Evaluating advisors: A policy‐capturing study under conditions of complete and missing information

Decision‐makers' relative preferences for various advisor characteristics were investigated in two multilevel policy‐capturing studies. The characteristics under consideration were: advisor expertise, advisor confidence, advisor intentions, and whether that advisor was the sole available source of advice. In Study 1, decision‐makers had access to all relevant information about the advisors. In contrast, some relevant information about the advisors was systematically made unavailable in Study 2, which allowed an investigation of the effect of missing information on decision‐makers' evaluations of advisors. Results from both studies indicated that advisor expertise and intentions were most important in promoting decision‐makers' positive evaluations of advisors, that this effect was even more pronounced under conditions of missing information, and that advisor expertise and intentions also interacted synergistically. Given that expertise and good intentions are determinants of an advisor's trustworthiness, the results highlight the interpersonal nature of advice giving and taking. Copyright © 2009 John Wiley & Sons, Ltd.     

Variation of Preference Inconsistency When Applying Ratio and Interval Scale Pairwise Comparisons

Several studies on numerical rating in discrete choice problems address the tendency of inconsistencies in decision makers' measured preferences. This is partly due to true inconsistencies in preferences or the decision makers' uncertainty on what he or she really wants. This uncertainty may be reflected in the elicited preferences in different ways depending on the questions asked and methods used in deriving the preferences for alternatives. Some part of the inconsistency is due to only having a discrete set of possible judgments. This study examined the variation of preference inconsistency when applying different pairwise preference elicitation techniques in a five‐item discrete choice problem. The study data comprised preferences of five career alternatives elicited applying interval scale and numerically and verbally anchored ratio scale pairwise comparisons. Statistical regression technique was used to analyse the differences of inconsistencies between the tested methods. The resulting relative residual variances showed that the interval ratio scale comparison technique provided the greatest variation of inconsistencies between respondents, thus being the most sensitive to inconsistency in preferences. The numeric ratio scale comparison gave the most uniform preferences between the respondents. The verbal ratio scale comparison performed between the latter two when relative residual variances were considered. However, the verbal ratio scale comparison had weaker ability to differentiate the alternatives. The results indicated that the decision recommendation may not be sensitive to the selection between these preference elicitation methods in this kind of five‐item discrete choice problem. The numeric ratio scale comparison technique seemed to be the most suitable method to reveal the decision makers' true preferences. However, to confirm this result, more studying will be needed, with an attention paid to users' comprehension and learning in the course of the experiment. Copyright © 2013 John Wiley & Sons, Ltd.     

An Optimized Design of Choice Experiments: A New Approach for Studying Decision Behavior in Choice Task Experiments

In this paper, we present a new approach for the optimal experimental design problem of generating diagnostic choice tasks, where the respondent's decision strategy can be unambiguously deduced from the observed choice. In this new approach, we applied a genetic algorithm that creates a one‐to‐one correspondence between a set of predefined decision strategies and the alternatives of the choice task; it also manipulates the characteristics of the choice tasks. In addition, this new approach takes into account the measurement errors that can occur when the preferences of the decision makers are being measured. The proposed genetic algorithm is capable of generating diagnostic choice tasks even when the search space of possible choice tasks is very large. As proof‐of‐concept, we used this novel approach to generate respondent‐specific choice tasks with either low or high context‐based complexity that we operationalize by the similarity of alternatives and the conflict between alternatives. We find in an experiment that an increase in the similarity of the alternatives and an increase in the number of conflicts within the choice task lead to an increased use of non‐compensatory strategies and a decreased use of compensatory decision strategies. In contrast, the size of the choice tasks, measured by the number of attributes and alternatives, only weakly influences the strategy selection. Copyright © 2014 John Wiley & Sons, Ltd.     

