The Influence of Hotel Price on Perceived Service Quality and Value in e-tourism



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Pricing and PSQ 2

EMPIRICAL RESULTS

The Impact of Price on Perceived Quality and Value

The results of the regression analysis of Model (3) are presented in Table 2. 

The analysis indicates a good fit, with a highly significant likelihood ratio (p = 

.000) and R

2

 of 0.359.



The coefficient of price is negative and significant. Thus, Hypothesis 1 is 

supported. The results also show that the four components of perceived service 



Table 2

The Impact of Price on Value Ratings

Coefficient



T

p > |t|

Constant


1.671

14.93


.000

ln(Price)

−0.127

−4.95


.000

ln(Ranking)

−0.027

−7.84


.000

Comfort


0.212

38.85


.000

Location


0.131

29.99


.000

Cleanliness

0.228

41.19


.000

Service


0.200

40.39


.000

StarRating

−0.014

−3.02


.003

StarRating × ln(Price)

0.009

1.76


.079

TripType


−0.014

−1.04


.301

TripType × ln(Price)

0.001

0.62


.536

Number of cases

43,721

F value

924.19


Adjusted R

2

0.359




32    JOURNAL OF HOSPITALITY & TOURISM RESEARCH

quality play a significant and determinative role in the reviewer’s perceptions of 

value for a given hotel. If a hotel improves Comfort by 20%, and the customer’s 

perceived value corresponds to a 4% increase, then room rates priced 165% 

lower would be perceived as offering the same amount of value.

To calculate QualityRating, we carried out a further factor analysis to extract 

a component as a measure of perceived service quality. Table 4 shows the 

results. The results confirmed the existence of Factor I with eigenvalue greater 

than 1.0 that accounted for 62% of the total variance (see Table 3).

The estimate of perceived service quality used in this study was the following:



QualityRating = 0.342(Comfort 

− 3.92)/0.904 + 0.253(Location − 4.01)/0.883 +  

 0.336(Cleanliness 

− 4.06)/0.862 + 0.282(Service − 3.91)/0.931 

(6)

The results of the analysis of price effects on perceived quality are presented 



in Table 5. The analysis indicates that the model is a good fit, with a highly 

significant likelihood ratio (p = .000) and R

2

 of 0.112. Also, the coefficient of 



price is positive and significant (p < .05). Thus, Hypothesis 2 is also supported.


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