The strategic advantage of innovative organizational culture: An exploratory analysis in digital transformation and big data analytics capabilities

Abstract

This study examines the antecedent role of organizational culture and the mediating role of digital transformation when promoting big data analytics capabilities. Employing the Competing Values Framework, we scrutinize the influence of various cultural typologies, including digital culture on the successful deployment of digital transformation and the enhancement of big data analytics capabilities. Our analysis utilizes Partial Least Squares Structural Equation Modeling on a dataset of 183 firms to evaluate our hypotheses. The findings reveal that adhocratic, digital and hierarchical cultures significantly foster big data analytics capabilities mediated by digital transformation, which is a dynamic process that needs supportive digital and innovative values. In contrast, market and clan cultures exhibit weaker linkages. By providing empirical evidence and practical implications, this study highlights how organizations with a strong adhocratic and digital cultures outperform those with traditional cultures in their digital transformation and big data analytics capabilities efforts.

Introduction

In the dynamic arena of contemporary business, digital transformation (DT) has undoubtedly ascended as a strategic imperative, fundamentally redefining processes, strategies, operations, and business models (Orero-Blat, Jordán, & Palacios-Marqués, 2022; Verhoef et al., 2021; Vial, 2019). Integral to leveraging this transformation, big data analytics capabilities (BDAC) serve as foundational constructs, enabling organizations to harness the exponential data growth for informed decision-making and competitive differentiation (Mikalef, Boura, Lekakos, & Krogstie, 2019; Mikalef, Krogstie, Pappas, & Pavlou, 2020; Wamba, Queiroz, Wu, & Sivarajah, 2020). Such capabilities, encompassing workforce, management, and infrastructure analytics, are essential for actualizing the investment in DT (Kim, Ritchie, & McCormick, 2012; Mikalef et al., 2019; Orero-Blat, Palacios-Marqués, Leal-Rodríguez, & Ferraris, 2024).

While the antecedents of BDAC have been subject to extensive scrutiny, organizational culture (OC) remains a relatively uncharted determinant (Chen, Lu, Wang, & Pedrycz, 2024; Upadhyay & Kumar, 2020). It has been argued that a deep understanding of cultural nuances is essential for a successful digital transition (Firican, 2023; Pedersen, 2022). Therefore, the lack of an adequate culture is also seen as the main obstacle to DT and the main reason why this difficult process often fails (Lunde et al., 2019). Research posits that without a proper cultural bedrock attuned to the exigencies of digital change, efforts to promote DT and BDAC may prove futile (Hemerling, Kilmann, Danoesastro, Stutts, & Ahern, 2018).

Studies like Pradana, Silvianita, Syarifuddin, and Renaldi (2022) concluded that OC becomes a key factor in enhancing digital strategy and performance, but digitalization doesn’t affect culture. For this reason, we focus on the antecedent role of OC in DT. Pfaff, Wohlleber, Münch, Küffner, and Hartmann (2023) have investigated the impact of OC dimensions, based on Hofstede’s model (Hofstede, 1998), on the process of DT. Nguyen (2018) analyzed the impact of OC in big data following Competing Values Framework (CVF) (Quinn and Rohrbaugh, 1983) but it has been demonstrated that without DT and BDAC an organization is not able to fully extract all value of big data (Gupta & George, 2016). Steiber and Alvarez (2023) posited that several values aligned with digital culture (Leal-Rodríguez, Sanchís-Pedregosa, Moreno-Moreno, & Leal-Millán, 2023) favor DT, but they do not consider in their research BDAC and its key role for organizations. As seen, the literature lacks a detailed exploration of specific cultural typologies that catalyze BDAC and the pivotal role of DT within this interplay. This study aims to close this research gap by exploring in detail how an organization’s cultural typology can be a key antecedent to the successful implementation of DT and the effective promotion of BDAC. So, the research question is: Which is the cultural archetype that favors the most DT and the promotion of BDAC?

Employing the Organizational Culture Assessment Instrument (OCAI) as outlined by Cameron and Quinn (1999), which draws from the CVF (Quinn and Rohrbaugh, 1983), and complemented by Leal-Rodríguez et al.’s (2023) digital culture scale, this study endeavors to align the assessment with contemporary organizational realities. This integration is crucial as it introduces the digital culture archetype, characterized by openness to innovation, technological fluency, agility, and data-centric decision-making. Unlike traditional cultural types such as hierarchical, market, and clan cultures, digital culture emphasizes continuous learning, rapid adaptation, and seamless integration of new technologies. The sample is composed by 183 Spanish companies from the point of view of the heterogeneity of the sectors. To do so, we will use the Partial Least Squares Structural Equation Modeling (PLS-SEM) methodology, in line with approaches by Felipe, Roldán, and Leal-Rodríguez (2017), Ashrafi, Ravasan, Trkman, and Afshari (2019), and Leal-Rodríguez et al. (2023).

