The international journal of tourism research tập 13, số 01, 2011 01 + 02

In Section 5: The Effects of Exchange Rates on Taiwan's Tourism, we examine the effects of foreign exchange rates on international tourist arrivals into Taiwan from major countries.. Bas

In this paper, we examine monthly tourist

arrivals from Japan, Hong Kong and the

USA between January 1971 and December

2008 Our purpose is to fi nd events or

variables that affect Taiwan’s international

tourism We fi nd that the Chinese New Year

has a positive effect on tourist arrivals from

Hong Kong, but negative effects for other

countries Through outlier detection, we

obtain a better understanding of the effects

of non-recurring events that have impacted

Taiwan’s international tourism Using

transfer function model with automatic

outlier detection and adjustment, we fi nd

that the exchange rate infl uences tourist

arrivals from Japan and Hong Kong

Copyright © 2010 John Wiley & Sons, Ltd.

Received 3 November 2009; Revised 22 February 2010;

Accepted 23 February 2010

Keywords: international tourism; Taiwan;

time series; calendar effects; outliers

INTRODUCTION

During the past 40 years, the economic

structure of Taiwan (the Republic of

China) has changed greatly It has

evolved from a mainly agriculture-based

economy in the 1970s to a technology-based

economy in recent years The rapid growth of

Taiwan’s economy inevitably gives rise to many new economic and societal issues, such

as a high demand for energy, increases in air and water pollution, and an M-shaped income distribution (i.e the rich gets richer and the poor gets poorer) To partially address such societal issues, the Taiwan government has refocused its attention on international tourism, which was overshadowed by manufacturing and technology-based industries in the past.More specifi cally, according to the statistical reports of the World Travel and Tourism Council, the annual output value of the Taiwan tourism sector amounted to US$19.7 billion in

2008 or 4.7% of Taiwan’s gross domestic product (GDP), which totalled US$419 billion According to the national statistics released by the directorate-general of Budget, Accounting and Statistics of Taiwan in 2007, the manufac-turing sector accounted for 23.76% of GDP In that same year, the agriculture sector accounted for only 1.45% of GDP Relatively speaking, the tourism sector is about one-fi fth of the size

of the manufacturing sector and is thus already

an important component of Taiwan’s economy.Globally, Taiwan has a moderate ranking in tourism According to the World Economic Forum (2009), the Travel and Tourism Competi-tiveness Index is composed of three major sub-indices of the travel and tourism sector, namely, the regularity framework sub-index, the busi-ness environment and infrastructure sub-index, and the human, cultural and nature sub-index Based on the index, Taiwan was ranked 30th in the Travel and Tourism Competitiveness Index among the 124 countries reported In compari-son, China was ranked 71st and Korea 42nd, while Japan was ranked 25th, Hong Kong the sixth and the USA the fi fth based on this index

and Joint Outlier Adjustments

Hui-Lin Lin1,*, Lon-Mu Liu2, Yi-Heng Tseng3 and Yu-Wen Su1

*Correspondence to: Dr H.-L Lin, Economics

Depart-ment, National Taiwan University, No.21 Hsu-Chow

Road, Taipei 100, Taiwan.

E-mail: huilin@ntu.edu.tw

In recent decades, there has been keen

inter-est in tourism studies in how tourism demand

is affected by various cultural, economic and

institutional factors, as well as major ‘one-time’

events In such studies, tourist arrivals have

been the most frequently used dependent

vari-able in quantitative analyses (e.g Martin and

Witt, 1989; Kulendran and King, 1997; Song and

Witt, 2006) Lim (1997) reviewed 124

tourism-related studies and concluded that 67 of these

studies used tourist arrivals and 54 used tourism

expenditures as the dependent variable Lim

(1997) also reviewed several commonly used

explanatory variables, such as income, relative

tourism prices, transportation costs, exchange

rates, the time trend, seasonal factors, economic

activity indicators, lagged dependent variables,

marketing and promotion, as well as various

qualitative factors Among such explanatory

variables, dummy variables were typically used

to deal with the infl uence of qualitative factors,

including well-known factors such as seasonal

variation (e.g Goh and Law, 2002; Hui and

Yuen, 2002) and ‘one-time’ events (e.g Ryan,

1993; Chen et al., 1999; Goodrich, 2001; Huang

and Min, 2002; Kim et al., 2006; Athanasopoulos

and Hyndman, 2008) Such an approach was

also used by Wang (2008) to study four major

local or international disasters potentially

rele-vant to Taiwan’s international tourism: the

Asian fi nancial crisis in 1997, the major

earth-quake on 21 September 1999 in Taiwan, the

ter-rorist attacks on 11 September 2001 in the USA

and the outbreak of severe acute respiratory

syndrome (SARS) in 2003

In most studies, traditional regression models

with dummy variables (e.g Witt and Witt, 1995;

Wang, 2008) or Autoregressive Integrated

Moving Average-related models (e.g Goh and

Law, 2002; Chu, 2008) were typically employed

Recently, a rough sets approach was used to

study tourism (Goh et al., 2008) It has the

advantage of being straightforward and directly

interpretable It considered various economic

and non-economic factors as well as month in a

year However, it did not consider effects

because of one-time events or calendar

varia-tion as shown in this paper In this paper, both

ARIMA and transfer function time series models

will be used Effects because of calendar

varia-tion are included in the models, and the

one-time events are handled through automatic

outlier detection and estimation in the context

of time series modelling

In this research, our primary interest is to study major factors or events that affect inter-national tourism in Taiwan Such factors or events may be classifi ed as recurring or non-recurring in nature Both will be studied in this paper On recurring factors, besides calendar variables, we focus on investigating the impact

of exchange rate as previous researches (see

e.g Crouch et al., 1992; Lim, 1997) demonstrate

that exchange rate has a signifi cant infl uence

on tourism However, they did not apply time series models using joint estimation of model parameters and outlier effects With rigorous time series analysis, these models will allow Taiwan to obtain information and knowledge

to better allocate its resource for promotion and expansion of international tourism as well

as providing a better ongoing tourism service.Before studying international tourism in rela-tion to Taiwan, we fi rst provide an overview of worldwide international tourism at both the national and regional levels in Section 2: Inter-national Tourism Worldwide and Taiwan This

is then followed by an introduction to the national tourist arrivals into Taiwan We have

inter-an extensive collection of monthly tourist als data into Taiwan from various countries and regions between 1971 and 2008, with each series having 456 observations In Section 3: Time Series Models for The Analysis of Taiwan's Tourism, Box–Jenkins time series models with calendar effects are introduced The parameters

arriv-of such models are estimated using a joint mation method of model parameters and outlier effects in Section 4: Analysis of Calendar Effects The effects of recurring and non-recurring events are presented and discussed in that section as well In Section 5: The Effects of Exchange Rates on Taiwan's Tourism, we examine the effects of foreign exchange rates on international tourist arrivals into Taiwan from major countries In Section 6: Discussion and Conclusion, we provide a discussion as well as the conclusion to this paper

esti-INTERNATIONAL TOURISM WORLDWIDE AND TAIWAN

Even though our primary interest is to study international tourism in Taiwan, it is

important to have a good understanding of

international tourism worldwide Table 1 lists

the annual tourist arrivals worldwide as well

as the tourist arrivals in several important

regions and countries Except for Taiwan,

tourist arrivals for the different regions and

counties are obtained from the World Tourism

Organization The annual tourist arrival data

for Taiwan are provided by the Tourism

Bureau, Ministry of Transportation and

Com-munications, China To facilitate a better

understanding of tourism growth in each

region/country, annual tourist arrivals are

indexed to 1995 levels (i.e the numbers in 1995

are set to 100) and displayed in Figure 1 (A,B)

The tourist arrival indices for the world as a

whole and the USA are displayed in Figure 1

(A,B) to facilitate the visual comparison

From Table 1 and Figure 1, we fi nd that the

Euro area accounts for more than one-third of

worldwide international tourism each year

and that the USA accounts for roughly 6–8%

of worldwide tourism However, the growth

of international tourist arrivals in the Euro

area, along with the growth in the USA, has

slowed substantially in recent years

Interna-tional tourism has grown at a signifi cantly

faster rate in Asia, including China, Japan and

the Association of Southeast Asian Nations

(ASEAN) area, despite the 11 September

ter-rorist attacks in 2001 and the SARS epidemic

in 2003 While the growth of international

tourism in Taiwan has been smaller in

com-parison with that in other countries or regions, the pace seems to have picked up following the SARS epidemic in 2003

In this study, our primary interest is to study major factors or events that affect international tourism in Taiwan Based on the total tourist arrivals data for 2008, the international tourists visiting Taiwan came primarily from the fol-lowing fi ve regions or countries: Japan (28.3%), Hong Kong (16.1%, including Macao), the ASEAN area (16.7%), the USA (10.1%) and Europe (5.2%) In Figure 2 (A), the total tourist arrivals in each month between January 1971 and April 2008 are displayed From this graph,

we fi nd that the total tourist arrivals exhibit a general upward trend While this trend was severely affected by the SARS epidemic in

2003, it resumed with higher growth following the SARS outbreak

As the total number of tourist arrivals is an aggregate of many time series, its properties are harder to interpret and less meaningful in their application To improve our study, tourist arrivals from major countries are displayed in Figure 2 (B–D) The solid lines in Figure 2 (B–D) represent monthly tourist arrivals from Japan, Hong Kong and the USA, the three prin-cipal sources of international tourism for Taiwan, and it is these that are the primary focus of this study The dashed lines in Figure

2 (C,D) represent monthly tourist arrivals from the European and ASEAN areas As these two series are also an aggregation of tourist arrivals

from various countries, they are not our focus

in this research study and are provided for

information only

Tourist arrivals from Japan, Hong Kong and

the USA were obviously impacted by the SARS

epidemic in 2003 However, their historical

temporal patterns are quite different The

average number of tourist arrivals from Japan

is much higher than that from Hong Kong and

the USA, but its growth rate has been much

smaller than the corresponding growth rates

for the other two areas in recent years The

numbers of tourist arrivals from the USA are

much smaller than the corresponding numbers

of arrivals from Japan and Hong Kong, but they display a persistent upward trend The numbers of tourist arrivals from Japan and Hong Kong have sometimes declined or have remained the same for extended periods of time

As in the cases of many other tourist arrival time series, the numbers of international tourist arrivals in Taiwan seem to fl uctuate season-ally We display the average monthly tourist arrivals into Taiwan from Japan, Hong Kong and the USA, as well as the total international

80 120 160 200 240 280

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Worldwide United States China

Japan Taiwan

(A)

80 120 160 200 240 280

1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Worldwide Euro Area

ASEAN United States

(B)

Figure 1 International tourist arrivals into various regions and countries ASEAN, Association of Southeast Asian Nations

tourist arrivals into Taiwan in Figure 3 Note

that the data for 2003 are excluded from the

monthly averages because the SARS epidemic

affected international tourism severely in that

year Except for October and December, the

seasonal pattern for total Taiwan international

tourist arrivals is very similar to the seasonal

pattern for Japan as Japan is the major source

of Taiwan’s international tourism

In the case of Japan, the numbers of tourist

arrivals are higher between January and March,

lower between April and October (with July

the lowest in a year), become higher in

Novem-ber and decline to a lower level in DecemNovem-ber

This pattern is rather different from the

inter-national tourist arrivals in the USA and Europe

where the summer months and Christmas

period tend to have higher numbers of tourist

arrivals The monthly tourist arrival pattern

for Japan may, to a large degree, be related to

the differences in climate between Taiwan and

Japan The climate in Taiwan between January

and March is much more temperate than that

in Japan and is thus more appealing to

Japa-nese tourists The summer months

(particu-larly between June and October) in Taiwan are

much hotter than in Japan and are thus less

appealing to Japanese tourists The climate in

Taiwan in November and December may be

warmer than in Japan, but Taiwan seems to

lose Japanese tourists to the USA/Europe in December As for Hong Kong and the USA, the tourist arrival patterns are somewhat different from that for Japan In these two areas, the summer months (June to August) and Decem-ber continue to have relatively high numbers

of tourist arrivals into Taiwan, and the tourist arrivals in October are particularly high because of the most important government-sponsored national holiday celebration that is held on 10 October each year

TIME SERIES MODELS FOR THE ANALYSIS OF TAIWAN’S TOURISMInternational tourist arrivals may be affected

by external factors that can be classifi ed as recurring variables and non-recurring events Non-recurring events, such as the 11 Septem-ber terrorist attacks and the SARS epidemic, can only be represented by discrete indicator variables Recurring variables such as exchange rates and other economic variables are data collected systematically and can be represented

by various forms of time series As tourist arrivals in Taiwan are compiled as monthly data, tourist arrivals may be infl uenced by cal-endar variation Calendar variation is recur-ring in nature, and it is very important to account for its effects in the analysis of monthly

