The Role of Marketing Communication and Dynamic Capabilities in Startup Growth: A Strategic Model for Business Model Evolution in Emerging Economies

Abstract

Purpose: The purpose of this research is to explore the intersection between marketing communication and dynamic capabilities in shaping startup growth within emerging economies, where institutional voids, volatile markets, and resource scarcity demand adaptive strategies. Research design, data, and methodology: The study adopts a qualitative multi-case research design to investigate startups operating in resource-constrained contexts. Data were gathered from ten startups across Indonesia, Nigeria, and India through semi-structured interviews and the analysis of relevant documents. This approach provides a rich empirical basis for comparing how communication practices are integrated with dynamic capabilities and how these interactions shape business model adaptation. Results: The results indicate that startups that strategically align communication practices-through message design, media choice, and stakeholder engagement-with the dynamic capabilities of sensing, seizing, and transforming are more effective in innovating, adapting, and maintaining customer orientation. This alignment strengthens their ability to adjust business models in uncertain and resource-constrained environments. Conclusions: The study concludes that marketing communication serves as a vital driver of dynamic capabilities, enabling startups in emerging economies to adapt, innovate, and scale. These insights provide practical guidance for entrepreneurs navigating resource-constrained environments and contribute conceptually to advancing scholarship in strategic management and communication.

1. Introduction

The contemporary business environment is increasingly characterized by volatility, uncertainty, complexity, and ambiguity (VUCA) (Bennett & Lemoine, 2014). Accelerating technological change and unstable market conditions have transformed organizational dynamics, requiring firms to build agility and adaptability to survive and sustain competitive advantage (Teece et al., 1997; Eisenhardt and Jeffrey A. Martin, 2000). Startups, in particular, operate at the intersection of innovation and uncertainty, facing resource constraints and rapidly shifting consumer demands. These conditions necessitate strategies that are both dynamic and integrative.

Within this context, the interplay of marketing communication and dynamic capabilities becomes a critical but underexplored area of inquiry. Marketing communication is not merely a promotional tool; it is a strategic mechanism through which startups shape consumer perceptions, establish legitimacy, and foster loyalty in crowded markets (De Pelsmacker et al., 2017; Kulsum, 2017). At the same time, business models have shifted from static frameworks of value creation to dynamic, iterative architectures that mediate between technological innovation and economic value capture (Teece et al., 1997). Dynamic capabilities—sensing, seizing, and transforming—are central to this adaptability, enabling firms to identify opportunities, mobilize resources, and renew organizational structures (Teece et al., 1997; Teece, 2018).

Despite substantial theoretical progress, prior research has tended to examine marketing communication in established firms or consumer markets, leaving its role as a driver of dynamic capabilities in startups—particularly within emerging economies—largely unaddressed. Similarly, while studies of business models and dynamic capabilities emphasize adaptation and renewal, they often overlook how communication strategies underpin these processes in resource-constrained and institutionally complex settings (Khanna & Palepu, 2010; Cuervo-Cazurra et al., 2018). This omission is notable given that startups in emerging economies must not only innovate under uncertainty but also overcome institutional voids and build consumer trust from a low baseline of brand recognition.

This paper addresses these gaps by developing a conceptual framework that integrates marketing communication and dynamic capabilities within the architecture of the Business Model Canvas (Osterwalder & Pigneur, 2010). By aligning key business components—such as customer segmentation, strategic partnerships, and revenue streams—with the processes of sensing, seizing, and transforming, the framework positions marketing communication as a core enabler of startup adaptability rather than a peripheral support function. While conceptual, the model draws on multi-case qualitative insights from startups in Indonesia, Nigeria, and India, illustrating how communication strategies aligned with dynamic capabilities support business model innovation under uncertainty.

The contributions of this paper are threefold. Theoretically, it advances understanding of how communication and capabilities intersect in the strategic management of startups in emerging economies. Empirically, it enriches the literature by drawing on cases from underrepresented contexts, where institutional and infrastructural challenges differ markedly from those in developed economies. Managerially, the framework offers actionable guidance for startup founders to integrate communication with capability-building for greater scalability, and for policymakers to design support mechanisms that strengthen entrepreneurial ecosystems through communication-driven innovation.

