Fuzzy Synthetic Evaluation Approach Research Articles

A Fuzzy Synthetic Evaluation Approach to Assess Usefulness of Tourism Reviews by Considering Bias Identified in Sentiments and Articulacy

A Fuzzy Synthetic Evaluation Approach to Assess Usefulness of Tourism Reviews by Considering Bias Identified in Sentiments and Articulacy

A fuzzy synthetic evaluation approach to assess the risks associated with municipal waste management: Implications for sustainability

The rapid growth of industry, urban areas, and populations has substantially increased waste production worldwide. The inadequacy of robust waste management systems and limited resources poses significant challenges for many emerging economies, including Bangladesh, resulting in environmental contamination. Despite numerous academic studies on sustainable waste management, there is a noticeable gap in the literature concerning identifying, evaluating, and modeling critical risks associated with adopting sustainable municipal waste management systems, particularly in emerging economies like Bangladesh. This study, therefore, aims to fill this gap by identifying, categorizing, and assessing the crucial risks in implementing sustainable municipal waste management systems. Through an extensive review of existing literature and validation with expert feedback, this study employs a fuzzy synthetic evaluation method-based framework to prioritize the identified risks. The study calculates the probability of occurrence and degree of impact values to provide decision-makers with insights into the severity of different risk categories, aiding in case-by-case attention. Scores assigned on a 1 to 5 scale range from 2.59 to 4.14 for the various risk categories. Notably, “Industrial challenges related” and “Community and infrastructure requirements related” emerge as the most significant risk categories among those analyzed. This study contributes to the existing literature by employing fuzzy synthetic evaluation, a methodology rarely used to determine critical risks in municipal waste management. Furthermore, it is poised to offer valuable insights to industrialists and waste management authorities, empowering them to develop responsive strategies and contribute to the sustainable development of cities and urban communities.

A fuzzy synthetic evaluation approach for climate for innovation measurement in construction firms

PurposeThis research aims to identify the climate for innovation variables and to propose an innovative tool to quantitatively assess the degree of climate for innovation of construction firms.Design/methodology/approach14 climate-for-innovation variables were identified from a literature review and discussion with experienced practitioners. After that, a questionnaire survey was developed to collect data. Factor analysis was used to analyze data gathered from 157 completed responses. Then, fuzzy synthetic evaluation (FSE) was employed to assess the degree of climate for innovation in Vietnamese construction firms.FindingsClimate-for-innovation variables were categorized into four factors by factor analysis. The FSE analysis shows leadership is the most critical category of four factors, followed by working culture, organization and employee commitment. The calculation also illustrates that the climate for innovation in Vietnamese construction firms is at a moderate level.Originality/valueThis research is one of the first integrated climate for innovation of construction firms in a comprehensive formulation. The formulation provides the decision-makers with a reliable tool to evaluate the degree of climate for innovation, thus having appropriate strategies to develop sustainable innovation performance within their organizations.

Evaluation of the Critical risk factors in PPP - procured Mass Housing Projects in Abuja Nigeria - A fuzzy synthetic evaluation (FSE) approach

The study accessed the critical risk factors in public-private partnership procured mass housing project (PPP-MHP) delivery in Nigeria. The research design adopts a quantitative approach, using well-structured questionnaires distributed to stakeholders involved in PPP-MHPs i.e. the consultants, in-house professionals, contractors, and the organized private sector (OPS) registered with PPP departments of the Federal Capital Territory Development Authority (FCDA) Abuja, Nigeria. The instrument relates to the background information of respondents and the risk peculiar to PPP-MHP. Sixty-three (63) risk factors were submitted for the respondents to rank on a Likert scale of 7 using Mean Item score (MIS) for risk occurrence and its severity, while the risk significance index (RI) was used to determine the risk impact. Fuzzy Synthetic Evaluation (FSE) method was subsequently applied to determine the risk criticality groups and the overall risk level in the sector. The findings show that thirty-one (31) risk factors were critical in the sector while the financial and micro-economic risk group is contributing most significantly to the overall risk level in PPP-MHPs in Nigeria. The implication for practice is that having known the risk group contributing most significantly to the overall risk level in PPP-MHPs, adequate financial and budgetary allocation should be made available before embarking on a such venture to sustain the scheme in the country. The study is one of the recent research conducted on housing since the procurement option is novel in the sector. The study is of immense value to PPP actors by providing the necessary information required to formulate risk response methods to minimize the impact of the risk factors in PPP MHPs.

