Examining the determinants of room rates for hotels in capital cities: The Oslo experience
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Examining the determinants of room rates for
hotels in capital cities: The Oslo experience
Christer Thrane
Received (in revised form): 7th November, 2006
Department of Social Sciences, Lillehammer University College, 2626 Lillehammer, Norway.
Tel: þ 47 61 28 82 47; Fax: þ 47 61 28 81 70; E-mail: Christer.Thrane@hil.no
Christer Thrane is Professor of Tourism in the what causes room rates to diverge. In this
Department of Social Sciences at Lillehammer respect, the multidimensional concept of
University College, Norway. His research quality is expected to be associated with hotel
interests include, among other things, quanti- prices in a more or less linear fashion: a higher
tative research in the areas of tourism, quality equals a higher price. In other words,
hospitality and recreation. The author would price differences between hotels signal quality
like to thank Jo Kleiven and the anonymous differences between hotels. In a related manner
reviewers for valuable comments to an earlier the presence or absence of various hotel
draft of this paper and Tone Kvamme and attributes (eg, a spa, a restaurant, a central
Guro Larsson for excellent research assis- location etc.) will be among the factors that
tance. The usual disclaimer applies. most people will expect to influence hotel
room prices. In addition, it stands to reason that
ABSTRACT lodging in hotels possessing many desirable
KEYWORDS: hotels, Oslo, room rates, price attributes will be more expensive than lodging
hedonics, SUR in hotels in which few or no such attributes
are present. This paper is concerned with
Price hedonic theory states that the price for a product the prices consumers pay for staying in
may be thought of as an additive function of the various the various hotels in the proximity of the
utility-bearing attributes embedded in the product. Norwegian capital of Oslo. In particular, it
Within this framework, the present study demonstrates examines how a number of these hotels’
how the room rates for hotels in and around the attributes explain variation in the room
Norwegian capital of Norway can be linked to certain rates for single and double rooms. The
hotel attributes. Seemingly unrelated regression (SUR) theoretical foundation for this research ques-
models incorporating nine hotel attributes explain tion is found in the price hedonic literature. In
about 70% of the variation in room rates. Of particular general terms, the results of price hedonic
importance in this respect, are the attributes mini-bar, studies may have important implications for
hairdryer, free parking and distance to downtown. consumers who want to compare the ‘marginal
Journal of Revenue and Pricing Management (2007) 5, utility’ of different product attributes. As such,
315–323. doi:10.1057/palgrave.rpm.5160055 the results shed light on which (hotel) attributes
they have to pay extra for and which (hotel)
INTRODUCTION attributes can be bought without a price
It is common knowledge that the prices people surcharge. The flip side of this, however, is
have to pay for accommodation in hotels vary that the findings also can be used by the
enormously. Furthermore, most people prob- hospitality industry to enhance their strategic
ably possess a more or less accurate intuition of pricing.
& 2007 Palgrave Macmillan Ltd, 1476-6930 $30.00 Vol. 5, 4 315–323 Journal of Revenue and Pricing Management 315Examining the determinants of room rates for hotels
THEORETICAL FRAMEWORK AND Skidmore (2003) scrutinised how a number of
PRIOR RESEARCH hotel attributes could be linked to room rates
Price hedonic theory states that the price for a local US market. Finally, Coenders et al.
of a product can be regarded as a function (2003) examined how hotel room prices in the
of its immanent attributes or characteristics sun-and-beach segment in the Mediterranean
(Lancaster, 1966; Rosen, 1974). Typical appli- region were influenced by a number of hotel
cations of the theory involve the price of attributes.
residential properties (Fujita, 1989), whereas In a related spirit, a number of papers have
more esoteric applications concern that of sought to determine how prices for (all-
Bordeaux wine (Combris et al., 1997). In the inclusive) package holidays are affected by
case of residential properties, the sale price of a hotel characteristics and related features (eg,
house can be regarded as an additive function Sinclair et al., 1990; Aguilo et al., 2001, 2003;
of its size, number of rooms, amenities, Papatheodorou, 2002; Espinet et al., 2003;
neighbourhood quality and proximity to key Thrane, 2005). Also, Roubi and Litteljohn
institutions. By the same logic, a wine’s district (2004) developed a regression model within a
of production, vintage and subjective quality price hedonic framework to explain the
(assessed by taste panels) will to a large degree variation in sales prices for hotel properties
determine its sale price. In other words, sold in the UK between 1996 and 2002.