This study contributes to the CVF theory by emphasizing the strategic importance of cultural typologies within organizations for DT and BDAC promotion. It offers novel insights into the domain of TD by meticulously detailing OC and identifying cultural typologies that positively influence the development of BDAC, mediated by DT. This is important because misalignment between OC and DT process could risk employees being unable to identify strategy and resist improvement initiatives (Carvalho, Sampaio, Rebentisch, Carvalho, & Saraiva, 2019). Such insights equip managers with the knowledge to effectuate incremental cultural adjustments, propelling organizations toward the successful realization of DT benefits.

Subsequent to this introduction, the ensuing sections delineate the research model, hypotheses, and theoretical foundations, followed by a description of the research methodology. The fourth section presents the empirical findings from the PLS-SEM analysis, and the paper culminates with a discussion of the implications, conclusions, and the broader impact of the study.

Theoretical framework

DT and BDAC

DT is a strategic priority for modern organizations, aiming to enhance technology-related resources to reduce costs, create new business opportunities, and improve organizational processes (Nicolás-Agustín et al., 2022). However, simply investing in digital technologies is not enough; organizations must also develop the necessary skills and foster the right culture to fully harness the benefits of DT (Coco et al., 2024).

DT facilitates better information exchange, improves operational efficiency and productivity (Loebbecke & Picot, 2015), and enhances stakeholder value (Choy & Kamoche, 2021). A key result of DT is the development of BDAC, which require a certain level of digital maturity within the organization (Pramanik, Kirtania, & Pani, 2019). BDAC enable companies to leverage data effectively, turning digital investments into actionable insights and competitive advantages (Mikalef et al., 2019).

The synergy between DT and BDAC is essential for organizations to maximize the value of their data, improving decision-making and increasing their agility in dynamic environments (Barlette & Baillette, 2022; Ceipek et al., 2021; Wamba et al., 2017). Without sufficient digital maturity and a strong foundation of DT, organizations may struggle to fully develop BDAC and unlock the full potential of their digital initiatives (Gupta & George, 2016).

OC and CVF

Following with the concept of OC, one can say that it can be characterized in various forms; it encapsulates the shared values, beliefs, and practices that unify the members of an organization – essentially, the ‘social glue’ that cements the organization’s collective identity. It encompasses an organization’s commitment to adapt and evolve within the technological milieu, striving to meet or anticipate future demands. This adaptability necessitates that organizations not only protect their core values to maintain strategic, functional, and operational continuity but also sustain their cultural essence amidst change (Leal-Millán, 1991; Schein, 1985).

This research adopts the CVF by Cameron and Quinn (1999), a seminal and widely applied model in the study of OC. The CVF outlines two key dimensions: one contrasting the focus on stability, order, and control with a focus on flexibility, dynamism, and adaptability; the other juxtaposing an external orientation – marked by differentiation, competition, and rivalry – with an internal orientation that promotes integration, unity, and collaboration. Intersecting these dimensions yields four distinct, yet complementary, cultural typologies: clan, adhocratic, market, and hierarchy, each with its own defining characteristics. Furthermore, recognizing the evolution of organizational environments, recent scholarship has introduced a digital cultural archetype. Pedersen (2022) and Leal-Rodríguez et al. (2023) have substantiated this with a validated psychometric scale.

The study of Zhang, Khan, Wang, and Tang (2023) about open government data highlights the profound influence of national culture on technological adoption, suggesting that similar cultural dimensions within organizations can significantly impact the successful deployment of DT and BDAC, due to the great importance of corporate values as predictors of the behavior and attitudes of the people who form the company (Clouet, Leal-Rodríguez, Sanchís-Pedregosa, & Orero-Blat, 2024). However, despite the established influence of OC on various organizational processes, knowledge about its specific role as a catalyst or barrier in the context of DT remains limited (Nicolás-Agustín, Jiménez-Jiménez, & Maeso-Fernández, 2022). The current literature on cultural archetypes provides the groundwork from which we draw inferences and postulate our research hypotheses, particularly concerning the alignment of cultural micro foundations and values with the nurturance of BDAC.

