Multi-attribute Value Analysis Research Articles

Modeling for Decision Making: The Case of Medical Equipment Replacement

Successful organizations outdecide their competitors in at least 3 ways: they make better decisions, they make decisions faster, and they implement decisions more” (E. F. Harrison. The Managerial Decision-Making Process, 1999). In the past 3 decades, Multiple Criteria Decision Aids methods and techniques were developed extensively to support managerial decision making. This article summarizes an MBA research project where multiattribute value analysis, one of the main Multiple Criteria Decision Aids techniques, was used to develop a decision model for planning equipment replacement. The project outcome is a model that can be automated and provides a budget planning tool for medical equipment replacement.

A critical analysis of multi-criteria models for the prioritisation of health threats

Multi-criteria assessments are increasingly being employed in the prioritisation of health threats, supporting decision processes related to health risk management. The use of multi-criteria analysis in this context is welcome, as it facilitates the consideration of multiple impacts of health threats, it can encompass the use of expert judgment to complement and amalgamate the evidence available, and it permits the modelling of policy makers’ priorities. However, these assessments often lack a clear multi-criteria conceptual framework, in terms of both axiomatic rigour and adequate procedures for preference modelling. Such assessments are ad hoc from a multi-criteria decision analysis perspective, despite the strong health expertise used in constructing these models. In this paper we critically examine some key assumptions and modelling choices made in these assessments, comparing them with the best practices of multi-attribute value analysis. Furthermore, we suggest a set of guidelines on how simulation studies might be employed to assess the impact of these modelling choices. We apply these guidelines to two relevant studies available in the health threat prioritisation domain. We identify severe variability in our simulations due to poor modelling choices, which could cause changes in the ranking of threats being assessed and thus lead to alternative policy recommendations than those suggested in their reports. Our results confirm the importance of carefully designing multi-criteria evaluation models for the prioritisation of health threats.

Modeling the values of private sector agents in multi-echelon humanitarian supply chains

Humanitarian organizations (HOs) increasingly look to engage private sector supply chains in achieving outcomes. The right engagement approach may require knowledge of agents’ preferences across multi-echelon supply chains to align private sector value creation with humanitarian outcomes. We propose a multi-attribute value analysis (MAVA) framework to elucidate such preferences. We formalize this approach and apply it in collaboration with a HO pilot aiming to facilitate better private sector availability of malaria rapid diagnostic tests in Uganda. We demonstrate how HOs could use criteria weights and value functions from MAVA for project evaluation; in the process, we reveal business model insights for importers, distributors, and retailers in the pilot. We also show how MAVA facilitates the impact assessment of hypothetical options (i.e., combinations of products, services, and subsidies) to guide HO resource deployment. This paper offers the first attempt, to our knowledge, to develop quantitative measures for economic and non-economic objectives involving all agents in a multi-echelon supply chain, either humanitarian or commercial. We hope that this initial step stimulates further research to validate results and develop the framework proposed.

AN MBSE APPROACH TO SUPPORT ORGANISATIONAL REFORM OF THE ROYAL AUSTRALIAN NAVY

ABSTRACTThis paper presents a unique MBSE approach to enterprise modelling using a combination of IDEF0 functional modelling method. We applied this approach to the modelling of the engineering and administrative processes of the Royal Australian Navy (RAN). We developed the model named Materiel Seaworthiness Functional Master Set (MS FMS). Importantly, the MS FMS initiative drive comes from the top‐down by the Head of Navy Engineering, Rear Admiral Mick Uzzell AM. He wants assurance that all organisational entities in the large and complex environment of Navy, Defence Groups, and Industry are performing the right functions in a coordinated way to continuously deliver seaworthy materiel (ships, submarines and support items). We are piloting an analytical capability using the well‐established Multi‐attribute Value Analysis (MVA) method named the FMS Traffic Light System that aims to facilitate “what if ” analysis, ascertain functional health status, and inform high‐level organisational resource allocation and strategic planning to further the quest to balance efficient delivery with efficient resource allocation.

Decision model to control water losses in distribution networks

The losses in the urban water supply networks have become a growing concern. There are several alternatives for the quantification, detection and monitoring of water losses. However, in general, water companies have budgetary and other constraints that hinder implementation. Therefore, this paper presents a model to aid the selection of a subset of preventive maintenance actions to control water losses while accounting for the water companies’ restrictions. The model combines an additive multi-attribute value analysis by applying the SMARTER method to evaluate alternatives with Integer Linear Programming (ILP). The model shows to be efficient in order to achieve a portfolio of preventive maintenance actions, particularly when the decision maker considers that, there is a compensation for attribute evaluations.

