Annals of Tourism Research, Vol. 30, No. 2, pp. 342­352, 2003
 2003 Elsevier Science Ltd. All rights reserved
Printed in Great Britain
0160-7383/03/$30.00
www.elsevier.com/locate/atoures
doi:10.1016/S0160-7383(02)00059-2
HOTEL INVESTMENT IN OPEN AREA
Linda J. Cox
Gary R. Vieth
University of Hawaii, USA
Abstract: Environmental open space is difficult to define and value. This paper estimates
the rate of return on hotels' investment in open area for three locations in the State of
Hawaii, United States. The marginal revenue for open area investment is estimated using a
hedonic analysis of hotel room prices. The marginal cost of open area investment is adapted
from secondary data. The study reports on estimated return rates, which in two locations
are consistent with previous research and with the risk levels faced by hotels/resorts in
Hawaii. The lower rate of the third location appears to be the result of inaccurate expec-
tations about changing land values. Keywords: open area, rate of return, hotel characteristics,
Hawaii hotels.  2003 Elsevier Science Ltd. All rights reserved.
Résumé: L'investissement des ho^tels dans l'espace ouvert. Le terrain environnmental est
difficile a` définer et a` évaluer. Cet article estime le taux de retour sur investissement dans
l'espace ouvert de la part des ho^tels a` trois endroits dans l'état de Hawaii, aux Etats-Unis.
La marge bénéficiaire de l'investissement dans le terrain ouvert est estimée en utilisant une
analyse hédonique des prix des chambres d'ho^tel. La marge des cou^ts est adaptée des don-
nées secondaires. L'étude présente les bénéfices estimés, qui sont en accord avec la recher-
che antérieure dans deux endroits et avec les niveaux de risque qui sont recontrés par les
ho^tels/lieux de vacances a` Hawaii. Le taux moins élevé du troisie`me endroit semble e^tre le
résultat d'attentes inexactes au sujet des valeurs foncie`res changeantes. Mots-clés: espace
ouvert, taux de rapport, caractéristiques des ho^tels, ho^tels a` Hawaii.  2003 Elsevier Science
Ltd. All rights reserved.
INTRODUCTION
Environmental open area is difficult to define and hence to value
(Garrod and Willis 1992). As a result, analyses of investment in open
area are often skewed in favor of public, rather than private, costs and
benefits. The quantity and quality of environmental open area does
affect the value of property in residential and commercial real estate
markets (Anderson and Cordell 1988; Bookout 1994; Evans 1992; Gar-
rod 1994; Hensley 1994; Tyrvainen 1997). Lack of information about
returns on private investment may lead firms to select alternatives that
directly increase revenues, rather than environmental amenities that
Linda Cox is a Community Economic Development Specialist providing formal and infor-
mal instruction and conducting applied research in natural resource management, business
management, sustainable economic development, and human resource development in the
Department of Natural Resources and Environmental Management, University of Hawaii
(Honolulu HI 96822-2279, USA. Email <lcox@hawaii.edu>). Gary Vieth, in the same depart-
ment, is Assistant Researcher specializing in market and non-market valuation for environ-
mental and natural resources.
342
343COX AND VIETH
indirectly contribute revenue through increased consumer satisfaction.
For example, a hotel is more likely to develop a retail area that will
contribute directly to revenue, rather than installing a garden that will
require continued maintenance without generating direct sales. If
firms providing accommodations to tourists do not invest in environ-
mental amenities due to the lack of information and knowledge, the
tourism industry as a whole can suffer long-term consequences.
This paper estimates the rate of return on investment in open area
for hotels. Due to the large differences in the cost of land, observations
for the analysis are divided into three groups: Waikiki (City and County
of Honolulu), Hawaii County, and Maui County. The principles of
investment analysis are discussed and applied to hotel investment. Esti-
mates of the revenues and costs associated with providing open area
at hotels are used to calculate the rates of returns from investment in
this environmental amenity. To evaluate current levels of investment,
the estimated rates of return are then compared to reported rates for
hotel investments in general.
HOTEL INVESTMENT IN OPEN AREA
From an economic perspective, an investment's costs and revenues
are used to judge its desirability. An investment in product character-
istics is like any other, although estimates of the revenues and costs
associated with the investment are difficult to obtain. Investment by a
hotel in land can yield revenue directly if the land is developed for
commercial purposes. The land can also be developed to increase the
attractiveness of the environment surrounding the property, with the
value of the investment being reflected indirectly by the rooms' rental
rate. Investing in land to be used for this purpose depends an evalu-
ation of the revenues and costs associated with such an investment.
