Set Pair Analysis Research Articles

Set pair analysis and system dynamics coupling approach for structure simulation and variation trend evaluation of water resources spatial equilibrium system

AbstractThe implement of water resources spatial equilibrium (WRSE) schemes is fundamental task of integrated water resources management in China, in which, the evaluation and simulation analysis of WRSE system is of great concern for understanding the overall variation and feedback characteristics of WRSE system. Therefore, we utilized the ordered degree, entropy and connection number coupling model to evaluate the variation of WRSE system, and also employed system dynamics (SD) and scenario simulation integrated method to reveal the feedback characteristics between different equilibrium variables and subsystems, and thus the set pair analysis‐SD based approach for structure simulation and variation trend evaluation of WRSE system was constructed. The application results in Anhui province, China demonstrated that, the overall variation of provincial spatial equilibrium situation of WRSE system presented obvious improving trend, 2009–2019, the index of ordered degree and connection number entropy in Hefei, increased from the minimum of 0.6434 (Grade 3, unequilibrium) to maximum of 0.9985 (Grade 1, equilibrium). Moreover, the future variation of WRSE system will display stable improving trend during 2020 to 2029, in which, annual water resources availability and water resources utilization efficiency will have significant influence on WRSE system. And the research findings can be favorable to formulate water resources development and utilization strategies.

Analysis and Optimization of the Effectiveness of Production Safety Standardization Construction Based on Set-Pair Analysis

Analysis and Optimization of the Effectiveness of Production Safety Standardization Construction Based on Set-Pair Analysis

Spatio-temporal evolution of social-ecological system resilience in ethnic tourism destinations in mountainous areas and trend prediction: a case study in Wuling, China

Mountainous ethnic tourism lands are important social-ecological system types. With tourism as the main disturbance factor, the theory of social-ecological system resilience provides a new way to realize the sustainable development of ethno-tourism in mountainous areas. This study divides the social-ecological system into social, economic, and ecological subsystems. It constructs an evaluation index system to assess the resilience of ethnic tourism destinations in mountainous areas, considering vulnerability and adaptability. We investigate 64 counties in the Wuling Mountain area and use set-pair analysis to assess the resilience index of the social-ecological system from 2000 to 2020 and reveal the temporal and spatial characteristics. Obstacle degree models and a genetic algorithm-back propagation neural network are utilized to determine the influencing factors and predict future development trends. The following results were obtained: (1) Temporally, the resilience index shows a steady upward trend, reaching a moderate level. The resilience of the social subsystem fluctuates and rises; the economic subsystem exhibits slow, fast, and slow growth rates with occasional abrupt changes; and the ecological subsystem demonstrates a stable, slightly increasing trend. (2) Spatially, the resilience index is high at the edges and low in the central area, exhibiting a concave distribution. Most counties have moderate or higher resilience. The social and ecological subsystems have low resilience in the south and high resilience in the north. The resilience of the economic subsystem is high at the edges and low in the central area. (3) On the distribution of major obstacle factors, the first two are similar at the county level, and the last three are significantly different. The similarity of the barrier factors is related to the degree of regional proximity of the county, and overall, the similarity is decreasing from north to south and from west to east in the distribution pattern within the area. and to a certain extent, it is affected by terrain and geomorphology. (4) The spatial distribution of the resilience index is similar in 2025 and 2030. The index decreases slightly and then increases annually, with a lower growth rate in the south than in the north. Lower values occur in the northern and southwestern parts, whereas higher values are observed around high-value areas. The region as a whole will develop in a coordinated and integrated manner in the future.

Spatial difference analysis and driving factor diagnosis for regional water resources carrying capacity based on set pair analysis

Studying regional water resources carrying capacity (WRCC) is an important way to find out and solve regional water resources problems. Analyzing the spatial difference of WRCC and diagnosing its driving factors is the basis for the implementation of the water control policy named "spatial balance". This study selects evaluation indicators for WRCC from three aspects: water resources, social economy, and ecological environment. The weights of indicators were determined by fuzzy analytic hierarchy process based on accelerated genetic algorithm (FAHP-AGA), and an evaluation method for WRCC was constructed based on set pair analysis (SPA). On this basis, the spatial difference analysis of regional WRCC and its key driving factor diagnosis model was established, and the empirical study was carried out in Anhui Province as an example. The results show that from 2011 to 2020, the WRCC of Anhui Province was increasing, with the average increase of each city reaching more than 0.3. The spatial difference of WRCC decreased, and the Gini coefficient decreased from 0.16 to 0.08. The key driving factors leading to the spatial difference of WRCC in Anhui Province include water resources module, water consumption per 10,000 yuan of GDP, equilibrium degree of water use structure, per capita GDP, population density, percentage of forest cover, and amount of chemical fertilizer applied per unit of effective irrigated area. Compared with common WRCC evaluation models, this model improves the comparability of the evaluation results. In addition, this model can further analyze the influence of multiple factor interactions on the evaluation results based on the common single factor analysis. The driving factor diagnosis results can provide theoretical guidance for the formulation of regulation measures for regional WRCC and the implementation of the "spatial equilibrium" water control policy.

