The relationship between ordinary and dynamic capability is reciprocal, with evidence supporting both enabling and reconfiguration dynamics. According to Morgan (2012), capabilities develop when individuals and groups combine and transform resources in ways that contribute to the firm’s strategic goals. These lower-level operational routines, such as product management, pricing, CRM, or marketing communications, form the foundational basis from which more advanced dynamic capabilities emerge. Similarly, Winter (2003) distinguishes between zero-order capabilities (operational) and higher-order (dynamic) capabilities, but acknowledges that first-order dynamic capabilities (like new product development or market sensing) build upon and refine these lower-order routines. This implies a bottom-up pathway, where operational routines enable and support the development of dynamic capabilities. Conversely, Teece (2007) and Helfat and Peteraf (2015) point out that dynamic capabilities such as "transforming" are necessary to reconfigure, adapt, or enhance operational capabilities. This shows a top-down influence, where dynamic capabilities shape and renew lower-order routines in response to environmental change.

At the core of dynamic capability are three interdependent processes: (a) sensing opportunities and threats; (b) seizing those opportunities through strategic action; and (c) transforming organisational assets and routines to remain aligned with changing market conditions (Teece, 2007; Helfat & Peteraf, 2015). These processes are underpinned by micro-foundations such as managerial cognition, learning routines, and coordination mechanisms, which together enable firms to navigate complexity and respond proactively to change. Sensing refers to a firm's ability to perceive and interpret opportunities and threats within its external environment (Teece, Pisano & Shuen, 1997). This goes beyond mere information gathering to encompass the insightful interpretation of market signals, technological shifts, and customer needs (Helfat & Peteraf, 2003). Effective sensing allows an organisation to identify potential areas for innovation and adaptation, even in highly uncertain conditions (Eisenhardt & Martin, 2000). Seizing capabilities involves the mobilisation of resources and the making of strategic decisions to address the opportunities identified during the sensing phase (Teece, Pisano & Shuen, 1997). This stage focuses on acting upon the perceived opportunities, which could involve designing new business models, developing new products or services, or implementing new processes. It requires effective decision-making, resource allocation, and a willingness to commit to new ventures or strategic shifts (Danneels, 2008).

Transforming, also referred to as reconfiguring or continual renewal, relates to a firm's ability to continually renew and reconfigure its organisational structure, assets, and operational processes to maintain competitive fitness in the face of dynamic environments (Teece, Pisano & Shuen, 1997). This involves the capacity for continuous learning, innovation, and strategic change, ensuring that the firm's capabilities remain aligned with evolving market demands and technological advancements (Helfat & Peteraf, 2003). It is a fundamental aspect of sustaining competitive advantage over the long term, adapting to both expected and unexpected shifts in the business landscape (Schilke, 2014). Sustained competitive advantage, in this context, implies an organisation’s ability to generate sustained abnormal (positive) returns over time, outperforming rivals consistently. This is achieved not merely by possessing valuable resources at a given point, but by the continuous capacity to adapt, innovate, and reconfigure the resource base more quickly and more effectively than competitors (Schilke, 2014). It means building new resource configurations in pursuit of temporary advantages, or leveraging existing ones strategically, in a cycle of continuous renewal to counteract market dynamism and imitation.

The dynamic capabilities of sensing, seizing, and transforming are often categorised into orders. Some studies group these practices into lower-order and higher-order capabilities (or competence), while other studies consider zero-order, first-order, and second-order capabilities. In these hierarchical frameworks, zero-order capabilities (also termed ordinary or operational capabilities) are those that enable a firm to perform its current income-generating activities and 'make a living' in the present (Winter, 2003). First-order dynamic capabilities then refer to the patterned processes used to extend, modify, or create these zero-level ordinary capabilities, such as routines for new product development or market expansion. Moving further up the hierarchy, second-order dynamic capabilities involve the capacity to learn and to systematically build, renew, or reconfigure the first-order dynamic capabilities themselves, essentially improving how the firm changes (Danneels, 2016; Danneels, 2008). Consequently, the overarching dynamic capabilities of sensing, seizing, and transforming, as conceptualised by Teece, represent these higher-order functions that guide the evolution of a firm's operational base and its approaches to adaptation and innovation (Teece, Pisano & Shuen, 1997). However, it should be noted that while transforming is typically higher-order, sensing and seizing are more ambiguous and contain both lower- and higher-order elements depending on how routinised or strategic they are (Teece, 2007; Helfat & Peteraf, 2015).

