Push, Pull and Mooring Factors on Offline-Online Learning Switching Behavior
Keywords:
Push Factor, Pull Factor, Mooring Factor, Push-Pull-Mooring (PPM) Theory, Switching Behavior
Abstract
During the pandemic, many sectors, including education, were affected. The shift from traditional to online learning is an opening for students and educators to explore online learning. Students may connect from anywhere at any time through this learning mode. This sudden shift has impacted the learning behavior of students to a large extent. People can access information anytime and anywhere that is typically available only through a traditional classroom. This study adopts the Push-Pull-Mooring (PPM) theory as the theoretical framework to understand how push, pull, and mooring factors affect students' shift from offline to online learning. A survey was used as the main instrument in this study. A quantitative approach was utilized to achieve the stated research objectives. The questionnaires were distributed among undergraduate students in public and private schools in Malaysia through convenience sampling techniques. The minimal 77 sample size has been determined by utilizing G*Power software. 117 responses were collected from the questionnaires that met the minimum required sample size for this study. The findings emphasize that push and pull factors are essential to student learning. However, the mooring factor does not affect the student's switching behavior. The study sheds light on capturing more essential measures in the theoretical development of switching behavior.
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References
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Algahtani, AF (2011) Evaluating the effectiveness of the e-learning experience in some universities in Saudi Arabia from male students’ perceptions. Durham theses, Durham University, UK.
Astuti, Y., & Eliana. (2019). Perilaku Switching Behavior Pengguna Electronic Commerce (e-Commerce) di Kota Langsa dengan Model Migrasi Konsumen Push, Pull, Mooring. SIMEN (Akuntansi dan Manajamen) STIES, 10(1), 9–21.
Barrot, J.S., Llenares, I.I. and del Rosario, L.S. (2021). Students' online learning challenges during the pandemic and how they cope with them: the case of the Philippines”, Education and Information Technologies, 26(6), 7321-7338, doi: 10.1007/s10639-021-10589-x.
Bawa, P. J. S. O. (2016). Retention in online courses: Exploring issues and solutions—A literature review. 6(1), 2158244015621777.
Brandt, J., & Hagge, K. S. (2020). Education and social support: Do migrants benefit as much as natives? Comparative Migration Studies, 8(1). https://doi.org/10.1186/s40878-020- 00199-w
Burnham, T. A., Frels, J. K., & Mahajan, V. J. J. o. t. A. o. m. S. (2003). Consumer switching costs: A typology, antecedents, and consequences. 31(2), 109-126.
Chang, H-H., Wong, K. H., & Li, S. Y. (2017). Applying push-pull-mooring to investigate channel switching behaviors: M-shopping self-efficacy and switching costs as moderators. Electronic Commerce Research and Applications, 24(July-August 2017), 50-67.
Chang, I.C., Liu, C.C. and Chen, K. (2014). The push, pull and mooring effects in virtual migration for social networking sites, Information Systems Journal, 24(4), 323-346.
Chao, M., Chen, X., Liu, T., Yang, H. and Hall, B.J. (2020). Psychological distress and state boredom during the COVID-19 outbreak in China: the role of meaning in life and media use”, European Journal of Psychotraumatology, 11(1), 11
Cheng, S., Lee, S.-J., & Choi, B. (2019). An empirical investigation of users’ voluntary switching intention for mobile personal cloud storage services based on the push-pull-mooring framework. Computers in Human Behavior, 98, 198–215. https://doi.org/10.1016/j.ch
Chen, Y.-H., & Keng, C.-J. (2019). Utilizing the Push-Pull-Mooring-Habit framework to explore users’ intention to switch from offline to online real-person English learning platforms. Internet Research, 29(1), 167-193.
Chen, J., Liu, C., Chang, R., Gui, P., & Na, S. J. I. (2020). From traditional to VR-based online education platforms: A model of the mechanism influencing user migration. 11(9), 423.
Cohen, J. (2013). Statistical power analysis for the behavioral sciences. Routledge.
Dhawan, S. (2020) Online learning: a panacea in the time of COVID-19 crisis. Journal of Educational Technology Systems 0(0): 1–18.
