Structure Of Fuzzy Model Research Articles

Enabling Industry 5.0-Driven Circular Economy Transformation: A Strategic Roadmap

Because Industry 4.0 is not a better solution to the problems of the circular economy development process, the European Union proposed Industry 5.0 as a supplement to Industry 4.0. However, presently, no relevant research exists on the promotion of a circular economy under Industry 5.0, and the limited understanding of this process is the fundamental obstacle for enterprises to pursue digitalization and sustainable operations. This study addresses this knowledge gap by developing a roadmap explaining the use of the drivers of Industry 5.0 to support and promote the transformation to a circular economy. This study first screens the literature and determines 11 drivers of Industry 5.0. Secondly, on this basis, a fuzzy explanatory structure model of these drivers promoting a circular economy is constructed. Finally, a strategic roadmap is constructed for Industry 5.0 to promote a circular economy. The results reveal that the 11 key factors driving the circular economy are complementary, among which the quantitative criteria and indicators are the most critical and are present at the bottom of the strategic map. Value chain integration and the transformation into a sustainable business model are the most complex drivers. The strategic roadmap can explain the effects of the various drivers on the transformation to a circular economy and the order required to promote this transformation. The resulting management mindset is expected to assist manufacturers, industrialists, academia, and governments in providing services, thus forming a strategic guideline driven by Industry 5.0 factors to promote the circular economy.

Sustainability Constraints on Rural Road Infrastructure

Research on the sustainability of rural roads is of great significance to the integrated promotion of rural habitat improvement, the maintenance of regional ecological patterns, and the implementation of the rural revitalization strategy. This paper examines the constraints to ensuring the sustainability of road infrastructure in rural Shaanxi, China. Rural road infrastructure plays an important role in poverty alleviation. Rural Shaanxi Province is situated among a variety of terrains and spans a large area. Therefore, using the current situation of rural roads in the province as a starting point, the constraints and their rankings that impede the sustainability of road infrastructure are identified through the fuzzy Delphi method (FDM) and structural equation modeling (SEM), which in turn suggests governance measures that can be taken. The data in this paper come from 498 valid questionnaires obtained from 50 townships and 101 sample villages in Shaanxi Province. Due to the huge number of questionnaires, the questionnaires were tested with the help of SPSS 26.0 software, which showed that the questionnaires had high reliability and validity, and then the structural equation model was validated and modified according to the recommendations of goodness-of-fit statistics measurement and the modification index. Finally, the key factors affecting the sustainable development of rural road infrastructure were finally identified.

The influence of Self System Model of Motivational Development on college students’ learning engagement: a hybrid three stage Fuzzy Delphi and structural equation modeling approach

Students’ Emotional Intelligence and academic motivation are theorized to shape student learning engagement activities. Nevertheless, there is limited knowledge regarding the mediating mechanisms that explain this relationship. Based on Self System Model of Motivational Development, this study examined whether teachers’ support mediated the relationship between Emotional Intelligence and learning engagement, as well as the connection between academic motivation and learning engagement among college students. Totally, 336 students (female: 63.4%, male: 36.6%, mean: 1.63, Std.:0.482) were recruited from two public vocational education institutes in China. The expert questionnaire was sent via email to 10 experts in order to collect their thoughts on the aspects that influenced learning engagement. The factors that influenced students’ learning engagement were identified based on the Fuzzy Delphi method. Hence, the quantitative (questionnaire survey) design was used to gather students’ data on demographic variables, emotional intelligence, academic motivation, teachers’ support and learning engagement. The structural equation model (PLS-SEM) was used to analyse the data. The findings of this study reveal the positive impact of students’ Emotional Intelligence and academic motivation on learning engagement in the educational field by adopting teachers’ support as a mediating variable. The results highlighted vital internal and external factors in the process of creating an academic environment that motivated students to learn. This will improve the performance of the teaching faculty and lead to the student’s academic success. This research proposed a new instrument to assess the students’ engagement, which contributed to carrying out new research in the university educational context from a new research perspective.

