CC BY
0Научная статья УДК 330
doi: 10.47576/2949-1916.2025.1.1.024
building multilevel resilience through adaptive
culture
Kaifeng Yan
St. Petersburg State University, St. Petersburg, Russia, [email protected]
Abstract. Escalating environmental turbulence compels organizations to undertake adaptive organizational changes that may cause overstress issues. Building resilience is critical for mitigating reform-induced pressures and serves as an effective response. This study focuses on the operating mechanisms of three levels of resilience: employee, team, and organizational, and how adaptive culture promotes the development of the multilevel resilience system. Using the partial least squares structural equation modeling (PLS-SEM) approach to analyze the answers of 86 managers from Chinese companies, the author finds a bottom-up process in multilevel resilience systems. Adaptive culture promotes the development of this system through two pathways: (1) directly influences employee resilience, team resilience, and organizational resilience; (2) influences three levels of resilience through a bottom-up chain mediation effect. These findings extend the literature on organizational culture and multilevel resilience and provide guidance for managers to effectively manage stress and cope with external challenges by building a culturally driving resilience system.
Keywords: adaptive culture; multilevel resilience; organizational resilience; team resilience; employee resilience; stress management.
For citation: Kaifeng Yan. Building multilevel resilience through adaptive culture. Regional and branch economy, 2025, no. 1, pp. 188-198. doi: 10.47576/2949-1916.2025.1.1.024.
формирование многоуровневой устойчивости с помощью адаптивной культуры
Кайфэн Янь
Санкт-Петербургский государственный университет, Санкт-Петербург, Россия, [email protected], [email protected]
Аннотация. Растущая турбулентность окружающей среды вынуждает организации проводить адаптивные организационные изменения. Повышение устойчивости имеет решающее значение для смягчения давления, вызванного реформами, и служит эффективным ответом. Исследование посвящено механизмам функционирования трех уровней устойчивости: сотрудников, команды и организации, а также тому, как адаптивная культура способствует развитию многоуровневой системы устойчивости. Используя метод моделирования структурных уравнений методом наименьших квадратов в частных производных (PLS-SEM) для анализа ответов 86 менеджеров китайских компаний, автор обнаружил восходящий процесс в многоуровневых системах обеспечения устойчивости. Адаптивная культура способствует развитию этой системы двумя путями: напрямую влияет на жизнестойкость сотрудников, команды и организации; влияет на три уровня жизнестойкости через посреднический эффект восходящей цепочки. Эти результаты дополняют литературу по организационной культуре и многоуровневой устойчивости и дают руководителям
рекомендации по эффективному управлению стрессом и преодолению внешних вызовов путем создания системы устойчивости, основанной на культурных принципах.
Ключевые слова: адаптивная культура; многоуровневая устойчивость; устойчивость организации; устойчивость команды; устойчивость сотрудников; управление стрессом.
Для цитирования: Кайфэн Янь. Формирование многоуровневой устойчивости с помощью адаптивной культуры // Региональная и отраслевая экономика. - 2025. -№ 1. - С. 188-198. doi: 10.47576/2949-1916.2025.1.1.024.
Introduction
Amidst the fluctuating market demands, contiguous technological innovations, and the introduction of new policies, companies are confronted with an increasingly volatile external environment. Such a turbulent environment forces companies to restructure their internal frameworks to better adapt to these evolving conditions. During the process of transformation, individuals and teams within the organization inevitably face significant stress, which requires companies to implement a series of intervention measures to enhance their resilience and alleviate the over-stress, ensuring a smooth transition through the change.
Resilience is a multi-dimensional concept that reflects a dynamic capacity to adapt to an external changing environment. Establishing resilience in organizations means shifting organizational stress management from a passive response to an active construction of stress-resistance mechanisms. Moreover, adversity is considered a necessary condition for demonstrating resilience, thus resonating with the literature on stress in the workplace. Within organizations, resilience is often discussed on three levels: employee, team, and organizational. These three levels of resilience are interrelated and form a hierarchical structure, with employee resilience (ER) underpinning team resilience (TR) and finally supporting organizational resilience (OR). The bottom-up mechanism among three levels of resilience forms multilevel resilience (MR) systems. Building MR enables employees and teams to make more positive appraisals when confronted with stressors, fostering a more optimistic attitude toward challenges. MR also facilitates innovation at the organizational level, empowering organizations to achieve sustainable competitive advantage in environmental turbulence.
