This paper aims to study how combinations of dimensions in experiential messaging within brand-generated content (BGC) can drive social media engagement behaviors (SMEBs). It adopts a comprehensive approach to experiential messaging, exploring interactions among these dimensions to create effective combinations. The study analyzes a dataset of 1,037 Facebook posts from a tourism resort operator, applying fuzzy-set qualitative comparative analysis (fsQCA). The results reveal that no single experiential dimension is sufficient to drive SMEBs. Instead, three combinations emerge: (1) interpersonal sensitivity-combining sensory and relational messages; (2) passionate soul-integrating sensory, affective, and relational messages; and (3) mindful heart-blending cognitive, sensory, and affective messages. This study advances social media marketing research by demonstrating that experiential messaging should be analyzed holistically. By applying complexity theory and fsQCA, it enhances the understanding of how different dimensions interact to enhance SMEBs, offering actionable insights for both scholars and managers.
This bibliometric review synthesizes the literature in the burgeoning field of artificial intelligence (AI) in marketing. Analyzing 1,878 research publications from the Scopus database, we map the intellectual structure and evolution of this domain. Our analysis identifies the foundational works, leading authors, and key thematic clusters, showing how AI technologies are integrated into marketing strategies and their subsequent impact on performance. The review advances the field by offering a qualitative synthesis that distills core theoretical paradigms and empirical insights on AI applications in business marketing. Building on this analysis, we determine critical research gaps and propose future research directions, presenting a structured framework to guide subsequent inquiries in AI-driven marketing.