Lower-order capabilities, commonly referred to as operational capabilities, consist of the repetitive routines and processes that underpin an organisation’s day-to-day functioning. These capabilities are typically stable, cumulative, and path-dependent. They enable firms to efficiently produce and deliver goods or services by leveraging existing knowledge, assets, and workflows (Eisenhardt & Martin, 2000; Winter, 2003). Their primary function lies in ensuring reliability, consistency, and productivity within known markets and technologies. As such, these capabilities are often associated with operational excellence and process optimisation but are generally considered imitable and unlikely to provide sustainable competitive advantage on their own (Teece, Pisano & Shuen, 1997; Carter, 2015). Although there is broad agreement that lower-order capabilities are essential for organisational continuity and incremental improvement, there remains disagreement over whether certain dynamic routines (such as sensing and seizing) should be partially categorised as lower-order, or whether they belong to a distinct layer of adaptive capabilities.

While lower-order capabilities are often distinguished from dynamic capabilities, some scholars argue that elements of sensing and seizing, as articulated in Teece (2007) dynamic capabilities framework, could partially rely on lower-order routines. For example, sensing may include routine data collection or customer feedback systems, and seizing may involve established procedures for allocating resources or making incremental improvements. However, while some views suggest that foundational capabilities can support the emergence of more dynamic forms (Watson et al., 2018), this needs to be interpreted cautiously, as elaborated below. Winter (2003) proposes a hierarchical model in which first-order dynamic capabilities are distinct from zero-order operational capabilities, but still incremental in nature, serving as precursors to more transformational second-order capabilities. This blurs the boundary between lower-order and dynamic capabilities, especially in moderately dynamic market environments (Eisenhardt & Martin, 2000). Capabilities are more structured and routine-like in stable contexts but become fluid and experiential in high-velocity environments. This view challenges any rigid classification scheme. Given organisational ambidexterity, firms can pursue both exploration and exploitation simultaneously, suggesting that capabilities could blend across hierarchical levels (O'Reilly & Tushman, 2011). Rindova and Kotha (2001) and Zott (2003) echo this by describing firms that continually morph and recombine capabilities in response to shifting competitive conditions.

Complementary to the above, higher-order capabilities, often referred to as second-order capabilities, represent a firm’s capacity to purposefully adapt, reconfigure, or build new resources and competences in response to substantial environmental change (Teece, 2007; Winter, 2003; Helfat & Maritan, 2024). Unlike operational capabilities, which focus on efficiency and reliability, higher-order capabilities are associated with organisational transformation, strategic renewal, and innovation (Teece, Pisano & Shuen, 1997; Zahra, Sapienza & Davidsson, 2006). These capabilities are crucial in turbulent environments, allowing firms to explore new markets and technologies, and to evolve strategically over time (Danneels, 2016; Danneels, 2012; Nguyen et al., 2023).

This transformative nature is captured in the “transforming” component of Teece’s triad of dynamic capabilities of sensing, seizing, and transforming (Teece, 2007; Teece, 2018). While sensing and seizing involve detecting opportunities and allocating resources, transforming encompasses deep structural change. However, the literature diverges on the sequencing and hierarchy of these capabilities (see Figure 1). Researchers such as Teece (2007); Teece (2019); Teece (2022) and Khurana, Dutta and Singh Ghura (2022) position transforming as an outcome of sensing and seizing. Others, such as Danneels (2016); Danneels (2008); Danneels (2012); Danneels (2002); Danneels (2011), present second-order capabilities as antecedents that enable the formation of new sensing and seizing routines. The former view suggests a bottom-up sequence in which higher-order capability emerges through the execution of more foundational processes. In contrast, the latter framing implies a top-down relationship. As such, second-order capabilities are not simply transformational outcomes of sensing and seizing routines, but rather the underlying strategic competencies that enable their very formation.

