The readings listed here are intended as starting points for learning about particular theories developed in fields/disciplines other than information and library science; they are not intended to be a complete list of the relevant literature. The list of theories included is similarly suggestive, rather than comprehensive.

Social cognitive theory (Bandura)

• Bandura, A. (1977). Social Learning Theory. Englewood Cliffs, NJ: Prentice-Hall. [Undergraduate Library - LB1084 .B357 1976]
• Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191-215.
• Bandura, A. (1986). Social Foundations of Thought and Action: A Social Cognitive Theory. Englewood Cliffs, NJ: Prentice-Hall. [Davis Library - HM251 .B433 1986]
• Gist, M.E., & Mitchell, T.R. (1992). Self-efficacy: A theoretical analysis of its determinants and malleability. Academy of Management Review, 17(2), 183-211.
• Compeau, D.R., & Higgins, C.A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211.
• Bandura, A. (1997). Self-Efficacy: The Exercise of Control. New York: W.H. Freeman. [Davis Library - BF637.S38 B36 1997]
• Marakas, G.M., Yi, M.Y., & Johnson, R.D. (1998). The multilevel and multifaceted character of computer self-efficacy: Toward clarification of the construct and an integrative framework for research. Information Systems Research, 9(2), 126-163.
• Compeau, D., Higgins, C.A., & Huff, S. (1999). Social cognitive theory and individual reactions to computing technology: A longitudinal study. MIS Quarterly, 23(2), 145-158.
• Ren, W.-H. (2000). Library instruction and college student self-efficacy in electronic information searching. Journal of Academic Librarianship, 26(5), 323-328.
• Debowski, S., Wood, R.E., & Bandura, A. (2001). Impact of guided exploration and enactive exploration on self-regulatory mechanisms and information acquisition through electronic search. Journal of Applied Psychology, 86(6), 1129-1141.
• Miwa, M. (2005). Bandura's social cognition. In Fisher, K.E., Erdelez, S., & McKechnie, L. (E.F.) (eds.), Theories of Information Behavior. Medford, NJ: Information Today, for ASIST, 54-57. [SILS Library - ZA3075 .T465 2005]

Sensemaking (Weick)

• Bantz, C.R., & Smith, D.H. (1977). A critique and experimental test of Weick's model of organizing. Communication Monographs, 44(3):171-184.
• Weick, K. (1995). Sensemaking in Organizations. Sage, Thousand Oaks.
• MacIntosh-Murray, A. (2005). Organizational sense making and information use. In Theories of Information Behavior. Information Today, Inc., 265-269.
• Maitlis, S. (2005). The social processes of organizational sensemaking. Academy of Management Journal, 48(1):21-49.
• Weick, K.E., Sutcliffe, K.M., & Obstfeld, D. (2005). Organizing and the process of sensemaking. Organization Science, 16(4), 409-421.

Theory of Reasoned Action (TRA); Technology Acceptance Model (TAM)

• Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley. [Davis Library - BF323.C5 F48]
• Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. Kuhl, J., & Beckmann, J. (eds.), Action Control: From Cognition to Behavior. Berlin: Springer-Verlag, 11-39. [Davis Library - BF611 .A27 1985]
• Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
• Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179-211.
• Venkatesh, V., & Davis, F.D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451-481.
• Venkatesh, V., & Davis, F.D. (2000). A theoretical extension of the Technology Acceptance Model: Four longitudinal field studies. Management Science, 46(2), 186-204.
• Moon, J.W., & Kim, Y.J. (2001). Extending the TAM for a World Wide Web context. Information & Management, 38(4), 217-230.
• Venkatesh, V., Morris, M.G., Davis, G.B., &Davis, F.D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
• DeLone, W.H., & McLean, E.R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9-30.
• Lee, Y., Kozar, K.A., & Larsen, K.R.T. (2003). The technology acceptance model: past, present, and future. Communications of the AIS, 12(50), 752-780.
• Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the Technology Acceptance Model. Information & Management, 40(3), 191-204.
• King, W.R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information & Management, 43(6), 740-755.
• Chan, H.C., & Teo, H.-H. (2007). Evaluating the boundary conditions of the technology acceptance model: An exploratory investigation. ACM Transactions on Computer-Human Interaction, 14(2), Article 9.
• Mathieson, K. (1991). Predicting user intentions: Comparing the Technology Acceptance Model with the Theory of Planned Behavior. Information Systems Research, 2(3), 173-191.

