© Media Watch 9 (1) 18-36, 2018
ISSN 0976-0911 e-ISSN 2249-8818
News Consumption through SNS Platforms: Extended Motivational Model
ISMAIL SHEIKH YUSUF AHMED1 2, SYED ARABI IDID2 & ZETI AZREEN AHMAD2
1Qatar University, Qatar
2International Islamic University Malaysia, Malaysia
The emergence of new media technologies has redefined how people, particularly the youth, are exposed to the news. Social networking sites (SNS), in particular, have widely changed the manner in which news is consumed. SNS platforms have emerged as news sources where people engage in several activities such as sharing, commenting and discussing news with peers, acquaintances and family members. Thus, drawing on the extended version of the motivational model, this study attempts to determine contributing factors. Using a stratified random sampling procedure, this study compiles a sample from leading higher education institutions in a Sub-Saharan African country. The data are then analysed using a structural equation modelling technique with SmartPLS software and the both the validity and reliability indexes are reported. The findings suggest that students’ attitude towards news consumption (ATT) via SNS platforms is influenced directly by perceived usefulness (PU), perceived enjoyment (PE) and subjective norms (SN) and indirectly by PE and SN factors. In addition, PU and PE are positively predicted by SN. Furthermore, ATT directly predicts SNS news consumption (SNC), while PU, PE and SN indirectly contribute to SNC.
Keywords: News consumption, social networking sites, motivational model,structural equation modelling
Ahmed, I. Y. S., El-Kasim, M., & Mustapha, L. K. (2017). University students’ intention of smartphone adoption for academic activities: Testing and extended TAM model. Media Watch: Journal of Communication, 8(2), 208–221.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.
Al-Debei, M., Al-Lozi, E., & Papazafeiropoulou, A. (2013). Why people keep coming back to Facebook: Explaining and predicting continuance participation from an extended theory of planned behaviour perspective. Decision Support Systems, 55(1), 43–54.
Al-Gahtani, S. (2001). The applicability of TAM outside North America: An empirical test in the United Kingdom. Information Resources Management Journal, 14(13), 26–28.
Al-Gahtani, S., & King, M. (1999). Attitudes, satisfaction and usage: Factors contributing to each in the acceptance of information technology. Behaviour & Information Technology, 18(4), 277–297.
Aladwani, A. M. (2014). Gravitating towards Facebook (GoToFB): What it is? and How can it be measured? Computers in Human Behavior, 33(April), 270–278.
Aref, N. (2013). Online news information seeking/ : An analysis of the usage of search engines vs social networks in Egypt. Journal of Middle East Media, 9(1), 46–68.
ASMR. (2011). Facebook Usage/ : Factors and Analysis. Dubia School of Government (Vol. 1). Retrieved from http://www.dsg.ae/NEWSANDEVENTS/UpcomingEvents/ASMRHome.aspx
Associated Press. (2014). Study: Middle East news consumers demand trustworthy , high-quality content. Retrieved July 7, 2016, from http://www.ap.org/Content/Press-Release/2014/Study-Middle-East-news-consumers-demand-trustworthy-high-quality-content
Babbie, E. (2011). The basics of social research (5th ed.). Belmont: Wadsworth.
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 074–094.
Bajaj, A., & Nidumolu, S. R. (1998). A feedback model to understand information system usage. Information & Management, 33(4), 213–224.
Baker, R. K., & White, K. M. (2010). Predicting adolescents’ use of social networking sites from an extended theory of planned behaviour perspective. Computers in Human Behavior, 26(6), 1591–1597.
BBC. (2016). Somalia profile-Media. Retrieved July 11, 2016, from http://www.bbc.com/news/world-africa-14094550
Boyd, D., & Ellison, N. B. (2007). Social Network Sites: Definition, History, and Scholarship. Journal of Computer-Mediated Communication, 13(1), 210–230.
Çelik, H., & Yilmaz, V. (2011). Extending the technology acceptance model for adoption of e-shopping by consumers in Turkey. Journal of Electronic Commerce Research, 12(2), 152–164. Retrieved from http://www.csulb.edu/journals/jecr/issues/20112/Paper3.pdf
Chang, C. C., Hung, S. W., Cheng, M. J., & Wu, C. Y. (2015). Exploring the intention to continue using social networking sites: The case of Facebook. Technological Forecasting and Social Change, 95, 48–56. http://doi.org/10.1016/j.techfore.2014.03.012
Chang, C., Hajiyev, J., & Su, C. (2017). Examining the students’ behavioral intention to use e-learning in Azerbaijan? The General Extended Technology Acceptance Model for E-learning approach. Computers and Education, 111, 128–143. http://doi.org/10.1016/j.compedu.2017.04.010
Chen, S.-C., Chen, H.-H., & Chen, M.-F. (2009). Determinants of satisfaction and continuance intention towards self-service technologies. Industrial Management & Data Systems, 109(9), 1248–1263.
