Propose Strategies For Improvement Research Articles

A-188 Modal Failure and Effects Analysis, FMEA methodology, as a strategy to increase patient safety

Abstract Background Patient safety during the clinical care process is considered a priority in healthcare. Failure Mode and Effects Analysis (FMEA) is a proactive and systematic method of process evaluation and is used to identifying where and how each phase of the analytical process could fail allowing the detection of the causes and the effects they produce on the quality of the results that are issued. A regular use of this tool makes possible to identify the most critical steps, propose improvement strategies and evaluate their impact. The aim of the study is to evaluate applicability of the FMEA tool to identify errors in the pre analytical, analytical, and post analytical phase of a clinical laboratory as well as the main causes and effects, to reduce them by proposing improvement strategies Methods For each phase into which the laboratory activity is divided, the frequency and type of errors that are made and their final consequences on the patient are evaluated. A risk index (NPR=OxDxS) is calculated for each error considering the frequency with which it occurs (O), the ease with which it is detected (D) and the severity of the consequences on the patient (S). Values goes from 1 (rarely) to 10 (often). Improvement actions are proposed for all errors with a risk index greater than 100 and this index is re-evaluated after the implementation of that improvement measures. This same analysis is performed for three times over the last 10 years (in 2014, 2019 and 2023). Results In FMEA analysis carried out in 2014, a total of 40 errors were identified in the pre-analytical phase (63.5% of the total), 12 in the analytical phase and 11 in the post-analytical phase. 50% of the total errors detected required improvement strategies because they had an NPR≥100 value. In the 2023 evaluation, a total of 27 errors were identified in the pre-analytical phase, 10 in the analytical phase, and 5 in the post-analytical phase but only 6 required improvement strategies, which represents an 80% reduction in the most critical errors for patient safety. However, the pre-analytical phase continues to be the most critical, as it continues to account for 64% of the total errors identified, including the lack of identification of the patient or sample and the inadequate prior preparation of the patient. In analytical and post-analytical phases, the NPR values obtained in 2023 decrease significantly over analysis carried out in 2014 and its not needed to apply improvement strategies. Automation and the IT tools significantly reduce the number of errors with high NPR values, but it is undoubtedly the involvement of service professionals that makes the difference over the years. Conclusions The use of the FMEA methodological tool allows the design of appropriate indicators to detect and reduce errors in the clinical laboratory. Its application as part of a good quality control allows a continuous improvement in the laboratory process and consequently a guarantee of quality for the patient

기회형 창업자와 생계형 창업자의 인식을 반영한 창업생태계 활성화 방안: IPA 및 추세 분석

This study aims to explore activation strategies for the Korean entrepreneurial ecosystem by reflecting the perceptions of both opportunity-driven and necessity-driven entrepreneurs. Using Importance-Performance Analysis (IPA) and trend analysis, we evaluate key components of the entrepreneurial ecosystem and analyze the perception differences between the two types of entrepreneurs. The results indicate significant differences in how opportunity-driven and necessity-driven entrepreneurs perceive the importance and performance of startup support policies, providing valuable policy implications. Specifically, opportunity-driven entrepreneurs highly evaluated the performance of funding and government support programs, whereas necessity-driven entrepreneurs emphasized the importance of social safety nets and tax policies. Based on these perception differences, this study proposes improvement strategies for the entrepreneurial ecosystem, aiming to enhance the survival rate of startups and promote sustainable growth. The findings offer critical policy insights to better support the diverse needs of entrepreneurs.

Dual improved enzyme-linked immunosorbent assay based on multivalent bifunctional nanobody and polymerized horseradish peroxide for the ultrasensitive detection of Ochratoxin A in coffee samples

