FAHP Method Research Articles

Revealing the Barriers of Blockchain Technology for Supply Chain Transparency and Sustainability in the Construction Industry: An Application of Pythagorean FAHP Methods

Blockchain technology has emerged as a promising solution to enhance supply chain transparency and sustainability in the construction industry. However, the widespread adoption of blockchain faces several barriers that need to be identified and understood. The construction industry faces significant challenges regarding supply chain transparency and sustainability. Current practices lack visibility, leading to difficulties in tracing material origins, tracking movement, and ensuring compliance. To fill this gap, this study employed a three-phase approach. In the first phase, a comprehensive literature review identified 37 potential barriers. Subsequently, expert discussions were held to refine the list, ultimately selecting 15 barriers of utmost importance. In the second phase, data were collected from 17 experts representing academia and industry. Finally, in the last phase, the collected data were analyzed using the Pythagorean fuzzy analytical hierarchical process (AHP) methodology. The findings revealed that the “transparency range” category was the most critical barrier, closely followed by “inadequate access to institutional finance”. Surprisingly, the study identified the “security environment” as the most significant barrier. These results offer construction companies, policymakers, and other industry stakeholders a comprehensive understanding of blockchain adoption’s challenges. With this knowledge, stakeholders can design effective strategies and policies to address these barriers. Moreover, the research highlights the importance of considering uncertainty in decision making when assessing technology adoption, making the findings applicable beyond the construction industry.

Research on Evaluation of Financial Risks in Agricultural Product Supply Chains Based on An Improved DEMATEL Method

In order to improve the rationality, accuracy, and timeliness of decisions on financial risks in agricultural product supply chains, it is necessary to evaluate and control these risks sensibly. In this paper, research is conducted on financial risk factors in agricultural product supply chains, and on this basis a financial risk evaluation index system for such supply chains is built in four identified dimensions – credit risk, market risk, pledge risk, and supply chain relation risk. Next, the weights of risk indexes are measured by means of combined weighting based on subjective F-AHP method and objective CRITIC method. The final risk weight coefficients are then derived with EDAS method. With the aid of an improved DEMATEL method, the agricultural product supply chain financial risk factors are analyzed, and comprehensive impact degrees of different risk factors in agricultural product supply chains are calculated. The calculation results show that financial risks in agricultural product supply chains are highly influenced by cooperation level, performance record, and financial standing and repayment history of borrowing organization. Based on the findings of this paper, appropriate financial risk management and control measures can be developed in light of the key risk factors identified in agricultural product supply chains, thereby providing a valuable reference for financial risk control in agricultural product supply chains.

Explanation of the future-oriented Spatial Resilience Planning Framework (SRPF) against earthquake and its verification with meta-analysis and FAHP methods

Explanation of the future-oriented Spatial Resilience Planning Framework (SRPF) against earthquake and its verification with meta-analysis and FAHP methods

Application of Multi-Criteria Assessment in Banking Risk Management

Abstract Banks face a number of business risks on a daily basis. Today, operational risk is dominant. The aim of this paper is to develop a decision-making system when choosing a method of operational risk management by using the Analytical Hierarchy Process (the AHP method) and the Fuzzy Analytic Hierarchy Process (the FAHP method). Analytical hierarchical process is a simple efficient process in solving decision-making problems. The final decision depends on the assessment of a set of alternatives and the decision criteria. The main purpose of the process is to find appropriate solutions for defined user factors in the current competitive environment. The results obtained by the classical AHP method, as well as the FAHP method, show that external factors are the dominant criterion, especially during the financial crisis or the Covid19 pandemic, and that solutions should be sought in international standards, using control tools created by the banks themselves.

RETRACTED ARTICLE: Analyzing the applications of big data in network public opinion monitoring using FAHP and EDAS methods

RETRACTED ARTICLE: Analyzing the applications of big data in network public opinion monitoring using FAHP and EDAS methods

A comparative and coupled study of the application of Dempster-Shafer, fuzzy overlay and FAHP methods for groundwater potential mapping in a fractured medium of a mine site

A comparative and coupled study of the application of Dempster-Shafer, fuzzy overlay and FAHP methods for groundwater potential mapping in a fractured medium of a mine site

Sustainability in Pakistan's textile industry: analyzing barriers and strategies for green supply chain management implementation.

