Factors affecting low-carbon consumption behavior of urban residents: A comprehensive review

Ding, Zhihua; Jiang, Xin; Liu, Zhenhua; Long, Ruyin; Xu, Zinan; Cao, Qingren

doi:10.1016/j.resconrec.2018.01.013

Cited by 157 publications

(83 citation statements)

References 97 publications

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“…These factors significantly affect residents' levels of low-carbon energy use and consumption behavior. Similar to the results of Ding, Yang, and others [8,19], women more commonly present low-carbon behavior in daily energy use and appliance selection owing to differences in their consumption habits and role division. However, according to Table 4, women tend to choose high-carbon travel modes such as motorization.…”

Section: Individual-level Variablessupporting

confidence: 84%

“…If we do not consider residential self-selection, then we will overestimate the impact of the built environment on residents' daily life behaviors. Therefore, low-carbon lifestyles and/or behavior influenced by residential self-selection have been paid significant attention [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

“…So, some studies have begun to pay attention to the significant impacts of individuals' attitudes and external environment on their behavior based on the attitudinal-behavior-circumstance (ABC) theory. These studies regard socioeconomic attributes and policy criteria as the external environment and analyzed the impacts of residents' gender, age, education, occupation, monthly income, housing type, environmental policies, and social criteria on low-carbon behaviors [8,14,[17][18][19][20][21]. Ye and Yang suggest that women have higher levels of low-carbon behavior than men in terms of daily energy use at home [17,19].…”

Section: Introductionmentioning

confidence: 99%

“…Nicholls and Ding suggest that residents with high-education have higher levels of low-carbon behavior [14,22]. Ding suggest that civil servants and unit staff have higher levels of low-carbon behavior [8]. Allen and Thogersen suggest that environmental policies and social norms have a positive impact on residents' low-carbon behavior [20,21].…”

Section: Introductionmentioning

confidence: 99%

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Impact of Residential Self-Selection on Low-Carbon Behavior: Evidence from Zhengzhou, China

Zhang

Qin

et al. 2019

Sustainability

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Current resident lifestyles pose a significant threat to urban sustainable development. Therefore, low-carbon behavior is receiving increasing attention from scholars and policy makers. Ascertaining residential self-selection is essential in order to study the relationship between the built environment and travel behavior. While several studies have explored the relationship between the urban form, socioeconomic factors, and travel behavior, only a few of them have studied the impact of self-selection on household energy consumption and other forms of consumption, which are also contribute to household carbon emissions. Using large-scale field surveys of 1,485 households and high-resolution images, sourced from Google Maps in 2018, of Zhengzhou city, the present study estimated the low-carbon level of three kinds of behavior: daily energy use at home, daily travel, and daily consumption. The study investigated the influence factors on low-carbon behavior using the hierarchical linear model. We found that residential self-selection impacts both energy use and daily travel. Residents in some built environments consumed less energy at home and contributed less CO2 emissions through daily travel than others. In particular, individual-level variables significantly affected the low-carbon energy use behavior. The female, elderly, highly educated, married, and working-class residents with children had higher levels of low-carbon energy use. Community-level variables significantly affected the level of low-carbon travel and low-carbon consumption. If residents lived in areas with high density, mixed land use, and high accessibility, their travel mode and consumption behavior would entail low carbon emissions. There is a relationship between individual variables and community variables. Different individual attributes living in the same built environment have different impacts on low-carbon behaviors.

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Section: Individual-level Variablessupporting

confidence: 84%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Impact of Residential Self-Selection on Low-Carbon Behavior: Evidence from Zhengzhou, China

Zhang

Qin

et al. 2019

Sustainability

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“…In the research on carbon inventory management, the focus has been on newsvendor models and EOQ (economic order quantity) models [13][14][15]. Song et al [16] analyzed a newsvendor model and demonstrated that it is possible to achieve multiple targets, including carbon emission reduction, cost saving, and profit improvement at the same time by applying a suitable order policy.…”

Section: Literature Reviewmentioning

confidence: 99%

The Impact of Lead Time Uncertainty on Supply Chain Performance Considering Carbon Cost

Fei

Er-min

et al. 2019

Sustainability

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In supply chain operation practices, lead time uncertainty is a common management issue. Uncertain lead time can lead to increased inventory costs and unstable service levels, which will directly affect the overall operation performance of the supply chain. While considering environmental performance in supply chain, it is important to understand how an uncertain lead time will affect sustainable performance. In this paper, we constructed a supply chain model with stochastic lead time and explored the relationship between uncertain lead time and supply chain performance. We considered carbon cost, inventory cost, and service level as a supply chain performance. System dynamics methodology was employed to observe and explore the dynamic change trend of the overall performance in the complicated supply chain model. This was done under both different levels of lead time standard deviation and different order policies. The results demonstrate how stochastic lead times can significantly increase inventory costs and carbon costs. Therefore, we propose appropriate ordering policies which mitigate the negative impacts of stochastic lead times.

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Analysis of factors influencing carbon emissions of urban households: A case study of old urban community in northern China

Xu,

Wang,

Tian

et al. 2023

Sustainable Development

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CO2 emissions reduction of urban residents is one of the main ways to mitigate climate change. Clarifying the key factors of carbon emissions can provide a reference basis for the government to formulate carbon reduction policies. The old urban community that widely exist in most cities in northern China is taken as the research object. Based on the fuzzy interpretive structural model and structural equation model, a new method is proposed to explore the influencing factors of household carbon emissions (HCEs). It is found that behavior change attitude and low‐carbon personal cognition are the two most important factors affecting HCE. Elderly families, high‐income families, and low‐education families are the groups with higher per capita HCE. Different suggestions were proposed to promote HCE reduction for the high‐income young tenants and low‐income elderly local residents in the community. In addition, by introducing multi‐agent judgment, the coupling model proposed in this study reduces the subjectivity caused by excessive reliance on single agent judgment in previous studies. It enhances the credibility of research conclusions and provides a good methodological reference for research in similar fields.

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Factors affecting low-carbon consumption behavior of urban residents: A comprehensive review

Cited by 157 publications

References 97 publications

Impact of Residential Self-Selection on Low-Carbon Behavior: Evidence from Zhengzhou, China

Impact of Residential Self-Selection on Low-Carbon Behavior: Evidence from Zhengzhou, China

The Impact of Lead Time Uncertainty on Supply Chain Performance Considering Carbon Cost

Analysis of factors influencing carbon emissions of urban households: A case study of old urban community in northern China

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