An Examination of the SERVQUAL Dimensions Using the GUTTMAN Svaling Procedure

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Journal of Hospitality & Tourism Research

DOI: 10.1177/1096348002238878

2003; 27; 3Journal of Hospitality & Tourism ResearchTae-Hwan Yoon and Yuksel Ekinci

An Examination Of The Servqual Dimensions Using The Guttman Scaling Procedure

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10.1177/1096348002238878ARTICLEJOURNALOFHOSPITALITY&TOURISMRESEARCHYoon,Ekinci/EXAMINATIONOFSERVQUALDIMENSIONS

AN EXAMINATION OF THE SERVQUAL

DIMENSIONS USING THE GUTTMAN

SCALING PROCEDURE

Tae-Hwan YoonYuksel Ekinci

University of Surrey, United Kingdom

Despite the popularity and continued use of the SERVQUAL Scale, a number of serious

criticisms have been raised concerning its validity. These criticisms focus on the generic

natureof theservicequalitydimensionsand theuseofdesired expectationas a comparisonstandard. Theobjectivesof this research are twofold. First, it sets out to examine the valid-

ity of the five SERVQUAL dimensions using an alternative scaling methodology known as

the Guttman scaling procedure. Second, it aims to determine the role of expectation in the

evaluation of hotel services. Of the five SERVQUAL dimensions tested,onlyfour are found

to bevalid.It is also apparent that differenttypes of expectations are used as a comparison

standard for the evaluation of service quality and customer satisfaction.

KEYWORDS: service quality; customer satisfaction; SERVQUAL scale; customer ex-

pectation.

Providingquality services hasbeen identified as oneof themost difficult long-

term strategies forestablishing a business. However, if this approach is pursued, it

eventually offers a competitive advantage in the market (Lewis, 1993) due to the

fact that high-quality services have been claimed to stimulate customer satisfac-

tion and reduce price competition (Hoffman & Bateson, 1997).

Because of the significant effect of service quality on an organizations suc-

cess, a customer-oriented model, SERVQUAL, was introduced to assess service

quality more than a decadeago(Parasuraman, Zeithaml,& Berry, 1988).Theaim

of this model is to help managers diagnose and improve the quality of services

under their control. According to SERVQUAL, quality is the gap between cus-

tomer expectationsandperception of performance.Hence, thegreater thepositive

gap, the higher the service quality and vice versa. It has been proposed that per-

ception of service quality is specificallyrelated to five generic dimensions: tangi-

bles, reliability, responsiveness, assurance, and empathy. In other words, the

model offers a multidimensional scale that aims to measure service quality in any(and every) service organization. This proposition has made SERVQUAL the

most popular research instrument in both academia and industry, and a great deal

Journal of Hospitality & Tourism Research, Vol. 27, No. 1, February 2003, 3-23

DOI: 10.1177/1096348002238878

2003 International Council on Hotel, Restaurant and Institutional Education

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of research hasbeen carried out in recentyears using this model in various service

organizations, including hotels.Despite itspopularity andcontinueduse, serious criticisms have been directed

at the model and the multidimensional instrument it presents. The majority of

these criticisms focus on the generic nature of the service quality dimensions

(Babakus & Boller, 1992; Carman, 1990) andtheuseof expectationas a compari-

son standard (Cronin & Taylor, 1994; Teas, 1994). The objectives of the present

study are twofold.First, it sets out to examine thevalidityof the five SERVQUAL

dimensions using an alternative scaling methodology known as theGuttman scal-

ing procedure (Ekinci & Riley, 1999; Guttman, 1950, as cited in McIver &

Carmines,1981). Second, it aims toassessthe role of customer expectations in the

evaluation of hotel services. The following section reviews some of the problems

associated with application of the SERVQUAL Scale and also outlines the ratio-

nale for the present research.

APPLICATIONS OF THE SERVQUAL SCALE AND ITS DIMENSIONS

Many attempts have been made to examine the generic quality of the

SERVQUAL dimensions within a specific industry (Babakus & Mangold, 1992,

as cited in Buttle, 1996; Cronin & Taylor, 1992). Carman (1990) showed that of

the five SERVQUAL dimensions, reliability, responsiveness, and tangibles are

the only robust ones when applied in three different retail outlets (a tire store,

placement center, and dental clinic). As a result, the study not only dismisses the

idea of themodels generic dimensions but also suggests that thenumberand type

of dimensions could be differentaccordingto theservices being evaluated. In line

with this view, Babakus and Boller (1992) stated that the domain of service qual-

itymight becomplex insome industries andverysimplein others. Following their

study, they too rejected the generic quality of SERVQUAL dimensions andargued that thenumberof relevantservice quality dimensions is dependenton the

nature of the services being evaluated.