The remainder of the paper is structured as follows. Section 2 critically reviews relevant literature on dynamic capabilities, marketing communication, and business model innovation. Section 3 presents the proposed conceptual framework. Section 4 discusses implications for research and practice, along with avenues for empirical validation.

2. Literature Review

Dynamic capabilities describe a firm’s ability to purposefully adapt, integrate, and reconfigure internal and external resources in response to fast-paced and unpredictable environments (Teece et al., 1997; Teixeira et al., 2021). This framework has become central to strategic management research, offering insight into how firms sustain competitive advantage under conditions of turbulence. More than a reactive function, dynamic capabilities emphasize anticipatory, proactive, and transformative action (Teixeira et al., 2021).

Teece (2007) distinguishes three interrelated dimensions: sensing, seizing, and transforming. Sensing entails scanning and interpreting shifts in markets, technologies, or regulations, requiring investment in intelligence gathering, stakeholder engagement, and exploratory activities (Supramono et al., 2025). Seizing refers to mobilizing resources and designing business models that convert opportunities into strategic action. Transforming involves continuous renewal of routines, structures, and competencies to sustain long-term adaptability. These processes collectively enable organizations to innovate, adapt, and remain resilient in volatile contexts (Dressler, 2023).

While foundational studies established the theoretical framework (Teece et al., 1997; Eisenhard & Martin, 2000). More recent scholarship has extended its application to startups and digital ecosystems. For instance, Ferereira et al. show that dynamic capabilities enhance innovation and competitive advantage through exploration and exploitation (Ferreira et al., 2020). In emerging markets, Filatotchev, Aguilera, and Wright (2020) highlight that startups rely on dynamic capabilities to overcome institutional voids and resource scarcity (Filatotchev et al., 2020). Similarly, scholars demonstrate how digital platforms allow startups in Asia and Africa to sense opportunities and rapidly reconfigure business models. Collectively, these studies underscore that dynamic capabilities are critical not only in established firms but also in nascent ventures navigating uncertain institutional contexts (João, 2023; Sarwar et al., 2024).

A consistent theme across this literature is the balancing of exploration and exploitation. Startups that combine experimentation with refinement of existing competencies achieve superior innovation outcomes (Ferreira et al., 2020). This balance is particularly salient in emerging economies, where volatility forces firms to pivot quickly while leveraging scarce resources. Breznik and Lahovnik (2016), in their case study of IT firms, stress that neglecting any one dimension—sensing, seizing, or transforming—weakens overall adaptability, suggesting the importance of a holistic capability configuration (Breznik & Lahovnik, 2016).

Dynamic capabilities are not exercised in isolation but are embedded in business models and mediated by communication strategies. Business models act as cognitive and structural templates for value creation and capture (Chesbrough, 2010; Zott & Amit, 2010). Recent research suggests that startups in digital ecosystems adapt their business models dynamically by integrating customer feedback and real-time market signals (Nambisan et al., 2019). In this process, marketing communication becomes pivotal. Rather than functioning as a peripheral promotional activity, it serves as a capability-enabling mechanism that shapes market sensing, facilitates customer engagement, and legitimizes business pivots (Sun et al., 2021).

This integrative perspective underscores two implications. Theoretically, it positions marketing communication as an embedded element of dynamic capabilities, aligning message design, media selection, and stakeholder engagement with sensing, seizing, and transforming. Practically, it suggests that startup founders should treat communication not as a downstream activity but as a strategic lever for business model innovation. For policymakers, the implication is that support for entrepreneurship must extend beyond financing and infrastructure to include capacity-building in communication strategies that enhance startups’ agility and resilience.

In sum, the literature highlights the centrality of dynamic capabilities in shaping firm adaptability, but it also reveals gaps. Most studies emphasize corporate-level dynamics in developed economies, with relatively limited exploration of startups in emerging markets. Moreover, existing frameworks (e.g., Teece, 2009; Schön, 2012) illustrate capability processes in broad terms but rarely integrate marketing communication into their architecture. This study addresses these omissions by proposing a conceptual framework that positions communication as a core micro-foundation of dynamic capabilities within startup business models, particularly in the turbulent and resource-constrained settings of emerging economies.

