An Examination of the Decision Analysis Approach to R&D Portfolios

A portfolio can be defined as “a purposeful combination of items” (Chien and Sainfort 1998). As the topic relates to research and development (R&D) the items in question are technologies, projects or products under consideration for inclusion in a given portfolio. As described by surveys from Cooper et al (1998), companies have widely varying practices for portfolio selection. This thesis examines existing literature to determine the key characteristics of good portfolio and portfolio method. The approach needs to handle multiple objectives, account for project interactions, and address the social aspect of decision making. The resulting portfolio should be aligned with business strategy, balanced, and of maximum value. It introduces general concepts that have been used to select single projects and reviews five specific applications and assesses them against the key characteristics from the literature. After identifying gaps in the current approaches, a comprehensive approach is proposed. This approach would (1) apply multi-attribute decision analysis at the portfolio level, (2) apply constraints for common inputs to cost such as resources, and (3) apply probabilistic methods to account for project interaction. This approach incorporates successful elements from existing approaches and addresses the two areas that are not adequately addressed with current approaches

The SIMRAND methodology: Theory and application for the simulation of research and development projects

A research and development (R&D) project often involves a number of decisions that must be made concerning which subset of systems or tasks are to be undertaken to achieve the goal of the R&D project. To help in this decision making, SIMRAND (SIMulation of Research ANd Development Projects) is a methodology for the selection of the optimal subset of systems or tasks to be undertaken on an R&D project. Using alternative networks, the SIMRAND methodology models the alternative subsets of systems or tasks under consideration. Each path through an alternative network represents one way of satisfying the project goals. Equations are developed that relate the system or task variables to the measure of reference. Uncertainty is incorporated by treating the variables of the equations probabilistically as random variables, with cumulative distribution functions assessed by technical experts. Analytical techniques of probability theory are used to reduce the complexity of the alternative networks. Cardinal utility functions over the measure of preference are assessed for the decision makers. A run of the SIMRAND Computer I Program combines, in a Monte Carlo simulation model, the network structure, the equations, the cumulative distribution functions, and the utility functions

Decision Support for Innovation Management: Application to the Lighting Industry

Making decisions about resource allocation for future innovations is a challenging task in both planned and market economies. Not only can such decisions not be reversed without considerable loss of efficiency, but the decision maker generally faces a number of conflicting objectives. In this report the authors try to combine two disciplines that have been evolving independently for a long time: innovation theory and decision theory. A decision support system for managing innovations should reflect the multistage nature of the innovation process and should also be suited to multiobjective decision making. At the same time it is necessary to simplify the real situation for the decision maker in order to apply former procedures. A very promising scheme is the decision tree, though it has shortcomings. Application of decision trees is closely connected with the evaluation process. Almost all models for evaluating innovation projects operate with only one objective. However, discussions with decision makers in the lighting industry, which shows classic features of the innovation process, revealed the necessity to include at least three objectives in the evaluation. Therefore, the authors have made use of the possibilities of multiobjective decision making. The decision problem in this work concerns the allocation of resources to innovation projects for the 1981-85 Five-Year Plan in the German Democratic Republic. At present the model for evaluating innovation projects is based upon linear programming and decision trees. It will be improved in close collaboration with decision makers, using the results of goal programming and other aspects of decision theory

Integrating Multiple Criteria Decision-Making Models Into the Decision Support System Framework for Marketing Decisions

The paper focuses on integrating the multiple criteria decision making (MCDM) models within the decision support system (DSS) framework to encourage greater use of these models. A DSS framework and the criteria used for the choice of a model is discussed. Based on these criteria MCDM models generally used in the marketing field are evaluated. The possibility of using a mixture of MCDM models within the DSS framework is also explored. Following this, the role of the MCDM models in DSS is delineated. It is argued that, within the problem-solving process, the confluence of MCDM models and DSS plays a vital role in developing high-quality solutions

R & D Planning Involving Multicriteria Decision Analytic Methods at the Branch Level

This series of papers are a product of collaborative research coordinated through IIASA's Management and Technology Area. The collaborating institutions are Hungarian State Office of Technical Development (Personnel: Anna Vari, Janos Vecsenyi, Laszlo David); Decision Analysis Unit, Brunel University, England (Personnel: Patrick Humphreys, Lawrence D. Phillips); All-Union Research Institute of Systems Studies, USSR (Personnel: Oleg. I Larichev). The papers report case studies prepared by the personnel from the collaborating institutions based on their own, and their colleagues' work in their own institutions. They worked together as a team in developing the methods for the analysis of these case studies which are described in the first paper in the series. IIASA provided support for this work through its telecenter for communication between the investigations, and provided facilities for short term meetings between the investigations at IIASA for development of case studies and their comparative analysis. Particular MMT staff were Ronald M. Lee, Nora Avedisians, and Miyoko Yamada, who is the editor of this series. A summary of this comparative analysis, based on the first four case studies in this series was presented at the IFIP/IIASA Conference on "Processes and Tools for Decision Support", Laxenburg, Austria, July, 1982. The paper presented at the IFIP/IIASA conference will be published as Humphreys, P.C., O.I. Larichev, A. Vari, and J. Vecsenyi, Comparative analysis of decision support systems in R&D decisions, in H.G. Sol (ed.), "Processes and Tools for Decision Support", Amsterdam: North Holland, 1982. Another study in this series was published separately as L.D. Phillips: Requisite decision modeling: a case study. "Journal of the Operations Research Society, 1982, 33:303-311

