Reframing the digital strategy–organisational culture relationship: a contingency-theoretic study of digital transformation in Polish energy SMEs

Digital transformation (DT) is a process that leads an organisation towards digital maturity (Weritz et al., 2020), which manifests itself not only in investing in digital initiatives but also in the leadership skills necessary to implement a digital transformation strategy (He et al., 2023). In an era where digital transformation (DT) is a key determinant of business success, companies increasingly recognise that the greatest challenges stem not from technology itself but from cultural factors (Dung, 2024; Jewapatarakul and Ueasangkomsate, 2024). Developing a supportive digital organisational culture (DOC) is therefore essential for the effective adoption of digital initiatives (Usai et al., 2021). However, the mechanisms shaping DOC remain underexplored (Martínez-Caro et al., 2020; Proksch et al., 2024), particularly in relation to digital strategy (DS), despite evidence suggesting that misalignment between strategy and culture can lead to strategic failure (Gong and Ribiere, 2021; Gupta, 2011). While some recent studies suggest that DS may influence DOC (e.g. Proksch et al., 2024; Sarfraz et al., 2025), these works focus predominantly on large (or unspecified size), digitally mature firms or technology-intensive industries, with DOC acting as a mediator. Empirical research that explicitly models DS as a driver of DOC in small and medium enterprises (SMEs), particularly within highly regulated and infrastructure-bound sectors such as energy, remains scarce. Our study addresses this underexplored intersection by focusing on SMEs in Poland’s energy sector, where regulatory pressure and strategic constraints shape digital transformation differently than in large corporations.

This environment creates a unique setting in which strategic intent is not only shaped by internal priorities but also externally imposed requirements, such as those associated with EU decarbonisation goals and digital reporting standards (Ecer and Güner, 2024; Jorge-Vazquez et al., 2024). These institutional demands place additional pressure on SMEs to align internal culture with digital imperatives.

The growing strategic relevance of DT arises from both environmental pressure and opportunity. Organisations must rapidly adapt to technological innovation, evolving customer expectations and increasingly complex regulatory environments. These conditions compel firms, especially SMEs in regulated sectors, to undergo deep organisational change. Yet, DT involves more than implementing technology; it requires cultural transformation, leadership realignment and development of new capabilities. As such, four interconnected domains, strategy, culture, leadership and capabilities, have emerged as critical levers of successful DT (Merten et al., 2022; Velyako and Musa, 2023). In this regard, DOC serves not only as a supportive environment but also as a reflection of an organisation’s ability to absorb and institutionalise strategic change (Chwiłkowska-Kubala et al., 2023; Malewska et al., 2024).

While prior research often assumes that DOC enables DS by facilitating strategy implementation (Bhatti et al., 2024; Ueasangkomsate, 2025), emerging studies suggest a reverse causal relationship, where DS actively shapes DOC (Proksch et al., 2024; Sarfraz et al., 2025). We adopt this latter perspective, arguing that strategic digital decisions drive cultural transformation by embedding digital mindsets, fostering openness to technological change, and ensuring alignment with digital initiatives. This aligns with contingency theory (Lawrence and Lorsch, 1967) and strategic choice theory (Child, 1972), which posit that strategic decisions shape organisational structures, capabilities and culture. These perspectives help explain how managers, through deliberate strategic action, can influence organisational culture to align with external demands and internal innovation objectives.

This is particularly relevant in the Polish energy sector, which remains digitally lagging compared to Western Europe, in part due to structural investment barriers (Rabiej-Sienicka et al., 2022). Here, DS becomes a compensatory mechanism for overcoming institutional inertia.

Furthermore, while numerous studies highlight the impact of digital transformational leadership (DTL) and digital capabilities (DCs) on DT (McCarthy et al., 2022), their mediating role between DS and DOC remains insufficiently examined. Given the growing importance of strategic alignment in DT (Jonathan and Kuika Watat, 2020), it is essential to understand how DS fosters DOC through DTL and DCs. DCs capture the technological readiness and absorptive capacity of the organisation, while DTL reflects the human element – how leaders shape, communicate and institutionalise strategic change. Together, these two constructs represent the operational pathways through which strategic intent becomes embedded in everyday cultural norms.

In this model, DCs translate technological vision into operational routines, while DTL reinforces behavioural and symbolic alignment with transformation objectives (Proksch et al., 2024). Yet their respective contributions to cultural adaptation remain empirically underexplored.

To address this research gap, the purpose of this study is to examine whether and through which mechanisms DS influences DOC in SMEs. Using survey data from 160 SMEs, we empirically test our research model in the Polish energy sector, which is undergoing rapid transitions due to regulatory and technological pressures (Jorge-Vazquez et al., 2024; Rabiej-Sienicka et al., 2022). SMEs, due to their agility and capacity for rapid adaptation (Zastempowski and Cyfert, 2023), provide an ideal setting to observe DS–DOC dynamics. For energy sector SMEs, digital transformation is not merely an option but a necessity, offering opportunities to innovate, adopt new business models, enhance productivity and support sustainable development (Singh et al., 2021). In this context, DS provides both the framework and strategic direction necessary for successful transformation, ensuring organisational readiness for change (Chwiłkowska-Kubala et al., 2023).

Our findings confirm that DS is the strongest predictor of DOC, with DCs playing a more significant mediating role than DTL. This suggests that while leadership facilitates digital readiness, an organisation’s technological capabilities are the primary mechanism for embedding DOC.