Empirical studies in hotels provideevidence thatcustomerscannot distinguish

between the SERVQUAL dimensions. Saleh and Ryans (1991, p. 338) study on

the hotel industry indicates that although the tangibles, assurance, and empathy

dimensions are generic, those of responsiveness and reliability cannot be repli-

cated. Initially, five factors were identified in the factor analysis, but the first fac-

tor, Conviviality, accounted for 68.5% of the total variance, which was 78%, and

the second factor, Tangibles, accounted for a further 6.9%; therefore, this is sug-

gestive of a two-factor solution. Similarly, Getty and Thompson (1994, p. 84)

showed thatalthoughthedimensions of tangiblesandreliability aregeneric, those

of assurance, responsiveness, and empathy merge to form a single factor termed

Contact. Interestingly, both studies suggest a three-dimensional model for the

evaluation of hotels. This is similar to Parasuraman, Zeithaml, andBerrys (1994)

empirical findings when they tested the original SERVQUAL Scale and later

came up with a three-dimensional model, as opposed to five-dimensional, in

retailing. Similarly, Oberoi and Haless (1990) research in the U.K. conference

hotels suggests that perception of service quality is two-dimensional. A study by

4 JOURNAL OF HOSPITALITY & TOURISM RESEARCH



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Ekinci, Riley, and Fife-Schaw (1998) supported these findings, as the original

SERVQUAL Scale failsto display thefive dimensions in resorthotels. After mod-ifications, a two-dimensional scale (tangibles and intangibles) is produced. How-

ever, despite discouraging empirical results, this instrument is still considered to

be validand is used by researchers in thehospitality industry (e.g., Heung, Wong,

& Qu, 2000; Lam, Yeung, & Chang, 1998).

The study aims to investigate the extent to which the dimensions of the

SERVQUAL Scale are generic for the evaluation of service quality in hotels. To

do this, theGuttman scaling procedure is applied as opposed to those scaling pro-

cedures most commonly used (e.g., Likert-type scales) in the tourism and hospi-

tality literature.

THE ROLE OF EXPECTATION AS A COMPARISON STANDARD

Theconcept of expectation hasbeen emphasized as a key variable in theevalu-ation of service quality. However, Teas (1994) pointed out that some validity

problems arise when customer expectation is used as a comparison standard. For

example, expectation is dynamic in nature and may change according to custom-

ers experiences and consumption situations. Boulding, Karla, Stealin, and

Zeithaml (1993, p. 24) rejected the use of expectation as a comparison standard

for the measurement of service quality and suggested that a performance-only

measurement would be sufficient.

The theoretical examination of customer expectation as a comparisonstandard

canbe considered from two perspectives: narrow andbroad.Thenarrow perspec-

tive views customer expectation as a belief in future performance of a product.

The broad perspective proposes that the expectation is multidimensional and

associated with different levels of performance. In this respect, Millers (1977)

definition is notable.Miller (1977) classified expectations into the following categories: ideal,

expected, minimum tolerable, and deserved.The ideal is thewished-for level and

reflects what the respondent feels the performance of the product or service can

be. The expectedis based on the respondents objective calculation of what the

performance will be. This is also known as predictive expectation. The minimum

tolerable is the least acceptable performance level. This is better than nothing

and reflects what the minimum level of perceived performance must be. The

deservedlevel can be determined by a consumers evaluation of the rewards and

costs involved in the relationship. Hence, this indicates what respondents, in the

light of investments, feel that the performance ought to be or should be (p. 76).

The types of expectation are hierarchical, with desired expectation at the top and

minimum tolerable at the bottom. The position of the expected service and

deserved service may change according to situational and personal factors.

The SERVQUAL research team defines desired service as the level of service

that customers hope to receive. This is a mixture of what customers believe the

level of performance can be and should be (Zeithaml, Berry, & Parasuraman,

1993).They also claim that this level of service performance associates with good

quality. The adequate service expectation is defined as the lower level of perfor-

Yoon, Ekinci / EXAMINATION OF SERVQUAL DIMENSIONS 5



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mance that consumerswill accept. Zeithaml et al. (1993,p. 6) noted that this level

of expectation is comparable to Millers minimum-tolerable expectation. This isknown aspredictive expectationand is associated withcustomer satisfaction. The

area between desired service and adequate service is called the zone of tolerance

(ZOT) and represents the level of service performance that customers would

tolerate.

However, according to Zeithaml et al.s (1993) study, the concept of desired

service is mixed with the ideal service and deserved service presented by Miller

(1977). They also argued that the definition of adequate service is comparable to

Millers minimum-tolerable level. But Miller highlighted that such a service per-

formance merely means better than nothing. He noted that at that level of ser-

vice performance,

the consumer experiences dissatisfaction. He may attempt to remedy the situa-

tionand probably wont purchase thatbrand(continue patronizing that store)but will switch to another. If no alternative is available, then he will probably

continue to use the product as long as it satisfies or fills a need. (p. 79)

Based on the above statement, performing just higher than the minimum-

tolerable level does not ensure satisfaction, as Zeithaml et al. (1993) proposed.

More importantly, consumers would not tolerate services that were equivalent to

their minimum-tolerableexpectation. Taking intoaccount Millers (1977) defini-

tion, consumerswill tolerateservice performance if it is equal to thedeserved-ser-

vice level. Therefore, a ZOT mayonly occur when theservice performance is be-

tween predicted (expected) and deserved expectations. Furthermore, the bottom

line for satisfaction is when the perceived service performance is equal to the de-

served expectation.

