Aligning values for engagement: how cultural fit shapes employee advocacy

Organizational culture is widely recognized as a critical driver of employee engagement, organizational performance, and long-term competitiveness (Chatman and O'Reilly, 2016; O'Reilly et al., 2025). However, in today's rapidly changing business landscape—defined by digital transformation, rising ESG (Environmental, Social, Governance) pressures, sustainability imperatives, and talent volatility— the question of how well employees' personal values align with their organization's cultural values has become increasingly strategic. In this vein, the intensification of digitalization and ESG agendas often introduces new routines, metrics, and governance mechanisms that can reshape employees' interpretations of “fit” with the organization. Although the concept of cultural fit (or cultural alignment) is well-documented in management literature (Kristof-Brown et al., 2005; Verquer et al., 2003), two persistent gaps remain: (1) organizations still struggle to understand which specific cultural configurations foster or hinder alignment and (2) to understand how these configurations translate into employee advocacy behaviors such as the Employee Net Promoter Score (eNPS). This issue is not merely theoretical: misalignment between employees and organizational culture can undermine retention, discretionary effort, employer attractiveness, and the credibility of strategic transformation initiatives, thereby generating tangible managerial and economic costs (Sheridan, 1992).

Although research has long emphasized the role of cultural fit in shaping positive employee outcomes (Watanabe et al., 2024; Rey-Tienda et al., 2025), its measurement remains a methodological challenge (Goldberg et al., 2016), particularly because conventional culture instruments, like Quinn and Rohrbaugh's (1981) Competing Values Framework (CVF) does not always capture emerging cultural domains such as digital transformation and ESG-oriented value systems. Existing frameworks fail to capture the values, routines, and structural dynamics of emerging Digital and ESG cultures, leaving scholars and practitioners without tools to assess their impact on employees' perceived cultural fit. In addition, beyond the omission of Digital and ESG domains, existing cultural fit measures remain limited, since they rely on static assessments that do not capture the ranked salience of organizational values across current, personal, and desired cultural states. As a result, prior approaches offer only a partial view of how contemporary culture systems shape employee alignment and advocacy. This study addresses that gap by examining how these underrepresented cultural archetypes shape employees' sense of fit and their willingness to advocate for their organization (eNPS).

To address this gap, the study employs the Cultural Fit Assessment Method (CFAM®) (Leal-Rodríguez and Sanchís-Pedregosa, 2025)—a scalable, values-based diagnostic model that extends the Competing Values Framework (CVF) (Quinn and Rohrbaugh, 1981, 1983; Cameron and Quinn, 2011) by integrating Digital and ESG Cultures with traditional archetypes (People, Innovation, Goals, Norms). Unlike static typologies, CFAM® operationalizes culture through ranked organizational values, enabling a dynamic assessment of alignment between what organizations enact, what employees value, and what they seek. Based on this framework, the study is guided by the following research questions:

Building on the above, the study's aim is twofold: (1) to analyze the predictive relationships among these archetypes, cultural fit, and eNPS, and (2) to validate CFAM® as a scalable, values-based tool for assessing cultural alignment within organizations. Toward this aim, this paper relies on Minzer® ^[1], a proprietary culture diagnostics platform developed through a university-industry partnership, to collect survey data from 882 employees across Spanish and Ibero-American firms to examine how six cultural archetypes (People, Innovation, Goals, Norms, Digital, and ESG) influence both cultural fit and eNPS.

Methodologically, this research uses Partial Least Squares Structural Equation Modeling (PLS-SEM) and Importance–Performance Map Analysis (IPMA) to test a conceptual model in which cultural fit mediates the relationship between cultural archetypes and eNPS. Results reveal that Organic Culture Archetypes (People, Goals, and Innovation) positively influence cultural fit and thereby increase employee advocacy. In contrast, Mechanistic Culture Archetypes (Norms, Digital, and ESG) tend to diminish cultural alignment and suppress advocacy, highlighting the importance of how cultural values are perceived and experienced by employees.

This study offers three key contributions. First, it introduces and empirically validates a multidimensional model of organizational culture that incorporates Digital and ESG values—two increasingly relevant yet underrepresented domains. Second, it proposes a novel, values-based operationalization of cultural fit, moving beyond perception-based and typological measures. Third, it reveals a previously underexplored link between cultural fit and employee advocacy, showing that fit fully mediates the relationship between cultural archetypes and eNPS. Collectively, these contributions position the study at the nexus of organizational culture, digital transformation, and sustainability-driven management, offering actionable insights for enhancing internal engagement and external reputation through culture management.

Organizational culture refers to the shared values, beliefs, norms, and assumptions that guide behavior and decision-making (Schein, 1985; Leal-Millán, 1991; Hatch, 1993). It shapes employee attitudes, work dynamics, and business performance (Denison et al., 2014). Despite its conceptual relevance, measuring culture has long posed methodological challenges (Hofstede et al., 1990). Among the most widely used frameworks is the Competing Values Framework (CVF), which classifies organizational culture into four archetypes: clan, adhocracy, market, and hierarchy (Quinn and Rohrbaugh, 1981, 1983). This typology underpins the widely used Organizational Culture Assessment Instrument (OCAI), which offers psychometrically valid diagnostics but does not account explicitly for contemporary cultural domains such as digitalization or sustainability.

