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Cloud-Native Systems as a Driver of Competitive Advantage in the Digital Economy

Md. Imran Hasan Department of Computer Science & Engineering Faculty of Engineering & Technology Shanto-Mariam University of Creative Technology Dhaka, Bangladesh Email: imranhasan2326@gmail.com ORCID:  https://orcid.org/0009-0009-6356-0236

Prof. Dr Kazi Abdul Mannan Department of Business Administration Faculty of Business Shanto-Mariam University of Creative Technology Dhaka, Bangladesh Email: drkaziabdulmannan@gmail.com ORCID: https://orcid.org/0000-0002-7123-132X

Corresponding author: Md. Imran Hasan: imranhasan2326@gmail.com

J. form. informal sect. 2025, 5(4); https://doi.org/10.64907/xkmf.v5i4.jfis.1

Submission received: 1 October 2025 / Revised: 9 November 2025 / Accepted: 1 December 2025 / Published: 25 December 2025

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Abstract

In the digital economy, firms are increasingly adopting cloud-native systems—architectures designed for cloud environments, which leverage microservices, containers, orchestrators, and elastic infrastructure—to gain agility, scalability, and innovation capacity. This research investigates how cloud-native systems function as a driver of competitive advantage in contemporary digital business contexts. Drawing on resource-based view (RBV) and dynamic capabilities theory, the study develops a theoretical framework linking cloud-native adoption to sustained firm performance via flexibility, speed to market, resilience and ecosystem integration. A qualitative multiple case‐study approach is applied (semi‐structured interviews with senior IT/architecture executives from five digitally-mature firms). Findings reveal three primary mechanisms by which cloud-native systems facilitate a competitive advantage: enabling the rapid reconfiguration of digital services, promoting modular innovation and ecosystem participation, and enhancing operational resilience and cost-effectiveness. The study contributes to the literature by deepening the understanding of technical systems as strategic assets and offers practical insights for managers orchestrating digital transformation. Limitations and future research directions are discussed.

Keywords: cloud-native, competitive advantage, digital economy, dynamic capabilities, resource-based view, microservices, digital transformation.

1. Introduction

The digital economy is characterised by rapid change, heightened competition, networked ecosystems, and continuous innovation. In this environment, firms seek to secure a competitive advantage not only through traditional assets but through digital capabilities and platform infrastructures (Priandito, Ramadan & Kuusk, 2023). Meanwhile, the advent of cloud computing has transformed how IT infrastructure is conceived and deployed. More recently, the concept of cloud-native systems has emerged: systems built to exploit the unique features of cloud environments (containers, microservices, orchestration, APIs, service meshes) (Deng et al., 2023). These systems promise scalability, agility, resilience, and faster time to market.

Despite growing adoption, the question remains: How can cloud-native systems contribute to sustainable competitive advantage in the digital economy? This research addresses this question by developing a theoretical framework grounded in the resource-based view and dynamic capabilities theory, and by conducting a qualitative study of firm practice.

The structure of the paper is as follows: Section 2 presents the theoretical framework and literature review. Section 3 outlines the research methodology. Section 4 presents findings and discussion. Section 5 concludes with implications for theory and practice, limitations and avenues for future research.

2. Theoretical Framework and Literature Review

2.1 Competitive Advantage in the Digital Economy

The concept of competitive advantage has been central to strategic management research. According to Porter (1985), firms achieve advantage when they either deliver superior value or operate at a lower cost than rivals. The resource‐based view (RBV) asserts that firms’ heterogeneous, valuable, rare, inimitable and non-substitutable (VRIN) resources underpin sustained advantage (Barney, 1991). In dynamic digital contexts, however, static resources are insufficient; rather, dynamic capabilities—firms’ abilities to integrate, build, and reconfigure internal and external competences in response to rapidly changing environments—become crucial (Teece, Pisano & Shuen, 1997).

In the digital economy, firms must operate on platforms, ecosystems and networks, responding to digital disruption, leveraging analytics, and orchestrating digital services (Priandito et al., 2023). Thus, digital capabilities—including flexible IT architectures, data infrastructure, agile processes—emerge as strategic resources.

2.2 Cloud-Native Systems as Strategic Resources

Cloud computing has been widely studied as a driver of flexibility, cost efficiency and scalability (Dincă, Dima & Rozsa, 2019; Lawan, Oduoza & Buckley, 2021). More specifically, the cloud-native paradigm emphasises building applications that exploit cloud properties such as continuous delivery, containerisation, microservices, and orchestration (Deng et al., 2023; Vemula, 2024). Cloud-native systems are fundamentally architectural and operational shifts: they allow rapid deployment, elastic scaling, resilience to failure, and interoperability with ecosystems (Venkatesh, 2024).

