A practical guideline for univariate meta-analytic structural equation modelling

Background:Meta-analysis is a quantitative approach that systematically integrates results from previous research to draw conclusions.Structural equation modelling is a statistical method that integrates factor analysis and path analysis.Meta-analytic structural equation modeling(MASEM)combines meta-analysis and structural equation modeling.It allows researchers to explain relationships among a group of variables across multiple studies.Methods:We used a simulated dataset to conduct a univariate MASEM analysis,using Comprehensive Meta Analysis 3.3,Analysis of Moment Structures 24.0 software.Results:Despite the lack of concise literature on the methodology,our study provided a practical step-by-step guide on univariate MASEM.Conclusion:Researchers can employ MASEM analysis in applicable fields based on the description,principles,and practices expressed in this study and our previous publications mentioned in this study.

Drivers of spatial structure in thinned forests

Background:As is widely known,an increasing number of forest areas were managed to preserve and enhance the health of forest ecosystems.However,previous research on forest management has often overlooked the importance of structure-based.Aims:Our objectives were to define the direction of structure-based forest management.Subsequently,we investigated the relationships between forest structure and the regeneration,growth,and mortality of trees under different thinning treatments.Ultimately,the drivers of forest structural change were explored.Methods:On the basis of 92 sites selected from northeastern China,with different recovery time (from 1 to 15years) and different thinning intensities (0–59.9%) since the last thinning.Principal component analysis (PCA)identified relationships among factors determining forest spatial structure.The structural equation model (SEM)was used to analyze the driving factors behind the changes in forest spatial structure after thinning.Results:Light thinning (0–20%trees removed) promoted forest regeneration,and heavy thinning (over 35% of trees removed) facilitated forest growth.However,only moderate thinning (20%–35%trees removed) created a reasonable spatial structure.While dead trees were clustered,and they were hardly affected by thinning intensity.Additionally,thinning intensity,recovery time,and altitude indirectly improve the spatial structure of the forest by influencing diameter at breast height (DBH) and canopy area.Conclusion:Creating larger DBH and canopy area through thinning will promote the formation of complex forest structures,which cultivates healthy and stable forests.

Measurement Research Based on Bayesian Structural Equation Cognitive Model

The Bayesian structural equation model integrates the principles of Bayesian statistics, providing a more flexible and comprehensive modeling framework. In exploring complex relationships between variables, handling uncertainty, and dealing with missing data, the Bayesian structural equation model demonstrates unique advantages. Therefore, Bayesian methods are used in this paper to establish a structural equation model of innovative talent cognition, with the measurement of college students’ cognition of innovative talent being studied. An in-depth analysis is conducted on the effects of innovative self-efficacy, social resources, innovative personality traits, and school education, aiming to explore the factors influencing college students’ innovative talent. The results indicate that innovative self-efficacy plays a key role in perception, social resources are significantly positively correlated with the perception of innovative talents, innovative personality tendencies and school education are positively correlated with the perception of innovative talents, but the impact is not significant.

A Survey Study on TPACK Framework for Normal Students of English Major in Ethnic Colleges and Universities:Empirical Analysis Based on Structural Equation Modeling

With the continuous advancement of education informatization,Technological Pedagogical Content Knowledge(TPACK),as a new theoretical framework,provides a novel method for measuring teachers’informatization teaching ability.This study takes normal students of English majors from three ethnic universities as the research object,collects relevant data through questionnaires,and uses structural equation modeling to conduct data analysis and empirical research to investigate the differences in the TPACK levels of these students at different grades and the structural relationships among the elements in the TPACK structure.The technological pedagogical knowledge element of the TPACK structure was not obtained by exploratory factors analysis but through path analysis and structural equation modeling,the results show that the one-dimensional core knowledge of technological knowledge(TK),content knowledge(CK),and pedagogical knowledge(PK)have a positive effect on the two-dimensional interaction knowledge of technological content knowledge(TCK)and pedagogical content knowledge(PCK);furthermore,TCK and PCK have a positive effect on TPACK;and TK,CK,and PK indirectly affect TPACK through TCK and PCK.On this basis,suggestions are provided to ethnic colleges and universities to develop the TPACK knowledge competence of normal students of English majors.

