Skip to main content
Log in

Social Networking and Individual Perceptions: Examining Predictors of Participation

  • Published:
Public Organization Review Aims and scope Submit manuscript

Abstract

Social networking is a process and practice that draws people and organizations together in an electronic medium. This article explores social interaction-based theories to suggest a social networking participation model that may help organizations understand acceptance or rejection of participation. Responses from 191 public administrators were analyzed using structural equation modeling (SEM), focusing on relationships between participation and five constructs: perceived usefulness, perceived ease of use, perceived improvement potential (PIP), intra-organizational trust, and type of use. The study found favorable model fit statistics that support positive correlations between the latent variables examined and participation in social networking activities. The results demonstrate the potential of the survey instrument to serve as an adoption and participation model to predict and promote social networking activities as they relate to perceived performance improvement.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Akdere, M., & Roberts, P. B. (2008). Economics of social capital: implications for organizational performance. Advances in Developing Human Resources, 10(6), 802.

    Article  Google Scholar 

  • Alkadry, M. G. (2000). If citizens talk back, do administrators listen? A structural equation model of administrative responsiveness to citizens. Unpublished Ph.D., Florida Atlantic University, United States—Florida.

  • Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: a review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423.

    Article  Google Scholar 

  • Anderson, S. E., & Harris, J. B. (1997). Factors associated with amount of Use and benefits obtained by users of a statewide educational telecomputing network. Educational Technology Research and Development, 45(1), 19–50.

    Article  Google Scholar 

  • Bachmann, R., Knights, D., Sydow, J. (2001). Special Issue: Trust and control in organizational relations. Organization Studies, 22(2).

  • Bandura, A. (1989). Human agency in social cognitive theory. American Psychologist, 44(9), 1175–1184.

    Article  Google Scholar 

  • Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99.

    Article  Google Scholar 

  • Bearman, T. C., Guynup, P., & Milevski, S. N. (1985). Information and productivity. Journal of the American Society for Information Science (pre-1986), 36(6), 369.

    Article  Google Scholar 

  • Boyd, D. M., & Ellison, N. B. (2008). Social network sites: definition, history, and scholarship. Journal of Computer-Mediated Communication, 13(1), 210–230.

    Article  Google Scholar 

  • Brandyberry, A. A., Li, X., Lin, L. (2010). Determinants of Perceived Usefulness and Perceived Ease of Use in Individual Adoption of Social Network Sites. Paper presented at the AMCIS 2010 Proceedings, Paper 544.

  • Brown, M. A., Sr. (2011). Social networking and individual performance: Examining predictors of participation. Unpublished Dissertation, Old Dominion University, Norfolk.

  • Cerulo, K. A. (1990). To Err is social: network prominence and its effects on self-estimation. Sociological Forum, 5(4), 619–634.

    Article  Google Scholar 

  • Chowdhury, S. (2005). The role of affect- and cognition-based trust in complex knowledge sharing. Journal of Managerial Issues, 17(3), 310–326.

    Google Scholar 

  • Chung, K. S. K., Hossain, L., Davis, J. (2007). Individual performance in knowledge intensive work through social networks. Paper presented at the Proceedings of the 2007 ACM SIGMIS CPR conference on Computer personnel research: The global information technology workforce, St. Louis, Missouri, USA.

  • Davis, F. D. (1989). Perceived usefulness, perceived ease of Use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.

    Article  Google Scholar 

  • Davis, T. R. V., & Luthans, F. (1980). A social learning approach to organizational behavior. The Academy of Management Review, 5(2), 281–290.

    Google Scholar 

  • Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of Two. Management Science, 35(8), 982.

    Article  Google Scholar 

  • Dedrick, J., Gurbaxani, V., & Kraemer, K. L. (2003). Information technology and economic performance: a critical review of the empirical evidence. ACM Computing Surveys, 35(1), 1–28.

    Article  Google Scholar 

  • Eastin, M. S., & LaRose, R. (2000). Internet self-efficacy and the psychology of the digital divide. Journal of Computer-Mediated Communication, 6(1), np.

  • Erickson, C. L., & Jacoby, S. M. (2003). The effects of employer networks on workplace innovation and training. Industrial & Labor Relations Review, 56(2), 203.

    Article  Google Scholar 

  • Fabrigar, L. R., Porter, R. D., & Norris, M. E. (2010). Some things you should know about structural equation modeling but never thought to ask. Journal of Consumer Psychology, 20(2), 221–225.

    Article  Google Scholar 

  • Fowler, S. W., Lawrence, T. B., & Morse, E. A. (2004). Virtually embedded ties. Journal of Management, 30(5), 647–666.

