Valerie Belton

A comparison of the analytic hierarchy process and a simple multi-attribute value function

Abstract The paper reviews the applicability of approaches to multiple criteria decision making to aiding in the selection of a preferred option from a short-list of alternatives in the light of a wealth of information about those alternatives. It is concluded that Saatys Analytic Hierarchy Process and a Simple Multi-Attributed Value Function are the approaches best suited to this problem and the most widely used in practice. The paper goes on to compare these approaches in detail from both a theoretical and a practical standpoint. The underlying assumptions of each are examined and considered in the light of practical decision aiding. The practical implications of the use of each approach are discussed. Reference is made to experimental work carried out by the author which has examined both practical and theoretical aspects of the use of each approach in isolation and in comparative studies. The paper will be of relevance to anyone facing a decision involving a finite number of alternatives and multiple criteria and considering the use of a formal approach.

Integrated Support from Problem Structuring through to Alternative Evaluation Using COPE and V·I·S·A

Work in the field of multiple criteria analysis has generally focused on evaluation procedures, taking as its starting point a well-defined problem with specified alternatives and criteria. However, in reality, problems are rarely so well-structured; hence, in order to usefully support decision making in practice, multiple criteria analysts need to address the issue of problem structuring. In this respect, much can be learned from the body of work stemming from operational research and systems in the U.K., known collectively as problem-structuring methods. In this paper we describe a study which sought to integrate one of these approaches, SODA (strategic options development and analysis), using the COPE software for cognitive mapping, with multiple criteria evaluation based on a multi-attribute value function using V·I·S·A. The study took the form of a 2 day action research workshop to explore the strategic direction of the Supplies and Commercial Services Department of a large U.K. NHS Hospital Trust and to develop an action plan consistent with the agreed direction. Even though the workshop was intended to be exploratory, from the point of view of both the facilitators and the participants, it enabled the group to make progress towards the definition of a strategic direction and led to an increased understanding and awareness of the issues. Drawing on this experience, we comment in general on the potential benefits arising from the integration of these two approaches and suggest fruitful areas for future research and development of the software tools and associated methodologies.

Adding value to performance measurement by using system dynamics and multicriteria analysis

The design, implementation and use of adequate performance measurement and management frameworks can play an important role if organisations are to succeed in an increasingly complex, interdependent and changing world. Yet, despite widespread recognition of the importance of performance assessment, there are some issues that require further study if measurement systems are to be effective in the process of management through monitoring and decision making. This article proposes and seeks to illustrate that the use of system dynamics and multicriteria decision analysis, as part of a broader framework for performance measurement, can address some of the issues identified. The use of these approaches, independently and in an integrated manner, provides a means of exploring the dynamic complexity of organisations, making explicit trade‐offs between performance measures, and assessing the impacts of initiatives to improve performance, thereby enhancing understanding and ultimately contributing to the improvement of organisational performance.

Causal maps and the evaluation of decision options - a review

Causal maps are widely employed in problem-structuring interventions. They permit a rich representation of ideas, through the modelling of complex chains of argument as networks. The last stage of a problem-structuring intervention is often to identify and agree to a set of potential strategic options. In some circumstances the preferred direction may emerge naturally from a process of negotiation; in others further, more-or-less formal, analysis to evaluate the options and to understand their impacts on the goals could be helpful. Such analysis may help to bring closure to the process. The main aim of this paper is to review systematically the approaches for evaluating options following from the use of a causal map for problem structuring; some directly using the map structure, others working with concepts extracted from, or an external model derived from, the map. Following a proposed taxonomy, each approach is presented, and its advantages and disadvantages are discussed.

A Framework for Group Decision Using a MCDA Model: Sharing, Aggregating or Comparing Individual Information?

ABSTRACT This article proposes a framework for group decision procedures which use A MCDA model. The framework is based on three elementary procedures—sharing, aggregating and comparing—which define the way in which the views of individuals are brought together with the aim of achieving a group decision. The framework refers to: (i) the main elements of a MCDA model, namely the aggregation method, the alternatives, the criteria, the evaluations and the weights, (ii) the extent to which these elements are individual or common to the group and, (Hi) the use of the three procedures—sharing, aggregating and comparing—to obtain and use these elements. The framework allows us to compare and contrast different ways of working with MCDA methods from a technical and a sociological perspective. The discussion highlights issues relating to process management, facilitation, time management and problem structuring.

