PROMETHEE Method Research Articles

Novel PROMETHEE method with dependent criteria

Novel PROMETHEE method with dependent criteria

Consumer Satisfaction Benchmarking Analysis Using Group Decision Support System (GDSS) PROMETHEE Methodology in a GIS Environment

In today’s competitive environment, multi-branch companies allocate their stores with the aim of expanding their territorial coverage to attract new customers and increase their market share. Consumer satisfaction surveys either produce global performance results or they are not able to differentiate consumer perceptions using location analytics. This research develops a novel framework to assist multi-branch companies in mapping the consumer satisfaction performance of their stores, expanding conventional customer relationship management to the spatial context. The framework developed proposes a decision model that combines the Group Decision Support extension of the PROMETHEE and CRITIC methods in a GIS environment to generate satisfaction performance mappings. The developed decision-making framework converts consumer responses into satisfaction performance maps, allowing the company’s stores and their competitors to be evaluated. Moreover, it provides insight into the potential opportunities and threats for each store. The performance of the proposed framework is highlighted through a case study involving a multi-branch coffeehouse company in a Greek city. Finally, a tool developed to assist the computational part of the framework is presented.

Evaluating Mobile Wallet Adoption Barriers Using Fuzzy Mathematical Model

A tremendous amount of research has been done on the factors influencing mobile wallet adoption as mobile wallet technology has seen rapid growth. Using expert opinion and Fuzzy PROMETHEE approach, this study investigates the key barriers to mobile wallet adoption. Mobile wallet adoption is constrained by Technological, security and infrastructural barriers, making adoption more challenging when user acceptance is skewed in emerging markets. In this study, we use the F-PROMETHEE to rank these barriers based on expert opinions. A panel of fintech and digital payments experts assessed the key adoption obstacles. Included in the PROMETHEE method were methods for handling variability or uncertainty through fuzzy logic and through subjective expert judgments. The results suggest that the major barriers to the adoption of mobile wallets were identified as risk and usage constraints. Moreover, value barriers are a leading factor. This study found that the risk and value barriers are the two principal risks that must be overcome to raise the client accepted rate of m-wallet services. A step forward in the assessment of such obstacles is the innovative use of a fuzzy mathematical model, which provides a more complex and adaptable approach than traditional methods. This study has learnt a few lessons that can help policy makers and industry players understand how to overcome the main barriers to mobile wallet adoption.

Portfolio Optimization with Entropy-CRITIC-IDDWS- PROMETHEE Model in BIST Retail Trade Sector

This research aims to construct an ideal stock portfolio by using financial data from firms in the BIST Retail Trade Sector throughout the 2022-2023 timeframe. . Entropy, CRITIC, IDDWS and PROMETHEE methodologies were used in the study. The criterion weights were determined using the approaches of Entropy, CRITIC, and IDDWS. The alternatives were ranked using the PROMETHEE method. According to the Entropy method, the most effective evaluation criterion on performance is the return on equity ratio in 2022 and the asset turnover ratio in 2023, according to the CRITIC method, the financing ratio in 2022 and the current ratio in 2023, according to the IDDWS method, the financing ratio in 2022 and the asset turnover ratio in 2023.It was concluded that there were 6 companies with values between 0 and +1 in the entire 2022-2023 period, there were 6 companies on the efficient frontier. These firms are CASA, SOKM, VAKKO, BIMAS, SUWEN and TKNSA. The study has a very unique perspective in terms of both proposing a new and original integrated model (Entropy-CRITIC-IDDWS-PROMETHEE) to investors about optimal portfolio selection and testing the proposed model for the 1st time in this study and the breadth of the data set used.

Selection of Artificial Intelligence Technology For Digitalization of Order Fulfillment on Drug Factory Using Multi Criteria Decision Making

Objective: This paper aims to identify the most suitable Artificial Intelligence (AI) technology for the order fulfillment process in pharmaceutical factory, along with the key criteria and sub-criteria for successful AI implementation. Theoretical Framework: The study integrates theories of digital transformation, process optimization, and decision-making. Method: The research assesses digital readiness to evaluate a company's preparedness for digital transformation. The as-is process is mapped using BPMN to identify potential AI applications. AI technologies are then ranked using BWM and PROMETHEE methods, followed by scenario analysis to determine the optimal technology. Results and Discussion: Demand Forecasting is the top AI technology for adoption in the pharmaceutical factory's order fulfillment process, reducing cycle time by 29.50% to 21.80 hours. Research Implications: The research contributes to the understanding of selecting the most effective AI technology for optimizing the order fulfillment process in pharmaceutical companies, providing valuable insights for improving efficiency. Originality/Value: The study proposes a perspective on applying AI to optimize the order fulfillment process in pharmaceutical factory, offering valuable insights for improving operational efficiency through digital transformation.

