Service quality, image and performance
Research has shown that service quality and image contribute to better organizational performance. This paper aims to develop a model (with the working title of QIP model) that assesses the extent to which these factors can explain variability in organizational performance and whether one factor can...
Published in: | Tímarit um viðskipti og efnahagsmál |
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Main Authors: | , , |
Format: | Article in Journal/Newspaper |
Language: | Icelandic |
Published: |
Institute of Business Research
2021
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Subjects: | |
Online Access: | http://www.efnahagsmal.is/article/view/a.2021.18.2.2 https://doi.org/10.24122/tve.a.2021.18.2.2 |
Summary: | Research has shown that service quality and image contribute to better organizational performance. This paper aims to develop a model (with the working title of QIP model) that assesses the extent to which these factors can explain variability in organizational performance and whether one factor can be considered more important than another. Furthermore, the method was used to determine if factors differ in importance depending on where respondents conduct their main business. The findings are based on quantitative data gathered in the spring of 2021 from customers of the three largest commercial banks in Iceland, which in combination have over 95% of the market share. A total of 719 individuals responded to the survey; after incomplete or incorrect answers were deleted, the number of valid responses was 480. The questionnaire used was based on a research project that began in 2004 and assessed image development, service quality, and customer recommendations of Icelandic banks. Responses were weighted by gender and age, and factor analysis revealed four factors: quality 1, quality 2, image, and performance; all factors showed satisfactory loading (α > 0.7). The results demonstrate that the model explained 65% of the variability in performance (R2 = 0.65). Of the factors used to explain the variability, quality 1 had the highest weight (β = 0.44), and that factor alone explained 9% of the variability in performance (P2 = 0.09). The second most important factor was image (β = 0.35), which explained 7% of the variability in performance (P2 = 0.07). The factor that explained the least of the variability was quality 2 (β = 0.13), which explained only 1.1% of the variability in performance (P2 = 0.011). It was revealed that some differences were dependent on where the respondents conducted their main business. Thus, quality 1 was by far the most important factor among Bank A’s customers (β = 0.56), while image was the most important factor among Bank C’s customers (β = 0.48). The importance of the factors was more ... |
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