The industries view green supply chain management (GSCM) as a viable means of achieving sustainable operations by reducing environmental impact and enhancing operational performance. Although conventional supply chains still dominate many industries, integrating eco-friendly practices through green supply chain management (GSCM) is crucial. Nonetheless, there are several barriers that hinder the successful adoption of GSCM practices. Therefore, this study proposes fuzzy-based multi-criteria decision-making approaches comprised of the Analytical Hierarchy Process (FAHP) and the Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS). The study evaluates and overcomes barriers to the adoption of GSCM practices in the textile manufacturing sector of Pakistan. After the comprehensive literature review, this study identifies 6 barriers, 24 sub-barriers, and 10 strategies. The FAHP method employs to analyze the barriers and sub-barriers. Then, the FTOPSIS method ranks the strategies to overcome various identified barriers. Based on the FAHP results, the most significant barriers to the adoption of GSCM practices are technological (MB4), financial (MB1), and information and knowledge (MB5). Further, the FTOPSIS indicates that increasing the research and development capacity (GS4) is the most vital strategy for implementing GSCM. The study's findings have important implications for policymakers, organizations, and other stakeholders interested in promoting sustainable development and implementing GSCM practices in Pakistan.

Investigation of the effect of working capital management on profitability by panel data analysis and multi-criteria decision making techniques

Purpose: The aim of this study is to reveal and compare the effect of working capital management on return on assets with different analysis methods, based on the annual financial statement data of companies in the tourism sector traded in Borsa Istanbul (BIST) in the period 2012-2020. This study aimed to reveal the drawbacks of including in the model variables that are not an element of working capital management. Methodology: Panel data analysis, the analytical hierarchy process and the fuzzy analytical hierarchy process were used to reveal the effect of working capital management variables on return on assets based on the financial statement data of the companies. Results: As a result of the analysis, a significant relationship was identified between the rankings made by using the realized return on assets ratios and the rankings obtained by AHP and FAHP, while no significant relationship was found between the rankings obtained by panel data analysis. Conclusion: Including some variables in the model as a working capital management variable in panel data analysis may cause misinterpretation of the effects of real working capital variables on return on assets. When the model that emerged according to the AHP and FAHP methods was examined, the asset turnover rate and financial leverage ratio variables were determined as the ratios with the lowest effect on return on assets, as the elements of working capital management in the weighting made according to the opinions of the experts.

Comprehensive evaluation of the optimal rates of irrigation and potassium application for strawberry

Accurate and effective management of irrigation and fertilization is essential for efficient greenhouse strawberry production. Here, the effects of the combined application of water and potassium on strawberry growth were evaluated by experimenting with 12 treatments, including four transpiration (ETC)-based irrigation levels (W1: 100% ETC, W2: 85% ETC, W3: 70% ETC, and W4: 55% ETC) and three potassium levels according to the target yield (K1: 369.5 kg/hm2, K2: 307.9 kg/hm2, and K3: 246.3 kg/hm2). Various indexes of strawberry yield, fruit quality, water and fertilizer utilization efficiency, and soil nutrient residues were measured. Irrigation and potassium application had significant effects on strawberry production. Higher irrigation levels increased yield (Y), and moderate water and potassium application increased single fruit weight (SFW), water utilization efficiency (WUE), total soluble sugar (TSSC), and the sugar-acid ratio (SAR). While low-application of potassium increased the soluble protein content (SP), partial factor productivity of potassium (PFPK), and reduce nutrient residues in soil effectively. A comprehensive system for evaluating strawberry growth and its benefits to the soil environment was developed. The FAHP and CRITIC methods were used to calculate the subjective weight and objective weight of each index, respectively. The largest subjective weight was observed for Y (0.200), and the largest objective weight was observed for soil-available potassium (0.101). The final weight was determined using Game theory; Y had the highest weight (0.185), and free amino acids (FAA) had the lowest weight (0.047). Grey relational analysis (GRA) was used to evaluate the optimal irrigation and potassium scheme for accomplishing multiple objectives. The response of the comprehensive score of strawberries to irrigation and potassium exhibited a negative parabolic relationship, and the effect of irrigation was greater than the effect of potassium application. There was a significant interaction between irrigation and potassium application, and an irrigation amount of 2053-2525 m3/hm2 with a potassium application rate of 288.1-334.2 kg/hm2 was optimal for promoting strawberry yield, fruit quality, and efficiency and reducing soil nutrient residues. The results of this study provide new insights that could aid the development of sustainable approaches for enhancing agricultural production. Keywords: strawberry, irrigation, potassium, FAHP, CRITIC, nutrient residues DOI: 10.25165/j.ijabe.20231602.7591 Citation: Yang X Q, Du R C, Zhang M C, Feng H W, Wang Z Q, Zhang Z. Comprehensive evaluation of the optimal rates of irrigation and potassium application for strawberry. Int J Agric & Biol Eng, 2023; 16(2): 65-72.

