Fuzzy Analytic Hierarchy Process Research Articles

Life Cycle Risk Management for Improving Labor Productivity in Construction Projects in Türkiye

The construction industry, being labor-intensive, prioritizes productivity to boost project performance, yet struggles to achieve expected levels despite increased focus by scholars and practitioners. This lagging causes significant losses in time, cost, and quality performance of construction projects but also broader implications for resource efficiency and environmental impacts. As a remedy to the multifaceted issue, this study aims to identify and evaluate life cycle risks of productivity management in construction projects in Türkiye. A comprehensive literature review identified risk factors affecting labor productivity, followed by a discussion session to finalize the decision framework, including life cycle phases of productivity management and risk factors in each phase. Then, the fuzzy analytical hierarchy (AHP) process revealed the most critical risk factors in each phase, followed by semi-structured interviews to reveal measures for addressing the most significant risks. The findings show that productivity management in construction projects contains nine phases. In addition, the most important factors were chiefly related to collaboration, information sharing, lack of supervision, work interruptions, and changes. Findings from semi-structured interviews emphasize regular employee training and open communication to enhance project outcomes, optimize workflows, and promote sustainability. The study’s key contribution is introducing a life cycle approach to construction productivity management, a previously unexplored perspective. This provides an effective framework that can be implemented in construction projects to manage and improve labor productivity as a whole-life cycle approach.

Exploring and Overcoming Challenges for Digital Transformation in the Energy Sector Toward Carbon Neutrality

ABSTRACTChina is committed to carbon neutral by 2060 to reduce its carbon footprint to zero. This research investigates the challenges surrounding the adoption of digitalisation in the energy sector and proposes policy plans to overcome them to achieve sustainability goals. This study utilised the fuzzy Analytical Hierarchy Process (AHP) method to assess the key challenges and sub‐challenges. Next, the fuzzy Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) method is used to rank the policy plans to overcome the challenges for digital transformation in the energy sector toward carbon neutrality in China. The result of fuzzy AHP identified that financial constraints (DES1) is the most crucial challenge hindering digitalisation efforts with a weight of 0.172, followed by operational and management barriers (DES8) with a weight of 0.156, and regulatory and policy challenges (DES2) with a weight of 0.144. Next, the findings of fuzzy TOPSIS revealed that enhancing financial viability and investment (PP2) has obtained the first rank plan with a score of 0.065, following fostering regulatory support and policy development (PP3) with a score of 0.063 and building public trust and engagement (PP10) with a score of 0.060. These policy plans play a crucial role in addressing the challenges associated with adopting digitalisation in China's energy sector, toward a more efficient, sustainable and resilient energy transition.

Reactions towards online advertisements for millennials: a fuzzy AHP approach

Reactions towards online advertisements for millennials: a fuzzy AHP approach

Evaluation of Barriers to Digital Transformation in Maritime Logistics Based on A Spherical Fuzzy Multi-Crıteria Decision-Making Framework

Purpose: The objective of this study is to identify and prioritize the barriers to the adoption of digital transformation in order to ensure more efficient and effective operation of the maritime logistics sector. Methodology: The Spherical Fuzzy Analytical Hierarchy Process (SF-AHP) method, which gives successful results in modelling uncertainty and uses Spherical fuzzy sets (SFSs), is used to rank the barriers affecting adoption of digital transformation according to their importance. Findings: In the application part of the study, firstly the barriers in the adoption of digital transformation were determined and as a result of expert evaluations, the barriers were ranked according to their importance by applying the steps of the method. When the results obtained from the study were examined, ‘Technology’ is the most important barrier category (B1) (0.341) for the adoption of digital transformation in maritime logistics, followed by the main barrier categories related to “Security” (B4) (0.266), “Environment” (B3) (0.223) and “Organisation” (B2) (0.171) respectively. Originality: This study represents a pioneering effort in the field of maritime logistics, as it is the first to identify and prioritize the barriers to digital transformation that impede operational efficiency.