Despite the obvious benefit of MR in effectively managing stress, resolving conflicts, and fostering positive organizational behaviors, empirical research on building MR remains scarce. The internal mechanisms of MR have yet to be fully elucidated. Moreover, research on antecedents that simultaneously influence three levels of resilience is also very limited [20].
Organizational culture is related to employee performance and organizational outcomes. Recent studies suggest that organizational culture, particularly cultures with adaptive characteristics, may promote the development of resilience. The relationship between adaptive culture (AC) and organizational resilience has been empirically proven by Madi Odeh et al.'s (2023) [19] study, in which AC plays a mediator role between transformational leadership and OR. However, there are still gaps in the research regarding the mechanisms through which AC drives resilience at cross-levels.
This study explores MR's operating mechanisms and the relationship between AC and MR. Dynamic capabilities theory (Teece, 2007) [25] and multilevel organizational theory (Klein & Kozlowski, 2000) [14] are used when building the theoretical framework. This study uses the data from Chinese managers. The study uses data from managers in Chinese firms, which takes into account the complex environmental turbulence faced by China as an important emerging economy and particularly high-stress workplace climate. In this context, stress becomes a crucial issue for managers. Therefore, the context of China has become a valuable example for establishing the AC-MR system as an effective stress management strategy.
Multilevel resilience
The concept of resilience was initially discussed in the field of ecology. According to Holling (1973)
[13], resilience refers to the ability to "absorb change and disturbance and still maintain the same relationships between populations or state variables" (p. 14). It, together with stability, consists of key measures of the persistence of systems. Subsequently, the concept of resilience has gradually been introduced into the management field. For example, Wildavsky (1991) [27] contrasted anticipation with resilience, arguing that resilience is more suitable for coping with complex and dynamic environments. Compared with anticipation, which relies on predicting risks and intervening in advance, resilience focuses on coping with unforeseen dangers after they occur and learning to bounce back. Besides, resilience enables the system to enhance its future capacity to cope through learning and adaptation. Early research focused more on "Bounce back," similar to its definition in physical sciences. Recent studies have begun to emphasize the "Bounce forward" of resilience, which refers to the development of new capabilities in adversity and the extended ability to adapt to the environment and create new opportunities (Lengnick-Hall et al., 2011) [16]. Moreover, the concept of resilience can be applied across disciplines, such as management, physical, and ecology science, reflecting its applicability in multi-dimensions. Raetze et al. (2022) [23] further categorized organization-related resilience into 10 clusters and indicated that MR belongs to the C10 (multilevel resilience) and focuses on how resilience is interrelated across levels. In this study, MR refers to the adaptive systems formed through the dynamic interaction of cross-level resilience of employees, teams, and organizations.
ER refers to the individual capacity to adapt continuously in the workplace (Kuntz et al., 2016) [15]. This concept is widely discussed in the field of positive psychology (Luthans et al., 2005) [18]. The research on ER or individual resilience in the workplace is generally related to dealing with specific workplace stress. Resilient employees demonstrate greater flexibility, energy, and mental agility; therefore, they may sustain positive emotions and actively pursue solutions in uncertain environments.
Compared to ER and OR, the concept of TR is relatively new and attracts increasing attention. West et al. (2009), based on the positive organizational behavior (POB) criterion (Luthans et al., 2007) [17], consider TR along
with team efficacy and team optimism as three variables to evaluate team-level POB capacities and define TR as a team's capacity to bounce back from threats to well-being. This means that the definition of TR is rooted in individual resilience. However, Alliger et al. (2015) point out that although resilience can operate at both individual and team levels, individual resilience is not synonymous with TR. A group of high-resilient individuals may not necessarily lead to a resilient team since TR emphasizes communication, collaboration, and mutual support among team members. Therefore, TR is not simply the sum of individual resilience. In this study, we follow Alliger et al. (2015) [1], who defined TR as a team's capacity "to withstand and overcome stressors in a manner that enables sustained performance" (p. 177). Under pressure, resilient teams effectively address challenges in a way that maintains their well-being and resources and achieves "bounce back and forward."
