Intervention Model for Analyzing the Impact of Terrorism to Tourism Industry
Abstract: Problem statement: It is common in time series data with extreme change in its mean caused by an intervention which comes from external and/or internal factors. This extreme change in mean is known as regime change or structural change. Problems of external factor intervention s...
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Format: | Article |
Language: | English |
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Science Publications
2009
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Online Access: | http://eprints.utm.my/id/eprint/9715/1/jms254322-329.pdf http://eprints.utm.my/id/eprint/9715/ http://www.scipub.org/fulltext/jms2/jms254322-329.pdf |
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Summary: | Abstract: Problem statement: It is common in time series data with extreme change in its mean
caused by an intervention which comes from external and/or internal factors. This extreme change in
mean is known as regime change or structural change. Problems of external factor intervention such as
the effect of the Arab oil embargo to consumption level of electricity in United States. The issue of
interest here is on the impact of terrorist Bali’s bomb to tourism industry in Indonesia. Approach: A
theoretical and empirical studies on the intervention model, particularly pulse function of intervention
is carried out focusing on the differential statistics that can be used to determine the order of intervention
model. A case study of the first Bali bomb that occurred on October 12th, 2002 is an intervention of
external factor that has affected the occupancy level of five star hotels in Bali. Results: The results of this
theoretical study were applied to construct a model procedure of intervention model. The empirical
study showed that intervention model is used to describe and explain the quantity and the length of the
first Bali bomb effect towards the occupancy level of five star hotels in Bali. It shows a decreasing
trend in tourist arrival in Bali, Indonesia. Conclusion: This study was focused on the derivation of
some effect shapes, i.e., temporary, gradually or permanent on the arrival of tourist into Bali. A new
model building procedure with three main iterative steps for determining an intervention model was
used for data with extreme change in mean. The results from this theoretical study will give an
opportunity for further research related to time series model that contains regime change, caused by
intervention of pulse function and/or step function.
Key words: Intervention model, pulse function, extreme values, time series and tourism INTRODUCTION the effects of metal detector technology to the number
of plane pirated and Suhartono and Hariroh[5] studied
A homogeneous non stationary time series can be on the impact of WTC’s bomb in New York to stock
reduced to a stationary time series by taking a proper market values around the world. Other study on internal
degree of differencing and the Autoregressive factor intervention can be found in the study of Box and
Integrated Moving Average (ARIMA) model is one Tiao[3], analyzing the effect of machine design law to
such model useful in describing various non stationary oxidant pollution level in Los Angeles, McSweeny[6]
time series. ARIMA is a popular time series model and researched on the effect of new law about constancy
has many applications[1] . value in Cincinnati Bell Telephone company to the
Extreme change in mean of a time series data is number of emergency calls, Leonard[7] observed the
known as regime change or structural change[2] . This effect of promotion and product cost increased by a
condition is usually caused by an intervention which company and analyzed the effect of promotion and cost
comes from external and/or internal factors. The increased in customer pulse consumption in Telkom
example of external factor intervention can be found in Regional Division. These models have been applied to
Montgomery and Weatherby[3] who analyzed the effect various problem domains such as medicine[6,8], fisheries
of Arabic oil embargo on the consumption level of research[9] , economic[10] , air transport and waste
electricity in United States and Enders et al. [4] studied management[8,11] .
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