Abstract
Adoption of technologies has long been a key area of research in the information systems (IS) discipline, and researchers have thus been interested in the attributes, beliefs, intentions, and behaviors of individuals and organizations that can explain information technology (IT) adoption. The focal unit of adoption has mainly been individuals and organizations, however, research at the group or social network levels as well as the interorganizational level has recently gained increased interest from information systems (IS) researchers. This recent focus views the world as being the sum of all relations. Various social network theories exist that seek to emphasize different proficiencies of social networks and explain theoretical mechanisms for behavior in social networks. The core idea of these theories is that social networks are valuable, and the relations among actors affect the behavior of individuals, groups, organizations, industries, and societies. IS researchers have also found that social network theory can help explain technology adoption. Some researchers, in addition, acknowledge that most adoption situations involve phenomena occurring at multiple levels, yet most technology adoption research applies a single level of analysis. Multilevel research can address the levels of theory, measurement, and analysis required to fully examining research questions. This chapter, therefore, adapts the Coleman diagram into the Multilevel Framework of Technology Adoption in order to explain how social network theory, at the individual and social network levels, can help explain adoption of IT. As Coleman (1990) attempts to create a link between the micro- and macro-levels in a holistic manner, his approach is applicable in explaining IT adoption.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
This is referred to as the ontological discussion of structure and agency on human behavior (Giddens 1984).
- 2.
When the value of an IT to one user depends on how many other users there are, the IT is said to exhibit network externalities or network effects.
Abbreviations
- ICT:
-
Information and Communication Technology
- IOIS:
-
Inter-Organizational Information Systems
- IS:
-
Information Systems
- IT:
-
Information Technology
- TAM:
-
Technology Acceptance Model
- TPB:
-
Theory of Planned Behavior
- TRA:
-
Theory of Reasoned Action
- UTAUT:
-
Unified Theory of Acceptance and Use of Technology
- VoIP:
-
Voice over Internet Protocol
References
Abell, P. M., Felin, T., & Foss, N. J. (2008). Building microfoundations for the routines, capabilities and performance link. Managerial and Decision Economics, 29, 489–502.
Agarwal, R., & Prasad, J. (1999). Are individual differences germane to the acceptance of information technologies? Decision Sciences, 30(2), 361–391.
Ajzen, I. (1988). Attitudes, personality, and behaviour. Milton Keynes: Open University Press.
Ajzen, I., & Fishbein, M. (1973). Attitudinal and normative variables as predictors of specific behavior. Journal of Personality and Social Psychology, 27(1), 41–57.
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour. New Jersey: Prentice-Hall.
Ajzen, I., & Fishbein, M. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211.
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckman (Eds.), Springer series in social psychology (pp. 11–39). Berlin: Springer.
Aral, S., Muchnik, L., & Sundararajan, A. (2009). Distinguishing influence based contagion from homophily driven diffusion in dynamic networks. Proceedings of the National Academy of Sciences (PNAS), 106(51), 21544.
Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs: Prentice-Hall.
Barnes, J. A. (1954). Class and committees in a Norwegian island parish. Human Relations, 7, 39–58.
Bourdieu, P. L., & Wacquant, J. D. (1992). An invitation to reflexive sociology. Chicago, London: University of Chicago Press.
Brass, D. J. (1995). A social network perspective on human resources management. Research in Personnel and Human Resources Management, 13, 39–79.
Burkhardt, M. (1994). Social interaction effects following a technological change: A longitudinal investigation. Academy of Management Journal, 37(4), 869–898.
Burt, R. S. (1992). Structural holes – the social structure of competition. Cambridge: Harvard University Press.
Burt, R. S. (1999). The social capital of opinion leaders. Annals, 566, 37–54.
Burt, R. S., & Minor, M. J. (1983). Applied network analysis. Newbury Park: Sage.
Byrne, D. E. (1971). The attraction paradigm. New York: Academic Press.