Using Residual Estimators to Detect Outliers and Potential Controlling Observations in Structural Equation Modelling: QQ Plot Approach

The structural equation model (SEM) concept is generally influenced by the presence of outliers and controlling variables. To a very large extent, this could have consequential effects on the parameters and the model fitness. Though previous researches have studied outliers and controlling observations from various perspectives including the use of box plots, normal probability plots, among others, the use of uniform horizontal QQ plot is yet to be explored. This study is, therefore, aimed at applying uniform QQ plots to identifying outliers and possible controlling observations in SEM. The results showed that all the three methods of estimators manifest the ability to identify outliers and possible controlling observations in SEM. It was noted that the Anderson-Rubin estimator of QQ plot showed a more efficient or visual display of spotting outliers and possible controlling observations as compared to the other methods of estimators. Therefore, this paper provides an efficient way identifying outliers as it fragments the data set.

Customer Satisfaction and Hotel Brand Equity： A Structural Equation Modelling Study

In this paper, a structural equation modelling technique was used to examine the effect of brand equity on customer satisfaction in the Egyptian hotel industry. Brand equity was separated into four constructs （brand loyalty, perceived quality, brand awareness and brand associations）, and each one was examined individually. A sample of hotel guests, who accommodated at four- and five-star branded hotels, in four tourism destinations in Egypt, was selected. A structured questionnaire that included established scales was then used to measure brand loyalty, perceived quality, brand awareness, brand associations and customer satisfaction. Data were collected from 280 usable questionnaires answered by hotel guests, and the relationships among the four variables of brand equity and customer satisfaction were examined using correlation analysis and structural equation modelling. The study found that brand loyalty, brand awareness and brand associations all had a significant positive effect on customer satisfaction. Perceived quality, however, did not have any effect. These findings suggest that customer satisfaction is a reasonable measure for the success of branding activities, and that branding managers should focus on brand loyalty, awareness and associations to raise their customers＇ satisfaction.

Application of Structural Equation Modelling in Construction Management Research

This paper, based on Deming＇s quality management （QM） theory embodied in ISO 9001, uses structural equation modelling （SEM） in a construction management research. Based on 100 usable responses collected from a nationwide survey carried out from 14th February to 30th May 2008 on all key players in the Malaysian construction value chain, this paper aims to： （a） validate the dimensions of registration efforts to obtain and maintain ISO 9001 certifications; （b） validate the eight QM principles in ISO 9001 for quality management system （QMS） practices; （c） determine the components of organisational improvements experienced as a result of ISO 9001 certifications in terms of company competitiveness, customer satisfaction, and business performance; and （d） investigate the causal relationships among registration efforts, QMS practices, company competitiveness, customer satisfaction, business performance of ISO 9001-certified companies. The knowledge gained from the application of SEM is an important contribution to the body of theoretical literature in QM.

Assessment of Relationship of Some Causal Factors Associated with Productivity of Longwall Mining Using Structured Equation Modeling

Enhancement of productivity optimization is steadily gaining the priority in mining companies especially in the underground coal mining industry which faces a daunting task to balance marginal profit generation with a comparatively high cost of production, volatile market price and rapid grade variation. This paper is aimed to analyze some of the causal factors both technical and site specific which are directly or indirectly impacting the productivity of the longwall coal mining system such as downtime of equipment system in longwall panel, overloading of conveyors and bin, preventive maintenance, gas management practices and injury severity rate. Structured Equation Modelling (SEM) was used to study the causal relationships between the above-mentioned factors and mine productivity. The equipment considered for analysis included shearer, armored face conveyor, crusher, bridge stage loader, chock supports, main gate drive, gate conveyor, hydraulic pumps and crusher. SEM was applied to relate the correlations existing among these causal variables in order to assess their direct or indirect impact on mining productivity. Based on the data extracted over a period of 10 months which included the extraction of 2 longwall panels, the study revealed a significant negative causal relationship between injury severity rate (p < 0.01) and equipment downtime (p = 0.001), with mine productivity. However, preventive maintenance delay time, gas management delay time and conveyor overloading delay time were found to have an insignificant direct influence on mine productivity but indirectly modify it through a significant mediator relationship with equipment downtime. This information would assist mine management to take proper preventive measures.