hedonic price analysis assumes that the price
of a product or a service is a function of a THE PRESENT STUDY
bundle of attributes. Based on the general ideas embedded in price
A few studies with a focus on the determi- hedonic theory and its prior hospitality and
nants of hotel room prices or room rates have tourism applications, there is ample evidence to
adopted the framework described above, albeit suggest that the presence or absence of certain
to varying degrees. Carvell and Herrin (1990) hotel attributes affect the room rates faced by
showed that price variations among hotels in consumers when they make their decisions
San Francisco were attributable to features such regarding hotel accommodation. Formally,
as location and other hotel characteristics. In a the determinants of the room rate (R) a
similar vein, Bull (1994) scrutinised how consumer must pay for a hotel stay is a function
certain locational and site-specific attributes of various objective hotel attributes (O) (eg,
affected motel room prices in Ballina, Australia. type of board; distance to downtown; presence
The small number of hotels/motels included in of swimming pool, bar and restaurant etc.)
these studies (20 and 15, respectively), how- and, possibly, more subjective attributes (S)
ever, precluded any certain generalisations. Wu (eg, service quality; hotel star rating;
(1998) examined whether chain-associated atmosphere etc.). Accordingly, the room rate
motels in Arkansas and Kansas were more for the ith hotel stay (Ri) can be described as
expensive to stay in than their non-chained Ri ¼ P(Oi, Si) where both Oi and Si are vectors
counterparts. More recently, Israeli (2002) of attributes. Ordinary Least Squares (OLS)
studied how hotel room prices in Israel were regression or the related log-linear form have in
influenced by hotels’ star rating, number of prior hospitality or tourism applications mostly
rooms and corporate affiliation (ie, chain been used to estimate this type of hedonic price
association). In a related manner, White and model.
Mulligan (2002) demonstrated how attributes As there exists no official star-rating classi-
such as presence of a pool and a spa, as well as fication for the hotels that make up the data in
climatic and locational features, affected the this study, the subsequent analysis focuses solely
hotel room rates in four southwestern US on objective attributes. At first glance this
states. Using the same approach, Monty and might appear as a limitation because most
316 Journal of Revenue and Pricing Management Vol. 5, 4 315–323 & 2007 Palgrave Macmillan Ltd, 1476-6930Thrane
previous scholars have included both star rating reasons for why the data could not be
and objective attributes in their price hedonic envisioned as a random sample from a universe
regressions. However, as argued by Papatheo- of hypothetical cases (Henkel, 1976).
dorou (2002) and Thrane (2005), using star The two dependent price variables in
rating as an independent variable alongside the study were the weekday rates in March
objective attributes amounts to a specification 2005 for a one-night stay in a single or a double
error because star rating is an endogenous room. It is important to note that these
independent variable. The simple reason for room rates do not necessarily reflect the price
this is that the star rating variable becomes a consumers actually pay because stays booked a
function of objective attributes to a substantial long time in advance usually are bought
degree, in much the same sense as price. at discount prices. As the hotels or hotel
Another problem that arises with this proce- chains set their prices in advance, however,
dure is that it likely will cause multicollinearity they signal hotel quality. For this reason it is
in many cases (ie, high correlations between the unproblematic to use these ‘price-proposals’ as
independent variables). Thus, the lack of an dependent variables within a price hedonic
official star rating classification for the hotels in framework (cf. Israeli 2002; Papatheodorou
the data does not create problems in the present 2002). Table 1 presents descriptive statistics for
context. these dependent variables, both in level and
In summary, prior research has clearly logged form. Table 1 also presents descriptive
demonstrated that the prices faced by con- statistics for the attributes or independent
sumers in their choice of accommodation variables considered in the study. One parti-
depend on the attributes embedded in the cular problem with price hedonic theory is
lodging facilities. In line with this research the that it offers few theoretical guidelines for
purpose of the present study is to examine the selecting independent variables (Andersson
relationships between a number of hotel 2000). The selection of independent variables
attributes and room rates in and around the in the present context was based on the
Norwegian capital of Oslo. research cited above, and in particular on
the list of relevant attributes compiled by
Data Espinet et al. (2003). The information about
The data for this study were extracted from the the attributes were mostly gathered from
Internet-based search engine for hotels in the various hotels’ websites, but in some
Norway in March 2005 (www.hotell.no). instances obtained through phone calls.
