User Acceptance of Agricultural Market Information System With Analytics

Abstract

An agricultural market information system with analytics is considered valuable in farming activities in developing countries. However, due to several factors, the agricultural market information system with analytics adoption remains limited. The paper aims to understand the factors that may influence users' intention to adopt the agricultural market information system with analytics in the coffee farming sector. The developed framework considered two external variables—computer self-efficacy and system complexity based on the technology acceptance model—through a field survey conducted in coffee farm sites and rural agriculture offices in the Philippines. The results show that the system's perceived usefulness has nothing to do with the computer self-efficacy and system complexity. On the other hand, the perceived ease of use is affected by computer self-efficacy alone and not with system complexity. Also, the perceived ease of use affects both the perceived usefulness and attitude towards using the system. Thus, solving the issues of perceived ease of use by providing training to gain computer skills will ensure the positive implications of perceived usefulness and attitude towards using. This study also discussed some practical and research implications.

Factors That Influence the Intention of Smallholder Rice Farmers to Adopt Cleaner Production Practices: An Empirical Study of Precision Agriculture Adoption

“…About 66% of farms rely on manual harvesting; only 10.8% use machinery ( Cirera et al, 2021 ). The World Bank reports that advanced irrigation systems are mostly used by larger-size-agricultural firms of larger size and are unpopular amongst most Vietnamese farming households ( Cirera et al, 2021 ; Tolentino & Hernandez, 2020 ). Vietnam’s high-tech agriculture lags behind other countries, despite a long agricultural history.…”

“…Several studies have addressed factors affecting adoption of general ICT applications for farming in Vietnam ( Lampach et al, 2021 ; Tran et al, 2019 ) and other developing countries ( Burkitbayeva et al, 2020 ; Kante et al, 2019 ; Tolentino & Hernandez, 2020 ). However, these findings do not fully explain the complex, unique nature of PA ( Nguyen et al, 2022 ): while other general ICTs require only a single system or device installation, PA technology often requires a systematic combination of diagnostic tools (GPS, GIS, and remote sensing) and applicative tools (variable rate application, unmanned vehicles) to ensure maximum benefits from synergizing crop monitoring and precise control of nutrient inputs ( Chawade et al, 2019 ; Zhao et al, 2020 ).…”