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 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.

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.

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.

A Structural Equation Model (SEM) for Pharmacist Competencies in Improving Quality of Life of Cancer Patients: Effect of Missing Values on the SEM

Objective: With the goal of improving health-related quality of life (HRQOL) in cancer patients, we previously reported a structural equation model (SEM) of subjected QOL and qualifications of pharmacists, based on a series of questionnaires completed by patients and pharmacists. However, several patients and pharmacists were excluded from the previous study because it was not always possible to obtain all the data intended for collection. In order to reveal the effect of missing data on the SEM, we established SEMs of HRQOL and the competency of pharmacists, using correlation matrices derived by two different statistical methods for handling missing data. Method: Fifteen cancer patients hospitalized for cancer and were receiving opioid analgesics for pain control, and eight pharmacists were enrolled in this study. Each subject was asked four times weekly to answer questions presented in a questionnaire. SEMs were explored using two correlation matrices derived with pair-wise deletion (PD matrix) and list-wise deletion (LD matrix). The final models were statistically evaluated with certain goodness-of-fit criteria. Results: Data were intended to be collected four times weekly for each patient, but there were some missing values. The same SEMs for HRQOL were optimized using both the LD and PD matrices. Although the path diagrams of the SEMs were not identical in the “competency of pharmacists,” the two models suggested that a higher competency of a pharmacist lowered the “severity” of condition and increased the “comfort” of patients, resulting in an increase in the subjected QOL. Conclusion: In collecting data for clinical research, missing values are unavoidable. When the structure of the model was robust enough, the missing data had a minor effect on our SEM of QOL. In QOL research, the LD matrix as well as the PD matrix would be effective, provided the model is sufficiently robust.

数字普惠金融赋能县域产业结构转型升级的动力机制——基于PLS-SEM模型分析

基于偏最小二乘法结构方程模型(PLS-SEM),运用河南省县域2014—2020年平衡面板数据研究数字普惠金融驱动河南省县域产业转型升级的机制与实证效果,结果表明:数字普惠金融能够推动河南省县域产业结构的转型升级;数字普惠金融主要通过经济发展、生态环境、社会共享三个方面共同推动河南省县域产业结构转型升级;从发展潜力方面看,数字普惠金融对产业结构升级有一定负相关性,可能的原因是河南省县域数字平台不够完善、数字信息技术落后,且大多以轻工业、农业为主,导致数字普惠金融的正向融入性存在延迟。必须持续推动数字普惠金融的产业融入性、夯实数字普惠金融服务实体经济的功能性,提高河南省县域产业经济韧性。

多维驱动因素联动效应对企业数字化创新的影响——基于SEM与fsQCA的实证分析

随着云计算、大数据、人工智能等数字科技蓬勃发展,数字化创新深刻影响着企业创新与运营模式。利用结构方程模型(SEM)与模糊集定性比较分析方法(fsQCA)分析技术不确定性、市场不确定性、企业家精神、组织学习、组织忘记对企业数字化创新的影响。结果发现:技术不确定性、市场不确定性、企业家精神、组织学习、组织忘记和数字化创新6个要素存在因果线性关系,并发现学习主导型、市场驱动学习型和市场主导型3条数字化创新路径,以及3条非高数字化创新路径。其中,市场驱动学习型最有可能激发数字化创新。结合结构方程模型(SEM)分析结果,比较上述6条路径发现,数字化创新的影响因素具有非对称性,3条非高数字化创新路径并不是3条高数字化创新路径的对立面。

基于Meta-SEM的建筑工人安全行为影响机制研究

为梳理建筑工人安全行为的前因变量并分析其影响机制,基于从众动机和计划行为理论,构建了建筑工人安全行为影响机制理论模型,运用元分析-结构方程模型(Meta-Structural Equation Modeling,Meta-SEM)法对国内外64项实证研究中的128个独立样本进行系统分析,以明确各前因变量与建筑工人安全行为的相互作用关系并探讨企业规模的调节作用。结果表明:在个体层面,安全意识、安全态度、安全动机与建筑工人安全行为的相关系数分别为0.663、0.513、0.509;在组织管理层面,安全氛围与建筑工人安全行为的相关系数为0.678;安全意识、安全态度、安全动机是安全氛围与建筑工人安全行为之间的中介变量;企业规模对安全意识、安全动机、安全氛围与建筑工人安全行为的关系间存在显著调节作用,其中,中小型企业的影响更显著。研究结论可为后续建筑工人安全行为研究提供一定的理论基础,也为建筑业管理者提供了管理依据。

基于SEM的煤矿工人易发不安全行为控制研究

为了准确识别煤矿工人易发不安全行为,预防由此导致的煤矿事故,文章首先构建了由作业过程、工艺设备、环境限制和作业决策4个一级指标和操作错误等18个二级指标构成的煤矿工人不安全行为评价指标体系。其次,将结构方程模型(SEM)运用到了煤矿工人易发不安全行为控制研究中。研究结果表明:作业过程等4个一级指标(潜在变量)均对煤矿工人不安全行为的发生具有显著影响;18个二级指标(观测变量)中,有无视警示进入危险区域等14种煤矿工人易发不安全行为,且根据路径系数得到了其易发程度。最后,提出了控制煤矿工人易发不安全行为的对策。文章为煤矿工人不安全行为研究提供了一种方法。

