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# The individual manager in the spotlight: Protecting sensitive knowledge in inter-firm coopetition relationships

Tatbeeq Raza-Ullah, Lea Stadtler, Anne-Sophie Fernandez

► To cite this version:

Tatbeeq Raza-Ullah, Lea Stadtler, Anne-Sophie Fernandez. The individual manager in the spotlight: Protecting sensitive knowledge in inter-firm coopetition relationships. Industrial Marketing Management, 2023, 110, pp.85-95. 10.1016/j.indmarman.2023.02.012. hal-04396195

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https://hal.science/hal-04396195v1

Submitted on 30 Sep 2025

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limitations mean that individual managers have leeway when deciding
which knowledge to share when collaborating with a competitor (Jar-
venpaa & Majchrzak, 2016), which protection mechanisms to use, and
for what purpose (Norman, 2001), as well as how to adapt them to the
specific context (Hurmelinna-Laukkanen, 2011; Lewicki et al., 1998).

Despite the pivotal role that managers seem to play, particularly in
leading positions at SMEs (Barrett, Dooley, & Bogue, 2021), the indi-
vidual level of knowledge protection has so far attracted limited
research attention. Previous studies have revealed managers' activities
(Jarvenpaa & Majchrzak, 2016) and decision paths (Bouty, 2000) un-
derlying effective knowledge protection, and investigated their choice of
protection mechanisms (Norman, 2001; Rouyre & Fernandez, 2019).
Nevertheless, the question of which individual characteristics, including
the underlying cognitions and values, enable managers to successfully
protect a firm's core knowledge vis-à-vis its coopetitors, still needs to be
systematically addressed. In view of the managerial leeway that coo-
petitive projects entail, we are particularly interested in the character-
istics of senior managers who lead these inter-firm relationships and
related negotiations, and are engaged in their day-to-day operations (i.
e., alliance managers, Norman, 2001). We therefore ask: Which senior
manager characteristics are positively related to the effective protection of
sensitive knowledge in coopetitive inter-firm relationships?

Addressing this question will help identify the strategic human re-
sources that help protect sensitive knowledge and sustain a firm's
competitive advantage (Ployhart, 2021). To develop these micro-macro
linkages, we explore the connections between Upper Echelons Theory
(UET) and the Resource-Based View (RBV). UET regards managers'
demographic characteristics, like their age, education, and tenure, as
indicators of their cognitions and values, which affect their strategic
processes and choices (Bromiley & Rau, 2016; Hambrick, 2007; Ham-
brick & Mason, 1984). In turn, the RBV suggests that heterogeneity in
resources is linked to heterogeneity in firm performance (Barney, 1991;
Barney, Ketchen Jr, & Wright, 2021).

Applied to the knowledge protection context, we suggest that man-
agers' cognition and values affect their awareness and interpretation of
the need to protect knowledge, as well as their ability to match the
perceived problems to suitable knowledge protection solutions (Cyert &
March, 1963; Ferrier, 2001; Hambrick & Mason, 1984). On this basis, we
hypothesize that senior managers' age, gender, education, and tenure
relate positively to effective knowledge protection which, by helping
protect a firm's competitive advantage (e.g., Kale et al., 2000; Khanna,
Gulati, & Nohria, 1998), impacts the subsequent firm performance
positively (Barney, 1991).

We test our hypotheses by focusing on senior SME managers involved in coopetitive relationships in high-tech and knowledge-intensive industries where the hazards associated with knowledge sharing are particularly salient (Estrada, Faems, & de Faria, 2016; Oxley & Sampson, 2004). We build on a unique dataset with both primary data (senior managers' responses) and secondary, time-lagged data. Based on a matched sample of 176 SMEs, our results support our hypotheses that cognitions and values associated with greater tenure and female gender relate positively to knowledge protection. However, education and age are negatively associated with knowledge protection, for which we discuss possible explanations.

Our study contributes to the literature on knowledge protection by
expanding the view on what managers do (Bouty, 2000; Jarvenpaa &
Majchrzak, 2016) and the mechanisms that they use (e.g., Norman,
2001; Rouyre & Fernandez, 2019) toward identifying managers' cog-
nitions and values, as expressed in their demographic characteristics,
and associated with effective knowledge protection. These insights are
also of interest to the literature on coopetition (Raza-Ullah, 2020) as
they explain how managers' cognitions and values enable the mastering
of knowledge protection as a pivotal condition for effective coopetitive
interactions. Finally, we provide empirical evidence that knowledge
protection matters beyond the scope of the collaborative relationship
(Khanna et al., 1998) as a prerequisite for securing a company's

competitive advantage. Specifically, our study's insights help address
the "resources for what" question at the interface of human resource
management and the RBV (Ployhart, 2021), thereby specifying the
managerial characteristics that promote effective knowledge protection
and contribute to securing a firm's competitive advantage (Barney,
1991; Barney et al., 2021). From a practical perspective, the respective
insights could help companies better select and support managers when
they need to navigate competitively sensitive inter-firm relationships.

## 2. The challenge of knowledge protection in coopetition

A large body of literature on knowledge protection focuses on the choice of protection mechanisms anchored either at the firm or alliance level. At the firm level, these include patenting, licensing, and trademarks through which firms formally register codified knowledge with governments and subsequently benefit from the legal protection that they provide (de Faria & Sofka, 2010; Manzini et al., 2012; Rouyre & Fernandez, 2019). Managers could also use more informal mechanisms, such as means of concealment (Fernandez & Chiambaretto, 2016; Hurmelinna-Laukkanen, 2011) based on undiscernible knowledge structures embodied in complex technology and products (de Faria & Sofka, 2010; Liebeskind, 1997; Wadhwa et al., 2017).

At the level of the alliance, a considered partner choice, restricting
the alliance's scope, third-party facilitation, and the development of
trust and relational capabilities could help manage the risk of opportu-
nistic behavior (Kale et al., 2000; Oxley & Sampson, 2004; Raza-Ullah,
2021; Rouyre & Fernandez, 2019). Further, alliance agreements and
secrecy could define, restrict, and monitor access to codified, but not
registered, knowledge such as recipes, formulas, software, algorithms,
technical procedures, and customer lists (de Faria & Sofka, 2010; Hur-
melinna-Laukkanen, 2011).

