IDEAS home Printed from https://ideas.repec.org/a/eee/aosoci/v21y1996i1p3-22.html
   My bibliography  Save this article

A comparison of compensatory and noncompensatory models of judgment: Effects of task predictability and degrees of freedom

Author

Listed:
  • G. Schneider, Linda
  • Selling, Thomas I.

Abstract

No abstract is available for this item.

Suggested Citation

  • G. Schneider, Linda & Selling, Thomas I., 1996. "A comparison of compensatory and noncompensatory models of judgment: Effects of task predictability and degrees of freedom," Accounting, Organizations and Society, Elsevier, vol. 21(1), pages 3-22, January.
  • Handle: RePEc:eee:aosoci:v:21:y:1996:i:1:p:3-22
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0361-3682(95)00017-4
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Biggs, Sf & Mock, Tj, 1983. "An Investigation Of Auditor Decision-Processes In The Evaluation Of Internal Controls And Audit Scope Decisions," Journal of Accounting Research, Wiley Blackwell, vol. 21(1), pages 234-255.
    2. Selling, Thomas & Shank, John, 1989. "Linear versus process tracing approaches to judgment modelling: A new perspective on cue importance," Accounting, Organizations and Society, Elsevier, vol. 14(1-2), pages 65-77, January.
    3. Klersey, George F. & Mock, Theodore J., 1989. "Verbal protocol research in auditing," Accounting, Organizations and Society, Elsevier, vol. 14(1-2), pages 133-151, January.
    4. Imran S. Currim & Linda G. Schneider, 1991. "A Taxonomy of Consumer Purchase Strategies in a Promotion Intensive Environment," Marketing Science, INFORMS, vol. 10(2), pages 91-110.
    5. Shields, Michael D., 1980. "Some effects on information load on search patterns used to analyze performance reports," Accounting, Organizations and Society, Elsevier, vol. 5(4), pages 429-442, October.
    6. Bettman, James R, 1974. "Toward a Statistics for Consumer Decision Net Models," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 1(1), pages 71-80, June.
    7. William F. Messier, Jr. & James V. Hansen, 1988. "Inducing Rules for Expert System Development: An Example Using Default and Bankruptcy Data," Management Science, INFORMS, vol. 34(12), pages 1403-1415, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. J. Randall Brown & Aviad A. Israeli & Abraham Mehrez, 2002. "Modelling a Decision Maker's Preferences with Different Assumptions about the Preference Structure: Theory Development and Initial Applications for Tourism and Hospitality Management," Tourism Economics, , vol. 8(1), pages 39-57, March.

    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. Kwok, Helen, 2002. "The effect of cash flow statement format on lenders' decisions," The International Journal of Accounting, Elsevier, vol. 37(3), pages 347-362.
    2. Coram, Paul J. & Mock, Theodore J. & Monroe, Gary S., 2011. "Financial analysts' evaluation of enhanced disclosure of non-financial performance indicators," The British Accounting Review, Elsevier, vol. 43(2), pages 87-101.
    3. Paul J. Coram & Theodore J. Mock & Jerry L. Turner & Glen L. Gray, 2011. "The Communicative Value of the Auditor's Report," Australian Accounting Review, CPA Australia, vol. 21(3), pages 235-252, September.
    4. Khouja, Moutaz & Subramaniam, Chandra & Vasudev, Vinay, 2020. "A comparative analysis of marketing promotions and implications for data analytics," International Journal of Research in Marketing, Elsevier, vol. 37(1), pages 151-174.
    5. Beynon, Malcolm J. & Peel, Michael J., 2001. "Variable precision rough set theory and data discretisation: an application to corporate failure prediction," Omega, Elsevier, vol. 29(6), pages 561-576, December.
    6. Enrico Supino & Nicola Piras, 2022. "Le performance dei modelli di credit scoring in contesti di forte instabilit? macroeconomica: il ruolo delle Reti Neurali Artificiali," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2022(2), pages 41-61.
    7. Kattan, MW & Cooper, RB, 1998. "The predictive accuracy of computer-based classification decision techniques.A review and research directions," Omega, Elsevier, vol. 26(4), pages 467-482, August.
    8. Pablo de Llano Monelos & Manuel Rodríguez López & Carlos Piñeiro Sánchez, 2013. "Bankruptcy Prediction Models in Galician companies. Application of Parametric Methodologies and Artificial Intelligence," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(1), pages 117-136.
    9. Seagle, John P. & Duchessi, Peter, 1995. "Acquiring expert rules with the aid of decision tables," European Journal of Operational Research, Elsevier, vol. 84(1), pages 150-162, July.
    10. Fejér-Király Gergely, 2015. "Bankruptcy Prediction: A Survey on Evolution, Critiques, and Solutions," Acta Universitatis Sapientiae, Economics and Business, Sciendo, vol. 3(1), pages 93-108, December.
    11. Tomi Rajala, 2019. "Mind the Information Expectation Gap," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 10(1), pages 104-125, March.
    12. Sezen Uludag, 2016. "The importance of control environment in an organization for an independent auditor to determine nature,timing, and extent of substantive tests: An application in Turkey," Journal of Administrative and Business Studies, Professor Dr. Usman Raja, vol. 2(6), pages 294-303.
    13. Casado Yusta, Silvia & Nœ–ez Letamendía, Laura & Pacheco Bonrostro, Joaqu’n Antonio, 2018. "Predicting Corporate Failure: The GRASP-LOGIT Model || Predicci—n de la quiebra empresarial: el modelo GRASP-LOGIT," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 26(1), pages 294-314, Diciembre.
    14. Ruey-Ching Hwang & K. F. Cheng & Jack C. Lee, 2007. "A semiparametric method for predicting bankruptcy," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(5), pages 317-342.
    15. Henderson, Geraldine R. & Iacobucci, Dawn & Calder, Bobby J., 1998. "Brand diagnostics: Mapping branding effects using consumer associative networks," European Journal of Operational Research, Elsevier, vol. 111(2), pages 306-327, December.
    16. Roy, Abhik, 1998. "An error components approach to segmentation and modelling brand choice dynamics," Journal of Economic Psychology, Elsevier, vol. 19(4), pages 463-484, August.
    17. Dilla, William N. & Raschke, Robyn L., 2015. "Data visualization for fraud detection: Practice implications and a call for future research," International Journal of Accounting Information Systems, Elsevier, vol. 16(C), pages 1-22.
    18. Yao-Zhi Xu & Jian-Lin Zhang & Ying Hua & Lin-Yue Wang, 2019. "Dynamic Credit Risk Evaluation Method for E-Commerce Sellers Based on a Hybrid Artificial Intelligence Model," Sustainability, MDPI, vol. 11(19), pages 1-17, October.
    19. Kida, Thomas & Smith, James F., 1995. "The encoding and retrieval of numerical data for decision making in accounting contexts: Model development," Accounting, Organizations and Society, Elsevier, vol. 20(7-8), pages 585-610.
    20. Petersen, Knut & Patzke, Henning, 1986. "Individuelles Informationsverhalten als Gegenstand des "Behavioral Accounting": Eine Meta-Analyse der empirischen Forschung," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 177, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.

    More about this item

    Statistics

    Access and download statistics

    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:eee:aosoci:v:21:y:1996:i:1:p:3-22. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/aos .

    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.