This study makes a threefold contribution to the existing literature. One major contribution lies in challenging the prevailing assumption, particularly common in earlier work, that DOC necessarily precedes or enables DS. Instead, our findings support the reverse relationship that DS acts as the initiating force that shapes DOC, especially in SMEs undergoing externally driven transformation. This repositions strategic alignment as a deliberate top-down lever for cultural change. The study also clarifies the distinct mediating roles of DTL and DCs in the DS–DOC relationship, reinforcing the importance of capability-building and leadership in digital transformation. Moreover, the results reveal that DC is a stronger mediator than DTL, though DS itself exerts the most significant direct influence. Thus, organisations should prioritise DS while strategically leveraging DCs and DTL to reinforce its impact.

Unlike prior studies that often neglect contextual factors such as firm size or industry characteristics, focusing primarily on unspecified size firms or technology-driven sectors (Özkan Alakaş, 2024; Proksch et al., 2024; Sarfraz et al., 2025), our study explores DS–DOC dynamics within SMEs in the highly regulated and rapidly evolving energy sector. This sector presents unique challenges and constraints, making it a critical yet underexplored setting for understanding how strategic digital initiatives translate into cultural transformation. Our research provides one of the first empirical tests of the mediating roles of DCs and DTL in this relationship, offering a novel perspective on how SMEs navigate digital transitions.

The remainder of this paper is structured as follows: Section 2 presents the theoretical framework and hypotheses; Section 3 outlines the methodology and results; Section 4 discusses the findings in detail; and Section 5 explores the implications and directions for future research.

In the literature, DT is defined as a complex, multidimensional construct, referring to fundamental changes in business models, organisational structures and modes of value creation that are driven by the integration and adaptation of digital technologies (Satı, 2024; Liu et al., 2022). The main objective of DT is to enhance the organisation’s adaptability and gain a sustainable competitive advantage in rapidly evolving market and technological environments (Xie and Wu, 2024).

However, DT is not limited to the deployment of modern technologies. A key dimension of this process is the profound reorganisation of mindsets, organisational culture and leadership models (Chang et al., 2024; Chwiłkowska-Kubala et al., 2023; Zhang et al., 2024). It is thus increasingly conceptualised as an internally driven process grounded in strategic, cultural and leadership-related competencies, rather than in purely technical advancement. In this integrated view, four interrelated domains emerge as essential for ensuring the effectiveness of DT: a clearly formulated DS (Zhang et al., 2024), a strong DOC (Malewska et al., 2024), effective DTL (Luu, 2023) and developed DCs (Bhatti et al., 2024). While each domain contributes in a distinct way, it is their mutual reinforcement that enables organisations to realise the full potential of digital transformation.

DS refers to the organisation’s long-term for integrating digital technologies within the organisation to support innovation and reconfigure business models (Lin and Kunnathur, 2019; Shirwa et al., 2025). When coherently developed, DS serves as the main framework for prioritising, coordinating and operationalising the DT process (Merten et al., 2022), thereby enabling systemic changes in business processes and organisational structures (Kane et al., 2016). DS also guides the formulation and execution of agile and adaptive strategies, crucial in volatile market conditions (Albannai et al., 2024a, b). Moreover, it enhances top-management decision-making (Luu, 2023), provides direction and sets measurable objectives that shape collective action during the transformation (Dióssy et al., 2024). Finally, DS helps to identify elements of the business model requiring modification in response to digital imperatives (AlNuaimi et al., 2022).

DOC represents the shared norms, values and beliefs that support digital initiatives, facilitate change adoption and serve as antecedents to employee readiness for transformation (Malewska et al., 2024; Martínez-Caro et al., 2020; Proksch et al., 2024). Whereas DS outlines the technological and strategic direction of change, DOC determines how that change is internalised and enacted by members of the organisation. It is shaped by structural factors supporting collaboration and knowledge sharing (Cubillas-Para et al., 2024), normative systems that promote innovation (Jewapatarakul and Ueasangkomsate, 2024) and shared practices that sustain adaptability in digital environments (Duerr et al., 2018). The development of DOC involves intentional reinforcement of digital behaviours and mindsets (An et al., 2024), along with broader changes in leadership style, communication patterns and organisational values (Malewska et al., 2024). As a core dimension of digital maturity, DOC reflects an organisation’s readiness for DT and requires strategic investment in capabilities and cultural openness (Chwiłkowska-Kubala et al., 2023; Li et al., 2025).

DTL is recognised as a dynamic and adaptive leadership approach that aligns technological innovation with cultural and organisational change capabilities (Gyamerah et al., 2025). Effective digital leaders communicate a compelling digital vision, foster innovation and promote employee engagement – creating a context conducive to ongoing change. Their role goes beyond direction-setting: they inspire employees to internalise digital values and participate actively in transformation (Ly, 2024). As a result, DTL significantly influences the pace and depth of DT (AlNuaimi et al., 2022; Khattak et al., 2025), while also supporting the integration of culture and leadership into daily management (Odai et al., 2025).

Finally, DCs, a subcategory of dynamic capabilities (Teece et al., 1997), reflect an organisation’s capacity to sense, seize and transform in response to digital opportunities (González-Varona et al., 2021; Saputra et al., 2021). They encompass the skills needed to acquire, assimilate and deploy digital technologies, directly supporting innovation and strategic agility (Marino-Romero et al., 2024; Zhou and Wu, 2010). DCs are critical enablers of DT, with direct links to technology integration, organisational resilience and value creation (Elia et al., 2021; Xie et al., 2022; Yang et al., 2024; Gyamerah et al., 2025; Ly, 2024). DCs focus on organisational resources and competencies to adapt to technological shifts (Teece et al., 1997), whereas DTL emphasises the human and symbolic dimensions of motivating, communicating and institutionalising digital vision (Proksch et al., 2024).

