Fuzzy Analytic Hierarchy Process Approach Research Articles

Evaluating Lecturer Performance in Vietnam: An Application of Fuzzy AHP and Fuzzy TOPSIS Methods

Higher education is regarded as being of paramount importance in Vietnam and as being essential to raising the level of the country's labor force and promoting economic progress. Evaluation of lecturers is one of the institution's activities and a crucial component of managing human resources in higher education institutions. How to evaluate faculty members' overall performance using a range of criteria is one of the key evaluation-related challenges. This study presents a method that uses fuzzy analytical hierarchy process (AHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) to assess and rank the performance of lecturers. Specifically, the evaluation framework is developed by identifying criteria and sub-criteria based on a comprehensive review of existing literature. Following that, the fuzzy AHP approach is used to determine the weights of the criteria and sub-criteria using the pairwise comparisons. The Fuzzy TOPSIS approach is employed to assess and prioritize lecturers identified through expert evaluation. When applied in group decision-making, utilizing fuzzy AHP and fuzzy TOPSIS promotes agreement among decision-makers and diminishes uncertainty in decision-making processes. The utilization of the multiple criterion measurement approach can then be used to carry out the evaluation. The suggested framework is also demonstrated via a case study. The use of this framework can improve the evaluation's objectivity, accuracy, and scientific methodology. It is believed that this work will assist managers of higher education institutions improve their standards for educational quality.

Examining the role of digitalization and technological innovation in promoting sustainable natural resource exploitation

In the era of technological advancement, the potential of digitalization and technical innovation to revolutionize sustainable resource exploitation has become a focal point. The promises of reduced environmental impact, heightened efficiency, and improved socio-economic outcomes underscore the transformative power that digitalization holds for resource management. To this extent, the fuzzy Analytical Hierarchy Process (AHP) and fuzzy VIsekriterijumsko KOmpromisno Rangiranje (VIKOR) methods are used to examine challenges and come up with possible solutions for the mining sector in Pakistan to adopt digital transformation. The study identifies several key challenges, sub-challenges, and strategies, giving readers a thorough grasp of digital transformation. These challenges and sub-challenges are evaluated and ranked according to their relative weights using the fuzzy AHP approach. The fuzzy VIKOR method is applied to determine strategies that can help overcome these challenges and promote digitalization and technological innovation in the sustainable exploitation of natural resources. The results of fuzzy AHP show that policy and regulation, infrastructure, and human capital are key challenges. The findings of fuzzy VIKOR indicate that robust policy development, investment in Research and Development (R&D), and leveraging global trends and partnerships are key strategies to overcome the challenges. These findings provide valuable insights for policymakers, researchers, and practitioners, offering new perspectives on integrating digital technology into the natural resource sector to foster sustainable development.

Bridging the knowledge gap of restaurant DINESERV attraction attributes between customer expectations and restaurateur priority ranking

ABSTRACT This study aims to explore and reveal the perception gap of restaurant attraction attributes between customers’ expectations and restaurateurs’ prioritization in casual and fine dining Korean table d’hôte restaurants. This study surveys the 16 critical restaurant attributes for restaurant visiting customers and restaurateurs. And, we employ the integrated importance-performance analysis (IPA) and fuzzy analytical hierarchy process (FAHP) approaches by setting the customers’ importance and the restaurateurs’ priority ranking for restaurant attributes as vertical and horizontal axes, respectively. The results of integrated IPA-FAHP suggested that most of the restaurant attributes were situated in the “Pairwise Harmonic Zone,” indicating that the customers’ importance and restaurateurs’ priorities were in agreement. Conversely, the attributes such as “restaurant ambience” and “restaurant sanitation and cleanliness” placed a relatively lower restaurateurs’ priority compared to high customers’ expectations. Casual and fine dining restaurants have different restaurant attraction attributes and operating strategies. Restaurateurs require operating initiatives and leverage strategies tailored to their characteristics to maximize operational efficiency. This study is a first attempt to bridge the perception gap of restaurant attraction attributes between expectation and priority ranking by using integrated IPA-FAHP approaches. We provide restaurant operating guidelines combining both customers’ and restaurateurs’ perspectives on restaurant attributes.

