the fuzzy sets and linguistic variables that contribute to the financial evaluation. It also presents a computer-based Fuzzy Logic Evaluation System consisting of the components Specify Fuzzy Sets, Edit Rules, and Evaluator. The Evaluator performs fuzzification, evaluation, and defuzzification activities. Using company-specific and industry financial data, the current version of the system appraises a company's credit, capital, and capacity performance. A specific example for efficiency analysis illustrates the system constructs.     

Graph productivity change measure using the least distance to the pareto-efficient frontier in data envelopment analysis

This paper proposes a new method to measure productivity change of decision making units in the full input-output space. The new approach is based on the calculation of the least distance to the Pareto-efficient frontier and hence provides the closest targets for evaluated decision making units to reach the strongly efficient frontier with least effort. Another advantage of the new methodology is that it always leads to feasible solutions. The productivity change in the new approach is operationalized as a Luenberger-type indicator in the Data Envelopment Analysis framework and it is decomposed into efficiency change and technical change. The paper empirically illustrates the new method using recent data on the Spanish quality wine sector.