Hong Yang
Sid Suntrayuth- International College, National Institute of Development Administration, Bangkok, Thailand
In rapidly changing and knowledge-driven environments, building resilient teams has become a strategic imperative for knowledge-based organizations, particularly higher education institutions. This paper conceptualizes team dynamic capabilities using the SECI model and examines the serial mediating roles of communicative, leadership, interpretation, and analytical. Using survey data from 617 faculty and staff members in Chinese higher education institutions. The study applies structural equation modeling (SEM) to test the proposed relationships. The results show that these four behavioral capacities serve as partial mediators between team dynamic capability and team resilience, highlighting the importance of knowledge-based team processes in shaping resilience. The findings provide practical implications for higher education institutions in building resilient teams under changing environments.
1 Introduction
Higher education institutions worldwide face diverse pressures originating from both inside and outside the university, from society, industry, and politics (Young et al., 2024). In recent years, universities worldwide have faced increasing pressure to adapt to rapidly changing environments, both externally and internally. In addition to external environmental pressures, functionalist expectations demand that universities broaden and extend their missions to meet the evolving needs of diverse stakeholders (Compagnucci and Spigarelli, 2020; Enders and De Boer, 2009). Within the Chinese higher education system, public universities are characterized by a pronounced hierarchical structure, including national, provincial, and local institutions. This stratification has been further intensified by the “Double World-Class Project,” a national policy that concentrates resources on a select group of elite universities and disciplines to enhance global competitiveness. Consequently, local universities that are excluded from this policy framework face mounting transformational pressures. These institutions are compelled to pursue differentiated development strategies and institutional innovations to sustain their relevance and viability.
Meanwhile, since 2019, China’s higher education system has transitioned from a stage of massification to universalization, shifting its reform focus toward high-quality development, particularly in terms of innovation potential. Innovation has been increasingly recognized as a value-added driver of higher education institutions’ social contributions (Huizingh, 2017), and as a means of continuously stimulating institutional vitality (Liu, 2021). These evolving demands have placed pressure on higher education systems to cultivate resilience and build adaptive capacities to respond to change. Resilience enables higher education institutions to maintain quality and operational continuity amid disruptions (Karlsson and Offord, 2023; Ramirez, 2020). Although universities have historically been viewed as among the most resilient organizations in society (Stolze and Sailer, 2022), there is now a global call for higher education to adopt new models and practices—developing management capabilities once reserved for businesses (Stolze and Sailer, 2022).
In the context of transformation, local higher education institutions often operate in environments disrupted by shifts in national budgets, new governance mandates, and even political interventions (Teece, 2018). especially when academic staff lack research and development skills, motivation, and awareness of knowledge creation. At the same time, the challenges faced by institutions are often characterized by a high degree of uncertainty, systemic interdependence, and complexity, which require a higher level of organizational coordination and knowledge integration mechanisms. Against this backdrop, teams have become increasingly important as basic organizational units within universities, serving to connect individuals, integrate knowledge, and drive task execution. Teams are not only carriers of knowledge and resource flows, but also key spaces for implementing management objectives and building organizational resilience. Therefore, a team’s ability to maintain coordination, flexibility, and adaptability under changing external environments has become a critical factor affecting the overall operational quality and transformation outcomes of higher education institutions. A prevalent feature of internal operations in Chinese higher education institutions is the dual role system, under which faculty members often assume multiple responsibilities across teaching, research, and administrative functions. This policy-driven structure significantly shapes the nature of academic teams, resulting in incomplete team compositions and blurred team boundaries. Within such a context, collaboration tends to be highly cross-departmental and interdisciplinary. If stakeholders can effectively mobilize interactive resources and establish stable mechanisms of cooperation, it may unlock greater collaborative potential and contribute to the generation of enhanced public value.
However, university teams currently face a major challenge in responding to complex tasks—namely, how to effectively improve problem-solving capabilities. Although team collaboration is believed to enhance problem-solving ability (De Boeck and Scalise, 2019), in practice, team members often encounter multiple challenges that may interrupt workflows and reduce performance, thereby weakening team resilience (Stoverink et al., 2020). These challenges include conflict management (Fisher et al., 2020), sustaining trust (Newman and Ford, 2021), overcoming communication barriers (Casoria et al., 2020), and maintaining accountability (Stewart et al., 2023). In other words, even when various collaborative f mechanisms are in place, teams may still fail due to internal obstacles (Tannenbaum et al., 2012).
Owing to the various potential barriers to team collaboration, team dynamics can help teams overcome these challenges and unlock their potential (Neves, 2024). In fact, in diverse practical contexts, the complementary skills of a team members are essential for exponentially accelerating an organization’s overall success (Neves, 2024). Especially in a knowledge economy environment, the value of team collaboration lies in its absorptive capacity for diverse perspectives and specialized knowledge (Thayer et al., 2018). According to the dynamic capability theory, the generative aspect of capabilities stems from team-level interactions among organizational members. When such interactions can identify and seize opportunities presented in the form of knowledge, they can lead to resource recombination and transformation. Within the dynamic capability framework, knowledge-based opportunities that are perceived and captured can result in the reconfiguration of existing resources (Nonaka et al., 2016). In this process, the knowledge creation model (Socialization–Externalization–Combination–Internalization, SECI) (Nonaka et al., 1996) provides a theoretical lens to understand how teams create knowledge through dynamic interaction, supporting the continuous evolution of knowledge and the reconstruction of capabilities. It offers important theoretical support for understanding how team members engage in knowledge creation. Existing research suggests that resilience is jointly determined by endogenous sources of new knowledge and deliberate decision-making (Martin-Breen and Anderies, 2011; Šūmane et al., 2018). Facilitating knowledge sharing within teams and enhancing information alignment can ensure that members’ capabilities match task requirements, thereby enabling the team to address complex problems in organizational environments (Hagemann and Kluge, 2017).
This paper aims to explore a new approach to understanding dynamic team functioning by examining the relationship between knowledge-creation-based team dynamic capabilities and team resilience. The serial mediation is conceptualized as a team behavioral mechanism, which facilitates the transition from knowledge creation to knowledge application for effective decision-making. It further reveals the internal mechanisms underlying the formation of functional teams and identifies critical boundary conditions.
2 Theoretical background and hypotheses
2.1 Dynamic capability theory
Dynamic capability focuses on “doing the right things”(Teece, 2015), aiming to enable organizations to renew their capabilities to adapt to changing environment (e.g., exploration) (Dixon et al., 2014). As one of the dominant theories in the field strategic management in recent years (Di Stefano et al., 2014; Forkmann et al., 2018), dynamic capability theory is applied to organizations to explain how the frequency of effectively reconfiguring resources contributes to achieving competitive advantage (Braganza et al., 2017).
In various studies, the definition of dynamic capabilities differs depending on the purpose (Barreto, 2010). However, a widely accepted composite definition by key contributors to the dynamic capabilities literature is that dynamic capabilities are the abilities of an organization to purposefully create, extend, or modify its resource base (Helfat et al., 2009). Here, the “resource base” refers to the organization’s resources, including tangible and intangible assets, human capital, and capabilities. This definition is currently regarded by key contributors as the most comprehensive reflection of the dynamic nature of dynamic capability (Munoz-Penas et al., 2024). In stable environments (Helfat and Winter, 2011), dynamic capability research claims to explain continuous, routine-based organizational change (Wenzel et al., 2021). Specifically, dynamic capability is considered to be a potential for systematically solve problems, which benefits from its tendency to sense opportunities and threats, this enables organizations to make timely decisions and effectively implement strategic decisions and changes, and thereby ensuring the right direction (Ferreira et al., 2020).
In contemporary organizational and managerial processes undergoing change, the primary task is to identify the need for or opportunity of transformation (Helfat et al., 2009). Accordingly, dynamic capabilities are viewed as “a combination of broad organizational capabilities and specific actions that work together to achieve organizational transformation” (Yeow et al., 2018), as well as “a subset of organizational and individual capabilities specifically dedicated to strategic change” (Helfat and Raubitschek, 2018). Moreover, since dynamic capabilities often rely on three general learning processes—experience accumulation, knowledge articulation, and knowledge codification (Zollo and Winter, 2002)—to enable capability evolution within organizations, it can be argued that knowledge constitutes the cognitive foundation of dynamic capabilities.
As in most of literature on focuses on the ability of an organization to sense, seize, and transform its ecosystem (Teece, 2007; Teece, 2014). This three-dimensional categorization enhances the conceptual consistency and clarity of dynamic capabilities (Eriksson, 2014). Dynamic capabilities, as higher-order capabilities (Cepeda and Vera, 2007; Collis, 1994; Teece, 2023; Winter, 2003), support the internal development of necessary competences (Gulbrandsen et al., 2017), thereby enabling unconventional managerial decision-making to play a greater role. In the higher education sector, institutions have been increasingly challenged for their capacity to respond to technological advancements, rapid commercialization, and social change (Bejinaru, 2017). The application of dynamic capabilities to higher education institutions is thus primarily reflected in their responsibility to function as innovative ecosystems that create value for society (Faccin et al., 2022). Dynamic capabilities are closely linked to innovation capacities in higher education (Akram and Hilman, 2017), and this theoretical lens offers a structural approach for strategic management within such institutions (Teece, 2018). It also assists in analyzing institutional activities in complex contexts (Heaton et al., 2019), with the aim of maximizing internal knowledge flow (Heaton et al., 2019; Kelleher and Ulrichsen, 2023).
2.2 Team dynamic capability
In knowledge-intensive domains, dynamic capabilities are essentially the development of knowledge-based dynamic capabilities (Kaur, 2019). Logically, dynamic capabilities are founded on all human-related factors, including skills, shared practical knowledge, and knowledge that facilitates purposeful action, indicating that knowledge creation serves as the operational pathway through which dynamic capabilities are actualized (Eisenhardt and Martin, 2000). Through knowledge creation, teams are able to establish new routines (Dong et al., 2004; Li and Chen, 2024). However, current research has primarily emphasized the “adaptive” dimension of dynamic capabilities—namely, the rapid reconfiguration of existing knowledge to respond to environmental changes. Much of this scholarship focuses on how teams develop dynamic capabilities to enhance firm performance, such as team learning capabilities (Harvey et al., 2018) and team R&D capabilities (Wang and Luo, 2013), or capabilities related to resource absorption, integration, decision optimization, and trust-based communication (Zhang et al., 2017). In contrast, relatively limited attention has been given to the “creative” dimension of dynamic capabilities—namely, the capacity to generate new knowledge and respond to complex environments.
High-quality collaboration for problem-solving requires the sharing of resources and skills among team members (Mola et al., 2020), enabling problem resolution through processes that foster knowledge renewal and collaboration. Ambrosini and Bowman (2009) argued that dynamic capabilities emerge from the co-evolution of tacit experiential accumulation and the articulation and codification of explicit knowledge activities. From the perspective of internal organizational concretization processes (Eisenhardt and Martin, 2000), creative dynamic capabilities are rooted in meso-level team activities within organizations—that is, in the interactions among team members (Nonaka et al., 2016). Nonaka et al. (2016) proposed a complementary approach integrating the SECI model (socialization, externalization, combination, internalization) with the dynamic capabilities framework, emphasizing that the knowledge creation process serves as the operational pathway of team dynamic capabilities. In other words, the knowledge creation process forms the foundation of team dynamic capabilities. Given the significant role of knowledge sharing in enhancing team effectiveness (Alsharo et al., 2017; Kim et al., 2023; Lin and Huang, 2020), dynamic knowledge creation is likely to constitute a form of team dynamic capability. That is, when team members possess complementary expertise and have mutual awareness of one another’s knowledge and tasks, teams are more capable of dynamic functioning (Salvato and Vassolo, 2018), thereby enabling the realization of the true value of team collaboration (Thayer et al., 2018).
Previous literature has largely acknowledged that the knowledge evolution phase of dynamic capabilities emphasizes both cognitive and behavioral foundations simultaneously (Dong et al., 2004; Nonaka et al., 2000). The evolutionary process of knowledge-based dynamic capabilities is characterized by a cyclical progression through four stages—variation, internal selection, retention, and propagation—indicating that cognitive efforts and behavioral efforts occur concurrently (Dong et al., 2004). Leadership, as a behavioral foundation of dynamic capabilities (Gheitarani et al., 2023), was integrated early on into the dynamic knowledge creation process through the unified model of SECI, Ba, and leadership (Nonaka et al., 2000). Similarly, the integrated model of knowledge-based dynamic capabilities (Nonaka et al., 2016) presents a unified process encompassing both cognitive and behavioral bases.
However, the value and impact of dynamic capabilities at the team level remain ambiguous and contested (Schilke, 2014). Wilden et al. (2016) argued that the research on dynamic capabilities should shift from the question of whether they influence performance to how they do so. Existing literature confirms that the mechanism through which dynamic capabilities lead to performance outcomes remains an unresolved issue in empirical research (Eriksson, 2014; Zhou et al., 2019). In other words, the “how” question has yet to be fully addressed (Wenzel et al., 2021). In light of this, recent research has begun to explore the indirect effects of dynamic capabilities (Baía and Ferreira, 2019; Laaksonen and Peltoniemi, 2018).
As previously noted, the dynamic knowledge creation process (SECI) inherently encompasses both cognitive and behavioral effort components. However, as Nonaka and Takeuchi (2021) emphasized, while knowledge creation enables teams to acquire new insights, it does not necessarily endow them with the wisdom to apply that knowledge effectively. The true value of knowledge must be realized through “knowledge practice.” According to Duchek (2020), resilience depends on the interplay between cognitive and behavioral capabilities and concrete actions. Building on the Knowledge-to-Action (KTA) Framework proposed by Graham et al. (2006), it is argued that following knowledge creation, teams members must apply, utilize, and translate knowledge into action in order to achieve resilience.
