Decision-Making

Incorporating Qualitative Support in Investment DSS

Gokul Bhandari & Khaled Hassanein

Background

Due to recent innovations in the financial industry, the advent of the web and the proliferation of inexpensive personal computers, individuals are getting unparalleled opportunities for investment. However, they face two critical problems: (i) a difficulty in finding the right investment instruments due to the enormous complexity of financial markets; and (ii) an increasing vulnerability to a vast amount of potentially biased and unsubstantiated information from the web. Both of these problems are exacerbated by individuals’ psychology often leading to flawed investment decisions.

Despite the significant role of psychology in investment decision-making, the emphasis of current DSS is still on providing quantitative support to investors. The fact that psychological support is becoming increasingly critical to investors underscores the importance of incorporating such support in investment DSS. This research is, therefore, guided by the following objectives:

  • Propose a framework of investment decision-making
  • Based on the proposed framework, suggest a comprehensive taxonomy for judgment biases and explore how they influence investment decision-making.
  • Based on the proposed taxonomy and findings of the empirical study, suggest an architecture for developing a human-centered investment DSS.
  • Develop a prototype DSS and conduct an empirical study investigating its effectiveness in lowering the impact of psychological biases.
  • Develop a theoretical model for factors contributing to investor satisfaction with such a DSS and empirically validate this model.

Potential Benefits to a Sponsoring Organization

An organization can benefit from sponsoring this research by:

  • Understanding different factors that can influence an individual’s investment decision process.
  • Obtaining an integrated framework of solutions that can assist an individual investor in making the optimal decision.
  • Potentially building and marketing software application based on the research.

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