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The purpose of this paper is to observe how to invest in upper-middle income countries via an innovation perspective following global innovation index (GII) by multicriteria decision aid (MCDA) approach, once MCDA was designed to support subjective decisions.

Pearson’s correlation was the milestone for understanding innovation indicators at upper-middle income countries profiles. In a MCDA first step, the analytical hierarchy process (AHP) was applied to obtain the criteria weight. In this step, the judgments or evaluations inputted in AHP were collected from a sample composed by five experts in GII. After getting the criteria weights compose to GII, Borda and Preference Ranking Organization Method for Enrichment Evaluations (PROMÉTHÉE) methods were applied to obtain an MCDA-based GII. The inputs for this second step were: the weights come from AHP output; and the countries performance came from GII data.

As a result, it was found out the upper-middle countries’ rank to invest and groups with countries acting like “hubs” or “bridges” for economic sectors in near countries; when they are grouped according to their maximum and minimum scores profiles, observing not only a particular region but also similar profiles at diverse world areas.

Pearson-AHP-PROMÉTHÉE works as a supportive decision tool for several and complex investment perspectives from criteria and alternatives analysis regarding innovation indicators for upper-middle income countries. This combination also demonstrates grouping possibilities, aligning profiles and not only ranking countries for investment and eliminating others but also grouping countries with similar profiles via innovation indicators MCDA combined application.

Policy makers are frequently challenged by the need to achieve sustainable development in cities and regions. Current decision-making processes are based on evaluation support systems which are unable to tackle the problem as they cannot take a holistic approach or a full account of actors. The purpose of this paper is to present a new generation of evaluation systems to support decision making in planning and regeneration processes which involve expert participation. These systems ensure network representation of the issues involved and visualization of multiple scenarios.

A literature review is used for both revising existing evaluation tools in urban planning and the built environment and highlighting the need to give stakeholders (industry, cities, operators, etc.) new tools for collaborative or individual decisions and to facilitate scaling up solutions. An overview of the new generation of decision support systems, named Multicriteria Spatial Decision Support Systems (MC-SDSS) is provided and real case studies are analyzed to show their ability to tackle the problem.

Recent research findings highlight that decisions in urban planning should be supported by collaborative and inclusive processes. Otherwise, they will fail. The case studies illustrated in this study highlight the usefulness of MC-SDSS for the successful resolution of complex problems, thanks to the visualization facilities and a network representation of the scenarios.

The case studies are limited to the Italian context.

These SDSS are able to empower planners and decision makers to better understand the interaction between city design, social preferences, economic issues and policy incentives. Therefore, they have been employed in several case studies related to territorial planning and regeneration processes.

This study provides three case studies and a review of the new MC-SDSS methodology which involve the Analytic Network Process technique to support decision-making in urban and regional planning.

Investigation of housing adaptability is related to understanding factors that influence project transformation. Factors may be associated with the design and project stage as also alternative uses to existing buildings. To structure methodology for criteria analysis of adaptability, the research aims to verify the importance level of factors related to adaptability and flexibility context in architecture.

Employing a multicriteria analysis and a diagnosis performed with architecture professionals, criteria importance identified in a bibliographic survey is contacted.

With harmonious results, key elements highlighted in the diagnosis are discussed. Adaptability and flexibility are mainly related to balance in the design of spaces and their connections, so the user can have control administrating the organization of their habitat.

As a complex subject, involving legal, social and cultural issues, the multicriteria method supports the scientific analysis of data. The results can be used in a practical case study as assessment of housing adaptability and flexibility, as a useful tool to decision support in architectural project.

The purpose of this study is to evaluate the effectiveness of the new service development (NSD) process in tourism. For this reason, factors influencing the process of service innovation in the hospitality sector were explored and correlated with business performance in the hospitality industry through a multicriteria decision analysis approach.

An original multicriteria decision analysis approach is applied in order to estimate the efficiency of the NSD process. The approach follows the principles of ordinal regression analysis, using goal programming techniques. Collected data are based on in-depth structured and questionnaire-based interviews of 77 hotel managers in 147 new services in a representative sample of 99 hotels in Greece. Several financial ratios, covering different aspects of business performance, are used in order to evaluate the NSD process for three years after the services innovation had been launched.

These findings reveal the importance of financial liquidity and business efficiency for the hotel industry (i.e. the ability of a firm to use available resources in order to achieve specific sales goals). The aforementioned variables can determine how quickly and effectively assets are converted to cash. In general, the findings show the emphasis that should be given to customer needs, as well as to the effective management of a NSD project.

Findings of this study may support hotel managers to make complex strategic decisions for future development. These findings have suggested that service innovation should be included as a strategic tool to assess differentiation effort in the hotel industry.