2.3 Team resilience
Teams are essentially goal-oriented entities, and team resilience is recognized as the team’s ability to handle problems and overcome obstacles (Alliger et al., 2015; Lengnick-Hall et al., 2011). This capability enables teams to proactively adjust their course of action to successfully execute specific tasks, thereby enhancing reliability, sustainability, and overall performance (Hartwig et al., 2020; Marchese et al., 2018; Specking et al., 2019). Theoretically, resilient teams are capable of rapidly identifying, designing, and implementing change while avoiding new obstacles that may impair team effectiveness beyond their current capabilities (Hoffman and Hancock, 2017). Given that interpersonal relationships form the foundation of resilience (Luthar, 2015), team resilience has been described as an emergent state arising from shared beliefs among team members (Kennedy et al., 2016), a collective outcome (Morgan et al., 2017), and a team goal cultivated through a shared vision, mutually agreed-upon “team charter,” and regular reinforcement (Morgan et al., 2019). On this basis, scholars have called for exploring team resilience through a consensus-based perspective that emphasizes emergence from team member interactions (Chapman et al., 2020; Raetze et al., 2021). This interpretation aligns with prior research that uses individual-level data to study collective phenomena when aggregation is not feasible.
Given its inherently social nature, a major research direction in team resilience focuses on team resources and interaction processes. For instance, team efficacy and collaboration (Strode et al., 2022), team personality (Mitchell et al., 2025), emotional and behavioral integration (Chen and Zhang, 2021; Hartmann et al., 2021), and the dynamic management of knowledge differences (Liu et al., 2023) have all been identified as factors that can foster team resilience (Liu and Harms, 2025). These research trends align with the recommendation in the dynamic capabilities literature to integrate organizational theories (e.g., resilience) and systems thinking to explore the development and functioning of dynamic capabilities in broader contexts (Arndt, 2019). From a knowledge management perspective, previous studies have demonstrated a significant positive correlation between knowledge management and resilience (Ibrahim Ismael et al., 2021; Singh et al., 2025; Yao et al., 2025). Particularly in certain professional environments, maintaining resilience at one level may require transformative change at another. In this sense, resilience is largely about organizational members learning how to change in order not to be changed (Walker, 2020), especially given the critical importance of knowledge integration within higher education institutions (Zahra et al., 2020).
2.4 Communicative
Communication encompasses all processes by which one person’s perspective influences another’s; it is a social behavior used to share attitudes, viewpoints, information, knowledge, and opinions (Shannon and Weaver, 1949). In organizational management, communication refers to the comprehensive process of sending, receiving, and exchanging multi-level and multi-content information among organizational members. It serves as the foundation for information transmission between individuals, institutions, and organizations, reflecting the processes of organizational design, management, and implementation. Therefore, it is critical to planning and decision-making (Khan et al., 2017). Particularly in the context of strategic change, communication plays a key role in how organizations deliberately use it to fulfill their overall mission (Frandsen and Johansen, 2017; Hallahan et al., 2007).
In knowledge management, the acquisition, transfer, and utilization of knowledge constitute the systemic flow of knowledge resources (Drucker, 1988). Communication is therefore regarded as one of the integral components of the dynamic knowledge evolution process, as exemplified in the SECI model (Nonaka et al., 1996). In this process, communication primarily functions to establish new routines for knowledge through widespread dissemination within the organization. Based on team collaboration (Gervits et al., 2016), communicative emphasizes collaboration among team members grounded in communication to facilitate knowledge creation. For instance, task-oriented, process-oriented, and socio-emotional-oriented communication allow team members to alternately focus on task demands, coordination issues, and interpersonal relationships, respectively (Stempfle and Badke-Schaub, 2002). Although these three types of communication differ significantly in their effectiveness for problem solving (Stempfle and Badke-Schaub, 2002), open communication channels within teams can still foster shared understanding through dialogic interaction (Clark and Schaefer, 1989).
However, as new knowledge accumulates into knowledge assets, its practical application often encounters common obstacles. Team members’ limited understanding of newly generated knowledge may hinder its enactment. In other words, the transition from knowledge creation to implementation is inherently a socialized process dependent on relational interactions; thus, dissemination and communication are essential for translating knowledge into action (Gagnon, 2011). According to sensemaking theory (Weick, 1995), sensemaking is viewed as a set of mechanisms that organizations typically use to define norms and rules for perceiving, interpreting, trusting, and acting (Sackmann, 1991). Communicative functions as one such behavioral mechanism, aiming to facilitate strategic information exchange among team members and serve as a foundation for decision-making processes.
2.5 Leadership
Leadership is characterized as an influential relationship among [people] aimed at achieving genuine transformation that reflects shared goals (Rost, 1993). It is regarded as a collective phenomenon shared among employees (Denis et al., 2012; Lord et al., 2017; Will, 2016; Yammarino et al., 2012) and a social phenomenon (Mumford et al., 2012), indicating that the focus of leadership development has shifted from individuals to the cultivation of relationships, teams, networks, and organizations (Day, 2000; Stogdill and Shartle, 1948). In other words, leadership is founded on social capital, transitioning from leader competencies to dialogic relationships (Eva et al., 2021). Simply put, leadership is not about a single individual or a position; rather, it represents a complex moral relationship between individuals, founded on trust, obligation, commitment, emotions, and a shared noble vision (Ciulla, 2004). It is an emergent attribute of interactions aimed at collective outcomes (Denis et al., 2012).
Nonaka and Toyama (2002) emphasize that the integrative function of leadership lies in “creating a knowledge vision, managing the knowledge-creation space, maintaining creative routines, and building an incentive system.” In other words, effective knowledge creation requires a pragmatic and dialogical form of leadership (Nonaka and Toyama, 2007). Leadership research has linked specific management styles to successful knowledge management (Lakshman, 2009). For example, empowering leadership is positively associated with knowledge management practices (Singh, 2008; Türkmendağ and Tuna, 2022), and transformational, transactional, knowledge-oriented, and strategic leadership styles have all been found to exert sustained and positive influences on knowledge management processes (Al Amiri et al., 2020). At the team level, distributed leadership is also recognized as a vital source of dynamic creativity (Nonaka et al., 2016). Some studies specifically highlight the critical role of leadership in knowledge management activities and processes—for instance, Von Krogh et al. (2012) integrated concepts such as Ba (knowledge-creating context), the SECI model, knowledge assets, and leadership behaviors to develop a knowledge-creating situational leadership framework (Nonaka and Konno, 1998; Nonaka et al., 1996), as well as the unified model of dynamic knowledge creation proposed by Nonaka et al. (2000).
In certain transformational environments, teams are primarily oriented toward problem-solving capabilities. Sternberg et al. (2021) suggest that employing the “meta-intelligence” model enables flexibility in generating problem-solving strategies. For instance, leaders may first use their creative skills to generate novel and high-quality solutions; second, they apply analytical skills to evaluate the logical coherence and feasibility of the proposed solutions; and third, they utilize wisdom-based skills to ensure that solutions contribute to the common good (Sternberg, 1998; Sternberg, 2003a; Sternberg, 2019; Sternberg, 2020). Therefore, leadership should influence the generation, sharing, and application of knowledge (Mac Gillivray, 2018). From a knowledge-practice perspective, effective leadership plays a critical role in decision-making by developing and integrating three core skills—wisdom, intelligence, and creativity (WICS) (Sternberg, 2003b). For example, knowledge-based leadership has been shown to encourage the development and application of knowledge practices (Donate and de Pablo, 2015). Given the practical challenges in knowledge management (Ding et al., 2019) and the value of dynamic capabilities as a basis for innovation in strategic planning (Nonaka et al., 2016), wise leadership consistently aims to guide team members toward decisions that benefit the collective (Nonaka and Takeuchi, 2011). Leaders who possess practical wisdom can optimistically enhance a team’s dynamic capabilities (Nonaka et al., 2016). Therefore, wise leadership teams may actively contribute to fostering environments conducive to knowledge sharing, encouraging member participation, and enhancing team spirit, thereby improving the efficiency of knowledge practices (Ding et al., 2019).
2.6 Interpretation
The response of a team to problems is partly based on how these issues are understood and interpreted (Ashmos et al., 1998; Burke et al., 2018; Dutton and Jackson, 1987; Gagné, 2018; Hitt and Tyler, 1991; Schneider and De Meyer, 1991; Thomas et al., 1993; Thomas and McDaniel, 1990; Von Krogh, 2018). Interpretation is an expression of collective thought (Weick and Roberts, 1993), the team needs to develop a shared processing mechanism to interpret events (Walsh and Ungson, 1991).
In strategic management, information is utilized to interpret environmental changes, generate new knowledge, and inform decision-making on courses of action. These processes involve interwoven behaviors that contribute to the organization’s deep interpretation of information (Choo, 1996). Prior studies have examined how decision-makers interpret strategic events through the lens of strategic issue diagnosis (SID) (Dutton et al., 1983). The SID framework emphasizes the need to construct understanding and assign meaning to an issue before linking it with potential solutions, thereby helping decision-makers avoid the “blindness” effect in strategic sensemaking (Dutton et al., 1983). Generally, interpretation is defined as an organization’s ability to make sense of its environment in multidimensional ways, especially under conditions of strategic complexity (Neill et al., 2007). This involves constructing cognitive frames to encode environmental cues and assign meaning to them for situational understanding. In a team context, interpretation focuses on how team members use the information and knowledge they possess to influence others (Thomas and McDaniel, 1990) and shape decision rationales. When new knowledge encounters barriers, teams may need to engage in reconstructive interpretation (Franke, 2023) and adopt an interpretive turn (Nicklin, 2012) to explore dynamic and decentralized frameworks for knowledge practice. This requires attention to how purposeful interpretive spaces are created (Liedtka, 2000), and how such interpretations either facilitate or inhibit collective team action within the broader knowledge system.
2.7 Analytical
Analytical is defined as “judgment based on psychological reasoning” (Allinson and Hayes, 1996) and refers to a rational, thoughtful, and conscious judgment (Epstein et al., 1996). It represents the extent to which data, facts, and logical reasoning are relied upon when addressing problems, wise decision making, or conducting evaluations (Wang et al., 2017). In the context of knowledge creation, team members primarily integrate diverse forms of both tacit and explicit knowledge to generate innovative ideas (Olaisen and Revang, 2018; Von Krogh et al., 2000). The analytical mode of knowledge creation refers to the understanding and interpretation of characteristics of the (natural) world (Moodysson et al., 2008). Previous research has shown that predictive analytics can influence knowledge creation in marketing (Hair, 2007). The decision-making process itself enhances the understanding of both the issue at hand and the processes involved. In other words, decision-making and knowledge creation are interdependent processes.
However, team members primarily apply new knowledge for problem-solving purposes. Previous research suggests that many problem-solving approaches are analytically driven and supported (Hoerl and Vining, 2021). Analytical capability, as a core component of the metacognitive approach to problem-solving (Sternberg et al., 2021), can be examined through the WICS framework (wisdom-intelligence-creativity-synthesized) (Sternberg, 2003a; Sternberg, 2019), which emphasizes the interaction among creative, analytical, and practical mechanisms in shaping a team’s ability to solve problems effectively. In particular, multi-perspective analysis reflects the team’s sensemaking capacity, requiring the ability to integrate diverse viewpoints, perform cognitive blending in decision-making processes, and transform problem identification into deep understanding (Neill et al., 2007). From this perspective, broad and diverse new knowledge indeed supports sustainable action processes and capacity building within teams (Caniglia et al., 2021).
2.8 Research gaps and positioning
As noted earlier, the dynamic knowledge creation process (SECI) already involves both cognitive and behavioral efforts. However, following Wilden et al. (2016), we argue that the research focus on dynamic capability literature should shift from whether it affects performance to how it does so. Our position is that existing literature has not fully answered the “how” question (Wenzel et al., 2021). Although prior research has addressed the “adaptive” dimension of dynamic capability, few have examined its “creative” dimension and subsequent knowledge enactment. As noted by Nonaka and Takeuchi (2021), knowledge only realizes its true value when it is enacted through purposeful practice. Based on the above-identified research gaps, the novelty of this study lies in drawing on the concept of Knowledge-to-Action (KTA) to explain how team dynamic capability contributes to team resilience.
In this paper, the theoretical foundation of the mediating mechanisms is rooted in sensemaking theory, particularly the three core dimensions widely recognized in organizational literature—communicative, interpretation, and analytical (Weick, 1995; Neill et al., 2007). These constructs have often been studied as dimensions of sensemaking capability. Building on this foundation, we intentionally disaggregate these three dimensions to examine their individual mediating roles. Moreover, we introduce wise leadership (Nonaka et al., 2016)—a construct closely linked to knowledge creation—as an additional and interrelated mediator. This combination forms a set of related yet distinct mediating mechanisms, which reflects a new theoretical perspective: it explains how team dynamic capability contributes to team resilience through the functional integration of sensemaking and knowledge activation processes. However, these four constructs are not dimensions of team dynamic capability, Instead, they are functional enabling mechanisms that emerge following the team’s dynamic knowledge creation process. In other words, the newly created knowledge enabled by dynamic capability requires knowledge enactment—through communicative, leadership, interpretation, and analytical—in order to generate value and inform resilient decision-making.
2.9 Hypothesis development and theoretical framework
2.9.1 Team dynamic capability and communicative
In environments characterized by change and innovation, collaboration and dynamic capability are often integrated as fundamental conditions for organizations. This implies that all participants need to contribute resources and expertise as complementary assets and capabilities to jointly bear costs and risks for a common goal (Dodgson, 2014). The creativity of dynamic capability arises from team-level interactions among members (Nonaka et al., 2016). Once new knowledge is created, team members must determine which knowledge to apply based on the specific contextual environment. This process inevitably requires information exchange to clarify each other’s capabilities and intentions in order to formulate strategies and plan tasks. Strategic communication, in particular, involves members purposefully engaging in dialogs that are meaningful to their collective objectives, playing a unique role throughout the processes of strategy formulation, revision, articulation, execution, implementation, and operation (Zerfass et al., 2020). Teams construct meaning for newly generated knowledge through communication, enabling members to build shared understanding (Hallahan et al., 2007) and reach decisions that satisfy multiple stakeholders. Thus, newly created knowledge within teams facilitates strategic information exchange among members. Therefore, this paper proposed that.
H1: Team dynamic capability positively affects communicative.