Do, T. D., & Le, L. C. (2020). Factors affecting high school students’ decision on choosing university: Case study of Ho Chi Minh City. Journal of Entrepreneurship Education, 23(3), 1-11.
Guo, J., Shan, S., Wang, Y., & Khan, Y. A. (2021). Analyzing Chinese customers’ switching intention of smartphone brands: Integrating the push-pull-mooring framework. Discrete Dynamics in Nature and Society.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24.
Handarkho, Y.D. (2020). The factors influencing customer loyalty in a social commerce platform: variety-seeking and social impact perspective”, International Journal of Web Information Systems, 16(4), 47-71.
Handarkho, Y. D., Khaerunnisa, K., & Michelle, B. (2023). Factors affecting the intentions of youngsters in switching to a virtual third place amidst the COVID-19 pandemic: the place attachment and push-pull mooring theory. Global Knowledge, Memory and Communication, 72(1/2), 119-137.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modelling. Journal of the academy of marketing science, 43, 115-135.
Hsieh, J. K., Hsieh, Y. C., Chiu, H. C., & Feng, Y. C. (2012). Post-adoption switching behavior for online service substitutes: A perspective of the push-pull–mooring framework. Computers in Human Behavior, 28(5), 1912-1920.
Hsu, J. S. C. (2014). Understanding the role of satisfaction in the formation of perceived switching value. Decision Support Systems, 59, 152–162. https://doi.org/10.1016/j.dss.2013.11.003
Jung, J., & Han, M. H. (2017). Travelers’ switching behavior in the airline industry from the perspective of the push-pull-mooring framework. Tourism Management, 59, 139–153.
Kline, P. (2015). A handbook of test construction (psychology revivals): introduction to psychometric design. Routledge.
Lai, J. Y., Debbarma, S., & Ulhas, K. R. J. I. J. o. M. C. (2012). An empirical study of consumer switching behavior towards mobile shopping: a Push–Pull–Mooring model. 10(4), 386-404.
Lee, E.S. (1966). A theory of migration, Demography, 3(1), 47-57.
Leong, K. (2022). Factors influencing switching intention to m-payment using a push-pull-mooring framework during the coronavirus pandemic in Malaysia. Asian Journal of Research in Business and Management, 4(3), 639–657.
Lin, X., Chien, S. W., Hung, C. W., Chen, S. C., & Ruangkanjanases, A. (2021). The impact of switching intention of telelearning in COVID-19 epidemic's era: the perspective of push-pull-mooring theory. Frontiers in Psychology, 12, 639589.
Lin, T.-C., & Huang, S.-L. (2014). Understanding the determinants of consumers' switching intentions in a standards war. International Journal of Electronic Commerce, 19(1), 163-189.
Liao, Y.-W., Huang, Y.-M., Huang, S.-H., Chen, H.-C., Wei, C.-W. J. E. J. o. M., Science, & Education, T. (2019). Exploring the switching intention of learners on social network-based learning platforms: a perspective of the push-pull–mooring model. 15(9), em1747.
Lisana, L. (2021). Factors influencing the adoption of mobile payment systems in Indonesia. International Journal of Web Information Systems, 17(3), 204–228
Lisana, L. (2023). Factors affecting university students switching intention to mobile learning: a push-pull-mooring theory perspective. Education and Information Technologies, 28(5), 5341-5361.
Li, Y., Nishimura, N., Yagami, H., & Park, H. (2021). An Empirical Study on Online Learners’ Continuance Intentions in China. Sustainability 2021, 13, 889.
Lowry, P. B., & Gaskin, J. (2014). Partial least squares (PLS) structural equation modelling (SEM) for building and testing behavioral causal theory: When to choose it and how to use it. IEEE transactions on professional communication, 57(2), 123-146.
Maheshwari, G. (2021). Factors affecting students’ intentions to undertake online learning: An Empirical Study in Vietnam. Education and Information Technologies. 10.1007/s10639-021-10465-8.