Similarly, the Denison model focuses on four performance-linked traits—Involvement, Consistency, Adaptability, and Mission—and provides valuable benchmarking capabilities (Denison et al., 2014). However, its primary aim is to link traits to performance rather than to assess nuanced value alignment across individual, current, and desired culture states.

To address these gaps, this study employs the Cultural Fit Assessment Method (CFAM®), which extends the CVF and the Organizational Culture Assessment Instrument (OCAI) developed by Cameron and Quinn (2011) by identifying six distinct cultural archetypes, including Digital and ESG—two domains often underrepresented in prior models (Leal-Rodríguez et al., 2023; Leal-Rodríguez and Sanchís-Pedregosa, 2025): (1) People Culture –emphasizing collaboration, trust, and employee well-being; (2) Innovation Culture –characterized by creativity, experimentation, and adaptability; (3) Goals Culture – prioritizing efficiency, productivity, and strategic objectives; (4) Norms Culture –defined by rules, processes, and stability; (5) Digital Culture – A data-driven, technology-enabled culture that fosters agility, continuous learning, and digital fluency; and (6) ESG Culture – A purpose-driven culture that integrates Environmental, Social, and Governance (ESG) principles into its core values.

CFAM® assesses culture through ranked value priorities across three dimensions: employees' perceptions of current organizational values, their personal values, and their desired corporate values. This structure enables the calculation of continuous fit indices, providing a nuanced view of value congruence. By capturing emerging cultural dynamics and supporting mediation analysis (culture → fit → eNPS), CFAM® serves as a diagnostic tool that is both conceptually integrative and empirically robust.

These archetypes are further categorized into Organic and Mechanistic cultures, drawing from classic management theory. Organic cultures—flexible, decentralized, and adaptive—foster open communication, autonomy, and informal coordination (Burns and Stalker, 1961; Mintzberg, 1979). Within this category, People Culture emphasizes human-centric values and psychological safety; Innovation Culture supports autonomy and learning; and Goals Culture promotes shared ambition and performance-driven flexibility. These traits enhance dynamic capabilities and employee engagement.

In contrast, Mechanistic cultures are formalized, hierarchical, and control-oriented, prioritizing stability, standardization, and defined roles (Burns and Stalker, 1961). Norms Culture, rooted in rules and procedures, exemplifies this model. Digital Culture, though associated with agility, often relies on codified workflows, automation, and centralized data systems. ESG Culture, while ethically progressive, introduces structured compliance, reporting, and institutionalized behaviors aligned with governance standards. Together, these Mechanistic Culture Archetypes emphasize predictability, conformity, and institutional control over flexibility and individual agency.

Cultural fit refers to the alignment between an individual's values and the dominant values of the organization (Kristof-Brown, 1996; Cable and DeRue, 2002). Extensive research has demonstrated that cultural fit predicts job satisfaction, commitment, and performance (Kristof-Brown et al., 2005; Verquer et al., 2003; Watanabe et al., 2024). When employees perceive a strong fit with their organization's culture, they are more likely to be engaged, motivated, and invested in the company's success (Chatman, 1991).

However, recent research suggests that cultural fit should not be viewed as a static, one-size-fits-all construct. Instead, it should be assessed dynamically, recognizing the influence of microcultures and evolving business environments (Gelfand et al., 2017). The CFAM® model provides a structured approach to measuring cultural fit by examining its alignment with specific cultural archetypes, thereby offering a more granular and actionable understanding of the concept. Such alignment unfolds through a temporal process in which personal values progressively connect with and reinforce those of the firm, thereby anchoring this engagement in a more lasting, coherent, and meaningful way (Query et al., 2025).

The Employee Net Promoter Score (eNPS) is a widely used metric that measures employee advocacy—specifically, how likely employees are to recommend their company as a great place to work (Reichheld, 2011; Owen and Brooks, 2008). Derived from the Net Promoter Score (NPS) methodology in customer satisfaction research, eNPS is an indicator of employee engagement and organizational commitment (Yaneva, 2018).

Employees are classified into three categories based on their responses to the eNPS question: (1) Promoters (9–10) – Highly engaged employees who actively advocate for the company; (2) Passives (7–8) – Neutral employees who are satisfied but not actively promoting the organization; and (3) Detractors (0–6) – Employees who are dissatisfied and unlikely to recommend the organization.

Research has demonstrated that higher eNPS scores correlate with higher levels of both employees' and customers' loyalty and performance, and with customers' NPS measure itself (Peláez and Román Calderón, 2024). However, the specific cultural drivers of eNPS remain underexplored, making this study a critical contribution to the field.

This study examines how organizational culture shapes employee advocacy via perceived cultural fit, drawing on functionalist, structuralist, and Job Demands–Resources (JD-R) perspectives—each illuminating distinct mechanisms in the conceptual model.

