Online marketing campaigns’ aesthetics: Measuring the direct effect on customers’ decision-making

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This research aims to investigate the direct and formal effect of visual aesthetics on customers’ willingness to participate in an online marketing campaign, given that visual aesthetics is considered a salient design characteristic that customers tend to refer to when expressing their experience with the online retailer environment. This research study incorporates the Theory of Reasoned Action (TRA) and the Technology Acceptance Model (TAM) to propose and estimate this direct effect through structural aesthetics TAM model. In order to validate the proposed model, an online survey with interactive experience was constructed utilizing an open-source platform and was primarily sent to scholars specializing in HCI, informatics, user experience, and digital marketing research in the United Kingdom. The data were obtained from 360 participants, and Partial Least Squares (PLS) path modeling using SmartPLS 4 was employed to evaluate the proposed model. The empirical evaluation demonstrated and confirmed the authenticity and novelty of significant direct and formal effects of customers’ perceived visual aesthetics on their willingness to participate in an online marketing campaign (β = 0.462, t = 10.847, p < 0.001), and their usage attitude (β = 0.789, t = 39.622, p < 0.001). These findings highlight the importance of visual aesthetics in online marketing campaign design, suggesting that concise, well-organized, and visually appealing user interfaces is more likely to engage customers than a complex, cluttered one.

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    • Figure 1. Research model: aesthetics TAM-based model
    • Figure 2. Validated aesthetics TAM-based model
    • Table 1. Measured constructs and related items
    • Table 2. Participants’ demographics
    • Table 3. Construct validity and reliability of the aesthetics TAM-based model
    • Table 4. Discriminate validity (HTMT) for constructs
    • Table 5. Summary of the aesthetics TAM-based model related hypotheses
    • Conceptualization
      Abdullah AlSokkar, Mahmoud Alghizzawi, Dalia Al Eisawi
    • Formal Analysis
      Abdullah AlSokkar, Mahmoud Alghizzawi, Dalia Al Eisawi
    • Methodology
      Abdullah AlSokkar, Jassim Ahmad Al-Gasawneh
    • Supervision
      Abdullah AlSokkar, Mahmoud Alghizzawi
    • Validation
      Abdullah AlSokkar, Mohammed Otair, Mahmoud Alghizzawi, Deemah Alarabiat
    • Writing – original draft
      Abdullah AlSokkar, Jassim Ahmad Al-Gasawneh
    • Data curation
      Jassim Ahmad Al-Gasawneh, Deemah Alarabiat
    • Investigation
      Jassim Ahmad Al-Gasawneh, Dalia Al Eisawi
    • Resources
      Mohammed Otair
    • Software
      Mohammed Otair, Dalia Al Eisawi
    • Writing – review & editing
      Mohammed Otair, Mahmoud Alghizzawi, Deemah Alarabiat