Analysis on structural characteristics of regional tourism network and its influence mechanism from the perspective of multi-dimensional flow ——Taking Yunnan Province as an example

doi:10.3969/j.issn.1004-9479.2021.03.2020376

Abstract

Abstract:

From the perspective of multi-dimensional tourism flow, the characteristics of the spatial network structure of tourism flow in Yunnan Province and their influence mechanism are compared and explored by using GIS spatial analysis and social network analysis.Results show that: (1)Supply and demand of the tourism flow in Yunnan Province show obvious reverse development trend, and the heterogeneous evolution characteristics in tourism flow network are obvious, which means the higher the tourism flow level is, the lower the quality of tourism flow is. The development of tourism economic flow has not been enhanced along with the development of tourism market. The network density is low and there is a long-term existence of tourism economic development isolation, and the tourism economic cooperation exchange is insufficient. The "zero-sum competition" development trend of the cities in the tourism economy flow network makes the tourism market a certain "common tragedy" phenomenon. (2)The level of tourism flow nodes and their spatial characteristics in Yunnan Province are significantly different, and the core-edge structure is obvious. (3) Tourism economic flow network in Yunnan Province is affected by the intermediary power of tourism flow, driving force of tourism information flow, and the pulling power of tourism capital flow. The three forces present historical differences: the intermediary power of tourism flow continued to strengthen, the driving force of tourism information flow steadily strengthened, the pulling power of tourism capital flow significantly decreased, but the impact of the force shows strong and long-lasting difference evolution. (4)The driving mode of tourism economic growth and tourism economic flow network in Yunnan province are gradually changing from "supply-side-driven" pattern to "demand-side-driven" pattern.

Key words: tourism flow, tourism network Structure, social network analysis, QAP Analysis, dynamic mechanism, Yunnan Province

摘要：

基于多维流视角，运用GIS及社会网络分析方法，对比分析云南省旅游经济流、客流、信息流、资金流的网络结构差异特征及相互影响作用机制。研究表明：云南省供需两侧旅游流反向发展态势明显，旅游流网络异质演变特征明显，流量水平趋高，而流质水平偏低。旅游经济流发展未能随着旅游客流和信息流的发展而增强，网络密度偏低且长期存在旅游经济发展孤点，旅游经济合作交流不足。各州市在旅游经济流网络中“零和竞争”的偏利非共生发展态势，使得旅游市场领域存在一定的“公地悲剧”现象。云南省旅游流节点水平及其空间特征差异显著，”核心-边缘”结构明显。云南省旅游经济流受到旅游客流的中介力、旅游信息流的推动力、旅游资金流的拉动力三者的共同作用影响，各作用力影响程度表现出强弱历时性差异演化，旅游客流中介力持续增强，旅游信息流推动力稳步强化，旅游资金流拉动力显著下降。云南省旅游经济增长及旅游经济流网络发展驱动模式，正逐步由“供给侧拉动型”向“需求侧推动型”转变。

关键词: 旅游流, 旅游网络结构, 社会网络分析, QAP分析, 作用机制, 云南省

Jianlei HAN, Qingzhong MING, Pengfei SHI, Dengshan LUO. Analysis on structural characteristics of regional tourism network and its influence mechanism from the perspective of multi-dimensional flow ——Taking Yunnan Province as an example[J]. World Regional Studies, 2021, 30(3): 645-656.

韩剑磊, 明庆忠, 史鹏飞, 骆登山. 多维“流”视角下区域旅游网络结构特征及其作用机制分析——以云南省为例[J]. 世界地理研究, 2021, 30(3): 645-656.

Figures/Tables 8

Tab.1 The overall space network characteristics of the tourism flow in Yunnan Province

年份	网络密度				网络关联性
年份	经济流	客流	信息流	资金流	经济流	客流	信息流	资金流
2012	0.1583	0.3125	0.2458	0.2625	0.7583	1.0000	1.0000	1.0000
2015	0.1500	0.3917	0.4167	0.2083	0.7583	1.0000	1.0000	1.0000
2018	0.1583	0.5735	0.5625	0.1833	0.7583	1.0000	1.0000	1.0000
年份	网络等级度				网络效率
年份	经济流	客流	信息流	资金流	经济流	客流	信息流	资金流
2012	0.2667	0.0000	0.5714	1.0000	0.8718	0.7143	0.6857	0.5429
2015	0.6410	0.0000	0.5000	1.0000	0.8462	0.6476	0.4476	0.6667
2018	0.4651	0.0000	0.0000	1.0000	0.8718	0.4476	0.3143	0.7238

Fig.1 The centrality degree of space network for the tourist flow in Yunnan Province

Fig.2 The close centrality degree of the space network for the tourist flow in Yunnan Province

