Decision Analysis Process Research Articles

Consultative multi-criteria decision making process for drought security

Water businesses have always sought to plan for drought-resilient urban water supply systems, especially in areas with extreme climate variability. The recently completed Lower Hunter Water Plan was developed to support population and business growth, and ensure reliable water supplies in drought. As well as introducing Water Wise Rules to encourage water conservation in normal conditions, the plan identified a portfolio (or combination) of drought response measures to be deployed progressively in a drought as water storage levels drop. The keys to the success of the Plan were thorough consultation with stakeholders, and collaborative analysis facilitating transparent evaluation of trade-offs among options and portfolios. A multi-criteria decision analysis process guided the assessment of the drought response options against both quantitative and qualitative criteria, and the assembly and analysis of portfolios. The process integrated the assessment of social and environmental criteria with cost effectiveness analysis, along with analysis of contextual uncertainties and risks, to determine the resilience of the options under different scenarios. The outcome was a portfolio of drought response options that best met the weighted criteria and satisfied their objectives.

Path dependence and biases in the even swaps decision analysis method

There are usually multiple paths that can be followed in a decision analysis process. It is possible that these different paths lead to different outcomes, i.e. there can exist path dependence. To demonstrate the phenomenon we show how path dependence emerges in the Even Swaps method. We also discuss the phenomenon in decision analysis in general. The Even Swaps process helps the decision maker to find the most preferred alternative out of a set of multi-attribute alternatives. In our experiment different paths are found to systematically lead to different choices in the Even Swaps process. This is explained by the accumulated effect of successive biased even swap tasks. The biases in these tasks are shown to be due to scale compatibility and loss aversion phenomena. Estimates of the magnitudes of these biases in the even swap tasks are provided. We suggest procedures to cancel out the effects of biases.

Multi-Criteria Decision Analysis to Value Orphan Medicines

Objectives: The purpose of this research is to identify the attributes to include in an orphan medicinal product (OMP) value framework, determine their relative importance via a multi-criteria decision analysis (MCDA) process, and test whether an MCDA approach can practically support decision making. Methods: The project included literature searches on the natural history and burden of 40 rare diseases and how payers assess treatment value as well as three workshops. Workshops also were held: the first with GlaxoSmithKline managers working on OMPs, the second with EU clinical and health economics experts, and the third with representatives of rare diseases patient groups in the European Union. Participants refined the attributes, weighted them, scored two case study OMPs in terms of those attributes, and tested the sensitivity of the overall ratings to changes in weights and scores. Results: Eight non-monetary attributes were agreed: four concern the disease being treated and four the treatment itself. Workshop participants agreed consensus weights for the attributes. The patient group representatives and the clinical and health economics experts both attributed about half of the weight to attributes reflecting the disease being treated, and half to attributes of the treatment. Patient group representatives gave greater weight than the experts to patients’ quality of daily life and less weight to clinical factors. The weighted attributes were readily applied by workshop participants to two example OMPs and yielded distinct ratings of their respective values. Conclusions: An OMP value framework with agreed attributes and weights is a viable proposition using an MCDA approach, and could improve clarity and transparency in decision making about the value of OMPs.

An Intelligent Project Management Maturity Model for Moroccan Engineering Companies

Engineering projects are managed in an environment often characterized by turbulence, complexity, and crucial need for flexibility and high quality information. The success or failure of these projects depends on decisions made during their life cycle. The burden of a bad decision in general and in the engineering sector, in particular, where business is generally run through projects, is becoming very overwhelming and these companies are urged to change the way they make decisions. They have to base their decisions more and more on high quality information, effective knowledge management (KM), and competitive intelligence (CI), tools. More importantly, they have to use an effective decision analysis process to avoid mental bias that is the most important reason behind bad decisions. Furthermore, such a project decision analysis process should reinforce the strategic alignment of the organization in order to achieve the desired decision strategic impact. However, the conjunction and harmonization of all these processes and systems require smooth and careful implementation, allowing for effective change management and high levels of maturity in project decision-making capabilities and competencies. Accordingly, the ECs need to climb suitable maturity levels, leading to both agility and flexibility. While agility relies on strong and adaptive processes covering the three main components of enterprise intelligence, namely business intelligence, CI and KM, flexibility for a project-based organization means a combination in a proper dosage of effective organizational PM processes, on the one hand, and balanced project decision processes, on the other.

