Nothing Special   »   [go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/a/hde/epregl/v57y2006i12p919-936.html
   My bibliography  Save this article

Segmentation Of Supermarket Shoppers Based On Their Satisfaction With Sales Staff And Store Design: Multivariance Analysis

Author

Listed:
  • Mirela Mihić

    (Faculty of Economics, University of Split)

Abstract
The aim of this study - based on the shoppers’ attitudes towards sales staff and store design - is to identify by using multivariance techniques some factors that may be used as a basis for market segmentation. Empirical research has been carried out on the sample of 15 supermarkets. In each store, 25 consumers were interviewed. Keeping in mind the issues and goals of the research, three hypotheses were formed. Three factors were identified by using the factor analysis (functional factors, atmospheric factors and personal factors), which were subsequently used as basic segmentation variables. Cluster analysis singled out three segments: satisfied with functional aspect, satisfied primarily with atmospherics and personal factors, and particularly dissatisfi ed with functional factors. To describe them better, demographic and behavioral variables were employed, as well as indicator of shoppers’ attitudes towards purchasing. The research results confi rmed the starting hypotheses and showed that retailers have to make changes if they want to be competitive in serving all the three segments. For that purpose those retailers were provided with suitable suggestions.

Suggested Citation

  • Mirela Mihić, 2006. "Segmentation Of Supermarket Shoppers Based On Their Satisfaction With Sales Staff And Store Design: Multivariance Analysis," Ekonomski pregled, Hrvatsko društvo ekonomista (Croatian Society of Economists), vol. 57(12), pages 919-936.
    • Handle: RePEc:hde:epregl:v:57:y:2006:i:12:p:919-936
    as

    Download full text from publisher

    File URL: https://hrcak.srce.hr/8528
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Ivana Pavlić & Katija Vojvodić & Barbara Puh, 2020. "Consumer Segmentation in Food Retailing in Croatia: A Latent Class Analysis," Tržište/Market, Faculty of Economics and Business, University of Zagreb, vol. 32(SI), pages 9-29.

    More about this item

    Keywords

    retailers; market segmentation; shoppers; factor analysis; cluster analysis; sales staff; store design;
    All these keywords.

    JEL classification:

    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce

    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:hde:epregl:v:57:y:2006:i:12:p:919-936. 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: Josip Tica (email available below). General contact details of provider: https://edirc.repec.org/data/hdeeeea.html .

    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.