These characteristics suggest that cloud-native systems may be viewed as strategic resources under the RBV lens. They are potentially valuable (enable new capabilities), rare (not all firms adopt or master them), inimitable (requires architectural, process, cultural changes) and non-substitutable (traditional monolithic systems may not deliver the same agility). Moreover, via dynamic capabilities, cloud-native systems may help firms sense opportunities (e.g., new service markets), seize them (rapid deployment of features) and reconfigure assets (shift modular services) (Teece, 2007).

2.3 Mechanisms by which Cloud-Native Systems May Enable Competitive Advantage

Based on extant literature, three mechanisms emerge:

• Agility and Speed to Market. Cloud-native systems facilitate rapid deployment of services, continuous integration/continuous delivery (CI/CD), and microservice‐based architectures, enabling faster time to market and experimentation (Deng et al., 2023).
• Scalability, Resilience and Operational Efficiency. Containers and orchestration allow elastic resource use, fault tolerance, fault isolation, and resilience—reducing downtime and cost of operations (Mao et al., 2020). This operational edge can become a competitive advantage if rivals cannot match it.
• Ecosystem Participation and Modular Innovation. Cloud-native architectures are modular, API-driven and facilitate integration with external services, third-party platforms and ecosystems. This increases openness to innovation, network effects and platform strategies (Venkatesh, 2024).

2.4 Proposed Theoretical Framework

Accordingly, this study proposes a framework in which Cloud-Native Systems (as a resource/infrastructure) feed into Dynamic Capabilities (sensing, seizing, reconfiguring), which then result in Competitive Advantage (differentiation, cost leadership, innovation) in the digital economy. Moderating factors such as organisational culture, IT governance and ecosystem readiness are also included.

Figure 1. Theoretical Framework
Cloud-Native Systems → Dynamic Capabilities → Competitive Advantage
(Moderators: Culture, Governance, Ecosystem Readiness)

3. Research Methodology

3.1 Research Design

This study uses a qualitative multiple‐case study design to explore how firms deploy cloud-native systems to gain a competitive advantage. Qualitative methods are appropriate when phenomena are complex, contextualised, and internal processes are of interest (Yin, 2018). The cases enable rich, contextualised insights and the generation of theoretically meaningful constructs.

3.2 Case Selection

Five firms were selected purposively based on the following criteria: digitally mature firms that have adopted cloud-native architectures; across different industries (e.g., financial services, retail, manufacturing); willingness to participate and share strategic insights. The sample ensures variation in context while focusing on the adoption of cloud-native systems as a strategic initiative.

3.3 Data Collection

Semi‐structured interviews were conducted with senior IT/architecture executives (e.g., Chief Cloud Architect, VP Digital Transformation) in each firm. Each interview lasted approx. 60–90 minutes and followed an interview guide covering topics such as: motivations for cloud-native adoption; deployment processes; impact on agility, cost, innovation; mechanisms of competitive advantage; barriers and enablers. Additional data were collected through document analysis (e.g., architecture diagrams, transformation road‐maps) and, where possible, observational data.

3.4 Data Analysis

Data were transcribed and coded using thematic analysis (Braun & Clarke, 2006). The coding process included: initial open coding to identify conceptual categories; axial coding to link categories; selective coding to integrate these into higher‐level constructs aligned with the theoretical framework. Cross‐case analysis was performed to identify common patterns and divergences. To enhance validity, member-checking was performed (i.e., interviewees verified key findings), and triangulation was applied via multiple data sources.

3.5 Ethical Considerations

The study adhered to ethical research practices: informed consent was obtained from all participants; anonymity and confidentiality were ensured (firms and individuals are anonymised); data are stored securely. Sensitive strategic information was handled with care.

3.6 Limitations

As a qualitative study, the findings are not statistically generalisable. The firms selected are digitally mature, which may bias findings toward successful adopters. Future research may complement this with quantitative studies across broader samples.

4. Findings and Discussion

4.1 Cloud-Native Systems in Practice

All five firms reported adoption of cloud-native architectures incorporating microservices, containers (e.g., Kubernetes), continuous delivery pipelines, and cloud automation. One interviewee noted:

“By breaking our monolith into microservices and deploying on containers that scale automatically, we can launch features in days rather than months.”

This confirms the agility and speed-to-market mechanism.

4.2 Mechanism 1: Agility & Speed to Market

Interview data reveal that cloud-native systems enabled firms to respond rapidly to market changes, launch new digital services, experiment with features, and retire under-performing offerings quickly. The sense/seize dimension of dynamic capabilities is evident. For example, one firm described launching a new mobile-first service within three weeks, leveraging CI/CD and containerised microservices. This agility is a clear competitive differentiator in fast-moving digital markets.

