Determinants of Technology Acceptance among Older Adults in Malaysia

Authors

  • Captain School of Business, UOW Malaysia KDU Penang University College
  • Mr School of Business, UOW Malaysia KDU Penang University College
  • Dr Department of Information Systems, Universiti Tunku Abdul Rahman
  • Ms School of Business, UOW Malaysia KDU Penang University College
  • Assoc. Prof. Dr School of Business, UOW Malaysia KDU Penang University College

DOI:

https://doi.org/10.47663/ibec.v4i1.396

Keywords:

Behavior Intention, Ease of Use, Performance Expectancy, Social Influence

Abstract

This study examines elderly Malaysians’ intention to use QR ordering through the Unified Theory of Acceptance and Use of Technology, focusing on ease of use, performance expectancy, and social influence. A survey was analysed using partial least squares structural equation modelling. Diagnostics indicated acceptable univariate normality with some multivariate non normality, and checks for common method variance were satisfactory. The measurement model met accepted reliability and validity standards. In the structural model, performance expectancy and ease of use both showed positive effects on behavioural intention, while social influence was not a significant driver. The importance performance map identified performance expectancy as the most influential driver of intention and ease of use as the next most influential, both with room for further enhancement, whereas social influence showed limited importance. Findings suggest that older adults form intention when the system clearly delivers benefits such as faster and more convenient ordering and is simple to operate. Practically, providers should highlight tangible benefits, streamline the journey, and offer clear guidance at the point of use. Limitations include a single service context, a cross sectional design, and reliance on self reported intention. Future research should test causal pathways and examine mediators and moderators such as recognition of benefits, education, and dining context.

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Author Biographies

Captain, School of Business, UOW Malaysia KDU Penang University College

Associate Professor Capt. Dr. Joshua Loo Teck Khun is a distinguished academic and former military officer at the School of Business and Administration, UOW Malaysia KDU Penang University College. Leveraging a unique background that combines disciplined leadership from his military service with advanced academic expertise, Dr. Loo brings a pragmatic and strategic perspective to his roles in teaching, research, and mentorship. He holds a Doctorate in Business Administration, a Master's in Economic Management, and a Bachelor's degree in Social Science majoring in Economics and Minoring in Political Science, forming a robust foundation for his diverse research interests. These include globalization, economics, organizational performance, strategic management, leadership, innovation, and marketing. An active and contributing scholar, Dr. Loo has been consistently disseminating his research findings at academic conferences and in peer-reviewed publications since 2016, establishing himself as a respected voice in his field

Mr, School of Business, UOW Malaysia KDU Penang University College

Chang Jie Jeng is an MBA candidate with a background in Computer Science and active involvement as an entrepreneur in the information technology industry. His professional interests bridge business strategy and technological innovation, focusing on the practical integration of digital solutions to enhance organizational performance and customer experience.

Dr, Department of Information Systems, Universiti Tunku Abdul Rahman

Dr. Sima Ahmadpour, presently working as an Assistant Professor at the Department of Computer Science, Faculty of Information and Communication Technology, Universiti Tunku Abdul Rahman, Malaysia. Sima received her PhD Degree from National Advanced IPv6 (NAv6) center at Universiti Sains Malaysia (USM), in 2016. She was honored with a fellowship award from USM at 2010. Since then, she taught various computer sciences courses in different inter(national) universities to undergraduate as well as graduate students. She has vast professional research experience and supervised several Master theses. Her research interests are Business Analytics, Statistical modeling, Data Science, Internet of Things (IoT), and Cybersecurity.

Ms, School of Business, UOW Malaysia KDU Penang University College

Ms. Sumiko Cheng Chun Yi is a Senior Lecturer at UOW Malaysia KDU Penang University College, specializing in business management, human resources, Tech-Tourism, hospitality, psychology, and e-learning. She has published a range of journal articles on topics such as virtual tourism experiences and consumer revisit intention in hospitality. Known for her innovation, she integrates AI into her pedagogy and has won multiple awards including Teaching Excellence (2024) and Innovation (2020).

