A Task-Technology Fit Theory Approach of Automated Flood Forecasting Systems for Emergency Responders

Predictive capabilities of technological systems, successful disaster preparedness and disaster response rely on how well response capabilities match the operational needs of disaster responders. This study integrated Task-Technology Fit (TTF) Evaluation Framework for the assessment of automated flood forecasting system in the Nigeria context of emergency management. The framework focused on under-researched aspect of flood forecasting, which often focused on the predictive quality of the forecast, but comparatively less attention has been paid to the operational, infrastructure, institutional and user conditions of where the forecast was used. The proposed framework further incorporated eight dimensions of the Task-Technology Fit theory of Goodhue and Thompson (1995 that related to the operational needs of emergency response agencies. A diagnostic scoring model was suggested for comparison of the technical capacity of an automated forecasting system with operational task requirements, in a multidimensional manner. The framework highlighted task–technology mismatches and serves as a structure for further technical, organizational, infrastructural and training interventions. The study is conceptual in nature and is not validated or empirically derived from the field for TTF scores. The numerical examples given in the framework are only illustrative and hypothetical and are provided to serve the purpose of giving an indication of how the proposed scoring process might work. The study thus theorized an extension of TTF to automated flood forecasting in Nigeria and laid a foundation for the empirical testing of the model in other emergency management contexts.

Task-Technology Fit; Automated Flood Forecasting; Emergency Response; Disaster Management; Nigeria; Socio-Technical Systems; Early Warning Systems.

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