Toward Measuring Adolescent Environmental Perception

1999 ◽  
Vol 4 (3) ◽  
pp. 139-151 ◽  
Author(s):  
Franz X. Bogner ◽  
Michael Wiseman
Keyword(s):  
Structural Equation Modeling ◽  
Secondary School ◽  
Latent Variables ◽  
Structural Equation ◽  
Two Dimensions ◽  
Equation Modeling ◽  
Environmental Perceptions ◽  
Factor Analyses ◽  
Structural Relationships ◽  
Proposed Model

This study presents a scale developed to measure two dimensions of environmental perceptions—reactions towards preservation and towards utilizing nature and/or the environment—consisting of two and three subscales, respectively. The empirical part consists of a reanalysis of data from four national samples, now analyzed together as one sample. The results of the four subsamples (of some 4,500 secondary school pupils in total) have been published elsewhere as bilateral studies. The aim of the present analysis is to identify a scale that is valid for the entire European sample: By means of factor analyses and structural equation modeling 20 items were extracted. Two latent variables, “Utilization” and “Preservation,” were hypothesized and related in a causal fashion, whereby “Utilization” influences “Preservation.” By application of the methods of linear structural relationships, the proposed model yields a good fit to the data.

scholarly journals Perception Model for Selecting Patentable Technologies

2020 ◽  
Vol 8 (11) ◽  
pp. 65-85
Author(s):  
Cleide Ane Barbosa Da Cruz ◽  
Ana Eleonora Almeida Paixão ◽  
Cristiane Toniolo Dias
Keyword(s):  
Structural Equation Modeling ◽  
Latent Variables ◽  
Structural Equation ◽  
New Technologies ◽  
Science And Technology ◽  
Equation Modeling ◽  
Proposed Model ◽  
Perception Model ◽  
Structured Questionnaire

With the development of new technologies, it is necessary to develop new tools for verification and assessment for their protection by the institutions. Therefore, this study aims to build and validate the perception model for selecting patentable technologies. In relation to the methodology, a structured questionnaire was applied with the members of the National Institutes of Science and Technology (INCT), and structural equation modeling was used to examine the relationships between latent variables. The results show that five hypotheses were tested, all of which were tested and validated. Two complementary models were developed, the first being, to better adjust the model, the market construct was removed. The second model analyzed the four constructs, but it was noticed that, without the market construct, the adjustment indices are more adequate, according to what is presented in the literature as recommended indices. Thus, it is noted that the proposed model can contribute to improving the process of appreciating the technologies produced by Universities.

Meta-Accuracy and Perceived Reciprocity From the Perception-Meta-Perception Social Relations Model

2019 ◽  
Vol 50 (1) ◽  
pp. 24-37
Author(s):  
Ben Porter ◽  
Camilla S. Øverup ◽  
Julie A. Brunson ◽  
Paras D. Mehta
Keyword(s):  
Structural Equation Modeling ◽  
Social Relations ◽  
Latent Variables ◽  
Structural Equation ◽  
Multilevel Structural Equation Modeling ◽  
Equation Modeling ◽  
Complete Understanding ◽  
Social Relations Model ◽  
Flexible Framework ◽  
Multilevel Structural Equation

Abstract. Meta-accuracy and perceptions of reciprocity can be measured by covariances between latent variables in two social relations models examining perception and meta-perception. We propose a single unified model called the Perception-Meta-Perception Social Relations Model (PM-SRM). This model simultaneously estimates all possible parameters to provide a more complete understanding of the relationships between perception and meta-perception. We describe the components of the PM-SRM and present two pedagogical examples with code, openly available on https://osf.io/4ag5m . Using a new package in R (xxM), we estimated the model using multilevel structural equation modeling which provides an approachable and flexible framework for evaluating the PM-SRM. Further, we discuss possible expansions to the PM-SRM which can explore novel and exciting hypotheses.

