Fuzzy-set Analysis Research Articles

ABSTRACT Digital transformation plays a central role in the balance between technology and sustainability, especially for small and medium‐sized enterprises (SMEs) in Romania. This study examines the impact of the adoption of digital technologies on the competitiveness, development of digital corporate culture, digital management and ESG (environmental, social, governance) performance of SMEs in the manufacturing sector. Based on 463 valid questionnaires, a model was developed and empirically tested using fsQCA (qualitative comparative fuzzy set analysis) and PLS‐SEM (partial least squares structural equation modeling) methods. The results show that the implementation of digital technologies contributes significantly to improving the competitiveness, performance and ESG practices of SMEs. Companies with a clear digital strategy and an innovative digital culture not only have greater operational efficiency, but also greater social and environmental responsibility. The study makes it clear that digital transformation is not only a strategic driver for sustainability and innovation for SMEs, but also contributes to adaptability and long‐term success. Policy and practice are recommended to expand targeted measures and funding programs to support the digitalization of SMEs to promote the balance between technological advances and sustainable business.

The increasing pressure of the need of environmentally friendly and resource-friendly industrial processes, has boosted the sustainable manufacturing as a strategic necessity, especially in the emerging economies such as India. The paper presents the multi-dimensional nature of the adoption of sustainability within Indian manufacturing, in particular, small and medium enterprises (SMEs). With the mixed-methods research design, the study combines survey information of more than 100 firms, interviews with experts, the estimation of green technology, organizational enablers, and policy mechanism using simulation modeling with RETScreens and MATLAB, and structural equation modeling (PLS-SEM) to evaluate the influence of green technologies, organizational enablers, and policy mechanisms. The findings indicate a middle ground of adoption as far as green manufacturing processes like energy systems, waste heat recovery, and closed-loop water reuse are concerned. However, adoption is not equally distributed across the sectors because of the limitation of capital, absence of technical competencies, and fractured laws. Companies that have incorporated the use of Industry 4.0 technologies including the IoT, AI, and blockchain have shown better sustainability results, particularly when coupled with endogenous forces such as the dedication of top management, cross-functional education, and awareness of cultures regarding sharing knowledge. The importance of favorable policies and government incentives is also mentioned in the study but the current mechanisms are usually found to be insufficient to cover the needs of SMEs. Fuzzy set analysis and life cycle analysis (LCA) validate that effective adoption of sustainability is the product of synergistic technologies, organizational capacity and institutional support. The study gives a verified sustainability evaluation tool that can be used by companies to compare performance and strategize on interventions. The findings offer policy-makers, executives in the manufacturing sector, and scientific communities interested in scaling sustainable manufacturing with a view to scaling it in an inclusive and systematic manner.

Communication is key to social interaction and people’s socialisation. The interaction between people and institutions is based on strategic communication as a vital component for the survival of society. This strategic communication is used by agent-communicators on behalf of formal organisations, and intended for their target public. Moreover, every strategic communication is affected by invisible social forces (institutions, networks, cognitive frames), which ‘manage’ the process of communication with the public. We use the SOFIA approach to provide an analytical model of influence of the social forces during the shaping of the public. The aim is to combine theoretical and practical approaches of Communication and Social Field Theory. Further, using qualitative comparative analysis (QCA), the causal complexity of these relationships is examined, taking account of the necessary and sufficient conditions for particular outcomes to occur. Institutions and networks are necessary conditions, yet neither meets the criteria for sufficiency. However, the absence of these conditions does not necessarily indicate the absence of communication. Exploring the combinations of necessary conditions for communication reveals complexities such as the interaction between institutions, networks and cognitive frames. The absence of certain social forces, together with the presence of other forces, emerges as a relevant condition for communication. Accordingly, the fact that institutions in the social field exist is not all that is important, but also that they communicate and create networks of interactions for the public’s better understanding. The strategic communication framework, navigated by the invisible social forces, actually improves the ability to shape the public in the desired direction. Keywords: social institutions, social networks, cognitive frames, fuzzy set analysis.

