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Health insurance risk analysis is crucial to the development of the insurance industry, allowing insurance companies to anticipate potential losses in health insurance's inverted product life cycle. The health insurance risk evaluation process is, however, carried out in various ways, which limits the application of transparency, fairness, and justice principles in the calculation of risk rewards. By combining cognitive mapping and measuring attractiveness by a categorical‐based evaluation technique (i.e., MACBETH, a multiple‐criteria decision analysis technique), this study sought to create a nonparametric and distinctive decision support system for individual private health insurance risk analysis. The proposed system facilitates greater transparency in the calculation of health insurance risk rewards. The results of a real‐world application of this system were analyzed and discussed in face‐to‐face group meetings with independent experts who work for two of the largest insurance companies in Portugal, thereby incorporating realism into the proposed evaluation mechanism. The advantages and limitations of this assessment framework are also discussed. [ABSTRACT FROM AUTHOR]

In 2021, Banco de Portugal started a new cycle of strategic planning. The Banco de Portugal's fourth strategic plan (i.e., PE21-25) was published at the institutional website, and defines 35 priorities/objectives grouped into five strategic guidelines. The interrelationships and causal dynamics of those guidelines and priorities are the core of the current research. The main purpose is to develop a set of actions aiming at producing recommendations for prioritizing the 35 strategic objectives using the Decision MAking Trial and Evaluation Laboratory (DEMATEL) method. The objective is to develop a constructivist procedure that, with the direct collaboration of a panel of relevant decision makers, grants the analysis objectivity and empirical substance for making recommendations at the strategic level. Contributing to the literature on central banking strategic planning is an additional objective. The results of the DEMATEL application include the identification of three priorities as central factors (i.e., high prominence and high relationship), and a hierarchical list of the PE21-25 strategic priorities analyzed, including their cause-and-effect relationships. [ABSTRACT FROM AUTHOR]

The organizational literature privileges objective performance indicators often selected by researchers. There is scarce research focusing on legitimacy-challenged hybrid and microorganizations and on perceived success under exigent conditions. To address this scarcity, this study, conducted among complementary and alternative medicine (CAM) microorganizations, explores success as a subjective measure originating from managers' perceptions. For the purpose, it integrates cognitive mapping and multiple criteria decision analysis (MCDA)—a methodological contribution to construct a subjective-success framework that can be helpful for contested hybrid microorganizations. Seven factors emerged, of which human capital is recognized as critical, while external factors are considered unimportant. [ABSTRACT FROM AUTHOR]

Purpose: This study was developed in response to the need to develop age-friendly smart living environments due to the complex demands placed on society by the ageing of the population. This study aims to analyse the potential that knowledge visualisation offers collaborative decision-making applied to the development of a multiple criteria framework supporting knowledge management (KM) through knowledge collaboration (KC) and knowledge sharing (KS) in the context of regional innovation systems (RIS). Design/methodology/approach: Using a socio-technical approach, knowledgeable and experienced representatives of RIS innovation actors were brought together to develop a constructivist multiple criteria framework that integrates knowledge visualisation and collaborative decision-making techniques (i.e. cognitive mapping and system dynamics). Findings: The study introduces a multiple criteria model supporting KM encompassing conditions and practices of RIS innovation actors facilitating and encouraging KC and KS. The potential for knowledge visualisation in collaborative decision-making is explored in great depth and illustrated in a case study setting. Practical implications: The panel members who participated in this study consider our methodological proposal to be extremely versatile and see great potential for further applications in RIS contexts. Originality/value: The combined use of cognitive mapping and system dynamics according to the strategic options development and analysis (SODA) approach offers a holistic and well-informed perspective on the issue in question. The literature reports no prior work of this methodological combination in the same research context. [ABSTRACT FROM AUTHOR]

