577
Views
1
CrossRef citations to date
0
Altmetric
Research Articles

Normative or Effective? The Role of News Diversity and Trust in News Recommendation Services

&
Pages 1216-1229 | Received 27 Jun 2021, Accepted 17 Mar 2022, Published online: 20 Apr 2022

References

  • Agag, G. M., & El-Masry, A. A. (2017). Why do consumers trust online travel websites? Drivers and outcomes of consumer trust toward online travel websites. Journal of Travel Research, 56(3), 347–369. https://doi.org/10.1177/0047287516643185
  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
  • Ajzen, I. (2002). Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. Journal of Applied Social Psychology, 32(4), 665–683. https://doi.org/10.1111/j.1559-1816.2002.tb00236.x
  • Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Prentice-Hall.
  • Alalwan, A. A. (2020). Mobile food ordering apps: An empirical study of the factors affecting customer e-satisfaction and continued intention to reuse. International Journal of Information Management, 50, 28–44. https://doi.org/10.1016/j.ijinfomgt.2019.04.008
  • Anderson, E. W., & Sullivan, M. W. (1993). The antecedents and consequences of customer satisfaction for firms. Marketing Science, 12(2), 125–143. https://doi.org/10.1287/mksc.12.2.125
  • Angst, C. M., & Agarwal, R. (2009). Adoption of electronic health records in the presence of privacy concerns: the elaboration likelihood model and individual persuasion. MIS Quarterly, 33(2), 339–370. https://doi.org/10.2307/20650295
  • Bakshy, E., Messing, S., & Adamic, L. A. (2015). Exposure to ideologically diverse news and opinion on Facebook. Science, 348(6239), 1130–1132. https://doi.org/10.1126/science.aaa1160
  • Barclay, D., Thompson, R., & Higgins, C. (1995). The partial least squares (PLS) approach to causal modeling: Personal computer adoption and use an illustration. Technology Studies, 2(2), 285–309.
  • Beam, M. A., & Kosicki, G. M. (2014). Personalized news portals: Filtering systems and increased news exposure. Journalism & Mass Communication Quarterly, 91(1), 59–77. https://doi.org/10.1177/1077699013514411
  • Belbad, A., de Jong, M., & Steehouder, M. (2010). How shall I trust the faceless and the intangible? A literature review on the antecedents of online trust. Computers in Human Behavior, 26(5), 857–869. https://doi.org/10.1016/j.chb.2010.03.013
  • Bennett, W. L., & Iyengar, S. (2008). A new era of minimal effects? The changing foundations of political communication. Journal of Communication, 58(4), 707–731. https://doi.org/10.1111/j.1460-2466.2008.00410.x
  • Bharat, K. (2006). And now, news. The Official Google Blog. Retrieved on 30 April, 2021. https://googleblog.blogspot.com/2006/01/and-now-news.html
  • Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351–370. https://doi.org/10.2307/3250921
  • Bhattacherjee, A., Perols, J., & Sanford, C. (2008). Information technology continuance: A theoretic extension and empirical test. Journal of Computer Information Systems, 49(1), 17–26. https://doi.org/10.1080/08874417.2008.11645302
  • Bollen, D., Knijnenburg, B. P., Willemsen, M. C., & Graus, M. (2010). The Fourth ACM Conference, understanding choice overload in recommender systems. Proceedings of on Recommender Systems, Barcelona (pp. 63–70). Association for Computing Machinery, New York, USA.
  • Bridge, D., & Kelly, J. P. (2006). Ways of computing diverse collaborative recommendations. Proceedings of the 4th International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems (pp. 41–50). Springer, Berlin.
