R&D Project Selection: A Decision Process Approach

The fundamental decision problem of an R&D firm is to select projects in which to invest. Most reported models dealing with this subject use sophisticated mathematical models maximizing specific attributes of the projects without dealing with the underlying motivation of the decision maker. This paper summarizes a successful application of a decision-making process involving multicriteria in the selection of R&D projects in the Ecogen Israel Partnership. We emphasize the structure of the decision problem, with the main goal of helping the decision maker to better understand the nature of his problem. We systematically generate the objective hierarchy of the decision maker, including his main criteria, subcriteria attributes and alternatives. The ‘best’ alternative can then be found using most interactive procedures found in the literature. As the decision maker is totally involved in the entire decision-making process he is better able to understand his problem and preferences.     

Simplified approaches for multicriteria decision making under uncertainty

The problem of uncertainty in the outcome of decisions has tended to be glossed over by many MCDM methods, with the exception of multiattribute utility theory (MAUT). MAUT does, however, require quite complicated preference elicitations and knowledge of the full multivariate distribution of outcomes. Results from a series of simulation studies indicate that the preference orderings of MAUT are only minimally changed when using a simple additive aggregation of marginal utilities, especially in relation to the natural imprecisions inherent in preference elicitation. It is shown in the simulations that by far the most critical aspect of multicriteria decision analysis under uncertainty is not the form of aggregation, but the correct elicitation of marginal utilities which properly represent decision maker preferences over gambles. We relate the results obtained here to other results on the approximation of distributions by three- or five-point discrete distributions, and suggest that the use of deterministic MCDM methods of any form (not necessarily value function techniques), applied to an extended formulation in which each criterion measure is repeated for three or five ‘scenarios’, can be justified.     

Preference Structures and Co-comparability Graphs

Order structures such as linear orders, weak orders, semiorders and interval orders are often considered as models of a decision maker's preferences. In this paper we introduce and study new order structures characterized by their symmetric part belonging to certain classes of co-comparability graphs. We outline possible interpretations and suggest special representations of these structures and we point out their potential use for approximating relations obtained through a multicriteria aggregation procedure. We provide various characterizations of the new structures (as well as of older ones) in terms of minimal forbidden configurations and by algebraic conditions.     

Accounting for Time Preference in Management Decisions: An Application to Invasive Species

Managers of invasive species seek to prevent and mitigate their impact, which vary in the time horizon over which they are realized. Likewise, stakeholders vary in the time horizons they consider relevant. Agricultural impacts might reasonably be considered over two or three decades, although ecologists typically consider environmental impacts over much longer time frames. Although time preference plays a critical role in decision making, it has largely been ignored in multicriteria analyses. In this study, we examine how time has been treated in previous decision analyses of invasive species management, focusing on the differences between multicriteria and economic cost–benefit analyses. We then outline a method for incorporating time preference information into multicriteria decision analyses to ensure that criteria weights remain a faithful representation of the decision maker's preferences. To illustrate how time preference can be elicited for invasive species problems involving both monetary and nonmonetary consequences, we describe a small empirical study we conducted with a small group of experts and managers. By outlining a way to consider time preference information in multicriteria analyses of invasive species management, we hope to facilitate better decision making that is reflective of the decision maker's true preferences. Copyright © 2013 John Wiley & Sons, Ltd.     

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.     

The Feasibility OF Collectives' Actions

Orthodox decision theory gives no advice to agents who hold two goods to be incommensurate in value because such agents will have incomplete preferences. According to standard treatments, rationality requires complete preferences, so such agents are irrational. Experience shows, however, that incomplete preferences are ubiquitous in ordinary life. In this paper, we aim to do two things: (1) show that there is a good case for revising decision theory so as to allow it to apply non-vacuously to agents with incomplete preferences, and (2) to identify one substantive criterion that any such non-standard decision theory must obey. Our criterion, Competitiveness, is a weaker version of a dominance principle. Despite its modesty, Competitiveness is incompatible with prospectism, a recently developed decision theory for agents with incomplete preferences. We spend the final part of the paper showing why Competitiveness should be retained, and prospectism rejected.     