Intrapreneurship has long been recognised as a way to develop competitive advantages. This is particularly evident in small and medium-sized enterprises (SMEs), so the intrapreneurial orientation (IO) of these companies should be evaluated from multiple perspectives. Research on this topic involves a wide variety of elements that not only have a direct impact on intrapreneurial behaviour but also change over time. Nonetheless, the development of a holistic system for evaluating IO in SMEs appears to be of great interest to academics and practitioners. Based on the epistemological convictions embodied in multiple criteria decision analysis (MCDA), this study sought to combine cognitive mapping techniques and the Choquet integral (CI) to develop a new IO evaluation system for SMEs. To this end, a panel of experienced decision makers with expertise in the subject under analysis was recruited. The results of a practical application of the proposed evaluation system and composite index were validated both by the panel members and a board member of the Entrepreneurship and Innovation Department of the Portuguese Institute for the Support of Small and Medium-Sized Enterprises and Innovation (in Portuguese, Instituto de Apoio às Pequenas e Médias Empresas e à Inovação (IAPMEI)). The contributions and limitations of the proposed dual methodology are also discussed. [ABSTRACT FROM AUTHOR]

Open innovation (OI) has captured increasing interest over recent decades as this approach is linked to higher level organizational ambidextrous strategy, and has become a prerequisite for achieving competitive advantages. Assessing firms’ propensity for OI has, however, turned out to be an increasingly challenging endeavor. This is particularly true for small and medium-sized enterprises (SMEs) due to the myriad of factors that influence these companies’ capability for innovation. To overcome this challenge, this paper sought to integrate two operational research/management science techniques—cognitive mapping and the Choquet integral (CI) (a nonadditive measure and information aggregator)—to identify and prioritize relevant criteria for evaluating SMEs’ propensity for OI, and improving their organizational ambidexterity. To facilitate a real-world application, information was first collected from SME managers and entrepreneurs who agreed to participate in face-to-face group meetings, allowing realism to be incorporated in the decision-making process. The results were validated by both the panel members and project director of COTEC Portugal—a leading think-and-action network for advancing technology diffusion and business innovation cooperation. The findings include that cognitive mapping facilitates the identification and understanding of cause-and-effect relationships between the determinants of OI in SMEs. The CI, in turn, introduces realism into the construction of value functions and the respective assessments of SMEs. The limitations and implications of the proposed system are also discussed. [ABSTRACT FROM AUTHOR]

MACBETH stands for measuring attractiveness by a categorical based evaluation technique. It is a multiple criteria decision analysis technique created by Carlos Bana e Costa and Jean-Claude Vansnick in the early 1990s. Due to both the increasing application of the technique and progress achieved to date, this study aims to conduct a bibliometric literature review on MACBETH. The database for the review contains 192 scientific articles published in scholarly publications indexed in the Scopus database from 1994 to 2016. Although other literature reviews of the technique exist, this study has a different emphasis and uses two distinct citation analysis methods—bibliographic coupling and co-citation—, allowing us to generate new insights regarding some of the most active and influential articles, journals and authors, as well as to reveal rankings, clusters of contributions and collaboration networks. The results obtained are important to enhance our understanding of the technique's anatomy (i.e., its intellectual structure), and can support the identification of new lines of application and development. [ABSTRACT FROM AUTHOR]

Social credit enhances countries' economic and social development. Few studies, however, have addressed this issue or, more specifically, have focused on social credit risk assessment. This evaluation process is often influenced by various factors, and, in many contexts, it is poorly understood or analyzed in ways that fail to take reality into account. This study is based on the principles of multiple criteria decision analysis (MCDA), as well as on an integrated use of cognitive mapping and the interactive multiple criteria decision making approach (i.e., TODIM). The objective was to develop an idiosyncratic decision support mechanism for identifying underlying criteria and calculating their corresponding weights (i.e., trade-offs) in risk assessments of social credit applications. This socio-technical approach was grounded in face-to-face work sessions with a panel of experts in credit risk analysis. The results reveal that the proposed methodological combination provides value to the process of evaluating social credit applications because of the privileged contact established with specialized know-how. The study's advantages, limitations, and practical implications are also discussed. [ABSTRACT FROM AUTHOR]

