User Roles in Online Communities and Their Moderating Effect on Online Community Usage Intention: An Integrated Approach

References

• Agrifoglio, R., Black, S., Metallo, C., & Ferrara., M. (2012). Extrinsic versus intrinsic motivation in continued twitter usage. Journal of Computer Information Systems, 53(1), 33–41.
   Web of Science ®Google Scholar
• Alexa. (n.d.). Retrieved from http://www.alexa.com/siteinfo/incisozluk.com.tr
   Google Scholar
• Angeletou, S., Rowe, M., & Alani, H. (2011). Modelling and analysis of user behaviour in online communities. Proceedings of International Semantic Web Conference (pp. 35–50), Berlin, Heidelberg. doi: 10.1007/978-3-642-25073-6_3.
   Google Scholar
• Arazy, O., Ortega, F., Nov, O., Yeo, L., & Balila, A. (2015). Functional roles and career paths in Wikipedia. Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing (pp. 1092–1105).
   Google Scholar
• Baek, S. I., & Kim, Y. M. (2015). Longitudinal analysis of online community dynamics. Industrial Management & Data Systems, 115(4), 661–677. doi:10.1108/IMDS-09-2014-0266
   Web of Science ®Google Scholar
• Belanche, D., Casaló, L. V., & Guinalíu, M. (2012). Website usability, consumer satisfaction and the intention to use a website: The moderating effect of perceived risk. Journal of Retailing and Consumer Services, 19(1), 124–132. doi:10.1016/j.jretconser.2011.11.001
   Google Scholar
• Biddle, B. J. (1986). Recent development in role theory. Annual Review of Sociology, 12, 67–92. doi:10.1146/annurev.so.12.080186.000435
   Web of Science ®Google Scholar
• Borgatti, S. P., & Everett, M. G. (1997). Network analysis of 2-mode data. Social Networks, 19(3), 243–269. doi:10.1016/S0378-8733(96)00301-2
   Web of Science ®Google Scholar
• Borgatti, S. P., Mehra, A., Brass, D. J., & Labianca, G. (2009). Network analysis in the social sciences. Science, 323, 892–895. doi:10.1126/science.1165821
   PubMed Web of Science ®Google Scholar
• Borrero, J. D., Yousafzai, S. Y., Javed, U., & Page, K. L. (2014). Expressive participation in Internet social movements: Testing the moderating effect of technology readiness and sex on student SNS use. Computers in Human Behavior, 30, 39–49. doi:10.1016/j.chb.2013.07.032
   Web of Science ®Google Scholar
• Brandtzaeg, P. B., & Heim, J. (2011). A typology of social networking sites users. International Journal of Web Based Communities, 7(1), 28–51. doi:10.1504/IJWBC.2011.038124
   Google Scholar
• Brewer, D. D., & Webster, C. M. (2000). Forgetting of friends and its effects on measuring friendship networks. Social Networks, 21(4), 361–373. doi:10.1016/S0378-8733(99)00018-0
   Web of Science ®Google Scholar
• Brewer, J. (2000). Ethnography. Buckingham, England: Open University Press.
   Google Scholar
• Buntain, C., & Golbeck, J. (2014). Identifying social roles in reddit using network structure. Proceedings of the 23rd International Conference on World Wide Web (pp. 615–620). Seoul, Korea. doi:10.1145/2567948.2579231.
   Google Scholar
• Castañeda, J. A., Muñoz-Leiva, F., & Luque, T. (2007). Web Acceptance Model (WAM): Moderating effects of user experience. Information & Management, 44(4), 384–396. doi:10.1016/j.im.2007.02.003
   Web of Science ®Google Scholar
• Chan, J., Hayes, C., & Daly, E. M. (2010). Decomposing discussion forums and boards using user roles. Icwsm, 10, 215–218.