These differing logics of meta-structural versus sequential practices generate apparent contradictions in how capabilities are classified and related. A third perspective supports a reciprocal or co-evolutionary relationship, where capabilities influence each other dynamically over time through feedback, learning, and recombination (Helfat & Peteraf, 2003; Helfat & Peteraf, 2015; Schilke & Goerzen, 2010). Similar emergent models propose that higher-order capabilities can arise from the integration and refinement of lower-level routines in practice, as seen in contexts such as organisational resilience or crisis adaptation (Khurana, Dutta & Singh Ghura, 2022; Newey & Zahra, 2009). This challenges linear and hierarchical assumptions of capability development.

Schilke and Goerzen (2010) support a structural view, conceptualising higher-order capabilities as second-order constructs composed of multiple interrelated lower-level routines, such as coordination, learning, and transformation. This implies a formative relationship, showing that lower-level routines form the higher-order construct. However, once established, the higher-order capability could guide or reshape its components, for instance, by institutionalising coordination routines. Other perspectives further complicate the picture of capability hierarchies and development. They propose a capability lifecycle model, in which capabilities evolve, branch, replicate, and adapt (Helfat & Peteraf, 2003; Helfat & Maritan, 2024; Helfat, 1997). This potentially blurs the boundaries between capability levels as they mature or change in function. Thus, over time, lower-order capabilities can evolve into higher-order ones and vice versa as part of adaptive learning paths. Alternative emergent models illustrate how complex second-order capabilities like organisational resilience can emerge through the dynamic interplay of sensing, seizing, and transforming processes in response to external shocks (Khurana, Dutta & Singh Ghura, 2022). By contrast, second-order capabilities as intentional meta-capabilities (deliberately architected or developed by managers or firms) can in some cases guide the formation or renewal of lower-order routines and competences in anticipation of strategic challenges (Zahra, Sapienza & Davidsson, 2006; Helfat & Winter, 2011).

To exemplify the above, recent work by Watson, Wilson, Smart and Macdonald (2018) highlights how foundational routines such as value framing and systematised learning can act as enablers of stakeholder-related dynamic capabilities. Similarly, studies by Khurana, Dutta and Singh Ghura (2022) and Nguyen and Strange (2025) show that complex higher-order capabilities like resilience and strategic flexibility emerge through the integration of multiple lower-level processes. At the same time, scholars such as Barreto, Freitas and Freitas de Paula (2024) and Ambrosini and Bowman (2009) caution against oversimplifying the concept of dynamic or second-order capabilities. They argue that the construct suffers from definitional ambiguity and lacks consistent operationalisation across empirical studies. This concern is echoed by Zahra, Sapienza and Davidsson (2006), who call for clearer boundary conditions and distinctions between ordinary capabilities, dynamic capabilities, and strategic intent. This ongoing theoretical tension reflects the evolving nature of the dynamic capabilities framework and highlights the need for more integrative, empirically grounded models.

Theory Updates/Extensions

The seminal work by Teece, Pisano and Shuen (1997) initially proposed dynamic capabilities as firm-specific, idiosyncratic abilities to integrate, build, and reconfigure internal and external resources. Subsequently, Eisenhardt and Martin (2000) significantly extended the theory, proposing dynamic capabilities as identifiable, best-practice routines, challenging the earlier notion of uniqueness. Later, Zollo and Winter (2002) refined the theory further by conceptualising dynamic capabilities as structured, systematic learning processes rather than merely ad hoc adaptations. Teece (2007) offered another influential revision, categorising dynamic capabilities into three core processes: sensing, seizing, and transforming capabilities, thus clarifying their functional roles. More recently, the literature has explored the micro-foundations perspective, emphasising managerial cognitive abilities, routines, and individual behaviours as underlying components of dynamic capabilities, reflecting an ongoing theoretical evolution towards greater specificity and empirical grounding (Helfat & Peteraf, 2015).

Applications

Since its introduction, the dynamic capability theory has been widely applied across multiple academic disciplines to explain how organisations adapt and sustain competitive advantage in changing environments. Originally grounded in strategic management (Teece, Pisano & Shuen, 1997), the concept has since informed research in fields such as operations and supply chain management, marketing, innovation management, information systems management, and other management research domains. Scholars have used dynamic capabilities to examine phenomena ranging from product innovation and supply chain agility to strategic alliances and digital transformation (Eisenhardt & Martin, 2000; Zahra, Sapienza & Davidsson, 2006; Franco & Giannoccaro, 2025).

