Intervention Model for Analyzing the Impact of Terrorism to Tourism Industry

Abstract

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] .