基于SEM的沙漠公路路基工程施工风险研究

在沙漠地区进行公路建设对完善交通网络节点、发展偏远地区经济具有重要意义。为有效探究沙漠公路路基工程施工风险,该文从人员风险、技术风险、材料风险、机械风险和环境风险5个方面出发,通过文献研究法筛选出影响沙漠公路路基工程施工风险的23项指标;基于问卷调查收集到的有效数据,构建沙漠公路路基工程施工风险的结构方程模型(Structural Equation Modeling,简称SEM);分析施工风险关键影响因素。结果表明:沙漠公路路基工程施工风险受恶劣气候、人员三违行为、风积沙质量、机械维修与保养、技术交底完整性的影响较大。提出具有针对性的控制措施,可为沙漠公路可持续发展提供参考。

基于SEM模型的张家苗寨古村落导视系统设计研究

目的改善村寨导视系统的用户体验,探寻用户评价导视系统满意度的标准体系,提供客观、以用户为导向的设计流程。方法使用文本挖掘技术对用户评价原始数据进行采集,使用探索性因子分析法对结果进行降维分析,通过主成分分析法提取5个成分,将其设置为潜在变量,并将相关指标作为观测变量,再使用结构方程模型构建潜在变量与观测变量之间的层次结构,并对其结果进行拟合度分析,最后将结果用于导视系统设计实践。结果根据结构模型结果,分析潜在变量和观测变量的影响权重,得出并验证了“明确的指向性”是影响用户满意度最重要的指标,其次分别为“民族造型美感”“文化功能性”“场景交互合理”,并通过具体的观测变量因子载荷数值排序来指导设计实践。结论导视系统在实现指向性功能的情况下,还应提升民族文化附加值,通过文化符号来扩大民族影响力,传承民族文化,促进民族村寨的发展。

家庭农场创业资源整合驱动因素与作用机理研究——基于扎根理论和SEM模型的融合方法

我国现有家庭农场尚处于起步阶段,因受自身弱质性、创业资源匮乏、创业环境复杂性等因素制约而面临着巨大挑战。文章基于相关文献将家庭农场创业资源整合过程界定为识别、获取、配置和运用,使用扎根理论方法分析30个家庭农场资源整合案例,形成创业资源、内在需求、整合意愿、农场主个性特征、创业环境和家庭农场创业资源整合6个维度理论构想,建立驱动因素模型。依据分析结果,借鉴相关测量量表开发创业资源整合驱动因素量表,验证量表信效度并利用结构方程模型对建构的理论模型进行实证检验。结果表明,创业资源和整合意愿直接驱动家庭农场进行创业资源整合,内在需求经由整合意愿驱动家庭农场进行创业资源整合,农场主个性特征和创业环境在内在需求与整合意愿关系中起调节作用。通过拓宽创业资源整合的研究外延,丰富家庭农场创业问题的理论与方法体系,为家庭农场破解资源约束困境提供了新思路。

声誉对互联网医院使用意愿影响的多元路径分析——基于SEM和fsQCA的实证分析

目的:探究声誉对互联网医院使用意愿的影响,对优化互联网医院服务供给模式,提高患者就医体验,促进医院高质量发展都具有重要意义。方法:基于信息-解释-响应(I-I-R)理论构建声誉对互联网医院使用意愿影响框架模型,采用结构方程模型(SEM)和模糊集定性比较分析法(fsQCA)对互联网医院的使用意愿和组态路径进行实证分析。结果:医院社会责任、医院实力和医生声誉正向影响评估性态度,路径系数由强到弱依次为0.360、0.301和0.260;医院实力和医院社会责任正向影响情感性态度,路径系数分别为0.449和0.272;评估性态度和情感性态度正向影响使用意愿,路径系数分别为0.519和0.386。且以医院社会责任型和医生声誉+医院实力型为核心条件可构成两种模式下的六条有效路径。结论:医生声誉、医院实力和医院社会责任对提高互联网医院使用意愿最有效。医院应构建专业度高的医疗服务平台,提高知名度;应定期开展学习和培训,更新医疗设备,保持信息公开透明,积极承担社会责任,提高医院实力;医生应改善服务态度,提高线上互动性。

基于SEM和神经网络的移动社交电商用户隐私信息披露意愿研究

在移动社交电商情境中,用户的交互方式发生改变,个人隐私信息安全问题凸显,上述变化将会对用户的隐私信息披露意愿产生重要影响。为了探究移动社交电商用户隐私信息披露意愿的影响因素,本文基于S-O-R理论建立结构方程模型,旨在探究影响用户隐私信息披露意愿的影响因素及其作用机理。结果表明隐私政策有效性、隐私设置有效性、信息交互、情感交互等因素均正向显著影响用户隐私信息披露意愿。在此基础上,基于平台特征和用户感知收益构建了GA-BP神经网络预测模型,并针对不同预测结果提出具体应对措施。最终,文章从隐私信息安全保障和平台个性化服务等方面提出促进移动社交电商平台可持续发展的建议。