0 50000 100000 150000 200000

0 20000 40000 60000 80000 100000

Worldwide Japan

Hong Kong United States

Month

Figure 3 Average monthly tourist arrivals into Taiwan (1/1971–12/2008, excluding the year 2003 because

of the severe acute respiratory syndrome epidemic)

use of these two calendars gives rise to

sub-stantial issues in the analysis of monthly time

series data for these countries The most

prob-lematic issue is that where important

tradi-tional festivals or holidays fall during different

Gregorian calendar months from year to year

For example, even though the Chinese New

Year is always on the fi rst of the fi rst month

each year according to the Chinese lunar

cal-endar, it may fall in either January or February

based on the Gregorian calendar As tourist

arrivals may be greatly affected by the Chinese

New Year, the observed time series may vary

substantially, depending on whether a

particu-lar month (January or February) includes the

Chinese New Year or not Such effects are

referred to as moving-holiday effects (Liu, 1980,

1986, 2006) In addition to moving holidays,

the number of tourist arrivals may depend on

the days of the week As the composition of

days of the week varies from month to month

and year to year, the observed series may be

affected by such variation as well Such effects,

which are by and largely because of the

com-position of trading days (or work days) in each

month, are referred to as trading-day (or

work-ing-day) effects (Hillmer et al., 1981; Hillmer,

1982; Bell and Hillmer, 1983)

A general time series model for

tourism analysis

Assuming that Yt is a time series that may be

subject to the infl uences of recurring variables

and non-recurring events, a general time series

model for Yt can be written as

,

a t ∼ 0 2 t 1 , n

(1)

where B is the backshift operator (i.e BYt =

Yt−1), C is a constant term, f(ω, Xt) represents

form as shown in Box and Jenkins (1976) The function f(ω, Xt) can be either in linear or non-linear form In this study, we consider a class

of linear and non-linear dynamic relationship

functions (often referred to as transfer tions) described in Box and Jenkins (1976).

func-Using the terminology of transfer function modelling (Box and Jenkins, 1976; Liu, 2006),

Nt is referred to as the disturbance or noise of

the model In the above model, Xt contains variables X1t, X2t, , Xmt that are used to char-acterise the effects because of various recurring variables, and ω is a vector of parameters refl ecting the effects of such variables Even though the effects because of non-recurring events (e.g the SARS epidemic, 11 September attacks, etc.) may be included in f(ω, Xt) with the X sit’ being indicator variables, it is more

fl exible to treat such events as outliers (Fox, 1972; Chang et al., 1988) Using an estimation

procedure developed by Chen and Liu (1993),

we can automatically detect outliers recurring events) and perform joint estima-tions of the outlier effects and model parameters Such an approach allows us to account for the effects of both known and unknown non-recurring events more effectively

(non-Model (1) can also be expressed in the lowing alternative form

of the model parameters

Time series models with calendar effects

We are interested in economic variables or certain tourism-related events that may affect tourist arrivals to Taiwan from a prospective

country/city To study the effects of such

vari-ables or events, we must include important

calendar effects in the model fi rst Calendar

effects are of interest in this study themselves

Furthermore, they also may be viewed as

important ‘nuisance’ effects that must be taken

care of before further econometric modelling is

conducted In addition to Chinese New Year

(referred to as H1t), there are two other major

moving holidays that potentially may affect

Taiwan international tourism These are the

Dragon Boat Festival (H2t) and the Autumn

Moon Festival (H3t) The Dragon Boat Festival

is on 5 May of the Chinese lunar calendar and

may vary between May and June of the

Grego-rian calendar The Autumn Moon Festival is on

15 August of the Chinese lunar calendar and

may vary between September and October of

the Gregorian calendar A model with such

moving-holiday effects can be expressed as

f(α β γ1, 1, 1,H1 t,H2t,H3t)=α1H1t+β1H2t+γ1H3t

(3)

if such moving-holiday effects are the same

over years (i.e staying constant), where the

variable Hit (i = 1,2,3) represents the proportion

of a particular holiday in the t-th month Here,

we assume that extra tourist arrival changes

(either increases or decreases) because of

Chinese New Year are distributed uniformly

during a 10-day period beginning 3 days prior

to the New Year and 7 days during the festival

As for the Dragon Boat and Autumn Moon

Festivals, we assume that the tourist changes

are distributed uniformly during a 5-day

period beginning 2 days prior to the festival

and 3 days over the duration of the festival

The assumptions for the length and effect

dis-tribution of the festivals are not crucial as most

of the festivals fall in the same months instead

of splitting across two adjacent months If

these moving-holiday effects increase (or

decrease) linearly over the years (i.e having an

upward or downward trend), then the

follow-ing model may represent the effects more

where Kt is 1 for all Kt in the fi rst year, 2 for all

Kt in the second year and so on

As for trading-day effects, the following model may be considered

where Wit, i = 1, 2 , , 7 represent the number

of Mondays, Tuesdays, and Sundays in the t-th month, respectively, and ξi, i = 1, 2, , 7 are the effects because of Monday, Tuesday, and Sunday To avoid multicol-linearity, it is desirable to restrict trading-day effects to vary around zero, or equivalently imposing ξ1 + ξ2 + + ξ7 = 0 Thus the model

in Equation (5) can be written as

−ξ2 −ξ6) In addition to D1t, , D6t, Hillmer (1982) and Bell and Hillmer (1983) include an additional term δ7D7t in Equation (6), where D7t

= W1t + W2t + + W7t is the length of a month The interpretation of δ7 depends on the form

of a model For a stationary time series, the δ7

parameter represents the average of daily effects and is used to adjust for the length of a month A similar interpretation holds if only the fi rst-order differencing operator (1–B) is present in the model However, when the model includes the seasonal differencing oper-ator (1–B12), the parameter δ7 refl ects the effect because of leap year that may or may not be important, and may be omitted from the model

in some situations

The model in Equation (6) implies that the trading-day effects are constant over time If the trading-day effects increase (or decrease) linearly from year to year, then the following model may be more appropriate:

(7)

Using the model identifi cation method

described in Liu (1986, 2006), we fi nd that the

disturbance term (Nt) in Equation (1) can be

for the monthly tourist arrivals from Japan,

Hong Kong and the USA as well as worldwide

monthly totals

ANALYSIS OF CALENDAR EFFECTS

To conduct a rigorous examination of the

potential calendar effects on tourist arrivals

into Taiwan from various countries (Japan,

Hong Kong and the USA) and worldwide, we

employ the calendar effect model with a trend

in Equation (8) and the disturbance model

in Equation (9) Both the original and

log-transformed series are examined The results

for these two scales (original and

log-transformed) are largely consistent and will be

presented using one or the other for the

purpose of simplifying the interpretation and

in order to increase clarity

As the tourist arrival time series in Taiwan

are all subject to outliers (e.g the SARS

epi-demic in 2003), the outliers must be identifi ed,

and their effects must be jointly estimated with

Furthermore, the Chinese New Year effects can

be simply represented by the trend parameter (α2) as the intercept parameter α1 is insignifi -cant Thus, the above calendar effects model can be simply expressed as

Yt =α2H1t×Kt+Nt (10)where Nt is the ARIMA model shown in Equation (9)

In the table below, we list the model eter estimates obtained by the joint estimation method of Chen and Liu (1993), where the critical value 4.0 is used for outlier detection Thus, major outliers such as those because of the SARS epidemic are automatically detected and adjusted during the joint estimation of model parameters and outlier effects Here, a larger critical value for outlier detection is used

param-as the series are long and we are only at the stage of obtaining appropriate model param-eter estimates The number of outliers detected using this critical value for each model is reported at the end of each row in Table 2 A smaller critical value for outlier detection will be used later when we try to detect non-recurring events in the time series More of the details are discussed later in this section.The results in the above table show that, except for Hong Kong, international tourist arrivals decrease during the Chinese New Year period, particularly for tourists arriving from Japan Chinese New Year is the most impor-tant holiday for families to get together during the year Therefore, hotels are primarily booked

Table 2 Parameter estimates of models

α2 θ1 θ12 σa Number ofoutliersJapan −479.52 (t = −12.29) 0.48 (t = 10.93) 0.56 (t = 13.91) 4834.36 9

Hong Kong 233.90 (t = 8.93) 0.64 (t = 16.49) 0.56 (t = 13.04) 2981.74 10

USA −6.13 (t = −0.41) 0.70 (t = 19.88) 0.64 (t = 16.29) 1582.69 5

Worldwide −398.09 (t = −5.31) 0.49 (t = 11.58) 0.67 (t = 17.68) 8686.26 9

by domestic customers, leaving little

availabil-ity for international tourists to book a hotel

Because of family ties between residents in

Hong Kong and Taiwan, tourist arrivals from

Hong Kong increase, rather than decrease

Outlier detection and estimation

In outlier detection and estimation in time

series, four basic types of outliers are typically

considered (Chang et al., 1988; Tsay, 1988)

These are additive outliers (AO), level shifts

(LS), temporary changes (TC) and innovational

outliers (IO) Other types of outliers can usually

be expressed as combinations of these four basic

types Details regarding the mathematical

for-mulation of models for these outliers and their

meanings can be found in Liu and Hudak

(1992), Chen and Liu (1993) and Liu (2006)

The benefi ts of time series outlier detection

and estimation are not limited to providing

better estimates of model parameters More

importantly, outlier detection often leads to the

discovery of events that may provide useful

information or knowledge (see, e.g Liu and

Chen, 1991; Chen and Liu, 1993) Thus, outlier

detection can also be used in time series data

mining (Liu et al., 2001) For such applications,

we retain the same estimates of the model

parameters but choose a smaller critical value

for outlier detection so that more outliers can be

detected In this study, the critical value 2.5 is

used, and only the AO, TC and LS outliers are

considered in the outlier detection Fewer outlier

types are employed here to avoid spurious

out-liers and misspecifi ed outlier types We detect

29 outliers for tourist arrivals from Japan, 30 for

Hong Kong, 29 for the USA and 40 for all tourist

arrivals into Taiwan These outliers and their

related estimates are listed in Table 3 As AO

affect only one observation, AO are not shown

in Table 3 if their t-values for all four series are

less than three This allows us to have a more

concise table and a sharper focus on identifying

events that have occurred around the time that

the major outliers were detected

In Table 3, brief descriptions of events that

may be relevant to the outliers are also listed

However, for some outliers, particularly those

that have occurred in the more distant past, it is

diffi cult to fi nd associated events because of

incomplete documentation or lack of

informa-tion For outliers that had been associated with a particular event, we fi nd that most events can explain the effects of the outliers well and reveal interesting information For example, we fi nd that the fi rst major energy crisis had more of an impact on tourism than the second major energy crisis, and tourists from countries located farther from Taiwan were impacted more than tourists from countries geographically closer to Taiwan (e.g US tourist arrivals were more affected than tourist arrivals from Japan) Recent wars (February 1991, October 2001 and March 2003), even though they occurred in the Middle East, still affected international tourism into Taiwan (shown as negative TC or AO), as wars threaten perceived travel safety The 11 September terror-ist attacks in the USA created a momentous change in the share of international tourism That

is, the share of international tourism shifted from Europe and the USA to Asia (as discussed in Section 2: International Tourism Worldwide and Taiwan) However, the event still negatively affected tourist arrivals into Taiwan (except for tourist arrivals from Hong Kong), but to a much lesser extent Undoubtedly, the SARS epidemic had a dramatic impact on international tourism

in Taiwan, in much the same way that it had on tourism in many other countries

Hong Kong tourist arrivals into Taiwan reached a peak in 1981 and then declined for the next 10 years until 1991 because of China’s efforts to entice tourists from Hong Kong and Macao beginning in the late 1970s It seems there were some attempts (e.g tourism promo-tions) to attract tourists from Hong Kong into Taiwan (shown as positive AO or TC), but such attempts did not reverse the overall decade-long decline As for the events sur-rounding Taiwan’s presidential election, the latest one in March 2008 was the most tense and attracted an increasing number of over-seas voters (shown as positive AO for the USA and positive LS for Hong Kong) Even though the voters were not counted as international tourists, their family members and friends may have been counted as such depending on the nature of their visas The newly elected government dramatically changed its policy towards, and relationship with, China This seems to have increased the tourist arrivals from Hong Kong substantially since the elec-tion took place (thus shown as positive LS)

occurred near the end of the series, hence, the

type and extent of its effect is more diffi cult to

evaluate (see, e.g Chen and Liu, 1993)

THE EFFECTS OF EXCHANGE RATES ON

TAIWAN’S TOURISM

Even though monthly time series data contain

rich information for various studies, it is not

appropriate to use such data directly when we

try to explore the relationships between tourist

arrivals and exchange rates This diffi culty is

partially because of the presence of seasonality

in monthly tourist arrivals, while exchange

rates are non-seasonal Fortunately, we have

38 years of data that allow us to use yearly time

series to explore such relationships The yearly

tourist arrivals from Japan, Hong Kong and

the USA, and their respective currency

exchange rates (indexed to 1971, i.e we set the

average exchange rate per New Taiwan Dollar

(NTD) in 1971 to 100 for each country/city) are

displayed in Figure 4 We shall use transfer

function models (also known as time series

regression models) to study the relationships

between tourist arrivals and exchange rates

To identify the transfer function models for

tourist arrivals from each country/city, we

employ the linear transfer function (LTF)

iden-and Liu (1993) is used Using the critical value 3.0 for outlier detection in the joint estimation,

we obtain the following models that best describe the relationships between the tourist arrivals and the exchange rates of each respec-tive country/city In the model below, we use

Yt to represent yearly total tourist arrivals and

Xt to represent yearly average exchange rates.Japan

σ

−−4 21 )

(11)Hong Kong

( 0 4957 ) n , σ 0 0764

== −( 2.36)

(12)USA

t = −3.58)Time = 33 (2003) TC (value = −0.450,

t = −5.00) AO (value t = −6.42)= −0.299,

AO, additive outliers; TC, temporary changes.