   Google Scholar
• Chi, E. H., Munson, S., Fischer, G., Vieweg, S., & Parr, C. (2010). Advancing the design of technology-mediated social participation systems. Computer, 43(11), 29–35. doi:10.1109/MC.2010.304
   Web of Science ®Google Scholar
• Chi, H., Yeh, H., & Hung, W. C. (2012). The moderating effect of subjective norm on cloud computing users’ perceived risk and usage intention. International Journal of Marketing Studies, 4(6), 95. doi:10.5539/ijms.v4n6p95
   Google Scholar
• Childers, T. L., Carr, C. L., Peck, J., & Carson, S. (2001). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of Retailing, 77(4), 511–535. doi:10.1016/S0022-4359(01)00056-2
   Web of Science ®Google Scholar
• Choi, D., Han, J., Chung, T., Ahn, Y. Y., Chun, B. G., & Kwon, T. T. (2015). Characterizing conversation patterns in Reddit: From the perspectives of content properties and user participation behaviors. Proceedings of the 2015 ACM on Conference on Online Social Networks (pp. 233–243). doi: 10.1145/2817946.2817959.
   Google Scholar
• Chung, J. E., Park, N., Wang, H., Fulk, J., & McLaughlin, M. (2010). Age differences in perceptions of online community participation among non-users: An extension of the Technology Acceptance Model. Computers in Human Behavior, 26(6), 1674–1684. doi:10.1016/j.chb.2010.06.016
   Web of Science ®Google Scholar
• Çiçek, M., & Eren-Erdogmus, I. (2013). Social media marketing: Exploring the user typology in Turkey. International Journal of Technology Marketing, 8(3), 254–271. doi:10.1504/IJTMKT.2013.055343
   Google Scholar
• Clauset, A., Newman, M. E., & Moore, C. (2004). Finding community structure in very large networks. Physical Review E, 70(6), 1–6. doi:10.1103/PhysRevE.70.066111
   Web of Science ®Google Scholar
• Cooil, B., Keiningham, T. L., Aksoy, L., & Hsu, M. (2007). A longitudinal analysis of customer satisfaction and share of wallet: Investigating the moderating effect of customer characteristics. Journal of Marketing, 71(1), 67–83. doi:10.1509/jmkg.71.1.67
   Web of Science ®Google Scholar
• Cronbach, L. J. (1971). Educational neasurement (2nd ed.). Washington, DC: American Council on Education.
   Google Scholar
• Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. doi:10.2307/249008
   Web of Science ®Google Scholar
• 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. doi:10.1287/mnsc.35.8.982
   Web of Science ®Google Scholar
• Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal Of Applied Social Psychology, 22(14), 1111–1132. doi:10.1111/j.1559-1816.1992.tb00945.x
   Web of Science ®Google Scholar
• De Valck, K., Langerak, F., Verhoef, P. C., & Verlegh, P. W. (2007). Satisfaction with virtual communities of interest: Effect on members’ visit frequency. British Journal of Management, 18(3), 241–256. doi:10.1111/j.1467-8551.2006.00499.x
   Web of Science ®Google Scholar
• Eysenbach, G., & Till., J. (2001). Ethical issues in qualitative research on Internet communities. British Medical Journal, 323, 1103–1105. doi:10.1136/bmj.323.7321.1103
   PubMed Web of Science ®Google Scholar
• Fernandez, M., Scharl, A., Bontcheva, K., & Alani, H. (2014). User profile modelling in online communities. Proceedings of the Third International Conference on Semantic Web Collaborative Spaces, 1275 (pp. 1–15).
   Google Scholar
• Fetscherin, M., & Lattemann, C. (2008). User acceptance of virtual worlds. Journal of Electronic Commerce Research, 9(3), 231.
   Web of Science ®Google Scholar
• Frankel, M. S., & Siang., S. (1999). Ethical and legal aspects of human subjects research on the Internet. Washington, DC: American Association for the Advancement of Science.
