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Measuring tourist judgment on service quality
Pergamon www.elsevier.com/locate/atoures
Annals of Tourism Research, Vol. 26, No. 4, pp. 1004±1021, 1999 # 1999 Elsevier Science Ltd. All rights reserved Printed in Great Britain 0160-7383/99/$20.00+0.00
PII: S0160-7383(99)00037-7
MEASURING TOURIST JUDGMENT ON SERVICE QUALITY Klaus Weiermair Matthias Fuchs University of Innsbruck, Austria Abstract: This study measures tourist judgments on service quality in alpine ski resorts. An attribute based method was employed in order to estimate weighting schemes both for quality judgments across different tourism activity domains and different quality dimensions within winter resorts and to quantify an overall quality measure. A linear regression and Sirgy's congruity model of customer satisfaction/dissatisfaction were adopted. The results indicate that there exists a linear relationship between the overall quality measure and the partial judgments of each domain/dimension. This allows deciphering the relevance of different domains of tourism activity and quality dimensions within the process of making quality judgments. Keywords: tourist judgments, winter resort, attribute based quality measure. # 1999 Elsevier Science Ltd. All rights reserved. Âsume Â: L'eÂvaluation des jugements de qualite de service par des touristes. Cette Âetude Re mesure les jugements de qualite de service faits par des touristes aux stations de ski alpin. On a utilise une meÂthode baseÂe sur des attributs qualitatifs pour Âevaluer des scheÂmas de coef®cients pour des jugements qualitatifs de divers domaines d'activite touristique et diverses dimensions qualitatives aux stations d'hiver, et pour quanti®er un mesurage de qualite geÂneÂrale. On a adopte une reÂgression lineÂaire et le modeÁle de congruite de Sirgy de la satisfaction/insatisfaction des clients. Les reÂsultats indiquent qu'il existe une relation lineÂaire entre l'eÂvaluation de qualite geÂneÂrale et les jugements partiels de chaque domain ou dimension. Ceci permer de deÂchiffrer l'inteÂreÃt des divers domaines d'activite touristique et Â. # 1999 Elsevier Science les dimensions qualitatives du processus des jugements de qualite Ltd. All rights reserved.
INTRODUCTION After decades of rapid growth in tourism, Austria and its neighboring regions in Germany, Switzerland and Upper Italy have over the past three years experienced sustained declines in the number of tourists visiting their destinations. While the alpine Central European regions may be a special case, all of Europe has experienced a decline in its world market share from 66% to 59% (Eurostat 1995). This has rekindled the public debate over the poss-
Klaus Weiermair is Professor and Head of the Institute of Tourism and Service Economics, University of Innsbruck (UniversitaÈtsstrasse 15, 6020-Innsbruck, Austria. Email: < [email protected] >). He has research experience in change management, human resource and organization development, competitive analysis, and consumer behavior within the hospitality and tourism context. Matthias Fuchs is Assistant Professor at the same Institute < [email protected] >. His research interests include labor market and human-resource economics, cultural tourism, and tourist satisfaction analysis.
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ible causes of this decline with price and price related factors (such as exchange rates) and quality being the major explanatory factors. Contrary to the past when price and income explanations have dominated (Keane 1997; Schulmeister 1975; Smeral 1994; Witt and Witt 1995) quality or value for money are now moving as possible explanations to the forefront (Mazanec 1996). As for the traditional activities of alpine tourism such as hiking and skiing and traditional quality attributes such as accessibility and friendliness, they no longer seem to suf®ce to attract a large number of tourists to areas such as Switzerland, or the alpine parts of Austria and Northern Italy, as can be evidenced by the declining number of overnight stays over the past years. A number of researchers have in this context written about changing attitudes and behavior of tourists and their service quality expectations (Opaschowski 1996; Poon 1993; Ryan 1995; Weiermair 1994). If their hypotheses are correct, one should be able to observe, even among those who have already made destination choices, possible service quality de®cits with respect to such new quality attributes as animation and fun or freedom of choice. Survey research will be presented which has been carried out in 11 winter sport resorts in Austria and Northern Italy involving a sample of 1,822 tourists vacationing during various periods in those resorts in the winter season of 1994±95. The survey aimed at obtaining correct quality measures for service quality broadly de®ned in seven domains of tourism activity: food and accommodation, sports activities (other than skiing), animation and culture, transportation aspects to and within resorts, skiing and related activities, enjoyment with nature and landscape, and shopping activities (Table 1). The design of quality attributes and associated quality measures of alpine tourism has been heavily in¯uenced by a rich and growing literature on the construction and use of quality attribute measures in services (Brown, Gummeson, Edvardsson and Gustavsson 1991; Chase and Bowen 1991; Fick and Ritchie 1991; Parasuraman, Zeithaml and Berry 1985). The ®nal choice of quality attributes and related questions had to be tempered with the chosen mix of the seven tourism activities. These seven attributes emerged as the most valid dimensions of service quality to be used for alpine winter Table 1. Domains of Tourism Activity Number 1. 2. 3. 4. 5. 6. 7.
Domain of Tourism Activity Food and Accommodation Sports activities (other than skiing) Animation and Culture Transportation Aspects to and within Resort Skiing and Related Activities Enjoyment with Nature and Landscape (e.g., hiking) Shopping Activities
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MEASURING TOURIST JUDGMENT ON SERVICE QUALITY Table 2. Quality Dimensions
Number 1. 2. 3. 4. 5. 6. 7.
Quality Dimensiona Aesthetics/Appearance Security/Safety Freedom of Choice (with respect to choosing activities) Authenticity/Honesty Service Orientation in terms of Punctuality and Reliability Variety/Fun Accessibility of Services
a
In order to obtain consistency and validity with respect to these seven dimensions, the wording had to be varied across different activity categoriesÐfor example, honesty with services corresponds to authenticity with nature, etc.
destinations (Table 2). Pretests were undertaken both with respect to a set of quality attributes originally derived from Parasuraman, Zeithaml and Berry (1985:47) and with the different wording of questions addressing these quality dimensions. The pretests involved tourists, tourism operators, and tourism of®cials. TOURIST JUDGMENTS ON SERVICE QUALITY Some authors have suggested that attribute importance can be used as a proxy for measuring expectations (Dall' Aglio 1996; Kohli 1988:124; Toy, Rager and Guadagnolo 1989). Hence, as a methodological starting point, the SERVQUAL model, which measures the gap between expectations and perceptions of the service by the consumer, as an indicator of service quality, was employed (Parasuraman, Zeithaml and Berry 1993; Zeithaml 1988). The quality observations in the study reported here were scored with a ®ve-point Likert scale. Each questionnaire contained sociodemographic and other background information on the tourist in addition to its partial and ®nal assessments concerning the seven quality dimensions found in each of the domains of activity: tourists were asked to indicate the importance of each attribute in each of the seven activities yielding 49 partial quality assessments. In addition they were also asked to assess the ®nal importance of each of the major activities and seven quality dimensions. Similarly they were requested to provide the same partial and ®nal quality assessments in terms of experienced satisfaction. Using different multivariate analyses the paper attempts to explain ®nal satisfaction and importance scores based on partial quality scores in each of the seven domains of tourism activity. Put differently, the exercise was to statistically estimate theoretically defensible weighting schemes for each of the single quality judgments across all activities, thereby explaining or interpreting tourists' ®nal quality assessments.
