More of our publications

Quantifying apparently subjective topics

Many widely-used concepts, such as complexity and novelty, are difficult to describe rigorously, and often involve subjective value judgments. The papers below describe ways of using a rigorous formalism (graph theory) to quantify technological complexity and novelty in the archaeological record in a non-judgmental way.

Rugg, G. (2011) Quantifying technological innovation. PalaeoAnthropology Special Issue: Innovation and Hominin Evolution, pp 154-165

Rugg, G. & Holland, N.K. (2011) Quantifying Novelty in the Archaeological Record. PalaeoAnthropology Special Issue: Innovation and Hominin Evolution, pp 166-173

Studying organisational culture

These publications include methods for studying organisational culture, which has historically been viewed as a difficult topic to investigate in a way that is rigorous while giving an accurate account of reality. We used methods such as card sorts and laddering to tackle this problem.

Curran, M.J, Rugg, G. & Corr, S. (2005). Attitudes to expert systems: A card sort study. The Foot, 15, pp190-197

Rugg, G., Eva, M., Mahmood, A., Rehman, N., Andrews, S. & Davies, S. (2002). Eliciting information about organisational culture via laddering. Information Systems Journal, 12, pp. 215-229

Rugg, G. & Krumbholz, M. Determining culture for effective ERP installation. Proceedings of the EMRPS’99 workshop, Venice, 25-26 November, 1999.

The big picture

Rugg, G, Rigby, C, Gerrard, S, Martin, A, Skillen, J, Bonfiglio, E, Gardner, A, Guo, Y, Minocha, S, and Taylor, G. (2022). Knowledge Infrastructure. Proceedings of the 35th British HCI and Doctoral Consortium 2022, Keele, UK.

This paper describes a framework for systematically identifying which parts of a process should be handled by computers, and which by humans. This is important because handling knowledge is a major challenge. This paper provides a structured process for tackling problems involving knowledge, which computers are not able to handle well, as opposed to information/data, which computers handle much better than humans.