Multi-attribute Value Theory Research Articles

Assessing energy storage technology options using a multi-criteria decision analysis-based framework

With the growing adoption of intermittent renewable energy generation the role for energy storage to provide a number of service needs is being increasingly recognised. However, ‘energy storage’ encompasses a family of technologies, each with its own set of performance, cost and physical characteristics, at different stages of development. At the same time, each energy system – however defined – has specific needs; and energy systems are themselves part of a wider socio-technical system which has aims beyond the confines of the energy ‘trilemma’. As energy storage technologies develop, funding is becoming available to demonstrate their application in realistic environments. However, with multiple technical and non-technical factors to consider, it is challenging for many decision makers who often have limited expertise and resources to select which projects to support.In this paper we first describe a novel framework for assessing the wider benefits that could come from deploying energy storage using Multi-Attribute Value Theory (MAVT), a form of Multi-Criteria Decision Analysis. We then use the framework to assess six potential energy storage projects through a combination of technical analysis and stakeholder input in the county of Cornwall in the UK: a region that has good solar and wind resource with relatively low demand and constrained network infrastructure. The projects assessed were: power to gas, a distributed battery system, battery storage integrated with solar PV and demand from Cornwall Airport Newquay, liquid air energy storage, battery storage integrated with wave energy, and thermal energy storage at a new residential development.We conclude that MAVT can provide a straightforward and user-friendly approach, which can be easily used by decision makers for assessing energy storage projects across a range of criteria and promoting engagement with stakeholders. This approach also allows the subjectivity of decision-making, a potential limitation, to be explored through a sensitivity analysis. The use of MAVT can lead to important insights for the development of energy systems, which in this study included the importance of local priorities to decision-making.In this case, battery storage with PV and demand from Cornwall Airport Newquay was the top-ranking project, performing well across a range of attributes including the maturity of the technology, its ability to defer grid upgrades and economic viability.

Multiple criteria decision analysis for sanitation selection in South African municipalities

A multiple criteria decision analysis (MCDA) was developed for the selection of sanitation systems. This decision support system was aimed at assisting municipal engineers to design and implement sustainable solutions to meet a municipality’s obligation to provide free basic sanitation (FBS). Multi-attribute value theory (MAVT) was selected as the method most suited to the problem under consideration. Criteria which determine the sustainability of sanitation were selected from the literature and a spreadsheet-based MCDA with stakeholder and expert user interfaces was developed. Stakeholders determine the weighting of each indicator and expert users determine the values to be entered for the alternatives against each indicator. The partial values are aggregated using a weighted sum function. Research carried out into the implementation of FBS by the eThekwini Municipality that includes the city of Durban was analysed. This informed the allocation of indicator values to the sanitation alternatives under consideration: ventilated improved pit latrines (VIPs) and urine diversion dehydrating toilets (UDDTs). An innovative scenario analysis method was used to determine the effect of different weightings and/or values, representing changes in stakeholder involvement, resource recovery and political support for ecological sanitation. The MCDA was found to provide a guiding framework for municipal engineers in their efforts to implement sustainable sanitation. The process of deriving values for the MCDA is likely to prove even more useful than the overall value scores of the options under consideration.

A flexible multicriteria decision-making methodology to support the strategic management of Science, Technology and Innovation research funding programs

Research funding programs are a policy instrument utilized by governments to influence the innovation process. They are usually elaborated, launched and managed by research funding agencies. In order to select the most adequate research projects, agencies often rely on the peer review process.This paper introduces a methodology to support funding decisions based on the peer review process. The methodology involves the use of a multicriteria decision model to support the assessment, evaluation, prioritization and selection of applications, under a multi-step decision-making process, which fits into a strategic management cycle within the agency. The Multiattribute Value Theory, being considered under a Value Focused Thinking approach, provides a basis for the construction of the multicriteria decision model. The good practices in peer review and also a logical framework for program management are considered by the methodology.A pilot study, presented in the paper, involved a retrospective implementation of a peer review process in the context of a program launched by the Ministry for Science, Technology, Innovations and Communications and the National Council of Technological and Scientific Development, in Brazil. The methodology allowed a clear distinction of roles. The agency staff in the role of decision-makers was responsible for making value judgments on behalf of the agency. The experts, in the role of committee members and ad hoc reviewers, contributed with their expertise by providing objective assessments. Such assessments served as a basis for evaluating the applications, characterizing the possible portfolios, and can be considered as data in future program evaluation studies.