Enzyme-linked immunosorbent assay (ELISA) is favored for its high throughput, low cost, and simplicity, but the limited sensitivity of the traditional colorimetric ELISA restricts its wider application. Therefore, developing improvement strategies to enhance its sensitivity is a current research hotspot. In this work, we developed a multivalent bifunctional nanobody (Nb28-C4-SBP) by fusing a nanobody gene (Nb28) against ochratoxin A (OTA) with a self-assembling peptide (C4) and a streptavidin-conjugated peptide (SBP), which can introduce streptavidin-conjugated polymerized horseradish peroxidase (SA-PolyHRP) as a probe into the detection system. Subsequently, a dual improved ELISA (DI-ELISA) was developed using the higher affinity multivalent bifunctional nanobody (Nb28-C4-SBP) and the more enzyme-loaded probe (SA-PolyHRP) for the ultrasensitive detection of OTA in coffee samples. The DI-ELISA demonstrated a detection limit of 1 pg/mL, which was about 20-fold lower than that of the Nb28-C4-SBP and SA-HRP based ELISA and 266-fold lower than that of the Nb28-SBP and SA-PolyHRP based ELISA, respectively. In summary, we developed an ultrasensitive, rapid, and simple immunoassay for detecting OTA in coffee samples. Additionally, the proposed improvement strategy based on multivalent nanobody and polymerized horseradish peroxide is straightforward to operate and holds great potential for enhancing the sensitivity in various immunoassays.

Perceptual Attributes Identification and Importance–Performance Alignment Assessment of Urban Underground Complex: A Case Study in Chengdu Tianfu Square

Background and objectives: The urban underground complex integrates comprehensive architecture and subterranean space, presenting physical and psychological complexities. To mitigate the negative experiences associated with this complexity, we need to explore, in depth, how the built environmental elements of underground complexes affect user perception to design a comfortable, healthy, and biophilic underground space. Methods: We selected Tianfu Square, a typical underground complex in Chengdu, China, as the empirical case. We identified 26 key environmental indicators affecting user perception and designed Kano and satisfaction questionnaires based on these indicators. A total of 476 questionnaires were distributed to collect data on users’ attitudes towards changes in element quality and their satisfaction levels. By integrating the Kano model and IPA method, we defined the perceptual attributes of elements based on their impact on user experiences and assessed the alignment between element attributes and satisfaction. Results: We categorized the elements into five perceptual types: attractive, one-dimensional, indifferent, must-be, and reverse attributes, and assigned corresponding importance levels. We then compared the importance and performance scores of these elements, evaluated their satisfaction alignment, identified elements needing optimization, and proposed improvement strategies. Implications: This research provides valuable guidance for designers on how various built environment elements in underground spaces influence user perceptions, with practical implications for urban underground complex planning and design.

Research on enhancing the efficiency of food safety sampling inspections in China based on Pareto's law.

Food safety is pivotal for public welfare and directly impacts consumer health. Food safety sampling inspections (FSSIs) are essential in detecting unqualified food products and non-compliant manufacturers, which form an integral part of government regulatory frameworks. However, given the constraints on budgetary resources, improving the efficiency of food safety sampling inspections (EFSSIs) remains a considerable challenge in China's food quality and safety supervision. This study aims to apply Pareto's law, starting from the examination of food sample testing items and major hazard types, to theoretically analyze methods for improving the EFSSIs. Following the theoretical analysis, the research employs provincial food sampling data from China in 2022 to empirically validate the proposed improvement strategies. The research findings indicate that applying Pareto's law significantly reduces the number of items that should be tested for each food subcategory, effectively lowering testing costs for each batch of food samples. Theoretically, employing Pareto's law in sampling inspections can increase the EFSSIs to 2.78 times the current observed level. Furthermore, empirical validation using food sampling data confirms that EFSSIs can be improved to 2.12 times the existing level, consistent with theoretical predictions. Implementing Pareto's law in FSSIs facilitates the detection of more unqualified food products and non-compliant manufacturers without additional financial burden, significantly enhancing the EFSSIs. This approach provides an innovative strategy for government to bolster their food safety management efforts. © 2024 Society of Chemical Industry.

LUD-YOLO: A novel lightweight object detection network for unmanned aerial vehicle

Autonomous execution of tasks by unmanned aerial vehicles (UAVs) relies heavily on object detection. However, object detection in most images presents challenges such as complex backgrounds, small targets, and obstructions. Additionally, the limited computing speed and memory of the UAV processor affects the accuracy of conventional object detection algorithms. This paper proposes LUD-You Only Look Once (YOLO), a small and lightweight object detection algorithm for UAVs based on YOLOv8. The proposed algorithm introduces a new multiscale feature fusion mode that solves the degradation in feature propagation and interaction through the introduction of upsampling in the feature pyramid network and the progressive feature pyramid network. The application of the dynamic sparse attention mechanism in the Cf2 module achieves flexible computing allocation and content awareness. Furthermore, the proposed model is optimized to be sparse and lightweight, making it possible to deploy on UAV edge devices. Finally, the effectiveness and superiority of LUD-YOLO were verified on the VisDrone2019 and UAVDT datasets. The results of ablation and comparison experiments show that compared with the original algorithm, LUDY-N and LUDY-S have shown excellent performance in various evaluation indexes, indicating that the proposed improvement strategies make the model have better robustness and generalization. Moreover, compared with multiple other popular competitors, the proposed improvement strategies enable LUD-YOLO to have the best overall performance, providing an effective solution for UAVs object detection while balancing model size and detection accuracy.

