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Decision Analysis and Behavioral Research

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... The aim of this study is to develop a new fuzzy decision-making approach for evaluation of e-waste management scenarios. The developed approach is based on the SECA (Simultaneous Evaluation of Criteria and Alternatives) method [17], fuzzy sets, α-cut intervals and SMART (Simple Multi-Attribute Rating Technique) [18]. SECA is an efficient and relatively new MCDM method that has been applied to several real-world evaluation problems in different fields of study including battery electric vehicles [19], sustainable manufacturing [20], system resilience analysis [21], hybrid machining processes [22], renewable energy [23], fuel-switching [24], high-rise wall buildings [25], cities smartness [26] and dynamic resource allocation [27]. ...
... The results of the study showed that design requirements to reduce greenhouse gases, air emissions, volatile organic compounds and carbon footprint are more important than the other factors for eco-efficiency in an e-product supply chain. 18 Fetanat, et al. [46] 2021 ANP, DEMATEL and MULTI-MOORA ...
... Simple Multi-Attribute Rating Technique or SMART is a classic MCDM method proposed by Von Winterfeldt and Edwards [18]. It can be applied to the determination of subjective criteria weights. ...
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Article
The process of production, consumption, and final disposal of electrical and electronic equipment usually leads to harmful waste to the environment called e-waste. Eliminating and decreasing this type of waste could be considered as an essential goal for many enterprises working toward sustainable management systems. In this paper, we aim at introducing a new methodology for evaluation of sustainable e-waste management scenarios. The evaluation is defined as an MCDM (Multi-Criteria Decision-Making) problem, and the scenarios are the alternatives of the problem that need to be evaluated with respect to several sustainability criteria. An extended fuzzy SECA (Simultaneous Evaluation of Criteria and Alternatives) integrated with SMART (Simple Multi-Attribute Rating Technique), named F-SECA, is proposed to deal with the evaluation process. The α-cut approach is used to consider different levels of uncertainty and obtain interval values for assessment of criteria and alternatives. The proposed methodology helps us to make the evaluation with incorporation of subjective and objective data, opinions of multiple experts and uncertainty of information. We applied the methodology to evaluate sustainable e-waste management scenarios in a case. Through comparative and sensitivity analyses, the paper shows that the proposed methodology is efficient and gives reliable results.
... Various expression modes are available for comparing different criteria as direct methods: direct rating (Bottomley, Doyle, & Green, 2000), swing weighting (Von Winterfeldt & Edwards, 1993), the simple multi-attribute rating technique (SMART) (Edwards, 1977), pairwise comparison methods such as the AHP (Saaty, 1977); and as indirect methods: decomposition methods such as discrete choice experiments (DCE) (de Bekker-Grob, , bisection and difference methods (Von Winterfeldt & Edwards, 1993) or the measuring attractiveness by a categoricalbased evaluation technique (MACBETH) (Ryan, Gerard, & Currie, 2012), conjoint analysis (Green, Krieger, & Wind, 2001), and the potentially all pairwise rankings of all possible alternatives (PAPRIKA) methodology (Hansen & Ombler, 2008). Each mode has its advantages and disadvantages, with an important influence on the final result (Table 1). ...
... Various expression modes are available for comparing different criteria as direct methods: direct rating (Bottomley, Doyle, & Green, 2000), swing weighting (Von Winterfeldt & Edwards, 1993), the simple multi-attribute rating technique (SMART) (Edwards, 1977), pairwise comparison methods such as the AHP (Saaty, 1977); and as indirect methods: decomposition methods such as discrete choice experiments (DCE) (de Bekker-Grob, , bisection and difference methods (Von Winterfeldt & Edwards, 1993) or the measuring attractiveness by a categoricalbased evaluation technique (MACBETH) (Ryan, Gerard, & Currie, 2012), conjoint analysis (Green, Krieger, & Wind, 2001), and the potentially all pairwise rankings of all possible alternatives (PAPRIKA) methodology (Hansen & Ombler, 2008). Each mode has its advantages and disadvantages, with an important influence on the final result (Table 1). ...
... Von Winterfeldt and Edwards (1993) MACBETH It is a scoring method based on the additive value model. Questions compare two options at a time (on each criterion or amongst criteria), asking the responder for only a qualitative preference differences judgement using seven semantic categories. ...
Chapter
Industrial activities and human impacts are responsible for severe environmental problems to the ecosystems. Decision-making in environmental projects can be complex, principally due to the multi-disciplinarily and the trade-offs between the areas involved, such as socio-political, environmental, and economic factors. Additionally, in socially relevant situations, the decision-maker has to explain to the stakeholders why some decisions are adopted compared to others. The multi-criteria-decision-making (MCDM) method offers a scientifically sound decision framework, which can provide for a comprehensive and transparent basis for sustainability assessments. This chapter aims at highlighting the main steps, the advantages, and the risks of developing a MCDM framework for the resolution of complex environmental problems. Further information about software applications, data requirements, scale of the analyses, target audience, and future trends are also provided.
... In the literature, we can find several techniques to obtain information regarding the DM's preferences to construct value functions in agreement with his/her answers (Goodwin & Wright, 1998;von Winterfeldt & Edwards, 1986), but the questions must be structured for each specific context. Table 1 summarizes the performance levels corresponding to values 0.25, 0.5, and 0.75 (resulting from this type of dialogue), such that an improvement from level 0 to level 0.25 corresponds to the same value as an improvement from level 0.25 to 0.5, etc. ...
... On the contrary, they are heavily dependent on the performances chosen to represent levels 0 and 1 on the value scale. In MCDA, several valid protocols are known to elicit weight restrictions derived from the DM's preferences (Goodwin & Wright, 1998;von Winterfeldt & Edwards, 1986). In this case, the swing technique is simple and clear for the DM. ...
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Chapter
This paper is aimed at presenting the Python implementation of the Value-Based Data Envelopment Analysis (VBDEA) method, which was designed to evaluate the efficiency of decision-making units (DMUs). This methodological framework explores the links between data envelopment analysis (DEA) and multi-criteria decision analysis (MCDA) and proposes a new perspective on the use of the additive DEA model using concepts from the multi-attribute value theory (MAVT). One of the major strengths of VBDEA over typical DEA methodologies is that it offers information on the main reasons behind DMUs’ (in)efficiency. Additionally, this approach allows straightforwardly ranking of efficient and inefficient DMUs, since it relies on a super-efficiency model. Because of the use of value functions, besides allowing the incorporation of the decision-maker (DM)’s preferences, this methodology easily handles negative or null data. In this context, we illustrate the Python implementation of the method by reproducing the main results obtained by (Gouveia et al., Or Spectrum 38:743–767, 2016), when these authors evaluated the performance of 12 health units in a Portuguese region incorporating management preferences given by real DMs.
... Based on the fact that each sensor type suggested to the customer may have several instances, thus we utilize a weighted utility function to rank these available instances based on their utility to the customer. This function is based on the Multi-Attribute Utility Theory (MAUT) approach [66]. To calculate the utility of available sensor type instances, it is important to have prior knowledge about: (i) Contributions of sensor instances in a set of utility dimensions/attributes. ...
... Based on this information, we applied the following weighted utility function [66] (cf. Equation (1)) to rank available sensor type instances. ...
