Aggregated Sum Product Assessment Research Articles

Assessing the internationalization dynamics of emerging markets: a comprehensive analysis utilizing SWARA-WASPAS techniques

Purpose This paper aims to evaluate the internationalization of countries represented in the MSCI Emerging Markets Index. The evaluation considers high-technology product imports, foreign direct investments, research and development expenditures, patent and industrial design applications, exports and gross domestic product (GDP) data, representing production. Design/methodology/approach This paper uses the Step-Wise Weight Assessment Ratio Analysis (SWARA) method to assess and rank the criteria for evaluating emerging markets. Four academics who are authorities in the field of foreign trade were consulted to weigh the criteria. The Weighted Aggregated Sum Product Assessment (WASPAS) method, considered one of the most reliable and robust MCDM techniques, was then used to evaluate and rank the countries. Findings The findings obtained during the research process reveal the internationalization dynamics of these countries based on the indicators they possess. As a result, it is observed which countries achieve higher performance in the internationalization process based on relevant criteria. Originality/value This study is theoretically unique and valuable as it simultaneously offers the potential for development to macro-level international trade theories, such as the technologic deficit hypothesis, and meso-level internationalization theories, such as the Uppsala model. Additionally, integrated multiple criteria decision-making (MCDM) methods, which are not frequently used in cross-country studies, have been used, and the performance of emerging markets has been ranked. The findings obtained from this application distinguish the research from the existing literature by transforming it into a performance ranking rather than focusing on the antecedents or consequences of internationalization and their interactions.

Examining thedrivers of forest cover change and deforestation susceptibility in Northeast India using multicriteria decision-makingmodels.

The increasing rates of forest cover change and heightened vulnerability to deforestation present significant environmental challenges in Northeast India. This study investigates the dynamics of forest cover changeand susceptibility to deforestation in this region from 2001 to 2021, utilizing data from the Hansen Global Forest Change (HGFC) productonthe Google Earth Engine (GEE) platform. A suite of multicriteria decision-making (MCDM) models-including VlseKriterijumska optimizacija I Kompromisno Resenje (VIKOR), Simple Additive Weighting (SAW), Evaluation Based on Distance from Average Solution (EDAS), and Weighted Aggregates Sum Product Assessment (WASPAS)-was employed to assess changes in forest cover and deforestation susceptibility across varied zones. Multicollinearity tests confirmed the relevance of the factors influencing deforestation. Statistical validations, such as the Wilcoxon Signed Ranks Test, underscored the models' robustness, revealing statistically significant outcomes. Additionally, Receiver Operating Characteristic (ROC) curve and Area Under the Curve (AUC) analysis demonstrated the superior fit of the VIKOR model (AUC = 0.938) compared to SAW (AUC = 0.901), EDAS (AUC = 0.895), and WASPAS (AUC = 0.864) in predicting current deforestation susceptibility. Validation affirmed the reliability of all MCDM methods, with VIKOR displaying high sensitivity (True Positive Rate, TPR = 0.878) and optimal AUC (0.938). Correlation analyses among the models identified significant inter-relationships, notably a positive correlation between EDAS and SAW, and a negative correlation between VIKOR and SAW. The regions of Assam, Nagaland, Mizoram, and Arunachal Pradesh were identified as experiencing significant forest cover loss, indicating a pronounced susceptibility to future deforestation. These findings underscore the need for immediate intervention to address this critical environmental issue.

Determination of Financial Performance in Electric Power Enterprises with Entropy Weighted WASPAS Analysis Method

In this study, Entropy weighted WASPAS method is applied to measure the financial performance of 11 electric power enterprises operating in Borsa Istanbul (BIST) for the period of 2022. 7 financial ratios for the year 2022 were accepted as criteria and the financial success ranking of 11 electric power enterprises was made. The financial ratios used in the study were selected among the ratios that can provide information about the liquidity and profitability status of the enterprises. In the first stage of the application, Entropy method was used to determine the criteria weights. The determined criteria weights were prioritized and used in the WASPAS (Weighted Aggregated Sum Product Assessment) method. Then, the financial performance of electric energy enterprises was ranked by making an evaluation with the WASPAS method.

