The Causality and Antecedents of Tourism Small & Medium-Sized Enterprises’ (SMEs) Coopetition in Complex Institutional Contexts

: This study aims to explore tourism sector small and medium-sized enterprises’ (SMEs) coopetition and its antecedents, and the consequences of sustainable competitive advantage in complex institutional contexts through the integration of institutional theory, social exchange theory and commitment theory. Through a ﬁeld survey in the Greater Bay Area in Southern China, this study identiﬁed the structural links between tourism SMEs’ institutional environment, economic beneﬁts and their commitment to a regional framework, on the one hand, and their coopetition and the effect on their sustainable competitive advantage, on the other, along with a comparative analysis based on the different social system regarding this structural model within this region.


Introduction
Coopetition has gained a considerable amount of attention with its potentiality of creating economic scale, enhancing performance, and increasing resource leveraging for small and medium-sized enterprises (SMEs) [1,2]. Previous studies have revealed from the perspective of strategic management, the effective link between coopetition and the tourism SMEs' sustainable advantages [3,4]. With respect to the antecedents that induced those SMEs' strategic cooperation and the propensity following the interaction between cooperation and competition, factors including economic, social relationship, and environmental aspects have been identified as having a predictive role [2,3].
However, the institutional factor, which has been discussed in terms of its impact on tourism firms' performance, such as entrepreneurship [5][6][7] and environmental sustainability [8], has not been taken into to the antecedent framework of tourism SMEs' coopetition. Therefore, this study chose the Greater Bay Area in southern China, in which exist the two socio-political systems-socialism and capitalism, respectively-within nine Chinese cities and two special administrative regions (Hong Kong and Macau) which lead to the different business models employed in the research site. Besides these, from the cognitive institutional perspective, the Lingnan culture (or Cantonese culture) occupies the whole GBA but illustrates differences due to the varying effects of developmental trajectories of the Canton System the colonial regimes of the British and Portuguese, and reform and opening-up policies [9]. The two SARs, especially, have experienced different development paths compared to the counterpart cities of Guangdong Province, both before and after the resumption of sovereignty by China. Meanwhile, this area not only has many world-famous tourism destinations but also has large numbers of middle-to-small-sized tourism firms to serve this industry, which provided sufficient appropriate comparative study cases.
This study aims to explore tourism SMEs' coopetition and its antecedents, and the consequence of sustainable competitive advantage in complex institutional contexts. This study has two theoretical implications. First, this research enriches the literature of organization coopetition due to strategic management in the context of tourism and hospitality SMEs through the discussion of the role of institutional environmental factors and their effect. Second, this study also provides a research framework for the institutional structure of China and its linkage to SMEs' development in tourism. In terms of practical implications, the results of this study will provide some insights for managers of tourism SMEs in the Guangdong-Hong Kong-Macao Greater Bay Area in terms of corporate strategy decisions.

Theoretical Foundation
Institutions are the humanly devised constraints that shape human interaction and shape the incentive structures by which people make exchange politically, socially, and economically; simply put, institutions are the rules of the game in a society [10]. An institutional perspective emphasizes the importance of symbolic aspects of environments [11]. For the institutional environment aspect, the institutional theory which originated from organizational sociology suggests that institutional environments are characterized by the elaboration of rules and requirements to which individual organizations must conform if they are to receive support and legitimacy from the environment. These requirements may stem from regulatory agencies authorized by the nation-state, from professional or trade associations, from generalized belief systems that define how specific types of organizations are to conduct themselves, and similar sources [12].
The influence of the system on the organization is often reflected in its constraints which are usually divided into formal and informal, with formal constraints such as rules that human beings devise, which impose mandatory constraints on members in the institutional environment, and informal constraints such as conventions and codes of behavior have no mandatory constraints [10]. It is noteworthy that business behaviour is not always rationally economic but is influenced by external environmental factors such as regulations, norms, values, beliefs and tradition, rather than aiming to maximize financial benefits [12][13][14]. These stem from government and professional organizations, interest groups and the general public such as professional agencies, customers, employees, and so forth [13], which can be divided into three pillars of regulative, normative and cognitive aspects [12]. This institutional environment must be considered in analyzing business behavior models because it is a powerful factor affecting organizational management, providing stability and meaning to social behavior [15].  Scott (1995) said that all inter-organizational relationships can be captured by institutional theory [11]. As a kind of interaction between organizations, competition and cooperation generally refers to the behavior of cooperation and competition at the same time [16], and the relationship with other types of organizations continues to play an important role in modern business [17,18]. Coopetition relationships may be influenced or even initiated by external agencies such as the government, customers or industry associations. Such unilateral influence means different management requirements, because the motivation of the participants is often different from the situation where the participants initiate cooperative competition out of their intrinsic intentions [19,20].