Assessing risky public investments with MUSTARD

This paper presents a practical implementation of multicriteria methodologies based on the UTA model by Jacquet‐Lagrèze and Siskos and Quasi‐UTA model by Beuthe and Scannella, which are specified with a non‐linear, but piecewise linear, additive utility function. In contrast with the general UTA model, the Quasi‐UTA specification structures the partial utilities as recursive exponential functions of only one curvature parameter. This allows for a reduction of the quantity of information necessary to build the utility function. The software MUSTARD implements different variants of these models. Firstly, it offers the basic deterministic UTA model of disaggregation, but also its first programmed stochastic version. In both cases, the software proceeds stepwise and interactively helping the decision maker to formulate the problem and state preferences between projects; in the stochastic case, the decision maker is even helped to build the criteria distributions. The Quasi‐UTA specification can be introduced in this disaggregation model. Secondly, the software offers an aggregation model whereby the Quasi‐UTA partial utility functions are built separately through specific questioning processes. The questions relating to deterministic criteria are of the ‘direct rating type’, while those of the stochastic criteria are either of the ‘variable probability’ or the ‘variable outcome’ type. The criteria weights can be assessed by the ‘swing weight’ method or by a UTA‐II side‐program. As an example as well as a test of the Quasi‐UTA aggregation approach, the paper presents its application to a real problem of selecting road investment projects in Belgium. Several experts and civil servants were interviewed, and their individual utility functions derived. The projects are ranked according to their rate of return, which is computed on the basis of the projects certain equivalent money value. Copyright © 2002 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 approach to and computational results on testing the form of a decision maker's utility function

In this paper we consider the problem of identifying the form of a decision maker's (DM) utility function. We consider a set of alternatives each defined by a number of criteria and we assume that the DM's preferences are consistent with some underlying utility function. We present some theory and develop approaches to test whether the DM's preferences are consistent with a linear, a quasi-concave, a quasi-convex or a general monotonic function. We present our computational experience showing that in almost all cases the approaches correctly identify the form of the underlying utility function and require very little preference information of the DM.     

Applications of the MACBETH Approach in the Framework of an Additive Aggregation Model

In measurement theory terminology, MACBETH is an interactive approach for mapping into a real scale the various degrees to which the elements of a finite set possess a property P. The originality of MACBETH's questioning procedure is the possibility of establishing a constructive path towards cardinal measurement in both quantitative and substantive meaningful terms, avoiding the operational problems recognized as a weakness of other procedures. The use of the notion of semantic absolute judgements plays a key role here and the simplicity, interactivity and constructiveness of our approach insert it in the modern paradigms of decision aid. This article illustrates the usefulness of MACBETH as a tool to facilitate decision support, by describing its application in two real public decision situations where we acted as facilitators. Although the cases correspond to quite different decision contexts and problematics and our interventions have addressed diverse issues, they have in common the fact that we conducted both evaluation processes in the framework of an additive multicriteria aggregation procedure. In the first case MACBETH has been used to support the construction of (local) cardinal value functions, while the second illustrates how our approach can serve as a weighting procedure to determine the scaling constants of an additive aggregation model. © 1997 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.     

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.     

First-Order Logic Formalisation of Impossibility Theorems in Preference Aggregation

In preference aggregation a set of individuals express preferences over a set of alternatives, and these preferences have to be aggregated into a collective preference. When preferences are represented as orders, aggregation procedures are called social welfare functions. Classical results in social choice theory state that it is impossible to aggregate the preferences of a set of individuals under different natural sets of axiomatic conditions. We define a first-order language for social welfare functions and we give a complete axiomatisation for this class, without having the number of individuals or alternatives specified in the language. We are able to express classical axiomatic requirements in our first-order language, giving formal axioms for three classical theorems of preference aggregation by Arrow, by Sen, and by Kirman and Sondermann. We explore to what extent such theorems can be formally derived from our axiomatisations, obtaining positive results for Sen’s Theorem and the Kirman-Sondermann Theorem. For the case of Arrow’s Theorem, which does not apply in the case of infinite societies, we have to resort to fixing the number of individuals with an additional axiom. In the long run, we hope that our approach to formalisation can serve as the basis for a fully automated proof of classical and new theorems in social choice theory.     

Determining the implementation order of a general plan by using a multicriteria method

We describe a real-life application of a new multicriteria method in the context of assisting the decision-making for a general plan in the municipality of Kirkkonummi in Uusimaa, Finland. At the time our group started working on the problem, a proposal for an overall plan had already been completed, but the order in which different regional parts of the plan should be implemented needed to be considered based on the environmental impact assessment (EIA) procedure. The EIA procedure generated a large amount of data about the different impacts of the alternatives. For this group decision making problem we developed the SMAA-3 decision support method which does not require any explicit preference information from the decision makers during the procedure. The uncertainty of the basic data is modelled using ELECTRE III-type pseudo-criteria with preference and indifference thresholds. © 1998 John Wiley & Sons, Ltd.     