Decision-making techniques based on aggregation operators and similarity measures under q-rung orthopair hesitant fuzzy connection numbers and their application

The concept of q-rung orthopair hesitant fuzzy set represents an advancement and extension of hesitant fuzzy sets, encompassing both fuzzy sets and q-rung orthopair fuzzy sets. q-rung orthopair hesitant fuzzy set characterizes a set of membership and non-membership grades within the interval [0, 1], which enhances its adaptability compared to existing methods. This flexibility proves invaluable in providing more insightful data about various objects. The primary objective of this research is to introduce a decision-making technique in the context of q-RHF using the theory of set pair analysis (SPA). q-RHFS effectively handles ambiguous data by incorporating membership and non-membership grades, while the connection number (CN) based on SPA theory manages the intricacies of uncertainty and certainty structures by relying on "identity", "discrepancy" and "contrary" grades. Building on the relationship between q-RHFS and the connection number of set pair analysis, a comprehensive framework known as q-rung hesitant fuzzy connection number set (qHCNs) is developed. This model not only addresses uncertainty, but also offers valuable insights. Furthermore, this research introduces similarity measures derived from qHCN and examines their advantages through illustrative examples. Additionally, a novel approach to decision modeling utilizing these measures applied to medical diagnosis is also introduced. The application of this established model contributes to an effective approach and demonstrated its soundness and efficiency. In addition, a detailed comparative study is conducted with the existing models and advantages of proposed model. The research concludes with a summary of the authors' findings, highlighting the consistency and effectiveness of their work.

Research on the Socio-Spatial Resilience Evaluation and Evolution of the Central Area of Beijing in Transitional China

In recent decades, the increasing threats of global climate change, natural disasters, and epidemics have brought extensive attention to resilience theory. However, most studies focus on the physical aspects of cities, overlooking the significance of the social perspective. This study addresses this gap by using social areas as the core spatial unit for analysis. By constructing a scientific indicator system and employing the set pair analysis method, this study comprehensively evaluates the multidimensional resilience levels of Beijing’s central area during its transitional period (1990–2020). The findings reveal that socio-spatial divisions, which emphasize the network structure of social relations and the dynamic changes in social spaces, are more suitable than traditional administrative divisions as fundamental units for resilience assessment. During Beijing’s transitional period, the comprehensive resilience of the central area and all social areas steadily increased, although social capital resilience faced the challenges of loss and slow recovery. Social areas with a unique internal connection, such as those based on ethnicity, exhibited more positive social capital resilience development. Additionally, social areas with lower population diversity and greater homogeneity tended to have higher comprehensive resilience and a more positive trend in social capital resilience development, whereas highly heterogeneous social areas faced significant constraints in resilience development. These findings may provide valuable insights for cities and communities to enhance their capacity to address future uncertainties and assist policymakers in making informed governance decisions.

Vertical Spatial Differentiation and Influencing Factors of Rural Livelihood Resilience: Evidence from the Mountainous Areas of Southwest China

