My research, which has been my primary focus over the last three decades, is a testament to the interdisciplinary nature of the field. I apply decision-support systems to study human-centred automated software, a complex area that spans disciplines such as psychology, management science, operations research, and engineering design. This interdisciplinary approach allows me to examine social and economic processes by studying complex behaviour from relatively simple activities. I find this area to be highly challenging and rewarding, and I have published over 110 international research articles (including book chapters) in the scientific community, with research papers appearing in the ACM SIGMIS Database, Expert Systems with Applications, Decision Support Systems, and various conferences.

 

There are numerous application opportunities to utilise this approach for enhancing the modelling and analysis of human-centric operations, services, and socio-technical systems in fields such as software system design, policy and engineering artefact design criticism. In particular, my interest lies in hybrid knowledge-representation and reasoning schemes in automated decision support systems. There are many areas of application of knowledge where no single representation is adequate to express all that is known. Because successes (and the limitations) of the most popular representations have now become clear, there has been a growing interest in hybrid knowledge-based systems, where sub-symbolic schemes are not in question, probably the two representations that are receiving the most excellent attention are rules (as means of expressing generalisations) and cases (as means of stating particular knowledge, and casuistic) – in the factual sense of that world as understood before about 1650, rather than the pejorative sense that comes to mind first at the present day.