Evaluating the Benefits of New Drugs in Health Technology Assessment Using Multiple Criteria Decision Analysis: A Case Study on Metastatic Prostate Cancer With the Dental and Pharmaceuticals Benefits Agency (TLV) in Sweden.

Background. Multiple criteria decision analysis (MCDA) has been identified as a prospective methodology for assisting decision makers in evaluating the benefits of new medicines in health technology assessment (HTA); however, limited empirical evidence exists from real-world applications. Objective. To test in practice a recently developed MCDA methodological framework for HTA, the Advance Value Framework, in a proof-of-concept case study with decision makers. Methods. A multi-attribute value theory methodology was adopted applying the MACBETH questioning protocol through a facilitated decision-analysis modelling approach as part of a decision conference with four experts. Settings. The remit of the Swedish Dental and Pharmaceutical Benefits Agency (Tandvårds- och läkemedelsförmånsverket [TLV]) was adopted but in addition supplementary value dimensions were considered. Patients. Metastatic castrate-resistant prostate cancer patients were considered having received prior chemotherapy. Interventions. Abiraterone, cabazitaxel, and enzalutamide were evaluated as third-line treatments. Measurements. Participants’ value preferences were elicited involving criteria selection, options scoring, criteria weighting, and their aggregation. Results. Eight criteria attributes were finally included in the model relating to therapeutic impact, safety profile, socioeconomic impact, and innovation level with relative importance weights 44.5%, 33.3%, 14.8%, and 7.4% per cluster, respectively. Enzalutamide scored the highest overall weighted preference value score, followed by abiraterone and cabazitaxel. Dividing treatments’ overall weighted preference value scores by their costs derived “costs per unit of value” for ranking the treatments based on value-for-money grounds. Limitations. Study limitations included lack of comparative clinical effects across treatments and the small sample of participants. Conclusion. The Advance Value Framework has the prospects of facilitating the evaluation process in HTA and health care decision making; additional research is recommended to address technical challenges and optimize the use of MCDA for policy making.

Decision Support Tool Selection for Eco-Design Integration into the Simultaneous Design of Product and its Supply Chain

In the simultaneous design of product and its supply chain (SDPSC), the main criteria that is usually used to choose a product design is product cost since it is assumed that up to 70% of product cost is determined during the design phase. However, some researches recognise that product design decisions also affect the environmental impact of the product throughout its supply chain. Consequently, merging eco-design tools with the joint DPSC can develop a better understanding of the product and its environmental interactions to achieve green product development. In this paper, we present a literature review dealing with environmental principles’ integration into the SDPSC, then we investigate tools for green product design selection using multi-criteria decision making (MCDM). We compare suitability of three selected MCDM methods, namely Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE), and Multi-Attribute Value Theory (MAVT). Two case studies were selected from literature, and a sensitivity analysis is applied for each selected method. Results suggest that although all methods are convenient and can be used in practice, TOPSIS method was more stable towards weighting changes.

A Hospital Bed Allocation Hybrid Model Based on Situation Awareness.

