Decision Analysis Process Research Articles

Multi-Criteria Decision Analysis Under Uncertainty: Two Approaches to Incorporating Data Uncertainty into Water, Sanitation and Hygiene Planning

In the era of the Sustainable Development Goals, for which one of the aims is to provide universal access to safe water, sanitation and hygiene (WASH) services, it is crucial to target and prioritize those who remain unserved. Multi-criteria decision analysis (MCDA) models can play an important role in WASH planning by supporting priority-setting and policy-making. However, in order to avoid misleading assumptions and policy decisions, data uncertainty — intrinsic to the available collection methods — must be integrated into the decision analysis process. In this paper, we present two approaches to incorporating data uncertainty into MCDA models (MAUT and ELECTRE-III). We use WASH planning in rural Kenya as a case study to illustrate and compare the two approaches. The comparison focuses on the way these two models handle uncertainty in the available data. The analysis shows that, while both methods incorporate data uncertainty in a considerably different manner, they lead to similar prioritization settings.

Decision Analysis and Political Processes

Decision analysis has been with us for at least half a century. Over that time, it has developed from a theoretical paradigm for individual rational choice to a practical tool for individuals, small groups, and “unitary” organizations, which helps them toward sound decision making mindful of the behavioural characteristics of individuals and group dynamics. Decision analysis has also shown its worth in the context of stakeholder engagement and public participation. The time is right for it to be more widely used in making societal decisions. However, to achieve that, we need to realize that in many circumstances it will only be one input to the political process that leads to the actual decision. Recognizing that suggests that our community of decision analysts needs to deconstruct our paradigm and attend more to communicating the result of the analysis in comparison with other inputs to the societal decision.

Analysts’ Forecasts, the Abandonment Option and Intellectual Capital

The abandonment option under various capital budgeting models are discussed in this manuscript to bring forth the notion that present value of cash flows is often improperly estimated in the financial models utilized in the decision analytic process. In this study, Intellectual Property Rights and other intangible assets often are not considered in accounting estimation processes utilized in financial accounting. A decision maker often utilizes misestimates of the present value of cash flow resulting in less than optimum capital budgeting decisions. Decisions to abandon for salvage and other similar decisions improve when the present value of intangibles and property rights are included in the decision process. This last statement is the goal of this study and to present well founded processes to improve abandonment and similar decisions in capital budgeting decisions. The estimation problem in financial accounting is included in the analysis to accomplish this goal.

Multi-criteria decision-making for marine propulsion: Hybrid, diesel electric and diesel mechanical systems from cost-environment-risk perspectives

The paper introduces a new decision-making process which is used to compare the performance of a ship with either diesel electric hybrid propulsion or conventional propulsion systems. A case study was carried out to compare the performance of both propulsions from cost, environmental and risk perspectives. This paper also overviews the modern approaches of multi-criteria decision-making and highlights some of their shortcomings in particular the fact that these approaches often rely on different criteria such as financial, environmental or risk. This paper aims to overcome this shortcoming by enhancing the process of multi-criteria decision analysis. The key process in this research was to convert all incomparable values into monetary values, thereby enabling the impacts of each criterion to be compared and integrated in a straightforward manner. Results of the case study showed that the use of a hybrid propulsion system could reduce annual operational costs by $ 300,000 (2% total cost) compared with a diesel electric system and almost $ 1 million (7%) compared to a diesel mechanical propulsion system. In order to investigate the optimal use of the hybrid propulsion system, various operational scenarios were identified and applied to the proposed decision-making process. The results showed that operating the ship in hybrid mode during manoeuvring and berthing is more desirable as the holistic cost can reduce in almost $ 1 million. The advantages of the proposed decision making process was illustrated by comparing the results obtained from a conventional decision-making process using the analytical hierarchical method. It is believed that the research findings not only present general understanding of the possible advantages of hybrid propulsion for stakeholders, but provide them with an insight into the enhanced approach into the multi-criteria decision analysis.