While DS articulates the overarching direction of change, DCs operationalise this intent through concrete routines and resources, and DTL activates the human and symbolic levers of engagement. Ultimately, it is DOC that determines the extent to which transformation becomes embedded in everyday practices. These domains, while analytically distinct, function as an interdependent system whose dynamic interplay underpins the success of DT.

Previous studies have largely conceptualised a unidirectional path from DS to DOC, viewing strategy as the initiating driver. For example, Proksch et al. (2024) demonstrate that DS significantly influences the development of DOC and DCs, serving as a foundation for digitalisation. Similarly, Sarfraz et al. (2025) highlight that DS, when combined with big data analytics and artificial intelligence, can stimulate business process innovation, with DOC acting as a moderator that reinforces the strategic impact. Research by Pradana et al. (2022) also suggests that organisational culture is an essential factor in improving DS and performance. According to strategic choice theory (Child, 1972), organisations can purposefully reshape culture to support strategic goals. In line with this, DS plays a central role in shaping DOC, by defining a digital vision, setting behavioural expectations and fostering values conducive to digital transformation. DS can influence cultural readiness, encourage experimentation and reduce the cost of technology implementation (Moshood et al., 2024). An effective DS initiates the transformation of both technological and cultural elements in an organisation.

However, this perspective may oversimplify the dynamic and iterative nature of digital transformation. Martínez-Caro et al. (2020) provide a more nuanced view, suggesting that DOC may also function as an antecedent to strategy formation, especially in mature digital contexts where bottom-up digital maturity pressures strategic repositioning. Some studies support this bidirectional view by emphasising the role of DOC in facilitating DS implementation (Ueasangkomsate, 2025). Internal cultural alignment is believed to support the acceptance and embedding of strategic digital initiatives. Conversely, misalignment between digital tools and organisational values may lead to rejection or superficial adaptation (Cooper, 1994; Harper and Utley, 2001).

With regard to this evolving discussion, and drawing on strategic choice theory (Child, 1972), we argue that DS, by defining a digital vision, setting expectations for behaviour and promoting values conducive to digital transformation, exerts a formative influence on DOC. In doing so, we extend the work of Proksch et al. (2024) and Sarfraz et al. (2025), who conceptualise DOC primarily as a contextual condition in which DS operates, rather than as a direct organisational outcome of strategic intent. By contrast, our approach positions DS as a key driver of cultural transformation, particularly in regulated SME environments where deliberate strategy may be the most effective lever for enabling digital cultural alignment. While this relationship has been explored in large enterprises (Canhoto et al., 2021; Ferrigno et al., 2023), research on SMEs, especially in the energy sector, remains limited (Broccardo et al., 2023; Giotopoulos et al., 2017). SMEs often face constraints in digital tool access, information and communication technologies capabilities, and strategic know-how, which heightens the importance of cultural support in strategy implementation (Peter et al., 2020).

In the energy sector, DS is particularly critical due to regulatory complexity and the sector’s dependence on digital technologies for real-time energy management and supply-demand balancing (Kivimaa and Sivonen, 2021). The integration of DS and DOC not only improves operational efficiency but also supports broader sustainability and innovation goals (Yi et al., 2022). While prior studies have examined the influence of DS on DOC (e.g. in large enterprises), empirical research specifically focused on SMEs, particularly in highly regulated industries such as the energy sector, remains scarce or entirely absent. Our study addresses this research gap by investigating how DS influences DOC in energy-sector SMEs, where cultural alignment is crucial to enabling digital transformation. Based on the above considerations, we propose the following research hypothesis:

Today's organisations are increasingly implementing DS aimed at adapting to dynamic technological and market changes (Nadkarni and Prügl, 2021). However, the mere presence of a DS does not yet guarantee the success of an organisational transformation (Carroll et al., 2023).

The DS is the starting point of the transformation process – it defines goals, courses of action and priorities for the use of digital technologies (Bharadwaj et al., 2013). However, its implementation requires not only management decisions but also adequate resources, competencies and organisational structures. In this context, DCs, understood as an organisation's ability to effectively use digital technologies to achieve business goals, turn out to be important (Chae et al., 2014). These include technological infrastructure, as well as employee competencies, process flexibility or the ability to manage data and innovation (Kane et al., 2016).

DCs mediate the impact of DS on DOC, as they enable the implementation of new practices, tools and work models, which in turn lead to changes in employees' values, norms and attitudes. As Vial (2019) points out, DCs are the foundation of an organisation's adaptability and influence the internal consistency between strategy and employee behaviour.

Lack of developed DCs can result in a situation where DS remains at the declarative level (Weritz et al., 2025), and culture change does not occur. Employees reluctant to embrace technology, unprepared to work in a digital environment or lacking technological support, may perpetuate traditional behaviour patterns (Cieslak and Valor, 2025; op ´t Roodt et al., 2025). Thus, digital transformation is blocked at the cultural level. Therefore, according to the DCs view (Teece et al., 1997), it is the organisation's ability to learn, integrate and reconfigure resources that determines its success in transforming organisational culture in line with strategy (Al-Moaid and Almarhdi, 2024; Ghosh and Srivastava, 2022).