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On the Use of Quality Judgments of Tourists: Some Theoretical Issues Following a number of researchers, the service quality construct was arrived at by comparing a service quality level which the consumer expects to receive (``importance'' is used as proxy indicator) and the service quality level which he/she has experienced (``satisfaction'' is used as proxy indicator). According to the model, the higher the level of expectation relative to the perceived quality experience the lower the level of perceived quality and vice versa (GroÈnroos 1982; Parasuraman, Zeithaml and Berry 1985, 1988, 1991; Sasser, Olson and Wyckoff 1978; Zeithaml 1988; Heskett, Sasser and Hart 1990). The main theoretical and empirical issue of this paper rests with tourists' varied assessments of service quality but once a major holiday decision has been made and tourists ®nd themselves vacationing in a particular destination, one cannot entirely exclude prepurchase/preconsumption decision criteria and behavior. Expectations or importance ``standards'' are formed for the most part prior to the decision making process and thus have a bearing on the subsequently used SERVQUAL measurement tool for service quality. As has been pointed out in the literature, customers may have different expectation levels regarding quality attributes ranging from desired to adequate to equitable and/or best brand norms (Stauss and Seidel 1995) thereby in¯uencing the absolute measure of discrepancy between quality expectation and quality experience (i.e., perceived quality). Since the focus on this paper is not about tourism decision making or client segmentation according to some absolute measure of quality importance (or expectations) and since distance measures will furthermore be expressed as relative concepts, the SERVQUAL methodology should provide non-biased results. Likewise, one could argue that consumers cannot make quality assessments, particularly those associated with satisfaction, without regard to price and/or value which could be expressed as quality divided by all of the costs involved in acquiring this quality (Heskett, Sasser and Hart 1990:3). In this study tourists were asked to provide ex post quality assessments after a purchasing decision had already been made. Hence, price will likely play less of a role than in an ex ante decision making context. Furthermore tourists may make quality evaluations independent of price, and rather use price as a separate check on the appropriateness or adequacy of service performance (Mazanec 1996). The subsequent models use a particular weighting scheme and thus attempt to calculate a shadow price or implicit opportunity cost associated with quality assessments. Expectations regarding certain levels of quality can best be circumscribed and empirically assessed through scores of importance, while quality experience or perceived quality can be best recorded and measured as a satisfaction score for a particular attribute (Cadotte, Woodruff and Jenkins 1987; Doren and Mattsson 1996; Fick and Ritchie 1991; Hu and Ritchie 1993; Pizam, Neumann and Reichel 1978). While the
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method used here is attribute based, there is a controversial opposing method of viewing the tourism service experience as a series of encounters, emphasizing more the process and interactive character of service consumption (Chase 1992). The sample included and reported verbal critical positive and negative incidents at the end of the survey which supported the main measurements, but theoretical reasons also suggest that neither attribute nor process-based approaches will yield superior results (Lemmink and Kunst 1992). Thus, a modi®ed version of the SERVQUAL-model was retained to analyze partial and ®nal quality assessments of tourists in the Austrian and Northern Italian winter destinations. Underlying Model of Quality Measurement Tourists typically consume a choice of tourism services and evaluate their experience holistically in terms of ®nal judgments. In arriving at ®nal statements concerning particular quality dimensions or domains of activity they are likely to weight the ®nal judgment according to the importance (or expectation) attached to particular single quality or activity elements. Put differently and applied to the survey data, the ®nal quality judgment scores (such as food and accommodation) should not be the simple arithmetic mean of its consistent seven quality attribute scores. Similarly, the scores for aesthetic quality over the whole sample should not equal the arithmetic mean of aesthetic quality scores over all domains of tourism activity. In different steps one can now attempt to decipher the weights attached to quality judgments by tourists. Thus, the ®rst attempt involved the regression of the ®nal quality judgment scores (in terms of the difference, i.e., the gap, between importance and satisfaction scores) in the seven domains of tourism activity and the seven categories of quality dimension (explained variable) against the seven consistent quality judgments derived from the partial assessments in terms of importance minus satisfaction (independent variables). As to be expected for unweighted estimations, the results were poor: the R2s were on average not over 0.2, most of the z-standardized beta-coef®cients were statistically insigni®cant and some had the wrong (i.e., negative) sign. In a second step, the same ®nal quality judgment scores (explained variables) were regressed against weighted quality scores whereas the latter were derived as weighted quality scores in the various domains of tourism activity, weighted by the ®nal quality assessments concerning activity and quality dimensions. Weighted Partial Quality Judgmentij qij IPij IFi IFj ÿ SPij SFi SFj with i=1 to 7, the quality dimensions, and with j=1 to 7, the domains of tourism activity. The following variables having a ®vepoint Likert range:
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IPij partial assessment for importance SPij partial assessment for satisfaction IFi final assessment for importance relative to the quality dimensions IFj final assessment for importance relative to the domains of tourism activity SFi final assessment for satisfaction relative to the quality dimensions SFj final assessment for satisfaction relative to the domains of tourism activity Regression models of ®nal quality judgment measure (FQl) explained separately FQl b0 b1 q1j b2 q2j b3 q3j . . . b7 q7j e one regression for each domain of tourism activity ( j=1 to 7) and the seven (weighted) judgments of quality dimension as predictor variables FQl b0 b1 qi1 b2 qi2 b3 qi3 . . . b7 qi7 e one regression for each quality dimension (i=1 to 7) and the seven (weighted) judgments of domains of tourism activity as predictor variables with l=1 to14 and FQl=gap between ®nal-assessment pairs (i.e., IFiÿSFi, IFjÿSFj respectively), bk=regression coef®cients (k=0 to 7), and e=error term, the results were better. The R2s increase in most cases to above 0.6, the z-standardized-beta-coef®cients (Std. Coeff.) have now the correct sign and are also statistically signi®cant. Most weights behaved as expected, but some observations are worth separate reporting as they are in line with the quoted literature on changes in tourists' values and attitudes towards tourism products (Moore, Cushman and Simmons 1995; Oppermann 1995; Pearce 1982, 1996). For example, with regard to Food and Accommodation service orientation still dominates, but aesthetics/appearence and authenticity/honesty are becoming almost equally important (Table 3). In analogous fashion the standardized beta-coef®cients for the single judgments involving the seven categories of quality dimensions can similarly be interpreted, yielding the corresponding weighting results.
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Table 3. Regression Final Quality Judgment ``Food and Accommodation'' ([j] No. 1)
Summary Statistics Table: Count=656
R=0.779
Analysis of Variance Table: Source
d.f.
Regression Residual Total
Sum of Squares
Mean Square
F-test
307.160 198.150 505.310
43.880 0.305
143.498 P = 0.0000
Coef®cient (b)
Std. Coeff.
t-Value
0.030 0.007 0.016 0.028 0.038 0.011 0.008 ÿ0.066
0.234 0.049 0.121 0.221 0.245 0.104 0.060
6.664 1.585 3.522 7.184 7.699 3.510 1.980 ÿ2.772
7 648 655
Beta Coef®cient Table: Variable (q11). Aesthetic/Appearance (q21). Security/Safety (q31). Freedom of Choice (q41). Authenticity/Honesty (q51). Service Orientation (q61). Variety/Fun (q71). Accessibility of Services Constant
R2=0.607 Adjusted Durbin R2=0.603 Watson=2.021
Probability 0.0000 0.1135 0.0005 0.0000 0.0000 0.0005 0.0482 0.0057
Comparability of Regression Results The above regression equations explaining quality judgments in seven domains of tourism actitvity and seven quality dimensions cannot be compared and correctly interpreted with respect to their in¯uence upon the ``overall'' quality judgment of a particular destination (problem of ®nding correct relative weights). Therefore, in a next step all 49 partial quality judgments (qij) for each of the activities and quality elements were summed up, and were used subsequently to explain the overall quality judgment relative to a particular destination, where the summated scale represents a hypothetical construct consisting of the sum of all the ®nal quality judgments (FQl). Regression models of overall quality judgment measure (OQ): with OQ
14 7 7 X X X FQl IFi ÿ SFi IFj ÿ SFj l1
i1
j1
as equivalent to the sum of the seven gaps between ®nal assessments related to seven quality dimensions and those associated with the seven domains of tourism activity
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I. Regression model of 0 1 0 1 0 1 7 7 7 X X X OQ b0 b1 @ q1j A b2 @ q2j A b3 @ q3j A j1
j1
j1
0
1 7 X . . . b7 @ q7j A e j1
II. Regression model of OQ b0 b1
. . . b7
! ! ! 7 7 7 X X X q1i b2 q2i b3 q3i i1
7 X
i1
i1
! q7i e
i1
Table 4. I. Regression Overall Quality Judgment with Partial Quality Judgments (j)
Summary Statistics Table: Count=777 Analysis of Variance Table: Source Regression Residual Total
P7
j1 q1j :
P7
j1 q2j : P7 j1 q3j : P 7j1 q4j : P 7j1 q5j : P 7j1 q6j : P 7j1 q7j : Constant
d.f. 7 769 776
Beta Coef®cient Table: Variable
R=0.917 R2=0.842 Adjusted Durbin R2=0.841 Watson=1.915
Coef®cient (b)
Sum of Squares
Mean Square
35856.624 5122.374 6695.694 8.707 46224.906 Std. Coeff.