PSY6 - Orphan Drugs Versus Ultra-Orphan Drugs: Price Comparison in England

Ultra-orphan drug (UOD) is a specific classification in England, encompassing drugs with a prevalence of less than 1/50,000. In May 2013, England enhanced specificity of UODs through a highly specialized technology (HST) process. This process confirms a focus on the overall magnitude of benefits to patients and society, rather than the cost-effectiveness threshold usually used for technology assessment. The aim of this study was to compare the prices of orphan drugs (ODs) and UODs in England. ODs approved in Europe up until 01/01/2018 were identified from the European Medicines Agency website. Based on the prevalence of the targeted diseases in England, ODs were divided between UODs (prevalence<1/50,000) and ODs (prevalence>1/50,000). Ex-factory prices available in England were extracted from IHS POLI database and annual treatment prices were calculated based on the posology described in the summary of products characteristics (SmPC). Median and mean annual prices were calculated in each group. One-hundred-two ODs approved in Europe were identified. Overall, 75 drugs had prices available in England: 12 UODs and 63 ODs. ODs’ annual prices varied widely between 610€ and 875,590€, while UODs annual prices varied between 6,868€ and 819,244€. UODs’ median annual prices was 2-fold the median prices of ODs (78,722€ versus 38,508€, respectively). Coherently, the mean annual prices reached almost the double of ODs’ mean annual prices; 193,248€ versus 108,790€ respectively. UODs benefit in England from a special decision analysis process and pricing pathway. This process incentivizes manufacturers to develop UODs, but may have a reverse effect for ODs. However, this may have led to very high prices, and, therefore, UODs are currently amongst the most expensive medicines on a yearly cost-per-patient basis. Still, there are important questions surrounding the actual use and access of such expensive drugs in England.

Probabilistic design optimization and simplified geotechnical risk analysis for large open pit excavations

A probabilistic geotechnical design optimization framework for large open pit excavations is proposed in the present work. An appropriate objective function is formulated in terms of normalized cost of excavation, while the overall slope angle constitutes the decision variable. Probability of slope's failure is computed via Monte Carlo simulations. Optimization curves identifying the optimum slope's angle are developed for different risk and volume factors. For illustrative purposes, a typical example of a surface lignite mine is analyzed and results are thoroughly discussed. The suggested methodology can be used as a complementary tool in the decision analysis process of similar projects.

Multi-criteria decision analysis for evaluating sustainable lifts design of public hospital buildings

Sustainability is a big trend in today’s building industry. For instance, energy use, resource efficiency, materials selection, safety, and life-cycle management are all important considerations in making the transition to greener buildings. In the past, lifts have been overlooked in green building planning yet including them is a useful way to improve overall building functionality and efficiency. Lifts use a relatively small amount of energy compared to the overall energy consumption of a building yet they provide both daily carrier service for user and so they should be included in sustainability planning. With so many building products being marketed with a sustainable angle, lifts also need to be included in this improvement. Building process has become complex due to the involvement of multiple benchmark like social, economic and environmental dimensions. A significant challenge for those involved in the building industry is identifying and incorporating sustainable features into each of the building stage. This in turn puts constrains to decision makers in selecting the finest decision in achieving sustainable goal for every aspect of building processes. This paper investigates the multi-criteria decision analysis for sustainable lifts design, namely; criteria selection, criteria weighting, evaluation and final aggregation. Decision analysis plays a vital role for designing the systems by considering various criteria. The criteria were grouped based on economic, environmental and social dimensions. Technique for order preference by similarity to ideal solution (TOPSIS) methods were employed to rank the most important criteria that need to be considered in making the decision. A design team from hospital project specifically from mechanical and electrical department have been chosen for this study due to their expertise in planning and designing the mechanical aspects for a project. As a result, it shows the process of decision analysis and provides the direction for sustainable lifts criteria selection which has a significant effect on the design. The result shows the preference dimension for sustainable lift design is economic aspect including its criteria required as decision analysis output for planning and designing lifts systems for public hospital buildings.

An Analytical Approach for Decision-Making

In this complex world, coping with daily problems is quite tedious. The more advancement in technology means more difficulties in decision-making process. Hence some analytical tools are needed to deal with improvement in decisions being made. A classic AHP model enables us to make efficient decision by reducing the complex issues. It takes multiple parameters into consideration. One of the area where decision-making is quite a tough job is Politics. Selection of the electoral party in any elections, be it Lok Sabha elections or Rajya Sabha elections, has been a matter of discussion for the voters as well as the media. The decisions are reflected when uncertainties are added in the opinions of the domain experts due to multiple parameters. In this paper we have proposed a model for rectifying the uncertainties using multi criteria decision analysis and analytic hierarchy process (AHP).

Proposal of a Measurement Scale of Decision Quality in Infrastructure Projects in Oil and Gas Exploitation

The objective in this paper is to present a proposal of a scale to measure the decision quality in infrastructure projects in the exploitation of oil and gas, as well as its foundations. One of the most important distinctions of Decision Analysis is the differentiation between a good decision and a good outcome, which is the approach of the scale, which occurs when decision making faces uncertainty. Therefore, a good decision does not always produce a good outcome. From this distinction, a progressive scale was designed, using an adjustment of the pairwise comparisons based on the Saaty scale achieving a quantitative hierarchy, which shows whether the decision guarantees quality, does not guarantee quality or is not acceptable. For its application, other existing decision processes used in the petroleum industry were located, from their common components a standardized decision analysis process was created, the common components are appropriate frame, objectives, decision and alternatives, risk and uncertainty, possibilities and modelling, values and exchanges and implementation and each of them subdivided into key aspects that are object of the measurement and evaluation. The objective set in a first stage was the proposed model of the measurement scale of decision quality and is subject to future validation work to verify its applicability in real life in a second stage.