Presenting an evolutionary model of entrepreneurial intelligence components in women: approaches to opportunity discovery and creation

PurposeA better understanding of the characteristics and capabilities of women entrepreneurs can significantly improve their chances of success. Therefore, three studies were conducted for this exploratory paper. We have discovered the characteristics of entrepreneurial intelligence among female entrepreneurs through semi-structured interviews based on conventional content analysis. According to the second study, qualitative meta-synthesis was utilized to identify characteristics of women's entrepreneurial intelligence at the international level. As a third study, we examined the evolutionary relationships of entrepreneurs' intelligence components following the discovery and creation of opportunities.Design/methodology/approachThe present paper was based on three studies. In the first study, 15 female entrepreneurs were interviewed using purposive sampling in the Guilan province of Iran to identify the characteristics of entrepreneurial intelligence at the national level. An inductive content analysis was performed on the data collected through interviews. Using Shannon entropy and qualitative validation, their validity was assessed. In the second study, using a qualitative meta-synthesis, the characteristics of women's entrepreneurial intelligence were identified. Then the results of these two studies were compared with each other. In the third study, according to the results obtained from the first and second studies, the emergence, priority and evolution of entrepreneurial intelligence components in two approaches to discovering and creating entrepreneurial opportunities were determined. For this purpose, interviews were conducted with 12 selected experts using the purposeful sampling method using the fuzzy total interpretive structural modeling (TISM) method.FindingsIn the first research, this article identified the components of entrepreneurial intelligence of women entrepreneurs in six categories: entrepreneurial insights, cognitive intelligence, social intelligence, intuitive intelligence, presumptuous intelligence and provocative intelligence. In the second study, the components of entrepreneurial intelligence were compared according to the study at the national level and international literature. Finally, in the third study, the evolution of the components of entrepreneurial intelligence was determined. In the first level, social intelligence, presumptuous intelligence and provocative intelligence are formed first and social intelligence and provocative intelligence have an interactive relationship. In the second level, entrepreneurial insight and cognitive intelligence appear, which, in addition to their interactive relationship, take precedence over the entrepreneur's intuitive intelligence in discovering entrepreneurial opportunities. With the evolution of the components of entrepreneurial intelligence in the opportunity creation approach, it is clear that intuitive intelligence is formed first at the first level and takes precedence. At the second level, there is cognitive intelligence is created. At the third level, motivational intelligence and finally, at the last level, entrepreneurial insight, social intelligence and bold intelligence.Originality/valueThis study has the potential to discover credible and robust approaches for further examining the contextualization of women's entrepreneurial intelligence at both national and international levels, thereby advancing new insights. By conceptualizing various components of entrepreneurial intelligence for the first time and exploring how contextual factors differ across nations and internationally for women's entrepreneurship, this paper challenges the assumption that the characteristics of women's entrepreneurial intelligence are uniform worldwide. It also depicts the evolution of the components of entrepreneurial intelligence.

Construction of a Comprehensive Evaluation System for the Core Literacy of Physical Education and Health Courses in Colleges and Universities

Abstract This study actively explores the importance of the joint construction of physical education and health courses in colleges and universities. It emphasizes its positive impact on students’ physical and mental health, talent cultivation and social development. Based on the PDCA model, the article establishes a comprehensive evaluation system, determines the weights of the indicators through the coefficient of variation method, and analyzes the cultivation of core literacy and the influencing factors using fuzzy comprehensive evaluation and structural equation modeling. The validity of the evaluation system is examined and verified with ten colleges and universities in Province L as an example, showing that the comprehensive evaluation score is as high as 95.16 points. This complete evaluation system not only helps colleges and universities to improve the quality of education, but also points out the direction for improving students’ core literacy in physical education and health.

