Stock market literacy and investment motivations: Tri-layer market analysis of stock market participation

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Bridging the gap between stock market literacy and active participation is the ultimate objective for institutions and policymakers globally, due to its ability to promote inclusive economic growth. In light of this, the study intended to assess the impact of intrinsic and extrinsic motivation on stock market literacy leading to participation. Further, an attempt was made to analyze the intervening role of investment decision and the moderating role of Tri-Layer Market Analysis. With the descriptive design, a survey questionnaire was used to gather data for this investigation, collecting responses from 376 commerce and management students across government, private, and deemed universities between June and July 2024 from the region of Karnataka, India. Following the data collection, statistical techniques, such as regression analysis, one-way Analysis of Variance, and structural equation modelling, were applied to evaluate intrinsic and extrinsic motivation’s direct and indirect impacts on students’ stock market participation. As per the results, the Intrinsic (β =.361, t = 8.416, p = 0.000) and External Motivations (β =.422, t = 9.816, p = 0.000) substantially impact stock market literacy that ultimately impacts investment decision making (β = .450, t = 9.761, p = 0.000) and stock market participation (β =.207, t = 4.495, p = 0.000). The results also validate the intervening role of investment decision in the relationship between stock market literacy and stock market participation (indirect effect: .131).

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    • Figure 1. Conceptual model
    • Figure 2. Tested structural model with path estimates
    • Table 1. Demographic characteristics of respondents
    • Table 2. Discriminant validity assessment (Fornell & Larcker criterion)
    • Table 3. Differences across technical, sentiment, and fundamental analyses
    • Table 4. Results of direct and mediation effects
    • Table 5. Moderating effects of tri-layer market analysis
    • Table 6. Summary of path estimates
    • Table A1. Factor loadings, composite reliability, and average variance extracted depicting reliability and validity of the instrument
    • Conceptualization
      Shakira Irfana, Mohammad Nihal, S. M. Riha Parvin, Madhura K.
    • Data curation
      Shakira Irfana, Mohammad Nihal, S. M. Riha Parvin, Niyaz Panakaje, Niha Sheikh, Madhura K., Mahammad Shahid
    • Methodology
      Shakira Irfana, S. M. Riha Parvin
    • Project administration
      Shakira Irfana, Niyaz Panakaje
    • Supervision
      Shakira Irfana, S. M. Riha Parvin, Niyaz Panakaje, Niha Sheikh
    • Validation
      Shakira Irfana, S. M. Riha Parvin, Niyaz Panakaje, Mahammad Shahid
    • Writing – original draft
      Shakira Irfana
    • Writing – review & editing
      Shakira Irfana, Mohammad Nihal, S. M. Riha Parvin, Niyaz Panakaje, Niha Sheikh, Madhura K., Mahammad Shahid
    • Resources
      Mohammad Nihal, Niha Sheikh, Madhura K., Mahammad Shahid
    • Formal Analysis
      S. M. Riha Parvin, Niyaz Panakaje
    • Visualization
      Niha Sheikh, Madhura K.