Malaysian Investment Development Authority, (2021) Evolution of e-Learning in the Malaysian Higher Education Institutions. Retrieved from https://www.mida.gov.my/mida-news/evolution-of-e-learning-in-the-malaysian-higher-education-institutions/
Menon, S., & Kahn, B. E. (1995). The impact of context on variety seeking in product choices. Journal of Consumer Research, 22(3), 285–295. https://doi.org/10.1086/209450
Mozie, N. M., Jailani, S. F. A. K., & Kassim, E. S. (2023). University Students' Offline-Online Learning Switching Behavior in the New Norm. Global Business & Management Research, 15.
Moon, B. (1995). Paradigms in migration research: exploring ' moorings' as a schema. Progress in Human Geography, 19(4), 504-524.
Monoarfa, T. A., Sumarwan, U., Suroso, A. I., & Wulandari, R. (2023). Switch or stay? Applying a push-pull–-mooring framework to evaluate behavior in E-grocery shopping. Sustainability, 15(7), 6018.
Nayak, B., Bhattacharyya, S. S., Goswami, S., & Thakre, S. J. J. o. C. i. E. (2022). Adoption of online education channel during the COVID-19 pandemic and associated economic lockdown: An empirical study from push–pull-mooring framework. 9(1), 1-23.
Nurlinda, R. A., & Anam, C. (2024). Factors Influencing Customer Switching Intentions in Online Food Delivery: A Perspective of The Push-Pull-Mooring Model. Jurnal Manajemen Perhotelan, 10(1), 43-54.
Pratama, R. S., Aditya, V. D., Putra, A. R., & Hendriana, E. (2024). Interregional study destination choice: Application of Push, Pull, and Mooring Model. Journal of Tourism, Hospitality and Culinary Arts, 16, 81-102.
Ramayah, T. J. F. H., Cheah, J., Chuah, F., Ting, H., & Memon, M. A. (2018). Partial least squares structural equation modeling (PLS-SEM) using smartPLS 3.0. An updated guide and practical guide to statistical analysis, 967-978.
Ramayah, T. (2018). Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS 3.0. Kuala Lumpur: Pearson.
Ranganathan, C., Seo, D., & Babad, Y. (2006). Switching behavior of mobile users: do users' relational investments and demographics matter? European Journal of Information Systems, 15(3), 269-276.
Rathinam, S., Yap, L. T., Navies, L. G., Murugiah, H., & Mohamad Zulkifli, N. S. (2023). Trends, Issues, and Challenges in E-Learning in the Malaysian Education System: A Review of Literature. Journal of Social Sciences and Business, 2(1), 1-15. DOI: 10.5281/zenodo.8152114.
Singh, V. and Thurman, A. (2019) How many ways can we define online learning? A systematic literature review of definitions of online learning (1988-2018). American Journal of Distance Education 33(4), 289–306.
Sun, Y., Liu, D., Chen, S., Wu, X., Shen, X. L., & Zhang, X. (2017). Understanding users’ switching behavior of mobile instant messaging applications: An empirical study from the perspective of the push-pull-mooring framework. Computers in Human Behavior, 75, 727–738.
Wang, L., Luo, X. R., Yang, X., Qiao, Z. J. I., & Management. (2019). Easy come or easy go? Empirical evidence on switching behaviors in mobile payment applications. 56(7), 103150.
Wong, K. K. K. (2013). Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24(1), 1-32.
Wu, K., Vassileva, J., & Zhao, Y. (2017). Understanding users' intention to switch personal cloud storage services: Evidence from the Chinese market. Computers in Human Behavior, 68, 300-314.
Xu, H., Wang, J., Tai, Z., & Lin, H.-C. (2021). An empirical study on the factors affecting user switching behavior of online learning platforms based on push-pull-mooring theory. Sustainability, 13(13), 7087.
Zeng, Z., Li, S., Lian, J.-W., Li, J., Chen, T., & Li, Y. J. L. U. P. (2021). Switching behavior in the adoption of a land information system in China: A perspective of the push-pull–mooring framework. 109, 105629.
Zhang, Y., Oh, H. K., & Lee, C. H. (2021). Understanding consumer switching intention of peer-to-peer accommodation: A push-pull-mooring framework. Journal of Hospitality and Tourism Management, 49, 321-330.
Zhou, T. (2016). Examining user switch between mobile stores: A push-pull-mooring perspective. Information Resources Management Journal (IRMJ), 29(2), 1-13.