Bed management is an important area of planning and control for hospitals, as it has the important role of maintaining the balance between patients from the emergency department, patients who have elective surgery or scheduled treatment, and patients who are discharged from the hospital, while maintaining high bed occupancy rates. Effective management of these resources has always been a challenge for managers. In the 1980s and 1990s, thousands of patients had operations canceled due to nonmedical reasons. Due to the constant uncertainty experienced by hospitals today, use of the cognitive model known as situation awareness has been increasing in healthcare. Situation awareness seeks to understand environmental context to design the future, using artificial intelligence techniques. In this context, this article contributes the use of situation awareness in bed management using a hybrid system that combines known techniques of artificial neural networks and multiattribute value theory for decision-making by automating the process of bed allocation. The system was evaluated in a hospital in Porto Alegre, Brazil, yielding a result of 93.5% similarity between the beds determined by the proposed model and those chosen by the hospital manager.

Container Port Selection in West Africa: A Multi-Criteria Decision Analysis

The West Africa gross domestic product is expected to grow and port expansion projects will increase capacity by over 12 million TEUs (Twenty-Foot Equivalent Units) by 2020. With the economic potential that the region offers and the steady growth of container traffic, the port selection decision by shipping lines is complex because the region has a poor shipping infrastructure and political instability that impact transportation security supply chain services. This research applies a multi-attribute value theory (MAVT) with value-focused thinking (VFT) and alternative-focused thinking (AFT) methodologies to develop a shipping lines’ container port selection decision models for West Africa. Criteria and port alternatives from a previous published study were used in the research. The study demonstrates that a decision analysis model can be developed based on available quantitative port data rather than using data from surveys, interviews and questionnaires, as done in previous publications. In both approaches the Abidjan Port is the best option for shipping lines and the worst option is the Lagos Port. The VFT approach offers graphical displays that help decision makers understand strengths, weaknesses, tradeoffs, and improvement opportunities for each port alternative.

DETERMINING PRODUCTION AND INVENTORY PARAMETERS: AN INTEGRATED SIMULATION AND MAVT APPROACH WITH TRADEOFF ELICITATION

ABSTRACT This study puts forward a multi-attribute decision model that determines good production and inventory parameter settings in make-to-stock (MTS) environments controlled by the Conwip (constant work-in-process) method. This model uses a discrete event simulation to evaluate the performance of a system in relation to work-in-process and a finished goods inventory. Based on Multi-Attribute Value Theory (MAVT), a compromise solution is found by taking into account the decision-maker’s preferences and tradeoff judgments as to the attributes of cycle time, throughput rate, holding cost and stockout cost. A numerical application is given to illustrate the use of the proposed multi-attribute model which includes a sensitivity analysis.

Application of Multi-Criteria Decision Analysis to the Selection of Software Measures

In this research we propose the application of a multi-criteria decision analysis to make documented and transparent decisions about software measures’ selection. The Pareto’s dominance method was utilized to narrow down the initial measures’ list. The multi-attribute value theory was applied for ranking the final set of measures. As a result there was eliminated about 40% of the initial measures and the final measures’ list was ranked.

Assessing urban quality: a proposal for a MCDA evaluation framework

The paper focuses on the assessment of urban design quality and sustainable urban spaces. In particular, the study is concentrated on the evaluation of urban quality provided by a good design of open spaces, including green areas, walkable areas and squares. In fact, despite the advancement of research during the past two decades and empirical evidence about the relationship among quality of life, quality of open spaces and urban sustainability, there is still a lack of studies on urban quality assessment. This paper brings forward a multidimensional methodology for assessing the quality of open spaces. More precisely, the contribution of this research is the proposal of a multidimensional and multi-methodological framework for assigning a numerical score to the quality of open spaces. The Multi-Attribute Value Theory has been used for addressing the problem under investigation with the aim of defining a synthetic index for the measurement of the urban quality of open spaces on the basis of different attributes, namely (a) accessibility; (b) liveability; (c) vitality and (d) identity. The methodology has been applied on a recently renovated district in the city of Milan, Italy. The proposed multi-methodological framework provides a robust basis for running different kind of analysis and for supporting policy and investment decisions both in the private and in the public sector.

