Risk Attitude Of Decision Maker Research Articles

Optimization Research of Urban Public Transport Network from the Perspective of Risk Attitudes of Decision Makers

Optimization Research of Urban Public Transport Network from the Perspective of Risk Attitudes of Decision Makers

Optimal condition-based maintenance decisions for systems with dependent stochastic degradation of components

Components in engineered systems are subjected to stochastic deterioration due to the operating environmental conditions, and the uncertainty in material properties. The components need to be inspected and possibly replaced based on preventive or failure replacement criteria to provide the intended and safe operation of the system. In the present study, we investigate the influence of dependent stochastic degradation of multiple components on the optimal maintenance decisions. We use copula to model the dependent stochastic degradation of components, and formulate the optimal decision problem based on the minimum expected cost rule and the stochastic dominance rules. The latter is used to cope with decision maker's risk attitude. We illustrate the developed probabilistic analysis approach and the influence of the dependency of the stochastic degradation on the preferred decisions through numerical examples.

Optimal Seismic Design Considering Risk Attitude, Societal Tolerable Risk Level, and Life Quality Criterion

The minimum expected life-cycle cost decision rule leads to an optimal design for a risk-neutral decision maker, but fails to incorporate the magnitude of uncertainty in the life-cycle cost and is incapable of coping with risk attitudes. The maximum expected utility decision rule results in a utility function dependent optimal decision that may not be accepted by a decision maker with a different utility function. This study develops a framework for selecting efficient or optimal seismic designs by considering the decision maker's risk attitude, societal tolerable risk level, and societal life quality criterion. Analysis results suggest that use of the developed framework can identify different sets of optimal designs for different risk attitudes. The results also show that the societal life quality criterion, for the considered examples, could only lead to a lower bound on the seismic design level for risk-seeking decision makers, whereas a reasonable tolerable risk level could provide a lower bound on the seismic design level for risk-seeking or risk-averse decision makers, or deny any acceptable designs for risk-neutral and risk-seeking decision makers.

Ambiguity Aversion, Robustness, and the Variational Representation of Preferences

We characterize, in the Anscombe–Aumann framework, the preferences for which there are a utility functionu on outcomes and an ambiguity indexc on the set of probabilities on the states of the world such that, for all acts f and g, . The function u represents the decision maker's risk attitudes, while the index c captures his ambiguity attitudes. These preferences include the multiple priors preferences of Gilboa and Schmeidler and the multiplier preferences of Hansen and Sargent. This provides a rigorous decision-theoretic foundation for the latter model, which has been widely used in macroeconomics and finance.

Utility transversality: a value‐based approach

AbstractWe examine multiattribute decision problems where a value function is specified over the attributes of a decision problem, as is typically done in the deterministic phase of a decision analysis. When uncertainty is present, a utility function is assigned over the value function to represent the decision maker's risk attitude towards value, which we refer to as a value‐based approach. A fundamental result of using the value‐based approach is a closed form expression that relates the risk aversion functions of the individual attributes to the trade‐off functions between them. We call this relation utility transversality. The utility transversality relation asserts that once the value function is specified there is only one dimension of risk attitude in multiattribute decision problems. The construction of multiattribute utility functions using the value‐based approach provides the flexibility to model more general functional forms that do not require assumptions of utility independence. For example, we derive a new family of multiattribute utility functions that describes richer preference structures than the usual multilinear family. We also show that many classical results of utility theory, such as risk sharing and the notion of a corporate risk tolerance, can be derived simply from the utility transversality relations by appropriate choice of the value function. Copyright © 2007 John Wiley & Sons, Ltd.

A decision tree solution considering the decision maker's attitude

We extend the expected monetary value (EMV) method of the decision tree to include the decision maker's preference information. Considering the decision maker's profit and risk attitude respectively, a decision tree method with ordered weighted average (OWA) aggregation operator is proposed. With given profit and risk optimistic level, the payoff values of the alternatives can be aggregated with geometric OWA operator and BADD (BAsic Defuzzification Distribution) neat OWA operator. Some properties of these two kinds of OWA operators are analyzed. And the process of the approach is shown by an illustrative example.