Revenues and Costs from Open Area
Consumers choose among products by weighing the product price
with their tastes and preferences to place a value on each characteristic
of the product (Lancaster 1971, 1991; Rosen 1974). They select the
combination of goods and services that provide the most benefit at the
lowest cost (Lancaster 1991). Hence, the value that consumers place
on the bundle of characteristics embodied in goods is reflected in the
prices that they are willing to pay for them. This relationship between
a product's price and its characteristics is the basis for a technique
called hedonic pricing. It can be used to statistically allocate the price
of a product among that product's characteristics.
To perform the hedonic analysis, each observation must contain the
same basic good with varying levels of the associated characteristic. For
example, equivalent rooms at different hotels will all have different
traits. These may include those of the rooms themselves and of the
building and grounds in general. In principle, if the group contains
enough goods with different combinations of characteristics, a relation-
344 HOTEL OPEN AREA
ship can be estimated using the price of a good as a function of their
various quantities (Freeman 1994).
Empirical application of hedonic price analysis is based upon two
important assumptions (Ladd and Suvannunt 1976). First, the charac-
teristics of the good do affect consumers' demand. Their quantity
obtained from a unit of the good multiplied by its unit value gives the
value that characteristic contributes to the good. The price of a good
is a function of the trait levels associated with that good. A consumer's
willingness to pay for the good, and hence its price, changes as charac-
teristic levels change. This value can be estimated by using regression
analysis to estimate the relationship between a product's price and
its characteristics.
A standard, double-occupancy hotel room with no ocean view and
no kitchen facilities is used as the good in this research. Its rate meas-
ured in US dollars per day is specified as the price of the good, or
dependent variable. Selecting measurable characteristics to use as
explanatory variables is more difficult. Goldberg, Green and Wind
(1984) use six general characteristics of a room in a conjoint analysis of
hotel amenities for business tourism. In addition to price, measurable
variables were included to represent atmosphere/facilities, room, asso-
ciated services, recreation/sports, lounge/entertainment, and security.
Interviews with Hawaii hotel managers, sales representatives, and staff
revealed that room-rate variables for tourists fall into three general
categories: location, physical ambience, and services. The character-
istics representing these categories include proximity to the ocean for
location; open area quantity, spa area, and swimming pool size and
quality index for physical ambience; and number of employees per
room for service.
The objective measurement of these variables merits further expla-
nation. Proximity to the ocean is assigned a value of two if the property
directly abuts the ocean, while those across the street from the ocean
are given a value of one, and all others are coded as zero. Open area
quantity is the total square footage of undeveloped space, where
developed space includes open parking areas and structures with at
least three walls and a roof. This variable is assumed to generate exist-
ence value, and is thus measured as the total area for the hotel. An
alternative specification was estimated using a per room figure, but the
coefficient was not significantly different from zero. This confirms the
expectation of an existence, rather than a use, value. On the other
hand, the pool and spa are assumed to generate use value, and the
measures incorporate the number of rooms. The pool index is a pro-
duct of the percent of actual services out of all possible pool services,
and the square footage of pool per room. Spa area is defined as its
square footage per room. Thus, dollars per day for a standard room
were estimated using regression analysis as a function of open area,
employees per room, pool index, spa area, and ocean proximity.
No clear guidelines exist on the choice of the appropriate functional
relationship between a room's rate and its characteristics. Other
researchers (Garrod and Willis 1992; Harris 1997; Ladd and Suvannunt
1976; Palmquist and Danielson 1989; Pompe and Rhinehart 1995;
345COX AND VIETH
Roka and Palmquist 1997; Tyrvainen 1997; Wheaton and Torto 1994)
use both linear and nonlinear relationships. Hartman (1989) shows
that an optimal product design exists in terms of characteristic levels
if a consumer's additional satisfaction decreases as more sought or con-
sumed (that is, as marginal utility for the characteristic decreases). This
condition ensures that the cost of the optimal level can be identified.
In this study, the natural logarithm of open area quantity is used to
allow for decreasing satisfaction with this characteristic, while the price
variable and other characteristics remain linear.