  • Brown, J. D., Bybee, C. R., Wearden, S. T., & Murdock, S. D. (1987). Invisible power: Newspaper news sources and the limits of diversity. Journalism Quarterly, 64(1), 45–54. https://doi.org/10.1177/107769908706400106
  • Chang, Y., Hou, R.-J., Wang, K., Cui, A. P., & Zhang, C.-B. (2020). Effects of intrinsic and extrinsic motivation on social loafing in online travel communities. Computers in Human Behavior, 109, 106360. https://doi.org/10.1016/j.chb.2020.106360
  • Chellappa, R. K., & Sin, R. G. (2005). Personalization versus privacy: an empirical examination of the online consumer's dilemma. Information Technology and Management, 6(2–3), 181–202. https://doi.org/10.1007/s10799-005-5879-y
  • Chen, Y. H., & Corkindale, D. (2008). Towards an understanding of the behavioral intention to use online news services. Internet Research, 18(3), 286–312. https://doi.org/10.1108/10662240810883326
  • Cheng, Y., Sharma, S., Sharma, P., & Kulathunga, K. (2020). Role of personalization in continuous use intention of mobile news apps in India: Extending the UTAUT2 model. Information, 11(1), 33. https://doi.org/10.3390/info11010033
  • Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic mail emotion/adoption study. Information Systems Research, 14(2), 189–217. https://doi.org/10.1287/isre.14.2.189.16018
  • Choi, H., Park, J., & Jung, Y. (2018). The role of privacy fatigue in online privacy behavior. Computers in Human Behavior, 81, 42–51. https://doi.org/10.1016/j.chb.2017.12.001
  • Chumg, H., Cooke, L., Fry, J., & Hung, I. (2015). Factors affecting knowledge sharing in the virtual organisation: Employees’ sense of well-being as a mediating effect. Computers in Human Behavior, 44, 70–80. https://doi.org/10.1016/j.chb.2014.11.040
  • Chung, N., Koo, C., & Kim, J. K. (2014). Extrinsic and intrinsic motivation for using a booth recommender system service on exhibition attendees' unplanned visit behavior. Computers in Human Behavior, 30, 59–68. https://doi.org/10.1016/j.chb.2013.07.035
  • Chyi, H. I., & Lee, A. M. (2013). Online news consumption. Digital Journalism, 1(2), 194–211. https://doi.org/10.1080/21670811.2012.753299
  • Das, A., Datar, M., Garg, A., Rajaram, S. (2007). Google news personalization: Scalable online collaborative filtering. Proceedings of the 16th International Conference on World Wide Web (271–280). Association for Computing Machinery, New York, USA.
  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982
  • Díaz, A., & Gervás, P. (2005). Personalisation in news delivery systems: Item summarization and multi-tier item selection using relevance feedback. Web Intelligence and Agent Systems, 3(3), 135–154.
  • Dinev, T., & Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information Systems Research, 17(1), 61–80. https://doi.org/10.1287/isre.1060.0080
  • Feuz, M., Fuller, M., & Stalder, F. (2011). Personal web searching in the age of semantic capitalism: Diagnosing the mechanisms of personalisation. First Monday, 16(2) https://doi.org/10.5210/fm.v16i2.3344
  • Fisher, C. (2016). The trouble with “trust” in news media. Communication Research and Practice, 2(4), 451–465. https://doi.org/10.1080/22041451.2016.1261251
  • Fisher, J., Burstein, F., Lynch, K., & Lazarenko, K. (2008). Usability + usefulness = trust”: an exploratory study of Australian health web sites. Internet Research, 18(5), 477–498. https://doi.org/10.1108/10662240810912747.
  • Flavián, C., Guinalíu, M., & Gurrea, R. (2006). The role played by perceived usability, satisfaction and consumer trust on website loyalty. Information & Management, 43(1), 1–14. https://doi.org/10.1016/j.im.2005.01.002
  • Flaxman, S., Goel, S., & Rao, J. M. (2016). Filter bubbles, echo chambers, and online news consumption. Public Opinion Quarterly, 80(S1), 298–320. https://doi.org/10.1093/poq/nfw006
  • Fletcher, R., & Nielsen, R. K. (2018). Automated serendipity. Digital Journalism, 6(8), 976–989. https://doi.org/10.1080/21670811.2018.1502045
  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
  • Fukuyama, F. (1995). Trust: The social virtues & the creation of prosperity. The Free Press.