基于SEM-AHP方法的核电厂定量人为因素评价研究

文章基于人为因素分析与分类系统,分析了115起核电厂执照运行事件报告(Licensed Operation Event Report,LOER),并对影响核电厂事件发生的人为因素进行分类,采用结构方程模型方法得出各影响因素的路径系数,两两比较得到层次分析模型的判断矩阵,进而确定各因素的权重。同时对核电厂人为因素的重要性做排序分析,找到核电厂运行过程中的安全管理薄弱环节,从而促进核电厂系统平稳运行。

基于SEM模型的强化激励对不安全行为影响研究

煤矿员工的不安全行为是导致煤矿安全事故发生的重要原因,为规范矿工的不安全行为,防止煤矿安全事故的发生,本文基于激励理论中的强化理论,以不安全行为意向作为中介调节变量,探讨正向激励与负向激励对不安全行为意向及不安全行为的影响,设计调查问卷,对山西某煤矿一线员工收集数据进行实证研究,构建正向激励、负向激励、不安全行为意向与不安全行为的结构方程模型(SEM)。研究结果表明:精神奖励、精神惩罚显著负向影响不安全行为意向,羞愧惩罚显著负向影响不安全行为,不安全行为意向显著正向影响不安全行为。

牧户的草原生态补偿政策满意度与支持度——基于CSI框架和SEM的检验

从生计和生态双重维度探究牧户的草原生态补偿政策满意度与支持度,对于深化草原生态补偿制度改革,促进草原生态文明建设和牧区绿色发展,具有重要的理论与现实意义。基于马克思“生态经济人”预设的微观视角,以费耐尔满意度逻辑模型(CSI)为理论框架,使用2020年若尔盖草原574个牧户调研数据,通过反映性指标的结构方程模型(SEM),对牧户草原生态补偿政策满意度和支持度的因果机制进行了多变量、多路径的验证性分析。结果表明:(1)牧户对生计收入和生态质量越重视、“生态经济人”理性越高,其政策满意度就越高,生态保护的心理主动性也越大,相对效应大小=0.271。(2)牧户对政策实施结果的质量评价,是牧户政策满意度和支持度的主要影响因素,相对效应大小=0.518。(3)牧户对政策实施效果的价值感知,将会直接提升其政策满意度,并进一步促进其生态保护理性,相对效应大小=0.312。因此,提高牧户对草原生态补偿政策的满意度与支持度,应重点从三个维度综合施策:首先,应重视发展草原生态文化,培育牧户生态经济理性。其次,要稳步提升生态补偿标准,加强草原保护的工作力量,提升政策实施结果的质量。最后,草原生态补偿要重点加强与牧户生计绿色发展的协同,提升政策实施效果的价值。

小样本下岭PLS-SEM与岭CB-SEM的比较

目前主要有两种结构方程模型(SEM):CB-SEM和PLS-SEM。当样本量较小时,CB-SEM常常会出现不收敛的情况,使用岭方法可以改善这个问题。文章主要研究将岭方法运用到PLS-SEM中,对比岭方法下PLS-SEM与CB-SEM的表现。研究表明,岭CB-SEM和岭PLS-SEM估计量总体上比常规的CB-SEM和PLS-SEM估计量更精确,但偏差没有明显改善;当样本量较小时,PLS-SEM、岭PLS-SEM估计的精确性都优于CB-SEM、岭CB-SEM;对于受到中介变量影响的内生潜变量来说,岭PLS-SEM在估计其他潜变量对它的影响(路径系数)时最精确。

Investigation of the role of personal factors on work injury in underground mines using structural equation modeling

Work injuries in mines are complex and generally characterized by several factors starting from personal to technical and technical to social characteristics.In this paper,investigation was made through the application of structural equation modeling to study the nature of relationships between the influencing/associating personal factors and work injury and their sequential relationships leading towards work injury occurrences in underground coal mines.Six variables namely,rebelliousness,negative affectivity,job boredom,job dissatisfaction and work injury were considered in this study.Instruments were developed to quantify them through a questionnaire survey.Underground mine workers were randomly selected for the survey.Responses from 300 participants were used for the analysis.The structural model of LISREL was used to estimate the interrelationships amongst the variables.The case study results show that negative affectivity and job boredom induce more job dissatisfaction to the workers whereas risk taking attitude of the individual is positively influenced by job dissatisfaction as well as by rebelliousness characteristics of the individual.Finally,risk taking and job dissatisfaction are having positive significant direct relationship with work injury.The findings of this study clearly reveal that rebelliousness,negative affectivity and job boredom are the three key personal factors influencing work related injuries in mines that need to be addressed properly through effective safety programs.

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.