Chiu, C.-M., Hsu, M.-H., & Wang, E. T. G. (2006). Understanding knowledge sharing in virtual communities: An integration of social capital and social cognitive theories. Decision Support Systems, 42, 1872–1888.
Choudrie, J., & Dwivedi, Y. K. (2005). Investigating the research approaches for examining technology adoption issues. Journal of Research Practice, 1(1), 1–12.
Christiaanse, E., & Rodon, J. (2005). A multilevel analysis of eHub adoption and consequences. Electronic Markets, 15(4), 355–364.
Coleman, J. S. (1988a). Social capital in the creation of human capital. The American Journal of Sociology, 94, 95–121.
Coleman, J. S. (1988b). The creation and destruction of social capital: Implications for the law. Notre Dame Journal of Law, Ethics, Public Policy, 3, 375–404.
Coleman, J. S. (1990). Foundations of social theory. Cambridge, MA: Belknap Press of Harvard University Press.
Coleman, J. S., Katz, E., & Menzel, H. (1966). Medical innovation: A diffusion study. New York: Bobbs-Merrill.
Compeau, D. R., Higgins, C. A., & Huff, S. (1999). Social cognitive theory and individual reactions to computing technology: A longitudinal study. Management Information Systems Quarterly, 23(2), 145–158.
Dansereau, F., Alutto, J., & Yammarino, F. (1984). Theory testing in organizational behavior: The varient approach. Englewood Cliffs, NJ: Prentice-Hall.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. Management Information Systems Quarterly, 13(3), 319–340.
Davis, F. D., Bagozzi, R. P., & Warshaw, R. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003.
Dickinger, A., Arami, M., & Meyer, D. (2008). The role of perceived enjoyment and social norm in the adoption of technology with network externalities. European Journal of Information Systems, 17, 4–11.
Dodds, P. S., Watts, D. J., & Sabel, C. F. (2003). Information exchange and robustness in organizational networks. Proceedings of the National Academy of Sciences, 100(21), 12516–12521.
Felin, T., & Foss, N. J. (2005). Strategic organization: A field in search of micro-foundations. Strategic Organization, 3, 441–455.
Firebaugh, G. (1979). Assessing group effects: A comparison of two methods. Sociological Methods & Research, 7, 384–395.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
Ford, D. (1980). The development of buyer–seller relationships in industrial markets. European Journal of Marketing, 14(5/6), 339–354.
Ford, D., Håkansson, H., & Johanson, J. (1986). How do companies interact? Industrial Marketing and Purchasing, 1(2), 26–41.
Foss, N. (2007). The emerging knowledge governance approach: Challenges and characteristics. Organization, 14(29), 29–52.
Foucault, M. (1970). The order of things. New York: Pantheon.
Foucault, M. (1972). Archaeology of knowledge. New York: Pantheon.
Frambach, R. T., & Schillewaert, N. (2002). Organizational innovation adoption: A multi-level framework of determinants and opportunities for future research. Journal of Business Research, 55, 163–176.
Friedkin, N. (1980). A test of structural features of Granovetter’s strength of weak ties. Social Networks, 2, 411–422.
Fulk, J. (1993). Social construction of communication technology. Academy of Management Journal, 36(5), 921–950.
Fulk, J., Schmitz, J., & Steinfield, C. W. (1990). A social influence model of technology use. In J. Fulk & C. W. Steinfield (Eds.), Organizations and communication technology (pp. 117–140). Newbury Park, CA: Sage Publications.
Gefen, D., Karahanna, E., & Straub, D. (2003). Trust and TAM in online shopping: An integrated model. Management Information Systems Quarterly, 27(1), 51–90.
Giddens, A. (1984). The constitution of society. Cambridge: Polity Press.
Gopalakrishnan, S., Wischnevsky, J. D., & Damanpour, F. (2003). A multilevel analysis of factors influencing the adoption of internet banking. IEEE Transactions on Engineering Management, 50(4), 413–426.
