The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Understanding the relationship between attribute performance and overall satisfaction: Theory, measurement and implications
Abstract
Purpose: There is a pressing need for practitioners to adopt viable analytic procedures that may help them optimize resource allocation to strengthen customer satisfaction. This paper reviews a range of procedures used for measuring customer satisfaction that are identified in the literature and tests which procedures might be more useful to practitioners. Design/methodology/approach: Customer satisfaction measurement procedures developed in the literature are reviewed to assess the non‐linear and asymmetric relationship between attribute performance and overall satisfaction. A convergent validity test between the two measurement procedures that the review suggests are the most suitable for application in practice is then conducted to discover the relative merits of each. The test is based on an empirical investigation carried out in the mobile communication industry. Findings: Two measurement procedures were identified as the most appropriate to practitioners, “regression with dummy variables” and the “Importance Grid”. These were compared using a convergent validity test, which revealed a lack convergent validity between the two. Discussion about the reliability of the two procedures and the implications for practice is provided. On balance, the regression with dummy variables was identified as the better approach. Originality/value: The paper highlights the importance that recognition is given to the non‐linear and asymmetric response of customer satisfaction to the performance of different product/service attributes if appropriate decisions are to be made for allocating marketing resources. While research on customer satisfaction has emphasized the need to account for the non‐linear and asymmetric relationship between attribute performance and overall satisfaction, no effort has been made to disseminate these insights fully among practitioners. Since understanding the relationship between attribute performance and overall satisfaction is paramount if resource allocation to improve attribute performance is to be prioritized correctly, there is a pressing concern to move customer satisfaction programs closer to the theory predictions. A range of measurement procedures is reviewed and compared. Through this work, academics and practitioners may gain further insight into procedures for measuring customer satisfaction and an understanding of the relative benefits and limitations of the procedures that may be adopted.
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Cites
The critical incident technique.
Flanagan, J. C. (1954) · Psychological Bulletin · doi:10.1037/h0061470 · Cited by 8,191
The Service Encounter: Diagnosing Favorable and Unfavorable Incidents
Bitner, M. J., Booms, B. H., & Tetreault, M. S. (1990) · Journal of Marketing · doi:10.2307/1252174 · Cited by 4,860
The antecedents and consequences of customer satisfaction for firms
Anderson, E. W., & Sullivan, M. W. (1993) · Marketing Science · doi:10.1287/mksc.12.2.125 · Cited by 4,610
Bolton, R. N. (1998) · Marketing Science · doi:10.1287/mksc.17.1.45 · Cited by 1,948
Mittal, V., Ross, W. T., & Baldasare, P. M. (1998) · Journal of Marketing · doi:10.2307/1251801 · Cited by 1,216
Cited by
The Process of Customer Engagement: A Conceptual Framework
Bowden, J. L.-H. (2009) · Journal of Marketing Theory and Practice · doi:10.2753/mtp1069-6679170105 · Cited by 1,365
Verhagen, T., & van Dolen, W. (2011) · Information & Management · doi:10.1016/j.im.2011.08.001 · Cited by 767
A critical review of techniques for classifying quality attributes in the Kano model
Mikulić, J., & Prebežac, D. (2011) · Managing Service Quality: An International Journal · doi:10.1108/09604521111100243 · Cited by 340
Six Sigma quality: a structured review and implications for future research
Gamal Aboelmaged, M. (2010) · International Journal of Quality & Reliability Management · doi:10.1108/02656711011023294 · Cited by 259
Metadata
- Authors
- Busacca, B., & Padula, G.
- Venue
- Marketing Intelligence & Planning
- Publisher
- Emerald
- Published
- 2005-10-01
- Volume
- 23
- Issue
- 6
- Pages
- 543-561
- ISSN
- 0263-4503 (ISSN-L)
- OpenAlex
- W1545697225
- Cited by
- 175
- References
- 5
- FWCI
- 5.29
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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