In China, smart city pilots has become an important scheme to promote the modernization of the national governance system and capacity. Based on the TOE framework, this study takes 35 Chinese smart cities as sample cities and uses the qualitative comparative analysis (QCA) to explore the influencing factors of smart city pilot construction. The results show that: (1) No single factor can constitute the necessary conditions for the high and non-high construction efficiency of a smart city pilot. (2) There are five configurations leading to the high construction efficiency of a smart city pilot, which can be summarized into three driving modes: the organizational mode composed of organizations, the organization–environment mode composed of organizations and environment, and the technology–environment mode composed of technology and environment. There are three driving modes of non-high construction efficiency of a smart city pilot, which have an asymmetric relationship with the driving mode of high construction efficiency of a smart city pilot. (3) There is a potential substitution relationship among relevant factors in the aspects of technology, organization, and environment, which can effectively replace and promote the efficient construction of a smart city. The research results have implications for improving the effectiveness of smart city construction and promoting urban innovative development and sustainable development.

Abstract Our country’s policy documents have put forward new requirements for the cultivation of students’ creative thinking in high school education, especially for the cultivation of creative thinking ability of students in the chemistry subject, which is a field of scientific education. In this context, this study introduces the concept of transactive memory system based on the research logic of educational psychology, and analyzes the configuration effect that inhibits the formation of creative thinking ability of high school students in the chemistry subject from the perspective of “transactive memory system-group characteristics”. Through the qualitative comparative analysis of fuzzy sets, it is found that the matching of transactive memory system and group characteristics sometimes inhibits the formation of creative thinking ability of high school students in the chemistry subject. Through the data analysis results of 179 high school student groups, it is found that there are two configurations that inhibit the formation of creative thinking ability of high school students in the chemistry subject, and low transactive memory system credibility and low group heterogeneity play a core role. The research results provide effective guidance for the theory and practice of high school chemistry education.

PurposeThis study aimed to formulate multi-level key performance indicators (KPIs) to systematically measure the performance of modular construction (MC) supply chains at the process, project, organization, and industry levels, as demonstrated in the case of modular integrated construction (MiC) for buildings in Hong Kong and the supply chain in the Greater Bay Area of China.Design/methodology/approachThis study first conducted a literature review to identify the initial indicators for MC supply chain performance measurement and verified them through three focus group meetings and twelve interviews. Based on the refined list of indicators, a questionnaire survey was carried out to determine the KPIs. Finally, this study organized a research workshop to consolidate and validate the findings.FindingsThrough scale ranking and fuzzy set analysis, a total of 15 KPIs were identified for measuring MC supply chain performance, including “manufacturability of module design,” “stakeholder satisfaction,” “MiC experience of supply group,” “assurance of supply,” “efficiency of approval procedures,” “end-user acceptance” and “incentive effectiveness.” The KPIs highlighted the pivotal domains that warrant attention and the necessity of multifaceted endeavors for MC supply chain enhancement.Originality/valueThis study contributes a multi-level measurement framework with KPIs to the literature on MC supply chain measurement. The efficacy of the mixed approach for formulating KPIs was demonstrated, providing a reference for other economies. Also, the multilevel KPIs help the government monitor the overall maturity of the entire supply chain network and facilitate the stakeholders directly involved in value creation activities to optimize process operations and strengthen organization capability.

COVID-19 and the changing profiles of poverty in India: A Fuzzy Set Analysis and Imputation Approach using PLFS Data

This research tackles an essential gap in understanding how passengers prefer to interact with artificial intelligence (AI) or human agents in airline customer service contexts. Using a mixed-methods approach that combines statistical analysis with fuzzy set theory, we examine these preferences across a range of service scenarios. With data from 163 participants’ Likert scale responses, our qualitative analysis via fuzzy set methods complements the quantitative results from regression analyses, highlighting a preference model contingent on context: passengers prefer AI for straightforward, routine transactions but lean towards human agents for nuanced, emotionally complex issues. Our regression findings indicate that perceived benefits and simplicity of tasks significantly boost satisfaction and trust in AI services. Through fuzzy set analysis, we uncover a gradient of preference rather than a stark dichotomy between AI and human interaction. This insight enables airlines to strategically implement AI for handling routine tasks while employing human agents for more complex interactions, potentially improving passenger retention and service cost-efficiency. This research not only enriches the theoretical discourse on human–computer interaction in service delivery but also guides practical implementation with implications for AI-driven services across industries focused on customer experience.

