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Cited by 678

The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.

Expectations as a Comparison Standard in Measuring Service Quality: An Assessment of a Reassessment

Teas, R. Kenneth·1994·Journal of Marketing

Abstract

The author responds to issues raised by Parasuraman, Zeithaml, and Berry (1994) concerning his 1993 article that outlines theoretical and operational problems associated with the SERVQUAL model of perceived service quality. Because theoretical problems and ambiguities must be resolved before operational issues can be addressed effectively, his response focuses on the Parasuraman, Zeithaml, and Berry (1994) comments concerning (1) the theoretical problems associated with the SERVQUAL P – E model and (2) the Teas (1993) evaluated performance (EP) and normed quality (NQ) models. In addition, he assesses the theoretical merit of the Parasuraman, Zeithaml, and Berry (1994) SERVQUAL “mixed-model.” His primary conclusions are that the conclusions reached by Parasuraman, Zeithaml, and Berry (1994) with respect to the Teas (1993) EP and NQ models are incorrect and that the proposed SERVQUAL mixed-model is merely a restricted version of (i.e., a re-expression that is less general than) the Teas (1993) NQ model.

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Metadata

Authors
Teas, R. K.
Venue
Journal of Marketing
Published
1994-01
Volume
58
Issue
1
Pages
132-139
ISSN
  • 0022-2429 (ISSN-L)
  • 1547-7185
OpenAlex
W2008848828
Cited by
678
References
10
FWCI
37.58
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Expectations as a Comparison Standard in Measuring Service Quality: An Assessment of a Reassessment. https://app.cochat.ai/papers/10.1177/002224299405800111
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Teas, R. K. (1994). Expectations as a Comparison Standard in Measuring Service Quality: An Assessment of a Reassessment. Journal of Marketing. https://doi.org/10.1177/002224299405800111

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.