On this basis, firms could define a portfolio of knowledge protection
structures, regulations, and procedures for managers to use when
interacting with external parties. However, the appropriate choice of
knowledge protection mechanisms is context-specific (Manzini et al.,
2012), depending, for example, on the size, strategy, and culture of the
focal firm (de Faria & Sofka, 2010), on the type of knowledge to be
shared (Fernandez & Chiambaretto, 2016; Gast, Gundolf, Harms, &
Collado, 2019), the technological environment (Laursen & Salter, 2006;
Manzini et al., 2012), as well as on the number of partners and the
collaboration phase (Manzini et al., 2012; Rouyre & Fernandez, 2019).
Likewise, the partner firm's (firms') characteristics need to be
acknowledged, including their trustworthiness, bargaining power, and
learning capacities (Manzini et al., 2012).

Not only is the appropriate choice of knowledge protection mecha-
nisms situationally dependent, but so is assessing knowledge as sensitive
(Bouty, 2000). While sensitive knowledge generally relates to "knowl-
edge possessed by one organization that another organization can act on
in ways that can cause harm to the releasing organization" (Jarvenpaa &
Majchrzak, 2016, p. 10), the sensitivity could change in the course of
mutual interaction and be related to the amount of knowledge already
released (Faems et al., 2010). Consequently, firms need to regulate their
knowledge flows (Jarvenpaa & Majchrzak, 2016; Norman, 2001) by, for
example, breaking down sensitive knowledge into segments shared in
different ways (Lewicki et al., 1998). In turn, a too strong focus on
knowledge protection could also be counterproductive if it annoys the
collaboration partner and undermines mutual learning and moving to-
ward the alliance goal (Jarvenpaa & Majchrzak, 2016; Raza-Ullah,
2020; Yang, Fang, Fang, & Chou, 2014).

Effective knowledge protection therefore requires the delicate
gauging of when to share what knowledge, how, and with whom, as well
as when and how to draw on specific protection mechanisms. While
defining generic guidelines and procedures could, in this respect, pro-
vide a reference, the context-specific nature of suitable protection
mechanisms limits these guideposts' applicability (Manzini et al., 2012).
Moreover, in innovative and knowledge-intensive relationships, for
example, when competitors co-develop a product, these relationships are dynamic and the required knowledge sharing processes are difficult to forecast (Seepana, Paulraj, & Huq, 2020). Formal mechanisms based on legal protection might prove too complex and inappropriate (Manzini et al., 2012), making knowledge protection a question of flexible adaptation (Gast et al., 2019). The managerial leeway that firm-specific regulations therefore provide in dynamic and context-specific collaborative relationships puts the spotlight on the managers who navigate the inter-firm interactions.

Pioneering research on individual managers' role has started revealing the managerial activities (Jarvenpaa & Majchrzak, 2016) and decision paths (Bouty, 2000) underlying effective knowledge protection, as well as the choice of appropriate knowledge protection mechanisms (Fernandez & Chiambaretto, 2016; Norman, 2001; Rouyre & Fernandez, 2019). In turn, managers' individual characteristics that influence their cognitive bases and values and, as such, their decisions and behavior in knowledge-sensitive situations, have received scarce research attention. Arguing that managerial characteristics matter especially in situations with discretionary leeway, we seek to systematically integrate and expand our insights into individual managers' role. This line of research should make the human resource-performance links more precise (Ployhart, 2021; Barney et al., 2021), thereby specifying manager characteristics associated with effective knowledge as a way to secure a firm's competitive advantage (Barney, 1991). To develop our theoretical framework, we connect arguments from the RBV at the firm level with insights from UET and strategic decision-making theory at the individual level.

Specifically, we borrow from the latter theory to better understand and structure individual decision-making processes along the (1) problem-sensing, (2) problem-interpretation, and (3) decision-making and implementation stages (Cyert & March, 1963; Hambrick & Mason, 1984; Kiesler & Sproull, 1982). UET further suggests that managers' cognitive bases and values shape an idiosyncratic interpretation of and reaction to a given strategic situation (Bromiley & Rau, 2016; Hambrick, 2007; Hambrick & Mason, 1984). The term "cognitive base" refers to managers' experience, knowledge, and assumptions regarding potential events, different alternatives, and various consequences (Hambrick & Mason, 1984; March & Simon, 1958). "Values" reflect the principles that managers use to rank the consequences or alternatives (Hambrick & Mason, 1984; March & Simon, 1958).

## 2.1. The role of individual managers in knowledge protection

Greater awareness facilitates problem sensing, which is a precondition for managerial action (Kiesler & Sproull, 1982). In the context of knowledge protection, the relevant awareness relates to managers' understanding of which knowledge builds the foundation of the firm's competitive advantage and, hence, has to be protected (Norman, 2001; Salter et al., 2014). Problem sensing also requires awareness of the danger of unintended knowledge leakages and their implications for the firm (Hurmelinna-Laukkanen, 2011; Manzini et al., 2012). Further, in a coopetitive setting, problem sensing also has a relational and a dynamic component: It requires discerning and evaluating the partners' emotions, intentions, and behavior (Jarvenpaa & Majchrzak, 2016; Raza-Ullah, Bengtsson, & Gnyawali, 2020) in order to identify changes and the related risks.

Once sensed, the interpretation of risk-related cues and signals influences whether and how managers take action (Kiesler & Sproull, 1982). In view of the trade-offs between knowledge sharing's immediate benefits and the long-term risks for the focal firm (Bouty, 2000) managers need to be sufficiently motivated to protect sensitive knowledge. Initial studies suggest that managers' risk propensity and their feeling of personal obligations and gratitude toward the focal firm might play a role (Bouty, 2000; Olander, Hurmelinna-Laukkanen, & Heilmann, 2015). Gratitude and loyalty might help manage identities and affiliations at the collaborative interface, thereby strengthening managers'

commitment to protecting sensitive knowledge in difficult situations (Hardy, Lawrence, & Grant, 2005; Lifshitz-Assaf, 2018).