Ranking of Autonomous Technologies for Sustainable Logistics Activities in the Confectionery Industry

The food supply chain (FSC) faces significant challenges, including the short shelf life of products, stringent food safety standards, and the growing demand for online ordering. These challenges underscore the need for a resilient and sustainable FSC, particularly in the confectionery industry, which is further burdened by the demand for innovative and healthier products. The aim of this paper is to optimize material handling activities in warehouse operations within the confectionery industry by ranking and selecting adequate material handling equipment (MHE). This paper proposes a novel hybrid multi-criteria decision-making model that integrates the Simple Aggregation of Preferences Expressed by Ordinal Vectors Group Decision Making (SAPEVO-M), Fuzzy Analytic Hierarchy Process (FAHP), and Fuzzy COmprehensive distance-Based Ranking (FCOBRA) methods. The model was applied to a real-world case study involving four alternative solutions and twelve defined evaluation criteria. The application of the model identified the implementation of an Automated Guided Vehicle system (AGVs) as the optimal alternative, offering substantial automation of logistics activities and addressing identified company challenges. The engagement of AGVs is estimated to reduce operational costs by 20%, improve warehouse operation efficiency by 30%, and decrease CO2 emissions by 25%. The contribution of this paper lies in the development of a methodological framework for evaluating and selecting MHE, as well as in highlighting the importance of optimizing material handling processes in the confectionery industry.

An Expert-Based Analysis of ESG Reporting in the context of the Circular Economy

Existing literature has highlighted how Environmental Social Governance (ESG) reporting enables companies to drive their Circular Economy (CE) practices. However, current approaches to ESG reporting do not specifically consider how company activities and decisions about CE contribute to sustainable development. Indeed, CE has a great potential to ensure that companies actively participate in the achievement of the United Nations 2030 Agenda Goals although a more effective way to link CE and sustainability reporting processes is necessary. The present paper recognizes the importance of developing a standardized approach that aligns ESG metrics with CE practices to enhance both transparency and accountability. To this end, taking into consideration the relevance of the GRI guidelines to make the ESG performance of companies more transparent, an expert-based analysis of the importance of GRI topics to capture the ability of CE practices to create circular value is proposed. Creating circular value through CE improves the company’s profitability and resilience while reducing costs for customers, and benefits society and the environment. The use of the fuzzy AHP (F-AHP) method ensures that the relevance of the economic, environmental, and social performance is estimated to make ESG reporting more informative about the company's commitment to a restorative and regenerative business. The findings offer guidelines for using CE reporting information to compare the companies’ contributions to SDGs Keywords: ESG reporting, GRI standards, Circular Economy (CE), Fuzzy Analytic Hierarchy Process (F-AHP), Sustainable Development Goals (SDGs), circular value.

Advanced Solar Energy Potential Assessment in Malawi: Utilizing High-Resolution WRF Model and GIS to Identify Optimal Sites for Photovoltaic Generation

Solar PV technology offers a promising electricity alternative in developing countries like Malawi, which face limited electricity access and increased vulnerability to climate change. This study assesses solar resources using the Weather Research and Forecasting (WRF) model's high-resolution capabilities. A two-year simulation helped compute solar PV's technical potential, focusing on annual energy generation, capacity factor, and global horizontal irradiance (GHI) variation. GIS and expert-based fuzzy analytic hierarchy process (FAHP) identified optimal solar PV sites, considering eight key constraints. Findings show an annual average daily peak GHI of 1106.45 W/m2 and a daily energy inflow of 6.76 kWh/m2/day, with a peak in October and a diffuse fraction of 10.61%, indicating clear skies ideal for solar PV. The average annual energy yield is about 14.11 TWh with a 21.48% capacity factor. Notably, the most suitable lands for solar PV, covering 10,288.2 km2 or 15.6% of acceptable land, are predominantly in the southern region. Thus, these solar PV potentials offer the possibility to significantly reduce CO2 emissions, placing Malawi in agreement with worldwide sustainability goals. Generally, this research lays a crucial foundation for Malawi's renewable energy strategies, highlighting the opportunity for improved electrification and more effective climate change mitigation endeavors.

Analysing the Failure Modes of Water Treatment Plant Using FMEA Based on Fuzzy AHP and Fuzzy VIKOR Methods

Analysing the Failure Modes of Water Treatment Plant Using FMEA Based on Fuzzy AHP and Fuzzy VIKOR Methods

Barriers to renewable energy investments in Turkiye: A fuzzy AHP approach

Barriers to renewable energy investments in Turkiye: A fuzzy AHP approach

Comparison of the Distance Learning Modalities Regarding Teaching Capacities and Performances on the Learners

ABSTRACTEspecially after the COVID‐19 pandemic, people have distances among each other, and this situation has affected everything. Education, which has been the most important thing for humanity since the beginning of history, has also been affected. To continue and survive the system, people started using and adapting different distance learning with the help of electronic devices, internet and technology. However, the impact of these new distance learning modalities does not have the same teaching capacity and performance on the learners. Besides, evaluation of the learners, fairness, interaction, feedback, etc. are the other important problems of the new distance learning modalities. Nevertheless, to discover the effect of the distance learning modalities regarding teaching capacities and performances on the learners, they are compared in this study with an integrated fuzzy multi criteria decision making model. The proposed model consists of two parts; fuzzy analytic hierarchy process and ELECTRE methods. In the first part, weights and the decision matrix are calculated by using a fuzzy analytic hierarchy process. Then, in the second part, distance learning modalities are evaluated with the application of the ELECTRE method through the decision matrix according to weights.

