The effects of multiple team membership on networking online and offline: using multilevel multiple membership modeling

References

• Anderson, N. B. (1998). Levels of analysis in health science: A framework for integrating sociobehavioral and biomedical research. Neuroimmunomodulation, 840, 563–576.
   Web of Science ®Google Scholar
• Bertolotti, F., Mattarelli, E., Vignoli, M., & Macri, D. M. (2015). Exploring the relationship between multiple team membership and team performance: The role of social networks and collaborative technology. Research Policy, 44(4), 911–924. doi: 10.1016/j.respol.2015.01.019
   Web of Science ®Google Scholar
• Blau, P. M. (1977). Inequality and heterogeneity: A primitive theory of social structure. New York: Free Press.
   Google Scholar
• Breiger, R. L. (1974). Duality of persons and groups. Social Forces, 53 (2), 181–190. doi: 10.1093/sf/53.2.181
   Web of Science ®Google Scholar
• Boase, J. (2008). Personal networks and the personal communication system. Information, Communication & Society, 11(4), 490–508. doi: 10.1080/13691180801999001
   Google Scholar
• Burt, R. S. (1993). The social structure of competition. In N. Nohria & R. Eccles (Eds.), Networks and organizations (pp. 57–91). Cambridge, MA: Harvard Business School Press.
   Google Scholar
• Chamakiotis, P., Dekoninck, E. A., & Panteli, N. (2013). Factors influencing creativity in virtual design teams: An interplay between technology, teams and individuals. Creativity & Innovation Management, 22(3), 265–279. doi: 10.1111/caim.12039
   Web of Science ®Google Scholar
• Chen, W., & McDonald, S. (2014). Do networked workers have more control? The implications of teamwork, telework, ICTs, and social capital for job decision latitude. American Behavioral Scientist, 59 (4), 492–507. doi: 10.1177/0002764214556808
   Web of Science ®Google Scholar
• Cox, T. (2001). Creating the multicultural organization: A strategy for capturing the power of diversity. University of Michigan Business School management series (1st ed.). San Francisco, CA: Jossey-Bass.
   Google Scholar
• Cummings, J. N., & Haas, M. R. (2012). So many teams, so little time: Time allocation matters in geographically dispersed teams. Journal of Organizational Behavior, 33(3), 316–341. doi: 10.1002/job.777
   Web of Science ®Google Scholar
• Cummings, J. N., & Kiesler, S. (2005). Collaborative research across disciplinary and organizational boundaries. Social Studies of Science, 35(5), 703–722. doi: 10.1177/0306312705055535
   Web of Science ®Google Scholar
• Dimitrova, D., Gruzd, A., Hayat, Z., Mo, G. Y., Mok, D., Robbins, T., … Zhuo, X. (2013). Navel gazing: Studying a networked scholarly organization. In Advances in network analysis and its applications (pp. 271–298). Berlin: Springer.
   Google Scholar
• Dimitrova, D., & Koku, E. (2010). Managing collaborative research networks: The dual life of a virtual community of practice. International Journal of Virtual Communities and Social Networking, 2(4), 1–22. doi: 10.4018/jvcsn.2010100101
   Google Scholar
• Dimitrova, D., & Wellman, B. (2015). Networked work and networked research: New forms of teamwork in the triple revolution. American Behavioral Scientist, 59(4), 443–456. doi: 10.1177/0002764214556811
   Web of Science ®Google Scholar
• van Duijn, M. A. J., van Busschbach, J. T., & Snijders, T. A. B. (1999). Multilevel analysis of personal networks as dependent variables. Social Networks, 21(2), 187–210. doi: 10.1016/S0378-8733(99)00009-X
   Web of Science ®Google Scholar
• Egghe, L. (2006). Theory and practise of the g-index. Scientometrics, 69 (1), 131–152. doi: 10.1007/s11192-006-0144-7
   Web of Science ®Google Scholar
• Erickson, B. H. (2004). The distribution of gendered social capital in Canada. In H. Flep & B. Volker (Eds.), Creation and returns of social capital: A new research program (pp. 27–50). New York: Routledge.
   Google Scholar
• Herring, C. (2009). Does diversity pay? Race, gender, and the business case for diversity. American Sociological Review, 74(2), 208–224. doi: 10.1177/000312240907400203
   Web of Science ®Google Scholar
• Hill, P. W., & Goldstein, H. (1998). Multilevel modeling of educational data with cross-classification and missing identification for units. Journal of Educational and Behavioral Statistics, 23(2), 117–128. doi: 10.3102/10769986023002117
   Web of Science ®Google Scholar
• Kerr, D. S., & Murthy, U. S. (2004). Divergent and convergent idea generation in teams: A comparison of computer-mediated and face-to-face communication. Group Decision and Negotiation, 13(4), 381–399. doi: 10.1023/B:GRUP.0000042960.38411.52
   Web of Science ®Google Scholar
• Krebs, V. (2007). Managing the 21st century organization. IHRIM Journal, 6(4), 2–8.
   Google Scholar
• Larson, A., & Starr, J. A. (1993). A network model of organizational formation. Entrepreneurship Theory and Practice, 18 (Winter), 5–15.
