Determining the Factors Affecting a Career Shifter’s Use of Software Testing Tools amidst the COVID-19 Crisis in the Philippines: TTF-TAM Approach

Ardvin Kester S. Ong, Yogi Tri Prasetyo (), Ralph Andre C. Roque, Jan Gabriel I. Garbo, Kirstien Paola E. Robas, Satria Fadil Persada and Reny Nadlifatin
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Ardvin Kester S. Ong: School of Industrial Engineering and Engineering Management, Mapúa University, Philippines 658 Muralla St., Intramuros, Manila 1002, Philippines
Yogi Tri Prasetyo: School of Industrial Engineering and Engineering Management, Mapúa University, Philippines 658 Muralla St., Intramuros, Manila 1002, Philippines
Ralph Andre C. Roque: School of Industrial Engineering and Engineering Management, Mapúa University, Philippines 658 Muralla St., Intramuros, Manila 1002, Philippines
Jan Gabriel I. Garbo: School of Electrical, Electronics, and Computer Engineering, Mapúa University, Philippines 658 Muralla St., Intramuros, Manila 1002, Philippines
Kirstien Paola E. Robas: School of Industrial Engineering and Engineering Management, Mapúa University, Philippines 658 Muralla St., Intramuros, Manila 1002, Philippines
Satria Fadil Persada: Entrepreneurship Department, BINUS Business School Undergraduate Program, Bina Nusantara University, Jakarta 11480, Indonesia
Reny Nadlifatin: Department of Information Systems, Institut Teknologi Sepuluh Nopember, Kampus ITS Sukolilo, Surabaya 60111, Indonesia

Sustainability, 2022, vol. 14, issue 17, 1-24

Abstract: The restrictions of the ongoing COVID-19 pandemic resulted in the downturn of various industries and in contrast a massive growth of the information technology industry. Consequently, more Filipinos are considering career changes to earn a living. However, more people still need to be upskilled. This study combines the extended Technology Acceptance Model and Task Technology Fit framework to determine factors affecting a career shifter’s use of software testing tools and its impact on perceived performance impact amidst the COVID-19 pandemic in the Philippines. A total of 150 software testers voluntarily participated and accomplished an online questionnaire consisting of 39 questions. The Structural Equation Modeling and Deep Learning Neural Network indicated that Task Technology Fit had a higher effect on Perceived Performance Impact. Moreover, Task Technology Fit positively influenced Perceived Usefulness. Computer Self-Efficacy was a strong predictor of Perceived Ease of Use. Perceived Ease of Use confirmed the Technology Acceptance Model framework as a strong predictor of Actual System Use. Intention to Use, Perceived Usefulness, Actual Use, and Subjective Norm were also significant factors affecting Perceived Performance Impact. This study is the first to explore the career shifter’s use of software testing tools in the Philippines. The framework would be very valuable in enhancing government policies for workforce upskilling, improving the private sector’s training and development practices, and developing a more competitive software testing tool that would hasten users’ adaptability. Lastly, the methodology, findings, and framework could be applied and extended to evaluate other technology adoption worldwide.

Keywords: structural equation modeling; deep neural network; task technology fit; career shifter; software testing tools (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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