IDEAS home Printed from
   My bibliography  Save this article

A modular fuzzy inference system approach in integrating qualitative and quantitative analysis of store image


  • Ling-Zhong Lin


  • Tsuen-Ho Hsu


The image situation in a store includes various stimuli, such as color, sound, scent, taste, layout and space, which are important clues for buyers. This paper describes store image response and a fuzzy logic model developed by comprehensive literature studies on image measurements (including atmospheric factors) and perceptual measures. Here, a fuzzy inference system is proposed as an alternative approach to handle effectively the impreciseness and uncertainty that are normally found in store image selection processes. This paper also shows that the proposed decision-making model is application to modified stimulus–organism–response (S–O–R) framework for integrating qualitative and quantitative analysis. The result of the simulation indicates a numerical and linguistic change in the store image perception after analyzing three input parameters. This finding is able to provide a solid foundation on which retailers and decision makers can base suitable strategies for ensuring the efficiency and stability of store image management system. Copyright Springer Science+Business Media B.V. 2012

Suggested Citation

  • Ling-Zhong Lin & Tsuen-Ho Hsu, 2012. "A modular fuzzy inference system approach in integrating qualitative and quantitative analysis of store image," Quality & Quantity: International Journal of Methodology, Springer, vol. 46(6), pages 1847-1864, October.
  • Handle: RePEc:spr:qualqt:v:46:y:2012:i:6:p:1847-1864
    DOI: 10.1007/s11135-011-9561-7

    Download full text from publisher

    File URL:
    Download Restriction: Access to full text is restricted to subscribers.

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

    References listed on IDEAS

    1. Samli, A. Coskun & Kelly, J. Patrick & Hunt, H. Keith, 1998. "Improving the Retail Performance by Contrasting Management- and Customer-Perceived Store Images: A Diagnostic Tool for Corrective Action," Journal of Business Research, Elsevier, vol. 43(1), pages 27-38, September.
    2. Belk, Russell W, 1975. " Situational Variables and Consumer Behavior," Journal of Consumer Research, Oxford University Press, vol. 2(3), pages 157-164, December.
    3. Chebat, Jean-Charles & Michon, Richard, 2003. "Impact of ambient odors on mall shoppers' emotions, cognition, and spending: A test of competitive causal theories," Journal of Business Research, Elsevier, vol. 56(7), pages 529-539, July.
    4. Collan, Mikael & Liu, Shuhua, 2002. "Fuzzy Logic and Intelligent Agents: Towards the Next Step of Capital Budgeting Decision Support," Working Papers 398, IAMSR, Åbo Akademi.
    Full references (including those not matched with items on IDEAS)


    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:spr:qualqt:v:46:y:2012:i:6:p:1847-1864. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Rebekah McClure). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.