scholarly journals Key factors influencing earthquake-induced liquefaction and their direct and mediation effects

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0246387
Author(s):  
Jilei Hu ◽  
Yunzhi Tan ◽  
Wenjun Zou
Keyword(s):  
Predictive Performance ◽  
Path Model ◽  
Multiple Mediation ◽  
Key Factors ◽  
Earthquake Parameters ◽  
Maximum Information ◽  
Mediation Effects ◽  
Capping Layer ◽  
Deposit Type ◽  
Causal Path

Many factors impact earthquake-induced liquefaction, and there are complex interactions between them. Therefore, rationally identifying the key factors and clarifying their direct and indirect effects on liquefaction help to reduce the complexity of the predictive model and improve its predictive performance. This information can also help researchers understand the liquefaction phenomenon more clearly. In this paper, based on a shear wave velocity (Vs) database, 12 key factors are quantitatively identified using a correlation analysis and the maximum information coefficient (MIC) method. Subsequently, the regression method combined with the MIC method is used to construct a multiple causal path model without any assumptions based on the key factors for clarifying their direct and mediation effects on liquefaction. The results show that earthquake parameters produce more important influences on the occurrence of liquefaction than soil properties and site conditions, whereas deposit type, soil type, and deposit age produce relatively small impacts on liquefaction. In the multiple causal path model, the influence path of each factor on liquefaction becomes very clear. Among the key factors, in addition to the duration of the earthquake and Vs, other factors possess multiple mediation paths that affect liquefaction; the thickness of the critical layer and thickness of the unsaturated zone between the groundwater table and capping layer are two indirect-only mediators, and the fines content and thickness of the impermeable capping layer induce suppressive effects on liquefaction. In addition, the constructed causal model can provide a logistic regression model and a structure of the Bayesian network for predicting liquefaction. Five-fold cross-validation is used to compare and verify their predictive performances.

Transition Engagement of African American Youth With Disabilities: A Serial Mediation Model

2019 ◽  
Vol 86 (3) ◽  
pp. 276-292
Author(s):  
Alo Dutta ◽  
Madan Kundu ◽  
Kanako Iwanaga ◽  
Nicole Ditchman ◽  
Fong Chan
Keyword(s):  
African American ◽  
High School Students ◽  
Students With Disabilities ◽  
Working Alliance ◽  
Autonomous Motivation ◽  
Outcome Expectancy ◽  
Multiple Mediation ◽  
School Students ◽  
Mediation Effects ◽  
Service Engagement

The purpose of this study was to draw from self-determination and self-efficacy theories to evaluate psychological constructs (autonomous motivation, competency, and outcome expectancy) as mediators of the relationship between working alliance and engagement in transition–vocational rehabilitation (VR) services among African American students with disabilities. A serial multiple mediation analysis was computed to evaluate the mediators of transition-VR service engagement in a sample of 88 African American high school students with disabilities. We found that working alliance was positively associated with active engagement in transition-VR services (total effect), whereas the direct effect of working alliance on engagement was not significant after controlling for the effects of autonomous motivation, competency, and outcome expectancy, supporting significant mediation effects. Findings suggest that a strong working alliance between students and rehabilitation counselors and transition specialists can foster autonomous motivation, competency, and outcome expectancy, resulting in higher levels of engagement in transition-VR services.

Nonprofits’ Internal Marketing and Its Influence on Volunteers’ Experiences and Behavior: A Multiple Mediation Analysis

2018 ◽  
Vol 48 (2) ◽  
pp. 388-416 ◽  
Author(s):  
Hellen P. Gross ◽  
Maren Rottler
Keyword(s):  
Structural Equation Modeling ◽  
Organizational Identification ◽  
Structural Equation ◽  
Internal Marketing ◽  
Equation Modeling ◽  
Arts Organizations ◽  
Relevant Factor ◽  
Multiple Mediation ◽  
Mediation Effects ◽  
And Behavior