Cheung, C. M. K., Chiu, P.-Y., & Lee, M. K. O. (2011). Online social networks: Why do students use facebook? Computers in Human Behavior, 27(4), 1337–1343.
Daud, N. M., Kassim, N. E. M., Said, W. S. R. W. M., & Noor, M. M. M. (2011). Determining critical success factors of mobile banking adoption in Malaysia. Australian Journal of Basic and Applied Sciences, 5(9), 252–265.
Davis, F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–339.
Davis, F. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–339.
Davis, F., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the work place. Journal of Applied Psychology, 22(14), 1111–1132.
Davis, F., Bagozzi, R., & Warshaw, P. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003.
Davis, F. D. (1993). User acceptance of information technology: System characteristics, user perceptions and behavioral impact. International Journal of Man-Machine Studies, 38(3), 475–487.
Dhaha, I. S. Y., & Igale, A. B. (2013). Facebook usage among Somali youth: A test of uses and gratificaitons approach. International Journal of Humanities and Social Sciences, 3(3), 299–313.
Dhaha, I. Y. S., & Igale, A. B. (2014). Motives as predictors of Facebook addiction: Empirical evidence from Somalia. SEARCH/ : The Journal of the South East Asia Research Centre, 6(3), 47–68.
Dong, T. P., Cheng, N. C., & Wu, Y. C. J. (2014). A study of the social networking website service in digital content industries: The Facebook case in Taiwan. Computers in Human Behavior, 30(1), 708–714.
Dunne, A., Lawlor, M.-A., & Rowley, J. (2010). Young People’s Use of Online Social Networking Sites: A Uses and Gratifications Perspective social networking sites – a uses. Journal of Research in Interactive Marketing, 4(1), 46–58.
El-kasim, M. (2016). Predicting social media use among public relations practitioners: Applying Technology Acceptance Model (TAM). Unpublished Doctoral Thesis: International Islamic University Malaysia.
Ellison, N. B., & Boyd, D. (2013). Sociality through Social Network Sites. In The Oxford Handbook of Internet Studies. (p. 151– 172). Oxford: Oxford University Press.
Facebook. (2017). Our history. Retrieved July 31, 2017, from http://newsroom.fb.com/company-info/
Feng, X., Fu, S., & Qin, J. (2016). Determinants of consumers’ attitudes toward mobile advertising: The mediating roles of intrinsic and extrinsic motivations. Computers in Human Behavior, 63(10), 334–341.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
Flanagin, A. J., & Metzger, M. J. (2000). Perceptions of Internet information credibility. Journalism & Mass Communication Quarterly, 77(3), 515–540.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
Freeman, K. S. (2013). News consumption behavior of young adults in Malaysia. International Journal of Social Science and Humanity, 3(2), 121–124.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis (7th ed). Upper Saddle River, New Jersey: Pearson Prentice Hall.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A primer on Partial least squares structural equation modeling (PLS-SEM). Los Angeles: Sage Publications.
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a Silver Bullet. The Journal of Marketing Theory and Practice, 19(2), 139–152.
Hair, J. F., Sarstedt, M., Ringle, M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Academy of Marketing Science, 40(3), 414–433.
Heijden, H. van der. (2003). Factors influencing the usage of websites: The case of a generic portal in the Netherlands. Information and Management, 40(6), 541–549.
Henseler, J., & Chin, W. (2010). A Comparison of approaches for the analysis of interaction effects between latent variables using Partial Least Squares path modeling. Structural Equation Modeling: A Multidisciplinary Journal, 17(1), 82–109.
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In R. r. Sinkovics & P. N. Ghauri (Eds.), New Challenges to International Marketing. Bingley: Emerald Group Publishing Limited.
Heritage Institute for Policy Studies. (2013). The State of Higher Education in Somalia: Privatization, rapid growth, and the need for regulation. Retrieved from http://www.heritageinstitute.org/wp- content/uploads/2013/08/HIPS_Higher_Education_ENGLISH.pdf
Holden, R. J., & Karsh, B. (2010). The Technology Acceptance Model: Its past and its future in health care. Journal of Biomedical Informatics, 43(1), 159–172.
Hsu, C. L., Yu, C. C., & Wu, C. C. (2014). Exploring the continuance intention of social networking websites: an empirical research. Information Systems and E-Business Management, 12(2), 139–163.
