In this section, the related works of this study have been reviewed including tourism networks and network structure effects as well as the global tourism networks, which help to find the research gaps and give the foundation of hypotheses and research methods.
2.1. Tourism Networks and Network Structure Effects
The network organization gradually takes over traditional individual businesses and has been one of the most significant breakthroughs in management thinking recently [
23], which also works on tourism. Hall has defined the tourism network as an arrangement of inter-organizational cooperation and collaboration, demonstrating the network structure as a corporative relationship among attendants [
24].
This newer type of organizational structure is always seen as a more effective and flexible structure with less hierarchy than others, which determines how it operates and performs. As clarification from Zach and Racherla, network organization can bring benefits for the participating tourism firms, enhance destinations’ tourism performance, and help form a memorable experience for visitors [
25]. Lynch et al. summarized three benefits of the tourism network including learning and exchange, business activity, and community, which highlighted the network’s value and left a lack of quantitative description [
26]. For the tourism firms, participating in a collaborative tourism network could produce merits through inter-organizational learning, improving knowledge exchange, supporting the innovation process, and constructing a sense of collective common purposes [
27]. In the destination system, a variety of local stakeholders involved in tourism development have been bound up in both business networks and service provider networks to balance the competition and collaboration [
28], which allows these actors to understand interdependence, reciprocity, mutual interest, trust, representativeness, and leadership [
29]. In the context of the tourism policy network, the effects of networks are focused on policy-making and understanding public–private relations with a goal of how network concepts can be used as an organizing method to cooperate in massive relationships [
30].
No matter which scenario or sector, the network concept can be used; the core value of the network described is the relationship and how these interactions constitute a framework or structure [
31]. For the individual, the network determines whom they will meet and what they will acquire, which must impact the outcome. For parts of the integration, the network contributes to recognizing mutual interdependence, more openly sharing knowledge and information, engaging in more significant future planning, and tending to take a more constructive problem-solving approach to conflict resolution.
Moreover, some factors that contribute to a thriving tourism network also have been detected, for instance, structure and leadership, resourcing, member engagement, and lifecycle stage [
32], where the network structure usually determines the network’s ability to explicate knowledge and facilitate the creation of sustainability outcomes [
33]. Thus, Bullmore and Sporns have pointed out that the most essential network recognition is “a network’s structural features are the system’s fundamental characteristic, which can be measured and significantly impact its function” [
34].
The effects of network structure have been discussed in many fields. For example, Sandström and Carlsson found an efficient and innovative policy network consisting of a series of central and dense actors, and the level of centralized integration network promotes the function of prioritizing in the progress of policy making [
34]. Zaheer and Bell posited that the firms with superior network structures were better able to exploit their internal capabilities and enhance their performance [
35]. Grund suggested that high intensity and low centralization networks encourage collaboration with better soccer team performance [
36]. Kim and Lee used an SEM method to detect the network density and found centrality positively affecting perceived convergence and the overall performance of Small and Medium-Sized Enterprises (SMEs) [
37]. Volgger and Pechlaner reviewed the benefits and strategies of a governing network structure working on tourism development [
38].
Thus, it can be inferred that both the whole network structure and nodal structure characteristics should affect the related performance. However, there is little evidence for how the tourism network structure affects the tourism performance. Some research provided knowledge on understanding the relationship between the tourism network structure and tourism industry performance. Pavlovich observes that high network density (more accounts of ties linking stakeholders) forces organizations to perform well because institutional values diffuse through the network [
39]. Aarstad, Ness, and Haugland pointed out that the small-world network structure can help form an efficient inter-firm coproduction in the tourism industry, which is typically characterized by a high clustering coefficient but a relatively low connection path between actors [
40]. Zach and Hill gave evidence that network structure characteristics can identify the most successful innovative partners, especially for betweenness centrality that shows strong positive effects on innovation [
41]. The question is whether these conclusions work in other sectors, which needs more testimonies. On the other hand, since various levels (the global level, the meso level, and the individual level) of structure metrics are commonly used [
42,
43,
44], different levels’ characteristics may bring unequal impact but need to be proven by real-world evidence. Above all, the past literature provides a research gap and a good foundation for this study.
