Cultural Effects on Organizational Resilience: Evidence from the NAFTA Region

To meet the challenges arising from turbulent environments, and to generate opportunities, organizations must develop resilience capacity (Hillmann et al. 2018; Lengnick-Hall et al. 2011). However, capturing the concept is challenging, and literature is still divided and inconsistent with the definitions and measurement of organizational resilience (Linnenluecke 2017; Hillmann and Guenther 2020).³ Recently, researchers have relied on capability-based theorizing for conceptualizations (Hillmann and Guenther 2020; Duchek 2020; Williams et al. 2017). Resilience goes beyond restoration of organizational functionality, and concerns the advancement of organizational processes and the development of new capabilities (Duchek 2020; Lengnick-Hall et al. 2011). In our study, we also drew upon a capability-based conceptualization, and have defined resilience as a set of organizational capabilities by which firms anticipate trends and threats, make sense of, and cope effectively with adversity, and adapt to changes to produce a dynamic capability that is directed towards facilitating organizational change (Limnios et al. 2014; Duchek 2020; Hillmann et al. 2018). To account for the dynamic perspective of resilience, researchers have added a process-based perspective to resilience (Duchek 2020; Williams et al. 2017) and have described capabilities that relate to before, during, and after times of crises: capabilities for durability, organizing and adjusting, responding to major disturbances, and feedback. They have provided a nuanced method of incorporating organizational, as well as collective and individual levels, and describing related endowments (Williams et al. 2017).

The importance of employees and cognitive capability endowments must also be recognized to ensure resilience (Lengnick-Hall et al. 2011). By investing in a deep talent pool, motivated and innovative employees that are committed to change (Nicholls-Nixon 2005; Ortiz-de-Mandojana and Bansal 2016; Shin et al. 2012) with a deep social fabric of goodwill (Lengnick-Hall and Beck 2005; Pal et al. 2014) can be attracted. Resilient organizations are more efficacious (Vogus and Sutcliffe 2007) through a staunch acceptance of reality, a deep belief that life is meaningful, and an ability to improvise (Coutu 2002). A strong sense of identity and purpose is another characteristic of a resilient organization, their teams, and employees (Freeman et al. 2004; McCann et al. 2009). Cognitive capability endowments further support the ability to anticipate trends and threats (Williams et al. 2017) and allow for the elimination of as many risks and threats as possible (McCann et al. 2009; Rerup 2001; Somers 2009). These organizations invest in enterprise-wide risk management systems (Starr et al. 2003) and use critical insights in creative and flexible ways (Williams et al. 2017). They build routines that not only reduce complexity, but also allow them to absorb and cope with it (Lengnick-Hall and Beck 2005). These are, for example, scenario planning (Bradfield et al. 2005; MacKay and McKiernan 2010; McCann et al. 2009) and organizational ambidexterity (Chermack et al. 2010; Clement and Rivera 2017). Organizations that put emphasis on anticipating events are more likely to continuously monitor and scan the environment or simulate possible unexpected events (Vogus and Sutcliffe 2007) through which they “combine and deploy knowledge and repertoires of action to resolve the problems at hand” (Williams et al. 2017, p. 744). Cognitive capability endowments further include the ability to quickly assimilate new information and recognize changes in the environment, to make sense of them, and direct attention accordingly (Williams et al. 2017). The ability to make sense of a situation is a critical one, as it precedes problem-solving (Weick 1993) and is essential to avoid failure (Chan 2011; Issel and Narasimha 2007); it helps to translate information about changes in the environment, and to understand specific developments and their influence on the organizations’ goals and success (Hamel and Välikangas 2003; Mantere et al. 2012; Weick and Sutcliffe 2007). As the complexity and uncertainty of the environment makes it impossible to anticipate all events, resilience is also about the ability to resist disturbances, recover after adverse situations (e.g., Horne and Orr 1998), or adapt to unexpected events (Lengnick-Hall and Beck 2005). Perceiving crises as an opportunity and cultivating a positive organizational culture supports organizations in “buffering” bad news (French and Holden 2012; Jackson and Dutton 1988), and thus, makes them more resilient. Resilient organizations find creative, prompt responses to minimize the impact of unexpected events (McCann et al. 2009; Weick and Sutcliffe 2007).

Capabilities for durability further include behavioral capability endowments, which include being comfortable with uncertainty (Williams et al. 2017), displaying an openness to change (McCann et al. 2009), and a staunch acceptance of reality where change is needed (Coutu 2002). They further include relational capability endowments that are represented in relationships, i.e., coordinative and cooperative practices, that were essential in overcoming challenges (Gittell et al. 2006; Williams et al. 2017). Trust, and well-established networking relationships as protective factors are an intangible resource endowment that has been shown to be important in recovering quickly from a disaster (Williams and Shepherd 2016; Danes et al. 2009). Maintained relationships and strengthened partnerships provide agility (Sheffi 2005; Starr et al. 2003) or put emphasis on strategic alliances to reduce and spread risk (Pal et al. 2014).

