Coronavirus (Covid-19): Latest updates and information
Skip to main content Skip to navigation


An Approach to Computer-based Knowledge Representation for the Business Environment using Empirical Modelling

The motivation for the thesis arises from the difficulties experienced by business people who are non-programmers with the inflexibilities of conventional packages and tools for model-making. After a review of current business software an argument is made for the need for a new computing paradigm that would offer more support for the way that people actually experience their business activities. The Empirical Modelling (EM) approach is introduced as a broad theoretical and practical paradigm for computing that can be viewed as a far-reaching generalisation of the spreadsheet concept.

The concepts and principles of EM emphasise the experiential processes underlying familiar abstractions and by which we come to identify reliable components in everyday life and, in particular, business activities. The emphasis on experience and on interaction leads to the new claim that EM environments offer a framework for combining propositional, experiential and tacit knowledge in a way that is more accessible and supportive of cognitive processes than conventional computer-based modelling. It is proposed that such environments offer an alternative kind of knowledge representation. Turning to the implementation and development of systems, the difficulties inherent in conventional methods are discussed and then the practical aspects of EM, and its potential for system building, are outlined.

Finally, a more detailed study is made of Decision Support Systems and the ways in which the EM focus on experience, and knowledge through interaction, can contribute to the representation of qualitative aspects of business activities and their use in a more human-centred, but computer-supported, process of decision making. Illustrations of the practical application of EM methods to the requirements of a decision support environment are given by means of extracts from a number of existing EM models.