- 期刊
- OpenAccess
Study of Consumers' Acceptance of Eco-friendly Green Food Hotels
並列摘要
This study is different from previous literature, as it uses AI technology, such as the artificial neural network and evolutionary computation techniques to analyze Taiwan's consumers' acceptance of eco-friendly green food hotels by sensor data mining, in order to know the characteristics of the consumption intentions of respondents. First, Grey Relational Analysis (GRA) is used to discuss the acceptance of various domains in the questionnaire and then the GRA performance values of the various domains are used for clustering analysis, in order to know the characteristics of the consumption intentions of different respondents. Finally, the evolutionary computation technique is combined with the artificial neural network to build an eco-friendly hotel acceptance detection model as reference for eco-friendly hotel operators. The findings show that, in the hotel operators' view, increasing the room rate of eco-friendly green food hotels can be accepted by consumers; the consumers agree with the subject of resource recovery; government bodies shall subsidize hotel operators in promoting eco-friendly green food hotels, thus, contributing to the promotion of eco-friendly green food hotels.