2.2. The Global Tourism Networks
Global tourism boosted by globalization has become a popular global leisure activity currently. Overall, 1.5 billion international tourist arrivals were recorded and donated US
$8.9 trillion contributions to the world’s GDP with a 10.3% occupation in 2019 [
45], confirming tourism as a leading sector in the world economic industry. Simultaneously, the global tourism rapid expansion calls for a responsibly managed way to best grasp the developing opportunities for every participant around the world [
46]. Obviously, the international tourism can generate benefits, including increasing business and trading opportunities, increasing the nation’s foreign exchange earnings, raising governmental tax revenues, diversifying industry structure, and promoting the destination country economic development [
47]; thus, almost every country wants to engage in booming international tourism [
48].
Improvement of international tourism performance is regarded as one of the essential objectives of tourism development. Some studies assessed destinations’ performance usually focusing on items such as tourists’ perception and satisfaction [
49,
50], destinations’ competitiveness [
51,
52], or just a single indicator such as tourism arrivals, tourism expenditures, and overnight visitors to show the differences in measurements [
53]. Some creative approaches borrowed from other fields such as technical efficiency [
54], and ecologic footprint [
55] also have been accepted due to developing sustainably. Assaf and Josiassen have concluded eight broad drivers of tourism performance, including related infrastructure; economic conditions; security, safety, and health; price competitiveness; government policies; environmental sustainability; labor skills and training; and natural and cultural resources [
56].
From a network perspective, Matthews has concluded that the international tourism performance reflects international relationships that were shaped through people (from origins to transnational destinations), governmental negotiations, and the corresponding political relationship [
57]. Therefore, international tourism development highly relies on cooperation and collaboration, which means whom they contact and how to link are the prerequisites for performance.
The global tourism network is a comprehensive system to show how tourists move among countries and explain the various phenomena in international tourism [
58]. A larger volume of flow connecting between two countries in the network always demonstrates a closer relationship, which may be affected by population, economy, cultural context, international policies, environment, transportation, employees in tourism, travel services, and others [
59,
60]. Depending on econometric and geographic modeling (e.g., linear or non-linear regression analysis, panel data, meta-analysis, gravity model, artificial neural network), plenty of works on the influential factors, tourists’ demands, and arrivals forecasting according to the international tourists’ flow have appeared in past three decades [
61,
62,
63,
64,
65], while relatively little has been published with a global network perspective.
Previous studies have shown some characteristics of the global tourism network. Miguéns et al. firstly used the complex networks method to clarify the free-scale and small-world structure of the worldwide tourist arrival network, which also showed a degree-correlation feature [
66]; Lozano and Gutiérrez found that the global tourism network with the most important ties among countries has a scale-free distribution with some occurrence of reciprocity, large transitivity, and high-degree centralization inside the formation of tourism clusters determined by geographical, trade and cultural factors [
67]. Similarly, in the work of Chung et al., the social network method has been applied to identify the global tourism cluster changes and showed the factors (including language, distance, attractions, crisis events and visa policies) affecting tourists flows [
5]. Recently, Seok et al. adopted social network analysis to find that global outbound and inbound tourism have decentralized gradually from 2002 to 2014, where the nodal degree, betweenness, and eigenvector centrality were correlated with each other as well as significantly affected by GDP and population [
8]. Undeniably, these research studies brought contributions to understand the GNT evolution and help clear the tourism relationship in the world, but some limitations also remain.
First, what does the GNT really mean to the participating countries? As a network can raise the transferring efficiency of information and knowledge, it is deemed to speed up the tourist’s travel frequencies and raise the number of international tourists’ arrivals. Thus, as the GNT expansion, global tourism’s performance may be changed by the unique structural characteristics, which needs a long period of observation but has not been born out.
Second, the network brings both cooperation and competition to each actor with a decentralized path; however, the impacts of the GNT on different individuals are various. What these impacts are and how they work are also the issues that need to be explored and explained.
Third, the international travel market is characterized by uncertainties; as Morrison et al. suggested, resources should be targeted at the careful formulation of networks guided by the identified success factors [
27]. As a member of the tourism network, the rule of choosing the best cooperators to improve the tourism industrial performance is essential for participants. The application of social network research shows an approach to detect the targets’ characteristics, which can be considered available on the GNT and is expected to provide more practical implications for international tourism management.