2.9.2 Team dynamic capability and leadership
Team dynamic capability primarily aims to build team efficiency in order to generate team performance. As a component of team collaboration quality, the knowledge creation process represents a “creative” form of team dynamic capability and constitutes the innovative value underlying organizational development planning (Nonaka et al., 2016). It requires leadership that integrates “pragmatism and dialog,” such as articulating a knowledge vision, managing “Ba” (shared spaces), maintaining innovation trajectories, and establishing incentive systems (Nonaka and Takeuchi, 2007). Therefore, it can be regarded as a facilitating condition for the enactment of team leadership functions (Bradshaw et al., 2015). Since the knowledge creation process is grounded in interpersonal interaction and engagement among team members, this team-rooted interaction pattern helps foster pragmatic and wise leadership (Nonaka et al., 2016). Conversely, wise leadership characterized by a “middle-up-down” approach allows team members to sense changes, seize opportunities, and enhance their management awareness. It cultivates a collective consciousness of participatory governance, in which every member perceives themselves as contributing to team management (Adler and Hiromoto, 2012), thereby providing momentum for knowledge enactment. Therefore, this paper proposed that.
H2: Team dynamic capability positively affects leadership.
2.9.3 Team dynamic capability and interpretation
As a team dynamic capability, the output of knowledge creation is the generation of rich new ideas, representing the realization of novel concepts (Nonaka et al., 1994). However, whether newly created knowledge can be effectively applied to the environment depends on the team’s ability to interpret external complexity, thereby enhancing the alignment between new knowledge and environmental demands. This interpretive process occurs within the shared context of “Ba” established by the team (Nonaka et al., 2001). The “Ba” can be understood both as a supportive environment and as an interpretive tool (Al-Mansour and Obembe, 2021). The energy generated within “Ba”—namely, the team members’ interpretation—can significantly enhance its effectiveness. In other words, the practical application of new knowledge requires active interaction among participants within various forms of “Ba,” guided by the team’s shared vision. The interaction and communication processes that take place in this shared environment constitute both interpretive and integrative mechanisms of information and knowledge. Learning and sharing activities help strengthen team members’ absorptive capacity, beliefs, and values, which in turn facilitate the interpretation of information (Abbas et al., 2020). Put differently, the practice of newly created knowledge allows team members to recognize how the team’s interpretive function contributes to overall team performance. Therefore, this paper proposed that.
H3: Team dynamic capability positively affects interpretation.
2.9.4 Team dynamic capability and analytical
The knowledge creation process is a systematized management activity that requires deliberate facilitation. When conceptualized as a team dynamic capability, knowledge creation implies that the new knowledge generated is rich in data and information, serving as essential input for analytical processes. Analytical is inherently a multiple perspective consideration (Neill et al., 2007), requiring team members to engage in diverse viewpoints when evaluating the application of new knowledge. The goal is to generate more contextualized insights and integrate them into coherent solutions, which plays a critical role in team-based problem solving (Srivastava et al., 2006; Zimmermann et al., 2021). Moreover, analytical within teams is often conducted through multiple-criteria decision-making processes, wherein team members evaluate alternative courses of action based on various competing priorities (Belton and Stewart, 2012). In this regard, newly created knowledge can promote rational, integrative thinking among team members, enabling more effective and structured decision-making processes in response to complex problems. Therefore, this paper proposed that.
H4: Team dynamic capability positively affects analytical.
2.9.5 Communicative and team resilience
Previous research has shown that team communicative actions can legitimize new knowledge, learning, and practices (Del Corso et al., 2015). From a problem-solving perspective, team communication behaviors enhance resilience by leveraging new knowledge to explore problem domains (Vos, 2017) and by facilitating communication-centered coordination (Doerfel et al., 2022). Team resilience largely depends on the existence and quality of interpersonal relationships (Carmeli et al., 2021). High-quality connections (HQCs) are generative and vital (Aarrestad et al., 2015) and are particularly valuable for resilience (Stephens et al., 2013), serving as an important resource for the formation of team resilience capabilities (Carmeli et al., 2013; Stephens et al., 2013). That is, team members who engage in proactive and communicative interactions can cultivate a high-quality communicative atmosphere. This active relational process can facilitate (or hinder) information sharing, learning processes, and the development of adaptive problem-solving solutions (Paulus and Nijstad, 2003). If members perceive that their team relationships contribute to generating new ideas and identifying new opportunities, they tend to be more resilient (Carmeli et al., 2013). However, since the strength of relationships among team members is measured by the duration or length of the relationship and the frequency of communication (Granovetter, 1973). Normative communication patterns, such as transparent team communication, can enhance trust among members and increase the value of members’ willingness to disclose information (Lee and Li, 2020). Through generating new ideas and establishing consistency within the team, team communication reflects its importance in shaping team resilience (Carmeli et al., 2013; Gomes et al., 2014). Based on the value of open and trusting team communication, a positive voice atmosphere has the potential to influence team resilience (Brykman and King, 2021). Therefore, this paper proposed that.
H5: Communicative positively affects team resilience.
2.9.6 Leadership and team resilience
Leaders play multifaceted roles in fostering resilience within organizations (McEwen, 2022), such as consistently demonstrating support for the team’s mission (Southwick et al., 2017). Literature has established that leadership (Bowers et al., 2017; Çop et al., 2021; Williams et al., 2017) is a key organizational factor influencing resilience and sustainability. Leaders can provide guidance and support to team members to effectively manage any disruptions (e.g., stress; Harms et al., 2017).
Leaders must guide the team in achieving its goals, encourage employee development, and instill a sense of participation and commitment (Lombardi et al., 2021). However, leaders must acquire practical wisdom or phronesis to enable team members to produce experiential knowledge that aligns with ethical standards (Nonaka and Takeuchi, 2011). Based on practical wisdom is vital for organizational resilience, effective communication, and societal well-being in complex governance (Awashreh and Hamid, 2024), it can be argued that teams characterized by wise leadership are more likely to enhance their resilience and strength. Therefore, this paper proposed that.
H6: Leadership positively affects team resilience.
2.9.7 Interpretation and team resilience
The ability to solve problems largely depends on whether team members can effectively utilize the knowledge resources available within the team (Lin et al., 2015). Team members perceive stimuli from the environment, categorize information into frameworks or update reference frameworks, communicate with one another, and then adopt the most favorable approach. This team process occurs through a simultaneous engagement of belief and skepticism regarding the interpretation of specific situations (Talat and Riaz, 2020).
From a sensemaking perspective, effective team management and coordination facilitate the interpretation of current situations (Klein et al., 2010), helping team members understand unexpected events or unforeseen stimuli they encounter (Maitlis and Christianson, 2014). As a sensemaking capability, interpretation also represents the extent to which teams absorb and understand external environmental conditions and information (Neill et al., 2007). It represents the team’s capacity to perceive environmental conditions and to form a collective understanding of external situations. Through this interpretive process, the absorption of information enables teams to identify a wider range of opportunities and to leverage knowledge more effectively, thereby gaining advantages that contribute to sustained resilience (Yuan et al., 2022). Therefore, this paper proposed that.
H7: Interpretation positively affects team resilience.
2.9.8 Analytical and team resilience
Information processing at the team level is, to varying degrees, thoughtful, effortful, and systematic (De Dreu and Beersma, 2010). Systematic information processing is typically characterized by open and thorough information exchange and the diligent integration of information (De Dreu, 2007). However, the complexity of problems encountered in many professional workplaces often exceeds the cognitive capacity of any single individual. Therefore, it is necessary for teams to develop shared knowledge (Bierhals et al., 2007) and build high-quality relationships among team members (Carmeli et al., 2021). These factors reflect a team’s collective problem-solving capacity (Hung, 2013), as evidenced by team’s analytical thinking, decision-making capability, root cause analysis, and reflective learning. Additionally, the degree of team cognition serves as the foundation for solving complex problems (Hung, 2013). As a psychological state that allows team members to anticipate and coordinate (Niler et al., 2021), diversity in team cognition can foster psychological safety within the team, thereby enhancing resilience (Paschertz, 2021). Therefore, this paper proposed that.
H8: Analytical positively affects team resilience.
2.9.9 Communicative as a mediator
Communication has long been regarded as a vital tool for team collaboration and coordination (Mintzberg, 1973) because it encourages information exchange and knowledge sharing (Dzamtoska-Zdravkovska and Haque, 2023; Malik et al., 2024). In team contexts, the outcomes of individual learning are often transmitted to other members through socio-psychological mechanisms such as communication, collaboration, and proactive information sharing (Carmeli et al., 2021). Communication is widely recognized as a crucial tool for problem-solving (Bodunde et al., 2024; Clark et al., 1994), as it facilitates deeper information processing, encourages the exchange of unique insights, and serves important socio-emotional functions within the team (Mesmer-Magnus and DeChurch, 2009). In particular, when team members maintain high-quality relationships and engage in high-quality communication, they are more likely to generate creative solutions to problems (Carmeli et al., 2021). This is because the strength of team connections depends on the collective knowledge, skills, and attitudes possessed by the team (Hartmann et al., 2020).
Research indicates that a key attribute of resilient teams is their respect for professional expertise (Alliger et al., 2015), which implies that resilient team members tend to rapidly exchange available information. In this regard, the dynamic capability of knowledge creation within teams facilitates the development of high-quality connections, thereby strengthening team resilience (Hartwig et al., 2020). Conversely, a lack of resilience hinders the establishment of high-quality connections and undermines the creation of a constructive communicative climate (Brykman and King, 2021). Taken together, the connectivity among team members may serve as a critical mechanism that enables teams to identify opportunities amid challenges and generate novel insights, thus enhancing team resilience and making the team more resourceful (Carmeli et al., 2013). Therefore, this paper proposed that.
H9: Communicative mediates the relationship between team dynamic capability and team resilience.
2.9.10 Leadership as a mediator
Previous literature has widely acknowledged that leaders play a pivotal role in the evolution of dynamic capabilities within organizations (Salvato, 2003), serving as microfoundations of such capabilities (Burton and Dickinger, 2025). The dynamic capability of knowledge creation emphasizes a condition in which participants engage in spontaneous collaboration and shift between roles of leadership and followership (Von Krogh et al., 2012), suggesting that leadership is distributed among team members. It is viewed as a collective attribute and a set of functions that the team must collectively fulfill (Gibb, 1954). This implies that, in the practice of knowledge, team members are expected to jointly assume leadership roles.
At the same time, the development of wise leadership is grounded in knowledge (Hassi and Storti, 2023), whereby new knowledge must be contextualized and integrated with real-world situations to generate team wisdom. This entails making judgments and taking actions in the process of applying knowledge and fostering a reflective and dialogical environment to cultivate practical wisdom. As one of the critical antecedents of team resilience (Hartwig et al., 2020), wise leadership may thus serve as an important mediating mechanism between dynamic capability and team resilience. Therefore, this paper proposed that.
H10: Leadership mediates the relationship between team dynamic capability and team resilience.
2.9.11 Interpretation as a mediator
Interpretation is a meaning-making ability that teams employ to handle complexity (Neill et al., 2007). Within the dynamic capabilities framework, team members must be adept at identifying and evaluating internal and external informational cues in order to translate knowledge into coherent action. The purpose of interpretation is to enhance the team’s decision-making quality. However, possessing new knowledge does not necessarily guarantee better decision outcomes (Stoverink et al., 2020). Team members often differ significantly in terms of roles, responsibilities, experience, and expertise, and there is frequently information asymmetry, with each individual holding distinct and unevenly distributed knowledge.
New knowledge is interpreted by team members based on their unique experiences and perspectives, a process that can result in multiple, and sometimes conflicting, interpretations. To form an accurate situational assessment, teams engage in sensemaking through the contributions of those with the most relevant expertise and practical experience (Butchibabu et al., 2016). ultimately guiding collective decisions. Research indicates that risk interpretations formed through the decoding of risk-related knowledge can enhance resilience regardless of environmental fluctuations (Odiase et al., 2020). Interpretation, as a dynamic team function, enables the transformation of individual cognition into organized responses, playing a crucial role in resilience under pressure. Therefore, this paper proposed that.
H11: Interpretation mediates the relationship between team dynamic capability and team resilience.
2.9.12 Analytical as a mediator
Achieving team performance and effectively leveraging newly created internal knowledge through knowledge sharing and renewal is inherently a complex task, which requires a certain degree of decision-making capacity (Abubakar et al., 2019). Analytical is not only a rational and structured mode of information processing but also represents a multi-perspective approach to thinking (Neill et al., 2007), in sharp contrast to intuition-based judgment. It enables teams to critically evaluate knowledge, integrate diverse viewpoints, weigh multiple options, and make reasoned decisions—capabilities that are essential for navigating dynamic environments.
The knowledge creation process in teams typically involves integrating different perspectives through social interaction. This process not only enriches the team’s cognitive resources but also fosters analytical capability by encouraging systematic reasoning and reflective learning. When teams are able to understand problems from multiple angles, they can deepen their decision-making processes, thereby improving decision quality (Pacini and Epstein, 1999) and enhancing overall performance (Kaufmann et al., 2014; Smolka et al., 2018; Zhu et al., 2021). In environments characterized by constant change and uncertainty, external pressures significantly increase the complexity of decision-making. Teams must not only react swiftly but also respond wisely. As the decision-making process is closely linked to resilience (Mishra et al., 2015; Son et al., 2020), analytically grounded decisions are more likely to influence and enhance team resilience (Agassian, 2021). Therefore, this paper proposed that.
H12: Analytical mediates the relationship between team dynamic capability and team resilience.
In summary, this study conceptualizes the mediating mechanisms as functionally enabling mechanisms that emerge following the team’s dynamic knowledge creation process. These mechanisms are supported by team dynamic capabilities and serve as intermediaries between team dynamic capability and team resilience. Based on the development of the hypotheses, the conceptual model is constructed as shown in Figure 1.
Figure 1. Conceptual model illustrating the mediating role of team competencies between dynamic capabilities and team resilience. Conceptual model illustrating how team dynamic capabilities influence team resilience through four functionally enabling mechanisms—communicative, leadership, interpretation, and analytical—collectively referred to as knowledge enactment.
3 Methods
Data collection was conducted primarily through an online survey (Tuten et al., 2002), which was designed in electronic format and distributed to participants via a hyperlink or QR code. Faculty and staff members from 64 public higher education institutions (e.g., academic or administrative professionals—given that Chinese public universities commonly adopt a dual-role system in which administrative staff also serve as academic personnel) were invited to complete the questionnaire. The survey was distributed across Guangxi Province through educational networks, allowing responses from a broad and diverse of public higher education institutions. Previous research has suggested that team resilience can be viewed as an isomorphic representation of individual resilience (West et al., 2009), as individuals within a team are typically directly or indirectly involved in all team-related activities. Accordingly, organizational or team-level resilience may be understood from the standpoint of employees, in a manner consistent with the transformational perspective (Kim, 2020). After distribution, collection, and screening in China, a valid sample size of 617 responses was obtained.