Finally, managerial responses require decision making and implementation that match the perceived problems with strategic solutions (Cyert & March, 1963; Ferrier, 2001). In this sense, effective knowledge protection not only requires familiarity with knowledge protection processes and mechanisms, but also with the focal firm's context (de Faria & Sofka, 2010) and the collaborative characteristics (Manzini et al., 2012; Rouyre & Fernandez, 2019). Likewise, the partner firm's or firms' characteristics, such as their trustworthiness, bargaining power, and learning capacities, need to be acknowledged (Manzini et al., 2012).

Further, since formal protection mechanisms might prove too complex and rigid (Manzini et al., 2012), knowledge protection largely depends on individuals' self-regulatory processes to anticipate and control the knowledge being shared (Jarvenpaa & Majchrzak, 2016; Olander et al., 2015). In this respect, self-regulation relates to "hav[ing] a keen awareness of [the own] actions and self-identities and [of] those around them" (Jarvenpaa & Majchrzak, 2016, p. 12), which might improve conscientiousness, which refers to the "socially prescribed impulse control that facilitates task- and goal-behavior, such as thinking before acting, delaying gratification, (...), and planning, organizing, and prioritizing tasks" (John & Srivastava, 1999, p. 121). Consequently, managers might be more effective if they segment knowledge and separate partner-specific knowledge and commercial domains flexibly (Faems et al., 2010).

Based on these individual-level insights into the knowledge protection process, we next seek to deepen our understanding of the role and relevance of specific managerial characteristics. Since it might not be possible to obtain and measure data on managers' cognitive and value dispositions, the UET suggests that demographic background characteristics could serve as proxies (Hambrick, 2007). The UET further suggests that strategic choices, which managers' demographic characteristics determine, impact the organizational outcomes. The UET is therefore a solid foundation on which to develop our hypotheses linking managers' demographic characteristics to effective knowledge protection (c.f. Liu, Zhang, Gupta, Zheng, & Wu, 2022), and to connect them to the RBV by linking effective knowledge protection to the securing of a firm's competitive advantage.

## 2.2. Managers' demographic background and knowledge protection

Our hypotheses focus on the most widely used and impactful demographic characteristics used in UET research, namely age, tenure, gender, and education (Liu, Fisher, & Chen, 2018). Fig. 1 shows our hypothesized model, suggesting a positive association between senior managers' demographic characteristics and knowledge protection in coopetition (hypotheses 1-4), as well as between knowledge protection and subsequent firm performance (hypothesis 5).

### 2.2.1. Managers' age

We first draw on UET studies that focus on managers' age as an important indicator explaining their behavior (Hambrick & Mason, 1984; Wang, Holmes Jr, Oh, & Zhu, 2016). With regard to knowledge protection, we build on three linked arguments: First, as managers grow older, they are likely to have witnessed knowledge leakage situations and the damage these caused. Such experiences sharpen their awareness of and sensitivity to the related risks. Second, research suggests that, simultaneously, their risk-taking behavior decreases (Hambrick & Mason, 1984; Serfling, 2014). In our setting, this implies that in unclear and ambiguous situations, older managers would rather protect than share sensitive firm knowledge. Third, older managers are reported to have greater capacity to think before acting, thereby to regulate their actions (North, 2019). On this basis, greater age might help managers approach knowledge sharing (Olander et al., 2015) and self-regulation more conscientiously, and this way help protect sensitive knowledge. Based on these arguments, we posit:
<figure><img src="image_3.png" /><figcaption>Fig. 1. Managers’ Demographic Background, Knowledge Protection, and Subsequent Firm Performance.</figcaption></figure>

**Hypothesis 1.** *Managers’ age is positively related to knowledge protection.*

### 2.2.2. Organizational tenure

Tenure, i.e., the number of years that a manager has been working for a focal firm, is one of the most common manager characteristics studied in UET research (Finkelstein, Cannella, Hambrick, & Cannella, 2009; Wang et al., 2016). For example, tenure promotes internal socialization and a greater understanding of a firm’s uniqueness and functioning (North, 2019; Wiersema & Bantel, 1992). In the context of knowledge protection, this understanding could spur awareness of when and how sensitive knowledge is at stake. Specifically, managers with longer tenure might be able to better distinguish between sensitive knowledge and that which is not, thereby sensing any risk to a firm’s “crown jewels” (Jarvenpaa & Majchrzak, 2016).

Longer tenured managers are also reported to be more risk averse (Lewis, Walls, & Dowell, 2014; Miller, 1991), to identify stronger with, and be more loyal toward their company (Wiersema & Bantel, 1992). On this basis, we suggest longer-tenured managers are more motivated to keep the firm’s long-term viability in mind when coping with difficult knowledge situations. Finally, longer-tenured managers’ specific insights into their firm’s unique internal routines, processes, and procedures for managing its knowledge flows (Liebeskind, 1997) might help them better choose, use, and adapt available knowledge protection mechanisms. We therefore posit:

**Hypothesis 2.** *Managers’ tenure is positively related to knowledge protection.*

### 2.2.3. Gender

UET studies also highlight the role of gender (e.g., Bao, Fainshmidt, Nair, & Vracheva, 2014): Female leaders are thought to draw on unique cognitive frames, since their experiences in their personal and professional lives probably differ from those of their male counterparts (Post & Byron, 2015). We draw on these insights and argue that women’s relational capacities, such as their active listening (Eagly & Carli, 2003), might help them discern and evaluate their partners’ emotions and behavior (Jarvenpaa & Majchrzak, 2016) and, on this basis, allow them to better sense knowledge-related risks. Building on insights into women’s tendency to limit strategic risk taking (Byrnes, Miller, & Schafer, 1999; Jeong & Harrison, 2017), i.e., “the degree to which strategic decisions are associated with [the] unpredictability of outcomes involving harm or loss” (Jeong & Harrison, 2017, p. 1222), we further suggest that female managers are more inclined to protect rather

than share sensitive knowledge in ambiguous situations. Finally, with regard to the active listening and sensing skill mentioned above (Eagly & Carli, 2003), women’s capability might help them design solutions that are better aligned with their partner’s specific profile and behavior. Consequently, we posit:

**Hypothesis 3.** *With regard to gender, female managers rather than their male counterparts are positively related to knowledge protection.*

### 2.2.4. Managers’ education

Previous UET studies suggest that the level of education could serve as an indicator of individuals’ cognitive ability and skills (Hambrick & Mason, 1984; Wiersema & Bantel, 1992). For example, greater education is positively related to the use of more complex administrative practices, such as thorough formal planning and comprehensive coordination devices (Hambrick & Mason, 1984). Likewise, higher levels of education seem to strengthen managers’ information processing capacity, as well as their ability to distinguish between a variety of stimuli (Wang et al., 2016; Wiersema & Bantel, 1992). Consequently, greater education could provide managers with a foundation to develop complex thinking processes that allow individuals to apply more abstract concepts and policies to new situations and to evaluate decisions and behaviors. On this basis, we suggest that higher levels of education enable greater conscientiousness (Olander et al., 2015) and self-regulation (Jarvenpaa & Majchrzak, 2016) for sensing knowledge-related risks and making appropriate knowledge protection decisions. We therefore hypothesize:

**Hypothesis 4.** *Higher education is positively related to knowledge protection.*

### 2.2.5. Knowledge protection and firm performance

When investigating knowledge protection’s relevance, previous studies specifically analyzed its impact on the success of the coopetitive alliance (Becerra, Lunnan, & Huemer, 2008) and on the focal firm’s innovation performance (Estrada et al., 2016; Hurmelinna-Laukkanen, 2011). These studies argued that the better a focal firm’s core knowledge is protected, the more it can share knowledge with its external partners and competitors (Hagedoorn & Zobel, 2015), and thus make the alliance succeed (Gnyawali & Park, 2011).

Building on the resource-based view (Barney, 1991), we argue that a firm’s core knowledge is a unique resource (Grant, 1996; Kogut & Zander, 1992), the protection of which not only impacts the focal firm’s
collaborative and innovation performance, but also firm performance more generally. Specifically, protecting knowledge from unwanted transfers or imitation should enable a firm to safeguard the sources of its competitive advantage for future market exploitation. Conversely, when sharing sensitive knowledge, such as that related to customers, accounting, production, and cost structures (Fernandez & Chiambaretto, 2016), this might not improve the collaborative innovation performance, but competitors might misuse this information for their own benefit, thereby threatening the focal firm's competitive advantage and, eventually, its revenue sources (Faems et al., 2010; Khanna et al., 1998; Sharif, Yang, Rehman, Kanwal, & WangDu, 2021). We thus posit.

**Hypothesis 5.** *Knowledge protection is positively related to firm performance.*

# 3. Methods

## 3.1. Sample and data collection

We tested our hypotheses on a sample of 176 small and medium firms engaged in coopetition. We chose the coopetition context, because competitor firms tend to be extremely cautious about protecting their core knowledge when they collaborate. Further, we chose to focus on SMEs since the role of senior managers leading the cooperative relationships is of greater relevance in SMEs than in large firms. Finally, knowledge leakages might affect SMEs more severely than large firms with multiple, more diversified business units (Torrès & Julien, 2005). We collected time-lagged data, using two different sources—survey data collection tool and a secondary database.

We used the Swedish Standard Industrial Classification codes (SNI 2007) for the former and randomly selected 900 firms in high-tech and knowledge-intensive industries. We telephoned each firm, briefly described our project, and inquired whether the firm was involved in coopetition (i.e., engaged in simultaneous cooperation and competition with another firm). After excluding firms not engaged in coopetition, those which were inaccessible, or which did not want to participate, we sent a link to our online questionnaire (May–Dec. 2015) to the senior managers of the remaining 404 firms actively involved in or responsible for such relationships. After three reminders, the final dataset comprised 225 complete responses, accounting for a 25% response rate. We tested the non-response bias by using the differences between the respondents and the non-respondents (Armstrong & Overton, 1977) based on the firm characteristics: size, age, and industry. Since the one-way ANOVA results did not show statistically significant differences, we concluded that non-response bias was not a major concern.

We obtained objective, time-lagged data for the latter in order to measure our dependent variable (firm performance, measured at time t and t + 1) and several controls. This database called *Retriever Business* contains information on firms, such as their unique organization numbers, number of employees, financial statements, etc. Using each firm's organization number as a unique identifier, we merged the primary and secondary datasets. Twenty-eight firms dropped out due to missing values and twenty-one firms due to their size (>250 employees), leaving us with a final dataset of 176 cases.

## 3.2. Measures

### 3.2.1. Demographic background

Based on the previous research, we took the most impactful demographic background characteristics into account: senior managers' age, gender, education, and organizational tenure (Liu et al., 2018). We measured managers' age in years, coded gender as 0 for men and 1 for women, coded education as 1 if managers had a university degree and 0 if they lacked a university degree, and based their tenure on the number of years they had worked in the focal firm (log transformed).

### 3.2.2. Knowledge protection

In our study, knowledge protection relates to the extent to which a firm has effectively protected its proprietary knowledge or technology from its competitor-partner (Norman, 2001; Yang et al., 2014). Using a seven-point Likert scale (7 = very large extent; 1 = not at all), we measured the respondents' knowledge protection by asking them about the extent to which their firm (i) protected its core knowledge or technologies and (ii) prevented the partner firm from appropriating its unique competences. The construct showed high convergent validity (Hair, Hult, Ringle, & Sarstedt, 2017), with both outer loadings being >0.70, while the value of the average variance extracted (AVE = 0.87) was well above the threshold of 0.50. Furthermore, the Cronbach's alpha and composite reliability (CR) values, 0.86 and 0.93 respectively, were above the cut-off criterion of 0.70. Lastly, the discriminant validity was established: the square root of the AVE (0.93) was larger than its correlation with any other variable in the model (see also Table 1).