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Nowadays, manufacturers are shifting from a traditional product-centric business paradigm to a service-centric one by offering products that are accompanied by services, which is known as Product-Service Systems (PSSs). PSS customization entails configuring products with varying degrees of differentiation to meet the needs of various customers. This is combined with service customization, in which configured products are expanded by customers to include smart IoT devices (e.g., sensors) to improve product usage and facilitate the transition to smart connected products. The concept of PSS customization is gaining significant interest; however, there are still numerous challenges that must be addressed when designing and offering customized PSSs, such as choosing the optimum types of sensors to install on products and their adequate locations during the service customization process. In this paper, we propose a data warehouse-based recommender system that collects and analyzes large volumes of product usage data from similar products to the product that the customer needs to customize by adding IoT smart devices. The analysis of these data helps in identifying the most critical parts with the highest number of incidents and the causes of those incidents. As a result, sensor types are determined and recommended to the customer based on the causes of these incidents. The utility and applicability of the proposed RS have been demonstrated through its application in a case study that considers the rotary spindle units of a CNC milling machine.
... In case of mutual independence of preferences between attributes, it is possible to proceed with a standard additive aggregation. Therefore, the overall value of an alternative is given by the sum of the products of all attributes for the relative weights [141]: ...
... Many approaches have been proposed in the literature to define value functions [144]. In particular, the following techniques have been proposed: direct rating; "curve fitting"; bisection; standard differences; parameter estimation and semantic judgments [141]. ...
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This contribution proposes an inter-scalar and multi-polar analysis evaluation model of the territory of the Enna district, aimed at providing a robust axiological representation of the salient aspects of the general issue of internal areas, and therefore of the set of criticalities affecting them from the perspective of the human and urban capital they express. In the prospect of investigating the relations between urban and life quality – corresponding to the “city effect” – in the territorial context of each of the 20 municipalities of the Enna district, a hierarchical descriptive-valuation model was created, which coordinates a relevant amount of information units (data) and the corresponding attributes, indicators and indices that have been turned in aggregate value judgments attributed to each administrative land unit, from the perspectives of the criteria referred to as the main forms of the territorial capital. This is a multi-dimensional valuation model based on the Multi-Attribute Value Theory. Each survey and processing is mapped with different levels of detail at the scale of municipalities, census sections and cadastral land units. The outcome of this complex process of analysis and assessment provides multiple comparisons, revealing unexpected and sometimes counter-intuitive aspects in several municipalities, some of which are characterised by innovative prospects and opportunities for redevelopment of their historic centers. Correlations between information units at the different levels of the dendrogram have also indicated interesting trends and attitudes, whose comparisons can address territorial policies on both a local and provincial scale. Furthermore, the focus on the “cities network” is here assumed and proposed as the privileged point of observation of territory and the related aspects of the quality of life.
... The Simple Multi Attribute Rating Technique (SMART) [71,72] is an approach for determining weighting factors indirectly through systematic comparison of attributes against the one deemed to be the least important. SMART consists of two general activities: (1) rank order attributes according to the relative importance overall, and (2) select either the least or most important attribute as a reference point and assess how much more or less important the other attributes are with respect to the reference point. ...
... The Swing Weighting Technique [72] is an approach for determining weighting factors indirectly through systematic comparison of attributes against the one deemed to be the most important. SWING consists of two general activities: (1) rank order attributes according to the relative importance of incremental changes in attribute values considering the full range of possibilities; (2) select either the least or most important attribute as a reference point and assess how much more or less important the other attributes are with respect to the reference point. ...
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Article
Computational models and simulations often involve representations of decision-making processes. Numerous methods exist for representing decision-making at varied resolution levels based on the objectives of the simulation and the desired level of fidelity for validation. Decision making relies on the type of decision and the criteria that is appropriate for making the decision; therefore, decision makers can reach unique decisions that meet their own needs given the same information. Accounting for personalized weighting scales can help to reflect a more realistic state for a modeled system. To this end, this article reviews and summarizes eight multi-criteria decision analysis (MCDA) techniques that serve as options for reaching unique decisions based on personally and individually ranked criteria. These techniques are organized into a taxonomy of ratio assignment and approximate techniques, and the strengths and limitations of each are explored. We compare these techniques potential uses across the Agent-Based Modeling (ABM), System Dynamics (SD), and Discrete Event Simulation (DES) modeling paradigms to inform current researchers, students, and practitioners on the state-of-the-art and to enable new researchers to utilize methods for modeling multi-criteria decisions.
... In the process of management and safety risk decision making in coal mine organizations, decision makers are influenced by insufficient experience, inadequate implementation of responsibilities, and limited life value assessment and deliberately make optimistic predictions about preferred actions or results, resulting in poor outcomes; it is difficult to correct this motivational bias. Cognitive bias is a systematic discrepancy between the "correct" answer to a judgmental task, given by a formal normative rule, and the decisionmaker's or expert's actual answer [45]. Analyzing a vast number of historical cases reveals that cognitive biases are prevalent in the course of accidents. ...
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Background and Objectives: Coal mine injuries commonly occur, affecting both the safety and health of miners, and the normal operation of the coal mine. Accordingly, this study aimed to explore the regularity of injury and injury-related risk factors in coal mines in China so as to establish a scientific basis for reducing the incidence and promoting the prevention and control of injuries. Methods: A meta-analysis of casualty cases and injury-related risk factors from 1956 to 2017 in China was conducted utilizing data from six databases, including CNKI, Web of Science, PubMed, Medline, Embase, and Wanfang data. Summary estimates were obtained using random effects models. Results: There were statistically significant variations in coal mine accident types, types of work, injury sites, age, experience, months, and shifts (p < 0.001). Eight types of accidents were susceptible to the risk of injury, and the greatest risk was presented by roof-related accidents (odds ratio (OR) = 0.46, 95% confidence interval (CI) = 0.32–0.6). Coal miners and drillers were at a greater risk of injury (OR = 0.39, 95% CI = 0.35–0.44; OR = 0.22, 95% CI = 0.17–0.26, respectively). The extremities and the soft tissues of the skin were at the greatest risk of injury (OR = 0.44, 95% CI = 0.3–0.58; OR = 0.23, 95% CI = 0.1–0.48, respectively). Compared with other ages, miners aged 21–30 were at a greater risk of injury (21–30 years, OR = 0.45, 95% CI = 0.42–0.47; 31–40 years, OR = 0.29, 95% CI = 0.25–0.32; <20 years, OR = 0.13, 95% CI = 0.03–0.23; >40 years, OR = 0.17, 95% CI = 0.09–0.25). Compared with other miners, those with 6–10 years of experience were at a greater risk of injury (6–10 years, OR = 0.29, 95% CI = 0.25–0.32; 2–5 years, OR = 0.33, 95% CI = 0.25–0.41; <1 year, OR = 0.22, 95% CI = 0.08–0.33; >11 years, OR = 0.22, 95% CI = 0.17–0.27). During the months of July to September, the risk of injury was elevated (7–9th months, OR = 0.32, 95% CI = 0.25–0.39; 10–12th months, OR = 0.24, 95% CI = 0.16–0.31; 1st–3rd months, OR = 0.22, 95% CI = 0.16–0.28; 4–6th months, OR = 0.21, 95% CI = 0.16–0.27). In the three-shift work system, the risk of injury was higher during night shifts (22:00–06:00, OR = 0.43, 95% CI = 0.3–0.56; 14:00–22:00, OR = 0.3, 95% CI = 0.23–0.27; 06:00–14:00, OR = 0.27, 95% CI = 0.18–0.35). Conclusions: The results of this research study reveal that coal mine injuries are prevalent among coal miners. These injuries are often related to the age, experience, months of work, and the three-shift work system of miners.
... Stakeholder were interviewed individually using a multicriteria decision analysis (MCDA) (e.g., Eisenführ et al., 2010) based on a decision analysis interview (DAI) approach and Web-HIPRE software (Marttunen & Hämäläinen, 2008). The weight elicitation for attributes of the alternatives used a combination of simple multi-attribute rating technique (SMART) and SWING weighting (von Winterfeldt & Edwards, 1986) techniques. In the elicitation the impacts of the ranges of the alternatives were clearly presented to ensure that participants took into account the decision context. ...