The negative empirical findings concerning the measurement of expectationshave led to some doubt about its value. Some scholars maintain that customer

expectation does not provide additional information for estimating service qual-

ity, and they further argue that a performance-only measurement already takes

into account much of this information (Babakus & Boller, 1992; Cronin& Taylor,

1992). Previous studies have suggested that a performance-only measurement

would be sufficient. However, it has been acknowledged that such an approach

would limit the explanatory power of service quality measurement (Parasuraman

et al., 1994) because assessment of desired anddeservedexpectationmay bevalu-

able indeterminingandmonitoring thelevel ofservice quality andcustomersatis-

faction. Also, this information might be used as an internal benchmark (or a stan-

dard) to enhance the existing level of service quality in the future. In addition,

attempts to explain the difference between service quality and customer satisfac-

tion, as recommended by Zeithaml et al.s (1993) model, appear to be unsuccess-ful due to the fact that the two concepts are always highly correlated.

To determinewhethercustomerexpectationshould be usedin theevaluationof

services, the Guttman scaling procedure is employed. The following section

introduces the principles behind the method and rationale for this approach.




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METHOD

Rationale for Using the Guttman Scaling Procedure

The Guttmanscaling procedure is consideredan appropriate method(Guttman,

1950, as cited in McIver & Carmines, 1981) to assessunidimensionality, which is

also seen as an essential part of construct validity (Ekinci & Riley, 1999; Hattie,

1985). In line with the reasoning of Gerbing and Anderson (1988), it is accepted

that exploratory factor analysis is not suitable for confirming unidimensionality.

Essentially, factoranalysis is based on linearcorrelationandis thereforea form of

probability modeling. The main assumption is that if there is a linear relationship

between the scale items, it is considered to be unidimensional. However, Hattie

(1985) argued that a linear relationship, in some cases, indicates homogeneity

rather than unidimensionality. Guttman scaling is a deterministic form of model-

ingthatprovidestwounique parameters to establishunidimensionality in contrast

to probability modeling. A scale has to be ordinal and cumulative. The rationalefor using the Guttman procedure is based on our assumption of discrete dimen-

sionsand theunique abilityof establishingunidimensionalityvia itsparameters.

Because the Guttman scaling procedure requires an ordinal (hierarchical) and

cumulative structure in a scale, unidimensionality of a scale is established by

checking the response patterns in the data (Guttman, 1944; McIver & Carmines,

1981; Oppenheim, 1966). For example, salt, rock, and diamond can be ordered

according to degree of hardness. Furthermore, the cumulative structure of the

scale can be checked on the basis of these response patterns and a predetermined

criterion, which in this example ishardness.Table1 andTable2 illustrate thelogic

of the Guttman scaling procedure. Table 1 shows a typical data matrix consisting

of 5 respondents, and Table2 shows a perfect scale matrix for a 3-item scale and 5

respondents.

On a purely unidimensional scale, if a person accepts that rock is hard, then he

or shemust accept that diamond is hard too. Alternatively, if a personaccepts that

salt is hard, he or she should accept that rock is hard too, as seen in Table 2.

According to the hypothetical data presented in Table 1, the first person would

achieve a score of 3. This means that he or she accepted the hardness of all three

materials. The third person, who achieved a score of 2, agreed that rock and dia-

mond were hard but not salt. This response pattern also matched the perfect scale

pattern in Table 2.

Because perfect scales rarely occur in real-life situations, the cumulative prop-

erty of the scales is checked and errors are counted using the perfect scale matrix.

For example, Respondent 5 inTable1 agrees that salt is hard but thinks rock is not

hard and then agrees again that diamond is hard (1, 0, 1 = 2). As a result, this

respondent achieves a score of 2. If this pattern is compared with the pattern intheperfectscale matrix(1, 1, 0 = 2),two errorsare seen tooccur. Guttman(1950,

as cited in McIver & Carmines, 1981) suggested that the coefficient of

reproducibility (CR) shouldbe used to assess thenumber of errors and thedegree

of scalability in such cases. Also, the CR score must be .90 or higher to claim that




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the dimension is scaleable or the scale is unidimensional. This indicates that the

scale contains a maximum of 10%error. Theformula formeasuring CR is thefol-

lowing (Guttman, 1950, as cited in McIver & Carmines, 1981):

CR = 1 Total Error/Total Responses

CR = 1 Total Error/(Items Respondents).

Edwards (1957) argued that scales with extreme items tend to spuriously

inflateCR scores; therefore, minimum marginalreproducibility (MMR)statistics

should be taken into consideration. MMR can be computed as follows:

MMR = (Total Responses Marginal Errors)/Total Responses

CR MMR = (Marginal Errors Scale Errors)/Total Responses.

Thedifference between CR andMMRshows thepotential for improvement of

unidimensionality (Edwards, 1957). Because there is no definitive interpretation

of thedifferencebetweenCR andMMR, various alternativeshavebeensuggested(McIver & Carmines, 1981). As a rule of thumb, MMR should not be excessively

high or close to CR. Menzel (1953, as cited in McIver & Carmines, 1981) offered

another statistic, the coefficient of scalability (CS), to check whether the scale

consists of balanced positive and negative responses. This measure indicates

whether the scale has potential for improvementof itsunidimensionality. Accord-


Table 1

A Data Matrix (n= 5)

Diamond Rock Salt Total Score

1 1 1 3

1 1 1 3

1 1 0 2

1 1 0 2

1 0 1 2

Note: 1 = agree; 0 = disagree.

Table 2

A Perfect Scale Matrix

Diamond Rock Salt Total Score

1 1 1 3

1 1 0 2

1 0 0 1

0 0 0 0

Note: 1 = agree; 0 = disagree.



