scholarly journals Spatio-Temporal Patterns of CO2 Emissions and Influencing Factors in China Using ESDA and PLS-SEM

Mathematics ◽  
2021 ◽  
Vol 9 (21) ◽  
pp. 2711
Author(s):  
Bin Wang ◽  
Qiuxia Zheng ◽  
Ao Sun ◽  
Jie Bao ◽  
Dianting Wu
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Co2 Emissions ◽  
Structural Equation ◽  
Structural Model ◽  
Industrial Structure ◽  
Reliability And Validity ◽  
Temporal Patterns ◽  
Measurement Model ◽  
Spatio Temporal

Controlling carbon dioxide (CO2) emissions is the foundation of China’s goals to reach its carbon peak by 2030 and carbon neutrality by 2060. This study aimed to explore the spatial and temporal patterns and driving factors of CO2 emissions in China. First, we constructed a conceptual model of the factors influencing CO2 emissions, including economic growth, industrial structure, energy consumption, urban development, foreign trade, and government management. Second, we selected 30 provinces in China from 2006 to 2019 as research objects and adopted exploratory spatial data analysis (ESDA) methods to analyse the spatio-temporal patterns and agglomeration characteristics of CO2 emissions. Third, on the basis of 420 data samples from China, we used partial least squares structural equation modelling (PLS-SEM) to verify the validity of the conceptual model, analyse the reliability and validity of the measurement model, calculate the path coefficient, test the hypothesis, and estimate the predictive power of the structural model. Fourth, multigroup analysis (MGA) was used to compare differences in the influencing factors for CO2 emissions during different periods and in various regions of China. The results and conclusions are as follows: (1) CO2 emissions in China increased year by year from 2006 to 2019 but gradually decreased in the eastern, central, and western regions. The eastern coastal provinces show spatial agglomeration and CO2 emission hotspots. (2) Confirmatory analysis showed that the measurement model had high reliability and validity; four latent variables (industrial structure, energy consumption, economic growth, and government management) passed the hypothesis test in the structural model and are the determinants of CO2 emissions in China. Meanwhile, economic growth is a mediating variable of industrial structure, energy consumption, foreign trade, and government administration on CO2 emissions. (3) The calculated results of the R2 and Q2 values were 76.3 and 75.4%, respectively, indicating that the structural equation model had substantial explanatory and high predictive power. (4) Taking two development stages and three main regions as control groups, we found significant differences between the paths affecting CO2 emissions, which is consistent with China’s actual development and regional economic pattern. This study provides policy suggestions for CO2 emission reduction and sustainable development in China.

scholarly journals Identifying the Impact of Strategic Alliances on the Performance of SMEs (Case Study: The Industry of Automotive Parts Manufacturers in Iran)

2017 ◽  
Vol 10 (6) ◽  
pp. 227 ◽  
Author(s):  
Kambiez Talebi ◽  
Jahangir Yadollahi Farsi ◽  
Hamideh Miriasl
Keyword(s):  
Strategic Alliances ◽  
Structural Equation ◽  
Structural Model ◽  
Reliability And Validity ◽  
Measurement Model ◽  
Equation Modeling ◽  
Innovative Capabilities ◽  
Automotive Parts ◽  
Technical Features ◽  
The Impact

This study has investigated the effects of strategic alliances on the performance of small and medium sized enterprises (SMEs) of the industry of automotive parts manufacturers. Questionnaires have been distributed among 400 senior managers of SMEs of the industry of auto parts manufacturers based on stratified random sampling. The data has been analyzed using structural equation modeling software and PLS2 software in two segments of measurement model and structural model. In the first segment, technical features of the questionnaire were tested in terms of reliability and validity. Moreover, in the second segment, t-test was used to test research hypotheses. The results show that there is a significant and positive relationship between the dimensions of strategic alliances, including new opportunities, entrepreneurial and innovative capabilities, social capital, and internationalization of business, and competitive advantage with the performance of SMEs.

scholarly journals Analysis of Spatial Effects in the Relationship between CO2 Emissions and Renewable Energy Consumption in the Context of Economic Growth

Energies ◽  
2021 ◽  
Vol 14 (18) ◽  
pp. 5829
Author(s):  
Mateusz Jankiewicz ◽  
Elżbieta Szulc
Keyword(s):  
Economic Growth ◽  
Renewable Energy ◽  
Energy Consumption ◽  
Environmental Protection ◽  
Co2 Emissions ◽  
Indirect Effects ◽  
Renewable Energy Consumption ◽  
Spatial Spillovers ◽  
Spatio Temporal ◽  
The Relationship