Differences in Language Communication Between Chinese and American Cultures

With globalization advancing, intercultural communication has become frequent, making language crucial for cultural exchange. As influential countries, China and the United States exhibit significant cultural differences in their communication styles. Chinese culture values politeness and subtlety, often favoring indirect expression, while American culture emphasizes direct and clear communication. These differences extend to non-verbal communication as well. Understanding and respecting these differences is essential for enhancing cooperation in politics, economy, and education. This paper explores the main differences in language communication between Chinese and American cultures, analyzes the misunderstandings and conflicts these differences cause, and proposes improvement strategies. The goal is to provide insights for intercultural communication, education, and training to cultivate global talents and foster a harmonious international environment. The paper is divided into five parts: the first introduces the relationship between language and culture and the cultural backgrounds of China and the United States; the second analyzes cultural differences in language communication; the third explores misunderstandings and conflicts; the fourth proposes strategies for improving intercultural communication; and the fifth summarizes the findings and suggests future research directions.

Characterization and description of beekeeping agroecosystems in Hopelchén, Campeche, Mexico

Objective: to characterize honey bee (Apis mellifera) production systems in the municipality of Hopelchén, Campeche, Mexico. Design/methodology/approach: the sample was made up by 10% of the beekeepers in Holpechén, identified through the snowball method. A semi-structured questionnaire was designed with 94 questions grouped into five sections (general information, structure of the systems, product trade, technologies used, and decision making). The questionnaire was applied through the technique of interviewing those responsible for the 118 beekeeping production systems. The information obtained with the questionnaires was analyzed with descriptive statistics. Results: beekeeping is an important productive activity in the region of Los Chenes and La Montaña in Hopelchén, which are undergoing the process of generational replacement and are currently maintained by young adult producers who are younger than 45 years old. They own 55 hives on average per producer, which are located at a distance of 7.7 km from their households. The main technology is the use of sugar for feed, by 50% of producers, followed by the diagnosis of Varroa infestation and determination of moisture with 35 and 21.5% of beekeepers. Limitations on study/implications: the limited access to regions with beekeeping potential, as well as the lack of monitoring by outside staff, does not ease open-mindedness of beekeepers toward researchers. Findings/conclusions: the characterization of beekeeping production systems with high potential allows proposing improvement strategies to promote the development of small-scale producers.

Research on the Professional Development for Senior High School English Teachers Under the Background of New Curriculum Standards

The professional development of teachers is essential for adapting to evolving educational standards and improving teaching effectiveness. This study investigates the professional development needs of senior high school English teachers under the background of New Curriculum Standards in China. It examines current practices, identifies key components of effective professional development, and proposes improvement strategies. The New Curriculum Standards emphasizes student-centered learning, competency-based education, and technology integration. Key findings highlight the importance of sustained learning, relevance, active engagement, collaboration, and reflective practice. Customized training programs, supported by mentorship and flexible learning options, are essential. Technology integration in professional development is crucial for providing access to online resources and fostering continuous learning. Despite these strengths, the study identifies areas for improvement, including personalized training, follow-up support, and time management. Future research should focus on the long-term effects of professional development programs and their impact on teaching effectiveness and student outcomes.

Regulatory Compliance of Cosmetic Products in Kenya: A Narrative Review on Quality and Safety