   Google Scholar
• Füller, J., Hutter, K., Hautz, J., & Matzler, K. (2014). User roles and contributions in innovation-contest communities. Journal of Management Information Systems, 31(1), 273–308. doi:10.2753/MIS0742-1222310111
   Web of Science ®Google Scholar
• Füller, J., Jawecki, G., & Mühlbacher., H. (2007). Innovation creation by online basketball communities. Journal of Business Research, 60(1), 60–71. doi:10.1016/j.jbusres.2006.09.019
   Web of Science ®Google Scholar
• Geddes, C. (2011). Achieving critical mass in social networks. Journal of Database Marketing & Customer Strategy Management, 18(2), 123–128. doi:10.1057/dbm.2011.14
   Google Scholar
• Gleave, E., Welser, H. T., Lento, T. M., & Smith, M. A. (2009). A conceptual and operational definition of ‘social role’ in online community. Proceedings of the 42nd Hawaii International Conference on System Science (pp. 1530–1605). Big Island, HI, USA.
   Google Scholar
• Golder, S. A., & Donath., J. (2004). Social roles in electronic communities. Internet Research, 5, 19–22.
   Google Scholar
• Gong, W., Lim, E. P., & Zhu, F. (2015). Characterizing silent users in social media communities. ICWSM (pp. 140–149).
   Google Scholar
• Goodhue, D. L., Thompson, R., & Lewis, W. (2013). Why you shouldn’t use PLS: Four reasons to be uneasy about using PLS in analyzing path models. Proceedings of System Sciences (HICSS), 2013 46th Hawaii International Conference on System Sciences (pp. 4739–4748). doi: 10.1109/HICSS.2013.612
   Google Scholar
• Hacker, J., Bodendorf, F., & Lorenz., P. (2017, February 12–15). Helper, sharer or seeker?– A concept to determine knowledge worker roles in enterprise social networks. Proceedings of 13th International Conference on Wirtschaftsinformatik (pp. 668–682), St. Gallen, Switzerland.
   Google Scholar
• Hair, J. F., Anderson, R. E., Babin, B. J., & Black, W. C. (2010). Multivariate data analysis: A global perspective (7th ed.). Upper Saddle River, NJ: Pearson.
   Google Scholar
• Han, J. Y., Kim, J. H., Yoon, H. J., Shim, M., McTavish, F. M., & Gustafson, D. H. (2012). Social and psychological determinants of levels of engagement with an online breast cancer support group: Posters, lurkers, and nonusers. Journal of Health Communication, 17(3), 356–371. doi:10.1080/10810730.2011.585696
   PubMed Web of Science ®Google Scholar
• Hartzel, K. S., Marley, K. A., & Spangler, W. E. (2016). Online social network adoption: A cross-cultural study. Journal of Computer Information Systems, 56(2), 87–96. doi:10.1080/08874417.2016.1117367
   Web of Science ®Google Scholar
• Haythornthwaite, C. (1996). Social network analysis: An approach and technique for the study of information exchange. Library & Information Science Research, 18(4), 323–342. doi:10.1016/S0740-8188(96)90003-1
   Google Scholar
• Hecking, T., Chounta, I. A., & Hoppe, H. U. (2015). Analysis of user roles and the emergence of themes in discussion forums. Proceedings of Network Intelligence Conference (ENIC), 2015 Second European (pp. 114–121). doi: 10.1109/ENIC.2015.24
   Google Scholar
• Hernández, B., Jiménez, J., & Martín, M. J. (2010). Customer behavior in electronic commerce: The moderating effect of e-purchasing experience. Journal of Business Research, 63(9), 964–971. doi:10.1016/j.jbusres.2009.01.019
   Web of Science ®Google Scholar
• Iskoujina, Z., Ciesielska, M., Roberts, J., & Li, F. (2017). Grasping the business value of online communities. Journal of Organizational Change Management, 30(3), 396–416. doi:10.1108/JOCM-02-2016-0023
   Web of Science ®Google Scholar
• Keil, M., Tan, B. C., Wei, K. K., Saarinen, T., Tuunainen, V., & Wassenaar, A. (2000). A cross-cultural study on escalation of commitment behavior in software projects. MIS Quarterly, 24(2), 299–325. doi:10.2307/3250940
   Web of Science ®Google Scholar
• Kemp, S. (2016). Digital Year Book. Retrieved January 11, 2017, from http://www.slideshare.net/wearesocialsg/2016-digital-yearbook
   Google Scholar
• Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). New York, NY: Guilford Press.