First, functionalist theory views cultural archetypes as system-level mechanisms that promote alignment, cohesion, and performance (Parsons and Shils, 1951; Gioia and Pitre, 1990). Culture is seen as an adaptive structure that optimizes organizational effectiveness (Denison and Mishra, 1995). CFAM® aligns with this view by classifying culture types based on their functional contributions (Leal-Rodríguez et al., 2023). Functionalism thus informs the first analytical layer: how culture typologies shape shared norms that underpin advocacy.

Second, structuralist theory highlights culture as lived experience, shaped by tensions, contradictions, and power dynamics (Burrell and Morgan, 1979). Cultural fit becomes a negotiated perception influenced by identity and context (Thornton et al., 2012). This lens supports the second layer by explaining how employees interpret fit in complex environments with coexisting archetypes.

Third, the JD-R model addresses psychological mechanisms linking culture to motivation and well-being. It frames culture as a mix of demands (e.g. workload) and resources (e.g. autonomy) that affect burnout and engagement (Demerouti et al., 2001; Bakker and Demerouti, 2017). Cultural archetypes reflect this dynamic: adhocratic cultures may function as resources, enhancing eNPS, while hierarchical ones may act as demands, reducing it (Bakker et al., 2023). JD-R informs the third layer, mapping how cultural environments shape motivational states that influence advocacy.

This study investigates how organizational culture archetypes influence employee advocacy, as measured by eNPS, through the mediating role of cultural fit (see Figure 1). Drawing from cultural typologies, we distinguish between two overarching cultural configurations: Organic (People, Goals, Innovation) and Mechanistic (Norms, Digital, ESG).

Organizational cultures are inherently heterogeneous; even dominant archetypes coexist with competing values and norms (Schein, 1985; Leal-Millán, 1991; Cameron and Quinn, 2011). As such, cultural fit is not static or uniform, but an ongoing negotiation between espoused values and the lived experiences of employees (Schein, 1985; Kristof-Brown and Billsberry, 2013). This perception of fit is central to fostering employees' engagement, a sense of belonging, and greater satisfaction—factors closely tied to their willingness to advocate for the organization, as reflected in eNPS (Watanabe et al., 2024; Reichheld, 2011).

Given the plurality of cultural influences, we posit that different archetypes exert distinct effects on eNPS. Some foster alignment and advocacy, thereby increasing eNPS, while others create dissonance, reducing the likelihood of employees recommending their organization.

The first hypothesis explores how Organic Culture Archetypes—People, Goals, and Innovation—enhance cultural fit. These cultures share traits of flexibility, strategic adaptability, and human-centric values that foster psychological safety and alignment with organizational goals (Denison and Mishra, 1995; Edmondson, 1999).

A People-oriented culture fosters trust, collaboration, and employee well-being, creating an inclusive environment where employees feel supported (Cameron and Quinn, 2011). Research highlights that organizations emphasizing interpersonal relationships and personal development promote higher psychological safety and stronger employee-organization alignment (Gelfand et al., 2017).

Similarly, a Goals-oriented culture, focused on achievement, performance metrics, and competitiveness, aligns with employees who thrive in high-performance work environments (Cameron and Quinn, 2011; Groysberg et al., 2018). Employees who share the organization's ambition for success tend to develop stronger cultural identification, thereby enhancing their perception of cultural fit.

Finally, an Innovation-oriented culture, which encourages creativity, autonomy, and continuous improvement, provides employees with a sense of agency and professional growth, fostering stronger alignment between individual aspirations and organizational values (Amabile, 1997; Cameron and Quinn, 2011).

Thus, we hypothesize:

In contrast to Organic Cultures, Mechanistic Culture Archetypes (ESG, Norms, and Digital) impose structured, prescriptive, and compliance-driven work environments, which may generate cultural misalignment for employees who do not naturally align with these organizational expectations.

A Norms-driven culture, characterized by bureaucratic stability, hierarchy, and strict procedural adherence, may create a rigid environment where employees struggle to develop a sense of personal belonging and autonomy (Leal-Rodríguez et al., 2015; Felipe et al., 2017). In this vein, recent studies on organizational design reveals that bureaucratic features (i.e. centralization/formalization)—core to normative cultures—are frequently associated with lower motivation, creativity, and satisfaction (proximal to fit and engagement), especially when job characteristics are held constant (Jong and Faerman, 2023).

A Digital-oriented culture, prioritizing technological transformation, data-driven decision-making, and automation, may pose adaptability challenges for employees who are not technologically inclined (Westerman et al., 2014; Leal-Rodríguez et al., 2023; Orero-Blat et al., 2024). These digitalization pressures tend to function as job demands (e.g. technostress, automation-driven standardization, compliance with digital protocols, etc.), which aligns with their mechanistic positioning. A robust empirical stream shows technostress and rapid digitalization (e.g. techno-overload/complexity) reduces well-being and engagement (Wang et al., 2023; López-Cabarcos et al., 2025).