Tourist Arrivals Japanese Yen per NTD

Tourist Arrivals Hong Kong Dollar per NTD

1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

Tourist Arrivals US Dollar per NTD

(C) United States

Figure 4 Annual international tourist arrivals into Taiwan and exchange rates (indexed to 1971) NTD, New Taiwan Dollar

where ∇ is the fi rst-order differencing operator

(1-B) The outliers detected and their estimates

are listed in Table 4 and will be explained later

in this section

It is important to note that a logged time

series with fi rst-order differencing (e.g ∇ᐍn(Yt)

and ∇ᐍn(Xt)) is equivalent to a percentage

change for the time series Thus, the above

transfer function weights (similar to regression

coeffi cients) can be interpreted as elasticity.

In the above models, we see that tourist

arrivals into Taiwan from Japan and Hong

Kong are infl uenced by their respective exchange rates, but this is not the case for the USA For tourist arrivals from Japan, it takes a whole year to refl ect the effect of exchange rate changes The effect is that 1% increase in the NTD will reduce Japanese tourist arrivals into Taiwan by 0.7249% one year later For tourist arrivals from Hong Kong, it takes two to three years for the exchange rate changes to affect the tourist arrivals The total effect is that 1% increase in the NTD will reduce Hong Kong tourist arrivals by 1.05% (i.e 0.5529% +

upward trend and are not affected by NTD

exchange rates

In the above joint estimation of the model

parameters and outlier effects, a few major

out-liers are detected and listed in Table 4 The most

important one is because of the SARS epidemic

in 2003 The SARS epidemic had a negative TC

effect on tourist arrivals from Japan beginning

in 2003, and only had a one-year negative effect

(shown as AO) on tourist arrivals from the USA

SARS also had a negative impact on tourist

arrivals from Hong Kong However, the tourist

arrivals from Hong Kong decreased

substan-tially in 2002 for a number of reasons, causing

the drop in 2003 (SARS) to be less prominent so

that it is not shown as a signifi cant outlier In

addition to the SARS epidemic, there was a

negative TC outlier for the US tourist arrivals in

1979, which was because of the second energy

crisis (also see the discussion in Section 4:

Analysis of Calendar Effects)

DISCUSSION AND CONCLUSION

In this paper, we study major variables or

events that affect international tourism in

Taiwan In the analysis of the time series for

tourist arrivals, it is important to account for

both known and unknown events in the series

when estimating the models, or else the

esti-mates of the model parameters may be

seri-ously compromised For known events, both

moving-holiday and trading-day effects are

examined We fi nd that tourist arrivals into

Taiwan are affected by the Chinese New Year

each year, but not by other moving holidays

such as the Dragon Boat Festival or the

Mid-Autumn Festival The trading-day effects are

not found to be signifi cant for all tourist arrival

series that we examined We use an automatic

outlier detection method to detect signifi cant

unknown events (shown as outliers) and

employ a joint estimation method to obtain the

parameter estimates and outlier effects

Incor-arrivals that we studied, we fi nd that tional tourist arrivals into Taiwan are affected

interna-by the exchange rates of the respective country/city in the case of Japan and Hong Kong, but not in the case of the USA

Temporal data aggregation often results in a loss of information Higher frequency time series usually provide more information and are practically more useful than lower frequency time series (e.g monthly time series are often more informative than yearly time series) However, in some situations, it is necessary to use lower frequency time series because of noise

or seasonality in the time series In the transfer function modelling of tourist arrivals and exchange rates, we fi nd it is inappropriate to use monthly time series, and the use of yearly time series is more informative

REFERENCES

Athanasopoulos G, Hyndman RJ 2008 Modeling and forecasting Australian domestic tourism

Tourism Management 29: 19–31.

Bell WR, Hillmer SC 1983 Modeling time series

with calendar variation Journal of the American

Statistical Association 78: 526–534.

Box GEP, Jenkins GM 1976 Time Series Analysis:

Forecasting and Control 2nd edn Holden Day: San

Francisco, CA

Box GEP, Jenkins GM, Reinsel GC 2008 Time Series

Analysis: Forecasting and Control 4th edn Wiley:

Journal of Travel Research 37: 391–394.

Chu FL 2008 A fractionally integrated sive moving average approach to forecasting

autoregres-tourism demand Tourism Management 29: 79–

88

Crouch GL, Schultz L, Valerio P 1992 Marketing

international tourism to Australia Tourism

Management 13: 196–208.

Fox AJ 1972 Outliers in time series Journal of the

Royal Statistical Society, Series B 34: 350–363.

Goh C, Law R 2002 Modeling and forecasting

tourism demand for arrivals with stochastic

non-stationary seasonality and intervention Tourism

Management 23: 499–510.

Goh C, Law R, Mok HMK 2008 Analyzing and

forecasting tourism demand: a rough sets

approach Journal of Travel Research 46: 327–

338

Goodrich JN 2001 September 11, 2001 attack on

America: a record of the immediate impacts and

reactions in the USA travel and tourism industry

Tourism Management 23: 573–580.

Hillmer SC 1982 Forecasting time series with

trading day variation Journal of Forecasting 1:

385–395

Hillmer SC, Bell WR, Tiao GC 1981 Modeling

con-siderations in the seasonal adjustment of

eco-nomic time series In Proceedings of the Conference

on Applied Time Series Analysis of Economic Data,

Zellner A (ed.) US Department of Commerce,

Bureau of the Census: Washington, DC; 74–100

Huang JH, Min JCH 2002 Earthquake devastation

and recovery in tourism: the Taiwan case Tourism

Management 23: 145–154.

Hui T, Yuen CC 2002 A study in the seasonal

varia-tion of Japanese tourist arrivals in Singapore

Tourism Management 23: 127–131.

Kim HJ, Chen MH, Jang SS 2006 Tourism

expan-sion and economic development: the case of

Taiwan Tourism Management 27: 925–933.

Kulendran N, King M 1997 Forecasting

interna-tional quarterly tourism fl ows using error

correc-tion and time series models Internacorrec-tional Journal

of Forecasting 13: 319–327.

Lim C 1997 Review of international tourism

demand models Annals of Tourism Research 24:

835–849

Liu LM 1980 Analysis of time series with calendar

effects Management Science 26: 106–112.

Liu LM 1986 Identifi cation of time series models

in the presence of calendar variation International

Journal of Forecasting 2: 357–372.

Liu LM 2006 Time Series Analysis and Forecasting

2nd edn Scientifi c Computing Associates Corp.: Chicago, IL

Liu LM, Chen C 1991 Recent developments of time series analysis in intervention in environmental

impact studies Journal of Environmental Science

and Health A26: 1217–1252.

Liu LM, Hanssens DM 1982 Identifi cation of

multiple-input transfer function models

Com-munications in Statistics A11: 297–314.

Liu LM, Hudak GB 1992 Forecasting and Time Series

Analysis Using the SCA Statistical System, Vol 1

Scientifi c Computing Associates Corp.: Chicago, IL

Liu LM, Bhattacharyya S, Sclove S, Chen R, Lattyak

W 2001 Data mining on time series: an illustration

using fast-food restaurant franchise data

Compu-tational Statistics and Data Analysis 37: 455–476.

Martin CA, Witt SF 1989 Forecasting tourism demand: a comparison of the accuracy of several

quantitative methods International Journal of

Forecasting 5: 7–19.

Pankratz A 1991 Forecasting with Dynamic

Regres-sion Models Wiley: New York.

Ryan C 1993 Crime, violence, terrorism and

tourism: an accidental or intrinsic relationship?

Tourism Management 14: 173–183.

Song H, Witt SF 2006 Forecasting international

tourist fl ows to Macau Tourism Management 27:

214–224

Tsay RS 1988 Outliers, level shifts, and variance

changes in time series Journal of Forecasting 7: 1–20.

Wang YS 2008 The impact of crisis events and macroeconomic activity on Taiwan’s interna-

tional inbound tourism demand Tourism

Man-agement 30: 75–82.

Witt SF, Witt CA 1995 Forecasting tourism demand:

a review of empirical reseach International Journal

of Forecasting 11: 447–475.

World Economic Forum 2009 Travel and tourism

competitiveness report 2009 Third Travel &

Tourism Competitiveness Report in 2009, Jennifer Blanke: Latin America, Rio de Janeiro

Entrepreneurs provide the engine of

development, especially in economically

unstable times In Spain, rural tourism is

undergoing a boom, and the Internet plays a

vital role for tourism This study therefore

considers: (i) the importance of

entrepreneurial talent for implementing a

website; (ii) the relations among

entrepreneurial talent, website

characteristics and business performance;

and (iii) the moderating effect of

entrepreneurial experience Using a sample

of 150 rural tourism establishments in

Spain, this study reveals how website

content affects performance and how

experience moderates the relationships

between entrepreneurial talent and

performance, and between entrepreneurial

talent and website design Copyright © 2010

John Wiley & Sons, Ltd.

Received 8 July 2009; Revised 9 March 2010; Accepted 26

May 2010

Keywords: entrepreneur; talent; new

technologies; website; performance; rural

tourism

INTRODUCTION

The importance of entrepreneurial talent

Although investigations have focused on

entrepreneurship, generally referred to

as the creation of new businesses, for nearly a century, we still lack a consensus about its defi nition, which remains an obstacle

to developing a conceptual framework of entrepreneurship (Shane and Venkataraman, 2000) Various terms exist to refer to entre-preneurship, including entrepreneur,

en trepreneurial function and more recently, entrepreneurial orientation and entrepre-neurial talent The latter refers specifi cally to a person’s special ability for entrepreneurship.Further investigations of entrepreneurial talent are critical for several reasons Entrepre-neurs represent engines of sustainable devel-

opment in an economy (Huiyuan and Hua,

2008) Entrepreneurship also enables society to convert technical information into products and services (Shane and Venkataraman, 2000) Furthermore, through this mechanism, societies can discover and address temporal and spatial ineffi ciencies in the economy (Shane and Venkataraman, 2000)

In times of economic crisis, these arguments become even more pertinent, because entre-preneurship and entrepreneurial talent can help countries deal with declining incomes and profi ts

The importance of rural tourism

Rural tourism, defi ned as a tourism that takes place in rural areas, motivated by tourists’

Performance by Rural Tourism

Establishments in Spain

Jannine Nieto, Rosa M Hernández-Maestro and Pablo A Muñoz-Gallego

Salamanca University, Salamanca, Spain

*Correspondence to: Jannine Nieto, Departamento de

Administración y Economía de la Empresa, Campus

Miguel de Unamuno, Edifi cio F.E.S., 37007 Salamanca,

España.

