Implementation of Quick Response (Qr) Code in Indonesian Restaurants: Integration Of Protection Motivation Theory (Pmt) And Theory Of Planned Behavior (Tpb)
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Published:
Jul 27, 2022
Keywords:
QR code; Protection Motivation Theory; Theory of Planned Behavior.
Section
Computer Science
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Abstract
Covid 19 has devastated the restaurant industry, including in Indonesia, which has prompted some of them to transform to improve service quality through the application of QR codes. The purpose of this study is to analyze consumer behavior towards the application of QR codes in restaurants in Indonesia by integrating Protection Motivation Theory (PMT) and Theory of Planned Behavior (TPB). Research data was collected through online questionnaire distribution with a total sample of 215 respondents who met certain criteria. The hypotheses were tested empirically through Smart PLS which met the criteria for the outer model and the inner model. The results of the study revealed that PMT through threat appraisal (perceived severity and perceived vulnerability) and coping appraisal (self-efficacy, response efficacy, and response cost) statistically affected attitudes on the QR code. Furthermore, the integration of PMT and TPB through attitudes to QR codes has been shown to have an effect on intentions to use QR codes. In addition, subjective norms statistically affect behavioral intentions using QR codes and behavioral intentions using QR codes are able to encourage actual behavior.
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How to Cite
saefudin, Sulaiman Kurdi and Nanang Apriliyanto (2022) “Implementation of Quick Response (Qr) Code in Indonesian Restaurants: Integration Of Protection Motivation Theory (Pmt) And Theory Of Planned Behavior (Tpb)”, Jurnal Mantik, 6(2), pp. 1920-1928. doi: 10.35335/mantik.v6i2.2663.
References
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Patil, K., & Karekar, N. V. (2019). Restaurant automation system using qr codes. IRE Journal, 2(12), 139–142.
Prasetyo, Y. T., Castillo, A. M., Salonga, L. J., Sia, J. A., & Seneta, J. A. (2020). Factors affecting perceived effectiveness of COVID-19 prevention measures among Filipinos during Enhanced Community Quarantine in Luzon, Philippines: Integrating Protection Motivation Theory and extended Theory of Planned Behavior. International Journal of Infectious Diseases, 99, 312–323. https://doi.org/10.1016/j.ijid.2020.07.074
Rad, R. E., Mohseni, S., Kamalzadeh Takhti, H., Hassani Azad, M., Shahabi, N., Aghamolaei, T., & Norozian, F. (2021). Application of the protection motivation theory for predicting COVID-19 preventive behaviors in Hormozgan, Iran: a cross-sectional study. BMC Public Health, 21, 1-11 https://doi.org/10.1186/s12889-021-10500-w
Sun, Y., Wang, N., Guo, X., & Peng, Z. (2013). Understanding the acceptance of mobile health services: A comparison and integration of alternative models. Journal of Electronic Commerce Research, 14(2), 183–200.
Tandon, R. (2020). COVID-19 and mental health: Preserving humanity, maintaining sanity, and promoting health. Asian Journal of Psychiatry, 51, 1-3. https://doi.org/10.1016/j.ajp.2020.102256
Tu, Z., Turel, O., Yuan, Y., & Archer, N. (2015). Learning to cope with information security risks regarding mobile device loss or theft: An empirical examination. Information and Management, 52(4), 506–517. https://doi.org/10.1016/j.im.2015.03.002
Wu, D. (2020). Empirical study of knowledge withholding in cyberspace: Integrating protection motivation theory and theory of reasoned behavior. Computers in Human Behavior, 105, 1-14. https://doi.org/10.1016/j.chb.2019.106229
Yang, J., Zhang, Y., & Lanting, C. J. M. (2017). Exploring the Impact of QR Codes in Authentication Protection: A Study Based on PMT and TPB. Wireless Personal Communications, 96(4), 5315–5334. https://doi.org/10.1007/s11277-016-3743-5
Zhang, X., Liu, S., Wang, L., Zhang, Y., & Wang, J. (2020). Mobile health service adoption in China: Integration of theory of planned behavior, protection motivation theory and personal health differences. Online Information Review, 44(1), 1–23. https://doi.org/10.1108/OIR-11-2016-0339
Ataei, P., Gholamrezai, S., Movahedi, R., & Aliabadi, V. (2021). An analysis of farmers’ intention to use green pesticides: The application of the extended theory of planned behavior and health belief model. Journal of Rural Studies, 81, 374–384. https://doi.org/10.1016/j.jrurstud.2020.11.003
Brizek, M. G., Frash, R. E., McLeod, B. M., & Patience, M. O. (2021). Independent restaurant operator perspectives in the wake of the COVID-19 pandemic. International Journal of Hospitality Management, 9, 1-8. https://doi.org/10.1016/j.ijhm.2020.102766
CDC COVID-19 Response Team, 2020. Preliminary estimates of the prevalence of selected underlying health conditions among patients with Coronavirus Disease 2019 – United States February 12-March 28,2020. Morbid Mortal Wkly Rep. 69, 13, 382–386. https://www.cdc.gov/mmwr/volumes/69/wr/mm6913e2.htm.