Diffusion theory (Rogers)

• Rogers, E.M. (1962). Diffusion of Innovations. New York: Free Press. [Davis Library -HM101 .R57]
• Downs, G.W., Jr., & Mohr, L.B. (1976). Conceptual issues in the study of innovation. Administrative Science Quarterly, 21, 700-714.
• Lucas, H.C., &Sutton, J.A. (1977). The stage hypothesis s-curve: Some contradictory evidence. Communications of the ACM, 20(4), 254-259.
• Rice, R.E., & Rogers, E.M. (1980). Reinvention in the innovation process. Knowledge: Creation, Diffusion, Utilization, 1(4), 499-514.
• Damanpour, F., & Childers, T. (1985). The adoption of innovations in public libraries. Library & Information Science Research, 7, 231-246.
• Chatman, E.A. (1986). Diffusion theory: A review and test of a conceptual model in information diffusion. Journal of the American Society for Information Science, 37(6), 377-386.
• Eveland, J.D. (1986). Diffusion, technology transfer, and implementation: Thinking and talking about change. Knowledge: Creation, Diffusion, Utilization, 8(2), 303-322.
• Marshall, J.G. (1990). Diffusion of innovation theory and end-user searching. Library and Information Science Research, 12(1), 55-69.
• Cooper, R.B., & Zmud, R.W. (1990). Information technology implementation research: A technological diffusion approach. Management Science, 36(2), 123-139.
• 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.
• Damanpour, F. (1991). Organizational innovation: A metaanalysis of effects of determinants and moderators. Academy of Managemet Journal, 34(3), 555-590.
• Zmud, R.W., & Apple, L.E. (1992). Measuring technology incorporation/infusion. Journal of Product Innovation and Management, 9, 148-155.
• Taylor, S., & Todd, P.A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176.
• Rogers, E.M. (2003). Diffusion of Innovations. 5th ed. New York: Free Press. [Davis Library - HM621 .R57 2003]
• Venkatesh, V., Morris, M.G., Davis, G.B., & Davis, F.D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
• Lajoie-Paquette, D. (2005). Diffusion theory. In Fisher, K.E., Erdelez, S., & McKechnie, L. (E.F.) (eds.), Theories of Information Behavior. Medford, NJ: Information Today, for ASIST, 118-122. [SILS Library - ZA3075 .T465 2005]
• Jeyaraj, A., Rottman, J.W., & Lacity, M.C. (2006). A review of the predictors, linkages, and biases in IT innovation adoption research. Journal of Information Technology, 21(1), 1-23.

Social network theory

• Mitchell, J.C. (1969). The concept and use of social networks. In Social Networks in Urban Situations: Analyses of Personal Relationships in Central African Towns. Manchester University Press, for the Institute for African Studies, University of Zambia, 1-50. [Davis Library - HN800 .Z32 S6]
• Granovetter, Mark S. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360-1380.
• Pool, I.D., & Kochen, M. (1978). Contacts and influence. Social Networks, 1(1), 5-51.
• Burt, R.S. (1980). Models of network structure. Annual Review of Sociology, 6, 79-141. [Available via UNC libraries/JSTOR]
• Monge, P. (1987). The network level of analysis. In Berger, C.R., & Chaffee, S.H. (eds.), Handbook of Communication Science. Newbury Park, CA: Sage, 239-270. [Davis Library - P90 .H294 1987]
• Marsden, P.V. (1990). Network data and measurement. Annual Review of Sociology, 16, 435-463.
• Haythornthwaite, C. (1996). Social network analysis: An approach and technique for the study of information exchange. Library & Information Science Research, 18(4), 323-342. [UNC libraries]
• Hansen, M.T. (2002). Knowledge networks: Explaining effective knowledge sharing in multiunit companies. Organization Science, 13(3), 232-248.
• Dixon, C.M. (2005). Strength of weak ties. In Fisher, K.E., Erdelez, S., & McKechnie, L. (E.F.) (eds.), Theories of Information Behavior. Medford, NJ: Information Today, for ASIST, 344-348. [SILS Library - ZA3075 .T465 2005]
• Morris, S.A., & Goldstein, M.L. (2007). Manifestation of research teams in journal literature: A growth model of papers, coauthorship, weak ties, authors, collaboration, and Lotka's law. Journal of the American Society for Information Science & Technology, 58(12), 1764-1782.
• Morris, S.A., & Van der Veer Martens, B. (2008). Mapping research specialties. Annual Review of Information Science & Technology, 42, 213-295.
• Oh, J.-S. (2010). Network analysis of shared interests represented by social bookmarking behaviors. Ph.D. dissertation, University of North Carolina at Chapel Hill. [UNC libraries]