Rural livelihood resilience (RLR) is significant for the sustainability of rural areas, farmers and agriculture. This research takes the mountainous areas of Southwest China as the study areas and integrates the buffer, adjustment and renewal capabilities to construct a RLR analysis framework and evaluation indicator system. The RLR of 234 sample counties was evaluated using set pair analysis, and the influencing factors of RLR were investigated using Geodetector. The aim is to scientifically analyze the vertical spatial differentiation and influencing factors of RLR and fully explore the risk-resistant potential of rural livelihood systems in mountainous areas. The results show that (1) From 2000 to 2020, RLR increases significantly, but the level is still low, and its structure shows a primary pattern of “buffer capability > adjustment capability > renewal capability”. (2) There is no significant negative correlation between RLR and terrain gradients, especially in the middle and low mountains. RLR in high mountainous areas is significantly lower than in low and medium mountainous areas, but the gap is narrowing. There are no significant gaps in RLR and various capabilities between low and medium mountain areas. (3) Economic development, non-agricultural industries and grassroots autonomous organizations are essential determinants for RLR. Economic development, grassroots autonomous organizations and transportation conditions are more important in low and medium mountain areas, while non-agricultural industries and medical conditions contribute more to high mountainous areas. (4) To enhance the RLR, policy recommendations should place a strong emphasis on extending the agricultural industry chain, improving rural production and living infrastructure and strengthening the supply of high-quality social public services. The findings can provide a scientific basis for governments to implement rural revitalization strategies and improve farmers’ well-being, as well as practical guidance for enhancing the risk resistance ability of underdeveloped mountainous rural areas.

Assessment of living quality in Guangdong: A hybrid knowledge-based and data-driven approach

Air, water, and radiation in urban living environments are crucial factors affecting human health, societal well-being, and sustainable development. This study developed a novel hybrid knowledge-based and data-driven approach for analyzing air, water, and radiation monitoring data to assess the quality of urban living natural environments (ULNEQ) in Guangdong Province. Fuzzy set-pair analysis was employed for data preprocessing, effectively incorporating domain knowledge into the raw data. Then, a hierarchical clustering algorithm was utilized to evaluate the ULNEQ level. The proposed approach enhanced data interpretability and optimized the clustering process, yielding more robust and reliable analytical results. The results revealed a diverse environmental landscape across the province, with Heyuan and Meizhou consistently maintaining high standards, whereas Dongguan and Jieyang exhibited notably poor conditions, ranking at Level IV or V for over 72% of the observed months. Key factors such as monthly average concentration ozone (0.56), the city water quality index (0.49), and the proportion of days with standard air quality (PDSAQ) (−0.39) significantly influenced the ULNEQ, with PDSAQ showing a negative correlation. Notably, a province-wide observation in June 2022 showed all cities maintaining ULEQ gradings of Level II or better. This innovative approach can be adapted to enhance the management and control of ULNEQ.

Semi‐partial Quadratic Subtraction Set Pair Potential (SQSSPP) method for regional drought risk assessment: A case study in Suzhou City, China

AbstractDrought risk assessment plays a crucial role in effective drought management. However, it is often challenging due to the intricate relationships among various indicators and the lack of practical guidance. This study presents a drought risk assessment model developed using the Semi‐partial Quadratic Subtraction Set Pair Potential (SQSSPP) method, which is derived from the theory of set pair analysis. The indicator system comprises 21 indicators divided into four subsystems. The SQSSPP method utilizes uncertainty information in the overall development trend of regional drought risk states by extracting connection numbers from the Subtraction Set Pair Potential (SSPP), improving the reliability of evaluation results. The SQSSPP method is validated through a case study of Suzhou City, China, from 2007 to 2017. Three grades are used to evaluate comprehensive drought risk. The result shows an overall decreasing trend over time, with a level III risk in 2010 and consistently at level II from 2011 to 2017. Indicators in the hazard and resilience subsystems are the primary factors influencing drought risk in the Suzhou City. Specific indicators requiring emphasis for improvement are identified, including arable land rate, agricultural population ratio, reservoir regulation rate, current water supply capacity, and irrigation index. The SQSSPP method not only provides targeted drought risk assessment but also provides valuable guidance for future water resource management. While the study focuses on Suzhou City, the proposed approach is applicable to broader‐scale risk management evaluations and practices.

Comprehensive evaluation and optimal management of extreme disaster risk in Chinese urban agglomerations by integrating resilience risk elements and set pair analysis

