Theory of planned behavior
Theory of planned behavior
Main dependent construct(s)/factor(s)
Behavioral intention, Behavior
Main independent construct(s)/factor(s)
Attitude toward behavior, Subjective norm, Perceived behavioral control
Concise description of theory
TPB posits that individual behavior is driven by behavioral intentions where behavioural intentions are a function of an individual's attitude toward the behaviour, the subjective norms surrounding the performance of the behavior, and the individual's perception of the ease with which the behavior can be performed (behavioral control). Attitude toward the behavior is defined as the individual's positive or negative feelings about performing a behaviour. It is determined through an assessment of one's beliefs regarding the consequences arising from a behavior and an evaluation of the desirability of these consequences. Formally, overall attitude can be assessed as the sum of the individual consequence x desirability assessments for all expected consequences of the behavior. Subjective norm is defined as an individual's perception of whether people important to the individual think the behavior should be performed. The contribution of the opinion of any given referent is weighted by the motivation that an individual has to comply with the wishes of that referent. Hence, overall subjective norm can be expressed as the sum of the individual perception x motivation assessments for all relevant referents. Behavioral control is defined as one's perception of the difficulty of performing a behavior. TPB views the control that people have over their behavior as lying on a continuum from behaviors that are easily performed to those requiring considerable effort, resources, etc. Although Ajzen has suggested that the link between behavior and behavioral control outlined in the model should be between behavior and actual behavioural control rather than perceived behavioural control, the difficulty of assessing actual control has led to the use of perceived control as a proxy.
While this theory has not yet been empirically proven to be explainable by Semantic theory of survey response, one theory built on TPB has been shown to be almost entirely semantically explainable.
Source: Eagly, A. H., & Chaiken, S. (1993). The psychology of attitudes. Fort Worth: Harcourt Brace Jovanovich College Publishers.
Diagram/schematic of theory
Ajzen (1985); Ajzen (1991)
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl, & J. Beckmann (Eds.), Springer series in social psychology (pp. 11-39). Berlin: Springer.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
Level of analysis
IS articles that use the theory
Bobbitt, L. M., & Dabholkar, P. A. (2001). Integrating attitudinal theories to understand and predict use of technology-based self-service: The internet as an illustration. International Journal of Service Industry Management, 12(5), 423-450.
Bosnjak, M., Tuten, T. L., & Wittmann, W. W. (2005). Unit (non)response in web-based access panel surveys: An extended planned-behavior approach. Psychology & Marketing, 22(6), 489-505.
Brown, S. A., & Venkatesh, V. (2005).Model of adoption of technology in households: A baseline model test and extension incorporating household life cycle. MIS Quarterly, 29(3), 399-426.
Celuch, K., Taylor, S. A., & Goodwin, S. (2004). Understanding insurance salesperson internet information management intentions: A test of competing models. Journal of Insurance Issues, 27(1), 22-40.
Chau, P. Y. K., & Hu, P. J. (2002). Investigating healthcare professionals' decisions to accept telemedicine technology: An empirical test of competing theories. Information & Management, 39(4), 297-311.
Chau, P. Y. K., & Hu, P. J. (2001). Information technology acceptance by individual professionals: A model comparison approach. Decision Sciences, 32(4), 699-719.
d'Astous, A., Colbert, F., & Montpetit, D. (2005). Music piracy on the web - how effective are anti-piracy arguments? evidence from the theory of planned behaviour. Journal of Consumer Policy, 28(3), 289-310.
Gentry, L., & Calantone, R. (2002). A comparison of three models to explain shop-bot use on the web. Psychology & Marketing, 19(11), 945-955.
George, J. F. (2004). The theory of planned behavior and internet purchasing. Internet Research, 14(3), 198-212.
Grandon, E. E., & Mykytyn, P. P.,Jr. (2004). Theory-based instrumentation to measure the intention to use electronic commerce in small and medium sized businesses. The Journal of Computer Information Systems, 44(3), 44-57.
Hansen, T., Jensen, J. M., & Solgaard, H. S. (2004). Predicting online grocery buying intention: A comparison of the theory of reasoned action and the theory of planned behavior. International Journal of Information Management, 24(6), 539-550.
Harrison, D. A., Mykytyn, P. P., & Riemenschneider, C. K. (1997). Executive decisions about adoption of information technology in small business: Theory and empirical tests. Information Systems Research, 8(2), 171-195.
Hsu, M., & Chiu, C. (2004). Internet self-efficacy and electronic service acceptance. Decision Support Systems, 38(3), 369-381.