Social credit is a type of micro-credit aiming at fighting poverty and social inequality. Although interest in this type of credit has increased significantly over time, namely after Muhammad Yunus was awarded the 2006 Nobel Peace Prize, there are few studies that address the assessment of social credit applications. This is an issue to be taken seriously primarily because the objectives of social credit differ from those of other types of credit, meaning that social credit applications should not be evaluated using the same credit-scoring systems. Assuming the baseline principles of the multiple criteria decision analysis (MCDA) approach, this study combines cognitive mapping and measuring attractiveness by a categorical-based evaluation technique (MACBETH) to develop an evaluation system for social credit applications. The results show that the social-technical approach followed in this study provides value for the evaluation processes of this type of credit application as a result of the privileged contact established with a panel of credit analysts. The advantages, limitations and managerial implications of our study are also discussed. [ABSTRACT FROM AUTHOR]

Resilience is an increasingly important concept in current socioeconomic landscapes. Due to the competitive global context in which we live, this trend is particularly noticeable in small and medium-sized enterprises (SMEs). Due to their limited resources and capabilities, these firms are exposed to unfavourable scenarios that can threaten their stability, viability, and development (i.e., their resilience). Thus, identifying the determinants of SME resilience and their respective cause-and-effect relationships is a vital endeavour because these companies' resilience involves a wide variety of conceptual or theoretical issues that need to be understood more fully. This study proposes the creation of a fuzzy cognitive map as a novel way to analyse the determinants of SME resilience. The fuzzy cognitive map was developed based on the insights obtained during two intensive group meetings with a panel of SME managers and entrepreneurs. The resulting well-informed, process-oriented framework contains the determinants that need to be considered in this research context. The static and dynamic analyses carried out produced an improved understanding of the cause-and-effect relationships between determinants of SME resilience, which facilitates better strategic planning by these firms' managers. The practical implications, advantages, and limitations of the proposed approach are also discussed. [ABSTRACT FROM AUTHOR]

Exponential increase in economic activity and high levels of consumption have hindered long-term planning and made the sustainable management across different areas more difficult. Given this context, decision problems have been complicated by an ever-greater degree of complexity, forcing decision makers to seek out new approaches and methodologies that facilitate the processes that support decision-making. MCDM and MCDA are now well-known acronyms for multiple-criteria decision-making and multiple-criteria decision analysis, respectively. Due to MCDM/A methods' exponential growth over the past few years, this special issue sought to bring together recent developments and methodological contributions within MCDM/A for economic development, social cohesion and environmental sustainability. All contributions relate to the 2030 Agenda for Sustainable Development, and were selected based on the way they relate to the Agenda's sustainable development goals (SDGs). [ABSTRACT FROM AUTHOR]

During the last years, the new science of cities has been established as a fertile quantitative approach to systematically understand the urban phenomena. One of its main pillars is the proposition that urban systems display universal scaling behavior regarding socioeconomic, infrastructural and individual basic services variables. This paper discusses the extension of the universality proposition by testing it against a broad range of urban metrics in a developing country urban system. We present an exploration of the scaling exponents for over 60 variables for the Brazilian urban system. Estimating those exponents is challenging from the technical point of view because the Brazilian municipalities’ definition follows local political criteria and does not regard characteristics of the landscape, density, and basic utilities. As Brazilian municipalities can deviate significantly from urban settlements, urban-like municipalities were selected based on a systematic density cut-off procedure and the scaling exponents were estimated for this new subset of municipalities. To validate our findings we compared the results for overlaying variables with other studies based on alternative methods. It was found that the analyzed socioeconomic variables follow a superlinear scaling relationship with the population size, and most of the infrastructure and individual basic services variables follow expected sublinear and linear scaling, respectively. However, some infrastructural and individual basic services variables deviated from their expected regimes, challenging the universality hypothesis of urban scaling. We propose that these deviations are a product of top-down decisions/policies. Our analysis spreads over a time-range of 10 years, what is not enough to draw conclusive observations, nevertheless we found hints that the scaling exponent of these variables are evolving towards the expected scaling regime, indicating that the deviations might be temporally constrained and that the urban systems might eventually reach the expected scaling regime. [ABSTRACT FROM AUTHOR]

