Theory of reasoned action

Acronym
TRA

Alternate name(s)
N/A

Main dependent construct(s)/factor(s)
Behavioral intention, Behavior

Main independent construct(s)/factor(s)
Attitude toward behavior, Subjective norm,

Concise description of theory
TRA posits that individual behavior is driven by behavioral intentions where behavioural intentions are a function of an individual's attitude toward the behaviour and subjective norms surrounding the performance of the behavior. 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. Algebraically TRA can be represented as B ≈ BI = w1AB + w2SN where B is behavior, BI is behavioral intention, AB is attitude toward behavior, SN is subjective norm, and w1 and w2 are weights representing the importance of each term.

The model has some limitations including a significant risk of confounding between attitudes and norms since attitudes can often be reframed as norms and vice versa. A second limitation is the assumption that when someone forms an intention to act, they will be free to act without limitation. In practice, constraints such as limited ability, time, environmental or organisational limits, and unconscious habits will limit the freedom to act. The theory of planned behavior (TPB) attempts to resolve this limitation.

Sources:

http://en.wikipedia.org/wiki/Technology_acceptance_model Eagly, A. H., & Chaiken, S. (1993). The psychology of attitudes. Fort Worth: Harcourt Brace Jovanovich College Publishers.

Diagram/schematic of theory


Source: Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior : An introduction to theory and research. Reading, Mass. ; Don Mills, Ontario: Addison-Wesley Pub. Co.

Originating author(s)
Fishbein (1967); Ajzen and Fishbein (1973); Fishbein and Ajzen (1975)

Seminal articles
Ajzen, I., & Fishbein, M. (1973). Attitudinal and normative variables as predictors of specific behavior. Journal of Personality and Social Psychology, 27(1), 41-57.

Fishbein, M. (1967). Attitude and the prediction of behavior. In M. Fishbein (Ed.), Readings in attitude theory and measurement (pp. 477-492). New York: Wiley.

Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention, and behavior : An introduction to theory and research. Reading, Mass. ; Don Mills, Ontario: Addison-Wesley Pub. Co.

Originating area
Social psychology

Level of analysis
Individual

IS articles that use the theory
Bagchi, S., Kanungo, S., & Dasgupta, S. (2003). Modeling use of enterprise resource planning systems: A path analytic study. European Journal of Information Systems, 12(2), 142-158.

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.

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.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.

Gentry, L., & Calantone, R. (2002). A comparison of three models to explain shop-bot use on the web. Psychology & Marketing, 19(11), 945-955.

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.

Hartwick, J., & Barki, H. (1994). Explaining the role of user participation in information system use. Management Science, 40(4), 440-465.

Hebert, M., & Benbasat, I. (1994). Adopting information technology in hospitals: The relationship between attitudes/expectations and behavior. Hospital & Health Services Administration, 39(3), 369-383.

Jae-Nam, L., & Young-Gul, K. (2005). Understanding outsourcing partnership: A comparison of three theoretical perspectives. IEEE Transactions on Engineering Management, 52(1), 43-58.

Jeffrey, A. C., & Fawzy, S. (1999). A graphical method for assessing knowledge-based systems investments. Logistics Information Management, 12(1/2), 63-77.

Karahanna, E., Straub, D. W., & Chervany, N. L. (1999). Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Quarterly, 23(2), 183-213.

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.

Liker, J. K., & Sindi, A. A. (1997). User acceptance of expert systems: A test of the theory of reasoned action. Journal of Engineering and Technology Management, 14(2), 147-173.

Mykytyn, P. P. J., & Harrison, D. A. (1993). The application of the theory of reasoned action to senior management and strategic information systems. Information Resources Management Journal, 6(2), 15-26.

Sheppard, B. H., Hartwick, J., & Warshaw, P. R. (1988). The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research. Journal of Consumer Research, 15(3), 325-343.

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.

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.

Yoh, E., Damhorst, M. L., Sapp, S., & Laczniak, R. (2003). Consumer adoption of the internet: The case of apparel shopping. Psychology & Marketing, 20(12), 1095-1118.

Links from this theory to other theories
Theory of planned behavior, Technology acceptance model, Unified theory of acceptance and use of technology

Original Contributor(s)
Brent Furneaux Please feel free to make modifications to this site. In order to do so, you must register. Return to Theories Used in IS Research