This study reviews the regulatory compliance of cosmetic products in Kenya, with a focus on consumer risks and potential public health impact. A narrative review study design was employed and a literature search was conducted using government reports, publications, academic databases, and other relevant sources. Keywords such as cosmetic industry challenges and cosmetic regulation in Kenya were employed to search the literature for papers. Data focusing on regulatory frameworks, enforcement mechanisms, adverse reactions, and industry challenges was then extracted and discussed in the form of a narration. The growth of the cosmetic industry, fueled by urbanization, a rising middle class, and increased grooming awareness, has attracted both local and international investors, presenting challenges in maintaining product quality and safety standards. Seven cases of adverse reactions related to cosmetics were reported by Pharmacy and Poisons Board between 2018-2023. The current study identifies noteworthy challenges by examining Kenya’s regulatory framework, led by the Pharmacy and Poisons Board and the Kenya Bureau of Standards. Enforcement disparities within international standards, variance in regulations on prohibited ingredients, inconsistent labeling requirements, industry dynamics, and counterfeiting, compounded with the complex nature of safety assessments raise concerns for cosmetic regulators, distributors, and manufacturers. The study highlights existing gaps in regulatory oversight emphasizing the necessity of robust enforcement mechanisms. Compliance assessments by KEBS and PPB encompass the evaluation of ingredients, formulations, microbial contamination, packaging, and labeling. Factors contributing to regulatory noncompliance include poor product quality aggravated by supply chain complexities in the vast and diverse sector. The cosmetic cottage industry inadvertently presents a quality risk to consumers due to limited process and testing capacity. Reported adverse reactions, particularly to mercury-containing skin-lightening products, raise concerns about public health implications. This study advocates for continuous product monitoring and heightened vigilance. The review proposes improvement strategies, emphasizing a dynamic regulatory approach, periodic ingredient reviews, a centralized product approval system, and alignment with global manufacturing standards. Targeted consumer education initiatives focusing on product quality attributes, adverse reaction reporting, label reading, and counterfeit awareness are recommended.

Internal control system in commercial companies of Cuenca – Ecuador

This study focuses on evaluating the internal control system in commercial companies in Cuenca and proposing improvement strategies based on the results. The methodology adopted combines qualitative and quantitative approaches, using an instrument based on the COSO methodology. This questionnaire consists of 63 closed questions, to collect information about the 5 components of internal control, the sample was made up of 14 companies. The evaluation was divided into four phases: I. Planning, II. Execution, III. Results and IV. Improvement plan. The results are positive for trust, in the system and for its components with ranges between 76% and 85%. While trust in supervision or monitoring was evaluated as moderate. Finally, the identified weaknesses were addressed by drawing up an improvement plan in some companies belonging to the studied population.

A thorough assessment of various forest management planning initiatives and development of improvement strategies towards an ecosystem-based planning

Management planning for forests in Turkey has undergone gradual evolution over the last century. Developing and implementing a comprehensive management planning framework present significant challenges. This paper evaluates the effectiveness of various forest management planning approaches implemented across the country over different time periods, with overarching planning principles. It formulates a robust planning framework and proposes improvements grounded in scientific advancements and international standards. The assessment indicated that the management plans were developed using reputable scientific methods and principles aimed at ensuring the sustainable management of forest resources with certain strengths and opportunities presented by SWOT analysis. All management plans shared a common planning concept primarily focused on maximizing wood production through the area-control harvest scheduling method (except for continuous cover forest, which employed the single tree selection method). Each management plan established its unique vision, targets, policies, objectives, and planning guidelines. Forest inventory data were gathered through a combination of ground surveys and remotely sensed data to characterize and stratify the landscape. A robust in-house management authority and governance system with appropriate technical capacity and guidelines were developed and implemented, fostering a sound common working culture and tools. However, some notable drawbacks were identified, including political pressure, biomass/carbon accounting, growth-yield modelling, economic analysis, limited characterization of the full range of ecosystem services, risk and uncertainty analysis, food security and, particularly, long-term sustainability and scenario analysis with the appropriate decision-making tools and methods. Despite a few strengths, these limitations may raise concerns about the far-sighted design and application, potentially jeopardizing the sustainable management of forest ecosystems. Proposed improvement strategies for an efficient forest ecosystem management planning system include characterization of ecosystem services, modelling their productivity, scenario analysis with a decision support system, stakeholder involvement, balancing utilization and conservation targets, conducting risk and uncertainty analysis and economic analysis of management actions.

Integrating Data and Model Optimization for Improved Multi-Class Land Cover Classification Using Multispectral Remote Sensing Data

Abstract. With the rapid development of artificial intelligence, significant progress has been made in land cover classification using deep learning methods. However, in existing research, most studies focus more on improving classification accuracy by optimizing the model structure and less on mining the value of the data itself. In this paper, experiments on remote sensing multi-class land cover classification were conducted based on Worldview3 data, and strategies to improve classification accuracy were proposed in terms of sampling methods, band combination, loss function, and model optimization. Experiment results show that the proposed improvement strategies are effective for multi-class land cover classification, with recall, F1, and IoU improved by 29%, 17%, and 19%, respectively. The significant improvement in classification accuracy for less-represented targets confirms that enhancing data richness and balance leads to greater improvement than just optimizing the model.