Screening for latent and active tuberculosis infection in the elderly at admission to residential care homes: A cost-effectiveness analysis in an intermediate disease burden area.

BackgroundTuberculosis (TB) in the elderly remains a challenge in intermediate disease burden areas like Hong Kong. Given a higher TB burden in the elderly and limited impact of current case-finding strategy by patient-initiated pathway, proactive screening approaches for the high-risk group could be optimal and increasingly need targeted economic evaluations. In this study, we examined whether and under what circumstance the screening strategies are cost-effective compared with no screening strategy for the elderly at admission to residential care homes.MethodsA decision analytic process based on Markov model was adopted to evaluate the cost-effectiveness of four strategies: (i) no screening, (ii) TB screening (CXR) and (iii) TB screening (Xpert) represent screening for TB in symptomatic elderly by chest X-ray and Xpert® MTB/RIF respectively, and (iv) LTBI/TB screening represents screening for latent and active TB infection by QuantiFERON®-TB Gold In-Tube and chest X-ray. The target population was a hypothetical cohort of 65-year-old people, using a health service provider perspective and a time horizon of 20 years. The outcomes were direct medical costs, life-years and quality-adjusted life-years (QALYs) measured by incremental cost-effectiveness ratio (ICER).ResultsIn the base-case analysis, no screening was the most cost-saving; TB screening (CXR) was dominated by TB screening (Xpert); LTBI/TB screening resulted in more life-years and QALYs accrued. The ICERs of LTBI/TB screening were US$19,712 and US$29,951 per QALY gained compared with no screening and TB screening (Xpert), respectively. At the willingness-to-pay threshold of US$50,000 per QALY gained, LTBI/TB screening was the most cost-effective when the probability of annual LTBI reactivation was greater than 0.155% and acceptability of LTBI/TB screening was greater than 38%. In 1,000 iterations of Monte Carlo simulation, the probabilities of no screening, TB screening (CXR), TB screening (Xpert), and LTBI/TB screening to be cost-effective were 0, 1.3%, 20.1%, and 78.6% respectively.ConclusionsScreening for latent and active TB infection in Hong Kong elderly people at admission to residential care homes appears to be highly effective and cost-effective. The key findings may be the next key factor to bring down TB endemic in the elderly population among intermediate TB burden areas.

A new multi-criteria decision process to prioritise requirements

Most software projects have more candidate requirements than can be realised within the time and cost constraints. This paper presents a novel multi-criteria decision analysis process to prioritise requirements. The novelty of the presented idea is three-fold. Firstly, to prioritise requirements, it distinguishes two categories of requirements according to their level of abstraction: low-level requirements and high-level requirements. Then, it relates business goals to the requirements of low-level which contribute to their fulfilment. This will improve the completeness and traceability of requirements. Secondly, requirements prioritisation is based on their degree of contribution to the identified business goals and their importance. So, business goals become the evaluation criteria. Finally, this process takes into account relationships and dependencies that may exist between business goals. At this end, we employ analytic hierarchy process (AHP) method to give weights to business goals and Choquet integral to calculate a global score, i.e. priority, for requirements.

USE OF CONTROL VARIABLES TO IMPROVE THE PERFORMANCE OF WATER AND POLYMER FLOODING STRATEGIES

In oil industry, decisions related to field development take into consideration scenarios that involve many uncertainties and high investments. Thus, a comprehensive decision analysis process is necessary to select the production strategy that maximizes field performance considering these uncertainties. For the selection of a production strategy, two main groups of optimization variables may be considered: design and control variables. The design variables relate to the development of the field, and cannot be altered after the implementation of the strategy (e.g. capacity of the platform, number and position of wells). On the contrary, control variables relate to the management of the field, and can be altered daily by the companies (e.g. production and injection rates). However, even with a robust production strategy selection process, unexpected or undesirable events can occur and decrease the economic efficiency of the project. The objective of this work is to evaluate the use of control variables when undesirable events occur after the implementation of a production strategy, to improve the economic performance of the project. Two production strategies are used: one that uses only water flooding and other one prepared for polymer flooding. The simulation model is based on a heterogeneous heavy oil offshore field. Two approaches (undesirable events) are considered in this work: (1) polymer degradation and (2) a geologic model that is different than the expected one. The results show that the economic performance can be improved greatly by simply adjusting the control variables for the described situations. Moreover, the gain in the polymer flooding case is higher than for water flooding, because of the higher number of optimization variables, such as polymer solution concentration and slug size, giving more flexibility to this kind of project.