Conceptual
The Guangdong-Hong Kong-Macao Greater Bay Area (known simply as the Greater Bay Area, or GBA) is the only bay area in the world with two social systems. Against the unique and evolving background of "One Country, Two Systems", the institutional environment and social culture in the Greater Bay Area is complex and diverse [21]. In order to obtain the legitimacy and resources needed for survival in such a highly complex institutional environment as the Great Bay Area, tourism SMEs must control production activities and coordinate external factors on the one hand, and actively seek appropriate strategic options on the other hand, especially in periods of slow business growth [22]. Simultaneously, the rise of an elaborate institutional environment stabilizes both external and internal organizational relationships [11]. Hence, this study proposed the following hypothesis: H1: Institutional environments support tourism SMEs' coopetition.

Economic Benefits
As the subject of market transactions, achieving predetermined profit targets is a common goal for all suppliers [23], and any inter-organizational relationship can be seen as a way to achieve this goal [24]. From social exchange theory, there are several advantages a firm can gain from both competition and cooperation [1], including the benefits perceived by the partner as collective [25], and so achieve higher innovation performance [26]. For small firms in the tourism and hospitality field, some scholars [27,28] found that decision-makers engage in either cooperation or competition with others after considering the potential economic benefits for the firm (competition) or the destination (cooperation). Thus, it could predict that tourism SMEs engage in coopetition with partner firms when they perceive an economic benefit for their business. It should not be overlooked that the coopetition relationship between companies also brings a higher competitive advantage to the region where they are located [29]. Hence, this study proposed the following hypothesis: H2: Economic benefits support tourism SMEs' coopetition.

Commitment in a Regional Network
A network represents a set of nodes and a set of ties. Network nodes in sociological research can be individuals or organizations, while ties represent some kind of relationship between nodes (individuals or organizations) [30]. Destination BTB research based on network perspective has become more and more extensive in recent years. The strength of ties in a destination network is not only important to the nodes, but also provides the same strong or weak feedback to the overall network or regional economy in which they are embedded [31], so to speak, and the success of a destination regional network is tied to individual companies, and so in turn, a strong regional network aggregation brings more opportunities for individual companies [32].
On the other side, although the firms in a tourism destination provide products and service based on their own role individually, they are also collectively required as members of the destination to create and deliver those products together [33,34]. Thus, they are not only dependent on the destination network, but downright committed to it [27]. In this kind of situation, firms want to be integrated to pursue their individual and mutual goals [35] and consequently they commit to dyadic cooperation with partners and the destination [36]. Therefore, this study proposed the following hypothesis: H3: Commitment of regional networks supports tourism SMEs' coopetition.

