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The purpose of this paper is to investigate antecedents of households’ local demand for
domestic tourism in Jordan
International Journal of Culture, Tourism and Hospitality Research
Antecedents of local demand for domestic tourism in Jordan
Ihab Khaled Magableh Radwan Kharabsheh
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To cite this document:
Ihab Khaled Magableh Radwan Kharabsheh, (2013),"Antecedents of local demand for domestic tourism in J ordan", International J ournal of
Culture, Tourism and Hospitality Research, Vol. 7 Iss 1 pp. 78 - 92
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Antecedents of local demand for domestic
tourism in Jordan
Ihab Khaled Magableh and Radwan Kharabsheh
Abstract
Purpose – The purpose of this paper is to investigate antecedents of households’ local demand for
domestic tourism in Jordan.
Design/methodology/approach – A sample of 600 households is surveyed and a two-stage demand
model is estimated. Stage 1 identi?es the antecedents of the probability of entering the domestic tourism
market. Stage 2 identi?es the antecedents of households’ expenditures on domestic tourism. The Heckit
method is used to estimate the ?rst stage and the OLS is used to estimate the second stage.
Findings – Certain socio-economic factors (household characteristics, individual characteristics and
ability variables) impact the local demand for domestic tourism, as do price and income variables.
Research limitations/implications – The generalizability of results to other countries is limited.
Practical implications – Identi?cation of antecedents of local demand for domestic tourism helps
governments to formulate and modify future tourism strategies.
Originality/value – This paper contributes to the literature by including socio-economic variables in the
domestic tourismdemand model. Further, there is a dearth of studies in Jordan in general and regarding
domestic tourism in particular.
Keywords Jordan, Tourism, Government policy, Domestic tourism, Local demand, Heckit method,
Socio-economic factors
Paper type Research paper
1. Introduction
Tourism is the world’s largest and fastest growing industry, and indeed the biggest provider
of jobs (World Trade and TourismCouncil, 2007; Coenen and Lobke, 2003; Chan et al., 2004,
2005). According to the World Bank (2009), $US2 trillion was earned by the tourism industry
in 2007. Tourismexpenditures have a positive impact on countries’ GDP, inter-linked sectors,
labor market and economic health in general. This positive impact of tourismappears at both
the micro and macro levels.
The literature distinguishes between local demand for external tourism (outbound tourism)
and demand for domestic tourism. The demand for domestic tourism is classi?ed into
external demand (inbound tourism) and local demand. External tourism has a bigger
multiplier effect on the economy in the form of increased tourism income, tourism GDP,
creation of jobs, support of inter-linked sectors such transportation and hospitality
industries, and ?nally increased foreign reserves. Local demand for domestic tourism, while
sharing some of the bene?ts of external tourism, helps in reducing foreign currency leakages
conditioned by domestic tourismbeing a substitute for outbound tourism. The advantages of
local tourism are due to the fact that it is less susceptible to regional and global economic
and political disturbances. For example, due to the near collapse of global tourism after the
September 11 attacks, terrorism and wars, the recent ?nancial crises, and the decreased
volume of international travel due to the spread of disease and epidemics such as SARS and
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VOL. 7 NO. 1 2013, pp. 78-92, Q Emerald Group Publishing Limited, ISSN 1750-6182 DOI 10.1108/17506181311301372
Ihab Khaled Magableh is
based at the Department of
Managerial Sciences, Talal
Abu Ghazaleh College of
Business, German Jordan
University, Amman, Jordan.
Radwan Kharabsheh is
based at the Department of
Business Administration,
Faculty of Economics and
Administrative Sciences,
The Hashemite University,
Zarqa, Jordan.
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swine ?u, local demand for domestic tourism becomes a safeguard and a viable substitute
for the shortage of inbound tourism.
In addition to its economic impact, local demand for domestic tourism creates awareness of
cultural heritage and loyalty to the country, increases ties among citizens within the country,
and helps protect the environment through creating awareness. In the economic sense local
tourism creates jobs and decreases poverty, limits the effect of seasonality of international
tourism, and limits income drain from the country. While the focus has traditionally been on
inbound tourism in the Middle East and North Africa (MENA) region, local demand for
domestic tourism has attracted less attention. In Jordan, tourism depends for a large part on
international tourism. While there are 480 tourist ?rms for inbound and outbound tourism,
there are as few as 20 operators for local tourism (Department of Statistics, 2009).
Considering that Jordan has plenty of world-class tourist locations, including historic,
religious and therapeutic sites, to offer, the problem is the demand for local tourism and not
the availability of touristic sites. For example, Petra, one of Jordan’s popular touristic sites,
has been voted one of the new world wonders. In addition, six of the ten major ancient
Roman cities are located in Jordan. The problem is in the ability to create, increase and
sustain local demand for domestic tourism. More importantly, in the tourism demand
literature, it is well acknowledged that income and tourism prices are the leading demand
antecedents in tourism demand analyses. For example, most studies focus on income and
price variables as demand antecedents for travel. According to the literature review by Lim
(2006), of 124 published papers, 105 empirical papers employed income variables. The
author also ?nds that 94 percent of the papers use relative prices, whereas 52 percent use
transportation costs.
Nevertheless, the literature neglects other possible socio-economic variables such as family
size, the availability of family and public transport, knowledge and awareness of local
destinations, household debt, sense of national duty, availability of time for leisure and the
number of hours worked in paid jobs. In fact, several studies argue that these variables
in?uence consumers in making decisions to travel. This study contributes to the literature by
including socio-economic variables in the tourism demand model.
2. Tourism in Jordan
The tourism industry makes a substantial contribution to the Jordanian economy. In 2009, it
accounted for 11 percent of GDP, with a compound annual growth rate (CAGR) of 16.2
percent during the period 2003-2009 (Department of Statistics, 2009). Employment in the
tourism cluster, including indirect employment, was estimated at around 130,000 (11
percent of the work force). The tourism cluster itself employs 34,405 people, of whom 77.5
percent are in the hotel and restaurant industry. In 2009, employment just around Amman
(the capital) accounted for 72 percent of total national employment.
Women form just 10 percent of overall tourism employment, a proportion that has not
changed much over the years within the hotel industry (?ve-star hotels). In comparison with
regional peers, however, Jordan’s tourism industry shows very low growth, both in terms of
tourist arrivals as well as their expenditure (World Bank, 2009). Table I shows the main
tourism indicators in Jordan. It shows an improvement over the years (2005-2009). It is
noted, however, that the room occupancy ratio is as low as 55 percent. Keeping in mind that
there are 481 hotels ranging from non-classi?ed to ?ve-star hotels and that the variety of
prices re?ects this range, it becomes clearer that the main problem is the demand side
rather than the supply side.
Given the importance of the tourismsector to the economy, the Government of Jordan (GoJ),
through the Ministry of Tourism and Antiquities (MoTA), has paid considerable attention to
developing a coherent tourism strategy (2004-2010). The GoJ employed numerous
initiatives to decrease the prices and costs of local tourism in Jordan, with very little success
(Fraihat, 2010). This implemented strategy follows froma heavy focus on price factors alone.
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Other non-price factors can better and comprehensively predict local demand for domestic
tourism. By identifying these factors, the GoJ may include such elements in its future
strategies to alleviate the level of local demand for domestic tourism in the country.
3. Local demand for domestic tourism
While an abundance of studies examine antecedents, development, and issues regarding
local demand for domestic tourism both in developed and developing countries, there is a
dearth of studies addressing these issues in Jordan. In addition, in the context of local
demand for domestic tourism, most studies focus on income and price variables as demand
antecedents for travel.
According to the literature review by Lim (2006), 105 empirical papers out of a total of 124
published papers employ income variables. The author also ?nds that 94 percent of the
papers use relative prices, whereas 52 percent use transportation costs. Nevertheless, the
literature neglects other possible socio-economic variables such as family size, the
availability of family and public transport, knowledge and awareness of local destinations,
household debt, availability of time for leisure and the number of hours worked in paid jobs.
In fact, several studies argue that these variables in?uence consumers in making decisions
to travel. For example, Allen and Yap (2009) model demand for Australian domestic tourism
using a panel approach. They ?nd that the income elasticity for domestic visiting friends and
relatives (VFR) trips in Australia is negative, implying that Australian households will not
choose to travel domestically when there is an increase in household income. They also ?nd
that the national income variables are positively correlated with domestic business tourism
demand, indicating that demand is strongly responsive to changes in Australia’s economic
conditions.
More importantly, the researchers ?nd that an increase in the current prices of domestic
travel causes demand for domestic trips to fall in the next one or two quarters ahead. Finally,
they ?nd that the coef?cients for lagged dependent variables are negative, indicating that
trips are made on a periodic basis. Yap (2008) examines the economic antecedents of
intrastate and interstate tourism demand in Australia. He investigates whether the economic
impacts of income and tourism prices differ between intrastate and interstate tourism using
Johansen’s co-integration analysis and error-correction models. Yap’s study highlights
numerous interesting ?ndings. First, changes in all economic variables, except income, in
the short term affect interstate tourist arrivals to Queensland. Income also in?uences
interstate tourist arrivals from Victoria to New South Wales in the short term. Secondly,
long-term income coef?cients are mostly negative, implying that an increase in domestic
household income depresses intrastate and interstate tourism demand in Australia.
Finally, domestic transportation costs are the main economic factors that in?uence interstate
tourism demand for Victoria and Western Australia in the long-term. Alegre and Pou (2004)
examine the frequency of travel as a predictor of the demand for local tourism in Spain. They
Table I Main tourism indicators (2005-2009)
Indicator 2005 2006 2006 2008 2009
Number of arrivals (millions) 5.8 6.7 6.5 7.03 7.1
Gross tourism income/GDP at current prices
(percent) 11.4 13.9 14 14.1 14.3
Value added of tourism at current prices (JD,
million) 510.7 730.4 819.2 1,004.3 1,100.6
Number of hotels 468 476 470 481 490
Number of rooms (thousands) 20.8 21.6 21.6 22.5 22.7
Room occupancy ratio (percent) 49.4 42.4 47.3 55.3 54
Employees in hotels (thousands) 12.9 13.5 13.2 14 14.5
Employees in tourism sector (thousands) 29.4 31.1 34.4 38.3 40.6
Source: Central Bank of Jordan (2009)
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use household data to examine antecedents of the number of quarters with positive tourist
expenditures within a year. Alegre and Pou (2004) highlight the relevance in travel frequency
analyses of distinguishing between the participation decision and the frequency decision
conditional on participation. They argue that although many socio-demographic variables
only show explanatory power for the participation decision, the two most relevant factors by
far in explaining each decision are the previous year’s tourism demand decisions
(suggesting evidence of habit persistence in tourism decisions) and disposable income,
although with an income elasticity below the unit.