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ing to Dunn-Rankin (1983, p. 106), CS should be greater than +.60 if a scale con-

sists of balanced positive and negative items.The Guttman scaling procedure proposes that the cumulative structure of the

scale should display a weak monotonic relationship between them. Hence, if a

scale successfully qualifies through the above procedure, a further test is

required toexamine theweakmonotonicrelationship.To checkthis, Yules Q cor-

relation is recommended for measurement scales that use a dichotomous rating

scale (Koslowsky, Pratt, & Wintrob, 1976, as cited in Ekinci & Riley, 1999).

Ekinciand Riley (1999)argued that theGuttman scaling procedurecanbe per-

formedusingtwo differentmethods. In thefirst method, thecontent of theitemsis

used to establish a hierarchical and cumulative scale. In the second method, the

hierarchical and cumulative structure of the scale is investigated in the data. The

principles of the Guttman scaling procedure are then employed to check

unidimensionality of the scale. Thus, the former method employs a ready-made

ordinal and cumulative scale before collecting data. Then, the cumulative struc-ture of the scale is examined according to the response patterns in the data. If a

construct is already scaledandclaimed to be valid, the lattermethod is more prac-

tical and seeks an ordinal and cumulative structure in the data (Edwards, 1957,

p. 184). In both cases, the purpose of the study is the same; that is, to assess

whether the scale is unidimensional.

The present study employed both methods. In the first method, a Guttman

Scale based on the items content, using different types of expectation, was uti-

lized. In doing so, four types of expectation were used to construct an ordinal and

cumulative scale. In the second method, each of the SERVQUAL Scales was

assumed to be unidimensional. Hence, the ordinal structure of the scales was

investigated by analyzing the scale items frequencies. The cumulative structure

of the scale was then examined using the error-counting procedure.

Questionnaire Development

The survey questionnaire consistedof five parts. The first part included demo-

graphic questions regarding respondents gender, age group, purpose of travel,

duration of visit,grading of thehotels they visited, and their location. Thesecond

part concerned themeasurement of service quality and therefore included the22-

itemSERVQUALScale (Parasuraman,Zeithaml,& Berry, 1991). A dichotomous

rating scale with two responses, agree and disagree, as opposed to a 7-point

Likert-type scale was used in accordance with the Guttman scaling procedure

(Guttman, 1944). The scale items were randomly distributed to avoid order bias

(see the appendix), and in line with previous studies, a performance-only mea-

surement was considered appropriate (Boulding et al., 1993; Cronin & Taylor,

1992).The third part of the questionnaire concerned the measurement of expectation

and included four statements relating to the four types of expectation: desired,

anticipated, deserved,and minimum tolerable. The scalestatements wereworded

as follows: (a) The level of service I received at this hotel was lower than I

desired, (b) The level of service at this hotel was lower than I anticipated, (c)

The level of service at this hotel waslowerthan I deserved, and(d)The level of




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service at this hotel was less than adequate. Definitions of desired (ideal), antici-

pated (expected), deserved, and adequate (minimum-tolerable) expectation wereadopted from other studies (Miller, 1977; Parasuraman et al., 1994), and they

accompanied thescale.Again, the items were randomly distributed to avoidorder

bias.

To measure the validity of the SERVQUAL Scale, the fourth part of the ques-

tionnaire pertains to the measurement of overall service quality, customer satis-

faction, and intention to recommend and/or return to the hotel. The questions

themselves were taken from Cronin and Taylors (1992) study. Overall service

quality was measured on a 5-point, bipolar numeric scale ranging from 1 (poor

quality) to 5 (excellent quality). Overall satisfaction with services was measured

on a 5-point, bipolar numeric scale. The verbal points of the scale ranged from 1

(completely dissatisfied) to 5 (completely satisfied). The respondents behavioral

intentions (torecommendand/or return) were also measured on a 5-point, bipolar

numeric scale ranging from 1 (extremely unlikely) to 5 (extremely likely).The final part of the questionnaire included questions relating to respondent

demographics. Before application, the questionnaire was tested by a group of

British people (N= 10) who stayed in hotels. The purpose of this test was to see

whether there was any difficulty comprehending the questions. As a result, some

of the expectation scale items and their definitions were edited.

The Sample

The field survey was conducted in Seoul, Korea, during the summer of 2000.

The English-language survey was conducted on the spot at Kimpo Airport. The

survey population consisted of international travelers who stayed in hotels. In

total, 110 questionnaires were randomly distributed. Of these, 102 usable ques-

tionnaires were collected. The sample size was sufficient, according to Guttman

(1950,ascited inMcIver & Carmines,1981). Table 3 shows theprofileof thetrav-

elers who participated in the survey.

As shown in Table 3, 69% of the participants were male and 31% were female.

A high proportion of the sample (55%) were U.S. citizens, and the majority of the

travelers (62%)stayedin five-star hotels. Accordingto Table 3, 63%of thesample

traveled for business purposes, and most of the visitors (89%) stayed in hotels

located in the citys center.

RESULTS

Findings Using the SERVQUAL Scale

To assess the unidimensionality of the SERVQUAL scales, the positive fre-

quency scores were used to establish a hierarchical structure between the scale

items. Table 4 shows the hierarchical order of the four tangibles items. The item

frequency scores suggest that Item 6 (neat appearance of hotel employees) is the

most favorable and Item 12 (modern-looking hotel equipment) is the least favor-

able one in the scale.