Assoc. Prof. Dr, School of Business, UOW Malaysia KDU Penang University College

Dr. Tan Kock Lim is a Program Leader and Lecturer at UOW Malaysia KDU University College, Penang. He holds a Doctor of Business Administration (Finance) and an MBA from Universiti Sains Malaysia. With over 15 years of banking experience at Alliance Bank and Hong Leong Bank, Dr. Tan is also a Certified Credit Professional (AICB). His research interests include banking, risk management, FinTech adoption, financial literacy, digital finance, and sustainable finance.

References

REFERENCES

An, S., Cheung, C. F., & Lo, Y. T. (2024). Improving Older Adults’ Technology Adoption on Mobile Map: A Gamification Approach. International Journal of Human–Computer Interaction, 1-19.

Ansari, C., Caroline, Adiati, M. P., & Rosman, D. (2024). The Impact of QR Code Integration on Purchase Intention and Ordering Convenience of Food and Beverage Menu in Restaurant Opportunities and Risks in AI for Business Development: Volume 1 (pp. 587-598): Springer.

Arioz, U., Smrke, U., Plohl, N., Špes, T., Musil, B., & Mlakar, I. (2024). Scoping review of technological solutions for community dwelling older adults and implications for instrumental activities of daily living. Aging and disease, 16(1), 345.

Ashrafi, D. M., Iskender, A., & Shahid, T. (2025). Bytes to bites: Investigating QR code menu use behavior and green satisfaction in the restaurantscapes through a hybrid PLS-SEM and machine learning approach. Journal of Foodservice Business Research, 1-47.

Attuquayefio, S., & Addo, H. (2014). Using the UTAUT model to analyze students’ ICT adoption. International Journal of Education and Development using ICT, 10(3).

Azhar, A. (2021). Mixed Reality Storytelling for Social Engagement with Older Adults.

Badowskaa, S., Zamojskab, A., & Rogalac, A. (2016). IMPACT OF PERFORMANCE EXPECTANCY AND EFFORT EXPECTANCY ON THE ELDERLY CONSUMERS'BEHAVIOUR REGARDING ACCEPTANCE AND USE OF TECHNOLOGICAL PRODUCTS: AN EMPIRICAL RESEARCH IN. Preparation for the Future Innovative Economy, 174.

Barnard, Y., Bradley, M. D., Hodgson, F., & Lloyd, A. D. (2013). Learning to use new technologies by older adults: Perceived difficulties, experimentation behaviour and usability. Computers in Human Behavior, 29(4), 1715-1724.

Basu, R. (2021). Age and Interface Equipping Older Adults with Technological Tools. OCAD University.

Baumgartner, H., Weijters, B., & Pieters, R. (2021). The biasing effect of common method variance: Some clarifications. Journal of the academy of marketing science, 49(2), 221-235.

Bhowmick, P. (2024). Beyond Digital Boundaries: Breaking Barriers to Social Connectivity for Older Adults Using Tangible, Customizable, Peer-Based, Check-In Solutions. Indiana University.

Boot, W. R., Boot, W. R. D., & Kalantari, S. (2024). Extended Reality Solutions to Support Older Adults: Springer.

Che Nawi, N., Mamun, A. A., Hayat, N., & Seduram, L. (2022). Promoting sustainable financial services through the adoption of eWallet among Malaysian working adults. Sage Open, 12(1), 21582440211071107.

Chee, S. Y. (2024). Age-related digital disparities, functional limitations, and social isolation: unraveling the grey digital divide between baby boomers and the silent generation in senior living facilities. Aging & mental health, 28(4), 621-632.

Chen, K., & Chan, A. H. S. (2014). Gerontechnology acceptance by elderly Hong Kong Chinese: a senior technology acceptance model (STAM). Ergonomics, 57(5), 635-652.

Chen, S. (2024). Age-appropriate design of smart senior care product APP interface based on deep learning. Heliyon, 10(7).

Chen, X., Wang, F., You, Z., Wang, X., Tao, C., & Liu, J. (2017). Design of interactive tutorials on mobile applications for chinese middle-aged and older adults. Art and Design Review, 5(3), 162-180.

Chin, C.-L., & Yao, G. (2024). Convergent validity Encyclopedia of quality of life and well-being research (pp. 1398-1399): Springer.

