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2. Literature review
2.1. Digital marketing innovation
Digital marketing innovation has increasingly been driven by the integration of big
data analytics and artificial intelligence (AI) technologies into marketing strategy and
operational processes. Big data–driven marketing refers to the use of large-scale, real-
time data generated from digital platforms, social media interactions, and online
transaction systems to support market segmentation, personalized communication, and
performance optimization (Wedel & Kannan, 2016). In data-rich environments, firms are
able to identify hidden customer patterns, predict purchasing behavior, and improve
targeting precision, thereby enhancing marketing effectiveness and customer value
creation.
The strategic role of big data in marketing has also been highlighted in studies on
customer analytics and digital transformation, which suggest that data utilization
capabilities can significantly influence firm innovation performance and competitive
positioning (Verhoef et al., 2021). Moreover, the emergence of data-driven business
models has encouraged firms to shift from traditional promotional strategies toward
predictive and adaptive marketing approaches supported by real-time analytics (Erevelles,
Fukawa, & Swayne, 2016).
Building upon big data capabilities, artificial intelligence technologies represent a
more advanced stage of digital marketing innovation. AI-enabled marketing systems
incorporate machine learning algorithms, recommendation engines, and automated
decision-support tools that enhance campaign efficiency and customer experience
management (Huang & Rust, 2021). Such intelligent marketing applications enable firms
to deliver personalized content, optimize digital advertising placement, and forecast
consumer demand with greater accuracy. Recent research further indicates that AI
adoption can transform marketing roles and decision-making processes by facilitating
human–machine collaboration and data-driven strategic planning (Davenport, Guha,
Grewal, & Bressgott, 2020).
Overall, the integration of big data analytics and AI technologies has accelerated the
transition from mass marketing toward intelligent, ecosystem-oriented marketing
innovation. This technological evolution supports the development of adaptive marketing
capabilities that are essential for firms operating in platform-mediated digital economies.
2.2. SMEs on E-commerce platforms
The participation of small and medium-sized enterprises (SMEs) in e-commerce
platforms has become a significant driver of digital market expansion and entrepreneurial
innovation in the digital economy. Digital platforms provide SMEs with access to broader
customer bases, integrated logistics and payment infrastructures, and data-driven
marketing tools that facilitate market entry and business scalability (Parker, Van Alstyne,
& Choudary, 2016). In this context, platform-based marketing enables SMEs to overcome
traditional barriers related to geographic constraints, limited distribution channels, and
high promotional costs.
Digital transformation plays a critical role in shaping SMEs’ ability to leverage e-
commerce-based marketing opportunities. From a dynamic capability perspective, SMEs
must continuously develop digital competencies, integrate technological resources, and
redesign marketing processes to adapt to evolving platform ecosystems and customer
expectations (Teece, 2018). Digitalization allows SMEs to implement targeted advertising
strategies, utilize platform analytics dashboards, and engage customers through

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