Assessing the factors influencing the adoption of geothermal energy to support the national grid in emerging economies: Implications for sustainability

The ongoing Russia-Ukraine conflict has made the global energy crisis a severe issue, particularly for emerging economies with a sharp rise in load shedding in communities, disruptions in industrial operation, and an increased cost of living. Shifting our focus from fossil fuel-based energy to sustainable and promising renewable energy sources, like geothermal energy (GE), is crucial to addressing the ongoing energy crisis. Therefore, this study aims to evaluate the significant factors influencing the adoption of GE to support the national grid of an emerging economy like Bangladesh. An integrated framework consisting of the Delphi method, fuzzy total interpretive structural modeling (TISM), and fuzzy Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis was utilized in this study to evaluate the hierarchical interrelationships among the significant factors. The findings indicate that the top two influencing factors are the “scope for new investments and employment” and the “growing need for inexpensive and renewable energy sources”. The study's findings can offer significant insights to decision-makers and policymakers, which can aid in the development of long-term strategic plans to facilitate the successful adoption and integration of GE and promote sustainability and low-carbon economy in the energy sector.

Measurement of carbon effect in land consolidation projects and evaluation of low-carbon promotion paths: a case study of Wudi County, Shandong Province, China.

Against the backdrop of China's "double carbon" objective, the exploration of low-carbon land consolidation has become a prominent area of focus for enhancing the development of ecological civilization. In this study, three typical projects at different time points (2016, 2019, and 2022) in Wudi County were selected to measure the carbon effect of land consolidation from four perspectives: artificial and industrial materials, mechanical shift consumption, land use structure, and farmland ecosystem. Based on the calculation of carbon effect of land consolidation by using carbon emission coefficient method, the changes of land use structure and carbon storage of farmland ecosystem before and after land consolidation were corrected by using GIS tools and net ecosystem productivity (NEP) model based on remote sensing technology, and the carbon emission intensity of each land consolidation project was finally obtained. The study summarized the influencing factors of carbon emissions through the above analysis and uses the fuzzy interpretation structure (FISM) model to provide the hierarchy of influencing factors of carbon emissions, thus proposing a low-carbon promotion path for land consolidation. The findings of this study can serve as a useful reference for low-carbon land consolidation efforts. The results showed that (1) the first, second, and third projects emitted 6140.06 t, 1243.78 t, and 17,604.62 t of carbon, respectively. Among them, the largest contributors to these emissions were labor and industrial materials, followed by mechanical shift; land use structure and farmland ecosystem were the main sources of carbon sinks and have a positive impact on the carbon cycle. (2) The carbon emission intensity of project one, project two, and project three after standardization is 0.26, 0.49, and 0.25, respectively, which are all at a high level. (3) According to the FISM model categorized 15 low-carbon upgrading paths, it was recommended that the government take a leading role in Wudi County by developing a scientific and rational construction plan. Additionally, efforts were made to actively protect farmland and forest land from destruction, reduce energy and material consumption, increase carbon storage in the farmland ecosystem, and promote low carbonization of land consolidation to the fullest extent possible.

G-normal fuzzy relational models are universal approximators

Making a fuzzy relational model (FRM) g-normal by a specific configuration of the FRM and putting some constraints on both its fuzzifier and its fuzzy relational matrix, results in some favorite features at the expense of loosing some degrees of freedom. In this paper, we show that the g-normal fuzzy relational modeling structure has the universal approximation property despite all the constraints that makes the model g-normal. Indeed, we prove that any real function in Lp (including continuous functions) can be modeled by a g-normal model with any arbitrary accuracy when the universe of discourse is a compact set.

An integrated approach to explore the barriers to lean manufacturing in the context of the COVID-19 pandemic: implications for sustainability