Research model and hypotheses development

In this section of the literature review, the five hypotheses of this research and finally the research model derived from them will be presented in a concise form.

The impact of clan culture on DT and BDAC

According to the model proposed by Cameron and Quinn (1999), some of the values that characterize the clan cultural archetype are cohesion, commitment, participation, integration and teamwork. Teamwork, collaboration, and team cohesion have been shown in several studies to be HRM practices favorable to DT (Bartsch et al. 2020). Collaboration and data sharing across business services also foster flexibility and responsiveness (Ciacci, Balzano, & Marzi, 2024). The development of BDAC requires greater collaboration, but also fosters this necessary collaboration that clan culture has intrinsic to its core values (Barlette & Baillette, 2022). Mutual trust between the firm and its employees is essential in today’s increasingly digital workplace (Akhtar et al., 2019). Working from home and having flexible hours are becoming norms, yet these conveniences call for the organization to have faith in its members’ dedication to the organization’s mission. Clan culture groups also foster a culture that is tolerant of failure and promotes knowledge sharing (Nanayakkara, Wilkinson, & Halvitigala, 2021), which is a necessary condition for creativity (Kane, Palmer, Phillips, Kiron, & Buckley, 2015).

However, clan culture is typical of family businesses where the CEO is the owner, who acts as a guide and mentor, but where there is no room for large investments in DT due to the size or possibilities (Barlette & Baillette, 2022). This creates some inconsistencies in the literature regarding the impact of clan culture in DT and BDAC. Nonetheless, when the relationship between clan culture and BDAC is mediated by DT, this cultural archetype’s positive influence on BDAC is likely to increase, as supported by previous studies (Pramanik et al., 2019; Troisi, Grimaldi, & Loia, 2021). We hypothesize the following assumptions:

Hypothesis 1: Clan culture has a positive and significant effect on DT.

Hypothesis 2: Clan culture has a positive and significant effect on BDAC.

Hypothesis 3: DT mediates the effect of clan culture on BDAC.

The impact of adhocratic culture on DT and BDAC

Adhocratic culture is the cultural archetype best suited to facilitate an organization’s DT, according to Cameron and Quinn (1999). This archetype is characterized by values such as dynamism, creativity, autonomy, boldness, and the ability to embrace change. Organizations with an adhocratic culture typically display high levels of risk tolerance (Fitzgerald, Kruschwitz, Bonnet, & Welch, 2014), active employee engagement in strategic decision-making (Nicolás-Agustín et al., 2022), and desire and propensity for adopting new ideas and continuous improvement (Leso, Cortimiglia, & Ghezzi, 2023; Xie, Wu, Xie, Yu, & Wang, 2021).

A key strength of this culture is its organizational agility, which involves the ability to detect changes in the environment and mobilize resources quickly to respond (Felipe, Leidner, Roldán, & Leal‐Rodríguez, 2020). In the context of DT, this agility is crucial, as it enables organizations to rapidly adapt to external threats and opportunities, making timely decisions that maximize the value of data analytics (Barlette & Baillette, 2022). The leadership in adhocratic cultures tends to be visionary and bold, characteristics that align well with a data-driven orientation and contribute positively to both DT and the development of BDAC (Akhtar et al., 2019; Troisi, Grimaldi, & Loia, 2021).

Furthermore, the adhocratic culture’s openness to new knowledge is a fundamental component of BDAC (Mikalef et al., 2019). Overall, this cultural archetype views change as a positive force and a source of opportunity in today’s dynamic environment (Felipe et al., 2017), positioning it as an ideal environment for fostering both DT and BDAC.

From the previously literature discussed, we hypothesize the following:

Hypothesis 4: Adhocratic culture has a positive and significant effect on DT.

Hypothesis 5: Adhocratic culture has a positive and significant effect on BDAC.

Hypothesis 6: DT mediates the effect of adhocratic culture on BDAC.

The impact of market culture on DT and BDAC

The market culture is characterized by values such as result-orientation, excellence, competitiveness, pragmatism, and ambition (Cameron & Quinn, 1999). This cultural archetype is often found in multinational corporations, consultancies like the ‘big 4,’ and investment banks, where leaders take on managerial and producer roles, driving productivity and emphasizing achievement feedback to workers. Market culture promotes high control, stability, and aggressive competition, which can hinder the DT process and the development of BDAC (Troisi, Grimaldi, & Loia, 2021; Verhoef et al., 2021).