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Chapter
This is the final text version of Chapter 4. A laid-out version of the full assessment report will be made available in the coming months.
... Criteria were weighted relative to each other using the SMART (Simple Multi-Attributable Rating Technique) and swing method [18][19][20]. Participants voted for the importance of each criterion, compared to the following ranked criterion on a scale of 0% to 100%, where 0% portrays the equal importance of the two compared criteria, and 100% indicates the higher ranked criterion to have double the importance of the lower criterion. Finally, a draft MCDA tool was created based on experts' understanding and votes. ...
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Background: With the availability of several similar medical devices performing the same function, choosing one for reimbursement is not easy, especially if purchased for a large number of patients. The objective of this project was to create a multicriteria decision analysis (MCDA) tool, that captures and compares all implantable medical devices' attributes, to provide an objective method for choosing among the available options in Egypt. Method: We conducted a systematic review and expert interviews, to identify the relevant criteria for inclusion in the tool. Subsequently, a workshop was conducted, that involved experts in procuring and tendering medical devices. Experts chose the criteria, ranked them, assigned weights and scoring functions for each criterion, and then created the draft tool. A pilot phase followed; then, another workshop was conducted to fine-tune the tool. We readjusted the tool based on experts' experience with the draft tool. Results: The final tool included eight criteria, arranged according to their weightage: technical characteristics (29.4%), country of origin (19.5%), use in reference countries (14.9%), supply reliability (11.7%), previous use in tenders (9.0%), instant replacement within product variety (6.9%), pharmacovigilance (4.6%), and refund or replacement (4.0%). Each medical device was assessed on these eight criteria to achieve a final score, that was compared to the alternative devices’ scores. Price is not included in the MCDA tool, but it will be added in the financial evaluation phase. Conclusion: Decisionmakers could use the MCDA tool, to make evidence-based and objective decisions for purchasing implantable devices, in the Egyptian public sector. Post price evaluation, the product with the best value will be chosen for reimbursement.
... In multi-attribute utility theory approaches, partial values are aggregated using compensatory methods, whereas partial values are aggregated using non-compensatory methods in outranking methods. The four most popular compensatory techniques are (i) the swing method (Winterfeldt and Edwards 1986), (ii) both include the creation of two extreme hypothetical situations, W and B, where the first (W) reflects the worst values of all criteria and the second (B) corresponds to the best values; these procedures identify the decision-dilemmas makers by a pairwise evaluation of criteria, (iii) the SMART strategy (Edwards and Barron 1994), which proposes a method for contrasting criteria using the best as well as worst criteria from a specified list of criteria; (iv) the Edwards and Barron-created SMARTER (Exploiting Ranks) technique is a new iteration of the SMART technique that establishes criteria weights using the centroid method. Contrary to compensatory methods, non-compensatory approaches largely represent the global values of the relative relevance of criteria. ...
Article
The paper aims to introduce a model of multiple criteria decision making to identify the reasons that cause the spread of the monkeypox virus. These days, this virus is spread widely all across the globe. To study this, a hybrid model named as trapezoidal fuzzy full consistency method (FUCOM)-AHP is proposed by taking the benefits of the trapezoidal fuzzy number, FUCOM and the AHP process. This method will give an innovative method to determine the subjective weighting associated with decision-making. The trapezoidal fuzzy FUCOM (TrF-FUCOM) method is used to determine the weight of the different criteria. The benefits that can be gained as a consequence of applying the FUCOM comprise comparisons made pairwise of the requirements no more extensive than n − 1 comparison. Further, a trapezoidal fuzzy analytic hierarchy process is defined to determine the weight of the alternatives. Finally, by keeping features of both weights, we state a hybrid method, named TrF-FUCOM-AHP, to determine the global weights of the decision process. To demonstrate the applicability of the proposed method, a case study related to the identification of the cause of the spread of the monkeypox virus is presented.
... Both BUsSort and StrRank are carried out through a Multiple Criteria Analysis model based on the Multi-Attribute Value Theory (MAVT) [111,112], an additive-type model that uses value functions to normalize the multiple performances of both the analyzed BUs and the outlined Strategies within a range of standard values. Quadrilinear normalization scales were used for BUsSort and bilinear ones for StrRank: ...
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This research deals with the issue of the recovery of the historic urban fabric with a view towards ecological transition, nowadays considered the preferable direction of sustainability for the reform of the house–city–landscape system. The massive incentives provided by the Italian government for sustainable building, in view of the post-pandemic economic recovery, risk being reduced to mere support for the real estate sector, which turns the financial transfer from the public into an increase in asset value for the private sector. Such an incentive system could contradict the original function of the city, which is to be the privileged place for social communication and the creation of the identity of settled communities. A process of property development that disregards the distribution of income favors the most valuable property, thus increasing the socioeconomic distance between centrality and marginality. The latter is a condition that often characterizes the parts of the historic city affected by extensive phenomena of physical and functional obsolescence of the built heritage, and it is less capable of attracting public funding. The increase of building decay and social filtering-down accelerates the loss and involution of neighborhood identities; the latter constitutes the psycho-social energy that helps preserve the physical, functional and anthropological integrity of the city, due to the differences that make its parts recognizable. This study, with reference to a neighborhood in the historic city of Syracuse (Italy), proposes a model of analysis, evaluation and planning of interventions on the buildings’ roofs, aimed at defining the best strategy for ecological–environmental regeneration. The model presented allows one to generate a multiplicity of alternative strategies that combine different uses of roofs: from the most sustainable green roofs, but that are less cost-effective from the identity and landscape point of view; to the most efficient photovoltaic roofs from the energy–environmental point of view; and up to the most cost-effective ones, the vertical extensions with an increase in building volume. The proposed tool is an inter-scalar multidimensional valuation model that connects the multiple eco-socio-systemic attitudes of individual buildings to the landscape, identity, energy–environmental and economic overall dimensions of the urban fabric and allows one to define and compare multiple alternative recovery hypotheses, evaluating their potential impacts on the built environment. The model allows the formation of 100 different strategies, which are internally coherent and differently satisfy the above four perspectives, and it provides the preferable ones for each of the five approaches practiced. The best strategy characterizes most green roofs, 427 out of 1075 building units, 277 blue roofs, 121 green–blue roofs and 46 grey roofs.
... In the case of the four indicators measured as a percentage (Table 4), the initial scoring was simple. For the remaining two indicators that outputted absolute alternatives (Emissions and Pollutants and Government Investment), the bisection method [78] scoring method was used. This method bases its scoring on the use of maximum and minimum alternatives. ...
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With connected, autonomous and electric vehicles (CAEV) developing rapidly, there is a need to better support their implementation into rural scenarios, where there are numerous transport challenges. The potential safety, efficiency and sustainability benefits of CAEVs could provide significant value for rural communities if implemented correctly. However, transport planner knowledge of CAEVs and their digital and physical infrastructure requirements in the UK is limited and, despite interest, there is little time or resources available to effectively explore rural CAEV implementation potential. This paper therefore describes the methodology behind, and development of, the CAEV Rural Transport Index (CARTI), based on existing literature and a combination of existing and developed indicators. The CARTI's purpose is to identify the levels of need, capacity and overall potential of different rural areas to support rural CAEV implementation. Application of the CARTI to several case study areas reveals a range of benefits, reviewed through workshops with local transport professionals. Ultimately, the CARTI is identified as a much-needed tool to support the implementation of CAEVs in rural areas, with potential for further development to establish it as a successful and long-term planning tool.
... One of four treatments followed (Fig. 2). Next, we elicited participants' preferences, specifically the weights, using the swing method (von Winterfeldt and Edwards, 1986;Eisenführ et al., 2010). Its procedure makes attribute ranges explicit (description see SI 4, with screenshots). ...