Analyzing the relationship between natural resource management, environmental protection, and agricultural economics for sustainable development in China

Sustainable development is crucial for achieving a balance between economic growth, social well-being, and environmental preservation. This study aims to evaluate the dimensions of natural resource management, environmental protection, and agricultural economics for promoting sustainable development in China. In this regard, the fuzzy Analytical Hierarchy Process (AHP) and fuzzy VIekriterijumsko KOmpromisno Rangiranje (VIKOR) approaches are used for the analysis. The hybrid approach combines the benefits of fuzzy logic and multi-criteria decision-making (MCDM) techniques, allowing for the consideration of uncertainties and imprecise data in decision-making. The study incorporates six criteria, twenty-four sub-criteria, and five strategies in a comprehensive evaluation framework. According to the results obtained using the fuzzy AHP method, it is evident that the primary criteria influencing sustainable development in China are economic viability, policy and governance, and environmental impact. Within these criteria, specific sub-criteria such as cost-effectiveness, policy alignment, air quality, and social inclusion emerge as key areas of focus. Furthermore, the results of the fuzzy VIKOR method show that investing in research and innovation, strengthening environmental regulations, and strengthening climate change adaptation are the most suited strategies to guide sustainable development efforts. To ensure sustainable development in China, policymakers need to give importance to implementing strategies stressing research and innovation, strengthened environmental regulations, and enhanced climate change adaptation.

Identification and Weighting of Supply Chain Risks with the Help of Fuzzy Analytical Hierarchy Process Approach (Case Study: Mobarakeh Steel Complex of Isfahan)

Identification and Weighting of Supply Chain Risks with the Help of Fuzzy Analytical Hierarchy Process Approach (Case Study: Mobarakeh Steel Complex of Isfahan)

Supply Chain Resiliency in Post- COVID-19 Times: Evaluating the Inhibitors Using a Fuzzy Analytic Hierarchy Process Approach

The COVID-19 pandemic has significantly affected the way supply chains function and operate. Supply chain resiliency (SCR) has become increasingly more relevant to the pandemic, with corporations and governments realising that their supply chains were not as resilient leading to shortages/delays of many consumer products. Delays in the delivery of essential items, including medicines, food supplies and healthcare equipment, have exposed the challenges that a supply chain might face during a major disruption such as the global pandemic, regional conflicts and natural disasters. The purpose of this study is to identify and evaluate some of the critical inhibitors associated with SCR during COVID-19. The study employs multi-criteria decision-making utilising the fuzzy analytical hierarchy process. This research was conducted in the context of the Indian pharmaceutical supply chains. The research showed that there are seven major inhibitors to SCR. The findings of the current study are expected to aid the pharmaceutical supply chain managers in identifying and evaluating the critical inhibitors to achieving SCR and designing strategies to mitigate any future catastrophe like a global pandemic.

Towards an IoT based secured framework for smart cities

<p>Cities are evolving into smart urban environments, where various devices, technologies, services, connections, blocks, and storage systems are transforming to embrace smart solutions, departing from traditional counterparts. This intricate network of interconnected devices collectively constitutes the Internet of Things (IoT), promising users a life of enhanced convenience. However, this transformation also introduces challenges, particularly in managing loosely linked devices and transmitting information across networks. This study conducts a comprehensive review of the various components contributing to the formation of a smart city, scrutinizing the challenges and factors that influence them. The overarching objective is to identify specific areas within smart cities grappling with cybersecurity challenges and ascertain the relative significance of each area. Data for this research is gathered through questionnaires, expert opinions, and paired comparisons drawn from previous studies, and employs the Fuzzy Analytic Hierarchy Process approach to determine the weight of each factor and sub-factor, subsequently ranking them. Among the nine identified factors, the "Smart Security" factor is the most critical, with a weight of 0.198, signifying its paramount importance. To overcome the security challenges in smart cities, we introduce an advanced secure framework (ARPL) for detecting security threats, using the Routing Protocol for Low Power and Lossy Networks (RPL) as its foundation. The advanced framework is adept at identifying a variety of attacks. Performance assessments of the proposed framework encompass several key parameters, such as ADA, TPR, FPR, and end-to-end delay. The positive outcomes observed strongly endorse the effectiveness of the proposed framework, positioning it as an optimal solution for RPL-based smart environments.</p>

Secure software design evaluation and decision making model for ubiquitous computing: A two-stage ANN-Fuzzy AHP approach