t-Value
F-test 588.304 P = 0.0000
Probability
Food and Accommodation
0.038
0.170
8.626
0.0000
Sport Activities
0.048
0.227
9.968
0.0000
Animation and Culture
0.017
0.061
2.857
0.0044
Transportation Aspects
0.022
0.109
5.938
0.0000
Skiing and Rel. Activities
0.029
0.138
7.045
0.0000
Nature and Landscape
0.040
0.151
7.520
0.0000
0.051 ÿ0.087
0.294
14.206 ÿ0.687
0.0000 0.4924
Shopping Aspects
MEASURING TOURIST JUDGMENT ON SERVICE QUALITY
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Table 5. II. Regression Overall Quality Judgment with Partial Quality Judgments (i)
Summary Statistics Table: Count=873
R=0.908 R2=0.826 Adjusted Durbin R2=0.824 Watson=2.055
Analysis of Variance Table: Source
d.f.
Regression Residual Total
7 865 872
Beta Coef®cient Table: Variable
P7
j1 q1j :
P7
j1 q2j : P 7j1 q3j : P 7j1 q4j : P 7j1 q5j : P 7j1 q6j : P 7j1 q7j :
Coef®cient (b)
Sum of Squares
Mean Square
38193.721 5456.245 8031.185 9.284 46224.906 Std. Coeff.
t-Value
F-test 587.665 P = 0.0000
Probability
Aesthetics/Appearance
0.023
0.102
4.686
0.0000
Security/Safety
0.019
0.074
3.693
0.0002
Freedom of Choice
0.047
0.199
8.833
0.0000
Authenticity/Honesty
0.042
0.187
8.578
0.0000
Service Orientation
0.035
0.134
5.928
0.0000
Variety/Fun
0.051
0.242
12.091
0.0000
Accessibility of Services
0.040
0.177
7.905
0.0000
ÿ0.318
0.7503
Constant
ÿ0.037
explains overall quality judgment by the quality dimensions (i=1 to 7) with e=error term. (For the regression model results I and II, see Table 4 and Table 5.) The positive linear relationship between overall quality judgment (OQ) and the 49 summed partial judgments can also be represented through a simple linear regression model showing the relationship between the overall quality judgment measure and the summation of all (summed up) partial quality judgments (Figure 1). Simple regression model of the overall quality judgment OQ b0 b1
49 X qij
! e
m1
with m=ij. The recorded Pearson correlation-coef®cient (Std. Coeff.) is 0.896, which suggests that the embedded theory of quality assessment using the construct of expectations minus experience of quality divided by all the costs involved in acquiring this quality (where
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Figure 1. Correlation: Overall Quality Judgment with Summed up Partial Judgments
the latter represents the original weight from ®nal statements as an approximation of opportunity costs), is useful in tracking quality evaluation and satisfaction of tourists. The above employed method of calculating relationships between partial and overall quality statements can also be useful in deciphering in¯uential activity and qualtiy dimensions affecting quality assessments of destinations by tourists. In the case of the 11 wintersport resorts of this study in Austria and Northern Italy, for example, shopping and additional sport activities and the quality dimensions of variety/fun and freedom of choice contributed the most to the formation of an overall quality judgment. Empirical Results Using a Congruity Approach As an empirical alternative to the above embedded traditional discon®rmation model of consumer satisfaction and dissatisfaction, Table 6. Congruity Type Number
Expectation
Experience
1. 2. 3. 4.
Low (ÿ) High (+) Low (ÿ) High (+)
High (+) High (+) Low (ÿ) Low (ÿ)
Congruity Type Positive incongruity Positive congruity Negative congruity Negative incongruity
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MEASURING TOURIST JUDGMENT ON SERVICE QUALITY Table 7. Computation of Congruity Types
Number 1. 2. 3. 4.
Computation
Congruity Type
Importance < satisfaction Importance=satisfaction Importance=satisfaction Importance>satisfaction
Positive incongruity Positive congruitya Negative congruityb Negative incongruity
a Group two includes all cases were importance and satisfaction yielded the Likertscore of one. b Group three includes all cases were importance and satisfaction scores were identical but higher than one.
a second model was constructed using the congruity approach of customer satisfaction (Chon, Christianson and Chih-Lin Lee 1993; Sirgy and Tyagi 1986). The model predicts satisfaction (quality judgments) to result from a cognitive matching process involving the establishment of congruity and/or incongruity between expectations and experience of quality yielding four basic congruity types (Tables 6±9). With respect to the data matrix of this survey using importance scores for expectations and satisfaction scores for experience (i.e., ®nal statements regarding domains of tourism activity and quality dimensions) the four congruity groupings are shown in Table 7. For each individual domain of tourism activity and quality dimension it is now possible to calculate the distribution of these four basic congruity types. For demonstration purposes the distribution of congruity types is tabulated only across the quality dimension (6) variety/fun and (7) accessibility of services, where the share of congruity type 4 (negative incongruity) of 18.8% far surpassed the next largest share of 16.5% observed for Accessibility of services (Table 8). As a next step, the congruity types formed for the 14 categories can now be used to explain the variance of the overall quality judgment measure (OQ). For illustration purposes the tourism activity domain Sports others than skiing is reported in Table 9.
Table 8. Distribution of Congruity Types Quality dimension Congruity type 1. 2. 3. 4. Total
(6) Variety/Fun Frequency
Percent
422 106 294 190 1,012
41.7 10.5 29.0 18.8 100.0
(7) Accessibility of Services Congruity type 1. 2. 3. 4.
Frequency
Percent
314 146 340 159 959
32.7 15.2 35.5 16.6 100.0
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Table 9. ANOVA: Overall Quality Judgment and Congruity Types Source
d.f.
Sum of Squares
Mean Square
F-test
3 1,014 1,017 N
16,858.308 36,387.689 53,245.996 Q/J Mean
5,619.436 35.885
156.594 P=0.0000
SD
Negative Incongruity
351
ÿ7.803
6.926
Negative Congruity
193
ÿ2.181
5.590
Positive Congruity
313
ÿ1.789
4.958
Positive Incongruity
161
4.124
6.086
Total
1,018
ÿ3.002
7.235
Duncan's Multiple Range-Test Evaluative Congruity (EC) Negative Incongruity Negative Congruity Positive Congruity Positive Incongruity
95 percent Conf.Int. for Mean ÿ8.530 to ÿ7.076 ÿ2.975 to ÿ1.387 ÿ2.340 to ÿ1.233 3.176 to 5.071 ÿ3.447 to ÿ2.556
Table: N Duncan's-Test for Q/J Meana 351 A 193 A 313 B 161 B
Between Groups Within Groups Total Evaluative Congruity (EC)
a The Quality Judgment means (Q/J Mean) with the same letter are not signi®cantly different.