This study comprehensively assesses the extreme disaster risk faced by Chinese urban agglomerations and optimizes disaster risk management strategies to enhance their disaster resilience and sustainable development. The focus is specifically on droughts, floods, and earthquakes. The integration of resilience risk elements and set pair analysis (SPA) is employed to obtain risk assessment results for different urban agglomerations, including hazard, exposure, vulnerability, and disaster prevention and mitigation capabilities. The study explores the contributions of important indicators, such as exposure, vulnerability, and disaster prevention and mitigation capabilities, in disaster risk assessment, as well as their performance in various risk-prone urban areas. Comparative analysis of the assessment results for different urban agglomerations under various disaster types reveals varying levels of risk in droughts, floods, and earthquakes across different regions. Some areas exhibit higher hazard, exposure, or vulnerability levels, necessitating strengthened disaster prevention and mitigation measures. Regions with high exposure, low vulnerability, and strong disaster prevention and mitigation capabilities may face lower earthquake disaster risk, while regions with low exposure, high vulnerability, and weak disaster prevention and mitigation capabilities may face higher earthquake disaster risk. Moreover, the Comprehensive SPA model and Interval-valued SPA model outperform traditional SPA methods in assessing the existing flood risk level in Chinese urban agglomerations. The integrated model plays a significant role in predicting earthquake disasters, demonstrating the best predictive performance. This study provides essential reference data for urban disaster prevention and mitigation efforts, aiming to enhance urban resilience and disaster resilience capabilities.

An Improved Algorithm of Image Edge Detection Based on the Degree Connection Situation

Aiming at the defect of the poor ability to suppress the noise of the algorithm of image edge detection, as well as too much sensitive to the noise, an improved algorithm of image edge detection based on SPA (set pair analysis) by combining trend relationship of the degree connection situation with the algorithm of half-neighborhood adaptive image edge pick-up is presented in this paper. The core of the algorithm is first to detect the most possible direction of the edge by using the biggest value of Degree Connection Situation--c/a, and then calculate absolute value of the D-value between the average value of three points and the average value of five points and the standard deviation value of all the points value in the 8-neighborhood, at last, decide whether the center-point is on the edge according to the threshold value of the standard deviation value. The result of simulation indicates that, without any processing to the image, the improved algorithm is not only accurate but also legible in object brim pick-up, compared with the algorithm in literature; furthermore, the noise is greatly suppressed by using it.

Multiple attribute decision making based on score function of q-connection numbers, q-CNPWG aggregation operator of q-connection numbers, and set pair analysis theory in the environments of q-rung orthopair fuzzy numbers

This paper proposes a new multiple attribute decision making (MADM) method in the environments of q-rung orthopair fuzzy numbers (q-ROFNs) based on the proposed score function of q-connection numbers (q-CNs), the proposed q-connection number power weighted geometric (q-CNPWG) aggregation operator (AO) of q-CNs, and the set pair analysis (SPA) theory. Firstly, we propose a score function of q-CNs based on the SPA theory, where we also present some properties of the proposed score function of q-CNs. Then, we propose the q-CNPWG AO for aggregating q-CNs, where we also present some properties of the proposed q-CNPWG AO of q-CNs. Finally, we propose a new MADM method in the environments of q-ROFNs based on the proposed score function of q-CNs, the proposed q-CNPWG AO of q-CNs, and the SPA theory. The proposed MADM method can overcome the drawbacks of existing MADM methods in the environments of q-ROFNs, where they cannot distinguish preference orders of alternatives in some situations. The proposed MADM method is very useful for MADM in the environments of q-ROFNs.

Regret-based three-way decisions with set pair analysis in incomplete information systems

Set pair analysis is a valuable tool for managing uncertain systems and can effectively handle missing information in the decision-making process. In addition, regret theory can objectively describe the impact of decision-maker psychology on decision-making. However, traditional decision-making methods rarely combine set pair analysis and regret theory to discuss decision problems. Thus, this article aims to integrate regret theory into the three-way decision theory based on set pair analysis, presenting a novel approach to address multi-attribute decision-making problems in real life. Specifically, we first propose a data-driven approach based on set pair analysis to determine attribute weights. Then, a similarity relationship is established based on the weighted distance to calculate conditional probability. Meanwhile, the average value of regret and joy under each attribute is selected as a reference point to determine the relative utility function using regret theory. Subsequently, we develop a new three-way decision method in incomplete information systems and apply it to solve practical problems. Finally, the effectiveness and superiority of our method are demonstrated by case analysis and comparison. We also conduct sensitivity analysis to examine the stability of the new method.