   Google Scholar
• Kock, N. (2011). Using WarpPLS in e-collaboration studies: An overview of five main analysis steps. Advancing Collaborative Knowledge Environments: New Trends in E-Collaboration: New Trends in E-Collaboration (pp. 180–191). Hershey, PA: Information Science Reference.
   Google Scholar
• Kock, N. (2014). Advanced mediating effects tests, multi-group analyses, and measurement model assessments in PLS-based SEM. International Journal of e-Collaboration, 10(1), 1–13. doi:10.4018/ijec.2014010101
   Google Scholar
• Krause, J., Croft, D. P., & James., R. (2007). Social network theory in the behavioural sciences: Potential applications. Behavirol Econology and Sociobiology, 62(1), 15–27. doi:10.1007/s00265-007-0445-8
   Web of Science ®Google Scholar
• Kulviwat, S., Bruner, G. C., & Al-Shuridah, O. (2009). The role of social influence on adoption of high tech innovations: The moderating effect of public/private consumption. Journal of Business Research, 62(7), 706–712. doi:10.1016/j.jbusres.2007.04.014
   Web of Science ®Google Scholar
• Lee, A. J., Yang, F. C., Tsai, H. C., & Lai, Y. Y. (2014). Discovering content-based behavioral roles in social networks. Decision Support Systems, 31(59), 250–261. doi:10.1016/j.dss.2013.12.004
   Google Scholar
• Lee, W., Tyrrell, T., & Erdem., M. (2013). Exploring the behavioral aspects of adopting technology: Meeting planners’ use of social network media and the impact of perceived critical mass. Journal of Hospitality and Tourism Technology, 4(1), 6–22. doi:10.1108/17579881311302329
   Google Scholar
• Leyden, J. (2010). Turkish pranksters load Facebook Translate with swears. Retrieved from https://www.theregister.co.uk/2010/07/29/facebook_translation_turkey_prank/
   Google Scholar
• Liao, C., To, P. L., Liu, C. C., Kuo, P. Y., & Chuang, S. H. (2011). Factors influencing the intended use of web portals. Online Information Review, 35(2), 237–254. doi:10.1108/14684521111128023
   Web of Science ®Google Scholar
• Liao, S., & Chou, E. Y. (2012). Intention to adopt knowledge through virtual communities: Posters vs lurkers. Online Information Review, 36(3), 442–461. doi:10.1108/14684521211241440
   Web of Science ®Google Scholar
• Lim, W. M. (2014). Sense of virtual community and perceived critical mass in online group buying. Journal of Strategic Marketing, 22(3), 268–283. doi:10.1080/0965254X.2013.876068
   Google Scholar
• Lin, H. F., & Lee., G. H. (2006). Determinants of success for online communities: An empirical study. Behavirol Information Technology, 25(6), 479–488. doi:10.1080/01449290500330422
   Web of Science ®Google Scholar
• Lin, H.-F. (2007). The role of online and offline features in sustaining virtual communities: An empirical study. Internet Research, 17(2), 119–138. doi:10.1108/10662240710736997
   Web of Science ®Google Scholar
• Lingyun, Q., & Li, D. (2008). Applying TAM in B2C E-commerce research: An extended model. Tsinghua Science & Technology, 13(3), 265–272. doi:10.1016/S1007-0214(08)70043-9
   Google Scholar
• Lorenzo-Romero, C., Constantinides, E., & Alarcón-del-Amo, M. D. C. (2011). Segmenting the web 2.0 market: Behavioural and usage patterns of social web consumers. Journal of Business Case Studies (JBCS), 6(7), 55–66. doi:10.19030/jbcs.v6i7.1064
   Google Scholar
• Lou, H., Luo, W., & Strong., D. (2000). Perceived critical mass effect on groupware acceptance. European Journal of Information Systems, 9(2), 91–103. doi:10.1057/palgrave.ejis.3000358
   Web of Science ®Google Scholar
• Marin, A., & Wellman, B. (2011). Social network analysis: An introduction. In J. Scott & P. J. Carrington (Eds.), The SAGE handbook of social network analysis (pp. 11–25). London, England: Sage Publications Ltd.