3. Method, Data, and Analysis

This study adopts a multi-case qualitative research design to illustrate and refine the proposed conceptual framework linking dynamic capabilities, marketing communication, and business model adaptation in startups (Teixeira et al., 2021; Feng et al., 2022). While this paper's primary contribution is conceptual, the integration of empirical evidence strengthens its theoretical grounding and provides contextual nuance, particularly in emerging economies where entrepreneurial ecosystems are often fragile.

A fundamental tension frequently arises in such contexts between business models and strategy. Startups must decide whether to adjust the business model to fit an emergent strategy or to reshape strategic choices to remain consistent with the existing model. This dilemma underscores the importance of strategic leadership. As Teece (2018a) emphasizes, when inconsistencies between strategy and business model emerge, it is the responsibility of top management to determine which element should adapt—highlighting the simultaneous need for flexibility and coherence. The present study explores how startups in dynamic markets confront this tension by mobilizing dynamic capabilities and leveraging communication strategically (Rinthaisong & Duangtong, 2024).

To capture this process, ten startups were purposefully sampled from Indonesia, Nigeria, and India—three emerging economies where market volatility, institutional gaps, and resource scarcity present both constraints and opportunities for entrepreneurial growth. The cases represent variation in sector (technology, consumer goods, education, and financial services) and stage of development (from early growth to scaling). Examining this diversity provides a rich basis for analyzing how business models evolve in response to shifting strategies, and how communication practices mediate the alignment between capabilities and growth trajectories.

The framework developed here makes two key contributions. Conceptually, it advances dynamic capabilities theory by positioning marketing communication not as a peripheral support function but as an embedded enabler of sensing, seizing, and transforming. Empirically, it extends the literature by providing insights from startups in emerging economies, a context often underrepresented yet increasingly central to global entrepreneurship.

The study also highlights important practical implications. For startup founders, the framework underscores the need to align communication strategies with capability development: designing messages that capture consumer insights (sensing), using media strategically to scale value propositions (seizing), and engaging stakeholders transparently to support business pivots (transforming). For policymakers and incubators, the findings suggest that capacity-building programs should integrate training in strategic communication alongside financial and technical support, thereby strengthening the broader ecosystem for entrepreneurial growth.

Figure 1: Dynamic capabilities chart

Dynamic capabilities—defined as a firm’s capacity to sense opportunities, seize them effectively, and transform its asset base (Teece, 2007)—enable organizations to continuously revise and improve their business models to revise and improve their business models continuously. These capabilities form the foundation for long-term competitiveness in fast-changing environments (Ambrosini & Bowman, 2009). The interdependence between business models and dynamic capabilities underscores the importance of integrative thinking in strategic decision-making.

Teece (2018a) proposes a conceptual model where business model design sits beneath and is influenced by dynamic capabilities. In this schema, dynamic capabilities allow for rapid prototyping, testing, and iterative refinement of business models (Oliveira-Dias et al., 2022). The strategic fit between capability development and business model configuration determines whether a firm can generate and sustain above-normal returns (Zahra et al., 2006). Critically, the architecture of the business model—its value proposition, revenue streams, cost structure, and key partnerships—must be intentionally aligned with the firm's evolving capabilities and environmental demands (Amit & Zott, 2001).

For innovative enterprises, dynamic capabilities facilitate the identification of underserved consumer segments and the design of novel value propositions. This process begins with the recognition of latent or emerging needs—what Christensen (1997) refers to as “non-consumption” markets. A robust business model then seeks to capture value by offering solutions consumers are willing to pay a premium for, thereby covering costs and generating sufficient returns. Importantly, firms with high dynamic capabilities can explore radical shifts in business model configuration, even when such changes necessitate restructuring internal resources or abandoning legacy activities (Teece, 2010).

In early-stage ventures and startups, dynamic capabilities have been empirically linked to growth trajectories. Telussa (2006), for instance, identifies key indicators of dynamic capabilities in startups—such as international product development, collaborative alliances, and investment in R&D—as predictive of firm growth. These capabilities can be quantitatively assessed through outcomes such as employee expansion, asset accumulation, and profitability, reflecting the firm’s ability to convert knowledge and innovation into tangible growth.