Site Selection for Girls Hostel in a University Campus by MCDM based Strategy

The area of interest based on girls’ hostel site selection is an important topic nowadays. The research directly impacts the well-being, safety, and academic success of female students who are taking the facilities for accommodation while pursuing their academic courses. An efficient hostel location not only supports the physical safety of students but also takes care of their psychological and emotional well-being by providing a suitable and helpful living atmosphere. Different valuable criteria and sub-criteria are considered for evaluating the most suitable site for a girls' hostel. The security and protection, proximity to academic buildings, accessibility, health and safety, and environmental factors as criteria with their associated sub-criteria are considered for this study. Two decision makers are given data sets in linguistic terms and further converted into crisp numbers. The weights of the criteria and sub-criteria are determined by a well-known multi-criteria decision-making (MCDM) technique called the Entropy weighted method. Further, the most prioritized location for the girls' hostel on the university campus was evacuated using the weighted aggregated sum product assessment (WASPAS) based ranking MCDM method. Additionally, the sensitivity analysis was conducted to check the stability and flexibility of the results.

Effect of combined parametric impacts on collapsing the wall quality of WAAM Al5356 component

Even though Wire and Arc Additive Manufacturing (WAAM) of the Al5356 component has garnered attention for making affordable, large-scale components, problems with porosity, humping, and undercut still exist. Therefore, optimising process parameters is crucial to achieving flawless products with consistent layer deposition. Hence in this research, the most important WAAM parameters including travel speed (TS), wire feed speed (WFS), and torch angle (TA), were examined in order to determine how they affected structural integrity while taking into account key responses such as porosity, pore diameter, and tensile strength. The Significance of Criteria Weighted Aggregated Sum Product Assessment (WASPAS) in conjunction with Intercriteria Correlation (CRITIC) was used to investigate the favourable circumstances and confirm that the TA is the most important parameter in the nucleation of pores. The verification studies demonstrate that a 58.2 % reduction in pore diameter results in a 31.8 % increase in tensile strength. An ideal TS and WFS of 65 cm/min and 5 m/min, with a maximum TA of 90°, were found to be the favorable conditions for printing Al5356 wall with a minimum porosity of 0.037 %, enhanced ultimate tensile strength of 278 MPa, and minimum pore diameter of 93 µm, according to the CRITIC associated WASPAS approach. Additionally, using the fractography, the damage process based on the porosity creation was investigated. The optimal parameters for generating a defect-free multi-layer structure were identified, hence enhancing the structure’s suitability for industrial use.

A narrative literature review on optimization of manufacturing processes using weighted aggregated sum product assessment (WASPAS) method

A narrative literature review on optimization of manufacturing processes using weighted aggregated sum product assessment (WASPAS) method

Analysis of mechanical properties of basalt fabric reinforced fly ash filled vinyl ester composites using multi criteria decision making technique

The current research was to examine the mechanical properties of composite material made of vinyl ester filled with fly ash of various weight percentages. Before fabrication the amount of fly ash and resin were identified by using the Multi Criteria Decision Making technique (MCDM). The best filler weight percentage of 5 wt% is determined by using Weighted Aggregate Sum Product Assessment (WASPAS) which is one of the MCDM methods. The virgin samples of vinyl esters are mixed with weight of 5 wt%fly ash by incremental of 5 wt% up to 20 wt%. All the mechanical tests of the specimen were conducted as per ASTM standards. Subsequently based on the results from the WASPAS method of fly ash content, the basalt fabric was reinforced with fly ash filled vinyl ester to fabricate the hybrid composites. By the mixing of fly-ash with vinyl ester the strength of the fly ash filled composites has been found to be enhanced in the filler. The results from the mechanical testing signified that fly ash can be used as filler material in basalt fabric reinforced vinyl ester resin. The fly ash infused basalt fibre reinforced yields significant development in mechanical performance contrast to the other fabricated composites.

PENERAPAN METODE WASPAS DAN ROC DALAM PEMILIHAN BANK TERBAIK UNTUK PELAYANAN MOBILE BANKING

Technological developments encourage increased use of banking services via mobile devices. Choosing the optimal bank for mobile banking services is an important challenge in meeting customer needs. This research uses a Decision Support System with the application of the Weighted Aggregated Sum Product Assessment (WASPAS) and Rank Order Centroid (ROC) methods. The WASPAS method helps find positive and negative ideal solutions in solving problems. The ROC method was chosen to reduce the level of subjectivity and uncertainty in determining weights. The weights in ROC are determined based on priority criteria. In this research, 5 alternatives are used, namely BCA Mobile, Livin' by Mandiri, BSI Mobile, BNI Mobile Banking, BRImo BRI, and apply criteria such as security, many enthusiasts, user friendly, rating, and cost. This research aims to provide a comprehensive picture of the quality of mobile banking services provided by various banks so as to help customers choose mobile banking according to the criteria they need. The research results show that BCA Mobile owned by BCA bank is the best alternative with the highest value of 0.940, followed by BRImo with a value of 0.613, BNI Mobile with a value of 0.612, Livin' by Mandiri 0.611, and the lowest value of 0.323 for BSI Mobile. Thus, BCA Mobile is declared the best choice for mobile banking services.

