Equation Modeling
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2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aleksandr M. Kitsis ◽  
Injazz J. Chen

Purpose This paper aims to examine the complex links between environmental proactivity, collaboration with suppliers and customers, green operations and firm performance. Design/methodology/approach Based on a sample of 208 US companies, five main effects and two mediation effects were tested using structural equation modeling analysis. Findings This study reveals that environmental proactivity exerts positive effects on green operations and that collaboration mediates the above relationship. Further, green operations are a powerful driver of a firm’s economic and environmental performance. Findings also demonstrate the critical mediating role of green operations in linking collaboration with performance. Research limitations/implications This research contributes to a scholarly debate by offering novel insights into the extent to which proactivity improves firm performance may be influenced by multiple supply chain practices. To managers, this study highlights the strategic value of environmental proactivity as it fosters collaboration and green operations in boosting a firm’s environmental and economic performance. Originality/value This study addresses a gap in the literature by investigating the links between environmental proactivity, collaboration, green operations and corporate performance.


Author(s):  
David Opeoluwa Oyewola ◽  
Emmanuel Gbenga Dada ◽  
Juliana Ngozi Ndunagu ◽  
Terrang Abubakar Umar ◽  
Akinwunmi S.A

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.


2021 ◽  
pp. 004912412110431
Author(s):  
Bert Weijters ◽  
Eldad Davidov ◽  
Hans Baumgartner

In factorial survey designs, respondents evaluate multiple short descriptions of social objects (vignettes) that experimentally vary different levels of attributes of interest. Analytical methods (including individual-level regression analysis and multilevel models) estimate the weights (or utilities) assigned to the levels of the different attributes by participants to arrive at an overall response to the vignettes. In the current paper, we explain how data from factorial surveys can be analyzed in a structural equation modeling framework using an approach called structural equation modeling for within-subject experiments. We review the use of factorial surveys in social science research, discuss typically used methods to analyze factorial survey data, introduce the structural equation modeling for within-subject experiments approach, and present an empirical illustration of the proposed method. We conclude by describing several extensions, providing some practical recommendations, and discussing potential limitations.


PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0259016
Author(s):  
Margaux Lê ◽  
Pauline Quémart ◽  
Anna Potocki ◽  
Manuel Gimenes ◽  
David Chesnet ◽  
...  

Several nonlanguage factors influence literacy development, and motor skills are among those most studied. Despite the publication of several studies that have supported the existence of this relationship, the type of influence and underlying mechanisms have been little explored. Herein, we propose modeling the relationship between motor skills and literacy through structural equation modeling, testing the contribution of executive functions and handwriting skills as the possible mediators of this relationship. In a study of 278 third-grade children, we used a wide range of measures related to written language (reading, spelling, reading comprehension, and written production), fine motor skills (dominant hand, nondominant hand, and bimanual dexterity), executive functions (verbal and visuospatial working memory, inhibition, and shifting), and handwriting. Structural equation modeling of the relationship between these different variables indicated that in the third grade, the influence of fine motor skills on literacy is fully mediated by both executive functions and handwriting skills. These motor skills effects are observed for both low levels of processing (reading, spelling) and high levels of processing (reading comprehension, written production). The results are discussed in terms of the potential mechanisms underlying different literacy skills and their implications for pedagogical programs.


Symmetry ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2273
Author(s):  
Rahmawati Erma Standsyah ◽  
Bambang Widjanarko Otok ◽  
Agus Suharsono

The fixed effect meta-analytic structural equation modeling (MASEM) model assumes that the population effect is homogeneous across studies. It was first developed analytically using Generalized Least Squares (GLS) and computationally using Weighted Least Square (WLS) methods. The MASEM fixed effect was not estimated analytically using the estimation method based on moment. One of the classic estimation methods based on moment is the Generalized Method of Moments (GMM), whereas GMM can possibly estimate the data whose studies has parameter uncertainty problems, it also has a high accuracy on data heterogeneity. Therefore, this study estimates the fixed effect MASEM model using GMM. The symmetry of this research is based on the proof goodness of the estimator and the performance that it is analytical and numerical. The estimation results were proven to be the goodness of the estimator, unbiased and consistent. To show the performance of the obtained estimator, a comparison was carried out on the same data as the MASEM using GLS. The results show that the estimation of MASEM using GMM yields the SE value in each coefficient is smaller than the estimation of MASEM using GLS. Interactive GMM for the determination of the optimal weight on GMM in this study gave better results and therefore needs to be developed in order to obtain a Random Model MASEM estimator using GMM that is much more reliable and accurate in performance.


2021 ◽  
Vol 6 ◽  
Author(s):  
Anuar Rasyid ◽  
Belli Nasution

Community empowerment is one of the goals to be realized through the company's CSR program. The purpose of the study was to analyze the effect of PTPN V's CSR communication in empowering the community in Pekanbaru. The research uses quantitative methods. The population in this study was 528 people. Samples were taken by accidental sampling technique of as many as 250 people analyzed using the SEM (Structural Equation Modeling) test. The data was processed using LISREL 8.7 software. The results of the study indicate that there is an effect of corporate CSR communication on community empowerment. The element of CSR communication that has the most effect on community empowerment is the message element. The elements of communication consist of messages, channels, and communication disturbances that affect community empowerment positively, while communicators and the communication environment have an effect in a negative direction.


2021 ◽  
pp. 073563312110536
Author(s):  
Wen Huang ◽  
Rod D. Roscoe ◽  
Scotty D. Craig ◽  
Mina C. Johnson-Glenberg

Virtual reality (VR) has a high potential to facilitate education. However, the design of many VR learning applications was criticized for lacking the guidance of explicit and appropriate learning theories. To advance the use of VR in effective instruction, this study proposed a model that extended the cognitive-affective theory of learning with media (CATLM) into a VR learning context and evaluated this model using a structural equation modeling (SEM) approach. Undergraduate students ( n = 77) learned about the solar system in a VR environment over three sessions. Overall, the results supported the core principles and assumptions of CATLM in a VR context (CATLM-VR). In addition, the CATLM-VR model illustrated how immersive VR may impact learning. Specifically, immersion had an overall positive impact on user experience and motivation. However, the impact of immersion on cognitive load was uncertain, and that uncertainty made the final learning outcomes less predictable. Enhancing students’ motivation and cognitive engagement may more directly increase learning achievement than increasing the level of immersion and may be more universally applicable in VR instruction.


2021 ◽  
Vol 24 (2) ◽  
pp. 33-40
Author(s):  
Nadiah Arum Mindarti ◽  
Made Siti Sundari ◽  
Sugeng Hariadi

This research studies the factors that influence consumers in using online food delivery services. The variables used are Time Saving Orientation, Price Saving Orientation, and Behavior Intention to OFD Services. The questionnaire is used in the data collectionprocess. Questions in this study were published online and offline. Online distribution is done through Google Form and offline distribution is done by distributing it to students of the University of Surabaya. A total of 208 valid questionnaires were collected to besubmitted using Structural Equation Modeling (SEM) data processing with SmartPLS software. Time Saving Orientation and Price Saving Orientation have positive and significant effect on Behavior Intention Towards OFD Services which support t-statisticsof 3,562 & 3,272 and P-Values of 0,000. The more culinary entrepreneurs who use e-commerce, the more transactions will occur, so it will increase the GRDP which will ultimately increase economic growth.


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