Mechanisms Influencing Learning Gains Under Information Security: Structural Equation Modeling with Mediating Effect

With the expanding enrollments in higher education,the quality of col-lege education and the learning gains of students have attracted much attention.It is important to study the influencing factors and mechanisms of individual stu-dents’acquisition of learning gains to improve the quality of talent cultivation in colleges.However,in the context of information security,the original data of learning situation surveys in various universities involve the security of educa-tional evaluation data and daily privacy of teachers and students.To protect the original data,data feature mining and correlation analyses were performed at the model level.This study selected 12,181 pieces of data from X University,which participated in the Chinese College Student Survey(CCSS)from 2018 to 2021.A confirmatory factor analysis was conducted and a structural equation modeling was conducted using AMOS 24.0.Through hypothesis testing,this study explored the mechanisms that influence learning gains from the per-spectives of student involvement,teacher involvement,and school support.The results indicated that the quality of student involvement has an important mediat-ing effect on learning gains and that a supportive campus environment has the greatest influence on learning gains.Establishing positive emotional communica-tions between teachers and students is a more direct and effective method than improving the teaching level to improve the quality of student involvement.This study discusses the implications of these results on the research and practice of connotative development in higher education.

How Users Perceive Infrastructure Development Affects Their Transport Mode Choice

Transport infrastructure development and perception vary across and within countries, influencing mode choice among road users. This study explores how road users perceive the development of infrastructure modes, service attributes, embedded safety levels, and commuting modes. Additionally, the research examines whether participants’ environmental backgrounds impact their mode choice patterns. The study gathered responses from 1169 participants residing in two regions of Amman, Jordan, each with distinct infrastructure development and population densities. Participants completed a standardized questionnaire, and several statistical techniques were employed for analysis. The findings revealed that facilities’ infrastructure attributes, development, and safety were assessed using three indices. Both participant groups perceived these indices differently on average. Residents of low population density areas with relatively developed infrastructure showed more consistent assessments, irrespective of their most frequently used mode of transportation, tending towards lower scores. Interestingly, subjective ratings of infrastructure development were higher (4.96) than attribute-based ratings (4.32). Despite their generally low-quality perception, public transportation services received the highest appraisal (4.9). Conversely, pedestrian infrastructure complementing public transport received the lowest assessment (4.57), only slightly higher than street environments (4.59). The study found weak associations between subjective service characteristics ratings. Traveler and trip characteristics influenced mode choice and trips more than infrastructure perception. In conclusion, the study suggests that policies should be developed to encourage green transportation, ensure social equality and safety. In addition, the study contributes to understanding perceptions about transport infrastructure, modes of transportation, and the factors that influence sustainable and equitable transportation systems.

Effects of landscape fragmentation of plantation forests on carbon storage in the Loess Plateau,China

Tree plantation and forest restoration are the major strategies for enhancing terrestrial carbon sequestration and mitigating climate change.The Grain for Green Project in China has positively impacted global carbon sequestration and the trend towards fragmentation of plantation forests.Limited studies have been conducted on changes in plantation biomass and stand structure caused by fragmentation,and the effect of fragmentation on the carbon storage of plantation forests remains unclear.This study evaluated the differences between carbon storage and stand structure in black locust forests in fragmented and continuous landscape in the Ansai District,China and discussed the effects of ecological significance of four landscape indices on carbon storage and tree density.We used structural equation modelling to explore the direct and indirect effects of fragmentation,edge,abiotic factors,and stand structure on above-ground carbon storage.Diameter at breast height(DBH)in fragmented forests was 53.3%thicker,tree density was 40.9%lower,and carbon storage was 49.8%higher than those in continuous forests;for all given DBH>10 cm,the trees in fragmented forests were shorter than those in continuous forests.The patch area had a negative impact on carbon storage,i.e.,the higher the degree of fragmentation,the lower the density of the tree;and fragmentation and distance to edge(DTE)directly increased canopy coverage.However,canopy coverage directly decreased carbon storage,and fragmentation directly increased carbon storage and tree density.In non-commercial forests,fragmentation reduces the carbon storage potential of plantation,and the influence of patch area,edge,and patchy connection on plantation should be considered when follow-up trees are planted and for the plantation management.Thus,expanding the area of plantation patches,repairing the edges of complex-shaped patches,enhancing the connectivity of similar patches,and applying nutrients to plantation forests at regular intervals are recommended in fragmented areas of the Loess Plateau.

