IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i9p5643-d809390.html
   My bibliography  Save this article

Factors Influencing the Perceived Effectiveness of COVID-19 Risk Assessment Mobile Application “MorChana” in Thailand: UTAUT2 Approach

Author

Listed:
  • Nattakit Yuduang

    (School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
    School of Graduate Studies, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines)

  • Ardvin Kester S. Ong

    (School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines)

  • Yogi Tri Prasetyo

    (School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines)

  • Thanatorn Chuenyindee

    (School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
    School of Graduate Studies, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
    Department of Industrial Engineering and Aviation Management, Navaminda Kasatriyadhiraj Royal Air Force Academy, Bangkok 10220, Thailand)

  • Poonyawat Kusonwattana

    (School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
    School of Graduate Studies, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines)

  • Waranya Limpasart

    (Department of Chemistry, Faculty of Science, Mahidol University, Bangkok 10400, Thailand)

  • Thaninrat Sittiwatethanasiri

    (Department of Industrial Engineering and Aviation Management, Navaminda Kasatriyadhiraj Royal Air Force Academy, Bangkok 10220, Thailand)

  • Ma. Janice J. Gumasing

    (School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
    School of Graduate Studies, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines)

  • Josephine D. German

    (School of Industrial Engineering and Engineering Management, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines
    School of Graduate Studies, Mapúa University, 658 Muralla St., Intramuros, Manila 1002, Philippines)

  • Reny Nadlifatin

    (Department of Information Systems, Institut Teknologi Sepuluh Nopember, Kampus ITS Sukolilo, Surabaya 60111, Indonesia)

Abstract

COVID-19 contact-tracing mobile applications have been some of the most important tools during the COVID-19 pandemic. One preventive measure that has been incorporated to help reduce the virus spread is the strict implementation of utilizing a COVID-19 tracing application, such as the MorChana mobile application of Thailand. This study aimed to evaluate the factors affecting the actual usage of the MorChana mobile application. Through the integration of Protection Motivation Theory (PMT) and Unified Theory of Acceptance and Use of Technology (UTAUT2), latent variables such as performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating conditions (FC), hedonic motivation (HM), habit (HB), perceived risk (PCR), self-efficacy (SEF), privacy (PR), trust (TR), and understanding COVID-19 (U) were considered to measure the intention to use MorChana (IU) and the actual usage (AU) of the mobile application. This study considered 907 anonymous participants who voluntarily answered an online self-administered survey collected via convenience sampling. The results show that IU presented the highest significant effect on AU, followed by HB, HM, PR, FC, U, SEF, PE, EE, TR, and SI. This is evident due to the strict implementation of using mobile applications upon entering any area of the vicinity. Moreover, PCR was not seen to be a significant latent factor affecting AU. This study is the first to have evaluated mobile contact tracing in Thailand. The integrated framework can be applied and extended to determine factors affecting COVID-19 tracing applications in other countries. Moreover, the findings of this study could be applied to other health-related mobile applications worldwide.