The impact of small and medium-sized enterprises' (SMEs) activities on the environment has proved to be negative in certain contexts, since these companies have not, for the most part, included environmentally sustainable practices in their processes, strategies, or long-term vision. Therefore, SMEs need to start adopting more environmentally-friendly behaviors to ensure a better future for coming generations. SMEs have failed to do this until now – despite making a significant effort – in part because dealing with this issue is a quite subjective process and a variety of aspects need to be considered. The current study sought to address this problem through the integrated application of cognitive mapping and the Analytic Hierarchy Process (AHP). Based on a constructivist approach, group sessions involving a panel of entrepreneurs and environmental experts created, tested, and validated a green index for SMEs that addresses two of the major limitations of current evaluation approaches. The first limitation is the manner in which evaluation criteria have been defined within the scope of SME environmental conduct assessments, while the second is the method with which these same criteria's weights – or trade-offs – are calculated. The proposed index produced promising results when used to identify the most environmentally-friendly SMEs in a sample of firms. These results can be used as benchmark data for environmental improvement initiatives, and the findings confirm that the methodologies underlying the proposed model-building process facilitate a clearer understanding of how to evaluate SMEs' pro-environmental behaviors. The advantages and limitations of the proposed index are also discussed. [ABSTRACT FROM AUTHOR]

The recent economic crisis led to significant changes in the real estate market; one of which was a shift toward home rental (rather than buying). Real estate investors have an important role in the growth of the rental market. However, there are often hindrances to investing for residential rental purposes. In order to overcome these barriers, they first need to be identified and understood. With this in mind, the main focus of this investigation was the creation of a conceptual model, through fuzzy cognitive mapping, to identify and understand the cause-and-effect relationships between the factors that represent an obstacle to real estate investments for residential rental purposes. The results show that cognitive maps can be of great use for the structuring of complex decision problems, minimizing the number of factors left out of the decision-making process. In particular, the tenant risk behavior, property location and associated costs (for the owner) were identified as the main obstacles to real estate investment. The practical implications of the model, as well as the advantages and limitations of the process followed, are also discussed. [ABSTRACT FROM AUTHOR]

As interest in sustainability-related issues has increased over recent years, so too hasurbansustainability risen to the fore, in academic, practitioner, and policymaking circles alike. Urban sustainability requires a balance between environmental concerns, the economy, and social development in urban areas. However, over the years, there has been an exponential increase in urban density, accompanied by increased economic activity and high levels of consumption, which have hindered urban planning and made the sustainable management of urban areas more difficult. It has therefore become increasingly necessary to combine the interests of the various stakeholders involved in – or affected by – urban planning measures, in order to achieve a balance between their needs, those of the environment and future generations, and the need for economic development. Sustainability evaluation models can in this sense be considered a baseline condition for sustainable development. However, most existing evaluation systems present limitations in terms of criteria identification and the calculation of the respective trade-offs. To address these issues, the current study aims to combine cognitive mapping and the Analytic Hierarchy Process (AHP) to prioritize the determinants of sustainable development in urban areas. The advantages and limitations of our proposal are also analyzed. [ABSTRACT FROM AUTHOR]

Choosing a tenant is a key issue in the housing rental market. Knowing, a priori, whether a tenant will pay the rent on time, be able to hold a good relationship with the neighbors or take care of the property (i.e. whether s/he will be a "good" tenant) is not a simple endeavor. It is crucial, however, as it can help save time, money and conflicts that can end up in court. This study aims to address this issue, through the integrated use of cognitive maps and the Decision EXpert (DEX) technique. Grounded on a constructivist logic, the study brought together a panel of experts with experience and knowledge in the residential rental market, in order to identify and articulate the criteria to be taken into account in the classification and selection of tenants. The results achieved show that the integration of these two methodologies (i.e. cognitive maps and DEX) can help increase our understanding of the decision problem at hand, and lead to more informed and potentially better tenant choices. Advantages and limitations of the framework are also discussed. [ABSTRACT FROM AUTHOR]