Researchers have recently begun investigating the multilevel nature of organizational resilience (e.g., Tasic et al. 2019; Williams et al. 2017; Lengnick-Hall et al. 2011).

Mallak (1998) and Horne and Orr (1998) have already discussed the role of individuals in strengthening organizational resilience. For example, Mallak (1998) argues that organizations can only be as resilient as their employees. Resilient individuals demonstrate great persistence through their high self-efficacy (Schwarzer and Warner 2013) and function well under stress and pressure (Mallak 1998). Coutu (2002) highlights that in a resilient organization, employees have a sense of reality which includes a realistic understanding of the situation. The author argues that plain optimism can lead to denial or ignorance of the situation (Coutu 2002). Furthermore, they see the big picture and, due to their realistic assessment of the situation, have a tolerance for ambiguity that is required in turbulent environments and crises (McCann et al. 2009). A resilient organization has employees that learn from their past mistakes and are open to change, which also involves a continuous willingness to learn and acquire new knowledge from past adversities (Williams et al. 2017; McCann and Selsky 2012). However, Horne and Orr (1998) point out that resilient employees do not always equal a resilient organization. These arguments are elaborated upon by Riolli and Savicki (2003, p. 231) who state that, on the one hand, organizational climate can strengthen individuals and, vice versa, organizations can benefit from its employee’s coping styles. On the other hand, a bad organizational climate can undermine an individual’s resilience, and a high-pressure task environment can drain individual resources and make them less resilient. Additionally, individuals with antagonistic behavior can weaken the organizational climate, and reduce organizational resilience. In crisis situations, individuals’ informal social relations become important as they “build unconventional bridges across organization to supplement unavailable formal connections (Tasic et al. 2019, p. 717)”. Employees also play an essential role in anticipating and preparing for crisis situations. When employees observe and (mis)interpret their environment, their responses are enacted through the organizational members that give meaning to them (Weick 1969, 1993; Whiteman and Cooper 2011), depending upon how organizational members’ attention is structured by organizational arrangements and information collection practices (Baum and Rowley 2005).

There are even less theoretical considerations for the influence of team resilience on organizational resilience. Although research on resilience at the team level is growing (e.g., Chapman et al. 2020; Morgan et al. 2013; Carmeli et al. 2013), few studies on measuring team resilience exist (e.g., Sharma and Sharma 2016); research on it is still in its infancy (Chapman et al. 2020). In their study on measuring team resilience, Sharma and Sharma (2016, p. 37) define team resilience as the “ability to either flourish under difficult situations, manage and adapt to significant change or stress, or simply recuperate from a negative experience are less likely to come across the potentially detrimental effects of intimidating situations (West et al. 2009)”. Morgan et al. (2013) propose that team resilience is a psycho-social process that protects individuals in a group from the negative stressors they collectively encounter. Team resilience involves processes in which team members use individual and collective resources to deal with adversity (Morgan et al. 2013), including a high tolerance for ambiguity and uncertainty, and the ability to function well under pressure and stress. Members of resilient teams are well-integrated into key decision-making processes and are good multi-taskers.

Following Cooper (2013), and comparable to arguments of Mallak (1998), the dynamics of each team member’s characteristics of resilience ensure a high level of productivity during turbulent times (Cooper 2013). Thus, resilient teams include members that are open to change, can see the big picture, are able to quickly acquire and apply new skills and knowledge, and have adopted the organization’s values and beliefs. In as much as an individual’s resilience can positively influence organizational resilience processes (Mallak 1998; Coutu 2002), this link can be assumed to be similar for team-level resilience. Resilient teams can therefore positively influence organizational resilience processes.

Another important aspect is collective efficacy (Morgan et al. 2013) which includes team members appreciating their collective well-developed problem-solving skills, inventiveness and creativity, their ability to making sense of ambiguous situations, and demonstration of moral and physical courage. Furthermore, Putnam (1995) argues that social capital (i.e., social connections, norms, and trust) supports team members in achieving common goals, which, following Sharma and Sharma (2016), are an important factor in resilient teams. This also includes teams having mentors or coaches, and team members that support and trust each other, and are well connected so that they can quickly change roles and responsibilities. This, in turn, positively influences resilience processes at the organizational level.

Low Kim Cheng (2007) shows that Singaporean companies are resilient as a result of their cultural background focusing on continuous learning and growth. In a study by Gupta et al. (2010), the ‘ubuntu’ principle is used to explain the family resilience of indigenous African businesses—this study is a rarity, because although the relationship of organizational culture and organizational resilience often features in studies, only few mention the role of national culture (e.g., Acar and Winfrey 1994; Collis 1991). A national culture is characterized by negotiable and non-negotiable values (Schein 2001), and will have a stronger influence on a person’s attitude and behavior than organizational culture, if a non-negotiable national culture value conflicts with an organizational culture value (Schein 2001).