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Table 3

Sample Demographics

Variable Percentage

Gender

Male 69

Female 31

Age group

16-24 6

25-35 43

35-44 30

45 and older 21

Nationality

American 55

British 12

Canadian 11

Australian 3

New Zealander 1

Others 18

Purpose of travel

Business 63

Leisure 20

Business and leisure 10

Other 7

Length of stay (in days)

1 6

2 8

3 26

4-6 35

7-14 5

> 14 20

Classification of hotels

1 star 12 star 3

3 star 9

4 star 15

5 star 62

Not known 10

Location of hotels

City center 89

City suburb 3

Coastal resort 6

Mountain resort 1

Countryside 1

Table 4

The Hierarchical Order of the Tangibles Scale Items

Question 6 Question 13 Question 5 Question 12

Number of agreed responses 87 81 79 78

Number of disagreed responses 7 13 15 16

Hierarchical order of items 1 2 3 4



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According to the Guttman scaling procedure (as cited in McIver & Carmines,1981),the scalemust becumulative. Inresponse to this, if a respondent agreesthat

a hotel has modern-looking equipment (Item 12), he or she must agree that the

hotel facilities are visually appealing (Item 5), the hotel employees are neat in

appearance (Item 6), and the materials associated with the service are visually

appealing (Item 13). Alternatively, if a respondent disagrees with Item 12 but

agrees with Item 5, then he or she is expected to agree with the rest of the scale

items to achieve a perfect cumulative pattern. If a participant response pattern

does not match with this profile, then errors are present.

As mentioned earlier, Guttman (1950, as cited in McIver & Carmines, 1981)

set a standard10%for the maximum number of tolerable errors in a scale.

This means that the minimum value of the CR statistic should be .90to determine

whether a dimension is scalable. Table 5 shows the CR, MMR, and CS scores for

the five SERVQUAL scales.

In response to the above recommendations, 2 of the SERVQUAL items (Item

2: The hotel had your best interests at heart and Item 9: When you had a prob-

lem, the hotel showed a sincere interest in solving it) should be deleted from the

scale. This process would reduce the total number of SERVQUAL scale items to

20. According to the obtained CR values, all of the SERVQUAL scales achieved

theminimum standard of unidimensionality (CR > .90) at this stage. However, as

can be seen from the MMR and CR scores, the four scales, except empathy, con-

sisted of extreme items (i.e., CS < +.60), and thus the obtained CR scores seemed

to have been spuriously inflated (Edwards, 1957). These results clearly threaten

the unidimensionality of the SERVQUAL scales.

Thenext stage of theanalysis involves testing of theweak monotonicrelation-

ship between the scale items. Hence, Yules Q correlation coefficient was used tocheck whether the relationship between the scale items was weakly monotonical

and statistically significant. Table 6 shows the findings of the correlation test

between the scale items.

As can be seen from the Yules Q correlation coefficients, the relationships

between theassurancescale items were notstatistically significant; therefore, the

whole scale shouldbe deleted. Furthermore,empathy 11 and18 andreliability 14


Table 5

Findings Using the SERVQUAL Scales: CR, MMR, and CS Scores

Number of Number of Number of

Scales Scale Items Itemsa

Errors CR MMR CS

Tangibles 4 4 30 .92 .86 .41

Responsiveness 4 4 28 .92 .90 .41

Assurance 4 4 20 .94 .90 .41

Reliability 5 4 18 .94 .91 .45

Empathy 5 4 32 .91 .77 .59

Total scale items 22 20

Note:CR= coefficient of reproducibility;MMR= minimum marginal reproducibility;CS = coef-

ficient of scalability.

a. Scale items are patterned after the Guttman scaling procedure.



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Table 6

Yules QCorrelation Among the SERVQUAL Scale Items

Scale Correlation Among the Scale Items

Tangibles Tangibles 5 Tangibles 6 Tangibles 12

5 1

6 .91*** 1

12 .84**** .90*** 1

13 .89**** .71 .60**

Responsiveness Responsiveness 1 Responsiveness 15 Responsiveness 17

1 1

15 .71** 1

17 .84**** .87*** 1

21 .81**** .89**** .78****

Reliability Reliabilty 3 Reliability 7 Reliability 103 1

7 .90*** 1

10 .98**** .93*** 1

14 .69 1.00*** .53

Assurance Assurance 4 Assurance 8 Assurance 16

4 1

8 .80 1

16 .60 .57 1

19 1.00 .67 .86

Empathy Empathy 11 Empathy 18 Empathy 20

11 1

18 .27 1

20 .65*** .94**** 1

22 .60** .96**** .89****

**p< .05. ***p< .01. ****p< .001.13

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seemed to produce insufficient scores to support the notion of a weak monotonic

relationship between the other scale items. Although they shouldbe deleted, theywere retained and transferred to thenext stage to seewhether they would perform

well in the following validity tests.

Validity of the SERVQUAL Scale

To establishthe validityof a scale, twotypesof validityare essential: construct

validity and criterion validity. Construct validity is how well the result obtained

from the use of the measure fits the theories around which the test is designed

(Sekaran, 2000, p. 208), and this can be investigated through convergent and

discriminant validity.