Leonard, L. N. K., Cronan, T. P., & Kreie, J. (2004). What influences IT ethical behavior intentions-planned behavior, reasoned action, perceived importance, or individual characteristics? Information & Management, 42(1), 143-158.
Liao, S., Shao, Y. P., Wang, H., & Chen, A. (1999). The adoption of virtual banking: An empirical study. International Journal of Information Management, 19(1), 63-74.
Lim, J. (2003). A conceptual framework on the adoption of negotiation support systems. Information and Software Technology, 45(8), 469-477.
Limayem, M., & Hirt, S. G. (2003). Force of habit and information systems usage: Theory and initial validation. Journal of the Association for Information Systems, 4, 65-97.
Lowry, Paul Benjamin, Gaskin, James, Twyman, Nathan W., Hammer, Bryan, and Roberts, Tom L. (2013). “Taking ‘fun and games’ seriously: Proposing the hedonic-motivation system adoption model (HMSAM),” Journal of the Association for Information Systems (JAIS), vol. 14(11), 617–671.
Lowry, Paul Benjamin, Jenkins, Jeffrey L., Twyman, Nathan W., Hammer, Bryan, Gaskin, James, and Hassell, Martin (2008). “Proposing the hedonic affect model (HAM) to explain how stimuli and performance expectations predict affect in individual and group hedonic systems use,” Proceedings of the Journal of the Association for Information Systems Theory Development Workshop at the International Conference on Systems Sciences, Paris, France, December 13. All Sprouts Content, vol. 8(24), paper 230, pp. 1–51.
Lowry, Paul Benjamin, Twyman, Nathan W., Gaskin, James, Hammer, Bryan, Bailey, Aaron, and Roberts, Tom L. (2007). “Proposing the interactivity-stimulus-attention model (ISAM) to explain and predict enjoyment, immersion, and adoption of purely hedonic systems,” Proceedings of the Special Interest Group on Human-Computer Interaction 2007 Pre-ICIS Workshop at the International Conference on System Sciences, Montréal, Canada, December 8, paper 11, pp. 72–76 (best-paper nomination) http://aisel.aisnet.org/sighci2007/11/.
Lwin, M. O., & Williams, J. D. (2003). A model integrating the multidimensional developmental theory of privacy and theory of planned behavior to examine fabrication of information online. Marketing Letters, 14(4), 257-272.
Mathieson, K. (1991). Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2(3), 173-191.
Morris, M. G., Venkatesh, V., & Ackerman, P. L. (2005). Gender and age differences in employee decisions about new technology: An extension to the theory of planned behavior. IEEE Transactions on Engineering Management, 52(1), 69-84.
Riemenschneider, C. K., Harrison, D. A., & Mykytn, P. P.,Jr. (2003). Understanding IT adoption decisions in small business: Integrating current theories. Information & Management, 40(4), 269-285.
Riemenschneider, C. K., & McKinney, V. R. (2001). Assessing belief differences in small business adopters and non-adopters of web-based e-commerce. The Journal of Computer Information Systems, 42(2), 101-107.
Shih, Y., & Fang, K. (2004). The use of a decomposed theory of planned behavior to study internet banking in taiwan. Internet Research, 14(3), 213-223.
Tan, M., & Teo, T. S. H. (2000). Factors influencing the adoption of internet banking. Journal of the Association for Information Systems, 1(5), 1-42.
Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144-176.
Venkatesh, V., & Brown, S. A. (2001). A longitudinal investigation of personal computers in homes: Adoption determinants and emerging challenges. MIS Quarterly, 25(1), 71-102.
Venkatesh, V., Morris, M. G., & Ackerman, P. L. (2000). A longitudinal field investigation of gender differences in individual technology adoption decision-making processes. Organizational Behavior and Human Decision Processes, 83(1), 33-60.
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.
Workman, M. (2005). Expert decision support system use, disuse, and misuse: A study using the theory of planned behavior. Journal of Computers in Human Behavior, 21, 211-231.
Links from this theory to other theories
http://en.wikipedia.org/wiki/Theory_of_planned_behaviour, Wikipedia presents an overview of the theory of planned behavior including references.
http://www.tcw.utwente.nl/theorieenoverzicht/Theory%20clusters/Health%20Communication/theory_planned_behavior.doc/ , The University of Twente in the Netherlands presents an overview of the theory of planned behavior and the theory of reasoned action including references.
http://www.people.umass.edu/aizen/tpb.html, Useful summary of TPB, including bibliography and survey items, from Icek Ajzen
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