Qualitative Judgments Research Articles

Challenging investment decision-making in pension funds

PurposeThe purpose of this study was to gain a better understanding of pension fund managers investment thinking when confronted with challenging investment decisions. The study focuses on the theoretical question of how dual thinking processes in experts’ investment decision-making emerge. This question has attracted interest in economic psychology but has not yet been answered. Here, it is explored in the context of pension funds.Design/methodology/approachThe sample included 22 pension fund managers. The authors explored their decision-making by applying the critical incident interview technique, which entailed collecting investment decisions that fund managers retrieved from recent memory (Flanagan, 1954). Questions concerned the investment situation, the decision-making process and the challenges and uncertainties the fund managers faced.FindingsMany of the 61 critical incidents examined concerned challenging (mostly stock) investments based on extensive analysis (e.g. reliance on external analysts for advice; analysis of massive amounts of hard company and stock market information; scrutiny of company reports and personal meetings with CEOs). However, fund managers to a high degree based their decisions on soft information judgments such as experience and qualitative judgements of teams. The authors found heuristics, intuitive thinking, biases (sunk cost effects) and social influences in investment decision-making.Research limitations/implicationsThe sample is small and not randomly selected.Practical implicationsThe authors suggest anti-bias training and better acquaintance with human forecasting limitations for pension fund managers.Originality/valuePension fund managers’ investment thinking has not previously been investigated. The authors show the types of investment situations in which analytical and intuitive thinking and biases occur.

Group decision making with multiplicative interval linguistic hesitant fuzzy preference relations

This paper proposes multiplicative interval linguistic hesitant fuzzy sets (MILHFSs) to denote the asymmetrically qualitative judgments with uncertain and hesitant characteristics, which are expressed by several interval linguistic judgments defined on the asymmetrical linguistic term set. Considering the utilization of MILHFSs, the concept of multiplicative interval linguistic hesitant fuzzy variables (MILHFVs) is introduced, and multiplicative interval linguistic hesitant fuzzy preference relations (MILHFPRs) are proposed. Then, we analyze the consistency and introduce an approach for computing the priority vector from consistent MILHFPRs. Meanwhile, incomplete MILHFPRs are discussed, and a model for obtaining unknown MILHFVs following the analysis of consistency is built. Considering group decision making (GDM), the analysis of consensus is made. Subsequently, an approach for GDM with inconsistent and incomplete MILHFPRs is provided that follows the analysis of consistency and consensus. The feasibility of the developed results is demonstrated by two practical GDM problems: (1) assessing seven-seat sport utility vehicles (SUVs) and (2) selecting the public-private partnership (PPP) model.

A procedure for group decision making with interval-valued intuitionistic linguistic fuzzy preference relations

To express the uncertain preferred and non-preferred qualitative judgments of decision makers, interval-valued intuitionistic linguistic fuzzy sets (IVILFSs) are proposed in a similar way as Atanassov and Gargov’s interval-valued intuitionistic fuzzy sets. Considering the application of IVILFSs, the concept of interval-valued intuitionistic linguistic fuzzy variables (IVILFVs) is defined and a ranking order is offered. Then, we introduce interval-valued intuitionistic linguistic fuzzy preference relations (IVILFPRs) whose elements are IVILFVs. Furthermore, an additive consistency concept is presented and a model for judging the consistency of IVILFPRs is built. Meanwhile, optimization models for deriving additively consistent IVILFPRs and for determining missing linguistic variables in incomplete IVILFPRs are constructed, respectively. For group decision making, optimization models for determining the weights of the decision makers and for improving the consensus level are established, respectively. A procedure for group decision making with IVILFPRs is developed that can cope with inconsistent and incomplete IVILFPRs. Finally, a practical group decision-making problem about evaluating express companies is selected to show the application of the new results.