Epilogue

This article explores the need for a paradigm shift in the policy and project decision analysis process of the development assistance industry in order to meet the challenges of global governance. The essay argues that such shifts will require the intentional use of narrative foresight to inform the leadership and engage followers in a shared vision of the desired future, and lays out a call to action for decision makers in the global commons that envisages seven key elements.

English

A learner is a cognitive system that develops by students information and knowledge-processing activities. To maximize the learners cognitive development, knowledge-intensive environments are essential particularly for achieving environmental knowledge. This paper proposes a model based on decision analysis approach in such a way could evaluate students cognitive development toward environmental problem A learner is a cognitive system that develops by his own information and knowledge-processing activities. To maximize the learner ' s cognitive development, knowledge-intensive environments are essential to help him explore a situation, construct his own concepts, and discover general laws by his own problem- solving activity (1). The lecturer, as knowledge facilitator, has an extremely complex problem on his hands. Before deciding exactly what course of action to take, he needs to consider many issues, including suitable environments and the uncertainties involving students abilities and school resources. Decision analysis provides effective methods for organizing a complex problem into a structure that can be analyzed (2). In particular, elements of a decision structure include the possible courses of action, the possible outcomes that could result, the likelihood of those outcomes, and eventual consequences to be derived from the different outcomes. Figure 1 shows a flowchart for the decision analysis process. For illustration, assume a lecturer needs to make a decision on which tutoring method to apply for motivating a class of under-achievers in engineering mechanics. A few alternatives may be considered: drill and practice, peer tutoring, hands-on activity, and on-line tutoring. Thereafter, variables associated with the alternatives are identified. The variables may be uncertainties such as students interest, their abilities, and availability of computer resources. Utility functions are assessed in order to model the way the lecturer values different outcomes and trade-off competing objectives. Decision analysis tools such as influence diagrams (2, 3) and decision trees (4, 5) are then used to model the problem for determining a preferred alternative. For complex models, computer software such as DPL (6) is available to auto-mate the computation. Additional analysis such as sensitivity study (7) may be performed to answerwhat if' questions such as: a computer resource is available, does it imply that on- line tutoring leads to a better student motivation?. If the answer is positive, then the lecturer may want to consider obtaining more information on that variable prior to making the decision.

Research on Conceptual Design Selection Based on Engineering Science

Engineering Science (ES) is bridge between basic science and engineering applications. It’s an important academic guidance for conceptual design selection of a large, complicated engineering project. Traditional plan selection depends largely on qualitative information and is subject to subjective factors. Using System Engineering (SE) methodology combined qualitative and quantitative information, this paper applies theory of ES to plan selection and decision making process Analysis on objectives, quantitative modeling and expert knowledge of complicated engineering project is conducted, in order to support a more objective, science-based decision making during conceptual design phase.

Net earthquake hazard and elements at risk (NEaR) map creation for city of Istanbul via spatial multi-criteria decision analysis

The creation of earthquake hazard maps requires various datasets with selected attenuation relations. Based on the selected attenuation relation, the calculation time varies from half an hour to a couple of days. The length of time needed to create an earthquake hazard map also depends on the resolution of the resulting map. The time gets longer as the resolution of the resulting earthquake hazard map gets higher. The basic form of an attenuation relation requires complex calculation algorithms including geospatial information related to the region of interest. Nowadays, next-generation attenuation (NGA) models are introduced to generate more realistic earthquake hazard maps. However, the more complex the attenuation relation is, the longer time will be required to create a hazard map. This paper offers a new method to create high-resolution earthquake hazard maps, faster than using traditional attenuation relation methods, by using an analytic hierarchy process of spatial multi-criteria decision analysis and geographic information systems. This method has been generated and tested for the city of Istanbul. The resulting maps are compared with the earthquake hazard maps created for the city of Istanbul by using the NGA model of Boore and Atkinson (in Boore–Atkinson NGA ground motion relations for the geometric mean horizontal component of peak and spectral ground motion parameters (trans: Engineering Co, University of California B). Pacific Earthquake Engineering Research Center 2007). A second output of this paper is a map of the elements at risk (EaR) for the population and buildings of Istanbul, and the introduction of a new approach of net elements at risk (NEaR).