According to Hattie (1985), unidimensionality means verifying the existence

of a single dimension by a set of observations, which would be considered evi-

dence for the convergent validity of a scale. In this study, convergent validity of

the SERVQUAL scales has already been investigated using the Guttman scaling

procedure. Results of the follow-up test statistics (CS and MMR) suggested that

theconvergentvalidity of the fourSERVQUALscales, except empathy, waspoor.

Discriminant validity of a scale is established if the factors and their items are

independent of each other (Sekaran, 2000). To assess the discriminant validity of

the four SERVQUAL scales, the relationships between the scales were investi-

gated by a linearcorrelationtest.Beforedoingthis, respondentstotal scoreswere

computed foreach scaleby summing their ratings on thescale items.As a result, a

total score on the scale was obtained for each person. For instance, if a respon-

dents rating for a 4-item scale was 1, 1, 1, and 0, then his or her total scale score

would be 3 for this scale. Table 7 shows the Spearmans correlation coefficients

pertaining to the four scales.

From the above correlation coefficients, the relationship between reliability

and responsiveness, as wellas between responsiveness andempathy, wasfoundto

be moderate as opposed to being weak. However, the tangiblesscale seemedto be

the only one that displayed relatively low correlation with respect to the other

scales, andthis supportedthe fact that thediscriminant validityof this scale is rea-

sonably good.

Relationships between the measurement scale and other theoretically related

variables should be investigated to establish criterion validity. This can be rein-

forced by concurrent validity and predictive validity. The relationship between

customers overall service quality rating and the four SERVQUAL scales was

examined to assess concurrent validity, and the relationship between customers

intention to recommend and the four SERVQUAL scales was examined to assess

predictive validity. To do this, a logistic regression procedure was employed to

check if the four SERVQUAL scales were successful in predicting customersoverall quality and intention to recommend behavior (Norusis, 1993, pp. 1-

30). Before conducting the analysis, the overall quality and intention to recom-

mend scaleswere mergedinto a dichotomous format(e.g.,values belowthemean

score were merged into 0 to indicate poor quality, and values equal to or higher

than the mean score were merged into 1 to indicate excellent quality), and these




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were used as dependent variables. Meanwhile, the four SERVQUAL scales were

regarded as independent variables.

The two logistic regression models based on this estimation were significant

according to chi-square and model improvement statistics (p > .000). The total

classification rate (88%) for overall service quality was reasonably good (46%for poor quality and 96% for excellent quality). However, the overall rate (71%)

for intention to recommend was poor (66% for not recommendingand80% for

recommending). Although the regression estimations between the SERVQUAL

scales and conceptually related variables fit, only the tangibles scale was statisti-

cally significant (p > .05) for predicting customer global service quality evalua-

tion (Waldstatistic= 9.62,R = .32,p > .05) and intention to recommend behavior

(Wald statistic = 4.76, R = .16, p > .05). Overall, these analyses indicate that the

criterion validity of the SERVQUAL scales is not strong.

Findings With the Expectation Scale

TheExpectationscalewasalsoanalyzedusing theGuttmanscaling procedure.

Hence, the same principles were applied to examine theunidimensionality of thisscale.Forexample, if a respondent agrees that the level of service quality is lower

than his or her predicted expectation, he or she should agree that the level of ser-

vice quality is lower than his or her desired expectation. Following this principle,

the first stage of error assessment yielded a satisfactory CR value (.96) for this

scale. Both the MMR (.78) and CS (.74) scores were compared with the obtained

CR value and were found to be sufficiently high. These results suggest that the

scale has passed the first criterion of unidimensionality.

The second stage of validating the expectation scale involved performing the

Yules Q correlation test to examine theweakmonotonicrelationship between the

scale items.Table 8 shows theYules Q correlation coefficientsamong the expec-

tation scale items.

As shown inTable 8, therelationships between theitems were quite robust, and

there was no need to eliminateanyitem from thescale (Yules Y> .70). This find-ingsupports thenotionthat customers rely on different types of expectationwhen

evaluating services.

To investigate the relationships between customer expectation, service quality,

and customer satisfaction, the Spearman correlation test was employed. Table 9

shows the correlation matrix involving the expectation, overall quality, and cus-

tomer satisfaction scales.


Table 7

Relationship Between the Four SERVQUAL Scales: Spearmans Rho Correlation

Scale Tangibles Reliability Responsiveness Empathy

Tangibles 1

Reliability .19 1

Responsiveness .31*** .48*** 1

Empathy .39*** .33*** .58*** 1

***Significant at the .01 level.



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The results show that expectations are positively correlated with overall ser-

vice quality and customer satisfaction. The correlation coefficient between the

expectation and customer satisfaction scales was higher than the coefficient

between expectation and overall service quality scales. Separate analyses also

revealed that the relationships between the expectation scale and the four

SERVQUAL scales were either weak or insignificant (all rvalues > .30, p > .05).

These findings show that the concept of expectation is a better indicator of cus-tomer satisfaction than service quality.

To investigate whether theconcept of service quality canbedistinguished from

customersatisfaction, using different types of expectation, an independent sam-

ples ttest was conducted. To do this, customers were classified into two groups

with respect to their expectationscores. Hence, Group 1 contained those custom-

erswho rated thelevel of service performanceequal toor higherthan their desired

expectations, andGroup2 included thosecustomerswho rated thelevel of service

performance lower than theirdesired expectations. The dependent variables were

measures of customer satisfaction and overall service quality. Table 10 shows the

findings of the independent samples ttest.