A Fuzzy Topsis Method for Prioritized Aggregation in Multi‐Criteria Decision Making Problems

Aggregation in a decision making environment requires the fusion of opinions of a group of decision makers. The group of decision makers are required to analyse a set of interrelated criteria that are usually measured on a linguistic scale. This process requires, in many instances, to capture experts experience, intuition and thinking that are traditionally expressed in a linguistic fashion rather than a numerical fashion. Furthermore, the necessity of considering the relationship between the criteria to the overall decision must be considered by the group of decision makers. This paper extends the application of fuzzy numbers, fuzzy relative importance scores (FRIS), fuzzy relative weights (FRW) and the fuzzy technique of order preference by similarity to ideal solution (TOPSIS) in prioritized aggregation. This extension provides a mean to systematically aggregate a group of decision makers' views for a set of interrelated criteria that are measured on a linguistic scale. First, an overview of the application of fuzzy numbers and the characteristics of aggregating fuzzy numbers in multi‐criteria decision making problems are presented. Then, the application of TOPSIS in fuzzy environments is presented. Next, past research is highlighted to present prioritized aggregation and the different aggregation operators' classes. Subsequently, a new prioritized aggregation method is presented. This method utilizes fuzzy TOPSIS with prioritized aggregation in fuzzy environments. Finally, the fuzzy prioritized aggregation method presented in this paper is applied on an actual case study. According to the results, the method presented in this paper provides a systematic approach to capture the uncertainty and imprecision associated with quantifying linguistic measurements in multi‐criteria decision making problems. Furthermore, it considers the relationship between the set of linguistically measured criteria undergoing prioritized aggregation in a fuzzy environment. Lastly, findings, conclusions and future work are presented. Copyright © 2016 John Wiley & Sons, Ltd.     

A new fuzzy multicriteria evaluation method for group site selection in GIS

Multiple criteria group site selection problems involve a group of individuals evaluating a set of alternative sites on the basis of multiple criteria. This paper presents an application of a new fuzzy algorithm for finding and exploring potential solutions to these problems in a raster Geographical Information System (GIS) environment. Linguistic assessments from decision‐makers are represented as triangular fuzzy numbers (TFN's), which are adjusted for uncertainty in the source data and their relationship to suitability by using an approach based on type‐2 fuzzy sets. The first aggregation of inputs is a compensatory one based on fuzzy multiattribute decision‐making (MADM) theory. An adjusted aggregation then factors in conflicts, risks and uncertainties to enable a variety of compensatory and non‐compensatory outcomes to be generated based on decision‐maker preferences. The algorithm was implemented in ArcView GIS as part of an ongoing collaborative project with Brisbane Airport. This paper outlines the fuzzy algorithm and its use in site selection for a recycling facility on the Brisbane Airport site. Copyright © 2005 John Wiley & Sons, Ltd.     

Group Decision Makers' Preferences Modelling within the Goal Programming Model: An Overview and a Typology

The Goal Programming (GP) model is one of the first models that have been developed to deal with managerial decision‐making problems where several incommensurable and conflicting objectives are involved. The GP variants integrate the decision maker's preferences differently. This model has also been applied to group decision‐making situations. The aim of this paper is to propose a new typology based on preferences articulation of decision makers through the GP model. This typology is based on the articulation and the elucidation process of the group decision makers' preferences. Copyright © 2012 John Wiley & Sons, Ltd.     

Information search and mental representation in risky decision making: The advantages first principle

In three experiments the problem is investigated how people identify early in the decision process those alternatives that are worthwhile to be examined in more detail. We assume that decision makers employ the Advantages first Principle: They first search for information about positive outcomes and then focus their information search (e.g., for negative consequences or for risk defusing operators) on those alternatives that appear attractive after this initial evaluation. In Experiment 1 (120 participants), initial information about consequences was varied for eight alternatives (no information, positive consequences, negative, or mixed for four alternatives). In all conditions, the great majority of participants followed both aspects of the Advantages first Principle. In Experiment 2, 60 participants decided in two quasi‐realistic scenarios with two alternatives each. Initial information was presented so that one alternative had better positive consequences, worse negative consequences, or both. In all conditions, more information was searched for in the initially better alternative. In Experiment 3 (20 participants) the Advantages first Principle was not only confirmed for a scenario but also for choices in traditional gambling tasks with two and eight alternatives, respectively. Participants could win or lose real money. Copyright © 2010 John Wiley & Sons, Ltd.     