Abumalloh, R. A., Asadi, S., Nilashi, M., Minaei-Bidgoli, B., Nayer, F. K., Samad, S., . . . Ibrahim, O. J. T. i. S. (2021). The impact of coronavirus pandemic (COVID-19) on education: The role of virtual and remote laboratories in education. 67, 101728.
Alexander, R. (2021). Career development and internal migration: A Scottish case study. British Journal of Guidance & Counselling, 49(5), 744–757. https://doi.org/10.1080/03069885.2021.1934654
Algahtani, AF (2011) Evaluating the effectiveness of the e-learning experience in some universities in Saudi Arabia from male students’ perceptions. Durham theses, Durham University, UK.
Astuti, Y., & Eliana. (2019). Perilaku Switching Behavior Pengguna Electronic Commerce (e-Commerce) di Kota Langsa dengan Model Migrasi Konsumen Push, Pull, Mooring. SIMEN (Akuntansi dan Manajamen) STIES, 10(1), 9–21.
Barrot, J.S., Llenares, I.I. and del Rosario, L.S. (2021). Students' online learning challenges during the pandemic and how they cope with them: the case of the Philippines”, Education and Information Technologies, 26(6), 7321-7338, doi: 10.1007/s10639-021-10589-x.
Bawa, P. J. S. O. (2016). Retention in online courses: Exploring issues and solutions—A literature review. 6(1), 2158244015621777.
Brandt, J., & Hagge, K. S. (2020). Education and social support: Do migrants benefit as much as natives? Comparative Migration Studies, 8(1). https://doi.org/10.1186/s40878-020- 00199-w
Burnham, T. A., Frels, J. K., & Mahajan, V. J. J. o. t. A. o. m. S. (2003). Consumer switching costs: A typology, antecedents, and consequences. 31(2), 109-126.
Chang, H-H., Wong, K. H., & Li, S. Y. (2017). Applying push-pull-mooring to investigate channel switching behaviors: M-shopping self-efficacy and switching costs as moderators. Electronic Commerce Research and Applications, 24(July-August 2017), 50-67.
Chang, I.C., Liu, C.C. and Chen, K. (2014). The push, pull and mooring effects in virtual migration for social networking sites, Information Systems Journal, 24(4), 323-346.
Chao, M., Chen, X., Liu, T., Yang, H. and Hall, B.J. (2020). Psychological distress and state boredom during the COVID-19 outbreak in China: the role of meaning in life and media use”, European Journal of Psychotraumatology, 11(1), 11
Cheng, S., Lee, S.-J., & Choi, B. (2019). An empirical investigation of users’ voluntary switching intention for mobile personal cloud storage services based on the push-pull-mooring framework. Computers in Human Behavior, 98, 198–215. https://doi.org/10.1016/j.ch
Chen, Y.-H., & Keng, C.-J. (2019). Utilizing the Push-Pull-Mooring-Habit framework to explore users’ intention to switch from offline to online real-person English learning platforms. Internet Research, 29(1), 167-193.
Chen, J., Liu, C., Chang, R., Gui, P., & Na, S. J. I. (2020). From traditional to VR-based online education platforms: A model of the mechanism influencing user migration. 11(9), 423.
Cohen, J. (2013). Statistical power analysis for the behavioral sciences. Routledge.
Dhawan, S. (2020) Online learning: a panacea in the time of COVID-19 crisis. Journal of Educational Technology Systems 0(0): 1–18.
Do, T. D., & Le, L. C. (2020). Factors affecting high school students’ decision on choosing university: Case study of Ho Chi Minh City. Journal of Entrepreneurship Education, 23(3), 1-11.
Guo, J., Shan, S., Wang, Y., & Khan, Y. A. (2021). Analyzing Chinese customers’ switching intention of smartphone brands: Integrating the push-pull-mooring framework. Discrete Dynamics in Nature and Society.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24.
Handarkho, Y.D. (2020). The factors influencing customer loyalty in a social commerce platform: variety-seeking and social impact perspective”, International Journal of Web Information Systems, 16(4), 47-71.