How Does Urban Shrinkage Affect Land Use Efficiency?A Case Study of Shrinking Cities in Northeast China

The effect of urban shrinkage has gradually become a new topic.Theoretically,urban shrinkage may exert great influence on land use efficiency(LUE)through various urban subsystems,but there is currently limited research examining these pathways.Using the Super-SBM-Undesirable model and the Structural Equation Model(SEM),this study calculates the LUE of shrinking cities in Northeast China and simulates the process of urban shrinkage affecting LUE.To quantify the process of urban shrinkage affecting LUE,three mediation variables,namely the economy,public services,and innovation,are used as latent variables to apply SEM.The results show that urban shrinkage will affect LUE through a direct path and indirect paths.In the direct path,urban shrinkage leads to an improvement in LUE.In the indirect paths,the economy and innovation will transmit the negative effect of urban shrinkage on LUE,while public services will reverse this effect.An important contribution of this study is that it quantifies the paths of urban shrinkage affecting LUE,thereby expanding the understanding of urban shrinkage effect and laying a foundation for the sustainable development of shrinking cities.

What are the underlying causes and dynamics of land use conflicts in metropolitan junction areas?A case study of the central Chengdu–Chongqing region in China

Land use conflicts(LUCs),as a spatial manifestation of the conflicts in the human-land relationships,have a profound impact on regional sustainable development.For China’s metropolitan junction areas(MJAs),the existence of“administrative district economies”has made the issue of LUCs more prominent.Based on a case study of the central Chengdu–Chongqing region,we conducted an exploratory spatial data analysis of the evolutionary process of regional LUCs.Furthermore,structural equation modeling was utilized to analyze the dynamic mechanism of LUCs in MJAs,with a particular emphasis on exploring the influences of administrative boundary.The results showed that from 2010 to 2020,LUCs in the central Chengdu–Chongqing region continued to worsen,and the spatial process conflict and spatial structure conflict indices increased by more than 30.0%.The intensification of LUCs in the central Chengdu–Chongqing region from 2010 to 2020 was mainly the result of the deterioration of conflicts in evaluation units with low conflict levels.LUCs in China’s metropolitan areas generally presented a circular gradient distribution,weakening from the core to the periphery,but there were some strong isolated conflict zones in the outer regions.LUCs in China’s MJAs were the result of interactions among multiple factors,e.g.,natural environment,socio-economic development,policy and institutional processes,and administrative boundary effects.Administrative boundary affected the flow of socio-economic elements,changing the supply-and-demand competition of stakeholders for land resources,consequently exerting an indirect influence on LUCs.This study advances the theory of the dynamic mechanism of LUCs,and provides theoretical support for the governance of these conflicts in transboundary areas.

Characteristics and drivers of the soil multifunctionality under different land use and land cover types in the drylands of China

The drylands of China cover approximately 6.6×106 km2 and are home to approximately 5.8×10^(8)people,providing important ecosystem services for human survival and development.However,dryland ecosystems are extremely fragile and sensitive to external environmental changes.Land use and land cover(LULC)changes significantly impact soil structure and function,thus affecting the soil multifunctionality(SMF).However,the effect of LULC changes on the SMF in the drylands of China has rarely been reported.In this study,we investigated the characteristics of the SMF changes based on soil data in the 1980s from the National Tibetan Plateau Data Center.We explored the drivers of the SMF changes under different LULC types(including forest,grassland,shrubland,and desert)and used structural equation modeling to explore the main driver of the SMF changes.The results showed that the SMF under the four LULC types decreased in the following descending order:forest,grassland,shrubland,and desert.The main driver of the SMF changes under different LULC types was mean annual temperature(MAT).In addition to MAT,pH in forest,soil moisture(SM)and soil biodiversity index in grassland,SM in shrubland,and aridity index in desert are crucial factors for the SMF changes.Therefore,the SMF in the drylands of China is regulated mainly by MAT and pH,and comprehensive assessments of the SMF in drylands need to be performed regarding LULC changes.The results are beneficial for evaluating the SMF among different LULC types and predicting the SMF under global climate change.