  • Geebren, A., Jabbar, A., & Luo, M. (2021). Examining the role of consumer satisfaction within mobile eco-systems: Evidence from mobile banking services. Computers in Human Behavior, 114, 106584. https://doi.org/10.1016/j.chb.2020.106584
  • Gefen, D., & Straub, D. (2003). Managing user trust in B2C e-services. e-Service Journal, 2(2), 7–24. https://doi.org/10.2979/esj.2003.2.2.7
  • Guo, X., Zhang, X., & Sun, Y. (2016). The privacy-personalization paradox in mHealth services acceptance of different age groups. Electronic Commerce Research and Applications, 16, 55–65. https://doi.org/10.1016/j.elerap.2015.11.001
  • Haim, M., Graefe, A., & Brosius, H. (2018). Burst of the filter bubble? Effects of personalization on the diversity of Google News. Digital Journalism, 6(3), 330–343. https://doi.org/10.1080/21670811.2017.1338145
  • Hair, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM). Sage publications.
  • 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. https://doi.org/10.1108/EBR-11-2018-0203
  • Hannak, A., Sapiezynski, P., Molavi Kakhki, A., Krishnamurthy, B., Lazer, D., Mislove, A., & Wilson, C. (2013). Measuring personalization of web search. Proceedings of The 22nd International Conference, on World Wide Web (pp. 527–538). Association for Computing Machinery, New York, USA.
  • Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
  • Hinds, J., Williams, E. J., & Joinson, A. N. (2020). “It wouldn't happen to me”: Privacy concerns and perspectives following the Cambridge Analytica scandal. International Journal of Human-Computer Studies, 143, 102498. https://doi.org/10.1016/j.ijhcs.2020.102498
  • Hu, M., Zhang, M., & Luo, N. (2016). Understanding participation on video sharing communities: The role of self-construal and community interactivity. Computers in Human Behavior, 62, 105–115. https://doi.org/10.1016/j.chb.2016.03.077
  • Iyengar, S., & Hahn, K., S. (2009). Red media, blue media: Evidence of ideological selectivity in media use. Journal of Communication, 59(1), 19–39. https://doi.org/10.1111/j.1460-2466.2008.01402.x
  • Jiang, Z., Heng, C. S., & Choi, B. C. F. (2013). Privacy concerns and privacy-protective behavior in synchronous online social interactions. Information Systems Research, 24(3), 579–595. https://doi.org/10.1287/isre.1120.0441
  • Kalogeropoulos, A., Suiter, J., Udris, L., & Eisenegger, M. (2019). News media trust and news consumption: Factors related to trust in news in 35 countries. International Journal of Communication, 13, 3672–3693.
  • Kalyanaraman, S., & Sundar, S. S. (2006). The psychological appeal of personalized content in web portals: Does customization affect attitudes and behavior? Journal of Communication, 56(1), 110–132. https://doi.org/10.1111/j.1460-2466.2006.00006.x
  • Keith, M. J., Lowry, P. B., Evans, C. M., Babb, J. (2014). Privacy fatigue: the effect of privacy control complexity on consumer electronic information disclosure. Thirty Fifth International Conference on Information Systems, ICIS(2014) (pp. 1–18). Auckland, New Zealand.
  • Kim, S. S., & Son, J.-Y. (2009). Out of dedication or constraint? A dual model of post-adoption phenomena and its empirical test in the context of online services. MIS Quarterly, 33(1), 49–70. https://doi.org/10.2307/20650278
  • Knijnenburg, B. P., Willemsen, M. C., Gantner, Z., Soncu, H., & Newell, C. (2012). Explaining the user experience of recommender systems. User Modeling and User-Adapted Interaction, 22(4–5), 441–504. https://doi.org/10.1007/s11257-011-9118-4
  • Kohring, M., & Matthes, J. (2007). Trust in news media: Development and validation of a multidimensional scale. Communication Research, 34(2), 231–252. https://doi.org/10.1177/0093650206298071
  • Komiak, S. Y. X., & Benbasat, I. (2006). The effects of personalization and familiarity on trust and adoption of recommendation agents. MIS Quarterly, 30(4), 941–960 https://doi.org/10.2307/25148760.
  • Koohang, A., Paliszkiewicz, J., & Goluchowski, J. (2018). Social media privacy concerns: trusting beliefs and risk beliefs. Industrial Management & Data Systems, 118(6), 1209–1228. https://doi.org/10.1108/IMDS-12-2017-0558
  • KoreaTechToday. (2019). AI-based personalization service increased content consumption. Retrieved on 30 April, 2021. https://www.koreatechtoday.com/naver-ai-based-personalization-service-increased-content-consumption/.