Article
Multi‐criteria decision analysis (MCDA) is well suited to address complex public policy problems but could benefit from new tools to involve many laypeople. Online information on specialized topics could be more engaging by including game elements. This paper reports an experiment that assessed a gamified interface to (1) inform laypeople about the objectives to consider in wastewater management decisions, (2) assist them in constructing range‐based preferences, and (3) provide a positive experience. We measured the effects with (1) a knowledge pre‐ and posttest, (2) the elicited weights and a range sensitivity index, and (3) an experience questionnaire based on self‐determination theory. Answers from 174 participants indicated that participants learnt about the objectives and constructed preferences in both the gamified and control treatments. However, in neither were weights sufficiently adjusted. Our gamification making the ranges salient did not help overcome this bias. Both treatments were experienced as neutral to positive, the gamified being more entertaining. We discuss implications: if gamification of tools for participatory decision‐making is to be promoted, it requires further research. Range insensitivity remains an unresolved bias in MCDA.
... There are various ways to assign the weights to criteria ( Riabacke et al., 2012 ). They can be asked directly from the stakeholders or by using some more sophisticated technique, such as Swing ( von Winterfeldt and Edwards, 1986 ) or SMART ( Edwards and Barron, 1994 ). Preference elicitation can be carried out, for example, in structured interviews with stakeholders representing different interest groups ( Marttunen and Hämäläinen, 2008 ) Comparison of the three applied decision support methods in terms of their theoretical and technical requirements and aspects. ...
Article
Environmental management problems are often portfolio problems where the task is to find a set of actions that meets different objectives (e.g., the reduction of greenhouse gas emissions) and constraints (e.g., costs). We report experiences from deploying multiple operations research (OR) methods in a real decision-making setting and discuss the insights gained from this process. The applied methods were Multi-Attribute Value Theory (MAVT), the project portfolio selection tool Your Own Decision Aid (YODA) and Robust Portfolio Modelling (RPM). The methods were applied in a portfolio case evaluating three peatland rewetting options (“No action”, “Restoration”, “Damming”) for 79 drained peatland stands in an important recreational and nature conservation area in southern Finland. The pros and cons of the methods were evaluated, as well as their key methodological challenges, in a participatory environmental portfolio case. The applied methods yielded similar results in terms of the superiority of rewetting options. The strength of MAVT was its ability to highlight the strengths and weaknesses of all three rewetting options for a single peatland stand. YODA's strength was its simplicity and the possibility to apply it independently via the Internet. RPM made it possible to determine the priority of peatland stands within constraints, even without precise preference information. To our knowledge, this is the first systematic evaluation of three methods representing different ‘method categories’ (MAVT, multi-criteria elimination, portfolio decision analysis) applied to a real environmental problem.
... We can also learn values of W i using multi-attribute value theory (MAVT) (Keeney and Raiffa, 1993;Von Winterfeldt and Edwards, 1986;Jansen, 2011;Dyer, 2016). Using concepts of the MAUT (Jansen, 2011, p. 150) for each welfare dimension, we can use a multi-attribute value model such that: the alternatives will be the Doings, attributes will be the actions, attributes level will be the level of actions and single-attribute utility will be the vector W i h . ...
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This paper aims at suggesting that welfare measurement could be based upon Sen’s capability approach (CA). This should allow establishing a “rational” framework improving how we aide the design and assessment of public policies. We propose the use of a multi-objective mathematical program as basis for measuring individual’s welfare and suggest that citizens with similar capabilities could be clustered together establishing targets for specific public policies aiming at improving or protecting the welfare on such well identified social groups.
... Therefore, LCA is sometimes criticized for making subjective choices. Participatory methods and/or Multi-Criteria Decision Analysis (MCDA), a family of methods that help decision makers identify and select a preferred alternative when faced with a complex decision-making problem characterized by multiple objectives [112], has been used for weighting in LCA to integrate and balance different sustainability dimensions [113][114][115]. Jouini et al. [116] constructed an operational framework integrating LCA and participatory approach in the evaluation of environmental impacts in rural areas of developing countries with limited available data. ...
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Agricultural Life Cycle Assessment (LCA) is an effective tool for the quantitative evaluation and analysis of agricultural materials production and operation activities in various stages of the agricultural system. Based on the concept of life cycle, it comprehensively summarizes the impact of agriculture on the environment, which is an effective tool to promote the sustainability and green development of agriculture. In recent years, agricultural LCA has been widely used in the agroecosystem for resource and environmental impacts analysis. However, some challenges still exist in agricultural LCA, i.e., the environmental impact assessment index system needs to be improved; its application in different production mode is limited; and combination research with other models needs more attention. This paper discusses the above-mentioned challenges and recommends research priorities for both scientific development and improvements in practical implementation. In summary, further research is needed to construct a regional heterogeneity database and develop innovated methodologies to develop more meaningful functional units for agricultural products to complement LCA by other models. These efforts will make agricultural LCA more robust and effective in environmental impacts assessment to support decision making from individual farm to regional or (inter)national for the sustainable future of agriculture.
... As individuals consider each alternative, MAUT is a way of "measuring the decision-maker's values separately for a set of influential attributes and by weighting these by the relative importance of these attributes as perceived by the decision-maker" (Jansen, 2011, p. 101). MAUT component of normative decision-making specifically argues individuals progress in the following five steps (Von Winterfeldt & Edwards, 1993): ...
... Swing (von Winterfeldt and Edwards, 1986): A DM starts from a hypothetical worst alternative scenario, in which all attributes are set to their worst possible levels. Next, the DM is asked to identify which attribute they would prefer most to change from its worst performance level to its best, and the attribute in question is then assigned a value of 100 by the DM, who then repeats this process and assigns values less than or equal to 100 until the worst attribute is assigned a value. ...
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In this study, the existence of anchoring bias-people's tendency to rely on, evaluate, and decide based on the first piece of information they receive-is examined in two multi-attribute decision-making (MADM) methods, simple multi-attribute rating technique (SMART), and Swing. Data were collected from university students for a transportation mode selection. Data analysis revealed that the two methods, which have different starting points, display different degrees of anchoring bias. Statistical analyses of the weights obtained from the two methods show that, compared to Swing (with a high anchor), SMART (with a low anchor) produces lower weights for the least important attributes, while for the most important attributes, the opposite is true. Despite their differences in anchoring bias, analytical approaches supported by empirical studies suggest that both methods (SMART and Swing) overweigh the less important attributes and underweigh the more important attributes. As such, we examined whether the best-worst method (BWM), which has two opposite anchors in its procedure (a possible promising anchoring debiasing strategy), could produce results that are less prone to anchoring bias. Our findings show that the BWM is indeed able to produce lower weights (com-pared to SMART and Swing) for the less important attributes and higher weights for the more important attributes. This study shows the vulnerability of MADM methods with a single anchor and supports the idea that MADM methods with multiple (opposite) anchors, like BWM, are less prone to anchoring bias.
... Decision theory, in its modem form, originates with the work of Ramsey (1931), Neumann and Morgenstem (1944), Cox (1946) and Savage (1954). A complete description of decision theory for the uninitiated is well beyond the scope of this dissertation -the interested reader should see the introductory texts (Savage 1954;Raiffa and Schlaifer 1961;Watson and Buede 1987) or (von Winterfeldt and Edwards 1986). For applications of decision theory in AI see (Russell and Wefald 1989;Horvitz 1990;Dean and Wellman 1991;Doyle 1992). ...