    Google Scholar 

  • Gambetta, D. (1988). Trust: making and breaking cooperative relations. New York: B. Blackwell.

    Google Scholar 

  • Goldsmith, S., & Eggers, W. D. (2004). Governing by network: the new shape of the public sector. Washington, D.C.: Brookings Institution Press.

    Google Scholar 

  • Grey, C., & Garsten, C. (2001). Trust, control and post-bureaucracy. Organization Studies, 22(2), 229–250.

    Article  Google Scholar 

  • Hatala, J.-P., & Fleming, P. R. (2007). Making transfer climate visible: utilizing social network analysis to facilitate the transfer of training. Human Resource Development Review, 6(1), 33.

    Article  Google Scholar 

  • Hendrix, W. H. (1984). Development of a contingency model organizational assessment survey for management consultants. The Journal of Experimental Education, 52(2), 95–105.

    Google Scholar 

  • Hertel, G., Konradt, U., & Orlikowski, B. (2004). Managing distance by interdependence: goal setting, task interdependence, and team-based rewards in virtual teams. European Journal of Work & Organizational Psychology, 13(1), 1–28.

    Article  Google Scholar 

  • Hosmer, L. T. (1995). Trust—the connecting link between organizational theory and philosophical ethics. Academy of Management Review, 20(2), 379–403.

    Google Scholar 

  • Hu, L.-T., & Bentler, P. M. (1995). In R. H. Hoyle (Ed.), Structural equation modeling: Concepts, issues, and applications. Thousand Oaks: Sage Publications.

    Google Scholar 

  • Hu, L.-T., Bentler, P. M., & Kano, Y. (1992). Can test statistics in covariance structure analysis be trusted? Psychological Bulletin, 112(2), 351–362.

    Article  Google Scholar 

  • Igbaria, M., & Tan, M. (1997). The consequences of information technology acceptance on subsequent individual performance. Information Management, 32(3), 113–121.

    Article  Google Scholar 

  • Ivancevich, J. M., Konopaske, R., & Matteson, M. T. (2008). Organizational behavior and management (8th ed.). New York: McGraw-Hill/Irwin.

    Google Scholar 

  • Konradt, U., Hertel, G., & Schmook, R. (2003). Quality of management by objectives, task-related stressors, and non-task-related stressors as predictors of stress and job satisfaction among teleworkers. European Journal of Work & Organizational Psychology, 12(1), 61.

    Article  Google Scholar 

  • Kramer, R. M. (1996). Trust in organizations: Frontiers of theory and research. Thousand Oaks: Sage Publications.

    Google Scholar 

  • Kwon, O., & Wen, Y. (2010). An empirical study of the factors affecting social network service use. Computers in Human Behavior, 26(2), 254–263.

    Article  Google Scholar 

  • Lambright, K. T., Mischen, P. A., & Laramee, C. B. (2010). Building trust in public and nonprofit networks: personal, dyadic, and third-party influences. The American Review of Public Administration, 40(1), 64–82.

    Article  Google Scholar 

  • Lane, C., & Bachmann, R. (1998). Trust within and between organizations: Conceptual issues and empirical applications. New York: Oxford University Press.

    Google Scholar 

  • Leaman, A., & Bordass, W. (2000). Productivity in buildings: The killer variables. In D. Clements-Croome (Ed.), Creating the productive workplace. London: E & FN Spon.

    Google Scholar 

  • Li, F., & Betts, S.C. (2003). Between Expectation and Behavioral Intent: A Model of Trust. Allied Academies International Conference. Academy of Organizational Culture, Communications and Conflict. Proceedings, 8(1), 33.

  • Luhmann, N. (1979). Trust and power: Two works. Chichester: Wiley.

    Google Scholar 

  • Marsh, W. (1990). Meeting the challenge of change. Australian Accountant, 60(1), 34.

    Google Scholar 

  • Masrom, M. (2007, 21–24 May 2007). Technology Acceptance Model and E-learning. Paper presented at the 12th International Conference on Education, Sultan Hassanal Bolkiah Institute of Education, Universiti Brunei Darussalam, Universiti Teknologi Malaysia City Campus.

  • Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of organizational trust. The Academy of Management Review, 20(3), 709–734.

    Google Scholar 

  • Mazman, S. G., & Usluel, Y. K. (2009). The usage of social networks in educational context. World Academy of Science, Engineering and Technology, 49, 404–408.