PNS54 SYSTEMATIC REVIEW AND BENCHMARKING OF US BUDGET IMPACT ANALYSES

Reimbursement authorities commonly require budget impact analyses (BIA) to support formulary decision-making. However, unlike cost-effectiveness analyses, which rely on the use of cost-effectiveness thresholds for interpretation, proper interpretation of BIA results is hampered by the lack of an accepted gold standard against which they can be evaluated. We conducted a systematic review of full-text, peer-reviewed, US-based pharmacotherapy BIAs to establish benchmarks in reported per-member per-month costs (PMPMCs) and assess how these have been qualitatively interpreted. Systematic PubMed searches (01/2003-10/2018) were conducted to identify published US peer-reviewed BIAs that reported PMPMCs associated with the introduction of new pharmacotherapies. All costs were inflation-adjusted to 2018 US dollars. Distribution of reported outcomes (PMPMCs and BIA authors’ qualitative judgments of their results) and study characteristics (indication and publication year) were analyzed descriptively. We identified 49 BIAs reporting 133 PMPMC estimates (some studies reported PMPMCs of multiple populations/indications/payers/years). Of these 49 studies, 55% were published in/after 2015 and 86% provided qualitative conclusions of BIA results. Most BIAs were conducted in oncology (33%), autoimmune disease (14%), or cardiovascular disease (10%). The median (interquartile range [IQR]) PMPMC across all 133 estimates was $0.01 ($0.00-$0.04). Among PMPMC estimates ≥$0 (n=104), 80% were reported along with interpretations. “Modest,” “small,” or “minimal” were the most commonly used terms to describe result acceptability ($0.00≤PMPMC<$0.01: 27%, 36%, 23%; $0.01≤PMPMC<$0.04: 34%, 31%, 9%; PMPMC ≥$0.04, 33%, 0%, 13%, respectively). Published PMPMC estimates are clustered within a few cents (median: $0.01; IQR: $0.00-$0.04) and have been invariably interpreted as acceptable, despite a 4-factor change separating the median from the 75th percentile PMPMC. Without pre-specified benchmarks, BIA authors should report actual values and refrain from providing qualitative judgement regarding PMPMC acceptability. Future research and guidance are needed to develop a set of US benchmarks to help interpret BIA results.

An Additive-Consistency- and Consensus-Based Approach for Uncertain Group Decision Making With Linguistic Preference Relations

Linguistic preference relations (LPRs) can indicate the decision makers (DMs)’ qualitative pairwise judgments regarding a set of alternatives in uncertain multicriteria decision-making problems. This paper examines several goal programming models for managing the additive consistency and consensus of LPRs and then develops an additive-consistency- and consensus-based method for group decision making (GDM) with LPRs. First, this paper offers a consistency index to quantify the consistency level for LPRs and define acceptable consistent LPRs. For an LPR that is unacceptably additive consistent, several additive-consistency-based programming models are developed to address the inconsistency and to establish an acceptably consistent LPR. Then, an additive-consistency-based procedure to generate the priority weight vector from the LPR is offered. An additive-consistency-based algorithm for decision making with an LPR is presented. Subsequently, considering the consensus in GDM, a consensus index is proposed for gauging the agreement degree among individual LPRs. Regarding individual LPRs that do not exhibit acceptably additive consistency or acceptable consensus, several goal programming models to derive new LPRs with acceptable consistency and consensus are provided. Afterward, the DMs’ weights are determined objectively, and individual LPRs are integrated into a collective LPR. An additive-consistency- and consensus-based GDM method with a group of LPRs is developed. Finally, two practical numerical examples are offered, and a comparative analysis is presented.

The qualculative dimension of healthcare data interoperability.

Research on interoperability and information exchange between information technology systems touts the use of secondary data for a variety of purposes, including research, management, quality improvement, and accountability. However, many studies have pointed out that this is difficult to achieve in practice. Hence, this article aims to examine the causes for this by reporting an ethnographic study of the data work performed by medical records coders and birth certificate clerks working in a hospital system to uncover the practices of creating administrative data (e.g. secondary data). The article illustrates that clerks and coders use situated qualitative judgments of the accuracy and authority of different primary medical accounts. Coders and clerks also employ their understandings of the importance of different future uses of data as they make crucial decisions about how much discretion to exercise in producing accurate data and how much effort to put toward clarifying problematic medical data. These findings suggest that information technology systems designed for interoperability and secondary data also need to be designed in ways that support the qualculative practices of data workers in order to succeed, including making future uses of data clear to data workers and finding ways to minimize conflicting data before data workers encounter it.