Integration of Analytic Hierarchy Process with Regression Analysis to Identify Attractive Locations for Market Expansion

Selection of new geographies in which to expand is a key decision for businesses aspiring to go beyond the opportunities in the existing markets. The conventional approaches of market selection can only provide a set of systematic steps for problem solving without considering the relationships between the decision factors. Decision models based on statistical techniques are able to examine the relationship between decision factors but are unable to effectively assist decision makers in identifying the most promising market, particularly in terms of prioritizing across decision factors. Analytic Hierarchy Process (AHP) is a commonly used approach for choosing alternatives by prioritizing across multiple decision factors. The typical AHP modelling requires knowledge of criteria and/or alternatives along with their relative weights, generally elicited from field experts. Quite often, firms encounter situations where decision makers are aware of only the overall objective and a set of earmarked geographies for setting up market locations while being relatively unaware of decision criteria and relative weights. This precludes using AHP to identify promising market locations. This paper conceptualizes a market selection decision model that integrates AHP with statistical modelling techniques to identify the attractive market locations for the purpose of expansion. The model first uses principal component analysis and multiple regression to determine significant decision criteria and their weights. Thereafter, it applies AHP to prioritize the market locations across the decision criteria. This integrative approach is illustrated for identifying the attractive locations in rural markets for a steel firm in India. The major advantage of this approach is that unlike the existing models, it works in situations when firms have not enough knowledge about factors for evaluating alternative market locations. Another key advantage of the proposed model is that of economizing resources for data collection on variables representing decision factors. Copyright © 2012 John Wiley & Sons, Ltd.     

Triple Bottomline Many‐Objective‐Based Decision Making for a Land Use Management Problem

A land use many‐objective optimization problem for a 1500‐ha farm with 315 paddocks was formulated with 14 objectives (maximizing sawlog production, pulpwood production, milksolids, beef, sheep meat, wool, carbon sequestration, water production, income and Earnings Before Interest and Tax; and minimizing costs, nitrate leaching, phosphorus loss and sedimentation). This was solved using a modified Reference‐point‐based Non‐dominated Sorting Genetic Algorithm II augmented by simulated epigenetic operations. The search space had complex variable interactions and was based on economic data and several interoperating simulation models. The solution was an approximation of a Hyperspace Pareto Frontier (HPF), where each non‐dominated trade‐off point represented a set of land‐use management actions taken within a 10‐year period and their related management options, spanning a planning period of 50 years. A trade‐off analysis was achieved using Hyper‐Radial Visualization (HRV) by collapsing the HPF into a 2‐D visualization capability through an interactive virtual reality (VR)‐based method, thereby facilitating intuitive selection of a sound compromise solution dictated by the decision makers' preferences under uncertainty conditions. Four scenarios of the HRV were considered emphasizing economic, sedimentation and nitrate leaching aspects—giving rise to a triple bottomline (i.e. the economic, environmental and social complex, where the social aspect is represented by the preferences of the various stakeholders). Highlights of the proposed approach are the development of an innovative epigenetics‐based multi‐objective optimizer, uncertainty incorporation in the search space data and decision making on a multi‐dimensional space through a VR‐simulation‐based visual steering process controlled at its core by a multi‐criterion decision making‐based process. This approach has widespread applicability to many other ‘wicked’ societal problem‐solving tasks. Copyright © 2014 John Wiley & Sons, Ltd.     

No decision‐maker is an Island: integrating expert advice with information acquisition

The present research examined the social context of information acquisition. The main purpose was to examine how decision‐makers' information acquisition processes changed when they were provided access to expert advice. Results indicated that all decision‐makers opted to acquire advice; however, they typically did so only after completing over 75% of their own information search. Decision‐makers agreed more with the advice as task complexity increased, but, in general, searched information in two stages—i.e., a pre‐advice “hypothesis generation” stage and a post‐advice “hypothesis testing” stage. To behave in an adaptive manner, decision‐makers could have used expert advice either to increase their decision accuracy or to reduce their effort expenditure (or both); they chose the former. Implications and further extensions are discussed. Copyright © 2006 John Wiley & Sons, Ltd.     