PIN120 - A Dynamic Decision Analysis Process For Evaluating Pandemic Influenza Intervention Strategies

Public health authorities (PHA) experience challenges during outbreaks of pandemic influenza. There are (1) a high public attention and pressure for fast and effective actions, (2) uncertainty regarding development and potential impact of the pandemic, (3) complexity of the decisions on selecting interventions – this involves considering multitude of criteria and interests of stakeholders. Therefore we suggest a dynamic decision analysis process, which supports comprehensiveness, transparency, and consistency in decisions regarding interventions. The process design was informed by scenario analysis, multi-criteria decision analysis methodology, and adapted to the Swedish context. The process was then validated in a pilot decision conference (DC) conducted at the PHA of Sweden. The process consists of elicitation and evaluation. Elicitation comprises developing scenarios, intervention strategies, and a multi-criteria model (MCM) against which the strategies are evaluated. In the evaluation process the strategies are scored, criteria weighted, and the results analyzed. In the pilot DC we considered a mild pandemic scenario, similar to the influenza pandemic of 2009. Three intervention strategies were evaluated, based on four interventions; vaccination (VAC), antiviral treatment (AVT), antiviral prophylaxis (AVP), school closure (SC). Strategy (1) included AVT to everyone with influenza-like illness (ILI), VAC to risk-groups, (2) AVT and AVP to risk-groups, SC, and VAC to everyone, and (3) AVT to everyone with ILI, AVP to risk-groups, and VAC to everyone. Guided by the process the seven participants outlined the MCM through a post-it session, evaluated the strategies against the criteria, and expressed criteria weights. Finally the results were aggregated and visualized. The analysis showed that strategy (1) was the most preferred. The process supports a dynamic, comprehensive, and transparent decision-making. An integrated decision-support toolset will be developed in forthcoming research along with contextualising and validating the process with Sweden related stakeholders.

Experiences of stakeholder participation in multi-criteria decision analysis (MCDA) processes for water infrastructure

The process of multi-criteria decision analysis is commonly utilized in planning processes for technical infrastructure. This includes water infrastructure, which is currently impacted by global changes in environmental conditions. Consequentially, technical and conceptual options have been developed with the focus on sustainability by closing water and material cycles. The inclusion of stakeholder perspectives in the planning process would be supported by purposeful MCDA implementation. This paper examines initial stages of the MCDA with a focus on the multi-stakeholder-group-driven collaborative development of a set of objectives (SOO). Additional emphasis is given to participatory methods for each stage of the two, presented case studies examined in this paper. An attempt has been made to describe perceptions and outcomes of the case studies. The developed SOOs are presented and discussed with special regard to the development process and the evaluation outcomes.

A model-based decision analysis comparing water and polymer flooding in the development of a heavy oil field

Polymer flooding is an effective means to recover oil although the method creates conditions absent in traditional water flooding, mainly due to the physical phenomena related to this technique, such as adsorption of polymer molecules and non-Newtonian behavior. This work aims to guide the selection, through a decision analysis methodology, of the best strategy option using comparisons between water and polymer flooding projects in a heavy oil field development, under uncertainty, through a risk-return analysis.The methodology is based on a complete risk evaluation and decision analysis process presented by Schiozer et al. (2015), including the generation of uncertain scenarios, selection of representative models (RM), production strategy optimization for the RM, combination of the strategies in all scenarios, risk-return and risk curves analysis and the selection of the best strategy. The case study is representative of a heavy oil and high heterogeneous reservoir. We combined geological, economic and polymer uncertainties. We use Expected Monetary Value (EMV) as the objective function to measure economic return and Net Present Value (NPV) semi-deviation to measure risk.The results show that simplified comparisons between these two recovery methods, by only changing the injection fluid may lead to ill-informed decisions, and therefore, pre-planning is needed to realize the advantages from additional polymer costs to choose an optimal strategy. Furthermore, the results suggest that polymer flooding may be a viable alternative in the heavy oil field studied in this work.