Selection of best leather item using a FAHP method to launch new leather industry in Ethiopia: A case study

The ready-to-wear sector is expanding quickly and already accounts for a significant contribution to Ethiopia's export revenue. Due to its lower labor and investment costs, availability of resources, government assistance, etc. than other sectors, this industry attracts young entrepreneurs from around the nation as investment destinations. However, while investing in the leather industry, there are frequently many more aspects to consider. Again, there are numerous leather investment opportunities in the leathers sector, including handbags, jackets, belts, shoes, gloves, etc. Different sorts of leather items necessitate various levels of capital investment, operator skill sets, and resource requirements, among many other things. Again, based on their capacity for managing businesses, available capital, business location, and other factors, not all investors are in the same position. To assist investors in making decisions on the opening of a new leather industry, this paper presents a FAHP methodology for choosing the best leather item among various possibilities in a fuzzy environment. The methods enable the decision-maker to incorporate language expressions of expert judgment into the evaluation process. Using the suggested process, the ideal leather item is chosen for the launching of a leather industry in Ethiopia under the current circumstances.

Applications of AHP, FAHP, BWM, Entropy, and CRITIC Methods in Electrohydraulic Forming Process Parametric Evaluation for Automotive Panels Using the 1100 Aluminum Alloy Sheets

Although multicriteria selection methods are flexible and extensively used in machining, less attention has been paid to their comprehensive test performance in the electrohydraulic forming process. In this study, five new applications of multicriteria selection methods are proposed to analyze available parameters in the electrohydraulic forming process and select parameters best suited for further analysis and improvement of the process. The analyzed parameters are the stand-off distance, electrode gap, voltage, and medium, while the multicriteria methods are the AHP, FAHP, BMW, entropy, and CRITIC. The proposed methods were demonstrated on experimental data from the literature utilizing an impulse magnetizer system (walker type). For each method, the prioritized parametric results were obtained. All the methods assign the first position to the medium as a parameter with consensus on the voltage parameter has the worst (lowest) value of weights in all the methods. The weights of the medium parameter for the best results are 0.5030 (AHP method), 0.5600 (FAHP method), 0.5230 (best-worst method), 0.4090 (entropy method), and 0.5000 (CRITIC method). The worst parameter for all the methods is the voltage of 0.0320 (FAHP method). The results obtained from the proposed applications were compared with one another and found to be effective for multicriteria selection decisions. This article offers new methods to establish the parametric values of the electrohydraulic forming process for machining composites made of AA1100 sheets.

Supply Chain RFID Solution Evaluation Applying AHP and FAHP Methods: A Case Study of the Serbian Market

Supply Chain RFID Solution Evaluation Applying AHP and FAHP Methods: A Case Study of the Serbian Market

Site Selection of Natural Gas Emergency Response Team Centers in Istanbul Metropolitan Area Based on GIS and FAHP

The location of natural gas emergency response team centers (NGERTCs) is critical in terms of addressing natural gas notifications that require a timely emergency response. The selection of NGERTCs in Istanbul has an important place in terms of providing better service, due to the necessity of responding to emergency natural gas notifications within 15 min, in addition to the over 200,000 natural gas notifications per year and heavy traffic conditions. Therefore, this study proposes a solution based on GIS and FAHP to determine suitable NGERTC locations in Istanbul Metropolitan Area. In the first stage of the study, the required 15-min coverage areas for emergency calls for 36 existing NGERTCs in Istanbul were extracted and the adequacy of their locations was analyzed. In the second stage of the study, the weights of seven criteria determined for new NGERTC site selection were calculated by the FAHP method. With spatial analysis made, 12 new NGERTC locations were proposed. Finally, re-coverage analysis was performed for proposed and existing NGERTCs, and changes in coverage area within a 15 min response time were analyzed. Natural gas network coverage increased from 70.04% to 83.86%, and natural gas subscriber coverage increased from 91.03% to 96.27%. The results show that GIS and FAHP are worth using in selecting suitable NGERTC locations.