Chong, C. K., Man, K. Y., Ding, A. C. A., & Cha, N. A. (2024). FACTORS INFLUENCING THE ADOPTION OF QR MOBILE PAYMENT AMONG MALAYSIAN CONSUMERS. Journal of Social Sciences and Business, 3(2), 10-19.

Cimperman, M., Brenčič, M. M., & Trkman, P. (2016). Analyzing older users’ home telehealth services acceptance behavior—applying an Extended UTAUT model. International Journal of Medical Informatics, 90, 22-31.

Czaja, S. J., Charness, N., Fisk, A. D., Hertzog, C., Nair, S. N., Rogers, W. A., & Sharit, J. (2006). Factors predicting the use of technology: findings from the Center for Research and Education on Aging and Technology Enhancement (CREATE). Psychology and aging, 21(2), 333.

Czaja, S. J., & Lee, C. C. (2007). The impact of aging on access to technology. Universal access in the information society, 5, 341-349.

Daniels, K., & Bonnechère, B. (2024). Harnessing digital health interventions to bridge the gap in prevention for older adults. Frontiers in public health, 11, 1281923.

Datta, A., & Jessup, L. M. (2013). Looking beyond the focal industry and existing technologies for radical innovations. Technovation, 33(10-11), 355-367.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.

DeCosse, R. (2023). QR code linked videos to enhance competencies in rural nursing. University of Lethbridge.

dos Santos, P. M., & Cirillo, M. Â. (2023). Construction of the average variance extracted index for construct validation in structural equation models with adaptive regressions. Communications in Statistics-Simulation and Computation, 52(4), 1639-1650.

Freeble, N. (2023). Cartwright felt like starting that all beyond measure he shall go. Natural except she used proper spelling was cool. Player award between them. Munirah Ermalovich Custom flame paint job are defined. Which simulator do its message unto thee! Carrot starting to mesh together perfectly. Gurl got down! Garden side bedroom.

Galavotti, G. (2023). Transforming the dining experience: a census of innovative payment solutions for restaurants.

Guenther, P., Guenther, M., Ringle, C. M., Zaefarian, G., & Cartwright, S. (2023). Improving PLS-SEM use for business marketing research. Industrial Marketing Management, 111, 127-142.

Gündüz, N., Zaim, S., & Erzurumlu, Y. Ö. (2024). Investigating impact of health belief and trust on technology acceptance in smartwatch usage: Turkish senior adults case. International Journal of Pharmaceutical and Healthcare Marketing, 18(3), 499-520.

Guo, P., Rau, P.-L. P., Yu, D., Gao, Y., Ng, C. R., Yu, X., . . . Masafumi, K. (2023). A study on the continuous usage factors of perceived ease of use, social influence, and performance expectancy for elderly people. Paper presented at the International Conference on Human-Computer Interaction.

Gupta, A., & Arora, N. (2017). Consumer adoption of m-banking: a behavioral reasoning theory perspective. International Journal of Bank Marketing, 35(4), 733-747.

Gurung, A. (2024). QR CODES AND CUSTOMER SATISFACTION OF COMMERCIAL BANK. Shanker Dev Campus.

Haan, M. d., Brankaert, R., Kenning, G., & Lu, Y. (2021). Creating a social learning environment for and by older adults in the use and adoption of smartphone technology to age in place. Frontiers in public health, 9, 568822.

Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Evaluation of reflective measurement models Partial least squares structural equation modeling (PLS-SEM) using R: A workbook (pp. 75-90): Springer International Publishing Cham.

Haji-Othman, Y., & Yusuff, M. S. S. (2022). Assessing reliability and validity of attitude construct using partial least squares structural equation modeling. Int J Acad Res Bus Soc Sci, 12(5), 378-385.

Han, J., Xu, Z., & Ma, Y. (2024). Ethical reflection on the “QR code dilemma” faced by older people during COVID-19 in China. Journal of Bioethical Inquiry, 21(2), 239-248.

Hawthorn, D. (2006). Designing effective interfaces for older users. The University of Waikato.

Heinz, M., Martin, P., Margrett, J. A., Yearns, M., Franke, W., Yang, H.-I., . . . Chang, C. K. (2013). Perceptions of technology among older adults. Journal of gerontological nursing, 39(1), 42-51.