Evaluation of extracting biomass energy using a strategic decision support system

Electricity significantly influences the long-term development of society. Traditional power generation technologies have encountered numerous challenges. The rising demand for power generation and the scarcity of fossil fuel resources have prompted the adoption of renewable energy sources. Biomass is a renewable energy source that can be utilized to generate power and promote a more sustainable environment. This paper presents improved Pythagorean Probabilistic Hesitancy Fuzzy Set (PPHFS) multi-criteria information fusion processes. The development of connection numbers (CN) and the proposal of a distance measure between CNs have been initiated. The suggested solution involves a distance measure based on the CN score function. Set-pair analysis (SPA) is a prior uncertainty theory that incorporates three elements of CN and overlaps with the PPHFS. Biomass energy generation poses a fuzzy multi-criteria decision-making (MCDM) problem that requires a wide range of resources for evaluation. The study introduces a novel Projection Ranking by Similarity to the Referencing Vector (PRSRV) and Simultaneous Evaluation of Criteria and Alternatives (SECA) to effectively handle data ambiguity and generate weights for all criteria in the MCDM problem. The criteria’s weights were found to fall within the range of 0.2122 and 0.0232. The proposed method indicates that animal residues are the most desirable resource for bioenergy production, followed by municipal solid residues, agricultural residues, forest and crop residues, industrial residues, and algae. The research aims to assist decision-makers and organizations in evaluating and prioritizing various energy sources on a sustainable scale. The method presented exhibits superior data adaptability compared to other MCDM approaches.

Evaluation of the impact of climate change on the ecological resistance and ecological corridors based on set pair analysis theory

Climate change significantly impacts ecological resistance and ecological corridors. However, the difficulty in evaluating this impact lies in two crucial issues: (i) the uncertainty arising from spatial heterogeneity, and (ii) the diversity of impacts arising from this uncertainty. A set pair analysis (SPA) model is designed to assess the impact of climate change on ecological resistance and ecological corridors for addressing the aforementioned problems. First, the ecological resistance and corridors under different climate change scenarios are simulated. Then, the five-element connection number is used to reflect changes in ecological resistance and corridors influenced by climate change and uncertainty. Finally, the influence indices are constructed to quantify the three distinct impacts of climate change on them. The evaluation results for Jiangxi Province are as follows. (i) The province’s UR index values are 0.085, 0.127, 0.351, 0.501, and 0.468 under five climate change scenarios, respectively. The impact of climate change on ecological resistance is rapidly deteriorating, and the central region is the high-value center for future ecological resistance. (ii) The values of UC in the central and southern regions range from − 0.568 to − 0.320 and from − 0.816 to − 0.446, respectively. In the two regions, the assessments of the impact of climate change on ecological corridors are negative, which results in a reduction in connectivity. (iii) The crucial meteorological risks with the greatest impact on ecological resistance and corridors are floods and high-temperature disasters. (iv) The proposals for Jiangxi Province to address climate change are as follows: enhancing flood prevention, improving high-temperature monitoring, and establishing an ecological management system. (v) The SPA model can effectively assess the different impacts of climate change with spatial uncertainty on ecological resistance and corridors.

Advances in Adjoint Functions of Connection Number in Water Resources Complex Systems: A Systematic Review.

The adjoint function of connection number has unique advantages in solving uncertainty problems of water resource complex systems, and has become an important frontier and research hotspot in the uncertainty research of water resource complex problems. However, in the rapid evolution of the adjoint function, some problems greatly limit the application of the adjoint function in the research of water resources. Therefore, based on bibliometric analysis, development, practical application issues, and prospects of the hot directions are analyzed. It is found that the development of the connection number of water resource set pair analysis can be divided into three stages: (1) relatively sluggish development before 2005, (2) a period of rapid advancement in adjoint function research spanning from 2005 to 2017, and (3) a subsequent surge post-2018. The introduction of the adjoint function of connection number promotes the continuous development of set pair analysis of water resources. Set pair potential and partial connection number are the crucial research directions of the adjoint function. Subtractive set pair potential has rapidly developed into a relatively independent and important trajectory. The research on connection entropy is comparatively less, which needs to be further strengthened, while that on adjacent connection number is even less. The adjoint function of set pair potential can be divided into three major categories: division set pair potential, exponential set pair potential, and subtraction set pair potential. The subtraction set pair potential, which retains the original dimension and quantity variation range of the connection number, is widely used in water resources and other fields. Coupled with the partial connection number, a series of new connection number adjoint functions have been developed. The partial connection number can be mainly divided into two categories: total partial connection number, and semi-partial connection number. Among these, the calculation expression and connotation of total partial connection numbers have not yet reached a consensus, accompanied by the slow development of high-order partial connection numbers. Semi-partial connection number can describe the mutual migration movement between different components of the connection number, which develops rapidly. With the limitations and current situation described above, promoting the exploration and application of the adjoint function of connection number in the field of water resources and other fields of complex systems has become the focus of future research.