Suggested Citation

  • Nattakit Yuduang & Ardvin Kester S. Ong & Yogi Tri Prasetyo & Thanatorn Chuenyindee & Poonyawat Kusonwattana & Waranya Limpasart & Thaninrat Sittiwatethanasiri & Ma. Janice J. Gumasing & Josephine D. , 2022. "Factors Influencing the Perceived Effectiveness of COVID-19 Risk Assessment Mobile Application “MorChana” in Thailand: UTAUT2 Approach," IJERPH, MDPI, vol. 19(9), pages 1-19, May.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:9:p:5643-:d:809390
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/9/5643/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/9/5643/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chen-Wei Yu & Cheng-Min Chao & Che-Fu Chang & Rueg-Juen Chen & Po-Chung Chen & Yi-Xuan Liu, 2021. "Exploring Behavioral Intention to Use a Mobile Health Education Website: An Extension of the UTAUT 2 Model," SAGE Open, , vol. 11(4), pages 21582440211, October.
    2. Piyapong Janmaimool, 2017. "Application of Protection Motivation Theory to Investigate Sustainable Waste Management Behaviors," Sustainability, MDPI, vol. 9(7), pages 1-16, June.
    3. Yogi Tri Prasetyo & Ardvin Kester S. Ong & Giero Krissianne Frances Concepcion & Francheska Mikaela B. Navata & Raphael Andrei V. Robles & Isaiash Jeremy T. Tomagos & Michael Nayat Young & John Franci, 2021. "Determining Factors Affecting Acceptance of E-Learning Platforms during the COVID-19 Pandemic: Integrating Extended Technology Acceptance Model and DeLone & McLean IS Success Model," Sustainability, MDPI, vol. 13(15), pages 1-16, July.
    4. Badran, Mona Farid, 2019. "eHealth in Egypt: The demand-side perspective of implementing electronic health records," Telecommunications Policy, Elsevier, vol. 43(6), pages 576-594.
    5. Donald Amoroso & Ricardo Lim & Francisco L. Roman, 2021. "Developing and Testing a Smartphone Dependency Scale Assessing Addiction Risk," International Journal of Risk and Contingency Management (IJRCM), IGI Global, vol. 10(4), pages 14-38, October.
    6. Ignacio Rodríguez-Rodríguez & José-Víctor Rodríguez & Niloofar Shirvanizadeh & Andrés Ortiz & Domingo-Javier Pardo-Quiles, 2021. "Applications of Artificial Intelligence, Machine Learning, Big Data and the Internet of Things to the COVID-19 Pandemic: A Scientometric Review Using Text Mining," IJERPH, MDPI, vol. 18(16), pages 1-29, August.
    7. Alam, Mohammad Zahedul & Hu, Wang & Kaium, Md Abdul & Hoque, Md Rakibul & Alam, Mirza Mohammad Didarul, 2020. "Understanding the determinants of mHealth apps adoption in Bangladesh: A SEM-Neural network approach," Technology in Society, Elsevier, vol. 61(C).
    8. Ramon Palau-Saumell & Santiago Forgas-Coll & Javier Sánchez-García & Emilio Robres, 2019. "User Acceptance of Mobile Apps for Restaurants: An Expanded and Extended UTAUT-2," Sustainability, MDPI, vol. 11(4), pages 1-24, February.
    9. Duarte, Paulo & Pinho, José Carlos, 2019. "A mixed methods UTAUT2-based approach to assess mobile health adoption," Journal of Business Research, Elsevier, vol. 102(C), pages 140-150.
    10. Essam A. Rashed & Akimasa Hirata, 2021. "Infectivity Upsurge by COVID-19 Viral Variants in Japan: Evidence from Deep Learning Modeling," IJERPH, MDPI, vol. 18(15), pages 1-15, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ardvin Kester S. Ong & Yogi Tri Prasetyo & Ralph Andre C. Roque & Jan Gabriel I. Garbo & Kirstien Paola E. Robas & Satria Fadil Persada & Reny Nadlifatin, 2022. "Determining the Factors Affecting a Career Shifter’s Use of Software Testing Tools amidst the COVID-19 Crisis in the Philippines: TTF-TAM Approach," Sustainability, MDPI, vol. 14(17), pages 1-24, September.
    2. Ardvin Kester S. Ong & Yogi Tri Prasetyo & Klint Allen Mariñas & Jehorom Px Alegre Perez & Satria Fadil Persada & Reny Nadlifatin & Thanatorn Chuenyindee & Thapanat Buaphiban, 2022. "Factors Affecting Customer Satisfaction in Fast Food Restaurant “Jollibee” during the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(22), pages 1-19, November.
    3. Ardvin Kester S. Ong & Yogi Tri Prasetyo & Nattakit Yuduang & Reny Nadlifatin & Satria Fadil Persada & Kirstien Paola E. Robas & Thanatorn Chuenyindee & Thapanat Buaphiban, 2022. "Utilization of Random Forest Classifier and Artificial Neural Network for Predicting Factors Influencing the Perceived Usability of COVID-19 Contact Tracing “MorChana” in Thailand," IJERPH, MDPI, vol. 19(13), pages 1-28, June.
    4. Ma. Janice J. Gumasing & Francee Mae F. Castro, 2023. "Determining Ergonomic Appraisal Factors Affecting the Learning Motivation and Academic Performance of Students during Online Classes," Sustainability, MDPI, vol. 15(3), pages 1-29, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ardvin Kester S. Ong & Yogi Tri Prasetyo & Nattakit Yuduang & Reny Nadlifatin & Satria Fadil Persada & Kirstien Paola E. Robas & Thanatorn Chuenyindee & Thapanat Buaphiban, 2022. "Utilization of Random Forest Classifier and Artificial Neural Network for Predicting Factors Influencing the Perceived Usability of COVID-19 Contact Tracing “MorChana” in Thailand," IJERPH, MDPI, vol. 19(13), pages 1-28, June.