To operationalize the variables, a structured questionnaire was designed following a literature review and discussions on the variables. Team dynamic capability was conceptualized as a higher-order construct grounded in the SECI model, and measured using the KMSP-Q scale developed by Farnese et al. (2019). The scale comprises three dimensions—Socialization, Externalization and Combination, and Internalization—captured through 30 items. A second-order Confirmatory Factor Analysis (CFA) was conducted to empirically test the hierarchical structure of TDC, and results confirmed that all three dimensions significantly loaded onto the higher-order latent construct. However, to enhance model parsimony and ensure consistency with prior studies adopting the SECI framework (e.g., Nonaka et al., 2016), only the first-order CFA results were presented in the main analysis.
Team resilience was measured with 3 items adapted from Stephens et al. (2013). Communicative was measured with 4 items adapted from Akgün et al. (2014). Leadership was assessed using 6 items derived from Nonaka et al. (2016), as well as Ding et al. (2019). Interpretation was measured with 5 items adapted from Neill et al. (2007), while analytical was measured with 7 items adapted from Akgün et al. (2014). In total, the questionnaire consisted of 59 items, all assessed on a five-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree).
Since the variable data from the scales in this study were derived from the same source of subjects, there may be an issue of common method bias (CMB). Therefore, two statistical control methods were employed to test for common method variance (CMV). First, Harman’s single-factor test was conducted to determine whether common variance was significant. This test involved factor analysis of all items the scale; if the variance explained by the first unrotated factor was less than 40% (Tang and Wen, 2020), it would indicate that common method bias was not severe. Second, this study further employed the effects of an unmeasured latent methods factor (ULMC) to test for CMV. In confirmatory factor analysis (CFA), the six-factor model of the core study served as the baseline model, incorporating the single method as a latent variable that was uncorrelated with the other factors in the six-factor model, allowing all test items to load on this latent variable. Finally, the differences in fit indices between the two models were compared. If the RMSEA and SRMR decreased by no more than 0.05, and the CFI and TLI increased by no more than 0.10, the model including the common factor would not show significant improvement over the model without the common factor, indicating that there was no serious issue of common method bias (Zhou and Long, 2004).
In terms of reliability, utilized the internal consistency coefficient method (Cronbach’s α > 0.70) and the split-half reliability coefficient (Spearman-Brown method) for reliability analysis. A split-half reliability coefficient exceeding 0.80 indicates good reliability (Wu, 2010). Validity analysis was primarily conducted via SPSS AMOS to construct a confirmatory measurement model to examine its convergent validity, discriminant validity, and construct validity (average variance extracted (AVE) exceeded 0.50), and composite reliability (CR) was greater than 0.70.
For hypothesis testing, a structural equation model (SEM) was constructed via SPSS AMOS to analyze the path relationships and assess the direct effects of team dynamic capability on communicative, leadership, interpretation, and analytical. The direct effects of communicative, leadership, interpretation, and analytical on team resilience, as well as the indirect effects of team dynamic capability on team resilience, were subsequently evaluated after the variables of communicative, leadership, interpretation, and analytical. The mediating effect was tested via the Sobel product coefficient method and the bootstrap method. The Sobel product coefficient method indicates the presence of a mediating effect if the Z value (absolute value) of the mediating effect is>1.96. The bootstrap sampling method (Hayes, 2009) was employed with both the percentile method and the bias-corrected percentile method to establish a 95% confidence interval. If the 95% confidence interval does not include 0 and p < 0.05, the indirect effect is significant, and the mediating effect is significant.
4 Results
A frequency analysis of the 617 valid sample responses revealed that there were 317 females (51.4%) and 300 males (48.6%). The sample population was predominantly aged centered between 31 and 40 age years (66.30%), with the highest number of qualifications holding a master’s degree (65.60%), followed by those with a doctoral degree (22.70%). This distribution reflects the common educational profile of professionals engaged in academic and administrative roles within public universities in China, where a master’s degree is typically the baseline qualification. Most participants had between 6 and 15 years of working experience (60.00%).
4.1 Common method variance
To Exploratory factor analysis of the scale variables revealed 8 factors with eigenvalues greater than1. The variance explained by the first unrotated factor was 32.815%, which is below the 40% threshold, indicating that there is no severe common method bias in the data of this study. After adding the common method latent factor, CMIN (x2) decreased by 44.092, degrees of freedom (df) decreased by 28, and CMIN/df (x2/df) decreased by 0.033. The RMSEA and SRMR values decreased by 0.002 and 0.003, respectively, whereas the CFI and TLI values increased by 0.002 and 0.001, respectively. The model fit did not change significantly, indicating that the CMV in this study’s data is not severe.
4.2 Reliability and validity analysis
4.2.1 Reliability
The reliability results of the scales are shown in Table 1. All the concepts demonstrated reliability coefficients within the acceptable range, indicating good scale reliability.
Table 1. Results of reliability.
4.2.2 Validity
The convergent validity and composite reliability results for the overall scale variables are shown in Table 2. The AVE values for the 6 variables ranged between 0.557 to 0.813 (greater than0.5), and the standardized factor loadings for all the items were exceeded 0.50, indicating good convergent validity for each subscale. The composite reliability (CR) values for all subscales greater than 0.70, and the squared multiple correlations (SMC) for items all above 0.33, demonstrating good structural reliability.
Table 2. Results of convergent validity and composite reliability.
The discriminant validity results for each scale are shown in Table 3. The AVE values for the six concepts ranged from 0.746 to 0.902, and the correlation coefficients among the concepts ranged from 0.333 to 0.579. The AVE values for each variable were greater than their corresponding correlation coefficients, indicating good discriminant validity among the six concepts. Therefore, the discriminant validity of the overall scale has been confirmed.
Table 3. Discriminant validity of the constructs.
4.3 Hypothesis testing
A six-factor model was constructed to analyze the overall construct validity of the different variables. The structural equation paths are shown in Figure 2.
Figure 2. Structural model showing the standardized path coefficients among variables.
Among the results of the path model fit indices, the RMSEA value was 0.031 and the SRMR value was 0.057, both of which are below 0.08. For the parsimonious fit index, the CMIN/DF value was 1.590, within the acceptable range of 1 to 3. With respect to the incremental fit indices, the IFI, TLI, and CFI values were all above 0.9. All fit indices were within acceptable ranges, indicating that the path model fit was acceptable.
The results of the path effects are shown in Table 4. Specifically, the independent variable team dynamic capability (TDC) had affected on communicative (CM) (β = 0.620, p < 0.001), therefore, Hypothesis H1 is supported. Team dynamic capability also affects leadership (LD) (β = 0.575, p < 0.001), therefore, hypothesis H2 is supported. Similarly, team dynamic capability (TDC) affects interpretation (IN) (β = 0.582, p < 0.001), hypothesis H3 is supported, and team dynamic capability (TDC) affects analytical (AN) (β = 0.489, p < 0.001), hypothesis H4 is supported.
Table 4. Structural model showing the standardized path coefficients among variables.
Furthermore, communicative (CM) affected on team resilience (TR) (β = 0.133, p = 0.003), and hypothesis H5 was supported. Leadership (LD) affected team resilience (TR) (β = 0.191, p < 0.001), and hypothesis H6 is supported. Interpretation (IN) affected team resilience (TR) (β = 0.188, p < 0.001), hypothesis H7 was supported, and analytical (AN) affected team resilience (TR) (β = 0.344, p < 0.001); thus, hypothesis H8 was supported.
According to the path results, the independent variable of team dynamic capability (TDC) has a significant positive effect on the dependent variable of team resilience (TR) (β = 0.183, p = 0.009). To further investigate whether the four variables communicative (CM), leadership (LD), interpretation (IN), and analytical (AN) play indirect roles in the relationship between team dynamic capability and team resilience, each of these 4 variables was tested as a mediator to examine the mediating effects as shown in Table 5.
Table 5. Mediating effects of team dynamic between team dynamic capabilities and team resilience.
For the results of the mediating effect of communicative, the indirect effect value was 0.082, the significance level Sig (p) was 0.020, which is less than 0.05, and the Z score from the Sobel test was 2.343, which is greater than 1.96. These results indicate that the mediating effect of communicative is significant. Thus, hypothesis H9 is supported. For the results of the mediating effect of leadership, the indirect effect value was 0.110, the significance level Sig (p) was less than 0.001, and the Z score from the Sobel test was 3.793, which is greater than 1.96. These results indicate that the mediating effect of leadership is significant. Thus, hypothesis H10 is supported. For the results of the mediating effect of interpretation, the indirect effect value was 0.109, the significance level Sig (p) was 0.001, which is less than 0.05, and the Z score from the Sobel test was 3.633, which is greater than 1.96. These results indicate that the mediating effect of interpretation is significant. Thus, hypothesis H11is supported. For the results of the mediating effect analytical, the indirect effect value was 0.168, the significance level Sig (p) was less than 0.001, and the Z score from the Sobel test was 6.720, which is greater than 1.96. These results indicate that the mediating effect of the analytical is significant. Thus, hypothesis H12 is supported.
5 Conclusions and discussion
Organizational adaptability and knowledge-driven innovation capability have become critical to the development of higher education institutions. Faced with complex reform tasks and strategic transformation goals, team dynamic capabilities—particularly in terms of cross-functional collaboration, knowledge integration, and adaptive decision-making—are of vital importance in universities. Investigating dynamic capabilities within university teams contributes to a deeper understanding of how local Chinese universities enhance team functioning to respond effectively to institutional reforms and resilience challenges under policy-driven contexts.
Previous research has primarily examined team resilience from the perspective of resource conservation, focusing on the accumulation and management of existing resources. This study shifts the focus to the dynamic capability mechanisms underlying team resilience, exploring how the knowledge creation process—considered a core element of team dynamic capability—influences resilience. Particular attention is given to the functional aspects of team dynamics. The findings reveal that communicative, leadership, interpretation, and analytical jointly form the dynamic functioning of teams, acting as partial mediators and significantly enhancing the practical value of knowledge within teams.
5.1 Theoretical implications
First, by focusing on the dynamic processes of teams, this study deepens the understanding of team resilience in the context of organizational change and clarifies theoretical boundaries by proposing a shift from a “resource-preservation” perspective to a “functional-evolution” perspective. As noted by Galy et al. (2023), Brykman and King (2021), since 2011, much of the literature has conceptualized resilience based on the Conservation of Resources (COR) theory (Hartmann et al., 2020; Hartwig et al., 2020; Hobfoll, 2011; Hobfoll et al., 2018; Stoverink et al., 2020; Westman, 2001), portraying resilience as a static attribute and a key mechanism for linking and protecting various resources through intersecting processes. This view primarily supports the restorative function of resilience. However, in relatively stable yet complex transformation contexts—often described as brittle, anxious, non-linear, and incomprehensible (BANI) systems (Cascio, 2020)—resilience increasingly entails the accumulation of resources, such as knowledge (Cascio, 2020), and is better understood as a dynamic function that supports sustainability and adaptive development in response to multifaceted challenges. Against this backdrop, the present study adopts a dynamic capability perspective, emphasizing how teams engage in sensing, seizing, and reconfiguring to proactively adapt to change. This reconceptualizes resilience as an evolutionary outcome rather than merely a restorative attribute, offering a novel theoretical lens for understanding team resilience.
Second, this study explores how resilience emerges through the interplay of multiple causal mechanisms by investigating the mediating effects among key behavioral constructs. As previously noted, although one of the foundations of resilience lies in the accumulation of knowledge resources, Nonaka and Takeuchi (2021) emphasize that while knowledge creation enables teams to acquire new insights, it alone does not confer the wisdom necessary for applying knowledge effectively. The true value of knowledge is realized through “knowledge practice,” that is, through the application, utilization, dissemination, and transformation of knowledge into action. Building on this premise, this study identifies communicative, leadership, interpretation, and analytical capacities as critical behavioral capabilities that collectively function as mediating mechanisms in the transformation of dynamic capabilities into resilience. This mechanistic perspective not only deepens the understanding of how dynamic capabilities contribute to resilience but also echoes Duchek (2020) view that resilience depends on the interaction between cognitive and behavioral capacities and organizational action. Furthermore, this behavioral pathway aligns with Zollo and Winter (2002) theory of organizational capability evolution, which emphasizes the gradual development of capabilities through mechanisms such as experiential learning, knowledge articulation, and codification. By uncovering the mediating behavioral pathways, this study provides a more actionable theoretical foundation for understanding the mechanisms that enhance team resilience.
5.2 Practical implications
First, it is essential to encourage knowledge creation processes within teams. As knowledge-based institutions, universities rely heavily on productivity and the effective generation of knowledge (Nkambule et al., 2024). In the context of innovation and change, high-quality development in universities involves the activation, reorganization, and systematization of knowledge. The dynamic capability of knowledge creation enables teams to aggregate differentiated knowledge, allowing members to efficiently and innovatively accumulate knowledge within a short time frame, even as their individual domains of expertise become more specialized. Team members can respond to complex environments by developing diverse skills, behaviors, and attitudes that collectively enhance the team’s capacity to address environmental challenges and produce valuable outcomes. Moreover, for universities and their working teams, managers should place team collaboration at the core of knowledge creation, emphasizing the participatory design of team members. Collective creation should be leveraged as a means of knowledge mobilization—enabling the sharing, activation, and utilization of available knowledge (Langley et al., 2018). This approach reflects the team’s capacity to sense its environment, capture advantageous information, and reconstruct it meaningfully. For example, institutions may establish interdisciplinary workshops or innovation labs, and develop dedicated knowledge integration platforms for teaching and research teams, or collaborative platforms for administrators. These platforms can systematically document team members’ expertise, interests, progress, and resource needs, thereby enhancing the efficiency of knowledge sharing and mobilization.
Second, it is crucial to prioritize the development of team dynamic capabilities within universities. In the practice of knowledge management in academic teams, it is important to recognize that the process of developing dynamic capabilities is influenced by collective functional mechanisms. University team management should acknowledge that dynamic capabilities are shaped and sustained by structured collective processes. Research teams engaged in organized scientific activities are expected to demonstrate collective intelligence in their outputs. Accordingly, team members must possess lifelong learning abilities, effective interpersonal communication skills (Aziz et al., 2024), critical thinking, and strong knowledge management competencies (Ding et al., 2019).