Data from a sample of hotels in Waikiki and Maui and Hawaii Coun-
ties were used to estimate the room rate and characteristics relation-
ship. About 100 hotels with 100 or more rooms that could be rented
on a daily basis were contacted to participate in the survey and the final
sample included 65 observations. The SHAZAM econometric package
(White 1997) was used to estimate the empirical relationship. Obser-
vations from different hotels for the same year are referred to as cross-
sectional data. A strong possibility of heteroskedasticity exists for cross-
sectional data, which means that the tests of significance may not be
reliable. The SHAZAM diagnostic (DIAGNOS HET) indicated that het-
eroskedasticity was present. Therefore, the SHAZAM OLS/HET pro-
cedure was used to estimate the hedonic price functions.
Table 1 presents the empirical results of the hedonic regression
analysis. The adjusted R2
presented in column six of the table indicates
that 71% of the variation in room rates is explained by the character-
istics included in the analysis. The F statistic in column seven shows
that this 71% is significantly different from zero in a statistical sense.
All the explanatory traits included in the analysis added value to rooms.
As indicated by Student t values, all except spa area contribute signifi-
cantly to room rate. While nearly all characteristics are significant, sub-
sequent discussion is limited to an open area because it is the focus
of this study. If only one variable is changing, estimation of its
incremental value using the appropriate regression coefficient in
Table 1 is possible.
The partial derivative of room rate with respect to open area is a
nonlinear relationship between the two variables, and measures the
increases in room rate as open area increases. The incremental value
of open area is in dollars per room per day per square foot. This num-
ber has little use when making decisions about providing open area
on the property. To translate the estimate into a more meaningful
figure, the number of rooms and average annual occupancy rate at a
typical operation are used to estimate the added revenue per acre.
Table 1. Results of the Hedonic Price Analysis
Statistic Ln Open Employees Pool Spa Ocean Adj. F Statistic
Area per Room Index Area Proximity R2
Coefficient 8.80 99.43 0.72 0.01 20.37 0.71 195.20
Student t 6.90 3.38 3.80 1.46 2.32
346 HOTEL OPEN AREA
Table 2 summarizes the calculations and gives annual revenue from
one acre. Columns one and two list average occupancy rates and aver-
age number of rooms that were used to obtain column three, average
room days of occupancy per year. Column four, annual revenue, is
average room days of occupancy multiplied by the value per room esti-
mated using the coefficient in Table 1. The annual revenue is then
divided by the acres in column six to determine the expected revenue
per year per acre given in the last column of Table 2. The revenue
per acre is expected annually for an indefinite period as long as the
appropriate maintenance is provided. These estimates are utilized later
in the analysis of return on investment.
Because previous studies find no evidence of economies or disecon-
omies of size with regard to the amount of landscaped area, the cost
of providing open area is assumed to be proportional to the amount.
For a linear cost relationship, the marginal cost is equal to the average
annual cost of maintenance. The average maintenance cost is used to
approximate the marginal or incremental cost.
The study used a uniform maintenance cost for types of hotel open
area, although maintenance costs may vary by type. The variable cost
of landscaping is based on the survey data of Cox, Hollyer and Schug
(1991) adjusted for inflation. Maintenance cost includes installation,
renovation, and daily care, including all purchased and rented inputs
such as labor, materials, plants and overhead. The data did not vary by
location, so the same figure of $10,900 per acre is used for all locations.
Investment Analysis
An investment is acceptable if the revenues it generates are greater
than its total cost, and not acceptable if they are less than the total
cost. However, the calculations needed to apply this criterion are com-
plicated because the revenues and costs occur at different times. Both
the revenues and corresponding maintenance costs are realized
incrementally over time. The cost of obtaining the land, however, is
incurred as a lump sum at one time. Money received or spent at differ-
ent times does not have the same value to people. Therefore, all rev-
enues are adjusted for investment analysis to reflect their value at the
same point in time, usually the present; this process is called present-
value discounting.
Table 2. Annual Revenue per Acre of Open Area
Location Occupancy Rooms Occupancy Revenue Open Area Revenue
(%) (no./hotel) (rm days/yr.) ($/hotel) (acre/hotel) ($/acre)
Waikiki 80 450 131,400 1,156,451 0.40 2,891,128
Hawaii 60 410 89,790 790,242 9.91 79,742
County
Maui 75 435 116,081 1,048,034 10.94 95,798
County
347COX AND VIETH
To apply the present-value investment analysis, all revenue and cost
estimates are discounted to the present using an appropriate discount
rate. However, empirical evidence indicates that rates of return on
hotel investment range from less than 8 to more than 15%, with one
extreme value of about 32% (Lesser and Rubin 1993). Given this large
variation, the rate-of-return approach may be more meaningful than
a present-value method to evaluate the investment.
