Green GDP Indicator with Application to Life Cycle of Sugar Industry in Thailand

The objective of this study was to develop new indicators that reflect economic growth by taking into account the impact on the environment and natural resources as well. The indicator calculated by subtracting environmental cost from the “Gross Domestic Product (GDP)” and is used in the assessment of the GDP by taking into consideration the cost of natural resources and the environment, called “green GDP”. This study uses Life Cycle Assessment, which is a technique used to assess the environmental impact of sugar industry from raw materials, distribution, production, and waste management. The system boundary for the life cycle inventory are cultivation, planting, transportation and sugar production. The results of the green GDP and GDP is difference about 6–12% due to the depletion cost resulting from the use of natural resources between 9.0–9.52 $/ton of sugar production and the degradation cost caused by the airborne emission and waterborne emission between 37–57 $/ton of sugar production. The quantity of Total Suspended Particulate (TSP) generated from the sugar production process is the main causing the environmental cost about 55%. In order to solve environmental causes, the policy making as Circular Economy Strategies can be used to meet the sustainable development in the future.

A Comparative Study of the Impacts of Human Capital and Physical Capital on Building Sustainable Economies at Different Stages of Economic Development

This study investigated the contributions of human capital and physical capital to economies at different stages by measuring the economic development with the traditional GDP and green GDP. The traditional GDP stood for the quantity of economic growth, and the green GDP, taking both the energy consumption and environmental pollution into account, was employed to represent the sustainability of economic development. We used a panel data of 143 countries and regions during the period from 1990 to 2014, and results showed that the elasticities of output with respect to human capital were greater compared to physical capital, while green GDP was significantly more sensitive to changes in human capital than the traditional GDP. In particular, considering the unbalanced distribution of economic growth among countries and regions, we employed the quantile regression model to explore the heterogeneous roles of physical and human capital in different stages of economic development, which evidenced not only the significance but also the stability of human capital. As national economic levels grew, countries became less dependent on physical capital, yet human capital maintained its outstanding role at different stages of economic development, particularly for the building of more sustainable economies.

Sustainable Development Based on Green GDP Accounting and Cloud Computing: A Case Study of Zhejiang Province

Cloud computing is a supercomputing that integrates large-scale and scalable computing, storage, data, applications, and other distributed computing resources for collaborative work in the form of virtualization technology as the basis and the network as the carrier to provide infrastructure, platform, software, and other service’s model. Green GDP (GGDP) is an assessment indicator for regional sustainable development. Hence, the evaluation index on GGDP and greening of the national economic accounting system (SNA) are the hotspots of current ecological and economic studies. In the recent years, Zhejiang’s economy has achieved rapid development, and there are also problems of high input and high consumption of natural resources, thereby restricting its sustainable development. Based on the statistical data of Zhejiang Province during 2000–2017, the GGDP within the sustainable development context is calculated using the system of integrated environmental and economic accounting (SEEA). The results indicated the following: (1) The GGDP accounted for 79.29%–96.78% of Zhejiang's GDP during the study period, which showed volatility upward trend, resulting from the significant environmental protection and conservation of natural resources in the study area. But economic development was heavily dependent on resources, and the local government still strengthened the work of improving resources and environment. (2) The proportion of secondary industry in Zhejiang Province fluctuated downwards during the period of 2000–2017, and the tertiary industry showed a volatility upward trend, which exceeded the proportion of the secondary industry, indicating that Zhejiang Province is from an industry-led economy to a service-oriented economy change. (3) The GGDP of Zhejiang Province accounted for the highest proportion of GDP in 2008, resulting from the result of a combination of relevant national policies and international competitions.

Spatial Effects of Energy Consumption and Green GDP in Regional Agreements

One of the main factors in environmental degradation and climate change is the consumption of fossil fuels. For this reason, cooperation between countries to overcome environmental challenges is seen more than ever. In this regard, regional economic treaties are a good platform for advancing common policies in the development of renewable energy, because this type of energy has fewer external effects on the environment. Accordingly, the purpose of this paper is to investigate the spatial effects of energy consumption and green production in Shanghai Cooperation Organization member states. For this purpose, the spatial panel data econometric approach has been used. Spatial effects refer to the effects of neighboring countries. According to CO2 emissions, the spatial effects of the positive or negative effects of these emissions and other determinants of neighboring countries are local. The results show that although both fossil fuels and renewable energy have a negative effect on green GDP, the impact of fossil fuels is almost four times greater. On the other hand, proximity and membership in the Shanghai Cooperation Organization have had a positive effect on green GDP in member countries, as countries have tried to coordinate their development policies in the field of renewable energy. Therefore, the development and strengthening of regional cooperation can play an effective role in controlling pollution caused by fossil fuel consumption and ultimately improve green production.

Green Technological Progress and the Backwardness Advantage of Green Development: Taking the Sustainable Development Strategy of Central and Western China as an Example

It is generally believed that research and development on green technology are difficult, but this paper finds that the gap in green technological progress between the central and western regions and the eastern region in China is significantly smaller than the gap in technological progress, and the per capita green GDP of the central and western regions caught up with the eastern region significantly faster than the per capita GDP. This paper proposes that the comparative advantage of human capital level in the central and western regions is the reason why these regions choose the direction of green technological progress, and the choice of the direction of green technological progress in the central and western regions may further bring about the backwardness advantages of green development in these regions. Through the system generalized method of moments (sys-GMM) estimation, empirical research using panel data from 29 provinces as well as the regional panel data in the mainland of China from 1995 to 2017 proved the above proposition. Specifically, due to the comparative advantages of human capital level, the central and western regions have chosen the direction of green technological progress; further, the central and western regions will obtain greater benefits of green GDP growth from the green technological progress, that is, the green technological progress enables these regions’ backwardness to take advantage from green development. This is a useful supplement to the theory of sustainable development and the theory of backwardness advantage.

Development of Internet Supply Chain Finance Based on Artificial Intelligence under the Enterprise Green Business Model

At present, China’s economic development has made unprecedented progress, but it is also facing a severe situation, and the environmental carrying capacity has almost reached its limit. For this reason, the government vigorously promotes the construction of ecological civilization and advocates green development, circular development, and low-carbon development. Enterprise green operation is a business activity that integrates environmental protection into the whole process of enterprise operation and management. It requires the guiding ideology of business operations and every link of business management to be based on environmental protection. The purpose of this article is to solve the problems between the development of corporate GDP and green protection and analyze the impact of green business development policies on China’s corporate GDP. In order to further clarify the impact of green development on social development of Chinese enterprises, this paper investigates the economic and environmental aspects of green transformation enterprises nationwide. The research results show that China’s green enterprise development has achieved remarkable development achievements. The average growth rate of China’s green development GDP in recent years has begun to significantly exceed the average growth rate of green GDP over the same period. The average annual growth rate of the enterprise’s total economic growth of green environmental protection GDP has reached 11.58%, surpassing the average growth rate of the green GDP economy of the same period of 0.12%. Chinese companies have also achieved impressive corporate achievements following the implementation of the national guidelines for green development. For the first time in 31 inland provinces, municipalities, and autonomous regions in China, chemical companies have achieved green production, and the average GDP growth rate has reached 8.75% for the first time.