The core values of stability and control are generally at odds with the flexibility and risk tolerance required for effective DT. The focus on winning, reputation, and success may conflict with the principles of experimentation and failure tolerance that are essential for fostering DT and, subsequently, BDAC. Leal-Rodríguez et al. (2023) also argue that values such as competitiveness, pragmatism, and ambition can act as barriers to DT.

However, some literature suggests that market culture’s focus on predicting market trends and understanding competition can enhance organizational agility, aiding in faster decision-making and improving knowledge management (Barlette & Baillette, 2022; Felipe et al., 2017). This, in turn, can reduce uncertainty and improve team effectiveness through control and adherence to deadlines, although the relationship between market culture and DT remains inconsistent across studies.

Proposed research hypotheses regarding market cultural archetype are as follows:

Hypothesis 7: Market culture has a negative and significant effect on DT.

Hypothesis 8: Market culture has a negative and significant effect on BDAC.

Hypothesis 9: DT mediates the effect of market culture on BDAC.

The impact of hierarchy culture on DT and BDAC

According to Felipe, Roldán, and Leal-Rodríguez (2016), some attributes related to the hierarchical culture archetype such as the stress on controlling, standardized processes and bureaucratic approaches lead an organization to have more organizational agility. As commented, different studies confirmed the positive relationship between the organizational agility and BDAC (Barlette & Baillette, 2022; Dubey et al., 2021), which in turn is also related to a higher level of DT as it enables the option to change, to deal with uncertain environmental factors, and to better adapt to every contingency that the process entails (Ashrafi et al., 2019).

Hierarchy culture is also characterized by its efficiency, and leaders often take on the role of organizers and coordinators of activities and validation of processes. Also, this cultural archetype hides a high level of knowledge management, which can be beneficial for DT in times of crisis and uncertainty, according to Felipe et al. (2017). However, there are many values intrinsic to a hierarchical culture that contradict everything previously studied about DT, especially about its micro-foundations and the values needed to achieve it such as formality, coordination, stability, and responsibility (Leal-Rodríguez et al., 2023). Hierarchical culture has an internal orientation, stability, and is based on power and tradition. It is difficult to change the status quo or processes in companies that base their culture on hierarchy as delegation of tasks, collaboration or speed in processes is not favored (Trenerry et al., 2021). According to some studies such as Hemerling et al. (2018), innovative firms and digital-oriented firms were less likely to exhibit control and internal direction, fundamental values of this type of culture.

From the previously discussed effects of the relationship between hierarchical culture, DT, and BDAC, we propose the following hypotheses:

Hypothesis 10: Hierarchy culture has a positive and significant effect on DT.

Hypothesis 11: Hierarchy culture has a positive and significant effect on BDAC.

Hypothesis 12: DT mediates the effect of hierarchy culture in BDAC

The impact of digital culture on DT and BDAC

The digital cultural archetype was developed based on numerous studies that examined the values of ‘born-digital’ companies and start-ups, which demonstrated strong adaptability to DT and digital environments (Leal-Rodríguez et al., 2023; Pradana et al., 2022; Steiber & Alvarez, 2023). This archetype reflects the characteristics necessary for thriving in a fast-paced digital landscape, including openness to change, risk-taking, agility, entrepreneurship, cooperation, an analytical mindset, and a digital orientation (Firican, 2023; Steiber & Alvarez, 2023; Upadhyay & Kumar, 2020).

Research shows that companies born in the digital era or with disruptive business models often exhibit a high tolerance for risk and failure, which is critical for successfully navigating DT and also to create BDAC. These organizations are built around values that align with rapid adaptability to environmental changes, which is essential for harnessing digital opportunities (Ciacci et al., 2024; Hemerling et al., 2018) and maximizing the value of BDAC (Mikalef et al., 2020). Companies with a digital culture emphasize collaboration, sharing information and experiences, and continuous learning, which aligns with the key behaviors needed to adapt to both internal and external demands (Kane et al., 2015; Vial, 2019).

Flexibility and knowledge are crucial in this current historical period. Culture generates knowledge, in this case, digital culture, means entering the renewal process. A successful DT is facilitated by dynamic capabilities and a digital culture (Kane et al., 2015; Vial, 2019), and for BDAC to succeed, a digital culture is crucial (Mikalef et al., 2019).