E-mail: janninenieto@gmail.com

desire to understand this way of life and come

into contact with nature (Hernández-Maestro

et al., 2007), has reached a worldwide peak

with regard to its revenue-generating abilities

Many studies address its implications and

issues, and institutions such as the World

Tourism Organization offer seminars to

consider its current situation and future

prospects

Rural tourism is a widespread activity in

Spain, and in recent years, it has been

por-trayed as part of the portfolio of leisure and

recreation activities available in virtually every

region (Barke, 2004) Spain ranks among the

top three countries in tourism, generating

turnover of 66.4 million euros in 2004 and

experiencing continued strong growth For

example, compared with 2001, the number of

rural tourism establishments increased from

5497 to 13 887 in 2009 (National Institute of

Statistics (INE), 2010), and they offered a total

of 126 234 beds In terms of the number of

tour-ists, 2 708 000 travellers used rural tourism

accommodations in Spain in 2009, 90% of

whom reside within the same country and 10%

from abroad, producing a total of 7 902 000

overnight stays, with an average stay of 2.9

days each

Rural tourism provides an ideal focus for

research into entrepreneurship and

entrepre-neurial talent because of its growth, the large

amount of governmental support it receives

through subsidies and the changes the rural

population has undergone in the switch from

agriculture to rural tourism

The importance of the Internet

The Internet has become a vital tool in people’s

daily activities, whether focused on

profes-sional, educational or amusement and leisure

activities In 2004, the Internet had 215 million

users worldwide (Cyr and Trevor-Smith, 2004);

as of 2009, there were more than 1.6 billion

Internet users (CIA, 2009) In turn, it seems

logical that the numbers of people who use the

Internet to look for, plan and even purchase

tourism products also are increasing

According to the INE, in 2009, 51.3% of the

Spanish population between the ages of 16 and

74 years was already using the Internet A

study carried out in the context of rural tourism

also has revealed that 47% of travellers learned about the establishment they visited through the Internet (Hernández-Maestro, 2005)

With regard to the importance that neurs in this sector attach to the Internet, an

entrepre-Internet Week survey reported that

approxi-mately 60% of tourism companies (e.g travel agencies, bars, hotels, motels) regard the Inter-net as a ‘substantial’ tool for acquiring new customers (Mullen, 2000; Baloglu and Pekcan, 2006) In Spain, 86.5% of rural tourism estab-lishments have a website, 81.6% advertise on the Internet and most autonomous regions in Spain include on their sites an offi cial page for searching for accommodations, though only 35.7% of accommodations can be contracted online (INE, 2006)

As Porter and Millar (1985) state, these new technologies have changed ways to do busi-ness, altering the structure of the industry, such that every company must now under-stand how to use technologies to compete In addition, they provide tools to facilitate the competitive strength of small- and medium-sized enterprises (SMEs) in the global market (Quelch and Klein, 1996; Baloglu and Pekcan, 2006) Yet, some studies suggest e-commerce is not being adopted by SMEs as quickly as might

be expected (Beveren and Thomson, 2002).Despite the above evidence, we fi nd a dearth

of research studies that combine rural tourism and new technologies Thus, this is another reason that has motivated this study

Research objectives

We pursue three main objectives with this study: (i) to analyse the importance of entre-preneurial talent with regard to the introduc-tion of new technologies and specifi cally a website on the Internet; (ii) to examine the impact of both entrepreneurial talent and new technologies on business performance; and (iii) to examine the potential moderating role

of an entrepreneur’s experience on the effects

of entrepreneurial talent

The rest of this paper therefore is structured

as follows: fi rst, we present hypotheses derived from our literature review regarding the possible relationship among entrepreneurial talent, the implementation of websites and business performance; second, we describe the

Entrepreneurial talent

A person with talent has the intelligence,

ability and fi tness to perform a particular

activ-ity Talent means the person can do something

better than others without talent can

(Ingenie-ros, 1913) In this sense, talent is not

‘super-natural’; some people simply may possess

great intelligence, energy or other generally

valuable traits that enable them to become one

of the best in their chosen occupations, whether

work related or otherwise (Murphy et al., 1991)

The most talented people in a particular area

tend to choose occupations that will earn them

returns on their talent Similarly, companies

need talented employees to achieve their

business goals (Ricker and Leahy, 2009)

Furthermore, talent implies the person can

fi nish an activity that others would abandon or

never start Therefore, entrepreneurial talent

implies that the entrepreneur not only

con-ceives of a good idea but also implements it

fully

As we have noted though, the concept of

‘entrepreneur’ remains vague, contradictory

and imprecise in its various defi nitions (Shane

and Venkataraman, 2000; Rauch et al., 2009;

Thompson, 2009)

Gartner (1989), in a meta-analytic review of

the term, showed that throughout history,

researchers have attempted to defi ne what an

entrepreneur is instead of what that person

does Three main features have marked defi

ni-tions of entrepreneurship throughout history

though: innovation, the search for information

and making decisions under uncertainty to

earn profi ts

Innovation Some researchers limit the idea of

newness to opening a new business (Mescon

et al., 1981), even if others are already

exploit-ing that line of business Others argue that

newness requires the creation of a totally new

business (Hornaday and Aboud, 1971) and the

exploitation of an original idea Innovation

existing situation, which is usually referred

to as a proactive personality (Becherer and

Maurer, 1999; Rauch et al., 2009) In this sense,

entrepreneurship has been associated with the active search for and discovery of opportuni-ties Not everyone has this ability to discover opportunities in an environment (Kirzner,

1973; Federici et al., 2008).

Search for information The phrase ‘knowledge

is power’ is well known, but its practical cation to entrepreneurship is unclear Gather-ing information for decision making is a critical

appli-activity for an entrepreneur (Cooper et al.,

1995) Entrepreneurs reporting higher levels of information search intensity will identify more

business opportunities (Ucbasaran et al., 2008) Uncertainty Although uncertainty may seem

like the normal state of affairs during economic crises, it remains prominent for entrepreneurs even when the economy is stable Therefore, the ability to make decisions under uncertainty

is critical for entrepreneurs These decisions eventually focus on a specifi c objective: profi ts

(Hull et al., 1980; de Klerk and Kruger, 2002)

All decisions contain some risk, but neurs often face particularly risk with regard

entrepre-to their fi nancial, physical and/or social status

in their efforts to achieve profi t objectives (Hull

et al., 1980; Federici et al., 2008; Rauch et al.,

2009)

Considering these three elements and the concepts of entrepreneur and talent, we note that these terms are not substitutive but rather adjective and noun That is, entrepreneurial talent would mean a special ability for entre-preneurship, that is, for embarking on and exploiting new opportunities, searching for information and making decisions under uncertainty in pursuit of profi ts, while assum-ing implicit risks

Age, education and experience also have been studied as characteristics that infl uence

entrepreneurship Regarding age, the process

of cognitive development continues

through-out life (Baron, 2009); thus, age may affect

stra-tegic decisions In contrast, highly educated

persons are more receptive to new ideas

(Kim-berly and Evanisko, 1981; Hua et al 2000) and

tend to identify more business opportunities

(Ucbasaran et al 2008) Finally, experience

acquired from having started multiple new

ventures in the past offers benefi ts in terms of

developing contacts (Danson, 1999), gaining

knowledge about obtaining the most

appropri-ate sources of fi nancing (Starr and Bygrave,

1991), learning managerial and technical skills

necessary for leading new ventures and

iden-tifying ways to serve new and emerging market

segments (Wright et al., 1998).

Entrepreneurial talent and

website characteristics

Even after an exhaustive review, we found

little research regarding the relationship

between entrepreneurial characteristics and

the characteristics of the company websites,

despite the seemingly relationship between

them

The research that exists indicates that

talented employees lead to greater

commit-ment to innovation and technology by

com-panies (Murray-Leslie, 2009; WEDC, 2009)

The banking sector even aims to hire talented

people who can help drive technology

improve-ments (Murray-Leslie, 2009) Moreover,

according to the Washington Economic

Devel-opment Commission (WEDC, 2009), talent

and entrepreneurship are two key drivers of

an innovation economy On the other hand,

a proactive personality appears to have a

mediating role between strategy and

innova-tion in Internet (Kickul and Walters, 2002)

There may be talent in large and small

com-panies, though according to Ferrante (2005),

there should be more talent in big companies,

which manage more workers In contrast,

larger companies tend to be more sluggish and

driven by established systems and procedures,

such that talented employees have less room

to contribute than they would in small fi rms

Yet, large fi rms have adopted and noted the

value of websites (Ellinger et al., 2003) far more

than small businesses, as is the case in our

sample, which tend to use simple websites (Bernert and Stricker, 2001)

Even with simple websites, talented preneurs should recognise the importance of their websites for increasing consumer aware-ness Therefore, the characteristics of their websites should differ from those of websites posted by entrepreneurs with less talent We propose the following hypothesis:

entre-Hypothesis 1a: Entrepreneurial talent determines characteristics of websites

Entrepreneurial talent and business performance

Empirical evidence in various contexts strate that human capital is positively asso-ciated with benefi ts such as higher income

demon-(Boylan, 1993; Ucbasaran et al., 2008), tivity (Mincer, 1974; Becker, 1975; Ucbasaran et al., 2008) and objective quality (Hernández- Maestro et al., 2009), all of which should

produc-generate better business performance (Flynn and Saladin, 2001; Meyer and Collier, 2001)

In addition, in a meta-analytic review, Rauch

0.242) correlation between entrepreneurial orientation and performance

Objective performance measures, such as changes in sales and profi ts (Roper, 1998;

Becherer and Maurer, 1999; Ratchford et al.,

2003; Ferrante, 2005), have also revealed tive relationships with proactiveness, though

posi-in some cases, the relation is not signifi cant (Becherer and Maurer, 1999) Other per-formance measures include organisational strategies (e.g investments in new products, management, control), which also tend to produce positive and signifi cant results in combination with measures such as education, experience and proactivity (Roper, 1998; Kickul and Gundry, 2002) Other studies indicate that entrepreneurs who engage in more intense information searches identify more business

opportunities (Ucbasaran et al., 2008)

There-fore, we posit:

Hypothesis 1b: Entrepreneurial talent positively affects business performance

various classifi cations are available Bart et al

(2005) used seven categories: privacy, safety,

navigation, brand power, help in solving

prob-lems, purchase orders and customers’

testimo-nies Baloglu and Pekcan (2006) instead divided

the characteristics into two big groups, each

with subdivisions: design characteristics and

content characteristics Yoon (2002) also argues

that customer confi dence, which positively

affects behavioural intentions, depends on

three website characteristics: transaction

safety, Web page properties and navigation

This variety of classifi cations suggests

merging several concepts to evaluate Web

page characteristics for our research

Website characteristics and business performance

Some studies confi rm a relationship between

website characteristics and business

perfor-mance Ellinger et al (2003) found a positive

and signifi cant relationship between the

inter-active characteristics of the website (e.g

self-help, online transactions, online purchase

order, delivery) and company earnings Polo

and Frías (2010) summarised several studies

that show information and communication

technology deployment encourages

competi-tive actions and commercialisation in diffi cult

periods, especially for rural tourism

Furthermore, customers’ preference for a

website and behavioural intentions can serve

as measures of performance, because such

intentions should favour added sales In this

regard, prior studies demonstrated that

char-acteristics of the website (e.g links to customer

service, privacy policy, customer testimonies)

can have positive and signifi cant effects on

customer preferences for specifi c sites (Resnick

and Montania, 2003) Other studies similarly

found a positive and signifi cant relationship

between customer confi dence, as derived from

navigation ease, purchase orders and

problem-solving assistance and behavioural intentions

(Yoon, 2002; Bart et al., 2005).

positive infl uence of website characteristics on company performance, we propose the follow-ing hypothesis:

Hypothesis 2: Website characteristics

posi-tively infl uence business performance.

Entrepreneurial experience

Experience has long been studied as a teristic of the entrepreneur with a potential effect on performance or as a moderator of other relationships (Roper, 1998; Ferrante, 2005; Hmieleski and Baron, 2009) As we noted previously, experience helps to defi ne the capabilities of human capital, may be an antecedent of entrepreneurial talent and likely affects managerial performance (Van de

charac-Ven et al., 1984; Jo and Lee, 1996; Chandler and

Hanks, 1998)

Some studies demonstrate that the greater the experience of business professionals in a particular sector, the higher the income is for the company, growth rate of assets and growth rate of employees (Jo and Lee, 1996) An entre-preneur’s related business experience (before starting the company) should positively affect productivity (Harada, 2004)

In terms of the potential moderating role of experience, it should have a positive and sig-nifi cant infl uence on the relationship between the frequency of visits to the customer and sales effectiveness (Martín and Román, 2004) Prior experience with creating ventures may also moderate strengthening the negative rela-tionship between entrepreneurs’ optimism and performance (Hmieleski and Baron, 2009)

In contrast, some authors found no such nifi cant relation (Collins and Moore, 1964; Sandberg and Holfer, 1987; Jo and Lee, 1996)

sig-In the area of the new technologies, Wetering and Koster (2007) found no positive effect of experience on innovative performance Van de

Ven et al (1984) even suggested a negative

correlation between prior start-up experience

and overall performance

In our study context, more experienced

entrepreneurs tend to be older We anticipate

that their experience (longer in the business)

gives them greater knowledge that should

increase their chances of success However,

their age may make them less likely to use the

Internet, because older people generally are

less familiar with new technologies

Further-more, educational systems change over time

(Baron, 2009); as Polo and Frías (2010) assert,

there may be a lack of knowledge and training

in new technologies among older

entrepre-neurs, who may not have been exposed to

formal business education and instead acquired

their knowledge through the ‘school of hard

knocks’ Their experience with strong

perfor-mance does not involve the Internet, so they

may believe they do not need it We therefore

propose our fi nal hypothesis:

Hypothesis 3: The experience of

entrepre-neurs in the sector (i) mitigates the

relation-ship between entrepreneurial talent and

website characteristics and (ii) strengthens

the relationship between entrepreneurial

talent and company performance

METHODOLOGY

Data collection

We used a database that contained information

about a sample of rural tourism entrepreneurs,

gathered between August and October 2004

Participating establishments were rural houses

with a maximum of 24 beds that appeared in

Spain’s offi cial 2003 guide to rural tourism

The database contained data about the

charac-teristics of the entrepreneurs, which enabled

us to derive measures of their entrepreneurial

talent and experience, as well as the

character-istics of the rural establishment and business

performance, in 17 autonomous communities

in Spain (survey available on request from the

authors)

We also identifi ed rural tourism

establish-ments that posted information on the Internet,

whether through their own websites or on the

sites of other institutions A survey was applied

to the resulting sample of establishments

(available on request from the authors) that aimed to measure the design and content char-acteristics of their websites, during March and April 2007 Of the 219 observations in the origi-nal database, we obtained a fi nal sample of 150

participants (95%, p = q = 0.5 error = 7.74%).