Sadeghi et al. (2004) estimate the expenditure and price elasticity of demand for household
domestic tourism in Hamedan, Iran, using cross-section data and the almost ideal demand
system (AIDS) model. They ?nd that the majority of tourist household heads are of middle
age, fairly well off, highly educated, well employed, traveled from larger cities, used their
own cars and their trips lasted, on average, close to three days. They also ?nd that the
Hamedan tourists did not include all social classes equally. Hence, there is room to expand
the tourism industry and cover a larger number of tourists by further facilitating tourism
activities and removing the obstacles. Eugenio-Martin (2003) argues that in the there are
multiple factors involved in the decision leading to the tourists’ destination choice. He
contends that individuals or families with exactly the same socio-economic and
demographic characteristics may choose very different destinations. In dealing with the
so-called ‘‘heterogeneity problem’’ (i.e. recognizing that there are taste differences among
tourists and that ?nal destination choice is not an independent decision, but the last decision
of a set of choices that are determining it), Eugenio-Martin (2003) argues that tourists face a
?ve-stage decision process:
1. people have to decide whether or not to travel within a period of time;
2. those who expect to travel need to estimate a budget for tourism expenses;
3. given the budget, they need to determine the frequency and length of stay of their trip;
4. once a date and the length of stay are proposed, tourists need to choose which kind of
tourist destination to visit; and
5. from among all the available destinations that satisfy a tourist’s conditions, the ?nal
destination and the mode of transportation are chosen.
Hamal (1996) models demand for domestic holiday in Australia and concludes that demand
for domestic holiday travel in Australia is in?uenced positively by per capita real household
disposable income and the real prices of holiday travel and accommodation overseas, and
negatively by the domestic real prices of holiday travel and accommodation. Hamal (1996)
explains that the positive and relatively higher cross price elasticity indicates that
substitution between domestic and overseas holiday destinations exists, and that holiday
makers are more sensitive to the change in real prices of holiday travel and accommodation
overseas than to the changes in income and the domestic real prices holiday travel and
accommodation.
This paper examines the socio-economic factors that affect the local demand for domestic
tourism by devising a two-stage process model of demand. The paper is divided into six
sections. Section 1 presents the introduction to the paper, while section 2 presents tourismin
Jordan and section 3 discusses local demand for domestic tourism. Section 4 presents the
model framework and the methodology, while section 5 presents the estimation method and
results. Finally, the last section presents conclusions and recommendations.
4. Model framework and method
A household enters a domestic tourism market as a demander when it has effective demand
for tourismgoods or services. Households’ involvement in the domestic tourismmarket goes
through two sequential stages. In the ?rst stage, a household has to decide whether to enter
the domestic tourismmarket and travel (whether to spend on tourismgoods and services) or
not. Lack of effective demand can be due to lack of ability and/or willingness factors. But, if a
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household decides to travel and spend on domestic tourismgoods and services, i.e. the ?rst
stage, it decides on the amount of expenditure, i.e. the second stage. The following two
equations represent the previous two stages:
ProbðDDTÞ ¼ FðRC
i
; HC
i
; OF
i
Þ; ð1Þ
where Prob(DDT) is a dummy variable that takes a value of 1 if the household chooses to
travel and spend on domestic tourism, and 0 otherwise; RC
i
is the vector of respondents’
(heads of household) characteristics that affect households’ demand for domestic tourism;
HC
i
is the vector of households’ characteristics that affect households’ demand for domestic
tourism; and OF
i
is the vector of other factors that affect households’ demand for domestic
tourism.
HEODT ¼ FðRC
j
; HC
j
; OF
j
Þ; ð2Þ
where HEODT is households’ expenditures on domestic tourism; RC
j
is the vector of the
head of households’ characteristics that affect households’ expenditures on domestic
tourism; HC
j
is the vector of households’ characteristics that affect households’ expenditures
on domestic tourism; and OF
j
is the vector of other factors that affect households’
expenditures on domestic tourism.
While a single equation may suf?ce to model the proportion of tourism spending
domestically as a function of the explanatory variable, the problem is that many of the
respondents did not report their precise tourismexpenditures. More importantly, many of the
respondents did not travel locally during the period under study, and thus their expenditure
on domestic tourism is zero. Therefore, the use of the two-stage model is deemed
appropriate in this case.
4.1 The survey
A random sample of 600 Jordanian households was surveyed in 2009 using a questionnaire
at the regional level (Northern, Middle and Southern). The distribution of the sample among
regions is in accord with the population distribution. Table II shows the size, response and
usage rates of the sample. Table II shows that the highest percentage of questionnaires
received was in the Middle region (94.6 percent) followed by the Southern region (91.6
percent), while the highest percentage of usable questionnaires was received in the
Southern region (88.3 percent), followed by the Middle region (84.95 percent).
The questionnaire was completed by the head of each household. It consisted of three
sections. The ?rst section described the characteristics of the respondents, while the
second described the characteristics of the households. The third section explored
households’ demand for domestic tourism in 2009.
4.2 Respondent’s characteristics
Table III shows the respondents’ personal characteristics. It shows that the respondents’
ages range between 20 and 61 years with an average of 34.4 years. About 71.3 percent of
the respondents are male; 82.9 percent of the respondents are married, of whom 72.14
percent are male. Table III also shows that 13.8 percent of the respondents have higher
education, 53.3 percent have a Bachelor’s degree, 13.6 percent have a diploma, and 19.2
percent have high school education or less. About 84.5 percent of the respondents are
employed (72.9 percent of them are male) of whom 44.3 percent work in the private sector,
Table II Response rate of the sample
Middle Region Northern Region
Southern
Region
n % n % n %
Questionnaires distributed 372 62 180 28 60 10
Questionnaires received 352 94.62 166 82.22 55 91.66
Usable responses 316 84.94 147 81.66 53 88.33
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44.7 percent work in the public sector, and the remaining 13.1 percent are self-employed. Of
the unemployed respondents, 65 percent are male and 35 percent are female.
With regard to the number of weekly working days, 53.9 percent of the respondents work six
days and 42.7 percent work ?ve days or fewer, whereas 3.4 percent work seven days. About
42.7 percent of the employed respondents work seven hours per day, 44.3 percent work
nine hours, and 13.1 percent work ten hours. The previous numbers of working hours are in
accord with the respondents’ type of job (i.e. public jobs extend for seven hours a day and
?ve days a week, whereas private-sector employees work nine hours a day and six days a
Table III Respondents’ personal characteristics
Percentage
Age
20-29 years 41.3
30-39 years 31
40-49 years 17.4
50-59 years 6.6
60 þ years 3.7
Gender
Male 71.3
Female 28.3
Working status
Employed 84.5
Jobless 15.5
Types of job
Public sector 42.7
Private sector 44.3
Self-employment (own business) 13.1
Monthly income
Less than JD500 74.8
JD500-JD999 15.9
JD1,000-JD1,499 5.8
JD1,500-JD1,999 3.5
JD2,000 þ 1
Level of education
Secondary and less 19.2
Diploma 13.6
Bachelor’s degree 53.3
Higher education 13.8
Marital status
Single 17.1
Married 82.9
Place of residency
Owned 69.8
Rented 30.2
Working days
Five days or fewer 42.7
Six days 53.9
Seven days 3.4
Monthly expenditures
Less than JD500 84.9
JD500-JD999 11.6
JD1,000-JD1,499 2.7
JD1,500-JD1,999 0.8
JD2,000 þ 0
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week). About 47 percent of those who are employed work in the services sector, 29.4
percent work in the commercial sector, 14.4 percent work in the industrial sector, and the
remaining 9.1 percent work in the agricultural sector.
Finally, the respondents’ monthly income ranges between JD130 and JD2,000 with an
average of JD380, whereas their monthly expenditures range between JD30 and JD1,800
with an average of JD276. About 74.8 percent earn less than JD500, 15.9 percent earn
between JD500 and JD999, 5.8 percent earn between JD1,000 and JD1,499, 3.5 percent
earn between JD1,500 and JD1,999, and only 1 percent earns JD3,000 or more. It is worth
noting that 38.1 percent of the respondents earn less than Jordan’s annual per capita
income of JD220 (Central Bank of Jordan, 2009). With regards to respondents’ monthly
expenditures, the majority (85 percent) spend less than JD500, 11.6 percent spend between
JD1,000 and JD1,499, 0.8 percent spends between JD1,500 and JD1,999, and none
spends JD2,000 or more. Accordingly, 15.7 percent of the respondents are net borrowers
(negative saving), 51.4 percent have no savings or borrowing, and the remaining 32.9
percent have savings.
4.3 Household characteristics
With regard to household characteristics, 69.8 percent of the respondents own their place of
residency and 30.2 percent rent their place of residency. About 45.5 percent of the
households have at least one car and 54.5 percent have none. Table IV shows the
percentage distribution of households according to their monthly income and expenditures.
4.4 Local demand for domestic tourism
With regards to the local demand for domestic tourism, 54.3 percent of the households
participated in domestic tourism activities (traveled locally). The number of trips ranges
between one and four. About 92.1 percent (258 out of 280) traveled once, while 4.6 percent,
1.8 percent, and 1.4 percent traveled two, three, and four times, respectively. Households’
expenditures on domestic tourismrange fromJD100 to JD1,200 with an average of JD253.3.
About 72.9 percent of households who traveled locally spent less than JD300, whereas 22.8
percent spent between JD300 and JD600. Respondents were also asked about the
in?uence of job environment, political factors and distance between home and tourstic
locations on their demand for domestic tourism. About 72.3 percent states that the job
environment affected their demand for tourism, whereas 72.1 percent states that local and
regional political conditions affected their demand for domestic tourism and ?nally, 73.4
percent states that distance between home and destination affected there demand for
domestic tourism.
The questionnaire asks those who traveled about their perceptions of the obstacles facing
households involvement in domestic tourism market. Table V shows, in decreasing order,
the obstacles facing household’s involvement in domestic tourism. Table V shows two types
of obstacles, i.e. demand and supply. Ability and willingness affect the local demand for
domestic tourism. The ability of households is determined by their disposable income, the
prices of tourism goods and services, entry fees, the size of the family, and the availability
of owned transport (obstacles 1, 2, 12, 13 and 15, respectively). The willingness of
households is determined by obstacles 6, 10, 11, 12, 14 and 15. The supply-side obstacles
include obstacles related to the cost of travel, marketing, infrastructure, government and
operators’ focus on foreign tourists against domestic ones (foreign tourists have a higher
Table IV Household’s monthly income and expenditures
Item Income (percent) Expenditure (percent)
Less than JD1,000 75.6 87.8
JD1,000-JD1,999 18.6 7.4
JD2,000-2JD999 2.9 2.9
JD3,000 þ 2.9 1.9
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multiplier effect), and the lack of tourism services in touristic sites. The least important
obstacle is the lack of diversity in touristic sites, since Jordan has a high variation of
touristic locations (Roman, Nabataean, Islamic, Christian, Bedouin, recreational, medical).
However, the ability obstacles are among the most important ?ve, indicating as argued
before that demand side of the tourism market is detrimental to the development of the
domestic tourism sector.
The questionnaire also asks those who did not travel in the year under study for the reasons
for not traveling locally. Table VI lists, in decreasing order, the reasons and their importance.
Table VI shows that four out of the ?rst ?ve reasons for not traveling locally are supply-side
related. Also, religious, social and environmental issues are among the reasons mentioned.
5. The estimation methods and results
The dependent variable in equation (1) is a binary variable that takes values of 0 or 1,
whereas the dependent variable in equation (2) is a quantitative variable. Therefore the
methods of estimation of the two equations differ extensively.