Drawing from theory and research on internal marketing as a relevant factor influencing volunteer behavior, we hypothesize that internal marketing practices are positively associated with the way volunteers act in the interest of an organization and that this relationship is mediated by volunteers’ satisfaction and organizational identification. In a study of volunteers in German arts organizations, this relationship is analyzed using structural equation modeling. Results indicate mediation effects of satisfaction on volunteer behavior and internal marketing. Similarly, identification with the organization positively influences volunteer behavior, although not in the form of a mediation. Implications for internal marketing practices and arts organizations relying on volunteers are discussed.

scholarly journals Effects of Nurse’s Second Victim Experiences on Third Victim Experiences: Multiple Mediation Effects of Second Victim Supports

2017 ◽  
Vol 23 (2) ◽  
pp. 23-34
Author(s):  
Eun-Mi Kim ◽  
Sun-Aee Kim ◽  
Ji-In Kim ◽  
Ju-Ry Lee ◽  
Sun-Gyoung Na
Keyword(s):  
Multiple Mediation ◽  
Mediation Effects ◽  
Second Victim

scholarly journals The Influence of Destination Image on Tourist Loyalty and Intention to Visit: Testing a Multiple Mediation Approach

2019 ◽  
Vol 11 (22) ◽  
pp. 6401 ◽  
Author(s):  
Shahida Kanwel ◽  
Zhou Lingqiang ◽  
Muhammad Asif ◽  
Jinsoo Hwang ◽  
Abid Hussain ◽  
...  
Keyword(s):  
Structural Equation ◽  
Tourism Industry ◽  
Mediation Effect ◽  
Destination Image ◽  
Equation Modeling ◽  
Multiple Mediation ◽  
Mediation Effects ◽  
Tourist Satisfaction ◽  
Research Findings ◽  
The Impact

Pakistan holds an important geographical status, but extremism and sabotage have severely damaged the tourism industry. In the present study, we examined the impact of destination image (DI) on tourist loyalty (TL) and intension to visit (IV) in Pakistan. Additionally, the study analyzed the mediation effects of electronic word of mouth (eWOM) and tourist satisfaction (TS) on these relationships. Data was collected from 780 tourists in Pakistan. We used confirmatory factor analysis (CFA) and structural equation modeling (SEM) to obtain the results. Our results demonstrated the positive relationships among DI, eWOM, TS, TL, and IV. This study also disclosed that eWOM has a partial mediation effect on the DI–TL relationship, and both eWOM and TS fully mediate the association between DI and IV. Hence, tourist satisfaction can be enhanced by eWOM and destination image, which directly effect tourist loyalty and intention to visit in Pakistan. The proposed framework and research findings will help stakeholders significantly to recognize the multi-facet association in the tourism industry of Pakistan. Testing the above relationships through multiple mediators is a relatively novel idea.

Causal and noncausal conditionals: An integrated model of interpretation and reasoning

2005 ◽  
Vol 58 (8) ◽  
pp. 1479-1513 ◽  
Author(s):  
Andrea Weidenfeld ◽  
Klaus Oberauer ◽  
Robin Hörnig
Keyword(s):  
Conditional Probability ◽  
Causal Link ◽  
Integrated Model ◽  
Path Model ◽  
Willingness To Accept ◽  
Indirect Pathway ◽  
Degree Of Belief ◽  
Direct Pathway ◽  
Conditional Statements ◽  
Causal Path

We present an integrated model for the understanding of and the reasoning from conditional statements. Central assumptions from several approaches are integrated into a causal path model. According to the model, the cognitive availability of exceptions to a conditional reduces the subjective conditional probability of the consequent, given the antecedent. This conditional probability determines people's degree of belief in the conditional, which in turn affects their willingness to accept logically valid inferences. In addition to this indirect pathway, the model contains a direct pathway: Availability of exceptional situations directly reduces the endorsement of valid inferences. We tested the integrated model with three experiments using conditional statements embedded in pseudonaturalistic cover stories. An explicitly mentioned causal link between antecedent and consequent was either present (causal conditionals) or absent (arbitrary conditionals). The model was supported for the causal but not for the arbitrary conditional statements.

Sign in / Sign up

Export Citation Format

Share Document