Risk analysis of residential real estate investments requires careful analysis of certain variables (or determinants). Because real estate is a key sector for economic and social development, this risk analysis is seen as critical in supporting decision processes relating to buying or selling residential properties, partly due to the pressures caused by the current economic environment. This study aims to develop a conceptual reference model for risk assessment of residential real estate using fuzzy cognitive mapping. This fuzzy model allows cause-and-effect relationships between determinants to be identified and better understood, which in turn allows for better informed investment decisions. The results show that the use of cognitive maps reduces the number of omitted criteria and favors learning with regard to how the criteria relate to each other, holding great potential and versatility in structuring complex decision problems. Practical implications, strengths and weaknesses of our proposal are discussed. [ABSTRACT FROM AUTHOR]

Factories of the Future roadmap identifies that the major challenges manufacturing companies face today are the growing complexity of their processes, therefore affecting the overall process of decision making. Thus, it is a very important research area to integrate the evolving technologies in the domain of Internet of Things (IoT) into the applications used for project management. At the same time, to capture events on the shop-floor and determine the meaning of information about those perceived events would be an important aspect for making decisions in heterogeneous, highly dynamic environments. This research paper aims to provide a framework for efficient project management by reducing the time for decision-making based on IoT technologies. The goal is pursued by dynamically establishing situational awareness on the top of existing manufacturing processes. The proposed framework is validated in real industrial scenario by implementing a platform for efficient project management within the domain of construction industry. [ABSTRACT FROM PUBLISHER]

Rapid population growth and urbanization have a strong impact on individuals' well-being. These trends are currently important topics in city management. As a significant driver of digitalization, technological development has been found to have great potential as a mitigator of a wide range of issues that cities face. To ensure the available technologies are being correctly used, municipalities need to measure their degree of digitalization. This assessment is also important to improve city officials' understanding of areas that need interventions so that cities can be managed better and provide their residents with a better quality of life. This study applies the baseline principles of the multiple-criteria decision analysis (MCDA) approach to develop a decision-support system that facilitates urban digitalization evaluations. The results rely on insights provided by a panel of experts in this area, who used cognitive mapping and the best worst method (BWM) to identify important evaluation criteria within urban digitalization and to analyze their cause-and-effect relationships. The final outcomes were validated by the panel members and representatives of the Associação Nacional de Municípios Portugueses (i.e. , National Association of Portuguese Municipalities) and the Agência National de Inovação (i.e. , National Innovation Agency). These specialists confirmed that the evaluation system developed facilitates city differentiation in key areas of urban digitalization. The advantages and limitations of the proposed procedures are also discussed. • This study contributes to a holistic understanding of urban digitalization. • The proposed system overcomes some limitations of purely statistical methods. • Cognitive mapping improves the selection of evaluation criteria. • BWM allows criteria weights to be calculated. • The system created allows urban digitalization to be evaluated. [ABSTRACT FROM AUTHOR]

Greater competition and the aftermath of the financial crisis have meant that banks are increasingly focused on improving service quality and achieving higher levels of customer loyalty. Doing so requires being able to identify, understand and measure the determinants of such loyalty, however; and given the variety of multi-faceted factors involved, and the interrelationships among them, this is a complex undertaking. This paper proposes and tests an integrated application of cognitive mapping and multiple criteria decision analysis (MCDA), thus combining metacognitive and psychometric decision-making approaches, to create a framework for the assessment of bank customer loyalty, which identifies its determinants and allows the trade-offs among them to be calculated. Practical advantages and limitations of our proposal are also discussed. [ABSTRACT FROM AUTHOR]