A convex approach for multicriteria decision making in hierarchical systems

In this paper hierarchical multicriteria optimization problems are addressed in a convex programming framework. It is assumed that the criteria are aggregated into a nonlinear function, which renders the problem nonseparable, in general. The projection of the problem onto the criteria space is used to obtain an equivalent separable problem, solved through a relaxation procedure implemented on basis of a multilevel structure. At the upper level of the structure, the decision making process involves the solution of a multicriteria problem formulated in the criteria space. The solution encountered at the upper level originates a lower level parametric optimization problem with separable structure that can be treated by standard coordination-decomposition techniques. The convergence of the overall procedure is ensured. The paper includes an application of the approach proposed for the control of dynamic systems with linear quadratic structure. © 1998 John Wiley & Sons, Ltd.     

Arrovian Aggregation of Generalised Expected-Utility Preferences: (Im)possibility Results by Means of Model Theory

Cerreia-Vioglio et al. (Econ Theory 48(2–3):341–375, 2011) have proposed a very general axiomatisation of preferences in the presence of ambiguity, viz. Monotonic Bernoullian Archimedean preference orderings. This paper investigates the problem of Arrovian aggregation of such preferences—and proves dictatorial impossibility results for both finite and infinite populations. Applications for the special case of aggregating expected-utility preferences are given. A novel proof methodology for special aggregation problems, based on model theory (in the sense of mathematical logic), is employed.     

Multicriteria approval: application of approval voting concepts to MCDM problems

Multicriteria decision making (MCDM) methods generally require information that is difficult and expensive to obtain. It is shown in this paper that given an ordering of criteria by importance, and whether each alternative is above the average evaluation of the alternatives for each criterion, considerable information can be extracted concerning the overall rankings of the alternatives. This is done by recognizing the similarity between criteria in MCDM, and voters in social choice theory. Multicriteria approval, proposed in this paper, is an MCDM adaptation of approval voting which can be used to classify decisions into one of several categories, depending on whether, and the manner in which, a superior alternative can be identified. An exhaustive examination of all possible decision situations of tractable size is made to measure the applicability of multicriteria approval, and the approach is demonstrated in an industrial procurement case. In addition to requiring minimal information from a decision maker, multicriteria approval satisfies several desirable criteria for MCDM techniques. © 1998 John Wiley & Sons, Ltd.     

The locality and globality of instrumental rationality: the normative significance of preference reversals

When we ask a decision maker to express her preferences, it is typically assumed that we are eliciting a pre-existing set of preferences. However, empirical research has suggested that our preferences are often constructed on the fly for the decision problem at hand. This paper explores the ramifications of this empirical research for our understanding of instrumental rationality. First, I argue that these results pose serious challenges for the traditional decision-theoretic view of instrumental rationality, which demands global coherence amongst all of one’s beliefs and desires. To address these challenges, I first develop a minimal notion of instrumental rationality that issues in localized, goal-relative demands of coherence. This minimal conception of instrumental rationality is then used to offer a more sophisticated account of the global aspects of instrumental rationality. The resulting view abandons all-or-nothing assessments of rationality and allows us to evaluate decision makers as being rational to varying degrees. My aim is to propose a theory that is both psychologically and normatively plausible.     

Inferences from decision difficulty

We propose that people infer the relative attractiveness of the choice alternatives from decision difficulty. A difficult decision signifies that the alternatives are close to each other in attractiveness, and an easy decision signifies that the alternatives are remote from each other in attractiveness. In Study 1, observers used reported decision difficulty to infer preferences of the decision maker. Studies 2-4 showed that inferences about the source of one’s own decision difficulty may affect a decision maker’s preferences. Study 4 integrates the notion of inferences from decision difficulty with dissonance theory, showing that in repeatable decisions difficulty reduces post-decisional spreading of alternatives, as predicted by our model, whereas with one-time decisions, difficulty enhances post-decisional spreading of alternatives, as predicted by dissonance theory.     

Reference-dependent utility with shifting reference points and incomplete preferences

Many empirical studies have shown that people's preferences are reference-dependent. Previous theoretical studies of reference-dependence assumed that the reference point was fixed and then imposed the usual assumptions of decision theory, in particular completeness of preferences. This paper gives preference foundations for additive reference-dependent utility when the reference point varies across decisions and is one of the options in the decision maker's opportunity set. This decision situation is common, for example because usually the retention of the status quo is an available option, but is difficult to handle axiomatically because it implies incompleteness of preferences. The results of this paper provide tools to extend existing theories of reference-dependent preferences, such as prospect theory, to new and empirically important decision contexts.