Street view images (SVIs) may provide information on near-surface urban changes which are not necessarily captured by spaceborne remote sensing data. The application of SVIs in assessing diverse built environment changes at the street level and over time remains challenging. This paper presents a stepwise rule-based method to identify key types of urban built environment changes using multi-year SVIs. In particular, physical/built environment changes along streets are evaluated based on proposed Street Units of Analysis (SUA) that account for both street layouts and street view features. The approach employs sharp variations of visual attributes derived from deep learning segmentation model DeepLabv3+. A stepwise rule-based algorithm classifies SUAs. Using panoramic SVIs from 2015–2019 in Wuhan, China, we identify critical types of changes such as those related to highway bridges, sidewalk increases, building increases, road losses, greenness increases, and mixed changes. Identified changes take place on over 50% of roads in the study area. In addition, the robustness of proposed approach is assessed based on results produced by manual labeling and by a fuzzy rough sets analysis. The approach is found to be robust and effective by having an 81.7% agreement with manually labeled analysis and an 80.5% agreement with fuzzy rough sets analysis. Overall, this study contributes to the development of a cost effective and efficient method for detecting physical changes on SUAs, which can be further utilized in studies that link urban changes, space use, and policy interventions.

This study employs fuzzy set analysis to categorize childcare policies across 19 OECD member countries, emphasizing defamilization strategies focusing on policy tool mixes. It investigates whether these strategies are state-centered or market-centered by analyzing the directness of funding, service creation, and the coerciveness of quality regulations. Key variables include the co-payment proportion of dual-income families, public preschool utilization rates, and monitoring intensity of childcare services, with women’s employment rates as the outcome. The analysis identifies six childcare service models based on government involvement and market dynamics, revealing that women’s employment rates tend to be higher when childcare services are predominantly market-driven. This suggests that market forces play a significant role in the defamilization of childcare, particularly as women’s participation in the labor market grows.

Subject. This article discusses a set of economic issues related to the innovative development of biological technology in agriculture. Objectives. The article aims to assess the role of biotechnology in ensuring food security, determining the level of innovative development of agricultural biotechnologies in Russia, the USA and China. Methods. For the study, we used the fuzzy set and cluster analysis methods. Results. Based on the analysis of trends in the development of the world market of agricultural biotechnologies, the article identifies the main factors hindering the innovative development of agricultural biotechnologies in Russia and the regions of Russia that are the most promising ones for the implementation of innovative projects. Conclusions. At present, Russia fails to keep pace with the United States and China in the field of agricultural biotechnology. It is necessary to use the positive foreign practices of introducing innovative biotechnologies in the agricultural regions of Russia.

Drug discovery and development is a challenging and time-consuming process. Laboratory experiments conducted on Vidarabine showed IC50 6.97 µg∕mL, 25.78 µg∕mL, and ˃ 100 µg∕mL against non-small Lung cancer (A-549), Human Melanoma (A-375), and Human epidermoid Skin carcinoma (skin/epidermis) (A-431) respectively. To address these challenges, this paper presents an Artificial Intelligence (AI) model that combines the capabilities of Deep Learning (DL) to identify potential new drug candidates, Fuzzy Rough Set (FRS) theory to determine the most important chemical compound features, Explainable Artificial Intelligence (XAI) to explain the features’ importance in the last layer, and medicinal chemistry to rediscover anticancer drugs based on natural products like Vidarabine. The proposed model aims to identify potential new drug candidates. By analyzing the results from laboratory experiments on Vidarabine, the model identifies Sulfur and magnesium oxide (MgO) as new potential anticancer agents. The proposed model selected Sulfur and MgO based on Interpreting their promising features, and further laboratory experiments were conducted to validate the model’s predictions. The results demonstrated that, while Vidarabine was inactive against the A-431 cell line (IC50 ˃ 100 µg∕mL), Sulfur and MgO exhibited significant anticancer activity (IC50 4.55 and 17.29 µg/ml respectively). Sulfur displayed strong activity against A-549 and A-375 cell lines (IC50 3.06 and 1.86 µg/ml respectively) better than Vidarabine (IC50 6.97 and 25.78 µg/ml respectively). However, MgO showed weaker activity against these two cell lines. This paper emphasizes the importance of uncovering hidden chemical features that may not be discernible without the assistance of AI. This highlights the ability of AI to discover novel compounds with therapeutic potential, which can significantly impact the field of drug discovery. The promising anticancer activity exhibited by Sulfur and MgO warrants further preclinical studies.

