The influence of store atmospherics on customers’ satisfaction at selected South African retail outlets

  • Received September 7, 2020;
    Accepted December 24, 2020;
    Published February 1, 2021
  • Author(s)
  • DOI
    http://dx.doi.org/10.21511/im.17(1).2021.03
  • Article Info
    Volume 17 2021, Issue #1, pp. 26-39
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This work is licensed under a Creative Commons Attribution 4.0 International License

In the retail environment, customers are stimulated by the look and feel of a store and how it is laid out. Certain store elements create an atmosphere that attracts customers to certain outlets as their preferred shopping destination. Therefore, retailers need to ensure the customers’ shopping experience is enjoyable. This study aimed to examine the influence of atmospheric store elements on the factors that influence customers` satisfaction. A quantitative, cross-sectional, descriptive study was conducted in four retail outlets in Cape Town, South Africa, with data collected through a structured questionnaire distributed to the outlets’ customers. A systematic random sample of 388 responses was achieved. The information collected was analyzed using relevant descriptive and inferential statistics. Although small, positive correlations were found between the independent variables (cleanliness, lighting, music, floor adverts, employee efficient service, employee appearance) and the dependent variables (positive image of store, pleasant mood, time spent in store, intention to revisit store). As such, the study highlighted the importance of store atmospherics to the factors that encourage customers` satisfaction. Since little research has been done into store atmospherics in the South African context of grocery stores, this study has contributed new knowledge in this field.

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    • Figure 1. Conceptual framework
    • Figure 2. Revised conceptual model
    • Table 1. Sample size breakdown
    • Table 2. Questionnaire derivation
    • Table 3. Response rate results
    • Table 4. Profile of respondents’ demographics
    • Table 5. Factor analysis and Cronbach’s alpha coefficient
    • Table 6. Descriptive statistics
    • Table 7. Correlation analysis
    • Conceptualization
      Richard Mfundi Ndengane, Roger B. Mason
    • Data curation
      Richard Mfundi Ndengane
    • Formal Analysis
      Richard Mfundi Ndengane, Misheck Mutize
    • Writing – original draft
      Richard Mfundi Ndengane, Roger B. Mason
    • Writing – review & editing
      Richard Mfundi Ndengane, Roger B. Mason, Misheck Mutize
    • Supervision
      Roger B. Mason, Misheck Mutize