We acknowledge that the time gap between the measurements of entrepreneurial talent and performance and website characteristics might imply that some of the information is not entirely accurate; some of the variables may have changed over time

Measures

In accordance with our literature review, we considered the intensity of the information search entrepreneurs undertake before making decisions as an important measure of entrepre-

neurial talent (Cooper et al., 1995; Ucbasaran

et al., 2008) Specifi cally, two items assess this

intensity: the number of trade fairs in the tourism industry that the entrepreneur attended in the previous 2 years and the pub-lications consulted in the last year The measure

of entrepreneurial talent therefore was limited

to information in the database Other variables also might serve to measure this construct, though we leave that effort to further research Moreover, in our study context, many entre-preneurs rely on relatively simple manage-ment practices, because their background is in agriculture or livestock practices Few of them have a business education, so being more active in information searching should dis-criminate effectively among entrepreneurs with more and less talent

To measure managerial performance, we consider various items in prior empirical literature A common distinction separates

fi nancial and non-fi nancial measures (Rauch

et al., 2009) Financial measures are popular

because they offer objectivity through items such as return on sales and return on invest-ment (Roper, 1998) In line with our literature review, (Roper, 1998; Becherer and Maurer,

1999; Ratchford et al., 2003; Ferrante, 2005), we

use two fi nancial measures: the level of annual income and the annual profi ts of the company Respondents indicated on a seven-point scale the range of income and profi ts, in euros, earned by their business establishment

(2) content characteristics: richness of

infor-mation offered.; and

(3) confi dence characteristics: technical confi

-dence the website inspires and opportunity

for interaction (e.g space for suggestions,

testimonies)

We used fi ve-point scales with objective

measures for most items For example, to

explain products and services they offered, the

respondents could choose from a range of

options, from none to all types of information

(e.g prices, number of rooms, room services,

other hotel services)

Finally and again based on our literature

review (Van de Ven et al., 1984; Martín and

Roman, 2004), to measure the respondents’

experience running this type of establishment,

we asked them to indicate the number of years

of practical experience they had in rural

housing or similar areas

Data analysis and results

The exploratory phase of our analysis, focused

on the data and relationships, relied on the SPSS

Inc., Chicago, USA (SPSS) 14.00 program We

continued with the confi rmatory phase, using

LISREL 8.54, a structural equation model that

can measure several relationships across

vari-ables simultaneously To estimate the model,

we used the robust maximum likelihood

Exploratory phase Sample representativeness

To confi rm that the sample was representative

of the broader population, we developed a

comparative chart We obtained similar results

in both groups, which indicate an absence of

bias and the representativeness of the sample

(Table 1)

Pilot test Subsequently, to demonstrate the

discriminatory power of the questionnaire that

measured website characteristics and confi rm

nate (professional Web, simple language, ability and consistency of the frame) and fi ve have very low loadings (ease of contracting, space to express opinions, information about owners, attention capture and related links) Therefore, we eliminated these variables from the study Because both variables measuring confi dence (reliability and space to express opinion) were eliminated, the construct disap-peared from our analysis The seven variables that remained loaded on two constructs: ‘Web design’ and ‘Web content’

reli-Therefore, we conducted an exploratory factor analysis on four constructs: Web design, Web content, entrepreneurial talent and per-formance (Table 2)

The analysis results in loadings greater than 0.7 for all the variables except one (address = 0.685); these excellent results far exceed the recommended minimum signifi cant factor loading of 0.45 for a sample of 150 observations

(Hair et al., 2001) The Kaiser–Meyer–Olkin

index is greater than 0.5 in all the cases, which indicates that the correlation matrix is correct for every construct Bartlett’s sphericity test shows a level of signifi cance within the accepted range (<0.05), so we can reject the null hypothesis of equality between the correlation matrix and the identity matrix, which would have made the factor model unsuitable The measure of sampling adequacy indicates the relation of every variable with the others; in all the cases, it is greater than the minimum of 0.3 The communalities are superior to 0.5, so all the variables are well explained by the factor The total explained variance is greater than 65%, and all the autovalues are greater than 1, which suggests every factor explains the vari-ance of at least one variable The Cronbach’s alpha is also greater than 0.6, so the individual indicators appear consistent in all the measures

The result of the exploratory factor analysis

is a general model, which represents the object

Table 2 Exploratory factor analysisVariable Load Cronbach’s alphaConstruct: entrepreneurial talent 0.612 Trade fairs 0.849

Publications 0.849Construct: Web design 0.795 Easy 0.837

Fast 0.900 Readability 0.770Construct: Web content 0.771 Multimedia 0.850

Prod-serv info 0.767 Contact 0.758 Address 0.685Construct: performance 0.807 Income 0.916

Profi ts 0.916

of this research, as we depict in Figure 1 The

model consists of four constructs that relate

through fi ve causal relationships:

entrepre-neurial talent–Web design, entrepreentrepre-neurial

talent–Web content, entrepreneurial talent–

performance, Web design–performance and Web content–performance The fi rst compo-nent of each relationship is the independent construct and the second is the dependent con-struct The potential moderating role of the

Table 1 Rural establishments by Autonomous Community*

Autonomous Community

Amount of rural establishments in Spain %

Amount of rural establishments, sample for study % Sample

Comparative between the total amount of rural establishments and used sample.

* Rural establishments for shared rent in Spain with a maximum of 24 accommodations.

Figure 1 General model.

entrepreneur’s experience appears in the

rela-tionships between entrepreneurial talent and

the other constructs

Regressions To confi rm that the proposed

relations might exist, we ran regressions for

the different relations between the

indepen-dent and depenindepen-dent constructs, using the

factor scores We fi nd a positive and signifi

-cant relation between Web content and

per-formance and between entrepreneurial talent

and performance

To estimate whether the entrepreneur’s

expe-rience moderates the relationships between

these constructs, we used the median of the

variable (6) and formed two groups: (i)

entre-preneurs with more experience (experience > 6); and (ii) entrepreneurs with less experience (experience ≤ 6) We observed a positive and signifi cant moderation of experience in the rela-tion between entrepreneurial talent and perfor-mance for those with more experience (Table 3)

Confi rmatory phase Measurement model fi t

First, we checked the fi t of the measurement model The extracted variance was higher than the recommended value of 0.60 for all the con-structs, and the compound reliability was greater than 0.70 All loadings between the variable and its construct were higher than 0.5,

in support of convergent validity (Table 4)

Table 3 Regressions

Relations

Without moderation(a) < Experience(b) > Experience(c)

load s R2 load s R2 load s R2

entrepreneurial talent — webdesign −0.02 0.42 −0.01 −0.15 0.10 0.01 0.14 0.14 0.00entrepreneurial talent — webcontent 0.08 0.16 0.00 0.06 0.29 −0.01 0.11 0.20 0.00entrepreneurial talent — performance 0.12 0.079** 0.01 −0.02 0.42 −0.01 0.27 0.014* 0.06webdesign — performance 0.03 0.35 −0.01

webcontent — performance 0.30 0.00* 0.08

(a) Regressions do not have the experience variable as moderator.

(b) Regressions for the less experienced entrepreneurs (experience < = median).

(c) Regressions for the more experienced entrepreneurs (experience > median).

* Correlation is signifi cant at level 0.05.

** Correlation is signifi cant at level 0.10.

s., signifi cance.

First-order confi rmatory factor analysis To

confi rm that the variables load on the

dif-ferent constructs, we conducted a confi

rma-tory fi rst-order factor analysis of the design

and content characteristics of the website We

obtained a good chi-square (χ2), with p > 0.2,

and a well-adjusted root mean squared error of

approximation (RMSEA = 0.041), as we show

in Figure 2

Causal model To confi rm the relations

between the constructs, we then estimated the

causal model with all four constructs and the

fi ve relations We found a positive and signifi

-cant relation between Web content and

perfor-mance, as we show in Figure 3

Next, to evaluate Hypothesis 3 (i.e

entre-preneur’s experience as a moderator), we

con-ducted a multi-group analysis, such that one

group was above the median and the other

was below or equal to the median on the

expe-rience variable (Table 5)

Hypothesis testing results Hypothesis 1a

pro-posed that entrepreneurial talent determines

the characteristics of entrepreneurs’ websites

However, this relationship is not signifi cant

(t < 1.96), and we must reject Hypothesis 1a Hypothesis 1b suggested that entrepreneurial talent would also positively affect business performance, but this infl uence is not signifi -

cant either, so we also reject Hypothesis 1b

(see Figure 3)

Hypothesis 2 posited that website istics would positively infl uence business performance We observed a positive and sig-nifi cant relationship between Web content and performance, with loading = 0.35, t = 4.1 and a good fi t of the model (χ2 = 45.28, p = 0.298,

character-RMSEA = 0.026) Therefore, the content acteristics of a website positively infl uence

char-business performance, in support of thesis 2 for content characteristics, though not for design characteristics (see Figure 3)

Hypo-In Hypothesis 3a, we proposed that the

experience of entrepreneurs in the focal sector would mitigate the relationship between entre-preneurial talent and website characteristics (Web design and Web content) First, we can confi rm that experience signifi cantly affects the relationship between entrepreneurial talent and the design characteristics of the website,

at a 90% confi dence interval However, in contrast with our expectations, the greater the

Table 4 Measurement model fi t

Variable Load Load2 Measurement error Extracted variance Compound reliabilityLatent variable: entrepreneurial talent

entrepreneur’s experience, the greater is the

impact of entrepreneurial talent on design

characteristics Therefore, we must reject

Hypothesis 3a Second, the coeffi cient

associ-ated with the relationship between

entrepre-neurial talent and Web content is higher among

the least experienced business professionals,

though the difference does not achieve signifi

-cance, so we reject Hypothesis 3a.

We stated in Hypothesis 3b that the

experi-ence of entrepreneurs in the sector should strengthen the relationship between entrepre-neurial talent and company performance The greater the experience of the entrepreneur in the sector in our sample, the greater the impact of his

or her entrepreneurial talent on business mance, at a 95% confi dence interval Therefore,

perfor-we fi nd support for Hypothesis 3b (Table 5).

Figure 2 First-order confi rmatory factor analysis constructs: Web design and Web content χ2= 16.33; degrees

of freedom = 13; p = 0.23163; root mean square area of approximation = 0.041.

Figure 3 Causal model χ2= 45.28; degrees of freedom = 41; p = 0.29782; root mean square area of

approxi-mation = 0.026; Comparative fi t index (CFI) = 0.995; Goodness of fi t index (GFI) = 0.95; Adjusted goodness

of fi t index (AGFI) = 0.919

Although experience is positively related

to age, it does not manage to reach statistical

signifi cance for the rest of the analysed

constructs

CONCLUSIONS AND DISCUSSION

Although 86.5% of rural tourism

establish-ments host a website and 81.6% advertise on

the Internet, very little research considers the

relationship between the characteristics of the

entrepreneur and the particular characteristics

of the company’s website We therefore make

a pertinent contribution to this research area

In the rural tourism sector, many

entrepre-neurs do not have their own website In our

study, only 42% of respondents ran their own

website, 47% used the website of a tourism

institution and 11% lacked any online

pres-ence Of those with their own website, the

majority hired an outside company to develop

the site These sites generally are not

sophisti-cated but rather are mainly informative; only

an exceptional few provide the capability to

book accommodations online

The methodology we have adopted enabled

us to explore the results fi rst and then confi rm

them using a more sophisticated approach

The results of the exploratory and confi

rma-tory analyses were mainly the same The

regression indicated signifi cant relationships

between entrepreneurial talent and

mance and between Web content and

perfor-mance Both relations receive confi rmation in

the confi rmatory analysis, though in the fi rst

case, this confi rmation applies only to preneurs with more experience

entre-However, many of our proposed ships cannot be confi rmed First, regarding the lack of relationship between entrepreneurial talent and website characteristics, we consider two explanations: (i) we may need a more com-plete measure of entrepreneurial talent; and (ii) most entrepreneurs pay others to develop their websites In this context, website quality may depend on the proper selection of a Web developer, not the entrepreneur’s own knowl-edge of proper design and content Perhaps greater experience helps entrepreneurs deter-mine which company to hire though, because

in the more experienced group, the ship between entrepreneurial talent and Web design is signifi cant (90% confi dence level) Thus, even if experience (i.e age) implies less familiarity with new technologies, experienced entrepreneurs may be better at recognising which fi rm to hire to develop their website.Second, entrepreneurial talent does not lead

relation-to better Web content When coupled with experience though, it appears that greater entrepreneurial talent leads to better Web design However, we note that it is the content

of the website that determines performance.Third, the relationship between entrepre-neurial talent and performance is not con-

fi rmed for the whole sample, but it emerges for the more experienced group, so we can confi rm the positive effects of knowledge derived from experience Again, a more complete measure

of entrepreneurial talent may be needed

Table 5 Moderation of experience

talent–Web content

0.05 0.34 0.13 1.11 0.01 1 0.92Entrepreneurial

talent–performance

0.41 2.83 −0.02 −0.15 5.72 1 0.02*

a p = probability of H0: groups are the same.