Table V Obstacles facing households’ involvement in domestic tourism – travelers’ point
of view
Obstacle Mean (0, 1)
Low disposable income 0.8895
High prices of commodities and services in tourist location 0.8837
Weakness of marketing of domestic tourist locations 0.7674
Infrastructure in general and in tourist locations speci?cally 0.7636
Employment status 0.7578
Lack of leisure time 0.7519
Operators focus on inbound tourists 0.7422
Lack of effective marketing of local media 0.7403
Lack of reliable public transport to tourist 0.6841
Environmental issues 0.6725
Lack of tourist services 0.6415
High entry fees 0.6376
Large family size 0.5988
No need for repetition 0.5620
Lack of self transport 0.5465
Lack of diversity 0.5446
External demand for tourism 0.5019
Competition from neighboring countries 0.4709
Table VI Reasons for not participating in domestic tourism activities
Reason Mean (0, 1)
Infrastructure 0.7
Lack of publicity and marketing 0.7
Lack of awareness 0.7
Focus on inbound tourists 0.6
Lack of attraction factors 0.6
High entry fees 0.6
Distance between residence and tourist location 0.5
Lack of direct transport to tourist locations 0.5
Lack of disposable income for tourism 0.5
Lack of time due to work pressure 0.5
Environmental issues 0.4
Lack of variety of tourist locations 0.4
Social reasons 0.3
Lack of demand 0.3
Religious reasons 0.2
Domestic tourism is not important for the Jordanian economy 0.1
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5.1 Binary dependent variables: probit models
Estimating choice models using the usual least squares estimation method is not the best
course of action. One problem with the linear probability model (LPM) is that the error is
heteroskedastic – that is, the variance of the error term varies from one observation to
another. The least squares method yields unreliable values of probability, less than 0 or more
than 1, due to the assumption of linearity between the probability and the explanatory
variables. The probability that an event occurs is non-linear and hence can be estimated by
a method called probit. The probit speci?cations are designed to analyze the qualitative
data re?ecting a choice between two alternatives.
The probit method provides a way of quantifying the relationship between the respondents’
characteristics in addition to other explanatory variables and the probability of choosing an
alternative. Estimating the probit model is performed by maximizing the likelihood function
with respect to all coef?cients. The maximization requires an iterative method, but in most
cases the algorithm will operate smoothly, because the PROBIT model likelihood function is
very well behaved (Hill et al., 2001). The EViews software package is used to estimate the
probit models of equation (1).
5.2 Sample selection bias: Heckit method
In equation (2) the dependent variable is observed only for households who entered the
domestic tourismmarket in the periodunder study, while it is not observable for those who did
not enter (did not travel locally). While it seems reasonable to ignore the respondents who did
not enter the domestic tourismmarket and then use the ordinary least squares (OLS) method
to estimate equation (2), ignoring those who did not travel locally creates biased results. The
biasedresults come fromthe fact that the sub-sample (households who traveledlocally) is not
random and therefore the observed data are selected by a systematic process.
Heckman (1979) analyzes the selection bias problem that results from using non-randomly
selected samples when estimating a behavioral relationship. In order to overcome this bias
problem, he suggests an alternative estimation method, which is known as the Heckit
method and is best used when there is a non-randomsample drawn. Therefore the use of the
Heckit method is deemed appropriate for this study since the sample of those who traveled
locally is a non-random sample.
Following Heckit method, two steps estimation are conducted for equation (2). In step 1, the
probit model of decision equation is estimated by maximum likelihood estimation method.
For each observation in the selected sample, the value of the inverse Mill’s ratio (IMR) is
calculated and saved. IMR accounts for the fact that the observed sample is not random. In
step 2, using the selected sample, the dependent variable in equation (2) is regressed on
the explanatory variables and the IMR (the IMR is created from the ?rst step probit
estimation) using the OLS method.
5.3 The estimation results
In this section, socio-economic explanatory variables that re?ect the respondents’ personal
characteristics and household characteristics, in addition to other variables, are examined
for their effect on Jordanian households’ involvement in the domestic tourism market and on
their tourism expenditures. Table VII presents the de?nitions of all explanatory variables.
5.4 Antecedents of entering domestic tourism market (stage 1): probit model
Equation (1) relates the explanatory variables to the probability of entering the domestic
tourism market. The explanatory variables that affect the households decision include the
respondents’ characteristics (age, level of education, martial status, working status, gender,
type of job, number of working days, number of daily working hours, etc.), the household
characteristics (yearly income and expenditures, family size, number of working members,
availability of family car) and other factors (entry fees, demand for external tourism, sense of
national duty, distance, tourism offers, festivals and occasions, political and environmental
issues).
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While adding expenditures on external tourisminto the model may be wise, it is not the case.
The decision not to add expenditures on external tourism was taken because it is very
dif?cult to measure participants’ expenditures on domestic and external tourism (some of
the expenditures could be implicit). Furthermore, respondents were not asked to report their
expenditures on external tourism since the focus of the study is on the antecedents of local
demand for domestic tourism. Accordingly, the demand for external tourismwas added as a
dummy variable (1 for those who traveled externally, and 0 for those who did not travel
externally). The researchers asked those who traveled locally and those who traveled
externally with the explicit purpose of determining whether external travel in?uenced their
demand for domestic tourism during the period of the study.
It was expected that those who traveled externally will be less likely to travel locally and their
expenditures on domestic tourism will be less. The model of the study examines
respondents who actually traveled externally during the period of the study and not those
who had the intention to travel externally. Finally, both the cost and ease of external travel are
among the antecedents of respondents’ demand for external tourism and re?ect on the
participants’ decision to travel externally.
The results of the ?rst stage probit model, which determine the factors that affect the
probability of households’ involvement in domestic tourism market, are shown in Table VIII.
Table VIII presents the results of estimation of the probit model in equation (1); it shows that
there are three categories of factors:
1. factors that increase the probability of entering the domestic tourism market;
Table VII De?nitions of variables
Variable De?nition
AGE Respondent’s age
AGES Respondent’s age squared
CAR Car ownership dummy (1 if respondent owns a car, 0 otherwise)
DISTANCE Distance between home and touristic location dummy (1 distance affect households decision, 0 otherwise)
DOMESTIC OFFERS Touristic offers dummy (1 if household gets offers to domestic touristic sites, 0 otherwise)
EXTOURISM Demand for external tourism dummy (1 if household prefers external tourism, 0 otherwise)
FAMILYSIZE Family size
FCAR Family car ownership dummy (1 if household has family car, 0 otherwise)
FEES Touristic sites entry fees
FESTIVALS Festivals and occasions dummy (1 if local festivals are organized, 0 otherwise)
GENDER Gender dummy variable (1 if male, 0 female)
HINCOME Head of household income
IMR Inverse Mill’s ratio
LOAN Loan dummy (1 if household has current loan payment, 0 otherwise)
LOED Years of formal education
MIDDLER Region dummy (1 if central region, 0 otherwise)
MS Respondent’s marital status dummy (1 if single, 0 married)
NDUTY National duty dummy (1 if household believe that supporting domestic tourismis a national duty, 0 otherwise)
NOVISITS Number of previous trips to local touristic sites
NOWORKERS Number of working family members
POLITICS Political events dummy (1 if there is political event, 0 otherwise)
POR House ownership dummy (1 if individual owns his house, 0 otherwise)
SERSEC Sector dummy (1 if service sector, 0 otherwise)
SOUTHR Region dummy (1 if Southern region, 0 otherwise)
TOJOB Type of job dummy (1 if public job, 0 otherwise)
WDS Number of working days
WHRS Number of daily working hours
WS Working status dummy (1 if employed, 0 unemployed)
YEXP Household’s yearly expenditures
YINCOME Family income
YINCOME Household’s yearly income
YSAVING Yearly saving
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2. factors that decrease the probability of entering the domestic tourism market; and
3. other factors that have no effect.
Each group of factors consists of some respondent and household characteristics.
The results show that older respondents, those with a higher level of education, those who
are employed, those who work in the private sector or are self-employed, those who work
longer hours, those who own their place of residency, those who have a car, and ?nally those
who are working overseas are more likely to enter the domestic tourism market (travel
locally), at least at the 10 percent signi?cance level. The previous results can be explained in
accordance with two main dimensions – i.e. ability enhancement and cost reduction.
For example, older people may be retired, may have less expenditure if their dependents
have left home, and have much more time and savings. Higher education and being
employed re?ect a higher income and therefore increased ability to enter the tourismmarket.
Working for the private sector or being self-employed indicates a higher income (the private
sector pays more than the public sector) and people in his sector have more control over
their working arrangements.
Working overseas implies higher income, higher demand for luxury goods and services, and
a seasonal return back home to visit family and friends. Those who own their place of
residency pay no rent and therefore have less expenditure and more ability to travel. Those
who own a car can use it for travel; car ownership also re?ects higher income and a reduced
Table VIII Antecedents of households’ demand for domestic tourism: Probit model
Variable Coef?cient Standard error Probability
Head of household characteristics variables (RC
i
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AGE 0.019299 0.012347 0.1181
AGES 0.003372 0.001011 0.0009***
LOED 0.223100 0.108975 0.0406**
TOJOB 22.042872 0.760145 0.0072***
POR 0.599883 0.201031 0.0028***
WS 4.622239 2.618902 0.0776*
GENDER 0.090298 0.214439 0.6737
WHRS 1.277905 0.442639 0.0039***
SERSECTOR 20.285778 0.100066 0.0043***
MS 0.139455 0.293522 0.6347
WDS 0.075559 0.205646 0.7133
CAR 0.317015 0.194985 0.1040*
Household characteristics variables (HC
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YINCOME 8.58E-05 4.27E-05 0.0446**
YEXP 29.62E-05 5.27E-05 0.0683*
FAMILYSIZE 20.459901 0.209643 0.0283**
MIDDLER 0.075195 0.190149 0.6925
SOUTHR 21.447944 0.494706 0.0034**
FCAR 0.452286 0.060187 0.0000***
NOWORKERS 0.527324 0.211412 0.0126**
NOVISITS 20.479315 0.160758 0.0029***
Other factors variables (OF
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FEES 20.518153 0.203058 0.0107**
EXTOURISM 20.592913 0.206681 0.0041***
NDUTY 0.700454 0.209224 0.0008***
POLITICS 20.650841 0.207557 0.0017***
DISTANCE 0.388705 0.219832 0.0770*
DOMESTIC OFFERS 0.673767 0.134562 0.0000***
FESTIVALS 0.827145 0.221396 0.0002***
Notes: Dependent variable: DDT. Number of observations ¼ 435, log likelihood= 2 145.0190.
*Signi?cant at the 1 percent level; **signi?cant at the 5 percent level; ***signi?cant at the 10 percent
level
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cost of traveling. With regard to the household characteristics that affect the probability of
entering the domestic tourism market, the results show that households with a higher yearly
income, those who have a family car or second car, those who have more working family
members, those who believe that supporting domestic tourism is a national duty, those who
receive tourstic offers and those who are far away from touristic sites are more likely to travel
locally. A higher income, having a family car and more working family members imply more
ability. The belief that visiting local touristic sites and supporting domestic tourism is a
national duty increases a household’s tendency to travel locally. The availability of touristic
offers to visit local sites increases the probability of entering the domestic tourism market
through reducing cost.