Building a Model of Family Caregiving for Children with Emotional Disorders

1997 ◽  
Vol 5 (3) ◽  
pp. 138-148 ◽  
Author(s):  
Thomas P. Mcdonald ◽  
Thomas K. Gregoire ◽  
John Poertner ◽  
Theresa J. Early
Keyword(s):  
Structural Equation Modeling ◽  
Emotional Disorders ◽  
Problem Behaviors ◽  
Family Caregiving ◽  
Latent Variables ◽  
Structural Equation ◽  
Empirical Literature ◽  
Equation Modeling ◽  
Special Challenge ◽  
And Coping

In this article we describe the results of an ongoing effort to better understand the caregiving process in families of children with severe emotional problems. We make two assumptions. First, we assume that these families are essentially like other families but are faced with a special challenge in raising and caring for their special children while at the same time performing the multiple tasks and demands faced by all families. Second, we assume that public policy and programs must be supportive of the care of these children in their own homes and communities whenever possible. The purpose of this article is to present a model of family caregiving that draws broadly from available theory and empirical literature in multiple fields and to subject this model to empirical testing. We use structural equation modeling with latent variables to estimate an empirical model based on the theoretical model. Results of the model testing point to the importance of the child's external problem behaviors and the family's socioeconomic status and coping strategies as determinants of caregiver stress. Other findings highlight difficulties in measuring and modeling the complex mediating process, which includes formal and informal supports, perceptions, and coping behaviors. The use of structural equation modeling can benefit our efforts to support families by making explicit our theories about the important dimensions of this process and the relationship between these dimensions, which can then be subjected to measurement and validation.

scholarly journals Structural Equation Modeling for the Effect of Main Factors on Abortion Issue

2019 ◽  
Vol 7 (1) ◽  
pp. 1-13
Author(s):  
Aras Jalal Mhamad ◽  
Renas Abubaker Ahmed
Keyword(s):  
Structural Equation Modeling ◽  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Close Contact ◽  
Maternity Hospital ◽  
Equation Modeling ◽  
Research Model ◽  
Statistical Tools ◽  
Main Factors

       Based on medical exchange and medical information processing theories with statistical tools, our study proposes and tests a research model that investigates main factors behind abortion issue. Data were collected from the survey of Maternity hospital in Sulaimani, Kurdistan-Iraq. Structural Equation Modelling (SEM) is a powerful technique as it estimates the causal relationship between more than one dependent variable and many independent variables, which is ability to incorporate quantitative and qualitative data, and it shows how all latent variables are related to each other. The dependent latent variable in SEM which have one-way arrows pointing to them is called endogenous variable while others are exogenous variables. The structural equation modeling results reveal is underlying mechanism through which statistical tools, as relationship between factors; previous disease information, food and drug information, patient address, mother’s information, abortion information, which are caused abortion problem. Simply stated, the empirical data support the study hypothesis and the research model we have proposed is viable. The data of the study were obtained from a survey of Maternity hospital in Sulaimani, Kurdistan-Iraq, which is in close contact with patients for long periods, and it is number one area for pregnant women to obtain information about the abortion issue. The results shows arrangement about factors effectiveness as mentioned at section five of the study. This gives the conclusion that abortion problem must be more concern than the other pregnancy problem.

scholarly journals Workload, Techno Overload, and Behavioral Stress During COVID-19 Emergency: The Role of Job Crafting in Remote Workers

2021 ◽  
Vol 12 ◽  
Author(s):  
Emanuela Ingusci ◽  
Fulvio Signore ◽  
Maria Luisa Giancaspro ◽  
Amelia Manuti ◽  
Monica Molino ◽  
...  
Keyword(s):  
Latent Variables ◽  
Structural Equation ◽  
Protective Factor ◽  
Two Dimensions ◽  
Job Crafting ◽  
Equation Modeling ◽  
Work Overload ◽  
Daily Work ◽  
Behavioral Stress

The radical changes deriving from the COVID-19 emergency have heavily upset some of the most familiar routines of daily work life. Abruptly, many workers have been forced to face the difficulties that come with switching to remote working. Basing on the theoretical framework proposed by the Job Demands-Resources model, the purpose of this paper was to explore the effect of work overload (workload and techno overload), on behavioral stress, meant as an outcome linked to the health impairment process. Furthermore, the aim of the study was to explore the mediating role of job crafting, considered as a second-order construct consisting of two dimensions (increasing structural resources and increasing challenging demands) in the abovementioned relation. Participants were 530 workers experiencing remote working or work-from-home during the first COVID-19 lockdown in Italy (March–May 2020). Hypotheses were explored by using three different latent variables, measured reflexively through indicators on a 5-point scale, extracted from validated questionnaires. Data analysis was performed through Structural Equation Modeling; to test the mediation, bootstrap validation was computed (n = 2,000). Results showed that the mediation of job crafting was partial. More specifically, the direct effect between work overload and behavioral stress was positive; moreover, the indirect, negative effect through the mediation of job crafting was also significant. Therefore, results showed that job crafting can play a crucial role as a protective factor supporting the activation and adjustment of suitable resources; these resources can be useful to deal with the negative effects of work overload, particularly under the condition of heavy remote working and use of technologies, on individual outcomes. Starting from the current global scenario of the pandemic that has not yet ceased its effects, the study suggested decisive theoretical and practical implications. Accordingly, findings extended the current trends in occupational health psychology research, with special reference to the mainstream topic “work and COVID-19” in the Italian context. Finally, results can give suggestions to companies engaged in managing change, recommending that they build a collaborative workplace at the individual and collective level to implement job crafting interventions and enrich the personal and organizational resources of workers, which is useful cope with the current demands.

