Consumer engagement on Facebook: modelling its antecedents and consequence

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Type of the article: Research Article

Abstract
The rapid growth of social media has transformed consumer-brand interactions, making the study of attachment and consumer engagement highly relevant for emerging markets such as the Philippines. This research aims to examine how higher-order constructs of attachment (identity-based attachment and bonding-based attachment) influence consumer engagement with local brands on Facebook and, subsequently, how this engagement shapes purchase intention. To achieve this, a structured online survey was conducted among 386 Filipino Facebook users who actively followed at least one local brand page. Data collection took place between August and October 2024, employing purposive sampling to ensure the representativeness of engaged local brand consumers. The survey method was chosen to capture consumers’ psychological attachment and behavioural responses within an authentic digital setting. Using Structural Equation Modelling (SEM), the findings reveal that bonding-based attachment exerts the strongest influence on consumer engagement (β = 0.56, p < 0.01), while identity-based attachment also demonstrates a significant but comparatively weaker effect (β = 0.34, p < 0.01). Both attachment dimensions indirectly enhance purchase intention through consumer engagement (β = 0.302 for bonding-based attachment, and β = 0.186 for identity-based attachment), with consumer engagement itself emerging as a robust predictor of purchase intention (β = 0.542, p < 0.001). Demographic characteristics such as age, gender, and income showed no significant moderating effects on the consumer engagement-purchase intention relationship. These results provide empirical support for the mediating role of consumer engagement in attachment-intention pathways, extending attachment theory into social media marketing and offering practical insights for brand managers in emerging economies.

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    • Figure 1. Proposed conceptual framework
    • Figure 2. Minimum sample size required using inverse square root and gamma-exponential methods
    • Figure 3. Second stage of the two-stage approach of PLS SEM model
    • Figure 4. The two-stage approach of PLS-SEM model
    • Figure 5. Structural model with standardized path loading
    • Table 1. Profile of respondents
    • Table 2. Quality criteria of the reflective first-order constructs
    • Table 3. Discriminant validity of the first-order constructs
    • Table 4. Collinearity test for indicators of the formative second order constructs
    • Table 5. Path analysis and hypothesis testing
    • Conceptualization
      Wilmark Ramos
    • Data curation
      Wilmark Ramos
    • Formal Analysis
      Wilmark Ramos
    • Investigation
      Wilmark Ramos
    • Methodology
      Wilmark Ramos
    • Project administration
      Wilmark Ramos
    • Resources
      Wilmark Ramos
    • Writing – original draft
      Wilmark Ramos
    • Writing – review & editing
      Wilmark Ramos
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