Igbaria, M. (1993). User acceptance of microcomputer technology/ : An empirical-test. Omega-International Journal of Management Science, 21(1), 73–90.
Igbaria, M. (1994). An examination of the factors contributing Microcomputer technology acceptance. Accounting, Management & Information Technology, 4(4), 205–224.
Igbaria, M., Guimaraes, T., & Davis, G. B. (1995). Testing the determinants of microcomputer usage via a structural equation model. Journal of Management Information Systems, 11(4), 87–114.
Internet World Statistics. (2017). World Statistcs-Africa. Retrieved July 11, 2016, from http://www.internetworldstats.com/africa.htm
Jan, M. T., & Haque, A. (2014). Antecedents of the use of online banking by students in Malaysia extended TAM validated through SEM. International Business Management, 8(5), 277–284.
Kummer, C. (2013). Students’ intentions to use wikis in higher education. In R.Alt. & B. Franczyk (Eds.), Proceedings of the 11th International Conference on Wirtschaftsinformatik (WI2013) (Vol. 2, pp. 1493–1508).
Kwon, S. J., Park, E., & Kim, K. J. (2014). What drives successful social networking services? A comparative analysis of user acceptance of Facebook and Twitter. The Social Science Journal, 51(4), 534–544.
Lee, A. M., & Chyi, H. I. (2014). Motivational consumption model: Exploring the psychological structure of news use. Journalism & Mass Communication Quarterly, 91(4), 706–724.
Lee, J., Cho, H., Gay, G., Davidson, B., & Ingraffea, A. (2003). Technology acceptance and social networking in distance learning. Educational Technology & Society, 6(2), 50–61.
Lee, M. K. O., Cheung, C. M. K., & Chen, Z. (2005). Acceptance of Internet-based learning medium: The role of extrinsic and intrinsic motivation. Information and Management, 42(8), 1095–1104.
Leng, G. S., Lada, S., & Muhammad, M. Z. (2011). An exploration of social networking sites (SNS) adoption in Malaysia using tehnology acceptance model (TAM), theory of planned behavior (TPB) and intrinsic motivation. Journal of Internet Banking and Commerce, 16(2), 1–27.
Lin, C.-P., & Bhattacherjee, A. (2008). Elucidating Individual Intention to Use Interactive Information Technologies: The Role of Network Externalities. International Journal of Electronic Commerce, 13(1), 85–108.
Lin, H., Fan, W., & Chau, P. Y. K. (2014). Determinants of users’ continuance of social networking sites: A self-regulation perspective. Information & Management, 51(5), 595–603.
Lu, J., Liu, C., Yu, C.-S., & Wang, K. (2008). Determinants of accepting wireless mobile data services in China. Information & Management, 45(1), 52–64.
Lucas, H. C., & Spitler, V. K. (1999). Technology Use and Performance: A Field Study of Broker Workstations. Decision Sciences, 30(2), 291–311.
Luo, M. M., & Remus, W. (2014). Uses and gratifications and acceptance of Web-based information services: An integrated model. Computers in Human Behavior, 38(September), 281–295.
Mazman, S. G., & Usluel, Y. K. (2010). Modeling educational usage of Facebook. Computers & Education, 55(2), 444–453.
Media Insight Project. (2015). How millennials get news: Inside the habits of America’s first digital generation. Retrieved from http://www.americanpressinstitute.org/wp-content/uploads/2015/08/Media-Insight-Millennials-Report-March-2015.pdf
Moon, J., & Kim, Y. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38(4), 217–230.
Nasri, W., & Charfeddine, L. (2012). An exploration of Facebook. com adoption in Tunisia using Technology Acceptance Model and Theory of Reasoned Action. Interdisciplinary Journal of Contemporary Reserch in Business, 4(5), 948–969.
Nysveen, H., Pedersen, P. E., & Thorbjornsen, H. (2005). Intentions to use mobile services: Antecedents and cross-service comparisons. Journal of the Academy of Marketing Science, 33(3), 330–346. http://doi.org/10.1177/0092070305276149
Ofcom. (2015). News consumption in the UK: Research report. Retrieved from http://stakeholders.ofcom.org.uk/market-data-research/other/tv-research/news-2015/
Papacharissi, Z., & Rubin, A. (2000). Predictors of Internet use. Journal of Broadcasting & Electronic Media, 44(2), 175–196.
Park, E., Baek, S., Ohm, J., & Chang, H. J. (2014). Determinants of player acceptance of mobile social network games: An application of extended technology acceptance model. Telematics and Informatics, 31(1), 3–15.
Petty, D. (2016). Facebook just prioritized updates from friends and family , taking focus off news.