A Teacher Competence Model and Measurement Based on Smart Education

Objective: This study mainly explores the impact of professional identity and digital literacy on the teacher ability of normal school graduates in the context of smart education and its impact channels and mechanisms. Theoretical Framework: Based on the research objectives and research hypotheses, we constructed a comprehensive conceptual model to understand the impact, impact pathways and mechanisms of professional identity and digital literacy on teacher competency of normal college students Method: The research uses a method that combines theoretical analysis and empirical investigation and combines positive psychology and teachers' professional development stage theory. This study established a competency structure model suitable for measuring normal college students. It used scale tools such as the College Students' Professional Identity Scale and the College Students' Learning Engagement Scale and used statistical methods such as structural equation modeling (SEM) and multiple regression to analyze the questionnaires. Results and Discussion: Examine the impact of professional identity and learning investment on teacher competency of normal college students, analyze the size of the influencing factors, measure the current competency level of normal college graduate teachers, analyze existing problems, and propose improvement strategies, thereby exploring the transformation of teacher education under the background of smart education basic logic and realistic path. Research Implications: The sample size and representativeness of this study are limited to one local undergraduate normal university. Therefore, there are still many shortcomings in this study, which need to be further deepened and improved in future research. Originality/Value: This study explores the relationship between teacher competence and digital literacy, professional identity, learning engagement, and learning efficacy among teacher trainees, and examines the mediating role of learning engagement and learning efficacy in the relationship between professional identity and learning. This is beneficial for us to gain a deeper understanding of the formation of teacher competence among teacher trainees in the context of smart education

Formation mechanism and improved remedy of thermal property of cold shut surface defects in Vortex Flow Meters: Numerical simulation and experimental verification in investment casting of 316 L stainless steel

The purpose of this study aims to investigate the leading causes of CS (Cold Shut) defects in VFM (Vortex Flow Meters) of intricate geometric configuration and propose improvement strategies to leverage the thermal property in the vicinity of thin-walled regions, such as insulation-enhanced uniformly distributed temperature via ceramic core embedment. First, penetrant testing reveals whether the defect is a penetrating-type defect. Second, several extensive material characterization techniques such as optical microscopy (OM), energy-dispersive X-ray spectroscopy (EDS) analysis, and charge-coupled device (CCD) were employed to provide deeper insights into the formation and morphology of defects. Third, numerical simulations and experimental verifications were utilized to further analyze the causes of CS defects in vortex flowmeters. Fourth, effective preventive measures were designed after identifying the causes of defects, which involved using ceramic cores to replace the shell at deep and thin-walled locations. A virtual thermo-dynamic sensor (VTDS) was used to analyze the temperature distribution in the area before and after the installation of ceramic cores. The results indicate that the temperature in the defect area increased by >40 degrees during the filling period from 2.5 s to 5 s. Additionally, adequate thermal uniformity was achieved through the high thermal conductivity of the ceramic material, thereby reducing the cooling rate and the coefficient of kinematic viscosity in that area, leading to improved fluidity of the molten iron. Ultimately, the occurrence rate of CS defects decreased from 42.6 % to 0 %.

Evaluation of the proposal for the teaching of emotional integration in the career of Medicine, for the improvement of professional pedagogical performance

The improvement strategy for the improvement of the professional pedagogical performance of teachers of the teaching of emotional integration in the subject Clinical Propaedeutics and Medical Semiology of the 3rd year of the Medicine career is directed by the mission: to achieve levels of preparation of the teacher to improve the professional pedagogical performance in the teaching of emotional integration; The vision of this strategy is to design self-improvement actions for teachers. Main objective: To assess the results obtained in the improvement of the professional pedagogical performance of teachers in the teaching of emotional integration in the subject. Method: A system of self-improvement activities was conceived that revealed and enhanced the functions, as well as allowed the system of relationships to function harmoniously, promoting the development and systematic evaluation of work. Periods were organized for exchanges, analyses, meetings and activities Scientific. After presenting the proposed overcoming strategy, the evaluation of 30 experts was requested, it is used in the processing Mc Nemar and chi-square. The evaluation of the instruments applied to the evaluation of teachers, through the consultation of specialists and the pre-experiment carried out, confirmed the viability of the proposed improvement strategy

Effect of compassion fatigue on emotional labor in female nurses: Moderating effect of self-compassion.