Cho, M., Bonn, M. A., & Li, J. (2020). Examining Risk-Reduction Behavior Toward Water Quality Among Restaurant Guests. Cornell Hospitality Quarterly, 1-16. https://doi.org/10.1177/1938965520919106
Crossler, R., & Bélanger, F. (2014). An extended perspective on individual security behaviors: Protection motivation theory and a unified security practices (USP) instrument. Data Base for Advances in Information Systems, 45(4), 51–71. https://doi.org/10.1145/2691517.2691521
Data Industri, (2021). Pertumbuhan Industri Penyedia Makanan Minuman Restoran & Sejenisnya. Web: https://www,dataindustri,com/produk/tren-datapertumbuhan-industri-penyediaan-makanan-minuman-restoran-&- sejenisnya/. Accessed on April 13, 2022.
Deng, Z., & Liu, S. (2017). Understanding consumer health information-seeking behavior from the perspective of the risk perception attitude framework and social support in mobile social media websites. International Journal of Medical Informatics, 105, 98–109. https://doi.org/10.1016/j.ijmedinf.2017.05.014
Guo, X., Han, X., Zhang, X., Dang, Y., & Chen, C. (2015). Investigating m-health acceptance from a protection motivation theory perspective: Gender and age differences. Telemedicine and E-Health, 21(8), 661–669. https://doi.org/10.1089/tmj.2014.0166
Ibrahim, H., & Al-Ajlouni, M. M. Q. (2018). Sustainable consumption: Insights from the protection motivation (PMT), deontic justice (DJT) and construal level (CLT) theories. Management Decision, 56(3), 610–633. https://doi.org/10.1108/MD-05-2016-0323
Kocaman, E. M. (2021). Operational effects of using restaurant management system: An assessment according to business features. International Journal of Gastronomy and Food Science, 25, 1-8. https://doi.org/10.1016/j.ijgfs.2021.100408
Laato, S., Islam, A. K. M. N., & Laine, T. H. (2020). Did location-based games motivate players to socialize during COVID-19? Telematics and Informatics, 54, 1-12. https://doi.org/10.1016/j.tele.2020.101458
Ling, M., Kothe, E. J., & Mullan, B. A. (2019). Predicting intention to receive a seasonal influenza vaccination using Protection Motivation Theory. Social Science and Medicine, 233, 87–92. https://doi.org/10.1016/j.socscimed.2019.06.002
Mahardika, H., Thomas, D., Ewing, M. T., & Japutra, A. (2020). Comparing the temporal stability of behavioural expectation and behavioural intention in the prediction of consumers pro-environmental behaviour. Journal of Retailing and Consumer Services, 54, 1-10. https://doi.org/10.1016/j.jretconser.2019.101943
Man, S. S., Alabdulkarim, S., Chan, A. H. S., & Zhang, T. (2021). The acceptance of personal protective equipment among Hong Kong construction workers: An integration of technology acceptance model and theory of planned behavior with risk perception and safety climate. Journal of Safety Research, 79, 329–340. https://doi.org/10.1016/j.jsr.2021.09.014
Milakovi?, I. K., & Miocevic, D. (2022). Consumer’s transition to online clothing buying during the COVID-19 pandemic: exploration through protection motivation theory and consumer well-being. Journal of Fashion Marketing and Management. https://doi.org/10.1108/JFMM-04-2021-0105