Howard, M. C., Boudreaux, M., & Oglesby, M. (2024). Can Harman’s single-factor test reliably distinguish between research designs? Not in published management studies. European Journal of Work and Organizational Psychology, 33(6), 790-804.

IMANI, A. (2013). Design and development of a user interface for a mobile personal indoor navigation assistant for the elderly.

Iskender, A., Sirakaya-Turk, E., Cardenas, D., & Hikmet, N. (2024). Restaurant patrons’ intentions toward QR code menus in the US during COVID-19: acceptance of technology adoption model (ATAM). Journal of Foodservice Business Research, 27(5), 497-522.

Islam, S. (2024). Impact of online payment systems on customer trust and loyalty in E-commerce analyzing security and convenience. Available at SSRN 5064838.

Karp, M., Silesky, M., Janzen, T., & Bonnevie, E. (2023). A Technology-Based Approach to Addressing Social Isolation and Loneliness Among Older Adults: The Story of Life Experienced. Available at SSRN 4620322.

Kebede, A. S., Ozolins, L.-L., Holst, H., & Galvin, K. (2022). Digital engagement of older adults: scoping review. Journal of Medical Internet Research, 24(12), e40192.

Khamaj, A., & Ali, A. M. (2024). Examining the usability and accessibility challenges in mobile health applications for older adults. Alexandria Engineering Journal, 102, 179-191.

Kim, N. (2021). A Jarque-Bera type test for multivariate normality based on second-power skewness and kurtosis. Communications for Statistical Applications and Methods, 28(5), 463-475.

Koo, J. H., Park, Y. H., & Kang, D. R. (2023). Factors Predicting Older People’s Acceptance of a Personalized Health Care Service App and the Effect of Chronic Disease: Cross-Sectional Questionnaire Study. JMIR aging, 6(1), e41429.

Kostanek, J., Karolczak, K., Kuliczkowski, W., & Watala, C. (2024). Bootstrap method as a tool for analyzing data with atypical distributions deviating from parametric assumptions: Critique and effectiveness evaluation. Data, 9(8), 95.

Kyriazos, T., & Poga, M. (2023). Dealing with multicollinearity in factor analysis: the problem, detections, and solutions. Open Journal of Statistics, 13(3), 404-424.

Le, X. C. (2022). The diffusion of mobile QR-code payment: an empirical evaluation for a pandemic. Asia-Pacific Journal of Business Administration, 14(4), 617-636.

Lee, L., & Maher, M. L. (2021). Factors affecting the initial engagement of older adults in the use of interactive technology. International journal of environmental research and public health, 18(6), 2847.

Li, W., Guo, J., Liu, W., Tu, J., & Tang, Q. (2024). Effect of older adults willingness on telemedicine usage: an integrated approach based on technology acceptance and decomposed theory of planned behavior model. BMC geriatrics, 24(1), 765.

Lin, W.-L., & Yao, G. (2024). Predictive validity Encyclopedia of quality of life and well-being research (pp. 5423-5424): Springer.

Ma, Q., Chan, A. H., & Teh, P.-L. (2021). Insights into older adults’ technology acceptance through meta-analysis. International Journal of Human–Computer Interaction, 37(11), 1049-1062.

Mazhar, A. F., Salleh, N. A. N., Usman, S. B., Dzia-Uddin, D. N., & Kamaruddin, W. N. B. W. (2024). Assessing the Customer Perception of Quick Response (QR) Code Application and their Purchase Intention in Penang's Casual Dining Restaurants, Malaysia. Asian Journal of Research in Education and Social Sciences, 6(S1), 30-43.

McLaughlin, A., & Pak, R. (2020). Designing displays for older adults: CRC press.

Md Fadzil, N. H., Shahar, S., Singh, D. K. A., Rajikan, R., Vanoh, D., Mohamad Ali, N., & Mohd Noah, S. A. (2023). Digital technology usage among older adults with cognitive frailty: a survey during COVID-19 pandemic. Digital Health, 9, 20552076231207594.

Mitzner, T. L., Boron, J. B., Fausset, C. B., Adams, A. E., Charness, N., Czaja, S. J., . . . Sharit, J. (2010). Older adults talk technology: Technology usage and attitudes. Computers in Human Behavior, 26(6), 1710-1721.

