Integrating multicriteria decision analysis and scenario planning : review and extension

Scenario planning and multiple criteria decision analysis (MCDA) are two key management science tools used in strategic planning. In this paper, we explore the integration of these two approaches in a coherent manner, recognizing that each adds value to the implementation of the other. Various approaches that have been adopted for such integration are reviewed, with a primary focus on the process of constructing preferences both within and between scenarios. Biases that may be introduced by inappropriate assumptions during such processes are identified, and used to motivate a framework for integrating MCDA and scenario thinking, based on applying MCDA concepts across a range of "metacriteria" (combinations of scenarios and primary criteria). Within this framework, preferences according to each primary criterion can be expressed in the context of different scenarios. The paper concludes with a hypothetical but non-trivial example of agricultural policy planning in a developing country

Analysis of the potentials of multi criteria decision analysis methods to conduct sustainability assessment

Sustainability assessments require the management of a wide variety of information types, parameters and uncertainties. Multi criteria decision analysis (MCDA) has been regarded as a suitable set of methods to perform sustainability evaluations as a result of its flexibility and the possibility of facilitating the dialogue between stakeholders, analysts and scientists. However, it has been reported that researchers do not usually properly define the reasons for choosing a certain MCDA method instead of another. Familiarity and affinity with a certain approach seem to be the drivers for the choice of a certain procedure. This review paper presents the performance of five MCDA methods (i.e. MAUT, AHP, PROMETHEE, ELECTRE and DRSA) in respect to ten crucial criteria that sustainability assessments tools should satisfy, among which are a life cycle perspective, thresholds and uncertainty management, software support and ease of use. The review shows that MAUT and AHP are fairly simple to understand and have good software support, but they are cognitively demanding for the decision makers, and can only embrace a weak sustainability perspective as trade-offs are the norm. Mixed information and uncertainty can be managed by all the methods, while robust results can only be obtained with MAUT. ELECTRE, PROMETHEE and DRSA are non-compensatory approaches which consent to use a strong sustainability concept, accept a variety of thresholds, but suffer from rank reversal. DRSA is less demanding in terms of preference elicitation, is very easy to understand and provides a straightforward set of decision rules expressed in the form of elementary “if … then …” conditions. Dedicated software is available for all the approaches with a medium to wide range of results capability representation. DRSA emerges as the easiest method, followed by AHP, PROMETHEE and MAUT, while ELECTRE is regarded as fairly difficult. Overall, the analysis has shown that most of the requirements are satisfied by the MCDA methods (although to different extents) with the exclusion of management of mixed data types and adoption of life cycle perspective which are covered by all the considered approaches

Weighting factor elicitation for sustainability assessment of energy technologies

In this paper, an approach for sustainability assessment of innovative energy technologies is expanded by multi-criteria decision analysis (MCDA) methods to aggregate indicator results and support decision-making. One of the most important steps for MCDA is to determine weighting factors for individual indicators. Thus, a workshop was performed to elicit weighting factors for sustainability assessments of energy technologies from developers of such technologies and energy system modellers from academia. These stakeholders expressed their preferences with respect to sustainability criteria using the Simple Multi Attribute Rating Technique (SMART). A triple bottom line approach of sustainable development was used as the basis for the aggregation of indicator results. This approach is based on Life Cycle Costing, Life Cycle Assessment and social indicators. Obtained weighting factors were applied to an integrative sustainability assessment with the aggregation method Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE). Hydrogen-based mobility as an important technology to foster decarbonization in the transport sector is used as a case study for the application of the derived weighting factors. A conventional vehicle, powered by fossil fuel, is compared with a fuel cell electric vehicle (FCEV) for the year 2050. Different options (pipeline, compressed gaseous hydrogen, liquid hydrogen, liquid organic hydrogen carrier) are discussed for the supply of hydrogen. The results for this weighting factor set are compared with an equal weighting scenario of the three sustainability dimensions and indicators within one sustainability dimension. The FCEV, using pipelines for hydrogen supply, came out first in the assessment as well as in all sensitivity analyses

A comparison of five multi attribute utility instruments

Abstract This paper presents the results of the validation study carried out to evaluate the Assessment of Quality of Life (AQoL) Instrument for the measurement of health related quality of life and utility. It involves, inter alia, the largest comparison of utility instruments that has been carried out to date. The five instruments included in the study are the AQoL, the Canadian HUI III, the Finnish 15D, the EuroQoL (EQ5D) and the SF36 with UK utility weights as quantified by Brazier (1998). The paper compares: (i) the absolute utility score obtained by different sub-populations; (ii) instrument sensitivity; (iii) the incremental differences in utility between different health states; (iv) the structural properties of descriptive systems; and (v) a limited comparison with a Time Trade-Off (TTO) assessment of own health by individuals. Using these criteria the AQoL performs very well. Its predicted utilities are very similar to those obtained from the HUI. There is evidence that the AQoL has greater sensitivity to health states than other instruments and its psychometric properties, as usually judged, are excellent. Despite this, it is concluded that, at present, no single MAU system can claim to be the gold standard and that researchers should select an instrument that is sensitive to the health states which they are investigating and that caution should be exercised in treating any of the instrument results as representing a utility score which truly represents a trade-off between life and health related quality of life

A framework for the selection of the right nuclear power plant

Civil nuclear reactors are used for the production of electrical energy. In the nuclear industry vendors propose several nuclear reactor designs with a size from 35–45 MWe up to 1600–1700 MWe. The choice of the right design is a multidimensional problem since a utility has to include not only financial factors as levelised cost of electricity (LCOE) and internal rate of return (IRR), but also the so called “external factors” like the required spinning reserve, the impact on local industry and the social acceptability. Therefore it is necessary to balance advantages and disadvantages of each design during the entire life cycle of the plant, usually 40–60 years. In the scientific literature there are several techniques for solving this multidimensional problem. Unfortunately it does not seem possible to apply these methodologies as they are, since the problem is too complex and it is difficult to provide consistent and trustworthy expert judgments. This paper fills the gap, proposing a two-step framework to choosing the best nuclear reactor at the pre-feasibility study phase. The paper shows in detail how to use the methodology, comparing the choice of a small-medium reactor (SMR) with a large reactor (LR), characterised, according to the International Atomic Energy Agency (2006), by an electrical output respectively lower and higher than 700 MWe

Decision support model for the selection of asphalt wearing courses in highly trafficked roads

The suitable choice of the materials forming the wearing course of highly trafficked roads is a delicate task because of their direct interaction with vehicles. Furthermore, modern roads must be planned according to sustainable development goals, which is complex because some of these might be in conflict. Under this premise, this paper develops a multi-criteria decision support model based on the analytic hierarchy process and the technique for order of preference by similarity to ideal solution to facilitate the selection of wearing courses in European countries. Variables were modelled using either fuzzy logic or Monte Carlo methods, depending on their nature. The views of a panel of experts on the problem were collected and processed using the generalized reduced gradient algorithm and a distance-based aggregation approach. The results showed a clear preponderance by stone mastic asphalt over the remaining alternatives in different scenarios evaluated through sensitivity analysis. The research leading to these results was framed in the European FP7 Project DURABROADS (No. 605404).The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under Grant Agreement No. 605404

The design of aircraft using the decision support problem technique

The Decision Support Problem Technique for unified design, manufacturing and maintenance is being developed at the Systems Design Laboratory at the University of Houston. This involves the development of a domain-independent method (and the associated software) that can be used to process domain-dependent information and thereby provide support for human judgment. In a computer assisted environment, this support is provided in the form of optimal solutions to Decision Support Problems