Parallel to this broad application, there has been a growing emphasis on the micro foundations of dynamic capabilities. Micro foundations are the individual-level and organisational mechanisms that underpin sensing, seizing, and transforming processes. This micro-level perspective focuses on routines, cognitive capabilities, and leadership behaviours as the building blocks of dynamic capability (Helfat & Peteraf, 2015). Specifically measuring and quantifying the micro foundations reflects a shift toward unpacking the internal workings of capabilities. This allows researchers to link abstract theoretical constructs to concrete actions, behaviours, and decision-making processes at various levels or units-of-analysis.

Strategic Management

In the field of strategic management, the micro foundations of dynamic capabilities are increasingly being examined through the cognitive, behavioural, and relational mechanisms that underpin how firms perceive, interpret, and respond to strategic change (Table 2). At the higher-order level, key micro foundations include managerial cognition, strategic foresight, and resource orchestration. These are mechanisms that enable firms to reconfigure their strategic directions and renew lower-level capabilities (Bendig et al., 2018; Kevill et al., 2021).

Helfat and Peteraf (2015) introduced the concept of "managerial cognitive capabilities". For instance, managers’ time allocation has been identified as a micro-foundation of dynamic managerial capabilities, with implications for both capability enactment and vulnerability (Kevill et al., 2021). These cognitive micro foundations play a central role in shaping how managers interpret strategic threats and opportunities, thereby influencing firm adaptation and long-term performance (Ljungkvist, Boers & Axell, 2024; Adner & Helfat, 2003). Supporting this, Kiss, Libaers, Barr, Wang and Zachary (2020) identify CEO cognitive flexibility and information search as vital micro foundations in driving organisational ambidexterity and innovation-based strategic responses. In the same vein, social capital embedded in CEOs through networks and external relationships acts as a micro-foundation for dynamic capabilities, influencing strategic responsiveness, especially under varying institutional and environmental conditions (Durán, Aguado & Perdomo-Ortiz, 2023; Durán & Aguado, 2022; Engelen et al., 2025).

In addition to cognitive mechanisms, scholars have emphasised behavioural and relational foundations such as decision-making routines, coordination practices, and leadership engagement. For instance, in structured environments, strategic decision-making is often supported by linear, analytical routines that facilitate stable performance, while in dynamic contexts, fast and iterative decision-making processes become essential (Eisenhardt & Martin, 2000). Similarly, Teece (2007) and Foss and Pedersen (2016) point to routines like scenario planning, performance monitoring, and strategy workshops as critical lower-order mechanisms that operationalise strategic change. Feedback loops, issue-selling routines, and organisational alignment mechanisms allow lower-level actors to shape strategic agendas and enhance the adaptability of strategic processes (Helfat & Winter, 2011; Ashiru et al., 2022). The dynamic interplay between these levels supports a co-evolutionary view of strategy. In this vein, high-level cognitive capabilities set direction, and lower-order routines reinforce and embed strategic intent.

Other studies expand this view by integrating structural and cultural elements. For instance, Kiss (2025) identifies strategic alignment, organisational structure, and leadership framing as critical micro foundations in retail banking’s dynamic capability development. Studies have also explored how leadership configuration and team-level processes contribute to dynamic strategic capability. For example, Martin (2011) and Taylor and Helfat (2009) show how middle managers facilitate strategic renewal by transforming shared cognitive frames within the firm. Managerial heterogeneity across executive teams has been linked to variation in strategic change, with evidence that diversity in beliefs and cognitive styles influences how firms interpret and react to environmental complexity (Eggers, 2012). Foss and Pedersen (2016) argue that strategic capabilities have to be understood through the interaction of individual-level cognition, group-level coordination, and firm-level routines, particularly as these layers interact to generate competitive advantage.