Morris, M. G., & Venkatesh, V. (2000). Age differences in technology adoption decisions: Implications for a changing work force. Personnel psychology, 53(2), 375-403.

Morrison, B. A., Nicholson, J., Wood, B., & Briggs, P. (2023). Life after lockdown: The experiences of older adults in a contactless digital world. Frontiers in Psychology, 13, 1100521.

Pang, C., Collin Wang, Z., McGrenere, J., Leung, R., Dai, J., & Moffatt, K. (2021). Technology adoption and learning preferences for older adults: evolving perceptions, ongoing challenges, and emerging design opportunities. Paper presented at the Proceedings of the 2021 CHI conference on human factors in computing systems.

Pee, N. C., Maksom, Z., & Norizan, A. R. (2014). Factor influencing the use of smart phone by Malaysian’s elderly. Journal of theoretical and applied information technology, 59(2), 421-425.

Peek, S. T., Wouters, E. J., Van Hoof, J., Luijkx, K. G., Boeije, H. R., & Vrijhoef, H. J. (2014). Factors influencing acceptance of technology for aging in place: a systematic review. International Journal of Medical Informatics, 83(4), 235-248.

Peral, Y. A., Concepción, E., López-Samaniego, I., & Zarza, G. (2022). An analysis on how can AI empower the senior population in their access to banking services. X Jornadas de Cloud Computing, Big Data & Emerging Topics.

Putit, L., & Sahudin, Z. (2023). Towards adopting innovative quick response (QR)-enabled contactless transaction payment: the Malaysian MSMES’entrepreneurial perspective in COVID-19 setting Open Innovation in Small Business: Creating Values for Sustainability (pp. 57-70): Springer.

Rachmad, Y. E., Bakri, A. A., Nuraini, R., & Nurdiani, T. W. (2024). Application of The Unified Theory of Acceptance and Use of Technology Method to Analyze Factors Influencing The Use of Digital Wallets in Indonesia. Jurnal Informasi Dan Teknologi, 229-234.

Renaud, K., & Van Biljon, J. (2008). Predicting technology acceptance and adoption by the elderly: a qualitative study. Paper presented at the Proceedings of the 2008 annual research conference of the South African Institute of Computer Scientists and Information Technologists on IT research in developing countries: riding the wave of technology.

Rivas, A. G., & Schulzetenberg, A. (2023). QR codes as a method for older adults to access a mobile survey. Paper presented at the International Conference on Human-Computer Interaction.

Rizky, R., Lestari, E. P., & Wihadanto, A. (2024). Cyberloafing Mechanism: The Impact Of Workload, Self-Control, And Job Stress On Civil Servant Performance. JURNAL EKBIS, 25(1).

Rose, S. A., Wass, S. V., Jankowski, J. J., & Djukic, A. (2021). Measures of attention in Rett syndrome: Internal consistency reliability. Neuropsychology, 35(6), 595.

Roupa, Z., Nikas, M., Gerasimou, E., Zafeiri, V., Giasyrani, L., Kazitori, E., & Sotiropoulou, P. (2010). The use of technology by the elderly. Health science journal, 4(2), 118.

Santoro, F. (2024). Optimizing Industrial Operations: A Web Application for QR Code-Based Machinery Information Management. Politecnico di Torino.

Saxena, M., Bagga, T., Gupta, S., & Kaushik, N. (2024). Exploring common method variance in analytics research in the Indian context: A comparative study with known techniques. FIIB Business Review, 13(5), 553-569.

Schroeder, T., Dodds, L., Georgiou, A., Gewald, H., & Siette, J. (2023). Older adults and new technology: Mapping review of the factors associated with older adults’ intention to adopt digital technologies. JMIR aging, 6(1), e44564.

Shin, D.-H., Jung, J., & Chang, B.-H. (2012). The psychology behind QR codes: User experience perspective. Computers in Human Behavior, 28(4), 1417-1426.

Tabira, K., Oguma, Y., Yoshihara, S., Shibuya, M., Nakamura, M., Doihara, N., . . . Manabe, T. (2024). Digital Peer-Supported App Intervention to Promote Physical Activity Among Community-Dwelling Older Adults: Nonrandomized Controlled Trial. JMIR aging, 7, e56184.