Selection of green remediation alternatives for chemical industrial sites: An integrated life cycle assessment and fuzzy synthetic evaluation approach

The concept of green site remediation calls for a model that can consider environmental impacts in the selection of site remediation alternatives. In this study, an integrated life cycle assessment (LCA)-fuzzy synthetic evaluation (FSE) model is developed to help practitioners select the optimal site remediation plan by incorporating life cycle impacts into the comprehensive suitability evaluation. The LCA module quantifies environmental and economic impacts using ReCiPe and Input-Output LCA methods, respectively. The impacts are evaluated along with other suitability considerations, presented in 32 indicators under ten criteria, by practitioners through a questionnaire survey. FSE is used to process the collected subjective judgments and generate a suitability index for informed selection. The integrated model is applied to a case study of an abandoned chemical industrial site contaminated by various organic chemicals and mercury. Four remediation alternatives, designed as the combined uses of ex-situ thermal desorption, in-situ thermal desorption, and in-situ containment, are evaluated. The LCA results show that the alternative with extensive use (treating 93.8 % of the contaminated soil) of in-situ thermal desorption is associated with the highest environmental and economic impacts, followed by the alternative with less extensive use (6.2 %) of in-situ thermal desorption. The FSE results show that the economic, technical, and environmental impact considerations are the top three important criteria. The integrated LCA-FSE results indicate that the alternative with mixed use of ex-situ thermal desorption and in-situ containment could be the optimal plan. Excluding LCA results could alter the suitability ranks of the alternatives.

A comprehensive risk assessment model based on a fuzzy synthetic evaluation approach for green building projects: the case of Vietnam

PurposeRisks in implementing green building (GB) projects have emerged as a significant obstacle for GB development, especially in developing countries. In recent years, both academics and construction practitioners have paid considerable attention to the risks associated with GB. In this study, the authors aimed to create a comprehensive risk assessment model that considers three crucial risk features: impact level, probability of occurrence and risk manageability.Design/methodology/approachIn the research, authors adopted the mean scoring and fuzzy synthetic evaluation method to assess GB risks. Based on expert assessments, this model can determine the significance of risk factors, risk groups and overall risk. Notably, this research applied the proposed model to assess GB risks in Vietnam by surveying 58 GB experienced professionals.FindingsThe findings revealed that GB risks are relatively high in Vietnam, implying that risk management is essential for GB projects to succeed. The results also showed that “lack of experience of GB designers” is the most critical factor, and “human resources risk in the design phase” is the top crucial risk group.Originality/valueThis study contributes a novel and practical model to help practitioners assess risks in GB projects. In addition, this research offers detailed GB risk evaluations in Vietnam and thus could be a valuable reference for construction practitioners and future studies.

Risk Identification and Assessment of PPP Forestry Projects in China Using a Fuzzy Synthetic Evaluation Approach

