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date: 22 June 2021

Social Networks and Employee Creativityfree

Social Networks and Employee Creativityfree

  • Gamze KoseogluGamze KoseogluDepartment of Management and Marketing, University of Melbourne
  •  and Christina E. ShalleyChristina E. ShalleyScheller College of Business, Georgia Institute of Technology


In the field of management, employee creativity, which is defined as the production of novel and useful ideas concerning products, processes, and services, has been found to be necessary for organizational success and survival. An employee’s relationships with others in the organization affect creativity because employees work in the presence of, and with, their coworkers. A social network approach has been taken to understand how employee relationships can affect creativity.

Social networks examine the interaction of individuals with those around them, such as asking them for help or advice. Four components of social networks that have a role in employee creativity have received attention: the nature of the employee’s relationships with coworkers, the structure of the employee’s social network, the position of the employee in the organizational network, and the employee’s network heterogeneity. Regarding the nature of relationships, while some researchers have found that weaker ties are more beneficial for employee creativity, other researchers have found that stronger ties are more advantageous. In order to resolve this conflict, researchers examined the role of strong versus weak ties at different stages of the creativity process and found that, while weak ties might be more useful during idea generation, strong ties come into play during idea elaboration. There are also conflicting findings on the role of the structure of social network. Specifically, a group of researchers found support for a positive relationship between sparse networks and employee creativity, and another group found a positive relationship between dense networks and creativity. Some researchers aimed to resolve this debate, and their findings mirrored the findings on tie strength. They found that density affects different stages of the creative process in unique ways, and while sparse networks are more beneficial during idea generation, dense networks become more important during idea implementation.

Compared to the previous two components, the role of network position and network heterogeneity has received less attention from researchers. Researchers found that both central and peripheral positions have certain benefits and costs for creativity. For example, on the one hand, employees located at the periphery of an organization can collect nonredundant information from outside of the organization that has not been shared by others in the organization and has a positive influence on creativity. On the other hand, employees at a central location gain benefits from fast and easy access to information based on many contracts and receiving recognition from many others, thereby improving creativity. Finally, researchers consistently found that different types of network heterogeneity, such as the diversity of one’s contacts in terms of functional background, organizational function, or nationality, positively affects employee creativity.

There are many opportunities for future research on the relationship between social networks and creativity, such as examining the role of motivational and cognitive processes as mediational mechanisms, focusing on the role of alter characteristics, studying social networks in a team setting, and taking a temporal approach to understand how changes in social networks over time affect employee creativity.


  • Human Resource Management
  • Organizational Behavior
  • Problem Solving and Creativity

What Is Employee Creativity?

At the individual, team, and organization levels, it has been argued that creativity is key for performance, competitiveness, entrepreneurship, and growth (Amabile, 1996; Oldham & Cummings, 1996; Shalley, 1991; Shalley et al., 2015; Woodman et al., 1993; Zhou, 1998). Creativity is defined as the production of new and useful ideas concerning products, services, processes, and procedures (see Amabile, 1996; Oldham & Cummings, 1996; Shalley, 1991). Both novelty and usefulness are necessary conditions for something to be regarded as creative in the workplace. So, for example, if an idea is considered to be unique or novel, but it is not useful, it is not viewed as creative.

All employees have the potential to be creative, not all the time or in every situation, but the potential is there. In addition, employees working in any kind of job and at all levels of the organization have the potential to be creative in their work (Amabile, 1996; Shalley et al., 2000; Woodman et al., 1993), although there are individual differences in terms of the magnitude of their potential. In addition, the level of creativity realized can vary from something that is novel yet incrementally different from what may already be known to exist, to something that is a radically new and significantly different idea, product, or process. A related concept is innovation. The primary difference between definitions of creativity and innovation is that whereas creativity emphasizes the production of new and useful ideas by individuals and teams, innovation emphasizes the implementation of new ideas or practices in a unit or throughout an organization (Shalley et al., 2015). Therefore, innovation also can involve an organization’s implementation of ideas that were developed by individuals in other organizations. That said, organizations that effectively promote and utilize their employees’ creativity have done a better job of leveraging their employees’ capabilities and have a better chance of creating and/or sustaining a competitive advantage.

