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Top1. Introduction
The Philippines archipelago is frequently visited by tropical cyclones (TCs) of diverse intensities, hence permanently exposed to natural hazards like extreme flooding. Cinco et al. (2016) found an average of nine TCs crossing the country every year caused innumerable losses to life and properties. Socio-economic damages relating to immense flooding are becoming a world problem. It is a pressing issue even at a household level in countries where disasters often occur. Nonetheless, flood information systems are introduced to help stakeholders minimize the risks of flooding and its impact on the communities.
Flood information systems play a vital role in providing early warnings and diminishing the damage caused by flooding. For the past five years, there has been a rapid rise in the development of flood information systems utilizing geographic information systems (GIS) integrations (Cabrerea & Lee, 2018; Garrote et al., 2020), enhanced visualizations (Vamvakeridou-Lyroudia et al., 2019), big data analytics (Donratanapat, 2019), and even social media (Tkachenko et al., 2017). Notably, these innovations are beneficial in understanding the impending flood calamity as well as in planning. Prior studies use a web-based application such as website or web portals in informing the public regarding flood warnings and advisories in their area (Donratanapat, 2019). Meanwhile, the voluminous availability of data is becoming useful in flood visualization and predictions. Moreover, recent developments in flood management have led to machine learning algorithms in predicting flood occurrence (Al-Juaidi et al., 2018; Lim & Lee, 2018). However, only a few of these systems assimilate flood analytics as an essential tool for decision-making.
Subsequently, the recurrent flooding in the Philippines, particularly in the urban capital, is continually a pressing issue. Moreover, despite the developments in using information systems for flood management efforts, there has been little discussion on the user’s acceptance of such systems in developing countries. This paper presents an investigation on user acceptance of a flood information system by employing a survey based on the Technology Acceptance Model (TAM). Significantly, the TAM model is beneficial in predicting the user acceptance of a developed information system. Using the recent model study by Meechang, 2019, several factors were affecting the perceived usefulness (PU) of the area-BCM, a flood mitigating support system. Likewise, the TAM model has been employed by the previous study in examining the user’s intention to adopt a Geographical Information System (GIS) for emergency management in times of natural disasters (Mirda et al., 2016). information systems.
Finally, suppose the people understand the risk of flooding. In that case, socio-economic losses will be averted, and damages to the property could be reduced, henceforth promoting national security and diminishing casualties in times of flood disasters. Also, assimilation of state-of-the-art technology adds value to flood management and monitoring at the local government level. Hence, this study contributes by addressing a few evidences of user acceptance of flood information systems with analytics in developing countries.
The paper is organized first, with the introduction included in the first section, followed by the background and review of related literature in section 2. Then, research methods in section 3, analysis and discussion in section 4, and the presentation of significant findings in the last section.