A GIS based Fuzzy-AHP for delineating groundwater potential zones in tropical river basin, southern part of India

Groundwater plays a vital role in the development of ecological niches, the durability of the environment, and the socio-economic growth of an area. To meet the demand for groundwater over the increasing population, the scientific community stresses the prospective of identifying groundwater potential zones (GWPZ), aiming at conservation, planning, and regulation for optimum utilization of this natural resource. The GWPZ evaluation of the Karuvannur River Basin (KRB) in the southern part of India was carried out through GIS-Fuzzy-Analytical Hierarchy Process (FAHP), by assigning weights to interdependent factors controlling groundwater potentials such as geomorphology (Gm), slope(S), geology(G), drainage density (Dd), lineament density (Ld) and Land Use Land Cover (Lu) with the aid of Geographical Information system (GIS). FAHP includes a pairwise comparison of criteria and sub-criteria elements expressed with Triangular Fuzzy Numbers (TFNs), which can avoid vagueness, imprecision, and uncertainty of the linguistic scale. The model result was validated with the depth to water level data of dug wells by plotting them on the GWPZ map. This study reveals that the FAHP method is efficient in delineating GWPZ in this region with an accuracy of 80.9%. Further, GWPZ are reliant on underlying lithology; very good (48.1%) aquifers occupy the coastal area; good (12.7%); moderate (18.3%) aquifers are provided by the secondary porosity provided by underlying structures while poor aquifers (20.9%) occupy the eastern hard rock areas of KRB. This type of cost-effective FAHP method is efficient in delineating GWPZ and can be used for sustainable groundwater policies and management.

Evaluation of digital economy development level based on multi-attribute decision theory.

The maturity and commercialization of emerging digital technologies represented by artificial intelligence, cloud computing, block chain and virtual reality are giving birth to a new and higher economic form, that is, digital economy. Digital economy is different from the traditional industrial economy. It is clean, efficient, green and recyclable. It represents and promotes the future direction of global economic development, especially in the context of the sudden COVID-19 pandemic as a continuing disaster. Therefore, it is essential to establish the comprehensive evaluation model of digital economy development scientifically and reasonably. In this paper, first on the basis of literature analysis, the relevant indicators of digital economy development are collected manually and then screened by the grey dynamic clustering and rough set reduction theory. The evaluation index system of digital economy development is constructed from four dimensions: digital innovation impetus support, digital infrastructure construction support, national economic environment and digital policy guarantee, digital integration and application. Next the subjective weight and objective weight are calculated by the group FAHP method, entropy method and improved CRITIC method, and the combined weight is integrated with the thought of maximum variance. The grey correlation analysis and improved VIKOR model are combined to systematically evaluate the digital economy development level of 31 provinces and cities in China from 2013 to 2019. The results of empirical analysis show that the overall development of China’s digital economy shows a trend of superposition and rise, and the development of digital economy in the four major economic zones is unbalanced. Finally, we put forward targeted opinions on the construction of China’s provincial digital economy.

A risk allocation model among the elements of freeway projects in public-private partnership (PPP) method using integrated fuzzy multi-criteria decision-making techniques

ABSTRACT In the present study, an appropriate risk assessment and allocation model was developed between the various elements of PPP based infrastructure projects. For this purpose, after a review of the research literature and identification of the most important risks, with a case study on PPP-based freeway projects in Iran, a systematic model for risk assessment using fuzzy MCDM methods including FAHP has developed in order to critical risk assessment (Objective 1), FTOPSIS Identification of Common Risks in PPP Transportation Projects (Objective 2) and FDEMATEL for Allocation and Impact of Risk Between Different Project Elements (Objective 3). The results of risk analysis by FAHP method showed that economic and financing, construction and operational risks have the greatest impact, respectively. In addition, the results of FTOPSIS method showed that projects Isfahan-Shiraz Freeway, Salafchegan-Arak Freeway and Khorramabad-Arak Freeway, respectively, were more affected by risks. Finally, the results of FDEMATEL analysis show the degree of interaction and impact strength of risks for each risk and from the perspective of each project manager, which indicates a significant relationship between different risks. The results of this research can be used as a management model in the process of evaluation and risk management of PPP projects.

Assessing cloud manufacturing applications using an optimally rectified FAHP approach

Cloud Manufacturing (CMfg) is a new manufacturing paradigm that promises to reduce costs, improve data analysis, increase efficiency and flexibility, and provide manufacturers with closer partnerships. However, most past CMfg research has focused on either the information technology infrastructure or the planning and scheduling of a hypothetical CMfg system. In addition, the cost effectiveness of a CMfg application has rarely been assessed. As a result, a manufacturer is not sure whether to adopt a CMfg application or not. To address this issue, an optimally rectified fuzzy analytical hierarchy process (OR-FAHP) approach is proposed in this study to assess a CMfg application. The OR-FAHP approach solves the inconsistency problem of the conventional FAHP method, a well-known technology assessment technique, to make the analysis results more trustable. The OR-FAHP approach has been applied to assess and compare 10 CMfg applications.