### 3.2.3. Firm performance

Following Rothaermel, Hitt, and Jobe (2006), we proxied the overall firm performance by using the net annual revenue, averaged over time t and t + 1 (i.e., 2016 and 2017 respectively) to reduce the potential bias of single year outliers (Cannella, Park, & Lee, 2008). Further, we used a different source (secondary database) to minimize concerns related to common method bias. We chose this measure, because if a firm is able to protect its core knowledge from being leaked to its competitors, it can maintain its competitive advantage, and would, consequently, gain higher revenues due to its unique, rare, inimitable, and non-substitutable products or services in the marketplace (Barney, 1991).

### 3.2.4. Control variables

We used six covariates, with the first four variables' data being acquired from the Retriever Business, while key informants reported the last two. The first, firm age, is a proxy for a firm's specific resources developed overtime, which will therefore not only impact its ability to protect knowledge, but also its performance. Firm age was measured as the total number of years a firm has been in business since its inception. Second, we included the firm growth as a covariate, because it allowed us to control for the previous growth's effects on the relationships between the demographic variables and the knowledge protection, as well as between the latter and the lagged measure of firm performance. Firm growth was assessed as the employee growth rate over the last two years before we administered the survey. Third, given that extra resources within a firm could have an important bearing on knowledge protection and performance (e.g., Anokhin, Ortqvist, Thorgren, & Wincent, 2011), we also controlled for potential slack resources, calculating it by subtracting total liabilities divided by total sales from the value of 1. For similar reasons, we controlled for a firm's previous performance, using the return on capital employed as a proxy (Meuleman, Amess, Wright, & Scholes, 2009). This proxy was measured by dividing the earnings before income tax by capital employed.

We also included two covariates from our survey. The first one, competitive intensity, was a single-item measure indicating the extent to which the partner firms competed with each other. This is an important variable to consider, because the degree of competition between partners could influence the level of knowledge protection and the subsequent firm performance. Lastly, we included knowledge sharing, as this could affect the relationship between the managerial characteristics and knowledge protection, as well as knowledge protection's impact on performance. This two-item construct reflected the extent to which firms share knowledge to help each other, as well as exchange ideas to improve their capabilities ($α = 0.85$; $CR = 0.93$; $AVE = 0.87$; $SqRoot AVE = 0.93$).
<table><caption>**Table 1**
Sample Analysis.</caption><thead><tr><th colspan="2">Firm</th><th colspan="6">Respondent</th></tr><tr><th>Number of Employees</th><th>Age (years)</th><th>Position</th><th>Age</th><th>Education</th><th>Gender</th><th>Tenure</th></tr></thead><tbody><tr><td>&lt;50 (74%)</td><td>&lt;5 (8%)</td><td>CEOs/VPs/Owners (44%)</td><td>&lt;30 (2%)</td><td>University degree (65%)</td><td>Males (72%)</td><td>&lt;5 (23%)</td></tr><tr><td>50–100 (14%)</td><td>5–10 (18%)</td><td>Key functional managers (32%)</td><td>30–40 (17%)</td><td>No university degree (35%)</td><td>Females (28%)</td><td>5–10 (39%)</td></tr><tr><td>101–150 (4%)</td><td>11–15 (23%)</td><td>Strategy/business dev. managers (18%)</td><td>41–50 (39%)</td><td></td><td></td><td>11–15 (21%)</td></tr><tr><td>151–200 (6%)</td><td>16–20 (16%)</td><td>Key account/project managers (5%)</td><td>51–60 (28%)</td><td></td><td></td><td>16–20 (9%)</td></tr><tr><td>201–250 (2%)</td><td>&gt;20 (35%)</td><td></td><td>&gt;60 (14%)</td><td></td><td></td><td>&gt;20 (8%)</td></tr></tbody></table>

# 4. Analysis of results

## 4.1. Sample description and hypotheses testing

All the respondents in our sample held senior managerial positions: 44% were CEOs, vice presidents, and owners, 32% were key functional managers (e.g., marketing, finance, R&D), 18% were strategy and business development managers, and 5% key account and project managers. The largest portion of our firm sample (74%) comprised small firms with fewer than 50 employees, followed by 14% firms with 50–100 employees. Only 12% of the sampled firms had >100 employees. The median firm age and respondent age were 16 and 49 years respectively. Furthermore, 28% of respondents were female, 65% held a university degree, and their average work experience at the focal firm (tenure) was about 9.5 years. We summarized these statistics in Table 1 and reported the means, standard deviations, and correlations between all the study variables in Table 2.

We used partial least squares structural equation modelling (PLS-SEM) to test our hypotheses. The choice of PLS-SEM was specifically appropriate due to it being quite robust regarding deviations from normality (i.e., it is non-parametric), being able to handle secondary/ archival data better, and its high statistical power (i.e., it renders relationships as significant when they are, in fact, significant in the population) and predictive ability to examine less developed theory and relationships (Hair et al., 2017; 2019).

Table 3 presents the path analysis results. In our first hypothesis, we predicted a positive association between the manager's age and knowledge protection. However, contrary to our expectation, the manager's age affects knowledge protection negatively (β = -0.229, *p* < 0.01). Hypothesis 1 is therefore not supported. Our second hypothesis is supported: organizational tenure affects knowledge protection positively and significantly (β = 0.181, *p* < 0.05). Hypothesis 3's suggestion that female managers contribute positively to knowledge protection is also supported (β = 0.163, *p* < 0.05). Hypothesis 4 suggests that higher education is positively related to knowledge protection. Surprisingly, however, higher education turned out to be a negative contributor to knowledge protection (β = -0.140), but the effect was only significant at *p* < 0.10. Our fifth hypothesis suggesting that knowledge protection leads to better firm performance is supported (β = 0.162, *p* < 0.01).

The coefficient of determination, the R² values of knowledge protection and firm performance are 0.11 and 0.18 respectively, which explain reasonable proportions of the variance in these exogenous variables as predicted by their respective endogenous variables. The blindfolding procedure (with omission distance, D = 7) provided the Q² (i.e., cross-validated redundancy measure) values of 0.05 and 0.10 for the knowledge protection and firm performance models respectively. All Q² values greater than zero indicate that our path model has predictive relevance for both the knowledge protection and firm performance variables. Lastly, the model demonstrates a good fit with an SRMR value of 0.02 (Hair et al., 2017).

