Research has shown that social networking sites (SNS), such as Facebook and WhatsApp, make it more convenient for older adults to bond with friends and family. However, despite such benefits, studies also found few older adults use SNS, and even fewer older adults use SNS in less developed nations. Therefore, it is important to identify factors that can influence intention to use SNS in older adults, especially among the Malaysian Chinese population, as they will face an aging society earlier than other ethnic groups in Malaysia. This study used the Technology Acceptance Model and Reasoned Action Approach to examine whether factors such as perceived ease of use, perceived usefulness, selfefficacy, and subjective norms, are significant predictors of intention to use SNS among Malaysian Chinese older adults. Purposive and snowball sampling methods were used to recruit 288 Malaysian Chinese adults aged 60 and above to participate in this survey. Multiple regression was used to analyze the data. Results showed that subjective norms played the most important role in intention to use SNS among Malaysian Chinese older adults. These findings can provide insight for program managers and policymakers when promoting SNS use among older adults.

Bahasa Abstract

Studi menunjukkan bahwa situs jejaring sosial (SJS) seperti "Facebook" dan "WhatsApp", membuat orang tua lebih nyaman untuk menjalin ikatan dengan teman dan keluarga. Namun, di samping manfaat menggunakan SJS, penelitian menemukan lebih sedikit lansia yang menggunakan situs jejaring sosial, dan jumlah lansia yang menggunakan SJS bahkan lebih sedikit di negara yang kurang berkembang. Oleh karena itu, penting untuk mengetahui faktor-faktor yang dapat memengaruhi niat untuk menggunakan SJS, terutama di kalangan orang tua Tionghoa Malaysia karena orang Tionghoa Malaysia akan menghadapi masalah kelompok masyarakat lanjut usia lebih awal daripada etnis lain di Malaysia. Penelitian ini menggunakan Technology Acceptance Model dan Reasoned Action Approach untuk menguji apakah faktor-faktor, seperti persepsi kemudahan penggunaan, persepsi kegunaan, efikasi diri dan norma subjektif, merupakan prediktor yang signifikan dari niat untuk menggunakan SJS di antara lansia Tionghoa Malaysia. Metode purposive dan snowball sampling digunakan untuk mengumpulkan 288 lansia Tionghoa Malaysia berusia 60 tahun ke atas untuk berpartisipasi dalam survei ini. Multiple Regression digunakan untuk menganalisis data. Hasil penelitian menunjukkan bahwa norma subjektif memainkan peran paling penting dalam niat untuk menggunakan SJS di kalangan manula Tionghoa Malaysia. Temuan ini dapat memberikan wawasan bagi manajer program dan pembuat kebijakan ketika mempromosikan SJS kepada orang tua.


Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour. Englewood Cliffs, NJ: Prentice Hall. Al-Ammary, J. (2010). Factors affecting the acceptance and use of computers and the internet by older adults people in the Kingdom of Bahrain. Proceeding to International Conference on Information Management, 2010, 9. Alarcón-del-Amo, M., Lorenzo-Romero, C., & GómezBorja, M. (2016). Cultural influence on the adoption of social networking sites. International Journal of Market Research, 58(2), 277-300. doi:10.2501/IJMR-2016-015 Alfian, H. (2017). 9.6 Million senior citizens expected in M’sia By 2050, Why this is worrying. Malaysian Digest. Retrieved from http://malaysiandigest.com/features/705341-9-6- million-senior-citizens-expected-in-m-sia-by-2050-whythis-is-worring.html Baecker, R., Sellen, K., Crosskey, S., Boscart, V., & Neves, B. B. (2014). Technology to reduce social isolation and loneliness. ASSETS ’14. Proceedings of the 16th international ACM SIGACCESS conference on computers & accessibility. ACM, 27-34. doi: 10.1145/2661334.2661375. Bell, C., Fausset, C., Farmer, S., Nguyen, J., Harley, L., & Fain, W.B. (2013). Examining social media use among elderly. Proceedings of the 24th ACM Conference on Hypertext and Social Media. ACM, 158- 163. doi: 10.1145/2481492.2481509. Brandyberry, A., Li, X., & Lin, L. (2010). Determinants of perceived usefulness and perceived ease of use in individual adoption of social network sites. AMCIS 2010 Proceedings. Retrieved from http://aisel.aisnet.org/amcis2010/544 Braun, M. T. (2013). Obstacles to social networking website use among elderly. Computers in Human Behavior, 29(3), 673-680. doi: 10.1016/j.chb.2012.12.004. Chai, S. T., & Hamid, T. A. (2015). Population ageing and the Malaysian Chinese: Issues and challenges. Malaysian Journal of Chinese Studies, 4(1), 1-13. Chan A. H. S., & Chen, K. (2016). Personal and other factors affecting acceptance of smartphone technology by older Chinese adults. Applied Ergonomics, 54, 62- 71. doi:10.1016/j.apergo.2015.11.015. 