Using combined AHP–genetic algorithm in artificial groundwater recharge site selection of Gareh Bygone Plain, Iran

Flood spreading is one of the suitable strategies to control and benefit from floods which in turn improve the groundwater recharge, makes soil more fertile, and increases nutrients in soil. It is also a method for reusing sediment, which is usually wasted. Thus, selection of suitable areas for flood spreading and directing the flood water into permeable formations are amongst the most effective strategies in flood spreading projects. Having combined analytic hierarchy process (AHP) of multi-criteria decision analysis and genetic algorithm (GA) of artificial intelligence approaches, this paper addresses the problem of finding the most suitable area location for flood spreading operation in the Gareh Bygone Plain of Iran. To this end, the nine effective geodata layers including slope, alluvium thickness, geology, morphology, electrical conductivity, land use, drainage density, aquifer transmissivity, and elevation were prepared in geographic information system environment. This stage was followed by elimination of the exclusionary areas for flood spreading while determining the potentially suitable ones. Having closely examined the potentially suitable areas using the proposed methodology, the land suitability map for flood spreading was produced. The AHP and GA were used for ranking all the alternatives and weighting the criteria involved, respectively. The results of the study showed that most suitable areas for the artificial groundwater recharge are located in Quaternary Qft2 and Qsf geologic units and in morphological units of pediment and Alluvial fans with slopes not exceeding 2 %. Finally, further evidence for the acceptable efficiency of the integrated AHP–GA method in locating most suitable flood spreading areas have been provided by such significant spatial coincidence between the produced map and the control areas located near Kowsar research station, where the earlier flood spreading projects were successfully performed.

Intelligent Multicriteria Decision Support System for Systems Design

It is challenging to assess new technology in complex, interdisciplinary integrated systems, such as air transportation systems. Conflicting disciplines and technologies are always involved in aerospace systems design processes. Multicriteria Decision Analysis techniques can help decision makers to effectively deal with such situations and make wise design decisions. There is a variety of existing methods; thus, selection of the most appropriate method is critical because the use of inappropriate methods is often the cause of misleading design decisions. In this paper, an appropriateness index is used to quantify the goodness of a method for solving the problem under consideration. This method selection approach is implemented and an intelligent knowledge-based system is developed consisting of a multicriteria decision analysis library storing widely used decision analysis methods and a knowledge base providing the information required for the method selection process. Furthermore, a new approach for uncertainty assessment in the decision analysis process is proposed in this study. This novel approach for uncertainty assessment can be used to aggregate input data from tools with different fidelity levels and is capable of propagating uncertainties in an assessment chain. A business aircraft evaluation problem is conducted as a proof of implementation.

Tradespace Exploration for the Engineering of Resilient Systems

Tradespace exploration supports the Systems Engineering Technical Management Process of Decision Analysis by identifying compromises, revealing opportunities, and communicating the impacts of decisions across a system's development lifecycle. Critical program decisions are made based on the outcomes of trades; trades being performed with multiple types and quantities of data coming out of tools and methods employing qualitative and quantitative analyses. Tradespace exploration for Engineered Resilient Systems (ERS) is envisioned to coalesce pertinent information tuned to specific decision makers, at the appropriate time, presenting a holistic view of decision impacts on required system capabilities. This study provides an ERS view of tradespace exploration, which reveals that having a valid set of attributes, and an understanding of how a cross-section of tools can satisfy them, is insufficient – what is needed is a deeper understanding of how these tools are used and, more importantly, how they can be used when performing tradespace exploration in support of the Decision Analysis Process. Gaining this understanding will enable users to better assess if they possess the appropriate tradespace exploration tools. A holistic view of 81 candidate tradespace exploration tools is provided. This study seeks to address a fundamental aspect of tradespace exploration by assembling a “best common practice” process for their requirements, identifying a set of attributes that defines an ideal tradespace exploration tool, and surveying existing tools that satisfy these attributes. In this way, a set of tools can be selected to enable the ERS tradespace vision on a particular project. A paradigm shift towards common tradespace methods, tools, cost models, and steps is emphasized.

