Project Description

Life would be much easier if organisations had a 3D map of the business landscape showing owners and entrepreneurs where best to go, how much they could benefit when they get there, as well as how much it would cost them along the way. Just as astronomers find out about our Universe by looking at lots of stars, and in different wavelengths, we are looking at lots of organisations and using metrics that are different to the ones that are normally visible. To do this we need to have a lot of information, this is called a “Big Data” approach. Unfortunately the metrics that are available in the UK, such as company annual returns, don’t tell us a lot. Indeed our previous research indicates that some important factors can be quite basic, e.g. the number of employees each year within an organisation, and these figures are simply not collected centrally in the UK. Thus we have teamed up with several international partners to obtain Big Data. Feeding this information into the computer model that we have developed in the UK, we can produce not only a user-friendly and very practical 3D map of the “Business Universe”, but also academically to reveal hidden insights into how humans cluster in organisations and indeed how clusters cluster. This approach is very relevant not only to consultants, owners, entrepreneurs and academics, but also to everyone who has a job. The proposed research involves:

(1) How do economic laws determine the development and shape of organisations?
(2) When organisations cluster in e.g. tech hubs or science parks, what is the best shape for them to organise their structure into, and
(3) Create a computer model for business clusters feasibility; what metric(s) can be used to stipulate the distance between clusters and how do age, size and stage in the maturity cycle affect this distance?

Funding Information

This is a self funded project, there is no funding attached to it.

References

Further reading:
Mellor, R. B. (2015) Modelling the value of external networks for knowledge realisation, innovation, organisational development and efficiency. International Journal of KnowledgeBased Development, 6, 3­14.
Mellor, R. B. (2014) The use of knowledge assets: Modelling the potential effect of adding innovators to low­innovation and high­innovation SMEs. International Journal of Knowledge­Based Development, 5, 367­380.
Mellor, R. B. (2014) Knowledge valley theory. International Journal of Knowledge­Based Development, 5, 5­16.
Mellor, R. B. (2011) Knowledge management and information systems: Strategy for growing organizations. Basingstoke, Palgrave.