Investigating spatially autocorrelated consumer preference for multiple ecolabels: Evidence from a choice experiment
Investigating spatially autocorrelated consumer preference for multiple ecolabels: Evidence from a choice experiment
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调查消费者对多个生态标签的空间自相关偏好:来自选择实验的证据
DOI:
10.1016/j.clrc.2022.100083
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发表时间:
2022
影响因子:
--
通讯作者:
Koichi Kuriyama
中科院分区:
文献类型:
--
作者:
Shinsuke Kyoi;Masaya Fujino;Koichi Kuriyama
This study investigates spatial autocorrelation in consumer preferences for diverse ecolabels, such as certified ecolabel (type I) and non-certified ecolabel (type II). Ecolabels encourage consumers to purchase environmentally friendly products by informing them of production methods, but their impact is still limited. Further exploration of consumer preferences for ecolabels is vital to understand their influences and improve the efficiency of ecolabel policy. Not only the socioeconomic attributes of consumers but also a spatial spillover effect among consumers may influence consumer preferences for ecolabels, but the extent of its influence remains unclear. This study conducted a choice experiment employing multiple ecolabeled rice and obtained spatially structured data. Spatial analysis revealed a positive spatial autocorrelation in consumers' choices, implying that homogeneous behavior would be observed among consumers who are spatially close to each other. This result suggests that consumers in one region would like to purchase ecolabeled rice frequently, whereas consumers in another region would like to decline to purchase it. Therefore, when evaluating the impact of ecolabel policies, ignoring a positive spatial autocorrelation misunderstands the impact of policies. Furthermore, consumers ' preferences are diverse according to the type of ecolabels. Consumers are willing to pay more to certified ecolabels than non-certified ecolabels. This study proposes practical policy implications for more efficient ecolabel policies based on the results.
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DOI:
10.1093/ajae/aar005
发表时间:
2011-04
期刊:
Agricultural & Natural Resource Economics eJournal
影响因子:
--
作者:
D. Thilmany;D. McFadden
通讯作者:
D. Thilmany;D. McFadden
影响因子:
5.8
作者:
K. Veld
通讯作者:
K. Veld
影响因子:
5.4
作者:
Jacob Lahne;A. Trubek
通讯作者:
A. Trubek
影响因子:
4.2
作者:
S. Dekhili;M. A. Achabou
通讯作者:
M. A. Achabou
影响因子:
5.8
作者:
B. Roe;M. Teisl;Corin R. Deans
通讯作者:
B. Roe;M. Teisl;Corin R. Deans