The purpose of this paper is to identify how multicriteria decision aid (MCDA) can assist the investment portfolios formation, increasing the reliability of decision-making.

To develop this paper, a simulation-based approach is used. Information about the assets traded on the spot market of the São Paulo Stock Exchange - BM&FBOVESPA was selected. They had 100 per cent participation in the 246 trading sessions carried out in 2015 and had an average number of business/day greater or equal to 1,000. The stratification resulted in the selection of 111 assets. Aiming assets evaluation, data are collected from 21 financial indicators. Subsequently, the principal component analysis (PCA) is used to reduce the mass of collected data without the loss of essential information. PROMETHEE II method is used for assets ranking; it belongs to the group of methods for MCDA. At the end of these stages, four groups of investment portfolios are created for simulation.

After the construction of portfolios, a simulation was performed with real data of the assets from January 03, 2011 to November 14, 2016. It resulted in a comparison in which it was observed that 100 per cent of portfolios showed positive returns on the investment. The result of portfolios’ group composed of assets based on the 21 financial indicators was higher than the other one formed from PCA criteria. Both of them were higher than Ibovespa result in the same period.

As a contribution to new research, the model presents an opportunity for improvement through linear programming methodologies with the objective of optimizing the results, as the results obtained with the model were not optimized.

This research presents an alternative logic to the traditional one, as it seeks the reduction of investment risk based on the results of the management of the companies, reflected through their indicators. The model implies a change in how companies, financial institutions and small and medium investors choose their assets to form investment portfolios. The authors believe that the model has the potential to attract investors looking for long-term gains, such as public servants, retirees, professionals and others who seek to build heritage to overcome the adversities of the uncertain future. The model offers these investors the opportunity to choose which companies to invest in, based on established indicators in the literature, whose information is available in the market. The model systematizes the information and builds a ranking of the best companies so that the investor can make a conscious decision, thus avoiding what experts call a “herd effect”, which makes the majority of investors decide according to the oscillation of the market, thus ignoring the financial fundamentals of companies.

This study presents a proprietary methodology by merging the PCA tool with MCDA to build efficient investment portfolios.

The purpose of this study is modelling of a problem of policing strategy order using a multicriteria method.

For the construction of the impact matrix strategies under the reduction of crime rates, considering a portfolio of crimes, a questionnaire applied to specialists was used. In a second moment, defined the criteria and strategies to be ordered, the multicriteria PROMETHEE II method was used, which with the help of the Visual PROMETHEE software, emulated the systematised data in the impact matrix and produced the final ordering of the most efficient strategies, in the fight against crime, in the perception of decision makers.

As a result, this research revealed that radio patrol, when used in a non-randomised manner, is the most effective policing strategy in reducing the 18 criminal demands studied in the perception of decision makers after data emulation with the PROMETHEE II method.

As research implications, it can be inferred that the use of multicriteria methods in the modelling of problems in public security area can contribute to the rationalisation of use of the available means in the fight against crime in large cities. This research showed that it is possible to use customised policing strategies to absolute reality.

The practical impact of this research lies in optimising the resources available to law enforcement agencies in the fight against crime in general.

It can be inferred that by choosing appropriate strategies to combat local crime, there is a direct implication in optimising the resources that the government makes available to police agencies. This optimisation allows pressure reduction under the public budget for more features. The model for choosing more effective strategies contributes to local crimes decrease, increasing the sense of the population security.

The originality lies in filling a gap in the literature with the elaboration of the impact matrix of policing strategies in reducing criminal indices and in their associated use in ordering strategies through a multicriteria method. This study contributed to applied police intelligence.

The financial crisis of 2007–2008 has brought critical attention to those financial institutions whose high destabilizing effects can have an impact on the financial system. Basel Committee (BIS) has introduced a set of regulations to identify such banks, defined global systemically important banks (G-SIBs). The purpose of this paper is to investigate the robustness of the BIS's methodology.

In this study, a multicriteria decision aid (MCDA) approach is considered, specifically HSMAA (hierarchy stochastic multiobjective acceptability analysis), which can take into account uncertainty on BIS's criteria weights as standard SMAA, but also uncertainty with respect to the subcriteria of the considered criteria. The results are analyzed to provide insights into the robustness of the BIS's methodology.

The obtained results indicate that overall the BIS's methodology does not appear robust. Within the two uncertainty scenarios considered, the results show a great variability in identifying the G-SIBs' systemic risk.

The paper proposes an analytical way to assess the robustness of the BIS's methodology. Moreover, the authors’ analysis reveals a great variability on the results, which highlight different issues for banks, regulators and enterprises.