Originally 88 hotels came up on this list. Seven It should be mentioned that the attributes
of these lodging premises could, however, not considered in this study also included the
be classified as hotels and were therefore features that are regularly quality-tested
discarded from the sample. Furthermore, in Norway’s leading financial newspaper,
because an important aspect of hedonic price Dagens Næringsliv (DN). Two attributes —
modelling is to make sure that the data TV in hotel room and Internet access — where
are homogenous enough to make relevant present in 72 out of the 74 hotels. As these
comparisons, seven more hotels that could be two attributes for all practical purposes
classified as either very influential cases or as came close to being constants, they were not
outliers were deleted from the sample. Thus, included among the independent variables/
the present analysis is restricted to 74 hotels. attributes in the analysis. It should be noted that
Arguably these data come closer to a popula- the mean values of the binary independent
tion than to a sample. Nevertheless, the use of variables in Table 1 indicate the proportion in
significance tests was deemed appropriate in the the data where the attribute of interest is
statistical analysis since there were few obvious present.
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Table 1: Descriptive statistics for study variables (N=74)
Variable Description of variable/attribute Mean Standard
deviation
RSING Room rate per night for single room (NOK) 1001 295.8
RDOUB Room rate per night for double room (NOK) 1247 360.9
LogRSING RSING, logged 6.86 0.331
LogRDOUB RDOUB, logged 7.08 0.306
CHAINa Hotel is associated with a chain (yes=1) 0.810 0.394
MINIBARa Mini-bar is present in hotel room (yes=1) 0.757 0.431
POOLa Pool is present in hotel (yes=1) 0.176 0.383
PARKFREEa Free parking space is present in hotel (yes=1) 0.500 0.503
RESTAUa Restaurant is present in hotel (yes=1) 0.649 0.480
HAIRDRYa Hairdryer is present in hotel room (yes=1) 0.838 0.371
ROOMSERVa Room service is present in hotel (yes=1) 0.338 0.476
DIST Distance in kilometers to Oslo Central Station 11.89 14.64
BEDS Number of beds in hotel 257.7 191.5
a
Indicates a binary variable (ie, an attribute). The mean value refers to the proportion in the data where the
attribute of interest is present.
Estimation superior compared with two sequential OLS
Most previous price hedonic research has regressions in terms of obtaining statistical
followed Rosen’s (1974) original advice and efficiency (Zellner, 1962). Thus, the estimation
used the log-linear specification instead of the of the two regression equations was carried out
linear one. Following convention, therefore, by means of Zellner’s seemingly unrelated
the natural logarithms of the two room rates regression (SUR) approach. Another advantage
were used as the dependent variables in this of the SUR technique is that it permits testing
study. An additional advantage of the log-linear for significant differences in regression coeffi-
form compared to the linear, is the former cients between the two equations.
technique’s ease of interpretation. In general
log-linear regression coefficients can be inter- Results
preted as the percentage change in the The results of Table 1 show that the mean rate
dependent variable associated with a one-unit for a one-night stay in a single room is 1,001
increase in the independent variable. Unfortu- Norwegian crowns (NOK). The similar
nately, dummy coefficients and large coeffi- rate for a double room is 1,247 NOK (as of
cients (ie, coefficients >0.20) do not permit this 11 May 2005, 1,000 NOK was the equivalent
straightforward interpretation. In this case, the of 80.09 h). The respective median values are
percentage difference between the character- 1,000 and 1,250 (results not shown). The
istic of interest and the reference category is bivariate correlation between the two price
obtained by taking the antilog of the coefficient variables is 0.89 (Po0.01). In other words, the
minus 1 (Halvorsen and Palmquist, 1980). rate differences between single and double
A priori it was expected that the two rooms are fairly constant for the hotels in
dependent price variables in this study were question. Table 2 shows how the two room
likely to be correlated. In such instances, a joint rates are affected by the various attributes listed
estimation of the two regression equations is in Table 1.
