Sheppard: Zones of Tolerance, Page 1
Published in Tourism Analysis, Vol 3. pp 111-114, 1998.
RESEARCH NOTE
Zone of Tolerance: A Proposed Model
Incorporating Subjective Criticality
Anthony G. Sheppard
Abstract: The idea of a zone of tolerance, between desired and adequate levels of service
quality, is well established. It has been suggested previously that the extent of this zone
of tolerance is somewhat determined by the nature or part of the service experience that is
being judged. This short paper proposes a revised model in which the zone of tolerance
is related to how subjectively critical an individual feels the service experience to be.
Keywords: Zone of tolerance, subjective criticality
Author: Anthony G. Sheppard is an Assistant Professor of Recreation and Leisure
Studies at California State University, Sacramento. Correspondence may be addressed to
the author at Department of Recreation & Leisure Studies, CSU Sacramento, 6000 J
Street, Sacramento, CA 95819-6110. Or by email to tony@csus.edu
Sheppard: Zones of Tolerance, Page 2
RESEARCH NOTE
As part of their gap analysis approach to measuring consumer perceptions
regarding service experiences, Parasuraman, Zeithaml and Berry referred to a zone of
tolerance between desired and adequate levels of service (c.f. Parasuraman, Zeithaml &
Berry, 1985; Berry & Parasuraman, 1991; Zeithaml, Berry & Parasuraman, 1993). While
noting certain circumstances that affected the relative magnitude of that zone of
tolerance, no single model was proposed that would incorporate these subjective
circumstances and, subsequently, how critical a given experience was to an individual.
This short paper is intended to suggest such an inclusive model.
In their related work, leading to development of the SERVQUAL scale (see also
Parasuraman, Zeithaml & Berry, 1988), the same authors identified five dimensions of
the service experience: reliability, responsiveness, assurance, empathy, and tangibles.
(While it is recognized that this dimensionality has since been questioned, amended
and/or criticized by several other researchers, even by the original authors, these
alternative viewpoints and findings are neither within the scope of this very brief
proposition or material to the basic premise of it.) Berry and Parasuraman (1991)
subsequently referred to the reliability dimension as the outcome dimension of the service
encounter and the other four dimensions as the process dimensions of the service
encounter. The authors also stressed the relative importance of the outcome dimension
over the process dimensions, as reported by subjects of their research. Figure 1
represents their conceptualization of the relative position and size of the zone of tolerance
with regard to expected levels of service performance, respective to both outcome and
Sheppard: Zones of Tolerance, Page 3
process dimensions. It can be seen that the more important outcome dimension coincides
with higher performance expectations and a narrower zone of tolerance than does the
process dimension.
[Insert Figure 1 about here]
The authors further identified nine factors that would cause the expectation levels
and zones of tolerance to vary (Berry & Parasuraman, 1991; Zeithaml, Parasuraman &
Berry, 1993). These included such factors as transitory service intensifiers (temporary
special needs) and explicit service promises (contracts, guarantees, advertising) that
might alter both expectations and tolerance.
A New Model
It is the purpose of this short paper to propose a single model that represents these
various phenomena in an inclusive manner. Rather than simply distinguishing between
the outcome and process dimensions (regardless of their exact makeup), this dichotomy
might be replaced with a continuum that reflects how critical a given expectation is in
relation to a performance evaluation, subjective to the individual and circumstance. For
the purposes of this monologue, this measure is termed subjective criticality and is,
essentially, an importance rating. The diagonal, dotted lines in Figure 2 are intended as a
bridging point in the development of the proposed model and stress the relative size and
position of the zones of tolerance illustrated in Figure 1. The proposed model can be
seen in Figure 3. Here, the lower axis represents subjective criticality (decreasing to be
Sheppard: Zones of Tolerance, Page 4
consistent with the placement of the dichotomous dimensions in Figures 1 and 2), or the
level to which the entire product or service encounter, or components thereof, are critical
to the individual consumer’s evaluation. It is this situationally specific measure of
importance that seems to reflect the differences between the earlier dimensions while
accommodating the effects of the suggested factors that might cause variation.
[Insert Figures 2 & 3 about here]
It is conjectured that as subjective criticality decreases, expected performance
levels decrease and the zone of tolerance widens. Conversely, as subjective criticality
increases, expected performance levels increase and the zone of tolerance narrows. This
is in keeping with the earlier models (Berry & Parasuraman, 1991). The extremes in
Figure 3 represent easily conceivable situations. At the upper left extreme (Point A)
might be found a situation wherein the service component is perceived to be so necessary
that the desired level of performance is the only acceptable level, with no lower level of
performance considered adequate. For example, a prospective hotel guest may be quite
flexible in terms of the features (size, location, etc) of a guestroom (relatively low
subjective criticality), but may not be at all tolerant of a situation in which no room is
available (extreme high subjective criticality – Point A). Point B (and points further to
the right) might represent a situation in which a particular component is considered
somewhat desirable, but for which the complete lack of that component is acceptable (an
intermediate level of subjective criticality). Similarly, Point C might represent a situation
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in which a specific component does not even rate a positive level of desirability (extreme
low subjective criticality).
It is worth noting that the model could be adapted to accommodate a trait that is
considered detrimental in some way. In such a case, the desired level might be the
complete lack of that component, while an acceptable level might represent some positive
representation of that trait. The measurement of such a trait would be negative (or else
the model would be inverted) and, for example, Point A in Figure 3 would be analogous
to a situation in which the complete lack of the trait was of critical importance and the
only acceptable result. Thus, a higher level of performance would represent the lower
level of the negatively perceived trait. Also, the model and associated arguments would
be similarly applicable to goods products and hybrids.
Implications
The proposed model appears to incorporate the features and ideas of the earlier
propositions, while allowing for greater flexibility and generalization. It would be
possible to test such a model within an existing data set that included both desired and
adequate performance levels and a measure of the relative importance of the
corresponding components. It may also be possible to combine such research with
existing importance-performance models.
By testing this proposition, both existing and future research may better enable us
to serve our various user groups. We intuitively associate higher performance ratings
with greater success in our respective endeavors. However, it is clearly possible for an
individual to rate one experience more highly than another in terms of performance while
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rating it lower in terms of satisfaction, given that their expectations of the two
experiences are not necessarily consistent. Similarly, any difference in subjective
criticality may also be found to affect perceptions of satisfaction and quality and, given
this knowledge, may require even higher levels of performance to accommodate higher
expectations and/or reduced tolerances.
Any increase in understanding regarding the extent to which tourists and other
consumers tolerate deviations from their expectations can only assist in increasing
satisfaction levels. This model would suggest the extreme importance of accurate
consumer based data regarding expectations for those products and components that are
subjectively perceived to be the most important. In practice, there may be no room for
error and no tolerance for underestimation of such expectations.
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References
Berry, L. L. & Parasuraman, A. (1991). Marketing services: Competing through quality.
New York: The Free Press.
Parasuraman, A, Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service
quality and its implications for future research. Journal of Marketing, 49(Fall),
41-50.
Parasuraman, A, Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A multiple-item
scale for measuring consumer perceptions of service quality. Journal of
Retailing, 64(1), 12-40.
Zeithaml, V. A., Berry, L. L., & Parasuraman, A. (1993). The nature and determinants of
customer expectations of service. Journal of the Academy of Marketing Science,
21(1), 1-12.