   Google Scholar
• Lazega, E., Jourda, M.-T., Mounier, L., & Stofer, R. (2008). Catching up with big fish in the big pond? Multi-level network analysis through linked design. Social Networks, 30(2), 159–176. doi: 10.1016/j.socnet.2008.02.001
   Web of Science ®Google Scholar
• Leckie, G. (2013). Multiple membership multilevel models. Bristol: Centre for Multilevel Modelling, University of Bristol.
   Google Scholar
• Lin, N., & Dumin, M. (1986). Access to occupations through social ties. Social Networks, 8(4), 365–385. doi: 10.1016/0378-8733(86)90003-1
   Web of Science ®Google Scholar
• Madden, M., & Jones, S. (2008). Networked workers. Washington, DC: Pew Internet & American Life Project.
   Google Scholar
• McPherson, M. J., Smith-Lovin, L., & Cook, J. M. (2001). Birds of a feather: Homophily in social networks. Annual Review of Sociology, 27, 415–444. doi: 10.1146/annurev.soc.27.1.415
   Web of Science ®Google Scholar
• de Miguel Luken, V., & Tranmer, M. (2010). Personal support networks of immigrants to Spain: A multilevel analysis. Social Networks, 32(4), 253–262. doi: 10.1016/j.socnet.2010.03.002
   Web of Science ®Google Scholar
• Mo, G. Y. (2015). How does diversity impact innovation in research network? A multilevel study of the GRAND NCE. Department of Sociology. University of Toronto.
   Google Scholar
• Mo, G. Y. (in press). Examining cross-disciplinary communication’s impact on multidisciplinary collaborations: Implications for innovations. Informaton, Communication & Society, 19(5). doi:10.1080/1369118X.2016.1139611
   Google Scholar
• Moore, G. (1990). Structural determinants of mens and womens personal networks. American Sociological Review, 55(5), 726–735. doi: 10.2307/2095868
   Web of Science ®Google Scholar
• O’Leary, M. B., Mortsen, M., & Woolley, A. W. (2011). Multiple team membership: A theoretical model of its effects on productivity and learning for individuals and teams. Academy of Management Review, 36(3), 461–478.
   Web of Science ®Google Scholar
• Olson, G. M., & Olson, J. S. (2000). Distance matters. Human Computer Interaction, 15(2), 139–178. doi: 10.1207/S15327051HCI1523_4
   Web of Science ®Google Scholar
• Olson, J. S., Hofer, E. C., Bos, N., Zimmerman, A., Olson, G. M., & Cooney, D. (2008). A theory of remote scientific collaboration (TORSC). In G. M. Olson, A. Zimmerman, & N. Bos (Eds.), Scientific collaboration on the internet (pp.73–98). Cambridge, MA: MIT Press.
   Google Scholar
• Pissarra, J., & Jesuino, J. C. (2005). Idea generation through computer – Mediated communication: The effects of anonymity. Journal of Managerial Psychology, 20(3/4), 275–291. doi: 10.1108/02683940510589055
   Google Scholar
• Rainie, L., & Wellman, B. (2012). Networked: The new social operating system. Cambridge, MA: MIT Press.
   Google Scholar
• Rasbash, J., & Browne, W. (2001). Modelling non-hierarchical structures. In A. H. Legland & H. Golstein (Eds.), Multilevel modeling of health statistics (pp. 93–105). Chicago, IL: Wiley.
   Google Scholar
• Reed, D. A., & Dongarra, J. (2015). Exascale computing and big data. Communications of the ACM, 58(7), 56–68. doi: 10.1145/2699414
   Web of Science ®Google Scholar
• Rosenfeld, M. J. (2015). Revisiting the data from the new family structure study: Taking family instability into account. Sociological Science, 2, 478–501. doi: 10.15195/v2.a23
   Google Scholar
• Shuffler, M. L., Jimenez-Rodriguez, M., & Kramer, W. S. (2015). The science of multiteam systems: A review and future research agenda. Small Group Research, 46(6), 659–699. doi: 10.1177/1046496415603455
   Web of Science ®Google Scholar
• Snijders, T. A. B., Spreen, M., & Zwaagstra, R. (1995). The use of multilevel modeling for analysing personal networks: Networks of cocaine users in an urban area. Jounal of Quantitative Anthropology, 5,85–105.
   Google Scholar
• Tranmer, M., Steel, D., & Browne, W. J. (2014). Multiple membership multiple classification models for social network and group dependences. Journal of the Royal Statistical Society (Series A) (Statistics in Society), 177(2), 439–455. doi: 10.1111/rssa.12021
   PubMed Web of Science ®Google Scholar
• Wang, P., Robins, G., Pattison, P., & Lazega, E. (2013). Exponential random graph models for multilevel networks. Social Networks, 35(1), 96–115. doi: 10.1016/j.socnet.2013.01.004
   Web of Science ®Google Scholar
• Wasserman, S., & Faust, K. (1994). Social Network Analysis: Methods and Applications, Cambridge, New York: Cambridge University Press.
   Google Scholar
• Weiss, M., & Hoegl, M. (2015). The history of teamwork’s societal diffusion: A multi-method review. Small Group Research, 46(6), 589–622. doi: 10.1177/1046496415602778
   Web of Science ®Google Scholar
• Wellman, B., & Frank, K. (2001). Network capital in a multi-level world: Getting support from personal communities. In N. Lin, K. Cook, & R. Burt (Eds.), Social capital: Theory and research (pp. 233–273). Chicago, IL: Aldine DeGruyter.
   Google Scholar