Finally, the farther the household is from touristic sites, the higher is the tendency to visit
these sites. Regarding the respondent characteristics that decrease the probability of
entering the domestic tourism market, Table VIII shows that respondents who work in the
public sector, those who work in the service sector, those who have higher yearly
expenditures, those who have a larger family size, those who live in the Southern sector and
those who visited have touristic sites before are less likely to travel locally. With regard to the
other factors, the results show that higher entry fees, spending on external tourism and
political disturbances make the household less likely to travel locally. Finally, the results also
show that respondents’ gender, respondents’ number of working days, and respondents’
martial status have no effect on the probability to travel locally for tourism purposes.
5.5 Antecedents of tourism expenditures
Equation (2) presents the explanatory variables that affect the households’ expenditures on
domestic tourism. Table IX shows that respondents’ and households’ characteristics, in
addition to other factors, affect households’ expenditures on domestic tourism. The results in
Table IX also show that male respondents, those with higher level of education and higher
income tend to spend more. Male respondents are the main source of income in Jordan and
therefore they play a major role in deciding how much to spend (they are mainly heads of
households). Those with higher education are well traveled and perceive tourism to be
bene?cial and a necessity.
Also, higher education implies a higher income and more ability. With regards to the
in?uence of household characteristics, the study ?nds that: the bigger the family size, the
bigger the yearly savings and the higher yearly income are – and the greater the
expenditures on domestic tourism are. Table IX also shows that a perception of supporting
domestic tourismto be part of national duty results in more expenditure on domestic tourism.
Finally, higher fees increase expenditures.
Table IX also shows the factors that negatively affect households’ expenditures. It shows that
older respondents, married respondents, and those with higher yearly expenditures spend
less on domestic tourism.
A positive relationship exists between age and lifecycle and expenditure. The older a person
becomes the higher his/her expenditure (family requirements) becomes. Therefore, less
money is available for tourism. With regard to household characteristics, Table IX shows that
the availability of a family car reduces the cost of travel and therefore reduces expenditure,
since transportation cost per traveler decrease. Due to the substitution effect, households
who travel externally spend less on domestic tourism ceteris paribus. Net borrower
households (those who have loan payments) spend less. Households that are exposed to an
awareness of touristic offers (cheap packages) spend less. Finally, Table IX shows that the
numbers of working days and type of job have no effect on tourism expenditures.
Common factors exist in both Tables VIII and IX that both have a signi?cant impact on the
probability to enter the domestic tourismmarket and on tourismexpenditure. However, these
factors vary in their strength and direction. For example, respondents with a higher level of
education, households with a higher income and those who have a perception that
supporting domestic tourism is part of their national duty are more likely to travel locally and
spend more.
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On the other hand, higher non-touristic expenditures and traveling externally (outbound
tourism) make households less likely to travel locally, decreasing domestic tourism
expenditure. Respondents’ gender and martial status affect expenditure on domestic
tourism but not the probability of traveling locally. Family size and entry fees make
households less likely to travel but increase expenditure on domestic tourism. Finally, the
availability of a family car and being aware of touristic offers make households more likely to
travel and decrease tourism expenditure.
6. Conclusions and recommendations
This study examines antecedents of households’ local demand for domestic tourism using a
random sample of 600 Jordanian households. The study proposes a two-stage estimation
process. Stage 1 identi?ed the antecedents of the probability of entering the domestic
tourism market. Stage 2 identi?ed the antecedents of household expenditure on domestic
tourism. Traditionally the majority of studies in the tourism demand literature focus on prices
and income as the main antecedents of demand for tourism. While prices and income are
good indicators of cost and ability, this study identi?ed other factors that predict and explain
local demand for domestic tourism more comprehensively. Accordingly, vectors of heads of
households’ characteristics, and households’ characteristics in addition to other factors, are
examined for their effect on households’ local demand for domestic tourism.
With regard to stage 1, i.e. the probability of traveling locally, the study ?nds that heads’ of
households characteristics (i.e. age (þ), level of education (þ), type of job (2), ownership of
residence (þ), working status (þ), number of daily working hours (þ), sector of operation
(2)), households characteristics (i.e. yearly income (þ), yearly expenditures (2), family size
(2), region (2), availability of family car (þ), number of working family members (þ), and
Table IX Antecedents of households’ expenditures on domestic tourism
Variable Coef?cient Standard error t-statistic Probability
Head of household characteristics variables (RC
i
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Constant 0.584128 0.212809 2.744846 0.0066***
GENDER 0.047787 0.023052 2.072971 0.0394**
AGE 20.025087 0.007462 23.361813 0.0009***
AGES 0.000262 9.22E-05 2.842547 0.0049***
LOED 0.026738 0.012390 2.158014 0.0320**
WDS 0.049355 0.031577 1.562992 0.1195
TOJOB 20.037623 0.027512 21.367540 0.1729
MS 20.076909 0.028363 22.711608 0.0072***
HINCOME 6.48E-05 1.67E-05 3.889806 0.0001***
Household characteristics variables (HC
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FAMILYSIZE 0.080213 0.021213 3.781244 0.0002***
YEXP 21.78E-05 9.27E-06 21.921707 0.0559*
YSAVING 0.000154 4.60E-05 3.356619 0.0009***
FCAR 20.033641 0.020253 21.661037 0.0981*
MIDDLER 20.030246 0.019819 21.526079 0.1284
YINCOME 1.24E-05 4.98E-06 2.489019 0.0136**
Other factors variables (OF
i
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EXTOURISM 20.041067 0.022904 21.792963 0.0744*
NDUTY 0.044611 0.021202 2.104071 0.0365**
FEES 0.056683 0.022079 2.567240 0.0109**
LOAN 20.034522 0.020589 21.676700 0.0950*
DOMESTIC OFFERS 20.081009 0.027320 22.965215 0.0034***
IMR 20.085824 0.040513 22.118416 0.0353**
Notes: Dependent variable: EODT. R
2
¼ 0:407069; adjusted R
2
¼ 0:355392; mean of dependent
variable ¼ 0:160420; SD of dependent variable ¼ 0:165307; log likelihood ¼ 153:3807; F-statistic ¼
7.877122; probability (F-statistic) ¼ 0.000000; Durbin-Watson statistic=1.830621. *Signi?cant at the
10 percent level; **signi?cant at the 5 percent level; ***signi?cant at the 1 percent level
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number of visit to touristic locations (þ)), and other factors (i.e. entry fees (2), demand for
outbound tourism (2), sense of national duty (þ), political disturbances (2), local festivals
and occasions (þ), distance (þ) and domestic offers (þ)) affect households’ tendency to
travel locally.
With regard to stage 2, i.e. the antecedents of tourism expenditure, the study ?nds that head
of households’ characteristics (i.e. gender (þ), age (þ), level of education (þ), martial
status (2), income (þ)), households’ characteristics (i.e. family size (2), yearly
expenditures (2), yearly savings (þ), availability of family car (2), income (þ)) and other
factors (i.e. demand for outbound (2), sense of national duty (þ), fees (þ), loan payment
(2), touristic offers (2)) affect households’ expenditures on domestic tourism.
Therefore, the study presents numerous recommendations. First, the GoJ needs to
understand that problems with local demand for domestic tourism are both supply- and
demand-side problems. Furthermore, income and substitution effects affect tourism.
Therefore, governmental policies must address both supply and demand. For example,
lowering prices does not necessarily stimulate local demand. A need must be met for a
holistic approach that considers factors that make households more likely to travel locally,
and at the same time reduce the impact of factors that decrease the tendency of households
to travel locally.
In addition, governments must overcome barriers and obstacles to travel locally, such as
poor infrastructure, poor marketing initiatives, and lack of awareness of touristic sites. Finally,
government policies should target government employees, school students and outbound
tourist with attractive offers. Studies should examine the size and antecedents of Jordanians’
outbound tourism in order to make the substitution effect work to the interest of domestic
tourism.
References
Alegre, J. and Pou, L. (2004), ‘‘Microeconometric determinants of the probability of tourism
consumption’’, Tourism Economics, Vol. 10, pp. 125-44.
Allen, D. and Yap, G. (2009), ‘‘Investigating other leading indicators in?uencing Australian domestic
tourism demand’’, paper presented at 18th World IMACS/MODSIM Congress, Cairns, 13-17 July.
Central Bank of Jordan (2009), Annual Report, Central Bank of Jordan, Amman.
Chan, F., Lim, C. and McAleer, M. (2005), ‘‘Modelling multivariate international tourism demand and
volatility’’, Tourism Management, Vol. 26 No. 3, pp. 459-71.
Chan, F., Lim, C. and McAleer, M. (2004), ‘‘Modelling conditional correlations in international tourism
demand’’, in Pahlwostl, C., Schmidt, S., Rizzoli, A.E. and Jakeman, A.J. (Eds), Complexity and
Integrated Resources Management: Transactions of the International Conference on Environmental
Modelling and Software, International Environmental Modelling and Software Society, Manno.
Coenen, M. and Lobke, V.E. (2003), ‘‘A study of the demand for domestic tourism by Swedish
households using a two-staged budgeting model’’, Scandinavian Journal of Hospitality and Tourism,
Vol. 3 No. 2, pp. 114-33.
Department of Statistics (2009), Statistical Yearbook, Issue 57, Department of Statistics, Amman.
Eugenio-Martin, J.L. (2003), ‘‘Modeling determinants of tourism demand as a ?ve-stage process:
a discrete choice methodological approach’’, TourismandHospitality Research, Vol. 4 No. 4, pp. 341-54.
Fraihat, H. (2010), personal communication, Director, Department of Statistics, Amman.
Hamal, K. (1996), ‘‘Modelling domestic holiday tourism demand in Australia: problems and solutions’’,
Asia Paci?c Journal of Tourism Research, Vol. 1 No. 2, pp. 35-46.
Heckman, J. (1979), ‘‘Sample selection bias as a speci?cation error’’, Econometrica, Vol. 47, pp. 153-61.
Hill, R.C., Grif?ths, E. and Judge, G. (Eds) (2001), Undergraduate Econometrics, Wiley, New York, NY.
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2
1
2
4
J
a
n
u
a
r
y
2
0
1
6
(
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T
)
Lim, C. (2006), ‘‘A survey of tourism demand modeling practice: issues and implications’’, in Dwyer, L.
and Forsyth, P. (Eds), International Handbook on the Economics of Tourism, Edward Elgar, Cheltenham,
pp. 45-72.
Sadeghi, J., Jamshidi, M. and Tayyebi, S. (2004), ‘‘Expenditure and price elasticities of demand for
household domestic tourism in Iran – a cross-sectional analysis’’, paper presented at the Economic
Research Forum for the Arab Countries, Iran and Turkey, Eleventh Annual Conference, Beirut,
16-18 December.
World Bank (2009), World Development Indicators, World Bank, Washington, DC.
World Trade and TourismCouncil (2007), Annual Reports, available at: www.wttc.org/eng/About_WTTC/
Annual_Reports/(accessed April 26, 2010).
Yap, G. (2008), ‘‘Intrastate and interstate tourism demand in Australia: an empirical analysis’’,
in Richardson, S., Fredline, L. and Ternel, M. (Eds), Proceedings of the 18th Annual CAUTHE
Conference, CD-ROM, Grif?th University, Gold Coast.