PurposeThe apparel industry of Bangladesh is rethinking lean manufacturing (LM) deployment because of the challenges imposed by the COVID-19 pandemic. Due to COVID-19, LM implementation in the apparel industry has become more difficult. Thus, the purpose of this study is to explore the barriers to implementing LM practices in the apparel industry of Bangladesh in the context of COVID-19 pandemic.Design/methodology/approachFor evaluating the barriers, an integrated framework that combines the Delphi method and fuzzy total interpretive structural modeling (TISM) has been designed. The application of fuzzy TISM has resulted in a structured hierarchical relationship model of the barriers with driving and driven power.FindingsThe findings reveal that “lack of synchronization of lean planning with strategic planning”, “lack of proper understanding of lean concept” and “low priority from the top management” are the three top most important barriers of LM implementation in apparel industry.Practical implicationsThese findings will help the apparel industry to formulate strategy for implementing the LM practices successfully. The proposed model is expected to contribute to the sustainable development goals (SDGs) such as Responsible Consumption and Production (SDG 12); Decent Work and Economic Growth (SDG 8); Industry, Innovation and Infrastructure (SDG 9) via resilient strategies.Originality/valueThis study is one of few initial efforts to investigate LM implementation barriers during the COVID-19 epidemic in a real-world setting.

Exploring barriers in supply chain disaster management using fuzzy total interpretative structure modeling approach: Insight from Thai automotive industry

Supply chain disaster management (SCDM) has become a topic of interest for academicians and practitioners. Many businesses worldwide are experiencing disasters that disrupt their supply chains. This study attempts to identify the barriers to SCDM implementation and investigate their interrelationships. Fourteen barriers are identified through a broad literature review and certified by a panel of experts. The Fuzzy interpretative structural modeling (Fuzzy-ISM) approach is applied to construct a hierarchical model and identify the contextual relationships among SCDM barriers. Matrice d’ impacts croises-multiplication applique a classement (MICMAC) is deployed to categorize the 14 barriers into four actionable groups based on driving and dependence power. This study contributes to SCDM knowledge by identifying the main barriers to implementation and revealing their interrelationships. This empirical study uses an upstream supply chain in the Thai automotive industry. The results provide insight into the Thai automotive industry to alleviate barriers and efficiently and effectively manage resources while implementing SCDM. Finally, future research directions and theoretical and managerial implications are discussed.

Fuzzy Model Parameter and Structure Optimization Using Analytic, Numerical and Heuristic Approaches

Fuzzy systems are widely used in most fields of science and engineering, mainly because the models they produce are robust, accurate, easy to evaluate and capture real-world uncertainty better than do the classical alternatives. We propose a new methodology for structure and parameter tuning of Takagi–Sugeno–Kang fuzzy models using several optimization techniques. The output parameters are determined analytically, by finding the minimum of the root-mean-square error (RMSE) for a properly defined error function. The membership functions are simplified by considering symmetry and equispacing, to reduce the optimization problem of finding their parameters, and allow it to be carried out using the numerical method of gradient descent. Both algorithms are fast enough to finally implement a strategy based on the hill climbing approach to finding the optimal structure (number and type of membership functions) of the fuzzy system. The effectiveness of the proposed strategy is shown by comparing its performance, using four case studies found in current relevant works, to the popular adaptive network-based fuzzy inference system (ANFIS), and to other recently published strategies based on evolutionary fuzzy models. In terms of the RMSE, performance was at least 28% better in all case studies.

Identification of 4D-BIM Barriers in Offshore Construction Projects Using Fuzzy Structural Equation Modeling

Planners face many obstacles during the planning phase of any new project, especially project scheduling due to the numerous details and complexity of each uniquely designed project; previous experience in similar projects and traditional scheduling methods are not sufficient. The 4D-BIM schedule is the best solution, as it can be integrated with other modern technologies such as UAS, which improves project scheduling by allowing the project team to access project plans, details, and time-related information to simulate construction sequences. Despite the benefits of using 4D-BIM, planners prefer traditional planning and scheduling methods because of the barriers to using modern technologies. This research proposes a structural equation model focusing on estimating the weights of BIM barriers in offshore construction projects, including: the investigation of barriers keeping the construction industry standing at 3D-BIM; the relationships between them; and the evaluation of the probability and impact of each, using fuzzy theory. To validate the proposed model, a case study of an offshore project was conducted. The most important latent variables were awareness, risk, demand, and management, while the most prominent observed variables were the uncertainty of the return on investment and the lack of experienced users. This research guides project managers on actions that can be taken for each key variable to enhance and develop the use of 4D-BIM in project scheduling.