A Study on the Role of Tourism in Enhancing Personal Mental Health in the Post-Epidemic Era

With the advent of the post-epidemic era,a great wave of tourism has been ushered in everywhere.The relationship between tourism and mental health has become a hot topic in society.This paper investigates the enhancement of people’s mental health after tourism through social survey.Using Hangzhou as the sample collection site,this paper conducted a study on the role of tourism in enhancing personal mental health through descriptive analysis,factor analysis and structural equation modeling,and further specifically analyzed the role of mediating variables.The results showed that:(1)The purpose of tourism is to relax and relieve stress,and the effectiveness of tourism is mainly reflected in the alleviation of emotional conditions;(2)Factor Analysis reduced the dimensionality of personal mental health indicators,and finally obtained four factors,among which the comprehensive behavioral ability and physiological manifestation had the best improvement effect after tourism;(3)The structural equation model shows that the enhancing effect of tourism on mental health originates from the factor of inner psychological characteristic,and this factor works through two paths:Inner Psychological Characteristic-Social Adaptability-Physiological Manifestations-Enhancement of Mental Health by Tourism,and Inner Psychological Characteristic-Comprehensive Behavioral Ability-Enhancement of Mental Health by Tourism;(4)Tourism has an enhancing effect on personal mental health,and the enhancing effect is most significant among the middle-aged and young people who are unmarried and do not have children yet.These results have been reasonably analyzed and explained,and relevant suggestions are put forward.

Change in self-image pressure level before and after autologous fat breast augmentation and its effect on social adaptability

BACKGROUND There is an increasingly strong demand for appearance and physical beauty in social life,marriage,and other aspects with the development of society and the improvement of material living standards.An increasing number of people have improved their appearance and physical shape through aesthetic plastic surgery.The female breast plays a significant role in physical beauty,and droopy or atrophied breasts can frequently lead to psychological inferiority and lack of confidence in women.This,in turn,can affect their mental health and quality of life.AIM To analyze preoperative and postoperative self-image pressure-level changes of autologous fat breast augmentation patients and their impact on social adaptability.METHODS We selected 160 patients who underwent autologous fat breast augmentation at the First Affiliated Hospital of Xinxiang Medical University from January 2020 to December 2022 using random sampling method.The general information,selfimage pressure level,and social adaptability of the patients were investigated using a basic information survey,body image self-assessment scale,and social adaptability scale.The self-image pressure-level changes and their effects on the social adaptability of patients before and after autologous fat breast augmentation were analyzed.RESULTS We collected 142 valid questionnaires.The single-factor analysis results showed no statistically significant difference in the self-image pressure level and social adaptability score of patients with different ages,marital status,and monthly income.However,there were significant differences in social adaptability among patients with different education levels and employment statuses.The correlation analysis results revealed a significant correlation between the self-image pressure level and social adaptability score before and after surgery.Multiple factors analysis results showed that the degree of concern caused by appearance in selfimage pressure,the degree of possible behavioral intervention,the related distress caused by body image,and the influence of body image on social life influenced the social adaptability of autologous fat breast augmentation patients.CONCLUSION The self-image pressure on autologous fat breast augmentation patients is inversely proportional to their social adaptability.

Trust beyond Technology Algorithms: A Theoretical Exploration of Consumer Trust and Behavior in Technological Consumption and AI Projects

In an era dominated by artificial intelligence (AI), establishing customer confidence is crucial for the integration and acceptance of AI technologies. This interdisciplinary study examines factors influencing customer trust in AI systems through a mixed-methods approach, blending quantitative analysis with qualitative insights to create a comprehensive conceptual framework. Quantitatively, the study analyzes responses from 1248 participants using structural equation modeling (SEM), exploring interactions between technological factors like perceived usefulness and transparency, psychological factors including perceived risk and domain expertise, and organizational factors such as leadership support and ethical accountability. The results confirm the model, showing significant impacts of these factors on consumer trust and AI adoption attitudes. Qualitatively, the study includes 35 semi-structured interviews and five case studies, providing deeper insight into the dynamics shaping trust. Key themes identified include the necessity of explainability, domain competence, corporate culture, and stakeholder engagement in fostering trust. The qualitative findings complement the quantitative data, highlighting the complex interplay between technology capabilities, human perceptions, and organizational practices in establishing trust in AI. By integrating these findings, the study proposes a novel conceptual model that elucidates how various elements collectively influence consumer trust in AI. This model not only advances theoretical understanding but also offers practical implications for businesses and policymakers. The research contributes to the discourse on trust creation and decision-making in technology, emphasizing the need for interdisciplinary efforts to address societal challenges associated with technological advancements. It lays the groundwork for future research, including longitudinal, cross-cultural, and industry-specific studies, to further explore consumer trust in AI.