318 Journal of Revenue and Pricing Management Vol. 5, 4 315–323 & 2007 Palgrave Macmillan Ltd, 1476-6930Thrane
Starting with the single room rates (ie, As to the coefficients for double room prices
LogRSING), we see that the room rates in (ie, LogRDOUB), we see that, contrary to the
hotels associated with chains are about 15% results for single rooms, a chain association does
more expensive than the room rates in non- not have an effect on the rates for double
chained hotels, ceteris paribus. Similarly, the rooms. By contrast, the effects of MINIBAR,
rates for rooms that include mini-bars are about PARKFREE, HAIRDRY and ROOMSERV
39% higher than the rooms not offering are very similar for single and double room
this facility (exp. (0.329)1 ¼ 0.389). Also, rates. In passing, it is also interesting to note
room rates in hotels where free parking is that the effect of MINIBAR on LogRSING is
available are about 19% higher than they are in significantly larger (F ¼ 3.04, Po0.10) than the
hotels that do not provide such a service, analogues effect on LogRDOUB. The greater
whereas hairdryers in hotel rooms drive up the the distance of hotels from Oslo Central Station
room rates by 44% compared with rooms (ie, downtown Oslo), the lower the prices for
where hairdryers are not available (exp. double rooms. For example, the room rate in a
(0.364)1 ¼ 0.439). Finally, room rates are, hotel located 30 km from Oslo Central Station
perhaps somewhat surprisingly, about is approximately 11% lower than the rate in a
12% lower in hotels offering room service hotel located only 10 km from this location,
than those that do not provide this feature. ceteris paribus (0.056 2 ¼ 0.112) (it is
The following attributes have no effect on also worth mentioning that the combined
the rates for single rooms: presence of swim- effect of DIST on LogRSING and Log-
ming pool in hotel (POOL), presence of RDOUB is statistically significant (F ¼ 7.58,
restaurant in hotel (RESTAU), distance to Po0.01)). All else being equal, the room rates
Oslo Central Station (DIST) and number of in larger hotels (as indicated by a greater
beds in hotel (BEDS). number of beds) are a bit more expensive than
Table 2: Room rates for one-night stay in single room (logged) and double room (logged) by
independent variables. Seemingly unrelated regression (N=74).
Independent LogRSING LogRDOUB F-test of model differences
variable
Coefficient Standard error Coefficient Standard error
CHAIN 0.147* 0.076 0.013 0.070 14.50***
MINIBAR 0.329*** 0.065 0.266*** 0.059 3.04*
POOL 0.065 0.068 0.075 0.062 0.804
PARKFREE 0.193*** 0.047 0.186*** 0.043 0.794
RESTAU 0.005 0.059 0.021 0.054 0.613
HAIRDRY 0.364*** 0.076 0.387*** 0.070 0.584
ROOMSERV 0.123** 0.051 0.127*** 0.047 0.896
DIST ( 10) 0.026 0.016 0.056*** 0.015 10.90***
BEDS ( 100) 0.003 0.014 0.022* 0.013 5.58**
Constant 6.13*** 0.068 6.50*** 0.063 91.40***
R2 0.703 0.705
Note: see Table 1 for variable definitions and descriptions. Breusch-Pagan test of independence between
regression equations: w2 (1 df)=51.75; Po0001, *Po10, **Po05, ***Po01 (two-tailed tests).
& 2007 Palgrave Macmillan Ltd, 1476-6930 $30.00 Vol. 5, 4 315–323 Journal of Revenue and Pricing Management 319Examining the determinants of room rates for hotels
those in smaller hotels. For example, the room variables are set to their modal values, whereas
rate in a hotel with 500 beds is about 9% higher BEDS is set to its mean value (see Wooldridge
than the rate in a similar hotel with 100 beds (2000, p. 203–204) on how to transform a
(0.022 4 ¼ 0.088). It is also worth pointing logged dependent variable into a level-form
out that the effects of DIST and BEDS are dependent variable).
significantly different for the two regression The explained variances in both of the
equations (F ¼ 10.90, Po0.01 for DIST; regression equations reported in Table 2
F ¼ 5.58, Po0.05 for BEDS). Just as for the (R2 ¼ 0.70) show acceptable model fit. Yet,
statistical explanation of LogRSING, the since the SUR regression was based on some-
independent variables POOL and RESTAU what few observations, a number of diagnostic
have no effects on LogRDOUB. Finally, the tests were carried out in order to examine the
Breusch-Pagan statistic is clearly significant. robustness of the findings. First, insignificant
This confirms that LogRSING and Log- RESET tests for misspecification (P>0.05 for
RDOUB are indeed correlated, and that the both equations) indicated that the models
two regression equations are not independent lacked no important explanatory variables.
of each other. In this way, the use of the SUR Second, insignificant Breusch-Pagan tests for
approach is clearly justified. heteroskedasticity (P>0.05 for both equations)
Especially two attributes have pronounced suggested that the variance in the data did not
effects on the rate for a stay in a double room: increase (or decrease) with price. Third,
MINIBAR and HAIRDRY. Figure 1, which both plots (available on request) and formal
also includes the variable DIST, displays this tests (Shapiro-Wilk W; P>0.05 for both
more clearly: The room rate in a hotel located equations) suggested that a normal distribution
50 km from Oslo Central Station in which for the residuals could not be rejected for any
neither a mini-bar nor a hairdryer are present is of the models. Fourth, multicollinearity is
about 650 NOK. By contrast, the analogues often a concern in regression models where
room rate in a hotel situated 10 km from Oslo many binary independent variables are present.