DCs are not only an element supporting the implementation of the DS (Konopik et al., 2022) but also perform a key mediating function, enabling the translation of strategic intentions into real changes in organisational culture (Ghafoori et al., 2024). Their development is a prerequisite for achieving coherence between DS and a culture open to technology, innovation and agile operations. On this basis, we formulate a hypothesis according to which:

Within the context of DT, leadership assumes a distinctly transformative role, extending beyond coordination and supervision to the active shaping of cultural and structural dimensions of the organisation. Leaders operating under a digital paradigm are expected to direct the reconfiguration of organisational systems and infrastructures to align with the demands of digitalisation, while simultaneously guiding the cultural realignment necessary for sustained innovation and adaptability (Albannai et al., 2024a).

Prior research has underscored that effective DTL fosters a climate of openness and innovation, essential for the successful assimilation of digital technologies and practices (Odai et al., 2025; Özkan Alakaş, 2024). In this capacity, digital leaders serve as agents of normative change, capable of influencing employees' cognitive and affective orientations towards digital initiatives (Kludacz-Alessandri et al., 2025; Luu, 2023). By articulating a compelling digital vision and modelling adaptive behaviour, transformational leaders inspire members of the organisation to internalise digital values and modify underlying assumptions in support of DT (Luu, 2023; Ly, 2024). This capacity to influence shared meaning systems and behavioural expectations situates DTL as a key antecedent to the emergence and consolidation of DOC.

Simultaneously, DTL has been conceptually linked to the formulation and operationalisation of DS. Leaders are responsible for defining the scope and trajectory of DT initiatives and for determining associated investment priorities (AlNuaimi et al., 2022; Ly, 2024). They engage in strategic reflection concerning enterprise architectures, business models and platforms (Albannai et al., 2024b) and ensure that digital strategies are coherently embedded across organisational levels and functions (Albannai et al., 2024a). In this regard, DTL plays a role in reinforcing strategic alignment and enhancing decision-making efficiency (Luu, 2023).

This dual orientation of DTL – towards both cultural and strategic dimensions – positions it as a central mediating construct. On one hand, DTL enables the translation of abstract strategic intent into situated cultural practices; on the other, it fosters cultural receptivity to transformation by aligning individual and collective values with the digital vision. Previous studies support this integrative view: Schiuma et al. (2022) demonstrate that DTL shapes DOC by cultivating shared meaning, supporting learning and promoting cross-functional collaboration. Similarly, Schwarzmüller et al. (2018) highlight how inclusive and participatory leadership styles enhance the coherence of digital values across organisational strata.

Further, DTL facilitates the institutionalisation of DS by embedding digital priorities into day-to-day organisational practices and symbolic frameworks (El Sawy, Kræmmergaard, Amsinck and Lerbech Vinther, 2016; Kane et al., 2016). It promotes learning, agility and resilience by serving as a behavioural conduit through which strategy is enacted (Correani et al., 2020). In this role, DTL effectively links high-level strategic direction to emergent cultural configurations, enabling a synchronised transformation process (Özkan Alakaş, 2024). Accordingly, we hypothesise:

A conceptual model with the formulated hypotheses is presented in Figure 1.

To test our model, we collected data from 160 SMEs in the energy sector in Poland. The selection of this context is grounded in its distinctive structural and institutional characteristics, which make it particularly suitable for analysing the dynamics of DT and its strategic antecedents.

The Polish energy sector faces intense pressure to modernise in response to systemic delays, including decarbonisation imperatives and the integration of renewable energy sources (Jorge-Vazquez et al., 2024; Sokołowski and Bouzarovski, 2022). In this setting, DT, when guided by DS and enabled by a strong DOC, offers a viable path towards greater efficiency, innovation and energy security (Kwiotkowska et al., 2021).

The sector’s rigid regulatory environment exerts a dual influence on DT: while compliance obligations limit flexibility and increase administrative burden, the same legal framework also catalyses digital adoption by mandating alignment with evolving EU standards in sustainability, transparency and reporting (Ecer and Güner, 2024). This paradox, where regulation simultaneously impedes and accelerates transformation, makes the Polish energy sector a uniquely revealing context for studying how DS, mediated by DCs and DTL, drives cultural adaptation in response to institutional pressure.

In comparison to Western European counterparts, Poland’s energy sector demonstrates relatively lower levels of digital maturity, attributable in part to long-standing investment barriers rooted in policy and governance regimes (Rabiej-Sienicka et al., 2022). This relative lag in DT reinforces the strategic importance of DS as a deliberate mechanism for overcoming structural limitations and accelerating convergence with EU digital and environmental benchmarks.

SMEs were selected due to their agility, limited resources and organisational structure make them an ideal context for studying DTL, DOC and DS. SMEs can adopt digital technologies faster than large corporations (Chan et al., 2019), offering a “laboratory” for understanding DT enablers and barriers. Their resource constraints demand strategic prioritisation of digital investments (Canhoto et al., 2021), leading to more adaptive decision-making. Additionally, SMEs’ flat hierarchies allow leaders greater influence over culture and change processes (Arbussa et al., 2017), further shaping DOC.

The research was conducted in four phases. First, a literature review identified research gaps and appropriate measurement scales. Second, scales were translated into Polish using back-translation, and a pilot study ensured clarity with input from SME experts in the energy sector. Third, data were collected by a research agency from 160 SMEs using a single-respondent-per-firm approach. The final phase of the study involved the analysis of the collected data to derive key findings.

The inclusion criteria required that the participating firm: (1) was officially classified as an SME under EU regulations (i.e. fewer than 250 employees), (2) operated within the energy domain (NACE Section D) and (3) had initiated at least one digital transformation project in the previous three years. Firms were selected using stratified purposive sampling to ensure diversity in size (small vs medium), geographical location and digital maturity level.