Social Networks and Creativity

Employee creativity has a social side that is influenced by the social context around individuals (Perry-Smith, 2006). One contextual factor that affects creativity is an employee’s communication with others around him or her (Ancona & Caldwell, 1992; Perry-Smith & Shalley, 2003). The contacts are important because often individuals alone do not have sufficient information or enough background to develop a complex idea; therefore, they do not generate ideas in isolation from others (Dahlander & Frederiksen, 2012; Taylor & Greve, 2006). In addition, individual creativity can be an outcome of a collective effort, through interactions like getting help from others in the organization (Hargadon & Bechky, 2006).

A social network approach allows the investigation of individuals’ interactions with the larger field of connections surrounding them (Kilduff et al., 2006). Social networks can affect several organizational outcomes, such as compensation (Burt, 2004), performance evaluation (Burt, 2004; Sparrowe et al., 2001), and promotions (Podolny & Baron, 1997). They can also affect employees’ level of creativity (Burt, 2004; Perry-Smith & Shalley, 2003), because a person can generate and develop more creative ideas if they can combine different perspectives and information gathered from different contacts in the network (Baer, 2010). While social networks can be a potential source of diverse information, ideas, and perspectives (Burt, 2004; Perry-Smith, 2006), depending on how and to whom a person is connected, they can at times be detrimental to creativity (Burt, 2004; Zhou et al., 2009). For example, Burt (2004) found that social networks can limit individuals’ perspectives when the networks are composed of similar, closely connected others. In addition, Zhou and colleagues (2009) found a curvilinear relationship between the number of weak ties and creativity, in that employees had greater creativity when their number of weak ties was at intermediate levels, rather than at high or low levels. This occurs because having more weak ties is desirable up to a certain point, after which there are diminishing returns for more ties, which can be distracting and may lead to cognitive overload.

The role of social networks in creativity received increased levels of attention after Perry-Smith and Shalley (2003) and Burt (2004) introduced networks as a critical contextual factor that can affect employee creativity. Accordingly, work published between 2003 and 2020 in top-tier international journals on the role of social networks on employee creativity and innovation can be categorized into four social network domains: the nature of ties, the structure of the network, the position in the network; and network heterogeneity. It should be noted that there have been conflicting findings in the literature, primarily in the first three domains (i.e., the nature of ties, the structure of the network, and the position in the network; Baer et al., 2015), and the results regarding network heterogeneity have been mainly consistent.

In addition, social networks have been studied at the full network level and at the ego network level (Kilduff et al., 2006). A full network includes all the individuals in a collective, such as an organization or an industry (Scott & Davis, 2007). Ego networks, on the other hand, consist of only a focal actor (ego), actors that are connected to the focal actor (alters), and the relationships between the alters (Scott & Davis, 2007). Studies that examine the effects of social networks on creativity have taken both a full network approach (e.g., Burt, 2004; Cattani & Ferriani, 2008; Fleming et al., 2007; Obstfeld, 2005; Perry-Smith, 2006; Perry-Smith & Shalley, 2003; Zhou et al., 2009) and an ego network approach (e.g., Baer, 2010; Jarvenpaa & Majchrzak, 2008; McFayden et al., 2009). This article discusses the findings for each of the four domains (i.e., the nature of ties, the structure of the network, position in the network, and network heterogeneity) and across the two levels, full network and ego network. The main debates that exist in the literature are also presented.

The Nature of the Ties and Employee Creativity

Researchers who focus on the nature of the ties study the quality of the relationships between individuals (Granovetter, 1973). Work in this area originated from Granovetter’s (1973) strength of weak ties argument. He defined tie strength as a combination of the frequency and duration of the relationship between two parties and the emotional intensity they have toward each other. He argued that individuals have a limited amount of time to develop relationships, so investing in many strong ties that have high emotional intensity, duration, and frequency is often infeasible, whereas building many weak ties with distant contacts within the same amount of time can be more efficient. Accordingly, he argued that having a high number of weak ties has informational benefits, because individuals can receive diverse information from a higher number of contacts.

Creativity researchers who follow Granovetter’s (1973) strength of weak ties argument have suggested that weak ties are more beneficial for collecting diverse and nonredundant information and perspectives from various contacts, (e.g., Baer, 2010; Perry-Smith, 2006; Perry-Smith & Shalley, 2003; Zhou et al., 2009). The assumption behind the strength of weak ties argument is that, as homophily theories state, individuals tend to keep similar others closer (Klein et al., 2004), and the similar others carry information that is similar to, and redundant with, information carried by the ego. Employees can have access to nonredundant information only if they form weak ties with distant contacts who are less similar to themselves (Zhou et al., 2009).