Thesis
p>An on-line planning problem is one where an agent must optimise some objective criterion by making a sequence of action selection decisions, where the time and resources used in making decisions count in assessing overall solution quality. Typically in these problems it is not possible to find an optimal complete solution before an initial action must be executed, instead to maximise its performance the agent must interleave decision making and execution. This thesis investigates using decision theoretic techniques to solve these problems by equipping the agent with the ability to reason about the “complexity induced” uncertainties in its information and the costs of computation. The major sub-problems such an agent must solve are: i) decision making – how to make decisions whilst in a state of “complexity induced uncertainty”, ii) search control – which node to expand next, iii) stopping – when to stop searching. Decision making is treated as a value estimation problem. By representing the agent’s uncertainty in probabilistic terms this can be solved using decision theoretic techniques. Existing decision making systems are analysed and new low computational cost approximate decision theoretic algorithms developed. These are shown to give significant improvements in decision quality. Search control is also treated as an estimation problem, in this case estimating the expected value of computation (EVC), which is the expected benefit of a computation in reducing the agent’s uncertainty (hence improving action selection). New, low computational cost, approximations for the EVC are also developed and shown to give significant improvements in decision quality. Sophisticated stopping can be achieved by trading-off the EVC of further search against its computational cost. Experimental results show that integration of the sub-problem solutions is critical to agent performance. The results also show that (assuming no adverse interactions) improving decision making gives the greatest improvements, with search control and stopping offering more modest benefits.</p
... This section is dedicated to analyze the data and results get using AHP model in responses from the experts of leading manufacturing industry and academia research experts. A software called Expert Choice ® developed by Thomas Saaty [22] and distributed by [23] Expert Choice ® Inc has been use to manage the computational complexity of AHP model. The initial weights of alternatives and criteria (including sub criteria) aggregated after computation are shown in the computed aggregate initial scores shown in ...
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Article
Development of design characteristics based dynamic decision support framework is presented in the current study, to facilitate the decision makers in the transformation of system in the industry 4.0 paradigm. The model development is designed for a robust decision-making approach to integrating human and machine knowledge to adopt smart technologies and system design. The system is based on prioritization of the industry 4.0 design principles and characteristics including flexibility, self-adaptability, self-reconfigurability, context awareness, decision autonomy, and real-time capabilities. It has been revealed from an industrial field study, the companies facing difficulty to transform the system, and systematics approach needed to overcome the challenge. A decision support process has been developed as an integrated approach to embedding human knowledge. The developed process has been validated using Technique for Order of Preference by Similarity to Ideal Solution, the results depict the operational flexibility, has been most crucial transformation characteristics prioritized using the Analytical Hierarchical Process. The developed process has the capability to help the system development and estimate the factors involved in the transformation.
... It is not uncommon that the MADM models use some part of the ordinal information of the ranking of items from the decision maker at the beginning of the process as well, namely the best, the worst or both alternatives. The most popular such methodologies are the SMART (simple multi-attribute rating technique) (Edwards, 1977), the Swing method (von Winterfeldt and Edwards, 1986), the SMARTS (SMART using Swings) and the SMARTER (SMART Exploiting Ranks) (Edwards and Barron, 1994;Mustajoki et al., 2005), and last but not least the best-worst method (Rezaei, 2015). The latter one generated an indeed large literature in the last few years (Mi et al., 2019), with theoretical extensions and studies (Liang et al., 2020;Mohammadi and Rezaei, 2020) as well as real applications (Rezaei et al., 2016). ...
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A crucial, both from theoretical and practical points of view, problem in preference modelling is the number of questions to ask from the decision maker. We focus on incomplete pairwise comparison matrices based on graphs whose average degree is approximately 3 (or a bit more), i.e., each item is compared to three others in average. In the range of matrix sizes we considered, n=5,6,7,8,9,10, this requires from 1.4n to 1.8n edges, resulting in completion ratios between 33% (n=10) and 80% (n=5). We analyze several types of union of two spanning trees (three of them building on additional ordinal information on the ranking), 2-edge-connected random graphs and 3-(quasi-)regular graphs with minimal diameter (the length of the maximal shortest path between any two vertices). The weight vectors are calculated from the natural extensions, to the incomplete case, of the two most popular weighting methods, the eigenvector method and the logarithmic least squares. These weight vectors are compared to the ones calculated from the complete matrix, and their distances (Euclidean, Chebyshev and Manhattan), rank correlations (Kendall and Spearman) and similarity (Garuti, cosine and dice indices) are computed in order to have cardinal, ordinal and proximity views during the comparisons. Surprisingly enough, only the union of two star graphs centered at the best and the second best items perform well among the graphs using additional ordinal information on the ranking. The union of two edge-disjoint spanning trees is almost always the best among the analyzed graphs.
... Sixth, it is important to state that some would argue that correct application of the swing weighting technique would involve a third step: consistency check [60,61]. Thus, the method of eliciting the criteria weights must be seen in light of this limitation, since consistency check was not performed. ...
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Background In recent years, the potential of multi-criteria decision analysis (MCDA) in the health field has been discussed widely. However, most MCDA methodologies have given little attention to the aggregation of different stakeholder individual perspectives. Objective To illustrate how a paraconsistent theory-based MCDA reusable framework, designed to aid hospital-based Health Technology Assessment (HTA), could be used to aggregate individual expert perspectives when valuing cancer treatments. Methods An MCDA methodological process was adopted based on paraconsistent theory and following ISPOR recommended steps in conducting an MCDA study. A proof-of-concept exercise focusing on identifying and assessing the global value of first-line treatments for metastatic colorectal cancer (mCRC) was conducted to foster the development of the MCDA framework. Results On consultation with hospital-based HTA committee members, 11 perspectives were considered in an expert panel: medical oncology, oncologic surgery, radiotherapy, palliative care, pharmacist, health economist, epidemiologist, public health expert, health media expert, pharmaceutical industry, and patient advocate. The highest weights were assigned to the criteria “overall survival” (mean 0.22), “burden of disease” (mean 0.21) and “adverse events” (mean 0.20), and the lowest weights were given to “progression-free survival” and “cost of treatment” (mean 0.18 for both). FOLFIRI and mFlox scored the highest global value score of 0.75, followed by mFOLFOX6 with a global value score of 0.71. mIFL was ranked last with a global value score of 0.62. The paraconsistent analysis (para-analysis) of 6 first-line treatments for mCRC indicated that FOLFIRI and mFlox were the appropriate options for reimbursement in the context of this study. Conclusion The Paraconsistent Value Framework is proposed as a step beyond the current MCDA practices, in order to improve means of dealing with individual expert perspectives in hospital-based HTA of cancer treatments.
... The MAVT is an algorithm that is widely used in the literature to support decisionmaking in numerous problems [148][149][150][151], and for this reason, we will report only some information. This will allow the reader to analyse a set of alternatives even from a perspective characterized by conflicting objectives. ...
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The issue of climate has posed major and urgent challenges for the global community. The European Green Deal sets out a new growth strategy aimed at turning the European Union into a just and prosperous society, with a modern, resource-efficient, and competitive economy, which will no longer generate net greenhouse gas emissions by 2050. Cities in this context are committed on several fronts to rapid adaptation to improve their resilience capacity. The historic centre is the most vulnerable part of a city, with a reduced capacity for adaptation, but also the densest of values, which increase the complexity of the challenge. This study proposes an integrated tool, Heuristic Planning Support System (HPSS), aimed at exploring green-blue strategies for the historic centre. The tool is integrated with classic Planning Support System (PSS), a decision process conducted from the perspective of heuristic approach and Geographic Information System (GIS). It comprises modules for technical assessment, environmental assessment Life Cycle Assessment (LCA), economic assessment Life Cycle Cost (LCC), Life Cycle Revenues (LCR), and Discounted Cash Flow Analysis (DCFA) extended to the life cycle of specific interventions, the Multi-attribute Value Theory (MAVT) for the assessment of energy, environmental, identity, landscape, and economic values. The development of a tool to support the ecological transition of historic centres stems from the initiative of researchers at the University of Catania, who developed it based on the preferences expressed by a group of decision makers, that is, a group of local administrators, scholars, and professionals. The proposed tool supports the exploration of green-blue strategies identified by decision makers and the development of the plan for the historic district of Borgata di Santa Lucia in Syracuse.