Fig.3 The centrality degree of the space network for tourism flow in Yunnan Province

Tab.2 The index of space network node of tourism flow in Yunnan Province (2018)

2018	旅游经济流						旅游客流
2018	内向集聚	外向辐射	受益与否	点度中心度	接近中心度	中间中心度	内向集聚	外向辐射	受益与否	点度中心度	接近中心度	中间中心度
昆明	11	6	受益	73.333	31.915	53.968	15	14	受益	100	100	14.054
玉溪	4	4	均衡	26.667	26.786	0.952	8	9	溢出	60.000	71.429	2.312
楚雄	3	3	均衡	20.000	26.786	0.764	9	8	受益	73.333	78.947	3.837
曲靖	2	3	溢出	20.000	26.316	0.000	9	8	受益	60.000	71.429	1.940
昭通	0	1	溢出	6.667	25.424	0.000	3	3	均衡	26.667	57.692	0.000
文山	0	2	溢出	13.333	25.862	0.000	6	5	受益	40.000	62.500	0.136
红河	4	2	受益	26.667	26.786	0.952	9	9	均衡	73.333	78.947	2.157
大理	5	4	受益	33.333	28.302	9.206	13	14	溢出	93.333	93.750	8.895
丽江	3	3	均衡	20.000	27.273	11.429	11	10	受益	80.000	83.333	6.288
迪庆	1	1	均衡	6.667	22.388	0.000	3	3	均衡	20.000	55.556	0.000
怒江	0	0	均衡	0.000	0.000	0.000	3	5	溢出	33.333	60.000	0.000
保山	2	3	受益	20.000	26.786	3.651	9	9	均衡	66.667	75.000	1.331
德宏	1	2	溢出	13.333	23.438	0.000	9	8	受益	66.667	75.000	1.331
普洱	1	2	溢出	13.333	25.862	0.000	8	8	均衡	66.667	75.000	1.399
临沧	0	0	均衡	0.000	0.000	0.000	7	7	均衡	53.333	68.182	0.212
西双版纳	1	2	溢出	13.333	25.862	0.000	7	9	溢出	60.000	71.429	0.869
2018	旅游信息流						旅游资金流
2018	内向集聚	外向辐射	受益与否	点度中心度	接近中心度	中间中心度	内向集聚	外向辐射	受益与否	点度中心度	接近中心度	中间中心度
昆明	15	15	均衡	100	100	5.180	15	0	受益	100	100	30.455
玉溪	7	13	溢出	86.667	88.235	2.460	4	2	受益	40.000	62.500	1.349
楚雄	7	9	溢出	73.333	78.947	0.864	8	1	受益	60.000	71.429	8.333
曲靖	9	14	溢出	93.333	93.750	4.222	0	3	溢出	20.000	55.560	0.106
昭通	5	5	均衡	46.667	65.217	0.000	0	3	溢出	20.000	55.560	0.106
文山	7	5	受益	53.333	68.182	0.000	0	3	溢出	20.000	55.560	0.106
红河	4	13	溢出	86.667	88.235	2.330	13	1	受益	93.333	93.750	27.619
大理	14	15	溢出	100	100	5.180	2	2	均衡	26.667	57.692	0.159
丽江	15	7	受益	100	100	5.180	2	2	均衡	26.667	57.692	0.159
迪庆	3	4	溢出	33.333	60.000	0.000	0	6	溢出	40.000	62.500	1.646
怒江	7	2	受益	53.333	68.182	0.212	0	6	溢出	40.000	62.500	1.646
保山	5	8	溢出	60.000	71.429	0.635	0	3	溢出	20.000	55.556	0.106
德宏	6	6	均衡	53.333	68.182	0.212	0	4	溢出	26.667	57.692	0.296
普洱	6	6	均衡	53.333	68.182	0.000	0	2	溢出	13.333	53.571	0.000
临沧	11	5	受益	73.333	78.947	0.864	0	4	溢出	26.667	57.692	0.296
西双版纳	14	8	受益	93.333	93.750	4.091	0	2	溢出	13.333	53.571	0.000

Tab.2 The index of space network node of tourism flow in Yunnan Province (2018)

