On the Similarities of Some Multi‐Criteria Decision Analysis Methods

Since multiple criteria characterise many practical decision problems, the research field of multicriteria decision analysis (MCDA) is flourishing. This paper compares the multi‐attribute decision making (MADM) methods, simple additive rating (SAR), simple additive weighting (SAW) as well as the outranking approach PROMETHEE and explains their similarities. We present a case study on industrial paint application and provide theoretical evidence that PROMETHEE can mimic other MADM algorithms. Copyright © 2011 John Wiley & Sons, Ltd.     

Preference‐based Learning of Ideal Solutions in TOPSIS‐like Decision Models

Combining established modelling techniques from multiple‐criteria decision aiding with recent algorithmic advances in the emerging field of preference learning, we propose a new method that can be seen as an adaptive version of TOPSIS, the technique for order preference by similarity to ideal solution decision model (or at least a simplified variant of this model). On the basis of exemplary preference information in the form of pairwise comparisons between alternatives, our method seeks to induce an ‘ideal solution’ that, in conjunction with a weight factor for each criterion, represents the preferences of the decision maker. To this end, we resort to probabilistic models of discrete choice and make use of maximum likelihood inference. First experimental results on suitable preference data suggest that our approach is not only intuitively appealing and interesting from an interpretation point of view but also competitive to state‐of‐the‐art preference learning methods in terms of prediction accuracy. Copyright © 2014 John Wiley & Sons, Ltd.     

Utility of composite and multiple criteria measuring discriminative efficiency in personnel selection

The present study examined the utility of decision making in personnel selection comparing multiple and composite criteria by discriminative efficiency, in a bricklaying training program. We have found valid predictors (aptitudes, personality and experience) with different forms of the criterion, the ERPF scale, in logistic and multiple regression analysis. Results seem indicate that there is not a better criterion, so it depends on different conditions and different aims to reach. We proposed criteria as combining measures but not opposed.     

An Approach to Multi‐Criteria Decision Problems Under Severe Uncertainty

Solving complex decision problems is a demanding task; it requires determining and evaluating the consequences of decision alternatives. To this end, uncertain factors that can only partly be influenced by the decision makers, and their interdependencies need to be considered. Scenarios focus on this part of the decision problem; they enable a systematic exploration of a multitude of possible future developments that are relevant for the decision including external events and decisions made. Scenarios are particularly useful when the problem is pervaded by severe uncertainties that cannot be quantified. For the evaluation of alternatives, multiple objectives and the potentially diverging preferences of the involved actors need to be respected. Multi‐criteria decision analysis aims at structuring the problem, evaluating the alternatives and supporting decision makers pursuing multiple goals. We propose an approach integrating scenarios and multi‐criteria decision analysis that focuses on the robustness of alternatives in complex, dynamic, uncertain and time‐bound situations. In this integrated framework, the scenarios provide the basis for evaluating a set of alternatives. Ideally, the set of scenarios considered captures all possible future developments. To appropriately explore this set, formal or analytical approaches to scenario construction generate a large number of scenarios. This challenges the decision makers' information‐processing capacity. To support them in managing the richness of information, a two‐fold approach that uses selection and aggregation is presented. By using a selection method, the scenarios that are deemed most relevant are identified, and their evaluations are presented in detail to decision makers. This approach is complemented by an aggregation of scenario evaluations on the basis of the decision makers' preferences. We present two approaches to facilitate the preference elicitation process. Copyright © 2013 John Wiley & Sons, Ltd.     

Multiple Criteria Decision‐Making in Management Accounting and Control‐State of the Art and Research Perspectives Based on a Bibliometric Study

As an academic discipline as well as in practice, decision support is one of the most important functions of management accounting and control (MAC). Owing to decision settings' increasing complexity, suitable multiple criteria methods are becoming increasingly important for MAC. We, therefore, examine the extent to which certain multiple criteria decision‐making (MCDM) methods are used in the MAC context. In order to do so, we undertook an extensive bibliometric analysis of the management accounting field during the last three decades. The results indicate an increase in the importance of MCDM. Furthermore, recent research activities were classified into different areas of decision‐making within MAC since the majority of publications deal with the areas of strategic management, budgeting and performance management. More specifically, strategy and performance evaluation, strategic planning and the selection of alternatives are the most prominent MCDM applications. Our analysis reveals that the analytic hierarchy process (AHP) is the most popular analytical tool with which to support management in complex decision‐making situations. The results of the study prove that technical MAC literature does not cover a desirable range of MCDM applications and that the AHP, as well as the analytic network process (ANP) are of increasing importance in respect of the international scope of MAC. Therefore, the area of MCDM continues to be an active part of management science research and application, specifically of MAC. Copyright © 2011 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.     