Research on the sustainability strategy space supports this layered understanding. Bağış et al (Bağış et al., 2025) identify mechanisms such as knowledge dissemination and process reconfiguration functions as lower-order routines, and others such as green innovation coordination and strategic transformation routines as higher-order micro foundations that drive sustainability-oriented capability renewal. In addition, Chevrollier, van Lieshout, Argyrou and Amelink (2024) identify strategic renewal, carbon footprint framing, and sustainability-oriented stakeholder engagement as key micro foundations enabling environmental dynamic capabilities. These mechanisms contribute to a firm’s ability to maintain strategic alignment in carbon-sensitive sectors. Ecosystem integration and circular learning routines as dynamic micro foundations facilitate strategic ecosystem creation in circular economy contexts (Castillo-Ospina et al., 2025). The above literature demonstrates that strategic DCs are built from the bottom up and top down, requiring the integration of lower-order routines with higher-order interpretive and orchestration mechanisms that dynamically co-evolve to drive competitive advantage.

Operation and Supply Chain Management (OSCM)

As shown in Table 3, dynamic capabilities are increasingly understood as being underpinned by a layered system of micro-foundations that include both operational routines and strategic orchestration mechanisms. At the lower-order level, frequently cited micro-foundations include supply chain integration, lean coordination routines, just-in-time inventory systems, and workflow standardisation, all of which support firms in maintaining responsiveness and process efficiency during external shocks (Bağış et al., 2022; Gohr, Torres & Lira, 2023). These operational routines are primarily linked to the sensing and seizing, as they enable real-time adjustments by improving information flow and synchronising the procurement, production, and logistics functions. In addition, supplier communication protocols, modular system architectures, and decentralised decision-making provide flexibility in execution and adaptation (Colombari, Neirotti & Berbegal-Mirabent, 2024). While these micro-foundations do not directly alter a firm’s strategic trajectory, they form the executional base that supports routine responsiveness and learning.

Conversely, higher-order micro-foundations in OSCM pertain to the ability to strategically reconfigure supply chains in response to longer-term changes and disruptions. Capabilities such as supply chain resilience, strategic supplier integration, end-to-end visibility, and ecosystem orchestration enable firms to adapt not only their operations but also their underlying business models and structures (Khurana, Dutta & Singh Ghura, 2022; Ashiru et al., 2022). These mechanisms are often relational and collaborative in nature, built on trust-based governance, multi-tier supplier collaboration, and inter-organisational learning routines that span firm boundaries (Brusset & Teller, 2017; Giudici, Reinmoeller & Ravasi, 2018). For example, Silva, Pereira and Hendry (2023) identify sustainability-oriented micro-foundations such as stakeholder engagement, adaptive rule-setting, and institutional responsiveness as critical to enabling reconfigurable and future-proof supply chains. Similarly, strategic integration operates as a higher-order micro-foundation, as it aligns long-term sustainability goals with operations and supply chain management (OSCM) transformation, while the operational and functional practices are more aligned with lower-order routines (Stoyanova & Stoyanov, 2024). Furthermore, leadership foresight, platform-enabled risk sensing, and dynamic orchestration of digital infrastructures function as meta-capabilities, linking operational routines with high-level transformation (Chirumalla, Leoni & Oghazi, 2023; Brunner, Schuster & Lehmann, 2023).

The co-evolution of lower-order and higher-order micro-foundations is central to dynamic capability development in OSCM. For instance, Eisenhardt and Martin (2000) argue that effective supply chain transformation relies on the recombination of internal and external resources through routines that can be both stable and reconfigurable. Moreover, in digitally intensive supply chains, analytics-based learning, automated sensing platforms, and flexible reconfiguration tools help bridge the divide between operational responsiveness and strategic renewal (Colombari, Neirotti & Berbegal-Mirabent, 2024; van Eechoud & Ganzaroli, 2023). These findings reinforce the idea that dynamic capabilities in OSCM are not simply about resilience or speed, but about the capacity to continuously restructure routines and realign resources in response to environmental complexity, uncertainty, and strategic shifts.