Corresponding author
Ihab Khaled Magableh can be contacted at: [email protected]
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doc_312783786.pdf
The purpose of this paper is to investigate antecedents of households’ local demand for
domestic tourism in Jordan
International Journal of Culture, Tourism and Hospitality Research
Antecedents of local demand for domestic tourism in Jordan
Ihab Khaled Magableh Radwan Kharabsheh
Article information:
To cite this document:
Ihab Khaled Magableh Radwan Kharabsheh, (2013),"Antecedents of local demand for domestic tourism in J ordan", International J ournal of
Culture, Tourism and Hospitality Research, Vol. 7 Iss 1 pp. 78 - 92
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Antecedents of local demand for domestic
tourism in Jordan
Ihab Khaled Magableh and Radwan Kharabsheh
Abstract
Purpose – The purpose of this paper is to investigate antecedents of households’ local demand for
domestic tourism in Jordan.
Design/methodology/approach – A sample of 600 households is surveyed and a two-stage demand
model is estimated. Stage 1 identi?es the antecedents of the probability of entering the domestic tourism
market. Stage 2 identi?es the antecedents of households’ expenditures on domestic tourism. The Heckit
method is used to estimate the ?rst stage and the OLS is used to estimate the second stage.
Findings – Certain socio-economic factors (household characteristics, individual characteristics and
ability variables) impact the local demand for domestic tourism, as do price and income variables.
Research limitations/implications – The generalizability of results to other countries is limited.
Practical implications – Identi?cation of antecedents of local demand for domestic tourism helps
governments to formulate and modify future tourism strategies.
Originality/value – This paper contributes to the literature by including socio-economic variables in the
domestic tourismdemand model. Further, there is a dearth of studies in Jordan in general and regarding
domestic tourism in particular.
Keywords Jordan, Tourism, Government policy, Domestic tourism, Local demand, Heckit method,
Socio-economic factors
Paper type Research paper
1. Introduction
Tourism is the world’s largest and fastest growing industry, and indeed the biggest provider
of jobs (World Trade and TourismCouncil, 2007; Coenen and Lobke, 2003; Chan et al., 2004,
2005). According to the World Bank (2009), $US2 trillion was earned by the tourism industry
in 2007. Tourismexpenditures have a positive impact on countries’ GDP, inter-linked sectors,
labor market and economic health in general. This positive impact of tourismappears at both
the micro and macro levels.
The literature distinguishes between local demand for external tourism (outbound tourism)
and demand for domestic tourism. The demand for domestic tourism is classi?ed into
external demand (inbound tourism) and local demand. External tourism has a bigger
multiplier effect on the economy in the form of increased tourism income, tourism GDP,
creation of jobs, support of inter-linked sectors such transportation and hospitality
industries, and ?nally increased foreign reserves. Local demand for domestic tourism, while
sharing some of the bene?ts of external tourism, helps in reducing foreign currency leakages
conditioned by domestic tourismbeing a substitute for outbound tourism. The advantages of
local tourism are due to the fact that it is less susceptible to regional and global economic
and political disturbances. For example, due to the near collapse of global tourism after the
September 11 attacks, terrorism and wars, the recent ?nancial crises, and the decreased
volume of international travel due to the spread of disease and epidemics such as SARS and
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Ihab Khaled Magableh is
based at the Department of
Managerial Sciences, Talal
Abu Ghazaleh College of
Business, German Jordan
University, Amman, Jordan.
Radwan Kharabsheh is
based at the Department of
Business Administration,
Faculty of Economics and
Administrative Sciences,
The Hashemite University,
Zarqa, Jordan.
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swine ?u, local demand for domestic tourism becomes a safeguard and a viable substitute
for the shortage of inbound tourism.
In addition to its economic impact, local demand for domestic tourism creates awareness of
cultural heritage and loyalty to the country, increases ties among citizens within the country,
and helps protect the environment through creating awareness. In the economic sense local
tourism creates jobs and decreases poverty, limits the effect of seasonality of international
tourism, and limits income drain from the country. While the focus has traditionally been on
inbound tourism in the Middle East and North Africa (MENA) region, local demand for
domestic tourism has attracted less attention. In Jordan, tourism depends for a large part on
international tourism. While there are 480 tourist ?rms for inbound and outbound tourism,
there are as few as 20 operators for local tourism (Department of Statistics, 2009).
Considering that Jordan has plenty of world-class tourist locations, including historic,
religious and therapeutic sites, to offer, the problem is the demand for local tourism and not
the availability of touristic sites. For example, Petra, one of Jordan’s popular touristic sites,
has been voted one of the new world wonders. In addition, six of the ten major ancient
Roman cities are located in Jordan. The problem is in the ability to create, increase and
sustain local demand for domestic tourism. More importantly, in the tourism demand
literature, it is well acknowledged that income and tourism prices are the leading demand
antecedents in tourism demand analyses. For example, most studies focus on income and
price variables as demand antecedents for travel. According to the literature review by Lim
(2006), of 124 published papers, 105 empirical papers employed income variables. The
author also ?nds that 94 percent of the papers use relative prices, whereas 52 percent use
transportation costs.
Nevertheless, the literature neglects other possible socio-economic variables such as family
size, the availability of family and public transport, knowledge and awareness of local
destinations, household debt, sense of national duty, availability of time for leisure and the
number of hours worked in paid jobs. In fact, several studies argue that these variables
in?uence consumers in making decisions to travel. This study contributes to the literature by
including socio-economic variables in the tourism demand model.
2. Tourism in Jordan
The tourism industry makes a substantial contribution to the Jordanian economy. In 2009, it
accounted for 11 percent of GDP, with a compound annual growth rate (CAGR) of 16.2
percent during the period 2003-2009 (Department of Statistics, 2009). Employment in the
tourism cluster, including indirect employment, was estimated at around 130,000 (11
percent of the work force). The tourism cluster itself employs 34,405 people, of whom 77.5
percent are in the hotel and restaurant industry. In 2009, employment just around Amman
(the capital) accounted for 72 percent of total national employment.
Women form just 10 percent of overall tourism employment, a proportion that has not
changed much over the years within the hotel industry (?ve-star hotels). In comparison with
regional peers, however, Jordan’s tourism industry shows very low growth, both in terms of
tourist arrivals as well as their expenditure (World Bank, 2009). Table I shows the main
tourism indicators in Jordan. It shows an improvement over the years (2005-2009). It is
noted, however, that the room occupancy ratio is as low as 55 percent. Keeping in mind that
there are 481 hotels ranging from non-classi?ed to ?ve-star hotels and that the variety of
prices re?ects this range, it becomes clearer that the main problem is the demand side
rather than the supply side.
Given the importance of the tourismsector to the economy, the Government of Jordan (GoJ),
through the Ministry of Tourism and Antiquities (MoTA), has paid considerable attention to
developing a coherent tourism strategy (2004-2010). The GoJ employed numerous
initiatives to decrease the prices and costs of local tourism in Jordan, with very little success
(Fraihat, 2010). This implemented strategy follows froma heavy focus on price factors alone.
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Other non-price factors can better and comprehensively predict local demand for domestic
tourism. By identifying these factors, the GoJ may include such elements in its future
strategies to alleviate the level of local demand for domestic tourism in the country.
3. Local demand for domestic tourism
While an abundance of studies examine antecedents, development, and issues regarding
local demand for domestic tourism both in developed and developing countries, there is a
dearth of studies addressing these issues in Jordan. In addition, in the context of local
demand for domestic tourism, most studies focus on income and price variables as demand
antecedents for travel.
According to the literature review by Lim (2006), 105 empirical papers out of a total of 124
published papers employ income variables. The author also ?nds that 94 percent of the
papers use relative prices, whereas 52 percent use transportation costs. Nevertheless, the
literature neglects other possible socio-economic variables such as family size, the
availability of family and public transport, knowledge and awareness of local destinations,
household debt, availability of time for leisure and the number of hours worked in paid jobs.
In fact, several studies argue that these variables in?uence consumers in making decisions
to travel. For example, Allen and Yap (2009) model demand for Australian domestic tourism
using a panel approach. They ?nd that the income elasticity for domestic visiting friends and
relatives (VFR) trips in Australia is negative, implying that Australian households will not
choose to travel domestically when there is an increase in household income. They also ?nd
that the national income variables are positively correlated with domestic business tourism
demand, indicating that demand is strongly responsive to changes in Australia’s economic
conditions.
More importantly, the researchers ?nd that an increase in the current prices of domestic
travel causes demand for domestic trips to fall in the next one or two quarters ahead. Finally,
they ?nd that the coef?cients for lagged dependent variables are negative, indicating that
trips are made on a periodic basis. Yap (2008) examines the economic antecedents of
intrastate and interstate tourism demand in Australia. He investigates whether the economic
impacts of income and tourism prices differ between intrastate and interstate tourism using
Johansen’s co-integration analysis and error-correction models. Yap’s study highlights
numerous interesting ?ndings. First, changes in all economic variables, except income, in
the short term affect interstate tourist arrivals to Queensland. Income also in?uences
interstate tourist arrivals from Victoria to New South Wales in the short term. Secondly,
long-term income coef?cients are mostly negative, implying that an increase in domestic
household income depresses intrastate and interstate tourism demand in Australia.
Finally, domestic transportation costs are the main economic factors that in?uence interstate
tourism demand for Victoria and Western Australia in the long-term. Alegre and Pou (2004)
examine the frequency of travel as a predictor of the demand for local tourism in Spain. They
Table I Main tourism indicators (2005-2009)
Indicator 2005 2006 2006 2008 2009
Number of arrivals (millions) 5.8 6.7 6.5 7.03 7.1
Gross tourism income/GDP at current prices
(percent) 11.4 13.9 14 14.1 14.3
Value added of tourism at current prices (JD,
million) 510.7 730.4 819.2 1,004.3 1,100.6
Number of hotels 468 476 470 481 490
Number of rooms (thousands) 20.8 21.6 21.6 22.5 22.7
Room occupancy ratio (percent) 49.4 42.4 47.3 55.3 54
Employees in hotels (thousands) 12.9 13.5 13.2 14 14.5
Employees in tourism sector (thousands) 29.4 31.1 34.4 38.3 40.6
Source: Central Bank of Jordan (2009)
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use household data to examine antecedents of the number of quarters with positive tourist
expenditures within a year. Alegre and Pou (2004) highlight the relevance in travel frequency
analyses of distinguishing between the participation decision and the frequency decision
conditional on participation. They argue that although many socio-demographic variables
only show explanatory power for the participation decision, the two most relevant factors by
far in explaining each decision are the previous year’s tourism demand decisions
(suggesting evidence of habit persistence in tourism decisions) and disposable income,
although with an income elasticity below the unit.
Sadeghi et al. (2004) estimate the expenditure and price elasticity of demand for household
domestic tourism in Hamedan, Iran, using cross-section data and the almost ideal demand
system (AIDS) model. They ?nd that the majority of tourist household heads are of middle
age, fairly well off, highly educated, well employed, traveled from larger cities, used their
own cars and their trips lasted, on average, close to three days. They also ?nd that the
Hamedan tourists did not include all social classes equally. Hence, there is room to expand
the tourism industry and cover a larger number of tourists by further facilitating tourism
activities and removing the obstacles. Eugenio-Martin (2003) argues that in the there are
multiple factors involved in the decision leading to the tourists’ destination choice. He
contends that individuals or families with exactly the same socio-economic and
demographic characteristics may choose very different destinations. In dealing with the
so-called ‘‘heterogeneity problem’’ (i.e. recognizing that there are taste differences among
tourists and that ?nal destination choice is not an independent decision, but the last decision
of a set of choices that are determining it), Eugenio-Martin (2003) argues that tourists face a
?ve-stage decision process:
1. people have to decide whether or not to travel within a period of time;
2. those who expect to travel need to estimate a budget for tourism expenses;
3. given the budget, they need to determine the frequency and length of stay of their trip;
4. once a date and the length of stay are proposed, tourists need to choose which kind of
tourist destination to visit; and
5. from among all the available destinations that satisfy a tourist’s conditions, the ?nal
destination and the mode of transportation are chosen.