Selection of Low-Carbon Contractors in a Fuzzy Multi-Objective Environment

The selection of contractors entails multiple uncertainties, including the lack of clear delineation of contractor qualifications, ambiguity surrounding project manager capabilities, and the uncertain nature of carbon emissions. These uncertainties compound the complexity involved in genuinely evaluating and choosing contractors. This paper establishes a fuzzy multi-objective contractor selection model that accounts for cost reduction, optimization of contractor qualifications, organizational management enhancement, carbon emissions reduction, and reputation optimization. Leveraging the Fuzzy Analytic Hierarchy Process (F-AHP) and Fuzzy Compromise Programming (F-CP) methods, we have devised a fuzzy multi-objective contractor selection model and outlined the procedural steps for its implementation. A case study was conducted to validate the effectiveness of the model we proposed.By applying this model to the case, we successfully transformed the complex multi-objective programming into a straightforward single-objective linear programming. Furthermore, based on the model, the weights assigned to cost, qualification indicators, management level, carbon emissions, and contractor reputation are 0.54, 0.09, 0.05, 0.19, and 0.13, respectively. By solving the model, we were able to identify the most suitable contractor.This paper aids the decision-making process in selecting an appropriate low-carbon contractor.

Analysis of Geographic Suitability of Chinese Medicine Based on Analytic Hierarchy Process-Fuzzy

Analysis of Geographic Suitability of Chinese Medicine Based on Analytic Hierarchy Process-Fuzzy

A Fuzzy Multi-Criteria Approach for Selecting Open-Source ERP Systems in SMEs Using Fuzzy AHP and TOPSIS

In a rapidly growing and competitive business era, selecting an open-source Enterprise Resource Planning (ERP) system is a critical step to support the efficiency and effectiveness of company operations. This research aims to propose an innovative methodology by integrating the fuzzy Analytical Hierarchy Process (fuzzy AHP) and fuzzy Technique for Order Preference by Similarity to the Ideal Solution (fuzzy TOPSIS) to improve the open-source ERP selection process. The method involves eight criteria and 26 sub-criteria to comprehensively evaluate 11 open-source ERP alternatives, specifically for SMEs in the transportation services sector in Indonesia. System quality has been identified as a critical factor in the selection of an open-source ERP system, with particular emphasis on aspects such as security and reliability. These sub-criteria are considered the most influential in determining the suitability of a system. The analysis further indicates that the 10th ERP alternative as the best choice, consistently outperforming others in meeting the defined criteria. Additionally, sensitivity analysis confirmed the robustness of this choice, demonstrating its stability and effectiveness despite changes in criteria weights. Beyond its practical implications for SMEs, this research contributes a versatile evaluation framework that can be adapted to other industries seeking effective ERP solutions. The findings emphasize the importance of structured decision-making in technology adoption, offering comprehensive and reliable guidance for organizations aiming to optimize their operations through open-source ERP systems. This study not only bridges a critical gap in ERP selection for SMEs but also establishes a methodological foundation for future research and applications across diverse industry sectors.

Multi-hazard vulnerability zone identification using GIS-based fuzzy AHP and MCDM techniques

Multi-hazard vulnerability zone identification using GIS-based fuzzy AHP and MCDM techniques

Analysis and optimization strategies for key factors in children’s clothing design

This study delves into the critical factors influencing children’s clothing design through a multifaceted approach. The investigation elucidates the most significant design elements by employing qualitative research methods, the fuzzy Delphi method (FDM), and the fuzzy analytic hierarchy process (FAHP). Initially, semi-structured interviews were conducted with experienced professionals, encompassing children’s clothing designers and related specialists with a minimum of fifteen years of expertise. These interviews served to gather valuable insights and experiences. Subsequently, the FDM was utilized to assess the relative importance of identified design elements. Finally, the FAHP was implemented to determine the weights assigned to each factor, establishing a hierarchy of importance. The findings reveal that safety reigns supreme as the most critical design consideration. Following safety are comfort, style elements and practicality. Safety prioritizes the utilization of non-toxic materials and secure fastenings. Comfort emphasizes breathable fabrics and textures that are gentle against the skin. Style elements encompass colour palettes, patterns and the incorporation of creative design aspects. Practical considerations delve into age-appropriateness, freedom of movement, garments with multifunctional purposes and enduring durability. This comprehensive study offers invaluable guidance for the field of children’s clothing design. It empowers designers to effectively address the needs of children while aligning with parental expectations. Ultimately, this approach propels market development and fosters children’s enhanced quality of life.