Consistent with this view, Perry-Smith (2006) found that while the number of weak ties had a positive relationship with employee creativity, the number of strong ties did not have a significant effect. Furthermore, she found that the number of weak ties affected employee creativity via access to a heterogeneous group of contacts. Zhou and colleagues (2009) extended Perry-Smith’s (2006) arguments and found a curvilinear relationship between number of weak ties and employee creativity, implying that a moderate number of weak ties is the most advantageous condition. They argued that the reason behind this outcome is that, after a certain number of weak ties have been accumulated, it becomes cumbersome to have meaningful discussions with each of the contacts and to develop and maintain relationships with each of them, and this can distract employees from the creative thinking process. In an experimental study, Perry-Smith (2014) dug further into the content of the nonredundant information that is carried via strong versus weak ties. She identified two types of knowledge content, factual information and frames, which are interpretations or perspectives. She found that both frames and factual information were received from weak ties, but only frames received from strong ties could facilitate creativity.

As opposed to the strength of weak ties, some researchers argued that stronger relationships are more beneficial for creative performance because people share higher quality information only if they have trust-based strong relationships with each other (Krackhardt, 1992; McFadyen et al., 2009). For instance, in his study of small organizations in the women’s knit dress industry, Uzzi (1997) found that strong ties created trust among actors and triggered information transfer and joint problem-solving. Smith et al. (2005) also found that strong ties were more advantageous for creativity, as complex and tacit knowledge can only be carried via strong relationships. Furthermore, Kijkuit and van den Ende (2010) found that tie strength is useful during the idea initiation and development phases of the innovation process. Fleming and colleagues (2007) found that if actors collaborated repeatedly, the creativity of their patent applications increased. Sosa (2011) reported that a strong relationship between actors facilitated the generation of creative ideas. In addition to focusing on the strength of the relationship, Sosa also examined the content of the information that was transferred via the relationship and found that strong ties that carried a wide domain of knowledge were better for creativity. Finally, a meta-analysis of 45 studies (Baer et al., 2015) found that there is a positive relationship between tie strength and employee creativity and innovation.

Some researchers aimed to resolve this puzzle by studying the impact of strong versus weak ties at different stages of the creative process (Hansen, 1999; Kijkuit & van den Ende, 2007; Perry-Smith & Mannucci, 2017), or by focusing on certain individual differences (Kim et al., 2018). For instance, Hansen (1999) argued that while weak ties are more beneficial during the knowledge-transfer process, strong ties are more beneficial during knowledge creation. In their conceptual piece, Perry-Smith and Mannucci (2017) argued that the number of weak ties can facilitate the idea-generation stage of the creative process, and that strong ties can facilitate the idea-elaboration stage. With regard to individual characteristics, in their conceptual work, Kim et al. (2018) argued that tie strength can affect individuals differently based on certain individual differences. They suggested that an individual’s openness to experience moderated the relationship between tie strength and employee creativity, such that weak ties would have a more positive effect if individuals were high on openness to experience, because the individuals can take advantage of the nonredundant information transferred via weak relationships. In summary, research indicates that both weak and strong ties can be beneficial for creativity, and which ties might be better can depend on the stage of the creative process or personal characteristics of the employee.

The Structure of the Network and Employee Creativity

Burt carried the focus of network studies from the tie level to the structure of the overall network. He developed the concept of structural holes, which are defined as gaps in the social network that occur between two individuals or two groups that are not connected to each other (Burt, 1992). A bridge or a broker is a person who fills this gap by connecting the two contacts or the two groups who would otherwise not be connected to each other (Burt, 2004; Fleming et al., 2007). Network density is evaluated as a proxy for structural holes in a network (Podolny & Baron, 1997). If there are a lot of structural holes in a person’s network, the network is considered sparse, because only one or a few of the alters are connected to each other. If there is only one person connecting these alters in a network, this person is considered to be in a brokerage position. When more of the alters are connected to each other, there is higher closure (Coleman, 1990), and the density of the network is higher.