OR refers to the capacity of an organization as a whole to maintain stability, recover quickly, and adapt when facing adverse conditions (Hillmann & Guenther, 2021) [12]. Resilience at individual and organizational levels are interlinked and mutually influence each other. However, just as with the relationship between resilience at individual and team levels, resilient individuals do not necessarily lead to high levels of OR, as OR is more prominently reflected in collective actions and organizational-level capabilities. OR not only helps organizations survive in the face of crises but also enhances their competitiveness through diverse strategic options and effective decision-making mechanisms.
Multilevel research is capable of more comprehensively capturing the complexity of organizational behavior (Klein & Kozlowski, 2000) [14]. However, most of the MR research is theoretical, and the empirical studies are very limited (Raetze et al., 2022). In this study, the essence of MR lies in its internal cross-level emergent mechanism. According to multilevel organizational theory (Klein & Kozlowski, 2000), an organization is a multilevel system that exits bottom-up emergent processes. For example, behaviors, perceptions, and attitudes at the individual level may emerge at higher levels, such as the team or organizational level, through interactions and dynamic processes. Based on this theory, MR, as a multilevel adaptive system, also exhibits a bottom-up process. The
development of resilience at lower levels may facilitate the emergence of resilient behaviors at higher levels, thereby achieving a systemic risk resistance and stress tolerance effect that is greater than the sum of its parts. For instance, high-resilient team members exhibited proactive behaviors under stress (e.g., spontaneously adjusting work processes and actively sharing risk information), which may enhance team trust and effective team interaction through social learning and role modeling within the team and finally promote TR. Teams are an important resource for organizational adaptive learning, and through adaptive behaviors and innovation practices at the team level, organizations can better cope with challenges. Resilient teams emphasize learning behaviors, and the adaptive experiences gained through reflection and integration of lessons can be absorbed by the organization to enhance its emergency response speed. Additionally, organizations can maintain stability during crises and quickly return to normal operations by establishing redundancy resources. Resilient teams can provide risk buffers for organizations through multi-skilled team member configurations and alternative decision-making pathways, enabling the organization to bounce back more quickly.
Based on the above perspective, the author proposes the following hypothesis:
H1: ER is positively related to TR.
H2: TR is positively related to OR.
H3: TR mediates the relationship between ER and OR.
Adaptive culture and multilevel resilience
Organizational culture refers to "a relatively stable, enduring set of values, beliefs, assumptions, and symbols shared in the organization" (Verdu-Jover et al., 2018) [26]. However, the current turbulent environment imposes continuous adaptive pressures on culture, rendering change an inherent attribute of culture.
AC is an important branch of organizational culture and helps organizations better cope with challenges in dynamic environments by emphasizing values oriented toward change and action (Costanza et al., 2016) [6]. According to Costanza et al. (2016), AC refers to a "pattern of shared beliefs, values, and behaviors that indicate the organization is aware of and concerned about environmental changes and oriented toward agile and flexible action to
address such changes." (p. 4). Compared with static organizational cultures, the adaptive nature of culture can better respond to environmental pressures. There are nine characteristics of AC: (1) external focus to adapt to an experimentation environment; (2) anticipation to foresee future trends and anticipate change; (3) openness to change; (4) taking a risk in response to change;
(5) confidence in their ability to cope with change;
(6) developing capabilities to address changes and future challenges; (7) collaborative action to work as one unit in planning and developing solutions; and (8) executing and (9) sustaining change(Costanza et al., 2016).