Damage Detection and Evaluation for an In-Service Shield Tunnel Based on the Monitored Increment of Neutral Axis Depth Using Long-Gauge Fiber Bragg Grating Sensors.

It is difficult to detect and evaluate the structural damage in a shield tunnel during operation because many traditional techniques based on the observation of vibrations are limited in daily monitoring in tunnels. Thus, the curvature radius of a static longitudinal settlement curve is used to identify the residual health and safety of an in-service shield tunnel. However, there are still two problems. The curvature radius is suitable for a qualitative judgment rather than a quantitative evaluation for longitudinal damage detection. Moreover, the curvature radius, which is calculated from the measured settlements of three neighboring points, gives an average damage degree in a wide scope only and is difficult to use to identify the damage’s precise location. By means of the analysis of three kinds of longitudinal failure modes in a shield tunnel, this paper proposes: (1) a damage detection method based on the monitored increment of the neutral axis depth; and (2) an index to evaluate longitudinal damage. The index is composed of the residual ratios of the equivalent flexural stiffness (HFM1) and the equivalent shear stiffness (HFM3). The neutral axis position and the proposed damage index can be determined using long-gauge Fiber Bragg Grating sensors. Results from numerical simulations show that the deviation between the HFM1 and the true value residual ratio of the equivalent flexural stiffness is no more than 1.7%. The HFM3 is equal to its true value in the entire damage process. A loading experiment for a scaled-down model of a shield tunnel using long-gauge Fiber Bragg Grating sensors indicated that the errors in the HFM1 were no more than 5.0% in the case of early damage development (HFM1 ≥ 0.5). The maximum error did not exceed 9.0% even under severe damage conditions in the model. Meanwhile, the HFM3 also coincided with its true value in the entire testing process.

Threshold Analysis as an Alternative to GRADE for Assessing Confidence in Guideline Recommendations Based on Network Meta-analyses.

Guideline development requires the synthesis of evidence on several treatments of interest, typically by using network meta-analysis (NMA). Because treatment effects may be estimated imprecisely or be based on evidence lacking internal or external validity, guideline developers must assess the robustness of recommendations made on the basis of the NMA to potential limitations in the evidence. Such limitations arise because the observed estimates differ from the true effects of interest, for example, because of study biases, sampling variation, or issues of relevance. The widely used GRADE (Grading of Recommendations Assessment, Development and Evaluation) framework aims to assess the quality of evidence supporting a recommendation by using a structured series of qualitative judgments. This article argues that GRADE approaches proposed for NMA are insufficient for the purposes of guideline development, because the influence of the evidence on the final recommendation is not taken into account. It outlines threshold analysis as an alternative approach, demonstrating the method with 2 examples of clinical guidelines from the National Institute for Health and Care Excellence (NICE) in the United Kingdom. Threshold analysis quantifies precisely how much the evidence could change (for any reason, such as potential biases, or simply sampling variation) before the recommendation changes, and what the revised recommendation would be. If it is judged that the evidence could not plausibly change by more than this amount, then the recommendation is considered robust; otherwise, it is sensitive to plausible changes in the evidence. In this manner, threshold analysis directly informs decision makers and guideline developers of the robustness of treatment recommendations.

Assessing Spatial Flood Vulnerability at Kalapara Upazila in Bangladesh Using an Analytic Hierarchy Process.