Elevating Pakistan’s flood preparedness: a fuzzy multi-criteria decision making approach

In South Asia, Pakistan has a long and deadly history of floods that cause losses to various infrastructures, lives, and industries. This study aims to identify the most appropriate flood risk mitigation strategies that the government of Pakistan should adopt. The assessment of flood risk mitigation strategies in this study is based on certain criteria, which are analyzed using the fuzzy full consistency method. Moreover, flood risk mitigation strategies are evaluated by using the fuzzy weighted aggregated sum product assessment (WASPAS) method, considering previously prioritized criteria. According to the results, lack of governance, lack of funding and resources, and lack of flood control infrastructure are the most significant flood intensifying factors and act as major criteria for assessing flood risk mitigation strategies in Pakistan. Adopting hard engineering strategies (e.g., dams, reservoirs, river straightening and dredging, embankments, and flood relief channels), maintaining existing infrastructure, and adopting soft engineering strategies (flood plain zoning, comprehensive flood risk assessment, and sophisticated flood modeling) are identified as the top three flood risk mitigation strategies by the fuzzy WASPAS method. The highest weight (0.98) was assigned to the adoption of hard engineering strategies to mitigate flood risks. The study introduces a novel dimension by analyzing the real-time impact of the unprecedented 2022 floods, during which approximately one-third of the nation was submerged. This focus on a recent and highly significant event enhances the study’s relevance and contributes a unique perspective to the existing literature on flood risk management. The study recommends that the government of Pakistan should prioritize hard engineering strategies for effective flood risk mitigation. It also recommends that the government should incorporate these strategies in the national policy framework to reduce flood losses in the future.

Selection of Head of Study Program using Weighted Aggregated Sum Product Assessment (WASPAS) method

Selecting a Head of Study Program is a crucial strategic decision in education, particularly in Vocational High Schools. At the Software Engineering Study Program Vocational School Sitibanun Sigambal, Labuhanbatu, Rantau Prapat, this process becomes highly complex due to the involvement of various criteria, such as Psychotest Scores, IQ Tests, Communication Skills, Cognitive Tests, and Teaching Experience. The Weighted Aggregated Sum Product Assessment (WASPAS) method, which combines the Weighted Sum Model (WSM) and Weighted Product Model (WPM), is utilized to enhance the accuracy and efficiency of decision-making. This method enables a more objective and structured selection process by leveraging information technology. Based on implementing the Decision Support System (DSS) using the WASPAS method, it can be concluded that it is highly effective in determining the best Head of Study Program rankings, considering the complex criteria and the need for accurate decisions. This DSS facilitates the selection process with results that are more objective, transparent, and aligned with the School's needs and priorities, thus aiding in achieving the School's mission of providing high-quality education.

Compression behavior and design optimization of triggered glass fiber reinforced polymer square tubes

AbstractGlass fiber reinforced polymer (GFRP) composite tubes have become increasingly popular in crashworthiness applications. On the other hand, square section GFRP tubes are prone to damage in a catastrophic failure mode in the early stages of the crushing process. At this point, triggering mechanisms have great potential to ensure deformation in progressive mode and improve the compression performance of GFRP tubes. Motivated by these facts, this paper aims to optimize the compression performance of square GFRP tubes by implementing notch‐type triggering mechanisms. The effects of notch width, number and length on the axial compression response of tubes were investigated to determine the optimal trigger configurations that would maximize specific energy absorption (SEA) and minimize peak crushing force (PCF). Experiments were conducted based on Taguchi L9 orthogonal array design, and Taguchi coupled Weighted Aggregated Sum Product Assessment (WASPAS) method was employed for optimizing multiple responses. The optimization results revealed that the proposed trigger mechanisms induced progressive crushing by preventing catastrophic failure, thereby significantly improving the compression performance of GFRP tubes. In particular, the results showed that the PCF of intact GFRP tube decreased by up to 38%, while SEA increased by up to 130% with the help of proposed trigger mechanism.Highlights The compression performance of square GFRP tubes improved by notch‐type triggering. The notch width, length and number were chosen as design parameters. Taguchi experimental design was used to find the best configuration of design parameters. The optimum configurations were examined through the entropy‐WASPAS approach. The results revealed that significant improvements can be achieved using trigger mechanism.

