Exploring the dynamics of consumer engagement in social media influencer marketing: from the self-determination theory perspective

The study addresses diminishing effectiveness of traditional online ads and the rise of influencer-endorsed advertising as a key strategy on social media. Given that influencers can sway purchasing decisions largely through consumer engagement behaviors, the research explores how to enhance engagement by examining stimulating factors and the underlying psychological mechanisms. The purpose is to understand how influencer advertising impacts consumer experience and engagement, providing both theoretical insights and practical guidance for advertisers.

Stimulus-Organism-Response (S-O-R) model: Originating from behavioral psychology, the S-O-R framework posits that external stimuli influence behavior through internal cognitive and affective states (organism). In consumer psychology and social media studies, it is used to model how stimuli affect internal cognitions that mediate behavioral responses. This study integrates S-O-R with motivation theory to examine consumer engagement in influencer advertising. Self-determination theory (SDT): SDT explains behavior through satisfaction of autonomy, competence, and relatedness needs. In online consumer contexts, these are operationalized as self-disclosure willingness (autonomy), innovativeness (competence), and trust (relatedness). Prior work shows SDT’s relevance to online knowledge sharing, eWOM, and engagement behaviors. Building on these, the study constructs the organism component with self-disclosure willingness, innovativeness, and information trust, and theorizes their effects on engagement (consumption, contribution, creation). The review develops hypotheses linking internal factors to engagement and external stimuli—parasocial identification and source credibility (influencer factors), informative value and ad targeting accuracy (information factors), and subjective norms (social factors)—to the internal factors and downstream engagement, including mediation pathways.

Design and framework: An exploratory S-O-R model grounded in self-determination theory and the theory of planned behavior was specified, with external stimuli (parasocial identification, source credibility, informative value, ad targeting accuracy, subjective norms) influencing organism-level cognitions (self-disclosure willingness, innovativeness, information trust) that drive consumer engagement behaviors (content consumption, contribution, creation). Participants and procedures: An online survey was administered via Wenjuanxing. Recruitment occurred on WeChat, Douyin, Weibo, etc. Inclusion and data-quality criteria: (1) respondents must follow influencers on social media; (2) two attention checks; (3) completion time > 1 minute; (4) no straight-lining across items. Of 600 collected questionnaires, 522 were valid (87.0% effective rate). Measures: Established multi-item Likert (7-point) scales adapted to the influencer context. Parasocial identification (Schramm & Hartmann, 2008); source credibility (Cheung et al., 2009; Luo & Yuan, 2019; 4 items); informative value (Voss et al., 2003; 4 items); ad targeting accuracy (Qiu & Chen, 2018; 3 items); subjective norm (Ajzen, 2002; 3 items); self-disclosure willingness (Chu & Kim, 2011; 3 items); innovativeness (Sun et al., 2006; 4 items); information trust (Chu & Cho, 2011; 3 items); engagement—content consumption, contribution, creation (Buhalis et al., 2020; total 8 items). A 30-person pretest assessed clarity and relevance. Data analysis: Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS was employed due to the exploratory model. Reliability and validity were assessed: after removing items with loadings < 0.5, all loadings ranged 0.730–0.964; Cronbach’s alpha 0.805–0.924; Composite Reliability > 0.7; AVE > 0.5; VIF < 10. Discriminant validity met Fornell–Larcker criterion. Common method bias was assessed via single-factor test (first factor 29.71% < 40%). Model fit and predictive relevance: R2 values exceeded 0.1; Stone–Geisser Q2 > 0; CFA indices: χ2/df=2.528, RMSEA=0.059, SRMR=0.055, CFI=0.953, TLI=0.942, NFI=0.923. Hypotheses were tested via bootstrapping (500 resamples).

- Psychological motivators and engagement: Self-disclosure willingness (SW), innovativeness (IN), and information trust (IT) positively predict engagement, with innovativeness exerting the strongest effects on higher-level engagement (contribution and creation). Notable paths include: IT→content consumption β=0.565, p<0.001; SW→content creation β=0.366, p<0.001; IN→content creation β=0.462, p<0.001; IT→content contribution β=0.165, p=0.001; IT→content creation β=0.192, p<0.001. Innovativeness did not significantly predict content consumption in some tests. - External stimuli and organism: Parasocial identification (PI) positively predicts self-disclosure willingness (PI→SW β=0.521, p<0.001) and fosters information trust via mediation pathways. Source credibility (SC) significantly increases information trust (SC→IT β=0.230, p<0.001) but showed limited or non-significant direct effects on self-disclosure willingness. Informative value (IV) and ad targeting accuracy (ATA) both elevate information trust (IV→IT β=0.227, p<0.001; ATA→IT significant), with innovativeness also linked to information trust. Subjective norm (SN) positively influences self-disclosure willingness (SN→SW β=0.326, p<0.001) and information trust (SN→IT β=0.208, p<0.001). - Mediation: Multiple mediation effects were supported, e.g., PI→SW→consumption (β=0.077, p=0.005), PI→SW→creation (β=0.124, p<0.001), IV/ATA→IT→engagement paths valid for various engagement outcomes. - Measurement and model adequacy: Factor loadings 0.730–0.964; Cronbach’s α 0.805–0.924; AVE > 0.5; CR > 0.7; CFI=0.953; TLI=0.942; RMSEA=0.059; SRMR=0.055; no critical common method bias. - Strategic implications from findings: Influencers effectively generate initial traffic (consumption) but have limited direct impact on deeper engagement; content quality/informational value is central to driving contribution and creation; social factors (subjective norms) also play a significant role.

The study clarifies how external stimuli in influencer marketing translate into consumer engagement via SDT-based internal processes. The results show that while influencer-related stimuli (parasocial identification and source credibility) can spark initial attention and trust, higher-order engagement relies more on consumers’ internal motivations—especially innovativeness—triggered by informative content. Trust is crucial for consumption (viewing/attending to content), whereas innovativeness is pivotal for contribution and creation, addressing the research question of what mechanisms elevate engagement along its continuum. These insights bridge influencer marketing and engagement literature, highlighting the differential roles of stimuli and organism factors across engagement levels, and stress the importance of content value and social influence in enhancing advertising effectiveness.

The study validates the applicability of self-determination theory in influencer advertising effectiveness research and extends engagement-focused advertising research. Main conclusions: (1) Innovativeness is the key driver for higher-level engagement (contribution and especially creation). (2) Influencers’ primary role is to attract initial traffic and reduce avoidance, with limited direct influence on deeper engagement. (3) Advertising information factors—particularly informative value—are critical; content remains king for driving contribution and creation. (4) Social influences (subjective norms) and trust mechanisms meaningfully shape engagement, offering strategic guidance: invest in high-value content, foster innovativeness and creativity among consumers, and leverage social proof while not overestimating influencer effects on deeper engagement.

- Scope of stimuli: The general model includes influencer, information, and social factors but does not exhaust all possible determinants; future work should add and test additional variables. - Platform effects: Engagement processes and effectiveness may differ across social media platforms; comparative, cross-platform studies are recommended. - Interactions and complex effects: The study emphasizes direct and mediated effects; potential interactions among stimuli and organism variables warrant further investigation.