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, doi: 10.1080/00140139.2014.895855.. Constantinides, E., Lorenzo-Romero, C., & AlarcónDel-Amo, M. (2013). Social networking sites as business tool: A study of user behavior. Springer Verlag. doi:10.1007/978-3-642-28409-0_9. Cornejo, R., Tentori, M., & Favela, J. (2013). Enriching in-person encounters through social media: A study on family connectedness for the elderly. International Journal Human-Computer Studies, 71, 889-899. doi:10.1016/j.ijhcs.2013.04.001 Davis, F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13, 319-340. doi: 10.2307/249008. Davis, F., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003. doi: 10.1287/mnsc.35.8.982 Department of Statistics Malaysia. (2016). Population Projection (Revised), Malaysia, 2010-2040. Retrieved from https://www.dosm.gov.my/v1/index.php?r=column/cthe meByCat&cat=118&bul_id=Y3kwU2tSNVFDOWp1Y mtZYnhUeVBEdz09&menu_id=L0pheU43NWJwRW VSZklWdzQ4TlhUUT09 Draper, S. W. (2016). Effect size. Retrieved from http://www.psy.gla.ac.uk/~steve/best/effect.html Eid, M. I., & Al-Jabri, I. M. (2016). Social networking, knowledge sharing, and student learning: The case of university student. Computers & Education, 99, 14-27. doi: 10.1016/j.compedu.2016.04.007. Erik, V. I., Rains, A. S., & Wright, B. K. (2017). Does social network site use buffer against well-being loss when older adultss face reduced functional ability? Computers in Human Behavior, 70, 168-177. doi: 10.1016/j.chb.2016.12.058. Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175-191. doi: 10.3758/BF03193146 Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behaviour. Reading, MA: AddisonWesley. Fishbein, M., & Ajzen, I. (2011). Predicting and changing behavior: The reasoned action approach. New York, NY: Psychology Press Gatti, F. M., Brivio, E., & Galimberti, C. (2017) “The future is ours too”: A training process to enable the learning perception and increase self-efficacy in the use of tablets in the elderly. Educational Gerontology, 43, 209-224. doi: 10.1080/03601277.2017.1279952. Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51-90. doi: 10.2307/30036519 Hasan, B., & Ahmed, M.U. (2007). Effects of interface style on user perceptions and behavioral intention to use computer systems. Computers in Human Behavior, 23, 3025-3037. doi: 10.1016/j.chb.2006.08.016 Havelka, D. (2003). Students’ beliefs and attitudes toward information technology. Information Systems Education Journal, 1(40), 3. Retrieved from http://isedj.org/1/40/ Hill, R., Beynon-Davies, P., & Williams, M. D. (2008). Older people and internet engagement: Acknowledging social moderators of internet adoption, access and use. Information Technology and People, 21(3), 244-266. doi:10.1108/09593840810896019. Hubona G. S., & A. Burton-Jones, (2003). "Modeling the user acceptance of e-mail". 36th Annual Hawaii International Conference on System Sciences, 2003. Proceedings of the, Big Island, HI, USA, 2003, 10. doi: 10.1109/HICSS.2003.1173675. Jap, T. (2017). The technology acceptance model of online game in Indonesian adolescents. Makara Human Behavior Studies In Asia, 21(1), 24-31. doi:10.7454/mssh.v21i1.3497 Jung, E. H., & Sundar, S. S. (2016). Senior citizens on Facebook: How do they interact and why? Computers in Human Behavior, 61, 27-35. doi: 10.1016/j.chb.2016.02.080. Karahanna, E., & Straub, D.W. (1999). The psychological origins of perceived usefulness and ease of use. Information & Management, 35(4), 237-250. doi: 10.1016/S0378-7206(98)00096-2 Kim, S., Lee, J., & Yoon, D. (2015). Norms in social media: The application of theory of reasoned action and personal norms in predicting interactions with Facebook page like ads. Communication Research Reports, 32(4), 322-331. doi: 10.1080/08824096.2015.1089851. Kim, Y., & Glassman, M. (2013). Beyond search and communication: Development and validation of the Internet Self-efficacy Scale (ISS). Computers in Human Behavior, 29(4), 