Although research around effects of culture on organizational resilience is sparse, some prior research in psychology has been carried out, which this study draws from. In psychology, resilience is understood through protective factors (Bonanno 2004; Gunnestad 2006; Steinhardt and Dolbier 2008) that determine an individual’s resilience. Following Gunnestad (2006), those protective factors include (1) network factors (i.e., how well the individual is embedded within the social group and experiences external support), (2) abilities and skills (i.e., physical and mental strength, emotional stability, communication skills, ability to explain him/herself, understand others, or solve problems), and (3) meanings, values, and faith (i.e., existential support from self-understanding, values, attitudes, and faith). Culture influences those protective factors, for example, in the way people from that culture perceive and value networks and engage in them or the skills that are valued. Resilience is explicitly linked to the factor of meaning and values, due to the deeply ingrained cultural influences that drive thought and behavior. Cultural practices can make people less resilient, and can simultaneously act as a resource for resilience (Gunnestad 2006).

Considering the aforementioned aspects of resilience, the influence of national culture on organizational resilience can also be explained through the connection between specific cultural values, norms, and belief systems. Organizational resilience is about organizational capabilities and resources that are, most importantly, enacted by individuals and groups in an organization (Chewning et al. 2013; Cho et al. 2006; Horne and Orr 1998; Salanova et al. 2012), which enhances the need to study cultural effects. Hofstede’s dimensions of national culture and their subsequent influences are expanded upon in the following section.

Power distance is defined as “the extent to which the less powerful members of institutions and organizations within a country expect and accept that power is distributed unequally” (Hofstede 2001, p. 98). These inequalities are accepted by both followers and leaders (Tata and Prasad 2015). Power distance influences the hierarchy and structure of an organization, for example whether employees take initiative, or whether they are permitted and willing to participate in decision-making (Euwema et al. 2007; Hofstede 2001; Taras et al. 2010). Subordinates in high power distance cultures that fear expressing disagreement to the boss will be less likely to take initiative. The power distance index (PDI) influences which style of leadership is tolerated or expected by both managers and employees (Tavanti 2012), which in turn affects engagement in decision-making.

Chiaburu et al. (2015) found that PDI influences organizational citizenship behavior, namely, the extent to which employees show engagement and commitment beyond their ordinary tasks. A strong focus on task performance can be particularly observed in employees in countries with a high PDI, as they acknowledge hierarchical order and delegated assignments (Farh et al. 2007). This may enable organizations to fulfill designated tasks and reach organizational goals on target. Conversely, low power distance supports an open relationship between managers and employees, where they are encouraged to engage beyond delegated tasks (Cohen 2007), thereby fostering innovation (Lažnjak 2011). This is important for change processes, and is relevant for organizational resilience, as it is about the general ability of dealing with change, and displaying a fundamental openness to change and acceptance of change (McCann et al. 2009). These processes are dependent upon the power distance relationship between employer and employee (Hergüner and Reeves 2000; Hofstede 2001). A high PDI impairs change processes, as it often manifests in a class system that hinders upward mobility and perpetuates less powerful employees (Markus and Kitayama 1991). As destroying barriers that impede the workflow, resource flow, or ideas (Dyer and Singh 1998; Goldman et al. 1994) is fundamental for a resilient organization, high PDI might be harmful for organizational resilience.

Power distance further influences trust in relationships. High power distance leads to lower trust in external networks compared to low power distance cultures. Low trust in external networks can hinder access to resources (Luczak et al. 2014; Shane 1994) that are essential for dealing with unexpected events. Resilient organizations have well-established support networks and put an emphasis on partnerships and strategic alliances, therefore low trust through high PDI can negatively influence an organization’s resilience.

Furthermore, low PDI fosters shared leadership, which strengthens team relations (Hiller et al. 2006). This is achieved through consultation, participation, and cooperation, which are especially valued in low PDI countries (Matveev and Nelson 2004). Gittell et al. (2006) found that positive relationships at work are a prerequisite for organizational resilience, thus, low PDI might be beneficial for organizational resilience.

Individualism describes the relationship between the individual and the group, that is, how strongly people in a culture derive their own identity from the self or the group (Hofstede 2011; Newman and Nollen 1996; Tata and Prasad 2015). Important characteristics of individualistic cultures are that the members in question are loosely tied to the group (Rinne et al. 2012; Taras et al. 2012; Tata and Prasad 2015), pursue their own interests above those of the group (Luczak et al. 2014; Rinne et al. 2012), emphasize individual initiatives (Tata and Prasad 2015), seize status from accomplishments (Newman and Nollen 1996), and value individual choice and thoughts (Herkenhoff 2004; Tata and Prasad 2015) that may encourage innovation (Lažnjak 2011) and enable flexible reactions to the unforeseen challenges that are beneficial for organizational resilience. As members of individualistic societies are less group-oriented, shared values are less of a priority than in collectivistic cultures (Luczak et al. 2014), which can be detrimental to organizational resilience, considering that shared values and a strong sense of identity and purpose is fundamental to a resilient organization (Freeman et al. 2004; McCann et al. 2009).

