scholarly journals Political Participation and Workplace Voice: The Spillover of Suppression by Supervisors

2020 ◽  
pp. 003232172096096
Author(s):  
Bram Geurkink ◽  
Agnes Akkerman ◽  
Roderick Sluiter
Keyword(s):  
Structural Equation Modeling ◽  
Political Participation ◽  
Structural Equation ◽  
Equation Modeling ◽  
Negative Effects ◽  
Political Voice ◽  
Do So ◽  
Unique Dataset

This article aims to establish the connection between people’s voice at work and their political voice. We theorize and model a spillover mechanism from supervisors’ responses to workplace voice to political participation. Applying structural equation modeling on a unique dataset (N = 3129), we find that while support and suppression of workplace voice both affect political participation, they do so through different mechanisms. In addition, we find that supervisors’ suppressive responses to employees’ voice can trigger both positive and negative effects on different forms of political participation. Thereby, we contribute to the understanding of the link between participation at work and participation in politics.

Parenting quality, adversity, and conduct problems in adolescence: Testing process-oriented models of resilience

1993 ◽  
Vol 5 (4) ◽  
pp. 663-682 ◽  
Author(s):  
Scott D. Gest ◽  
Jennifer Neemann ◽  
Jon J. Hubbard ◽  
Ann S. Masten ◽  
Auke Tellegen
Keyword(s):  
Structural Equation Modeling ◽  
Conduct Problems ◽  
Structural Equation ◽  
Extended Family ◽  
Equation Modeling ◽  
Childhood And Adolescence ◽  
Moderating Effects ◽  
Negative Effects ◽  
Effective Parenting ◽  
Parenting Quality

AbstractStructural equation modeling was used (a) to determine the extent to which parent-related and non-parent-related adversity were associated with increases in conduct problems between childhood and adolescence and (b) to evaluate the possible preventive, compensatory, and moderating effects of parenting quality in this regard. Subjects were 180 boys and girls from the Project Competence longitudinal study of adversity, competence, and resilience (Garmezy & Tellegen, 1984). Conduct problems, parenting quality, and socioeconomic status were assessed when subjects were in the third through sixth grades, and adversity and conduct problems were assessed again 7 years later. Results were consistent with the view that parentrelated adversity experienced between the two assessment times was associated with a small increase in conduct problems. Adversity involving siblings, extended family, and friends was not associated with changes in conduct. Effective parenting was associated with less parent-related adversity during adolescence. Effective parenting, however, did not directly compensate for the negative effects of adversity; nor did it moderate the effects of adversity. Structural equation modeling was helpful in testing for several of these effects simultaneously. Short-term longitudinal studies with baseline measures, more frequent assessments, and adequate sample size are necessary to clarify the processes suggested by these results.

scholarly journals COVID-19 Risk Factors, Economic Factors, and Epidemiological Factors nexus on Economic Impact: Machine Learning and Structural Equation Modelling Approaches

2021 ◽  
pp. 395-405
Author(s):  
David Opeoluwa Oyewola ◽  
Emmanuel Gbenga Dada ◽  
Juliana Ngozi Ndunagu ◽  
Terrang Abubakar Umar ◽  
Akinwunmi S.A
Keyword(s):  
Machine Learning ◽  
Risk Factors ◽  
Structural Equation Modeling ◽  
Latent Variables ◽  
Structural Equation ◽  
Equation Modeling ◽  
Support Vector ◽  
Economic Factors ◽  
Negative Effects ◽  
The Impact

Since the declaration of COVID-19 as a global pandemic, it has been transmitted to more than 200 nations of the world. The harmful impact of the pandemic on the economy of nations is far greater than anything suffered in almost a century. The main objective of this paper is to apply Structural Equation Modeling (SEM) and Machine Learning (ML) to determine the relationships among COVID-19 risk factors, epidemiology factors and economic factors. Structural equation modeling is a statistical technique for calculating and evaluating the relationships of manifest and latent variables. It explores the causal relationship between variables and at the same time taking measurement error into account. Bagging (BAG), Boosting (BST), Support Vector Machine (SVM), Decision Tree (DT) and Random Forest (RF) Machine Learning techniques was applied to predict the impact of COVID-19 risk factors. Data from patients who came into contact with coronavirus disease were collected from Kaggle database between 23 January 2020 and 24 June 2020. Results indicate that COVID-19 risk factors have negative effects on epidemiology factors. It also has negative effects on economic factors.

scholarly journals A Primer on the Conditional Mediation Analysis in PLS-SEM

2021 ◽  
Vol 52 (SI) ◽  
pp. 43-100
Author(s):  
Jun-Hwa Cheah ◽  
Christian Nitzl ◽  
José L. Roldán ◽  
Gabriel Cepeda-Carrion ◽  
Siegfried P. Gudergan
Keyword(s):  
Structural Equation Modeling ◽  
Information Systems ◽  
Individual Differences ◽  
Least Squares ◽  
Mediation Analysis ◽  
Structural Equation ◽  
Empirical Studies ◽  
Equation Modeling ◽  
Advance Theory ◽  
Do So

