Research: Constructing Algorithmic Commercial Legitimacy in the Creator Economy: A Cyberphenomenological Theory of Human–Algorithm Interaction
The creator economy has transformed digital commerce by positioning creators as entrepreneurial actors operating within algorithm-driven platform ecosystems. Existing studies primarily explain influencer credibility, consumer trust, and social commerce from consumer-centric perspectives, providing limited understanding of how creators construct commercial legitimacy through their lived experiences. This study addresses this gap by exploring the experiences of TikTok affiliate creators using a qualitative cyberphenomenological approach. Data were collected through in-depth semi-structured interviews and digital observations and analyzed using iterative coding, thematic development, and theory triangulation. The findings identify four interconnected dimensions of commercial legitimacy: digital identity construction, algorithmic visibility negotiation, marketplace trust curation, and adaptive commercial learning. These dimensions interact dynamically, demonstrating that creators continuously negotiate legitimacy through interactions with platform algorithms, audiences, and marketplace actors rather than relying solely on persuasive communication or consumer evaluation. Based on these findings, the study proposes Algorithmic Commercial Legitimacy as a novel theoretical construct that extends Source Credibility Theory, Signaling Theory, Social Commerce Theory, and Creator Economy literature. The study contributes by offering a creator-centered explanation of legitimacy construction and advancing cyberphenomenology as an interpretive approach for understanding human–algorithm interaction in digital commerce.