Modeling the challenges of technology adoption in dairy farming

Purpose The global research evidences indicate that the technology adoption in case of agribusiness has a potential to enhance the performance and bring operational efficiency. India is the world’s largest producer as well as consumer of milk but struggles with yield per cattle, overall productivity, low rate of technology acceptance and adoption, health detection of milching units, animal data recording and presence of dairy products in the global market. The purpose of this study is to focus on identifying the challenges of technology adoption in dairy farms and constructing a hierarchical model using soft systems methodology. Design/methodology/approach This study uses nominal group technique-based discussion with domain experts and personal interviews with dairy farm owners/managers for the identification of challenges, fuzzy interpretative structural modeling as well as FMICMAC to develop a hierarchical model of challenging elements and to divide the identified elements into four categories based on the dominance of driving-dependence power. Findings This research has developed a list of 12 challenges affecting the technology adoption in a dairy farm business unit, identified through the personal interviews with 60 dairy farms across three highest milk-producing states of India in terms of annual milk output – Haryana, Punjab and Uttar Pradesh. Lack of government support followed by lack of educational opportunities in dairy-based education were found as the most crucial and high driving challenges, whereas high cost, huge investment and low acceptance of decision-maker were found as the most dependent challenges of technology adoption. Research limitations/implications This research is one step ahead of interpretive structural modeling that considers the fuzzy-based dominance in the model to showcase the degree of relationship along with its existence, but it lacks to statistically validate the findings using techniques like SEM. Practical implications This paper has developed a list of challenges in adoption of technology along with their inter-relationships to highlight the required focus challenge that drives or is dependent on the other challenges. The goal is to bring performance improvement and assist Indian dairy farm business stakeholders or decision-makers in formulating strategic and action plans and help policy planners to make favorable policies based on the understanding of contextual relationship between challenges. Social implications In Indian context, dairy is an important part of agriculture sector, and milk is an essential item that facilitates income generation to small and rural households and a source item for several other businesses and activities. The results of this research suggested the policy planners and government to ensure subsidized and insured technologies, training support and facilities, educational opportunities and efforts for promotion of technology adoption among dairy farmers. The suggestions are purely on the basis of the relevance of challenges in the hierarchy and can play a significant role in improving the level of technology adoption and can ultimately uplift the social and economic well-being from micro-level of farmers to macro-stage concerning economic development of India. Originality/value To the best of the authors’ knowledge, this study is purely original and outcome of the research conducted by authors.

Auxiliary superfield method for statistical predictions of complex, structural acoustics systems: Saddle point approximation for the mean field.

The auxiliary superfield approach is proposed as a method to obtain statistical predictions of the acoustic response of complex elastic structures. The potential advantage of the method is the full retention of interference and resonance effects associated with the degrees of freedom being averaged over. It is not known whether this approach leads to tractable problems for structural acoustics systems, however. We have applied the method to the idealized case of an infinite, thin plate with attached oscillators to obtain the mean Green's function. The oscillators are assumed to have an uncorrelated, Gaussian distributed mass and stiffness distribution representing a simple form of complex internal structure. Using the auxiliary superfield approach, the mean Green's functions are expressed exactly as a functional integral. For relatively small disorder, the integral may be estimated by a saddle point approximation which leads to coupled integral equations for effective mass and stiffness matrices that can be solved numerically for a given spatial distribution of the disorder. With the solutions for these matrices, one obtains a self-consistently determined, generalized fuzzy structure model. We give analytical solutions for the simple case of a uniform spatial distribution. The results are promising for the application of the method to more challenging geometries.