Floods are common natural disasters worldwide, frequently causing loss of lives and huge economic and environmental damages. A spatial vulnerability mapping approach incorporating multi-criteria at the local scale is essential for deriving detailed vulnerability information for supporting flood mitigation strategies. This study developed a spatial multi-criteria-integrated approach of flood vulnerability mapping by using geospatial techniques at the local scale. The developed approach was applied on Kalapara Upazila in Bangladesh. This study incorporated 16 relevant criteria under three vulnerability components: physical vulnerability, social vulnerability and coping capacity. Criteria were converted into spatial layers, weighted and standardised to support the analytic hierarchy process. Individual vulnerability component maps were created using a weighted overlay technique, and then final vulnerability maps were produced from them. The spatial extents and levels of vulnerability were successfully identified from the produced maps. Results showed that the areas located within the eastern and south-western portions of the study area are highly vulnerable to floods due to low elevation, closeness to the active channel and more social components than other parts. However, with the integrated coping capacity, western and south-western parts are highly vulnerable because the eastern part demonstrated particularly high coping capacity compared with other parts. The approach provided was validated by qualitative judgement acquired from the field. The findings suggested the capability of this approach to assess the spatial vulnerability of flood effects in flood-affected areas for developing effective mitigation plans and strategies.

The Optional Qualitative Assessment in Impairment Tests

The qualitative assessment allowed after December 2011 is intended to reduce the complexity and costs of impairment tests for goodwill and other indefinite-lived intangibles. This assessment is unique because it gives an unconditional option to companies and depends on subjective qualitative judgment. We demonstrate that firms using this option have comparatively better financial performance and face higher expected costs for conducting quantitative tests. Using a difference-in-differences research design, we show that firms using this option have a marginally higher incidence of impairments, suggesting that the qualitative assessment does not systematically allow companies to avoid write-downs. We do not find consistent evidence that this option decreases the timeliness of impairments or increases monitoring costs for auditors, regulators, and investors. Our study provides evidence about the intended and unintended consequences of a revised impairment approach and speaks to the broader issue of allowing unconditional options and qualitative judgments in financial reporting.

Analyzing environment sustainability enablers using fuzzy DEMATEL for an Indian steel manufacturing company

PurposeThe purpose of this paper is to analyze the Environmental Sustainability Enablers (ESEs) for an Indian steel manufacturing company to select the appropriate set of ESEs for implementing and enhancing environmental sustainability.Design/methodology/approachA methodology using fuzzy Decision-Making Trail and Evaluation Laboratory (DEMATEL) is proposed to analyze ESEs capturing multiple experts’ qualitative judgments on their mutual impacts. It is applied to an Indian steel manufacturing company to understand the salient features of the concept.FindingsThe relevant 18 ESEs were classified into cause and effect group and also interactions (i.e. influencing and influenced) of each ESE with other ESEs were evaluated. It was observed that the five ESEs (i.e. competitors’ environmental sustainability strategy, environmental compliance certification, government regulations and incentives, influence of external factors and air pollution controlling system) are the most prominent in the cause group.Research limitations/implicationsThe results obtained are specific to an Indian steel manufacturing company and it cannot be generalized for steel manufacturing sector. However, the current paper can show direction to carry out such work in other manufacturing companies.Practical implicationsThe proposed methodology will be helpful for allocating efforts and resources to enhance the impact of ESEs for successful achievement of environmental sustainability.Originality/valueNo such paper has been reported in the literature with an objective to develop structural framework for Indian steel manufacturing company to improve environmental sustainability.

Cultural Adaptation and Psychometric Properties of the Persian Version of the Affordance in the Home Environment for Motor Development.

This study aimed to translate the Affordance in the Home Environment for Motor Development (AHEMD) scales (3-18 months (IS) and 18-42 month (SR) versions) into Persian and examine its cultural adaptation and psychometric properties. Four stages process was conducted as translation of the questionnaires (use of International Quality of Life Assessment protocol), cultural adaptation, and determination of its psychometric properties. Qualitative judgments were provided by 11 experts and 30 mothers for interview sessions. Quantitative data were gathered using 212 mothers. For the IS version, validity values ranged from 0.63 to 0.95. Intraclass correlation coefficient for reliability of total score was 0.87 (0.83-0.97) and was Cronbach's alpha (0.75). Validity for the AHEMD-SR ranged from 0.63 to 0.90, with reliability for total score of 0.98 (0.98-0.99, ICC). Cronbach's alpha for this version was 0.84. Correlations with SES were significant for both scales: IS (r = 0.40) and AHEMD-SR (r = 0.42). Both translated versions of the AHEMD were valid and reliable assessments of the home environment of Iranian young children.