In the current competitive environment, great emphasis is placed on the knowl- edge and skills of the workforce as important elements in achieving organizational goals. As this focus on employee skills has increased, so have organizational programs and initiatives to ensure that the training in place to develop those skills is not sporadic, but rather part of a continuous effort toward keeping employee skills up to date. It becomes fundamental, in this context, to understand such programs and evaluate their impact, both within companies and externally, in terms of their decision making and business results. This paper aims to do that, through a study of the work-related training practices of in- dustrial firms in the Northern-Spanish region of Asturias. In addition, it develops a new variable –training intensity– and examines its impact on the planning, execution and evaluation of training programs in these firms. Among other findings, our study confirms that training-intensive firms have a more defined strategic approach to the market and are generally more conscious of business competition than their non-training-intensive competitors. Implications for management are also presented. [ABSTRACT FROM AUTHOR]

Bank customer loyalty is becoming a priority concern for banking institutions, as a means of gradually increasing complementary margins and eliminating the lack of liquidity caused by the current economic climate. Following a top down process, this focus culminates at the branch level, where banks’ front office employees are seen as a driving-force for building customer loyalty. At the same time, however, the difficulty in identifying and operationalizing the factors or determinants that most contribute to creating and maintaining bank customer loyalty has long been recognized. In this sense, based on the integrated use of cognitive maps and measuring attractiveness by a categorical based evaluation technique (MACBETH), this study proposes a multiple criteria framework for bank customer loyalty measurement and management. The results show that our framework allows bank customers with higher rates of customer loyalty to be identified and, from a benchmarking perspective, indicates what best practices should be followed to boost long-term relationships. Implications for scholars and practitioners are discussed. [ABSTRACT FROM PUBLISHER]

Most banks have been negatively affected by the recent economic recession, which has forced them to evaluate their operating performance including the financial performance of bank branches. Approaches that have been applied to address the financial performance evaluation of bank branches include: optimization techniques, simulations, stochastic tools, fuzzy logics and decision support systems. Although recent improvements have been made in assessing financial performance, the potential for significant further improvement remains since the recent world economic crisis is adding pressure on business margins. The purpose of this paper is to construct an exemplificative evaluation index for bank branch financial performance by integrating cognitive maps with measuring attractiveness by a categorical based evaluation technique. We aim to apply this methodology constructively to serve as a learning mechanism and introduce transparency in the decision making process. Practical applications, strengths and weaknesses of the proposed evaluation index are also discussed. [ABSTRACT FROM PUBLISHER]

Purpose – Considered the largest investment for most households, buying a house requires careful and transparent analysis by all parties involved in the transaction. The aim of this paper is to propose a methodological framework allowing for the readjustment of trade-offs among risk evaluation criteria, considered of extreme importance in the lending decision process of mortgage loans. Design/methodology/approach – Multiple criteria decision analysis (MCDA) has proved over the years to be effective and versatile in handling compensations among criteria. Measuring attractiveness is applied by a categorical based evaluation technique (MACBETH) to a pre-established structure of credit-scoring criteria for mortgage lending risk evaluation. This pre-established structure is currently used by one of the largest banks in Portugal. Findings – The framework allowed the authors to provide the credit experts who participated in the study with a more informed, transparent and accurate mortgage-lending risk-evaluation system. The sensitivity and robustness analyses carried out also helped in promoting discussion and supporting the readjustments made. Research limitations/implications – The study shows the usefulness of using the MACBETH approach to assist credit analysts in making better informed decisions, and opens avenues for further research. However, due to the dependence on the participants involved, extrapolations without proper caution are discouraged. Practical implications – The credit analysts who participated in this study considered the framework more discerning in terms of Basel directives. Originality/value – The integration of MACBETH and credit-scoring mechanisms holds great potential for risk assessment and decision support. No prior work reporting the application of MACBETH in terms of mortgage-lending risk-evaluation is known. [ABSTRACT FROM AUTHOR]