Hamal (1996) models demand for domestic holiday in Australia and concludes that demand
for domestic holiday travel in Australia is in?uenced positively by per capita real household
disposable income and the real prices of holiday travel and accommodation overseas, and
negatively by the domestic real prices of holiday travel and accommodation. Hamal (1996)
explains that the positive and relatively higher cross price elasticity indicates that
substitution between domestic and overseas holiday destinations exists, and that holiday
makers are more sensitive to the change in real prices of holiday travel and accommodation
overseas than to the changes in income and the domestic real prices holiday travel and
accommodation.
This paper examines the socio-economic factors that affect the local demand for domestic
tourism by devising a two-stage process model of demand. The paper is divided into six
sections. Section 1 presents the introduction to the paper, while section 2 presents tourismin
Jordan and section 3 discusses local demand for domestic tourism. Section 4 presents the
model framework and the methodology, while section 5 presents the estimation method and
results. Finally, the last section presents conclusions and recommendations.
4. Model framework and method
A household enters a domestic tourism market as a demander when it has effective demand
for tourismgoods or services. Households’ involvement in the domestic tourismmarket goes
through two sequential stages. In the ?rst stage, a household has to decide whether to enter
the domestic tourismmarket and travel (whether to spend on tourismgoods and services) or
not. Lack of effective demand can be due to lack of ability and/or willingness factors. But, if a
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household decides to travel and spend on domestic tourismgoods and services, i.e. the ?rst
stage, it decides on the amount of expenditure, i.e. the second stage. The following two
equations represent the previous two stages:
ProbðDDTÞ ¼ FðRC
i
; HC
i
; OF
i
Þ; ð1Þ
where Prob(DDT) is a dummy variable that takes a value of 1 if the household chooses to
travel and spend on domestic tourism, and 0 otherwise; RC
i
is the vector of respondents’
(heads of household) characteristics that affect households’ demand for domestic tourism;
HC
i
is the vector of households’ characteristics that affect households’ demand for domestic
tourism; and OF
i
is the vector of other factors that affect households’ demand for domestic
tourism.
HEODT ¼ FðRC
j
; HC
j
; OF
j
Þ; ð2Þ
where HEODT is households’ expenditures on domestic tourism; RC
j
is the vector of the
head of households’ characteristics that affect households’ expenditures on domestic
tourism; HC
j
is the vector of households’ characteristics that affect households’ expenditures
on domestic tourism; and OF
j
is the vector of other factors that affect households’
expenditures on domestic tourism.
While a single equation may suf?ce to model the proportion of tourism spending
domestically as a function of the explanatory variable, the problem is that many of the
respondents did not report their precise tourismexpenditures. More importantly, many of the
respondents did not travel locally during the period under study, and thus their expenditure
on domestic tourism is zero. Therefore, the use of the two-stage model is deemed
appropriate in this case.
4.1 The survey
A random sample of 600 Jordanian households was surveyed in 2009 using a questionnaire
at the regional level (Northern, Middle and Southern). The distribution of the sample among
regions is in accord with the population distribution. Table II shows the size, response and
usage rates of the sample. Table II shows that the highest percentage of questionnaires
received was in the Middle region (94.6 percent) followed by the Southern region (91.6
percent), while the highest percentage of usable questionnaires was received in the
Southern region (88.3 percent), followed by the Middle region (84.95 percent).
The questionnaire was completed by the head of each household. It consisted of three
sections. The ?rst section described the characteristics of the respondents, while the
second described the characteristics of the households. The third section explored
households’ demand for domestic tourism in 2009.
4.2 Respondent’s characteristics
Table III shows the respondents’ personal characteristics. It shows that the respondents’
ages range between 20 and 61 years with an average of 34.4 years. About 71.3 percent of
the respondents are male; 82.9 percent of the respondents are married, of whom 72.14
percent are male. Table III also shows that 13.8 percent of the respondents have higher
education, 53.3 percent have a Bachelor’s degree, 13.6 percent have a diploma, and 19.2
percent have high school education or less. About 84.5 percent of the respondents are
employed (72.9 percent of them are male) of whom 44.3 percent work in the private sector,
Table II Response rate of the sample
Middle Region Northern Region
Southern
Region
n % n % n %
Questionnaires distributed 372 62 180 28 60 10
Questionnaires received 352 94.62 166 82.22 55 91.66
Usable responses 316 84.94 147 81.66 53 88.33
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44.7 percent work in the public sector, and the remaining 13.1 percent are self-employed. Of
the unemployed respondents, 65 percent are male and 35 percent are female.
With regard to the number of weekly working days, 53.9 percent of the respondents work six
days and 42.7 percent work ?ve days or fewer, whereas 3.4 percent work seven days. About
42.7 percent of the employed respondents work seven hours per day, 44.3 percent work
nine hours, and 13.1 percent work ten hours. The previous numbers of working hours are in
accord with the respondents’ type of job (i.e. public jobs extend for seven hours a day and
?ve days a week, whereas private-sector employees work nine hours a day and six days a
Table III Respondents’ personal characteristics
Percentage
Age
20-29 years 41.3
30-39 years 31
40-49 years 17.4
50-59 years 6.6
60 þ years 3.7
Gender
Male 71.3
Female 28.3
Working status
Employed 84.5
Jobless 15.5
Types of job
Public sector 42.7
Private sector 44.3
Self-employment (own business) 13.1
Monthly income
Less than JD500 74.8
JD500-JD999 15.9
JD1,000-JD1,499 5.8
JD1,500-JD1,999 3.5
JD2,000 þ 1
Level of education
Secondary and less 19.2
Diploma 13.6
Bachelor’s degree 53.3
Higher education 13.8
Marital status
Single 17.1
Married 82.9
Place of residency
Owned 69.8
Rented 30.2
Working days
Five days or fewer 42.7
Six days 53.9
Seven days 3.4
Monthly expenditures
Less than JD500 84.9
JD500-JD999 11.6
JD1,000-JD1,499 2.7
JD1,500-JD1,999 0.8
JD2,000 þ 0
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week). About 47 percent of those who are employed work in the services sector, 29.4
percent work in the commercial sector, 14.4 percent work in the industrial sector, and the
remaining 9.1 percent work in the agricultural sector.
Finally, the respondents’ monthly income ranges between JD130 and JD2,000 with an
average of JD380, whereas their monthly expenditures range between JD30 and JD1,800
with an average of JD276. About 74.8 percent earn less than JD500, 15.9 percent earn
between JD500 and JD999, 5.8 percent earn between JD1,000 and JD1,499, 3.5 percent
earn between JD1,500 and JD1,999, and only 1 percent earns JD3,000 or more. It is worth
noting that 38.1 percent of the respondents earn less than Jordan’s annual per capita
income of JD220 (Central Bank of Jordan, 2009). With regards to respondents’ monthly
expenditures, the majority (85 percent) spend less than JD500, 11.6 percent spend between
JD1,000 and JD1,499, 0.8 percent spends between JD1,500 and JD1,999, and none
spends JD2,000 or more. Accordingly, 15.7 percent of the respondents are net borrowers
(negative saving), 51.4 percent have no savings or borrowing, and the remaining 32.9
percent have savings.
4.3 Household characteristics
With regard to household characteristics, 69.8 percent of the respondents own their place of
residency and 30.2 percent rent their place of residency. About 45.5 percent of the
households have at least one car and 54.5 percent have none. Table IV shows the
percentage distribution of households according to their monthly income and expenditures.
4.4 Local demand for domestic tourism
With regards to the local demand for domestic tourism, 54.3 percent of the households
participated in domestic tourism activities (traveled locally). The number of trips ranges
between one and four. About 92.1 percent (258 out of 280) traveled once, while 4.6 percent,
1.8 percent, and 1.4 percent traveled two, three, and four times, respectively. Households’
expenditures on domestic tourismrange fromJD100 to JD1,200 with an average of JD253.3.
About 72.9 percent of households who traveled locally spent less than JD300, whereas 22.8
percent spent between JD300 and JD600. Respondents were also asked about the
in?uence of job environment, political factors and distance between home and tourstic
locations on their demand for domestic tourism. About 72.3 percent states that the job
environment affected their demand for tourism, whereas 72.1 percent states that local and
regional political conditions affected their demand for domestic tourism and ?nally, 73.4
percent states that distance between home and destination affected there demand for
domestic tourism.
The questionnaire asks those who traveled about their perceptions of the obstacles facing
households involvement in domestic tourism market. Table V shows, in decreasing order,
the obstacles facing household’s involvement in domestic tourism. Table V shows two types
of obstacles, i.e. demand and supply. Ability and willingness affect the local demand for
domestic tourism. The ability of households is determined by their disposable income, the
prices of tourism goods and services, entry fees, the size of the family, and the availability
of owned transport (obstacles 1, 2, 12, 13 and 15, respectively). The willingness of
households is determined by obstacles 6, 10, 11, 12, 14 and 15. The supply-side obstacles
include obstacles related to the cost of travel, marketing, infrastructure, government and
operators’ focus on foreign tourists against domestic ones (foreign tourists have a higher
Table IV Household’s monthly income and expenditures
Item Income (percent) Expenditure (percent)
Less than JD1,000 75.6 87.8
JD1,000-JD1,999 18.6 7.4
JD2,000-2JD999 2.9 2.9
JD3,000 þ 2.9 1.9
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multiplier effect), and the lack of tourism services in touristic sites. The least important
obstacle is the lack of diversity in touristic sites, since Jordan has a high variation of
touristic locations (Roman, Nabataean, Islamic, Christian, Bedouin, recreational, medical).
However, the ability obstacles are among the most important ?ve, indicating as argued
before that demand side of the tourism market is detrimental to the development of the
domestic tourism sector.
The questionnaire also asks those who did not travel in the year under study for the reasons
for not traveling locally. Table VI lists, in decreasing order, the reasons and their importance.
Table VI shows that four out of the ?rst ?ve reasons for not traveling locally are supply-side
related. Also, religious, social and environmental issues are among the reasons mentioned.
5. The estimation methods and results
The dependent variable in equation (1) is a binary variable that takes values of 0 or 1,
whereas the dependent variable in equation (2) is a quantitative variable. Therefore the
methods of estimation of the two equations differ extensively.