A two-stage model of the fuzzy analytic hierarchy process and the fuzzy synthetic evaluation technique to prioritize sustainable sanitation services under uncertainty

In the context of the Sustainable Development Goals (SDGs), which strive to ensure comprehensive access to fundamental water, sanitation, and hygiene (WASH) services, it is extremely imperative to prioritize communities in need and still disadvantaged. Moreover, tackling the worldwide sanitation crisis entails advancing the development of productive and sustainable sanitation systems and infrastructure. Sanitation planning is a multidimensional exercise encompassing multiple dimensions, stakeholders, and strategies, typically with conflicting objectives. Poor planning, funding obstacles, stakeholder priorities, climatic changes, growing populations, system constraints, and user engagement all complicate the entire process. Intelligent strategic decision-making is crucial, particularly for resource-constrained economies. Multi-criteria decision analysis (MCDA) models offer opportunities to figure out and resolve such conflicts, while also optimizing prioritization and policymaking. These models assist with considering trade-offs, data uncertainty, and arriving at decisions by considering technical, economic, social, and environmental sustainability. In the present work, a two-stage integrated model of the Fuzzy Analytic Hierarchy Process (FAHP) and the Fuzzy Synthetic Evaluation Technique (FSET) was developed, accompanied by a sensitivity analysis, yielding an assessment index designated as the Sanitation Priority Index (SPI). This index is particularly applicable in prioritizing and categorizing communities in need of sanitation infrastructure (e.g., wastewater collection systems and treatment plants), considering competition over scarce resources, reliance on third-party funds, and sustainability factors. The decision-making problem was designed as a hierarchical structure that integrates all problem elements and specifies the key criteria contributing to the SPI. Fuzzy set theory handles data uncertainty, with FAHP evaluating criteria significance in a group decision-making context and FSET designing criteria membership functions. Field data on criteria contributing to the SPI is transformed into fuzzy intervals, synthesized, and defuzzified to derive the SPI at community level. The model’s robustness is examined using sensitivity analysis as it is applied to several Palestinian communities lacking sanitation infrastructure. The outcomes show that the demographic criterion has the major impact on the SPI (20.38%), followed by water consumption (16.76%) and wastewater reuse potential (15.40%). Environmental risks account for 12.40%, utilities’ competency (11.5%), and industrial wastes risks (8.72%). The socioeconomic context is valued at 5.10%, geographical constraints at 4.51%, and license constraints at 4.8%. Out of the 25 communities investigated, five exhibited SPI values surpassing 60.0%. Eleven communities possessed SPI values between 50.0% and 60.0%, and nine achieved SPI values ranging from 40.0 to 50.0%. The sensitivity analysis application reveals almost complete stability in prioritizing communities. Introducing this model into relevant bodies’ sanitation management practices and planning strategies holds the potential to significantly boost sustainable sanitation services as well as the performance of water and wastewater utilities. It further enables the incorporation of additional criteria and the interests of more stakeholders.

Assessing groundwater artificial recharge suitability in the Mi River basin using GIS, RS, and FAHP: a comprehensive analysis with seasonal variations

The escalating depletion and irrational exploitation of global groundwater resources have led to severe ecological and environmental repercussions and exacerbated water scarcity. Therefore, effective, sustainable management remains urgent to ensure the security and balance of water resources. This study utilized an integrated approach that combines Geographic information systems (GIS), remote sensing, and the fuzzy analytic hierarchy process to assess the suitability of artificial recharge in the Mi River watershed, creating 14 thematic layers. FAHP is a crucial tool for assigning relative weights to these layers, enabling a comprehensive assessment of the suitability of artificial recharge. The study area was categorized into five suitability classes with notable seasonal variations. During the wet season, the areas were rated as follows: 5.80%, very good; 35.24%, good; 41.96%, moderate; 16.11%, poor; 0.89%, very poor. These percentages during the dry season changed to 11.02% (very good), 39.80% (good), 34.39% (moderate), 10.39% (poor), and 4.39% (very poor). The central basin regions were deemed less suitable for artificial recharge. The model's accuracy was validated by analyzing receiver operating characteristic curves derived from a dataset of 29 wells. This study provides a scientific foundation for sustainable groundwater management within the Mi River watershed and substantiates the effectiveness of GIS and FAHP in evaluating artificial recharge potential. Future research should improve data accuracy to increase model precision and extend its applicability to various geographical and environmental settings.