Rate of return is determined by setting the discounted net revenue
stream equal to the investment opportunity cost. Annual revenue per
acre from open area for the three geographic areas from Table 2 is
presented in column one of Table 3. Annual variable cost in column
two is assumed constant at an estimated $10,900. The cost of invest-
ment is the opportunity cost of the land or, in a competitive market
like Hawaii, the market value of suitable land. Since land is assessed
at 100% of its value for the highest and best use, which equals market
value for real property tax purposes in Hawaii, these assessments were
used as the cost of land. The assessed value of land for all three coun-
ties was collected from the Real Property Division, Department of
Budget and Fiscal Services, City and County of Honolulu, with the per-
mission and cooperation of Maui and Hawaii Counties. Since the mar-
ket for land differs between the three locations, the assessed values
vary by location. Table 3 gives estimates of the gross revenue, variable
cost, net revenue, land cost, and rate of return on investment. These
results are within the range of overall rates of return reported for
hotels by Lesser and Rubin (1993). Currently, properties in Waikiki
and Hawaii County are estimated to earn about 15%, while those in
Maui County earn about 7%.
Waikiki and Hawaii County returns are near the top end of the range
reported by Lesser and Rubin, which is not surprising because tourism
in Hawaii is subject to a number of external factors. In addition, the
total investment required in Hawaii is significant, and occupancy
directly influences rates of return. Therefore, Hawaii hotels face sig-
nificant risks in their investment decisions and require a rate of return
sufficient to compensate for this risk.
The low 7% return in Maui County requires further explanation.
Evaluating the return depends on current as well as future economic
conditions. If the effect of inflation on revenues and costs is approxi-
mately the same, rate-of-return analyses are expected to yield approxi-
mately the same results at different points in time. The opportunity
cost of land, which is its market value in a competitive market, is
Table 3. Hotel Open Area Investment Revenues, Costs and Rates of Return
Location Revenue Variable Cost Net Revenue Land Cost Return Rate
($/acre/yr.) ($/acre/yr.) ($/acre/yr.) ($/acre) (%/yr.)
Waikiki 2,891,129 10,900 2,880,229 21,252,924 15.68
Hawaii County 79,742 10,900 68,842 530,125 14.92
Maui County 95,798 10,900 84,898 1,305,058 6.96
348 HOTEL OPEN AREA
assumed to be the cost of investment in open area. Therefore, an inves-
tigation of land prices will provide insight into changes in the opport-
unity cost of land in the three locations. Land values within the City
and County of Honolulu, and Maui and Hawaii Counties, are meas-
ured using aggregate property tax assessments. The City and County
of Honolulu is used here rather than Waikiki because of data avail-
ability, and because about 87% of the rooms in the City and County
of Honolulu are in Waikiki (DBEDT 2001). Because land prices tend
to move together, an aggregate property tax assessment is used here
as a proxy for the change in the opportunity cost of land. Growth in
tourism accommodation inventories was greatest prior to 1980, indicat-
ing that many investment decisions were made based upon economic
conditions at that time.
During the 70s in Hawaii, when many of the hotel investment
decisions were made, Maui County land prices were relatively lower
than in other locations. Since 1970, land values in Maui County have
increased more than twice as fast as those in the City and County of
Honolulu, and more than four times as fast as those in Hawaii County.
The greater increases in land prices on Maui are likely to have been
unanticipated, or Maui hotels would have been expected to adjust their
investment in land accordingly.
Variable and Model Specification
The rates-of-return estimates for open areas are generally consistent
with those for investment in general, which in open space appear to
be treated the same as other types. While the methodology described
here is demonstrated to be appropriate and applicable to similar invest-
ment analyses, it could be further refined. Hedonic price analysis
assumes that all subjects have the same preferences and willingness to
pay for a characteristic. This may not be the case in the current study.
Tourists may have different preferences and select their destinations
accordingly. This would result in a unique marginal willingness to pay,
and marginal revenue for each one. While the latter estimates could
be obtained for each individual using stated willingness to pay, the
estimates would be difficult to aggregate. Analyzing each destination
separately is a compromise, but further disaggregation may make it
impossible to obtain a significant hedonic price analysis. Additionally,
Purcell (1992) concludes that abstract landscape characteristics, which
are independent of a consumer's cultural affiliation or geographic
place of residence, do affect preference. Such tendencies for scene
types were found to be similar for all groups of participants looking
at a variety of scenes within and outside the home environment (Peron,
Purcell, Staats, Falchero and Lamb 1998).