At present, the Chinese government is vigorously promoting the use of PPP mode to attract social capital and financial capital into the field of forestry, including ecological construction, protection and utilization, which is of great significance for promoting the construction of ecological civilization and the development of both the economy and the society. Because the financing, organization, implementation and environmental factors of PPP forestry projects are relatively complicated, there are certain risks for both the government and social capital. In order to evaluate the risks of China's forestry projects for the government and social capital, 43 risk factors were identified and divided into 4 groups based on Delphi method and questionnaire survey. 23 key risk factors were selected according to the standardized values. Then, the probability of occurrence (PO), impact size (IS) and overall risk level (ORL) of each key factor were determined by fuzzy synthetic evaluation(FSE) method, and each KRF, KRG and overall risk level (ORL) were calculated. Based on the results, "Government Decision Risk" in KRF was the most critical risk factor, and KRG "Financial Risk" was the most critical risk factor group. Overall, fuzzy comprehensive results showed that the ORL of China's forestry PPP project is relatively high. According to the analysis results, countermeasures were put forward. The research results could provide reference for all participants in PPP forestry projects to make decisions, and formulate a comprehensive risk management plan to use limited resources. In addition, this study could expand professional knowledge and enrich relevant results.

Detecting and mapping karst landforms using object-based image analysis: Case study: Takht-Soleiman and Parava Mountains, Iran

This study presents a novel, semi-automated approach for integrating decision rules and object-based image analysis (OBIA) methods for identifying and mapping karst zones and landforms. We developed a multi-resolution segmentation approach using an Approximate Gaussian function to compute the degree of fuzzy memberships of object-based features and applied it to Sentinel-2 satellite images and a digital elevation model. The object based features and decision rules were applied to identify and detect karst landforms in the semi-automated approach. The efficiency of each technique was examined based on two case studies in Takht-Soleiman and Parava-Biston in Iran using a fuzzy synthetic evaluation (FSE) approach and ground control points. The validation of the karst landform detection and delineation yielded high accuracies for the six prominent landforms, namely Dolin (96.8%), Ouvala (99.2%), Lapiez (95.1%), Canyon (98.3%), Polje (96.1%) and Karren (97.4%), respectively. Based on the research outcome, we conclude that the combined use of spatial (e.g. shape index, compactness, asymmetry), spectral (e.g. brightness, mean and standard deviation) and textural (grey-level co-occurrence matrix, GLCM) features allows us to detect and map karst landforms efficiently. This fuzzy rule object-based approach can enhance the accuracy of geomorphological and geological maps and allows for a regular update of the usually labor-intensive geological mapping campaigns.

Analysing the Barriers to Renewable Energy Adoption in Ghana Using Delphi and a Fuzzy Synthetic Evaluation Approach

Analysing the Barriers to Renewable Energy Adoption in Ghana Using Delphi and a Fuzzy Synthetic Evaluation Approach

Integrating building information modelling for improving facility management operations: a fuzzy synthetic evaluation of the critical success factors

PurposeBuilding information modelling (BIM) is a novel technological advancement in the built environment. Despite the potentials of BIM, its adoption and implementation are undermined in facility management (FM) operations. This might be because of limited information on the critical success factors (CSFs) that can enhance its adoption. The study aims to integrate building information modelling to improve facility management operation by adopting fuzzy synthetic approach for evaluating the critical success factors.Design/methodology/approachData for the study were sourced from practising and registered facility managers within Lagos metropolis, Nigeria. The data collected were analysed using a combination of methods which include mean item score, factor analysis and fuzzy synthetic evaluation (FSE).FindingsThe factor analysis results showed that six underlying groups of CSFs would enhance the effective adoption of BIM in facility operations. The FSE results showed that out of the six groups, the three topmost important CSF grouping (CSFG) in the decision rule would enhance the effectiveness of BIM adoption for FM operations.Practical implicationsThe result of this study provides a credible road map for facility managers, policymakers and other stakeholders in FM operations on the CSFs and CSFG required for the adoption of BIM.Originality/valuePrevious studies that aimed at integrating BIM into FM are limited. Hence, this study provides a broad perspective on the CSF required for BIM adoption and implementation in FM operations using the FSE approach.

