IDEAS home Printed from https://ideas.repec.org/a/sae/anname/v640y2012i1p58-80.html
   My bibliography  Save this article

The Reasoned Action Model

Author

Listed:
  • James Jaccard

Abstract

The reasoned action model (RAM) of Fishbein and Ajzen has been highly influential in the social and health sciences. This article describes three areas for future research that should expand its explanatory power. One area of research focuses on an idiographic RAM that encourages researchers to pursue the estimation of RAM parameters on a per-individual level rather than through traditional nomothetic modeling. The second area encourages scientists to develop a split-second RAM, that is, a RAM that can provide perspectives on the split-second decisions people make in everyday life. Integration of the RAM with models of working (short-term) memory is stressed. The third area for research encourages scientists to develop a multioption RAM that incorporates and is responsive to the choices that people make when confronted with multiple alternatives. This perspective stresses the need to apply the RAM to the full range of behavioral options that are available to people as they contemplate performing one behavior versus another. Perspectives for theoretical advancement in each area are developed.

Suggested Citation

  • James Jaccard, 2012. "The Reasoned Action Model," The ANNALS of the American Academy of Political and Social Science, , vol. 640(1), pages 58-80, March.
    • Handle: RePEc:sae:anname:v:640:y:2012:i:1:p:58-80
    DOI: 10.1177/0002716211426097
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0002716211426097
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0002716211426097?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Wayne S. DeSarbo & Kamel Jedidi & Indrajit Sinha, 2001. "Customer value analysis in a heterogeneous market," Strategic Management Journal, Wiley Blackwell, vol. 22(9), pages 845-857, September.
    2. Einhorn, Hj & Hogarth, Rm, 1981. "Behavioral Decision-Theory - Processes Of Judgment And Choice," Journal of Accounting Research, Wiley Blackwell, vol. 19(1), pages 1-31.
    3. Jaccard, James & Brinberg, David & Ackerman, Lee J, 1986. "Assessing Attribute Importance: A Comparison of Six Methods," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 12(4), pages 463-468, March.
    4. Lee, Kevin C & Pesaran, M Hashem & Pierse, Richard G, 1990. "Testing for Aggregation Bias in Linear Models," Economic Journal, Royal Economic Society, vol. 100(400), pages 137-150, Supplemen.
    5. Hong‐Tu Zhu & Heping Zhang, 2004. "Hypothesis testing in mixture regression models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(1), pages 3-16, February.
    6. Bengt Muthén & Kerby Shedden, 1999. "Finite Mixture Modeling with Mixture Outcomes Using the EM Algorithm," Biometrics, The International Biometric Society, vol. 55(2), pages 463-469, June.
    7. Brenda Curtis, 2012. "Understanding Tailored Internet Smoking Cessation Messages," The ANNALS of the American Academy of Political and Social Science, , vol. 640(1), pages 136-149, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Juan Shen & Xuming He, 2015. "Inference for Subgroup Analysis With a Structured Logistic-Normal Mixture Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 303-312, March.
    2. Georgiev, Iliyan, 2010. "Model-based asymptotic inference on the effect of infrequent large shocks on cointegrated variables," Journal of Econometrics, Elsevier, vol. 158(1), pages 37-50, September.
    3. Cabras, Stefano & Fidrmuc, Jan & de Dios Tena Horrillo, Juan, 2017. "Minimum wage and employment: Escaping the parametric straitjacket," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 11, pages 1-20.
    4. Michael Prendergast & David Huang & Yih-Ing Hser, 2008. "Patterns of Crime and Drug Use Trajectories in Relation to Treatment Initiation and 5-Year Outcomes," Evaluation Review, , vol. 32(1), pages 59-82, February.
    5. Mingyue Li & Jingjing Wang & Kai Chen & Lianbei Wu, 2020. "Willingness and Behaviors of Farmers’ Green Disposal of Pesticide Packaging Waste in Henan, China: A Perceived Value Formation Mechanism Perspective," IJERPH, MDPI, vol. 17(11), pages 1-18, May.
    6. Gerd Gigerenzer, 1997. "Bounded Rationality: Models of Fast and Frugal Inference," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 133(II), pages 201-218, June.
    7. Shumway, C. Richard & Davis, George C., 2001. "Does consistent aggregation really matter?," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 45(2), pages 1-34.
    8. Chorus, Caspar & van Cranenburgh, Sander & Daniel, Aemiro Melkamu & Sandorf, Erlend Dancke & Sobhani, Anae & Szép, Teodóra, 2021. "Obfuscation maximization-based decision-making: Theory, methodology and first empirical evidence," Mathematical Social Sciences, Elsevier, vol. 109(C), pages 28-44.
    9. S. Larsson & G. R. Chesley, 1986. "An analysis of the auditor's uncertainty about probabilities," Contemporary Accounting Research, John Wiley & Sons, vol. 2(2), pages 259-282, March.
    10. Ana Oliveira-Brochado & F. Vitorino Martins, 2006. "Examining the segment retention problem for the “Group Satellite” case," FEP Working Papers 220, Universidade do Porto, Faculdade de Economia do Porto.
    11. Giancarlo Lutero & Marco Marini, 2010. "Direct vs Indirect Forecasts of Foreign Trade Unit Value Indices," Rivista di statistica ufficiale, ISTAT - Italian National Institute of Statistics - (Rome, ITALY), vol. 12(2-3), pages 73-96, October.
    12. Getachew A. Dagne, 2016. "A growth mixture Tobit model: application to AIDS studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(7), pages 1174-1185, July.
    13. Bacci, Silvia & Bartolucci, Francesco & Pigini, Claudia & Signorelli, Marcello, 2014. "A finite mixture latent trajectory model for hirings and separations in the labor market," MPRA Paper 59730, University Library of Munich, Germany.
    14. Yu‐Lin Hsu & Gavin C. Reid, 2021. "Two‐stage decision‐making within the firm: Analysis and case studies," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(6), pages 1355-1373, September.
    15. Karen Green & Benson Wier, 2015. "Influence of Ethical Position and Information Asymmetry on Transfer Price Negotiations," Accounting and Finance Research, Sciedu Press, vol. 4(1), pages 1-30, February.
    16. Arnold, Vicky & Bedard, Jean C. & Phillips, Jillian R. & Sutton, Steve G., 2011. "Do section 404 disclosures affect investors' perceptions of information systems reliability and stock price predictions?," International Journal of Accounting Information Systems, Elsevier, vol. 12(4), pages 243-258.
    17. Schneider, Andreas, 2019. "Deterrence Theory in Paraguay: Exploring Fraud and Violation of Trust Cases," MPRA Paper 102204, University Library of Munich, Germany.
    18. Francesco Bartolucci & Ivonne Solis-Trapala, 2010. "Multidimensional Latent Markov Models in a Developmental Study of Inhibitory Control and Attentional Flexibility in Early Childhood," Psychometrika, Springer;The Psychometric Society, vol. 75(4), pages 725-743, December.
    19. Yuan Liu & Hongyun Liu, 2019. "Effects of Distance and Shape on the Estimation of the Piecewise Growth Mixture Model," Journal of Classification, Springer;The Classification Society, vol. 36(3), pages 659-677, October.
    20. Benjamin Agbo & Hussain Al-Aqrabi & Richard Hill & Tariq Alsboui, 2022. "Missing Data Imputation in the Internet of Things Sensor Networks," Future Internet, MDPI, vol. 14(5), pages 1-16, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:anname:v:640:y:2012:i:1:p:58-80. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.