## 4.2. Additional analyses/robustness checks

We conducted the following post-hoc analyses and robustness checks: First, although we already reduced common method variance

(CMV) by following *ex ante* remedies (Chang, Van Witteloostuijn, & Eden, 2010; Podsakoff, MacKenzie, Lee, & Podsakoff, 2003)—e.g., using multiple sources and a time-lagged data, ensured the respondent anonymity, and reduced the item ambiguity—as *ex post*, we ran Herman's one-factor test. The results of an unrotated principal component factor analysis of all the survey instrument variables indicated that the extracted factor only explained 20% of the variance, suggesting that CMV was not of much concern.

Second, we assessed the potential endogeneity by following Hult et al. (2018) systematic procedure which underscores two steps to detect endogeneity issues, using the R package. In step 1, we carried out the Kolmogorov-Smirnov test, including the Lilliefors correction, on the latent variable scores of the manager's age, tenure, gender, education, and knowledge protection, which serve as the main independent variables in the partial regressions of the PLS path model. We found that with the exception of age, all of the other constructs were non-normally distributed. Subsequently, we calculated the Gaussian Copulas by using Park and Gupta's (2012) approach to those constructs. The results show that none of the Gaussian copulas is significant (*p* values >0.10), suggesting that endogeneity is not a major concern in our study.

Third, we tested for potential nonlinearities in the structural model relationships by including the squared terms in the model to represent independent variables' quadratic effects on dependent variables. None of these effects was significant, ruling out the possibility of a nonlinear relationship.

Finally, we conducted Multi-Group Analyses (MGA) to explore how interactions/combinations of senior managers' characteristics influence knowledge protection.<fnref n="1" /> Specifically, we checked whether the path coefficients of our hypothesized relationships between specific sample groups, for example, female versus male managers and managers with a university degree versus those without—are statistically different. It can, for example, be argued that highly educated managers with a long tenure tend to better protect sensitive knowledge than those with lower levels of education. The MGA results show that none of the path coefficients of the hypothesized relationship between any two pre-defined data groups is significantly different. The exception, however, is the gender group's tenure-knowledge protection relationship (path coefficient difference = -0.50 and *p*-value <0.05). We used gender as a moderator on the relationship between tenure and knowledge protection to gain further insights into this finding. The interaction between gender and tenure (plotted in Fig. 2) shows that tenure has a more important effect on male than female senior managers, which suggests that male senior managers' knowledge protection tends to improve strongly as their tenure in their present firm increases.

# 5. Discussion and conclusions

In this study, we suggest that managers' cognitive and value bases, as reflected in their demographic characteristics, influence their tendency to protect sensitive knowledge effectively and, thereby, the overall firm

<footnote n="1">¹ We thank one of the anonymous reviewers who suggested exploring combinations of characteristics in order to further enrich our understanding of the tested relationships.</footnote>
<table><caption>Table 2
Descriptive Statistics.</caption><thead><tr><th>Variables</th><th>Mean</th><th>SD</th><th>(1)</th><th>(2)</th><th>(3)</th><th>(4)</th><th>(5)</th><th>(6)</th><th>(7)</th><th>(8)</th><th>(9)</th><th>(10)</th><th>(11)</th><th>(12)</th></tr></thead><tbody><tr><td>(1) Age</td><td>49.09</td><td>9.45</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(2) Competitive intensity</td><td>4.87</td><td>1.89</td><td>-0.080</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(3) Education</td><td>0.99</td><td>0.05</td><td>-0.113</td><td>-0.041</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(4) Firm Age</td><td>20.90</td><td>17.87</td><td>0.165*</td><td>0.094</td><td>0.063</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(5) Firm Growth</td><td>0.07</td><td>0.21</td><td>0.025</td><td>0.120</td><td>-0.096</td><td>-0.157*</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(6) Gender</td><td>0.99</td><td>0.10</td><td>-0.007</td><td>0.118</td><td>0.037</td><td>-0.080</td><td>0.015</td><td>1.000</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(7) Knowledge sharing</td><td>3.68</td><td>1.73</td><td>-0.097</td><td>0.067</td><td>0.060</td><td>0.023</td><td>-0.008</td><td>0.063</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(8) Knowledge protection</td><td>4.89</td><td>1.51</td><td>-0.144</td><td>-0.015</td><td>-0.100</td><td>0.059</td><td>-0.017</td><td>0.122†</td><td>(0.932)</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(9) Performance (log)</td><td>10.63</td><td>1.25</td><td>0.179*</td><td>0.196**</td><td>0.001</td><td>0.298***</td><td>0.134†</td><td>0.026</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(10) Previous performance</td><td>40.08</td><td>50.37</td><td>-0.078</td><td>0.009</td><td>-0.032</td><td>-0.092</td><td>0.181*</td><td>-0.138†</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(11) Slack</td><td>0.53</td><td>0.28</td><td>-0.036</td><td>0.030</td><td>-0.098</td><td>0.035</td><td>0.017</td><td>0.025</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>(12) Tenure (log)</td><td>2.15</td><td>0.67</td><td>0.259**</td><td>0.072</td><td>-0.090</td><td>0.161*</td><td>0.018</td><td>-0.117</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>

performance. By testing our hypotheses on a rare sample of 176 senior managers of SMEs engaged in coopetitive projects, we show the relationships between managers’ age, gender, tenure, and education and knowledge protection, and subsequent firm performance. In the light of our results, we highlight our three main contributions to the intersection between knowledge protection, coopetition, and RBV literatures.

## 5.1. Theoretical contributions

First, we support the strategic choice view that senior managers have an important influence on the protection of sensitive knowledge in collaborative relationships (Bouty, 2000; Jarvenpaa & Majchrzak, 2016; Norman, 2001). Specifically, the dynamic context of coopetitive inter-firm relationships provides managers with leeway, which largely shifts the situational interpretation of confidentiality and sensitive knowledge to the individual manager (Bouty, 2000; Faems et al., 2010). In this process, the decision regarding which knowledge to share and which knowledge to protect and how to do so, is also shifted to the individual manager (Manzini et al., 2012). Although previous literature examined decision paths (Bouty, 2000), interactive activities (Jarvenpaa & Majchrzak, 2016), and knowledge protection processes at the individual manager level (Norman, 2001), we expand this body of knowledge by identifying managers’ demographic characteristics as a reflection of the underlying cognitive bases and values that inform their knowledge protection decisions and behaviors.