Some aspects of collectivistic cultures are beneficial to organizational resilience, and outweigh possible positive effects of individualistic cultures: First, members influenced by collectivistic cultures are loyal to their group, put the interests of their group first, and receive protection from the group at the same time (Hofstede 2001; Newman and Nollen 1996). They are closely connected to their network and have strong ties with other members of their group (Hofstede 2001; Luczak et al. 2010; Rinne et al. 2012), valuing sharing, group goals, and obligations (Jiao et al. 2013; Tata and Prasad 2015). Second, at the team level, collectivism was found to be positively related to collective efficacy and team performance in terms of developing group norms (Celani and Tasa 2010). Those norms include informal rules and expectations that determine the value of group membership and collective responsibility (Celani and Tasa 2010). Third, collectivistic cultures put emphasis on cooperative strategies (Hornsby et al. 2013). For these reasons, a negative relationship of this dimension to organizational resilience is proposed.

The gender dimension of masculinity vs. femininity refers to values beyond absolute gender difference. These values are related to masculine or feminine roles in a society (Hofstede et al. 2010; Tavanti 2012). Masculinity is characterized by values like assertiveness, competition, performance, and focus on material success, while feminine values include maintaining relationships, solidarity, service orientation, and quality of life issues (Luczak et al. 2010; Taras et al. 2012; Tavanti 2012). A country scores highly for this dimension when male values are more present in the society than feminine values (Hofstede et al. 2010; Tavanti 2012). Hofstede suggests that feminine societies might be more successful in the service sector, due to their emphasis on social relationships (Hofstede 1983; Luczak et al. 2010). Masculine societies pursue management practices, with a focus on doing and acquiring, rather than thinking and observing. Achievement and avoiding failure are more important than in feminine cultures that encourage affiliation, and treat failure as less decisive (Newman und Nollen 1996).

Furthermore, the dimension of masculinity vs. femininity may have an impact on the relationship between an employee and the organization. When organizations are less supportive of their employees, employees rely more on self-sufficiency in masculine societies than in feminine societies. Employees are shown to be more team-oriented and valued and supported by their employers in feminine cultures (Chiaburu et al. 2015).

Moreover, the gender dimension indicates a tendency towards shared values. Due to their social orientation, feminine cultures encourage shared values, while masculine cultures are more performance-oriented and foster more individual-based results (Luczak et al. 2014).

For this dimension, the relationship to organizational resilience is not clear, as there is no defined expectation for a specific direction. Employees with a predominant feminine cultural background emphasize support and teamwork, which could result in higher organizational resilience, as knowledge-sharing and collective commitment can strengthen an organization and prepare for unpredicted situations. However, the focus on assertiveness, competition, and performance valued in masculine cultures can also be beneficial for organizational resilience, such as in a period of crisis. Therefore, it is assumed that there will be no clear connection between this cultural dimension and organizational resilience.

Uncertainty avoidance is defined as the degree to which people react to situations they cannot predict (Hofstede 2001; Taras et al. 2012). It indicates how a culture deals with ambiguity and situational demands. Members of a culture with high uncertainty avoidance wish to avert uncertain situations and feel uncomfortable or even threatened without clear structures or regulations. In cultures with low uncertainty avoidance, people are open to change, more flexible, less formal, and willing to take risks (Doney et al. 1998; Tata and Prasad 2015).

In addressing a society’s tolerance for uncertainty and ambiguity, this cultural dimension also refers to the search for truth. Cultures with a high level of uncertainty avoidance are not only trying to reduce the likelihood of uncertain situations by a tight framework of laws, rules, regulations, and security measures, they also tend to find a way to deal with ambiguous situations on a philosophical and religious level, for example, through a belief in an absolute truth (Hofstede 2011; Tavanti 2012). Members of high uncertainty avoidance cultures rely on traditional social norms, established administrative practices, and formalized procedures to prevent events which could have a negative impact (Alas et al. 2011). They articulate expectations very clearly (Congden et al. 2009).