Similar to the weak versus strong relationships trade-off, the importance of sparse versus dense networks is the subject of an ongoing debate. According to Burt (1992, 2004), a person who can bridge structural holes in a sparse network by connecting two disconnected others has control over the flow of information, and this person can have access to nonredundant and unique information from these contacts that the contacts have not shared between the two of them. One of the early studies on the benefits of a brokerage position was a qualitative study in a design company, IDEO, by Hargadon and Sutton (1997). They concluded that firms acting as a broker between unconnected organizations and industries tend to be more innovative because these firms access a variety of ideas and technologies from different companies and combine them in new and original ways. Burt (2004) empirically tested the role of structural holes at the individual level and found that individuals who bridge across different groups can generate better ideas because they are able to access different knowledge and perspectives. Similarly, Gargiulo and Benassi (2000) found that sparse networks provide flexibility to managers in adapting to changes in the environment with new solutions, and this flexibility can be considered a proxy for the creativity of managers. Consistent with this view, in their meta-analysis, Baer and colleagues (2015) found that network brokerage had a positive relationship with employee innovation.

As opposed to Burt’s sparse network perspective, Coleman (1990) claimed that dense networks are superior to sparse ones, because people located in dense cliques, where alters are already connected to each other, develop trust-based relationships. Employees working in these dense networks share more information and collaborate with each other, which can eventually improve their creativity (Fleming et al., 2007; McFadyen et al., 2009). In contrast to the bridge, who strategically keeps the alters apart from each other, the tertius iungens orientation was introduced by Obstfeld (2005). He stated that those who have this orientation close the gaps in the network by strategically introducing unconnected alters to each other, resulting in the increased density of the social network. Obstfeld found that this behavior generates new collaborations between actors, and therefore people with high levels of a tertius iungens orientation tend to have higher levels of involvement in the innovation process. He also found that actors who have a dense network are also more involved in the innovation process. Kauppila et al. (2018) further examined the role of tertius iungens orientation in employee creative performance and found a positive relationship between the two.

Although research raised the issue of whether sparse versus dense networks were better for creativity, some researchers tried to disentangle the conflicting findings by integrating the dense versus sparse networks perspectives. To do that, researchers focused on the role of different network structures at different stages of the creativity process. For example, Fleming and colleagues (2007) found that an inventor in a broker position is more likely to create new combinations. However, in idea implementation, the new combinations that were generated in a cohesive and collaborative network structure are more likely to be used again because others in the dense network feel that they have contributed to the idea development as well, and the ideas spread more effectively between inventors in a dense structure. Kijkuit and van den Ende (2007) suggested that idea development has three stages: idea generation, idea development, and idea evaluation. Similar to Fleming and colleagues, Kijkuit and van den Ende (2010) found that for higher creative output, network density should gradually increase in each stage, because while network sparsity has benefits for the idea-generation stage, for idea refinement, dense networks are better, because idea refinement requires coordination and the willingness to help among actors.

In order to address the conflicting findings, Jokisaari and Vuori (2014) paid attention to a specific group of employees who were the newcomers to an organization. They found that, because newcomers have limited knowledge about the new organizational environment and what information each of their coworkers is holding, it is more advantageous for them to have a sparse network in order to have higher innovative performance, because then they have access to a wider range of information and they also are bringing in different perspectives. However, the researchers also found that this relationship is moderated by the extent to which newcomers provide information to the existing members of the organization: if the newcomers give information to others in the organization, the sparsity of their networks is no longer important. The researchers proposed that this might be because as newcomers provide more information to the existing members, they become more socialized, their skills and knowledge are more valued by others, and they acquire sufficient competence to perform creatively, reducing the relevance of their sparse network.

Finally, Soda et al. (2019) challenged the assumption that a specific network structure, either a dense or a sparse one, automatically leads to collaboration. That network structure alone leads to certain employee behaviors and motivations can be considered an oversimplified assumption that ignores individual agency (Tasselli & Kilduff, 2021). Soda and colleagues (2019) argued that network structures do not immediately offer benefits like collaboration, but they offer opportunities to be recognized by the actors in the network. Accordingly, Soda et al. introduced collaboration as a moderator mechanism that affects the role of dense or sparse networks in employee creativity, rather than assuming one of the structures will definitely lead to collaboration. They found that individuals who work in a dense network have higher creativity if collaboration in the network is high, and employees who act as a bridge in a sparse network are more creative if collaboration in the network is low.