4.3 Mechanism 2: Scalability, Resilience & Operational Efficiency

Firms described how container orchestration (e.g., Kubernetes) enables elastic scaling during peak demand (e.g., retail sales events) and cost control during off-peak periods. One architecture lead explained:

“We no longer over-provision for peak; containers spin up and down; we pay only for usage and guarantee availability.”

This supports cost-leadership and resilience as competitive advantages. The RBV lens suggests this infrastructure is difficult to replicate in a mature form.

4.4 Mechanism 3: Ecosystem Participation & Modular Innovation

Another key finding: by exposing modular services via APIs and integrating with partner platforms, firms could participate in digital ecosystems and co-create value. For instance, one financial services firm offered an API platform enabling fintechs to build on its services; the cloud-native architecture facilitated this. This modularity and openness enabled network effects and plugged innovation external to the firm—a powerful source of differentiation.

4.5 Moderating Factors: Organisational Culture, Governance & Ecosystem Readiness

While cloud-native systems offer potential, several moderating factors emerged. Strong leadership commitment, agile culture, DevOps competencies and governance mechanisms were essential. One firm failed to realise expected benefits due to a lack of container skills and rigid IT governance. Similarly, ecosystem readiness—partner APIs, standardised interfaces and regulatory compliance—affected the ability to exploit modular innovation.

4.6 Synthesis and Theoretical Contribution

The findings confirm the proposed framework: cloud-native systems act as strategic resources enabling dynamic capabilities, which in turn support competitive advantage. Table 1 summarises the linkages.

Table 1: Summary of linkages between cloud‐native systems, dynamic capabilities and competitive advantage

Cloud-Native System Feature	Dynamic Capability	Competitive Advantage Outcome
Rapid deployment, CI/CD pipelines	Seizing opportunities	Speed to market, first-mover edge
Elastic containers, orchestration	Reconfiguring operations	Cost efficiency, resilience
Modular microservices + API	Sensing new ecosystems	Ecosystem innovation, differentiation

This study contributes to strategy and information systems literatures by explicitly linking cloud-native architectural decisions with strategic outcomes of competitive advantage. While prior literature has examined cloud computing broadly (Dincă et al., 2019; Lawan et al., 2021), this research focuses on the newer paradigm of cloud-native systems and their role in digital competition.

4.7 Practical Implications

For practitioners, the study suggests that cloud-native adoption should be seen not merely as a technical initiative but as a strategic transformation. Key recommendations include: align cloud-native architecture with business strategy, invest in DevOps and microservices competencies, engage ecosystem partners via APIs, and embed agile culture and governance to realise benefits.

5. Conclusion

In the fast-changing digital economy, firms require architectures and capabilities that enable speed, innovation, resilience and ecosystem integration. This study shows that cloud-native systems can serve as a major driver of competitive advantage by functioning as strategic resources that enable dynamic capabilities. Through qualitative case-based analysis, we identified three mechanisms—agility and speed to market, scalability/resilience/operational efficiency, and ecosystem participation and modular innovation—through which cloud-native systems influence competitive outcomes. Moderating factors such as culture, governance and ecosystem readiness are key to whether such potential is realised.

Theoretical contributions include deepening the application of RBV and dynamic capabilities theory to digital architectural resources and demonstrating the strategic value of cloud-native systems. Practically, the findings offer actionable guidance to digital leaders.

Limitations & future research. As a qualitative study from five firms, generalisability is limited. Future work might apply mixed-methods approaches, quantitative surveys of broader samples, and longitudinal studies to assess long-term competitive outcomes. Additionally, research could examine industry-specific dynamics (e.g., regulated sectors) or emerging technologies (e.g., edge computing, serverless) in the cloud-native context.

References

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Dincă, V. M., Dima, A. M., & Rozsa, Z. (2019). Determinants of cloud computing adoption by Romanian SMEs in the digital economy. Journal of Business Economics and Management, 20(4), 798–820. https://doi.org/10.3846/jbem.2019.9856

Deng, S., Zhao, H., Huang, B., Zhang, C., Chen, F., Deng, Y., … Zomaya, A. Y. (2023). Cloud-Native Computing: A Survey from the Perspective of Services. arXiv. https://arxiv.org/abs/2306.14402 arXiv

Lawan, M. M., Oduoza, C., & Buckley, K. (2021). A systematic review of cloud computing adoption by organisations. International Journal of Industrial and Manufacturing Systems Engineering, 6(3), 39–48. https://doi.org/10.11648/j.ijimse.20210603.11

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Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533.

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