The Shape of Utility Functions and Organizational Behavior

Based on measurements among 332 owner-managers, we investigate how the global shape of the utility function (i.e., S-shaped versus concave or convex over the total range of outcomes) relates to choice behavior. We find that the global shape of the utility function differs across decision makers (about one-third of the owner-managers exhibit an S-shaped utility function) and that the global shape is linked to organizational behavior (i.e., the production system employed), a result that does not change when using different methods to identify the decision maker's global shape of the utility function. The decision maker's risk attitude (risk averse or risk seeking) does not affect the choice of the production system. Whereas the degree of risk aversion, based on the local shape of the utility function, may be important in explaining owner-managers' trading behavior (Pennings and Smidts 2000), more structural organizational behavior appears to be linked to the global shape of the utility function.

A Most Probable Point-Based Method for Efficient Uncertainty Analysis

Abstract Uncertainty is inevitable at every stage of life cycle development of a product. To make use of probabilistic information and to make reliable decisions by incorporating decision maker's risk attitude, methods for propagating the effect of uncertainty are therefore needed. When designing complex systems, the efficiency of methods for uncertainty propagation becomes critical. In this paper, a most probable point (MPP)-based uncertainty analysis (MPPUA) method is proposed. The concept of the MPP is utilized to generate the cumulative distribution function (CDF) of a system output by evaluating probability estimates at a serial of limit states across a range of output performance. To improve the efficiency of locating the MPP, a novel MPP search algorithm is presented that employs a new search algorithm and a search strategy. A mathematical example and an engine design problem are used to verify the effectiveness of the proposed method. The proposed MPPUA method will serve as a useful tool for propa...

A Most Probable Point-Based Method for Efficient Uncertainty Analysis

Abstract Uncertainty is inevitable at every stage of life cycle development of a product. To make use of probabilistic information and to make reliable decisions by incorporating decision maker's risk attitude, methods for propagating the effect of uncertainty are therefore needed. When designing complex systems, the efficiency of methods for uncertainty propagation becomes critical. In this paper, a most probable point (MPP)-based uncertainty analysis (MPPUA) method is proposed. The concept of the MPP is utilized to generate the cumulative distribution function (CDF) of a system output by evaluating probability estimates at a serial of limit states across a range of output performance. To improve the efficiency of locating the MPP, a novel MPP search algorithm is presented that employs a new search algorithm and a search strategy. A mathematical example and an engine design problem are used to verify the effectiveness of the proposed method. The proposed MPPUA method will serve as a useful tool for propagating the effect of uncertainty when making decisions under uncertainty.

A Decision Theoretic Approach to Choose Among Alternative Import Protocols for an Import Competing Commodity

The global push toward free trade and the consequent rise in volume of imports from a wider range of countries incurs the likelihood of introducing unwanted pathogens. Given that a zero-risk quarantine policy is not possible, there are tradeoffs between the gains from international trade and the potential costs to society of disease incursions. The aim in this paper is to demonstrate a means for choosing among alternative import protocols through a combined trade and decision model.The economic modeling approach applied to a stylised set of import protocols is a two-step process. First, the gains and losses to consumers and producers, including costs of disease, are estimated for each import protocol. In the second step, three decision rules - minimax, minimin and minimax regret – are applied to a cost matrix to determine the most efficient import protocol.These rules suggest a strong association between the risk attitudes of decision-makers, such as the Australian Quarantine and Inspection Service (AQIS) and the type of protocol chosen. For example, if AQIS is not willing to accept the risks of pest and disease incursions and adopts the minimax criterion, the most conservative import protocol that severely restricts imports would be chosen.

Using Distributed Resources to Manage Risks Caused by Demand Uncertainty

This paper presents a method to calculate the cost of satisfying transmission and distribution (T&D) system capacity needs as a function of investment modularity and lead-time. It accounts for the dynamic nature of demand uncertainty, the decision-maker's risk attitude, and the correlation between costs and firm profits. Results indicate that the modularity and short lead-times associated with the distributed resources can increase their attractiveness in comparison to long lead-time, large-scale T&D investments. Results also suggest that distributed resources can operate as a type of load growth insurance if demand growth is positively correlated with profits (so that costs are incurred when profits are high) and if the distributed resource costs are part of a larger portfolio that cannot be diversified.