Analysis of Commuting Modal Shift in Consideration of Social Interaction of Consciousness for Environment

It is the matter for achievement of the low carbon transport system that the excessive use of private vehicles can be controlled appropriately.Not only improvement of service level of modes except private vehicle,but also consciousness for environmental problem of individual trip maker is important for eco-commuting promotion.On the other hand,consciousness for environment would be changed by influence of other person.Accordingly,it is aimed in the study that the structure of decision-making process for modal shift to the eco-commuting mode in the local city is described considering environmental consciousness and social interaction.For the purpose,the consciousness for the environment problem and the travel behavior of the commuter at the suburban area in the local city are investigated by the questionnaire survey.The covariance structure about the eco-consciousness is analyzed with the database of the questionnaire survey by structural equation modeling.As the result,it can be confirmed with the structural equation model that the individual environmental consciousness is strongly related with the intention of self-sacrifice and is influenced with the local interaction of the individual connections.On the other hand,the intention of modal shift for the commuting mode is analyzed with the database of the questionnaire survey.It can be found out that the environmental consciousness is not statistically significant for commuting mode choice with the present poor level of service of public transport.However,the intention of self-sacrifice for the prevention of the global warming is statistically confirmed as the factor of modal shift with the operation of eco-commuting bus service with the RP/SP integrated estimation method.As the result,the multi-agent simulation system with social interaction model for eco consciousness is developed to measure the effect of the eco-commuting promotion.For the purpose,the carbon dioxide emission is estimated based on traffic demand and road network condition in the traffic environment model.On the other hand,the relation between agents is defined based on the small world network.The proposed multi-agent simulation is applied to measure the effect of the eco-commuting promotion such as improvement of level of service on the public transport or education of eco-consciousness.The effect of the promotion plan can be observed with the proposed multi-agent system.Finally,it can be concluded that the proposed multi-agent simulation with social interaction for eco-consciousness is useful for planning of eco-commuting promotion.

Research on the Interactive Impact of Transportation Systems on Socio-Economic Development

This paper aims to explore the interactive impact between transportation systems and socio-economic development,employing Structural Equation Modeling(SEM)to analyze data from 31 provincial-level administrative regions in China from 2013 to 2022.It comprehensively considers key indicators from the economic,social,and transportation sectors.The paper constructs a model encompassing 5 latent variables and 15 observed variables.Through in-depth analysis,it reveals the promoting role of transportation systems on economic growth and social development,as well as the demand for transportation system construction and optimization driven by socio-economic development levels.The results indicate that an efficient transportation system can not only directly drive economic growth but also indirectly promote social development by improving social welfare and enhancing quality of life.This paper provides new insights into understanding the complex relationship between transportation systems and socio-economic development and holds significant implications for policymakers in optimizing transportation infrastructure to foster economic and social development.

Coupling Relationship Analysis on Households′ Production Behaviors and Their Influencing Factors in Nature Reserves:A Structural Equation Model

A households′production behavior directly influences the quality of the environment and determines the successful development of nature reserves.Meanwhile,the households′production behaviors are complicated by interrelated factors,such as protection attitudes,resource endowment,and family wealth.This research evaluated households near the Crested Ibis National Nature Reserve in Shaanxi Province,acquiring data from 436 households around Yang County and Ningshan County in the south slope of Qinling Mountains,China.Based on the collected data,we developed a structural equation model to evaluate the coupling relationships among households′ protection attitudes,production behaviors,resource endowment,and family wealth.The results showed that:1) households with great resource endowment had more negative attitudes,probably due to their greater protection costs;2) the households with higher education levels had worse protection attitudes;3) the households with more family wealth were likely to use fewer fertilizers,pesticides,and firewood;4) the households with more resource endowment showed less production and management behaviors;5) the enhancement of households' attitudes improved production behaviors to protection the environment,but the effects were not statistically significant.Our results provide a basis for the government's protection policy making,exploring the effective management measures that are beneficial for both nature reserve management and community development.