In summary, based on the current state of the research on the structure of networks and employee creativity, we can conclude that, depending on the stage of the creative process, there are times when having a sparse network is better for employee creativity and other times when having a dense network is more beneficial for employee creativity. Also, in general, the positive effect of network density has been found to increase with each stage in order to lead to higher creativity. Furthermore, network structures provide the opportunity to be recognized by actors in the network, but collaboration is necessary to realize their benefits. For example, higher creativity can result in dense networks when there is high collaboration and in sparse networks when there is low collaboration, and having employees who act as a bridge leads to higher creativity.

Position in the Network and Employee Creativity

The third domain of social networks is an employee’s location in the organizational network. Although there are different types of centrality, most current research examines degree centrality, which is the main focus here. Degree centrality is defined as the number of contacts one has in the network (Freeman et al., 1979). When an employee has many contacts in the network, this person is more central (i.e., in a core position). If the individual has many contacts outside of the organization, rather than inside of the organization, the location of this person in the organizational network is more on the periphery.

There is a trade-off between core and peripheral positions. On the one hand, some researchers found that peripheral locations are more advantageous for creativity because being in a peripheral position has the potential benefit of giving access to different and nonredundant information outside of the organization that is less likely to have been shared by other members of the organization (Cattani & Ferriani, 2008; Perry-Smith & Shalley, 2003). Accordingly, Perry-Smith (2006) found that centrality has no direct effect on employee creativity, but that having a high number of outside ties (i.e., a peripheral location) has a positive relationship with creativity. In addition, she found that being in a central location in the organization while also having many outside ties can be detrimental, because having too many relationships inside and outside the organization at the same time can be distracting.

On the other hand, some researchers argued that central positions have certain benefits for employee creativity, such as having easy and fast access to information from many contacts and receiving recognition from others due to the central person’s increased popularity, which increases the likelihood that one’s ideas will be accepted (Cattani & Ferriani, 2008; Dahlander & Fredericksen, 2012). Yet, central positions can also have some limitations, such as the tendency for individuals at a very central location to conform to social norms and values, which can be detrimental for creativity (Dahlander & Frederiksen, 2012). Reflecting on the impact of this trade-off, Cattani and Ferriani (2008) found an inverted U-shaped relationship between employee centrality and creativity, suggesting that an intermediate position between a central and a peripheral location would be the best for employee creativity. Cattani et al. (2015) further suggested that an intermediate position should be a position where individuals can have access to new ideas by being close to the periphery, but they can also maintain their legitimacy and recognition by being close to the center.

Work on other types of centrality is very limited. One other type of centrality is closeness centrality, which is the distance between an actor and all the other actors in the network. A study that looked at closeness centrality was done by Perry-Smith (2006). She found that closeness centrality interacted with the number of ties outside the organization, such that it had a positive effect on creativity if the employee had a low number of outside ties and had a negative effect on creativity if the employee had a high number of outside ties. In other words, when an individual has many ties outside of the organization, being central loses its importance for being creative, and an employee who has high closeness centrality can get distracted and may have difficulty in managing relationships if this employee also has many contacts outside of the organization.

In summary, there has not been as much research on position in the network as research on the nature of ties or on the structure of the network and creativity. In the future, it would be good to see more work on degree centrality as well as other types of centrality, such as closeness centrality. From the work that does exist on degree centrality, it is still unclear if being central in the network versus on the periphery is best for creativity. Research has highlighted a problem with being too central or with being both central in the network and having many ties outside the network, because both situations can lead to distractions and require a great deal of time to maintain the many ties. Therefore, it would be good to have more research examining the conditions in which degree centrality is best for creativity and the conditions in which being on the periphery of the network is positive for creativity.

Network Heterogeneity and Employee Creativity

The final network characteristic that has been studied is network heterogeneity, although there is much less research on its effect on creativity. Knoke and Yang (2008) described network heterogeneity as the level of diversity with respect to a specific characteristic of the alters of an ego. Studies that have examined the role of network heterogeneity usually take an ego network approach, because the main interests are who the ego is and who the ego’s contacts are. The diversity characteristics can take various forms, such as functional background (Baer, 2010), organizational function (Gong et al., 2020), or nationalities (Perry-Smith & Shalley, 2014) of alters. As opposed to the other network domains discussed above, which have contradictory findings for employee creativity, researchers consistently have found that network heterogeneity enhances creativity, because heterogeneous ties can provide nonredundant and diverse information and perspectives to the creator (see Chua, 2018; Gong et al., 2020; Huang & Liu, 2015; Perry-Smith & Shalley, 2014; Rodan & Galunic, 2004). In fact, Rodan and Galunic (2004) found that network heterogeneity has a greater impact on individuals’ innovative performance than on their overall managerial performance, suggesting its critical role for creativity. However, because there has not been as much work in this area, it would be beneficial for future research to examine and compare differential effects of several types of heterogeneity (e.g., functional background versus ethnic background) on employee creativity.