Biases in multicriteria decision analysis: The case of environmental planning in Southern Nevada

Multicriteria decision analysis is a decision support aid touted for its ability to help participants overcome bias and make holistic assessments. However, few offer empirical tests of this thesis. This research examines the use of multicriteria decision analysis to implement the Southern Nevada Public Lands Management Act. The Act called upon federal, regional, and local agencies to develop a connected system of parks, trails, and natural areas throughout Nevada. The partners used multicriteria decision analysis to make decisions about which parks, trails, and natural areas projects to fund. We assess the extent of political and cognitive biases among the participants when using the multicriteria decision analysis process. We find no strong evidence of strategic behavior, a finding that highlights many of the celebratory claims made about multicriteria decision analysis. However, we also note a preference for projects adjacent to high-income areas as well as the presence of cognitive biases in the assignment of scores to projects.

Decision Analysis for Metric Selection on a Clinical Quality Scorecard.

Clinical quality scorecards are used by health care institutions to monitor clinical performance and drive quality improvement. Because of the rapid proliferation of quality metrics in health care, BJC HealthCare found it increasingly difficult to select the most impactful scorecard metrics while still monitoring metrics for regulatory purposes. A 7-step measure selection process was implemented incorporating Kepner-Tregoe Decision Analysis, which is a systematic process that considers key criteria that must be satisfied in order to make the best decision. The decision analysis process evaluates what metrics will most appropriately fulfill these criteria, as well as identifies potential risks associated with a particular metric in order to identify threats to its implementation. Using this process, a list of 750 potential metrics was narrowed to 25 that were selected for scorecard inclusion. This decision analysis process created a more transparent, reproducible approach for selecting quality metrics for clinical quality scorecards.

Using Decision Analysis to Understand the Indications for Unilateral Hand Transplantation.

Background: Upper extremity transplantation has been performed to improve quality of life, the benefit which must be traded off for the risk created by life-long immunosuppression. We believe the process of decision analysis is well suited to improve our understanding of these trade-offs. Method: We created a decision tree to include a branch point to illustrate the expected recovery of useful function in the transplant, using the best estimates for utility and probability that exist. Results: Our model revealed that when the probability of achieving a good result, graded as Chen level one or two is greater than 73%, transplantation is preferred over no transplantation. The decision is sensitive to the probability of major complications and the utility of a transplanted limb with minimal function. Conclusions: The results of this analysis show that under some circumstances given a high probability of satisfactory functional recovery, unilateral hand transplantation can be justified.

Landfill site selection using combination of GIS and fuzzy AHP, a case study: Iranshahr, Iran.

One of the most important recent challenges in solid waste management throughout the world is site selection of sanitary landfill. Commonly, because of simultaneous effects of social, environmental, and technical parameters on suitability of a landfill site, landfill site selection is a complex process and depends on several criteria and regulations. This study develops a multi-criteria decision analysis (MCDA) process, which combines geographic information system (GIS) analysis with a fuzzy analytical hierarchy process (FAHP), to determine suitable sites for landfill construction in Iranshahr County, Iran. The GIS was used to calculate and classify selected criteria and FAHP was used to assess the criteria weights based on their effectiveness on selection of potential landfill sites. Finally, a suitability map was prepared by overlay analyses and suitable areas were identified. Four suitability classes within the study area were separated, including high, medium, low, and very low suitability areas, which represented 18%, 15%, 55%, and 12% of the study area, respectively.

Integrated fuzzy analytic hierarchy process and VIKOR method in the prioritization of pavement maintenance activities

Maintenance activities and pavement rehabilitation require the allocation of massive finances. Yet due to budget shortfalls, stakeholders and decision-makers must prioritize projects in maintenance and rehabilitation. This article addresses the prioritization of pavement maintenance alternatives by integrating the fuzzy analytic hierarchy process (AHP) with the VIKOR method (which stands for ‘VlseKriterijumska Optimizacija I Kompromisno Resenje,’ meaning multi-criteria optimization and compromise solution) for the process of multi-criteria decision analysis (MCDA) by considering various pavement network indices. The indices selected include the pavement condition index (PCI), traffic congestion, pavement width, improvement and maintenance costs, and the time required to operate. In order to determine the weights of the indices, the fuzzy AHP is used. Subsequently, the alternatives’ priorities are ranked according to the indices weighted with the VIKOR model. The choice of these two independent methods was motivated by the fact that integrating fuzzy AHP with the VIKOR model can assist decision makers with solving MCDA problems. The case study was conducted on a pavement network within the same particular region in Tehran; three main streets were chosen that have an empirically higher maintenance demand. The most significant factors were evaluated and the project with the highest priority was selected for urgent maintenance. By comparing the index values of the alternative priorities, Delavaran Blvd. was revealed to have higher priority over the other streets in terms of maintenance and rehabilitation activities.