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|Other Titles: ||Public perceived risk toward genetically modified foods|
|Authors: ||劉航宇;Liou, Hang-Yu|
李月華;Lee, Yueh-Hua;趙慕芬;Chao, Mu-Fen
|Keywords: ||社會信任;知覺風險;知覺利益;基因接受度模型;結構方程模式(SEM);Social Trust;perceived risk;Perceived Benefits;Genes Acceptance Model;Structural Equation Modeling (SEM)|
|Issue Date: ||2015-05-04 09:51:06 (UTC+8)|
The attitudes and perceived risk of GM foods toward people will affect it''s consumer behavior. To investigate the effects of perceived risks in GM food, most researchers use the gene technology acceptance model to measure the relationship of path analysis. More commonly used variables are the degree of trust and knowledge, and it have an impact on perceived risk and perceived benefits respectively, thereby affecting the attitude of GM. In this study, refer to this model and add a new dimension (intergenerational influence), the purpose is to understand the relationship about intergenerational influence, food neophobia, social trust, GM knowledge, perceived risk, perceived benefit and behavioral intentions.
In this study, samples taken from Taiwan, we retrieved 423 valid samples. First we start pilot test to identify the item of reliability and validity, then using confirmatory factor analysis to determine the factor structure between variables and potential variables. In the end, we use path analysis to assess the relationship between variables of structural equation model.
Our study developed a structural model ,and the results of structural equation modeling analysis give evidence that GM knowledge and intergenerational influence have positive impacts on the perceived risk,but social trust have negative impact on the perceived benefits. while the perceived risk and food neophobia have negative impacts on the behavioral intention,but the perceived benefits have positive impacts on the behavioral intention. The contribution of this study is that more understanding the mechanism between perception and behavior intention, and our study try to add a new dimension to probe the structural model, in addition, our study by clustering groups to understand the impact of differences. Our Study included management implications and recommends for manufacturers and government, as well as the future direction of research.
|Appears in Collections:||[企業管理學系暨研究所] 學位論文|
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