Interpretation of Results There exist highly signi®cant differences among the four congruity types with respect to the overall quality judgment (with the exception of the observations made with group two and three which corresponds to the results reported by Chon et al, 1993). The mean of the overall quality judgment of group one (negative incongruity) is positioned at the extreme low satisfaction end of the spectrum (ÿ7.80) while that of group four (positive incongruity) is situated at the highest end of the positive overall quality judgment (+4.12). This suggests that the approach's basic theoretical constructs could be empirically veri®ed. From different variance analyses for each of the seven domains of activity and each of the seven quality dimensions it is now possible to calculate the explaining power of these four congruity types upon the overall quality judgment (eta2=intergroup variance/total variance). In the above reported domain
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MEASURING TOURIST JUDGMENT ON SERVICE QUALITY
sports others than the skiing, eta2 was 0.31; that is, 31% of the total variance of the overall quality judgment measure relative to a particular destination could be explained via these four congruity groups (independent variable) relative to that domain of activity. The latter implies that the greater the obtained eta2 the higher will be the in¯uence and explanatory power of activity domains and quality dimensions/attributes upon the formation of the overall
Figure 2. Ranking of Tourism Activity Domains
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Figure 3. Ranking of Tourism Quality Domains
quality judgment (OQ). The in¯uence of domains of tourism acitivity and quality dimensions was noted earlier, using regression techniques (Tables 6 and 7). Provided that both methods yield correct results, the same ranking of the obtained weighting schemes, similar results would recon®rm earlier ®ndings from the regression analysis. Thus one may compare below the standardized beta-coef®cients from the regression results and the eta2s from the ANOVAs
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MEASURING TOURIST JUDGMENT ON SERVICE QUALITY
for both domains of tourism activity and quality dimensions in descending order of relevance (Figures 2 and 3). In the majority of cases either method yields the same ranking. The three tourism activity domains of shopping activities, sports others than skiing and food and accommodation and the two quality dimensions variety/fun and authenticity/honesty have the highest impact on the overall quality judgment associated with particular winter resorts while the two quality dimensions of aesthetics/ appearance and security/safety yield the smallest in¯uence upon the overall quality judgment. CONCLUSION The study has used implicitly a priori assumptions of tourists' preferences, attitudes, and decision making based on a body of existing literature associated particularly with the life cycle and lifestyle theories of tourism behavior (Bojanic 1992; Lawson 1991). These subsequently have been modi®ed and valididated through alpine tourism speci®c observations and questionnaire pretests. The study has been less concerned with questions of tourism motivation and decision making than with an ex post evaluation of perceptions, evaluations, and satisfaction with tourism activities and service characteristics. Since conjoint analysis tools are often viewed as too restrictive and constrained with respect to the comparison of attribute characteristics (Green 1984; Toy, Rager and Guadagnolo 1989), a multi-attribute measurement model has been chosen to evaluate service quality and tourist satisfaction. From a methodological point of view, the results of the study are encouraging in that they have once more shown the usefulness of expectancy-value or multi-attribute models in deciphering relevant ®elds of tourist (dis-)satisfaction. Experimenting with alternate statistical techniques and exploring alternate tourist satisfaction measurement approaches yielded a surprisingly consistent picture of disaggregated measures (weights) of perceived service quality in eleven winter sport destinations. The results have rather important implications for product development and/or the marketing of alpine winter tourism in Austria and Northern Italy in pinpointing at possible roots of guest dissatisfaction. Some authors have recently advanced the hypothesis that traditional alpine tourism activities are losing their appeal on account of changing customer preferences and tastes (Opaschowski 1996; Weiermair 1995, 1996). This study con®rms this hypothesis and offers some clues as to the relative quantitative importance of speci®c quality attributes within the total package typically offered to winter sport tourists in Austria. The latter holds particularly true for such quality attributes as variety/fun, freedom of choice, and authenticity/honesty associated with locally provided tourism products and services. The results should prove useful in Austria's national and regional boards' efforts to reengineer development of tourism products which are now under way in many parts of Austria.&
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Acknowledgments ÐThis research was funded by the Austrian National Bank Jubilee È NBF). The authors thank Josef Mazanec (Commerce, Vienna, Foundation (O University) and Gottfried Tappeiner (SOWI, Innsbruck University) for useful comments on an earlier draft version.
REFERENCES Bojanic, D. 1992 A Look at a Modernised Family Life Cycle and Overseas Travel. Journal of Travel and Tourism Marketing 1(1):68±80. Brown, S. W., E. Gummeson, B. Edvardsson and B. Gustavsson, eds. 1991 Service Quality Multidisciplinary and Multinational Perspectives. Lexington MA: Heath. Cadotte, E. R., R. B. Woodruff, and R. L. Jenkins 1987 Expectations and Norms in Models of Consumer Satisfaction. Journal of Marketing Research 24:305±314. Chase, R. 1992 The Customer Content Approach to Service: Theoretical Bases and Practical extensions. In Managing Services (2nd ed.), C. Lovelock, ed., pp. 43± 49. Englewood Cliffs NJ: Prentice±Hall. Chase, R. B., and D. R. Bowen 1991 Service Quality and the Service Delivery System. A Diagnostic Framework. In Service Quality Multidisciplinary and Multinational Perspectives, S. W. Brown, E. Gummeson, B. Edvardsson and B. Gustavsson, eds., pp. 157±176. Lexington MA: Heath. Chon, K. S., D. J. Christianson, and Chih-Lin Lee 1993 Contemporary Research Issues Related to Tourist Satisfaction and Dissatisfaction. Spoilt for ChoiceÐDecision Making Processes and Preference Changes of TouristsÐIntertemporal and Intercountry Perspectives. In Conference Proceedings, Institute of Tourism and Service Economics, K. Weiermair and R. V. Gasser, eds., pp. 150±160. Dall' Aglio, S. 1996 Tourist Satisfaction: Measurement for Management. Paper presented at Tourism Research Center meeting, Bergen, The Netherlands. Doren, D. C., and J. Mattsson 1996 An Empirical Assessment of Customer Satisfaction in Tourism. The Service Industries Journal 16(3):305±320. Eurostat 1995 Jahrbuch 1995: Europa im Blick der Statistik, 1983±1993. Luxemburg: Eurostat. Fick, G. R., and J. B. Ritchie 1991 Measuring Service Quality in the Travel and Tourism Industry. Journal of Travel Research 30(2):2±9. Green, P. E. 1984 Hybrid Models for Conjoint Analysis: An Expository Review. Journal of Marketing Research 21(May):155±169. GroÈnroos, C. 1982 An Applied Service Marketing Theory. European Journal of Marketing 16:30±41. Heskett, J. L., J. R. Sasser, and C. W. L. Hart 1990 Service Breakthroughs, Changing the Rules of the Game. New York: The Free Press. Hu, J., and B. Ritchie 1993 Measuring Destination Attractiveness: A Contextual Approach. Journal of Travel Research 32(2):25±34. Keane, M. J. 1997 Quality and Pricing in Tourism Destinations. Annals of Tourism Research 24:117±130.
