The Effect of Building Electricity Consumption on Residents’ Subjective Well-Being: Evidence from China

Wu, Yidong; Wu, Yanbo; Zhang, Yalin; Wang, Xianzhu; Song, Zisheng

doi:10.3390/buildings12060710

Cited by 12 publications

(4 citation statements)

References 45 publications

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“…The degree of air pollution decreases, and residents’ personal satisfaction significantly improves [ 29 ]. At the same time, residential electricity consumption can improve subjective well-being, narrow the difference between men and women, and improve the problem of educational imbalances [ 30 ].…”

Section: Introductionmentioning

confidence: 99%

Clean Household Energy Consumption and Residents’ Well-Being: Empirical Analysis and Mechanism Test

Ren¹,

Liu²,

Li³

et al. 2022

IJERPH

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Improving well-being is a critical problem for worldwide social progress. Research on well-being effects of clean household energy consumption is of great significance for the realization of United Nation’s Sustainable Development Goals (SDGs). Due to the multifaceted role of clean household energy in enhancing well-being as a sustainable development goal, it has attracted extensive academic attention and research but still needs to be further refined through new perspectives. This paper uses data from the 2018 China Health and Retirement Longitudinal Study to conduct an empirical analysis of clean household energy consumption and residents’ well-being using an ordered probit model, the instrumental variables method, a conditional mixed process (CMP) method, and a mechanism analysis model. The results show that (1) household clean energy consumption contributes to residents’ well-being, and the results remained significant after selecting “Do you have an electric Bicycle?” as an instrumental variable to address the endogeneity question. (2) According to heterogeneity research, women’s wellbeing is impacted by clean energy consumption in the household more than men’s. Only in rural locations can clean household energy consumption significantly boost well-being; urban and suburban areas are unaffected. (3) In the mechanism analysis, health condition and depression played a mediating role on the impact of clean household energy consumption on well-being, and social contact played a moderating role on the impact of clean household energy consumption on well-being. The findings and policy recommendations in this paper are suggestive of how we can improve the well-being of residents in low- and middle-income countries and provide reference values for research in related fields around the world.

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Section: Introductionmentioning

confidence: 99%

Clean Household Energy Consumption and Residents’ Well-Being: Empirical Analysis and Mechanism Test

Ren¹,

Liu²,

Li³

et al. 2022

IJERPH

View full text Add to dashboard Cite

show abstract

“…(3) Similar research on residential buildings in China revealed that inadequate energy supply has led to low life satisfaction in people living in residential buildings irrespective of their age class. (4) As a way of overcoming this energy problem, most of the affected people have resorted to using non-renewable sources of energy such as diesel and kerosene to sustain their homes. (5) The wide use of non-renewable energy is due to its low cost and easy accessibility.…”

Section: Introductionmentioning

confidence: 99%

Optimizing energy consumption in smart homes using GA-LSTM

Akibor Junior Chukwuka,

Bakare-Bolaji Moyosoreoluwa,

Dibba Baboucarr

2024

Int. J. Sci. Res. Arch.

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The need to optimize energy consumption arises from the inadequate energy supply many homes face. However, to optimize energy consumption in a home, one must be equipped with the knowledge of the energy consumption rate and energy supply rate in the home. This paper proposed the use of a Long Short-Term Memory (LSTM) model optimized by Genetic Algorithm (GA) to optimize the energy consumption in a smart home. The model was designed using 8 input variables, which were observed weather information of a given region over a span of 350 days. The data set was split into a training data set and a test data set in the ratio 4:1. Both the baseline LSTM model and our proposed GA-LSTM model was used to train and test the data. The results of the baseline LSTM model showed a Mean Average Percentage Error (MAPE) of 0.15 and a Root Mean Square Error (RMSE) of 0.0007, while our proposed GA-LSTM recorded an MAPE of 0.07 and RMSE of 0.0004. The implication of these results is a better performance of our proposed GA-LSTM model over the baseline LSTM model. This paper demonstrated how the Genetic Algorithm was able to optimize the baseline LSTM model by selecting the best weights during the LSTM training process. The findings of this paper are recommended for smart homes having the capability to monitor energy usage of installed electrical appliances and the ability to predict to weather condition of the region the home is sited.

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“…Furthermore, favorable social relationships, occupational participation, social and cultural orientations, and engagement enhance residents' happiness [19] . In terms of consumption, increasing residents' electricity consumption can increase their happiness [20] . However, these studies have focused more on developed countries, and few have focused on the impact of Internet use on well-being in developing countries.…”

Section: Introductionmentioning

confidence: 99%

Does the use of the internet enhance residents’ well-being?—Evidence from China

Wu,

Meng,

Liu

et al. 2024

Environ. Soc. Psychol.

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Using data from the 2018 Chinese General Social Survey (CGSS), this study empirically examined the impact of Chinese residents’ Internet use on their subjective well-being. The results show that Internet use significantly increases residents’ subjective well-being; the results of the marginal effect show that the increase in Internet use increases the probability of residents choosing “Relatively happy” and “Extremely happy”; further analysis shows that Internet use increases the probability of residents choosing “Relatively happy” and “Extremely happy” through the marginal effect. “Moreover, in the heterogeneity analysis, Internet use significantly increases the subjective happiness of middle-aged people aged 35–60, and increases the subjective happiness of low-education and low-income groups, while rural residents have higher subjective well-being from Internet use relative to urban residents. This study mitigates the estimation bias that may be caused by the sample self-selection problem through propensity score matching (PSM), and conducts a series of robustness tests on the empirical results. Therefore, the government should emphasize the role of Internet use in enhancing residents’ happiness and promoting the happiness effect of Internet use by further improving Internet infrastructure and upgrading residents’ Internet use skills.

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The Effect of Building Electricity Consumption on Residents’ Subjective Well-Being: Evidence from China

Cited by 12 publications

References 45 publications

Clean Household Energy Consumption and Residents’ Well-Being: Empirical Analysis and Mechanism Test

Clean Household Energy Consumption and Residents’ Well-Being: Empirical Analysis and Mechanism Test

Optimizing energy consumption in smart homes using GA-LSTM

Does the use of the internet enhance residents’ well-being?—Evidence from China

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