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Supplier Selection (SS) is one of the vital decisions frequently executed by numerous industries. In recent times, the number of suppliers has increased enormously depending on a wide range of criteria. A selection of suppliers is a sensitive process that may impact various supply chain activities. The purpose of this research is to explore an underutilized technique called PROMETHEE II method for SS.

Various tools and techniques are available under multi-criteria decision-making tools, which sometimes creates confusion in researchers' minds regarding reliability. PROMETHEE II was the most prominent method for ranking all available alternatives that ultimately avoid decision-making errors. To execute this equal and unequal weights approach has been used with three case studies.

In this research, three case studies have been used and soved with the help of the PROMETHEE II approach. The study also provides fundamental insights into the supplier's ranking on different criteria using sensitivity analysis. Further, criteria were divided as per benefits and non-beneficial to get a robust result. The pros and cons of PROMETHEE II approaches are also highlighted compared to other MCDM tools in this study.

Most of the SS research uses either AHP or TOPSIS as per existing literature. There are very few attempts highlighted in the literature that use PROMETHEE II for the SS problem with sensitivity analysis. The proposed method is probable to motivate decision-makers to consider using a more sophisticated method like PROMETHEE II in supplier evaluation processes. This study opens a new direction for the ranking of suppliers in the field of the supply chain. The study also bears significant practical as well as managerial implications.

The purpose of this paper is to prioritize Indian energy sector projects, namely, coal, gas, hydro and solar using fuzzy PROMETHHE (F-PROMETHEE) and Visual PROMETHEE applications and multicriteria decision-making (MCDM) analyses.

The MCDM outranking approach of PROMETHEE under fuzzy environment is used. Four projects of energy sector are selected as alternatives and are compared based on various criteria. These criteria selected on the perspectives of life cycle costing (LCC) analysis and related management approaches for prioritizing projects for effective decision-making (DM). The F-PROMETHEE is described and results are also compared with outranking application in Visual PROMETHEE software based on same set of criteria. For better understanding, the graphical representations of the multicriteria problem are also shown using graphical analysis for interactive aid.

On applying F-PROMETHEE on four energy projects, coal and solar projects outrank high and results shows that coal-based project is preferable and should be considered.

Here F-PROMETHEE and Visual PROMETHEE are used as MCDM techniques. However, few other MCDM techniques such as ELECTRE and EATWOS can be also explored to outrank Indian energy sector projects.

Indian energy sector involves high degree of complexity for effective DM on the front of prioritized investment-related capacity addition through energy projects. Outranking methods like F-PROMETHEE is able to address the criteria to criteria impact on DM support precisely.

The finding can provide information to the government or public sector regarding various possible investment options on energy projects in India.

This paper can be supplement and act as the support for DM in conflicting situations specifically for prioritizing investments on various energy projects, which further can synergize conflicting ideas of various stakeholders of the Indian energy sector.

The purpose of this research paper is to assess efficacy of e-governance implementation, influenced under the Indian-EU (European Union – EU) strategic dialogue. For the same purpose, this study aims to analyse and measure penetration level of information and communication technology (ICT) applications across ten select gross domestic product-dependent sectors (gross domestic product – GDP) in Indian economy.

Multi-criteria decision-making (MCDM) approach of PROMETHEE, using its partial and complete versions in fuzzy environment, is applied. The approach assesses e-governance efficacy in various sectors, which is chosen based on their contribution to GDP, where criteria values are assigned by expert opinions, feedback is received and lessons are learnt from training and initiatives taken under the Digital India programme launched by the Government of India. These criteria related to IT policy implementation, cyber security breaches, IT infrastructure development initiatives in select sectors are identified. Later, sectors outranking results have been highlighted using both fuzzy set theory along with PROMETHEE (F-PROMETHEE) and its visual application.

On applying F-PROMETHEE, studies found that industrial, railways, health and finance and education sectors outrank in their high merit orders. Contrary, outranking shows that agriculture, defence and aerospace sectors should be more open and accessible to adopt ICT applications in order to promote e-governance processes and their implementation to make e-services available to common citizens. For better interpretation of results, graphical analysis for interactive aid is used to present the analyses.

Research study was found useful in the assessment of ICT penetration level in to support Indo-EU relations, where PROMETHEE method is used to outrank sectors alternatives. Criteria are also weighted using fuzzy scale, and the impact of criteria on all alternatives has also been assessed. MCDM framework addresses that subjectivity lies in sectors to implement ICTs bases services. However, few other MCDM frameworks, methods such as COPRAS, GST, GRA, SAW and SWARA, can be used for the same purpose.

Sectors alternative involve high degree of complexity to adopt ICT applications for smooth e-governance and seek effective decision-making for investment prioritization and future development. This study also aims to address cyber security concerns of policymakers. Outranking methods of F-PROMETHEE are able to address the criteria-to-criteria impact and support decision-making in a more precise way.