  • Kwak, K. T., Lee, S. Y., & Lee, S. W. (2021). News and user characteristics used by personalized algorithms: The case of Korea’s news aggregators, Naver News and Kakao News. Technological Forecasting and Social Change, 171, 120940. https://doi.org/10.1016/j.techfore.2021.120940
  • Lavie, T., Sela, M., Oppenheim, I., Inbar, O., & Meyer, J. (2010). User attitudes towards news content personalization. International Journal of Human-Computer Studies, 68(8), 483–495. https://doi.org/10.1016/j.ijhcs.2009.09.011
  • Lee, S., & Choi, J. (2017). Enhancing user experience with conversational agent for movie recommendation: Effects of self-disclosure and reciprocity. International Journal of Human-Computer Studies, 103, 95–105. https://doi.org/10.1016/j.ijhcs.2017.02.005
  • Lee, A. M., & Chyi, H. I. (2014). When newsworthy is not noteworthy. Journalism Studies, 15(6), 807–820. https://doi.org/10.1080/1461670X.2013.841369
  • Lee, C. H., & Cranage, D. A. (2011). Personalisation-privacy paradox: The effects of personalisation and privacy assurance on customer responses to travel web sites. Tourism Management, 32(5), 987–994. https://doi.org/10.1016/j.tourman.2010.08.011
  • Lee, D., & Kim, D. (2019). Kakao deep reading index: Consumption time as a key factor in news curation algorithm. KSII Transactions on Internet and Information Systems, 13(10), 4833–4848. https://doi.org/10.3837/tiis.2019.10.001
  • Lee, N., & Kwon, O. (2015). A privacy-aware feature selection method for solving the personalization-privacy paradox in mobile wellness healthcare services. Expert Systems with Applications, 42(5), 2764–2771. https://doi.org/10.1016/j.eswa.2014.11.031
  • Lee, J. D., & Moray, N. (1994). Trust, self-confidence, and operator's adaptation to automation. International Journal of Human-Computer Studies, 40(1), 153–184. https://doi.org/10.1006/ijhc.1994.1007
  • Lee, A. R., Son, S. M., & Kim, K. K. (2016). Information and communication technology overload and social networking service fatigue: a stress perspective. Computers in Human Behavior, 55(A), 51–61. https://doi.org/10.1016/j.chb.2015.08.011
  • Liang, T. P., Lai, H. J., & Ku, Y. C. (2006). Personalized content recommendation and user satisfaction: Theoretical synthesis and empirical findings. Journal of Management Information Systems, 23(3), 45–70. https://doi.org/10.2753/MIS0742-1222230303
  • Liébana-Cabanillas, F., Muñoz-Leiva, F., & Rejón-Guardia, F. (2013). The determinants of satisfaction with e-banking. Industrial Management and Data Systems, 113(5), 750–767. https://doi.org/10.1108/02635571311324188
  • Lin, H., Fan, W., & Chau, P. Y. (2014). Determinants of users' continuance of social networking sites: A self-regulation perspective. Information & Management, 51(5), 595–603. https://doi.org/10.1016/j.im.2014.03.010
  • Lischka, J. A., & Messerli, M. (2016). Examining the benefits of audience integration: Does sharing of or commenting on online news enhance the loyalty of online readers? Digital Journalism, 4(5), 597–620. https://doi.org/10.1080/21670811.2015.1068128.