Stakeholder interviews with two MAVT preference elicitation philosophies in a Swiss water infrastructure decision: Aggregation using SWING-weighting and disaggregation using UTAGMS

We used two types of preference elicitation methods based on multi-attribute value theory (MAVT) for a wastewater infrastructure decision in Switzerland. We aimed to register the implementation impacts of two preference elicitation philosophies (aggregation, disaggregation) in a large, real-world case and give guidance on these elicitation approaches for practitioners. We conducted two series of face-to-face interviews with the same ten. The first interview set used direct aggregation preference elicitation methods, which decomposed an additive value model into the elicitation of weights (SMART/SWING-variant) and marginal value functions (bi-section method). In the second interview series, indirect disaggregation was used, based on UTAGMS. The weights and marginal value functions for 19 objectives were later simultaneously inferred with linear programming from pairwise comparisons of hypothetical alternatives. One aim was to design the UTAGMS comparisons for many objectives. Further, we aimed to identify differences and commonalities of the two methods concerning the elicited preferences, the MAVT evaluation results of six real-world wastewater infrastructure alternatives, and the stakeholders’ and analysts’ feedbacks. Similar best alternatives indicate convergence of the two elicitation methods. This demonstrates the applicability of the UTAGMS elicitation procedure to a very complex decision problem. However, the two elicitation methods were perceived differently by the respondents and required different effort from the analysts. For individual stakeholders, preferences were sometimes rather different between the interviews, which could be largely explained by the constructive nature of preference formation. This indicates the importance of supporting stakeholder learning in the application of MCDA.

A decision support tool for selecting the optimal sewage sludge treatment

Sewage sludge contains significant amounts of resources, such as nutrients and organic matter. At the same time, the organic contaminants (OC) found in sewage sludge are of growing concern. Consequently, in many European countries incineration is currently favored over recycling in agriculture. This study presents a Multi-Attribute Value Theory (MAVT)-based decision support tool (DST) for facilitating sludge treatment decisions. Essential decision criteria were recognized and prioritized, i.e., weighted, by experts from water utilities. Since the fate of organic contaminants was in focus, a simple scoring method was developed to take into account their environmental risks. The final DST assigns each sludge treatment method a preference score expressing its superiority compared to alternative methods.The DST was validated by testing it with data from two Finnish municipal wastewater treatment plants (WWTP). The validation results of the first case study preferred sludge pyrolysis (preference score: 0.629) to other alternatives: composting and incineration (score 0.580, and 0.484 respectively). The preference scores were influenced by WWTP dependent factors, i.e., the operating environment and the weighting of the criteria. A lack of data emerged as the main practical limitation. Therefore, not all of the relevant criteria could be included in the value tree. More data are needed on the effects of treatment methods on the availability of nutrients, the quality of organic matter and sludge-borne OCs. Despite these shortcomings, the DST proved useful and adaptable in decision-making. It can also help achieve a more transparent, understandable and comprehensive decision-making process.

Multiple criteria decision analysis in the context of health technology assessment: a simulation exercise on metastatic colorectal cancer with multiple stakeholders in the English setting