Some studies focus on the positive outcome of AC. For example, AC can promote product/ service innovation outcomes (Verdu-Jover et al., 2018). Costanza et al. (2016) point out that organizations with AC are more likely to survive. Chalab and Chraimukh (2023) [3] propose that AC enhances organizational flexibility, which in turn promotes structural differentiation, finally improving the organization's ability to respond to environmental change. In this context, the concept of organizational flexibility overlaps with that of OR, meaning that resilient organizations typically require the ability to flexibly adjust their internal structures and processes to adapt to environmental changes.
Dynamic capabilities theory provides a systematic explanatory framework for AC and MR. This theory focuses on how firms integrate, build, and reconfigure internal and external resources and capabilities to generate new capabilities that enable adaptation to rapidly changing environments (Teece et al., 1997) [25]. Dynamic capabilities are referred to as first-order capability. Compared with zero-order capabilities (organizational capabilities), which are oriented toward organizational survival and emphasize the effective exploitation of existing resources, dynamic capabilities are development-oriented and focus on the effective exploration and implementation of new opportunities. According to dynamic capabilities theory (Teece, 2007), there are three core dimensions for dynamic capabilities:(a)sensing(andshaping)opportunities and threats, (b) seizing opportunities, and (c) managing threats/ transforming/reconfiguration. Dynamic capabilities support the realization of MR, and the characteristics of AC help drive the three dimensions of dynamic capabilities, thereby facilitating the development of MR.
At the employee level, (1) external focus and (2) anticipation help employees (a) perceive changes in the environment, such as technological iterations and changes in job requirements. By promoting (6) the adjustment and development of employees' capabilities, they can prepare for the challenges. The (4) risk-taking and (5) self-confidence support employees in taking swift action, such as learning new skills or applying for internal transfers. This enables employees to leverage existing resources and transform challenges into new opportunities, thereby (b) seizing them. (3) openness and (8) executing and (9) sustaining change facilitate employees in (c) adjusting their cognitive frameworks, thereby fostering a change/growth-oriented mindset. The author proposes the following hypothesis:
H4. AC is positively related to ER.
At the team level, the (1) external focus and (7) collaborative action promote (a) information sharing within the team, such as customer feedback and competitor dynamic, and gradually lead to the formation of a shared team routine. The (8) execution capability and (4) risk-taking can drive rapid experimentation and product iteration within the team and integrate diverse skills through (7) cross-functional collaboration. This helps the team (b) seize new opportunities in the face of challenges. The (9) sustaining change and (3) openness support the team in adjusting its division of labor and decision-making processes, thereby (c) enhancing the team's reconfiguration abilities. Therefore, the author proposes the following hypothesis:
H5: AC is positively related to TR.
At the organizational level, (1) external focus and (2) anticipation drive organizations to establish environmental monitoring systems to (a) identify external risks. The (8) execution capability and (7) collaborative action support the organization in rapidly reallocating resources during turbulent periods, thereby reducing response time. The (9) sustaining change, (3) openness, and (6) capability development promote (c) structural reorganization, thereby enhancing overall resilience. Therefore, the author proposes the following hypothesis:
H6: AC is positively related to OR.
Integrating dynamic capabilities theory (Teece, 2007) and multilevel organizational theory (Klein & Kozlowski, 2000). We can see how AC drives MR through building dynamic capabilities. In terms of (a) sensing capabilities, (1) external focus, (2) anticipation, and (3) openness prompt employees to perceive external information, such as customer feedback, identifying personal skill gaps, and triggering learning motivation. The behavior of learning enhances ER. High-resilient team members establish shared routines in cross-functional teams, thereby enhancing TR. Strategic departments integrate data from multiple sources to effectively anticipate external risks. In terms of (b) seizing capabilities, (7) collaborative action, (8) execution changes, and (4) risk-taking encourage employees to seize opportunities and propose innovative solutions. Resilient employees can better engage in cross-team collaboration, integrating resources to form
AC ER
TR
_ H2
OR
a. The direct effect model
H3
H7
b. The chain mediation model
Figure 1. Empirical Model
an agile project team. Resilient teams can rapidly experiment and iterate, driving organizational resource reallocation and configuration. Finally, in terms of (c) reconfiguration capabilities, (9) sustaining change, (6) capabilities development, and (5) self-confidence help employees acquire new skills through training to adapt to role changes, thereby ER. Teams composed of resilient members can more effectively adjust their division of labor, creating resilient teams. Organizations with resilient teams demonstrate greater structural flexibility when reconfiguring their business models. Based on the arguments, the author proposes the following hypothesis:
H7: ER and TR sequentially mediate the relationship between AC and OR.
