Modeling the willingness to pay for energy efficient residence in urban residential sector in China

被引:19
|
作者
Jia, Jun-Jun [1 ]
Wu, Hua-Qing [1 ]
Nie, Hong-Guang [2 ]
Fan, Ying [3 ]
机构
[1] Hefei Univ Technol, Sch Econ, Hefei 230601, Peoples R China
[2] Changchun Univ Sci & Technol, Sch Econ & Management, Changchun 130022, Peoples R China
[3] Beihang Univ, Sch Econ & Management, Beijing 100191, Peoples R China
基金
中国国家自然科学基金;
关键词
Willingness to pay; Energy efficient residence; Residential sector; Consumer choice model; Probit model; Interval regression model; GREEN ELECTRICITY; SAVING MEASURES; TECHNOLOGIES; PREFERENCES; INFORMATION; BEHAVIOR; ADOPTION; POLICY;
D O I
10.1016/j.enpol.2019.111003
中图分类号
F [经济];
学科分类号
02 ;
摘要
Whether and how to share the incremental cost of energy efficient residence compared with common buildings between housing developers and buyers is an urgent problem to be solved in promoting energy efficient residence. This study estimates urban residents' willingness to pay (WTP) for energy efficient residence in Beijing and Changchun in China to provide important reference for this issue. The revised norm-motivated consumer choice model is used to identify the key factors in the two decision-making stages of determining WTP. Based on survey data and using probit and interval regression models, it shows that energy-saving revenue and incremental cost are the key factors affecting whether or not to buy energy efficient residence, and the preference for positive personal image only has a significant positive effect in Beijing. The mean and median WTP of Beijing residents are about 340 Yuan and 405 Yuan per square meter, respectively, whereas those of Changchun residents are about 350 Yuan per square meter. Policies targeting the energy saving and incremental cost of energy efficient residence and tailored to local residents' preferences can stimulate the promotion of energy efficient residence effectively.
引用
收藏
页数:11
相关论文
共 50 条
  • [41] Heating choices and residential willingness to pay for clean heating: Evidence from a household survey in rural China
    Bai, Chunyue
    Zhan, Jinyan
    Wang, Huihui
    Yang, Zheng
    Liu, Huizi
    Liu, Wei
    Wang, Chao
    Chu, Xi
    Teng, Yanmin
    ENERGY POLICY, 2023, 178
  • [42] Empirical analysis on the willingness to pay for energy sports information consumption of Shijiazhuang urban inhabitants
    Liu, Ying
    Wang, Lina
    Guo, Chao
    Energy Education Science and Technology Part A: Energy Science and Research, 2013, 31 (01): : 175 - 178
  • [43] Comparison of Willingness to Pay for Quality Air and Renewable Energy Considering Urban Living Experience
    Zhou, Rui
    Fukuda, Hiroatsu
    Li, You
    Wang, Yafei
    ENERGIES, 2023, 16 (02)
  • [44] Risk preferences and purchase of energy-efficient technologies in the residential sector
    Qiu, Yueming
    Colson, Gregory
    Grebitus, Carola
    ECOLOGICAL ECONOMICS, 2014, 107 : 216 - 229
  • [45] Determinants of and Willingness to Use and Pay for Digital Health Technologies Among the Urban Elderly in Hangzhou, China
    Yang, Keng
    Li, Yang
    Qi, Hanying
    RISK MANAGEMENT AND HEALTHCARE POLICY, 2023, 16 : 463 - 478
  • [46] Assessing the willingness of the public to pay to conserve urban green spaces: The Hangzhou City, China, case
    Chen, Bo
    Bao, Zhiyi
    Zhu, Zhujun
    JOURNAL OF ENVIRONMENTAL HEALTH, 2006, 69 (05) : 26 - 30
  • [47] Public willingness to pay for urban smog mitigation and its determinants: A case study of Beijing, China
    Dong, Kangyin
    Zeng, Xiangang
    ATMOSPHERIC ENVIRONMENT, 2018, 173 : 355 - 363
  • [48] Estimating the willingness to pay for green space services in Shanghai: Implications for social equity in urban China
    Xiao, Yang
    Lu, Yi
    Guo, Yan
    Yuan, Yuan
    URBAN FORESTRY & URBAN GREENING, 2017, 26 : 95 - 103
  • [49] Uncovering the willingness-to-pay for urban green space conservation: A survey of the capital area in China
    Xu, Feng
    Wang, Yating
    Xiang, Nan
    Tian, Jinping
    Chen, Lujun
    RESOURCES CONSERVATION AND RECYCLING, 2020, 162
  • [50] Market penetration modeling of high energy efficiency appliances in the residential sector
    Radpour, Saeidreza
    Mondal, Md Alam Hossain
    Kumar, Amit
    ENERGY, 2017, 134 : 951 - 961