Close
Thesis: Understanding how heuristics and biases impact the effectiveness of decisions taken in major infrastructure projects
Name:
Mohamed H. Al-Ali
Supervisors:
Michael Emes
Raúl Leal Ascencio
Research Theme:
Abstract:
The decision-making process can be biased by virtue of the role that mental shortcuts play in human decision making. Although many researchers have studied this fact in form of psychological behaviours and behavioural economics, limited research has explored the role of heuristics and biases in the selection and definition of infrastructure projects.
Decision-making traps and psychological barriers, which is well known as "heuristics and biases", play an important role in the decision-making process. The commonly-used phrase “Heuristics” is mental shortcuts that occur in the human mind by which some parts of a complex problem is ignored as more focus is given to one aspect of the problem. As a result, some systematic errors might occur when making a decision. According to researchers, using quantitative decision analysis techniques, following structured analysis, and increasing the awareness of the psychological traps can help to avoid mental errors and improve taken decisions.
This research project seeks to highlight barriers to effective decision making in major infrastructure projects. Through multiple-criteria decision analysis, a series of decision-making experiments will be conducted to analyze the role of heuristics and biases in the selection and definition of infrastructure projects.
Biography:
Mohamed Al-Ali is a PhD candidate at University College London. He obtained his bachelor's degree in Industrial and Management System Engineering in Kuwait University. He also studied project management in accordance with the Project Management Institute (PMI) and obtained a trainer certification on project appraisal with the application of COMFAR software, which is accepted by the United Nations Industrial Development Organization. He attended several courses working with ArcGIS (Geographic Information System software). In addition, he obtained his master's degree from Kingston University - London in Engineering Project and Systems Management. His research interests include Decision making processes, financial assistance and economics analysis, and risk association.
Publications/academic works:
Mehmet Savsar and Mohamed H. Al-Ali (2017). Classification and Analysis of Hazardous Conditions and Near Misses by Using Fault Trees: A Case Application in Oil Industry. China-USA Business Review, 16(4).
Al-Ali, M. (2017). Implementing a combinational framework to accumulate the most efficient regional renewable energy technique: Aid the power of decision making of the future energy planning in UAE. 7th Annual Conference on Industrial Engineering and Operations Management.