Table V Obstacles facing households’ involvement in domestic tourism – travelers’ point
of view
Obstacle Mean (0, 1)
Low disposable income 0.8895
High prices of commodities and services in tourist location 0.8837
Weakness of marketing of domestic tourist locations 0.7674
Infrastructure in general and in tourist locations speci?cally 0.7636
Employment status 0.7578
Lack of leisure time 0.7519
Operators focus on inbound tourists 0.7422
Lack of effective marketing of local media 0.7403
Lack of reliable public transport to tourist 0.6841
Environmental issues 0.6725
Lack of tourist services 0.6415
High entry fees 0.6376
Large family size 0.5988
No need for repetition 0.5620
Lack of self transport 0.5465
Lack of diversity 0.5446
External demand for tourism 0.5019
Competition from neighboring countries 0.4709
Table VI Reasons for not participating in domestic tourism activities
Reason Mean (0, 1)
Infrastructure 0.7
Lack of publicity and marketing 0.7
Lack of awareness 0.7
Focus on inbound tourists 0.6
Lack of attraction factors 0.6
High entry fees 0.6
Distance between residence and tourist location 0.5
Lack of direct transport to tourist locations 0.5
Lack of disposable income for tourism 0.5
Lack of time due to work pressure 0.5
Environmental issues 0.4
Lack of variety of tourist locations 0.4
Social reasons 0.3
Lack of demand 0.3
Religious reasons 0.2
Domestic tourism is not important for the Jordanian economy 0.1
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5.1 Binary dependent variables: probit models
Estimating choice models using the usual least squares estimation method is not the best
course of action. One problem with the linear probability model (LPM) is that the error is
heteroskedastic – that is, the variance of the error term varies from one observation to
another. The least squares method yields unreliable values of probability, less than 0 or more
than 1, due to the assumption of linearity between the probability and the explanatory
variables. The probability that an event occurs is non-linear and hence can be estimated by
a method called probit. The probit speci?cations are designed to analyze the qualitative
data re?ecting a choice between two alternatives.
The probit method provides a way of quantifying the relationship between the respondents’
characteristics in addition to other explanatory variables and the probability of choosing an
alternative. Estimating the probit model is performed by maximizing the likelihood function
with respect to all coef?cients. The maximization requires an iterative method, but in most
cases the algorithm will operate smoothly, because the PROBIT model likelihood function is
very well behaved (Hill et al., 2001). The EViews software package is used to estimate the
probit models of equation (1).
5.2 Sample selection bias: Heckit method
In equation (2) the dependent variable is observed only for households who entered the
domestic tourismmarket in the periodunder study, while it is not observable for those who did
not enter (did not travel locally). While it seems reasonable to ignore the respondents who did
not enter the domestic tourismmarket and then use the ordinary least squares (OLS) method
to estimate equation (2), ignoring those who did not travel locally creates biased results. The
biasedresults come fromthe fact that the sub-sample (households who traveledlocally) is not
random and therefore the observed data are selected by a systematic process.
Heckman (1979) analyzes the selection bias problem that results from using non-randomly
selected samples when estimating a behavioral relationship. In order to overcome this bias
problem, he suggests an alternative estimation method, which is known as the Heckit
method and is best used when there is a non-randomsample drawn. Therefore the use of the
Heckit method is deemed appropriate for this study since the sample of those who traveled
locally is a non-random sample.
Following Heckit method, two steps estimation are conducted for equation (2). In step 1, the
probit model of decision equation is estimated by maximum likelihood estimation method.
For each observation in the selected sample, the value of the inverse Mill’s ratio (IMR) is
calculated and saved. IMR accounts for the fact that the observed sample is not random. In
step 2, using the selected sample, the dependent variable in equation (2) is regressed on
the explanatory variables and the IMR (the IMR is created from the ?rst step probit
estimation) using the OLS method.
5.3 The estimation results
In this section, socio-economic explanatory variables that re?ect the respondents’ personal
characteristics and household characteristics, in addition to other variables, are examined
for their effect on Jordanian households’ involvement in the domestic tourism market and on
their tourism expenditures. Table VII presents the de?nitions of all explanatory variables.
5.4 Antecedents of entering domestic tourism market (stage 1): probit model
Equation (1) relates the explanatory variables to the probability of entering the domestic
tourism market. The explanatory variables that affect the households decision include the
respondents’ characteristics (age, level of education, martial status, working status, gender,
type of job, number of working days, number of daily working hours, etc.), the household
characteristics (yearly income and expenditures, family size, number of working members,
availability of family car) and other factors (entry fees, demand for external tourism, sense of
national duty, distance, tourism offers, festivals and occasions, political and environmental
issues).
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While adding expenditures on external tourisminto the model may be wise, it is not the case.
The decision not to add expenditures on external tourism was taken because it is very
dif?cult to measure participants’ expenditures on domestic and external tourism (some of
the expenditures could be implicit). Furthermore, respondents were not asked to report their
expenditures on external tourism since the focus of the study is on the antecedents of local
demand for domestic tourism. Accordingly, the demand for external tourismwas added as a
dummy variable (1 for those who traveled externally, and 0 for those who did not travel
externally). The researchers asked those who traveled locally and those who traveled
externally with the explicit purpose of determining whether external travel in?uenced their
demand for domestic tourism during the period of the study.
It was expected that those who traveled externally will be less likely to travel locally and their
expenditures on domestic tourism will be less. The model of the study examines
respondents who actually traveled externally during the period of the study and not those
who had the intention to travel externally. Finally, both the cost and ease of external travel are
among the antecedents of respondents’ demand for external tourism and re?ect on the
participants’ decision to travel externally.
The results of the ?rst stage probit model, which determine the factors that affect the
probability of households’ involvement in domestic tourism market, are shown in Table VIII.
Table VIII presents the results of estimation of the probit model in equation (1); it shows that
there are three categories of factors:
1. factors that increase the probability of entering the domestic tourism market;
Table VII De?nitions of variables
Variable De?nition
AGE Respondent’s age
AGES Respondent’s age squared
CAR Car ownership dummy (1 if respondent owns a car, 0 otherwise)
DISTANCE Distance between home and touristic location dummy (1 distance affect households decision, 0 otherwise)
DOMESTIC OFFERS Touristic offers dummy (1 if household gets offers to domestic touristic sites, 0 otherwise)
EXTOURISM Demand for external tourism dummy (1 if household prefers external tourism, 0 otherwise)
FAMILYSIZE Family size
FCAR Family car ownership dummy (1 if household has family car, 0 otherwise)
FEES Touristic sites entry fees
FESTIVALS Festivals and occasions dummy (1 if local festivals are organized, 0 otherwise)
GENDER Gender dummy variable (1 if male, 0 female)
HINCOME Head of household income
IMR Inverse Mill’s ratio
LOAN Loan dummy (1 if household has current loan payment, 0 otherwise)
LOED Years of formal education
MIDDLER Region dummy (1 if central region, 0 otherwise)
MS Respondent’s marital status dummy (1 if single, 0 married)
NDUTY National duty dummy (1 if household believe that supporting domestic tourismis a national duty, 0 otherwise)
NOVISITS Number of previous trips to local touristic sites
NOWORKERS Number of working family members
POLITICS Political events dummy (1 if there is political event, 0 otherwise)
POR House ownership dummy (1 if individual owns his house, 0 otherwise)
SERSEC Sector dummy (1 if service sector, 0 otherwise)
SOUTHR Region dummy (1 if Southern region, 0 otherwise)
TOJOB Type of job dummy (1 if public job, 0 otherwise)
WDS Number of working days
WHRS Number of daily working hours
WS Working status dummy (1 if employed, 0 unemployed)
YEXP Household’s yearly expenditures
YINCOME Family income
YINCOME Household’s yearly income
YSAVING Yearly saving
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2. factors that decrease the probability of entering the domestic tourism market; and
3. other factors that have no effect.
Each group of factors consists of some respondent and household characteristics.
The results show that older respondents, those with a higher level of education, those who
are employed, those who work in the private sector or are self-employed, those who work
longer hours, those who own their place of residency, those who have a car, and ?nally those
who are working overseas are more likely to enter the domestic tourism market (travel
locally), at least at the 10 percent signi?cance level. The previous results can be explained in
accordance with two main dimensions – i.e. ability enhancement and cost reduction.
For example, older people may be retired, may have less expenditure if their dependents
have left home, and have much more time and savings. Higher education and being
employed re?ect a higher income and therefore increased ability to enter the tourismmarket.
Working for the private sector or being self-employed indicates a higher income (the private
sector pays more than the public sector) and people in his sector have more control over
their working arrangements.
Working overseas implies higher income, higher demand for luxury goods and services, and
a seasonal return back home to visit family and friends. Those who own their place of
residency pay no rent and therefore have less expenditure and more ability to travel. Those
who own a car can use it for travel; car ownership also re?ects higher income and a reduced
Table VIII Antecedents of households’ demand for domestic tourism: Probit model
Variable Coef?cient Standard error Probability
Head of household characteristics variables (RC
i
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AGE 0.019299 0.012347 0.1181
AGES 0.003372 0.001011 0.0009***
LOED 0.223100 0.108975 0.0406**
TOJOB 22.042872 0.760145 0.0072***
POR 0.599883 0.201031 0.0028***
WS 4.622239 2.618902 0.0776*
GENDER 0.090298 0.214439 0.6737
WHRS 1.277905 0.442639 0.0039***
SERSECTOR 20.285778 0.100066 0.0043***
MS 0.139455 0.293522 0.6347
WDS 0.075559 0.205646 0.7133
CAR 0.317015 0.194985 0.1040*
Household characteristics variables (HC
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YINCOME 8.58E-05 4.27E-05 0.0446**
YEXP 29.62E-05 5.27E-05 0.0683*
FAMILYSIZE 20.459901 0.209643 0.0283**
MIDDLER 0.075195 0.190149 0.6925
SOUTHR 21.447944 0.494706 0.0034**
FCAR 0.452286 0.060187 0.0000***
NOWORKERS 0.527324 0.211412 0.0126**
NOVISITS 20.479315 0.160758 0.0029***
Other factors variables (OF
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FEES 20.518153 0.203058 0.0107**
EXTOURISM 20.592913 0.206681 0.0041***
NDUTY 0.700454 0.209224 0.0008***
POLITICS 20.650841 0.207557 0.0017***
DISTANCE 0.388705 0.219832 0.0770*
DOMESTIC OFFERS 0.673767 0.134562 0.0000***
FESTIVALS 0.827145 0.221396 0.0002***
Notes: Dependent variable: DDT. Number of observations ¼ 435, log likelihood= 2 145.0190.
*Signi?cant at the 1 percent level; **signi?cant at the 5 percent level; ***signi?cant at the 10 percent
level
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cost of traveling. With regard to the household characteristics that affect the probability of
entering the domestic tourism market, the results show that households with a higher yearly
income, those who have a family car or second car, those who have more working family
members, those who believe that supporting domestic tourism is a national duty, those who
receive tourstic offers and those who are far away from touristic sites are more likely to travel
locally. A higher income, having a family car and more working family members imply more
ability. The belief that visiting local touristic sites and supporting domestic tourism is a
national duty increases a household’s tendency to travel locally. The availability of touristic
offers to visit local sites increases the probability of entering the domestic tourism market
through reducing cost.
Finally, the farther the household is from touristic sites, the higher is the tendency to visit
these sites. Regarding the respondent characteristics that decrease the probability of
entering the domestic tourism market, Table VIII shows that respondents who work in the
public sector, those who work in the service sector, those who have higher yearly
expenditures, those who have a larger family size, those who live in the Southern sector and
those who visited have touristic sites before are less likely to travel locally. With regard to the
other factors, the results show that higher entry fees, spending on external tourism and
political disturbances make the household less likely to travel locally. Finally, the results also
show that respondents’ gender, respondents’ number of working days, and respondents’
martial status have no effect on the probability to travel locally for tourism purposes.