Central Station in which both of these As no Variance Inflations Scores (VIF) ex-
accessories are present is about 1,600 NOK. ceeded 2.06 for any of the independent
In Figure 1, the remaining binary independent variables and the mean VIF-score
was 1.63, multicollinearity was not a problem
in the present analysis. Finally, the estimations
1800 were also carried out using the so-called ‘robust
1600 regression’ procedure, and the results were
1400 similar to the reported ones. Thus, the results
Room rates for double rooms
1200 of these tests were all satisfactory.
1000
800 DISCUSSION AND CONCLUSION
600 During the last 15 years a number of hospitality
400 and tourism studies have been concerned about
200 how the utility-bearing attributes embedded in
0 lodging facilities are associated with the overall
0 10 20 30 40 50 price for such products. The theoretical frame-
Distance to Oslo Central Station in kilometers
work for these studies has generally been the
No mini-bar, no hairdryer Mini-bar, no hairdryer seminal work by Rosen (1974) on price
No mini-bar, hairdryer Mini-bar and hairdryer
hedonic theory. In general the results of this
Figure 1: Room rates for double rooms by three type of research tell consumers which attributes
hotel attributes they have to pay extra for, which attributes
320 Journal of Revenue and Pricing Management Vol. 5, 4 315–323 & 2007 Palgrave Macmillan Ltd, 1476-6930Thrane
result in discount, and which attributes located farther away from Oslo downtown (ie,
do not affect the price. At the same time, Oslo Central Station). Espinet et al. (2003) also
however, the providers of hospitality and found that parking was associated with hotel
tourism products may use such results room prices.
as a means for strategic pricing. The ambition Variables measuring aspects of location have
of the present research has been to examine in most of the prior research shown predictive
how certain hotel attributes are related ability with respect to lodging prices (Bull,
to the room rates for single and double rooms 1994; White and Mulligan, 2002; Monty and
in the region surrounding Norway’s capital, Skidmore, 2003; Thrane, 2005). In this study, a
Oslo. Most of the findings of this study locational effect was supported in the sense that
have been in general accordance with previous longer distances to Oslo Central Station (ie,
studies. However, some results were also downtown Oslo) were associated with less
unexpected. Below follows a recapitulation of expensive room rates (cf. Figure 1). Prior
the main findings and some comments in this studies have also found that hotels associated
regard. with a hotel chain (ie, corporate affiliation)
The two most important attributes in terms charge higher room rates than hotels with no
of explaining variance in room rates were the such associations (Wu, 1998; Israeli, 2002). The
presence or absence of the amenities mini-bars results of this study partially supported this
and hairdryers, as Figure 1 displays. It is also notion, as a chain-association only affected the
interesting to note that these two attributes are room rates in the expected way for single
the only ones that refer to the actual hotel rooms.
rooms, and not to the hotels themselves. Another novel, and to some extent un-
While the effect of hairdryers must be expected, result of this study was the effect of
considered as a novel feature of this room service on room rates. In this respect, the
study, Aguilo et al. (2001, 2003) also observed room rates in hotels offering room service were
the effect with respect to mini-bars. The about 12% less expensive than similar rates in
next interesting question to ask is whether or hotels not providing this service. At this point,
not consumers have the opportunity to the question of why this pattern was observed is
choose between hotels that do, or do not, only a matter of speculation. A preliminary
offer these amenities in their rooms. In conjecture would be that hotels offering room
other words, do consumers have real choices service anticipate that the income generated by
as regards saving money by choosing a this service will likely compensate for the lower
hotel that does not offer these facilities? A room rates. In addition, lower room rates will
quick glance at the data suggests that consumers by themselves likely attract more customers.
for most practical purposes face such a choice Obviously, however, more research is needed
to a somewhat limited degree, since as many 76 before any certain conclusions can be drawn in
and 84% of the hotels in the data offer, this regard.
respectively, mini-bars and hairdryers in their The following attributes did not appear to
rooms. have a bearing on room rates in any of the
Free parking was another attribute with a models: presence of swimming pool, presence
noticeable effect on room rates in this study. In of restaurant and, for all practical purposes,
all, 50% of the hotels in the data offered this hotel size (ie, number of hotel beds). As these
facility, so in this regard consumers have a real characteristics have all been identified as salient
choice as to saving money if they want to. in many prior studies, the lack of these
However, further analysis (results available on associations also beg an explanation. Based on
request) showed that presence of free parking the reasonable assumption that the hotels
was more frequently associated with hotels analysed in this study are characterised by a
& 2007 Palgrave Macmillan Ltd, 1476-6930 $30.00 Vol. 5, 4 315–323 Journal of Revenue and Pricing Management 321Examining the determinants of room rates for hotels
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