Third, as team resilience is considered a form of shared consensus outcome (Chapman et al., 2020; Raetze et al., 2021), strengthening team resilience can enhance problem-solving and decision-making quality within university management teams, as well as foster innovation in management processes. Given the current strategic importance of digital transformation (DT), resilience-building plays a pivotal role in guiding and enabling such transitions (Benavides et al., 2020; Rof et al., 2020). Emphasizing contingency planning and reflective mechanisms within teams requires members to document daily management processes, encourages continuous learning, and fosters anticipation of change, thereby enabling team members to become more adaptable, stable, and self-reliant (Shaya et al., 2023).
5.3 Limitations and potential research directions
Although this paper provides constructive insights into team resilience, several limitations should be acknowledged. The research model is grounded in the context of local public universities, which restricts the generalizability of the findings due to the singular organizational type and cultural background. It does not account for the hierarchical structure of Chinese higher education institutions (e.g., national vs. local universities), nor does it test the applicability of the model across industries (e.g., business, nonprofit sectors) or cultural settings (e.g., high vs. low power distance societies). These contextual differences are increasingly recognized as both limitations and opportunities for future cross-cultural research. Future studies should consider expanding the sample scope to include a broader range of institutional types and geographic regions. This would allow for an exploration of how dynamic capability configurations function differently across various sectors and cultural environments, thereby contributing to the development of a more universally applicable theoretical framework of team resilience.
This paper employed a serial mediation model to represent the dynamic functions of teams, which remains exploratory in nature. The proposed sequence is not intended to be definitive or exhaustive; rather, it reflects a theoretically grounded configuration informed by the literature on knowledge creation, sensemaking, and team learning (e.g., Nonaka et al., 2016; Weick, 1995; Edmondson, 1999). Future research could test alternative models, such as adopting the Knowledge-to-Action Framework (KTA) (Graham et al., 2006) as a comprehensive theoretical foundation. Additionally, incorporating contextual moderators may further refine the mechanisms through which team dynamic capabilities influence resilience, thereby contributing to the development of a more robust theoretical model.
In line with Farnese et al. (2019), the cross-sectional design precludes the ability to make statements of causal relationships on organizational performance indicators, and future studies utilizing time-lagged or multisource data are recommended. The findings of this study reflect individual-level perceptions rather than objectively constructed team-level phenomena. Future research should adopt multilevel designs with appropriate aggregation indices to more accurately capture team-level constructs. Additionally, the integration of team dynamic capability with other variables in a combined model was intended to assess discriminant validity. Although hierarchical modeling might be more conceptually appropriate, technical constraints in addressing discriminant validity at the single-dimension level limited this approach. Future research may explore the use of hierarchical modeling followed by integration into a comprehensive structural model.
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Author contributions
HY: Writing – original draft. SS: Writing – review & editing.
Funding
The author(s) declare that no financial support was received for the research and/or publication of this article.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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References
Aarrestad, M., Brøndbo, M. T., and Carlsen, A. (2015). When stakes are high and guards are low: high-quality connections in knowledge creation. Knowl. Process. Manag. 22, 88–98. doi: 10.1002/kpm.1469
Abbas, J., Zhang, Q., Hussain, I., Akram, S., Afaq, A., and Shad, M. A. (2020). Sustainable innovation in small medium enterprises: the impact of knowledge management on organizational innovation through a mediation analysis by using SEM approach. Sustainability 12:2407. doi: 10.3390/su12062407
Abubakar, A. M., Elrehail, H., Alatailat, M. A., and Elçi, A. (2019). Knowledge management, decision-making style and organizational performance. J. Innov. Knowl. 4, 104–114. doi: 10.1016/j.jik.2017.07.003
Adler, R. W., and Hiromoto, T. (2012). Amoeba management: lessons from Japan’s Kyocera. MIT Sloan Manag. Rev. 54, 83–89.
Agassian, R. (2021). Building Resilient Teams: Compositional and Compilational Approaches. Dissertation/master’s thesis, Melbourne: Florida Institute of Technology.
Akgün, A. E., Keskin, H., Byrne, J. C., and Lynn, G. S. (2014). Antecedents and consequences of organizations' technology sensemaking capability. Technol. Forecast. Soc. Change 88, 216–231. doi: 10.1016/j.techfore.2014.07.002
Akram, K., and Hilman, H. (2017). Is dynamic capability view relevant to the higher education institutions for innovation capability? Int. J. Innov. Knowl. Concepts 5, 41–49.
Al Amiri, N., Rahima, R. E. A., and Ahmed, G. (2020). Leadership styles and organizational knowledge management activities: a systematic review. Gadjah Mada Int. J. Bus. 22, 250–275. doi: 10.22146/gamaijb.49903
Alliger, G. M., Cerasoli, C. P., Tannenbaum, S. I., and Vessey, W. B. (2015). Team resilience: how teams flourish under pressure. Organ. Dyn. 44, 176–184. doi: 10.1016/j.orgdyn.2015.05.003
Allinson, C. W., and Hayes, J. (1996). The cognitive style index: a measure of intuition-analysis for organizational research. J. Manage. Stud. 33, 119–135. doi: 10.1111/j.1467-6486.1996.tb00801.x
Al-Mansour, J., and Obembe, D. (2021). Analysing the communication process between middle and top managers through the concept of'ba'. Electron. J. Knowl. Manag. 19, 226–236. doi: 10.34190/ejkm.19.3.2550
Alsharo, M., Gregg, D., and Ramirez, R. (2017). Virtual team effectiveness: the role of knowledge sharing and trust. Inf. Manag. 54, 479–490. doi: 10.1016/j.im.2016.10.005
Ambrosini, V., and Bowman, C. (2009). What are dynamic capabilities and are they a useful construct in strategic management? Int. J. Manag. Rev. 11, 29–49. doi: 10.1111/j.1468-2370.2008.00251.x
Arndt, F. (2019). Dynamic capabilities: a retrospective, state-of-the-art, and future research agenda. J. Manag. Organ. 1-4, 1–4. doi: 10.1017/jmo.2019.21
Ashmos, D. P., Duchon, D., and McDaniel, R. R. Jr. (1998). Participation in strategic decision making: the role of organizational predisposition and issue interpretation. Decis. Sci. 29, 25–51. doi: 10.1111/j.1540-5915.1998.tb01343.x
Awashreh, R. A., and Hamid, A. A. (2024). Understanding wise leadership: employees' perspective in Oman's government sector. S. Afr. J. Hum. Resour. Manage. 22:1-11. doi: 10.4102/sajhrm.v22i0.2747
Aziz, S. N. M., Aldaba, A. M. A., Tumiran, M. A., and Maidin, Z. (2024). Characteristics of wise leadership practices in an educational setting: a content analysis. Asian J. Res. Educ. Soc. Sci. 6, 604–614. doi: 10.55057/ajress.2024.6.2.54
Baía, E. P., and Ferreira, J. J. (2019). Dynamic capabilities and performance: how has the relationship been assessed? J. Manag. Organ. 30, 188–217. doi: 10.1017/jmo.2019.88
Barreto, I. (2010). Dynamic capabilities: a review of past research and an agenda for the future. J. Manage. 36, 256–280. doi: 10.1177/0149206309350776
Bejinaru, R. (2017). Dynamic capabilities of universities in the knowledge economy. Manag. Dyn. Knowl. Econ. 5, 577–595. doi: 10.25019/MDKE/5.4.07
Belton, V., and Stewart, T. (2012). Multiple criteria decision analysis: An integrated approach. Dordrecht: Springer Science + Business Media.
Benavides, L. M. C., Tamayo Arias, J. A., Arango Serna, M. D., Branch Bedoya, J. W., and Burgos, D. (2020). Digital transformation in higher education institutions: a systematic literature review. Sensors 20:3291. doi: 10.3390/s20113291
Bierhals, R., Schuster, I., Kohler, P., and Badke-Schaub, P. (2007). Shared mental models—linking team cognition and performance. CoDesign 3, 75–94. doi: 10.1080/15710880601170891
Bodunde, K., Bello, S., and Olasunkanmi, L. (2024). Information exchange and collaborative problem-solving roles in organizational conflict resolution. J. Manage. Econ. Ind. Organ. 8, 18–33. doi: 10.31039/jomeino.2024.832
Bowers, C., Kreutzer, C., Cannon-Bowers, J., and Lamb, J. (2017). Team resilience as a second-order emergent state: a theoretical model and research directions. Front. Psychol. 8:1360. doi: 10.3389/fpsyg.2017.01360
Bradshaw, R., Chebbi, M., and Oztel, H. (2015). Leadership and knowledge sharing. Asian J. Bus. Res. 4:15001. doi: 10.14707/ajbr.150001
Braganza, A., Brooks, L., Nepelski, D., Ali, M., and Moro, R. (2017). Resource management in big data initiatives: processes and dynamic capabilities. J. Bus. Res. 70, 328–337. doi: 10.1016/j.jbusres.2016.08.006
Brykman, K. M., and King, D. D. (2021). A resource model of team resilience capacity and learning. Group Org. Manag. 46, 737–772. doi: 10.1177/10596011211018008
Burke, C. S., Priest, H. A., Salas, E., Sims, D., and Mayer, K. (2018). “Stress and teams: how stress affects decision making at the team level” in Performance under stress. eds. J. L. Szalma and P. A. Hancock (London: CRC Press), 197–224.
Burton, A. M., and Dickinger, A. (2025). Innovation in crisis. The role of leadership and dynamic capabilities for a more innovative hospitality industry. Int. J. Hosp. Manag. 124:103946. doi: 10.1016/j.ijhm.2024.103946
Butchibabu, A., Sparano-Huiban, C., Sonenberg, L., and Shah, J. (2016). Implicit coordination strategies for effective team communication. Hum. Factors 58, 595–610. doi: 10.1177/0018720816639712
Caniglia, G., Lüderitz, C., von Wirth, T., Fazey, I., Martín-López, B., Hondrila, K., et al. (2021). A pluralistic and integrated approach to action-oriented knowledge for sustainability. Nat. Sustain. 4, 93–100. doi: 10.1038/s41893-020-00616-z
Carmeli, A., Friedman, Y., and Tishler, A. (2013). Cultivating a resilient top management team: the importance of relational connections and strategic decision comprehensiveness. Saf. Sci. 51, 148–159. doi: 10.1016/j.ssci.2012.06.002
Carmeli, A., Levi, A., and Peccei, R. (2021). Resilience and creative problem-solving capacities in project teams: a relational view. Int. J. Proj. Manag. 39, 546–556. doi: 10.1016/j.ijproman.2021.03.007
Cascio, W. (2020). Managing a brittle, anxious, nonlinear, incomprehensible world. Harvard Business Review.
Casoria, F., Riedl, A., and Werner, P. (2020). “Behavioral aspects of communication in organizations” in Handbook of labor, human resources and population economics. ed. K. F. Zimmermann (Cham: Springer).
Cepeda, G., and Vera, D. (2007). Dynamic capabilities and operational capabilities: a knowledge management perspective. J. Bus. Res. 60, 426–437. doi: 10.1016/j.jbusres.2007.01.013
Chapman, M. T., Lines, R. L., Crane, M., Ducker, K. J., Ntoumanis, N., Peeling, P., et al. (2020). Team resilience: a scoping review of conceptual and empirical work. Work Stress. 34, 57–81. doi: 10.1080/02678373.2018.1529064
Chen, Y., and Zhang, Y. (2021). Fostering resilience in new venture teams: the role of behavioral and affective integration. Group Organ. Manag. 46, 773–816. doi: 10.1177/10596011211033164
Choo, C. W. (1996). The knowing organization: how organizations use information to construct meaning, create knowledge and make decisions. Int. J. Inf. Manag. 16, 329–340. doi: 10.1016/0268-4012(96)00020-5
Ciulla, J. B. (2004). Ethics and leadership effectiveness. Nat. Leadersh. 11, 302–327. doi: 10.1007/978-1-137-24203-7_23
Clark, T. W., Reading, R. P., and Clarke, A. L. (1994). A professional perspective: Improving problem solving, communication and effectiveness. Endangered species recovery: Finding the lessons, improving the process. Washington, DC: Island Press, 351–369.
Clark, H. H., and Schaefer, E. F. (1989). Contributing to discourse. Cogn. Sci. 13, 259–294. doi: 10.1016/0364-0213(89)90008-6
Collis, D. J. (1994). Research note: how valuable are organizational capabilities? Strateg. Manag. J. 15, 143–152. doi: 10.1002/smj.4250150910
Compagnucci, L., and Spigarelli, F. (2020). The third mission of the university: a systematic literature review on potentials and constraints. Technol. Forecast. Soc. Change 161:120284. doi: 10.1016/j.techfore.2020.120284
Çop, S., Olorunsola, V. O., and Alola, U. V. (2021). Achieving environmental sustainability through green transformational leadership policy: can green team resilience help? Bus. Strateg. Environ. 30, 671–682. doi: 10.1002/bse.2646
Day, D. V. (2000). Leadership development: a review in context. Leadersh. Q. 11, 581–613. doi: 10.1016/S1048-9843(00)00061-8
De Boeck, P., and Scalise, K. (2019). Collaborative problem solving: processing actions, time, and performance. Front. Psychol. 10:1280. doi: 10.3389/fpsyg.2019.01280
De Dreu, C. K. (2007). Cooperative outcome interdependence, task reflexivity, and team effectiveness: a motivated information processing perspective. J. Appl. Psychol. 92, 628–638. doi: 10.1037/0021-9010.92.3.628
De Dreu, C. K., and Beersma, B. (2010). Team confidence, motivated information processing, and dynamic group decision making. Eur. J. Soc. Psychol. 40, 1110–1119. doi: 10.1002/ejsp.763
Del Corso, J.-P., Kephaliacos, C., and Plumecocq, G. (2015). Legitimizing farmers' new knowledge, learning and practices through communicative action: application of an agro-environmental policy. Ecol. Econ. 117, 86–96. doi: 10.1016/j.ecolecon.2015.05.017
Denis, J.-L., Langley, A., and Sergi, V. (2012). Leadership in the plural. Acad. Manage. Ann. 6, 211–283. doi: 10.5465/19416520.2012.667612
Di Stefano, G., Peteraf, M., and Verona, G. (2014). The organizational drivetrain: a road to integration of dynamic capabilities research. Acad. Manage. Perspect. 28, 307–327. doi: 10.5465/amp.2013.0100
Ding, W., Choi, E., and Aoyama, A. (2019). Relational study of wise (phronetic) leadership, knowledge management capability, and innovation performance. Asia Pac. Manag. Rev. 24, 310–317. doi: 10.1016/j.apmrv.2018.10.005
Dixon, S., Meyer, K., and Day, M. (2014). Building dynamic capabilities of adaptation and innovation: a study of micro-foundations in a transition economy. Long Range Plan. 47, 186–205. doi: 10.1016/j.lrp.2013.08.011
Dodgson, M. (2014). “Collaboration and innovation management” in The Oxford handbook of innovation management. eds. M. Dodgson, D. M. Gann, and N. Phillips (Oxford: Oxford University Press), 462–481.