While the dynamic capabilities framework offers a compelling lens for understanding the interplay between marketing communications, strategy, and business models, it is not without critique. Scholars have pointed out that the operationalization of dynamic capabilities remains ambiguous and context-dependent (Arndt & Bach, 2015). Furthermore, the recursive feedback loop between strategy, business models, and capabilities—acknowledged but not fully developed in Teece’s (2018a) model—deserves greater empirical scrutiny. As Bowman and Ambrosini (2003) argue, strategic value is not just created through the firm’s internal processes but is. Still, it is also socially constructed by stakeholders, making marketing communication a critical tool in shaping perceptions and legitimacy.

Moreover, integrating marketing communications into this framework extends its strategic value beyond message dissemination. Communication practices influence customer co-creation, brand narratives, and stakeholder alignment—all of which are essential in dynamic environments (Keller, 2009). Firms must, therefore, develop communication strategies that are not only consistent with the business model but are also flexible enough to evolve as capabilities mature.

4. Marketing Communications and the Impact of Dynamic Capabilities on the Startup Business Model

The implementation of marketing communications in the business model for startups needs high flexibility, making it very important. Market development (Schön, 2012) is critical in the early phases in adherence to the following pattern:

According to Figure 2, startups should anticipate four market characteristics, including volatility, the pace of change, complexity, and power shift. The business model is focused differently at each stage of dynamic capability. Dynamic capabilities are often analyzed at the "corporate" level in large companies, but this is still suitable for startups. Furthermore, they should also be necessary at the business unit, product, and individual manager levels of managerial capabilities. However, they should be viewed as a whole in theory, and an individual, particular element approach should also be carried out, such as product involvement, price logic, and geographical distribution. These elements can or cannot be selected or developed separately. Each element should be coherently adapted to the strategic vision to generate profit when included in the business system (Teece, 2018b). Therefore, dynamic capabilities can be broken down into microelements as shown below:

Figure 2: Market development

Figure 3: Micro foundation dynamic capabilities for a startup

Dynamic capabilities constitute a critical independent variable in assessing the growth trajectory of new ventures and startups (Corvello, Cimino, and Felicetti, 2023). As firms navigate highly uncertain and competitive environments, dynamic capabilities—defined as the firm’s ability to integrate, build, and reconfigure internal and external competencies—become central to achieving sustainable competitive advantage (Teece, 2007). In the context of startups, critical resources emerge as essential components of the business model, particularly when linked with key indicators of dynamic capabilities such as research and development, new product innovation, entry into international markets, and strategic alliances with external entities.

However, startup growth is inherently multidimensional and cannot be attributed to dynamic capabilities alone. Other determinants—such as financial capital, human capital, social capital, organizational learning, and environmental dynamism—also play integral roles. These complementary factors provide the necessary foundation for the mobilization of dynamic capabilities and shape the conditions under which they can be effectively deployed.

Result and Discussion

In the domain of marketing communication, dynamic capabilities serve as a pivotal mechanism for startups to respond to volatile market conditions, particularly those arising from rapid technological advances characteristic of the Fourth Industrial Revolution. Since the emergence of Industry 4.0 around 2011, the capacity to adapt business models swiftly and strategically has become indispensable. Dynamic capabilities unfold in three interconnected phases—sensing, seizing, and transforming—each requiring specific adjustments to the startup’s business model elements to formulate and sustain competitive strategies.

During the sensing phase, startups identify emerging customer needs and market opportunities. In practice, this often translates into rapid experimentation with different customer segments and value propositions. For example, an Indonesian edtech startup initially targeting university students shifted its focus to primary and secondary school learners after recognizing increased parental demand for digital tutoring during the COVID-19 pandemic. This adjustment illustrates how the Customer Segments and Value Proposition components of the Business Model Canvas (BMC) must remain fluid, adapting to shifting technological and consumer landscapes (Dejardin et al., 2023).