Sistem Pendukung Keputusan Pemilihan Bimbingan Belajar Terbaik Kota Pekalongan Menggunakan Metode Promethee

Tutoring institutions for elementary school levels have been proliferating in Pekalongan City due to the large number of elementary school students, totaling 18,356 students spread across 103 schools. Finding the right tutoring center that meets specific needs can sometimes be challenging. This study aims to assist with this by developing a decision support system. Using the Promethee method, which offers a more detailed evaluation of multiple criteria, the system is expected to provide a suitable decision support solution. This research produces a web-based decision support system that parents can use to find a tutoring center that meets their desired criteria.

The Evaluatıon Of Technıcal Unıversıtıes In Turkey In Accordance Wıth Tübitak Entrepreneurıal And Innovatıve Unıversıty Index

Educational institutions compete with each other with entrepreneurial and innovative steps, just like production enterprises operating in different sectors. The Scientific and Technical Research Council of Turkey (TÜBİTAK) has been evaluating universities on a total of twenty-three sub-dimensions under four dimensions in line with the Entrepreneurial and Innovative University Index (GYÜE) every year since 2012. It shares the top fifty universities in the ranking with the public. These universities include both state universities and foundation universities. Eight of the top fifty universities in the ranking are Technical Universities. Since technical universities can integrate into more university-industry collaborations, they can undertake innovative and entrepreneurial projects and create value. In this context, the aim of the study is; It is the evaluation and ranking of Technical Universities in line with TÜBİTAK-GYÜE. Method of the research; The criterion weights of the technical universities included in the TÜBITAK 2022 index were determined by the AHP method, and in this direction, the findings were obtained by using the PROMETHEE method. The study is also important in terms of determining the differences between technical universities and other universities in the context of the entrepreneurial and innovative university index and the reasons for these differences.

Analysis of the Application the Promethee Method in Determining Work Partners at the Central Statistics Agency of Central Aceh Regency

The selection of partners at the Central Statistics Agency of Central Aceh Regency faces challenges because manual selection methods are considered inefficient and inaccurate. Therefore, this study aims to improve the accuracy and efficiency of the selection process by applying the Promethee (Preference Ranking Organization Method for Enrichment Evaluations) method. This method is used as a multi-criteria decision-making technique and is implemented using the Python programming language for automatic and real-time data processing. The data used comes from the 2024 partner recruitment process at the Central Statistics Agency of Central Aceh Regency, consisting of candidates who have met the administrative requirements. The validity of the promethee method is tested through the calculation of an error percentage that reaches 10%, demonstrating the method's ability to filter partners according to the established criteria. In conclusion, the application of the promethee method has been proven to improve the efficiency and accuracy of the partner selection process, where the Python-based system developed can reduce the time and effort required in decision-making while producing more valid and reliable partner recommendations.

Location selection for logistics centre using PROMETHEE method

Logistics and distribution centres are essential to the supply chains of many manufacturing and logistics companies. Efficiently locating logistic centres involves thorough search for optimal place, prioritizing proximity to suppliers and minimizing costs. Companies’ management often solves the location problem of new halls, mostly to minimise the associated costs. Such a problem is solved in the automotive industry as part of the launch of a new international project. The key factor for the decision of where to locate the logistics centre is the location of the suppliers, since material deliveries generate a large part of the project costs. The aim of this study is to define a methodology for the location of the logistics centre, considering several alternative locations and relevant criteria. The location alternatives and criteria are defined in terms of minimising project costs and sustainability elements. The problem is solved using the multi-criteria decision-making approach. First, the AHP method is used to assign weights to the criteria. Then the PROMETHEE method is applied to find a suitable location for the logistics centre and to perform a thorough sensitivity analysis. The sensitivity analysis is focused on the impact of values of weights on the solution. Consequently, the analysis proves the correctness of the selected alternative. Based on the case study, a general methodology for locating a logistics centre is proposed.