This study is inspired from the strategic implementation of the framework of the e-Government Action Plan 2016-2020 of the EU. The findings from the paper can provide referential support to the Indian Government and policymakers to support information delivery, implement cyber security policies and various sector developments.

This research study can act as a strong base in the decision-making process in conflicting situations of e-governance in India. This study not only can synergize conflicting ideas of various stakeholders, academicians in the Indian IT-sector but also can act as support to administrators and the policymakers to monitor the status of the India-EU Information Society Dialogue.

In this paper, the four popular multiple-criteria decision-making (MCDM) methods in fuzzy environment are utilized to reflect the vagueness and uncertainty on the judgments of decision-makers (DMs), because the crisp pairwise comparison in these conventional MCDM methods seems to be insufficient and imprecise to capture the right judgments of DMs. Of these methods, as Fuzzy analytic hierarchy process (F-AHP) is used to calculate criteria weights, the other methods; Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (F-TOPSIS), Fuzzy Grey relational analysis (F-GRA) and Fuzzy Preference Ranking Organization METhod for Enrichment of Evaluations (F- PROMETHEE II) are used to rank alternatives in the three different ways for a comparative study.

The demand for green products has dramatically increased because the importance and public awareness of the preservation of natural environment was taken into consideration much more in the last two decades. As a result of this, especially manufacturing companies have been forced to design more green products, resulting in a problem of how they incorporate environmental issues into their design and evaluate concept options. The need for the practical decision-making tools to address this problem is rapidly evolving since the problem turns into an MCDM problem in the presence of a set of green concept alternatives and criteria.

The incorporation of fuzzy set theory into these methods is discussed on a real-life case study, and a comparative analysis is done by using its numerical results in which the three fuzzy-based methods reveal the same outcomes (or rankings), while F-GRA requires less computational steps. Moreover, more detailed analyses on the numerical results of the case study are completed on the normalization methods, distance metrics, aggregation functions, defuzzification methods and other issues.

The designing and manufacturing environmental-friendly products in a product design process has been a vital issue for many companies which take care of reflecting environmental issues into their product design and meeting standards of recent green guidelines. These companies have utilized these guidelines by following special procedures at the design phase. Along the design process consisting of various steps, the environmental issues have been considered an important factor in the end-of-life of products since it can reduce the impact on the nature. In the stage of developing a new product with the aim of environmental-friendly design, the green thinking should be incorporated as early as possible in the process.

The case study was inspired from the previous work of the author, which was realized in a hot runner systems manufacturer, used in injection molding systems in a Canada. In a new product development process, the back- and front-ends of development efforts mainly determine the following criteria: cost, risk, quality and green used in this paper. The case study showed that the three fuzzy MCDM methods come to the same ranking outcomes. F-GRA has a better time complexity compared to the other two methods and uses a smaller number of computational steps. Moreover, a comparative analysis of the three F-MCDM methods; F-PROMETHEE II, F-TOPSIS and F-GRA used in ranking for green concept alternatives using the numerical results of the case study. For the case study; as seen in table 20, the three F-MCDM methods produced the numerical results on the rankings of the green concept alternatives as follows; {Concept A-Concept C–Concept B–Concept D}.

Inclusion of environmental-related criteria into concept selection problem has been gaining increasing importance in the last decade. Therefore, to facilitate necessary calculations in applying each method especially with its fuzzy extension, it can be developed a knowledge-based (KB) or an expert system (ES) to help the DMs make the required calculations of each method, and interpret its results with detailed analysis.

The objective of the research was to propose a F-AHP based F-MCDM approach to green concept selection problem through F-PROMETHEE II, F-TOPSIS and F-GRA methods. As the F-AHP is used to weight evaluation criteria, the other methods are respectively used for ranking the concept alternatives and determine the best concept alternative.

The purpose of this paper is thus to develop a hybrid decision-making model for optimal coal blending strategy. Coal is one of the major resources contributing to generation of electricity and anthropogenic carbon-dioxide emission. Being formed from dead plant matter, it undergoes a series of morphological changes from peat to lignite, and finally to anthracite. Because of non-uniform distribution of coal over the whole earth and continuous variation in its compositions, coals mined from different parts of the world have widely varying properties. Hence, it requires an ideal blending strategy such that the coking coal having the optimal combination of all of its properties can be used for maximum benefit to the steel making process.

In this paper, a multi-criteria decision-making approach is proposed while integrating preference ranking organization method for enrichment of evaluations (PROMETHEE II and V) and geometrical analysis for interactive aid (GAIA) method to aid in formulating an optimal coal blending strategy. The optimal decision is arrived at while taking into account some practical implications associated with blending of coal, such as coal price from different reserves.

Different grades of coal are ranked from the best to the worst to find out the composition of constituent coals in the final blending process. Coals from the mines of two different geographical regions are considered here so as to prove the applicability of the proposed model. Adoption of this hybrid decision-making model would subsequently improve the performance of coal after blending and help in addressing some sustainability issues, like less pollution.