    2. Su-Chen(Cecilia) Lin & Mei-Chen Chuang & Chen-Yuan Huang & Chia-En Liu, 2023. "Nursing Staff’s Behavior Intention to Use Mobile Technology: An Exploratory Study Employing the UTAUT 2 Model," SAGE Open, , vol. 13(4), pages 21582440231, November.
    3. Nattakit Yuduang & Ardvin Kester S. Ong & Nicole B. Vista & Yogi Tri Prasetyo & Reny Nadlifatin & Satria Fadil Persada & Ma. Janice J. Gumasing & Josephine D. German & Kirstien Paola E. Robas & Thanat, 2022. "Utilizing Structural Equation Modeling–Artificial Neural Network Hybrid Approach in Determining Factors Affecting Perceived Usability of Mobile Mental Health Application in the Philippines," IJERPH, MDPI, vol. 19(11), pages 1-19, May.
    4. Thanatorn Chuenyindee & Ardvin Kester S. Ong & Yogi Tri Prasetyo & Satria Fadil Persada & Reny Nadlifatin & Thaninrat Sittiwatethanasiri, 2022. "Factors Affecting the Perceived Usability of the COVID-19 Contact-Tracing Application “Thai Chana” during the Early COVID-19 Omicron Period," IJERPH, MDPI, vol. 19(7), pages 1-16, April.
    5. Arfi, Wissal Ben & Nasr, Imed Ben & Kondrateva, Galina & Hikkerova, Lubica, 2021. "The role of trust in intention to use the IoT in eHealth: Application of the modified UTAUT in a consumer context," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    6. Yu-Sheng Kao & Kazumitsu Nawata & Chi-Yo Huang, 2019. "An Exploration and Confirmation of the Factors Influencing Adoption of IoT-Based Wearable Fitness Trackers," IJERPH, MDPI, vol. 16(18), pages 1-31, September.
    7. Chen-Wei Yu & Cheng-Min Chao & Che-Fu Chang & Rueg-Juen Chen & Po-Chung Chen & Yi-Xuan Liu, 2021. "Exploring Behavioral Intention to Use a Mobile Health Education Website: An Extension of the UTAUT 2 Model," SAGE Open, , vol. 11(4), pages 21582440211, October.
    8. Mengyao Zhang & Hasliza Hassan & Melissa Wendy Migin, 2023. "Exploring the Consumers’ Purchase Intention on Online Community Group Buying Platform during Pandemic," Sustainability, MDPI, vol. 15(3), pages 1-13, January.
    9. Alessandro Concari & Gerjo Kok & Pim Martens, 2020. "A Systematic Literature Review of Concepts and Factors Related to Pro-Environmental Consumer Behaviour in Relation to Waste Management Through an Interdisciplinary Approach," Sustainability, MDPI, vol. 12(11), pages 1-50, May.
    10. Sharma, Mahak & Antony, Rose & Sehrawat, Rajat & Cruz, Angel Contreras & Daim, Tugrul U., 2022. "Exploring post-adoption behaviors of e-service users: Evidence from the hospitality sector /online travel services," Technology in Society, Elsevier, vol. 68(C).
    11. Farida Saleem & Ahmad Adeel & Rizwan Ali & Shabir Hyder, 2018. "Intentions to adopt ecopreneurship: moderating role of collectivism and altruism," Entrepreneurship and Sustainability Issues, VsI Entrepreneurship and Sustainability Center, vol. 6(2), pages 517-537, December.
    12. Agus Sugiarto & Cheng-Wen Lee & Andrian Dolfriandra Huruta & Christine Dewi & Abbott Po Shun Chen, 2022. "Predictors of Pro-Environmental Intention and Behavior: A Perspective of Stimulus–Organism–Response Theory," Sustainability, MDPI, vol. 14(23), pages 1-17, December.
    13. Ardvin Kester S. Ong & Jelline C. Cuales & Jose Pablo F. Custodio & Eisley Yuanne J. Gumasing & Paula Norlene A. Pascual & Ma. Janice J. Gumasing, 2023. "Investigating Preceding Determinants Affecting Primary School Students Online Learning Experience Utilizing Deep Learning Neural Network," Sustainability, MDPI, vol. 15(4), pages 1-24, February.
    14. Sami S. Binyamin & Md. Rakibul Hoque, 2020. "Understanding the Drivers of Wearable Health Monitoring Technology: An Extension of the Unified Theory of Acceptance and Use of Technology," Sustainability, MDPI, vol. 12(22), pages 1-20, November.
    15. Ma. Janice J. Gumasing & Ardvin Kester S. Ong & Maria Angelica D. Bare, 2022. "User Preference Analysis of a Sustainable Workstation Design for Online Classes: A Conjoint Analysis Approach," Sustainability, MDPI, vol. 14(19), pages 1-23, September.
    16. Xinlu Wen & Marios Sotiriadis & Shiwei Shen, 2023. "Determining the Key Drivers for the Acceptance and Usage of AR and VR in Cultural Heritage Monuments," Sustainability, MDPI, vol. 15(5), pages 1-24, February.
    17. Chakraborty, Debarun & Paul, Justin, 2023. "Healthcare apps’ purchase intention: A consumption values perspective," Technovation, Elsevier, vol. 120(C).
    18. Alam, Mohammad Zahedul & Hu, Wang & Kaium, Md Abdul & Hoque, Md Rakibul & Alam, Mirza Mohammad Didarul, 2020. "Understanding the determinants of mHealth apps adoption in Bangladesh: A SEM-Neural network approach," Technology in Society, Elsevier, vol. 61(C).
    19. Ma. Janice J. Gumasing & Francee Mae F. Castro, 2023. "Determining Ergonomic Appraisal Factors Affecting the Learning Motivation and Academic Performance of Students during Online Classes," Sustainability, MDPI, vol. 15(3), pages 1-29, January.
    20. Cobelli, Nicola & Cassia, Fabio & Donvito, Raffaele, 2023. "Pharmacists' attitudes and intention to adopt telemedicine: Integrating the market-orientation paradigm and the UTAUT," Technological Forecasting and Social Change, Elsevier, vol. 196(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:9:p:5643-:d:809390. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.