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MOC is most valuable when firms can process vast market data with speed and
precision. AIBDA amplifies MOC by using AI algorithms to identify emerging trends,
forecast demand, and detect competitor shifts in real time (Huang et al., 2018; Mneney et
al., 2016). Rather than relying on intuition, AIBDA-equipped firms transform market
intelligence into rapid, data-driven strategic responses. This technological synergy
reduces uncertainty and maximizes the performance gains derived from market-oriented
behaviors (Wamba et al., 2017; Bouwman et al., 2019).
H2a: AIBDA application positively moderates the relationship between MOC and EP.
AIBDA as a moderator for CRMC and EP:
The application of big data analytics facilitates real-time responsiveness and
information sharing, which are critical for international buyer satisfaction (Mneney et al.,
2016). Through AI-driven CRM systems, firms can segment export customers with high
accuracy, predict switching intentions, and personalize services (Davenport et al., 2014;
Huang et al., 2018). High levels of AIBDA thus empower firms to leverage their
relationship management capabilities more effectively, converting customer bonds into
superior export results.
H2b: AIBDA application positively moderates the relationship between CRMC and EP.
AIBDA as a moderator for BMC and EP:
The effectiveness of Brand Management Capability (BMC) hinges on accurate
insights and the ability to adapt branding to global shifts. AIBDA enhances BMC by
enabling firms to monitor online sentiment, analyze brand perception, and optimize
digital campaigns in real time (Huang et al., 2018; Davenport et al., 2014). Consequently,
firms utilizing AIBDA are better positioned to translate their brand equity into enhanced
credibility and trust within international markets.
H2c: AIBDA application positively moderates the relationship between BMC and EP.
AIBDA as a moderator for NPDC and EP:
Exporting new products carries significant risk due to market heterogeneity. AIBDA
mitigates these risks by allowing firms to evaluate product-market fit more accurately
through predictive modeling and demand forecasting. By analyzing customer preferences
and testing concepts via data-driven tools, AIBDA reduces the uncertainty and costs
associated with innovation. This ensures that NPDC is more effectively translated into
successful export outcomes.
H2d: AIBDA application positively moderates the relationship between NPDC and EP.

Figure 1. Research model
Source: Synthesized by authors

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