Reasoning maps for decision aid: an integrated approach for problem-structuring and multi-criteria evaluation

This paper proposes a tool for multi-criteria decision aid to be referred to as a Reasoning Map. It is motivated by a desire to provide an integrated approach to problem structuring and evaluation, and in particular, to make the transition between these two processes a natural and seamless progression. The approach has two phases. In the first one, the building of a Reasoning Map supports problem structuring, capturing a decision makers reasoning as a network of means and ends concepts. In the second phase, this map is enhanced, employing a user-defined qualitative scale to measure both performances of decision options and strengths of influence for each means–end link. This latter phase supports the decision maker in evaluating the positive and negative impacts of an action through synthesis of the qualitative information. A case study, which investigates the use of the method in practice, is also presented.

Technology-driven and model-driven approaches to group decision support: focus, research philosophy, and key concepts

There are (at least) two distinct traditions within group decision support: what we will call the ‘Technology-driven’ tradition, which originates in the Information Systems discipline, and what we will call the ‘Model-driven’ tradition, which originates in OR/MS. Although proponents of the two traditions share many of the same objectives, in the past there has been little communication between the two groups. In this paper, we describe the basic distinction between the two traditions in terms of two primary themes: research focus (i.e., what the researchers find of interest) and research philosophy and methodology (i.e., how researchers go about studying their chosen subject matter); and we trace these implications of these differences through the key concepts of each tradition. We conclude by arguing that there are many opportunities for synergy between the two traditions.

Use of a Simple Multi-Attribute Value Function Incorporating Visual Interactive Sensitivity Analysis for Multiple Criteria Decision Making

V·I·S·A is a computer program for multiple criteria decision aid, based on a simple weighted multi-attribute value function, incorporating a hierarchical structure of criteria and visual interactive sensitivity analysis. The use of a model of this kind as an aid to multi-attribute decision making is nothing new. Long before MCDM became an established field of study in the 1970’s use of models of this kind been reported in the literature, for example, Churchman and Ackoff, 1954. Many popular approaches to decision aiding adopt the same framework, for example, Edwards’ SMART (Edwards, 1982), the Analytic Hierarchy Process developed by Saaty (Saaty, 1980), Social Cost Benefit Analysis (Lichfield et al., 1975). The approach is best suited to the problem of choosing a preferred alternative from a set of well defined alternatives, or to indicate a preference ordering over such a set of alternatives. There are many other approaches suited to this type of problem, for example, the Electre methods and Promethee. However, few approaches have been developed to handle a situation in which the decision maker wants to take account of very many criteria; in such a situation those methods incorporating a hierarchical structure of criteria are most appropriate, namely the multi-attribute value function and the Analytic Hierarchy Process.

Problem Structuring and Multiple Criteria Decision Analysis

This chapter addresses two complementary themes in relation to problem structuring and MCDA. The first and primary theme highlights the nature and importance of problem structuring for MCDA and then reviews suggested ways for how this process may be approached. The integrated use of problem structuring methods (PSMs) and MCDA is one such approach; this potential is explored in greater depth and illustrated by four short case studies. In reflecting on these and other experiences we conclude with a brief discussion of the complementary theme that MCDA can also be viewed as creating a problem structure within which many other standard tools of OR may be applied, and could therefore also be viewed as a PSM.

Decision support systems: learning from visual interactive modelling

Abstract The two research fields of, in the first instance, Decision Support Systems (DSS) and then secondly, Visual Interactive Modelling (VIM) have developed by mostly independent research. Yet these two fields seek many common goals. The VIM field has been seen as a largely technical development aiding certain Operational Research methods. On the other hand DSS have developed in the wider context of a recognition of a need to provide directed and helpful information to support decision making. In this paper we develop, firstly, an understanding of VIM in the context of current thinking on DSS. Ostensibly, it would seem that VIM is simply a DSS with a sophisticated user interface. However, we argue that VIM is an approach which has at its core an ability to allow decision makers to learn about their own subjective values while modelling technical issues. We suggest that embracing this learning objective at the design stage will enhance the power of Visual Interactive Models in particular and Decision Support Systems in general.