The age distribution indicates a diverse representation across different age groups. The majority of respondents aged from 36 to 50 (53.5 %). The gender distribution is nearly balanced, with 58.1 % females and 41.9 % males. The industry affiliation of respondents spans a wide array of sectors, providing a robust test bed for generalizability across different business environments (see Table 1).
Measures
All measure variables were used on a seven-point Likert scale, where 1 means strongly disagree, and 7 means strongly agree.
The overall empirical model can be found in Figure 1:
Methodology Data collection
The author utilized a dataset from managers in Chinese companies. The data collection commenced in May 2024 and lasted for three months. The author contacted potential respondents directly via telephone and WeChat (a popular social platform in China) and sent the survey links to those who accepted the invitation. Since all items were obligatory to answer, there was no missing data. Through the online survey, the author ultimately received 86 answers. Table 1 presents the basic demographic information of the respondents.
AC was measured using a nine-item scale developed by Costanza et al. (2016). These items represent the nine characteristics of AC mentioned before. One example item to measure external focus is that "Our company pays attention to its external environments, especially our customers. Our company is able to read and interpret signals from environments."
ER was measured using the 9-item EmpRes scale developed by Näswall et al. (2015) [22]. An example item is "Employees in our company can effectively collaborate with others to handle unexpected challenges at work."
Table 1. Respondents Profile
Frequency Percent Valid Percent%
Age Lower than 35 29 33.7 33.7
36 to 50 46 53.5 53.5
Higer than 51 11 12.8 12.8
Gender male 36 41.9 41.9
female 50 58.1 58.1
Industry Insurance 2 2.3 2.3
Hospitality 1 1.2 1.2
E-commerce 1 1.2 1.2
Real Estate 7 8.1 8.1
Service 4 4.7 4.7
Finance 26 30.2 30.2
Express Delivery 1 1.2 1.2
Food Import and Export 1 1.2 1.2
Retail 2 2.3 2.3
Manufacturing 32 37.2 37.2
Telecommunications 4 4.7 4.7
Aging Industry 5 5.8 5.8
TR was measured by a 7-item scale developed by Salanova et al. (2013) [24] based on Mallak's (1998) [20] principles for implementing resilience in organizations. An example item is "In difficult situations, our team tries to look for the positive side."
OR was measured by a 10-item scale proposed by Connor and Davidson (2003) [5] and Campbell-Sills and Stein (2007) [2]. An example item is "Our organization has been able to adapt to changes because of environmental turbulence."
Data analysis
This study used PLS-SEM with the software SmartPLS to test the empirical model. This technique is widely used for testing variance-based structural equation models and is very suitable for estimating complex models (Hair et al., 2019) [7]. This study used the bootstrapping approach (5000 resamples) to assess the path coefficient.
Results
Measurement model assessment The reliability and validity scores of the constructs can be found in Table 2.
For the external model, the outer loading of each item was assessed. A given indicator can be left if its loading is greater than 0.5 (Hair et al., 2022) [10]. All loadings significantly exceeded the threshold and, therefore, were retained.
For testing internal consistency reliability, composite reliability (CR), reliability coefficient (Rho_A), and Cronbach's alpha were used. All constructs exceeded the threshold of 0.70 (Hair et al., 2011) [9], which means that all constructs have adequate internal consistency.
For testing convergent validity, average variance extracted (AVE) was used. The threshold recommended by Chin (1998) [4] was at least 0.50. AVE for all constructs significantly exceeded the threshold. Therefore, all the constructs in this study had sufficient convergent validity.