The seizing phase necessitates the mobilization of Key Resources and Key Partnerships to capture identified opportunities. Several cases in this study demonstrate the strategic use of partnerships to scale offerings. For instance, a Nigerian fintech startup leveraged alliances with local banks and mobile operators to extend its services to rural populations, thereby pursuing a “blue ocean strategy” that tapped into previously underserved markets. Such deliberate targeting of untapped niches not only mitigated direct competition but also reinforced the firm’s capacity to seize opportunities through communication strategies that emphasized trust, accessibility, and inclusion (Batista & VIgente, 2020; Osabutey & Jackson, 2024)

In the transforming phase, startups reconfigure their Cost Structures and Revenue Streams in response to scaling operations, evolving market demands, and potential diversification. Strategic collaborations and alliances play a vital role in facilitating this transformation. For example, an Indian consumer goods startup initially operating through direct-to-consumer sales integrated its distribution with established retail chains as it scaled. This pivot required revising revenue models, while transparent stakeholder communication enabled smoother negotiation with investors and suppliers. Such transformations underscore how startups can maintain agility while sustaining coherence across business model elements (Natasha, 2025). While the proposed conceptual framework links dynamic capabilities to specific BMC components and offers a structured pathway for startup growth, these findings highlight the need for empirical nuance. The case illustrations suggest that the interaction between dynamic capabilities and business model elements is not linear but iterative, often requiring multiple cycles of experimentation before stability is achieved. Future research should therefore employ longitudinal and comparative studies to test the model’s predictive power and explore its applicability across diverse startup contexts. Moreover, an integrated approach that examines the interplay between dynamic capabilities and external enablers—such as financial capital, organizational structure, social networks, human capital, and environmental volatility—would yield a more holistic understanding of the drivers of startup success (Randhawa et al., 2021; Sanasi, 2023).

In sum, dynamic capabilities are not merely supportive of startup growth—they are foundational. When systematically integrated into a flexible and adaptive business model, they empower startups to anticipate change, mobilize resources effectively, and reconfigure strategies in response to disruption. This analytical lens underscores the need for strategic agility, continuous innovation, and collaborative capacity as essential levers in the pursuit of sustainable entrepreneurial growth. By demonstrating how sensing, seizing, and transforming manifest in specific entrepreneurial practices, this study contributes to bridging the conceptual and empirical divide.

In the domain of marketing communication, dynamic capabilities serve as a pivotal mechanism for startups to respond to volatile market conditions, particularly those arising from rapid technological advances characteristic of the Fourth Industrial Revolution. Since the emergence of Industry 4.0 around 2011, the capacity to adapt business models swiftly and strategically has become indispensable. Dynamic capabilities unfold in three interconnected phases—sensing, seizing, and transforming—each requiring specific adjustments to the startup’s business model elements to formulate and sustain competitive strategies.

During the sensing phase, startups identify emerging customer needs and market opportunities. Here, Customer Segments and Value Proposition components of the Business Model Canvas (BMC) must remain fluid, adapting to shifting technological and consumer landscapes. The seizing phase necessitates the mobilization of Key Resources and Key Partnerships to capture identified opportunities. Startups at this stage often adopt a “blue ocean strategy,” deliberately targeting untapped markets to mitigate direct competition. In the transforming phase, startups must reconfigure their Cost Structures and Revenue Streams in response to scaling operations, evolving market demands, and potential diversification. Strategic collaborations and alliances often play a vital role in facilitating this transformation.

While the proposed conceptual framework links dynamic capabilities to specific BMC components and offers a structured pathway for startup growth, it remains a hypothetical model that has yet to undergo empirical validation. Future research should employ longitudinal and comparative studies to test the model’s predictive power and explore its applicability across diverse startup contexts. Moreover, an integrated approach that examines the interplay between dynamic capabilities and external enablers—such as financial capital, organizational structure, social networks, human capital, and environmental volatility—would yield a more holistic understanding of the drivers of startup success.

This study demonstrates that dynamic capabilities—sensing, seizing, and transforming—are critical to shaping the evolution of startup business models in volatile markets. By integrating these phases with the Business Model Canvas, this paper offers a practical and adaptable framework for strategic decision-making in startups. Future research should empirically test this model across various emerging market contexts and industries, potentially incorporating metrics such as growth rate, market entry speed, or customer retention as outcome variables

Conclusion and Suggestion

This study provides an integrated perspective on how dynamic capabilities and marketing communication jointly shape the growth trajectories of startups in volatile and resource-constrained environments. By mapping the dynamic capability processes—sensing, seizing, and transforming—onto the key components of the Business Model Canvas (BMC), the study advances a conceptual framework that demonstrates how startups can strategically adapt their business models in response to environmental turbulence, technological disruption, and evolving consumer expectations.