1421-1429. doi: 10.1016/j.chb.2013.01.018 Olson, K. E., O'Brien M. A., Rogers W. A., & Charness N. (2011). Diffusion of technology: Frequency of use for younger and older adults. Ageing International, 36(1),123-145. doi: 10.1007/s12126-010-9077-9 Pan, S., & Jordan-Marsh, M. (2010). Internet use intention and adoption among Chinese older adults: From the expanded technology acceptance model perspective. Computers in Human Behavior, 26(5), 1111-1119. doi: 10.1108/07363760910927037. Phang, W. C., Sutanto, J., Kankanhalli, A., Li, Y., Tan, B. C. Y., & Teo, H. H. (2006). Senior citizens’ acceptance of information systems: A study in the context of e- Government services. IEEE Transactions of Engineering Management, 53(4), 555-569. doi: 10.1109/TEM.2006.883710 Pornwasin, A. (2015). Elderly people worldwide not sold on mobile internet. Retrieved 14 Jan 2016, from http://digital.asiaone.com/digital/news/older adultspeople-worldwide-not-sold-mobile-internet Ramayah, T., & Jaafar, M, (2008). Technology usage among construction students. The moderating role of gender. Journal of Construction in Developing Countries, 13(1). Retrieved from http://web.usm.my/jcdc/vol13_1_2008/4_T.Ramayah% 20(p.%2063%20-77).pdf Renaud, K. & Biljon, J. V. (2008). Predicting technology acceptance and adoption by the elderly: a qualitative study. In: Proceedings of the 2008 Annual Research Conference of the South African Institute of Computer. doi: 10.1145/1456659.1456684 Rouibah, K., Ramayah, T., & Oh, S. M. (2009). User acceptance of internet banking in Malaysia: Test of three competing models. International Journal of EAdoption, 1(1), 1-19. Doi: 10.4018/jea.2009010101. Shaughnessy, J., Zechmeister, E., & Zechmeister, J. (2015). Research methods in psychology. New York: McGraw-Hill. Smith, P. B. (2015). Yes, subjective norms are important, but let’s not lose sight of cultural differences. Journal of Cross-Cultural Psychology, 46(10), 1310– 1313. doi: 10.1177/0022022115599444 Tsai, T. H., Chang, H. T., & Ho, Y. L. (2016). Perceptions of a specific family communication application among grandparents and grandchildren: An extension of the technology acceptance model. PLoS ONE, 11(6), 1-24. doi: 10.1371/journal.pone.0156680. Tsai, T.-H., Chang, H.-T., Chen, Y.-J., & Chang, Y.-S. (2017). Determinants of user acceptance of a specific social platform for older adults: An empirical examination of user interface characteristics and behavioral intention. Plos ONE, 12(8). doi: 10.1371/journal.pone.0180102. Tsai, T-H., Chang, H-T., Chang, Y-C., & Chang, Y. S. (2017). Personality disclosure on social network sites: An empirical examination of differences in Facebook usage behavior, profile contents and privacy settings. Computers in Human Behaviour, 76, 469-482. doi: 10.1016/j.chb.2017.08.003. Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-315. doi:10.1111/j.15405915.2008.00192.x. Venkatesh, V., & Davis, F. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204. doi: 10.1287/mnsc. Vroman K., Arthanat S., & Lysack C. (2015). “Who over 65 is online?” Older adults’ disposition toward information communication technology. Computers in Human Behavior, 43, 156-166. doi:10.1016/j.chb.2014.10.018. Wang, J. L., Jackson, L. A., Wang, H. Z., & Gaskin, J. (2015). Predicting social networking site (SNS) use: Personality, attitudes, motivation and internet selfefficacy. Personality and Individual Differences, 80, 119-124. doi: 10.1016/j.paid.2015.02.016 Weerasinghe, S., & Hindagolla, M. B. (2018). Technology acceptance model and social network sites (SNS): A selected review of literature. Library Review, 67, 142-153. doi:10.1108/GKMC-09-2017-0079. Wirtz, B. W., & Göttel, V. (2016). Technology acceptance in social media: Review, synthesis and directions for future empirical research. Journal of Electronic Commerce Research, 17(2), 97-115. Retrieved from http://www.jecr.org/node/489 World Health Organization. (2017). Process of translation and adaptation of instruments. Retrieved from https://www.who.int/substance_abuse/research_tools/tra nslation/en/ Zhang, Z., & Lu, T. (2011). Understanding SNS users’ intention: An extension of the technology acceptance model. 2011 International Conference on Electrical and Control Engineering, ICECE 2011 – Proceedings, 5148-5151. doi: 10.1109/ICECENG.2011.6057409.



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