scholarly journals MASEM Infrastructure in Underdeveloped Areas of Java Island

2021 ◽  
Vol 56 (1) ◽  
Author(s):  
Bambang Widjanarko Otok ◽  
Agus Suharsono ◽  
Purhadi ◽  
Rahmawati Erma Standsyah ◽  
Harun Al Azies
Keyword(s):  
Latent Variables ◽  
Latent Variable ◽  
Average Distance ◽  
Meta Analysis ◽  
Generalized Least Squares ◽  
Structural Equations ◽  
Access To Health Services ◽  
Factors Affecting ◽  
Underdeveloped Areas ◽  
The Government

This article develops a method of modeling meta-analytical structural equations (MASEM) which merge meta-analysis and modeling of structural equations on infrastructural issues in underdeveloped areas of Java Island in Indonesia. The implementation of this research is MASEM modeling using the approach of generalized least squares. The modeling is used to analyze the factors affecting the infrastructure of the underdeveloped areas in the provinces located on Java Island. This study uses three exogenous latent variables (economy, accessibility, and regional characteristics) and one endogenous latent variable (infrastructure). The results of the implementation of this study indicate that the "accessibility factor", which is an indicator of the average distance from the capital/district to access to health services, has a positive and significant effect on the infrastructure of underdeveloped areas of Java Island. This result can be used as a reference for the government in determining policy directions to tackle the problems of underdeveloped areas; in particular, in the infrastructure dimension.

The international profile of the firm

2019 ◽  
Vol 32 (3) ◽  
pp. 392-410
Author(s):  
Luz-Dary Botero-Pinzón ◽  
Jose C. Casillas ◽  
Marisol Valencia-Cárdenas
Keyword(s):  
Latin American ◽  
Latent Variables ◽  
Latent Variable ◽  
Statistical Technique ◽  
Structural Equations ◽  
International Expansion ◽  
Content Type ◽  
Latent Variable Analysis ◽  
Four Levels ◽  
And Cluster Analysis

Purpose The purpose of this paper is to design a system for measuring the level of internationalisation of companies in the field of developing countries, through latent variables based on multiple indicators, external and internal orientation. Design/methodology/approach From a sample of 112 international companies in Colombia, the methodology of latent variable analysis (LPA) is applied to a series of complementary tools, such as a model of structural equations, regression models and cluster analysis of companies. Findings The paper allows to verify the identification of six latent variables and their relationships, as well as to identify four levels of internationalisation from the structure of latent variables identified. Originality/value This is the first application of this recent and sophisticated statistical technique to the field of measuring the level of business internationalisation, especially indicated in the Latin American area, where an increasing number of companies are advancing in their process of international expansion.

Farmer knowledge and willingness to pay for soil testing in Haiti

2018 ◽  
Vol 45 (7) ◽  
pp. 1109-1121
Author(s):  
Senakpon Kokoye ◽  
Joseph Molnar ◽  
Curtis Jolly ◽  
Dennis Shannon ◽  
Gobena Huluka
Keyword(s):  
Willingness To Pay ◽  
International Development ◽  
Latent Variables ◽  
Choice Model ◽  
Structural Equations ◽  
Soil Testing ◽  
Farm Size ◽  
Content Type ◽  
Factors Affecting ◽  
Fertilizer Use

Purpose The purpose of this paper is to investigate factors affecting farmers’ perceptions and knowledge of soil testing benefits and fertilizers use in Northern Haiti. Design/methodology/approach Data were collected from 452 farmers within 17 localities in Northern Haiti. The findings reveal that farmers currently have little or no knowledge of soil testing benefits and but know better about fertilizer use. The soil testing benefits and knowledge on fertilizers use were collected using Likert scale. Analyses were done using structural equations model and choice model. Findings Factors such as farm size, participation in project, rice, banana and cocoa growers, affect farmers’ perceptions and knowledge of soil testing benefits. Factors affecting willingness to pay include group membership, type of crops grown, whether farmer’ land is on the slope, his farm size and whether he participates in the US Agency for International Development (USAID) project. Knowledge on fertilizer use is influenced by rice and banana growers, fertilizer use, participation in soil testing program and AVANSE/USAID. The effects of both latent variables are found to be positive but non-significant. Practical implications As policy implication; farmers need training module to be better informed on soil testing benefits. Originality/value Soil testing is a novel agricultural input that is being popularized in developing countries. For sustainability of the laboratory to be installed, this study is needed to fill the gap in research on farmers’ behaviors toward and demand of soil testing in Northern Haiti.