Our research illustrates how managers’ “personalized interpretation of the strategic situations they face” (Hambrick, 2007, p. 334) manifests itself in the relationship between managers’ cognition and values, and the effectiveness of their knowledge protection choices. Consequently, our study helps explain knowledge protection on the basis of managerial characteristics (Hambrick, 2007; Hambrick & Mason, 1984), including their awareness of what constitutes the firm’s “crown jewels,” what knowledge leakage might imply, their motivational sources in terms of their risk attitude and firm loyalty, as well as their capability in terms of their sensing, self-regulatory, and adaptability skills, which are anchored in their demographic background. On this basis, our study contributes to informing the black box of who managers, who engage in effective knowledge protection, are.

If we zoom into the specific findings, our results support the suggestion that a manager’s longer tenure and female gender support knowledge protection. These insights could encourage companies to entrust longer-tenured managers and women with positions dealing with competitively sensitive relationships. In our study, however, only 28% of the sample managers were women, although this is probably one of the highest percentages of female managers, since Sweden ranks 4th in the World Economic Forum gender equality index (WEF World Economic Forum, 2020).

Furthermore, we were surprised to find a significant negative relationship between age, as well as higher education, and knowledge protection. A possible explanation with respect to age is that a decrease in information processing capacity undermines the assumed greater awareness of knowledge risks, the greater risk aversion in this regard, as well as the consciousness of and self-regulation regarding knowledge risks (Carstensen & Mikels, 2005). Since interactions in coopetitive alliances, especially in the high-tech and knowledge-intensive industries, are dynamic and volatile, speed and the information processing capacity, which are associated with a younger age (Carstensen & Mikels, 2005), might matter more. A possible explanation with respect to the negative relationship between education, in the form of a university degree, and knowledge protection is the reverse effect of the greater use of administrative complexity, which is associated with higher education (Hambrick & Mason, 1984). Since the interplay between knowledge sharing and protection is dynamic, the greater use of administrative complexity could limit managers’ ability to respond flexibly to evolving situations and to use their intuition (e.g., by sensing changes in the partner relationships, Jarvenpaa & Majchrzak, 2016) to protect sensitive

<footnote>**p < 0.001, **p < 0.01, *p < 0.05, †p < 0.1. Bold diagonal elements in parentheses are the square root of AVEs.</footnote>
<caption>**Table 3**</caption>

Results.

<table><thead><tr><th>Variables</th><th>Knowledge Protection</th><th>Firm Performance</th></tr></thead><tbody><tr><td>Previous Performance</td><td>-0.004 (0.053)</td><td>0.040 (0.546)</td></tr><tr><td>Competitive Intensity</td><td>-0.080 (0.972)</td><td>0.153* (2.299)</td></tr><tr><td>Firm Age</td><td>0.099 (1.516)</td><td>0.301*** (5.064)</td></tr><tr><td>Organizational Slack</td><td>-0.125† (1.727)</td><td>0.087 (1.072)</td></tr><tr><td>Firm Growth</td><td>-0.002 (0.025)</td><td>0.154* (2.297)</td></tr><tr><td>Knowledge Sharing</td><td>0.043 (0.482)</td><td>0.070 (0.728)</td></tr><tr><td>Manager Age</td><td>-0.229** (3.123)</td><td></td></tr><tr><td>Organizational Tenure</td><td>0.181* (2.294)</td><td></td></tr><tr><td>Gender</td><td>0.163* (2.060)</td><td></td></tr><tr><td>Education</td><td>-0.140† (1.924)</td><td></td></tr><tr><td>Knowledge Protection</td><td></td><td>0.162** (2.585)</td></tr><tr><td>R<sup>2</sup></td><td>0.111</td><td>0.182</td></tr><tr><td>Q<sup>2</sup></td><td>0.05</td><td>0.10</td></tr></tbody></table>

\*\*\*p < 0.001, \*\*\*p < 0.01, \*p < 0.05, †p < 0.1. (t-values in parentheses).

Bootstrapping procedure based on 5000 subsamples.

R²: Coefficient of determination.

Q²: Cross-validated redundancy measure – should be >0.

<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Interaction between Gender and Tenure.</figcaption></figure>

knowledge. Consequently, companies should carefully analyze the knowledge protection awareness and capability of those managers working on coopetitive relationships, and anticipate challenges by offering them tailored training and coaching support.

These findings are a starting point for explaining knowledge protection differences by taking senior managers' different characteristics into account, as well as the implications of these for their managerial decisions and behavior. These insights are of interest for the literature on knowledge management with regard to inter-firm relationships in general (Kale et al., 2000; Kauppila, 2015) and coopetition in particular (Bengtsson & Kock, 2000; Fernandez & Chiambaretto, 2016; Gast et al., 2019; Raza-Ullah, 2020; Rouyre & Fernandez, 2019), as they explain how managers' cognitions and values enable them to master knowledge protection as a pivotal condition for effective (coopetitive) inter-firm interactions.

Our second contribution draws attention to knowledge protection's performance implications in competitively relevant relationships. While previous studies primarily tested knowledge protection's effects on an alliance's success (Becerra et al., 2008), or on a focal firm's innovation performance (Estrada et al., 2016; Hurmelinna-Laukkanen, 2011), we expand this view by demonstrating knowledge protection's positive association with the overall firm performance. These insights support the commonly assumed relationship between the protection of a firm's competitive advantage (Faems et al., 2010; Khanna et al., 1998) and its performance. We explored this relationship with regard to SMEs engaged in collaborations with competitors. However, leakages of sensitive knowledge could also be risky in the context of buyer or supplier collaboration (Squire, Cousins, & Brown, 2009). Suppliers or business

customers might use the information to support their negotiation position, sharing it consciously or unconsciously with other actors, such as with the focal firm's competitors, and/or eventually decide to vertically integrate some or all the focal firm's activities.

