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| 099 | 9 | _aAIT Thesis no.AB-25-03 | |
| 100 | 1 | _aAuxtero, Kathleen Mae Anino | |
| 245 | 1 | 0 |
_aAssessing farmers' adoption and continuance intention to use a mobile app for agrometeorological forecasts and advisories : _binsights from Thailand and Vietnam |
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_aPathum Thani, Thailand : _bAsian Institute of Technology, _c2025 |
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_a118 leaves : _bill. + _e1online resource |
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_aThesis ; _vno. AB-25-03 |
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| 500 | _aA Thesis submitted in partial fulfillment of the requirements for the degree of Master of Agribusiness Management | ||
| 502 | _aThesis (M. Am.) - Asian Institute of Technology, 2025 | ||
| 520 | _aThe agriculture industry in the Greater Mekong Subregion (GMS) is highly vulnerable to climate variability, making timely and localized weather information critical for informed farm decision-making. In response to this need, a mobile application called ClimaFarm, a digital tool that provides agrometeorological information and agronomic advisories to farmers, was developed. This study then explores smallholder farmers' adoption, usage behavior, and continued use of the ClimaFarm app in Nakhon Phanom, Thailand, and Can Tho, Vietnam. Additionally, the experienced benefits, challenges, and opportunities linked with the app use were also identified. Partial Least Squares Structural Equation Modeling (PLS-SEM) and Binary Logistic Regression (BLR) were used to analyze adoption behavior, while continued use was assessed through an adapted Technology Continuance Theory (TCT) model using PLS-SEM analysis. Findings from 168 respondents revealed that most farmers found the app useful, convenient, and supportive in weather-based decision-making, particularly for planting, irrigation, and fertilizer and pest management. Perceived usefulness (Ý=0.261, p<0.01), trust (Ý=0.280, p<0.1), satisfaction (Ý=0.251, p<0.05), and attitude (Ý=0.247, p<0.05) were significant behavior-specific predictors of continued use, while social influence (Ý=-0.581, p<0.01), and perceived usefulness (Ý=0.440, p<0.1) influenced adoption. Furthermore, socio-demographic factors such as farming experience (Ý=-0.037, p<0.05) and household income (Ý=-0.161, p<0.05) also influenced adoption and continued use, respectively. Key challenges reported included app interface and language difficulties, limited forecast accuracy, and internet connectivity issues. Despite these barriers, the majority of farmers reported positive early impacts, with 85% willing to recommend the app to others. The study offers theoretical contributions to understanding the adoption of digital tools in agriculture and delivers practical advice for app developers, policymakers, and extension providers. It emphasizes the significance of a user-centered design, reliable content, and inclusive implementation strategies in scaling mobile advisory tools for climate-smart agriculture in the GMS. | ||
| 650 | 0 | _aAgricultural applications | |
| 650 | 0 | _aMobile apps | |
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_aCrops and climate _zMekong River Region |
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| 700 | 1 |
_aHimanshu, Sushil Kumar, _eChairperson |
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| 700 | 1 |
_aYaseen, Muhammad, _eExamination Committee |
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| 700 | 1 |
_aPramanik, Malay, _eExamination Committee |
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_aHer Majesty the Queen{u2019}s Scholarship (Thailand), _eScholarship Donor |
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_aAsian Institute of Technology. _tThesis ; _vno. AB-25-03 |
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| 856 | 4 | 0 |
_3Full-Text _uhttp://203.159.5.9/ait-thesis/detail.php?q=B22764 |
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