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Kohli, R. 1988 Assessing Attribute Signi®cance in Conjoint Analysis: Nonparametric Tests and Empirical Validation. Journal of Marketing Research 25(May):123±133. Lawson, R. 1991 Pattern of Tourist Expenditures and Type of Vacation Across the Family Life Cycle. Journal of Travel Research 29(4):12±18. Lemmink, J., and P. Kunst 1992 Quality Management in Services. Assen: Van Gorcum. Mazanec, J. È sterreichs 1996 Ursachenanalyse der AttraktivitaÈtseinbuûe O als È GAF/ Sommerurlaubsland: Preisniveau oder AngebotsqualitaÈt? Wien: O È Osterreichische Gesellschaft fu Èr Angewandte Fremdenverkehrswissenschaft. Moore, K., G. Cushman, and D. Simmons 1995 Behavioural Conceptualization of Tourism and Leisure. Annals of Tourism Research 22:67±85. Oppermann, M. 1995 Travel Life Cycle. Annals of Tourism Research 22:535±552. Opaschowski, H. 1996 TourismusÐEine systematische Einfu Èhrung. Opladen. Parasuraman, A., V. A. Zeithaml, and L. L. Berry 1988 SERVQUAL: A Multiple Item Scale for Measuring Consumer Perceptions of Service Quality. Journal of Retailing 64(1):12±40. 1985 A Conceputal Model of Service Quality and its Implications for Future Research. Journal of Marketing 49:41±50. 1991 Re®nement and Reassessment of the SERVQUAL Scale. Journal of Retailing 67(4):420±450. 1993 The Nature and Determinants of Customer Expectations of Service. Journal of the Academy of Marketing Science 2:1±12. Pizam, A., Y. Neumann, and A. Reichel 1978 Dimensions of Tourism Satisfaction with a Destination Area. Annals of Tourism Research 5(3):314±322. Pearce, P. L. 1982 Perceived Changes in Holiday Destinations. Annals of Tourism Research 9:145±162. 1996 Recent Research in Tourist Behaviour. Asia Paci®c Journal of Tourism Research 1(1):7±17. Poon, A. 1993 Tourism, Technology and Competitive Strategies. Wallingford: CAB International. Ryan, C. 1995 Researching Tourist SatisfactionÐIssues, Concepts, Problems. London: Routledge. Sasser, W. E., R. P. Olson, and D. D. Wyckoff 1978 The Management of Service Operations. Newton MA: Alleyn & Bacon. Schulmeister, S. 1975 Internationaler Reiseverkehr und Wirtschaftswachstum-Beschreibung, Analyse und Prognose der langfristigen NaÈchtigungsentwicklung fu Èr die wichÈ sterreichisches Institut fu Ènder. Wien: O tigsten Herkunfts- und Ziella Èr Wirtschaftsforschung. Sirgy, M. J., and P. K. Tyagi 1986 An Attempt Toward an Integrated Theory of Consumer Psychology and Decision Making. Systems Research 3(3):161±175. Smeral, E. È berreuter. 1994 Tourismus 2005. Wien: U Stauss, B., and W. Seidel 1995 Prozessuale Zufriedenheitsermittlung und Zufriedenheitsdynamik bei Dienstleistungen. In Kundenzufriedenheit: Konzepte-Methoden-Erfahrungen, H. Simon and C. Homburg, eds., pp. 179±203. Wiesbaden: Gablev. Toy, D., R. Rager, and F. Guadagnolo 1989 Strategic Marketing for Recreational Facilities: A Hybrid Conjoint Analysis Approach. Journal of Leisure Research 21(4):276±296.
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Weiermair, K. 1994 Quality Management in Tourism: Lessons from the Service Industries. AIEST Congress on Tourism Research: Achievements. Failures and Unresolved Puzzles, pp. 93±114. St Gallen, Switzerland. 1995. Austria's Tourism Development from 1992 to 1995: Cyclical or Structural Changes? An Encyclopedia of International Tourism, F. Vellas, ed., pp. 37±43. Paris: SocieÂte d'Etude, Realisation et Diffusion Internationale. 1996 Strukturwandel im alpinen Tourismus. In Theorie und Praxis der Tourismus- und Verkehrswissenschaft im Wertewandel, G. Fischer and C. Laesser, eds., pp. 187±198. Witt, C. A., and S. F. Witt 1995 An Overview of Tourism Forecasting Accuracy Comparisons. Tourist Review 48(2):29±35. Zeithaml, V. A. 1988 Consumer Perception of Price, Quality and Value: A Means-end Model and Synthesis of Evidence. Journal of Marketing 52:2±22. Submitted 6 October 1997. Resubmitted 22 January 1998. Resubmitted 5 June 1998. Accepted 3 September 1998. Final version 17 February 1999. Refereed anonymously. Coordinating Editor: Boris VukonicÂ.
Annals of Tourism Research, Vol. 26, No. 4, pp. 1004±1021, 1999 # 1999 Elsevier Science Ltd. All rights reserved Printed in Great Britain 0160-7383/99/$20.00+0.00
PII: S0160-7383(99)00037-7
MEASURING TOURIST JUDGMENT ON SERVICE QUALITY Klaus Weiermair Matthias Fuchs University of Innsbruck, Austria Abstract: This study measures tourist judgments on service quality in alpine ski resorts. An attribute based method was employed in order to estimate weighting schemes both for quality judgments across different tourism activity domains and different quality dimensions within winter resorts and to quantify an overall quality measure. A linear regression and Sirgy's congruity model of customer satisfaction/dissatisfaction were adopted. The results indicate that there exists a linear relationship between the overall quality measure and the partial judgments of each domain/dimension. This allows deciphering the relevance of different domains of tourism activity and quality dimensions within the process of making quality judgments. Keywords: tourist judgments, winter resort, attribute based quality measure. # 1999 Elsevier Science Ltd. All rights reserved. Âsume Â: L'eÂvaluation des jugements de qualite de service par des touristes. Cette Âetude Re mesure les jugements de qualite de service faits par des touristes aux stations de ski alpin. On a utilise une meÂthode baseÂe sur des attributs qualitatifs pour Âevaluer des scheÂmas de coef®cients pour des jugements qualitatifs de divers domaines d'activite touristique et diverses dimensions qualitatives aux stations d'hiver, et pour quanti®er un mesurage de qualite geÂneÂrale. On a adopte une reÂgression lineÂaire et le modeÁle de congruite de Sirgy de la satisfaction/insatisfaction des clients. Les reÂsultats indiquent qu'il existe une relation lineÂaire entre l'eÂvaluation de qualite geÂneÂrale et les jugements partiels de chaque domain ou dimension. Ceci permer de deÂchiffrer l'inteÂreÃt des divers domaines d'activite touristique et Â. # 1999 Elsevier Science les dimensions qualitatives du processus des jugements de qualite Ltd. All rights reserved.
INTRODUCTION After decades of rapid growth in tourism, Austria and its neighboring regions in Germany, Switzerland and Upper Italy have over the past three years experienced sustained declines in the number of tourists visiting their destinations. While the alpine Central European regions may be a special case, all of Europe has experienced a decline in its world market share from 66% to 59% (Eurostat 1995). This has rekindled the public debate over the poss-
Klaus Weiermair is Professor and Head of the Institute of Tourism and Service Economics, University of Innsbruck (UniversitaÈtsstrasse 15, 6020-Innsbruck, Austria. Email: < [email protected] >). He has research experience in change management, human resource and organization development, competitive analysis, and consumer behavior within the hospitality and tourism context. Matthias Fuchs is Assistant Professor at the same Institute < [email protected] >. His research interests include labor market and human-resource economics, cultural tourism, and tourist satisfaction analysis.
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ible causes of this decline with price and price related factors (such as exchange rates) and quality being the major explanatory factors. Contrary to the past when price and income explanations have dominated (Keane 1997; Schulmeister 1975; Smeral 1994; Witt and Witt 1995) quality or value for money are now moving as possible explanations to the forefront (Mazanec 1996). As for the traditional activities of alpine tourism such as hiking and skiing and traditional quality attributes such as accessibility and friendliness, they no longer seem to suf®ce to attract a large number of tourists to areas such as Switzerland, or the alpine parts of Austria and Northern Italy, as can be evidenced by the declining number of overnight stays over the past years. A number of researchers have in this context written about changing attitudes and behavior of tourists and their service quality expectations (Opaschowski 1996; Poon 1993; Ryan 1995; Weiermair 1994). If their hypotheses are correct, one should be able to observe, even among those who have already made destination choices, possible service quality de®cits with respect to such new quality attributes as animation and fun or freedom of choice. Survey research will be presented which has been carried out in 11 winter sport resorts in Austria and Northern Italy involving a sample of 1,822 tourists vacationing during various periods in those resorts in the winter season of 1994±95. The survey aimed at obtaining correct quality measures for service quality broadly de®ned in seven domains of tourism activity: food and accommodation, sports activities (other than skiing), animation and culture, transportation aspects to and within resorts, skiing and related activities, enjoyment with nature and landscape, and shopping activities (Table 1). The design of quality attributes and associated quality measures of alpine tourism has been heavily in¯uenced by a rich and growing literature on the construction and use of quality attribute measures in services (Brown, Gummeson, Edvardsson and Gustavsson 1991; Chase and Bowen 1991; Fick and Ritchie 1991; Parasuraman, Zeithaml and Berry 1985). The ®nal choice of quality attributes and related questions had to be tempered with the chosen mix of the seven tourism activities. These seven attributes emerged as the most valid dimensions of service quality to be used for alpine winter Table 1. Domains of Tourism Activity Number 1. 2. 3. 4. 5. 6. 7.
