| Literature DB >> 32287753 |
Xin Cathy Jin1, Mingya Qu2, Jigang Bao3.
Abstract
International tourism is highly susceptible to external political, economic and environmental crisis events. This paper consists of two studies. Study 1 uses time-series monthly data and the TRAMO/SEATS model to detect and estimate the impact of a range of political, economic and environmental crisis events on the tourist flows from China to Japan and South Korea during the period of 2005-2017. Study 2 uses in-depth interviews to investigate the factors intensifying or alleviating the negative impacts of these crisis events on tourism as well as factors contributing to post-events tourism recovery and growth. Results identify the varying levels of impacts caused by event type and other causative factors for negative impacts. The paper discusses the influence of these factors to provide references to relevant stakeholders for strategic planning, policy making and recovery and growth scheme development.Entities:
Keywords: Chinese outbound tourism; Crisis event; Japan; Recovery; South Korea
Year: 2019 PMID: 32287753 PMCID: PMC7115362 DOI: 10.1016/j.tourman.2019.04.011
Source DB: PubMed Journal: Tour Manag ISSN: 0261-5177
Fig. 1Plot of monthly visitations by Chinese tourists to Japan and year-on-year growth rates.
Fig.2The number of Chinese outbound tourists to Korea and Year-on-year growth rates.
Fig. 3The sequence decomposition results of Chinese tourists to Japan from 2005 to 2017.
Outlier test of Chinese travelling pattern to Japan (2005–2017).
| Outliers | Coefficients | T-Stat | P[|T| > t] |
|---|---|---|---|
| AO (2–2009) | −0.4485 | −4.47 | 0.0000 |
| TC (6–2009) | −0.6244 | −5.40 | 0.0000 |
| LS (3–2011) | −0.5550 | −4.67 | 0.0000 |
| AO (2–2012) | −0.4570 | −4.56 | 0.0000 |
| LS (10–2012) | −0.5830 | −4.94 | 0.0000 |
The impact of crisis events on Chinese travelling to Japan (2005–2017).
| Event | The affected period | Actual value | Background value | Loss rate |
|---|---|---|---|---|
| Financial crisis | 5–2009 | 60530 | 80719 | 25.0% |
| 6–2009 | 36597 | 72060 | 49.2% | |
| 7–2009 | 67944 | 113896 | 40.3% | |
| 8–2009 | 109017 | 121096 | 10.0% | |
| 9–2009 | 98697 | 118664 | 16.8% | |
| 10–2009 | 108301 | 111237 | 2.6% | |
| 11–2009 | 81462 | 90963 | 10.4% | |
| 12–2009 | 62527 | 72104 | 13.3% | |
| Fukushima earthquake and nuclear accident | 3–2011 | 62450 | 107167 | 41.7% |
| 4–2011 | 76164 | 117384 | 35.1% | |
| 5–2011 | 58608 | 95624 | 38.7% | |
| 6–2011 | 61419 | 82043 | 25.1% | |
| 7–2011 | 86963 | 127793 | 31.9% | |
| 8–2011 | 102640 | 136161 | 24.6% | |
| 9–2011 | 112493 | 121602 | 7.5% | |
| 10–2011 | 106174 | 123130 | 13.8% | |
| Diaoyu Island "nationalization" | 10–2012 | 69713 | 154904 | 55.0% |
| 11–2012 | 51993 | 121323 | 57.1% | |
| 12–2012 | 52336 | 97506 | 46.3% | |
| 1–2013 | 72301 | 153241 | 52.8% | |
| 2–2013 | 80903 | 140038 | 42.2% | |
| 3–2013 | 102265 | 167421 | 38.9% | |
| 4–2013 | 100160 | 181003 | 44.7% | |
| 5–2013 | 81571 | 136851 | 40.4% | |
| 6–2013 | 98996 | 127598 | 22.4% | |
| 7–2013 | 139905 | 195976 | 28.6% | |
| 8–2013 | 162288 | 205517 | 21.0% | |
| 9–2013 | 156201 | 183219 | 14.7% |
Fig. 4The sequence decomposition results of Chinese tourists to Korea from 2005 to 2017.
Outlier test of Chinese travel pattern to Korea (2005–2017).
| Outliers | Coefficients | T-Stat | P[|T| > t] |
|---|---|---|---|
| TC (6–2015) | −0.7346 | −7.76 | 0.0000 |
| AO (7–2015) | −0.5488 | −7.16 | 0.0000 |
| TC (3–2017) | −0.6062 | −5.61 | 0.0000 |
| LS (4–2017) | −0.8520 | −8.63 | 0.0000 |
The impact of crisis events on Chinese travelling to Korea (2005–2017).
| Event | The affected period | Actual value | Background value | Loss rate |
|---|---|---|---|---|
| MERS epidemic | 6–2015 | 315095 | 658802 | 52.2% |
| 7–2015 | 255632 | 815710 | 68.7% | |
| 8–2015 | 513275 | 901104 | 43.0% | |
| 9–2015 | 591242 | 738964 | 20.0% | |
| THAAD incident | 3–2017 | 360,782 | 662793 | 45.6% |
| 4–2017 | 227,811 | 794070 | 71.3% | |
| 5–2017 | 253,359 | 789452 | 67.9% | |
| 6–2017 | 254,930 | 883059 | 71.1% | |
| 7–2017 | 281,263 | 1085508 | 74.1% | |
| 8–2017 | 339,388 | 1092556 | 68.9% | |
| 9–2017 | 318,682 | 933795 | 65.9% | |
| 10–2017 | 345,384 | 886487 | 61.0% | |
| 11–2017 | 299,247 | 679521 | 56.0% | |
| 12–2017 | 332,474 | 656491 | 49.4% |
Fig. 5An integrated guide for post crisis events recovery and growth.