BackgroundMultiple criteria decision analysis (MCDA) has appeared as a methodology to address limitations of economic evaluation in health technology assessment (HTA), however there are limited empirical evidence from real world applications. The aim of this study is to test in practice a recently developed MCDA methodological framework known as Advance Value Framework (AVF) through a proof-of-concept case study engaging multiple stakeholders.MethodsA multi-attribute value theory methodological process was adopted involving problem structuring, model building, model assessment and model appraisal phases. A facilitated decision analysis modelling approach was used as part of a decision conference with thirteen participants. An expanded scope of the National Institute for Health and Care Excellence (NICE) remit acted as the study setting with the use of supplementary value concerns. Second-line biological treatments were evaluated for metastatic colorectal cancer (mCRC) patients having received prior chemotherapy, including cetuximab monotherapy, panitumumab monotherapy and aflibercept in combination with FOLFIRI chemotherapy. Initially 18 criteria attributes were considered spanning four value domains relating to therapeutic impact, safety profile, innovation level and socioeconomic impact.ResultsNine criteria attributes were finally included. Cetuximab scored the highest overall weighted preference value score of 45.7 out of 100, followed by panitumumab with 42.3, and aflibercept plus FOLFIRI with 14.4. The relative weights of the two most important criteria (overall survival and Grade 4 adverse events) added up to more than the relative weight of all other criteria together (52.1%). Main methodological limitation was the lack of comparative clinical effects across treatments and challenges included the selection of “lower” and “higher” reference levels on criteria attributes, eliciting preferences across attributes where participants had less experience, and ensuring that all attributes possess the right decision theory properties.ConclusionsThis first application of AVF produced transparent rankings for three mCRC treatments based on their value, by assessing an explicit set of evaluation criteria while allowing for the elicitation and construction of participants’ value preferences and their trade-offs. It proved it can aid the evaluation process and value communication of the alternative treatments for the group participants. Further research is needed to optimise its use as part of policy-making.

The EMAS-ISO standards in the quality assessment of the integrated water service

This contribution proposes a theoretical model to support the environmental assessment for the organizations aiming at implementing an EMAS-ISO auditing process in the ground of the water services industry. The model tries to combine a new theory of value – based on natural, bio-genealogical and semantic surplus – with the cycle input - output - re-input characterizing namely the most critical area of the integrated waters service, the waste water treatment plants. A multidimensional pattern based on the Multi-Attribute Value Theory has been assumed as an effective operational framework connecting the contents of the treatment process, as defined by the scientific and technological tools supporting the judges of fact , and the issues of sustainability, supporting the value judgements .

Multiple Criteria Decision Analysis (MCDA) for evaluating new medicines in Health Technology Assessment and beyond: The Advance Value Framework

Escalating drug prices have catalysed the generation of numerous “value frameworks” with the aim of informing payers, clinicians and patients on the assessment and appraisal process of new medicines for the purpose of coverage and treatment selection decisions. Although this is an important step towards a more inclusive Value Based Assessment (VBA) approach, aspects of these frameworks are based on weak methodologies and could potentially result in misleading recommendations or decisions.In this paper, a Multiple Criteria Decision Analysis (MCDA) methodological process, based on Multi Attribute Value Theory (MAVT), is adopted for building a multi-criteria evaluation model. A five-stage model-building process is followed, using a top-down “value-focused thinking” approach, involving literature reviews and expert consultations. A generic value tree is structured capturing decision-makers' concerns for assessing the value of new medicines in the context of Health Technology Assessment (HTA) and in alignment with decision theory.The resulting value tree (Advance Value Tree) consists of three levels of criteria (top level criteria clusters, mid-level criteria, bottom level sub-criteria or attributes) relating to five key domains that can be explicitly measured and assessed: (a) burden of disease, (b) therapeutic impact, (c) safety profile (d) innovation level and (e) socioeconomic impact. A number of MAVT modelling techniques are introduced for operationalising (i.e. estimating) the model, for scoring the alternative treatment options, assigning relative weights of importance to the criteria, and combining scores and weights.Overall, the combination of these MCDA modelling techniques for the elicitation and construction of value preferences across the generic value tree provides a new value framework (Advance Value Framework) enabling the comprehensive measurement of value in a structured and transparent way. Given its flexibility to meet diverse requirements and become readily adaptable across different settings, the Advance Value Framework could be offered as a decision-support tool for evaluators and payers to aid coverage and reimbursement of new medicines.

