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Theory of Reasoned Action
 

Theory of Reasoned Action

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A brief presentation on the theory of reasoned action

A brief presentation on the theory of reasoned action

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    Theory of Reasoned Action Theory of Reasoned Action Presentation Transcript

    • THEORY OF REASONED ACTION (TRA) Aravind Sesagiri Raamkumar
    • AGENDA Example Introduction Development of Theory Usage in IS Discussion
    • LETS START WITH A REAL WORLD EXAMPLE
    • COMPONENTS Attitude towards behavior Intentions for Behavior behavior Subjective Norms Dependent Variables Independent Variables  Behavior  Attitude towards the behavior  Intentions for behaviors  Subjective Norms or Normative Beliefs  Intentions for behaviors
    • BACKGROUND Domain: Social Psychology Base Theory: Dulany’s Theory of Propositional Control(1968) Objective: To establish relationship between attitude and overt behavior Main Contributors: Icek Ajzen and Martin Fishbein Period of Work: 1965-1980s
    • MAIN PAPERS 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., & Ajzen, I. (1975). Belief, attitude, intention, and behavior : An introduction to theory and research. Reading, Mass. ; Don Mills, Ontario: Addison-Wesley Pub. Co
    • THE THEORY B ≈ BI = (w1)AB + (w2)SN B -> Behavior | BI -> Behavioral Intention | AB -> Attitude towards behavior SN -> Subjective Norms | W1 -> Weight for AB | W2 -> Weight for SN
    • STEP BY STEP VERIFICATION WITH EMPIRICAL DATA Step 1: Behavior (B) and Behavioral Intentions (BI) • Experiment: Prisoner’s Dilemma based games with two persons • Motivational Orientations: Competitive, Cooperative or Individualistic • Correlation of 0.822 (p < 0.001) between B and BI over 20 trails • Confirmatory findings from other researchers- Hornik (1970) & Darroch (1971) Constraints 1. The measurement of intentions needs to be taken in close proximity to the behavior 2. Mediating variables can cause changes in behaviors independent of measured intentions
    • STEP BY STEP VERIFICATION WITH EMPIRICAL DATA Step 2 and Step 3: Attitude & Normative Beliefs with Behavioral Intentions • Same set of experiments • AB was measures by rating the behavior in question using semantic differential scales • SN or NB was measured by a direct question concerning expectations of others • Average correlation was found to be 0.808 -> High predictive value • Attitudinal component (AB)has more influence than normative beliefs(NB) Constraints Prediction of B varies based on 1) Type of Behavior 2) Situation 3) Individual Difference between the actors
    • STATISTICAL ANALYSIS
    • OTHER FACTORS Beliefs play an important role in Attitude formation  Existence of a circular loop between behavior to belief External variables don’t’ directly cause changes in intentions rather it is through AB and SN General attitude towards an object is a summation of the attitudes related to different behaviors related to the particular object
    • ISSUES WITH THE THEORY Only works when the individual has volitional control Difficulty in differentiating attitudes and social norms Doesn’t take factors such as skills, unconscious habits and restricted environment into account
    • SUCCESSORS TO THE THEORY Theory of Planned Behavior(TPB) Technology Acceptance Model(TAM) Unified Theory of Acceptance and Use of Technolog
    • USAGE OF TRA IN IS Mainly used in studies related to user intentions Examples:  Consumer online grocery buying intention (2004)  Study of students’ interest in IS career (2011)  Study of Social Networking Behavior (2012) Methodology of usage  Check if the TRA model fits the problem space  Factor analysis  Take the measurements and use them for prediction  Structural Equation Modeling
    • DISCUSSIONWhere can we use this model?  TRA model finds application if the problem space involves understanding and changing the behavior of users  Most studies try to compare TRA, TPB and TAM and see which model performs fits and performs better Conversion of conceptual variables into measurable variables can be tricky
    • Q&A…
    • Consumer online grocery buying intention (2004) Home
    • Consumer online grocery buying intention (2004) Home
    • Study of Social Networking Behavior (2012) Home