The results in Table 10 reveal that perceptions of service quality and customer

satisfaction are statistically different for the two groups of customers (p > .00).

This finding indicates that desired expectation is an antecedent of both servicequality and customer satisfaction. The descriptive statistics for the measurement

of customer satisfaction(M= 3.98, SD = 89)and overall service quality (M= 4.03,

SD = 89)show that customerswouldlike to receivea level of service close to their

desired expectations.


Table 8

Yules QCorrelation Between the Expectation Scale Items

Item 1 2 3 4

1. Lower than desired 1

2. Lower than anticipated .98*** 1

3. Lower than deserved .96*** .91*** 1

4. Less than adequate .94*** .95*** .74* 1

*p< .10. ***p


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However, asshownby themeanvalues of thetwosegments, evaluationsof cus-

tomer satisfaction and service quality are the same; therefore, these two con-

structs cannot be separated according to the level of desired expectation. In both

cases, customers would like services to be equal to or higher than their desired

levels. A ZOT mayoccur eitherbetween desired andpredictive expectations (ser-

vice quality [SQ] mean = 4.00, customer satisfaction [CS/D] mean = 3.67) or

between desired and minimum-tolerable expectations (SQ mean = 3.50, CS/D

mean = 3.35), as proposed by Zeithaml et al. (1993). Also, testing of this proposi-

tion was not possible due to the limited number of observations: For the former

group, the sample was 4; for the latter group, in which service performance was

lower than minimum tolerable, thesamplewas0. However, using theexpectationscale, three levels of service performance were identified that provide some

insight into this proposition: (a) levels of service equal to or higher than desired,

(b) levels of service lower than anticipated but equal to or higher than deserved,

and (c) levels of service lower than deserved but equal to or higher than minimum

tolerable. Table 11 shows the means of customer satisfaction and service quality

evaluation with respect to these segments.

The mean scores of the customer satisfaction and service quality scales indi-

cate that customer evaluations of both constructs are either the same or similar in

the three segments. Therefore, it maybe argued that these two concepts cannot be

separated according to the different types of expectation. As shown in Table 11,

the service performance level that is equal to or higher than the minimum-tolera-

ble expectation (mean = 2.71) is rather low and does not ensure satisfaction or

superior service quality, as opposed to Zeithaml et al.s (1993) proposition. Theresultof this analysis suggests that theminimum thresholdforservice quality and

satisfaction occurs when the level of service performance is equal to the cus-

tomers deserved expectation (overall service quality mean = 3.79, CS mean =

3.57), and this is similar to what was originally proposed by Miller.


Table 10

Evaluation of Service Quality and Customer

Satisfaction in Terms of Desired Expectation

Independent Samples t-Test Statistics

Group n M SD t Value Significance

Overall service quality

Equal to or higher

than desired 61 4.25 .72

Lower than desired 26 3.50 .95 4.00 .000

Customer satisfaction

Equal to or higher

than desired 61 4.25 .70

Lower than desired 26 3.35 .94 4.95 .000



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Table 11

Three Perceived Service Performance Levels According to Different Types of Expectation

Lower Than Anticipated but Low

Equal to or Higher Than Equal to or Higher Than Eq

Desired Expectation Deserved Expectation Minimu

Scale M SD M SD

Overall service quality 4.25 .72 3.79 .80 2Customer satisfaction 4.25 .70 3.57 .76 2

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DISCUSSION AND CONCLUSION

The objective of this research was to examine the generic nature of the

SERVQUAL Scale dimensions in hotels by employing an alternative scaling

methodknownas theGuttmanscaling procedure. Of thefive SERVQUAL dimen-

sions tested, four were qualified in terms of unidimensionality in the first test.

These were tangibles, reliability, responsiveness, and empathy. However, the fol-

low-up tests suggestedunidimensionality of the three scales, except for empathy,

which was poor. These findings support Carmans (1990) proposition that the

ideal number and type of service quality dimensions may be different depending

on the type of service industry and service being evaluated. In addition, it should

be noted that failure to detect a dimension (e.g., assurance) in a given research

context does not mean that the dimension does not exist but that it is simply not

valid. It could be validin other service categories andthereforeused by customers

for the evaluation of quality (Ekinci, 2001).The correlation analysis among the four SERVQUAL scales reveals that there

is a high degree of interrelation between them. This finding indicatesthat both the

discriminant andcriterion validityof thescales (except tangibles) arepoor. This is

in line with Babakus and Bollers (1992) study and supports the notion that some

of the SERVQUAL Scale dimensions should be treated as one or two, rather than

five. The major implication of this study is that the validity of the SERVQUAL

Scale must be checked whenever it is applied to a different service setting. This

process may be more fruitful as it may reveal a successful modification in the

scale that enables more valid conclusions to be drawn.

The second objective of this study was to determine the role of customers

expectations in theevaluation of service quality in hotels. TheCR, MMR, andCS

scores of the expectation scale (.95, .78, and .74, respectively) provided strong

evidence that the evaluation of services could be scaled according to differenttypes of expectationdesired, anticipated, deserved, and adequate. In other

words, customers use four types of expectation as a comparison standard. This

finding supports Millers (1977) theory that expectation is an antecedent of cus-

tomer satisfaction. Zeithaml et al.s (1993) proposition regarding the use of

desired expectation as a comparison standard was partly supported by this study.