At the same time, the model may not be accurately specified in terms
of variables included or functional form. The marginal revenue esti-
mated here would be consistently over- or under-estimated, ensuring
that the deviation would be in the same direction in every case. Prelimi-
nary research conducted to determine which traits are important to
consumers focused on characteristics in general; no query about spe-
349COX AND VIETH
cific ones was made. Therefore, the empirical estimation procedures
could be refined through further investigation of stated and revealed
consumer preferences for various characteristics.
Given the variety in hotels and consumers, measuring characteristic
levels remains a challenge. With regard to open areas, a large body of
research on the topic of landscape quality exists. However, the litera-
ture dealing directly with references for natural landscapes in an urban
setting is not extensive, and emphasizes the importance of nature in
such settings (Herzog 1989). Kaplan and Kaplan (1989) found prefer-
ences to be strongly affected by the context of the scene, with prefer-
ence correlating positively with vegetation. In contrast, the presence
of manmade objects was found to decrease the positive aesthetic
response to a view (Coeterier 1994).
Open area is considered a homogeneous characteristic in this study.
The literature indicates a preference for natural elements that obscure
manmade objects. Therefore, the quantity and quality of natural
elements, rather than generic open space, are more likely to be valued.
Interior or vertical uses of natural elements are other ways to enhance
values, particularly those in more urban settings such as Waikiki.
Further research is needed to determine tourists' valuations of differ-
ent types of open area, in order to predict how landscape design
elements will affect the value of a given amount.
The cost function used here is assumed to be linear, and the cost
of design and installation for open area is not included. More work
is needed to determine the exact nature of design, installation and
maintenance costs. Any investment in a landscape can be broken down
into these three cost components, and the return on investment in
any or all of them differs depending on the quantity and quality of
the initial and on going investments (Cox, Hollyer and Leones 1994).
For example, the cost of converting developed land back into open
area in Waikiki would differ significantly from the cost of converting
barren lava rock in Hawaii County. Therefore, open area creation may
not be feasible in Waikiki since land is extremely costly, making
interior or vertical landscapes the only alternative. In Hawaii County,
on the other hand, soil can be brought in to cover and plant the exten-
sive open spaces surrounding many resorts along the Kona coast.
CONCLUSION
Environmental open space is difficult to define and value, given the
complexities of estimating the marginal revenue and marginal cost of
hotel open area. This paper estimates the rate of return on investment
in open area at hotels and resorts in Waikiki, Hawaii County, and Maui
County. Hedonic price analysis is used to determine the marginal rev-
enue from open area, while costs were estimated from secondary data.
The estimated return rates for the three areas were 16, 15, and 7%,
respectively. The Waikiki and Hawaii rates are consistent with previous
research and with the risk levels faced by hotels and resorts in the
state. These results indicate that hotels are making rational decisions
regarding investment in open area. The possible exception of proper-
350 HOTEL OPEN AREA
ties on Maui can be explained by the long-term nature of the invest-
ment decision, and the observed change in the opportunity cost of
land over time. Maui's low rate appears to be the result of inaccurate
expectations about future land values that resulted in smaller returns
on investment in other locations.
As the world becomes increasingly developed, tourists will continue
to seek interaction with nature. The response of the tourism industry
to this preference will remain a prominent issue for research. The
industry likely will continue to maximize its return on investment by
providing open areas valued by tourists. At the same time, residents
are likely to encourage efforts to make tourism developments more
attractive. In Kauai County, for example, the planning commission
restricted hotel zoning by mandating maximum building heights and
the amounts of land that can be covered by buildings. The commission
also specified that parking areas and some buildings must be screened
and/or landscaped. In Waikiki, public open area in the form of mini-
parks has been a strong component of revitalization. The amount of
benefits that hotels in the area reap from these publicly sponsored
mini-parks is open to question. With slight modification, the method-
ology presented in this paper can also be used to analyze these types
of public policies and programs.
In other countries, where economies are less mature, or in more
rural areas, landscaping is likely to be more profitable than in tourism
destinations located in urban areas. Public decision-makers need to
consider the opportunity cost of land as an integral component in
public policies to support tourism development. Even if the opport-
unity cost of land is low, as is to be expected in some areas, capital
constraints may prevent private firms from investing in additional land.
If the tourism industry is unable to finance open-area investment, con-
sideration should be given to the provision of an environmental amen-
ity that can be experienced by tourists as a substitute. A
Acknowledgements--The Tropical/Subtropical Research Program of the United States
Department of Agriculture funded this work. The assistance of former graduate students
Frank Eastwood and Jeanmarie Foy is greatly appreciated.
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