On the contrary, members of a culture with low uncertainty avoidance (and thus, a high uncertainty tolerance) are more open-minded towards different opinions and new approaches that may differ from daily routines, and think outside the box (Tavanti 2012) to encourage innovative solutions (Lažnjak 2011). This tendency towards flexible thinking might be beneficial for organizational resilience, as it can aid adaptation to unexpected events and sudden critical situations (Tata and Prasad 2015). In contrast to high uncertainty avoidance cultures, where risks are avoided through the implementation of strict rules, cultures with a low uncertainty avoidance level aim to reduce risks by engaging in long-term relationships (Doney et al. 1998; Luczak et al. 2014). However, these positive traits of low uncertainty avoidance cultures regarding organizational resilience such as pragmatism, readiness for change, and flexibility, are also accompanied by less positive tendencies, such as spontaneity instead of planning and proactivity—thereby being mostly driven by outside influences rather than actively shaping their corporate environment to improve conditions and influence and foster organizational resilience. As high uncertainty avoidance index (UAI) cultures prepare for various situations and outcomes, as well as an uncertain future, by establishing comprehensive frameworks and guidelines, it is assumed that the traits of high uncertainty avoidance outweigh the traits of low uncertainty avoidance and thus, high uncertainty avoidance has a positive impact on organizational resilience.

The cultural dimension of long-term vs. short-term orientation depicts the focus on the future. Cultures with long-term perspectives emphasize long-term relationships and concentrate on the future—valuing persistence, diligence, dedication, and thrift (Hofstede 1993). Long-term orientation has a positive influence on trust, as relationships are expected to last for a long time and are designed to be beneficial for all stakeholders. Furthermore, long-term oriented relationships tend to be on a more personal level than short-term relationships (Luczak et al. 2010). Thus, social sanctions resulting from violations of trust have a much larger impact than in more business-oriented short-term relationships (Chung et al. 2006).

Short-term orientation focuses on the present and, to a certain degree, on past experiences. Relationships are on a transactional level, are more specific, and based upon values like personal stability (Grimmer and Oddy 2007). Short-term oriented cultures are more competition-focused, and interested in fast and short-term solutions (Luczak et al. 2010).

Organizations with long-term orientation are seen as being more sustainable. Managers in long-term oriented cultures tend to be more patient, focused on long-term profits—even to the extent of giving up immediate benefits—to ensure the organizations’ long-term development. This should be beneficial in the case of organizational resilience, as an investment in organizational resilience may come to fruition over a longer timeframe (Ortiz-de-Mandojana and Bansal 2016). Employee development, community involvement, and environmental protection require long-term oriented engagement, and are more likely to be pursued by managers with a long-term orientation (Tata and Prasad 2015; Newman and Nollen 1996). Moreover, networks built on long-term relationships might enable access to diverse and useful resources. As business partners consider their results to relate to their partners’ results, relational exchanges to maximize profits are emphasized (Luczak et al. 2010). Short-term oriented managers focus on transactional exchanges with their business partners, which aim for prompt returns and fast solutions, sometimes even at the expense of possible future benefits (Tata and Prasad 2015). Nevertheless, there are also situations that require immediate action and a focus on short-term return on investments, especially for companies operating in a highly competitive market environment. There is always an uncertainty if, and when long-term actions and investments pay off, therefore a focus on the current situation cannot be neglected. Companies can put themselves in a favorable market position if they can react and adapt quickly to changing market conditions and external influences. Short-term oriented companies tend to pursue more specific transactions with more detailed and elaborated goal-setting (Luczak et al. 2010). Thus, there are also aspects of short-term orientation that might be beneficial for organizational resilience.

However, as long-term oriented companies are considered to be more sustainable, and might be better prepared for unforeseen events thanks to elaborate long-term scenario planning (Ortiz-de-Mandojana and Bansal 2016), it is assumed that the effects of a long-term orientation will outweigh the effects of a short-term orientation, and thus long-term orientation has a positive effect on organizational resilience.

The cultural dimension of indulgence vs. restraint describes how people may control their desires, behavior, and emotions (Hofstede et al. 2010). In sum, it depicts the degree to which people value pleasure over duty (Zhou et al. 2015). Indulgent cultures are characterized by a weak control over desires, behavior, and emotions (Hofstede 2011). Hedonistic values and leisure time are very important, with such a society accepting an expressive way of satisfaction and enjoyment of life. People tend to be rather optimistic; value their individual freedom, and live more in the moment. They also have a more accepting attitude for spending money to satisfy their needs and desires (Ismail and Lu 2014).

A study from Lažnjak (2011) indicates that societies with a high score on indulgence have a higher innovation rate than restrained societies. A restraint culture maintains strong control over people’s desires, feelings, impulses, behavior, and emotions. They are regulated by strict social norms (Gallego-Álvarez and Ortas 2017). Leisure activities are in general less important than the professional life in general, with people displaying more long-term orientation, pursue utilitarian values and are rather pessimistic regarding future outlooks (Zhou et al. 2015).

People from cultures with high indulgence scores create a positive and relaxed working atmosphere that promotes networking and team commitment. Personal and professional satisfaction is more important than routine activities, tangible rewards, and high salaries. In professional life, members of indulgent cultures are intrinsically motivated, as opposed to the extrinsic motivation in restraint cultures (Dumitraşcu and Dumitraşcu 2016).

