摘要
推广被动式房屋被认为是解决中国能源危机、减轻环境压力的有效并且符合可持续性的一条途径。基于计划行为理论,加入环境关注、政府激励因素来研究河北省城镇居民被动房购买行为,并使用收集的197名河北省消费者调查问卷来检验所构建的预测模型。从PLS-SEM模型结果得出,感知行为控制、主观规范还有购买态度对购买意图产生的影响是积极的,政府激励能够正向影响感知行为控制,环境关注也被证实能够正向影响购买态度。基于政府激励对购买意愿的影响作用,建立政府与购房者之间演化博弈模型,使用Python进行购房者成本收益分析,结果表明被动房增量成本变动会引起购房者决策变化,而补贴金额变动不会影响购房者决策变化。最后对被动房的未来发展提出对策建议。
The promotion of passive housing is considered to be an effective and sustainable way to solve China's energy crisis and reduce environmental pressure.Based on the theory of planned behavior,this paper studies the passive housing purchase behavior of urban residents in Hebei Province by adding environmental concerns and government incentives,and collects 197 consumers'questionnaires from Hebei Province to test the prediction model.From the results of PLS-SEM model,we can see that perceived behavior control,subjective norms and purchase attitude have a positive impact on purchase intention.Government incentives can positively affect perceived behavior control,and environmental concerns can positively affect purchase attitude.Based on the influence of government incentives on purchase intention.Based on the influence of government incentive on purchase intention,an evolutionary game model between government and buyers will be established,and the cost-benefit of the buyers will be analyzed by using python.The results show that the change of incremental cost of the passive party will lead to the change of buyers'decision-making,while the change of subsidy amount will not affect the change of buyers'decision-making.Finally,the paper puts forward some suggestions for the future development of passive housing.
作者
任伟
邹晓丹
王亚晓
REN Wei;ZOU Xiao-dan;WANG Ya-xiao(College of Economics, North China University of Science and Technology, Tangshan Hebei 063210, China)
出处
《华北理工大学学报（社会科学版）》
2021年第6期34-43,共10页
Journal of North China University of Science and Technology(Social Science Edition)
基金
河北省教育厅青年基金项目“人口结构转变背景下河北省住房需求演化机理与供给优化匹配研究”(编号:SQ201102)。
关键词
被动房
购买行为
影响因素
演化博弈
passive house
purchase behavior
influencing factors
evolutionary game