Domain of Tourism Activity Food and Accommodation Sports activities (other than skiing) Animation and Culture Transportation Aspects to and within Resort Skiing and Related Activities Enjoyment with Nature and Landscape (e.g., hiking) Shopping Activities
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MEASURING TOURIST JUDGMENT ON SERVICE QUALITY Table 2. Quality Dimensions
Number 1. 2. 3. 4. 5. 6. 7.
Quality Dimensiona Aesthetics/Appearance Security/Safety Freedom of Choice (with respect to choosing activities) Authenticity/Honesty Service Orientation in terms of Punctuality and Reliability Variety/Fun Accessibility of Services
a
In order to obtain consistency and validity with respect to these seven dimensions, the wording had to be varied across different activity categoriesÐfor example, honesty with services corresponds to authenticity with nature, etc.
destinations (Table 2). Pretests were undertaken both with respect to a set of quality attributes originally derived from Parasuraman, Zeithaml and Berry (1985:47) and with the different wording of questions addressing these quality dimensions. The pretests involved tourists, tourism operators, and tourism of®cials. TOURIST JUDGMENTS ON SERVICE QUALITY Some authors have suggested that attribute importance can be used as a proxy for measuring expectations (Dall' Aglio 1996; Kohli 1988:124; Toy, Rager and Guadagnolo 1989). Hence, as a methodological starting point, the SERVQUAL model, which measures the gap between expectations and perceptions of the service by the consumer, as an indicator of service quality, was employed (Parasuraman, Zeithaml and Berry 1993; Zeithaml 1988). The quality observations in the study reported here were scored with a ®ve-point Likert scale. Each questionnaire contained sociodemographic and other background information on the tourist in addition to its partial and ®nal assessments concerning the seven quality dimensions found in each of the domains of activity: tourists were asked to indicate the importance of each attribute in each of the seven activities yielding 49 partial quality assessments. In addition they were also asked to assess the ®nal importance of each of the major activities and seven quality dimensions. Similarly they were requested to provide the same partial and ®nal quality assessments in terms of experienced satisfaction. Using different multivariate analyses the paper attempts to explain ®nal satisfaction and importance scores based on partial quality scores in each of the seven domains of tourism activity. Put differently, the exercise was to statistically estimate theoretically defensible weighting schemes for each of the single quality judgments across all activities, thereby explaining or interpreting tourists' ®nal quality assessments.
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On the Use of Quality Judgments of Tourists: Some Theoretical Issues Following a number of researchers, the service quality construct was arrived at by comparing a service quality level which the consumer expects to receive (``importance'' is used as proxy indicator) and the service quality level which he/she has experienced (``satisfaction'' is used as proxy indicator). According to the model, the higher the level of expectation relative to the perceived quality experience the lower the level of perceived quality and vice versa (GroÈnroos 1982; Parasuraman, Zeithaml and Berry 1985, 1988, 1991; Sasser, Olson and Wyckoff 1978; Zeithaml 1988; Heskett, Sasser and Hart 1990). The main theoretical and empirical issue of this paper rests with tourists' varied assessments of service quality but once a major holiday decision has been made and tourists ®nd themselves vacationing in a particular destination, one cannot entirely exclude prepurchase/preconsumption decision criteria and behavior. Expectations or importance ``standards'' are formed for the most part prior to the decision making process and thus have a bearing on the subsequently used SERVQUAL measurement tool for service quality. As has been pointed out in the literature, customers may have different expectation levels regarding quality attributes ranging from desired to adequate to equitable and/or best brand norms (Stauss and Seidel 1995) thereby in¯uencing the absolute measure of discrepancy between quality expectation and quality experience (i.e., perceived quality). Since the focus on this paper is not about tourism decision making or client segmentation according to some absolute measure of quality importance (or expectations) and since distance measures will furthermore be expressed as relative concepts, the SERVQUAL methodology should provide non-biased results. Likewise, one could argue that consumers cannot make quality assessments, particularly those associated with satisfaction, without regard to price and/or value which could be expressed as quality divided by all of the costs involved in acquiring this quality (Heskett, Sasser and Hart 1990:3). In this study tourists were asked to provide ex post quality assessments after a purchasing decision had already been made. Hence, price will likely play less of a role than in an ex ante decision making context. Furthermore tourists may make quality evaluations independent of price, and rather use price as a separate check on the appropriateness or adequacy of service performance (Mazanec 1996). The subsequent models use a particular weighting scheme and thus attempt to calculate a shadow price or implicit opportunity cost associated with quality assessments. Expectations regarding certain levels of quality can best be circumscribed and empirically assessed through scores of importance, while quality experience or perceived quality can be best recorded and measured as a satisfaction score for a particular attribute (Cadotte, Woodruff and Jenkins 1987; Doren and Mattsson 1996; Fick and Ritchie 1991; Hu and Ritchie 1993; Pizam, Neumann and Reichel 1978). While the
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MEASURING TOURIST JUDGMENT ON SERVICE QUALITY
method used here is attribute based, there is a controversial opposing method of viewing the tourism service experience as a series of encounters, emphasizing more the process and interactive character of service consumption (Chase 1992). The sample included and reported verbal critical positive and negative incidents at the end of the survey which supported the main measurements, but theoretical reasons also suggest that neither attribute nor process-based approaches will yield superior results (Lemmink and Kunst 1992). Thus, a modi®ed version of the SERVQUAL-model was retained to analyze partial and ®nal quality assessments of tourists in the Austrian and Northern Italian winter destinations. Underlying Model of Quality Measurement Tourists typically consume a choice of tourism services and evaluate their experience holistically in terms of ®nal judgments. In arriving at ®nal statements concerning particular quality dimensions or domains of activity they are likely to weight the ®nal judgment according to the importance (or expectation) attached to particular single quality or activity elements. Put differently and applied to the survey data, the ®nal quality judgment scores (such as food and accommodation) should not be the simple arithmetic mean of its consistent seven quality attribute scores. Similarly, the scores for aesthetic quality over the whole sample should not equal the arithmetic mean of aesthetic quality scores over all domains of tourism activity. In different steps one can now attempt to decipher the weights attached to quality judgments by tourists. Thus, the ®rst attempt involved the regression of the ®nal quality judgment scores (in terms of the difference, i.e., the gap, between importance and satisfaction scores) in the seven domains of tourism activity and the seven categories of quality dimension (explained variable) against the seven consistent quality judgments derived from the partial assessments in terms of importance minus satisfaction (independent variables). As to be expected for unweighted estimations, the results were poor: the R2s were on average not over 0.2, most of the z-standardized beta-coef®cients were statistically insigni®cant and some had the wrong (i.e., negative) sign. In a second step, the same ®nal quality judgment scores (explained variables) were regressed against weighted quality scores whereas the latter were derived as weighted quality scores in the various domains of tourism activity, weighted by the ®nal quality assessments concerning activity and quality dimensions. Weighted Partial Quality Judgmentij qij IPij IFi IFj ÿ SPij SFi SFj with i=1 to 7, the quality dimensions, and with j=1 to 7, the domains of tourism activity. The following variables having a ®vepoint Likert range:
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1009
IPij partial assessment for importance SPij partial assessment for satisfaction IFi final assessment for importance relative to the quality dimensions IFj final assessment for importance relative to the domains of tourism activity SFi final assessment for satisfaction relative to the quality dimensions SFj final assessment for satisfaction relative to the domains of tourism activity Regression models of ®nal quality judgment measure (FQl) explained separately FQl b0 b1 q1j b2 q2j b3 q3j . . . b7 q7j e one regression for each domain of tourism activity ( j=1 to 7) and the seven (weighted) judgments of quality dimension as predictor variables FQl b0 b1 qi1 b2 qi2 b3 qi3 . . . b7 qi7 e one regression for each quality dimension (i=1 to 7) and the seven (weighted) judgments of domains of tourism activity as predictor variables with l=1 to14 and FQl=gap between ®nal-assessment pairs (i.e., IFiÿSFi, IFjÿSFj respectively), bk=regression coef®cients (k=0 to 7), and e=error term, the results were better. The R2s increase in most cases to above 0.6, the z-standardized-beta-coef®cients (Std. Coeff.) have now the correct sign and are also statistically signi®cant. Most weights behaved as expected, but some observations are worth separate reporting as they are in line with the quoted literature on changes in tourists' values and attitudes towards tourism products (Moore, Cushman and Simmons 1995; Oppermann 1995; Pearce 1982, 1996). For example, with regard to Food and Accommodation service orientation still dominates, but aesthetics/appearence and authenticity/honesty are becoming almost equally important (Table 3). In analogous fashion the standardized beta-coef®cients for the single judgments involving the seven categories of quality dimensions can similarly be interpreted, yielding the corresponding weighting results.