   Google Scholar
• Marsden, P. V. (2003). Interviewer effects in measuring network size using a single name generator. Social Networks, 25(1), 1–16. doi:10.1016/S0378-8733(02)00009-6
   Web of Science ®Google Scholar
• Martino, F., & Spoto, A. (2006). Social Network Analysis: A brief theoretical review and further perspectives in the study of Information Technology. PsychNology Journal, 4(1), 53–86.
   Google Scholar
• Mislove, A. E. (2009). Online social networks: measurement, analysis, and applications to distributed information systems (Published PhD thesis). Rice University, Houston, TX, USA.
   Google Scholar
• Moon, J. W., & Kim., Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38(4), 217–230. doi:10.1016/S0378-7206(00)00061-6
   Web of Science ®Google Scholar
• Moore, G. C., & Benbasat., I. (1991). Development of an instrument to measure the perceptions of adopting an information technology adoption. Information Systems Research, 2(3), 192–222. doi:10.1287/isre.2.3.192
   Web of Science ®Google Scholar
• Moqbel, M. (2012). The effect of the use of social networking sites in the workplace on job performance ( PhD. Dissertation), Texas A&M International University.
   Google Scholar
• Muller, M., Shami, N. S., Millen, D. R., & Feinberg, J. (2010). We are all lurkers: Consuming behaviors among authors and readers in an enterprise file-sharing service. Proceedings of the 16th ACM international conference on Supporting group work (pp. 201–210). doi: 10.1145/1880071.1880106.
   Google Scholar
• Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York, NY: McGraw-Hill.
   Google Scholar
• Nunnally, J. C., & Bernstein., I. H. (1994). The assessment of reliability. Psychometric Theory, 3(1), 248–292.
   Google Scholar
• Oliver, P., Marwell, G., & Teixeira., R. (1985). A theory of the critical mass. Interdependence, group heterogeneity, and the production of collective action. American Journal of Sociology, 91(3), 522–556. doi:10.1086/228313
   Web of Science ®Google Scholar
• Palmer, J. W. (2002). Web site usability, design, and performance metrics. Information Systems Research, 13(2), 151–167. doi:10.1287/isre.13.2.151.88
   Web of Science ®Google Scholar
• Pfeil, U., Svangstu, K., Ang, C. S., & Zaphiris, P. (2011). Social roles in an online support community for older people. International Journal of Human-Computer Interaction, 27(4), 323–347. doi:10.1080/10447318.2011.540490
   Web of Science ®Google Scholar
• Pluempavarn, P., Panteli, N., Joinson, A., Eubanks, D., Watts, L., & Dove, J. (2011). Social roles in online communities: Relations and trajectories. Proceedings of 6th Mediterranean Conference on Information Systems (pp. 2012), Nicosia, Cyprus, 4.
   Google Scholar
• Preece, J., & Shneiderman, B. (2009). The reader-to-leader framework: Motivating technology-mediated social participation. AIS Transactions on Human-Computer Interaction, 1(1), 13–32. doi:10.17705/1thci.00005
   Google Scholar
• Qin, L., Kim, Y., Hsu, J., & Tan, X. (2011). The effects of social influence on user acceptance of online social networks. International Journal of Human-Computer Interaction, 27(9), 885–899. doi:10.1080/10447318.2011.555311
   Web of Science ®Google Scholar
• Rauniar, R., Rawski, G., Yang, J., & Johnson, B. (2014). Technology acceptance model (TAM) and social media usage: An empirical study on Facebook. Journal of Enterprise Information Management, 27(1), 6–30. doi:10.1108/JEIM-04-2012-0011
   Web of Science ®Google Scholar
• Ren, Y., Kraut, R., & Kiesler, S. (2007). Applying common identity and bond theory to design of online communities. Organization Studies, 28(3), 377–408. doi:10.1177/0170840607076007
   Web of Science ®Google Scholar
• Rheingold, H. (1993). The virtual community: Finding commection in a computerized world. Boston, MA: Addison-Wesley Longman Publishing Co., Inc.