  • Milne, G. R., & Culnan, M. J. (2004). Strategies for reducing online privacy risks: Why consumers read (or don’t read) online privacy notices. Journal of Interactive Marketing, 18(3), 15–29. https://doi.org/10.1002/dir.20009
  • Möller, J., Trilling, D., Helberger, N., & van Es, B. (2018). Do not blame it on the algorithm: An empirical assessment of multiple recommender systems and their impact on content diversity. Information, Communication & Society, 21(7), 959–977. https://doi.org/10.1080/1369118X.2018.1444076
  • Monzer, C., Moeller, J., Helberger, N., & Eskens, S. (2020). User perspectives on the news personalisation process: Agency, trust and utility as building blocks. Digital Journalism, 8(9), 1142–1162. https://doi.org/10.1080/21670811.2020.1773291
  • Mosteller, J., & Poddar, A. (2017). To share and protect: Using regulatory focus theory to examine the privacy paradox of consumers' social media engagement and online privacy protection behaviors. Journal of Interactive Marketing, 39, 27–38. https://doi.org/10.1016/j.intmar.2017.02.003
  • Muslim, A., Sajad, R., & Maryam, A. (2014). User satisfaction with mobile websites: the impact of perceived usefulness (PU), perceived ease of use (PEOU) and trust. Nankai Business Review International, 5(3), 258–274. https://doi.org/10.1108/NBRI-01-2014-0005
  • Nechushtai, E., & Lewis, S. C. (2019). What kind of news gatekeepers do we want machines to be? Filter bubbles, fragmentation, and the normative dimensions of algorithmic recommendations. Computers in Human Behavior, 90, 298–307. https://doi.org/10.1016/j.chb.2018.07.043
  • Nelson, E. C., Verhagen, T., & Noordzij, M. L. (2016). Health empowerment through activity trackers: An empirical smart wristband study. Computers in Human Behavior, 62, 364–374. https://doi.org/10.1016/j.chb.2016.03.065
  • Newman, N., Fletcher, R., Kalogeropoulos, A., & Nielsen, R. K. (2019). Reuters Institute digital news report 2019. Reuters Institute for the Study of Journalism.
  • Newman, N., Fletcher, R., Schulz, A., Andi, S., & Nielsen, R. K. (2020). Reuters Institute digital news report 2020. Reuters Institute for the Study of Journalism.
  • Nguyen, T. T., Harper, F. M., Terveen, L., & Konstan, J. A. (2018). User personality and user satisfaction with recommender systems. Information Systems Frontiers, 20(6), 1173–1189. https://doi.org/10.1007/s10796-017-9782-y
  • Nikolov, D., Oliveira, D. F. M., Flammini, A., & Menczer, F. (2015). Measuring online social bubbles. PeerJ Computer Science, 1(e38), e38–14. https://doi.org/10.7717/peerj-cs.38
  • Nunally, J. C. (1978). Psychometric theory. McGraw-Hill.
  • Pariser, E. (2011). The filter bubble: How the new personalized web is changing what we read and how we think. Penguin.
  • Park, J. H. (2014). The effects of personalization on user continuance in social networking sites. Information Processing & Management, 50(3), 462–475. https://doi.org/10.1016/j.ipm.2014.02.002
  • Podsakoff, P. M., & Organ, D. W. (1986). Self-reports in organizational research: Problems and prospects. Journal of Management, 12(4), 531–544. https://doi.org/10.1177/014920638601200408
  • Ribeiro, M. T., Ziviani, N., Moura, E. S. D., Hata, I., Lacerda, A., & Veloso, A. (2015). Multiobjective pareto-efficient approaches for recommender systems. ACM Transactions on Intelligent Systems and Technology, 5(4), 1–20. https://doi.org/10.1145/2629350
  • Russmann, U., & Hess, A. (2020). News consumption and trust in online and social media: An in-depth qualitative study of young adults in Austria. International Journal of Communication, 14, 3184–3201.
