https://gaexcellence.com/ijcrei/issue/feed 2026-04-29T10:56:28+08:00 Open Journal Systems <p>The <strong>International Journal of Creative Industries (IJCREI)</strong> is published by <strong>Global Academic Excellence (M) Sdn Bhd (GAE)</strong> to serve academicians a platform of sharing and updating their knowledge and research outputs as well as information within the sphere of creative industries. <strong>IJCREI </strong>invites researchers, academicians, practitioners and students for the submission of articles either in English or Malay. The publication for this refereed journal are<strong> quarterly (March, June, September and December).</strong> This journal uses <strong>double</strong>-<strong>blind review</strong>, which means that both the <strong>reviewer</strong> and <strong>author identities</strong> are concealed from the reviewers, and vice versa, throughout the review process. To facilitate this, authors need to ensure that their manuscripts are prepared in a way that does not give away their identity.</p> https://gaexcellence.com/ijcrei/article/view/7494 2026-04-29T10:56:28+08:00 Mohd Arif Yusoff ariflunda4@gmail.com Ahmad Azaini Abdul Manaf azaini.am@umk.edu.my

<p style="text-align: justify;">This study investigates the limitations of existing static models in explaining career development within digitally mediated creative industries. In the contemporary creative economy, career trajectories are increasingly shaped by platform-driven ecosystems, iterative participation, and continuous technological adaptation. However, dominant frameworks such as the Technology Readiness Index (TRI) and the Unified Theory of Acceptance and Use of Technology (UTAUT) remain grounded in cross-sectional and temporally stable assumptions, creating theoretical misalignment in explaining dynamic career formation. To address this gap, this study develops and empirically validates the Time-Varying Ecosystem Model of Technology Readiness, Interest Development, and Career Alignment (TVEM-TRICA). A longitudinal quantitative research design involving three waves of data collection (T1–T3) was employed. Data were analysed using cross-lagged panel modelling, latent growth modelling, and structural equation modelling (SEM) to capture reciprocal and time-dependent relationships among constructs. The findings reveal a dynamic reconfiguration of causal influence, where technology readiness significantly shapes early-stage interest (β = 0.41, p &lt; 0.001) but diminishes over time, while interest progressively becomes the dominant predictor of career alignment (β = 0.47, p &lt; 0.001). UTAUT constructs demonstrate declining influence across temporal stages, whereas ecosystem factors significantly moderate and mediate key relationships. This study contributes theoretically by shifting the analytical paradigm from static variance explanation to time-dependent process modelling. Practically, the proposed model offers implications for adaptive policy design, curriculum innovation, and sustainable talent development in digitally mediated creative economies.</p> <p style="text-align: justify;">&nbsp;</p>

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