Ubiquitous computing systems are deployed everywhere to process and service complex applications in real time. It has been noticed that most ubiquitous computing practitioners are trying to develop a highly secure design while maintaining usability. Unfortunately, the highly secure design of software becomes worthless because the usability of software is very low. When improving the security of software design, underlying security design threats (SDTs) and secure design practices (SDPs) play an important role in improving the design security of ubiquitous computing projects. Therefore, the objective of this study is to develop an SSD evaluation and decision-making model using artificial neural network (ANN) and fuzzy analytical hierarchy process (FAHP), for analyzing the SSD threats and its practices to improve ubiquitous computing. Initially, we identified 11 major SDTs and 50 SDPs to mitigate these threats by conducting an empirical study with 50 ubiquitous computing security experts. Moreover, 13 ubiquitous computing security expert panel reviews were conducted to analyze the interrelationships among the SDTs and SDPs using ANN and FAHP approaches. The ANN outcome presents that the foremost significant independent threat in predicting SSD intention is “SDT2: failure to adhere to accepted security design principles” (100%) importance. Furthermore, the FAHP was used to prioritize the list of SDPs. The results and analysis of this study provide a ranked-based decision-making model, which assists the ubiquitous computing practitioners in considering the most weighted SSD practice (“SDP: Implement Sandboxing and respect for User Privacy” having global weight: 0.05088 and global rank: 1) on priority. The study findings will assist real-world industry experts and academic researchers to improve and develop new techniques for the improvements of ubiquitous computing projects.

Evaluating multi-hazard risk associated with tropical cyclones using the fuzzy analytic hierarchy process model

Multi-hazard events have received attention globally due to their increasing frequency and severity in recent years. The coastal region of Bangladesh is particularly vulnerable to multi-hazard events induced by tropical cyclones (TC), including coastal flooding, extreme precipitation, extreme winds, and salinity intrusion. These events inflict substantial damage on human lives and property, yet there has been limited effort to quantitatively assess the associated risks. This study aims to investigate the spatial distribution of multi-hazard risks stemming from TC events, employing a Fuzzy Analytic Hierarchy Process (FAHP) approach. Risk is assessed in relation to hazard, exposure, vulnerability, and mitigation capacities in the study area. Various indicators are selected to define each of these four risk components, with weights determined through expert input for FAHP modeling. The results indicate that more than 50% of the area faces multi-hazard risks, with the hazard component exhibiting the highest degree of risk association, followed by exposure, vulnerability, and adaptive capacity. Storm surge-induced flooding is identified as the most prominent hazard during TC events, followed by intense precipitation, extreme winds, and salinity intrusion. Areas characterized by high population density, a large number of vulnerable populations (e.g., those under 15 years or over 65 years), low elevation, and underdevelopment are found to be the most risk prone. Notably, the presence of hospitals, cyclone centers, and effective warning systems in proximity to an area enhances its potential to withstand multi-hazard impacts. Among the 19 coastal districts, Cox's Bazar and Feni are identified as the most risk prone. The framework and findings presented in this study offer valuable insights for the development and prioritization of multi-hazard risk mitigation policies by identifying the most vulnerable zones and the associated risk factors.

Fuzzy Analytic Hierarchal Process for Sustainable Public Transport System

The analytic The Analytic Hierarchy Process (AHP) is a well-established methodology for tackling complex multi-criteria decision problems in practical contexts. However, like many decision-making approaches, AHP confronts certain limitations, particularly in scenarios where evaluations are fraught with uncertainty and imprecision. This study sets out to enhance the capabilities of the AHP method and provide a comprehensive evaluation of public bus transport service quality within Budapest, Hungary. To address the inherent uncertainties in real-world decision-making, the study leverages the Fuzzy Analytic Hierarchy Process (FAHP), a fusion of Fuzzy Set Theory with the traditional AHP. This novel approach equips decision-makers with a more robust framework to handle the multifaceted nature of real-world decision problems. The study is grounded in empirical data obtained through dynamic surveys, ensuring its relevance to the actual conditions experienced in Budapest. Expert evaluators, well-versed in the field, contribute their assessments to enrich the analysis. This novel FAHP approach doesn't just promise improved decision-making outcomes; it also champions simplicity and comprehensibility. Its computational efficiency streamlines the decision-making process, providing a powerful tool for evaluating public bus transport service quality, thereby offering a significant contribution to the sustainable development of Budapest's transportation system.