Finally, our third contribution is that we develop a knowledge protection framework that, by connecting the micro and the macro levels, contributes to forging synergy between the RBV (Barney et al., 2021) and the UET (Hambrick & Mason, 1984). By focusing on knowledge protection, our study responds to the RBV's “resources for what” question (Ployhart, 2021) and helps explain how characteristics defining a given type of (here, human) resources relate to performance behavior and the securing of a firm's competitive advantage. More specifically, we show how the UET could be leveraged to inform how senior managers' cognitive bases and values, as expressed in their demographic characteristics, relate to effective knowledge management. In this way, we contribute to the human resource-performance links' precision (Combs, Liu, Hall, & Ketchen, 2006; Crook, Todd, Combs, Woehr, & Ketchen, 2011).

Research has started identifying human resource's role in inter-firm relationships with a specific aim to create value at the alliance and firm levels by means of knowledge sharing and knowledge absorption (Bengtsson & Raza-Ullah, n.d.; Bogers, Foss, & Lyngsie, 2018; Salter et al., 2014; Sharif et al., 2021). We, however, contribute to shifting this aim toward highlighting strategic human resources' importance for knowledge protection. By protecting a firm's sensitive knowledge, managers help sustain the value capturing aspect as a comparatively less acknowledged component of sustaining a competitive advantage (Barney, 1991). Our findings in this respect are interesting in terms of how specific individual characteristics either enhance or undermine a manager's propensity to protect sensitive knowledge effectively, which position human resources as either protecting or threatening a firm's competitive advantage.

## 5.2. Managerial implications

These research insights also have practical relevance in that they might help companies decide how to staff competitively sensitive projects appropriately. Our results, which are based on a Swedish sample of SMEs, suggest that senior managers associated with effective knowledge protection tend to be mostly female, are relatively young, have a longer tenure at a focal firm (rather than at multiple firms), and do not require a university degree. Further, firms could invest in reinforcing their managers' knowledge protection awareness (e.g., training), their motivation (e.g., strengthening the corporate values and their identification with these) and their capability (e.g., with simulations, other situational applications, and coaching).
## 5.3. Limitations and future research avenues

We invite future research to deepen these insights, first, by enriching the analysis with managerial characteristics, such as the managers’ functional experiences and their industry, technology, and geographical background, and by expanding the study context from Sweden to multiple locations. Further, since our study suggests that the differences in manager profiles lead to different knowledge protection outcomes, qualitative studies could update and expand Bouty’s (2000) decision path by acknowledging different manager profiles. Second, while the small firm size in our sample suggests that the examined senior managers, as individuals, play critical roles in coopetitive relationships, the influence of team dynamics at the firm and inter-firm levels is an important area for future research (see e.g., Bengtsson & Raza-Ullah, n. d.; Bromiley & Rau, 2016; Neely Jr, Lovelace, Cowen, & Hiller, 2020).

Third, we focused on the knowledge protection side of collaboration, because individual-level studies are scarce compared to the knowledge sharing side (Lifshitz-Assaf, 2018; Salter et al., 2014). We used knowledge sharing as a control variable, which, however, did not lead to any significant results. Consequently, we encourage more studies on the interplay of knowledge protection and sharing, as well as investigations into the underlying decision-making processes across different manager profiles. Given the paradoxical relationship underlying knowledge sharing and knowledge protection in coopetitive projects, such future studies would be of particular interest (Bengtsson & Kock, 2000; Raza-Ullah, 2021; Rouyre & Fernandez, 2019): Knowledge sharing is critical for mutual learning and advancement toward an alliance's goal (Fernandez & Chiambaretto, 2016; Jarvenpaa & Majchrzak, 2016; Raza-Ullah, 2020; Yang et al., 2014), while protection of sensitive knowledge, as evidenced in this study, is critical to ensure a firm's competitive advantage.

Against this background, future studies could more systematically explore how senior managers’ demographic characteristics could, through their associated cognitive bases and values, promote the sharing of (non-sensitive) knowledge and an alliance’s performance. When juxtaposed with our knowledge protection findings, is there evidence to suggest that managerial characteristics reveal a duality in the knowledge-protection and knowledge sharing relationship (i.e., does strength at one end mean a threat at the other end)? Or is this relationship more complex, revealing a two-continuum approach (see e.g. Bengtsson, Eriksson, & Wincent, 2010), in which a supportive effect for knowledge protection does not necessary imply a negative effect for knowledge sharing (and vice versa)?

Finally, the next step in analyzing knowledge protection at the individual level could comprise further investigation of the role of contextual variables that may further explain or even change the effect of individual managerial characteristics. For example, by integrating UET and contingency theory, future research can investigate the conditions such as TMT diversity (Bengtsson, Raza-Ullah, & Srivastava, 2020), market factors (Crick, 2019), and relational capabilities (Raza-Ullah, 2021), under which the individual characteristics (or combinations) would positively or negatively impact knowledge protection. Further, while the results of our preliminary ad-hoc tests were mostly insignificant, they indicated that in the course of a longer organizational tenure, male managers could improve their ability to protect sensitive knowledge effectively. Moreover, this trend was more distinct in respect of these male senior managers than the female ones. Although the latter result might seem counterintuitive, a possible explanation could be that over a longer organizational tenure, women’s active listening skills and lower risk-taking propensity, which are both associated with effective knowledge protection, could be slightly attenuated when working in a more male-dominated working environment. A recent study shows (Grant Thornton, 2021) that men still represent about 66% of senior management in the European Union. We invite future research to more systematically examine how different combinations of managerial characteristics influence knowledge protection. Overall, in view of the

growing call for collaborative strategies to address economic and societal challenges, developing a more robust understanding of knowledge protection decisions and behaviors in competitively sensitive relationships seems timely and, as our study shows, also relevant regarding their performance.

## Declaration of Competing Interest

None.

## Data availability

The data that has been used is confidential.

## Acknowledgements

The first author acknowledges the financial support from Jan Wal-landers och Tom Hedelius Stiftelse samt Tore Browaldhs Stiftelse (W18-0024).

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