scholarly journals MODEL PERSAMAAN STRUKTURAL UNTUK MENGETAHUI PERSEPSI KONSUMEN TERHADAP BUAH IMPOR

2020 ◽  
Vol 9 (3) ◽  
pp. 149
Author(s):  
I KADEK TEGUH PRADANA ◽  
NI KETUT TARI TASTRAWATI ◽  
I PUTU EKA NILA KENCANA
Keyword(s):  
Structural Equation Modeling ◽  
Latent Variables ◽  
Structural Equation ◽  
Sem Analysis ◽  
Consumer Perception ◽  
Equation Modeling ◽  
Consumer Knowledge

This research is aimed to determine the factors that significantly influence consumer perception in buying imported fruits using structural equation modeling (SEM) analysis. The study use 164 data obtained from questionnaire, which respondents were aged 18 years old or above, from Gianyar Regency, had bought and had felt imported fruits. The study use 4 latent variables (perception, product, personal, culture) with 19 measured variables. The results showed that consumer knowledge about imported fruits (product) and culture about the use of imported fruits in traditional ceremonies (culture) were significantly influence consumer perception about consumption of imported fruit (perception).

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.

Correlation of Reverse Logistics Performance to Solutions Using Structural Equation Modeling

2019 ◽  
Vol 18 (04) ◽  
pp. 511-525
Author(s):  
Pornwasin Sirisawat ◽  
Tossapol Kiatcharoenpol
Keyword(s):  
Factor Analysis ◽  
Structural Equation Modeling ◽  
Reverse Logistics ◽  
Empirical Data ◽  
Sustainable Management ◽  
Structural Equation ◽  
Electronics Industry ◽  
Equation Modeling ◽  
Proposed Model ◽  
Confirmatory Factor

Nowadays, reverse logistics (RL) is one of the key strategies in many industries, especially in the electronics industry due to increasing environmental awareness and sustainable management. The main aim of this research is to investigate the correlation of RL performance to solutions for RL practice of the electronics industry in Thailand. In this research, questionnaires were distributed to 417 companies in the electronics industry of Thailand. A conceptual model was developed and the model examined by using structural equation modeling (SEM). Both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used in this study. The hypotheses were tested in which RL performance was directly positively associated with the overall solutions for RL practices. RL performance was also indirectly positively associated with management & organization solutions, legal & technology solutions and collaboration and support solutions of the various solutions for RL practices. Empirical data was tested by using SEM and it was found that the proposed model could fit with the empirical data. The proposed results of this study will help to understand more about RL practices and could provide further direction for researchers and practitioners in the electronics industry and other related industries.

Using WarpPLS in E-collaboration Studies

2010 ◽  
Vol 6 (4) ◽  
pp. 1-11 ◽  
Author(s):  
Ned Kock
Keyword(s):  
Structural Equation Modeling ◽  
Research Methods ◽  
Latent Variables ◽  
Structural Equation ◽  
Software Tools ◽  
Equation Modeling ◽  
Modeling Analysis ◽  
Modeling Software ◽  
S Curve ◽  
Complex Phenomena

Most relationships between variables describing natural and behavioral phenomena are nonlinear, with U-curve and S-curve relationships being particularly common. Yet, structural equation modeling software tools do not estimate coefficients of association taking nonlinear relationships between latent variables into consideration. This can lead to misleading results, particularly in multivariate and complex phenomena like those related to e-collaboration. One notable exception is WarpPLS (available from: warppls.com), a new structural equation modeling software currently available in its first release. The discussion presented in this paper contributes to the literature on e-collaboration research methods by providing a description of the main features of WarpPLS in the context of an e-collaboration study. The focus of this discussion is on the software’s features and their use and not on e-collaboration study itself. Particular emphasis is placed on the five steps through which a structural equation modeling analysis is conducted through WarpPLS.

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