A systematic approach to analyzing the enablers of post-pandemic supply chain resilience in an emerging economy: a fuzzy AHP approach

PurposeThis study aims to identify the enablers of supply chain resilience (SCR) through a literature review and expert panel input in the context of Pakistan and the post-pandemic era. This study also aims to categorize and rank the identified enablers using expert panel input.Design/methodology/approachA review of the extant literature was conducted to investigate and identify the factors that contribute to SCR. The relative ranking of the enablers was carried out by a group of industry and academic experts. The expert panel was convened to compare the main categories and each enabler in pairs and to score the enablers using triangular fuzzy numbers.FindingsThis study identified 16 critical SCR enablers. Using the fuzzy analytic hierarchy process (AHP), these enablers were divided into three groups and analyzed. The results show that financial enablers, technology enablers and then social enablers are prioritized when it comes to SCR in emerging markets. The robustness of the ranking of enablers is tested through sensitivity analysis.Practical implicationsThe results shall be helpful for policymakers and managers to understand the important enablers and also help allocate resources to important enablers. Managers will be able to formulate strategies to achieve SCR in an uncertain environment.Originality/valueThis is one of the first attempts to identify and rank the enablers of SCR in an emerging economy context.

The Impact of Consumer Culture on Innovation Adoption in Developing Countries

There is limited research on the factors that influence people’s continued use of mobile payments in developing countries, and it is likely that these factors vary from country to country. This study aims to explore how the factors affecting the continued use of mobile payments differ between Jordan and India, using the Unified Theory of Acceptance and Use of Technology (UTAUT2) as a framework. Additionally, this study extends the UTAUT2 model by including other factors such as trust, advertising value, payment culture, awareness, smartphone experience, and satisfaction. The study employs the fuzzy Analytic Hierarchy Process (AHP) approach to rank the factors that affect the intention to continue using mobile payments. The results suggest that price value and payment culture have the greatest influence on both Jordanian and Indian perceptions. Furthermore, habit was found to be the third most important factor affecting Jordanian perceptions, while smartphone experience was the third most significant factor affecting Indian perceptions.

Flexible English Learning Platform using Collaborative Cloud-Fog-Edge Networking

In the modern age, developing practical online learning tools for English language learners is challenging due to existing systems’ shortcomings. These systems often need proper instructional design, are well-connected to motivational theories, and have limited infrastructure for data sharing, leading to poor learning outcomes and low motivation. To tackle these issues, a new approach called OAELT has been proposed in this paper. OAELT is an Online Assisted English Learning Tool that uses the Fuzzy Analytical Hierarchy Process (FAHP) and collaborative cloud-fog-edge networking to create a flexible learning design that adapts to the needs and preferences of individual learners. Using the FAHP approach, OAELT provides an improved learning experience by tailoring its design to each learner’s unique needs. The collaborative cloud-fog-edge networking approach uses each computing layer’s strengths to deliver a personalized and seamless learning experience. OAELT employs adaptive and dynamic approaches within a flexible instructional paradigm to ensure effective instructional design. This paradigm facilitates collective learning data exchange across cloud, fog, and edge computing layers. The effectiveness of OAELT was evaluated using a descriptive statistics approach, which included a five-dimension questionnaire for students covering cognition, emotion, action, cooperation, and literacy. The results demonstrated that OAELT could enhance learning effectiveness and motivation while providing a flexible and seamless learning experience. According to the experimental data of the proposed model, 46.8% of learners often read English magazines and newspapers to improve their flexibility in English learning. Additionally, 50.4% classified and memorized English according to their categories, while 59% of learners often used context to memorize. These findings suggest that the traditional methods for flexible English learning are not adequate, and the average score of the student’s methods and strategies is mediocre. However, after using OAELT, some students have been able to use different learning curricular reading. Overall, OAELT’s integration of cloud-fog-edge computing with a flexible English learning design can create a more effective and personalized learning system that addresses the challenges of modern learning.