Granovetter, M. (1973). The strength of weak ties. The American Journal of Sociology, 78(6), 1360–1381.
Granovetter, M. (1978). Threshold models of collective behavior. The American Journal of Sociology, 83(6), 1420–1443.
Granovetter, M. S. (1983). The strength of weak ties – A network theory revisited. Sociological Theory, 1, 201–233.
Gregor, S., & Johnston, R. (2000). Developing an understanding of interorganizational systems: Arguments for multi-level analysis and structuration theory (pp. 575–582). Vienna: Elsevier.
Gu, B., Konana, P., & Chen, M. (2008). Melting-pot or homophily? – An empirical investigation of user interactions in virtual investment-related communities. McCombs research paper series no. IROM-05-08. http://ssrn.com/abstract=1259224. Accessed 12 June 2010.
Hitt, M. A., Beamish, P. W., Jackson, S. E., & Mathieu, J. E. (2007). Building theoretical and empirical bridges across levels: Multilevel research in management. Academy of Management Review, 50(6), 1385–1399.
Hsu, H. L., & Lin, J. C. C. (2008). Acceptance of blog usage: The roles of technology acceptance, social influence and knowledge sharing motivation. Information & Management, 45, 65–74.
Jasperson, J., Sambamurthy, V., & Zmud, R. (1999). Social influence and individual IT use: Unraveling the pathways of appropriation moves. In P. De & J. I. DeGross (Eds.), Proceedings of the 20th international conference on information systems (pp. 113–118). NC: ACM Press.
Jung, D. I., & Sosik, J. J. (2003). Group potency and collective efficacy: Examining their predictive validity, level of analysis, and effect of performance feedback on future group performance. Group and Organization Management, 28(3), 366–391.
Katz, E., & Levine, M. L. (1963). Traditions of research on the diffusions of innovations. American Sociological Review, 28, 237–253.
Klein, K. J., Dansereau, F., & Hall, R. J. (1994). Levels issues in theory development, data collection, and analysis. Academy of Management Review, 19, 195–229.
Klein, K. J., & Kozlowski, S. W. J. (2000). From micro to Meso: Critical steps in conceptualizing and conducting multilevel research. Organizational Research Methods, 3, 211–236.
Klein, K., Tosi, H., & Canella, A. A. (1999). Multilevel theory building: Benefits, barriers, and new developments. Academy of Management Review, 24(2), 243–248.
Krackhardt, D. (1987). Cognitive social structures. Social Networks, 9, 109–134.
Krackhardt, D. (1990). Assessing the political landscape: Culture, cognition and power in organizations. Administrative Science Quarterly, 35, 342–369.
Lapointe, L., & Rivard, S. (2005). A multilevel model of resistance to information technology implementation. Management Information Systems Quarterly, 29(3), 461–492.
Lazarsfeld, P. F., Menzel, H., et al. (1961). On the relation between individual and collective properties. In Complex organizations: A sociological reader. New York: Holt, Rhinehart and Winston.
Lazarsfeld, P. F., Merton, R. K., et al. (1964). Friendship as social process: A substantive and methodological analysis. In M. Berger (Ed.), Freedom and control in modern society. New York: Octagon.
Levin, D., Cross, R., & Abrams, L. C. (2004). The strength of weak ties you can trust: The mediating role of trust in effective knowledge transfer. Management Science, 50, 1477–1490.
Liebowitz, S. J., & Margolis, S. E. (1995). Path dependence,lock-in, and history. Journal of Law, Economics, and Organization, 11(1), 205–226.
Lu, J., Yao, J. E., & Chun-Sheng, Y. (2005). Personal innovativeness, social influences and adoption of wireless internet services via mobile technology. The Journal of Strategic Information Systems, 14, 245–268.
Lyytinen, K., & Damsgaard, J. (2001). What’s wrong with diffusion of innovations theory?. In Proceedings of the IFIP TC8//WG 8.6. Fourth working conference on diffusing software product and process innovations (pp. 173–190), Banff, Canada.
