Page 370 - ISC PROCEEDINGS 21.4

emphasize restructuring and innovating those strategies to fit the environment (Adner &
Helfat, 2003). As higher-order capabilities, DMCs require intense cross-functional
coordination between marketing, R&D, and sales to achieve sustainable value creation
(Barrales-Molina et al., 2014; Gliga & Evers, 2023; Fang & Zou, 2009). This study adopts
the four-dimensional framework by Hoque et al. (2020) to operationalize DMCs:
Market Orientation Capability (MOC): The capacity to inter-functionally gather and
respond to customer and competitor intelligence (Narver & Slater, 1990).
Customer Relationship Management Capability (CRMC): Proficiency in leveraging
data to cultivate loyalty and enhance customer value (Boulding et al., 2005).
Brand Management Capability (BMC): The ability to build, position, and augment
core brand equity (Cadogan, 2009).
New Product Development Capability (NPDC): The aptitude for innovating products
to meet evolving market demands (Hoque et al., 2020).
These dimensions represent the flexible deployment of resources necessary for
maintaining a competitive edge in dynamic global environments.
2.1.3. Export performance (EP)
In a globalized economy, exporting is both a strategic expansion tool and a primary
driver of corporate growth and international competitiveness (Aghion et al., 2018;
Bugamelli et al., 2018). From the Dynamic Capabilities View (DCV), superior Export
Performance (EP) signals a firm's ability to effectively deploy international marketing
resources and adapt to volatile environments (Ngo-Thi-Ngoc & Nguyen-Viet, 2021; Safari
& Saleh, 2020). DMCs, in particular, enable firms to seize opportunities and mobilize
resources to achieve success abroad.
Given that EP is a multidimensional concept (Chen et al., 2016), this study utilizes
the widely validated EXPERF scale (Zou et al., 1998; Ramon-Jeronimo et al., 2019), which
remains highly relevant in the era of AIBDA (Yu et al., 2025). The scale evaluates
performance across three core dimensions:
Financial Performance: Quantitative metrics including sales revenue, net profit, and
foreign market share.
Strategic Performance: Outcomes related to market penetration and the
consolidation of competitive positions.
Perceptual Performance: Managerial satisfaction with export results relative to
internal objectives or competitors.
2.1.4. Application of AI and big data analytics (AIBDA)
Artificial Intelligence (AI) and Big Data Analytics (AIBDA) have emerged as a
transformative paradigm for value creation and operational efficiency. AI encompasses
systems capable of mimicking human intelligence—such as reasoning, learning, and
decision-making—through techniques like Machine Learning, Natural Language
Processing, and Computer Vision (Chin et al., 2024; Russell et al., 2017; Huang & Rust,
2018). These tools allow firms to automate complex tasks and extract precise insights
from vast datasets.
Complementing this, Big Data Analytics focuses on processing massive datasets
characterized by high volume, velocity, variety, and veracity (Gandomi & Haider, 2015) to
uncover hidden patterns and market trends. AI and Big Data share a symbiotic
relationship: Big Data provides the essential input for AI models, while AI offers the
analytical power to overcome traditional data limitations (Zong et al., 2025). Collectively,
AIBDA enables unprecedented predictive capabilities. In this study, AIBDA is viewed as a

369