Investment Behaviour and Financial Decision-Making of Engineering Faculty: A Behavioural and Analytical Approach

Abstract

The investment decisions of salaried professionals, a group focused on both financial security and long-term wealth accumulation, have garnered significant attention in behavioral finance. Engineering faculty members constitute a distinct group of educated individuals whose financial choices are influenced by factors such as income stability, their perception of risk, their level of financial knowledge, and individual goals. Although they possess considerable technical skills, there has been a scarcity of studies investigating their investment strategies and financial planning approaches.

This research examines how engineering faculty make investment choices and financial decisions, employing both behavioural and analytical perspectives. The study delves into significant factors influencing these decisions, including individuals' willingness to take risks, their level of financial knowledge, anticipated returns, preferences for portfolio diversification, and their long-term financial objectives. Data was gathered through structured surveys administered at engineering institutions, and statistical and analytical methods were utilized to uncover the behavioural drivers behind the investment choices made by the participants.

The results will help to understand how cognitive biases, income patterns, and financial literacy levels determine the preferences of portfolio choices and strategic planning of faculty members. The study helps in a deeper understanding of professional investment habits in the academic community by integrating the behavioural finance theory and empirical studies. The findings can guide policymakers, financial advisors and institutional organizations in developing specific financial education and planning interventions among salaried professionals. In general, the study contributes to the existing body of literature on behavioural finance by targeting an area of the knowledge workforce that has been largely unexplored but has an important economic implication.