Likewise, the ESG framework also adopts a mechanistic conception, since it reflects organizational engagement with policy-driven sustainability governance, reporting structures, formal accountability mechanisms, and audit-based compliance. Hence, the effect of an ESG-oriented culture on employees' level of engagement is heterogeneous, insofar as some of these factors can raise engagement for some cohorts (e.g. Gen-Z) (Lulewicz-Sas et al., 2025), they may create cultural misalignment for employees who prioritize financial incentives, business efficiency, or competitive performance over sustainability objectives (Eccles et al., 2020). Employees who do not strongly identify with social and environmental responsibility narratives may struggle to align with the overarching values of the organization (Gond et al., 2017; Sheehan et al., 2023).

Accordingly, we hypothesize:

The third hypothesis examines the direct impact of cultural fit on eNPS. Employees who experience a high degree of cultural fit are more likely to identify with their organization, leading to stronger engagement, motivation, and advocacy (Kristof-Brown, 1996; O'Reilly et al., 1991).

From a functional-structuralist perspective, cultural fit ensures alignment between individual and organizational goals, reinforcing positive advocacy behaviors (Denison and Mishra, 1995; Gioia and Pitre, 1990). Conversely, when employees experience cultural misalignment, they are more likely to withdraw, disengage, or actively criticize the organization, lowering eNPS scores (Burrell and Morgan, 1979).

Empirical evidence suggests that employees who perceive strong cultural fit are significantly more likely to act as promoters, whereas those experiencing cultural misalignment tend to be passive or detractors (Reichheld, 2011; Owen and Brooks, 2008).

Thus, we hypothesize:

Cultural archetypes influence employee Net Promoter Score (eNPS) not directly, but through the mediating role of cultural fit, which acts as a perceptual filter between organizational context and employee behavior. Employees do not assess culture in abstract terms; rather, they interpret it through the lens of their own values, expectations, and experiences (Kristof-Brown and Billsberry, 2013). Cultural fit thus becomes a critical psychological construct that shapes how individuals internalize organizational signals, influencing their engagement and willingness to advocate for their workplace.

For Organic Culture Archetypes—People, Goals, and Innovation—cultural fit exerts a positive mediating effect. These cultures foster openness, adaptability, collaboration, and empowerment. When employees perceive alignment with such environments, they are more likely to feel valued, motivated, and psychologically safe (Denison and Mishra, 1995; Edmondson, 1999). This sense of alignment strengthens belonging and purpose, enhancing intrinsic motivation and commitment—key predictors of advocacy within the eNPS framework. Thus, in cultures centered on trust, learning, and shared ambition, cultural fit reinforces the pathway from culture to advocacy.

Conversely, Mechanistic Culture Archetypes—ESG, Norms, and Digital—emphasize formalization, standardization, and top-down control. While such structures may support efficiency and compliance, they can also create rigidity and misalignment for employees who value autonomy, creativity, or informal collaboration. When personal values conflict with institutional expectations, cultural dissonance arises (Schein, 1985), weakening identification with the organization and reducing advocacy. In this context, cultural fit mediates the relationship negatively, dampening the potential positive effects these cultures might otherwise have on eNPS.

In line with Person–Organization Fit theory, we theorize cultural fit as the most proximal psychological mechanism linking organizational culture to advocacy. Accordingly, the model is specified in terms of full mediation, insofar as employees' advocacy is expected to depend less on cultural archetypes per se than on whether those archetypes are internalized as personally meaningful and value-congruent. Nevertheless, alternative specifications involving partial mediation remain plausible and should be examined in future research.

Thus, we hypothesize:

This study operationalized two core constructs—organizational culture archetypes and cultural fit—using the Cultural Fit Assessment Method (CFAM®), a validated framework grounded in the Competing Values Framework (CVF) (Quinn and Rohrbaugh, 1981, 1983; Cameron and Quinn, 2011) and expanded by Leal-Rodríguez and Sanchís-Pedregosa (2025). CFAM® extends the CVF by incorporating Digital and ESG archetypes, hence comprising six archetypes—People, Goals, Innovation, Norms, Digital, and ESG—each defined by a cluster of six universal values. To assess culture, participants ranked 36 values based on their relevance within their organization, enabling identification of dominant archetypes and capturing the coexistence of multiple value systems.

Cultural dynamics were assessed across three dimensions. First, participants evaluated their current organizational culture by ranking values that reflected the existing environment. Second, they ranked values representing their individual mindset, capturing alignment between personal and organizational values. Third, they identified values they considered essential for the desired future culture. This structure allowed CFAM® to generate a nuanced, data-driven analysis of cultural fit across organizational levels (Leal-Rodríguez and Sanchís-Pedregosa, 2025).

Cultural fit was measured through two indicators. The first captured alignment between current culture and personal values, reflecting how well employees identify with the present work environment. The second assessed alignment between current and desired culture, indicating the extent to which the existing configuration matches employees' expectations for the organization's future. Both indicators were derived through an algorithm comparing value rankings across dimensions, producing a continuous fit score, with higher values indicating stronger alignment.

Employee advocacy was measured using the Employee Net Promoter Score (eNPS), assessed through the standard single-item question: “On a scale from 0 to 10, how likely are you to recommend your company as a great place to work?” Following established methodology (Reichheld, 2003), responses were categorized as promoters (9–10), passives (7–8), and detractors (0–6). The eNPS score was calculated by subtracting the percentage of detractors from the percentage of promoters, yielding a single index of advocacy.