Pew Research Center. (2016). News use across social media platforms 2016. Retrieved from http://www.journalism.org/2016/05/26/news-use-across-social-media-platforms-2016/
Pietro, L. Di, Virgilio, F. Di, & Pantano, E. (2012). Social network for the choice of tourist destination: attitude and behavioural intention. Journal of Hospitality and Tourism Technology, 3(1), 60–76.
Pillai, A., & Mukherjee, J. (2011). User acceptance of hedonic versus utilitarian social networking web sites. Journal of Indian Business Research, 3(3), 180–191.
Pinho, J. C. M. R., & Soares, A. M. (2011). Examining the technology acceptance model in the adoption of social networks. Journal of Research in Interactive Marketing, 5(2/3), 116–129.
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. The Journal of Applied Psychology, 88(5), 879–903.
Praveena, K., & Thomas, S. (2014). Continuance Intention to Use Facebook: A Study of Perceived Enjoyment and TAM. Bonfring International Journal of Industrial Engineering and Management Science, 4(1), 24–29.
Reinecke, L., Vorderer, P., & Knop, K. (2014). Entertainment 2.0? The Role of Intrinsic and Extrinsic Need Satisfaction for the Enjoyment of Facebook Use. Journal of Communication, 64(3), 417–438.
Reuters Institute For the Study of Journalism. (2016). Reuters Institute digital news report 2016. Oxford. Retrieved from http://www.digitalnewsreport.org/
Ringle, C. M., Wende, S., & Becker, J.-M. (2017). SmartPLS 3. Bönningstedt: SmartPLS. Retrieved from http://www.smartpls.com
Ryan, R., & Deci, E. (2000). Self-determination theory and the facilitation of intrinsic motivation. American Psychologist, 55(1), 68–78.
Sayid, O., Echchabi, A., & Aziz, H. (2012). Investigating Mobile Money Acceptance in Somalia: An Empirical Study. Pakistan Journal of Commerce & Social Sciences, 6(2), 269–281.
Schepers, J., & Wetzels, M. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information & Management, 44(1), 90–103.
Schierz, P. G., Schilke, O., & Wirtz, B. W. (2010). Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic Commerce Research and Applications, 9(3), 209–216.
StatsMonkey. (2015). Social Network Usage Statistics in Somalia. Retrieved July 11, 2016, from https://www.statsmonkey.com/sunburst/21701-somalia-social-network-usage-statistics-2015.php
Subramanian, G. H. (1994). A replication of perceived usefulness and perceived ease of. Decision Sciences, 25(5,6), 863.
Sun, Y., Liu, L., Peng, X., Dong, Y., & Barnes, S. J. (2014). Understanding Chinese users’ continuance intention toward online social networks: An integrative theoretical model. Electronic Markets, 24(1), 57–66.
Venkatesh, V., & Davis, F. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.
White, M. G. (2012). What Types of Social Networks Exist. Retrieved from http://socialnetworking.lovetoknow.com/What_Types_of_Social_Networks_Exist
Wu, B., & Chen, X. (2017). Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model. Computers in Human Behavior, 67(2), 221–232.
Xu, C., Ryan, S., Prybutok, V., & Wen, C. (2012). It is not for fun: An examination of social network site usage. Information & Management, 49(5), 210–217.
Yi, M. Y., & Hwang, Y. (2003). Predicting the use of web-based information systems: Self-efficacy, enjoyment, learning goal orientation, and the technology acceptance model. International Journal of Human-Computer Studies, 59(4), 431–449.
Yi, M. Y., Jackson, J. D., Park, J. S., & Probst, J. C. (2006). Understanding information technology acceptance by individual professionals: Toward an integrative view. Information & Management, 43(3), 350–363. http://doi.org/10.1016/j.im.2005.08.006
Yoo, S. J., Han, S. H., & Huang, W. (2012). The roles of intrinsic motivators and extrinsic motivators in promoting e-learning in the workplace: A case from South Korea. Computers in Human Behavior, 28(3), 942–950.
Ismail Sheikh Yusuf Ahmed is currently affiliated with Mass Communication Department of Qatar University. He is finalizing his doctoral programme at the Department of Communication, International Islamic University Malaysia (IIUM). His main research interest areas include political communication, media effects, news consumption/ credibility, and new media technologies adoption and consequences.
Syed Arabi Idid is a professor in the Department of Communication at International Islamic University Malaysia. He was Dean of the Research Centre in July 2001 and was later appointed as Rector of IIUM from June 2006 until May 2011.
Zeti Azreen Ahmad is an assistant professor in the Department of Communication at Kulliyyah of Islamic Revealed Knowledge and Human Sciences, IIUM. Currently she is engaged in several research projects that include the role of media in promoting social well-being and public relations research.