... Different scenarios have different degrees of risk, fuzziness, and uncertainty; therefore, different methods of MCDA are developed to be compatible with different scenarios. The Simple Multi-Attribute Rating Technique (SMART) [41], SWING weighting [42], TRADEOFF weighting [43], and Analytical Hierarchy Process (AHP) [44] are some of the more well-known MCDA methods in the literature. Among these methods, AHP has been a popular method for MCDM applications including but not limited to sustainable energy planning [45], wind farm site selection [46], bidding decision making [47], maintenance planning of reinforced concrete [48], post-disaster sustainability analysis [49], classification of areas suitable for fish farming [50], and safety evaluation of urban public parks [51]. ...
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Technical Report
This project performed preliminary work to support use of Unmanned Aerial Vehicles (UAV)-based for bridge inspections, providing an economical and safer alternative to conventional inspection practices. The main challenge is that most existing technologies rely on general-purpose UAV platforms and there is no verified methodology for UAV-enabled bridge inspection principles and relevant considerations to reliably obtain inspection data. There have been some efforts to use general-purpose commercially available UAVs for bridge inspection. However, the turbulent environment that often exists around bridges requires customized and enhanced UAV platforms with a higher level of robustness, taking into account the bridge type and structure as well as the weather conditions around the bridge. Additionally, the data-acquisition capabilities of commercially available UAVs need to be compared to those required for bridge inspection. Previously, there has not been a study to quantify the gap between the performance of the commercially available UAVs and ideal desired performances. In this multidisciplinary project, a comprehensive set of experiments were developed for selection, testing, and evaluation techniques of candidate UAVs, the complex nature of flying UAVs in close proximity to bridges was explored, and the limitations of UAV flight due to turbulent flows around bridge components and nearby terrain was assessed. Commercially available platforms for bridge inspection were selected, tested, and evaluated. Deliverables from this project include: (1) measurable metrics to evaluate the performance of UAVs for bridge inspection, (2) experiments to test the suitability of UAVs for bridge inspection, and (3) a comprehensive analysis near-bridge environment flow field. Computational analysis of air flow patterns near bridge elements shows that the bridge geometry creates areas of turbulence and flow variation which impact the control requirements of the UAV. Local weather conditions can amplify these areas. Test flights were performed at selected structures to provide additional insight into the flight and data collection capabilities of the UAVs under consideration. Findings and deliverables from this project will help NCDOT justify capital purchases made to support UAV-assisted inspection, as well as additional research needed to integrate UAVs into their current bridge inspection processes. Ultimately, this work supports a follow-up project to develop workflows and implementation tools for efficient UAV-enabled bridge inspection.
... An extensive literature in Decision Sciences addresses the cognitive effort that gathering, computing and analyzing these information entails for clients and analysts developing decision support models (see [17,48]), and associated biases plaguing decision aiding processes. An important outcome of these reflection is the development of "user friendly" methods (such as rule based decision support models; see [18,43]) and preference learning techniques (see [11,16,29]). ...
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Preprint
Decision support is the science and associated practice that consist in providing recommendations to decision makers facing problems, based on available theoretical knowledge and empirical data. Although this activity is often seen as being concerned with solving mathematical problems and conceiving algorithms, it is essentially an empirical and socially framed activity, where interactions between clients and analysts, and between them and concerned third parties, play a crucial role. Since the 80s, two concepts have structured the literature devoted to analysing this aspect of decision support: validity and legitimacy. Whereas validity is focused on the interactions between the client and the analyst, legitimacy refers to the broader picture: the organisational context, the overall problem situation, the environment, culture, history. Despite its importance, this concept has not received the attention it deserves in the literature in decision support. The present paper aims at filling this gap. For that purpose, we review the literature in other disciplines relevant to elaborate a concept of legitimacy useful in decision support contexts. Based on this review, we propose a general theory of legitimacy, adapted to decision support contexts, encompassing the relevant contributions we found in the literature. According to this general theory, a legitimate decision support intervention is one for which the decision support provider produces a justification that satisfies two conditions: (i) it effectively convinces the decision support provider's interlocutors (effectiveness condition) and (ii) it is organised around the active elicitation of as many and as diverse counterarguments as possible (truthfulness condition). Despite its conceptual simplicity, legitimacy, understood in this sense, is a very exacting requirement, opening ambitious research avenues that we delineate.
... The idea behind this approach was to ensure a maximum distinction between the 'objective' estimates, gathered by the analyst, and the 'subjective' judgements, carried out by the stakeholders. For the performance scores, a 7-step scale ranging from − 3 to +3 (very negativevery positive, later converted to − 1 <=>1) was used, and for the weights the SMART (Simple Multiplicative Attribute Rating Technique) (Von Winterfeldt and Edwards, 1986) was used, rating criteria from 0 to 10 (not important -most important, later converted to 0 <=> 1). The reason for choosing this direct-rating technique was it is relatively user-friendly, but also controllable, in the sense that it allows auditors to verify the input of the stakeholder input, in contrast to pairwise-comparison weighting techniques such as AHP (Analytic Hierarchy Process) (Saaty, 1989), where the weights are the result of relatively complex calculations. ...
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Article
Although there is general consensus on the necessity of evaluation for decision support in major transport projects, there is no method that is universally accepted. Multi-criteria analysis (MCA) is often suggested as the alternative for the dominant but much-criticised (social) cost benefit analysis (CBA), especially in complex multi-stakeholder projects. The paper argues that especially in this type of projects the applicability of conventional MCA techniques is limited because they require the project to be structured as a ranking-choice problem with multiple well-defined mutually exclusive decision alternatives. This often does not suit the planning question in the strategic early project phase, which is characterised by uncertainties relating to design, preferences and impacts. This article proposes a novel evaluation technique, Stakeholder-based Impact Scoring, the primary purpose of which is not to rank alternatives but to identify their positive and negative impacts for multiple stakeholders, in order to support the iterative improvement rather than the mere selection or rejection of alternatives. It is based on two principles: non-compensation, i.e. distinguishing positive and negative impacts; and non-relativity, i.e. the feature that alternatives are scored in comparison to a universal baseline scenario, instead of as relative to one another. The article demonstrates the technique in a project that concerns the reconfiguration of a large elevated urban motorway in Brussels, showing the added value of the method in highlighting key points of discord between stakeholders.
... or attribute disconfirmation, to satisfaction. This linear model has been applied previously in attribute utility models [64][65][66]. This linear model has been shown to be robust, and to give a good approximation of alternative, nonlinear specifications [67], although it may result in negative coefficients, in the case of multicollinearity among the attributes [11]. ...
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We studied the determinants of consumer satisfaction with mobile phones on the basis of their perceived product attribute performance, and the disconfirmation of product attribute expectations. Disconfirmation refers to the discrepancy between the prior expectation about the performance of a product’s attributes, and its perceives realizations after purchase. Evaluability theory assumes that the perceived attribute performance has a larger effect on consumer satisfaction for easy-to-evaluate than for difficult-to-evaluate attributes, after product acquisition. Furthermore, we used predictions of the asymmetric evaluations of gains (product performs better than expected) and losses (product performs worse than expected) from prospect theory, in combination with evaluability theory. We studied how evaluability influences the effects of the asymmetric evaluations of both positive and negative disconfirmation of product attribute expectations on consumer satisfaction. Our empirical study included 3099 participants of Amazon Mechanical Turk. We found that negative attribute disconfirmation had a larger effect on satisfaction than positive attribute disconfirmation, which is in line with loss aversion theory. Although the perceived product attribute performance positively influenced satisfaction, we found little support for the effects of perceived attribute performance being influenced by attribute evaluability. However, our findings indicated that negative attribute disconfirmation influenced satisfaction to a greater extent for relatively difficult-to-evaluate attributes than for relatively easy-to-evaluate attributes. We discuss both theoretical and managerial implications of our findings.