Predictive modelling and optimization of WEDM parameter for Mg–Li alloy using ANN integrated CRITIC-WASPAS approach

This work intended to improve the precision and machining efficiency of Magnesium alloy (Mg–Li–Sr) using Wire electrical discharge machining (WEDM). Mg–Li–Sr alloy is prepared through inert gas assisted stir casting route. Taguchi approach is used for experimental design for WEDM parameter such as pulse OFF time, pulse ON time, wire feed rate, servo voltage and current. L27 orthogonal array is considered to understand the influence of control parameter such as Kerf Width (KW), Roughness of the surface (Ra), Material Removal Rate (MRR). Integration of the CRITIC (Criteria Importance Through Intercriteria Correlation) -WASPAS (Weighted Aggregated Sum Product Assessment) multi-objective optimization method with Artificial Neural Network (ANN) modelling with different network structure for prediction and optimization is a novel approach that significantly improves prediction accuracy and machining outcomes. The developed ANN model with better R2 value of 99.9 % has better ability for prediction while correlated with formulated conventional regression equation. The error percentages identified through confirmation tests for regression and ANN models are Ra - 8.5 % and 3.4 %, MRR - 5.9 % and 2.8 %, KW - 6.7 % and 2.2 % respectively. Optimal output response attained by CRITIC-WASPAS approach yields surface roughness of 4.62 μm, material removal rate of 0.073 g/min and kerf width of 0.388 μm.

Sustainable solutions: using MCDM to choose the best location for green energy projects

Purpose This study aims to find the best location for constructing green energy facilities in India and reducing CO2 emissions. Incorporating green energy is a priority for many countries under the Paris Agreement. This task is challenging due to factors that affect implementation, and making the wrong decision wastes resources. India’s goals are net-zero emissions by 2070 and 50% renewable electricity by 2030. Other developing nations should emulate India’s renewable energy strategy. India ranks fourth in renewable energy and wind power, and fifth in solar power capacity. This research aims to identify the best locations in India for implementing green energy projects. Design/methodology/approach To identify the optimal green energy implementation sites in India, this research uses the hybrid multicriteria decision analysis (MCDA) in an uncertain environment. This research uses the Delphi method to identify the most suitable green energy implementation sites in India. It adapts the elements for this investigation. In addition, the utilization of the Fermatean fuzzy weighted aggregated sum product assessment technique is implemented to effectively prioritize the factors that impact the selection of these sites. This study used the MEREC method (method based on the removal effects of criteria) to identify the most suitable areas in India for implementing green energy. The highest accuracy is attained through the amalgamation of these hybrid methods. Findings Following the computation data by hybrid MCDA in uncertainty environment, NP Kunta in Andhra Pradesh emerges as the recommended green energy site among the 11 considered. Also among the factors political strategies and objectives hold the highest priority among them. Originality/value This study is pioneering in its efforts to provide a comprehensive perspective on the development and management of green energy operations in India. The study proves advantageous for diverse sites in the successful adoption and management of green energy. The study is additionally valuable in informing policy development aimed at promoting the use of green energy by employees through the utilization of MCDA methods in uncertain environments.

Organizational Innovativeness: The Role of Innovation Adoption Capability

Organizations develop capabilities to manage activities and generate value for their customers. This study focuses on the adoption capability of innovation adopting organizations. Adoption capability is a complex, and multidimensional concept that includes a high level of uncertainty, making it difficult to measure. This study attempts to find a systematic methodology to measure the innovation adoption capability of firms, through which management can monitor and evaluate a firm’s strengths and weaknesses in each capability dimension compared with competitors, predict their future needs for improvements, and plan necessary activities to stay competitive in the market. The proposed model considers multiple quantitative and qualitative adoption capability dimensions simultaneously and utilizes a relatively comprehensive set of adoption capability elements by developing 35 items and classifying them into six dimensions. This study uses the fuzzy weighted aggregated sum product assessment (WASPAS) method as a multi-attribute decision-making (MADM) approach. The model is applied to three competing firms in the consumer electronics sector, and the results are discussed.

Unveiling Afghanistan's wind and hydrogen potential: a comparative study.