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MEASURING TOURIST JUDGMENT ON SERVICE QUALITY
Table 3. Regression Final Quality Judgment ``Food and Accommodation'' ([j] No. 1)
Summary Statistics Table: Count=656
R=0.779
Analysis of Variance Table: Source
d.f.
Regression Residual Total
Sum of Squares
Mean Square
F-test
307.160 198.150 505.310
43.880 0.305
143.498 P = 0.0000
Coef®cient (b)
Std. Coeff.
t-Value
0.030 0.007 0.016 0.028 0.038 0.011 0.008 ÿ0.066
0.234 0.049 0.121 0.221 0.245 0.104 0.060
6.664 1.585 3.522 7.184 7.699 3.510 1.980 ÿ2.772
7 648 655
Beta Coef®cient Table: Variable (q11). Aesthetic/Appearance (q21). Security/Safety (q31). Freedom of Choice (q41). Authenticity/Honesty (q51). Service Orientation (q61). Variety/Fun (q71). Accessibility of Services Constant
R2=0.607 Adjusted Durbin R2=0.603 Watson=2.021
Probability 0.0000 0.1135 0.0005 0.0000 0.0000 0.0005 0.0482 0.0057
Comparability of Regression Results The above regression equations explaining quality judgments in seven domains of tourism actitvity and seven quality dimensions cannot be compared and correctly interpreted with respect to their in¯uence upon the ``overall'' quality judgment of a particular destination (problem of ®nding correct relative weights). Therefore, in a next step all 49 partial quality judgments (qij) for each of the activities and quality elements were summed up, and were used subsequently to explain the overall quality judgment relative to a particular destination, where the summated scale represents a hypothetical construct consisting of the sum of all the ®nal quality judgments (FQl). Regression models of overall quality judgment measure (OQ): with OQ
14 7 7 X X X FQl IFi ÿ SFi IFj ÿ SFj l1
i1
j1
as equivalent to the sum of the seven gaps between ®nal assessments related to seven quality dimensions and those associated with the seven domains of tourism activity
WEIERMAIR AND FUCHS
1011
I. Regression model of 0 1 0 1 0 1 7 7 7 X X X OQ b0 b1 @ q1j A b2 @ q2j A b3 @ q3j A j1
j1
j1
0
1 7 X . . . b7 @ q7j A e j1
II. Regression model of OQ b0 b1
. . . b7
! ! ! 7 7 7 X X X q1i b2 q2i b3 q3i i1
7 X
i1
i1
! q7i e
i1
Table 4. I. Regression Overall Quality Judgment with Partial Quality Judgments (j)
Summary Statistics Table: Count=777 Analysis of Variance Table: Source Regression Residual Total
P7
j1 q1j :
P7
j1 q2j : P7 j1 q3j : P 7j1 q4j : P 7j1 q5j : P 7j1 q6j : P 7j1 q7j : Constant
d.f. 7 769 776
Beta Coef®cient Table: Variable
R=0.917 R2=0.842 Adjusted Durbin R2=0.841 Watson=1.915
Coef®cient (b)
Sum of Squares
Mean Square
35856.624 5122.374 6695.694 8.707 46224.906 Std. Coeff.
t-Value
F-test 588.304 P = 0.0000
Probability
Food and Accommodation
0.038
0.170
8.626
0.0000
Sport Activities
0.048
0.227
9.968
0.0000
Animation and Culture
0.017
0.061
2.857
0.0044
Transportation Aspects
0.022
0.109
5.938
0.0000
Skiing and Rel. Activities
0.029
0.138
7.045
0.0000
Nature and Landscape
0.040
0.151
7.520
0.0000
0.051 ÿ0.087
0.294
14.206 ÿ0.687
0.0000 0.4924
Shopping Aspects
MEASURING TOURIST JUDGMENT ON SERVICE QUALITY
1012
Table 5. II. Regression Overall Quality Judgment with Partial Quality Judgments (i)
Summary Statistics Table: Count=873
R=0.908 R2=0.826 Adjusted Durbin R2=0.824 Watson=2.055
Analysis of Variance Table: Source
d.f.
Regression Residual Total
7 865 872
Beta Coef®cient Table: Variable
P7
j1 q1j :
P7
j1 q2j : P 7j1 q3j : P 7j1 q4j : P 7j1 q5j : P 7j1 q6j : P 7j1 q7j :
Coef®cient (b)
Sum of Squares
Mean Square
38193.721 5456.245 8031.185 9.284 46224.906 Std. Coeff.
t-Value
F-test 587.665 P = 0.0000
Probability
Aesthetics/Appearance
0.023
0.102
4.686
0.0000
Security/Safety
0.019
0.074
3.693
0.0002
Freedom of Choice
0.047
0.199
8.833
0.0000
Authenticity/Honesty
0.042
0.187
8.578
0.0000
Service Orientation
0.035
0.134
5.928
0.0000
Variety/Fun
0.051
0.242
12.091
0.0000
Accessibility of Services
0.040
0.177
7.905
0.0000
ÿ0.318
0.7503
Constant
ÿ0.037
explains overall quality judgment by the quality dimensions (i=1 to 7) with e=error term. (For the regression model results I and II, see Table 4 and Table 5.) The positive linear relationship between overall quality judgment (OQ) and the 49 summed partial judgments can also be represented through a simple linear regression model showing the relationship between the overall quality judgment measure and the summation of all (summed up) partial quality judgments (Figure 1). Simple regression model of the overall quality judgment OQ b0 b1
49 X qij
! e
m1
with m=ij. The recorded Pearson correlation-coef®cient (Std. Coeff.) is 0.896, which suggests that the embedded theory of quality assessment using the construct of expectations minus experience of quality divided by all the costs involved in acquiring this quality (where
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1013
Figure 1. Correlation: Overall Quality Judgment with Summed up Partial Judgments
the latter represents the original weight from ®nal statements as an approximation of opportunity costs), is useful in tracking quality evaluation and satisfaction of tourists. The above employed method of calculating relationships between partial and overall quality statements can also be useful in deciphering in¯uential activity and qualtiy dimensions affecting quality assessments of destinations by tourists. In the case of the 11 wintersport resorts of this study in Austria and Northern Italy, for example, shopping and additional sport activities and the quality dimensions of variety/fun and freedom of choice contributed the most to the formation of an overall quality judgment. Empirical Results Using a Congruity Approach As an empirical alternative to the above embedded traditional discon®rmation model of consumer satisfaction and dissatisfaction, Table 6. Congruity Type Number
Expectation
Experience
1. 2. 3. 4.