Nevertheless, people of restraint cultures display higher persistence in their professional lives, as they are determined by duty, and are used to following strict rules and regulations (Hofstede et al. 2010). They are used to working hard and are willing to work overtime if it is required to get the job done. Such a dedicated work ethic among managers and employees might strengthen organizational resilience, and in the event of unforeseen or critical situations, managers and employees will do everything possible to ensure corporate success.

People from restraint cultures are also more likely to accept their vulnerabilities as a consequence of their duties in their professional and private lives. In many cases, they do not even express their concerns, often because of rigid social norms (Upadhyaya and Rittenburg 2015), which may result in a feeling of helplessness.

Indulgent cultures are expected to be less vulnerable, due to the tendency for people to be more optimistic and happier as they choose their own way of life, as opposed to feeling pressured in restraint cultures (Dückers et al. 2015). Furthermore, members of indulgent cultures tend to actively manage and respond to vulnerabilities by participating in programs, expressing themselves to others, and actively looking for help. Managing vulnerabilities is essential for building organizational resilience and organizations can only be as resilient as their individuals (Coutu 2002; Horne and Orr 1998; Mallak 1998), consequently, a high indulgence score should be beneficial.

The sample is the result of an online survey conducted by the American Management Association and Human Resource Institute in 2006 (AMA 2006).⁴ The study investigated drivers or barriers of organizational change, agility and resiliency, and how higher-performing organizations manage turbulence in different industries (AMA 2006). As Bono and McNamara (2011) point out, cross-sectional data, although not without flaws, can be potentially useful if both the research question and the research design are matched. We argue that the application of cross-sectional data is beneficial in analyzing the effects of national culture, as one major point of critique of Hofstede’s first data collection published in 1980 was a lack of cross-sectional data (Baskerville 2003; McSweeney 2002) which may result in measuring the subculture of a particular industry instead of the national culture. Consequently, in his replication studies that resulted in Hofstede’s matched 2010 dataset used in our study, cross-sectional data was collected and analyzed to acquire the scores of the six cultural dimensions (Hofstede et al. 2010). The use of cross-sectional data in our case is beneficial in that it allows for the analysis of the effects of national culture on organizational resilience rather than one subculture of a particular industry.

Respondents include senior executives, managers, and high-level human resource professionals responsible for, or intimately involved in, change management initiatives within their organizations (McCann et al. 2009). The applied resilience data and our subsequent analysis refers solely to the branch location in the respective country (USA, Canada, or Mexico) and does not include foreign subsidiaries. 72% of the participating companies stated that they employ nationals of their country almost exclusively. Twenty eight percent (28%) of the companies have a higher degree of multinational employees; however, a majority of the employees in the surveyed branch are still nationals of the branch’s location. Thus, it is feasible to apply Hofstede’s national culture dimensions to the surveyed branches. There are numerous other studies conducting the same approach (Kirkman et al. 2006; Tsui et al. 2007; Ronen and Shenkar 2013).

Furthermore, our data represents old data which can still act as a source for generating valuable insights (Zimmerman 2008). The reasons for using old data are threefold: First, there are no quantitative empirical studies on the effects of national culture on organizational resilience to refer to. There are two qualitative studies by Low Kim Cheng (2007) and Gupta et al. (2010). In the event of new research field development, it is, following Zimmerman (2008), feasible to draw new knowledge from old data to open a new avenue for further research. In a letter from the Editor, Stolowy (2017) qualifies old data as acceptable “if the work is based on ‘private/specific/original data that date from several years ago’ but for which the phenomenon studied is still of current interest (p. 415)”. We are convinced that these criteria apply in our case, and as such, we decided to use that rich dataset and matched it with data of Hofstede’s national culture framework.

The cultural dimension scores for power distance, uncertainty avoidance, individualism, masculinity, long-term orientation, and indulgence were added to that sample. For this study, the scores published in Hofstede et al. (2010) have been applied, as the Hofstede’s data from 2001 provides the scores for the four original dimensions of his framework, and the 2010 data offers scores for the newer dimensions of long-term orientation and indulgence for all three countries of our sample. Validation studies (e.g., Hofstede 2001; Beugelsdijk et al. 2015; Schmitz and Weber 2014) show that national cultures are stable over a longer period of time. By comparing the 1980 publication to the 2001 publication, most of Hofstede’s scores have not changed at all, and when there was a changing value, it accounted for only a small margin that did not affect construct validity (Hofstede 2001; Beugelsdijk et al. 2015; Schmitz and Weber 2014). Consequently, it can be reasonably assumed that Hofstede’s scores (2001) for the four original dimensions first published in Hofstede (1980) can be matched with the scores of Hofstede et al. (2010) for the newer dimensions of long-term orientation and indulgence for all three countries of our sample. This matched Hofstede et al. framework (2010) was also validated by replication studies (Schmitz and Weber 2014). Thus, the two different times of data collection and publication of the cultural dimensions were not deemed critical for the application and analysis in our study. Moreover, a new comprehensive cultural framework comparable to Hofstede with newly collected data has not yet been published (Ronen and Shenkar 2013).