Simulation of Preference Information in an Interactive Reference Point‐Based Method for the Bi‐Objective Inventory Routing Problem

In the research area of multiple criteria decision making, very few publications exist that explicitly design the simulation of a decision maker (DM) in an interactive approach. For this reason, we outline some methods widely used in the literature to identify common assumptions of simulating the DM's responses and the required input preference information. Our paper aims at covering the identified gap by introducing experimental concepts. Such concepts are used for theoretical analyses of a combined search‐and‐decision‐making procedure. Simulating the DM is a fruitful idea because the algorithm can be tested without integrating a human decision maker. Finally, we conduct experiments based on the proposed settings for a multiobjective inventory routing problem, which is a relevant and challenging logistic problem. Copyright © 2014 John Wiley & Sons, Ltd.     

Group‐analytic network process for balancing stakeholder views on fire protection of steel‐framed buildings

To select appropriate fire protection options for buildings during their design stage, economic, safety, environmental, and societal criteria need to be accounted for. The divergent and sometimes conflictual desires from different fire design stakeholders involved in the process present a multicriteria decision problem. Design decision criteria and fire protection options can be interdependent, and so there is a need to manage these desires with an advanced decision analysis technique, thereby reducing uncertainties in the complex decision‐making process. The aim of this paper is to use the weighted/geometric mean method‐analytic network process (W/GMM‐ANP) to balance the opinions of fire design stakeholders extracted from 42 structured stakeholder interviews on selecting the most suitable fire protection option for buildings constructed of steel frames. Different categories of interdependent decision elements were developed from 22 design decision criteria and 5 proposed fire protection options to produce a network of decision clusters for multicriteria decision analysis. In the synthesis and ranking of fire protection options, the W/GMM‐ANP accounted for the multiple interdependencies of weighted and unweighted stakeholder desires and managed the complexity of the decision‐making problem. The technique is proposed for approaching suitable group decisions in structural fire design of steel‐framed buildings as well as other performance‐based engineering decision making that may involve multidisciplinary stakeholders.     

Teaching Ethics to Engineers: Ethical Decision Making Parallels the Engineering Design Process

In order to fulfill ABET requirements, Northern Arizona University’s Civil and Environmental engineering programs incorporate professional ethics in several of its engineering courses. This paper discusses an ethics module in a 3rd year engineering design course that focuses on the design process and technical writing. Engineering students early in their student careers generally possess good black/white critical thinking skills on technical issues. Engineering design is the first time students are exposed to “grey” or multiple possible solution technical problems. To identify and solve these problems, the engineering design process is used. Ethical problems are also “grey” problems and present similar challenges to students. Students need a practical tool for solving these ethical problems. The step-wise engineering design process was used as a model to demonstrate a similar process for ethical situations. The ethical decision making process of Martin and Schinzinger was adapted for parallelism to the design process and presented to students as a step-wise technique for identification of the pertinent ethical issues, relevant moral theories, possible outcomes and a final decision. Students had greatest difficulty identifying the broader, global issues presented in an ethical situation, but by the end of the module, were better able to not only identify the broader issues, but also to more comprehensively assess specific issues, generate solutions and a desired response to the issue.     

The Selection of Multiattribute Decision Making Methods for Scholarship Student Selection

Selecting scholarship students from a number of competing candidates is a complex decision making process, in which multiple selection criteria have to be considered simultaneously. Multiattribute decision making (MADM) has proven to be an effective approach for ranking or selecting one or more alternatives from a finite number of alternatives with respect to multiple, usually conflicting criteria. This paper formulates the scholarship student selection process as an MADM problem, and presents suitable compensatory methods for solving the problem. A new empirical validity procedure is developed to deal with the inconsistent ranking problem caused by different MADM methods. The procedure aims at selecting a ranking outcome which has a minimum expected value loss, when true attribute weights are not known. An empirical study of a scholarship student selection problem in an Australian university is conducted to illustrate how the selection procedure works.     