Contemporary Approaches and Future Research Directions

The majority of the research that has examined the role of social networks in employee creativity has focused on disentangling the conflicting findings related to weak versus strong ties, dense versus sparse networks, and central versus peripheral locations. Instead of focusing on the conflicting findings in each domain, a growing trend is to integrate different social network characteristics to study their effects. For example, Baer (2010) examined the interaction between network diversity, network size, and network strength and found that the highest creativity occurred when employees had weak relationships with contacts, high network diversity, and an optimal network size. Specifically, he argued that an optimal network size provides the breadth of information necessary for creativity, weak ties ensure that the information is novel as the actor reaches out to distant contacts through weak relationships, and, on top of the first two, network diversity ensures that information from each distant contact is distinct and nonredundant because the contacts belong to different social groups. McFadyen and colleagues (2009) found that network density and average tie strength interacted, such that those scientists who had strong relationships with their contacts on average and who had sparse networks had the highest levels of knowledge creation. Gong and colleagues (2020) studied the interaction effect of network diversity and tie strength and found that those employees who had a diverse network and connected to this diverse set of contacts via strong relationships had higher levels of creative self-efficacy, which eventually improved employees’ creative performance. Finally, a recent meta-analysis by Baer and colleagues (2015) took a new approach by comparing the relative importance of different network characteristics for employee innovation. They found that brokerage was the strongest predictor of employee innovation, followed by network size, network heterogeneity, and finally the strength of relationships.

Recently, researchers started moving away from the conflicting findings, which opened multiple research avenues for future research. First, researchers started testing the role of new mediation mechanisms. For example, Gong and colleagues (2020) indicated that an information lens had been dominating research on social networks. In other words, when researchers tried to understand positive or negative effects of tie strength, network structure, position in the network, or network heterogeneity, they mainly focused on the informational benefits that would be provided by the networks. Gong and colleagues, however, took a motivational lens, and examined the role of employee’s creative self-efficacy as a motivational mediation mechanism. They found that employees who had diverse social ties felt more confident about their resources and the potential information they might be able to access, which increased employees’ creativity via strengthening their creative self-efficacy. In the future, researchers can examine the role of other motivational or cognitive mechanisms related to creativity and innovation instead of focusing only on informational mechanisms.

Second, until the early 21st century, researchers examined the role of the individual characteristics or the network characteristics of the ego in an individual’s creativity. However, the characteristics of the contacts on the other end of the relationship (i.e., alters) and the specific resources the contacts provide also may play a critical role (Lin et al., 1981). Accordingly, there is a shift in the literature to focusing on alter characteristics in addition to the characteristics of the ego. For example, Grosser et al. (2017) found that an employee’s alters’ creative self-efficacy had a positive relationship with the employee’s generation and implementation of ideas because alters with higher creative self-efficacy serve as better role models. The researchers further found that alters’ average creative self-efficacy interacted with alters’ network density. Specifically, having alters with high creative self-efficacy had a stronger impact on employee creativity if alters’ average network density was low, because alters who had sparse personal networks could provide more nonredundant information to the employee. Li et al. (2018) also focused on alter characteristics and found a positive relationship between the brokerage position of an advice giver and an advice recipient’s creativity enhancement over time. In the future, researchers can investigate the effects of other network characteristics of an ego’s alters, as well as their interactive effects with alters’ individual traits, to determine their overall effects on the ego’s creativity.

