Acceptance of Mobile Technology for Citizen Science

Dutch water management is considered highly efficient, but it faces a lack of public awareness and other certain physical challenges. One proposed strategy to deal with these challenges includes increasing citizen participation and citizen science using mobile devices in particular. Such mobile crowd sensing (MCS) can be used to enhance canal operations and model predictive control (MPC) by nonexperts. The data collector often pushes implementations, and little knowledge and experience from the field of product design is used. This can lead to underperformance both with regards to the technology and the volunteer citizens. This study uses an adapted Technology Acceptance Model 3 (TAM3) to survey Dutch citizens’ intentions while operating a mock-up smartphone application to identify key drivers of their acceptance in an early design phase. Included among the important drivers of citizens’ behavioral intentions (BI) are usefulness, relevance to the task, and the demonstrability of benefits. These insights can possibly unveil validated design criteria for future MCS applications. Such validated criteria can not only prevent the underperformance of citizen science from a volunteer point of view, but it can also affect the performance of the MCS as well.