With the ancient Silk Road as the historical background, the ‘Belt and Road’ initiative aims to foster common development of regional economies. Regional tourism development is an essential part of the initiative. Taking 55 countries participating in the initiative as a research sample, the article investigates the determinants and spillover effect of Chinese outbound tourist flows by spatial panel models. Furthermore, we identify different spillover paths from the perspectives of geographic and cultural proximities. The results confirm that there exist significant positive spillover effects in tourist flows among countries with geographic proximity. Meanwhile, there exist significant positive spillover effects in tourist flows among countries with cultural proximity. In addition, geographic and cultural distances between China and tourist destinations have negative impacts on Chinese outbound tourist flow.
AnselinLFloraxRReySJ (2004) Advances in Spatial Econometrics: Methodology, Tools and Applications. Berlin: Springer Science & Business Media.
2.
BalliFTsuiWHK (2016) Tourism demand spillovers between Australia and New Zealand. Journal of Travel Research55(6): 804–812.
3.
BrouderPErikssonR (2013) Tourism evolution: On the synergies of tourism studies and evolutionary economic geography. Annals of Tourism Research43: 370–389.
4.
ChangCLKhamkaewTTansuchatR, et al. (2011) Interdependence of international tourism demand and volatility in leading ASEAN destinations. Tourism Economics17(3): 481–507.
5.
DrakosKKutanAM (2003) Regional effects of terrorism on tourism in three Mediterranean countries. Journal of Conflict Resolution47(5): 621–641.
6.
ElhorstJP (2012) Dynamic spatial panels: Models, methods, and inferences. Journal of Geographical Systems14(1): 5–28.
7.
ElhorstJP (2014) Matlab software for spatial panels. International Regional Science Review37(3): 389–405.
8.
GooroochurnNHanleyA (2005) Spillover effects in long-haul visitors between two regions. Regional Studies39(6): 727–738.
9.
JacobsJLigthartJEVrijburgH (2009) Dynamic panel data models featuring endogenous interaction and spatially correlated errors. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.1517257
10.
LazzerettiLCaponeF (2009) Spatial spillovers and employment dynamics in local tourist systems in Italy (1991–2001). European Planning Studies17(11): 1665–1683.
11.
LeSageJPPaceRK (2009) Introduction to Spatial Econometrics. Boca Raton: CRC Press.
12.
LiM (2014) Cross- cultural tourist research: A meta- analysis. Journal of Hospitality & Tourism Research2014; 38(1): 40–77.
13.
LiuH (2014) Understanding Destination Choice from a Cultural Distance Perspective[D]. Columbia: University of South Carolina, 2014.
14.
LueCCCromptonJLFesenmaierDR (1993) Conceptualization of multi-destination pleasure trips. Annals of Tourism Research20(2): 289–301.
15.
MarrocuEPaciR (2013) Different tourists to different destinations. Evidence from spatial interaction models. Tourism Management39(39): 71–83.
16.
MayerTZignagoS (2011) Notes on CEPII’s distances measures: The GeoDist database. CEPII Working Papers 2011-25.
17.
KogutBSinghH (1988) The effect of national culture on the choice of entry mode. Journal of international business studies19(3): 411–432.
18.
KulendranNWilsonK (2000) Is there a relationship between international trade and international travel?Applied Economics32(8): 1001–1009.
19.
MoneyRBCrottsJC (2003) The effect of uncertainty avoidance on information search, planning, and purchases of international travel vacations. Tourism Management24(2): 191–202.
20.
NeumayerE (2004) The impact of political violence on tourism: Dynamic cross-national estimation. Journal of Conflict Resolution48(2): 259–281.
21.
NgSILeeJASoutarGN (2007) Tourists’ intention to visit a country: The impact of cultural distance. Tourism Management28(6): 1497–1506.
22.
NgSILeeJASoutarGN (2009) The influence of cultural similarity and individual factors on visitation. TEAM Journal of Hospitality & Tourism6(1): 68–81.
23.
RomãoJSaitoH (2017) A spatial analysis on the determinants of tourism performance in Japanese Prefectures. Asia-Pacific Journal of Regional Science1(1): 243–264.
24.
RosenbaumMSSpearsDL (2005) Who buys that? Who does what? Analysis of cross-cultural consumption behaviors among tourists in Hawaii. Journal of Vacation Marketing11(3): 235–247.
25.
ShenkarO (2002) Institutional distance and the multinational enterprise. Academy of Management Review27(4): 608–618.
26.
WilliamsAShawG (2011) Internationalization and innovation in tourism. Annals of Tourism Research38: 27–51.
27.
YangYFikT (2014) Spatial effects in regional tourism growth. Annals of Tourism Research46(2): 144–162.
28.
YangYWongKKF (2012) A spatial econometric approach to model spillover effects in tourism flows. Journal of Travel Research51(6): 768–778.
29.
YangYFikTJZhangH (2017) Designing a tourism spillover index based on multidestination travel: A two-stage distance-based modeling approach. Journal of Travel Research56(3): 317–333.
30.
YangYFikTZhangJ (2013) Modeling sequential tourist flows: Where is the next destination?Annals of Tourism Research43(7): 297–320.
31.
ZhangJHBarrosCPBottiL, et al. (2009) Spatial distribution of inbound tourism in China: Determinants and implications. Tourism & Hospitality Research9(1): 32–49.
32.
ZhangYXuJZhuangP (2011) The spatial relationship of tourist distribution in Chinese cities. Tourism Geographies13(1): 75–90.
33.
ZhengXYuYWangJ, et al. (2014) Identifying the determinants and spatial nexus of provincial carbon intensity in China: A dynamic spatial panel approach. Regional Environmental Change14(4): 1651–1661.
34.
ZhouBYangBLiH, et al. (2017) The spillover effect of attractions: Evidence from Eastern China. Tourism Economics23(4): 731–743.