To mitigate common method bias, several procedural remedies were applied. First, data were gathered exclusively from senior managers, defined as individuals occupying top- or mid-level executive positions (e.g. Chief Executive Officer, Chief Technology Officer, Chief Information Officer, Head of Department or Senior Project Manager) with direct responsibility for strategic planning and digital initiatives. All respondents had at least five years of managerial experience (not necessarily in the surveyed company) and were actively involved in shaping or supervising digital transformation efforts within their firms. This ensured that participants possessed relevant expertise and a thorough understanding of the phenomena under study, thereby reducing ambiguity and enhancing response accuracy.

Second, the questionnaire incorporated two reverse-scored items, strategically placed within the survey. These reverse-scored items required respondents to cognitively switch perspectives, thereby minimising potential biases related to acquiescence or careless responding. The final sample included 59 small and 101 medium firms, with 66.9% operating for over 20 years (Table 1).

A G*Power analysis confirmed that the sample size was statistically sufficient for testing the hypothesised parallel mediation model using Hayes’ PROCESS Model 4. The analysis assumed a medium effect size (f² = 0.15), significance level α = 0.05 and power = 0.95, indicating that a minimum of 119 observations would be required. With 160 valid responses, the study exceeded this threshold, providing robust power for mediation testing via ordinary least squares (OLS) estimation.

Our study builds on established multi-item scales validated in the extant literature (see Table 2). Items for DS and DTL were adopted directly from AlNuaimi et al. (2022), which provide a theoretically grounded and empirically validated instrument in the digital transformation domain. DOC was measured using the scale developed by Martínez-Caro et al. (2020), reflecting organisational openness to digital initiatives and innovation culture.

For DCs, we adapted the capability assessment scale originally proposed by Zhou and Wu (2010), which evaluates a firm’s comparative technological strength in areas such as acquisition, deployment and exploitation of advanced technologies. While the original instrument was developed in a broader innovation context, we reworded and refocused each item to specifically capture DCs relevant to contemporary transformation efforts. This adaptation approach has also been used in recent research on digital transformation and SME innovation (Khin and Ho, 2018; Matalamäki and Joensuu-Salo, 2022; Turkcan et al., 2025; Velyako and Musa, 2023; Wang et al., 2024), which confirms its continued relevance and applicability in digital contexts.

All items were evaluated through CFA (see Table 3) to confirm their dimensionality and construct validity. Respondents indicated their agreement using a five-point Likert-type scale (1 = strongly disagree (DS, DTL, DOC)/much worse (DCs); 5 = strongly agree (DS, DTL, DOC)/much better (DCs)).

We conducted mediation analysis using Hayes’ (Hayes et al., 2017) Model 4 for parallel multiple mediation. Reliability and validity were assessed with Cronbach’s α and confirmatory factor analysis (CFA). Pearson correlations examined construct relationships, while ordinary least squares (OLS) estimation supported model development. Bootstrap resampling validated model estimation and effect sizes, with a 0.05 significance level applied.

The analysis was performed in Jupyter Notebook (6.4.5) using Python (3.9.7) with NumPy (1.22.4), pandas (2.1.4), SciPy (1.13.1), statsmodels (0.14.1) and semopy (2.3.9).

CFA was conducted to evaluate the reliability and validity of the measurement model, which included four key constructs. The constructs were assessed from different perspectives, including factor loadings (FL > 0.6) (Awang, 2012), Cronbach’s alpha, composite reliability (Cα and CR > 0.70) (Flynn et al., 2010) and average variance extracted (AVE>0.50) (Chau, 1997). The summary of the relevant estimates is presented in Table 3.

All constructs exhibit strong internal consistency, with Cronbach’s alpha and composite reliability exceeding 0.7. Convergent validity is adequate, as AVE values surpass 0.5, though DTL’s AVE is the lowest. However, since all factor loadings exceed 0.7, this is acceptable. The lowest factor loading (DTL:0.702) remains above 0.6, confirming construct validity. As no critical reliability or validity issues were found, no scale refinements were necessary, and the existing constructs will be used.

Table 4 presents the descriptive statistics for the variables, including the mean, standard deviation (SD) and median, along with the Jarque–Bera (JB) normality test statistics, skewness and kurtosis.

The mean and median values are closely aligned, indicating roughly symmetric distributions (Table 5). All constructs show slight left-skewness and platykurtic distributions, with DOC having the lowest kurtosis. The JB test confirms no significant deviations from normality (p > 0.05), though DTL exhibits the most pronounced left-skew.

All constructs exhibit moderate to strong positive correlations, indicating interdependence (Table 6). The strongest relationships are between DOC and DS (0.88), DCs and DS (0.84) and DOC and DCs (0.82). The weakest, between DTL and DCs (0.59), remains moderate. While correlations are high, no multicollinearity concerns arise, with DOC and DS showing particularly strong interconnectedness.

The DOC model includes three antecedent variables: DS, DCs and DTL (Table 7). The estimate for DS is 0.5357, with a significance level of p < 0.001, indicating a strong and statistically significant relationship. The effect of DCs on DOC is also positive and significant (estimate = 0.3138, p < 0.001), suggesting that it plays a meaningful role in explaining variations in DOC. Similarly, DTL has a statistically significant effect (estimate = 0.2130, p < 0.001), though its influence is weaker compared to DS and DCs. The model fit (R2 = 0.81) suggests that these predictors explain a substantial portion of the variance in DOC.