Doerfel, M. L., Kim, M., Kwestel, M., Yoon, H., and Quow, J. (2022). Resilience organizing: a multilevel communication framework. J. Commun. 72, 605–618. doi: 10.1093/joc/jqac027
Donate, M. J., and de Pablo, J. D. S. (2015). The role of knowledge-oriented leadership in knowledge management practices and innovation. J. Bus. Res. 68, 360–370. doi: 10.1016/j.jbusres.2014.06.022
Dong, J., Huang, J., and Chen, Z. (2004). An intellectual model of the evolution of dynamic capabilities; and a relevant case study of a Chinese enterprise. Manage. World 4, 117–127. doi: 10.19744/j.cnki.11-1235/f.2004.04.012
Drucker, P. F. (1988). The coming of the new organization. Investig. Adm. 14, 1–7. doi: 10.35426/IAv14n63.04
Duchek, S. (2020). Organizational resilience: a capability-based conceptualization. Bus. Res. 13, 215–246. doi: 10.1007/s40685-019-0085-7
Dutton, J. E., Fahey, L., and Narayanan, V. K. (1983). Toward understanding strategic issue diagnosis. Strateg. Manag. J. 4, 307–323. doi: 10.1002/smj.4250040403
Dutton, J. E., and Jackson, S. E. (1987). Categorizing strategic issues: links to organizational action. Acad. Manag. Rev. 12, 76–90. doi: 10.2307/257995
Dzamtoska-Zdravkovska, S., and Haque, S. (2023). The theoretical basis of internal communication as an active process of information exchange. Technium Soc. Sci. J. 431:252. doi: 10.47577/tssj.v43i1.8810
Edmondson, A. (1999). Psychological safety and learning behavior in work teams. Adm. Sci. Q. 44, 350–383. doi: 10.2307/2666999
Eisenhardt, K. M., and Martin, J. A. (2000). Dynamic capabilities: what are they? Strateg. Manag. J. 21, 1105–1121. doi: 10.1002/1097-0266(200010/11)21:10/11<1105::AID-SMJ133>3.0.CO;2-E
Enders, J., and De Boer, H. (2009). “The mission impossible of the European university: institutional confusion and institutional diversity” in European integration and the governance of higher education and research. eds. A. Amaral, G. Neave, C. Musselin, and P. Maassen (Dordrecht: Springer Science+Business Media).
Epstein, S., Pacini, R., Denes-Raj, V., and Heier, H. (1996). Individual differences in intuitive–experiential and analytical–rational thinking styles. J. Pers. Soc. Psychol. 71, 390–405. doi: 10.1037/0022-3514.71.2.390
Eriksson, T. (2014). Processes, antecedents and outcomes of dynamic capabilities. Scand. J. Manage. 30, 65–82. doi: 10.1016/j.scaman.2013.05.001
Eva, N., Cox, J. W., Herman, H., and Lowe, K. B. (2021). From competency to conversation: a multi-perspective approach to collective leadership development. Leadersh. Q. 32:101346. doi: 10.1016/j.leaqua.2019.101346
Faccin, K., Thomas, E., and Kretschmer, C. (2022). University Dynamic Capabilities to Boost Innovation Ecosystems: The Case of a University Alliance in Brazil. Universities and Regional Engagement: From the Exceptional to the Everyday.
Farnese, M. L., Barbieri, B., Chirumbolo, A., and Patriotta, G. (2019). Managing knowledge in organizations: a Nonaka’s SECI model operationalization. Front. Psychol. 10:506330. doi: 10.3389/fpsyg.2019.02730
Ferreira, J., Coelho, A., and Moutinho, L. (2020). Dynamic capabilities, creativity and innovation capability and their impact on competitive advantage and firm performance: the moderating role of entrepreneurial orientation. Technovation 92-93:102061. doi: 10.1016/j.technovation.2018.11.004
Fisher, J., Stutzman, H., Vedoveto, M., Delgado, D., Rivero, R., Quertehuari Dariquebe, W., et al. (2020). Collaborative governance and conflict management: lessons learned and good practices from a case study in the Amazon Basin. Soc. Nat. Resour. 33, 538–553. doi: 10.1080/08941920.2019.1620389
Forkmann, S., Henneberg, S. C., and Mitrega, M. (2018). Capabilities in business relationships and networks: research recommendations and directions. Ind. Mark. Manage. 74, 4–26. doi: 10.1016/j.indmarman.2018.07.007
Frandsen, F., and Johansen, W. (2017). “Strategic communication” in The international encyclopedia of organizational communication. eds. C. R. Scott and L. Lewis (Hoboken: Wiley Blackwell), 1–9.
Franke, U. (2023). “Interpretive approaches” in Research handbook on NATO. ed. S. Mayer (Cheltenham: Edward Elgar Publishing Limited), 84–97.
Gagné, M. (2018). From strategy to action: transforming organizational goals into organizational behavior. Int. J. Manag. Rev. 20, S83–S104. doi: 10.1111/ijmr.12159
Gagnon, M. L. (2011). Moving knowledge to action through dissemination and exchange. J. Clin. Epidemiol. 64, 25–31. doi: 10.1016/j.jclinepi.2009.08.013
Galy, A., Chênevert, D., Fouquereau, E., and Groulx, P. (2023). Toward a new conceptualization of resilience at work as a meta-construct? Front. Psychol. 14:1211538. doi: 10.3389/fpsyg.2023.1211538
Gervits, F., Eberhard, K., and Scheutz, M. (2016). Team communication as a collaborative process. Front. Robot. AI 3:62. doi: 10.3389/frobt.2016.00062
Gheitarani, F., Nawaser, K., Hanifah, H., and Vafaei-Zadeh, A. (2023). Human-behavioural micro-foundations of dynamic capabilities: a systematic review of the last two decades of research. Int. J. Manag. Decis. Mak. 22, 1–26. doi: 10.1504/IJMDM.2023.127685
Gibb, C. A. (1954). “Leadership” in Handbook of social psychology. eds. S. T. Fiske, D. T. Gilbert, and G. Lindzey (Hoboken: John Wiley & Sons, Inc).
Gomes, J. O., Borges, M. R., Huber, G. J., and Carvalho, P. V. R. (2014). Analysis of the resilience of team performance during a nuclear emergency response exercise. Appl. Ergon. 45, 780–788. doi: 10.1016/j.apergo.2013.10.009
Graham, I. D., Logan, J., Harrison, M. B., Straus, S. E., Tetroe, J., Caswell, W., et al. (2006). Lost in knowledge translation: time for a map? J. Contin. Educ. Health Prof. 26, 13–24. doi: 10.1002/chp.47
Granovetter, M. S. (1973). The strength of weak ties. Am. J. Sociol. 78, 1360–1380. doi: 10.1086/225469
Gulbrandsen, B., Lambe, C. J., and Sandvik, K. (2017). Firm boundaries and transaction costs: the complementary role of capabilities. J. Bus. Res. 78, 193–203. doi: 10.1016/j.jbusres.2016.12.015
Hagemann, V., and Kluge, A. (2017). Complex problem solving in teams: the impact of collective orientation on team process demands. Front. Psychol. 8:1730. doi: 10.3389/fpsyg.2017.01730
Hair, J. F. Jr. (2007). Knowledge creation in marketing: the role of predictive analytics. Eur. Bus. Rev. 19, 303–315. doi: 10.1108/09555340710760134
Hallahan, K., Holtzhausen, D., Van Ruler, B., Verčič, D., and Sriramesh, K. (2007). Defining strategic communication. Int. J. Strateg. Commun. 1, 3–35. doi: 10.1080/15531180701285244
Harms, P. D., Credé, M., Tynan, M., Leon, M., and Jeung, W. (2017). Leadership and stress: a meta-analytic review. Leadersh. Q. 28, 178–194. doi: 10.1016/j.leaqua.2016.10.006
Hartmann, S., Weiss, M., Hoegl, M., and Carmeli, A. (2021). How does an emotional culture of joy cultivate team resilience? A sociocognitive perspective. J. Organ. Behav. 42, 313–331. doi: 10.1002/job.2496
Hartmann, S., Weiss, M., Newman, A., and Hoegl, M. (2020). Resilience in the workplace: a multilevel review and synthesis. Appl. Psychol. 69, 913–959. doi: 10.1111/apps.12191
Hartwig, A., Clarke, S., Johnson, S., and Willis, S. (2020). Workplace team resilience: a systematic review and conceptual development. Organ. Psychol. Rev. 10, 169–200. doi: 10.1177/2041386620919476
Harvey, J.-F., Bresman, H. M., and Edmondson, A. C. (2018). Team learning capabilities: a meso model of sustained innovation and firm performance. Acad. Manag. 2018:18086. doi: 10.5465/AMBPP.2018.18086
Hassi, A., and Storti, G. (2023). Wise leadership: construction and validation of a scale. Mod. Manag. Rev. 28, 47–69. doi: 10.7862/rz.2023.mmr.03
Hayes, A. F. (2009). Beyond baron and Kenny: statistical mediation analysis in the new millennium. Commun. Monogr. 76, 408–420. doi: 10.1080/03637750903310360
Heaton, S., Siegel, D. S., and Teece, D. J. (2019). Universities and innovation ecosystems: a dynamic capabilities perspective. Ind. Corp. Change 28, 921–939. doi: 10.1093/icc/dtz038
Helfat, C. E., Finkelstein, S., Mitchell, W., Peteraf, M., Singh, H., Teece, D., et al. (2009). Dynamic capabilities: Understanding strategic change in organizations. Oxford: John Wiley and Sons.
Helfat, C. E., and Raubitschek, R. S. (2018). Dynamic and integrative capabilities for profiting from innovation in digital platform-based ecosystems. Res. Policy 47, 1391–1399. doi: 10.1016/j.respol.2018.01.019
Helfat, C. E., and Winter, S. G. (2011). Untangling dynamic and operational capabilities: strategy for the (N) ever-changing world. Strateg. Manage. J. 32, 1243–1250. doi: 10.1002/smj.955
Hitt, M. A., and Tyler, B. B. (1991). Strategic decision models: integrating different perspectives. Strateg. Manage. J. 12, 327–351. doi: 10.1002/smj.4250120502
Hobfoll, S. E. (2011). “Conservation of resources theory: Its implication for stress, health, and resilience” in The Oxford handbook of stress, health, and coping. ed. S. Folkman (New York: Oxford University Press), 147.
Hobfoll, S. E., Halbesleben, J., Neveu, J.-P., and Westman, M. (2018). Conservation of resources in the organizational context: the reality of resources and their consequences. Annu. Rev. Organ. Psychol. Organ. Behav. 5, 103–128. doi: 10.1146/annurev-orgpsych-032117-104640
Hoerl, R. W., and Vining, G. G. (2021). The journey to establish the discipline of statistical engineering. Appl. Stoch. Models Bus. Ind. 37, 372–383. doi: 10.1002/asmb.2583
Hoffman, R. R., and Hancock, P. A. (2017). Measuring resilience. Hum. Factors 59, 564–581. doi: 10.1177/0018720816686248
Huizingh, E. K. (2017). Moving the innovation horizon in Asia. Technovation 60, 43–44. doi: 10.1016/j.technovation.2017.01.005
Hung, W. (2013). Team-based complex problem solving: a collective cognition perspective. Educ. Technol. Res. Dev. 61, 365–384. doi: 10.1007/s11423-013-9296-3
Ibrahim Ismael, Z., Mamdouh El-kholy, S., and Abd-Elrhaman, S. A. (2021). Knowledge management as a predictor of organizational resilience and agility. Egypt. J. Health Care 12, 1397–1412. doi: 10.21608/ejhc.2021.209025
Karlsson, P. S., and Offord, M. (2023). Higher education during crisis: a case study on organic resilience. Contin. Resil. Rev. 5, 185–197. doi: 10.1108/CRR-10-2022-0030
Kaufmann, L., Meschnig, G., and Reimann, F. (2014). Rational and intuitive decision-making in sourcing teams: effects on decision outcomes. J. Purch. Supply Manag. 20, 104–112. doi: 10.1016/j.pursup.2014.03.003
Kaur, V. (2019). Knowledge-based dynamic capabilities and competitive advantage–data analysis and interpretations. Knowledge-Based Dynamic Capabilities: The Road Ahead in Gaining Organizational Competitiveness, pp. 145–208.
Kelleher, L., and Ulrichsen, T. C. (2023). Universities driving innovation in the ‘new normal’: a multi-ontological perspective of dynamic capability microfoundations for knowledge exchange.