The resilience of the organization (OrgRes) was measured with 17 items (see McCann et al. 2009; American Management Association (AMA) 2006). These items measure several aspects relevant to organizational resilience (Appendix, Table 4) on a 5-point Likert scale.

National culture is considered the main predictor variable. To measure national culture, this study has relied upon the cultural dimensions of Hofstede. National culture is measured by the dimensions of power distance index (PDI), individualism vs. collectivism (IDV), uncertainty avoidance index (UAI), masculinity vs. femininity (MAS), long-term orientation vs. short-term normative orientation (LTO), and indulgence vs. restraint (IVR) (Hofstede et al. 2010). The archival data provided by Hofstede et al. (2010) is applied.

Although Hofstede is not without criticism (see, for example, Baskerville 2003; McSweeney 2002), there are various reasons to apply Hofstede in empirical studies (Cohen 2007; Livermore and Rippa 2014; Rinne et al. 2012). First, robust factor analyses have shown that Hofstede’s work is valid and reliable, and has strong correlations with other cultural indices (Rinne et al. 2012). Erez and Earley (1993) showed that most of the criticism is not valid, and that Hofstede’s work is clear and parsimonious. Therefore, secondly, Hofstede’s work is considered one of the leading models for the study of cross-cultural differences (Brewer and Venaik 2014; Beugelsdijk et al. 2015); it is also the most-applied measure in studies on culture and organizational phenomena, particularly organizational behavior (Cohen 2007; Erez and Gati 2004; Beugelsdijk et al. 2015). Moreover, the literature examining the relationship between (aspects of) organizational resilience and the Globe study, that is the second-highest recognized national culture model in the management context next to Hofstede’s dimensions, is sparse.

As we explain in section 2.3, we have assumed that individual and team resilience also influences organizational resilience. We also assumed that those constructs have a stronger influence than national culture. Therefore, we have included the data on both levels to explore and account for their influence. Individual resilience is measured through 17 items (see AMA 2006) on a 5-point Likert scale (see Appendix, Table 4). Team resilience is measured through 18 items on a 5-point Likert scale that measures aspects of team resilience (see AMA 2006).

As another control variable, environmental turbulence was included to see if companies in a turbulent environment are more, or less resilient than companies in a stable environment. This was measured through an overall composite measure that is created by pace of change and disruptiveness (McCann et al. 2009; AMA 2006). Pace of change was measured by the respondents’ perception of the current pace of change as experienced over the past five years. They were asked whether the pace is (1) actually slower—briefer periods of significant change, (2) about the same and still predictable, (3) faster but still predictable, (4) much faster and increasingly unpredictable, or (5) extremely fast—it is impossible to predict what will happen next (see McCann et al. 2009). For disruptiveness, respondents were asked to compare the past five years to current experienced conditions: (1) fewer and less frequent shocks and surprises than before, (2) about the same number and frequency of shocks and surprises, (3) more shocks and surprises, (4) many more shocks and surprises, or (5) very many more shocks and surprises (see McCann et al. 2009).

It was further controlled for profitability, as building resilience of an organization is related to costs (Boin and van Eeten 2013) and is more likely to be implemented by organizations with financial resources (Gittell et al. 2006; Ortiz-de-Mandojana and Bansal 2016).

Organizational resilience might vary according to the life cycle stage of an organization. Literature has referred to the problem of rigidity in established organizations (e.g., Gilbert 2005; Limnios et al. 2014) being linked to both the failure and survival of organizations (Välikangas 2007). A reasonably well-established company might suffer from rigidity, but can still show resilience—also called undesirable resilience by Limnios et al. (2014). Therefore, we have used the life cycle stage as a control variable. Life cycle stage was measured through the respondents’ self-assessment: 1 = Start-up focusing on introducing new products, 2 = rapidly growing firm with increasing market share, 3 = mature firm with brand name recognition, 4 = Firm repositioning itself for the future, 5 = Firm focused on increasing quality and profitability, and 6 = established firm with strong structure and system. These six categories align with existing literature on organizational life cycle stages and can be related to the stages Birth, Growth, Maturity, Revival, and Decline (see Lester et al. 2003; Miller and Friesen 1984; Quinn and Cameron 1983).

Size as a control variable was further included and was measured in terms of workforce. In the original survey, workforce was measured through five categories (i.e., 1 = 100–499; 2 = 500–999; 3 = 1000–3499; 4 = 3500–4999; 5 = 5000–9999; 6 = 10,000, and more). These categories are difficult in terms of scale and distant measurement, so they were transformed into three dummy variables to enhance interpretability. Miller and Cardinal (1994) have defined small to medium-sized companies as those with up to 500 employees, and large companies are considered those with over 500 employees. Therefore, the first dummy variable was built for medium-sized companies (100–499). The remaining categories were divided into two further dummy variables: large company (500–4999) and very large company (5000 and more).