Identification and Ranking of Factors Affecting the Emission of CO Gas in Karkar Coal Mine

Karkar coal mine is one of the biggest mines in the country, where mining has been going on since 1938. During the mining period, the Karkar mine has witnessed unfortunate incidents caused by the release and explosion of gases, which have caused substantial financial and human losses. Carbon monoxide gas is one of the essential factors in the occurrence of accidents in the Karkar mine. This research includes literature reviews, field data collection using the CEM CO-181 model gas meter, and statistical calculations using Shannon entropy and Promethee methods. First, the concentration of CO gas was measured in ventilation tunnels, development, and excavation areas. Extraction workshops of the Karkar coal mine at different working times, and then 26 cases that may result in a reduction in accidents were used as effective criteria, and 9 cases were used as influential factors on CO emissions through the order and distribution of questionnaires and interviews with identified experts. The final weights of twenty-six effective criteria on the emission of CO gas were calculated based on the Shannon entropy method. As a result, the criterion of consumed oils with a final weight of 0.1790 was ranked first, and the criterion of lack of experience with a final weight of 0.1065 was ranked last. The influential factors have been ranked based on the amount of net flow and the parameter method. As a result, the factors of mining fire and coal dust explosion ranked first and last, respectively, with net flows of 0.55 and -0.84, and the rest of the factors are placed in different positions according to their net flow rate and have their effects on the emission of CO gas.

A Fuzzy PROMETHEE Method for Evaluating Strategies towards a Cross-Country Renewable Energy Cooperation: The Cases of Egypt and Morocco

Recognising the urgency of addressing climate change and the imperative to mitigate its effects, the European Union (EU) has embarked on a transformative journey to reshape its energy landscape, with a pronounced emphasis on harnessing renewable energy sources (RESs) and augmenting their contribution to electricity generation. To propel Europe towards sustainable development through its energy transition, EU member states are encouraged to foster collaborative efforts on a European scale, inviting neighbouring countries to participate in joint ventures aimed at leveraging RESs for electricity generation. Consequently, it becomes imperative to evaluate the potential depth of cooperation among these nations, assessing how such partnerships can align with Europe’s overarching objectives while fostering mutually beneficial conditions. This paper seeks to undertake a thorough analysis and evaluation of the potential impacts of such cooperation, both in advancing RES objectives and in promoting broader cooperation goals concerning the countries involved. The appropriate methodological framework has been developed, utilising and implementing the fuzzy PROMETHEE multicriteria decision analysis method, to address the problem’s multidimensional character, intending to implement an appropriate action plan and promote production from RESs. The methodology has been applied to assess alternative strategies in two case study countries, Morocco and Egypt, while important outcomes have emerged towards the successful implementation of cooperation mechanisms promoting RES.

Supporting strategy for investment evaluation of photovoltaic power generation engineering projects using multi-criteria decision analysis methods

This scientific study examines the evaluation of photovoltaic power generation projects through the application of multi-criteria decision analysis methods. Two groups of large-scale grid-connected PV power generation system projects with a nominal power of 50 MW and 500 MW respectively were analyzed and evaluated. These systems were designed to be installed in the same wider geographical area in northern Greece, but they were differentiated in the part of the PV circuit. Twelve systems were analyzed in which either monocrystalline silicon panels or poly-crystalline silicon panels or bifacial photovoltaic panels were to be installed. In these systems either central photovoltaic inverters or photovoltaic string inverters were considered for installation. The following criteria were used to evaluate the investment in these projects. These criteria were related to the profitability, the financial cost, the technical level, and the electrical energy production of the systems and these were the initial investment cost, the operation and maintenance cost, the levelized cost of electricity, the net present value, the internal rate of return, the capital recovery or payback period, the technical level of the photovoltaic circuit, the technical maturity of the photovoltaic circuit, and the annual electricity production. The evaluation of these criteria was initially conducted with fixed weighting coefficients followed by a sensitivity analysis of these weighting coefficients. The results of the evaluation using the PROMETHEE, AHP and TOPSIS multi-criteria decision analysis methods showed that the PV power generation systems which should be preferred are those with increased nominal power, where monocrystalline silicon technology panels are employed following the central inverter topology.

Comprehensive decision-making considerations in the transition to electrification transportation system in a developing country

Introducing suitable alternatives to the existing fossil fuels can provide insightful aspects of the expected benefits. In the energy sector, the transportation system is one of the key contributors to fossil fuel consumption and greenhouse gas productions. To elaborate on the performance of each introduced alternative, two perspectives are considered; short-term and long-term evaluations. In the short outlook, the PROMETHEE method is used for evaluation. Six scenarios are introduced based on the technical, economic, social, and policy criteria and each scenario benefits from different weights. In this scheme, the impacts of evolutions in the battery applications in the vehicles are investigated. Based on the short-term study, CNG and gasoline are considered the best options for the fuels of vehicles in Iran by taking into consideration the current situation. By viewing the technical and economic criteria, it was concluded that the Li-Ion battery provides better performance in comparison with gasoline in the long run. By 2040, the number of EVs will reach 10% of the overall vehicle production. It is obtained that the benefits of the electrical vehicles’ presence as the alternative to the internal combustion vehicles can provide growing interest in this outlook from 2.02 × 106 US$ in 2025 to 17.55 × 108 US$ in 2040.