Kennedy, D. M., Landon, L. B., and Maynard, M. T. (2016). Extending the conversation: employee resilience at the team level. Ind. Organ. Psychol. 9, 466–475. doi: 10.1017/iop.2016.41
Khan, S., Mishra, J. L., Lin, K.-h. E., and Doyle, E. E. (2017). Rethinking communication in risk interpretation and action. Nat. Hazards 88, 1709–1726. doi: 10.1007/s11069-017-2942-z
Kim, Y. (2020). Organizational resilience and employee work-role performance after a crisis situation: exploring the effects of organizational resilience on internal crisis communication. J. Public Relat. Res. 32, 47–75. doi: 10.1080/1062726X.2020.1765368
Kim, M. S., Phillips, J. M., Park, W.-W., and Gully, S. M. (2023). When leader-member exchange leads to knowledge sharing: the roles of general self-efficacy, team leader modeling, and LMX differentiation. Int. J. Hum. Resour. Manag. 34, 1442–1469. doi: 10.1080/09585192.2021.1886150
Klein, G., Wiggins, S., and Dominguez, C. O. (2010). Team sensemaking. Theor. Issues Ergon. Sci. 11, 304–320. doi: 10.1080/14639221003729177
Laaksonen, O., and Peltoniemi, M. (2018). The essence of dynamic capabilities and their measurement. Int. J. Manag. Rev. 20, 184–205. doi: 10.1111/ijmr.12122
Lakshman, C. (2009). Organizational knowledge leadership: an empirical examination of knowledge management by top executive leaders. Leadersh. Organ. Dev. J. 30, 338–364. doi: 10.1108/01437730910961676
Langley, J., Wolstenholme, D., and Cooke, J. (2018). Collective making’as knowledge mobilisation: the contribution of participatory design in the co-creation of knowledge in healthcare. BMC Health Serv. Res. 18, 1–10. doi: 10.1186/s12913-018-3397-y
Lee, Y., and Li, J.-Y. Q. (2020). The value of internal communication in enhancing employees’ health information disclosure intentions in the workplace. Public Relat. Rev. 46:101872. doi: 10.1016/j.pubrev.2019.101872
Lengnick-Hall, C. A., Beck, T. E., and Lengnick-Hall, M. L. (2011). Developing a capacity for organizational resilience through strategic human resource management. Hum. Resour. Manag. Rev. 21, 243–255. doi: 10.1016/j.hrmr.2010.07.001
Li, J., and Chen, Y. (2024). Research on the micro-foundations of sustainable development by overseas innovation ecosystems: a dynamic capabilities view. Asia Pac. J. Manag. 1, 1–62. doi: 10.1007/s10490-024-09996-8
Liedtka, J. (2000). In defense of strategy as design. Calif. Manag. Rev. 42, 8–30. doi: 10.2307/41166040
Lin, T.-C., Chen, C.-M., Hsu, J. S.-C., and Fu, T.-W. (2015). The impact of team knowledge on problem solving competence in information systems development team. Int. J. Proj. Manag. 33, 1692–1703. doi: 10.1016/j.ijproman.2015.07.007
Lin, C.-Y., and Huang, C.-K. (2020). Understanding the antecedents of knowledge sharing behaviour and its relationship to team effectiveness and individual learning. Australas. J. Educ. Technol. 36, 89–104. doi: 10.14742/ajet.4549
Liu, G. (2021). The new development pattern and high-quality development of higher education. Tsinghua J. Edc. 42, 25–32. doi: 10.14138/j.1001-4519.2021.01.002508
Liu, J., and Harms, R. (2025). Pathways to survive in abrupt adversities: a configurational approach to understanding the resilience of new venture teams. Rev. Manag. Sci. 19, 1447–1476. doi: 10.1007/s11846-024-00798-2
Liu, X., Yuan, Y., Sun, R., Zhao, C., and Zhao, D. (2023). Influence of entrepreneurial team knowledge conflict on ambidextrous entrepreneurial learning—a dual-path perspective of entrepreneurial resilience and fear of failure. J. Innov. Knowl. 8:100389. doi: 10.1016/j.jik.2023.100389
Lombardi, S., Cunha, M. P., and Giustiniano, L. (2021). Improvising resilience: the unfolding of resilient leadership in COVID-19 times. Int. J. Hosp. Manag. 95:102904. doi: 10.1016/j.ijhm.2021.102904
Lord, R. G., Day, D. V., Zaccaro, S. J., Avolio, B. J., and Eagly, A. H. (2017). Leadership in applied psychology: three waves of theory and research. J. Appl. Psychol. 102, 434–451. doi: 10.1037/apl0000089
Luthar, S. S. (2015). “Resilience in development: A synthesis of research across five decades” in Developmental psychopathology: Risk, disorder, and adaptation. eds. D. Cicchetti and D. J. Cohen (New York: John Wiley & Sons, Inc.), 739–795.
Mac Gillivray, A. E. (2018). Leadership as practice meets knowledge as flow: emerging perspectives for leaders in knowledge-intensive organizations. J. Public Aff. 18:e1699. doi: 10.1002/pa.1699
Maitlis, S., and Christianson, M. (2014). Sensemaking in organizations: taking stock and moving forward. Acad. Manag. Ann. 8, 57–125. doi: 10.5465/19416520.2014.873177
Malik, A., Nguyen, M., Budhwar, P., Chowdhury, S., and Gugnani, R. (2024). Leveraging high-performance HRM practices and knowledge sharing for managing technological and social change in emerging market healthcare providers. Technol. Forecast. Soc. Change 205:123463. doi: 10.1016/j.techfore.2024.123463
Marchese, D., Reynolds, E., Bates, M. E., Morgan, H., Clark, S. S., and Linkov, I. (2018). Resilience and sustainability: similarities and differences in environmental management applications. Sci. Total Environ. 613-614, 1275–1283. doi: 10.1016/j.scitotenv.2017.09.086
Martin-Breen, P., and Anderies, J. M. (2011). Resilience: A literature review. The Bellagio Initiative. Brighton: Institute of Development Studies.
McEwen, K. (2022). Building resilience at work: a practical framework for leaders. J. Leadersh. Stud. 16, 42–49. doi: 10.1002/jls.21814
Mesmer-Magnus, J. R., and DeChurch, L. A. (2009). Information sharing and team performance: a meta-analysis. J. Appl. Psychol. 94, 535–546. doi: 10.1037/a0013773
Mishra, J. L., Allen, D., and Pearman, A. (2015). Understanding decision making during emergencies: a key contributor to resilience. EURO J. Decis. Process. 3, 397–424. doi: 10.1007/s40070-015-0039-z
Mitchell, R., von Stieglitz, S., Gu, J., Boyle, B., and Ocampo, A. C. G. (2025). Tackling adversity with open minds: team personality composition facilitates shared leadership and team resilience. Appl. Psychol. 74:e12568. doi: 10.1111/apps.12568
Mola, L., Rossignoli, C., Carugati, A., and Giangreco, A. (2020). Business intelligence system design and its consequences for knowledge sharing, collaboration, and decision-making: an exploratory study. Int. J. Technol. Hum. Interact. 11, 1–25. doi: 10.4018/IJTHI.2015100101
Moodysson, J., Coenen, L., and Asheim, B. (2008). Explaining spatial patterns of innovation: analytical and synthetic modes of knowledge creation in the Medicon Valley life-science cluster. Environ. Plan. A 40, 1040–1056. doi: 10.1068/a39110
Morgan, P. B., Fletcher, D., and Sarkar, M. (2017). Recent developments in team resilience research in elite sport. Curr. Opin. Psychol. 16, 159–164. doi: 10.1016/j.copsyc.2017.05.013
Morgan, P. B., Fletcher, D., and Sarkar, M. (2019). Developing team resilience: a season-long study of psychosocial enablers and strategies in a high-level sports team. Psychol. Sport Exerc. 45:101543. doi: 10.1016/j.psychsport.2019.101543
Mumford, M. D., Friedrich, T. L., Vessey, W. B., and Ruark, G. A. (2012). Collective leadership: thinking about issues Vis-à-Vis others. Ind. Organ. Psychol. 5, 408–411. doi: 10.1111/j.1754-9434.2012.01469.x
Munoz-Penas, J., Clarke, A. H., and Evald, M. R. (2024). Building a commercialization capability: a dynamic capability view. Ind. Mark. Manag. 117, 344–355. doi: 10.1016/j.indmarman.2024.01.015
Neill, S., McKee, D., and Rose, G. M. (2007). Developing the organization's sensemaking capability: precursor to an adaptive strategic marketing response. Ind. Mark. Manag. 36, 731–744. doi: 10.1016/j.indmarman.2006.05.008
Neves, R. (2024). “Collaboration and team dynamics” in The engineering leadership playbook: Strategies for team success and business growth. ed. R. Neves (Berkeley, CA: Apress), 113–179.
Newman, S. A., and Ford, R. C. (2021). Five steps to leading your team in the virtual COVID-19 workplace. Organ. Dyn. 50:100802. doi: 10.1016/j.orgdyn.2020.100802
Nicklin, G. (2012). Strategic thinking, shared meaning-making and the interpretive turn in policy-a case study. Aust. J. Public Adm. 71, 45–54. doi: 10.1111/j.1467-8500.2012.00750.x
Niler, A. A., Mesmer-Magnus, J. R., Larson, L. E., Plummer, G., DeChurch, L. A., and Contractor, N. S. (2021). Conditioning team cognition: a meta-analysis. Organ. Psychol. Rev. 11, 144–174. doi: 10.1177/2041386620972112
Nkambule, B., Ngubane, S. A., and Mashiane-Nkabinde, B. (2024). Management of context-specific knowledge creation and application through collective social responsibility in school? Community partnerships. Int. J. Learn. Teach. Educ. Res. 23, 499–524. doi: 10.26803/ijlter.23.7.25
Nonaka, I., Byosiere, P., Borucki, C. C., and Konno, N. (1994). Organizational knowledge creation theory: a first comprehensive test. Int. Bus. Rev. 3, 337–351. doi: 10.1016/0969-5931(94)90027-2
Nonaka, I., Hirose, A., and Takeda, Y. (2016). ‘Meso’-foundations of dynamic capabilities: team-level synthesis and distributed leadership as the source of dynamic creativity. Glob. Strategy J. 6, 168–182. doi: 10.1002/gsj.1125
Nonaka, I., and Konno, N. (1998). The concept of “Ba”: building a foundation for knowledge creation. Calif. Manag. Rev. 40, 40–54. doi: 10.2307/41165942
Nonaka, I., Konno, N., and Toyama, R. (2001). “Emergence of “Ba”” in Knowledge emergence: Social, technical, and evolutionary dimensions of knowledge creation. eds. I. Nonaka and T. Nishiguch (New York: Oxford University Press), 13–29.
Nonaka, I., and Takeuchi, H. (2007). The knowledge-creating company. Harvard Business Review, p. 162.
Nonaka, I., and Takeuchi, H. (2021). Humanizing strategy. Long Range Plan. 54:102070. doi: 10.1016/j.lrp.2021.102070
Nonaka, l., Takeuchi, H., and Umemoto, K. (1996). A theory of organizational knowledge creation. Int. J. Technol. Manag. 11, 833–845. doi: 10.1504/IJTM.1996.025472
Nonaka, I., and Toyama, R. (2002). A firm as a dialectical being: towards a dynamic theory of a firm. Ind. Corp. Change 11, 995–1009. doi: 10.1093/icc/11.5.995
Nonaka, I., and Toyama, R. (2007). Strategic management as distributed practical wisdom (phronesis). Ind. Corp. Change 16, 371–394. doi: 10.1093/icc/dtm014
Nonaka, I., Toyama, R., and Konno, N. (2000). SECI, Ba and leadership: a unified model of dynamic knowledge creation. Long Range Plan. 33, 5–34. doi: 10.1016/S0024-6301(99)00115-6
Odiase, O., Wilkinson, S., and Neef, A. (2020). Risk of a disaster: risk knowledge, interpretation and resilience. Jàmbá J. Disaster Risk Stud. 12, 1–9. doi: 10.4102/jamba.v12i1.845
Olaisen, J., and Revang, O. (2018). Exploring the performance of tacit knowledge: how to make ordinary people deliver extraordinary results in teams. Int. J. Inf. Manag. 43, 295–304. doi: 10.1016/j.ijinfomgt.2018.08.016
Pacini, R., and Epstein, S. (1999). The interaction of three facets of concrete thinking in a game of chance. Think. Reason. 5, 303–325. doi: 10.1080/135467899393959
Paschertz, B. (2021). What makes a team resilient? The moderating roles of cognitive diversity and team potency on the relationship of psychological safety and team resilience. Dissertation/Master's thesis, Utrecht (The Netherlands): Utrecht University.
Paulus, P. B., and Nijstad, B. A. (2003). Group creativity: Innovation through collaboration. New York: Oxford University Press.
Raetze, S., Duchek, S., Maynard, M. T., and Kirkman, B. L. (2021). Resilience in organizations: an integrative multilevel review and editorial introduction. Group Organ. Manag. 46, 607–656. doi: 10.1177/10596011211032129
Ramirez, V. E. (2020). Resilience amidst pandemic: HEI sustaining quality assurance in a digital world. Higher Educ. Qual. Assur. 1, 1–32. doi: 10.13140/RG.2.2.33039.82080
Rof, A., Bikfalvi, A., and Marquès, P. (2020). Digital transformation for business model innovation in higher education: overcoming the tensions. Sustainability 12:4980. doi: 10.3390/su12124980
Sackmann, S. (1991). Cultural knowledge in organizations: Exploring the collective mind. Thousand Oaks, CA: Sage Publications.
Salvato, C. (2003). The role of micro-strategies in the engineering of firm evolution. J. Manage. Stud. 40, 83–108. doi: 10.1111/1467-6486.t01-2-00005
Salvato, C., and Vassolo, R. (2018). The sources of dynamism in dynamic capabilities. Strateg. Manage. J. 39, 1728–1752. doi: 10.1002/smj.2703
Schilke, O. (2014). On the contingent value of dynamic capabilities for competitive advantage: the nonlinear moderating effect of environmental dynamism. Strateg. Manage. J. 35, 179–203. doi: 10.1002/smj.2099
Schneider, S. C., and De Meyer, A. (1991). Interpreting and responding to strategic issues: the impact of national culture. Strateg. Manage. J. 12, 307–320. doi: 10.1002/smj.4250120406
Shannon, C. E., and Weaver, W. (1949). The mathematical theory of communication. Urbana: University of Illinois Press.