A non-probabilistic purposive sampling strategy, consistent with a deductive design, was employed to gather targeted, context-specific data. While this approach allowed for the collection of rich, diverse cultural data across multiple organizations, it limits statistical generalizability beyond the sampled contexts. As participants were not randomly selected, results should be interpreted cautiously when extrapolated to broader populations. Nonetheless, purposive sampling is appropriate for exploratory, theory-driven studies using PLS-SEM, where the emphasis is on model estimation rather than population inference (Hair et al., 2017). The sample included managers and staff from Spanish and Ibero-American firms, reflecting the view that culture emerges through shared practices across all organizational levels—not just from top-down leadership—consistent with current perspectives on culture as a co-constructed and dynamic process.

Data were collected via Minzer®, an intranet-based proprietary culture diagnostics platform that provided efficient organizational access while maintaining strict confidentiality protocols. To minimize leadership influence, participation was voluntary, no identifiable information was collected, and leaders had no access to individual responses. Anonymity was ensured through unique, randomized survey links and secure submission procedures. To mitigate common method bias (CMB), participants were assured of confidentiality, and questions were neutrally worded to reduce social desirability bias.

The final sample comprised 882 valid responses—well above the 200-respondent threshold recommended for multivariate and structural equation modeling (Kline, 2005)—with respondents from Spain (53%) and Ibero-America (47%). Participants represented diverse roles, locations, and genders (52% male, 39% female, 9% undisclosed). A post hoc power analysis was conducted to confirm the adequacy of the sample. Using the minimum R² method (Hair et al., 2017), the required sample size to detect an effect of f² = 0.129 with α = 0.05, power = 0.80, and k = 3 predictors is approximately n = 65; the present sample (n = 882) clearly exceeds this requirement. Consistent with this, a G*Power 3.1 sensitivity analysis (Faul et al., 2009) indicates that the achieved statistical power at the observed effect size exceeds 0.99, well above the conventional 0.80 threshold. The sample size is therefore considered more than adequate.

Partial Least Squares Structural Equation Modeling (PLS-SEM) has established itself as a second-generation multivariate analysis technique that is particularly valuable in social sciences and business research (Hair et al., 2017). This methodology is well suited for predicting target constructs and identifying key relationships in complex models with formative or reflective latent variables (Richter et al., 2016). PLS-SEM was chosen for its predictive orientation, the inclusion of six formative culture archetypes, and the model's formative–reflective mediation structure (culture → fit → eNPS). Culture archetypes were modeled formatively, as they represent distinct value sets that collectively define perceived organizational culture. Additionally, preliminary diagnostics indicated non-normal indicator distributions, further justifying the use of PLS-SEM, which does not assume multivariate normality. Although PLS-SEM is more robust to common method bias (Hair et al., 2017), procedural remedies were also applied, including psychological separation of predictors and outcomes to reduce consistency artifacts (Podsakoff et al., 2003).

The measurement model analysis followed established PLS-SEM guidelines (Hair et al., 2017; Ringle et al., 2020). This phase ensures the reliability and validity of the constructs (Sarstedt et al., 2017). An overview of the measurement model appraisal and the scales used in this study is provided in Table 1, which is available as Supplementary Material.

Our model distinguished between formative and reflective constructs, as recommended in the literature (Diamantopoulos and Siguaw, 2006). Formative constructs included the Organic and Mechanistic Cultural Archetypes. The Organic dimension comprised People, Goals, and Innovation Cultures, while the Mechanistic dimension included ESG, Norms, and Digital Cultures—each measured through six values-based indicators.

Reflective constructs, modeled as Mode A, included Cultural Fit (two items) and eNPS (one item). As effects of their latent constructs, reflective indicators must demonstrate internal consistency and inter-item correlation. Cultural Fit items CF1 (0.805) and CF2 (0.866) showed strong loadings, with composite reliability at 0.824—above the 0.70 threshold and below the 0.95 ceiling. eNPS, modeled as a single-item construct, had a fixed loading and composite reliability of 1.000.

Convergent validity was confirmed by AVE values of 0.700 (Cultural Fit) and 1.000 (eNPS), both exceeding the 0.50 threshold (Fornell and Larcker, 1981). Discriminant validity was also established: the square roots of AVE (0.837 for Cultural Fit; 1.000 for eNPS) exceeded inter-construct correlations, and the HTMT ratio of 0.521 remained below the conservative 0.85 threshold.

For formative constructs (Mode B), where indicators shape rather than reflect the construct, multicollinearity was assessed using the Variance Inflation Factor (VIF). All VIF values ranged from 1.004 to 1.386, well below the critical value of 5.0. Outer weights revealed the relative contribution of each archetype. Within Organic cultures, Goals had the strongest weight (0.785), followed by People (0.436) and Innovation (0.266). For Mechanistic cultures, ESG led (0.618), followed by Digital (0.463) and Norms (0.400) (see Table 2).