A two-stage survey design with a convenience sample. Participants were female nursing staff recruited from emergency departments, intensive care units, ward nursing units, and outpatient departments of medical centers, regional hospitals, and district hospitals in Taiwan. A total of 300 questionnaire copies in each of the first and second stages were distributed, and 272 pairs of responses were retrieved (valid response rate = 91%). The reliability and validity of the questionnaire were tested, and confirmatory factor analysis was conducted with AMOS 21. The proposed hypotheses were verified using hierarchical regression conducted with SPSS version 25.0. This study revealed that compassion fatigue positively predicted surface acting (β = 0.12, p < 0.05) and negatively predicted deep acting (β = -0.18, p < 0.01) and expression of genuine emotions (β = -0.31, p < 0.01). In addition, self-compassion negatively moderates the relationships between compassion fatigue and surface acting (β = -0.12, p < 0.05), and positively moderates the relationships between compassion fatigue and expression of genuine emotions (β = 0.15, p < 0.01). To avoid excessive consumption of emotional resources, nurses with high compassion fatigue may employ surface acting by engaging in emotional labor without making an effort to adjust their feelings. Nurses need also be sympathized with, and such sympathy can come from hospitals, supervisors, colleagues, and, most crucially, the nurses themselves. Hospital executives should propose improvement strategies that can prevent the compassion fatigue on nurses, such as improving nurses' self-compassion.

Current Status and Improvement Strategies for Medical Humanities Education in Medical Schools

With the increasing demand for humanistic qualities in the healthcare industry, the importance of medical humanities education in cultivating high-quality medical talents is continuously growing. Medical humanities education not only involves the study of medical knowledge but more importantly, focuses on cultivating students' compassion, ethical perspectives, communication skills, and sense of social responsibility. However, there are some challenges faced by medical schools in implementing humanities education, such as insufficient educational resources, unreasonable course settings, and a lack of effective practical teaching. In view of this, this paper aims to analyze the current status of medical humanities education and propose improvement strategies based on this analysis, in order to promote the development of medical humanities education and better meet the comprehensive quality requirements of medical talents demanded by society.

Electric Vehicle Ordered Charging Planning Based on Improved Dual-Population Genetic Moth–Flame Optimization

This work discusses the electric vehicle (EV) ordered charging planning (OCP) optimization problem. To address this issue, an improved dual-population genetic moth–flame optimization (IDPGMFO) is proposed. Specifically, to obtain an appreciative solution of EV OCP, the design for a dual-population genetic mechanism integrated into moth–flame optimization is provided. To enhance the global optimization performance, the adaptive nonlinear decreasing strategies with selection, crossover and mutation probability, as well as the weight coefficient, are also designed. Additionally, opposition-based learning (OBL) is also introduced simultaneously. The simulation results show that the proposed improvement strategies can effectively improve the global optimization performance. Obviously, more ideal optimization solution of the EV OCP optimization problem can be obtained by using IDPGMFO.

Influencing factors and improvement strategies of supply chain resilience of prefabricated construction from the perspective of dynamic capabilities: the case of China

PurposeThis study adopts the perspective of dynamic capabilities to investigate influencing factors and proposes improvement strategies of supply chain resilience of prefabricated construction.Design/methodology/approachThe structural equation model (SEM) is used to identify and verify the relationship between factors influencing supply chain resilience of prefabricated construction from the perspective of dynamic capabilities. The system dynamics (SD) model is constructed to dynamically simulate the specific effects of different influencing factors.FindingsResults indicate that: (1) An evaluation index system for supply chain resilience of prefabricated construction containing five first-level indicators and 36 second-level indicators is constructed; (2) Ability to anticipate, ability to respond, ability to adapt, ability to recover and ability to learn are positively correlated with the supply chain resilience of prefabricated construction and (3) ANT3 (information system), RES1 (quick response), ADA3 (buffer stock) and LEA4 (trust) are the most leading factors influencing supply chain resilience of prefabricated construction over time.Originality/valueThis study fulfills the need for an in-depth exploration of the various influencing factors on supply chain resilience of prefabricated construction from the perspective of dynamic capabilities. Furthermore, this study provides improvement strategies to enhance supply chain resilience of prefabricated construction in China.