Digital coupons and Gen Z: An application of technology acceptance model with coupon proneness as a moderator

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This study aimed to comprehend the perceptions and intentions of Generation Z consumers in India regarding the utilization of digital coupons, adopting the framework of the technology acceptance model. Through purposive sampling, 386 participants from Generation Z were selected to offer diverse perspectives, reflecting the significant influence of demographics on contemporary consumer behavior. An online survey was conducted across India, utilizing popular social networking applications, such as WhatsApp, LinkedIn, and Facebook, to distribute the online questionnaire as these platforms have widespread usage and accessibility among the target demographic. Structural equation modeling (SEM) was used to examine the relationships between the constructs. The study revealed that perceived ease of use had no significant impact on the attitudes toward digital coupons (p > 0.05). However, a strong positive relationship was observed between perceived usefulness and ease of use (β = 0.542, p ≤ 0.05). Similarly, perceived usefulness positively influenced attitudes toward digital coupons (β = 0.484, p ≤ 0.05), as did attitudes toward usage intention (β = 0.746, p ≤ 0.05). The relationships between attitude and perceived ease of use (β = –0.093, p ≤ 0.05) and attitude and usage intention (β = –0.124, p ≤ 0.05) were moderated by digital coupon proneness. Insights derived from this study hold substantial relevance for marketers aiming to effectively engage Generation Z through digital couponing strategies.

Acknowledgment
The authors are thankful to their respective universities, heads of departments, and others who have supported and contributed to the effective conduct of this study.

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    • Figure 1. Conceptual framework
    • Figure 2. Bootstrapping analysis
    • Table 1. Measurement items
    • Table 2. Demographic profile
    • Table 3. Summary of the measurement model
    • Table 4. Fornell-Larcker criterion
    • Table 5. Explanatory power of the model
    • Table 6. Path analysis and structural model assessment
    • Conceptualization
      Neha Pandey, Nimish Gupta, Sanjay Rastogi, Rashika Rajan Singh, Manish Mishra
    • Data curation
      Neha Pandey, Manish Mishra
    • Formal Analysis
      Neha Pandey
    • Investigation
      Neha Pandey, Sanjay Rastogi, Manish Mishra
    • Methodology
      Neha Pandey, Nimish Gupta
    • Software
      Neha Pandey, Rashika Rajan Singh, Manish Mishra
    • Writing – original draft
      Neha Pandey
    • Writing – review & editing
      Neha Pandey
    • Supervision
      Nimish Gupta, Sanjay Rastogi, Rashika Rajan Singh
    • Validation
      Nimish Gupta, Sanjay Rastogi, Rashika Rajan Singh
    • Visualization
      Sanjay Rastogi