The structural model evaluation tested the hypothesized relationships in two phases. The baseline model examined the direct effects between cultural archetypes and the Employee Net Promoter Score (eNPS). Subsequently, the mediation model introduced Cultural Fit as a mediating variable to provide a more nuanced view of these relationships.

In the baseline model, Organic Culture Archetypes showed a positive and significant impact on eNPS (β = 0.160, t = 3.466, p < 0.001; 95% CI [0.061, 0.242]), while Mechanistic Culture Archetypes had a weaker but still significant negative effect (β = −0.086, t = 2.022, p = 0.043; 95% CI [−0.158, −0.005]). These results suggest that organic cultures foster employee advocacy, whereas mechanistic cultures may inhibit it, albeit to a lesser extent.

In the mediation model, Cultural Fit emerged as a significant explanatory mechanism. Organic Culture Archetypes positively predicted Cultural Fit (β = 0.180, t = 3.531, p < 0.001; CI [0.075, 0.275]), while Mechanistic Culture Archetypes showed a significant negative relationship (β = −0.211, t = 4.391, p < 0.001; CI [−0.300, −0.112]). Cultural Fit, in turn, strongly influenced eNPS (β = 0.353, t = 9.116, p < 0.001; CI [0.273, 0.425]).

Interestingly, when Cultural Fit was introduced as a mediator, the direct effects of both cultural archetype groups on eNPS became non-significant. For Organic Culture Archetypes, the direct effect dropped to β = 0.072 (t = 1.147, p = 0.251), and for Mechanistic Culture Archetypes, to β = 0.013 (t = 0.222, p = 0.824), with both confidence intervals including zero.

However, significant indirect effects were observed. The effect of Organic Culture Archetypes on eNPS through Cultural Fit was positive and significant (β = 0.064, t = 3.442, p < 0.001; CI [0.027, 0.099]). Mechanistic Cultural Archetypes showed a significant negative indirect effect through Cultural Fit (β = −0.075, t = 3.913, p < 0.001; CI [−0.113, −0.039]).

These results support a full mediation model, indicating that the influence of cultural archetypes on employee advocacy operates entirely through employees' perceived cultural alignment. Cultural Fit, rather than the cultural archetypes themselves, is the proximal predictor of eNPS (see Table 3).

The model's explanatory power was assessed using the coefficient of determination (R²) for both baseline and mediation models. In the baseline model, cultural archetypes alone explained 6.8% of the variance in Employee Net Promoter Score (eNPS), indicating limited predictive strength (R² = 0.068).

However, introducing Cultural Fit as a mediator significantly improved explanatory capacity. In the mediation model, R² for eNPS increased to 0.162, showing that 16.2% of its variance was explained—more than double the baseline result. Additionally, cultural archetypes explained 12.7% of the variance in Cultural Fit (R² = 0.127).

This comparison underscores the value of including Cultural Fit in the model. The substantial increase in explained variance confirms that cultural alignment plays a critical role in translating organizational culture into employee advocacy outcomes. Although R² for eNPS improves substantially when cultural fit is included, the absolute magnitude of R² remains within what Hair et al. (2017) classify as weak-to-moderate predictive accuracy. Such a level of explanatory power is theoretically plausible given that employee advocacy is shaped not only by cultural fit, but also by other contextual and individual factors not modeled here, (i.e. leadership quality, job design, incentives and rewards, career opportunities, and labor-market conditions, among others).

Besides, the f² results confirm that Cultural Fit is the only predictor with a meaningful effect on eNPS (f² = 0.129, approaching medium threshold), while both Organic Culture Archetypes (f² = 0.003) and Mechanistic Cultural Archetypes (f² = 0.000) show negligible to zero direct effects, supporting a mediation role for Cultural Fit between organizational culture and employee advocacy (see Table 4).

Using k-fold PLSpredict, we obtained positive Q²_predict values for both endogenous constructs—Cultural Fit (0.109) and eNPS (0.036)—as well as for all indicators (CF1 = 0.024; CF2 = 0.126; eNPS = 0.035), indicating out-of-sample predictive relevance compared to a mean predictor (Hair et al., 2021). To assess the strength of this relevance, we followed Shmueli et al. (2019) in comparing PLS-SEM prediction errors against those from a naïve linear model (LM) at the indicator level. PLS-SEM did not outperform LM on RMSE for any indicator, indicating no added predictive power relative to the LM benchmark. Overall, while the model demonstrates predictive relevance over the mean predictor, it does not exceed the performance of the linear model (see Table 5).

The Importance-Performance Map Analysis (IPMA) offers practical insights by integrating each construct's importance (total effects) with its performance (average scores) (Ringle and Sarstedt, 2016) (see Figures 2 and 3).

IPMA results reveal that Cultural Fit has the strongest total effect on eNPS, reinforcing its central mediating role in the structural model. Among the cultural archetypes, indicators related to Goals, People, and Innovation show the highest importance values—consistent with the structural model, where Organic Culture Archetypes have significant positive effects on Cultural Fit and, through it, on eNPS.