The DCs model includes DS as a sole predictor. The coefficient for DS was estimated at 0.8159, with a p-value<0.001, indicating that DS is a dominant factor influencing DCs. This strong relationship underscores the interconnected nature of the constructs.

The DTL model consists of a single predictor, DS, with a coefficient of 0.6285 and a highly significant p-value (<0.001). This confirms that DS plays a crucial role in shaping DTL.

The Breusch–Pagan test results indicated the presence of heteroskedasticity in the DTL model (BP = 13.52, p < 0.001). Additionally, two instances of non-normality were observed in the residuals of the DOC and DCs models. The JB test results (JB = 7.11, p = 0.03 for DOC; JB = 20.05, p < 0.001 for DCs) confirmed significant deviations from normality in these cases.

Despite these findings, visual inspection of residual plots did not reveal any strong patterns, and no evidence of conditional heteroskedasticity was observed. Therefore, while deviations from normality should be acknowledged, they are unlikely to materially impact the inference process.

1. Indirect Effect 1 (IE1): DS→DCs→DOC,

2. Indirect Effect 2 (IE2): DS→DTL→DOC.

Both indirect pathways (DS→DCs→DOC and DS→DTL→DOC) are statistically significant, jointly accounting for 42% of the total effect (Table 8). The first indirect effect (IE1) is 0.256 (SE = 0.059, z = 4.31, p < 0.001), and the second (IE2) is 0.134 (SE = 0.036, z = 3.74, p < 0.001), confirming the relevance of both DCs and DTL as mediating mechanisms. The total indirect effect (TIE) amounts to 0.390 (SE = 0.069, z = 5.62, p < 0.001), indicating a strong overall mediating role. However, the direct effect of DS on DOC (DE = 0.536, SE = 0.075, z = 7.10, p < 0.001) remains statistically significant and dominant, suggesting that the mediation is partial. The total effect (TE) is 0.926 (SE = 0.103, z = 9.03, p < 0.001), confirming that both direct and indirect paths substantially contribute to shaping DOC in energy-sector SMEs.

The Sobel, Aroian and Goodman tests for both indirect effects (IE1 and IE2) yield consistent, significant results, confirming strong mediation for IE1 (Sobel = 4.31, p < 0.001) and IE2 (Sobel = 3.74, p < 0.001). The Aroian and Goodman tests align with Sobel, reinforcing the robustness of these effects and confirming the substantial role of both indirect paths in mediation process.

To ensure the robustness of the hypothesised parallel mediation model and to account for potential confounding influences, two control variables were included in extended analyses: company age and company size.

Company age, defined as the number of years since the firm’s establishment, was included because organisational maturity may significantly influence the development and institutionalisation of DCS. Older firms often possess more established processes, deeper reservoirs of tacit knowledge and greater experience with strategic transformation – factors that can enhance or inhibit both capability development and leadership effectiveness. These characteristics may shape how DS is translated into DTL and, ultimately, a DOC. Controlling for age allows us to account for lifecycle-related variance and isolate the theorised indirect pathways driven by strategic intent rather than organisational inertia or legacy systems.

Company size was operationalised as a binary variable distinguishing between small enterprises (coded as 1) and medium-sized ones (coded as 0). Organisational size is known to influence digital transformation outcomes via its effects on structural complexity, innovation agility and access to strategic resources. Smaller firms may demonstrate faster adaptation but face constraints in scaling DCs or institutionalising cultural change. These asymmetries can influence the strength and stability of the mediating mechanisms linking DS to DOC through DCS and DTL. Including firm size as a control variable helps disentangle theoretically motivated relationships from variance attributable to differences in organisational scale. These controls were selected based on both theoretical relevance and consistent findings in the strategic and sustainability management literature, where firm age and size have been show to systematically influence organisational behaviour, resource deployment and environmental performance outcomes. Their inclusion allows for a more rigorous assessment of the proposed mediation model.

A point-biserial correlation was conducted to assess the relationship between company size (medium = 0, small = 1) and company age. The analysis revealed a moderate, negative and statistically significant association, rpb = −0.27, p < 0.001. This indicates that, on average, smaller companies in the sample tend to be younger than medium-sized firms. This relationship supports the inclusion of both age and size as control variables in the mediation model, as they are not independent and may jointly account for variance in the mediating or outcome variables.

To assess the robustness of the hypothesised serial mediation model, three indirect effects were examined under four control conditions: (1) no control variables, (2) controlling for company age, (3) controlling for company size and (4) controlling for both (Table 9).

Across all four models, the two indirect effects remained statistically significant, with confidence intervals that excluded zero, indicating robust mediation relationships. Specifically, IE1 ranged from 0.25 to 0.26 (p < 0.001 across models) and IE2 ranged from 0.13 to 0.14 (p < 0.001). These findings suggest that the proposed pathways from DS to digital organisational culture through DCs and DTL are stable regardless of whether company age or size is accounted for.

Notably, neither company age nor company size emerged as significant predictors in the underlying models. This suggests that these structural characteristics do not substantially influence the mechanisms captured by the mediators or the outcome variable in the context of the study. While their inclusion served to rule out potential confounding effects, their statistical insignificance reinforces the theoretical primacy of the proposed mediators.

In conclusion, the consistency of indirect effects across models with and without control variables strengthens the credibility of the hypothesised parallel mediation model. The findings highlight the central role of DCs and DTL in translating DS into digital organisational culture, independently of firm age or size.

