Determining factors affecting the perceived usability of air pollution detection mobile application "AirVisual" in Thailand: A structural equation model forest classifier approach

Ardvin Kester S Ong; Yogi Tri Prasetyo; Poonyawat Kusonwattana; Klint Allen Mariñas; Nattakit Yuduang; Thanatorn Chuenyindee; Kirstien Paola E Robas; Satria Fadil Persada; Reny Nadlifatin

doi:10.1016/j.heliyon.2022.e12538

Determining factors affecting the perceived usability of air pollution detection mobile application "AirVisual" in Thailand: A structural equation model forest classifier approach

Heliyon. 2022 Dec 22;8(12):e12538. doi: 10.1016/j.heliyon.2022.e12538. eCollection 2022 Dec.

Authors

Affiliations

¹ School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines.
² International Program in Engineering for Bachelor, Yuan Ze University, 135 Yuan-Tung Road, Chung-Li 32003, Taiwan.
³ Department of Industrial Engineering and Management, Yuan Ze University, 135 Yuan-Tung Road, Chung-Li 32003, Taiwan.
⁴ Department of Industrial Engineering, Faculty of Engineering, North-Chiang Mai University, Chiang Mai 50230, Thailand.
⁵ Department of Industrial and Systems Engineering, Chung Yuan Christian University, Taoyuan 320, Taiwan.
⁶ Department of Industrial Engineering and Aviation Management, Navaminda Kasatriyadhiraj Royal Air Force Academy, Bangkok, 10220, Thailand.
⁷ Entrepreneurship Department, BINUS Business School Undergraduate Program, Bina Nusantara University, Jakarta 11480, Indonesia.
⁸ Department of Information Systems, Institut Teknologi Sepuluh Nopember, Kampus ITS Sukolilo, Surabaya 60111, Indonesia.

Abstract

Air pollution has been evident worldwide. It presented numerous pieces of evidence that affect health-related adverse effects causing diseases and even death and the development of technology has helped monitor the exposure of people to air pollution. This research analyzed factors affecting the perceived usability of air pollution detection on the 'AirVisual' mobile application based on the integrated model of Protection Motivation Theory (PMT) and Unified Theory of Acceptance and Use of Technology (UTAUT2). A total of 416 participants voluntarily answered a self-administered survey consisting of adapted constructs covering factors such as Performance expectancy (PE), Effort expectancy (EE), Social influence (SI), Facilitating conditions (FC), Habit (HB), Perceived risk (PR), Perceived trust (PT), Intention to use (IU), and Perceived usability (PU). Structural Equation Modeling and Random Forest Classifier were utilized to determine factors affecting perceived usability of the 'AirVisual' mobile application. The results showed that PE, EE, SI, and FC were key factors leading to very high PU among users. Moreover, IU was seen to be the most significant factor affecting PU, followed by PT, PR, and HB. This study is one of the first studies that considered the evaluation of usability among health-related mobile applications covering air pollution. The results and the framework utilized in this model may be applied to evaluate other factors and applications related to health among people. Lastly, this study can also be extended to evaluate other mobile applications worldwide.

Keywords: Air pollution; Perceived usability; Protection motivation theory; System usability.