Shaya, N., Abukhait, R., Madani, R., and Khattak, M. N. (2023). Organizational resilience of higher education institutions: an empirical study during Covid-19 pandemic. High Educ. Pol. 36, 529–555. doi: 10.1057/s41307-022-00272-2
Singh, S. K. (2008). Role of leadership in knowledge management: a study. J. Knowl. Manag. 12, 3–15. doi: 10.1108/13673270810884219
Singh, K., Chatterjee, S., Chaudhuri, R., Vrontis, D., and Yildiz, H. (2025). Knowledge management and organizational resilience in MSMEs: the intervening role of innovation orientation. Strat. Change. 2025:2640. doi: 10.1002/jsc.2640
Smolka, K. M., Verheul, I., Burmeister–Lamp, K., and Heugens, P. P. (2018). Get it together! Synergistic effects of causal and effectual decision–making logics on venture performance. Entrep. Theory Pract. 42, 571–604. doi: 10.1177/1042258718783429
Son, C., Sasangohar, F., Neville, T., Peres, S. C., and Moon, J. (2020). Investigating resilience in emergency management: an integrative review of literature. Appl. Ergon. 87:103114. doi: 10.1016/j.apergo.2020.103114
Southwick, F. S., Martini, B. L., Charney, D. S., and Southwick, S. M. (2017). “Leadership and resilience” in Leadership today: Practices for personal and professional performance. ed. F. S. Southwick (Berlin: Springer), 315–333.
Specking, E., Cottam, B., Parnell, G., Pohl, E., Cilli, M., Buchanan, R., et al. (2019). Assessing engineering resilience for systems with multiple performance measures. Risk Anal. 39, 1899–1912. doi: 10.1111/risa.13395
Srivastava, A., Bartol, K. M., and Locke, E. A. (2006). Empowering leadership in management teams: effects on knowledge sharing, efficacy, and performance. Acad. Manag. J. 49, 1239–1251. doi: 10.5465/amj.2006.23478718
Stempfle, J., and Badke-Schaub, P. (2002). Thinking in design teams-an analysis of team communication. Des. Stud. 23, 473–496. doi: 10.1016/S0142-694X(02)00004-2
Stephens, J. P., Heaphy, E. D., Carmeli, A., Spreitzer, G. M., and Dutton, J. E. (2013). Relationship quality and virtuousness: emotional carrying capacity as a source of individual and team resilience. J. Appl. Behav. Sci. 49, 13–41. doi: 10.1177/0021886312471193
Sternberg, R. J. (1998). A balance theory of wisdom. Rev. Gen. Psychol. 2, 347–365. doi: 10.1037/1089-2680.2.4.347
Sternberg, R. J. (2003a). WICS: a model of leadership in organizations. Acad. Manage. Learn. Educ. 2, 386–401. doi: 10.5465/amle.2003.11902088
Sternberg, R. J. (2003b). Wisdom, intelligence, and creativity synthesized. Cambridge, UK: Cambridge University Press.
Sternberg, R. J. (2019). “Why people often prefer wise guys to guys who are wise: An augmented balance theory of the production and reception of wisdom” in The Cambridge handbook of wisdom. eds. R. J. Sternberg and J. Glück (Cambridge, UK: Cambridge University Press), 162–181.
Sternberg, R. J. (2020). 28-The Augmented Theory of Successful Intelligence. Cambridge, UK: Cambridge University Press.
Sternberg, R. J., Glaveanu, V., Karami, S., Kaufman, J. C., Phillipson, S. N., and Preiss, D. D. (2021). Meta-intelligence: understanding, control, and interactivity between creative, analytical, practical, and wisdom-based approaches in problem solving. J. Intelligence 9:19. doi: 10.3390/jintelligence9020019
Stewart, V. R., Snyder, D. G., and Kou, C.-Y. (2023). We hold ourselves accountable: a relational view of team accountability. J. Bus. Ethics 183, 691–712. doi: 10.1007/s10551-021-04969-z
Stogdill, R. M., and Shartle, C. L. (1948). Methods for determining patterns of leadership behavior in relation to organization structure and objectives. J. Appl. Psychol. 32, 286–291. doi: 10.1037/h0057264
Stolze, A., and Sailer, K. (2022). Advancing HEIs’ third-mission through dynamic capabilities: the role of leadership and agreement on vision and goals. J. Technol. Transf. 47, 580–604. doi: 10.1007/s10961-021-09850-9
Stoverink, A. C., Kirkman, B. L., Mistry, S., and Rosen, B. (2020). Bouncing back together: toward a theoretical model of work team resilience. Acad. Manag. Rev. 45, 395–422. doi: 10.5465/amr.2017.0005
Strode, D., Dingsøyr, T., and Lindsjorn, Y. (2022). A teamwork effectiveness model for agile software development. Empir. Softw. Eng. 27:56. doi: 10.1007/s10664-021-10115-0
Šūmane, S., Kunda, I., Knickel, K., Strauss, A., Tisenkopfs, T., des Ios Rios, I., et al. (2018). Local and farmers' knowledge matters! How integrating informal and formal knowledge enhances sustainable and resilient agriculture. J. Rural. Stud. 59, 232–241. doi: 10.1016/j.jrurstud.2017.01.020
Talat, A., and Riaz, Z. (2020). An integrated model of team resilience: exploring the roles of team sensemaking, team bricolage and task interdependence. Pers. Rev. 49, 2007–2033. doi: 10.1108/PR-01-2018-0029
Tang, D., and Wen, Z. (2020). Statistical approaches for testing common method bias: problems and suggestions. J. Psychol. Sci. 43:215. doi: 10.16719/j.cnki.1671-6981.20200130
Tannenbaum, S. I., Mathieu, J. E., Salas, E., and Cohen, D. (2012). On teams: unifying themes and the way ahead. Ind. Organ. Psychol. 5, 56–61. doi: 10.1111/j.1754-9434.2011.01406.x
Teece, D. J. (2007). Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance. Strateg. Manag. J. 28, 1319–1350. doi: 10.1002/smj.640
Teece, D. J. (2014). The foundations of enterprise performance: dynamic and ordinary capabilities in an (economic) theory of firms. Acad. Manage. Perspect. 28, 328–352. doi: 10.5465/amp.2013.0116
Teece, D. J. (2015). “A dynamic capabilities-based entrepreneurial theory of the multinational enterprise” in The eclectic paradigm: A framework for synthesizing and comparing theories of international business from different disciplines or perspectives. ed. J. Cantwell (London: Palgrave Macmillan), 224–273.
Teece, D. J. (2018). Managing the university: why “organized anarchy” is unacceptable in the age of massive open online courses. Strat. Organ. 16, 92–102. doi: 10.1177/1476127017732760
Teece, D. J. (2023). “The evolution of the dynamic capabilities framework” in Artificiality and sustainability in entrepreneurship. ed. R. Adams (Cham: Springer Nature), 113.
Thayer, A. L., Petruzzelli, A., and McClurg, C. E. (2018). Addressing the paradox of the team innovation process: a review and practical considerations. Am. Psychol. 73, 363–375. doi: 10.1037/amp0000310
Thomas, J. B., Clark, S. M., and Gioia, D. A. (1993). Strategic sensemaking and organizational performance: linkages among scanning, interpretation, action, and outcomes. Acad. Manag. J. 36, 239–270. doi: 10.2307/256522
Thomas, J. B., and McDaniel, R. R. (1990). Interpreting strategic issues: effects of strategy and the information-processing structure of top management teams. Acad. Manag. J. 33, 286–306. doi: 10.2307/256326
Türkmendağ, Z., and Tuna, M. (2022). Empowering leadership and knowledge management: the mediating role of followers' technology use. J. Organ. Change Manag. 35, 330–347. doi: 10.1108/JOCM-11-2020-0364
Tuten, T. L., Urban, D. J., and Bosnjak, M. (2002). “Internet surveys and data quality: a review” in Online social sciences. ed. B. Batinic (Hogrefe & Huber: Seattle, WA), 14–35.
Von Krogh, G. (2018). Artificial intelligence in organizations: new opportunities for phenomenon-based theorizing. Acad. Manage. Discoveries 4, 404–409. doi: 10.5465/amd.2018.0084
Von Krogh, G., Ichijo, K., and Nonaka, I. (2000). Enabling knowledge creation: How to unlock the mystery of tacit knowledge and release the power of innovation. Oxford, UK: Oxford University Press.
Von Krogh, G., Nonaka, I., and Rechsteiner, L. (2012). Leadership in organizational knowledge creation: a review and framework. J. Manage. Stud. 49, 240–277. doi: 10.1111/j.1467-6486.2010.00978.x
Vos, M. (2017). Communication in turbulent times: Exploring issue arenas and crisis communication to enhance organisational resilience. Jyväskylä, Finland: University of Jyväskylä, School of Business and Economics.
Walker, B. (2020). Resilience: what it is and is not. Ecol. Soc. 25:211. doi: 10.5751/ES-11647-250211
Walsh, J., and Ungson, G. (1991). Organizational memory. Acad. Manag. Rev. 16, 57–91. doi: 10.2307/258607
Wang, Y., Highhouse, S., Lake, C. J., Petersen, N. L., and Rada, T. B. (2017). Meta-analytic investigations of the relation between intuition and analysis. J. Behav. Decis. Making 30, 15–25. doi: 10.1002/bdm.1903
Wang, J., and Luo, L. (2013). A research on the relationship among team dynamic ability, innovation and development performance. East China Econ. Manag. 27, 167–173. doi: 10.3969/j.issn.1007-5097.2013.10.032
Weick, K. E., and Roberts, K. H. (1993). Collective mind in organizations: heedful interrelating on flight decks. Adm. Sci. Q. 38:357. doi: 10.2307/2393372
Wenzel, M., Danner-Schröder, A., and Spee, A. P. (2021). Dynamic capabilities? Unleashing their dynamics through a practice perspective on organizational routines. J. Manage. Inq. 30, 395–406. doi: 10.1177/1056492620916549
West, B. J., Patera, J. L., and Carsten, M. K. (2009). Team level positivity: investigating positive psychological capacities and team level outcomes. J. Organ. Behav. 30, 249–267. doi: 10.1002/job.593
Westman, M. (2001). Stress and strain crossover. Hum. Relat. 54, 717–751. doi: 10.1177/0018726701546002
Wilden, R., Devinney, T. M., and Dowling, G. R. (2016). The architecture of dynamic capability research identifying the building blocks of a configurational approach. Acad. Manage. Ann. 10, 997–1076. doi: 10.5465/19416520.2016.1161966
Will, T. E. (2016). Flock leadership: understanding and influencing emergent collective behavior. Leadersh. Q. 27, 261–279. doi: 10.1016/j.leaqua.2016.01.002
Williams, T. A., Gruber, D. A., Sutcliffe, K. M., Shepherd, D. A., and Zhao, E. Y. (2017). Organizational response to adversity: fusing crisis management and resilience research streams. Acad. Manag. Ann. 11, 733–769. doi: 10.5465/annals.2015.0134
Winter, S. G. (2003). Understanding dynamic capabilities. Strateg. Manage. J. 24, 991–995. doi: 10.1002/smj.318
Wu, M. (2010). Questionnaire statistical analysis practice: SPSS operation and application. Chongqing: Chongqing University Press.
Yammarino, F. J., Salas, E., Serban, A., Shirreffs, K., and Shuffler, M. L. (2012). Collectivistic leadership approaches: putting the “we” in leadership science and practice. Ind. Organ. Psychol. 5, 382–402. doi: 10.1111/j.1754-9434.2012.01467.x
Yao, W., Zhou, P., Yu, H.-L., and Liu, S.-W. (2025). Resilience of Chinese high-tech enterprises amid a pandemic: a knowledge management perspective. J. Knowl. Econ. 1, 1–29. doi: 10.1007/s13132-025-02740-7
Yeow, A., Soh, C., and Hansen, R. (2018). Aligning with new digital strategy: a dynamic capabilities approach. J. Strateg. Inf. Syst. 27, 43–58. doi: 10.1016/j.jsis.2017.09.001
Young, M., Pinheiro, R., and Avramovic, A. (2024). Unpacking resilience in higher education: investigating twenty-first-century shifts in universities’ academic cores. High. Educ. 87, 221–236. doi: 10.1007/s10734-023-01003-1
Yuan, R., Luo, J., Liu, M. J., and Yu, J. (2022). Understanding organizational resilience in a platform-based sharing business: the role of absorptive capacity. J. Bus. Res. 141, 85–99. doi: 10.1016/j.jbusres.2021.11.012
Zahra, S. A., Neubaum, D. O., and Hayton, J. (2020). What do we know about knowledge integration: fusing micro-and macro-organizational perspectives. Acad. Manage. Ann. 14, 160–194. doi: 10.5465/annals.2017.0093
Zerfass, A., Verčič, D., Nothhaft, H., and Werder, K. P. (2020). “Strategic communication: defining the field and its contribution to research and practice” in Future directions of strategic communication. ed. H. Nothhaft (London: Routledge), 159–177.
Zhang, L., Tang, Z., and Yu, F. (2017). A Ipd Team’s Dynamic Capabilities And Their Impact On Team Collaboration Satisfaction. Proceedings of the International Annual Conference of the American Society for Engineering Management, Huntsville, AL: American Society for Engineering Management (ASEM).
Zhou, H., and Long, L. (2004). Statistical remedies for common method biaes. Adv. Psychol. Sci. 12, 942–950. doi: 10.3969/j.issn.1671-3710.2004.06.018
Zhou, S. S., Zhou, A. J., Feng, J., and Jiang, S. (2019). Dynamic capabilities and organizational performance: the mediating role of innovation. J. Manage. Organ. 25, 731–747. doi: 10.1017/jmo.2017.20
Zhu, X. S., Wolfson, M. A., Dalal, D. K., and Mathieu, J. E. (2021). Team decision making: the dynamic effects of team decision style composition and performance via decision strategy. J. Manag. 47, 1281–1304. doi: 10.1177/0149206320916232
Zimmermann, A., Albers, N., and Kenter, J. O. (2021). Deliberating our frames: how members of multi-stakeholder initiatives use shared frames to tackle within-frame conflicts over sustainability issues. J. Bus. Ethics 178, 757–782. doi: 10.1007/s10551-021-04789-1
Keywords: team dynamic capability, knowledge creation, team resilience, wise leadership, communicative, interpretation, analytical
Citation: Yang H and Suntrayuth S (2025) Enhancing team resilience through team knowledge dynamics: a mediated approach. Front. Psychol. 16:1615909. doi: 10.3389/fpsyg.2025.1615909
Edited by:
Patrick S. W. Fong, Griffith University, AustraliaReviewed by:
Ferda Alper Ay, Cumhuriyet University, TürkiyeBin Mai, Texas A and M University, United States
Copyright © 2025 Yang and Suntrayuth. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Hong Yang, aG9uZy55YW5Ac3R1Lm5pZGEuYWMudGg=