Tsai, H.-y. S., Shillair, R., Cotten, S. R., Winstead, V., & Yost, E. (2015). Getting grandma online: are tablets the answer for increasing digital inclusion for older adults in the US? Educational gerontology, 41(10), 695-709.

Tu, M., Wu, L., Wan, H., Ding, Z., Guo, Z., & Chen, J. (2022). The adoption of QR code mobile payment technology during COVID-19: a social learning perspective. Frontiers in Psychology, 12, 798199.

Usakli, A., & Rasoolimanesh, S. M. (2023). Which SEM to use and what to report? A comparison of CB-SEM and PLS-SEM Cutting edge research methods in hospitality and tourism (pp. 5-28): Emerald Publishing Limited.

Vaportzis, E., Giatsi Clausen, M., & Gow, A. J. (2017). Older adults perceptions of technology and barriers to interacting with tablet computers: a focus group study. Frontiers in Psychology, 8, 1687.

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.

Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, 157-178.

Von Kalckreuth, N., & Feufel, M. A. (2023). Extending the privacy calculus to the mHealth domain: survey study on the intention to use mHealth apps in Germany. JMIR Human Factors, 10, e45503.

Wang, K., Karling, M. J., Arellano-Valle, R. B., & Genton, M. G. (2024). Multivariate unified skew-t distributions and their properties. Journal of Multivariate Analysis, 203, 105322.

Wang, S., Bolling, K., Mao, W., Reichstadt, J., Jeste, D., Kim, H.-C., & Nebeker, C. (2019). Technology to support aging in place: Older adults’ perspectives. Paper presented at the Healthcare.

Wang, Y. (2021). Developing a nuanced understanding of the factors that influence digital inclusion for active and healthy ageing among older people. University of Sheffield.

Warpenius, E., Alasaarela, E., Sorvoja, H., & Kinnunen, M. (2015). A mobile user-interface for elderly care from the perspective of relatives. Informatics for Health and Social Care, 40(2), 113-124.

Williams, D. M. (2014). Designing an educational and intelligent human-computer interface for older adults. Marquette University.

Wong, K. P., Teh, P.-L., Lim, W. M., & Lee, S. W. H. (2025). Enhancing Older Adults’ Lives Through Positive Aging Perception, Quality-of-Life Enhancement, and Social Support to Drive Acceptance and Readiness Toward Indoor Assistive Technology: Cross-Sectional Study. JMIR aging, 8(1), e59665.

Wu, C., & Lim, G. G. (2024). Investigating older adults users’ willingness to adopt wearable devices by integrating the technology acceptance model (Utaut2) and the technology readiness index theory. Frontiers in public health, 12, 1449594.

Xie, B., Watkins, I., & Huang, M. (2011). Making web-based multimedia health tutorials senior-friendly: design and training guidelines Proceedings of the 2011 iConference (pp. 230-237).

Xie, Y., Wu, J., & Yow, W. Q. (2021). How Can We Encourage Older Adults to Adopt Digital Services? Innovation in Aging, 5(Suppl 1), 1008.

Yusif, S., Soar, J., & Hafeez-Baig, A. (2016). Older people, assistive technologies, and the barriers to adoption: A systematic review. International Journal of Medical Informatics, 94, 112-116.

Zhao, W., Kelly, R. M., Rogerson, M. J., & Waycott, J. (2023). Older adults using technology for meaningful activities during COVID-19: An analysis through the lens of self-determination theory. Paper presented at the Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems.

Zhao, Y., Zhang, T., Dasgupta, R. K., & Xia, R. (2023). Narrowing the age‐based digital divide: Developing digital capability through social activities. Information Systems Journal, 33(2), 268-298.

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Published

2025-12-19

How to Cite

Loo, J. T. K., Chang, J. J., Ahmadpour, S., Cheng, S. . C. Y., & Tan, K. L. (2025). Determinants of Technology Acceptance among Older Adults in Malaysia. PROCEEDING INTERNATIONAL BUSINESS AND ECONOMICS CONFERENCE (IBEC), 4(1), 326–348. https://doi.org/10.47663/ibec.v4i1.396

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