* p signifi cant at 95% level of confi dence.

** p signifi cant at 90% level of confi dence.

d.f., degrees of freedom.

distinction as a control variable.

In relation to our measure of business

per-formance, it would be interesting to evaluate

the infl uence of other, perhaps more subjective

measures, such as consumers’ behavioural

intentions, the degree of consumer satisfaction

or the positioning of the rural establishment

These measures then might be compared

against the objective measures we used herein

(i.e income and profi ts)

The compilation of information about the

website characteristics was conducted by only

one researcher, who directly assessed every

website This method might be an advantage,

because it eliminates variation, but it also

might be a limitation, due to the possibility of

bias on the part of the researcher These

mea-sures therefore should be extended, perhaps

by using customers’ impressions to evaluate

websites

The results of this study also offer some

implications for entrepreneurs and

policymak-ers First, in view of the strong governmental

support, through subsidies, for new

technolo-gies, this work suggests a means to

discrimi-nate among projects for resource allocations

Subsidies should focus on improving website

contents, because according to our research,

the contents affect business performance It

follows that website contents should be taken

into account in the case of institutional and

private websites, so that rural tourism

estab-lishments can ensure that the resource is being

used to their advantage and improve their

per-formance A website with suffi cient and

neces-sary information about the business is crucial,

particularly for this type of service This study

therefore offers a guide for business

profes-sionals in this sector to expend their resources

Second, the most experienced business

pro-fessionals search intensively for information,

and then use that information to support

per-formance improvements Experience running

rural tourism establishments thus has a

posi-Internet site marketing practices of upscale and

luxury hotels in Turkey Tourism Management 27:

171–176

Barke M 2004 Rural tourism in Spain International

Journal of Tourism Research 6(3): 137–149.

Baron R 2009 Effectual versus predictive logics in entrepreneurial decision making: differences between experts and novices: does experience in starting new ventures change the way entrepre-neurs think? Perhaps, but for now, ‘caution’ is

essential Journal of Business Venturing 24: 310–315.

Bart Y, Shankar V, Sultan F, Urban G 2005 Are the drivers and role of online trust the same for all web sites and customers? A large-scale

exploratory empirical study Journal of Marketing

Bernert A, Stricker S 2001 German wineries on the

web: a survey of Web sites of Mosel-Saar-Ruwer and Pfalz wineries Submitted for the 75th European

Seminar of the EAAE, Bonn, Germany; 14–16 Feb 2001: 1–8

Beveren J, Thomson H 2002 The use of electronic

commerce by SMEs in Victoria, Australia Journal

of Small Business Management 40(3): 250–253.

Boylan R 1993 The effect of the number of

diplomas on their value Sociology of Education

66:206–221 [Cited in Ucbasaran et al., 2008].

Chandler G, Hanks S 1998 An examination of the substitutability of founders human and fi nancial

capital in emerging business ventures Journal of

Business Venturing 13: 353–369.

CIA 2009 The World Factbook Central Intelligence

Agency Available at https://www.cia.gov/library/publications/the-world-factbook/rankorder/2153rank.html (accessed 26 February 2010)

Collins O, Moore D 1964 The Enterprising Man

Michigan State University: East Lansing, MI [Cited in Jo and Lee, 1996]

Cooper A, Folta T, Woo C 1995 Entrepreneurial

information search Journal of Business Venturing

10: 107–120

Coyle J, Thorson E 2001 The effects of progressive

levels of interactivity and vividness in web

mar-keting sites Journal of Advertising 30(3): 65–77.

Cyr D, Trevor-Smith H 2004 Localization of web

design: an empirical comparison of German,

Jap-anese, and United States web site characteristics

Journal of the American Society for Information

Science and Technology 55(13): 1199–1208.

Danson M 1999 Debates and reviews Regional

Studies 33(2): 157–173.

Ellinger A, Lynch D, Hansen J 2003 Firm size, web

site content, and fi nancial performance in the

transportation industry Industrial Marketing

Management 32(3): 177–185.

Federici D, Ferrante F, Vistocco D 2008 On the

sources of entrepreneurial talent: tacit vs

codi-fi ed knowledge Journal of Knowledge Management

6(6): 7–28

Ferrante F 2005 Revealing entrepreneurial talent

Small Business Economics 25: 159–174.

Flynn BB, Saladin B 2001 Further evidence on the

validity of the theoretical models underlying the

Baldrige criteria Journal of Operations Management

19: 617–652

Gartner B 1989 ‘Who is an entrepreneur?’ is the

wrong question Entrepreneurship Theory and

Prac-tice 13(4): 47–68.

Hair J, Anderson R, Tatham R, Black W 2001

Análi-sis Multivariante [Multivariate AnalyAnáli-sis] Prentice

Hall: Madrid

Harada N, 2004 Productivity and entrepreneurial

characteristics in new Japanese fi rms Small

Busi-ness Economics 23: 299–310.

Hernández-Maestro R 2005 Análisis de la calidad en

el turismo rural Doctoral dissertation,

Universi-dad de Salamanca: Salamanca, Spain

Hernández-Maestro R, Muñoz-Gallego P,

Santos-Requejo L 2007 The moderating role of

familiar-ity in rural tourism in Spain Tourism Management

28: 951–964

Hernández-Maestro R, Muñoz-Gallego P,

Santos-Requejo L 2009 Small-business owners’

knowledge and rural tourism establishment

performance in Spain Journal of Travel

Research 48(1): 58–77.

Hmieleski K, Baron R 2009 Entrepreneurs’

optimism and new venture performance: a social

cognitive perspective Academy of Management

Journal 52(3): 473–488.

Hornaday J, Aboud J 1971 Characteristics of

suc-cessful entrepreneurs Personnel Psychology 24(2):

141–153

Hua H, Chin KS, Sun H, Xu Y 2000 An empirical

study on quality management practices in

Shang-hai manufacturing industries Total Quality

neurs by personality characteristics Journal of

Small Business Management 18(1): 11–18.

INE 2006/2010 Available at http://www.ine

es (accessed 16 May 2007, 21 August 2008, 20 February 2010)

Ingenieros J, 1913 El Hombre Mediocre Available

at http://www.elaleph.com, 2000 (accessed 22 February 2010)

Jo H, Lee J 1996 The relationship between an preneur’s background and performance in a new

opportu-International Journal of Entrepreneurial Behaviour

and Research 8(6): 292–308.

Kimberly JR and MJ Evanisko 1981 Organizational innovation: the infl uence of individual, organiza-tional and contextual factors on hospital adoption

of technological and administrative innovations

Academy of Management Journal 24(4): 689–

713

Kirzner I 1973 Competition and Entrepreneurship

University of Chicago Press: Chicago, IL [Cited

in de Klerk and Kruger, 2002]

de Klerk G, Kruger S 2002 The Driving Force Behind

Entrepreneurship: An Exploratory Perspective

Avail-able at http://www.kmu.unisg.ch/rencontres/band2002/F_04_deKlerk.pdf (accessed 2 June 2009)

Martín P, Román N 2004 Infl uencia de la experiencia

del vendedor industrial en su efectividad en términos

de ventas ante un aumento de la frecuencia de visitas

[Infl uence of the experience of industrial sales representatives on sales effi ciency owing to an increase in the frequency of visits] XVI Encuen-tro de Profesores de Marketing: Alicante, 22–24 September: 647–653

Mescon T, Montanari J, Tinker T 1981 The alities of independent and franchise entrepre-

person-neurs: an empirical analysis of concepts Journal

Murray-Leslie N 2009 Talent and technology:

forward thinking regional banks act fast to hire

and invest in fi nancial technology as the downturn

creates opportunity Superdatives: 1–5 Available at

http://www.rfpconnect.com/Content/userfi les/

super-derivatives-talent-and-technology.pdf

(accessed 18 February 2010)

Polo A, Frías D 2010 The relationship between

business characteristics and ICT deployment

in the rural tourism sector The case of Spain

International Journal of Tourism Research 12(1):

34–48

Porter M, Millar V 1985 How information gives

you competitive advantage Harvard Business

Review 63(4): 149–160.

Quelch J, Klein L 1996 The Internet and

interna-tional marketing Sloan Management Review 37(3):

60–75

Ratchford B, Pan X, Shankar V 2003 On the effi

-ciency of Internet markets for consumer goods

Journal of Public Policy and Marketing 22(1): 4–16.

Rauch A, Wiklund J, Lupkin G, Frese M 2009

Entrepreneurial orientation and business

perfor-mance: an assessment of past research and

sug-gestions for the future Entrepreneurship Theory

and Practice 33(3): 761–787.

Resnick M, Montania R 2003 Perceptions of

cus-tomer service, information privacy, and product

quality from semiotic design features in an online

web store International Journal of

Human-Computer Interaction 16(2): 211–234.

Ricker D, Leahy M 2009 Attracting, developing

and retaining talent Research Technology

Manage-ment 52(6): 33–44.

Roper S 1998 Entrepreneurial characteristics,

stra-tegic choice and small business performance

Small Business Economics 11: 11–24.

of Management Review 13(1): 217–226.

Starr J, Bygrave W 1991 The assets and liabilities of

prior start-up experience: an exploratory study of tiple venture entrepreneurs In Frontiers of Entrepre- neurship Research, Churchill N, Bygrave W, Covin

mul-J, Sexton D, Slevin D, Vesper K, Wetzel, W (eds) Babson College: Wellesley, MA; 213–227 [Cited

in Hmieleski and Baron, 2009]

Thompson R 2009 Individual entrepreneurial intent: construct clarifi cation and development of

an internationally reliable metric

Entrepreneur-ship Theory and Practice 33(3): 669–694.

Ucbasaran D, Westhead M, Wright M 2008 tunity identifi cation and pursuit does an entre-

Oppor-preneur’s human capital matter? Small Business

Economics 30: 153–173.

Van De Ven A, Hudson R, Schroeder D 1984 Designing new business startups: entrepreneur-ial, organizational, and ecological considerations

Journal of Management 10(1): 87–107.

Washington Economic Development Commission

(WEDC) 2009 The Washington Innovation Economy

Executive Summary Available at http://www.wedc.wa.gov/Download%20files/WEDCExecutiveSummary04072009.pdf (accessed 28 February 2010)

Wetering A, Koster S 2007 Inheriting knowledge and sustaining relationships: what stimulates the innovative performance of small software fi rms in

the Netherlands? Research Policy 36(3): 320–335.

Wright M, Westhead P, Sohl J 1998 Editors’ introduction: habitual entrepreneurs and angel

investors Entrepreneurship Theory and Practice

22(4): 5–21

Yoon S 2002 The antecedents and consequences

of trust in online-purchase decisions Journal of

Interactive Marketing 16(2): 47–63.

Most economics and urban literature

focuses on the economic aspects of foreign

investors’ impact on cities and defends their

positive role in urban development This

paper takes a different approach by

developing an urban economics model for

tourist cities that illustrates how, when

there is local underinvestment and a large

infl ux of foreign labour, transnational

enterprises may make their profi ts at the

expense of local businesses Therefore, it is

the government’s responsibility to regulate

foreign investment in a way that is

conducive to sustainable development

Macao is adopted as a case study Copyright

© 2010 John Wiley & Sons, Ltd.