Proper efficiency and cardinal utilities in multicriteria decision making

The concept of proper efficiency has been characterized in several ways in the Multicriteria Decision Making (MCDM) literature. Geoffrion has optimized a positively weighted sum of the multicriteria value functions, and Choo and Atkins have used an extended form of the generalized Tchebycheff norm. This paper investigates proper efficiency in MCDM when it is possible to represent the decision maker's risk attitudes and preferences by cardinal (especially additive cardinal) utilities. Proper efficiency is characterized by optimizing associated utility-related scalar optimization problems. More detailed relationships among proper efficiency, measure of risk aversion and allocation strategies are discussed in an asset allocation context.

Efficiency measurement of production operations under uncertainty

This paper focuses on the non-parametric efficiency measurement of production operations under uncertainties. The authors extend the existing data envelopment analysis method to deal with inputs and outputs subject to random disturbances. They propose a new approach to performance evaluation using certainty equivalence of utility functions, which can accommodate decision maker's risk attitude. They also formulate appropriate models to implement these approaches.

Risk attitude and decision making in contagious disease control

Accurate control of contagious animal diseases is of major concern for most countries. Basic and advanced decision rules are presented and applied, to show the impact of various risk attitudes of decision makers in determining what control strategy to choose, taking Foot-and-Mouth disease control in the Netherlands as an example. The choice appears to vary considerably among the decision rules (i.e. risk attitudes). Eventually, it is up to the decision maker to decide what rule is the most appropriate. Insight into the potential consequences of the various alternatives may contribute towards a more thoughtful approach in this respect.

The Role of Cardinal Utilities in Multiple Objective Programming

SYNOPTIC ABSTRACTOrdinal utilities are often used in investigating different types of efficient solutions in the multiple objective programming literature. The use of ordinal utilities implies that the decision making process does not involve risky alternatives, and very few of the important decisions in the real world can be successfully made without carefully considering the risk phenomenon. This paper examines the multiple objective programming problem by taking a decision maker's preferences and risk attitudes into account. The characterization of a particular type of efficiency, proper efficiency, is made via optimizing the associated utility-related scalar problems.

Application of stochastic dominance tests to utility resource planning under uncertainty

Uncertainty and risk have become critical elements of electric-utility planning. Planning has become more complex because of uncertainties about future growth in electricity demand, cost and performance of new generating resources, performance of demand-side resources that increase end-use efficiencies, and overall structure and competition within electricity markets. Current methodologies for incorporating risk and uncertainty into planning are limited by their potential lack of consistency with economic theory, or the necessity to specify expected utility functions that are difficult to defend. In this paper, we describe these limitations and suggest a new approach to utility planning under uncertainty, called stochastic dominance, which can augment or, in some cases, replace existing methods to evaluate uncertainty. Stochastic dominance permits comparison of resource plans with uncertain performance in a theoretically consistent manner, without having to assess or justify individual expected utility functions. Stochastic dominance tests can also be implemented with little additional effort over current decision methodologies, especially those methodologies that rely on Monte-Carlo models as a planning tool. Stochastic dominance tests can incorporate alternative risk attitudes of decision makers more easily than existing empirical methods and therefore provide more robust solutions to decision making under uncertainty. The paper concludes with a demonstration of stochastic dominance applied to a resource-planning decision for a hypothetical utility.

Decision analysis models of futures options purchase decisions

Decision analysis models can provide powerful insights about the relationships between variables in the futures/options purchase decision. These variables include the decision-maker's risk attitude, assessed price distribution, options conditions and price. This paper structures the ‘put’ option purchase decision faced by decision-makers (as price takers) who consider using the options market to modify their risk profile. Such models can be used to evaluate options as a form of commodity price insurance.

Conditions on Risk Attitude for a Single Attribute

For a decision problem having consequences described by a single attribute, the task of determining a utility function can be facilitated by verifying that the decision maker's risk attitude satisfies a condition such as constant risk aversion. We investigate a general class of conditions on risk attitude, and show that a utility function for such a condition may exist only when the condition is of a special type. Next, we discuss and interpret conditions of this special type. Then, we define two conditions which imply that the decision maker's risk attitude satisfies a condition of this type and is represented by a generalized logarithmic utility function or a linear fractional utility function.