The paper presents a spatial approach to the analysis of the relationship between air pollution, economic growth, and renewable energy consumption. The economic growth of every country is based on the energy consumption that leads to an increase in national productivity. Using renewable energy is very important for the environmental protection and security of the earth’s resources. Promoting environmentally friendly operations increases awareness of sustainable development, which is currently a major concern of state governments. In this study, we explored the influence of economic growth and the share of renewable energy out of total energy consumption on CO2 emissions. The study was based on the classical environmental Kuznets curve (EKC) and enriched with the spatial dependencies. In particular, we determined the spatial spillovers in the form of the indirect effects of changes in renewable energy consumption of a specific country on the CO2 emissions of neighboring countries. A neighborhood in this study was defined by ecological development similarity. The neighborhood matrix was constructed based on the values of the ecological footprint measure. We used the spatio-temporal Durbin model, with which the indirect effects were determined in relation to the spatially lagged renewable energy consumption. The results of our study also show the strength of the effects caused by imitating actions from the states with high levels of environmental protection. The study was conducted using data for 75 selected countries from the period of 2013–2019. Cumulative spatial and spatio-temporal effects allowed us to determine (1) the countries with the greatest impact on others and (2) the countries that follow the leading ones.

scholarly journals Un modelo de ecuaciones estructurales sobre el efecto de la salud en la intención de practicar desplazamiento activo: estudio de la invarianza factorial por sexo y edad (A structural equation model about the effect of health on behaviour intention to pra

Retos ◽  
2021 ◽  
Vol 44 ◽  
pp. 386-394
Author(s):  
José Antonio Ortiz Sánchez ◽  
José M. Ramírez Hurtado ◽  
Ignacio Contreras
Keyword(s):  
Structural Equation Model ◽  
Structural Equation ◽  
Structural Model ◽  
Reliability And Validity ◽  
Measurement Model ◽  
Health Problems ◽  
Equation Model ◽  
Factorial Invariance ◽  
Active Commuting ◽  
Convenience Sample

  En los últimos años ha habido un elevado crecimiento de problemas de salud en las personas, tales como obesidad, sobrepeso, diabetes, etc. Una forma de combatir este problema es el desplazamiento activo. El objetivo de este trabajo es evaluar el efecto de la salud, el confort y la conciencia medioambiental sobre la intención de practicar desplazamiento activo, así como estudiar la invarianza factorial por sexo y edad. Para ello se diseñó un cuestionario y se distribuyó mediante un muestreo por conveniencia con efecto de bola de nieve, obteniéndose 448 respuestas válidas. Para el análisis se especificó y estimó un modelo de ecuaciones estructurales con AMOS. Los resultados permitieron verificar la fiabilidad y validez del modelo de medida y del modelo estructural. De igual modo, los resultados permitieron concluir que se cumple la invarianza factorial para la variable sexo, pero no se cumple la invarianza factorial estricta para la variable edad. Abstract. A growing of health problems in people have been in recent years, as obesity, overweight, diabetes, etc. Active commuting is a way to combat these problems. The objective of this work is to assess the effect of health, comfort and environmental awareness on behaviour intention to practice active commuting, as well as to study the factorial invariance by sex and age. For this purpose, a questionnaire was designed and distributed by means of a convenience sample with snowball effect. 448 responses were obtained from this sample. The specification and estimation of structural equation model with AMOS was designed for the analysis of the data. The results show that the reliability and validity of measurement model and structural model is verified. The results also show that factorial invariance by sex is verified but strict factorial invariance for age is not verified.

scholarly journals An extensive comparison of CB-SEM and PLS-SEM for reliability and validity

2020 ◽  
pp. 357-364
Author(s):  
Asyraf Afthanorhan ◽  
Zainudin Awang ◽  
Nazim Aimran
Keyword(s):  
Structural Equation ◽  
Structural Model ◽  
Reliability And Validity ◽  
Measurement Model ◽  
Equation Modeling ◽  
Unbiased Estimation ◽  
Crucial Issue ◽  
R Software ◽  
Erroneous Result ◽  
The Impact