An MBSE Approach to Support Organisational Reform of the Royal Australian Navy

AbstractThis paper presents a unique MBSE approach to enterprise modelling using a combination of IDEF0 functional modelling method. This approach has been applied to the modelling of the engineering and administrative processes of the Royal Australian Navy (RAN). The developed model is named Materiel Seaworthiness Functional Master Set (MS FMS). Importantly, the MS FMS initiative is being driven from the top‐down by the Head of Navy Engineering, Rear Admiral Mick Uzzell AM, so that he can be assured that all organisational entities in the large and complex environment of Navy, Defence Groups and Industry are performing the right functions in a coordinated way to continuously deliver seaworthy materiel (i.e. ships, submarines and support items). To further the quest to balance effective delivery with efficient resource allocation, an analytical capability using the well established Multi‐attribute Value Analysis (MVA) method is being piloted, and is named the FMS Traffic Light System which aims to facilitate “what if” analysis, ascertain functional health status, and inform high‐level organisational resource allocation and strategic planning.

Does the intuitive logics method – and its recent enhancements – produce “effective” scenarios?

In this paper, we synthesize the extant literature to establish the common objectives of scenario interventions within organizations and contextualize the well-established, but basic, “intuitive logics” scenario development methodology. We next consider if the basic intuitive logics method achieves these objectives. Then, we consider recent augmentations of the intuitive logics method and evaluate whether these augmentations enhance the basic method's capabilities. We find that there is a strong case for arguing that these scenario methods are designed to address two of the three objectives that we identified from the literature, namely: (i) enhancing understanding: of the causal processes, connections and logical sequences underlying events — thus uncovering how a future state of the world may unfold, and (ii) challenging conventional thinking in order to reframe perceptions and change the mindsets of those within organizations. However, other than in the augmentation in which multi-attribute value analysis is applied, none of the recent developments that we detail address directly the third objective that we distil from the literature: (iii) improving decision making: to inform strategy development. On this basis, we conclude that the ubiquitous term “scenario planning” is a misnomer and propose that other “scenario” terminologies might usefully be adopted that more precisely indicate the process and objectives of scenario interventions.

From the Editors…

This issue's “From the Editors…” column is coauthored with Managing Editor Kelly Kophazi. In addition to introducing our articles, we report here on the past year from the perspective of the editorial office. The authors of the first three articles conducted laboratory experiments to examine decision behavior in financial investment decisions, bidding in auctions, and inventory ordering decisions. First, Dennis Vrecko, Alexander Klos, and Thomas Langer report on the “Impact of Presentation Format and Self-Reported Risk Aversion on Revealed Skewness Preferences.” Our second article is “A Direct Test of Risk Aversion and Regret in First Price Sealed-Bid Auctions,” by Richard Engelbrecht-Wiggans and Elena Katok. The third article, by Srinagesh Gavirneni and Yusen Xia, is on “Anchor Selection and Group Dynamics in Newsvendor Decisions—A Note.” Our final article, describing the application of decision analysis for an Italian waste processing decision, is “Resource-Limited Multiattribute Value Analysis of Alternatives for Immobilizing Radioactive Liquid Process Waste Stored in Saluggia, Italy,” by Alan J. Brothers, Shas V. Mattigod, Denis M. Strachan, Gordon H. Beeman, Paul K. Kearns, Angelo Papa, and Carlo Monti.

Resource-Limited Multiattribute Value Analysis of Alternatives for Immobilizing Radioactive Liquid Process Waste Stored in Saluggia, Italy

This large Italian public works project started with the development of engineering data to support the evaluation of three alternatives for processing nuclear waste. After an analysis of the alternatives' performance from an engineering perspective was completed, Società Gestione Impianti Nucleari (Sogin), which is the Italian authority with the responsibility to decommission Italy's four nuclear power plants, asked Battelle, a company thoroughly familiar with nuclear waste processing, to provide an independent assessment of this important decision. The initial analysis did not include an evaluation of alternative performance from the perspective of a broad set of public values. As part of the assessment, we developed a decision methodology as a practical variation of the data-intensive decision processes often found in textbooks. In this paper, we describe a decision process in which we made use of engineering data and expert judgment to minimize expensive additional data collection so that we could perform a multiattribute decision analysis that was theoretically grounded and economical to implement, while incorporating both engineering and stakeholder objectives. Through this process, the Battelle staff verified the initial selection made by the staff at Sogin.