Table 2. Reliability and Validity
Factor loading Cronbach's Alpha rho_A CR ave
AC1 0.842 0.955 0.965 0.962 0.741
AC2 0.864
AC3 0.671
AC4 0.715
AC5 0.914
AC6 0.945
AC7 0.928
AC8 0.923
AC9 0.902
ER1 0.571 0.911 0.925 0.928 0.594
ER2 0.609
ER3 0.808
ER4 0.862
ER5 0.872
ER6 0.815
ER7 0.762
ER8 0.703
ER9 0.869
TR1 0.819 0.932 0.935 0.945 0.713
TR2 0.876
TR3 0.896
TR4 0.884
TR5 0.869
TR6 0.798
TR7 0.758
OR1 0.883 0.973 0.973 0.976 0.803
Factor loading Cronbach's Alpha rho_A CR ave
OR2 0.840
OR3 0.911
OR4 0.899
OR5 0.901
OR6 0.899
OR7 0.898
OR8 0.906
OR9 0.918
OR10 0.901
The discriminant validity was tested by testing the HTMT rate. Table 3 showed that all HTMT values were below the 0.9 threshold (Hair et al., 2017) [8], therefore fulfilling discriminant validity. For testing model fit, standardized root mean
Structural model assessment In the first step, the author tests empirical model (a), which is about whether AC is directly related to three levels of resilience. The result shows that AC -> ER (&= 0.597, p<0.001), AC -> TR (&=0.640, p<0.001), and AC -> OR (&=
In the second step, the empirical model (b) was tested to determine whether the MR system exists as a bottom-up emergent process and whether AC promotes the MR system. The direct effect tests show that AC -> ER (&= 0.587, p<0.001), ER -> TR (&= 0.827, p<0.001), and TR -> OR (&= 0.726, p<0.001). These results show that ER-positive influences TR and TR positively influence OR, therefore supporting H1 and H2. The indirect effect results show that ER -> TR
square residual (SRMR) was used. The SRMR is 0.071, which is lower than the threshold of 0.078 (Henseler et al., 2016) [11], showing that the overall model fit was adequate.
0.830, p<0.001). This means that AC can directly influence ER, TR, and OR. According to the path coefficient, AC has the strongest influence on OR, then on TR, and the least influence on ER. The result supports H4, H5, and H6 (see Table 4).
-> OR (&= 0.601, p<0.001), which means that TR serves as a mediator between ER and OR, therefore proving the existence of a bottom-up process of MR and supporting H3. The indirect effect result also shows that AC -> ER -> TR -> OR (&= 0.359, p<0.001), which means that AC can promote MR through the emergent process in which ER and TR serve as mediators. The result supported H7 (see Tables 5 and 6).
Table 3. Heterotrait- Monotrait Ratio (HTMT)
AC ER OR TR
AC
ER 0.591
OR 0.855 0.653
TR 0.641 0.882 0.746
Table 4. Result of Model (a)
Path coefficient Standard Deviation T value P value
AC -> ER 0.597 0.112 5.045 0.000
AC -> TR 0.640 0.077 8.086 0.000
AC -> OR 0.830 0.057 14.603 0.000
Table 5. Result of Model (b): The Direct Path
Path coefficient Standard Deviation T value P value
AC -> ER 0.587 0.112 5.033 0.000
ER -> TR 0.827 0.040 20.737 0.000
TR -> OR 0.726 0.084 8.515 0.000
Table 6. Result of Model (b): The Indirect Path
Path coefficient Standard deviation t value P value
AC -> ER -> TR -> OR 0.359 0.102 3.225 0.001
ER -> TR -> OR 0.601 0.080 7.330 0.000
Discussion and conclusion The empirical findings provide robust evidence for the dual pathways through which AC drives MR. First, the direct effect of AC on ER, TR, and OR posits that culture serves as the soft infrastructure enabling sensing, seizing, and reconfiguring capacities. The hierarchical strength of AC's influence (strongest at the organizational level and weakest at the individual level) suggests that cultural attributes (e.g., collaborative action, execution of change) are more critical for macro-level strategic agility than micro-level psychological adaptation.
