The objective of this study were to analyze the key factors in technology acceptance targeted for the participation farmer who does some degree recognition of innovative technologies through New Technology Demonstration Projects of Agricultural Extens...
The objective of this study were to analyze the key factors in technology acceptance targeted for the participation farmer who does some degree recognition of innovative technologies through New Technology Demonstration Projects of Agricultural Extension Service.
These findings implied that if innovative farmers were targeted to adopt innovations, other farmers would soon follow, speeding up the adoption of new agricultural practices. The idea was simple and compelling, and it provided the basis for a model of agricultural development that the Extension Service continues to use today.
The present research develops and tests a theoretical extension of the Technology Acceptance Model(TAM) that explains perceived usefulness and usage intentions in terms of Adopters characteristics and Innovations characteristics. Both characteristics of adopters (innovativeness, realibility, output quality) and innovations characteristics(usefulness, ease of use) significantly influenced continuous usage intention. The major results of the study are as follows.
At First, the main factors of technology acceptance were divided into six sub-project fields including rice, upland crop, vegetable, fruit, flower and livestock by crop.
At all points of measurement, Rice, upland crop, Fruit and Livestock usage decisions were more strongly influenced by their perceptions of innovativeness. In contrast, Vegetable and Fruit were more strongly influenced by perceptions of trust.
Second, the key factors of technology acceptance were classified mechanical technology, biological technology and chemical technology according to agricultural technology characteristics. At all three points of measurement, compared to biological technology, mechanical technology usage decisions were more strongly influenced by their perceptions of innovativeness and trust. In contrast, biological technology were more strongly influenced by perceptions of usefulness and technical support. The other side, usefulness and technical supports are positively related to the continuous usage intention to chemical technology.
Finally, the key factors of technology acceptance were classified by 'Self- sufficiency farmer', 'Top farmer' and 'Farmer with scale extension' according to farm's types and farming characteristics.
At all three points of measurement, 'Farmer with scale extension' usage decisions were more strongly influenced by their perceptions of technical support. In contrast, 'Self- sufficiency farmer' were more strongly influenced by perceptions of usefulness and trust.
These findings advance theory and contribute to be foundation for future research aimed at improving our understanding of adopter acceptance behavior.