However, the result of this study indicates that different types of expectation can-

not clearly distinguish between the concept of customer satisfaction and service

quality.

In the present study, although the expectation scale was strongly correlated

with both service quality and customer satisfaction, the magnitude of correlation

with customer satisfaction was stronger (r= .51) than with service quality (r=

.43). This suggests that the concept of expectation may be more appropriate for

measuring customer satisfaction than service quality, as originally suggested byMiller (1977). It can also be argued that customer satisfaction is related more to

customersself-image and therefore involves theuseof expectationas a compari-

son standard for the satisfaction decision (Ekinci & Riley, in press).

This study provides some insight concerning the SERVQUAL model, in par-

ticular the gap-orientedmeasurement of service quality in whichcustomerexpec-




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tation and perceived performance are used together. According to this study,

although expectation is employed for the evaluation of service quality, both cus-tomer satisfaction and expectation should be taken into account. However, this

may be best practiced by keeping the expectation and performance scores sepa-

rate ratherthan subtracting the latter from theformer to determine the levelof ser-

vice quality or customer satisfaction. By thesame token, theexpectationmeasure

provides additional information; therefore, customer expectation should be seen

as one of the antecedents of customer satisfaction or service quality.

One of theconclusions of this study is that researchers shouldassess thevalid-

ity and reliability of the SERVQUAL Scale before drawing any conclusions.

Another implication is that managers must keep the service level higher than the

customersdeserved expectations to avoid dissatisfaction. Similarly, service per-

formance shouldbe close toor higherthan thedesiredexpectationto improveper-

ceived quality or customer satisfaction. The study indicates that the use of an

expectation scalealongwith themeasuresof overallsatisfactionand servicequal-ity would provide a better diagnostic capability in assessing service quality and

customer satisfaction. Such a practice would provide more valid information and

improve managersdecision making for developing service strategies. The study

also demonstrates that service quality can be measured using an alternative scal-

ing methodology (the Guttman scaling procedure) that involves a categorical rat-

ing scale different from the most commonly used ones (e.g., the Likert-type

scales).

This research has certain limitations; thus, the interpretation of its findings

needs tobeapproached with caution. First,the studysampleis smallandis limited

toa relatively specific group of travelers whostayedin Korean hotels. Second, the

structure of the sample seems to be biased toward a certain group of variables

(e.g.,males, business travelers, and five-star hotels). Therefore, the results cannot

be generalized to the whole population. Finally, measurements of overall servicequality andcustomer satisfactionwere carried outusinga single-item scale,andit

was not possible to estimate their reliability.

There area numberof areas that futureresearch shouldaddress. First, a further

study containing a larger sample size could investigate the generic nature of the

SERVQUAL dimensions in other hotel samples. Second, because this study pro-

duced a different version of the SERVQUAL Scale using a dichotomous rating

scale, it would be interesting to check the validity of its findings with a further

study. Third, testing of theexpectationscale using different samples would better

establish its external validity. Finally, it would be productive to test thevalidityof

the concept of ZOT and the role of expectation in the evaluation of services

against other comparison standards.




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APPENDIX

The SERVQUAL Scale

Item Scale/

Number Dimension

Tangibles

5 The hotel facilities were visually appealing.

6 The hotel employees were neat in appearance.

12 The hotel had modern-looking equipment.

13 Materials associatedwith theservice (e.g., service menu, cutlery, furniture,

etc.) were visually appealing at the hotel.

Reliability

3 The hotel provided its services at the t ime it promised to do so.

7 When the hotel promised to do something by a certain time, it did so.9 When you had a problem, the hotel showed a sincere interest in solving it.

10 The hotel performed the service at the right time.

14 The hotel paperwork was accurate.

Responsiveness

1 Employees of the hotel were never too busy to respond to your requests.

15 Employees of the hotel gave you prompt service.

17 Employees of the hotel were always will ing to help you.

21 Employees of the hotel told you exactly when services were available.

Assurance

4 You felt safe in your transactions with the hotel.

8 Employees of the hotel had the knowledge to answer your questions.

16 The behavior of employees of the hotel instilled confidence in customers.

19 Employees of the hotel were consistently courteous with you.

Empathy

2 The hotel had your best interests at heart.

11 The hotel had operating hours convenient to all of its customers.

18 The hotel had employees who gave you personal attention.

20 The hotel gave you individual attention.

22 Employees of the hotel understood your specific needs.

Note: The items random number appeared on the survey questionnaire.



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1-12.

Submitted January 2, 2001

First Revision Submitted July 3, 2001

Second Revision Submitted January 28, 2002

Final Revision Submitted February 7, 2002

Accepted February 9, 2002

Refereed Anonymously

Tae-Hwan Yoon (e-mail: [email protected]) is a researcher in the School of

Management Studies for the Service Sector at the University of Surrey, United Kingdom.

Yuksel Ekinci, Ph.D. (e-mail: [email protected]), is a lecturer in hospitality

management at theSchool of Management Studies forthe Service Sector at theUniversity

of Surrey, United Kingdom.


Documents

An Examination of the SERVQUAL Dimensions Using the GUTTMAN Svaling Procedure