A Value-Driven Framework For The Evaluation Of Biosurveillance Systems

ObjectiveTo describe the development of an evaluation framework thatallows quantification of surveillance functions and subsequentaggregation towards an overall score for biosurveillance systemperformance.IntroductionEvaluation and strengthening of biosurveillance systems is acomplex process that involves sequential decision steps, numerousstakeholders, and requires accommodating multiple and conflictingobjectives. Biosurveillance evaluation, the initiating step towardsbiosurveillance strengthening, is a multi-dimensional decisionproblem that can be properly addressed via multi-criteria-decisionmodels.Existing evaluation frameworks tend to focus on “hard” technicalattributes (e.g. sensitivity) while ignoring other “soft” criteria(e.g. transparency) of difficult measurement and aggregation. Asa result, biosurveillance value, a multi-dimensional entity, is notproperly defined or assessed. Not addressing the entire range of criterialeads to partial evaluations that may fail to convene sufficient supportacross the stakeholders’ base for biosurveillance improvements.We seek to develop a generic and flexible evaluation frameworkcapable of integrating the multiple and conflicting criteria and valuesof different stakeholders, and which is sufficiently tractable to allowquantification of the value of specific biosurveillance projects towardsthe overall performance of biosurveillance systems.MethodsWe chose a Multi Attribute Value Theory model (MAVT) tosupport the development of the evaluation framework. Developmentof the model was done through online decision conferencing sessionswith expert judgement, an indispensable part of MAVT modelling,provided by surveillance experts recruited from the member pool ofthe International Society for Disease Surveillance.The surveillance functions or quality criteria that were consideredfor the framework were initially gathered from a review of theliterature with specific attention to a subset of public health qualitycriteria (1). Group discussions with the experts led to a final list offunctions, finally reviewed to comply with the properties for goodcriteria in decision models. The eleven functions were: sensitivity;timeliness; positive predictive value (PPV); transparency; versatility;multiple utility; representativeness; sustainability; advancing thefield and innovation; risk reduction; and actionable information.In addition, 24 different scenarios were developed for sensitivity,PPV, and timeliness since their values may differ with the level ofinfectiousness of the condition/event of interest, its severity andthe availability of treatment and/or prevention measures. Four orfive levels of performance were also developed for each criterion.Macbeth (Measuring Attractiveness by a Category-Based EvaluationTechnique) tables were used to elicit values of different levels ofperformance from the experts using qualitative pairwise comparisonsand then convert them into numerical values.ResultsTo date, two criteria, sensitivity and transparency, have beenassessed by more than one expert working on the same scenario.Value functions were generated for each criterion and scenario bycalculating the median of the different values produced by the experts.For both sensitivity and transparency, value functions were mostlylinear, indicating similar preferences between levels of performance.However, for some scenarios, experts allocated greater value toincreases at the higher end of the performance level distribution.ConclusionsAt the time of writing new elicitation sessions are planned toconclude the model. Next, we will apply swing weights to supportthe trade-offs between the different criteria. We will present thebaseline model elicitated from the experts and demonstrate howto apply portfolio decision analysis to assess overall performanceof biosurveillance systems according to the specific needs ofstakeholders and in conjunction with macro-epidemiological models.

A natural language generation approach to support understanding and traceability of multi-dimensional preferential sensitivity analysis in multi-criteria decision making

Multi-Criteria Decision Analysis (MCDA) enables decision makers (DM) and decision analysts (DA) to analyse and understand decision situations in a structured and formalised way. With the increasing complexity of decision support systems (DSSs), it becomes challenging for both expert and novice users to understand and interpret the model results. Natural language generation (NLG) techniques are used in various DSSs to cope with this challenge as they reduce the cognitive effort to achieve understanding of decision situations. However, NLG techniques in MCDA have so far mainly been developed for deterministic decision situations or one-dimensional sensitivity analyses. In this paper, a concept for the generation of textual explanations for a multi-dimensional preferential sensitivity analysis in MCDA is developed. The key contribution is a NLG approach that provides detailed explanations of the implications of preferential uncertainties in Multi-Attribute Value Theory (MAVT). It generates a report that assesses the influences of simultaneous or separate variations of inter-criteria and intra-criteria preferential parameters determined within the decision analysis. We explore the added value of the natural language report in an online survey. Our results show that the NLG approach is particularly beneficial for difficult interpretational tasks.