Lyytinen, K., & Damsgaard, J. (2010). Configuration analysis of inter-organizational information systems adoption. In Proceedings of the first scandinavian conference on information systems, SCIS 2010, (pp. 127–138), Rebild, Denmark.
Mahler, A., & Rogers, E. M. (1999). The diffusion of interactive communication innovations and the critical mass – The adoption of telecommunications services by German Banks. Telecommunications Policy, 23, 719–740.
Markus, M. L. (1987). Toward a ‘critical mass’ theory of interactive medua: universal access, interdependence, and diffusion. Communications Research, 14(5), 491–511.
Meyer, A. D., & Goes, J. B. (1988). Organizational assimilation of innovations: A multilevel contextual analysis. Academy of Management Journal, 31(4), 897–923.
Monge, P. R., & Contractor, N. (1988). Communication networks: Measurement techniques. In C. H. Tardy (Ed.), A handbook for the study of organizational communication (pp. 440–502). Thousand Oaks, CA: Sage.
Monge, P. R., & Contractor, N. (2003). Theories of communication networks. New York: Oxford University Press.
Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192–222.
Nahapiet, J., & Ghoshal, S. (1998). Social capital, intellectual capital, and the organizational advantage. Academy of Management Review, 23(2), 242–266.
Oh, H., Labianca, G., & Chung, M. (2006). A multilevel model of group social capital. Academy of Management Review, 31(3), 569–582.
Onnela, J.-P., Saramäki, J., Hyvönen, J., Szabó, G., Lazer, D., Kaski, K., Kertész, K., & Barabási, A. L. (2007). Structure and tie strengths in mobile communication networks. Proceedings of the National Academy of Sciences of the United States of America, 104, 7332–7336.
Ostroff, C. (1993). Comparing correlations based on individual level and aggregate data. The Journal of Applied Psychology, 78, 569–582.
Poole, M. S., & DeSanctis, G. (1990). Understanding the use of group decision support systems: The theory of adaptive structuration. In J. Fulk & C. Steinfeld (Eds.), Organzations and communications technology (pp. 173–191). Newbury Park, CA: Sage.
Porter, L. W. (1996). Forty years of organization studies: Reflections from a micro perspective. Administrative Science Quarterly, 41, 262–269.
Putnam, R. (1993). Making democracy work: Civic traditions in modern Italy. Princeton, NJ: Princeton University Press.
Putnam, R. (1995). Bowling alone: America’s declining social capital. Journal of Democracy, 6, 65–78.
Putnam, L. L., & Fairhurst, G. T. (2001). Discourse analysis in organizations: Issues and concerns. In F. M. Jablin & L. L. Putnam (Eds.), The new handbook of organizational communication: Advances in theory, research, and methods (pp. 78–136). Thousand Oaks, CA: Sage.
Rashotte, L. (2007). Social influence. In A. S. R. Manstead, M. Hewstone, & M. A. Malden (Eds.), The blackwell encyclopedia of social psychology (pp. 1–3). Cambridge: Blackwell Publishing.
Rice, R. E., Grant, A. E., Schmitz, J., & Torobin, J. (1990). Individual and network influences on the adoption and perceived outcomes of electronic messaging. Social Networks, 12(1), 27–53.
Rogers, E. (2003). Diffusion of innovations. New York: The Free Press.
Rousseau, D. M., & House, R. J. (1994). Meso-organizational behavior: Avoiding three fundamental biases. Journal of Organizational Behavior, 1(1), 13–30.
Sarker, S. (2006). Examining the “level of analysis” issue in understanding technology adoption by groups – Social, behavioral, and organizational aspects of information systems. In Proceedings of the 27th international conference on information systems: Milwaukee.
Schachter, S. (1959). The psychology of affiliation. Stanford, CA: Stanford University Press.