Collaborative Value Modelling in corporate contexts with MACBETH

In complex organizational choices with consequences spread all over the organization, good management practice recommends the auscultation of the points of view of people from different operational areas, to inform a final decision-making body. In large corporations such an internal participatory process may easily involve a large number of people, however time and scheduling constraints are not compatible with gathering them together in presential meetings to reach an alignment around key decision objectives. One of these cases was the selection of a new Enterprise Management System (EMS) for GALP ENERGIA (a Portuguese energy company). The aim of this paper is to report on how a socio-technical process was designed and took place under the “Collaborative Value Modelling” framework, combining technical elements of the MACBETH multicriteria evaluation method with two social settings: firstly, Web-Delphi to elicit individual qualitative judgements from a large number of collaborators from the different departments of GALP ENERGIA; followed by a Decision Conference where a small steering committee used the knowledge collected in the Delphi to inform the construction of a quantitative model to compare the EMS alternatives proposed by information technology companies. To detail our rationale, we focus on the qualitative swing-weighting questioning MACBETH mode, implemented in the Welphi information technology platform in which GALP collaborators provided individual weighting judgements, and then in the decision conferencing for final weighting of criteria by the steering committee. The main contribution of this paper is on detailing how, through the “Collaborative Value Modeling” framework, it is possible to promote “dialogue” among a large group of participants in a corporate setting, therefore promoting alignment and increasing model acceptance within the company.

A New Method for Agricultural Market Share Assessment

The Romanian market for plant protection products (PPP) is fragmented, dispersed, and very competitive. In recent years, there has been a constant decrease of farmers’ profitability, which has cascaded into the distribution of pesticides, fertilizers, and seeds. Since the structure of any market is dynamic over time, companies can determine the effectiveness of their different marketing strategies using analytical tools. As an alternative to econometric tools for predicting the market share in the farming industry, we propose the analytic network process (ANP) model, in which the market share is described as a network of nodes and clusters. Domain experts validate the ANP structure with respect to criteria and alternatives. The model allows the quantification of qualitative judgments provided by either experts or customers, through the highest eigenvalues. The eigenvalues are then further aggregated to deliver conclusive scores for the distribution of a particular market among competitors. The purpose of this research is twofold: (1) to develop an ANP-based tool for analyzing the competitive position (market share) of a company and (2) to help companies use the new tool in order to improve their business. The paper is of interest to PPP distributors, PPP manufacturers, customers, and policy-makers. The first two categories of stakeholders can use the analysis to better direct their marketing efforts, the customers can use it to select their providers, and the policy-makers can use it to evaluate and improve the control of PPP.

A DYNAMIC RISK ASSESSMENT MODELING BASED ON FUZZY ANP FOR SAFETY MANAGEMENT SYSTEMS

Risk assessment in large organizations with extensive operational domains has been a challenging issue. Employing an efficient method along with realistic pair comparisons, applying subjective inferences of organization experts, and purging the intrinsic ambiguity of inferences, are not reflected in current airlines' safety management. Traditional two-dimensional risk assessment for risk management of safety hazards, however, is no longer sufficient to comply with this complexity. A new model for risk management and a novel formula for risk index calculation, based on a fuzzy approach, are presented in this study. In this new model, unlike in the traditional approach, the latent aftermath of safety reports, especially those which affect the continuity of the business, is also taken into account. In this model, along with the definition of a new structure for risk management, risk analysis should be restructured. To that end, a two-dimensional classic risk formula was replaced with three-dimensional (nonlinear) exponential ones, considering “the impact on the business” as a source of risk and hazard. For measuring the safety risk using the Fuzzy hierarchical evaluation method, considering experts' opinions, three criteria in four different operational fields were developed. This method employs a Fuzzy ANP to help quantify judgments, make qualitative judgments in the traditional method, and weigh the priority of elements contributing to risk. Also, it provides a tool for top-level as well as expert level management to monitor safety more precisely, monitor the safety level within their departments or organizations, set quantitative safety goals and provide feedback for improvement as well as find the most critical areas with the least cost. In this study, an airline has been selected as a case study for the risk assessment of reports based on the new model.

