IDEAS home Printed from https://ideas.repec.org/a/oup/jconrs/v33y2006i1p25-27.html
   My bibliography  Save this article

Accessibility-Diagnosticity and the Multiple Pathway Anchoring and Adjustment Model

Author

Listed:
  • John G. Lynch Jr.

Abstract

I discuss how the Multiple Pathway Anchoring and Adjustment model is similar to and different from the Feldman and Lynch accessibility-diagnosticity model, elaborated as an anchoring and adjustment model by Lynch, Marmorstein, and Weigold. Cohen and Reed's concept of representational sufficiency embraces both attitude coherence and retrieval fluency; these map to prior operationalizations of diagnosticity in past accessibility-diagnosticity research. Cohen and Reed's functional sufficiency maps closely to Lynch et al.'s notion of a comparison of cumulative diagnosticity to a diagnosticity threshold in an anchoring and adjustment process. I identify differences between the two models and call for research to distinguish their predictions. (c) 2006 by JOURNAL OF CONSUMER RESEARCH, Inc..

Suggested Citation

  • John G. Lynch Jr., 2006. "Accessibility-Diagnosticity and the Multiple Pathway Anchoring and Adjustment Model," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 33(1), pages 25-27, June.
  • Handle: RePEc:oup:jconrs:v:33:y:2006:i:1:p:25-27
    DOI: 10.1086/504129
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1086/504129
    File Function: link to full text
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1086/504129?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
    ---><---

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

    Citations

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


    Cited by:

    1. Chatterjee, Swagato & Goyal, Divesh & Prakash, Atul & Sharma, Jiwan, 2021. "Exploring healthcare/health-product ecommerce satisfaction: A text mining and machine learning application," Journal of Business Research, Elsevier, vol. 131(C), pages 815-825.
    2. Swoboda, Bernhard & Sinning, Carolina, 2020. "How country development and national culture affect the paths of perceived brand globalness to consumer behavior across nations," Journal of Business Research, Elsevier, vol. 118(C), pages 58-73.
    3. Legoux, Renaud & Larocque, Denis & Laporte, Sandra & Belmati, Soraya & Boquet, Thomas, 2016. "The effect of critical reviews on exhibitors' decisions: Do reviews affect the survival of a movie on screen?," International Journal of Research in Marketing, Elsevier, vol. 33(2), pages 357-374.
    4. Sebastian Schneider, 2022. "Price-related consumer discussions in China and the United States: a cross-cultural study investigating price perceptions and word-of-mouth transmission," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(3), pages 274-290, June.
    5. Sebastian Schneider & Frank Huber, 2022. "You paid what!? Understanding price-related word-of-mouth and price perception among opinion leaders and innovators," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(1), pages 64-80, February.
    6. Jha, Subhash & Balaji, M.S. & Peck, Joann & Oakley, Jared & Deitz, George D., 2020. "The Effects of Environmental Haptic Cues on Consumer Perceptions of Retailer Warmth and Competence," Journal of Retailing, Elsevier, vol. 96(4), pages 590-605.
    7. Habel, Johannes & Alavi, Sascha & Pick, DoreƩn, 2017. "When serving customers includes correcting them: Understanding the ambivalent effects of enforcing service rules," International Journal of Research in Marketing, Elsevier, vol. 34(4), pages 919-941.
    8. Liu, Ran & Ford, John B. & Zhang, Weiyong & Bonnici, Joseph, 2023. "Reappraising the roles of review valence and conflict in online relationships," Journal of Business Research, Elsevier, vol. 167(C).
    9. Kristiina Herold & Anssi Tarkiainen & Sanna Sundqvist, 2016. "How the source of word-of-mouth influences information processing in the formation of brand attitudes," Journal of Marketing for Higher Education, Taylor & Francis Journals, vol. 26(1), pages 64-85, January.
    10. Wendy Hui, 2010. "Self-generated Validity, Framing Effects, and Survey Research in IS," ICBBR Working Papers 11, International Centre for Behavioural Business Research.
    11. Lee, Saerom & Bolton, Lisa E., 2020. "Mixed signals? Decoding luxury consumption in the workplace," Journal of Business Research, Elsevier, vol. 117(C), pages 331-345.

    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:oup:jconrs:v:33:y:2006:i:1:p:25-27. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: the person in charge (email available below). General contact details of provider: https://academic.oup.com/jcr .

    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.