An organization will only acquire the benefits of BDA if the invest sufficient in digital culture and a proper DT framework (Hemerling et al., 2018; Upadhyay & Kumar, 2020; Wamba et al., 2020). The values of this archetype, along with behaviors like adaptability and data interpretation, position organizations for success in a digital environment.

Hypothesis 13: Digital culture has a positive and significant effect on DT.

Hypothesis 14: Digital culture has a positive and significant effect on BDAC.

Hypothesis 15: DT mediates the effect of digital culture on BDAC.

The role of DT on the generation of BDAC

It has been extensively researched that the creation of BDAC is impossible without a specific degree of DT, which is indicated by the amount of digital maturity that a firm achieves (Pramanik et al., 2019; Troisi et al., 2021). This is because, after a minimum of openness, technology, digital mindset, collaboration, and procedures with the necessary infrastructure are in place, the organization must be ready to acquire and cultivate specific competencies linked to BDA such as in Loebbecke and Picot (2015), Choy and Kamoche (2021) and Orero-Blat et al. (2024). We may formulate the following study hypothesis and even go so far as to say that DT is a prerequisite for BDAC promotion.

Hypothesis 16: DT has a positive and significant effect on BDAC.

The relationships between the above variables and hypotheses are then graphically represented, resulting in the subsequent research model (Figure 1).

Source: Own elaboration

Figure 1. Research model.

Methodology

The research process for this study conducted several steps:

1. 1. Study target definition: To ensure the relevance and accuracy of the data, we established specific criteria for organizations eligible to participate in our survey. Given the early stage of DT among many Spanish companies, we implemented a filter to exclude organizations that were not sufficiently advanced in their DT efforts. Therefore, we set the requirement of an annual turnover exceeding €7 million and a significant engagement in the DT process. Additionally, to ensure the respondents had the necessary expertise, we required that they held managerial roles with proficiency in big data and DT tools. This ensured that both the organization and the respondent were equipped to address the complexities of DT.

2. 2. Sampling: A non-probabilistic convenience sampling method was employed, drawing participants from various Spanish sectors, with a predominance in information technology (28.42%), financial services (15.3%), and logistics (12.02%), followed by non-financial services (6.56%), the metal-mechanical industry (4.37%), and traditional sectors including footwear, textiles, wood, and toy manufacturing (3.83%), as well as tourism (3.83%).

3. 3. Questionnaire development and measures: We used the CVF (Cameron & Quinn, 1999) to measure OC, extensively applied across diverse organizational dimensions including agility, human resources, quality management, learning capabilities, and innovation outcomes (Cameron & Quinn, 1999; Felipe et al., 2017; Leal-Rodríguez, Albort-Morant, & Martelo-Landroguez, 2017). It was supplemented with the digital culture scale by Leal-Rodríguez et al. (2023) to incorporate attributes of digital culture. For DT and BDAC, use scales from Nicolás-Agustín et al. (2022) and Kim et al. (2012), respectively. All scales are detailed in Annex I.

4. 4. Data collection: A total of 183 valid survey responses were collected in July 2022, using a 1- to-7-point Likert scale questionnaire. The demographic distribution was 46% female, 54% male, with 55% aged between 18 and 39 years and 45% between 40 and 66 years. Within the organizational hierarchy, 18.03% were CEOs or general managers, 12.57% were CIOs, and 16.94% were dedicated DT managers, alongside other executive or middle management positions, including COO, CMO, or CFO.

5. 5. Analysis tools: Partial Least Squares Structural Equation Modelling (PLS-SEM) was used for hypothesis testing. The software SmartPLS v3.2.9 (Ringle, Da Silva, & Bido, 2015) was employed to estimate the measurement, structural, and predictive model. PLS-SEM is particularly effective for exploring interrelations among latent constructs such as attitudes, beliefs, and behaviors within complex frameworks, making it well-suited for this study’s focus on digital culture’s predictive influence (Hair, Ringle, & Sarstedt, 2011). Moreover, it fits perfectly with the exploratory nature of our paper’s objectives among the OC, DT, and BDAC constructs. According to Hair, Sarstedt, Hopkins, and Kuppelwieser (2014), it is a good fit for examining the connections between latent categories like attitudes, beliefs, and actions in complex systems. Its robustness in handling models with composite constructs has been reinforced through empirical simulations (Felipe et al., 2020; Leal-Rodríguez et al., 2023) and previous scholarship (Henseler et al., 2014; Rigdon, Sarstedt, & Ringle, 2017), with its neutrality (Sarstedt, Hair, Ringle, Thiele, & Gudergan, 2016) and consistency (Rigdon, 2016) being particularly noted. PLS-SEM is a suitable tool for analysis, since this study also attempts to evaluate the prediction capacity of important components in connection to digital culture.