Claimed by the Harvard Business Review as one of the main innovations of recent decades in management systems, the Balanced Scorecard (BSC) has been widely studied and applied in different management contexts. However, despite recent progress and its undeniable merit, the BSC has its own shortcomings. As reported in the literature, it seems generally agreed that the way compensations between criteria within a BSC framework are calculated remains an open issue. Thus, one of the contributions of this study is to augment the theoretical discussion on the potentialities of the multiple criteria decision analysis (MCDA) approach to bring simplicity and transparency to the calculation of compensations (i.e. trade-offs) among evaluation criteria within a BSC framework. It seems important to underline that this paper builds on previous work and is not empirical research. However, it aims to extend the discussion to other (new) measurement contexts. We believe that the development and promotion of the integrated use of MCDA tools in BSC applications to measure trade-offs among evaluation criteria in the BSC framework can be a key factor in ensuring more successful implementations and uses of the BSC within firms. [ABSTRACT FROM AUTHOR]

Remarkable progress has occurred over the years in the performance evaluation of bank branches. Even though financial measures are usually considered the most important in assessing branch viability, we posit that insufficient attention has been given to other factors that affect the branches' potential profitability and attractiveness, such as: location features, trade area characteristics and facilities management. Based on the integrated use of cognitive maps and multiple criteria decision analysis, we propose a framework that adds value to the way that potential attractiveness criteria to assess bank branches are selected and to the way that the trade-offs among those criteria are obtained. This framework is the result of a process involving several directors from the five largest banks operating in Portugal, and follows a constructivist approach. Our findings suggest that the use of cognitive maps systematically identifies previously omitted criteria that may assess potential attractiveness. The use of multiple criteria techniques clarify and add transparency to the way trade-offs are dealt with. Advantages and disadvantages of the proposed framework are also discussed. [ABSTRACT FROM AUTHOR]

Substantial population growth, increasing urbanization, overloaded infrastructure, more energy consumption, environmental impacts, and investment in technological developments are major challenges in city management and development. Municipalities seek to improve their citizens' wellbeing and quality of life, but the need to find a balance between these complex factors makes decision-making processes more difficult. Experts must analyze the determinants of smart cities, which are urban centers intended to be socially involved, habitable, and economically and environmentally sustainable, and that rely strongly on technology and innovation. Based on multiple-criteria decision analysis (MCDA) principles, this study combines cognitive mapping techniques and the decision-making trial and evaluation laboratory (DEMATEL) method to develop a multicriteria model that can help managers analyze smart city determinants in a collaborative manner. The research included identifying these determinants and their respective cause-and-effect relationships using an expert panel's experience and knowledge related to the subject under analysis. The results were validated by both the panel and the city councilor responsible for mobility and municipal projects within Évora City Council, Portugal, which has implemented smart city strategies. The latter specialist verified that the proposed evaluation system can be used as a tool to facilitate smart city collaborative decision-making processes. The study's main advantages and limitations are also analyzed and discussed. • This study contributes to a collaborative understanding of smart city. • The proposed approach overcomes some limitations of purely statistical methods. • Cognitive mapping and DEMATEL improve understanding of causal relationships. • Our proposal supports the formulation of smart city development strategies. [ABSTRACT FROM AUTHOR]

• This study contributes to a holistic understanding of urban blight. • The proposed approach overcomes some limitations of purely statistical methods. • Cognitive mapping and DEMATEL improve understanding of cause-and-effect relationships between decision criteria. • The combined use of cognitive maps and DEMATEL supports the formulation of anti-blight intervention strategies. Urban blight has been the subject of numerous worldwide studies. However, because of blight's complexity, direct relationship with ​​urban planning and multifaceted associated variables, studies targeting certain aspects of blight require detailed conceptualization and structure to facilitate decision-making processes that address blight. Many urban, socio-economic and cultural externalities associated with blight need to be addressed in developing viable intervention strategies for prevention, attenuation and eradication. Identifying and simplifying the complex issues associated with blight is important as their intricacy creates difficulties for decision makers. We simplify the blight problem by using unique techniques for structuring complex decision problems (i.e. , problem structuring methods (PSMs)). This methodology is based on multiple-criteria decision analysis (MCDA) principles, as well as a combination of participatory techniques (i.e. , decision conferencing and cognitive mapping). In a subsequent phase, the decision-making trial and evaluation laboratory (DEMATEL) technique is used to enable the development of a more realistic, transparent analysis model for blight intervention strategies. This study assumes a constructivist logic, so both objective and subjective elements are included. The proposed methodology's advantages and limitations are also discussed. [ABSTRACT FROM AUTHOR]