Conditional mediation (CoMe) analysis integrates mediation and moderation analyses to examine and test hypotheses about how mediated relationships vary as a function of context, boundaries, or individual differences. Although CoMe analysis can be a crucial element of empirical studies that seek to advance theory in information systems, applications of such analysis are scarce, in general, and in partial least squares structural equation modeling (PLS-SEM), in particular. This paper clarifies conceptual fundamentals of and develops guidelines for CoMe analysis within the PLS-SEM context. Furthermore, the paper outlines the illustrative use of CoMe analysis in PLS-SEM and presents detailed step-by-step procedures to do so in the PLS-SEM setting. Overall, this paper provides researchers and practitioners with the required knowledge to properly carry out, report, and interpret CoMe analysis in PLS-SEM.

scholarly journals Recursive Effects to Study Feature-Based Capabilities in Supply Chain Management

Logistics ◽  
2020 ◽  
Vol 4 (4) ◽  
pp. 28
Author(s):  
Pietro De Giovanni
Keyword(s):  
Supply Chain ◽  
Structural Equation Modeling ◽  
Supply Chain Management ◽  
Structural Equation ◽  
Operational Performance ◽  
Equation Modeling ◽  
Negative Effects ◽  
Chain Management ◽  
External Pressures ◽  
Feature Based

This paper explores the benefits that firms obtain when investing in feature-based capabilities. We investigate the external pressures when deciding their feature-based strategy. In addition, we analyze the consumers’ customization options and the needs for facilitators to mitigate the negative effects of excessive features. We assess the influence of feature-based capabilities on performance and search for an economically feasible loop that feature-based capabilities might entail. This latter is carried out by investigating the recursive effects in structural equation modeling. Our findings reveal that feature-based capabilities entail an economically feasible loop through competitors and supply chain partners but not also through facilitators and operational performance.

Integrating Moderation and Mediation

2016 ◽  
Vol 20 (4) ◽  
pp. 721-745 ◽  
Author(s):  
Shruti R. Sardeshmukh ◽  
Robert J. Vandenberg
Keyword(s):  
Structural Equation Modeling ◽  
Research Methods ◽  
Latent Variable ◽  
Structural Equation ◽  
Equation Modeling ◽  
Latent Variable Interactions ◽  
Variable Interactions ◽  
Do So

It is increasingly common to test hypotheses combining moderation and mediation. Structural equation modeling (SEM) has been the favored approach to testing mediation hypotheses. However, the biggest challenge to testing moderation hypotheses in SEM was the complexity underlying the modeling of latent variable interactions. We discuss the latent moderated structural equation procedure (LMS) approach to specifying latent variable interactions, which is implemented in Mplus, and offer a simple and accessible way of testing combined moderation and mediation hypotheses using SEM. To do so, we provide sample code for six commonly encountered moderation and mediation cases and relevant equations that can be easily adapted to researchers’ data. By articulating the similarities in the two different approaches, discussing the combination of moderation and mediation, we also contribute to the research methods literature.

O IMPACTO DO ENVOLVIMENTO NAS RELAÇÕES ENTRE CONFIANÇA, VALOR PERCEBIDO E LEALDADE: UM ESTUDO EM UMA IES PRIVADA

2008 ◽  
Vol 13 (2) ◽  
pp. 11 ◽  
Author(s):  
Lélis Balestrin Espartel ◽  
Cláudio Hoffmann Sampaio ◽  
Marcelo Gatterman Perin
Keyword(s):  
Structural Equation Modeling ◽  
Theoretical Model ◽  
Structural Equation ◽  
Group Analysis ◽  
Perceived Value ◽  
Equation Modeling ◽  
Trust Value ◽  
Moderate Effect ◽  
The Relationship ◽  
Do So

This paper proposes the test of a theoretical model presenting trust and perceived value as loyalty antecedents, and to verify the moderate effect of student involvement with the course on the relationship among constructs. In order to do so, the model behavior was tested in a sample of 414 cases. The outcomes suggest that the intensity of the model constructs (trust, value and loyalty) is significantly higher in students that demonstrate higher involvement with the course, i.e., these subjects have higher trust on the employees and on the institution, they perceive higher value in the course and they are more loyal to the institution. From the application of multi-group analysis in Structural Equation Modeling (SEM), the conclusion is that there exists stability of the proposed relationship in the theoretical model, once the outcomes do not indicate significant invariances between higher and lower involvement groups. As a result, the involvement seems not to be a moderate construct, once the models have similar statistic behavior, but an impact construct, as the model constructs presented statistically higher averages for the highest involvement group.

scholarly journals The Role of Sensory Emotions in Increasing Willingness to Read in EFL Learners

PUBLICACIONES ◽  
2019 ◽  
Vol 49 (2) ◽  
pp. 169-189
Author(s):  
Behnoosh Borsipour ◽  
Reza Pishghadam ◽  
Elham Naji Meidani
Keyword(s):  
Reading Comprehension ◽  
Structural Equation Modeling ◽  
Language Learners ◽  
Structural Equation ◽  
Language Education ◽  
Equation Modeling ◽  
Structured Interviews ◽  
Efl Learners ◽  
Do So