... Surveys were conducted with 14 different officers attending the 85th Military Operations Research Symposium at West Point, NY on June 19-22, 2017. Due to the limited time available for in-person discussion and elicitation and the illustrative nature of the default weights, a simple and readily understandable approach of direct ranking and weighting was selected over alternate weight-elicitation techniques like swing weight elicitation (Winterfeldt and Edwards 1986). The officers were first asked to rank the criteria in importance from 1 to 10 and then use a four-star rating system for identifying relative criteria importance. ...
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The process used to determine site suitability for military base camps lacks a formal framework for reducing relative risks to soldier safety and maximise mission effectiveness. Presently, military personnel responsible for determining site suitability of a base camp must assess large amounts of geographic, socioeconomic and logistical data, without a decision analysis framework to aid in the process. By adopting a multicriteria decision analysis (MCDA) framework to determine site suitability of base camps, battlespace commanders can make better, more defensible decisions. This paper surveys US Army officers with recent base camp experience to develop a set of initial criteria and weights relevant to base camp site selection. The developed decision framework is demonstrated using an MCDA methodology in an illustrative example to compare alternative base camp locations within a designated Area of Interest (AoI). Leveraging the site ranking output and/or criteria weights resulting from the methodology provides decision-making support that can be used in the field when time, resources and data may not be readily available.
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Wetland restoration is an important water quality and climate resilience strategy. Wetland restoration rarely considers tradeoffs at large spatial and temporal scales, which limits capacity to aid decision makers. High resolution data can reveal hundreds to thousands of possible restoration options across a landscape, but guidance for setting restoration targets at these scales is limited. This study uses structured decision making (SDM) as a process for evaluating the desirability of numerous restoration options, with a case study on the Outer Coastal Plain of the Chesapeake Bay watershed, USA. The Nature Conservancy, in partnership with federal, state, and nonprofit organizations, evaluated a decision to target large-scale wetland restoration based on two fundamental objectives: improve water quality and enhance climate resilience. A total of 964 potentially restorable alternatives were delineated across the study area. The alternatives were evaluated on seven water quality and climate resilience criteria. High-priority alternatives were mapped based on multi-criteria ranking methods and principal component analysis. Sensitivity analysis included varying nutrient load data, implementing multiple ranking methods with different assumptions, and varying criteria weights. The maps revealed seven distinct regions of restoration opportunities. Tradeoffs were evaluated to distinguish between desirable and less desirable regions. Results indicated that three regions were promising choices to initiate landowner engagement and outreach. This study highlights the advantages of SDM to structure large-scale restoration decisions. In doing so, our work offers a roadmap toward further developing SDM in future applied restoration contexts.
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This work resume the potential of some native species of arid zones of Mexico for the use to biofuel; the cetane number is calculated and compared with the international standars, like a form to measure the potential. The cetane number range was 45 to 64, this indicate are good to produce biofuel.
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Based on the conceptual framework developed for this program, a system of risk indicators is proposed that represents the current vulnerability and risk management situation in each country. The indicators proposed are transparent, relatively easy to update periodically, and easily understood by public policymakers. Four components or composite indicators have been designed to represent the main elements of vulnerability and show each country’s progress in managing risk. The four indicators are the Disaster Deficit Index (DDI), the Local Disaster Index (LDI), the Prevalent Vulnerability Index (PVI), and the Risk Management Index (RMI).
Article
Multi‐criteria methods and systems have been developed over many years to support decision‐making with a process of eliciting preferences. The emphasis has been on those that incorporate compensatory rationality, the characteristics of which make the process more complex. Neuroscience has offered the opportunity to capture aspects of cognition, generating insights. This paper investigates the preference elicitation process with Flexible and Interactive Tradeoff (FITradeoff), using electroencephalography and eye‐tracking applied to a sample of undergraduate and graduate students. While FITradeoff offers greater flexibility when evaluating recent advances in the area, the experiment carried out incorporates paradigms present in other methods developed for compensatory rationality. The results indicate the effect the type of predominant criterion has on cognitive effort. Moreover, a non‐linear relationship between the number of criteria and questions was found, which suggests that decision‐makers use a strategy of minimizing cognitive effort. Such findings help to direct efforts to enhance systems and methods with compensatory rationality.
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This paper uses Value-Based Data Envelopment Analysis (VBDEA), to assess the impact of the COVID-19 pandemic on the efficiency of 37 state-owned enterprises (SOE) hospitals by employing data publicly available from the Portuguese Health Service database between January and November 2019 and 2020, respectively. Furthermore, a productivity index (specifically adjusted to the VBDEA approach) is also used that allows identifying which factors are behind the relative efficiency changes of these hospitals. The factors considered to perform the efficiency assessment of the Portuguese SOE hospitals include labour, capacity, and activity-related indicators. Out of the 37 SOE hospitals, 21 and 17 were efficient in 2019 and 2020, respectively. Irrespective of the value functions considered, the hospitals more often viewed as a reference for best practices were Santa Maria Maior, Tâmega e Sousa and Entre Douro e Vouga. Santa Maria Maior and Algarve were the only hospitals found to be robustly efficient for both years. Overall, the majority of SOE hospitals showed negative productivity (except for Évora and Santa Maria Maior) and all of them presented negative technological change, thus highlighting the massive impact that the COVID-19 outbreak has had on the performance of these hospitals. An additional conclusion is that inefficient hospitals substantially increased all their resources in 2020 as compared to inefficient hospitals in 2019, suggesting that the inefficiency of these hospitals was not due to the lack of resources. Finally, irrespective of the model employed, the hospitals located in the Portuguese northern region were more resilient to the COVID-19 crisis. All in all, to become more resilient (even for future COVID-19 outbreaks), hospitals should undertake changes that are advantageous irrespective of the obstacles they face and that are even beneficial during normal times. A culture of cooperation within and across hospitals should also be cultivated, which allows exchanging resources where they can be used more efficiently.
Chapter
Global warming is disturbing both the environment and quality of life. A cause of global warming is greenhouse gas (GHG) emissions which are caused by using fossil fuels for transportation and power generation. As a novel source of energy, the world is moving towards renewable and clean energy. In the transportation sector, usage of electric vehicles supports decreasing GHG emissions. As a result, we face a new decision problem about the selection of electric vehicles. The electric vehicle selection problem is a multicriteria decision-making problem that includes various criteria and alternatives. The criteria considered within the scope of the problem may involve objective criteria such as max speed and subjective criteria such as the design of the car. In this study, we propose Fuzzy SMART (Simple Multi Attribute Rating Technique) as an extension of the crisp SMART method. With the proposed method both crisp and imprecise criteria can be integrated within a decision problem. In this study, we construct a sample decision model for the electric vehicle selection problem and solve it by using the proposed Fuzzy SMART method.KeywordsSmartFuzzy setsElectric vehicle selection
Chapter
Multiple criteria decision-making/aiding (MCDM/A) situations involve one (or more) individual(s) with decision-making power, a set of decision alternatives, and a set of conflicting objectives with respect to which alternatives are evaluated. Building mathematical models for dealing with decision processes based on structured methods, which have been developed specifically for modeling preferences, can be a useful approach for tackling such situations in practice, due to the high amount of information and complexity involved, especially those within the scope of risk, reliability, and maintenance (RRM). In this context, this chapter gives an overview of MCDM/A methods that have been developed for dealing with the preferences of decision makers (DMs) and build a recommendation regarding the decision alternatives. MCDM/A methods for both compensatory and non-compensatory rationalities are presented here. In addition to these classical methods, this chapter also points to new challenges and future developments within the field of decision-making for RRM models.KeywordsMulticriteria decision-making/aidingPreference modelingDecision under riskMulticriteria methods
Article
This study attempts to examine individual investor’s psychology and their investment decision in NEPSE with an objective to identify whether the individual psychological factors and their biases influence decision making in Nepalese stock market. The sample size of 347 was taken from broker office located in Butwal city for this study. Psychological factors named anchoring, herding, mental accounting, overconfidence; regret aversion and loss aversion were undertaken. These factors were further categorized as cognitive bias (anchoring, herding and mental accounting) and emotional bias (overconfidence, regret aversion and loss aversion). Self-administered questionnaire were used to collect data. In the same way descriptive and analytical research design were used to analyze the data. Multiple regression analysis showed that overconfidence, herding and loss aversion have impact on investment decision whereas anchoring, mental accounting and regret aversion does not have an impact on individual investors investment decision. The result further showed that cognitive and emotion biases both have positive and significant influence on the investment decision making of individual investor in Nepalese stock exchange.