Marketing

In the marketing domain, the micro foundations of dynamic capabilities span a broad spectrum of sensing, interpretive, and transformative mechanisms, as listed in table 4. Dynamic marketing capabilities enable market learning, resource reconfiguration, and capability enhancement. In this context, cross-functional (e.g., CRM, brand management) and architectural capabilities (e.g., strategic planning, implementation) integrate lower-order routines to support adaptive strategy and positional advantage. Other foundational routines such as customer sensing, data analytics infrastructures, and real-time market monitoring support firms in detecting and interpreting emerging opportunities (Morgan & Feng, 2024; Ajgaonkar, Neelam & Wiemann, 2022). Though largely lower-order, these mechanisms are critical in guiding strategic marketing responses. Sambamurthy, Bharadwaj and Grover (2003), for example, have introduced customer agility, comprising virtual customer communities, automated feedback loops, and insight integration routines that enhance responsiveness to evolving demand. In the same vein, real-time competitive intelligence and digital platform sensing act as behavioural and technological micro foundations that enhance strategic adaptability in volatile markets .

Beyond sensing, research highlights the micro foundations that enable seizing and transformation. Value-based selling, especially in B2B, relies on solution-oriented routines, customised delivery, and relational engagement, which can be elevate to higher-order capabilities when integrated into broader innovation systems (Liu & Zhao, 2021). Other notable micro foundations include brand ambidexterity, customer co-creation, and agile campaign systems. For instance, coordination and learning routines are essential in high-velocity digital environments (Schilke & Goerzen, 2010), while value framing and stakeholder interpretation routines support innovation and collaborative strategy (Watson et al., 2018). Zott (2003) identifies business model design as a marketing capability grounded in experimentative routines and network sensing, while Chirumalla, Leoni and Oghazi (2023) highlight servitisation routines, such as customer experience integration and digital feedback, as key enablers of renewal.

In digitally mature firms, marketing analytics is a vital micro foundation. Automated segmentation, real-time optimisation, and machine learning profiling drive precision and adaptability (Brunner, Schuster & Lehmann, 2023; Kroh et al., 2024). For instance, digital dashboards, AI-assisted decisions, and adaptive pricing are critical to marketing agility (Ajgaonkar, Neelam & Wiemann, 2022). In global contexts, attention structures and institutional framing routines also help align market interpretations across regions (Kaur, 2023). Lastly, strategic elements like brand orientation, internal knowledge dissemination, and emotional engagement further connect daily operations to long-term strategic adaptation (Watson et al., 2018; Newey & Zahra, 2009). Together, these findings show that marketing DCs consist of both lower-order routines (e.g., analytics, coordination, feedback) and higher-order mechanisms (e.g., brand orchestration, market transformation), enabling firms to continually reconfigure in response to dynamic technological, cultural, and market shifts.

Innovation Management

In the domain of innovation management, the micro foundations of dynamic capabilities are central to how firms sense, seize, and transform their innovation processes (Table 5). At the lower-order level, firms often rely on absorptive capacity, cross-functional collaboration, knowledge recombination, and structured R&D routines to assimilate and exploit new external knowledge (Bağış et al., 2022; Gohr, Torres & Lira, 2023). These mechanisms underpin exploration and exploitation efforts and facilitate the generation of new products, processes, and business models. Higher-order innovation capabilities emerge when firms intentionally orchestrate and align these lower-order routines across organisational structures. For instance, repeated stakeholder integration routines evolve into learning capabilities that transform internal decision-making for product innovation. In this context, internal and external stakeholder engagement routines, when institutionalised, function as dynamic capabilities driving sustainable innovation strategies (Ayuso, Ángel Rodríguez & Enric Ricart, 2006). Equally, open innovation implementation routines, including partner selection frameworks and absorptive capacity mechanisms, act as essential higher-order capabilities (Shenoy, Mahapatra & Mahanty, 2025).

The co-evolutionary perspective is also important in innovation management, where systems evolve through interaction between individuals and organisational routines. Horbach (2008) highlights how the restructuring of organisational systems and norms supports new product and process innovations. Meanwhile, Gahan, Theilacker, Adamovic, Choi, Harley, Healy and Olsen (2021) show that high-performance work systems and leadership capabilities serve as strategic enablers of innovation, particularly when adapted to environmental dynamism. Lastly, micro foundations like engagement learning routines, value framing, and organisational cognition enable firms to shift from ad hoc experimentation to routinised innovation management (Watson et al., 2018). Thus, in innovation management, dynamic capabilities are scaffolded by micro foundations ranging from codified R&D to adaptive leadership, progressing from sensing and seizing to transformation through strategic alignment and learning.