Low (ÿ) High (+) Low (ÿ) High (+)
High (+) High (+) Low (ÿ) Low (ÿ)
Congruity Type Positive incongruity Positive congruity Negative congruity Negative incongruity
1014
MEASURING TOURIST JUDGMENT ON SERVICE QUALITY Table 7. Computation of Congruity Types
Number 1. 2. 3. 4.
Computation
Congruity Type
Importance < satisfaction Importance=satisfaction Importance=satisfaction Importance>satisfaction
Positive incongruity Positive congruitya Negative congruityb Negative incongruity
a Group two includes all cases were importance and satisfaction yielded the Likertscore of one. b Group three includes all cases were importance and satisfaction scores were identical but higher than one.
a second model was constructed using the congruity approach of customer satisfaction (Chon, Christianson and Chih-Lin Lee 1993; Sirgy and Tyagi 1986). The model predicts satisfaction (quality judgments) to result from a cognitive matching process involving the establishment of congruity and/or incongruity between expectations and experience of quality yielding four basic congruity types (Tables 6±9). With respect to the data matrix of this survey using importance scores for expectations and satisfaction scores for experience (i.e., ®nal statements regarding domains of tourism activity and quality dimensions) the four congruity groupings are shown in Table 7. For each individual domain of tourism activity and quality dimension it is now possible to calculate the distribution of these four basic congruity types. For demonstration purposes the distribution of congruity types is tabulated only across the quality dimension (6) variety/fun and (7) accessibility of services, where the share of congruity type 4 (negative incongruity) of 18.8% far surpassed the next largest share of 16.5% observed for Accessibility of services (Table 8). As a next step, the congruity types formed for the 14 categories can now be used to explain the variance of the overall quality judgment measure (OQ). For illustration purposes the tourism activity domain Sports others than skiing is reported in Table 9.
Table 8. Distribution of Congruity Types Quality dimension Congruity type 1. 2. 3. 4. Total
(6) Variety/Fun Frequency
Percent
422 106 294 190 1,012
41.7 10.5 29.0 18.8 100.0
(7) Accessibility of Services Congruity type 1. 2. 3. 4.
Frequency
Percent
314 146 340 159 959
32.7 15.2 35.5 16.6 100.0
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1015
Table 9. ANOVA: Overall Quality Judgment and Congruity Types Source
d.f.
Sum of Squares
Mean Square
F-test
3 1,014 1,017 N
16,858.308 36,387.689 53,245.996 Q/J Mean
5,619.436 35.885
156.594 P=0.0000
SD
Negative Incongruity
351
ÿ7.803
6.926
Negative Congruity
193
ÿ2.181
5.590
Positive Congruity
313
ÿ1.789
4.958
Positive Incongruity
161
4.124
6.086
Total
1,018
ÿ3.002
7.235
Duncan's Multiple Range-Test Evaluative Congruity (EC) Negative Incongruity Negative Congruity Positive Congruity Positive Incongruity
95 percent Conf.Int. for Mean ÿ8.530 to ÿ7.076 ÿ2.975 to ÿ1.387 ÿ2.340 to ÿ1.233 3.176 to 5.071 ÿ3.447 to ÿ2.556
Table: N Duncan's-Test for Q/J Meana 351 A 193 A 313 B 161 B
Between Groups Within Groups Total Evaluative Congruity (EC)
a The Quality Judgment means (Q/J Mean) with the same letter are not signi®cantly different.
Interpretation of Results There exist highly signi®cant differences among the four congruity types with respect to the overall quality judgment (with the exception of the observations made with group two and three which corresponds to the results reported by Chon et al, 1993). The mean of the overall quality judgment of group one (negative incongruity) is positioned at the extreme low satisfaction end of the spectrum (ÿ7.80) while that of group four (positive incongruity) is situated at the highest end of the positive overall quality judgment (+4.12). This suggests that the approach's basic theoretical constructs could be empirically veri®ed. From different variance analyses for each of the seven domains of activity and each of the seven quality dimensions it is now possible to calculate the explaining power of these four congruity types upon the overall quality judgment (eta2=intergroup variance/total variance). In the above reported domain
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sports others than the skiing, eta2 was 0.31; that is, 31% of the total variance of the overall quality judgment measure relative to a particular destination could be explained via these four congruity groups (independent variable) relative to that domain of activity. The latter implies that the greater the obtained eta2 the higher will be the in¯uence and explanatory power of activity domains and quality dimensions/attributes upon the formation of the overall
Figure 2. Ranking of Tourism Activity Domains
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Figure 3. Ranking of Tourism Quality Domains
quality judgment (OQ). The in¯uence of domains of tourism acitivity and quality dimensions was noted earlier, using regression techniques (Tables 6 and 7). Provided that both methods yield correct results, the same ranking of the obtained weighting schemes, similar results would recon®rm earlier ®ndings from the regression analysis. Thus one may compare below the standardized beta-coef®cients from the regression results and the eta2s from the ANOVAs
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for both domains of tourism activity and quality dimensions in descending order of relevance (Figures 2 and 3). In the majority of cases either method yields the same ranking. The three tourism activity domains of shopping activities, sports others than skiing and food and accommodation and the two quality dimensions variety/fun and authenticity/honesty have the highest impact on the overall quality judgment associated with particular winter resorts while the two quality dimensions of aesthetics/ appearance and security/safety yield the smallest in¯uence upon the overall quality judgment. CONCLUSION The study has used implicitly a priori assumptions of tourists' preferences, attitudes, and decision making based on a body of existing literature associated particularly with the life cycle and lifestyle theories of tourism behavior (Bojanic 1992; Lawson 1991). These subsequently have been modi®ed and valididated through alpine tourism speci®c observations and questionnaire pretests. The study has been less concerned with questions of tourism motivation and decision making than with an ex post evaluation of perceptions, evaluations, and satisfaction with tourism activities and service characteristics. Since conjoint analysis tools are often viewed as too restrictive and constrained with respect to the comparison of attribute characteristics (Green 1984; Toy, Rager and Guadagnolo 1989), a multi-attribute measurement model has been chosen to evaluate service quality and tourist satisfaction. From a methodological point of view, the results of the study are encouraging in that they have once more shown the usefulness of expectancy-value or multi-attribute models in deciphering relevant ®elds of tourist (dis-)satisfaction. Experimenting with alternate statistical techniques and exploring alternate tourist satisfaction measurement approaches yielded a surprisingly consistent picture of disaggregated measures (weights) of perceived service quality in eleven winter sport destinations. The results have rather important implications for product development and/or the marketing of alpine winter tourism in Austria and Northern Italy in pinpointing at possible roots of guest dissatisfaction. Some authors have recently advanced the hypothesis that traditional alpine tourism activities are losing their appeal on account of changing customer preferences and tastes (Opaschowski 1996; Weiermair 1995, 1996). This study con®rms this hypothesis and offers some clues as to the relative quantitative importance of speci®c quality attributes within the total package typically offered to winter sport tourists in Austria. The latter holds particularly true for such quality attributes as variety/fun, freedom of choice, and authenticity/honesty associated with locally provided tourism products and services. The results should prove useful in Austria's national and regional boards' efforts to reengineer development of tourism products which are now under way in many parts of Austria.&
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Acknowledgments ÐThis research was funded by the Austrian National Bank Jubilee È NBF). The authors thank Josef Mazanec (Commerce, Vienna, Foundation (O University) and Gottfried Tappeiner (SOWI, Innsbruck University) for useful comments on an earlier draft version.
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