Damage Assessment in Tourism Caused by an Earthquake Disaster

Nishimura, Taiki; Kajitani, Yoshio; Tatano, Hirokazu

doi:10.2208/jscejipm.68.i_267

Cited by 7 publications

(3 citation statements)

References 9 publications

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“…Many studies used ITS analysis to investigate the impact of disasters in several research fields. Such studies include the impact of earthquake and nuclear disaster on birth rate (Kurita 2019), impact of flood on infectious diseases (Zhang et al 2019), impact of technological disasters (chlorine spill) on primary care access (Runkle et al 2012), increase in suicide trends following an earthquake (Yang et al 2005), impact of natural disasters on capital markets (Worthington and Valadkhani 2004), increase in suicide rates following terrorist attacks (Pridemore et al 2009), impact of flooding on mental health (Milojevic et al 2017), and decrease in the number of tourists in disaster-affected areas (Nishimura et al 2012). In a case study of the 2016 Kumamoto earthquake, Matsushita (2019) examined the impact of a special subsidy system for tourists in the affected area using ITS.…”

Section: Interrupted Time Series Analysis For Impact Evaluationmentioning

confidence: 99%

Increased motor vehicle crashes following the 2016 Kumamoto earthquake, Japan: an interrupted time series analysis of property damage crashes

Maruyama

Taguchi

2021

Nat Hazards

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Driving after natural disasters entails a substantial amount of stress; therefore, the number of motor vehicle crashes may increase. However, few studies have examined this issue. This study investigated motor vehicle crashes after the 2016 Kumamoto earthquake in Japan. Monthly data about crashes resulting in property damage from 49 municipalities in Kumamoto from 2015 to 2018 were used. An interrupted time series analysis using Poisson or negative binomial regression models was conducted for 49 municipalities; the models were estimated for four classified areas to obtain the robust results. We found that property damage crashes increased significantly in the heavily affected area (Relative Risk (RR) = 1.48, 95% Confidence interval (CI): 1.29, 1.71) and the affected area (RR = 1.25, 95% CI: 1.15, 1.36) after the earthquake. A mountainous area showed a reduction in property damage crashes despite its heavy damage (RR = 0.74, 95% CI: 0.67, 0.82), which can be attributed to the closure of its main gate routes. The unaffected area showed no difference before and after the earthquake. Geographical presentation of the result demonstrates a clear positive association of earthquake damage and increased crashes. The findings of this study highlight the importance of motor-vehicle-crash alerts after an earthquake.

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Section: Interrupted Time Series Analysis For Impact Evaluationmentioning

confidence: 99%

Increased motor vehicle crashes following the 2016 Kumamoto earthquake, Japan: an interrupted time series analysis of property damage crashes

Maruyama

Taguchi

2021

Nat Hazards

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“…Taking a severely affected county (city) as the decision-making unit (DMU), the number of units is N = 10. There are I types of input, O types of output, and x ni represents the type I economic input of the Nth quake-hit county, and y no represents the type O economic output of the Nth quake-hit county (Banker et al, 1984;Baade, 2007;Nishimura et al, 2013). The DEA model is described by Eq.…”

Section: Improved Dea Model With Vrsmentioning

confidence: 99%

Post-earthquake economic resilience and recovery efficiency in the border areas of the Tibetan Plateau: A case study of areas affected by the Wenchuan Ms 8.0 Earthquake in Sichuan, China in 2008

2020

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The border areas of the Tibetan Plateau and the neighboring mountainous areas have a high incidence of earthquakes with a magnitude greater than M s 5.0, as well as having a dense distribution of geological disasters such as collapses, landslides, and debris flows. Revealing the post-disaster economic development and recovery process is very important for enhancing disaster prevention and response capacity in order to formulate control policies and recovery methods for post-disaster economic reconstruction based on economic resilience. Using long-term socioeconomic data and the autoregressive integrated moving average (ARIMA) model, this paper calculated the economic resilience index of the areas most severely affected by the Wenchuan Earthquake of 2008 and adopted the improved variable returns to scale (VRS) date envelopment analysis (DEA) model and the Malmquist productivity index to analyze the efficiency and effect of annual post-disaster recovery. The results show that: (1) the economic resilience index of the areas most severely affected by the Wenchuan Earthquake was 0.877. The earthquake resulted in a short-term economic recession in the affected areas, but the economy returned to pre-quake levels within two years. In addition, the industrial economy was less resilient than agriculture and the service industry. (2) The comprehensive economic recovery efficiency of the disaster-stricken area in the year following the disaster was 0.603. The comprehensive efficiency, the pure technical efficiency, and the scale efficiency of the plain and hilly areas were significantly greater than those of the plateau and mountain areas. (3) The annual fluctuation in total factor productivity (TFP) following the disaster was considerable, and the economic recovery efficiency decreased significantly, resulting in a short-term economic recession. The TFP index returned to steady state following decreases of 33.7% and 15.2%, respectively, in the two years following the disaster. (4) The significant decrease in the post-disaster recovery efficiency was caused mainly by technological changes, and the renewal of the production system was the leading

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“…Also, each economic section experiences the effects of disasters based on its functions and specific characteristics, such as human or financial resources or its resiliency. Therefore, first of all, the literature is reviewed to find the disastrous effects on the hotel sector since most studies have considered the disastrous effects on the tourism industry (e.g., Yang et al, 2008;Nishimura et al, 2013;Wu & Hayashi, 2013;Kunwar & Chand, 2016;Seraphin, 2019). In this regard, the following question is put forth: What steps are considered for the disaster preparedness by each group of the hotels and why?…”

Section: Introductionmentioning

confidence: 99%

How Does the Hotel Quality Rate Influence the Preparedness against the Effects of Disasters?

Badri

Kazemi

2020

Journal of Quality Assurance in Hospitality & Tourism

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Heretofore, hotels have experienced different disasters in various places; and the effects have proven the vulnerability of the hospitality industry and the importance of disaster preparedness. Although studies in the field of hotels and disasters have shown the ill-preparedness to the extent that the hoteliers were shocked by the disasters, none of them have considered a framework to measure the disaster preparedness, and the differences in this industry. Therefore, an index-based approach was proposed by a systematic review on the disasters' effects on the hotels to measure the disaster preparedness. Findings obtained from the hotels located in Tehran suggested that the preparedness measures among the star hotels can be classified into three classes; measures taken by all the hotels, measures refused by all the hotels, and measures that are different among them. Results confirmed a correlation between the hotels' preparedness and their quality rate. In this regard, financial resources, human resources, management approaches, hotels' facilities, and structure were among the main reasons for the differences existing between the hotels. The lack of crisis management knowledge, risk perception, and priority for preparedness against the disasters were determined as the factors that must be considered in the disaster plans for hotels.

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Damage Assessment in Tourism Caused by an Earthquake Disaster

Cited by 7 publications

References 9 publications

Increased motor vehicle crashes following the 2016 Kumamoto earthquake, Japan: an interrupted time series analysis of property damage crashes

Increased motor vehicle crashes following the 2016 Kumamoto earthquake, Japan: an interrupted time series analysis of property damage crashes

Post-earthquake economic resilience and recovery efficiency in the border areas of the Tibetan Plateau: A case study of areas affected by the Wenchuan Ms 8.0 Earthquake in Sichuan, China in 2008

How Does the Hotel Quality Rate Influence the Preparedness against the Effects of Disasters?

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