Chapter
s Here we detail the ways in which decision alternatives can be evaluated in a situation wherein multiple objectives must be achieved and negotiated, alongside discussing the ways in which we must assess and rank health threats with multiple impacts. We first introduce the evaluation of alternatives which incurs two consequences, as this decision problem provides us with an opportunity to discuss several important concepts in this type of decision. The evaluation of decision alternatives is subsequently extended to multiple consequences. We also demonstrate how we can consider the impact of health threats on the multiple consequences to rank these threats.
Article
The reasonable design of the alarm signal in the man-machine system is one of the important factors that determine the occurrence of safety accidents. Neuroergonomics provides a new perspective for the study of the cognitive process of alarm signals, which can reveal the mechanism of human perception of visual alarm signals from the cognitive level of the brain, thereby identifying the effectiveness of alarm signals. The article's research simulated the human-machine system for heat dissipation of new energy vehicles, used the automatic control interface of the cooling water system as the stimulus material, and used the event-related potential technology in cognitive neuroscience for experimental verification. The experimental results showed that: three kinds of alarm signals (color, color + shape, color + orientation) all induce visual mismatch waves, and the effective response of human to the alarm signal is color + orientation, color + shape, color from small to large, which provides a reference for the design of the alarm signal of the man-machine system.
Article
The North American Wetlands Conservation Act (16 U.S.C. 4401-4412) provided funding and administration for wetland management and conservation projects. The North American Wetland Conservation Fund, enabled in 1989 with the Act, provides financial resources. Resource allocation decisions are based, in part, on regional experts, particularly migratory bird Joint Ventures (JVs) (i.e., partnerships for cooperative planning and coordinated management of the continent’s waterfowl populations and habitats). The JVs evaluate funding proposals submitted with their respective regions each year and make funding recommendations to decision makers. Proposal evaluation procedures differ among JVs, however, it could be helpful to consider a transparent, repeatable, and data-driven framework for prioritization within regions. We used structured decision making and linear additive value models for ranking proposals within JV regions. We used two JVs as case studies and constructed two different value models using JV-specific objectives and weights. The framework was developed through a collaborative process with JV staff and stakeholders. Models were written in Microsoft Excel. To test these models, we used six NAWCA proposals submitted to the Upper Mississippi / Great Lakes Joint Venture in 2016 and seven proposals submitted to the Gulf Coast Joint Venture in 2017. We compared proposal ranks assigned by the value model to ranks assigned by each JV’s management board. Ranks assigned by the value model differed from ranks assigned by the board for the Upper Mississippi / Great Lakes Joint Venture, but not for the Gulf Coast Joint Venture. However, ranks from the value model could change markedly with different objective weights and value functions. The weighted linear value model was beneficial for ranking NAWCA proposals because it allows JVs to treat the ranking as a multiple objective problem and tailor the ranking to their specific regional concerns. We believe a structured decision making approach could be adapted by JV staff to facilitate a systematic and transparent process for proposal ranking by their management boards.
Chapter
Decision support is the science and associated practice that consist in providing recommendations to decision-makers facing problems, based on the available theoretical knowledge and empirical data. Although this activity is often seen as being mainly concerned with solving mathematical problems and conceiving algorithms, it is essentially an empirical and socially framed activity, where interactions between clients and analysts, and between them and concerned third parties, play a crucial role. Since the 80s, two concepts have structured the literature devoted to analyzing this aspect of decision support: validity and legitimacy. Whereas validity is focused on the interactions between the client and the analyst, legitimacy refers to the broader picture: the organizational context, the overall problem situation, the environment, culture, and history. Despite its unmistakable importance, this concept has not received the attention it deserves in the literature in operational research and decision support. The present chapter aims at filling this gap. For that purpose, we review the literature in other disciplines (mainly philosophy and political science) that is demonstrably relevant to elaborate a concept of legitimacy useful in decision support contexts. Based on this review, we propose a general theory of legitimacy, adapted to decision support contexts, encompassing the relevant contributions we found in the literature. According to this general theory, a legitimate decision support intervention is one for which the decision support provider produces a justification that satisfies two conditions: (i) it effectively convinces the decision support provider’s interlocutors (effectiveness condition) and (ii) it is organized around the active elicitation of as many and as diverse counter-arguments as possible (truthfulness condition). Despite its conceptual simplicity, legitimacy, understood in this sense, is a very exacting requirement, opening ambitious research avenues that we delineate.
Article
In order to better design more sustainable farming systems, and prepare for the development of multi‐criteria farm decision model, we investigate how farmers rank their main goals when making decisions. First, we identified the main goals used by farmers through in‐depth interviews with randomly selected farmers in which we used small games to elicit the main goals they are using to make farm‐level decisions. Then, we developed a best–worst scaling (BWS) experiment, in which farmers have to declare the “most” and the least “important” goals they use when making decisions. The experiment was conducted with 120 farmers. We first derive a ranking of the goals according to the population average, which showed the importance of rice self‐sufficiency and transmission of farm capital. We then use a scale‐adjusted latent class analysis. We identified four groups of homogenous preferences among farmers. The use of differentiated scale, a measure of choice inconsistencies, suggested different levels of certainty about the ranking, and the presence of more inconsistencies when asking the least important goal. While a large group focuses only on rice self‐sufficiency, and farm transmission, we also identified a group of optimizers, and risk‐averse farmers. Farmers of each group are likely to behave differently with regard to sustainable innovations. We also showed that some socio‐economic variables describing the farms and the households influenced the probabilities for farmers to belong to one of the four classes. Overall, we showed that BWS scaling experiments provide a rich set of information about the diversity of rankings. It also provides the set of tools to evaluate the consistency and quality of respondents' choices.
Article
Group decision making occurs when individuals collectively choose from a set of alternatives based on individual preferences. In these ubiquitous situations, it can be helpful for decision makers to visually model and compare stakeholder preferences in order to better understand others' points of view and reach consensus. Although a number of collaboration support tools allow preference inspection in some form, they are rarely based on a comprehensive understanding of the needs of group decision makers. The goal of our work is to study these demands, develop abstractions to model them, and create a framework to inform the design and assessment of existing and future tools. First, guided by decision analysis theory, we examine a diverse set of group decision making scenarios, characterizing variations in problem formulation, analysis goals, and situational features. Second, we amalgamate these findings into data and task abstractions that can be used to relate specific scenarios to the language of visualization. Finally, we use this framework to assess existing preference visualization tools in order to shed light on areas for future work in supporting group decision making.
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