Third, instead of evaluating the role of characteristics of direct networks, it is possible to examine the role of indirect networks, which extend direct networks to second, third, or even fourth-degree contacts (i.e., two degrees of separation means the contacts of a contact, three degrees of separation means the contacts of a contact of a contact, and so on). For example, Hirst et al. (2015) studied reach efficiency and creativity, with reach efficiency being an indirect network measure that involves who you are directly connected to and who that person is connected to, by which you can potentially gain access to nonredundant information. They found that reach efficiency can lead to an actor’s getting nonredundant information from people who are two, three, and four degrees of separation from the actor and that this could still positively affect employee creativity. Researchers can focus on other network measures in future studies, such as multiplexity (i.e., the number of different types of interactions between two actors; Hartman & Johnson, 1989), eigenvector centrality (i.e., a weighted centrality measure that takes into account the centrality scores of each of the contacts; Bonacich, 1972), or structural equivalence (i.e., the degree to which two actors have the same profile of relationships across alters; Sailer, 1978).

Fourth, there is a growing emphasis on the relationship between social networks and creativity in a team setting. For example, Li and colleagues (2020) found that creative stars who were located at a central position in a team had a positive direct effect on team creativity, because they were a source of new and useful ideas. However, creative stars’ team centrality also had a negative indirect impact on team creativity because it negatively affected nonstars’ team learning, which reduced team creativity. Tang et al. (2020) found that a team member’s centrality in the team’s problem-solving network moderates the relationship between the employee’s external knowledge-searching behavior and creativity in the science research field. Perry-Smith and Shalley (2014) examined the outside ties of a team and found that teams had the highest levels of creativity when each team member’s contacts outside the team had high levels of nationality heterogeneity, and teams were more creative when team members had weaker outside ties rather than stronger ties. Wang et al. (2015) found that an employee’s weak ties outside of the team improved the employee’s innovativeness by increasing the quality of leader–member exchange (LMX). Wang et al. argued that this is because the employee can provide benefits to the leader by bringing nonredundant information to which he or she has access outside of the team, and potentially the employee can help to extend the leader’s connections outside of the team. However, if there are strong relationships among team members within the team, the importance of LMX for individual innovation diminishes. There is much opportunity in this area for future study of the role of other team inputs, processes, and emergent states in the relationship between teams’ inside and outside ties and creativity.

Finally, research in the early 21st century on employee creativity and social networks has taken a more static approach, examining networks of individuals at a single time point (Burt & Merluzzi, 2016). However, relationships, and therefore social networks, are dynamic, and people constantly make decisions about which relationships to invest in and which relationships to end (Sasovova et al., 2010). Therefore, there is a need for research to examine the role of changes in relationship strength and position in the organizational network in employee creativity. For example, Buskens and Van de Rijt (2008) found that the benefits gained from a brokerage position disappeared soon after they were used.


In the early 21st century, there has been a prodigious growth in the number of studies focused on social networks and creativity. This work can be clustered into four main areas: the nature of ties, the structure of the network, position in the network, and network heterogeneity. The contemporary approaches to studying social networks and creativity include examining social networks and creativity in a team setting. Finally, there are some promising future research directions, such as examining the role of changes in network position and strength in employee creativity, since networks are dynamic. Certainly, there is still much that is not known about social networks and creativity, and there are some exciting new directions for research.

Further Reading

  • Baer, M. (2012). Putting creativity to work: The implementation of creative ideas in organizations. Academy of Management Journal, 55, 1102–1119.
  • Borgatti, S. P., Everett, M. G., & Johnson, J. C. (2013). Analyzing social networks. SAGE.
  • Gargiulo, M., Ertug, G., & Galunic, C. (2009). The two faces of control: Network closure and individual performance among knowledge works. Administrative Science Quarterly, 54(2), 299–333.
  • Kilduff, M., & Brass, D. J. (2010). Organizational social network research: Core ideas and key debates. The Academy of Management Annals, 4(1), 317–357.
  • Oh, H., & Kilduff, M. (2008). The ripple effect of person on social structure: Self-monitoring origins of network brokerage. Journal of Applied Psychology, 93(5), 1155–1164.
  • Perry-Smith, J. E. (2008). When being social facilitates creativity: Social networks and creativity within organizations. In J. Zhou & C. E. Shalley (Eds.), Handbook of organizational creativity (pp. 189–210). Lawrence Erlbaum Associates.
  • Shalley, C. E., & Perry-Smith, J. E. (2008). The emergence of team creative cognition: The role of diverse outside ties, socio-cognitive network centrality, and team evolution. Strategic Entrepreneurship Journal, 1(2), 23–41.
  • Wasserman, S., & Faust, K. (2009). Social network analysis: Methods and applications (19th ed.). Cambridge University Press.


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