Abstract In order to realize the reform and development of the enterprise’s economic management mode under the digital economic environment, this paper proposes the path of enterprise economic management informatization construction based on ERP and correspondingly constructs its enterprise economic management informatization construction evaluation model. Determine the evaluation factor set and construct the evaluation index system, determine the weights through the AHP method, calculate the index affiliation degree, and utilize the fuzzy comprehensive evaluation model to carry out a comprehensive assessment. Based on the QCA method, the fuzzy set qualitative comparative analysis method fsQCA is proposed to explore the effectiveness of the enterprise economic management informatization construction path. Evaluation and analysis of enterprise economic management informatization construction using real estate enterprises in Henan Province, China, as a sample. The overall performance of economic management informatization construction of real estate enterprises in Henan Province belongs to the excellent grade. In the conditional group state analysis in the qualitative comparative analysis of fuzzy sets, as high as 98.1% of the enterprise economic management informationization construction shows a high-performance level, and the four group state paths can explain 67.2% of the cases of the enterprise economic management informationization construction performance level, which proves that the results of this paper have strong explanatory power.

The Influencing Factors of the Active Utilization of Rural Idle Homestead Sites—Qualitative Comparative Analysis of Fuzzy Sets Based on 12 Cases

The Influencing Factors of the Active Utilization of Rural Idle Homestead Sites—Qualitative Comparative Analysis of Fuzzy Sets Based on 12 Cases

An analysis of intuitionistic fuzzy sets in risk-based inspection: A case study of hydrogen crack damage in steel tanks under gas pressure

Green buildings are a crucial element in achieving sustainable development. The use of green buildings can save energy and reduce greenhouse gas emissions. Promoting the widespread adoption of green buildings has become a significant concern in many countries or regions. Although previous studies have identified a range of key factors influencing the promotion of green buildings, further analysis of the combination of these critical factors needs to be conducted. Therefore, based on the technology–organization–environment (TOE) framework, this study utilizes the fuzzy-set qualitative comparative analysis (fsQCA) method to analyze survey data from 26 cities in China, resulting in four high-level configuration paths for the widespread adoption of green buildings. The results indicate that (1) achieving high levels of widespread adoption of green buildings does not depend on any single factor; instead, it relies on the collaborative interaction of multiple elements across technological, organizational, and environmental dimensions; (2) the potential substitution relationships between conditional variables among different configurations within the TOE framework indicate that science and technology expenditure and gross domestic product play more significant roles in the path combinations for the promotion of green buildings; (3) through the study of the substitutive relationships of four configuration paths, it was found that when a city faces challenges in the widespread adoption of green buildings, such as an insufficient number of green building technology patents or underdeveloped green finance incentive systems, it can still achieve efficient green building adoption by formulating corresponding policies and enhancing cultural value guidance for groups like developers, contractors, and consumers. Conversely, the same is true. This paper explores the combination of critical factors in green building adoption, providing insights into addressing the differing foundational conditions of cities in the process.

Intelligent manufacturing enterprises play a crucial role in the modern industrial system and are key to high-quality economic development. However, most current research on intelligent manufacturing technology innovation focuses on single variables, lacking a comprehensive analysis from a linkage grouping perspective. This paper constructs an analytical framework for the technology innovation path of intelligent manufacturing enterprises from three dimensions: technology level, organization level, and environment level. Six antecedent variables are selected: R&D investment, digital transformation, human capital structure, profitability, government support, and competitive position. Using the fuzzy sets of qualitative comparative analysis (fsQCA) methodology, the paper examines the technological innovation paths of intelligent manufacturing enterprises in China. The research indicates that no single antecedent variable is necessary for high technological innovation; instead, the innovation path results from the synergistic effect of multiple conditions. The study identifies three paths leading to high technological innovation in intelligent manufacturing:"Government and Human Resource driven types," "Environmental-Organizational linkage types,"and"Organizational Resilience dominant types." This analysis provides reference suggestions for enterprises to adopt suitable development strategies based on their competitive positions.

Measurement and distribution characteristics of urban green productivity: based on fuzzy rough set and spatial autocorrelation analysis

On entrepreneurial and ambidextrous universities. Comparative study in Ibero-American Higher Education Institutions