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In summary, these findings support the hypothesis that AIBDA acts as a vital
moderator, primarily amplifying information-driven capabilities (MOC and BMC) to drive
export success.
4. Contributions and limitations
4.1. Theoretical contributions
This study advances international marketing and strategic management literature
through two primary contributions. First, it extends the Dynamic Capabilities View (DCV)
within the Vietnamese SME context, demonstrating that dynamic marketing capabilities
(DMCs) do not influence export performance (EP) uniformly. The findings reveal that
market sensing and product adaptation (MOC and NPDC) are far more critical for export
success than relational or branding capabilities (CRMC and BMC). Second, the research
refines the DCV by identifying AIBDA as a moderating mechanism rather than a mere
direct performance driver. Crucially, digital technologies selectively amplify capabilities
linked to market intelligence and brand adaptation, providing a more nuanced
understanding of how technology interacts with organizational processes.
4.2. Practical contributions
For Vietnamese SME managers, these findings offer a strategic roadmap for digital
transformation. Investments should be prioritized toward AIBDA tools that strengthen
market orientation, such as real-time market scanning, demand forecasting, and
competitor analysis. These applications are more likely to yield immediate export gains
than broad, unfocused digitalization. Additionally, firms should utilize AI-driven sentiment
analysis and personalized communication to bridge the gap between brand management
and export outcomes. However, the non-significant moderation for CRMC and NPDC
serves as a cautionary note: managers must precisely match specific AIBDA tools to the
capability areas where they generate the highest value, rather than assuming AI adoption
is a universal remedy.
4.3. Limitations and future research
Despite its insights, this study has limitations. The focus on Vietnamese SMEs may
restrict the generalizability of findings to larger firms or different geographic contexts.
Theoretically, treating DMCs as independent variables may overlook complex internal
synergies, and the exclusion of qualitative factors—such as corporate culture and
leadership—may omit critical organizational context.
To address these gaps, future research should:
Expand the Sample Scope: Survey a broader range of export sectors, larger
enterprises, and multiple countries to enhance generalizability.
Explore DMC Interdependencies: Investigate how various dynamic marketing
capabilities mutually reinforce each other to collectively drive export performance.
Integrate Qualitative Factors: Incorporate variables like organizational culture and
leadership capabilities, while exploring complex moderators (e.g., national culture) to
provide a more holistic perspective on global competitiveness.

References
[1]. Abrokwah-Larbi, K., & Awuku-Larbi, Y. (2023). The impact of artificial
intelligence in marketing on the performance of business organizations: Evidence from
SMEs in an emerging economy. Journal of Entrepreneurship in Emerging Economies.
https://doi.org/10.1108/JEEE-07-2022-0207

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