A parameter analysis method for the weight‐set to satisfy preference orders of alternatives in additive multi‐criteria value models

In the context of the additive multi‐criteria value model, this paper investigates how the set of criteria weights (weight‐set hereafter) can be determined according to the preference orders of alternatives given by the decision maker. A construction method is proposed for the weight‐set for different intervals of β, where β is a differential amount of value between the preference information on two alternatives. The results of this paper are important for sensitivity analysis in multi‐criteria decision making (MCDM) problems and multi‐criteria group decision analysis. Copyright © 2000 John Wiley & Sons, Ltd.     

The Negotiation Matching Process: Relationships and Partner Selection

We present 3 studies that examine the process of partner selection in negotiations and the influence that relationships may have on the partner-selection decision. In Study 1, we present a simulated matching market experiment in which we compare the matching process when relationships can influence the partner-selection decision with the matching process when relationships cannot influence this decision. We find that when relationships are not allowed to influence the matching process, there are more economically optimal agreements, a larger market surplus, and more search activity. In Study 2, a simulation of a naturally occurring market selection process provides additional quantitative support for the findings from Study 1 and offers qualitative data on the reasoning process behind partner selection, including the social factors that are influential in this decision. Study 3 utilizes a repeated trial experimental simulation to offer further support for the negative relationship between relationships and economic outcomes and to suggest that the relative power of the negotiators influences the extent to which relationships help versus hurt individual profitability. Implications of these findings are discussed.     

A postulate-based analysis of comparative preference statements

There has been a growing interest in the study of preferences for their utility in solving problems related to decision making. Most of the preference representation languages developed in the literature are based on comparative preference statements since they offer a simple and intuitive way for expressing preferences. They can be further interpreted following different semantics, imparting a greater flexibility on how outcomes can be compared. So far the main objective has been to rank-order the set of outcomes given a set of comparative preference statements and one or several semantics. Tackling this problem from a different angle, we look into the behavioural aspects of the preference semantics and statements by attempting to formalise the intuition behind them using postulates studied in preference logics and non-monotonic reasoning. We select the postulates w.r.t. three criteria: coherence, syntax independence and inference. Thus, our analysis provides a means to determine those properties that are satisfied for a given preference semantics.     

Lay rationalism and inconsistency between predicted experience and decision

Decision‐makers are sometimes depicted as impulsive and overly influenced by ‘hot’, affective factors. The present research suggests that decision‐makers may be too ‘cold’ and overly focus on rationalistic attributes, such as economic values, quantitative specifications, and functions. In support of this proposition, we find a systematic inconsistency between predicted experience and decision. That is, people are more likely to favor a rationalistically‐superior option when they make a decision than when they predict experience. We discuss how this work contributes to research on predicted and decision utilities; we also discuss when decision‐makers overweight hot factors and when they overweight cold factors. Copyright © 2003 John Wiley & Sons, Ltd.     

Experimental consideration of preference in decision making under certainty

This paper describes an experiment in decision making under certainty with multiple, conflicting objectives and continuous decision variables. Two techniques for analysing such problems are considered: one taken from the paradigm of multicriteria decision making (MCDM), a non-directed approach called the NAIVE technique, and one from the paradigm of multiattribute decision analysis (D/A), the SMART technique. While the two techniques seek and are throught to arrive at the same end—a solution which is in some sense optimal for the decision maker (DM)—the former approach implicitly incorporates DM preferences while the latter approach considers preferences explicitly. The setting is a laboratory study using a sample of university students on a three-criteria problem which is designed to study the extent to which value functions implied/assessed by the techniques are consistent with DMs' holistic ranking of alternatives. Results show that (1) the two techniques of interest show significantly better rank order correlation with holistic judgement compared with other techniques, (2) DMs prefer the non-directed MCDM approach and (3) subjects break down into two groups: those that use assessable value functions when ranking and those that do not. This implies that for small-dimensioned problems DMs may first need to be classified as to the assessability of their value functions before a solution method is chosen.     