Supporting the allocation of software development work in distributed teams with multi-criteria decision analysis

In the fast moving software industry, projects have been increasingly developed by distributed teams, which are located in geographically remote offices and collaborate using information communication technologies. In such environments, project distribution presents specific challenges, as work in distributed teams increases project technical complexity, communication lines multiply and stakeholders’ interests may be divergent. Despite the importance and complexity of this type of problem, it seems that there is a lack of reports, in the literature, of systems that could support these decisions. This paper presents a real-world case study, where we developed a multi-criteria model for supporting the distributed team work allocation decision for a major global software company. It was developed with a group of software development project managers, using decision conferencing and multi-attribute value analysis. The model deals not only with software engineering attributes, but also “soft” and strategic issues, like team satisfaction and training opportunities. We also discuss some issues and challenges faced during this modelling process.

Using a Bayesian Approach to Quantify Scale Compatibility Bias

This paper proposes a new analytical framework to quantify and correct for scale compatibility bias in the assessment of trade-off weights in multiattribute value analysis. The procedure is demonstrated with an application to a fisheries management problem. Trade-off judgments are elicited from a group of fisheries experts with management responsibility in the Lake Erie basin. Then we use a Bayesian method to compute posterior probability distributions of attribute weights. In computing the Bayesian weights, our measurement model assumes that the weight ratios produced by each respondent's judgments are subject to random error and an unknown scale compatibility bias. Ratios are log-transformed and analyzed by a Bayesian linear model with a noninformative prior distribution. Posterior distributions are then developed for the weights and the bias. We estimate the compatibility bias for each person and, in most cases, it is found to be large and in the predicted direction, suggesting the importance of its consideration in deriving trade-off weights. In addition, the Bayesian framework is shown to be useful for quantifying the value of additional information about multiattribute weights. Finally, a simple heuristic procedure for assessing the weights appears to be effective in eliminating the bias.

New industrial product design and evaluation using multiattribute value analysis

Increasingly, the design of successful new industrial products is related to careful market assessment. Traditionally, managers and researchers have studied their markets by examining a small number of product attributes that are common across a range of informed respondents. In many ways, these techniques fail to meet the challenges posed by today's often heterogeneous, highly competitive, fast moving industrial markets. Ralph Keeney and Gary Lilien introduce us to a technique they call multiattribute value analysis, both describing the procedure and describing a comprehensive example. Their approach introduces considerable flexibility to the process of market assessment. Technically, it permits the evaluation of many more attributes, value tradeoffs, and synergies among attributes than do more traditional methods. In addition, it permits nonlinear evaluation functions that may be idiosyncratic to the individual. Practically, their approach, illustrated with a detailed case application, is shown to have significant potential for aiding product design decisions.

New Industrial Product Design and Evaluation Using Multiattribute Value Analysis

Increasingly, the design of successful new industrial products is related to careful market assessment. Traditionally, managers and researchers have studied their markets by examining a small number of product attributes that are common across a range of informed respondents. In many ways, these techniques fail to meet the challenges posed by today's often heterogeneous, highly competitive, fast moving industrial markets. Ralph Keeney and Gary Lilien introduce us to a technique they call multiattribute value analysis, both describing the procedure and describing a comprehensive example. Their approach introduces considerable flexibility to the process of market assessment. Technically, it permits the evaluation of many more attributes, value tradeoffs, and synergies among attributes than do more traditional methods. In addition, it permits nonlinear evaluation functions that may be idiosyncratic to the individual. Practically, their approach, illustrated with a detailed case application, is shown to have significant potential for aiding product design decisions.

Structuring Multi-attribute Value Hierarchies

The first stage in a multi-attribute value analysis is the development of a hierarchical structure of the attributes of the problem. This paper reports the process of developing such a structure for the problem of choosing a suitable mode of transport for radioactive waste. The initial hierarchy of attributes went through several stages of development as new insights emerged about the nature of the problem. Some of the reasons behind this restructuring are discussed, and several important questions about the structuring process are formulated.

Environmental Impact Assessment and Decision Analysis

A brief introduction to environmental impact assessment (E.I.A.) is given. An E.I.A. requires, as a final stage, the aggregation of diverse and highly subjective impacts, though in practice this is often done implicitly. Explicit aggregation techniques have their origins in cost-benefit analysis or decision analysis, and the appropriateness of these two techniques for applications in E.I.A.s is considered.An illustration of decision analysis is given in which multi-attribute value analysis is used to assist in the siting of new mines. The method can be presented as a development of the simple visual sieving technique, and by employing colour graphics facilities and microcomputers, a portable, flexible and powerful decision aid emerges: but powerful tools require careful handling.