The process of identifying and analyzing proactive measures for the prevention of urban blight is complicated by its complexity and death of data. Blight affects people's lives in many ways, including economically, socially, psychologically, and physically. The phenomenon comprises many factors, including making appropriate identification and eradication decisions that are challenging to analyze and structure. This study took a constructivist stance and sought to develop a new approach to urban blight to complement the existing literature. The methodology combined cognitive mapping techniques applied in decision conferences, and the decision making trial and evaluation laboratory technique based on the multiple-criteria decision analysis approach. This integrated approach facilitated the development of a multi-criteria model that identifies proactive anti-blight measures in a more complete, transparent way. This dual methodology enables incorporating objective and subjective elements, and field specialists' knowledge and experiences, thereby reducing important decision criteria omissions. Additionally, this approach generates a transparent visualization of relationships among criteria. Identified blight determinants can be used to prevent blight, and improve the quality of life in the affected areas. These strategies were carefully analyzed by two independent experts from the Direção Geral do Território (General Directorate of the Territory of Portugal). The advantages and limitations of the proposed methodology are also deliberated. • This real-world study contributes to a holistic understanding of urban blight. • The process-oriented approach followed overcomes some limitations of purely statistical methods. • Cognitive mapping and DEMATEL improve the understanding of proactive anti-blight strategies. • No prior research was found that has adopted the proposed methodology in this study context. [ABSTRACT FROM AUTHOR]

• Proposition of a mean-CVaR portfolio optimization model with integer variables. • Development of an evolutionary algorithm for solving the proposed model. • Comparison of proposed and existing multi-attribute decision-making methods. • Trading simulations show that investor profiles affect gains provided by the method. This paper proposes an integer multiobjective mean-CVaR portfolio optimization model with variable cardinality constraint and rebalancing and two different methods of decision-maker used to guide and select, according to the decision maker preferences, a solution comes from the non-dominated portfolios generated by a proposed evolutionary algorithm. The decision-making methods were used to approximate investor behavior according to three functions, chosen to represent different investor profiles (conservative, moderate and aggressive). The proposed methods are compared with those found in the literature. Additionally, computational simulations are performed using assets from the Brazilian stock exchange for the period between January 2011 and December 2015. The strategy is that each beginning of the month: the previous portfolio is sold, the optimization is performed, and the decision-making method selects the new portfolio to be purchased. Results of the simulations consider monthly maximum drawdown and cumulative return during the entire study period and show that the optimization model is robust, considering the three simulated profiles. The methods always present cumulative returns above safe investments for the analyzed period, and the aggressive profile obtained bigger gains with greater risk. [ABSTRACT FROM AUTHOR]

Human beings live in a networked world in which information spreads very fast thanks to advances in technology. This helps to promote conflicts that lead to the dominance of certain ideologies, set of values, belief or opinion. Such conflicts can lead to a decrease in freedom, oppression and to the deterioration of established institutions. Here, we propose a simple model to study, to a certain extent, this class of problems. We look at interacting agents connected in networks to analyze the multi-agent decision stochastic process. Each individual decision may be influenced by others' decisions. We consider a first neighbor interaction between agents in one-dimensional network. Some agents are also connected to a hub, or master node, who has preferential opinions. The role of the master node is to persuade others to follow a specific orientation, in which there is a probability of successful persuasion. The connections between master node and the network society are quenched disorder. Using a simple model, we found a phase transition from disorder to order for three different control parameters. The evidence for the phase transition in the model was obtained by finite-size scaling analysis. In addition, we present an analytical result via the mean-field approximation. Finally, we discuss how this model may be useful as a framework to study the spread of morality, innovation, opinion formation and consensus. • We study the emergence of consensus by a stochastic quenched model. • The model is a mixture of deterministic and stochastic dynamical rules. • The critical exponents depend on the three control parameters • We found an absorbing phase transition to consensus. [ABSTRACT FROM AUTHOR]