An Interactive Approach for Multicriteria Decision Making Using a Tchebycheff Utility Function Approximation

Multicriteria decision making (MCDM) can provide an efficient mean for considering various and conflicting objectives to reveal the alternative that maximizes the decision maker's (DM) utility. In this paper, we propose a new interactive MCDM method for implicit alternatives to help a DM obtain a most preferred solution. We employ a Tchebycheff function to generate weights for objectives consistent with the DM's responses to pairwise comparisons between alternatives and present a mixed integer linear programming formulation to generate these weights. Thus, we approximate the DM's utility function by a Tchebycheff function and generate weights consistent with the DM's responses. We test our approach with different true utility functions on various sized multiple criteria linear programming problems. The computational results show that even with non‐Tchebycheff true utility functions, our method can generate alternatives very close to the optimal solution with few questions. The comparison of our results with other methods reveals its advantages. Copyright © 2013 John Wiley & Sons, Ltd.     

Deflecting Arrow by Aggregating Rankings of Multiple Correlated Criteria According to Borda

This paper has two objectives. The first is to review and address concerns raised by Hazelrigg that Arrow's impossibility theorem prevents the selection of rational aggregation methods for use in engineering trade studies. In addressing these concerns, the work of Saari is cited to establish the fact that the Borda count is the only ‘non‐dictatorial’ positional voting method that satisfies the criteria for a rational decision procedure while using complete information. Hence, the resulting rank ordering of the alternatives is the most reliable outcome. Several previous studies that use other aggregation methods are critiqued, and Borda is applied to examples to illustrate the differences in the outcomes. The second objective is to extend the applicability of Borda to include attributes such as cost, schedule duration, and certain technical and performance measures that are generally more reasonably described as correlated random variables. Exact Probabilities by Simulation with Borda, a method introduced by Hulkower that improves a technique by Book for determining which candidate in a trade study is the probable lowest‐cost alternative, is generalized to include multiple correlated criteria, each of which is expressed as a random variable and thus incorporates probabilistic uncertainty. Copyright © 2016 John Wiley & Sons, Ltd.     

Locating a Waste Treatment Facility by Multicriteria Analysis

We describe an application of multicriteria decision aid to the location of a waste treatment facility in eastern Finland. In Finland, the Act on Environmental Impact Assessment Procedure requires that when the amount of waste to be dealt with in a facility exceeds 20,000 tons per year, the process of environmental impact assessment (EIA) must be performed. In addition, the opinions of citizens and different interest groups need to be heard. Generally, EIA requires many different factors to be dealt with. Therefore the use of some multicriteria decision aid may be helpful to preserve the information obtained through the EIA in the decision-making process. The alternative locations for the facility were considered based on 14 criteria by 28 decision makers. The present paper makes use of the PROMETHEE decision aid, which was found to fit well with certain constraints in this type of problem with multiple criteria and multiple decision makers. © 1997 by John Wiley & Sons, Ltd. J. Multi-Crit. Decis. Anal. 6 : 175–184 (1997) No. of Figures: 2. No. of Tables: 3. No. of References: 18.     

Interrupting the cascade: orienting contributes to decision making even in the absence of visual stimulation

Most systematic studies of human decision making approach the subject from a cost analysis point of view and assume that people make the highest utility choice. Very few articles investigate subjective decision making, such as that involving preference, although such decisions are very important for our daily functioning. We have argued (Shimojo, Simion, Shimojo, & Scheier, 2003) that an orienting bias effectively leads to the preference decision by means of a positive feedback loop involving mere exposure and preferential looking. The illustration of this process is a continually increasing gaze bias toward the eventual choice, which we call the gaze cascade effect. In the present study, we interrupt the natural process of preference selection, but we show that gaze behavior does not change even when the stimuli are removed from observers' visual field. This demonstrates that once started, the involvement of orienting in decision making cannot be stopped and that orienting acts independently of the presence of visual stimuli. We also show that the cascade effect is intrinsically linked to the decision itself and is not triggered simply by a tendency to look at preferred targets.