The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Measuring Information Systems Service Quality: Concerns for a Complete Canvas1
Abstract
This paper responds to the research note in this issue by Van Dyke et al. concerning the use of SERVQUAL, an instrument to measure service quality, and its use in the IS domain. This paper attempts to balance some of the arguments they raise from the marketing literature on the topic with the well-documented counterarguments of SERVQUAL’s developers, as well as our own research evidence and observations in an IS-specific environment. Specifically, evidence is provided to show that the service quality perceptions-expectations subtraction in SERVQUAL is far more rigorously grounded than Van Dyke et al. suggest; that the expectations construct, while potentially ambiguous, is generally a vector in the case of an IS department; and that the dimensions of service quality seem to be as applicable to the IS department as to any other organizational setting. Then, the paper demonstrates that the problems of reliability of difference score calculations in SERVQUAL are not nearly as serious as Van Dyke et al. suggest; that while perceptions-only measurement of service quality might have marginally better predictive and convergent validity, this comes at considerable expense to managerial diagnostics; and reiterate some of the problems of dimensional instability found in our previous research, highlighted by Van Dyke et al. and discussed in many other studies of SERVQUAL across a range of settings. Finally, four areas for further research in this area are identified.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
SERVQUAL: A multiple-Item Scale for measuring consumer perceptions of service quality
Parasuraman, A., Berry, L. L., & Zeithaml, V. A. (1988) · Zenodo · doi:10.5281/zenodo.14579729 · Cited by 21,118
A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions
Oliver, R. L. (1980) · Journal of Marketing Research · doi:10.1177/002224378001700405 · Cited by 14,494
Cited by
Customer Loyalty in E-Commerce
Drexel University, & Gefen, D. (2002) · Journal of the Association for Information Systems · doi:10.17705/1jais.00022 · Cited by 1,062
Perceived system performance: a test of an extended technology acceptance model
Liu, L., & Ma, Q. (2006) · ACM SIGMIS Database: the DATABASE for Advances in Information Systems · doi:10.1145/1161345.1161354 · Cited by 80
The impact of user‐perceived e‐procurement quality on system and contract compliance
Brandon‐Jones, A., & Carey, S. (2011) · International Journal of Operations & Production Management · doi:10.1108/01443571111111928 · Cited by 58
Metadata
- Authors
- Pitt, L. F., Watson, R. T., & Kavan, C. B.
- Venue
- MIS Quarterly
- Publisher
- MIS Quarterly
- Published
- 1997-06-01
- Volume
- 21
- Issue
- 2
- Pages
- 209-221
- ISSN
- 0276-7783 (ISSN-L)
- 2162-9730
- OpenAlex
- W1542558466
- Cited by
- 274
- References
- 2
- FWCI
- 11.49
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Measuring Information Systems Service Quality: Concerns for a Complete Canvas1. https://app.cochat.ai/papers/10.2307/249420
- The paper
- Pitt, L. F., Watson, R. T., & Kavan, C. B. (1997). Measuring Information Systems Service Quality: Concerns for a Complete Canvas1. MIS Quarterly. https://doi.org/10.2307/249420
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.