6. 6. Hypothesis testing: Finally, we analyze the relationships between OC, BDAC, and DT, using PLS-SEM to explore how these constructs interrelate. This could be seen in the following section.

Results

Measurement model

The evaluation of the measurement model should comprise for such constructs the following steps: individual item reliability, composite reliability, convergent validity, and discriminant validity. Table 1 reveals that most of the items achieve outer loadings of at least 0.891. Construct level assessment confirms that the Cronbach’s α, composite reliability, and Rho A indicators surpass the 0.7 threshold (Hair et al., 2014), substantiating composite reliability. Notwithstanding a few items within the OC falling below this benchmark, the retention of these items is justified in deference to the established validity of the classical OC scale (Cameron & Quinn, 1999).

Table 1. Measurement model

Source: Own elaboration from SmartPLS software version 3.2.9 (Ringle et al., 2015).

Besides, the average variance extracted exceeds 0.5, and therefore the constructs satisfy convergent validity according to the criteria of Fornell and Larcker (1981), which postulates that more than 50% of indicator variance should be accounted for by the construct. Finally, the model attains discriminant validity by applying the Heterotrait-Monotrait (HTMT) approach (Henseler et al., 2014).

In the conceptual model, the constructs shaping cultural archetypes as well as BDAC are modeled in formative mode (mode B), while DT is articulated in reflective mode (mode A). This approach aligns with Leal-Rodríguez et al. (2023) and is consistent with precedent research that has applied Mode B estimation for cultural archetypes within the OCAI framework (Roldán & Sánchez-Franco, 2012; Felipe et al., 2017). Accordingly, discriminant validity analysis is not requisite for formative constructs; however, an assessment of potential collinearity is imperative. The model’s Variance Inflation Factor satisfies the stringent criterion posited by Petter, Straub, and Rai (2007), remaining below the benchmark of 3.3. Subsequently, an examination of the weights illustrates the significance and magnitude of each indicator’s contribution to the composite construct (Chin, 1998). This analysis permits a hierarchical classification of indicators based on their contribution magnitudes.

Structural model

Table 2 encapsulates the necessary parameters for the structural model’s evaluation. An initial examination reveals the coefficient of determination (R ²), a measure of the variance explained and indicative of model efficacy, which ideally approaches unity for augmented explanatory power (Chin, 1998). The R ² values in our study surpass the 0.6 benchmark stipulated by Chin (1998), denoting a robust explanatory mode.

Table 2. Structural model

Source: Own elaboration from SmartPLS software version 3.2.9 (Ringle et al., 2015).

The evaluation progresses with an examination of the structural relationships between constructs, scrutinizing the sign, magnitude, and statistical strength of the coefficients. Following the criterion set forth by Hair et al. (2011), a p-value below .05 is indicative of a statistically significant relationship. The analysis confirms significant statistical support for the direct influences of adhocratic culture on DT, market culture on BDAC, hierarchy culture on both DT and BDAC, and digital culture on DT. Additionally, DT demonstrates a significant positive effect on BDAC.

However, the analysis extends beyond direct relationships to consider the nuanced interplay where DT acts as a mediating variable. It is in the investigation of these indirect relationships where the cultural archetypes’ impact on BDAC, as mediated by DT, becomes particularly salient. All hypotheses, save for two concerning clan and market cultures, garner empirical support. This exception suggests that the intrinsic values associated with clan and market cultures do not inherently facilitate DT, nor do they foster the genesis of BDAC within the organization.

It is therefore posited that adhocratic, hierarchical, and digital cultures, when embedded within an organization that has undergone DT, significantly enhance BDAC. These results not only resonate with but also expand upon the findings of prior studies by Felipe et al. (2017), Upadhyay and Kumar (2020), Wamba et al. (2020), and Leal-Rodríguez et al. (2023), providing fresh insights into the academic dialogue. A comprehensive discussion of these findings and their broader implications is forthcoming in the concluding section of this paper.

