The Poverty of Empiricism
Mende, Jens, Informing Science: the International Journal of an Emerging Transdiscipline
There is a world of difference between the terms 'empirical' and 'empiricism'. The term 'empirical' refers to a battery of very useful research methods. The term 'empiricism' refers to a restrictive methodological doctrine which claims that researchers may only use empirical methods. The purpose of this paper is not to disparage empirical research methods, but to warn readers that the empiricist doctrine impoverishes any discipline where it is deeply entrenched (Gower, 1997, p10), and to suggest some avenues of counteraction.
The subsequent sections explain why the empiricist doctrine impoverishes research. The first section shows that researchers need knowledge of various kinds of research processes and knowledge products, and that this knowledge is distributed over three academic disciplines: Philosophy of Science, History of Science and Research Methodology. The next three sections examine the origin and current status of the empiricist doctrine in the Philosophy of Science, and the debilitating effect of empiricism on research process and product knowledge in the History of Science and in Research Methodology. The last section calls for counter-action in the form of meta-research aimed at identifying non-empirical research processes and knowledge products that could be mentioned in those three disciplines especially in Research Methodology.
As the argument in those sections is lengthy, no space is left over for detailed analysis of the impact of the empiricist doctrine on the Information Systems discipline, nor on any of the other disciplines under the umbrella of Informing Science. Readers are invited to judge by themselves, from their personal experience, whether those disciplines are dominated by the empiricist doctrine, and whether that doctrine has impoverished them.
Research is a process of producing new knowledge. So it is a productive process similar to the productive processes of manufacturing cars, computers, software, etc. Some useful insights emerge by analysing the other productive processes and then comparing them with the research process.
All productive processes require productive knowledge. For example:
* in order to produce cars, people need knowledge of car production;
* in order to produce computers, they need knowledge of computer production;
* in order to produce software, they need knowledge of software production.
Productive knowledge consists of process knowledge as well as product knowledge (see Mende, 2000 for more detail). When manufacturers establish a new factory, they have to decide what the factory is to produce, and how the factory will produce it. So they need to know what kinds of manufactured products are needed, and what kinds of processes can be used to produce them. For example, when Henry Ford decided to produce motor cars, he had to know that people need cars, and that cars can be produced on a production line.
Similarly, when researchers embark on a research project, they have to decide what knowledge product to produce and how to produce it. So they too need to know what kinds of knowledge products are required and what kinds of research processes can be used (Kantorovich, 1993, p11; Singleton, Straits & Straits, 1993, p18). For example, when Ohm embarked on his famous research project to find the empirical law of electric current variation with voltage, he had to be aware that people need empirical laws, and that empirical laws can be produced by means of inductive research processes. Similarly, when Darwin embarked on his famous research project on the theory of evolution, he had to be aware that people need theories, and that theories can be established by means of deductive research processes.
Therefore, by analogy with manufacturing management, researchers need knowledge of different types of research processes and knowledge products. …