Scheepers, J., de Jong, A., Wetzels, M., & de Ruyter, K. (2008). Psychological safety and social support in groupware adoption: A multi-level assessment in education. Computers & Education, 51, 757–775.
Scott, J. (1988). Social network analysis. Newbury Park, CA: Sage.
Scott, J. (2000). Social network analysis: A handbook. London: Sage Publications.
Shapiro, C., & Varian, H. R. (1999). Information rules: A strategic guide to the network economy. Boston, MA: Harvard Business School Press.
Shumaker, S., & Brownell, A. (1984). Toward a theory of social support: Closing conceptual gaps. Journal of Social Issues, 40(4), 11–36.
Tajfel, H. (1974). Social identity and intergroup behaviour. Social Science Information, 13, 65–93.
Teo, H. H., Wei, K. K., & Benbasat, I. (2003). Predicting intention to adopt inter-organizational linkages: An institutional perspective. Management Information Systems Quarterly, 27(1), 19–49.
Thompson, M. (2002). ICT, power, and developmental discourse: A critical analysis. In E. H. Wynn, E. A. Whitley, M. D. Myers, & J. I. DeGross (Eds.), Proceedings of the IFIP TC8/WG8.2 working conference on global and organizational discourse about information technology (pp. 347–373). Boston: Kluwer Academic Publishers.
Tscherning, H., & Mathiassen, L. (2010). Early adoption of mobile devices: A social network perspective. Journal of Information Technology Theory and Application, 11(1), 23–42.
Valente, T. W. (1996). Social network thresholds in the diffusion of innovations. Social Networks, 18(1), 69–89.
van den Bulte, C., & Lilien, G. (2001). Medical innovation revisited: Social contagion versus marketing effort. The American Journal of Sociology, 106(5), 1409–1435.
van Dijk, J. A. (2005). Outline of a multilevel approach of the network society. In Annual meeting of the international communication association, May 26–30, 2005, New York.
van Dolen, W. M., & de Ruyter, K. (2002). Moderated group chat: An empirical assessment of a new e-service encounter. International Journal of Service Industry Management, 13(5), 496–511.
Venkatesh, V., & Morris, M. G. (2000). Why don’t men ever stop to ask for directions? gender, social influence, and their role in technology acceptance and usage behavior. Management Information Systems Quarterly, 24(1), 115–139.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. Management Information Systems Quarterly, 27(3), 425–479.
Vigden, R., Madsen, S., & Kautz, K. (2004). Mapping the information systems development process. In Proceedings of IFIP WG8.6 working conference on IT innovation, IFIP. Dublin, Ireland.
Wasko, M. M., & Faraj, S. (2005). Why should I share? Examining social capital and knowledge contribution in electronic networks of practice. Management Information Systems Quarterly, 29(1), 35–57.
Wasserman, S., & Faust, K. (1995). Social network analysis – Methods and applications. New York: Cambridge University Press.
Weber, M. (1904). Die protestantische ethik und der ‘geist’ des kapitalismus. Tübingen: Mohr.
Wellman, B. (1999). Networks in the global village: Life in contemporary communities. Boulder, CO: Westview Press.
Wellman, B. (2001). Computer networks as social networks. Science, 293(14), 2031–2034.
Wilson, M. (2003). Understanding the international ICT and development discourse: Assumptions and implications. The South African Journal of Information and Communication, (3). http://link.wits.ac.za/journal/j0301-merridy-fin.pdf. Accessed 2 Sept 2010.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Tscherning, H. (2012). A Multilevel Social Network Perspective on IT Adoption. In: Dwivedi, Y., Wade, M., Schneberger, S. (eds) Information Systems Theory. Integrated Series in Information Systems, vol 28. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-6108-2_20
Download citation
DOI: https://doi.org/10.1007/978-1-4419-6108-2_20
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-6107-5
Online ISBN: 978-1-4419-6108-2
eBook Packages: Business and EconomicsBusiness and Management (R0)