Evaluating the desirability of energy inequality mitigation strategies within underserved communities in sub-Saharan Africa

Due to inequality, millions of people in sub-Saharan Africa lack access to reliable and affordable energy. Attempts this challenge has attracted different approaches addressing this challenge have attracted different approaches, such as non-linear modelling approaches, which have attracted different approaches, such as non-linear modelling approaches, which have attracted different techniques, such as non-linear modelling. While these approaches have been used to generate information about technical requirements for solving energy inequality, limited information existscresocio-economic information about energy inequality. This research, therefore, uses a multi-criteria decision-making (MCDM) framework to address energy inequality in sub-Saharan Africa. The framework contains a fuzzy analytical hierarchical process (FAHP) for determining criteria importance and VIKOR (VIseKriterijumska Optimizacija i Kompromisno Resenje) for emerging socio-economic criteria and mitigation strategies for energy inequality. Also, the framework contains nine socio-economic criteria and ten mitigation strategies. A sub-urban community was used to evaluate the framework performance. This study compared the VIKOR method performance with a fuzzy PROMETHEE (reference Ranking Organization METHod for Enrichment Evaluation) and a fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method. The results from the FAHP method showed that environmental sustainability was the fundamental criterion for evaluating mitigation strategies for energy inequality. On the other hand, the results from the VIKOR method indicated that decentralized renewable energy solutions were the most suitable strategy for addressing energy inequality. According to the TOPSIS method results, cross-subsidization models was the best strategy for addressing energy inequality. Based on Spareman's correlation results for VIKOR and TOPSIS methods, it was observed that a significant association between these methods. On the other hand, there was no significant correlation between the VIKOR and PROMETHEEE results. The aggregation of the VIKOR, PROMETHEE, and TOPSIS results show that decentralized renewable energy solution was the best strategy for addressing energy inequality for the case study. The research findings will guide stakeholders, especially investors, on the best action for investment initiatives in sub-Saharan Africa.

Prioritization of Human-Centric and Sustainable City Criteria by Proportional Spherical Fuzzy Analytic Hierarchy Process

Human-centric and sustainable cities have become one of the most popular research areas today. They are based on a holistic approach that aims to both improve people’s quality of life and ensure environmental sustainability. The weighting of numerous tangible and intangible criteria used in the performance evaluation of these cities has emerged as an important problem. The symmetrical representation of vague and imprecise data using fuzzy set theory is an absolute necessity for a successful weighting process. In this study, symmetrical representation of especially intangible criteria is carried out with proportional spherical fuzzy sets. Proportional spherical fuzzy sets provide significant convenience to the expert in determining the membership, non-membership and hesitancy degrees and ensure that the assigned values are more accurate and consistent. In the study, five main human centric and sustainable city (HCSC) criteria and 26 HCSC sub-criteria determined from the literature were weighted. In addition, criteria weights were obtained by classical spherical fuzzy analytic hierarchy process (AHP) for comparison purpose. The first four most important HCSC criteria were determined as water management and conservation, employment/unemployment rate, carbon emission reduction strategies and economic sustainability, respectively.

Assessing the Equitable Renewable Energy Access and Environmental Justice for Sustainable Development in China

ABSTRACTThe pursuit of sustainable development in China necessitates a comprehensive evaluation of renewable energy access and environmental justice. As China experiences rapid economic growth and shifts towards cleaner energy sources, it is crucial to examine the fairness of renewable energy distribution and the equitable allocation of environmental benefits and burdens. This study explores the complexities involved in balancing renewable energy, social equity, and environmental factors. A twofold methodological approach was employed such as the fuzzy analytic hierarchy process (AHP) was first used to systematically assess the equity of renewable energy distribution, identifying six key factors and 24 sub‐factors that influence renewable energy access and environmental justice. The results from fuzzy AHP show that the distribution of environmental burdens and socio‐economic equity are the most critical factors shaping renewable energy access and environmental justice. To further refine strategic insights, the fuzzy complex proportional assessment (COPRAS) method was applied, ranking six strategic approaches for advancing renewable energy access and environmental justice. The top‐ranked strategy was expanding renewable energy infrastructure in underserved regions which emerged as the most impactful, emphasising the importance of addressing geographic disparities. Following closely were strategies aimed at strengthening financial mechanisms for low‐income households and promoting community‐led renewable energy projects, emphasising the importance of economic support and local empowerment in achieving energy justice.