Graph model for conflict resolution with hybrid information based on prospect theory and PROMETHEE method and its application in water resources conflict

Water resources are crucial for national economic growth, but industrial development has led to severe pollution, sparking conflicts between government and enterprises over their responsibilities. Addressing these water pollution conflicts is urgent. The Graph Model for Conflict Resolution (GMCR) offers a simple and logical approach to analyzing such conflicts with minimal data. However, current models overlook decision makers’ (DMs) heterogeneity, bounded rationality, and the theoretical foundation for preference ranking. To overcome these limitations, this study integrates hybrid information to account for DMs’ diverse knowledge and experience. Prospect theory is employed to capture DMs’ bounded rationality, enhancing the accuracy of decision outcomes. The PROMETHEE method is introduced for preference ranking during GMCR modeling, guided by multi-attribute decision-making (MADM) theory. Additionally, the four basic stability concepts are redefined and proven, expanding GMCR’s theoretical applications. Finally, a case study of the Huangshui River water conflict and the comparative analysis demonstrate the model’s validity and advantages.

Urban Polycentricity and Architectural Heritage: A PROMETHEE-Based Multicriteria Approach

Polycentricity is a multiscalar concept referring to the interconnections of neighboring spatial areas in search of synergies. More specifically, urban polycentricity has lately gained increasing momentum in academic research and strategic planning as urban polycentric structures could stimulate urban and regional performance in a sustainable way. Architectural heritage, with its connotative meanings, is among the indicators of incorporation in polycentric networking. The present paper investigates the challenges of implementing urban polycentricity methodological approaches to highlight new polycentric networks based on built architectural heritage. In this study, appointed architectural assets are considered as nodes of the potential networks. As a new research strand, the MCDA PROMETHEE method is applied to compile and assemble all indicators (namely, rank size and node hierarchy, accessibility, transportation, and digital promotion). The ultimate research goal is to build a new polycentricity index as an innovative methodological tool to highlight polycentric networking synergies on interurban and intraregional scales. The region of Thrace in Northern Greece is chosen to apply the proposed methodology. Research on ways to couple polycentricity and PROMETHEE methods is limited, and thus, the proposed methodological approach is expected to contribute to the field of urban and regional strategies for researchers and practitioners.

Minat Generasi Muda dalam Usaha Tani Padi Organik di Desa Gentungan Kecamatan Mojogedang Kabupaten Karanganyar

<p>The development of organic rice farming in Gentungan Village faced aging farmers. This research aims to assess the interest of the younger generation in organic rice farming in Gentungan Village, analyze the efforts made to increase youth interest in organic rice farming, and the impact of the existence of the Taruna Tani Lestari group. This research method uses descriptive qualitative. The location selection was purposively in Gentungan Village, Mojogedang Sub-district, Karanganyar. The number of informants in this research was 18, consisting of youth members of the Taruna Tani group, youth farmers not members of the Taruna Tani groups, and non-youth farmers—data analysis using Miles and Huberman using the Promethee method. Data validity used triangulation of sources and data collection methods. The results showed that youth interest in organic rice farming began to increase due to various efforts made by the village in collaboration with universities and other agricultural start-ups. The existing efforts include forming the Taruna Tani group, introducing technology and development of agricultural infrastructure, education and training in agriculture, collaborating with various stakeholders, establishing agro-tourism, and developing other commodities. However, the Gentungan Village government needs to formulate multiple policies in the Village Medium Term Development Plan (RPJM) related to efforts to increase youth interest in organic farming businesses to realize Gentungan Village as an Organic Village in 2030.</p>

Application of the PROMETHEE Method in Determining Scholarship Recipients at University

This study aims to use the PROMETHEE method as a decision support system in determining the recipients of the Academic Achievement Improvement Scholarship at Universitas Dharmas Indonesia (UNDHARI). The methodological steps include problem identification, analysis, goal setting, and application of the PROMETHEE method. In this study, criteria and alternatives have been identified to evaluate achievement improvement scholarship recipients. The criteria weights are set, and the criteria preference types are determined. After obtaining baseline data from questionnaire assessments, pairwise preference values and multicriteria preference index values are calculated. Then, ranking is performed using the Leaving Flow, Entering Flow, and Net Flow methods, resulting in the priority order of Achievement Improvement scholarship recipients. The ranking results show that Irza Silvia (IS) has the highest Net Flow value (0.30), while Aldian Virgo Vani (AV) has the lowest Net Flow value (-0.35). Thus, the priority order from highest to lowest is IS (Irza Silvia), AV (Abdullah Gimnastiar), RD (Rini Damayanti), YM (Yesnia Marni), and AV (Aldian Virgo Vani). In the context of Net Flow scores, these results indicate that Irza Silvia (IS) has the greatest chance of receiving the achievement improvement scholarship. This study provides important insights for UNDHARI in the scholarship recipient determination process using the PROMETHEE method as a decision-making tool.