Information Systems Management

In the field of Information Systems Management (ISM), the micro foundations of dynamic capabilities, shown in table 6, have increasingly been studied through the lens of digital transformation and technology-enabled adaptation. Foundational lower-order micro foundations include real-time data analytics, IT infrastructure integration, and data-driven decision-making routines, which allow firms to sense changes in the digital environment and react quickly to emerging market conditions (Kroh et al., 2024). These are complemented by platform coordination mechanisms, such as enterprise resource planning (ERP) systems and digital dashboards, which enable seamless internal alignment and operational responsiveness. Transactional-level IT capabilities, including remote monitoring and adaptive service platforms, act as enablers of operational agility in digitally sensitive domains such as healthcare (Singh et al., 2011).

Higher-order micro foundations, by contrast, are more strategic and transformative in nature. These include capabilities like digital leadership, IT-business strategic alignment, and digital mindset crafting processes that enable organisations to integrate digital sensing, seizing, and transforming activities (Helfat & Raubitschek, 2018). For example, organisations that implement cross-functional digital steering committees and cultivate digital governance frameworks are more adept at orchestrating enterprise-wide changes and responding proactively to disruptive innovation (Schilke, Hu & Helfat, 2018). Digital sensing sub-capabilities such as digital scouting, scenario planning, and competitive IT intelligence have been identified as essential for anticipating technological shifts , while digital seizing mechanisms include rapid prototyping, agile development cycles, and design thinking, particularly when embedded within strategic agility frameworks. Ravichandran (2018) adds that digital transformation success also depends on organisational capability layering, where micro foundations evolve through recursive learning between business and IT units.

Studies further highlight such micro foundations as ecosystem foresight, digital capability orchestration, and value co-creation with external partners. This is especially relevant in platform-based business models and digital ecosystems (Sjödin, Liljeborg & Mutter, 2024). In such contexts, integrative capabilities play a crucial role by linking external technological innovations to internal reconfiguration processes. Additionally, IT ambidexterity, defined as the ability to balance exploratory and exploitative digital initiatives, has emerged as a key micro foundation supporting long-term renewal and responsiveness (Wetering, 2021). IS research increasingly views these micro foundations not only as drivers of digital competitiveness but also as mediators of business model transformation and strategic renewal (Velu, 2017). Thus, dynamic capabilities in ISM are shaped by an interplay of IT-enabled routines and strategic foresight mechanisms, where both technological and managerial capabilities have to co-evolve to sustain firm performance in turbulent digital landscapes.

Limitations

Despite extensive application in strategic management research, dynamic capability (DC) theory has attracted substantial critique, primarily for its conceptual ambiguity, operationalisation challenges, and tautological reasoning. Scholars argue that DC theory suffers from significant definitional vagueness, leading to inconsistent interpretations and empirical applications. Laaksonen and Peltoniemi (2018) specifically emphasise the problematic operationalisation of dynamic capabilities, noting discrepancies between theoretical constructs and empirical measures, which complicate the distinction between dynamic and ordinary capabilities and introduce methodological biases. Further criticism arises from tautological concerns, as researchers often retrospectively attribute superior firm performance to dynamic capabilities without adequately specifying how these capabilities are independently identified and verified.

Additionally, the contextual dependency of DCs, varying distinctly across moderately and highly dynamic environments, raises concerns about the theory’s generalisability and universal applicability (Eisenhardt & Martin, 2000). Internal theoretical contradictions, notably the divergent perspectives proposed by Teece, Pisano and Shuen (1997) emphasising firm-specific and evolutionary processes, versus Eisenhardt and Martin (2000) identification of broadly applicable ‘best practices’, further challenge the coherence and robustness of DC theory. The theory also inadequately addresses spontaneous, ad-hoc responses and managerial improvisation, which could be crucial in highly volatile environments. Lastly, despite an emphasis on micro-foundations and managerial agency as vital to capability development, empirical studies struggle to systematically account for these complex cognitive and behavioural factors, leaving significant gaps in understanding how DCs practically manifest themselves within organisational processes. These critiques collectively indicate significant theoretical and methodological limitations, necessitating refined definitions, rigorous empirical approaches, and clearer articulation of DCs’ operational mechanisms and boundary conditions.