Handarkho, Y. D., Khaerunnisa, K., & Michelle, B. (2023). Factors affecting the intentions of youngsters in switching to a virtual third place amidst the COVID-19 pandemic: the place attachment and push-pull mooring theory. Global Knowledge, Memory and Communication, 72(1/2), 119-137.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modelling. Journal of the academy of marketing science, 43, 115-135.
Hsieh, J. K., Hsieh, Y. C., Chiu, H. C., & Feng, Y. C. (2012). Post-adoption switching behavior for online service substitutes: A perspective of the push-pull–mooring framework. Computers in Human Behavior, 28(5), 1912-1920.
Hsu, J. S. C. (2014). Understanding the role of satisfaction in the formation of perceived switching value. Decision Support Systems, 59, 152–162. https://doi.org/10.1016/j.dss.2013.11.003
Jung, J., & Han, M. H. (2017). Travelers’ switching behavior in the airline industry from the perspective of the push-pull-mooring framework. Tourism Management, 59, 139–153.
Kline, P. (2015). A handbook of test construction (psychology revivals): introduction to psychometric design. Routledge.
Lai, J. Y., Debbarma, S., & Ulhas, K. R. J. I. J. o. M. C. (2012). An empirical study of consumer switching behavior towards mobile shopping: a Push–Pull–Mooring model. 10(4), 386-404.
Lee, E.S. (1966). A theory of migration, Demography, 3(1), 47-57.
Leong, K. (2022). Factors influencing switching intention to m-payment using a push-pull-mooring framework during the coronavirus pandemic in Malaysia. Asian Journal of Research in Business and Management, 4(3), 639–657.
Lin, X., Chien, S. W., Hung, C. W., Chen, S. C., & Ruangkanjanases, A. (2021). The impact of switching intention of telelearning in COVID-19 epidemic's era: the perspective of push-pull-mooring theory. Frontiers in Psychology, 12, 639589.
Lin, T.-C., & Huang, S.-L. (2014). Understanding the determinants of consumers' switching intentions in a standards war. International Journal of Electronic Commerce, 19(1), 163-189.
Liao, Y.-W., Huang, Y.-M., Huang, S.-H., Chen, H.-C., Wei, C.-W. J. E. J. o. M., Science, & Education, T. (2019). Exploring the switching intention of learners on social network-based learning platforms: a perspective of the push-pull–mooring model. 15(9), em1747.
Lisana, L. (2021). Factors influencing the adoption of mobile payment systems in Indonesia. International Journal of Web Information Systems, 17(3), 204–228
Lisana, L. (2023). Factors affecting university students switching intention to mobile learning: a push-pull-mooring theory perspective. Education and Information Technologies, 28(5), 5341-5361.
Li, Y., Nishimura, N., Yagami, H., & Park, H. (2021). An Empirical Study on Online Learners’ Continuance Intentions in China. Sustainability 2021, 13, 889.
Lowry, P. B., & Gaskin, J. (2014). Partial least squares (PLS) structural equation modelling (SEM) for building and testing behavioral causal theory: When to choose it and how to use it. IEEE transactions on professional communication, 57(2), 123-146.
Maheshwari, G. (2021). Factors affecting students’ intentions to undertake online learning: An Empirical Study in Vietnam. Education and Information Technologies. 10.1007/s10639-021-10465-8.
Malaysian Investment Development Authority, (2021) Evolution of e-Learning in the Malaysian Higher Education Institutions. Retrieved from https://www.mida.gov.my/mida-news/evolution-of-e-learning-in-the-malaysian-higher-education-institutions/
Menon, S., & Kahn, B. E. (1995). The impact of context on variety seeking in product choices. Journal of Consumer Research, 22(3), 285–295. https://doi.org/10.1086/209450
Mozie, N. M., Jailani, S. F. A. K., & Kassim, E. S. (2023). University Students' Offline-Online Learning Switching Behavior in the New Norm. Global Business & Management Research, 15.
Moon, B. (1995). Paradigms in migration research: exploring ' moorings' as a schema. Progress in Human Geography, 19(4), 504-524.
Monoarfa, T. A., Sumarwan, U., Suroso, A. I., & Wulandari, R. (2023). Switch or stay? Applying a push-pull–-mooring framework to evaluate behavior in E-grocery shopping. Sustainability, 15(7), 6018.