Structural Equation Modeling (SEM) includes measurement and structural model for hypothesis testing. The results yielded from structural model is unlikely to be valid if a poor loading of an indicator is selected. The impact of these erroneous result on standardized loading is disregard. Thus, knowing how poor loading can affect the validity of measurement model is a crucial issue. This paper attempts to compare the standardized loadings result between two prominent SEM methods (CBSEM and PLS-SEM) using three varied of simula-tion models (TRA, Loyalty and UTAUT model) to investigate their effects on reliability and validity of measurement model. The data for each model were generated using R software by setting the value of standardized loading and the construct correlations (N=50, 100, 200 and 500). The value of standardized loadings was set to 0.60 for each construct in the model while the construct correlations were set in the range between 0.45 to 0.65. Then, the AMOS 21.0 and ADANCO 2.0 were used to perform the statistical analysis. It shows that good standardized loading can increase the reliability and validity of construct representation. CBSEM is particularly yielded valid and unbiased estimation under confirmatory condition (established theory) compared with PLS-SEM. The results are illustrated with empirical examples. This paper provides updated evidence about CBSEM and PLS-SEM when assessing the measurement model.

The Impact of Service Satisfaction, Relational Satisfaction and Commitment on Customer Loyalty in Logistics Outsourcing Relationship

2015 ◽  
Vol 4 (1and2) ◽  
Author(s):  
Sanjit Singh H.
Keyword(s):  
Customer Loyalty ◽  
Structural Equation ◽  
Structural Model ◽  
Reliability And Validity ◽  
Service Satisfaction ◽  
Equation Modeling ◽  
Relational Satisfaction ◽  
Logistics Outsourcing ◽  
Major Predictor ◽  
The Impact

This research explores the impact of service satisfaction, relational satisfaction, price satisfaction, and commitment on customer loyalty in logistics outsourcing relationships in Indian scenario. 254 users of logistics services from India were selected for investigating the potential linkages among the aforementioned satisfaction aspects and loyalty. Structural equation modeling (SEM) was employed to test the reliability and validity of the measurement and structural model developed to study the relationship among the linkages. Findings from the study supports that logistics service satisfaction, price satisfaction, relational satisfaction and commitment do influence loyalty positively. The analysis suggests that service satisfaction is the most important antecedent having primary influence in the formation of customer loyalty. Service satisfaction also has secondary influence on loyalty by acting as a strong driver in both relational satisfaction and commitment aspects of the service dimensions. Price satisfaction though positively been driven by service satisfaction, was found to have less significant effect as a predictor of loyalty in this context. The present study suggests that relational satisfaction is the second major predictor of loyalty which also drives commitment. This research is not an end-point but an attempt to establish the linkages and the effect among the antecedents driving the building and retention of good buyer-seller relationship in logistics outsourcing.

scholarly journals Economic Development, CO2 Emissions and Energy Use Nexus-Evidence from the Danube Region Countries

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3165
Author(s):  
Eva Litavcová ◽  
Jana Chovancová
Keyword(s):  
Economic Growth ◽  
Energy Consumption ◽  
Co2 Emissions ◽  
Carbon Emissions ◽  
Bounds Testing ◽  
Mutual Cooperation ◽  
Long Run ◽  
Short Run ◽  
Danube Region ◽  
The Impact

The aim of this study is to examine the empirical cointegration, long-run and short-run dynamics and causal relationships between carbon emissions, energy consumption and economic growth in 14 Danube region countries over the period of 1990–2019. The autoregressive distributed lag (ARDL) bounds testing methodology was applied for each of the examined variables as a dependent variable. Limited by the length of the time series, we excluded two countries from the analysis and obtained valid results for the others for 26 of 36 ARDL models. The ARDL bounds reliably confirmed long-run cointegration between carbon emissions, energy consumption and economic growth in Austria, Czechia, Slovakia, and Slovenia. Economic growth and energy consumption have a significant impact on carbon emissions in the long-run in all of these four countries; in the short-run, the impact of economic growth is significant in Austria. Likewise, when examining cointegration between energy consumption, carbon emissions, and economic growth in the short-run, a significant contribution of CO2 emissions on energy consumptions for seven countries was found as a result of nine valid models. The results contribute to the information base essential for making responsible and informed decisions by policymakers and other stakeholders in individual countries. Moreover, they can serve as a platform for mutual cooperation and cohesion among countries in this region.

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