A decision analysis framework for stakeholder involvement and learning in groundwater management

Abstract. Multi-criteria decision analysis (MCDA) methods are increasingly used to facilitate both rigorous analysis and stakeholder involvement in natural and water resource planning. Decision-making in that context is often complex and multi-faceted with numerous trade-offs between social, environmental and economic impacts. However, practical applications of decision-support methods are often too technically oriented and hard to use, understand or interpret for all participants. The learning of participants in these processes is seldom examined, even though successful deliberation depends on learning. This paper analyzes the potential of an interactive MCDA framework, the decision analysis interview (DAI) approach, for facilitating stakeholder involvement and learning in groundwater management. It evaluates the results of the MCDA process in assessing land-use management alternatives in a Finnish esker aquifer area where conflicting land uses affect the groundwater body and dependent ecosystems. In the assessment process, emphasis was placed on the interactive role of the MCDA tool in facilitating stakeholder participation and learning. The results confirmed that the structured decision analysis framework can foster learning and collaboration in a process where disputes and diverse interests are represented. Computer-aided interviews helped the participants to see how their preferences affected the desirability and ranking of alternatives. During the process, the participants' knowledge and preferences evolved as they assessed their initial knowledge with the help of fresh scientific information. The decision analysis process led to the opening of a dialogue, showing the overall picture of the problem context and the critical issues for the further process.

NEW MCEQLS TFN METHOD FOR EVALUATING QUALITY AND REUSABILITY OF LEARNING OBJECTS

The aim of the paper is to present a new simple to use and efficient MCEQLS (Multiple Criteria Evaluation of the Quality of Learning Software) TFN (Trapezoidal Fuzzy Numbers) method for the expert evaluation of the quality and reusability of learning objects (LOs). MCEQLS and TFN methods are analysed, improved, and practically applied to present the decision analysis process for selecting LOs suitable to reuse in different pedagogical situations and in different education systems. The research results are implemented in eQNet – a three-year strategic pan-European project focused on reusability of LOs. A novel method of consecutive application of Fuzzy Numbers theory to establish the weights of LOs quality criteria and MCEQLS approach to establish final evaluation results are explored in more detail. A number of multiple criteria decision analysis principles are applied to create a comprehensive quality model (criteria system) for evaluating the quality and reusability of LOs. Several practical examples of LOs evaluated against the proposed MCEQLS TFN method are presented in the paper. The research results have shown that the proposed method is quite objective, exact, simple to use, and efficient for selecting qualitative reusable LOs alternatives in the market.

Using multi‐criteria analysis to prioritize stakeholders

PurposeMany problems in science and engineering fields involve decision making. Usually these decision‐making processes are based on several criteria that represent various experts' knowledge. Stakeholder prioritization is useful for assisting in decision‐making situations where various stakeholders have competing interests, resources are limited, and stakeholder requirements must be appropriately balanced. When these conflicts arise it is important to the success of the organization that it has prioritized each stakeholder according to the situation. To date, few researchers tried to resolve this question, mostly are based on intuitive and very simple reasoning methods which are error prone. The purpose of this paper is to propose a multi‐criteria decision analysis process to help decision makers when evaluating and prioritizing stakeholders.Design/methodology/approachIn this process, Mitchell et al.'s model is used for identifying criteria on which stakeholders will be evaluated and the fuzzy Choquet integral as an aggregation operator. This research also tested and discussed the proposal using a case study from Toulouse city subway.FindingsThe results show the applicability of this process and the effectiveness of using the fuzzy Choquet integral than a traditional multi‐criteria evaluation method for human subjective evaluation, or when criteria are not mutually independent.Research limitations/implicationsThe highly subjective nature of criteria weights and rapid elicitation can lead to questions of validity. Also, results are not always widely accepted.Originality/valueThe paper is original in considering the stakeholder prioritization problem as a multi‐criteria decision analysis problem; using a simple and well‐known model to classify stakeholders, i.e Mitchell et al.'s model; and in using Choquet integral as an aggregation operator which allows considering interaction between criteria.

About the Authors

About the Authors

Multi-Criteria Decision Analysis in Occupational Safety Management Systems

Increasing the effectiveness of occupational safety increases the safety of an organization as its important performance. Safety performance indicators measure changes in the level of safety (related to accident prevention, preparedness and response) over time, which result from the actions taken to reduce appropriate risks. This paper presents the characteristics of basic types of safety indicators, the structure of safety factors, performances and indicators, as well as the multi-criteria decision analysis process and methods in safety management systems.