scholarly journals Estimating and interpreting latent variable interactions

2014 ◽  
Vol 39 (1) ◽  
pp. 87-96 ◽  
Author(s):  
Julie Maslowsky ◽  
Justin Jager ◽  
Douglas Hemken
Keyword(s):  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Model Fitting ◽  
Psychological Research ◽  
Structural Equations ◽  
Model Fit ◽  
Equation Modeling ◽  
Modeling Framework ◽  
Quadratic Effects

Latent variables are common in psychological research. Research questions involving the interaction of two variables are likewise quite common. Methods for estimating and interpreting interactions between latent variables within a structural equation modeling framework have recently become available. The latent moderated structural equations (LMS) method is one that is built into Mplus software. The potential utility of this method is limited by the fact that the models do not produce traditional model fit indices, standardized coefficients, or effect sizes for the latent interaction, which renders model fitting and interpretation of the latent variable interaction difficult. This article compiles state-of-the-science techniques for assessing LMS model fit, obtaining standardized coefficients, and determining the size of the latent interaction effect in order to create a tutorial for new users of LMS models. The recommended sequence of model estimation and interpretation is demonstrated via a substantive example and a Monte Carlo simulation. Finally, extensions of this method are discussed, such as estimating quadratic effects of latent factors and interactions between latent slope and intercept factors, which hold significant potential for testing and advancing developmental theories.

scholarly journals Factors Affecting Willingness to Pay for Outpatient Services at RSU Tangerang Selatan

2020 ◽  
Vol 15 (1) ◽  
pp. 14
Author(s):  
Farah Elena Astrilia ◽  
Yanti Harjono Hadiwiardjo ◽  
Gatot Soeryo
Keyword(s):  
Health Insurance ◽  
Willingness To Pay ◽  
Outpatient Services ◽  
Access To Health Services ◽  
Cross Sectional ◽  
Factors Affecting ◽  
Treatment Experience ◽  
Ability To Pay ◽  
The Government ◽  
Information Treatment

Background: The government established a national health insurance program (NHI) to increase access to health services but the program is still not optimal, it affects the number of hospital visits and income. Therefore it required an analysis of patient’s willingness to pay out of pocket for outpatient services. The purpose of this study was to determine factors affecting patient’s willingness to pay. Method: This research is a cross sectional study involving 124 internal medicine outpatients at General Hospital (RSU) South Tangerang City in November 2019. Data were obtained from a questionnaire. Patient’s income, information, treatment experience, health insurance, distance to hospital, health service, ability to pay, and willingness to pay was investigated using chi square and logistic regression analysis. Results: The results outcomes showed that the level of willingness to pay of respondents is quite high and is influenced by patient’s income (p = 0.001), information (p = 0.045), treatment experience (p = 0.010), and ability to pay (ATP) (p = 0.001).  Factors that have the most significant associations were patient’s ability to pay (OR = 14,502). Conclusion: Patient’s income, information, treatment experience, and ATP affect the willingness to pay of patients.

scholarly journals A PROPOSAL FOR A STRUCTURAL EQUATION MODEL TO EXPLAIN ACADEMIC PERFORMANCE IN E-LEARNING

2020 ◽  
Vol 6 ◽  
Author(s):  
Adrián Moneta Pizarro ◽  
Mariana Verónica González ◽  
Carina María Tofful ◽  
Mercedes Arrieta ◽  
Valeria Britos
Keyword(s):  
Academic Performance ◽  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Self Regulation ◽  
Structural Equations ◽  
Population Characteristics ◽  
Model Specification ◽  
Measurement Scales ◽  
Structural Equations Model

Purpose: Present the advances of a research project whose main goal is the construction and empirical validation of a structural equations model to explain the students’ academic performance in Administration distance degree careers of the Universidad de la Defensa Nacional (Argentina). Methodology/Approach: Were selected and adapted indicators for each latent variable identified at the theorical model. For selection in some cases we resort to measurable variables in objective units and in other cases to subjective variables measurement scales validated by previous research. For adaptation, we consider the population characteristics under study and the distance education model particularly applied in the University. Findings: A measurement model formulation was obtained which, linked to the causal model proposed as a result of bibliographic background integration, allowed us to reach a complete structural equations model specification with six latent variables, five endogenous and one exogenous. Research Limitation/implication: Consider that the observed variables selected are the ones that best combine to identify the hypothesized constructs. Originality/Value of paper: Learning in virtual environments is the main endogenous latent variable of the model, explained by previous knowledge, motivation, digital skills, self-regulation and interaction processes.

scholarly journals Pengaruh Penyaluran Dana Desa pada Indikator Perekonomian Kabupaten Daerah Tertinggal di Indonesia