Coopetition as the Antecedent of Sustainable Competitive Advantage
Coopetition has been widely acknowledged as the dynamic process which encompass both competitive and cooperative interaction in the interorganizational relationship [37]. With regards to the potentiality of creating economic scale [1], several scholars indicated that coopetition strategies could improve firms' competitive advantage [38]. According to the dynamic capabilities theory [39], companies intend to adapt the dynamic marketing environment by realigning the organizational competence through a sustainable learning process. Therefore, coopetition has also been reflected as the antecedent of sustainable competitive advantage due to dynamic restructuring process of business strategies [40][41][42].
On the other side, previous studies have already implied that the cross-sectional social interaction as one of the collaborative actions is a necessary strategy for enterprises to deal with complex market environments, especially in uncertain situations [43]. For example, the increasing changing tourist segmentations of the world require tourism SMEs to track and communicate the progress of tourists. In this situation, those enterprises have the natural needs of coopetition regarding its potential economic benefit. In addition to the affirmed positive impact on sustainable competitive advantage in the tourism industry [3], coopetition strategies were also suggested to be an effective approach to gain competitive advantage within co-existing industries, such as hotels not only because of the centralization of hotel locations but also due to existing hotel alliances and the collaboration mechanism in this industry [2,44]. Meanwhile, the unique institutional circumstance of Great Bay Area of "One Country, Two Systems" both indicates a different business environment while also providing dual opportunity for those hotels in this area. Therefore, it could be predicted that the dynamic coopetition strategies would perform as a stimulus for those tourism SMEs to pursue sustainable competitive advantage in the GBA area. Thus, this study proposed the following hypothesis: H4: Coopetition support sustainable competitive advantage.

Trust and Dependency as the Moderator
In business-to-business research, the impact of trust is pervasive from the beginning to the end of a business-to-business benefit exchange. Early business partnerships are often "experimental" and therefore the exchange process may be relatively small or low-risk because the building blocks of trust have not yet been established [45,46], and as firms enjoy the benefits of these low-risk exchanges, companies may increase the size of the exchange to achieve greater rewards while offering equal or greater benefits to exchange partners [47], and so over time and as transactions increase in size, trust will transform discrete business-to-business exchanges into continuous exchanges [48].
Meanwhile, trust is a building block of collaboration [49] and also is one element of coopetition [45,50] since it is built on competition but also on collaboration. The firms in coopetition might opportunistically take advantage of the dependent part if they trust each other [51][52][53][54]. Trust and dependency have been involved in the relationships between the antecedents of the firms' coopetition and their performance [55,56]. Besides this, this study also adopted the social system as the control variable to evaluate the potential difference of the performance of tourism SMEs' coopetition in socialist mainland China and capitalist Macao. Hence, this study proposed the following hypotheses: H5a: Trust and dependency moderates the relationship between institutional environment and coopetition.
H5b: Trust and dependency moderates the relationship between economic benefit and coopetition.
H5c: Trust and dependency moderates the relationship between commitment of regional network and coopetition.
H6: Trust and dependency moderates the relationship between coopetition and sustainable competitive advantage.
Thus, based on the abovementioned hypotheses, a conceptual framework of this study has been proposed in Figure 1:

Measurement and Data Collection
A structured questionnaire was developed by reviewing previous related studies in the tourism and hospitality field. The questionnaire was composed of seven parts, including the factors and general background information about respondents. Consequently, a total of 20 items (Appendix A) which were developed based on previous studies [1,27,28,37,[57][58][59][60] and 5 items included to gather demographic information were employed in this questionnaire. This questionnaire was expected to be completed in about ten minutes. All the items were measured by 5-Likert scale from extremely disagree (1) to extremely agree (5).
Before the main data collection, a pilot survey was conducted to assure the questionnaire's suitability through face-to-face interview with the owners and managers of smallmiddle-sized companies in the GBA area in May 2020. This procedure facilitated questionnaire quality by gathering feedback from respondents and the collected data meant that it was possible to conduct a reliability examination. Consequently, 60 usable samples were collected, and the result of reliability tests indicated a good Cronbach's alpha coefficient for each scale, all higher than 0.9 [61]. Given the results, all items were retained during this stage and subsequently applied in the major data collection.
The major data collection was conducted consistently after the pilot test during July and September 2020.The questionnaire was distributed online and in onsite channels to increase the sample size during the pandemic period. Consequently, separate 250-convenience samples were collected from tourism SMEs in each of Macao and Mainland China. By eliminating the responses with incomplete answers and short filling times, 214 usable questionnaires (a response rate of approximately 84%) remained for tourism SMEs in Macao, and 204 usable samples with a response rate of 81.6% were retained for tourism SMEs in Mainland China.