Invited Review—Survey of Value‐Focused Thinking: Applications,Research Developments and Areas for Future Research

Criteria are the central focus of multi‐criteria decision analysis. Many authors have suggested using our values (or preferences) to define the criteria we use to evaluate alternatives. Value‐focused thinking (VFT) is an important philosophy that advocates a more fundamental view of values in our decision making in our private and professional lives. VFT proponents advocate starting first with our values and then using our values to create decision opportunities, evaluate alternatives and finally develop improved alternatives. It has been 20 years since VFT was first introduced by Ralph Keeney. This paper surveys the VFT literature to provide a comprehensive summary of the significant applications, describe the main research developments and identify areas for future research. We review the scope and magnitude of VFT applications and the key developments in theory since VFT was introduced in 1992 and found 89 papers written in 29 journals from 1992 to 2010. We develop about 20 research questions that include the type of article (application, theory, case study, etc.), the size of the decision space (which, when given, ranged from $200K to billions of dollars), the contribution documented in the article (application benefits) and the research contributions (categorized by preferences, uncertainties and alternatives). After summarizing the answers to these questions, we conclude the paper with suggestions for improving VFT applications and potential future research. We found a large number of significant VFT applications and several useful research contributions. We also found an increasing number of VFT papers written by international authors. Copyright © 2012 John Wiley & Sons, Ltd.     

An evaluation of multi‐criteria methods in integrated assessment of climate policy

Those who conduct integrated assessments (IAs) are aware of the need to explicitly consider multiple criteria and uncertainties when evaluating policies for preventing global warming. MCDM methods are potentially useful for understanding tradeoffs and evaluating risks associated with climate policy alternatives. A difficulty facing potential MCDM users is the wide range of different techniques that have been proposed, each with distinct advantages. Methods differ in terms of validity, ease of use, and appropriateness to the problem. Alternative methods also can yield strikingly different rankings of alternatives. A workshop was held in which climate change experts and policy makers evaluated the usefulness of MCDM for IA. Participants applied several methods in the context of a hypothetical greenhouse gas policy decision. Methods compared include value and utility functions, goal programming, ELECTRE, fuzzy sets, stochastic dominance, min max regret, and several weight selection methods. Ranges, rather than point estimates, were provided for some questions to incorporate imprecision regarding weights. Additionally, several visualization methods for both deterministic and uncertain cases were used and evaluated. Analysis of method results and participant feedback through questionnaires and discussion provide the basis for conclusions regarding the use of MCDM methods for climate change policy and IA analyses. Hypotheses are examined concerning predictive and convergent validity of methods, existence of splitting bias among experts, perceived ability of methods to aid decision‐making, and whether expressing imprecision can change ranking results. Because participants gained from viewing a problem from several perspectives and results from different methods often significantly differed, it appears worthwhile to apply several MCDM methods to increase user confidence and insight. The participants themselves recommended such multimethod approaches for policymaking. Yet they preferred the freedom of unaided decision‐making most of all, challenging the MCDM community to create transparent methods that permit maximum user control. Copyright © 2002 John Wiley & Sons, Ltd.     

Multicriteria Classification with Unknown Categories: A Clustering–Sorting Approach and an Application to Conflict Management

This work proposes an approach to cluster and sort a set of alternatives considering multi‐criteria categories with a partial order structure. It can be considered a heuristic approach because it does not attempt to derive an optimal partial order among all conceivable clusters of alternatives. Rather than this, it intends to be a simple approach that is transparent to the Decision Maker (DM) whose assistance is sought to help shaping the results. The approach proposed arises from the conjugation of traditional Clustering analysis and Multi‐criteria sorting tools. At the outset, the number of categories and their characteristics is unknown. First, we need to detect only the clusters themselves on the basis of a similarity measure independent of the preferences of the DM. Next, we detect potential partial order relations that might exist between them, according to the subjective preferences of the DM. Such preferences are elicited only after the DM has examined the clusters detected and deemed that these categories made sense. The new approach performs very well in a real‐world problem of management of intragroup conflicts and conflict handling strategies. Copyright © 2012 John Wiley & Sons, Ltd.     