In terms of sector related effects, four dummy variables were created that controlled for economic sector affiliations. The dummies included primary, secondary, tertiary, and other sectors (Kenessey 1987). Companies that could not be assigned to a single economic sector were classified in the category “other”.

No country controls were added, as findings from prior research indicates that cultural dimensions correlate with country level indicators, such as code of law, corruption, or human rights (Cox et al. 2011; Daniels and Greguras 2014). Many of these country differences occur because the underlying national culture (i.e., beliefs, norms and values) is the dominant factor for the establishment of social structures, such as the legal system (Schein 2001; Hofstede et al. 2010).

Following Karam and Ralston (2016), another step in preparing the analysis was the correction of problems in the data set. Missing data is a problem that all researchers face, but it is usually not explicitly addressed (Cole 2008; Schafer and Graham 2002). Therefore, it is important to think about what to do with missing data, and to clearly describe the techniques for future replication purposes (Karam and Ralston 2016).

There are two types of missing values in the data set. First, some companies did not answer all questions related to a specific level, such as individual or team level. These cases were deleted listwise, as they exceeded the 5% cut-off level (DiLalla and Dollinger 2006). Second, some responded with “don’t know” to some of the questions. This category allows the respondent to make a choice if a particular question does not apply for the respondent or if one is not able to answer. Following Ang (2014), these data values should be treated as missing data. How missing data is dealt with depends on various aspects. Many researchers in social science decide to exclude these cases through listwise deletion (Karam and Ralston 2016); however, alternatives to this should be considered, since listwise deletion is not acceptable in some cases, for example, the presence of a pattern behind the lack of information (Lynch 2007; Schafer and Graham 2002; Osborne 2013). If the data is not missing completely at random (MCAR condition), these cases should not simply be eliminated from further consideration (Lynch 2007; Little and Rubin 2002; Osborne 2013). Following Allison (2001) and Osborne (2013), replacing the missing data with MI based on the EM algorithm is acceptable and has advantages over mean substitution. Nevertheless, to ensure that inferences from the results are not influenced by the missing data, a dummy variable can control the applied treatment (Young 2012). We have added a dummy variable into the regression that indicates cases with missing data.

Before regression analysis, a factor analysis was applied for the three variables of individual, team, and organizational resilience (Costello and Osborne 2005; Karam and Ralston 2016). First, sample adequacy was tested by calculating the Bartlett’s test of sphericity, as well as the Kaiser-Meyer-Olkin (KMO) index (Karam and Ralston 2016). The KMO value was above 0.9, which indicates that the dataset is perfectly suitable for dimension reduction (Kaiser 1974; Yong and Pearce 2013). Bartlett’s test of sphericity was also highly significant (p < 0.001), therefore factor analysis is appropriate.

Subsequently, a principal-axis factor analysis with an oblique rotation (oblimin) was carried out. Theoretically, a multi-dimensional factor solution and a high correlation of factors were assumed, which deemed an orthogonal rotation inappropriate. Following Costello and Osborne (2005), an uncorrelated factor solution is rather rare, especially in social sciences. Besides, if the factor solution is orthogonal, an oblique rotation would produce the same results as an orthogonal rotation (Costello and Osborne 2005).

All items that strongly violated the commonality, such as cross-loading or factor-loading criteria, were eliminated (e.g., Costello and Osborne 2005). Items with a communality value of less than 0.2 also had to be eliminated (Child 2006). Communalities with 0.4 or higher are good and, for items in the range 0.2–0.4, research discussions can be based on theory about whether to drop or keep the items (Costello and Osborne 2005). For individual resilience and team resilience, four items had to be excluded. For organizational resilience, two items were excluded. Results surprisingly showed a one-factor solution for individual, team, and organizational resilience (Table 1).

We further tested for common method bias for organizational resilience, team resilience, and individual resilience. Since the data for all items was collected within a single survey and in a cross-sectional manner, the data might underlie a common method bias (Podsakoff et al. 2003). To examine whether common method bias is present, we conducted a Harman’s Single Factor test and the common latent factor method. No evidence for common method bias was found.

Within this study, culture is treated as the main effect (Type I hypothesis) (Aycan 2000; Lytle et al. 1995) and, therefore, culture is studied as the independent variable with a direct effect on organizational resilience, resulting in the following regression model:

Literature has emphasized that the Hofstede dimensions are correlated (see Baskerville 2003; Schmitz and Weber 2014), as seen with power distance (PDI) being highly correlated with individualism (IDV) (see Dückers et al. 2015). Thus, the correlations of the cultural dimensions in the sample were tested by using a Pearson Correlation Coefficient. Results showed that cultural dimensions were significantly correlated, with p = 0.01 (two-tailed). Thus, each cultural dimension was entered separately into the regression to eliminate multicollinearity.