A linguistic decision support model for QoS priorities in networking

Networking resources and technologies are mission-critical in organizations, companies, universities, etc. Their relevance implies the necessity of including tools for Quality of Service (QoS) that assure the performance of such critical services. To address this problem and guarantee a sufficient bandwidth transmission for critical applications/services, different strategies and QoS tools based on the administrator’s knowledge may be used. However it is common that network administrators might have a nonrealistic view about the needs of users and organizations. Consequently it seems convenient to take into account such users’ necessities for traffic prioritization even though they could involve uncertainty and subjectivity. This paper proposes a linguistic decision support model for traffic prioritization in networking, which uses a group decision making process that gathers user’s needs in order to improve organizational productivity. This model manages the inherent uncertainty, imprecision and vagueness of users’ necessities, modeling the information by means of linguistic information and offering a flexible framework that provides multiple linguistic scales to the experts, according to their degree of knowledge. Thereby, this decision support model will consist of two processes: (i) A linguistic decision analysis process that evaluates and assesses priorities for QoS of the network services according to users and organizations’ necessities. (ii) A priority assignment process that sets up the network traffic in agreement with the previous values.

An evolutionary Bayesian belief network methodology for participatory decision making under uncertainty: An application to groundwater management

An integrated participatory approach based on Bayesian belief network (BBN) and evolutionary multiobjective optimization is proposed as an efficient decision-making tool in complex management problems. The proposed methodology incorporates all the available evidence and conflicting objectives to evaluate implications of alternative actions in the decision-making process and suggests best decision pathways under uncertainty. A BBN provides a framework within which the contributions of stakeholders can be taken into account. It allows a range of different factors and their probabilistic relationship to be considered simultaneously. It takes into account uncertainty by assigning probability to those variables whose states are not certain. The integration of BBN with evolutionary multiobjective optimization allows the analysis of tradeoff between different objectives and incorporation and acknowledgement of a broader set of decision goals into the search and decision-making process. The proposed methodology can be used as a decision support tool to model decision-making processes for complex problems. It deals with uncertainties in decision making pertaining to human behavior and checks for consistency of the developed BBN structure and the parameters of the probabilistic relationship by uncovering discrepancies in the decision analysis process (e.g., bias in completeness or redundancy of the model based on a utility function). It generates a set of efficient management options (appropriate combinations of interventions) that balances conflicting objectives. The effectiveness of the proposed methodology is discussed through application to a real case study. It is shown that it successfully identifies any inconsistencies in the developed BBN models and generates large numbers of management options that achieve an optimal tradeoff between different objectives.

Concepts Of Decision Making Under Uncertain, Risky Deterministic Situations

Making decisions is certainly the most important task of a manager and it is often a very difficult one. This paper offers a decision making procedure for solving complex problems step by step. It presents the decision-analysis process for both public and private decision-making, using different decision criteria, different types of information, and information of varying quality. It describes the elements in the analysis of decision alternatives and choices, as well as the goals and objectives that guide decision-making. The key issues related to a decision-maker's preferences regarding alternatives, criteria for choice, and choice modes, together with the risk assessment tools are also presented. The domain of decision analysis models falls between two extreme cases. This depends upon the degree of knowledge we have about the outcome of our actions. One "pole" on this scale is deterministic. The opposite "pole" is pure uncertainty. Between these two extremes are problems under risk. The main idea here is that for any given problem, the degree of certainty varies among managers depending upon how much knowledge each one has about the same problem. This reflects the recommendation of a different solution by each person. Probability is an instrument used to measure the likelihood of occurrence for an event. When you use probability to express your uncertainty, the deterministic side has a probability of 1 (or zero), while the other end has a flat (all equally probable) probability. The following sections of this paper are arranged as below. After introduction in section one, Decision Making under Pure Uncertainty are disscussed in section two. Section 3 and 4, are allocated to decision making under risk and bayesian approach respectively. Fifth section talks about decision tree and influence diagram and finally the paper will end with a brief conclusion.

A Fuzzy Multi-criteria Outranking Approach in Support of Business Angels’ Decision-Analysis Process for the Assessment of Companies as Investment Opportunities

In this paper, a multi-criteria method is presented for the evaluation and ranking of a selected set of companies as investment opportunities in aid of the relevant decision-analysis process of business angels. The multi-criteria methodology is based on the PROMETHEE method, which is further extended to deal with fuzzy input data in order to address the data imprecision and uncertainty of the decision process. The paper concludes by suggesting a web-based system implementation of the proposed methodology, which will significantly enhance modern business angels networks.