Model and interactive algorithm of bi‐level multi‐objective decision‐making with multiple interconnected decision makers

Furthering a prior research on two‐person bi‐level multi‐objective decision‐making problems of the leader‐follower Stackelberg game, we present an extended model of bi‐level multi‐objective decision‐making with multiple interconnected decision makers at the lower level. In the model, the upper level decision maker acts as a leader and the lower level decision makers behave as the followers, and inter‐connections and interactions exist among these followers in decision‐making scenarios. Following the rules of leader‐follower Stackelberg game, we develop an interactive algorithm of the model for solving multi‐objective decision‐making problems and reflecting the interactive natures among the decision makers. Finally, the authors exemplify the model and algorithm, and draw a conclusion on points of contributions and the significance of this study in decision‐making and support. Copyright © 2001 John Wiley & Sons, Ltd.     

Reliance on Numerical Precision: Compatibility between Accuracy versus Efficiency Goals and Numerical Precision Level Influence Attribute Weighting in Two‐Stage Decisions

This research examines how the weighting of an attribute is jointly affected by attribute precision and decision stage. Building on prior work suggesting (a) that less (more) precise numerical values are easier to process (more accurate), (b) that decision‐makers' motivation to be efficient (accurate) is greater when creating a consideration set (making a final choice), and (c) that decision‐makers tend to overweight information that is compatible with their goals, we hypothesize that when creating a consideration set (making a choice) participants tend to assign greater weight to less (more) precise attributes. Five studies (two of them reported in the Appendix S1) offer triangulating evidence for these predictions. Overall, this work contributes to research on numerical cognition, efficiency versus accuracy trade‐offs, attribute weighting, and two‐stage decisions.     

Fuzzy MCDM based on the concept of α‐cut

In a fuzzy multiple criteria decision‐making (MCDM) problem, with a hierarchical structure of more than two levels and involving multiple decision‐makers (DMs), to find the exact membership functions of the final aggregation ratings of all feasible alternatives is almost impossible. Thus, ranking methods based on exact membership functions cannot be utilized to rank the feasible alternatives and complete the optimal selection. To resolve the above‐mentioned complexity and to incorporate assessments of all DMs' viewpoints, in this paper a fuzzy MCDM method with multiple DMs, based on the concepts of fuzzy set theory and α‐cut, is developed. This method incorporates a number of perspectives on how to approach the fuzzy MCDM problem with multiple DMs, as follows: (1) combining quantitative and qualitative criteria as well as negative and positive ones; (2) using the generalized means to develop the aggregation method of multiple DMs' opinions; (3) incorporating the risk attitude index β to convey the total risk attitude of all DMs by using the estimation data obtained at the data input stage; (4) employing the algebraic operations of fuzzy numbers based on the concept of α‐cut to calculate the final aggregation ratings and develop a matching ranking method for proposed fuzzy MCDM method with multiple DMs. Furthermore, we use this method to survey the site selection for free port zone (FPZ) in Taiwan as an empirical study to demonstrate the proposed fuzzy MCDM algorithm. The result of this empirical investigation shows that the port of Kaohsiung, the largest international port of Taiwan as well as the sixth container port in the world in 2004, is optimal for the Taiwan government in enacting the plan of FPZ. Copyright © 2005 John Wiley & Sons, Ltd.     

“All‐or‐None” Versus “Most‐or‐Some” Options in Risky Choice: Effects of Domain and Handedness

Two methodological variants of Kahneman and Tversky's Asian disease scenario were investigated. One variant involved replacing the “all‐or‐none” outcome scenarios of the risky choice with “most‐or‐some” scenario outcomes, and the second variant involved replacing the negative domain of lives lost with a positive domain of jobs created. In addition, the effects of strength of handedness, a variable related to individual differences in risk perception, were examined. Results indicated that standard framing effects were obtained across both domains, with a decrease in risky choice under the gain domain. Scenario type also interacted with handedness, such that the all‐or‐none scenario yielded framing effects for consistent (strong)‐handers only, whereas the most‐or‐some scenario yielded framing effects for inconsistent (mixed)‐handers only (consistent‐handers are those who use the same hand exclusively for almost all activities). These results demonstrate that framing effects are strongly influenced by the presence versus absence of extreme/absolute outcomes and that individuals (in this case, decision makers with varying degrees of handedness strength) are differentially sensitive to different pieces of information. Copyright © 2014 John Wiley & Sons, Ltd.