Risk assessment of crane operation hazards using modified FMEA approach with Z-number and set pair analysis

In view of two key deficiencies of failure mode and effects analysis (FMEA) in crane operation hazard risk assessment—information loss and hazard grade lack, a crane operation hazard risk assessment model based on the Z-number and set pair analysis (Z-SPA) is proposed. In this research, the Z-number is used to address the information uncertainty. To reduce the risk losing evaluation information in the conversion of the Z-number into a crisp number, it is translated into an interval number. In this assessment model, the grades of crane operation hazards are determined using grade discrimination rules and a score function of a connection number based on set pair analysis. Two case studies are presented to exemplify the effectiveness of the approach. The first case validates the proposed method, and the second case illustrates the application of the modified FMEA to crane operation hazard risk analysis. Furthermore, the assessment results are analyzed and compared with previous studies to highlight the superiority of the proposed model.

Research on coal mining intensity based on the DPSIR-SPA model.

High-intensity mining has become a major trend in future coal mining. However, it will unavoidably worsen the harm done to the natural environment of mining sites by coal mining, which is already prone to doing so. So, how may coal mining intensity (CMI) be decreased? Minimize the harm that coal mining causes to the environment and offer a theoretical basis for protecting the environment in mining sites. In order to achieve this, based on the existing literature on CMI, we first redefine the concept of CMI, analyze its influencing factors, propose an evaluation index system, and introduce the theory of set pair analysis (SPA) to build a quantitative evaluation model of CMI. We then propose an adjustment strategy for the CMI and conduct a verification analysis using the Halagou Coal Mine and Caojiatan Coal Mine as an example. The results show that the Halagou and Caojiatan Coal Mine belong to the higher-intensity mining stage. It is consistent with existing research. Moreover, the development trend of CMI in the Halagou Coal Mine is analyzed in conjunction with the set pair potential theory, and specific measures to reduce CMI are given, from the perspective of coal mining. It provides the basis for the source protection of the ecological environment in the mining area. Theoretically, this study can help both the quantitative assessment of mining intensity and the source protection of the mining ecological environment. Besides, it offers specific guidelines for building environmentally friendly mines.

TOPSIS method based on connection number of set pair analysis subject to bipolar fuzzy environment with application in decision making

In this manuscript, we develop TOPSIS (Technique for order of preference by similarity to ideal solution) method in the setting of bipolar fuzzy environment which has the ability to deal the data while keeping in view the positive and negative aspects. By using bipolar fuzzy sets, we establish the novel concept of rating the numerous preferences of any object described through the connection number(CN) of set pair analysis(SPA). In this regard, we extend the TOPSIS method based on the connection number(CN) of set pair analysis(SPA) in the frame of bipolar fuzzy sets. For the sake of verification, effectiveness and superiority of our method, we conduct the comparative study of some real life problem related to decision making theory. Moreover, we observe that our proposed method also fulfills the existing test criterions.

Blockchain-driven framework for financing credit in small and medium-sized real estate enterprises

PurposeThis study aimed to improve the financing credit evaluation for small and medium-sized real estate enterprises (SMREEs). A financing credit evaluation model was proposed, and a blockchain-driven financing credit evaluation framework was designed to improve the transparency, credibility and applicability of the financing credit evaluation process.Design/methodology/approachThe design science research methodology was adopted to identify the main steps in constructing the financing credit model and blockchain-driven framework. The fuzzy analytic hierarchy process (FAHP)–entropy weighting method (EWM)–set pair analysis (SPA) method was used to design a financing credit evaluation model. Moreover, the proposed framework was validated using data acquired from actual cases.FindingsThe results indicate that: (1) the proposed blockchain-driven financing credit evaluation framework can effectively realize a transparent evaluation process compared to the traditional financing credit evaluation system. (2) The proposed model has high effectiveness and can achieve efficient credit ranking, reflect SMREEs' credit status and help improve credit rating.Originality/valueThis study proposes a financing credit evaluation model of SMREEs based on the FAHP–EWM–SPA method. All credit rating data and evaluation process data are immediately stored in the proposed blockchain framework, and the immutable and traceable nature of blockchain enhances trust between nodes, improving the reliability of the financing credit evaluation process and results. In addition, this study partially fulfills the lack of investigations on blockchain adoption for SMREEs' financing credit.