The empirical results confirm our conceptual model (see Figure 1), particularly supporting H1 by showing that DS significantly and positively influences DOC in energy-sector SMEs. These findings reinforce the dominant view in prior studies that DS acts as a driver of cultural change (Proksch et al., 2024; Sarfraz et al., 2025), especially when supported by enabling mechanisms such as DTL and DCs. In our SME-based sample, the path from DS to DOC remains stronger and more consistent than any reciprocal relationship, suggesting the primacy of strategic framing during early-stage digital transformation.

Our study offers new empirical insight into the role of DS as a primary driver of DOC, particularly within SMEs operating in the highly regulated energy sector. The robust direct effect confirms that integrating digital initiatives into corporate strategy is essential for embedding digital values, cultivating behavioural alignment and enabling transformation. This challenges prior assumptions that DS in SMEs tends to be reactive (Sagala and Őri, 2024), supporting instead the view that DS functions as a proactive cultural mechanism (Proksch et al., 2024; Shirwa et al., 2025). By confirming the role of DS as a driver of DOC, our study highlights the importance of strategic clarity and cultural alignment in digital transformation, particularly in regulated sectors such as energy, where compliance and innovation must coexist.

Our findings also highlight the mediating roles of DCs and DTL in the DS–DOC relationship. While both mechanisms contribute to cultural embedding, DCs exhibit a more substantial influence (see Table 7), suggesting that, at least in regulated SME environments, capability development may offer a more direct pathway for translating strategic intent into cultural alignment than leadership alone. This interpretation refines prevailing assumptions in the literature, which often frame DTL as the primary enabler of DT and organisational readiness (Albannai et al., 2024b; Kusuma et al., 2024; Luu, 2023; Özkan Alakaş, 2024).

Contrary to studies suggesting that a pre-existing DOC enables DS execution (Martínez-Caro et al., 2020; Özkan Alakaş, 2024; Ueasangkomsate, 2025), our results imply reverse causality: DS shapes DOC. This challenges many SME transformation models that frame culture as antecedent, aligning instead with strategic choice theory (Child, 1972), where managerial intent is a catalyst for structural and behavioural shifts.

Compared to earlier research, our study clarifies the role of DS in shaping DOC more explicitly. For instance, while Proksch et al. (2024) and Sarfraz et al. (2025) acknowledge the importance of DS, they treat it primarily as a contextual enabler of product and process digitalisation. In their models, DOC is conceptualised as a mediator (Proksch et al., 2024) or moderator (Sarfraz et al., 2025) rather than a dependent outcome. These studies do not isolate DOC as a distinct construct nor examine its relative weight. Notably, Proksch et al. (2024) report limited explanatory power of DS over DOC, and Sarfraz et al. (2025) treat DOC as influencing the strength of DS’s impact, not being shaped by it.

By contrast, our study explicitly models DOC as a strategic outcome and empirically validates this directional pathway using a dual-mediator structure. This approach offers greater explanatory clarity and conceptual coherence, particularly within SME settings that are resource-constrained and face regulatory pressures. Our findings also suggest that DOC should not be conflated with DCs or treated as a passive element. While previous work has often blurred these distinctions, we operationalise DOC as a standalone construct, empirically validated and strategically relevant. This delineation enables a more precise understanding of how culture functions both as a dependent variable and a transformation enabler within DS implementation. Additionally, we contribute to literature by assessing the relative explanatory power of DTL and DCs, an aspect largely absent from prior work. Our findings suggest that when resources are limited, SMEs may be better served by prioritising competence development over leadership interventions. This has tangible implications for resource allocation in transformation programmes.

Finally, our study addresses theoretical fragmentation in digital transformation research by integrating strategic choice theory and contingency theory. While some models adopt a resource-based view (RBV), prioritising existing capabilities, we argue that intentional strategy plays a transformative role, shaping both organisational culture and capability trajectories. In this framing, DS becomes not only a roadmap but also a factor that actively shapes DOC, enabling alignment, readiness and ultimately success of DT.

Our study provides new insight into how DS shapes DOC, particularly in SMEs operating in a highly regulated environment. We demonstrate that DS not only supports digital transformation at a structural level but also acts as a cultural driver by embedding digital values and behaviours. Importantly, we identify two key mediators in relationship between DS and DOC - DCs and DTL and show that DCs play a more substantial role in translating strategic intent into cultural alignment. Our findings position DS as the central enabler of cultural transformation and highlight the dual role of strategy in shaping both technological infrastructure and cultural orientation.

Our study offers several contributions to the existing literature on DT, DS and DOC.

One major contribution lies in reconceptualising the relationship between DS and DOC. While previous studies have suggested that DOC may serve as a mechanism through which organisations initiate a DS in rapidly changing environments (Martínez-Caro et al., 2020), or treated DOC as a contextual condition in which DS operates rather than as its direct outcome (Proksch et al., 2024; Sarfraz et al., 2025), our results show that DS can actively shape and embed DOC. This supports strategic choice theory (Child, 1972) and highlights the proactive role of strategic intent in driving cultural change (Proksch et al., 2024).

Another insight clarifies how DS influences DOC by confirming a dual mediation mechanism through DCs and DTL. While both mediators are significant, DCs have a stronger effect, reinforcing insights from dynamic capabilities theory (Augier and Teece, 2009) and extending earlier research on organisational enablers of DT (Proksch et al., 2024). Additionally, our results reinforce prior research showing that DOC enhances DCs, indicating a dynamic interplay between these factors (Velyako and Musa, 2023).

We also find that DS not only influences DOC directly but also stabilises SMEs, helping them navigate strategic drift (Street et al., 2017). SMEs often lack formal strategic planning, but DS provides a guiding framework that reduces uncertainty and fosters DOC, ensuring cultural transformation is strategically directed.