Nayak, B., Bhattacharyya, S. S., Goswami, S., & Thakre, S. J. J. o. C. i. E. (2022). Adoption of online education channel during the COVID-19 pandemic and associated economic lockdown: An empirical study from push–pull-mooring framework. 9(1), 1-23.
Nurlinda, R. A., & Anam, C. (2024). Factors Influencing Customer Switching Intentions in Online Food Delivery: A Perspective of The Push-Pull-Mooring Model. Jurnal Manajemen Perhotelan, 10(1), 43-54.
Pratama, R. S., Aditya, V. D., Putra, A. R., & Hendriana, E. (2024). Interregional study destination choice: Application of Push, Pull, and Mooring Model. Journal of Tourism, Hospitality and Culinary Arts, 16, 81-102.
Ramayah, T. J. F. H., Cheah, J., Chuah, F., Ting, H., & Memon, M. A. (2018). Partial least squares structural equation modeling (PLS-SEM) using smartPLS 3.0. An updated guide and practical guide to statistical analysis, 967-978.
Ramayah, T. (2018). Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS 3.0. Kuala Lumpur: Pearson.
Ranganathan, C., Seo, D., & Babad, Y. (2006). Switching behavior of mobile users: do users' relational investments and demographics matter? European Journal of Information Systems, 15(3), 269-276.
Rathinam, S., Yap, L. T., Navies, L. G., Murugiah, H., & Mohamad Zulkifli, N. S. (2023). Trends, Issues, and Challenges in E-Learning in the Malaysian Education System: A Review of Literature. Journal of Social Sciences and Business, 2(1), 1-15. DOI: 10.5281/zenodo.8152114.
Singh, V. and Thurman, A. (2019) How many ways can we define online learning? A systematic literature review of definitions of online learning (1988-2018). American Journal of Distance Education 33(4), 289–306.
Sun, Y., Liu, D., Chen, S., Wu, X., Shen, X. L., & Zhang, X. (2017). Understanding users’ switching behavior of mobile instant messaging applications: An empirical study from the perspective of the push-pull-mooring framework. Computers in Human Behavior, 75, 727–738.
Wang, L., Luo, X. R., Yang, X., Qiao, Z. J. I., & Management. (2019). Easy come or easy go? Empirical evidence on switching behaviors in mobile payment applications. 56(7), 103150.
Wong, K. K. K. (2013). Partial least squares structural equation modeling (PLS-SEM) techniques using SmartPLS. Marketing Bulletin, 24(1), 1-32.
Wu, K., Vassileva, J., & Zhao, Y. (2017). Understanding users' intention to switch personal cloud storage services: Evidence from the Chinese market. Computers in Human Behavior, 68, 300-314.
Xu, H., Wang, J., Tai, Z., & Lin, H.-C. (2021). An empirical study on the factors affecting user switching behavior of online learning platforms based on push-pull-mooring theory. Sustainability, 13(13), 7087.
Zeng, Z., Li, S., Lian, J.-W., Li, J., Chen, T., & Li, Y. J. L. U. P. (2021). Switching behavior in the adoption of a land information system in China: A perspective of the push-pull–mooring framework. 109, 105629.
Zhang, Y., Oh, H. K., & Lee, C. H. (2021). Understanding consumer switching intention of peer-to-peer accommodation: A push-pull-mooring framework. Journal of Hospitality and Tourism Management, 49, 321-330.
Zhou, T. (2016). Examining user switch between mobile stores: A push-pull-mooring perspective. Information Resources Management Journal (IRMJ), 29(2), 1-13.
Published
2024-10-05
How to Cite
Kader Jailani, S. F. A., Mat Ali, S. A., Yunus, N. M., & Mozie, N. M. (2024). Push, Pull and Mooring Factors on Offline-Online Learning Switching Behavior. Information Management and Business Review, 16(3(I)S), 776-786. https://doi.org/10.22610/imbr.v16i3(I)S.4107
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Copyright (c) 2024 Sri Fatiany Abdul Kader Jailani, Syukrina Alini Mat Ali, Noorain Mohamad Yunus, Noorizan Mohamad Mozie
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