Examining challenges and solutions for environmental and natural resource management with a focus on mineral resources

The Covid-19 pandemic has caused a significant negative influence on the environment and natural resources, especially in developing countries that already face environmental issues. This research examines the effects of the pandemic on environmental degradation and natural resource depletion in developing countries. In this study, the fuzzy Analytical Hierarchy Process (AHP) and fuzzy Weighted Aggregated Sum Product Assessment (WASPAS) methods are used to examine the challenges and solutions for environmental and natural resource management with a special attention on mineral resources policy. In this regard, the various critical challenges and solutions are proposed for the sustainable development of mineral resources. According to the results of the fuzzy AHP approach, the depletion of natural resources, energy use and emissions, and deforestation and biodiversity loss are of paramount relevance challenges. While, the fuzzy WASPAS results show that sustainable development planning, research innovation, and conservation and protection of natural resources are key solutions in addressing environmental and natural resource depletion after the Covid-19 crisis in developing countries. The findings have enriched our understanding regarding how the Covid-19 outbreak has affected the environment and natural resources in developing countries. The study highlights the significance of considering mineral resources in the overall assessment and the need for sustainable resource management practices throughout the post-pandemic recovery stage.

A Safety Assessment Model for Handling Dangerous Goods in Port Operations: The Key Role of Detection Capability

Recently, resilience studies have been emphasized in the port field, recognizing that many high-risk and unsafe factors in ports might bring serious disasters and economic losses. One major cause of significant losses is accidents from fires, explosions, and the resultant adverse impacts from dangerous goods. Whilst the occurrence of major events related to dangerous goods is relatively low in occurrence, their impact on the environment and economic and social loss, and on human casualties, can be extremely high when they do occur. In order to prevent potential risks and reduce losses, based on a literature review, a safety assessment model was developed with four criteria and 15 sub-criteria of dangerous goods in ports using a fuzzy analytic hierarchy process (FAHP) approach. This model formed the basis for a subsequent stage involving questionnaires with 25 experts. The results of these questionnaires found that the key criteria are detection capability, followed by recovery capability, rescue capability, and resistance capability. Sensitivity analysis is used to identify the criteria’s weight value changes under various scenarios. These findings concern dangerous goods operations management in ports. Critically, these findings emphasize the key role played in the initial stages of determining precisely and exactly what specific goods are in fact dangerous goods, thereby avoiding a domino effect of adverse consequences later. Suggestions are made for policymakers regarding funding and supporting processes for handling dangerous goods, as well as for future research.

How do corporate social responsibility and green finance strategies impact sustainable development in China's renewable energy sector?

As the globe transitions to a low-carbon economy, China's renewable energy (RE) sector is crucial to attaining sustainable growth. Green financing and corporate social responsibility (CSR) strategies have become increasingly important in promoting the growth and sustainability of the RE sector. In order to evaluate CSR factors and green finance strategies for effective integration in supporting the RE industry, this research employs hybrid Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy VIekriterijumsko KOmpromisno Rangiranje (FVIKOR) approaches in the context of China. The FAHP method is used to determine the various CSR factors and subfactors, while the FVIKOR method is employed to prioritize the key green finance strategies. The findings of the FAHP method highlight the importance of socioeconomic development, environmental protection, and stakeholder engagement as critical CSR factors for RE sectors. Moreover, the results of the FVIKOR method reveal that innovative financing mechanisms, green bonds, and green banks emerged as significant green finance strategies for mobilizing capital and resources for RE projects. The study highlights the value of aspects of CSR and green financing techniques in fostering sustainable development in the RE industry. The results can aid in the promotion of sustainable practices and the assistance of China's transition to a more resource- and environment-wise economy by firms, investors, governments, and other stakeholders.

Prioritization and taxonomy of factors related to environmental tax reform (ETR) using fuzzy AHP approach

PurposeEnvironmental taxes have been in place for many years to reduce environmental damage and pay more attention to the environment. However, some of the adverse socio-economic impacts that may result from such taxes and the many challenges facing developing countries have necessitated policy reform. Therefore, identifying and prioritizing the factors related to environmental tax reform (ETR) is necessary to help governments and environmental protection agencies (EPAs) focus on this prioritizing to develop and improve this process. Awareness of the benefits of ETR encourages governments to use this policy to reduce adverse environmental impacts and contribute to economic growth.Design/methodology/approachThe primary purpose of this work is to prioritize and taxonomy the factors related to ETR using the Fuzzy Analytic Hierarchy Process (FAHP) approach. In the first stage, 25 factors were extracted from the available literature. These factors were divided into five categories for more accessible review. In the second stage, the FAHP as a Multiple-Criteria Decision-Making (MCDM) Technique was used to prioritize and develop the taxonomy of identified factors and the categories of these factors.FindingsThe results show that reducing carbon emissions (DF4) is the essential prioritization factor that governments and environmental organizations can achieve if the ETR is implemented. Following that, reducing greenhouse gas emissions (DF1), double benefit (EcF7) and increase sustainability reports (EnF4) can be achieved by implementing ETR.Research limitations/implicationsThis study is geographically limited to Iran. In terms of the study population, this study is limited to 25 academic, tax and public policy experts. Moreover, in this study, FAHP is the only approach used. For further research, the results of this study can be compared with that of other multi-criteria techniques like FAHP, fuzzy TOPSIS or BWM.Practical implicationsRatings of factors related to ETR can guide and help governments identify important factors that affect environmental tax reform, which can, in addition to controlling ecological pollution will, increase the economic benefits of governments.Originality/valueThis study is the first to identify factors related to environmental tax reform and to develop an MCDM technique for prioritizing these factors and finding important ones.