In terms of leadership theory, our results show that although DTL supports cultural alignment (Schiuma et al., 2022), its effect is partial and weaker than that of DCs. This finding suggests that leadership must be supported by robust organisational capabilities to generate sustained cultural impact (Wahyu Wasono Mihardjo and Sasmoko, 2020).

Finally, we refine the debate on DS as a contextual factor in DT. While DS has been studied as a moderator in leadership-driven digital change (AlNuaimi et al., 2022), we confirm that DS itself is the primary enabler of cultural transformation, rather than a secondary element supporting leadership effectiveness. This distinction strengthens conceptual models by positioning DS as an independent force in shaping DOC.

Our study provides several practical implications for SMEs in the Polish energy sector, supporting their DT efforts in a highly regulated national context. The findings demonstrate a significant relationship between DS and DOC, suggesting that SMEs should adopt a structured approach to formulating DS that explicitly integrates cultural transformation. Although building a DS can be challenging for SMEs due to competency limitations (Li and Qian, 2007), it offers tangible benefits. Effective structuring of digital initiatives can reduce costs, increase productivity and accelerate business scalability (Proksch et al., 2024). In developing a strategy, SME owners and managers should integrate a clear vision of organisational development aligned with cultural values, fostering innovation, openness and collaboration in a digital environment. DCs are not a by-product of tech adoption but result from long-term process requiring structured leadership and strategic alignment to ensure a sustainable DT. While enhancing DCs should be prioritised, DTL remains essential, as leadership facilitates cultural alignment and employee adaptation to change. SMEs should implement targeted upskilling programs to enhance DCs and initiate leadership development to build managerial competencies for DT.

Our results confirm that both DCs and DTL significantly and positively influence DOC, acting as mediators in the DS–DOC relationship (see Table 7). While both effects are statistically significant (p < 0.001), DCs demonstrate a stronger effect size, underscoring their greater contribution to strategic-cultural alignment in SMEs. Building on these findings, SMEs should embed these enablers into their digital strategies through structured training, targeted recruitment and leadership development. Managers are encouraged to establish digital champions and cross-functional teams to actively promote DOC. Since digital leaders shape culture by setting strategic priorities (Proksch et al., 2024), SMEs should invest in leadership training, mentoring and partnerships with academic institutions. Recruitment strategies should prioritise candidates with adaptability, innovation and digital thinking (Müller et al., 2024). As leaders who embrace DT tend to focus on building DCs (Özkan Alakaş, 2024), selective investments in employee development can help integrate technology and strengthen DOC (Sagala and Őri, 2024).

Our findings also demonstrate that DCs exert a stronger influence on DOC than DTL. While DTL remains an important factor, DCs serves as the foundation for cultural transformation and should therefore be prioritised by SME owners and managers with limited resources. Specifically, greater emphasis should be placed on targeted training programmes and digital upskilling initiatives. Promoting a culture of continuous learning and knowledge sharing across the organisation is recommended as a cost-effective, long-term strategy.

Our findings have particular implications for SMEs in the Polish energy sector. The need to adapt quickly to technological and legal changes reinforces the importance of DOC as a critical success factor in the transformation process. To remain competitive, SMEs should focus on integrated culture-building, capability development and leadership reinforcement. Investment in AI-based energy management and digital security systems is crucial to ensuring compliance and long-term viability. Finally, the study has policy implications. Given the structural and resource constraints SMEs faced by SMEs, especially in regulated sectors like the Polish energy industry, there is a need for targeted public support. Policymakers could facilitate digital transformation by providing funding for capability development, upskilling programs and strategy formulation support. These actions would help SMEs align with regulatory expectations and strengthen their long-term competitiveness.

This study has some limitations, which indicate possible directions for further research.

Firstly, we used a single-respondent design, which, despite targeting knowledgeable managers and explaining the constructs, may have led to common method bias. Future research could address this by conducting case studies within a single organisation or collecting data from multiple organisational levels to gain a more comprehensive understanding of the studied mechanisms.

Secondly, our research focused on SMEs in the Polish energy sector, ensuring data comparability and minimising external variability. However, this sector-specific and country-specific scope limits the generalisability of our findings. Future studies should examine other industries or countries to determine whether the results hold across different contexts. Additionally, the energy sector is highly regulated, which may shape the role of DS in ways that differ from less-regulated industries. Examining larger firms or sectors with different regulatory environments could provide deeper insights into how DS fosters DOC.

Thirdly, our model simplifies the mediating mechanisms by focusing on DTL and DCs. While these factors significantly mediate the DS–DOC relationship, other organisational variables, such as managerial commitment, internal collaboration and agility, could also play a role. Future research should explore additional mediators to extend our findings, including organisational agility, internal communication quality or innovation climate, which may further illuminate how DS translates into cultural change. In future research, it would also be worthwhile to consider expanding the model with a separate construct of digital maturity.

Moreover, this study relies on cross-sectional data, capturing relationships at a single point in time. Given the evolving nature of digital transformation, future research could adopt a longitudinal approach to examine how DS influences DOC over time and how organisations dynamically adapt to digital changes. Such studies would offer valuable insights into the temporal dynamics of strategic-cultural alignment and reveal whether the DS–DOC relationship strengthens, weakens or transforms under varying environmental conditions.

Finally, we employed a quantitative approach, which allows for robust statistical testing but may not fully capture the nuances of organisational decision-making processes. Future studies could complement these findings with qualitative methods, such as in-depth interviews or case studies, to explore how DS, DCs, and DTL interact in shaping DOC.