Evaluation of the prediction capability of AHP and F-AHP methods in flood susceptibility mapping of Ernakulam district (India)

Floods are one of the frequent natural hazards occurring in Kerala because of the remarkably high annual rate of rainfall. The objective of this study is to prepare the flood susceptibility maps of Ernakulam district by integrating remote sensing data, GIS, analytical hierarchy process (AHP), and fuzzy-analytical hierarchy process methods. Ernakulam is one of Kerala's most flood-prone districts. The development of this map can help to raise awareness about the risks of flooding. Factors such as slope angle, soil types (texture), land use/land cover, stream density, water ratio index, normalized difference built-up index, topographic wetness index, stream power index, aspect, and sediment transport index have been selected. The area of the final maps is grouped into five flood susceptible zones, ranging from very low to very high. The major reasons for flood occurrence in Ernakulam district are the combined effect of multiple factors such as excess silting, reduction of stream width due to anthropogenic activities, and changes in land cover and land-use pattern, lower slope, higher soil moisture content, lower stream capacity, and poor infiltration capacity of soils. The prepared map was validated using the receiver operating characteristic (ROC) curve method. The area under the ROC curve (AUC) values of 0.75 and 0.81 estimated by the ROC curve method for the AHP and F-AHP methods are considered acceptable and excellent, which confirms the prediction capability of the prepared maps. The very high susceptible zone constitutes around 19% of the district. This map is useful for land-use planners and policymakers to adopt strategies that will reduce the impact of flood hazards and damage in the future.

Hybrid FAHP and TOPSIS to determine recommendation for improving SMEs facing Covid-19 pandemic

The Covid-19 pandemic has had an impact on domestic economy, such as a decrease in people’s consumption and purchasing power, a decline in company performance, as well as SMEs. This situation, SMEs sector controls 99.99% of all existing businesses, employs 97.16% of private sector workforce, and contributes 57.5% to Indonesia’s gross product. Various government program efforts in helping Batik SMEs players face Covid-19 pandemic so that they are right on target. The large number of SMEs in Bangkalan is around 166,768, causing department to find it difficult to determine recommendations for improvement for each MSME. Based on these problems, a cooperative model for the SMEs industry is needed so that official work program runs smoothly on target. The method used is FAHP and TOPSIS integration method, FAHP method is used to determine weighting and TOPSIS method is used for ranking and recommendations for improvement. The advantage of FAHP is consistency index to control error rate of decision. TOPSIS method is capable of making multi-criteria decisions based on alternative SMEs industry mapping process. The purpose is make a recommendation model for improvement using hybrid method of FAHP and TOPSIS with balanced scorecard indicators for learning and growth perspective. The research contribution is to make decisions based on group recommendations and consistency ratio (CR) is less than 0.1. The findings research, that the influential indicators are batik business ownership and variations of batik motifs. The recommendations for improvement, the average MSME still does not have branding.

Salt Farmer measurement performance system facing Covid-19 pandemic used interval type-2 FAHP Method

Indonesia is an archipelagic country with a coastline of about 81,000 km and has a variety of very large biological and non-biological resources. Position as an archipelagic country with a very wide sea causes each region to have the potential to produce salt. The Covid-19 pandemic has resulted in various negative impacts on several fields such as the economy, social, SMEs and community services. Covid-19 has also resulted in a decrease in salt production and farmers also have difficulty marketing it. The research problem is the large number of salt farmers and number of indicators in providing assistance so that a model for measuring performance of salt farmers is needed. This performance measurement model is guided by several indicators, namely land area (K1), production result (K2), business capital (K3), and marketing system (K4). The method used Interval type-2 Fuzzy Analytic Hierarchy Process (IVFAHP). IVFAHP is used to determine indicators that most influence measurement of salt farmers. This study aims to build a model for measuring performance of salt farmers to increase economic productivity and ability of human resources to deal with COVID-19 pandemic. The contribution is a group-based decision by developing the fuzzy interval type-2 method with triangular fuzzy number (TFN) one midpoints. The findings from study are that the most influential indicators in dealing with COVID-19 pandemic are business capital and salt marketing. This research also produces recommendations for improvement salt farmers in an effort to increase salt production.