As this model takes into account the purchase price of coals from different reserves, it is always expected to provide more realistic solutions. Thus, it would be beneficial to deploy this decision-making model to different blending optimization problems in other spheres of a manufacturing industry. This model can further accommodate some more realistic criteria, such as availability of coal in different reserves as a topic of future research work.

The cost-optimal analysis is not able to address the multi-dimensionality of the decision according to the new European objectives and International sustainable development goals in the field of the nearly-zero energy building (NZEB) design. The purpose of this paper is to study the role of multi-criteria decision analysis (MCDA) for guiding energy investment decisions.

The paper explores the Preference ranking organization method for enrichment of evaluations II (PROMETHEE II) application to support the project of transforming a rural building into a NZEB. The evaluation provides an estimate of the effects of alternative energy efficiency measures, involving energy consumption, life cycle costs, carbon emissions, property value and indoor comfort criteria. The study performs a multi-actors analysis in order to understand how different consumers' point of views can influence the final choice of the best investment. Furthermore, a multi-site analysis explores the spatial variation of NZEB building appreciation in the real estate market.

The PROMETHEE II-based model ranks 16 alternative solutions for the NZEB according to energy, economic and extra-economic criteria. The multi-actors analysis highlights the configuration of the NZEB building that best meets the needs of different end-users, respecting the European directives and national standards. The multi-site analysis concludes that location does not change users' appreciation and not influence the output for the best solution.

The MCDA occurs as a support tool that helps to optimize the preliminary design phase of NZEB through the exploration of the optimal solution considering crucial criteria in the energy and environmental and real estate market rules.

The purpose of this paper is to provide to the Board of Directors and CEOs of a firm to be aware of and accountable for the information they provide to the public. As long as the quality of the companies’ public information is high, it will be able to retain its investors as well as to obtain new ones more easily.

This paper introduces a Multi-Criteria Decision Aid (MCDA) tool with the use of the PROMETHEE II method to formulate an alternative aggregate ESG quality approach. We conduct comparisons in a sectorial and regional based perspective during different exam periods before and after the implementation of International Financial Reporting Standards (IFRS), in an attempt to provide a robust framework for corporate disclosure reporting.

The findings are of particular interest to both scholars and decision-makers, including providers of corporate governance indices and rating agencies. The innovation of this paper lies among others in using the MCDA method with the ESG framework, which proposes a combination of qualitative and quantitative criteria, enabling experienced and/or not experienced analysts to avoid manipulating techniques in business information.

The sample of companies based on the US and Europe companies incorporating only large-sized ones.

Findings are of particular interest to both scholars and decision-makers including providers of corporate governance indices and rating agencies.

Better understanding features pay key importance for increasing the “quality” information in firms financial statements, especially after the use of IFRS in reporting standards.

The authors proceed to analysis using a multiple perspective use that is decomposed into the following options: (a) Time-period oriented option, (b) Regional-oriented option and (c) Sectoral-oriented option respectively.

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 purpose of this paper is to develop a method to compare supply chains (SCs) of an industry in the scope of supplier's supplier to customer's customer.

The proposed method is based on five processes provided in SCOR model version 9.0 (plan, source, make, deliver and return) and main business stages of the industry. It uses Data Envelopment Analysis (DEA) and PROMETHEE II, a multiple criteria decision‐making technique, as tools to compare SCs in the process level, business stage level and SC level. Therefore, the method is basically a new combination of existing models and methods including SCOR model, DEA and PROMETHEE II. To show the applicability and strength of the method in comparing SCs, it has been implemented in the seven SCs of the Iran broiler industry as a case study.

Comparing SCs of an industry via the proposed method results in process benchmarking, business stage benchmarking and SCs ranking in the scope of supplier's supplier to customer's customer.

The suggested method provides realistic and attainable information for SCs' owner/managers to find out the strengths and weaknesses of their SCs and improve their performance by process benchmarking and business stage benchmarking. Also they could identify their competitive position in the industry by SCs ranking.

As in line with eco benchmarking, the purpose of this paper is to solve a location selection problem in an emerging country by applying sustainability benchmarking principles.

A hybrid multi-criteria decision-making method, fuzzy AHP and Preference Ranking Organization METHod for Enrichment Evaluations (PROMETHEE), is used as methodology to make sustainability benchmarking for logistics center location selection.

It is revealed that according to AHP and PROMETHEE calculations, Kemalpasa is determined as the most appropriate location from the sustainable perspectives. Torbali is specified as the worst location to construct a logistics center in terms of benchmarking criteria based on sustainability concerns. Based on these numerical results, managerial implications are presented with a sustainability benchmarking view.

The main originality of this study is integrating one of the relatively new topics, sustainability benchmarking, with a popular area, logistics center location selection.