2018	旅游经济流						旅游客流
2018	内向集聚	外向辐射	受益与否	点度中心度	接近中心度	中间中心度	内向集聚	外向辐射	受益与否	点度中心度	接近中心度	中间中心度
昆明	11	6	受益	73.333	31.915	53.968	15	14	受益	100	100	14.054
玉溪	4	4	均衡	26.667	26.786	0.952	8	9	溢出	60.000	71.429	2.312
楚雄	3	3	均衡	20.000	26.786	0.764	9	8	受益	73.333	78.947	3.837
曲靖	2	3	溢出	20.000	26.316	0.000	9	8	受益	60.000	71.429	1.940
昭通	0	1	溢出	6.667	25.424	0.000	3	3	均衡	26.667	57.692	0.000
文山	0	2	溢出	13.333	25.862	0.000	6	5	受益	40.000	62.500	0.136
红河	4	2	受益	26.667	26.786	0.952	9	9	均衡	73.333	78.947	2.157
大理	5	4	受益	33.333	28.302	9.206	13	14	溢出	93.333	93.750	8.895
丽江	3	3	均衡	20.000	27.273	11.429	11	10	受益	80.000	83.333	6.288
迪庆	1	1	均衡	6.667	22.388	0.000	3	3	均衡	20.000	55.556	0.000
怒江	0	0	均衡	0.000	0.000	0.000	3	5	溢出	33.333	60.000	0.000
保山	2	3	受益	20.000	26.786	3.651	9	9	均衡	66.667	75.000	1.331
德宏	1	2	溢出	13.333	23.438	0.000	9	8	受益	66.667	75.000	1.331
普洱	1	2	溢出	13.333	25.862	0.000	8	8	均衡	66.667	75.000	1.399
临沧	0	0	均衡	0.000	0.000	0.000	7	7	均衡	53.333	68.182	0.212
西双版纳	1	2	溢出	13.333	25.862	0.000	7	9	溢出	60.000	71.429	0.869
2018	旅游信息流						旅游资金流
2018	内向集聚	外向辐射	受益与否	点度中心度	接近中心度	中间中心度	内向集聚	外向辐射	受益与否	点度中心度	接近中心度	中间中心度
昆明	15	15	均衡	100	100	5.180	15	0	受益	100	100	30.455
玉溪	7	13	溢出	86.667	88.235	2.460	4	2	受益	40.000	62.500	1.349
楚雄	7	9	溢出	73.333	78.947	0.864	8	1	受益	60.000	71.429	8.333
曲靖	9	14	溢出	93.333	93.750	4.222	0	3	溢出	20.000	55.560	0.106
昭通	5	5	均衡	46.667	65.217	0.000	0	3	溢出	20.000	55.560	0.106
文山	7	5	受益	53.333	68.182	0.000	0	3	溢出	20.000	55.560	0.106
红河	4	13	溢出	86.667	88.235	2.330	13	1	受益	93.333	93.750	27.619
大理	14	15	溢出	100	100	5.180	2	2	均衡	26.667	57.692	0.159
丽江	15	7	受益	100	100	5.180	2	2	均衡	26.667	57.692	0.159
迪庆	3	4	溢出	33.333	60.000	0.000	0	6	溢出	40.000	62.500	1.646
怒江	7	2	受益	53.333	68.182	0.212	0	6	溢出	40.000	62.500	1.646
保山	5	8	溢出	60.000	71.429	0.635	0	3	溢出	20.000	55.556	0.106
德宏	6	6	均衡	53.333	68.182	0.212	0	4	溢出	26.667	57.692	0.296
普洱	6	6	均衡	53.333	68.182	0.000	0	2	溢出	13.333	53.571	0.000
临沧	11	5	受益	73.333	78.947	0.864	0	4	溢出	26.667	57.692	0.296
西双版纳	14	8	受益	93.333	93.750	4.091	0	2	溢出	13.333	53.571	0.000

Fig.4 "Core-Edge" structure of space network for tourism flow in Yunnan Province

Tab.3 The regression result of QAP on the influence factors of space network for tourism flow in Yunnan Province

参数	相关分析			回归分析
参数	2012	2015	2018	2012	2015	2018
旅游客流	0.545^***	0.500^***	0.402^***	0.409^***	0.416^***	0.514^***
旅游信息流	0.389^***	0.331^***	0.336^***	0.121^**	0.123^*	0.128^**
旅游资金流	0.260^***	0.302^*	0.237^*	0.241^***	0.230^***	0.104^*
$R 2$				0.317	0.318	0.367
调整后 $R 2$				0.311	0.312	0.362

Tab.3 The regression result of QAP on the influence factors of space network for tourism flow in Yunnan Province

参数	相关分析			回归分析
参数	2012	2015	2018	2012	2015	2018
旅游客流	0.545^***	0.500^***	0.402^***	0.409^***	0.416^***	0.514^***
旅游信息流	0.389^***	0.331^***	0.336^***	0.121^**	0.123^*	0.128^**
旅游资金流	0.260^***	0.302^*	0.237^*	0.241^***	0.230^***	0.104^*
$R 2$				0.317	0.318	0.367
调整后 $R 2$				0.311	0.312	0.362

Fig.5 Function mechanism of the space network for tourism flow in Yunnan Province

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