Empirically, the research contributes to the understanding of how startups in emerging markets deploy marketing communication as a strategic enabler of capability development rather than as a peripheral promotional function. Theoretically, it highlights the interdependence between dynamic capabilities and business model innovation, suggesting that adaptability and strategic agility are foundational—not supplementary—to sustained entrepreneurial growth. Economically, the findings offer actionable insights for founders, investors, and policymakers seeking to enhance the resilience and scalability of new ventures in emerging economies.

Nevertheless, the study is not without limitations. The framework remains primarily conceptual and has not yet been subjected to systematic empirical validation, which constrains its generalizability across industries and geographies. The absence of longitudinal data further limits the ability to assess how dynamic capabilities evolve or respond to repeated shocks. Moreover, the model does not explicitly integrate external contextual factors such as regulatory environments, access to capital, or cultural norms, all of which may significantly influence startup trajectories. To address these limitations, future research should adopt longitudinal and multi-country case studies to capture the temporal evolution of dynamic capabilities and their relationship with business model adaptation. Comparative studies across different sectors would also help identify industry-specific contingencies. Additionally, quantitative testing using performance metrics—such as growth rate, customer retention, market entry speed, or investment attraction—would allow for empirical assessment of the model’s predictive validity. Mixed-methods approaches that combine survey data with in-depth case evidence could provide a more holistic view of how dynamic capabilities interact with communication strategies under varying institutional conditions.

From a practical standpoint, the framework offers several implications for startup founders. It underscores the importance of integrating marketing communication into the very fabric of dynamic capabilities—using consumer insights to guide opportunity sensing, designing scalable media strategies for opportunity seizing, and employing transparent stakeholder engagement to support transformation and pivots. For policymakers and incubators, the findings suggest that entrepreneurial capacity-building should extend beyond financial and technical assistance to include training in strategic communication and dynamic capability development. Embedding such training into national startup programs or incubation schemes could help foster more resilient entrepreneurial ecosystems.

In conclusion, while dynamic capabilities are not a universal solution, they constitute essential mechanisms that enable startups to survive and thrive in conditions of uncertainty. When integrated with adaptive marketing communication and agile business modelling, they provide a robust pathway toward sustainable and scalable growth in emerging economies. This study offers an integrated perspective on the role of dynamic capabilities and marketing communication in shaping the growth trajectories of startups operating in volatile and resource-constrained environments. By mapping the dynamic capability processes—sensing, seizing, and transforming—onto key components of the Business Model Canvas (BMC), the study presents a conceptual framework that highlights how startups can strategically adapt their business models in response to environmental turbulence, technological disruption, and shifting consumer expectations.

Empirically, the research contributes to the understanding of how startups in emerging markets utilize marketing communication as a strategic enabler rather than merely a promotional tool. This study also adds theoretical value by illustrating the interdependence between dynamic capabilities and business model innovation, suggesting that adaptability and strategic agility are foundational—not supplementary—to sustained entrepreneurial growth. Economically, the findings offer actionable insights for startup founders, investors, and policymakers seeking to enhance the resilience and scalability of new ventures in emerging economies.

However, the study is not without limitations. The proposed framework remains conceptual and has yet to be tested through rigorous empirical validation. As such, the generalizability of the model across different industries and geographies may be limited. Methodological limitations include the absence of longitudinal data, which restricts the ability to assess how dynamic capabilities evolve or respond to repeated environmental shocks. Moreover, the model does not fully account for external factors such as regulatory environments, access to capital, or cultural norms, all of which could significantly influence startup growth dynamics.

Future research should focus on empirically testing the proposed framework using mixed methods or comparative case studies across diverse national and sectoral contexts. It is also recommended that scholars explore the role of enabling factors such as digital infrastructure, institutional support, and leadership style to further refine the model.

In conclusion, while dynamic capabilities are not a panacea, they are essential strategic mechanisms for startups to survive and thrive in uncertainty. Integrating these capabilities with adaptive marketing communication and agile business modelling provides a robust pathway toward sustainable growth in emerging markets.

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