Data Analysis
The study first of all explored the antecedent variables' internal constructions through exploratory factor analysis along with a validity evaluation of the measurement models that represented the illustrations in different tourism SMEs groups. For hypothesis testing, this study applied PLS-SEM approach to examine the causal relationships for hypotheses 1 to 4. Compared to covariance-based SEM, PLS-SEM has been suggested to be an optimized approach for verifying the causal relationship in complex models with small sample size [62,63]. Further, Hair et al. (2019) also suggested PLS-SEM has shown better estimating capacity without stringent distribution assumptions [64]. In addition,

Measurement and Data Collection
A structured questionnaire was developed by reviewing previous related studies in the tourism and hospitality field. The questionnaire was composed of seven parts, including the factors and general background information about respondents. Consequently, a total of 20 items (Appendix A) which were developed based on previous studies [1,27,28,37,[57][58][59][60] and 5 items included to gather demographic information were employed in this questionnaire. This questionnaire was expected to be completed in about ten minutes. All the items were measured by 5-Likert scale from extremely disagree (1) to extremely agree (5).
Before the main data collection, a pilot survey was conducted to assure the questionnaire's suitability through face-to-face interview with the owners and managers of small-middle-sized companies in the GBA area in May 2020. This procedure facilitated questionnaire quality by gathering feedback from respondents and the collected data meant that it was possible to conduct a reliability examination. Consequently, 60 usable samples were collected, and the result of reliability tests indicated a good Cronbach's alpha coefficient for each scale, all higher than 0.9 [61]. Given the results, all items were retained during this stage and subsequently applied in the major data collection.
The major data collection was conducted consistently after the pilot test during July and September 2020.The questionnaire was distributed online and in onsite channels to increase the sample size during the pandemic period. Consequently, separate 250-convenience samples were collected from tourism SMEs in each of Macao and Mainland China. By eliminating the responses with incomplete answers and short filling times, 214 usable questionnaires (a response rate of approximately 84%) remained for tourism SMEs in Macao, and 204 usable samples with a response rate of 81.6% were retained for tourism SMEs in Mainland China.

Data Analysis
The study first of all explored the antecedent variables' internal constructions through exploratory factor analysis along with a validity evaluation of the measurement models that represented the illustrations in different tourism SMEs groups. For hypothesis testing, this study applied PLS-SEM approach to examine the causal relationships for hypotheses 1 to 4. Compared to covariance-based SEM, PLS-SEM has been suggested to be an optimized approach for verifying the causal relationship in complex models with small sample size [62,63]. Further, Hair et al. (2019) also suggested PLS-SEM has shown better estimating capacity without stringent distribution assumptions [64]. In addition, Cao et al. (2021) indicated that PLS-SEM possesses a stronger explanatory power for examining mediation and moderating effects in complex models [65]. Therefore, hypotheses 1 to 4 have been tested through a PLS-SEM approach. Finally, the proposed moderating impact of inertia was investigated by employing metric invariance tests for measurement and structural models.
This study also used the fuzzy-set Qualitative Comparative Analysis (fsQCA) to further explore causality in these tourism SMEs' perception of sustainable competitive advantage as a case-oriented technique which focuses on combinatorial effects. This method accepts asymmetry between independent and dependent variables, as well as equifinality in which multiple combinations of the simple antecedent conditions may lead to the same outcome. Furthermore, the results of fsQCA could provide the combinations of the antecedents which cause the low levels of the outcome, as a modification and supplementation of the SEM results.

Respondents' Profile
According to the data collected from Mainland China, the sample had many more male respondents than females. The modal age of respondents was between 36 and 45 years, accounting for more than 60% of the sample. Regarding industry distribution, nearly 30% of them were in travel agencies, including OTAs. Nearly 37% of the respondents had a monthly income above 20,001. In terms of education level, most of the respondents held a bachelor's degree (35%).
For the results gathered from tourism SMEs in Macao, the gender distribution is dominated by male employees (54.7%). A similar pattern can also be observed with age, showing that most respondents were between 36-45 years old (45.3%). The data also revealed that more than 75% the respondents earnt more than 25,000 mops. Moreover, 45.8% of the samples held a diploma degree. The detailed demographic information of respondents is presented in Table 1. Table 1.

Item
Variable (

Exploratory Factor Analysis
This study utilizes principal component analysis as a method of extraction and varimax rotation with Kaiser normalization as recommended by past researchers [63] for a parsimonious description of the dimensions. The Kaiser-Meyer-Olkin (KMO) values were above 0.7 [66], meaning the variables were interrelated and they shared common factors. Meanwhile, Barlett's test of sphericity achieved statistical significance (p = 0.000) [67] indicating the factorability of the correlation matrix. As shown in Table 2, the communalities ranges suggest that the variance of the original values is fairly explained by the common factors [63]. The results of the factor analysis suggested the Cronbach alpha score of the dimensions ranged from 0.69 to 0.87, indicating satisfactory internal consistency [68]. According to the results of the measurement model reliability and convergent validity tests for both groups (Table 2), the convergence validity of the measurement model has been confirmed since the AVE values exceeded the minimum criterion of 0.50 [69]. Furthermore, alpha values of all of the constructs in this study exceeded the conventional suggested value of 0.70 [70] and the construct CR values were greater than 0.70 [71]. Likewise, all of the factor loading for each item exceeded the cut-off point of 0.70 [72]. Accordingly, the reliability of the measurement model has been confirmed. In addition, the comparison result between the square root of AVE scores and item correlation coefficients [69] supported the discriminant validity of the constructs.

Structural Model Identification
The proposed model was tested through the SEM. The results of the SEM showed that the overall fit of the model was satisfactory. Consequently, this final model was used for all further analyses. The details of the final model are presented in Table 3. The model had a strong predictive ability of tourism SMEs' coopetition, accounting for 82.5% of the total variance. In addition, this model explained about 75.2% of the total variance in sustainable competitive advantage. The hypothesized paths to tourism SMEs' coopetition were tested. Three links were significant, supporting Hypotheses 1, 2, and 3. However, Hypotheses 4 was rejected in the group of tourism SMEs from Mainland China. On the other side, the hypothesis analysis of the group of tourism SMEs from Macao indicated the different result that the H1 was rejected while the rest of the hypotheses were supported.

Moderation Effect Identification
To test the proposed moderating effect of inertia, grouping was conducted. The respondents were divided into two groups based on their responses to the items discerning trust and dependency using Kmeans cluster analysis. The groups were named the high (198 cases) and low (220 cases) trust and dependency groups. As a next step, a test for measurement invariance was conducted. In particular, CFA, without constraining any factor loadings between groups, was assessed (non-restricted model), and this model was compared to the full-metric invariance model in which all factor loadings were equally constrained across groups (full-metric invariance model). As shown in Table 4, a chi-square difference test revealed that non-restricted and full-metric invariance models were not significantly different (∆X 2 (12) = 3.878, p > 0.001), verifying that the impact of probable variation between the high and low trust and dependency groups in the measurement structure is minor and statistically insignificant. Thus, full-metric invariance was supported.  After this test for the equality of factor loadings, a test for structural invariance was conducted. To generate a baseline model for the high and low trust and dependency groups, SEM was run by including all paths of the final model. The baseline model had a satisfactory fit to the data. This model was compared to a series of nested models in sequence to test a hypothesized moderating effect of trust and dependency. In particular, the specific path of each nested model was constrained to be equal across groups, and then each model was compared to the freely estimated baseline model using a chi-square difference test. The findings are summarized in Table 4.
The paths from institutional environment, economic benefit and commitment to regional network to coopetition were completely significantly different across the high and low trust and dependency groups. As expected, the relationships were stronger for the high trust and dependency group than the low group (high: β IE-COP = 0.336, p < 0.01 vs. low: β IE-COP = 0.278; high: β EB-COP = 0.298, p < 0.01 vs. low: β EB-COP = 0.225, p < 0.01; high: β CRN-COP = 0.395, p < 0.01 vs. low: β CRN-COP = 0.193, p < 0.01). Thus, Hypotheses 5b and 5c were supported. Hypothesis 6 was rejected since the difference across groups for the link between COP to SCA was not statistically significant.

Analysis of Necessary Conditions
To determine whether any of the five antecedent conditions were required for the outcome, this study conducted a necessary condition analysis to assess whether a condition is always present (or absent) for cases in which the outcome is present (or absent) [73]. Note that if the outcome is present, and an antecedent condition is then found to be always present, then this antecedent condition is necessary for the outcome. Accordingly, it should be preceded to identify the necessary conditions, though the sufficient condition analysis is regarded as the main part of fsQCA [74]. The degree to which the cases conform to this rule reflects 'consistency'. A condition is 'necessary' or 'almost always necessary' when the corresponding consistency score exceeds the threshold of 0.9 or 0.8, respectively [75]. Table 5 presents the results of the fsQCA test on the necessity of the conditions relative to the SCA outcome. The results show that all of the five factors are all necessary conditions for SCA. (IE = institutional environment; EB = economic benefits; CRN = commitment of regional network; TD = trust and dependency; COP = coopetition).

Configurational Analysis
In the configurational analysis step, to identify which configurations are sufficient for achieving the outcomes, the study applies a consistency threshold that is not less than 0.80 [75] to "avoid the simultaneous subset relations of attribute combinations in both the outcomes and their negations" [76]. This study analyzes the complex solutions (Table 6) for the outcome (SCA) and its negation, as these solutions make no simplifying assumptions [75]. The consistency and coverage values for each complex solution and their respective configurations surpass the minimum acceptable values [75,76]. (RC = row coverage; UC = unique coverage; C = consistency; IE = institutional environment; EB = economic benefits; CRN = commitment of regional network; TD = trust and dependency; * means AND). Table 6 provides the configuration models for tourism SMEs in both mainland China and Macao for sustainable competitive advantage and its negation. In the group of tourism SMEs in Mainland China, the economic benefit and trust and dependency in these three configurations played a necessary and sufficient role in the contribution of high outcomes of SCA. In particular, institutional environment clearly illustrated that the collaboration with the rest three factors was necessary to achieve causality. On the other side, Table 5 also demonstrated the combinations of the conditions which induce low causality in SCA as well through the two configurations. For model 1, institutional environment was not a sufficient condition. Moreover, the negation of the three factors were crucial as well. In model 2, however, although institutional environment has been found to be a condition in this configuration, it was an unnecessary factor for this outcome either. Meanwhile, despite the same sufficient demonstration of the economic benefit and trust and dependency as in model 1, both of them were identified as unnecessary, which induces the low outcome of the SCA.

Research Summary
With regards to the results shown in Table 3, this study confirmed that economic benefits and commitment to regional network were significant antecedents of tourism SMEs' coopetition. The results were consistent with the conclusions which were evidently proved by previous studies [35,77]. With regards to the complex institutional environment in the GBA area, this study is the first attempt to investigate the relevant key items to coopetition in the circumstance of two different social systems. Although institutional environment has already been acknowledged as a powerful factor that affect organizational management and behavior [15], this study found no direct causal relationship between institutional environment and coopetition. Instead, institutional environment, economic benefits and commitment to regional network were evidently proved to be significant antecedents by introducing trust and dependencies as a moderator, as Table 4 showed. More specifically, the effect of institutional environment, economic benefits and commitment to regional network on coopetition were stronger among the tourism SMEs which possessed higher level of trust and dependency. Further, this study confirmed that institutional environment played a necessary and sufficient role in contributing to high outcomes of sustainable competitive advantage by collaborating with economic benefits, commitment of regional network, and trust and dependency through fsQCA analysis. These results also highlight importance of trust and dependency in generating interorganizational' coopetition activities, which were already proved by previous studies [55,56]. In addition, coopetition strategies also led to sustainable competitive advantage for tourism SMEs which possessed higher levels of trust and dependencies in a complex institutional environment.
This study expands on previous research into institutional environmental difference for tourism SMEs' sustainable competitive advantage based on the theory of coopetition. Tourism SMEs are one of the key groups of tourism organizations, and their activities of management and operation are always being affected by the institutional environment. In a complex institutional environment, such as the GBA area which has two different social systems, individuals and organizations are frequently under pressure because of the uncertainty of decision making. When people and systems are under pressure regarding such uncertainty, dynamics and even emergency situations, if they are to achieve organizational success, organizational and individual factors must be considered. Based on an empirical study of the coopetition performance of tourism SMEs in the Greater Bay Area of China according to the data over the past two years, this study for the first time discusses the causality of the construction of relevant key elements in coopetition and the differentiation of its effects on the organization performance in multiple institutional conditions of social system.
Besides the theoretical discussion of the research results, this study also has provided managerial implications for both tourism SMEs as well as the destination managers. First of all, establishing a successful regional network is suggested as an effective approach to stimulate coopetition activities through participation of industrial associations and through regular conversation among tourism SMEs. Given the ultimate goal of economic profits for tourism SMEs, the changeable market situation, and the specific institutional environment in the GBA area, tourism SMEs should improve their organizational capabilities to meet the abovementioned circumstance, such as crisis readiness, dynamic response systems, and knowledge management. Furthermore, trust and dependencies among tourism SMEs possess the capacity of amplifying the sustainable competitive advantage which are brought by coopetition strategies. As the only bay area in the world with two different social systems, holding cross-sectional industrial conferences and interaction activities should be effective approaches to enhance the level of trust and dependencies among tourism SMEs in the GBA area. In addition, the incessant interaction between them could further contribute to the regional competitive advantage of tourism destinations in the area of the GBA.
Several limitations exist in this study. First, despite the generalization efforts, the results may only be applicable to the tourism SMEs in the Greater Bay Area in China. The research sites in this study include Macau and other mainland Chinese cities that are located in capitalist and socialist systems, respectively, meaning that while they may be innovative in this study their impact could be limited in other places given the special "One Country, Two Systems" that these tourism SMEs must obey. These systems outline national laws, regulation and rules, that are different from other places. Therefore, other empirical studies regarding tourism SMEs coopetition and sustainable competitive advantages in other regions are expected to be used to explore this topic in the future. Second, other institutional factors that lead to tourism SMEs' coopetition and sustainable competitive advantage might extend beyond those considered herein. The governance structure, law system, profession regulation and local cultural elements could be further decisive factors. Finally, this study conducted the field survey in the COVID-19 pandemic situation, which may influence the correctness and objectivity of the research results, as the tourism SMEs were in the crisis. It will be necessary to conduct a comparative study of the tourism SMEs' coopetition and its contribution to sustainable competitive advantage before this crisis and since it for a richer theoretical contribution consideration.  2. There are industrial standards and practices in place regarding organizations' coopetition.
3. There are expectations of coopetition from local communities, consumers, suppliers, employees and investors.
Economic benefits 1. The cooperative partners and my company got competitive advantage through coopetition strategies.
2. The cooperative partners and my company have improved our market position through coopetition strategies.
3. Adopting coopetition strategies will improve existing capabilities of my company, which leads to higher business value compared to my cooperative partners. 4. Adopting coopetition strategies will improve the quality of our products and services, which leads to higher business value compared to my cooperative partners. Table A1. Cont. Commitment to regional network 1. My company has a strong sense of loyalty and enthusiasm to the relationships with the cooperative partners during the coopetition process.
2. My company dedicates enough resources to maintain relationships with the cooperative partners during the coopetition process.