  • Sakagami, H., & Kamba, T. (1997). Learning personal preferences on online newspaper articles from user behaviors. Computer Networks, 29(8–13), 1447–1455. https://doi.org/10.1016/S0169-7552(97)00016-0
  • Sarstedt, M., Ringle, C. M., Smith, D., Reams, R., & Hair, J. F. (2014). Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers. Journal of Family Business Strategy, 5(1), 105–115. https://doi.org/10.1016/j.jfbs.2014.01.002
  • Scheibehenne, B., Greifeneder, R., & Todd, P. M. (2010). Can there ever be too many options? a meta-analytic review of choice overload. Journal of Consumer Research, 37(3), 409–425. https://doi.org/10.1086/651235
  • Schroeder, R., & Kralemann, M. (2005). Journalism Ex Machina—Google News Germany and its news selection processes. Journalism Studies, 6(2), 245–247. https://doi.org/10.1080/14616700500057486
  • Sela, M., Lavie, T., Inbar, O., Oppenheim, I., & Meyer, J. (2015). Personalizing news content: An experimental study. Journal of the Association for Information Science and Technology, 66(1), 1–12. https://doi.org/10.1002/asi.23167
  • Sethna, B. N., Sunil, H., & Salil, T. (2021). Antecedents of satisfaction with Facebook in the context of user involvement, privacy, and trust. Journal of Customer Behaviour, 20 (in press). https://doi.org/10.1362/147539221X16206323664287
  • Song, J., & Zahedi, F. M. (2007). Trust in health Infomediaries. Decision Support Systems, 43(2), 390–407. https://doi.org/10.1016/j.dss.2006.11.011
  • Sundar, S. S., & Marathe, S. S. (2010). Personalization versus customization: The importance of agency, privacy, and power usage. Human Communication Research, 36(3), 298–322. https://doi.org/10.1111/j.1468-2958.2010.01377.x
  • Sunstein, C. R. (2009). Republic.Com 2.0. Princeton University Press.
  • Tam, K. Y., & Ho, S. Y. (2006). Understanding the impact of web personalization on user information processing and decision outcomes. MIS Quarterly, 30(4), 865–890. https://doi.org/10.2307/25148757
  • Taylor, S., & Todd, P. A. (1995). Understanding technology usage: A test of competing models. Information Systems Research, 6(2), 144–176. https://doi.org/10.1287/isre.6.2.144
  • Thurman, N., Moeller, J., Helberger, N., & Trilling, D. (2019). My friends, editors, algorithms, and I: Examining audience attitudes to news selection. Digital Journalism, 7(4), 447–469. https://doi.org/10.1080/21670811.2018.1493936
  • Tsfati, Y. (2010). Online news exposure and trust in the mainstream media: Exploring possible associations. American Behavioral Scientist, 54(1), 22–42. https://doi.org/10.1177/0002764210376309
  • Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. https://doi.org/10.1287/mnsc.46.2.186.11926
  • 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, 36(1), 157–178. https://doi.org/10.2307/41410412
  • Wessel, M., Thies, F. (2015). The effects of personalization on purchase intentions for online news: An experimental study of different personalization increments. ECIS 2015 Completed Research Papers Paper 200. ECIS, Munster, Germany.
  • Willemsen, M. C., Graus, M. P., & Knijnenburg, B. P. (2016). Understanding the role of latent feature diversification on choice difficulty and satisfaction. User Modeling and User-Adapted Interaction, 26(4), 347–389. https://doi.org/10.1007/s11257-016-9178-6
  • Yang, M., Shao, Z., Liu, Q., & Liu, C. (2017). Understanding the quality factors that influence the continuance intention of students toward participation in MOOCs. Educational Technology Research and Development, 65(5), 1195–1214. https://doi.org/10.1007/s11423-017-9513-6
  • Ye, Q., Luo, Y., Chen, G., Guo, X., Wei, Q., & Tan, S. (2019). Users intention for continuous usage of mobile news apps: The roles of quality, switching costs, and personalization. Journal of Systems Science and Systems Engineering, 28(1), 91–109. https://doi.org/10.1007/s11518-019-5405-0
  • Zhang, S., Zhao, L., Lu, Y., & Yang, J. (2016). Do you get tired of socializing? An empirical explanation of discontinuous usage behaviour in social network services. Information & Management, 53(7), 904–914. https://doi.org/10.1016/j.im.2016.03.006
  • Zhu, Q., Yin, H., Liu, J., & Lai, K. (2014). How is employee perception of organizational efforts in corporate social responsibility related to their satisfaction and loyalty towards developing harmonious society in Chinese enterprises? Corporate Social Responsibility and Environmental Management, 21(1), 28–40. https://doi.org/10.1002/csr.1302
  • Ziegler, C.-N., McNee, S. M., Konstan, J. A., Lausen, G. (2005). Improving recommendation lists through topic diversification. Proceedings of the 14th International Conference on World Wide Web (22–32). Association for Computing Machinery, New York, USA.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.