Given the detrimental environmental impacts of fossil fuels, there is a gradual worldwide shift towards renewable energy sources. Wind power, renowned for its cost-effectiveness and simplicity, has been widely embraced. Despite Afghanistan facing significant challenges in its energy sector, its considerable wind energy potential offers a chance to mitigate some of these issues. This study employed a multi-criteria decision-making approach to evaluate potential wind-hydrogen project sites in Afghanistan, encompassing economic, technical, social, risk, and environmental considerations. Five criteria and sub-criteria for wind-hydrogen project implementation were analyzed using the Step-wise Weight Assessment Ratio Analysis (SWARA) method. The Weighted Aggregated Sum Product Assessment (WASPAS), Additive Ratio Assessment (ARAS), Evaluation based on Distance from Average Solution (EDAS), and Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) methods were then applied to prioritize provinces for wind-hydrogen project implementation. The analysis found that the Duration of the Payback Period and Levelized Cost of Electricity (LCOE) with weight of 6.6% and 5.6% were critical sub-criteria. Farah, Herat, and Nimroz emerged as Afghanistan's most promising provinces for wind-hydrogen energy development. In Farah, utilizing 900-kW turbines, it is feasible to generate 2679.8 MWh of electricity and produce 43.4 tons of hydrogen annually, with a Levelized Cost of Electricity of 0.0690 $/kWh and Levelized Cost of Hydrogen of 1.747 $/kg.

Group decision making method for third-party logistics management: An interval rough cloud optimization model

Group decision making in third-party logistics service selection plays an essential role for improving service quality, increasing efficiency and reducing the net cost. Fuzzy and uncertain linguistic variables are commonly used to represent experts‘rankings in optimization problems. To recognize the limits of human cognition and subjectivity of human evaluations, several optimization approaches have been studied to select remanufacturing alternatives in decision making processes, however these methods have certain deficiencies such as lacking manipulation tools of diverse information, randomness, use of predefined parameters increasing uncertainty, interpersonal relations among evaluation criteria. The integration of interval numbers, rough approximations, and cloud model theory plays a significant role to model incomplete and inadequate information occurring in decision making problems. This research paper focuses on the integration of dual interval rough integrated cloud model with best-worst optimization technique, Multi-Attributive Border Approximation area Comparison (MABAC) and Weighted Aggregated Sum Product Assessment (WASPAS) approaches. A novel min–max optimization model based dual interval rough integrated cloud values is designed to compute the weight coefficients and consistency ratio for each criteria. The consistency of proposed optimization model is checked using a consistency ratio test. Secondly, the alternatives are ranked using the proposed DIRI cloud based MABAC and WASPAS approaches using interval clouds based weighted sum and weighted product coefficients, approximation area values and distance formulae. The significance of the proposed model is highlighted with a case study of third-party logistics service management of an electronic firm. The rationality and out-performance of the proposed methodology is studied by a comparative analysis with existing approaches and detailed sensitivity analysis on different variations of criteria weights and parameter.

Promoting inclusivity in education amid the post-COVID-19 challenges: An interval-valued fuzzy model for pedagogy method selection

The advent of the COVID-19 pandemic has brought about unprecedented disruptions in the field of education, necessitating a reevaluation of pedagogical approaches in the post-COVID era. This research paper introduces a novel interval-valued fuzzy simple additive weighting (SAW), weighted product model (WPM), and weighted aggregates sum product assessment (WASPAS) multi-criteria decision-making (MCDM) framework to address the challenge of promoting inclusivity in education amidst the post-COVID era. Leveraging the uncertainty inherent in the post-pandemic educational landscape, the proposed method offers a comprehensive pedagogy selection approach incorporating interval-valued fuzzy sets to account for imprecise and ambiguous data. By integrating the principles of inclusivity and diversity, the method evaluates various pedagogical approaches and their effectiveness in fostering an inclusive learning environment for diverse student populations. The study showcases the application of pedagogy selection in real-world educational scenarios, demonstrating its potential to inform policy decisions and enable educational institutions to adapt and cater to the evolving needs of learners in the aftermath of the COVID-19 pandemic.