Structuration theory (Giddens)

• Orlikowski, W.J., & Robey, D. (1991). Information technology and the structuring of organizations. Information Systems Research, 2(2), 143-169. [UNC libraries]
• Jones, M.R., & Karsten, H. (2008). Giddens's structuration theory and information systems research. MIS Quarterly, 32(1), 127-157. [UNC libraries]
• Rosenbaum, H. (1997). Notes on a structurational view of digital information in organizations. ASIS '97: Proceedings of the 60th ASIS Annual Meeting, 34, 328-334. [UNC libraries]
• Rosenbaum, H. (1993). Information use environments and structuration: Towards an integration of Taylor and Giddens. ASIS '93: Proceedings of the 56th ASIS Annual Meeting, 235-245. [UNC libraries]

Transtheoretical model of behavior change

• Petty, R.E., & Wegener, D.T. (1999). The elaboration likelihood model: Current status and controversies. In Chaiken, Shelly; Trope, Yaacov (eds.), Dual-Process Theories in Social Psychology. New York Guilford Press, 41-72. [Davis Library - HM291 .D76 1999, with viewing on Google Books]
• Wathen, C.N., & Harris, R.M. (2005). Transtheoretical model of the health behavior change. In Fisher, K.E., Erdelez, S., & McKechnie, L. (E.F.) (eds.), Theories of Information Behavior. Medford, NJ: Information Today, for ASIST, 363-367. [SILS Library - ZA3075 .T465 2005]

Reader response theory

• Ross, C.S. (2005). Reader response theory. In Fisher, K.E., Erdelez, S., & McKechnie, L. (E.F.) (eds.), Theories of Information Behavior. Medford, NJ: Information Today, for ASIST, 303-307. [SILS Library - ZA3075 .T465 2005]

Activity theory

• Engestrom, Y. (2000). Activity theory as a framework for analyzing and redesigning work. Ergonomics, 43(7), 960-974. [UNC libraries]
• Kuutti, K. (1996). Activity theory as a potential framework for human-computer interaction research. In Nardi, B.A. (ed.), Context and Consciousness: Activity Theory and Human-Computer Interaction. Cambridge, MA: MIT Press, 17-44. [SILS Library - QA76.9 .H85 C68 1996]
• Kaptelinin, V. (1996). Activity theory: implications for human-computer interaction. In Nardi, B.A. (ed.), Context and Consciousness: Activity Theory and Human-Computer Interaction. Cambridge, MA: MIT Press, 103-116. [SILS Library - QA76.9 .H85 C68 1996]
• Bertelsen, O.W., & Bodker, S. (2003). Activity theory. In Carroll, J.M. (ed.), HCI Models, Theories, and Frameworks: Toward a Multidisciplinary Science. Amsterdam: Moran Kaufmann, 291-324. [SILS Library - QA76.9.H85 C367 2003]
• Bedny, G.Z., & Harris, S.R. (2005). The systemic-structural theory of activity: Applications to the study of human work. Mind, Culture, and Activity, 12(2), 128-147. [Available in UNC libraries]
• Bedny, G.Z., & Karwowski, W. (2004). Activity theory as a basis for the study of work. Ergonomics, 47(2), 134-153. [Available in UNC libraries]
• Wilson, T.D. (2006). A re-examination of information seeking behaviour in the context of activity theory. Information Research, 11(4). http://informationr.net/ir/11-4/paper260.html.

Distributed cognition

• Perry, M. (2003). Distributed cognition.In Carroll, J.M. (ed.), HCI Models, Theories, and Frameworks: Toward a Multidisciplinary Science. Amsterdam: Moran Kaufmann, 193-224. [SILS Library - QA76.9.H85 C367 2003]

Human information processor model (Card, Moran, & Newell)

• MacKenzie, I.S. (2003). Motor behavior models for human-computer interaction. In Carroll, J.M. (ed.), HCI Models, Theories, and Frameworks: Toward a Multidisciplinary Science. Amsterdam: Moran Kaufmann, 27-54. [SILS Library - QA76.9.H85 C367 2003]
• John, B.E. (2003). Information processing and skilled behavior. In Carroll, J.M. (ed.), HCI Models, Theories, and Frameworks: Toward a Multidisciplinary Science. Amsterdam: Moran Kaufmann, 55-102. [SILS Library - QA76.9.H85 C367 2003]

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The INLS 887 website, UNC-CH, 2011, is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 United States License. Address all comments and questions to Barbara M. Wildemuth at wildemuth@unc.edu. This page was last modified on January 4, 2013, by Barbara M. Wildemuth.