In contrast, Digital, ESG and Norms-related indicators display low importance, mirroring the model's negative paths from Mechanistic Cultural Archetypes to Cultural Fit. Their limited or negative influence suggests that emphasizing these values, especially in rigid, compliance-driven forms—may reduce perceived alignment. Thus, low-importance mechanistic indicators should not be dismissed, but rather interpreted as requiring relational or adaptive practices to enhance fit and advocacy.

Analytically, the IPMA pattern suggests that not all cultural levers are equally efficient for improving employee advocacy. The comparatively high importance of Goals, People, and Innovation indicates that these archetypes operate as high-yield alignment mechanisms, meaning that marginal improvements in these areas are more likely to translate into gains in fit and advocacy. By contrast, the low or negative contribution of Digital, ESG and Norms archetypes suggests that their organizational value may depend on complementary relational practices. In other words, formal systems alone appear insufficient; their contribution to advocacy increases when embedded in supportive, participatory, and autonomy-preserving contexts.

Therefore, from a managerial perspective, IPMA offers actionable guidance:

1. Organic Culture Archetypes (Goals, Innovation, People) represent strategic priorities for improving Cultural Fit and boosting eNPS—offering potential “quick wins.”

2. Mechanistic Culture Archetypes (ESG, Norms, Digital) should be applied judiciously; while essential for compliance, overemphasis without accompanying flexibility or inclusion may undermine fit and advocacy.

The results support the core proposition that cultural fit is the key mechanism through which cultural archetypes influence employee advocacy. The study's originality lies in empirically testing this mechanism within an extended six-archetype CVF model and in positioning eNPS as a meaningful advocacy outcome linked to cultural alignment (Quinn and Rohrbaugh, 1981, 1983; Cameron and Quinn, 2011; Reichheld, 2003, 2011; Owen and Brooks, 2008).

The findings show that Organic Culture Archetypes (People, Goals, Innovation) are positively associated with cultural fit, suggesting that adaptive, collaborative, and purpose-driven cultures foster stronger alignment. In contrast, Mechanistic Culture Archetypes (Norms, Digital, ESG) are negatively associated with cultural fit, reflecting value misalignment between employees and organizational practices. Taken together, these complementary patterns provide convergent support for Person–Organization Fit theory (Kristof-Brown et al., 2005), by showing that both value congruence and incongruence systematically shape employee outcomes and reinforce the role of cultural congruence in driving positive employee attitudes and behaviors.

These findings suggest that the cultural enactment of digitalization or ESG commitments may become misaligned when perceived primarily as compliance-driven or imposed through rigid governance logics. This interpretation aligns with recent work emphasizing that digital transformation is a socio-technical process that reconfigures human–digital work arrangements, making cultural alignment a critical implementation factor (Nadkarni and Prügl, 2021; Martínez-Caro et al., 2020; Warner and Wäger, 2019). Research also underscores the pivotal role of leadership in translating digital initiatives into value-congruent cultural practices (Bevilacqua et al., 2025; Grover et al., 2022; Kraus et al., 2022). Similarly, the negative association with ESG archetypes supports arguments that ESG performance is shaped not only by strategic intent but also by cultural and mindset-related barriers to adoption and internalization (Eccles et al., 2020; Sheehan et al., 2023; Bai et al., 2024).

Importantly, these findings should not be interpreted as suggesting that Digital or ESG archetypes are intrinsically detrimental to cultural fit. Rather, their effects appear contingent on how they are implemented and experienced by employees. When digitalization and ESG agendas are enacted through participatory, dialogic, and enabling practices, they may function as cultural resources that strengthen meaning, learning, and identification. By contrast, when they are introduced primarily through compliance-driven, top-down, and control-oriented mechanisms, they are more likely to be experienced as demands that weaken perceived cultural alignment. These relationships are also likely to be context-sensitive. The negative association observed here may vary according to organizational maturity, national setting, sector, leadership style, and the stage of digital or ESG implementation. In more mature transformation contexts, or where these agendas are enacted through participatory leadership and strong sensemaking, Digital and ESG cultures may be experienced less as control systems and more as shared value systems. This suggests that the present findings should be interpreted as contingent rather than universal, opening a productive avenue for future comparative research.

Taken together, the mediation findings are best understood through the joint contribution of the three theoretical lenses mobilized in this study. From a functionalist perspective, cultural archetypes shape the normative conditions that enable or constrain organizational coherence. From a structuralist perspective, employees do not merely absorb those cultural signals passively, but interpret them through identity, experience, and context, which makes perceived cultural fit the key interpretive mechanism. From the JD-R perspective, these same cultural environments operate as configurations of resources and demands that influence motivation, well-being, and, ultimately, advocacy. Considered together, these lenses explain why organizational culture affects eNPS not directly, but through the extent to which employees experience that culture as aligned with their own values and expectations. (Chatman and O'Reilly, 2016; Reichheld, 2003).