Integrated water resources management stumbling blocks: Prioritization for better implementation under Ethiopian context

Implementation of Integrated Water Resources Management (IWRM), as internationally recognized, is not straightforward. IWRM is tailored to bring about three outcomes: Economic efficiency, Social equity, and Environmental and Ecological sustainability. Thus, each country faces a unique challenge in implementing IWRM. Literature reports several stumbling blocks (SBs) that hinder IWRM implementation in Ethiopia. The SBs can be categorized as Water Resources: Availability, Development, Use, and Governance-Related SBs. The spatiotemporal impacts of stumbling blocks were evaluated based on the contribution of each SB to the three outcomes. Prioritizing SBs based on their spatiotemporal contribution to hindering IWRM implementation is essential for environmental and economic reasons to simultaneously solve all SBs. The Fuzzy Analytic Hierarchy Process (FAHP) was used to prioritize the SBs. The results indicate food insecurity in the water use category is the highest-ranked SB, whereas market inaccessibility is the least. Poverty and less attention to water infrastructure from water resources development are the second-ranked SBs to hinder IWRM implementation. This research has shown prioritization of SBs is possible using FAHP, and resolving these SBs in their stated priority will make IWRM implementation in the Ethiopian context much better. The research also shows IWRM implementation in Ethiopia requires careful consideration of the SBs, for which the FAHP approach is reliable.

An integrated fuzzy AHP and fuzzy TOPSIS approach for screening backfill materials for contaminant containment in slurry trench cutoff walls

The inclusion of backfill material is crucial for the effective containment of contaminants in a slurry trench cutoff wall. However, selecting the optimal backfill material is complex and involves multiple criteria. This study aimed to develop a new approach to assist in the selection process by rationally dealing with the subjective judgment of decision makers. The approach employed fuzzy analytic hierarchy process (AHP) and fuzzy technique for order preference by similarity to ideal solution (TOPSIS) methods. Initially, consistent judgment matrices were established based on a unique consulting questionnaire. The fuzzy AHP method used Buckley's method to calculate the fuzzy weights of pairwise comparisons. The fuzzy TOPSIS method was then employed to rank and evaluate four different backfill materials. The proposed methodology was successfully implemented at a real contaminated site in China to select the appropriate backfill material for construction of a slurry trench cutoff wall. Based on the proposed integrated methodology, fiber reinforced reactive magnesia-activated slag-soil-bentonite (FMSB) was determined as the most appropriate backfill materials for contaminant containment in slurry trench cutoff walls at the site reported in this study.

Fiscal Risk Management of Public–Private Partnership Projects: A Multidimensional Identification and Assessment Framework

In public–private partnership (PPP) projects, governments often need to provide guarantees to investors because of the risks created by the large scale of the investments and the long tenures of the projects. Yet, research on the assessment of fiscal risk in PPP projects remains scarce. Based on the theory of project life-cycle management, this study constructed a multidimensional identification and assessment framework for PPP fiscal risk. A fiscal risk matrix model was developed, and feasibility, standardization, and sustainability were identified. These were categorized into three dimensions of PPP fiscal risk, and their indicators’ hierarchical levels were evaluated and ranked. A risk model, called the fuzzy evaluation model of PPP fiscal risk, which shows the value of the comprehensive evaluation of PPP fiscal risk based on a fuzzy analytic hierarchy process (FAHP) approach, is proposed. The results demonstrate the significance of this valuation for both governments and investors, providing a clear reference when they face pressure from the fiscal risks of PPP projects.