Second, the bottom-up mediation chain (AC -> ER -> TR -> OR) validates multilevel organizational theory's emphasis on emergent processes. ER's role as the foundational mediator implies that resilient employees collectively "scale up" resilience through team-level coordination, which is subsequently institutionalized as organizational routines.
Finally, comparing path coefficients for the direct effect of AC on OR and the indirect effect reveals that the direct effect is stronger than the indirect effect. This suggests that organizational dynamic capabilities, such as top-level decision-making and structural flexibility, operate more efficiently in driving outcomes than the transmission mechanisms mediated by individual and team-level resilience. Theoretical contribution This study makes three key theoretical advances. First, by empirically validating the bottom-up emergence mechanism (AC ^ ER ^ TR ^ OR), the author addresses the theoretical nature of current MR literature (Raetze et al., 2021; Visser & Jacobs, 2019). The hierarchical amplification of resilience from individual adaptation to institutionalized organizational routines provides a processual framework that
bridges multilevel theory (Klein & Kozlowski, 2000) with dynamic capabilities literature.
Second, the finding is consistent with the opinion of Muadzah and Suryanto (2024) [21], who propose that cultural factors such as flexibility, adaptability, and open communication enhance resilience, and building a supportive and adaptive culture is vital for organizational success in dynamic environments. This study provides empirical support from Chinese data and highlights the dual functionality of AC in promoting resilience in organizations, thereby contributing to a comprehensive understanding of the mechanism between AC and resilience.
Finally, grounded in the perspective that MR serves as an effective response mechanism to stressors and environmental turbulence, this study demonstrates how MR dynamically coordinates individual coping, team buffering, and organizational reconfiguration under turbulent environments, contributing to the stress management literature. Managerial implications This study reveals that AC can drive MR through dual pathways, providing practical guidance for managers to build a resilience system under stressful conditions,
The result shows that AC has the strongest direct effect on OR, indicating that cultural factors such as collaborative action and the ability to execute sustainable changes are core drivers for macro-strategic agility. Managers can assess their organizational culture and qualify the results for nine AC characteristics. They can also design cultural intervention measures tailored to the resilience needs of different levels.
Secondly, the bottom-up relationship among the three levels of resilience indicates that ER is the foundational trigger of the MR system, which means that companies may focus on
cultivating the resilience of front-line employees and enhancing the transmission efficiency of resilience across levels by encouraging cross-functional and cross-departmental collaboration among employees and teams.
Finally, the direct effect of AC on OR is stronger than its indirect effects, implying the necessity of balancing investment in both pathways and establishing a dual-track resilience investment plan. For example, more resources could be allocated to developing dynamic capabilities at the macro level. Moreover, companies could establish a multilevel stress monitoring system. When stress indices are excessively high, direct intervention targeting OR can be activated promptly to avoid response delays caused by over-reliance on the chain reaction between ER, TR, and OR.
Limitations and future research suggestions
The findings of this study are primarily based
on sample data from Chinese companies and may be influenced by China's institutional and cultural context. For example, the Confucian tradition of collectivism may enhance the role of relational networks in resilience transmission. In contrast, in countries with low power distance cultures, individualism may alter the direct effect pathway of AC on OR. Therefore, it is recommended that the model be validated in different cultural configurations, such as by comparing the formation mechanisms of MR in high power distance and egalitarian cultures, to enhance the generalizability of results.
Additionally, external factors may weaken the culture-driven mechanisms. Hence, it is suggested that future models incorporate the external environment as a moderating variable, such as policy uncertainty or the pace of technological innovation within industries.
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Information about the author
KAIFENG YAN - Graduate School of Management (GSOM), St. Petersburg State University, St. Petersburg, Russia, [email protected]
Сведения об авторе
КАЙФЭН ЯНЬ - Высшая школа менеджмента (ВШМ), Санкт-Петербургский государственный университет, Санкт-Петербург, Россия, [email protected]