Design and Evaluation of Feedback Schemes for Multiattribute Procurement Auctions

Multiattribute auctions, which allow bids on multiple dimensions of the product, are IT-enabled sourcing mechanisms that increase the efficiency of procurement for configurable goods and services compared to price-only auctions. Given the strategic nature of procurement auctions, the amount of information concerning the buyer’s preferences that is disclosed to the suppliers has implications on the profits of the buyer and suppliers and, consequently, on the long-term relationship between them. This study develops novel feedback schemes for multiattribute auctions that protect buyer’s preference information from the supplier and suppliers’ cost schedule from the buyer. We conduct a laboratory experiment to study bidder behavior and profit implications under three different feedback regimes. Our results indicate that bidders are able to extract more profit with more information regarding the state of the auction in terms of provisional allocation and prices. Furthermore, bidding behavior is substantially influenced by the nature and type of feedback

Integrating Multiple Criteria Decision-Making Models Into the Decision Support System Framework for Marketing Decisions

The paper focuses on integrating the multiple criteria decision making (MCDM) models within the decision support system (DSS) framework to encourage greater use of these models. A DSS framework and the criteria used for the choice of a model is discussed. Based on these criteria MCDM models generally used in the marketing field are evaluated. The possibility of using a mixture of MCDM models within the DSS framework is also explored. Following this, the role of the MCDM models in DSS is delineated. It is argued that, within the problem-solving process, the confluence of MCDM models and DSS plays a vital role in developing high-quality solutions

Rationalizing Systems Analysis for the Evaluation of Adaptation Strategies in Complex Human-Water Systems

Water resources management is a nontrivial process requiring a holistic understanding of the factors driving the dynamics of human-water systems. Policy-induced or autonomous behavioral changes in human systems may affect water and land management, which may affect water systems and feedback to human systems, further impacting water and land management. Currently, hydro-economic models lack the ability to describe such dynamics either because they do not account for the multifactor/multioutput nature of these systems and/or are not designed to operate at a river basin scale. This paper presents a flexible and replicable methodological framework for integrating a microeconomic multifactor/multioutput Positive Multi-Attribute Utility Programming (PMAUP) model with an eco-hydrologic model, the Soil and Water Assessment Tool (SWAT). The connection between the models occurs in a sequential modular approach through a common spatial unit, the “hydrologic-economic representative units” (HERUs), derived from the boundaries of decision-making entities and hydrologic responsive units. The resulting SWAT-PMAUP model aims to provide the means for exploring the dynamics between the behavior of socio-economic agents and their connection with the water system through water and land management. The integrated model is illustrated by simulating the impacts of irrigation restriction policies on the Río Mundo subbasin in south-eastern Spain. The results suggest that agents' adaptation strategies in response to the irrigation restrictions have broad economic impacts and subsequent consequences on surface and groundwater hydrology. We suggest that the integrated modeling framework can be a valuable tool to support decision-making in water resources management across a wide range of scales

Strategy-to-task resource management : application of hierarchies in Defense Resource Planning

Current defense planning methods do not ensure a direct connection between national security objectives and military tasks. The Strategy-to-Task method provides a framework for solving this deficiency by establishing a hierarchy, starting from national objectives, through military objectives and missions to military tasks. Below these tasks, performance standards can be used for estimating the utility of a given task. This hierarchical approach helps decision-makers understand these important linkages. It could also serve as a framework for prioritizing the different tasks and contribute to better resource allocation, by analyzing different alternatives in a multi-attribute space. There are two decision-supporting methods for setting up priorities within this hierarchy of multi-attribute objectives. The first one, Multi-Attribute Utility Function Analysis, is a useful method for cases when performance standards can easily be established. This method could be used under both certainty and uncertainty and can address dependence and independence among the attributes or their utilities. The second method, the Analytic Hierarchy Process, could be used in cases when performance standards are difficult to establish as is typically the case in the higher levels of the hierarchy. The hierarchical approach and the two methods are illustrated through the case of Hungary's participation in NATO peace-operations.http://archive.org/details/strategytotaskre1094513504Hungarian Army athor.Approved for public release; distribution is unlimited