This study presents four main theoretical contributions:

First, it expands the Competing Values Framework (CVF) by introducing two new cultural archetypes: Digital Culture and ESG Culture. While the CVF has been widely used in organizational research, it has historically been limited to four cultural dimensions. The addition of Digital and ESG cultures reflects the evolving nature of contemporary organizations, where technological transformation and sustainability commitments play an increasingly prominent role (Bai et al., 2024; Orero-Blat et al., 2024). By integrating Digital and ESG cultures, the study advances organizational culture research by reflecting the growing influence of technological and sustainability-driven values in contemporary corporate environments.

Second, this study advances Person–Organization Fit theory by offering an empirically tested, multidimensional approach to assessing cultural alignment. CFAM® operationalizes fit as value congruence within culturally plural organizations, extending traditional models by capturing tensions between current and desired cultural states. This dynamic conceptualization addresses critiques of static fit measures and aligns with research framing fit as an adaptive process embedded in organizational change and evolving cultural contexts (Kristof-Brown et al., 2005; Kristof-Brown and Billsberry, 2013; Gelfand et al., 2017).

Third, the study establishes a direct link between cultural fit and employee advocacy, measured through eNPS. While prior research has primarily connected fit to attitudinal outcomes such as job satisfaction and commitment (Kristof-Brown et al., 2005; Verquer et al., 2003), these findings position advocacy as a distinct behavioral outcome linking internal alignment to external reputation (Reichheld, 2003, 2011; Chatman and O'Reilly, 2016). By integrating eNPS into the culture–fit framework, the study extends engagement research toward advocacy-focused outcomes, consistent with growing support for net promoter–type metrics in employee research (Owen and Brooks, 2008; Brown, 2020).

Fourth, the full mediation pattern has an important theoretical implication: organizational culture appears to matter for employee advocacy primarily insofar as it is subjectively internalized as perceived fit. In other words, culture does not automatically translate into advocacy simply because certain values are institutionally present. Its influence depends on whether employees experience those values as congruent with their own preferences, identities, and expectations. This reinforces the view that culture is behaviorally consequential through interpretive and psychological mechanisms rather than through structural characteristics alone.

For managers, the findings highlight cultural fit as a strategic lever for sustaining engagement and advocacy during transformation. Organizations aiming to shift from rigid, mechanistic cultures to more organic configurations can do so by redesigning managerial practices and everyday routines. Involving employees in co-designing digital workflows, establishing cross-functional innovation labs, or granting teams greater discretion to experiment with new tools can foster autonomy and psychological safety, thereby enhancing cultural alignment.

During digital or ESG-driven transformations, misalignment can be reduced by translating strategic goals into locally meaningful practices. Rather than approaching ESG primarily through compliance metrics, organizations can embed sustainability objectives into team goals, daily decisions, and recognition systems. Similarly, digital initiatives are more effective when leadership emphasizes learning, dialogue, and shared sensemaking over control and monitoring.

For HR professionals, CFAM® offers a diagnostic framework to align talent attraction, onboarding, and retention with lived cultural values. Early-stage diagnostics can identify emerging misalignments, inform leadership development, and guide targeted interventions that support cultural evolution during strategic change.

This study aims to explain how organizational culture archetypes shape employee advocacy through the mediating role of cultural fit. The findings show that Organic Culture Archetypes strengthen perceived fit and, through it, enhance eNPS, whereas Mechanistic Culture Archetypes weaken fit and indirectly suppress advocacy. In doing so, the study contributes to the literature by extending the CVF with Digital and ESG archetypes, by operationalizing cultural fit through a multidimensional values-based approach, and by demonstrating that employee advocacy is shaped primarily through employees' perceived cultural alignment rather than by cultural archetypes directly.

These results are timely and relevant for management research and practice because they show that contemporary strategic agendas such as digitalization and ESG do not generate positive employee outcomes automatically. Their effects depend on whether employees experience them as meaningful, participatory, and congruent with their own values. This highlights the strategic opportunity for organizations to manage transformation not only through systems and structures, but also through cultural alignment.

Despite its strengths, this study has limitations that suggest avenues for future research. The use of non-probabilistic sampling limits generalizability; although the sample was sizable (n = 882), future studies should employ probabilistic sampling across industries and regions. The cross-sectional design also restricts causal inference and precludes observation of how cultural fit evolves during organizational transformation. Longitudinal studies would be especially valuable, given prior evidence that fit and commitment shift over time in response to change.

Additionally, while eNPS is a widely used and conceptually relevant proxy for advocacy, its single-item nature may not fully capture the complexity of engagement. Future research could combine eNPS with multidimensional constructs—such as psychological engagement or well-being—to broaden explanatory scope (Schaufeli and Bakker, 2004). Nevertheless, HRD research supports the criterion validity of net promoter–type metrics when applied thoughtfully in organizational contexts (Brown, 2020).

Future studies should also explore moderating mechanisms, such as leadership style and hybrid work arrangements (Carter and Greer, 2013), to better understand when digital and ESG archetypes function as cultural resources versus demands. In addition, future research should incorporate robustness checks such as multigroup analysis across countries, demographic strata, organizational levels, and industry settings to assess whether the structural relationships identified here remain stable across heterogeneous contexts.

The authors used AI-assisted tools exclusively for grammar, wording, and clarity improvements during the editing phase.

The supplementary material for this article can be found online.