Accounting for Uncertainty in Value Judgements when Applying Multi-Attribute Value Theory

In environmental decisions, analysts commonly face substantial uncertainties around stakeholders’ values judgments. Multi-Attribute Value Theory (MAVT), a family of multi-criteria decision analysis techniques, is applied in participative settings to articulate stakeholders’ values in decision-making. In MAVT, value judgments represent the intensity of individuals’ preferences in a set of objectives, which are operationalized as scaling factors or weights. Different sets of weights may express variation in people’s preferences or value judgments. Unfortunately, there are still important methodological gaps regarding how to incorporate uncertainty and the substantial variation commonly encountered in stakeholders’ preferences. This article presents a model of uncertainty that encompasses the dispersion of value judgments in MAVT. To achieve this goal, we draw on info-gap theory, which provides a mathematically grounded method for exploring sensitivity to preference weights when there are relatively high levels of uncertainties. We experimentally tested the uncertainty model in an environmental decision problem. We found that MAVT can use info-gap analysis to deal with multiple value judgments, avoiding exclusive reliance on nominal expected values to inform decisions. We explored a mechanism to explicitly consider the trade-offs between the performance of alternatives and the level of uncertainty that in any specified context a decision maker is willing to accept. Findings emphasize the potential of MAVT to support environmental management decisions, particularly in situations where multiple stakeholders and their contested value judgments have to be considered simultaneously to explore uncertainties around value trade-offs.

Life cycle, PESTLE and Multi-Criteria Decision Analysis of CCS process alternatives

CO2 is the primary greenhouse gas (GHG) due to its large quantity of anthropogenic emission. In this work the amine based carbon capture process and the CO2 storage, called Carbon Capture and Storage (CCS) is analysed from different viewpoints. PESTLE (Political, Economic, Social, Technological, Legal and Environmental) analysis of the CCS alternatives (Fossil based, Improved process, Renewable based) is investigated in detail and the alternatives are also compared with the uncontrolled CO2 release using Life Cycle Assessment (LCA) methods. Life cycle inventory data is set up and analysed with four life cycle impact assessment methods. In order to conclude the comparison of CCS and the uncontrolled release of CO2 a Multi-Criteria Decision Analysis (MCDA) is also applied with Multi Attribute Value Theory (MAVT) method. Our results show that applying process improvement and renewable energy sources (e.g., biogas) for absorbent regeneration result in a CCS technology of much smaller environmental and social impacts, and therefore the CCS technology becomes more favorable than the uncontrolled release.

A Multi Attribute Value Theory approach to rank association rules for leveraging better business decision making

Market Basket Analysis or Association Rule Mining (ARM) is an approach to discover the purchase patterns of the customers by extracting and analyzing the basket of items which sell together. Businesses are also keen to discover those rules which can generate more profits. These profitable purchase patterns of customers once identified can lead to better product assortment decision making for businesses. Better Product Assortment decisions can surely be a competitive advantage for businesses in terms of customer satisfaction and profit generation. The concepts of support and confidence in the association rules help to extract the rules with frequent and reliable co-occurrences of the items in customers’ purchases. The profitable rules can be assessed using the domain-related measures such as item set value and the cross-selling profit associated with the association rules. We propose a ranking mechanism to combine the different criteria of Confidence, Support, Item Set Value and Cross-Selling Profit to get an overall interestingness measure; using Multi-Attribute Value Theory (MAVT) approach; which in turn uses DIVIZ as the implementation tool. These association rules can be used as a leverage for the marketing activities like cross-selling promotions, shelf placement etc. and other crucial decisions like product assortment selection.