Predictive Modelling of Career Preferences Among Generation Z Using Survey-Driven Career Decision Analytics

Authors

  • Mohammed Ameen CMS Business school, Bangalore Author
  • Ms. Amita Gupta Assistant Professor in practice Author

DOI:

https://doi.org/10.5281/zenodo.19948683

Keywords:

Generation Z, Career Preferences, Predictive Modelling, Career Decision Analytics, Machine Learning, Entrepreneurial Intention, Indian

Abstract

This study investigates the career preferences of Generation Z recent graduates in India through a survey-driven predictive modelling framework, addressing a significant gap in the existing literature on youth career decision analytics within the Indian context. The research focuses on three primary dimensions of career preference — industry and sector preferences, remote work and workplace flexibility orientations, and entrepreneurial inclination and career intention — among respondents aged 22 to 26 years. Primary data was collected from 154 Generation Z graduates across India through a structured self-administered online questionnaire. The data was analysed using descriptive statistics, Chi-Square hypothesis testing, and supervised machine learning classification algorithms — specifically Logistic Regression and Random Forest.

The findings reveal that Information Technology and Software is the most preferred industry sector, hybrid work arrangements are the dominant work preference, and entrepreneurially oriented career intentions account for 59.1% of respondents — with starting one's own business being the single most frequently expressed career intention. Among the four hypotheses tested, risk tolerance was identified as a statistically significant predictor of entrepreneurial career intention (χ² = 12.645, p = 0.027), consistent with the Theory of Planned Behaviour.

The Random Forest classifier outperformed Logistic Regression across all three predictive models, with entrepreneurial self-concept, age, career growth orientation, work experience, and educational qualification emerging as the most influential predictors of career intention. The study contributes theoretical extensions to Social Cognitive Career Theory, the Theory of Planned Behaviour, and Person-Environment Fit Theory, while offering actionable managerial implications for corporate recruiters, educational institutions, and policymakers engaged with the Indian Gen Z workforce.

Author Biography

  • Ms. Amita Gupta, Assistant Professor in practice

    Faculty of Management Studies, CMS Business School,

    JAIN (Deemed-to-be-University), Bangalore, Karnataka, India

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Published

2026-05-11

Issue

Section

Articles

How to Cite

Predictive Modelling of Career Preferences Among Generation Z Using Survey-Driven Career Decision Analytics. (2026). International Academic Research Journal of Business and Management, 14(1), 140-145. https://doi.org/10.5281/zenodo.19948683

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