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              315
Examining 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, 1476-6930
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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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Examining the determinants of room rates for hotels

              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.

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   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              319
Examining 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

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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        321
Examining the determinants of room rates for hotels

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