Dairy Farmers’ Intention to Use High-Precision Area-Level Weather Warning Technology in Dairy Farms in Thailand Through an Application on Mobile Phones
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引用次数: 0
Abstract
Data from information technology has been crucial in advancing the agricultural and livestock industries, especially for Thai dairy farms located in tropical regions where sudden weather changes can occur. This study uses the technology acceptance model (TAM) and the innovation diffusion theory (IDT) to predict the Thai dairy farmers’ intention to use a high-precision area-level weather warning technology through a mobile phone application. A questionnaire was collected from dairy farm owners in Thailand’s central and northeastern regions, and the data was analyzed using stepwise multiple linear regression. The main factor influencing the acceptance of this technology was its compatibility with existing technology, and it needed to be available on mobile phones for instant access. The role of technology had to provide dairy farmers with information for decision-making, especially during extreme weather conditions, to mitigate potential damage. Training sessions and workshops on the implementation of this technology were necessary, and young farmers could share content on social media to promote its benefits. Service providers should set up call centers to help dairy farmers make decisions. This study identifies factors that can increase farmers’ intentions to use digital technology. By addressing these factors, the adoption of technology can improve the efficiency and productivity of dairy farming in Thailand.
期刊介绍:
This interdisciplinary journal focuses on the exchange of relevant trends and research results and presents practical experiences gained while developing and testing elements of interactive mobile technologies. It bridges the gap between pure academic research journals and more practical publications. So it covers the full range from research, application development to experience reports and product descriptions. Fields of interest include, but are not limited to: -Future trends in m-technologies- Architectures and infrastructures for ubiquitous mobile systems- Services for mobile networks- Industrial Applications- Mobile Computing- Adaptive and Adaptable environments using mobile devices- Mobile Web and video Conferencing- M-learning applications- M-learning standards- Life-long m-learning- Mobile technology support for educator and student- Remote and virtual laboratories- Mobile measurement technologies- Multimedia and virtual environments- Wireless and Ad-hoc Networks- Smart Agent Technologies- Social Impact of Current and Next-generation Mobile Technologies- Facilitation of Mobile Learning- Cost-effectiveness- Real world experiences- Pilot projects, products and applications