Valuing health states: is the MACBETH approach useful for valuing EQ-5D-3L health states?

BackgroundQuality Adjusted Life Years (QALYs) are a key outcome measure widely used within health technology assessment and health service research studies. QALYs combine quantity and quality of life, with quality of life calculations relying on the value of distinct health states. Such health states’ values capture the preferences of a population and have been typically built through numerical elicitation methods. Evidence points to these value scores being influenced by methods in use and individuals reporting cognitive difficulties in eliciting their preferences. Evidence from other areas has further suggested that individuals may prefer using distinct elicitation techniques and that this preference can be influenced by their numeracy. In this study we explore the use of the MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) non-numerical preference elicitation approach for health states’ evaluation.MethodsA new protocol for preference elicitation based on MACBETH (only requiring qualitative judgments) was developed and tested within a web survey format. A sample of the Portuguese general population (n=243) valued 25 EQ-5D-3L health states with the MACBETH protocol and with a variant of the time trade-off (TTO) protocol, for comparison purposes and for understanding respondents’ preference for distinct protocols and differences in inconsistent evaluations. Respondents answered to a short numeracy test, and basic socio-economic information collected.ResultsResults show that the mean values derived from MACBETH and the TTO variant are strongly correlated; however, there are substantial differences for several health states’ values. Large and similar numbers of logical inconsistencies were found in respondents’ answers with both methods. Participants with higher levels of numeracy according to the test preferred expressing value judgments with MACBETH, while participants with lower levels were mostly indifferent to both methods. Higher correlations between MACBETH and TTO variant evaluations were observed for individuals with higher numeracy.ConclusionResults suggest that it is worth researching the use of non-numerical preference elicitation methods. Numeracy tests more appropriate for preference elicitation when no explicit considerations of uncertainty are made need to be explored and used. Further behavioural research is needed to fully understand the potential for using these methods in distinct settings (e.g. in different evaluation contexts and in face-to-face and non-face-to-face environments), as well as to explore the effect of literacy on assessments and on respondents’ preferences.

Banking crises and business cycle: evidence for Italy(1861-2016)

PurposeThis paper aims to focus on the banking crises recorded in Italy in the period 1861-2016 and to propose a novel classification based upon the timing of the crisis with respect to the business cycle.Design/methodology/approachA simple and objective rule to distinguish between slowdown and inner-banking crises is introduced. The real impact of banking crises is evaluated by integrating the narrative approach with an empirical vector autoregression analysis.FindingsFirst, banking crises are not always associated to economic downturns. Especially in Italy, (but this analysis can be easily extended to other countries), they have often limited their negative effects within the financial system (“inner” crises). Second, the simultaneity of macroeconomic effects (credit contraction and GDP recession) leave the causal link undetermined. Third, the empirical and narrative analyses performed testify that boom–bust mechanisms are an exception in the panorama of (Italian) banking crises; although when the economy experiences such episodes, the economic and social consequences are not only severe but also enduring.Research limitations/implicationsTo classify historically recognized banking crisis episodes, the authors look at credit and GDP dynamics (and their ratio) around crisis years. Relying on a single definition of crisis is avoided. The classification provides an empirical rule to determine in what way banking crises differ. The classification is mostly based on the synchronization with the business cycle and, using the documented evolution of macroeconomic aggregates, it permits to highlight the fact that a variety of interactions occur between financial and real aggregates during and around banking crises.Originality/valueAs to the concept of systemic banking crisis, a qualitative judgment is often adopted to select relevant episodes, thus confirming the absence of a quantitative rule in classification criteria (Chaudron and de Haan, 2014). This paper proposes a simple and objective rule to distinguish between slowdown and inner-banking crises; the former occur close to a GDP contraction, whereas the latter appear to spread their effects with no substantial evidence of output loss.