Received 2 September 2009; Revised 24 May 2010; Accepted 17

June 2010

Keywords: foreign investment; local

underinvestment; foreign labour; sustainable

development

INTRODUCTION

Transnational enterprises and

interna-tional organisations, such as the

Interna-tional Monetary Fund, the World Bank,

the World Economic Forum and the World

Tourism Organization, enthusiastically urge

cities to seek out competitive advantages to

ensure their survival and prosperity They

assume the escalation of inter-city competition

for capital, labour and consumers, and thus, they encourage cities to create market condi-tions that attract foreign factors of production

to exploit local competitive advantages A large volume of economic literature supports the desirability of foreign capital, labour and con-sumers According to these studies, free factor mobility has various advantages, such as pro-moting growth (Oliva and Rivera-Batiz, 2002; Qiu, 2005; Robert, 2008; Thompson, 2008; Xafa, 2008), fostering competition (Edwards, 2001; Majek and Hayter, 2008; Sheng, 2010), transfer-ring technology and management skills (Lopez-Mejia, 1999; Ivarsson, 2002; Savvides and Zachariadis, 2005; Takii, 2009) and enhancing policy transparency and market discipline (Moreno, 2001; Coe and Wrigley, 2007) However, a number of studies on tourist cities bear witness to the serious side effects that can accompany an upsurge in tourism, such as leakage, rising cost of living, asset bubbles, bankruptcies of local fi rms and overreliance on tourism (Copeland, 1991; Wilkinson, 1999; Chand, 2003; Croes, 2006; Scheyvens and Momsen, 2008; Sheng and Tsui, 2010)

Our research asked whether a tourist city’s accommodation of as many foreign factors as possible, as mainstream liberal doctrine recommends, is benefi cial for local businesses

We developed an urban economics model for tourist cities that illustrates how the interests

of foreign investors and local businesses diverge signifi cantly in the case of local under-investment and a massive infl ux of foreign labour We suggested that mainstream liberal doctrine predominantly supports multina-tional enterprises and, in many cases, does so

at the expense of local businesses After ing the theoretical modelling, we present the case study of Macao to support the theoretical construct

describ-Int J Tourism Res 13, 32–40 (2011)

Published online 14 July 2010 in Wiley Online Library

(wileyonlinelibrary.com) DOI: 10.1002/jtr.795

Foreign Investors versus Local

Businesses: an Urban Economics Model for Tourist Cities

Li Sheng*

Gaming Teaching and Research Centre, Macao Polytechnic Institute, Taipa, Macao

*Correspondence to: Prof L Sheng, Gaming Teaching

and Research Centre, Macao Polytechnic Institute, Taipa

00853, Macao.

E-mail: edmundsheng@ipm.edu.mo

growth depends on it The city uses the revenue

from the export of tourism services to fi nance

importing various consumer goods The terms

of trade (TOT), which express the relative

prices of exportable and importable goods as

well as services, play a key role in determining

economy-wide production, consumption and

welfare If trade is balanced, the TOT are

equivalent in value to the ratio of import values

to export values Clearly, the price of tourism

services is affected by how the TOT are decided

in the presence of substantial exports of tourism

services and large imports of consumer goods

A tourist city, if it is a small open economy,

may accept the TOT as given, or, if the city has

a certain amount of market power over

exter-nal trade, it may be able to infl uence the TOT

The latter case is common because many tourist

destinations have no clear substitutes due to

their unique historical heritage, special natural

landscape or convenient location Therefore,

these cities can signifi cantly infl uence TOT

despite their small size (Sheng and Tsui,

2009c)

In Figure 1, S is the tourist city’s supply

curve of tourism services, and D is the

com-bined demand curve for these services, where

compared with mainland China, the small open economy assumption is inappropriate for Macao because it holds a monopolistic power

on commercial gambling trade over the rest of the country As Figure 1 illustrates, when rapid construction and the opening of tourism facili-ties shift S outwards, increasing numbers of tourists enter the city, which shifts D outwards

to a larger extent As a result, the TOT increase

in equilibrium and exert a signifi cantly tive impact on the local economy’s real income and welfare Whether there is an increase in TOT and welfare depends on whether the tourist city has a dominant infl uence on the setting of TOT Usually, TOT is closer to that

posi-of larger economies However, a number posi-of tourist cities possess specifi c, sometimes unique, tourism resources, similar to Macao’s monopolistic position in ‘Greater China’ with regard to legalised commercial gambling Therefore, while our model applies to tourist cities that infl uence TOT to a large extent despite their small size, for tourist cities without such substantial degrees of market power like Macao, Figure 1 may not be repre-sentative In the latter case, welfare effect may

be ambiguous

However, when there is an uneven tion of investment, the positive impact of the improved TOT has different implications for tourism fi rms depending on their ownership

distribu-In comparison with fi nancially powerful multinational tourism enterprises, local tourism fi rms, especially in the developing world, are relatively underinvested They are put in a disadvantageous position because they have to pay higher wages to compete with their foreign counterparts and therefore face smaller profi t margins even when outside tourism demand rises substantially The under-investment assumptions are valid because many tourist cities, particularly in the develop-ing world, rely on foreign investment to accom-modate large infl uxes of tourists

Figure 1 Terms of trade (TOT) and welfare of a

booming tourist city

In fact, a general underinvestment in

domes-tic fi rms in comparison with foreign-owned

businesses is evident across the developing

world Moreover, it is a common phenomenon

that an infl ow of foreign capital raises overall

wage levels in host countries, and foreign fi rms

often take qualifi ed staff from local fi rms by

providing more attractive salary packages

For-tanier and Wijk (2010) studied data from

inter-views with the managers of foreign- and locally

owned hotels in Mozambique, Tanzania and

Ethiopia, and they found that foreign fi rms offer

attractive compensation packages to attract

well-trained employees from local hotels, which

causes a local shortage of human resources

Consequently, foreign hotels expand rapidly,

while their local counterparts shrink, despite

the overall tourism growth in these developing

tourism destinations Willmore (1986) analysed

data for foreign-owned as well as private

Brazilian fi rms and identifi ed signifi cant

differ-ences between local and foreign entities in terms

of wages and other employee benefi ts He

argued that these differences constitute one of

the major reasons that foreign fi rms can hire

more high-quality staff and, consequently, grow

at a faster pace with higher productivity, higher

ratios of value added to output and greater

exports than local fi rms Das (2002) examined

the effect of foreign direct investment on wages

in the context of a developing economy He

recognised that the infl ow of foreign capital

generally raises in wages in host countries and

that fi nancially stronger foreign fi rms can recruit

experienced managers and skilled workers

from local fi rms by offering attractive salaries

As a result, foreign fi rms succeed at the expense

of local fi rms Ahiakpor (1986) found that, in

Ghana, foreign fi rms are signifi cantly more

profi table than fi rms under other ownership

groups He identifi ed higher-quality staff as one

of the major reasons for foreign successes As

noted above, however, this recruitment is

largely due to the higher salaries that foreign

fi rms offer As a result, local fi rms only

margin-ally benefi t from economic growth, but foreign

fi rms make remarkable profi ts Further

litera-ture on local underinvestment can also be found

in Ramstetter (2004), Wu (2001), Heyman et al

(2007), and Chen and Tang (1987)

We specifi ed the production function for

tourist cities as X = F(T; L, K), where X stands

for the output of tourism services, T for the number of customers (tourists), L for the labour employed and K for the stock of capital Labour (L) is mobile across sectors to a great extent, and customers can be completely mobile across service providers (fi rms) within the tourism sector However, capital (K) is an industry-specifi c factor of production and is barely mobile across tourism and other sectors

Ob viously, the extreme case is F(0; L, K) = 0 (i.e no customer and no output), and any level

of operating capacity is characterised by a certain combination of (L, K) A realised output (X) is determined jointly by customers (M) and other production inputs such as labour (L) and capital (K) For physical goods, production is separable from and usually precedes consump-tion; however, the production of tourism ser-vices cannot be separated from the consumption

of those services In a tourist city, tourism nesses and tourists interact with each other in the same time and place to create an output of tourism services As economics literature gen-erally assumes, the marginal productivity of T,

busi-L and K is positive but diminishing We defi ned tourism profi t as Π = PXX − cT − wL − rK, where

w refers to the wage rate, r to the user’s cost of capital and c to the unit cost of attracting cus-tomers (e.g the cost of advertising) Tourism revenue is PXX, but for expository convenience, economists often use augmented concepts of revenue depending on specifi c research pur-poses of different two-sector models (Baffoe-Bonnie, 2004; Chambers and Färe, 2004; Salvatore 2004) Augmented revenues may take the form of R(T; L, K) = PXF(T; L, K) − wL

− rK, if we focus on cost of attracting tourists,

or R(L; T, K) = PXF(L; T, K) − cT − rK, if we focus on labour cost Profi t function derived from the former is (ΠT) = R(T; L, K) − cT; that derived from the latter becomes (L) = R(L; ΠT, K) − wL Profi t maximisation requires the mar-ginal revenue MR to equal the marginal cost

MC (i.e MR = c or MR = w) As we try to trate revenue and profi t distribution between local and foreign business in the face of increas-ing tourism demand and increasing labour supply through labour import, we use the aug-mented revenue depending on labour cost and depict MR = w in Figure 2

illus-We explored why local tourism businesses are shrinking and foreign fi rms are profi tably

expanding under the same demand condition:

substantial numbers of visiting tourists In

Figure 2, labour is mobile across domestic and

foreign businesses (depicted by the origins Oh

and Of respectively), but capital is not The

horizontal axis measures the total supply of

labour available to the city’s tourism industry,

and the vertical axis measures the wage rate w

The tourism wages w are determined by

inter-actions between domestic and foreign fi rms

The marginal revenue for either domestic (Mh)

or foreign (Mf) fi rms slopes downward due to

diminishing returns Before a rapid growth in

demand, w* = ED in equilibrium, OhD of L is

employed by domestic fi rms, and DOf is

employed by foreign fi rms

We assumed that large numbers of tourists

fl ow into the city (e.g due to an economic boom

in their home countries), and that the labour

supply and its distribution among local and

foreign fi rms are fi xed in the short run This

expansion improves the TOT of the city and, in

particular, renders labour relatively scarce

Consequently, the overall wage level increases

Graphically, we observed that Mh and Mf shift

upwards, and E moves to E′, which indicates a

higher equilibrium wage In response to the

growth in tourism demand and increase in

wages, the city permits the expanding tourism

businesses to employ foreign workers, in the amount of OfOf′ This surge in the labour supply dampens labour costs and renders capital rela-tively scarce; consequently, higher capital returns become possible Graphically, Mf′ shifts outwards to Mf″, and the import of labour drops equilibrium wages to a level equal to E″D″, which is determined by the intersection between Mh′ and Mf″ Thus, domestic fi rms are supposed to hire more labour (DD″), and D″Of′

is left to foreign fi rms In this case, both tic and foreign output (Xh and Xf) would increase, and the capital income r that accrues

domes-to domestic and foreign owners would also increase Capital income increases because the law of diminishing returns to capital is weak-ened when more L is used with fi xed Kh and Kf

to produce Xh and Xf.The increase in capital returns attracts mul-tinational companies to enter the potential market or to strengthen their investments in existing subsidiaries in the city The existing literature confi rms our assumption that foreign investment fl ows into countries that promise higher capital returns Ogawa and Lee (1995) found that labour-intensive industries in Japan were experiencing falling profi ts Therefore, Japanese businesses had an incentive to invest

in other countries that promised higher capital

Figure 2 Foreign profi table expansion at expense of local businesses

returns for the same industries Ogawa and

Lee presented a formal model to illustrate the

relationship between capital returns in some of

the industries in which Japan was losing its

comparative advantage and direct investment

in foreign counterparts of these industries

Thus, they argued that investment overseas is

a means to guarantee reasonable capital

returns Using a nested logit model to analyse

data on foreign logistics establishments in

China, Hong and Chin (2007) identifi ed the

location determinants of foreign investment in

China’s logistic industry They found that a

larger market, lower labour costs, higher

labour quality and an effi cient transportation

infrastructure ultimately lead to higher capital

returns and attract foreign logistics

invest-ment Goss et al (2007) applied a Cobb–Douglas

production function to data covering the

period 1988–1999 in the USA and identifi ed a

signifi cant positive link between the growth of

productivity and increased investments of

foreign capital Moreover, they found that

foreign capital predominantly fl ows into

branches with higher capital returns and

stim-ulates the overall productivity and profi

tabil-ity of these branches Silva (2010) presented a

model to show how managerial ability can

increase capital returns and thus explain the

pattern of international capital fl ows The

model implies that countries with more

high-ability managers usually have higher total

factor productivity and promise higher capital

returns Therefore, these countries are

attrac-tive to foreign investors The links between

capital returns and foreign capital infl ow were

also documented in Bardhan (1996), Reis

(2001), Chaudhuri and Mukherjee (2002), Toh

and Ng (2002), and Jefferson and Su (2006)