Predictive analysis

In the concluding segment of our empirical analysis, we appraise the predictive capability of the conceptual model. This evaluation addresses the influence of varying cultural archetypes on DT and BDAC, offering a valuable theoretical and practical contribution. The ability to forecast organizational performance in DT and BDAC creation based on a diagnostic of their OC stands as a significant advancement. To measure the model’s predictive ability, we adhere to the methodology proposed by Shmueli and Koppius (2011), which advocates for a positive Q² coefficient at both the construct and indicator levels as evidence of model robustness. Table 3 reveals that this is met in all cases, reaching levels of 0.752 as in the case of BDAC. Thus, the posited model raises predictive ability both at the constructs and indicators levels.

Table 3. Predictive ability

Source: Own elaboration from SmartPLS software version 3.2.9 (Ringle et al., 2015).

Discussion

Following the line of Warner and Wäger (2019), Duerr et al. (2018), and Pfaff et al. (2023), our findings imply that transformation is a continuous process, demanding ongoing commitment from organizations to cultivate a digital OC conducive to overcoming future challenges. Moreover, our results underscore the necessity for OC to evolve toward managing organizational barriers and structural modifications (Martínez-Caro, Cegarra-Navarro, & Alfonso-Ruiz, 2020; Vial, 2019), thereby enabling companies to harness the extensive benefits that arise from DT that could foster innovation.

The results draw attention to the influence each cultural archetype exerts on DT and the promotion of BDAC. A nuanced analysis at the disaggregated level of OC reveals that while all cultural archetypes endorse values conducive to DT and BDAC, the degree of impact varies. Values act as a compass guiding decisions and behaviors within organizations (Clouet et al., 2024), and it is the particular values intrinsic to certain cultural archetypes that propel the DT process and the enhancement of BDAC. It is the particular values intrinsic to certain cultural archetypes that propel the DT process and the enhancement of BDAC. Through an analysis of the direct and indirect relationships between cultural archetypes, DT, and BDAC, we conclude that adhocratic, hierarchical, and digital cultures significantly advance BDAC, contingent on the mediating role of DT. These findings diverge from those of Leal-Rodríguez et al. (2023) but are in line with different studies such as Ashrafi et al. (2019), Baiyere, Salmela and Tapanainen (2020) and Pradana et al. (2022).

Hierarchical culture leads, thanks to its intrinsic values, to a more agile and adaptable organization, especially in scenarios with high uncertainty or crisis (Felipe et al., 2020, 2017), such as the current situation after the COVID-19 crisis and the DT ecosystem. Adhocratic culture is undoubtedly synonymous with openness, dynamism, creativity, agility, and change. Leaders here tend to be visionary and innovative, and the people who form it have training adapted to the needs of the organization (Troisi, Grimaldi, & Loia, 2021; Xie et al., 2021; Leal-Rodríguez et al., 2023) that are continuously reviewed and contribute to an increase in organizational capabilities.

Moreover, in our analysis, digital culture emerges as the main driver in fostering BDAC via DT. This is attributed to its foundational values: an openness to change, a learning orientation, an acceptance of failure as a growth mechanism, a focus on analytics, and a strong customer-centric strategy (Leal-Rodriguez et al., 2023). Such values, hallmarks of digitally native companies, serve as a beacon for those embarking on DT – as in the case study of Steiber and Alvarez (2023) – and seeking to elevate their analytical capabilities. Yet, it is critical to underscore that the infusion of digital values into a company’s ethos contributes to BDAC generation only when predicated by established DT – thereby positioning DT as a mediating variable in this dynamic.

Innovative and digital cultures are characterized by their emphasis on creativity, flexibility, and a willingness to embrace change. This alignment fosters an environment where continuous improvement, customer feedback, and adaptive learning are integral to successful DT and BDAC (Ciacci et al., 2024).

In contrast, market and clan cultures exhibit no marked or significant correlation with BDAC when mediated by DT. Following the work of Akhtar et al. (2019), our results are in line with the results of coercive and manipulative powers who do not favor BDA to impact on increasing innovation. Despite this, the goal-oriented nature of market culture maintains a direct and significant correlation with BDAC. Organizations ingrained with market culture, endeavoring to embark on DT, must recognize the potential complexities of such a transformation. To mitigate these challenges, a concerted effort to foster a learning environment, team development, and, fundamentally, a culture that endorses such transformation is recommended (Leal-Rodríguez et al., 2023).