   Google Scholar
• Risser, H. S., & Bottoms., S. (2014). “Newbies” and “Celebrities”: Detecting social roles in an online network of teachers via participation patterns. International Journal of Computer-Supported Collaboration Learning, 9(4), 433–450. doi:10.1007/s11412-014-9197-4
   Web of Science ®Google Scholar
• Salter-Townshend, M., & Brendan Murphy, T. (2015). Role analysis in networks using mixtures of exponential random graph models. Journal of Computational and Graphical Statistics, 24(2), 520–538. doi:10.1080/10618600.2014.923777
   PubMed Web of Science ®Google Scholar
• Shen, A. X., Cheung, C. M., Lee, M. K., & Chen, H. (2011). How social influence affects we-intention to use instant messaging: The moderating effect of usage experience. Information Systems Frontiers, 13(2), 157–169. doi:10.1007/s10796-009-9193-9
   Web of Science ®Google Scholar
• Shin, D. H. (2010). Analysis of online social networks: A cross-national study. Online Information Review, 34(3), 473–495. doi:10.1108/14684521011054080
   Web of Science ®Google Scholar
• Sledgianowski, D., & Kulviwat., S. (2009). Using social network sites: The effects of playfulness, critical mass and trust in a hedonic context. Journal of Computer Information Systems, 49(4), 74–83.
   Web of Science ®Google Scholar
• Söllner, M., Hoffmann, A., & Leimeister., J. M. (2016). Why different trust relationships matter for information systems users. European Journal of Information Systems, 25(3), 274–287. doi:10.1057/ejis.2015.17
   Web of Science ®Google Scholar
• Tamjidyamcholo, A., Kumar, S., Sulaiman, A., & Gholipour, R. (2016). Willingness of members to participate in professional virtual communities. Quality & Quantity, 50(6), 2515–2534. doi:10.1007/s11135-015-0274-1
   Web of Science ®Google Scholar
• Tarhini, A., Hone, K., & Liu, X. (2014). Measuring the moderating effect of gender and age on e-learning acceptance in England: A structural equation modeling approach for an extended technology acceptance model. Journal of Educational Computing Research, 51(2), 163–184. doi:10.2190/EC.51.2.b
   Web of Science ®Google Scholar
• Trend Micro (2010). Facebook prank, lost in translation. Retrieved from http://countermeasures.trendmicro.eu/facebook-prank-lost-in-translation/
   Google Scholar
• Van Slyke, C., Ilie, V., Lou, H., & Stafford, T. (2007). Perceived critical mass and the adoption of a communication technology. European Journal of Information Systems, 16(3), 270–283. doi:10.1057/palgrave.ejis.3000680
   Web of Science ®Google Scholar
• Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204. doi:10.1287/mnsc.46.2.186.11926
   Web of Science ®Google Scholar
• Welser, H. T., Cosley, D., Kossinets, G., Lin, A., Dokshin, F., Gay, G., & Smith, M. (2011). Finding social roles in Wikipedia. Proceedings of the 2011 iConference (pp. 122–129). Seattle, Washington, USA. doi:10.1145/1940761.1940778.
   Google Scholar
• White, A. J., Chan, J., Hayes, C., & Murphy, T. B. (2012). Mixed membership models for exploring user roles in online fora. Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media (pp. 1–4).
   Google Scholar
• Wu, B., Zhou, X., Jin, Q., Lin, F., & Leung, H. (2017). Analyzing social roles based on a hierarchical model and data mining for collective decision-making support. IEEE Systems Journal, 11(1), 356–365. doi:10.1109/JSYST.2014.2386611
   Web of Science ®Google Scholar
• Yeh, N. C., Chuan-Chuan Lin, J., & Lu, H. P. (2011). The moderating effect of social roles on user behaviour in virtual worlds. Online Information Review, 35(5), 747–769. doi:10.1108/14684521111176480
   Web of Science ®Google Scholar