It seems that one of the factors contributing to language learners’ interest in reading comprehension texts is the sensory emotions they may have for reading topics. In this study, the association between language learners’ sensory emotions towards some topics and their willingness to read (WTR) about them was examined. To do so, 201 intermediate and upper-intermediate English as a foreign langauge (EFL) learners were asked to complete a newly-deigned scale measuring their sensory emotions, frequency of exposure, and WTR regarding 18 topics from various fields. Structural equation modeling (SEM) and analysis of variance (ANOVA) were employed to analyze the data. Moreover, semi-structured interviews were conducted with 21 participants regarding their emotions and WTR towards topics. The results showed that the higher the level of sensory emotions towards a topic, the higher the WTR. In the end, the findings were discussed in the context of language education and implications were provided.

scholarly journals The Effects of Asymmetrical Guanxi Perception on Job Burnout: Task Conflict, Relationship Conflict, and Process Conflict as Mediators

2021 ◽  
Vol 12 ◽  
Author(s):  
Hao-Kai Hung
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Job Burnout ◽  
Task Conflict ◽  
Relationship Conflict ◽  
Equation Modeling ◽  
Negative Effects ◽  
Cross Sectional ◽  
Process Conflict ◽  
The Relationship

In Chinese organizations, individuals benefit in many ways from having good guanxi. For employees, however, guanxi also comes with well-documented negative effects. Until recently, the guanxi investigated in these studies was always of a substantial nature. The negative effects of non-substantial guanxi (in effect, the absence of real guanxi), such as the guanxi of misunderstandings for those who lack good guanxi, have not been examined. This study investigates how the existence of asymmetrical guanxi perception for an employee (i.e., when other people believe that good guanxi exists between a manager and an employee, but the employee disagrees with the belief that he/she has good guanxi with his/her supervisors) contributes to job burnout for that employee due to task conflict, relationship conflict, and process conflict. A cross-sectional data sample was collected from 363 employees of 10 hotels in Taiwan. Structural equation modeling results suggest that relationship conflict is the most powerful mediator affecting the relationship between asymmetrical guanxi perception and job burnout. The results provide insights for researchers interested in the mechanism of how asymmetrical guanxi perception induces employee job burnout while generating useful implications for managers charged with reducing such burnout.

Organizational Identification as a Double-Edged Sword

2015 ◽  
Vol 14 (4) ◽  
pp. 182-191 ◽  
Author(s):  
Yongxin Li ◽  
Jinyan Fan ◽  
Shenran Zhao
Keyword(s):  
Life Satisfaction ◽  
Structural Equation Modeling ◽  
Survey Research ◽  
Family Conflict ◽  
Organizational Identification ◽  
Structural Equation ◽  
Equation Modeling ◽  
Negative Effects ◽  
Republic Of China ◽  
Positive Effects

Abstract. Previous research on organizational identification has almost exclusively focused on its positive effects on organization-related outcomes, paying relatively less attention to its effects on individual-related outcomes and its potential negative effects on both organization-related and individual-related outcomes. We proposed a model in which organizational identification was hypothesized to have both positive and negative effects on job and life satisfaction. Further, we proposed work-to-family conflict as a mediator of the negative effects of organizational identification. Participants in this survey research were 545 teachers in the People’s Republic of China. Results based on structural equation modeling largely supported our proposition that in addition to the well-established positive effects, organizational identification may also have negative effects on organization-related and individual-related outcomes.

scholarly journals Social Media Use and Adolescents’ Self-Esteem: Heading for a Person-Specific Media Effects Paradigm

2021 ◽  
Vol 71 (1) ◽  
pp. 56-78
Author(s):  
Patti Valkenburg ◽  
Ine Beyens ◽  
J Loes Pouwels ◽  
Irene I van Driel ◽  
Loes Keijsers
Keyword(s):  
Social Media ◽  
Structural Equation Modeling ◽  
Media Effects ◽  
Structural Equation ◽  
Media Use ◽  
Self Esteem ◽  
Equation Modeling ◽  
Negative Effects ◽  
Social Media Use ◽  
Specific Effects

Abstract Eighteen earlier studies have investigated the associations between social media use (SMU) and adolescents’ self-esteem, finding weak effects and inconsistent results. A viable hypothesis for these mixed findings is that the effect of SMU differs from adolescent to adolescent. To test this hypothesis, we conducted a preregistered three-week experience sampling study among 387 adolescents (13–15 years, 54% girls). Each adolescent reported on his/her SMU and self-esteem six times per day (126 assessments per participant; 34,930 in total). Using a person-specific, N = 1 method of analysis (Dynamic Structural Equation Modeling), we found that the majority of adolescents (88%) experienced no or very small effects of SMU on self-esteem (−.10 < β < .10), whereas 4% experienced positive (.10 ≤ β ≤ .17) and 8% negative effects (−.21 ≤ β ≤ −.10). Our results suggest that person-specific effects can no longer be ignored in future media effects theories and research.

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