With the massive infl ow of foreign

invest-ment, the city’s total capital stock and the

foreign share in this stock increase

Conse-quently, local businesses become relatively

underinvested in the face of foreign expansion

Graphically, the infl ux of foreign capital shifts

Mf″ up to Mf″′ and drives the overall labour

cost higher Eventually, the equilibrium occurs

at point E″′ with an even higher wage than the

initial wage The labour usage for domestic

fi rms now is only OhD″′, which is much less

than usage for foreign fi rms D″′Of′; this result

implies that the market share of domestic fi rms

declines in the face of foreign expansion nomically, this decline occurs because fi nan-cially strong international fi rms compete with

Eco-fi nancially weak local fi rms for human resources and boost the overall wage level higher Therefore, labour, in particular mana-gerial staff and skilled workers, moves from local to foreign fi rms Moreover, as Sheng and Tsui (2009b) pointed out, foreign capital fl ows may cause real estate bubbles and thus increase the cost of rent Local businesses, especially the small- and medium-sized ones, face a lack of quality staff and higher costs; they therefore encounter serious fi nancial diffi culties or even

a free port without any capital control, and foreign investments are encouraged by benefi -cial treatment Macao is a typical tourist city;

in 2008, tourist spending accounted for 68% of its gross domestic product (GDP), and 45% of its labour was employed in the tourism sector The gambling sector accounted for 55% of Macao’s GDP, 23% of its total employment and 76% of government revenue (Macao Statistics and Census Services, 2008)

Macao is a place to propagandise China’s openness and demonstrate how capitalism and democracy can coexist with socialism; this public image is conducive to China’s reunion with Taiwan Macao’s political meaning and the benefi ts it provides for China motivate the Beijing government to grant the tourist city full support Macao secured a monopoly over legalised casino gambling in China Moreover, China eased the restrictions on travel between mainland China and Macao with the launch of the Free Individual Travel (FIT) scheme in

2003 Under this scheme, citizens who live in the rich coastal provinces of mainland China can travel to Macao after a simple application procedure (Sheng and Tsui, 2009a) The number of tourists from mainland China increased from 1.65 million in 1999 to 11.61 million in 2008, and they make up the largest

MGM, Venetian and Galaxy, invested billions

to build integrated casino resorts in the city

Since the market opened, huge amounts of

foreign investment have fl owed into the city

Macao’s net foreign capital infl ow (i.e capital

infl ow minus outfl ow) increased from US$160

million in 2001 to US$2.12 billion in 2007

(Macao Statistics and Census Services, 2008)

The city has become a large construction zone,

and dozens of new casinos and hotels have

sprung up in the span of several years To

support the rapidly growing tourism industry,

large numbers of foreign workers have been

invited to the city From 2002 to 2008, the

number of guest workers increased from 23 460

to 85 207 to account for one-third of Macao’s

total employment (Macao Statistics and Census

Services, 2008) With these stimulations on

demand (i.e FIT) and supply (i.e gaming

liberalisation), Macao has been experiencing

spectacular economic growth Macao’s GDP

not benefi ting to the extent that is generally assumed In fact, they are suffering in the face

of fi erce foreign competition Gaming licences were granted to foreign fi rms in 2002, and, in

2004, Venetian was the fi rst foreign fi rm to open its casino in Macao Therefore, this study focuses on the period from 2004 to 2008 (see Table 1) MGM Grand, Melco PBL, Wynn and Galaxy started their gaming businesses in Macao in 2007, 2006, 2006 and 2005 respec-tively First, foreign casino tycoons have sig-nifi cantly more capital than local business owners; Venetian has approximately 13 times

as much capital as the local fi rm Sociedade de Jogos de Macau (SJM), and Wynn has four times as much capital as SJM In fact, SJM accounted for only 5% of the total capital of casino fi rms in Macao in 2008, but Venetian accounted for more than half Second, SJM’s market share has decreased signifi cantly, from 100% in 2002 to around 25% in 2008, since the

Table 1 Net capital, gross revenue and net profi t of six gaming concessionaires in Macao from 2004 to 2008 (in million patacas) Sources: Annual reports of Galaxy Casino, SJM, MGM Grand Paradise, Wynn Resorts (Macau), Venetian Macau, and Melco PBL Jogos (Macau)

SJM MGM Grand Melco PBL Venetian Wynn GalaxyCapital 2004 6 714 — — 3 662 — —Revenue 2004 35 206 — — 3 247 — —Profi t 2004 4 044 — — 952 — —Capital 2005 4 878 — — 7 075 — 6 735Revenue 2005 34 409 — — 8 013 — 4 015Profi t 2005 5 560 — — 2 372 — 6Capital 2006 5 090 — 129 22 592 11 801 8 554Revenue 2006 35 222 — 159 10 510 2 362 7 786Profi t 2006 2 512 — −386 2 972 6 056 −450Capital 2007 6 935 248 3 665 39 452 13 492 9 201Revenue 2007 33 111 162 3 783 16 354 13 161 11 857Profi t 2007 1 845 −712 −1 041 1 579 1 485 561Capital 2008 4 312 −3 3 817 55 284 15 755 13 110Revenue 2008 28 832 8794 15 582 26 048 18 192 11 243Profi t 2008 747 −251 152 1 414 2 118 −362

SJM, Sociedade de Jogos de Macau.

market opened to foreign fi rms It should be

noted that the MGM Grand and the Melco PBL

are joint ventures between members of Stanley

Ho’s family and foreign fi rms However, the

Ho family’s total market share, including their

joint ventures, makes up less than half of the

Macao gaming market Third, SJM’s net profi ts

(after tax) have fallen drastically despite the

massive increase in tourist arrivals SJM

recorded a net profi t of 5.56 billion patacas in

2005, but this fi gure shrunk to 747 million

patacas in 2008 Furthermore, the Ho family’s

joint ventures recorded net losses in 2007

Fourth, foreign casinos are considerably profi

t-able; Venetian recorded a net profi t of 2.97

billion patacas in 2006, and Wynn recorded

6.06 billion patacas

The uneven distribution of wealth between

foreign and local businesses in Macao is largely

due to local underinvestment in comparison

with the massive infl ow of foreign capital since

gaming liberalisation Before Macao’s

sover-eignty was returned from Portugal to China in

1999, it was a relatively unknown regional city;

despite several locally run casinos, Macao was

much poorer than its renowned neighbour

Hong Kong China initiated the FIT policy in

early 2003, and the Macao government

imple-mented gaming liberalisation enacted in 2002

The fi rst foreign casino was established in

Macao in 2004 Therefore, we compared

mac-roeconomic statistics before and after these

transformative events to prove our

underin-vestment assumption It should be noted that,

in the case of Macao, the term ‘foreign’ means

non-local and therefore includes mainland

China and Hong Kong First, Macao’s gross

fi xed capital formation increased from 8981

million patacas in 2003 to 49 474 million patacas

in 2008 Obviously, local investment could not

support this growth by more than fi vefold

within fi ve years It is noteworthy that local

residents’ bank deposits only increased by 80%

during the same period of time In fact, most

of Macao’s ongoing construction projects,

which cost billions, are foreign-owned (Macao

Daily News, 27 August 2007, 29 October 2008,

22 October 2009) Second, Macao’s total real

estate transactions increased from 8980 million

patacas in 2003 to 35 025 patacas in 2008

Obvi-ously, this boom did not occur without a

sub-stantial infl ow of foreign capital The square

meter price for residential housing increased from 13 189 patacas to 36 783 patacas, which is far beyond the fi nancial capacity of most local residents In fact, foreign fi rms hold a large portion of Macao’s real estate for speculative purposes (Macao Daily News, 15 October 2009,

14 February 2010 and 2 April 2010) Third, the stock of foreign investment in the city increased from 26 131 million patacas in 2002 to 63 021 million patacas in 2007 Returns on foreign investments increased from 3213 million patacas in 2002 to 11 165 million patacas in

2007 Total foreign assets in Macao increased from 136 206 million patacas in 2003 to 359 939 million patacas in 2008 These fi gures confi rm that Macao is experiencing massive foreign capital infl ow and local underinvestment, and that foreign fi rms are reaping large profi ts (Macao Statistics and Census Services, 2008) Macao’s underinvested local fi rms cannot afford the high wages that their foreign coun-terparts offer The median salary was 4800 patacas in 2003 and increased to 8000 patacas

in 2008 Foreign casinos, with their attractive salary packages, attracted employees not only from local casinos but also from local indus-tries, sales, banks and even the civil service Despite the import of workers to Macao, many local businesses are facing a human resources shortage (Macao Daily News, 11 May 2005, 17 May 2006 and 27 July 2006) These underin-vested local businesses, especially small ones,

fi nd it very diffi cult to survive in the face of labour shortage and high rental prices In 2004,

101 bankruptcies were recorded in Macao, but this fi gure increased to 383 in 2008 (Macao Statistics and Census Services, 2008)

CONCLUSIONThis paper developed an urban economics model to analyse the diverging interests of transnational enterprises and local businesses

in the case of local underinvestment If liberal economic doctrine dominates a tourist city’s policy-making, then transnational enterprises make their profi ts at the expense of local businesses Data from Macao supported this paper’s theoretical predictions Therefore, it is the government’s responsibility to regulate the infl ow of foreign capital at the optimal level that is conducive to sustainable development

Baffoe-Bonnie J 2004 Learning-by-doing and input

demand of a rate-of-return regulated fi rm

Eco-nomic Modelling 21(6): 1015–1037.

Catching up Sands, Galaxy becomes giant in Cotai

Strip (2009, October 22) Macao Daily News, p

A.02

Chambers RG, Färe R 2004 Additive

decomposi-tion of profi t effi ciency Economics Letters 84(3):

329–334

Chand S 2003 Economic trends in the Pacifi c island

countries Pacifi c Economic Bulletin 18: 1–15.

Chaudhuri S, Mukherjee U 2002 Removal of

protectionism, foreign investment and welfare

in a model of informal sector Japan and the

World Economy 14(1): 101–116.

Chen TJ, Tang DP 1987 Comparing technical effi

-ciency between import-substitution-oriented and

export-oriented foreign fi rms in a developing

economy Journal of Development Economics 26(2):

277–289

Coe NM, Wrigley N 2007 Host economy impacts

of transnational retail: the research agenda

Journal of Economic Geography 4: 341–371.

Copeland B 1991 Tourism, welfare, and

de-industrialization in a small open economy

Economica 58: 515–529.

Croes RR 2006 A paradigm shift to a new strategy

for small island economies: embracing demand

side economics for value enhancement and long

term economic stability Tourism Management 27:

453–465

Das S 2002 Foreign direct investment and the

relative wage in a developing economy

Journal of Development Economics 67(1): 55–77.

Edwards S 2001 Capital mobility and economic

performance: are emerging markets different?

NBER Working Paper, No W8076 National

Bureau of Economic Research: Cambridge,

MA

Fortanier F, Wijk J 2010 Sustainable tourism

indus-try development in sub-Saharan Africa:

conse-quences of foreign hotels for local employment

International Business Review 19(2): 191–205.

Four Seasons open, 1 billion investment (2008,

October 29) Macao Daily News, p A.01.

Galaxy Casino. Annual Reports, 2005–2008 Galaxy

Casino: Macao

dence from matched employer–employee data

Journal of International Economics 73(2): 355–376.

Hong JJ, Chin TH 2007 Modeling the location choices of foreign investments in Chinese

logistics industry China Economic Review

18(4): 425–437

Human resource department established dealing

with labor shortage (2006, May 17) Macao Daily

News, p A.01.

Immigration through investment causes real estate

bubble (2009, October 15) Macao Daily News, p

A.07

Ivarsson I 2002 Transnational corporations and the geographical transfer of localised technology: a multi-industry study of foreign affi liates in

Sweden Journal of Economic Geography 2: 221–247.

Jefferson GH, Su J 2006 Privatization and turing in China: evidence from shareholding

restruc-ownership, 1995–2001 Journal of Comparative

Eco-nomics 34(1): 146–166.

Local casinos facing labor shortage, SJM raises

wages (2006, July 27) Macao Daily News, p A.02.

Lopez-Mejia A 1999 Large capital fl ows: a survey

of causes, consequences and policy responses IMF Working Paper, WP/99/7 International Monetary Fund: Washington, DC

Macao Statistics and Census Services 2008 Yearbook

of Statistics, 1999–2008 Macao Statistics and

Census Services: Macao

Majek T, Hayter R 2008 Hybrid branch plants: Japanese lean production in Poland’s automobile

industry Economic Geography 84(3): 333–358.

Melco PBL Jogos (Macau) Annual Reports, 2006–

2008 Melco PBL Jogos: Macao.

MGM Grand Paradise Annual Reports, 2007–2008

MGM Grand Paradise: Macao

Moreno R 2001 Capital controls and emerging

markets Economic Letters August Issue 2001: