Social capital is defined as “the sum of resources, actual or virtual, that accrue to an individual or a group by virtue of possessing a durable network of more or less institutionalized relationships of mutual acquaintance and recognition” (4). In other words, social capital refers to the advantages a person gains from having relationships within a network. According to social capital theory, the resources, information, and opportunities accessible through relationships within social networks can be fundamental drivers of both individual and collective success (5) since these networks foster norms of reciprocity, trustworthiness, and mutual support, which in turn facilitate efficient communication, cooperation, and the sharing of knowledge among members. Social capital is often conceptualized in two forms: bonding social capital, which refers to ties among individuals with similar backgrounds or interests (i.e., internal relations), and bridging social capital, which connects individuals across diverse social groups or organizational boundaries (i.e., external relations) (6). Both forms are essential—bonding social capital strengthens group cohesion and emotional support, while bridging social capital introduces new information, resources, and innovative perspectives.

Extensive research has confirmed the wide-ranging benefits of social capital, showing that it enhances individual and organizational effectiveness across numerous domains. For instance, high levels of social capital have been linked to better educational outcomes through supportive peer networks (7), improved public health via the dissemination of health information and collective action (8), greater efficacy in community governance and economic development through trust-based collaborations (9), and an increased capacity for creative problem-solving by leveraging diverse expertise and viewpoints (10). In the context of sports teams, social capital not only supports collaboration and coordination but also builds resilience, adaptability, and a shared commitment to group goals. By intentionally cultivating both strong internal relationships and broad external networks, teams and organizations can maximize the flow of resources and information, ultimately fostering a culture of sustained high performance.

Because team sports involve a group of people (i.e., athletes) working together to achieve common goals (11), team cohesion serves an important role in sport performance and has been frequently examined as a key factor in developing successful sport teams (12). Given the nature of team sports, where results depend heavily on interactions among teammates, research applying a social network approach in the context of sports offers a valuable perspective. In social network analysis, network density is associated with group cohesion (13, 14) and has often been interpreted as reflecting team cohesion in sport (15, 16). Among several types of networks, advice and friendship networks have been regarded as important means of measuring network characteristics at the team level, as they can serve a key role in facilitating communication and the transmission of performance-related knowledge. For instance, Wang et al. (17) investigated advice networks to interpret the relationship between cooperative goals and team performance. Anderson and Warner (18), meanwhile, used friendship networks to measure team cohesion on a volleyball team. Further, Gibbons (19) conducted a study investigating changes in advice networks and friendship networks among teachers. Following such research, the current study adopted the concept of advice networks to assess team cohesion.

In general, a high level of density in an advice network among team members has the potential to affect knowledge and information sharing that contributes to team performance. In fact, the causal relationships between team cohesion and team performance have been explored extensively, as we further detail below.

Generally, it is well accepted that strong team cohesion can enhance overall team effectiveness because the increase in task performance that results from greater team cohesion influences team efficiency and goal attainment (12). In the literature, numerous studies have examined and reported a positive relationship between team cohesion and team effectiveness and performance. A meta-analysis conducted by Carron et al. (20), for example, confirmed the general relationship between team cohesion and performance in sport. Carron et al. examined the relationship between team cohesion and team performance based on type of sport (individual vs. team sports), type of team cohesion (social vs. task cohesion), gender, skill level, and age. The findings indicated a moderate, positive, and significant correlation between team cohesion and performance across various sport, cohesion type, and skill levels and age groups. The findings also indicated that the positive correlation between team cohesion and performance was significantly stronger for women compared to men. Filho et al. (21) also conducted a meta-analysis using studies from between 2000 and 2010, which found support for the general positive relationship between these two variables as well as the moderating effect of gender in the relationship.

Teach cohesion aids performance in important ways, as cohesive teams tend to demonstrate higher collective effort and motivation, driven by a sense of shared responsibility and reinforced by mutual trust and reciprocity within the group. Team cohesion is expected to also promote the sharing of expertise and resources, enhancing the group's overall ability and skills. Open communication and support among team members lead to better coordination and preparation, while strong social bonds foster persistence and resilience during challenges. Finally, effective collaboration and seamless task execution are facilitated by shared resources and information, made possible by strong social capital (22).

The current study was designed to examine cross-cultural team dynamics between Korea and Hong Kong, focusing on their distinct cultural backgrounds (e.g., collectivism vs. individualism) and sports development systems (e.g., elite-oriented vs. sport-participation). While both countries share certain Confucian cultural roots, their distinct positions within East Asian cultural frameworks provide a valuable lens to understand how national cultures influence individual and group behavior. According to Hofstede's framework (23), Korea is characterized as a strongly collectivistic society with high power distance and strong uncertainty avoidance—characteristics that theoretically support hierarchical team structures with strong internal cohesion. In contrast, Hong Kong presents a unique cultural hybrid, influenced by both Chinese collectivistic traditions and a British individualistic colonial history, resulting in moderate individualism scores and different power distance orientations compared to Korea.

In addition to cultural differences, variations in sport development systems in Hong Kong and Korea also create different environments for student-athletes, since the diverse collegiate sports environment may influence the formation of team chemistry and associated impact on team outcomes. The Korean collegiate sports system emphasizes elite development and competitive excellence, creating high-stakes environments where social capital investment becomes critical for individual and team success (2). Hong Kong's collegiate sports system, in contrast, emphasizes broader participation and recreational benefits rather than elite competition, potentially creating different incentive structures for social capital development (13). For example, the main role of collegiate sports in Hong Kong is to provide students opportunities to learn sportsmanship and encourage physical activity as an important part of the academic curriculum, while the main role of collegiate sports in Korea is to provide intensive athletic training and support to a few elite student-athletes (2). In other words, while college sport is more participatory in Hong Kong, it is focused primarily on competition in Korea.

In Hong Kong, the University Sports Federation of Hong Kong (USFHK) emphasizes collegiate sports as an integral part of academic life. In this way, the USFHK seeks to integrate sports with academics as a significant part of university culture. In the 2023–24 season, student-athletes from 13 tertiary institutions in Hong Kong participated in 18 sports. In contrast, the Korea University Sport Federation (KUSF) primarily provides more of an advisory role rather than organizing competitions, as it provides limited annual leagues for several men's sports. In fact, university competitions are mainly organized by each national sports association. While the USFHK offers the same opportunities for male and female student-athletes to participate in annual leagues, the KUSF provides only limited sports leagues for female student-athletes, which accentuates the male-dominant elite sports culture in Korea. This highlights a divergence in collegiate sports systems between Hong Kong and Korea, with Hong Kong prioritizing broad student participation and Korea focusing more on elite athlete development (2).

With this context in mind, the main goal of this study was to explore how the unique sports cultures in Korea and Hong Kong could impact the connection between team cohesion and team performance. The study's hypotheses proposed that student-athletes' attitudes and behaviors in their athletic pursuits may be influenced by the structures and characteristics of sports in each country. By examining these variations, the study aimed to uncover the relationship between culture, teamwork, and athletic success in Korea and Hong Kong. The hypotheses were as follows:

Hypothesis 1: Team effectiveness varies based on the density of the team network.

Hypothesis 2: Variations in team effectiveness are apparent based on nationality.

Hypothesis 3: The interaction effect of team network density and nationality influences team effectiveness.

The population for this study were student-athletes participating in collegiate sports in Korea and Hong Kong. Data from Korean athletes were collected between October and December 2023, while data from Hong Kong athletes were collected between April and May 2023. The choice of these time periods was based on to the academic year disparities between two countries; Korea's academic year commences in March, whereas Hong Kong's begins in September. This scheduling ensured that participants had completed an entire season of college sport before taking the survey.

To create a survey environment where every athlete could nominate their teammates, we asked team managers to facilitate a meeting for all members of their team. Consequently, we gathered as many team members as possible and requested their participation in our survey. However, we found that some data included inaccurate responses (e.g., incorrect or inappropriate names), which were excluded from the final analysis. In addition, we excluded responses from teams where less than 50% of the members participated. Through this process, 600 data points were utilized for the final analysis. Specifically, in Korea, 256 athletes from 30 teams (12 men's teams and 18 women's teams) completed the survey, while in Hong Kong, 344 athletes from 14 men's teams and 13 women's teams participated in the survey. Consequently, the respondents engaged in 21 different sports (e.g., badminton, basketball, dragon boat, fencing, handball, rugby, table tennis, taekwondo, volleyball, water polo, shooting) across the two countries. Additional demographic information is presented in Table 1.

The questionnaire employed in the current study consisted of three components: a. demographic information, b. Name Generator Questionnaire (NGQ) based on social network analysis, and c. pre-existing item-based scale for team effectiveness.

The first section of the survey asked participants' demographic information (i.e., nationality, gender, and sport). We considered only three demographic variables so as to avoid survey fatigue and foster thorough, comprehensive completion of the NGQ, which requires significant cognitive effort.

The second section included the NGQ, which asked participants to nominate names of athletes in their advice network. For the NGQ component, participants were asked the following question: “Who do you ask for advice among your team members?” Participants were allowed to write five names of team members for the above question. The NGQ measurement has been utilized as a proxy of team cohesion by numerous social network studies (18, 24, 25). For instance, in Wei et al. (26) study, the relationship with team effectiveness was revealed by measuring the nurse's team cohesion in the NGQ method. In addition, Wäsche et al. (27) suggested that adoption of social network analysis (SNA) included NGQ has proven useful in sport field. SNA focuses on the relational nature of social structure rather than categories attributed to independent social units. As such, SNA represents a method to advance the substantive understanding of structures and processes constructed through or resulting in relations among social actors. NGQ, which is based on the sociometric scale rather than the indirect measurement method through a questionnaire, is effective in identifying the structural relationship of a team. In addition, criteria for identifying inappropriate responses (e.g., repetitive nomination, reference to an off-list name) were established, and these data were excluded from the final analysis.

The third section included an existing, previously validated scale for team effectiveness—20 items with five sub-factors (i.e., ability, effort, persistence, preparation, and unity) from the Collective Efficacy Questionnaire for Sports (CEQS) developed by Short et al. (28). The CEQS was used to assess student-athletes' perceptions of team effectiveness using a 7-point Likert scale ranging from 1 (strongly disagree) to 7 (strongly agree). The measurement tool was validated through a translation and back-translation process by experts. A final version was then created in two languages (Korean and Chinese) and administered to a Korean sample and a Hong Kong sample, respectively. This study received approval from the Research Ethics Committee of the Hong Kong Baptist University (REC/22-23/0372), and the informed consent was obtained from each participant prior to data collection.

The current study used density of advice network to measure team cohesion. The exchange of internal advice among athletes within a sport team is critical, as the advice shared between team members can profoundly impact the team's ability to achieve its goals or desired outcomes (20). Additionally, internal advice plays a crucial role in the team's strategic decision-making process (29). While prior studies (25, 30) often used a representative value, such as the mean, of individual responses to assess team cohesion, the limitations of this indirect measurement approach have been widely recognized in the literature. In response, several researchers (18, 31, 32) have attempted to measure team cohesion more directly through density of networks, similar to the approach taken in the current study.

Advice network density measures the proportion of actual relationships among the members of a person's social network compared to the maximum number of possible relationships (33). The density calculation can be computed using the following formula.advicenetworkdensity=2kn(n−1)In this formula, k denotes the number of advice connections present in a network, while n represents the total number of student-athletes in the network. Advice network density may range from 0 to 1. For instance, if all individual players in the network were completely unconnected, the structural cohesion measure would be 0. However, if all players were fully connected to each other (i.e., all members of the team are nominated by teammates as people from whom they seek advice), the structural cohesion measure would be 1. Therefore, in this study, a dense network means that members of a team are closely interconnected via advice sharing, while a sparse network would suggest the opposite. In this context, a connection refers to a relationship where two players exchange advice with each other.

Upon computing the advice density of each sports team in both countries through the provided formula, teams were categorized into two groups—dense advice network and sparse advice network—using the respective medians. In other words, the teams were divided into two groups according to being either above or below the median advice density values (.388 for Korea teams and.431 for Hong Kong teams). In turn, this process created four groups: 1. a dense advice network group in Hong Kong, 2. a sparse advice network group in Hong Kong, 3. a dense advice network group in Korea team, and 4. a sparse advice network group in Korea (D).

Subsequently, considering that gender of team members and team size were important variables for team effectiveness, a two-way ANCOVA was conducted on sub-dimensions of team effectiveness (i.e., effort, ability, preparation, persistence, and unity). Additionally, for intuitive comparison, Figures 1–5 were displayed to compare the means across the four groups. All statistical significance levels were 0.05, and SPSS 24.0 was employed for the analysis. Also, to determine the homoscedasticity of the assumptions of ANCOVA, the Breusch-pagan test was carried out.

The current study utilized advice network density as a proxy for team cohesion, which, while appropriate, may not fully capture all critical aspects of team dynamics, such as emotional support and informal social interactions that also play a role in cohesion within sports teams. Therefore, future research should incorporate additional measures that assess communication and leadership styles to gain a more comprehensive understanding of team cohesion in sports settings, including exploring the influence of emotional support and informal social interactions.

Furthermore, the findings in this study were limited to collegiate sports environments in two countries, which may limit generalizability to other organizational contexts, such as professional sports teams. To improve the broader generalizability of findings, future research should expand beyond collegiate sports environments to encompass various organizational settings, including professional sports teams. Such an approach would facilitate comparisons across different types of organizations and enhance the transferability of research outcomes to a wider array of contexts.