2021 ◽  
Vol 6 (1) ◽  
pp. 57-74
Author(s):  
Gema Otheliansyah ◽  
Raynal Yasni
Keyword(s):  
Central Government ◽  
Simultaneous Equation ◽  
Equation Model ◽  
Structural Equations ◽  
Economic Indicators ◽  
Good Effect ◽  
Infrastructure Development ◽  
Underdeveloped Areas ◽  
The Government ◽  
The Village

ABSTRACT The different characteristics in each region in Indonesia make the pattern of economic activity, infrastructure development and human resources in each region are not similar. Thus have implications to inequality problem. There are regions have growth but also there are regions that have growth slowly or can be called underdeveloped areas. To overcome this problem, the central government directs development activities with the main focus on villages and underdeveloped areas. Underdeveloped areas are considered to be lagging behind in various economic and development aspects. The Village Law has mandated the central government to distribute the Village Fund. This study aims to determine the effect of Village Fund distribution on two economic indicators in 122 underdeveloped areas. The analytical method that used in this research is a simultaneous equation model consist of two structural equations. The results showed that the distribution of village funds had a good effect on two economic indicators of underdeveloped areas. Hopefully, the government in underdeveloped areas can use the village fund well to improve the economy in their area.                    ABSTRAK Perbedaaan karakteristik di setiap wilayah di Indonesia mengakibatkan pola pembangunan ekonomi infrastruktur dan sumber daya manusia di tiap daerah menjadi tidak seragam. Hal tersebut berimplikasi pada munculnya masalah ketimpangan. Ada daerah yang maju lebih cepat dan ada juga daerah yang tumbuh lebih lambat atau bisa dikatakan sebagai daerah tertinggal. Untuk mengatasi permasalahan tersebut, pemerintah pusat mengarahkan kegiatan pembangunan di daerah dengan fokus utama desa dan daerah tertinggal. Daerah tertinggal dianggap masih tertinggal di berbagai aspek ekonomi dan pembangunan. Undang-Undang Desa memberikan mandate kepada pemerintah untuk menyalurkan Dana Desa. Penelitian ini bertujuan untuk mengetahui pengaruh penyaluran Dana Desa terhadap dua indikator perekonomian pada 122 kabupaten daerah tertinggal. Metode analisis yang digunakan adalah model persamaan simultan yang terdiri dari dua persamaan struktural. Hasil penelitian menunjukkan bahwa penyaluran dana desa memberikan pengaruh yang baik bagi dua indikator perekonomian daerah tertinggal. Dengan demikian pemerintah di kabupaten daerah tertingga dapat mengoptimalkan penggunaan Dana Desa yang telah disalurkan guna peningkatan perekonomian.

Probability-Based and Measurement-Related Hypotheses With Full Restriction for Investigations by Means of Confirmatory Factor Analysis

Methodology ◽  
2011 ◽  
Vol 7 (4) ◽  
pp. 157-164
Author(s):  
Karl Schweizer
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Cognitive Processing ◽  
Latent Variables ◽  
Repeated Measures ◽  
Latent Variable ◽  
Model Fit ◽  
Repeated Measures Data ◽  
Confirmatory Factor ◽  
And Performance

Probability-based and measurement-related hypotheses for confirmatory factor analysis of repeated-measures data are investigated. Such hypotheses comprise precise assumptions concerning the relationships among the true components associated with the levels of the design or the items of the measure. Measurement-related hypotheses concentrate on the assumed processes, as, for example, transformation and memory processes, and represent treatment-dependent differences in processing. In contrast, probability-based hypotheses provide the opportunity to consider probabilities as outcome predictions that summarize the effects of various influences. The prediction of performance guided by inexact cues serves as an example. In the empirical part of this paper probability-based and measurement-related hypotheses are applied to working-memory data. Latent variables according to both hypotheses contribute to a good model fit. The best model fit is achieved for the model including latent variables that represented serial cognitive processing and performance according to inexact cues in combination with a latent variable for subsidiary processes.