Risk assessment of wind-photovoltaic-hydrogen storage projects using an improved fuzzy synthetic evaluation approach based on cloud model: A case study in China

In the energy transition process to full sustainability, Wind-Photovoltaic-Hydrogen storage projects are up-and-coming in electricity supply and carbon emission reduction. However, there are many risk factors in Wind-Photovoltaic-Hydrogen storage projects, which lead to the difficulty of investment and construction. This problem slowed down energy transformation to renewable. Therefore, this paper tries to conduct a risk assessment of Wind-Photovoltaic-Hydrogen storage projects using an improved fuzzy synthetic evaluation approach based on cloud model. Firstly, a total of 72 risk factors of Wind-Photovoltaic-Hydrogen storage projects are collected through literature review. Then 14 key risk factors are identified by expert questionnaires and classified into four groups: economic risk, technical risk, environment risk, and safety risk. Secondly, the importance weights of these risk factors are determined by the Analytic Hierarchy Process. Following this, an improved fuzzy synthetic evaluation approach based on cloud model is proposed to calculate the overall risk level of Wind-Photovoltaic-Hydrogen storage projects. A case study in China is provided to illustrate the validation of the proposed framework. Results show that China's Wind-Photovoltaic-Hydrogen storage projects are mainly between relatively low risk and medium risk. Finally, some policy implications are given to alleviate or remove those high-risk factors. And with criterion weight 0.21 to 0.06, technical risk is much more important than environment risk.

Flood Risk Assessment Based on Fuzzy Synthetic Evaluation Method in the Beijing-Tianjin-Hebei Metropolitan Area, China

Flooding is one of the most devastating natural events and leads to enormous and recurring loss of life, properties, and resources around the globe. With climate change and accelerating urbanization, flood disasters in China have increasingly affected the sustainable development of metropolitan areas. Risk assessment is an essential step in flood management and disaster mitigation, which provide a quantitative measure of flood risk. However, the difficulty of flood risk zoning is dealing with the uncertainty of the evaluation process and the complicated non-linear relationship between indicators and risk levels. To address this issue, a fuzzy synthetic evaluation (FSE) method based on combined weight (CW) was utilized in this paper to generate flood risk maps at a grid-scale (1 × 1 km). For the case study in the Beijing-Tianjin-Hebei metropolitan area (BTH) in China, fourteen indicators were selected to construct the flood risk assessment model based on the FSE approach integrated with ArcGIS. The research demonstrates that moderate, high, and very high risk zones are distributed in the southeast fluvial plain of the BTH area, accounting for 31.36% of the total land area. Meanwhile, low and very-low risk zones occupy 68.64% of the total land area, and are primarily located in the high plateau and mountain regions in the northwest. We analyzed the risk level of each county and proposed risk mitigation measures based on field investigations. The verified risk assessment results were spatially consistent with the historical flood disaster records and loss positions, indicating the accuracy and reliability of the risk assessment map using the FSE approach. Compared with the IPCC (Intergovernmental Panel on Climate Change) TAR (Third Assessment Report) and AR5 (Fifth Assessment Report) methods, FSE has significant advantages in handling uncertainty, complexity, and the non-linear relationship between indices and risk grades. This study provides a novel quantitative method for flood risk assessment in metropolitan areas and practical implications for urban flood management.

Assessing building information modeling implementation readiness in building projects in Singapore

Purpose The purpose of this paper is to identify critical non-value adding (NVA) building information modeling (BIM) implementation activities in current building project delivery process, develop a BIM implementation readiness (BIMIR) evaluation model, and assess BIMIR statuses in building projects in Singapore. Design/methodology/approach A questionnaire survey and four post-survey interviews were conducted in Singapore. A fuzzy synthetic evaluation approach was adopted in the model development. Findings In total, 38 out of 44 NVA BIM implementation activities were deemed critical and used in the proposed model, among which “lack of involvement by contractors to contribute site knowledge” in the design development phase was ranked top. This model was validated in five projects. It was found that most of 73 surveyed building projects were in a low BIMIR status and the assessment results were consistent with current industry practices of BIM implementation in Singapore. Research limitations/implications There may be geographical limitation on the identification of the critical NVA BIM implementation activities. However, because BIM mandate spreads globally, the findings can help overseas project teams customize their own NVA activities and evaluation models. Practical implications As BIM implementation is mandated in Singapore, BIMIR evaluation helps local project teams identify weak areas of their BIM implementation activities and prioritize resources to enhance those areas. Originality/value No tool has been developed for evaluating BIMIR at the project level in the construction industry in Singapore or at large in Asia. Four BIMIR statuses are defined, which are consistent with Singapore’s BIM guidelines and standards.

