Transmission mechanism between energy prices and carbon emissions using geographically weighted regression

Li, Wei; Sun, Wenqiang; Li, Guomin; Jin, Baihui; Wu, Wen Jie; Cui, Pengfei; Zhao, Guohao

doi:10.1016/j.enpol.2018.01.005

Cited by 49 publications

(26 citation statements)

References 44 publications

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“…Geographic weighted regression (GWR) [17,35,36] is an extension of the general linear regression model, which attempts to build a linear relationship between the dependent variable and a set of independent variables. By taking into account spatial changes between variables caused by geographic changes, a linear regression equation is established for each spatial unit, improving the explanatory ability between variables within the overall scope, so that…”

Section: Ggeographic Weighted Regressionmentioning

confidence: 99%

Spatiotemporal Characteristics of Bike-Sharing Usage around Rail Transit Stations: Evidence from Beijing, China

Wang

Cheng

et al. 2020

Sustainability

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As an emerging mode of transport, bike-sharing is being quickly accepted by Chinese residents due to its convenience and environmental friendliness. As hotspots for bike-sharing, railway-station service areas attract thousands of bikes during peak hours, which can block roads and pedestrian walkways. Of the many works devoted to the connection between bikes and rail, few have addressed the spatial‒temporal pattern of bike-sharing accumulating around station service areas. In this work, we investigate the distribution patterns of bike-sharing in station service areas, which are influenced not only by railway-station ridership but also by the built environment around the station, illustrating obvious spatial heterogeneity. To this end, we established a geographic weighted regression (GWR) model to capture this feature considering the variables of passenger flow and the built environment. Using the data from bike-sharing in Beijing, China, we applied the GWR model to carry out a spatiotemporal characteristic analysis of the relationship between bike-sharing usage in railway-station service areas and its determinants, including the passenger flow in stations, land use, bus lines, and road-network characteristics. The influence of these factors on bike-sharing usage is quite different in time and space. For instance, bus lines are a competing mode of transport with bike-sharing in suburban areas but not in city centers, whereas industrial and residential areas could also heavily affect the bike-sharing demand as well as railway-station ridership. The results of this work can help facilitate the dynamic allocation of bike-sharing and increase the efficiency of this emerging mode of transport.

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Section: Ggeographic Weighted Regressionmentioning

confidence: 99%

Spatiotemporal Characteristics of Bike-Sharing Usage around Rail Transit Stations: Evidence from Beijing, China

Wang

Cheng

et al. 2020

Sustainability

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“…Carbon emissions are increased by the scale effect of the regional economy offset of the carbon emissions and decreased by the optimization of energy structure and improvements in energy efficiency. In addition, the unreasonable industry structure and division of labor lead to a reduction in resource allocation to creating greater efficiency and an increase in the energy rebound effect, which further accelerates carbon emissions (Li, Sun, Li, Jin, & Zhao, 2018).…”

Section: Three Ways In Which Local Government Decision‐making Competimentioning

confidence: 99%

Effect of local government decision‐making competition on carbon emissions: Evidence from China's three urban agglomerations

2020

Bus Strat Env

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Analyzing the effect of local government decision‐making competition on regional carbon emissions is important for reducing carbon emissions in rapidly urbanizing areas. Taking the energy rebound effect into account, this study analyzes the effect on carbon emissions of competition between local governments in decision making. Focusing on China's three urban agglomerations, this study further discusses how to avoid this influence. The results show that local government decision‐making competition is one of the main causes of the regional “green paradox”; the effect of local government decision‐making competition on carbon emissions has significant regional heterogeneity and spatial dependence, and the short‐term energy rebound effect is greater than the long‐term energy rebound effect; and local government decision‐making competition has three effects on carbon emissions that also have interaction and substitution effects between them: factor market distortion, investment bias, and the “race to the bottom” of environmental policies. However, four measures can reduce the effect of local government decision‐making competition on carbon emissions: one, improving the performance evaluation system of local governments; two, promoting the marketization of factor prices; three, improving both the energy efficiency and upgrading of industrial structures; and four, introducing macro emission reduction policies that allow the central government to intervene directly.

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“…In the presence of an environmentally conscious consumer, however, if the emissions are high, consumer demand will decrease, so the retailer will appreciate the manufacturer's reducing the carbon emissions per product unit. Some literatures give the conclusion through their studies (Heyes & Kapur, 2012;Li et al, 2018;Yalabik & Fairchild, 2011), but some research thinks that consumer are concerned with price more than carbon emissions. For example, the BIS(2010) report indicates that consumers pay more attention to cost savings than carbon emissions.…”

Section: Problem Description and Model Assumptionsmentioning

confidence: 99%

“…If a CONTACT Yunlong Liu longyun768@126.com; Qiankun Song qiankunsong@163.com product's emission is high, a firm's social responsibility is low, and it can expect consumer punishment from production through sale; for example, by paying a high price to attract and motivate employees, which raises production costs and impacts sales (Heyes & Kapur, 2012). If the product is green, on the other hand, because of the consumer's environment preference, consumer demand is linked with carbon emissions of per product unit (Li et al, 2018), consumers may be willing to pay a premium price (Arora & Gangopadhyay, 1995), which means that the manufacturer's efforts to reduce carbon emissions are also enjoyed by the retailer, who becomes a free rider. As a result, some firms are calling for other stakeholders to also reduce related carbon emissions so as to lower emissions overall.…”

Section: Introductionmentioning

confidence: 99%

Carbon emissions reduction and transfer in supply chains under A cap-and-trade system with emissions-sensitive demand

Liu

Huang

Song

et al. 2018

Systems Science & Control Engineering

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Although 'Cap-and-trade' mainly constrains the manufacturer, the decision of the manufacturer's emission reduction will affect the decision of the whole supply chain. In this paper, we investigate manufacturer and retailer's decision under decentralized decision and centralized decision and taking into account the impact of carbon price and consumer environmental consciousness. Specially, we analyse the condition of whether a manufacturer transfers the emission reduction task to retailer. Besides, we use computational experiments to analyse the sensitivity by changing the cost function. Through the research, we have some findings: under a decentralized decision, manufacturer transfers emissions reduction task in more times, if the manufacturer transfers the emissions reduction task, the effectiveness of the emissions reduction, demand, retailer's revenue per product and consumer welfare decrease. Under centralized decision, the manufacturer does not transfer emissions reduction task all time, which is affected by emissions reduction cost of the manufacturer and retailer, carbon price and consumer environmental consciousness. In addition, emissions reduction cost function is not the sensitivity factor.

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Transmission mechanism between energy prices and carbon emissions using geographically weighted regression

Cited by 49 publications

References 44 publications

Spatiotemporal Characteristics of Bike-Sharing Usage around Rail Transit Stations: Evidence from Beijing, China

Spatiotemporal Characteristics of Bike-Sharing Usage around Rail Transit Stations: Evidence from Beijing, China

Effect of local government decision‐making competition on carbon emissions: Evidence from China's three urban agglomerations

Carbon emissions reduction and transfer in supply chains under A cap-and-trade system with emissions-sensitive demand

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