A comparative evaluation of multi-criteria decision-making framework for armed unmanned aerial vehicle

PurposeThis study focuses on the selection of armed unmanned aerial vehicles (AUAV), which have recently taken an important place on the world agenda, are used effectively in the defense industry and change the war systems of countries. This study aims to select the most suitable armed AUAV by using and comparing multi-criteria decision-making (MCDM) methods.Design/methodology/approachThere are various types of (unmanned aerial vehicles) UAVs, and some of them are Armed UAVs. This study used the criteria obtained from the market and previous UAV studies and ranked/selected various AUAVs produced in line with the determined criteria. The AHP method was used to prioritize the criteria, and the PROMETHEE method, a powerful ranking method, was used to rank/select the alternatives.FindingsBy the expert judgments, the payload capacity (28.2%) criteria took first rank by far as the most important criteria. The AUAV alternatives are listed as 1-6-5-2-7-3-4, respectively.Practical implicationsUAVs around the world have been showing significant and rapid developments recently, and those concerned closely follow developments in this field. Depending on the development of the aviation industry and technology, UAVs provide services to individuals or institutions in various ways for civil or military use.Originality/valueThe difference from similar studies is the research of Armed UAVs. Sensitivity analysis was performed and alternatives were analyzed by their weights. Comparisons were made using the MEREC, LOPCOW, and ELECTRE methods.

New hybrid EC-PROMETHEE method with multiple iterations of random weight ranges: Step-by-step application in Python

The decision-making process consists of finding the best solution to an analyzed problem. This search is carried out in the face of countless interactions when analyzing an alternative criterion by criterion, under which weights are assigned that distinguish the degree of importance they have for the decision-makers. The definition of weight for each criterion gives rise to three lines of thought on the subject. There are objective, subjective, and hybrid methods. This discussion concerns the degree to which experts define the criteria weights. Based on this discussion, we developed a hybrid method to integrate the Entropy and CRITIC methods with the PROMETHEE method, called EC-PROMETHEE. The innovation of this method is that the combination of the Entropy and CRITIC methods does not result in a single set of weights. In reality, the weights generated by each method are used to define each criterion's upper and lower limits. The range of weights generated for each criterion is emulated "n" times and builds a set of weights that are applied to the ranking definition process. The model generates "n" rankings, defining a single ranking. In this article, we demonstrate a step-by-step application of a tool developed in Python called EC-PROMETHEE and use it as an example of the problem of choosing rotary-wing airplanes for application in the military police service.➢The method reduces discretion in determining the weights of the criteria;➢The innovation lies in the use of a range of weights for criteria;➢Consistency in defining the final ranking.

Comparative analysis of Turkey’s environmental performance with Eastern European countries according to international EPI 2022 data

In order to effectively address environmental issues, it is important for governments to identify the problems causing environmental pollution within their scope and to develop appropriate solution policies. In order to identify environmental problems and develop necessary policies, it is necessary to consider the environmental performance of countries. Therefore, measuring the environmental performance of countries is of great importance. One of the prominent indices in measuring environmental performance today is the Environmental Performance Index (EPI) developed by Yale University. The main purpose of EPI is to quantitatively measure and compare the environmental performances of countries in order to monitor their progress in environmental sustainability. As of 2022, EPI consists of three main criteria: climate change, environmental health, and ecosystem vitality. In this study, Turkey’s environmental performance was evaluated using the Entropy-based PROMETHEE method with international EPI 2022 data. Subsequently, the environmental performances of Turkey and other Eastern European countries were compared in terms of criterion superiority to determine their strengths and weaknesses. In this context, various sub-criteria were analyzed under main criteria such as climate change mitigation, air quality, sanitation and drinking water, heavy metals, waste management, biodiversity and habitat, ecosystem services, fisheries, acid rain, agriculture, and water resources. As a result of the analysis conducted as of 2022, it emerged that Turkey generally exhibited weak environmental performance among Eastern European countries and there is a need for improvement in each criterion. Giving priority to criteria such as Climate Change Mitigation, Sanitation and Drinking Water, Biodiversity and Habitat, Fisheries, and Acid Rain, in which Turkey obtained the lowest scores in the ranking, would be a more strategic approach.