Identifying the Critical Risks in Railway Projects Based on Fuzzy and Sensitivity Analysis: A Case Study of Belt and Road Projects

The Belt and Road Initiative (BRI) is a Chinese development strategy developed in order to establish connectivity and deepen cooperation between China and other countries, increase trade, and support the socio-economic development of vast regions. A significant number of railway projects are planned to be constructed under BRI since railways are the most efficient means of transportation. This paper investigates the critical risks in railway projects implemented under BRI. In total, 24 potential risks in BRI railway projects are identified and categorized into 6 groups. A questionnaire survey is conducted in order to collect data about the probability of risk occurrence and their impact. To identify the critical risks in railway projects, a novel method based on fuzzy and sensitivity analysis is developed and applied for risk assessment. This method uses a fuzzy synthetic evaluation approach to assess risks and sensitivity analysis as criteria for critical risk identification. The results show that the most critical risks in railway projects are changes in design, design errors, cooperation between China and BRI country, loan risk, complex geological conditions of terrain, and geopolitical risk. The theoretical contribution of this paper is a novel method which combines fuzzy and sensitivity analysis into a single approach.

Sustainability Performance Evaluation of Hybrid Energy System Using an Improved Fuzzy Synthetic Evaluation Approach

The hybrid energy system (HES) has attracted more and more attention since it can not only achieve multi-energy supply but realize cascade utilization of energy resources. However, the performances of the HES in relation to economic, environmental, social, and technological aspects are rarely studied. Therefore, this paper tries to fill this research gap to evaluate the sustainability performance of an HES. First, an evaluation criteria system is established based on a literature review. After that, the group analytic hierarchy process (GAHP) technique is used to obtain the importance weights of these criteria. Later, the sustainability performance of the HES is calculated through an improved fuzzy synthetic evaluation (FSE) approach based on a cloud model. The applicability of this approach is demonstrated by a real case study in Zhejiang province, China. Finally, the sensitivity analysis results reveal that the overall consequence is that the performance of an HES is robust when the criteria weight is floating within a certain range (−30–30%), and the comparative analysis with the traditional FSE also reveals that the proposed approach is superior.

Evaluating fuzzy operators of an object-based image analysis for detecting landslides and their changes

This article presents a method of object-based image analysis (OBIA) for landslide delineation and landslide-related change detection from multi-temporal satellite images. It uses both spatial and spectral information on landslides, through spectral analysis, shape analysis, textural measurements using a gray-level co-occurrence matrix (GLCM), and fuzzy logic membership functionality. Following an initial segmentation step, particular combinations of various information layers were investigated to generate objects. This was achieved by applying multi-resolution segmentation to IRS-1D, SPOT-5, and ALOS satellite imagery in sequential steps of feature selection and object classification, and using slope and flow direction derivatives from a digital elevation model together with topographically-oriented gray level co-occurrence matrices. Fuzzy membership values were calculated for 11 different membership functions using 20 landslide objects from a landslide training data. Six fuzzy operators were used for the final classification and the accuracies of the resulting landslide maps were compared. A Fuzzy Synthetic Evaluation (FSE) approach was adapted for validation of the results and for an accuracy assessment using the landslide inventory database. The FSE approach revealed that the AND operator performed best with an accuracy of 93.87% for 2005 and 94.74% for 2011, closely followed by the MEAN Arithmetic operator, while the OR and AND (*) operators yielded relatively low accuracies. An object-based change detection was then applied to monitor landslide-related changes that occurred in northern Iran between 2005 and 2011. Knowledge rules to detect possible landslide-related changes were developed by evaluating all possible landslide-related objects for both time steps.