Conversely, clan culture is the one that exhibits no favorable association with DT, therefore rejecting hypotheses 1–3. According to Cameron and Quinn (1999), some of the values that characterize the clan cultural archetype are cohesion, organizational commitment, participation, integration, or teamwork. Although these values are typically conducive to HRM innovations that support DT (Bartsch et al. 2020), this premise is not always met. A people-centric archetype, commonly observed in family-run businesses, may be deeply entrenched in tradition, potentially obfuscating strategic foresight. This allegiance to the past can thwart the effective implementation of technological investments and impede the successful initiation of DT and subsequent BDAC creation.

Conclusions

Our study contributes to the academic literature by providing new insights into the relationship between OC and DT. By integrating the digital culture archetype into the CVF, we advance the understanding of how specific cultural traits influence DT and BDAC. Practically, this research highlights the importance of cultural assessment and strategic action planning to foster a conducive environment for DT. This significantly contributes to innovation management, addressing why innovation and digitalization processes often fall short of expectations, and demonstrating how culture can be a lever for change and a key to success if certain recommendations are followed.

This study elucidates several practical implications. First, it emphasizes the importance of diagnosing OC and values to align them with DT requirements. Recognizing the fluid and ongoing nature of corporate culture, conducting an initial cultural assessment and maintaining vigilance through ongoing evaluation are pivotal for digitalization success (Leal-Rodríguez et al., 2023). This method, based on the concept of competing values (Quinn and Rohrbaugh, 1983), allows professionals to assess their current culture and pinpoint areas that require cultural change as part of the DT process (Pedersen, 2022).

Once the OC has been diagnosed, the imperative shifts to action planning. This involves identifying and cultivating cultural elements within the organization that are conducive to DT and fostering BDAC. It is important to see whether there are values in the current culture that support digitalization and to establish an action plan. Managing the transition from traditional to innovative and digital cultures requires a strategic approach. According to Cameron and Quinn (2011) and Nanayakkara et al. (2021), recommendations for cultural change can be followed depending on the predominant cultural archetype. For instance, in organizations where clan culture prevails, fostering a reciprocal evaluation ecosystem between management and staff can propel innovation and adaptability. Encouraging intrapreneurship may lead to enhanced performance and spur organizational innovation.

Additionally, following the recommendations of Coco et al. (2024), practices associated with open innovation and design thinking (such as workshops and networking events for idea exchange) can be adopted to overcome resistance to DT and BDAC. Employees’ feedback and ideas should be incorporated into strategic decision-making, for example, by creating innovation committees or cross-functional data analytics programs. The creation of multidisciplinary teams and personal training programs is also encouraged for employees based on their aspirations, motivations, and market requirements. In organizations with high market or goal-oriented culture values, practices such as interviewing employees and customers to discover their aspirations and expectations for the company can be introduced. Encouraging openness to the market and implementing a total quality management system will help ease cultural change.

This study, while providing valuable insights, is not without limitations. The use of a non-probabilistic sample poses constraints on the generalizability of our findings, so they should be interpreted with caution. Furthermore, the geographical limitation confines our conclusions to Spanish organizations. Cultural, economic, and technological dynamics can vary significantly across different regions and countries. Therefore, the extent to which these results can be extrapolated to organizations outside of Spain is uncertain. Variations in digital maturity, OC, and the business environment in other regions may lead to different interactions between DT, BDAC, and OC.

To mitigate the issues associated with non-probabilistic sampling, future research could employ probabilistic sampling techniques, ensuring a more representative demographic spread and potentially more generalizable results. Comparative studies across different geographical areas could provide a more comprehensive understanding of the cultural dynamics at play in DT. This would allow exploration of how regional and national cultures impact the adoption and integration of digital technology in business practices.

Future research could focus on the examination of digital mindset as a moderating force in the relationship between employees’ technological skills and proficiency. This inquiry would probe the extent to which a digital mindset, with its intrinsic values of innovation and continuous learning, predicts and enhances the technological competencies of the workforce. By quantifying the influence of digital values on employees’ ability to navigate and master new technologies, scholars could elucidate the symbiotic relationship between cultural environment and technological acumen. Such an investigation might involve longitudinal studies to track the development of technical skills over time within varying digital cultures or cross-sectional analyses to compare proficiency levels across different OCs and contexts (Dąbrowska et al., 2022). Ultimately, this line of research promises to reveal how deeply ingrained digital values within an organization can equip its members to excel in a technology-driven business landscape, offering strategic insights into workforce development and DT policies.