Green consumerism has been an interesting aspect both for scholars and practitioners due to the growing environmental awareness among consumers globally. The aim of this study was to propose a theoretical explanation of the relationship between green product and purchasing intentions of the product in the context of developing countries. Based on a quantitative experimental study, we exhibited that green product influenced purchasing intention indirectly, but no directly through environmental concern. The present study demonstrated that environmental concern among consumers plays a crucial role in inducing purchasing decision of green products. The theoretical and practical contributions as well as direction of future studies were presented.
Background Economic growth is dependent on economic activity, which often translates to higher levels of carbon emissions. With the emergence of technologies that promote sustainable production, governments are working towards achieving their target economic growth while minimizing environmental emissions to meet their commitments to the international community. The IPCC reports that economic activities associated with electricity and heat production contributed most to GHG emissions and it led to the steady increase in global average temperatures. Currently, more than 90% of the total GHG emissions of the ASEAN region is attributable to Indonesia, Malaysia, the Philippines, Thailand, and Vietnam. These regions are expected to be greatly affected with climate change. This work analyzes how ASEAN nations can achieve carbon reduction targets while aspiring for economic growth rates in consideration of interdependencies between nations. We thus develop a multi-regional input–output model which can either minimize collective or individual carbon emissions. A high-level eight-sector economy is used for analyzing different economic strategies. Results This model shows that minimizing collective carbon emissions can still yield economic growth. Countries can focus on developing sectors that have potentials for growth and lower carbon intensity as new technologies become available. In the case study examined, results indicate that the services sector, agriculture, and food manufacturing sector have higher potential for economic growth under carbon reduction emission constraints. In addition, the simultaneous implementation of multiple carbon emission reduction strategies provides the largest reduction in regional carbon emissions. Conclusions This model provides a more holistic view of how the generation of carbon emissions are influenced by the interdependence of nations. The emissions reduction achieved by each country varied depending on the state of technology and the level of economic development in the different regions. Though the presented case focused on the ASEAN region, the model framework can be used for the analysis of other multi-regional systems at various levels of resolution if data is available. Insights obtained from the model results can be used to help nations identify more appropriate and achievable carbon reduction targets and to develop coordinated and more customized policies to target priority sectors in a country. This model is currently limited by the assumption of fixed technical coefficients in the exchange and interdependence of different regions. Future work can investigate modelling flexible multi-regional trade where regions have the option of substituting goods and products in its import or export structure. Other strategies for reducing carbon emission intensity can also be explored, such as modelling transport mode choices, or establishing sectors for waste management. Hybrid models which integrate the multi-regional input–output linear program model with data envelopment analysis can also be developed.
BackgroundEconomic growth is dependent on economic activity, which often translates to higher levels of carbon emissions. With the emergence of technologies that promote sustainable production, governments are working towards achieving their target economic growth while minimizing environmental emissions to meet their commitments to the international community. The IPCC reports that economic activities associated with electricity and heat production contributed most to GHG emissions and it led to the steady increase in global average temperatures. Currently, more than 90% of the total GHG emissions of the ASEAN region is attributable to Indonesia, Malaysia, the Philippines, Thailand, and Vietnam. These regions are also expected to be greatly affected with climate change. To analyze how ASEAN nations can achieve carbon reduction targets while aspiring for economic growth rates, and in consideration of interdependencies between nations, this study develops a multi-regional input-output model for minimizing collective and individual carbon emissions. A high-level eight-sector economy is used for analyzing different economic strategies.ResultsThis model shows that minimizing collective carbon emissions can still yield economic growth. Countries can focus on developing sectors that have growth potentials and lower carbon intensity-such as the services sector, agriculture, and food manufacturing sector. In addition, the simultaneous implementation of multiple carbon emission reduction strategies provides the largest reduction in regional carbon emissions. ConclusionsThis model provides a more holistic view of how the generation of carbon emissions are influenced by the interdependence of nations. The emissions reduction achieved by each country varied depending on the state of technology and the level of economic development in the different regions. This current model can be used to help nations identify more appropriate and achievable carbon reduction targets and to develop more customized policies to target priority sectors in a country. This model is currently limited by the assumption of fixed technical coefficients in the exchange and interdependence of different regions. Future work can investigate modelling flexible multi-regional trade where regions have the option of substituting goods and products in its import or export structure. Other strategies for reducing carbon emission intensity can also be explored, such as modelling transport mode choices, or establishing sectors for waste management. Hybrid models which integrate the multi-regional input-output linear program model with data envelopment analysis can also be developed.
This study analyses the mediating role of work engagement in the relationship between personality and employee performance, especially employees who work as customer service at a government-owned bank in Kupang City. It is explanatory research using a quantitative approach. The data source was gained from a sample of 92 peopledata analysis using Structural Equation Modeling (SEM) equations through path analysis with the help of SmartPLS. The research results are 1) Personality has a positive effect on CS performance, 2) Personality has a positive effect on work engagement, 3) Work engagement has a positive effect on CS performance, 4) Work enggament acts as a mediating variable in the relationship between personality and CS performance.
The study aims at analyzing the direct and indirect effects of resilience, job burnout, and the performance of Special Investigation and Criminal Investigators of the East Nusa Tenggara Regional Police during the Covid 19 Pandemic. Investigators need resilience in law enforcement. Respondents were 57 people from a total of 67 investigators. Path analysis is used in the Structural Equation Modeling (SEM) equation with the help of SmartPLS. The results showed that: 1) job burnout had a positive effect on performance and resilience; 2) resilience has a positive effect on performance; and 3) resilience mediates work burnout and performance.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.