A novel failure mode and effect analysis model based on extended interval-valued q-rung orthopair fuzzy approach for risk analysis

The failure mode and effect analysis (FMEA) is an essential technique for risk assessment that can not only determine the potential failure modes, causes of failure and effects, but also expunge the potential failure modes in a system. Imprecise evaluation outcomes may be achieved due to the inherent imperfections caused by the traditional FMEA approach. Accordingly, a hybrid FMEA model based upon the interval-valued q-rung orthopair fuzzy (IVq-ROF) set and extended weighted aggregated sum product assessment (WASPAS) method is propounded to provide decision support for risk assessment. The main dedications of this investigation are as below. First, an innovative IVq-ROF score function is presented to compare the IVq-ROF numbers and the related properties of the proposed function are also discussed. Second, the IVq-ROF Aczel–Alsina operation laws are investigated and then some novel IVq-ROF Hamy mean operators are propounded on based on the advanced operations. Third, the IVq-ROF logarithmic percentage change-driven objective weighting (LOPCOW) method is advanced based on the presented score function to determine the objective importance of the risk criteria and the fuzzy full consistency method (FUCOM) is utilized to ascertain the subjective importance of the risk criteria. Fourth, a novel FMEA model based on extended WASPAS method is presented to ascertain the prioritization of failure modes. Lastly, an empirical about risk assessment in the shipbuilding process is implemented to verify the applicability and feasibility of the designed FMEA model. The comparison analysis and sensibility study are executed to demonstrate the significant merits and stability of the developed model. The best advantage of the presented model is that it not only obtains a consistent outcome and takes into account the interrelations among the risk criteria, but also addresses more problems where the weights of the criteria and experts are not determined in advance.

Evaluation based on multi-criteria decision-making methods and spherical fuzzy framework for security and privacy in metaverse technologies: A case study

Integrating the metaverse technology with the transportation system has several security and privacy issues. This study assesses the 12 security solutions to select the best one to overcome security and privacy issues (such as data theft, unauthorized access, and theft of personal data) when integrating the transportation system with metaverse technology. A suggested methodology is conducted by experts and decision-makers using linguistic terms and spherical fuzzy numbers to express their opinions on evaluating the criteria and alternatives. Selecting the best security solution (alternative) is critical because it includes several conflict security criteria, such as data theft, authentication, security attacks, and others. This paper introduces a methodology for multi-criteria decision-making (MCDM) in a spherical fuzzy (SF) environment. The MCDM method dealt with various conflicting criteria, and SF dealt with uncertainty and vague information while evaluating the criteria and alternatives. The suggested methodology consists of two main phases. The first phase introduces the analytic hierarchy process (SF-AHP) method to compute the criteria weights. The second phase introduces the Weighted Aggregates Sum Product Assessment (SF-WASPAS) method to rank and select the best alternative. The results show the end-to-end authentication protocol is the best alternative (security solution). This study conducted a sensitivity analysis of the stability of the rank by changing the criteria’s weights. The sensitivity analysis results show that the end-to-end authentication protocol is the best alternative (security solution) in different cases. We compare the suggested methodology with six other MCDM methods: SF-TOPSIS, SF-VIKOR, SF-MABAC, SF-CODAS, SF-MARCOS, and SF-COPRAS to show the effectiveness of the proposed method. The results show that the presented methodology is robust compared to other MCDM methods.

Challenges of Microfinance and Financial Inclusion for Development Using WASPAS Method

Financial inclusion refers to the process of ensuring that individuals and businesses have access to useful and affordable financial products and services that meet their needs – transactions, payments, savings, credit, and insurance – delivered in a responsible and sustainable way. The concept aims to eliminate the barriers that exclude people from participating in the financial sector, enhancing their ability to improve their economic conditions. Microfinance is a critical tool within the broader financial inclusion agenda. It involves offering financial services to low-income individuals or those who do not have access to typical banking services. These services include microloans, savings accounts, insurance, and money transfers. Microfinance institutions (MFIs) cater to people who are traditionally excluded from the formal banking sector, helping them to start or expand small businesses, manage risks, and improve their quality of life.One of the primary significances of researching financial inclusion and microfinance is their critical role in promoting economic development. By providing access to financial services, individuals and small businesses can engage in economic activities that contribute to the overall growth of their communities and economies. Microfinance allows entrepreneurs to start or expand small businesses, which can lead to job creation and increased productivity. Understanding the mechanisms and impacts of these financial services helps policymakers and stakeholders design better programs to stimulate economic development, particularly in underserved regions. Alternative taken as Program A, Program B, Program C, Program D, Program E. Evaluation Preference taken as Loan Disbursement Rate (%), Client Outreach (thousands), Loan Default Rate (%), Operational Costs (% of budget). The results Program E Advertising achieved the highest rank, while Search Program B received the lowest rank being attained. “The value of the dataset for Financial Inclusion and Microfinance, according to the Weighted Aggregated Sum Product Assessment Program E Advertising achieves the highest ranking.”