Industrialization, servicification, and environmental Kuznets curve: non-linear panel regression analysis

Taşdemir, Fatma

doi:10.1007/s11356-021-16012-9

Cited by 9 publications

(3 citation statements)

References 56 publications

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“…The impact of industrial restructuring on carbon emissions has been analyzed mainly from the following three aspects. (1) The relationship between industrial restructuring and carbon emissions: most researchers believe that industrial restructuring can significantly reduce carbon emission intensity and optimize the regional environment [ 18 , 19 ], while some scholars hold that there is a significant nonlinear relationship between industrial structure and carbon emission intensity [ 20 , 21 ]. (2) The methods used to explore the impact of industrial restructuring on carbon emissions: the widely used method is the LMDI decomposition model.…”

Section: Literature Reviewmentioning

confidence: 99%

Study of the Impact of Industrial Restructuring on the Spatial and Temporal Evolution of Carbon Emission Intensity in Chinese Provinces—Analysis of Mediating Effects Based on Technological Innovation

Wang

et al. 2022

IJERPH

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Global warming caused by greenhouse gas emissions seriously threatens a region's sustainable environmental and socioeconomic development. Promoting industrial restructuring and strengthening technological innovation have become an important path to achieving pollution and carbon reduction as well as the green transformation of economic structure. This paper explored the mechanism of the mediating effect of technological innovation on industrial restructuring and carbon reduction while accounting for the direct effect of industrial restructuring on carbon emissions. Then, based on China's provincial panel data from 2001 to 2019, we estimated the carbon emission intensity using the Intergovernmental Panel on Climate Change (IPCC)'s methods and analyzed its spatiotemporal evolution characteristics. Finally, we constructed a fixed-effect model and a mediating effect model to empirically analyze how industrial restructuring and technological innovation affect carbon emission intensity. The results are as follows: (1) From 2001 to 2019, China's carbon emission intensity showed a continuous downward trend, with a pronounced convergence trend; there were obvious differences in carbon emission intensity between eastern, central, and western regions (western region > central region > eastern region) due to the unbalanced industrial structure. (2) In terms of direct effects, industrial restructuring can significantly reduce carbon emission intensity. The intensity of the effect is inversely proportional to the level of industrial restructuring, and the results of sub-regional tests are similar. Nevertheless, there is an obvious regional difference in the size of the carbon emission reduction effect of industrial restructuring in the east, central, and western regions. (3) In terms of indirect effects, industrial restructuring can reduce carbon emission intensity by enhancing technological innovation, and it acts as a mediating variable in the process of industrial restructuring to reduce carbon emission. Finally, we put forward recommendations for promoting industrial restructuring, strengthening green technological innovation, and properly formulating carbon reduction measures to provide a reference for countries and regions to achieve the goals of carbon neutrality, carbon peaking, and high-quality economic development.

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Section: Literature Reviewmentioning

confidence: 99%

Study of the Impact of Industrial Restructuring on the Spatial and Temporal Evolution of Carbon Emission Intensity in Chinese Provinces—Analysis of Mediating Effects Based on Technological Innovation

Wang

et al. 2022

IJERPH

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“…Thus, such shift in preferences, which is one of the keys why businesses should not neglect customers, legislators and business that strive for sustainable solutions, and which is also changing market pre-scription and market drivers, is to be addressed. For example, servicification as showing value in use [31]. In this regard, "value in use" discusses new sustainable opportunities available as the interest shifts from the product to the value of the product.…”

Section: Sustainable Innovation Practicesmentioning

confidence: 99%

Sustainable Digital Innovation – Preconditions and Methods of Integrating Sustainability Aspects into Digitalization

Stiegler¹

2021

EBM

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Sustainability and digitalization have nowadays become core aspects of entrepreneurial actions. In a post-COVID world sustainable solution will be encouraged by incentives and regulations. If businesses want to survive on the market as a progressive company in the long term, they are almost forced to be digitally innovative. Therefore, during the pandemic, many businesses have enforced their investments in sustainable solutions. However, digital innovation activities can only be promising in the long term if they consider sustainable developments and are therefore "sustainable" themselves. Thus, digital innovation and sustainability, in context of entrepreneurial activities and business decisions requires a special approach. As sustainable digital innovation changes the way we are doing business now and in the future, we have gone through contextual settings and how perceived changes will affect businesses, but our approach has been to address the market opportunities. Sustainable digital innovation enables industry to take advantage of opportunities that sustainability concerns bring. Changes in the business environment asks for new solutions and new business approaches. The potential of digital technologies can help business leaders think about managing and re-defining/innovate company's roles in their business ecosystems. As the market changes and customers and society search for more sustainable solutions new sustainable opportunities arise as we are witnessing dematerialization, servicification and digitalization.

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“…However, recent literature indicates that the economic structure plays a crucial role in assessing the validity of the EKC hypothesis. Neglecting this aspect may lead to misleading conclusions regarding the validity of the EKC hypothesis (Taşdemir, 2022). The relationship between carbon dioxide emissions and income may differ across economic sectors.…”

Section: Introductionmentioning

confidence: 99%

Testing the Kuznets Curve Hypothesis at the Sector Level: Evidence from PNARDL for OECD Countries

Songur,

Uğurlu,

Muratoğlu

et al. 2024

Preprint

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Since the contribution of economic sectors to GDP is heterogeneous, they also contribute differently to CO2 emissions and environmental degradation. Although many studies investigate the Environmental Kuznets Curve (EKC) hypothesis, there are still gaps in this literature, specifically in sectors. This study contributes to the literature in several ways. First, it examines the validity of the environmental EKC hypothesis for four different sectors (Agriculture, Industry, Manufacture and Service). Second, the impact of energy consumption on CO2 is examined asymmetrically. Finally, annual data from 38 OECD countries from 1990 to 2022 are used to fill this gap. The method used in the study is a new panel nonlinear ARDL to capture the asymmetric effect of energy consumption on CO2. The findings show that the EKC hypothesis is valid for sectors other than the industrial sector and for the overall economy. The turning point of the Kuznets Curve for the total economy is estimated as $29250 GDP per capita. The PNARDL model's error correction term (ec) is negative and significant. However, the magnitude of the term suggests that the system will return to long-term equilibrium after approximately 2.87 years following any shock. It has been determined that agriculture is the sector that causes the most environmental degradation by increasing CO2 emissions. This situation highlights the limited availability of productive capital equipment and renewable sources in the agricultural sector, even in OECD countries. Moreover, the empirical results clearly show that energy consumption has asymmetric effects on emissions in both the long and short run. Positive and negative shocks in energy consumption increase CO2 emissions in OECD economies in the long run. Asymmetric effects are valid for four sectors. Jel Codes: Q42, Q43, Q53

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Industrialization, servicification, and environmental Kuznets curve: non-linear panel regression analysis

Cited by 9 publications

References 56 publications

Study of the Impact of Industrial Restructuring on the Spatial and Temporal Evolution of Carbon Emission Intensity in Chinese Provinces—Analysis of Mediating Effects Based on Technological Innovation

Study of the Impact of Industrial Restructuring on the Spatial and Temporal Evolution of Carbon Emission Intensity in Chinese Provinces—Analysis of Mediating Effects Based on Technological Innovation

Sustainable Digital Innovation – Preconditions and Methods of Integrating Sustainability Aspects into Digitalization

Testing the Kuznets Curve Hypothesis at the Sector Level: Evidence from PNARDL for OECD Countries

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