MULTI-MOTOR DRIVE NON-PARAMETRIC BLACK-BOX FUZZY MODEL

The multi-motor drives, the typical examples of which are continuous lines (CL) for tension processing of various materials are complex and coupled MIMO higher-order nonlinear systems, which parameters are difficult to identify. The article focuses on a method for the design of a non-parametric black-box fuzzy model of a continuous production line with emphasis on minimal knowledge on the modelled system. The proposed fuzzy model structure is based on the state space representation of the dynamic system in discrete form, which only requires a suitable set of information on its input/output relations. The properties of the proposed CL fuzzy model were verified by experimental measurements on a CL laboratory model. The obtained results have confirmed the rightness and effectiveness of the fuzzy model design method that can be applied not only in the field of industry technologies with CL but also in modeling and control of nonlinear dynamic systems.

A mixed method for determination of cut-off dates in liner shipping

ABSTRACT Operating with fixed schedules requires coordinating and cooperating with many actors in liner shipping. Therefore, liner operators announce predetermined cut-off dates for each voyage for Sippers to perform cargo-related transactions and send their documents. The shippers complain that the cut-off times are primarily for the operator’s benefit and create a very tight time. However, the operators have trouble that the shippers cannot fulfill the necessary instructions and documents on time. From this point of view, this study aims to offer optimized cut-off determination for liner services and employs a mixed-method approach to evaluate the cut-off process of liner operators. Firstly, a qualitative study was conducted to obtain factors affecting cut-off date determination. Second, the factors affecting cut-off dates were analyzed with the fuzzy Total Interpretive Structural Modelling (TISM) method. Third, a step-by-step shipping process from booking to the vessel’s departure was developed. Moreover, the simulation method was applied with actual data to offer alternative schedules for a liner operator for its two liner services. The results show that even using only the two strongest driving factors determined in the TISM process (TEU capacity of the vessel and number of port calls) improves the cut-off determination simulation performance results by 20%.

Delving Into the Interdependencies in the Network of Economic Sustainability Innovations

Legislative pressures and public awareness are urging companies to foster sustainability innovations that improve business operations. Limited studies explored the underpinnings of the economic dimension of sustainability innovations; studying economic innovation criteria in the manufacturing sector of emerging economies can inform other industries while recession fears loom the financial prospects. This article develops a decision analysis and evaluation framework for investigating the interdependencies in the network of economic sustainability innovation criteria using fuzzy Total Interpretive Structural Modeling (TISM). It is found that the “ <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">availability of financial resources for promoting innovation</i> ” is the criterion with the most network relations; this is what the managers should focus on to better pursue sustainability innovations in the supply chains and facilitate the shift towards sustainable industrial development. The study is concluded by providing practical insights into the economic dimension of sustainability innovations for industrial managers and academics.

Prioritising and testing the integrated behavioural model of organisational citizenship behaviour through fuzzy AHP and structural equation modelling

Prioritising and testing the integrated behavioural model of organisational citizenship behaviour through fuzzy AHP and structural equation modelling

Prioritising and testing the integrated behavioural model of organisational citizenship behaviour through fuzzy AHP and structural equation modelling

Prioritising and testing the integrated behavioural model of organisational citizenship behaviour through fuzzy AHP and structural equation modelling

Applying Fuzzy Cognitive Map Based on Structural Equation Modeling for Perceiving the Service Quality and Attributes in Service Industry

&lt;p&gt;This study explores why the business firm survival due to provide the service quality and perceived values since servicescape, waiting experiences and food quality are three major factors that affect customer intentions. Therefore, the most examined restaurant attributes are included physical setting and environment, wait time, and food and service quality in this study. Servicescape positively effects perceived service quality. However, service quality is an overall judgment that a based on the perception of the object in consumer process of customer and can be seen as the result of customer evaluation. Therefore, we analyze data from 396 full-service restaurant diners in Taiwan based on Fuzzy Cognitive Map (FCM) and Structural Equation Model (SEM) to investigate hypothesis and to identify the most relevant decision factors to enhance outcome variables and furthers to help decision makers have a clear picture of affecting factors in the customer behavioral intention. The findings support the model and show that perceived overall service quality and perceived value do exert mediating effects in the relationship between restaurant-related attributes and customer behavioral intention. This study could ultimately contribute to the business firms in service industry to provide decision makers the most desirable outcomes to survival the competitive society.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;