    Google Scholar 

  • McAllister, D. J. (1995). Affect-based and cognition-based trust as foundations for interpersonal cooperation in organizations. Academy of Management Journal, 38(1), 24–59.

    Article  Google Scholar 

  • McEvily, B., Perrone, V., & Zaheer, A. (2003). Introduction to the special issue on trust in an organizational context. Organization Science, 14(1), 1.

    Article  Google Scholar 

  • Nakata, C., Zhu, Z. J., & Kraimer, M. L. (2008). The complex contribution of information technology capability to business performance. Journal of Managerial Issues, 20(4), 485.

    Google Scholar 

  • Newell, S., & Swan, J. (2000). Trust and inter-organizational networking. Human Relations, 53(10), 1287–1328.

    Google Scholar 

  • Nyhan, R. C. (2000). Changing the paradigm: trust and its role in public sector organizations. The American Review of Public Administration, 30(1), 87–109.

    Article  Google Scholar 

  • Otis, B. (2007). Factors in Social Computing Related to Worker Productivity. Unpublished Capstone Report, University of Oregon, Portland.

  • Pallis, G., Zeinalipour-Yazti, D., & Dikaiakos, M. D. (2011). Online social networks: Status and trends. In New Directions in Web Data Management 1 (Vol. 331, pp. 213–234). Tiergartenstrasse 17, Heidelberg: Springer Verlag.

    Chapter  Google Scholar 

  • Passy, F., & Giugni, M. (2001). Social networks and individual perceptions: explaining differential participation in social movements. Sociological Forum, 16(1), 123–153.

    Article  Google Scholar 

  • Perry, R. (2006). Diffusion theories. In E. F. Borgatta & R. J. V. Montgomery (Eds.), Encyclopedia of Sociology (2 ed, Vol. 1, pp. 674–681). New York: Macmillan Reference USA, 2001.

  • 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.

    Google Scholar 

  • Rodgers, R., & Hunter, J. E. (1991). Impact of management by objectives on organizational productivity. Journal of Applied Psychology, 76(2), 322–336.

    Article  Google Scholar 

  • Rousseau, D. M., Sitkin, S. B., Burt, R. S., & Camerer, C. (1998). Not so different after all: a cross-discipline view of trust. Academy of management. The Academy of Management Review, 23(3), 393.

    Article  Google Scholar 

  • Segrest, S. L., Domke-Damonte, D. J., Miles, A. K., & Anthony, W. P. (1998). Following the crowd: social influence and technology usage. Journal of Organizational Change Management, 11(5), 425.

    Article  Google Scholar 

  • Shetzer, L. (1993). A social information processing model of employee participation. Organization Science, 4(2), 252.

    Article  Google Scholar 

  • Shin, D.-H. (2010). The effects of trust, security and privacy in social networking: a security-based approach to understand the pattern of adoption. Interacting with Computers, 22(5), 428–438.

    Article  Google Scholar 

  • Steinfield, C., DiMicco, J. M., Ellison, N. B., Lampe, C. (2009). Bowling online: social networking and social capital within the organization. Paper presented at the Proceedings of the Fourth International Conference on Communities and Technologies, University Park, PA.

  • van de Bunt, G. G., Wittek, R. P. M., & de Klepper, M. C. (2005). The evolution of intra-organizational trust networks: the case of a German paper factory: an empirical test of six trust mechanisms. International Sociology, 20(3), 339–369.

    Article  Google Scholar 

  • Vandermerwe, S. (1987). Diffusing New ideas in-house. The Journal of Product Innovation Management, 4(4), 256.

    Article  Google Scholar 

  • Venkatesh, V. (2000). Determinants of perceived ease of use: integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342.

    Article  Google Scholar 

  • Warshaw, P. R., & Davis, F. D. (1985). Disentangling behavioral intention and behavioral expectation. Journal of Experimental Social Psychology, 21(3), 213–228.

    Article  Google Scholar 

  • Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Wasserman, S., Faust, K., & Scott, J. (1996). Social network analysis: methods and applications. The British Journal of Sociology, 47(2), 374.

    Article  Google Scholar 

  • Zack, M. H., & McKenney, J. L. (1995). Social context and interaction in ongoing computer-supported management groups. Organization Science, 6(4), 394.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Michael A. Brown Sr..

Rights and permissions

Reprints and permissions

About this article

Cite this article

Brown, M.A., Alkadry, M.G. & Resnick-Luetke, S. Social Networking and Individual Perceptions: Examining Predictors of Participation. Public Organiz Rev 14, 285–304 (2014). https://doi.org/10.1007/s11115-013-0218-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11115-013-0218-y

Keywords

Navigation