นวัตกรรมระบบสารสนเทศเพื่อสนับสนุนการตัดสินใจในการจัดการฟาร์มกุ้งของเกษตรกรรายย่อยภายใต้กลุ่มสหกรณ์ / ธนภัทร ยีขะเด = Innovative information system for decision support in shrimp farm management of small-scale farmers under cooperative / Thanapat Yeekhaday
This research aims as 1) study information behaviours toward decision support of small scale shrimp farmers under cooperative context 2) develop innovation system for shrimp farmers decision support management tools 3) study shrimp farmers’ technology acceptance and 4) determine the technology commercialization. This research applies mixed method both qualitative and quantitative. The qualitative research applied to understand the context of information behaviours for farm management and decision support. The quantitative research was applied to study the factors influence online collaboration among shrimp farmers’ cooperative from 90 samples. The quantitative also was applied to develop shrimp price forecasting model from 830 data set of 5 years backward (2014-2018) from secondary data that available on web sites by using linear regression method. The result found that 1) shrimp farmers need information for decision support in 7 main tasks are farm site selection, farm business plan, pond management, shrimp management, financial management, farm management, and community or cooperative management. The study also found that trust, effort expectancy, facilitating condition, social influence and partner power are factors influence with online collaboration among shrimp farmers’ cooperative (Adjusted R2 = .514). 2) The study of factors influence shrimp price forecasting = -1759.426-1.066 (weigh/kg.) + 9.881 (Consumer price Index) + 11.135 (Producer price index) -1.835 (Crop production index) + 1.863 (Exchange rate) + 0.002 (Vannamei shrimp production) -1.864 (Diesel price) + (Coefficient value of each moth + 42.448 (in case of January) + 53.286 (in case of February) + 30.325 (in case of March) + 2.057 (in case of April) - 20.070 (in case of May) - 10.085 (in case of June) - 3.180 (in case of July) - 3.320 (in case of August) - 15.877 (in case of September) - 30.390 (in case of October) - 11.835 (in case of November) which this model adjusted R2= 89.7%. Therefor the forecasting model was applied to develop mobile application for farm information management and financial decision support tools. 3) The survey of users’ technology acceptance from 30 samples found that user satisfied with the system in terms of usability, design, system content, security, data support decision, perceived usefulness, and intention to use in Somewhat Satisfied. 4) The non-exclusive licensing is the most appropriate way for technology commercialization with expected payback period is 3.5 years