Conceptualizing Protective Family Context and Its effect on Substance Use: Comparisons Across Diverse Ethnic-Racial Youth

2019 ◽  
Author(s):  
Kevin Constante ◽  
Edward Huntley ◽  
Emma Schillinger ◽  
Christine Wagner ◽  
Daniel Keating
Keyword(s):  
Substance Use ◽  
Measurement Invariance ◽  
Latent Variables ◽  
Latent Variable ◽  
Path Model ◽  
Family Context ◽  
Partial Metric ◽  
Racial Groups ◽  
Protective Methods ◽  
Family Variables

Background: Although family behaviors are known to be important for buffering youth against substance use, research in this area often evaluates a particular type of family interaction and how it shapes adolescents’ behaviors, when it is likely that youth experience the co-occurrence of multiple types of family behaviors that may be protective. Methods: The current study (N = 1716, 10th and 12th graders, 55% female) examined associations between protective family context, a latent variable comprised of five different measures of family behaviors, and past 12 months substance use: alcohol, cigarettes, marijuana, and e-cigarettes. Results: A multi-group measurement invariance assessment supported protective family context as a coherent latent construct with partial (metric) measurement invariance among Black, Latinx, and White youth. A multi-group path model indicated that protective family context was significantly associated with less substance use for all youth, but of varying magnitudes across ethnic-racial groups. Conclusion: These results emphasize the importance of evaluating psychometric properties of family-relevant latent variables on the basis of group membership in order to draw appropriate inferences on how such family variables relate to substance use among diverse samples.

Internet-based Online Higher Education in Nepal Amidst COVID-19

2020 ◽  
Author(s):  
Ashis Acharya ◽  
Nabaraj Poudyal ◽  
Ganesh Lamichhane ◽  
Babita Aryal ◽  
Bibek Raj Bhattarai ◽  
...  
Keyword(s):  
Higher Education ◽  
Human Life ◽  
The Internet ◽  
Online Classes ◽  
Traditional Concept ◽  
Digital Platforms ◽  
Factors Affecting ◽  
Online Higher Education ◽  
Alternative Means ◽  
The Government

The COVID-19 global pandemic has affected all aspects of human life, with education, not an exception. In an attempt to stop the SARS-CoV-2 spreading like wildfire, the Government of Nepal has implemented nationwide lockdowns since March 24, 2020, that have enforced schools and universities to shut down. As a consequence, more than four hundred thousand students of various levels in higher education institutions (HEIs) are in a dilemma about restoring the situation. Several HEIs, nationwide, have leaped forward from the traditional concept of learning—limited within the boundary of the classroom—to choosing digital platforms as an alternative means of teaching because of the pandemic. For this research, the descriptive and inferential analysis was carried out to investigate the effects and challenges of learning via digital platforms during this pandemic. Data were collected from students and faculty at various levels of higher education and analyzed statistically with different factors using t-test and ANOVA, and variables were found to be approximately normally distributed. The study revealed that 70% of the respondents had access to the Internet, but 36% of the Internet accessed did not continue online classes due to unexpected disturbance in Internet and electrical connectivity. Likewise, 65% of students did not feel comfortable with online classes, and among attendees of online classes, 78% of students want to meet the instructor for a better understanding of course matters. According to the analytic hierarchy process (AHP) model, three factors, such as institutional policy, internet access, and poverty, are found to be significant factors affecting the online higher education systems in Nepal. On the brighter side, this outbreak has brought ample opportunities to reform the conventional teaching-learning paradigm in Nepal.

Analysis of Financial Performance of Public Sector Banks in India: CAMEL

2020 ◽  
pp. 097674792096686
Author(s):  
Yudhvir Singh ◽  
Ram Milan
Keyword(s):  
Public Sector ◽  
Banking Sector ◽  
Positive Impact ◽  
Secondary Data ◽  
Capital Adequacy ◽  
Factors Affecting ◽  
Public Sector Banks ◽  
The Government ◽  
And Performance ◽  
Asset Quality

Public sector banks have been merged by the government in the last few years. This is the rationale behind conducting this study. The purpose of this article is to determine the factors affecting the performance of public sector banks in India and the interrelationship between bank-specific determinants and performance of public sector banks. In this article, we shall analyse the financial data of all the public sector commercial banks for a period spread across 11 years (2009–2019); Capital adequacy, Assets quality, Management efficiency, Earning, and Liquidity (CAMEL) has been used as a performance determinant; system generalised method of moments (GMM) analysis has been used to find the effect of determinants on the performance measurement of public sector banks; and CCA (canonical correlation analysis) has been used to find the interrelationship between the bank-specific determinants and the performance of public sector banks. The finding has important implications in terms of performance in the banking sector. Certain limitations of this study are: It is based on secondary data. The study only covers the financial aspects and not the non-financial aspects. It is found that the asset quality is negatively related with performance of public sector banks. Liquidity and inflation are inversely related to performance of public sector banks in India. Capital adequacy is positively related with banks’ performance, but inversely related with banks’ interest margin. GDP growth has a significant positive impact on banks’ performance, but inversely related with banks’ interest income. Inflation rate is inversely related with banks’ performance. Banking sector reforms are insignificantly related with banks’ performance.

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