Applying Fuzzy Synthetic Evaluation Approach to Risk Assessment of Large-scale Activities

Applying Fuzzy Synthetic Evaluation Approach to Risk Assessment of Large-scale Activities

A fuzzy synthetic evaluation approach for risk assessment: a case of Singapore's green projects

In recent years, green building has attracted wide attention from both academia and industry. As green building projects are inevitably plagued with risks, this study attempted to assess the risks in green building projects in Singapore. Categorizing a list of 28 risk factors into 11 groups, the study performed a questionnaire survey and received 31 responses from project managers in Singapore. A risk assessment model was developed using the fuzzy synthetic evaluation approach. Using the proposed model, the likelihood of occurrence, magnitude of impact and risk criticality of each risk factor, group and the overall risk were calculated. “Inaccurate cost estimation” was the top risk factor, and “cost overrun risk” was the most critical risk group. The overall risk criticality was high, implying risk management was still necessary for green construction in Singapore. The proposed risk assessment model is reliable and practical for professionals in the green building industry, and can be applied in risk assessment in other countries. As few studies focused on risks in green projects, this study expands the knowledge and literature.

Comprehensive evaluation of substrates in vertical-flow constructed wetlands for domestic wastewater treatment

Substrates are the important component of constructed wetlands (CWs), which have an effect on construction cost, purification capability and stable operation, so that substrate optimization is the key part of CWs design. The comprehensive evaluation system, including four layers, eleven indicators and nine schemes, for substrates in vertical-flow CWs treating domestic wastewater was established based on analytic hierarchy process. Then combined with Delphi method and fuzzy synthetic evaluation approach, zeolite, anthracite, shale, vermiculite, ceramic filter material, gravel, steel slag, bio-ceramic and combination substrate (isopyknic layered anthracite, bio-ceramic and zeolite) were evaluated from the viewpoints of purification effect, practical performance and economic analysis. The results showed that phosphorus removal, nitrogen removal, chemical stability were the main factors of substrate selection. Combination substrate was the best scheme among nine substrates. Zeolite was ideal substrate for nitrogen removal and biocompatibility, while anthracite and steel slag were ideal substrates for phosphorus removal. The comprehensive evaluation system of substrates was beneficial to comprehensive compare all aspects of performance for different substrates, and could be improved according to the actual situation of engineering applications, so as to provide guidance of substrate selection for CWs design.

Evaluation and ranking of risk factors in public–private partnership water supply projects in developing countries using fuzzy synthetic evaluation approach

As governments embark on public–private partnerships (PPPs) to develop their water infrastructure, effective risk assessment, which has remained nebulous, has become an important step to ensure success of these projects. This paper investigates the risk factors and assesses the risk level of PPP water supply projects in developing countries using fuzzy synthetic evaluation (FSE) approach. A 40-factor risk list was established through investigation in water projects cases and related literature and an industry-wide questionnaire survey with industry practitioners. Initial statistical analysis yielded 22 critical risk factors that would have significant impacts on water supply partnerships. These factors were categorized into three principal factors (financial/commercial, legal and socio-political, and technical) forming the input variables for FSE analysis. The study showed that the overall risk level of water PPPs in developing countries is high, suggesting that these projects are risky to both governments and private participants. The fuzzy analysis, overall, confirmed that financial/commercial risk category is the most critical principal factor, followed by legal and socio-political category and technical category. The FSE approach to risk assessment can be used as an initial screening to establish risk factors that require attention of management and further detailed analysis. This study demonstrates that FSE methodology can be used to synthetically analyze local conditions in a country prior to setting up the project structure and normal due diligence. It is a multi-attribute risk assessment framework and may serve as a risk evaluation tool for private investors, policy-makers and decision-makers.