A hybrid outranking method for greenhouse gas emissions’ institution selection with picture 2-tuple linguistic information

An appropriate greenhouse gas (GHG) emissions’ institution largely affects long-term development of cement corporates. The primary objective of this paper is to investigate a scientific method for selecting an optimal institution for a cement corporate. The paper mainly makes the following contributions to effectively resolving this selection problem. Given the capacity of picture 2-tuple linguistic sets (P2TLSs) in depicting voting information, they are used as evaluation representation in this case. Another contribution is that this paper newly proposes a prospect theory-based score function to rank picture 2-tuple linguistic numbers (P2TLNs). The proposed score function effectively overcomes the limitations in the existing score function by considering the voting potential of those decision-makers (DMs) who hold “abstain” opinion. Meanwhile, this proposed score function also adequately considers the rational-bounded behavior of DMs, thereby making the evaluation more approximate to the reality. Furthermore, this paper investigates a hybrid outranking method to select institution in the context of P2TLSs. It takes different types of preference functions and the Elimination and Choice Translating Reality (ELECTRE) method into account simultaneously. Compared with other similar type methods, this hybrid method can flexibly choose criteria type and provide specific values to represent quantitative dominance relation rather than qualitative judgment. Finally, an illustrative example and comparative analyses are provided to certify the availability and reliability of the proposed method.

Use of multi-criteria decision analysis to define social resilience to disaster: the case of the EU LIFE PRIMES project

Community resilience to disaster is a concept that deals with different meanings depending on diverse disciplines and so far more attention has been given to its structural aspects. Only recently the social dimensions have sparked interests and its assessment is still a challenge dealing with the integration of quantitative variables and qualitative judgments. Multicriteria Decision Analysis (MCDA) can provide a consistent methodology to deal with this aspect, creating indeed, the background for ranking and evaluating the effect of potential decision and policy strategies aiming to enhance the social resilience. In this work, we proposed a study for defining social resilience through the application of the Promethee method. Five social macro-indicators, characterized by specific sub-indicators, were analyzed in ten Italian case study areas involved in the EU LIFE PRIMES Project. The information for the definition of the sub-indicators were carried out through the delivering of anonymous questionnaires to a sample of citizens in each interested area. The approach provided both a classification of communities in term of social resilience and the individuation of the most important indicators influencing the final ranking. This method can be suggested as an effective tool for studying the various dimensions characterizing social resilience.

Xenon anesthesia for awake craniotomy: safety and efficacy.

The asleep-awake-asleep (AAA) craniotomy is a technique that offers the opportunity of having a patient fully cooperative during the awake phase, and minimizes the possible discomfort, due to the asleep phase. The aim of this prospective observational study was to test the use of xenon in the first asleep phase of an AAA craniotomy, in patients undergoing craniotomy for brain tumor resection. The data have been collected from 40 awake craniotomy procedures, performed in patients with cerebral tumor, treated with the AAA technique. Patients were treated with xenon during the asleep phase, and quality of mapping, complications and qualitative judgment of the experience given by the patients were recorded. The mapping was carried out as planned in 37 out of 40 cases. The doses of xenon administered during the first asleep phase of the anesthesia was 13±2 L. Time for awakening after xenon was switched off was 5±1 minute. A combination of xenon and regional anesthesia (with no need for additional systemic anesthetics) was adequate to accomplish craniotomy in 27/40 patients (67.5%). On the day after the operation, 37 patients recalled the testing procedure for mapping during the awake period, none had recollection of local anesthetic injections for regional anesthesia or sound associated with the neurosurgical drill. Five patients (12.5%) reported mild pain during tumor removal (VAS Score less than three). In this case series, xenon anesthesia was successfully used for the sedative phase of an awake craniotomy accomplished with an AAA approach.