5.5 Antecedents of tourism expenditures
Equation (2) presents the explanatory variables that affect the households’ expenditures on
domestic tourism. Table IX shows that respondents’ and households’ characteristics, in
addition to other factors, affect households’ expenditures on domestic tourism. The results in
Table IX also show that male respondents, those with higher level of education and higher
income tend to spend more. Male respondents are the main source of income in Jordan and
therefore they play a major role in deciding how much to spend (they are mainly heads of
households). Those with higher education are well traveled and perceive tourism to be
bene?cial and a necessity.
Also, higher education implies a higher income and more ability. With regards to the
in?uence of household characteristics, the study ?nds that: the bigger the family size, the
bigger the yearly savings and the higher yearly income are – and the greater the
expenditures on domestic tourism are. Table IX also shows that a perception of supporting
domestic tourismto be part of national duty results in more expenditure on domestic tourism.
Finally, higher fees increase expenditures.
Table IX also shows the factors that negatively affect households’ expenditures. It shows that
older respondents, married respondents, and those with higher yearly expenditures spend
less on domestic tourism.
A positive relationship exists between age and lifecycle and expenditure. The older a person
becomes the higher his/her expenditure (family requirements) becomes. Therefore, less
money is available for tourism. With regard to household characteristics, Table IX shows that
the availability of a family car reduces the cost of travel and therefore reduces expenditure,
since transportation cost per traveler decrease. Due to the substitution effect, households
who travel externally spend less on domestic tourism ceteris paribus. Net borrower
households (those who have loan payments) spend less. Households that are exposed to an
awareness of touristic offers (cheap packages) spend less. Finally, Table IX shows that the
numbers of working days and type of job have no effect on tourism expenditures.
Common factors exist in both Tables VIII and IX that both have a signi?cant impact on the
probability to enter the domestic tourismmarket and on tourismexpenditure. However, these
factors vary in their strength and direction. For example, respondents with a higher level of
education, households with a higher income and those who have a perception that
supporting domestic tourism is part of their national duty are more likely to travel locally and
spend more.
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On the other hand, higher non-touristic expenditures and traveling externally (outbound
tourism) make households less likely to travel locally, decreasing domestic tourism
expenditure. Respondents’ gender and martial status affect expenditure on domestic
tourism but not the probability of traveling locally. Family size and entry fees make
households less likely to travel but increase expenditure on domestic tourism. Finally, the
availability of a family car and being aware of touristic offers make households more likely to
travel and decrease tourism expenditure.
6. Conclusions and recommendations
This study examines antecedents of households’ local demand for domestic tourism using a
random sample of 600 Jordanian households. The study proposes a two-stage estimation
process. Stage 1 identi?ed the antecedents of the probability of entering the domestic
tourism market. Stage 2 identi?ed the antecedents of household expenditure on domestic
tourism. Traditionally the majority of studies in the tourism demand literature focus on prices
and income as the main antecedents of demand for tourism. While prices and income are
good indicators of cost and ability, this study identi?ed other factors that predict and explain
local demand for domestic tourism more comprehensively. Accordingly, vectors of heads of
households’ characteristics, and households’ characteristics in addition to other factors, are
examined for their effect on households’ local demand for domestic tourism.
With regard to stage 1, i.e. the probability of traveling locally, the study ?nds that heads’ of
households characteristics (i.e. age (þ), level of education (þ), type of job (2), ownership of
residence (þ), working status (þ), number of daily working hours (þ), sector of operation
(2)), households characteristics (i.e. yearly income (þ), yearly expenditures (2), family size
(2), region (2), availability of family car (þ), number of working family members (þ), and
Table IX Antecedents of households’ expenditures on domestic tourism
Variable Coef?cient Standard error t-statistic Probability
Head of household characteristics variables (RC
i
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Constant 0.584128 0.212809 2.744846 0.0066***
GENDER 0.047787 0.023052 2.072971 0.0394**
AGE 20.025087 0.007462 23.361813 0.0009***
AGES 0.000262 9.22E-05 2.842547 0.0049***
LOED 0.026738 0.012390 2.158014 0.0320**
WDS 0.049355 0.031577 1.562992 0.1195
TOJOB 20.037623 0.027512 21.367540 0.1729
MS 20.076909 0.028363 22.711608 0.0072***
HINCOME 6.48E-05 1.67E-05 3.889806 0.0001***
Household characteristics variables (HC
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FAMILYSIZE 0.080213 0.021213 3.781244 0.0002***
YEXP 21.78E-05 9.27E-06 21.921707 0.0559*
YSAVING 0.000154 4.60E-05 3.356619 0.0009***
FCAR 20.033641 0.020253 21.661037 0.0981*
MIDDLER 20.030246 0.019819 21.526079 0.1284
YINCOME 1.24E-05 4.98E-06 2.489019 0.0136**
Other factors variables (OF
i
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EXTOURISM 20.041067 0.022904 21.792963 0.0744*
NDUTY 0.044611 0.021202 2.104071 0.0365**
FEES 0.056683 0.022079 2.567240 0.0109**
LOAN 20.034522 0.020589 21.676700 0.0950*
DOMESTIC OFFERS 20.081009 0.027320 22.965215 0.0034***
IMR 20.085824 0.040513 22.118416 0.0353**
Notes: Dependent variable: EODT. R
2
¼ 0:407069; adjusted R
2
¼ 0:355392; mean of dependent
variable ¼ 0:160420; SD of dependent variable ¼ 0:165307; log likelihood ¼ 153:3807; F-statistic ¼
7.877122; probability (F-statistic) ¼ 0.000000; Durbin-Watson statistic=1.830621. *Signi?cant at the
10 percent level; **signi?cant at the 5 percent level; ***signi?cant at the 1 percent level
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number of visit to touristic locations (þ)), and other factors (i.e. entry fees (2), demand for
outbound tourism (2), sense of national duty (þ), political disturbances (2), local festivals
and occasions (þ), distance (þ) and domestic offers (þ)) affect households’ tendency to
travel locally.
With regard to stage 2, i.e. the antecedents of tourism expenditure, the study ?nds that head
of households’ characteristics (i.e. gender (þ), age (þ), level of education (þ), martial
status (2), income (þ)), households’ characteristics (i.e. family size (2), yearly
expenditures (2), yearly savings (þ), availability of family car (2), income (þ)) and other
factors (i.e. demand for outbound (2), sense of national duty (þ), fees (þ), loan payment
(2), touristic offers (2)) affect households’ expenditures on domestic tourism.
Therefore, the study presents numerous recommendations. First, the GoJ needs to
understand that problems with local demand for domestic tourism are both supply- and
demand-side problems. Furthermore, income and substitution effects affect tourism.
Therefore, governmental policies must address both supply and demand. For example,
lowering prices does not necessarily stimulate local demand. A need must be met for a
holistic approach that considers factors that make households more likely to travel locally,
and at the same time reduce the impact of factors that decrease the tendency of households
to travel locally.
In addition, governments must overcome barriers and obstacles to travel locally, such as
poor infrastructure, poor marketing initiatives, and lack of awareness of touristic sites. Finally,
government policies should target government employees, school students and outbound
tourist with attractive offers. Studies should examine the size and antecedents of Jordanians’
outbound tourism in order to make the substitution effect work to the interest of domestic
tourism.
References
Alegre, J. and Pou, L. (2004), ‘‘Microeconometric determinants of the probability of tourism
consumption’’, Tourism Economics, Vol. 10, pp. 125-44.
Allen, D. and Yap, G. (2009), ‘‘Investigating other leading indicators in?uencing Australian domestic
tourism demand’’, paper presented at 18th World IMACS/MODSIM Congress, Cairns, 13-17 July.
Central Bank of Jordan (2009), Annual Report, Central Bank of Jordan, Amman.
Chan, F., Lim, C. and McAleer, M. (2005), ‘‘Modelling multivariate international tourism demand and
volatility’’, Tourism Management, Vol. 26 No. 3, pp. 459-71.
Chan, F., Lim, C. and McAleer, M. (2004), ‘‘Modelling conditional correlations in international tourism
demand’’, in Pahlwostl, C., Schmidt, S., Rizzoli, A.E. and Jakeman, A.J. (Eds), Complexity and
Integrated Resources Management: Transactions of the International Conference on Environmental
Modelling and Software, International Environmental Modelling and Software Society, Manno.
Coenen, M. and Lobke, V.E. (2003), ‘‘A study of the demand for domestic tourism by Swedish
households using a two-staged budgeting model’’, Scandinavian Journal of Hospitality and Tourism,
Vol. 3 No. 2, pp. 114-33.
Department of Statistics (2009), Statistical Yearbook, Issue 57, Department of Statistics, Amman.
Eugenio-Martin, J.L. (2003), ‘‘Modeling determinants of tourism demand as a ?ve-stage process:
a discrete choice methodological approach’’, TourismandHospitality Research, Vol. 4 No. 4, pp. 341-54.
Fraihat, H. (2010), personal communication, Director, Department of Statistics, Amman.
Hamal, K. (1996), ‘‘Modelling domestic holiday tourism demand in Australia: problems and solutions’’,
Asia Paci?c Journal of Tourism Research, Vol. 1 No. 2, pp. 35-46.
Heckman, J. (1979), ‘‘Sample selection bias as a speci?cation error’’, Econometrica, Vol. 47, pp. 153-61.
Hill, R.C., Grif?ths, E. and Judge, G. (Eds) (2001), Undergraduate Econometrics, Wiley, New York, NY.
VOL. 7 NO. 1 2013
j
INTERNATIONAL JOURNAL OF CULTURE, TOURISM AND HOSPITALITY RESEARCH
j
PAGE 91
D
o
w
n
l
o
a
d
e
d
b
y
P
O
N
D
I
C
H
E
R
R
Y
U
N
I
V
E
R
S
I
T
Y
A
t
2
2
:
2
1
2
4
J
a
n
u
a
r
y
2
0
1
6
(
P
T
)
Lim, C. (2006), ‘‘A survey of tourism demand modeling practice: issues and implications’’, in Dwyer, L.
and Forsyth, P. (Eds), International Handbook on the Economics of Tourism, Edward Elgar, Cheltenham,
pp. 45-72.
Sadeghi, J., Jamshidi, M. and Tayyebi, S. (2004), ‘‘Expenditure and price elasticities of demand for
household domestic tourism in Iran – a cross-sectional analysis’’, paper presented at the Economic
Research Forum for the Arab Countries, Iran and Turkey, Eleventh Annual Conference, Beirut,
16-18 December.
World Bank (2009), World Development Indicators, World Bank, Washington, DC.
World Trade and TourismCouncil (2007), Annual Reports, available at: www.wttc.org/eng/About_WTTC/
Annual_Reports/(accessed April 26, 2010).
Yap, G. (2008), ‘‘Intrastate and interstate tourism demand in Australia: an empirical analysis’’,
in Richardson, S., Fredline, L. and Ternel, M. (Eds), Proceedings of the 18th Annual CAUTHE
Conference, CD-ROM, Grif?th University, Gold Coast.
Corresponding author
Ihab Khaled Magableh can be contacted at: [email protected]
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