Miraja, B. A., Persada, S. F., Prasetyo, Y. T., Belgiawan, P. F., & Redi, A. A. N. P. (2019). Applying protection motivation theory to understand Generation Z students intention to comply with educational software anti piracy law. International Journal of Emerging Technologies in Learning, 14(18), 39–52. https://doi.org/10.3991/ijet.v14i18.10973
Okuhara, T., Okada, H., & Kiuchi, T. (2020). Predictors of staying at home during the covid-19 pandemic and social lockdown based on protection motivation theory: A cross-sectional study in japan. Healthcare, 8(4), 1-11. https://doi.org/10.3390/healthcare8040475
Ong, A. K. S., Prasetyo, Y. T., Lagura, F. C., Ramos, R. N., Sigua, K. M., Villas, J. A., Young, M. N., Diaz, J. F. T., Persada, S. F., & Redi, A. A. N. P. (2021). Factors affecting intention to prepare for mitigation of “the big one” earthquake in the Philippines: Integrating protection motivation theory and extended theory of planned behavior. International Journal of Disaster Risk Reduction, 63, 1-13. https://doi.org/10.1016/j.ijdrr.2021.102467
Patil, K., & Karekar, N. V. (2019). Restaurant automation system using qr codes. IRE Journal, 2(12), 139–142.
Prasetyo, Y. T., Castillo, A. M., Salonga, L. J., Sia, J. A., & Seneta, J. A. (2020). Factors affecting perceived effectiveness of COVID-19 prevention measures among Filipinos during Enhanced Community Quarantine in Luzon, Philippines: Integrating Protection Motivation Theory and extended Theory of Planned Behavior. International Journal of Infectious Diseases, 99, 312–323. https://doi.org/10.1016/j.ijid.2020.07.074
Rad, R. E., Mohseni, S., Kamalzadeh Takhti, H., Hassani Azad, M., Shahabi, N., Aghamolaei, T., & Norozian, F. (2021). Application of the protection motivation theory for predicting COVID-19 preventive behaviors in Hormozgan, Iran: a cross-sectional study. BMC Public Health, 21, 1-11 https://doi.org/10.1186/s12889-021-10500-w
Sun, Y., Wang, N., Guo, X., & Peng, Z. (2013). Understanding the acceptance of mobile health services: A comparison and integration of alternative models. Journal of Electronic Commerce Research, 14(2), 183–200.
Tandon, R. (2020). COVID-19 and mental health: Preserving humanity, maintaining sanity, and promoting health. Asian Journal of Psychiatry, 51, 1-3. https://doi.org/10.1016/j.ajp.2020.102256
Tu, Z., Turel, O., Yuan, Y., & Archer, N. (2015). Learning to cope with information security risks regarding mobile device loss or theft: An empirical examination. Information and Management, 52(4), 506–517. https://doi.org/10.1016/j.im.2015.03.002
Wu, D. (2020). Empirical study of knowledge withholding in cyberspace: Integrating protection motivation theory and theory of reasoned behavior. Computers in Human Behavior, 105, 1-14. https://doi.org/10.1016/j.chb.2019.106229
Yang, J., Zhang, Y., & Lanting, C. J. M. (2017). Exploring the Impact of QR Codes in Authentication Protection: A Study Based on PMT and TPB. Wireless Personal Communications, 96(4), 5315–5334. https://doi.org/10.1007/s11277-016-3743-5
Zhang, X., Liu, S., Wang, L., Zhang, Y., & Wang, J. (2020). Mobile health service adoption in China: Integration of theory of planned behavior, protection motivation theory and personal health differences. Online Information Review, 44(1), 1–23. https://doi.org/10.1108/OIR-11-2016-0339
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