Environmental decision making involving multiple stakeholders can benefit from the use of a formal process to structure stakeholder interactions, leading to more successful outcomes than traditional discursive decision processes. There are many tools available to handle complex decision making. Here we illustrate the use of a multicriteria decision analysis (MCDA) outranking tool (PROMETHEE) to facilitate decision making at the watershed scale, involving multiple stakeholders, multiple criteria, and multiple objectives. We compare various MCDA methods and their theoretical underpinnings, examining methods that most realistically model complex decision problems in ways that are understandable and transparent to stakeholders.

This paper is focused on developing an integrated algorithmic approach named as data envelopment analysis and multicriteria decision-making (DEA-MCDM) for ranking decision-making units (DMUs) based on cross-efficiency technique and subjective preference(s) of the decision maker.

Self-evaluation in data envelopment analysis (DEA) lacks in discrimination power among DMUs. To fix this, a cross-efficiency technique has been introduced that ranks DMUs based on peer-evaluation. Different cross-efficiency formulations such as aggressive and benevolent and neutral are available in the literature. The existing ranking approaches fail to incorporate subjective preference of “one” or “some” or “all” or “most” of the cross-efficiency evaluation formulations. Therefore, the integrated framework in this paper, based on DEA and multicriteria decision-making (MCDM), aims to present a ranking approach to incorporate different cross-efficiency formulations as well as subjective preference(s) of decision maker.

The proposed approach has an advantage that each of the aggressive, benevolent and neutral cross-efficiency formulations contribute to select the best alternative among the DMUs in a MCDM problem. Ordered weighted averaging (OWA) aggregation is applied to aggregate final cross-efficiencies and to achieve complete ranking of the DMUs. This new approach is further illustrated and compared with existing MCDM approaches like simple additive weighting (SAW) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prove its validity in real situations.

The choice of cross-efficiency formulation(s) as per subjective preference of the decision maker and different orness levels lead to different aggregated scores and thus ranking of the DMUs accordingly. The proposed ranking approach is highly useful in real applications like R and D projects, flexible manufacturing systems, electricity distribution sector, banking industry, labor assignment and the economic environmental performances for ranking and benchmarking.

To prove the practical applicability and robustness of the proposed integrated DEA-MCDM approach, it is applied to top twelve Indian banks in terms of three inputs and two outputs for the period 2018–2019. The findings of the study (1) ensure the impact of non-performing assets (NPAs) on the ranking of the selected banks and (2) are enormously valuable for the bank experts and policy makers to consider the impact of peer-evaluation and subjective preference(s) in formulating appropriate policies to improve performance and ranks of underperformed banks in competitive scenario.

To the best of the authors’ knowledge, this is the first study that has integrated both DEA and MCDM via OWA aggregation to present a ranking approach that can incorporate different cross-efficiency formulations and subjective preference(s) of the decision maker for ranking DMUs.

Because that the crime in a wide way impacts the life of the people in the big metropolis, researchers have treated the question from several angles. The purpose of the paper, under the umbrella of operational research, is to develop a model of the ordering of police strategies, in the fight against crime in general, according to a certain criminal demand.

For the construction of the impact matrix of the strategies under the reduction of crime rates, considering a portfolio of crimes, a questionnaire applied to specialists was used. In a second moment, defined the criteria and strategies to be ordered, the multicriteria ELECTRE IV method was used, which with the help of the J-Electre software emulated the systematized data in the impact matrix and produced the final ordering of the most efficient strategies, in the fight against crime, in the perception of decision-makers.

As a result, the research revealed that policing strategies directed at solving specific crimes are the most effective in the perception of decision-makers after the emulation of data with the ELECTRE IV method.

As research implications, it can be inferred that the use of multicriteria methods in the modeling of problems in the area of public security can contribute to rationalization of the use of the means available in the fight against crime in large cities. The research showed that it is possible to use customized policing strategies to a certain reality.

The method presented in this research is directly related to the major strategies: problem-oriented policing and hot spot policing. This method allows public safety managers to consider the possibility of combining different law enforcement strategies in each context. In this sense, the use of the multiple-criteria decision analysis (MCDA) (ELECTRE IV) method allows the evaluation of a large set of alternatives according to a set of established criteria, speeding up the process and reducing subjectivity, allowing the manager to analyze several scenarios with greater clarity and impartiality and choosing an alternative that best solves the proposed problem. The expected result is the rationalization of the available means applied in the search for the reduction of crime rates.

The customization of policing strategies, according to criminal demands, implies the efficient way to reduce criminal charges. Reducing criminal rates enables the development of the local economy, tourism and the quality of life of people by exercising their freedom to the full.

The originality lies in filling a gap in the literature with the elaboration of the impact matrix of policing strategies in reducing criminal indices, and in their associated use in ordering strategies through a multicriteria method.